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Park J. Genome-wide association study to reveal new candidate genes using single-step approaches for productive traits of Yorkshire pig in Korea. Anim Biosci 2024; 37:451-460. [PMID: 38271983 PMCID: PMC10915189 DOI: 10.5713/ab.23.0255] [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: 06/11/2023] [Revised: 09/25/2023] [Accepted: 11/08/2023] [Indexed: 01/27/2024] Open
Abstract
OBJECTIVE The objective is to identify genomic regions and candidate genes associated with age to 105 kg (AGE), average daily gain (ADG), backfat thickness (BF), and eye muscle area (EMA) in Yorkshire pig. METHODS This study used a total of 104,380 records and 11,854 single nucleotide polymorphism (SNP) data obtained from Illumina porcine 60K chip. The estimated genomic breeding values (GEBVs) and SNP effects were estimated by single-step genomic best linear unbiased prediction (ssGBLUP). RESULTS The heritabilities of AGE, ADG, BF, and EMA were 0.50, 0.49, 0.49, and 0.23, respectively. We identified significant SNP markers surpassing the Bonferroni correction threshold (1.68×10-6), with a total of 9 markers associated with both AGE and ADG, and 4 markers associated with BF and EMA. Genome-wide association study (GWAS) analyses revealed notable chromosomal regions linked to AGE and ADG on Sus scrofa chromosome (SSC) 1, 6, 8, and 16; BF on SSC 2, 5, and 8; and EMA on SSC 1. Additionally, we observed strong linkage disequilibrium on SSC 1. Finally, we performed enrichment analyses using gene ontology and Kyoto encyclopedia of genes and genomes (KEGG), which revealed significant enrichments in eight biological processes, one cellular component, one molecular function, and one KEGG pathway. CONCLUSION The identified SNP markers for productive traits are expected to provide valuable information for genetic improvement as an understanding of their expression.
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Affiliation(s)
- Jun Park
- Department of Animal Biotechnology, Jeonbuk National University, Jeonju 54896,
Korea
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Hubert JN, Perret M, Riquet J, Demars J. Livestock species as emerging models for genomic imprinting. Front Cell Dev Biol 2024; 12:1348036. [PMID: 38500688 PMCID: PMC10945557 DOI: 10.3389/fcell.2024.1348036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2023] [Accepted: 01/19/2024] [Indexed: 03/20/2024] Open
Abstract
Genomic imprinting is an epigenetically-regulated process of central importance in mammalian development and evolution. It involves multiple levels of regulation, with spatio-temporal heterogeneity, leading to the context-dependent and parent-of-origin specific expression of a small fraction of the genome. Genomic imprinting studies have therefore been essential to increase basic knowledge in functional genomics, evolution biology and developmental biology, as well as with regard to potential clinical and agrigenomic perspectives. Here we offer an overview on the contribution of livestock research, which features attractive resources in several respects, for better understanding genomic imprinting and its functional impacts. Given the related broad implications and complexity, we promote the use of such resources for studying genomic imprinting in a holistic and integrative view. We hope this mini-review will draw attention to the relevance of livestock genomic imprinting studies and stimulate research in this area.
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Affiliation(s)
| | | | | | - Julie Demars
- GenPhySE, Université de Toulouse, INRAE, ENVT, Castanet Tolosan, France
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Zhang Y, Zhuang Z, Liu Y, Huang J, Luan M, Zhao X, Dong L, Ye J, Yang M, Zheng E, Cai G, Wu Z, Yang J. Genomic prediction based on preselected single-nucleotide polymorphisms from genome-wide association study and imputed whole-genome sequence data annotation for growth traits in Duroc pigs. Evol Appl 2024; 17:e13651. [PMID: 38362509 PMCID: PMC10868536 DOI: 10.1111/eva.13651] [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: 12/11/2022] [Revised: 10/31/2023] [Accepted: 01/13/2024] [Indexed: 02/17/2024] Open
Abstract
The use of whole-genome sequence (WGS) data is expected to improve genomic prediction (GP) power of complex traits because it may contain mutations that in strong linkage disequilibrium pattern with causal mutations. However, a few previous studies have shown no or small improvement in prediction accuracy using WGS data. Incorporating prior biological information into GP seems to be an attractive strategy that might improve prediction accuracy. In this study, a total of 6334 pigs were genotyped using 50K chips and subsequently imputed to the WGS level. This cohort includes two prior discovery populations that comprise 294 Landrace pigs and 186 Duroc pigs, as well as two validation populations that consist of 3770 American Duroc pigs and 2084 Canadian Duroc pigs. Then we used annotation information and genome-wide association study (GWAS) from the WGS data to make GP for six growth traits in two Duroc pig populations. Based on variant annotation, we partitioned different genomic classes, such as intron, intergenic, and untranslated regions, for imputed WGS data. Based on GWAS results of WGS data, we obtained trait-associated single-nucleotide polymorphisms (SNPs). We then applied the genomic feature best linear unbiased prediction (GFBLUP) and genomic best linear unbiased prediction (GBLUP) models to estimate the genomic estimated breeding values for growth traits with these different variant panels, including six genomic classes and trait-associated SNPs. Compared with 50K chip data, GBLUP with imputed WGS data had no increase in prediction accuracy. Using only annotations resulted in no increase in prediction accuracy compared to GBLUP with 50K, but adding annotation information into the GFBLUP model with imputed WGS data could improve the prediction accuracy with increases of 0.00%-2.82%. In conclusion, a GFBLUP model that incorporated prior biological information might increase the advantage of using imputed WGS data for GP.
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Affiliation(s)
- Yuling Zhang
- College of Animal Science and National Engineering Research Center for Breeding Swine IndustrySouth China Agricultural UniversityGuangzhouChina
- Guangdong Provincial Key Laboratory of Agro‐animal Genomics and Molecular BreedingSouth China Agricultural UniversityGuangzhouChina
| | - Zhanwei Zhuang
- College of Animal Science and National Engineering Research Center for Breeding Swine IndustrySouth China Agricultural UniversityGuangzhouChina
- Guangdong Provincial Key Laboratory of Agro‐animal Genomics and Molecular BreedingSouth China Agricultural UniversityGuangzhouChina
| | - Yiyi Liu
- College of Animal Science and National Engineering Research Center for Breeding Swine IndustrySouth China Agricultural UniversityGuangzhouChina
- Guangdong Provincial Key Laboratory of Agro‐animal Genomics and Molecular BreedingSouth China Agricultural UniversityGuangzhouChina
| | - Jinyan Huang
- College of Animal Science and National Engineering Research Center for Breeding Swine IndustrySouth China Agricultural UniversityGuangzhouChina
- Guangdong Provincial Key Laboratory of Agro‐animal Genomics and Molecular BreedingSouth China Agricultural UniversityGuangzhouChina
| | - Menghao Luan
- College of Animal Science and National Engineering Research Center for Breeding Swine IndustrySouth China Agricultural UniversityGuangzhouChina
- Guangdong Provincial Key Laboratory of Agro‐animal Genomics and Molecular BreedingSouth China Agricultural UniversityGuangzhouChina
| | - Xiang Zhao
- College of Animal Science and National Engineering Research Center for Breeding Swine IndustrySouth China Agricultural UniversityGuangzhouChina
- Guangdong Provincial Key Laboratory of Agro‐animal Genomics and Molecular BreedingSouth China Agricultural UniversityGuangzhouChina
| | - Linsong Dong
- Guangdong Zhongxin Breeding Technology Co., LtdGuangzhouChina
| | - Jian Ye
- Guangdong Zhongxin Breeding Technology Co., LtdGuangzhouChina
| | - Ming Yang
- College of Animal Science and TechnologyZhongkai University of Agriculture and EngineeringGuangzhouChina
| | - Enqin Zheng
- College of Animal Science and National Engineering Research Center for Breeding Swine IndustrySouth China Agricultural UniversityGuangzhouChina
- Guangdong Provincial Key Laboratory of Agro‐animal Genomics and Molecular BreedingSouth China Agricultural UniversityGuangzhouChina
| | - Gengyuan Cai
- College of Animal Science and National Engineering Research Center for Breeding Swine IndustrySouth China Agricultural UniversityGuangzhouChina
- Guangdong Provincial Key Laboratory of Agro‐animal Genomics and Molecular BreedingSouth China Agricultural UniversityGuangzhouChina
| | - Zhenfang Wu
- College of Animal Science and National Engineering Research Center for Breeding Swine IndustrySouth China Agricultural UniversityGuangzhouChina
- Guangdong Provincial Key Laboratory of Agro‐animal Genomics and Molecular BreedingSouth China Agricultural UniversityGuangzhouChina
- Guangdong Zhongxin Breeding Technology Co., LtdGuangzhouChina
| | - Jie Yang
- College of Animal Science and National Engineering Research Center for Breeding Swine IndustrySouth China Agricultural UniversityGuangzhouChina
- Guangdong Provincial Key Laboratory of Agro‐animal Genomics and Molecular BreedingSouth China Agricultural UniversityGuangzhouChina
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4
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Zhao X, Qiu Y, Meng F, Zhuang Z, Ruan D, Wu J, Ma F, Zheng E, Cai G, Yang J, Yang M, Wu Z. Genome-wide association studies for loin muscle area, loin muscle depth and backfat thickness in DLY pigs. Anim Genet 2024; 55:134-139. [PMID: 38098441 DOI: 10.1111/age.13386] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2022] [Revised: 10/17/2023] [Accepted: 11/28/2023] [Indexed: 01/04/2024]
Abstract
This study aimed at identifying genes associated with loin muscle area (LMA), loin muscle depth (LMD) and backfat thickness (BFT). We performed single-trait and multi-trait genome-wide association studies (GWASs) after genotyping 685 Duroc × (Landrace × Yorkshire) (DLY) pigs using the Geneseek Porcine 50K SNP chip. In the single-trait GWASs, we identified two, eight and two significant SNPs associated with LMA, LMD and BFT, respectively, and searched genes within the 1 Mb region near the significant SNPs with relevant functions as candidate genes. Consequently, we identified one (DOCK5), three (PID1, PITX2, ELOVL6) and three (CCR1, PARP14, CASR) promising candidate genes for LMA, LMD and BFT, respectively. Moreover, the multi-trait GWAS identified four significant SNPs associated with the three traits. In conclusion, the GWAS analysis of LMA, LMD and BFT in a DLY pig population identified several associated SNPs and candidate genes, further deepening our understanding of the genetic basis of these traits, and they may be useful for marker-assisted selection to improve the three traits in DLY pigs.
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Affiliation(s)
- Xiang Zhao
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, China
| | - Yibin Qiu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, China
| | - Fanming Meng
- State Key Laboratory of Livestock and Poultry Breeding/Guangdong Key Laboratory of Animal Breeding and Nutrition, Institute of Animal Science, Guangdong Academy of Agricultural Sciences, Guangzhou, Guangdong, China
| | - Zhanwei Zhuang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, China
| | - Donglin Ruan
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, China
| | - Jie Wu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, China
| | - Fucai Ma
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, China
| | - Enqin Zheng
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, China
- Guangdong Provincial Key Laboratory of Agro-animal Genomics and Molecular Breeding, South China Agricultural University, Guangzhou, Guangdong, China
| | - Gengyuan Cai
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, China
- Guangdong Provincial Key Laboratory of Agro-animal Genomics and Molecular Breeding, South China Agricultural University, Guangzhou, Guangdong, China
- Guangdong Zhongxin Breeding Technology Co., Ltd, Guangzhou, Guangdong, China
| | - Jie Yang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, China
- Guangdong Provincial Key Laboratory of Agro-animal Genomics and Molecular Breeding, South China Agricultural University, Guangzhou, Guangdong, China
| | - Ming Yang
- Guangdong Zhongxin Breeding Technology Co., Ltd, Guangzhou, Guangdong, China
- College of Animal Science and Technology, Zhongkai University of Agriculture and Engineering, Guangzhou, Guangdong, China
| | - Zhenfang Wu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, China
- Guangdong Provincial Key Laboratory of Agro-animal Genomics and Molecular Breeding, South China Agricultural University, Guangzhou, Guangdong, China
- Yunfu Subcenter of Guangdong Laboratory for Lingnan Modern Agriculture, Yunfu, Guangdong, China
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5
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Gao X, Zhou S, Liu Z, Ruan D, Wu J, Quan J, Zheng E, Yang J, Cai G, Wu Z, Yang M. Genome-Wide Association Study for Somatic Skeletal Traits in Duroc × (Landrace × Yorkshire) Pigs. Animals (Basel) 2023; 14:37. [PMID: 38200769 PMCID: PMC10778498 DOI: 10.3390/ani14010037] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Revised: 12/15/2023] [Accepted: 12/18/2023] [Indexed: 01/12/2024] Open
Abstract
The pig bone weight trait holds significant economic importance in southern China. To expedite the selection of the pig bone weight trait in pig breeding, we conducted molecular genetic research on these specific traits. These traits encompass the bone weight of the scapula (SW), front leg bone weight (including humerus and ulna) (FLBW), hind leg bone weight (including femur and tibia) (HLBW), and spine bone weight (SBW). Up until now, the genetic structure related to these traits has not been thoroughly explored, primarily due to challenges associated with obtaining the phenotype data. In this study, we utilized genome-wide association studies (GWAS) to discern single nucleotide polymorphisms (SNPs) and genes associated with four bone weight traits within a population comprising 571 Duroc × (Landrace × Yorkshire) hybrid pigs (DLY). In the analyses, we employed a mixed linear model, and for the correction of multiple tests, both the false discovery rate and Bonferroni methods were utilized. Following functional annotation, candidate genes were identified based on their proximity to the candidate sites and their association with the bone weight traits. This study represents the inaugural application of GWAS for the identification of SNPs associated with individual bone weight in DLY pigs. Our analysis unveiled 26 SNPs and identified 12 promising candidate genes (OPRM1, SLC44A5, WASHC4, NOPCHAP1, RHOT1, GLP1R, TGFB3, PLCB1, TLR4, KCNJ2, ABCA6, and ABCA9) associated with the four bone weight traits. Furthermore, our findings on the genetic mechanisms influencing pig bone weight offer valuable insights as a reference for the genetic enhancement of pig bone traits.
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Affiliation(s)
- Xin Gao
- College of Animal Science and Technology, Zhongkai University of Agriculture and Engineering, Guangzhou 510225, China; (X.G.); (S.Z.); (Z.L.)
| | - Shenping Zhou
- College of Animal Science and Technology, Zhongkai University of Agriculture and Engineering, Guangzhou 510225, China; (X.G.); (S.Z.); (Z.L.)
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou 510642, China
| | - Zhihong Liu
- College of Animal Science and Technology, Zhongkai University of Agriculture and Engineering, Guangzhou 510225, China; (X.G.); (S.Z.); (Z.L.)
| | - Donglin Ruan
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou 510642, China
| | - Jie Wu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou 510642, China
| | - Jianping Quan
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou 510642, China
| | - Enqin Zheng
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou 510642, China
| | - Jie Yang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou 510642, China
| | - Gengyuan Cai
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou 510642, China
| | - Zhenfang Wu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou 510642, China
| | - Ming Yang
- College of Animal Science and Technology, Zhongkai University of Agriculture and Engineering, Guangzhou 510225, China; (X.G.); (S.Z.); (Z.L.)
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Zhou F, Lin D, Dong L, Hong Y, Zeng H, Cai G, Ye J, Wu Z. Genetic evaluation for production and body size traits using different animal models in purebred-Duroc pigs. Front Vet Sci 2023; 10:1274266. [PMID: 38164395 PMCID: PMC10758212 DOI: 10.3389/fvets.2023.1274266] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Accepted: 11/27/2023] [Indexed: 01/03/2024] Open
Abstract
Duroc pigs are popular crossbred terminal sires, and accurate assessment of genetic parameters in the population can help to rationalize breeding programmes. The principle aim of this study were to evaluate the genetic parameters of production (birth weight, BW; age at 115 kg, AGE; feed conversion ratio, FCR) and body size (body length, BL; body height, BH; front cannon circumference, FCC) traits of Duroc pigs. The second objective was to analyze the fit of different genetic assessment models. The variance components and correlations of BW (28,348 records), AGE (28,335 records), FCR (11,135 records), BL (31,544 records), BH (21,862 records), and FCC (14,684 records) traits were calculated by using DMU and AIREMLF90 from BLUPF90 package. In the common environment model, the heritability of BW, AGE, FCR, BL, BH, and FCC traits were 0.17 ± 0.014, 0.30 ± 0.019, 0.28 ± 0.024, 0.16 ± 0.013, 0.14 ± 0.017, and 0.081 ± 0.016, with common litter effect values of 0.25, 0.20, 0.18, 0.23, 0.19, and 0.16, respectively. According to the results of the Akaike information criterion (AIC) calculations, models with smaller AIC values have a better fit. We found that the common environment model with litter effects as random effects for estimating genetic parameters had a better fit. In this Model, the estimated genetic correlations between AGE with BW, FCR, BL, BH, and FCC traits were -0.28 (0.040), 0.76 (0.038), -0.71 (0.036), -0.44 (0.060), and -0.60 (0.073), respectively, with phenotypic correlations of -0.17, 0.52, -0.22, -0.13 and -0.24, respectively. In our analysis of genetic trends for six traits in the Duroc population from 2012 to 2021, we observed significant genetic trends for AGE, BL, and BH. Particularly noteworthy is the rapid decline in the genetic trend for AGE, indicating an enhancement in the pig's growth rate through selective breeding. Therefore, we believe that some challenging-to-select traits can benefit from the genetic correlations between traits. By selecting easily measurable traits, they can gain from synergistic selection effects, leading to genetic progress. Conducting population genetic parameter analysis can assist us in devising breeding strategies.
