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Yao M, Chang L, Xu S, Zhang J, Li P, Tian B, Luo L, Yang D, Long Q, Zou X. Comparison of production performance and meat quality characteristics between Guizhou Black goats and F4 generation hybrids of South African Kalahari Goats. Sci Rep 2024; 14:18608. [PMID: 39127724 PMCID: PMC11316849 DOI: 10.1038/s41598-024-69174-0] [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: 05/30/2024] [Accepted: 08/01/2024] [Indexed: 08/12/2024] Open
Abstract
This study spanned 6 years and 4 generations, involving the progressive crossbreeding of South African Kalahari Goat (SK) and Guizhou Black Goat (GB) over three generations, followed by cross fixation F3 with F1 in the fourth generation, accompanied by the use of molecular markers technology to select a high fertility population, resulting in the creation of a hybrid goat, BKF4 (11/16 SK lineage and 5/16 GB lineage). A comparative evaluation of the BKF4 hybrid breed and its parental breeds was conducted. Reproductive and production parameters of GB, SK, and BKF4 goat groups were monitored, including lambing rate (LR), survival rate (SR), daily weight gain at 3 months of age (DWG), and adult body weight (ABW) (n = 110, 106, 112 per group). In addition, dressing percentage (DP) (n = 12 per group) and analyses of amino acids (n = 8, 6, 10 per group) and fatty acids (n = 6 per group) were conducted to evaluate meat quality indicators. Results: (1) Reproductive and production performance: The index of LR reached 199%, significantly higher than GB and SK (p ≤ 0.001), with a SR of 95.0%, markedly higher than SK (p ≤ 0.001); DWG was 276.5 g, ABW reached 56.6 kg and with a dressing percentage (DP) of 54.5%, they are significantly surpassing GB (p ≤ 0.001). (2) Regarding meat quality: pH45-value and crude protein content (CP) increased, while intramuscular fat content increased compared to GB and ash content decreased. The amino acid composition was similar to GB, but the taste was more similar to SK. However, there were some negative impacts on fatty acid composition and functionality. (3) PCA analysis revealed that: BKF4 exhibited superior meat quality compared to GB and SK, influenced by two key factors contributing 83.49% and 16.51% to the explained variance, respectively. The key factors affecting meat quality include intramuscular fat (IMF), nutrient index (NI), PUFAs/MUFAs, n-6FAs, and drip loss (DL).
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Affiliation(s)
- Min Yao
- Institute of Fungus Resources, College of Life Sciences, Guizhou University, Guiyang, 550025, Guizhou Province, China
- Guizhou Testing Center for Livestock and Poultry Germplasm, Guiyang, 550018, Guizhou Province, China
| | - Lingle Chang
- Institute of Agro-Bioengineering/Key Laboratory of Plant Resource Conservation and Germplasm Innovation in Mountainous Region and Key Laboratory of Animal Genetics, Breeding and Reproduction in the Plateau Mountainous Region (Ministry of Education), College of Life Sciences and College of Animal Science, Guizhou University, Guiyang, 500025, Guizhou Province, China
| | - Suyun Xu
- Institute of Fungus Resources, College of Life Sciences, Guizhou University, Guiyang, 550025, Guizhou Province, China
| | - Jing Zhang
- Institute of Animal Husbandry and Veterinary Sciences, Guiyang, 550005, Guizhou Province, China
| | - Ping Li
- Guizhou Testing Center for Livestock and Poultry Germplasm, Guiyang, 550018, Guizhou Province, China
| | - Bing Tian
- Guizhou Testing Center for Livestock and Poultry Germplasm, Guiyang, 550018, Guizhou Province, China
| | - Li Luo
- Institute of Fungus Resources, College of Life Sciences, Guizhou University, Guiyang, 550025, Guizhou Province, China
| | - Danpin Yang
- Guizhou Kalahari Goat Breeding Company, Qianxinan, 562400, Guizhou Province, China
| | - Qingmeng Long
- Guizhou Testing Center for Livestock and Poultry Germplasm, Guiyang, 550018, Guizhou Province, China.
| | - Xiao Zou
- Institute of Fungus Resources, College of Life Sciences, Guizhou University, Guiyang, 550025, Guizhou Province, China.
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Yang L, Yin H, Bai L, Yao W, Tao T, Zhao Q, Gao Y, Teng J, Xu Z, Lin Q, Diao S, Pan Z, Guan D, Li B, Zhou H, Zhou Z, Zhao F, Wang Q, Pan Y, Zhang Z, Li K, Fang L, Liu GE. Mapping and functional characterization of structural variation in 1060 pig genomes. Genome Biol 2024; 25:116. [PMID: 38715020 PMCID: PMC11075355 DOI: 10.1186/s13059-024-03253-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2022] [Accepted: 04/19/2024] [Indexed: 05/12/2024] Open
Abstract
BACKGROUND Structural variations (SVs) have significant impacts on complex phenotypes by rearranging large amounts of DNA sequence. RESULTS We present a comprehensive SV catalog based on the whole-genome sequence of 1060 pigs (Sus scrofa) representing 101 breeds, covering 9.6% of the pig genome. This catalog includes 42,487 deletions, 37,913 mobile element insertions, 3308 duplications, 1664 inversions, and 45,184 break ends. Estimates of breed ancestry and hybridization using genotyped SVs align well with those from single nucleotide polymorphisms. Geographically stratified deletions are observed, along with known duplications of the KIT gene, responsible for white coat color in European pigs. Additionally, we identify a recent SINE element insertion in MYO5A transcripts of European pigs, potentially influencing alternative splicing patterns and coat color alterations. Furthermore, a Yorkshire-specific copy number gain within ABCG2 is found, impacting chromatin interactions and gene expression across multiple tissues over a stretch of genomic region of ~200 kb. Preliminary investigations into SV's impact on gene expression and traits using the Pig Genotype-Tissue Expression (PigGTEx) data reveal SV associations with regulatory variants and gene-trait pairs. For instance, a 51-bp deletion is linked to the lead eQTL of the lipid metabolism regulating gene FADS3, whose expression in embryo may affect loin muscle area, as revealed by our transcriptome-wide association studies. CONCLUSIONS This SV catalog serves as a valuable resource for studying diversity, evolutionary history, and functional shaping of the pig genome by processes like domestication, trait-based breeding, and adaptive evolution.
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Affiliation(s)
- Liu Yang
- Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, Guangdong, China
- Animal Genomics and Improvement Laboratory, Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, MD, 20705, USA
| | - Hongwei Yin
- Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, Guangdong, China
| | - Lijing Bai
- Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, Guangdong, China
| | - Wenye Yao
- Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, Guangdong, China
| | - Tan Tao
- Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, Guangdong, China
| | - Qianyi Zhao
- Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, Guangdong, China
| | - Yahui Gao
- Animal Genomics and Improvement Laboratory, Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, MD, 20705, USA
| | - Jinyan Teng
- State Key Laboratory of Swine and Poultry Breeding Industry, 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, China
| | - Zhiting Xu
- State Key Laboratory of Swine and Poultry Breeding Industry, 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, China
| | - Qing Lin
- State Key Laboratory of Swine and Poultry Breeding Industry, 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, China
| | - Shuqi Diao
- State Key Laboratory of Swine and Poultry Breeding Industry, 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, China
| | - Zhangyuan Pan
- Department of Animal Science, University of California-Davis, Davis, CA, USA
| | - Dailu Guan
- Department of Animal Science, University of California-Davis, Davis, CA, USA
| | - Bingjie Li
- Animal and Veterinary Sciences, Scotland's Rural College (SRUC), Roslin Institute Building, Easter Bush, Midlothian, EH25 9RG, United Kingdom
| | - Huaijun Zhou
- Department of Animal Science, University of California-Davis, Davis, CA, USA
| | - Zhongyin Zhou
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
| | - Fuping Zhao
- Key Laboratory of Animal Genetics, Breeding and Reproduction (Poultry) of Ministry of Agriculture, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193, China
| | - Qishan Wang
- Department of Animal Science, College of Animal Sciences, Zhejiang University, Hangzhou, 310058, China
| | - Yuchun Pan
- Department of Animal Science, College of Animal Sciences, Zhejiang University, Hangzhou, 310058, China
| | - Zhe Zhang
- State Key Laboratory of Swine and Poultry Breeding Industry, 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, China
| | - Kui Li
- Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, Guangdong, China.
| | - Lingzhao Fang
- Center for Quantitative Genetics and Genomics, Aarhus University, Aarhus, Denmark.
| | - George E Liu
- Animal Genomics and Improvement Laboratory, Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, MD, 20705, USA.
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Getmantseva L, Kolosova M, Fede K, Korobeinikova A, Kolosov A, Romanets E, Bakoev F, Romanets T, Yudin V, Keskinov A, Bakoev S. Finding Predictors of Leg Defects in Pigs Using CNV-GWAS. Genes (Basel) 2023; 14:2054. [PMID: 38002997 PMCID: PMC10671522 DOI: 10.3390/genes14112054] [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: 10/08/2023] [Revised: 11/04/2023] [Accepted: 11/07/2023] [Indexed: 11/26/2023] Open
Abstract
One of the most important areas of modern genome research is the search for meaningful relationships between genetic variants and phenotypes. In the livestock field, there has been research demonstrating the influence of copy number variants (CNVs) on phenotypic variation. Despite the wide range in the number and size of detected CNVs, a significant proportion differ between breeds and their functional effects are underestimated in the pig industry. In this work, we focused on the problem of leg defects in pigs (lumps/growths in the area of the hock joint on the hind legs) and focused on searching for molecular genetic predictors associated with this trait for the selection of breeding stock. The study was conducted on Large White pigs using three CNV calling tools (PennCNV, QuantiSNP and R-GADA) and the CNVRanger association analysis tool (CNV-GWAS). As a result, the analysis identified three candidate CNVRs associated with the formation of limb defects. Subsequent functional analysis suggested that all identified CNVs may act as potential predictors of the hock joint phenotype of pigs. It should be noted that the results obtained indicate that all significant regions are localized in genes (CTH, SRSF11, MAN1A1 and LPIN1) responsible for the metabolism of amino acids, fatty acids, glycerolipids and glycerophospholipids, thereby related to the immune response, liver functions, content intramuscular fat and animal fatness. These results are consistent with previously published studies, according to which a predisposition to the formation of leg defects can be realized through genetic variants associated with the functions of the liver, kidneys and hematological characteristics.
