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Van Goor A, Pasternak A, Walugembe M, Chehab N, Hamonic G, Dekkers JCM, Harding JCS, Lunney JK. Genome wide association study of thyroid hormone levels following challenge with porcine reproductive and respiratory syndrome virus. Front Genet 2023; 14:1110463. [PMID: 36845393 PMCID: PMC9947478 DOI: 10.3389/fgene.2023.1110463] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Accepted: 01/25/2023] [Indexed: 02/11/2023] Open
Abstract
Introduction: Porcine reproductive and respiratory syndrome virus (PRRSV) causes respiratory disease in piglets and reproductive disease in sows. Piglet and fetal serum thyroid hormone (i.e., T3 and T4) levels decrease rapidly in response to Porcine reproductive and respiratory syndrome virus infection. However, the genetic control of T3 and T4 levels during infection is not completely understood. Our objective was to estimate genetic parameters and identify quantitative trait loci (QTL) for absolute T3 and/or T4 levels of piglets and fetuses challenged with Porcine reproductive and respiratory syndrome virus. Methods: Sera from 5-week-old pigs (N = 1792) at 11 days post inoculation (DPI) with Porcine reproductive and respiratory syndrome virus were assayed for T3 levels (piglet_T3). Sera from fetuses (N = 1,267) at 12 or 21 days post maternal inoculation (DPMI) with Porcine reproductive and respiratory syndrome virus of sows (N = 145) in late gestation were assayed for T3 (fetal_T3) and T4 (fetal_T4) levels. Animals were genotyped using 60 K Illumina or 650 K Affymetrix single nucleotide polymorphism (SNP) panels. Heritabilities, phenotypic correlations, and genetic correlations were estimated using ASREML; genome wide association studies were performed for each trait separately using Julia for Whole-genome Analysis Software (JWAS). Results: All three traits were low to moderately heritable (10%-16%). Phenotypic and genetic correlations of piglet_T3 levels with weight gain (0-42 DPI) were 0.26 ± 0.03 and 0.67 ± 0.14, respectively. Nine significant quantitative trait loci were identified for piglet_T3, on Sus scrofa chromosomes (SSC) 3, 4, 5, 6, 7, 14, 15, and 17, and collectively explaining 30% of the genetic variation (GV), with the largest quantitative trait loci identified on SSC5, explaining 15% of the genetic variation. Three significant quantitative trait loci were identified for fetal_T3 on SSC1 and SSC4, which collectively explained 10% of the genetic variation. Five significant quantitative trait loci were identified for fetal_T4 on SSC1, 6, 10, 13, and 15, which collectively explained 14% of the genetic variation. Several putative immune-related candidate genes were identified, including CD247, IRF8, and MAPK8. Discussion: Thyroid hormone levels following Porcine reproductive and respiratory syndrome virus infection were heritable and had positive genetic correlations with growth rate. Multiple quantitative trait loci with moderate effects were identified for T3 and T4 levels during challenge with Porcine reproductive and respiratory syndrome virus and candidate genes were identified, including several immune-related genes. These results advance our understanding of growth effects of both piglet and fetal response to Porcine reproductive and respiratory syndrome virus infection, revealing factors associated with genomic control of host resilience.
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Affiliation(s)
- Angelica Van Goor
- Animal Parasitic Diseases Laboratory, United States Department of Agriculture, Agricultural Research Services, Beltsville Agricultural Research Center, Beltsville, MD, United States
| | - Alex Pasternak
- Department of Animal Science, Purdue University, West Lafayette, IN, United States
| | - Muhammed Walugembe
- Department of Animal Science, Iowa State University, Ames, IA, United States
| | - Nadya Chehab
- Animal Parasitic Diseases Laboratory, United States Department of Agriculture, Agricultural Research Services, Beltsville Agricultural Research Center, Beltsville, MD, United States
| | - Glenn Hamonic
- Department of Large Animal Clinical Sciences, Western College of Veterinary Medicine, University of Saskatchewan, Saskatoon, SK, Canada
| | - Jack C. M. Dekkers
- Department of Animal Science, Iowa State University, Ames, IA, United States
| | - John C. S. Harding
- Department of Large Animal Clinical Sciences, Western College of Veterinary Medicine, University of Saskatchewan, Saskatoon, SK, Canada
| | - Joan K. Lunney
- Animal Parasitic Diseases Laboratory, United States Department of Agriculture, Agricultural Research Services, Beltsville Agricultural Research Center, Beltsville, MD, United States,*Correspondence: Joan K. Lunney,
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Gui S, Martinez-Rivas FJ, Wen W, Meng M, Yan J, Usadel B, Fernie AR. Going broad and deep: sequencing-driven insights into plant physiology, evolution, and crop domestication. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2023; 113:446-459. [PMID: 36534120 DOI: 10.1111/tpj.16070] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Revised: 12/12/2022] [Accepted: 12/13/2022] [Indexed: 06/17/2023]
Abstract
Deep sequencing is a term that has become embedded in the plant genomic literature in recent years and with good reason. A torrent of (largely) high-quality genomic and transcriptomic data has been collected and most of this has been publicly released. Indeed, almost 1000 plant genomes have been reported (www.plabipd.de) and the 2000 Plant Transcriptomes Project has long been completed. The EarthBioGenome project will dwarf even these milestones. That said, massive progress in understanding plant physiology, evolution, and crop domestication has been made by sequencing broadly (across a species) as well as deeply (within a single individual). We will outline the current state of the art in genome and transcriptome sequencing before we briefly review the most visible of these broad approaches, namely genome-wide association and transcriptome-wide association studies, as well as the compilation of pangenomes. This will include both (i) the most commonly used methods reliant on single nucleotide polymorphisms and short InDels and (ii) more recent examples which consider structural variants. We will subsequently present case studies exemplifying how their application has brought insight into either plant physiology or evolution and crop domestication. Finally, we will provide conclusions and an outlook as to the perspective for the extension of such approaches to different species, tissues, and biological processes.
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Affiliation(s)
- Songtao Gui
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
| | | | - Weiwei Wen
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
| | - Minghui Meng
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
| | - Jianbing Yan
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
| | - Björn Usadel
- IBG-4 Bioinformatics, Forschungszentrum Jülich, Wilhelm Johnen Str, BioSc, 52428, Jülich, Germany
- Institute for Biological Data Science, CEPLAS, Heinrich Heine University, 40225, Düsseldorf, Germany
| | - Alisdair R Fernie
- Max-Planck-Institute of Molecular Plant Physiology, Am Mühlenberg 1, Potsdam-Golm, 14476, Germany
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Machado PC, Brito LF, Martins R, Pinto LFB, Silva MR, Pedrosa VB. Genome-Wide Association Analysis Reveals Novel Loci Related with Visual Score Traits in Nellore Cattle Raised in Pasture-Based Systems. Animals (Basel) 2022; 12:ani12243526. [PMID: 36552446 PMCID: PMC9774243 DOI: 10.3390/ani12243526] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Revised: 12/06/2022] [Accepted: 12/10/2022] [Indexed: 12/15/2022] Open
Abstract
Body conformation traits assessed based on visual scores are widely used in Zebu cattle breeding programs. The aim of this study was to identify genomic regions and biological pathways associated with body conformation (CONF), finishing precocity (PREC), and muscling (MUSC) in Nellore cattle. The measurements based on visual scores were collected in 20,807 animals raised in pasture-based systems in Brazil. In addition, 2775 animals were genotyped using a 35 K SNP chip, which contained 31,737 single nucleotide polymorphisms after quality control. Single-step GWAS was performed using the BLUPF90 software while candidate genes were identified based on the Ensembl Genes 69. PANTHER and REVIGO platforms were used to identify key biological pathways and STRING to create gene networks. Novel candidate genes were revealed associated with CONF, including ALDH9A1, RXRG, RAB2A, and CYP7A1, involved in lipid metabolism. The genes associated with PREC were ELOVL5, PID1, DNER, TRIP12, and PLCB4, which are related to the synthesis of long-chain fatty acids, lipid metabolism, and muscle differentiation. For MUSC, the most important genes associated with muscle development were SEMA6A, TIAM2, UNC5A, and UIMC1. The polymorphisms identified in this study can be incorporated in commercial genotyping panels to improve the accuracy of genomic evaluations for visual scores in beef cattle.
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Affiliation(s)
- Pamela C. Machado
- Department of Animal Sciences, State University of Ponta Grossa, Ponta Grossa 84030-900, PR, Brazil
| | - Luiz F. Brito
- Department of Animal Sciences, Purdue University, West Lafayette, IN 47907, USA
| | - Rafaela Martins
- Department of Animal Sciences, State University of Ponta Grossa, Ponta Grossa 84030-900, PR, Brazil
| | - Luis Fernando B. Pinto
- Department of Animal Science, Federal University of Bahia, Av. Adhemar de Barros 500, Ondina, Salvador 40170-110, BA, Brazil
| | - Marcio R. Silva
- Melhore Animal and Katayama Agropecuaria Lda, Guararapes 16700-000, SP, Brazil
| | - Victor B. Pedrosa
- Department of Animal Sciences, State University of Ponta Grossa, Ponta Grossa 84030-900, PR, Brazil
- Department of Animal Sciences, Purdue University, West Lafayette, IN 47907, USA
- Correspondence:
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Liu H, Zhai J, Wu H, Wang J, Zhang S, Li J, Niu Z, Shen C, Zhang K, Liu Z, Jiang F, Song E, Sun X, Wang Y, Lan X. Diversity of Mitochondrial DNA Haplogroups and Their Association with Bovine Antral Follicle Count. Animals (Basel) 2022; 12:ani12182350. [PMID: 36139210 PMCID: PMC9495067 DOI: 10.3390/ani12182350] [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: 05/18/2022] [Revised: 06/30/2022] [Accepted: 09/05/2022] [Indexed: 12/02/2022] Open
Abstract
Maternal origins based on the bovine mitochondrial D-loop region are proven to have two main origins: Bos taurus and Bos indicus. To examine the association between the maternal origins of bovine and reproductive traits, the complete mitochondrial D-loop region sequences from 501 Chinese Holstein cows and 94 individuals of other breeds were analyzed. Based on the results obtained from the haplotype analysis, 260 SNPs (single nucleotide polymorphism), 32 indels (insertion/deletion), and 219 haplotypes were identified. Moreover, the nucleotide diversity (π) and haplotype diversity (Hd) were 0.024 ± 0.001 and 0.9794 ± 0.003, respectively, indicating the abundance of genetic resources in Chinese Holstein cows. The results of the median-joining network analysis showed two haplogroups (HG, including HG1 and HG2) that diverged in genetic distance. Furthermore, the two haplogroups were significantly (p < 0.05) correlated with the antral follicle (diameter ≥ 8 mm) count, and HG1 individuals had more antral follicles than HG2 individuals, suggesting that these different genetic variants between HG1 and HG2 correlate with reproductive traits. The construction of a neighbor-joining phylogenetic tree and principal component analysis also revealed two main clades (HG1 and HG2) with different maternal origins: Bos indicus and Bos taurus, respectively. Therefore, HG1 originating from the maternal ancestors of Bos indicus may have a greater reproductive performance, and potential genetic variants discovered may promote the breeding process in the cattle industry.
