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Gene finding in metatranscriptomic sequences

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 o...

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Autores principales: Ismail, Wazim Mohammed, Ye, Yuzhen, Tang, Haixu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4168707/
https://www.ncbi.nlm.nih.gov/pubmed/25253067
http://dx.doi.org/10.1186/1471-2105-15-S9-S8
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author Ismail, Wazim Mohammed
Ye, Yuzhen
Tang, Haixu
author_facet Ismail, Wazim Mohammed
Ye, Yuzhen
Tang, Haixu
author_sort Ismail, Wazim Mohammed
collection PubMed
description 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. CONCLUSION: 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. AVAILABILITY: TransGeneScan is available as open-source software on SourceForge at https://sourceforge.net/projects/transgenescan/.
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spelling pubmed-41687072014-10-02 Gene finding in metatranscriptomic sequences Ismail, Wazim Mohammed Ye, Yuzhen Tang, Haixu BMC Bioinformatics Proceedings 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. CONCLUSION: 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. AVAILABILITY: TransGeneScan is available as open-source software on SourceForge at https://sourceforge.net/projects/transgenescan/. BioMed Central 2014-09-10 /pmc/articles/PMC4168707/ /pubmed/25253067 http://dx.doi.org/10.1186/1471-2105-15-S9-S8 Text en Copyright © 2014 Ismail et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/4.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Proceedings
Ismail, Wazim Mohammed
Ye, Yuzhen
Tang, Haixu
Gene finding in metatranscriptomic sequences
title Gene finding in metatranscriptomic sequences
title_full Gene finding in metatranscriptomic sequences
title_fullStr Gene finding in metatranscriptomic sequences
title_full_unstemmed Gene finding in metatranscriptomic sequences
title_short Gene finding in metatranscriptomic sequences
title_sort gene finding in metatranscriptomic sequences
topic Proceedings
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4168707/
https://www.ncbi.nlm.nih.gov/pubmed/25253067
http://dx.doi.org/10.1186/1471-2105-15-S9-S8
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