definition of hypothesis in genetics

Hypothesis n., plural: hypotheses [/haɪˈpɑːθəsɪs/] Definition: Testable scientific prediction

Table of Contents

What Is Hypothesis?

A scientific hypothesis is a foundational element of the scientific method . It’s a testable statement proposing a potential explanation for natural phenomena. The term hypothesis means “little theory” . A hypothesis is a short statement that can be tested and gives a possible reason for a phenomenon or a possible link between two variables . In the setting of scientific research, a hypothesis is a tentative explanation or statement that can be proven wrong and is used to guide experiments and empirical research.

It is an important part of the scientific method because it gives a basis for planning tests, gathering data, and judging evidence to see if it is true and could help us understand how natural things work. Several hypotheses can be tested in the real world, and the results of careful and systematic observation and analysis can be used to support, reject, or improve them.

Researchers and scientists often use the word hypothesis to refer to this educated guess . These hypotheses are firmly established based on scientific principles and the rigorous testing of new technology and experiments .

For example, in astrophysics, the Big Bang Theory is a working hypothesis that explains the origins of the universe and considers it as a natural phenomenon. It is among the most prominent scientific hypotheses in the field.

“The scientific method: steps, terms, and examples” by Scishow:

Biology definition: A hypothesis  is a supposition or tentative explanation for (a group of) phenomena, (a set of) facts, or a scientific inquiry that may be tested, verified or answered by further investigation or methodological experiment. It is like a scientific guess . It’s an idea or prediction that scientists make before they do experiments. They use it to guess what might happen and then test it to see if they were right. It’s like a smart guess that helps them learn new things. A scientific hypothesis that has been verified through scientific experiment and research may well be considered a scientific theory .

Etymology: The word “hypothesis” comes from the Greek word “hupothesis,” which means “a basis” or “a supposition.” It combines “hupo” (under) and “thesis” (placing). Synonym: proposition; assumption; conjecture; postulate Compare:   theory See also: null hypothesis

Characteristics Of Hypothesis

A useful hypothesis must have the following qualities:

It should never be written as a question.
You should be able to test it in the real world to see if it’s right or wrong.
It needs to be clear and exact.
It should list the factors that will be used to figure out the relationship.
It should only talk about one thing. You can make a theory in either a descriptive or form of relationship.
It shouldn’t go against any natural rule that everyone knows is true. Verification will be done well with the tools and methods that are available.
It should be written in as simple a way as possible so that everyone can understand it.
It must explain what happened to make an answer necessary.
It should be testable in a fair amount of time.
It shouldn’t say different things.

Sources Of Hypothesis

Sources of hypothesis are:

Patterns of similarity between the phenomenon under investigation and existing hypotheses.
Insights derived from prior research, concurrent observations, and insights from opposing perspectives.
The formulations are derived from accepted scientific theories and proposed by researchers.
In research, it’s essential to consider hypothesis as different subject areas may require various hypotheses (plural form of hypothesis). Researchers also establish a significance level to determine the strength of evidence supporting a hypothesis.
Individual cognitive processes also contribute to the formation of hypotheses.

One hypothesis is a tentative explanation for an observation or phenomenon. It is based on prior knowledge and understanding of the world, and it can be tested by gathering and analyzing data. Observed facts are the data that are collected to test a hypothesis. They can support or refute the hypothesis.

For example, the hypothesis that “eating more fruits and vegetables will improve your health” can be tested by gathering data on the health of people who eat different amounts of fruits and vegetables. If the people who eat more fruits and vegetables are healthier than those who eat less fruits and vegetables, then the hypothesis is supported.

Hypotheses are essential for scientific inquiry. They help scientists to focus their research, to design experiments, and to interpret their results. They are also essential for the development of scientific theories.

Types Of Hypothesis

In research, you typically encounter two types of hypothesis: the alternative hypothesis (which proposes a relationship between variables) and the null hypothesis (which suggests no relationship).

Simple Hypothesis

It illustrates the association between one dependent variable and one independent variable. For instance, if you consume more vegetables, you will lose weight more quickly. Here, increasing vegetable consumption is the independent variable, while weight loss is the dependent variable.

Complex Hypothesis

It exhibits the relationship between at least two dependent variables and at least two independent variables. Eating more vegetables and fruits results in weight loss, radiant skin, and a decreased risk of numerous diseases, including heart disease.

Directional Hypothesis

It shows that a researcher wants to reach a certain goal. The way the factors are related can also tell us about their nature. For example, four-year-old children who eat well over a time of five years have a higher IQ than children who don’t eat well. This shows what happened and how it happened.

Non-directional Hypothesis

When there is no theory involved, it is used. It is a statement that there is a connection between two variables, but it doesn’t say what that relationship is or which way it goes.

Null Hypothesis

It says something that goes against the theory. It’s a statement that says something is not true, and there is no link between the independent and dependent factors. “H 0 ” represents the null hypothesis.

Associative and Causal Hypothesis

When a change in one variable causes a change in the other variable, this is called the associative hypothesis . The causal hypothesis, on the other hand, says that there is a cause-and-effect relationship between two or more factors.

Examples Of Hypothesis

Examples of simple hypotheses:

Students who consume breakfast before taking a math test will have a better overall performance than students who do not consume breakfast.
Students who experience test anxiety before an English examination will get lower scores than students who do not experience test anxiety.
Motorists who talk on the phone while driving will be more likely to make errors on a driving course than those who do not talk on the phone, is a statement that suggests that drivers who talk on the phone while driving are more likely to make mistakes.

Examples of a complex hypothesis:

Individuals who consume a lot of sugar and don’t get much exercise are at an increased risk of developing depression.
Younger people who are routinely exposed to green, outdoor areas have better subjective well-being than older adults who have limited exposure to green spaces, according to a new study.
Increased levels of air pollution led to higher rates of respiratory illnesses, which in turn resulted in increased costs for healthcare for the affected communities.

Examples of Directional Hypothesis:

The crop yield will go up a lot if the amount of fertilizer is increased.
Patients who have surgery and are exposed to more stress will need more time to get better.
Increasing the frequency of brand advertising on social media will lead to a significant increase in brand awareness among the target audience.

Examples of Non-Directional Hypothesis (or Two-Tailed Hypothesis):

The test scores of two groups of students are very different from each other.
There is a link between gender and being happy at work.
There is a correlation between the amount of caffeine an individual consumes and the speed with which they react.

Examples of a null hypothesis:

Children who receive a new reading intervention will have scores that are different than students who do not receive the intervention.
The results of a memory recall test will not reveal any significant gap in performance between children and adults.
There is not a significant relationship between the number of hours spent playing video games and academic performance.

Examples of Associative Hypothesis:

There is a link between how many hours you spend studying and how well you do in school.
Drinking sugary drinks is bad for your health as a whole.
There is an association between socioeconomic status and access to quality healthcare services in urban neighborhoods.

Functions Of Hypothesis

The research issue can be understood better with the help of a hypothesis, which is why developing one is crucial. The following are some of the specific roles that a hypothesis plays: (Rashid, Apr 20, 2022)

A hypothesis gives a study a point of concentration. It enlightens us as to the specific characteristics of a study subject we need to look into.
It instructs us on what data to acquire as well as what data we should not collect, giving the study a focal point .
The development of a hypothesis improves objectivity since it enables the establishment of a focal point.
A hypothesis makes it possible for us to contribute to the development of the theory. Because of this, we are in a position to definitively determine what is true and what is untrue .

How will Hypothesis help in the Scientific Method?

The scientific method begins with observation and inquiry about the natural world when formulating research questions. Researchers can refine their observations and queries into specific, testable research questions with the aid of hypothesis. They provide an investigation with a focused starting point.
Hypothesis generate specific predictions regarding the expected outcomes of experiments or observations. These forecasts are founded on the researcher’s current knowledge of the subject. They elucidate what researchers anticipate observing if the hypothesis is true.
Hypothesis direct the design of experiments and data collection techniques. Researchers can use them to determine which variables to measure or manipulate, which data to obtain, and how to conduct systematic and controlled research.
Following the formulation of a hypothesis and the design of an experiment, researchers collect data through observation, measurement, or experimentation. The collected data is used to verify the hypothesis’s predictions.
Hypothesis establish the criteria for evaluating experiment results. The observed data are compared to the predictions generated by the hypothesis. This analysis helps determine whether empirical evidence supports or refutes the hypothesis.
The results of experiments or observations are used to derive conclusions regarding the hypothesis. If the data support the predictions, then the hypothesis is supported. If this is not the case, the hypothesis may be revised or rejected, leading to the formulation of new queries and hypothesis.
The scientific approach is iterative, resulting in new hypothesis and research issues from previous trials. This cycle of hypothesis generation, testing, and refining drives scientific progress.

Importance Of Hypothesis

Hypothesis are testable statements that enable scientists to determine if their predictions are accurate. This assessment is essential to the scientific method, which is based on empirical evidence.
Hypothesis serve as the foundation for designing experiments or data collection techniques. They can be used by researchers to develop protocols and procedures that will produce meaningful results.
Hypothesis hold scientists accountable for their assertions. They establish expectations for what the research should reveal and enable others to assess the validity of the findings.
Hypothesis aid in identifying the most important variables of a study. The variables can then be measured, manipulated, or analyzed to determine their relationships.
Hypothesis assist researchers in allocating their resources efficiently. They ensure that time, money, and effort are spent investigating specific concerns, as opposed to exploring random concepts.
Testing hypothesis contribute to the scientific body of knowledge. Whether or not a hypothesis is supported, the results contribute to our understanding of a phenomenon.
Hypothesis can result in the creation of theories. When supported by substantive evidence, hypothesis can serve as the foundation for larger theoretical frameworks that explain complex phenomena.
Beyond scientific research, hypothesis play a role in the solution of problems in a variety of domains. They enable professionals to make educated assumptions about the causes of problems and to devise solutions.

Research Hypotheses: Did you know that a hypothesis refers to an educated guess or prediction about the outcome of a research study?

It’s like a roadmap guiding researchers towards their destination of knowledge. Just like a compass points north, a well-crafted hypothesis points the way to valuable discoveries in the world of science and inquiry.

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The Evolving Definition of the Term “Gene”

Petter portin.

* Laboratory of Genetics, Department of Biology, University of Turku, 20014, Finland

Adam Wilkins

† Institute of Theoretical Biology, Humboldt Universität zu Berlin, 10115, Germany

This paper presents a history of the changing meanings of the term “gene,” over more than a century, and a discussion of why this word, so crucial to genetics, needs redefinition today. In this account, the first two phases of 20th century genetics are designated the “classical” and the “neoclassical” periods, and the current molecular-genetic era the “modern period.” While the first two stages generated increasing clarity about the nature of the gene, the present period features complexity and confusion. Initially, the term “gene” was coined to denote an abstract “unit of inheritance,” to which no specific material attributes were assigned. As the classical and neoclassical periods unfolded, the term became more concrete, first as a dimensionless point on a chromosome, then as a linear segment within a chromosome, and finally as a linear segment in the DNA molecule that encodes a polypeptide chain. This last definition, from the early 1960s, remains the one employed today, but developments since the 1970s have undermined its generality. Indeed, they raise questions about both the utility of the concept of a basic “unit of inheritance” and the long implicit belief that genes are autonomous agents. Here, we review findings that have made the classic molecular definition obsolete and propose a new one based on contemporary knowledge.

IN 1866, Gregor Mendel, a Moravian scientist and Augustinian friar, working in what is today the Czech Republic, laid the foundations of modern genetics with his landmark studies of heredity in the garden pea ( Pisum sativum ) ( Mendel 1866 ). Though he did not speak of “genes”—a term that first appeared decades later—but rather of elements , and even “cell elements” (original German Zellelemente p. 42), it is clear that Mendel was hypothesizing the hereditary behavior of miniscule hidden factors or determinants underlying the stably inherited visible characteristics of an organism, which today we would call genes. This is apparent throughout his publication in his use of abstract letter symbols for hereditary determinants to denote the physical factors underlying the inheritance of characteristics. There is no doubt that he considered the mediators of heredity to be material entities, though he made no conjectures about their nature.

The word “gene” was not coined until early in the 20th century, by the Danish botanist Johannsen (1909) , but it rapidly became fundamental to the then new science of genetics, and eventually to all of biology. Its meaning, however, has been evolving since its birth. In the beginning, the concept was used as a mere abstraction. Indeed, Johannsen thought of the gene as some form of calculating element (a point to which we will return), but deliberately refrained from speculating about its physical attributes ( Johannsen 1909 ). By the second decade of the 20th century, however, a number of genes had been localized to specific positions on specific chromosomes, and could, at least, be treated, if not thought of precisely, as dimensionless points on chromosomes. Furthermore, groups of genes that showed some degree of coinheritance could be placed in “linkage groups,” which were the epistemic equivalent of the cytological chromosome. We term this phase the “classical period” of genetics. By the early 1940s, certain genes had been shown to have internal structure, and to be dissectable by genetic recombination; thus, the gene, at this point, had conceptually acquired a single dimension, length. Twenty years later, by the early 1960s, the gene had achieved what seemed like a definitive physical identity as a discrete sequence on a DNA molecule that encodes a polypeptide chain. At this point, the gene had a visualizable three-dimensional structure as a particular kind of molecule. We will call this period—from roughly the end of the 1930s to the early 1960s—the “neoclassical period.”

The 1960s definition of the gene is the one most geneticists employ today, but it is clearly out-of-date for deoxyribonucleic acid (DNA)-based organisms. (We will deal only with the latter; RNA viruses and their genes will not be discussed.) Here, we review the older history of the terminology, and then the findings from the 1970s onwards that have undermined the generality of the 1960s definition. We will then propose a contemporary definition of the “gene” that accounts for the complexities revealed in recent decades. This publication is a follow-on paper to an earlier paper by one of us ( Portin 2015 ).

The Classical Period of Genetics

The development of modern genetics began in 1900, when three botanists—the German Carl Correns, the Dutchman Hugo de Vries, and the Austrian Erich von Tschermak—independently cited and discussed the experiments of Mendel as basic to understanding the nature of heredity. They presented results similar to Mendel’s though using different plants as experimental material ( Correns 1900 ; de Vries 1900 ; Tschermak 1900 ). Their conceptual contributions as “rediscoverers” of Mendel, however, were probably not equivalent. De Vries and Correns claimed that they had discovered the essential facts and developed their interpretation before they found Mendel’s article, and they demonstrated that they fully understood the essential aspects of Mendel’s theory ( Stern 1970 ). In contrast, Tschermak’s analysis of his own data was inadequate, and his paper lacked an interpretation. Thus, while he sensed the significance of Mendel’s work, Tschermak should not be given credit equal to that due to de Vries and Correns.

In 1900, chromosomes were already known, and they were soon seen to provide a concrete basis for Mendel’s abstract hereditary factors. This postulated connection between genes and chromosomes, which later came to be known as the chromosome theory of inheritance, was initially provided by the German biologist T. H. Boveri and the American geneticist and physician W. S. Sutton during the years 1902–1903. Boveri first demonstrated the individuality of chromosomes with microscopic observations on the sea urchin Paracentrotus lividus ( Boveri 1902 ). He went on to demonstrate the continuity of chromosomes through cell divisions with studies of Ascaris megalocephala , a parasitic nematode worm ( Boveri 1903 ). These two characteristics—individuality and continuity—are necessary, although not sufficient, characteristics of the genetic material. Sutton’s contribution ( Sutton 1903 ), on the basis of his studies on the spermatogenesis of Brachystola magna , a large grasshopper, was to demonstrate a clear equivalence between the behavior of chromosomes at the meiotic divisions and Mendel’s postulated separation and independent inheritance of character differences at gamete formation. Thus, this early version of the chromosome theory of inheritance suggests an explanation for Mendel’s laws of inheritance: the law of segregation and the law of independent assortment. It was not until 1916, however, that it could be considered to be proven. In that year, C. B. Bridges, an American geneticist, showed in Drosophila melanogaster that nondisjunction, a rare exceptional behavior of genetic makers (lack of segregation) during gamete formation, was always associated with an analogous exceptional behavior of a given chromosome pair during meiosis ( Bridges 1916 ).

