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Selionova M, Trukhachev V, Aibazov M, Sermyagin A, Belous A, Gladkikh M, Zinovieva N. Genome-Wide Association Study of Milk Composition in Karachai Goats. Animals (Basel) 2024; 14:327. [PMID: 38275787 PMCID: PMC10812594 DOI: 10.3390/ani14020327] [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: 11/22/2023] [Revised: 01/10/2024] [Accepted: 01/18/2024] [Indexed: 01/27/2024] Open
Abstract
This study is first to perform a genome-wide association study (GWAS) to investigate the milk quality traits in Karachai goats. The objective of the study was to identify candidate genes associated with milk composition traits based on the identification and subsequent analysis of all possible SNPs, both genome-wide (high-confidence) and suggestive (subthreshold significance). To estimate the milk components, 22 traits were determined, including several types of fatty acids. DNA was extracted from ear tissue or blood samples. A total of 167 Karachai goats were genotyped using an Illumina GoatSNP53K BeadChip panel (Illumina Inc., San Diego, CA, USA). Overall, we identified 167 highly significant and subthreshold SNPs associated with the milk components of Karachai goats. A total of 10 SNPs were located within protein-coding genes and 33 SNPs in close proximity to them (±0.2 Mb). The largest number of genome-wide significant SNPs was found on chromosomes 2 and 8 and some of them were associated with several traits. The greatest number of genome-wide significant SNPs was identified for crude protein and lactose (6), and the smallest number-only 1 SNP-for freezing point depression. No SNPs were identified for monounsaturated and polyunsaturated fatty acids. Functional annotation of all 43 SNPs allowed us to identify 66 significant candidate genes on chromosomes 1, 2, 3, 4, 5, 8, 10, 13, 16, 18, 21, 23, 25, 26, and 27. We considered these genes potential DNA markers of the fatty acid composition of Karachai goat milk. Also, we found 12 genes that had a polygenic effect: most of them were simultaneously associated with the dry matter content and fatty acids (METTL, SLC1A 8, PHACTR1, FMO2, ECI1, PGP, ABCA3, AMDHD2). Our results suggest that the genes identified in our study affecting the milk components in Karachai goats differed from those identified in other breeds of dairy goats.
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Affiliation(s)
- Marina Selionova
- Subdepartment of Animal Breeding, Genetics and Biotechnology, Russian State Agrarian University—Moscow Timiryazev Agricultural Academy, Timiryazevskaya Street, 41, 127434 Moscow, Russia (M.G.)
| | - Vladimir Trukhachev
- Subdepartment of Animal Breeding, Genetics and Biotechnology, Russian State Agrarian University—Moscow Timiryazev Agricultural Academy, Timiryazevskaya Street, 41, 127434 Moscow, Russia (M.G.)
| | - Magomet Aibazov
- L. K. Ernst Federal Research Center for Animal Husbandry, Dubrovitsy 60, 142132 Podolsk, Moscow Region, Russia; (M.A.); (A.S.); (A.B.); (N.Z.)
| | - Alexander Sermyagin
- L. K. Ernst Federal Research Center for Animal Husbandry, Dubrovitsy 60, 142132 Podolsk, Moscow Region, Russia; (M.A.); (A.S.); (A.B.); (N.Z.)
| | - Anna Belous
- L. K. Ernst Federal Research Center for Animal Husbandry, Dubrovitsy 60, 142132 Podolsk, Moscow Region, Russia; (M.A.); (A.S.); (A.B.); (N.Z.)
| | - Marianna Gladkikh
- Subdepartment of Animal Breeding, Genetics and Biotechnology, Russian State Agrarian University—Moscow Timiryazev Agricultural Academy, Timiryazevskaya Street, 41, 127434 Moscow, Russia (M.G.)
| | - Natalia Zinovieva
- L. K. Ernst Federal Research Center for Animal Husbandry, Dubrovitsy 60, 142132 Podolsk, Moscow Region, Russia; (M.A.); (A.S.); (A.B.); (N.Z.)
