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Hu J, Gui L, Wu Z, Huang L. Construction of the porcine genome mobile element variations and investigation of its role in population diversity and gene expression. J Anim Sci Biotechnol 2024; 15:162. [PMID: 39627810 PMCID: PMC11616153 DOI: 10.1186/s40104-024-01121-5] [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: 07/17/2024] [Accepted: 10/29/2024] [Indexed: 12/06/2024] Open
Abstract
BACKGROUND Mobile element variants (MEVs) have a significant and complex impact on genomic diversity and phenotypic traits. However, the quantity, distribution, and relationship with gene expression and complex traits of MEVs in the pig genome remain poorly understood. RESULTS We constructed the most comprehensive porcine MEV library based on high-depth whole genome sequencing (WGS) data from 747 pigs across 59 breeds worldwide. This database identified a total of 147,993 polymorphic MEVs, including 121,099 short interspersed nuclear elements (SINEs), 26,053 long interspersed nuclear elements (LINEs), 802 long terminal repeats (LTRs), and 39 other transposons, among which 54% are newly discovered. We found that MEVs are unevenly distributed across the genome and are strongly influenced by negative selection effects. Importantly, we identified 514, 530, and 584 candidate MEVs associated with population differentiation, domestication, and breed formation, respectively. For example, a significantly differentiated MEV is located in the ATRX intron between Asian and European pigs, whereas ATRX is also differentially expressed between Asian and European pigs in muscle tissue. In addition, we identified 4,169 expressed MEVs (eMEVs) significantly associated with gene expression and 6,914 splicing MEVs (sMEVs) associated with gene splicing based on RNA-seq data from 266 porcine liver tissues. These eMEVs and sMEVs explain 6.24% and 9.47%, respectively, of the observed cis-heritability and highlight the important role of MEVs in the regulation of gene expression. Finally, we provide a high-quality SNP-MEV reference haplotype panel to impute MEV genotypes from genome-wide SNPs. Notably, we identified a candidate MEV significantly associated with total teat number, demonstrating the functionality of this reference panel. CONCLUSIONS The present investigation demonstrated the importance of MEVs in pigs in terms of population diversity, gene expression and phenotypic traits, which may provide useful resources and theoretical support for pig genetics and breeding.
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Affiliation(s)
- Jianchao Hu
- National Key Laboratory for Swine Genetic Improvement and Germplasm Innovation, Ministry of Science and Technology of China, Jiangxi Agricultural University, Nanchang, People's Republic of China
| | - Lu Gui
- National Key Laboratory for Swine Genetic Improvement and Germplasm Innovation, Ministry of Science and Technology of China, Jiangxi Agricultural University, Nanchang, People's Republic of China
| | - Zhongzi Wu
- National Key Laboratory for Swine Genetic Improvement and Germplasm Innovation, Ministry of Science and Technology of China, Jiangxi Agricultural University, Nanchang, People's Republic of China.
| | - Lusheng Huang
- National Key Laboratory for Swine Genetic Improvement and Germplasm Innovation, Ministry of Science and Technology of China, Jiangxi Agricultural University, Nanchang, People's Republic of China.
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2
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Sun J, Yang X, Zhao G, He Z, Xing W, Chen Y, Tan X, Wang M, Li W, An B, Pan Z, Zhou Z, Wen J, Liu R. Protein phosphatase 1 catalytic subunit gamma is a causative gene for meat lightness and redness. PLoS Genet 2024; 20:e1011467. [PMID: 39565795 PMCID: PMC11616877 DOI: 10.1371/journal.pgen.1011467] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Revised: 12/04/2024] [Accepted: 10/23/2024] [Indexed: 11/22/2024] Open
Abstract
The quality of meat is important to the consumer. Color is a primary indicator of meat quality and is characterized mainly into lightness, redness, and yellowness. Here, we used the genome-wide association study (GWAS) and gene-based association analysis with whole-genome resequencing of 230 fast-growing white-feathered chickens to map genes related to meat lightness and redness to a 6.24 kb QTL region (GGA15: 6298.34-6304.58 kb). This analysis revealed that only the protein phosphatase 1 catalytic subunit gamma (PPP1CC) was associated with meat color (P = 8.65E-08). The causal relationships between PPP1CC expression and meat lightness/redness were further validated through Mendelian randomization analyses (P < 2.9E-12). Inducible skeletal muscle-specific PPP1CC knockout (PPP1CC-SSKO) mice were generated and these mice showed increased lightness and decreased myoglobin content in the limb muscles. In addition, the predominant myofiber shifted from slow-twitch to fast-twitch myofibers. Through transcriptome and targeted metabolome evidence, we found that inhibition of PPP1CC decreased the expression of typical slow-twitch myofiber and myofiber-type specification genes and enhanced the glycolysis pathway. Functional validation through a plasmid reporter assay revealed that a SNP (rs315520807, C > T) located in the intron of PPP1CC could regulate the gene transcription activity. The differences in meat color phenotypes, myoglobin content, frequency of rs315520807 variant, expression of PPP1CC and fast-twitch fiber marker genes were detected between fast-growing white-feathered chickens and local chickens. In this study, PPP1CC was identified as the causative gene for meat color, and the novel target gene and variant that can aid in the innovation of meat improvement technology were detected.
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Affiliation(s)
- Jiahong Sun
- State Key Laboratory of Animal Biotech Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Beijing, China
| | - Xinting Yang
- State Key Laboratory of Animal Biotech Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Beijing, China
| | - Guiping Zhao
- State Key Laboratory of Animal Biotech Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Beijing, China
| | - Zhengxiao He
- State Key Laboratory of Animal Biotech Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Beijing, China
| | - Wenhao Xing
- State Key Laboratory of Animal Biotech Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Beijing, China
| | - Yanru Chen
- State Key Laboratory of Animal Biotech Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Beijing, China
| | - Xiaodong Tan
- State Key Laboratory of Animal Biotech Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Beijing, China
| | - Mengjie Wang
- State Key Laboratory of Animal Biotech Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Beijing, China
| | - Wei Li
- State Key Laboratory of Animal Biotech Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Beijing, China
| | - Bingxing An
- State Key Laboratory of Animal Biotech Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Beijing, China
| | - Zhangyuan Pan
- State Key Laboratory of Animal Biotech Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Beijing, China
| | - Zhengkui Zhou
- State Key Laboratory of Animal Biotech Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Beijing, China
| | - Jie Wen
- State Key Laboratory of Animal Biotech Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Beijing, China
| | - Ranran Liu
- State Key Laboratory of Animal Biotech Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Beijing, China
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3
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Wang H, Chen Z, Ma L, Wu Y, Zhao X, Zhang K, Xue J, Luo Y, Wang C, Liu Z, Xie Y, Chen Y, Gao G, Wang Q. Identification of Single Nucleotide Polymorphisms Through Genome-Wide Association Studies of pH Traits in Goose Meat. BIOLOGY 2024; 13:865. [PMID: 39596820 PMCID: PMC11592244 DOI: 10.3390/biology13110865] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/21/2024] [Revised: 10/18/2024] [Accepted: 10/21/2024] [Indexed: 11/29/2024]
Abstract
The genetic regulation of goose meat quality traits remains relatively unexplored, and the underlying mechanisms are yet to be elucidated. This study aims to employ single nucleotide polymorphism (SNP) genotyping in conjunction with genome-wide association studies (GWAS) to investigate critical candidate regions and genes associated with the pH trait of meat in Sichuan white geese. A cohort of 203 healthy male Sichuan white geese was randomly selected and slaughtered at 70 days of age. Measurements were taken of meat pH, growth parameters, body dimensions, and post-slaughter traits. High-throughput sequencing on the Illumina HiSeq X Ten platform facilitated gene resequencing and SNP evaluation, and GWAS was employed to detect key genes within quantitative trait loci (QTL) intervals. The sequencing of 203 individuals yielded a total of 2601.19 Gb of genomic data, with an average sequencing depth of 10.89×. Through GWAS analysis, a total of 30 SNPs associated with pH were identified. These SNPs were identified on multiple chromosomes, including on chromosome 17 (chr: 23.57-23.68 Mb) and chromosome 13 (chr13: 31.52-31.61 Mb). By annotating these associated SNPs, nine candidate genes (including C19L2, AMFR, POL, RERGL, ZN484, GMDS, WAC) associated with the pH of goose meat were identified. The matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF) genotyping of 10 SNPs centered on these nine candidate genes was confirmed. GO enrichment analysis revealed that genes within 1 Mb of the associated SNPs are significantly enriched in pathways involved in lymphocyte activation, in response to hydrogen peroxide, Salmonella infection, and other metabolic processes. This study explores the gene regulatory pathways influencing pH traits in goose meat and provides molecular markers for enhancing meat quality. These findings are expected to facilitate the advancement of molecular breeding programs in geese.
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Affiliation(s)
- Haiwei Wang
- Chongqing Engineering Research Center of Goose Genetic Improvement, Institute of Poultry Science, Chongqing Academy of Animal Science, Chongqing 402460, China; (H.W.); (Z.C.); (L.M.); (X.Z.); (K.Z.); (J.X.); (Y.L.); (C.W.); (Z.L.); (Y.X.); (Y.C.)
| | - Zhuping Chen
- Chongqing Engineering Research Center of Goose Genetic Improvement, Institute of Poultry Science, Chongqing Academy of Animal Science, Chongqing 402460, China; (H.W.); (Z.C.); (L.M.); (X.Z.); (K.Z.); (J.X.); (Y.L.); (C.W.); (Z.L.); (Y.X.); (Y.C.)
| | - Lin Ma
- Chongqing Engineering Research Center of Goose Genetic Improvement, Institute of Poultry Science, Chongqing Academy of Animal Science, Chongqing 402460, China; (H.W.); (Z.C.); (L.M.); (X.Z.); (K.Z.); (J.X.); (Y.L.); (C.W.); (Z.L.); (Y.X.); (Y.C.)
| | - Yifan Wu
- College of Animal Science and Technology, Southwest University, Chongqing 402460, China;
| | - Xianzhi Zhao
- Chongqing Engineering Research Center of Goose Genetic Improvement, Institute of Poultry Science, Chongqing Academy of Animal Science, Chongqing 402460, China; (H.W.); (Z.C.); (L.M.); (X.Z.); (K.Z.); (J.X.); (Y.L.); (C.W.); (Z.L.); (Y.X.); (Y.C.)
| | - Keshan Zhang
- Chongqing Engineering Research Center of Goose Genetic Improvement, Institute of Poultry Science, Chongqing Academy of Animal Science, Chongqing 402460, China; (H.W.); (Z.C.); (L.M.); (X.Z.); (K.Z.); (J.X.); (Y.L.); (C.W.); (Z.L.); (Y.X.); (Y.C.)
| | - Jiajia Xue
- Chongqing Engineering Research Center of Goose Genetic Improvement, Institute of Poultry Science, Chongqing Academy of Animal Science, Chongqing 402460, China; (H.W.); (Z.C.); (L.M.); (X.Z.); (K.Z.); (J.X.); (Y.L.); (C.W.); (Z.L.); (Y.X.); (Y.C.)
| | - Yi Luo
- Chongqing Engineering Research Center of Goose Genetic Improvement, Institute of Poultry Science, Chongqing Academy of Animal Science, Chongqing 402460, China; (H.W.); (Z.C.); (L.M.); (X.Z.); (K.Z.); (J.X.); (Y.L.); (C.W.); (Z.L.); (Y.X.); (Y.C.)
| | - Chao Wang
- Chongqing Engineering Research Center of Goose Genetic Improvement, Institute of Poultry Science, Chongqing Academy of Animal Science, Chongqing 402460, China; (H.W.); (Z.C.); (L.M.); (X.Z.); (K.Z.); (J.X.); (Y.L.); (C.W.); (Z.L.); (Y.X.); (Y.C.)
| | - Zuohua Liu
- Chongqing Engineering Research Center of Goose Genetic Improvement, Institute of Poultry Science, Chongqing Academy of Animal Science, Chongqing 402460, China; (H.W.); (Z.C.); (L.M.); (X.Z.); (K.Z.); (J.X.); (Y.L.); (C.W.); (Z.L.); (Y.X.); (Y.C.)
| | - Youhui Xie
- Chongqing Engineering Research Center of Goose Genetic Improvement, Institute of Poultry Science, Chongqing Academy of Animal Science, Chongqing 402460, China; (H.W.); (Z.C.); (L.M.); (X.Z.); (K.Z.); (J.X.); (Y.L.); (C.W.); (Z.L.); (Y.X.); (Y.C.)
| | - Ying Chen
- Chongqing Engineering Research Center of Goose Genetic Improvement, Institute of Poultry Science, Chongqing Academy of Animal Science, Chongqing 402460, China; (H.W.); (Z.C.); (L.M.); (X.Z.); (K.Z.); (J.X.); (Y.L.); (C.W.); (Z.L.); (Y.X.); (Y.C.)
| | - Guangliang Gao
- Chongqing Engineering Research Center of Goose Genetic Improvement, Institute of Poultry Science, Chongqing Academy of Animal Science, Chongqing 402460, China; (H.W.); (Z.C.); (L.M.); (X.Z.); (K.Z.); (J.X.); (Y.L.); (C.W.); (Z.L.); (Y.X.); (Y.C.)
| | - Qigui Wang
- Chongqing Engineering Research Center of Goose Genetic Improvement, Institute of Poultry Science, Chongqing Academy of Animal Science, Chongqing 402460, China; (H.W.); (Z.C.); (L.M.); (X.Z.); (K.Z.); (J.X.); (Y.L.); (C.W.); (Z.L.); (Y.X.); (Y.C.)
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4
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Lim WL, Gaunt JR, Tan JM, Zainolabidin N, Bansal VA, Lye YM, Ch'ng TH. CREB-regulated transcription during glycogen synthesis in astrocytes. Sci Rep 2024; 14:17942. [PMID: 39095513 PMCID: PMC11297295 DOI: 10.1038/s41598-024-67976-w] [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: 01/26/2024] [Accepted: 07/18/2024] [Indexed: 08/04/2024] Open
Abstract
Glycogen storage, conversion and utilization in astrocytes play an important role in brain energy metabolism. The conversion of glycogen to lactate through glycolysis occurs through the coordinated activities of various enzymes and inhibition of this process can impair different brain processes including formation of long-lasting memories. To replenish depleted glycogen stores, astrocytes undergo glycogen synthesis, a cellular process that has been shown to require transcription and translation during specific stimulation paradigms. However, the detail nuclear signaling mechanisms and transcriptional regulation during glycogen synthesis in astrocytes remains to be explored. In this report, we study the molecular mechanisms of vasoactive intestinal peptide (VIP)-induced glycogen synthesis in astrocytes. VIP is a potent neuropeptide that triggers glycogenolysis followed by glycogen synthesis in astrocytes. We show evidence that VIP-induced glycogen synthesis requires CREB-mediated transcription that is calcium dependent and requires conventional Protein Kinase C but not Protein Kinase A. In parallel to CREB activation, we demonstrate that VIP also triggers nuclear accumulation of the CREB coactivator CRTC2 in astrocytic nuclei. Transcriptome profiles of VIP-induced astrocytes identified robust CREB transcription, including a subset of genes linked to glucose and glycogen metabolism. Finally, we demonstrate that VIP-induced glycogen synthesis shares similar as well as distinct molecular signatures with glucose-induced glycogen synthesis, including the requirement of CREB-mediated transcription. Overall, our data demonstrates the importance of CREB-mediated transcription in astrocytes during stimulus-driven glycogenesis.
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Affiliation(s)
- Wei Lee Lim
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Clinical Science Building, 11 Mandalay Road, 10-01-01M, Singapore, 308232, Singapore
| | - Jessica Ruth Gaunt
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Clinical Science Building, 11 Mandalay Road, 10-01-01M, Singapore, 308232, Singapore
| | - Jia Min Tan
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Clinical Science Building, 11 Mandalay Road, 10-01-01M, Singapore, 308232, Singapore
| | - Norliyana Zainolabidin
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Clinical Science Building, 11 Mandalay Road, 10-01-01M, Singapore, 308232, Singapore
| | - Vibhavari Aysha Bansal
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Clinical Science Building, 11 Mandalay Road, 10-01-01M, Singapore, 308232, Singapore
| | - Yi Ming Lye
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Clinical Science Building, 11 Mandalay Road, 10-01-01M, Singapore, 308232, Singapore
| | - Toh Hean Ch'ng
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Clinical Science Building, 11 Mandalay Road, 10-01-01M, Singapore, 308232, Singapore.
- School of Biological Science, Nanyang Technological University, Singapore, 636551, Singapore.
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Farhangi S, Gòdia M, Derks MFL, Harlizius B, Dibbits B, González-Prendes R, Crooijmans RPMA, Madsen O, Groenen MAM. Expression genome-wide association study identifies key regulatory variants enriched with metabolic and immune functions in four porcine tissues. BMC Genomics 2024; 25:684. [PMID: 38992576 PMCID: PMC11238464 DOI: 10.1186/s12864-024-10583-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Accepted: 07/01/2024] [Indexed: 07/13/2024] Open
Abstract
BACKGROUND Integration of high throughput DNA genotyping and RNA-sequencing data enables the discovery of genomic regions that regulate gene expression, known as expression quantitative trait loci (eQTL). In pigs, efforts to date have been mainly focused on purebred lines for traits with commercial relevance as such growth and meat quality. However, little is known on genetic variants and mechanisms associated with the robustness of an animal, thus its overall health status. Here, the liver, lung, spleen, and muscle transcriptomes of 100 three-way crossbred female finishers were studied, with the aim of identifying novel eQTL regulatory regions and transcription factors (TFs) associated with regulation of porcine metabolism and health-related traits. RESULTS An expression genome-wide association study with 535,896 genotypes and the expression of 12,680 genes in liver, 13,310 genes in lung, 12,650 genes in spleen, and 12,595 genes in muscle resulted in 4,293, 10,630, 4,533, and 6,871 eQTL regions for each of these tissues, respectively. Although only a small fraction of the eQTLs were annotated as cis-eQTLs, these presented a higher number of polymorphisms per region and significantly stronger associations with their target gene compared to trans-eQTLs. Between 20 and 115 eQTL hotspots were identified across the four tissues. Interestingly, these were all enriched for immune-related biological processes. In spleen, two TFs were identified: ERF and ZNF45, with key roles in regulation of gene expression. CONCLUSIONS This study provides a comprehensive analysis with more than 26,000 eQTL regions identified that are now publicly available. The genomic regions and their variants were mostly associated with tissue-specific regulatory roles. However, some shared regions provide new insights into the complex regulation of genes and their interactions that are involved with important traits related to metabolism and immunity.
