教育资源为主的文档平台

当前位置: 查字典文档网> 所有文档分类> 高等教育> 生物学> ceRNA networks Cupid simultaneos reconstruct on of microRNA-target and

ceRNA networks Cupid simultaneos reconstruct on of microRNA-target and

上传者:李伯全
|
上传时间:2015-05-11
|
次下载

ceRNA networks Cupid simultaneos reconstruct on of microRNA-target and

内容需要下载文档才能查看

Downloaded from http://wendang.chazidian.com on November 6, 2014 - Published by Cold Spring Harbor Laboratory Press

Hua-Sheng Chiu, David Llobet-Navas, Xuerui Yang, et al. Genome Res. published online November 5, 2014Access the most recent version at doi:10.1101/gr.178194.114 Cupid: simultaneous reconstruction of microRNA-target andceRNA networksP<P AcceptedManuscript CreativeCommons License

Email AlertingServicePublished online November 5, 2014 in advance of the print journal. Peer-reviewed and accepted for publication but not copyedited or typeset; acceptedmanuscript is likely to differ from the final, published version. This article is distributed exclusively by Cold Spring Harbor Laboratory Press for thefirst six months after the full-issue publication date (see http://wendang.chazidian.com/site/misc/terms.xhtml). After six months, it is available undera Creative Commons License (Attribution-NonCommercial 4.0 International), as described at http://wendang.chazidian.com/licenses/by-nc/4.0/. Receive free email alerts when new articles cite this article - sign up in the box at thetop right corner of the article or click here.

Advance online articles have been peer reviewed and accepted for publication but have not yetappeared in the paper journal (edited, typeset versions may be posted when available prior to final publication). Advance online articles are citable and establish publication priority; they are indexedby PubMed from initial publication. Citations to Advance online articles must include the digital object identifier (DOIs) and date of initial publication.

To subscribe to Genome Research go to: http://wendang.chazidian.com/subscriptions

Published by Cold Spring Harbor Laboratory Press

Downloaded from http://wendang.chazidian.com on November 6, 2014 - Published by Cold Spring Harbor Laboratory Press

Cupid: simultaneous reconstruction of

microRNA-target and ceRNA networks

Hua-Sheng Chiu1,2,3,7,12, David Llobet-Navas8,12, Xuerui Yang9, Wei-Jen Chung1,2,3, Alberto Ambesi-Impiombato4,5, Archana Iyer1, Hyunjae Ryan Kim10, Elena G. Seviour11, Zijun Luo11, Vasudha Sehgal11, Tyler Moss11, Yiling Lu11, Prahlad Ram11, José Silva8, Gordon B Mills11, Andrea Califano1,2,3,4,5,6,* & Pavel Sumazin7,*

1

2

3

4

5

6 Department of Systems Biology, Center for Computational Biology and Bioinformatics, Department of Biomedical Informatics, Institute for Cancer Genetics, Herbert Irving Comprehensive Cancer Center, Department of Biochemistry and Molecular Biophysics,

Columbia University, New York, New York, 10032, USA

Texas Children's Cancer Center, Baylor College of Medicine, Houston, Texas, 77030, USA

Department of Pathology, Icahn School of Medicine at Mount Sinai, New York, New York, 10029, USA 78

9 MOE Key Laboratory of Bioinformatics, Tsinghua-Peking Center for Life Sciences,

School of Life Sciences, Tsinghua University, Beijing 100084, China

Laboratory of RNA Molecular Biology, Rockefeller University, 1230 York Avenue, Box 301, New York, NY 10065, USA

Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas, 77030, USA

These authors contributed equally to this work 101112

* Correspondence: califano@c2b2.columbia.edu,

Running title: Cupid: miRNA-target and ceRNA networks

Key words: microRNA, ceRNA, reverse phase protein array (RPPA), breast cancer

Page | 1

Downloaded from http://wendang.chazidian.com on November 6, 2014 - Published by Cold Spring Harbor Laboratory Press

Abstract

We introduce a method for simultaneous prediction of microRNA-target interactions and their mediated competitive endogenous RNA (ceRNA) interactions. Using high-throughput validation assays in breast cancer cell lines, we show that our integrative approach significantly improves on microRNA-target prediction accuracy as assessed by both mRNA and protein level measurements. Our biochemical assays support nearly 500 microRNA-target interactions with evidence for regulation in breast-cancer tumors. Moreover, these assays constitute the most extensive validation platform for computationally inferred networks of microRNA-target interactions in breast-cancer tumors, providing a useful benchmark to ascertain future improvements.

