Whole genome sequencing and its applications in medical genetics
Jiaxin Wu, Mengmeng Wu, Ting Chen, Rui Jiang
Whole genome sequencing and its applications in medical genetics
Fundamental improvement was made for genome sequencing since the next-generation sequencing (NGS) came out in the 2000s. The newer technologies make use of the power of massively-parallel short-read DNA sequencing, genome alignment and assembly methods to digitally and rapidly search the genomes on a revolutionary scale, which enable large-scale whole genome sequencing (WGS) accessible and practical for researchers. Nowadays, whole genome sequencing is more and more prevalent in detecting the genetics of diseases, studying causative relations with cancers, making genome-level comparative analysis, reconstruction of human population history, and giving clinical implications and instructions. In this review, we first give a typical pipeline of whole genome sequencing, including the lab template preparation, sequencing, genome assembling and quality control, variants calling and annotations. We compare the difference between whole genome and whole exome sequencing (WES), and explore a wide range of applications of whole genome sequencing for both mendelian diseases and complex diseases in medical genetics. We highlight the impact of whole genome sequencing in cancer studies, regulatory variant analysis, predictive medicine and precision medicine, as well as discuss the challenges of the whole genome sequencing.
whole genome sequencing / whole exome sequencing / next-generation sequencing / non-coding / regulatory variant
[1] |
Veeramah, K. R. and Hammer, M. F. ( 2014 ) The impact of whole-genome sequencing on the reconstruction of human population history. Nat. Rev. Genet. , 15 , 149 – 162
CrossRef
Google scholar
|
[2] |
Hendrix, R. W. ( 2003 ) Bacteriophage genomics. Curr. Opin. Microbiol. , 6 , 506 – 511
CrossRef
Google scholar
|
[3] |
Metzker, M. L. ( 2010 ) Sequencing technologies—the next generation. Nat. Rev. Genet. , 11 , 31 – 46
CrossRef
Google scholar
|
[4] |
Zimmermann, J. , Voss, H. , Schwager, C. , Stegemann, J. and Ansorge, W. ( 1988 ) Automated Sanger dideoxy sequencing reaction protocol. FEBS Lett. , 233 , 432 – 436
CrossRef
Google scholar
|
[5] |
Watson, J. D. ( 1990 ) The human genome project: past, present, and future. Science , 248 , 44 – 49
CrossRef
Google scholar
|
[6] |
Fleischmann, R. , Adams, M. , White, O. , Clayton, R. , Kirkness, E. , Kerlavage, A. , Bult, C. , Tomb, J. , Dougherty, B. , Merrick, J. ,
CrossRef
Google scholar
|
[7] |
Pabinger, S. , Dander, A. , Fischer, M. , Snajder, R. , Sperk, M. , Efremova, M. , Krabichler, B. , Speicher, M. R. , Zschocke, J. and Trajanoski, Z. ( 2014 ) A surveyof tools for variant analysis of next-generation genome sequencing data. Brief. Bioinform. , 15 , 256 – 278
CrossRef
Google scholar
|
[8] |
Liu, L. , Li, Y. H. , Li, S. L. , Hu, N. , He, Y. M. , Pong, R. , Lin, D. N. , Lu, L. H. and Law, M. ( 2012 ) Comparison of next-generation sequencing systems . J. BioMed. Biotech. , 251364
|
[9] |
Voelkerding, K. V. , Dames, S. A. and Durtschi, J. D. ( 2009 ) Next-generation sequencing: from basic research to diagnostics. Clin. Chem. , 55 , 641 – 658
CrossRef
Google scholar
|
[10] |
