SNP discovery from transcriptome of the swimbladder of Takifugu rubripes

Jun Cui; Hongdi Wang; Shikai Liu; Lifu Zhu; Xuemei Qiu; Zhiqiang Jiang; Xiuli Wang; Zhanjiang Liu

doi:10.1371/journal.pone.0092502

SNP discovery from transcriptome of the swimbladder of Takifugu rubripes

PLoS One. 2014 Mar 20;9(3):e92502. doi: 10.1371/journal.pone.0092502. eCollection 2014.

Authors

Jun Cui¹, Hongdi Wang¹, Shikai Liu², Lifu Zhu³, Xuemei Qiu¹, Zhiqiang Jiang¹, Xiuli Wang¹, Zhanjiang Liu²

Affiliations

¹ Key Laboratory of Mariculture & Stock Enhancement in North China's Sea, Ministry of Agriculture, Dalian Ocean University, Dalian, China.
² The Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences and Program of Cell and Molecular Biosciences, Auburn University, Auburn, Alabama, United States of America.
³ School of Environmental and Chemical Engineering, Dalian Jiaotong University, Dalian, China.

Abstract

Single nucleotide polymorphisms (SNPs) have become the marker of choice for genome-wide association studies in many species. High-throughput sequencing of RNA was developed primarily to analyze global gene expression, while it is an efficient way to discover SNPs from the expressed genes. In this study, we conducted transcriptome sequencing of the swimbladder of Takifugu rubripes using Illumina HiSeq2000 platform to identify gene-associated SNPs in the swimbladder. A total of 30,312,181 unique-mapped-reads were obtained from 44,736,850 raw reads. A total of 62,270 putative SNPs were discovered, which were located in 11,306 expressed genes and 2,246 scaffolds. The average minor allele frequency (MAF) of the SNPs was 0.26. GO and KEGG pathway analysis were conducted to analyze the genes containing SNPs. Validation of selected SNPs revealed that 54% of SNPs (26/48) were true SNPs. The results suggest that RNA-Seq is an efficient and cost-effective approach to discover gene-associated SNPs. In this study, a large number of SNPs were identified and these data will be useful resources for population genetic study, evolution analysis, resource assessment, genetic linkage analysis and genome-wide association studies.

Publication types

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

MeSH terms

Alleles
Animals
Computational Biology / methods
Gene Frequency
Genetic Markers
Genome-Wide Association Study
Genotype
Humans
Lung
Molecular Sequence Annotation
Polymorphism, Single Nucleotide*
Reproducibility of Results
Takifugu / genetics*
Transcriptome*
Wnt Proteins / genetics

Substances

Genetic Markers
Wnt Proteins

Grants and funding

This project was supported by the Program for Liaoning Excellent Talents in University (LR201010) and the grant of Dalian Ocean University (2012HYDX07). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.