DOI QR코드

DOI QR Code

Identification of loci affecting teat number by genome-wide association studies on three pig populations

  • Tang, Jianhong (State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University) ;
  • Zhang, Zhiyan (State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University) ;
  • Yang, Bin (State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University) ;
  • Guo, Yuanmei (State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University) ;
  • Ai, Huashui (State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University) ;
  • Long, Yi (State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University) ;
  • Su, Ying (State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University) ;
  • Cui, Leilei (State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University) ;
  • Zhou, Liyu (State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University) ;
  • Wang, Xiaopeng (State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University) ;
  • Zhang, Hui (State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University) ;
  • Wang, Chengbin (State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University) ;
  • Ren, Jun (State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University) ;
  • Huang, Lusheng (State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University) ;
  • Ding, Nengshui (State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University)
  • Received : 2015.11.30
  • Accepted : 2016.03.25
  • Published : 2017.01.01

Abstract

Objective: Three genome-wide association studies (GWAS) and a meta-analysis of GWAS were conducted to explore the genetic mechanisms underlying variation in pig teat number. Methods: We performed three GWAS and a meta-analysis for teat number on three pig populations, including a White Duroc${\times}$Erhualian $F_2$ resource population (n = 1,743), a Chinese Erhualian pig population (n = 320) and a Chinese Sutai pig population (n = 383). Results: We detected 24 single nucleotide polymorphisms (SNPs) that surpassed the genome-wide significant level on Sus Scrofa chromosomes (SSC) 1, 7, and 12 in the $F_2$ resource population, corresponding to four loci for pig teat number. We highlighted vertnin (VRTN) and lysine demethylase 6B (KDM6B) as two interesting candidate genes at the loci on SSC7 and SSC12. No significant associated SNPs were identified in the meta-analysis of GWAS. Conclusion: The results verified the complex genetic architecture of pig teat number. The causative variants for teat number may be different in the three populations

