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A genome-wide association study of reproduction traits in four pig populations with different genetic backgrounds

  • Jiang, Yao (National Engineering Laboratory for Animal Breeding, Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture, College of Animal Science and Technology, China Agricultural University) ;
  • Tang, Shaoqing (Beijing Station of Animal Husbandry) ;
  • Xiao, Wei (Beijing Station of Animal Husbandry) ;
  • Yun, Peng (Beijing Station of Animal Husbandry) ;
  • Ding, Xiangdong (National Engineering Laboratory for Animal Breeding, Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture, College of Animal Science and Technology, China Agricultural University)
  • Received : 2019.05.26
  • Accepted : 2019.09.03
  • Published : 2020.09.01

Abstract

Objective: Genome-wide association study and two meta-analysis based on GWAS performed to explore the genetic mechanism underlying variation in pig number born alive (NBA) and total number born (TNB). Methods: Single trait GWAS and two meta-analysis (single-trait meta analysis and multi-trait meta analysis) were used in our study for NBA and TNB on 3,121 Yorkshires from 4 populations, including three different American Yorkshire populations (n = 2,247) and one British Yorkshire populations (n = 874). Results: The result of single trait GWAS showed that no significant associated single nucleotide polymorphisms (SNPs) were identified. Using single-trait meta analysis and multi-trait meta analysis within populations, 11 significant loci were identified associated with target traits. Spindlin 1, vascular endothelial growth factor A, forkhead box Q1, msh homeobox 1, and LHFPL tetraspan submily member 3 are five functionally plausible candidate genes for NBA and TNB. Compared to the single population GWAS, single-trait Meta analysis can improve the detection power to identify SNPs by integrating information of multiple populations. The multiple-trait analysis reduced the power to detect trait-specific loci but enhanced the power to identify the common loci across traits. Conclusion: In total, our findings identified novel genes to be validated as candidates for NBA and TNB in pigs. Also, it enabled us to enlarge population size by including multiple populations with different genetic backgrounds and increase the power of GWAS by using meta analysis.

