This document discusses the Hardy-Weinberg law of genetic equilibrium. It states that in a large, randomly mating population, the frequencies of genotypes will remain constant from generation to generation in the absence of evolutionary influences like mutation, migration, genetic drift and non-random mating. The law establishes that the frequency of alleles A and a will be p and q, and the frequencies of genotypes AA, Aa and aa will be p^2, 2pq and q^2 respectively, where p + q = 1. The document provides examples of calculating genotype and gamete frequencies under Hardy-Weinberg equilibrium.
This document provides information about triple test cross analysis, which involves crossing randomly selected F2 plants with both parent plants (P1 and P2) and their F1 hybrid. It requires four crop seasons. Triple test cross analysis provides estimates of additive and dominance effects and can detect the presence of epistasis. It has advantages like reliable information about epistasis and independent estimates of additive and dominance variances. However, it requires more time than other analyses and choice of contrasting parent lines can be difficult.
Association mapping, GWAS, Mapping, natural population mappingMahesh Biradar
This document discusses association mapping for crop improvement. It explains that association mapping exploits historical recombination events in populations to map quantitative trait loci with greater precision than family-based linkage analysis. Association mapping can be applied to diverse populations and detect more alleles than bi-parental mapping. Genome-wide association studies allow for high-resolution mapping of traits down to the sequence level by leveraging linkage disequilibrium. Statistical methods must account for population structure and kinship to avoid false positives in association analyses.
This document introduces different measures used to calculate linkage disequilibrium (LD) between two loci, including D, D', r, and r2. It provides the steps and equations to calculate each measure using an example with two SNPs, each with two alleles. The key measures are D, D', and r2. D represents the deviation from expected haplotype frequencies under linkage equilibrium. D' standardizes D between 0-1. r2 is the squared correlation coefficient and can be used to test for statistically significant LD between loci. An example calculation is shown to illustrate the application of these measures.
This document provides an overview of genome-wide association studies (GWAS). It discusses the basic concept of GWAS, running and analyzing a GWAS, and interpreting the results. Key points include: GWAS genotype individuals for hundreds of thousands to millions of SNPs to look for associations with traits; extensive quality control is required; imputation can increase SNP coverage; statistical analysis includes computing p-values and correcting for multiple testing; significant findings still require replication in independent samples.
1) Association mapping is a method that relies on linkage disequilibrium to study the relationship between genetic markers and phenotypic traits in natural populations. It aims to find statistical associations between genes or markers and complex traits.
2) The key advantage of association mapping over traditional QTL mapping is that it has higher resolution because it utilizes more historical recombinations, does not require developing new mapping populations, and allows evaluation of many alleles simultaneously.
3) Linkage disequilibrium, which is the non-random association of alleles at different loci, is required for association mapping to be effective. Factors like population structure, relatedness, and recombination rates impact the extent of linkage disequilibrium.
This document summarizes a study that analyzed genomic runs of homozygosity (ROH) in populations from the HGDP dataset to understand population history and consanguinity. The study found that Native American populations had the longest ROHs, Oceanian populations had the most short ROHs, and South/Central Asian and West Asian populations had more long ROHs, reflecting consanguineous marriages. Hunter-gatherer populations generally had more total ROH lengths than farmer populations. Overall, short ROHs made up most ROHs present across populations, but the most inbred populations had more long ROHs, providing information about demographic history and disease risk.
This document discusses the Hardy-Weinberg law of genetic equilibrium. It states that in a large, randomly mating population, the frequencies of genotypes will remain constant from generation to generation in the absence of evolutionary influences like mutation, migration, genetic drift and non-random mating. The law establishes that the frequency of alleles A and a will be p and q, and the frequencies of genotypes AA, Aa and aa will be p^2, 2pq and q^2 respectively, where p + q = 1. The document provides examples of calculating genotype and gamete frequencies under Hardy-Weinberg equilibrium.
This document provides information about triple test cross analysis, which involves crossing randomly selected F2 plants with both parent plants (P1 and P2) and their F1 hybrid. It requires four crop seasons. Triple test cross analysis provides estimates of additive and dominance effects and can detect the presence of epistasis. It has advantages like reliable information about epistasis and independent estimates of additive and dominance variances. However, it requires more time than other analyses and choice of contrasting parent lines can be difficult.
Association mapping, GWAS, Mapping, natural population mappingMahesh Biradar
This document discusses association mapping for crop improvement. It explains that association mapping exploits historical recombination events in populations to map quantitative trait loci with greater precision than family-based linkage analysis. Association mapping can be applied to diverse populations and detect more alleles than bi-parental mapping. Genome-wide association studies allow for high-resolution mapping of traits down to the sequence level by leveraging linkage disequilibrium. Statistical methods must account for population structure and kinship to avoid false positives in association analyses.