Keywords

References

  1. Bidanel JP, Rosendo A, Iannuccelli N, et al. Detection of quantitative trait loci for teat number and female reproductive traits in Meishan x Large White $F_2$ pigs. Animal 2008;2:813-20.
  2. Lopes MS, Bastiaansen JW, Harlizius B, Knol EF, Bovenhuis H. A genome-wide association study reveals dominance effects on number of teats in pigs. PLoS One 2014;9:e105867. https://doi.org/10.1371/journal.pone.0105867
  3. Duijvesteijn N, Veltmaat JM, Knol EF, Harlizius B. High-resolution association mapping of number of teats in pigs reveals regions controlling vertebral development. BMC Genomics 2014;15:542. https://doi.org/10.1186/1471-2164-15-542
  4. Lee JB, Jung EJ, Park HB, et al. Genome-wide association analysis to identify SNP markers affecting teat numbers in an F2 intercross population between Landrace and Korean native pigs. Mol Biol Rep 2014;41:7167-73. https://doi.org/10.1007/s11033-014-3599-2
  5. Guo T, Ren J, Yang K, Ma J, Zhang Z, Huang L. Quantitative trait loci for fatty acid composition in longissimus dorsi and abdominal fat: results from a White DurocxErhualian intercross $F_2$ population. Anim Genet 2009;40:185-91. https://doi.org/10.1111/j.1365-2052.2008.01819.x
  6. Ding N, Guo Y, Knorr C, et al. Genome-wide QTL mapping for three traits related to teat number in a White Duroc x Erhualian pig resource population. BMC Genet 2009;10:6.
  7. Ramos AM, Crooijmans RP, Affara NA, et al. Design of a high density SNP genotyping assay in the pig using SNPs identified and characterized by next generation sequencing technology. PloS one 2009;4:e6524. https://doi.org/10.1371/journal.pone.0006524
  8. Zhang Z, Druet T. Marker imputation with low-density marker panels in Dutch Holstein cattle. J Dairy Sci 2010;93:5487-94. https://doi.org/10.3168/jds.2010-3501
  9. Druet T, Georges M. A hidden Markov model combining linkage and linkage disequilibrium information for haplotype reconstruction and quantitative trait locus fine mapping. Genetics 2010;184:789-98. https://doi.org/10.1534/genetics.109.108431
  10. Druet T, Farnir FP. Modeling of identity-by-descent processes along a chromosome between haplotypes and their genotyped ancestors. Genetics 2011;188:409-19. https://doi.org/10.1534/genetics.111.127720
  11. Purcell S, Neale B, Todd-Brown K, et al. PLINK: a tool set for wholegenome association and population-based linkage analyses. Am J Hum Genet 2007;81:559-75. https://doi.org/10.1086/519795
  12. Aulchenko YS, Ripke S, Isaacs A, Van Duijn CM. GenABEL: an R library for genome-wide association analysis. Bioinformatics 2007;23:1294-6. https://doi.org/10.1093/bioinformatics/btm108
  13. Storey JD. A direct approach to false discovery rates. J R Stat Soc 2002;64:479-98. https://doi.org/10.1111/1467-9868.00346
  14. Storey JD, Tibshirani R. Statistical significance for genomewide studies. Proc Natl Acad Sci USA 2003;100:9440-5. https://doi.org/10.1073/pnas.1530509100
  15. Willer CJ, Li Y, Abecasis GR. METAL: fast and efficient metaanalysis of genomewide association scans. Bioinformatics 2010; 26:2190-1. https://doi.org/10.1093/bioinformatics/btq340
  16. Hernandez S, Finlayson H, Ashworth C, Haley C, Archibald A. A genome‐wide linkage analysis for reproductive traits in $F_2$ Large WhitexMeishan cross gilts. Anim Genet 2014;45:191-7. https://doi.org/10.1111/age.12123
  17. Wada Y, Akita T, Awata T, et al. Quantitative trait loci (QTL) analysis in a MeishanxGottingen cross population. Anim Genet 2000;31:376-84. https://doi.org/10.1046/j.1365-2052.2000.00696.x
  18. Hao K, Chudin E, McElwee J, Schadt EE. Accuracy of genomewide imputation of untyped markers and impacts on statistical power for association studies. BMC Genet 2009;10:27.
  19. Pei YF, Li J, Zhang L, Papasian CJ, Deng HW. Analyses and comparison of accuracy of different genotype imputation methods. PLoS One 2008;3:e3551. https://doi.org/10.1371/journal.pone.0003551
  20. Marchini J, Howie B. Genotype imputation for genome-wide association studies. Nat Rev Genet 2010;11:499-511. https://doi.org/10.1038/nrg2796
  21. Zhao X, Zhao K, Ren J, et al. An imputation-based genome-wide association study on traits related to male reproduction in a White Duroc x Erhualian F population. Anim Sci J 2015.
  22. Wise AL, Gyi L, Manolio TA. eXclusion: toward integrating the X chromosome in genome-wide association analyses. Am J Hum Genet 2013;92:643-7. https://doi.org/10.1016/j.ajhg.2013.03.017
  23. Guo YM, Lee G, Archibald A, Haley C. Quantitative trait loci for production traits in pigs: a combined analysis of two MeishanxLarge White populations. Anim Genet 2008;39:486-95. https://doi.org/10.1111/j.1365-2052.2008.01756.x
  24. Tortereau F, Gilbert H, Heuven HC, Bidanel JP, Groenen MA, Riquet J. Combining two Meishan $F_2$ crosses improves the detection of QTL on pig chromosomes 2, 4 and 6. Genet Sel Evol 2010;42:42. https://doi.org/10.1186/1297-9686-42-42
  25. Holl J, Cassady J, Pomp D, Johnson R. A genome scan for quantitative trait loci and imprinted regions affecting reproduction in pigs. J Anim Sci 2004;82:3421-9. https://doi.org/10.2527/2004.82123421x
  26. Lee S, Chen Y, Moran C, et al. Linkage and QTL mapping for Sus scrofa chromosome 5. J Anim Breed Geneti2003;120:38-44. https://doi.org/10.1046/j.0931-2668.2003.00422.x
  27. Cassady JP, Johnson RK, Pomp D, et al. Identification of quantitative trait loci affecting reproduction in pigs. J Anim Sci 2001;79:623-33. https://doi.org/10.2527/2001.793623x
  28. Sato S, Atsuji K, Saito N, et al. Identification of quantitative trait loci affecting corpora lutea and number of teats in a Meishan x Duroc $F_2$ resource population. J Anim Sci 2006;84:2895-901. https://doi.org/10.2527/jas.2006-176
  29. Hirooka H, de Koning DJ, Harlizius B, et al. A whole-genome scan for quantitative trait loci affecting teat number in pigs. J Anim Sci 2001;79:2320-6. https://doi.org/10.2527/2001.7992320x
  30. Guo YM, Zhang ZY, Ma JW, Ai HS, Ren J, Huang LS. A genomewide association study of feed efficiency and feeding behaviors at two fattening stages in a White DurocxErhualian F population. J Anim Sci 2015;93:1481-9. https://doi.org/10.2527/jas.2014-8655
  31. Ohtani K, Zhao C, Dobreva G, et al. Jmjd3 controls mesodermal and cardiovascular differentiation of embryonic stem cells. Circ Res 2013;113:856-62. https://doi.org/10.1161/CIRCRESAHA.113.302035
  32. Davenport TG, Jerome-Majewska LA, Papaioannou VE. Mammary gland, limb and yolk sac defects in mice lacking Tbx3, the gene mutated in human ulnar mammary syndrome. Development 2003;130:2263-73. https://doi.org/10.1242/dev.00431
  33. Jerome‐Majewska LA, Jenkins GP, Ernstoff E, Zindy F, Sherr CJ, Papaioannou VE. Tbx3, the ulnar‐mammary syndrome gene, and Tbx2 interact in mammary gland development through a p19Arf/p53‐independent pathway. Dev Dyn 2005;234:922-33. https://doi.org/10.1002/dvdy.20575
  34. Eblaghie MC, Song SJ, Kim JY, Akita K, Tickle C, Jung HS. Interactions between FGF and Wnt signals and Tbx3 gene expression in mammary gland initiation in mouse embryos. J Anat 2004; 205:1-13. https://doi.org/10.1111/j.0021-8782.2004.00309.x
  35. Rapini RP, Bolognia J, Jorizzo J. Dermatology, 2-Volume Set. St. Louis: Mosby, 2007: ISBN 1-4160-2999-0.
  36. Klopocki E, Neumann LM, Tonnies H, Ropers H-H, Mundlos S, Ullmann R. Ulnar-mammary syndrome with dysmorphic facies and mental retardation caused by a novel 1.28 Mb deletion encompassing the TBX3 gene. Eur J Hum Genet 2006;14:1274-9. https://doi.org/10.1038/sj.ejhg.5201696
  37. Mikawa S, Sato S, Nii M, et al. Identification of a second gene associated with variation in vertebral number in domestic pigs. BMC Genet 2011;12:5.
  38. Fan Y, Xing Y, Zhang Z, et al. A further look at porcine chromosome 7 reveals VRTN variants associated with vertebral number in Chinese and Western pigs. PloS one 2013;8:e62534. https://doi.org/10.1371/journal.pone.0062534
  39. Yang J, Huang L, Yang M, et al. Possible introgression of the VRTN mutation increasing vertebral number, carcass length and teat number from Chinese pigs into European pigs. Sci Rep 2016;6.

