Computational and analytical framework for small RNA profiling by high-throughput sequencing

被引：95

作者：

Fahlgren, Noah ^{[1
,2
]}

Sullivan, Christopher M. ^{[1
,2
]}

Kasschau, Kristin D. ^{[1
,2
]}

Chapman, Elisabeth J. ^{[1
,2
]}

Cumbie, Jason S. ^{[1
,2
]}

Montgomery, Taiowa A. ^{[1
,2
]}

Gilbert, Sunny D. ^{[1
,2
]}

Dasenko, Mark ^{[1
]}

Backman, Tyler W. H. ^{[1
,2
]}

Givan, Scott A. ^{[1
,2
]}

Carrington, James C. ^{[1
,2
]}

机构：

[1] Oregon State Univ, Ctr Genome Res & Biocomp, Corvallis, OR 97331 USA

[2] Oregon State Univ, Dept Bot & Plant Pathol, Corvallis, OR 97331 USA

来源：

RNA | 2009年 / 15卷 / 05期

关键词：

small RNA; sequencing-by-synthesis; CASHX; SAM-seq; oligoribonucleotide standards; statistical methods; ENDOGENOUS SIRNAS; MICRORNAS; PATHWAY; 21U-RNAS; IDENTIFICATION; BIOGENESIS; METABOLISM; EXPRESSION; EVOLUTION; PROTEINS;

D O I：

10.1261/rna.1473809

中图分类号：

Q5 [生物化学]; Q7 [分子生物学];

学科分类号：

071010 ; 081704 ;

摘要：

The advent of high-throughput sequencing (HTS) methods has enabled direct approaches to quantitatively profile small RNA populations. However, these methods have been limited by several factors, including representational artifacts and lack of established statistical methods of analysis. Furthermore, massive HTS data sets present new problems related to data processing and mapping to a reference genome. Here, we show that cluster-based sequencing-by-synthesis technology is highly reproducible as a quantitative profiling tool for several classes of small RNA from Arabidopsis thaliana. We introduce the use of synthetic RNA oligoribonucleotide standards to facilitate objective normalization between HTS data sets, and adapt microarray-type methods for statistical analysis of multiple samples. These methods were tested successfully using mutants with small RNA biogenesis (miRNA-defective dcl1 mutant and siRNA-defective dcl2 dcl3 dcl4 triple mutant) or effector protein (ago1 mutant) deficiencies. Computational methods were also developed to rapidly and accurately parse, quantify, and map small RNA data.

引用

页码：992 / 1002

页数：11