Figure 1

Trinity-based assembly of short-read metatranscriptomic data improves annotation. The de novo transcriptome assembler, Trinity [19], was applied to a metatranscriptomic dataset generated from a non-obese diabetic (NOD) mouse cecal sample (NOD503CecMN). The probability of obtaining a significant sequence alignment (bit score >50) to a known protein increases with contig length. Contigs greater than 79 bp demonstrate greater annotation potential compared to unassembled reads.