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Xiao M, Ruan Y, Huang J, Dai L, Xu J, Xu H. Association analysis between Acetyl-Coenzyme A Acyltransferase-1 gene polymorphism and growth traits in Xiangsu pigs. Front Genet 2024; 15:1346903. [PMID: 38756449 PMCID: PMC11096523 DOI: 10.3389/fgene.2024.1346903] [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: 11/30/2023] [Accepted: 04/15/2024] [Indexed: 05/18/2024] Open
Abstract
Introduction Acetyl-Coenzyme A Acyltransferase-1 (ACAA1) is a peroxisomal acyltransferase involved in fatty acid metabolism. Current evidence does not precisely reveal the effect of the ACAA1 gene on pig growth performance. Methods The present study assessed the mRNA expression levels of the ACAA1 gene in the heart, liver, spleen, lung, kidney of 6-month-old Xiangsu pigs and in the longissimus dorsi muscle at different growth stages (newborn, 6 months and 12 months of age) using RT-qPCR. The relationship between single-nucleotide polymorphisms (SNPs) of ACAA1 gene and growth traits in 6-month-old and 12-month-old Xiangsu pigs was investigated on 184 healthy Xiangsu pigs using Sanger sequencing. Results The ACAA1 gene was expressed in heart, liver, spleen, lung, kidney, and longissimus dorsi muscle of 6-month-old pigs, with the highest level of expression in the liver. ACAA1 gene expression in the longissimus dorsi muscle decreased with age (p < 0.01). In addition, four SNPs were identified in the ACAA1 gene, including exon g.48810 A>G (rs343060194), intron g.51546 T>C (rs319197012), exon g.55035 T>C (rs333279910), and exon g.55088 C>T (rs322138947). Hardy-Weinberg equilibrium (p > 0.05) was found for the four SNPs, and linkage disequilibrium (LD) analysis revealed a strong LD between g.55035 T>C (rs333279910) and g.55088 C>T (rs322138947) (r 2 = 1.000). Association analysis showed that g.48810 A>G (rs343060194), g.51546 T>C (rs319197012), g.55035 T>C (rs333279910), and g.55088 C>T (rs322138947) varied in body weight, body length, body height, abdominal circumference, leg and hip circumference and living backfat thickness between 6-month-old and 12-month-old Xiangsu pigs. Conclusion These findings strongly demonstrate that the ACAA1 gene can be exploited for marker-assisted selection to improve growth-related phenotypes in Xiangsu pigs and present new candidate genes for molecular pig breeding.
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Affiliation(s)
- Meimei Xiao
- Key Laboratory of Animal Genetics, Breeding and Reproduction in the Plateau Mountainous Region, Ministry of Education, Guizhou University, Guiyang, China
- Guizhou Provincial Key Laboratory of Animal Genetics, Breeding and Reproduction, Guizhou University, Guiyang, China
- College of Animal Science, Guizhou University, Guiyang, China
| | - Yong Ruan
- Key Laboratory of Animal Genetics, Breeding and Reproduction in the Plateau Mountainous Region, Ministry of Education, Guizhou University, Guiyang, China
- Guizhou Provincial Key Laboratory of Animal Genetics, Breeding and Reproduction, Guizhou University, Guiyang, China
- College of Animal Science, Guizhou University, Guiyang, China
| | - Jiajin Huang
- Key Laboratory of Animal Genetics, Breeding and Reproduction in the Plateau Mountainous Region, Ministry of Education, Guizhou University, Guiyang, China
- Guizhou Provincial Key Laboratory of Animal Genetics, Breeding and Reproduction, Guizhou University, Guiyang, China
- College of Animal Science, Guizhou University, Guiyang, China
| | - Lingang Dai
- Key Laboratory of Animal Genetics, Breeding and Reproduction in the Plateau Mountainous Region, Ministry of Education, Guizhou University, Guiyang, China
- Guizhou Provincial Key Laboratory of Animal Genetics, Breeding and Reproduction, Guizhou University, Guiyang, China
- College of Animal Science, Guizhou University, Guiyang, China
| | - Jiali Xu
- Key Laboratory of Animal Genetics, Breeding and Reproduction in the Plateau Mountainous Region, Ministry of Education, Guizhou University, Guiyang, China
- Guizhou Provincial Key Laboratory of Animal Genetics, Breeding and Reproduction, Guizhou University, Guiyang, China
- College of Animal Science, Guizhou University, Guiyang, China
| | - Houqiang Xu
- Key Laboratory of Animal Genetics, Breeding and Reproduction in the Plateau Mountainous Region, Ministry of Education, Guizhou University, Guiyang, China
- Guizhou Provincial Key Laboratory of Animal Genetics, Breeding and Reproduction, Guizhou University, Guiyang, China
- College of Animal Science, Guizhou University, Guiyang, China
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Yang R, Zhou D, Tan X, Zhao Z, Lv Y, Tian X, Ren L, Wang Y, Li J, Zhao Y, Zhang J. Genome-Wide Association Study of Body Conformation Traits in Tashi Goats ( Capra hircus). Animals (Basel) 2024; 14:1145. [PMID: 38672293 PMCID: PMC11047570 DOI: 10.3390/ani14081145] [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: 02/29/2024] [Revised: 04/01/2024] [Accepted: 04/03/2024] [Indexed: 04/28/2024] Open
Abstract
Identifying genetic markers of economically valuable traits has practical benefits for the meat goat industry. To better understand the genomic variations influencing body conformation traits, a genome-wide association study was performed on Tashi goats, an indigenous Chinese goat breed. A total of 155 Tashi goats were phenotyped for eight body conformation traits: body height, body length, chest depth, chest width, chest girth, rump width, rump height, and cannon bone circumference. Then, 100 Tashi goats were randomly selected for whole-genome sequencing and genotyped. We obtained 1676.4 Gb of raw data with an average sequencing depth of 6.2X. Clean reads were aligned to the ARS1.2 reference genome, and 11,257,923 single nucleotide polymorphisms (SNPs) were identified. The structure analysis showed that these Tashi goats were almost not genetically related. The 109, 20, 52, 14, 62, 51, 70, and 7 SNPs were significantly associated with body height, body length, chest depth, chest width, chest girth, rump width, rump height, and cannon bone circumference. Within the ±500 kb region of significant SNPs, 183 genes were annotated. The most significantly enriched KEGG pathway was "olfactory transduction", and the most significantly enriched gene ontology (GO) terms were "cellular process", "cellular anatomical entity", and "molecular transducer activity". Interestingly, we found several SNPs on chromosomes 10 and 11 that have been identified multiple times for all eight body conformation traits located in two fragments (114 kb and 1.03 Mb). In chr.10:25988403-26102739, the six SNPs were tightly linked, the TACTAG genotype was the highest at 91.8%, and the FNTB (Farnesyltransferase, CAAX Box Beta) and CHURC1 (Churchill Domain Containing 1) genes were located. In chr.11:88216493-89250659, ten SNPs were identified with several dependent linkage disequilibrium (LD) blocks, and seven related genes were annotated, but no significant SNP was located in them. Our results provide valuable biological information for improving growth performance with practical applications for genomic selection in goats.
