An automated, high-throughput sequence read classification pipeline for preliminary genome characterization

Abstract In the absence of a complete genome sequence, considerable insight into genome structure can be gained from survey sequencing of genomic DNA. To facilitate high-throughput characterization of genome structure based on shotgun sequence reads, we have developed an automated sequence read classification pipeline (SRCP). The SRCP uses a battery of novel and standard sequence analysis algorithms along with a sophisticated decision tree to place reads into “best fit” functional/descriptive categories. Once “primed” with genomic sequence data, the SRCP also permits estimation of gene/repeat enrichment afforded by reduced-representation sequencing techniques. To our knowledge, the SRCP is the only tool that has been designed to provide a description of a genome or a genome component based on sample sequence reads. In an initial test of the SRCP using sequence data from Sorghum bicolor , it was shown to provide results similar in quality to results generated by manual classification. Although the SRCP is not a replacement for manual sequence characterization, it can provide a rapid, high-quality overview of genome sequence content and facilitate subsequent annotation. The SRCP presumably can be adapted for analysis of any eukaryotic genome.