Ng, P. C. and Kirkness, E. F. ( 2010 ) Whole Genome Sequencing. In Genetic Variation , pp. 215 – 226 , Springer
|
[11] |
Hurd, P. J. and Nelson, C. J. ( 2009 ) Advantages of next-generation sequencing versus the microarray in epigenetic research. Brief. Funct. Genomics , 8, 174 – 183
|
[12] |
Lam, H. Y. , Clark, M. J. , Chen, R. , Chen, R. , Natsoulis, G. , O’Huallachain, M. , Dewey, F. E. , Habegger, L. , Ashley, E. A. , Gerstein, M. B. ,
CrossRef
Google scholar
|
[13] |
Carlton, J. M. , Angiuoli, S. V. , Suh, B. B. , Kooij, T. W. , Pertea, M. , Silva, J. C. , Ermolaeva, M. D. , Allen, J. E. , Selengut, J. D. , Koo, H. L. ,
CrossRef
Google scholar
|
[14] |
Herring, C. D. , Raghunathan, A. , Honisch, C. , Patel, T. , Applebee, M. K. , Joyce, A. R. , Albert, T. J. , Blattner, F. R. , van den Boom, D. , Cantor, C. R. ,
CrossRef
Google scholar
|
[15] |
Lupski, J. R. ( 2015 ) Structural variation mutagenesis of the human genome: impact on disease and evolution. Environ. Mol. Mutagen. , 56 , 419 – 436
CrossRef
Google scholar
|
[16] |
Saunders, C. J. , Miller, N. A. , Soden, S. E. , Dinwiddie, D. L. , Noll, A. , Alnadi, N. A. , Andraws, N. , Patterson, M. L. , Krivohlavek L. A. , Fellis, J. ,
|
[17] |
Cirulli, E. T. and Goldstein, D. B. ( 2010 ) Uncovering the roles of rare variants in common disease through whole-genome sequencing. Nat. Rev. Genet. , 11 , 415 – 425
CrossRef
Google scholar
|
[18] |
Foley, S. B. , Rios, J. J. , Mgbemena, V. E. , Robinson, L. S. , Hampel, H. L. , Toland, A. E. , Durham, L. and Ross, T. S. ( 2015 ) Use of whole genome sequencing for diagnosis and discovery in the cancer genetics clinic. EBioMedicine , 2 , 74 – 81
CrossRef
Google scholar
|
[19] |
Chen, K. and Meric-Bernstam, F. ( 2015 ) Whole genome sequencing in cancer clinics. EBioMedicine , 2 , 15 – 16
CrossRef
Google scholar
|
[20] |
Berg, J. S. , Khoury, M. J. and Evans, J. P. ( 2011 ) Deploying whole genome sequencing in clinical practice and public health: meeting the challenge one bin at a time. Genet.Med. , 13 , 499 – 504
CrossRef
Google scholar
|
[21] |
Dewey, F. E. , Grove, M. E. , Pan, C. , Goldstein, B. A. , Bernstein, J. A. , Chaib, H. , Merker, J. D. , Goldfeder, R. L. , Enns, G. M. , David, S. P. ,
CrossRef
Google scholar
|
[22] |
Belkadi, A. , Bolze, A. , Itan, Y. , Cobat, A. , Vincent, Q. B. , Antipenko, A. , Shang, L. , Boisson, B. , Casanova, J.-L. and Abel, L. ( 2015 ) Whole-genome sequencing is more powerful than whole-exome sequencing for detecting exome variants. Proc. Natl. Acad. Sci. USA , 112 , 5473 – 5478
CrossRef
Google scholar
|
[23] |
Ekblom, R. and Wolf, J. B. ( 2014 ) A field guide to whole-genome sequencing, assembly and annotation. Evol. Appl. , 7 , 1026 – 1042
CrossRef
Google scholar
|
[24] |
|
[25] |
van Dijk, E. L. , Jaszczyszyn, Y. and Thermes, C. ( 2014 ) Library preparation methods for next-generation sequencing: tone down the bias. Exp. Cell Res. , 322 , 12 – 20
CrossRef
Google scholar
|
[26] |
Miyamoto, M. , Motooka, D. , Gotoh, K. , Imai, T. , Yoshitake, K. , Goto, N. , Iida, T. , Yasunaga, T. , Horii, T. , Arakawa, K. ,
CrossRef
Google scholar
|
[27] |
|
[28] |
Bao, S. , Jiang, R. , Kwan, W. K. , Wang, B. B. , Ma, X. and Song, Y.-Q. ( 2011 ) Evaluation of next-generation sequencing software in mapping and assembly. J. Hum. Genet. , 56 , 406 – 414
CrossRef
Google scholar
|
[29] |
