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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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Zhang L, Zhang S, Yuan M, Zhan F, Song M, Shang P, Yang F, Li X, Qiao R, Han X, Li X, Fang M, Wang K. Genome-Wide Association Studies and Runs of Homozygosity to Identify Reproduction-Related Genes in Yorkshire Pig Population. Genes (Basel) 2023; 14:2133. [PMID: 38136955 PMCID: PMC10742578 DOI: 10.3390/genes14122133] [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: 10/11/2023] [Revised: 11/10/2023] [Accepted: 11/19/2023] [Indexed: 12/24/2023] Open
Abstract
Reproductive traits hold considerable economic importance in pig breeding and production. However, candidate genes underpinning the reproductive traits are still poorly identified. In the present study, we executed a genome-wide association study (GWAS) and runs of homozygosity (ROH) analysis using the PorcineSNP50 BeadChip array for 585 Yorkshire pigs. Results from the GWAS identified two genome-wide significant and eighteen suggestive significant single nucleotide polymorphisms (SNPs) associated with seven reproductive traits. Furthermore, we identified candidate genes, including ELMO1, AOAH, INSIG2, NUP205, LYPLAL1, RPL34, LIPH, RNF7, GRK7, ETV5, FYN, and SLC30A5, which were chosen due to adjoining significant SNPs and their functions in immunity, fertilization, embryonic development, and sperm quality. Several genes were found in ROH islands associated with spermatozoa, development of the fetus, mature eggs, and litter size, including INSL6, TAF4B, E2F7, RTL1, CDKN1C, and GDF9. This study will provide insight into the genetic basis for pig reproductive traits, facilitating reproduction improvement using the marker-based selection methods.
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Affiliation(s)
- Lige Zhang
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450002, China; (L.Z.); (S.Z.); (M.Y.); (F.Z.); (M.S.); (F.Y.); (X.L.); (R.Q.); (X.H.); (X.L.)
| | - Songyuan Zhang
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450002, China; (L.Z.); (S.Z.); (M.Y.); (F.Z.); (M.S.); (F.Y.); (X.L.); (R.Q.); (X.H.); (X.L.)
| | - Meng Yuan
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450002, China; (L.Z.); (S.Z.); (M.Y.); (F.Z.); (M.S.); (F.Y.); (X.L.); (R.Q.); (X.H.); (X.L.)
| | - Fengting Zhan
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450002, China; (L.Z.); (S.Z.); (M.Y.); (F.Z.); (M.S.); (F.Y.); (X.L.); (R.Q.); (X.H.); (X.L.)
| | - Mingkun Song
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450002, China; (L.Z.); (S.Z.); (M.Y.); (F.Z.); (M.S.); (F.Y.); (X.L.); (R.Q.); (X.H.); (X.L.)
| | - Peng Shang
- Animal Science College, Tibet Agriculture and Animal Husbandry University, Linzhi 860000, China;
| | - Feng Yang
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450002, China; (L.Z.); (S.Z.); (M.Y.); (F.Z.); (M.S.); (F.Y.); (X.L.); (R.Q.); (X.H.); (X.L.)
| | - Xiuling Li
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450002, China; (L.Z.); (S.Z.); (M.Y.); (F.Z.); (M.S.); (F.Y.); (X.L.); (R.Q.); (X.H.); (X.L.)
| | - Ruimin Qiao
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450002, China; (L.Z.); (S.Z.); (M.Y.); (F.Z.); (M.S.); (F.Y.); (X.L.); (R.Q.); (X.H.); (X.L.)
| | - Xuelei Han
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450002, China; (L.Z.); (S.Z.); (M.Y.); (F.Z.); (M.S.); (F.Y.); (X.L.); (R.Q.); (X.H.); (X.L.)
| | - Xinjian Li
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450002, China; (L.Z.); (S.Z.); (M.Y.); (F.Z.); (M.S.); (F.Y.); (X.L.); (R.Q.); (X.H.); (X.L.)
| | - Meiying Fang
- Department of Animal Genetics and Breeding, National Engineering Laboratory for Animal Breeding, MOA Laboratory of Animal Genetics and Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Kejun Wang
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450002, China; (L.Z.); (S.Z.); (M.Y.); (F.Z.); (M.S.); (F.Y.); (X.L.); (R.Q.); (X.H.); (X.L.)
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Lakhssassi K, Meneses C, Sarto MP, Serrano M, Calvo JH. Genome-wide analysis reveals that the cytochrome P450 family 7 subfamily B member 1 gene is implicated in growth traits in Rasa Aragonesa ewes. Animal 2023; 17:100975. [PMID: 37734362 DOI: 10.1016/j.animal.2023.100975] [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: 03/29/2023] [Revised: 08/16/2023] [Accepted: 08/25/2023] [Indexed: 09/23/2023] Open
Abstract
Sheep are very well adapted to changing environments and are able to produce and reproduce with low inputs in feed and water better than other domestic ruminants. Indeed, the ewe body condition score (BCS) and live weight (LW) play a significant role in productive and reproductive performance. This work conducts a genome-wide association study (GWAS) to detect genetic variants associated with growth traits in 225 adult ewes of the Rasa Aragonesa breed by using the genotypes from 50 k and HD Illumina Ovine BeadChip. These ewes were measured for LW, BCS and growth rate (GR) for 2 years, from January to September. Corrected phenotypes for BCS, LW and GR were estimated and used as input for the GWAS. Only one single nucleotide polymorphism (SNP) rs425509273 in chromosome 9 (OAR9), associated with the GR, overcame the genome-wise significance level. One, three and nine SNPs were associated at the chromosome-wise level (FDR 10%) for traits BCS, LW and GR, respectively. The cytochrome P450 family 7 subfamily B member 1 (CYP7B1) candidate gene, located 83 kb upstream from SNP rs425509273 in OAR9, was partially isolated and Sanger-sequenced. Fifteen polymorphisms comprising 12 SNPs, two indels and one polyC, were detected in promoter, exon 1, 3, 5, and intron 1-3 region. The SNP association analysis of the polymorphisms located close to the transcription start site (TSS) showed that a 22 bp insertion located at -58 nucleotides from the TSS (indel (-58)), a polyC (-25), and two A/G SNPs (SNP3 (-114) and SNP5 (-63)) were associated with the GR trait, whereas only the indel (-58) was associated with the BCS trait. The haplotype analysis confirmed these results. The functional characterisation of the polymorphisms at CYP7B1 gene in liver by real-time quantitative PCR analysis confirmed that the mutations in the promoter region affected CYP7B1 gene expression. Our results demonstrated the involvement of the CYP7B1 gene promoter on GR and BCS traits in Rasa Aragonesa. These findings suggest that variations in ovine CYP7B1 may serve as potential genetic markers to be used in breeding programmes to improve growth characteristics that could influence reproductive traits.
