Journal of Microbiology and Biotechnology

The Korean Society for Microbiology and Biotechnology (한국미생물·생명공학회)
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Transcriptome Profiling and In Silico Analysis of the Antimicrobial Peptides of the Grasshopper Oxya chinensis sinuosa

  • Kim, In-Woo (Department of Agricultural Biology, National Institute of Agricultural Sciences, Rural Development Administration) ;
  • Markkandan, Kesavan (Theragen ETEX Bio Institute, Theragen Etex Inc.) ;
  • Lee, Joon Ha (Department of Agricultural Biology, National Institute of Agricultural Sciences, Rural Development Administration) ;
  • Subramaniyam, Sathiyamoorthy (Theragen ETEX Bio Institute, Theragen Etex Inc.) ;
  • Yoo, Seungil (Theragen ETEX Bio Institute, Theragen Etex Inc.) ;
  • Park, Junhyung (Theragen ETEX Bio Institute, Theragen Etex Inc.) ;
  • Hwang, Jae Sam (Department of Agricultural Biology, National Institute of Agricultural Sciences, Rural Development Administration)
  • Received : 2016.08.11
  • Accepted : 2016.08.30
  • Published : 2016.11.28
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Abstract

Antimicrobial peptides/proteins (AMPs) are present in all types of organisms, from microbes and plants to vertebrates and invertebrates such as insects. The grasshopper Oxya chinensis sinuosa is an insect species that is widely consumed around the world for its broad medicinal value. However, the lack of available genetic information for this species is an obstacle to understanding the full potential of its AMPs. Analysis of the O. chinensis sinuosa transcriptome and expression profile is essential for extending the available genetic information resources. In this study, we determined the whole-body transcriptome of O. chinensis sinuosa and analyzed the potential AMPs induced by bacterial immunization. A high-throughput RNA-Seq approach generated 94,348 contigs and 66,555 unigenes. Of these unigenes, 36,032 (54.14%) matched known proteins in the NCBI database in a BLAST search. Functional analysis demonstrated that 38,219 unigenes were clustered into 5,499 gene ontology terms. In addition, 26 cDNAs encoding novel AMPs were identified by an in silico approach using public databases. Our transcriptome dataset and AMP profile greatly improve our understanding of O. chinensis sinuosa genetics and provide a huge number of gene sequences for further study, including genes of known importance and genes of unknown function.

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