Imputation of canine genotype array data using 365 whole-genome sequences improves power of genome-wide association studies

English version

Autoři: Jessica J. Hayward ^aff001; Michelle E. White ^aff001; Michael Boyle ^aff002; Laura M. Shannon ^aff003; Margret L. Casal ^aff004; Marta G. Castelhano ^aff005; Sharon A. Center ^aff005; Vicki N. Meyers-Wallen ^aff001; Kenneth W. Simpson ^aff005; Nathan B. Sutter ^aff007; Rory J. Todhunter ^aff005; Adam R. Boyko ^aff001
Působiště autorů: Department of Biomedical Sciences, College of Veterinary Medicine, Cornell University, Ithaca, New York, United States of America ^aff001; Cornell Center for Astrophysics and Planetary Science, Cornell University, Ithaca, New York, United States of America ^aff002; Department of Horticultural Science, University of Minnesota, St Paul, Minnesota, United States of America ^aff003; School of Veterinary Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America ^aff004; Department of Clinical Sciences, College of Veterinary Medicine, Cornell University, Ithaca, New York, United States of America ^aff005; Baker Institute for Animal Health, College of Veterinary Medicine, Cornell University, Ithaca, New York, United States of America ^aff006; Biology Department, La Sierra University, Riverside, California, United States of America ^aff007
Vyšlo v časopise: Imputation of canine genotype array data using 365 whole-genome sequences improves power of genome-wide association studies. PLoS Genet 15(9): e32767. doi:10.1371/journal.pgen.1008003
Kategorie: Research Article
doi: https://doi.org/10.1371/journal.pgen.1008003

Souhrn

Genomic resources for the domestic dog have improved with the widespread adoption of a 173k SNP array platform and updated reference genome. SNP arrays of this density are sufficient for detecting genetic associations within breeds but are underpowered for finding associations across multiple breeds or in mixed-breed dogs, where linkage disequilibrium rapidly decays between markers, even though such studies would hold particular promise for mapping complex diseases and traits. Here we introduce an imputation reference panel, consisting of 365 diverse, whole-genome sequenced dogs and wolves, which increases the number of markers that can be queried in genome-wide association studies approximately 130-fold. Using previously genotyped dogs, we show the utility of this reference panel in identifying potentially novel associations, including a locus on CFA20 significantly associated with cranial cruciate ligament disease, and fine-mapping for canine body size and blood phenotypes, even when causal loci are not in strong linkage disequilibrium with any single array marker. This reference panel resource will improve future genome-wide association studies for canine complex diseases and other phenotypes.

Klíčová slova:

Biology and life sciences – Computational biology – Genome-wide association studies – Genetics – Genomics – Genome analysis – Animal genomics – Mammalian genomics – Human genetics – Genetic loci – Quantitative trait loci – Molecular genetics – Organisms – Eukaryota – Animals – Animal types – Pets and companion animals – Vertebrates – Amniotes – Mammals – Dogs – Zoology – Physiology – Physiological parameters – Molecular biology – Medicine and health sciences

Zdroje

1. Asher L, Diesel G, Summers JF, McGreevy PD, Collins LM. Inherited defects in pedigree dogs. Part 1: Disorders related to breed standards. Vet J. 2009;182: 402–411. doi: 10.1016/j.tvjl.2009.08.033 19836981

2. Lindblad-Toh K, Wade CM, Mikkelsen TS, Karlsson EK, Jaffe DB, Kamal M, et al. Genome sequence, comparative analysis and haplotype structure of the domestic dog. Nature. 2005;438: 803–819. doi: 10.1038/nature04338 16341006

3. Hoeppner MP, Lundquist A, Pirun M, Meadows JRS, Zamani N, Johnson J, et al. An Improved Canine Genome and a Comprehensive Catalogue of Coding Genes and Non-Coding Transcripts. PLOS ONE. 2014;9: e91172. doi: 10.1371/journal.pone.0091172 24625832

4. Kirkness EF, Bafna V, Halpern AL, Levy S, Remington K, Rusch DB, et al. The Dog Genome: Survey Sequencing and Comparative Analysis. Science. 2003;301: 1898–1903. doi: 10.1126/science.1086432 14512627

5. Vaysse A, Ratnakumar A, Derrien T, Axelsson E, Pielberg GR, Sigurdsson S, et al. Identification of Genomic Regions Associated with Phenotypic Variation between Dog Breeds using Selection Mapping. PLOS Genet. 2011;7: e1002316. doi: 10.1371/journal.pgen.1002316 22022279

