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Chen Y, Wang Z, Qu X, Song B, Tang Y, Li B, Cao G, Yi G. An intronic SNP affects skeletal muscle development by regulating the expression of TP63. Front Vet Sci 2024; 11:1396766. [PMID: 38933706 PMCID: PMC11199888 DOI: 10.3389/fvets.2024.1396766] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2024] [Accepted: 05/28/2024] [Indexed: 06/28/2024] Open
Abstract
Background Porcine skeletal muscle development is pivotal for improving meat production. TP63, a transcription factor, regulates vital cellular processes, yet its role in skeletal muscle proliferation is unclear. Methods The effects of TP63 on skeletal muscle cell viability and proliferation were investigated using both mouse and porcine skeletal muscle myoblasts. Selective sweep analysis in Western pigs identified TP63 as a potential candidate gene for skeletal muscle development. The correlation between TP63 overexpression and cell proliferation was assessed using quantitative real-time PCR (RT-qPCR) and 5-ethynyl-2'-deoxyuridine (EDU). Results The study revealed a positive correlation between TP63 overexpression and skeletal muscle cell proliferation. Bioinformatics analysis predicted an interaction between MEF2A, another transcription factor, and the mutation site of TP63. Experimental validation through dual-luciferase assays confirmed that a candidate enhancer SNP could influence MEF2A binding, subsequently regulating TP63 expression and promoting skeletal muscle cell proliferation. Conclusion These findings offer experimental evidence for further exploration of skeletal muscle development mechanisms and the advancement of genetic breeding strategies aimed at improving meat production traits.
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Affiliation(s)
- Yufen Chen
- Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
- College of Animal Science, Shanxi Agricultural University, Jinzhong, China
| | - Zhen Wang
- Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Xiaolu Qu
- Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Bangmin Song
- Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Yueting Tang
- Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Bugao Li
- College of Animal Science, Shanxi Agricultural University, Jinzhong, China
| | - Guoqing Cao
- College of Animal Science, Shanxi Agricultural University, Jinzhong, China
| | - Guoqiang Yi
- Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
- Kunpeng Institute of Modern Agriculture at Foshan, Chinese Academy of Agricultural Sciences, Foshan, China
- Bama Yao Autonomous County Rural Revitalization Research Institute, Bama, China
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Zhou F, Lin D, Dong L, Hong Y, Zeng H, Cai G, Ye J, Wu Z. Genetic evaluation for production and body size traits using different animal models in purebred-Duroc pigs. Front Vet Sci 2023; 10:1274266. [PMID: 38164395 PMCID: PMC10758212 DOI: 10.3389/fvets.2023.1274266] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Accepted: 11/27/2023] [Indexed: 01/03/2024] Open
Abstract
Duroc pigs are popular crossbred terminal sires, and accurate assessment of genetic parameters in the population can help to rationalize breeding programmes. The principle aim of this study were to evaluate the genetic parameters of production (birth weight, BW; age at 115 kg, AGE; feed conversion ratio, FCR) and body size (body length, BL; body height, BH; front cannon circumference, FCC) traits of Duroc pigs. The second objective was to analyze the fit of different genetic assessment models. The variance components and correlations of BW (28,348 records), AGE (28,335 records), FCR (11,135 records), BL (31,544 records), BH (21,862 records), and FCC (14,684 records) traits were calculated by using DMU and AIREMLF90 from BLUPF90 package. In the common environment model, the heritability of BW, AGE, FCR, BL, BH, and FCC traits were 0.17 ± 0.014, 0.30 ± 0.019, 0.28 ± 0.024, 0.16 ± 0.013, 0.14 ± 0.017, and 0.081 ± 0.016, with common litter effect values of 0.25, 0.20, 0.18, 0.23, 0.19, and 0.16, respectively. According to the results of the Akaike information criterion (AIC) calculations, models with smaller AIC values have a better fit. We found that the common environment model with litter effects as random effects for estimating genetic parameters had a better fit. In this Model, the estimated genetic correlations between AGE with BW, FCR, BL, BH, and FCC traits were -0.28 (0.040), 0.76 (0.038), -0.71 (0.036), -0.44 (0.060), and -0.60 (0.073), respectively, with phenotypic correlations of -0.17, 0.52, -0.22, -0.13 and -0.24, respectively. In our analysis of genetic trends for six traits in the Duroc population from 2012 to 2021, we observed significant genetic trends for AGE, BL, and BH. Particularly noteworthy is the rapid decline in the genetic trend for AGE, indicating an enhancement in the pig's growth rate through selective breeding. Therefore, we believe that some challenging-to-select traits can benefit from the genetic correlations between traits. By selecting easily measurable traits, they can gain from synergistic selection effects, leading to genetic progress. Conducting population genetic parameter analysis can assist us in devising breeding strategies.
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Affiliation(s)
- Fuchen Zhou
- National Engineering Research Center for Breeding Swine Industry and College of Animal Science, South China Agricultural University, Guangzhou, China
| | - Danyang Lin
- National Engineering Research Center for Breeding Swine Industry and College of Animal Science, South China Agricultural University, Guangzhou, China
| | - Linsong Dong
- National Engineering Research Center for Breeding Swine Industry, Wens Foodstuff Group Co., Ltd., Yunfu, China
| | - Yifeng Hong
- National Engineering Research Center for Breeding Swine Industry and College of Animal Science, South China Agricultural University, Guangzhou, China
| | - Haiyu Zeng
- National Engineering Research Center for Breeding Swine Industry, Wens Foodstuff Group Co., Ltd., Yunfu, China
| | - Gengyuan Cai
- National Engineering Research Center for Breeding Swine Industry and College of Animal Science, South China Agricultural University, Guangzhou, China
- National Engineering Research Center for Breeding Swine Industry, Wens Foodstuff Group Co., Ltd., Yunfu, China
| | - Jian Ye
- National Engineering Research Center for Breeding Swine Industry, Wens Foodstuff Group Co., Ltd., Yunfu, China
| | - Zhenfang Wu
- National Engineering Research Center for Breeding Swine Industry and College of Animal Science, South China Agricultural University, Guangzhou, China
- National Engineering Research Center for Breeding Swine Industry, Wens Foodstuff Group Co., Ltd., Yunfu, China
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Panigrahi M, Rajawat D, Nayak SS, Ghildiyal K, Sharma A, Jain K, Lei C, Bhushan B, Mishra BP, Dutt T. Landmarks in the history of selective sweeps. Anim Genet 2023; 54:667-688. [PMID: 37710403 DOI: 10.1111/age.13355] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Accepted: 08/28/2023] [Indexed: 09/16/2023]
Abstract
Half a century ago, a seminal article on the hitchhiking effect by Smith and Haigh inaugurated the concept of the selection signature. Selective sweeps are characterised by the rapid spread of an advantageous genetic variant through a population and hence play an important role in shaping evolution and research on genetic diversity. The process by which a beneficial allele arises and becomes fixed in a population, leading to a increase in the frequency of other linked alleles, is known as genetic hitchhiking or genetic draft. Kimura's neutral theory and hitchhiking theory are complementary, with Kimura's neutral evolution as the 'null model' and positive selection as the 'signal'. Both are widely accepted in evolution, especially with genomics enabling precise measurements. Significant advances in genomic technologies, such as next-generation sequencing, high-density SNP arrays and powerful bioinformatics tools, have made it possible to systematically investigate selection signatures in a variety of species. Although the history of selection signatures is relatively recent, progress has been made in the last two decades, owing to the increasing availability of large-scale genomic data and the development of computational methods. In this review, we embark on a journey through the history of research on selective sweeps, ranging from early theoretical work to recent empirical studies that utilise genomic data.
