Skip to main content
SpringerLink
Log in

eQTL

  • Protocol
  • First Online:
Quantitative Trait Loci (QTL)

Part of the book series: Methods in Molecular Biology ((MIMB,volume 871))

Abstract

The goal of mapping expression quantitative trait loci (eQTLs) is to identify genomic regions regulating gene expression traits, which can be gathered through microarrays, RNA-Seq, or related methods. Because thousands of expression traits are analyzed simultaneously, eQTL analysis can help elucidate regulatory networks and provide valuable insights into the molecular mechanisms underlying complex traits. Numerous eQTL studies have been conducted to delineate regulatory networks in various organisms, and they have led to many significant findings. In this chapter, we provide a step-by-step protocol for genome-wide eQTL mapping and downstream analysis.

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

Access this chapter

Log in via an institution
Protocol
USD 49.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 89.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 119.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
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

References

  1. Falchi M, Andrew T, Snieder H, Swaminathan R, Surdulescu G, Spector T (2005) Identification of QTLs for serum lipid levels in a female sib-pair cohort: a novel application to improve the power of two-locus linkage analysis. Hum Mol Genet 14:2971–2979

    Article  PubMed  CAS  Google Scholar 

  2. Lettre G, Jackson AU, Gieger C, Schumacher FR, Berndt SI, Sanna S, Eyheramendy S, Voight BF, Butler JL, Guiducci C, Illig T, Hackett R, Heid IM, Jacobs KB, Lyssenko V, Uda M, Boehnke M, Chanock SJ, Groop LC, Hu FB, Isomaa B, Kraft P, Peltonen L, Salomaa V, Schlessinger D, Hunter DJ, Hayes RB, Abecasis GR, Wichmann HE, Mohlke KL, Hirschhorn JN (2008) Identification of ten loci associated with height highlights new biological pathways in human growth. Nat Genet 40:584–591

    Article  PubMed  CAS  Google Scholar 

  3. Weedon MN, Lango H, Lindgren CM, Wallace C, Evans DM, Mangino M, Freathy RM, Perry JRB, Stevens S, Hall AS, Samani NJ, Shields B, Prokopenko I, Farrall M, Dominiczak A, Johnson T, Bergmann S, Beckmann JS, Vollenweider P, Waterworth DM, Mooser V, Palmer CNA, Morris AD, Ouwehand WH, Caulfield M, Munroe PB, Hattersley AT, McCarthy MI, Frayling TM (2008) Genome-wide association analysis identifies 20 loci that influence adult height. Nat Genet 40:575–583

    Article  PubMed  CAS  Google Scholar 

  4. Brem RB, Yvert G, Clinton R, Kruglyak L (2002) Genetic dissection of transcriptional regulation in budding yeast. Science 296:752–755

    Article  PubMed  CAS  Google Scholar 

  5. Morley M, Molony CM, Weber TM, Devlin JL, Ewens KG, Spielman RS, Cheung VG (2004) Genetic analysis of genome-wide variation in human gene expression. Nature 430:743–747

    Article  PubMed  CAS  Google Scholar 

  6. Schadt EE, Monks SA, Drake TA, Lusis AJ, Che N, Colinayo V, Ruff TG, Milligan SB, Lamb JR, Cavet G, Linsley PS, Mao M, Stoughton RB, Friend SH (2003) Genetics of gene expression surveyed in maize, mouse and man. Nature 422:297–302

    Article  PubMed  CAS  Google Scholar 

  7. Stranger BE, Nica AC, Forrest MS, Dimas A, Bird CP, Beazley C, Ingle CE, Dunning M, Flicek P, Koller D, Montgomery S, Tavare S, Deloukas P, Dermitzakis ET (2007) Population genomics of human gene expression. Nat Genet 39:1217–1224

    Article  PubMed  CAS  Google Scholar 

  8. Grundberg E, Kwan T, Pastinen TM (2010) Analysis of the impact of genetic variation on human gene expression. Methods Mol Biol 628:321–339

    Article  PubMed  CAS  Google Scholar 

  9. Breitling R, Li Y, Tesson BM, Fu J, Wu C, Wiltshire T, Gerrits A, Bystrykh LV, de Haan G, Su AI, Jansen RC (2008) Genetical genomics: spotlight on QTL hotspots. PLoS Genet 4:e1000232

