Abstract
Pigs share numerous physiological and phenotypic similarities with human and thus have been considered as a good model in nonrodent mammals for the study of genetic basis of human obesity. Researches on candidate genes for obesity traits have successfully identified some common genes between humans and pigs. However, few studies have assessed how many similarities exist between the genetic architecture of obesity in pigs and humans by large-scale comparative genomics. Here, we performed a genome-wide association study (GWAS) using the porcine 60 K SNP Beadchip for BMI and other four conformation traits at three different ages in a Chinese Laiwu pig population, which shows a large variability in fat deposition. In total, 35 SNPs were found to be significant at Bonferroni-corrected 5 % chromosome-wise level (P = 2.13 × 10−5) and 88 SNPs had suggestive (P < 10−4) association with the conformation traits. Some SNPs showed age-dependent association. Intriguingly, out of 32 regions associated with BMI in pigs, 18 were homologous with the loci for BMI in humans. Furthermore, five closest genes to GWAS peaks including HIF1AN, SMYD3, COX10, SLMAP, and GBE1 have been already associated with BMI in humans, which makes them very promising candidates for these QTLs. The result of GO analysis provided strong support to the fact that mitochondria and synapse play important roles in obesity susceptibility, which is consistent with previous findings on human obesity, and it also implicated new gene sets related to chromatin modification and Ig-like C2-type 5 domain. Therefore, these results not only provide new insights into the genetic architecture of BMI in pigs but also highlight that humans and pigs share the significant overlap of obesity-related genes.
Similar content being viewed by others
References
Ai H, Huang L, Ren J (2013) Genetic diversity, linkage disequilibrium and selection signatures in chinese and Western pigs revealed by genome-wide SNP markers. PLoS One 8:e56001
Allen HL, Estrada K, Lettre G, Berndt SI, Weedon MN, Rivadeneira F, Willer CJ, Jackson AU, Vedantam S, Raychaudhuri S (2010) Hundreds of variants clustered in genomic loci and biological pathways affect human height. Nature 467:832–838
Andersson L, Haley CS, Ellegren H, Knott SA, Johansson M, Andersson K, Andersson-Eklund L, Edfors-Lilja I, Fredholm M, Hansson I (1994) Genetic mapping of quantitative trait loci for growth and fatness in pigs. Science 263:1771–1774
Aulchenko YS, Ripke S, Isaacs A, van Duijn CM (2007) GenABEL: an R library for genome-wide association analysis. Bioinformatics 23:1294–1296
Barrett JC, Fry B, Maller J, Daly MJ (2005) Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics 21:263–265
Berg F, Stern S, Andersson K, Andersson L, Moller M (2006) Refined localization of the FAT1 quantitative trait locus on pig chromosome 4 by marker-assisted backcrossing. BMC Genet 7:17
Comuzzie AG, Cole SA, Laston SL, Voruganti VS, Haack K, Gibbs RA, Butte NF (2012) Novel genetic loci identified for the pathophysiology of childhood obesity in the Hispanic population. PLoS One 7:e51954
Do DN, Strathe AB, Ostersen T, Jensen J, Mark T, 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
Dvořáková V, Bartenschlager H, Stratil A, Horák P, Stupka R, Čítek J, Šprysl M, Hrdlicová A, Geldermann H (2012) Association between polymorphism in the FTO gene and growth and carcass traits in pig crosses. Genet Sel Evol 44:1–8