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Affiliation(s)
- Manjit Panigrahi
- Division of Animal Genetics, Indian Veterinary Research Institute, Bareilly, India
| | - Divya Rajawat
- Division of Animal Genetics, Indian Veterinary Research Institute, Bareilly, India
| | | | - Kanika Ghildiyal
- Division of Animal Genetics, Indian Veterinary Research Institute, Bareilly, India
| | - Anurodh Sharma
- Division of Animal Genetics, Indian Veterinary Research Institute, Bareilly, India
| | - Karan Jain
- Division of Animal Genetics, Indian Veterinary Research Institute, Bareilly, India
| | - Chuzhao Lei
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, China
| | - Bharat Bhushan
- Division of Animal Genetics, Indian Veterinary Research Institute, Bareilly, India
| | - Bishnu Prasad Mishra
- Division of Animal Biotechnology, ICAR-National Bureau of Animal Genetic Resources, Karnal, India
| | - Triveni Dutt
- Livestock Production and Management Section, Indian Veterinary Research Institute, Bareilly, India
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Han Y, Tan T, Li Z, Ma Z, Lan G, Liang J, Li K, Bai L. Identification of Selection Signatures and Loci Associated with Important Economic Traits in Yunan Black and Huainan Pigs. Genes (Basel) 2023; 14:genes14030655. [PMID: 36980926 PMCID: PMC10048629 DOI: 10.3390/genes14030655] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Revised: 02/26/2023] [Accepted: 03/01/2023] [Indexed: 03/08/2023] Open
Abstract
Henan Province is located in central China and rich in domestic pig populations; Huainan (HN) pigs are one of three Henan indigenous breeds with great performance, including early maturation, strong disease resistance and high meat quality. Yunan (YN) black pigs are a typical, newly cultivated breed, synthesized between HN pigs and American Duroc, and are subjected to selection for important traits, such as fast growth and excellent meat quality. However, the genomic differences, selection signatures and loci associated with important economic traits in YN black pigs and HN pigs are still not well understood. In this study, based on high-density SNP chip analysis of 159 samples covering commercial DLY (Duroc × Landrace × Large White) pigs, HN pigs and YN black pigs, we performed a comprehensive analysis of phylogenetic relationships and genetic diversity among the three breeds. Furthermore, we used composite likelihood ratio tests (CLR) and F-statistics (Fst) to identify specific signatures of selection associated with important economic traits and potential candidate genes. We found 147 selected regions (top 1%) harboring 90 genes based on genetic differentiation (Fst) in the YN-DLY group. In the HN-DLY group, 169 selected regions harbored 58 genes. In the YN-HN group, 179 selected regions harbored 77 genes. In addition, the QTLs database with the most overlapping regions was associated with triglyceride level, number of mummified pigs, hemoglobin and loin muscle depth for YN black pigs, litter size and intramuscular fat content for HN pigs, and humerus length, linolenic acid content and feed conversion ratio mainly in DLY pigs. Of note, overlapping 14 tissue-specific promoters’ annotation with the top Fst 1% selective regions systematically demonstrated the muscle-specific and hypothalamus-specific regulatory elements in YN black pigs. Taken together, these results contribute to an accurate knowledge of crossbreeding, thus benefitting the evaluation of production performance and improving the genome-assisted breeding of other important indigenous pig in the future.
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Affiliation(s)
- Yachun Han
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China
| | - Tao Tan
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China
| | - Zixin Li
- College of Animal Science & Technology, Guangxi University, Nanning 530003, China
| | - Zheng Ma
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China
| | - Ganqiu Lan
- College of Animal Science & Technology, Guangxi University, Nanning 530003, China
| | - Jing Liang
- College of Animal Science & Technology, Guangxi University, Nanning 530003, China
| | - Kui Li
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China
| | - Lijing Bai
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China
- Correspondence: ; Tel./Fax: +86-0755-2325-0160
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Wang S, Yang J, Li G, Ding R, Zhuang Z, Ruan D, Wu J, Yang H, Zheng E, Cai G, Wang X, Wu Z. Identification of Homozygous Regions With Adverse Effects on the Five Economic Traits of Duroc Pigs. Front Vet Sci 2022; 9:855933. [PMID: 35573406 PMCID: PMC9096619 DOI: 10.3389/fvets.2022.855933] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2022] [Accepted: 03/28/2022] [Indexed: 11/13/2022] Open
Abstract
Runs of homozygosity (ROH) are widely used to estimate genomic inbreeding, which is linked to inbreeding depression on phenotypes. However, the adverse effects of specific homozygous regions on phenotypic characteristics are rarely studied in livestock. In this study, the 50 K SNP data of 3,770 S21 Duroc (American origin) and 2,096 S22 Duroc (Canadian origin) pigs were used to investigate the harmful ROH regions on five economic traits. The results showed that the two Duroc lines had different numbers and distributions of unfavorable ROHs, which may be related to the different selection directions and intensities between the two lines. A total of 114 and 58 ROH segments were found with significant adverse effects on the economic traits of S21 and S22 pigs, respectively. Serval pleiotropic ROHs were detected to reduce two or multiple phenotypic performances in two Duroc populations. Candidate genes in these shared regions were mainly related to growth, fertility, immunity, and fat deposition. We also observed that some ROH genotypes may cause opposite effects on different traits. This study not only enhances our understanding of the adverse effects of ROH on phenotypes, but also indicates that ROH information could be incorporated into breeding programs to estimate and control the detrimental effects of homozygous regions.
