Refined ab initio gene predictions of Heterorhabditis bacteriophora using RNA-seq

Int J Parasitol. 2018 Jul;48(8):585-590. doi: 10.1016/j.ijpara.2018.02.001. Epub 2018 Mar 9.

Abstract

Interest has recently grown in developing the entomopathogenic nematode Heterorhabditis bacteriophora as a model to genetically dissect the process of parasitic infection. Despite the availability of a full genome assembly, there is substantial variation in gene model accuracy. Here, a methodology is presented for leveraging RNA-seq evidence to generate improved annotations using ab initio gene prediction software. After alignment of reads and subsequent generation of a RNA-seq supported annotation, the new gene prediction models were verified on a selection of genes by comparison with sequenced 5' and 3' rapid amplification of cDNA ends products. By utilising a whole transcriptome for genome annotation, the current reference annotation was enriched, demonstrating the importance of coupling transcriptional data with genome assemblies.

Keywords: Gene annotation; Gene modelling; Heterorhabditis bacteriophora; Nematode; RNA-seq.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Animals
  • Base Sequence
  • Molecular Sequence Annotation
  • RNA / genetics*
  • Rhabditoidea / genetics*
  • Rhabditoidea / physiology
  • Sequence Analysis, RNA / methods*

Substances

  • RNA