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Affiliation(s)
- Hongfei Liu
- College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Junjun Zhai
- College of Life Science, Yulin University, Yulin 719000, China
| | - Hui Wu
- College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Jingyi Wang
- College of Veterinary Medicine, Northwest A&F University, Yangling 712100, China
| | - Shaowei Zhang
- College of Veterinary Medicine, Northwest A&F University, Yangling 712100, China
| | - Jie Li
- College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Zhihan Niu
- College of Veterinary Medicine, Northwest A&F University, Yangling 712100, China
| | - Chenglong Shen
- College of Veterinary Medicine, Northwest A&F University, Yangling 712100, China
| | - Kaijuan Zhang
- College of Veterinary Medicine, Northwest A&F University, Yangling 712100, China
| | - Zhengqing Liu
- College of Veterinary Medicine, Northwest A&F University, Yangling 712100, China
| | - Fugui Jiang
- Shandong Key Laboratory of Animal Disease Control and Breeding, Institute of Animal Science and Veterinary Medicine, Shandong Academy of Agricultural Sciences, Jinan 250000, China
| | - Enliang Song
- Shandong Key Laboratory of Animal Disease Control and Breeding, Institute of Animal Science and Veterinary Medicine, Shandong Academy of Agricultural Sciences, Jinan 250000, China
| | - Xiuzhu Sun
- College of Grassland Agriculture, Northwest A&F University, Yangling 712100, China
| | - Yongsheng Wang
- College of Veterinary Medicine, Northwest A&F University, Yangling 712100, China
- Correspondence: (Y.W.); (X.L.)
| | - Xianyong Lan
- College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
- Correspondence: (Y.W.); (X.L.)
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Liu D, Xu Z, Zhao W, Wang S, Li T, Zhu K, Liu G, Zhao X, Wang Q, Pan Y, Ma P. Genetic parameters and genome-wide association for milk production traits and somatic cell score in different lactation stages of Shanghai Holstein population. Front Genet 2022; 13:940650. [PMID: 36134029 PMCID: PMC9483179 DOI: 10.3389/fgene.2022.940650] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Accepted: 08/04/2022] [Indexed: 11/13/2022] Open
Abstract
The aim of this study was to investigate the genetic parameters and genetic architectures of six milk production traits in the Shanghai Holstein population. The data used to estimate the genetic parameters consisted of 1,968,589 test-day records for 305,031 primiparous cows. Among the cows with phenotypes, 3,016 cows were genotyped with Illumina Bovine SNP50K BeadChip, GeneSeek Bovine 50K BeadChip, GeneSeek Bovine LD BeadChip v4, GeneSeek Bovine 150K BeadChip, or low-depth whole-genome sequencing. A genome-wide association study was performed to identify quantitative trait loci and genes associated with milk production traits in the Shanghai Holstein population using genotypes imputed to whole-genome sequences and both fixed and random model circulating probability unification and a mixed linear model with rMVP software. Estimated heritabilities (h2) varied from 0.04 to 0.14 for somatic cell score (SCS), 0.07 to 0.22 for fat percentage (FP), 0.09 to 0.27 for milk yield (MY), 0.06 to 0.23 for fat yield (FY), 0.09 to 0.26 for protein yield (PY), and 0.07 to 0.35 for protein percentage (PP), respectively. Within lactation, genetic correlations for SCS, FP, MY, FY, PY, and PP at different stages of lactation estimated in random regression model were ranged from -0.02 to 0.99, 0.18 to 0.99, 0.04 to 0.99, 0.04 to 0.99, 0.01 to 0.99, and 0.33 to 0.99, respectively. The genetic correlations were highest between adjacent DIM but decreased as DIM got further apart. Candidate genes included those related to production traits (DGAT1, MGST1, PTK2, and SCRIB), disease-related (LY6K, COL22A1, TECPR2, and PLCB1), heat stress–related (ITGA9, NDST4, TECPR2, and HSF1), and reproduction-related (7SK and DOCK2) genes. This study has shown that there are differences in the genetic mechanisms of milk production traits at different stages of lactation. Therefore, it is necessary to conduct research on milk production traits at different stages of lactation as different traits. Our results can also provide a theoretical basis for subsequent molecular breeding, especially for the novel genetic loci.