This document introduces different measures used to calculate linkage disequilibrium (LD) between two loci, including D, D', r, and r2. It provides the steps and equations to calculate each measure using an example with two SNPs, each with two alleles. The key measures are D, D', and r2. D represents the deviation from expected haplotype frequencies under linkage equilibrium. D' standardizes D between 0-1. r2 is the squared correlation coefficient and can be used to test for statistically significant LD between loci. An example calculation is shown to illustrate the application of these measures.
This document provides an overview of genome-wide association studies (GWAS). It discusses the basic concept of GWAS, running and analyzing a GWAS, and interpreting the results. Key points include: GWAS genotype individuals for hundreds of thousands to millions of SNPs to look for associations with traits; extensive quality control is required; imputation can increase SNP coverage; statistical analysis includes computing p-values and correcting for multiple testing; significant findings still require replication in independent samples.
1) Association mapping is a method that relies on linkage disequilibrium to study the relationship between genetic markers and phenotypic traits in natural populations. It aims to find statistical associations between genes or markers and complex traits.
2) The key advantage of association mapping over traditional QTL mapping is that it has higher resolution because it utilizes more historical recombinations, does not require developing new mapping populations, and allows evaluation of many alleles simultaneously.
3) Linkage disequilibrium, which is the non-random association of alleles at different loci, is required for association mapping to be effective. Factors like population structure, relatedness, and recombination rates impact the extent of linkage disequilibrium.
This document summarizes a study that analyzed genomic runs of homozygosity (ROH) in populations from the HGDP dataset to understand population history and consanguinity. The study found that Native American populations had the longest ROHs, Oceanian populations had the most short ROHs, and South/Central Asian and West Asian populations had more long ROHs, reflecting consanguineous marriages. Hunter-gatherer populations generally had more total ROH lengths than farmer populations. Overall, short ROHs made up most ROHs present across populations, but the most inbred populations had more long ROHs, providing information about demographic history and disease risk.
Epigenetics and it's relevance in crop improvementShamlyGupta
Epigenetics means ‘above’ or ‘on top of genetics’
A study of the changes in gene expression that are mitotically and/or meiotically heritable and do not involve a change in the DNA sequence
Gene-regulatory information that is not expressed in DNA sequences but transmitted from one generation (of cells or organisms) to the next
Coined by embryologist C. H. Waddington in 1942.
Dominant traits are caused by a single allele masking the phenotype of the other allele. Recessive traits require inheriting two copies of the recessive allele to manifest. Gregor Mendel established that purple flower color in peas was dominant over white, as peas needed only one purple allele. When heterozygous, the dominant trait manifests as the recessive allele remains inactive. Examples show homozygous dominant as AA, heterozygous dominant as Aa displaying the dominant trait, and homozygous recessive as aa.
Neutral theory proposes that most mutations are neutral and do not affect fitness. Under neutral evolution, genetic drift is the main factor driving changes in allele frequencies in populations rather than natural selection. Tests based on polymorphism and divergence data can help determine if loci are evolving neutrally or under the influence of selection. Extended haplotype homozygosity (EHH) and cross population EHH (XPEHH) are methods used to detect signatures of positive selection by examining the breakdown of linkage disequilibrium around candidate regions.
This document provides an overview of genome-wide association studies (GWAS). It defines key terms related to GWAS such as linkage disequilibrium, minor allele frequency, and odds ratio. It compares linkage mapping and association mapping. It describes the methodology of GWAS including identifying population structure, selecting case and control subjects, genotyping samples, and determining associated SNPs. It discusses challenges such as multiple hypothesis testing and population structure. It provides examples of successful GWAS in crops like maize and Arabidopsis. Overall, the document provides a comprehensive introduction and overview of GWAS.
This document provides an introduction to principles of quantitative genetics. It discusses the history and development of the field, beginning with Mendel's foundational work in genetics and Galton's development of statistical techniques. It describes how early geneticists differed in their views of inheritance as qualitative vs quantitative. Key figures who helped establish quantitative genetics are mentioned, including Fisher who integrated Mendelian and statistical approaches. The document outlines differences between Mendelian and polygenic traits. It also discusses types of statistics used in quantitative genetics like first and second degree statistics, as well as biometrical techniques and parameters used in plant breeding like assessment of variability, selection of elite genotypes, choice of parents, and stability analysis.