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Affiliation(s)
- Lyubov Getmantseva
- Federal State Budgetary Educational Institution of Higher Education, Don State Agrarian University, 346493 Persianovsky, Russia; (L.G.); (A.K.)
- Federal State Budgetary Institution, “Center for Strategic Planning and Management of Medical and Biological Health Risks” of the Federal Medical and Biological Agency, 10/1 Pogodinskaya St., 119121 Moscow, Russia; (K.F.); (A.K.)
| | - Maria Kolosova
- Federal State Budgetary Educational Institution of Higher Education, Don State Agrarian University, 346493 Persianovsky, Russia; (L.G.); (A.K.)
| | - Kseniia Fede
- Federal State Budgetary Institution, “Center for Strategic Planning and Management of Medical and Biological Health Risks” of the Federal Medical and Biological Agency, 10/1 Pogodinskaya St., 119121 Moscow, Russia; (K.F.); (A.K.)
| | - Anna Korobeinikova
- Federal State Budgetary Institution, “Center for Strategic Planning and Management of Medical and Biological Health Risks” of the Federal Medical and Biological Agency, 10/1 Pogodinskaya St., 119121 Moscow, Russia; (K.F.); (A.K.)
| | - Anatoly Kolosov
- Federal State Budgetary Educational Institution of Higher Education, Don State Agrarian University, 346493 Persianovsky, Russia; (L.G.); (A.K.)
| | - Elena Romanets
- Federal State Budgetary Educational Institution of Higher Education, Don State Agrarian University, 346493 Persianovsky, Russia; (L.G.); (A.K.)
| | - Faridun Bakoev
- Federal State Budgetary Educational Institution of Higher Education, Don State Agrarian University, 346493 Persianovsky, Russia; (L.G.); (A.K.)
| | - Timofey Romanets
- Federal State Budgetary Educational Institution of Higher Education, Don State Agrarian University, 346493 Persianovsky, Russia; (L.G.); (A.K.)
| | - Vladimir Yudin
- Federal State Budgetary Institution, “Center for Strategic Planning and Management of Medical and Biological Health Risks” of the Federal Medical and Biological Agency, 10/1 Pogodinskaya St., 119121 Moscow, Russia; (K.F.); (A.K.)
| | - Anton Keskinov
- Federal State Budgetary Institution, “Center for Strategic Planning and Management of Medical and Biological Health Risks” of the Federal Medical and Biological Agency, 10/1 Pogodinskaya St., 119121 Moscow, Russia; (K.F.); (A.K.)
| | - Siroj Bakoev
- Federal State Budgetary Institution, “Center for Strategic Planning and Management of Medical and Biological Health Risks” of the Federal Medical and Biological Agency, 10/1 Pogodinskaya St., 119121 Moscow, Russia; (K.F.); (A.K.)
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4
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Wang Q, Song X, Bi Y, Zhu H, Wu X, Guo Z, Liu M, Pan C. Detection distribution of CNVs of SNX29 in three goat breeds and their associations with growth traits. Front Vet Sci 2023; 10:1132833. [PMID: 37706075 PMCID: PMC10495836 DOI: 10.3389/fvets.2023.1132833] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2022] [Accepted: 07/17/2023] [Indexed: 09/15/2023] Open
Abstract
As a member of the SNX family, the goat sorting nexin 29 (SNX29) is initially identified as a myogenesis gene. Therefore, this study aimed to examine the polymorphism in the SNX29 gene and its association with growth traits. In this study, we used an online platform to predict the structures of the SNX29 protein and used quantitative real-time PCR to detect potential copy number variation (CNV) in Shaanbei white cashmere (SBWC) goats (n = 541), Guizhou black (GB) goats (n = 48), and Nubian (NB) goats (n = 39). The results showed that goat SNX29 protein belonged to non-secretory protein. Then, five CNVs were detected, and their association with growth traits was analyzed. In SBWC goats, CNV1, CNV3, CNV4, and CNV5 were associated with chest width and body length (P < 0.05). Among them, the CNV1 individuals with gain and loss genotypes were superior to those individuals with a median genotype, but CNV4 and CNV5 of individuals with the median genotype were superior to those with the loss and gain genotypes. In addition, individuals with the gain genotype had superior growth traits in CNV3. In brief, this study suggests that the CNV of SNX29 can be used as a molecular marker in goat breeding.
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Affiliation(s)
- Qian Wang
- College of Animal Science and Technology, Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, Northwest A&F University, Yangling, Shaanxi, China
| | - Xiaoyue Song
- Shaanxi Provincial Engineering and Technology Research Center of Cashmere Goats, Yulin University, Yulin, Shaanxi, China
- Life Science Research Center, Yulin University, Yulin, Shaanxi, China
| | - Yi Bi
- College of Animal Science and Technology, Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, Northwest A&F University, Yangling, Shaanxi, China
| | - Haijing Zhu
- Shaanxi Provincial Engineering and Technology Research Center of Cashmere Goats, Yulin University, Yulin, Shaanxi, China
- Life Science Research Center, Yulin University, Yulin, Shaanxi, China
| | - Xianfeng Wu
- Institute of Animal Husbandry and Veterinary, Fujian Academy of Agricultural Sciences, Fuzhou, Fujian, China
| | - Zhengang Guo
- Animal Husbandry and Veterinary Science Institute of Bijie City, Bijie, Guizhou, China
| | - Mei Liu
- College of Animal Science and Technology, Hunan Agricultural University, Changsha, Hunan, China
| | - Chuanying Pan
- College of Animal Science and Technology, Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, Northwest A&F University, Yangling, Shaanxi, China
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5
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Arias KD, Gutiérrez JP, Fernández I, Álvarez I, Goyache F. Copy Number Variation Regions Differing in Segregation Patterns Span Different Sets of Genes. Animals (Basel) 2023; 13:2351. [PMID: 37508128 PMCID: PMC10376189 DOI: 10.3390/ani13142351] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2023] [Revised: 07/17/2023] [Accepted: 07/18/2023] [Indexed: 07/30/2023] Open
Abstract
Copy number variations regions (CNVRs) can be classified either as segregating, when found in both parents, and offspring, or non-segregating. A total of 65 segregating and 31 non-segregating CNVRs identified in at least 10 individuals within a dense pedigree of the Gochu Asturcelta pig breed was subjected to enrichment and functional annotation analyses to ascertain their functional independence and importance. Enrichment analyses allowed us to annotate 1018 and 351 candidate genes within the bounds of the segregating and non-segregating CNVRs, respectively. The information retrieved suggested that the candidate genes spanned by segregating and non-segregating CNVRs were functionally independent. Functional annotation analyses allowed us to identify nine different significantly enriched functional annotation clusters (ACs) in segregating CNVR candidate genes mainly involved in immunity and regulation of the cell cycle. Up to five significantly enriched ACs, mainly involved in reproduction and meat quality, were identified in non-segregating CNVRs. The current analysis fits with previous reports suggesting that segregating CNVRs would explain performance at the population level, whereas non-segregating CNVRs could explain between-individuals differences in performance.
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Affiliation(s)
- Katherine D Arias
- Área de Genética y Reproducción Animal, SERIDA-Deva, Camino de Rioseco 1225, 33394 Gijón, Spain
| | - Juan Pablo Gutiérrez
- Departamento de Producción Animal, Universidad Complutense de Madrid, 28040 Madrid, Spain
| | - Iván Fernández
- Área de Genética y Reproducción Animal, SERIDA-Deva, Camino de Rioseco 1225, 33394 Gijón, Spain
| | - Isabel Álvarez
- Área de Genética y Reproducción Animal, SERIDA-Deva, Camino de Rioseco 1225, 33394 Gijón, Spain
| | - Félix Goyache
- Área de Genética y Reproducción Animal, SERIDA-Deva, Camino de Rioseco 1225, 33394 Gijón, Spain
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6
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Jiang YF, Wang S, Wang CL, Xu RH, Wang WW, Jiang Y, Wang MS, Jiang L, Dai LH, Wang JR, Chu XH, Zeng YQ, Fang LZ, Wu DD, Zhang Q, Ding XD. Pangenome obtained by long-read sequencing of 11 genomes reveal hidden functional structural variants in pigs. iScience 2023; 26:106119. [PMID: 36852268 PMCID: PMC9958381 DOI: 10.1016/j.isci.2023.106119] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Revised: 12/21/2022] [Accepted: 01/30/2023] [Indexed: 02/05/2023] Open
Abstract
Long-read sequencing (LRS) facilitates both the genome assembly and the discovery of structural variants (SVs). Here, we built a graph-based pig pangenome by incorporating 11 LRS genomes with an average of 94.01% BUSCO completeness score, revealing 206-Mb novel sequences. We discovered 183,352 nonredundant SVs (63% novel), representing 12.12% of the reference genome. By genotyping SVs in an additional 196 short-read sequencing samples, we identified thousands of population stratified SVs. Particularly, we detected 7,568 Tibetan specific SVs, some of which demonstrate significant population differentiation between Tibetan and low-altitude pigs, which might be associated with the high-altitude hypoxia adaptation in Tibetan pigs. Further integrating functional genomic data, the most promising candidate genes within the SVs that might contribute to the high-altitude hypoxia adaptation were discovered. Overall, our study generates a benchmark pangenome resource for illustrating the important roles of SVs in adaptive evolution, domestication, and genetic improvement of agronomic traits in pigs.
