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Xie K, Ning C, Yang A, Zhang Q, Wang D, Fan X. Resequencing Analyses Revealed Genetic Diversity and Selection Signatures during Rabbit Breeding and Improvement. Genes (Basel) 2024; 15:433. [PMID: 38674368 PMCID: PMC11049387 DOI: 10.3390/genes15040433] [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: 02/21/2024] [Revised: 03/23/2024] [Accepted: 03/26/2024] [Indexed: 04/28/2024] Open
Abstract
Domestication has shaped the diverse characteristics of rabbits, including coat color, fur structure, body size, and various physiological traits. Utilizing whole-genome resequencing (DNBSEQ-T7), we analyzed the genetic diversity, population structure, and genomic selection across 180 rabbits from 17 distinct breeds to uncover the genetic basis of these traits. We conducted whole-genome sequencing on 17 rabbit breeds, identifying 17,430,184 high-quality SNPs and analyzing genomic diversity, patterns of genomic variation, population structure, and selection signatures related to coat color, coat structure, long hair, body size, reproductive capacity, and disease resistance. Through PCA and NJ tree analyses, distinct clusters emerged among Chinese indigenous rabbits, suggesting varied origins and domestication histories. Selective sweep testing pinpointed regions and genes linked to domestication and key morphological and economic traits, including those affecting coat color (TYR, ASIP), structure (LIPH), body size (INSIG2, GLI3), fertility (EDNRA, SRD5A2), heat stress adaptation (PLCB1), and immune response (SEC31A, CD86, LAP3). Our study identified key genomic signatures of selection related to traits such as coat color, fur structure, body size, and fertility; these findings highlight the genetic basis underlying phenotypic diversification in rabbits and have implications for breeding programs aiming to improve productive, reproductive, and adaptive traits. The detected genomic signatures of selection also provide insights into rabbit domestication and can aid conservation efforts for indigenous breeds.
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Affiliation(s)
- Kerui Xie
- College of Animal Science and Veterinary Medicine, Shandong Agricultural University, Tai’an 271018, China;
| | - Chao Ning
- Shandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention, Shandong Agricultural University, 61 Daizong Street, Tai’an 271018, China; (C.N.); (Q.Z.)
| | - Aiguo Yang
- Shandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention, Shandong Agricultural University, 61 Daizong Street, Tai’an 271018, China; (C.N.); (Q.Z.)
| | - Qin Zhang
- Shandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention, Shandong Agricultural University, 61 Daizong Street, Tai’an 271018, China; (C.N.); (Q.Z.)
| | - Dan Wang
- Key Laboratory of Efficient Utilization of Non-Grain Feed Resources (Co-Construction by Ministry and Province), Ministry of Agriculture and Rural Affairs, College of Animal Science and Veterinary Medicine, Shandong Agricultural University, Tai’an 271018, China
| | - Xinzhong Fan
- College of Animal Science and Veterinary Medicine, Shandong Agricultural University, Tai’an 271018, China;
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Chen Z, Teng J, Diao S, Xu Z, Ye S, Qiu D, Zhang Z, Pan Y, Li J, Zhang Q, Zhang Z. Insights into the architecture of human-induced polygenic selection in Duroc pigs. J Anim Sci Biotechnol 2022; 13:99. [PMID: 36127741 PMCID: PMC9490910 DOI: 10.1186/s40104-022-00751-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Accepted: 07/03/2022] [Indexed: 11/10/2022] Open
Abstract
Background As one of the most utilized commercial composite boar lines, Duroc pigs have been introduced to China and undergone strongly human-induced selection over the past decades. However, the efficiencies and limitations of previous breeding of Chinese Duroc pigs are largely understudied. The objective of this study was to uncover directional polygenic selection in the Duroc pig genome, and investigate points overlooked in the past breeding process. Results Here, we utilized the Generation Proxy Selection Mapping (GPSM) on a dataset of 1067 Duroc pigs with 8,766,074 imputed SNPs. GPSM detected a total of 5649 putative SNPs actively under selection in the Chinese Duroc pig population, and the potential functions of the selection regions were mainly related to production, meat and carcass traits. Meanwhile, we observed that the allele frequency of variants related to teat number (NT) relevant traits was also changed, which might be influenced by genes that had pleiotropic effects. First, we identified the direction of selection on NT traits by \documentclass[12pt]{minimal}