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Affiliation(s)
- K Lakhssassi
- Departamento de Ciencia Animal, Centro de Investigación y Tecnología Agroalimentaria de Aragón (CITA-IA2), Avda. Montañana 930, 50059 Zaragoza, Spain; Research Unit of Animal Production, National Institute for Agronomic Research (INRA), BP 6356, Institutes 10101, Rabat, Morocco
| | - C Meneses
- Departamento de Mejora Genética Animal, Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA-CSIC), 28040 Madrid, Spain
| | - M P Sarto
- Departamento de Ciencia Animal, Centro de Investigación y Tecnología Agroalimentaria de Aragón (CITA-IA2), Avda. Montañana 930, 50059 Zaragoza, Spain
| | - M Serrano
- Departamento de Mejora Genética Animal, Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA-CSIC), 28040 Madrid, Spain.
| | - J H Calvo
- Departamento de Ciencia Animal, Centro de Investigación y Tecnología Agroalimentaria de Aragón (CITA-IA2), Avda. Montañana 930, 50059 Zaragoza, Spain; Aragonese Foundation for Research and Development (ARAID), 50018 Zaragoza, Spain
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Genome-Wide Association Study of Growth Traits in a Four-Way Crossbred Pig Population. Genes (Basel) 2022; 13:genes13111990. [DOI: 10.3390/genes13111990] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2022] [Revised: 10/28/2022] [Accepted: 10/28/2022] [Indexed: 11/04/2022] Open
Abstract
Growth traits are crucial economic traits in the commercial pig industry and have a substantial impact on pig production. However, the genetic mechanism of growth traits is not very clear. In this study, we performed a genome-wide association study (GWAS) based on the specific-locus amplified fragment sequencing (SLAF-seq) to analyze ten growth traits on 223 four-way intercross pigs. A total of 227,921 highly consistent single nucleotide polymorphisms (SNPs) uniformly dispersed throughout the entire genome were used to conduct GWAS. A total of 53 SNPs were identified for ten growth traits using the mixed linear model (MLM), of which 18 SNPs were located in previously reported quantitative trait loci (QTL) regions. Two novel QTLs on SSC4 and SSC7 were related to average daily gain from 30 to 60 kg (ADG30–60) and body length (BL), respectively. Furthermore, 13 candidate genes (ATP5O, GHRHR, TRIM55, EIF2AK1, PLEKHA1, BRAP, COL11A2, HMGA1, NHLRC1, SGSM1, NFATC2, MAML1, and PSD3) were found to be associated with growth traits in pigs. The GWAS findings will enhance our comprehension of the genetic architecture of growth traits. We suggested that these detected SNPs and corresponding candidate genes might provide a biological foundation for improving the growth and production performance of pigs in swine breeding.
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Genome-Wide Association Study Reveals Additive and Non-Additive Effects on Growth Traits in Duroc Pigs. Genes (Basel) 2022; 13:genes13081454. [PMID: 36011365 PMCID: PMC9407794 DOI: 10.3390/genes13081454] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2022] [Revised: 08/12/2022] [Accepted: 08/13/2022] [Indexed: 12/24/2022] Open
Abstract
Growth rate plays a critical role in the pig industry and is related to quantitative traits controlled by many genes. Here, we aimed to identify causative mutations and candidate genes responsible for pig growth traits. In this study, 2360 Duroc pigs were used to detect significant additive, dominance, and epistatic effects associated with growth traits. As a result, a total number of 32 significant SNPs for additive or dominance effects were found to be associated with various factors, including adjusted age at a specified weight (AGE), average daily gain (ADG), backfat thickness (BF), and loin muscle depth (LMD). In addition, the detected additive significant SNPs explained 2.49%, 3.02%, 3.18%, and 1.96% of the deregressed estimated breeding value (DEBV) variance for AGE, ADG, BF, and LMD, respectively, while significant dominance SNPs could explain 2.24%, 13.26%, and 4.08% of AGE, BF, and LMD, respectively. Meanwhile, a total of 805 significant epistatic effects SNPs were associated with one of ADG, AGE, and LMD, from which 11 sub-networks were constructed. In total, 46 potential genes involved in muscle development, fat deposition, and regulation of cell growth were considered as candidates for growth traits, including CD55 and NRIP1 for AGE and ADG, TRIP11 and MIS2 for BF, and VRTN and ZEB2 for LMD, respectively. Generally, in this study, we detected both new and reported variants and potential candidate genes for growth traits of Duroc pigs, which might to be taken into account in future molecular breeding programs to improve the growth performance of pigs.
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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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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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Nguyen LT, Lau LY, Fortes MRS. Proteomic Analysis of Hypothalamus and Pituitary Gland in Pre and Postpubertal Brahman Heifers. Front Genet 2022; 13:935433. [PMID: 35774501 PMCID: PMC9237413 DOI: 10.3389/fgene.2022.935433] [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: 05/03/2022] [Accepted: 05/25/2022] [Indexed: 11/28/2022] Open
Abstract
The hypothalamus and the pituitary gland are directly involved in the complex systemic changes that drive the onset of puberty in cattle. Here, we applied integrated bioinformatics to elucidate the critical proteins underlying puberty and uncover potential molecular mechanisms from the hypothalamus and pituitary gland of prepubertal (n = 6) and postpubertal (n = 6) cattle. Proteomic analysis in the hypothalamus and pituitary gland revealed 275 and 186 differentially abundant (DA) proteins, respectively (adjusted p-value < 0.01). The proteome profiles found herein were integrated with previously acquired transcriptome profiles. These transcriptomic studies used the same tissues harvested from the same heifers at pre- and post-puberty. This comparison detected a small number of matched transcripts and protein changes at puberty in each tissue, suggesting the need for multiple omics analyses for interpreting complex biological systems. In the hypothalamus, upregulated DA proteins at post-puberty were enriched in pathways related to puberty, including GnRH, calcium and oxytocin signalling pathways, whereas downregulated proteins were observed in the estrogen signalling pathway, axon guidance and GABAergic synapse. Additionally, this study revealed that ribosomal pathway proteins in the pituitary were involved in the pubertal development of mammals. The reported molecules and derived protein-protein networks are a starting point for future experimental approaches that might dissect with more detail the role of each molecule to provide new insights into the mechanisms of puberty onset in cattle.
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Affiliation(s)
- Loan To Nguyen
- Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, Brisbane, Australia
- *Correspondence: Loan To Nguyen,
| | - Li Yieng Lau
- Agency of Science, Technology and Research, Singapore, Singapore
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Zhang M, Guo Y, Su R, Corazzin M, Li J, Huang H, Zhang Y, Yao D, Su L, Zhao L, Jin Y. Effects of physical exercise on muscle metabolism and meat quality characteristics of Mongolian sheep. Food Sci Nutr 2022; 10:1494-1509. [PMID: 35592278 PMCID: PMC9094461 DOI: 10.1002/fsn3.2768] [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] [Indexed: 01/21/2023] Open
Abstract
The objective of this study was to investigate the effects of exercise training on muscle metabolism, fatty acid composition, carcass traits, and meat quality characteristics of Mongolian sheep. Fourteen Mongolian sheep were randomly divided into two groups (7 sheep in each) and placed in two adjacent livestock pens. One group of sheep was kept in the pen (Control [C] group) and the other group of sheep (Training [T] group) were driven away in a field to walk twice a day. The results showed a reduction in pH measured 45 min post mortem, L*, a*, and b* value, intramuscular fat, and carcass length, and an increase in the ultimate pH value and shear force in the meat of T group in comparison with that of C group (p < .050). Also, exercise training moderately affected the fatty acid composition of LT muscle. Compared with C group, the concentrations of myristoleic acid (C14:1) and stearic acid (C18:0) were increased (p < .050), while the concentrations of C20:3 n‐6, neurolic acid (C24:1), and n‐3 polyunsaturated fatty acid (PUFA) were decreased in T group (p < .050). Transcriptome analysis highlighted 621 genes differentially expressed in two groups, including 385 were up‐regulated (e.g., GLUT4 and PGC‐1α) and 236 were down‐regulated (e.g., PLIN1 and ACSL3) in T with respect to C group. Besides, considering these genes, a number of enrichment pathways related to muscle metabolic processes, involving carbohydrate metabolism, lipid metabolism, oxidation reduction process, and muscle tissue development, were highlighted. In conclusion, these results contributed to a better understanding of the possible biological and molecular processes underlying the effects of exercise training on muscle metabolism and meat quality in Mongolian sheep, and provide useful information for contributing to understand the phenotypic and functional differences in meat quality of sheep.