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Affiliation(s)
- Yi-Fan Jiang
- National Engineering Laboratory for Animal Breeding, Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Sheng Wang
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
| | - Chong-Long Wang
- Key Laboratory of Pig Molecular Quantitative Genetics of Anhui Academy of Agricultural Sciences, Anhui Provincial Key Laboratory of Livestock and Poultry Product Safety Engineering, Institute of Animal Husbandry and Veterinary Medicine, Anhui Academy of Agricultural Sciences, Hefei 230031, China
| | - Ru-Hai Xu
- Key Laboratory of Animal Genetics and Breeding of Zhejiang Province, Institute of Animal Husbandry and Veterinary Science, Zhejiang Academy of Agricultural Sciences, Hangzhou 310021, China
| | - Wen-Wen Wang
- Shandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention, College of Animal Science and Technology, Shandong Agricultural University, Taian 271001, China
| | - Yao Jiang
- National Engineering Laboratory for Animal Breeding, Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
- Key Laboratory of Pig Molecular Quantitative Genetics of Anhui Academy of Agricultural Sciences, Anhui Provincial Key Laboratory of Livestock and Poultry Product Safety Engineering, Institute of Animal Husbandry and Veterinary Medicine, Anhui Academy of Agricultural Sciences, Hefei 230031, China
| | - Ming-Shan Wang
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
| | - Li Jiang
- National Engineering Laboratory for Animal Breeding, Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Li-He Dai
- Key Laboratory of Animal Genetics and Breeding of Zhejiang Province, Institute of Animal Husbandry and Veterinary Science, Zhejiang Academy of Agricultural Sciences, Hangzhou 310021, China
| | - Jie-Ru Wang
- Key Laboratory of Pig Molecular Quantitative Genetics of Anhui Academy of Agricultural Sciences, Anhui Provincial Key Laboratory of Livestock and Poultry Product Safety Engineering, Institute of Animal Husbandry and Veterinary Medicine, Anhui Academy of Agricultural Sciences, Hefei 230031, China
| | - Xiao-Hong Chu
- Key Laboratory of Animal Genetics and Breeding of Zhejiang Province, Institute of Animal Husbandry and Veterinary Science, Zhejiang Academy of Agricultural Sciences, Hangzhou 310021, China
| | - Yong-Qing Zeng
- Shandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention, College of Animal Science and Technology, Shandong Agricultural University, Taian 271001, China
| | - Ling-Zhao Fang
- Center for Quantitative Genetics and Genomics, Aarhus University, Aarhus, 8000, Denmark
| | - Dong-Dong Wu
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
| | - Qin Zhang
- Shandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention, College of Animal Science and Technology, Shandong Agricultural University, Taian 271001, China
| | - Xiang-Dong Ding
- National Engineering Laboratory for Animal Breeding, Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
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7
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Genome-Wide Detection and Analysis of Copy Number Variation in Anhui Indigenous and Western Commercial Pig Breeds Using Porcine 80K SNP BeadChip. Genes (Basel) 2023; 14:genes14030654. [PMID: 36980927 PMCID: PMC10047991 DOI: 10.3390/genes14030654] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Revised: 02/27/2023] [Accepted: 03/01/2023] [Indexed: 03/08/2023] Open
Abstract
Copy number variation (CNV) is an important class of genetic variations widely associated with the porcine genome, but little is known about the characteristics of CNVs in foreign and indigenous pig breeds. We performed a genome-wide comparison of CNVs between Anhui indigenous pig (AHIP) and Western commercial pig (WECP) breeds based on data from the Porcine 80K SNP BeadChip. After analysis using the PennCNV software, we detected 3863 and 7546 CNVs in the AHIP and WECP populations, respectively. We obtained 225 (loss: 178, gain: 47) and 379 (loss: 293, gain: 86) copy number variation regions (CNVRs) randomly distributed across the autosomes of the AHIP and WECP populations, accounting for 10.90% and 22.57% of the porcine autosomal genome, respectively. Functional enrichment analysis of genes in the CNVRs identified genes related to immunity (FOXJ1, FOXK2, MBL2, TNFRSF4, SIRT1, NCF1) and meat quality (DGAT1, NT5E) in the WECP population; these genes were a loss event in the WECP population. This study provides important information on CNV differences between foreign and indigenous pig breeds, making it possible to provide a reference for future improvement of these breeds and their production performance.
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Arias KD, Pablo Gutiérrez J, Fernandez I, Menéndez-Arias NA, Álvarez I, Goyache F. Segregation patterns and inheritance rate of copy number variations regions assessed in a Gochu Asturcelta pig pedigree. Gene X 2023; 854:147111. [PMID: 36509293 DOI: 10.1016/j.gene.2022.147111] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Revised: 11/30/2022] [Accepted: 12/06/2022] [Indexed: 12/14/2022] Open
Abstract
Copy Number Variation Regions (CNVR) were subjected to pedigree analysis to contribute to the understanding of their segregation patterns. Up to 492 Gochu Asturcelta pig individuals forming 478 different parents-offspring trios (61 different families) were genotyped using the Axiom_PigHDv1 Array (658,692 SNPs). CNVR calling, performed using two different platforms (PennCNV and QuantiSNP), allowed to identify a total of 344 candidate CNVR on the 18 porcine autosomes covering about 106.8 Mb of the pig genome. Sixty-nine CNVR were identified, to some extent, in both the parents and the offspring and were classified as segregating CNVR. The other candidate CNVR were called in one or more progeny but in neither parent and classified either as singleton or recurrent de novo CNVR. Segregating CNVR were, on average, larger and more frequent than the recurrent de novo CNVR (444.8 kb vs 287.9 kb long and 34 vs 5 individuals, respectively). In any case, segregating CNVR did not conform to strict Mendelian inheritance patterns: estimates of average paternal and maternal transmission rates ranged from 11.0 % to 13.4 % and mean inheritance rate was below 21 %. This issue should be carefully considered when interpreting the results of CNV studies. Segregating CNVR, present across generations, are unlikely to be artifacts or false positives and can be hypothesized to be important at the population level.
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Affiliation(s)
| | - Juan Pablo Gutiérrez
- Departamento de Producción Animal, Universidad Complutense de Madrid, Avda. Puerta de Hierro s/n, 28040 Madrid, Spain
| | | | | | | | - Félix Goyache
- SERIDA-Deva, Camino de Rioseco 1225, 33394-Gijón, Spain.
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9
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Analysis of Copy Number Variation in the Whole Genome of Normal-Haired and Long-Haired Tianzhu White Yaks. Genes (Basel) 2022; 13:genes13122405. [PMID: 36553672 PMCID: PMC9777850 DOI: 10.3390/genes13122405] [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: 10/18/2022] [Revised: 12/06/2022] [Accepted: 12/16/2022] [Indexed: 12/23/2022] Open
Abstract
Long-haired individuals in the Tianzhu white yak population are a unique genetic resource, and have important landscape value. Copy number variation (CNV) is an important source of phenotypic variation in mammals. In this study, we used resequencing technology to detect the whole genome of 10 long-haired Tianzhu white yaks (LTWY) and 10 normal-haired Tianzhu white yaks (NTWY), and analyzed the differences of CNV in the genome of LTWYs and NTWYs. A total of 110268 CNVs were identified, 2006 CNVRs were defined, and the distribution map of these CNVRs on chromosomes was constructed. The comparison of LTWYs and NTWYs identified 80 differential CNVR-harbored genes, which were enriched in lipid metabolism, cell migration and other functions. Notably, some differential genes were identified as associated with hair growth and hair-follicle development (e.g., ASTN2, ATM, COL22A1, GK5, SLIT3, PM20D1, and SGCZ). In general, we present the first genome-wide analysis of CNV in LTWYs and NTWYs. Our results can provide new insights into the phenotypic variation of different hair lengths in Tianzhu white yaks.
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10
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Copy Number Variations Contribute to Intramuscular Fat Content Differences by Affecting the Expression of PELP1 Alternative Splices in Pigs. Animals (Basel) 2022; 12:ani12111382. [PMID: 35681846 PMCID: PMC9179479 DOI: 10.3390/ani12111382] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Revised: 05/24/2022] [Accepted: 05/24/2022] [Indexed: 12/20/2022] Open
Abstract
Simple Summary Copy number variation (CNV) is a type of variant that may influence meat quality of, for example intramuscular fat (IMF). In this study, a genome-wide association study (GWAS) was then performed between CNVs and IMF in a pig F2 resource population. A total of 19 CNVRs were found to be significantly associated with IMF. RNA-seq and qPCR validation results indicated that CNV150, which is located on the 3′UTR end of the proline, as well as glutamate and the leucine rich protein 1 (PELP1) gene may affect the expression of PELP1 alternative splices. We infer that the CNVR may influence IMF content by regulating the alternative splicing of the PELP1 gene and ultimately affects the structure of the PELP1 protein. These findings suggest a novel mechanistic approach for meat quality improvement in animals and the potential treatment of insulin resistance in human beings. Abstract Intramuscular fat (IMF) is a key meat quality trait. Research on the genetic mechanisms of IMF decomposition is valuable for both pork quality improvement and the treatment of obesity and type 2 diabetes. Copy number variations (CNVs) are a type of variant that may influence meat quality. In this study, a total of 1185 CNV regions (CNVRs) including 393 duplicated CNVRs, 432 deleted CNVRs, and 361 CNVRs with both duplicated and deleted status were identified in a pig F2 resource population using next-generation sequencing data. A genome-wide association study (GWAS) was then performed between CNVs and IMF, and a total of 19 CNVRs were found to be significantly associated with IMF. QTL colocation analysis indicated that 3 of the 19 CNVRs overlapped with known QTLs. RNA-seq and qPCR validation results indicated that CNV150, which is located on the 3′UTR end of the proline, as well as glutamate and the leucine rich protein 1 (PELP1) gene may affect the expression of PELP1 alternative splices. Sequence alignment and Alphafold2 structure prediction results indicated that the two alternative splices of PELP1 have a 23 AA sequence variation and a helix-fold structure variation. This region is located in the region of interaction between PELP1 and other proteins which have been reported to be significantly associated with fat deposition or insulin resistance. We infer that the CNVR may influence IMF content by regulating the alternative splicing of the PELP1 gene and ultimately affects the structure of the PELP1 protein. In conclusion, we found some CNVRs, especially CNV150, located in PELP1 that affect IMF. These findings suggest a novel mechanistic approach for meat quality improvement in animals and the potential treatment of insulin resistance in human beings.
