Skip to main content

Genome-Wide Association Studies: A Comprehensive Tool to Explore Comparative Genomic Variations and Interactions

  • Chapter
  • First Online:
Translational Bioinformatics and Its Application

Part of the book series: Translational Medicine Research ((TRAMERE))

  • 2334 Accesses

Abstract

In the recent past, significant advances in sequencing technologies have led to genome-wide association studies (GWASs) that had revealed substantial insight into the genetic architecture of human phenotypes. The technique involves rapid scanning of markers across the whole genome of many people in order to find genetic variants that can be attributed to a particular disease condition. The enormous contributions of genetic information to common disease conditions and newer algorithms have set a stage for rapid and efficient screening of the data. Such information in the future will enable a tailor-made disease prevention program through selection of treatment options. An archive of data from genome-wide association studies on a variety of diseases and conditions already can be accessed through an NCBI Web site, called the Database of Genotype and Phenotype (dbGaP) located at http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=gap.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 149.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 199.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 199.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  • Abecasis GR, Auton A, Brooks LD, DePristo MA, Durbin RM, Handsaker RE, Kang HM, Marth GT, McVean GA. An integrated map of genetic variation from 1,092 human genomes. Nature. 2012;491:56–65.

    Article  PubMed  Google Scholar 

  • Amos CI. Successful design and conduct of genome-wide association studies. Hum Mol Genet. 2007;16 (2):R220–5. Epub;%2007 Jun 27.: R220–5.

    Google Scholar 

  • Balding DJ. A tutorial on statistical methods for population association studies. Nat. Rev. Genet. 2006;7:781–91.

    Article  CAS  PubMed  Google Scholar 

  • Benson AK, Kelly SA, Legge R, Ma F, Low SJ, Kim J, Zhang M, Oh PL, Nehrenberg D, Hua K, Kachman SD, Moriyama EN, Walter J, Peterson DA, Pomp D. Individuality in gut microbiota composition is a complex polygenic trait shaped by multiple environmental and host genetic factors. Proc Natl Acad Sci U S A. 2010;107:18933–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Boone C, Bussey H, Andrews BJ. Exploring genetic interactions and networks with yeast. Nat. Rev. Genet. 2007;8:437–49.

    Article  CAS  PubMed  Google Scholar 

  • Chen WM, Abecasis GR. Family-based association tests for genome wide association scans. Am J Hum Genet. 2007;81:913–26.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Chen PE, Shapiro BJ. The advent of genome-wide association studies for bacteria. Curr Opin Microbiol. 2015;25:17–24. doi:10.1016/j.mib.2015.03.002. . Epub;%2015 Mar 31.

    Article  CAS  PubMed  Google Scholar 

  • Chewapreecha C, Marttinen P, Croucher NJ, Salter SJ, Harris SR, Mather AE, Hanage WP, Goldblatt D, Nosten FH, Turner C, Turner P, Bentley SD, Parkhill J. Comprehensive identification of single nucleotide polymorphisms associated with beta-lactam resistance within pneumococcal mosaic genes. PLoS Genet. 2014;10:e1004547.

    Article  PubMed  PubMed Central  Google Scholar 

  • Cooper JD, Smyth DJ, Smiles AM, Plagnol V, Walker NM, Allen JE, Downes K, Barrett JC, Healy BC, Mychaleckyj JC, Warram JH, Todd JA. Meta-analysis of genome-wide association study data identifies additional type 1 diabetes risk loci. Nat Genet. 2008;40:1399–401.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Denny JC, Ritchie MD, Basford MA, Pulley JM, Bastarache L, Brown-Gentry K, Wang D, Masys DR, Roden DM, Crawford DC. PheWAS: demonstrating the feasibility of a phenome-wide scan to discover gene-disease associations. Bioinformatics. 2010;26:1205–10.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Denny JC, Crawford DC, Ritchie MD, Bielinski SJ, Basford MA, Bradford Y, Chai HS, Bastarache L, Zuvich R, Peissig P, Carrell D, Ramirez AH, Pathak J, Wilke RA, Rasmussen L, Wang X, Pacheco JA, Kho AN, Hayes MG, Weston N, Matsumoto M, Kopp PA, Newton KM, Jarvik GP, Li R, Manolio TA, Kullo IJ, Chute CG, Chisholm RL, Larson EB, McCarty CA, Masys DR, Roden DM, de AM. Variants near FOXE1 are associated with hypothyroidism and other thyroid conditions: using electronic medical records for genome- and phenome-wide studies. Am J Hum Genet. 2011;89:529–42.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Distefano JK, Taverna DM. Technological issues and experimental design of gene association studies. Methods Mol Biol. 2011;700:3–16. doi:10.1007/978-1-61737-954-3_1.

