Literature DB >> 27000824

Identification of allelic expression imbalance genes in human hepatocellular carcinoma through massively parallel DNA and RNA sequencing.

Qiudao Wang1,2, Yan An1, Qing Yuan2, Yao Qi2, Ying Ou2, Junhui Chen3, Jian Huang4,5,6,7.   

Abstract

Hepatocellular carcinoma (HCC) is a common malignant tumor worldwide. The prognosis and treatment of this disease have changed little in recent decades because the mechanisms underlying most events of this disease remain obscure. Allelic variation of gene expression is associated with many important biological processes, which provide a new perspective to understand HCC pathogenesis at the molecular level. To identify allelic expression imbalance (AEI) genes in HCCs, we developed a computational method that considered accurate mapping and vigorous AEI detection using paired DNA-seq and RNA-seq data. We analyzed the DNA-seq and RNA-seq data derived from two HCC samples and two cell lines. By applying a strict criterion, a total of 203 tumor-specific AEI genes were identified with high confidence, and several genes have been reported to be associated with the migration or proliferation of cancer cells, such as the genes RELN and DHRS3. In addition, we also found some novel AEI genes in HCCs, such as HNRNPR and PTAFR. Our study provides new insight into AEI events that may contribute to understanding gene expression regulation, cell proliferation and migration, and tumorigenesis.

Entities:  

Keywords:  Allelic expression imbalance; Cancer; DNA-seq; Hepatocellular carcinoma; RNA-seq; Tumor-specific AEI gene

Mesh:

Year:  2016        PMID: 27000824     DOI: 10.1007/s12032-016-0751-y

Source DB:  PubMed          Journal:  Med Oncol        ISSN: 1357-0560            Impact factor:   3.064


  37 in total

1.  High-resolution characterization of a hepatocellular carcinoma genome.

Authors:  Yasushi Totoki; Kenji Tatsuno; Shogo Yamamoto; Yasuhito Arai; Fumie Hosoda; Shumpei Ishikawa; Shuichi Tsutsumi; Kohtaro Sonoda; Hirohiko Totsuka; Takuya Shirakihara; Hiromi Sakamoto; Linghua Wang; Hidenori Ojima; Kazuaki Shimada; Tomoo Kosuge; Takuji Okusaka; Kazuto Kato; Jun Kusuda; Teruhiko Yoshida; Hiroyuki Aburatani; Tatsuhiro Shibata
Journal:  Nat Genet       Date:  2011-04-17       Impact factor: 38.330

2.  A powerful and flexible statistical framework for testing hypotheses of allele-specific gene expression from RNA-seq data.

Authors:  Daniel A Skelly; Marnie Johansson; Jennifer Madeoy; Jon Wakefield; Joshua M Akey
Journal:  Genome Res       Date:  2011-08-26       Impact factor: 9.043

3.  Genome-wide survey of recurrent HBV integration in hepatocellular carcinoma.

Authors:  Wing-Kin Sung; Hancheng Zheng; Shuyu Li; Ronghua Chen; Xiao Liu; Yingrui Li; Nikki P Lee; Wah H Lee; Pramila N Ariyaratne; Chandana Tennakoon; Fabianus H Mulawadi; Kwong F Wong; Angela M Liu; Ronnie T Poon; Sheung Tat Fan; Kwong L Chan; Zhuolin Gong; Yujie Hu; Zhao Lin; Guan Wang; Qinghui Zhang; Thomas D Barber; Wen-Chi Chou; Amit Aggarwal; Ke Hao; Wei Zhou; Chunsheng Zhang; James Hardwick; Carolyn Buser; Jiangchun Xu; Zhengyan Kan; Hongyue Dai; Mao Mao; Christoph Reinhard; Jun Wang; John M Luk
Journal:  Nat Genet       Date:  2012-05-27       Impact factor: 38.330

4.  An ORFeome-based analysis of human transcription factor genes and the construction of a microarray to interrogate their expression.

Authors:  David N Messina; Jarret Glasscock; Warren Gish; Michael Lovett
Journal:  Genome Res       Date:  2004-10       Impact factor: 9.043

5.  Detection of splice junctions from paired-end RNA-seq data by SpliceMap.

Authors:  Kin Fai Au; Hui Jiang; Lan Lin; Yi Xing; Wing Hung Wong
Journal:  Nucleic Acids Res       Date:  2010-04-05       Impact factor: 16.971

6.  Differential and epigenetic gene expression profiling identifies frequent disruption of the RELN pathway in pancreatic cancers.

Authors:  Norihiro Sato; Noriyoshi Fukushima; Rubens Chang; Hiroyuki Matsubayashi; Michael Goggins
Journal:  Gastroenterology       Date:  2006-02       Impact factor: 22.682

7.  RNASEQR--a streamlined and accurate RNA-seq sequence analysis program.

Authors:  Leslie Y Chen; Kuo-Chen Wei; Abner C-Y Huang; Kai Wang; Chiung-Yin Huang; Danielle Yi; Chuan Yi Tang; David J Galas; Leroy E Hood
Journal:  Nucleic Acids Res       Date:  2011-12-22       Impact factor: 16.971

8.  Effect of read-mapping biases on detecting allele-specific expression from RNA-sequencing data.

Authors:  Jacob F Degner; John C Marioni; Athma A Pai; Joseph K Pickrell; Everlyne Nkadori; Yoav Gilad; Jonathan K Pritchard
Journal:  Bioinformatics       Date:  2009-10-06       Impact factor: 6.937

9.  A comprehensive comparison of RNA-Seq-based transcriptome analysis from reads to differential gene expression and cross-comparison with microarrays: a case study in Saccharomyces cerevisiae.

Authors:  Intawat Nookaew; Marta Papini; Natapol Pornputtapong; Gionata Scalcinati; Linn Fagerberg; Matthias Uhlén; Jens Nielsen
Journal:  Nucleic Acids Res       Date:  2012-09-10       Impact factor: 16.971

10.  TopHat: discovering splice junctions with RNA-Seq.

Authors:  Cole Trapnell; Lior Pachter; Steven L Salzberg
Journal:  Bioinformatics       Date:  2009-03-16       Impact factor: 6.937

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  2 in total

1.  Weighted gene co-expression network analysis of gene modules for the prognosis of esophageal cancer.

Authors:  Cong Zhang; Qian Sun
Journal:  J Huazhong Univ Sci Technolog Med Sci       Date:  2017-06-06

2.  Intrinsic MYH7 expression regulation contributes to tissue level allelic imbalance in hypertrophic cardiomyopathy.

Authors:  Judith Montag; Mandy Syring; Julia Rose; Anna-Lena Weber; Pia Ernstberger; Anne-Kathrin Mayer; Edgar Becker; Britta Keyser; Cristobal Dos Remedios; Andreas Perrot; Jolanda van der Velden; Antonio Francino; Francesco Navarro-Lopez; Carolyn Yung Ho; Bernhard Brenner; Theresia Kraft
Journal:  J Muscle Res Cell Motil       Date:  2017-11-03       Impact factor: 2.698

  2 in total

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