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Qiao Y, Gu M, Zhang Y, Bai Z, Qin Y, Xu Y, Dou X, Han D, Lin G, Wang L, Wang Z, Wang J, Sun Y, Wu Y, Chen R, Zhang Q, Li Q, Wang X, Xu Z, Cong Y, Chen J, Wang Z. Association analysis for SNPs of LIPE and ITGB4 genes with cashmere production performance, body measurement traits and milk production traits in Liaoning cashmere goats. Anim Biotechnol 2023; 34:3827-3836. [PMID: 37428531 DOI: 10.1080/10495398.2023.2230484] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/11/2023]
Abstract
Liaoning cashmere goat (LCG) is one of the excellent cashmere goat breeds in China. Because of its larger size, better cashmere, and better cashmere production performance, people pay special attention to it. This article mainly studied the relationship between SNP loci of LIPE gene and ITGB4 gene and milk production, cashmere production and body measurement traits of LCGs. We further identified potential SNP loci by PCR-Seq polymorphism detection and gene sequence comparison of LIPE and ITGB4 genes. Further, we use SPSS and SHEsis software to analyze their relationship to production performance. The consequence indicated that CC genotype of LIPE gene T16409C locus was dominant genotype in milk production and cashmere production, while CT genotype of LIPE gene T16409C locus was dominant in body size. The CT genotype of C168T locus of ITGB4 gene is the dominant genotype of body type and cashmere production, while the dominant genotype of milk production is TT genotype. Through joint analysis, in haploid combinations, H1H2:CCCT is the dominant haplotype combination in cashmere fineness. H3H4:TTCT is a dominant haplotype combination of milk production traits and body measurement traits. These dominant genotypes can provide a reliable basis for the study of production performance of LCG.
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Affiliation(s)
- Yanjun Qiao
- College of Animal Science & Veterinary Medicine, Shenyang Agricultural University, Shenyang, China
| | - Ming Gu
- College of Animal Science & Veterinary Medicine, Shenyang Agricultural University, Shenyang, China
| | - Yu Zhang
- College of Animal Science & Veterinary Medicine, Shenyang Agricultural University, Shenyang, China
| | - Zhixian Bai
- College of Animal Science & Veterinary Medicine, Shenyang Agricultural University, Shenyang, China
| | - Yuting Qin
- College of Animal Science & Veterinary Medicine, Shenyang Agricultural University, Shenyang, China
| | - Yanan Xu
- College of Animal Science & Veterinary Medicine, Shenyang Agricultural University, Shenyang, China
| | - Xingtang Dou
- Liaoning Province Modern Agricultural Production Base Construction Engineering Center, Liaoyang, China
| | - Di Han
- Liaoning Province Modern Agricultural Production Base Construction Engineering Center, Liaoyang, China
| | - Guangyu Lin
- Liaoning Province Modern Agricultural Production Base Construction Engineering Center, Liaoyang, China
| | - Lingling Wang
- Liaoning Province Modern Agricultural Production Base Construction Engineering Center, Liaoyang, China
| | - Zhanhong Wang
- Liaoning Province Modern Agricultural Production Base Construction Engineering Center, Liaoyang, China
| | - Jiaming Wang
- Liaoning Province Modern Agricultural Production Base Construction Engineering Center, Liaoyang, China
| | - Yinggang Sun
- College of Animal Science & Veterinary Medicine, Shenyang Agricultural University, Shenyang, China
| | - Yanzhi Wu
- College of Animal Science & Veterinary Medicine, Shenyang Agricultural University, Shenyang, China
| | - Rui Chen
- College of Animal Science & Veterinary Medicine, Shenyang Agricultural University, Shenyang, China
| | - Qiu Zhang
- College of Animal Science & Veterinary Medicine, Shenyang Agricultural University, Shenyang, China
| | - Qian Li
- College of Animal Science & Veterinary Medicine, Shenyang Agricultural University, Shenyang, China
| | - Xiaowei Wang
- College of Animal Science & Veterinary Medicine, Shenyang Agricultural University, Shenyang, China
| | - Zhiguo Xu
- Dalian Modern Agricultural Production Development Service Center, Dalian, China
| | - Yuyan Cong
- College of Animal Science & Veterinary Medicine, Shenyang Agricultural University, Shenyang, China
| | - Jing Chen
- College of Animal Science & Veterinary Medicine, Shenyang Agricultural University, Shenyang, China
| | - Zeying Wang