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Affiliation(s)
- Rong Yang
- Guizhou Provincial Breeding Livestock and Poultry Germplasm Determination Center, Guiyang 550018, China; (R.Y.); (Y.L.)
| | - Di Zhou
- Guizhou Provincial Breeding Livestock and Poultry Germplasm Determination Center, Guiyang 550018, China; (R.Y.); (Y.L.)
| | - Xiaoshan Tan
- Guizhou Provincial Breeding Livestock and Poultry Germplasm Determination Center, Guiyang 550018, China; (R.Y.); (Y.L.)
| | - Zhonghai Zhao
- Zunyi Animal Husbandry and Fishery Station, Zunyi 563000, China
| | - Yanli Lv
- Guizhou Provincial Breeding Livestock and Poultry Germplasm Determination Center, Guiyang 550018, China; (R.Y.); (Y.L.)
| | - Xingzhou Tian
- College of Animal Science, Guizhou University, Guiyang 550025, China
| | - Liqun Ren
- Guizhou Provincial Breeding Livestock and Poultry Germplasm Determination Center, Guiyang 550018, China; (R.Y.); (Y.L.)
| | - Yan Wang
- Guizhou Provincial Breeding Livestock and Poultry Germplasm Determination Center, Guiyang 550018, China; (R.Y.); (Y.L.)
| | - Jun Li
- Guizhou Provincial Breeding Livestock and Poultry Germplasm Determination Center, Guiyang 550018, China; (R.Y.); (Y.L.)
| | - Yongju Zhao
- College of Animal Science and Technology, Southwest University, Chongqing 400715, China;
| | - Jipan Zhang
- College of Animal Science and Technology, Southwest University, Chongqing 400715, China;
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Volkova NA, Romanov MN, Abdelmanova AS, Larionova PV, German NY, Vetokh AN, Shakhin AV, Volkova LA, Sermyagin AA, Anshakov DV, Fisinin VI, Griffin DK, Sölkner J, Brem G, McEwan JC, Brauning R, Zinovieva NA. Genome-Wide Association Study Revealed Putative SNPs and Candidate Genes Associated with Growth and Meat Traits in Japanese Quail. Genes (Basel) 2024; 15:294. [PMID: 38540354 PMCID: PMC10970133 DOI: 10.3390/genes15030294] [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: 12/15/2023] [Revised: 02/08/2024] [Accepted: 02/23/2024] [Indexed: 06/14/2024] Open
Abstract
The search for SNPs and candidate genes that determine the manifestation of major selected traits is one crucial objective for genomic selection aimed at increasing poultry production efficiency. Here, we report a genome-wide association study (GWAS) for traits characterizing meat performance in the domestic quail. A total of 146 males from an F2 reference population resulting from crossing a fast (Japanese) and a slow (Texas White) growing breed were examined. Using the genotyping-by-sequencing technique, genomic data were obtained for 115,743 SNPs (92,618 SNPs after quality control) that were employed in this GWAS. The results identified significant SNPs associated with the following traits at 8 weeks of age: body weight (nine SNPs), daily body weight gain (eight SNPs), dressed weight (33 SNPs), and weights of breast (18 SNPs), thigh (eight SNPs), and drumstick (three SNPs). Also, 12 SNPs and five candidate genes (GNAL, DNAJC6, LEPR, SPAG9, and SLC27A4) shared associations with three or more traits. These findings are consistent with the understanding of the genetic complexity of body weight-related traits in quail. The identified SNPs and genes can be used in effective quail breeding as molecular genetic markers for growth and meat characteristics for the purpose of genetic improvement.
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Affiliation(s)
- Natalia A. Volkova
- L. K. Ernst Federal Research Center for Animal Husbandry, Dubrovitsy, Podolsk 142132, Moscow Oblast, Russia; (N.A.V.); (A.S.A.); (P.V.L.); (N.Y.G.); (A.N.V.); (A.V.S.); (L.A.V.); (A.A.S.)
| | - Michael N. Romanov
- L. K. Ernst Federal Research Center for Animal Husbandry, Dubrovitsy, Podolsk 142132, Moscow Oblast, Russia; (N.A.V.); (A.S.A.); (P.V.L.); (N.Y.G.); (A.N.V.); (A.V.S.); (L.A.V.); (A.A.S.)
- School of Biosciences, University of Kent, Canterbury CT2 7NJ, Kent, UK;
| | - Alexandra S. Abdelmanova
- L. K. Ernst Federal Research Center for Animal Husbandry, Dubrovitsy, Podolsk 142132, Moscow Oblast, Russia; (N.A.V.); (A.S.A.); (P.V.L.); (N.Y.G.); (A.N.V.); (A.V.S.); (L.A.V.); (A.A.S.)
| | - Polina V. Larionova
- L. K. Ernst Federal Research Center for Animal Husbandry, Dubrovitsy, Podolsk 142132, Moscow Oblast, Russia; (N.A.V.); (A.S.A.); (P.V.L.); (N.Y.G.); (A.N.V.); (A.V.S.); (L.A.V.); (A.A.S.)
| | - Nadezhda Yu. German
- L. K. Ernst Federal Research Center for Animal Husbandry, Dubrovitsy, Podolsk 142132, Moscow Oblast, Russia; (N.A.V.); (A.S.A.); (P.V.L.); (N.Y.G.); (A.N.V.); (A.V.S.); (L.A.V.); (A.A.S.)
| | - Anastasia N. Vetokh
- L. K. Ernst Federal Research Center for Animal Husbandry, Dubrovitsy, Podolsk 142132, Moscow Oblast, Russia; (N.A.V.); (A.S.A.); (P.V.L.); (N.Y.G.); (A.N.V.); (A.V.S.); (L.A.V.); (A.A.S.)
| | - Alexey V. Shakhin
- L. K. Ernst Federal Research Center for Animal Husbandry, Dubrovitsy, Podolsk 142132, Moscow Oblast, Russia; (N.A.V.); (A.S.A.); (P.V.L.); (N.Y.G.); (A.N.V.); (A.V.S.); (L.A.V.); (A.A.S.)
