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.
1. The document discusses factors that can initiate microevolution by changing gene frequencies in populations.
2. It explains that microevolution occurs within populations and involves changes in gene frequency over time due to factors like mutation, natural selection, genetic drift, non-random mating, and gene flow.
3. For a population to evolve, at least one of the five conditions of Hardy-Weinberg equilibrium must be absent - no mutations, random mating, no natural selection, extremely large population size, or no gene flow.
This document discusses quantitative traits and heritability. It begins by defining qualitative and quantitative traits, with PKU used as an example of a qualitative trait and ADHD as an example of a quantitative trait. It then discusses how quantitative traits are assumed to arise from many genetic variants of small effect, following a normal distribution. The document also defines heritability as the proportion of trait variation attributable to genetic factors, and discusses how heritability is estimated from twin studies. It notes that heritability is population-specific. The last part discusses preparing phenotype data, including summarizing sample characteristics and trait distributions, and checking if a trait follows a normal distribution. Transformations may be needed to achieve normality before further analysis.
Quantitative Trait LOci (QTLs) Mapping: Basics procedure, principle and MethodsMahesh Hampannavar
Basics procedure, principle, and Methods of QTL mapping, preparation of linkage mapping, calculation of recombination frequency and LOD value.
For more information on Calculation of LOD value and single marker analysis contact me personally on following mail id: mahi5295@gmail.com
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.
1. The document discusses factors that can initiate microevolution by changing gene frequencies in populations.
2. It explains that microevolution occurs within populations and involves changes in gene frequency over time due to factors like mutation, natural selection, genetic drift, non-random mating, and gene flow.
3. For a population to evolve, at least one of the five conditions of Hardy-Weinberg equilibrium must be absent - no mutations, random mating, no natural selection, extremely large population size, or no gene flow.
This document discusses quantitative traits and heritability. It begins by defining qualitative and quantitative traits, with PKU used as an example of a qualitative trait and ADHD as an example of a quantitative trait. It then discusses how quantitative traits are assumed to arise from many genetic variants of small effect, following a normal distribution. The document also defines heritability as the proportion of trait variation attributable to genetic factors, and discusses how heritability is estimated from twin studies. It notes that heritability is population-specific. The last part discusses preparing phenotype data, including summarizing sample characteristics and trait distributions, and checking if a trait follows a normal distribution. Transformations may be needed to achieve normality before further analysis.
Quantitative Trait LOci (QTLs) Mapping: Basics procedure, principle and MethodsMahesh Hampannavar
Basics procedure, principle, and Methods of QTL mapping, preparation of linkage mapping, calculation of recombination frequency and LOD value.
For more information on Calculation of LOD value and single marker analysis contact me personally on following mail id: mahi5295@gmail.com
Inbreeding coefficient
Inbreeding and self-fertilization
Genotypes mate at random with respect to their genotype at this particular locus.
There are many ways in which this assumption might be violated:
• Some genotypes may be more successful in mating than others, sexual selection.
• Genotypesthataredifferentfromoneanothermaymatemoreoftenthanexpecteddisassortative mating, e.g., self-incompatibility alleles in flowering plants, MHC lociinhumans (the smelly t-shirt experiment)
• Genotypesthataresimilartooneanothermaymatemoreoftenthanexpectedassortativemating.
• Some fraction of the offspring produced may be produced asexually.
• Individuals may mate with relatives inbreeding.
– self-fertilization
– sib-mating
– first-cousin mating
– parent-offspring mating
– etc.
This presentation summarizes research on interspecific hybridization between Atlantic salmon and brown trout. The study examined hybridization in rivers in northern Spain where one species colonized areas inhabited by the other. When Atlantic salmon colonized brown trout areas, 5-10% of juveniles were found to be hybrids, with Atlantic salmon as the maternal species. Similarly, when brown trout colonized an area, 5-7% of juveniles were hybrids with brown trout as the maternal species. The research suggests that the colonizing female species exhibits relaxed mate choice, leading to initial hybridization. However, as the colonizing species expands, hybridization decreases or changes direction. Introgression between the species occurs at low levels and is unlikely
This document summarizes a presentation on genetic mapping and association mapping. It discusses genetic mapping, how it orders genes along chromosomes based on recombination frequency. It then introduces association mapping as an alternative that uses linkage disequilibrium to identify marker-trait associations in natural populations. Key factors that influence linkage disequilibrium like germplasm, recombination rates, and generations are described. The document contrasts linkage and association mapping, noting how association mapping allows for higher resolution mapping. Approaches for association mapping like candidate gene and genome-wide methods are outlined, along with their advantages and limitations.
