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A genome scan for selection signatures in Taihu pig breeds using next-generation sequencing

Published online by Cambridge University Press:  10 July 2018

Z. Wang ,
H. Sun ,
Q. Chen ,
X. Zhang ,
Q. Wang  and
Y. Pan
Z. Wang
Affiliation:
Department of Animal Science, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai 200240, PR China Shanghai Key Laboratory of Veterinary Biotechnology, Shanghai 200240, PR China
H. Sun
Affiliation:
Department of Animal Science, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai 200240, PR China Shanghai Key Laboratory of Veterinary Biotechnology, Shanghai 200240, PR China
Q. Chen
Affiliation:
Department of Animal Science, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai 200240, PR China Shanghai Key Laboratory of Veterinary Biotechnology, Shanghai 200240, PR China
X. Zhang
Affiliation:
Department of Animal Science, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai 200240, PR China Shanghai Key Laboratory of Veterinary Biotechnology, Shanghai 200240, PR China
Q. Wang
Affiliation:
Department of Animal Science, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai 200240, PR China Shanghai Key Laboratory of Veterinary Biotechnology, Shanghai 200240, PR China
Y. Pan*
Affiliation:
Department of Animal Science, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai 200240, PR China Shanghai Key Laboratory of Veterinary Biotechnology, Shanghai 200240, PR China
*
†E-mail: panyuchun1963@aliyun.com
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Abstract

Taihu pig breeds are the most prolific breeds of swine in the world, and they also have superior economic traits, including high resistance to disease, superior meat quality, high resistance to crude feed and a docile temperament. The formation of these phenotypic characteristics is largely a result of long-term artificial or natural selection. Therefore, exploring selection signatures in the genomes of the Taihu pigs will help us to identify porcine genes related to productivity traits, disease and behaviour. In this study, we used both intra-population (Relative Extend Haplotype Homozygosity Test (REHH)) and inter-population (the Cross-Population Extend Haplotype Homozygosity Test (XPEHH); F-STATISTICS, FST) methods to detect genomic regions that might be under selection process in Taihu pig breeds. As a result, we found 282 (REHH) and 112 (XPEHH) selection signature candidate regions corresponding to 159.78 Mb (6.15%) and 62.29 Mb (2.40%) genomic regions, respectively. Further investigations of the selection candidate regions revealed that many genes under these genomic regions were related to reproductive traits (such as the TLR9 gene), coat colour (such as the KIT gene) and fat metabolism (such as the CPT1A and MAML3 genes). Furthermore, gene enrichment analyses showed that genes under the selection candidate regions were significantly over-represented in pathways related to diseases, such as autoimmune thyroid and asthma diseases. In conclusion, several candidate genes potentially under positive selection were involved in characteristics of Taihu pig. These results will further allow us to better understand the mechanisms of selection in pig breeding.

Keywords

indigenous pigcommercial pigsingle nucleotide polymorphismhaplotype homozygosity testgene enrichment analyses
Type
Research Article
Information
animal , Volume 13 , Issue 4 , April 2019 , pp. 683 - 693
Copyright
© The Animal Consortium 2018 

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Footnotes

a

These two authors contributed equally to this work.