Elks CE, den Hoed M, Zhao JH, Sharp SJ, Wareham NJ, Loos RJ, Ong KK (2012) Variability in the heritability of body mass index: a systematic review and meta-regression. Front Endocrinol 3:29
Fall T, Ingelsson E (2014) Genome-wide association studies of obesity and metabolic syndrome. Mol Cell Endocrinol 382:740–757
Farquharson C, Ahmed SF (2013) Inflammation and linear bone growth: the inhibitory role of SOCS2 on GH/IGF-1 signaling. Pediatr Nephrol 28:547–556
Fontanesi L, Schiavo G, Galimberti G, Calo DG, Scotti E, Martelli PL, Buttazzoni L, Casadio R, Russo V (2012) A genome wide association study for backfat thickness in Italian Large White pigs highlights new regions affecting fat deposition including neuronal genes. BMC Genom 13:583
Fox CS, Liu Y, White CC, Feitosa M, Smith AV, Heard-Costa N, Lohman K, Johnson AD, Foster MC, Greenawalt DM (2012) Genome-wide association for abdominal subcutaneous and visceral adipose reveals a novel locus for visceral fat in women. PLoS Genet 8:e1002695
Groenen MA, Archibald AL, Uenishi H, Tuggle CK, Takeuchi Y, Rothschild MF, Rogel-Gaillard C, Park C, Milan D, Megens H-J (2012) Analyses of pig genomes provide insight into porcine demography and evolution. Nature 491:393–398
Hayes MG, Pluzhnikov A, Miyake K, Sun Y, Ng MC, Roe CA, Below JE, Nicolae RI, Konkashbaev A, Bell GI (2007) Identification of type 2 diabetes genes in Mexican Americans through genome-wide association studies. Diabetes 56:3033–3044
Hellemans J, Simon M, Dheedene A, Alanay Y, Mihci E, Rifai L, Sefiani A, van Bever Y, Meradji M, Superti-Furga A, Mortier G (2009) Homozygous inactivating mutations in the NKX3-2 gene result in spondylo-megaepiphyseal-metaphyseal dysplasia. Am J Hum Genet 85:916–922
Huang DW, Sherman BT, Lempicki RA (2008) Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc 4:44–57
Kessler K, Pivovarova O, Pfeiffer A (2014) Circadian clocks and energy metabolism: implications for health. Dtsch med Wochenschr 139:684–686
Keys A, Fidanza F, Karvonen MJ, Kimura N, Taylor HL (1972) Indices of relative weight and obesity. J chron dis 25:329–343
Kim KS, Thomsen H, Bastiaansen J, Nguyen NT, Dekkers JC, Plastow GS, Rothschild MF (2004) Investigation of obesity candidate genes on porcine fat deposition quantitative trait loci regions. Obes Res 12:1981–1994
Kobayashi M, Ohno T, Ihara K, Murai A, Kumazawa M, Hoshino H, Iwanaga K, Iwai H, Hamana Y, Ito M, Ohno K, Horio F (2014) Searching for genomic region of high-fat diet-induced type 2 diabetes in mouse chromosome 2 by analysis of congenic strains. PLoS One 9:e96271
Kogelman LJ, Kadarmideen HN, Mark T, Karlskov-Mortensen P, Bruun CS, Cirera S, Jacobsen MJ, Jorgensen CB, Fredholm M (2013) An f2 pig resource population as a model for genetic studies of obesity and obesity-related diseases in humans: design and genetic parameters. Front genet 4:29
Koopmans SJ, Schuurman T (2015) Considerations on pig models for appetite, metabolic syndrome and obese type 2 diabetes: from food intake to metabolic disease. Eur J Pharmacol 759:231–239
Lettice LA, Purdie LA, Carlson GJ, Kilanowski F, Dorin J, Hill RE (1999) The mouse bagpipe gene controls development of axial skeleton, skull, and spleen. Proc Natl Acad Sci USA 96:9695–9700
Locke AE, Kahali B, Berndt SI, Justice AE, Pers TH, Day FR, Powell C, Vedantam S, Buchkovich ML, Yang J et al (2015) Genetic studies of body mass index yield new insights for obesity biology. Nature 518:197–206
Ma J, Ren J, Guo Y, Duan Y, Ding N, Zhou L, Li L, Yan X, Yang K, Huang L, Song Y, Xie J, Milan D, Huang L (2009) Genome-wide identification of quantitative trait loci for carcass composition and meat quality in a large-scale White Duroc x Chinese Erhualian resource population. Anim Genet 40:637–647