Page | 2

Downloaded from http://wendang.chazidian.com on November 6, 2014 - Published by Cold Spring Harbor Laboratory Press

Introduction

MicroRNAs (miRNAs) regulate RNA stability and mRNA translation (Filipowicz et al. 2008) and their dysregulation has been implicated in a wide range of human diseases including cancer (Garzon et al. 2009). Consequently, establishing accurate and comprehensive repertoires of miRNA-target interactions is a necessary step toward elucidating their mechanistic role in pathophysiology. Dissecting miRNA regulation, however, has proven challenging because candidate miRNA binding sites are ubiquitous and their regulatory effects are context specific (Liu et al. 2005; Lu et al. 2005; Mukherji et al. 2011). As a result, and despite of their relatively low accuracy, computational prediction methods that incorporate context-specific data are preferred for screening for miRNA-target interactions in tumor contexts (Carroll et al. 2013; Erhard et al. 2014).

To address these challenges, we introduce Cupid, an integrative framework for the context-specific inference of miRNA targets. Cupid integrates sequence-based evidence and functional clues derived from RNA and miRNA expression analysis, predicting candidate miRNA binding sites and associated target genes using ensemble machine learning classifiers that are trained on validated interactions. Candidate interactions emerging from this step are then refined based on independent, context specific clues, including their predicted ability to mediate competitive endogenous RNA (ceRNA) interactions, where mRNA compete for shared miRNA regulators (Fig. 1A) (Tay et al. 2014). Thus, Cupid simultaneously infers both interaction types (ceRNA and miRNA-target interactions). In addition, we considered evidence for combinatorial regulation by multiple miRNA species (Boissonneault et al. 2009; Xu et al. 2011) (Fig. 1B) and for indirect miRNA regulation through effector proteins (Fig. 1C). Taken individually, these clues are predictive of bona fide miRNA-target interactions and can significantly improve the tradeoff between precision and recall.

We show that Cupid predictions outperform other leading algorithms, based on multiple experimental assays, including PAR-CLIP data, miRNA perturbation followed by mRNA

Page | 3

Downloaded from http://wendang.chazidian.com on November 6, 2014 - Published by Cold Spring Harbor Laboratory Press

and protein expression profiles, and 3’ luciferase activity assays. Critically, while Cupid predicts fewer interactions than other methods (Fig. 1D-F), its predictions are much more likely to be consistent with experimental evidence. This is critical since high false-positive prediction rates are a key limitation of current miRNA-target prediction methods.

Results

Algorithm outline and miRNA-target prediction in breast cancer tumors

Cupid is implemented in three sequential steps (Fig. 1A). First, Cupid re-evaluates candidate miRNA binding sites in 3’ UTRs, as inferred by TargetScan (Lewis et al. 2005), miRanda (John et al. 2004) and PITA (Kertesz et al. 2007). This is accomplished by integrating their algorithm-specific scores, their location in the 3’ UTR, and their cross-species conservation. Then, miRNA-target interactions are predicted by further integrating information about selected sites, their multiplicity, and the statistical dependency between the expression profiles of miRNA and putative targets.

Likelihoods for each predictive feature are computed based on a positive gold standard set of 588 experimentally confirmed miRNA-target interactions, representing 1481 binding sites in TarBase (Papadopoulos et al. 2009), TRANSFAC (Matys et al. 2006) and miRecords (Xiao et al. 2009). They are then integrated using a support vector machine (SVM) algorithm (Chang and Lin 2011). Finally, Cupid assesses whether inferred targets compete for their predicted miRNA regulators. In the following sections, we discuss results from Cupid-inferred miRNA targets, based on gene expression profile data of TCGA breast cancer samples (The Cancer Genome Atlas 2012).

Step I (miRNA binding site analysis): miRNA binding sites in 3’ UTRs were predicted and scored independently by TargetScan, miRanda and PITA. Taken together, these algorithms predicted a total of 37M candidate binding sites (Fig. 1D). Each site was associated with the following features: (a) TargetScan, miRanda and PITA confidence scores, when available; (b) PhastCons (Siepel et al. 2005) species-conservation scores; and (c) relative distance from the 3’ and 5’ ends of the target 3’ UTR. These features Page | 4

版权声明:此文档由查字典文档网用户提供,如用于商业用途请与作者联系,查字典文档网保持最终解释权!