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Affiliation(s)
- Samin Farhangi
- Animal Breeding and Genomics, Wageningen University and Research, Wageningen, The Netherlands
| | - Marta Gòdia
- Animal Breeding and Genomics, Wageningen University and Research, Wageningen, The Netherlands.
| | - Martijn F L Derks
- Animal Breeding and Genomics, Wageningen University and Research, Wageningen, The Netherlands
- Topigs Norsvin Research Center, 's-Hertogenbosch, The Netherlands
| | | | - Bert Dibbits
- Animal Breeding and Genomics, Wageningen University and Research, Wageningen, The Netherlands
| | - Rayner González-Prendes
- Animal Breeding and Genomics, Wageningen University and Research, Wageningen, The Netherlands
- Ausnutria BV, Zwolle, The Netherlands
| | | | - Ole Madsen
- Animal Breeding and Genomics, Wageningen University and Research, Wageningen, The Netherlands
| | - Martien A M Groenen
- Animal Breeding and Genomics, Wageningen University and Research, Wageningen, The Netherlands
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Molinero E, Pena RN, Estany J, Ros-Freixedes R. A novel QTL region for pH and meat color in Duroc pigs. Anim Genet 2024; 55:465-470. [PMID: 38584305 DOI: 10.1111/age.13426] [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: 03/21/2024] [Revised: 03/21/2024] [Accepted: 03/23/2024] [Indexed: 04/09/2024]
Abstract
One of the most important processes that occur during the transformation of muscle to meat is the pH decline as a consequence of the post-mortem metabolism of muscle tissue. Abnormal pH declines lead to pork defects such as pale, soft, and exudative meat. There is genetic variance for ultimate pH and the role of some genes on this phenotype is well established. After conducting a genome-wide association study on ultimate pH using 526 purebred Duroc pigs, we identified associated regions on Sus scrofa chromosomes (SSC) 3, 8, and 15. Functional candidate genes in these regions included PRKAG3 and PHKG1. The SSC8 region, at 71.6 Mb, was novel and, although no candidate causative gene could be identified, it may have regulatory effects. Subsequent analysis on 828 pigs from the same population confirmed the impact of the three associated regions on pH and meat color. We detected no interaction between the three regions. Further investigations are necessary to unravel the functional significance of the novel genomic region at SSC8. These variants could be used as markers in marker-assisted selection for improving meat quality.
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Affiliation(s)
- Eduard Molinero
- Departament de Ciència Animal, Universitat de Lleida, Lleida, Spain
- Agrotecnio-CERCA Center, Lleida, Spain
| | - Ramona N Pena
- Departament de Ciència Animal, Universitat de Lleida, Lleida, Spain
- Agrotecnio-CERCA Center, Lleida, Spain
| | - Joan Estany
- Departament de Ciència Animal, Universitat de Lleida, Lleida, Spain
- Agrotecnio-CERCA Center, Lleida, Spain
| | - Roger Ros-Freixedes
- Departament de Ciència Animal, Universitat de Lleida, Lleida, Spain
- Agrotecnio-CERCA Center, Lleida, Spain
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7
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Yang G, Dai R, Ma X, Huang C, Ma X, Li X, La Y, Dingkao R, Renqing J, Guo X, Zhaxi T, Liang C. Proteomic Analysis Reveals the Effects of Different Dietary Protein Levels on Growth and Development of Jersey-Yak. Animals (Basel) 2024; 14:406. [PMID: 38338049 PMCID: PMC10854544 DOI: 10.3390/ani14030406] [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: 10/27/2023] [Revised: 01/09/2024] [Accepted: 01/23/2024] [Indexed: 02/12/2024] Open
Abstract
Jersey-yak is a hybrid offspring of Jersey cattle and yak (Bos grunniens). Changing the feeding system of Jersey-yak can significantly improve its growth performance. In this study, tandem mass tag (TMT) proteomics technology was used to determine the differentially expressed proteins (DEPs) of the longissimus lumborum (LL) muscle of Jersey-yak fed different protein levels of diet. The results showed that compared with the traditional grazing feeding, the growth performance of Jersey-yaks was significantly improved by crude protein supplementation after grazing. A total of 3368 proteins were detected in these muscle samples, of which 3365 were quantified. A total of 434 DEPs were identified. Through analyses, it was found that some pathways related to muscle growth and development were significantly enriched, such as Rap1 signaling pathway, mTOR signaling pathway, and TGF-beta signaling pathway. A number of DEPs enriched in these pathways are related to muscle cell development, differentiation, and muscle development, including integrin subunit alpha 7 (ITGA7), myosin heavy chain 8 (MYH8), and collagen type XII alpha 1 chain (COL12A1). In conclusion, the results of this study provide insights into the proteomics of different feeding patterns of Jersey-yak, providing a stronger basis for further understanding the biological mechanism of hybrid varieties.
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Affiliation(s)
- Guowu Yang
- Key Laboratory of Animal Genetics and Breeding on Tibetan Plateau, Ministry of Agriculture and Rural Affairs, Key Laboratory of Yak Breeding Engineering of Gansu Province, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China; (G.Y.); (R.D.); (X.M.); (C.H.); (X.M.); (X.L.); (Y.L.); (X.G.)
- College of Life Sciences and Engineering, Northwest Minzu University, Lanzhou 730106, China
| | - Rongfeng Dai
- Key Laboratory of Animal Genetics and Breeding on Tibetan Plateau, Ministry of Agriculture and Rural Affairs, Key Laboratory of Yak Breeding Engineering of Gansu Province, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China; (G.Y.); (R.D.); (X.M.); (C.H.); (X.M.); (X.L.); (Y.L.); (X.G.)
| | - Xiaoming Ma
- Key Laboratory of Animal Genetics and Breeding on Tibetan Plateau, Ministry of Agriculture and Rural Affairs, Key Laboratory of Yak Breeding Engineering of Gansu Province, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China; (G.Y.); (R.D.); (X.M.); (C.H.); (X.M.); (X.L.); (Y.L.); (X.G.)
| | - Chun Huang
- Key Laboratory of Animal Genetics and Breeding on Tibetan Plateau, Ministry of Agriculture and Rural Affairs, Key Laboratory of Yak Breeding Engineering of Gansu Province, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China; (G.Y.); (R.D.); (X.M.); (C.H.); (X.M.); (X.L.); (Y.L.); (X.G.)
| | - Xiaoyong Ma
- Key Laboratory of Animal Genetics and Breeding on Tibetan Plateau, Ministry of Agriculture and Rural Affairs, Key Laboratory of Yak Breeding Engineering of Gansu Province, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China; (G.Y.); (R.D.); (X.M.); (C.H.); (X.M.); (X.L.); (Y.L.); (X.G.)
| | - Xinyi Li
- Key Laboratory of Animal Genetics and Breeding on Tibetan Plateau, Ministry of Agriculture and Rural Affairs, Key Laboratory of Yak Breeding Engineering of Gansu Province, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China; (G.Y.); (R.D.); (X.M.); (C.H.); (X.M.); (X.L.); (Y.L.); (X.G.)
- College of Life Sciences and Engineering, Northwest Minzu University, Lanzhou 730106, China
| | - Yongfu La
- Key Laboratory of Animal Genetics and Breeding on Tibetan Plateau, Ministry of Agriculture and Rural Affairs, Key Laboratory of Yak Breeding Engineering of Gansu Province, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China; (G.Y.); (R.D.); (X.M.); (C.H.); (X.M.); (X.L.); (Y.L.); (X.G.)
| | - Renqing Dingkao
- Animal Husbandry Station, Gannan Tibetan Autonomous Prefecture, Hezuo 747099, China;
| | - Ji Renqing
- Zogemanma Town Animal Husbandry and Veterinary Station, Hezuo 747003, China;
| | - Xian Guo
- Key Laboratory of Animal Genetics and Breeding on Tibetan Plateau, Ministry of Agriculture and Rural Affairs, Key Laboratory of Yak Breeding Engineering of Gansu Province, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China; (G.Y.); (R.D.); (X.M.); (C.H.); (X.M.); (X.L.); (Y.L.); (X.G.)
| | - Ta Zhaxi
- Qilian County Animal Husbandry Veterinary Workstation, Haibei Prefecture, Qilian 810400, China
| | - Chunnian Liang
- Key Laboratory of Animal Genetics and Breeding on Tibetan Plateau, Ministry of Agriculture and Rural Affairs, Key Laboratory of Yak Breeding Engineering of Gansu Province, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China; (G.Y.); (R.D.); (X.M.); (C.H.); (X.M.); (X.L.); (Y.L.); (X.G.)
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8
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Yang W, Hou L, Wang B, Wu J, Zha C, Wu W. Integration of transcriptome and machine learning to identify the potential key genes and regulatory networks affecting drip loss in pork. J Anim Sci 2024; 102:skae164. [PMID: 38865489 PMCID: PMC11214104 DOI: 10.1093/jas/skae164] [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] [Received: 03/18/2024] [Accepted: 06/10/2024] [Indexed: 06/14/2024] Open
Abstract
Low level of drip loss (DL) is an important quality characteristic of meat with high economic value. However, the key genes and regulatory networks contributing to DL in pork remain largely unknown. To accurately identify the key genes affecting DL in muscles postmortem, 12 Duroc × (Landrace × Yorkshire) pigs with extremely high (n = 6, H group) and low (n = 6, L group) DL at both 24 and 48 h postmortem were selected for transcriptome sequencing. The analysis of differentially expressed genes and weighted gene co-expression network analysis (WGCNA) were performed to find the overlapping genes using the transcriptome data, and functional enrichment and protein-protein interaction (PPI) network analysis were conducted using the overlapping genes. Moreover, we used machine learning to identify the key genes and regulatory networks related to DL based on the interactive genes of the PPI network. Finally, nine potential key genes (IRS1, ESR1, HSPA6, INSR, SPOP, MSTN, LGALS4, MYLK2, and FRMD4B) mainly associated with the MAPK signaling pathway, the insulin signaling pathway, and the calcium signaling pathway were identified, and a single-gene set enrichment analysis (GSEA) was performed to further annotate the functions of these potential key genes. The GSEA results showed that these genes are mainly related to ubiquitin-mediated proteolysis and oxidative reactions. Taken together, our results indicate that the potential key genes influencing DL are mainly related to insulin signaling mediated differences in glycolysis and ubiquitin-mediated changes in muscle structure and improve the understanding of gene expression and regulation related to DL and contribute to future molecular breeding for improving pork quality.
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Affiliation(s)
- Wen Yang
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science and Technology, Nanjing Agricultural University, Nanjing, China
| | - Liming Hou
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science and Technology, Nanjing Agricultural University, Nanjing, China
| | - Binbin Wang
- Institute of Animal Husbandry and Veterinary, Zhejiang Academy of Agricultural Sciences, Hangzhou 310021, China
| | - Jian Wu
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science and Technology, Nanjing Agricultural University, Nanjing, China
| | - Chengwan Zha
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science and Technology, Nanjing Agricultural University, Nanjing, China
| | - Wangjun Wu
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science and Technology, Nanjing Agricultural University, Nanjing, China
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9
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Yan M, Li L, Huang Y, Tang X, Shu Y, Cui D, Yu C, Hu Y, Ma J, Xiao S, Guo Y. Investigation on muscle fiber types and meat quality and estimation of their heritability and correlation coefficients with each other in four pig populations. Anim Sci J 2024; 95:e13915. [PMID: 38303133 DOI: 10.1111/asj.13915] [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: 06/28/2023] [Revised: 12/12/2023] [Accepted: 12/19/2023] [Indexed: 02/03/2024]
Abstract
The aim of this study was to investigate the muscle fiber types and meat quality in four populations and estimate the heritability and correlation coefficients of those traits in Shanxia long black pig (SX). In this study, a total of 318 pigs were recorded for 16 traits of the muscle fiber types and meat quality in four populations, including 256 individuals from the new breed SX. The population had a significant effect on all recorded traits, and the meat quality of the Lulai black pig was better than the remaining populations. The heritability (h2 ) of meat quality traits was from 0.06 (pH at 24 h) to 0.47 (shearing force), and the muscle fiber types belonged to the traits with low to medium heritability. The density of total fiber had the highest h2 (0.40), while the percentage of type IIA had the lowest h2 (0.04). Most traits are phenotypically correlated with each other, but only a small proportion of traits are genetically correlated with each other. None fiber type genetically correlated with meat quality significantly, because the genetic correlation coefficients had large standard errors. These results provided some insights into genetic improvements for the meat quality in pig breeds and also indicated that the parameters of muscle fiber characteristics can explain parts of the variation in meat quality.
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Affiliation(s)
- Min Yan
- National Key Laboratory for Pig Genetic Improvement and Germplasm Innovation, Ministry of Science and Technology of China, Jiangxi Agricultural University, Nanchang, Jiangxi Province, China
| | - Longyun Li
- National Key Laboratory for Pig Genetic Improvement and Germplasm Innovation, Ministry of Science and Technology of China, Jiangxi Agricultural University, Nanchang, Jiangxi Province, China
| | - Yizhong Huang
- National Key Laboratory for Pig Genetic Improvement and Germplasm Innovation, Ministry of Science and Technology of China, Jiangxi Agricultural University, Nanchang, Jiangxi Province, China
| | - Xi Tang
- National Key Laboratory for Pig Genetic Improvement and Germplasm Innovation, Ministry of Science and Technology of China, Jiangxi Agricultural University, Nanchang, Jiangxi Province, China
| | - Yujie Shu
- National Key Laboratory for Pig Genetic Improvement and Germplasm Innovation, Ministry of Science and Technology of China, Jiangxi Agricultural University, Nanchang, Jiangxi Province, China
| | - Dengshuai Cui
- National Key Laboratory for Pig Genetic Improvement and Germplasm Innovation, Ministry of Science and Technology of China, Jiangxi Agricultural University, Nanchang, Jiangxi Province, China
| | - Chuangang Yu
- National Key Laboratory for Pig Genetic Improvement and Germplasm Innovation, Ministry of Science and Technology of China, Jiangxi Agricultural University, Nanchang, Jiangxi Province, China
| | - Yongqiang Hu
- National Key Laboratory for Pig Genetic Improvement and Germplasm Innovation, Ministry of Science and Technology of China, Jiangxi Agricultural University, Nanchang, Jiangxi Province, China
| | - Junwu Ma
- National Key Laboratory for Pig Genetic Improvement and Germplasm Innovation, Ministry of Science and Technology of China, Jiangxi Agricultural University, Nanchang, Jiangxi Province, China
| | - Shijun Xiao
- National Key Laboratory for Pig Genetic Improvement and Germplasm Innovation, Ministry of Science and Technology of China, Jiangxi Agricultural University, Nanchang, Jiangxi Province, China
| | - Yuanmei Guo
- National Key Laboratory for Pig Genetic Improvement and Germplasm Innovation, Ministry of Science and Technology of China, Jiangxi Agricultural University, Nanchang, Jiangxi Province, China
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10
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Chung Y, Jang SS, Kang DH, Kim YK, Kim HJ, Chung KY, Choi I, Lee SH. Identification of potential biomarkers associated with meat tenderness in Hanwoo (Korean cattle): An expression quantitative trait loci analysis. Anim Genet 2023; 54:786-791. [PMID: 37828654 DOI: 10.1111/age.13360] [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: 08/29/2023] [Revised: 08/29/2023] [Accepted: 09/21/2023] [Indexed: 10/14/2023]
Abstract
Meat tenderness is considered the most important trait contributing to beef quality, level of consumer satisfaction, willingness to pay premium prices and industry profit. Genomic selection method would be helpful for genetic improvement of traits with low heritability and that are difficult to measure. The identification of core genes can aid genomic selection for complex traits with low heritability that are difficult to measure. We performed statistical analysis of associations between longissimus dorsi muscle tenderness and gene expression in 20 Hanwoo cattle, using Warner-Bratzler shear force and RNAseq data, respectively. We found a total of 166 core genes, from which six (ASAP1, CAPN5, ELN, SUMF2, TTC8 and MGAT4A) were regulated by 16 cis-expression quantitative trait loci (eQTL) SNPs. Notably, we found that a cis-eQTL SNP of the ELN gene contained an MFZ-1 binding site in its putative promoter region. These findings provide useful information for genomic prediction of beef tenderness in Hanwoo cattle.
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Affiliation(s)
- Yoonji Chung
- Division of Animal and Dairy Science, Chungnam National University, Daejeon, South Korea
| | - Sun Sik Jang
- Hanwoo Research Institute, National Institute of Animal Science, Pyeongchang, South Korea
| | - Dong Hun Kang
- Department of Beef Science, Korea National University of Agriculture and Fisheries, Wanju, South Korea
| | - Yeong Kuk Kim
- Quantomic Research and Solution, Daejeon, South Korea
| | - Hyun Joo Kim
- Hanwoo Research Institute, National Institute of Animal Science, Pyeongchang, South Korea
- School of Environmental and Rural Science, University of New England, Armidale, New South Wales, Australia
| | - Ki Yong Chung
- Department of Beef Science, Korea National University of Agriculture and Fisheries, Wanju, South Korea
| | - Inchul Choi
- Division of Animal and Dairy Science, Chungnam National University, Daejeon, South Korea
| | - Seung Hwan Lee
- Division of Animal and Dairy Science, Chungnam National University, Daejeon, South Korea
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11
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Zhou F, Wang S, Qin H, Zeng H, Ye J, Yang J, Cai G, Wu Z, Zhang Z. Genome-wide association analysis unveils candidate genes and loci associated with aplasia cutis congenita in pigs. BMC Genomics 2023; 24:701. [PMID: 37990155 PMCID: PMC10664689 DOI: 10.1186/s12864-023-09803-6] [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] [Received: 08/06/2023] [Accepted: 11/11/2023] [Indexed: 11/23/2023] Open
Abstract
BACKGROUND Aplasia cutis congenita (ACC) is a rare genetic disorder characterized by the localized or widespread absence of skin in humans and animals. Individuals with ACC may experience developmental abnormalities in the skeletal and muscular systems, as well as potential complications. Localized and isolated cases of ACC can be treated through surgical and medical interventions, while extensive cases of ACC may result in neonatal mortality. The presence of ACC in pigs has implications for animal welfare. It contributes to an elevated mortality rate among piglets at birth, leading to substantial economic losses in the pig farming industry. In order to elucidate candidate genetic loci associated with ACC, we performed a Genome-Wide Association Study analysis on 216 Duroc pigs. The primary goal of this study was to identify candidate genes that associated with ACC. RESULTS This study identified nine significant SNPs associated with ACC. Further analysis revealed the presence of two quantitative trait loci, 483 kb (5:18,196,971-18,680,098) on SSC 5 and 159 kb (13:20,713,440-207294431 bp) on SSC13. By annotating candidate genes within a 1 Mb region surrounding the significant SNPs, a total of 11 candidate genes were identified on SSC5 and SSC13, including KRT71, KRT1, KRT4, ITGB7, CSAD, RARG, SP7, PFKL, TRPM2, SUMO3, and TSPEAR. CONCLUSIONS The results of this study further elucidate the potential mechanisms underlying and genetic architecture of ACC and identify reliable candidate genes. These results lay the foundation for treating and understanding ACC in humans.
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Affiliation(s)
- Fuchen Zhou
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, 510642, P.R. China
| | - Shenghui Wang
- Guangdong Wens Breeding Swine Technology Co., Ltd, Guangdong, 527400, P.R. China
| | - Haojun Qin
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, 510642, P.R. China
| | - Haiyu Zeng
- Guangdong Wens Breeding Swine Technology Co., Ltd, Guangdong, 527400, P.R. China
| | - Jian Ye
- Guangdong Wens Breeding Swine Technology Co., Ltd, Guangdong, 527400, P.R. China
| | - Jie Yang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, 510642, P.R. China
| | - Gengyuan Cai
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, 510642, P.R. China
- Guangdong Wens Breeding Swine Technology Co., Ltd, Guangdong, 527400, P.R. China
| | - Zhenfang Wu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, 510642, P.R. China.