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\begin{document}$$\hat{G}$$\end{document}G^, and further pinpointed large-effect genomic regions associated with NT relevant traits by selection signature and GWAS. Combining results of NT relevant traits-specific selection signatures and GWAS, we found three common genome regions, which were overlapped with QTLs related to production, meat and carcass traits besides “teat number” QTLs. This implied that there were some pleiotropic variants underlying NT and economic traits. We further found that rs346331089 has pleiotropic effects on NT and economic traits, e.g., litter size at weaning (LSW), litter weight at weaning (LWW), days to 100 kg (D100), backfat thickness at 100 kg (B100), and loin muscle area at 100 kg (L100) traits. Conclusions The selected loci that we identified across methods displayed the past breeding process of Chinese Duroc pigs, and our findings could be used to inform future breeding decision. Supplementary Information The online version contains supplementary material available at 10.1186/s40104-022-00751-x.
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Affiliation(s)
- Zitao Chen
- National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, 510642, P.R. China.,Department of Animal Science, College of Animal Science, Zhejiang University, 866# Yuhangtang Road, Hangzhou, 310058, P.R. China
| | - Jinyan Teng
- National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, 510642, P.R. China
| | - Shuqi Diao
- National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, 510642, P.R. China
| | - Zhiting Xu
- National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, 510642, P.R. China
| | - Shaopan Ye
- National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, 510642, P.R. China.,Guangdong Provincial Key Laboratory of Marine Biotechnology, Shantou University, 243 Daxue Road, Shantou, 515063, P.R. China
| | - Dingjie Qiu
- Fujian Yongcheng Agricultural & Animal Husbandry Sci-Tech Group Co., Ltd., Fuqing, 350399, P.R. China
| | - Zhe Zhang
- Department of Animal Science, College of Animal Science, Zhejiang University, 866# Yuhangtang Road, Hangzhou, 310058, P.R. China
| | - Yuchun Pan
- Department of Animal Science, College of Animal Science, Zhejiang University, 866# Yuhangtang Road, Hangzhou, 310058, P.R. China
| | - Jiaqi Li
- National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, 510642, P.R. China
| | - Qin Zhang
- Department of Animal Genetics and Breeding, College of Animal Science and Technology, Shandong Agricultural University, Tai'an, 271018, P.R. China
| | - Zhe Zhang
- National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, 510642, P.R. China.
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Davoudi P, Do DN, Colombo SM, Rathgeber B, Miar Y. Application of Genetic, Genomic and Biological Pathways in Improvement of Swine Feed Efficiency. Front Genet 2022; 13:903733. [PMID: 35754793 PMCID: PMC9220306 DOI: 10.3389/fgene.2022.903733] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Accepted: 05/20/2022] [Indexed: 12/24/2022] Open
Abstract
Despite the significant improvement of feed efficiency (FE) in pigs over the past decades, feed costs remain a major challenge for producers profitability. Improving FE is a top priority for the global swine industry. A deeper understanding of the biology underlying FE is crucial for making progress in genetic improvement of FE traits. This review comprehensively discusses the topics related to the FE in pigs including: measurements, genetics, genomics, biological pathways and the advanced technologies and methods involved in FE improvement. We first provide an update of heritability for different FE indicators and then characterize the correlations of FE traits with other economically important traits. Moreover, we present the quantitative trait loci (QTL) and possible candidate genes associated with FE in pigs and outline the most important biological pathways related to the FE traits in pigs. Finally, we present possible ways to improve FE in swine including the implementation of genomic selection, new technologies for measuring the FE traits, and the potential use of genome editing and omics technologies.
