ArticleBMC bioinformatics2014
Gene finding in metatranscriptomic sequences.
Article in BMC bioinformatics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed.
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- Metatranscriptomics reveals protistan and viral metabolic reprogramming of sinking particle microbiomes in Oyashio waters.ISME communications · 2026Article
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- Widespread and active piezotolerant microorganisms mediate phenolic compound degradation under high hydrostatic pressure in hadal trenches.Marine life science & technology · 2024Article
- Biosynthetic Potential ofJournal of fungi (Basel, Switzerland) · 2023Article
- Metatranscriptomic insights into the microbial electrosynthesis of acetate by FeWorld journal of microbiology & biotechnology · 2023Article
- Metatranscriptomic Analyses Reveal Important Roles of the Gut Microbiome in Primate Dietary Adaptation.Genes · 2023Article
- Music of metagenomics-a review of its applications, analysis pipeline, and associated tools.Functional & integrative genomics · 2022Review
- Identification and structural analysis of a thermophilic β-1,3-glucanase from compost.Bioresources and bioprocessing · 2021Article
- Micropathogen community identification in ticks (Acari: Ixodidae) using third-generation sequencing.International journal for parasitology. Parasites and wildlife · 2021Article
- The reference genome and transcriptome of the limestone langur, Trachypithecus leucocephalus, reveal expansion of genes related to alkali tolerance.BMC biology · 2021Article
- Chinese Liquor Fermentation: Identification of Key Flavor-ProducingApplied and environmental microbiology · 2020Article
- Effect of Baicalin-Aluminum Complexes on Fecal Microbiome in Piglets.International journal of molecular sciences · 2019Article
- Corallivory and the microbial debacle in two branching scleractinians.The ISME journal · 2018Article
- Cloud-based adaptive exon prediction for DNA analysis.Healthcare technology letters · 2018Article
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMetatranscriptomic 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.
resultsIn 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.
conclusionWe 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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