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Affiliation(s)
- Min Zhang
- College of Food Science and Engineering Inner Mongolia Agriculture University Hohhot China
| | - Yueying Guo
- College of Food Science and Engineering Inner Mongolia Agriculture University Hohhot China
| | - Rina Su
- Inner Mongolia Vocational College of Chemical Engineering Hohhot China
| | - Mirco Corazzin
- Dipartimento di Scienze Animali Università di Udine Italy
| | - Jiale Li
- College of Food Science and Engineering Inner Mongolia Agriculture University Hohhot China
| | - Huan Huang
- College of Food Science and Engineering Inner Mongolia Agriculture University Hohhot China
| | - Yue Zhang
- College of Food Science and Engineering Inner Mongolia Agriculture University Hohhot China
| | - Duo Yao
- College of Food Science and Engineering Inner Mongolia Agriculture University Hohhot China
| | - Lin Su
- College of Food Science and Engineering Inner Mongolia Agriculture University Hohhot China
| | - Lihua Zhao
- College of Food Science and Engineering Inner Mongolia Agriculture University Hohhot China
| | - Ye Jin
- College of Food Science and Engineering Inner Mongolia Agriculture University Hohhot China
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Xu Q, Zhao J, Guo Y, Liu M, Schinckel AP, Zhou B. A Single-Nucleotide Polymorphism in the Promoter of Porcine ARHGAP24 Gene Regulates Aggressive Behavior of Weaned Pigs After Mixing by Affecting the Binding of Transcription Factor p53. Front Cell Dev Biol 2022; 10:839583. [PMID: 35433684 PMCID: PMC9010951 DOI: 10.3389/fcell.2022.839583] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Accepted: 02/28/2022] [Indexed: 11/18/2022] Open
Abstract
Pigs are important biomedical model animals for the study of human neurological diseases. Similar to human aggressive behavior in children and adolescents, weaned pigs also show more aggressive behavior after mixing, which has negative effects on animal welfare and growth performance. The identification of functional single-nucleotide polymorphisms (SNPs) related to the aggressive behavior of pigs would provide valuable molecular markers of the aggressive behavioral trait for genetic improvement program. The Rho GTPase–activating protein 24 (ARHGAP24) gene plays an important role in regulating the process of axon guidance, which may impact the aggressive behavior of pigs. By resequencing the entire coding region, partially adjacent introns and the 5′ and 3′ flanking regions, six and four SNPs were identified in the 5′ flanking region and 5′ untranslated region (UTR) of the porcine ARHGAP24 gene, respectively. Association analyses revealed that nine SNPs were significantly associated with aggressive behavioral traits (p = < 1.00 × 10–4–4.51 × 10–2), and their haplotypes were significantly associated with aggressive behavior (p = < 1.00 × 10–4–2.99 × 10–2). The core promoter region of the ARHGAP24 gene has been identified between −670 and −1,113 bp. Furthermore, the luciferase activity of allele A of rs335052970 was significantly less than that of allele G, suggesting that the transcriptional activity of the ARHGAP24 gene was inhibited by allele A of rs335052970. It was identified that the transcription factor p53 bound to the transcription factor binding sites (TFBSs) containing allele A of rs335052970. In porcine primary neural cells, p53 binds to the target promoter region of the ARHGAP24 gene, reduces its promoter transcriptional activity, and then reduces its messenger RNA (mRNA) and protein expression. The results demonstrated that the ARHGAP24 gene had significant genetic effects on aggressive behavioral traits of pigs. Therefore, rs335052970 in the ARHGAP24 gene can be used as a molecular marker to select the less aggressive pigs.
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Affiliation(s)
- Qinglei Xu
- College of Animal Science and Technology, Nanjing Agricultural University, Nanjing, China
| | - Jing Zhao
- College of Animal Science and Technology, Nanjing Agricultural University, Nanjing, China
| | - Yanli Guo
- College of Animal Science and Technology, Nanjing Agricultural University, Nanjing, China
| | - Mingzheng Liu
- College of Animal Science and Technology, Nanjing Agricultural University, Nanjing, China
| | - Allan P. Schinckel
- Department of Animal Sciences, Purdue University, West Lafayette, IN, United States
| | - Bo Zhou
- College of Animal Science and Technology, Nanjing Agricultural University, Nanjing, China
- *Correspondence: Bo Zhou,
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11
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Zhao H, Zhu S, Guo T, Han M, Chen B, Qiao G, Wu Y, Yuan C, Liu J, Lu Z, Sun W, Wang T, Li F, Zhang Y, Hou F, Yue Y, Yang B. Whole-genome re-sequencing association study on yearling wool traits in Chinese fine-wool sheep. J Anim Sci 2021; 99:6319907. [PMID: 34255028 PMCID: PMC8418636 DOI: 10.1093/jas/skab210] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2020] [Accepted: 07/10/2021] [Indexed: 12/11/2022] Open
Abstract
To investigate single nucleotide polymorphism (SNP) loci associated with yearling wool traits of fine-wool sheep for optimizing marker-assisted selection and dissection of the genetic architecture of wool traits, we conducted a genome-wide association study (GWAS) based on the fixed and random model circulating probability unification (FarmCPU) for yearling staple length (YSL), yearling mean fiber diameter (YFD), yearling greasy fleece weight (YGFW), and yearling clean fleece rate (YCFR) by using the whole-genome re-sequenced data (totaling 577 sheep) from the following four fine-wool sheep breeds in China: Alpine Merino sheep (AMS), Chinese Merino sheep (CMS), Qinghai fine-wool sheep (QHS), and Aohan fine-wool sheep (AHS). A total of 16 SNPs were detected above the genome-wise significant threshold (P = 5.45E-09), and 79 SNPs were located above the suggestive significance threshold (P = 5.00E-07) from the GWAS results. For YFD and YGFW traits, 7 and 9 SNPs reached the genome-wise significance thresholds, whereas 10 and 12 SNPs reached the suggestive significance threshold, respectively. For YSL and YCFR traits, none of the SNPs reached the genome-wise significance thresholds, whereas 57 SNPs exceeded the suggestive significance threshold. We recorded 14 genes located at the region of ±50-kb near the genome-wise significant SNPs and 59 genes located at the region of ±50-kb near the suggestive significant SNPs. Meanwhile, we used the Average Information Restricted Maximum likelihood algorithm (AI-REML) in the “HIBLUP” package to estimate the heritability and variance components of the four desired yearling wool traits. The estimated heritability values (h2) of YSL, YFD, YGFW, and YCFR were 0.6208, 0.7460, 0.6758, and 0.5559, respectively. We noted that the genetic parameters in this study can be used for fine-wool sheep breeding. The newly detected significant SNPs and the newly identified candidate genes in this study would enhance our understanding of yearling wool formation, and significant SNPs can be applied to genome selection in fine-wool sheep breeding.
