Distinguishing highly similar gene isoforms with a clustering-based bioinformatics analysis of PacBio single-molecule long reads
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- 作者：Ma Liang ; Castle Raley ; Xin Zheng ; Geetha Kutty ; Emile Gogineni…
- 关键词：PacBio ; Bioinformatics analysis ; Gene isoforms ; Repetitive sequences ; Major surface glycoprotein ; Pneumocystis ; NGS ; Uclust
- 刊名：BioData Mining
- 出版年：2016
- 出版时间：December 2016
- 年：2016
- 卷：9
- 期：1
- 全文大小：1,057 KB
- 刊物主题：Computer Appl. in Life Sciences; Computational Biology/Bioinformatics; Data Mining and Knowledge Discovery; Bioinformatics; Algorithms;
- 出版者：BioMed Central
- ISSN：1756-0381
文摘
Background Gene isoforms are commonly found in both prokaryotes and eukaryotes. Since each isoform may perform a specific function in response to changing environmental conditions, studying the dynamics of gene isoforms is important in understanding biological processes and disease conditions. However, genome-wide identification of gene isoforms is technically challenging due to the high degree of sequence identity among isoforms. Traditional targeted sequencing approach, involving Sanger sequencing of plasmid-cloned PCR products, has low throughput and is very tedious and time-consuming. Next-generation sequencing technologies such as Illumina and 454 achieve high throughput but their short read lengths are a critical barrier to accurate assembly of highly similar gene isoforms, and may result in ambiguities and false joining during sequence assembly. More recently, the third generation sequencer represented by the PacBio platform offers sufficient throughput and long reads covering the full length of typical genes, thus providing a potential to reliably profile gene isoforms. However, the PacBio long reads are error-prone and cannot be effectively analyzed by traditional assembly programs.