Literature DB >> 20331775

Mining transcriptome sequences towards identifying adaptive single nucleotide polymorphisms in lake whitefish species pairs (Coregonus spp. Salmonidae).

Sébastien Renaut1, Arne W Nolte, Louis Bernatchez.   

Abstract

Next-generation sequencing allows the discovery of large numbers of single nucleotide polymorphisms (SNPs) in species where little genomic information was previously available. Here, we assembled, de novo, over 130 mb of non-normalized cDNA using 454 pyrosequencing data from dwarf and normal lake whitefish and backcross hybrids. Our main goals were to gather a large data set of SNP markers, document their distribution within coding regions, evaluate the effect of species divergence on allele frequencies and combine results with previous genomic studies to identify candidate genes underlying the adaptive divergence of lake whitefish. We identified 6094 putative SNPs in 2674 contigs (mean size: 576 bp, range: 101-6116) and 1540 synonymous and 1734 non-synonymous mutations for a genome-wide non-synonymous to synonymous substitution rate ratio (p(N)/p(S)) of 0.37. As expected based on the young age (<15 000 years) of whitefish species pair, the overall level of divergence between them was relatively weak. Yet, 89 SNPs showed pronounced allele frequency differences between sympatric normal and dwarf whitefish. Among these, SNPs in genes annotated to energy metabolic functions were the most abundant and this, in addition to previous experimental data at the gene expression and phenotypic level, brings compelling evidence that genes involved in energy metabolism are prime candidates explaining the adaptive divergence of lake whitefish species pairs. Finally, we unexpectedly identified 44 contigs annotated to transposable elements and these were predominantly composed of backcross hybrids sequences. This indicates an elevated activity of transposable elements, which could potentially contribute to the reduced fitness of hybrids previously documented.

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Year:  2010        PMID: 20331775     DOI: 10.1111/j.1365-294X.2009.04477.x

Source DB:  PubMed          Journal:  Mol Ecol        ISSN: 0962-1083            Impact factor:   6.185


  73 in total

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Review 4.  Applications of next generation sequencing in molecular ecology of non-model organisms.

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