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11
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Assessment of linkage disequilibrium patterns between structural variants and single nucleotide polymorphisms in three commercial chicken populations. BMC Genomics 2022; 23:193. [PMID: 35264116 PMCID: PMC8908679 DOI: 10.1186/s12864-022-08418-7] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Accepted: 02/24/2022] [Indexed: 12/29/2022] Open
Abstract
BACKGROUND Structural variants (SV) are causative for some prominent phenotypic traits of livestock as different comb types in chickens or color patterns in pigs. Their effects on production traits are also increasingly studied. Nevertheless, accurately calling SV remains challenging. It is therefore of interest, whether close-by single nucleotide polymorphisms (SNPs) are in strong linkage disequilibrium (LD) with SVs and can serve as markers. Literature comes to different conclusions on whether SVs are in LD to SNPs on the same level as SNPs to other SNPs. The present study aimed to generate a precise SV callset from whole-genome short-read sequencing (WGS) data for three commercial chicken populations and to evaluate LD patterns between the called SVs and surrounding SNPs. It is thereby the first study that assessed LD between SVs and SNPs in chickens. RESULTS The final callset consisted of 12,294,329 bivariate SNPs, 4,301 deletions (DEL), 224 duplications (DUP), 218 inversions (INV) and 117 translocation breakpoints (BND). While average LD between DELs and SNPs was at the same level as between SNPs and SNPs, LD between other SVs and SNPs was strongly reduced (DUP: 40%, INV: 27%, BND: 19% of between-SNP LD). A main factor for the reduced LD was the presence of local minor allele frequency differences, which accounted for 50% of the difference between SNP - SNP and DUP - SNP LD. This was potentially accompanied by lower genotyping accuracies for DUP, INV and BND compared with SNPs and DELs. An evaluation of the presence of tag SNPs (SNP in highest LD to the variant of interest) further revealed DELs to be slightly less tagged by WGS SNPs than WGS SNPs by other SNPs. This difference, however, was no longer present when reducing the pool of potential tag SNPs to SNPs located on four different chicken genotyping arrays. CONCLUSIONS The results implied that genomic variance due to DELs in the chicken populations studied can be captured by different SNP marker sets as good as variance from WGS SNPs, whereas separate SV calling might be advisable for DUP, INV, and BND effects.
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12
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Wang BB, Hou LM, Zhou WD, Liu H, Tao W, Wu WJ, Niu PP, Zhang ZP, Zhou J, Li Q, Huang RH, Li PH. Genome-wide association study reveals a quantitative trait locus and two candidate genes on Sus scrofa chromosome 5 affecting intramuscular fat content in Suhuai pigs. Animal 2021; 15:100341. [PMID: 34425484 DOI: 10.1016/j.animal.2021.100341] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/25/2020] [Revised: 07/22/2021] [Accepted: 07/23/2021] [Indexed: 12/14/2022] Open
Abstract
Intramuscular fat content (IFC) is an essential quantitative trait of meat, affecting multiple meat quality indicators. A certain amount of IFC could not only improve the sensory score of pork but also increase the flavour, tenderness, juiciness and shelf-life. To dissect the genetic determinants of IFC, two methods, including genome-wide efficient mixed-model analysis (GEMMA) and linkage disequilibrium adjusted kinships (LDAKs), were used to carry out genome-wide association studies for IFC in Suhuai pig population. A total of 14 and 18 significant single nucleotide polymorphisms (SNPs) were identified by GEMMA and LDAK, respectively. The results of these two methods were highly consistent and all 14 significant SNPs in GEMMA were detected by LDAK. Seven of the 18 SNPs reached the genome-wide significance level (P < 9.85E-07) while 11 cases reached the suggestive significance level (P < 1.77E-05). These significant SNPs were mainly distributed on Sus scrofa chromosome (SSC) 5, 3, and 7. Moreover, one locus resides in a 2.27 Mb (71.37-73.64 Mb) region on SSC5 harbouring 13 significant SNPs associated with IFC, and the lead SNP (rs81302978) also locates in this region. Linkage disequilibrium (LD) analysis showed that there were four pairs of complete LD (r2 = 1) among these 13 SNPs, and the remaining 9 SNPs with incomplete LD (r2 ≠ 1) were selected for subsequent analyses of IFC. Association analyses showed that 7 out of 9 SNPs were significantly associated with IFC (P < 0.05) in 330 Suhuai pigs, and the other 2 SNPs tended to reach a significant association level with IFC (P < 0.1). The phenotypic variance explained (PVE) range of these 9 SNPs was 0.92-3.55%. Meanwhile, the lead SNP was also significantly associated (rs81302978) with IFC (P < 0.05) in 378 commercial hybrid pigs (Pietrain × Duroc) × (Landrace × Yorkshire) (PDLY), and the PVE was 1.38%. Besides, two lipid metabolism-relevant candidate genes, the leucine rich repeat kinase 2 (LRRK2) and PDZ domain containing ring finger 4 (PDZRN4) were identified in the 2.27 Mb region on SSC5. In conclusion, our results may provide a set of markers useful for genetic improvement of IFC in pigs and will advance the genome selection process of IFC on pig breeding programmes.
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Affiliation(s)
- B B Wang
- Institute of Swine Science, Nanjing Agricultural University, Nanjing 210095, China; Huaian Academy, Nanjing Agricultural University, Huaian 223005, China
| | - L M Hou
- Institute of Swine Science, Nanjing Agricultural University, Nanjing 210095, China; Huaian Academy, Nanjing Agricultural University, Huaian 223005, China
| | - W D Zhou
- Institute of Swine Science, Nanjing Agricultural University, Nanjing 210095, China
| | - H Liu
- Institute of Swine Science, Nanjing Agricultural University, Nanjing 210095, China; Huaian Academy, Nanjing Agricultural University, Huaian 223005, China
| | - W Tao
- Institute of Swine Science, Nanjing Agricultural University, Nanjing 210095, China; Huaian Academy, Nanjing Agricultural University, Huaian 223005, China
| | - W J Wu
- Institute of Swine Science, Nanjing Agricultural University, Nanjing 210095, China
| | - P P Niu
- Huaian Academy, Nanjing Agricultural University, Huaian 223005, China
| | - Z P Zhang
- Huaian Academy, Nanjing Agricultural University, Huaian 223005, China
| | - J Zhou
- Huaiyin Pig Breeding Farm of Huaian City, Huaian 223322, China
| | - Q Li
- Huaiyin Pig Breeding Farm of Huaian City, Huaian 223322, China
| | - R H Huang
- Institute of Swine Science, Nanjing Agricultural University, Nanjing 210095, China; Huaian Academy, Nanjing Agricultural University, Huaian 223005, China
| | - P H Li
- Institute of Swine Science, Nanjing Agricultural University, Nanjing 210095, China; Huaian Academy, Nanjing Agricultural University, Huaian 223005, China.
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13
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Donaldson B, Villagomez DAF, King WA. Classical, Molecular, and Genomic Cytogenetics of the Pig, a Clinical Perspective. Animals (Basel) 2021; 11:1257. [PMID: 33925534 PMCID: PMC8146943 DOI: 10.3390/ani11051257] [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: 03/21/2021] [Revised: 04/16/2021] [Accepted: 04/23/2021] [Indexed: 02/06/2023] Open
Abstract
The chromosomes of the domestic pig (Sus scrofa domesticus) are known to be prone to reciprocal chromosome translocations and other balanced chromosome rearrangements with concomitant fertility impairment of carriers. In response to the remarkable prevalence of chromosome rearrangements in swine herds, clinical cytogenetics laboratories have been established in several countries in order to screen young boars for chromosome rearrangements prior to service. At present, clinical cytogenetics laboratories typically apply classical cytogenetics techniques such as giemsa-trypsin (GTG)-banding to produce high-quality karyotypes and reveal large-scale chromosome ectopic exchanges. Further refinements to clinical cytogenetics practices have led to the implementation of molecular cytogenetics techniques such as fluorescent in-situ hybridization (FISH), allowing for rearrangements to be visualized and breakpoints refined using fluorescently labelled painting probes. The next-generation of clinical cytogenetics include the implementation of DNA microarrays, and next-generation sequencing (NGS) technologies such as DNA sequencing to better explore tentative genome architecture changes. The implementation of these cytogenomics techniques allow the genomes of rearrangement carriers to be deciphered at the highest resolution, allowing rearrangements to be detected; breakpoints to be delineated; and, most importantly, potential gene implications of those chromosome rearrangements to be interrogated. Clinical cytogenetics has become an integral tool in the livestock industry, identifying rearrangements and allowing breeders to make informed breeding decisions.
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Affiliation(s)
- Brendan Donaldson
- Department of Biomedical Sciences, University of Guelph, Guelph, ON N1G 2W1, Canada;
| | | | - W. Allan King
- Department of Biomedical Sciences, University of Guelph, Guelph, ON N1G 2W1, Canada;
- Karyotekk Inc., Box 363 OVC, University of Guelph, Guelph, ON N1G 2W1, Canada
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14
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Bovo S, Ribani A, Muñoz M, Alves E, Araujo JP, Bozzi R, Charneca R, Di Palma F, Etherington G, Fernandez AI, García F, García-Casco J, Karolyi D, Gallo M, Gvozdanović K, Martins JM, Mercat MJ, Núñez Y, Quintanilla R, Radović Č, Razmaite V, Riquet J, Savić R, Schiavo G, Škrlep M, Usai G, Utzeri VJ, Zimmer C, Ovilo C, Fontanesi L. Genome-wide detection of copy number variants in European autochthonous and commercial pig breeds by whole-genome sequencing of DNA pools identified breed-characterising copy number states. Anim Genet 2020; 51:541-556. [PMID: 32510676 DOI: 10.1111/age.12954] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/30/2020] [Indexed: 02/06/2023]
Abstract
In this study, we identified copy number variants (CNVs) in 19 European autochthonous pig breeds and in two commercial breeds (Italian Large White and Italian Duroc) that represent important genetic resources for this species. The genome of 725 pigs was sequenced using a breed-specific DNA pooling approach (30-35 animals per pool) obtaining an average depth per pool of 42×. This approach maximised CNV discovery as well as the related copy number states characterising, on average, the analysed breeds. By mining more than 17.5 billion reads, we identified a total of 9592 CNVs (~683 CNVs per breed) and 3710 CNV regions (CNVRs; 1.15% of the reference pig genome), with an average of 77 CNVRs per breed that were considered as private. A few CNVRs were analysed in more detail, together with other information derived from sequencing data. For example, the CNVR encompassing the KIT gene was associated with coat colour phenotypes in the analysed breeds, confirming the role of the multiple copies in determining breed-specific coat colours. The CNVR covering the MSRB3 gene was associated with ear size in most breeds. The CNVRs affecting the ELOVL6 and ZNF622 genes were private features observed in the Lithuanian Indigenous Wattle and in the Turopolje pig breeds respectively. Overall, the genome variability unravelled here can explain part of the genetic diversity among breeds and might contribute to explain their origin, history and adaptation to a variety of production systems.