- Guangdong Wens Breeding Swine Technology Co., Ltd, Guangdong, 527400, P.R. China.
| | - Zebin Zhang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, 510642, P.R. China.
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12
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Wang C, Lei B, Liu Y. An Analysis of a Transposable Element Expression Atlas during 27 Developmental Stages in Porcine Skeletal Muscle: Unveiling Molecular Insights into Pork Production Traits. Animals (Basel) 2023; 13:3581. [PMID: 38003198 PMCID: PMC10668843 DOI: 10.3390/ani13223581] [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: 09/30/2023] [Revised: 11/13/2023] [Accepted: 11/17/2023] [Indexed: 11/26/2023] Open
Abstract
The development and growth of porcine skeletal muscle determine pork quality and yield. While genetic regulation of porcine skeletal muscle development has been extensively studied using various omics data, the role of transposable elements (TEs) in this context has been less explored. To bridge this gap, we constructed a comprehensive atlas of TE expression throughout the developmental stages of porcine skeletal muscle. This was achieved by integrating porcine TE genomic coordinates with whole-transcriptome RNA-Seq data from 27 developmental stages. We discovered that in pig skeletal muscle, active Tes are closely associated with active epigenomic marks, including low levels of DNA methylation, high levels of chromatin accessibility, and active histone modifications. Moreover, these TEs include 6074 self-expressed TEs that are significantly enriched in terms of muscle cell development and myofibril assembly. Using the TE expression data, we conducted a weighted gene co-expression network analysis (WGCNA) and identified a module that is significantly associated with muscle tissue development as well as genome-wide association studies (GWAS) of the signals of pig meat and carcass traits. Within this module, we constructed a TE-mediated gene regulatory network by adopting a unique multi-omics integration approach. This network highlighted several established candidate genes associated with muscle-relevant traits, including HES6, CHRNG, ACTC1, CHRND, MAMSTR, and PER2, as well as novel genes like ENSSSCG00000005518, ENSSSCG00000033601, and PIEZO2. These novel genes hold promise for regulating muscle-related traits in pigs. In summary, our research not only enhances the TE-centered dissection of the genetic basis underlying pork production traits, but also offers a general approach for constructing TE-mediated regulatory networks to study complex traits or diseases.
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Affiliation(s)
- Chao Wang
- Key Lab of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education and Key Laboratory of Swine Genetics and Breeding of Ministry of Agriculture, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan 430070, China; (C.W.); (B.L.)
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China
- Innovation Group of Pig Genome Design and Breeding, Research Centre for Animal Genome, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China
| | - Bowen Lei
- Key Lab of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education and Key Laboratory of Swine Genetics and Breeding of Ministry of Agriculture, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan 430070, China; (C.W.); (B.L.)
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China
- Innovation Group of Pig Genome Design and Breeding, Research Centre for Animal Genome, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China
| | - Yuwen Liu
- Key Lab of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education and Key Laboratory of Swine Genetics and Breeding of Ministry of Agriculture, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan 430070, China; (C.W.); (B.L.)
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China
- Innovation Group of Pig Genome Design and Breeding, Research Centre for Animal Genome, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China
- Kunpeng Institute of Modern Agriculture at Foshan, Chinese Academy of Agricultural Sciences, Foshan 528226, China
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13
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Lee JB, Lim JH, Park HB. Genome-wide association studies to identify quantitative trait loci and positional candidate genes affecting meat quality-related traits in pigs. JOURNAL OF ANIMAL SCIENCE AND TECHNOLOGY 2023; 65:1194-1204. [PMID: 38616878 PMCID: PMC11007289 DOI: 10.5187/jast.2023.e70] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Revised: 06/06/2023] [Accepted: 07/11/2023] [Indexed: 04/16/2024]
Abstract
Meat quality comprises a set of key traits such as pH, meat color, water-holding capacity, tenderness and marbling. These traits are complex because they are affected by multiple genetic and environmental factors. The aim of this study was to investigate the molecular genetic basis underlying nine meat quality-related traits in a Yorkshire pig population using a genome-wide association study (GWAS) and subsequent biological pathway analysis. In total, 45,926 single nucleotide polymorphism (SNP) markers from 543 pigs were selected for the GWAS after quality control. Data were analyzed using a genome-wide efficient mixed model association (GEMMA) method. This linear mixed model-based approach identified two quantitative trait loci (QTLs) for meat color (b*) on chromosome 2 (SSC2) and one QTL for shear force on chromosome 8 (SSC8). These QTLs acted additively on the two phenotypes and explained 3.92%-4.57% of the phenotypic variance of the traits of interest. The genes encoding HAUS8 on SSC2 and an lncRNA on SSC8 were identified as positional candidate genes for these QTLs. The results of the biological pathway analysis revealed that positional candidate genes for meat color (b*) were enriched in pathways related to muscle development, muscle growth, intramuscular adipocyte differentiation, and lipid accumulation in muscle, whereas positional candidate genes for shear force were overrepresented in pathways related to cell growth, cell differentiation, and fatty acids synthesis. Further verification of these identified SNPs and genes in other independent populations could provide valuable information for understanding the variations in pork quality-related traits.
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Affiliation(s)
- Jae-Bong Lee
- Korea Zoonosis Research Institute (KoZRI),
Jeonbuk National University, Iksan 54531, Korea
| | - Ji-Hoon Lim
- Department of Animal Resources Science,
Kongju National University, Yesan 32439, Korea
| | - Hee-Bok Park
- Department of Animal Resources Science,
Kongju National University, Yesan 32439, Korea
- Resource Science Research Institute,
Kongju National University, Yesan 32439, Korea
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14
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Wu F, Chen Z, Zhang Z, Wang Z, Zhang Z, Wang Q, Pan Y. The Role of SOCS3 in Regulating Meat Quality in Jinhua Pigs. Int J Mol Sci 2023; 24:10593. [PMID: 37445769 DOI: 10.3390/ijms241310593] [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: 05/24/2023] [Revised: 06/15/2023] [Accepted: 06/20/2023] [Indexed: 07/15/2023] Open
Abstract
Meat quality is an important economic trait that influences the development of the pig industry. Skeletal muscle development and glycolytic potential (GP) are two crucial aspects that significantly impact meat quality. It has been reported that abnormal skeletal muscle development and high glycogen content results in low meat quality. However, the genetic mechanisms underlying these factors are still unclear. Compared with intensive pig breeds, Chinese indigenous pig breeds, such as the Jinhua pig, express superior meat quality characteristics. The differences in the meat quality traits between Jinhua and intensive pig breeds make them suitable for uncovering the genetic mechanisms that regulate meat quality traits. In this study, the Jinhua pig breed and five intensive pig breeds, including Duroc, Landrace, Yorkshire, Berkshire, and Pietrain pig breeds, were selected as experimental materials. First, the FST and XP-EHH methods were used to screen the selective signatures on the genome in the Jinhua population. Then, combined with RNA-Seq data, the study further confirmed that SOCS3 could be a key candidate gene that influences meat quality by mediating myoblast proliferation and glycometabolism because of the down-regulated expression of SOCS3 in Jinhua pigs compared with Landrace pigs. Finally, through SOCS3 knockout (KO) and overexpression (OE) experiments in mouse C2C12 cells, the results showed that SOCS3 regulated the cell proliferation of myoblasts. Moreover, SOCS3 is involved in regulating glucose uptake by the IRS1/PI3K/AKT signaling pathway. Overall, these findings provide a basis for the genetic improvement of meat quality traits in the pig industry.
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Affiliation(s)
- Fen Wu
- College of Animal Sciences, Zhejiang University, Hangzhou 310058, China
| | - Zitao Chen
- College of Animal Sciences, Zhejiang University, Hangzhou 310058, China
| | - Zhenyang Zhang
- College of Animal Sciences, Zhejiang University, Hangzhou 310058, China
| | - Zhen Wang
- College of Animal Sciences, Zhejiang University, Hangzhou 310058, China
| | - Zhe Zhang
- College of Animal Sciences, Zhejiang University, Hangzhou 310058, China
| | - Qishan Wang
- College of Animal Sciences, Zhejiang University, Hangzhou 310058, China
- Key Laboratory of Livestock and Poultry Resources Evaluation and Utilization, Ministry of Agriculture and Rural Affairs, Hangzhou 310058, China
| | - Yuchun Pan
- College of Animal Sciences, Zhejiang University, Hangzhou 310058, China
- Key Laboratory of Livestock and Poultry Resources Evaluation and Utilization, Ministry of Agriculture and Rural Affairs, Hangzhou 310058, China
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15
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Desire S, Johnsson M, Ros-Freixedes R, Chen CY, Holl JW, Herring WO, Gorjanc G, Mellanby RJ, Hickey JM, Jungnickel MK. A genome-wide association study for loin depth and muscle pH in pigs from intensely selected purebred lines. Genet Sel Evol 2023; 55:42. [PMID: 37322449 DOI: 10.1186/s12711-023-00815-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Accepted: 05/26/2023] [Indexed: 06/17/2023] Open
Abstract
BACKGROUND Genome-wide association studies (GWAS) aim at identifying genomic regions involved in phenotype expression, but identifying causative variants is difficult. Pig Combined Annotation Dependent Depletion (pCADD) scores provide a measure of the predicted consequences of genetic variants. Incorporating pCADD into the GWAS pipeline may help their identification. Our objective was to identify genomic regions associated with loin depth and muscle pH, and identify regions of interest for fine-mapping and further experimental work. Genotypes for ~ 40,000 single nucleotide morphisms (SNPs) were used to perform GWAS for these two traits, using de-regressed breeding values (dEBV) for 329,964 pigs from four commercial lines. Imputed sequence data was used to identify SNPs in strong ([Formula: see text] 0.80) linkage disequilibrium with lead GWAS SNPs with the highest pCADD scores. RESULTS Fifteen distinct regions were associated with loin depth and one with loin pH at genome-wide significance. Regions on chromosomes 1, 2, 5, 7, and 16, explained between 0.06 and 3.55% of the additive genetic variance and were strongly associated with loin depth. Only a small part of the additive genetic variance in muscle pH was attributed to SNPs. The results of our pCADD analysis suggests that high-scoring pCADD variants are enriched for missense mutations. Two close but distinct regions on SSC1 were associated with loin depth, and pCADD identified the previously identified missense variant within the MC4R gene for one of the lines. For loin pH, pCADD identified a synonymous variant in the RNF25 gene (SSC15) as the most likely candidate for the muscle pH association. The missense mutation in the PRKAG3 gene known to affect glycogen content was not prioritised by pCADD for loin pH. CONCLUSIONS For loin depth, we identified several strong candidate regions for further statistical fine-mapping that are supported in the literature, and two novel regions. For loin muscle pH, we identified one previously identified associated region. We found mixed evidence for the utility of pCADD as an extension of heuristic fine-mapping. The next step is to perform more sophisticated fine-mapping and expression quantitative trait loci (eQTL) analysis, and then interrogate candidate variants in vitro by perturbation-CRISPR assays.
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Affiliation(s)
- Suzanne Desire
- The Roslin Institute, The University of Edinburgh, Midlothian, UK.
| | - Martin Johnsson
- Swedish University of Agricultural Sciences, Uppsala, Sweden
| | - Roger Ros-Freixedes
- Departament de Ciència Animal, Universitat de Lleida-Agrotecnio-CERCA Center, Lleida, Spain
| | - Ching-Yi Chen
- The Pig Improvement Company, Genus Plc, Hendersonville, TN, USA
| | - Justin W Holl
- The Pig Improvement Company, Genus Plc, Hendersonville, TN, USA
| | | | - Gregor Gorjanc
- The Roslin Institute, The University of Edinburgh, Midlothian, UK
| | - Richard J Mellanby
- The Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Midlothian, UK
| | - John M Hickey
- The Roslin Institute, The University of Edinburgh, Midlothian, UK
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16
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Liu D, Zhang H, Yang Y, Liu T, Guo Z, Fan W, Wang Z, Yang X, Zhang B, Liu H, Tang H, Yu D, Yu S, Gai K, Mou Q, Cao J, Hu J, Tang J, Hou S, Zhou Z. Metabolome-Based Genome-Wide Association Study of Duck Meat Leads to Novel Genetic and Biochemical Insights. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2023; 10:e2300148. [PMID: 37013465 PMCID: PMC10288243 DOI: 10.1002/advs.202300148] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/07/2023] [Revised: 02/20/2023] [Indexed: 06/19/2023]
Abstract
Meat is among the most consumed foods worldwide and has a unique flavor and high nutrient density in the human diet. However, the genetic and biochemical bases of meat nutrition and flavor are poorly understood. Here, 3431 metabolites and 702 volatiles in 423 skeletal muscle samples are profiled from a gradient consanguinity segregating population generated by Pekin duck × Liancheng duck crosses using metabolomic approaches. The authors identified 2862 metabolome-based genome-wide association studies (mGWAS) signals and 48 candidate genes potentially modulating metabolite and volatile levels, 79.2% of which are regulated by cis-regulatory elements. The level of plasmalogen is significantly associated with TMEM189 encoding plasmanylethanolamine desaturase 1. The levels of 2-pyrrolidone and glycerophospholipids are regulated by the gene expression of AOX1 and ACBD5, which further affects the levels of volatiles, 2-pyrrolidone and decanal, respectively. Genetic variations in GADL1 and CARNMT2 determine the levels of 49 metabolites including L-carnosine and anserine. This study provides novel insights into the genetic and biochemical basis of skeletal muscle metabolism and constitutes a valuable resource for the precise improvement of meat nutrition and flavor.
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Affiliation(s)
- Dapeng Liu
- Institute of Animal ScienceChinese Academy of Agricultural SciencesBeijing100193P. R. China
| | - He Zhang
- Institute of Animal ScienceChinese Academy of Agricultural SciencesBeijing100193P. R. China
| | - Youyou Yang
- Institute of Animal ScienceChinese Academy of Agricultural SciencesBeijing100193P. R. China
| | - Tong Liu
- Institute of Animal ScienceChinese Academy of Agricultural SciencesBeijing100193P. R. China
| | - Zhanbao Guo
- Institute of Animal ScienceChinese Academy of Agricultural SciencesBeijing100193P. R. China
| | - Wenlei Fan
- Institute of Animal ScienceChinese Academy of Agricultural SciencesBeijing100193P. R. China
| | - Zhen Wang
- Institute of Animal ScienceChinese Academy of Agricultural SciencesBeijing100193P. R. China
| | - Xinting Yang
- Institute of Animal ScienceChinese Academy of Agricultural SciencesBeijing100193P. R. China
| | - Bo Zhang
- Institute of Animal ScienceChinese Academy of Agricultural SciencesBeijing100193P. R. China
| | - Hongfei Liu
- Institute of Animal ScienceChinese Academy of Agricultural SciencesBeijing100193P. R. China
| | - Hehe Tang
- Institute of Animal ScienceChinese Academy of Agricultural SciencesBeijing100193P. R. China
| | - Daxin Yu
- Institute of Animal ScienceChinese Academy of Agricultural SciencesBeijing100193P. R. China
| | - Simeng Yu
- Institute of Animal ScienceChinese Academy of Agricultural SciencesBeijing100193P. R. China
| | - Kai Gai
- Institute of Animal ScienceChinese Academy of Agricultural SciencesBeijing100193P. R. China
| | - Qiming Mou
- Institute of Animal ScienceChinese Academy of Agricultural SciencesBeijing100193P. R. China
| | - Junting Cao
- Institute of Animal ScienceChinese Academy of Agricultural SciencesBeijing100193P. R. China
| | - Jian Hu
- Institute of Animal ScienceChinese Academy of Agricultural SciencesBeijing100193P. R. China
| | - Jing Tang
- Institute of Animal ScienceChinese Academy of Agricultural SciencesBeijing100193P. R. China
| | - Shuisheng Hou
- Institute of Animal ScienceChinese Academy of Agricultural SciencesBeijing100193P. R. China
| | - Zhengkui Zhou
- Institute of Animal ScienceChinese Academy of Agricultural SciencesBeijing100193P. R. China
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Suárez-Mesa R, Ros-Freixedes R, Laghouaouta H, Pena RN, Hernández-Ortiz B, Rondón-Barragán I, Estany J. Identification of breed-specific genomic variants in Colombian Creole pig breeds by whole-genome sequencing. Trop Anim Health Prod 2023; 55:154. [PMID: 37041265 PMCID: PMC10089996 DOI: 10.1007/s11250-023-03557-9] [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: 12/02/2022] [Accepted: 03/29/2023] [Indexed: 04/13/2023]
Abstract
Dissecting genetic variation of local breeds is important for the success of conservation. In this research, we investigated the genomic variation of Colombian Creole (CR) pigs, with a focus on the breed-specific variants in the exonic region of 34 genes with reported effects on adaptive and economic traits. Seven individuals of each of the three CR breeds (CM, Casco de Mula; SP, San Pedreño; and ZU, Zungo) were whole-genome sequenced along with 7 Iberian (IB) pigs and 7 pigs of each of the four most used cosmopolitan (CP) breeds (Duroc, Landrace × Large White, and Pietrain). Molecular variability in CR (6,451,218 variants; from 3,919,242, in SP, to 4,648,069, in CM) was comparable to that in CP, but higher than in IB. For the investigated genes, SP pigs displayed less exonic variants (178) than ZU (254), CM (263), IB (200), and the individual CP genetic types (201 to 335). Sequence variation in these genes confirmed the resemblance of CR to IB and indicates that CR pigs, particularly ZU and CM, are not exempt from selective introgression of other breeds. A total of 50 exonic variants were identified as being potentially specific to CR, including a high-impact deletion in the intron between exons 15 and 16 of the leptin receptor gene, which was only found in CM and ZU. The identification of breed-specific variants in genes related to adaptive and economical traits can bolster the understanding of the role of gene-environment interactions on local adaptation and points the way for effective breeding and conservation of CR pigs.
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Affiliation(s)
- Rafael Suárez-Mesa
- Department of Animal Science, University of Lleida Agrotecnio-CERCA Center, 191 Rovira Roure, 25198, Lleida, Catalonia, Spain.