Marklund L, Nyström P-E, Stern S, Andersson-Eklund L, Andersson L (1999) Confirmed quantitative trait loci for fatness and growth on pig chromosome 4. Heredity 82:134–141
Melka MG, Bernard M, Mahboubi A, Abrahamowicz M, Paterson AD, Syme C, Lourdusamy A, Schumann G, Leonard GT, Perron M (2011) Genome-wide scan for loci of adolescent obesity and their relationship with blood pressure. J Clin Endocrinol Metabol 97:E145–E150
Okut H, Gianola D, Rosa GJ, Weigel KA (2011) Prediction of body mass index in mice using dense molecular markers and a regularized neural network. Genet Res 93:189–201
Pant SD, Karlskov-Mortensen P, Jacobsen MJ, Cirera S, Kogelman LJ, Bruun CS, Mark T, Jorgensen CB, Grarup N, Appel EV, Galjatovic EA, Hansen T, Pedersen O, Guerin M, Huby T, Lesnik P, Meuwissen TH, Kadarmideen HN, Fredholm M (2015) Comparative analyses of QTLs influencing obesity and metabolic phenotypes in pigs and humans. PLoS One 10:e0137356
Pearson T, Manolio T (2008) How to interpret a genome-wide association study. JAMA 299:1335–1344
Provot S, Kempf H, Murtaugh LC, Chung UI, Kim DW, Chyung J, Kronenberg HM, Lassar AB (2006) Nkx3.2/Bapx1 acts as a negative regulator of chondrocyte maturation. Development 133:651–662
Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MA, Bender D, Maller J, Sklar P, de Bakker PI, Daly MJ, Sham PC (2007) PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet 81:559–575
Rubin C-J, Megens H-J, Barrio AM, Maqbool K, Sayyab S, Schwochow D, Wang C, Carlborg Ö, Jern P, Jørgensen CB (2012) Strong signatures of selection in the domestic pig genome. Proc Natl Acad Sci USA 109:19529–19536
Sanchez M-P, Tribout T, Iannuccelli N, Bouffaud M, Servin B, Tenghe A, Dehais P, Muller N, Del Schneider MP, Mercat M-J (2014) A genome-wide association study of production traits in a commercial population of Large White pigs: evidence of haplotypes affecting meat quality. Genet Sel Evol 46(10):1186
Soma Y, Uemoto Y, Sato S, Shibata T, Kadowaki H, Kobayashi E, Suzuki K (2011) Genome-wide mapping and identification of new quantitative trait loci affecting meat production, meat quality, and carcass traits within a Duroc purebred population. J Anim Sci 89:601–608
Speliotes EK, Willer CJ, Berndt SI, Monda KL, Thorleifsson G, Jackson AU, Lango Allen H, Lindgren CM, Luan J et al (2010) Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index. Nat Genet 42:937–948
Spurlock ME, Gabler NK (2008) The development of porcine models of obesity and the metabolic syndrome. J Nutr 138:397–402
Vimaleswaran KS, Tachmazidou I, Zhao JH, Hirschhorn JN, Dudbridge F, Loos RJ (2012) Candidate genes for obesity-susceptibility show enriched association within a large genome-wide association study for BMI. Hum Mol Genet 21:4537–4542
Vitarius JA, Sehayek E, Breslow JL (2006) Identification of quantitative trait loci affecting body composition in a mouse intercross. Proc Natl Acad Sci USA 103:19860–19865
Welter D, MacArthur J, Morales J, Burdett T, Hall P, Junkins H, Klemm A, Flicek P, Manolio T, Hindorff L (2014) The NHGRI GWAS catalog, a curated resource of SNP-trait associations. Nucleic Acids Res 42:D1001–D1006
Willer CJ, Speliotes EK, Loos RJ, Li S, Lindgren CM, Heid IM, Berndt SI, Elliott AL, Jackson AU, Lamina C, Lettre G et al (2009) Six new loci associated with body mass index highlight a neuronal influence on body weight regulation. Nat Genet 41:25–34
