De novo transcript sequence reconstruction from RNA-seq using the Trinity platform for reference generation and analysis

被引：6234

作者：

Haas, Brian J. ^{[1
]}

Papanicolaou, Alexie ^{[2
]}

Yassour, Moran ^{[1
,3
]}

Grabherr, Manfred ^{[4
]}

Blood, Philip D. ^{[5
]}

Bowden, Joshua ^{[6
]}

Couger, Matthew Brian ^{[7
]}

Eccles, David ^{[8
]}

Li, Bo ^{[9
]}

Lieber, Matthias ^{[10
]}

MacManes, Matthew D. ^{[11
]}

Ott, Michael ^{[2
]}

Orvis, Joshua ^{[12
]}

Pochet, Nathalie ^{[1
,13
]}

Strozzi, Francesco ^{[14
]}

Weeks, Nathan ^{[15
]}

Westerman, Rick ^{[16
]}

William, Thomas ^{[17
]}

Dewey, Colin N. ^{[18
]}

Henschel, Robert ^{[19
]}

Leduc, Richard D. ^{[19
]}

Friedman, Nir

Regev, Aviv ^{[1
,20
]}

机构：

[1] Broad Inst Massachusetts Inst Technol MIT & Harva, Cambridge, England

[2] Black Mt Labs, Commonwealth Sci & Ind Res Org CSIRO Ecosyst, Canberra, ACT, Australia

[3] Hebrew Univ Jerusalem, Selim & Rachel Benin Sch Comp Sci, Jerusalem, Israel

[4] Uppsala Univ, Dept Med Biochem & Microbiol, Sci Life Lab, Uppsala, Sweden

[5] Carnegie Mellon Univ, Pittsburgh Supercomp Ctr, Pittsburgh, PA 15213 USA

[6] CSIRO Informat Management & Technol, St Lucia, Qld, Australia

[7] Oklahoma State Univ, Dept Microbiol & Mol Genet, Stillwater, OK 74078 USA

[8] Griffith Univ, Genom Res Ctr, Gold Coast, Qld, Australia

[9] Univ Wisconsin, Dept Comp Sci, Madison, WI 53706 USA

[10] Tech Univ Dresden, Ctr Informat Serv & High Performance Comp ZII I, D-01062 Dresden, Germany

[11] Univ Calif Berkeley, Calif Inst Quantitat Biosci, Berkeley, CA 94720 USA

[12] Inst Genome Sci, Baltimore, MD USA

[13] Univ Ghent VIB, Dept Plant Biotechnol & Bioinformat, Dept Plant Syst Biol, Ghent, Belgium

[14] Localita Cascina Codazza, Lodi, Italy

[15] USDA ARS, Corn Insects & Crop Genet Res Unit, Ames, IA USA

[16] Purdue Univ, Genom Facil, W Lafayette, IN 47907 USA

[17] GWT TUD GmbH, Saxony, Germany

[18] Univ Wisconsin, Dept Biostat & Med Informat, Madison, WI USA

[19] Indiana Univ, Res Technol Div, Univ Informat Technol Serv, Bloomington, IN USA

[20] MIT, Howard Hughes Med Inst, Dept Biol, Cambridge, MA USA

来源：

NATURE PROTOCOLS | 2013年 / 8卷 / 08期

基金：

美国国家科学基金会; 美国国家卫生研究院;

关键词：

DIFFERENTIAL EXPRESSION ANALYSIS; GENE; QUANTIFICATION; NORMALIZATION; ALIGNMENT; GENOMICS; REVEALS; DESIGN;

D O I：

10.1038/nprot.2013.084

中图分类号：

Q5 [生物化学];

学科分类号：

071010 ; 081704 ;

摘要：

De novo assembly of RNA-seq data enables researchers to study transcriptomes without the need for a genome sequence; this approach can be usefully applied, for instance, in research on 'non-model organisms' of ecological and evolutionary importance, cancer samples or the microbiome. In this protocol we describe the use of the Trinity platform for de novo transcriptome assembly from RNA-seq data in non-model organisms. We also present Trinity-supported companion utilities for downstream applications, including RSEM for transcript abundance estimation, R/Bioconductor packages for identifying differentially expressed transcripts across samples and approaches to identify protein-coding genes. In the procedure, we provide a workflow for genome-independent transcriptome analysis leveraging the Trinity platform. The software, documentation and demonstrations are freely available from http://trinityrnaseq.sourceforge.net. The run time of this protocol is highly dependent on the size and complexity of data to be analyzed. The example data set analyzed in the procedure detailed herein can be processed in less than 5 h.

引用

页码：1494 / 1512

页数：19

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