Keywords

References

  1. Zhang LC, Yue JW, Pu L, et al. Genome-wide study refines the quantitative trait locus for number of ribs in a Large White x Minzhu intercross pig population and reveals a new candidate gene. Mol Genet Genomics 2016;291:1885-90. https://doi.org/10.1007/s00438-016-1220-1
  2. Rothschild M, Jacobson C, Vaske D, et al. The estrogen receptor locus is associated with a major gene influencing litter size in pigs. Proc Natl Acad Sci USA 1996;93:201-5. https://doi.org/10.1073/pnas.93.1.201
  3. Fangmann A, Sharifi RA, Heinkel J, et al. Empirical comparison between different methods for genomic prediction of number of piglets born alive in moderate sized breeding populations. J Anim Sci 2017;95:1434-43. https://doi.org/10.2527/jas.2016.0991
  4. Wu P, Wang K, Yang Q, et al. Identifying SNPs and candidate genes for three litter traits using single-step GWAS across six parities in Landrace and Large White pigs. Physiol Genomics 2018;50:1026-35. https://doi.org/10.1152/physiolgenomics.00071.2018
  5. Suwannasing R, Duangjinda M, Boonkum W, Taharnklaew R, Tuangsithtanon K. The identification of novel regions for reproduction trait in Landrace and Large White pigs using a single step genome-wide association study. Asian-Australas J Anim Sci 2018;31:1852-62. https://doi.org/10.5713/ajas.18.0072
  6. Hong JK, Jeong YD, Cho ES, et al. A genome-wide association study of social genetic effects in Landrace pigs. Asian-Australas J Anim Sci 2018;31:784-90. https://doi.org/10.5713/ajas.17.0440
  7. Lee T, Shin DH, Cho S, et al. Genome-wide association study of integrated meat quality-related traits of the duroc pig breed. Asian-Australas J Anim Sci 2014;27:303-9. https://doi.org/10.5713/ajas.2013.13385
  8. Wang J, Yuan X, Ye S, et al. Genome wide association study on feed conversion ratio using imputed sequence data in chickens. Asian-Australas J Anim Sci 2019;32:494-500. https://doi.org/10.5713/ajas.18.0319
  9. Guo X, Su G, Christensen OF, Janss L, Lund MS. Genomewide association analyses using a Bayesian approach for litter size and piglet mortality in Danish Landrace and Yorkshire pigs. BMC Genomics 2016;17:468. https://doi.org/10.1186/s12864-016-2806-z
  10. Wang C, Wang H, Zhang Y, Tang Z, Li K, Liu B. Genome-wide analysis reveals artificial selection on coat colour and reproductive traits in Chinese domestic pigs. Mol Ecol Resour 2014;15:414-24. https://doi.org/10.1111/1755-0998.12311
  11. MariaMunoz, Fernandez AI, Ovilo C, et al. Non-additive effects of RBP4, ESR1 and IGF2 polymorphisms on litter size at different parities in a Chinese-European porcine line. Genet Sel Evol 2010;42:23. https://doi.org/10.1186/1297-9686-42-23
  12. Bosse M, Megens HJ, Frantz LA, et al. Genomic analysis reveals selection for Asian genes in European pigs following human-mediated introgression. Nat Commun 2014;5:4392. https://doi.org/10.1038/ncomms5392
  13. Purcell S, Neale B, Todd-Brown K, et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet 2007;81:559-75. https://doi.org/10.1086/519795
  14. Yang J, Lee SH, Goddard ME, Visscher PM. GCTA: a tool for genome-wide complex trait analysis. Am J Hum Genet 2011;88:76-82. https://doi.org/10.1016/j.ajhg.2010.11.011
  15. VanRaden PM. Efficient methods to compute genomic predictions. J Dairy Sci 2008;91:4414-23. https://doi.org/10.3168/jds.2007-0980
  16. Bolormaa S, Pryce JE, Reverter A, et al. A multi-trait, meta-analysis for detecting pleiotropic polymorphisms for stature, fatness and reproduction in beef cattle. PLoS Genetics 2014;10:e1004198. https://doi.org/10.1371/journal.pgen.1004198
  17. Daikoku T, Cha J, Sun X, et al. Conditional deletion of Msx homeobox genes in the uterus inhibits blastocyst implantation by altering uterine receptivity. Dev Cell 2011;21:1014-25. https://doi.org/10.1016/j.devcel.2011.09.010
  18. Nallasamy S, Li Q, Bagchi MK, Bagchi IC. Msx homeobox genes critically regulate embryo implantation by controlling paracrine signaling between uterine stroma and epithelium. PLoS Genet 2012;8:e1002500. https://doi.org/10.1371/journal.pgen.1002500
  19. Cha J, Sun X, Bartos A, et al. A new role for muscle segment homeobox genes in mammalian embryonic diapause. Open Biol 2013;3:130035. https://doi.org/10.1098/rsob.130035
  20. Onteru SK, Fan B, Du ZQ, Garrick DJ, Stalder KJ, Rothschild MF. A whole-genome association study for pig reproductive traits. Anim Genet 2012;43:18-26. https://doi.org/10.1111/j.1365-2052.2011.02213.x
  21. Janecki DM, Sajek M, Smialek MJ, et al. SPIN1 is a proto-oncogene and SPIN3 is a tumor suppressor in human seminoma. Oncotarget 2018;9:32466-77. https://doi.org/10.18632/oncotarget.25977
  22. Choi JW, Zhao MH, Liang S, et al. Spindlin 1 is essential for metaphase II stage maintenance and chromosomal stability in porcine oocytes. Mol Hum Reprod 2017;23:166-76. https://doi.org/10.1093/molehr/gax005
  23. Chen X, Li A, Chen W, Wei J, Fu J, Wang A. Differential gene expression in uterine endometrium during implantation in pigs. Biol Reprod 2015;92:52. https://doi.org/10.1095/biolreprod.114.123075
  24. Sell-Kubiak E, Duijvesteijn N, Lopes MS, et al. Genome-wide association study reveals novel loci for litter size and its variability in a Large White pig population. BMC Genomics 2015;16:1049. https://doi.org/10.1186/s12864-015-2273-y
  25. Ptacek T, Song C, Walker CL, Sell SM. Physical mapping of distinct 7q22 deletions in uterine leiomyoma and analysis of a recently annotated 7q22 candidate gene. Cancer Genet Cytogenet 2007;174:116-20. https://doi.org/10.1016/j.cancergencyto.2006.11.018
  26. Wotton KR, Shimeld SM. Analysis of lamprey clustered Fox genes: insight into Fox gene evolution and expression in vertebrates. Gene 2011;489:30-40. https://doi.org/10.1016/j.gene.2011.08.007
  27. Ogaki S, Harada S, Shiraki N, Kume K, Kume S. An expression profile analysis of ES cell-derived definitive endodermal cells and Pdx1-expressing cells. BMC Dev Biol 2011;11:13. https://doi.org/10.1186/1471-213X-11-13
  28. Tucker G, Price AL, Berger B. Improving the power of GWAS and avoiding confounding from population stratification with PC-select. Genetics 2014;197:1045-9. https://doi.org/10.1534/genetics.114.164285
  29. Price AL, Zaitlen NA, Reich D, Patterson N. New approaches to population stratification in genome-wide association studies. Nat Rev Genet 2010;11:459-63. https://doi.org/10.1038/nrg2813
  30. Janss L, de Los Campos G, Sheehan N, Sorensen D. Inferences from genomic models in stratified populations. Genetics 2012;192:693-704. https://doi.org/10.1534/genetics.112.141143
  31. Qiao R, Gao J, Zhang Z, et al. Genome-wide association analyses reveal significant loci and strong candidate genes for growth and fatness traits in two pig populations. Genet Sel Evol 2015;47:17. https://doi.org/10.1186/s12711-015-0089-5
  32. Willer CJ, Li Y, Abecasis GR. METAL: fast and efficient meta-analysis of genomewide association scans. Bioinformatics 2010;26:2190-1. https://doi.org/10.1093/bioinformatics/btq340
  33. Liu A, Wang Y, Sahana G, et al. Genome-wide Association studies for female fertility traits in Chinese and Nordic Holsteins. Sci Rep 2017;7:8487. https://doi.org/10.1038/s41598-017-09170-9
  34. Evangelou E, Ioannidis JPA. Meta-analysis methods for genomewide association studies and beyond. Nat Rev Genet 2013;14:379-89. https://doi.org/10.1038/nrg3472
  35. Guo Y, Hou L, Zhang X, et al. A meta analysis of genome-wide association studies for limb bone lengths in four pig populations. BMC Genetics 2015;16:95. https://doi.org/10.1186/s12863-015-0257-1
  36. Le TH, Christensen OF, Nielsen B, Sahana G. Genome-wide association study for conformation traits in three Danish pig breeds. Genet Sel Evol 2017;49:12. https://doi.org/10.1186/s12711-017-0289-2
  37. Hoglund JK, Sahana G, Guldbrandtsen B, Lund MS. Validation of associations for female fertility traits in Nordic Holstein, Nordic Red and Jersey dairy cattle. BMC Genetics 2014;15:8. https://doi.org/10.1186/1471-2156-15-8
  38. Minozzi1 G, Lazzari B, Nicolazzi EL, et al. Genome wide analysis of fertility and production traits in Italian Holstein cattle. Plos One 2013;8:e80219. https://doi.org/10.1371/journal.pone.0080219