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Affiliation(s)
- Fuchen Zhou
- National Engineering Research Center for Breeding Swine Industry and College of Animal Science, South China Agricultural University, Guangzhou, China
| | - Danyang Lin
- National Engineering Research Center for Breeding Swine Industry and College of Animal Science, South China Agricultural University, Guangzhou, China
| | - Linsong Dong
- National Engineering Research Center for Breeding Swine Industry, Wens Foodstuff Group Co., Ltd., Yunfu, China
| | - Yifeng Hong
- National Engineering Research Center for Breeding Swine Industry and College of Animal Science, South China Agricultural University, Guangzhou, China
| | - Haiyu Zeng
- National Engineering Research Center for Breeding Swine Industry, Wens Foodstuff Group Co., Ltd., Yunfu, China
| | - Gengyuan Cai
- National Engineering Research Center for Breeding Swine Industry and College of Animal Science, South China Agricultural University, Guangzhou, China
- National Engineering Research Center for Breeding Swine Industry, Wens Foodstuff Group Co., Ltd., Yunfu, China
| | - Jian Ye
- National Engineering Research Center for Breeding Swine Industry, Wens Foodstuff Group Co., Ltd., Yunfu, China
| | - Zhenfang Wu
- National Engineering Research Center for Breeding Swine Industry and College of Animal Science, South China Agricultural University, Guangzhou, China
- National Engineering Research Center for Breeding Swine Industry, Wens Foodstuff Group Co., Ltd., Yunfu, China
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Deng H, Jia Q, Ming X, Sun Y, Lu Y, Liu L, Zhou J. Hippo pathway in intestinal diseases: focusing on ferroptosis. Front Cell Dev Biol 2023; 11:1291686. [PMID: 38130953 PMCID: PMC10734691 DOI: 10.3389/fcell.2023.1291686] [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: 09/10/2023] [Accepted: 11/22/2023] [Indexed: 12/23/2023] Open
Abstract
The incidence of intestinal diseases, such as inflammatory bowel disease, gastric cancer, and colorectal cancer, has steadily increased over the past decades. The Hippo pathway is involved in cell proliferation, tissue and organ damage, energy metabolism, tumor formation, and other physiologic processes. Ferroptosis is a form of programmed cell death characterized by the accumulation of iron and lipid peroxides. The Hippo pathway and ferroptosis are associated with various intestinal diseases; however, the crosstalk between them is unclear. This review elaborates on the current research on the Hippo pathway and ferroptosis in the context of intestinal diseases. We summarized the connection between the Hippo pathway and ferroptosis to elucidate the underlying mechanism by which these pathways influence intestinal diseases. We speculate that a mutual regulatory mechanism exists between the Hippo pathway and ferroptosis and these two pathways interact in several ways to regulate intestinal diseases.
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Affiliation(s)
- Hongwei Deng
- Department of Anesthesiology, Southwest Medical University, Luzhou, China
- Anesthesiology and Critical Care Medicine Key Laboratory of Luzhou, Luzhou, China
| | - Qiuting Jia
- Department of Anesthesiology, Southwest Medical University, Luzhou, China
- Anesthesiology and Critical Care Medicine Key Laboratory of Luzhou, Luzhou, China
| | - Xin Ming
- Anesthesiology and Critical Care Medicine Key Laboratory of Luzhou, Luzhou, China
- School of Clinical Medicine, Southwest Medical University, Luzhou, China
| | - Yuxin Sun
- Anesthesiology and Critical Care Medicine Key Laboratory of Luzhou, Luzhou, China
- School of Basic Medicine, Southwest Medical University, Luzhou, China
| | - Yuxuan Lu
- Department of Anesthesiology, Southwest Medical University, Luzhou, China
- Anesthesiology and Critical Care Medicine Key Laboratory of Luzhou, Luzhou, China
| | - Li Liu
- Department of Anesthesiology, Southwest Medical University, Luzhou, China
- Anesthesiology and Critical Care Medicine Key Laboratory of Luzhou, Luzhou, China
- Department of Anesthesiology, The Affiliated Hospital, Southwest Medical University, Luzhou, Sichuan, China
| | - Jun Zhou
- Department of Anesthesiology, Southwest Medical University, Luzhou, China
- Anesthesiology and Critical Care Medicine Key Laboratory of Luzhou, Luzhou, China
- Department of Anesthesiology, The Affiliated Hospital, Southwest Medical University, Luzhou, Sichuan, China
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Zhou F, Quan J, Ruan D, Qiu Y, Ding R, Xu C, Ye Y, Cai G, Liu L, Zhang Z, Yang J, Wu Z, Zheng E. Identification of Candidate Genes for Economically Important Carcass Cutting in Commercial Pigs through GWAS. Animals (Basel) 2023; 13:3243. [PMID: 37893967 PMCID: PMC10603759 DOI: 10.3390/ani13203243] [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: 09/12/2023] [Revised: 10/08/2023] [Accepted: 10/16/2023] [Indexed: 10/29/2023] Open
Abstract
During the process of pork production, the carcasses of pigs are divided and sold, which provides better economic benefits and market competitiveness for pork production than selling the carcass as a whole. Due to the significant cost of post-slaughter phenotypic measurement, the genetic architecture of tenderloin weight (TLNW) and rib weight (RIBW)-important components of pig carcass economic value-remain unknown. In this study, we conducted genome-wide association studies (GWAS) for TLNW and RIBW traits in a population of 431 Duroc × Landrace × Yorkshire (DLY) pigs. In our study, the most significant single nucleotide polymorphism (SNP) associated with TLNW was identified as ASGA0085853 (3.28 Mb) on Sus scrofa chromosome 12 (SSC12), while for RIBW, it was Affx-1115046258 (172.45 Mb) on SSC13. Through haplotype block analysis, we discovered a novel quantitative trait locus (QTL) associated with TLNW, spanning a 5 kb region on SSC12, and a novel RIBW-associated QTL spanning 1.42 Mb on SSC13. Furthermore, we hypothesized that three candidate genes, TIMP2 and EML1, and SMN1, are associated with TLNW and RIBW, respectively. Our research not only addresses the knowledge gap regarding TLNW, but also serves as a valuable reference for studying RIBW. The identified SNP loci strongly associated with TLNW and RIBW may prove useful for marker-assisted selection in pig breeding programs.
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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, Guangzhou 510642, China; (F.Z.); (J.Q.); (D.R.); (Y.Q.); (R.D.); (C.X.); (Y.Y.); (G.C.); (L.L.); (Z.Z.); (J.Y.)
| | - Jianping Quan
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou 510642, China; (F.Z.); (J.Q.); (D.R.); (Y.Q.); (R.D.); (C.X.); (Y.Y.); (G.C.); (L.L.); (Z.Z.); (J.Y.)
| | - Donglin Ruan
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou 510642, China; (F.Z.); (J.Q.); (D.R.); (Y.Q.); (R.D.); (C.X.); (Y.Y.); (G.C.); (L.L.); (Z.Z.); (J.Y.)
| | - Yibin Qiu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou 510642, China; (F.Z.); (J.Q.); (D.R.); (Y.Q.); (R.D.); (C.X.); (Y.Y.); (G.C.); (L.L.); (Z.Z.); (J.Y.)
| | - Rongrong Ding
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou 510642, China; (F.Z.); (J.Q.); (D.R.); (Y.Q.); (R.D.); (C.X.); (Y.Y.); (G.C.); (L.L.); (Z.Z.); (J.Y.)
| | - Cineng Xu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou 510642, China; (F.Z.); (J.Q.); (D.R.); (Y.Q.); (R.D.); (C.X.); (Y.Y.); (G.C.); (L.L.); (Z.Z.); (J.Y.)
| | - Yong Ye
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou 510642, China; (F.Z.); (J.Q.); (D.R.); (Y.Q.); (R.D.); (C.X.); (Y.Y.); (G.C.); (L.L.); (Z.Z.); (J.Y.)
| | - Gengyuan Cai
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou 510642, China; (F.Z.); (J.Q.); (D.R.); (Y.Q.); (R.D.); (C.X.); (Y.Y.); (G.C.); (L.L.); (Z.Z.); (J.Y.)
- Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, South China Agricultural University, Guangzhou 510642, China
- Guangdong Zhongxin Breeding Technology Co., Ltd., Guangzhou 510642, China
| | - Langqing Liu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou 510642, China; (F.Z.); (J.Q.); (D.R.); (Y.Q.); (R.D.); (C.X.); (Y.Y.); (G.C.); (L.L.); (Z.Z.); (J.Y.)
| | - Zebin Zhang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou 510642, China; (F.Z.); (J.Q.); (D.R.); (Y.Q.); (R.D.); (C.X.); (Y.Y.); (G.C.); (L.L.); (Z.Z.); (J.Y.)
| | - Jie Yang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou 510642, China; (F.Z.); (J.Q.); (D.R.); (Y.Q.); (R.D.); (C.X.); (Y.Y.); (G.C.); (L.L.); (Z.Z.); (J.Y.)
- Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, South China Agricultural University, Guangzhou 510642, China
| | - Zhenfang Wu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou 510642, China; (F.Z.); (J.Q.); (D.R.); (Y.Q.); (R.D.); (C.X.); (Y.Y.); (G.C.); (L.L.); (Z.Z.); (J.Y.)
- Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, South China Agricultural University, Guangzhou 510642, China
- Guangdong Zhongxin Breeding Technology Co., Ltd., Guangzhou 510642, China
- Yunfu Subcenter of Guangdong Laboratory for Lingnan Modern Agriculture, Yunfu 527400, China
| | - Enqin Zheng
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou 510642, China; (F.Z.); (J.Q.); (D.R.); (Y.Q.); (R.D.); (C.X.); (Y.Y.); (G.C.); (L.L.); (Z.Z.); (J.Y.)
- Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, South China Agricultural University, Guangzhou 510642, China
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9
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Zapata RC, Zhang D, Yoon D, Nasamran CA, Chilin-Fuentes DR, Libster A, Chaudry BS, Lopez-Valencia M, Ponnalagu D, Singh H, Petrascheck M, Osborn O. Targeting Clic1 for the treatment of obesity: A novel therapeutic strategy to reduce food intake and body weight. Mol Metab 2023; 76:101794. [PMID: 37604246 PMCID: PMC10480059 DOI: 10.1016/j.molmet.2023.101794] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/01/2023] [Revised: 08/13/2023] [Accepted: 08/17/2023] [Indexed: 08/23/2023] Open
Abstract
OBJECTIVE Despite great advances in obesity therapeutics in recent years, there is still a need to identify additional therapeutic targets for the treatment of this disease. We previously discovered a signature of genes, including Chloride intracellular channel 1 (Clic1), whose expression was associated with drug-induced weight gain, and in these studies, we assess the effect of Clic1 inhibition on food intake and body weight in mice. METHODS We studied the impact of Clic1 inhibition in mouse models of binge-eating, diet-induced obese mice and genetic models of obesity (Magel2 KO mice). RESULTS Clic1 knockout (KO) mice ate significantly less and had a lower body weight than WT littermates when either fed chow or high fat diet. Furthermore, pharmacological inhibition of Clic1 in diet-induced obese mice resulted in suppression of food intake and promoted highly efficacious weight loss. Clic1 inhibition also reduced food intake in binge-eating models and hyperphagic Magel2 KO mice. We observed that chronic obesity resulted in a significant change in subcellular localization of Clic1 with an increased ratio of Clic1 in the membrane in the obese state. These observations provide a novel therapeutic strategy to block Clic1 translocation as a potential mechanism to reduce food intake and lower body weight. CONCLUSIONS These studies attribute a novel role of Clic1 as a driver of food intake and overconsumption. In summary, we have identified hypothalamic expression of Clic1 plays a key role in food intake, providing a novel therapeutic target to treat overconsumption that is the root cause of modern obesity.
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Affiliation(s)
- Rizaldy C Zapata
- Division of Endocrinology and Metabolism, School of Medicine, University of California San Diego, La Jolla, CA, 92093, USA
| | - Dinghong Zhang
- Division of Endocrinology and Metabolism, School of Medicine, University of California San Diego, La Jolla, CA, 92093, USA
| | - Dongmin Yoon
- Division of Endocrinology and Metabolism, School of Medicine, University of California San Diego, La Jolla, CA, 92093, USA
| | - Chanond A Nasamran
- Center for Computational Biology & Bioinformatics, Department of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Daisy R Chilin-Fuentes
- Center for Computational Biology & Bioinformatics, Department of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Avraham Libster
- Division of Endocrinology and Metabolism, School of Medicine, University of California San Diego, La Jolla, CA, 92093, USA
| | - Besma S Chaudry
- Division of Endocrinology and Metabolism, School of Medicine, University of California San Diego, La Jolla, CA, 92093, USA
| | - Mariela Lopez-Valencia
- Division of Endocrinology and Metabolism, School of Medicine, University of California San Diego, La Jolla, CA, 92093, USA
| | - Devasena Ponnalagu
- Department of Physiology and Cell Biology, The Ohio State University, Columbus, OH, USA; Dorothy M. Davis Heart and Lung Research Institute, The Ohio State University, Columbus, OH, USA
| | - Harpreet Singh
- Department of Physiology and Cell Biology, The Ohio State University, Columbus, OH, USA; Dorothy M. Davis Heart and Lung Research Institute, The Ohio State University, Columbus, OH, USA
| | - Michael Petrascheck
- Department of Molecular Medicine, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA, 92037, USA; Department of Neuroscience, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA, 92037, USA
| | - Olivia Osborn
- Division of Endocrinology and Metabolism, School of Medicine, University of California San Diego, La Jolla, CA, 92093, USA.
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10
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Xie Z, Gan M, Du J, Du G, Luo Y, Liu B, Zhu K, Cheng W, Chen L, Zhao Y, Niu L, Wang Y, Wang J, Zhu L, Shen L. Comparison of Growth Performance and Plasma Metabolomics between Two Sire-Breeds of Pigs in China. Genes (Basel) 2023; 14:1706. [PMID: 37761845 PMCID: PMC10531030 DOI: 10.3390/genes14091706] [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: 07/27/2023] [Revised: 08/22/2023] [Accepted: 08/25/2023] [Indexed: 09/29/2023] Open
Abstract
The Yorkshire pigs, renowned for their remarkable growth rate, low feed conversion ratio (FCR), and high meat production, emerge as a novel preference for paternal breeding. In this study, we found that purebred paternal Yorkshire pigs (PY) surpass the purebred Duroc breed in terms of growth rate. Specifically, purebred PY attain a weight of 100 kg at an earlier age compared to purebred Duroc (Male, 145.07 vs. 162.91; Female, 145.91 vs. 167.57; p-value < 0.01). Furthermore, different hybrid combinations suggest that offspring involving purebred PY exhibit superior growth performance. Compared with purebred Duroc, the offspring of purebred PY have an earlier age in days (173.23 vs. 183.54; p-value < 0.05) at the same slaughter weight. The changes of plasma metabolites of 60-day-old purebred boars in the two sire-breeds showed that 1335 metabolites in plasma were detected. Compared with Duroc, 28 metabolites were down-regulated and 49 metabolites were up-regulated in PY. Principal component analysis (PCA) discerned notable dissimilarities in plasma metabolites between the two sire-breeds of pigs. The levels of glycerol 3-phosphate choline, cytidine, guanine, and arachidonic acid increased significantly (p-value < 0.05), exerting an impact on their growth and development. According to our results, PY could be a new paternal option as a terminal sire in three-way cross system.
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Affiliation(s)
- Zhongwei Xie
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu 611130, China; (Z.X.); (M.G.)
- Key Laboratory of Livestock and Poultry Multi-Omics, Ministry of Agriculture and Rural Affairs, College of Animal and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Mailin Gan
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu 611130, China; (Z.X.); (M.G.)
- Key Laboratory of Livestock and Poultry Multi-Omics, Ministry of Agriculture and Rural Affairs, College of Animal and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Junhua Du
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu 611130, China; (Z.X.); (M.G.)
- Key Laboratory of Livestock and Poultry Multi-Omics, Ministry of Agriculture and Rural Affairs, College of Animal and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Gao Du
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu 611130, China; (Z.X.); (M.G.)
- Key Laboratory of Livestock and Poultry Multi-Omics, Ministry of Agriculture and Rural Affairs, College of Animal and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Yi Luo
- Sichuan Dekon Livestock Foodstuff Group, Chengdu 610200, China
| | - Bin Liu
- Sichuan Dekon Livestock Foodstuff Group, Chengdu 610200, China
| | - Kangping Zhu
- Sichuan Dekon Livestock Foodstuff Group, Chengdu 610200, China
| | - Wenqiang Cheng
- National Animal Husbandry Service, Beijing 100125, China
| | - Lei Chen
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu 611130, China; (Z.X.); (M.G.)
- Key Laboratory of Livestock and Poultry Multi-Omics, Ministry of Agriculture and Rural Affairs, College of Animal and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Ye Zhao
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu 611130, China; (Z.X.); (M.G.)
- Key Laboratory of Livestock and Poultry Multi-Omics, Ministry of Agriculture and Rural Affairs, College of Animal and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Lili Niu
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu 611130, China; (Z.X.); (M.G.)
- Key Laboratory of Livestock and Poultry Multi-Omics, Ministry of Agriculture and Rural Affairs, College of Animal and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Yan Wang
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu 611130, China; (Z.X.); (M.G.)
- Key Laboratory of Livestock and Poultry Multi-Omics, Ministry of Agriculture and Rural Affairs, College of Animal and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Jingyong Wang
- Chongqing Academy of Animal Science, Chongqing 402460, China
| | - Li Zhu
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu 611130, China; (Z.X.); (M.G.)
- Key Laboratory of Livestock and Poultry Multi-Omics, Ministry of Agriculture and Rural Affairs, College of Animal and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Linyuan Shen
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu 611130, China; (Z.X.); (M.G.)
