{"title":"Analysis of the Metatranscriptome of Microbial Communities by Comparison of Different Assembly Tools Reveals Improved Functional Annotation","authors":"C. Badapanda","doi":"10.19080/APBIJ.2017.03.555618","DOIUrl":null,"url":null,"abstract":"Before the advent of Next Generation Sequencing (NGS) technology, data generation of uncultured species along with the analysis of microbial data was limited. Advancement in the sequencing technology has revolutionized the sequencing of individual genome as well as metagenome. NGS technology coupled with the development of algorithm for analysis of NGS data have increased our understanding of microbial community structure [1,2]. In met genomic study, the information of all genes are used to interpret microbial identities up to the species or strain level [3] whereas, metatranscriptomic study reveals the gene expression patterns of active genes and their functionality in different pathways [4,5]. In both the pipeline (met genomic and metatranscriptomic), it is important to assemble the reads into contigs which represents gene objects. However, there are various challenges associated with the assembly of metatranscriptome and metagenome data, which is addressed below:","PeriodicalId":8778,"journal":{"name":"Biochemistry international","volume":"22 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2017-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biochemistry international","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.19080/APBIJ.2017.03.555618","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Before the advent of Next Generation Sequencing (NGS) technology, data generation of uncultured species along with the analysis of microbial data was limited. Advancement in the sequencing technology has revolutionized the sequencing of individual genome as well as metagenome. NGS technology coupled with the development of algorithm for analysis of NGS data have increased our understanding of microbial community structure [1,2]. In met genomic study, the information of all genes are used to interpret microbial identities up to the species or strain level [3] whereas, metatranscriptomic study reveals the gene expression patterns of active genes and their functionality in different pathways [4,5]. In both the pipeline (met genomic and metatranscriptomic), it is important to assemble the reads into contigs which represents gene objects. However, there are various challenges associated with the assembly of metatranscriptome and metagenome data, which is addressed below: