Skip to main content
SpringerLink
Log in

Heterogeneous Stock Populations for Analysis of Complex Traits

  • Protocol
  • First Online:
Systems Genetics

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1488))

Abstract

Heterogeneous Stock (HS) populations allow for fine-resolution genetic mapping of a variety of complex traits. HS mice and rats were created from breeding together eight inbred strains, followed by maintaining the colony in a manner that minimizes inbreeding. After 50 or more generations of breeding, the resulting animals’ chromosomes represent a genetic mosaic of the founders’ haplotypes, with the average distance between recombination events in the centiMorgan range. This allows for genetic mapping to only a few Mb, a much smaller region than what can be identified using traditional F2 intercross or backcross mapping strategies. HS animals have been used to fine-map a variety of complex traits including anxiety and fear behaviors, diabetes, asthma, and heart disease, among others. Once a quantitative trait locus (QTL) has been identified, founder sequence and expression analysis can be used to identify underlying causal genes. In the following review, we provide an overview of how HS rats and mice have been used to identify genetic loci, and in some cases the causal genes, underlying complex traits. We discuss the creation and breeding strategies for both HS rats and mice. We then discuss the statistical analyses used to identify genetic loci, as well as strategies to identify causal genes underlying these loci. We end the chapter by discussing limitations faced when using HS populations, including several statistical challenges that have not been fully resolved.

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 109.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 139.99
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

References

  1. Mott R, Flint J (2013) Dissecting quantitative traits in mice. Annu Rev Genomics Hum Genet 14:421–439. doi:10.1146/annurev-genom-091212-153419

    Article  CAS  PubMed  Google Scholar 

  2. Mott R, Talbot CJ, Turri MG, Collins AC, Flint J (2000) A method for fine mapping quantitative trait loci in outbred animal stocks. Proc Natl Acad Sci U S A 97(23):12649–12654. doi:10.1073/pnas.230304397

    Article  PubMed  PubMed Central  Google Scholar 

  3. Hansen C, Spuhler K (1984) Development of the National Institutes of Health genetically heterogeneous rat stock. Alcohol Clin Exp Res 8(5):477–479

    Article  CAS  PubMed  Google Scholar 

  4. McClearn GE, Wilson JR, Meredith W (1970) The use of isogenic and heterogenic mouse stocks in behavioral research. In: Lindzey G, Thiessen D (eds) Contributions to behavior-genetic analysis: the mouse as a prototype. Appleton Century Crofts, New York, pp 3–22

    Google Scholar 

  5. Flint J, Corley R, DeFries JC, Fulker DW, Gray JA, Miller S, Collins AC (1995) A simple genetic basis for a complex psychological trait in laboratory mice. Science 269(5229):1432–1435

    Article  CAS  PubMed  Google Scholar 

  6. Talbot CJ, Nicod A, Cherny SS, Fulker DW, Collins AC, Flint J (1999) High-resolution mapping of quantitative trait loci in outbred mice. Nat Genet 21(3):305–308. doi:10.1038/6825

    Article  CAS  PubMed  Google Scholar 

  7. Aylor DL, Valdar W, Foulds-Mathes W, Buus RJ, Verdugo RA, Baric RS, Ferris MT, Frelinger JA, Heise M, Frieman MB, Gralinski LE, Bell TA, Didion JD, Hua K, Nehrenberg DL, Powell CL, Steigerwalt J, Xie Y, Kelada SN, Collins FS, Yang IV, Schwartz DA, Branstetter LA, Chesler EJ, Miller DR, Spence J, Liu EY, McMillan L, Sarkar A, Wang J, Wang W, Zhang Q, Broman KW, Korstanje R, Durrant C, Mott R, Iraqi FA, Pomp D, Threadgill D, de Villena FP, Churchill GA (2011) Genetic analysis of complex traits in the emerging Collaborative Cross. Genome Res 21(8):1213–1222. doi:10.1101/gr.111310.110

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Durrant C, Tayem H, Yalcin B, Cleak J, Goodstadt L, de Villena FP, Mott R, Iraqi FA (2011) Collaborative Cross mice and their power to map host susceptibility to Aspergillus fumigatus infection. Genome Res 21(8):1239–1248. doi:10.1101/gr.118786.110

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Kover PX, Valdar W, Trakalo J, Scarcelli N, Ehrenreich IM, Purugganan MD, Durrant C, Mott R (2009) A multiparent advanced generation inter-cross to fine-map quantitative traits in Arabidopsis thaliana. PLoS Genet 5(7):e1000551. doi:10.1371/journal.pgen.1000551

    Article  PubMed  PubMed Central  Google Scholar 

  10. Long AD, Macdonald SJ, King EG (2014) Dissecting complex traits using the Drosophila Synthetic Population Resource. Trends Genet 30(11):488–495. doi:10.1016/j.tig.2014.07.009

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Darvasi A, Soller M (1995) Advanced intercross lines, an experimental population for fine genetic mapping. Genetics 141(3):1199–1207

    CAS  PubMed  PubMed Central  Google Scholar 

  12. Parker CC, Cheng R, Sokoloff G, Palmer AA (2012) Genome-wide association for methamphetamine sensitivity in an advanced intercross mouse line. Genes Brain Behav 11(1):52–61. doi:10.1111/j.1601-183X.2011.00747.x

    Article  CAS  PubMed  Google Scholar 

  13. Svenson KL, Gatti DM, Valdar W, Welsh CE, Cheng R, Chesler EJ, Palmer AA, McMillan L, Churchill GA (2012) High-resolution genetic mapping using the mouse diversity outbred population. Genetics 190(2):437–447. doi:10.1534/genetics.111.132597

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Yalcin B, Flint J (2012) Association studies in outbred mice in a new era of full-genome sequencing. Mamm Genome 23(9–10):719–726. doi:10.1007/s00335-012-9409-z

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Zhang W, Korstanje R, Thaisz J, Staedtler F, Harttman N, Xu L, Feng M, Yanas L, Yang H, Valdar W, Churchill GA, Dipetrillo K (2012) Genome-wide association mapping of quantitative traits in outbred mice. G3 (Bethesda) 2(2):167–174. doi:10.1534/g3.111.001792

    Article  Google Scholar 

  16. Solberg Woods LC (2014) QTL mapping in outbred populations: successes and challenges. Physiol Genomics 46(3):81–90. doi:10.1152/physiolgenomics.00127.2013

    Article  PubMed  Google Scholar 

  17. Valdar W, Solberg LC, Gauguier D, Burnett S, Klenerman P, Cookson WO, Taylor MS, Rawlins JN, Mott R, Flint J (2006) Genome-wide genetic association of complex traits in heterogeneous stock mice. Nat Genet 38(8):879–887

    Article  CAS  PubMed  Google Scholar 

  18. Johannesson M, Lopez-Aumatell R, Stridh P, Diez M, Tuncel J, Blazquez G, Martinez-Membrives E, Canete T, Vicens-Costa E, Graham D, Copley RR, Hernandez-Pliego P, Beyeen AD, Ockinger J, Fernandez-Santamaria C, Gulko PS, Brenner M, Tobena A, Guitart-Masip M, Gimenez-Llort L, Dominiczak A, Holmdahl R, Gauguier D, Olsson T, Mott R, Valdar W, Redei EE, Fernandez-Teruel A, Flint J (2009) A resource for the simultaneous high-resolution mapping of multiple quantitative trait loci in rats: the NIH heterogeneous stock. Genome Res 19(1):150–158. doi:10.1101/gr.081497.108

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Talbot CJ, Radcliffe RA, Fullerton J, Hitzemann R, Wehner JM, Flint J (2003) Fine scale mapping of a genetic locus for conditioned fear. Mamm Genome 14(4):223–230

    Article  PubMed  Google Scholar 

  20. Demarest K, Koyner J, McCaughran J Jr, Cipp L, Hitzemann R (2001) Further characterization and high-resolution mapping of quantitative trait loci for ethanol-induced locomotor activity. Behav Genet 31(1):79–91

    Article  CAS  PubMed  Google Scholar 

  21. Johnsen AK, Valdar W, Golden L, Ortiz-Lopez A, Hitzemann R, Flint J, Mathis D, Benoist C (2011) Genome-wide and species-wide dissection of the genetics of arthritis severity in heterogeneous stock mice. Arthritis Rheum 63(9):2630–2640. doi:10.1002/art.30425

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Solberg Woods LC, Holl K, Tschannen M, Valdar W (2010) Fine-mapping a locus for glucose tolerance using heterogeneous stock rats. Physiol Genomics 41(1):102–108. doi:10.1152/physiolgenomics.00178.2009, 00178.2009 [pii]