    Article  PubMed  Google Scholar 

  10. Frazer K, Ballinger D, Cox D, Hinds D, Stuve L, Gibbs R, Belmont J, Boudreau A, Hardenbol P, Leal S, Pasternak S, Wheeler D, Willis T, Yu F, Yang H, Zeng C, Gao Y, Hu H, Hu W, Li C, Lin W, Liu S, Pan H, Tang X, Wang J, Wang W, Yu J, Zhang B, Zhang Q, Zhao H, Zhou J, Gabriel S, Barry R, Blumenstiel B, Camargo A, Defelice M, Faggart M, Goyette M, Gupta S, Moore J, Nguyen H, Onofrio R, Parkin M, Roy J, Stahl E, Winchester E, Ziaugra L, Altshuler D, Shen Y, Yao Z, Huang W, Chu X, He Y, Jin L, Liu Y, Sun W, Wang H, Wang Y, Xiong X, Xu L, Waye M, Tsui S, Xue H, Wong J, Galver L, Fan J, Gunderson K, Murray S, Oliphant A, Chee M, Montpetit A, Chagnon F, Ferretti V, Leboeuf M, Olivier J, Phillips M, Roumy S, Sallée C, Verner A, Hudson T, Kwok P, Cai D, Koboldt D, Miller R, Pawlikowska L, Taillon-Miller P, Xiao M, Tsui L, Mak W, Song Y, Tam P, Nakamura Y, Kawaguchi T, Kitamoto T, Morizono T, Nagashima A, Ohnishi Y, Sekine A, Tanaka T, Tsunoda T, Deloukas P, Bird C, Delgado M, Dermitzakis E, Gwilliam R, Hunt S, Morrison J, Powell D, Stranger B, Whittaker P, Bentley D, Daly M, de Bakker P, Barrett J, Chretien Y, Maller J, McCarroll S, Patterson N, Pe'er I, Price A, Purcell S, Richter D, Sabeti P, Saxena R, Schaffner S, Sham P, Varilly P, Stein L, Krishnan L, Smith A, Tello-Ruiz M, Thorisson G, Chakravarti A, Chen P, Cutler D, Kashuk C, Lin S, Abecasis G, Guan W, Li Y, Munro H, Qin Z, Thomas D, McVean G, Auton A, Bottolo L, Cardin N, Eyheramendy S, Freeman C, Marchini J, Myers S, Spencer C, Stephens M, Donnelly P, Cardon L, Clarke G, Evans D, Morris A, Weir B, Mullikin J, Sherry S, Feolo M, Skol A, Zhang H, Matsuda I, Fukushima Y, Macer D, Suda E, Rotimi C, Adebamowo C, Ajayi I, Aniagwu T, Marshall P, Nkwodimmah C, Royal C, Leppert M, Dixon M, Peiffer A, Qiu R, Kent A, Kato K, Niikawa N, Adewole I, Knoppers B, Foster M, Clayton E, Watkin J, Muzny D, Nazareth L, Sodergren E, Weinstock G, Yakub I, Birren B, Wilson R, Fulton L, Rogers J, Burton J, Carter N, Clee C, Griffiths M, Jones M, McLay K, Plumb R, Ross M, Sims S, Willey D, Chen Z, Han H, Kang L, Godbout M, Wallenburg J, L'Archevêque P, Bellemare G, Saeki K, An D, Fu H, Li Q, Wang Z, Wang R, Holden A, Brooks L, McEwen J, Guyer M, Wang V, Peterson J, Shi M, Spiegel J, Sung L, Zacharia L, Collins F, Kennedy K, Jamieson R, Stewart J, Consortium IH (2007) A second generation human haplotype map of over 3.1 million SNPs. Nature 449:851–861

    Article  PubMed  CAS  Google Scholar 

  11. Bolstad B, Irizarry R, Astrand M, Speed T (2003) A comparison of normalization methods for high density oligonucleotide array data based on variance and bias. Bioinformatics 19:185–193

    Article  PubMed  CAS  Google Scholar 

  12. Gentleman RC, Carey VJ, Bates DM, Bolstad B, Dettling M, Dudoit S, Ellis B, Gautier L, Ge Y, Gentry J, Hornik K, Hothorn T, Huber W, Iacus S, Irizarry R, Leisch F, Li C, Maechler M, Rossini AJ, Sawitzki G, Smith C, Smyth G, Tierney L, Yang JY, Zhang J (2004) Bioconductor: open software development for computational biology and bioinformatics. Genome Biol 5:R80

    Article  PubMed  Google Scholar 

  13. Motulsky H, Brown R (2006) Detecting outliers when fitting data with nonlinear regression—a new method based on robust nonlinear regression and the false discovery rate. BMC Bioinformatics 7:123

    Article  PubMed  Google Scholar 

  14. Lai Y, Wu B, Chen L, Zhao H (2004) A statistical method for identifying differential gene-gene co-expression patterns. Bioinformatics 20:3146–3155

    Article  PubMed  CAS  Google Scholar 

  15. Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira M, Bender D, Maller J, Sklar P, de Bakker P, Daly M, Sham P (2007) PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet 81:559–575

    Article  PubMed  CAS  Google Scholar 

  16. Kendziorski C, Wang P (2006) A review of statistical methods for expression quantitative trait loci mapping. Mamm Genome 17:509–517

    Article  PubMed  Google Scholar 

  17. Ballard D, Abraham C, Cho J, Zhao H (2010) Pathway analysis comparison using Crohn’s disease genome wide association studies. BMC Med Genomics 3:25