Swindell, S. R. and Plasterer, T. N. ( 1997 ) SEQMAN. In Sequence Data Analysis Guidebook , pp. 75 – 89 , New York : Springer
|
[30] |
Sundquist, A. , Ronaghi, M. , Tang, H. , Pevzner, P. and Batzoglou, S. ( 2007 ) Whole-genome sequencing and assembly with high-throughput, short-read technologies. PLoS One , 2 , e484
CrossRef
Google scholar
|
[31] |
Paszkiewicz, K. and Studholme, D. J. ( 2010 ) De novo assembly of short sequence reads. Brief. Bioinform. , 11, 457 – 472
|
[32] |
Hunt, M. , Kikuchi, T. , Sanders, M. , Newbold, C. , Berriman, M. and Otto, T. D. ( 2013 ) REAPR: a universal tool for genome assembly evaluation. Genome Biol. , 14 , R47
CrossRef
Google scholar
|
[33] |
Liu, X. , Han, S. , Wang, Z. , Gelernter, J. and Yang, B.-Z. ( 2013 ) Variant callers for next-generation sequencing data: a comparison study. PLoS One , 8 , e75619
CrossRef
Google scholar
|
[34] |
Altmann, A. , Weber, P. , Bader, D. , Preuß, M. , Binder, E. B. and Müller-Myhsok, B. ( 2012 ) A beginners guide to SNP calling from high-throughput DNA-sequencing data. Hum. Genet. , 131 , 1541 – 1554
CrossRef
Google scholar
|
[35] |
Pirooznia, M. , Goes, F. S. and Zandi, P. P ( 2015 ) Whole-genome CNV analysis: advances in computational approaches. Front.Genet. , 6, 138
|
[36] |
DePristo, M. A. , Banks, E. , Poplin, R. , Garimella, K. V. , Maguire, J. R. , Hartl, C. , Philippakis, A. A. , del Angel, G. , Rivas, M. A. , Hanna, M. ,
CrossRef
Google scholar
|
[37] |
Kircher, M. , Witten, D. M. , Jain, P. , O’Roak, B. J. , Cooper, G. M. and Shendure, J. ( 2014 ) A general framework for estimating the relative pathogenicity of human genetic variants. Nat. Genet. , 46 , 310 – 315
CrossRef
Google scholar
|
[38] |
Liu, X. , Jian, X. and Boerwinkle, E. ( 2011 ) dbNSFP: a lightweight database of human nonsynonymous SNPs and their functional predictions. Hum. Mutat. , 32 , 894 – 899
CrossRef
Google scholar
|
[39] |
McKenna, A. , Hanna, M. , Banks, E. , Sivachenko, A. , Cibulskis, K. , Kernytsky, A. , Garimella, K. , Altshuler, D. , Gabriel, S. , Daly, M. ,
CrossRef
Google scholar
|
[40] |
Paila, U. , Chapman, B. A. , Kirchner, R. and Quinlan, A. R. ( 2013 ) GEMINI: integrative exploration of genetic variation and genome annotations. PLoS Comput. Biol. , 9 , e1003153
CrossRef
Google scholar
|
[41] |
Wu, J. , Li, Y. and Jiang, R. ( 2014 ) Integrating multiple genomic data to predict disease-causing nonsynonymous single nucleotide variants in exome sequencing studies. PLoS Genet. , 10 , e1004237
CrossRef
Google scholar
|
[42] |
Makarov, V. , O’Grady, T. , Cai, G. , Lihm, J. , Buxbaum, J. D. and Yoon, S. ( 2012 ) AnnTools: a comprehensive and versatile annotation toolkit for genomic variants. Bioinformatics , 28 , 724 – 725
CrossRef
Google scholar
|
[43] |
Wang, K. , Li, M. and Hakonarson, H. ( 2010 ) ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data. Nucleic Acids Res. , 38 , e164
CrossRef
Google scholar
|
[44] |
Zhao, M. and Zhao, Z. ( 2013 ) CNVannotator: a comprehensive annotation server for copy number variation in the human genome . 8 , e80170
|
[45] |
McLaren, W. , Pritchard, B. , Rios, D. , Chen, Y. , Flicek, P. and Cunningham, F. ( 2010 ) Deriving the consequences of genomic variants with the Ensembl API and SNP Effect Predictor. Bioinformatics , 26 , 2069 – 2070
CrossRef
Google scholar