Population Genetics 2015 03-20 (AGB 32012)Suvanthinis
The document discusses Hardy-Weinberg equilibrium, which states that allele and genotype frequencies in a population will remain constant from one generation to the next if the population is large, randomly mating, and not experiencing mutation, immigration, emigration or natural selection. It defines key population genetics terms like population, gene pool, allele frequency. It outlines the five conditions for Hardy-Weinberg equilibrium and provides an example calculation of genotype frequencies given allele frequencies in a population of cats. Factors that can disrupt Hardy-Weinberg equilibrium include small population size, non-random mating, mutation, migration, and natural selection.
This document discusses gene mapping and genetic linkage. It explains that gene mapping determines the order and relative distances between genes on chromosomes. The distance between genes, measured in centimorgans (cM), can be determined by calculating recombination frequencies between alleles from genetic crosses. A recombination frequency of 1% corresponds to 1 cM. Genes with less than 50% recombination are linked on the same chromosome, while those with over 50% recombination are far apart. While genetic distance correlates with physical distance, recombination rates are not always uniform along chromosomes. The document also demonstrates chi-square analysis to determine if two traits are independently assorted or linked.
This document discusses linkage mapping and quantitative trait locus (QTL) mapping in plants. It begins by explaining the principles of genetic linkage and crossover, and how they can be used to construct genetic linkage maps showing the relative distances between loci on chromosomes. It describes how molecular markers are used for high-density linkage mapping. It then explains how QTL mapping involves correlating marker genotypes with quantitative trait phenotypes to identify genomic regions associated with traits of interest. The document provides an example of how marker data can be analyzed to map a disease severity trait in a plant population.
Inbreeding occurs when related individuals mate and can increase the proportion of homozygosity. This raises the chances that offspring will be affected by recessive or deleterious traits, leading to genetic disorders and conditions. Inbreeding depression can result in smaller litters, lower fertility, and stillborn or deformed offspring in experiments with animals like adders. The inbreeding coefficient is used to measure inbreeding depression based on the expected and observed heterozygosity within a population. While inbreeding can establish desirable traits in livestock, it generally reduces survival and fertility over time.
Modern cytogenetic tools in crop improvementShreyas A
it includes FISH, GISH and their recent modifications such as comparative genome hybridization, chromosome painting, spectral karyotyping, multicolour FISH, fiber FISH and Q-FISH
This document discusses quantitative trait loci (QTL) analysis and mapping. It begins with a brief history of genetics and quantitative traits. QTL analysis uses phenotypic and genotypic data to link complex trait variation to genetics. There are several approaches for QTL analysis, including single marker analysis, interval mapping, and association mapping. Interval mapping uses flanking markers and likelihood estimates to more precisely map QTL locations compared to single marker analysis. Composite interval mapping further refines this by using additional markers as cofactors. The accuracy of QTL mapping is influenced by genetic and environmental factors as well as population size and experimental error. QTLs can be confirmed through multiple methods such as stability across environments or using near-isogenic lines.
This document summarizes a study that used genome wide association mapping (GWAS) and genomic selection (GS) to identify genetic markers linked to leaf tip necrosis (LTN) in wheat. GWAS identified markers linked to known LTN genes Lr34, Lr46, and Lr68, as well as novel loci on chromosomes 2BL, 3BS, 5BL and 7BS. Genomic selection models were able to accurately predict LTN, with the G-BLUP model achieving the highest prediction accuracy. The study demonstrated the utility of genotyping by sequencing (GBS) markers, GWAS and GS for dissecting complex traits in wheat breeding.
This document discusses different types of gene interactions:
1. Hereditary traits like eye color are passed from parents to offspring, while non-hereditary traits like scars are acquired during one's lifetime.
2. Examples of gene interactions include recessive epistasis in mice coat color and dominant epistasis in squash fruit color. In recessive epistasis, a recessive allele masks other alleles, while in dominant epistasis a dominant allele masks other alleles.