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Affiliation(s)
- Pourya Davoudi
- Department of Animal Science and Aquaculture, Dalhousie University, Truro, NS, Canada
| | - Duy Ngoc Do
- Department of Animal Science and Aquaculture, Dalhousie University, Truro, NS, Canada
| | - Stefanie M Colombo
- Department of Animal Science and Aquaculture, Dalhousie University, Truro, NS, Canada
| | - Bruce Rathgeber
- Department of Animal Science and Aquaculture, Dalhousie University, Truro, NS, Canada
| | - Younes Miar
- Department of Animal Science and Aquaculture, Dalhousie University, Truro, NS, Canada
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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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Delpuech E, Aliakbari A, Labrune Y, Fève K, Billon Y, Gilbert H, Riquet J. Identification of genomic regions affecting production traits in pigs divergently selected for feed efficiency. Genet Sel Evol 2021; 53:49. [PMID: 34126920 PMCID: PMC8201702 DOI: 10.1186/s12711-021-00642-1] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2020] [Accepted: 05/28/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Feed efficiency is a major driver of the sustainability of pig production systems. Understanding the biological mechanisms that underlie these agronomic traits is an important issue for environment questions and farms' economy. This study aimed at identifying genomic regions that affect residual feed intake (RFI) and other production traits in two pig lines divergently selected for RFI during nine generations (LRFI, low RFI; HRFI, high RFI). RESULTS We built a whole dataset of 570,447 single nucleotide polymorphisms (SNPs) in 2426 pigs with records for 24 production traits after both imputation and prediction of genotypes using pedigree information. Genome-wide association studies (GWAS) were performed including both lines (global-GWAS) or each line independently (LRFI-GWAS and HRFI-GWAS). Forty-five chromosomal regions were detected in the global-GWAS, whereas 28 and 42 regions were detected in the HRFI-GWAS and LRFI-GWAS, respectively. Among these 45 regions, only 13 were shared between at least two analyses, and only one was common between the three GWAS but it affects different traits. Among the five quantitative trait loci (QTL) detected for RFI, two were close to QTL for meat quality traits and two pinpointed novel genomic regions that harbor candidate genes involved in cell proliferation and differentiation processes of gastrointestinal tissues or in lipid metabolism-related signaling pathways. In most cases, different QTL regions were detected between the three designs, which suggests a strong impact of the dataset structure on the detection power and could be due to the changes in allelic frequencies during the establishment of lines. CONCLUSIONS In addition to efficiently detecting known and new QTL regions for feed efficiency, the combination of GWAS carried out per line or simultaneously using all individuals highlighted chromosomal regions that affect production traits and presented significant changes in allelic frequencies across generations. Further analyses are needed to estimate whether these regions correspond to traces of selection or result from genetic drift.
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Affiliation(s)
- Emilie Delpuech
- GenPhySE, Université de Toulouse, INRAE, ENVT, 31320, Castanet-Tolosan, France
| | - Amir Aliakbari
- GenPhySE, Université de Toulouse, INRAE, ENVT, 31320, Castanet-Tolosan, France
| | - Yann Labrune
- GenPhySE, Université de Toulouse, INRAE, ENVT, 31320, Castanet-Tolosan, France
| | - Katia Fève
- GenPhySE, Université de Toulouse, INRAE, ENVT, 31320, Castanet-Tolosan, France
| | | | - Hélène Gilbert
- GenPhySE, Université de Toulouse, INRAE, ENVT, 31320, Castanet-Tolosan, France
| | - Juliette Riquet
- GenPhySE, Université de Toulouse, INRAE, ENVT, 31320, Castanet-Tolosan, France.
