Abstract
Quantitative genetic studies in model organisms, particularly in mice, have been extremely successful in identifying chromosomal regions that are associated with a wide variety of behavioral and other traits. However, it is now widely understood that identification of the underlying genes will be far more challenging. In the last few years, a variety of populations have been utilized in an effort to more finely map these chromosomal regions with the goal of identifying specific genes. The common property of these newer populations is that linkage disequilibrium spans relatively short distances, which permits fine-scale mapping resolution. This review focuses on advanced intercross lines (AILs) which are the simplest such population. As originally proposed in 1995 by Darvasi and Soller, an AIL is the product of intercrossing two inbred strains beyond the F2 generation. Unlike recombinant inbred strains, AILs are maintained as outbred populations; brother–sister matings are specifically avoided. Each generation of intercrossing beyond the F2 further degrades linkage disequilibrium between adjacent makers, which allows for fine-scale mapping of quantitative trait loci (QTLs). Advances in genotyping technology and techniques for the statistical analysis of AILs have permitted rapid advances in the application of AILs. We review some of the analytical issues and available software, including QTLRel, EMMA, EMMAX, GEMMA, TASSEL, GRAMMAR, WOMBAT, Mendel, and others.
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References
Abney M, McPeek MS, Ober C (2000) Estimation of variance components of quantitative traits in inbred populations. Am J Hum Genet 66:629–650
Abney M, Ober C, McPeek MS (2002) Quantitative-trait homozygosity and association mapping and empirical genomewide significance in large, complex pedigrees: fasting serum-insulin level in the Hutterites. Am J Hum Genet 70:920–934
Aldinger KA, Sokoloff G, Rosenberg DM et al (2009) Genetic variation and population substructure in outbred CD-1 mice: implications for genome-wide association studies. PLoS ONE 4:e4729. doi:10.1371/journal.pone.0004729
Amin N, van Duijn CM, Aulchenko YS (2007) A genomic background based method for association analysis in related individuals. PLoS ONE 2:e1274. doi:10.1371/journal.pone.0001274
Astle W, Balding DJ (2009) Population structure and cryptic relatedness in genetic association studies. Stat Sci 24:451–471. doi:10.1214/09-STS307
Atwell S, Huang YS, Vilhjálmsson BJ et al (2010) Genome-wide association study of 107 phenotypes in Arabidopsis thaliana inbred lines. Nature 465:627–631. doi:10.1038/nature08800
Aulchenko YS, de Koning D-J, Haley C (2007) Genomewide rapid association using mixed model and regression: a fast and simple method for genomewide pedigree-based quantitative trait loci association analysis. Genetics 177:577–585. doi:10.1534/genetics.107.075614
Backdahl L, Guo JP, Jagodic M et al (2008) Definition of arthritis candidate risk genes by combining rat linkage-mapping results with human case–control association data. Ann Rheum Dis 68:1925–1932. doi:10.1136/ard.2008.090803
Bartnikas TB, Parker CC, Cheng R et al (2012) QTLs for murine red blood cell parameters in LG/J and SM/J F2 and advanced intercross lines. Mamm Genome 23:356–366. doi:10.1007/s00335-012-9393-3
Baud A, Hermsen R, Guryev V et al (2013) Combined sequence-based and genetic mapping analysis of complex traits in outbred rats. Nat Genet 45:767–775. doi:10.1038/ng.2644
Bauman LE, Sinsheimer JS, Sobel EM, Lange K (2008) Mixed effects models for quantitative trait loci mapping with inbred strains. Genetics 180:1743–1761. doi:10.1534/genetics.108.091058
Becanovic K, Jagodic M, Sheng JR et al (2006) Advanced intercross line mapping of Eae5 reveals Ncf-1 and CLDN4 as candidate genes for experimental autoimmune encephalomyelitis. J Immunol 176:6055–6064
Behnke JM, Iraqi FA, Mugambi JM et al (2006) High resolution mapping of chromosomal regions controlling resistance to gastrointestinal nematode infections in an advanced intercross line of mice. Mamm Genome 17:584–597. doi:10.1007/s00335-005-0174-0
Belonogova NM, Svishcheva GR, van Duijn CM et al (2013) Region-based association analysis of human quantitative traits in related individuals. PLoS ONE 8:e65395. doi:10.1371/journal.pone.0065395
Bennett KE, Flick D, Fleming KH et al (2005) Quantitative trait loci that control dengue-2 virus dissemination in the mosquito Aedes aegypti. Genetics 170:185–194. doi:10.1534/genetics.104.035634