Shortly after the birth of the chromosome theory, however, a new phenomenon had been discovered that appeared to contradict Mendel’s law of independent assortment. This was the phenomenon of linkage, initially found in the sweet pea ( Lathyrus odoratus ), in which some genes were found to exhibit “coupling,” violating independent assortment ( Bateson et al. 1905a , b ). This exception to the rule, however, became the basis of an essential extension of the chromosome theory when it was realized that genes showing linkage are located on the same chromosome, and genes showing independent assortment are located on different chromosomes.

According to the canonical history of genetics, it was the American geneticist T. H. Morgan who was the first to propose in 1910 this extension of the chromosome theory ( Morgan 1910 , 1917 ). Recent studies on the history of genetics ( Edwards 2013 ), however, show that, most likely, Morgan was influenced by the first textbook of genetics in English written by R. H. Lock, a British botanist associated with Bateson and Punnet, published in 1906, where the possibility that linkage might result from genes lying on the same chromosome was first suggested ( Lock 1906 ). Thus, it is Lock to whom the credit of explaining linkage must be given.

It was soon understood that genes sufficiently far apart on the chromosome can also show independent assortment, due to extensive genetic recombination during meiosis, while genes that are closer to each other show a degree of coinheritance, the frequency of their separation by recombination being directly related to the distance between them. Owing to the work of Morgan and his group on the fruit fly ( D. melanogaster ), the phenomenon of linkage and its breakdown via crossing over became the essential basis for the mapping of genes ( Morgan 1919 , 1926 ; Morgan et al. 1915 ). The first map, of the Drosophila X-chromosome, was constructed by Alfred Sturtevant, one of Morgan’s students ( Sturtevant 1913 ). The linear sequence of genes he diagrammed was the abstract genetic epistemic equivalent of the chromosome itself.

The genetic maps of the linkage groups were subsequently followed by cytological maps of the chromosomes. These were first constructed by showing that X-ray-induced changes of the order of the genes in the linkage groups, such as translocations and deletions, were associated with corresponding changes in the structure of chromosomes ( Dobzhansky 1929 ; Muller and Painter 1929 ; Painter and Muller 1929 ). This was followed by detailed cytological mapping of genes, made possible by the existence of the “giant” chromosomes of the salivary glands of the fruit fly, in which genes identified by their inheritance patterns could be localized to specific (visible) locations on chromosomes ( Painter 1934 ; Bridges 1935 , 1938 ).

Morgan conceived the cytological explanation for the genetical phenomenon of crossing over by adopting the chiasmatype theory of Frans Alfons Jannsens, a Belgian cytologist, that was based on his observations of meiosis at spermatogenesis in the salamander Batrachoseps attenuatis ( Janssens 1909 ; see also Koszul et al. 2012 ). Janssens observed cross figures at synapsis in meiotic chromosome preparations of this amphibian that resembled the Greek letter chi (χ). Accordingly, he called such a junction “chiasma” (pl. chiasmata). Janssens interpreted each of these as due to fusion at one point between two of the four strands of the tetrad of chromatids at the pachytene stage of the meiotic prophase. According to the chiasmatype theory, chiasmata were due to breakage and reunion of one maternal and one paternal chromatid of the tetrad. Consequently, the formation of each chiasma leads to an exchange of equal and corresponding regions of two of the four chromatids. This mechanism of exchange provided the needed physical explanation for the partial genetic linkage of genes that Morgan had observed. In other words, chiasmata are cytological counterparts of the genetical crossover points.

An alternative explanation for the origin of chiasmata was the so called classical hypothesis, which did not require breakage and rejoining of chromosomes, but assumed that chiasmata were simply a result of the paternal and maternal chromatids going across each other, forming a cross-like configuration at the pachytene stage of meiosis ( McClung 1927 ; Sax 1932a , b ). This hypothesis did not explain the phenomenon of genetic recombination, but was preferred by most cytologists of that time because it did not threaten the permanence and individuality of the chromosomes, which the chiasmatype theory initially seemed to do. During subsequent years, many cytological facts, as reviewed, for example, in Whitehouse (1973) , supported the chiasmatype theory, but not the classical theory.

Thus, by the early 1930s, the concept of the gene had become more concrete. Genes were regarded as indivisible units of inheritance, each located at a specific point on a specific chromosome. Furthermore, they could be defined in terms of their behavior as fundamental units on the basis of four criteria: (1) hereditary transmission, (2) genetic recombination, (3) mutation, and (4) gene function. Moreover, it was believed, albeit without any empirical evidence, that these four ways of defining the gene fully agreed with one another (reviewed in Portin 1993 ; Keller 2000 ). As A. Sturtevant and G. W. Beadle wrote in (1939), near the end of what we are calling the classical period of genetics, it was also clear that genes determine the nature of developmental reactions and thus, ultimately, the visible traits they generate. But how genes do these things was unknown; indeed, that was considered one of the major unsolved problems in biology, and it remained so for two decades ( Sturtevant and Beadle 1962 , p. 335). Further, it was believed that the integration of genetics with such fields as biochemistry, developmental physiology, and experimental embryology would lead to a deep understanding of the nature and role of genes, and that this integration would add to our understanding of those processes that make up development ( Sturtevant and Beadle 1962 , p. 357; see also Sturtevant 1965 ).

The significance of this perspective was initially elaborated by H. J. Muller, an American geneticist and a student of Morgan’s, who had done important work on several key aspects of the subject: the mapping of genes ( Muller 1920 ), the relation between genes and characteristics of organisms ( Muller 1922 ), and the nature of gene mutation ( Muller 1927 ; also see Carlson 1966 ). In his classic paper dealing with the effect of changes in individual genes on the variation of the organism, Muller (1922 ) published arguments that can be viewed as a theoretical summary of the essence of the classical period of genetics. On the basis of a considerable body of earlier work, he put forward an influential theory that genes are molecules with three essential capacities: autocatalysis (self-reproduction), heterocatalysis (production of nongenetic material or effects), and ability to mutate (while retaining the first two properties). In this view, genes were undoubted physical entities, three-dimensional ultramicroscopic ones, possessing individuated heritable structures, with some capacity for change that itself could be passed on.

In another visionary paper, Muller (1926) connected the concept of the gene to the theory of evolution, while he described the gene as the basis of evolution and the origin of life itself, indeed as the basis of life itself. These profound views of Muller strongly influenced the direction of much future research, not only in genetics, but in biology as a whole ( Carlson 1966 p. 82).

The Neoclassical Period of Genetics

Whatever the speculations of Muller and a few others, the classical period of genetics was one in which the gene could be treated effectively as a dimensionless point on a chromosome. It was followed, however, by what we are calling the neoclassical period, in which the gene first acquired an unambiguous spatial dimension, namely length, and later a likewise linear chemical identity, in the form of the DNA molecule. This period of genetics involved two different, but complementary, research programs: on the one hand, it was demonstrated, using the classic genetic tool of recombinational mapping, that genes have an internal structure; on the other hand, the basic molecular nature of the gene and its function began to be revealed. These two streams fused in the late 1950s.

The neoclassical period began in the early 1940s, with work in formal genetics showing that genes could be dissected into contiguous segments by genetic recombination. Hence, they were not dimensionless points but entities with length. These observations were made first in D. melanogaster ( Oliver 1940 ; Lewis 1941 ; 1945 ; Green and Green 1949 ), and then in microbial fungi ( Bonner 1950 ; Giles 1952 ; Pontecorvo 1952 ; Pritchard 1955 ).

If genes had length, however, they must be long molecules of some sort, and the question was whether those molecules were proteins or DNA, the two major molecular constituents of the chromosomes. Critically important work in the early 1940s, in the laboratory of Oswald Avery at Rockefeller University, answered the question. Avery and his colleagues showed that DNA is the hereditary material by demonstrating that the causative agent in bacterial transformation, which entailed a heritable change in the morphology of the bacterial cells ( Griffith 1928 ), was DNA ( Avery et al. 1944 ). Though this work was published in 1944, it would take nearly a decade for this to become universally accepted. The experimental proof that convinced the scientific community was the experiment of Hershey and Chase (1952) , in which these authors showed that the DNA component of bacteriophages was the one responsible for their multiplication.

The most critical and final breakthrough for the DNA theory of inheritance, however, was the revelation of the double-helical structure of DNA ( Watson and Crick 1953a , 1954 ), and the realization of the genetic implications of that ( Watson and Crick 1953b ). This was followed by demonstrations in the early 1960s that genes are first transcribed into messenger RNA (mRNA), which transmitted the genetic information from the nucleus to the protein synthesis machinery in the cytoplasm (reviewed in Portin 1993 ; Judson 1996 ). Earlier work in the 1940s had established the connection between genes and proteins, in the “one gene-one enzyme” hypothesis of Beadle and Tatum (1941) (see also Srb and Horowitz 1944 ; reviewed in Strauss 2016 ). By the late 1950s, there was thus a satisfying molecular theory of both the nature of the gene, and the connections between genes and proteins.

Crucial further work involved the genetic fine structure mapping of genes—a research program that reached its culmination with work by S. Benzer and C. Yanofsky. Benzer, using the operational cis -trans test, originated by E. B. Lewis in Drosophila , defined the unit of genetic complementation, i.e. , the basic unit of gene function, which he called the cistron ( Box 1 ). He also defined the smallest units of genetic recombination and gene mutation: the recon and muton, respectively ( Benzer 1955 , 1959 , 1961 ). The postulate of the classical period that the gene was a fundamental unit not only of function, but also of recombination and mutation, was definitively disproved by Benzer’s work showing that the “gene” had many mutons and recons. Yanofsky and his coworkers validated the material counterparts of these formal concepts of Benzer. The equivalent of the cistron is a sequence of nucleotide pairs in DNA that contain information for the synthesis of a polypeptide, and determines its amino acid sequences, an idea known as the colinearity hypothesis. Furthermore, the physical DNA equivalent of the recon and the muton was shown to be one nucleotide pair ( Crawford and Yanofsky 1958 ; Yanofsky and Crawford 1959 ; Yanofsky et al. 1964 , 1967 ). The period of neoclassical genetics culminated in the cracking of the universal genetic code by several teams, revealing that nucleotide sequences specify the sequence of polypeptide chains (reviewed in Ycas 1969 ; Judson 1996 ).

The neoclassical concept of the gene, outlined above, can be summarized in the formulation “one gene—one mRNA—one polypeptide,” which combines the idea of mRNA, as developed by Jacob and Monod (1961a) ; Gros et al. (1961) ; Brenner et al. (1961) , and the earlier “one gene—one enzyme” hypothesis of Beadle and Tatum (1941) (and see Srb and Horowitz 1944 ). Another version of this hypothesis is that of “one cistron—one polypeptide” ( Crick 1963 ), which emerged as a slogan in the 1960s–1980s. Altogether, the conceptual journey from Johannsen’s totally abstract entities termed “genes” to a defined, molecular idea of what a gene is, and how it works, had taken a little over half a century.

The Breakdown of the Neoclassical Concept of the Gene and the Beginning of the Modern Period of Genetics

Deviations from the one gene—one mrna—one polypeptide hypothesis.

The hypothesis of “one gene—one mRNA—one polypeptide” as a general description of the gene and how it works started to expire, however, when it was realized that a single gene could produce more than one mRNA, and that one gene can be a part of several transcription units. This one-to-several relationship of genes to mRNAs occurs by means of complex promoters and/or alternative splicing of the primary transcript.

Multiple transcription initiation sites, i.e. , alternative promoters, have been found in all kingdoms of organisms, and they have been classified into six classes ( Schibler and Sierra 1987 ). All of them can produce transcripts that do not obey the rule of one-to-one correspondence between the gene and the transcription unit, since transcription can be initiated at different promoters. The result is that a single gene can produce more than one kind of transcript ( Schibler and Sierra 1987 ).

The discovery of alternative splicing as a way of producing different transcripts from one gene had a more complex history. In the late 1970s it was discovered, first in animal viruses and then in eukaryotes, that genes have a split structure. That is, genes are interrupted by introns (see review by Portin 1993 ). Split genes produce one pre-mRNA molecule, from which the introns are removed during the maturation of the mRNA by pre-mRNA splicing. Depending on the gene, the splicing pattern can be invariant (“constitutive”) or variable (“alternative”). In constitutive splicing, all the exons present in a transcript are incorporated into one mature mRNA through invariant ligation of consecutive exons, yielding a single kind of mRNA from the gene. In alternative splicing, nonconsecutive exons are joined by the processing of some, but not all, transcripts from a gene. In other words, individual exons can be excluded from the mature mRNA in some transcripts, but they can be included in others ( Leff et al. 1986 ; Black 2003 ). Alternative splicing is a regulated process, being tissue-specific and developmental-stage-specific. Nevertheless, the colinearity of the gene and the mRNA is preserved, since the order of the exons in the gene is not changed.

In addition to alternative splicing, two other phenomena are now known that contradict a basic tenet of the neoclassical gene concept, namely that amino-acid sequences of proteins, and consequently their functions, are always derivable from the DNA of the corresponding gene. These are the phenomena of RNA editing (reviewed by Brennickle et al. 1999 ; Witzany 2011 ) and of gene sharing originally found by J. Piatigorsky (reviewed in Piatigorsky 2007 ). The term RNA editing describes post-transcriptional molecular processes in which the structure of an RNA molecule is altered. Though a rare event, it has been observed to occur in eukaryotes, their viruses, archaea and prokaryotes, and involves several kinds of base modifications in RNA molecules. RNA editing in mRNAs effectively alters the amino acid sequence of the encoded protein so that it differs from that predicted by the genomic DNA sequence ( Brennickle et.al . 1999 ). The concept of gene sharing describes the fact that different cells contain identically sequenced polypeptides, derived from the same gene, but so differently configured in different cellular contexts that they perform wildly different functions. This phenomenon, facetiously called “protein moonlighting,” means that a gene may acquire and maintain a second function without gene duplication, and without loss of the primary function. Such genes are under two or more entirely different selective constraints ( Piatigorsky and Wistow 1989 ).

Despite these observations, showing the potential one-to-many relationships of genes to mRNAs and their encoded proteins, the concept of the gene remained intact; the gene itself could still be seen as a defined and localized nucleotide sequence of DNA even though it could contain information for more than one kind of polypeptide chain. Matters changed, however, when the sequencing projects revealed still more bizarre phenomena.

Severe cracks in the concept of the gene

These new findings have shown that there are multiple possible relationships between DNA sequences and the molecular products they specify. The net result has been the realization that the basic concept of the gene as some form of generic, universal “unit of heredity” is too simple, and correspondingly, that, a new definition or concept of “the gene” is needed ( Keller 2000 ; Falk 2009 ; Portin 2009 ). Several observations have been crucial to this re-evaluation, and one of us has reviewed these relatively recently ( Portin 2009 ). They are worth summarizing here:

In eukaryotic organisms, there are few if any absolute boundaries to transcription, making it impossible to establish simple general relationships between primary transcripts and the ultimate products of those transcripts.

Hence, the structural boundaries of the gene as the unit of transcription are often far from clear, as documented particularly well in mammals (reviewed by Carninci 2006 ). In reality, whole chromosomes, if not the whole genome, seem to be continuums of transcription ( Gingeras 2007 ). Furthermore, the genome is full of overlapping transcripts, thus making it impossible to draw 1:1:1 relationship between specific DNA sequences, transcripts and functions ( Pearson 2006 ). Indeed, convincing evidence indicates that the human genome is comprehensively transcribed from both DNA strands, so that the majority of its bases can be found in primary transcripts that compendiously overlap one another (The FANTOM Consortium and RIKEN Genome Exploration Group 2005; The ENCODE Project Consortium 2007 ; 2012 ). Both protein coding and noncoding transcripts may be derived from either or both DNA strands, and they may be overlapping and interlaced. Furthermore, different transcripts often include the same coding sequences ( Mattick 2005 ). The functional significance of these overlaps is still largely unclear, but there is an increasing number of examples in which both transcripts are known to have protein-coding exons from one position in the genome combined with exons from another part of the genome hundreds of thousands of nucleotides away ( Kapranov et al. 2007 ). This was wholly unanticipated when the 1960s definition of the gene was formulated.

2. Exons of different genes can be members of more than one transcript.

Gene fusion, at the level of transcripts, is a reality, and is completely at odds with the “one gene—one mRNA—one protein” hypothesis. And this is not a rare phenomenon. It has been estimated that at least 4–5% of the tandem gene pairs in the human genome can be transcribed into a single RNA sequence, called chimeric transcripts, encoding a putative chimeric protein ( Parra et al. 2006 ).