- Research Group in Immunobiology and Pathogenesis, Faculty of Veterinary Medicine and Zootechnics, University of Tolima, Barrio Santa Helena Parte Alta, Ibagué, Colombia.
| | - Roger Ros-Freixedes
- Department of Animal Science, University of Lleida Agrotecnio-CERCA Center, 191 Rovira Roure, 25198, Lleida, Catalonia, Spain
| | - Houda Laghouaouta
- Department of Animal Science, University of Lleida Agrotecnio-CERCA Center, 191 Rovira Roure, 25198, Lleida, Catalonia, Spain
| | - Ramona N Pena
- Department of Animal Science, University of Lleida Agrotecnio-CERCA Center, 191 Rovira Roure, 25198, Lleida, Catalonia, Spain
| | - Byron Hernández-Ortiz
- Research and Innovation Group in Animal Health and Welfare Germplasm Animal Bank, Agrosavia, Bogotá, 250047, Colombia
| | - Iang Rondón-Barragán
- Research Group in Immunobiology and Pathogenesis, Faculty of Veterinary Medicine and Zootechnics, University of Tolima, Barrio Santa Helena Parte Alta, Ibagué, Colombia
| | - Joan Estany
- Department of Animal Science, University of Lleida Agrotecnio-CERCA Center, 191 Rovira Roure, 25198, Lleida, Catalonia, Spain.
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18
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Xie X, Huang C, Huang Y, Zou X, Zhou R, Ai H, Huang L, Ma J. Genetic architecture for skeletal muscle glycolytic potential in Chinese Erhualian pigs revealed by a genome-wide association study using 1.4M SNP array. Front Genet 2023; 14:1141411. [PMID: 37007966 PMCID: PMC10064215 DOI: 10.3389/fgene.2023.1141411] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Accepted: 02/16/2023] [Indexed: 03/19/2023] Open
Abstract
Introduction: Muscle glycolytic potential (GP) is a key factor affecting multiple meat quality traits. It is calculated based on the contents of residual glycogen and glucose (RG), glucose-6-phosphate (G6P), and lactate (LAT) contents in muscle. However, the genetic mechanism of glycolytic metabolism in skeletal muscle of pigs remains poorly understood. With a history of more than 400 years and some unique characteristics, the Erhualian pig is called the “giant panda” (very precious) in the world’s pig species by Chinese animal husbandry.Methods: Here, we performed a genome-wide association study (GWAS) using 1.4M single nucleotide polymorphisms (SNPs) chips for longissimus RG, G6P, LAT, and GP levels in 301 purebred Erhualian pigs.Results: We found that the average GP value of Erhualian was unusually low (68.09 μmol/g), but the variation was large (10.4–112.7 μmol/g). The SNP-based heritability estimates for the four traits ranged from 0.16–0.32. In total, our GWAS revealed 31 quantitative trait loci (QTLs), including eight for RG, nine for G6P, nine for LAT, five for GP. Of these loci, eight were genome-wide significant (p < 3.8 × 10−7), and six loci were common to two or three traits. Multiple promising candidate genes such as FTO, MINPP1, RIPOR2, SCL8A3, LIFR and SRGAP1 were identified. The genotype combinations of the five GP-associated SNPs also showed significant effect on other meat quality traits.Discussion: These results not only provide insights into the genetic architecture of GP related traits in Erhualian, but also are useful for pig breeding programs involving this breed.
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Affiliation(s)
- Xinke Xie
- National Key Laboratory for Swine Genetic Improvement and Production Technology, Ministry of Science and Technology of China, Jiangxi Agricultural University, Nanchang, China
| | - Cong Huang
- National Key Laboratory for Swine Genetic Improvement and Production Technology, Ministry of Science and Technology of China, Jiangxi Agricultural University, Nanchang, China
| | - Yizhong Huang
- National Key Laboratory for Swine Genetic Improvement and Production Technology, Ministry of Science and Technology of China, Jiangxi Agricultural University, Nanchang, China
| | - Xiaoxiao Zou
- National Key Laboratory for Swine Genetic Improvement and Production Technology, Ministry of Science and Technology of China, Jiangxi Agricultural University, Nanchang, China
| | - Runxin Zhou
- National Key Laboratory for Swine Genetic Improvement and Production Technology, Ministry of Science and Technology of China, Jiangxi Agricultural University, Nanchang, China
| | - Huashui Ai
- National Key Laboratory for Swine Genetic Improvement and Production Technology, Ministry of Science and Technology of China, Jiangxi Agricultural University, Nanchang, China
| | - Lusheng Huang
- National Key Laboratory for Swine Genetic Improvement and Production Technology, Ministry of Science and Technology of China, Jiangxi Agricultural University, Nanchang, China
- Correspondence: Lusheng Huang, ; Junwu Ma,
| | - Junwu Ma
- National Key Laboratory for Swine Genetic Improvement and Production Technology, Ministry of Science and Technology of China, Jiangxi Agricultural University, Nanchang, China
- Correspondence: Lusheng Huang, ; Junwu Ma,
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19
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Wang H, Wang X, Li M, Sun H, Chen Q, Yan D, Dong X, Pan Y, Lu S. Genome-wide association study reveals genetic loci and candidate genes for meat quality traits in a four-way crossbred pig population. Front Genet 2023; 14:1001352. [PMID: 36814900 PMCID: PMC9939654 DOI: 10.3389/fgene.2023.1001352] [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: 07/23/2022] [Accepted: 01/24/2023] [Indexed: 02/08/2023] Open
Abstract
Meat quality traits (MQTs) have gained more attention from breeders due to their increasing economic value in the commercial pig industry. In this genome-wide association study (GWAS), 223 four-way intercross pigs were genotyped using the specific-locus amplified fragment sequencing (SLAF-seq) and phenotyped for PH at 45 min post mortem (PH45), meat color score (MC), marbling score (MA), water loss rate (WL), drip loss (DL) in the longissimus muscle, and cooking loss (CL) in the psoas major muscle. A total of 227, 921 filtered single nucleotide polymorphisms (SNPs) evenly distributed across the entire genome were detected to perform GWAS. A total of 64 SNPs were identified for six meat quality traits using the mixed linear model (MLM), of which 24 SNPs were located in previously reported QTL regions. The phenotypic variation explained (PVE) by the significant SNPs was from 2.43% to 16.32%. The genomic heritability estimates based on SNP for six meat-quality traits were low to moderate (0.07-0.47) being the lowest for CL and the highest for DL. A total of 30 genes located within 10 kb upstream or downstream of these significant SNPs were found. Furthermore, several candidate genes for MQTs were detected, including pH45 (GRM8), MC (ANKRD6), MA (MACROD2 and ABCG1), WL (TMEM50A), CL (PIP4K2A) and DL (CDYL2, CHL1, ABCA4, ZAG and SLC1A2). This study provided substantial new evidence for several candidate genes to participate in different pork quality traits. The identification of these SNPs and candidate genes provided a basis for molecular marker-assisted breeding and improvement of pork quality traits.
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Affiliation(s)
- Huiyu Wang
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, Yunnan, China,Faculty of Animal Science, Xichang University, Xichang, Sichuan, China
| | - Xiaoyi Wang
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, Yunnan, China
| | - Mingli Li
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, Yunnan, China
| | - Hao Sun
- Faculty of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai, China
| | - Qiang Chen
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, Yunnan, China
| | - Dawei Yan
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, Yunnan, China
| | - Xinxing Dong
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, Yunnan, China
| | - Yuchun Pan
- Faculty of Animal Science, Zhejiang University, Hangzhou, Zhejiang, China,*Correspondence: Yuchun Pan, ; Shaoxiong Lu,
| | - Shaoxiong Lu
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, Yunnan, China,*Correspondence: Yuchun Pan, ; Shaoxiong Lu,
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20
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Zhuang Z, Wu J, Xu C, Ruan D, Qiu Y, Zhou S, Ding R, Quan J, Yang M, Zheng E, Wu Z, Yang J. The Genetic Architecture of Meat Quality Traits in a Crossbred Commercial Pig Population. Foods 2022; 11:foods11193143. [PMID: 36230219 PMCID: PMC9563986 DOI: 10.3390/foods11193143] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Revised: 10/07/2022] [Accepted: 10/08/2022] [Indexed: 11/25/2022] Open
Abstract
Meat quality is of importance in consumer acceptance and purchasing tendency of pork. However, the genetic architecture of pork meat quality traits remains elusive. Herein, we conducted genome-wide association studies to detect single nucleotide polymorphisms (SNPs) and genes affecting meat pH and meat color (L*, lightness; a*, redness; b*, yellowness) in 1518 three-way crossbred pigs. All individuals were genotyped using the GeneSeek Porcine 50K BeadChip. In sum, 30 SNPs and 20 genes are found to be associated with eight meat quality traits. Notably, we detect one significant quantitative trait locus (QTL) on SSC15 with a 143 kb interval for meat pH (pH_12h), together with the most promising candidate TNS1. Interestingly, two newly identified SNPs located in the TTLL4 gene demonstrate the highest phenotypic variance of pH_12h in this QTL, at 2.67%. The identified SNPs are useful for the genetic improvement of meat quality traits in pigs by assigning higher weights to associated SNPs in genomic selection.
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Affiliation(s)
- Zhanwei Zhuang
- National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou 510642, China
| | - Jie Wu
- National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou 510642, China
| | - Cineng Xu
- National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou 510642, China
| | - Donglin Ruan
- National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou 510642, China
| | - Yibin Qiu
- National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou 510642, China
| | - Shenping Zhou
- National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou 510642, China
| | - Rongrong Ding
- National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou 510642, China
- Guangdong Zhongxin Breeding Technology Co., Ltd., Guangzhou 511466, China
| | - Jianping Quan
- National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou 510642, China
| | - Ming Yang
- College of Animal Science and Technology, Zhongkai University of Agriculture and Engineering, Guangzhou 510225, China
| | - Enqin Zheng
- National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou 510642, China
- 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
- 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
- National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou 510642, China
- Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, South China Agricultural University, Guangzhou 510642, China
- Correspondence:
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21
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Wei W, Zha C, Jiang A, Chao Z, Hou L, Liu H, Huang R, Wu W. A Combined Differential Proteome and Transcriptome Profiling of Fast- and Slow-Twitch Skeletal Muscle in Pigs. Foods 2022; 11:foods11182842. [PMID: 36140968 PMCID: PMC9497725 DOI: 10.3390/foods11182842] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2022] [Revised: 09/01/2022] [Accepted: 09/07/2022] [Indexed: 11/16/2022] Open
Abstract
Skeletal muscle fiber types can contribute in part to affecting pork quality parameters. Biceps femoris (Bf) (fast muscle or white muscle) and Soleus (Sol) (slow muscle or red muscle) are two typical skeletal muscles characterized by obvious muscle fiber type differences in pigs. However, the critical proteins and potential regulatory mechanisms regulating porcine skeletal muscle fibers have yet to be clearly defined. In this study, the isobaric Tag for Relative and Absolute Quantification (iTRAQ)-based proteome was used to identify the key proteins affecting the skeletal muscle fiber types with Bf and Sol, by integrating the previous transcriptome data, while function enrichment analysis and a protein–protein interaction (PPI) network were utilized to explore the potential regulatory mechanisms of skeletal muscle fibers. A total of 126 differentially abundant proteins (DAPs) between the Bf and Sol were identified, and 12 genes were found to be overlapping between differentially expressed genes (DEGs) and DAPs, which are the critical proteins regulating the formation of skeletal muscle fibers. Functional enrichment and PPI analysis showed that the DAPs were mainly involved in the skeletal-muscle-associated structural proteins, mitochondria and energy metabolism, tricarboxylic acid cycle, fatty acid metabolism, and kinase activity, suggesting that PPI networks including DAPs are the main regulatory network affecting muscle fiber formation. Overall, these data provide valuable information for understanding the molecular mechanism underlying the formation and conversion of muscle fiber types, and provide potential markers for the evaluation of meat quality.
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Affiliation(s)
- Wei Wei
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science and Technology, Nanjing Agricultural University, Nanjing 210095, China
| | - Chengwan Zha
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science and Technology, Nanjing Agricultural University, Nanjing 210095, China
| | - Aiwen Jiang
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science and Technology, Nanjing Agricultural University, Nanjing 210095, China
| | - Zhe Chao
- Institute of Animal Science and Veterinary Medicine, Hainan Academy of Agricultural Sciences, Haikou 571100, China
| | - Liming Hou
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science and Technology, Nanjing Agricultural University, Nanjing 210095, China
| | - Honglin Liu
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science and Technology, Nanjing Agricultural University, Nanjing 210095, China
| | - Ruihua Huang
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science and Technology, Nanjing Agricultural University, Nanjing 210095, China
| | - Wangjun Wu
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science and Technology, Nanjing Agricultural University, Nanjing 210095, China
- Correspondence: ; Tel.: +86-25-84399762
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22
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Sun Y, Lin X, Zhang Q, Pang Y, Zhang X, Zhao X, Liu D, Yang X. Genome-wide characterization of lncRNAs and mRNAs in muscles with differential intramuscular fat contents. Front Vet Sci 2022; 9:982258. [PMID: 36003408 PMCID: PMC9393339 DOI: 10.3389/fvets.2022.982258] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Accepted: 07/18/2022] [Indexed: 11/21/2022] Open
Abstract
Meat quality is one of the most important traits in pig production. Long non-coding RNAs (lncRNAs) have been involved in diverse biological processes such as muscle development through regulating gene expression. However, studies on lncRNAs lag behind and a comparatively small number of lncRNAs have been identified in pigs. Also, the effects of lncRNAs on meat quality remain to be characterized. Here, we analyzed lncRNAs in longissimus thoracis (LT) and semitendinosus (ST) muscles, being different in meat quality, with RNA-sequencing technology. A total of 500 differentially expressed lncRNAs (DELs) and 2,094 protein-coding genes (DEGs) were identified. Through KEGG analysis on DELs, we first made clear that fat deposition might be the main reason resulting in the differential phenotype of LT and ST, for which cGMP–PKG and VEGF signaling pathways were the most important ones. In total, forty-one key DELs and 50 DEGs involved in the differential fat deposition were then characterized. One of the key genes, cAMP-response element binding protein 1, was selected to confirm its role in porcine adipogenesis with molecular biology methods and found that it promotes the differentiation of porcine preadipocytes, consistent with its higher expression level and intramuscular fat contents in LT than that in ST muscle. Furthermore, through integrated analysis of DELs and DEGs, transcription factors important for differential fat deposition were characterized among which BCL6 has the most target DEGs while MEF2A was targeted by the most DELs. The results provide candidate genes crucial for meat quality, which will contribute to improving meat quality with molecular-breeding strategies.
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Affiliation(s)
- Yuanlu Sun
- College of Animal Science and Technology, Northeast Agricultural University, Harbin, China
| | - Xu Lin
- College of Animal Science and Technology, Northeast Agricultural University, Harbin, China
| | - Qian Zhang
- College of Animal Science and Technology, Northeast Agricultural University, Harbin, China
| | - Yu Pang
- College of Animal Science and Technology, Northeast Agricultural University, Harbin, China
| | - Xiaohan Zhang
- College of Animal Science and Technology, Northeast Agricultural University, Harbin, China
| | - Xuelian Zhao
- College of Animal Science and Technology, Northeast Agricultural University, Harbin, China
| | - Di Liu
- Heilongjiang Academy of Agricultural Sciences, Harbin, China
- *Correspondence: Di Liu
| | - Xiuqin Yang
- College of Animal Science and Technology, Northeast Agricultural University, Harbin, China
- Xiuqin Yang
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23
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Zhu Y, Zhou Z, Huang T, Zhang Z, Li W, Ling Z, Jiang T, Yang J, Yang S, Xiao Y, Charlier C, Georges M, Yang B, Huang L. Mapping and analysis of a spatiotemporal H3K27ac and gene expression spectrum in pigs. SCIENCE CHINA. LIFE SCIENCES 2022; 65:1517-1534. [PMID: 35122624 DOI: 10.1007/s11427-021-2034-5] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/09/2021] [Accepted: 10/29/2021] [Indexed: 12/12/2022]
Abstract
The limited knowledge of genomic noncoding and regulatory regions has restricted our ability to decipher the genetic mechanisms underlying complex traits in pigs. In this study, we characterized the spatiotemporal landscape of putative enhancers and promoters and their target genes by combining H3K27ac-targeted ChIP-Seq and RNA-Seq in fetal (prenatal days 74-75) and adult (postnatal days 132-150) tissues (brain, liver, heart, muscle and small intestine) sampled from Asian aboriginal Bama Xiang and European highly selected Large White pigs of both sexes. We identified 101,290 H3K27ac peaks, marking 18,521 promoters and 82,769 enhancers, including peaks that were active across all tissues and developmental stages (which could indicate safe harbor locus for exogenous gene insertion) and tissue- and developmental stage-specific peaks (which regulate gene pathways matching tissue- and developmental stage-specific physiological functions). We found that H3K27ac and DNA methylation in the promoter region of the XIST gene may be involved in X chromosome inactivation and demonstrated the utility of the present resource for revealing the regulatory patterns of known causal genes and prioritizing candidate causal variants for complex traits in pigs. In addition, we identified an average of 1,124 super-enhancers per sample and found that they were more likely to show tissue-specific activity than ordinary peaks. We have developed a web browser to improve the accessibility of the results ( http://segtp.jxau.edu.cn/pencode/?genome=susScr11 ).
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Affiliation(s)
- Yaling Zhu
- State Key Laboratory of Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China
- Laboratory Animal Research Center, School of Basic Medical Sciences, Anhui Medical University, Hefei, 230032, China
| | - Zhimin Zhou
- State Key Laboratory of Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China
| | - Tao Huang
- State Key Laboratory of Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China
| | - Zhen Zhang
- State Key Laboratory of Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China
| | - Wanbo Li
- State Key Laboratory of Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China
| | - Ziqi Ling
- State Key Laboratory of Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China
| | - Tao Jiang
- State Key Laboratory of Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China
| | - Jiawen Yang
- State Key Laboratory of Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China
| | - Siyu Yang
- State Key Laboratory of Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China
| | - Yanyuan Xiao
- State Key Laboratory of Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China
| | - Carole Charlier
- State Key Laboratory of Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China
- Unit of Animal Genomics, GIGA-Institute and Faculty of Veterinary Medicine, University of Liege, 4000, Liege, Belgium
| | - Michel Georges
- State Key Laboratory of Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China
- Unit of Animal Genomics, GIGA-Institute and Faculty of Veterinary Medicine, University of Liege, 4000, Liege, Belgium
| | - Bin Yang
- State Key Laboratory of Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China.
| | - Lusheng Huang
- State Key Laboratory of Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China.
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24
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Tan X, He Y, Qin Y, Yan Z, Chen J, Zhao R, Zhou S, Irwin DM, Li B, Zhang S. Comparative analysis of differentially abundant proteins between high and low intramuscular fat content groups in donkeys. Front Vet Sci 2022; 9:951168. [PMID: 35967999 PMCID: PMC9364086 DOI: 10.3389/fvets.2022.951168] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Accepted: 07/05/2022] [Indexed: 11/13/2022] Open
Abstract
Intramuscular fat (IMF) is an important regulator that determines meat quality, and its content is closely related to flavor, tenderness, and juiciness. Many studies have used quantitative proteomic analysis to identify proteins associated with meat quality traits in livestock, however, the potential candidate proteins that influence IMF in donkey muscle are not fully understood. In this study, we performed quantitative proteomic analysis, with tandem-mass-tagged (TMT) labeling, with samples from the longissimus dorsi (LD) muscle of the donkey. A total of 585,555 spectra were identified from the six muscle samples used in this study. In total, 20,583 peptides were detected, including 15,279 unique peptides, and 2,540 proteins were identified. We analyzed differentially abundant proteins (DAPs) between LD muscles of donkeys with high (H) and low (L) IMF content. We identified 30 DAPs between the H and L IMF content groups, of which 17 were upregulated and 13 downregulated in the H IMF group. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analysis of these DAPs revealed many GO terms (e.g., bone morphogenetic protein (BMP) receptor binding) and pathways (e.g., Wnt signaling pathway and Hippo signaling pathway) involved in lipid metabolism and adipogenesis. The construction of protein-protein interaction networks identified 16 DAPs involved in these networks. Our data provide a basis for future investigations into candidate proteins involved in IMF deposition and potential new approaches to improve meat quality in the donkey.
