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Liu C, Chen Z, Zhang Z, Wang Z, Guo X, Pan Y, Wang Q. Unveiling the Genetic Mechanism of Meat Color in Pigs through GWAS, Multi-Tissue, and Single-Cell Transcriptome Signatures Exploration. Int J Mol Sci 2024; 25:3682. [PMID: 38612491 PMCID: PMC11012088 DOI: 10.3390/ijms25073682] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2024] [Revised: 03/22/2024] [Accepted: 03/23/2024] [Indexed: 04/14/2024] Open
Abstract
Meat color traits directly influence consumer acceptability and purchasing decisions. Nevertheless, there is a paucity of comprehensive investigation into the genetic mechanisms underlying meat color traits in pigs. Utilizing genome-wide association studies (GWAS) on five meat color traits and the detection of selection signatures in pig breeds exhibiting distinct meat color characteristics, we identified a promising candidate SNP, 6_69103754, exhibiting varying allele frequencies among pigs with different meat color characteristics. This SNP has the potential to affect the redness and chroma index values of pork. Moreover, transcriptome-wide association studies (TWAS) analysis revealed the expression of candidate genes associated with meat color traits in specific tissues. Notably, the largest number of candidate genes were observed from transcripts derived from adipose, liver, lung, spleen tissues, and macrophage cell type, indicating their crucial role in meat color development. Several shared genes associated with redness, yellowness, and chroma indices traits were identified, including RINL in adipose tissue, ENSSSCG00000034844 and ITIH1 in liver tissue, TPX2 and MFAP2 in lung tissue, and ZBTB17, FAM131C, KIFC3, NTPCR, and ENGSSSCG00000045605 in spleen tissue. Furthermore, single-cell enrichment analysis revealed a significant association between the immune system and meat color. This finding underscores the significance of the immune system associated with meat color. Overall, our study provides a comprehensive analysis of the genetic mechanisms underlying meat color traits, offering valuable insights for future breeding efforts aimed at improving meat quality.
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Affiliation(s)
- Cheng Liu
- Department of Animal Science, College of Animal Science, Zhejiang University, 866# Yuhangtang Road, Hangzhou 310058, China; (C.L.); (Z.C.); (Z.Z.); (Z.W.); (X.G.); (Y.P.)
| | - Zitao Chen
- Department of Animal Science, College of Animal Science, Zhejiang University, 866# Yuhangtang Road, Hangzhou 310058, China; (C.L.); (Z.C.); (Z.Z.); (Z.W.); (X.G.); (Y.P.)
| | - Zhe Zhang
- Department of Animal Science, College of Animal Science, Zhejiang University, 866# Yuhangtang Road, Hangzhou 310058, China; (C.L.); (Z.C.); (Z.Z.); (Z.W.); (X.G.); (Y.P.)
| | - Zhen Wang
- Department of Animal Science, College of Animal Science, Zhejiang University, 866# Yuhangtang Road, Hangzhou 310058, China; (C.L.); (Z.C.); (Z.Z.); (Z.W.); (X.G.); (Y.P.)
| | - Xiaoling Guo
- Department of Animal Science, College of Animal Science, Zhejiang University, 866# Yuhangtang Road, Hangzhou 310058, China; (C.L.); (Z.C.); (Z.Z.); (Z.W.); (X.G.); (Y.P.)
| | - Yuchun Pan
- Department of Animal Science, College of Animal Science, Zhejiang University, 866# Yuhangtang Road, Hangzhou 310058, China; (C.L.); (Z.C.); (Z.Z.); (Z.W.); (X.G.); (Y.P.)
- Hainan Institute, Zhejiang University, Yongyou Industry Park, Yazhou Bay Sci-Tech City, Sanya 572000, China
| | - Qishan Wang
- Department of Animal Science, College of Animal Science, Zhejiang University, 866# Yuhangtang Road, Hangzhou 310058, China; (C.L.); (Z.C.); (Z.Z.); (Z.W.); (X.G.); (Y.P.)