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6
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Miao Y, Mei Q, Fu C, Liao M, Liu Y, Xu X, Li X, Zhao S, Xiang T. Genome-wide association and transcriptome studies identify candidate genes and pathways for feed conversion ratio in pigs. BMC Genomics 2021; 22:294. [PMID: 33888058 PMCID: PMC8063444 DOI: 10.1186/s12864-021-07570-w] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2020] [Accepted: 03/25/2021] [Indexed: 12/03/2022] Open
Abstract
Background The feed conversion ratio (FCR) is an important productive trait that greatly affects profits in the pig industry. Elucidating the genetic mechanisms underpinning FCR may promote more efficient improvement of FCR through artificial selection. In this study, we integrated a genome-wide association study (GWAS) with transcriptome analyses of different tissues in Yorkshire pigs (YY) with the aim of identifying key genes and signalling pathways associated with FCR. Results A total of 61 significant single nucleotide polymorphisms (SNPs) were detected by GWAS in YY. All of these SNPs were located on porcine chromosome (SSC) 5, and the covered region was considered a quantitative trait locus (QTL) region for FCR. Some genes distributed around these significant SNPs were considered as candidates for regulating FCR, including TPH2, FAR2, IRAK3, YARS2, GRIP1, FRS2, CNOT2 and TRHDE. According to transcriptome analyses in the hypothalamus, TPH2 exhibits the potential to regulate intestinal motility through serotonergic synapse and oxytocin signalling pathways. In addition, GRIP1 may be involved in glutamatergic and GABAergic signalling pathways, which regulate FCR by affecting appetite in pigs. Moreover, GRIP1, FRS2, CNOT2, and TRHDE may regulate metabolism in various tissues through a thyroid hormone signalling pathway. Conclusions Based on the results from GWAS and transcriptome analyses, the TPH2, GRIP1, FRS2, TRHDE, and CNOT2 genes were considered candidate genes for regulating FCR in Yorkshire pigs. These findings improve the understanding of the genetic mechanisms of FCR and may help optimize the design of breeding schemes. Supplementary Information The online version contains supplementary material available at 10.1186/s12864-021-07570-w.
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Affiliation(s)
- Yuanxin Miao
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & Key Laboratory of Swine Genetics and Breeding of Ministry of Agriculture, Huazhong Agricultural University, Wuhan, 430070, China.,The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070, China.,Jingchu University of Technology, Jingmen, 448000, China
| | - Quanshun Mei
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & Key Laboratory of Swine Genetics and Breeding of Ministry of Agriculture, Huazhong Agricultural University, Wuhan, 430070, China.,The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070, China
| | - Chuanke Fu
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & Key Laboratory of Swine Genetics and Breeding of Ministry of Agriculture, Huazhong Agricultural University, Wuhan, 430070, China.,The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070, China
| | - Mingxing Liao
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & Key Laboratory of Swine Genetics and Breeding of Ministry of Agriculture, Huazhong Agricultural University, Wuhan, 430070, China.,The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070, China.,Agriculture and Rural Affairs Administration of Jingmen City, Jingmen, 448000, China
| | - Yan Liu
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & Key Laboratory of Swine Genetics and Breeding of Ministry of Agriculture, Huazhong Agricultural University, Wuhan, 430070, China.,The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070, China
| | - Xuewen Xu
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & Key Laboratory of Swine Genetics and Breeding of Ministry of Agriculture, Huazhong Agricultural University, Wuhan, 430070, China.,The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070, China
| | - Xinyun Li
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & Key Laboratory of Swine Genetics and Breeding of Ministry of Agriculture, Huazhong Agricultural University, Wuhan, 430070, China.,The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070, China
| | - Shuhong Zhao
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & Key Laboratory of Swine Genetics and Breeding of Ministry of Agriculture, Huazhong Agricultural University, Wuhan, 430070, China.,The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070, China
| | - Tao Xiang
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & Key Laboratory of Swine Genetics and Breeding of Ministry of Agriculture, Huazhong Agricultural University, Wuhan, 430070, China. .,The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070, China.