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Affiliation(s)
- Xiaofan Tan
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science and Veterinary Medicine, Shenyang Agricultural University, Shenyang, China
| | - Yu He
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science and Veterinary Medicine, Shenyang Agricultural University, Shenyang, China
| | - Yanchun Qin
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science and Veterinary Medicine, Shenyang Agricultural University, Shenyang, China
| | - Zhiwei Yan
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science and Veterinary Medicine, Shenyang Agricultural University, Shenyang, China
| | - Jing Chen
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science and Veterinary Medicine, Shenyang Agricultural University, Shenyang, China
| | - Ruixue Zhao
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science and Veterinary Medicine, Shenyang Agricultural University, Shenyang, China
| | - Shenglan Zhou
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science and Veterinary Medicine, Shenyang Agricultural University, Shenyang, China
| | - David M. Irwin
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada
| | - Bojiang Li
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science and Veterinary Medicine, Shenyang Agricultural University, Shenyang, China
| | - Shuyi Zhang
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science and Veterinary Medicine, Shenyang Agricultural University, Shenyang, China
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Rare and population-specific functional variation across pig lines. Genet Sel Evol 2022; 54:39. [PMID: 35659233 PMCID: PMC9164375 DOI: 10.1186/s12711-022-00732-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Accepted: 05/17/2022] [Indexed: 01/09/2023] Open
Abstract
BACKGROUND It is expected that functional, mainly missense and loss-of-function (LOF), and regulatory variants are responsible for most phenotypic differences between breeds and genetic lines of livestock species that have undergone diverse selection histories. However, there is still limited knowledge about the existing missense and LOF variation in commercial livestock populations, in particular regarding population-specific variation and how it can affect applications such as across-breed genomic prediction. METHODS We re-sequenced the whole genome of 7848 individuals from nine commercial pig lines (average sequencing coverage: 4.1×) and imputed whole-genome genotypes for 440,610 pedigree-related individuals. The called variants were categorized according to predicted functional annotation (from LOF to intergenic) and prevalence level (number of lines in which the variant segregated; from private to widespread). Variants in each category were examined in terms of their distribution along the genome, alternative allele frequency, per-site Wright's fixation index (FST), individual load, and association to production traits. RESULTS Of the 46 million called variants, 28% were private (called in only one line) and 21% were widespread (called in all nine lines). Genomic regions with a low recombination rate were enriched with private variants. Low-prevalence variants (called in one or a few lines only) were enriched for lower allele frequencies, lower FST, and putatively functional and regulatory roles (including LOF and deleterious missense variants). On average, individuals carried fewer private deleterious missense alleles than expected compared to alleles with other predicted consequences. Only a small subset of the low-prevalence variants had intermediate allele frequencies and explained small fractions of phenotypic variance (up to 3.2%) of production traits. The significant low-prevalence variants had higher per-site FST than the non-significant ones. These associated low-prevalence variants were tagged by other more widespread variants in high linkage disequilibrium, including intergenic variants. CONCLUSIONS Most low-prevalence variants have low minor allele frequencies and only a small subset of low-prevalence variants contributed detectable fractions of phenotypic variance of production traits. Accounting for low-prevalence variants is therefore unlikely to noticeably benefit across-breed analyses, such as the prediction of genomic breeding values in a population using reference populations of a different genetic background.
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Xu J, Jiang AM, Zhang C, Zheng Y, Zhang T, Zhou L. Potential of eight mutations for marker-assisted breeding in Chinese Lulai black pigs. CANADIAN JOURNAL OF ANIMAL SCIENCE 2022. [DOI: 10.1139/cjas-2021-0108] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
Molecular marker-assisted selection (MAS) provides an efficient tool for pig breeding. In this study, according to the literature, we selected eight effective or causal mutations from eight functional genes, including five causal mutations in PHKG1 (rs330928088), MUC13 (rs319699771), IGF2 (g.3072G>A), VRTN (g.20311_20312ins291) and MYH3 (XM_013981330.2:g.-1805_-1810del) genes, and three effective mutations in LIPE (rs328830166), LEPR (rs45435518) and MC4R (rs81219178) genes, to investigate the potential breeding effect of them in 418 Lulai pigs. The linear model was used to analyze the association between mutations and intramuscular fat (IMF) content, average backfat thickness (ABT) and muscle moisture percent (MMP). The results revealed that among the four effective mutations, only the mutation in the LEPR gene, which affect IMF deposition, was significantly associated with IMF content. However, the other molecular markers were not significantly associated with the affected traits reported in previous studies, and these mutations are ineffective for MAS in the Lulai black pig population. Therefore, causal mutations in PHKG1, IGF2 and VRTN genes, and an effective mutation in LEPR gene could be used as effective breeding makers for MAS in Lulai pigs. These results can provide helpful information for further breeding in Lulai black pigs.
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Affiliation(s)
- Jing Xu
- Qingdao Agricultural University, 98431, Qingdao, China, 266109
| | - Ai mei Jiang
- Jiaozhou City Bureau of Agriculture and Rural Affairs, Qingdao, China
| | | | | | - Tingrong Zhang
- Qingdao Agricultural University, 98431, Qingdao, China, 266109
| | - Lisheng Zhou
- Qingdao Agricultural University, 98431, Qingdao, China, 266109
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Gu J, Qi Y, Lu Y, Tao Q, Yu D, Jiang C, Liu J, Liang X. Lung adenocarcinoma-derived vWF promotes tumor metastasis by regulating PHKG1-mediated glycogen metabolism. Cancer Sci 2022; 113:1362-1376. [PMID: 35150045 PMCID: PMC8990721 DOI: 10.1111/cas.15298] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2021] [Revised: 01/20/2022] [Accepted: 02/01/2022] [Indexed: 11/29/2022] Open
Abstract
Tumor metastasis is a series of complicated biological events. Hematogenous metastasis mediated by von Willebrand factor (vWF) is critical in tumor metastasis. However, the source of vWF and its role in tumor metastasis are controversial, and the further mechanism involved in mediating tumor metastasis is still unclear. In this study, we first demonstrated that lung adenocarcinoma cells could express vWF de novo and promotes tumor metastasis. Through the analysis of transcriptome sequencing, metastasis promotion effect of vWF may be related to phosphorylase kinase subunit G1 (PHKG1), a catalytic subtype of phosphorylase kinase PhK. PHKG1 was highly expressed in lung adenocarcinoma patients and led to poor prognosis. Further experiments found that lung adenocarcinoma-derived vWF induced the up-regulation of PHKG1 through the PI3K/AKT pathway to promote glycogenolysis. Glycogen was funneled into glycolysis, leading to increased metastasis. Tumor metastasis assayed in vitro and in vivo showed that knockdown of PHKG1 or synergistic injection of phosphorylase inhibition based on the overexpression of vWF could inhibit metastasis. In summary, our research proved that lung adenocarcinoma-derived vWF may mediate tumor metastasis by regulating PHKG1 to promote glycogen metabolism, and suggested potential targets for inhibition of lung adenocarcinoma metastasis.
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Affiliation(s)
- Jiayi Gu
- Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai, China
| | - Yingxue Qi
- Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai, China
| | - Yuxin Lu
- Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai, China
| | - Qianying Tao
- Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai, China
| | - Die Yu
- Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai, China.,Central laboratory, General Surgery, Putuo Hospital, and Interventional Cancer Institute of Chinese Integrative Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, 200062, PR China
| | - Chunchun Jiang
- Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai, China
| | - Jianwen Liu
- Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai, China
| | - Xin Liang
- Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai, China
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28
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Davoli R, Vegni J, Cesarani A, Dimauro C, Zappaterra M, Zambonelli P. Identification of differentially expressed genes in early-postmortem Semimembranosus muscle of Italian Large White heavy pigs divergent for glycolytic potential. Meat Sci 2022; 187:108754. [DOI: 10.1016/j.meatsci.2022.108754] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2021] [Revised: 01/18/2022] [Accepted: 02/01/2022] [Indexed: 10/19/2022]
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29
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Ding R, Zhuang Z, Qiu Y, Ruan D, Wu J, Ye J, Cao L, Zhou S, Zheng E, Huang W, Wu Z, Yang J. Identify known and novel candidate genes associated with backfat thickness in Duroc pigs by large-scale genome-wide association analysis. J Anim Sci 2022; 100:6509022. [PMID: 35034121 PMCID: PMC8867564 DOI: 10.1093/jas/skac012] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Accepted: 01/14/2022] [Indexed: 01/18/2023] Open
Abstract
Backfat thickness (BFT) is complex and economically important traits in the pig industry, since it reflects fat deposition and can be used to measure the carcass lean meat percentage in pigs. In this study, all 6,550 pigs were genotyped using the Geneseek Porcine 50K SNP Chip to identify SNPs related to BFT and to search for candidate genes through genome-wide association analysis in two Duroc populations. In total, 80 SNPs, including 39 significant and 41 suggestive SNPs, and 6 QTLs were identified significantly associated with the BFT. In addition, 9 candidate genes, including a proven major gene MC4R, 3 important candidate genes (RYR1, HMGA1, and NUDT3) which were previously described as related to BFT, and 5 novel candidate genes (SIRT2, NKAIN2, AMH, SORCS1, and SORCS3) were found based on their potential functional roles in BFT. The functions of candidate genes and gene set enrichment analysis indicate that most important pathways are related to energy homeostasis and adipogenesis. Finally, our data suggest that most of the candidate genes can be directly used for genetic improvement through molecular markers, except that the MC4R gene has an antagonistic effect on growth rate and carcass lean meat percentage in breeding. Our results will advance our understanding of the complex genetic architecture of BFT traits and laid the foundation for additional genetic studies to increase carcass lean meat percentage of pig through marker-assisted selection and/or genomic selection.
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Affiliation(s)
- Rongrong Ding
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, 510642, P. R. China,Guangdong Wens Breeding Swine Technology Co., Ltd., Guangdong, 527400, P. R. China
| | - Zhanwei Zhuang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, 510642, P. R. China
| | - Yibin Qiu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, 510642, P. R. China
| | - Donglin Ruan
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, 510642, P. R. China
| | - Jie Wu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, 510642, P. R. China
| | - Jian Ye
- Guangdong Wens Breeding Swine Technology Co., Ltd., Guangdong, 527400, P. R. China
| | - Lu Cao
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, 510642, P. R. China
| | - Shenping Zhou
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, 510642, P. R. China
| | - Enqin Zheng
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, 510642, P. R. China,Lingnan Guangdong Laboratory of Modern Agriculture, Guangzhou, 510642, P. R. China
| | - Wen Huang
- Department of Animal Science, Michigan State University, East Lansing, MI, USA
| | - Zhenfang Wu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, 510642, P. R. China,Guangdong Wens Breeding Swine Technology Co., Ltd., Guangdong, 527400, P. R. China,Lingnan Guangdong Laboratory of Modern Agriculture, Guangzhou, 510642, P. R. China
| | - Jie Yang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, 510642, P. R. China,Lingnan Guangdong Laboratory of Modern Agriculture, Guangzhou, 510642, P. R. China,Corresponding authors:
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Xiong X, Liu X, Zhu X, Tan Y, Wang Z, Xu J, Tu X, Rao Y, Duan J, Zhao W, Zhou M. A mutation in PHKG1 causes high drip loss and low meat quality in Chinese Ningdu yellow chickens. Poult Sci 2021; 101:101556. [PMID: 34852315 PMCID: PMC8639467 DOI: 10.1016/j.psj.2021.101556] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2021] [Revised: 08/29/2021] [Accepted: 10/14/2021] [Indexed: 12/18/2022] Open
Abstract
With increasing societal development and the concurrent improvement in people's quality of life, meat consumption has gradually changed from a focus on “quantity” to “quality”. Broiler production is increasingly used as a means to improve meat quality by altering various characteristics, especially its genetic factors. However, until now, little has been known about the genetic variants related to meat quality traits in Chinese purebred chicken populations. To better understand these genetic underpinnings, a total of 17 traits related to meat quality and carcass were measured in 325 Chinese Ningdu yellow chickens. We performed DNA sequencing to detect nucleotide mutations, after which we conducted association studies between PHKG1 gene polymorphisms and traits related to meat quality and carcass. Results indicated a large phenotypic variation in meat quality traits. More specifically, the single nucleotide polymorphism (SNP) rs15845448 was significantly associated with drip loss at 24 h (P = 8.04 × 10−6) and 48 h (P = 5.47 × 10−6), pH (P = 2.39 × 10−3), and meat color L* (P = 9.88 × 10−3). Moreover, the SNP rs15845448 reduced 24 h and 48 h drip loss by 3.62 and 5.97%, respectively. However, no significant associations were found between rs15845448 and carcass traits (P > 0.05). Furthermore, a haplotype block containing 2 adjacent SNPs (rs15845448 and rs15845450) was identified. This block displayed 4 distinct haplotypes that had significant association with drip loss at 24 h and 48 h, pH, and meat color L*. Collectively, these results provide new insights into the genetic basis of meat quality in Chinese Ningdu yellow chickens. Moreover, the significance of SNP rs15845448 could be incorporated into the selection programs involving this breed.
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Affiliation(s)
- Xinwei Xiong
- Institute of Biological Technology, Nanchang Normal University, Nanchang, 330032, China; Key Laboratory for Genetic Improvement of Indigenous Chicken Breeds of Jiangxi Province, Nanchang, 330032, China
| | - Xianxian Liu
- Key Laboratory of Women's Reproductive Health of Jiangxi, Jiangxi Provincial Maternal and Child Health Hospital, Nanchang, 330006, China
| | - Xuenong Zhu
- Institute of Biological Technology, Nanchang Normal University, Nanchang, 330032, China; Key Laboratory for Genetic Improvement of Indigenous Chicken Breeds of Jiangxi Province, Nanchang, 330032, China
| | - Yuwen Tan
- Institute of Biological Technology, Nanchang Normal University, Nanchang, 330032, China; Key Laboratory for Genetic Improvement of Indigenous Chicken Breeds of Jiangxi Province, Nanchang, 330032, China
| | - Zhangfeng Wang
- Institute of Biological Technology, Nanchang Normal University, Nanchang, 330032, China; Key Laboratory for Genetic Improvement of Indigenous Chicken Breeds of Jiangxi Province, Nanchang, 330032, China
| | - Jiguo Xu
- Institute of Biological Technology, Nanchang Normal University, Nanchang, 330032, China; Key Laboratory for Genetic Improvement of Indigenous Chicken Breeds of Jiangxi Province, Nanchang, 330032, China
| | - Xutang Tu
- Institute of Biological Technology, Nanchang Normal University, Nanchang, 330032, China; Key Laboratory for Genetic Improvement of Indigenous Chicken Breeds of Jiangxi Province, Nanchang, 330032, China
| | - Yousheng Rao
- Institute of Biological Technology, Nanchang Normal University, Nanchang, 330032, China; Key Laboratory for Genetic Improvement of Indigenous Chicken Breeds of Jiangxi Province, Nanchang, 330032, China
| | - Jinhong Duan
- Institute of Biological Technology, Nanchang Normal University, Nanchang, 330032, China; Key Laboratory for Genetic Improvement of Indigenous Chicken Breeds of Jiangxi Province, Nanchang, 330032, China
| | - Wenliang Zhao
- Institute of Biological Technology, Nanchang Normal University, Nanchang, 330032, China; Key Laboratory for Genetic Improvement of Indigenous Chicken Breeds of Jiangxi Province, Nanchang, 330032, China
| | - Min Zhou
- Institute of Biological Technology, Nanchang Normal University, Nanchang, 330032, China; Key Laboratory for Genetic Improvement of Indigenous Chicken Breeds of Jiangxi Province, Nanchang, 330032, China.
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31
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Yang Y, Yan J, Fan X, Chen J, Wang Z, Liu X, Yi G, Liu Y, Niu Y, Zhang L, Wang L, Li S, Li K, Tang Z. The genome variation and developmental transcriptome maps reveal genetic differentiation of skeletal muscle in pigs. PLoS Genet 2021; 17:e1009910. [PMID: 34780471 PMCID: PMC8629385 DOI: 10.1371/journal.pgen.1009910] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2021] [Revised: 11/29/2021] [Accepted: 10/25/2021] [Indexed: 12/13/2022] Open
Abstract
Natural and artificial directional selections have resulted in significantly genetic and phenotypic differences across breeds in domestic animals. However, the molecular regulation of skeletal muscle diversity remains largely unknown. Here, we conducted transcriptome profiling of skeletal muscle across 27 time points, and performed whole-genome re-sequencing in Landrace (lean-type) and Tongcheng (obese-type) pigs. The transcription activity decreased with development, and the high-resolution transcriptome precisely captured the characterizations of skeletal muscle with distinct biological events in four developmental phases: Embryonic, Fetal, Neonatal, and Adult. A divergence in the developmental timing and asynchronous development between the two breeds was observed; Landrace showed a developmental lag and stronger abilities of myoblast proliferation and cell migration, whereas Tongcheng had higher ATP synthase activity in postnatal periods. The miR-24-3p driven network targeting insulin signaling pathway regulated glucose metabolism. Notably, integrated analysis suggested SATB2 and XLOC_036765 contributed to skeletal muscle diversity via regulating the myoblast migration and proliferation, respectively. Overall, our results provide insights into the molecular regulation of skeletal muscle development and diversity in mammals.