3. Other types of gene interactions discussed include dominant inhibitory epistasis shown in rice pigmentation, duplicate recessive epistasis in pea flower color, and polymeric gene interaction in squash fruit shape inheritance. Each interaction results
Bio 106
Lecture 11 Genes in Populations
A. Population Genetics
B. Gene Frequencies and Equilibrium
1. Gene Frequencies
2. Gene Pool
3. Model System for Population Stability (Hardy – Weinberg Law)
2
cces2015
C. Changes in Gene Frequencies
1. Mutation
2. Selection
2.1 Relative Fitness
2.2 Selections and Variability
2.3 Selection and Mating
3. Systems
4. Migration
5. Genetic Drift
3
cces2015
D. Race and Species Formation
1. The Concept of Races
2. The Concept of Species
2.1 Reproductive Isolating Mechanisms
2.2 Rapid Speciation
This document discusses population genetics and Hardy-Weinberg equilibrium. It begins by defining Hardy-Weinberg equilibrium as describing the null model of evolution for a population at genetic equilibrium. It then lists the five conditions that must be met for a population to be in Hardy-Weinberg equilibrium: 1) no genetic drift, 2) no migration, 3) no mutation, 4) no selection, and 5) random mating. The document provides examples of how to calculate allele frequencies and determine if a population is in Hardy-Weinberg equilibrium. It also discusses concepts such as genetic drift, bottleneck effects, and the founder effect.
This document discusses genetic values and means. It defines average effect as the mean deviation from the population mean of individuals with a particular allele from one parent and a random allele from the other parent. The average effect depends on gene frequency and population. Breeding value is defined as the average value of an individual's progeny, which is equal to the sum of the average effects of its alleles. Genotypic value can be partitioned into additive genetic effects, dominance deviations, and interaction deviations. Phenotypic value is the sum of these genetic effects and environmental effects.
The neutral theory of evolution proposes that most genetic mutations are selectively neutral or nearly neutral. Under this theory, genetic drift rather than natural selection is the primary determinant of whether a mutation becomes fixed in a population or lost. The neutral theory makes specific, testable predictions about levels of genetic polymorphism within species and rates of genetic divergence between species. Motoo Kimura developed the neutral theory in the 1950s-60s as an alternative to the prevailing view that natural selection determined the fate of most mutations.
This document discusses genotype-environment interaction. It begins by defining genotype-environment interaction as different genotypes responding differently to environmental variation. It then covers the history of debates around this topic. It explains that phenotype results from both genotype and environment. Several epidemiological models of genotype-environment interaction are presented. The document discusses methods of analyzing interaction, including twin and adoption studies as well as molecular analyses. It addresses modeling interaction statistically and provides some examples, like skin cancer risk with sun exposure. The significance of understanding genotype-environment interaction is explained, like improving disease prevention.
The document discusses different types of mapping populations that are commonly used in gene mapping and agricultural biotechnology. It describes F2, F2:F3, doubled haploids (DHs), recombinant inbred lines (RILs), and near-isogenic lines (NILs). Each type has advantages for specific applications, such as F2 populations for preliminary mapping and RILs for identifying tightly linked markers through repeated meiosis. DHs, RILs, and NILs are considered "immortal populations" as they can be propagated indefinitely without further segregation.
Inbreeding coefficient
Inbreeding and self-fertilization
Genotypes mate at random with respect to their genotype at this particular locus.
There are many ways in which this assumption might be violated:
• Some genotypes may be more successful in mating than others, sexual selection.
• Genotypesthataredifferentfromoneanothermaymatemoreoftenthanexpecteddisassortative mating, e.g., self-incompatibility alleles in flowering plants, MHC lociinhumans (the smelly t-shirt experiment)
• Genotypesthataresimilartooneanothermaymatemoreoftenthanexpectedassortativemating.
• Some fraction of the offspring produced may be produced asexually.
• Individuals may mate with relatives inbreeding.
– self-fertilization
– sib-mating
– first-cousin mating
– parent-offspring mating
– etc.