This document summarizes an association mapping study of seed oil and protein contents in upland cotton. 180 cotton accessions were genotyped using 228 SSR markers and phenotyped for oil and protein content over multiple locations and years. Population structure analysis identified two subpopulations. Association analysis identified 86 marker-trait associations between 58 SSR markers and the two traits, with 15 and 12 markers associated with oil and protein content respectively. 18 markers were significantly associated with the traits in more than one environment, with 9 markers associated with both oil and protein content simultaneously and stably across locations.
This document provides an overview of molecular phylogenetics and computational methods for reconstructing evolutionary relationships between genetic sequences. It discusses key topics like molecular evolution, calculating genetic distances, clustering algorithms like UPGMA and neighbor joining, and cladistic methods like parsimony. The document also explains important concepts in phylogenetics including orthologs and paralogs, phenetic versus cladistic approaches, and maximum likelihood methods.
This document provides information about population genetics and the Hardy-Weinberg principle of genetic equilibrium. It defines key population genetics concepts such as gene pool, allele frequencies, and genotypes. It describes the five conditions required for Hardy-Weinberg equilibrium: large population size, random mating, no mutations, no migration, and no natural selection. Examples are provided to demonstrate how to calculate allele and genotype frequencies using the Hardy-Weinberg equation.
B.sc. agri i pog unit 4 population geneticsRai University
This document provides an overview of population genetics and principles of evolution. It discusses how genetic variation is maintained in populations through mechanisms such as sexual reproduction, genetic drift, mutation and natural selection. A key concept is that evolution occurs through changes in allele frequencies in populations over generations. The document also covers Mendelian inheritance, Darwinian evolution, the Hardy-Weinberg principle of genetic equilibrium, and factors that can lead to deviations from equilibrium, driving microevolutionary changes within populations.
Population genetics reconciled Darwin and Mendel's ideas by showing how natural selection could act on variation present in populations. The Hardy-Weinberg theorem describes genetic equilibrium in a population where allele frequencies remain constant between generations unless disrupted by factors like genetic drift, migration, non-random mating, mutation, or natural selection. These disruptions to equilibrium allow for microevolution and populations to change over time through natural selection acting on genetic variation.
Selection system: Biplots and Mapping genotyoeAlex Harley
The document discusses using biplots and genotype mapping to analyze multi-environment trials. It describes biplots, how they are constructed using methods like AMMI analysis of variance and principal component analysis. Biplots can show the relationship between genotypes and environments, and identify stable genotypes. The document also discusses genotype by genotype environment (GGE) biplots and their use in identifying mega-environments and ranking genotypes. It provides an example study using these methods to analyze rice hybrids in different locations and identify high yielding stable varieties.
This document discusses methods for estimating heritability and the components of phenotypic variance from genetic and environmental sources. It explains that heritability is estimated based on the resemblance between relatives, which is determined by the genetic variance they share. Various methods are described, including regression of offspring on parents, half-sib and full-sib correlations, and using twin data. The appropriate method depends on minimizing bias from non-additive genetic and common environmental effects, while maximizing precision by using data from close relatives.
Marker assisted whole genome selection in crop improvementSenthil Natesan
Mapping and tagging of agriculturally important genes have been greatly facilitated by an array of molecular markers in crop plants. Marker-assisted selection (MAS) is gaining considerable importance as it would improve the efficiency of plant breeding through precise transfer of genomic regions of interest (foreground selection) and accelerating the recovery of the recurrent parent genome (background selection). MAS has been more widely employed for simply inherited traits than for polygenic traits, although there are a few success stories in improving quantitative traits through MAS
Population genetics focuses on the frequencies and distribution of genes in populations. It combines Darwin's theory of evolution with Mendelian genetics and molecular biology. There are several forces that can change allelic and genotypic frequencies in a population over time, including mutation, natural selection, migration between populations, and genetic drift. Hardy-Weinberg equilibrium describes the relationship between gene and genotypic frequencies in a population, where the frequencies will remain constant from generation to generation if these evolutionary forces are not present.
Mendel's experiments with pea plants showed that traits are passed from parents to offspring through invisible "factors" now called genes. Epistasis occurs when the effect of one gene is dependent on or masked by another gene. There are several types of epistatic interactions that result in fewer than four phenotypes in the F2 generation, including dominant epistasis (12:3:1 ratio), recessive epistasis (9:3:4 ratio), duplicate recessive genes (9:7 ratio), duplicate dominant genes (15:1 ratio), dominant-recessive interaction (13:3 ratio), and duplicate genes with cumulative effect (9:6:1 ratio). Epistasis plays a role in determining
This document summarizes a seminar on the molecular basis of heterosis, or hybrid vigor, in crop plants. It discusses the history of research on heterosis dating back to Darwin. Modern research shows that heterozygous hybrids often outperform their homozygous parents in traits like yield, growth, and stress resistance. Several genetic models have been proposed to explain heterosis, including dominance, overdominance, and epistasis, but no single model is sufficient. Omics studies of hybrids and polyploids have found both additive and non-additive changes in gene expression, proteins, and metabolites involved in growth, development, stress response, and signaling pathways.