- Key Laboratory of Livestock and Poultry Multi-Omics, Ministry of Agriculture and Rural Affairs, College of Animal and Technology, Sichuan Agricultural University, Chengdu 611130, China
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11
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Jourshari MG, Shadparvar AA, Ghavi Hossein-Zadeh N, Rafeie F, Banabazi MH, Johansson AM. Genome-wide association study on abdomen depth, head width, hip width, and withers height in native cattle of Guilan (Bos indicus). PLoS One 2023; 18:e0289612. [PMID: 37595009 PMCID: PMC10437930 DOI: 10.1371/journal.pone.0289612] [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: 03/11/2023] [Accepted: 07/22/2023] [Indexed: 08/20/2023] Open
Abstract
Native breeds in any country are a national capital, and their preservation is of great importance. Native Cattle of Guilan (NCG) is one of the few pure native breeds in Iran and the West Asia region. During the last decade, NCG population has decreased by more than 40%. This study aimed to identify significant single nucleotide polymorphisms (SNPs) and candidate genes associated with meat production traits in NCG using a genome-wide association study (GWAS). The blood and hair samples were collected from 72 NCG individuals and genotyped using the Illumina Bovine SNP50 chip. The results of the genomic scan showed that several SNPs were associated with abdominal depth, head width, hip width, and withers height in NCG. Several candidate genes were identified, including multiple epidermal growth factor-like domains 11 (MEGF11), Methionine Sulfoxide Reductase A (MSRA), chondroitin sulfate synthase 3 (CHSY3), Cyclin-Dependent Kinase 7 (CDK7), and Parkin (PRKN) genes, which are involved in muscle growth, meat tenderness, differentiation of fat cells, fat metabolism, and adipogenesis. These genes can contribute to meat quantity and quality in NCG. This study provided valuable insights into the genetics of NCG and the identification of effective genes associated with meat production traits. The results of this study could be used for the preservation and sustainable use of this breed of native cattle, as an important genetic resource in Iran.
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Affiliation(s)
| | - Abdol Ahad Shadparvar
- Department of Animal Science, Faculty of Agricultural Sciences, University of Guilan, Rasht, Iran
| | | | - Farjad Rafeie
- Department of Agricultural Biotechnology, Faculty of Agricultural Sciences, University of Guilan, Rasht, Iran
| | - Mohammad Hossein Banabazi
- Department of Biotechnology, Animal Science Research Institute of IRAN (ASRI), Agricultural Research, Education & Extension Organization (AREEO), Karaj, Iran
- Department of Animal Breeding and Genetics (HGEN), Centre for Veterinary Medicine and Animal Science (VHC), Swedish University of Agricultural Sciences (SLU), Uppsala, Sweden
| | - Anna Maria Johansson
- Department of Animal Breeding and Genetics (HGEN), Centre for Veterinary Medicine and Animal Science (VHC), Swedish University of Agricultural Sciences (SLU), Uppsala, Sweden
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12
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Wang J, Yang H, Chen S, Li W, Yu J, Hu Z, Zhuo Y, Huang Q, Liu Z, Zhou L, Wu J, Wang Z, Guo F, Yun P, Wang X, Liu JF. Genome-wide association study reveals candidate genes for pollution excreta traits in pigs. Anim Genet 2023. [PMID: 37040927 DOI: 10.1111/age.13323] [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: 06/16/2022] [Revised: 11/13/2022] [Accepted: 03/18/2023] [Indexed: 04/13/2023]
Abstract
Excreta traits comprise a very important characteristic in breeding that have been neglected for a long time. With the growth of intensive pig farming, plenty of environment problems have been raised, and people have begun to pay attention to pig excreta behaviors from genetics and breeding perspectives. However, the genetic architecture of excreta traits remains unclear. To investigate the genetic architecture of excreta traits in pigs, eight excreta traits and feed conversion ratio (FCR) were analyzed in this study. We performed genome-wide association studies (GWASs) on 213 Yorkshire pigs and estimated genetic parameters for a total number of 290 pigs, comprising 213 Yorkshire, 52 Landrace and 25 Duroc. After analysis, eight and 22 genome-wide significant SNPs were detected for FCR and the eight excreta traits in single-trait GWASs separately, and 18 were detected in a multi-trait meta-analysis for excreta traits, six of which were detected in both the single-trait and the multi-trait GWAS. Eighty, 182 and 133 genes were detected within 1 Mb of the genome-wide significant SNPs for FCR, excreta traits and multi-trait meta-analysis, respectively. Five candidate genes (BCKDC, DBT, ANKRD7, SHPRH and HCRT) with biochemical and physiological effects relevant to feed efficiency and excreta traits might be interesting markers for future breeding. Meanwhile, functional enrichment analysis indicates that most of the significant pathways are associated with the glutathione catabolic process, DNA topological change and replication fork protection complex. This study reveals the architecture of excreta traits in commercial pigs and offers an opportunity for decreasing the pollution from excreta using genomic selection in pigs.
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Affiliation(s)
- Junjian Wang
- State Key Laboratory of animal Biotech Breeding, Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Huawei Yang
- Shenzhen Kingsino Technology Co., Ltd., 518107, Shenzhen, No.18 Guangdian North Rd, High-Tech Industrial Park, Guangming District, China
| | - Shaokang Chen
- Beijing General Station of Animal Husbandry, 100107, Beijing, China
| | - Weining Li
- State Key Laboratory of animal Biotech Breeding, Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Jian Yu
- State Key Laboratory of animal Biotech Breeding, Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Zhengzheng Hu
- State Key Laboratory of animal Biotech Breeding, Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Yue Zhuo
- State Key Laboratory of animal Biotech Breeding, Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Qianqian Huang
- State Key Laboratory of animal Biotech Breeding, Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Zhen Liu
- State Key Laboratory of animal Biotech Breeding, Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Lei Zhou
- State Key Laboratory of animal Biotech Breeding, Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Jianliang Wu
- Beijing Zhongyu Pig Breeding Co. Ltd., 100194, Beijing, China
| | - Zhaojun Wang
- Beijing Zhongyu Pig Breeding Co. Ltd., 100194, Beijing, China
| | - Feng Guo
- Beijing General Station of Animal Husbandry, 100107, Beijing, China
| | - Peng Yun
- Beijing General Station of Animal Husbandry, 100107, Beijing, China
| | - Xiaofeng Wang
- Beijing General Station of Animal Husbandry, 100107, Beijing, China
| | - Jian-Feng Liu
- State Key Laboratory of animal Biotech Breeding, Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture, College of Animal Science and Technology, China Agricultural University, Beijing, China
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13
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Cheng Y, Ding S, Azad MAK, Song B, Kong X. Small Intestinal Digestive Functions and Feed Efficiency Differ in Different Pig Breeds. Animals (Basel) 2023; 13:ani13071172. [PMID: 37048428 PMCID: PMC10093237 DOI: 10.3390/ani13071172] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Revised: 03/17/2023] [Accepted: 03/23/2023] [Indexed: 03/29/2023] Open
Abstract
Small intestinal growth and health affect its digestion and absorption ability, while little information exists about the small intestinal morphology and function differences among the different pig breeds. Therefore, 90 healthy 35 days of age Taoyuan black (TB), Xiangcun black (XB), and Duroc (DR) pigs (30 pigs per breed) with similar body weight (BW) of the same breed were reared to 185 days of age to evaluate the potential relationship between feed efficiency and small intestinal morphology and function at 80, 125, and 185 days of age. The results show that the TB and XB pigs had lower initial and final BW, ADG, and ADFI and plasma CHO and LDL-C levels, whereas they had higher plasma LIP levels and jejunal trypsin, invertase, lactase, and maltase activities and higher DM, ADF, Tyr, Arg, and His digestibility at 80 days of age compared with the DR pigs. At 125 days of age, TB and XB pigs had lower apparent total tract digestibility and plasma CHO, HDL-C, LDL-C, and NH3 levels; XB pigs had lower DM and NDF digestibility, and TB pigs had higher jejunal lactase and maltase activities. At 185 days of age, TB and XB pigs had lower DM, EE, ADF, and GE digestibility, while having higher plasma ALT and UN levels; TB pigs had higher plasma AST level and jejunal chymase activity. Furthermore, the plasma free amino acid contents, small intestinal VH, and nutrient transporter expression levels differed at different ages. Therefore, the different pig breeds exhibited significantly different growth performance and small intestinal growth, mainly resulting from the differences in digestive enzymes and nutrient transporters in the small intestine.
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14
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Zeng H, Zhong Z, Xu Z, Teng J, Wei C, Chen Z, Zhang W, Ding X, Li J, Zhang Z. Meta-analysis of genome-wide association studies uncovers shared candidate genes across breeds for pig fatness trait. BMC Genomics 2022; 23:786. [DOI: 10.1186/s12864-022-09036-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Accepted: 11/22/2022] [Indexed: 12/02/2022] Open
Abstract
Abstract
Background
Average backfat thickness (BFT) is a critical complex trait in pig and an important indicator for fat deposition and lean rate. Usually, genome-wide association study (GWAS) was used to discover quantitative trait loci (QTLs) of BFT in a single population. However, the power of GWAS is limited by sample size in a single population. Alternatively, meta-analysis of GWAS (metaGWAS) is an attractive method to increase the statistical power by integrating data from multiple breeds and populations. The aim of this study is to identify shared genetic characterization of BFT across breeds in pigs via metaGWAS.
Results
In this study, we performed metaGWAS on BFT using 15,353 pigs (5,143 Duroc, 7,275 Yorkshire, and 2,935 Landrace) from 19 populations. We detected 40 genome-wide significant SNPs (Bonferroni corrected P < 0.05) and defined five breed-shared QTLs in across-breed metaGWAS. Markers within the five QTL regions explained 7 ~ 9% additive genetic variance and showed strong heritability enrichment. Furthermore, by integrating information from multiple bioinformatics databases, we annotated 46 candidate genes located in the five QTLs. Among them, three important (MC4R, PPARD, and SLC27A1) and seven suggestive candidate genes (PHLPP1, NUDT3, ILRUN, RELCH, KCNQ5, ITPR3, and U3) were identified.
Conclusion
QTLs and candidate genes underlying BFT across breeds were identified via metaGWAS from multiple populations. Our findings contribute to the understanding of the genetic architecture of BFT and the regulating mechanism underlying fat deposition in pigs.
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15
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Li H, Xu C, Meng F, Yao Z, Fan Z, Yang Y, Meng X, Zhan Y, Sun Y, Ma F, Yang J, Yang M, Yang J, Wu Z, Cai G, Zheng E. Genome-Wide Association Studies for Flesh Color and Intramuscular Fat in (Duroc × Landrace × Large White) Crossbred Commercial Pigs. Genes (Basel) 2022; 13:2131. [PMID: 36421806 PMCID: PMC9690869 DOI: 10.3390/genes13112131] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2022] [Revised: 11/12/2022] [Accepted: 11/12/2022] [Indexed: 07/30/2023] Open
Abstract
The intuitive impression of pork is extremely important in terms of whether consumers are enthusiastic about purchasing it. Flesh color and intramuscular fat (IMF) are indispensable indicators in meat quality assessment. In this study, we determined the flesh color and intramuscular fat at 45 min and 12 h after slaughter (45 mFC, 45 mIMF, 12 hFC, and 12 hIMF) of 1518 commercial Duroc × Landrace × Large White (DLY) pigs. We performed a single nucleotide polymorphism (SNP) genome-wide association study (GWAS) analysis with 28,066 SNPs. This experiment found that the correlation between 45 mFC and 12 hFC was 0.343. The correlation between 45 mIMF and 12 hIMF was 0.238. The heritability of the traits 45 mFC, 12 hFC, 45 mIMF, and 12 hIMF was 0.112, 0.217, 0.139, and 0.178, respectively, and we identified seven SNPs for flesh color and three SNPs for IMF. Finally, several candidate genes regulating these four traits were identified. Three candidate genes related to flesh color were provided: SNCAIP and PRR16 on SSC2, ST3GAL4 on SSC5, and GALR1 on SSC1. A total of three candidate genes related to intramuscular fat were found, including ABLIM3 on SSC2, DPH5 on SSC4, and DOCK10 on SSC15. Furthermore, GO and KEGG analysis revealed that these genes are involved in the regulation of apoptosis and are implicated in functions such as pigmentation and skeletal muscle metabolism. This study applied GWAS to analyze the scoring results of flesh color and IMF in different time periods, and it further revealed the genetic structure of flesh color and IMF traits, which may provide important genetic loci for the subsequent improvement of pig meat quality traits.
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Affiliation(s)
- Hao Li
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou 510642, China
- State Key Laboratory of Livestock and Poultry Breeding, Guangdong Key Laboratory of Animal Breeding and Nutrition, Institute of Animal Science, Guangdong Academy of Agricultural Sciences, Guangzhou 510640, China
| | - Cineng Xu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou 510642, China
| | - Fanming Meng
- State Key Laboratory of Livestock and Poultry Breeding, Guangdong Key Laboratory of Animal Breeding and Nutrition, Institute of Animal Science, Guangdong Academy of Agricultural Sciences, Guangzhou 510640, China
| | - Zekai Yao
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou 510642, China
- State Key Laboratory of Livestock and Poultry Breeding, Guangdong Key Laboratory of Animal Breeding and Nutrition, Institute of Animal Science, Guangdong Academy of Agricultural Sciences, Guangzhou 510640, China
| | - Zhenfei Fan
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou 510642, China
| | - Yingshan Yang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou 510642, China
| | - Xianglun Meng
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou 510642, China
| | - Yuexin Zhan
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou 510642, China
| | - Ying Sun
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou 510642, China
| | - Fucai Ma
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou 510642, China
| | - Jifei Yang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou 510642, China
| | - Ming Yang
- College of Animal Science and Technology, Zhongkai University of Agriculture and Engineering, Guangzhou 510225, China
| | - Jie Yang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, 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
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, 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
| | - Gengyuan Cai
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, 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
| | - Enqin Zheng
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou 510642, China
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16
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Wang Z, He Y, Tan Z. Transcription Analysis of Liver and Muscle Tissues from Landrace Finishing Pigs with Different Feed Conversion Ratios. Genes (Basel) 2022; 13:2067. [PMID: 36360304 PMCID: PMC9690258 DOI: 10.3390/genes13112067] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Revised: 10/30/2022] [Accepted: 10/31/2022] [Indexed: 10/29/2023] Open
Abstract
The efficiency of feed utilization determines the cost and economic benefits of pig production. In the present study, two pairs of full-sibling and two pairs of half-sibling female Landrace finishing pigs were selected, with each pair including individuals with different feed conversion rates, with liver and longissimus muscle tissue samples collected from each group for transcriptome analysis. A total of 561 differentially expressed genes (DEGs), among which 224 were up-regulated and 337 were down-regulated, were detected in the liver transcriptomes in the high-feed efficiency group compared to the low-feed efficiency group. The DEGs related to phosphorus and phosphate metabolism, arginine biosynthesis, chemical carcinogenesis, cytokine-cytokine receptor interaction, the biosynthesis of amino acids, and drug metabolism-cytochrome P450 in liver tissue were also associated with feed efficiency. In total, 215 DEGs were screened in the longissimus muscle tissue and were mainly related to disease and immune regulation, including complement and coagulation cascades, systemic lupus erythematosus, and prion diseases. The combination of gene expression and functional annotation results led to the identification of candidate feed efficiency-related biomarkers, such as ARG1, ARG2, GOT1, GPT2, ACAA2, ACADM, and ANGPTL4, members of cytochrome P450 family, and complement component family genes. Although the novel feed efficiency-related candidate genes need to be further evaluated by a larger sample size and functional studies, the present study identifies novel candidate biomarkers for the identification of functional SNPs underlying porcine feed efficiency.
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Affiliation(s)
| | | | - Zhen Tan
- School of Animal Science and Technology, Hainan University, Haikou 570228, China
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17
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Ding R, Zhuang Z, Qiu Y, Wang X, Wu J, Zhou S, Ruan D, Xu C, Hong L, Gu T, Zheng E, Cai G, Huang W, Wu Z, Yang J. A composite strategy of genome-wide association study and copy number variation analysis for carcass traits in a Duroc pig population. BMC Genomics 2022; 23:590. [PMID: 35964005 PMCID: PMC9375371 DOI: 10.1186/s12864-022-08804-1] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Accepted: 07/31/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Carcass traits are important in pig breeding programs for improving pork production. Understanding the genetic variants underlies complex phenotypes can help explain trait variation in pigs. In this study, we integrated a weighted single-step genome-wide association study (wssGWAS) and copy number variation (CNV) analyses to map genetic variations and genes associated with loin muscle area (LMA), loin muscle depth (LMD) and lean meat percentage (LMP) in Duroc pigs. RESULTS Firstly, we performed a genome-wide analysis for CNV detection using GeneSeek Porcine SNP50 Bead chip data of 3770 pigs. A total of 11,100 CNVs were detected, which were aggregated by overlapping 695 CNV regions (CNVRs). Next, we investigated CNVs of pigs from the same population by whole-genome resequencing. A genome-wide analysis of 21 pigs revealed 23,856 CNVRs that were further divided into three categories (851 gain, 22,279 loss, and 726 mixed), which covered 190.8 Mb (~ 8.42%) of the pig autosomal genome. Further, the identified CNVRs were used to determine an overall validation rate of 68.5% for the CNV detection accuracy of chip data. CNVR association analyses identified one CNVR associated with LMA, one with LMD and eight with LMP after applying stringent Bonferroni correction. The wssGWAS identified eight, six and five regions explaining more than 1% of the additive genetic variance for LMA, LMD and LMP, respectively. The CNVR analyses and wssGWAS identified five common regions, of which three regions were associated with LMA and two with LMP. Four genes (DOK7, ARAP1, ELMO2 and SLC13A3) were highlighted as promising candidates according to their function. CONCLUSIONS We determined an overall validation rate for the CNV detection accuracy of low-density chip data and constructed a genomic CNV map for Duroc pigs using resequencing, thereby proving a value genetic variation resource for pig genome research. Furthermore, our study utilized a composite genetic strategy for complex traits in pigs, which will contribute to the study for elucidating the genetic architecture that may be influenced and regulated by multiple forms of variations.