This presentation summarizes research on interspecific hybridization between Atlantic salmon and brown trout. The study examined hybridization in rivers in northern Spain where one species colonized areas inhabited by the other. When Atlantic salmon colonized brown trout areas, 5-10% of juveniles were found to be hybrids, with Atlantic salmon as the maternal species. Similarly, when brown trout colonized an area, 5-7% of juveniles were hybrids with brown trout as the maternal species. The research suggests that the colonizing female species exhibits relaxed mate choice, leading to initial hybridization. However, as the colonizing species expands, hybridization decreases or changes direction. Introgression between the species occurs at low levels and is unlikely
This document summarizes a presentation on genetic mapping and association mapping. It discusses genetic mapping, how it orders genes along chromosomes based on recombination frequency. It then introduces association mapping as an alternative that uses linkage disequilibrium to identify marker-trait associations in natural populations. Key factors that influence linkage disequilibrium like germplasm, recombination rates, and generations are described. The document contrasts linkage and association mapping, noting how association mapping allows for higher resolution mapping. Approaches for association mapping like candidate gene and genome-wide methods are outlined, along with their advantages and limitations.
Population Genetics 2015 03-20 (AGB 32012)Suvanthinis
The document discusses Hardy-Weinberg equilibrium, which states that allele and genotype frequencies in a population will remain constant from one generation to the next if the population is large, randomly mating, and not experiencing mutation, immigration, emigration or natural selection. It defines key population genetics terms like population, gene pool, allele frequency. It outlines the five conditions for Hardy-Weinberg equilibrium and provides an example calculation of genotype frequencies given allele frequencies in a population of cats. Factors that can disrupt Hardy-Weinberg equilibrium include small population size, non-random mating, mutation, migration, and natural selection.
This document discusses gene mapping and genetic linkage. It explains that gene mapping determines the order and relative distances between genes on chromosomes. The distance between genes, measured in centimorgans (cM), can be determined by calculating recombination frequencies between alleles from genetic crosses. A recombination frequency of 1% corresponds to 1 cM. Genes with less than 50% recombination are linked on the same chromosome, while those with over 50% recombination are far apart. While genetic distance correlates with physical distance, recombination rates are not always uniform along chromosomes. The document also demonstrates chi-square analysis to determine if two traits are independently assorted or linked.
This document discusses linkage mapping and quantitative trait locus (QTL) mapping in plants. It begins by explaining the principles of genetic linkage and crossover, and how they can be used to construct genetic linkage maps showing the relative distances between loci on chromosomes. It describes how molecular markers are used for high-density linkage mapping. It then explains how QTL mapping involves correlating marker genotypes with quantitative trait phenotypes to identify genomic regions associated with traits of interest. The document provides an example of how marker data can be analyzed to map a disease severity trait in a plant population.
Inbreeding occurs when related individuals mate and can increase the proportion of homozygosity. This raises the chances that offspring will be affected by recessive or deleterious traits, leading to genetic disorders and conditions. Inbreeding depression can result in smaller litters, lower fertility, and stillborn or deformed offspring in experiments with animals like adders. The inbreeding coefficient is used to measure inbreeding depression based on the expected and observed heterozygosity within a population. While inbreeding can establish desirable traits in livestock, it generally reduces survival and fertility over time.
Modern cytogenetic tools in crop improvementShreyas A
it includes FISH, GISH and their recent modifications such as comparative genome hybridization, chromosome painting, spectral karyotyping, multicolour FISH, fiber FISH and Q-FISH
This document discusses quantitative trait loci (QTL) analysis and mapping. It begins with a brief history of genetics and quantitative traits. QTL analysis uses phenotypic and genotypic data to link complex trait variation to genetics. There are several approaches for QTL analysis, including single marker analysis, interval mapping, and association mapping. Interval mapping uses flanking markers and likelihood estimates to more precisely map QTL locations compared to single marker analysis. Composite interval mapping further refines this by using additional markers as cofactors. The accuracy of QTL mapping is influenced by genetic and environmental factors as well as population size and experimental error. QTLs can be confirmed through multiple methods such as stability across environments or using near-isogenic lines.
This document summarizes a study that used genome wide association mapping (GWAS) and genomic selection (GS) to identify genetic markers linked to leaf tip necrosis (LTN) in wheat. GWAS identified markers linked to known LTN genes Lr34, Lr46, and Lr68, as well as novel loci on chromosomes 2BL, 3BS, 5BL and 7BS. Genomic selection models were able to accurately predict LTN, with the G-BLUP model achieving the highest prediction accuracy. The study demonstrated the utility of genotyping by sequencing (GBS) markers, GWAS and GS for dissecting complex traits in wheat breeding.