    Article  CAS  PubMed  Google Scholar 

  • Farhat MR, Shapiro BJ, Kieser KJ, Sultana R, Jacobson KR, Victor TC, Warren RM, Streicher EM, Calver A, Sloutsky A, Kaur D, Posey JE, Plikaytis B, Oggioni MR, Gardy JL, Johnston JC, Rodrigues M, Tang PK, Kato-Maeda M, Borowsky ML, Muddukrishna B, Kreiswirth BN, Kurepina N, Galagan J, Gagneux S, Birren B, Rubin EJ, Lander ES, Sabeti PC, Murray M. Genomic analysis identifies targets of convergent positive selection in drug-resistant Mycobacterium tuberculosis. Nat Genet. 2013;45:1183–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Frazer KA, Murray SS, Schork NJ, Topol EJ. Human genetic variation and its contribution to complex traits. Nat. Rev. Genet. 2009;10:241–51.

    Article  CAS  PubMed  Google Scholar 

  • Goodrich JK, Waters JL, Poole AC, Sutter JL, Koren O, Blekhman R, Beaumont M, Van TW, Knight R, Bell JT, Spector TD, Clark AG, Ley RE. Human genetics shape the gut microbiome. Cell. 2014;159:789–99.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Hebbring SJ. The challenges, advantages and future of phenome-wide association studies. Immunology. 2014;141:157–65.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Hebbring SJ, Schrodi SJ, Ye Z, Zhou Z, Page D, Brilliant MH. A PheWAS approach in studying HLA-DRB1*1501. Genes Immun. 2013;14:187–91.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Hindorff LA, MacArthur J, Morales J, Junkins HA, Hall PN, Klemm AK, Manolio TA. A catalog of published genome-wide association studies. 2013.

    Google Scholar 

  • Human Microbiome Project Consortium. A framework for human microbiome research. Nature. 2012;486:215–21.

    Article  Google Scholar 

  • Khachatryan ZA, Ktsoyan ZA, Manukyan GP, Kelly D, Ghazaryan KA, Aminov RI. Predominant role of host genetics in controlling the composition of gut microbiota. PLoS One. 2008;3:e3064.

    Article  PubMed  PubMed Central  Google Scholar 

  • Klein RJ. Power analysis for genome-wide association studies. BMC Genet. 2007;8:58.

    Article  PubMed  PubMed Central  Google Scholar 

  • Knights D, Silverberg MS, Weersma RK, Gevers D, Dijkstra G, Huang H, Tyler AD, van SS, Imhann F, Stempak JM, Huang H, Vangay P, Al-Ghalith GA, Russell C, Sauk J, Knight J, Daly MJ, Huttenhower C, Xavier RJ. Complex host genetics influence the microbiome in inflammatory bowel disease. Genome Med. 2014;6:107–0107.

    Article  PubMed  PubMed Central  Google Scholar 

  • Lapierre P, Gogarten JP. Estimating the size of the bacterial pan-genome. Trends Genet. 2009;25:107–10.

    Article  CAS  PubMed  Google Scholar 

  • Li E, Hamm CM, Gulati AS, Sartor RB, Chen H, Wu X, Zhang T, Rohlf FJ, Zhu W, Gu C, Robertson CE, Pace NR, Boedeker EC, Harpaz N, Yuan J, Weinstock GM, Sodergren E, Frank DN. Inflammatory bowel diseases phenotype, C. difficile and NOD2 genotype are associated with shifts in human ileum associated microbial composition. PLoS One. 2012;7:e26284.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Ma J, Coarfa C, Qin X, Bonnen PE, Milosavljevic A, Versalovic J, Aagaard K. mtDNA haplogroup and single nucleotide polymorphisms structure human microbiome communities. BMC Genomics. 2014;15:257–15. doi:10.1186/1471-2164-15-257.

    Article  PubMed  PubMed Central  Google Scholar 

  • Martin ER, Monks SA, Warren LL, Kaplan NL. A test for linkage and association in general pedigrees: the pedigree disequilibrium test. Am J Hum Genet. 2000;67:146–54.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • McCarthy MI, Abecasis GR, Cardon LR, Goldstein DB, Little J, Ioannidis JP, Hirschhorn JN. Genome-wide association studies for complex traits: consensus, uncertainty and challenges. Nat Rev Genet. 2008;9:356–69.

    Article  CAS  PubMed  Google Scholar 

  • McCarty CA, Chisholm RL, Chute CG, Kullo IJ, Jarvik GP, Larson EB, Li R, Masys DR, Ritchie MD, Roden DM, Struewing JP, Wolf WA. The eMERGE Network: a consortium of biorepositories linked to electronic medical records data for conducting genomic studies. BMC Med Genet. 2011;4:13. doi:10.1186/1755-8794-4-13.

    Google Scholar 

  • Misteli T. The concept of self-organization in cellular architecture. J Cell Biol. 2001;155:181–5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Mohlke KL, Boehnke M, Abecasis GR. Metabolic and cardiovascular traits: an abundance of recently identified common genetic variants. Hum Mol Genet. 2008;17:R102–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Mukherjee S, Simon J, Bayuga S, Ludwig E, Yoo S, Orlow I, Viale A, Offit K, Kurtz RC, Olson SH, Klein RJ. Including additional controls from public databases improves the power of a genome-wide association study. Hum Hered. 2011;72:21–34.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Nguyen TT, Pahl R, Schafer H. Optimal robust two-stage designs for genome-wide association studies. Ann Hum Genet. 2009;73:638–51.