This document discusses Hardy-Weinberg equilibrium, which describes the expected genotype and allele frequencies in a population that is not evolving. It will be in equilibrium if 5 assumptions are met: large population size, no migration, negligible mutations, random mating, no natural selection. The model consists of two equations to calculate expected allele and genotype frequencies. Observed frequencies in a sample California population at the EST locus match the expected frequencies, indicating the population is in equilibrium at this locus and not evolving. However, the assumptions are often violated in real populations.
Introduction:
Proposed by Meuwissen et al. (2001)
GS is a specialized form of MAS, in which information from genotype data on marker alleles covering the entire genome forms the basis of selection.
The effects associated with all the marker loci, irrespective of whether the effects are significant or not, covering the entire genome are estimated.
The marker effect estimates are used to calculate the genomic estimated breeding values (GEBVs) of different individuals/lines, which form the basis of selection.
Why to go for genomic selection:
Marker-assisted selection (MAS) is well-suited for handling oligogenes and quantitative trait loci (QTLs) with large effects but not for minor QTLs.
MARS attempts to take into account small effect QTLs by combining trait phenotype data with marker genotype data into a combined selection index.
Based on markers showing significant association with the trait(s) and for this reason has been criticized as inefficient
The genomic selection (GS) scheme was to rectify the deficiency of MAS and MARS schemes. The GS scheme utilizes information from genome-wide marker data whether or not their associations with the concerned trait(s) are significant.
GEBV: GenomicEstimated Breeding Values-
The sum total of effects associated with all the marker alleles present in the individual and included in the GS model applied to the population under selection
Calculated on a single individual basis
Gene-assisted genomic selection:
A GS model that uses information about prior known QTLs, the targeted QTLs were accumulated in much higher frequencies than when the standard ridge regression was used
The sum total of effects associated with all the marker alleles present in the individual and included in the GS model applied to the population under selection
Calculated on a single individual basis
Population used:
Training population: used for training of the GS model and for obtaining estimates of the marker-associated effects needed for estimation of GEBVs of individuals/lines in the breeding population.
Breeding population: the population subjected to GS for achieving the desired improvement and isolation of superior lines for use as new varieties/parents of new improved hybrids.
Training population-
large enough: must be representative of the breeding population: max. trait variance with marker : by cluster analysis
should have either equal or comparable LD, LD decay rates with breeding populations
Updated by including individuals/lines from the breeding population
Training more than one generation
Low colinearity between markers is needed since high colinearity tends to reduce prediction accuracy of certain GS models. (colinearity disturbed by recombination)
Epigenetics and it's relevance in crop improvementShamlyGupta
Epigenetics means ‘above’ or ‘on top of genetics’
A study of the changes in gene expression that are mitotically and/or meiotically heritable and do not involve a change in the DNA sequence
Gene-regulatory information that is not expressed in DNA sequences but transmitted from one generation (of cells or organisms) to the next
Coined by embryologist C. H. Waddington in 1942.
Dominant traits are caused by a single allele masking the phenotype of the other allele. Recessive traits require inheriting two copies of the recessive allele to manifest. Gregor Mendel established that purple flower color in peas was dominant over white, as peas needed only one purple allele. When heterozygous, the dominant trait manifests as the recessive allele remains inactive. Examples show homozygous dominant as AA, heterozygous dominant as Aa displaying the dominant trait, and homozygous recessive as aa.
Neutral theory proposes that most mutations are neutral and do not affect fitness. Under neutral evolution, genetic drift is the main factor driving changes in allele frequencies in populations rather than natural selection. Tests based on polymorphism and divergence data can help determine if loci are evolving neutrally or under the influence of selection. Extended haplotype homozygosity (EHH) and cross population EHH (XPEHH) are methods used to detect signatures of positive selection by examining the breakdown of linkage disequilibrium around candidate regions.
This document provides an overview of genome-wide association studies (GWAS). It defines key terms related to GWAS such as linkage disequilibrium, minor allele frequency, and odds ratio. It compares linkage mapping and association mapping. It describes the methodology of GWAS including identifying population structure, selecting case and control subjects, genotyping samples, and determining associated SNPs. It discusses challenges such as multiple hypothesis testing and population structure. It provides examples of successful GWAS in crops like maize and Arabidopsis. Overall, the document provides a comprehensive introduction and overview of GWAS.
