Inheritance Of Quantitative Traits In Plants PDF

List of Topics for the Lecture 1. Introduction to Quantitative Characters 2. Genetic Architecture of Quantitative Traits 3. Polygenic Inheritance and Its Statistical Basis 4. Genetic Variance Component 5. GxE Interaction in Quantitative Trait Inheritance 6. Selection Methods...

List of Topics for the Lecture 1. Introduction to Quantitative Characters 2. Genetic Architecture of Quantitative Traits 3. Polygenic Inheritance and Its Statistical Basis 4. Genetic Variance Component 5. GxE Interaction in Quantitative Trait Inheritance 6. Selection Methods in Quantitative Breeding Learning Objectives Based on Bloom’s Taxonomy 1. Explain the fundamental differences between qualitative and quantitative characters in crops. 2. Describe the genetic and environmental factors affecting the inheritance of quantitative traits. 3. Analyze polygenic inheritance and its statistical basis. 4. Compute for the genetic variance components and heritability of characters. 5. Estimate the magnitude of GxE in quantitative trait inheritance 6. Design appropriate selection methods for quantitative characters. What is a quantitatively inherited trait? Many of the traits that plant breeders strive to improve are quantitatively inherited. A quantitatively inherited trait is controlled by many genes at different loci, with each gene — known as a polygene — contributing a small effect to the expression of the character. What is the most economically important quantitative trait of crops?  What is Quantitative Genetics? Polygenes are also known quantitative trait loci (QTL). QTLs involved in expression of a quantitative character act cumulatively to determine the phenotype of the trait. Their mode of inheritance is called quantitative genetics.  Quantitative genetics describes the connection between phenotype and genotype and provides tools to show how phenotypic selection of complex characters changes allele frequencies. SOURCE: https://www.frontiersin.org/journals/plant-science/articles/10.3389/fpls.2022.733996/full Quantitative genetics focuses on the nature of genetic differences, seeks to determine the relative importance of genetic vs. environmental factors, and examines how phenotypic variation relates to evolutionary change. Typically, quantitative genetic analysis is executed on traits showing a continuous range of values. What is the difference between Heritable vs. Environmental Variation? The phenotype of a plant or group of plants is modeled as a function of its genotype as modified by the environment. Phenotype = Genotype + Environment + (Genotype x Environment) P=G+E+(G×E) Some characters are more responsive or sensitive to growing conditions than others. Qualitative traits such as flower color are not strongly influenced by the environment. On the other hand, quantitative traits such as grain yield or abiotic stress tolerance are influenced markedly by the environment. The degree of sensitivity or the range of potential responses to the environment is determined by the genetic composition of the individual plant or population of plants. Genetic variation is essential in order to make progress in cultivar improvement. However, sources of variation include: Environmental variation Genetic variation and Interaction of genetic and environmental variation Plant breeders must distinguish among these sources of variation for the character of interest in order to effectively select and transmit the desired character or assemblage of characters to subsequent generations. What is Genotype Environment Interaction? A gene–environment (G×E) interaction is an association between a genetic factor, or allele, and a phenotype, in which that association is modified by some factor in the environment. How will you explain the differences among the three graphs? B C A Fig. 3 Hypothetical comparisons of genetic x environment interactions (GxE) in yield of two watermelon cultivars in response to increasing levels of soil salinity. How are quantitative traits inherited? Inheritance of quantitative traits involves two or more nonallelic genes (multiple genes or polygenes); the combined action of these genes, as influenced by the environment, produces the phenotype. The effect of individual genes on the trait is not apparent. However, early in the 1900s it was discovered that the inheritance of the individual genes contributing to the phenotype of quantitative traits do indeed follow the same Mendelian inheritance principles as simply-inherited genes. Inheritance of Quantitative Traits In 1909, Herman Nilsson-Ehle, a Swedish geneticist and wheat breeder, conducted some of the classic studies on quantitatively inherited traits in wheat. He developed what is known as the “Multiple Factor” or multi-factorial theory of genetic transmission. A key observation made by Nilsson-Ehle was that although a spectrum of continuous variation in kernel color (a quantitatively inherited trait influenced by environmental factors) could be observed in segregating generations, he was able to determine that segregation for these genes fit a model that each separate contributing gene followed a pattern of Mendelian inheritance. Bread wheat is a hexaploid — allopolyploid that contains three slightly different, but similar ancestral genomes (referred to as A, B, and D) in its genome (AABBDD). Depending on the cultivars that Nilsson-Ehle studied, each genome had a single gene that affected kernel color, and each of these loci has a red allele (R) and a white allele (r). Alleles at each locus varied slightly in their effect on kernel color, and will be designated in this example by different superscripts, e.g., R1 or r3. He crossed two cultivars of wheat that varied in kernel color, one with dark red seeds (homozygous dominant genotype R1R1R2R2R3R3, based on the symbols designating the ancestral genomes) and another with white kernels (homozygous recessive r1r1r2r2r3r3). He noted that the F1 of a cross between these parents (heterozygote R1r1R2r2R3r3) was intermediate in color (light red), but the F2 generation could be grouped into seven classes, ranging in color from dark red to white. He explained the distribution on the basis of three pairs of genes segregating independently, with each dominant allele contributing to the intensity of the red color. With three independent pairs of genes segregating, each with two alleles, as well as environmental effects acting on kernel color, the F2 progeny would contain 63 plants with varying shades of red kernels and one with white kernels. Linkage among the genes restricts independent assortment, so that the required size of the F2 population becomes larger. What are the indicative characteristics of Quantitative Inheritance? Based on a random sample from a genetically mixed population, the distribution of a quantitative trait’s expression approximates a normal or bell curve. Phenotypic values for the specific trait, resulting from simultaneous segregation of multiple genes, exhibit continuous variation, rather than distinct classes. In general, the distribution of values of quantitatively inherited traits in a population follows a normal distribution (also called a Gaussian distribution or bell curve). These curves are generally characterized by two parameters, the