Dataset Information

Association of Twelve Candidate Gene Polymorphisms with the Intramuscular Fat Content and Average Backfat Thickness of Chinese Suhuai Pigs.

ABSTRACT: The present study aimed to identify the molecular markers for genes that influence intramuscular fat content (IFC), but not average backfat thickness (ABT). A total of 330 Suhuai pigs were slaughtered, and measurements of IFC and ABT were obtained. Phenotypic and genetic correlations between IFC and ABT were calculated. Thirteen single nucleotide polymorphisms (SNPs) among 12 candidate genes for IFC were analyzed, including FABP3, LIPE, IGF1, IGF2, LEP, LEPR, MC4R, PHKG1, RETN, RYR1, SCD, and UBE3C. Associations of the evaluated SNPs with IFCIFC and ABT were performed. Our results showed that the means of IFC and ABT were 1.99 ± 0.03 % and 26.68 ± 0.28 mm, respectively. The coefficients of variation (CVs) of IFC and ABT were 31.21% and 19.36%, respectively. The phenotypic and genetic correlations between IFC and ABT were moderate. Only the FABP3 (rs1110770079) was associated with IFC (p < 0.05) but not with ABT. Besides, there was a tendency for associations of RYR1 (rs344435545) and SCD (rs80912566) with IFC (p < 0.1). Our results indicated that the FABP3 (rs1110770079) SNP could be used as a marker to improve IFC without changing ABT in the Suhuai pig breeding system.

SUBMITTER: Wang B

PROVIDER: S-EPMC6912197 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature

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Association of Twelve Candidate Gene Polymorphisms with the Intramuscular Fat Content and Average Backfat Thickness of Chinese Suhuai Pigs.

Wang Binbin B Li Pinghua P Zhou Wuduo W Gao Chen C Liu Hang H Li Huixia H Niu Peipei P Zhang Zongping Z Li Qiang Q Zhou Juan J Huang Ruihua R

Animals : an open access journal from MDPI 20191023 11

The present study aimed to identify the molecular markers for genes that influence intramuscular fat content (IFC), but not average backfat thickness (ABT). A total of 330 Suhuai pigs were slaughtered, and measurements of IFC and ABT were obtained. Phenotypic and genetic correlations between IFC and ABT were calculated. Thirteen single nucleotide polymorphisms (SNPs) among 12 candidate genes for IFC were analyzed, including FABP3, LIPE, IGF1, IGF2, LEP, LEPR ...[more]

PMID: 31652864

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Project description:Integrating the single-nucleotide polymorphisms (SNPs) significantly affecting target traits from imputed whole-genome sequencing (iWGS) data into the genomic prediction (GP) model is an economic, efficient, and feasible strategy to improve prediction accuracy. The objective was to dissect the genetic architecture of intramuscular fat content (IFC) by genome wide association studies (GWAS) and to investigate the accuracy of GP based on pedigree-based BLUP (PBLUP) model, genomic best linear unbiased prediction (GBLUP) models and Bayesian mixture (BayesMix) models under different strategies. A total of 482 Suhuai pigs were genotyped using an 80 K SNP chip. Furthermore, 30 key samples were selected for resequencing and were used as a reference panel to impute the 80 K chip data to the WGS dataset. The 80 K data and iWGS data were used to perform GWAS and test GP accuracies under different scenarios. GWAS results revealed that there were four major regions affecting IFC. Two important functional candidate genes were found in the two most significant regions, including protein kinase C epsilon (PRKCE) and myosin light chain 2 (MYL2). The results of the predictions showed that the PBLUP model had the lowest reliability (0.096 ± 0.032). The reliability (0.229 ± 0.035) was improved by replacing pedigree information with 80 K chip data. Compared with using 80 K SNPs alone, pruning iWGS SNPs with the R-squared cutoff of linkage disequilibrium (0.55) led to a slight improvement (0.006), adding significant iWGS SNPs led to an improvement of reliability by 0.050 when using a one-component GBLUP, a further increase of 0.033 when using a two-component GBLUP model. For BayesMix models, compared with using 80 K SNPs alone, adding additional significant iWGS SNPs into one- or two-component BayesMix models led to improvements of reliabilities for IFC by 0.040 and 0.089, respectively. Our results may facilitate further identification of causal genes for IFC and may be beneficial for the improvement of IFC in pig breeding programs.

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Dataset Information

Association of Twelve Candidate Gene Polymorphisms with the Intramuscular Fat Content and Average Backfat Thickness of Chinese Suhuai Pigs.

Publications

Association of Twelve Candidate Gene Polymorphisms with the Intramuscular Fat Content and Average Backfat Thickness of Chinese Suhuai Pigs.

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