|
[46] |
Bick, D. and Dimmock, D. ( 2011 ) Whole exome and whole genome sequencing. Curr. Opin. Pediatr. , 23 , 594 – 600
CrossRef
Google scholar
|
[47] |
Gilchrist, C. A. , Turner, S. D. , Riley, M. F. , Petri, W. A. Jr and Hewlett, E. L. ( 2015 ) Whole-genome sequencing in outbreak analysis. Clin. Microbiol. Rev. , 28 , 541 – 563
CrossRef
Google scholar
|
[48] |
|
[49] |
Online Mendelian Inheritance in Man . Johns Hopkins University (Baltimore,MD) ,
|
[50] |
Botstein, D. and Risch, N. ( 2003 ) Discovering genotypes underlying human phenotypes: pastsuccesses for mendelian disease, future approaches for complex disease. Nat. Genet. , 33 , 228 – 237
CrossRef
Google scholar
|
[51] |
Ku, C.-S. , Naidoo, N. and Pawitan, Y. ( 2011 ) Revisiting Mendelian disorders through exome sequencing. Hum. Genet. , 129 , 351 – 370
CrossRef
Google scholar
|
[52] |
Bamshad, M. J. , Ng, S. B. , Bigham, A. W. , Tabor, H. K. , Emond, M. J. , Nickerson, D. A. and Shendure, J. ( 2011 ) Exome sequencing as a tool for Mendelian disease gene discovery. Nat. Rev. Genet. , 12 , 745 – 755
CrossRef
Google scholar
|
[53] |
Ng, S. B. , Buckingham, K. J. , Lee, C. , Bigham, A. W. , Tabor, H. K. , Dent, K. M. , Huff, C. D. , Shannon, P. T. , Jabs, E. W. , Nickerson, D. A. ,
CrossRef
Google scholar
|
[54] |
Yang, Y. , Muzny, D. M. , Reid, J. G. , Bainbridge, M. N. , Willis, A. , Ward, P. A. , Braxton, A. , Beuten, J. , Xia, F. , Niu, Z. ,
CrossRef
Google scholar
|
[55] |
Ng, S. B. , Bigham, A. W. , Buckingham, K. J. , Hannibal, M. C. , McMillin, M. J. , Gildersleeve, H.I. , Beck, A. E. , Tabor, H. K. , Cooper, G. M. , Mefford, H. C. ,
CrossRef
Google scholar
|
[56] |
Roach, J. C. , Glusman, G. , Smit, A. F. A. , Huff, C. D. , Hubley, R. , Shannon, P. T. , Rowen, L. , Pant, K. P. , Goodman, N. , Bamshad, M. ,
CrossRef
Google scholar
|
[57] |
Lupski, J. R. , Reid, J. G. , Gonzaga-Jauregui, C. , Rio Deiros, D. , Chen, D. C. Y. , Nazareth, L. , Bainbridge, M. , Dinh, H. , Jing, C. , Wheeler, D. A. ,
CrossRef
Google scholar
|
[58] |
Cooper, G. M. ,
CrossRef
Google scholar
|
[59] |
Taylor, J. C. , Martin, H. C. , Lise, S. , Broxholme, J. , Cazier, J.-B. , Rimmer, A. , Kanapin, A. , Lunter, G. , Fiddy, S. , Allan, C. ,
CrossRef
Google scholar
|
[60] |
Kumar, P. , Henikoff, S. and Ng, P. C. ( 2009 ) Predicting the effects of coding non-synonymous variants on protein function using the SIFT algorithm. Nat. Protoc. , 4 , 1073 – 1081
CrossRef
Google scholar
|
[61] |
Adzhubei, I. A. , Schmidt, S. , Peshkin, L. , Ramensky, V. E. , Gerasimova, A. , Bork, P. , Kondrashov, A. S. and Sunyaev, S. R. ( 2010 ) A method and server for predicting damaging missense mutations. Nat. Methods , 7 , 248 – 249
CrossRef
Google scholar
|
[62] |
Kircher, M. , Witten, D. M. , Jain, P. , O’Roak, B. J. , Cooper, G. M. and Shendure, J. ( 2014 ) A general framework for estimating the relative pathogenicity of human genetic variants. Nat. Genet. , 46 , 310 – 315
CrossRef
Google scholar
|
[63] |
Quang, D. , Chen, Y. and Xie, X. ( 2015 ) DANN: a deep learning approach for annotating the pathogenicity of genetic variants. Bioinformatics , 31 , 761 – 763
CrossRef
Google scholar
|
[64] |
Shihab, H. A. , Rogers, M. F. , Gough, J. , Mort, M. , Cooper, D. N. , Day, I. N. M ., Gaunt, T. R. and Campbell C. ( 2015 ) An integrative approach to predicting the functional effects of non-coding and coding sequence variation. Bioinformatics , 10.1093/bioinformatics/btv009