下载文档

热门试卷

2016年四川省内江市中考化学试卷
广西钦州市高新区2017届高三11月月考政治试卷
浙江省湖州市2016-2017学年高一上学期期中考试政治试卷
浙江省湖州市2016-2017学年高二上学期期中考试政治试卷
辽宁省铁岭市协作体2017届高三上学期第三次联考政治试卷
广西钦州市钦州港区2016-2017学年高二11月月考政治试卷
广西钦州市钦州港区2017届高三11月月考政治试卷
广西钦州市钦州港区2016-2017学年高一11月月考政治试卷
广西钦州市高新区2016-2017学年高二11月月考政治试卷
广西钦州市高新区2016-2017学年高一11月月考政治试卷
山东省滨州市三校2017届第一学期阶段测试初三英语试题
四川省成都七中2017届高三一诊模拟考试文科综合试卷
2017届普通高等学校招生全国统一考试模拟试题(附答案)
重庆市永川中学高2017级上期12月月考语文试题
江西宜春三中2017届高三第一学期第二次月考文科综合试题
内蒙古赤峰二中2017届高三上学期第三次月考英语试题
2017年六年级(上)数学期末考试卷
2017人教版小学英语三年级上期末笔试题
江苏省常州西藏民族中学2016-2017学年九年级思想品德第一学期第二次阶段测试试卷
重庆市九龙坡区七校2016-2017学年上期八年级素质测查(二)语文学科试题卷
江苏省无锡市钱桥中学2016年12月八年级语文阶段性测试卷
江苏省无锡市钱桥中学2016-2017学年七年级英语12月阶段检测试卷
山东省邹城市第八中学2016-2017学年八年级12月物理第4章试题(无答案)
【人教版】河北省2015-2016学年度九年级上期末语文试题卷(附答案)
四川省简阳市阳安中学2016年12月高二月考英语试卷
四川省成都龙泉中学高三上学期2016年12月月考试题文科综合能力测试
安徽省滁州中学2016—2017学年度第一学期12月月考​高三英语试卷
山东省武城县第二中学2016.12高一年级上学期第二次月考历史试题(必修一第四、五单元)
福建省四地六校联考2016-2017学年上学期第三次月考高三化学试卷
甘肃省武威第二十三中学2016—2017学年度八年级第一学期12月月考生物试卷

网友关注视频

外研版英语三起5年级下册(14版)Module3 Unit1
冀教版小学英语五年级下册lesson2教学视频(2)
外研版八年级英语下学期 Module3
人教版历史八年级下册第一课《中华人民共和国成立》
苏科版数学 八年级下册 第八章第二节 可能性的大小
化学九年级下册全册同步 人教版 第22集 酸和碱的中和反应(一)
【部编】人教版语文七年级下册《过松源晨炊漆公店(其五)》优质课教学视频+PPT课件+教案,江苏省
沪教版八年级下册数学练习册21.3(3)分式方程P17
每天日常投篮练习第一天森哥打卡上脚 Nike PG 2 如何调整运球跳投手感?
冀教版小学数学二年级下册第二周第2课时《我们的测量》宝丰街小学庞志荣
第8课 对称剪纸_第一课时(二等奖)(沪书画版二年级上册)_T3784187
冀教版小学英语四年级下册Lesson2授课视频
【部编】人教版语文七年级下册《逢入京使》优质课教学视频+PPT课件+教案,安徽省
外研版英语三起6年级下册(14版)Module3 Unit2
二年级下册数学第一课
外研版英语七年级下册module3 unit2第一课时
北师大版数学四年级下册第三单元第四节街心广场
沪教版牛津小学英语(深圳用) 五年级下册 Unit 12
第五单元 民族艺术的瑰宝_16. 形形色色的民族乐器_第一课时(岭南版六年级上册)_T3751175
【部编】人教版语文七年级下册《泊秦淮》优质课教学视频+PPT课件+教案,天津市
沪教版牛津小学英语(深圳用) 四年级下册 Unit 7
冀教版英语三年级下册第二课
化学九年级下册全册同步 人教版 第25集 生活中常见的盐(二)
外研版英语三起6年级下册(14版)Module3 Unit1
沪教版牛津小学英语(深圳用) 四年级下册 Unit 4
冀教版小学数学二年级下册第二单元《余数和除数的关系》
沪教版牛津小学英语(深圳用) 四年级下册 Unit 3
【部编】人教版语文七年级下册《泊秦淮》优质课教学视频+PPT课件+教案,辽宁省
冀教版英语五年级下册第二课课程解读
冀教版小学数学二年级下册第二单元《有余数除法的整理与复习》