3. Comparably, in the organelles of microbial eukaryotes, many examples of “encrypted” genes are known: genes are often in pieces that can be found as separate segments around the genome.

Hence, in addition to the fusion of two adjacent genes at the level of transcription, different building blocks of a given mRNA molecule can often be located, as modules, on different chromosomes (reviewed in Landweber 2007 ). Some evidence indicates that, even in multicellular eukaryotes, protein-coding transcripts are derived from different nonhomologous chromosomes (reviewed in Claverie 2005 ).

4. In contradiction to the neoclassical definition of a gene, which posits that the hereditary information resides solely in DNA sequences, there is increasing evidence that the functional status of some genes can be inherited from one generation of individuals to the next, a phenomenon known as transgenerational epigenetic inheritance ( Holliday 1987 ; Gerhart and Kirschner 2007 ; Jablonka and Raz 2009 ).

One example is mouse epigenetic changes mediated by RNA that are inherited between generations in a non-Mendelian fashion ( Rassoulzadegan et al. 2006 ). On the other hand, many of the epigenetic changes, or so called epimutations, are inherited otherwise in a Mendelian fashion, except that, in contrast to conventional mutations, they are not always inherited with the same stability, but can be swept away during the course of some generations ( e.g. , Jablonka and Raz 2009 ).

5. “Genetic restoration” a mechanism of non-Mendelian inheritance of extragenomic information, first found in Arabidopsis thaliana , may also take place ( Lolle et al. 2005 ).

It was observed that several independent mutant strains yielded apparently normal progeny at a high frequency of a few percent, which is higher than could be expected if it were a question of random mutations. It seems neither to be a question of epigenetic changes, but rather healing of fixed mutations. Lolle et al. (2005) suggested that this is due to precise reversion of the original DNA with a mechanism that involves template-directed restoration of ancestral DNA passed on in an RNA cache. This phenomenon, called the “RNA cache” hypothesis, means that organisms can sometimes rewrite their DNA on the basis of RNA messages inherited from generations past ( Lolle et al. 2005 ). The RNA cache hypothesis has, however, been disputed by several authors ( Comai and Cartwright 2005 ; Mercier et al. 2008 ; Miyagawa et al. 2013 ).

6. Finally, in addition to protein coding genes, there are many RNA-encoding genes that produce diverse RNA molecules that are not translated to proteins.

That there are special genes that specify only RNA products was recognized in the early 1960s; these are the ribosomal RNA and tRNA genes, vital for protein synthesis. Yet, it is now apparent that there are many transcripts that do not encode proteins, and that are not the classic structural RNAs of protein synthesis (tRNAs and rRNAs). Those sequences that specify long noncoding RNAs (lncRNAs), and which serve some biological function, surely deserve to be called genes. In contrast, sequences specifying lncRNAs or transcripts from defunct mobile elements, which are made constitutively in all or most cell types probably do not have biological function and should not be designated as genes. The surprisingly large multitude of different noncoding RNA genes and their function has been reviewed by several authors ( e.g. , Eddy 2001 ; Carninci and Hayashizaki 2007 ; Carninci et al. 2008 ).

Current Status and Future Perspectives Regarding the Concept of the Gene

The observations summarized above, together with many others, have created the interesting situation that the central term of genetics— “the gene”—can no longer be defined in simple terms. The neoclassical molecular definition of the gene does not capture the bewildering variety of hereditary elements, all based in DNA, that collectively specify the organism, and which therefore deserve the appellation of “genes.” Even the classical notion of the gene simply as a fundamental “unit of heredity” is itself problematic. After all, if it is difficult or impossible to generalize about the nature of such “units,” it is probably not very helpful to speak about them. Unsurprisingly, this realization has called forth various attempts to redefine the gene, in terms of both DNA sequence properties, and those of the products specified by those sequences. A number of proposed definitions are listed in Table 1 . A detailed discussion of these ideas will not be given here, but they have been summarized, classified, and characterized (see Waters 2013 ). These definitions, however, all tend to neglect one central, albeit implicit, aspect of the earlier notions of the “gene”: its presumed autonomy of action. We return to this matter below.

Essential Content or Character of the Proposition	Classification	Author(s)
These three first operational definitions give criteria, formal, experimental and computational, for identifying genes in the DNA sequences of genomes, annotation of genomes, and for specifying the function of genes	Operational
	Operational
	Operational	(2009)
In these three following definitions, classified as molecular, the structural and the functional gene are conceptually distinguished and separated	Molecular
	Molecular
	Molecular
In this definition two gene concepts, “gene-P (preformationist)” and “gene-D (developmental)”, are distinguished	Complex
This definition presents three different concepts of the gene: instrumental, nominal and postgenomic	Complex
This definition aims at to define the gene on the basis of its products and separates it from DNA	A new kind of redefinition

How should geneticists deal with this situation? Should we simply invoke a plurality of different kinds of genes and leave it at that? In effect, we could settle for using the collective term “the genes” as a synonym for the genome, and not fuss over the seeming impossibility of defining the singular form, the “gene.” This, however, would seem to be more of an evasion of the problem than its solution. Alternatively, would it be preferable to accept the inadequacy of the notion of a simple general “unit of heredity,” and foreswear the use of the term “gene” altogether?

The problem with that last suggestion, junking the term “gene,” is not just that the word is used ubiquitously by geneticists and laymen alike, but that it seems indispensable to the discipline’s discourse. This is apparent in the foundations of several subdisciplines of genetics, such as many fields of applied genetics, like medical genetics and plant and animal breeding, that frequently deal in genes identified solely by their nonmolecular mutant phenotypes. It also applies to quantitative genetics and population genetics, which operate using mathematical modeling, and in which the gene is often regarded merely as an abstract unit of calculation (not dissimilarly to the view of Johannsen described below), but one that is vital to conceptualizing the genetic compositions of populations and their changes. In those fields, the molecular intricacies and complications of the genetic material can be largely ignored, at least initially, but the term “gene” itself seems irreplaceable. It is hard to imagine those disciplines abandoning it, whatever the range of molecular complexities that the word both hides and embraces.

In other subdisciplines, such as developmental genetics and molecular genetics, however, there is an urgent need to redefine the gene because the molecular details are often crucial to understanding the phenomena being investigated. The definitions that have been attempted so far ( Table 1 ), however, seem inadequate; for the most part, they focus on either structural or functional aspects, yet it is ultimately meaningless to separate structure and function, even though both can initially be studied in isolation from one another. One attempt to unite the structural and functional aspects of the gene in a single definition has been made by P. E. Griffiths and E. M. Neumann-Held, who introduced the “molecular process” gene concept. In this idea, the word “gene” denotes not some structural “unit of heredity” but the recurring process that leads to the temporally and spatially regulated expression of a particular polypeptide product ( Griffiths and Neumann-Held 1999 ; Neumann-Held 1999 , 2001 ). One difficulty with this redefinition is that it neglects all the nonconventional genes that specify only RNA products. More fundamentally, it has nothing to say about hereditary transmission, which was the original and fundamental impetus for coining the term “gene.”

Perhaps the way forward is to take a step backward in history, and focus on the initial concerns of Johannsen. He not only coined the term “gene,” but was also responsible for the words “genotype” and “phenotype,” and the crucial distinction between them in heredity. Though he could say nothing about how genes (genotype) specified or determined traits (phenotype), he clearly saw this as a crucial question. Indeed, that issue has been at the heart of genetics since the 1930s, in contrast to the questions about how genes are transmitted in heredity, which dominated the first decades of 20th-century genetics. It is apparent, however, that Johannsen thought that the genotype is primary, and that genes are minute computational devices whose precise material nature could be left for solution to a later time. He wrote: “Our formulas, as used here for not directly observable genotypic factors—genes as we used to say—are and remain computational-formulas , placement-devices that should facilitate our overview. It is precisely therefore that the little word “gene” is in place; no imagination of the nature of this “construction” is prejudiced by it, rather the different possibilities remain open from case to case.” ( Johannsen 1926 p. 434, English translation in Falk 2009 p. 70).

The initial expectations were that the connections between genes and phenes would be fairly direct, an expectation bolstered initially by findings about pigmentation genetics, and later by mutations affecting nutritional requirements in microbial cells. In both situations, the connection between the mutant effects and the known biochemistry were often direct and easy to understand. Furthermore, the early success of Mendelian genetics had been based, in large part, on the fact that many of the genetic variants initially studied had constant, unambiguous effects; this was vital to the work of Mendel and to the early 20th-century Mendelians. As the field matured, however, it became apparent that the phenotypic effects of many alleles could be influenced by other genes, influencing both the degree of severity of a mutation’s expression (its “expressivity”), and the proportion of individuals possessing the mutation that expressed it at all (its “penetrance”).

To illustrate the differences in the manifestation of a given gene’s function caused by genetic background effects, take the various degrees of expression of the gene regulating the size and shape of incisors in man. Copies of one dominant gene, identical by descent, caused missing, or peg-shaped, or strongly mesio-distally reduced upper lateral incisors in subsequent generations ( Alvesalo and Portin 1969 ). Though the precise nature of the gene involved is not known, the example shows that the same gene can have different manifestations in different individuals, i.e. , in different genetic backgrounds. There is an enormous number of documented examples of such genetic background effects in all organisms that have been investigated genetically.

The phenomenon of genetic background effects was already well recognized by geneticists in the second decade of the 20th century, as illustrated, for example, in the multi-part series of papers, dealing with coat color inheritance in mammals by S. Wright, published in Journal of Genetics ( Wright 1917a , b ). (Wright would later achieve eminence as one of the key founders of population genetics, but he started his career in what was then known as “physiological genetics.”) The whole matter, however, was raised to a new conceptual level in the 1930s, by C. H. Waddington, a British developmental biologist and geneticist, who called the totality of interactions among genes and between genes and the environment “the epigenotype.”

The epigenotype consists of the total developmental system lying between the genotype and the phenotype through which the adult form of an organism is realized ( Waddington 1939 ). Although a clear concept of “gene regulation” did not exist in the 1940s and 1950s, Waddington, with this concept, was clearly edging toward it. When the Jacob-Monod model of gene regulation came forth in the early 1960s, Waddington promptly saw its relevance for development ( Waddington 1962 ; 1966 ) as, of course, did Jacob and Monod themselves ( Jacob and Monod 1961a , b ; Monod and Jacob 1961 ). The crucial point, with respect to the definition of the gene, is that genes are not autonomous, independent agents—as was implicit in much of the early treatment of genes, and which indeed remains potent in much contemporary thinking, as exemplified in R. Dawkins’ still influential book, “The Selfish Gene” ( Dawkins 1976 ). Rather, they exert their effects within, or as the output of, complex systems of gene interactions. Today, we term such systems “genetic networks” or “genetic regulatory networks” (GRNs). Sewall Wright, along with Waddington, was an early exponent of such network thinking ( Wright 1968 ), but the modern concept of GRNs reached its fruition only in the late 1990s (reviewed in Davidson 2001 ; Wilkins 2002 ; Davidson and Erwin 2006 ; Wilkins 2007 ).

The conceptual consequences of viewing individual genes not as autonomous actors but as interactive elements or outputs of networks are profound. For one thing, it becomes relatively easy to think about the nature of genetic background effects in terms of the structure of GRNs ( Box 2 ). While much of the thinking of the 20th century about genes was based on the premise that the route from gene to phenotype was fairly direct, and often deducible from the nature of the gene product, the network perspective envisages far more complexity and indirectness of effects. In general, the path from particular genes to specific phenes is long, and the role of many gene products seems to be the activation or repression of the activities of other genes. As a result, for most of these interactive effects, the normal (wild-type) function of the gene can only rarely be deduced directly from the mutant phenotype, which often involves complicated secondary effects resulting from the disrupted operation of the GRN within which the gene acts. Hence, the widely held popular belief that particular genes govern or “determine” particular traits, including complex psychological ones ( e.g. , risk-taking, gender identity, autism), as inferred from studies of genetic variants, is a gross oversimplification, hence distortion, of a complex reality.

In effect, genes do not have independent “agency”; for the most part they are simply cogs in the complex machinery of GRNs, and interpreting their mutant phenotypes is often difficult. In contrast, the genes for which there is an obvious connection between the mutant form and an altered phenotype are usually ultimate outputs of GRNs, such as pigmentation genes, hemoglobins, and enzymes of intermediary metabolism. These genes, however, also lack true autonomy, being activated in response to the operation of GRNs. Therefore, to fully understand how a gene functions, one must comprehend the larger systems in which they operate. Genetics, in this sense, is becoming systems biology, a point that has also been made by others (see, for example, Keller 2005 ). In effect, since genes can only be defined with respect to their products, and those products are governed by GRNs, the particular cellular and regulatory (GRN) contexts involved may be considered additional “dimensions” vital to specifying a gene’s function and identity. The examples of “gene sharing,” in which the function of the gene is wholly a function of its cellular context, illustrate this in a particularly vivid way. The “gene”—however it comes to be defined—can therefore be seen not as a three-dimensional entity but as a multi-dimensional one.

Putting it all Together: Toward a New Definition of the “Gene”

Where do all these considerations leave us? It took approximately half a century to go from Johannsen’s wholly abstract formulation of the term “gene” as a “unit of heredity,” to reach the early 1960s concept of the gene as a continuous segment of DNA sequence specifying a polypeptide chain. A further half century’s worth of experimental investigation has brought us to the realization that the 1960s definition is no longer adequate as a general one. Yet the term “gene” persists as a vaguely understood generic description. It is, to say the least, an anomalous situation that the central term of genetics should now be shrouded in confusion and ambiguity. That is not only intellectually unsatisfactory for the discipline, but has detrimental effects on the popular understanding of genetics. Such misunderstanding is seen most starkly in the situation noted earlier, the commonly held view that there are individual genes responsible “for” certain complex conditions, e.g. , schizophrenia, alcoholism, etc. A clearer definition of the term would thus help both the field of genetics, and, ultimately, public understanding.

Here, therefore, we will propose a definition that we believe comes closer to doing justice to the idea of the “gene,” in light of current knowledge. It makes no reference to “the unit of heredity”—the long-standing sense of the term—because we feel that it is now clear that no such generic universal unit exists. By referring to DNA sequences, however, our definition embodies the hereditary dimension of genes (in a way that pure “process”-centered definitions focused on gene expression do not). Furthermore, in its emphasis on the ultimate molecular products and reference to GRNs as both evokers and mediators of the actions of those products, it recognizes the long causal chains that often operate between genes and their effects. Our provisional definition is this:

A gene is a DNA sequence (whose component segments do not necessarily need to be physically contiguous) that specifies one or more sequence-related RNAs/proteins that are both evoked by GRNs and participate as elements in GRNs , often with indirect effects , or as outputs of GRNs , the latter yielding more direct phenotypic effects .

This is an explicitly “molecular” definition, but we think that is what is needed now. In contrast, “genes” that are identified purely by their phenotypic effects, as for example in genome-wide association study (GWAS) experiments, would, in our view, not deserve such a characterization until found to specify one or more RNAs/proteins. The genetic effects picked up in such work often identify purely regulatory elements, and these should not qualify as genes, only as part of genes. Our definition, like the classic 1960s’ formulation, makes identifying the product(s) crucial to delimiting, hence identifying, the genes themselves. It, however, also emphasizes the molecular and cellular context in which those products form and function. Those larger contexts, in effect, become necessary to define the function of the specifying gene(s).

The new definition, however, is slightly cumbersome. We therefore offer it only as a tentative solution, hence as a challenge to the field to find a better formulation but one that does justice to the complex realities of the genetic material uncovered in the past half-century.

The cis -trans test

Of fundamental importance in the operational definition of the gene is the cis-trans test ( Lewis 1951 ; Benzer 1957 ). To test whether mutations a and b belong to the same gene or cistron ( Benzer 1957 ), or different cistrons, the cis -heterozygote a b/+ + and the trans -heterozygote a +/+ b are compared. If the cis -heterozygotes, and the trans -heterozygotes are phenotypically similar (usually wild type), they are said to “complement” one another, and the mutations are inferred to fall into different cistrons. If, however, the cis -heterozygotes and the trans -heterozygotes are phenotypically different, the trans -heterozygote being (usually) mutant, and the cis -heterozygote (usually) of wild type, the mutations do not complement, and are inferred to belong to the same cistron. The attached figure clarifies the idea.