Bennett BJ, Farber CR, Orozco L et al (2010) A high-resolution association mapping panel for the dissection of complex traits in mice. Genome Res 20:281–290. doi:10.1101/gr.099234.109
Benson AK, Kelly SA, Legge R et al (2010) Individuality in gut microbiota composition is a complex polygenic trait shaped by multiple environmental and host genetic factors. Proc Natl Acad Sci USA 107:18933–18938. doi:10.1073/pnas.1007028107
Besnier F, Wahlberg P, Rönneg\aard L et al (2011) Fine mapping and replication of QTL in outbred chicken advanced intercross lines. Genet Sel Evol 43:3
Bryant CD, Kole LA, Guido MA et al (2012) Congenic dissection of a major QTL for methamphetamine sensitivity implicates epistasis. Genes Brain Behav 11:623–632. doi:10.1111/j.1601-183X.2012.00795.x
Buchner DA, Geisinger JM, Glazebrook PA et al (2012) The juxtaparanodal proteins CNTNAP2 and TAG1 regulate diet-induced obesity. Mamm Genome 23:431–442. doi:10.1007/s00335-012-9400-8
Chen Y-P, Prashar A, Erichsen JT et al (2011) Heritability of ocular component dimensions in chickens: genetic variants controlling susceptibility to experimentally induced myopia and pretreatment eye size are distinct. Invest Ophthalmol Vis Sci 52:4012–4020. doi:10.1167/iovs.10-7045
Cheng R, Palmer AA (2012) A simulation study of permutation, bootstrap, and gene dropping for assessing statistical significance in the case of unequal relatedness. Genetics 193:1015–1018. doi:10.1534/genetics.112.146332
Cheng R, Lim JE, Samocha KE et al (2010) Genome-wide association studies and the problem of relatedness among advanced intercross lines and other highly recombinant populations. Genetics 185:1033–1044. doi:10.1534/genetics.110.116863
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
Cheng R, Parker CC, Abney M, Palmer AA (2013) Practical considerations regarding the use of genotype and pedigree data to model relatedness in the context of genome-wide association studies. G358 Genes Genomes Genet0 3:1861–1867. doi:10.1534/g3.113.007948
Chesler EJ, Miller DR, Branstetter LR et al (2008) The collaborative cross at oak ridge national laboratory: developing a powerful resource for systems genetics. Mamm Genome 19:382–389. doi:10.1007/s00335-008-9135-8
Cheverud JM, Lawson HA, Fawcett GL et al (2010) Diet-dependent genetic and genomic imprinting effects on obesity in mice. Obesity 19:160–170. doi:10.1038/oby.2010.141
Chia R, Achilli F, Festing MFW, Fisher EMC (2005) The origins and uses of mouse outbred stocks. Nat Genet 37:1181–1186. doi:10.1038/ng1665
Churchill GA, Doerge RW (1994) Empirical threshold values for quantitative trait mapping. Genetics 138:963–971
Churchill GA, Doerge RW (2008) Naive application of permutation testing leads to inflated type I error rates. Genetics 178:609–610. doi:10.1534/genetics.107.074609
Clark MJ, Chen R, Lam HYK et al (2011) Performance comparison of exome DNA sequencing technologies. Nat Biotechnol 29:908–914. doi:10.1038/nbt.1975
Courtney SM, Massett MP (2012) Identification of exercise capacity QTL using association mapping in inbred mice. Physiol Genomics 44:948–955. doi:10.1152/physiolgenomics.00051.2012
Cubillos FA, Parts L, Salinas F et al (2013) High resolution mapping of complex traits with a four-parent advanced intercross yeast population. Genetics. doi:10.1534/genetics.113.155515
Darvasi A, Soller M (1995) Advanced intercross lines, an experimental population for fine genetic mapping. Genetics 141:1199
Demarest K, Koyner J, McCaughran J Jr et al (2001) Further characterization and high-resolution mapping of quantitative trait loci for ethanol-induced locomotor activity. Behav Genet 31:79–91
Devlin B, Roeder K (1999) Genomic control for association studies. Biometrics 55:997–1004
Ehrich TH, Hrbek T, Kenney-Hunt JP et al (2005) Fine-mapping gene-by-diet interactions on chromosome 13 in a LG/J$\times$ SM/J murine model of obesity. Diabetes 54:1863–1872
Elshire RJ, Glaubitz JC, Sun Q et al (2011) A robust, simple genotyping-by-sequencing (GBS) approach for high diversity species. PLoS ONE 6:e19379. doi:10.1371/journal.pone.0019379
Fawcett GL, Roseman CC, Jarvis JP et al (2008) Genetic architecture of adiposity and organ weight using combined generation QTL analysis. Obesity 16:1861–1868. doi:10.1038/oby.2008.300
Fawcett GL, Jarvis JP, Roseman CC et al (2009) Fine-mapping of obesity-related quantitative trait loci in an F9/10 advanced intercross line. Obesity 18:1383–1392. doi:10.1038/oby.2009.411