    Article  PubMed  Google Scholar 

  23. Tsaih SW, Holl K, Jia S, Kaldunski M, Tschannen M, He H, Andrae JW, Li SH, Stoddard A, Wiederhold A, Parrington J, Ruas da Silva M, Galione A, Meigs J, Hoffmann RG, Simpson P, Jacob H, Hessner M, Solberg Woods LC (2014) Identification of a novel gene for diabetic traits in rats, mice, and humans. Genetics 198(1):17–29. doi:10.1534/genetics.114.162982

    Article  PubMed  PubMed Central  Google Scholar 

  24. Baud A, Hermsen R, Guryev V, Stridh P, Graham D, McBride MW, Foroud T, Calderari S, Diez M, Ockinger J, Beyeen AD, Gillett A, Abdelmagid N, Guerreiro-Cacais AO, Jagodic M, Tuncel J, Norin U, Beattie E, Huynh N, Miller WH, Koller DL, Alam I, Falak S, Osborne-Pellegrin M, Martinez-Membrives E, Canete T, Blazquez G, Vicens-Costa E, Mont-Cardona C, Diaz-Moran S, Tobena A, Hummel O, Zelenika D, Saar K, Patone G, Bauerfeind A, Bihoreau MT, Heinig M, Lee YA, Rintisch C, Schulz H, Wheeler DA, Worley KC, Muzny DM, Gibbs RA, Lathrop M, Lansu N, Toonen P, Ruzius FP, de Bruijn E, Hauser H, Adams DJ, Keane T, Atanur SS, Aitman TJ, Flicek P, Malinauskas T, Jones EY, Ekman D, Lopez-Aumatell R, Dominiczak AF, Johannesson M, Holmdahl R, Olsson T, Gauguier D, Hubner N, Fernandez-Teruel A, Cuppen E, Mott R, Flint J (2013) Combined sequence-based and genetic mapping analysis of complex traits in outbred rats. Nat Genet 45(7):767–775. doi:10.1038/ng.2644

    Article  CAS  PubMed  Google Scholar 

  25. Baud A, Guryev V, Hummel O, Johannesson M, Flint J (2014) Genomes and phenomes of a population of outbred rats and its progenitors. Sci Data 1:140011. doi:10.1038/sdata.2014.11

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Alam I, Koller DL, Canete T, Blazquez G, Mont-Cardona C, Lopez-Aumatell R, Martinez-Membrives E, Diaz-Moran S, Tobena A, Fernandez-Teruel A, Stridh P, Diez M, Olsson T, Johannesson M, Baud A, Econs MJ, Foroud T (2015) Fine mapping of bone structure and strength QTLs in heterogeneous stock rat. Bone 81:417–426. doi:10.1016/j.bone.2015.08.013

    Article  PubMed  PubMed Central  Google Scholar 

  27. Solberg Woods LC, Stelloh C, Regner KR, Schwabe T, Eisenhauer J, Garrett MR (2010) Heterogeneous stock rats: a new model to study the genetics of renal phenotypes. Am J Physiol Renal Physiol 298(6):F1484–F1491. doi:10.1152/ajprenal.00002.2010, 00002.2010 [pii]

    Article  PubMed  PubMed Central  Google Scholar 

  28. Richards JB, Lloyd DR, Kuehlewind B, Militello L, Paredez M, Solberg Woods L, Palmer AA (2013) Strong genetic influences on measures of behavioral-regulation among inbred rat strains. Genes Brain Behav 12(5):490–502. doi:10.1111/gbb.12050

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Wang T, Han W, Wang B, Jiang Q, Solberg-Woods LC, Palmer AA, Chen H (2014) Propensity for social interaction predicts nicotine-reinforced behaviors in outbred rats. Genes Brain Behav 13(2):202–212. doi:10.1111/gbb.12112

    Article  CAS  PubMed  Google Scholar 

  30. Diaz-Moran S, Palencia M, Mont-Cardona C, Canete T, Blazquez G, Martinez-Membrives E, Lopez-Aumatell R, Tobena A, Fernandez-Teruel A (2012) Coping style and stress hormone responses in genetically heterogeneous rats: comparison with the Roman rat strains. Behav Brain Res 228(1):203–210. doi:10.1016/j.bbr.2011.12.002, S0166-4328(11)00844-8 [pii]