6. Wolf ZT, Brand HA, Shaffer JR, Leslie EJ, Arzi B, Willet CE, et al. Genome-Wide Association Studies in Dogs and Humans Identify ADAMTS20 as a Risk Variant for Cleft Lip and Palate. PLOS Genet. 2015;11: e1005059. doi: 10.1371/journal.pgen.1005059 25798845

7. Tengvall K, Kierczak M, Bergvall K, Olsson M, Frankowiack M, Farias FHG, et al. Genome-Wide Analysis in German Shepherd Dogs Reveals Association of a Locus on CFA 27 with Atopic Dermatitis. PLOS Genet. 2013;9: e1003475. doi: 10.1371/journal.pgen.1003475 23671420

8. Hayward JJ, Castelhano MG, Oliveira KC, Corey E, Balkman C, Baxter TL, et al. Complex disease and phenotype mapping in the domestic dog. Nat Commun. 2016;7: 10460. doi: 10.1038/ncomms10460 26795439

9. Mogensen MS, Karlskov-Mortensen P, Proschowsky HF, Lingaas F, Lappalainen A, Lohi H, et al. Genome-Wide Association Study in Dachshund: Identification of a Major Locus Affecting Intervertebral Disc Calcification. J Hered. 2011;102: S81–S86. doi: 10.1093/jhered/esr021 21846751

10. Quilez J, Martínez V, Woolliams JA, Sanchez A, Pong-Wong R, Kennedy LJ, et al. Genetic Control of Canine Leishmaniasis: Genome-Wide Association Study and Genomic Selection Analysis. PLOS ONE. 2012;7: e35349. doi: 10.1371/journal.pone.0035349 22558142

11. Daetwyler HD, Capitan A, Pausch H, Stothard P, van Binsbergen R, Brøndum RF, et al. Whole-genome sequencing of 234 bulls facilitates mapping of monogenic and complex traits in cattle. Nat Genet. 2014;46: 858–865. doi: 10.1038/ng.3034 25017103

12. The 1000 Genomes Project Consortium. A global reference for human genetic variation. Nature. 2015;526: 68–74. doi: 10.1038/nature15393 26432245

13. Friedenberg SG, Lunn KF, Meurs KM. Evaluation of the genetic basis of primary hypoadrenocorticism in Standard Poodles using SNP array genotyping and whole-genome sequencing. Mamm Genome Off J Int Mamm Genome Soc. 2017;28: 56–65. doi: 10.1007/s00335-016-9671-6 27864587

14. Karlsson EK, Lindblad-Toh K. Leader of the pack: gene mapping in dogs and other model organisms. Nat Rev Genet. 2008;9: 713–725. doi: 10.1038/nrg2382 18714291

15. Eigenmann JE, Patterson DF, Froesch ER. Body size parallels insulin-like growth factor I levels but not growth hormone secretory capacity. Acta Endocrinol (Copenh). 1984;106: 448–453.

16. Boyko AR, Quignon P, Li L, Schoenebeck JJ, Degenhardt JD, Lohmueller KE, et al. A Simple Genetic Architecture Underlies Morphological Variation in Dogs. PLOS Biol. 2010;8: e1000451. doi: 10.1371/journal.pbio.1000451 20711490

17. Jones P, Chase K, Martin A, Davern P, Ostrander EA, Lark KG. Single-Nucleotide-Polymorphism-Based Association Mapping of Dog Stereotypes. Genetics. 2008;179: 1033–1044. doi: 10.1534/genetics.108.087866 18505865

18. Rimbault M, Beale HC, Schoenebeck JJ, Hoopes BC, Allen JJ, Kilroy-Glynn P, et al. Derived variants at six genes explain nearly half of size reduction in dog breeds. Genome Res. 2013;23: 1985–1995. doi: 10.1101/gr.157339.113 24026177

19. Sutter NB, Bustamante CD, Chase K, Gray MM, Zhao K, Zhu L, et al. A single IGF1 allele is a major determinant of small size in dogs. Science. 2007;316: 112–115. doi: 10.1126/science.1137045 17412960

20. Parker HG, VonHoldt BM, Quignon P, Margulies EH, Shao S, Mosher DS, et al. An Expressed Fgf4 Retrogene Is Associated with Breed-Defining Chondrodysplasia in Domestic Dogs. Science. 2009;325: 995–998. doi: 10.1126/science.1173275 19608863