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Affiliation(s)
- Yalan Yang
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
- Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
- Kunpeng Institute of Modern Agriculture at Foshan, Foshan, China
| | - Junyu Yan
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
- Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Xinhao Fan
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
- Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Jiaxing Chen
- Department of Computer Science, City University of Hong Kong, Kowloon, Hong Kong, China
| | - Zishuai Wang
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
- Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
- Department of Computer Science, City University of Hong Kong, Kowloon, Hong Kong, China
| | - Xiaoqin Liu
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
- Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Guoqiang Yi
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
- Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
- Kunpeng Institute of Modern Agriculture at Foshan, Foshan, China
- Guangxi Engineering Centre for Resource Development of Bama Xiang Pig, Bama, China
| | - Yuwen Liu
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
- Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
- Kunpeng Institute of Modern Agriculture at Foshan, Foshan, China
| | | | - Longchao Zhang
- Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Lixian Wang
- Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - ShuaiCheng Li
- Department of Computer Science, City University of Hong Kong, Kowloon, Hong Kong, China
- * E-mail: (SCL); (KL); (ZLT)
| | - Kui Li
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
- Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
- Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
- Research Centre of Animal Nutritional Genomics, State Key Laboratory of Animal Nutrition, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Shenzhen, China
- * E-mail: (SCL); (KL); (ZLT)
| | - Zhonglin Tang
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
- Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
- Kunpeng Institute of Modern Agriculture at Foshan, Foshan, China
- Guangxi Engineering Centre for Resource Development of Bama Xiang Pig, Bama, China
- Research Centre of Animal Nutritional Genomics, State Key Laboratory of Animal Nutrition, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Shenzhen, China
- * E-mail: (SCL); (KL); (ZLT)
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Liu X, Zhang J, Xiong X, Chen C, Xing Y, Duan Y, Xiao S, Yang B, Ma J. An Integrative Analysis of Transcriptome and GWAS Data to Identify Potential Candidate Genes Influencing Meat Quality Traits in Pigs. Front Genet 2021; 12:748070. [PMID: 34745221 PMCID: PMC8567094 DOI: 10.3389/fgene.2021.748070] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Accepted: 09/27/2021] [Indexed: 11/13/2022] Open
Abstract
Understanding the genetic factors behind meat quality traits is of great significance to animal breeding and production. We previously conducted a genome-wide association study (GWAS) for meat quality traits in a White Duroc × Erhualian F2 pig population using Illumina porcine 60K SNP data. Here, we further investigate the functional candidate genes and their network modules associated with meat quality traits by integrating transcriptomics and GWAS information. Quantitative trait transcript (QTT) analysis, gene expression QTL (eQTL) mapping, and weighted gene co-expression network analysis (WGCNA) were performed using the digital gene expression (DGE) data from 493 F2 pig's muscle and liver samples. Among the quantified 20,108 liver and 23,728 muscle transcripts, 535 liver and 1,014 muscle QTTs corresponding to 416 and 721 genes, respectively, were found to be significantly (p < 5 × 10-4) correlated with 22 meat quality traits measured on longissiums dorsi muscle (LM) or semimembranosus muscle (SM). Transcripts associated with muscle glycolytic potential (GP) and pH values were enriched for genes involved in metabolic process. There were 42 QTTs (for 32 genes) shared by liver and muscle tissues, of which 10 QTTs represent GP- and/or pH-related genes, such as JUNB, ATF3, and PPP1R3B. Furthermore, a genome-wide eQTL mapping revealed a total of 3,054 eQTLs for all annotated transcripts in muscle (p < 2.08 × 10-5), including 1,283 cis-eQTLs and 1771 trans-eQTLs. In addition, WGCNA identified five modules relevant to glycogen metabolism pathway and highlighted the connections between variations in meat quality traits and genes involved in energy process. Integrative analysis of GWAS loci, eQTL, and QTT demonstrated GALNT15/GALNTL2 and HTATIP2 as strong candidate genes for drip loss and pH drop from postmortem 45 min to 24 h, respectively. Our findings provide valuable insights into the genetic basis of meat quality traits and greatly expand the number of candidate genes that may be valuable for future functional analysis and genetic improvement of meat quality.
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Affiliation(s)
- Xianxian Liu
- State Key Laboratory of Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, China
| | - Junjie Zhang
- State Key Laboratory of Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, China
| | - Xinwei Xiong
- State Key Laboratory of Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, China
| | - Congying Chen
- State Key Laboratory of Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, China
| | - Yuyun Xing
- State Key Laboratory of Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, China
| | - Yanyu Duan
- State Key Laboratory of Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, China
| | - Shijun Xiao
- State Key Laboratory of Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, China
| | - Bin Yang
- State Key Laboratory of Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, China
| | - Junwu Ma
- State Key Laboratory of Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, China
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Liu Y, Long H, Feng S, Ma T, Wang M, Niu L, Zhang X, Wang L, Lei Y, Chen Y, Wang Q, Xu X. Trait correlated expression combined with eQTL and ASE analyses identified novel candidate genes affecting intramuscular fat. BMC Genomics 2021; 22:805. [PMID: 34749647 PMCID: PMC8577010 DOI: 10.1186/s12864-021-08141-9] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2021] [Accepted: 10/29/2021] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Intramuscular fat (IMF) content is a determining factor for meat taste. The Luchuan pig is a fat-type local breed in southern China that is famous for its desirable meat quality due to high IMF, however, the crossbred offspring of Luchuan sows and Duroc boars displayed within-population variation on meat quality, and the reason remains unknown. RESULTS In the present study, we identified 212 IMF-correlated genes (FDR ≤ 0.01) using correlation analysis between gene expression level and the value of IMF content. The IMF-correlated genes were significantly enriched in the processes of lipid metabolism and mitochondrial energy metabolism, as well as the AMPK/PPAR signaling pathway. From the IMF-correlated genes, we identified 99 genes associated with expression quantitative trait locus (eQTL) or allele-specific expression (ASE) signals, including 21 genes identified by both cis-eQTL and ASE analyses and 12 genes identified by trans-eQTL analysis. Genome-wide association study (GWAS) of IMF identified a significant QTL on SSC14 (p-value = 2.51E-7), and the nearest IMF-correlated gene SFXN4 (r = 0.28, FDR = 4.00E-4) was proposed as the candidate gene. Furthermore, we highlighted another three novel IMF candidate genes, namely AGT, EMG1, and PCTP, by integrated analysis of GWAS, eQTL, and IMF-gene correlation analysis. CONCLUSIONS The AMPK/PPAR signaling pathway together with the processes of lipid and mitochondrial energy metabolism plays a vital role in regulating porcine IMF content. Trait correlated expression combined with eQTL and ASE analysis highlighted a priority list of genes, which compensated for the shortcoming of GWAS, thereby accelerating the mining of causal genes of IMF.
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Affiliation(s)
- Yan Liu
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070, China.,The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070, China.,Key Lab of Swine Genetics and Breeding of Ministry of Agriculture and Rural Affairs, Wuhan, 430070, China
| | - Huan Long
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070, China.,The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070, China
| | - Simin Feng
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070, China.,The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070, China
| | - Tingting Ma
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070, China.,The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070, China
| | - Mufeng Wang
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070, China.,The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070, China
| | - Lizhu Niu
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070, China.,The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070, China
| | - Xinyi Zhang
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070, China.,The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070, China
| | - Lianni Wang
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070, China.,The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070, China
| | - Yu Lei
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070, China.,The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070, China
| | - Yilong Chen
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070, China.,The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070, China
| | - Qiankun Wang
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070, China.,The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070, China
| | - Xuewen Xu
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070, China. .,The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070, China. .,Key Lab of Swine Genetics and Breeding of Ministry of Agriculture and Rural Affairs, Wuhan, 430070, China.
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Johnsson M, Jungnickel MK. Evidence for and localization of proposed causative variants in cattle and pig genomes. Genet Sel Evol 2021; 53:67. [PMID: 34461824 PMCID: PMC8404348 DOI: 10.1186/s12711-021-00662-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2021] [Accepted: 08/20/2021] [Indexed: 12/18/2022] Open
Abstract
BACKGROUND This paper reviews the localization of published potential causative variants in contemporary pig and cattle reference genomes, and the evidence for their causality. In spite of the difficulties inherent to the identification of causative variants from genetic mapping and genome-wide association studies, researchers in animal genetics have proposed putative causative variants for several traits relevant to livestock breeding. RESULTS For this review, we read the literature that supports potential causative variants in 13 genes (ABCG2, DGAT1, GHR, IGF2, MC4R, MSTN, NR6A1, PHGK1, PRKAG3, PLRL, RYR1, SYNGR2 and VRTN) in cattle and pigs, and localized them in contemporary reference genomes. We review the evidence for their causality, by aiming to separate the evidence for the locus, the proposed causative gene and the proposed causative variant, and report the bioinformatic searches and tactics needed to localize the sequence variants in the cattle or pig genome. CONCLUSIONS Taken together, there is usually good evidence for the association at the locus level, some evidence for a specific causative gene at eight of the loci, and some experimental evidence for a specific causative variant at six of the loci. We recommend that researchers who report new potential causative variants use referenced coordinate systems, show local sequence context, and submit variants to repositories.
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Affiliation(s)
- Martin Johnsson
- Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Box 7023, 750 07 Uppsala, Sweden
| | - Melissa K. Jungnickel
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Midlothian, EH25 9RG Scotland, UK
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Yan G, Liu X, Xiao S, Xin W, Xu W, Li Y, Huang T, Qin J, Xie L, Ma J, Zhang Z, Huang L. An imputed whole-genome sequence-based GWAS approach pinpoints causal mutations for complex traits in a specific swine population. SCIENCE CHINA-LIFE SCIENCES 2021; 65:781-794. [PMID: 34387836 DOI: 10.1007/s11427-020-1960-9] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/17/2021] [Accepted: 05/19/2021] [Indexed: 01/08/2023]
Abstract
Sequencing-based genome-wide association studies (GWAS) have facilitated the identification of causal associations between genetic variants and traits in diverse species. However, it is cost-prohibitive for the majority of research groups to sequence a large number of samples. Here, we carried out genotype imputation to increase the density of single nucleotide polymorphisms in a large-scale Swine F2 population using a reference panel including 117 individuals, followed by a series of GWAS analyses. The imputation accuracies reached 0.89 and 0.86 for allelic concordance and correlation, respectively. A quantitative trait nucleotide (QTN) affecting the chest vertebrate was detected directly, while the investigation of another QTN affecting the residual glucose failed due to the presence of similar haplotypes carrying wild-type and mutant allelesin the reference panel used in this study. A high imputation accuracy was confirmed by Sanger sequencing technology for the most significant loci. Two candidate genes, CPNE5 and MYH3, affecting meat-related traits were proposed. Collectively, we illustrated four scenarios in imputation-based GWAS that may be encountered by researchers, and our results will provide an extensive reference for future genotype imputation-based GWAS analyses in the future.
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Affiliation(s)
- Guorong Yan
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China
- Institute of Photomedicine, Shanghai Skin Disease Hospital, School of Medicine, Tongji University, Shanghai, 200092, China
| | - Xianxian Liu
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China
| | - Shijun Xiao
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China
| | - Wenshui Xin
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China
| | - Wenwu Xu
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China
| | - Yiping Li
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China
| | - Tao Huang
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China
| | - Jiangtao Qin
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China
| | - Lei Xie
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China
| | - Junwu Ma
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China.
| | - Zhiyan Zhang
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China.
| | - Lusheng Huang
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China
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36
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Ding R, Qiu Y, Zhuang Z, Ruan D, Wu J, Zhou S, Ye J, Cao L, Hong L, Xu Z, Zheng E, Li Z, Wu Z, Yang J. Genome-wide association studies reveals polygenic genetic architecture of litter traits in Duroc pigs. Theriogenology 2021; 173:269-278. [PMID: 34403972 DOI: 10.1016/j.theriogenology.2021.08.012] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Revised: 08/08/2021] [Accepted: 08/09/2021] [Indexed: 01/02/2023]
Abstract
With continuous improvement of sow litter size, breeders are gradually paying more attention to the quality of litter traits that directly impact the production efficiency of pig companies, such as the rate of piglets born alive (RBA) and the rate of healthy births (RHB). The objectives of this study are to dissect the genetic basis of litter traits in pig and to identify valuable genes and genetic markers, especially pleiotropic, for pig breeding. Herein, 1140 Duroc pigs and 2046 reproduction records, 5 litter traits, including the number of healthy births (NHB), number of deformed fetuses (NDF), number of stillborn (NSB), RBA, and RHB, were used in this study. Subsequently, a genome-wide association study (GWAS) was performed for the five litter traits in the first two parities from two Duroc populations. A total of 76 significantly related SNPs and 10 potential candidate genes (CAV1, DAB2, FGF12, FHOD3, DYNC2H1, GRHL1, TCTN3, PYROXD2, MMP8, MMP13, and PGR) were detected, including 13 pleiotropic SNPs that affected more than one litter trait. Finally, the functional enrichment analysis of functional genes that were closest to these significant SNPs indicated that most of the significant pathways were associated with hormone secretion and embryo and organ development. This study advances our understanding of the genetic mechanisms of litter traits, especially the survival rate of piglets born, and provides an opportunity to increase the quality of litter using marker-assisted selection or genomic selection in pigs.
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Affiliation(s)
- Rongrong Ding
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, 510642, PR China; Guangdong Wens Breeding Swine Technology Co., Ltd., Guangdong, 527400, PR China
| | - Yibin Qiu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, 510642, PR China
| | - Zhanwei Zhuang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, 510642, PR China
| | - Donglin Ruan
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, 510642, PR China
| | - Jie Wu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, 510642, PR China
| | - Shenping Zhou
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, 510642, PR China
| | - Jian Ye
- Guangdong Wens Breeding Swine Technology Co., Ltd., Guangdong, 527400, PR China
| | - Lu Cao
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, 510642, PR China
| | - Linjun Hong
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, 510642, PR China
| | - Zheng Xu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, 510642, PR China
| | - Enqin Zheng
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, 510642, PR China; Lingnan Guangdong Laboratory of Modern Agriculture, Guangzhou, 510642, PR China
| | - Zicong Li
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, 510642, PR China; Lingnan Guangdong Laboratory of Modern Agriculture, Guangzhou, 510642, PR China
| | - Zhenfang Wu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, 510642, PR China; Guangdong Wens Breeding Swine Technology Co., Ltd., Guangdong, 527400, PR China; Lingnan Guangdong Laboratory of Modern Agriculture, Guangzhou, 510642, PR China.
| | - Jie Yang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, 510642, PR China; Lingnan Guangdong Laboratory of Modern Agriculture, Guangzhou, 510642, PR China.
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Liu X, Liu L, Wang J, Cui H, Zhao G, Wen J. FOSL2 Is Involved in the Regulation of Glycogen Content in Chicken Breast Muscle Tissue. Front Physiol 2021; 12:682441. [PMID: 34295261 PMCID: PMC8290175 DOI: 10.3389/fphys.2021.682441] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2021] [Accepted: 05/03/2021] [Indexed: 01/22/2023] Open
Abstract
The glycogen content in muscle of livestock and poultry animals affects the homeostasis of their body, growth performance, and meat quality after slaughter. FOS-like 2, AP-1 transcription factor subunit (FOSL2) was identified as a candidate gene related to muscle glycogen (MG) content in chicken in our previous study, but the role of FOSL2 in the regulation of MG content remains to be elucidated. Differential gene expression analysis and weighted gene coexpression network analysis (WGCNA) were performed on differentially expressed genes (DEGs) in breast muscle tissues from the high-MG-content (HMG) group and low-MG-content (LMG) group of Jingxing yellow chickens. Analysis of the 1,171 DEGs (LMG vs. HMG) identified, besides FOSL2, some additional genes related to MG metabolism pathway, namely PRKAG3, CEBPB, FOXO1, AMPK, and PIK3CB. Additionally, WGCNA revealed that FOSL2, CEBPB, MAP3K14, SLC2A14, PPP2CA, SLC38A2, PPP2R5E, and other genes related to the classical glycogen metabolism in the same coexpressed module are associated with MG content. Also, besides finding that FOSL2 expression is negatively correlated with MG content, a possible interaction between FOSL2 and CEBPB was predicted using the STRING (Search Tool for the Retrieval of Interacting Genes) database. Furthermore, we investigated the effects of lentiviral overexpression of FOSL2 on the regulation of the glycogen content in vitro, and the result indicated that FOSL2 decreases the glycogen content in DF1 cells. Collectively, our results confirm that FOSL2 has a key role in the regulation of the MG content in chicken. This finding is helpful to understand the mechanism of MG metabolism regulation in chicken and provides a new perspective for the production of high-quality broiler and the development of a comprehensive nutritional control strategy.
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Affiliation(s)
- Xiaojing Liu
- State Key Laboratory of Animal Nutrition, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Lu Liu
- College of Animal Science and Technology, College of Veterinary Medicine of Zhejiang A&F University, Hangzhou, China
| | - Jie Wang
- State Key Laboratory of Animal Nutrition, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Huanxian Cui
- State Key Laboratory of Animal Nutrition, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Guiping Zhao
- State Key Laboratory of Animal Nutrition, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Jie Wen
- State Key Laboratory of Animal Nutrition, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
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38
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Accelerated discovery of functional genomic variation in pigs. Genomics 2021; 113:2229-2239. [PMID: 34022350 DOI: 10.1016/j.ygeno.2021.05.017] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2020] [Revised: 03/30/2021] [Accepted: 05/17/2021] [Indexed: 11/21/2022]
Abstract
The genotype-phenotype link is a major research topic in the life sciences but remains highly complex to disentangle. Part of the complexity arises from the number of genes contributing to the observed phenotype. Despite the vast increase of molecular data, pinpointing the causal variant underlying a phenotype of interest is still challenging. In this study, we present an approach to map causal variation and molecular pathways underlying important phenotypes in pigs. We prioritize variation by utilizing and integrating predicted variant impact scores (pCADD), functional genomic information, and associated phenotypes in other mammalian species. We demonstrate the efficacy of our approach by reporting known and novel causal variants, of which many affect non-coding sequences. Our approach allows the disentangling of the biology behind important phenotypes by accelerating the discovery of novel causal variants and molecular mechanisms affecting important phenotypes in pigs. This information on molecular mechanisms could be applicable in other mammalian species, including humans.
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39
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Gao G, Gao N, Li S, Kuang W, Zhu L, Jiang W, Yu W, Guo J, Li Z, Yang C, Zhao Y. Genome-Wide Association Study of Meat Quality Traits in a Three-Way Crossbred Commercial Pig Population. Front Genet 2021; 12:614087. [PMID: 33815461 PMCID: PMC8010252 DOI: 10.3389/fgene.2021.614087] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2020] [Accepted: 02/12/2021] [Indexed: 01/12/2023] Open
Abstract
Meat quality is an important trait for pig-breeding programs aiming to meet consumers' demands. Geneticists must improve meat quality based on their understanding of the underlying genetic mechanisms. Previous studies showed that most meat-quality indicators were low-to-moderate heritability traits; therefore, improving meat quality using conventional techniques remains a challenge. Here, we performed a genome-wide association study of meat-quality traits using the GeneSeek Porcine SNP50K BeadChip in 582 crossbred Duroc × (Landrace × Yorkshire) commercial pigs (249 males and 333 females). Meat conductivity, marbling score, moisture, meat color, pH, and intramuscular fat (IMF) content were investigated. The genome-wide association study was performed using both fixed and random model Circulating Probability Unification (FarmCPU) and a mixed linear model (MLM) with the rMVP software. The genomic heritability of the studied traits ranged from 0.13 ± 0.07 to 0.55 ± 0.08 for conductivity and meat color, respectively. Thirty-two single-nucleotide polymorphisms (SNPs) were identified for meat quality in the crossbred pigs using both FarmCPU and MLM. Among the detected SNPs, five, nine, seven, four, six, and five were significantly associated with conductivity, IMF, marbling score, meat color, moisture, and pH, respectively. Several candidate genes for meat quality were identified in the detected genomic regions. These findings will contribute to the ongoing improvement of meat quality, meeting consumer demands and improving the economic outlook for the swine industry.