CrossRef
Google scholar
|
[65] |
Fu, Y. , Liu, Z. , Lou, S. , Bedford, J. , Mu, X. J. , Yip, K. Y. , Khurana, E. and Gerstein, M. ( 2014 ) FunSeq2: a framework for prioritizing noncoding regulatory variants in cancer. Genome Biol. , 15 , 480
CrossRef
Google scholar
|
[66] |
Khurana, E. , Fu, Y. , Colonna, V. , Mu, X. J. , Kang, H. M. , Lappalainen, T. , Sboner, A. , Lochovsky, L. , Chen, J. , Harmanci, A. ,
CrossRef
Google scholar
|
[67] |
Lehmann, K.-V. and Chen, T. ( 2013 ) Exploring functional variant discovery in non-coding regions with SInBaD. Nucleic Acids Res. , 41 , e7
CrossRef
Google scholar
|
[68] |
Lee, D. , Gorkin, D. U. , Baker, M. , Strober, B. J. , Asoni, A. L. , McCallion, A. S. and Beer, M. A. ( 2015 ) A method to predict the impact of regulatory variants from DNA sequence. Nat. Genet. , 47 , 955 – 961
CrossRef
Google scholar
|
[69] |
Ritchie, G. R. , Dunham, I. , Zeggini, E. and Flicek, P. ( 2014 ) Functional annotation of noncoding sequence variants. Nat. Methods , 11 , 294 – 296
CrossRef
Google scholar
|
[70] |
Zhang, F. and Lupski, J. R. ( 2015 ) Noncoding genetic variants in human disease. Hum. Mol. Genet. ,
CrossRef
Google scholar
|
[71] |
Lupski, J. R. ( 1998 ) Genomic disorders: structural features of the genome can lead to DNA rearrangements and human disease traits. Trends Genet. , 14 , 417 – 422
CrossRef
Google scholar
|
[72] |
Lee, C. and Morton, C. C. ( 2008 ) Structural genomic variation and personalized medicine. N. Engl. J. Med. , 358 , 740 – 741
CrossRef
Google scholar
|
[73] |
Lupski, J. R. ( 2009 ) Genomic disorders ten years on. Genome Med. , 1 , 42
CrossRef
Google scholar
|
[74] |
Sathirapongsasuti, J. F. , Lee, H. , Horst, B. A. J. , Brunner, G. , Cochran, A. J. , Binder, S. , Quackenbush, J. and Nelson, S. F. ( 2011 ) Exome sequencing-based copy-number variation and loss of heterozygosity detection: ExomeCNV. Bioinformatics , 27 , 2648 – 2654
CrossRef
Google scholar
|
[75] |
Fromer, M. , Moran, J. L. , Chambert, K. , Banks, E. , Bergen, S. E. , Ruderfer, D. M. , Handsaker, R. E. , McCarroll, S. A. , O’Donovan, M. C. , Owen, M. J. ,
CrossRef
Google scholar
|
[76] |
Zong, C. , Lu, S. , Chapman, A. R. and Xie, X. S. ( 2012 ) Genome-wide detectionof single-nucleotide and copy-number variations of a single humancell. Science , 338 , 1622 – 1626
CrossRef
Google scholar
|
[77] |
Cardon, L. R. and Bell, J. I. ( 2001 ) Association study designs for complex diseases. Nat. Rev. Genet. , 2 , 91 – 99
CrossRef
Google scholar
|
[78] |
Manolio, T. A. , Collins, F. S. , Cox, N. J. , Goldstein, D. B. , Hindorff, L. A. , Hunter, D. J. , McCarthy, M. I. , Ramos, E. M. , Cardon, L. R. , Chakravarti, A. ,
CrossRef
Google scholar
|
[79] |
Schork, N. J. , Murray, S. S. , Frazer, K. A. and Topol, E. J. ( 2009 ) Common vs. rare allele hypotheses for complex diseases. Curr. Opin. Genet. Dev. , 19 , 212 – 219
CrossRef
Google scholar
|
[80] |
Spain, S. L. and Barrett, J. C. ( 2015 ) Strategies for fine-mapping complex traits. Hum. Mol. Genet. ,
CrossRef
Google scholar
|
[81] |
CONVERGE consortium ( 2015 ) Sparse whole-genome sequencing identifiestwo loci for major depressive disorder . Nature , 523 , 588 –591.