    Article  CAS  PubMed  Google Scholar 

  31. Lopez-Aumatell R, Guitart-Masip M, Vicens-Costa E, Gimenez-Llort L, Valdar W, Johannesson M, Flint J, Tobena A, Fernandez-Teruel A (2008) Fearfulness in a large N/Nih genetically heterogeneous rat stock: differential profiles of timidity and defensive flight in males and females. Behav Brain Res 188(1):41–55. doi:10.1016/j.bbr.2007.10.015, S0166-4328(07)00559-1 [pii]

    Article  PubMed  Google Scholar 

  32. Lopez-Aumatell R, Vicens-Costa E, Guitart-Masip M, Martinez-Membrives E, Valdar W, Johannesson M, Canete T, Blazquez G, Driscoll P, Flint J, Tobena A, Fernandez-Teruel A (2009) Unlearned anxiety predicts learned fear: a comparison among heterogeneous rats and the Roman rat strains. Behav Brain Res 202(1):92–101. doi:10.1016/j.bbr.2009.03.024, S0166-4328(09)00185-5 [pii]

    Article  PubMed  Google Scholar 

  33. Bice PJ, Liang T, Zhang L, Graves TJ, Carr LG, Lai D, Kimpel MW, Foroud T (2010) Fine mapping and expression of candidate genes within the chromosome 10 QTL region of the high and low alcohol-drinking rats. Alcohol 44(6):477–485. doi:10.1016/j.alcohol.2010.06.004, S0741-8329(10)00079-0 [pii]

    Article  CAS  PubMed  Google Scholar 

  34. Foroud T, Bice P, Castelluccio P, Bo R, Miller L, Ritchotte A, Lumeng L, Li TK, Carr LG (2000) Identification of quantitative trait loci influencing alcohol consumption in the high alcohol drinking and low alcohol drinking rat lines. Behav Genet 30(2):131–140

    Article  CAS  PubMed  Google Scholar 

  35. Spuhler K, Deitrich RA (1984) Correlative analysis of ethanol-related phenotypes in rat inbred strains. Alcohol Clin Exp Res 8(5):480–484

    Article  CAS  PubMed  Google Scholar 

  36. Parker CC, Chen H, Flagel SB, Geurts AM, Richards JB, Robinson TE, Solberg Woods LC, Palmer AA (2014) Rats are the smart choice: rationale for a renewed focus on rats in behavioral genetics. Neuropharmacology 76 Pt B:250–258. doi:10.1016/j.neuropharm.2013.05.047

    Article  PubMed  Google Scholar 

  37. Katter K, Geurts AM, Hoffmann O, Mates L, Landa V, Hiripi L, Moreno C, Lazar J, Bashir S, Zidek V, Popova E, Jerchow B, Becker K, Devaraj A, Walter I, Grzybowksi M, Corbett M, Filho AR, Hodges MR, Bader M, Ivics Z, Jacob HJ, Pravenec M, Bosze Z, Rulicke T, Izsvak Z (2013) Transposon-mediated transgenesis, transgenic rescue, and tissue-specific gene expression in rodents and rabbits. FASEB J 27(3):930–941. doi:10.1096/fj.12-205526

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Zhao L, Oliver E, Maratou K, Atanur SS, Dubois OD, Cotroneo E, Chen CN, Wang L, Arce C, Chabosseau PL, Ponsa-Cobas J, Frid MG, Moyon B, Webster Z, Aldashev A, Ferrer J, Rutter GA, Stenmark KR, Aitman TJ, Wilkins MR (2015) The zinc transporter ZIP12 regulates the pulmonary vascular response to chronic hypoxia. Nature 524(7565):356–360. doi:10.1038/nature14620

    Article  CAS  PubMed  Google Scholar 

  39. Gatti DM, Svenson KL, Shabalin A, Wu LY, Valdar W, Simecek P, Goodwin N, Cheng R, Pomp D, Palmer A, Chesler EJ, Broman KW, Churchill GA (2014) Quantitative trait locus mapping methods for diversity outbred mice. G3 (Bethesda) 4(9):1623–1633. doi:10.1534/g3.114.013748

    Article  Google Scholar 

  40. Valdar W, Holmes CC, Mott R, Flint J (2009) Mapping in structured populations by resample model averaging. Genetics 182(4):1263–1277. doi:10.1534/genetics.109.100727, genetics.109.100727 [pii]