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Affiliation(s)
- Dengying Liu
- Shanghai Key Laboratory of Veterinary Biotechnology, Department of Animal Science, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai, China
| | - Zhong Xu
- Hubei Key Laboratory of Animal Embryo and Molecular Breeding, Institute of Animal Husbandry and Veterinary, Hubei Provincial Academy of Agricultural Sciences, Wuhan, China
| | - Wei Zhao
- Shanghai Key Laboratory of Veterinary Biotechnology, Department of Animal Science, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai, China
| | - Shiyi Wang
- Shanghai Key Laboratory of Veterinary Biotechnology, Department of Animal Science, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai, China
| | - Tuowu Li
- Shanghai Key Laboratory of Veterinary Biotechnology, Department of Animal Science, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai, China
| | - Kai Zhu
- Shanghai Dairy Cattle Breeding Centre Co, Ltd, Shanghai, China
| | - Guanglei Liu
- Shanghai Dairy Cattle Breeding Centre Co, Ltd, Shanghai, China
| | - Xiaoduo Zhao
- Shanghai Dairy Cattle Breeding Centre Co, Ltd, Shanghai, China
| | - Qishan Wang
- Department of Animal Breeding and Reproduction, College of Animal Science, Zhejiang University, Hangzhou, China
| | - Yuchun Pan
- Department of Animal Breeding and Reproduction, College of Animal Science, Zhejiang University, Hangzhou, China
- *Correspondence: Peipei Ma, ; Yuchun Pan,
| | - Peipei Ma
- Shanghai Key Laboratory of Veterinary Biotechnology, Department of Animal Science, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai, China
- *Correspondence: Peipei Ma, ; Yuchun Pan,
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Liu SH, Ma XY, Hassan FU, Gao TY, Deng TX. Genome-wide analysis of runs of homozygosity in Italian Mediterranean buffalo. J Dairy Sci 2022; 105:4324-4334. [PMID: 35307184 DOI: 10.3168/jds.2021-21543] [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: 11/07/2021] [Accepted: 02/07/2022] [Indexed: 11/19/2022]
Abstract
Runs of homozygosity (ROH) are a powerful tool to explore patterns of genomic inbreeding in animal populations and detect signatures of selection. The present study used ROH analysis to evaluate the genome-wide patterns of homozygosity, inbreeding levels, and distribution of ROH islands using the SNP data sets from 899 Mediterranean buffaloes. A total of 42,433 ROH segments were identified, with an average of 47.20 segments per individual. The ROH comprising mostly shorter segments (1-4 Mb) accounted for approximately 72.29% of all ROH. In contrast, the larger ROH (>8 Mb) class accounted for only 7.97% of all ROH segments. Estimated inbreeding coefficients from ROH (FROH) ranged from 0.0201 to 0.0371. Pearson correlations between FROH and genomic relationship matrix increased with the increase of ROH length. We identified ROH hotspots in 12 genomic regions, located on chromosomes 1, 2, 3, 5, 17, and 19, harboring a total of 122 genes. Protein-protein interaction (PPI) analysis revealed the clustering of these genes into 7 PPI networks. Many genes located in these regions were associated with different production traits. In addition, 5 ROH islands overlapped with cattle quantitative trait loci that were mainly associated with milk traits. These findings revealed the genome-wide autozygosity patterns and inbreeding levels in Mediterranean buffalo. Our study identified many candidate genes related to production traits that could be used to assist in selective breeding for genetic improvement of buffalo.
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Affiliation(s)
- Shen-He Liu
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450046, China.
| | - Xiao-Ya Ma
- Guangxi Provincial Key Laboratory of Buffalo Genetics, Breeding and Reproduction Technology, Buffalo Research Institute, Chinese Academy of Agricultural Sciences, Nanning 530001, China
| | - Faiz-Ul Hassan
- Institute of Animal and Dairy Sciences, University of Agriculture, Faisalabad 38040, Pakistan
| | - Teng-Yun Gao
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450046, China
| | - Ting-Xian Deng
- Guangxi Provincial Key Laboratory of Buffalo Genetics, Breeding and Reproduction Technology, Buffalo Research Institute, Chinese Academy of Agricultural Sciences, Nanning 530001, China.