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Affiliation(s)
- Guangxiong Gao
- School of Life Sciences and Engineering, Foshan University, Foshan, China
| | - Ning Gao
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou, China
- Guangxi Yangxiang Co., Ltd., Guigang, China
| | - Sicheng Li
- Guangxi Yangxiang Co., Ltd., Guigang, China
| | - Weijian Kuang
- School of Life Sciences and Engineering, Foshan University, Foshan, China
| | - Lin Zhu
- Guangxi Yangxiang Co., Ltd., Guigang, China
| | - Wei Jiang
- Guangxi Yangxiang Co., Ltd., Guigang, China
| | - Weiwei Yu
- School of Life Sciences and Engineering, Foshan University, Foshan, China
| | - Jinbiao Guo
- School of Life Sciences and Engineering, Foshan University, Foshan, China
| | - Zhili Li
- School of Life Sciences and Engineering, Foshan University, Foshan, China
| | - Chengzhong Yang
- School of Life Sciences and Engineering, Foshan University, Foshan, China
| | - Yunxiang Zhao
- School of Life Sciences and Engineering, Foshan University, Foshan, China
- Guangxi Yangxiang Co., Ltd., Guigang, China
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40
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Liu X, Lai H, Xin S, Li Z, Zeng X, Nie L, Liang Z, Wu M, Zheng J, Zou Y. Whole-exome sequencing identifies novel mutations in ABC transporter genes associated with intrahepatic cholestasis of pregnancy disease: a case-control study. BMC Pregnancy Childbirth 2021; 21:110. [PMID: 33546617 PMCID: PMC7866704 DOI: 10.1186/s12884-021-03595-x] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2020] [Accepted: 01/27/2021] [Indexed: 01/03/2023] Open
Abstract
Background Intrahepatic cholestasis of pregnancy (ICP) can cause premature delivery and stillbirth. Previous studies have reported that mutations in ABC transporter genes strongly influence the transport of bile salts. However, to date, their effects are still largely elusive. Methods A whole-exome sequencing (WES) approach was used to detect novel variants. Rare novel exonic variants (minor allele frequencies: MAF < 1%) were analyzed. Three web-available tools, namely, SIFT, Mutation Taster and FATHMM, were used to predict protein damage. Protein structure modeling and comparisons between reference and modified protein structures were performed by SWISS-MODEL and Chimera 1.14rc, respectively. Results We detected a total of 2953 mutations in 44 ABC family transporter genes. When the MAF of loci was controlled in all databases at less than 0.01, 320 mutations were reserved for further analysis. Among these mutations, 42 were novel. We classified these loci into four groups (the damaging, probably damaging, possibly damaging, and neutral groups) according to the prediction results, of which 7 novel possible pathogenic mutations were identified that were located in known functional genes, including ABCB4 (Trp708Ter, Gly527Glu and Lys386Glu), ABCB11 (Gln1194Ter, Gln605Pro and Leu589Met) and ABCC2 (Ser1342Tyr), in the damaging group. New mutations in the first two genes were reported in our recent article. In addition, compared to the wild-type protein structure, the ABCC2 Ser1342Tyr-modified protein structure showed a slight change in the chemical bond lengths of ATP ligand-binding amino acid side chains. In placental tissue, the expression level of the ABCC2 gene in patients with ICP was significantly higher (P < 0.05) than that in healthy pregnant women. In particular, the patients with two mutations in ABC family genes had higher average values of total bile acids (TBA), aspartate transaminase (AST), direct bilirubin (DBIL), total cholesterol (CHOL), triglycerides (TG) and high-density lipoprotein (HDL) than the patients who had one mutation, no mutation in ABC genes and local controls. Conclusions Our present study provide new insight into the genetic architecture of ICP and will benefit the final identification of the underlying mutations. Supplementary Information The online version contains supplementary material available at 10.1186/s12884-021-03595-x.
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Affiliation(s)
- Xianxian Liu
- Key Laboratory of Women's Reproductive Health of Jiangxi Province, Jiangxi Provincial Maternal and Child Health Hospital, Nanchang, 330006, Jiangxi, China.,Central Lab, Jiangxi Provincial Maternal and Child Health Hospital, Nanchang, 330006, Jiangxi, China
| | - Hua Lai
- Key Laboratory of Women's Reproductive Health of Jiangxi Province, Jiangxi Provincial Maternal and Child Health Hospital, Nanchang, 330006, Jiangxi, China.,Department of Obstetrics, Jiangxi Provincial Maternal and Child Health Hospital, Nanchang, 330006, Jiangxi, China
| | - Siming Xin
- Key Laboratory of Women's Reproductive Health of Jiangxi Province, Jiangxi Provincial Maternal and Child Health Hospital, Nanchang, 330006, Jiangxi, China.,Department of Obstetrics, Jiangxi Provincial Maternal and Child Health Hospital, Nanchang, 330006, Jiangxi, China
| | - Zengming Li
- Key Laboratory of Women's Reproductive Health of Jiangxi Province, Jiangxi Provincial Maternal and Child Health Hospital, Nanchang, 330006, Jiangxi, China
| | - Xiaoming Zeng
- Key Laboratory of Women's Reproductive Health of Jiangxi Province, Jiangxi Provincial Maternal and Child Health Hospital, Nanchang, 330006, Jiangxi, China.,Department of Obstetrics, Jiangxi Provincial Maternal and Child Health Hospital, Nanchang, 330006, Jiangxi, China
| | - Liju Nie
- Key Laboratory of Women's Reproductive Health of Jiangxi Province, Jiangxi Provincial Maternal and Child Health Hospital, Nanchang, 330006, Jiangxi, China.,Department of Obstetrics, Jiangxi Provincial Maternal and Child Health Hospital, Nanchang, 330006, Jiangxi, China
| | - Zhengyi Liang
- Key Laboratory of Women's Reproductive Health of Jiangxi Province, Jiangxi Provincial Maternal and Child Health Hospital, Nanchang, 330006, Jiangxi, China.,Department of Obstetrics, Jiangxi Provincial Maternal and Child Health Hospital, Nanchang, 330006, Jiangxi, China
| | - Meiling Wu
- Key Laboratory of Women's Reproductive Health of Jiangxi Province, Jiangxi Provincial Maternal and Child Health Hospital, Nanchang, 330006, Jiangxi, China.,Department of Obstetrics, Jiangxi Provincial Maternal and Child Health Hospital, Nanchang, 330006, Jiangxi, China
| | - Jiusheng Zheng
- Key Laboratory of Women's Reproductive Health of Jiangxi Province, Jiangxi Provincial Maternal and Child Health Hospital, Nanchang, 330006, Jiangxi, China. .,Department of Obstetrics, Jiangxi Provincial Maternal and Child Health Hospital, Nanchang, 330006, Jiangxi, China.
| | - Yang Zou
- Key Laboratory of Women's Reproductive Health of Jiangxi Province, Jiangxi Provincial Maternal and Child Health Hospital, Nanchang, 330006, Jiangxi, China. .,Central Lab, Jiangxi Provincial Maternal and Child Health Hospital, Nanchang, 330006, Jiangxi, China.
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Liu Y, Liu X, Zheng Z, Ma T, Liu Y, Long H, Cheng H, Fang M, Gong J, Li X, Zhao S, Xu X. Genome-wide analysis of expression QTL (eQTL) and allele-specific expression (ASE) in pig muscle identifies candidate genes for meat quality traits. Genet Sel Evol 2020; 52:59. [PMID: 33036552 PMCID: PMC7547458 DOI: 10.1186/s12711-020-00579-x] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2019] [Accepted: 09/28/2020] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND Genetic analysis of gene expression level is a promising approach for characterizing candidate genes that are involved in complex economic traits such as meat quality. In the present study, we conducted expression quantitative trait loci (eQTL) and allele-specific expression (ASE) analyses based on RNA-sequencing (RNAseq) data from the longissimus muscle of 189 Duroc × Luchuan crossed pigs in order to identify some candidate genes for meat quality traits. RESULTS Using a genome-wide association study based on a mixed linear model, we identified 7192 cis-eQTL corresponding to 2098 cis-genes (p ≤ 1.33e-3, FDR ≤ 0.05) and 6400 trans-eQTL corresponding to 863 trans-genes (p ≤ 1.13e-6, FDR ≤ 0.05). ASE analysis using RNAseq SNPs identified 9815 significant ASE-SNPs in 2253 unique genes. Integrative analysis between the cis-eQTL and ASE target genes identified 540 common genes, including 33 genes with expression levels that were correlated with at least one meat quality trait. Among these 540 common genes, 63 have been reported previously as candidate genes for meat quality traits, such as PHKG1 (q-value = 1.67e-6 for the leading SNP in the cis-eQTL analysis), NUDT7 (q-value = 5.67e-13), FADS2 (q-value = 8.44e-5), and DGAT2 (q-value = 1.24e-3). CONCLUSIONS The present study confirmed several previously published candidate genes and identified some novel candidate genes for meat quality traits via eQTL and ASE analyses, which will be useful to prioritize candidate genes in further studies.
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Affiliation(s)
- Yan Liu
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070 China
- The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070 China
- Key Lab of Swine Genetics and Breeding of Ministry of Agriculture and Rural Affairs, Wuhan, 430070 China
| | - Xiaolei Liu
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070 China
- The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070 China
- Key Lab of Swine Genetics and Breeding of Ministry of Agriculture and Rural Affairs, Wuhan, 430070 China
| | - Zhiwei Zheng
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070 China
- The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070 China
- Key Lab of Swine Genetics and Breeding of Ministry of Agriculture and Rural Affairs, Wuhan, 430070 China
| | - Tingting Ma
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070 China
- The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070 China
- Key Lab of Swine Genetics and Breeding of Ministry of Agriculture and Rural Affairs, Wuhan, 430070 China
| | - Ying Liu
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070 China
- The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070 China
- Key Lab of Swine Genetics and Breeding of Ministry of Agriculture and Rural Affairs, Wuhan, 430070 China
| | - Huan Long
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070 China
- The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070 China
- Key Lab of Swine Genetics and Breeding of Ministry of Agriculture and Rural Affairs, Wuhan, 430070 China
| | - Huijun Cheng
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070 China
- The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070 China
- Key Lab of Swine Genetics and Breeding of Ministry of Agriculture and Rural Affairs, Wuhan, 430070 China
| | - Ming Fang
- Key Laboratory of Healthy Mariculture for the East China Sea, Ministry of Agriculture and Rural Affairs, Fisheries College, Jimei University, Xiamen, 361021 China
| | - Jing Gong
- Colleges of Informatics, Huazhong Agricultural University, Wuhan, 430070 China
| | - Xinyun Li
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070 China
- The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070 China
- Key Lab of Swine Genetics and Breeding of Ministry of Agriculture and Rural Affairs, Wuhan, 430070 China
| | - Shuhong Zhao
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070 China
- The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070 China
- Key Lab of Swine Genetics and Breeding of Ministry of Agriculture and Rural Affairs, Wuhan, 430070 China
| | - Xuewen Xu
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070 China
- The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070 China
- Key Lab of Swine Genetics and Breeding of Ministry of Agriculture and Rural Affairs, Wuhan, 430070 China
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Zhao X, Wang C, Wang Y, Zhou L, Hu H, Bai L, Wang J. Weighted gene co-expression network analysis reveals potential candidate genes affecting drip loss in pork. Anim Genet 2020; 51:855-865. [PMID: 32986257 DOI: 10.1111/age.13006] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/03/2020] [Indexed: 01/26/2023]
Abstract
Drip loss is an essential evaluation indicator for pork quality. It is closely related to other meat quality indicators, including water-holding capacity, water loss rate and pH value at 45 min (pH1 ) and 24 h post-mortem (pH2 ), and is influenced by environmental and genetic factors and their interactions. We previously conducted differentially expressed gene analysis to identify candidate genes affecting drip loss using eight individuals with extremely high- and low-drip loss selected from 28 purebred Duroc pigs. Using 28 identical samples, in the present study, we performed weighted gene co-expression network analysis with drip loss and drip loss-related traits, including water-holding capacity, water loss rate, pH1 and pH2 . A total of 25 modules were identified, and five of them correlated with at least two drip loss or drip loss-related traits. After functional enrichment analysis of genes in the five modules, three modules were found to be critical, as their genes were significantly involved in amino acid metabolism, immune response and apoptosis, which have potential relationships with drip loss. Furthermore, we identified five candidate genes affecting drip loss in one critical module, AASS, BCKDHB, ALDH6A1, MUT and MCCC1, as they overlapped with differentially expressed genes detected in our previous study, exhibited protein-protein interactions and had potential biological functions in affecting drip loss according to the literature. The outcomes of the present study enhance our understanding of the molecular mechanisms underlying drip loss and will aid in improving the pork quality.
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Affiliation(s)
- X Zhao
- Shandong Provincial Key Laboratory of Animal Disease Control and Breeding, Institute of Animal Science and Veterinary Medicine, Shandong Academy of Agricultural Sciences, Jinan, Shandong Province, 250100, China
| | - C Wang
- Shandong Provincial Key Laboratory of Animal Disease Control and Breeding, Institute of Animal Science and Veterinary Medicine, Shandong Academy of Agricultural Sciences, Jinan, Shandong Province, 250100, China
| | - Y Wang
- Shandong Provincial Key Laboratory of Animal Disease Control and Breeding, Institute of Animal Science and Veterinary Medicine, Shandong Academy of Agricultural Sciences, Jinan, Shandong Province, 250100, China
| | - L Zhou
- College of Animal Science and Technology, Qingdao Agricultural University, Qingdao, Shandong Province, 266109, China
| | - H Hu
- Shandong Provincial Key Laboratory of Animal Disease Control and Breeding, Institute of Animal Science and Veterinary Medicine, Shandong Academy of Agricultural Sciences, Jinan, Shandong Province, 250100, China
| | - L Bai
- Shandong Provincial Key Laboratory of Animal Disease Control and Breeding, Institute of Animal Science and Veterinary Medicine, Shandong Academy of Agricultural Sciences, Jinan, Shandong Province, 250100, China
| | - J Wang
- Shandong Provincial Key Laboratory of Animal Disease Control and Breeding, Institute of Animal Science and Veterinary Medicine, Shandong Academy of Agricultural Sciences, Jinan, Shandong Province, 250100, China
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Genome-wide association analysis reveals the genetic locus for high reproduction trait in Chinese Arbas Cashmere goat. Genes Genomics 2020; 42:893-899. [PMID: 32506265 DOI: 10.1007/s13258-020-00937-5] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2019] [Accepted: 04/24/2020] [Indexed: 02/07/2023]
Abstract
BACKGROUND Litter size is the most important reproductive trait which plays a crucial role in goat production. Therefore, improvement of litter size trait has been of increasing interest in goat industry as small improvement in litter size may lead to large profit. The recent Cashmere goat breeding program produced a high-reproductive genetic line of Arbas Cashmere goat. But the genetic mechanism of high reproduction rate remains largely unknown in this Chinese native goat breed. To address this question, we performed a genome-wide association studies (GWAS) using two groups of goats varying in fecundity. OBJECTIVES Our study was aimed to investigate the significant SNPs and genes associated with high reproduction trait in Inner Mongolia Arbas Cashmere Goat. METHODS We used logistic model association to perform GWAS using 47 goats from high fecundity group (~ 190%) and 314 goats from low fecundity group (~ 130%) of the Arbas Cashmere goat breed. RESULTS We identified 66 genomic regions associated with genome wide significant level wherein six loci were found to be associated with reproduction traits. Further analysis showed that five key candidate genes including KISS1, KHDRBS2, WNT10B, SETDB2 and PPP3CA genes are involved in goat fecundity trait. Gene ontology enrichment analysis revealed that several biological pathways could be involved in the variation of fecundity in female goats. CONCLUSIONS The identified significant SNPs or genes provide useful information about the underlying genetic control of fecundity trait which will be helpful to use them in goat breeding programs for improving the reproductive efficiency of goats.
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Liu X, Liu L, Wang J, Cui H, Chu H, Bi H, Zhao G, Wen J. Genome-Wide Association Study of Muscle Glycogen in Jingxing Yellow Chicken. Genes (Basel) 2020; 11:genes11050497. [PMID: 32366026 PMCID: PMC7290304 DOI: 10.3390/genes11050497] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2020] [Revised: 04/14/2020] [Accepted: 04/14/2020] [Indexed: 01/13/2023] Open
Abstract
Glucose metabolism plays an important role in many normal and pathological physiological processes in the body. The breakdown and synthesis of muscle glycogen provides ATP for muscle activities. A genome-wide association study for muscle glycogen was performed in 473 Jingxing yellow chickens to identify significant single nucleotide polymorphisms (SNPs) and insertions and deletions (INDELs) involved in muscle glycogen metabolism. A total of nine SNPs (p < 1/699341) and three INDELs (p < 1/755733) reached a significant level of potential association. The following results were obtained through a series of analyses, including additive effects and gene function annotation. Two significant SNPs were found in introns 12 and 13 of copine 4 (CPNE4) on chromosome 2. The wild-type and mutant individuals had significant differences in glycogen metabolism at two loci (p < 0.01 for both). Individuals carrying two mutations had increased muscle glycogen content. According to the gene annotation of chromosome 11, there is a significant INDEL in intron 6 of naked cuticle homolog 1 (NKD1). After the INDEL mutation, the glycogen content increased significantly. There was a significant difference between wild-type and mutant individuals (p < 0.01). These mutations likely affecting two genes (CPNE4 and NKD1) may affect glycogen storage in a pleiotropic manner. Gene annotation indicates that CPNE4 and NKD1 may affect the process of glucose metabolism. Our findings contribute to understanding the genetic regulation of muscle glycogen metabolism and provide theoretical support.
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Affiliation(s)
- Xiaojing Liu
- State Key Laboratory of Animal Nutrition, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (X.L.); (L.L.); (J.W.); (H.C.); (G.Z.)
| | - Lu Liu
- State Key Laboratory of Animal Nutrition, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (X.L.); (L.L.); (J.W.); (H.C.); (G.Z.)
| | - Jie Wang
- State Key Laboratory of Animal Nutrition, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (X.L.); (L.L.); (J.W.); (H.C.); (G.Z.)
| | - Huanxian Cui
- State Key Laboratory of Animal Nutrition, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (X.L.); (L.L.); (J.W.); (H.C.); (G.Z.)
| | - Huanhuan Chu
- Yantai Dadi Animal Husbrandry Co., Ltd., Yantai 1265100, China; (H.C.); (H.B)
| | - Huijuan Bi
- Yantai Dadi Animal Husbrandry Co., Ltd., Yantai 1265100, China; (H.C.); (H.B)
| | - Guiping Zhao
- State Key Laboratory of Animal Nutrition, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (X.L.); (L.L.); (J.W.); (H.C.); (G.Z.)
| | - Jie Wen
- State Key Laboratory of Animal Nutrition, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (X.L.); (L.L.); (J.W.); (H.C.); (G.Z.)