This document provides an introduction to principles of quantitative genetics. It discusses the history and development of the field, beginning with Mendel's foundational work in genetics and Galton's development of statistical techniques. It describes how early geneticists differed in their views of inheritance as qualitative vs quantitative. Key figures who helped establish quantitative genetics are mentioned, including Fisher who integrated Mendelian and statistical approaches. The document outlines differences between Mendelian and polygenic traits. It also discusses types of statistics used in quantitative genetics like first and second degree statistics, as well as biometrical techniques and parameters used in plant breeding like assessment of variability, selection of elite genotypes, choice of parents, and stability analysis.
This document summarizes an association mapping study of seed oil and protein contents in upland cotton. 180 cotton accessions were genotyped using 228 SSR markers and phenotyped for oil and protein content over multiple locations and years. Population structure analysis identified two subpopulations. Association analysis identified 86 marker-trait associations between 58 SSR markers and the two traits, with 15 and 12 markers associated with oil and protein content respectively. 18 markers were significantly associated with the traits in more than one environment, with 9 markers associated with both oil and protein content simultaneously and stably across locations.
This document provides an overview of molecular phylogenetics and computational methods for reconstructing evolutionary relationships between genetic sequences. It discusses key topics like molecular evolution, calculating genetic distances, clustering algorithms like UPGMA and neighbor joining, and cladistic methods like parsimony. The document also explains important concepts in phylogenetics including orthologs and paralogs, phenetic versus cladistic approaches, and maximum likelihood methods.
This document provides information about population genetics and the Hardy-Weinberg principle of genetic equilibrium. It defines key population genetics concepts such as gene pool, allele frequencies, and genotypes. It describes the five conditions required for Hardy-Weinberg equilibrium: large population size, random mating, no mutations, no migration, and no natural selection. Examples are provided to demonstrate how to calculate allele and genotype frequencies using the Hardy-Weinberg equation.
B.sc. agri i pog unit 4 population geneticsRai University
This document provides an overview of population genetics and principles of evolution. It discusses how genetic variation is maintained in populations through mechanisms such as sexual reproduction, genetic drift, mutation and natural selection. A key concept is that evolution occurs through changes in allele frequencies in populations over generations. The document also covers Mendelian inheritance, Darwinian evolution, the Hardy-Weinberg principle of genetic equilibrium, and factors that can lead to deviations from equilibrium, driving microevolutionary changes within populations.
Population genetics reconciled Darwin and Mendel's ideas by showing how natural selection could act on variation present in populations. The Hardy-Weinberg theorem describes genetic equilibrium in a population where allele frequencies remain constant between generations unless disrupted by factors like genetic drift, migration, non-random mating, mutation, or natural selection. These disruptions to equilibrium allow for microevolution and populations to change over time through natural selection acting on genetic variation.
Selection system: Biplots and Mapping genotyoeAlex Harley
The document discusses using biplots and genotype mapping to analyze multi-environment trials. It describes biplots, how they are constructed using methods like AMMI analysis of variance and principal component analysis. Biplots can show the relationship between genotypes and environments, and identify stable genotypes. The document also discusses genotype by genotype environment (GGE) biplots and their use in identifying mega-environments and ranking genotypes. It provides an example study using these methods to analyze rice hybrids in different locations and identify high yielding stable varieties.
This document discusses methods for estimating heritability and the components of phenotypic variance from genetic and environmental sources. It explains that heritability is estimated based on the resemblance between relatives, which is determined by the genetic variance they share. Various methods are described, including regression of offspring on parents, half-sib and full-sib correlations, and using twin data. The appropriate method depends on minimizing bias from non-additive genetic and common environmental effects, while maximizing precision by using data from close relatives.
Marker assisted whole genome selection in crop improvementSenthil Natesan
Mapping and tagging of agriculturally important genes have been greatly facilitated by an array of molecular markers in crop plants. Marker-assisted selection (MAS) is gaining considerable importance as it would improve the efficiency of plant breeding through precise transfer of genomic regions of interest (foreground selection) and accelerating the recovery of the recurrent parent genome (background selection). MAS has been more widely employed for simply inherited traits than for polygenic traits, although there are a few success stories in improving quantitative traits through MAS
Population genetics focuses on the frequencies and distribution of genes in populations. It combines Darwin's theory of evolution with Mendelian genetics and molecular biology. There are several forces that can change allelic and genotypic frequencies in a population over time, including mutation, natural selection, migration between populations, and genetic drift. Hardy-Weinberg equilibrium describes the relationship between gene and genotypic frequencies in a population, where the frequencies will remain constant from generation to generation if these evolutionary forces are not present.