21. Hoopes BC, Rimbault M, Liebers D, Ostrander EA, Sutter NB. The insulin-like growth factor 1 receptor (IGF1R) contributes to reduced size in dogs. Mamm Genome Off J Int Mamm Genome Soc. 2012;23: 780–790. doi: 10.1007/s00335-012-9417-z 22903739

22. Chase K, Carrier DR, Adler FR, Jarvik T, Ostrander EA, Lorentzen TD, et al. Genetic basis for systems of skeletal quantitative traits: Principal component analysis of the canid skeleton. Proc Natl Acad Sci. 2002;99: 9930–9935. doi: 10.1073/pnas.152333099 12114542

23. Quignon P, Schoenebeck JJ, Chase K, Parker HG, Mosher DS, Johnson GS, et al. Fine Mapping a Locus Controlling Leg Morphology in the Domestic Dog. Cold Spring Harb Symp Quant Biol. 2009;74: 327–333. doi: 10.1101/sqb.2009.74.009 19717540

24. Drögemüller C, Karlsson EK, Hytönen MK, Perloski M, Dolf G, Sainio K, et al. A mutation in hairless dogs implicates FOXI3 in ectodermal development. Science. 2008;321: 1462. doi: 10.1126/science.1162525 18787161

25. Cadieu E, Neff MW, Quignon P, Walsh K, Chase K, Parker HG, et al. Coat Variation in the Domestic Dog Is Governed by Variants in Three Genes. Science. 2009;326: 150–153. doi: 10.1126/science.1177808 19713490

26. Baker LA, Rosa GJM, Hao Z, Piazza A, Hoffman C, Binversie EE, et al. Multivariate genome-wide association analysis identifies novel and relevant variants associated with anterior cruciate ligament rupture risk in the dog model. BMC Genet. 2018;19: 39. doi: 10.1186/s12863-018-0626-7 29940858

27. Baker LA, Kirkpatrick B, Rosa GJM, Gianola D, Valente B, Sumner JP, et al. Genome-wide association analysis in dogs implicates 99 loci as risk variants for anterior cruciate ligament rupture. PLOS ONE. 2017;12: e0173810. doi: 10.1371/journal.pone.0173810 28379989

28. Baird AEG, Carter SD, Innes JF, Ollier W, Short A. Genome-wide association study identifies genomic regions of association for cruciate ligament rupture in Newfoundland dogs. Anim Genet. 2014;45: 542–549. doi: 10.1111/age.12162 24835129

29. Huang M, Hayward JJ, Corey E, Garrison SJ, Wagner GR, Krotscheck U, et al. A novel iterative mixed model to remap three complex orthopedic traits in dogs. PLOS ONE. 2017;12: e0176932. doi: 10.1371/journal.pone.0176932 28614352

30. Baird AEG, Carter SD, Innes JF, Ollier WE, Short AD. Genetic basis of cranial cruciate ligament rupture (CCLR) in dogs. Connect Tissue Res. 2014;55: 275–281. doi: 10.3109/03008207.2014.910199 24684544

31. White ME, Hayward JJ, Stokol T, Boyko AR. Genetic Mapping of Novel Loci Affecting Canine Blood Phenotypes. PLOS ONE. 2015;10: e0145199. doi: 10.1371/journal.pone.0145199 26683458

32. Brown EA, Dickinson PJ, Mansour T, Sturges BK, Aguilar M, Young AE, et al. FGF4 retrogene on CFA12 is responsible for chondrodystrophy and intervertebral disc disease in dogs. Proc Natl Acad Sci. 2017;114: 11476–11481. doi: 10.1073/pnas.1709082114 29073074

33. Plassais J, Rimbault M, Williams FJ, Davis BW, Schoenebeck JJ, Ostrander EA. Analysis of large versus small dogs reveals three genes on the canine X chromosome associated with body weight, muscling and back fat thickness. PLOS Genet. 2017;13: e1006661. doi: 10.1371/journal.pgen.1006661 28257443

34. Millar DS, Lewis MD, Horan M, Newsway V, Easter TE, Gregory JW, et al. Novel mutations of the growth hormone 1 (GH1) gene disclosed by modulation of the clinical selection criteria for individuals with short stature. Hum Mutat. 2003;21: 424–440. doi: 10.1002/humu.10168 12655557