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Affiliation(s)
- Hongchang Zhao
- Lanzhou Institute of Husbandry and Pharmaceutical Sciences of Chinese Academy of Agricultural Sciences, Sheep Breeding Engineering Technology Research Center, Lanzhou, 730050, China
| | - Shaohua Zhu
- Lanzhou Institute of Husbandry and Pharmaceutical Sciences of Chinese Academy of Agricultural Sciences, Sheep Breeding Engineering Technology Research Center, Lanzhou, 730050, China
| | - Tingting Guo
- Lanzhou Institute of Husbandry and Pharmaceutical Sciences of Chinese Academy of Agricultural Sciences, Sheep Breeding Engineering Technology Research Center, Lanzhou, 730050, China
| | - Mei Han
- Lanzhou Institute of Husbandry and Pharmaceutical Sciences of Chinese Academy of Agricultural Sciences, Sheep Breeding Engineering Technology Research Center, Lanzhou, 730050, China
| | - Bowen Chen
- Lanzhou Institute of Husbandry and Pharmaceutical Sciences of Chinese Academy of Agricultural Sciences, Sheep Breeding Engineering Technology Research Center, Lanzhou, 730050, China
| | - Guoyan Qiao
- Lanzhou Institute of Husbandry and Pharmaceutical Sciences of Chinese Academy of Agricultural Sciences, Sheep Breeding Engineering Technology Research Center, Lanzhou, 730050, China
| | - Yi Wu
- Lanzhou Institute of Husbandry and Pharmaceutical Sciences of Chinese Academy of Agricultural Sciences, Sheep Breeding Engineering Technology Research Center, Lanzhou, 730050, China
| | - Chao Yuan
- Lanzhou Institute of Husbandry and Pharmaceutical Sciences of Chinese Academy of Agricultural Sciences, Sheep Breeding Engineering Technology Research Center, Lanzhou, 730050, China
| | - Jianbin Liu
- Lanzhou Institute of Husbandry and Pharmaceutical Sciences of Chinese Academy of Agricultural Sciences, Sheep Breeding Engineering Technology Research Center, Lanzhou, 730050, China
| | - Zengkui Lu
- Lanzhou Institute of Husbandry and Pharmaceutical Sciences of Chinese Academy of Agricultural Sciences, Sheep Breeding Engineering Technology Research Center, Lanzhou, 730050, China
| | - Weibo Sun
- Lanzhou Institute of Husbandry and Pharmaceutical Sciences of Chinese Academy of Agricultural Sciences, Sheep Breeding Engineering Technology Research Center, Lanzhou, 730050, China
| | - Tianxiang Wang
- Gansu Provincial Sheep Breeding Technology Extension Station, Sunan, 734031, China
| | - Fanwen Li
- Gansu Provincial Sheep Breeding Technology Extension Station, Sunan, 734031, China
| | - Yajun Zhang
- Xinjiang Gongnaisi Breeding Sheep Farm, Xinyuan, 835808, China
| | - Fujun Hou
- Aohan Banner Breeding Sheep Farm, Chifeng, 024300, China
| | - Yaojing Yue
- Lanzhou Institute of Husbandry and Pharmaceutical Sciences of Chinese Academy of Agricultural Sciences, Sheep Breeding Engineering Technology Research Center, Lanzhou, 730050, China
| | - Bohui Yang
- Lanzhou Institute of Husbandry and Pharmaceutical Sciences of Chinese Academy of Agricultural Sciences, Sheep Breeding Engineering Technology Research Center, Lanzhou, 730050, China
- Corresponding author:
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12
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Hong Y, Ye J, Dong L, Li Y, Yan L, Cai G, Liu D, Tan C, Wu Z. Genome-Wide Association Study for Body Length, Body Height, and Total Teat Number in Large White Pigs. Front Genet 2021; 12:650370. [PMID: 34408768 PMCID: PMC8366400 DOI: 10.3389/fgene.2021.650370] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2021] [Accepted: 06/15/2021] [Indexed: 01/08/2023] Open
Abstract
Body length, body height, and total teat number are economically important traits in pig breeding, as these traits are usually associated with the growth, reproductivity, and longevity potential of piglets. Here, we report a genetic analysis of these traits using a population comprising 2,068 Large White pigs. A genotyping-by-sequencing (GBS) approach was used to provide high-density genome-wide SNP discovery and genotyping. Univariate and bivariate animal models were used to estimate heritability and genetic correlations. The results showed that heritability estimates for body length, body height, and total teat number were 0.25 ± 0.04, 0.11 ± 0.03, and 0.22 ± 0.04, respectively. The genetic correlation between body length and body height exhibited a strongly positive correlation (0.63 ± 0.15), while a positive but low genetic correlation was observed between total teat number and body length. Furthermore, we used two different genome-wide association study (GWAS) approaches: single-locus GWAS and weighted single-step GWAS (WssGWAS), to identify candidate genes for these traits. Single-locus GWAS detected 76, 13, and 29 significant single-nucleotide polymorphisms (SNPs) associated with body length, body height, and total teat number. Notably, the most significant SNP (S17_15781294), which is located 20 kb downstream of the BMP2 gene, explained 9.09% of the genetic variance for body length traits, and it also explained 9.57% of the genetic variance for body height traits. In addition, another significant SNP (S7_97595973), which is located in the ABCD4 gene, explained 8.92% of the genetic variance for total teat number traits. GWAS results for these traits identified some candidate genomic regions, such as SSC6: 14.96–15.02 Mb, SSC7: 97.18–98.18 Mb, SSC14: 128.29–131.15 Mb, SSC17: 15.39–17.27 Mb, and SSC17: 22.04–24.15 Mb, providing a starting point for further inheritance research. Most quantitative trait loci were detected by single-locus GWAS and WssGWAS. These findings reveal the complexity of the genetic mechanism of the three traits and provide guidance for subsequent genetic improvement through genome selection.
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Affiliation(s)
- Yifeng Hong
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China.,National Engineering Research Center for Breeding Swine Industry, Wens Foodstuff Group Co., Ltd., Yunfu, China
| | - Jian Ye
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China.,National Engineering Research Center for Breeding Swine Industry, Wens Foodstuff Group Co., Ltd., Yunfu, China
| | - Linsong Dong
- National Engineering Research Center for Breeding Swine Industry, Wens Foodstuff Group Co., Ltd., Yunfu, China
| | - Yalan Li
- National Engineering Research Center for Breeding Swine Industry, Wens Foodstuff Group Co., Ltd., Yunfu, China
| | - Limin Yan
- National Engineering Research Center for Breeding Swine Industry, Wens Foodstuff Group Co., Ltd., Yunfu, China
| | - Gengyuan Cai
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China.,National Engineering Research Center for Breeding Swine Industry, Wens Foodstuff Group Co., Ltd., Yunfu, China
| | - Dewu Liu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
| | - Cheng Tan
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China.,National Engineering Research Center for Breeding Swine Industry, Wens Foodstuff Group Co., Ltd., Yunfu, China
| | - Zhenfang Wu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, 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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13
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A compendium and comparative epigenomics analysis of cis-regulatory elements in the pig genome. Nat Commun 2021; 12:2217. [PMID: 33850120 PMCID: PMC8044108 DOI: 10.1038/s41467-021-22448-x] [Citation(s) in RCA: 59] [Impact Index Per Article: 19.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2020] [Accepted: 03/15/2021] [Indexed: 02/01/2023] Open
Abstract
Although major advances in genomics have initiated an exciting new era of research, a lack of information regarding cis-regulatory elements has limited the genetic improvement or manipulation of pigs as a meat source and biomedical model. Here, we systematically characterize cis-regulatory elements and their functions in 12 diverse tissues from four pig breeds by adopting similar strategies as the ENCODE and Roadmap Epigenomics projects, which include RNA-seq, ATAC-seq, and ChIP-seq. In total, we generate 199 datasets and identify more than 220,000 cis-regulatory elements in the pig genome. Surprisingly, we find higher conservation of cis-regulatory elements between human and pig genomes than those between human and mouse genomes. Furthermore, the differences of topologically associating domains between the pig and human genomes are associated with morphological evolution of the head and face. Beyond generating a major new benchmark resource for pig epigenetics, our study provides basic comparative epigenetic data relevant to using pigs as models in human biomedical research.