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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, 527439, P.R. China.,Lingnan Guangdong Laboratory of Modern Agriculture, Guangzhou, 510642, 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.,Lingnan Guangdong Laboratory of Modern Agriculture, Guangzhou, 510642, 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.,Lingnan Guangdong Laboratory of Modern Agriculture, Guangzhou, 510642, China
| | - Xingwang Wang
- 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.,Lingnan Guangdong Laboratory of Modern Agriculture, Guangzhou, 510642, 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.,Lingnan Guangdong Laboratory of Modern Agriculture, Guangzhou, 510642, 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.,Lingnan Guangdong Laboratory of Modern Agriculture, Guangzhou, 510642, China
| | - Cineng Xu
- 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, China
| | - Linjun Hong
- 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, China
| | - Ting Gu
- 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, 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, 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.,Lingnan Guangdong Laboratory of Modern Agriculture, Guangzhou, 510642, 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. .,Lingnan Guangdong Laboratory of Modern Agriculture, Guangzhou, 510642, 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, China.
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18
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Genome-Wide Association Analysis and Genetic Parameters for Feed Efficiency and Related Traits in Yorkshire and Duroc Pigs. Animals (Basel) 2022; 12:ani12151902. [PMID: 35892552 PMCID: PMC9329986 DOI: 10.3390/ani12151902] [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: 05/24/2022] [Revised: 07/04/2022] [Accepted: 07/20/2022] [Indexed: 11/17/2022] Open
Abstract
Simple Summary Genetic improvements in feed efficiency (FE) and related traits could considerably reduce pig production costs and energy consumption. Thus, we performed a genetic parameter estimation and genome-wide association study of four FE and FE-related traits, namely, average daily feed intake, average daily gain, the feed conversion ratio, and residual feed intake, of two pig breeds, Yorkshire and Duroc. The results demonstrate the genetic relationships of FE and FE-related traits with two growth traits, age and backfat thickness at 100 kg. We also identified many single-nucleotide polymorphisms (SNPs) and novel candidate genes related to these traits. In addition, we found many pathways significantly associated with FE and FE-related traits, and they are generally involved in digestive and metabolic processes. The results of this study are expected to provide a valuable reference for the genomic selection of FE and FE-related traits in pigs. Abstract Feed efficiency (FE) traits are key factors that can influence the economic benefits of pig production. However, little is known about the genetic architecture of FE and FE-related traits. This study aimed to identify SNPs and candidate genes associated with FE and FE-related traits, namely, average daily feed intake (ADFI), average daily gain (ADG), the feed conversion ratio (FCR), and residual feed intake (RFI). The phenotypes of 5823 boars with genotyped data (50 K BeadChip) from 1365 boars from a nucleus farm were used to perform a genome-wide association study (GWAS) of two breeds, Duroc and Yorkshire. Moreover, we performed a genetic parameter estimation for four FE and FE-related traits. The heritabilities of the FE and FE-related traits ranged from 0.13 to 0.36, and there were significant genetic correlations (−0.69 to 0.52) of the FE and FE-related traits with two growth traits (age at 100 kg and backfat thickness at 100 kg). A total of 61 significant SNPs located on eight different chromosomes associated with the four FE and FE-related traits were identified. We further identified four regions associated with FE and FE-related traits that have not been previously reported, and they may be potential novel QTLs for FE. Considering their biological functions, we finally identified 35 candidate genes relevant for FE and FE-related traits, such as the widely reported MC4R and INSR genes. A gene enrichment analysis showed that FE and FE-related traits were highly enriched in the biosynthesis, digestion, and metabolism of biomolecules. This study deepens our understanding of the genetic mechanisms of FE in pigs and provides valuable information for using marker-assisted selection in pigs to improve FE.
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Davoudi P, Do DN, Colombo SM, Rathgeber B, Miar Y. Application of Genetic, Genomic and Biological Pathways in Improvement of Swine Feed Efficiency. Front Genet 2022; 13:903733. [PMID: 35754793 PMCID: PMC9220306 DOI: 10.3389/fgene.2022.903733] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Accepted: 05/20/2022] [Indexed: 12/24/2022] Open
Abstract
Despite the significant improvement of feed efficiency (FE) in pigs over the past decades, feed costs remain a major challenge for producers profitability. Improving FE is a top priority for the global swine industry. A deeper understanding of the biology underlying FE is crucial for making progress in genetic improvement of FE traits. This review comprehensively discusses the topics related to the FE in pigs including: measurements, genetics, genomics, biological pathways and the advanced technologies and methods involved in FE improvement. We first provide an update of heritability for different FE indicators and then characterize the correlations of FE traits with other economically important traits. Moreover, we present the quantitative trait loci (QTL) and possible candidate genes associated with FE in pigs and outline the most important biological pathways related to the FE traits in pigs. Finally, we present possible ways to improve FE in swine including the implementation of genomic selection, new technologies for measuring the FE traits, and the potential use of genome editing and omics technologies.
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Affiliation(s)
- Pourya Davoudi
- Department of Animal Science and Aquaculture, Dalhousie University, Truro, NS, Canada
| | - Duy Ngoc Do
- Department of Animal Science and Aquaculture, Dalhousie University, Truro, NS, Canada
| | - Stefanie M Colombo
- Department of Animal Science and Aquaculture, Dalhousie University, Truro, NS, Canada
| | - Bruce Rathgeber
- Department of Animal Science and Aquaculture, Dalhousie University, Truro, NS, Canada
| | - Younes Miar
- Department of Animal Science and Aquaculture, Dalhousie University, Truro, NS, Canada
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20
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Chang Wu Z, Wang Y, Huang X, Wu S, Bao W. A genome-wide association study of important reproduction traits in large white pigs. Gene 2022; 838:146702. [PMID: 35772658 DOI: 10.1016/j.gene.2022.146702] [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: 01/25/2022] [Revised: 06/13/2022] [Accepted: 06/24/2022] [Indexed: 11/04/2022]
Abstract
Augmenting the reproductive efficiency of sows remains the predominant challenge in the swine industry. This work was aimed at scrutinizing vital genetic markers for reproductive traits in this animal. This entailed probing of the records of vital attributes of Large White pigs (n = 695) inclusive of the total number of born (TNB), number of born alive (NBA), number of weaned pigs (NWP), number of healthy births (NHS), total litter weight of piglets born alive (BALWT), weaning litter weight (WNWT), and corrected litter weight at 21 days (W21). A genome-wide association study (GWAS) for the four litter traits and three traits of litter weight in the Denmark Large White population then ensued. We discovered seven significantly related SNPs and eleven potential candidate genes (e.g., TUSC3, THRB for TNB; STT3B for NBA). The subsequent functional enrichment analysis of these genes showed that the significant gene were associated with steroid hormone receptor activity. Our findings indicated that the genes TUSC3, THRB and STT3B probably contribute to litter traits in this population. This work reveals genetic mechanisms of reproduction traits and also supports ensuing genetic improvement employing marker-assisted selection in Large White pigs.
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Affiliation(s)
- Zheng Chang Wu
- College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, P. R. China; College of Veterinary Medicine, Yangzhou University, Yangzhou 225009, P. R. China.
| | - Yifu Wang
- College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, P. R. China.
| | - Xiaoguo Huang
- Jiangsu Engineering Research Centre for Molecular Breeding of Pig, Changzhou 215000, Jiangsu Province, China.
| | - Shenglong Wu
- College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, P. R. China.
| | - Wenbin Bao
- College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, P. R. China.
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21
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Waters DL, Clark SA, Moghaddar N, van der Werf JH. Genomic analysis of the slope of the reaction norm for body weight in Australian sheep. Genet Sel Evol 2022; 54:40. [PMID: 35659541 PMCID: PMC9164502 DOI: 10.1186/s12711-022-00734-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Accepted: 05/20/2022] [Indexed: 11/23/2022] Open
Abstract
Background Selection of livestock based on their robustness or sensitivity to environmental variation could help improve the efficiency of production systems, particularly in the light of climate change. Genetic variation in robustness arises from genotype-by-environment (G × E) interactions, with genotypes performing differently when animals are raised in contrasted environments. Understanding the nature of this genetic variation is essential to implement strategies to improve robustness. In this study, our aim was to explore the genetics of robustness in Australian sheep to different growth environments using linear reaction norm models (RNM), with post-weaning weight records of 22,513 lambs and 60 k single nucleotide polymorphisms (SNPs). The use of scale-corrected genomic estimated breeding values (GEBV) for the slope to account for scale-type G × E interactions was also investigated. Results Additive genetic variance was observed for the slope of the RNM, with genetic correlations between low- and high-growth environments indicating substantial re-ranking of genotypes (0.44–0.49). The genetic variance increased from low- to high-growth environments. The heritability of post-weaning body weight ranged from 0.28 to 0.39. The genetic correlation between intercept and slope of the reaction norm for post-weaning body weight was low to moderate when based on the estimated (co)variance components but was much higher when based on back-solved SNP effects. An initial analysis suggested that a region on chromosome 11 affected both the intercept and the slope, but when the GEBV for the slope were conditioned on the GEBV for the intercept to remove the effect of scale-type G × E interactions on SNP effects for robustness, a single genomic region on chromosome 7 was found to be associated with robustness. This region included genes previously associated with growth traits and disease susceptibility in livestock. Conclusions This study shows a significant genetic variation in the slope of RNM that could be used for selecting for increased robustness of sheep. Both scale-type and rank-type G × E interactions contributed to variation in the slope. The correction for scale effects of GEBV for the slope should be considered when analysing robustness using RNM. Overall, robustness appears to be a highly polygenic trait. Supplementary Information The online version contains supplementary material available at 10.1186/s12711-022-00734-6.
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Affiliation(s)
- Dominic L Waters
- School of Environmental & Rural Science, University of New England, Armidale, NSW, 2351, Australia.
| | - Sam A Clark
- School of Environmental & Rural Science, University of New England, Armidale, NSW, 2351, Australia
| | - Nasir Moghaddar
- School of Environmental & Rural Science, University of New England, Armidale, NSW, 2351, Australia
| | - Julius H van der Werf
- School of Environmental & Rural Science, University of New England, Armidale, NSW, 2351, Australia
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22
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Wang K, Wang S, Ji X, Chen D, Shen Q, Yu Y, Xiao W, Wu P, Tang G. Genome-wide association studies identified loci associated with both feed conversion ratio and residual feed intake in Yorkshire pigs. Genome 2022; 65:405-412. [PMID: 35594567 DOI: 10.1139/gen-2021-0105] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
Feed occupies a significant proportion in the production cost of pigs, and the feed efficiency (FE) in pigs are of utmost economic importance. Hence, the objective of this study is to identify single nucleotide polymorphisms (SNPs) and candidate genes associated with FE related traits, including feed conversion ratio (FCR) and residual feed intake (RFI). A genome-wide association study (GWAS) was conducted for FCR and RFI in 169 Yorkshire pigs using whole-genome sequencing data. A total of 23 and 33 suggestive significant SNPs (P<1×10^(-6)) were detected for FCR and RFI, respectively. However, none of the SNPs achieved the genome-wide significance threshold (P<5×10^(-8)). Importantly, three common SNPs (SSC7:7987268, SSC13:42350250, and SSC13:42551718) were associated with both FCR and RFI. Additionally, the NEDD9 gene related to FCR and RFI traits was overlapped. This study detected novel SNPs on SSC7 and SSC13 common for FCR and RFI. These results provide new insights into the genetic mechanisms and candidate genes of FE-related traits in pigs.
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Affiliation(s)
- Kai Wang
- Sichuan Agricultural University, 12529, Chengdu, Sichuan, China;
| | - Shujie Wang
- Sichuan Agricultural University, 12529, Chengdu, Sichuan, China;
| | - Xiang Ji
- Sichuan Agricultural University, 12529, Chengdu, Sichuan, China;
| | - Dong Chen
- Sichuan Agricultural University, 12529, Chengdu, Sichuan, China;
| | - Qi Shen
- Sichuan Agricultural University, 12529, Chengdu, Sichuan, China;
| | - Yang Yu
- Sichuan Agricultural University, 12529, Chengdu, Sichuan, China;
| | - Weihang Xiao
- Sichuan Agricultural University, 12529, Yaan, Sichuan, China, 625014;
| | - Pingxian Wu
- Chongqing Academy of Animal Science, Chongqing, China, 402460;
| | - Guoqing Tang
- Sichuan Agricultural University, 12529, Yaan, Sichuan, China, 625014;
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23
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Zhou S, Ding R, Zhuang Z, Zeng H, Wen S, Ruan D, Wu J, Qiu Y, Zheng E, Cai G, Yang J, Wu Z, Yang M. Genome-Wide Association Analysis Reveals Genetic Loci and Candidate Genes for Chest, Abdominal, and Waist Circumferences in Two Duroc Pig Populations. Front Vet Sci 2022; 8:807003. [PMID: 35224076 PMCID: PMC8865076 DOI: 10.3389/fvets.2021.807003] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2021] [Accepted: 12/15/2021] [Indexed: 12/16/2022] Open
Abstract
Chest circumference (CC), abdominal circumference (AC), and waist circumference (WC) are regarded as important indicators for improving economic traits because they can reflect the growth and physiological status in pigs. However, the genetic architecture of CC, AC, and WC is still elusive. Here, we performed single-trait and multi-trait genome-wide association studies (GWASs) for CC, AC, and WC in 2,206 American origin Duroc (AOD) and 2,082 Canadian origin Duroc (COD) pigs. As a result, one novel quantitative trait locus (QTL) on Sus scrofa chromosome (SSC) one was associated with CC and AC in COD pigs, which spans 6.92 Mb (from 170.06 to 176.98 Mb). Moreover, multi-trait GWAS identified 21 significant SNPs associated with the three conformation traits, indicating the multi-trait GWAS is a powerful statistical approach that uncovers pleiotropic locus. Finally, the three candidate genes (ITGA11, TLE3, and GALC) were selected that may play a role in the conformation traits. Further bioinformatics analysis indicated that the candidate genes for the three conformation traits mainly participated in sphingolipid metabolism and lysosome pathways. For all we know, this study was the first GWAS for WC in pigs. In general, our findings further reveal the genetic architecture of CC, AC, and WC, which may offer a useful reference for improving the conformation traits in pigs.
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Affiliation(s)
- Shenping Zhou
- College of Animal Science and Technology, Zhongkai University of Agriculture and Engineering, Guangzhou, China
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
| | - Rongrong Ding
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
- Guangdong Wens Breeding Swine Technology Co., Ltd., Yunfu, China
| | - Zhanwei Zhuang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
| | - Haiyu Zeng
- Guangdong Wens Breeding Swine Technology Co., Ltd., Yunfu, China
| | - Shuxian Wen
- Guangdong Wens Breeding Swine Technology Co., Ltd., Yunfu, China
| | - Donglin Ruan
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
| | - Jie Wu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
| | - Yibin Qiu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
| | - Enqin Zheng
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
| | - Gengyuan Cai
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
- Guangdong Wens Breeding Swine Technology Co., Ltd., Yunfu, China
| | - Jie Yang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
| | - Zhenfang Wu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
- Guangdong Wens Breeding Swine Technology Co., Ltd., Yunfu, China
- *Correspondence: Zhenfang Wu
| | - Ming Yang
- College of Animal Science and Technology, Zhongkai University of Agriculture and Engineering, Guangzhou, China
- Ming Yang
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Zhao P, Wang C, Xia Y, Hu Y, Fang R, Zhao J. Seroprevalence Investigation of Classic Swine Fever Virus Before, During, and After African Swine Fever Virus Outbreak in Some Provinces of China from 2017 to 2021. Viral Immunol 2022; 35:33-40. [PMID: 35020503 DOI: 10.1089/vim.2021.0109] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Classic swine fever is a severe infectious and fatal disease in pigs caused by the classic swine fever virus (CSFV). Surveillance and investigation for CSFV seroprevalence contribute to knowing the immune efficiency of CSFV vaccines and reflect health status of swine herd, especially since the African swine fever virus (ASFV) outbreak in China in 2018. A total of 40,489 pig serum samples with related descriptive variables were obtained from 12 provinces and 2 cities of China from December 2017 to May 2021, covering before, during, and after three periods of ASFV outbreak. Pearson chi-square test and multivariable logistic regression analysis were used to identify impact factors related to variations in CSFV seroprevalence. Total CSFV seroprevalence was 60.40% (95% confidence interval: 59.92-60.88). Seroprevalence and antibody blocking rate mean of CSFV before outbreak of ASFV in China are higher and change gently compared with that after outbreak of ASFV. Serum collected from "summer and autumn," "north, southwest and northwest of China," "pig farm located in hill or mountain," " period before outbreak of ASFV," "PRRSV negative farm," and "replacement gilts, multiparous sows and boars" show high seroprevalence of CSFV. These results show trends in prevalence of CSFV antibody in recent years in China, especially when ASFV entered China. Identified impact factors provide references for improving immune efficiency of CSFV vaccine and benefit for prevention of CSFV.
