How deep is deep enough for RNA-Seq profiling of bacterial transcriptomes?

被引:162
作者
Haas, Brian J. [1 ]
Chin, Melissa [1 ]
Nusbaum, Chad [1 ]
Birren, Bruce W. [1 ]
Livny, Jonathan [1 ,2 ]
机构
[1] Broad Inst MIT & Harvard, Genome Sequencing & Anal Program, Cambridge, MA 02142 USA
[2] Harvard Univ, Sch Med, Channing Lab, Brigham & Womens Hosp, Boston, MA 02115 USA
来源
BMC GENOMICS | 2012年 / 13卷
基金
美国国家卫生研究院;
关键词
FULLY AUTOMATED PROCESS; HIGH-THROUGHPUT; DIFFERENTIAL EXPRESSION; VIBRIO-CHOLERAE; CONSTRUCTION; ARCHITECTURE; DISCOVERY;
D O I
10.1186/1471-2164-13-734
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
Background: High-throughput sequencing of cDNA libraries (RNA-Seq) has proven to be a highly effective approach for studying bacterial transcriptomes. A central challenge in designing RNA-Seq-based experiments is estimating a priori the number of reads per sample needed to detect and quantify thousands of individual transcripts with a large dynamic range of abundance. Results: We have conducted a systematic examination of how changes in the number of RNA-Seq reads per sample influences both profiling of a single bacterial transcriptome and the comparison of gene expression among samples. Our findings suggest that the number of reads typically produced in a single lane of the Illumina HiSeq sequencer far exceeds the number needed to saturate the annotated transcriptomes of diverse bacteria growing in monoculture. Moreover, as sequencing depth increases, so too does the detection of cDNAs that likely correspond to spurious transcripts or genomic DNA contamination. Finally, even when dozens of barcoded individual cDNA libraries are sequenced in a single lane, the vast majority of transcripts in each sample can be detected and numerous genes differentially expressed between samples can be identified. Conclusions: Our analysis provides a guide for the many researchers seeking to determine the appropriate sequencing depth for RNA-Seq-based studies of diverse bacterial species.
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页数:11
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