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14
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Gao G, Gao N, Li S, Kuang W, Zhu L, Jiang W, Yu W, Guo J, Li Z, Yang C, Zhao Y. Genome-Wide Association Study of Meat Quality Traits in a Three-Way Crossbred Commercial Pig Population. Front Genet 2021; 12:614087. [PMID: 33815461 PMCID: PMC8010252 DOI: 10.3389/fgene.2021.614087] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2020] [Accepted: 02/12/2021] [Indexed: 01/12/2023] Open
Abstract
Meat quality is an important trait for pig-breeding programs aiming to meet consumers' demands. Geneticists must improve meat quality based on their understanding of the underlying genetic mechanisms. Previous studies showed that most meat-quality indicators were low-to-moderate heritability traits; therefore, improving meat quality using conventional techniques remains a challenge. Here, we performed a genome-wide association study of meat-quality traits using the GeneSeek Porcine SNP50K BeadChip in 582 crossbred Duroc × (Landrace × Yorkshire) commercial pigs (249 males and 333 females). Meat conductivity, marbling score, moisture, meat color, pH, and intramuscular fat (IMF) content were investigated. The genome-wide association study was performed using both fixed and random model Circulating Probability Unification (FarmCPU) and a mixed linear model (MLM) with the rMVP software. The genomic heritability of the studied traits ranged from 0.13 ± 0.07 to 0.55 ± 0.08 for conductivity and meat color, respectively. Thirty-two single-nucleotide polymorphisms (SNPs) were identified for meat quality in the crossbred pigs using both FarmCPU and MLM. Among the detected SNPs, five, nine, seven, four, six, and five were significantly associated with conductivity, IMF, marbling score, meat color, moisture, and pH, respectively. Several candidate genes for meat quality were identified in the detected genomic regions. These findings will contribute to the ongoing improvement of meat quality, meeting consumer demands and improving the economic outlook for the swine industry.
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Affiliation(s)
- Guangxiong Gao
- School of Life Sciences and Engineering, Foshan University, Foshan, China
| | - Ning Gao
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou, China
- Guangxi Yangxiang Co., Ltd., Guigang, China
| | - Sicheng Li
- Guangxi Yangxiang Co., Ltd., Guigang, China
| | - Weijian Kuang
- School of Life Sciences and Engineering, Foshan University, Foshan, China
| | - Lin Zhu
- Guangxi Yangxiang Co., Ltd., Guigang, China
| | - Wei Jiang
- Guangxi Yangxiang Co., Ltd., Guigang, China
| | - Weiwei Yu
- School of Life Sciences and Engineering, Foshan University, Foshan, China
| | - Jinbiao Guo
- School of Life Sciences and Engineering, Foshan University, Foshan, China
| | - Zhili Li
- School of Life Sciences and Engineering, Foshan University, Foshan, China
| | - Chengzhong Yang
- School of Life Sciences and Engineering, Foshan University, Foshan, China
| | - Yunxiang Zhao
- School of Life Sciences and Engineering, Foshan University, Foshan, China
- Guangxi Yangxiang Co., Ltd., Guigang, China
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15
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Wu X, Zhou R, Zhang W, Cao B, Xia J, Caiyun W, Zhang X, Chu M, Yin Z, Ding Y. Genome-wide scan for runs of homozygosity identifies candidate genes in Wannan Black pigs. Anim Biosci 2021; 34:1895-1902. [PMID: 33705632 PMCID: PMC8563231 DOI: 10.5713/ab.20.0679] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2020] [Accepted: 02/07/2021] [Indexed: 11/27/2022] Open
Abstract
Objective Runs of homozygosity (ROH) are contiguous lengths of homozygous genotypes that can reveal inbreeding levels, selection pressure, and mating schemes. In this study, ROHs were evaluated in Wannan Black pigs to assess the inbreeding levels and the genome regions with high ROH frequency. Methods In a previous study, we obtained 501.52 GB of raw data from resequencing (10×) of the genome and identified 21,316,754 single-nucleotide variants in 20 Wannan Black pig samples. We investigated the number, length, and frequency of ROH using resequencing data to characterize the homozygosity in Wannan Black pigs and identified genomic regions with high ROH frequencies. Results In this work, 1,813 ROHs (837 ROHs in 100 to 500 kb, 449 ROHs in 500 to 1,000 kb, 527 ROHs in >1,000 kb) were identified in all samples, and the average genomic inbreeding coefficient (FROH) in Wannan Black pigs was 0.5234. Sixty-one regions on chromosomes 2, 3, 7, 8, 13, 15, and 16 harbored ROH islands. In total, 105 genes were identified in 42 ROH islands, among which some genes were related to production traits. Conclusion This is the first study to identify ROH across the genome of Wannan Black pigs, the Chinese native breed of the Anhui province. Overall, Wannan Black pigs have high levels of inbreeding due to the influence of ancient and recent inbreeding due to the genome. These findings are a reliable resource for future studies and contribute to save and use the germplasm resources of Wannan Black pigs.
