Genome-wide association study of the backfat thickness trait in two pig populations
Dandan ZHU, Xiaolei LIU, Rothschild MAX, Zhiwu ZHANG, Shuhong ZHAO, Bin FAN
Genome-wide association study of the backfat thickness trait in two pig populations
Backfat thickness is a good predictor of carcass lean content, an economically important trait, and a main breeding target in pig improvement. In this study, the candidate genes and genomic regions associated with the tenth rib backfat thickness trait were identified in two independent pig populations, using a genome-wide association study of porcine 60K SNP genotype data applying the compressed mixed linear model (CMLM) statistical method. For each population, 30 most significant single-nucleotide polymorphisms (SNPs) were selected and SNP annotation implemented using Sus scrofa Build 10.2. In the first population, 25 significant SNPs were distributed on seven chromosomes, and SNPs on SSC1 and SSC7 showed great significance for fat deposition. The most significant SNP (ALGA0006623) was located on SSC1, upstream of the MC4R gene. In the second population, 27 significant SNPs were recognized by annotation, and 12 SNPs on SSC12 were related to fat deposition. Two haplotype blocks, M1GA0016251-MARC0075799 and ALGA0065251-MARC0014203-M1GA0016298-ALGA0065308, were detected in significant regions where the PIPNC1 and GH1 genes were identified as contributing to fat metabolism. The results indicated that genetic mechanism regulating backfat thickness is complex, and that genome-wide associations can be affected by populations with different genetic backgrounds.
backfat thickness / SNP chip / genome-wide association study / compressed mixed linear model / pig
[1] |
Kim K S, Larsen N, Short T, Plastow G, Rothschild M F. A missense variant of the porcine melanocortin-4 receptor (MC4R) gene is associated with fatness, growth, and feed intake traits. Mammalian Genome, 2000, 11(2): 131–135
CrossRef
Pubmed
Google scholar
|
[2] |
Fan B, Du Z Q, Rothschild M F. The fat mass and obesity-associated (FTO) gene is associated with intramuscular fat content and growth rate in the pig. Animal Biotechnology, 2009, 20(2): 58–70
CrossRef
Pubmed
Google scholar
|
[3] |
Bidanel J P, Milan D, Iannuccelli N, Amigues Y, Boscher M Y, Bourgeois F, Caritez J C, Gruand J, Le Roy P, Lagant H, Quintanilla R, Renard C, Gellin J, Ollivier L, Chevalet C. Detection of quantitative trait loci for growth and fatness in pigs. Genetics Selection Evolution, 2001, 33(3): 289–309
CrossRef
Pubmed
Google scholar
|
[4] |
Malek M, Dekkers J C, Lee H K, Baas T J, Rothschild M F. A molecular genome scan analysis to identify chromosomal regions influencing economic traits in the pig. I. Growth and body composition. Mammalian Genome, 2001, 12(8): 630–636
CrossRef
Pubmed
Google scholar
|
[5] |
Ramos A M, Crooijmans R P, Affara N A, Amaral A J, Archibald A L, Beever J E, Bendixen C, Churcher C, Clark R, Dehais P, Hansen M S, Hedegaard J, Hu Z L, Kerstens H H, Law A S, Megens H J, Milan D, Nonneman D J, Rohrer G A, Rothschild M F, Smith T P, Schnabel R D, Van Tassell C P, Taylor J F, Wiedmann R T, Schook L B, Groenen M A. 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(8): e6524
CrossRef
Pubmed
Google scholar
|
[6] |
Do D N, Ostersen T, Strathe A B, Mark T, Jensen J, Kadarmideen H N. Genome-wide association and systems genetic analyses of residual feed intake, daily feed consumption, backfat and weight gain in pigs. BMC Genetics, 2014, 15(1): 27
CrossRef
Pubmed
Google scholar
|
[7] |
Fan B, Onteru S K, Du Z Q, Garrick D J, Stalder K J, Rothschild M F. Genome-wide association study identifies Loci for body composition and structural soundness traits in pigs. PLoS ONE, 2011, 6(2): e14726
CrossRef
Pubmed
Google scholar
|
[8] |
Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira M A, Bender D, Maller J, Sklar P, de Bakker P I, Daly M J, Sham P C. PLINK: a tool set for whole-genome association and population-based linkage analyses. American Journal of Human Genetics, 2007, 81(3): 559–575
CrossRef
Pubmed
Google scholar
|
[9] |
Zhang Z, Ersoz E, Lai C Q, Todhunter R J, Tiwari H K, Gore M A, Bradbury P J, Yu J, Arnett D K, Ordovas J M, Buckler E S. Mixed linear model approach adapted for genome-wide association studies. Nature Genetics, 2010, 42(4): 355–360
CrossRef
Pubmed
Google scholar
|
[10] |
Pearson T A, Manolio T A. How to interpret a genome-wide association study. The Journal of the American Medical Association, 2008, 299(11): 1335–1344
CrossRef
Pubmed
Google scholar
|
[11] |
Barrett J C, Fry B, Maller J, Daly M J. Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics, 2005, 21(2): 263–265
CrossRef
Pubmed
Google scholar
|
[12] |
Li M, Wu H, Luo Z, Xia Y, Guan J, Wang T, Gu Y, Chen L, Zhang K, Ma J, Liu Y, Zhong Z, Nie J, Zhou S, Mu Z, Wang X, Qu J, Jing L, Wang H, Huang S, Yi N, Wang Z, Xi D, Wang J, Yin G, Wang L, Li N, Jiang Z, Lang Q, Xiao H, Jiang A, Zhu L, Jiang Y, Tang G, Mai M, Shuai S, Li N, Li K, Wang J, Zhang X, Li Y, Chen H, Gao X, Plastow G S, Beck S, Yang H, Wang J, Wang J, Li X, Li R. An atlas of DNA methylomes in porcine adipose and muscle tissues. Nature Communications, 2012, 3: 850
CrossRef
Pubmed
Google scholar
|
[13] |
Yue G, Stratil A, Cepica S, Schröffel JJr, Schröffelova D, Fontanesi L, Cagnazzo M, Moser G, Bartenschlager H, Reiner G, Geldermann H. Linkage and QTL mapping for Sus scrofa chromosome 7. Journal of Animal Breeding and Genetics, 2003, 120(s1): 56–65
CrossRef
Google scholar
|
[14] |
Muñoz M, Alves E, Corominas J, Folch J M, Casellas J, Noguera J L, Silió L, Fernández A I. Survey of SSC12 regions affecting fatty acid composition of intramuscular fat using high-density SNP data. Frontiers in Genetics, 2011, 2: 101
Pubmed
|
[15] |
Wabitsch M. Overweight and obesity in European children: definition and diagnostic procedures, risk factors and consequences forlater health outcome. European Journal of Pediatrics, 2000, 159(S1): S8–S13
CrossRef
Pubmed
Google scholar
|
/
〈 | 〉 |