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Ye S, Chen ZT, Zheng R, Diao S, Teng J, Yuan X, Zhang H, Chen Z, Zhang X, Li J, Zhang Z. New Insights From Imputed Whole-Genome Sequence-Based Genome-Wide Association Analysis and Transcriptome Analysis: The Genetic Mechanisms Underlying Residual Feed Intake in Chickens. Front Genet 2020; 11:243. [PMID: 32318090 PMCID: PMC7147382 DOI: 10.3389/fgene.2020.00243] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2019] [Accepted: 02/28/2020] [Indexed: 12/26/2022] Open
Abstract
Poultry feed constitutes the largest cost in poultry production, estimated to be up to 70% of the total cost. Moreover, there is pressure on the poultry industry to increase production to meet the protein demand of humans and simultaneously reduce emissions to protect the environment. Therefore, improving feed efficiency plays an important role to improve profits and the environmental footprint in broiler production. In this study, using imputed whole-genome sequencing data, genome-wide association analysis (GWAS) was performed to identify single-nucleotide polymorphisms (SNPs) and genes associated with residual feed intake (RFI) and its component traits. Furthermore, a transcriptomic analysis between the high-RFI and the low-RFI groups was performed to validate the candidate genes from GWAS. The results showed that the heritability estimates of average daily gain (ADG), average daily feed intake (ADFI), and RFI were 0.29 (0.004), 0.37 (0.005), and 0.38 (0.004), respectively. Using imputed sequence-based GWAS, we identified seven significant SNPs and five candidate genes [MTSS I-BAR domain containing 1, folliculin, COP9 signalosome subunit 3, 5′,3′-nucleotidase (mitochondrial), and gametocyte-specific factor 1] associated with RFI, 20 significant SNPs and one candidate gene (inositol polyphosphate multikinase) associated with ADG, and one significant SNP and one candidate gene (coatomer protein complex subunit alpha) associated with ADFI. After performing a transcriptomic analysis between the high-RFI and the low-RFI groups, both 38 up-regulated and 26 down-regulated genes were identified in the high-RFI group. Furthermore, integrating regional conditional GWAS and transcriptome analysis, ras-related dexamethasone induced 1 was the only overlapped gene associated with RFI, which also suggested that the region (GGA14: 4767015–4882318) is a new quantitative trait locus associated with RFI. In conclusion, using imputed sequence-based GWAS is an efficient method to identify significant SNPs and candidate genes in chicken. Our results provide valuable insights into the genetic mechanisms of RFI and its component traits, which would further improve the genetic gain of feed efficiency rapidly and cost-effectively in the context of marker-assisted breeding selection.
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Affiliation(s)
- Shaopan Ye
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, China
| | - Zi-Tao Chen
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, China
| | - Rongrong Zheng
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, China
| | - Shuqi Diao
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, China
| | - Jinyan Teng
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, China
| | - Xiaolong Yuan
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, China
| | - Hao Zhang
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, China
| | - Zanmou Chen
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, China
| | - Xiquan Zhang
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, China
| | - Jiaqi Li
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, China
| | - Zhe Zhang
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, China
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Ghoreishifar SM, Moradi-Shahrbabak H, Fallahi MH, Jalil Sarghale A, Moradi-Shahrbabak M, Abdollahi-Arpanahi R, Khansefid M. Genomic measures of inbreeding coefficients and genome-wide scan for runs of homozygosity islands in Iranian river buffalo, Bubalus bubalis. BMC Genet 2020; 21:16. [PMID: 32041535 PMCID: PMC7011551 DOI: 10.1186/s12863-020-0824-y] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2019] [Accepted: 02/04/2020] [Indexed: 01/06/2023] Open
Abstract