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Affiliation(s)
- Pengfei Zhao
- State Key Laboratory of Agricultural Microbiology, College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, China
| | - Chaofei Wang
- State Key Laboratory of Agricultural Microbiology, College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, China
| | - Yingjun Xia
- State Key Laboratory of Agricultural Microbiology, College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, China
| | - Yanli Hu
- State Key Laboratory of Agricultural Microbiology, College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, China
| | - Rui Fang
- State Key Laboratory of Agricultural Microbiology, College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, China
| | - Junlong Zhao
- State Key Laboratory of Agricultural Microbiology, College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, China
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Xu C, Liu Z, Xiao J. Ferroptosis: A Double-Edged Sword in Gastrointestinal Disease. Int J Mol Sci 2021; 22:ijms222212403. [PMID: 34830285 PMCID: PMC8620748 DOI: 10.3390/ijms222212403] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Revised: 11/15/2021] [Accepted: 11/15/2021] [Indexed: 12/24/2022] Open
Abstract
Ferroptosis is a novel form of regulated cell death (RCD) that is typically accompanied by iron accumulation and lipid peroxidation. In contrast to apoptosis, autophagy, and necroptosis, ferroptosis has unique biological processes and pathophysiological characteristics. Since it was first proposed in 2012, ferroptosis has attracted attention worldwide. Ferroptosis is involved in the progression of multiple diseases and could be a novel therapeutic target in the future. Recently, tremendous progress has been made regarding ferroptosis and gastrointestinal diseases, including intestinal ischemia/reperfusion (I/R) injury, inflammatory bowel disease (IBD), gastric cancer (GC), and colorectal cancer (CRC). In this review, we summarize the recent progress on ferroptosis and its interaction with gastrointestinal diseases. Understanding the role of ferroptosis in gastrointestinal disease pathogenesis could provide novel therapeutic targets for clinical treatment.
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26
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Zhang H, Zhuang Z, Yang M, Ding R, Quan J, Zhou S, Gu T, Xu Z, Zheng E, Cai G, Yang J, Wu Z. Genome-Wide Detection of Genetic Loci and Candidate Genes for Body Conformation Traits in Duroc × Landrace × Yorkshire Crossbred Pigs. Front Genet 2021; 12:664343. [PMID: 34707635 PMCID: PMC8542986 DOI: 10.3389/fgene.2021.664343] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2021] [Accepted: 09/16/2021] [Indexed: 11/30/2022] Open
Abstract
The Duroc × (Landrace × Yorkshire) hybrid pigs (DLY) are the most popular commercial pigs, providing consumers with the largest source of pork. In order to gain more insights into the genetic architecture of economically important traits in pigs, we performed a genome-wide association study (GWAS) using the GeneSeek Porcine 50 K SNP Chip to map the genetic markers and genes associated with body conformation traits (BCT) in 311 DLY pigs. The quantitative traits analyzed included body weight (BW), carcass length (CL), body length (BL), body height (BH), and body mass index (BMI). BMI was defined as BMICL, BMIBL, and BMIBH, respectively, based on CL, BL, and BH phenotypic data. We identified 82 SNPs for the seven traits by GEMMA-based and FarmCPU-based GWASs. Both methods detected two quantitative trait loci (QTL) on SSC8 and SSC17 for body conformation traits. Several candidate genes (such as TNFAIP3, KDM4C, HSPG2, BMP2, PLCB4, and GRM5) were found to be associated with body weight and body conformation traits in pigs. Notably, the BMP2 gene had pleiotropic effects on CL, BL, BH, BMICL, and BMIBL and is proposed as a strong candidate gene for body size due to its involvement in growth and bone development. Furthermore, gene set enrichment analysis indicated that most of the pathway terms are associated with regulation of cell growth, negative regulation of cell population proliferation, and chondrocyte differentiation. We anticipate that these results further advance our understanding of the genetic architecture of body conformation traits in the popular commercial DLY pigs and provide new insights into the genetic architecture of BMI in pigs.
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Affiliation(s)
- Hui Zhang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, China
| | - Zhanwei Zhuang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, China
| | - Ming Yang
- College of Animal Science and Technology, Zhongkai University of Agriculture and Engineering, Guangdong, China
| | - Rongrong Ding
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, China
| | - Jianping Quan
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, China
| | - Shenping Zhou
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, China
| | - Ting Gu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, China
| | - Zheng Xu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, China
| | - Enqin Zheng
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, China
| | - Gengyuan Cai
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, China
| | - Jie Yang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, China
| | - Zhenfang Wu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, China
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27
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Cheng J, Putz AM, Harding JCS, Dyck MK, Fortin F, Plastow GS, Canada PG, Dekkers JCM. Genetic parameters of drinking and feeding traits of wean-to-finish pigs under a polymicrobial natural disease challenge. J Anim Sci Biotechnol 2021; 12:105. [PMID: 34493327 PMCID: PMC8425002 DOI: 10.1186/s40104-021-00622-x] [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: 02/16/2021] [Accepted: 07/16/2021] [Indexed: 11/17/2022] Open
Abstract
Background The pork industry faces unprecedented challenges from disease, which increases cost of production and use of antibiotics, and reduces production efficiency, carcass quality, and animal wellbeing. One solution is to improve the overall resilience of pigs to a broad array of common diseases through genetic selection. Behavioral changes in feeding and drinking are usually the very first clinical signs when animals are exposed to stressors such as disease. Changes in feeding and drinking behaviors in diseased pigs may reflect the way they cope with the challenge and, thus, could be used as indicator traits to select for disease resilience. The objectives of this study were to estimate genetic parameters of feeding and drinking traits for wean-to-finish pigs in a natural polymicrobial disease challenge model, to estimate genetic correlations of feeding and drinking traits with growth rate and clinical disease traits, and to develop indicator traits to select for disease resilience. Results In general, drinking traits had moderate to high estimates of heritability, especially average daily water dispensed, duration, and number of visits (0.44 to 0.58). Similar estimates were observed for corresponding feeding traits (0.35 to 0.51). Most genetic correlation estimates among drinking traits were moderate to high (0.30 to 0.92) and higher than among feeding traits (0 to 0.11). Compared to other drinking traits, water intake duration and number of visits had relatively stronger negative genetic correlation estimates with treatment rate and mortality, especially across the challenge nursery and finisher (− 0.39 and − 0.45 for treatment rate; − 0.20 and − 0.19 for mortality). Conclusion Most of the recorded drinking and feeding traits under a severe disease challenge had moderate to high estimates of heritability, especially for feed or water intake duration and number of visits. Phenotypic and genetic correlations among the recorded feeding traits under disease were generally low but drinking traits showed high correlations with each other. Water intake duration and number of visits are potential indicator traits to select for disease resilience because of their high heritability and had moderate genetic correlations with treatment and mortality rates under severe disease. Supplementary Information The online version contains supplementary material available at 10.1186/s40104-021-00622-x.
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Affiliation(s)
- Jian Cheng
- Department of Animal Science, Iowa State University, Ames, IA, 50011, USA
| | - Austin M Putz
- Department of Animal Science, Iowa State University, Ames, IA, 50011, USA.,Hendrix Genetics, Swine Business Unit, Boxmeer, The Netherlands, 5831, CK
| | - John C S Harding
- Department of Large Animal Clinical Science, University of Saskatchewan, Saskatoon, SK, S7N 5A2, Canada
| | - Michael K Dyck
- Department of Agriculture, Food and Nutritional Science, University of Alberta, Edmonton, AB, T6G 2R3, Canada
| | - Frederic Fortin
- Centre de Développement du Porc du Québec Inc., Québec City, G1V 4M6, Canada
| | - Graham S Plastow
- Department of Agriculture, Food and Nutritional Science, University of Alberta, Edmonton, AB, T6G 2R3, Canada
| | - Pig Gen Canada
- PigGen Canada Research Consortium, Guelph, Ontario, N1H4G8, Canada
| | - Jack C M Dekkers
- Department of Animal Science, Iowa State University, Ames, IA, 50011, USA.
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28
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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: 9] [Impact Index Per Article: 3.0] [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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Bus JD, Boumans IJ, Webb LE, Bokkers EA. The potential of feeding patterns to assess generic welfare in growing-finishing pigs. Appl Anim Behav Sci 2021. [DOI: 10.1016/j.applanim.2021.105383] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
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30
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Yang R, Guo X, Zhu D, Tan C, Bian C, Ren J, Huang Z, Zhao Y, Cai G, Liu D, Wu Z, Wang Y, Li N, Hu X. Accelerated deciphering of the genetic architecture of agricultural economic traits in pigs using a low-coverage whole-genome sequencing strategy. Gigascience 2021; 10:giab048. [PMID: 34282453 PMCID: PMC8290195 DOI: 10.1093/gigascience/giab048] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Revised: 03/21/2021] [Accepted: 06/15/2021] [Indexed: 11/20/2022] Open
Abstract
BACKGROUND Uncovering the genetic architecture of economic traits in pigs is important for agricultural breeding. However, high-density haplotype reference panels are unavailable in most agricultural species, limiting accurate genotype imputation in large populations. Moreover, the infinitesimal model of quantitative traits implies that weak association signals tend to be spread across most of the genome, further complicating the genetic analysis. Hence, there is a need to develop new methods for sequencing large cohorts without large reference panels. RESULTS We describe a Tn5-based highly accurate, cost- and time-efficient, low-coverage sequencing method to obtain 11.3 million whole-genome single-nucleotide polymorphisms in 2,869 Duroc boars at a mean depth of 0.73×. On the basis of these single-nucleotide polymorphisms, a genome-wide association study was performed, resulting in 14 quantitative trait loci (QTLs) for 7 of 21 important agricultural traits in pigs. These QTLs harbour genes, such as ABCD4 for total teat number and HMGA1 for back fat thickness, and provided a starting point for further investigation. The inheritance models of the different traits varied greatly. Most follow the minor-polygene model, but this can be attributed to different reasons, such as the shaping of genetic architecture by artificial selection for this population and sufficiently interconnected minor gene regulatory networks. CONCLUSIONS Genome-wide association study results for 21 important agricultural traits identified 14 QTLs/genes and showed their genetic architectures, providing guidance for genetic improvement harnessing genomic features. The Tn5-based low-coverage sequencing method can be applied to large-scale genome studies for any species without a good reference panel and can be used for agricultural breeding.
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Affiliation(s)
- Ruifei Yang
- State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, No. 2 Yuanmingyuan west road, Haidian district, Beijing 100193, China
| | - Xiaoli Guo
- State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, No. 2 Yuanmingyuan west road, Haidian district, Beijing 100193, China
| | - Di Zhu
- State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, No. 2 Yuanmingyuan west road, Haidian district, Beijing 100193, China
| | - Cheng Tan
- National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, No. 483 Wushan road, Tianhe district, Guangdong 510640, China
| | - Cheng Bian
- State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, No. 2 Yuanmingyuan west road, Haidian district, Beijing 100193, China
| | - Jiangli Ren
- State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, No. 2 Yuanmingyuan west road, Haidian district, Beijing 100193, China
| | - Zhuolin Huang
- State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, No. 2 Yuanmingyuan west road, Haidian district, Beijing 100193, China
| | - Yiqiang Zhao
- State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, No. 2 Yuanmingyuan west road, Haidian district, Beijing 100193, China
| | - Gengyuan Cai
- National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, No. 483 Wushan road, Tianhe district, Guangdong 510640, China
| | - Dewu Liu
- National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, No. 483 Wushan road, Tianhe district, Guangdong 510640, China
| | - Zhenfang Wu
- National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, No. 483 Wushan road, Tianhe district, Guangdong 510640, China
| | - Yuzhe Wang
- State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, No. 2 Yuanmingyuan west road, Haidian district, Beijing 100193, China
- National Research Facility for Phenotypic and Genotypic Analysis of Model Animals (Beijing), China Agricultural University, No. 2 Yuanmingyuan west road, Haidian district, Beijing 100193, China
| | - Ning Li
- State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, No. 2 Yuanmingyuan west road, Haidian district, Beijing 100193, China
| | - Xiaoxiang Hu
- State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, No. 2 Yuanmingyuan west road, Haidian district, Beijing 100193, China
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31
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Wang Z, He Y, Wang C, Ao H, Tan Z, Xing K. Variations in Microbial Diversity and Metabolite Profiles of Female Landrace Finishing Pigs With Distinct Feed Efficiency. Front Vet Sci 2021; 8:702931. [PMID: 34307537 PMCID: PMC8299115 DOI: 10.3389/fvets.2021.702931] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Accepted: 06/21/2021] [Indexed: 11/13/2022] Open
Abstract
To enhance pig production, feed efficiency (FE) should be improved; however, the mechanisms by which gut microbes affect FE in pigs have not been fully elucidated. To investigate the differences between the composition and functionality of the gut microbiota associated with low and high FE, microbial compositions were characterized using 16S rRNA sequencing, functional annotations were performed by shotgun metagenomics, and metabolomic profiles were created by GC-TOF-MS from female Landrace finishing pigs with low and high feed conversion ratios (FCRs). Lactobacillus was enriched in the gut microbiota of individuals with low FCRs (and thus high FE), while Prevotella abundance was significantly higher in individuals with high FCRs (and thus low FE). This may be linked to carbohydrate consumption and incomplete digestion. The activity of pathways involved in the metabolism of cofactors and vitamins was greater in pigs with lower FE. We also identified differences in pyruvate-related metabolism, including phenylalanine and lysine metabolism. This suggests that pyruvate metabolism is closely related to microbial fermentation in the colon, which in turn affects glycolysis. This study deepens our understanding of how gut microbiota are related to pig growth traits, and how regulating microbial composition could aid in improving porcine FE. However, these results need to be validated using a larger pig cohort in the future.
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Affiliation(s)
- Zhixin Wang
- College of Animal Science and Technology, Hainan University, Haikou, China
| | - Yingzhi He
- College of Animal Science and Technology, Hainan University, Haikou, China
| | - Chuduan Wang
- Key Laboratory of Animal Genetics, Breeding, and Reproduction, Ministry of Agriculture, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Hong Ao
- State Key Laboratory for Animal Nutrition, Key Laboratory for Domestic Animal Genetic Resources and Breeding of the Ministry of Agriculture of China, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Zhen Tan
- College of Animal Science and Technology, Hainan University, Haikou, China
| | - Kai Xing
- Animal Science and Technology College, Beijing University of Agriculture, Beijing, China
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32
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Delpuech E, Aliakbari A, Labrune Y, Fève K, Billon Y, Gilbert H, Riquet J. Identification of genomic regions affecting production traits in pigs divergently selected for feed efficiency. Genet Sel Evol 2021; 53:49. [PMID: 34126920 PMCID: PMC8201702 DOI: 10.1186/s12711-021-00642-1] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2020] [Accepted: 05/28/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Feed efficiency is a major driver of the sustainability of pig production systems. Understanding the biological mechanisms that underlie these agronomic traits is an important issue for environment questions and farms' economy. This study aimed at identifying genomic regions that affect residual feed intake (RFI) and other production traits in two pig lines divergently selected for RFI during nine generations (LRFI, low RFI; HRFI, high RFI). RESULTS We built a whole dataset of 570,447 single nucleotide polymorphisms (SNPs) in 2426 pigs with records for 24 production traits after both imputation and prediction of genotypes using pedigree information. Genome-wide association studies (GWAS) were performed including both lines (global-GWAS) or each line independently (LRFI-GWAS and HRFI-GWAS). Forty-five chromosomal regions were detected in the global-GWAS, whereas 28 and 42 regions were detected in the HRFI-GWAS and LRFI-GWAS, respectively. Among these 45 regions, only 13 were shared between at least two analyses, and only one was common between the three GWAS but it affects different traits. Among the five quantitative trait loci (QTL) detected for RFI, two were close to QTL for meat quality traits and two pinpointed novel genomic regions that harbor candidate genes involved in cell proliferation and differentiation processes of gastrointestinal tissues or in lipid metabolism-related signaling pathways. In most cases, different QTL regions were detected between the three designs, which suggests a strong impact of the dataset structure on the detection power and could be due to the changes in allelic frequencies during the establishment of lines. CONCLUSIONS In addition to efficiently detecting known and new QTL regions for feed efficiency, the combination of GWAS carried out per line or simultaneously using all individuals highlighted chromosomal regions that affect production traits and presented significant changes in allelic frequencies across generations. Further analyses are needed to estimate whether these regions correspond to traces of selection or result from genetic drift.
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Affiliation(s)
- Emilie Delpuech
- GenPhySE, Université de Toulouse, INRAE, ENVT, 31320, Castanet-Tolosan, France
| | - Amir Aliakbari
- GenPhySE, Université de Toulouse, INRAE, ENVT, 31320, Castanet-Tolosan, France
| | - Yann Labrune
- GenPhySE, Université de Toulouse, INRAE, ENVT, 31320, Castanet-Tolosan, France
| | - Katia Fève
- GenPhySE, Université de Toulouse, INRAE, ENVT, 31320, Castanet-Tolosan, France
| | | | - Hélène Gilbert
- GenPhySE, Université de Toulouse, INRAE, ENVT, 31320, Castanet-Tolosan, France
| | - Juliette Riquet
- GenPhySE, Université de Toulouse, INRAE, ENVT, 31320, Castanet-Tolosan, France.