- College of Animal Science & Veterinary Medicine, Shenyang Agricultural University, Shenyang, China
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Zhang Y, Qin Y, Gu M, Xu Y, Dou X, Han D, Lin G, Wang L, Wang Z, Wang J, Sun Y, Wu Y, Chen R, Qiao Y, Zhang Q, Li Q, Wang X, Xu Z, Cong Y, Chen J, Wang Z. Association between the cashmere production performance, milk production performance, and body size traits and polymorphism of COL6A5 and LOC102181374 genes in Liaoning cashmere goats. Anim Biotechnol 2023; 34:4415-4429. [PMID: 36527393 DOI: 10.1080/10495398.2022.2155177] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
The purpose of this study was to analyze the relationship between COL6A5 (collagen type VI alpha 5 chain) and LOC102181374 (alcohol dehydrogenase 1) genes and the production performance of Liaoning cashmere goats by single nucleotide polymorphism (SNP). We have searched for SNP loci of COL6A5 and LOC102181374 genes through sequence alignment and PCR experiments, and have used SPSS and SHEsis software to analyze production data. We obtained five SNP loci in total, including three SNP loci (G50985A, G51140T, G51175A) in COL6A5 gene and two SNP loci (A10067G, T10108C) in LOC102181374 gene. The genotypes G50985A (AG), G51140T (GT), G51175A (AA), A10067G (AA), and T10108C (CC) of these loci have certain advantages in improving the production performance of Liaoning cashmere goats. The haplotype combinations that can improve production performance in COL6A5 gene were H1H5:AGGGAG, H4H4:GGGGAA, and H4H4:GGGGAA. H3H3:GGCC and H2H4:AGTT were the dominant combinations in LOC102181374 gene. At G51175A and A10067G loci, we found that H1H2:AAAG and H1H3:AGAA have dominant effects. These results may provide some support for the molecular breeding of production traits in Liaoning cashmere goats.
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Affiliation(s)
- Yu Zhang
- College of Animal Science & Veterinary Medicine, Shenyang Agricultural University, Shenyang, China
| | - Yuting Qin
- College of Animal Science & Veterinary Medicine, Shenyang Agricultural University, Shenyang, China
| | - Ming Gu
- College of Animal Science & Veterinary Medicine, Shenyang Agricultural University, Shenyang, China
| | - Yanan Xu
- College of Animal Science & Veterinary Medicine, Shenyang Agricultural University, Shenyang, China
| | - Xingtang Dou
- Liaoning Province Modern Agricultural Production Base Construction Engineering Center, Liaoyang, China
| | - Di Han
- Liaoning Province Modern Agricultural Production Base Construction Engineering Center, Liaoyang, China
| | - Guangyu Lin
- Liaoning Province Modern Agricultural Production Base Construction Engineering Center, Liaoyang, China
| | - Lingling Wang
- Liaoning Province Modern Agricultural Production Base Construction Engineering Center, Liaoyang, China
| | - Zhanhong Wang
- Liaoning Province Modern Agricultural Production Base Construction Engineering Center, Liaoyang, China
| | - Jiaming Wang
- Liaoning Province Modern Agricultural Production Base Construction Engineering Center, Liaoyang, China
| | - Yinggang Sun
- College of Animal Science & Veterinary Medicine, Shenyang Agricultural University, Shenyang, China
| | - Yanzhi Wu
- College of Animal Science & Veterinary Medicine, Shenyang Agricultural University, Shenyang, China
| | - Rui Chen
- College of Animal Science & Veterinary Medicine, Shenyang Agricultural University, Shenyang, China
| | - Yanjun Qiao
- College of Animal Science & Veterinary Medicine, Shenyang Agricultural University, Shenyang, China
| | - Qiu Zhang
- College of Animal Science & Veterinary Medicine, Shenyang Agricultural University, Shenyang, China
| | - Qian Li
- College of Animal Science & Veterinary Medicine, Shenyang Agricultural University, Shenyang, China
| | - Xiaowei Wang
- College of Animal Science & Veterinary Medicine, Shenyang Agricultural University, Shenyang, China
| | - Zhiguo Xu
- Dalian Modern Agricultural Production Development Service Center, Dalian, China
| | - Yuyan Cong
- College of Animal Science & Veterinary Medicine, Shenyang Agricultural University, Shenyang, China
| | - Jing Chen
- College of Animal Science & Veterinary Medicine, Shenyang Agricultural University, Shenyang, China
| | - Zeying Wang
- College of Animal Science & Veterinary Medicine, Shenyang Agricultural University, Shenyang, China