| | - Ludmila A. Volkova
- L. K. Ernst Federal Research Center for Animal Husbandry, Dubrovitsy, Podolsk 142132, Moscow Oblast, Russia; (N.A.V.); (A.S.A.); (P.V.L.); (N.Y.G.); (A.N.V.); (A.V.S.); (L.A.V.); (A.A.S.)
| | - Alexander A. Sermyagin
- L. K. Ernst Federal Research Center for Animal Husbandry, Dubrovitsy, Podolsk 142132, Moscow Oblast, Russia; (N.A.V.); (A.S.A.); (P.V.L.); (N.Y.G.); (A.N.V.); (A.V.S.); (L.A.V.); (A.A.S.)
| | - Dmitry V. Anshakov
- Breeding and Genetic Center “Zagorsk Experimental Breeding Farm”—Branch of the Federal Research Center “All-Russian Poultry Research and Technological Institute”, Russian Academy of Sciences, Sergiev Posad 141311, Moscow Oblast, Russia;
| | - Vladimir I. Fisinin
- Federal Research Center “All-Russian Poultry Research and Technological Institute” of the Russian Academy of Sciences, Sergiev Posad 141311, Moscow Oblast, Russia;
| | - Darren K. Griffin
- School of Biosciences, University of Kent, Canterbury CT2 7NJ, Kent, UK;
| | - Johann Sölkner
- Institute of Livestock Sciences (NUWI), University of Natural Resources and Life Sciences Vienna, 1180 Vienna, Austria;
| | - Gottfried Brem
- Institute of Animal Breeding and Genetics, University of Veterinary Medicine, 1210 Vienna, Austria;
| | - John C. McEwan
- AgResearch, Invermay Agricultural Centre, Mosgiel 9053, New Zealand; (J.C.M.); (R.B.)
| | - Rudiger Brauning
- AgResearch, Invermay Agricultural Centre, Mosgiel 9053, New Zealand; (J.C.M.); (R.B.)
| | - Natalia A. Zinovieva
- L. K. Ernst Federal Research Center for Animal Husbandry, Dubrovitsy, Podolsk 142132, Moscow Oblast, Russia; (N.A.V.); (A.S.A.); (P.V.L.); (N.Y.G.); (A.N.V.); (A.V.S.); (L.A.V.); (A.A.S.)
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Khan MZ, Chen W, Huang B, Liu X, Wang X, Liu Y, Chai W, Wang C. Advancements in Genetic Marker Exploration for Livestock Vertebral Traits with a Focus on China. Animals (Basel) 2024; 14:594. [PMID: 38396562 PMCID: PMC10885964 DOI: 10.3390/ani14040594] [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: 12/25/2023] [Revised: 01/29/2024] [Accepted: 02/07/2024] [Indexed: 02/25/2024] Open
Abstract
In livestock breeding, the number of vertebrae has gained significant attention due to its impact on carcass quality and quantity. Variations in vertebral traits have been observed across different animal species and breeds, with a strong correlation to growth and meat production. Furthermore, vertebral traits are classified as quantitative characteristics. Molecular marker techniques, such as marker-assisted selection (MAS), have emerged as efficient tools to identify genetic markers associated with vertebral traits. In the current review, we highlight some key potential genes and their polymorphisms that play pivotal roles in controlling vertebral traits (development, length, and number) in various livestock species, including pigs, donkeys, and sheep. Specific genetic variants within these genes have been linked to vertebral development, number, and length, offering valuable insights into the genetic mechanisms governing vertebral traits. This knowledge has significant implications for selective breeding strategies to enhance structural characteristics and meat quantity and quality in livestock, ultimately improving the efficiency and quality of the animal husbandry industry.
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Affiliation(s)
- Muhammad Zahoor Khan
- Liaocheng Research Institute of Donkey High-Efficiency Breeding and Ecological Feeding, Liaocheng University, Liaocheng 522000, China
| | | | | | | | | | | | | | - Changfa Wang
- Liaocheng Research Institute of Donkey High-Efficiency Breeding and Ecological Feeding, Liaocheng University, Liaocheng 522000, China
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Zhao X, Qiu Y, Meng F, Zhuang Z, Ruan D, Wu J, Ma F, Zheng E, Cai G, Yang J, Yang M, Wu Z. Genome-wide association studies for loin muscle area, loin muscle depth and backfat thickness in DLY pigs. Anim Genet 2024; 55:134-139. [PMID: 38098441 DOI: 10.1111/age.13386] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2022] [Revised: 10/17/2023] [Accepted: 11/28/2023] [Indexed: 01/04/2024]
Abstract
This study aimed at identifying genes associated with loin muscle area (LMA), loin muscle depth (LMD) and backfat thickness (BFT). We performed single-trait and multi-trait genome-wide association studies (GWASs) after genotyping 685 Duroc × (Landrace × Yorkshire) (DLY) pigs using the Geneseek Porcine 50K SNP chip. In the single-trait GWASs, we identified two, eight and two significant SNPs associated with LMA, LMD and BFT, respectively, and searched genes within the 1 Mb region near the significant SNPs with relevant functions as candidate genes. Consequently, we identified one (DOCK5), three (PID1, PITX2, ELOVL6) and three (CCR1, PARP14, CASR) promising candidate genes for LMA, LMD and BFT, respectively. Moreover, the multi-trait GWAS identified four significant SNPs associated with the three traits. In conclusion, the GWAS analysis of LMA, LMD and BFT in a DLY pig population identified several associated SNPs and candidate genes, further deepening our understanding of the genetic basis of these traits, and they may be useful for marker-assisted selection to improve the three traits in DLY pigs.
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Affiliation(s)
- Xiang Zhao
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, China
| | - Yibin Qiu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, China
| | - Fanming Meng
- State Key Laboratory of Livestock and Poultry Breeding/Guangdong Key Laboratory of Animal Breeding and Nutrition, Institute of Animal Science, Guangdong Academy of Agricultural Sciences, Guangzhou, Guangdong, China
| | - Zhanwei Zhuang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, China
| | - Donglin Ruan
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, China
| | - Jie Wu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, China
| | - Fucai Ma
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, China
| | - Enqin Zheng
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, China
- Guangdong Provincial Key Laboratory of Agro-animal Genomics and Molecular Breeding, South China Agricultural University, Guangzhou, Guangdong, China
| | - Gengyuan Cai
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, China
- Guangdong Provincial Key Laboratory of Agro-animal Genomics and Molecular Breeding, South China Agricultural University, Guangzhou, Guangdong, China
- Guangdong Zhongxin Breeding Technology Co., Ltd, Guangzhou, Guangdong, China
| | - Jie Yang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, China
- Guangdong Provincial Key Laboratory of Agro-animal Genomics and Molecular Breeding, South China Agricultural University, Guangzhou, Guangdong, China
| | - Ming Yang
- Guangdong Zhongxin Breeding Technology Co., Ltd, Guangzhou, Guangdong, China
- College of Animal Science and Technology, Zhongkai University of Agriculture and Engineering, Guangzhou, Guangdong, China
| | - Zhenfang Wu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, China
- Guangdong Provincial Key Laboratory of Agro-animal Genomics and Molecular Breeding, South China Agricultural University, Guangzhou, Guangdong, China
- Yunfu Subcenter of Guangdong Laboratory for Lingnan Modern Agriculture, Yunfu, Guangdong, China
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Gao X, Zhou S, Liu Z, Ruan D, Wu J, Quan J, Zheng E, Yang J, Cai G, Wu Z, Yang M. Genome-Wide Association Study for Somatic Skeletal Traits in Duroc × (Landrace × Yorkshire) Pigs. Animals (Basel) 2023; 14:37. [PMID: 38200769 PMCID: PMC10778498 DOI: 10.3390/ani14010037] [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: 10/24/2023] [Revised: 12/15/2023] [Accepted: 12/18/2023] [Indexed: 01/12/2024] Open
Abstract
The pig bone weight trait holds significant economic importance in southern China. To expedite the selection of the pig bone weight trait in pig breeding, we conducted molecular genetic research on these specific traits. These traits encompass the bone weight of the scapula (SW), front leg bone weight (including humerus and ulna) (FLBW), hind leg bone weight (including femur and tibia) (HLBW), and spine bone weight (SBW). Up until now, the genetic structure related to these traits has not been thoroughly explored, primarily due to challenges associated with obtaining the phenotype data. In this study, we utilized genome-wide association studies (GWAS) to discern single nucleotide polymorphisms (SNPs) and genes associated with four bone weight traits within a population comprising 571 Duroc × (Landrace × Yorkshire) hybrid pigs (DLY). In the analyses, we employed a mixed linear model, and for the correction of multiple tests, both the false discovery rate and Bonferroni methods were utilized. Following functional annotation, candidate genes were identified based on their proximity to the candidate sites and their association with the bone weight traits. This study represents the inaugural application of GWAS for the identification of SNPs associated with individual bone weight in DLY pigs. Our analysis unveiled 26 SNPs and identified 12 promising candidate genes (OPRM1, SLC44A5, WASHC4, NOPCHAP1, RHOT1, GLP1R, TGFB3, PLCB1, TLR4, KCNJ2, ABCA6, and ABCA9) associated with the four bone weight traits. Furthermore, our findings on the genetic mechanisms influencing pig bone weight offer valuable insights as a reference for the genetic enhancement of pig bone traits.
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Affiliation(s)
- Xin Gao
- College of Animal Science and Technology, Zhongkai University of Agriculture and Engineering, Guangzhou 510225, China; (X.G.); (S.Z.); (Z.L.)
| | - Shenping Zhou
- College of Animal Science and Technology, Zhongkai University of Agriculture and Engineering, Guangzhou 510225, China; (X.G.); (S.Z.); (Z.L.)
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou 510642, China
| | - Zhihong Liu
- College of Animal Science and Technology, Zhongkai University of Agriculture and Engineering, Guangzhou 510225, China; (X.G.); (S.Z.); (Z.L.)
| | - Donglin Ruan
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou 510642, China
| | - Jie Wu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou 510642, China
| | - Jianping Quan
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou 510642, China
| | - Enqin Zheng
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou 510642, China
| | - Jie Yang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou 510642, China
| | - Gengyuan Cai
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou 510642, China
| | - Zhenfang Wu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou 510642, China
| | - Ming Yang
- College of Animal Science and Technology, Zhongkai University of Agriculture and Engineering, Guangzhou 510225, China; (X.G.); (S.Z.); (Z.L.)
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Zhou F, Lin D, Dong L, Hong Y, Zeng H, Cai G, Ye J, Wu Z. Genetic evaluation for production and body size traits using different animal models in purebred-Duroc pigs. Front Vet Sci 2023; 10:1274266. [PMID: 38164395 PMCID: PMC10758212 DOI: 10.3389/fvets.2023.1274266] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Accepted: 11/27/2023] [Indexed: 01/03/2024] Open
Abstract
Duroc pigs are popular crossbred terminal sires, and accurate assessment of genetic parameters in the population can help to rationalize breeding programmes. The principle aim of this study were to evaluate the genetic parameters of production (birth weight, BW; age at 115 kg, AGE; feed conversion ratio, FCR) and body size (body length, BL; body height, BH; front cannon circumference, FCC) traits of Duroc pigs. The second objective was to analyze the fit of different genetic assessment models. The variance components and correlations of BW (28,348 records), AGE (28,335 records), FCR (11,135 records), BL (31,544 records), BH (21,862 records), and FCC (14,684 records) traits were calculated by using DMU and AIREMLF90 from BLUPF90 package. In the common environment model, the heritability of BW, AGE, FCR, BL, BH, and FCC traits were 0.17 ± 0.014, 0.30 ± 0.019, 0.28 ± 0.024, 0.16 ± 0.013, 0.14 ± 0.017, and 0.081 ± 0.016, with common litter effect values of 0.25, 0.20, 0.18, 0.23, 0.19, and 0.16, respectively. According to the results of the Akaike information criterion (AIC) calculations, models with smaller AIC values have a better fit. We found that the common environment model with litter effects as random effects for estimating genetic parameters had a better fit. In this Model, the estimated genetic correlations between AGE with BW, FCR, BL, BH, and FCC traits were -0.28 (0.040), 0.76 (0.038), -0.71 (0.036), -0.44 (0.060), and -0.60 (0.073), respectively, with phenotypic correlations of -0.17, 0.52, -0.22, -0.13 and -0.24, respectively. In our analysis of genetic trends for six traits in the Duroc population from 2012 to 2021, we observed significant genetic trends for AGE, BL, and BH. Particularly noteworthy is the rapid decline in the genetic trend for AGE, indicating an enhancement in the pig's growth rate through selective breeding. Therefore, we believe that some challenging-to-select traits can benefit from the genetic correlations between traits. By selecting easily measurable traits, they can gain from synergistic selection effects, leading to genetic progress. Conducting population genetic parameter analysis can assist us in devising breeding strategies.