Fernandez J (2005) Efficiency of the use of pedigree and molecular marker information in conservation programs. Genetics 170:1313–1321. doi:10.1534/genetics.104.037325
Flint J, Eskin E (2012) Genome-wide association studies in mice. Nat Rev Genet 13:807–817. doi:10.1038/nrg3335
Flint J, Mackay TFC (2009) Genetic architecture of quantitative traits in mice, flies, and humans. Genome Res 19:723–733. doi:10.1101/gr.086660.108
Frésard L, Leroux S, Dehais P et al (2012) Fine mapping of complex traits in non-model species: using next generation sequencing and advanced intercross lines in Japanese quail. BMC Genom 13:551
Ghazalpour A, Doss S, Kang H et al (2008) High-resolution mapping of gene expression using association in an outbred mouse stock. PLoS Genet 4:e1000149. doi:10.1371/journal.pgen.1000149
Ghazalpour A, Rau CD, Farber CR et al (2012) Hybrid mouse diversity panel: a panel of inbred mouse strains suitable for analysis of complex genetic traits. Mamm Genome 23:680–692. doi:10.1007/s00335-012-9411-5
Gillett A, Marta M, Jin T et al (2010) TNF production in macrophages is genetically determined and regulates inflammatory disease in rats. J Immunol Baltim Md 1950 185:442–450. doi: 10.4049/jimmunol.0904101
Gilmour AR, Gogel BJ, Cullis BR, Thompson R (2009) ASReml user guide release 3.0. VSN Int. Ltd., Hemel Hempstead
Goddard ME, Wray NR, Verbyla K, Visscher PM (2009) Estimating effects and making predictions from genome-wide marker data. Stat Sci 24:517–529. doi:10.1214/09-STS306
Gomez-Machorro C, Bennett KE, del Lourdes Munoz M, Wc Black (2004) Quantitative trait loci affecting dengue midgut infection barriers in an advanced intercross line of Aedes aegypti. Insect Mol Biol 13:637–648
Harper JM (2008) Wild-derived mouse stocks: an underappreciated tool for aging research. AGE 30:135–145. doi:10.1007/s11357-008-9057-0
Hasenstein J, Lamont SJ (2007) chicken gallinacin gene cluster associated with salmonella colonization in two advanced intercross lines. Iowa State University, Ames
Heifetz EM, Fulton JE, O’Sullivan NP et al (2009) Mapping QTL affecting resistance to Marek’s disease in an F6 advanced intercross population of commercial layer chickens. BMC Genom 10:20. doi:10.1186/1471-2164-10-20
Henderson CR (1975) Best linear unbiased estimation and prediction under a selection model. Biometrics 31:423–447
Hernandez-Valladares M, Naessens J, Gibson JP et al (2004a) Confirmation and dissection of QTL controlling resistance to malaria in mice. Mamm Genome Off J Int Mamm Genome Soc 15:390–398. doi:10.1007/s00335-004-3042-4
Hernandez-Valladares M, Rihet P, Ole-MoiYoi OK, Iraqi FA (2004b) Mapping of a new quantitative trait locus for resistance to malaria in mice by a comparative mapping approach with human Chromosome 5q31–q33. Immunogenetics 56:115–117. doi:10.1007/s00251-004-0667-0
Hersch M, Peter B, Kang HM et al (2012) Mapping genetic variants associated with beta-adrenergic responses in inbred mice. PLoS ONE 7:e41032. doi:10.1371/journal.pone.0041032
Heydemann A, Swaggart KA, Kim GH et al (2012) The superhealing MRL background improves muscular dystrophy. Skelet Muscle 2:26. doi:10.1186/2044-5040-2-26
Himes BE, Sheppard K, Berndt A et al (2013) Integration of mouse and human genome-wide association data identifies KCNIP4 as an asthma gene. PLoS ONE 8:e56179. doi:10.1371/journal.pone.0056179
Huang BE, Shah R, George AW (2012a) dlmap: an R Package for mixed model QTL and association analysis. J Stat Softw 50:1–22
Huang W, Richards S, Carbone MA et al (2012b) Epistasis dominates the genetic architecture of Drosophila quantitative traits. Proc Natl Acad Sci 109:15553–15559
Huberle A, Beyeen AD, Ockinger J et al (2009) Advanced intercross line mapping suggests that Ncf1 (Ean6) regulates severity in an animal model of Guillain–Barre syndrome. J Immunol 182:4432–4438. doi:10.4049/jimmunol.0803847
Iancu OD, Darakjian P, Kawane S, Bottomly D, Hitzemann R, McWeeney S (2012) Detection of expression quantitative trait Loci in complex mouse crosses: impact and alleviation of data quality and complex population substructure. Front Genet 3:157. doi:10.3389/fgene.2012.00157
Iancu O, Darakjian P, Walter N et al (2010) Genetic diversity and striatal gene networks: focus on the heterogeneous stock-collaborative cross (HS-CC) mouse. BMC Genom 11:585
Iancu OD, Oberbeck D, Darakjian P et al (2013) Selection for drinking in the dark alters brain gene coexpression networks. Alcohol Clin Exp Res 37:1295–1303. doi:10.1111/acer.12100
