English name:

Quantitative genetics

Definition:

A branch of genetics that uses mathematical statistics and mathematical methods to study the genetic laws of quantitative characteristics of biological populations.

Theme:

Genetics (first-class discipline); Introduction (two disciplines)

This content is approved and published by the National Committee for the Examination and Approval of Scientific and Technical Terminology.

Quantitative genetics is a branch of genetics, which uses mathematical statistics and mathematical analysis to study the inheritance of quantitative traits.

1909 a brief history Swedish geneticist H. Nihlsson-Eller put forward the polygene theory, and explained the inheritance of quantitative traits by Mendel separation of each pair of minor genes. British statistician and geneticist R.A. Fisher, American geneticist S Wright and British physiologist and geneticist J.B.S. Haldane laid the theoretical foundation of quantitative genetics in the 1920s. In the 1940s, American scholar J.L. Lesch and British quantitative geneticist K Mather further developed the study of quantitative genetics, which K Mather called biogenetics. Since 1950s, with the gradual application of probability theory, linear algebra, multivariate statistics and stochastic process, the content of quantitative genetics has developed greatly.

The research method is mainly to use biostatistics to randomly sample and measure some quantitative characters of the population, calculate the average and variance, and make mathematical analysis on this basis. According to the research of Danish plant physiologist and geneticist W.L. Johansen, the phenotypic value P of quantitative traits is equal to the sum of genotype value G and environmental value E; The average phenotypic value of the population is equal to the strong average genotype value (because ∑ e = 0); Genotype value consists of cumulative effect value A, dominant effect value D and epistatic effect value I among non-alleles. In this way, the genetic variation of a quantitative trait in the population can be expressed by genetic variance VG, which is the sum of cumulative variance VA, dominant variance VD and epistatic variance VI. If the interaction between environmental factors and genetic factors is not considered, then the measured phenotypic variance (VP) is equal to the sum of genotype variance VG and environmental variance VE, which can be written as the following formula:

VP = VG+VE = VA+VD+VI+VE According to this formula, as long as the environmental variance can be estimated (for example, it can be expressed by the variance of pure line parents or hybrid generation), the genetic variance in the representative variance of hybrid segregation can be measured. On this basis, we can also estimate a series of instructive genetic parameters such as heritability, repeatability, genetic correlation, genetic progress and selection index in breeding practice. Using these parameters, we can analyze and predict the genetic dynamics of quantitative trait variation as a reference for animal and plant breeding.

Another important content of quantitative genetics is to study various genetic mating designs (such as diallel cross, recurrent selection, various mating systems of animals, etc.). ) and the genetic dynamics of quantitative traits in these mating designs. In addition, the interaction between genotype and environment is also an important research topic in quantitative genetics in recent years.

related notion

Heritability Heritability, or heritability, is used to measure the proportion of some variation caused by genetic reasons (in terms of environmental impact) in phenotypic variation in a population, and use it as a reference index for selection, so as to judge the possibility of this trait variation being passed on to future generations. For example, the heritability of birth weight of dairy cows is 49% (see table), which shows that birth weight is largely determined by genetic factors, so it is more likely to succeed in breeding Daniel according to birth weight. On the contrary, the heritability of the conception rate is 3%, which means that the conception rate is mostly not determined by genetic factors, so it is unlikely to succeed in breeding prolific cows according to the conception rate. Generalized heritability (h2B) is expressed by the ratio of genetic variance to phenotypic variance (H2b = VG/VP). If the heritability is large, the variation of this trait mainly comes from genetic factors and is less affected by environmental changes. Because only the cumulative variance VA is the variation that can be fixed from generation to generation, the ratio of cumulative variance to phenotypic variance is often used in breeding to express heritability (H2n = VA/VP), which is the narrow sense heritability. Heritability is widely used in animal and plant breeding. In breeding practice, the heritability of quantitative traits is often needed as a reference to determine the selection method and period, as well as to predict the selection effect and estimate the cumulative effect value, that is, breeding value (see table).

