Guilherme J. M. Rosa Department of Animal Sciences

Department of Biostatistics & Medical Informatics

57a Reunião da RBRAS 5-9 de maio de 2012 - Piracicaba/SP

Modelagem Estatística Aplicada à Genética Quantitativa e Genômica

Quantitative Genetics and Genomics

Evolution

Medicine

Conservation

Agriculture breeding programs

Statistics in Genetics and Genomics

•  Genomic resources: genome assembling (sequencing errors), alignment algorithms

•  Gene expression: microarray analysis, NGS, proteomics

•  Genomic variation between populations/species: phylogenetic analysis

•  Genetic and genomic variation within populations: mixed models (genetic relationship matrix), molecular marker analysis

•  Gene (marker) – phenotype association: QTL analysis, GWAS, prediction of phenotype

Phenotypic Variation

Nature vs. Nurture

Simply-Inherited Traits

Complex traits

Mendel: Experiment 1

Simply Inherited Traits

A1A2 A1A2

25% A1A1 + 50% A1A2 + 25% A2A2

Genotypes A1A1 A1A2 A2A2

Observed O11 O12 O22

Expected E11 E12 E22

E11 = 0.25 × N E12 = 0.50 × N E22 = 0.25 × N

N = O11 + O12 + O22

2)1k(

k

1i i

2ii2 ~

E)EO(X −

=

χ−

=∑k: # of classes

Testing for Segregation Distortion

▪ Sire 1 and GG dams: significant excess of GG vs. GC embryos ▪ Sire 3: significant segregation distortion in all pairings - decreased number of embryos with the GG genotype - only 2 surviving GG embryos produced from GG dams, compared

to 14 GC embryos - no GG genotypes were detected with GC dams - mating with CC dams resulted in an excess of CC vs. GC embryos

(Khatib et al., 2008)

Phenotype = Genetics + Environment

iii GP ε++µ=

Basic Genetic Model

Pi = phenotypic value of individual i µ = population mean Gi = genotypic value of individual i εi = environmental effects

Gene combination value (non-additive genetic effects) Breeding value

(additive genetic effects)

iii GCVBVG +=

Heritability

)(V)GCV(V)BV(V)P(V ε++=→ε+++µ= GCVBVP

ð Heritability, narrow sense (h2): )P(V)BV(Vh2 =

)P(V)GCV(V)BV(VH2 +

=ð Heritability, broad sense (H2):

OUTLINE

Ø DNA Sequence; genomic variation

Ø Phenotypic and genetic variation

Ø Gene expression; transcriptome

Ø Genotype-phenotype association; QTL mapping

•  Basic background

•  Statistical issues -  Dimensionality -  n << p - Multiple testing

Illustrative examples using SAS Software

Alternatively

http://www.bioconductor.org/

http://www.r-project.org/