35. Mullen MP, Berry DP, Howard DJ, Diskin MG, Lynch CO, Berkowicz EW, et al. Associations between novel single nucleotide polymorphisms in the Bos taurus growth hormone gene and performance traits in Holstein-Friesian dairy cattle. J Dairy Sci. 2010;93: 5959–5969. doi: 10.3168/jds.2010-3385 21094770

36. Lango Allen H, Estrada K, Lettre G, Berndt SI, Weedon MN, Rivadeneira F, et al. Hundreds of variants clustered in genomic loci and biological pathways affect human height. Nature. 2010;467: 832–838. doi: 10.1038/nature09410 20881960

37. Weedon MN, Lango H, Lindgren CM, Wallace C, Evans DM, Mangino M, et al. Genome-wide association analysis identifies 20 loci that influence adult height. Nat Genet. 2008;40: 575–583. doi: 10.1038/ng.121 18391952

38. Demerath EW, Guan W, Grove ML, Aslibekyan S, Mendelson M, Zhou Y- H, et al. Epigenome-wide association study (EWAS) of BMI, BMI change and waist circumference in African American adults identifies multiple replicated loci. Hum Mol Genet. 2015;24: 4464–4479. doi: 10.1093/hmg/ddv161 25935004

39. Jiang BJ, Zhan XL, Fu CZ, Wang HB, Cheng G, Zan LS. Identification of ANAPC13 gene polymorphisms associated with body measurement traits in Bos taurus. Genet Mol Res. 2012;11: 2862–2870. doi: 10.4238/2012.June.15.6 22782628

40. Cianfarani S. Insulin-like growth factor-II: new roles for an old actor. Front Endocrinol. 2012;3. doi: 10.3389/fendo.2012.00118 23060858

41. Luderer HF, Bai S, Longmore GD. The LIM protein LIMD1 influences osteoblast differentiation and function. Exp Cell Res. 2008;314: 2884–2894. doi: 10.1016/j.yexcr.2008.06.003 18657804

42. Feng Y, Zhao H, Luderer HF, Epple H, Faccio R, Ross FP, et al. The LIM Protein, LIMD1, Regulates AP-1 Activation through an Interaction with TRAF6 to Influence Osteoclast Development. J Biol Chem. 2007;282: 39–48. doi: 10.1074/jbc.M607399200 17092936

43. Willer CJ, Sanna S, Jackson AU, Scuteri A, Bonnycastle LL, Clarke R, et al. Newly identified loci that influence lipid concentrations and risk of coronary artery disease. Nat Genet. 2008;40: 161–169. doi: 10.1038/ng.76 18193043

44. Kathiresan S, Melander O, Guiducci C, Surti A, Burtt NP, Rieder MJ, et al. Six new loci associated with blood low-density lipoprotein cholesterol, high-density lipoprotein cholesterol or triglycerides in humans. Nat Genet. 2008;40: 189–197. doi: 10.1038/ng.75 18193044

45. Li Y, Willer C, Sanna S, Abecasis G. Genotype imputation. Annu Rev Genomics Hum Genet. 2009;10: 387–406. doi: 10.1146/annurev.genom.9.081307.164242 19715440

46. Erbe M, Hayes BJ, Matukumalli LK, Goswami S, Bowman PJ, Reich CM, et al. Improving accuracy of genomic predictions within and between dairy cattle breeds with imputed high-density single nucleotide polymorphism panels. J Dairy Sci. 2012;95: 4114–4129. doi: 10.3168/jds.2011-5019 22720968

47. Yang J, Bakshi A, Zhu Z, Hemani G, Vinkhuyzen AAE, Lee SH, et al. Genetic variance estimation with imputed variants finds negligible missing heritability for human height and body mass index. Nat Genet. 2015;47: 1114–1120. doi: 10.1038/ng.3390 26323059

48. Friedenberg SG, Meurs KM. Genotype imputation in the domestic dog. Mamm Genome. 2016;27: 485–494. doi: 10.1007/s00335-016-9636-9 27129452

49. Howie BN, Donnelly P, Marchini J. A Flexible and Accurate Genotype Imputation Method for the Next Generation of Genome-Wide Association Studies. PLOS Genet. 2009;5: e1000529. doi: 10.1371/journal.pgen.1000529 19543373

50. Browning BL, Browning SR. A Unified Approach to Genotype Imputation and Haplotype-Phase Inference for Large Data Sets of Trios and Unrelated Individuals. Am J Hum Genet. 2009;84: 210–223. doi: 10.1016/j.ajhg.2009.01.005 19200528