Background Consecutive homozygous fragments of a genome inherited by offspring from a common ancestor are known as runs of homozygosity (ROH). ROH can be used to calculate genomic inbreeding and to identify genomic regions that are potentially under historical selection pressure. The dataset of our study consisted of 254 Azeri (AZ) and 115 Khuzestani (KHZ) river buffalo genotyped for ~ 65,000 SNPs for the following two purposes: 1) to estimate and compare inbreeding calculated using ROH (FROH), excess of homozygosity (FHOM), correlation between uniting gametes (FUNI), and diagonal elements of the genomic relationship matrix (FGRM); 2) to identify frequently occurring ROH (i.e. ROH islands) for our selection signature and gene enrichment studies. Results In this study, 9102 ROH were identified, with an average number of 21.2 ± 13.1 and 33.2 ± 15.9 segments per animal in AZ and KHZ breeds, respectively. On average in AZ, 4.35% (108.8 ± 120.3 Mb), and in KHZ, 5.96% (149.1 ± 107.7 Mb) of the genome was autozygous. The estimated inbreeding values based on FHOM, FUNI and FGRM were higher in AZ than they were in KHZ, which was in contrast to the FROH estimates. We identified 11 ROH islands (four in AZ and seven in KHZ). In the KHZ breed, the genes located in ROH islands were enriched for multiple Gene Ontology (GO) terms (P ≤ 0.05). The genes located in ROH islands were associated with diverse biological functions and traits such as body size and muscle development (BMP2), immune response (CYP27B1), milk production and components (MARS, ADRA1A, and KCTD16), coat colour and pigmentation (PMEL and MYO1A), reproductive traits (INHBC, INHBE, STAT6 and PCNA), and bone development (SUOX). Conclusion The calculated FROH was in line with expected higher inbreeding in KHZ than in AZ because of the smaller effective population size of KHZ. Thus, we find that FROH can be used as a robust estimate of genomic inbreeding. Further, the majority of ROH peaks were overlapped with or in close proximity to the previously reported genomic regions with signatures of selection. This tells us that it is likely that the genes in the ROH islands have been subject to artificial or natural selection.
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Affiliation(s)
- Seyed Mohammad Ghoreishifar
- Department of Animal Science, University College of Agriculture and Natural Resources, University of Tehran, Karaj, 31587-11167, Iran
| | - Hossein Moradi-Shahrbabak
- Department of Animal Science, University College of Agriculture and Natural Resources, University of Tehran, Karaj, 31587-11167, Iran.
| | - Mohammad Hossein Fallahi
- Department of Animal Science, University College of Agriculture and Natural Resources, University of Tehran, Karaj, 31587-11167, Iran
| | - Ali Jalil Sarghale
- Department of Animal Science, University College of Agriculture and Natural Resources, University of Tehran, Karaj, 31587-11167, Iran
| | - Mohammad Moradi-Shahrbabak
- Department of Animal Science, University College of Agriculture and Natural Resources, University of Tehran, Karaj, 31587-11167, Iran
| | - Rostam Abdollahi-Arpanahi
- Departments of Animal and Poultry Science, College of Aburaihan, University of Tehran, Pakdasht, 33916-53755, Iran
| | - Majid Khansefid
- AgriBio Centre for AgriBioscience, Agriculture Victoria, Bundoora, VIC, 3083, Australia
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Genomic analysis reveals genes affecting distinct phenotypes among different Chinese and western pig breeds. Sci Rep 2018; 8:13352. [PMID: 30190566 PMCID: PMC6127261 DOI: 10.1038/s41598-018-31802-x] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2018] [Accepted: 08/21/2018] [Indexed: 01/04/2023] Open
Abstract
The differences in artificial and natural selection have been some of the factors contributing to phenotypic diversity between Chinese and western pigs. Here, 830 individuals from western and Chinese pig breeds were genotyped using the reduced-representation genotyping method. First, we identified the selection signatures for different pig breeds. By comparing Chinese pigs and western pigs along the first principal component, the growth gene IGF1R; the immune genes IL1R1, IL1RL1, DUSP10, RAC3 and SWAP70; the meat quality-related gene SNORA50 and the olfactory gene OR1F1 were identified as candidate differentiated targets. Further, along a principal component separating Pudong White pigs from others, a potential causal gene for coat colour (EDNRB) was discovered. In addition, the divergent signatures evaluated by Fst within Chinese pig breeds found genes associated with the phenotypic features of coat colour, meat quality and feed efficiency among these indigenous pigs. Second, admixture and genomic introgression analysis were performed. Shan pigs have introgressed genes from Berkshire, Yorkshire and Hongdenglong pigs. The results of introgression mapping showed that this introgression conferred adaption to the local environment and coat colour of Chinese pigs and the superior productivity of western pigs.
