Literature DB >> 21834575

Comparing next-generation sequencing and microarray technologies in a toxicological study of the effects of aristolochic acid on rat kidneys.

Zhenqiang Su1, Zhiguang Li, Tao Chen, Quan-Zhen Li, Hong Fang, Don Ding, Weigong Ge, Baitang Ning, Huixiao Hong, Roger G Perkins, Weida Tong, Leming Shi.   

Abstract

RNA-Seq has been increasingly used for the quantification and characterization of transcriptomes. The ongoing development of the technology promises the more accurate measurement of gene expression. However, its benefits over widely accepted microarray technologies have not been adequately assessed, especially in toxicogenomics studies. The goal of this study is to enhance the scientific community's understanding of the advantages and challenges of RNA-Seq in the quantification of gene expression by comparing analysis results from RNA-Seq and microarray data on a toxicogenomics study. A typical toxicogenomics study design was used to compare the performance of an RNA-Seq approach (Illumina Genome Analyzer II) to a microarray-based approach (Affymetrix Rat Genome 230 2.0 arrays) for detecting differentially expressed genes (DEGs) in the kidneys of rats treated with aristolochic acid (AA), a carcinogenic and nephrotoxic chemical most notably used for weight loss. We studied the comparability of the RNA-Seq and microarray data in terms of absolute gene expression, gene expression patterns, differentially expressed genes, and biological interpretation. We found that RNA-Seq was more sensitive in detecting genes with low expression levels, while similar gene expression patterns were observed for both platforms. Moreover, although the overlap of the DEGs was only 40-50%, the biological interpretation was largely consistent between the RNA-Seq and microarray data. RNA-Seq maintained a consistent biological interpretation with time-tested microarray platforms while generating more sensitive results. However, there is clearly a need for future investigations to better understand the advantages and limitations of RNA-Seq in toxicogenomics studies and environmental health research.

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Year:  2011        PMID: 21834575     DOI: 10.1021/tx200103b

Source DB:  PubMed          Journal:  Chem Res Toxicol        ISSN: 0893-228X            Impact factor:   3.739


  50 in total

1.  The concordance between RNA-seq and microarray data depends on chemical treatment and transcript abundance.

Authors:  Charles Wang; Binsheng Gong; Pierre R Bushel; Jean Thierry-Mieg; Danielle Thierry-Mieg; Joshua Xu; Hong Fang; Huixiao Hong; Jie Shen; Zhenqiang Su; Joe Meehan; Xiaojin Li; Lu Yang; Haiqing Li; Paweł P Łabaj; David P Kreil; Dalila Megherbi; Stan Gaj; Florian Caiment; Joost van Delft; Jos Kleinjans; Andreas Scherer; Viswanath Devanarayan; Jian Wang; Yong Yang; Hui-Rong Qian; Lee J Lancashire; Marina Bessarabova; Yuri Nikolsky; Cesare Furlanello; Marco Chierici; Davide Albanese; Giuseppe Jurman; Samantha Riccadonna; Michele Filosi; Roberto Visintainer; Ke K Zhang; Jianying Li; Jui-Hua Hsieh; Daniel L Svoboda; James C Fuscoe; Youping Deng; Leming Shi; Richard S Paules; Scott S Auerbach; Weida Tong
Journal:  Nat Biotechnol       Date:  2014-08-24       Impact factor: 54.908

2.  RNA-Seq and expression microarray highlight different aspects of the fetal amniotic fluid transcriptome.

Authors:  Lillian M Zwemer; Lisa Hui; Heather C Wick; Diana W Bianchi
Journal:  Prenat Diagn       Date:  2014-06-29       Impact factor: 3.050

3.  A Joint Bayesian Model for Integrating Microarray and RNA Sequencing Transcriptomic Data.

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4.  Application of quantitative trait locus mapping and transcriptomics to studies of the senescence-accelerated phenotype in rats.

Authors:  Elena E Korbolina; Nikita I Ershov; Leonid O Bryzgalov; Natalia G Kolosova
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5.  Integrative RNA-seq and microarray data analysis reveals GC content and gene length biases in the psoriasis transcriptome.

Authors:  William R Swindell; Xianying Xing; John J Voorhees; James T Elder; Andrew Johnston; Johann E Gudjonsson
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6.  RNA-seq data analysis at the gene and CDS levels provides a comprehensive view of transcriptome responses induced by 4-hydroxynonenal.

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Review 7.  Analysis of the transcriptome in molecular epidemiology studies.

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8.  The functional genetic link of NLGN4X knockdown and neurodevelopment in neural stem cells.

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Journal:  Hum Mol Genet       Date:  2013-05-24       Impact factor: 6.150

Review 9.  Application of toxicogenomic profiling to evaluate effects of benzene and formaldehyde: from yeast to human.

Authors:  Cliona M McHale; Martyn T Smith; Luoping Zhang
Journal:  Ann N Y Acad Sci       Date:  2014-02-26       Impact factor: 5.691

Review 10.  Development of blood biomarkers for drug-induced liver injury: an evaluation of their potential for risk assessment and diagnostics.

Authors:  David E Amacher; Shelli J Schomaker; Jiri Aubrecht
Journal:  Mol Diagn Ther       Date:  2013-12       Impact factor: 4.074

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