Repeatability refers to the degree to which the phenotypic value of a quantitative trait may be repeated between different production cycles, which is used to measure the stability of a genotype of a trait in a fluctuating environment. It can also be used to study the similarity of quantitative characters in different environments. Repeatability is also an intra-group correlation coefficient, so it can also determine the number of times a phenotypic value should be measured. For example, the repeatability of milk fat rate is 80%, which means that the repeatability is high. Through several measurements, the future milk fat rate level of this cow can be roughly determined. In addition, repeatability can also be used to estimate the stability of population or individual traits.

Genetic correlation refers to the correlation between the genotypic cumulative effects of two traits of the same individual, which is equal to the ratio of the product of the genetic covariance of the two traits and the genetic standard deviation of each trait. Genetic correlation can reflect the degree of correlation between genotypes, so some economic traits with high genetic correlation but low heritability or difficult to measure can be indirectly selected by using traits with high heritability to improve the selection effect.

Genetic correlation is more reliable than phenotypic correlation because it removes the influence of environment. The heritability of weight variation of home-made eggs is 60%, and the heritability of weight variation is only 31%. This shows that the effect of raising large breeders by weight is not good. Although the phenotypic correlation between these two traits is only 0. 16%, the genetic correlation is 50%, so large breeders can be selected indirectly through egg weight. Another example is that the milk yield of cattle is closely related to the body shape and breast shape of cattle, and the yield of rice is also related to yield factors (such as the number of spikes per plant, the number of grains per spike, the 1000-grain weight, etc.). ).

In breeding, the selection value of one trait is usually predicted indirectly from the characteristics of another trait according to the correlation of the trait. However, this is only phenotypic correlation, and it also includes environmental impact, so it can't truly reflect the genetic relationship between different traits. Genetic correlation truly reflects the correlation between genotypes, and better results can be obtained on this basis, especially for traits with low heritability.

Genetic progress (also known as genetic gain) is the value that the average value of a quantitative trait of hybrid offspring is higher than that of the original population under a certain selection intensity. It is a function of heritability h2 and selection difference I, that is, δ g = IH2. Selection difference refers to the difference between the average value of a quantitative trait in the population and the average value of the trait selected as the next generation parent. Genetic progress is an important estimate to determine genetic effects. As long as we find out the heritability of two traits and their genetic correlation, we can estimate the genetic progress of indirectly selecting another trait through the selection of one trait.

According to the heritability of traits, genetic progress has different effects. For traits with high heritability and large genetic variance, greater genetic progress can be obtained under a certain selection intensity, which shows that the selection effect of this trait is higher. Therefore, genetic progress is an important parameter to determine the selection effect. In addition, the relationship between traits is just like the correlation between traits, and the choice of one trait will affect the genetic progress of another. The correlation between traits only shows the closeness of the two traits relatively; The correlation of genetic progress between traits is the correlation of absolute values obtained by two traits in heredity. Therefore, genetic progress can be used not only to predict the absolute progress of a certain trait under selection, but also to predict the corresponding progress caused by other traits. Based on this, we can evaluate the breeding materials properly and arrange and deal with the materials to be tested reasonably.

Selection index is a selection index for comprehensive selection of multiple quantitative traits, and the target traits can be improved to the greatest extent through selection. The index value is equal to the algebraic sum of the product of the phenotypic value and the index coefficient of each trait. With the different nature and requirements of the problem, there are different methods to determine the index coefficient, so there are many methods to estimate the index that can be used as an index when selecting multiple quantitative traits.

Another important content of quantitative genetics is to study various genetic mating designs (such as diallel cross, recurrent selection, various mating systems of animals, etc.). ) and the genetic dynamics of quantitative traits in these mating designs. In addition, the interaction between genotype and environment is also an important research topic in quantitative genetics in recent years.

Genetic laws are combined with biostatistics and other branches of mathematics to explain the genetic laws of quantitative traits and the laws of biological development, thus enriching genetics and evolution. Because most economic traits are quantitative traits, it is of great significance to study the genetic variation of quantitative traits for breeding practice.

Open classification:

Biochemistry, Biology, Genetics and Microbiology Reference:

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