Xiong X, Liu X, Zhou L, Yang J, Yang B, Ma H, Xie X, Huang Y, Fang S, Xiao S, Ren J, Chen C, Ma J, Huang L (2015a) Genome-wide association analysis reveals genetic loci and candidate genes for meat quality traits in Chinese Laiwu pigs. Mamm genome 26(3-4):181–190
Xiong X, Liu X, Zhou L, Yang J, Yang B, Ma H, Xie X, Huang Y, Fang S, Xiao S, Ren J, Chen C, Ma J, Huang L (2015b) Genome-wide association analysis reveals genetic loci and candidate genes for meat quality traits in Chinese Laiwu pigs. Mamm Genome 26:181–190
Yang Q, Cui J, Chazaro I, Cupples LA, Demissie S (2005) Power and type I error rate of false discovery rate approaches in genome-wide association studies. BMC Genet 6(Suppl 1):S134
Zhang N, Fu Z, Linke S, Chicher J, Gorman JJ, Visk D, Haddad GG, Poellinger L, Peet DJ, Powell F, Johnson RS (2010) The asparaginyl hydroxylase factor inhibiting HIF-1alpha is an essential regulator of metabolism. Cell Metab 11:364–378
Zhang Y, Kent J, Olivier M, Ali O, Broeckel U, Abdou R, Dyer T, Comuzzie A, Curran J, Carless M (2013) QTL-based association analyses reveal novel genes influencing pleiotropy of metabolic syndrome (MetS). Obesity 21:2099–2111
Zhu J, Chen C, Yang B, Guo Y, Ai H, Ren J, Peng Z, Tu Z, Yang X, Meng Q, Friend S, Huang L (2015) A systems genetics study of swine illustrates mechanisms underlying human phenotypic traits. BMC Genom 16:88
Acknowledgments
The study was supported by the Development Programs for Basic Research of China (973 Programs, No. 2014CB160311) and the Key Project of National Nature Science Foundation of China (No. 31230069).
Author information
Authors and Affiliations
Corresponding authors
Ethics declarations
Competing interests
The authors declare that they have no competing interest.
Additional information
Lisheng Zhou and Jiuxiu Ji have contributed equally to this work.
Electronic supplementary material
Below is the link to the electronic supplementary material.
335_2016_9657_MOESM1_ESM.docx
Supplementary material 1 (DOCX 17 kb) Table S1: Correlations of the several relative weight indices with body length and fatness
335_2016_9657_MOESM2_ESM.docx
Supplementary material 2 (DOCX 42 kb) Table S2: Description of SNPs suggestively associated with body conformation traits
335_2016_9657_MOESM4_ESM.tif
Supplementary material 4 (TIFF 4420 kb) Figure S2: Manhattans plots of GWAS for BW_210, BL_210 and CC_210. Description: Chromosomes 1-18 and 19 (X) are shown in different colors. The solid lines indicate the Bonferroni-corrected thresholds of chromosome-wide significance and the dashed lines indicate the thresholds of suggestive significance
335_2016_9657_MOESM5_ESM.tif
Supplementary material 5 (TIFF 5376 kb) Figure S3: Manhattans plots of GWAS for body conformation traits. Description: Chromosomes 1-18 and 19 (X) are shown in different colors. The solid lines indicate the Bonferroni-corrected thresholds of chromosome-wide significance and the dashed lines indicate the thresholds of suggestive significance
335_2016_9657_MOESM6_ESM.tif
Supplementary material 6 (TIFF 111 kb) Figure S4: Extent of LD (predicted r2) as a function of inter-SNP distance in Laiwu pigs
Rights and permissions
About this article
Cite this article
Zhou, L., Ji, J., Peng, S. et al. A GWA study reveals genetic loci for body conformation traits in Chinese Laiwu pigs and its implications for human BMI. Mamm Genome 27, 610–621 (2016). https://doi.org/10.1007/s00335-016-9657-4
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00335-016-9657-4