title: Gene finding in metatranscriptomic sequences.
abstract: BACKGROUND
  Metatranscriptomic sequencing is a highly sensitive bioassay of functional activity in a microbial community, providing complementary information to the metagenomic sequencing of the community. The acquisition of the metatranscriptomic sequences will enable us to refine the annotations of the metagenomes, and to study the gene activities and their regulation in complex microbial communities and their dynamics.
  
  
  RESULTS
  In this paper, we present TransGeneScan, a software tool for finding genes in assembled transcripts from metatranscriptomic sequences. By incorporating several features of metatranscriptomic sequencing, including strand-specificity, short intergenic regions, and putative antisense transcripts into a Hidden Markov Model, TranGeneScan can predict a sense transcript containing one or multiple genes (in an operon) or an antisense transcript.
  
  
  CONCLUSIONS
  We tested TransGeneScan on a mock metatranscriptomic data set containing three known bacterial genomes. The results showed that TranGeneScan performs better than metagenomic gene finders (MetaGeneMark and FragGeneScan) on predicting protein coding genes in assembled transcripts, and achieves comparable or even higher accuracy than gene finders for microbial genomes (Glimmer and GeneMark). These results imply, with the assistance of metatranscriptomic sequencing, we can obtain a broad and precise picture about the genes (and their functions) in a microbial community.
  
  
  BACKGROUND
  TransGeneScan is available as open-source software on SourceForge at https://sourceforge.net/projects/transgenescan/.
authors.forename: Wazim Mohammed
authors.initials: WM
authors.lastname: Ismail
authors.forename: Yuzhen
authors.initials: Y
authors.lastname: Ye
authors.forename: Haixu
authors.initials: H
authors.lastname: Tang
mesh_terms: D001419:Bacteria / Q000235:genetics*; D005798:Genes, Bacterial; D016680:Genome, Bacterial; D008390:Markov Chains; D054892:Metagenome; D056186:Metagenomics / Q000379:methods*; D008957:Models, Genetic; D009876:Operon; D016372:RNA, Antisense / Q000235:genetics; D017423:Sequence Analysis, RNA / Q000379:methods; D012984:Software; D059467:Transcriptome
chemical_list: D016372:RNA, Antisense