SOAPdenovo-Trans: de novo transcriptome assembly with short RNA-Seq reads

Yinlong Xie; Gengxiong Wu; Jingbo Tang; Ruibang Luo; Jordan Patterson; Shanlin Liu; Weihua Huang; Guangzhu He; Shengchang Gu; Shengkang Li; Xin Zhou; Tak-Wah Lam; Yingrui Li; Xun Xu; Gane Ka-Shu Wong; Jun Wang

doi:10.1093/bioinformatics/btu077

SOAPdenovo-Trans: de novo transcriptome assembly with short RNA-Seq reads

Bioinformatics. 2014 Jun 15;30(12):1660-6. doi: 10.1093/bioinformatics/btu077. Epub 2014 Feb 13.

Authors

Affiliations

¹ School of Bioscience and Bioengineering, South China University of Technology 510006, Guangzhou, China, BGI-Shenzhen, Shenzhen 518083, China, HKU-BGI Bioinformatics Algorithms and Core Technology Research Laboratory and Department of Computer Science, University of Hong Kong, Pokfulam, Hong Kong, Institute of Biomedical Engineering, XiangYa School of Medicine, Central South University, Changsha 410008, China, BGI-tech, BGI-Shenzhen, Shenzhen 518083, China, Department of Medicine, University of Alberta, Edmonton, AB T6G 2E1, Canada, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China, Department of Biological Sciences, University of Alberta, Edmonton, AB T6G 2E9, Canada, The Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen DK-2200, Denmark, Department of Biology, University of Copenhagen, Copenhagen DK-2200, Denmark and Princess Al Jawhara Center of Excellence in the Research of Hereditary Disorders, King Abdulaziz University, Jeddah 21589, Saudi ArabiaSchool of Bioscience and Bioengineering, South China University of Technology 510006, Guangzhou, China, BGI-Shenzhen, Shenzhen 518083, China, HKU-BGI Bioinformatics Algorithms and Core Technology Research Laboratory and Department of Computer Science, University of Hong Kong, Pokfulam, Hong Kong, Institute of Biomedical Engineering, XiangYa School of Medicine, Central South University, Changsha 410008, China, BGI-tech, BGI-Shenzhen, Shenzhen 518083, China, Department of Medicine, University of Alberta, Edmonton, AB T6G 2E1, Canada, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China, Department of Biological Sciences, University of Alberta, Edmonton, AB T6G 2E9, Canada, The Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen DK-2200, Denmark, Department of Biology, University of Copenhagen, Copenhagen DK-2200, Denmark and Princess Al Jawha
² School of Bioscience and Bioengineering, South China University of Technology 510006, Guangzhou, China, BGI-Shenzhen, Shenzhen 518083, China, HKU-BGI Bioinformatics Algorithms and Core Technology Research Laboratory and Department of Computer Science, University of Hong Kong, Pokfulam, Hong Kong, Institute of Biomedical Engineering, XiangYa School of Medicine, Central South University, Changsha 410008, China, BGI-tech, BGI-Shenzhen, Shenzhen 518083, China, Department of Medicine, University of Alberta, Edmonton, AB T6G 2E1, Canada, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China, Department of Biological Sciences, University of Alberta, Edmonton, AB T6G 2E9, Canada, The Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen DK-2200, Denmark, Department of Biology, University of Copenhagen, Copenhagen DK-2200, Denmark and Princess Al Jawhara Center of Excellence in the Research of Hereditary Disorders, King Abdulaziz University, Jeddah 21589, Saudi Arabia.

PMID: 24532719
DOI: 10.1093/bioinformatics/btu077

Abstract

Motivation: Transcriptome sequencing has long been the favored method for quickly and inexpensively obtaining a large number of gene sequences from an organism with no reference genome. Owing to the rapid increase in throughputs and decrease in costs of next- generation sequencing, RNA-Seq in particular has become the method of choice. However, the very short reads (e.g. 2 × 90 bp paired ends) from next generation sequencing makes de novo assembly to recover complete or full-length transcript sequences an algorithmic challenge.

Results: Here, we present SOAPdenovo-Trans, a de novo transcriptome assembler designed specifically for RNA-Seq. We evaluated its performance on transcriptome datasets from rice and mouse. Using as our benchmarks the known transcripts from these well-annotated genomes (sequenced a decade ago), we assessed how SOAPdenovo-Trans and two other popular transcriptome assemblers handled such practical issues as alternative splicing and variable expression levels. Our conclusion is that SOAPdenovo-Trans provides higher contiguity, lower redundancy and faster execution.

Availability and implementation: Source code and user manual are available at http://sourceforge.net/projects/soapdenovotrans/.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Algorithms*
Alternative Splicing
Animals
Gene Expression Profiling / methods*
Genomics / methods
High-Throughput Nucleotide Sequencing / methods*
Mice
Oryza / genetics
Sequence Analysis, RNA / methods*