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Affiliation(s)
- Shiyuan Wang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
| | - Jie Yang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
- Guangdong Provincial Laboratory of Lingnan Modern Agricultural Science and Technology, Guangzhou, China
| | - Guixin Li
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
| | - Rongrong Ding
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
| | - Zhanwei Zhuang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
| | - Donglin Ruan
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
| | - Jie Wu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
| | - Huaqiang Yang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
| | - Enqin Zheng
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
| | - Gengyuan Cai
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
| | - Xiaopeng Wang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
- *Correspondence: Xiaopeng Wang
| | - Zhenfang Wu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
- Guangdong Provincial Laboratory of Lingnan Modern Agricultural Science and Technology, Guangzhou, China
- Zhenfang Wu
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6
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Yang W, Liu Z, Zhao Q, Du H, Yu J, Wang H, Liu X, Liu H, Jing X, Yang H, Shi G, Zhou L, Liu J. Population Genetic Structure and Selection Signature Analysis of Beijing Black Pig. Front Genet 2022; 13:860669. [PMID: 35401688 PMCID: PMC8987279 DOI: 10.3389/fgene.2022.860669] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2022] [Accepted: 03/08/2022] [Indexed: 12/04/2022] Open
Abstract
Beijing Black pig is an excellent cultivated black pig breed in China, with desirable body shape, tender meat quality and robust disease resistance. To explore the level of admixture and selection signatures of Beijing Black pigs, a total number of 90 individuals covering nine pig breeds were used in our study, including Beijing Black pig, Large White, Landrace, Duroc, Lantang pig, Luchuan pig, Mashen pig, Huainan pig and Min pig. These animals were resequenced with 18.19 folds mapped read depth on average. Generally, we found that Beijing Black pig was genetically closer to commercial pig breeds by population genetic structure and genetic diversity analysis, and was also affected by Chinese domestic breeds Huainan pig and Min pig. These results are consistent with the cross-breeding history of Beijing Black pig. Selection signal detections were performed on three pig breeds, Beijing Black pig, Duroc and Large White, using three complementary methods (FST, θπ, and XP-EHH). In total, 1,167 significant selected regions and 392 candidate genes were identified. Functional annotations were enriched to pathways related to immune processes and meat and lipid metabolism. Finally, potential candidate genes, influencing meat quality (GPHA2, EHD1, HNF1A, C12orf43, GLTP, TRPV4, MVK, and MMAB), reproduction (PPP2R5B and MAP9), and disease resistance (OASL, ANKRD13A, and GIT2), were further detected by gene annotation analysis. Our results advanced the understanding of the genetic mechanism behind artificial selection of Beijing Black pigs, and provided theoretical basis for the subsequent breeding and genetic research of this breed.
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Affiliation(s)
- Wenjing Yang
- College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Zhen Liu
- College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Qiqi Zhao
- College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Heng Du
- College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Jian Yu
- College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Hongwei Wang
- Beijing Heiliu Stockbreeding Technology Co.,Ltd, Beijing, China
| | - Xiance Liu
- Beijing Heiliu Stockbreeding Technology Co.,Ltd, Beijing, China
| | - Hai Liu
- Beijing Heiliu Stockbreeding Technology Co.,Ltd, Beijing, China
| | - Xitao Jing
- Beijing Heiliu Stockbreeding Technology Co.,Ltd, Beijing, China
| | - Hongping Yang
- Beijing Heiliu Stockbreeding Technology Co.,Ltd, Beijing, China
| | - Guohua Shi
- Beijing Heiliu Stockbreeding Technology Co.,Ltd, Beijing, China
| | - Lei Zhou
- College of Animal Science and Technology, China Agricultural University, Beijing, China
- *Correspondence: Lei Zhou, ; Jianfeng Liu,
| | - Jianfeng Liu
- College of Animal Science and Technology, China Agricultural University, Beijing, China
- *Correspondence: Lei Zhou, ; Jianfeng Liu,
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7
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Wang X, Li G, Ruan D, Zhuang Z, Ding R, Quan J, Wang S, Jiang Y, Huang J, Gu T, Hong L, Zheng E, Li Z, Cai G, Wu Z, Yang J. Runs of Homozygosity Uncover Potential Functional-Altering Mutation Associated With Body Weight and Length in Two Duroc Pig Lines. Front Vet Sci 2022; 9:832633. [PMID: 35350434 PMCID: PMC8957889 DOI: 10.3389/fvets.2022.832633] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Accepted: 01/24/2022] [Indexed: 12/29/2022] Open
Abstract
Runs of homozygosity (ROH) are widely used to investigate genetic diversity, demographic history, and positive selection signatures of livestock. Commercial breeds provide excellent materials to reveal the landscape of ROH shaped during the intense selection process. Here, we used the GeneSeek Porcine 50K single-nucleotide polymorphism (SNP) Chip data of 3,770 American Duroc (AD) and 2,096 Canadian Duroc (CD) pigs to analyze the genome-wide ROH. First, we showed that AD had a moderate genetic differentiation with CD pigs, and AD had more abundant genetic diversity and significantly lower level of inbreeding than CD pigs. In addition, sows had larger levels of homozygosity than boars in AD pigs. These differences may be caused by differences in the selective intensity. Next, ROH hotspots revealed that many candidate genes are putatively under selection for growth, sperm, and muscle development in two lines. Population-specific ROHs inferred that AD pigs may have a special selection for female reproduction, while CD pigs may have a special selection for immunity. Moreover, in the overlapping ROH hotspots of two Duroc populations, we observed a missense mutation (rs81216249) located in the growth and fat deposition-related supergene (ARSB-DMGDH-BHMT) region. The derived allele of this variant originated from European pigs and was nearly fixed in Duroc pigs. Further selective sweep and association analyses indicated that this supergene was subjected to strong selection and probably contributed to the improvement of body weight and length in Duroc pigs. These findings will enhance our understanding of ROH patterns in different Duroc lines and provide promising trait-related genes and a functional-altering marker that can be used for genetic improvement of pigs.