Illingworth CJR, Parts L, Bergström A et al (2013) Inferring genome-wide recombination landscapes from advanced intercross lines: application to yeast crosses. PLoS ONE 8:e62266. doi:10.1371/journal.pone.0062266
Iraqi F, Clapcott SJ, Kumari P et al (2000) Fine mapping of trypanosomiasis resistance loci in murine advanced intercross lines. Mamm Genome 11:645–648. doi:10.1007/s003350010133
Ishikawa A, Matsuda Y, Namikawa T (2000) Detection of quantitative trait loci for body weight at 10 weeks from Philippine wild mice. Mamm Genome 11:824–830. doi:10.1007/s003350010145
Jagodic M, Becanovic K, Sheng JR et al (2004) An advanced intercross line resolves Eae18 into two narrow quantitative trait loci syntenic to multiple sclerosis candidate loci. J Immunol 173:1366–1373
Jakobsdottir J, McPeek MS (2013) MASTOR: mixed-model association mapping of quantitative traits in samples with related individuals. Am J Hum Genet 92:652–666. doi:10.1016/j.ajhg.2013.03.014
Jarvis JP, Cheverud JM (2010) Mapping the epistatic network underlying murine reproductive fatpad variation. Genetics 187:597–610. doi:10.1534/genetics.110.123505
Jennen DG, Vereijken AL, Bovenhuis H et al (2005) Confirmation of quantitative trait loci affecting fatness in chickens. Genet Sel Evol 37:215. doi:10.1186/1297-9686-37-3-215
Johannesson M, Karlsson J, Wernhoff P et al (2005) Identification of epistasis through a partial advanced intercross reveals three arthritis loci within the Cia5 QTL in mice. Genes Immun 6:175–185. doi:10.1038/sj.gene.6364155
Johnson NV, Ahn SH, Deshmukh H et al (2012) Haplotype association mapping identifies a candidate gene region in mice infected with Staphylococcus aureus. G358 Genes Genomes Genet 2:693–700. doi:10.1534/g3.112.002501
Ka S, Markljung E, Ring H et al (2013) Expression of carnitine palmitoyl-CoA transferase-1B is influenced by a cis-acting eQTL in two chicken lines selected for high and low body weight. Physiol Genomics 45:367–376. doi:10.1152/physiolgenomics.00078.2012
Kang HM, Zaitlen NA, Wade CM et al (2008) Efficient control of population structure in model organism association mapping. Genetics 178:1709–1723. doi:10.1534/genetics.107.080101
Kang HM, Sul JH, Service SK et al (2010) Variance component model to account for sample structure in genome-wide association studies. Nat Genet 42:348–354. doi:10.1038/ng.548
Kärst S, Strucken EM, Schmitt AO et al (2013) Effect of the myostatin locus on muscle mass and intramuscular fat content in a cross between mouse lines selected for hypermuscularity. BMC Genom 14:16
Kelly SA, Nehrenberg DL, Hua K et al (2009) Parent-of-origin effects on voluntary exercise levels and body composition in mice. Physiol Genomics 40:111–120. doi:10.1152/physiolgenomics.00139.2009
Kelly SA, Nehrenberg DL, Peirce JL et al (2010) Genetic architecture of voluntary exercise in an advanced intercross line of mice. Physiol Genomics 42:190–200. doi:10.1152/physiolgenomics.00028.2010
Kelly SA, Nehrenberg DL, Hua K et al (2012) Functional genomic architecture of predisposition to voluntary exercise in Mice: expression QTL in the brain. Genetics 191:643–654. doi:10.1534/genetics.112.140509
Kenny EE, Kim M, Gusev A et al (2010) Increased power of mixed models facilitates association mapping of 10 loci for metabolic traits in an isolated population. Hum Mol Genet 20:827–839. doi:10.1093/hmg/ddq510
Kirby A, Kang HM, Wade CM et al (2010) Fine mapping in 94 inbred mouse strains using a high-density haplotype resource. Genetics 185:1081–1095. doi:10.1534/genetics.110.115014
Korte A, Vilhjálmsson BJ, Segura V et al (2012) A mixed-model approach for genome-wide association studies of correlated traits in structured populations. Nat Genet 44:1066–1071. doi:10.1038/ng.2376
Kraja AT, Lawson HA, Arnett DK et al (2012) Obesity–insulin targeted genes in the 3p26-25 region in human studies and LG/J and SM/J mice. Metabolism 61:1129–1141. doi:10.1016/j.metabol.2012.01.008
Kruuk LEB (2004) Estimating genetic parameters in natural populations using the “animal model.”Philos Trans R Soc B Biol Sci 359:873–890. doi:10.1098/rstb.2003.1437
Lange K, Papp JC, Sinsheimer JS et al (2013) Mendel: the Swiss army knife of genetic analysis programs. Bioinformatics 29:1568–1570. doi:10.1093/bioinformatics/btt187
Laurie CC, Nickerson DA, Anderson AD et al (2007) Linkage disequilibrium in wild mice. PLoS Genet 3:e144
Lawson HA, Zelle KM, Fawcett GL et al (2010) Genetic, epigenetic, and gene-by-diet interaction effects underlie variation in serum lipids in a LG/J × SM/J murine model. J Lipid Res 51:2976–2984. doi:10.1194/jlr.M006957