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He Y, Zhou X, Zheng R, Jiang Y, Yao Z, Wang X, Zhang Z, Zhang H, Li J, Yuan X. The Association of an SNP in the EXOC4 Gene and Reproductive Traits Suggests Its Use as a Breeding Marker in Pigs. Animals (Basel) 2021; 11:ani11020521. [PMID: 33671441 PMCID: PMC7921996 DOI: 10.3390/ani11020521] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2021] [Revised: 02/07/2021] [Accepted: 02/10/2021] [Indexed: 02/07/2023] Open
Abstract
In mammals, the exocyst complex component 4 (EXOC4) gene has often been reported to be involved in vesicle transport. The SNP rs81471943 (C/T) is located in the intron of porcine EXOC4, while six quantitative trait loci (QTL) within 5-10 Mb around EXOC4 are associated with ovary weight, teat number, total offspring born alive, and corpus luteum number. However, the molecular mechanisms between EXOC4 and the reproductive performance of pigs remains to be elucidated. In this study, rs81471943 was genotyped from a total of 994 Duroc sows, and the genotype and allele frequency of SNP rs81471943 (C/T) were statistically analyzed. Then, the associations between SNP rs81471943 and four reproductive traits, including number of piglets born alive (NBA), litter weight at birth (LWB), number of piglets weaned (NW), and litter weight at weaning (LWW), were determined. Sanger sequencing and PCR restriction fragment length polymorphism (PCR-RFLP) were utilized to identify the rs81471943 genotype. We found that the genotype frequency of CC was significantly higher than that of CT and TT, and CC was the most frequent genotype for NBA, LWB, NW, and LWW. Moreover, 5'-deletion and luciferase assays identified a positive transcription regulatory element in the EXOC4 promoter. After exploring the EXOC4 promoter, SNP -1781G/A linked with SNP rs81471943 (C/T) were identified by analysis of the transcription activity of the haplotypes, and SNP -1781 G/A may influence the potential binding of P53, E26 transformation specific sequence -like 1 transcription factor (ELK1), and myeloid zinc finger 1 (MZF1). These findings provide useful information for identifying a molecular marker of EXOC4-assisted selection in pig breeding.
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Affiliation(s)
- Yingting He
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (Y.H.); (X.Z.); (R.Z.); (Y.J.); (Z.Z.); (H.Z.)
| | - Xiaofeng Zhou
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (Y.H.); (X.Z.); (R.Z.); (Y.J.); (Z.Z.); (H.Z.)
| | - Rongrong Zheng
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (Y.H.); (X.Z.); (R.Z.); (Y.J.); (Z.Z.); (H.Z.)
| | - Yao Jiang
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (Y.H.); (X.Z.); (R.Z.); (Y.J.); (Z.Z.); (H.Z.)
| | - Zhixiang Yao
- Guangdong Dexing Food Co., Ltd., Shantou 515100, China;
| | - Xilong Wang
- Guangdong Provincial Key Laboratory of Laboratory Animals, Guangdong Laboratory Animals Monitoring Institute, Guangzhou 510260, China;
| | - Zhe Zhang
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (Y.H.); (X.Z.); (R.Z.); (Y.J.); (Z.Z.); (H.Z.)
| | - Hao Zhang
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (Y.H.); (X.Z.); (R.Z.); (Y.J.); (Z.Z.); (H.Z.)
| | - Jiaqi Li
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (Y.H.); (X.Z.); (R.Z.); (Y.J.); (Z.Z.); (H.Z.)
- Correspondence: (J.L.); (X.Y.)
| | - Xiaolong Yuan
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (Y.H.); (X.Z.); (R.Z.); (Y.J.); (Z.Z.); (H.Z.)
- Guangdong Provincial Key Laboratory of Laboratory Animals, Guangdong Laboratory Animals Monitoring Institute, Guangzhou 510260, China;
- Correspondence: (J.L.); (X.Y.)
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