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Affiliation(s)
- Xiaopeng Wang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
| | - Guixin Li
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
| | - Donglin Ruan
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
| | - Zhanwei Zhuang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
| | - Rongrong Ding
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
- Guangdong Wens Breeding Swine Technology Co., Ltd., Yunfu, China
| | - Jianping Quan
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
| | - Shiyuan Wang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
| | - Yongchuang Jiang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
| | - Jinyan Huang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
| | - Ting Gu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
| | - Linjun Hong
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
| | - Enqin Zheng
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
| | - Zicong Li
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
| | - Gengyuan Cai
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
- Guangdong Wens Breeding Swine Technology Co., Ltd., Yunfu, China
| | - Zhenfang Wu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
- Guangdong Wens Breeding Swine Technology Co., Ltd., Yunfu, China
- Guangdong Provincial Laboratory of Lingnan Modern Agricultural Science and Technology, Guangzhou, China
- *Correspondence: Zhenfang Wu
| | - Jie Yang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
- Guangdong Provincial Laboratory of Lingnan Modern Agricultural Science and Technology, Guangzhou, China
- Jie Yang
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8
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Chebii VJ, Mpolya EA, Muchadeyi FC, Domelevo Entfellner JB. Genomics of Adaptations in Ungulates. Animals (Basel) 2021; 11:1617. [PMID: 34072591 PMCID: PMC8230064 DOI: 10.3390/ani11061617] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Revised: 05/22/2021] [Accepted: 05/23/2021] [Indexed: 11/16/2022] Open
Abstract
Ungulates are a group of hoofed animals that have long interacted with humans as essential sources of food, labor, clothing, and transportation. These consist of domesticated, feral, and wild species raised in a wide range of habitats and biomes. Given the diverse and extreme environments inhabited by ungulates, unique adaptive traits are fundamental for fitness. The documentation of genes that underlie their genomic signatures of selection is crucial in this regard. The increasing availability of advanced sequencing technologies has seen the rapid growth of ungulate genomic resources, which offers an exceptional opportunity to understand their adaptive evolution. Here, we summarize the current knowledge on evolutionary genetic signatures underlying the adaptations of ungulates to different habitats.
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Affiliation(s)
- Vivien J. Chebii
- School of Life Science and Bioengineering, Nelson Mandela Africa Institution of Science and Technology, P.O. Box 447, Arusha, Tanzania;
- Biosciences Eastern and Central Africa, International Livestock Research Institute (BecA-ILRI) Hub, P.O. Box 30709, Nairobi 00100, Kenya;
| | - Emmanuel A. Mpolya
- School of Life Science and Bioengineering, Nelson Mandela Africa Institution of Science and Technology, P.O. Box 447, Arusha, Tanzania;
| | - Farai C. Muchadeyi
- Agricultural Research Council Biotechnology Platform (ARC-BTP), Private Bag X5, Onderstepoort 0110, South Africa;
| | - Jean-Baka Domelevo Entfellner
- Biosciences Eastern and Central Africa, International Livestock Research Institute (BecA-ILRI) Hub, P.O. Box 30709, Nairobi 00100, Kenya;
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9
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Karimi K, Farid AH, Myles S, Miar Y. Detection of selection signatures for response to Aleutian mink disease virus infection in American mink. Sci Rep 2021; 11:2944. [PMID: 33536540 PMCID: PMC7859209 DOI: 10.1038/s41598-021-82522-8] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2020] [Accepted: 01/21/2021] [Indexed: 02/06/2023] Open
Abstract
Aleutian disease (AD) is the most significant health issue for farmed American mink. The objective of this study was to identify the genomic regions subjected to selection for response to infection with Aleutian mink disease virus (AMDV) in American mink using genotyping by sequencing (GBS) data. A total of 225 black mink were inoculated with AMDV and genotyped using a GBS assay based on the sequencing of ApeKI-digested libraries. Five AD-characterized phenotypes were used to assign animals to pairwise groups. Signatures of selection were detected using integrated measurement of fixation index (FST) and nucleotide diversity (θπ), that were validated by haplotype-based (hap-FLK) test. The total of 99 putatively selected regions harbouring 63 genes were detected in different groups. The gene ontology revealed numerous genes related to immune response (e.g. TRAF3IP2, WDR7, SWAP70, CBFB, and GPR65), liver development (e.g. SULF2, SRSF5) and reproduction process (e.g. FBXO5, CatSperβ, CATSPER4, and IGF2R). The hapFLK test supported two strongly selected regions that contained five candidate genes related to immune response, virus–host interaction, reproduction and liver regeneration. This study provided the first map of putative selection signals of response to AMDV infection in American mink, bringing new insights into genomic regions controlling the AD phenotypes.
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Affiliation(s)
- Karim Karimi
- Department of Animal Science and Aquaculture, Dalhousie University, Truro, NS, Canada
| | - A Hossain Farid
- Department of Animal Science and Aquaculture, Dalhousie University, Truro, NS, Canada
| | - Sean Myles
- Department of Plant, Food, and Environmental Sciences, Dalhousie University, Truro, NS, Canada
| | - Younes Miar
- Department of Animal Science and Aquaculture, Dalhousie University, Truro, NS, Canada.
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Zhang S, Zhang K, Peng X, Zhan H, Lu J, Xie S, Zhao S, Li X, Ma Y. Selective sweep analysis reveals extensive parallel selection traits between large white and Duroc pigs. Evol Appl 2020; 13:2807-2820. [PMID: 33294024 PMCID: PMC7691457 DOI: 10.1111/eva.13085] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2020] [Revised: 07/27/2020] [Accepted: 07/28/2020] [Indexed: 12/19/2022] Open
Abstract
In the process of pig genetic improvement, different commercial breeds have been bred for the same purpose, improving meat production. Most of the economic traits, such as growth and fertility, have been selected similarly despite the discrepant selection pressure, which is known as parallel selection. Here, 28 whole-genome sequencing data of Danish large white pigs with an approximately 25-fold depth each were generated, resulting in about 12 million high-quality SNPs for each individual. Combined with the sequencing data of 27 Duroc and 23 European wild boars, we investigated the parallel selection of Danish large white and Duroc pigs using two complementary methods, Fst and iHS. In total, 67 candidate regions were identified as the signatures of parallel selection. The genes in candidate regions of parallel selection were mainly associated with sensory perception, growth rate, and body size. Further functional annotation suggested that the striking consistency of the terms may be caused by the polygenetic basis of quantitative traits, and revealing the complex genetic basis of parallel selection. Besides, some unique terms were enriched in population-specific selection regions, such as the limb development-related terms enriched in Duroc-specific selection regions, suggesting unique selections of breed-specific selected traits. These results will help us better understand the parallel selection process of different breeds. Moreover, we identified several potential causal SNPs that may contribute to the pig genetic breeding process.