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Object name is 1353figx1.jpg

The principle of the cis-trans test. If mutations a and b belong to the same cistron, the phenotypes of the cis - and trans -heterozygotes are different. If, however, the cis - and trans -heterozygotes are phenotypically similar, the mutations a and b belong to different cistrons. The notation “works” on the Figure means that the cistron is able to produce a functional polypeptide. Mutations a and b are recessive mutations that both affect the same phenotypic trait, such as the eye color of D. melanogaster , for example.

Interpreting “genetic background” effects in terms of GRNs

Genetic background effects typically exhibit either of two forms, when a pre-existing mutation, with an associated phenotypic manifestation, is crossed into a different strain: the reduction (“suppression”) of the mutant phenotype or its increase (“enhancement”). The effects involve either changes in the degree (“expressivity”) of the mutant effect, or the number of individuals) affected (its “penetrance”), or both. When analyzed genetically, these effects could often be traced to specific “suppressor” or “enhancer” loci, which could be either tightly linked or distant in the genome from the original mutant locus. Typically regarded as an unnecessary complication in analysis of the original mutation, they were usually not pursued further. Yet, in terms of current understanding of GRNs, they are not, in principle, mysterious. Each gene that is part of a GRN can be thought of as either transmitting a signal for the activation or repression of one or more other “downstream” genes in that network, but, given the hierarchical nature of GRNs, it follows that a mutational alteration in a specific gene in the network can be either strengthened or reduced by other mutational changes in the network, either upstream or downstream of the original mutation. The particular effect achieved will depend on the characteristics of each of the two mutations involved—whether they are loss-of- or gain-of-function mutations—and the precise nature of their connectivity. Such effects are most readily illustrated with linear sequences of gene actions, genetic pathways ( Wilkins 2007 ), but can be understood in networks, when the network structure and the placement of the two genes within them is known. Some genetic background effects, in principal, however, might involve partially redundant networks, in which the effects of the two pathways are additive. In those cases, a mutant effect in one pathway may be either compensated, hence suppressed, or exacerbated, by a second mutation in the other pathway, the precise effects again depending upon the specific characteristics of the mutations and the degree of redundancy between the two GRNs.

Acknowledgments

We thank Mark Johnston and Richard Burian for many helpful suggestions, both editorial and substantive, on previous drafts. A.W. would also like to acknowledge earlier conversations with Jean Deutsch on the subject of this article; we disagreed on much but the process was stimulating and helpful. P.P. wants to thank his friends Marja Vieno, M.Sc. for linguistic aid at the very first stages of this project, and Harri Savilahti, Ph.D. for a fruitful discussion, and Docent Mikko Frilander, Ph.D. for consultation. The authors declare no conflict of interest.

Communicating editor: M. Johnston

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What is a Gene? Colinearity and Transcription Units

In the early part of the twentieth century, scientists knew what genes did, but they did not know what they were. Francis Crick, one of the codiscoverers of the three-dimensional double helical structure of DNA , was among the first to propose that a gene was a linear sequence of nucleotides and that each gene encoded a single protein . Crick called this proposal the sequence hypothesis (Crick, 1958); other scientists have since referred to it as the genes-on-a-string hypothesis. In Crick's words, this hypothesis "assumes that the specificity of a piece of nucleic acid is expressed solely by the sequence of its bases, and this sequence is a (simple) code for the amino acid sequence of a particular protein." Crick freely admitted that his hypothesis was just that: a hypothesis "for which proof is completely lacking." However, in an effort to rationalize his speculation, Crick cited some experimental work with bacteriophages that had been conducted by American molecular biologist Seymour Benzer. Benzer's work demonstrated that, in Crick's words, "a functional gene consists of many sites arranged strictly in a linear order " (Crick, 1958; italics original).

Today, scientists no longer speak of the sequence hypothesis. Instead, the notion that nucleotide sequences (genes) directly dictate amino acid sequences is known as colinearity (Figure 1). Scientists have confirmed that colinearity is a regular occurrence among many viruses, like the ones Benzer studied, as well as among bacteria . However, it turns out that colinearity is the exception, not the rule, in eukaryotic genomes.

Alternatives to Colinearity

One of the first clues that the colinearity of DNA and amino acid sequences is not as simple as what Crick had proposed was the discovery of RNA splicing in the 1970s. Using common cold viruses as their experimental systems, English molecular chemist Richard Roberts and American molecular biologist Philip Sharp independently discovered that genes can be split into several segments along the genome (Berget et al. , 1977; Chow et al. , 1977). Then, using electron microscopy, both scientists observed that a single messenger RNA ( mRNA ) molecule hybridized not to a single stretch of DNA but to as many as four or more discontinuous DNA segments (Figure 2).

Roberts and Sharp also noted that the genetic material actually breaks apart and then re-forms itself at certain points in protein synthesis. Specifically, the sections of DNA that encode protein production are known as exons, and the noncoding sections interspersed among the exons are known as introns. During splicing, which occurs after transcription (i.e., the synthesis of RNA from a DNA template), the introns are removed and the exons are joined, or spliced together.

Roberts's and Sharp's findings not only raised serious doubts about the concept of a gene as a continuous, clearly demarcated segment of DNA, but they also led to a flurry of research activity, with scientists curious about whether the same was true in other species . As other researchers were quick to discover, discontinuous gene structure and splicing during RNA processing are the norm, not the exception, in most eukaryotes. Some vertebrate genes contain as many as 50 exons, and exons often make up only a small portion of the transcribed region of a gene. For example, in one early splicing study that involved examination of the intron-exon pattern of a chicken ovalbumin gene, Stein et al. (1980) measured eight exons ranging in length from 20 to 181 base pairs and seven introns ranging in length from 264 to 1,150 base pairs. Since that study, scientists have detected introns as long as 50,000 base pairs or more in some species.

The final protein products encoded by any given intron-exon sequence also vary in structure, depending on which exons are spliced back together during RNA processing. This so-called " alternative splicing " is illustrated in Figure 3. Scientists have also since learned that eukaryotic cells have evolved another "alternative" mRNA processing pathway: the use of multiple 3' cleavage sites in a single exon. (Every intron has a 5' and 3' splice site .) As illustrated in Figure 3, the end result is the same as with alternative splicing: different mRNA molecules are produced from a single protein-coding gene. Clearly, contrary to the conventional notion of a single gene encoding a single protein, a single continuous stretch of DNA can encode multiple mRNA molecules and, ultimately, multiple protein products.

Transcription Units Instead of Genes

Given the vast quantity of DNA that appears to have little protein-encoding power and the fact that so much of this DNA resides right in the middle of functional genes (as introns), some scientists prefer to think in terms of "transcription units" rather than "genes." A transcription unit is a linear sequence of DNA that extends from a transcription start site to a transcription stop site (Figure 4).

The promoter , a DNA sequence that lies upstream of the RNA coding region, serves as an indicator of where and in which direction transcription should proceed. The promoter is not actually transcribed; its role is purely regulatory. While promoters vary tremendously among eukaryotes, there are some common features. For example, most promoters lie immediately upstream of the transcription unit (transcription proceeds in an upstream to downstream direction), and most contain what is known as a TATA box ; this is a sequence that is recognized and bound by a so-called TATA binding protein. The TATA binding protein helps position the RNA polymerase machinery and initiates transcription. Some promoters work in concert with other types of regulatory sequences known as enhancers, which sometimes lie several kilobases further upstream or downstream from the coding sequence itself, or even within introns. These two sequences are able to interact because of the way DNA molecules bend in space, enabling sections that would otherwise be very far from each other to interact (via DNA-binding proteins). Enhancer regions serve as binding sites for proteins known as activators (Figure 5). The proteins that bind to promoters to regulate transcription are called transcription factors. The RNA coding region, the main component of the transcription unit, contains the actual exons and introns. The terminator , a sequence of nucleotides at the end of the transcription unit, is transcribed along with the RNA coding region. The terminator serves as a speed bump of sorts; transcription stops only after this region has been transcribed.

Scientists have recently discovered that some mRNA molecules are coded by exons from multiple transcription units through a process known as trans-splicing . In fact, in 2005, a European group of researchers estimated that about 4% to 5% of tandem transcription units (i.e., distinct but adjacent transcription units) in humans are transcribed together to create single "chimeric" mRNA molecules (Parra et al. , 2005). Scientists are not sure how this occurs. Some speculate that transcription overrides the first transcription terminator and doesn't stop until it reaches the second termination site; others suspect that both transcripts are formed independently and then spliced together to form the chimeric mRNA molecule.

Delineating Gene Regions

It seems that the more scientists learn about the genome and gene expression , the less they seem to be able to identify the point along a stretch of nucleotides at which a single gene actually begins and ends; indeed, it appears to be increasingly more difficult to determine whether there are even actual discrete nucleotide start and stop points for genes. This complexity continues to make it difficult for scientists to agree on exactly what a gene is. At the very least, scientists now know that Crick's original sequence hypothesis was overly simplistic, at least for eukaryotes. Genes are not linear sequences of DNA that directly correspond one-to-one with their protein counterparts.

Moreover, scientists now know that not all transcribed RNA molecules, or transcripts, end up being translated into protein products. For example, in a study of the mouse genome, researchers found that as much as 63% of the genome is transcribed but only about 1% to 2% is translated into a functional protein product (FANTOM Consortium et al. , 2005). So not only is the notion of colinearity overly simplistic, but so too is the notion that all genes encode proteins. Many code other types of molecules, like tRNA and rRNA , that have important known cellular functions. Other non-protein-coding RNAs work to regulate gene expression at multiple levels, and still other transcripts have unknown functions.

References and Recommended Reading

Beadle, G. W., & Tatus, E. L. Genetic control of biochemical reactions in Neurospora . Proceedings of the National Academy of Sciences 27 , 499–506 (1941)

Berget, S. M., et al . Spliced segments at the 5' terminus of adenovirus 2 late mRNA. Proceedings of the National Academy of Sciences 74 , 3171–3175 (1977)

Chow, L. T., et al . An amazing sequence arrangement at the 5' ends of adenovirus 2 messenger RNA. Cell 12 , 1–8 (1977)

Crick, F. On protein synthesis. The Biological Replication of Macromolecules: Symposium for the Society of Experimental Biology 12 , 138–162 (1958)

FANTOM Consortium, et al . The transcriptional landscape of the mammalian genome. Science 309 , 1559–1563 (2005) doi:10.1126/science.1112014

Parra, G., et al. Tandem chimerism as a means to increase protein complexity in the human genome. Genome Research 16 , 37–44 (2006)

Stein, J. P., et al. Ovomucoid intervening sequences specify functional domains and generate protein polymorphism. Cell 21 , 681–687 (1980)

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Home » What is a Hypothesis – Types, Examples and Writing Guide

What is a Hypothesis – Types, Examples and Writing Guide

Table of Contents

Definition:

Hypothesis is an educated guess or proposed explanation for a phenomenon, based on some initial observations or data. It is a tentative statement that can be tested and potentially proven or disproven through further investigation and experimentation.

Hypothesis is often used in scientific research to guide the design of experiments and the collection and analysis of data. It is an essential element of the scientific method, as it allows researchers to make predictions about the outcome of their experiments and to test those predictions to determine their accuracy.

Types of Hypothesis

Types of Hypothesis are as follows:

Research Hypothesis

A research hypothesis is a statement that predicts a relationship between variables. It is usually formulated as a specific statement that can be tested through research, and it is often used in scientific research to guide the design of experiments.

Null Hypothesis

The null hypothesis is a statement that assumes there is no significant difference or relationship between variables. It is often used as a starting point for testing the research hypothesis, and if the results of the study reject the null hypothesis, it suggests that there is a significant difference or relationship between variables.

Alternative Hypothesis

An alternative hypothesis is a statement that assumes there is a significant difference or relationship between variables. It is often used as an alternative to the null hypothesis and is tested against the null hypothesis to determine which statement is more accurate.

Directional Hypothesis

A directional hypothesis is a statement that predicts the direction of the relationship between variables. For example, a researcher might predict that increasing the amount of exercise will result in a decrease in body weight.

Non-directional Hypothesis

A non-directional hypothesis is a statement that predicts the relationship between variables but does not specify the direction. For example, a researcher might predict that there is a relationship between the amount of exercise and body weight, but they do not specify whether increasing or decreasing exercise will affect body weight.

Statistical Hypothesis

A statistical hypothesis is a statement that assumes a particular statistical model or distribution for the data. It is often used in statistical analysis to test the significance of a particular result.

Composite Hypothesis

A composite hypothesis is a statement that assumes more than one condition or outcome. It can be divided into several sub-hypotheses, each of which represents a different possible outcome.

Empirical Hypothesis

An empirical hypothesis is a statement that is based on observed phenomena or data. It is often used in scientific research to develop theories or models that explain the observed phenomena.

Simple Hypothesis

A simple hypothesis is a statement that assumes only one outcome or condition. It is often used in scientific research to test a single variable or factor.

Complex Hypothesis

A complex hypothesis is a statement that assumes multiple outcomes or conditions. It is often used in scientific research to test the effects of multiple variables or factors on a particular outcome.

Applications of Hypothesis

Hypotheses are used in various fields to guide research and make predictions about the outcomes of experiments or observations. Here are some examples of how hypotheses are applied in different fields:

Science : In scientific research, hypotheses are used to test the validity of theories and models that explain natural phenomena. For example, a hypothesis might be formulated to test the effects of a particular variable on a natural system, such as the effects of climate change on an ecosystem.
Medicine : In medical research, hypotheses are used to test the effectiveness of treatments and therapies for specific conditions. For example, a hypothesis might be formulated to test the effects of a new drug on a particular disease.
Psychology : In psychology, hypotheses are used to test theories and models of human behavior and cognition. For example, a hypothesis might be formulated to test the effects of a particular stimulus on the brain or behavior.
Sociology : In sociology, hypotheses are used to test theories and models of social phenomena, such as the effects of social structures or institutions on human behavior. For example, a hypothesis might be formulated to test the effects of income inequality on crime rates.
Business : In business research, hypotheses are used to test the validity of theories and models that explain business phenomena, such as consumer behavior or market trends. For example, a hypothesis might be formulated to test the effects of a new marketing campaign on consumer buying behavior.
Engineering : In engineering, hypotheses are used to test the effectiveness of new technologies or designs. For example, a hypothesis might be formulated to test the efficiency of a new solar panel design.

How to write a Hypothesis

Here are the steps to follow when writing a hypothesis:

Identify the Research Question

The first step is to identify the research question that you want to answer through your study. This question should be clear, specific, and focused. It should be something that can be investigated empirically and that has some relevance or significance in the field.

Conduct a Literature Review

Before writing your hypothesis, it’s essential to conduct a thorough literature review to understand what is already known about the topic. This will help you to identify the research gap and formulate a hypothesis that builds on existing knowledge.

Determine the Variables

The next step is to identify the variables involved in the research question. A variable is any characteristic or factor that can vary or change. There are two types of variables: independent and dependent. The independent variable is the one that is manipulated or changed by the researcher, while the dependent variable is the one that is measured or observed as a result of the independent variable.

Formulate the Hypothesis

Based on the research question and the variables involved, you can now formulate your hypothesis. A hypothesis should be a clear and concise statement that predicts the relationship between the variables. It should be testable through empirical research and based on existing theory or evidence.

Write the Null Hypothesis

The null hypothesis is the opposite of the alternative hypothesis, which is the hypothesis that you are testing. The null hypothesis states that there is no significant difference or relationship between the variables. It is important to write the null hypothesis because it allows you to compare your results with what would be expected by chance.

Refine the Hypothesis

After formulating the hypothesis, it’s important to refine it and make it more precise. This may involve clarifying the variables, specifying the direction of the relationship, or making the hypothesis more testable.

Examples of Hypothesis

Here are a few examples of hypotheses in different fields:

Psychology : “Increased exposure to violent video games leads to increased aggressive behavior in adolescents.”
Biology : “Higher levels of carbon dioxide in the atmosphere will lead to increased plant growth.”
Sociology : “Individuals who grow up in households with higher socioeconomic status will have higher levels of education and income as adults.”
Education : “Implementing a new teaching method will result in higher student achievement scores.”
Marketing : “Customers who receive a personalized email will be more likely to make a purchase than those who receive a generic email.”
Physics : “An increase in temperature will cause an increase in the volume of a gas, assuming all other variables remain constant.”
Medicine : “Consuming a diet high in saturated fats will increase the risk of developing heart disease.”

