a some basic concepts in genetics revised

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    2 Some basic concepts in genetics

    Fred van Eeuwijk, Marcos Malosetti, Hans Jansen & Martin BoerWageningen, June 2011

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    Phenotype, Genotype and Environment

    Phenotype =

    Function of

    Genotype

    Genes, QTLs

    Environment

    Is this a sufficient description?

    Which genotype-to-phenotype (G2P) function transforms the genotype in

    the phenotype (additive, multiplicative, crop growth model, network

    model)?

    What is a genotype (single/multi-locus, interactions within and between

    loci)?

    How does the environment enter the G2P function (GxE, environmentalcharacterization)?

    What about intermediate omics-levels between genotype and phenotype?

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    An ambitious definition

    Task of statistical modeling in (plant)

    genetics:

    Predict phenotypic expression for from molecular marker variation, genomic information

    and environmental inputs

    for various types of (offspring) populations

    across a range of environmental conditions for multiple traits

    over developmental time

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    Before QTL mapping

    Recombination

    Types of breeding populations

    Phenotypic and genotypic values

    Genetic variance, heritability

    Genetic architecture

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    Recombination in F2

    Marker 1

    Marker 2

    Marker 1

    Marker 2

    Marker 1

    Marker 2

    Three-generation pedigree

    Grandparents

    Parent

    Gametes

    produced

    by parent

    Molecular marker =

    short DNA segment

    point on one of the chromosomes

    = locus

    (plural: loci)

    Allele =

    DNA variant

    grandmaternal variant:grandpaternal variant:

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    Recombination in F2

    Marker 1

    Marker 2

    Marker 1

    Marker 2

    Marker 1

    Marker 2

    Three-generation pedigree

    Grandparents

    Parent

    Gametes

    produced

    by parent

    Marker 1

    Marker 2

    Frequencies of gametes

    produced by parent

    2

    1 r

    2

    1 r

    2

    r

    2

    r

    r= recombination frequency

    probability that the grandparental origin of

    the allele of marker 1 is different from the

    grandparental origin of the allele of marker 2

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    Recombination in F2 and DHs

    Marker 1

    Marker 2

    Marker 1

    Marker 2

    Marker 1

    Marker 2

    Three-generation pedigree

    Grandparents

    Parent

    Gametes

    produced

    by parent

    Problem:

    we cannot observe gametes

    (haploid genotypes)

    we observe combinations of gametes

    (diploid genotypes)

    Doubled haploids

    obtained using anther/ovary culture

    Marker 1

    Marker 2

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    Estimation of recombination frequency

    JoinMap format

    Doubledhaploid1

    Doubledhaploid2

    Doubledhaploid3

    Doubledhaploid4

    Marker 1 a b b a

    Marker 2 a b a b

    In a doubled-haploid population we have four different types of marker

    data for any pair of markers:

    type observed number probability

    of doubled haploid

    a-a naa paa=(1-r)/2

    b-b nbb pbb= (1-r)/2

    b-a nba pba= r/2

    a-b nab

    pab

    =r/2

    RRN

    nnnn

    abbabbaa

    N

    nnnnabbabbaa

    N

    nrnrnrnr

    abbabbaa

    nab

    nba

    nbb

    naa

    abbabbaa

    rrC

    rrnnnn

    N

    rrrrnnnn

    N

    nnnn

    N

    ppppnnnn

    NL

    abbabbaa

    abbabbaa

    abbabbaa

    abbabbaa

    1

    1!!!!

    !

    11!!!!

    !

    !!!!

    !

    !!!!

    !

    21

    21

    2221

    21

    Likelihood:

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    Estimation of recombination frequency

    RRN rrCL 1Likelihood:

    The maximum likelihood estimator of ris obtained by maximizing the likelihoodLwith regard to r.

    Easier: take the natural logarithm of the likelihood rather than the likelihood itself.

    rRrRNC ln1lnln Log-Likelihood:

    Take derivative of log-likelihood and put result equal to zero:

    rrrNR

    rr

    RrRNr

    r

    R

    r

    RN

    1

    1

    1

    10

    Maximum likelihood estimator:N

    Rr

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    Estimation of recombination frequency

    Fisher information: Expectation with regard toRof minus the second derivative of the log-likelihood

    r

    R

    r

    RN

    r

    1

    1stderivative:

    222

    2

    1 r

    R

    r

    RN

    r

    2nd derivative:

    rrN

    rrN

    r

    Nr

    r

    NrN

    rE

    1

    1

    1

    1

    1 222

    2

    N

    rrr

    1

    var

    Variance: Inverse of Fisher information

    The variance is zero if r = 0; thevariance attains a maximum of 1/(4N) if r = .