References

Ai, H, Huang, L and Ren, J 2013. Genetic diversity, linkage disequilibrium and selection signatures in Chinese and Western pigs revealed by genome-wide markers. PLoS One 8, e56001.Google Scholar
Amaral, AJ, Ferretti, L, Megens, HJ, Crooijmans, RP, Nie, H, Ramos-Onsins, SE, Perez-Enciso, M, Schook, LB and Groenen, MA 2011. Genome-wide footprints of pig domestication and selection revealed through massive parallel sequencing of pooled DNA. PLoS One 6, e14782.Google Scholar
Bosse, M, Lopes, MS, Madsen, O, Megens, HJ, Crooijmans, RP, Frantz, LA, Harlizius, B, Bastiaansen, JW and Groenen, MA 2015. Artificial selection on introduced Asian haplotypes shaped the genetic architecture in European commercial pigs. Proceedings of the Royal Society B 282, 20152019.Google Scholar
Chen, K, Baxter, T, Muir, WM, Groenen, MA and Schook, LB 2007. Genetic resources, genome mapping and evolutionary genomics of the pig (Sus scrofa). International Journal of Biological Sciences 3, 153–165.Google Scholar
Chen, Q, Ma, Y, Yang, Y, Chen, Z, Liao, R, Xie, X, Wang, Z, He, P, Tu, Y, Zhang, X, Yang, C, Yang, H, Yu, F, Zheng, Y, Zhang, Z, Wang, Q and Pan, Y 2013. Genotyping by genome reducing and sequencing for outbred animals. PLoS One 8, e67500.Google Scholar
China National Commission of Animal Genetic Resources 2011. Animal genetic resources in China pigs. China Agriculture Press, Beijing.Google Scholar
Dennis, G Jr, Sherman, BT, Hosack, DA, Yang, J, Gao, W, Lane, HC and Lempicki, RA 2003. DAVID: database for annotation, visualization, and integrated discovery. Genome Biology 4, P3.Google Scholar
Do, DN, Strathe, AB, Ostersen, T, Jensen, J, Mark, T and Kadarmideen, HN 2013. Genome-wide association study reveals genetic architecture of eating behavior in pigs and its implications for humans obesity by comparative mapping. PLoS One 8, e71509.Google Scholar
Donnelly, MP, Paschou, P, Grigorenko, E, Gurwitz, D, Barta, C, Lu, RB, Zhukova, OV, Kim, JJ, Siniscalco, M, New, M, Li, H, Kajuna, SLB, Manolopoulos, VG, Speed, WC, Pakstis, AJ, Kidd, JR and Kidd, KK 2012. A global view of the OCA2-HERC2 region and pigmentation. Human Genetics 131, 683–696.Google Scholar
Herrero-Medrano, JM, Megens, HJ, Groenen, MAM, Bosse, M, Perez-Enciso, M and Crooijmans, RPMA 2014. Whole-genome sequence analysis reveals differences in population management and selection of European low-input pig breeds. BMC Genomics 15, 601.Google Scholar
Jung, EJ, Park, HB, Lee, JB, Yoo, CK, Kim, BM, Kim, HI, Kim, BW and Lim, HT 2014. Genome-wide association analysis identifies quantitative trait loci for growth in a Landrace purebred population. Animal Genetics 45, 442–444.Google Scholar
Larson, G, Albarella, U, Dobney, K, Rowley-Conwy, P, Schibler, J, Tresset, A, Vigne, JD, Edwards, CJ, Schlumbaum, A, Dinu, A, Balacsescu, A, Dolman, G, Tagliacozzo, A, Manaseryan, N, Miracle, P, Van Wijngaarden-Bakker, L, Masseti, M, Bradley, DG and Cooper, A 2007. Ancient DNA, pig domestication, and the spread of the Neolithic into Europe. Proceedings of the National Academy of Sciences of the United States of America 104, 15276–15281.Google Scholar
Li, C, Sun, D, Zhang, S, Wang, S, Wu, X, Zhang, Q, Liu, L, Li, Y and Qiao, L 2014. Genome wide association study identifies 20 novel promising genes associated with milk fatty acid traits in Chinese Holstein. PLoS One 9, e96186.Google Scholar
