Principles and methods of in-silico prioritization of non-coding regulatory variants

被引:33
作者
Lee, Phil H. [1 ,2 ,3 ]
Lee, Christian [1 ,2 ,4 ]
Li, Xihao [3 ,5 ]
Wee, Brian [1 ,2 ]
Dwivedi, Tushar [1 ,2 ,6 ]
Daly, Mark [1 ,2 ,7 ]
机构
[1] Massachusetts Gen Hosp, Ctr Genom Med, Simches Res Bldg,185 Cambridge St, Boston, MA 02114 USA
[2] Harvard Med Sch, Simches Res Bldg,185 Cambridge St, Boston, MA 02114 USA
[3] Harvard TH Chan Sch Publ Hlth, Quantitat Genom Program, Boston, MA USA
[4] Harvard Univ, Dept Life Sci, Cambridge, MA 02138 USA
[5] Harvard TH Chan Sch Publ Hlth, Dept Biostat, Boston, MA USA
[6] Harvard Univ, John A Paulson Sch Engn & Appl Sci, Cambridge, MA 02138 USA
[7] Broad Inst MIT & Harvard, Program Med & Populat Genet, Cambridge, MA 02142 USA
关键词
TRANSCRIPTION FACTOR-BINDING; GENOME-WIDE ASSOCIATION; GENETIC-VARIANTS; CHROMATIN STATES; EXPRESSION; SEQUENCE; IDENTIFICATION; ANNOTATION; INSIGHTS; ELEMENTS;
D O I
10.1007/s00439-017-1861-0
中图分类号
Q3 [遗传学];
学科分类号
071007 ; 090102 ;
摘要
Over a decade of genome-wide association, studies have made great strides toward the detection of genes and genetic mechanisms underlying complex traits. However, the majority of associated loci reside in non-coding regions that are functionally uncharacterized in general. Now, the availability of large-scale tissue and cell type-specific transcriptome and epigenome data enables us to elucidate how non-coding genetic variants can affect gene expressions and are associated with phenotypic changes. Here, we provide an overview of this emerging field in human genomics, summarizing available data resources and state-of-the-art analytic methods to facilitate in-silico prioritization of non-coding regulatory mutations. We also highlight the limitations of current approaches and discuss the direction of much-needed future research.
引用
收藏
页码:15 / 30
页数:16
相关论文
共 117 条
[1]   The role of regulatory variation in complex traits and disease [J].
Albert, Frank W. ;
Kruglyak, Leonid .
NATURE REVIEWS GENETICS, 2015, 16 (04) :197-212
[2]  
Backenroth D, 2017, FUN LDA LATENT DIRIC
[3]  
Bae Jae-Bum, 2013, Genomics & Informatics, V11, P7
[4]   Methylation QTLs Are Associated with Coordinated Changes in Transcription Factor Binding, Histone Modifications, and Gene Expression Levels [J].
Banovich, Nicholas E. ;
Lan, Xun ;
McVicker, Graham ;
van de Geijn, Bryce ;
Degner, Jacob F. ;
Blischak, John D. ;
Roux, Julien ;
Pritchard, Jonathan K. ;
Gilad, Yoav .
PLOS GENETICS, 2014, 10 (09)
[5]   ChroMoS: an integrated web tool for SNP classification, prioritization and functional interpretation [J].
Barenboim, Maxim ;
Manke, Thomas .
BIOINFORMATICS, 2013, 29 (17) :2197-2198
[6]   BioProject and BioSample databases at NCBI: facilitating capture and organization of metadata [J].
Barrett, Tanya ;
Clark, Karen ;
Gevorgyan, Robert ;
Gorelenkov, Vyacheslav ;
Gribov, Eugene ;
Karsch-Mizrachi, Ilene ;
Kimelman, Michael ;
Pruitt, Kim D. ;
Resenchuk, Sergei ;
Tatusova, Tatiana ;
Yaschenko, Eugene ;
Ostell, James .
NUCLEIC ACIDS RESEARCH, 2012, 40 (D1) :D57-D63
[7]   Characterizing the genetic basis of transcriptome diversity through RNA-sequencing of 922 individuals [J].
Battle, Alexis ;
Mostafavi, Sara ;
Zhu, Xiaowei ;
Potash, James B. ;
Weissman, Myrna M. ;
McCormick, Courtney ;
Haudenschild, Christian D. ;
Beckman, Kenneth B. ;
Shi, Jianxin ;
Mei, Rui ;
Urban, Alexander E. ;
Montgomery, Stephen B. ;
Levinson, Douglas F. ;
Koller, Daphne .
GENOME RESEARCH, 2014, 24 (01) :14-24
[8]   PredictSNP: Robust and Accurate Consensus Classifier for Prediction of Disease-Related Mutations [J].
Bendl, Jaroslav ;
Stourac, Jan ;
Salanda, Ondrej ;
Pavelka, Antonin ;
Wieben, Eric D. ;
Zendulka, Jaroslav ;
Brezovsky, Jan ;
Damborsky, Jiri .
PLOS COMPUTATIONAL BIOLOGY, 2014, 10 (01)
[9]   The NIH Roadmap Epigenomics Mapping Consortium [J].
Bernstein, Bradley E. ;
Stamatoyannopoulos, John A. ;
Costello, Joseph F. ;
Ren, Bing ;
Milosavljevic, Aleksandar ;
Meissner, Alexander ;
Kellis, Manolis ;
Marra, Marco A. ;
Beaudet, Arthur L. ;
Ecker, Joseph R. ;
Farnham, Peggy J. ;
Hirst, Martin ;
Lander, Eric S. ;
Mikkelsen, Tarjei S. ;
Thomson, James A. .
NATURE BIOTECHNOLOGY, 2010, 28 (10) :1045-1048
[10]   Access to personalized medicine: factors influencing the use and value of gene expression profiling in breast cancer treatment [J].
Bombard, Y. ;
Rozmovits, L. ;
Trudeau, M. ;
Leighl, N. B. ;
Deal, K. ;
Marshall, D. A. .
CURRENT ONCOLOGY, 2014, 21 (03) :E426-E433