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Zhang W, Jin M, Li T, Lu Z, Wang H, Yuan Z, Wei C. Whole-Genome Resequencing Reveals Selection Signal Related to Sheep Wool Fineness. Animals (Basel) 2023; 13:2944. [PMID: 37760343 PMCID: PMC10526036 DOI: 10.3390/ani13182944] [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: 08/03/2023] [Revised: 09/11/2023] [Accepted: 09/12/2023] [Indexed: 09/29/2023] Open
Abstract
Wool fineness affects the quality of wool, and some studies have identified about forty candidate genes that affect sheep wool fineness, but these genes often reveal only a certain proportion of the variation in wool thickness. We further explore additional genes associated with the fineness of sheep wool. Whole-genome resequencing of eight sheep breeds was performed to reveal selection signals associated with wool fineness, including four coarse wool and four fine/semi-fine wool sheep breeds. Multiple methods to reveal selection signals (Fst and θπ Ratio and XP-EHH) were applied for sheep wool fineness traits. In total, 269 and 319 genes were annotated in the fine wool (F vs. C) group and the coarse wool (C vs. F) group, such as LGR4, PIK3CA, and SEMA3C and NFIB, OPHN1, and THADA. In F vs. C, 269 genes were enriched in 15 significant GO Terms (p < 0.05) and 38 significant KEGG Pathways (p < 0.05), such as protein localization to plasma membrane (GO: 0072659) and Inositol phosphate metabolism (oas 00562). In C vs. F, 319 genes were enriched in 21 GO Terms (p < 0.05) and 16 KEGG Pathways (p < 0.05), such as negative regulation of focal adhesion assembly (GO: 0051895) and Axon guidance (oas 04360). Our study has uncovered genomic information pertaining to significant traits in sheep and has identified valuable candidate genes. This will pave the way for subsequent investigations into related traits.
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Affiliation(s)
- Wentao Zhang
- State Key Laboratory of Animal Biotech Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (W.Z.); (M.J.); (T.L.); (H.W.)
| | - Meilin Jin
- State Key Laboratory of Animal Biotech Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (W.Z.); (M.J.); (T.L.); (H.W.)
| | - Taotao Li
- State Key Laboratory of Animal Biotech Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (W.Z.); (M.J.); (T.L.); (H.W.)
| | - Zengkui Lu
- Key Laboratory of Animal Genetics and Breeding on Tibetan Plateau, Ministry of Agriculture and Rural Affairs, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China;
| | - Huihua Wang
- State Key Laboratory of Animal Biotech Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (W.Z.); (M.J.); (T.L.); (H.W.)
| | - Zehu Yuan
- College of Animal Science and Technology, Yangzhou University, Yangzhou 225000, China;
| | - Caihong Wei
- State Key Laboratory of Animal Biotech Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (W.Z.); (M.J.); (T.L.); (H.W.)
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Xu Y, Cai W, Chen R, Zhang X, Bai Z, Zhang Y, Qin Y, Gu M, Sun Y, Wu Y, Wang Z. Metabolomic Analysis and MRM Verification of Coarse and Fine Skin Tissues of Liaoning Cashmere Goat. Molecules 2022; 27:molecules27175483. [PMID: 36080249 PMCID: PMC9457707 DOI: 10.3390/molecules27175483] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2022] [Revised: 08/17/2022] [Accepted: 08/25/2022] [Indexed: 11/16/2022] Open
Abstract
One of the critical elements in evaluating the quality of cashmere is its fineness, but we still know little about how it is regulated at the metabolic level. In this paper, we use UHPLC–MS/MS detection and analysis technology to compare the difference in metabolites between coarse cashmere (CT_LCG) and fine cashmere (FT_LCG) skin of Liaoning cashmere goats. According to the data, under positive mode four metabolites were significantly up-regulated and seven were significantly down-regulated. In negative mode, seven metabolites were significantly up-regulated and fourteen metabolites were significantly down-regulated. The two groups’ most significant metabolites, Gly–Phe and taurochenodeoxycholate, may be crucial in controlling cashmere’s growth, development, and fineness. In addition, we enriched six KEGG pathways, of which cholesterol metabolism, primary bile acid biosynthesis, and bile secretion were enriched in positive and negative modes. These findings offer a new research idea for further study into the critical elements influencing cashmere’s fineness.
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