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Affiliation(s)
- Saixian Zhang
- Key Laboratory of Agricultural Animal Genetics, Breeding, and Reproduction of the Ministry of Education & Key Laboratory of Swine Genetics and Breeding of the Ministry of AgricultureHuazhong Agricultural UniversityWuhanChina
| | - Kaili Zhang
- Key Laboratory of Agricultural Animal Genetics, Breeding, and Reproduction of the Ministry of Education & Key Laboratory of Swine Genetics and Breeding of the Ministry of AgricultureHuazhong Agricultural UniversityWuhanChina
| | - Xia Peng
- Key Laboratory of Agricultural Animal Genetics, Breeding, and Reproduction of the Ministry of Education & Key Laboratory of Swine Genetics and Breeding of the Ministry of AgricultureHuazhong Agricultural UniversityWuhanChina
| | - Huiwen Zhan
- Key Laboratory of Agricultural Animal Genetics, Breeding, and Reproduction of the Ministry of Education & Key Laboratory of Swine Genetics and Breeding of the Ministry of AgricultureHuazhong Agricultural UniversityWuhanChina
| | - Jiahui Lu
- Key Laboratory of Agricultural Animal Genetics, Breeding, and Reproduction of the Ministry of Education & Key Laboratory of Swine Genetics and Breeding of the Ministry of AgricultureHuazhong Agricultural UniversityWuhanChina
| | - Shengsong Xie
- Key Laboratory of Agricultural Animal Genetics, Breeding, and Reproduction of the Ministry of Education & Key Laboratory of Swine Genetics and Breeding of the Ministry of AgricultureHuazhong Agricultural UniversityWuhanChina
| | - Shuhong Zhao
- Key Laboratory of Agricultural Animal Genetics, Breeding, and Reproduction of the Ministry of Education & Key Laboratory of Swine Genetics and Breeding of the Ministry of AgricultureHuazhong Agricultural UniversityWuhanChina
| | - Xinyun Li
- Key Laboratory of Agricultural Animal Genetics, Breeding, and Reproduction of the Ministry of Education & Key Laboratory of Swine Genetics and Breeding of the Ministry of AgricultureHuazhong Agricultural UniversityWuhanChina
| | - Yunlong Ma
- Key Laboratory of Agricultural Animal Genetics, Breeding, and Reproduction of the Ministry of Education & Key Laboratory of Swine Genetics and Breeding of the Ministry of AgricultureHuazhong Agricultural UniversityWuhanChina
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11
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Liu Y, Liu X, Zheng Z, Ma T, Liu Y, Long H, Cheng H, Fang M, Gong J, Li X, Zhao S, Xu X. Genome-wide analysis of expression QTL (eQTL) and allele-specific expression (ASE) in pig muscle identifies candidate genes for meat quality traits. Genet Sel Evol 2020; 52:59. [PMID: 33036552 PMCID: PMC7547458 DOI: 10.1186/s12711-020-00579-x] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2019] [Accepted: 09/28/2020] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND Genetic analysis of gene expression level is a promising approach for characterizing candidate genes that are involved in complex economic traits such as meat quality. In the present study, we conducted expression quantitative trait loci (eQTL) and allele-specific expression (ASE) analyses based on RNA-sequencing (RNAseq) data from the longissimus muscle of 189 Duroc × Luchuan crossed pigs in order to identify some candidate genes for meat quality traits. RESULTS Using a genome-wide association study based on a mixed linear model, we identified 7192 cis-eQTL corresponding to 2098 cis-genes (p ≤ 1.33e-3, FDR ≤ 0.05) and 6400 trans-eQTL corresponding to 863 trans-genes (p ≤ 1.13e-6, FDR ≤ 0.05). ASE analysis using RNAseq SNPs identified 9815 significant ASE-SNPs in 2253 unique genes. Integrative analysis between the cis-eQTL and ASE target genes identified 540 common genes, including 33 genes with expression levels that were correlated with at least one meat quality trait. Among these 540 common genes, 63 have been reported previously as candidate genes for meat quality traits, such as PHKG1 (q-value = 1.67e-6 for the leading SNP in the cis-eQTL analysis), NUDT7 (q-value = 5.67e-13), FADS2 (q-value = 8.44e-5), and DGAT2 (q-value = 1.24e-3). CONCLUSIONS The present study confirmed several previously published candidate genes and identified some novel candidate genes for meat quality traits via eQTL and ASE analyses, which will be useful to prioritize candidate genes in further studies.