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Affiliation(s)
- Fuchen Zhou
- National Engineering Research Center for Breeding Swine Industry and College of Animal Science, South China Agricultural University, Guangzhou, China
| | - Danyang Lin
- National Engineering Research Center for Breeding Swine Industry and College of Animal Science, South China Agricultural University, Guangzhou, China
| | - Linsong Dong
- National Engineering Research Center for Breeding Swine Industry, Wens Foodstuff Group Co., Ltd., Yunfu, China
| | - Yifeng Hong
- National Engineering Research Center for Breeding Swine Industry and College of Animal Science, South China Agricultural University, Guangzhou, China
| | - Haiyu Zeng
- National Engineering Research Center for Breeding Swine Industry, Wens Foodstuff Group Co., Ltd., Yunfu, China
| | - Gengyuan Cai
- National Engineering Research Center for Breeding Swine Industry and College of Animal Science, South China Agricultural University, Guangzhou, China
- National Engineering Research Center for Breeding Swine Industry, Wens Foodstuff Group Co., Ltd., Yunfu, China
| | - Jian Ye
- National Engineering Research Center for Breeding Swine Industry, Wens Foodstuff Group Co., Ltd., Yunfu, China
| | - Zhenfang Wu
- National Engineering Research Center for Breeding Swine Industry and College of Animal Science, South China Agricultural University, Guangzhou, China
- National Engineering Research Center for Breeding Swine Industry, Wens Foodstuff Group Co., Ltd., Yunfu, China
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8
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Liu Y, Zhang Y, Zhou F, Yao Z, Zhan Y, Fan Z, Meng X, Zhang Z, Liu L, Yang J, Wu Z, Cai G, Zheng E. Increased Accuracy of Genomic Prediction Using Preselected SNPs from GWAS with Imputed Whole-Genome Sequence Data in Pigs. Animals (Basel) 2023; 13:3871. [PMID: 38136908 PMCID: PMC10740755 DOI: 10.3390/ani13243871] [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: 11/02/2023] [Revised: 12/13/2023] [Accepted: 12/14/2023] [Indexed: 12/24/2023] Open
Abstract
Enhancing the accuracy of genomic prediction is a key goal in genomic selection (GS) research. Integrating prior biological information into GS methods using appropriate models can improve prediction accuracy for complex traits. Genome-wide association study (GWAS) is widely utilized to identify potential candidate loci associated with complex traits in livestock and poultry, offering essential genomic insights. In this study, a GWAS was conducted on 685 Duroc × Landrace × Yorkshire (DLY) pigs to extract significant single-nucleotide polymorphisms (SNPs) as genomic features. We compared two GS models, genomic best linear unbiased prediction (GBLUP) and genomic feature BLUP (GFBLUP), by using imputed whole-genome sequencing (WGS) data on 651 Yorkshire pigs. The results revealed that the GBLUP model achieved prediction accuracies of 0.499 for backfat thickness (BFT) and 0.423 for loin muscle area (LMA). By applying the GFBLUP model with GWAS-based SNP preselection, the average prediction accuracies for BFT and LMA traits reached 0.491 and 0.440, respectively. Specifically, the GFBLUP model displayed a 4.8% enhancement in predicting LMA compared to the GBLUP model. These findings suggest that, in certain scenarios, the GFBLUP model may offer superior genomic prediction accuracy when compared to the GBLUP model, underscoring the potential value of incorporating genomic features to refine GS models.
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Affiliation(s)
- Yiyi Liu
- National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (Y.L.); (Y.Z.); (F.Z.); (Z.Y.); (Y.Z.); (Z.F.); (X.M.); (Z.Z.); (L.L.); (J.Y.); (Z.W.)
- Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, South China Agricultural University, Guangzhou 510642, China
| | - Yuling Zhang
- National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (Y.L.); (Y.Z.); (F.Z.); (Z.Y.); (Y.Z.); (Z.F.); (X.M.); (Z.Z.); (L.L.); (J.Y.); (Z.W.)
- Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, South China Agricultural University, Guangzhou 510642, China
| | - Fuchen Zhou
- National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (Y.L.); (Y.Z.); (F.Z.); (Z.Y.); (Y.Z.); (Z.F.); (X.M.); (Z.Z.); (L.L.); (J.Y.); (Z.W.)
- Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, South China Agricultural University, Guangzhou 510642, China
| | - Zekai Yao
- National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (Y.L.); (Y.Z.); (F.Z.); (Z.Y.); (Y.Z.); (Z.F.); (X.M.); (Z.Z.); (L.L.); (J.Y.); (Z.W.)
- Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, South China Agricultural University, Guangzhou 510642, China
| | - Yuexin Zhan
- National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (Y.L.); (Y.Z.); (F.Z.); (Z.Y.); (Y.Z.); (Z.F.); (X.M.); (Z.Z.); (L.L.); (J.Y.); (Z.W.)
- Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, South China Agricultural University, Guangzhou 510642, China
| | - Zhenfei Fan
- National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (Y.L.); (Y.Z.); (F.Z.); (Z.Y.); (Y.Z.); (Z.F.); (X.M.); (Z.Z.); (L.L.); (J.Y.); (Z.W.)
- Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, South China Agricultural University, Guangzhou 510642, China
| | - Xianglun Meng
- National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (Y.L.); (Y.Z.); (F.Z.); (Z.Y.); (Y.Z.); (Z.F.); (X.M.); (Z.Z.); (L.L.); (J.Y.); (Z.W.)
- Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, South China Agricultural University, Guangzhou 510642, China
| | - Zebin Zhang
- National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (Y.L.); (Y.Z.); (F.Z.); (Z.Y.); (Y.Z.); (Z.F.); (X.M.); (Z.Z.); (L.L.); (J.Y.); (Z.W.)
- Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, South China Agricultural University, Guangzhou 510642, China
| | - Langqing Liu
- National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (Y.L.); (Y.Z.); (F.Z.); (Z.Y.); (Y.Z.); (Z.F.); (X.M.); (Z.Z.); (L.L.); (J.Y.); (Z.W.)
- Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, South China Agricultural University, Guangzhou 510642, China
| | - Jie Yang
- National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (Y.L.); (Y.Z.); (F.Z.); (Z.Y.); (Y.Z.); (Z.F.); (X.M.); (Z.Z.); (L.L.); (J.Y.); (Z.W.)
- Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, South China Agricultural University, Guangzhou 510642, China
| | - Zhenfang Wu
- National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (Y.L.); (Y.Z.); (F.Z.); (Z.Y.); (Y.Z.); (Z.F.); (X.M.); (Z.Z.); (L.L.); (J.Y.); (Z.W.)
- Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, South China Agricultural University, Guangzhou 510642, China
- Guangdong Zhongxin Breeding Technology Co., Ltd., Guangzhou 510642, China
| | - Gengyuan Cai
- National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (Y.L.); (Y.Z.); (F.Z.); (Z.Y.); (Y.Z.); (Z.F.); (X.M.); (Z.Z.); (L.L.); (J.Y.); (Z.W.)
- Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, South China Agricultural University, Guangzhou 510642, China
- Guangdong Zhongxin Breeding Technology Co., Ltd., Guangzhou 510642, China
| | - Enqin Zheng
- National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (Y.L.); (Y.Z.); (F.Z.); (Z.Y.); (Y.Z.); (Z.F.); (X.M.); (Z.Z.); (L.L.); (J.Y.); (Z.W.)
- Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, South China Agricultural University, Guangzhou 510642, China
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Deng S, Qiu Y, Zhuang Z, Wu J, Li X, Ruan D, Xu C, Zheng E, Yang M, Cai G, Yang J, Wu Z, Huang S. Genome-Wide Association Study of Body Conformation Traits in a Three-Way Crossbred Commercial Pig Population. Animals (Basel) 2023; 13:2414. [PMID: 37570223 PMCID: PMC10417164 DOI: 10.3390/ani13152414] [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: 05/24/2023] [Revised: 06/28/2023] [Accepted: 07/05/2023] [Indexed: 08/13/2023] Open
Abstract
Body conformation is the most direct production index, which can fully reflect pig growth status and is closely related to critical economic traits. In this study, we conducted a genome-wide association study (GWAS) on body conformation traits in a population of 1518 Duroc × (Landrace × Yorkshire) commercial pigs. These traits included body length (BL), body height (BH), chest circumference (CC), abdominal circumference (AC), and waist circumference (WC). Both the mixed linear model (MLM) and fixed and random model circulating probability unification (FarmCPU) approaches were employed for the analysis. Our findings revealed 60 significant single nucleotide polymorphisms (SNPs) associated with these body conformation traits in the crossbred pig population. Specifically, sixteen SNPs were significantly associated with BL, three SNPs with BH, thirteen SNPs with CC, twelve SNPs with AC, and sixteen SNPs with WC. Moreover, we identified several promising candidate genes located within the genomic regions associated with body conformation traits. These candidate genes include INTS10, KIRREL3, SOX21, BMP2, MAP4K3, SOD3, FAM160B1, ATL2, SPRED2, SEC16B, and RASAL2. Furthermore, our analysis revealed a novel significant quantitative trait locus (QTL) on SSC7 specifically associated with waist circumference, spanning an 84 kb interval. Overall, the identification of these significant SNPs and potential candidate genes in crossbred commercial pigs enhances our understanding of the genetic basis underlying body conformation traits. Additionally, these findings provide valuable genetic resources for pig breeding programs.
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Affiliation(s)
- Shaoxiong Deng
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou 510642, China; (S.D.); (Y.Q.); (Z.Z.); (J.W.); (X.L.); (D.R.); (C.X.); (E.Z.); (G.C.); (J.Y.)
| | - Yibin Qiu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou 510642, China; (S.D.); (Y.Q.); (Z.Z.); (J.W.); (X.L.); (D.R.); (C.X.); (E.Z.); (G.C.); (J.Y.)
| | - Zhanwei Zhuang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou 510642, China; (S.D.); (Y.Q.); (Z.Z.); (J.W.); (X.L.); (D.R.); (C.X.); (E.Z.); (G.C.); (J.Y.)
| | - Jie Wu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou 510642, China; (S.D.); (Y.Q.); (Z.Z.); (J.W.); (X.L.); (D.R.); (C.X.); (E.Z.); (G.C.); (J.Y.)
| | - Xuehua Li
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou 510642, China; (S.D.); (Y.Q.); (Z.Z.); (J.W.); (X.L.); (D.R.); (C.X.); (E.Z.); (G.C.); (J.Y.)
| | - Donglin Ruan
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou 510642, China; (S.D.); (Y.Q.); (Z.Z.); (J.W.); (X.L.); (D.R.); (C.X.); (E.Z.); (G.C.); (J.Y.)
| | - Cineng Xu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou 510642, China; (S.D.); (Y.Q.); (Z.Z.); (J.W.); (X.L.); (D.R.); (C.X.); (E.Z.); (G.C.); (J.Y.)
| | - Enqing Zheng
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou 510642, China; (S.D.); (Y.Q.); (Z.Z.); (J.W.); (X.L.); (D.R.); (C.X.); (E.Z.); (G.C.); (J.Y.)
- Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, South China Agricultural University, Guangzhou 510642, China
| | - Ming Yang
- College of Animal Science and Technology, Zhongkai University of Agriculture and Engineering, Guangzhou 510225, China;
| | - Gengyuan Cai
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou 510642, China; (S.D.); (Y.Q.); (Z.Z.); (J.W.); (X.L.); (D.R.); (C.X.); (E.Z.); (G.C.); (J.Y.)
- Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, South China Agricultural University, Guangzhou 510642, China
- Yunfu Subcenter of Guangdong Laboratory for Lingnan Modern Agriculture, Yunfu 527400, China
| | - Jie Yang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou 510642, China; (S.D.); (Y.Q.); (Z.Z.); (J.W.); (X.L.); (D.R.); (C.X.); (E.Z.); (G.C.); (J.Y.)
- Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, South China Agricultural University, Guangzhou 510642, China
| | - Zhenfang Wu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou 510642, China; (S.D.); (Y.Q.); (Z.Z.); (J.W.); (X.L.); (D.R.); (C.X.); (E.Z.); (G.C.); (J.Y.)
- Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, South China Agricultural University, Guangzhou 510642, China
- Yunfu Subcenter of Guangdong Laboratory for Lingnan Modern Agriculture, Yunfu 527400, China
| | - Sixiu Huang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou 510642, China; (S.D.); (Y.Q.); (Z.Z.); (J.W.); (X.L.); (D.R.); (C.X.); (E.Z.); (G.C.); (J.Y.)
