| 
					
						|  |  
    					|  |  
    					| Genome-wide association study of the backfat thickness trait in two pig populations |  
						| Dandan ZHU1,Xiaolei LIU1,Rothschild MAX2,Zhiwu ZHANG3,Shuhong ZHAO1,Bin FAN1,*(  ) |  
						| 1. Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan 430070, China 2. Department of Animal Science, Iowa State University, Ames, IA 50011, USA
 3. Institute for Genomic Diversity, Cornell University, Ithaca, NY 14853, USA
 |  
						|  |  
					
						| 
								
									|  
          
          
            
              
				
								                
													
													    |  |  
														| 
													
													    | Abstract 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. |  
															| Keywords 
																																																				backfat thickness  
																		  																																				SNP chip  
																		  																																				genome-wide association study  
																		  																																				compressed mixed linear model  
																		  																																				pig |  
															| Corresponding Author(s):
																Bin FAN |  
															| Online First Date: 22 September 2014   
																																														Issue Date: 10 October 2014 |  |  
								            
								                
																																												
															| 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 https://doi.org/10.1007/s003350010025
														     															     															     		pmid: 10656927
 |  
															| 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 https://doi.org/10.1080/10495390902800792
														     															     															     		pmid: 19370455
 |  
															| 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 https://doi.org/10.1186/1297-9686-33-3-289
														     															     															     		pmid: 11403749
 |  
															| 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 https://doi.org/10.1007/s003350020018
														     															     															     		pmid: 11471058
 |  
															| 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 https://doi.org/10.1371/journal.pone.0006524
														     															     															     		pmid: 19654876
 |  
															| 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 https://doi.org/10.1186/1471-2156-15-27
														     															     															     		pmid: 24533460
 |  
															| 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 https://doi.org/10.1371/journal.pone.0014726
														     															     															     		pmid: 21383979
 |  
															| 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 https://doi.org/10.1086/519795
														     															     															     		pmid: 17701901
 |  
															| 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 https://doi.org/10.1038/ng.546
														     															     															     		pmid: 20208535
 |  
															| 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 https://doi.org/10.1001/jama.299.11.1335
														     															     															     		pmid: 18349094
 |  
															| 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 https://doi.org/10.1093/bioinformatics/bth457
														     															     															     		pmid: 15297300
 |  
															| 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 https://doi.org/10.1038/ncomms1854
														     															     															     		pmid: 22617290
 |  
															| 13 | Yue G, Stratil A, Cepica S, Schr?ffel JJr, Schr?ffelova 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 https://doi.org/10.1046/j.0931-2668.2003.00424.x
 |  
															| 14 | Mu?oz 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 pmid: 22303395
 |  
															| 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 https://doi.org/10.1007/PL00014368
														     															     															     		pmid: 10653322
 |  
								            
												
											    	
											        	|  | Viewed |  
											        	|  |  |  
												        |  | Full text 
 | 
 
 |  
												        |  |  |  
												        |  | Abstract 
 | 
 |  
												        |  |  |  
												        |  | Cited |  |  
												        |  |  |  |  
													    |  | Shared |  |  
													    |  |  |  |  
													    |  | Discussed |  |  |  |  |