Li, H and Durbin, R 2009. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 25, 1754–1760.Google Scholar
Li, H, Handsaker, B, Wysoker, A, Fennell, T, Ruan, J, Homer, N, Marth, G, Abecasis, G and Durbin, R, and Genome Project Data Processing S 2009. The Sequence Alignment/Map format and SAMtools. Bioinformatics 25, 2078–2079.Google Scholar
Lin, X, Shim, K and Odle, J 2010. Carnitine palmitoyltransferase I control of acetogenesis, the major pathway of fatty acid {beta}-oxidation in liver of neonatal swine. American Journal of Physiology-Regulatory Integrative and Comparative Physiology 298, R1435–1443.Google Scholar
Ma, Y, Wei, J, Zhang, Q, Chen, L, Wang, J, Liu, J and Ding, X 2015. A genome scan for selection signatures in pigs. PLoS One 10, e0116850.Google Scholar
Mayer, M, Bercsenyi, K, Geczi, K, Szabo, G and Lele, Z 2010. Expression of two type II cadherins, Cdh12 and Cdh22 in the developing and adult mouse brain. Gene Expression Patterns 10, 351–360.Google Scholar
Megens, HJ, Crooijmans, RP, San Cristobal, M, Hui, X, Li, N and Groenen, MA 2008. Biodiversity of pig breeds from China and Europe estimated from pooled DNA samples: differences in microsatellite variation between two areas of domestication. Genetics Selection Evolution 40, 103–128.Google Scholar
Melo, C, Gallardo, D, Quintanilla, R, Zidi, A, Castello, A, Diaz, I, Amills, M and Pena, RN 2013. An association analysis between polymorphisms of the pig solute carrier family 27A (SLC27A), member 1 and 4 genes and serum and muscle lipid traits. Livestock Science 152, 143–146.Google Scholar
Merks, JW, Mathur, PK and Knol, EF 2012. New phenotypes for new breeding goals in pigs. Animal 6, 535–543.Google Scholar
Oczkowicz, M, Ropka-Molik, K and Tyra, M 2013. Analysis of the associations between polymorphisms in GNAS complex locus and growth, carcass and meat quality traits in pigs. Molecular Biology Reports 40, 6419–6427.Google Scholar
Oleksyk, TK, Smith, MW and O’Brien, SJ 2010. Genome-wide scans for footprints of natural selection. Philosophical Transactions of the Royal Society of London Series B-Biological Sciences 365, 185–205.Google Scholar
Onteru, SK, Gorbach, DM, Young, JM, Garrick, DJ, Dekkers, JC and Rothschild, MF 2013. Whole genome association studies of residual feed intake and related traits in the pig. Plos One 8, e61756.Google Scholar
Pickrell, JK, Coop, G, Novembre, J, Kudaravalli, S, Li, JZ, Absher, D, Srinivasan, BS, Barsh, GS, Myers, RM, Feldman, MW and Pritchard, JK 2009. Signals of recent positive selection in a worldwide sample of human populations. Genome Research 19, 826–837.Google Scholar
Pierzchala, M, Pareek, CS, Urbanski, P, Goluch, D, Kamyczek, M, Rozycki, M, Smoczynski, R, Horbanczuk, JO and Kuryl, J 2012. Study of the differential transcription in liver of growth hormone receptor (GHR), insulin-like growth factors (IGF1, IGF2) and insulin-like growth factor receptor (IGF1R) genes at different postnatal developmental ages in pig breeds. Molecular Biology Reports 39, 3055–3066.Google Scholar
Revilla, M, Ramayo-Caldas, Y, Castello, A, Corominas, J, Puig-Oliveras, A, Ibanez-Escriche, N, Munoz, M, Ballester, M and Folch, JM 2014. New insight into the SSC8 genetic determination of fatty acid composition in pigs. Genetics Selection Evolution 46, 28.Google Scholar
