What is Quantitative Genetics?
Quantitative genetics is the part of genetics that deals with the continuous trait, where the expression of various genes influences the phenotypes. Thus genes are expressed together to produce a trait with continuous variability. This is unlike the classical traits or qualitative traits, where each trait is controlled by the expression of a single or very few genes to produce a discontinuous variation.
How does quantitative trait work?
In simple words, it is governed by many allelic and nonallelic genes in the different regions, and each contributes such a small amount to create a continuous phenotype. Traits that exhibit continuous variation can usually be quantified by measuring, weighing, and counting. Traits such as body weight gain, mature plant heights, egg or milk production records are known as quantitative or complex traits, also referred to as metric traits with continuous variability.
The well-known examples of quantitative genetics are the color of human skin, body weight, egg or milk production, the yield of grain per acre, etc.
In quantitative genetics, for quantitative traits, there is no genetic interaction between non-alleles of different regions. Each gene space may be occupied by a contributing allele, which contributes to the constant number of traits, or by a non-contributing one, whose phenotypic contribution is quantitative. Let us explain the quantitative trait with the following example- the kernel color of wheat, which varies from one phenotypic extreme, i.e., dark red, to the other, i.e., white with no clear-cut breaks in between. When a particular strain of wheat has dark red kernels crossed with another strain having white kernels, all the F1 or first-generation plants have kernels that are intermediate in color. When these pants are self-fertilized, the kernel ratio in the F2 or second-generation is 1 dark red: 2 intermediates: 1 white.
The main properties of quantitative genetics are-
- Each contributing gene has small and relatively equal effects.
- The effects of each trait are additive.
- There is no dominance.
- There is no epistasis or interaction among the different loci contributing to the value of the trait.
- Environmental factors also influence the value of the trait.
- It also shows heritability, i.e., the number of genetic variations in a population due to variation in genetic factors.
Nilsson- Ehle's experiment
In terms of genetic studies, Nilsson- Ehle's experiment is one of the most important methods for studying quantitative genetics. In one set of experiments, wheat with red grain was crossed with the white grain. The F1 generation demonstrated an intermediate color. When these plants are self-fertilized, at least seven color classes, from red to white, were distinguishable in a ratio of 1:6:15:20:15:6:1. This result is explained by assuming that three traits are assorting independently, each with two alleles, such that one produces a unit of red color whereas the other does not. If three gene pairs are operating, each with one potential contributing and one potential non-contributing, the generation of such variations can be envisioned.
Distribution of the Frequency in the F2 Generation with a Different Number of Gene Loci
As more gene pairs become involved in quantitative genetics, a greater number of classes would be expected to appear in the more complex ratio. However, the study of a quantitative characteristic in a large population usually reveals that very few individuals are found nearer the average value for that population. This type of symmetrical distribution is characteristically bell-shaped. It is called the normal or Gaussian distribution. These curves are characterized by the mean or midpoint and by the Variance or width.
Calculation of the Number of Gene Pairs
In genetic studies, the number of gene pairs (n) involved in characterizing a particular polymorphic trait can be determined if the ratio of F2 progeny resembling either of the two extreme phenotypes is known. It can be calculated by using a simple formula:
The ratio of F2 progeny expressing either extreme phenotype = 1/4n
For example, if 1/64 of the progeny in the F2 generation are either of the two extremes of a trait, then the number of gene pairs involved in characterizing phenotypes are:
1/64 = 1/4n or 1/64 = 1/43
The number of gene pairs (n) = 3.
Number of the Class of Traits
In genetic studies, as the number of genes controlling a trait increases, the class of particular traits becomes increasingly indistinguishable. Thus, for n number of gene pairs, the possible class of external traits in the F2 progeny will be 2n + 1. for example, if there are three gene pairs involved (n = 3), then the total class of external traits in F2 progeny will be 7 (2 × 3 + 1 = 7).
Quantitative Trait Locus (QTL) analysis
In quantitative genetics, it is the most important method for the detection of genetic interaction. Many genes control quantitative traits. The regions within genomes that contain genes associated with a particular quantitative trait are known as QTLs. This is a statistical method used in genetic studies. It links two types of information, phenotypic data or trait measurement band genotypic data, usually molecular markers. To conduct a QTL analysis, two things are required. First, two or more strains of organisms differ genetically for the trait of interest. Secondly, the selection of genetic markers is important. DNA markers are preferred for genotyping because these markers do not affect the trait of interest. Many types of markers are used in genetics like Single Nucleotide polymorphisms (SNP), Simple Sequence Repeats (SSR), Restriction Fragment Length Polymorphism (RFLP)
How to carry out QTL analysis?
The parental strains are crossed to carry out QTL analysis or QTL detection, resulting in heterozygous F1 individuals. Then they are crossed. Finally, the phenotypes and genotypes of the derived F2 population are scored. Genetic markers genetically linked to a QTL influencing the trait of interest will segregate more frequently with trait values. Conversely, unlinked markers will not show a significant association with the phenotypes.
The goal of QTL analysis
This is one of the most important methods of quantitative genetics as well as Mendelian genetics. A principal goal of QTL analysis is to answer the question of whether phenotypic differences are primarily due to a few loci with fairly large effects or too many, each with subtle effects.
In genetics, traits that vary between the individuals in a population are caused by environmental and genetic factors. Heritability is a concept that describes how much of the variation in a trait is due to variation in genetic factors. Often, this is used about the resemblance between parents and their offspring. High heritability implies a strong resemblance between parent and offspring concerning a specific trait. The lower one implies a low level of resemblance.
Comparison of Quantitative Genetics with Qualitative Genetics
- Qualitative genetics is concerned with traits that follow Mendelian inheritance. It can be described according to kind and can be categorized into two or more categories. Quantitative genetic traits are described in terms of the degree of expression of the trait rather than the kind.
- Qualitative genetic traits provide discontinuous phenotypic variation. Conversely, quantitative genetic traits produce a continuous variation.
- In qualitative genetics, the effect of a single gene is readily detectable, while in a quantitative study, a single gene effect is not detectable. Here the traits are under polygenic control, i.e., genes with small indistinguishable effects.
- Qualitative genetic analysis is quite straightforward and is based on counts or ratios. On the other hand, a quantitative genetic study provides estimates of population parameters.
A plant with a genotype of aabb and a height of 40 cm is crossed with a plant of genotype AABB and 60 cm. If each dominant allele contributes to heights additively, what is the expected height of the F1 progeny?
The expected height of the F1 progeny will be 50 cm. Difference between two heights is (60 - 40) = 20 cm. Each dominant trait contributes an average of 5 cm to the height of the plant. Therefore, the heterozygote has two contributing factors; 2 X 5 = 10 cm above the base of 40 cm or a total of 50 cm.
H2 = VG/VP
(VG = Variance in genotypes, VP= Variance in phenotypes)
VG = VA + VD + VI
VP = VE + VG + VGE
(VA = Additive variance, VD = Dominance variance, VI and VE are Epistatic and Environmental Variance respectively, VGE = Variance resulting from the interaction of environment and genotype)
h2 = VA/VP
(H2 and h2 are Broad sense and Narrow sense heritability, respectively)
Context and Applications
This topic is significant in the professional exams for both under-graduate and post-graduate courses, especially for:
- Bachelor of Science in Biological Sciences
- Master of Science in Biological Sciences
- Bachelor of Science in Zoology
- Master of Science in Zoology
- Master of Science in Genetics
- Genetic Variance
- Multiple alleles
- Maternal effect
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