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33
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Wu J, Ye Y, Quan J, Ding R, Wang X, Zhuang Z, Zhou S, Geng Q, Xu C, Hong L, Xu Z, Zheng E, Cai G, Wu Z, Yang J. Using nontargeted LC-MS metabolomics to identify the Association of Biomarkers in pig feces with feed efficiency. Porcine Health Manag 2021; 7:39. [PMID: 34078468 PMCID: PMC8170940 DOI: 10.1186/s40813-021-00219-w] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2021] [Accepted: 05/11/2021] [Indexed: 12/15/2022] Open
Abstract
Background Improving feed efficiency is economically and environmentally beneficial in the pig industry. A deeper understanding of feed efficiency is essential on many levels for its highly complex nature. The aim of this project is to explore the relationship between fecal metabolites and feed efficiency-related traits, thereby identifying metabolites that may assist in the screening of the feed efficiency of pigs. Results We performed fecal metabolomics analysis on 50 individuals selected from 225 Duroc x (Landrace x Yorkshire) (DLY) commercial pigs, 25 with an extremely high feed efficiency and 25 with an extremely low feed efficiency. A total of 6749 and 5644 m/z features were detected in positive and negative ionization modes by liquid chromatography-mass spectrometry (LC/MS). Regrettably, the PCA could not classify the the samples accurately. To improve the classification, OPLS-DA was introduced. However, the predictive ability of the OPLS-DA model did not perform well. Then, through weighted coexpression network analysis (WGCNA), we found that one module in each positive and negative mode was related to residual feed intake (RFI), and six and three metabolites were further identified. The nine metabolites were found to be involved in multiple metabolic pathways, including lipid metabolism (primary bile acid synthesis, linoleic acid metabolism), vitamin D, glucose metabolism, and others. Then, Lasso regression analysis was used to evaluate the importance of nine metabolites obtained by the annotation process. Conclusions Altogether, this study provides new insights for the subsequent evaluation of commercial pig feed efficiency through small molecule metabolites, but also provide a reference for the development of new feed additives. Supplementary Information The online version contains supplementary material available at 10.1186/s40813-021-00219-w.
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Affiliation(s)
- Jie Wu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, 510642, China.,Guangdong Provincial Laboratory of Lingnan Modern Agricultural Science and Technology, Guangzhou, 510642, China
| | - Yong Ye
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, 510642, China.,Guangdong Provincial Laboratory of Lingnan Modern Agricultural Science and Technology, Guangzhou, 510642, China
| | - Jianping Quan
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, 510642, China.,Guangdong Provincial Laboratory of Lingnan Modern Agricultural Science and Technology, Guangzhou, 510642, China
| | - Rongrong Ding
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, 510642, China.,Guangdong Provincial Laboratory of Lingnan Modern Agricultural Science and Technology, Guangzhou, 510642, China
| | - Xingwang Wang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, 510642, China.,Guangdong Provincial Laboratory of Lingnan Modern Agricultural Science and Technology, Guangzhou, 510642, China
| | - Zhanwei Zhuang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, 510642, China.,Guangdong Provincial Laboratory of Lingnan Modern Agricultural Science and Technology, Guangzhou, 510642, China
| | - Shenping Zhou
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, 510642, China.,Guangdong Provincial Laboratory of Lingnan Modern Agricultural Science and Technology, Guangzhou, 510642, China
| | - Qian Geng
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, 510642, China.,Guangdong Provincial Laboratory of Lingnan Modern Agricultural Science and Technology, Guangzhou, 510642, China
| | - Cineng Xu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, 510642, China.,Guangdong Provincial Laboratory of Lingnan Modern Agricultural Science and Technology, Guangzhou, 510642, China
| | - Linjun Hong
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, 510642, China.,Guangdong Provincial Laboratory of Lingnan Modern Agricultural Science and Technology, Guangzhou, 510642, China
| | - Zheng Xu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, 510642, China.,Guangdong Provincial Laboratory of Lingnan Modern Agricultural Science and Technology, Guangzhou, 510642, China
| | - Enqin Zheng
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, 510642, China.,Guangdong Provincial Laboratory of Lingnan Modern Agricultural Science and Technology, Guangzhou, 510642, China
| | - Gengyuan Cai
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, 510642, China.,Guangdong Provincial Laboratory of Lingnan Modern Agricultural Science and Technology, Guangzhou, 510642, China
| | - Zhenfang Wu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, 510642, China. .,Guangdong Provincial Laboratory of Lingnan Modern Agricultural Science and Technology, Guangzhou, 510642, China. .,State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, Guangzhou, 510642l, China. .,Guangdong Provincial Key Laboratory of Agro-animal Genomics and Molecular Breeding, Guangzhou, 510642, China.
| | - Jie Yang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, 510642, China. .,Guangdong Provincial Laboratory of Lingnan Modern Agricultural Science and Technology, Guangzhou, 510642, China.
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34
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Qiu Y, Ding R, Zhuang Z, Wu J, Yang M, Zhou S, Ye Y, Geng Q, Xu Z, Huang S, Cai G, Wu Z, Yang J. Genome-wide detection of CNV regions and their potential association with growth and fatness traits in Duroc pigs. BMC Genomics 2021; 22:332. [PMID: 33964879 PMCID: PMC8106131 DOI: 10.1186/s12864-021-07654-7] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2020] [Accepted: 04/27/2021] [Indexed: 11/19/2022] Open
Abstract
Background In the process of pig breeding, the average daily gain (ADG), days to 100 kg (AGE), and backfat thickness (BFT) are directly related to growth rate and fatness. However, the genetic mechanisms involved are not well understood. Copy number variation (CNV), an important source of genetic diversity, can affect a variety of complex traits and diseases and has gradually been thrust into the limelight. In this study, we reported the genome-wide CNVs of Duroc pigs using SNP genotyping data from 6627 animals. We also performed a copy number variation region (CNVR)-based genome-wide association studies (GWAS) for growth and fatness traits in two Duroc populations. Results Our study identified 953 nonredundant CNVRs in U.S. and Canadian Duroc pigs, covering 246.89 Mb (~ 10.90%) of the pig autosomal genome. Of these, 802 CNVRs were in U.S. Duroc pigs with 499 CNVRs were in Canadian Duroc pigs, indicating 348 CNVRs were shared by the two populations. Experimentally, 77.8% of nine randomly selected CNVRs were validated through quantitative PCR (qPCR). We also identified 35 CNVRs with significant association with growth and fatness traits using CNVR-based GWAS. Ten of these CNVRs were associated with both ADG and AGE traits in U.S. Duroc pigs. Notably, four CNVRs showed significant associations with ADG, AGE, and BFT, indicating that these CNVRs may play a pleiotropic role in regulating pig growth and fat deposition. In Canadian Duroc pigs, nine CNVRs were significantly associated with both ADG and AGE traits. Further bioinformatic analysis identified a subset of potential candidate genes, including PDGFA, GPER1, PNPLA2 and BSCL2. Conclusions The present study provides a necessary supplement to the CNV map of the Duroc genome through large-scale population genotyping. In addition, the CNVR-based GWAS results provide a meaningful way to elucidate the genetic mechanisms underlying complex traits. The identified CNVRs can be used as molecular markers for genetic improvement in the molecular-guided breeding of modern commercial pigs. Supplementary Information The online version contains supplementary material available at 10.1186/s12864-021-07654-7.
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Affiliation(s)
- Yibin Qiu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, 510642, People's Republic of China
| | - Rongrong Ding
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, 510642, People's Republic of China.,Guangdong Wens Breeding Swine Technology Co., Ltd., Yunfu, Guangdong, 527400, People's Republic of China
| | - Zhanwei Zhuang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, 510642, People's Republic of China
| | - Jie Wu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, 510642, People's Republic of China
| | - Ming Yang
- Guangdong Wens Breeding Swine Technology Co., Ltd., Yunfu, Guangdong, 527400, People's Republic of China
| | - Shenping Zhou
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, 510642, People's Republic of China
| | - Yong Ye
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, 510642, People's Republic of China
| | - Qian Geng
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, 510642, People's Republic of China
| | - Zheng Xu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, 510642, People's Republic of China.,Lingnan Guangdong Laboratory of Modern Agriculture, Guangzhou, 510642, People's Republic of China
| | - Sixiu Huang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, 510642, People's Republic of China
| | - Gengyuan Cai
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, 510642, People's Republic of China.,Guangdong Wens Breeding Swine Technology Co., Ltd., Yunfu, Guangdong, 527400, People's Republic of China.,Lingnan Guangdong Laboratory of Modern Agriculture, Guangzhou, 510642, People's Republic of China
| | - Zhenfang Wu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, 510642, People's Republic of China. .,Guangdong Wens Breeding Swine Technology Co., Ltd., Yunfu, Guangdong, 527400, People's Republic of China. .,Lingnan Guangdong Laboratory of Modern Agriculture, Guangzhou, 510642, People's Republic of China.
| | - Jie Yang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, 510642, People's Republic of China. .,Lingnan Guangdong Laboratory of Modern Agriculture, Guangzhou, 510642, People's Republic of China.
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Miao Y, Mei Q, Fu C, Liao M, Liu Y, Xu X, Li X, Zhao S, Xiang T. Genome-wide association and transcriptome studies identify candidate genes and pathways for feed conversion ratio in pigs. BMC Genomics 2021; 22:294. [PMID: 33888058 PMCID: PMC8063444 DOI: 10.1186/s12864-021-07570-w] [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: 11/26/2020] [Accepted: 03/25/2021] [Indexed: 12/03/2022] Open
Abstract
Background The feed conversion ratio (FCR) is an important productive trait that greatly affects profits in the pig industry. Elucidating the genetic mechanisms underpinning FCR may promote more efficient improvement of FCR through artificial selection. In this study, we integrated a genome-wide association study (GWAS) with transcriptome analyses of different tissues in Yorkshire pigs (YY) with the aim of identifying key genes and signalling pathways associated with FCR. Results A total of 61 significant single nucleotide polymorphisms (SNPs) were detected by GWAS in YY. All of these SNPs were located on porcine chromosome (SSC) 5, and the covered region was considered a quantitative trait locus (QTL) region for FCR. Some genes distributed around these significant SNPs were considered as candidates for regulating FCR, including TPH2, FAR2, IRAK3, YARS2, GRIP1, FRS2, CNOT2 and TRHDE. According to transcriptome analyses in the hypothalamus, TPH2 exhibits the potential to regulate intestinal motility through serotonergic synapse and oxytocin signalling pathways. In addition, GRIP1 may be involved in glutamatergic and GABAergic signalling pathways, which regulate FCR by affecting appetite in pigs. Moreover, GRIP1, FRS2, CNOT2, and TRHDE may regulate metabolism in various tissues through a thyroid hormone signalling pathway. Conclusions Based on the results from GWAS and transcriptome analyses, the TPH2, GRIP1, FRS2, TRHDE, and CNOT2 genes were considered candidate genes for regulating FCR in Yorkshire pigs. These findings improve the understanding of the genetic mechanisms of FCR and may help optimize the design of breeding schemes. Supplementary Information The online version contains supplementary material available at 10.1186/s12864-021-07570-w.
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Affiliation(s)
- Yuanxin Miao
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & Key Laboratory of Swine Genetics and Breeding of Ministry of Agriculture, Huazhong Agricultural University, Wuhan, 430070, China.,The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070, China.,Jingchu University of Technology, Jingmen, 448000, China
| | - Quanshun Mei
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & Key Laboratory of Swine Genetics and Breeding of Ministry of Agriculture, Huazhong Agricultural University, Wuhan, 430070, China.,The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070, China
| | - Chuanke Fu
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & Key Laboratory of Swine Genetics and Breeding of Ministry of Agriculture, Huazhong Agricultural University, Wuhan, 430070, China.,The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070, China
| | - Mingxing Liao
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & Key Laboratory of Swine Genetics and Breeding of Ministry of Agriculture, Huazhong Agricultural University, Wuhan, 430070, China.,The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070, China.,Agriculture and Rural Affairs Administration of Jingmen City, Jingmen, 448000, China
| | - Yan Liu
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & Key Laboratory of Swine Genetics and Breeding of Ministry of Agriculture, 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 of Ministry of Education & Key Laboratory of Swine Genetics and Breeding of Ministry of Agriculture, Huazhong Agricultural University, Wuhan, 430070, China.,The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070, China
| | - Xinyun Li
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & Key Laboratory of Swine Genetics and Breeding of Ministry of Agriculture, Huazhong Agricultural University, Wuhan, 430070, China.,The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070, China
| | - Shuhong Zhao
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & Key Laboratory of Swine Genetics and Breeding of Ministry of Agriculture, Huazhong Agricultural University, Wuhan, 430070, China.,The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070, China
| | - Tao Xiang
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & Key Laboratory of Swine Genetics and Breeding of Ministry of Agriculture, Huazhong Agricultural University, Wuhan, 430070, China. .,The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070, China.
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Alvarenga AB, Oliveira HR, Chen SY, Miller SP, Marchant-Forde JN, Grigoletto L, Brito LF. A Systematic Review of Genomic Regions and Candidate Genes Underlying Behavioral Traits in Farmed Mammals and Their Link with Human Disorders. Animals (Basel) 2021; 11:ani11030715. [PMID: 33800722 PMCID: PMC7999279 DOI: 10.3390/ani11030715] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Revised: 02/21/2021] [Accepted: 02/27/2021] [Indexed: 12/25/2022] Open
Abstract
Simple Summary This study is a comprehensive review of genomic regions associated with animal behavior in farmed mammals (beef and dairy cattle, pigs, and sheep) which contributes to a better understanding of the biological mechanisms influencing the target indicator trait and to gene expression studies by suggesting genes likely controlling the trait, and it will be useful in optimizing genomic predictions of breeding values incorporating biological information. Behavioral mechanisms are complex traits, genetically controlled by multiple genes spread across the whole genome. The majority of the genes identified in cattle, pigs, and sheep in association with a plethora of behavioral measurements (e.g., temperament, terrain use, milking speed, tail biting, and sucking reflex) are likely controlling stimuli reception (e.g., olfactory), internal recognition of stimuli (e.g., neuroactive ligand–receptor interaction), and body response to a stimulus (e.g., blood pressure, fatty acidy metabolism, hormone signaling, and inflammatory pathways). Six genes were commonly identified between cattle and pigs. About half of the genes for behavior identified in farmed mammals were also identified in humans for behavioral, mental, and neuronal disorders. Our findings indicate that the majority of the genes identified are likely controlling animal behavioral outcomes because their biological functions as well as potentially differing allele frequencies between two breed groups (subjectively) clustered based on their temperament characteristics. Abstract The main objectives of this study were to perform a systematic review of genomic regions associated with various behavioral traits in the main farmed mammals and identify key candidate genes and potential causal mutations by contrasting the frequency of polymorphisms in cattle breeds with divergent behavioral traits (based on a subjective clustering approach). A total of 687 (cattle), 1391 (pigs), and 148 (sheep) genomic regions associated with 37 (cattle), 55 (pigs), and 22 (sheep) behavioral traits were identified in the literature. In total, 383, 317, and 15 genes overlap with genomic regions identified for cattle, pigs, and sheep, respectively. Six common genes (e.g., NR3C2, PITPNM3, RERG, SPNS3, U6, and ZFAT) were found for cattle and pigs. A combined gene-set of 634 human genes was produced through identified homologous genes. A total of 313 out of 634 genes have previously been associated with behavioral, mental, and neurologic disorders (e.g., anxiety and schizophrenia) in humans. Additionally, a total of 491 candidate genes had at least one statistically significant polymorphism (p-value < 0.05). Out of those, 110 genes were defined as having polymorphic regions differing in greater than 50% of exon regions. Therefore, conserved genomic regions controlling behavior were found across farmed mammal species and humans.
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Affiliation(s)
- Amanda B. Alvarenga
- Department of Animal Sciences, Purdue University, West Lafayette, IN 47907, USA; (A.B.A.); (H.R.O.); (S.-Y.C.); (L.G.)
| | - Hinayah R. Oliveira
- Department of Animal Sciences, Purdue University, West Lafayette, IN 47907, USA; (A.B.A.); (H.R.O.); (S.-Y.C.); (L.G.)
- Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, ON N1G 2W1, Canada
| | - Shi-Yi Chen
- Department of Animal Sciences, Purdue University, West Lafayette, IN 47907, USA; (A.B.A.); (H.R.O.); (S.-Y.C.); (L.G.)
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu 625014, China
| | | | - Jeremy N. Marchant-Forde
- Livestock Behavior Research Unit, United States Department of Agriculture—Agricultural Research Service (USDA–ARS), West Lafayette, IN 47907, USA;
| | - Lais Grigoletto
- Department of Animal Sciences, Purdue University, West Lafayette, IN 47907, USA; (A.B.A.); (H.R.O.); (S.-Y.C.); (L.G.)
- Department of Veterinary Medicine, College of Animal Science and Food Engineering, University of Sao Paulo, Pirassununga 05508, São Paulo, Brazil
| | - Luiz F. Brito
- Department of Animal Sciences, Purdue University, West Lafayette, IN 47907, USA; (A.B.A.); (H.R.O.); (S.-Y.C.); (L.G.)
- Correspondence:
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Jiang H, Fang S, Yang H, Chen C. Identification of the relationship between the gut microbiome and feed efficiency in a commercial pig cohort. J Anim Sci 2021; 99:6133345. [PMID: 33570553 DOI: 10.1093/jas/skab045] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2020] [Accepted: 02/05/2021] [Indexed: 12/11/2022] Open
Abstract
Feed efficiency (FE) is an economically important trait in pig production. Gut microbiota plays an important role in energy harvest, nutrient metabolism, and fermentation of dietary indigestible components. Whether and which gut microbes affect FE in pigs are largely unknown. Here, a total of 208 healthy Duroc pigs were used as experimental materials. Feces and serum samples were collected at the age of 140 d. We first performed 16S rRNA gene and metagenomic sequencing analysis to investigate the relationship between the gut microbiome and porcine residual feed intake (RFI). 16S rRNA gene sequencing analysis detected 21 operational taxonomic units showing the tendency to correlation with the RFI (P < 0.01). Metagenomic sequencing further identified that the members of Clostridiales, e.g., Ruminococcus flavefaoiens, Lachnospiraceae bacterium 28-4, and Lachnospiraceae phytofermentans, were enriched in pigs with low RFI (high-FE), while 11 bacterial species including 5 Prevotella spp., especially, the Prevotella copri, had higher abundance in pigs with high RFI. Functional capacity analysis suggested that the gut microbiome of low RFI pigs had a high abundance of the pathways related to amino acid metabolism and biosynthesis, but a low abundance of the pathways associated with monosaccharide metabolism and lipopolysaccharide biosynthesis. Serum metabolome and fecal short-chain fatty acids were determined by UPLC-QTOF/MS and gas chromatography, respectively. Propionic acid in feces and the serum metabolites related to amino acid metabolism were negatively correlated with the RFI. The results from this study may provide potential gut microbial biomarkers that could be used for improving FE in pig production industry.