- Hainan Institute, Zhejiang University, Yongyou Industry Park, Yazhou Bay Sci-Tech City, Sanya 572000, China
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Zhao X, Qiu Y, Meng F, Zhuang Z, Ruan D, Wu J, Ma F, Zheng E, Cai G, Yang J, Yang M, Wu Z. Genome-wide association studies for loin muscle area, loin muscle depth and backfat thickness in DLY pigs. Anim Genet 2024; 55:134-139. [PMID: 38098441 DOI: 10.1111/age.13386] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2022] [Revised: 10/17/2023] [Accepted: 11/28/2023] [Indexed: 01/04/2024]
Abstract
This study aimed at identifying genes associated with loin muscle area (LMA), loin muscle depth (LMD) and backfat thickness (BFT). We performed single-trait and multi-trait genome-wide association studies (GWASs) after genotyping 685 Duroc × (Landrace × Yorkshire) (DLY) pigs using the Geneseek Porcine 50K SNP chip. In the single-trait GWASs, we identified two, eight and two significant SNPs associated with LMA, LMD and BFT, respectively, and searched genes within the 1 Mb region near the significant SNPs with relevant functions as candidate genes. Consequently, we identified one (DOCK5), three (PID1, PITX2, ELOVL6) and three (CCR1, PARP14, CASR) promising candidate genes for LMA, LMD and BFT, respectively. Moreover, the multi-trait GWAS identified four significant SNPs associated with the three traits. In conclusion, the GWAS analysis of LMA, LMD and BFT in a DLY pig population identified several associated SNPs and candidate genes, further deepening our understanding of the genetic basis of these traits, and they may be useful for marker-assisted selection to improve the three traits in DLY pigs.
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Affiliation(s)
- Xiang Zhao
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, China
| | - Yibin Qiu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, China
| | - Fanming Meng
- State Key Laboratory of Livestock and Poultry Breeding/Guangdong Key Laboratory of Animal Breeding and Nutrition, Institute of Animal Science, Guangdong Academy of Agricultural Sciences, Guangzhou, Guangdong, China
| | - Zhanwei Zhuang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, China
| | - Donglin Ruan
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, China
| | - Jie Wu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, China
| | - Fucai Ma
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, China
| | - Enqin Zheng
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, China
- Guangdong Provincial Key Laboratory of Agro-animal Genomics and Molecular Breeding, South China Agricultural University, Guangzhou, Guangdong, China
| | - Gengyuan Cai
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, China
- Guangdong Provincial Key Laboratory of Agro-animal Genomics and Molecular Breeding, South China Agricultural University, Guangzhou, Guangdong, China
- Guangdong Zhongxin Breeding Technology Co., Ltd, Guangzhou, Guangdong, China
| | - Jie Yang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, China
- Guangdong Provincial Key Laboratory of Agro-animal Genomics and Molecular Breeding, South China Agricultural University, Guangzhou, Guangdong, China
| | - Ming Yang
- Guangdong Zhongxin Breeding Technology Co., Ltd, Guangzhou, Guangdong, China
- College of Animal Science and Technology, Zhongkai University of Agriculture and Engineering, Guangzhou, Guangdong, China
| | - Zhenfang Wu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, China
- Guangdong Provincial Key Laboratory of Agro-animal Genomics and Molecular Breeding, South China Agricultural University, Guangzhou, Guangdong, China
- Yunfu Subcenter of Guangdong Laboratory for Lingnan Modern Agriculture, Yunfu, Guangdong, China
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Liu LL, Chen B, Chen SL, Liu WJ. A Genome-Wide Association Study of the Chest Circumference Trait in Xinjiang Donkeys Based on Whole-Genome Sequencing Technology. Genes (Basel) 2023; 14:genes14051081. [PMID: 37239441 DOI: 10.3390/genes14051081] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Revised: 05/07/2023] [Accepted: 05/09/2023] [Indexed: 05/28/2023] Open
Abstract
Animal genotyping by means of genome-wide association studies is important for connecting phenotypes of interest with their underlying genetics in livestock. However, the use of whole genome sequencing to investigate chest circumference (CC) in donkeys has rarely been reported. We aimed to use the genome-wide association study approach to detect significant single nucleotide polymorphisms (SNPs) and key genes associated with chest circumference traits in Xinjiang donkeys. We assessed 112 Xinjiang donkeys in this study. The chest circumference of each was measured 2 h before milking. We re-sequenced blood samples from the Xinjiang donkeys, and genome-wide association study analyses were performed using a mixed model with the PLINK, GEMMA, and REGENIE programs. We tested 38 donkeys for candidate SNPs for genome-wide association study using three software programs. Additionally, 18 SNP markers reached genome-wide significance (p < 1.61 × 10-9). On the basis of these, 41 genes were identified. Previously proposed candidate genes for CC traits were supported by this study, including NFATC2 (Nuclear Factor of Activated T Cells 2), PROP1 (PROP Paired-Like Homeobox 1), UBB (Ubiquitin B), and HAND2 (Heart and Neural Crest Derivatives Expressed 2). These promising candidates provide a valuable resource for validating potential meat production genes and will facilitate the development of high-yielding Xinjiang donkey breeds through marker-assisted selection or gene editing.