Lawson HA, Cady JE, Partridge C et al (2011a) Genetic effects at pleiotropic loci are context-dependent with consequences for the maintenance of genetic variation in populations. PLoS Genet 7:e1002256. doi:10.1371/journal.pgen.1002256
Lawson HA, Lee A, Fawcett GL et al (2011b) The importance of context to the genetic architecture of diabetes-related traits is revealed in a genome-wide scan of a LG/J × SM/J murine model. Mamm Genome 22:197–208. doi:10.1007/s00335-010-9313-3
Leamy LJ, Kelly SA, Hua K, Pomp D (2012) Exercise and diet affect quantitative trait loci for body weight and composition traits in an advanced intercross population of mice. Physiol Genomics 44:1141–1153. doi:10.1152/physiolgenomics.00115.2012
Leamy LJ, Kelly SA, Hua K et al (2013) Quantitative trait loci for bone mineral density and femoral morphology in an advanced intercross population of mice. Bone 55:222–229. doi:10.1016/j.bone.2013.02.014
Legare ME, Bartlett FS, Frankel WN (2000) A major effect QTL determined by multiple genes in epileptic EL mice. Genome Res 10:42–48
Lionikas A, Cheng R, Lim JE et al (2010) Fine-mapping of muscle weight QTL in LG/J and SM/J intercrosses. Physiol Genomics 42A:33–38. doi:10.1152/physiolgenomics.00100.2010
Lippert C, Listgarten J, Liu Y et al (2011) FaST linear mixed models for genome-wide association studies. Nat Methods 8:833–835. doi:10.1038/nmeth.1681
Lippert C, Quon G, Kang EY et al (2013) The benefits of selecting phenotype-specific variants for applications of mixed models in genomics. Sci Rep 3:1815
Listgarten J, Lippert C, Heckerman D (2013) FaST-LMM-Select for addressing confounding from spatial structure and rare variants. Nat Genet 45:470–471. doi:10.1038/ng.2620
Listgarten J, Lippert C, Kadie CM et al (2012) Improved linear mixed models for genome-wide association studies. Nat Meth 9:525–526. doi:10.1038/nmeth.2037
Logan RW, Robledo RF, Recla JM et al (2013) High-precision genetic mapping of behavioral traits in the diversity outbred mouse population: genetic mapping of behavioral traits in the outbred mouse. Genes Brain Behav 12:424–437. doi:10.1111/gbb.12029
Loschiavo M, Nguyen QK, Duselis AR, Vrana PB (2007) Mapping and identification of candidate loci responsible for Peromyscus hybrid overgrowth. Mamm Genome 18:75–85. doi:10.1007/s00335-006-0083-x
MacCluer JW, VandeBerg JL, Read B, Ryder OA (1986) Pedigree analysis by computer simulation. Zoo Biol 5:147–160
Manolio TA, Collins FS, Cox NJ et al (2009) Finding the missing heritability of complex diseases. Nature 461:747–753. doi:10.1038/nature08494
Marta M, Stridh P, Becanovic K et al (2010) Multiple loci comprising immune-related genes regulate experimental neuroinflammation. Genes Immun 11:21–36. doi:10.1038/gene.2009.62
McGuire JL, Bergstrom HC, Parker CC et al (2013) Traits of fear resistance and susceptibility in an advanced intercross line. Eur J Neurosci 38:3314–3324. doi:10.1111/ejn.12337
McNeil CL, Bain CL, Macdonald SJ, Fay JC (2011) Multiple quantitative trait loci influence the shape of a male-specific genital structure in Drosophila melanogaster. G358 Genes Genomes Genet 1:343–351. doi:10.1534/g3.111.000661
McPeek MS (2000) From mouse to human: fine mapping of quantitative trait loci in a model organism. Proc Natl Acad Sci USA 97:12389–12390. doi:10.1073/pnas.240463597
Meyer K (2007) WOMBAT—a tool for mixed model analyses in quantitative genetics by restricted maximum likelihood (REML). J Zhejiang Univ Sci B 8:815–821. doi:10.1631/jzus.2007.B0815
Meyer K, Tier B (2011) “SNP Snappy”: a strategy for fast genome-wide association studies fitting a full mixed model. Genetics 190:275–277. doi:10.1534/genetics.111.134841
Moradi Marjaneh M, Martin ICA, Kirk EP et al (2012) QTL mapping of complex binary traits in an advanced intercross line: QTL mapping of complex binary traits in an advanced intercross line. Anim Genet 43:97–101. doi:10.1111/j.1365-2052.2012.02383.x
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 USA 97:12649–12654
Mott R, Yuan W, Kaisaki P et al (2014) The architecture of parent-of-origin effects in mice. Cell 156:332–342. doi:10.1016/j.cell.2013.11.043
Newman DL, Abney M, McPeek MS et al (2001) The importance of genealogy in determining genetic associations with complex traits. Am J Hum Genet 69:1146
Norgard EA, Jarvis JP, Roseman CC et al (2009) Replication of long-bone length QTL in the F9–F10 LG, SM advanced intercross. Mamm Genome 20:224–235. doi:10.1007/s00335-009-9174-9
