Evaluation of different reference based annotation strategies using RNA-Seq - a case study in Drososphila pseudoobscura.
RNA-Seq is a powerful tool for the annotation of genomes, in particular for the identification of isoforms and UTRs. Nevertheless, several software tools exist and no standard strategy to obtain a reliable annotation is yet established. We tested different combinations of the most commonly used reference-based alignment tools (TopHat, GSNAP) in combination with two frequently used reference-based assemblers (Cufflinks, Scripture) and evaluated the potential of RNA-Seq to improve the annotation of Drosophila pseudoobscura. While GSNAP maps a higher proportion of reads, TopHat resulted in a more accurate annotation when used in combination with Cufflinks. Scripture had the lowest sensitivity. Interestingly, after subsampling to the same coverage for GSNAP and TopHat, we find that both mappers have similar performance, implying that the advantage of TopHat is mainly an artifact of the lower coverage. Overall, we observed a low concordance among the different approaches tested both at junction and isoform levels. Using data from both sexes of two adult strains of D. pseudoobscura we detected alternative splicing for about 30% of the FlyBase multiple-exon genes. Moreover, we extended the boundaries for 6523 genes (about 40%). We annotated 669 new genes, 45% of them with splicing evidence. Most of the new genes are located on unassembled contigs, reflecting their incomplete annotation. Finally, we identified 99 additional new genes that are not represented in the current genome contigs of D. pseudoobscura, probably due to location in genomic regions that are difficult to assemble (e.g. heterochromatic regions).
Institut für Populationsgenetik, Vetmeduni Vienna, Vienna, Austria. nicola.palmieri@vetmeduni.ac.at
Nicola
N
Palmieri
Viola
V
Nolte
Anton
A
Suvorov
Carolin
C
Kosiol
Christian
C
Schlötterer
D000818:Animals; D004330:Drosophila / Q000235:genetics*; D012313:RNA / Q000235:genetics*; D017423:Sequence Analysis, RNA / Q000379:methods*
D012313:RNA