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    Testing for linkage

    RRN rrCL 1 Maximum likelihood:

    Likelihood under assumption of no linkage (r= ):

    N

    RRN

    C

    CL

    21

    21

    21

    Likelihood ratio:

    N

    RRN

    N

    RRN

    rr

    C

    rrCLR

    21

    21

    1

    1

    10log(LR) is called the LOD score for linkage.

    Geneticists speak: a LOD of 3 means that the observed value of the recombination frequency is

    1000 times as likely as the value .

    2ln(LR) follows (approximately) a chi-square distribution with 1 degree of freedom

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    Some population types

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    F2

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    Back cross

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    Population types

    Recombinant inbred lines

    Per locus:

    every generation the proportion of

    heterozygotes is halved

    ...2,1g2

    1)g(He

    1g

    008.02

    1)8(

    7

    He

    a h b

    a

    h

    b

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    Population types

    Recombinant inbred lines

    Number of recombinant individuals:

    Nrr

    R

    21

    2

    intensity of recombination2 if r is small

    Estimate of the recombination frequency:

    RNRr 2

    By the process of repeated selfing we obtain

    (nearly) twice as many recombinations as in

    a single meiosis.

    We are able to produce denser maps

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    Accumulated recombination history

    BC and DH populations have less accumulated

    recombination than RILs and for that reason mapping inRILs can be more accurate

    The accumulated recombination history of a population

    determines how accurate QTLs can be mapped & the

    power to identify QTLs Another factor determining the power to pick up QTLs is

    the number of different genetic effects that can be picked

    up at a particular locus

    Additive + Dominance effects in F2 (Advanced Intercross Lines) Additive effects in DHs and RILs

    What about BCs?

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    Accumulated recombination history for complex populations?

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    Transforming genotype into phenotype (multi-locus)

    Genes segregating in populations affect

    phenotypic distribution of trait

    For quantitative (complex) trait there are many

    genes, whose effect in addition may depend on

    the environment (gene by environmentinteraction)

    Linear model

    P = G + E + GxE + error (field trials in plant genetics)

    Variance decomposition

    Vp= VG+ VE+ VGxE+ Verror

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    Genetic effects (Table 4.3 Lynch & Walsh)

    Additive and dominance effects for alleles

    Intrinsic property of allele, but may differ with genetic background(population)

    Average (additive) effect due to substitution of alleles

    Property of alleles in a particular population, function of intrinsic

    additive and dominance effects & genotype frequencies Breeding value

    Property of individual in particular reference population, sum of

    average effects of an individuals alleles

    Additive genetic variance

    Variance of breeding values of individuals in particular population

    Mean and genetic variance for trait under single gene in HW

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    Mean and genetic variance for trait under single gene in HW

    Additive and dominance variance (single and multiple genes)

    For multiple non interactive genes:

    Average substitution effect

    Wu, Ma & Casella, 1.7

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    Genotypic values and frequencies for 2 genes in F2

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    Back cross

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    Two locus epistatic model (F2)

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    Genotypic values and frequencies for two locus epistatic model (F2)

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    Broad sense heritability

    General

    H2= VG/[VG+ VE+ VGxE+ Verror]

    In plant breeding heritability comparison are

    made between genotypes within environments

    (eliminate VEfrom total variation)

    For homozygous population types (DH, RIL) H2

    can be manipulated by increasing number of

    environments and replicates within environmentsat which genotypes are evaluated

    H2= VG/[VG+ VGxE/nE+ Verror/nEnr]

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    Narrow sense heritability

    What is the use of broad and narrow sense heritability?

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    Estimating genetic variances and heritabilities in practice

    Create a set of crosses following specific mating

    designs and grow the offspring populations (forexample: back cross, F2, RIL, DH, etc) in field

    experiments using appropriate experimental

    design to minimize environmental disturbances in

    the estimation of quantitative genetic parameters. Example: Grow Parent 1 (P1), Parent 2 (P2), F1

    and F2together in a trial

    Then

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    Genetic architecture of quantitative trait

    Fairly large number of loci (50 or more) Additive, dominance, epistatic action & interaction

    with environment

    Magnitude of effects at different loci can vary

    considerably

    Same gene may act at different phenotypic traits:

    pleiotropy

    Genes for a trait are distributed over the genomeat random or following particular pattern

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    Estimation of gene number

    Assume two contrasting parental lines,

    homozygous and one containing all + alleles, andother allalleles, meunlinked effective genes

    with the same effect (a), purely additive

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    Summary

    Recombination

    Genotypic and average allele effect due to substitution Genetic, environmental, GxE variances

    Broad sense and narrow sense heritability

    Estimating number of genes underlying a trait