    Article  PubMed  Google Scholar 

  18. Churchill G, Doerge R (1994) Empirical threshold values for quantitative trait mapping. Genetics 138:963–971

    PubMed  CAS  Google Scholar 

  19. Benjamini Y, Hochberg Y (1995) Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc Series B Stat Methodol 57:289–300

    Google Scholar 

  20. Schadt E, Molony C, Chudin E, Hao K, Yang X, Lum P, Kasarskis A, Zhang B, Wang S, Suver C, Zhu J, Millstein J, Sieberts S, Lamb J, GuhaThakurta D, Derry J, Storey J, Avila-Campillo I, Kruger M, Johnson J, Rohl C, van Nas A, Mehrabian M, Drake T, Lusis A, Smith R, Guengerich F, Strom S, Schuetz E, Rushmore T, Ulrich R (2008) Mapping the genetic architecture of gene expression in human liver. PLoS Biol 6:e107

    Article  PubMed  Google Scholar 

  21. da Huang W, Sherman BT, Tan Q, Collins JR, Alvord WG, Roayaei J, Stephens R, Baseler MW, Lane HC, Lempicki RA (2007) The DAVID gene functional classification tool: a novel biological module-centric algorithm to functionally analyze large gene lists. Genome Biol 8:R183

    Article  Google Scholar 

  22. Zhang B, Horvath S (2005) A general framework for weighted gene co-expression network analysis. Stat Appl Genet Mol Biol 4:Article17

    Google Scholar 

  23. Gauderman W, Murcray C, Gilliland F, Conti D (2007) Testing association between disease and multiple SNPs in a candidate gene. Genet Epidemiol 31:383–395

    Article  PubMed  Google Scholar 

  24. Wang T, Elston R (2007) Improved power by use of a weighted score test for linkage disequilibrium mapping. Am J Hum Genet 80:353–360

    Article  PubMed  CAS  Google Scholar 

  25. Wang K, Abbott D (2008) A principal components regression approach to multilocus genetic association studies. Genet Epidemiol 32:108–118

    Article  PubMed  Google Scholar 

  26. Chapman J, Cooper J, Todd J, Clayton D (2003) Detecting disease associations due to linkage disequilibrium using haplotype tags: a class of tests and the determinants of statistical power. Hum Hered 56:18–31

    Article  PubMed  Google Scholar 

  27. Ballard DH, Cho J, Zhao H (2010) Comparisons of multi-marker association methods to detect association between a candidate region and disease. Genet Epidemiol 34:201–212

    Article  PubMed  Google Scholar 

  28. Zhang W, Zhu J, Schadt EE, Liu JS (2010) A Bayesian partition method for detecting pleiotropic and epistatic eQTL modules. PLoS Comput Biol 6:e1000642

    Article  PubMed  Google Scholar 

  29. Veyrieras JB, Kudaravalli S, Kim SY, Dermitzakis ET, Gilad Y, Stephens M, Pritchard JK (2008) High-resolution mapping of expression-QTLs yields insight into human gene regulation. PLoS Genet 4:e1000214

    Article  PubMed  Google Scholar 

  30. Zhu J, Zhang B, Smith EN, Drees B, Brem RB, Kruglyak L, Bumgarner RE, Schadt EE (2008) Integrating large-scale functional genomic data to dissect the complexity of yeast regulatory networks. Nat Genet 40:854–861

    Article  PubMed  CAS  Google Scholar 

Download references

Acknowledgments

Supported in part by fellowship awards from the China Scholarship Council and NIH grant GM 59507.

Author information

Authors and Affiliations

  1. Hubei Bioinformatics and Molecular Imaging Key Laboratory, Huazhong University of Science and Technology, Wuhan, Hubei, China

    Lun Li

  2. Department of Epidemiology and Public Health, Yale University, New Haven, CT, USA

    Lun Li, Xianghua Zhang & Hongyu Zhao

  3. Department of Electronic Science and Technology, University of Science and Technology of China, Hefei, Anhui, China

    Xianghua Zhang

Authors
  1. Lun Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xianghua Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Hongyu Zhao
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Hongyu Zhao .

Editor information

Editors and Affiliations

  1. University of California, San Diego, Gilman Drive 9500, La Jolla, 92093, California, USA

    Scott A. Rifkin

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer Science+Business Media

About this protocol

Cite this protocol

Li, L., Zhang, X., Zhao, H. (2012). eQTL. In: Rifkin, S. (eds) Quantitative Trait Loci (QTL). Methods in Molecular Biology, vol 871. Humana Press. https://doi.org/10.1007/978-1-61779-785-9_14

Download citation

  • DOI: https://doi.org/10.1007/978-1-61779-785-9_14

  • Published:

  • Publisher Name: Humana Press

  • Print ISBN: 978-1-61779-784-2

  • Online ISBN: 978-1-61779-785-9

  • eBook Packages: Springer Protocols

Publish with us

Policies and ethics

Search

Navigation