|
[82] |
Lippert, C. , Listgarten, J. , Liu, Y. , Kadie, C. M. , Davidson, R. I. and Heckerman, D. ( 2011 ) FaST linear mixed models for genome-wide association studies. Nat. Methods , 8 , 833 – 835
CrossRef
Google scholar
|
[83] |
Widmer, C. , Lippert, C. , Weissbrod, O. , Fusi, N. , Kadie, C. , Davidson, R. , Listgarten, J . and Heckerman , D. ( 2014 ) Further improvements to linear mixed models for genome-wide association studies. Sci. Rep. , 4 , 6874
|
[84] |
Wu, M. C. , Lee, S. , Cai, T. , Li, Y. , Boehnke, M. and Lin, X. ( 2011 ) Rare-variant association testing for sequencing data with the sequence kernel association test. Am. J. Hum. Genet. , 89 , 82 – 93
CrossRef
Google scholar
|
[85] |
Taylor, P. N. , Porcu, E. , Chew, S. , Campbell, P. J. , Traglia, M. , Brown, S. J. , Mullin, B. H. , Shihab, H. A. , Min, J. , Walter, K. ,
|
[86] |
Morrison, A. C. , Voorman, A. , Johnson, A. D. , Liu, X. M. , Yu, J. , Li, A. , Muzny, D. , Yu, F. L. , Rice, K. , Zhu, C. S. ,
CrossRef
Google scholar
|
[87] |
Gibson, G. ( 2012 ) Rare and common variants: twenty arguments. Nat. Rev. Genet. , 13 , 135 – 145
CrossRef
Google scholar
|
[88] |
Yang, J. , Benyamin, B. , McEvoy, B. P. , Gordon, S. , Henders, A. K. , Nyholt, D. R. , Madden, P. A. , Heath, A. C. , Martin, N. G. , Montgomery, G. W. ,
CrossRef
Google scholar
|
[89] |
Li, Y. , Sidore, C. , Kang, H. M. , Boehnke, M. and Abecasis, G. R. ( 2011 ) Low-coverage sequencing: implications for design of complex trait association studies. Genome Res. , 21 , 940 – 951
CrossRef
Google scholar
|
[90] |
Edwards, S. L. , Beesley, J. , French, J. D. and Dunning, A. M. ( 2013 ) Beyond GWASs: illuminating the dark road from association to function. Am. J. Hum. Genet. , 93 , 779 – 797
CrossRef
Google scholar
|
[91] |
Farh, K. K.-H. , Marson, A. , Zhu, J. , Kleinewietfeld, M. , Housley, W. J. , Beik, S. , Shoresh, N. , Whitton, H. , Ryan, R. J. H. , Shishkin, A. A. ,
CrossRef
Google scholar
|
[92] |
Maller, J. B. , McVean, G. , Byrnes, J. , Vukcevic, D. , Palin, K. , Su, Z. , Howson, J. M. M. , Auton, A. , Myers, S. , Morris, A. ,
CrossRef
Google scholar
|
[93] |
Barbieri, C. E. , Baca, S. C. , Lawrence, M. S. , Demichelis, F. , Blattner, M. , Theurillat, J.-P. , White, T. A. , Stojanov, P. , Van Allen, E. , Stransky, N. ,
CrossRef
Google scholar
|
[94] |
Wang, K. , Kan, J. , Yuen, S. T. , Shi, S. T. , Chu, K. M. , Law, S. , Chan, T. L. , Kan, Z. , Chan, A. S. Y. , Tsui, W. Y. ,
CrossRef
Google scholar
|
[95] |
Nakagawa, H. , Wardell, C. P. , Furuta, M. , Taniguchi, H. and Fujimoto, A. ( 2015 ) Cancer whole-genome sequencing: present and future. Oncogene , 34 , 5943 – 5950
CrossRef
Google scholar
|
[96] |
Huang, F. W. , Hodis, E. , Xu, M. J. , Kryukov, G. V. , Chin, L. and Garraway, L. A. ( 2013 ) Highly recurrent TERT promoter mutations in human melanoma. Science , 339 , 957 – 959
CrossRef
Google scholar
|
[97] |
Vinagre, J. , Almeida, A. , Pópulo, H. , Batista, R. , Lyra, J. , Pinto, V. , Coelho, R. , Celestino, R. , Prazeres, H. , Lima, L. ,
|
[98] |
Mansour, M. R. , Abraham, B. J. , Anders, L. , Berezovskaya, A. , Gutierrez, A. , Durbin, A. D. , Etchin, J. , Lawton, L. , Sallan, S. E. , Silverman, L. B. ,
CrossRef
Google scholar
|
[99] |
Weinhold, N. , Jacobsen, A. , Schultz, N. , Sander, C. and Lee, W. ( 2014 ) Genome-wide analysis of noncoding regulatory mutationsin cancer. Nat. Genet. , 46 , 1160 – 1165
