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HIGH‐DIMENSIONAL VARIANCE PARTITIONING REVEALS THE MODULAR GENETIC BASIS OF ADAPTIVE DIVERGENCE IN GENE EXPRESSION DURING REPRODUCTIVE CHARACTER DISPLACEMENT
Author(s) -
McGraw Elizabeth A.,
Ye Yixin H.,
Foley Brad,
Chenoweth Stephen F.,
Higgie Megan,
Hine Emma,
Blows Mark W.
Publication year - 2011
Publication title -
evolution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.84
H-Index - 199
eISSN - 1558-5646
pISSN - 0014-3820
DOI - 10.1111/j.1558-5646.2011.01371.x
Subject(s) - biology , genetics , genetic divergence , genetic variation , selection (genetic algorithm) , gene , evolutionary biology , gene expression , inbred strain , candidate gene , dna microarray , heritability , genetic diversity , population , demography , artificial intelligence , sociology , computer science
Although adaptive change is usually associated with complex changes in phenotype, few genetic investigations have been conducted on adaptations that involve sets of high‐dimensional traits. Microarrays have supplied high‐dimensional descriptions of gene expression, and phenotypic change resulting from adaptation often results in large‐scale changes in gene expression. We demonstrate how genetic analysis of large‐scale changes in gene expression generated during adaptation can be accomplished by determining high‐dimensional variance partitioning within classical genetic experimental designs. A microarray experiment conducted on a panel of recombinant inbred lines (RILs) generated from two populations of Drosophila serrata that have diverged in response to natural selection, revealed genetic divergence in 10.6% of 3762 gene products examined. Over 97% of the genetic divergence in transcript abundance was explained by only 12 genetic modules. The two most important modules, explaining 50% of the genetic variance in transcript abundance, were genetically correlated with the morphological traits that are known to be under selection. The expression of three candidate genes from these two important genetic modules was assessed in an independent experiment using qRT‐PCR on 430 individuals from the panel of RILs, and confirmed the genetic association between transcript abundance and morphological traits under selection.