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Affiliation(s)
- S Bovo
- Division of Animal Sciences, Department of Agricultural and Food Sciences, University of Bologna, Viale Fanin 46, Bologna, 40127, Italy
| | - A Ribani
- Division of Animal Sciences, Department of Agricultural and Food Sciences, University of Bologna, Viale Fanin 46, Bologna, 40127, Italy
| | - M Muñoz
- Departamento Mejora Genética Animal, INIA, Crta. de la Coruña, km. 7,5, Madrid, 28040, Spain
| | - E Alves
- Departamento Mejora Genética Animal, INIA, Crta. de la Coruña, km. 7,5, Madrid, 28040, Spain
| | - J P Araujo
- Centro de Investigação de Montanha, Instituto Politécnico de Viana do Castelo, Escola Superior Agrária, Refóios do Lima, Ponte de Lima, 4990-706, Portugal
| | - R Bozzi
- DAGRI - Animal Science Section, Università di Firenze, Via delle Cascine 5, Firenze, 50144, Italy
| | - R Charneca
- MED - Mediterranean Institute for Agriculture, Environment and Development, Universidade de Évora, Pólo da Mitra, Apartado 94, Évora, 7006-554, Portugal
| | - F Di Palma
- Earlham Institute, Norwich Research Park, Colney Lane, Norwich, NR47UZ, UK
| | - G Etherington
- Earlham Institute, Norwich Research Park, Colney Lane, Norwich, NR47UZ, UK
| | - A I Fernandez
- Departamento Mejora Genética Animal, INIA, Crta. de la Coruña, km. 7,5, Madrid, 28040, Spain
| | - F García
- Departamento Mejora Genética Animal, INIA, Crta. de la Coruña, km. 7,5, Madrid, 28040, Spain
| | - J García-Casco
- Departamento Mejora Genética Animal, INIA, Crta. de la Coruña, km. 7,5, Madrid, 28040, Spain
| | - D Karolyi
- Department of Animal Science, Faculty of Agriculture, University of Zagreb, Svetošimunska c. 25, Zagreb, 10000, Croatia
| | - M Gallo
- Associazione Nazionale Allevatori Suini, Via Nizza 53, Roma, 00198, Italy
| | - K Gvozdanović
- Faculty of Agrobiotechnical Sciences Osijek, University of Osijek, Vladimira Preloga 1, Osijek, 31000, Croatia
| | - J M Martins
- MED - Mediterranean Institute for Agriculture, Environment and Development, Universidade de Évora, Pólo da Mitra, Apartado 94, Évora, 7006-554, Portugal
| | - M J Mercat
- IFIP Institut Du Porc, La Motte au Vicomte, BP 35104, Le Rheu Cedex, 35651, France
| | - Y Núñez
- Departamento Mejora Genética Animal, INIA, Crta. de la Coruña, km. 7,5, Madrid, 28040, Spain
| | - R Quintanilla
- Programa de Genética y Mejora Animal, IRTA, Torre Marimon, Caldes de Montbui, Barcelona, 08140, Spain
| | - Č Radović
- Department of Pig Breeding and Genetics, Institute for Animal Husbandry, Belgrade-Zemun, 11080, Serbia
| | - V Razmaite
- Animal Science Institute, Lithuanian University of Health Sciences, R. Žebenkos 12, Baisogala, 82317, Lithuania
| | - J Riquet
- GenPhySE, INRA, Université de Toulouse, Chemin de Borde-Rouge 24, Auzeville Tolosane, Castanet Tolosan, 31326, France
| | - R Savić
- Faculty of Agriculture, University of Belgrade, Nemanjina 6, Belgrade-Zemun, 11080, Serbia
| | - G Schiavo
- Division of Animal Sciences, Department of Agricultural and Food Sciences, University of Bologna, Viale Fanin 46, Bologna, 40127, Italy
| | - M Škrlep
- Kmetijski Inštitut Slovenije, Hacquetova 17, Ljubljana, SI-1000, Slovenia
| | - G Usai
- AGRIS SARDEGNA, Loc. Bonassai, Sassari, 07100, Italy
| | - V J Utzeri
- Division of Animal Sciences, Department of Agricultural and Food Sciences, University of Bologna, Viale Fanin 46, Bologna, 40127, Italy
| | - C Zimmer
- Bäuerliche Erzeugergemeinschaft Schwäbisch Hall, Haller Str. 20, Wolpertshausen, 74549, Germany
| | - C Ovilo
- Departamento Mejora Genética Animal, INIA, Crta. de la Coruña, km. 7,5, Madrid, 28040, Spain
| | - L Fontanesi
- Division of Animal Sciences, Department of Agricultural and Food Sciences, University of Bologna, Viale Fanin 46, Bologna, 40127, Italy
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15
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Hao D, Wang X, Thomsen B, Kadarmideen HN, Wang X, Lan X, Huang Y, Qi X, Chen H. Copy Number Variations and Expression Levels of Guanylate-Binding Protein 6 Gene Associated with Growth Traits of Chinese Cattle. Animals (Basel) 2020; 10:E566. [PMID: 32230930 PMCID: PMC7222342 DOI: 10.3390/ani10040566] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2020] [Revised: 03/18/2020] [Accepted: 03/22/2020] [Indexed: 11/16/2022] Open
Abstract
Association studies have indicated profound effects of copy number variations (CNVs) on various phenotypes in different species. In this study, we identified the CNV distributions and expression levels of guanylate-binding protein 6 (GBP6) associated with the growth traits of Chinese cattle. The results showed that the phenotypic values of body size and weight of Xianan (XN) cattle were higher than those of Nanyang (NY) cattle. The medium CNV types were mostly identified in the XN and NY breeds, but their CNV distributions were significantly different (adjusted p < 0.05). The association analysis revealed that the body weight, cannon circumference and chest circumference of XN cattle had significantly different values in different CNV types (p < 0.05), with CNV gain types (Log22-ΔΔCt > 0.5) displaying superior phenotypic values. We also found that transcription levels varied in different tissues (p < 0.001) and the CNV gain types showed the highest relative gene expression levels in the muscle tissue, consistent with the highest phenotypic values of body weight and cannon circumference among the three CNV types. Consequently, our results suggested that CNV gain types of GBP6 could be used as the candidate markers in the cattle-breeding program for growth traits.
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Affiliation(s)
- Dan Hao
- College of Animal Science and Technology, Northwest A&F University, Shaanxi Key Laboratory of Animal Genetics, Breeding and Reproduction, Yangling 712100, Shaanxi, China; (D.H.); (X.W.); (X.L.); (Y.H.)
- Department of Molecular Biology and Genetics, Aarhus University, 8000 Aarhus C, Denmark;
| | - Xiao Wang
- Department of Applied Mathematics and Computer Science, Technical University of Denmark, 2800 Kongens Lyngby, Denmark; (X.W.); (H.N.K.)
| | - Bo Thomsen
- Department of Molecular Biology and Genetics, Aarhus University, 8000 Aarhus C, Denmark;
| | - Haja N. Kadarmideen
- Department of Applied Mathematics and Computer Science, Technical University of Denmark, 2800 Kongens Lyngby, Denmark; (X.W.); (H.N.K.)
| | - Xiaogang Wang
- College of Animal Science and Technology, Northwest A&F University, Shaanxi Key Laboratory of Animal Genetics, Breeding and Reproduction, Yangling 712100, Shaanxi, China; (D.H.); (X.W.); (X.L.); (Y.H.)
| | - Xianyong Lan
- College of Animal Science and Technology, Northwest A&F University, Shaanxi Key Laboratory of Animal Genetics, Breeding and Reproduction, Yangling 712100, Shaanxi, China; (D.H.); (X.W.); (X.L.); (Y.H.)
| | - Yongzhen Huang
- College of Animal Science and Technology, Northwest A&F University, Shaanxi Key Laboratory of Animal Genetics, Breeding and Reproduction, Yangling 712100, Shaanxi, China; (D.H.); (X.W.); (X.L.); (Y.H.)
| | - Xinglei Qi
- Bureau of Animal Husbandry of Biyang County, Biyang 463700, Henan, China;
| | - Hong Chen
- College of Animal Science and Technology, Northwest A&F University, Shaanxi Key Laboratory of Animal Genetics, Breeding and Reproduction, Yangling 712100, Shaanxi, China; (D.H.); (X.W.); (X.L.); (Y.H.)
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16
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Wang Y, Zhang T, Wang C. Detection and analysis of genome-wide copy number variation in the pig genome using an 80 K SNP Beadchip. J Anim Breed Genet 2019; 137:166-176. [PMID: 31506991 DOI: 10.1111/jbg.12435] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2019] [Revised: 08/02/2019] [Accepted: 08/05/2019] [Indexed: 12/23/2022]
Abstract
Copy number variation (CNV) is an important source of genetic variability in human or animal genomes and play key roles in phenotypic diversity and disease susceptibility. In the present study, we performed a genome-wide analysis for CNV detection using SNP genotyping data of 857 Large White pigs. A total of 312 CNV regions (CNVRs) were detected with the PennCNV algorithm, which covered 57.76 Mb of the pig genome and correspond to 2.36% of the genome sequence. The length of the CNVRs on autosomes ranged from 1.77 Kb to 1.76 Mb with an average of 185.11 Kb. Of these, 220 completely or partially overlapped with 1,092 annotated genes, which enriched a wide variety of biological processes. Comparisons with previously reported pig CNVR revealed 92 (29.49%) novel CNVRs. Experimentally, 80% of CNVRs selected randomly were validated by quantitative PCR (qPCR). We also performed an association analysis between some of the CNVRs and reproductive traits, with results demonstrating the potential importance of CNVR61 and CNVR283 associated with litter sizes. Notably, the GPER1 gene located in CNVR61 plays a key role in reproduction. Our study is an important complement to the CNV map in the pig genome and provides valuable information for investigating the association between genomic variation and economic traits.