Mendel's experiments with pea plants showed that traits are passed from parents to offspring through invisible "factors" now called genes. Epistasis occurs when the effect of one gene is dependent on or masked by another gene. There are several types of epistatic interactions that result in fewer than four phenotypes in the F2 generation, including dominant epistasis (12:3:1 ratio), recessive epistasis (9:3:4 ratio), duplicate recessive genes (9:7 ratio), duplicate dominant genes (15:1 ratio), dominant-recessive interaction (13:3 ratio), and duplicate genes with cumulative effect (9:6:1 ratio). Epistasis plays a role in determining
This document summarizes a seminar on the molecular basis of heterosis, or hybrid vigor, in crop plants. It discusses the history of research on heterosis dating back to Darwin. Modern research shows that heterozygous hybrids often outperform their homozygous parents in traits like yield, growth, and stress resistance. Several genetic models have been proposed to explain heterosis, including dominance, overdominance, and epistasis, but no single model is sufficient. Omics studies of hybrids and polyploids have found both additive and non-additive changes in gene expression, proteins, and metabolites involved in growth, development, stress response, and signaling pathways.
This document discusses Hardy-Weinberg equilibrium, which describes the expected genotype and allele frequencies in a population that is not evolving. It will be in equilibrium if 5 assumptions are met: large population size, no migration, negligible mutations, random mating, no natural selection. The model consists of two equations to calculate expected allele and genotype frequencies. Observed frequencies in a sample California population at the EST locus match the expected frequencies, indicating the population is in equilibrium at this locus and not evolving. However, the assumptions are often violated in real populations.
Introduction:
Proposed by Meuwissen et al. (2001)
GS is a specialized form of MAS, in which information from genotype data on marker alleles covering the entire genome forms the basis of selection.
The effects associated with all the marker loci, irrespective of whether the effects are significant or not, covering the entire genome are estimated.
The marker effect estimates are used to calculate the genomic estimated breeding values (GEBVs) of different individuals/lines, which form the basis of selection.
Why to go for genomic selection:
Marker-assisted selection (MAS) is well-suited for handling oligogenes and quantitative trait loci (QTLs) with large effects but not for minor QTLs.
MARS attempts to take into account small effect QTLs by combining trait phenotype data with marker genotype data into a combined selection index.
Based on markers showing significant association with the trait(s) and for this reason has been criticized as inefficient
The genomic selection (GS) scheme was to rectify the deficiency of MAS and MARS schemes. The GS scheme utilizes information from genome-wide marker data whether or not their associations with the concerned trait(s) are significant.
GEBV: GenomicEstimated Breeding Values-
The sum total of effects associated with all the marker alleles present in the individual and included in the GS model applied to the population under selection
Calculated on a single individual basis
Gene-assisted genomic selection:
A GS model that uses information about prior known QTLs, the targeted QTLs were accumulated in much higher frequencies than when the standard ridge regression was used
The sum total of effects associated with all the marker alleles present in the individual and included in the GS model applied to the population under selection
Calculated on a single individual basis
Population used:
Training population: used for training of the GS model and for obtaining estimates of the marker-associated effects needed for estimation of GEBVs of individuals/lines in the breeding population.
Breeding population: the population subjected to GS for achieving the desired improvement and isolation of superior lines for use as new varieties/parents of new improved hybrids.
Training population-
large enough: must be representative of the breeding population: max. trait variance with marker : by cluster analysis
should have either equal or comparable LD, LD decay rates with breeding populations
Updated by including individuals/lines from the breeding population
Training more than one generation
Low colinearity between markers is needed since high colinearity tends to reduce prediction accuracy of certain GS models. (colinearity disturbed by recombination)
1. The document discusses three main questions regarding human evolutionary genetics: the debate between hybridization models vs. the Southern dispersal route out of Africa, the coevolution of cultural and biological diversity, and challenges to the persistence of racial paradigms given genomic data.
2. Regarding the first question, the author notes several problems with hybridization hypotheses and presents evidence supporting an earlier dispersal of modern humans out of Africa via a Southern route, avoiding contact with Neanderthals.
3. For the second question, the author reviews evidence that increases in brain size did not necessarily correlate with genes associated with cognitive functions, and that cultural and linguistic changes likely evolved in parallel with biological changes.
4.
This document summarizes research on human genetic population structure and diversity. The key points are:
- 85% of human genetic variation exists within populations, 10% among continental groups, and 5% among populations within the same continent.