CrossRef
Google scholar
|
[100] |
Fredriksson, N. J. , Ny, L. , Nilsson, J. A. and Larsson, E. ( 2014 ) Systematic analysisof noncoding somatic mutations and gene expression alterations across 14 tumor types. Nat. Genet. , 46 , 1258 – 1263
CrossRef
Google scholar
|
[101] |
Melton, C. , Reuter, J. A. , Spacek, D. V. and Snyder, M. ( 2015 ) Recurrent somatic mutations in regulatory regions of human cancer genomes. Nat. Genet. , 47 , 710 – 716
CrossRef
Google scholar
|
[102] |
Li, B. and Leal, S. M. ( 2008 ) Methods for detecting associations with rare variants for common diseases: application to analysis of sequence data. Am. J. Hum. Genet. , 83 , 311 – 321
CrossRef
Google scholar
|
[103] |
Lin, D.-Y. and Tang, Z.-Z. ( 2011 ) A general framework for detecting disease associations with rare variants in sequencing studies. Am. J. Hum. Genet. , 89 , 354 – 367
CrossRef
Google scholar
|
[104] |
Gonzalez-Perez, A. , Mustonen, V. , Reva, B. , Ritchie, G. R. S. , Creixell, P. , Karchin, R. , Vazquez, M. , Fink, J. L. , Kassahn, K. S. , Pearson, J. V. ,
CrossRef
Google scholar
|
[105] |
Albert, F. W. and Kruglyak, L. ( 2015 ) The role of regulatory variation in complex traits and disease. Nat. Rev. Genet. , 16 , 197 – 212
CrossRef
Google scholar
|
[106] |
Li, M. J. , Yan, B. , Sham, P. C. , and Wang, J.W. ( 2014 ) Exploring the function of genetic variants in the non-codinggenomic regions: approaches for identifying human regulatory variants affecting gene expression. Brief. Bioinform. , 16 , 393 – 412
|
[107] |
Ward, L. D. and Kellis, M. ( 2012 ) Interpreting noncoding genetic variation in complex traitsand human disease. Nat. Biotechnol. , 30 , 1095 – 1106
CrossRef
Google scholar
|
[108] |
Rockman, M. V. and Kruglyak, L. ( 2006 ) Genetics of global gene expression. Nat. Rev. Genet. , 7 , 862 – 872
CrossRef
Google scholar
|
[109] |
Degner, J. F. , Pai, A. A. , Pique-Regi, R. , Veyrieras, J.-B. , Gaffney, D. J. , Pickrell, J. K. , De Leon, S. , Michelini, K. , Lewellen, N. , Crawford, G. E. ,
CrossRef
Google scholar
|
[110] |
Monlong, J. , Calvo, M. , Ferreira, P. G. and Guigó, R. ( 2014 ) Identification of genetic variants associated with alternative splicing using sQTLseekeR . Nat. Commun. , 5 , 4698
|
[111] |
Koren, A. , Handsaker, R. E. , Kamitaki, N. , Karlić, R. , Ghosh, S. , Polak, P. , Eggan, K. and McCarroll, S. A. ( 2014 ) Genetic variation in human DNA replication timing. Cell , 159 , 1015 – 1026
CrossRef
Google scholar
|
[112] |
del Rosario, R. C.-H. , Poschmann, J. , Rouam, S. L. , Png, E. , Khor, C. C. , Hibberd, M. L. and Prabhakar, S. ( 2015 ) Sensitive detection of chromatin-altering polymorphisms reveals autoimmune diseasemechanisms. Nat. Methods , 12 , 458 – 464
CrossRef
Google scholar
|
[113] |
Gibbs, J. R. , van der Brug, M. P. , Hernandez, D. G. , Traynor, B. J. , Nalls, M. A. , Lai, S.-L. , Arepalli, S. , Dillman, A. , Rafferty, I. P. , Troncoso, J. ,
CrossRef
Google scholar
|
[114] |
Lappalainen, T. , Sammeth, M. , Friedländer, M. R. , ‘t Hoen, P. A. C. , Monlong, J. , Rivas, M. A. , Gonzàlez-Porta, M. , Kurbatova, N. , Griebel, T. , Ferreira, P. G. ,
CrossRef
Google scholar
|
[115] |
Maurano, M. T. , Humbert, R. , Rynes, E. , Thurman, R. E. , Haugen, E. , Wang, H. , Reynolds, A. P. , Sandstrom, R. , Qu, H. , Brody, J. ,
CrossRef
Google scholar
|
[116] |