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Affiliation(s)
- Yuan Wang
- College of Animal Science and Technology, Qingdao Agricultural University, Qingdao, China.,Key Laboratory of Animal Genetics and Breeding of Ministry of Agriculture, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Tingrong Zhang
- College of Animal Science and Technology, Qingdao Agricultural University, Qingdao, China
| | - Chuduan Wang
- Key Laboratory of Animal Genetics and Breeding of Ministry of Agriculture, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
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17
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Wang L, Zhao L, Zhang L, Liu X, Hou X, Gao H, Yan H, Zhao F, Wang L. NTN1 Affects Porcine Intramuscular Fat Content by Affecting the Expression of Myogenic Regulatory Factors. Animals (Basel) 2019; 9:ani9090609. [PMID: 31461826 PMCID: PMC6770873 DOI: 10.3390/ani9090609] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2019] [Revised: 08/12/2019] [Accepted: 08/17/2019] [Indexed: 12/27/2022] Open
Abstract
Simple Summary Intramuscular fat (IMF) is a key meat quality trait in the pork industry. In this study, we validated the effect of the copy number of Netrin-1 (NTN1-CNV) on Netrin-1 (NTN1) protein expression and explored the possible affective mechanism of NTN1 on IMF. The results indicated that NTN1-CNV may affect the expression of NTN1 protein by its gene dose, and the expression of NTN1 may affect the proliferation and differentiation of muscle cells by the AMP-activated protein kinase (AMPK) pathway and finally influence the IMF content. Abstract Intramuscular fat (IMF) content is an important economic trait for pork quality. Our previous results regarding the genome-wide association between IMF content and copy number variations (CNVs) indicated that the CNV within Netrin-1(NTN1-CNV) was significantly associated with IMF. In order to validate the effect of NTN1-CNV, we detected the Netrin-1 (NTN1) gene dose and protein expression content in the longissimus dorsi of different IMF content pigs using Western blotting and investigated the expression of NTN1 RNA in different tissues using real-time quantitative polymerase chain reaction (qPCR). The knock-down of the NTN1 gene in C2C12 and 3T3-L1 cells and over-expression in C2C12 cells during the proliferation and differentiation stage were also investigated to explore the possible pathway of action of NTN1. The results showed that in individuals with IMF content differences, the gene dose of NTN1 and the expression of NTN1 protein were also significantly different, which indicated that NTN1-CNV may directly affect IMF by its coding protein. NTN1 had the highest expression in pig longissimus dorsi and backfat tissues, which indicates that NTN1 may play an important role in muscle and fat tissues. The in vitro validation assay indicated that NTN1 silencing could promote the proliferation and inhibit the differentiation of C2C12 cells, with no effect on 3T3-L1 cells. Additionally, NTN1 over-expression could inhibit the proliferation and promote the differentiation of C2C12 cells. Combined with previous research, we conclude that NTN1-CNV may affect IMF by its gene dose, and the expression of NTN1 may affect the proliferation and differentiation of muscle cells by the AMP-activated protein kinase (AMPK) pathway and finally influence the IMF.
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Affiliation(s)
- Ligang Wang
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Lingling Zhao
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China
- College of Animal Science and Technology, Qingdao Agricultural University, Qingdao 266109, China
| | - Longchao Zhang
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Xin Liu
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Xinhua Hou
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Hongmei Gao
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Hua Yan
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Fuping Zhao
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Lixian Wang
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China.
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18
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Peng SJ, Cao XK, Dong D, Liu M, Hao D, Shen XM, Huang YZ, Lei CZ, Ma Y, Bai YY, Hu LY, Qi XL, Chaogetu B, Chen H. Integrative analysis of APOL3 gene CNV for adult cattle stature. Anim Biotechnol 2019; 31:440-446. [PMID: 31104559 DOI: 10.1080/10495398.2019.1615933] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Copy number variations (CNVs) have been identified as another important structural variation of genome. In recent years, a large amount of CNVRs have been identified in humans and animals. However, association and dosage effects studies of CNVs are very limited. Apolipoprotein L3 (APOL3) gene plays a central role in modulating gene transcription and is located within a CNVR that encompasses quantitative trait locis (QTLs) for economic traits like meat quality. Herein, we analyzed the CNV polymorphism of APOL3 in 421 individuals from five distinct cattle breeds, and then correlated their genotypes with growth traits. Association analysis revealed that the APOL3 CNV was significantly associated with hip height and cannon circumference of Xianan (XN) cattle (P < .01), and visibly associated with body slanting length and hucklebone width of Pinan (PN) cattle (P < .05). Overall, the data provide evidence for the functional role of APOL3 CNV and a basis for future applications in cattle breeding.
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Affiliation(s)
- Shu-Jun Peng
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, China
| | - Xiu-Kai Cao
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, China
| | - Dong Dong
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, China
| | - Mei Liu
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, China
| | - Dan Hao
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, China
| | - Xue-Mei Shen
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, China
| | - Yong-Zhen Huang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, China
| | - Chu-Zhao Lei
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, China
| | - Yun Ma
- College of Life Sciences, Xinyang Normal University, Xinyang, China.,Institute for Conservation and Utilization of Agro-Bioresources in Dabie Mountains, Xinyang, China
| | - Yue-Yu Bai
- Animal Health Supervision in Henan Province, Zhengzhou, China
| | - Lin-Yong Hu
- Key Laboratory of Adaptation and Evolution of Plateau Biota, Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining, China
| | - Xing-Lei Qi
- Bureau of Animal Husbandry of Biyang County, Biyang, China
| | - Buren Chaogetu
- Animal Disease Control Center of Haixi Mongolian and Tibetan Autonomous Prefecture, Delingha, China
| | - Hong Chen
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, China
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19
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Di Gerlando R, Sutera AM, Mastrangelo S, Tolone M, Portolano B, Sottile G, Bagnato A, Strillacci MG, Sardina MT. Genome-wide association study between CNVs and milk production traits in Valle del Belice sheep. PLoS One 2019; 14:e0215204. [PMID: 31013280 PMCID: PMC6478285 DOI: 10.1371/journal.pone.0215204] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2018] [Accepted: 03/28/2019] [Indexed: 11/19/2022] Open
Abstract
Copy number variation (CNV) is a major source of genomic structural variation. The aim of this study was to detect genomic CNV regions (CNVR) in Valle del Belice dairy sheep population and to identify those affecting milk production traits. The GO analysis identified possible candidate genes and pathways related to the selected traits. We identified CNVs in 416 individuals genotyped using the Illumina OvineSNP50 BeadChip array. The CNV association using a correlation-trend test model was examined with the Golden Helix SVS 8.7.0 tool. Significant CNVs were detected when their adjusted p-value was <0.01 after false discovery rate (FDR) correction. We identified 7,208 CNVs, which gave 365 CNVRs after aggregating overlapping CNVs. Thirty-one CNVRs were significantly associated with one or more traits included in the analysis. All CNVRs, except those on OAR19, overlapped with quantitative trait loci (QTL), even if they were not directly related to the traits of interest. A total of 222 genes were annotated within the significantly associated CNVRs, most of which played important roles in biological processes related to milk production and health-related traits. Identification of the genes in the CNVRs associated with the studied traits will provide the basis for further investigation of their role in the metabolic pathways related to milk production and health traits.
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Affiliation(s)
- Rosalia Di Gerlando
- Università degli Studi di Palermo, Dipartimento di Scienze Agrarie, Alimentari e Forestali, Italy
| | - Anna Maria Sutera
- Università degli Studi di Palermo, Dipartimento di Scienze Agrarie, Alimentari e Forestali, Italy
| | - Salvatore Mastrangelo
- Università degli Studi di Palermo, Dipartimento di Scienze Agrarie, Alimentari e Forestali, Italy
| | - Marco Tolone
- Università degli Studi di Palermo, Dipartimento di Scienze Agrarie, Alimentari e Forestali, Italy
| | - Baldassare Portolano
- Università degli Studi di Palermo, Dipartimento di Scienze Agrarie, Alimentari e Forestali, Italy
| | - Gianluca Sottile
- Università degli Studi di Palermo, Dipartimento di Scienze Economiche, Aziendali e Statistiche, Italy
| | - Alessandro Bagnato
- Università degli Studi di Milano, Dipartimento di Medicina Veterinaria, Italy
| | | | - Maria Teresa Sardina
- Università degli Studi di Palermo, Dipartimento di Scienze Agrarie, Alimentari e Forestali, Italy
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20
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Gong J, Cheng T, Wu Y, Yang X, Feng Q, Mita K. Genome-wide patterns of copy number variations in Spodoptera litura. Genomics 2018; 111:1231-1238. [PMID: 30114452 DOI: 10.1016/j.ygeno.2018.08.002] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2018] [Revised: 07/26/2018] [Accepted: 08/04/2018] [Indexed: 01/06/2023]
Abstract
Spodoptera litura is a polyphagous pest and can feed on more than 100 species of plants, causing great damage to agricultural production. The SNP results showed that there were gene exchanges between different regions. To explore the variations of larger segments in S. litura genome, we used genome resequencing samples from 14 regions of China, India, and Japan to study the copy number variations (CNVs). We identified 3976 CNV events and 1581 unique copy number variation regions (CNVRs) occupying the 108.5 Mb genome of S. litura. A total of 5527 genes that overlapped with CNVRs were detected. Selection signal analysis identified 19 shared CNVRs and 105 group-specific CNVRs, whose related genes were involved in various biological processes in S. litura. We constructed the first CNVs map in S. litura genome, and our findings will be valuable for understanding the genomic variations and population differences of S. litura.
