Literature DB >> 23103023

How next-generation sequencing is transforming complex disease genetics.

Helena Kilpinen1, Jeffrey C Barrett.   

Abstract

Progress in understanding the genetics of human disease is closely tied to technological developments in DNA sequencing. Recently, next-generation technology has transformed the scale of sequencing; compared to the methods used in the Human Genome Project, modern sequencers are 50000-fold faster. Complex disease genetics presents an immediate opportunity to use this technology to move from approaches using only partial information (linkage and genome-wide association studies, GWAS) to complete analysis of the relationship between genomic variation and phenotype. We first describe sequence-based improvements to existing study designs, followed by prioritization of both samples and genomic regions to be sequenced, and then address the ultimate goal of analyzing thousands of whole-genome sequences. Finally, we discuss how the same technology will also fundamentally change the way we understand the biological mechanisms underlying disease associations discovered through sequencing.
Copyright © 2012 Elsevier Ltd. All rights reserved.

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Year:  2012        PMID: 23103023     DOI: 10.1016/j.tig.2012.10.001

Source DB:  PubMed          Journal:  Trends Genet        ISSN: 0168-9525            Impact factor:   11.639


  25 in total

1.  A systematic review of cancer GWAS and candidate gene meta-analyses reveals limited overlap but similar effect sizes.

Authors:  Christine Q Chang; Ajay Yesupriya; Jessica L Rowell; Camilla B Pimentel; Melinda Clyne; Marta Gwinn; Muin J Khoury; Anja Wulf; Sheri D Schully
Journal:  Eur J Hum Genet       Date:  2013-07-24       Impact factor: 4.246

Review 2.  Case-only exome sequencing and complex disease susceptibility gene discovery: study design considerations.

Authors:  Lang Wu; Daniel J Schaid; Hugues Sicotte; Eric D Wieben; Hu Li; Gloria M Petersen
Journal:  J Med Genet       Date:  2014-11-04       Impact factor: 6.318

Review 3.  OPENMENDEL: a cooperative programming project for statistical genetics.

Authors:  Hua Zhou; Janet S Sinsheimer; Douglas M Bates; Benjamin B Chu; Christopher A German; Sarah S Ji; Kevin L Keys; Juhyun Kim; Seyoon Ko; Gordon D Mosher; Jeanette C Papp; Eric M Sobel; Jing Zhai; Jin J Zhou; Kenneth Lange
Journal:  Hum Genet       Date:  2019-03-26       Impact factor: 4.132

Review 4.  Evolving approaches to the ethical management of genomic data.

Authors:  Jean E McEwen; Joy T Boyer; Kathie Y Sun
Journal:  Trends Genet       Date:  2013-02-28       Impact factor: 11.639

Review 5.  A review of genome-wide association studies for multiple sclerosis: classical and hypothesis-driven approaches.

Authors:  V V Bashinskaya; O G Kulakova; A N Boyko; A V Favorov; O O Favorova
Journal:  Hum Genet       Date:  2015-09-25       Impact factor: 4.132

6.  Exome analysis of patients with concurrent pediatric inflammatory bowel disease and autoimmune disease.

Authors:  Gaia Andreoletti; James J Ashton; Tracy Coelho; Claire Willis; Rachel Haggarty; Jane Gibson; John Holloway; Akshay Batra; Nadeem A Afzal; Robert Mark Beattie; Sarah Ennis
Journal:  Inflamm Bowel Dis       Date:  2015-06       Impact factor: 5.325

7.  LipidSeq: a next-generation clinical resequencing panel for monogenic dyslipidemias.

Authors:  Christopher T Johansen; Joseph B Dubé; Melissa N Loyzer; Austin MacDonald; David E Carter; Adam D McIntyre; Henian Cao; Jian Wang; John F Robinson; Robert A Hegele
Journal:  J Lipid Res       Date:  2014-02-06       Impact factor: 5.922

8.  SeqSIMLA: a sequence and phenotype simulation tool for complex disease studies.

Authors:  Ren-Hua Chung; Chung-Chin Shih
Journal:  BMC Bioinformatics       Date:  2013-06-20       Impact factor: 3.169

9.  Genomic and epigenomic insights into nutrition and brain disorders.

Authors:  Margaret Joy Dauncey
Journal:  Nutrients       Date:  2013-03-15       Impact factor: 5.717

10.  TASSEL-GBS: a high capacity genotyping by sequencing analysis pipeline.

Authors:  Jeffrey C Glaubitz; Terry M Casstevens; Fei Lu; James Harriman; Robert J Elshire; Qi Sun; Edward S Buckler
Journal:  PLoS One       Date:  2014-02-28       Impact factor: 3.240

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