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Affiliation(s)
- Xudong Wu
- College of Animal Science and Technology, Anhui Agricultural University, Hefei, Anhui 230036, P. R. China.,Anhui province key laboratory of local livestock and poultry genetic resource conservation and bio-breeding, Anhui Agricultural University, Hefei, 230036, P.R. China
| | - Ren Zhou
- College of Animal Science and Technology, Anhui Agricultural University, Hefei, Anhui 230036, P. R. China.,Anhui province key laboratory of local livestock and poultry genetic resource conservation and bio-breeding, Anhui Agricultural University, Hefei, 230036, P.R. China
| | - Wei Zhang
- College of Animal Science and Technology, Anhui Agricultural University, Hefei, Anhui 230036, P. R. China.,Key Laboratory of Pig Molecular Quantitative Genetics of Anhui Academy of Agricultural Sciences, Anhui Provincial Key Laboratory of Livestock and Poultry Product Safety Engineering, Institute of Animal Husbandry and Veterinary Medicine, Anhui Academy of Agricultural Sciences, Hefei, Anhui 230031, P.R. China
| | - Bangji Cao
- College of Animal Science and Technology, Anhui Agricultural University, Hefei, Anhui 230036, P. R. China.,Anhui province key laboratory of local livestock and poultry genetic resource conservation and bio-breeding, Anhui Agricultural University, Hefei, 230036, P.R. China
| | - Jing Xia
- College of Animal Science and Technology, Anhui Agricultural University, Hefei, Anhui 230036, P. R. China.,Anhui province key laboratory of local livestock and poultry genetic resource conservation and bio-breeding, Anhui Agricultural University, Hefei, 230036, P.R. China
| | - Wang Caiyun
- College of Animal Science and Technology, Anhui Agricultural University, Hefei, Anhui 230036, P. R. China.,Anhui province key laboratory of local livestock and poultry genetic resource conservation and bio-breeding, Anhui Agricultural University, Hefei, 230036, P.R. China
| | - Xiaodong Zhang
- College of Animal Science and Technology, Anhui Agricultural University, Hefei, Anhui 230036, P. R. China.,Anhui province key laboratory of local livestock and poultry genetic resource conservation and bio-breeding, Anhui Agricultural University, Hefei, 230036, P.R. China
| | - Mingxing Chu
- Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing,100193, P. R. China
| | - Zongjun Yin
- College of Animal Science and Technology, Anhui Agricultural University, Hefei, Anhui 230036, P. R. China.,Anhui province key laboratory of local livestock and poultry genetic resource conservation and bio-breeding, Anhui Agricultural University, Hefei, 230036, P.R. China
| | - Yueyun Ding
- College of Animal Science and Technology, Anhui Agricultural University, Hefei, Anhui 230036, P. R. China.,Anhui province key laboratory of local livestock and poultry genetic resource conservation and bio-breeding, Anhui Agricultural University, Hefei, 230036, P.R. China
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16
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Zhou S, Ding R, Meng F, Wang X, Zhuang Z, Quan J, Geng Q, Wu J, Zheng E, Wu Z, Yang J, Yang J. A meta-analysis of genome-wide association studies for average daily gain and lean meat percentage in two Duroc pig populations. BMC Genomics 2021; 22:12. [PMID: 33407097 PMCID: PMC7788875 DOI: 10.1186/s12864-020-07288-1] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2020] [Accepted: 11/28/2020] [Indexed: 02/07/2023] Open
Abstract
Background Average daily gain (ADG) and lean meat percentage (LMP) are the main production performance indicators of pigs. Nevertheless, the genetic architecture of ADG and LMP is still elusive. Here, we conducted genome-wide association studies (GWAS) and meta-analysis for ADG and LMP in 3770 American and 2090 Canadian Duroc pigs. Results In the American Duroc pigs, one novel pleiotropic quantitative trait locus (QTL) on Sus scrofa chromosome 1 (SSC1) was identified to be associated with ADG and LMP, which spans 2.53 Mb (from 159.66 to 162.19 Mb). In the Canadian Duroc pigs, two novel QTLs on SSC1 were detected for LMP, which were situated in 3.86 Mb (from 157.99 to 161.85 Mb) and 555 kb (from 37.63 to 38.19 Mb) regions. The meta-analysis identified ten and 20 additional SNPs for ADG and LMP, respectively. Finally, four genes (PHLPP1, STC1, DYRK1B, and PIK3C2A) were detected to be associated with ADG and/or LMP. Further bioinformatics analysis showed that the candidate genes for ADG are mainly involved in bone growth and development, whereas the candidate genes for LMP mainly participated in adipose tissue and muscle tissue growth and development. Conclusions We performed GWAS and meta-analysis for ADG and LMP based on a large sample size consisting of two Duroc pig populations. One pleiotropic QTL that shared a 2.19 Mb haplotype block from 159.66 to 161.85 Mb on SSC1 was found to affect ADG and LMP in the two Duroc pig populations. Furthermore, the combination of single-population and meta-analysis of GWAS improved the efficiency of detecting additional SNPs for the analyzed traits. Our results provide new insights into the genetic architecture of ADG and LMP traits in pigs. Moreover, some significant SNPs associated with ADG and/or LMP in this study may be useful for marker-assisted selection in pig breeding.
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Affiliation(s)
- Shenping Zhou
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, 510642, Guangdong, 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, 510642, Guangdong, People's Republic of 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, Guangdong, 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, 510642, Guangdong, 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, 510642, Guangdong, 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, 510642, Guangdong, 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, 510642, Guangdong, 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, 510642, Guangdong, 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, 510642, Guangdong, 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, 510642, Guangdong, People's Republic of China
| | - Jianhui Yang
- YueYang Vocational Technical College, Yueyang, 414000, Hunan, 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, 510642, Guangdong, People's Republic of China.
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17
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Xue Y, Li C, Duan D, Wang M, Han X, Wang K, Qiao R, Li XJ, Li XL. Genome-wide association studies for growth-related traits in a crossbreed pig population. Anim Genet 2020; 52:217-222. [PMID: 33372713 DOI: 10.1111/age.13032] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/20/2020] [Indexed: 12/24/2022]
Abstract
Growth-related traits are important economic traits in the pig industry that directly influence pork production efficiency. To detect quantitative trait loci and candidate genes affecting growth traits, genome-wide association studies were performed for backfat thickness (BF) and loin muscle depth (LMD) in 370 Chuying-black pigs using Illumina PorcineSNP50 BeadChip array. We totally identified 14 BF-associated SNPs, which included 11 genome-wide SNPs (P < 1.39E-06) and 3 chromosome-wide suggestive SNPs (P < 2.79E-05) and for LMD, 9 SNPs surpassed the genome-wide significant threshold (P < 1.39E-06). These SNPs explained 30.33 and 27.51% phenotypic variance for BF and LMD respectively. Furthermore, 14 and 9 genes nearest to the significant SNPs were selected to be candidate genes, including MAGED1, GPHN, CCSER1, and GUCY2D for BF and PARM1, COL18A1, HSF5, and SCML2 genes for LMD. One significant SNP, which explained 6.07% of phenotypic variance for BF, mapped to a pleiotropic quantitative trait locus with a 494-kb interval. Together, the SNPs and candidate genes identified in this study will advance our understanding of the complex genetic architecture of BF and LMD traits, and they will also provide important clues for future implementation of a genomic selection program in Chuying-black pigs.
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Affiliation(s)
- Y Xue
- College of Animal Sciences and Technology, Henan Agricultural University, Zhengzhou, Henan, 450046, China
| | - C Li
- College of Animal Sciences and Technology, Henan Agricultural University, Zhengzhou, Henan, 450046, China
| | - D Duan
- College of Animal Sciences and Technology, Henan Agricultural University, Zhengzhou, Henan, 450046, China
| | - M Wang
- College of Animal Sciences and Technology, Henan Agricultural University, Zhengzhou, Henan, 450046, China
| | - X Han
- College of Animal Sciences and Technology, Henan Agricultural University, Zhengzhou, Henan, 450046, China
| | - K Wang
- College of Animal Sciences and Technology, Henan Agricultural University, Zhengzhou, Henan, 450046, China
| | - R Qiao
- College of Animal Sciences and Technology, Henan Agricultural University, Zhengzhou, Henan, 450046, China
| | - X-J Li
- College of Animal Sciences and Technology, Henan Agricultural University, Zhengzhou, Henan, 450046, China
| | - X-L Li
- College of Animal Sciences and Technology, Henan Agricultural University, Zhengzhou, Henan, 450046, China
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18
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Moscarelli A, Sardina MT, Cassandro M, Ciani E, Pilla F, Senczuk G, Portolano B, Mastrangelo S. Genome-wide assessment of diversity and differentiation between original and modern Brown cattle populations. Anim Genet 2020; 52:21-31. [PMID: 33174276 DOI: 10.1111/age.13019] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/08/2020] [Indexed: 02/06/2023]
Abstract
Identifying genomic regions involved in the differences between breeds can provide information on genes that are under the influence of both artificial and natural selection. The aim of this study was to assess the genetic diversity and differentiation among four different Brown cattle populations (two original vs. two modern populations) and to characterize the distribution of runs of homozygosity (ROH) islands using the Illumina Bovine SNP50 BeadChip genotyping data. After quality control, 34 735 SNPs and 106 animals were retained for the analyses. Larger heterogeneity was highlighted for the original populations. Patterns of genetic differentiation, multidimensional scaling, and the neighboring joining tree distinguished the modern from the original populations. The FST -outlier identified several genes putatively involved in the genetic differentiation between the two groups, such as stature and growth, behavior, and adaptability to local environments. The ROH islands within both the original and the modern populations overlapped with QTL associated with relevant traits. In modern Brown (Brown Swiss and Italian Brown), ROH islands harbored candidate genes associated with milk production traits, in evident agreement with the artificial selection conducted to improve this trait in these populations. In original Brown (Original Braunvieh and Braunvieh), we identified candidate genes related with fat deposition, confirming that breeding strategies for the original Brown populations aimed to produce dual-purpose animals. Our study highlighted the presence of several genomic regions that vary between Brown populations, in line with their different breeding histories.