Purpose of Hypothesis

The purpose of a hypothesis is to provide a testable explanation for an observed phenomenon or a prediction of a future outcome based on existing knowledge or theories. A hypothesis is an essential part of the scientific method and helps to guide the research process by providing a clear focus for investigation. It enables scientists to design experiments or studies to gather evidence and data that can support or refute the proposed explanation or prediction.

The formulation of a hypothesis is based on existing knowledge, observations, and theories, and it should be specific, testable, and falsifiable. A specific hypothesis helps to define the research question, which is important in the research process as it guides the selection of an appropriate research design and methodology. Testability of the hypothesis means that it can be proven or disproven through empirical data collection and analysis. Falsifiability means that the hypothesis should be formulated in such a way that it can be proven wrong if it is incorrect.

In addition to guiding the research process, the testing of hypotheses can lead to new discoveries and advancements in scientific knowledge. When a hypothesis is supported by the data, it can be used to develop new theories or models to explain the observed phenomenon. When a hypothesis is not supported by the data, it can help to refine existing theories or prompt the development of new hypotheses to explain the phenomenon.

When to use Hypothesis

Here are some common situations in which hypotheses are used:

In scientific research , hypotheses are used to guide the design of experiments and to help researchers make predictions about the outcomes of those experiments.
In social science research , hypotheses are used to test theories about human behavior, social relationships, and other phenomena.
I n business , hypotheses can be used to guide decisions about marketing, product development, and other areas. For example, a hypothesis might be that a new product will sell well in a particular market, and this hypothesis can be tested through market research.

Characteristics of Hypothesis

Here are some common characteristics of a hypothesis:

Testable : A hypothesis must be able to be tested through observation or experimentation. This means that it must be possible to collect data that will either support or refute the hypothesis.
Falsifiable : A hypothesis must be able to be proven false if it is not supported by the data. If a hypothesis cannot be falsified, then it is not a scientific hypothesis.
Clear and concise : A hypothesis should be stated in a clear and concise manner so that it can be easily understood and tested.
Based on existing knowledge : A hypothesis should be based on existing knowledge and research in the field. It should not be based on personal beliefs or opinions.
Specific : A hypothesis should be specific in terms of the variables being tested and the predicted outcome. This will help to ensure that the research is focused and well-designed.
Tentative: A hypothesis is a tentative statement or assumption that requires further testing and evidence to be confirmed or refuted. It is not a final conclusion or assertion.
Relevant : A hypothesis should be relevant to the research question or problem being studied. It should address a gap in knowledge or provide a new perspective on the issue.

Advantages of Hypothesis

Hypotheses have several advantages in scientific research and experimentation:

Guides research: A hypothesis provides a clear and specific direction for research. It helps to focus the research question, select appropriate methods and variables, and interpret the results.
Predictive powe r: A hypothesis makes predictions about the outcome of research, which can be tested through experimentation. This allows researchers to evaluate the validity of the hypothesis and make new discoveries.
Facilitates communication: A hypothesis provides a common language and framework for scientists to communicate with one another about their research. This helps to facilitate the exchange of ideas and promotes collaboration.
Efficient use of resources: A hypothesis helps researchers to use their time, resources, and funding efficiently by directing them towards specific research questions and methods that are most likely to yield results.
Provides a basis for further research: A hypothesis that is supported by data provides a basis for further research and exploration. It can lead to new hypotheses, theories, and discoveries.
Increases objectivity: A hypothesis can help to increase objectivity in research by providing a clear and specific framework for testing and interpreting results. This can reduce bias and increase the reliability of research findings.

Limitations of Hypothesis

Some Limitations of the Hypothesis are as follows:

Limited to observable phenomena: Hypotheses are limited to observable phenomena and cannot account for unobservable or intangible factors. This means that some research questions may not be amenable to hypothesis testing.
May be inaccurate or incomplete: Hypotheses are based on existing knowledge and research, which may be incomplete or inaccurate. This can lead to flawed hypotheses and erroneous conclusions.
May be biased: Hypotheses may be biased by the researcher’s own beliefs, values, or assumptions. This can lead to selective interpretation of data and a lack of objectivity in research.
Cannot prove causation: A hypothesis can only show a correlation between variables, but it cannot prove causation. This requires further experimentation and analysis.
Limited to specific contexts: Hypotheses are limited to specific contexts and may not be generalizable to other situations or populations. This means that results may not be applicable in other contexts or may require further testing.
May be affected by chance : Hypotheses may be affected by chance or random variation, which can obscure or distort the true relationship between variables.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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What Are Genes, DNA, and Chromosomes?

Chromosomes

Genetic Testing

Genetic Disorders

Genes are the basic units that determine the traits that we inherit from our parents. They contain coded information found in nearly every cell of the human body.

Our genes are made up of DNA, a molecule with this coded information. Hundreds to thousands of genes are found on each chromosome inside our cells. Together, the DNA, genes, and chromosomes make up the complete set of genetic instructions for every individual—referred to as a genome. These instructions include a person's sex, features, and risk of medical conditions.

The Human Genome Project, founded in 1990, mapped the entire human genome to understand how genes and chromosomes influence diseases and to find better ways to treat them. Based on information from the project, scientists have been able to discover over 1,800 genes that cause disease and, in turn, create tests and medicines to help diagnose and treat them.

What Are Genes Made Of?

Genes are composed of DNA and encoded for a specific purpose. How genes are encoded will determine how you look or how your body functions. Every person has two copies of a gene, each inherited from a parent.

Some genes provide instructions to produce specific types of proteins. Proteins are the molecules that not only make up tissues (like muscles and skin) but also play critical roles in the development and function of the body.

Other genes are encoded to produce RNA ( ribonucleic acid ), a molecule that converts the information stored in DNA to make protein. Different versions of a gene are known as alleles .

Every human has around 20,000 genes, half inherited from a person's mother and half inherited from a person's father.

The alleles you inherit from your parents may determine, for example, if you have brown eyes or blue eyes. Others may lead to congenital (inherited) disorders like cystic fibrosis or Huntington’s disease . Others still may not cause disease but may increase your risk of getting one (like cancer ). Genes only make up between 1% and 5% of the human genome. The rest is made up of non-coded DNA that doesn't produce protein but helps regulate how genes function.

What Is DNA Made Of?

DNA ( deoxyribonucleic acid ) is a building block that makes up your genes.

Within DNA is a unique chemical code that guides your growth, development, and function. The code is determined by the arrangement of the following four chemicals known as nucleotide bases :

Adenine (A)
Cytosine (C)
Guanine (G)
Thymine (T)

The bases pair up with each other—A with T and C with G—to form units known as base pairs. The pairs are then attached to form what looks like a spiraling ladder, known as a double helix .

The specific order, or sequence, of these nucleotide bases determines which instructions are given.

Human DNA consists of around 3 billion of these bases, of which 99% are the same for all humans. The remaining 1% is what differentiates one human from the next.

What Are Chromosomes Made Of?

Chromosomes are made up of around 1,000 genes. In total, there are two sets of 23 chromosomes in nearly every cell of the body, one set inherited from a person's mother and the other from a person's father.

One pair of chromosomes, called the sex chromosomes , determines whether you are born male or female. Females have a pair of XX chromosomes, while males have a pair of XY chromosomes.

The other 22 pairs are called autosomal chromosomes . These determine the rest of your body’s makeup.

Certain genes within these chromosomes may either be dominant or recessive. This can determine which traits predominate and which don't. By definition:

Autosomal dominant means that you need only one copy of an allele from one parent for a trait to develop (such as brown eyes or Huntington's disease).
Autosomal recessive means that you need two copies of the allele—one from each parent—for a trait to develop (such as blue eyes or cystic fibrosis).

What Is a Genome?

A genome is the complete set of genetic instructions that determine the traits and characteristics of an organism. It contains all the information needed for an individual to develop and function, based on their chromosomes, genes, and DNA.

While the genome of each species is distinct, every organism within that species has its own unique genome. This is why no two people are exactly alike, including twins.

What Is Genetic Variation?

Genes are prone to coding errors. Many errors won't make any significant difference in the structure or function of a person's body, but some can.

Some genetic variations will directly cause a defect or disease, some of which may be congenital (seen at birth) and others that may only be seen later in life.

Other variations can lead to changes in the entire "gene pool" (the characteristic genes in a population) that will affect inheritance patterns in later generations.

There are three common types of genetic variation:

Genetic Mutations

A genetic mutation is a change in the sequence of DNA. This is often due to copying errors that occur when a cell divides. It can also be caused by outside forces like an infection, chemicals, or radiation that damage the structure of genes.

Genetic disorders like sickle cell disease, Tay-Sachs disease, and phenylketonuria are all caused by the mutation of a single gene.

Radiation-induced cancer is caused by genetic changes caused by excessive exposure to medical or occupational radiation.

Genetic Recombination

Genetic recombination is a process in which pieces of DNA are broken, recombined, and repaired to produce a new allele. Also referred to as "genetic reshuffling," recombination occurs randomly in nature during a normal event during cell division. The new allele can then be passed from parents to offspring.

Down syndrome is one such example of genetic recombination.

Genetic Migration

Genetic migration is an evolutionary process in which the addition or loss of people in a population changes the gene pool, making certain traits either less common or more common.

A theoretical example is the loss of red-haired people from Scotland, which over time may result in fewer and fewer Scottish children being born with red hair.

Based on the findings of the Human Genome Project, scientists have been able to create over 2,000 genetic tests to help diagnose genetic disorders or predict your risk of getting them. Genetic testing can be performed on blood, skin, hair, amniotic fluid , or other body tissues.

Genetic tests look for specific DNA mutations associated with different diseases. If you are suspected of having an inheritable disease or have a family history of one, genetic testing may be recommended.

Other reasons for testing include:

To determine if certain parents are at risk of having a child with a genetic disease
To determine if you are a "carrier" of a gene you can pass to a child
To determine if an unborn child has a genetic disease
To routinely screen newborns for up to 50 different genetic disease
To see if a person is at an increased risk of developing a certain disease
To determine if targeted drugs can be used based on the genetic makeup of the target cell
To determine what dose of a drug is needed based on a person's genetic makeup

Some of these tests have a higher prognostic (predictive) value than others. While some test results are conclusive, delivering a positive or negative result, others may require a genetic counselor to help you understand what a result does and doesn't mean.

This is especially true if parents learn that they are at risk of having a baby with a potentially severe birth defect. A genetic counselor can help characterize the risk so that they can make an informed choice.

List of Genetic Disorders Detected by Genetic Testing

Today, there are not only lab-based tests to detect certain diseases but also home kits you can purchase at stores or online to help predict your risk. While the prognostic values of self-tests are improving, they are prone to inaccuracies.

Even so, a positive result may encourage you to see a healthcare provider for further testing (such as finding you have a BRCA mutation linked to an increased risk of breast cancer ).

Lab-based genetic testing can help detect an ever-increase range of disorders and diseases, including:

Acute lymphoblastic leukemia (ALL)
Acute myeloid leukemia (AML)
Alzheimer's disease (early-onset)
Amyloidosis
Aortic aneurysm (familial)
Autoimmune diseases
Breast cancer
Chronic insomnia
Chronic pancreatitis
Color blindness
Congenital heart defects
Cystic fibrosis
Down syndrome
Huntington's disease
Macular degeneration
Multiple endocrine neoplasia syndrome (MENS)
Muscular dystrophy
Neural tube defects
Parkinson's disease (early-onset)
Phenylketonuria
Polycythemia vera
Retinoblastoma
Sickle cell disease (SCD)
Tay-Sachs disease
Thalassemia
Thrombocytopenia
Tourette's syndrome

DNA is the building blocks that contain the coded instructions for building and maintaining a body. Genes are comprised of DNA and are tasked with making specific proteins that play a critical role in the structure and function of the body. Chromosomes containing thousands of genes are passed from parents to offspring and determine an individual's unique traits.

Together, DNA, genes, and chromosomes make up each organism's genome.

Genetic tests can detect mutations that may help diagnose or predict your risk of certain diseases. They can also be used to see if you or your partner are carriers of a gene you can pass to a child if you decide to get pregnant.

MedlinePlus. What is a gene?

Merck Manual. Genes and chromosomes .

Genomics England. What is a genome?

National Human Genome Research Institute. The human genome project .

MedlinePlus. What is DNA?

MedlinePlus. What is a chromosome?

Genetic Alliance. Appendix B. Classic Mendelian genetics (patterns of inheritance) . In: Understanding Genetics: A District of Columbia Guide for Patients and Health Professionals. Washington, DC: District of Columbia Department of Health.

National Human Genome Institute. Mutation .

Shah DJ, Sachs RK, Wilson DJ. Radiation-induced cancer: a modern view . Br J Radiol. 2014 Dec;85(1020):e1166–e1173. doi:10.1259/bjr/25026140

Stapley J, Feulner PGD. Johnston SE, Santure AW, Smadja CM. Recombination: the good, the bad and the variable . Philos Trans R Soc Lond B Biol Sc i. 2017 Dec 19;372(1736):20170279. doi:10.1098/rstb.2017.0279

Ellstrand NC, Rieseberg LH. When gene flow really matters: gene flow in applied evolutionary biology . Evol Appl . 2016 Aug;9(7):833–6. doi:10.1111/eva.12402

U.S. National Library of Medicine. What are the risks and limitations of genetic testing?

National Society of Genetic Counselors. About genetic counselors .

Oh B. Direct-to-consumer genetic testing: advantages and pitfalls . Genomics Inform. 2019 Sep;17(3):e33. doi:10.5808/GI.2019.17.3.e33

Ibrahim M, Yadav S, Ogunleye F, Zakalik D. Male BRCA mutation carriers: clinical characteristics and cancer spectrum . BMC Cancer . 2018;18(1):179. doi:10.1186/s12885-018-4098-y

National Library of Medicine. GTR (genetic testing registry) .

By Mary Kugler, RN Mary Kugler, RN, is a pediatric nurse whose specialty is caring for children with long-term or severe medical problems.

$ 0.00 0 items

Genetic inheritance

Genetic inheritance is a basic principle of genetics and explains how characteristics are passed from one generation to the next.

Genetic inheritance occurs due to genetic material, in the form of DNA, being passed from parents to their offspring. When organisms reproduce, all the information for growth, survival, and reproduction for the next generation is found in the DNA passed down from the parent generation.

Much of our understanding of inheritance began with the work of a monk by the name of Gregor Mendel. His experiments and ‘Laws of Inheritance’ provide the foundations for modern genetics.

In sexual reproduction, the genetic material of two parents is combined and passed on to one individual. Although the offspring receives a combination of genetic material from two parents, certain genes from each parent will dominate the expression of different traits.

Gregor Mendel

Mendel is accredited as the first person to correctly understand the process of how characteristics are inherited by offspring from parents. Before Mendel, many other incorrect hypotheses attempted to explain how characteristics and traits were passed from generation to generation. The most commonly accepted theory was the ‘blending theory’ which proposed that the traits of parents were blended together and an intermediate trait was expressed in the offspring. Mendel’s work on the common pea plant proved that was not the case.

Mendel’s experiments

Mendel performed a series of rigorous experiments that looked at 7 different characteristics (e.g. flower color, seed color and seed shape), each with 2 different traits (e.g. purple flower and white flowers).

He established true-breeding lines for each characteristic. For example, one line of plants would produce only purple flowers and another only white. He then crossed individuals with two different traits to see the resulting trait of the offspring over three generations.

In his observations, Mendel found that in the first generation of offspring only one of the traits was ever expressed (e.g. purple flowers). After crossing the first generation of offspring with each other, Mendel found that approximately 75% of the second generation inherited the same trait as their parents (i.e. the purple flowers of the first generation of offspring). The remaining 25% expressed the second trait of the original parents (e.g. white flowers), the trait that appeared to be lost in the first generation of offspring.

Mendel’s conclusions

Following three generations of cross-breeding Mendel produced three significant conclusions regarding genetic inheritance. His first conclusion was that each trait is passed on unchanged to offspring via ‘units of inheritance’. These units are now known as ‘alleles’.

Mendel’s second conclusion, offspring inherit one allele from each parent for each characteristic. His third and final conclusion was that some alleles may not be expressed in an individual but can still be passed on to the next generation.