This document discusses different types of gene interactions:
1. Hereditary traits like eye color are passed from parents to offspring, while non-hereditary traits like scars are acquired during one's lifetime.
2. Examples of gene interactions include recessive epistasis in mice coat color and dominant epistasis in squash fruit color. In recessive epistasis, a recessive allele masks other alleles, while in dominant epistasis a dominant allele masks other alleles.
3. Other types of gene interactions discussed include dominant inhibitory epistasis shown in rice pigmentation, duplicate recessive epistasis in pea flower color, and polymeric gene interaction in squash fruit shape inheritance. Each interaction results
Bio 106
Lecture 11 Genes in Populations
A. Population Genetics
B. Gene Frequencies and Equilibrium
1. Gene Frequencies
2. Gene Pool
3. Model System for Population Stability (Hardy – Weinberg Law)
2
cces2015
C. Changes in Gene Frequencies
1. Mutation
2. Selection
2.1 Relative Fitness
2.2 Selections and Variability
2.3 Selection and Mating
3. Systems
4. Migration
5. Genetic Drift
3
cces2015
D. Race and Species Formation
1. The Concept of Races
2. The Concept of Species
2.1 Reproductive Isolating Mechanisms
2.2 Rapid Speciation
This document discusses population genetics and Hardy-Weinberg equilibrium. It begins by defining Hardy-Weinberg equilibrium as describing the null model of evolution for a population at genetic equilibrium. It then lists the five conditions that must be met for a population to be in Hardy-Weinberg equilibrium: 1) no genetic drift, 2) no migration, 3) no mutation, 4) no selection, and 5) random mating. The document provides examples of how to calculate allele frequencies and determine if a population is in Hardy-Weinberg equilibrium. It also discusses concepts such as genetic drift, bottleneck effects, and the founder effect.
This document discusses genetic values and means. It defines average effect as the mean deviation from the population mean of individuals with a particular allele from one parent and a random allele from the other parent. The average effect depends on gene frequency and population. Breeding value is defined as the average value of an individual's progeny, which is equal to the sum of the average effects of its alleles. Genotypic value can be partitioned into additive genetic effects, dominance deviations, and interaction deviations. Phenotypic value is the sum of these genetic effects and environmental effects.
The neutral theory of evolution proposes that most genetic mutations are selectively neutral or nearly neutral. Under this theory, genetic drift rather than natural selection is the primary determinant of whether a mutation becomes fixed in a population or lost. The neutral theory makes specific, testable predictions about levels of genetic polymorphism within species and rates of genetic divergence between species. Motoo Kimura developed the neutral theory in the 1950s-60s as an alternative to the prevailing view that natural selection determined the fate of most mutations.
This document discusses genotype-environment interaction. It begins by defining genotype-environment interaction as different genotypes responding differently to environmental variation. It then covers the history of debates around this topic. It explains that phenotype results from both genotype and environment. Several epidemiological models of genotype-environment interaction are presented. The document discusses methods of analyzing interaction, including twin and adoption studies as well as molecular analyses. It addresses modeling interaction statistically and provides some examples, like skin cancer risk with sun exposure. The significance of understanding genotype-environment interaction is explained, like improving disease prevention.
The document discusses different types of mapping populations that are commonly used in gene mapping and agricultural biotechnology. It describes F2, F2:F3, doubled haploids (DHs), recombinant inbred lines (RILs), and near-isogenic lines (NILs). Each type has advantages for specific applications, such as F2 populations for preliminary mapping and RILs for identifying tightly linked markers through repeated meiosis. DHs, RILs, and NILs are considered "immortal populations" as they can be propagated indefinitely without further segregation.
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.
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.
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. Linkage e linkage disequilibrium
Linkage: l’associazione fisica dei loci sui cromosomi,
Linkage disequilibrium: l’associazione non casuale degli alleli
di diversi loci nei cromosomi/gameti, a formare aplotipi.