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Affiliation(s)
- Ling-Ling Liu
- Department of Animal Science, Xinjiang Agricultural University, Urumqi 830052, China
| | - Bin Chen
- Department of Animal Science, Xinjiang Agricultural University, Urumqi 830052, China
| | - Sheng-Lei Chen
- Department of Animal Science, Xinjiang Agricultural University, Urumqi 830052, China
| | - Wu-Jun Liu
- Department of Animal Science, Xinjiang Agricultural University, Urumqi 830052, China
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Teng J, Wang D, Zhao C, Zhang X, Chen Z, Liu J, Sun D, Tang H, Wang W, Li J, Mei C, Yang Z, Ning C, Zhang Q. Longitudinal genome-wide association studies of milk production traits in Holstein cattle using whole-genome sequence data imputed from medium-density chip data. J Dairy Sci 2023; 106:2535-2550. [PMID: 36797187 DOI: 10.3168/jds.2022-22277] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Accepted: 10/20/2022] [Indexed: 02/16/2023]
Abstract
Longitudinal traits, such as milk production traits in dairy cattle, are featured by having phenotypic values at multiple time points, which change dynamically over time. In this study, we first imputed SNP chip (50-100K) data to whole-genome sequence (WGS) data in a Chinese Holstein population consisting of 6,470 cows. The imputation accuracies were 0.88 to 0.97 on average after quality control. We then performed longitudinal GWAS in this population based on a random regression test-day model using the imputed WGS data. The longitudinal GWAS revealed 16, 39, and 75 quantitative trait locus regions associated with milk yield, fat percentage, and protein percentage, respectively. We estimated the 95% confidence intervals (CI) for these quantitative trait locus regions using the logP drop method and identified 581 genes involved in these CI. Further, we focused on the CI that covered or overlapped with only 1 gene or the CI that contained an extremely significant top SNP. Twenty-eight candidate genes were identified in these CI. Most of them have been reported in the literature to be associated with milk production traits, such as DGAT1, HSF1, MGST1, GHR, ABCG2, ADCK5, and CSN1S1. Among the unreported novel genes, some also showed good potential as candidate genes, such as CCSER1, CUX2, SNTB1, RGS7, OSR2, and STK3, and are worth being further investigated. Our study provided not only new insights into the candidate genes for milk production traits, but also a general framework for longitudinal GWAS based on random regression test-day model using WGS data.