Cited by

  1. Genotyping by sequencing reveals a new locus for pig teat number vol.48, pp.4, 2017, https://doi.org/10.1111/age.12547
  2. A QTL for Number of Teats Shows Breed Specific Effects on Number of Vertebrae in Pigs: Bridging the Gap Between Molecular and Quantitative Genetics vol.10, pp.None, 2017, https://doi.org/10.3389/fgene.2019.00272
  3. Mitigating the effects of drought on cattle production in communal rangelands of Zimbabwe vol.52, pp.1, 2020, https://doi.org/10.1007/s11250-019-02020-y
  4. Revealing New Candidate Genes for Teat Number Relevant Traits in Duroc Pigs Using Genome-Wide Association Studies vol.11, pp.3, 2017, https://doi.org/10.3390/ani11030806
  5. A genome‐wide association study for the number of teats in European rabbits (Oryctolagus cuniculus) identifies several candidate genes affecting this trait vol.52, pp.2, 2021, https://doi.org/10.1111/age.13036
  6. Single‐marker and haplotype‐based genome‐wide association studies for the number of teats in two heavy pig breeds vol.52, pp.4, 2017, https://doi.org/10.1111/age.13095
  7. Genome scanning reveals novel candidate genes for vertebral and teat number in the Beijing Black Pig vol.52, pp.5, 2021, https://doi.org/10.1111/age.13111