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Affiliation(s)
- A Moscarelli
- Dipartimento Scienze Agrarie, Alimentari e Forestali, University of Palermo, Palermo, 90128, Italy
| | - M T Sardina
- Dipartimento Scienze Agrarie, Alimentari e Forestali, University of Palermo, Palermo, 90128, Italy
| | - M Cassandro
- Dipartimento di Agronomia Animali Alimenti Risorse naturali e Ambiente, University of Padova, Legnaro, 35020, Italy
| | - E Ciani
- Dipartimento di Bioscienze, Biotecnologie e Biofarmaceutica, University of Bari, Bari, 70124, Italy
| | - F Pilla
- Dipartimento Agricoltura, Ambiente e Alimenti, University of Molise, Campobasso, 86100, Italy
| | - G Senczuk
- Dipartimento Agricoltura, Ambiente e Alimenti, University of Molise, Campobasso, 86100, Italy
| | - B Portolano
- Dipartimento Scienze Agrarie, Alimentari e Forestali, University of Palermo, Palermo, 90128, Italy
| | - S Mastrangelo
- Dipartimento Scienze Agrarie, Alimentari e Forestali, University of Palermo, Palermo, 90128, Italy
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19
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Edea Z, Jung KS, Shin SS, Yoo SW, Choi JW, Kim KS. Signatures of positive selection underlying beef production traits in Korean cattle breeds. JOURNAL OF ANIMAL SCIENCE AND TECHNOLOGY 2020; 62:293-305. [PMID: 32568261 PMCID: PMC7288235 DOI: 10.5187/jast.2020.62.3.293] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/24/2019] [Revised: 03/04/2020] [Accepted: 03/15/2020] [Indexed: 01/01/2023]
Abstract
The difference in the breeding programs and population history may have diversely
shaped the genomes of Korean native cattle breeds. In the absence of phenotypic
data, comparisons of breeds that have been subjected to different selective
pressures can aid to identify genomic regions and genes controlling qualitative
and complex traits. In this study to decipher genetic variation and identify
evidence of divergent selection, 3 Korean cattle breeds were genotyped using the
recently developed high-density GeneSeek Genomic Profiler F250 (GGP-F250) array.
The three Korean cattle breeds clustered according to their coat color
phenotypes and breeding programs. The Heugu breed reliably showed smaller
effective population size at all generations considered. Across the autosomal
chromosomes, 113 and 83 annotated genes were identified from Hanwoo-Chikso and
Hanwoo-Heugu comparisons, respectively of which 16 genes were shared between the
two pairwise comparisons. The most important signals of selection were detected
on bovine chromosomes 14 (24.39–25.13 Mb) and 18 (13.34–15.07 Mb),
containing genes related to body size, and coat color (XKR4,
LYN, PLAG1, SDR16C5,
TMEM68, CDH15, MC1R, and
GALNS). Some of the candidate genes are also associated
with meat quality traits (ACSF3, EIF2B1,
BANP, APCDD1, and GALM)
and harbor quantitative trait locus (QTL) for beef production traits. Further
functional analysis revealed that the candidate genes (DBI,
ACSF3, HINT2, GBA2,
AGPAT5, SCAP, ELP6,
APOB, and RBL1) were involved in gene
ontology (GO) terms relevant to meat quality including fatty acid oxidation,
biosynthesis, and lipid storage. Candidate genes previously known to affect beef
production and quality traits could be used in the beef cattle selection
strategies.
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Affiliation(s)
- Zewdu Edea
- Department of Animal Science, Chungbuk National University, Cheongju 28644, Korea
| | - Kyoung Sub Jung
- Institute of Livestock and Veterinary Research, Cheongju 28153, Korea
| | - Sung-Sub Shin
- Korea Institute for Animal Products Quality Evaluation, Sejong 30100, Korea
| | - Song-Won Yoo
- Korea Institute for Animal Products Quality Evaluation, Sejong 30100, Korea
| | - Jae Won Choi
- Institute of Livestock and Veterinary Research, Cheongju 28153, Korea
| | - Kwan-Suk Kim
- Department of Animal Science, Chungbuk National University, Cheongju 28644, Korea
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20
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Scholtens M, Jiang A, Smith A, Littlejohn M, Lehnert K, Snell R, Lopez-Villalobos N, Garrick D, Blair H. Genome-wide association studies of lactation yields of milk, fat, protein and somatic cell score in New Zealand dairy goats. J Anim Sci Biotechnol 2020; 11:55. [PMID: 32489662 PMCID: PMC7247195 DOI: 10.1186/s40104-020-00453-2] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2019] [Accepted: 04/01/2020] [Indexed: 12/12/2022] Open
Abstract
Background Identifying associations between genetic markers and traits of economic importance will provide practical benefits for the dairy goat industry, enabling genomic prediction of the breeding value of individuals, and facilitating discovery of the underlying genes and mutations. Genome-wide association studies were implemented to detect genetic regions that are significantly associated with effects on lactation yields of milk (MY), fat (FY), protein (PY) and somatic cell score (SCS) in New Zealand dairy goats. Methods A total of 4,840 goats were genotyped with the Caprine 50 K SNP chip (Illumina Inc., San Diego, CA). After quality filtering, 3,732 animals and 41,989 SNPs were analysed assuming an additive linear model. Four GWAS models were performed, a single-SNP additive linear model and three multi-SNP BayesC models. For the single-SNP GWAS, SNPs were fitted individually as fixed covariates, while the BayesC models fit all SNPs simultaneously as random effects. A cluster of significant SNPs were used to define a haplotype block whose alleles were fitted as covariates in a Bayesian model. The corresponding diplotypes of the haplotype block were then fit as class variables in another Bayesian model. Results Across all four traits, a total of 43 genome-wide significant SNPs were detected from the SNP GWAS. At a genome-wide significance level, the single-SNP analysis identified a cluster of variants on chromosome 19 associated with MY, FY, PY, and another cluster on chromosome 29 associated with SCS. Significant SNPs mapped in introns of candidate genes (45%), in intergenic regions (36%), were 0-5 kb upstream or downstream of the closest gene (14%) or were synonymous substitutions (5%). The most significant genomic window was located on chromosome 19 explaining up to 9.6% of the phenotypic variation for MY, 8.1% for FY, 9.1% for PY and 1% for SCS. Conclusions The quantitative trait loci for yield traits on chromosome 19 confirms reported findings in other dairy goat populations. There is benefit to be gained from using these results for genomic selection to improve milk production in New Zealand dairy goats.
