Résumé
Next-generation sequencing (NGS) technologies offer the opportunity for
population genomic study of non-model organisms sampled in the wild. The
transcriptome is a convenient and popular target for such purposes.
However, designing genetic markers from NGS transcriptome data requires
assembling gene-coding sequences out of short reads. This is a complex
task owing to gene duplications, genetic polymorphism, alternative
splicing and transcription noise. Typical assembling programmes return
thousands of predicted contigs, whose connection to the species true gene
content is unclear, and from which SNP definition is uneasy. Here, the
transcriptomes of five diverse non-model animal species (hare, turtle,
ant, oyster and tunicate) were assembled from newly generated 454 and
Illumina sequence reads. In two species for which a reference genome is
available, a new procedure was introduced to annotate each predicted
contig as either a full-length cDNA, fragment, chimera, allele, paralogue,
genomic sequence or other, based on the number of, and overlap between,
blast hits to the appropriate reference. Analyses showed that (i) the
highest quality assemblies are obtained when 454 and Illumina data are
combined, (ii) typical de novo assemblies include a majority of irrelevant
cDNA predictions and (iii) assemblies can be appropriately cleaned by
filtering contigs based on length and coverage. We conclude that robust,
reference-free assembly of thousands of genes from transcriptomic NGS data
is possible, opening promising perspectives for transcriptome-based
population genomics in animals. A Galaxy pipeline implementing our
best-performing assembling strategy is provided.