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10
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Zhao Y, He S, Huang J, Liu M. Genome-Wide Association Analysis of Muscle pH in Texel Sheep × Altay Sheep F 2 Resource Population. Animals (Basel) 2023; 13:2162. [PMID: 37443959 DOI: 10.3390/ani13132162] [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: 05/08/2023] [Revised: 05/29/2023] [Accepted: 06/25/2023] [Indexed: 07/15/2023] Open
Abstract
pH was one of the important meat quality traits, which was an important factor affecting the storage/shelf life and quality of meat in meat production. In order to find a way to extend the storage/shelf life, the pH values (pH45min, pH24h, pH48h and pH72h) of the longissimus dorsi muscles in F2 individuals of 462 Texel sheep × Altay sheep were determined, genotyping was performed using Illumina Ovine SNP 600 K BeadChip and whole genome resequencing technology, a genome-wide association analysis (GWAS) was used to screen the candidate genes and molecular markers for pH values related to the quality traits of mutton, and the effects of population stratification were detected by Q-Q plots. The results showed that the pH population stratification analysis did not find significant systemic bias, and there was no obvious population stratification effect. The results of the association analysis showed that 28 SNPs significantly associated with pH reached the level of genomic significance. The candidate gene associated with pH45min was identified as the CCDC92 gene by gene annotation and a search of the literature. Candidate genes related to pH24h were KDM4C, TGFB2 and GOT2 genes. The candidate genes related to pH48h were MMP12 and MMP13 genes. The candidate genes related to pH72h were HILPDA and FAT1 genes. Further bioinformatics analyses showed 24 gene ontology terms and five signaling pathways that were significantly enriched (p ≤ 0.05). Many terms and pathways were related to cellular components, processes of protein modification, the activity of protein dimerization and hydrolase activity. These identified SNPs and genes could provide useful information about meat and the storage/shelf life of meat, thereby extending the storage/shelf life and quality of meat.
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Affiliation(s)
- Yilong Zhao
- College of Animal Science and Technology, Shihezi University, Shihezi 832000, China
- College of Animal Science and Technology, Xinjiang Agricultural Vocational and Technical College, Changji 831100, China
| | - Sangang He
- Biotechnology Institute, Xinjiang Academy of Animal Science, Urumqi 830013, China
| | | | - Mingjun Liu
- Biotechnology Institute, Xinjiang Academy of Animal Science, Urumqi 830013, China
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11
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Hu J, Chen J, Hou Q, Xu X, Ren J, Ma L, Yan X. Core-predominant gut fungus Kazachstania slooffiae promotes intestinal epithelial glycolysis via lysine desuccinylation in pigs. MICROBIOME 2023; 11:31. [PMID: 36814349 PMCID: PMC9948344 DOI: 10.1186/s40168-023-01468-3] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/04/2022] [Accepted: 01/13/2023] [Indexed: 06/18/2023]
Abstract
BACKGROUND Gut fungi are increasingly recognized as important contributors to host physiology, although most studies have focused on gut bacteria. Post-translational modifications (PTMs) of proteins play vital roles in cell metabolism. However, the contribution of gut fungi to host protein PTMs remains unclear. Mining gut fungi that mediate host protein PTMs and dissecting their mechanism are urgently needed. RESULTS We studied the gut fungal communities of 56 weaned piglets and 56 finishing pigs from seven pig breeds using internal transcribed spacer (ITS) gene amplicon sequencing and metagenomics. The results showed that Kazachstania slooffiae was the most abundant gut fungal species in the seven breeds of weaned piglets. K. slooffiae decreased intestinal epithelial lysine succinylation levels, and these proteins were especially enriched in the glycolysis pathway. We demonstrated that K. slooffiae promoted intestinal epithelial glycolysis by decreasing lysine succinylation by activating sirtuin 5 (SIRT5). Furthermore, K. slooffiae-derived 5'-methylthioadenosine metabolite promoted the SIRT5 activity. CONCLUSIONS These findings provide a landscape of gut fungal communities of pigs and suggest that K. slooffiae plays a crucial role in intestinal glycolysis metabolism through lysine desuccinylation. Our data also suggest a potential protective strategy for pigs with an insufficient intestinal energy supply. Video Abstract.
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Affiliation(s)
- Jun Hu
- State Key Laboratory of Agricultural Microbiology, Hubei Hongshan Laboratory, Frontiers Science Center for Animal Breeding and Sustainable Production, College of Animal Sciences and Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, China
- The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070, Hubei, China
- Hubei Provincial Engineering Laboratory for Pig Precision Feeding and Feed Safety Technology, Wuhan, 430070, Hubei, China
| | - Jianwei Chen
- BGI Research-Qingdao, BGI, Qingdao, 266555, China
| | - Qiliang Hou
- State Key Laboratory of Agricultural Microbiology, Hubei Hongshan Laboratory, Frontiers Science Center for Animal Breeding and Sustainable Production, College of Animal Sciences and Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, China
- The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070, Hubei, China
- Hubei Provincial Engineering Laboratory for Pig Precision Feeding and Feed Safety Technology, Wuhan, 430070, Hubei, China
| | - Xiaojian Xu
- State Key Laboratory of Agricultural Microbiology, Hubei Hongshan Laboratory, Frontiers Science Center for Animal Breeding and Sustainable Production, College of Animal Sciences and Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, China
- The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070, Hubei, China
- Hubei Provincial Engineering Laboratory for Pig Precision Feeding and Feed Safety Technology, Wuhan, 430070, Hubei, China
| | - Jing Ren
- State Key Laboratory of Agricultural Microbiology, Hubei Hongshan Laboratory, Frontiers Science Center for Animal Breeding and Sustainable Production, College of Animal Sciences and Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, China
- The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070, Hubei, China
- Hubei Provincial Engineering Laboratory for Pig Precision Feeding and Feed Safety Technology, Wuhan, 430070, Hubei, China
| | - Libao Ma
- State Key Laboratory of Agricultural Microbiology, Hubei Hongshan Laboratory, Frontiers Science Center for Animal Breeding and Sustainable Production, College of Animal Sciences and Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, China
- The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070, Hubei, China
- Hubei Provincial Engineering Laboratory for Pig Precision Feeding and Feed Safety Technology, Wuhan, 430070, Hubei, China
| | - Xianghua Yan
- State Key Laboratory of Agricultural Microbiology, Hubei Hongshan Laboratory, Frontiers Science Center for Animal Breeding and Sustainable Production, College of Animal Sciences and Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, China.
- The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070, Hubei, China.
- Hubei Provincial Engineering Laboratory for Pig Precision Feeding and Feed Safety Technology, Wuhan, 430070, Hubei, China.