    Article  PubMed  PubMed Central  Google Scholar 

  41. Cheng R, Abney M, Palmer AA, Skol AD (2011) QTLRel: an R package for genome-wide association studies in which relatedness is a concern. BMC Genet 12:66. doi:10.1186/1471-2156-12-66, doi:1471-2156-12-66 [pii]

  42. Cheng R, Lim JE, Samocha KE, Sokoloff G, Abney M, Skol AD, Palmer AA (2010) Genome-wide association studies and the problem of relatedness among advanced intercross lines and other highly recombinant populations. Genetics 185(3):1033–1044. doi:10.1534/genetics.110.116863, genetics.110.116863 [pii]

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Rockman MV, Kruglyak L (2008) Breeding designs for recombinant inbred advanced intercross lines. Genetics 179(2):1069–1078. doi:10.1534/genetics.107.083873

    Article  PubMed  PubMed Central  Google Scholar 

  44. Mott R, Yuan W, Kaisaki P, Gan X, Cleak J, Edwards A, Baud A, Flint J (2014) The architecture of parent-of-origin effects in mice. Cell 156(1–2):332–342. doi:10.1016/j.cell.2013.11.043

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Kang HM, Zaitlen NA, Wade CM, Kirby A, Heckerman D, Daly MJ, Eskin E (2008) Efficient control of population structure in model organism association mapping. Genetics 178(3):1709–1723. doi:10.1534/genetics.107.080101, doi:178/3/1709 [pii]

    Article  PubMed  PubMed Central  Google Scholar 

  46. Solberg Woods LC, Holl KL, Oreper D, Xie Y, Tsaih SW, Valdar W (2012) Fine-mapping diabetes-related traits, including insulin resistance, in heterogeneous stock rats. Physiol Genomics 44(21):1013–1026. doi:10.1152/physiolgenomics.00040.2012

    Article  PubMed  Google Scholar 

  47. Yalcin B, Flint J, Mott R (2005) Using progenitor strain information to identify quantitative trait nucleotides in outbred mice. Genetics 171(2):673–681

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Keane TM, Goodstadt L, Danecek P, White MA, Wong K, Yalcin B, Heger A, Agam A, Slater G, Goodson M, Furlotte NA, Eskin E, Nellaker C, Whitley H, Cleak J, Janowitz D, Hernandez-Pliego P, Edwards A, Belgard TG, Oliver PL, McIntyre RE, Bhomra A, Nicod J, Gan X, Yuan W, van der Weyden L, Steward CA, Bala S, Stalker J, Mott R, Durbin R, Jackson IJ, Czechanski A, Guerra-Assuncao JA, Donahue LR, Reinholdt LG, Payseur BA, Ponting CP, Birney E, Flint J, Adams DJ (2011) Mouse genomic variation and its effect on phenotypes and gene regulation. Nature 477(7364):289–294. doi:10.1038/nature10413

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Huang GJ, Shifman S, Valdar W, Johannesson M, Yalcin B, Taylor MS, Taylor JM, Mott R, Flint J (2009) High resolution mapping of expression QTLs in heterogeneous stock mice in multiple tissues. Genome Res 19(6):1133–1140. doi:10.1101/gr.088120.108

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Chen Y, Zhu J, Lum PY, Yang X, Pinto S, MacNeil DJ, Zhang C, Lamb J, Edwards S, Sieberts SK, Leonardson A, Castellini LW, Wang S, Champy MF, Zhang B, Emilsson V, Doss S, Ghazalpour A, Horvath S, Drake TA, Lusis AJ, Schadt EE (2008) Variations in DNA elucidate molecular networks that cause disease. Nature 452(7186):429–435. doi:10.1038/nature06757, nature06757 [pii]

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Ghazalpour A, Doss S, Zhang B, Wang S, Plaisier C, Castellanos R, Brozell A, Schadt EE, Drake TA, Lusis AJ, Horvath S (2006) Integrating genetic and network analysis to characterize genes related to mouse weight. PLoS Genet 2(8):e130. doi:10.1371/journal.pgen.0020130, 06-PLGE-RA-0128R2 [pii]

    Article  PubMed  PubMed Central  Google Scholar 

  52. Keller MP, Choi Y, Wang P, Belt Davis D, Rabaglia ME, Oler AT, Stapleton DS, Argmann C, Schueler KL, Edwards S, Steinberg HA, Chaibub Neto E, Kleinhanz R, Turner S, Hellerstein MK, Schadt EE, Yandell BS, Kendziorski C, Attie AD (2008) A gene expression network model of type 2 diabetes links cell cycle regulation in islets with diabetes susceptibility. Genome Res 18(5):706–716. doi:10.1101/gr.074914.107, gr.074914.107 [pii]

