Transcriptomic profiling of rat liver samples in a comprehensive study design by RNA-Seq.
Transcriptomic profiling of rat liver samples in a comprehensive study design by RNA-Seq.
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DOI：
10.1038/sdata.2014.21
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发表时间：
2014
期刊：
影响因子：
9.8
通讯作者：
Xu, Joshua
中科院分区：
文献类型：
--
作者：
Gong, Binsheng;Wang, Charles;Su, Zhenqiang;Hong, Huixiao;Thierry-Mieg, Jean;Thierry-Mieg, Danielle;Shi, Leming;Auerbach, Scott S.;Tong, Weida;Xu, Joshua
RNA-Seq提供了从基因表达、等位基因特异性表达、选择性剪接、融合基因检测等多个层面表征整个转录组的能力。美国FDA主导的SEQC（即MAQC-III）项目进行了一项全面的研究，重点关注经27种化学物质处理的大鼠肝脏样本的转录组分析，以评估RNA-Seq在安全性评估和毒性机制阐明中的效用。这些化学物质代表多种化学基因组作用模式 (MOA)，并表现出不同程度的转录反应。使用 Illumina HiScanSQ 和/或 HiSeq 2000 生成双端 100bp 测序数据。除了核心研究外，还对六只动物（即三只黄曲霉毒素 B1 处理的大鼠和三只媒介对照大鼠）进行了 3 次测序，并在两台测序机上进行了两次单独的文库制备。这个大型毒物基因组学数据集可以作为表征化学扰动副产品的转录组变化（例如选择性剪接）各个方面的资源。
RNA-Seq provides the capability to characterize the entire transcriptome in multiple levels including gene expression, allele specific expression, alternative splicing, fusion gene detection, and etc. The US FDA-led SEQC (i.e., MAQC-III) project conducted a comprehensive study focused on the transcriptome profiling of rat liver samples treated with 27 chemicals to evaluate the utility of RNA-Seq in safety assessment and toxicity mechanism elucidation. The chemicals represented multiple chemogenomic modes of action (MOA) and exhibited varying degrees of transcriptional response. The paired-end 100 bp sequencing data were generated using Illumina HiScanSQ and/or HiSeq 2000. In addition to the core study, six animals (i.e., three aflatoxin B1 treated rats and three vehicle control rats) were sequenced three times, with two separate library preparations on two sequencing machines. This large toxicogenomics dataset can serve as a resource to characterize various aspects of transcriptomic changes (e.g., alternative splicing) that are byproduct of chemical perturbation.
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影响因子：
46.9
作者：
Trapnell C;Williams BA;Pertea G;Mortazavi A;Kwan G;van Baren MJ;Salzberg SL;Wold BJ;Pachter L
通讯作者：
Pachter L
影响因子：
46.9
作者：
Wang, Charles;Gong, Binsheng;Bushel, Pierre R.;Thierry-Mieg, Jean;Thierry-Mieg, Danielle;Xu, Joshua;Fang, Hong;Hong, Huixiao;Shen, Jie;Su, Zhenqiang;Meehan, Joe;Li, Xiaojin;Yang, Lu;Li, Haiqing;Labaj, Pawel P.;Kreil, David P.;Megherbi, Dalila;Gaj, Stan;Caiment, Florian;van Delft, Joost;Kleinjans, Jos;Scherer, Andreas;Devanarayan, Viswanath;Wang, Jian;Yang, Yong;Qian, Hui-Rong;Lancashire, Lee J.;Bessarabova, Marina;Nikolsky, Yuri;Furlanello, Cesare;Chierici, Marco;Albanese, Davide;Jurman, Giuseppe;Riccadonna, Samantha;Filosi, Michele;Visintainer, Roberto;Zhang, Ke K.;Li, Jainying;Hsieh, Jui-Hua;Svoboda, Daniel L.;Fuscoe, James C.;Deng, Youping;Shi, Leming;Paules, Richard S.;Auerbach, Scott S.;Tong, Weida
通讯作者：
Tong, Weida
影响因子：
5.4
作者：
Malone JH;Oliver B
通讯作者：
Oliver B
影响因子：
12.3
作者：
Langmead B;Trapnell C;Pop M;Salzberg SL
通讯作者：
Salzberg SL
影响因子：
48
作者：
Mortazavi, Ali;Williams, Brian A.;Wold, Barbara
通讯作者：
Wold, Barbara