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Affiliation(s)
- Jun Teng
- Shandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention, College of Animal Science and Technology, Shandong Agricultural University, Tai'an 271018, China
| | - Dan Wang
- Shandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention, College of Animal Science and Technology, Shandong Agricultural University, Tai'an 271018, China
| | - Changheng Zhao
- Shandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention, College of Animal Science and Technology, Shandong Agricultural University, Tai'an 271018, China
| | - Xinyi Zhang
- Shandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention, College of Animal Science and Technology, Shandong Agricultural University, Tai'an 271018, China
| | - Zhi Chen
- College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China
| | - Jianfeng Liu
- College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Dongxiao Sun
- College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Hui Tang
- Shandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention, College of Animal Science and Technology, Shandong Agricultural University, Tai'an 271018, China
| | - Wenwen Wang
- Shandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention, College of Animal Science and Technology, Shandong Agricultural University, Tai'an 271018, China
| | - Jianbin Li
- Institute of Animal Science and Veterinary Medicine, Shandong Academy of Agricultural Sciences, Jinan 250100, China
| | - Cheng Mei
- Dongying Shenzhou AustAsia Modern Dairy Farm Co. Ltd., Dongying 257200, China
| | - Zhangping Yang
- College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China
| | - Chao Ning
- Shandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention, College of Animal Science and Technology, Shandong Agricultural University, Tai'an 271018, China.
| | - Qin Zhang
- Shandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention, College of Animal Science and Technology, Shandong Agricultural University, Tai'an 271018, China.
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Genetic Parameter Estimation and Genome-Wide Association Analysis of Social Genetic Effects on Average Daily Gain in Purebreds and Crossbreds. Animals (Basel) 2022; 12:ani12172300. [PMID: 36078021 PMCID: PMC9454713 DOI: 10.3390/ani12172300] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Revised: 08/23/2022] [Accepted: 09/01/2022] [Indexed: 11/29/2022] Open
Abstract
Simple Summary Average daily gain (ADG) is influenced by both an individual’s direct genetic effect (DGE) and by a social genetic effect (SGE) derived from pen mates. Therefore, identifying the DGE and SGE on ADG is essential for a better understanding of pig breeding systems. We conducted this study to elucidate the genetic characteristics and relationships of DGE and SGE on ADG using purebred and crossbred pigs. We found that the DGE and SGE both contributed to ADG in both populations. In addition, the SGE of purebred pigs was highly correlated with the DGE of crossbred pigs. Furthermore, we identified several genomic regions that may be associated with the DGE and SGE on ADG. Our findings will contribute to future genomic evaluation studies of socially affected traits. Abstract Average daily gain (ADG) is an important growth trait in the pig industry. The direct genetic effect (DGE) has been studied mainly to assess the association between genetic information and economic traits. The social genetic effect (SGE) has been shown to affect ADG simultaneously with the DGE because of group housing systems. We conducted this study to elucidate the genetic characteristics and relationships of the DGE and SGE of purebred Korean Duroc and crossbred pigs by single-step genomic best linear unbiased prediction and a genome-wide association study. We used the genotype, phenotype, and pedigree data of 1779, 6022, and 7904 animals, respectively. Total heritabilities on ADG were 0.19 ± 0.04 and 0.39 ± 0.08 for purebred and crossbred pigs, respectively. The genetic correlation was the greatest (0.77 ± 0.12) between the SGE of purebred and DGE of crossbred pigs. We found candidate genes located in the quantitative trait loci (QTLs) for the SGE that were associated with behavior and neurodegenerative diseases, and candidate genes in the QTLs for DGE that were related to body mass, size of muscle fiber, and muscle hypertrophy. These results suggest that the genomic selection of purebred animals could be applied for crossbred performance.