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Schadt EE, Lamb J, Yang X, Zhu J, Edwards S, Guhathakurta D, Sieberts SK, Monks S, Reitman M, Zhang C, Lum PY, Leonardson A, Thieringer R, Metzger JM, Yang L, Castle J, Zhu H, Kash SF, Drake TA, Sachs A, Lusis AJ (2005) An integrative genomics approach to infer causal associations between gene expression and disease. Nat Genet 37(7):710–717. doi:10.1038/ng1589, ng1589 [pii]

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Stamatoyannopoulos JA, Snyder M, Hardison R, Ren B, Gingeras T, Gilbert DM, Groudine M, Bender M, Kaul R, Canfield T, Giste E, Johnson A, Zhang M, Balasundaram G, Byron R, Roach V, Sabo PJ, Sandstrom R, Stehling AS, Thurman RE, Weissman SM, Cayting P, Hariharan M, Lian J, Cheng Y, Landt SG, Ma Z, Wold BJ, Dekker J, Crawford GE, Keller CA, Wu W, Morrissey C, Kumar SA, Mishra T, Jain D, Byrska-Bishop M, Blankenberg D, Lajoie BR, Jain G, Sanyal A, Chen KB, Denas O, Taylor J, Blobel GA, Weiss MJ, Pimkin M, Deng W, Marinov GK, Williams BA, Fisher-Aylor KI, Desalvo G, Kiralusha A, Trout D, Amrhein H, Mortazavi A, Edsall L, McCleary D, Kuan S, Shen Y, Yue F, Ye Z, Davis CA, Zaleski C, Jha S, Xue C, Dobin A, Lin W, Fastuca M, Wang H, Guigo R, Djebali S, Lagarde J, Ryba T, Sasaki T, Malladi VS, Cline MS, Kirkup VM, Learned K, Rosenbloom KR, Kent WJ, Feingold EA, Good PJ, Pazin M, Lowdon RF, Adams LB (2012) An encyclopedia of mouse DNA elements (Mouse ENCODE). Genome Biol 13(8):418. doi:10.1186/gb-2012-13-8-418

    Article  PubMed  PubMed Central  Google Scholar 

  55. Hosseini M, Goodstadt L, Hughes JR, Kowalczyk MS, de Gobbi M, Otto GW, Copley RR, Mott R, Higgs DR, Flint J (2013) Causes and consequences of chromatin variation between inbred mice. PLoS Genet 9(6):e1003570. doi:10.1371/journal.pgen.1003570

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Thomas KR, Capecchi MR (1990) Targeted disruption of the murine int-1 proto-oncogene resulting in severe abnormalities in midbrain and cerebellar development. Nature 346(6287):847–850. doi:10.1038/346847a0

    Article  CAS  PubMed  Google Scholar 

  57. Geurts AM, Cost GJ, Freyvert Y, Zeitler B, Miller JC, Choi VM, Jenkins SS, Wood A, Cui X, Meng X, Vincent A, Lam S, Michalkiewicz M, Schilling R, Foeckler J, Kalloway S, Weiler H, Menoret S, Anegon I, Davis GD, Zhang L, Rebar EJ, Gregory PD, Urnov FD, Jacob HJ, Buelow R (2009) Knockout rats via embryo microinjection of zinc-finger nucleases. Science 325(5939):433. doi:10.1126/science.1172447, doi:325/5939/433 [pii]

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Flint J, Eskin E (2012) Genome-wide association studies in mice. Nat Rev Genet 13(11):807–817. doi:10.1038/nrg3335

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Long AD, Mullaney SL, Mackay TF, Langley CH (1996) Genetic interactions between naturally occurring alleles at quantitative trait loci and mutant alleles at candidate loci affecting bristle number in Drosophila melanogaster. Genetics 144(4):1497–1510

    CAS  PubMed  PubMed Central  Google Scholar 

  60. Yalcin B, Willis-Owen SA, Fullerton J, Meesaq A, Deacon RM, Rawlins JN, Copley RR, Morris AP, Flint J, Mott R (2004) Genetic dissection of a behavioral quantitative trait locus shows that Rgs2 modulates anxiety in mice. Nat Genet 36(11):1197–1202