Mendel’s Laws of Inheritance

Law of Segregation – The alleles for each character segregate during gamete production so that each gamete will only have one of the two alleles for each gene.
Law of Independent Assortment – Pairs of alleles for each characteristic/gene segregate independently of each other.

Mendel’s work has been heavily built upon over the past 150 years and the field of genetics has come a long way since his pea experiments. His work set the foundation for our understanding of genetic inheritance in animals, plants and other complex organisms.

The process of inheritance is hugely important for understanding the complexity of life on Earth, in particular for its role in sexual reproduction and evolution . For this, Mendel’s contributions to science, biology and genetics are still widely recognized and applauded within the scientific community.

Alleles, genotype & phenotype

Alleles and genotypes are important foundations of genetics. An allele is a particular form of a gene and they are passed from parents to their offspring. A genotype is the combination of two alleles, one received from each parent.

The physical expression of a genotype is called the phenotype. The specific combination of the two alleles (the genotype) influences the physical expression (the phenotype) of the physical trait that the alleles carry information for. The phenotype can also be influenced by the environment

An allele is a particular form of one specific gene. When Gregor Mendel completed his experiments on peas he was crossing different traits of one characteristic, such as flower color.

Genetically, the variation in traits, e.g. purple flowers or white flowers, is caused by different alleles. In most cases in the plant and animal world, individuals have two alleles for each gene; one allele is inherited from their father and the second from their mother.

Depending on which alleles an individual has received will determine how their genes are expressed. For example, if two parents have blue eyes and pass the blue-eyed alleles onto their children, their children will also possess the alleles for blue eyes.

The genotype is the genetic combination of two alleles. If, for example, a child has received one brown-eye allele – represented by ‘B’ – and one blue-eye allele – represented by ‘b’ – then their genotype would be ‘Bb’. If, however, the child received two brown-eye alleles their genotype would be ‘BB’, and a child with two blue-eye alleles ‘bb’.

As previously mentioned, the brown-eye allele is dominant over the blue-eye allele so a child with the genotype ‘Bb’ would, in theory, have brown eyes, rather than blue or a mix between the two. Genotypes with two alleles that are the same, i.e. ‘BB’ and ‘bb’, are known as homozygous genotypes and genotypes with two different alleles are known as heterozygous genotypes.

The physical appearance of the genotype is called the phenotype. For example, children with the genotypes ‘BB’ and ‘Bb’ have brown-eye phenotypes, whereas a child with two blue-eye alleles and the genotype ‘bb’ has blue eyes and a blue-eye phenotype. The phenotype can also be influenced by the environment and sometimes certain alleles will be expressed in some environments but not in others. Therefore two individuals with the same genotype can sometimes have different phenotypes in they live in different environments.

Definitions:

Gene – a section of DNA that contains the genetic material for one characteristic
Allele – a particular form of a gene. One allele is received from each parent
Genotype – the combination of the two alleles that are received from an individual’s parents
Phenotype – the physical expression of the gene which is determined by both the genotype and the environment
Heterozygous – a genotype with two different alleles
Homozygous – a genotype with two of the same alleles

Punnet Squares

Last edited: 31 August 2020

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What Is A Research (Scientific) Hypothesis? A plain-language explainer + examples

By: Derek Jansen (MBA) | Reviewed By: Dr Eunice Rautenbach | June 2020

If you’re new to the world of research, or it’s your first time writing a dissertation or thesis, you’re probably noticing that the words “research hypothesis” and “scientific hypothesis” are used quite a bit, and you’re wondering what they mean in a research context .

“Hypothesis” is one of those words that people use loosely, thinking they understand what it means. However, it has a very specific meaning within academic research. So, it’s important to understand the exact meaning before you start hypothesizing.

Research Hypothesis 101

What is a hypothesis ?
What is a research hypothesis (scientific hypothesis)?
Requirements for a research hypothesis
Definition of a research hypothesis
The null hypothesis

What is a hypothesis?

Let’s start with the general definition of a hypothesis (not a research hypothesis or scientific hypothesis), according to the Cambridge Dictionary:

Hypothesis: an idea or explanation for something that is based on known facts but has not yet been proved.

In other words, it’s a statement that provides an explanation for why or how something works, based on facts (or some reasonable assumptions), but that has not yet been specifically tested . For example, a hypothesis might look something like this:

Hypothesis: sleep impacts academic performance.

This statement predicts that academic performance will be influenced by the amount and/or quality of sleep a student engages in – sounds reasonable, right? It’s based on reasonable assumptions , underpinned by what we currently know about sleep and health (from the existing literature). So, loosely speaking, we could call it a hypothesis, at least by the dictionary definition.

But that’s not good enough…

Unfortunately, that’s not quite sophisticated enough to describe a research hypothesis (also sometimes called a scientific hypothesis), and it wouldn’t be acceptable in a dissertation, thesis or research paper . In the world of academic research, a statement needs a few more criteria to constitute a true research hypothesis .

What is a research hypothesis?

A research hypothesis (also called a scientific hypothesis) is a statement about the expected outcome of a study (for example, a dissertation or thesis). To constitute a quality hypothesis, the statement needs to have three attributes – specificity , clarity and testability .

Let’s take a look at these more closely.

Need a helping hand?

Hypothesis Essential #1: Specificity & Clarity

A good research hypothesis needs to be extremely clear and articulate about both what’ s being assessed (who or what variables are involved ) and the expected outcome (for example, a difference between groups, a relationship between variables, etc.).

Let’s stick with our sleepy students example and look at how this statement could be more specific and clear.

Hypothesis: Students who sleep at least 8 hours per night will, on average, achieve higher grades in standardised tests than students who sleep less than 8 hours a night.

As you can see, the statement is very specific as it identifies the variables involved (sleep hours and test grades), the parties involved (two groups of students), as well as the predicted relationship type (a positive relationship). There’s no ambiguity or uncertainty about who or what is involved in the statement, and the expected outcome is clear.

Contrast that to the original hypothesis we looked at – “Sleep impacts academic performance” – and you can see the difference. “Sleep” and “academic performance” are both comparatively vague , and there’s no indication of what the expected relationship direction is (more sleep or less sleep). As you can see, specificity and clarity are key.

A good research hypothesis needs to be very clear about what’s being assessed and very specific about the expected outcome.

Hypothesis Essential #2: Testability (Provability)

A statement must be testable to qualify as a research hypothesis. In other words, there needs to be a way to prove (or disprove) the statement. If it’s not testable, it’s not a hypothesis – simple as that.

For example, consider the hypothesis we mentioned earlier:

Hypothesis: Students who sleep at least 8 hours per night will, on average, achieve higher grades in standardised tests than students who sleep less than 8 hours a night.

We could test this statement by undertaking a quantitative study involving two groups of students, one that gets 8 or more hours of sleep per night for a fixed period, and one that gets less. We could then compare the standardised test results for both groups to see if there’s a statistically significant difference.

Again, if you compare this to the original hypothesis we looked at – “Sleep impacts academic performance” – you can see that it would be quite difficult to test that statement, primarily because it isn’t specific enough. How much sleep? By who? What type of academic performance?

So, remember the mantra – if you can’t test it, it’s not a hypothesis 🙂

A good research hypothesis must be testable. In other words, you must able to collect observable data in a scientifically rigorous fashion to test it.

Defining A Research Hypothesis

You’re still with us? Great! Let’s recap and pin down a clear definition of a hypothesis.

A research hypothesis (or scientific hypothesis) is a statement about an expected relationship between variables, or explanation of an occurrence, that is clear, specific and testable.

So, when you write up hypotheses for your dissertation or thesis, make sure that they meet all these criteria. If you do, you’ll not only have rock-solid hypotheses but you’ll also ensure a clear focus for your entire research project.

What about the null hypothesis?

You may have also heard the terms null hypothesis , alternative hypothesis, or H-zero thrown around. At a simple level, the null hypothesis is the counter-proposal to the original hypothesis.

For example, if the hypothesis predicts that there is a relationship between two variables (for example, sleep and academic performance), the null hypothesis would predict that there is no relationship between those variables.

At a more technical level, the null hypothesis proposes that no statistical significance exists in a set of given observations and that any differences are due to chance alone.

And there you have it – hypotheses in a nutshell.

If you have any questions, be sure to leave a comment below and we’ll do our best to help you. If you need hands-on help developing and testing your hypotheses, consider our private coaching service , where we hold your hand through the research journey.

Psst... there’s more!

This post was based on one of our popular Research Bootcamps . If you're working on a research project, you'll definitely want to check this out ...

17 Comments

Very useful information. I benefit more from getting more information in this regard.

Very great insight,educative and informative. Please give meet deep critics on many research data of public international Law like human rights, environment, natural resources, law of the sea etc

In a book I read a distinction is made between null, research, and alternative hypothesis. As far as I understand, alternative and research hypotheses are the same. Can you please elaborate? Best Afshin

This is a self explanatory, easy going site. I will recommend this to my friends and colleagues.

Very good definition. How can I cite your definition in my thesis? Thank you. Is nul hypothesis compulsory in a research?

It’s a counter-proposal to be proven as a rejection

Please what is the difference between alternate hypothesis and research hypothesis?

It is a very good explanation. However, it limits hypotheses to statistically tasteable ideas. What about for qualitative researches or other researches that involve quantitative data that don’t need statistical tests?

In qualitative research, one typically uses propositions, not hypotheses.

could you please elaborate it more

I’ve benefited greatly from these notes, thank you.

This is very helpful

well articulated ideas are presented here, thank you for being reliable sources of information

Excellent. Thanks for being clear and sound about the research methodology and hypothesis (quantitative research)

I have only a simple question regarding the null hypothesis. – Is the null hypothesis (Ho) known as the reversible hypothesis of the alternative hypothesis (H1? – How to test it in academic research?

this is very important note help me much more

Hi” best wishes to you and your very nice blog”

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How to Write a Great Hypothesis

Hypothesis Definition, Format, Examples, and Tips

Verywell / Alex Dos Diaz

The Scientific Method

Hypothesis Format

Falsifiability of a hypothesis.

Operationalization

Hypothesis Types

Hypotheses examples.

Collecting Data

A hypothesis is a tentative statement about the relationship between two or more variables. It is a specific, testable prediction about what you expect to happen in a study. It is a preliminary answer to your question that helps guide the research process.

Consider a study designed to examine the relationship between sleep deprivation and test performance. The hypothesis might be: "This study is designed to assess the hypothesis that sleep-deprived people will perform worse on a test than individuals who are not sleep-deprived."

At a Glance

A hypothesis is crucial to scientific research because it offers a clear direction for what the researchers are looking to find. This allows them to design experiments to test their predictions and add to our scientific knowledge about the world. This article explores how a hypothesis is used in psychology research, how to write a good hypothesis, and the different types of hypotheses you might use.

The Hypothesis in the Scientific Method

In the scientific method , whether it involves research in psychology, biology, or some other area, a hypothesis represents what the researchers think will happen in an experiment. The scientific method involves the following steps:

Forming a question
Performing background research
Creating a hypothesis
Designing an experiment
Collecting data
Analyzing the results
Drawing conclusions
Communicating the results

The hypothesis is a prediction, but it involves more than a guess. Most of the time, the hypothesis begins with a question which is then explored through background research. At this point, researchers then begin to develop a testable hypothesis.

Unless you are creating an exploratory study, your hypothesis should always explain what you expect to happen.

In a study exploring the effects of a particular drug, the hypothesis might be that researchers expect the drug to have some type of effect on the symptoms of a specific illness. In psychology, the hypothesis might focus on how a certain aspect of the environment might influence a particular behavior.

Remember, a hypothesis does not have to be correct. While the hypothesis predicts what the researchers expect to see, the goal of the research is to determine whether this guess is right or wrong. When conducting an experiment, researchers might explore numerous factors to determine which ones might contribute to the ultimate outcome.

In many cases, researchers may find that the results of an experiment do not support the original hypothesis. When writing up these results, the researchers might suggest other options that should be explored in future studies.

In many cases, researchers might draw a hypothesis from a specific theory or build on previous research. For example, prior research has shown that stress can impact the immune system. So a researcher might hypothesize: "People with high-stress levels will be more likely to contract a common cold after being exposed to the virus than people who have low-stress levels."

In other instances, researchers might look at commonly held beliefs or folk wisdom. "Birds of a feather flock together" is one example of folk adage that a psychologist might try to investigate. The researcher might pose a specific hypothesis that "People tend to select romantic partners who are similar to them in interests and educational level."

Elements of a Good Hypothesis

So how do you write a good hypothesis? When trying to come up with a hypothesis for your research or experiments, ask yourself the following questions:

Is your hypothesis based on your research on a topic?
Can your hypothesis be tested?
Does your hypothesis include independent and dependent variables?

Before you come up with a specific hypothesis, spend some time doing background research. Once you have completed a literature review, start thinking about potential questions you still have. Pay attention to the discussion section in the journal articles you read . Many authors will suggest questions that still need to be explored.

How to Formulate a Good Hypothesis

To form a hypothesis, you should take these steps:

Collect as many observations about a topic or problem as you can.
Evaluate these observations and look for possible causes of the problem.
Create a list of possible explanations that you might want to explore.
After you have developed some possible hypotheses, think of ways that you could confirm or disprove each hypothesis through experimentation. This is known as falsifiability.

In the scientific method , falsifiability is an important part of any valid hypothesis. In order to test a claim scientifically, it must be possible that the claim could be proven false.

Students sometimes confuse the idea of falsifiability with the idea that it means that something is false, which is not the case. What falsifiability means is that if something was false, then it is possible to demonstrate that it is false.

One of the hallmarks of pseudoscience is that it makes claims that cannot be refuted or proven false.

The Importance of Operational Definitions

A variable is a factor or element that can be changed and manipulated in ways that are observable and measurable. However, the researcher must also define how the variable will be manipulated and measured in the study.

Operational definitions are specific definitions for all relevant factors in a study. This process helps make vague or ambiguous concepts detailed and measurable.

For example, a researcher might operationally define the variable " test anxiety " as the results of a self-report measure of anxiety experienced during an exam. A "study habits" variable might be defined by the amount of studying that actually occurs as measured by time.

These precise descriptions are important because many things can be measured in various ways. Clearly defining these variables and how they are measured helps ensure that other researchers can replicate your results.

Replicability

One of the basic principles of any type of scientific research is that the results must be replicable.

Replication means repeating an experiment in the same way to produce the same results. By clearly detailing the specifics of how the variables were measured and manipulated, other researchers can better understand the results and repeat the study if needed.

Some variables are more difficult than others to define. For example, how would you operationally define a variable such as aggression ? For obvious ethical reasons, researchers cannot create a situation in which a person behaves aggressively toward others.

To measure this variable, the researcher must devise a measurement that assesses aggressive behavior without harming others. The researcher might utilize a simulated task to measure aggressiveness in this situation.

Hypothesis Checklist

Does your hypothesis focus on something that you can actually test?
Does your hypothesis include both an independent and dependent variable?
Can you manipulate the variables?
Can your hypothesis be tested without violating ethical standards?

The hypothesis you use will depend on what you are investigating and hoping to find. Some of the main types of hypotheses that you might use include:

Simple hypothesis : This type of hypothesis suggests there is a relationship between one independent variable and one dependent variable.
Complex hypothesis : This type suggests a relationship between three or more variables, such as two independent and dependent variables.
Null hypothesis : This hypothesis suggests no relationship exists between two or more variables.
Alternative hypothesis : This hypothesis states the opposite of the null hypothesis.
Statistical hypothesis : This hypothesis uses statistical analysis to evaluate a representative population sample and then generalizes the findings to the larger group.
Logical hypothesis : This hypothesis assumes a relationship between variables without collecting data or evidence.

A hypothesis often follows a basic format of "If {this happens} then {this will happen}." One way to structure your hypothesis is to describe what will happen to the dependent variable if you change the independent variable .

The basic format might be: "If {these changes are made to a certain independent variable}, then we will observe {a change in a specific dependent variable}."

A few examples of simple hypotheses:

"Students who eat breakfast will perform better on a math exam than students who do not eat breakfast."
"Students who experience test anxiety before an English exam will get lower scores than students who do not experience test anxiety."
"Motorists who talk on the phone while driving will be more likely to make errors on a driving course than those who do not talk on the phone."
"Children who receive a new reading intervention will have higher reading scores than students who do not receive the intervention."