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Genome-Wide Association Analysis and Genetic Parameters for Feed Efficiency and Related Traits in Yorkshire and Duroc Pigs. Animals (Basel) 2022; 12:ani12151902. [PMID: 35892552 PMCID: PMC9329986 DOI: 10.3390/ani12151902] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Revised: 07/04/2022] [Accepted: 07/20/2022] [Indexed: 11/17/2022] Open
Abstract
Simple Summary Genetic improvements in feed efficiency (FE) and related traits could considerably reduce pig production costs and energy consumption. Thus, we performed a genetic parameter estimation and genome-wide association study of four FE and FE-related traits, namely, average daily feed intake, average daily gain, the feed conversion ratio, and residual feed intake, of two pig breeds, Yorkshire and Duroc. The results demonstrate the genetic relationships of FE and FE-related traits with two growth traits, age and backfat thickness at 100 kg. We also identified many single-nucleotide polymorphisms (SNPs) and novel candidate genes related to these traits. In addition, we found many pathways significantly associated with FE and FE-related traits, and they are generally involved in digestive and metabolic processes. The results of this study are expected to provide a valuable reference for the genomic selection of FE and FE-related traits in pigs. Abstract Feed efficiency (FE) traits are key factors that can influence the economic benefits of pig production. However, little is known about the genetic architecture of FE and FE-related traits. This study aimed to identify SNPs and candidate genes associated with FE and FE-related traits, namely, average daily feed intake (ADFI), average daily gain (ADG), the feed conversion ratio (FCR), and residual feed intake (RFI). The phenotypes of 5823 boars with genotyped data (50 K BeadChip) from 1365 boars from a nucleus farm were used to perform a genome-wide association study (GWAS) of two breeds, Duroc and Yorkshire. Moreover, we performed a genetic parameter estimation for four FE and FE-related traits. The heritabilities of the FE and FE-related traits ranged from 0.13 to 0.36, and there were significant genetic correlations (−0.69 to 0.52) of the FE and FE-related traits with two growth traits (age at 100 kg and backfat thickness at 100 kg). A total of 61 significant SNPs located on eight different chromosomes associated with the four FE and FE-related traits were identified. We further identified four regions associated with FE and FE-related traits that have not been previously reported, and they may be potential novel QTLs for FE. Considering their biological functions, we finally identified 35 candidate genes relevant for FE and FE-related traits, such as the widely reported MC4R and INSR genes. A gene enrichment analysis showed that FE and FE-related traits were highly enriched in the biosynthesis, digestion, and metabolism of biomolecules. This study deepens our understanding of the genetic mechanisms of FE in pigs and provides valuable information for using marker-assisted selection in pigs to improve FE.
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Wang K, Wang S, Ji X, Chen D, Shen Q, Yu Y, Xiao W, Wu P, Tang G. Genome-wide association studies identified loci associated with both feed conversion ratio and residual feed intake in Yorkshire pigs. Genome 2022; 65:405-412. [PMID: 35594567 DOI: 10.1139/gen-2021-0105] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
Feed occupies a significant proportion in the production cost of pigs, and the feed efficiency (FE) in pigs are of utmost economic importance. Hence, the objective of this study is to identify single nucleotide polymorphisms (SNPs) and candidate genes associated with FE related traits, including feed conversion ratio (FCR) and residual feed intake (RFI). A genome-wide association study (GWAS) was conducted for FCR and RFI in 169 Yorkshire pigs using whole-genome sequencing data. A total of 23 and 33 suggestive significant SNPs (P<1×10^(-6)) were detected for FCR and RFI, respectively. However, none of the SNPs achieved the genome-wide significance threshold (P<5×10^(-8)). Importantly, three common SNPs (SSC7:7987268, SSC13:42350250, and SSC13:42551718) were associated with both FCR and RFI. Additionally, the NEDD9 gene related to FCR and RFI traits was overlapped. This study detected novel SNPs on SSC7 and SSC13 common for FCR and RFI. These results provide new insights into the genetic mechanisms and candidate genes of FE-related traits in pigs.
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Affiliation(s)
- Kai Wang
- Sichuan Agricultural University, 12529, Chengdu, Sichuan, China;
| | - Shujie Wang
- Sichuan Agricultural University, 12529, Chengdu, Sichuan, China;
| | - Xiang Ji
- Sichuan Agricultural University, 12529, Chengdu, Sichuan, China;
| | - Dong Chen
- Sichuan Agricultural University, 12529, Chengdu, Sichuan, China;
| | - Qi Shen
- Sichuan Agricultural University, 12529, Chengdu, Sichuan, China;
| | - Yang Yu
- Sichuan Agricultural University, 12529, Chengdu, Sichuan, China;
| | - Weihang Xiao
- Sichuan Agricultural University, 12529, Yaan, Sichuan, China, 625014;
| | - Pingxian Wu
- Chongqing Academy of Animal Science, Chongqing, China, 402460;
| | - Guoqing Tang
- Sichuan Agricultural University, 12529, Yaan, Sichuan, China, 625014;
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