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Affiliation(s)
- Yan Liu
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070 China
- The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070 China
- Key Lab of Swine Genetics and Breeding of Ministry of Agriculture and Rural Affairs, Wuhan, 430070 China
| | - Xiaolei Liu
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070 China
- The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070 China
- Key Lab of Swine Genetics and Breeding of Ministry of Agriculture and Rural Affairs, Wuhan, 430070 China
| | - Zhiwei Zheng
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070 China
- The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070 China
- Key Lab of Swine Genetics and Breeding of Ministry of Agriculture and Rural Affairs, Wuhan, 430070 China
| | - Tingting Ma
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070 China
- The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070 China
- Key Lab of Swine Genetics and Breeding of Ministry of Agriculture and Rural Affairs, Wuhan, 430070 China
| | - Ying Liu
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070 China
- The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070 China
- Key Lab of Swine Genetics and Breeding of Ministry of Agriculture and Rural Affairs, Wuhan, 430070 China
| | - Huan Long
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070 China
- The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070 China
- Key Lab of Swine Genetics and Breeding of Ministry of Agriculture and Rural Affairs, Wuhan, 430070 China
| | - Huijun Cheng
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070 China
- The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070 China
- Key Lab of Swine Genetics and Breeding of Ministry of Agriculture and Rural Affairs, Wuhan, 430070 China
| | - Ming Fang
- Key Laboratory of Healthy Mariculture for the East China Sea, Ministry of Agriculture and Rural Affairs, Fisheries College, Jimei University, Xiamen, 361021 China
| | - Jing Gong
- Colleges of Informatics, Huazhong Agricultural University, Wuhan, 430070 China
| | - Xinyun Li
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070 China
- The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070 China
- Key Lab of Swine Genetics and Breeding of Ministry of Agriculture and Rural Affairs, Wuhan, 430070 China
| | - Shuhong Zhao
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070 China
- The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070 China
- Key Lab of Swine Genetics and Breeding of Ministry of Agriculture and Rural Affairs, Wuhan, 430070 China
| | - Xuewen Xu
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070 China
- The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070 China
- Key Lab of Swine Genetics and Breeding of Ministry of Agriculture and Rural Affairs, Wuhan, 430070 China
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12
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Zhou Z, Fan Y, Wang G, Lai Z, Gao Y, Wu F, Lei C, Dang R. Detection of Selection Signatures Underlying Production and Adaptive Traits Based on Whole-Genome Sequencing of Six Donkey Populations. Animals (Basel) 2020; 10:ani10101823. [PMID: 33036357 PMCID: PMC7600737 DOI: 10.3390/ani10101823] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2020] [Revised: 10/01/2020] [Accepted: 10/03/2020] [Indexed: 12/28/2022] Open
Abstract
Simple Summary After a long period of artificial selection, the donkey now presents a variety of body types and production performance values. In this experiment, we performed selective signal scanning on the second-generation resequencing data of six different varieties. The regions and candidate genes related to artificial selection were identified to provide reference for future breeding. Abstract Donkeys (Equus asinus) are an important farm animal. After long-term natural and artificial selection, donkeys now exhibit a variety of body sizes and production performance values. In this study, six donkey breeds, representing different regions and phenotypes, were used for second-generation resequencing. The sequencing results revealed more than seven million single nucleotide variants (SNVs), with an average of more than four million SNVs per species. We combined two methods, Z-transformed heterozygosity (ZHp) and unbiased estimates of pairwise fixation index (di) values, to analyze the signatures of selection. We mapped 11 selected regions and identified genes associated with coat color, body size, motion capacity, and high-altitude adaptation. These candidate genes included staining (ASIP and KITLG), body type (ACSL4, BCOR, CDKL5, LCOR, NCAPG, and TBX3), exercise (GABPA), and adaptation to low-oxygen environments (GLDC and HBB). We also analyzed the SNVs of the breed-specific genes for their potential functions and found that there are three varieties in the conserved regions with breed-specific mutation sites. Our results provide data to support the establishment of the donkey SNV chip and reference information for the utilization of the genetic resources of Chinese domestic donkeys.
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13
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Genome-Wide Detection of Selection Signatures in Duroc Revealed Candidate Genes Relating to Growth and Meat Quality. G3-GENES GENOMES GENETICS 2020; 10:3765-3773. [PMID: 32859686 PMCID: PMC7534417 DOI: 10.1534/g3.120.401628] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
With the development of high-throughput genotyping techniques, selection signatures in the genome of domestic pigs have been extensively interrogated in the last decade. The Duroc, a major commercial pig breed famous for its fast growth rate and high lean ratio, has not been extensively studied focusing on footprints of intensively artificial selection in their genomes by a lot of re-sequencing data. The goal of this study was to investigate genomic regions under artificial selection and their contribution to the unique phenotypic traits of the Duroc using whole-genome resequencing data from 97 pigs. Three complementary methods (di, CLR, and iHH12) were implemented for selection signature detection. In Total, 464 significant candidate regions were identified, which covered 46.4 Mb of the pig genome. Within the identified regions, 709 genes were annotated, including 600 candidate protein-coding genes (486 functionally annotated genes) and 109 lncRNA genes. Genes undergoing selective pressure were significantly enriched in the insulin resistance signaling pathway, which may partly explain the difference between the Duroc and other breeds in terms of growth rate. The selection signatures identified in the Duroc population demonstrated positive pressures on a set of important genes with potential functions that are involved in many biological processes. The results provide new insights into the genetic mechanisms of fast growth rate and high lean mass, and further facilitate follow-up studies on functional genes that contribute to the Duroc's excellent phenotypic traits.
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14
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Bovo S, Ribani A, Muñoz M, Alves E, Araujo JP, Bozzi R, Čandek-Potokar M, Charneca R, Di Palma F, Etherington G, Fernandez AI, García F, García-Casco J, Karolyi D, Gallo M, Margeta V, Martins JM, Mercat MJ, Moscatelli G, Núñez Y, Quintanilla R, Radović Č, Razmaite V, Riquet J, Savić R, Schiavo G, Usai G, Utzeri VJ, Zimmer C, Ovilo C, Fontanesi L. Whole-genome sequencing of European autochthonous and commercial pig breeds allows the detection of signatures of selection for adaptation of genetic resources to different breeding and production systems. Genet Sel Evol 2020; 52:33. [PMID: 32591011 PMCID: PMC7318759 DOI: 10.1186/s12711-020-00553-7] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2019] [Accepted: 06/17/2020] [Indexed: 12/21/2022] Open
Abstract
Background Natural and artificial directional selection in cosmopolitan and autochthonous pig breeds and wild boars have shaped their genomes and resulted in a reservoir of animal genetic diversity. Signatures of selection are the result of these selection events that have contributed to the adaptation of breeds to different environments and production systems. In this study, we analysed the genome variability of 19 European autochthonous pig breeds (Alentejana, Bísara, Majorcan Black, Basque, Gascon, Apulo-Calabrese, Casertana, Cinta Senese, Mora Romagnola, Nero Siciliano, Sarda, Krškopolje pig, Black Slavonian, Turopolje, Moravka, Swallow-Bellied Mangalitsa, Schwäbisch-Hällisches Schwein, Lithuanian indigenous wattle and Lithuanian White old type) from nine countries, three European commercial breeds (Italian Large White, Italian Landrace and Italian Duroc), and European wild boars, by mining whole-genome sequencing data obtained by using a DNA-pool sequencing approach. Signatures of selection were identified by using a single-breed approach with two statistics [within-breed pooled heterozygosity (HP) and fixation index (FST)] and group-based FST approaches, which compare groups of breeds defined according to external traits and use/specialization/type. Results We detected more than 22 million single nucleotide polymorphisms (SNPs) across the 23 compared populations and identified 359 chromosome regions showing signatures of selection. These regions harbour genes that are already known or new genes that are under selection and relevant for the domestication process in this species, and that affect several morphological and physiological traits (e.g. coat colours and patterns, body size, number of vertebrae and teats, ear size and conformation, reproductive traits, growth and fat deposition traits). Wild boar related signatures of selection were detected across all the genome of several autochthonous breeds, which suggests that crossbreeding (accidental or deliberate) occurred with wild boars. Conclusions Our findings provide a catalogue of genetic variants of many European pig populations and identify genome regions that can explain, at least in part, the phenotypic diversity of these genetic resources.