Examples of a complex hypothesis include:

"People with high-sugar diets and sedentary activity levels are more likely to develop depression."
"Younger people who are regularly exposed to green, outdoor areas have better subjective well-being than older adults who have limited exposure to green spaces."

Examples of a null hypothesis include:

"There is no difference in anxiety levels between people who take St. John's wort supplements and those who do not."
"There is no difference in scores on a memory recall task between children and adults."
"There is no difference in aggression levels between children who play first-person shooter games and those who do not."

Examples of an alternative hypothesis:

"People who take St. John's wort supplements will have less anxiety than those who do not."
"Adults will perform better on a memory task than children."
"Children who play first-person shooter games will show higher levels of aggression than children who do not."

Collecting Data on Your Hypothesis

Once a researcher has formed a testable hypothesis, the next step is to select a research design and start collecting data. The research method depends largely on exactly what they are studying. There are two basic types of research methods: descriptive research and experimental research.

Descriptive Research Methods

Descriptive research such as case studies , naturalistic observations , and surveys are often used when conducting an experiment is difficult or impossible. These methods are best used to describe different aspects of a behavior or psychological phenomenon.

Once a researcher has collected data using descriptive methods, a correlational study can examine how the variables are related. This research method might be used to investigate a hypothesis that is difficult to test experimentally.

Experimental Research Methods

Experimental methods are used to demonstrate causal relationships between variables. In an experiment, the researcher systematically manipulates a variable of interest (known as the independent variable) and measures the effect on another variable (known as the dependent variable).

Unlike correlational studies, which can only be used to determine if there is a relationship between two variables, experimental methods can be used to determine the actual nature of the relationship—whether changes in one variable actually cause another to change.

The hypothesis is a critical part of any scientific exploration. It represents what researchers expect to find in a study or experiment. In situations where the hypothesis is unsupported by the research, the research still has value. Such research helps us better understand how different aspects of the natural world relate to one another. It also helps us develop new hypotheses that can then be tested in the future.

Thompson WH, Skau S. On the scope of scientific hypotheses . R Soc Open Sci . 2023;10(8):230607. doi:10.1098/rsos.230607

Taran S, Adhikari NKJ, Fan E. Falsifiability in medicine: what clinicians can learn from Karl Popper [published correction appears in Intensive Care Med. 2021 Jun 17;:]. Intensive Care Med . 2021;47(9):1054-1056. doi:10.1007/s00134-021-06432-z

Eyler AA. Research Methods for Public Health . 1st ed. Springer Publishing Company; 2020. doi:10.1891/9780826182067.0004

Nosek BA, Errington TM. What is replication ? PLoS Biol . 2020;18(3):e3000691. doi:10.1371/journal.pbio.3000691

Aggarwal R, Ranganathan P. Study designs: Part 2 - Descriptive studies . Perspect Clin Res . 2019;10(1):34-36. doi:10.4103/picr.PICR_154_18

Nevid J. Psychology: Concepts and Applications. Wadworth, 2013.

By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

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Wobble Hypothesis (With Diagram) | Genetics

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In this article we will discuss about the concept of wobble hypothesis.

Crick (1966) proposed the ‘wobble hypothesis’ to explain the degeneracy of the genetic code. Except for tryptophan and methionine, more than one codons direct the synthesis of one amino acid. There are 61 codons that synthesise amino acids, therefore, there must be 61 tRNAs each having different anticodons. But the total number of tRNAs is less than 61.

This may be explained that the anticodons of some tRNA read more than one codon. In addition, identity of the third codon seems to be unimportant. For example CGU, CGC, CGA and CGG all code for arginine. It appears that CG specifies arginine and the third letter is not important. Conventionally, the codons are written from 5′ end to 3′ end.

Therefore, the first and second bases specify amino acids in some cases. According to the Wobble hypothesis, only the first and second bases of the triple codon on 5′ → ‘3 mRNA pair with the bases of the anticodon of tRNA i.e A with U, or G with C.

The pairing of the third base varies according to the base at this position, for example G may pair with U. The conventional pairing (A = U, G = C) is known as Watson-Crick pairing (Fig. 7.1) and the second abnormal pairing is called wobble pairing.

This was observed from the discovery that the anticodon of yeast alanine-tRNA contains the nucleoside inosine (a deamination product of adenosine) in the first position (5′ → 3′) that paired with the third base of the codon (5′ → 3′). Inosine was also found at the first position in other tRNAs e.g. isoleucine and serine.

The purine, inosine, is a wobble nucleotide and is similar to guanine which normally pairs with A, U and C. For example a glycine-tRNA with anticodon 5′-ICC-3′ will pair with glycine codons GGU, GGC, GGA and GGG (Fig 7.2). Similarly, a seryl-tRNA with anticodon 5′-IGA-3′ pairs with serine codons UCC, UCU and UCA (5-3′). The U at the wobble position will be able to pair with an adenine or a guanine.

According to Wobble hypothesis, allowed base pairings are given in Table 7.5:

Due to the Wobble base pairing one tRNA becomes able to recognise more than one codons for an individual amino acid. By direct sequence of several tRNA molecules, the wobble hypothesis is confirmed which explains the pattern of redundancy in genetic code in some anticodons (e.g. the anticodons containing U, I and G in the first position in 5’→ 3′ direction)

The seryl-tRNA anticodon (UCG) 5′-GCU-3′ base pairs with two serine codons, 5′-AGC-3′ and 5′-AGU-3′. Generally, Watson-Crick pairing occurs between AGC and GCU. However, in AGU and GCU pairing, hydrogen bonds are formed between G and U. Such abnormal pairing called ‘Wobble pairing’ is given in Table 7.5.

Three types of wobble pairings have been proposed:

(i) U in the wobble position of the tRNA anticodon pairs with A or G of codon,

(ii) G pairs with U or C, and

(iii) 1 pairs with A, U or C.

Short Notes on Anticodons | Genetics
Genetic Code: Degeneracy and Universality | Protein

Microbiology , Genetics , Wobble Hypothesis , Concept of Wobble Hypothesis

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Definition of hypothesis

Did you know.

The Difference Between Hypothesis and Theory

A hypothesis is an assumption, an idea that is proposed for the sake of argument so that it can be tested to see if it might be true.

In the scientific method, the hypothesis is constructed before any applicable research has been done, apart from a basic background review. You ask a question, read up on what has been studied before, and then form a hypothesis.

A hypothesis is usually tentative; it's an assumption or suggestion made strictly for the objective of being tested.

A theory , in contrast, is a principle that has been formed as an attempt to explain things that have already been substantiated by data. It is used in the names of a number of principles accepted in the scientific community, such as the Big Bang Theory . Because of the rigors of experimentation and control, it is understood to be more likely to be true than a hypothesis is.

In non-scientific use, however, hypothesis and theory are often used interchangeably to mean simply an idea, speculation, or hunch, with theory being the more common choice.

Since this casual use does away with the distinctions upheld by the scientific community, hypothesis and theory are prone to being wrongly interpreted even when they are encountered in scientific contexts—or at least, contexts that allude to scientific study without making the critical distinction that scientists employ when weighing hypotheses and theories.

The most common occurrence is when theory is interpreted—and sometimes even gleefully seized upon—to mean something having less truth value than other scientific principles. (The word law applies to principles so firmly established that they are almost never questioned, such as the law of gravity.)

This mistake is one of projection: since we use theory in general to mean something lightly speculated, then it's implied that scientists must be talking about the same level of uncertainty when they use theory to refer to their well-tested and reasoned principles.

The distinction has come to the forefront particularly on occasions when the content of science curricula in schools has been challenged—notably, when a school board in Georgia put stickers on textbooks stating that evolution was "a theory, not a fact, regarding the origin of living things." As Kenneth R. Miller, a cell biologist at Brown University, has said , a theory "doesn’t mean a hunch or a guess. A theory is a system of explanations that ties together a whole bunch of facts. It not only explains those facts, but predicts what you ought to find from other observations and experiments.”

While theories are never completely infallible, they form the basis of scientific reasoning because, as Miller said "to the best of our ability, we’ve tested them, and they’ve held up."

proposition
supposition

hypothesis , theory , law mean a formula derived by inference from scientific data that explains a principle operating in nature.

hypothesis implies insufficient evidence to provide more than a tentative explanation.

theory implies a greater range of evidence and greater likelihood of truth.

law implies a statement of order and relation in nature that has been found to be invariable under the same conditions.

Examples of hypothesis in a Sentence

These examples are programmatically compiled from various online sources to illustrate current usage of the word 'hypothesis.' Any opinions expressed in the examples do not represent those of Merriam-Webster or its editors. Send us feedback about these examples.

Word History

Greek, from hypotithenai to put under, suppose, from hypo- + tithenai to put — more at do

1641, in the meaning defined at sense 1a

Phrases Containing hypothesis

counter - hypothesis
nebular hypothesis
null hypothesis
planetesimal hypothesis
Whorfian hypothesis

Articles Related to hypothesis

This is the Difference Between a...

This is the Difference Between a Hypothesis and a Theory

In scientific reasoning, they're two completely different things

Dictionary Entries Near hypothesis

hypothermia

hypothesize

Cite this Entry

“Hypothesis.” Merriam-Webster.com Dictionary , Merriam-Webster, https://www.merriam-webster.com/dictionary/hypothesis. Accessed 25 Aug. 2024.

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Introduction

Chemical structure of genes

Gene transcription and translation, gene regulation, gene mutations.

What are mutation hotspots?

DNA strand illustration art, double helix, deoxyribonucleic acid, genetics

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Table Of Contents

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gene , unit of hereditary information that occupies a fixed position (locus) on a chromosome . Genes achieve their effects by directing the synthesis of proteins .

In eukaryotes (such as animals , plants , and fungi ), genes are contained within the cell nucleus . The mitochondria (in animals) and the chloroplasts (in plants) also contain small subsets of genes distinct from the genes found in the nucleus. In prokaryotes (organisms lacking a distinct nucleus, such as bacteria ), genes are contained in a single chromosome that is free-floating in the cell cytoplasm . Many bacteria also contain plasmids —extrachromosomal genetic elements with a small number of genes.

Find out what an organism is and consider which one is the world's smallest

The number of genes in an organism’s genome (the entire set of chromosomes) varies significantly between species. For example, whereas the human genome contains an estimated 20,000 to 25,000 genes, the genome of the bacterium Escherichia coli O157:H7 houses precisely 5,416 genes. Arabidopsis thaliana —the first plant for which a complete genomic sequence was recovered—has roughly 25,500 genes; its genome is one of the smallest known to plants. Among extant independently replicating organisms, the bacterium Mycoplasma genitalium has the fewest number of genes, just 517.

A brief treatment of genes follows. For full treatment, see heredity .

Genes are composed of deoxyribonucleic acid ( DNA ), except in some viruses , which have genes consisting of a closely related compound called ribonucleic acid ( RNA ). A DNA molecule is composed of two chains of nucleotides that wind about each other to resemble a twisted ladder. The sides of the ladder are made up of sugars and phosphates, and the rungs are formed by bonded pairs of nitrogenous bases. These bases are adenine (A), guanine (G), cytosine (C), and thymine (T). An A on one chain bonds to a T on the other (thus forming an A–T ladder rung); similarly, a C on one chain bonds to a G on the other. If the bonds between the bases are broken, the two chains unwind , and free nucleotides within the cell attach themselves to the exposed bases of the now-separated chains. The free nucleotides line up along each chain according to the base-pairing rule—A bonds to T, C bonds to G. This process results in the creation of two identical DNA molecules from one original and is the method by which hereditary information is passed from one generation of cells to the next.

The sequence of bases along a strand of DNA determines the genetic code . When the product of a particular gene is needed, the portion of the DNA molecule that contains that gene will split. Through the process of transcription , a strand of RNA with bases complementary to those of the gene is created from the free nucleotides in the cell. (RNA has the base uracil [U] instead of thymine, so A and U form base pairs during RNA synthesis.) This single chain of RNA, called messenger RNA (mRNA), then passes to the organelles called ribosomes , where the process of translation , or protein synthesis, takes place. During translation, a second type of RNA, transfer RNA (tRNA), matches up the nucleotides on mRNA with specific amino acids . Each set of three nucleotides codes for one amino acid. The series of amino acids built according to the sequence of nucleotides forms a polypeptide chain ; all proteins are made from one or more linked polypeptide chains.

Experiments conducted in the 1940s indicated one gene being responsible for the assembly of one enzyme , or one polypeptide chain. This is known as the one gene–one enzyme hypothesis . However, since this discovery, it has been realized that not all genes encode an enzyme and that some enzymes are made up of several short polypeptides encoded by two or more genes.

Experiments have shown that many of the genes within the cells of organisms are inactive much or even all of the time. Thus, at any time, in both eukaryotes and prokaryotes, it seems that a gene can be switched on or off. The regulation of genes between eukaryotes and prokaryotes differs in important ways.

The process by which genes are activated and deactivated in bacteria is well characterized. Bacteria have three types of genes: structural, operator, and regulator. Structural genes code for the synthesis of specific polypeptides. Operator genes contain the code necessary to begin the process of transcribing the DNA message of one or more structural genes into mRNA. Thus, structural genes are linked to an operator gene in a functional unit called an operon . Ultimately, the activity of the operon is controlled by a regulator gene , which produces a small protein molecule called a repressor . The repressor binds to the operator gene and prevents it from initiating the synthesis of the protein called for by the operon. The presence or absence of certain repressor molecules determines whether the operon is off or on. As mentioned, this model applies to bacteria.

The genes of eukaryotes, which do not have operons, are regulated independently. The series of events associated with gene expression in higher organisms involves multiple levels of regulation and is often influenced by the presence or absence of molecules called transcription factors . These factors influence the fundamental level of gene control, which is the rate of transcription , and may function as activators or enhancers. Specific transcription factors regulate the production of RNA from genes at certain times and in certain types of cells. Transcription factors often bind to the promoter, or regulatory region, found in the genes of higher organisms. Following transcription, introns (noncoding nucleotide sequences) are excised from the primary transcript through processes known as editing and splicing. The result of these processes is a functional strand of mRNA. For most genes this is a routine step in the production of mRNA, but in some genes there are multiple ways to splice the primary transcript, resulting in different mRNAs, which in turn result in different proteins. Some genes also are controlled at the translational and posttranslational levels.

Mutations occur when the number or order of bases in a gene is disrupted. Nucleotides can be deleted, doubled, rearranged, or replaced, each alteration having a particular effect. Mutation generally has little or no effect, but, when it does alter an organism, the change may be lethal or cause disease. A beneficial mutation will rise in frequency within a population until it becomes the norm.

For more information on the influence of genetic mutations in humans and other organisms, see human genetic disease and evolution .

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What is Heterosis?

An introduction to heterosis.

Plant breeding is the application of genetic principles in developing new plant varieties, known as cultivar development, crop improvement, and seed improvement. Heterosis in plant breeding is described as the superiority of an F 1 hybrid over both parents in terms of yield or other characteristics. Heterosis contributes to increased vigour, size, growth rate, yield, or other attributes. However, in exceptional cases, the hybrid may be inferior to the weaker parent. The methods of estimation of heterosis and the genetic basis of heterosis are described here.

Heterosis Definition

Heterosis refers to the superiority of F, hybrids over their parents in one or more characteristics. The word hybrid vigour is a synonym for heterosis. George Harrison Shull coined the term heterosis in 1914.

Some features of heterosis are described below.

Superiority Over Parents: Heterosis results in superiority over its parents in adaptability, yield, quality, disease resistance, maturity, and general vigour. Positive heterosis is often seen as desirable. However, in some circumstances, negative heterosis is preferable. Negative heterosis for plant height, maturity time, and hazardous chemicals, for example, is beneficial in many circumstances since it demonstrates superiority over the parents. In most agricultural plants , heterosis of 40% or more over the superior parent is regarded as substantial from a practical standpoint.

Confined to F 1 : Heterosis is restricted to the F 1 , resulting in the production of a cross. As a result of segregation and recombination, it diminishes and vanishes in F 1 and later generations of a cross. As a result, heterosis is linked to the F 1 generation.

Genetic Control: Nuclear genes regulate the expression of heterosis. In certain cases, heterosis is caused by the interaction of nuclear genes and cytoplasm.

Reproducible: Once recognised, heterosis may be easily reproduced in a specific environment. The expression of heterosis, on the other hand, is more evident in the region of hybrid adaptability.