Il linkage è una causa (non la sola) del linkage disequilibrum
5. Il genoma è diviso in blocchi di aplotipi, al cui interno la
ricombinazione è rara
Nove diversi aplotipi in questa regione
6. Origini del linkage disequilibrium (LD)
Alla sua comparsa, una nuova mutazione è in LD (grigio) con tutti I loci dello
stesso cromosoma. Attraverso le generazioni la ricombinazione riduce
progressivamente l’area di LD. Contano soprattutto:
1. Tasso di ricombinazione
2. Numero di generazioni
7. Quindi: Equilibrio di Hardy-Weinberg e
linkage disequilibrium
• Basta una generazione di accoppiamento casuale per
raggiungere l’equilibrio di HW a un locus
• Se si studiano più loci, possono essere necessarie
parecchie generazioni perché si raggiunga anche un
linkage equilibrium, cioé perché gli alleli siano associati
casualmente nei gameti
8. Attraverso le generazioni, il LD si riduce in
maniera esponenziale
cromosomi in LD
ricombinazione
cromosomi con assoc.
casuale degli alleli
r
(1-r)
non ricombinazione
cromosomi in LD
LD fra due loci al tempo t: Dt = (1-r)t D0
9. Attraverso le generazioni, il LD si riduce in
maniera esponenziale
Clegg, Kidwell e Horch (1980)
Dynamics of correlated
genetic systems. V. Rates of
decay of linkage
disequilibrium in
experimental populations of
Drosophila melanogaster.
Genetics 94:217-224.
10. Vediamo se ci siamo capiti
Perché il LD declina più
rapidamente del
previsto?
Perché nell’esperimento
indicato dalla linea blu
alla fine si ottiene un LD
opposto a quello di
partenza?
11. E attraverso le generazioni si riduce anche
l’area di LD
Nature Reviews Genetics 4; 701-709 (2003)
12. Se gli alleli ai due loci non sono associati in maniera casuale,
ci sarà una deviazione delle frequenze degli aplotipi (D)
rispetto alle frequenze attese:
p11 = p1q1 + D
p12 = p1q2 – D
p21 = p2q1 – D
p22 = p2q2 + D
Il parametro D è il coefficiente di linkage disequilibrium,
proposto per primi da Lewontin e Kojima (1960).
Dmax è uguale a min (p1q2, p2q1) per D>0,
o a max (-p1q1, -p2q2) per D < 0.
13.
14. Il valore assoluto di D dipende dalle frequenze alleliche,
il suo segno dalle etichette arbitrarie attribuite agli alleli
(1 o 2)
D = p11 – pA1pB1 = p11p22 – p12p21
Se pA1= pB1 = 0.50
Dmax = 0.50 - 0.25 = 0.25 (p11=0.5, p22=0.5)
Dmin = 0.00 - 0.25 = -0.25 (p12=0.5, p21=0.5)
Se pA1≠ 0.50 o pB1 ≠ 0.50, p. es. 0.20 e 0.80
Dmax = 0.20 - 0.16 = 0.04 (p11=0.2, p22=0.2, p12=0.6)
Dmin = 0.00 - 0.16 = -0.16 (p12=0.8, p21=0.2)
15.
16.
17.
18.
19. Un sito web che calcola LD
http://www.evotutor.org/EvoGen/EG4A.html
20. Non tutti i geni sono trasmessi indipendentemente,
perché ci sono più loci che cromosomi
da Kidd et al. 1999
21. Le associazioni di alleli in aplotipi variano
attraverso le popolazioni
24 = 16 possibili aplotipi
22. I livelli di linkage disequilibrium variano
attraverso le popolazioni
24. Solo una frazione degli aplotipi possibili è presente
nelle popolazioni
Crawford et al. 2004
25. Ma una larga parte degli aplotipi presenti è
condivisa fra popolazioni
Una media di 5.3 blocchi di
aplotipi per ogni regione di
genoma (15 Mb
complessivamente)
26. Rappresentazione
grafica del linkage
disequilibrium e
individuazione di
blocchi
SNP associati con una forma
di schizofrenia (parte alta del
grafico) e
blocchi di LD (in rosso, in
basso) attraverso 209 kb.
Shi et al. (2009) Common
variants on chromosome
6p22.1 are associated with
schizophrenia. Nature 460:
753-757
28. Sintesi
• Due loci sono in linkage equilibrium se le frequenze
genotipiche a un locus sono indipendenti da quelle all’altro
locus
• Il linkage disequilibrium è causato dalla mutazione e ridotto
dalla ricombinazione
• Basta una generazione di accoppiamento casuale per
raggiungere l’equilibrio di Hardy-Weinberg, ma non il LD
• Si misura il LD confrontando frequenze genotipiche
osservate e attese a due loci, tramite le statistiche r, D e D’