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Affiliation(s)
- Hui Jiang
- State Key Laboratory of Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, PR China
| | - Shaoming Fang
- State Key Laboratory of Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, PR China
| | - Hui Yang
- State Key Laboratory of Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, PR China.,College of Bioscience and Engineering, Jiangxi Agricultural University, Nanchang, PR China
| | - Congying Chen
- State Key Laboratory of Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, PR China
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Du H, Diao C, Zhao P, Zhou L, Liu JF. Integrated hybrid de novo assembly technologies to obtain high-quality pig genome using short and long reads. Brief Bioinform 2021; 22:6082823. [PMID: 33429431 DOI: 10.1093/bib/bbaa399] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2020] [Revised: 11/20/2020] [Accepted: 12/08/2020] [Indexed: 11/12/2022] Open
Abstract
With the rapid progress of sequencing technologies, various types of sequencing reads and assembly algorithms have been designed to construct genome assemblies. Although recent studies have attempted to evaluate the appropriate type of sequencing reads and algorithms for assembling high-quality genomes, it is still a challenge to set the correct combination for constructing animal genomes. Here, we present a comparative performance assessment of 14 assembly combinations-9 software programs with different short and long reads of Duroc pig. Based on the results of the optimization process for genome construction, we designed an integrated hybrid de novo assembly pipeline, HSCG, and constructed a draft genome for Duroc pig. Comparison between the new genome and Sus scrofa 11.1 revealed important breakpoints in two S. scrofa 11.1 genes. Our findings may provide new insights into the pan-genome analysis studies of agricultural animals, and the integrated assembly pipeline may serve as a guide for the assembly of other animal genomes.
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Affiliation(s)
- Heng Du
- National Engineering Laboratory for Animal Breeding; Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture; College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Chenguang Diao
- National Engineering Laboratory for Animal Breeding; Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture; College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Pengju Zhao
- National Engineering Laboratory for Animal Breeding; Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture; College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Lei Zhou
- National Engineering Laboratory for Animal Breeding; Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture; College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Jian-Feng Liu
- National Engineering Laboratory for Animal Breeding; Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture; College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
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Vanvanhossou SFU, Scheper C, Dossa LH, Yin T, Brügemann K, König S. A multi-breed GWAS for morphometric traits in four Beninese indigenous cattle breeds reveals loci associated with conformation, carcass and adaptive traits. BMC Genomics 2020; 21:783. [PMID: 33176675 PMCID: PMC7656759 DOI: 10.1186/s12864-020-07170-0] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2020] [Accepted: 10/20/2020] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND Specific adaptive features including disease resistance and growth abilities in harsh environments are attributed to indigenous cattle breeds of Benin, but these breeds are endangered due to crossbreeding. So far, there is a lack of systematic trait recording, being the basis for breed characterizations, and for structured breeding program designs aiming on conservation. Bridging this gap, own phenotyping for morphological traits considered measurements for height at withers (HAW), sacrum height (SH), heart girth (HG), hip width (HW), body length (BL) and ear length (EL), including 449 cattle from the four indigenous Benin breeds Lagune, Somba, Borgou and Pabli. In order to utilize recent genomic tools for breed characterizations and genetic evaluations, phenotypes for novel traits were merged with high-density SNP marker data. Multi-breed genetic parameter estimations and genome-wide association studies (GWAS) for the six morphometric traits were carried out. Continuatively, we aimed on inferring genomic regions and functional loci potentially associated with conformation, carcass and adaptive traits. RESULTS SNP-based heritability estimates for the morphometric traits ranged between 0.46 ± 0.14 (HG) and 0.74 ± 0.13 (HW). Phenotypic and genetic correlations ranged from 0.25 ± 0.05 (HW-BL) to 0.89 ± 0.01 (HAW-SH), and from 0.14 ± 0.10 (HW-BL) to 0.85 ± 0.02 (HAW-SH), respectively. Three genome-wide and 25 chromosome-wide significant SNP positioned on different chromosomes were detected, located in very close chromosomal distance (±25 kb) to 15 genes (or located within the genes). The genes PIK3R6 and PIK3R1 showed direct functional associations with height and body size. We inferred the potential candidate genes VEPH1, CNTNAP5, GYPC for conformation, growth and carcass traits including body weight and body fat deposition. According to their functional annotations, detected potential candidate genes were associated with stress or immune response (genes PTAFR, PBRM1, ADAMTS12) and with feed efficiency (genes MEGF11 SLC16A4, CCDC117). CONCLUSIONS Accurate measurements contributed to large SNP heritabilities for some morphological traits, even for a small mixed-breed sample size. Multi-breed GWAS detected different loci associated with conformation or carcass traits. The identified potential candidate genes for immune response or feed efficiency indicators reflect the evolutionary development and adaptability features of the breeds.
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Affiliation(s)
| | - Carsten Scheper
- Institute of Animal Breeding and Genetics, Justus-Liebig-University Gießen, Gießen, Germany
| | - Luc Hippolyte Dossa
- School of Science and Technics of Animal Production, Faculty of Agricultural Sciences, University of Abomey-Calavi, Cotonou, Benin
| | - Tong Yin
- Institute of Animal Breeding and Genetics, Justus-Liebig-University Gießen, Gießen, Germany
| | - Kerstin Brügemann
- Institute of Animal Breeding and Genetics, Justus-Liebig-University Gießen, Gießen, Germany
| | - Sven König
- Institute of Animal Breeding and Genetics, Justus-Liebig-University Gießen, Gießen, Germany.
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Carmelo VAO, Kadarmideen HN. Genetic variations (eQTLs) in muscle transcriptome and mitochondrial genes, and trans-eQTL molecular pathways in feed efficiency from Danish breeding pigs. PLoS One 2020; 15:e0239143. [PMID: 32941478 PMCID: PMC7498092 DOI: 10.1371/journal.pone.0239143] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2020] [Accepted: 08/31/2020] [Indexed: 01/08/2023] Open
Abstract
Feed efficiency (FE) is a key trait in pig production, as improvement in FE has positive economic and environmental impact. FE is a complex phenotype and testing animals for FE is costly. Therefore, there has been a desire to find functionally relevant single nucleotide polymorphisms (SNPs) as biomarkers, to improve our biological understanding of FE as well as accuracy of genomic prediction for FE. We have performed a cis- and trans- eQTL (expression quantitative trait loci) analysis, in a population of Danbred Durocs (N = 11) and Danbred Landrace (N = 27) using both a linear and ANOVA model based on muscle tissue RNA-seq. We analyzed a total of 1425x19179 or 2.7x107 Gene-SNP combinations in eQTL detection models for FE. The 1425 genes were from RNA-Seq based differential gene expression analyses using 25880 genes related to FE and additionally combined with mitochondrial genes. The 19179 SNPs were from applying stringent quality control and linkage disequilibrium filtering on genotype data using a GGP Porcine HD 70k SNP array. We applied 1000 fold bootstrapping and enrichment analysis to further validate and analyze our detected eQTLs. We identified 13 eQTLs with FDR < 0.1, affecting several genes found in previous studies of commercial pig breeds. Examples include MYO19, CPT1B, ACSL1, IER5L, CPT1A, SUCLA2, CSRNP1, PARK7 and MFF. The bootstrapping results showed statistically significant enrichment (p-value<2.2x10-16) of eQTLs with p-value < 0.01 in both cis and trans-eQTLs. Enrichment analysis of top trans-eQTLs revealed high enrichment for gene categories and gene ontologies associated with genomic context and expression regulation. This included transcription factors (p-value = 1.0x10-13), DNA-binding (GO:0003677, p-value = 8.9x10-14), DNA-binding transcription factor activity (GO:0003700,) nucleus gene (GO:0005634, p-value<2.2x10-16), negative regulation of expression (GO:0010629, p-value<2.2x10-16). These results would be useful for future genome assisted breeding of pigs to improve FE, and in the improved understanding of the functional mechanism of trans eQTLs.
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Affiliation(s)
- Victor A. O. Carmelo
- Quantitative Genomics, Bioinformatics and Computational Biology Group, Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kongens Lyngby, Denmark
| | - Haja N. Kadarmideen
- Quantitative Genomics, Bioinformatics and Computational Biology Group, Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kongens Lyngby, Denmark
- * E-mail:
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Brito LF, Oliveira HR, McConn BR, Schinckel AP, Arrazola A, Marchant-Forde JN, Johnson JS. Large-Scale Phenotyping of Livestock Welfare in Commercial Production Systems: A New Frontier in Animal Breeding. Front Genet 2020; 11:793. [PMID: 32849798 PMCID: PMC7411239 DOI: 10.3389/fgene.2020.00793] [Citation(s) in RCA: 47] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2020] [Accepted: 07/03/2020] [Indexed: 12/13/2022] Open
Abstract
Genomic breeding programs have been paramount in improving the rates of genetic progress of productive efficiency traits in livestock. Such improvement has been accompanied by the intensification of production systems, use of a wider range of precision technologies in routine management practices, and high-throughput phenotyping. Simultaneously, a greater public awareness of animal welfare has influenced livestock producers to place more emphasis on welfare relative to production traits. Therefore, management practices and breeding technologies in livestock have been developed in recent years to enhance animal welfare. In particular, genomic selection can be used to improve livestock social behavior, resilience to disease and other stress factors, and ease habituation to production system changes. The main requirements for including novel behavioral and welfare traits in genomic breeding schemes are: (1) to identify traits that represent the biological mechanisms of the industry breeding goals; (2) the availability of individual phenotypic records measured on a large number of animals (ideally with genomic information); (3) the derived traits are heritable, biologically meaningful, repeatable, and (ideally) not highly correlated with other traits already included in the selection indexes; and (4) genomic information is available for a large number of individuals (or genetically close individuals) with phenotypic records. In this review, we (1) describe a potential route for development of novel welfare indicator traits (using ideal phenotypes) for both genetic and genomic selection schemes; (2) summarize key indicator variables of livestock behavior and welfare, including a detailed assessment of thermal stress in livestock; (3) describe the primary statistical and bioinformatic methods available for large-scale data analyses of animal welfare; and (4) identify major advancements, challenges, and opportunities to generate high-throughput and large-scale datasets to enable genetic and genomic selection for improved welfare in livestock. A wide variety of novel welfare indicator traits can be derived from information captured by modern technology such as sensors, automatic feeding systems, milking robots, activity monitors, video cameras, and indirect biomarkers at the cellular and physiological levels. The development of novel traits coupled with genomic selection schemes for improved welfare in livestock can be feasible and optimized based on recently developed (or developing) technologies. Efficient implementation of genetic and genomic selection for improved animal welfare also requires the integration of a multitude of scientific fields such as cell and molecular biology, neuroscience, immunology, stress physiology, computer science, engineering, quantitative genomics, and bioinformatics.
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Affiliation(s)
- Luiz F. Brito
- Department of Animal Sciences, Purdue University, West Lafayette, IN, United States
| | - Hinayah R. Oliveira
- Department of Animal Sciences, Purdue University, West Lafayette, IN, United States
- Department of Animal Biosciences, University of Guelph, Guelph, ON, Canada
| | - Betty R. McConn
- Oak Ridge Institute for Science and Education, Oak Ridge, TN, United States
| | - Allan P. Schinckel
- Department of Animal Sciences, Purdue University, West Lafayette, IN, United States
| | - Aitor Arrazola
- Department of Comparative Pathobiology, Purdue University, West Lafayette, IN, United States
| | | | - Jay S. Johnson
- USDA-ARS Livestock Behavior Research Unit, West Lafayette, IN, United States
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Bergamaschi M, Tiezzi F, Howard J, Huang YJ, Gray KA, Schillebeeckx C, McNulty NP, Maltecca C. Gut microbiome composition differences among breeds impact feed efficiency in swine. MICROBIOME 2020; 8:110. [PMID: 32698902 PMCID: PMC7376719 DOI: 10.1186/s40168-020-00888-9] [Citation(s) in RCA: 91] [Impact Index Per Article: 22.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/27/2020] [Accepted: 06/30/2020] [Indexed: 05/08/2023]
Abstract
BACKGROUND Feed efficiency is a crucial parameter in swine production, given both its economic and environmental impact. The gut microbiota plays an essential role in nutrient digestibility and is, therefore, likely to affect feed efficiency. This study aimed to characterize feed efficiency, fatness traits, and gut microbiome composition in three major breeds of domesticated swine and investigate a possible link between feed efficiency and gut microbiota composition. RESULTS Average daily feed intake (ADFI), average daily gain (ADG), feed conversion ratio (FCR), residual feed intake (RFI), backfat, loin depth, and intramuscular fat of 615 pigs belonging to the Duroc (DR), Landrace (LR), and Large White (LW) breeds were measured. Gut microbiota composition was characterized by 16S rRNA gene sequencing. Orthogonal contrasts between paternal line (DR) and maternal lines (LR+LW) and between the two maternal lines (LR versus LW) were performed. Average daily feed intake and ADG were statistically different with DR having lower ADFI and ADG compared to LR and LW. Landrace and LW had a similar ADG and RFI, with higher ADFI and FCR for LW. Alpha diversity was higher in the fecal microbial communities of LR pigs than in those of DR and LW pigs for all time points considered. Duroc communities had significantly higher proportional representation of the Catenibacterium and Clostridium genera compared to LR and LW, while LR pigs had significantly higher proportions of Bacteroides than LW for all time points considered. Amplicon sequence variants from multiple genera (including Anaerovibrio, Bacteroides, Blautia, Clostridium, Dorea, Eubacterium, Faecalibacterium, Lactobacillus, Oscillibacter, and Ruminococcus) were found to be significantly associated with feed efficiency, regardless of the time point considered. CONCLUSIONS In this study, we characterized differences in the composition of the fecal microbiota of three commercially relevant breeds of swine, both over time and between breeds. Correlations between different microbiome compositions and feed efficiency were established. This suggests that the microbial community may contribute to shaping host productive parameters. Moreover, our study provides important insights into how the intestinal microbial community might influence host energy harvesting capacity. A deeper understanding of this process may allow us to modulate the gut microbiome in order to raise more efficient animals. Video Abstract.
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Affiliation(s)
- Matteo Bergamaschi
- Department of Animal Science, North Carolina State University, Raleigh, NC 27695 USA
| | - Francesco Tiezzi
- Department of Animal Science, North Carolina State University, Raleigh, NC 27695 USA
| | - Jeremy Howard
- Smithfield Premium Genetics, Rose Hill, NC 28458 USA
| | - Yi Jian Huang
- Smithfield Premium Genetics, Rose Hill, NC 28458 USA
| | - Kent A. Gray
- Smithfield Premium Genetics, Rose Hill, NC 28458 USA
| | | | | | - Christian Maltecca
- Department of Animal Science, North Carolina State University, Raleigh, NC 27695 USA
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43
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Fu L, Jiang Y, Wang C, Mei M, Zhou Z, Jiang Y, Song H, Ding X. A Genome-Wide Association Study on Feed Efficiency Related Traits in Landrace Pigs. Front Genet 2020; 11:692. [PMID: 32719719 PMCID: PMC7350416 DOI: 10.3389/fgene.2020.00692] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2019] [Accepted: 06/05/2020] [Indexed: 12/27/2022] Open
Abstract
Feed efficiency (FE) traits in pigs are of utmost economic importance. Genetic improvement of FE related traits in pigs might significantly reduce production cost and energy consumption. Hence, our study aimed at identifying SNPs and candidate genes associated with FE related traits, including feed conversion ratio (FCR), average daily gain (ADG), average daily feed intake (ADFI), and residual feed intake (RFI). A genome-wide association study (GWAS) was performed for the four FE related traits in 296 Landrace pigs genotyped with PorcineSNP50 BeadChip. Two different single-trait methods, single SNP linear model GWAS (LM-GWAS) and single-step GWAS (ssGWAS), were implemented. Our results showed that the two methods showed high consistency with respect to SNP identification. A total of 32 common significant SNPs associated with the four FE related traits were identified. Bioinformatics analysis revealed eight common QTL regions, of which three QTL regions related to ADFI and RFI traits were overlapped. Gene ontology analysis revealed six common candidate genes (PRELID2, GPER1, PDX1, TEX2, PLCL2, ICAM2) relevant for the four FE related traits. These genes are involved in the processes of fat synthesis and decomposition, lipid transport process, insulin metabolism, among others. Our results provide, new insights into the genetic mechanisms and candidate function genes of FE related traits in pigs. However, further investigations to validate these results are warranted.
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Affiliation(s)
- Lu Fu
- National Engineering Laboratory for Animal Breeding, Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Yao Jiang
- National Engineering Laboratory for Animal Breeding, Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Chonglong Wang
- Institute of Animal Husbandry and Veterinary Medicine, Anhui Academy of Agricultural Sciences, Hefei, China
| | - Mengran Mei
- National Engineering Laboratory for Animal Breeding, Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Ziwen Zhou
- National Engineering Laboratory for Animal Breeding, Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Yifan Jiang
- National Engineering Laboratory for Animal Breeding, Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Hailiang Song
- National Engineering Laboratory for Animal Breeding, Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Xiangdong Ding
- National Engineering Laboratory for Animal Breeding, Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture, College of Animal Science and Technology, China Agricultural University, Beijing, China
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Te Pas MFW, Borg R, Buddiger NJH, Wood BJ, Rebel JMJ, van Krimpen MM, Calus MPL, Park JE, Schokker D. Regulating appetite in broilers for improving body and muscle development - A review. J Anim Physiol Anim Nutr (Berl) 2020; 104:1819-1834. [PMID: 32592266 PMCID: PMC7754290 DOI: 10.1111/jpn.13407] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2019] [Revised: 05/27/2020] [Accepted: 05/28/2020] [Indexed: 12/12/2022]
Abstract
Appetite is the desire for feed and water and the voluntary intake of feed and is an important regulator of livestock productivity and animal health. Economic traits such as growth rate and muscle development (meat deposition) in broilers are directly correlated to appetite. Factors that may influence appetite include environmental factors, such as stress and temperature variation, and animal‐specific factors, such as learning period, eating capacity and preferences. Feed preferences have been reported to be determined in early life, and this period is important in broilers due to their fast growth and relatively short growth trajectories. This may be of importance when contemplating the use of more circular and sustainable feeds and the optimization of appetite for these feeds. The objective of this review was to review the biological mechanisms underlying appetite using data from human, animal and bird models and to consider the option for modulating appetite particularly as it relates to broiler chickens.