Relationship with SCA: Heterosis shows a positive relationship with specific combining ability (SCA) variation. The SCA is a measure of dominance variance, and having a high degree of dominance variance is required to carry out a heterosis breeding program.

Heterozygosity Effect: The degree of heterosis is related to heterozygosity since dominance variance is related to heterozygosity. The dominance effects should be most significant in cross-pollinated species and least significant in self-pollinated species. As a result, heterosis occurs more frequently in cross-pollinated crops than in self-pollinated crops.

Masks Recessive Genes: When there is heterosis, the beneficial influence of dominant genes masks harmful recessive genes. As a result, recessive mutant genes are concealed in heterozygous individuals.

Low Frequency: The frequency of good heterotic pairings is quite low. Only a few good heterotic pairings are discovered after screening thousands of F 1 crosses. All of the F 1 crosses lack desired heterosis.

Genetic Basis of Heterosis

To explain the mechanism of heterosis, two significant theories have been suggested. The first is the dominance theory, while the second is the overdominance hypothesis . Epistasis is also probably related to heterosis. As a result, there are three potential genetic origins of heterosis, which are:

Overdominance

Dominance Hypothesis

Davenport (1908), Bruce (1910), and Keeble and Pellew (1910) proposed this hypothesis. This is the most commonly accepted explanation for heterosis. According to this theory, heterosis is caused by the superiority of dominant alleles when recessive alleles are harmful. The hybrid shows heterosis because the deleterious recessive genes of one parent are concealed by the dominant genes of the other parent. Both parents have different dominant genes.

Assume one parent's genetic make-up is AABBccdd and the other's is aabbCCDD. A hybrid of these two parents will have four dominant genes, giving it superiority over both parents having two dominant genes. Thus, heterosis is proportional to the number of dominant genes contributed by each parent.

Overdominance Hypothesis

Shull and East separately presented this hypothesis in 1908. This hypothesis is known as stimulation of heterozygosis, cumulative action of divergent alleles, single-gene heterosis, super-dominance, and overdominance. Even though Shull and East proposed this hypothesis in 1908, Hull used the word overdominance in 1945 when working on maize. According to this theory, heterosis is caused by the heterozygote's superiority over both of its homozygous parents. Thus, heterosis is proportional to heterozygosity.

The superiority of the heterozygote over both homozygotes may result from:

The production of a superior hybrid substance in the heterozygote that is entirely different from either of the homozygous.

Greater buffering capacity in the heterozygote due to cumulative action of divergent alleles or stimulation of divergent alleles. East explained this theory in 1936, suggesting a set of alleles a1, a2, a3, and a4 with steadily increasing divergence in function. As a result, a combination of more divergent alleles will have more heterosis than a combination of less divergent alleles. Combinations of a1a4, for example, demonstrate more heterosis than combinations of a1a2, a2a3, and a3a4. Overdominance has been reported in barley.

The interaction of alleles from two or more distinct loci is referred to as epistasis. It is sometimes referred to as nonallelic interaction. Non-allelic interactions are classified into three types: additive x additive, dominance x dominance, and additive x dominance. It is widely documented that the presence and size of non-interaction have a positive relationship with the incidence and magnitude of heterosis. Epistasis, especially dominance effects (dominance x dominance), may lead to heterosis. Cotton and maize have both shown this (Moll and Stuber 1974). Various biometrical models can detect or estimate epistasis.

Methods of Estimation of Heterosis

Heterosis is estimated in three ways:

Over mid parent

Over better parent

Over a commercial hybrid

Thus, based on estimation, heterosis is classified into three types, as shown below.

Average Heterosis: When the heterosis is estimated over the mid parent, i.e., the average value of the two parents, it is known as average heterosis, which is calculated as Average Heterosis= {(F 1 -MP)/MP} X 100

Where F 1 is the mean value of F 1 and MP is the mean value of the two parents involved in the cross.

Heterobeltiosis: It occurs when the heterosis is estimated to be superior or better than the superior or a better parent. It is known as heterobeltiosis. It is calculated as follows:

Heterobeltiosis= {((F 1 -BP)/BP) X 100}

BP is the mean value (across replications) of the cross's better parents.

Useful Heterosis: Meredith and Bridge coined the term useful heterosis in 1972. It is also known as economic heterosis and refers to F 1 's superiority over the normal commercial check type. This sort of heterosis has direct use in plant breeding. It is calculated as follows.

Useful heterosis= {((F 1 -CC)/CC) X 100}

Where CC is the mean value (across replications) of the local commercial hybrid. Over the conventional commercial hybrid, heterosis is sometimes worked out.

Standard Heterosis: Heterosis is estimated in crops where hybrids are already available for comparison. Standard heterosis refers to this sort of heterosis. This is also directly applicable in plant breeding. It is calculated as follows.

{(F 1 -SH)/SH} X 100 = Standard heterosis

Where SH is the mean value of the standard hybrid.

Heterosis refers to the superiority of F 1 hybrids in one or more characteristics over their parents. The term hybrid vigour is used interchangeably with heterosis. Dr. G. H. Shull coined the term "heterosis" in 1914. Heterosis is the process by which a less vigorous organism is turned into a more vigorous organism by absorbing DNA from the media.

FAQs on What is Heterosis?

1. What are the three main types of heterosis?

Individual, maternal, and paternal heterosis are the three types of heterosis. According to Bourdon (2000), retained heterosis is the improvement in the performance of crossbred progeny over purebred parents. Individual heterosis refers to the advantage of the crossbred individual over the purebred average. A Limousin x Hereford calf, for example, may grow faster than a purebred Limousin and Hereford's calf.

Maternal heterosis is defined as a cow's output exceeding the average of her parent breeds, such as in terms of maternal ability, reproduction, longevity, calf survivability, pounds of calf weaned, and younger age at puberty.

Paternal heterosis is the improvement of the bull's productive and reproductive characteristics. Reduced puberty age, increased scrotal circumference, improved sperm concentration, increased pregnancy rate, and weaning rate when mated to cows are examples.

2. What are the differences between heterosis and inbreeding depression?

The primary distinction between heterosis and inbreeding depression is that heterosis is characterized by beneficial augmentations of phenotypic trait values in offspring of genetically distant parents. Inbreeding depression, on the other hand, is characterized by negative reductions in phenotypic trait values in the offspring of genetically related parents. As a result, heterosis results from outbreeding enhancement, whereas inbreeding depression results from inbreeding. Furthermore, heterosis is caused by increased offspring heterozygosity, whereas inbreeding depression is caused by increased offspring homozygosity.

3. What are the uses of heterosis?

Heterosis is typically used to increase vigour, size, growth rate, yield, etc. Uses can be in the following form.

Increased yield

Increased reproductive ability

Increase in size and vigour

Better quality

Greater adaptability

Heterosis is also increased by a rise in the rate of DNA reduplication, transcription, and translation, enzymatic activity, other regulatory systems, and the formation of hybrid protein molecules. However, in exceptional cases, the hybrid may be inferior to the weaker parent.

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Definition of hypothesis noun from the Oxford Advanced Learner's Dictionary

to formulate/confirm a hypothesis
a hypothesis about the function of dreams
There is little evidence to support these hypotheses.
formulate/advance a theory/hypothesis
build/construct/create/develop a simple/theoretical/mathematical model
develop/establish/provide/use a theoretical/conceptual framework
advance/argue/develop the thesis that…
explore an idea/a concept/a hypothesis
make a prediction/an inference
base a prediction/your calculations on something
investigate/evaluate/accept/challenge/reject a theory/hypothesis/model
design an experiment/a questionnaire/a study/a test
do research/an experiment/an analysis
make observations/measurements/calculations
carry out/conduct/perform an experiment/a test/a longitudinal study/observations/clinical trials
run an experiment/a simulation/clinical trials
repeat an experiment/a test/an analysis
replicate a study/the results/the findings
observe/study/examine/investigate/assess a pattern/a process/a behaviour
fund/support the research/project/study
seek/provide/get/secure funding for research
collect/gather/extract data/information
yield data/evidence/similar findings/the same results
analyse/examine the data/soil samples/a specimen
consider/compare/interpret the results/findings
fit the data/model
confirm/support/verify a prediction/a hypothesis/the results/the findings
prove a conjecture/hypothesis/theorem
draw/make/reach the same conclusions
read/review the records/literature
describe/report an experiment/a study
present/publish/summarize the results/findings
present/publish/read/review/cite a paper in a scientific journal
Her hypothesis concerns the role of electromagnetic radiation.
Her study is based on the hypothesis that language simplification is possible.
It is possible to make a hypothesis on the basis of this graph.
None of the hypotheses can be rejected at this stage.
Scientists have proposed a bold hypothesis.
She used this data to test her hypothesis
The hypothesis predicts that children will perform better on task A than on task B.
The results confirmed his hypothesis on the use of modal verbs.
These observations appear to support our working hypothesis.
a speculative hypothesis concerning the nature of matter
an interesting hypothesis about the development of language
Advances in genetics seem to confirm these hypotheses.
His hypothesis about what dreams mean provoked a lot of debate.
Research supports the hypothesis that language skills are centred in the left side of the brain.
The survey will be used to test the hypothesis that people who work outside the home are fitter and happier.
This economic model is really a working hypothesis.
speculative
concern something
be based on something
predict something
on a/the hypothesis
hypothesis about
hypothesis concerning

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It would be pointless to engage in hypothesis before we have the facts.

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Hypothesis
PPT
Gene for Gene hypothesis
13 Different Types of Hypothesis (2024)
Research Hypothesis: Definition, Types, Examples and Quick Tips
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COMMENTS

Genetics and Statistical Analysis
The key is statistical examination, which allows you to determine whether your data are consistent with your hypothesis. For instance, when performing a genetic cross, the chi-square test allows ...
Hypothesis
Hypothesis is an idea or prediction that scientists make before they do experiments. Click to learn about its types, and importance of hypotheses in research and science. Take the quiz!
The Evolving Definition of the Term "Gene"
Abstract. This paper presents a history of the changing meanings of the term "gene," over more than a century, and a discussion of why this word, so crucial to genetics, needs redefinition today. In this account, the first two phases of 20th century genetics are designated the "classical" and the "neoclassical" periods, and the ...
Scientific hypothesis
hypothesis. science. scientific hypothesis, an idea that proposes a tentative explanation about a phenomenon or a narrow set of phenomena observed in the natural world. The two primary features of a scientific hypothesis are falsifiability and testability, which are reflected in an "If…then" statement summarizing the idea and in the ...
Gregor Mendel and the Principles of Inheritance
Gregor Mendel's principles of inheritance form the cornerstone of modern genetics. So just what are they? When looking at the figure, notice that for each F 1 plant, the self-fertilization ...
What is a Gene? Colinearity and Transcription Units
In 1958, Francis Crick's sequence hypothesis finally provided an answer to the question: what is a gene? Why is this definition now considered overly simplistic? Roberts and Sharp also noted that ...
What is a Hypothesis
Definition: Hypothesis is an educated guess or proposed explanation for a phenomenon, based on some initial observations or data. It is a tentative statement that can be tested and potentially proven or disproven through further investigation and experimentation. Hypothesis is often used in scientific research to guide the design of experiments ...
What Are Genes, DNA, and Chromosomes?
Genes, DNA, and chromosomes make up the human genome. Learn the role they play in genetics, inheritance, physical traits, and your risk of disease.
Genetic Inheritance
Genetic inheritance. Genetic inheritance is a basic principle of genetics and explains how characteristics are passed from one generation to the next. Genetic inheritance occurs due to genetic material, in the form of DNA, being passed from parents to their offspring. When organisms reproduce, all the information for growth, survival, and ...
Hypothesis
hypothesis, something supposed or taken for granted, with the object of following out its consequences (Greek hypothesis, "a putting under," the Latin equivalent being suppositio ). Discussion with Kara Rogers of how the scientific model is used to test a hypothesis or represent a theory. Kara Rogers, senior biomedical sciences editor of ...
What Is A Research Hypothesis? A Simple Definition
Learn exactly what a research hypothesis (or scientific hypothesis) is with Grad Coach's clear, plain-language definition, including loads of examples.
Genetics
Genetics, study of heredity in general and of genes in particular. Genetics forms one of the central pillars of biology and overlaps with many other areas, such as agriculture, medicine, and biotechnology. Learn more about the history, biology, areas of study, and methods of genetics.
Multiple Factor Hypothesis (With Example)
ADVERTISEMENTS: In this article we will discuss about the multiple factor hypothesis. Laws of heredity by Mendel offer a simple and correct explanation of qualitative difference among plants and animals such as the flower colour, red or white and the seed colour, either yellow or green. But certain characters are quantitative instead of being qualitative […]
Hypothesis: Definition, Examples, and Types
A hypothesis is a tentative statement about the relationship between two or more variables. Explore examples and learn how to format your research hypothesis.
Wobble Hypothesis (With Diagram)
Wobble Hypothesis (With Diagram) | Genetics. In this article we will discuss about the concept of wobble hypothesis. Crick (1966) proposed the 'wobble hypothesis' to explain the degeneracy of the genetic code. Except for tryptophan and methionine, more than one codons direct the synthesis of one amino acid. There are 61 codons that ...
Lyon hypothesis Definition & Meaning
Ly· on hypothesis ˈlī-ən-. : a hypothesis explaining why the phenotypic effect of the X chromosome is the same in the mammalian female which has two X chromosomes as it is in the male which has only one X chromosome: one of each two somatic X chromosomes in mammalian females is selected at random and inactivated early in embryonic development.
Hypothesis Definition & Meaning
hypothesis: [noun] an assumption or concession made for the sake of argument. an interpretation of a practical situation or condition taken as the ground for action.
Gene
gene, unit of hereditary information that occupies a fixed position (locus) on a chromosome. Genes achieve their effects by directing the synthesis of proteins. In eukaryotes (such as animals, plants, and fungi ), genes are contained within the cell nucleus. The mitochondria (in animals) and the chloroplasts (in plants) also contain small ...
Heterosis
Overdominance Hypothesis Shull and East separately presented this hypothesis in 1908. This hypothesis is known as stimulation of heterozygosis, cumulative action of divergent alleles, single-gene heterosis, super-dominance, and overdominance.
Particulate inheritance
Ronald Fisher. Particulate inheritance is a pattern of inheritance discovered by Mendelian genetics theorists, such as William Bateson, Ronald Fisher or Gregor Mendel himself, showing that phenotypic traits can be passed from generation to generation through "discrete particles" known as genes, which can keep their ability to be expressed while ...
hypothesis noun
Definition of hypothesis noun in Oxford Advanced Learner's Dictionary. Meaning, pronunciation, picture, example sentences, grammar, usage notes, synonyms and more.

What Is Hypothesis?

Characteristics Of Hypothesis

Sources Of Hypothesis

Types Of Hypothesis

Simple Hypothesis

Complex Hypothesis

Directional Hypothesis

Non-directional Hypothesis

Null Hypothesis

Associative and Causal Hypothesis

Examples Of Hypothesis

Functions Of Hypothesis

Importance Of Hypothesis

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The Evolving Definition of the Term “Gene”

Adam Wilkins

The Classical Period of Genetics

The Neoclassical Period of Genetics

The Breakdown of the Neoclassical Concept of the Gene and the Beginning of the Modern Period of Genetics

Severe cracks in the concept of the gene

Current Status and Future Perspectives Regarding the Concept of the Gene

Putting it all Together: Toward a New Definition of the “Gene”

The cis -trans test

Interpreting “genetic background” effects in terms of GRNs

Acknowledgments

Literature Cited

Alternatives to Colinearity

Transcription Units Instead of Genes

Delineating Gene Regions

References and Recommended Reading

Article History

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What is a Hypothesis – Types, Examples and Writing Guide

Types of Hypothesis

Research Hypothesis

Null Hypothesis

Alternative Hypothesis

Directional Hypothesis

Non-directional Hypothesis

Statistical Hypothesis

Composite Hypothesis

Empirical Hypothesis

Simple Hypothesis

Complex Hypothesis

Applications of Hypothesis

How to write a Hypothesis

Identify the Research Question

Conduct a Literature Review

Determine the Variables

Formulate the Hypothesis

Write the Null Hypothesis

Refine the Hypothesis

Examples of Hypothesis

Purpose of Hypothesis

When to use Hypothesis

Characteristics of Hypothesis

Advantages of Hypothesis

Limitations of Hypothesis

About the author

Muhammad Hassan

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