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Ding R, Yang M, Wang X, Quan J, Zhuang Z, Zhou S, Li S, Xu Z, Zheng E, Cai G, Liu D, Huang W, Yang J, Wu Z. Genetic Architecture of Feeding Behavior and Feed Efficiency in a Duroc Pig Population. Front Genet 2018; 9:220. [PMID: 29971093 PMCID: PMC6018414 DOI: 10.3389/fgene.2018.00220] [Citation(s) in RCA: 54] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2018] [Accepted: 05/29/2018] [Indexed: 11/13/2022] Open
Abstract
Increasing feed efficiency is a major goal of breeders as it can reduce production cost and energy consumption. However, the genetic architecture of feeding behavior and feed efficiency traits remains elusive. To investigate the genetic architecture of feed efficiency in pigs, three feeding behavior traits (daily feed intake, number of daily visits to feeder, and duration of each visit) and two feed efficiency traits (feed conversion ratio and residual feed intake) were considered. We performed genome-wide association studies (GWASs) of the five traits using a population of 1,008 Duroc pigs genotyped with an Illumina Porcine SNP50K BeadChip. A total of 9 genome-wide (P < 1.54E-06) and 35 suggestive (P < 3.08E-05) single nucleotide polymorphisms (SNPs) were detected. Two pleiotropic quantitative trait loci (QTLs) on SSC 1 and SSC 7 were found to affect more than one trait. Markers WU_10.2_7_18377044 and DRGA0001676 are two key SNPs for these two pleiotropic QTLs. Marker WU_10.2_7_18377044 on SSC 7 contributed 2.16 and 2.37% of the observed phenotypic variance for DFI and RFI, respectively. The other SNP DRGA0001676 on SSC 1 explained 3.22 and 5.46% of the observed phenotypic variance for FCR and RFI, respectively. Finally, functions of candidate genes and gene set enrichment analysis indicate that most of the significant pathways are associated with hormonal and digestive gland secretion during feeding. This study advances our understanding of the genetic mechanisms of feeding behavior and feed efficiency traits and provide an opportunity for increasing feeding efficiency using marker-assisted selection or genomic selection in pigs.
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Affiliation(s)
- Rongrong Ding
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, China
| | - Ming Yang
- National Engineering Research Center for Breeding Swine Industry, Guangdong Wens Foodstuffs Group, Co., Ltd., Guangdong, China
| | - Xingwang Wang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, China
| | - Jianping Quan
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, China
| | - Zhanwei Zhuang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, China
| | - Shenping Zhou
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, China
| | - Shaoyun Li
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, China
| | - Zheng Xu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, China
| | - Enqin Zheng
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, China
| | - Gengyuan Cai
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, China.,National Engineering Research Center for Breeding Swine Industry, Guangdong Wens Foodstuffs Group, Co., Ltd., Guangdong, China
| | - Dewu Liu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, China
| | - Wen Huang
- Department of Animal Science, Michigan State University, East Lansing, MI, United States
| | - Jie Yang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, China
| | - Zhenfang Wu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, China.,National Engineering Research Center for Breeding Swine Industry, Guangdong Wens Foodstuffs Group, Co., Ltd., Guangdong, China
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