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Affiliation(s)
- Jiao Gong
- State Key Laboratory of Silkworm Genome Biology, Southwest University, Chongqing 400716, China
| | - Tingcai Cheng
- State Key Laboratory of Silkworm Genome Biology, Southwest University, Chongqing 400716, China; Chongqing Engineering and Technology Research Center for Novel Silk Materials, Southwest University, 2, Tiansheng Road, Beibei, Chongqing 400715, China.
| | - Yuqian Wu
- State Key Laboratory of Silkworm Genome Biology, Southwest University, Chongqing 400716, China
| | - Xi Yang
- State Key Laboratory of Silkworm Genome Biology, Southwest University, Chongqing 400716, China
| | - Qili Feng
- Guangzhou Key Laboratory of Insect Development Regulation and Application Research, South China Normal University, Guangzhou 510631, China
| | - Kazuei Mita
- State Key Laboratory of Silkworm Genome Biology, Southwest University, Chongqing 400716, China
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21
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Zhou Y, Connor EE, Wiggans GR, Lu Y, Tempelman RJ, Schroeder SG, Chen H, Liu GE. Genome-wide copy number variant analysis reveals variants associated with 10 diverse production traits in Holstein cattle. BMC Genomics 2018; 19:314. [PMID: 29716533 PMCID: PMC5930521 DOI: 10.1186/s12864-018-4699-5] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2017] [Accepted: 04/18/2018] [Indexed: 01/08/2023] Open
Abstract
BACKGROUND Copy number variation (CNV) is an important type of genetic variation contributing to phenotypic differences among mammals and may serve as an alternative molecular marker to single nucleotide polymorphism (SNP) for genome-wide association study (GWAS). Recently, GWAS analysis using CNV has been applied in livestock, although few studies have focused on Holstein cattle. RESULTS We describe 191 CNV detected using intensity data from over 700,000 SNP genotypes generated with the BovineHD Genotyping BeadChip (Illumina, San Diego, CA) in 528 Holstein cows. The CNV were used for GWAS analysis of 10 important production traits of 473 cattle related to feed intake, milk quality, and female fertility, as well as 2 composite traits of net merit and productive life. In total, we detected 57 CNV associated (P < 0.05 after false discovery rate correction) with at least one of the 10 phenotypes. Focusing on feed efficiency and intake-related phenotypes of residual feed intake and dry matter intake, we detected a single CNV associated with both traits which overlaps a predicted olfactory receptor gene OR2A2 (LOC787786). Additionally, 2 CNV within the RXFP4 (relaxin/insulin like family peptide receptor 4) and 2 additional olfactory receptor gene regions, respectively, were associated with residual feed intake. The RXFP4 gene encodes a receptor for an orexigenic peptide, insulin-like peptide 5 produced by intestinal L cells, which is expressed by enteric neurons. Olfactory receptors are critical for transmitting the effects of odorants, contributing to the sense of smell, and have been implicated in participating in appetite regulation. CONCLUSIONS Our results identify CNV for genomic evaluation in Holstein cattle, and provide candidate genes, such as RXFP4, contributing to variation in feed efficiency and feed intake-related traits. These results indicate potential novel targets for manipulating feed intake-related traits of livestock.
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Affiliation(s)
- Yang Zhou
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, 10300 Baltimore Avenue, Bldg. 306, BARC-East, Beltsville, MD, 20705, USA.,Shaanxi Key Laboratory of Agricultural Molecular Biology, College of Animal Science and Technology, Northwest A&F University, Yangling, 712100, Shaanxi, China.,Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Education Ministry of China, Huazhong Agricultural University, Wuhan, 430070, Hubei, China
| | - Erin E Connor
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, 10300 Baltimore Avenue, Bldg. 306, BARC-East, Beltsville, MD, 20705, USA
| | - George R Wiggans
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, 10300 Baltimore Avenue, Bldg. 306, BARC-East, Beltsville, MD, 20705, USA
| | - Yongfang Lu
- Department of Animal Science, Michigan State University, East Lansing, MI, 48824, USA
| | - Robert J Tempelman
- Department of Animal Science, Michigan State University, East Lansing, MI, 48824, USA
| | - Steven G Schroeder
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, 10300 Baltimore Avenue, Bldg. 306, BARC-East, Beltsville, MD, 20705, USA
| | - Hong Chen
- Shaanxi Key Laboratory of Agricultural Molecular Biology, College of Animal Science and Technology, Northwest A&F University, Yangling, 712100, Shaanxi, China
| | - George E Liu
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, 10300 Baltimore Avenue, Bldg. 306, BARC-East, Beltsville, MD, 20705, USA.
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22
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Revilla M, Puig-Oliveras A, Castelló A, Crespo-Piazuelo D, Paludo E, Fernández AI, Ballester M, Folch JM. A global analysis of CNVs in swine using whole genome sequence data and association analysis with fatty acid composition and growth traits. PLoS One 2017; 12:e0177014. [PMID: 28472114 PMCID: PMC5417718 DOI: 10.1371/journal.pone.0177014] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2016] [Accepted: 04/20/2017] [Indexed: 11/30/2022] Open
Abstract
Copy number variations (CNVs) are important genetic variants complementary to SNPs, and can be considered as biomarkers for some economically important traits in domestic animals. In the present study, a genomic analysis of porcine CNVs based on next-generation sequencing data was carried out to identify CNVs segregating in an Iberian x Landrace backcross population and study their association with fatty acid composition and growth-related traits. A total of 1,279 CNVs, including duplications and deletions, were detected, ranging from 106 to 235 CNVs across samples, with an average of 183 CNVs per sample. Moreover, we detected 540 CNV regions (CNVRs) containing 245 genes. Functional annotation suggested that these genes possess a great variety of molecular functions and may play a role in production traits in commercial breeds. Some of the identified CNVRs contained relevant functional genes (e.g., CLCA4, CYP4X1, GPAT2, MOGAT2, PLA2G2A and PRKG1, among others). The variation in copy number of four of them (CLCA4, GPAT2, MOGAT2 and PRKG1) was validated in 150 BC1_LD (25% Iberian and 75% Landrace) animals by qPCR. Additionally, their contribution regarding backfat and intramuscular fatty acid composition and growth–related traits was analyzed. Statistically significant associations were obtained for CNVR112 (GPAT2) for the C18:2(n-6)/C18:3(n-3) ratio in backfat and carcass length, among others. Notably, GPATs are enzymes that catalyze the first step in the biosynthesis of both triglycerides and glycerophospholipids, suggesting that this CNVR may contribute to genetic variation in fatty acid composition and growth traits. These findings provide useful genomic information to facilitate the further identification of trait-related CNVRs affecting economically important traits in pigs.
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Affiliation(s)
- Manuel Revilla
- Departament de Ciència Animal i dels Aliments, Facultat de Veterinària, Universitat Autònoma de Barcelona (UAB), Bellaterra, Spain
- Plant and Animal Genomics, Centre de Recerca en Agrigenòmica (CRAG), Consorci CSIC-IRTA-UAB-UB, Campus UAB, Bellaterra, Spain
- * E-mail:
| | - Anna Puig-Oliveras
- Departament de Ciència Animal i dels Aliments, Facultat de Veterinària, Universitat Autònoma de Barcelona (UAB), Bellaterra, Spain
- Plant and Animal Genomics, Centre de Recerca en Agrigenòmica (CRAG), Consorci CSIC-IRTA-UAB-UB, Campus UAB, Bellaterra, Spain
| | - Anna Castelló
- Departament de Ciència Animal i dels Aliments, Facultat de Veterinària, Universitat Autònoma de Barcelona (UAB), Bellaterra, Spain
- Plant and Animal Genomics, Centre de Recerca en Agrigenòmica (CRAG), Consorci CSIC-IRTA-UAB-UB, Campus UAB, Bellaterra, Spain
| | - Daniel Crespo-Piazuelo
- Departament de Ciència Animal i dels Aliments, Facultat de Veterinària, Universitat Autònoma de Barcelona (UAB), Bellaterra, Spain
- Plant and Animal Genomics, Centre de Recerca en Agrigenòmica (CRAG), Consorci CSIC-IRTA-UAB-UB, Campus UAB, Bellaterra, Spain
| | - Ediane Paludo
- Department of Animal Science, Santa Catarina State University, Lages, Santa Catarina, Brazil
| | - Ana I. Fernández
- Departamento de Genética Animal, Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA), Madrid, Spain
| | - Maria Ballester
- Departament de Genètica i Millora Animal, Institut de Recerca i Tecnologia Agroalimentàries (IRTA), Torre Marimon, Caldes de Montbui, Spain
| | - Josep M. Folch
- Departament de Ciència Animal i dels Aliments, Facultat de Veterinària, Universitat Autònoma de Barcelona (UAB), Bellaterra, Spain
- Plant and Animal Genomics, Centre de Recerca en Agrigenòmica (CRAG), Consorci CSIC-IRTA-UAB-UB, Campus UAB, Bellaterra, Spain
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23
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Prunier J, Caron S, MacKay J. CNVs into the wild: screening the genomes of conifer trees (Picea spp.) reveals fewer gene copy number variations in hybrids and links to adaptation. BMC Genomics 2017; 18:97. [PMID: 28100184 PMCID: PMC5241962 DOI: 10.1186/s12864-016-3458-8] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2016] [Accepted: 12/22/2016] [Indexed: 12/31/2022] Open
Abstract
Background Copy number variations (CNVs) have been linked to different phenotypes in human, including many diseases. A genome-scale understanding of CNVs is available in a few plants but none are wild species, leaving a knowledge gap regarding their genome biology and evolutionary role. We developed a reliable CNV detection method for species lacking contiguous reference genome. We selected multiple probes within 14,078 gene sequences and developed comparative genome hybridization on arrays. Gene CNVs were assessed in three full-sib families from species with 20 Gb genomes, i.e., white and black spruce, and interior spruce - a natural hybrid. Results We discovered hundreds of gene CNVs in each species, 3612 in total, which were enriched in functions related to stress and defense responses and narrow expression profiles, indicating a potential role in adaptation. The number of shared CNVs was in accordance with the degree of relatedness between individuals and species. The genetically mapped subset of these genes showed a wide distribution across the genome, implying numerous structural variations. The hybrid family presented significantly fewer CNVs, suggesting that the admixture of two species within one genome reduces the occurrence of CNVs. Conclusions The approach we developed is of particular interest in non-model species lacking a reference genome. Our findings point to a role for CNVs in adaptation. Their reduced abundance in the hybrid may limit genetic variability and evolvability of hybrids. We propose that CNVs make a qualitatively distinct contribution to adaptation which could be important for short term change. Electronic supplementary material The online version of this article (doi:10.1186/s12864-016-3458-8) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Julien Prunier
- Institute for System and Integrative Biology (IBIS), Université Laval, Quebec, QC, G1V 0A6, Canada. .,Centre for Forest Research, Université Laval, Quebec, QC, G1V 0A6, Canada.
| | - Sébastien Caron
- Institute for System and Integrative Biology (IBIS), Université Laval, Quebec, QC, G1V 0A6, Canada
| | - John MacKay
- Centre for Forest Research, Université Laval, Quebec, QC, G1V 0A6, Canada.,Department of Plant Sciences, University of Oxford, Oxford, OX1 3RB, UK
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24
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Copy number variation of bovine MAPK10 modulates the transcriptional activity and affects growth traits. Livest Sci 2016. [DOI: 10.1016/j.livsci.2016.09.014] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
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25
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Galla SJ, Buckley TR, Elshire R, Hale ML, Knapp M, McCallum J, Moraga R, Santure AW, Wilcox P, Steeves TE. Building strong relationships between conservation genetics and primary industry leads to mutually beneficial genomic advances. Mol Ecol 2016; 25:5267-5281. [PMID: 27641156 DOI: 10.1111/mec.13837] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2016] [Revised: 08/23/2016] [Accepted: 08/24/2016] [Indexed: 02/06/2023]
Abstract
Several reviews in the past decade have heralded the benefits of embracing high-throughput sequencing technologies to inform conservation policy and the management of threatened species, but few have offered practical advice on how to expedite the transition from conservation genetics to conservation genomics. Here, we argue that an effective and efficient way to navigate this transition is to capitalize on emerging synergies between conservation genetics and primary industry (e.g., agriculture, fisheries, forestry and horticulture). Here, we demonstrate how building strong relationships between conservation geneticists and primary industry scientists is leading to mutually-beneficial outcomes for both disciplines. Based on our collective experience as collaborative New Zealand-based scientists, we also provide insight for forging these cross-sector relationships.