    Article  CAS  PubMed  Google Scholar 

  61. Adams DJ, van der Weyden L (2008) Contemporary approaches for modifying the mouse genome. Physiol Genomics 34(3):225–238. doi:10.1152/physiolgenomics.90242.2008

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Cheng R, Palmer AA (2013) A simulation study of permutation, bootstrap, and gene dropping for assessing statistical significance in the case of unequal relatedness. Genetics 193(3):1015–1018. doi:10.1534/genetics.112.146332

    Article  PubMed  PubMed Central  Google Scholar 

  63. Logan RW, Robledo RF, Recla JM, Philip VM, Bubier JA, Jay JJ, Harwood C, Wilcox T, Gatti DM, Bult CJ, Churchill GA, Chesler EJ (2013) High-precision genetic mapping of behavioral traits in the diversity outbred mouse population. Genes Brain Behav 12(4):424–437. doi:10.1111/gbb.12029

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Samocha KE, Lim JE, Cheng R, Sokoloff G, Palmer AA (2010) Fine mapping of QTL for prepulse inhibition in LG/J and SM/J mice using F(2) and advanced intercross lines. Genes Brain Behav 9(7):759–767. doi:10.1111/j.1601-183X.2010.00613.x, GBB613 [pii]

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Hastie T, Tibshirani R, Friedman J (2009) The elements of statistical learning: data mining, inference, and prediction, 2nd edn. Springer, New York

    Book  Google Scholar 

  66. Visscher PM, Thompson R, Haley CS (1996) Confidence intervals in QTL mapping by bootstrapping. Genetics 143(2):1013–1020

    CAS  PubMed  PubMed Central  Google Scholar 

  67. Manichaikul A, Dupuis J, Sen S, Broman KW (2006) Poor performance of bootstrap confidence intervals for the location of a quantitative trait locus. Genetics 174(1):481–489. doi:10.1534/genetics.106.061549, genetics.106.061549 [pii]

    Article  PubMed  PubMed Central  Google Scholar 

  68. Durrant C, Mott R (2010) Bayesian quantitative trait locus mapping using inferred haplotypes. Genetics 184(3):839–852. doi:10.1534/genetics.109.113183, genetics.109.113183 [pii]

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  69. Mott R, Flint J (2002) Simultaneous detection and fine mapping of quantitative trait loci in mice using heterogeneous stocks. Genetics 160(4):1609–1618

    CAS  PubMed  PubMed Central  Google Scholar 

  70. Valdar WS, Flint J, Mott R (2003) QTL fine-mapping with recombinant-inbred heterogeneous stocks and in vitro heterogeneous stocks. Mamm Genome 14(12):830–838. doi:10.1007/s00335-003-3021-1

    Article  PubMed  Google Scholar 

  71. Valdar W, Flint J, Mott R (2006) Simulating the collaborative cross: power of quantitative trait loci detection and mapping resolution in large sets of recombinant inbred strains of mice. Genetics 172(3):1783–1797. doi:10.1534/genetics.104.039313, doi:genetics.104.039313 [pii]

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI, 53130, USA

    Leah C. Solberg Woods

  2. UCL Genetics Institute, University College London, Gower St., London, WC1E 6BT, UK

    Richard Mott

Authors
  1. Leah C. Solberg Woods
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Richard Mott
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Leah C. Solberg Woods .

Editor information

Editors and Affiliations

  1. Department of Infection Genetics, Helmholtz Centre for Infection Research & University of Veterinary Medicine Hannover, Braunschweig, Niedersachsen, Germany

    Klaus Schughart

  2. Department of Microbiology, Immunology and Biochemistry, University of Tennessee Health Science Center, Memphis, Tennessee, USA

    Robert W. Williams

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer Science+Business Media New York

About this protocol

Cite this protocol

Woods, L.C.S., Mott, R. (2017). Heterogeneous Stock Populations for Analysis of Complex Traits. In: Schughart, K., Williams, R. (eds) Systems Genetics. Methods in Molecular Biology, vol 1488. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-6427-7_2

Download citation

  • DOI: https://doi.org/10.1007/978-1-4939-6427-7_2

  • Published:

  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-6425-3

  • Online ISBN: 978-1-4939-6427-7

  • eBook Packages: Springer Protocols

Publish with us

Policies and ethics

Search

Navigation