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Zeng H, Zhong Z, Xu Z, Teng J, Wei C, Chen Z, Zhang W, Ding X, Li J, Zhang Z. Meta-analysis of genome-wide association studies uncovers shared candidate genes across breeds for pig fatness trait. BMC Genomics 2022; 23:786. [DOI: 10.1186/s12864-022-09036-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Accepted: 11/22/2022] [Indexed: 12/02/2022] Open
Abstract
Abstract
Background
Average backfat thickness (BFT) is a critical complex trait in pig and an important indicator for fat deposition and lean rate. Usually, genome-wide association study (GWAS) was used to discover quantitative trait loci (QTLs) of BFT in a single population. However, the power of GWAS is limited by sample size in a single population. Alternatively, meta-analysis of GWAS (metaGWAS) is an attractive method to increase the statistical power by integrating data from multiple breeds and populations. The aim of this study is to identify shared genetic characterization of BFT across breeds in pigs via metaGWAS.
Results
In this study, we performed metaGWAS on BFT using 15,353 pigs (5,143 Duroc, 7,275 Yorkshire, and 2,935 Landrace) from 19 populations. We detected 40 genome-wide significant SNPs (Bonferroni corrected P < 0.05) and defined five breed-shared QTLs in across-breed metaGWAS. Markers within the five QTL regions explained 7 ~ 9% additive genetic variance and showed strong heritability enrichment. Furthermore, by integrating information from multiple bioinformatics databases, we annotated 46 candidate genes located in the five QTLs. Among them, three important (MC4R, PPARD, and SLC27A1) and seven suggestive candidate genes (PHLPP1, NUDT3, ILRUN, RELCH, KCNQ5, ITPR3, and U3) were identified.
Conclusion
QTLs and candidate genes underlying BFT across breeds were identified via metaGWAS from multiple populations. Our findings contribute to the understanding of the genetic architecture of BFT and the regulating mechanism underlying fat deposition in pigs.
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Genome-Wide Association Study of Growth Traits in a Four-Way Crossbred Pig Population. Genes (Basel) 2022; 13:genes13111990. [DOI: 10.3390/genes13111990] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2022] [Revised: 10/28/2022] [Accepted: 10/28/2022] [Indexed: 11/04/2022] Open
Abstract
Growth traits are crucial economic traits in the commercial pig industry and have a substantial impact on pig production. However, the genetic mechanism of growth traits is not very clear. In this study, we performed a genome-wide association study (GWAS) based on the specific-locus amplified fragment sequencing (SLAF-seq) to analyze ten growth traits on 223 four-way intercross pigs. A total of 227,921 highly consistent single nucleotide polymorphisms (SNPs) uniformly dispersed throughout the entire genome were used to conduct GWAS. A total of 53 SNPs were identified for ten growth traits using the mixed linear model (MLM), of which 18 SNPs were located in previously reported quantitative trait loci (QTL) regions. Two novel QTLs on SSC4 and SSC7 were related to average daily gain from 30 to 60 kg (ADG30–60) and body length (BL), respectively. Furthermore, 13 candidate genes (ATP5O, GHRHR, TRIM55, EIF2AK1, PLEKHA1, BRAP, COL11A2, HMGA1, NHLRC1, SGSM1, NFATC2, MAML1, and PSD3) were found to be associated with growth traits in pigs. The GWAS findings will enhance our comprehension of the genetic architecture of growth traits. We suggested that these detected SNPs and corresponding candidate genes might provide a biological foundation for improving the growth and production performance of pigs in swine breeding.
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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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Ruan D, Yang J, Zhuang Z, Ding R, Huang J, Quan J, Gu T, Hong L, Zheng E, Li Z, Cai G, Wang X, Wu Z. Assessment of Heterozygosity and Genome-Wide Analysis of Heterozygosity Regions in Two Duroc Pig Populations. Front Genet 2022; 12:812456. [PMID: 35154256 PMCID: PMC8830653 DOI: 10.3389/fgene.2021.812456] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Accepted: 12/15/2021] [Indexed: 01/02/2023] Open
Abstract
Heterozygosity can effectively reflect the diverse models of population structure and demographic history. However, the genomic distribution of heterozygotes and the correlation between regions of heterozygosity (runs of heterozygosity, ROHet) and phenotypes are largely understudied in livestock. The objective of this study was to identify ROHet in the Duroc pig genome, and investigate the relationships between ROHet and eight important economic traits. Here, we genotyped 3,770 American Duroc (S21) and 2,096 Canadian Duroc (S22) pigs using 50 K single nucleotide polymorphism array to analyze heterozygosity. A total of 145,010 and 84,396 ROHets were characterized for S21 and S22 populations, respectively. ROHet segments were mostly enriched in 1–2 Mb length classification (75.48% in S21 and 72.25% in S22). The average genome length covered by ROHet was 66.53 ± 12.20 Mb in S21 and 73.32 ± 13.77 Mb in S22 pigs. Additionally, we detected 20 and 13 ROHet islands in S21 and S22 pigs. Genes in these genomic regions were mainly involved in the biological processes of immunity and reproduction. Finally, the genome-wide ROHet-phenotypes association analysis revealed that 130 ROHets of S21 and 84 ROHets of S22 were significantly associated with eight economic traits. Among the candidate genes in the significant ROHet regions, 16 genes related to growth, metabolism, and meat quality were considered as candidate genes for important economic traits of pigs. This work preliminarily explores the effect of heterozygosity-rich regions in the pig genome on production performance and provides new insights for subsequent research on pig genetic improvement.
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Affiliation(s)
- Donglin Ruan
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
| | - Jie Yang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
- Guangdong Provincial Laboratory of Lingnan Modern Agricultural Science and Technology, Guangzhou, China
| | - Zhanwei Zhuang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
| | - Rongrong Ding
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
- Guangdong Wens Breeding Swine Technology Co., Ltd., Yunfu, China
| | - Jinyan Huang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
| | - Jianping Quan
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
| | - Ting Gu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
| | - Linjun Hong
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
| | - Enqin Zheng
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
| | - Zicong Li
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
| | - Gengyuan Cai
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
- Guangdong Wens Breeding Swine Technology Co., Ltd., Yunfu, China
| | - Xiaopeng Wang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
- *Correspondence: Xiaopeng Wang, ; Zhenfang Wu,
| | - Zhenfang Wu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
- Guangdong Provincial Laboratory of Lingnan Modern Agricultural Science and Technology, Guangzhou, China
- Guangdong Wens Breeding Swine Technology Co., Ltd., Yunfu, China
- *Correspondence: Xiaopeng Wang, ; Zhenfang Wu,
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