Norgard EA, Lawson HA, Pletscher LS et al (2010) Genetic factors and diet affect long-bone length in the F34 LG, SM advanced intercross. Mamm Genome 22:178–196. doi:10.1007/s00335-010-9311-5
Ockinger J, Serrano-Fernández P, Möller S et al (2006) Definition of a 1.06-Mb region linked to neuroinflammation in humans, rats and mice. Genetics 173:1539–1545. doi:10.1534/genetics.106.057406
Ockinger J, Stridh P, Beyeen AD et al (2010) Genetic variants of CC chemokine genes in experimental autoimmune encephalomyelitis, multiple sclerosis and rheumatoid arthritis. Genes Immun 11:142–154. doi:10.1038/gene.2009.82
Park Y-G, Zhao X, Lesueur F et al (2005) Sipa1 is a candidate for underlying the metastasis efficiency modifier locus Mtes1. Nat Genet 37:1055–1062. doi:10.1038/ng1635
Parker CC, Palmer AA (2011) Dark matter: are mice the solution to missing heritability? Front Genet. doi:10.3389/fgene.2011.00032
Parker CC, Cheng R, Sokoloff G et al (2011) Fine-mapping alleles for body weight in LG/J × SM/J F2 and F34 advanced intercross lines. Mamm Genome 22:563–571. doi:10.1007/s00335-011-9349-z
Parker CC, Cheng R, Sokoloff G, Palmer AA (2012) Genome-wide association for methamphetamine sensitivity in an advanced intercross mouse line. Genes Brain Behav 11:52–61. doi:10.1111/j.1601-183X.2011.00747.x
Parker CC, Chen H, Flagel SB et al (2013a) Rats are the smart choice: rationale for a renewed focus on rats in behavioral genetics. Neuropharmacology. doi:10.1016/j.neuropharm.2013.05.047
Parker CC, Sokoloff G, Leung E et al (2013b) A large QTL for fear and anxiety mapped using an F 2 cross can be dissected into multiple smaller QTLs: Dissection of a large QTL. Genes Brain Behav n/a–n/a. doi: 10.1111/gbb.12064
Pasaniuc B, Rohland N, McLaren PJ et al (2012) Extremely low-coverage sequencing and imputation increases power for genome-wide association studies. Nat Genet 44:631–635. doi:10.1038/ng.2283
Pavlicev M, Wagner GP, Noonan JP et al (2013) Genomic correlates of relationship QTL involved in fore- versus hind limb divergence in mice. Genome Biol Evol 5:1926–1936. doi:10.1093/gbe/evt144
Peirce JL, Lu L, Gu J et al (2004) A new set of BXD recombinant inbred lines from advanced intercross populations in mice. BMC Genet 5:7. doi:10.1186/1471-2156-5-7
Peirce JL, Broman KW, Lu L et al (2008) Genome reshuffling for advanced intercross permutation (GRAIP): simulation and permutation for advanced intercross population analysis. PLoS ONE 3:e1977. doi:10.1371/journal.pone.0001977
Pérez-Enciso M, Misztal I (2011) Qxpak. 5: old mixed model solutions for new genomics problems. BMC Bioinformatics 12:202
Pettersson M, Besnier F, Siegel PB, Carlborg Ö (2011) Replication and explorations of high-order epistasis using a large advanced intercross line pedigree. PLoS Genet 7:e1002180. doi:10.1371/journal.pgen.1002180
Philip VM, Sokoloff G, Ackert-Bicknell CL et al (2011) Genetic analysis in the collaborative cross breeding population. Genome Res 21:1223–1238. doi:10.1101/gr.113886.110
Prashar A, Hocking PM, Erichsen JT et al (2009) Common determinants of body size and eye size in chickens from an advanced intercross line. Exp Eye Res 89:42–48. doi:10.1016/j.exer.2009.02.008
Price AL, Patterson NJ, Plenge RM et al (2006) Principal components analysis corrects for stratification in genome-wide association studies. Nat Genet 38:904–909. doi:10.1038/ng1847
Pritchard JK, Stephens M, Donnelly P (2000) Inference of population structure using multilocus genotype data. Genetics 155:945–959
Putnam AS, Ivy JA (2013) Kinship-based management strategies for captive breeding programs when pedigrees are unknown or uncertain. J Hered. doi:10.1093/jhered/est068
Rakitsch B, Lippert C, Stegle O, Borgwardt K (2013) A Lasso multi-marker mixed model for association mapping with population structure correction. Bioinform Oxf Engl 29:206–214. doi:10.1093/bioinformatics/bts669
Redmond SB, Chuammitri P, Andreasen CB et al (2011) Genetic control of chicken heterophil function in advanced intercross lines: associations with novel and with known Salmonella resistance loci and a likely mechanism for cell death in extracellular trap production. Immunogenetics 63:449–458. doi:10.1007/s00251-011-0523-y
Rockman MV, Kruglyak L (2008) Breeding designs for recombinant inbred advanced intercross lines. Genetics 179:1069–1078. doi:10.1534/genetics.107.083873
Rohland N, Reich D (2012) Cost-effective, high-throughput DNA sequencing libraries for multiplexed target capture. Genome Res 22:939–946. doi:10.1101/gr.128124.111