- Clustering analyses of genetic data yield inconsistent groupings depending on the traits or markers used, and populations form a continuous gradient without clear boundaries.
- The patterns of genetic diversity are consistent with an origin of modern humans in Africa followed by serial founder effects during dispersal, around 56,000 years ago.
1. The document compares genetic and linguistic diversity in Europe and finds some correlations between the two.
2. Structural features of languages may provide a better basis for comparison than vocabulary. Principal component analysis of genetic and linguistic data show some similarities in clustering.
3. Recent population mixing can account for some inconsistencies between the genetic and linguistic patterns. Overall, geography, genetics, and language are interrelated but influenced by separate evolutionary processes over long time periods.
1. The human genome is very similar to the chimpanzee genome, with individual genetic diversity among humans being the lowest of all primates.
2. While population differences among humans are also relatively low, genetic studies show inconsistent clustering of genotypes across genes and loci.
3. Models of human migration out of Africa best explain observed genetic patterns, with gradients of diversity correlated with distance from Africa.
Andrea Baucon, corso di paleontologia - lezione 11 - evoluzione 2 (speciazione)Andrea Baucon
Impara i concetti, gli strumenti e le tecniche per esplorare il registro fossile! In questa presentazione apprenderai come fa una nuova specie ad evolversi. La presentazione fa parte del corso di Paleontologia tenuto da Andrea Baucon presso l'Università di Trieste.
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Learn the concepts, tools and techniques to explore the fossil record! In this presentation you will learn how does a new species evolve. The presentation is part of the palaeontology course taught by Andrea Baucon at the University of Trieste, Italy.
Perché alle Olimpiadi le gare di sprint le vincono sempre atleti caraibici, le maratone gli africani dell'est, che però nel nuoto non combinano niente? Non sarà che ci sono differenze razziali? La risposta, ancora una volta, è no.
2. Programma del corso
1. Diversità genetica
2. Equilibrio di Hardy-Weinberg
3. Inbreeding
4. Linkage disequilibrium
5. Mutazione
6. Deriva genetica
7. Flusso genico e varianze genetiche
8. Selezione
9. Mantenimento dei polimorfismi e teoria neutrale
10. Introduzione alla teoria coalescente
11. Struttura e storia della popolazione umana
+ Lettura critica di articoli
3. Unione non casuale
• Quando la scelta del partner riproduttivo non è
casuale rispetto al suo genotipo si parla di unione
assortativa
4. L’unione assortativa è positiva
quando si scelgono
preferenzialmente partner
geneticamente affini,
negativa quando avviene il
contrario
Aumentato rischio di omozigosi per alleli patologici recessivi
Suddivisione del pool genico che favorisce la speciazione
5. Unione non casuale
• L’unione assortativa positiva provoca un deficit di
eterozigoti rispetto alle attese di Hardy-Weinberg
• Il deficit di eterozigoti viene misurato dal coefficiente F di
inbreeding
• Coefficienti di inbreeding possono essere stimati dalle
frequenze genotipiche o dagli alberi genealogici
• L’inbreeding è conseguenza anche del fatto che il numero
di antenati di ognuno raddoppia ad ogni generazione,
mentre le popolazioni hanno dimensioni finite
6. Unione assortativa positiva per le dimensioni corporee:
Asellus aquaticus
(isopodi)
Gammarus pulex
(gambero d’acqua dolce, amfipodi)
Unione assortativa positiva per la morfologia
Salvelinus alpinus
(salmerino, salmonidi)
Plecia nearctica
(lovebug, ditteri)
7. Unione assortativa positiva per
caratteristiche comportamentali
In molti uccelli le femmine preferiscono
accoppiarsi con maschi che cantano lo stesso
dialetto cantato dai loro padri.
Zonotrichia leucophrys
(white-crowned sparrow)
Agelaius phoeniceus
(merlo ala rossa)
8. Unione assortativa negativa: alleli di
autoincompatibilità nelle piante
An incompatible pollination in Brassica showing the
inhibition of self-pollen (Po) and the inability of the
emerging pollen tube (Pt) to invade the wall of a stigma
epidermal cell (SE).
Effect of the S (sterility) locus.
The number of S-locus alleles is usually large, being
estimated at 22 in Iberis, 34 in Raphanus, 50 in B.
oleracea and 30 in B. campestris.
Da Nasrallah (1997) PNAS
9. Vediamo se ci siamo capiti
Il numero di alleli al locus S è generalmente elevato usually large, e si stima che sia
50 in Brassica oleracea.