    Article  PubMed  Google Scholar 

  • Sale MM, Mychaleckyj JC, Chen WM. Planning and executing a genome wide association study (GWAS). Methods Mol Biol. 2009;590:403–18. doi:10.1007/978-1-60327-378-7_25.

    Article  CAS  PubMed  Google Scholar 

  • Schierding W, Cutfield WS, O’Sullivan JM. The missing story behind Genome Wide Association Studies: single nucleotide polymorphisms in gene deserts have a story to tell. Front Genet. 2014;5:39. doi:10.3389/fgene.2014.00039. eCollection;%2014.

    Article  PubMed  PubMed Central  Google Scholar 

  • Shameer K, Denny JC, Ding K, Jouni H, Crosslin DR, de AM, Chute CG, Peissig P, Pacheco JA, Li R, Bastarache L, Kho AN, Ritchie MD, Masys DR, Chisholm RL, Larson EB, McCarty CA, Roden DM, Jarvik GP, Kullo IJ. A genome- and phenome-wide association study to identify genetic variants influencing platelet count and volume and their pleiotropic effects. Hum Genet. 2014;133:95–109.

    Article  PubMed  Google Scholar 

  • Sheppard SK, Didelot X, Meric G, Torralbo A, Jolley KA, Kelly DJ, Bentley SD, Maiden MC, Parkhill J, Falush D. Genome-wide association study identifies vitamin B5 biosynthesis as a host specificity factor in Campylobacter. Proc Natl Acad Sci U S A. 2013;110:11923–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Sherry ST, Ward MH, Kholodov M, Baker J, Phan L, Smigielski EM, Sirotkin K. dbSNP: the NCBI database of genetic variation. Nucleic Acids Res. 2001;29:308–11.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Skol AD, Scott LJ, Abecasis GR, Boehnke M. Joint analysis is more efficient than replication-based analysis for two-stage genome-wide association studies. Nat Genet. 2006;38:209–13.

    Article  CAS  PubMed  Google Scholar 

  • Spor A, Koren O, Ley R. Unravelling the effects of the environment and host genotype on the gut microbiome. Nat Rev Microbiol. 2011;9:279–90.

    Article  CAS  PubMed  Google Scholar 

  • Steemers FJ, Chang W, Lee G, Barker DL, Shen R, Gunderson KL. Whole-genome genotyping with the single-base extension assay. Nat Methods. 2006;3:31–3.

    Article  CAS  PubMed  Google Scholar 

  • Stenson PD, Mort M, Ball EV, Shaw K, Phillips A, Cooper DN. The Human Gene Mutation Database: building a comprehensive mutation repository for clinical and molecular genetics, diagnostic testing and personalized genomic medicine. Hum Genet. 2014;133:1–9.

    Article  CAS  PubMed  Google Scholar 

  • Tryka KA, Hao L, Sturcke A, Jin Y, Wang ZY, Ziyabari L, Lee M, Popova N, Sharopova N, Kimura M, Feolo M. NCBI’s database of genotypes and phenotypes: dbGaP. Nucleic Acids Res. 2014;42:D975–9.

    Article  CAS  PubMed  Google Scholar 

  • Vernikos G, Medini D, Riley DR, Tettelin H. Ten years of pan-genome analyses. Curr Opin Microbiol. 2015;23:148–54. doi: 10.1016/j.mib.2014.11.016. Epub;%2014 Dec 5.

  • Wang MC, Chen FC, Chen YZ, Huang YT, Chuang TJ. LDGIdb: a database of gene interactions inferred from long-range strong linkage disequilibrium between pairs of SNPs. BMC Res Notes. 2012;5:212–5. doi:10.1186/1756-0500-5-212.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Wellcome Trust Case Control Consortium. Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature. 2007;447:661–8.

    Google Scholar 

  • Welter D, MacArthur J, Morales J, Burdett T, Hall P, Junkins H, Klemm A, Flicek P, Manolio T, Hindorff L, Parkinson H. The NHGRI GWAS Catalog, a curated resource of SNP-trait associations. Nucleic Acids Res. 2014;42:D1001–6.

    Article  CAS  PubMed  Google Scholar 

  • Zondervan KT, Cardon LR. Designing candidate gene and genome-wide case-control association studies. Nat Protoc. 2007;2:2492–501.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Aruni Wilson .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Shanghai Jiao Tong University Press, Shanghai and Springer Science+Business Media Dordrecht

About this chapter

Cite this chapter

Wilson, A. (2017). Genome-Wide Association Studies: A Comprehensive Tool to Explore Comparative Genomic Variations and Interactions. In: Wei, DQ., Ma, Y., Cho, W., Xu, Q., Zhou, F. (eds) Translational Bioinformatics and Its Application. Translational Medicine Research. Springer, Dordrecht. https://doi.org/10.1007/978-94-024-1045-7_9

Download citation

Publish with us

Policies and ethics