Rosas U, Cibrian-Jaramillo A, Ristova D et al (2013) Integration of responses within and across Arabidopsis natural accessions uncovers loci controlling root systems architecture. Proc Natl Acad Sci USA 110:15133–15138. doi:10.1073/pnas.1305883110
Saavedra-Rodriguez K, Strode C, Flores Suarez A et al (2008) Quantitative trait loci mapping of genome regions controlling permethrin resistance in the mosquito Aedes aegypti. Genetics 180:1137–1152. doi:10.1534/genetics.108.087924
Samocha KE, Lim JE, Cheng R et al (2010) Fine mapping of QTL for prepulse inhibition in LG/J and SM/J mice using F2 and advanced intercross lines. Genes Brain Behav 9:759–767. doi:10.1111/j.1601-183X.2010.00613.x
Searle SR, Casella G, McCulloch CE (2008) Maximum likelihood (ML) and restricted maximum likelihood (REML). Var. Compon. Wiley, New York, pp 232–257
Segura V, Vilhjálmsson BJ, Platt A et al (2012) An efficient multi-locus mixed-model approach for genome-wide association studies in structured populations. Nat Genet 44:825–830. doi:10.1038/ng.2314
Sheng JR, Jagodic M, Dahlman I et al (2005) Eae19, a new locus on rat chromosome 15 regulating experimental autoimmune encephalomyelitis. Genetics 170:283–289. doi:10.1534/genetics.104.035261
Shirley RL, Walter NAR, Reilly MT et al (2004) Mpdz is a quantitative trait gene for drug withdrawal seizures. Nat Neurosci 7:699–700. doi:10.1038/nn1271
Stridh P, Thessen Hedreul M, Beyeen AD et al (2010) Fine-mapping resolves Eae23 into two QTLs and implicates ZEB1 as a candidate gene regulating experimental neuroinflammation in rat. PLoS ONE 5:e12716. doi:10.1371/journal.pone.0012716
Stylianou IM, Christians JK, Keightley PD et al (2004) Genetic complexity of an obesity QTL (Fob3) revealedby detailed genetic mapping. Mamm Genome 15:472–481. doi:10.1007/s00335-004-3039-z
Sul JH, Eskin E (2013) Mixed models can correct for population structure for genomic regions under selection. Nat Rev Genet 14:300. doi:10.1038/nrg2813-c1
Svenson KL, Gatti DM, Valdar W et al (2012) High-resolution genetic mapping using the mouse diversity outbred population. Genetics 190:437–447. doi:10.1534/genetics.111.132597
Svishcheva GR, Axenovich TI, Belonogova NM et al (2012) Rapid variance components—based method for whole-genome association analysis. Nat Genet 44:1166–1170. doi:10.1038/ng.2410
Szatkiewicz JP, Beane GL, Ding Y et al (2008) An imputed genotype resource for the laboratory mouse. Mamm Genome 19:199–208. doi:10.1007/s00335-008-9098-9
Taylor J, Verbyla A (2011) R package wgaim: QTL analysis in bi-parental populations using linear mixed models. J Stat Softw 40:1–18
Terenina E, Babigumira BM, Le Mignon G et al (2013) Association study of molecular polymorphisms in candidate genes related to stress responses with production and meat quality traits in pigs. Domest Anim Endocrinol 44:81–97. doi:10.1016/j.domaniend.2012.09.004
Thaisz J, Tsaih S-W, Feng M et al (2012) Genetic analysis of albuminuria in collaborative cross and multiple mouse intercross populations. AJP Ren Physiol 303:F972–F981. doi:10.1152/ajprenal.00690.2011
Thompson R (2008) Estimation of quantitative genetic parameters. Proc Biol Sci 275:679–686. doi:10.1098/rspb.2007.1417
Thompson EA (2013) Identity by descent: variation in meiosis, across genomes, and in populations. Genetics 194:301–326. doi:10.1534/genetics.112.148825
Thornton T, McPeek MS (2010) ROADTRIPS: case–control association testing with partially or completely unknown population and pedigree structure. Am J Hum Genet 86:172–184. doi:10.1016/j.ajhg.2010.01.001
Uchiyama K, Iwata H, Moriguchi Y et al (2013) Demonstration of genome-wide association studies for identifying markers for wood property and male strobili traits in Cryptomeria japonica. PLoS ONE 8:e79866. doi:10.1371/journal.pone.0079866
Valdar W, Holmes CC, Mott R, Flint J (2009) Mapping in structured populations by resample model averaging. Genetics 182:1263–1277. doi:10.1534/genetics.109.100727
Wahlsten D, Metten P, Crabbe JC (2003) A rating scale for wildness and ease of handling laboratory mice: results for 21 inbred strains tested in two laboratories. Genes Brain Behav 2:71–79
Wang M, Lemon WJ, Liu G et al (2003a) Fine mapping and identification of candidate pulmonary adenoma susceptibility 1 genes using advanced intercross lines. Cancer Res 63:3317–3324
Wang X, Le Roy I, Nicodeme E et al (2003b) Using advanced intercross lines for high-resolution mapping of HDL cholesterol quantitative trait loci. Genome Res 13:1654–1664
Wang JR, de Villena FP-M, Lawson HA et al (2012) Imputation of single-nucleotide polymorphisms in inbred mice using local phylogeny. Genetics 190:449–458. doi:10.1534/genetics.111.132381