Rubin, CJ, Megens, HJ, Martinez Barrio, A, Maqbool, K, Sayyab, S, Schwochow, D, Wang, C, Carlborg, O, Jern, P, Jorgensen, CB, Archibald, AL, Fredholm, M, Groenen, MA and Andersson, L 2012. Strong signatures of selection in the domestic pig genome. Proceedings of the National Academy of Sciences of the United States of America 109, 19529–19536.Google Scholar
Sabeti, PC, Reich, DE, Higgins, JM, Levine, HZ, Richter, DJ, Schaffner, SF, Gabriel, SB, Platko, JV, Patterson, NJ, McDonald, GJ, Ackerman, HC, Campbell, SJ, Altshuler, D, Cooper, R, Kwiatkowski, D, Ward, R and Lander, ES 2002. Detecting recent positive selection in the human genome from haplotype structure. Nature 419, 832–837.Google Scholar
Sabeti, PC, Varilly, P, Fry, B, Lohmueller, J, Hostetter, E, Cotsapas, C, Xie, X, Byrne, EH, McCarroll, SA, Gaudet, R, Schaffner, SF and Lander, ES, International HapMap C, Frazer, KA, Ballinger, DG, Cox, DR, Hinds, DA, Stuve, LL, Gibbs, RA, Belmont, JW, Boudreau, A, Hardenbol, P, Leal, SM, Pasternak, S, Wheeler, DA, Willis, TD, Yu, F, Yang, H, Zeng, C, Gao, Y, Hu, H, Hu, W, Li, C, Lin, W, Liu, S, Pan, H, Tang, X, Wang, J, Wang, W, Yu, J, Zhang, B, Zhang, Q, Zhao, H, Zhao, H, Zhou, J, Gabriel, SB, Barry, R, Blumenstiel, B, Camargo, A, Defelice, M, Faggart, M, Goyette, M, Gupta, S, Moore, J, Nguyen, H, Onofrio, RC, Parkin, M, Roy, J, Stahl, E, Winchester, E, Ziaugra, L, Altshuler, D, Shen, Y, Yao, Z, Huang, W, Chu, X, He, Y, Jin, L, Liu, Y, Shen, Y, Sun, W, Wang, H, Wang, Y, Wang, Y, Xiong, X, Xu, L, Waye, MM, Tsui, SK, Xue, H, Wong, JT, Galver, LM, Fan, JB, Gunderson, K, Murray, SS, Oliphant, AR, Chee, MS, Montpetit, A, Chagnon, F, Ferretti, V, Leboeuf, M, Olivier, JF, Phillips, MS, Roumy, S, Sallee, C, Verner, A, Hudson, TJ, Kwok, PY, Cai, D, Koboldt, DC, Miller, RD, Pawlikowska, L, Taillon-Miller, P, Xiao, M, Tsui, LC, Mak, W, Song, YQ, Tam, PK, Nakamura, Y, Kawaguchi, T, Kitamoto, T, Morizono, T, Nagashima, A, Ohnishi, Y, Sekine, A, Tanaka, T, Tsunoda, T, Deloukas, P, Bird, CP, Delgado, M, Dermitzakis, ET, Gwilliam, R, Hunt, S, Morrison, J, Powell, D, Stranger, BE, Whittaker, P, Bentley, DR, Daly, MJ, de Bakker, PI, Barrett, J, Chretien, YR, Maller, J, McCarroll, S, Patterson, N, Pe’er, I, Price, A, Purcell, S, Richter, DJ, Sabeti, P, Saxena, R, Schaffner, SF, Sham, PC, Varilly, P, Altshuler, D, Stein, LD, Krishnan, L, Smith, AV, Tello-Ruiz, MK, Thorisson, GA, Chakravarti, A, Chen, PE, Cutler, DJ, Kashuk, CS, Lin, S, Abecasis, GR, Guan, W, Li, Y, Munro, HM, Qin, ZS, Thomas, DJ, McVean, G, Auton, A, Bottolo, L, Cardin, N, Eyheramendy, S, Freeman, C, Marchini, J, Myers, S, Spencer, C, Stephens, M, Donnelly, P, Cardon, LR, Clarke, G, Evans, DM, Morris, AP, Weir, BS, Tsunoda, T, Johnson, TA, Mullikin, JC, Sherry, ST, Feolo, M, Skol, A, Zhang, H, Zeng, C, Zhao, H, Matsuda, I, Fukushima, Y, Macer, DR, Suda, E, Rotimi, CN, Adebamowo, CA, Ajayi, I, Aniagwu, T, Marshall, PA, Nkwodimmah, C, Royal, CD, Leppert, MF, Dixon, M, Peiffer, A, Qiu, R, Kent, A, Kato, K, Niikawa, N, Adewole, IF, Knoppers, BM, Foster, MW, Clayton, EW, Watkin, J, Gibbs, RA, Belmont, JW, Muzny, D, Nazareth, L, Sodergren, E, Weinstock, GM, Wheeler, DA, Yakub, I, Gabriel, SB, Onofrio, RC, Richter, DJ, Ziaugra, L, Birren, BW, Daly, MJ, Altshuler, D, Wilson, RK, Fulton, LL, Rogers, J, Burton, J, Carter, NP, Clee, CM, Griffiths, M, Jones, MC, McLay, K, Plumb, RW, Ross, MT, Sims, SK, Willey, DL, Chen, Z, Han, H, Kang, L, Godbout, M, Wallenburg, JC, L’Archeveque, P, Bellemare, G, Saeki, K, Wang, H, An, D, Fu, H, Li, Q, Wang, Z, Wang, R, Holden, AL, Brooks, LD, McEwen, JE, Guyer, MS, Wang, VO, Peterson, JL, Shi, M, Spiegel, J, Sung, LM, Zacharia, LF, Collins, FS, Kennedy, K, Jamieson, R and Stewart, J 2007. Genome-wide detection and characterization of positive selection in human populations. Nature 449, 913–918.Google Scholar