La fecondazione fallisce se il granulo pollinico ha lo stesso genotipo delle cellule
ovariche.
Qual è la probabilità P(x) che ci sia incrocio fra due individui che, per caso, hanno
genotipo identico?
Bisogna fare qualche assunzione: p. es., ogni allele ha la stessa frequenza.
Con 50 alleli, ognuno ha frequenza q=0.02
P(x) = 0.022 x 50 = 0.0004 x 50 =
0.02
E, più in generale, se n è il numero degli alleli: P(x)
= 1/n2 x n = 1/n
Dunque, 1 diviso il numero degli alleli è la frazione di incroci possibili che falliscono per
autoincompatibilità, cioè il prezzo (riduzione di fertilità) che la pianta paga al
meccanismo che evita l’autofecondazione
10. Abbiamo tanti antenati
6 miliardi di nucleotidi nel genoma umano
1750: 1024 antenati
1500: 1 milione
1240: 1 miliardo
1000: 1000 miliardi
250 aC: 1030
Madre
4 nonni
16 trisavoli
Padre
Figlio
8 bisnonni
32 antenati 4 generazioni fa
e ciascuno ci ha trasmesso un pezzetto del suo genoma
11.
12.
13.
14.
15.
16. Probabilità di identità per discesa di un allele
P = 1/26 = 1/64
Vale sia per A che per a
La probabilità complessiva è
F = 1/32 = 0.03125
21. Stima del coefficiente di inbreeding da pedigree
Il valore di F è pari a ½ elevato a una potenza pari al numero di
passaggi nel pedigree.
Valore di F nella progenie di varie unioni consanguinee:
Autofecondazione: ½
Fra fratello e sorella: ¼
Fra zio e nipote: 1/8
Fra cugini primi: 1/16
Fra cugini 1 e ½: 1/32
Fra cugini secondi: 1/64
…
23. Unione assortativa positiva: autofecondazione
f(AA) = ¼
f(Aa) = ½
f(aa) = ¼
¼ AA x AA 100% AA
½ Aa x Aa ¼ AA, ½ Aa, ¼ aa
¼ aa x aa
100% aa
f(AA) = ¼ + (½ x ¼) f(Aa) = 1/4 f(aa) = ¼ + (½ x ¼)
f(AA) = 3/8
f(Aa) = ¼
f(aa) = 3/8
24. Unione assortativa positiva: autofecondazione
f(AA) = 3/8
f(Aa) = ¼
f(aa) = 3/8
3/8 AA x AA 100% AA
¼ Aa x Aa ¼ AA, ½ Aa, ¼ aa
3/8 aa x aa
100% aa
f(AA) = 3/8 + (¼ x ¼) f(Aa) = 1/8 f(aa) = 3/8 + (¼ x ¼)
f(AA) = 7/16
f(Aa) = 1/8
f(aa) = 7/16
25. Unione assortativa positiva: autofecondazione
Generazione
1
2
3
4
N
AA
¼
3/8
7/16
15/32
Aa
½
1/4
1/8
1/16
1/2N
aa
¼
3/8
7/16
15/32
28. Unione assortativa positiva: inbreeding
Se Foss(Aa) = H
Fatt(Aa) = H0 = 2pq
(H0 – H) / H0 = F coefficiente di inbreeding
FH0 = H0 – H
H = H0 – FH0 , ma H0 = 2pq
H = 2pq - 2pqF = 2pq(1-F)
Un coefficiente di inbreeding pari a F porta a un deficit di
eterozigoti pari a (1-F): metà AA e metà aa
31. Nessuno è immune dall’inbreeding
40 generazioni fa (1000 dC): 1 000 000 000 000 antenati
Popolazione stimata della terra: 100 000 000
80 generazioni fa: 1030 antenati
Popolazione stimata della terra: 10 000 000
1000 generazioni fa: 10300 antenati
Popolazione stimata della terra: 1 000 000
Quindi:
Del milione di individui presenti 25 000 anni fa, molti non hanno lasciato
discendenti, molti non sono nostri antenati, altri lo sono miliardi di volte
Le nostre genealogie sono tutte fortemente intrecciate
32. Riassunto
• L’unione assortativa positiva provoca un deficit di
eterozigoti rispetto alle attese di Hardy-Weinberg
• Il deficit di eterozigoti viene misurato dal coefficiente F di
inbreeding
• Coefficienti di inbreeding possono essere stimati dalle
frequenze genotipiche o dagli alberi genealogici
• L’inbreeding è conseguenza anche del fatto che il numero
di antenati di ognuno raddoppia ad ogni generazione,
mentre le popolazioni hanno dimensioni finite