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Affiliation(s)
- Stephanie J Galla
- School of Biological Sciences, University of Canterbury, Private Bag 4800, Christchurch, 8140, New Zealand.
| | - Thomas R Buckley
- Landcare Research, Private Bag 92170, Auckland Mail Centre, Auckland, 1142, New Zealand.,School of Biological Sciences, University of Auckland, Auckland, 1010, New Zealand
| | - Rob Elshire
- The Elshire Group, Ltd., 52 Victoria Avenue, Palmerston North, 4410, New Zealand
| | - Marie L Hale
- School of Biological Sciences, University of Canterbury, Private Bag 4800, Christchurch, 8140, New Zealand
| | - Michael Knapp
- Department of Anatomy, University of Otago, P.O. Box 913, Dunedin, 9054, New Zealand
| | - John McCallum
- Breeding and Genomics, New Zealand Institute for Plant and Food Research, Private Bag 4704, Christchurch, 8140, New Zealand
| | - Roger Moraga
- AgResearch, Ruakura Research Centre, Bisley Road, Private Bag 3115, Hamilton, 3240, New Zealand
| | - Anna W Santure
- School of Biological Sciences, University of Auckland, Auckland, 1010, New Zealand
| | - Phillip Wilcox
- Department of Mathematics and Statistics, University of Otago, P.O. Box 56, 710 Cumberland Street, Dunedin, 9054, New Zealand
| | - Tammy E Steeves
- School of Biological Sciences, University of Canterbury, Private Bag 4800, Christchurch, 8140, New Zealand
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26
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Zhang X, Wang K, Wang L, Yang Y, Ni Z, Xie X, Shao X, Han J, Wan D, Qiu Q. Genome-wide patterns of copy number variation in the Chinese yak genome. BMC Genomics 2016; 17:379. [PMID: 27206476 PMCID: PMC4875690 DOI: 10.1186/s12864-016-2702-6] [Citation(s) in RCA: 49] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2016] [Accepted: 05/06/2016] [Indexed: 12/02/2022] Open
Abstract
Background Copy number variation (CNV) represents an important source of genetic divergence that can produce drastic phenotypic differences and may therefore be subject to selection during domestication and environmental adaptation. To investigate the evolutionary dynamics of CNV in the yak genome, we used a read depth approach to detect CNV based on genome resequencing data from 14 wild and 65 domestic yaks and determined CNV regions related to domestication and adaptations to high-altitude. Results We identified 2,634 CNV regions (CNVRs) comprising a total of 153 megabases (5.7 % of the yak genome) and 3,879 overlapping annotated genes. Comparison between domestic and wild yak populations identified 121 potentially selected CNVRs, harboring genes related to neuronal development, reproduction, nutrition and energy metabolism. In addition, we found 85 CNVRs that are significantly different between domestic yak living in high- and low-altitude areas, including three genes related to hypoxia response and six related to immune defense. This analysis shows that genic CNVs may play an important role in phenotypic changes during yak domestication and adaptation to life at high-altitude. Conclusions We present the first refined CNV map for yak along with comprehensive genomic analysis of yak CNV. Our results provide new insights into the genetic basis of yak domestication and adaptation to living in a high-altitude environment, as well as a valuable genetic resource that will facilitate future CNV association studies of important traits in yak and other bovid species. Electronic supplementary material The online version of this article (doi:10.1186/s12864-016-2702-6) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Xiao Zhang
- State Key Laboratory of Grassland Agroecosystem, College of Life Science, Lanzhou University, Lanzhou, 730000, China
| | - Kun Wang
- State Key Laboratory of Grassland Agroecosystem, College of Life Science, Lanzhou University, Lanzhou, 730000, China
| | - Lizhong Wang
- State Key Laboratory of Grassland Agroecosystem, College of Life Science, Lanzhou University, Lanzhou, 730000, China
| | - Yongzhi Yang
- State Key Laboratory of Grassland Agroecosystem, College of Life Science, Lanzhou University, Lanzhou, 730000, China
| | - Zhengqiang Ni
- State Key Laboratory of Grassland Agroecosystem, College of Life Science, Lanzhou University, Lanzhou, 730000, China
| | - Xiuyue Xie
- State Key Laboratory of Grassland Agroecosystem, College of Life Science, Lanzhou University, Lanzhou, 730000, China
| | - Xuemin Shao
- State Key Laboratory of Grassland Agroecosystem, College of Life Science, Lanzhou University, Lanzhou, 730000, China
| | - Jin Han
- State Key Laboratory of Grassland Agroecosystem, College of Life Science, Lanzhou University, Lanzhou, 730000, China
| | - Dongshi Wan
- State Key Laboratory of Grassland Agroecosystem, College of Life Science, Lanzhou University, Lanzhou, 730000, China.
| | - Qiang Qiu
- State Key Laboratory of Grassland Agroecosystem, College of Life Science, Lanzhou University, Lanzhou, 730000, China.
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Sato S, Uemoto Y, Kikuchi T, Egawa S, Kohira K, Saito T, Sakuma H, Miyashita S, Arata S, Kojima T, Suzuki K. SNP- and haplotype-based genome-wide association studies for growth, carcass, and meat quality traits in a Duroc multigenerational population. BMC Genet 2016; 17:60. [PMID: 27094516 PMCID: PMC4837538 DOI: 10.1186/s12863-016-0368-3] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2016] [Accepted: 04/15/2016] [Indexed: 12/21/2022] Open
Abstract
Background The aim of the present study was to compare the power of single nucleotide polymorphism (SNP)-based genome-wide association study (GWAS) and haplotype-based GWAS for quantitative trait loci (QTL) detection, and to detect novel candidate genes affecting economically important traits in a purebred Duroc population comprising seven-generation pedigree. First, we performed a simulation analysis using real genotype data of this population to compare the power (based on the null hypothesis) of the two methods. We then performed GWAS using both methods and real phenotype data comprising 52 traits, which included growth, carcass, and meat quality traits. Results In total, 836 animals were genotyped using the Illumina PorcineSNP60 BeadChip and 14 customized SNPs from regions of known candidate genes related to the traits of interest. The power of SNP-based GWAS was greater than that of haplotype-based GWAS in a simulation analysis. In real data analysis, a larger number of significant regions was obtained by SNP-based GWAS than by haplotype-based GWAS. For SNP-based GWAS, 23 genome-wide significant SNP regions were detected for 17 traits, and 120 genome-wide suggestive SNP regions were detected for 27 traits. For haplotype-based GWAS, 6 genome-wide significant SNP regions were detected for four traits, and 11 genome-wide suggestive SNP regions were detected for eight traits. All genome-wide significant SNP regions detected by haplotype-based GWAS were located in regions also detected by SNP-based GWAS. Four regions detected by SNP-based GWAS were significantly associated with multiple traits: on Sus scrofa chromosome (SSC) 1 at 304 Mb; and on SSC7 at 35–39 Mb, 41–42 Mb, and 103 Mb. The vertnin gene (VRTN) in particular, was located on SSC7 at 103 Mb and was significantly associated with vertebrae number and carcass lengths. Mapped QTL regions contain some candidate genes involved in skeletal formation (FUBP3; far upstream element binding protein 3) and fat deposition (METTL3; methyltransferase like 3). Conclusion Our results show that a multigenerational pig population is useful for detecting QTL, which are typically segregated in a purebred population. In addition, a novel significant region could be detected by SNP-based GWAS as opposed to haplotype-based GWAS. Electronic supplementary material The online version of this article (doi:10.1186/s12863-016-0368-3) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Shuji Sato
- National Livestock Breeding Center, Nishigo, Fukushima, 961-8511, Japan.
| | - Yoshinobu Uemoto
- National Livestock Breeding Center, Nishigo, Fukushima, 961-8511, Japan
| | - Takashi Kikuchi
- National Livestock Breeding Center, Nishigo, Fukushima, 961-8511, Japan
| | - Sachiko Egawa
- Miyazaki Branch of National Livestock Breeding Center, Kobayashi, Miyazaki, 886-0004, Japan
| | - Kimiko Kohira
- National Livestock Breeding Center, Nishigo, Fukushima, 961-8511, Japan
| | - Tomomi Saito
- National Livestock Breeding Center, Nishigo, Fukushima, 961-8511, Japan
| | - Hironori Sakuma
- National Livestock Breeding Center, Nishigo, Fukushima, 961-8511, Japan
| | - Satoshi Miyashita
- Miyazaki Branch of National Livestock Breeding Center, Kobayashi, Miyazaki, 886-0004, Japan
| | - Shinji Arata
- Miyazaki Branch of National Livestock Breeding Center, Kobayashi, Miyazaki, 886-0004, Japan
| | - Takatoshi Kojima
- National Livestock Breeding Center, Nishigo, Fukushima, 961-8511, Japan
| | - Keiichi Suzuki
- Graduate School of Agricultural Science, Tohoku University, Sendai, Miyagi, 981-8555, Japan
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