51. Shearin AL, Ostrander EA. Leading the way: canine models of genomics and disease. Dis Model Mech. 2010;3: 27–34. doi: 10.1242/dmm.004358 20075379

52. Li H, Durbin R. Fast and accurate short read alignment with Burrows–Wheeler transform. Bioinformatics. 2009;25: 1754–1760. doi: 10.1093/bioinformatics/btp324 19451168

53. McKenna A, Hanna M, Banks E, Sivachenko A, Cibulskis K, Kernytsky A, et al. The Genome Analysis Toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res. 2010;20: 1297–1303. doi: 10.1101/gr.107524.110 20644199

54. DePristo MA, Banks E, Poplin R, Garimella KV, Maguire JR, Hartl C, et al. A framework for variation discovery and genotyping using next-generation DNA sequencing data. Nat Genet. 2011;43: 491–498. doi: 10.1038/ng.806 21478889

55. Van der Auwera GA, Carneiro MO, Hartl C, Poplin R, del Angel G, Levy-Moonshine A, et al. From FastQ Data to High-Confidence Variant Calls: The Genome Analysis Toolkit Best Practices Pipeline. Curr Protoc Bioinforma. 2013;43: 11.10.1–11.10.33.

56. Browning BL, Browning SR. Genotype Imputation with Millions of Reference Samples. Am J Hum Genet. 2016;98: 116–126. doi: 10.1016/j.ajhg.2015.11.020 26748515

57. The 1000 Genomes Project Consortium. An integrated map of genetic variation from 1,092 human genomes. Nature. 2012;491: 56–65. doi: 10.1038/nature11632 23128226

58. Delaneau O, Howie B, Cox AJ, Zagury J- F, Marchini J. Haplotype Estimation Using Sequencing Reads. Am J Hum Genet. 2013;93: 687–696. doi: 10.1016/j.ajhg.2013.09.002 24094745

59. Howie B, Fuchsberger C, Stephens M, Marchini J, Abecasis GR. Fast and accurate genotype imputation in genome-wide association studies through pre-phasing. Nat Genet. 2012;44: 955–959. doi: 10.1038/ng.2354 22820512

60. Perez F, Granger BE. IPython: A System for Interactive Scientific Computing. Comput Sci Engg. 2007;9: 21–29. doi: 10.1109/MCSE.2007.53

61. Hunter JD. Matplotlib: A 2D Graphics Environment. Comput Sci Eng. 2007;9: 90–95. doi: 10.1109/MCSE.2007.55

62. Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MAR, Bender D, et al. PLINK: A Tool Set for Whole-Genome Association and Population-Based Linkage Analyses. Am J Hum Genet. 2007;81: 559–575. doi: 10.1086/519795 17701901

63. Zhou X, Stephens M. Genome-wide Efficient Mixed Model Analysis for Association Studies. Nat Genet. 2012;44: 821–824. doi: 10.1038/ng.2310 22706312

64. Li M- X, Yeung JMY, Cherny SS, Sham PC. Evaluating the effective numbers of independent tests and significant p-value thresholds in commercial genotyping arrays and public imputation reference datasets. Hum Genet. 2011;131: 747–756. doi: 10.1007/s00439-011-1118-2 22143225

65. Sutter NB, Eberle MA, Parker HG, Pullar BJ, Kirkness EF, Kruglyak L, et al. Extensive and breed-specific linkage disequilibrium in Canis familiaris. Genome Res. 2004;14: 2388–2396. doi: 10.1101/gr.3147604 15545498

66. R Core Team. R: A Language and Environment for Statistical Computing. [Internet]. Vienna, Austria: R Foundation for Statistical Computing; 2013. Available: http://www.R-project.org/

67. Venables WN, Ripley BD. Modern Applied Statistics with S. Fourth edition. New York: Springer; 2002.

68. Cingolani P, Platts A, Wang LL, Coon M, Nguyen T, Wang L, et al. A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff. Fly (Austin). 2012;6: 80–92. doi: 10.4161/fly.19695 22728672

69. Campbell CL, Bhérer C, Morrow BE, Boyko AR, Auton A. A Pedigree-Based Map of Recombination in the Domestic Dog Genome. G3 GenesGenomesGenetics. 2016;6: 3517–3524. doi: 10.1534/g3.116.034678 27591755