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Affiliation(s)
- Samuele Bovo
- Department of Agricultural and Food Sciences, Division of Animal Sciences, University of Bologna, Viale Fanin 46, 40127, Bologna, Italy
| | - Anisa Ribani
- Department of Agricultural and Food Sciences, Division of Animal Sciences, University of Bologna, Viale Fanin 46, 40127, Bologna, Italy
| | - Maria Muñoz
- Departamento Mejora Genética Animal, INIA, Crta. de la Coruña km. 7,5, 28040, Madrid, Spain
| | - Estefania Alves
- Departamento Mejora Genética Animal, INIA, Crta. de la Coruña km. 7,5, 28040, Madrid, Spain
| | - Jose P Araujo
- Centro de Investigação de Montanha (CIMO), Instituto Politécnico de Viana do Castelo, Escola Superior Agrária, Refóios do Lima, 4990-706, Ponte de Lima, Portugal
| | - Riccardo Bozzi
- DAGRI - Animal Science Section, Università di Firenze, Via delle Cascine 5, 50144, Florence, Italy
| | | | - Rui Charneca
- Instituto de Ciências Agrárias e Ambientais Mediterrânicas (ICAAM), Universidade de Évora, Polo da Mitra, Apartado 94, 7006-554, Évora, Portugal
| | - Federica Di Palma
- Earlham Institute, Norwich Research Park, Colney Lane, Norwich, NR47UZ, UK
| | - Graham Etherington
- Earlham Institute, Norwich Research Park, Colney Lane, Norwich, NR47UZ, UK
| | - Ana I Fernandez
- Departamento Mejora Genética Animal, INIA, Crta. de la Coruña km. 7,5, 28040, Madrid, Spain
| | - Fabián García
- Departamento Mejora Genética Animal, INIA, Crta. de la Coruña km. 7,5, 28040, Madrid, Spain
| | - Juan García-Casco
- Departamento Mejora Genética Animal, INIA, Crta. de la Coruña km. 7,5, 28040, Madrid, Spain
| | - Danijel Karolyi
- Department of Animal Science, Faculty of Agriculture, University of Zagreb, Svetošimunska c. 25, 10000, Zagreb, Croatia
| | - Maurizio Gallo
- Associazione Nazionale Allevatori Suini (ANAS), Via Nizza 53, 00198, Rome, Italy
| | - Vladimir Margeta
- Faculty of Agrobiotechnical Sciences, University of Osijek, Vladimira Preloga 1, 31000, Osijek, Croatia
| | - José Manuel Martins
- Instituto de Ciências Agrárias e Ambientais Mediterrânicas (ICAAM), Universidade de Évora, Polo da Mitra, Apartado 94, 7006-554, Évora, Portugal
| | - Marie J Mercat
- IFIP Institut du porc, La Motte au Vicomte, BP 35104, 35651, Le Rheu Cedex, France
| | - Giulia Moscatelli
- Department of Agricultural and Food Sciences, Division of Animal Sciences, University of Bologna, Viale Fanin 46, 40127, Bologna, Italy
| | - Yolanda Núñez
- Departamento Mejora Genética Animal, INIA, Crta. de la Coruña km. 7,5, 28040, Madrid, Spain
| | - Raquel Quintanilla
- Programa de Genética y Mejora Animal, IRTA, Torre Marimon, 08140, Caldes de Montbui, Barcelona, Spain
| | - Čedomir Radović
- Department of Pig Breeding and Genetics, Institute for Animal Husbandry, Belgrade-Zemun, 11080, Serbia
| | - Violeta Razmaite
- Animal Science Institute, Lithuanian University of Health Sciences, Baisogala, Lithuania
| | - Juliette Riquet
- GenPhySE, INRAE, Université de Toulouse, Chemin de Borde-Rouge 24, Auzeville Tolosane, 31326, Castanet Tolosan, France
| | - Radomir Savić
- Faculty of Agriculture, University of Belgrade, Nemanjina 6, Belgrade-Zemun, 11080, Serbia
| | - Giuseppina Schiavo
- Department of Agricultural and Food Sciences, Division of Animal Sciences, University of Bologna, Viale Fanin 46, 40127, Bologna, Italy
| | - Graziano Usai
- AGRIS SARDEGNA, Loc. Bonassai, 07100, Sassari, Italy
| | - Valerio J Utzeri
- Department of Agricultural and Food Sciences, Division of Animal Sciences, University of Bologna, Viale Fanin 46, 40127, Bologna, Italy
| | - Christoph Zimmer
- Bäuerliche Erzeugergemeinschaft Schwäbisch Hall, Schwäbisch Hall, Germany
| | - Cristina Ovilo
- Departamento Mejora Genética Animal, INIA, Crta. de la Coruña km. 7,5, 28040, Madrid, Spain
| | - Luca Fontanesi
- Department of Agricultural and Food Sciences, Division of Animal Sciences, University of Bologna, Viale Fanin 46, 40127, Bologna, Italy.
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Wang X, Cheng J, Qin W, Chen H, Chen G, Shang X, Zhang M, Balsai N, Chen H. Polymorphisms in 5' proximal regulating region of THRSP gene are associated with fat production in pigs. 3 Biotech 2020; 10:267. [PMID: 32509500 DOI: 10.1007/s13205-020-02266-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2020] [Accepted: 05/18/2020] [Indexed: 01/17/2023] Open
Abstract
Chinese and imported pig breeds differ in fat production potential, which is associated with the polymorphisms in the 5' proximal regulating region (5'PRR) of thyroid hormone responsive gene (THRSP). In three Chinese breeds (Dingyuan, CDY; Wannanhua, CWH; and Jixi, CJX) and one introduced breed (Yorkshire, YKS), three variant sites were located at T/C-400, A/G-376, and G/A-98 in the 5'PRR. Chinese pig breeds had higher C-400 allele frequencies than YKS. The frequencies of A-376 in CDY and G-376 in CWH were about 0.8. G-98 allele frequencies in CWH and YKS were 0.8617 and 0.8149, respectively. TGG was the dominant haplotype in YKS, CGG in CWH and CJX, and CAA in CDY. According to haplotype frequency, four breeds were clustered into three types, which was consistent with the geographical distribution of the breeds. In CDY, the average backfat thickness (BFT) was the highest with the CC-400 genotype, followed by CT-400 and TT-400 genotypes. In YKS, the pigs with CC-400 or CT-400 genotypes had higher BFT and average daily weight gain, whereas those with CC-400 or TT-400 genotypes had larger lion-eye area. No significant difference was observed in carcass traits among different genotypes at the A/G-376 and G/A-98 loci. The mRNA abundance of THRSP expression for the CCAGAG genotype was significantly higher than that for CTAGAG or TTAGAG genotype. These results indicated that the polymorphisms and genotype distribution of THRSP were closely related to the potential for fat production in pig breeds, which were the result of adaptation to artificial selection and natural selection.