mean and the variance or standard deviation. In the figure below, the mean of the random sample is depicted by the symbol and the standard deviation by the symbol s. If the reference is made to a population instead of a sample from a population, the population mean is usually symbolized by μ and the population standard deviation by σ. There are three general types of traits that are quantitatively inherited: continuous, meristic, and threshold. An example of the first type, a continuous trait, is fruit width of pineapple. The second type, a meristic character, is a countable trait that can take on integer values only, e.g., number of tillers of maize or branches of a rose bush. The third type of quantitative trait is known as a threshold character or “all-or-none” trait. Such traits are typically ranked simply as presence or absence, e.g., Downy Mildew disease in soybean. Threshold traits are assumed to be represented by an underlying normally distributed “liability trait” that is the sum of the independent genetic and environmental components of the distribution. A disease would have to be present before you could determine if certain genotypes were susceptible or not. For example, plants might be able to tolerate low to moderate levels of nicotine in their tissues until a threshold was crossed, above which the high level of nicotine present would be lethal. Threshold characters exhibit only two phenotypes — the trait is either present or absent — but the susceptibility to the trait varies continuously. Environment has a large influence on the trait’s phenotype. That is, for the particular trait, the relative responses of plants change when grown under different environmental conditions. Distinct segregation ratios of individual nonallelic genes are not observed. Recombination and segregation patterns are based on the combined effect of the polygenes on the trait. The more loci controlling the character, the greater the complexity. What is genotypic value? Genes may differ in their individual gene action, but their effect on the trait is cumulative. Types of gene action include additive, dominance, overdominance and epistasis. For an individual, the breeding value is calculated by the summation of the average effects of its genes (also referred to as the additive effect of genes). The average effect of an allele is approximately the average deviation of the mean phenotypic value from the population mean if the allele at a particular locus is substituted by another allele (Falconer and Mackay 1996). Descriptive Statistics Range — the lowest and highest phenotypic values in the population or sample for the character. Mean (µ or M for population; ¯XX¯ for sample) — describes the average performance of a random sample from a population for a trait. The mean is a measure of central tendency — it does not tell anything about the distribution of individual observations. Mean equals the sum of the trait values of each individual divided by the number of samples (n): Variance (V or σ2 for population; s2 for sample) — a measure of the scatter or dispersion of phenotypic values. The greater the variability among individuals, the greater the variance. Two populations with the same mean for the same character could differ greatly in their respective variance for that character. Standard deviation (σ for population; s for sample) — also a measure of dispersion around the mean. Standard deviation expresses the dispersion in the same unit as the mean. Standard deviation is the square root of the variance. A small variance and a small standard deviation tell us that the phenotypic values are near the mean value. In contrast, a large variance and standard deviation indicate that the trait values have a wide range. Coefficient of variation (CV) — the standard deviation as a percentage of the mean. Because the units cancel out, CV is a unitless measure. Divide the standard deviation by the mean and multiply by 100: A CV of about 10% or less is desirable in assessing biological systems. When the CV is greater than 10%, the variability in the sample or the population may be too great to sort out the factors contributing to that variability. The mean and the variance are used to describe an individual characteristic, but plant breeders are frequently interested in more than one trait simultaneously. Two or more characteristics can vary together, and are thus not independent of one another. What are Multiple Genes and Gene Actions? The general types of gene action for quantitative characters (additive, full and partial dominance, and over-dominance) do not differ from those for qualitative traits. However, the genes contributing to the phenotype of a quantitative character may or may not differ in their individual gene action, and their relative effects on the trait’s expression may differ. Some may have major influence and others may have only minor effects on the phenotype. The genes controlling a quantitative trait may also interact. The table below gives examples of types of gene action at two loci. For quantitative traits this would be expanded to multiple loci. Some may have major influence and others may have only minor effects on the phenotype. The genes controlling a quantitative trait may also interact. Why are quantitative traits challenging to measure under different environments? Heritability of these traits is a function of the incidence of the trait in the population, so it is difficult to determine the importance of genetic factors in different environments or in different populations that differ in incidence. What is heritability? Heritability estimates the relative contribution of genetic factors to the phenotypic variability observed in a population. What causes variance among plants and among lines or varieties? Phenotypic variation observed among plants or varieties is due to differences in their genetic makeup, environmental influences on each plant or genotype, and interaction of the genotype and environment. The effectiveness with which selection can be expected to take advantage of variability depends on how much of that variability results from genetic differences. Why? Only genetic effects can be transmitted to progeny. What does heritability estimate? Heritability estimates the degree of similarity between parent and progeny for a particular trait, and the effectiveness with which selection can be expected to take advantage of genetic variability. HERITABILITY is often used by plant breeders to quantify the precision of single field trials or of series of field trials. It is defined as the proportion of phenotypic variance among individuals in a population that is due to heritable genetic effects. What are the two types of heritability? The general term that describes the proportion of the genetic variance to the total variance is heritability. Two specific types of heritability can be estimated. The broad-sense heritability is the ratio of total genetic variance to total phenotypic variance. H2 = VG/VP  The narrow-sense heritability is the ratio of additive genetic variance to the total phenotypic variance. h2 = VA/VP Heritability does not indicate the degree to which a trait is genetic, it measures the proportion of the phenotypic variance that is the result of genetic factors.