- Correspondence:
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Liu J, Lei Q, Li F, Zhou Y, Gao J, Liu W, Han H, Cao D. Dynamic Transcriptomic Analysis of Breast Muscle Development From the Embryonic to Post-hatching Periods in Chickens. Front Genet 2020; 10:1308. [PMID: 31998367 PMCID: PMC6967404 DOI: 10.3389/fgene.2019.01308] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2019] [Accepted: 11/27/2019] [Indexed: 11/30/2022] Open
Abstract
Skeletal muscle development and growth are closely associated with efficiency of poultry meat production and its quality. We performed whole transcriptome profiling based on RNA sequencing of breast muscle tissue obtained from Shouguang chickens at embryonic days (E) 12 and 17 to post-hatching days (D) 1, 14, 56, and 98. A total of 9,447 differentially expressed genes (DEGs) were filtered (Q < 0.01, fold change > 2). Time series expression profile clustering analysis identified five significantly different expression profiles that were divided into three clusters. DEGs from cluster I with downregulated pattern were significantly enriched in cell proliferation processes such as cell cycle, mitotic nuclear division, and DNA replication. DEGs from cluster II with upregulated pattern were significantly enriched in metabolic processes such as glycolysis/gluconeogenesis, insulin signaling pathway, calcium signaling pathway, and biosynthesis of amino acids. DEGs from cluster III, with a pattern that increased from E17 to D1 and then decreased from D1 to D14, mainly contributed to lipid metabolism. Therefore, this study may help us explain the mechanisms underlying the phenotype that myofiber hyperplasia occurs predominantly during embryogenesis and hypertrophy occurs mainly after birth at the transcriptional level. Moreover, lipid metabolism may contribute to the early muscle development and growth. These findings add to our knowledge of muscle development in chickens.
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Affiliation(s)
- Jie Liu
- Poultry Institute, Shandong Academy of Agricultural Sciences, Jinan, China
- Poultry Breeding Engineering Technology Center of Shandong Province, Jinan, China
- Shandong Provincial Key Laboratory of Poultry Diseases Diagnosis and Immunology, Jinan, China
| | - Qiuxia Lei
- Poultry Institute, Shandong Academy of Agricultural Sciences, Jinan, China
- Poultry Breeding Engineering Technology Center of Shandong Province, Jinan, China
- Shandong Provincial Key Laboratory of Poultry Diseases Diagnosis and Immunology, Jinan, China
| | - Fuwei Li
- Poultry Institute, Shandong Academy of Agricultural Sciences, Jinan, China
- Poultry Breeding Engineering Technology Center of Shandong Province, Jinan, China
- Shandong Provincial Key Laboratory of Poultry Diseases Diagnosis and Immunology, Jinan, China
| | - Yan Zhou
- Poultry Institute, Shandong Academy of Agricultural Sciences, Jinan, China
- Poultry Breeding Engineering Technology Center of Shandong Province, Jinan, China
- Shandong Provincial Key Laboratory of Poultry Diseases Diagnosis and Immunology, Jinan, China
| | - Jinbo Gao
- Poultry Institute, Shandong Academy of Agricultural Sciences, Jinan, China
- Poultry Breeding Engineering Technology Center of Shandong Province, Jinan, China
- Shandong Provincial Key Laboratory of Poultry Diseases Diagnosis and Immunology, Jinan, China
| | - Wei Liu
- Poultry Institute, Shandong Academy of Agricultural Sciences, Jinan, China
- Poultry Breeding Engineering Technology Center of Shandong Province, Jinan, China
- Shandong Provincial Key Laboratory of Poultry Diseases Diagnosis and Immunology, Jinan, China
| | - Haixia Han
- Poultry Institute, Shandong Academy of Agricultural Sciences, Jinan, China
- Poultry Breeding Engineering Technology Center of Shandong Province, Jinan, China
- Shandong Provincial Key Laboratory of Poultry Diseases Diagnosis and Immunology, Jinan, China
| | - Dingguo Cao
- Poultry Institute, Shandong Academy of Agricultural Sciences, Jinan, China
- Poultry Breeding Engineering Technology Center of Shandong Province, Jinan, China
- Shandong Provincial Key Laboratory of Poultry Diseases Diagnosis and Immunology, Jinan, China
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Zhao X, Wang C, Wang Y, Lin H, Wang H, Hu H, Wang J. Comparative gene expression profiling of muscle reveals potential candidate genes affecting drip loss in pork. BMC Genet 2019; 20:89. [PMID: 31791257 PMCID: PMC6889219 DOI: 10.1186/s12863-019-0794-0] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2019] [Accepted: 11/22/2019] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND Drip loss is a key aspect of meat quality. Transcriptome profiles of muscle with divergent drip loss would offer important insight into the genetic factors responsible for the trait. In this study, drip loss and other meat quality traits of 28 purebred Duroc pigs were measured, muscles of these individuals were RNA sequenced, and eight individuals with extremely low and high drip loss were selected for analyzing their transcriptome differences and identifying potential candidate genes affecting drip loss. RESULTS As a result, 363 differentially expressed (DE) genes were detected in the comparative gene expression analysis, of which 239 were up-regulated and 124 were down-regulated in the low drip loss group. The DE genes were further filtered by correlation analysis between their expression and drip loss values in the 28 Duroc pigs measured and comparison of them with QTLs affecting drip loss. Consequently, of the 363 DE genes, 100 were identified as critical DE genes for drip loss. Functional analysis of these critical DE genes revealed some GO terms (extracellular matrix, cell adhesion mediated by integrin, heterotypic cell-cell adhesion), pathway (ECM-receptor interaction), and new potential candidate genes (TNC, ITGA5, ITGA11, THBS3 and CD44) which played an important role in regulating the variation of drip loss, and deserved to carry further studies to unravel their specific mechanism on drip loss. CONCLUSIONS Our study revealed some GO terms, pathways and potential candidate genes affecting drip loss. It provides crucial information to understand the molecular mechanism of drip loss, and would be of help for improving meat quality of pigs.
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Affiliation(s)
- Xueyan Zhao
- Shandong Provincial Key Laboratory of Animal Disease Control and Breeding, Institute of Animal Science and Veterinary Medicine, Shandong Academy of Agricultural Sciences, Jinan, 250100, China
| | - Cheng Wang
- Shandong Provincial Key Laboratory of Animal Disease Control and Breeding, Institute of Animal Science and Veterinary Medicine, Shandong Academy of Agricultural Sciences, Jinan, 250100, China
| | - Yanping Wang
- Shandong Provincial Key Laboratory of Animal Disease Control and Breeding, Institute of Animal Science and Veterinary Medicine, Shandong Academy of Agricultural Sciences, Jinan, 250100, China
| | - Haichao Lin
- Shandong Provincial Key Laboratory of Animal Disease Control and Breeding, Institute of Animal Science and Veterinary Medicine, Shandong Academy of Agricultural Sciences, Jinan, 250100, China
| | - Huaizhong Wang
- Shandong Provincial Key Laboratory of Animal Disease Control and Breeding, Institute of Animal Science and Veterinary Medicine, Shandong Academy of Agricultural Sciences, Jinan, 250100, China
| | - Hongmei Hu
- Shandong Provincial Key Laboratory of Animal Disease Control and Breeding, Institute of Animal Science and Veterinary Medicine, Shandong Academy of Agricultural Sciences, Jinan, 250100, China
| | - Jiying Wang
- Shandong Provincial Key Laboratory of Animal Disease Control and Breeding, Institute of Animal Science and Veterinary Medicine, Shandong Academy of Agricultural Sciences, Jinan, 250100, China.
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Association of Twelve Candidate Gene Polymorphisms with the Intramuscular Fat Content and Average Backfat Thickness of Chinese Suhuai Pigs. Animals (Basel) 2019; 9:ani9110858. [PMID: 31652864 PMCID: PMC6912197 DOI: 10.3390/ani9110858] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2019] [Revised: 10/18/2019] [Accepted: 10/21/2019] [Indexed: 12/16/2022] Open
Abstract
Simple Summary Appropriate intramuscular fat content (IFC) is the goal of consumers and the direction that breeders must pursue. However, it is difficult to improve the IFC but not average backfat thickness (ABT) by traditional breeding methods, and pigs must be slaughtered to accurately measure IFC. Marker-assisted selection (MAS) provides an economic and efficient method to improve the IFC in pigs. Our research indicated that the FABP3 (rs1110770079) single nucleotide polymorphism (SNP) could be a candidate gene associated with IFC (but not ABT), and IFC could be improved by selecting the individuals with a favorable genotype (GG) of FABP3 (rs1110770079) SNP for pig breeding. Abstract The present study aimed to identify the molecular markers for genes that influence intramuscular fat content (IFC), but not average backfat thickness (ABT). A total of 330 Suhuai pigs were slaughtered, and measurements of IFC and ABT were obtained. Phenotypic and genetic correlations between IFC and ABT were calculated. Thirteen single nucleotide polymorphisms (SNPs) among 12 candidate genes for IFC were analyzed, including FABP3, LIPE, IGF1, IGF2, LEP, LEPR, MC4R, PHKG1, RETN, RYR1, SCD, and UBE3C. Associations of the evaluated SNPs with IFCIFC and ABT were performed. Our results showed that the means of IFC and ABT were 1.99 ± 0.03 % and 26.68 ± 0.28 mm, respectively. The coefficients of variation (CVs) of IFC and ABT were 31.21% and 19.36%, respectively. The phenotypic and genetic correlations between IFC and ABT were moderate. Only the FABP3 (rs1110770079) was associated with IFC (p < 0.05) but not with ABT. Besides, there was a tendency for associations of RYR1 (rs344435545) and SCD (rs80912566) with IFC (p < 0.1). Our results indicated that the FABP3 (rs1110770079) SNP could be used as a marker to improve IFC without changing ABT in the Suhuai pig breeding system.
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A time-dependent genome-wide SNP-SNP interaction analysis of chicken body weight. BMC Genomics 2019; 20:771. [PMID: 31646968 PMCID: PMC6813082 DOI: 10.1186/s12864-019-6132-0] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2019] [Accepted: 09/23/2019] [Indexed: 02/07/2023] Open
Abstract
Background The important property of the quantitative traits of model organisms is time-dependent. However, the methodology for investigating the genetic interaction network over time is still lacking. Our study aims to provide insights into the mechanistic basis of epistatic interactions affecting the phenotypes of model organisms. Results We performed an exhaustive genome-wide search for significant SNP-SNP interactions associated with male birds’ body weight (BW) (n = 475) at multiple time points (day of hatch (BW0) and 1, 3, 5, and 7 weeks (BW1, BW3, BW5, and BW7)). Statistical analysis detected 67, four, and two significant SNP pairs associated with BW0, BW1, and BW3, respectively, with a significance threshold at 8.67 × 10− 12 (Bonferroni-adjusted: 1%). Meanwhile, no significant SNP pairs associated with BW5 and BW7 were found. The SNP-SNP interaction networks of BW0, BW1, and BW3 were built and annotated. Conclusions With strong annotated information and a strict significant threshold, SNP-SNP interactions underpinned the gene-gene interactions that might occur between chromosomes or within the same chromosome. Comparing and combing the networks, the results indicated that the genetic network for chicken body weight was dynamic and time-dependent.
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Wu P, Wang K, Zhou J, Chen D, Yang Q, Yang X, Liu Y, Feng B, Jiang A, Shen L, Xiao W, Jiang Y, Zhu L, Zeng Y, Xu X, Li X, Tang G. GWAS on Imputed Whole-Genome Resequencing From Genotyping-by-Sequencing Data for Farrowing Interval of Different Parities in Pigs. Front Genet 2019; 10:1012. [PMID: 31681435 PMCID: PMC6813215 DOI: 10.3389/fgene.2019.01012] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2019] [Accepted: 09/23/2019] [Indexed: 12/30/2022] Open
Abstract
The whole-genome sequencing (WGS) data can potentially discover all genetic variants. Studies have shown the power of WGS for genome-wide association study (GWAS) lies in the ability to identify quantitative trait loci and nucleotides (QTNs). However, the resequencing of thousands of target individuals is expensive. Genotype imputation is a powerful approach for WGS and to identify causal mutations. This study aimed to evaluate the imputation accuracy from genotyping-by-sequencing (GBS) to WGS in two pig breeds using a resequencing reference population and to detect single-nucleotide polymorphisms (SNPs) and candidate genes for farrowing interval (FI) of different parities using the data before and after imputation for GWAS. Six hundred target pigs, 300 Landrace and 300 Large White pigs, were genotyped by GBS, and 60 reference pigs, 20 Landrace and 40 Large White pigs, were sequenced by whole-genome resequencing. Imputation for pigs was conducted using Beagle software. The average imputation accuracy (allelic R 2) from GBS to WGS was 0.42 for Landrace pigs and 0.45 for Large White pigs. For Landrace pigs (Large White pigs), 4,514,934 (5,533,290) SNPs had an accuracy >0.3, resulting an average accuracy of 0.73 (0.72), and 2,093,778 (2,468,645) SNPs had an accuracy >0.8, resulting an average accuracy of 0.94 (0.93). Association studies with data before and after imputation were performed for FI of different parities in two populations. Before imputation, 18 and 128 significant SNPs were detected for FI in Landrace and Large White pigs, respectively. After imputation, 125 and 27 significant SNPs were identified for dataset with an accuracy >0.3 and 0.8 in Large White pigs, and 113 and 18 SNPs were found among imputed sequence variants. Among these significant SNPs, six top SNPs were detected in both GBS data and imputed WGS data, namely, SSC2: 136127645, SSC5: 103426443, SSC6: 27811226, SSC10: 3609429, SSC14: 15199253, and SSC15: 150297519. Overall, many candidate genes could be involved in FI of different parities in pigs. Although imputation from GBS to WGS data resulted in a low imputation accuracy, association analyses with imputed WGS data were optimized to detect QTNs for complex trait. The obtained results provide new insight into genotype imputation, genetic architecture, and candidate genes for FI of different parities in Landrace and Large White pigs.
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Affiliation(s)
- Pingxian Wu
- Farm Animal Genetic Resources Exploration and Innovation, Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, China
| | - Kai Wang
- Farm Animal Genetic Resources Exploration and Innovation, Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, China
| | - Jie Zhou
- Farm Animal Genetic Resources Exploration and Innovation, Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, China
| | - Dejuan Chen
- Farm Animal Genetic Resources Exploration and Innovation, Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, China
| | - Qiang Yang
- Farm Animal Genetic Resources Exploration and Innovation, Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, China
| | - Xidi Yang
- Farm Animal Genetic Resources Exploration and Innovation, Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, China
| | - Yihui Liu
- Sichuan Province Department of Agriculture and Rural Affairs, Sichuan Animal Husbandry Station, Chengdu, China
| | - Bo Feng
- Sichuan Province Department of Agriculture and Rural Affairs, Sichuan Animal Husbandry Station, Chengdu, China
| | - Anan Jiang
- Farm Animal Genetic Resources Exploration and Innovation, Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, China
| | - Linyuan Shen
- Farm Animal Genetic Resources Exploration and Innovation, Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, China
| | - Weihang Xiao
- Farm Animal Genetic Resources Exploration and Innovation, Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, China
| | - Yanzhi Jiang
- College of Life Science, Sichuan Agricultural University, Yaan, China
| | - Li Zhu
- Farm Animal Genetic Resources Exploration and Innovation, Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, China
| | - Yangshuang Zeng
- Sichuan Province Department of Agriculture and Rural Affairs, Sichuan Animal Husbandry Station, Chengdu, China
| | - Xu Xu
- Sichuan Province Department of Agriculture and Rural Affairs, Sichuan Animal Husbandry Station, Chengdu, China
| | - Xuewei Li
- Farm Animal Genetic Resources Exploration and Innovation, Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, China
| | - Guoqing Tang
- Farm Animal Genetic Resources Exploration and Innovation, Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, China
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Liu X, Zhou L, Xie X, Wu Z, Xiong X, Zhang Z, Yang J, Xiao S, Zhou M, Ma J, Huang L. Muscle glycogen level and occurrence of acid meat in commercial hybrid pigs are regulated by two low-frequency causal variants with large effects and multiple common variants with small effects. Genet Sel Evol 2019; 51:46. [PMID: 31443641 PMCID: PMC6708195 DOI: 10.1186/s12711-019-0488-0] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2018] [Accepted: 08/08/2019] [Indexed: 11/10/2022] Open
Abstract
Background Meat production from the commercial crossbred Duroc × (Landrace × Yorkshire) (DLY) pig is predominant in the pork industry, but its meat quality is often impaired by low ultimate pH (pHu). Muscle glycogen level at slaughter is closely associated with pHu and meat technological quality, but its genetic basis remains elusive. The aim of this study was to identify genes and/or causative mutations associated with muscle glycogen level and other meat quality traits by performing a genome-wide association study (GWAS) and additional analyses in a population of 610 DLY pigs. Results Our initial GWAS identified a genome-wide significant (P = 2.54e−11) quantitative trait locus (QTL) on SSC15 (SSC for Sus scrofa chromosome) for the level of residual glycogen and glucose (RG) in the longissimus muscle at 45 min post-mortem. Then, we demonstrated that a low-frequency (minor allele frequency = 0.014) R200Q missense mutation in the PRKAG3 (RN) gene caused this major QTL effect on RG. Moreover, we showed that the 200Q (RN–) allele was introgressed from the Hampshire breed into more than one of the parental breeds of the DLY pigs. After conditioning on R200Q, re-association analysis revealed three additional QTL for RG on SSC3 and 4, and on an unmapped scaffold (AEMK02000452.1). The SSC3 QTL was most likely caused by a splice mutation (g.8283C>A) in the PHKG1 gene that we had previously identified. Based on functional annotation, the genes TMCO1 on SSC4 and CKB on the scaffold represent promising candidate genes for the other two QTL. There were significant interaction effects of the GWAS tag SNPs at those two loci with PRKAG3 R200Q on RG. In addition, a number of common variants with potentially smaller effects on RG (P < 10−4) were uncovered by a second conditional GWAS after adjusting for the two causal SNPs, R200Q and g.8283C>A. Conclusions We found that the RN– allele segregates in the parental lines of our DLY population and strongly influences its meat quality. Our findings also indicate that the genetic basis of RG in DLY can be mainly attributed to two major genes (PRKAG3 and PHKG1), along with many minor genes. Electronic supplementary material The online version of this article (10.1186/s12711-019-0488-0) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Xianxian Liu
- State Key Laboratory for Swine Genetics, Breeding and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China
| | - Lisheng Zhou
- State Key Laboratory for Swine Genetics, Breeding and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China
| | - Xianhua Xie
- State Key Laboratory for Swine Genetics, Breeding and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China
| | - Zhongzi Wu
- State Key Laboratory for Swine Genetics, Breeding and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China
| | - Xinwei Xiong
- State Key Laboratory for Swine Genetics, Breeding and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China
| | - Zhiyan Zhang
- State Key Laboratory for Swine Genetics, Breeding and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China
| | - Jie Yang
- State Key Laboratory for Swine Genetics, Breeding and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China
| | - Shijun Xiao
- State Key Laboratory for Swine Genetics, Breeding and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China
| | - Mengqing Zhou
- State Key Laboratory for Swine Genetics, Breeding and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China
| | - Junwu Ma
- State Key Laboratory for Swine Genetics, Breeding and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China.
| | - Lusheng Huang
- State Key Laboratory for Swine Genetics, Breeding and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China.
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