Scheet, P and Stephens, M 2006. A fast and flexible statistical model for large-scale population genotype data: applications to inferring missing genotypes and haplotypic phase. American Journal of Human Genetics 78, 629–644.Google Scholar
Suzuki, Y 2010. Statistical methods for detecting natural selection from genomic data. Genes & Genetic Systems 85, 359–376.Google Scholar
Suzuki-Anekoji, M, Suzuki, A, Wu, SW, Angata, K, Murai, KK, Sugihara, K, Akama, TO, Khoo, KH, Nakayama, J, Fukuda, MN and Fukuda, M 2013. In vivo regulation of steroid hormones by the Chst10 sulfotransferase in mouse. Journal of Biological Chemistry 288, 5007–5016.Google Scholar
Vicart, S, Sternberg, D, Fontaine, B and Meola, G 2005. Human skeletal muscle sodium channelopathies. Neurological Sciences 26, 194–202.Google Scholar
Vidal, O, Noguera, JL, Amills, M, Varona, L, Gil, M, Jimenez, N, Davalos, G, Folch, JM and Sanchez, A 2005. Identification of carcass and meat quality quantitative trait loci in a Landrace pig population selected for growth and leanness. Journal of Animal Science 83, 293–300.Google Scholar
Villela, D, Kimura, L, Schlesinger, D, Goncalves, A, Pearson, PL, Suemoto, CK, Pasqualucci, C, Krepischi, AC, Grinberg, LT and Rosenberg, C 2013. Germline DNA copy number variation in individuals with Argyrophilic grain disease reveals CTNS as a plausible candidate gene. Genetics and Molecular Biology 36, 498–501.Google Scholar
Wang, Z, Chen, Q, Liao, R, Zhang, Z, Zhang, X, Liu, X, Zhu, M, Zhang, W, Xue, M, Yang, H, Zheng, Y, Wang, Q and Pan, Y 2016. Genome-wide genetic variation discovery in Chinese Taihu pig breeds using next generation sequencing. Animal Genetics 48, 38–47.Google Scholar
Wang, Z, Chen, Q, Yang, Y, Yang, H, He, P, Zhang, Z, Chen, Z, Liao, R, Tu, Y, Zhang, X, Wang, Q and Pan, Y 2014. A genome-wide scan for selection signatures in Yorkshire and Landrace pigs based on sequencing data. Animal Genetics 45, 808–816.Google Scholar
Weir, BS and Cockerham, CC 1984. Estimating F-statistics for the analysis of population structure. Evolution 38, 1358–1370.Google Scholar
Wuyts, W, Spieker, N, Van Roy, N, De Boulle, K, De Paepe, A, Willems, PJ, Van Hul, W, Versteeg, R and Speleman, F 1999. Refined physical mapping and genomic structure of the EXTL1 gene. Cytogenetics and Cell Genetics 86, 267–270.Google Scholar
Yang, Y, Wang, Q, Chen, Q, Liao, R, Zhang, X, Yang, H, Zheng, Y, Zhang, Z and Pan, Y 2014. A new genotype imputation method with tolerance to high missing rate and rare variants. Plos One 9, e101025.Google Scholar
Zhang, LC, Yue, JW, Pu, L, Wang, LG, Liu, X, Liang, J, Yan, H, Zhao, KB, Li, N, Shi, HB, Zhang, YB and Wang, LX 2016. 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. Molecular Genetics and Genomics 291, 1885–1890.Google Scholar
Zhang, Z, Wang, Z, Yang, Y, Zhao, J, Chen, Q, Liao, R, Chen, Z, Zhang, X, Xue, M, Yang, H, Zheng, Y, Wang, Q and Pan, Y 2016. Identification of pleiotropic genes and gene sets underlying growth and immunity traits: a case study on Meishan pigs. Animal 10, 550–557.Google Scholar
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