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Affiliation(s)
- Xiaohong Wang
- School of Animal Science and Technology, Anhui Agricultural University, Hefei, 230036 China
- Experimental Animal Center of Anhui Medical University, Hefei, 230032 China
| | - Jin Cheng
- School of Animal Science and Technology, Anhui Agricultural University, Hefei, 230036 China
| | - Wenjuan Qin
- School of Animal Science and Technology, Anhui Agricultural University, Hefei, 230036 China
- Anhui Agricultural University International Immunization Center, Hefei, 230036 China
| | - Hua Chen
- School of Animal Science and Technology, Anhui Agricultural University, Hefei, 230036 China
| | - Gongwei Chen
- School of Animal Science and Technology, Anhui Agricultural University, Hefei, 230036 China
| | - Xuanjian Shang
- School of Animal Science and Technology, Anhui Agricultural University, Hefei, 230036 China
| | - Mengting Zhang
- School of Animal Science and Technology, Anhui Agricultural University, Hefei, 230036 China
| | - Nyamsuren Balsai
- School of Animal Science and Technology, Anhui Agricultural University, Hefei, 230036 China
| | - Hongquan Chen
- School of Animal Science and Technology, Anhui Agricultural University, Hefei, 230036 China
- Key Laboratory of Local Livestock and Poultry Genetic Resources Conservation and Biobreeding of Anhui Province, Hefei, 230036 China
- Anhui Agricultural University International Immunization Center, Hefei, 230036 China
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Ma H, Zhang S, Zhang K, Zhan H, Peng X, Xie S, Li X, Zhao S, Ma Y. Identifying Selection Signatures for Backfat Thickness in Yorkshire Pigs Highlights New Regions Affecting Fat Metabolism. Genes (Basel) 2019; 10:genes10040254. [PMID: 30925743 PMCID: PMC6523431 DOI: 10.3390/genes10040254] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2019] [Revised: 03/23/2019] [Accepted: 03/26/2019] [Indexed: 02/07/2023] Open
Abstract
Identifying the genetic basis of improvement in pigs contributes to our understanding of the role of artificial selection in shaping the genome. Here we employed the Cross Population Extended Haplotype Homozogysity (XPEHH) and the Wright's fixation index (FST) methods to detect trait-specific selection signatures by making phenotypic gradient differential population pairs, and then attempted to map functional genes of six backfat thickness traits in Yorkshire pigs. The results indicate that a total of 283 and 466 single nucleotide polymorphisms (SNPs) were identified as trait-specific selection signatures using FST and XPEHH, respectively. Functional annotation suggested that the genes overlapping with the trait-specific selection signatures such as OSBPL8, ASAH2, SMCO2, GBE1, and ABL1 are responsible for the phenotypes including fat metabolism, lean body mass and fat deposition, and transport in mouse. Overall, the study developed the methods of gene mapping on the basis of identification of selection signatures. The candidate genes putatively associated with backfat thickness traits can provide important references and fundamental information for future pig-breeding programs.
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Affiliation(s)
- Haoran Ma
- Key Laboratory of Agricultural Animal Genetics, Breeding, and Reproduction of the Ministry of Education & Key Laboratory of Swine Genetics and Breeding of the Ministry of Agriculture, Huazhong Agricultural University, Wuhan 430070, China.
| | - Saixian Zhang
- Key Laboratory of Agricultural Animal Genetics, Breeding, and Reproduction of the Ministry of Education & Key Laboratory of Swine Genetics and Breeding of the Ministry of Agriculture, Huazhong Agricultural University, Wuhan 430070, China.
| | - Kaili Zhang
- Key Laboratory of Agricultural Animal Genetics, Breeding, and Reproduction of the Ministry of Education & Key Laboratory of Swine Genetics and Breeding of the Ministry of Agriculture, Huazhong Agricultural University, Wuhan 430070, China.
| | - Huiwen Zhan
- Key Laboratory of Agricultural Animal Genetics, Breeding, and Reproduction of the Ministry of Education & Key Laboratory of Swine Genetics and Breeding of the Ministry of Agriculture, Huazhong Agricultural University, Wuhan 430070, China.
| | - Xia Peng
- Key Laboratory of Agricultural Animal Genetics, Breeding, and Reproduction of the Ministry of Education & Key Laboratory of Swine Genetics and Breeding of the Ministry of Agriculture, Huazhong Agricultural University, Wuhan 430070, China.
| | - Shengsong Xie
- Key Laboratory of Agricultural Animal Genetics, Breeding, and Reproduction of the Ministry of Education & Key Laboratory of Swine Genetics and Breeding of the Ministry of Agriculture, Huazhong Agricultural University, Wuhan 430070, China.
| | - Xinyun Li
- Key Laboratory of Agricultural Animal Genetics, Breeding, and Reproduction of the Ministry of Education & Key Laboratory of Swine Genetics and Breeding of the Ministry of Agriculture, Huazhong Agricultural University, Wuhan 430070, China.
| | - Shuhong Zhao
- Key Laboratory of Agricultural Animal Genetics, Breeding, and Reproduction of the Ministry of Education & Key Laboratory of Swine Genetics and Breeding of the Ministry of Agriculture, Huazhong Agricultural University, Wuhan 430070, China.
| | - Yunlong Ma
- Key Laboratory of Agricultural Animal Genetics, Breeding, and Reproduction of the Ministry of Education & Key Laboratory of Swine Genetics and Breeding of the Ministry of Agriculture, Huazhong Agricultural University, Wuhan 430070, China.
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