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Affiliation(s)
- Marinus F W Te Pas
- Wageningen University and Research, Wageningen Livestock Research, Wageningen, The Netherlands
| | | | | | - Benjamin J Wood
- Hendrix Genetics North America Office, Kitchener, ON, Canada
| | - Johanna M J Rebel
- Wageningen University and Research, Wageningen Livestock Research, Wageningen, The Netherlands
| | - Marinus M van Krimpen
- Wageningen University and Research, Wageningen Livestock Research, Wageningen, The Netherlands
| | - Mario P L Calus
- Wageningen University and Research, Wageningen Livestock Research, Wageningen, The Netherlands
| | - Jong-Eun Park
- Animal Genomics & Bioinformatics Division, National Institute of Animal Science, Rural Development Administration, Jeonju, Korea
| | - Dirkjan Schokker
- Wageningen University and Research, Wageningen Livestock Research, Wageningen, The Netherlands
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45
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Carmelo VAO, Kadarmideen HN. Genome Regulation and Gene Interaction Networks Inferred From Muscle Transcriptome Underlying Feed Efficiency in Pigs. Front Genet 2020; 11:650. [PMID: 32655625 PMCID: PMC7324801 DOI: 10.3389/fgene.2020.00650] [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: 01/16/2020] [Accepted: 05/28/2020] [Indexed: 01/03/2023] Open
Abstract
Improvement of feed efficiency (FE) is key for Sustainability and cost reduction in pig production. Our aim was to characterize the muscle transcriptomic profiles in Danbred Duroc (Duroc; n = 13) and Danbred Landrace (Landrace; n = 28), in relation to FE for identifying potential biomarkers. RNA-seq data on the 41 pigs was analyzed employing differential gene expression methods, gene-gene interaction and network analysis, including pathway and functional analysis. We also compared the results with genome regulation in human exercise data, hypothesizing that increased FE mimics processes triggered in exercised muscle. In the differential expression analysis, 13 genes were differentially expressed, including: MRPS11, MTRF1, TRIM63, MGAT4A, KLH30. Based on a novel gene selection method, the divergent count, we performed pathway enrichment analysis. We found five significantly enriched pathways related to feed conversion ratio (FCR). These pathways were mainly related to mitochondria, and summarized in the mitochondrial translation elongation (MTR) pathway. In the gene interaction analysis, the most interesting genes included the mitochondrial genes: PPIF, MRPL35, NDUFS4 and the fat metabolism and obesity genes: AACS, SMPDL3B, CTNNBL1, NDUFS4, and LIMD2. In the network analysis, we identified two modules significantly correlated with FCR. Pathway enrichment of module genes identified MTR, electron transport chain and DNA repair as enriched pathways. The network analysis revealed the mitochondrial gene group NDUF as key network hub genes, showing their potential as biomarkers. Results show that genes related to human exercise were enriched in identified FCR related genes. We conclude that mitochondrial activity is a key driver for FCR in muscle tissue, and mitochondrial genes could be potential biomarkers for FCR in pigs.
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Affiliation(s)
- Victor A O Carmelo
- Quantitative Genomics, Bioinformatics and Computational Biology Group, Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kongens Lyngby, Denmark
| | - Haja N Kadarmideen
- Quantitative Genomics, Bioinformatics and Computational Biology Group, Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kongens Lyngby, Denmark
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46
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Wang X, Kadarmideen HN. Metabolite Genome-Wide Association Study (mGWAS) and Gene-Metabolite Interaction Network Analysis Reveal Potential Biomarkers for Feed Efficiency in Pigs. Metabolites 2020; 10:metabo10050201. [PMID: 32429265 PMCID: PMC7281523 DOI: 10.3390/metabo10050201] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2020] [Revised: 05/10/2020] [Accepted: 05/11/2020] [Indexed: 12/21/2022] Open
Abstract
Metabolites represent the ultimate response of biological systems, so metabolomics is considered the link between genotypes and phenotypes. Feed efficiency is one of the most important phenotypes in sustainable pig production and is the main breeding goal trait. We utilized metabolic and genomic datasets from a total of 108 pigs from our own previously published studies that involved 59 Duroc and 49 Landrace pigs with data on feed efficiency (residual feed intake (RFI)), genotype (PorcineSNP80 BeadChip) data, and metabolomic data (45 final metabolite datasets derived from LC-MS system). Utilizing these datasets, our main aim was to identify genetic variants (single-nucleotide polymorphisms (SNPs)) that affect 45 different metabolite concentrations in plasma collected at the start and end of the performance testing of pigs categorized as high or low in their feed efficiency (based on RFI values). Genome-wide significant genetic variants could be then used as potential genetic or biomarkers in breeding programs for feed efficiency. The other objective was to reveal the biochemical mechanisms underlying genetic variation for pigs’ feed efficiency. In order to achieve these objectives, we firstly conducted a metabolite genome-wide association study (mGWAS) based on mixed linear models and found 152 genome-wide significant SNPs (p-value < 1.06 × 10−6) in association with 17 metabolites that included 90 significant SNPs annotated to 52 genes. On chromosome one alone, 51 significant SNPs associated with isovalerylcarnitine and propionylcarnitine were found to be in strong linkage disequilibrium (LD). SNPs in strong LD annotated to FBXL4, and CCNC consisted of two haplotype blocks where three SNPs (ALGA0004000, ALGA0004041, and ALGA0004042) were in the intron regions of FBXL4 and CCNC. The interaction network revealed that CCNC and FBXL4 were linked by the hub gene N6AMT1 that was associated with isovalerylcarnitine and propionylcarnitine. Moreover, three metabolites (i.e., isovalerylcarnitine, propionylcarnitine, and pyruvic acid) were clustered in one group based on the low-high RFI pigs. This study performed a comprehensive metabolite-based genome-wide association study (GWAS) analysis for pigs with differences in feed efficiency and provided significant metabolites for which there is significant genetic variation as well as biological interaction networks. The identified metabolite genetic variants, genes, and networks in high versus low feed efficient pigs could be considered as potential genetic or biomarkers for feed efficiency.
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47
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Zhuang Z, Ding R, Peng L, Wu J, Ye Y, Zhou S, Wang X, Quan J, Zheng E, Cai G, Huang W, Yang J, Wu Z. Genome-wide association analyses identify known and novel loci for teat number in Duroc pigs using single-locus and multi-locus models. BMC Genomics 2020; 21:344. [PMID: 32380955 PMCID: PMC7204245 DOI: 10.1186/s12864-020-6742-6] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2019] [Accepted: 04/16/2020] [Indexed: 12/31/2022] Open
Abstract
BACKGROUND More teats are necessary for sows to nurse larger litters to provide immunity and nutrient for piglets prior to weaning. Previous studies have reported the strong effect of an insertion mutation in the Vertebrae Development Associated (VRTN) gene on Sus scrofa chromosome 7 (SSC7) that increased the number of thoracic vertebrae and teat number in pigs. We used genome-wide association studies (GWAS) to map genetic markers and genes associated with teat number in two Duroc pig populations with different genetic backgrounds. A single marker method and several multi-locus methods were utilized. A meta-analysis that combined the effects and P-values of 34,681 single nucleotide polymorphisms (SNPs) that were common in the results of single marker GWAS of American and Canadian Duroc pigs was conducted. We also performed association tests between the VRTN insertion and teat number in the same populations. RESULTS A total of 97 SNPs were found to be associated with teat number. Among these, six, eight and seven SNPs were consistently detected with two, three and four multi-locus methods, respectively. Seven SNPs were concordantly identified between single marker and multi-locus methods. Moreover, 26 SNPs were newly found by multi-locus methods to be associated with teat number. Notably, we detected one consistent quantitative trait locus (QTL) on SSC7 for teat number using single-locus and meta-analysis of GWAS and the top SNP (rs692640845) explained 8.68% phenotypic variance of teat number in the Canadian Duroc pigs. The associations between the VRTN insertion and teat number in two Duroc pig populations were substantially weaker. Further analysis revealed that the effect of VRTN on teat number may be mediated by its LD with the true causal mutation. CONCLUSIONS Our study suggested that VRTN insertion may not be a strong or the only candidate causal mutation for the QTL on SSC7 for teat number in the analyzed Duroc pig populations. The combination of single-locus and multi-locus GWAS detected additional SNPs that were absent using only one model. The identified SNPs will be useful for the genetic improvement of teat number in pigs by assigning higher weights to associated SNPs in genomic selection.
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Affiliation(s)
- Zhanwei Zhuang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, 510642, People's Republic of China
| | - Rongrong Ding
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, 510642, People's Republic of China
| | - Longlong Peng
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, 510642, People's Republic of China
| | - Jie Wu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, 510642, People's Republic of China
| | - Yong Ye
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, 510642, People's Republic of China
| | - Shenping Zhou
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, 510642, People's Republic of China
| | - Xingwang Wang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, 510642, People's Republic of China
| | - Jianping Quan
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, 510642, People's Republic of China
| | - Enqin Zheng
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, 510642, People's Republic of China
| | - Gengyuan Cai
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, 510642, People's Republic of China
| | - Wen Huang
- Department of animal science, Michigan State University, East Lansing, MI, USA
| | - Jie Yang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, 510642, People's Republic of China.
| | - Zhenfang Wu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, 510642, People's Republic of China.
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48
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Banerjee P, Carmelo VAO, Kadarmideen HN. Genome-Wide Epistatic Interaction Networks Affecting Feed Efficiency in Duroc and Landrace Pigs. Front Genet 2020; 11:121. [PMID: 32184802 PMCID: PMC7058701 DOI: 10.3389/fgene.2020.00121] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2019] [Accepted: 01/31/2020] [Indexed: 12/12/2022] Open
Abstract
Interactions among genomic loci have often been overlooked in genome-wide association studies, revealing the combinatorial effects of variants on phenotype or disease manifestation. Unexplained genetic variance, interactions among causal genes of small effects, and biological pathways could be identified using a network biology approach. The main objective of this study was to determine the genome-wide epistatic variants affecting feed efficiency traits [feed conversion ratio (FCR) and residual feed intake (RFI)] based on weighted interaction SNP hub (WISH-R) method. Herein, we detected highly interconnected epistatic SNP modules, pathways, and potential biomarkers for the FCR and RFI in Duroc and Landrace purebreds considering the whole population, and separately for low and high feed efficient groups. Highly interacting SNP modules in Duroc (1,247 SNPs) and Landrace (1,215 SNPs) across the population and for low feed efficient (Duroc-80 SNPs, Landrace-146 SNPs) and high feed efficient group (Duroc-198 SNPs, Landrace-232 SNPs) for FCR and RFI were identified. Gene and pathway analyses identified ABL1, MAP3K4, MAP3K5, SEMA6A, KITLG, and KAT2B from chromosomes 1, 2, 5, and 13 underlying ErbB, Ras, Rap1, thyroid hormone, axon guidance pathways in Duroc. GABBR2, GNA12, and PRKCG genes from chromosomes 1, 3, and 6 pointed towards thyroid hormone, cGMP-PKG and cAMP pathways in Landrace. From Duroc low feed efficient group, the TPK1 gene was found involved with thiamine metabolism, whereas PARD6G, DLG2, CRB1 were involved with the hippo signaling pathway in high feed efficient group. PLOD1 and SETD7 genes were involved with lysine degradation in low feed efficient group in Landrace, while high feed efficient group pointed to genes underpinning valine, leucine, isoleucine degradation, and fatty acid elongation. Some SNPs and genes identified are known for their association with feed efficiency, others are novel and potentially provide new avenues for further research. Further validation of epistatic SNPs and genes identified here in a larger cohort would help to establish a framework for modelling epistatic variance in future methods of genomic prediction, increasing the accuracy of estimated genetic merit for FE and helping the pig breeding industry.
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Affiliation(s)
- Priyanka Banerjee
- Quantitative Genomics, Bioinformatics and Computational Biology Group, Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kongens Lyngby, Denmark
| | - Victor Adriano Okstoft Carmelo
- Quantitative Genomics, Bioinformatics and Computational Biology Group, Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kongens Lyngby, Denmark
| | - Haja N Kadarmideen
- Quantitative Genomics, Bioinformatics and Computational Biology Group, Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kongens Lyngby, Denmark
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49
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Hou X, Pu L, Wang L, Liu X, Gao H, Yan H, Zhang J, Zhang Y, Yue J, Zhang L, Wang L. Transcriptome Analysis of Skeletal Muscle in Pigs with Divergent Residual Feed Intake Phenotypes. DNA Cell Biol 2020; 39:404-416. [PMID: 32004088 DOI: 10.1089/dna.2019.4878] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022] Open
Abstract
Residual feed intake (RFI) is defined as the difference between the observed and expected feed intake for maintenance and growth requirements. In this study, the expression profiles of mRNAs and long noncoding RNAs (lncRNAs) from skeletal muscle in Duroc pigs with divergent RFI phenotypes were investigated by Illumina sequencing. Finally, a total of 2195 annotated lncRNAs and 1976 novel lncRNAs were obtained. About 210 mRNAs and 43 lncRNAs were differentially expressed among high and low RFI pigs. The differentially expressed mRNAs were potentially involved in the biological processes of lipid metabolism, extracellular matrix organization, cell proliferation, and cell adhesion. The lipolysis in skeletal muscle was increased in high RFI pigs, suggesting that high RFI pigs might need more energy than low RFI pigs. However, skeletal muscle development was increased in low RFI pigs. These results suggested that low RFI pigs might be more efficient in energy utilization during skeletal muscle growth. The function of lncRNA was also analyzed by target prediction. Nine lncRNAs might be candidate lncRNAs for the determination of RFI phenotype, by the regulation of the biological processes of lipid metabolism, cell proliferation, and cell adhesion. This study should facilitate a further understanding of the molecular mechanism for the determination of RFI phenotype in pigs.
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Affiliation(s)
- Xinhua Hou
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Lei Pu
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China.,College of Animal Science and Veterinary Medicine, Tianjin Agricultural University, Tianjin, China
| | - Ligang Wang
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Xin Liu
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Hongmei Gao
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Hua Yan
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Jinshan Zhang
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Yuebo Zhang
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Jingwei Yue
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Longchao Zhang
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Lixian Wang
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
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50
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Quan J, Wu Z, Ye Y, Peng L, Wu J, Ruan D, Qiu Y, Ding R, Wang X, Zheng E, Cai G, Huang W, Yang J. Metagenomic Characterization of Intestinal Regions in Pigs With Contrasting Feed Efficiency. Front Microbiol 2020; 11:32. [PMID: 32038603 PMCID: PMC6989599 DOI: 10.3389/fmicb.2020.00032] [Citation(s) in RCA: 41] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2019] [Accepted: 01/09/2020] [Indexed: 11/13/2022] Open
Abstract
Greater feed efficiency (FE) is critical in increasing profitability while reducing the environmental impact of pig production. Previous studies that identified swine FE-associated bacterial taxa were limited in either sampling sites or sequencing methods. This study characterized the microbiomes within the intestine of FE contrasting Duroc × (Landrace × Yorkshire) (DLY) pigs with a comprehensive representation of diverse sampling sites (ileum, cecum, and colon) and a metagenomic sequencing approach. A total of 226 pigs were ranked according to their FE between weaning to 140 day old, and six with extreme phenotypes were selected, three for each of the high and low groups. The results revealed that the cecum and colon had similar microbial taxonomic composition and function, and had higher capacity in polysaccharide metabolism than the ileum. We found in cecum that the high FE pigs had slightly higher richness and evenness in their micriobiota than the low FE pigs. We identified 12 phyla, 17 genera, and 39 species (e.g., Treponema porcinum, Treponema bryantii, and Firmicutes bacterium CAG:110) that were potentially associated with swine FE variation in cecum microbiota through LEfSe analysis. Species enriched in the cecum of the high FE pigs had a greater ability to utilize dietary polysaccharides and dietary protein according to the KEGG annotation. Analysis of antibiotic resistance based on the CARD database annotation indicated that the macB resistant gene might play an important role in shaping the microbial community in the cecum of pigs with contrasting FE. The bacteria from the genus Prevotella was highly enriched in the cecum of low FE pigs, which may impair the establishment of a more effective nutrient harvesting microbiota because of the interaction between Prevotella and other benefical microbes. These findings improved our understanding of the microbial compositions in the different gut locations of DLY pigs and identified many biomarkers associated with FE variation wich may be used to develop strategies to improve FE in pigs.
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Affiliation(s)
- Jianping Quan
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China.,Department of Animal Science, College of Agriculture and Natural Resources, Michigan State University, East Lansing, MI, United States
| | - Zhenfang Wu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
| | - Yong Ye
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
| | - Longlong Peng
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
| | - Jie Wu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
| | - Donglin Ruan
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
| | - Yibin Qiu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
| | - Rongrong Ding
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
| | - Xingwang Wang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
| | - Enqin Zheng
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
| | - Gengyuan Cai
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
| | - Wen Huang
- Department of Animal Science, College of Agriculture and Natural Resources, Michigan State University, East Lansing, MI, United States
| | - Jie Yang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
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