Genomewide Identification of Genes Under Directional Selection: Gene TranscriptionQST Scan in Diverging Atlantic Salmon Subpopulations

Abstract

Evolutionary genomics has benefited from methods that allow identifying evolutionarily important genomic regions on a genomewide scale, including genome scans and QTL mapping. Recently, genomewide scanning by means of microarrays has permitted assessing gene transcription differences among species or populations. However, the identification of differentially transcribed genes does not in itself suffice to measure the role of selection in driving evolutionary changes in gene transcription. Here, we propose and apply a ''transcriptome scan'' approach to investigating the role of selection in shaping differential profiles of gene transcription among populations. We compared the genomewide transcription levels between two Atlantic salmon subpopulations that have been diverging for only six generations. Following assessment of normality and unimodality on a gene-per-gene basis, the additive genetic basis of gene transcription was estimated using the animal model. Gene transcription h 2 estimates were significant for 1044 (16%) of all detected cDNA clones. In an approach analogous to that of genome scans, we used the distribution of the Q ST values estimated from intra-and intersubpopulation additive genetic components of the transcription profiles to identify 16 outlier genes (average Q ST estimate ¼ 0.11) whose transcription levels are likely to have evolved under the influence of directional selection within six generations only. Overall, this study contributes both empirically and methodologically to the quantitative genetic exploration of gene transcription data.

Pervasive Sex-Linked Effects on Transcription Regulation As Revealed by Expression Quantitative Trait Loci Mapping in Lake Whitefish Species Pairs (Coregonus sp., Salmonidae)

“…To date, eQTL mapping has not been specifically applied toward investigating the regulation architecture of genes involved in the process of recent population divergence in the wild. However, this should be a fundamental research goal since variation in gene expression within and between natural populations has been recently reported to underlie adaptation (Gibson 2002;Oleksiak et al 2002Oleksiak et al , 2005Bochdanovits et al 2003;Whitehead and Crawford 2005;Roberge et al 2007). Investigating the genetic architecture of transcriptome regulation in natural populations or closely related species exhibiting phenotypic divergence related to distinct environmental responses provides a powerful means to reach a more complete understanding of the molecular mechanisms related to the process of adaptive phenotypic divergence, which in turn are involved in the course of speciation events.…”

Additive transcriptomic variation associated with reproductive traits suggest local adaptation in a recently settled population of the Pacific oyster, Crassostrea gigas

“…This could be explained by the fact that eP ST estimates were only performed on transcripts showing additive patterns and that most of the eP ST outliers did not have a high p-value in the ANOVA analysis. Roberge et al [37], who find similar discordant results between ANOVA and Q ST estimates on salmon, suggested evolution as consequence of selection but without an additive genetic basis for these traits. eP ST estimates performed separately on males and females, demonstrates that considering sexes separately, when sex effect is so strong on gene expression patterns like in in gonads, could help in highlighting new candidates.…”

“…Furthermore, comparing the extent of quantitative genetic differences of phenotypic traits among populations could be assessed by the degree of differentiation in quantitative traits Q ST [33] that has been widely used to assess the relative contributions of selection to phenotypic traits divergence [34,35] and gene transcription profiles [36]. Transcriptomic scan (eQ ST ) can indeed reveal adaptation, as outlier genes, showing the highest levels of differentiation between populations, will represent those that are most likely to evolve under directional selection [37]. Conversely, P ST (differentiation phenotypic traits) and eP ST scan can reveal selective selection [38].…”

Landscape Genomics in Livestock

“…Bonin, 2008;Akey, 2009) that can be used to identify candidate genes for functional analysis (Akey et al, 2002;Vigouroux et al, 2002;Roberge et al, 2007;Bonin et al, 2009;Bigham et al, 2010).…”