Maurano, M. T. , Haugen, E. , Sandstrom, R. , Vierstra, J. , Shafer, A. , Kaul, R. and Stamatoyannopoulos, J. A. ( 2015 ) Large-scale identification of sequence variants influencing human transcription factor occupancy in vivo . Nat. Genet. , 47 , 1393 – 1401
CrossRef
Google scholar
|
[117] |
Kasowski, M. , Grubert, F. , Heffelfinger, C. , Hariharan, M. , Asabere, A. , Waszak, S. M. , Habegger, Lukas. , Rozowsky, J. , Shi, M. , Urban, A. E. ,
|
[118] |
Karczewski, K. J. , Dudley, J. T. , Kukurba, K. R. , Chen, R. , Butte, A. J. , Montgomery, S. B. and Snyder, M. ( 2013 ) Systematic functional regulatory assessment of disease-associated variants. Proc. Natl. Acad. Sci. USA , 110 , 9607 – 9612
CrossRef
Google scholar
|
[119] |
Chiang, C. , Layer, R. M. , Faust, G. G. , Lindberg, M. R. , Rose, D. B. , Garrison, E. P. , Marth, G. T. , Quinlan, A. R. and Hall, I. M. ( 2014 ) SpeedSeq: Ultra-fast personal genome analysis and interpretation. Nat. Meth., 12 , 966 – 968
|
[120] |
Park, P. J. ( 2009 ) ChIP–seq: advantages and challenges of a maturing technology. Nat. Rev. Genet. , 10 , 669 – 680
CrossRef
Google scholar
|
[121] |
Song, L. and Crawford, G. E. ( 2010 ) DNase-seq: a high-resolution technique for mapping activegene regulatory elements across the genome from mammalian cells. Cold Spring Harb. Protoc. pdb . prot5384
|
[122] |
Buenrostro, J. D. , Giresi, P. G. , Zaba, L. C. , Chang, H. Y. and Greenleaf, W. J. ( 2013 ) Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position. Nat. Methods , 10 , 1213 – 1218
CrossRef
Google scholar
|
[123] |
dbWGFP :
|
[124] |
Biesecker, L. G. ( 2013 ) Hypothesis-generating research and predictive medicine. Genome Res. , 23 , 1051 – 1053
CrossRef
Google scholar
|
[125] |
Simon, R. ( 2011 ) Genomic biomarkers in predictive medicine. An interim analysis. EMBO Mol. Med. , 3 , 429 – 435
CrossRef
Google scholar
|
[126] |
Matsui, S. , Simon, R. , Qu, P. , Shaughnessy, J. D. , Barlogie, B. and Crowley, J. ( 2012 ) Developing and validating continuous genomic signatures in randomized clinical trials for predictive medicine. Clin. Cancer Res. , 18 , 6065 – 6073
CrossRef
Google scholar
|
[127] |
Collins, F. S. and Varmus, H. ( 2015 ) A new initiative on precision medicine. N. Engl. J. Med. , 372 , 793 – 795
CrossRef
Google scholar
|
[128] |
Rubin, M. A. ( 2015 ) Health: Make precision medicine work for cancer care. Nature , 520 , 290 – 291
CrossRef
Google scholar
|
[129] |
Bellmunt, J. , Orsola, A. and Sonpavde, G. ( 2015 ) Precision and predictive medicine in urothelial cancer: Are we making progress? Eur. Urol. , 68 , 547 – 549
CrossRef
Google scholar
|
[130] |
Geschwind, D. H. and State, M. W. ( 2015 ) Gene hunting in autism spectrum disorder: on the path to precision medicine. Lancet Neurol. , 14 , 1109 – 1120
CrossRef
Google scholar
|
[131] |
Mak, H. C. ( 2012 ) Genome interpretation and assembly—recent progress and next steps. Nat. Biotechnol. , 30 , 1081 – 1083
CrossRef
Google scholar
|
[132] |
Shendure, J. and Aiden, E. L. ( 2012 ) The expanding scope of DNA sequencing. Nat. Biotechnol. , 30 , 1084 – 1094
CrossRef
Google scholar
|
[133] |
Fujimoto, A. , Nakagawa, H. , Hosono, N. , Nakano, K. , Abe, T. , Boroevich, K. A. , Nagasaki, M. , Yamaguchi, R. , Shibuya, T. , Kubo, M. ,
CrossRef
Google scholar
|
[134] |
Gonzaga-Jauregui, C. , Lupski, J. R. and Gibbs, R. A. ( 2012 ) Human genome sequencing in health and disease. Annu. Rev. Med. , 63 , 35 – 61
CrossRef
Google scholar
|
/
〈 | 〉 |