Comparative genomics based on massive parallel transcriptome sequencing reveals patterns of substitution and selection across 10 bird species

Abstract

Next-generation sequencing technology provides an attractive means to obtain largescale sequence data necessary for comparative genomic analysis. To analyse the patterns of mutation rate variation and selection intensity across the avian genome, we performed brain transcriptome sequencing using Roche 454 technology of 10 different non-model avian species. Contigs from de novo assemblies were aligned to the two available avian reference genomes, chicken and zebra finch. In total, we identified 6499 different genes across all 10 species, with $1000 genes found in each full run per species. We found evidence for a higher mutation rate of the Z chromosome than of autosomes (male-biased mutation) and a negative correlation between the neutral substitution rate (d S ) and chromosome size. Analyses of the mean d N ⁄ d S ratio (x) of genes across chromosomes supported the Hill-Robertson effect (the effect of selection at linked loci) and point at stochastic problems with x as an independent measure of selection. Overall, this study demonstrates the usefulness of next-generation sequencing for obtaining genomic resources for comparative genomic analysis of non-model organisms.

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

“…Such a comparative genomics analysis has recently been performed in a study of avian genome evolution using 454 sequence data from 10 different bird species (Kü nstner et al, 2010). Another interesting example studied two sympatric species of crater lake cichlids (Elmer et al, 2010).…”

Obtaining mtDNA genomes from next-generation transcriptome sequencing: A case study on the basal Passerida (Aves: Passeriformes) phylogeny

“…As in prior studies (Paton et al, 2002;Slack et al, 2006), the NADH dehydrogenase 6 (ND6) gene was excluded because it is encoded on the opposite strand and has a very different base composition compared to the other mitochondrial protein-coding genes. We focused on protein-coding genes because the RNA isolation method used in Künstner et al (2010) was designed to select for transcripts with terminal poly-As (see below). We first downloaded all complete passerine mitochondrial genomes available (May 2010) in GENBANK from NCBI (http:// www.ncbi.nlm.nih.gov/), including gray-headed broadbill (Smithornis sharpei, NC_000879), fuscous flycatcher (Cnemotriccus fuscatus, NC_007975), superb lyrebird (Menura novaehollandiae, NC_000880), rook (Corvus frugilegus, NC_002069), eastern-orphean warbler (Sylvia crassirostris, NC_010229), village indigobird (Vidua chalybeata, NC_007883), zebra finch (Taeniopygia guttata, NC_007897), Taiwan (Styan's) Bulbul (Pycnonotus taivanus, NC_013483), blackcap (Sylvia atricapilla, NC_010228), and Eurasian reed warbler (Acrocephalus scirpaceus, NC_010227).…”

“…In this study we evaluated the feasibility of this approach by analyzing brain transcriptome sequences from four passerine species obtained through Roche 454 sequencing as recently reported by Künstner et al (2010). We then used these data together with 11 previously published avian mtDNA genomes to study Passerida relationships.…”

What is comparable in comparative cognition?

“…The very recent development of new sequencing technologies has revolutionized the rate at which new genome data are being generated and analysed [102], so allowing increasing numbers of taxa to be studied at depths previously possible for just a tiny number of model organisms. The associated boom in studies of phylogenomics, population genomics and genome-wide associations all present unprecedented opportunities for gene discovery, allowing us to distinguish between ancestral and derived character states for thousands of loci [103,104]. Combining such gene sequence data with transgenic and recombinant technologieswhich are already being applied to studies of cognition [58,105]-offers a promising and powerful means of dissecting the commonalities and differences in neuro-computational and cognitive processing in a comparative framework.…”