Heart transcriptome of the bank vole (Myodes glareolus): towards understanding the evolutionary variation in metabolic rate

Abstract

Background: Understanding the genetic basis of adaptive changes has been a major goal of evolutionary biology. In complex organisms without sequenced genomes, de novo transcriptome assembly using a longer read sequencing technology followed by expression profiling using short reads is likely to provide comprehensive identification of adaptive variation at the expression level and sequence polymorphisms in coding regions. We performed sequencing and de novo assembly of the bank vole heart transcriptome in lines selected for high metabolism and unselected controls.

Results: A single 454 Titanium run produced over million reads, which were assembled into 63,581 contigs. Searches against the SwissProt protein database and the ENSEMBL collection of mouse transcripts detected similarity to 11,181 and 14,051 genes, respectively. As judged by the representation of genes from the heart-related Gene Ontology categories and UniGenes detected in the mouse heart, our detection of the genes expressed in the heart was nearly complete (> 95% and almost 90% respectively). On average, 38.7% of the transcript length was covered by our sequences, with notably higher (45.0%) coverage of coding regions than of untranslated regions (24.5% of 5' and 32.7% of 3'UTRs). Lower sequence conservation between mouse and bank vole in untranslated regions was found to be partially responsible for poorer UTR representation. Our data might suggest a widespread transcription from noncoding genomic regions, a finding not reported in previous studies regarding transcriptomes in non-model organisms. We also identified over 19 thousand putative single nucleotide polymorphisms (SNPs). A much higher fraction of the SNPs than expected by chance exhibited variant frequency differences between selection regimes.

Conclusion: Longer reads and higher sequence yield per run provided by the 454 Titanium technology in comparison to earlier generations of pyrosequencing proved beneficial for the quality of assembly. An almost full representation of genes known to be expressed in the mouse heart was identified. Usage of the extensive genomic resources available for the house mouse, a moderately (20-40 mln years) divergent relative of the voles, enabled a comprehensive assessment of the transcript completeness. Transcript sequences generated in the present study allowed the identification of candidate SNPs associated with divergence of selection lines and constitute a valuable permanent resource forming a foundation for RNAseq experiments aiming at detection of adaptive changes both at the level of gene expression and sequence variants, that would facilitate studies of the genetic basis of evolutionary divergence.

Figure 1

Length distribution of "cleaned" sequencing reads. "Cleaning" involved adapter trimming and removal of reads with high similarity to repetitive sequences.

Figure 2

Length distribution of contigs (note Y axis logarithmic scale).

Figure 3

Cumulative fraction of bases assembled into contigs and the cumulative assembly length. Contigs are ranked from the longest to the shortest

Figure 4

Comparison of the length distribution of transcripts detected in the bank vole with all mouse transcripts. The distribution of maximum transcript length (based on the ENSEMBL mouse database) for genes detected in the bank vole compared to the distribution for all mouse genes.

Figure 5

The completeness of the bank vole transcripts. Based on the fraction of the mouse ENSEML transcript length covered by aligned bank vole sequences. A) completeness of the total transcript length, B) completeness of the coding regions.

Figure 6

The relationship between the transcript length and transcript completeness. The relationship between the mouse transcript length and the fraction of transcript covered by the bank vole sequences. For computation of R² (0.077, P < 10^-4) transcript length was log-transformed and fraction covered arcsin square root transformed, but the plot shows, for clarity non-transformed data and only transcripts up to 12 kb.

Figure 7

Completeness of transcripts and transcript regions. Fractions of the 5' untranslated regions (5' UTR), 3' untranslated regions (3' UTR), coding sequence (cds) and of the total transcript covered by the bank vole sequences.

Figure 8

The relationship between transcript completeness and coverage. The per base coverage is averaged over the total transcript length. Only coverages up to 50 × are shown. Logarithmic curves were fitted to three subsets of the data: transcripts < 1 kb, 1-2 kb and > 2 kb.