Weber JN, Peterson BK, Hoekstra HE (2013) Discrete genetic modules are responsible for complex burrow evolution in Peromyscus mice. Nature 493:402–405. doi:10.1038/nature11816
Wiren A, Gunnarsson U, Andersson L, Jensen P (2009) Domestication-related genetic effects on social behavior in chickens—effects of genotype at a major growth quantitative trait locus. Poult Sci 88:1162–1166. doi:10.3382/ps.2008-00492
Wu C, DeWan A, Hoh J, Wang Z (2011) A comparison of association methods correcting for population stratification in case–control studies: method comparison in population structure. Ann Hum Genet 75:418–427. doi:10.1111/j.1469-1809.2010.00639.x
Yalcin B, Nicod J, Bhomra A et al (2010) Commercially available outbred mice for genome-wide association studies. PLoS Genet 6:e1001085. doi:10.1371/journal.pgen.1001085
Yang H, Ding Y, Hutchins LN et al (2009) A customized and versatile high-density genotyping array for the mouse. Nat Methods 6:663–666. doi:10.1038/nmeth.1359
Yang J, Benyamin B, McEvoy BP et al (2010) Common SNPs explain a large proportion of the heritability for human height. Nat Genet 42:565–569. doi:10.1038/ng.608
Yang H, Wang JR, Didion JP et al (2011) Subspecific origin and haplotype diversity in the laboratory mouse. Nat Genet 43:648–655. doi:10.1038/ng.847
Yang J, Ferreira T, Morris AP et al (2012) Conditional and joint multiple-SNP analysis of GWAS summary statistics identifies additional variants influencing complex traits. Nat Genet 44(369–375):S1–S3. doi:10.1038/ng.2213
Yang J, Zaitlen NA, Goddard ME et al (2014) Advantages and pitfalls in the application of mixed-model association methods. Nat Genet 46:100–106. doi:10.1038/ng.2876
Yazbek SN, Buchner DA, Geisinger JM et al (2011) Deep congenic analysis identifies many strong, context-dependent QTLs, one of which, Slc35b4, regulates obesity and glucose homeostasis. Genome Res 21:1065–1073. doi:10.1101/gr.120741.111
Yoshizawa M, Yamamoto Y, O’Quin KE, Jeffery WR (2012) Evolution of an adaptive behavior and its sensory receptors promotes eye regression in blind cavefish. BMC Biol 10:108. doi:10.1186/1741-7007-10-108
Yu J, Pressoir G, Briggs WH et al (2005) A unified mixed-model method for association mapping that accounts for multiple levels of relatedness. Nat Genet 38:203–208. doi:10.1038/ng1702
Yu X, Bauer K, Wernhoff P et al (2006) Fine mapping of collagen-induced arthritis quantitative trait loci in an advanced intercross line. J Immunol 177:7042–7049
Yu X, Bauer K, Wernhoff P, Ibrahim SM (2007) Using an advanced intercross line to identify quantitative trait loci controlling immune response during collagen-induced arthritis. Genes Immun 8:296–301
Yu X, Teng H, Marques A et al. (2009) High resolution mapping of Cia3: a common arthritis quantitative trait loci in different species. J Immunol Baltim Md 1950 182:3016–3023. doi:10.4049/jimmunol.0803005
Zhang S, Lou Y, Amstein TM et al (2005) Fine mapping of a major locus on Chromosome 10 for exploratory and fear-like behavior in mice. Mamm Genome 16:306–318. doi:10.1007/s00335-004-2427-8
Zhang Z, Ersoz E, Lai C-Q et al (2010) Mixed linear model approach adapted for genome-wide association studies. Nat Genet 42:355–360. doi:10.1038/ng.546
Zhang W, Korstanje R, Thaisz J et al (2012) Genome-wide association mapping of quantitative traits in outbred mice. G358 Genes Genomes Genet 2:167–174. doi:10.1534/g3.111.001792
Zhao K, Aranzana MJ, Kim S et al (2007) An Arabidopsis example of association mapping in structured samples. PLoS Genet 3:e4. doi:10.1371/journal.pgen.0030004
Zhou X, Stephens M (2012) Genome-wide efficient mixed-model analysis for association studies. Nat Genet 44:821–824. doi:10.1038/ng.2310
Zhou JJ, Ghazalpour A, Sobel EM et al (2011) Quantitative trait loci association mapping by imputation of strain origins in multifounder crosses. Genetics 190:459–473. doi:10.1534/genetics.111.135095
Acknowledgments
This work was supported by funding from the NIH (R01DA021336 and T32GM71987). We thank Mark Abney and Peter Carbonetto for their insightful comments during the preparation of this manuscript.
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Gonzales, N.M., Palmer, A.A. Fine-mapping QTLs in advanced intercross lines and other outbred populations. Mamm Genome 25, 271–292 (2014). https://doi.org/10.1007/s00335-014-9523-1
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DOI: https://doi.org/10.1007/s00335-014-9523-1