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Affiliation(s)
- Megan Scholtens
- AL Rae Centre for Genetics and Breeding, School of Agriculture, Massey University, Palmerston North, New Zealand
| | - Andrew Jiang
- Applied Translational Genetics Group, School of Biological Sciences, The University of Auckland, Auckland, New Zealand
| | - Ashley Smith
- Applied Translational Genetics Group, School of Biological Sciences, The University of Auckland, Auckland, New Zealand
| | - Mathew Littlejohn
- Research and Development, Livestock Improvement Corporation, Ruakura Road, Hamilton, New Zealand
| | - Klaus Lehnert
- Applied Translational Genetics Group, School of Biological Sciences, The University of Auckland, Auckland, New Zealand
| | - Russell Snell
- Applied Translational Genetics Group, School of Biological Sciences, The University of Auckland, Auckland, New Zealand
| | - Nicolas Lopez-Villalobos
- AL Rae Centre for Genetics and Breeding, School of Agriculture, Massey University, Palmerston North, New Zealand
| | - Dorian Garrick
- AL Rae Centre for Genetics and Breeding, School of Agriculture, Massey University, Palmerston North, New Zealand
| | - Hugh Blair
- AL Rae Centre for Genetics and Breeding, School of Agriculture, Massey University, Palmerston North, New Zealand
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21
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An B, Xu L, Xia J, Wang X, Miao J, Chang T, Song M, Ni J, Xu L, Zhang L, Li J, Gao H. Multiple association analysis of loci and candidate genes that regulate body size at three growth stages in Simmental beef cattle. BMC Genet 2020; 21:32. [PMID: 32171250 PMCID: PMC7071762 DOI: 10.1186/s12863-020-0837-6] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2019] [Accepted: 03/04/2020] [Indexed: 01/08/2023] Open
Abstract
Background Body size traits as one of the main breeding selection criteria was widely used to monitor cattle growth and to evaluate the selection response. In this study, body size was defined as body height (BH), body length (BL), hip height (HH), heart size (HS), abdominal size (AS), and cannon bone size (CS). We performed genome-wide association studies (GWAS) of these traits over the course of three growth stages (6, 12 and 18 months after birth) using three statistical models, single-trait GWAS, multi-trait GWAS and LONG-GWAS. The Illumina Bovine HD 770 K BeadChip was used to identify genomic single nucleotide polymorphisms (SNPs) in 1217 individuals. Results In total, 19, 29, and 10 significant SNPs were identified by the three models, respectively. Among these, 21 genes were promising candidate genes, including SOX2, SNRPD1, RASGEF1B, EFNA5, PTBP1, SNX9, SV2C, PKDCC, SYNDIG1, AKR1E2, and PRIM2 identified by single-trait analysis; SLC37A1, LAP3, PCDH7, MANEA, and LHCGR identified by multi-trait analysis; and P2RY1, MPZL1, LINGO2, CMIP, and WSCD1 identified by LONG-GWAS. Conclusions Multiple association analysis was performed for six growth traits at each growth stage. These findings offer valuable insights for the further investigation of potential genetic mechanism of growth traits in Simmental beef cattle.
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Affiliation(s)
| | | | - Jiangwei Xia
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, 310000, China
| | - Xiaoqiao Wang
- Institute of Animal Science, Chinese Academy of Agricultural Science, Beijing, 100193, China
| | - Jian Miao
- Institute of Animal Science, Chinese Academy of Agricultural Science, Beijing, 100193, China
| | - Tianpeng Chang
- Institute of Animal Science, Chinese Academy of Agricultural Science, Beijing, 100193, China
| | - Meihua Song
- Zhuang Yuan Veterinary Station of Qixia city, Yantai, 265300, China
| | - Junqing Ni
- Heibei Livestock Breeding Workstation, Shijiazhuang, 050061, China
| | - Lingyang Xu
- Institute of Animal Science, Chinese Academy of Agricultural Science, Beijing, 100193, China
| | - Lupei Zhang
- Institute of Animal Science, Chinese Academy of Agricultural Science, Beijing, 100193, China
| | - Junya Li
- Institute of Animal Science, Chinese Academy of Agricultural Science, Beijing, 100193, China
| | - Huijiang Gao
- Institute of Animal Science, Chinese Academy of Agricultural Science, Beijing, 100193, China.
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22
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Xu P, Ni L, Tao Y, Ma Z, Hu T, Zhao X, Yu Z, Lu C, Zhao X, Ren J. Genome-wide association study for growth and fatness traits in Chinese Sujiang pigs. Anim Genet 2020; 51:314-318. [PMID: 31909836 DOI: 10.1111/age.12899] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/06/2019] [Indexed: 12/14/2022]
Abstract
Growth and fatness traits are complex and economically important traits in the pig industry. The molecular basis underlying porcine growth and fatness traits remains largely unknown. To uncover genetic loci and candidate genes for these traits, we explored the GeneSeek GGP Porcine 80K SNP chip to perform a GWAS for seven growth and fatness traits in 365 individuals from the Sujiang pig, a recently developed breed in China. We identified two, 17, one and 11 SNPs surpassing the suggestively significant threshold (P < 1.86 × 10-5 ) for body weight, chest circumference, chest width and backfat thickness respectively. Of these SNPs, 20 represent novel genetic loci, and five and four SNPs were respectively associated with chest circumference and backfat thickness at a genome-wide significant threshold (P < 9.31 × 10-7 ). Eight SNPs had a pleiotropic effect on both chest circumference and backfat thickness. The most remarkable locus resided in a region between 72.95 and 76.27 Mb on pig chromosome 4, harboring a number of previously reported quantitative trait loci related to backfat deposition. In addition to two reported genes (PLAG1 and TAS2R38), we identified four genes including GABRB3, ZNF106, XKR4 and MGAM as novel candidates for body weight and backfat thickness at the mapped loci. Our findings provide insights into the genetic architecture of porcine growth and fatness traits and potential markers for selective breeding of Chinese Sujiang pigs.
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Affiliation(s)
- P Xu
- School of Animal Science and Technology, Jiangsu Agri-animal Husbandry Vocational College, 225300, Taizhou, China
| | - L Ni
- School of Animal Science and Technology, Jiangsu Agri-animal Husbandry Vocational College, 225300, Taizhou, China.,Unit of Pig Breeding, Jiangsu Sujiang Pig Breeding Farm, 225400, Taixing, China
| | - Y Tao
- School of Animal Science and Technology, Jiangsu Agri-animal Husbandry Vocational College, 225300, Taizhou, China.,Unit of Pig Breeding, Jiangsu Sujiang Pig Breeding Farm, 225400, Taixing, China
| | - Z Ma
- School of Animal Science and Technology, Jiangsu Agri-animal Husbandry Vocational College, 225300, Taizhou, China
| | - T Hu
- School of Animal Science and Technology, Jiangsu Agri-animal Husbandry Vocational College, 225300, Taizhou, China
| | - X Zhao
- School of Animal Science and Technology, Jiangsu Agri-animal Husbandry Vocational College, 225300, Taizhou, China
| | - Z Yu
- School of Animal Science and Technology, Jiangsu Agri-animal Husbandry Vocational College, 225300, Taizhou, China
| | - C Lu
- School of Animal Science and Technology, Jiangsu Agri-animal Husbandry Vocational College, 225300, Taizhou, China
| | - X Zhao
- School of Animal Science and Technology, Jiangsu Agri-animal Husbandry Vocational College, 225300, Taizhou, China
| | - J Ren
- College of Animal Science, South China Agricultural University, 510642, Guangzhou, China
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23
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Bergamaschi M, Maltecca C, Fix J, Schwab C, Tiezzi F. Genome-wide association study for carcass quality traits and growth in purebred and crossbred pigs1. J Anim Sci 2020; 98:skz360. [PMID: 31768540 PMCID: PMC6978898 DOI: 10.1093/jas/skz360] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2019] [Accepted: 11/25/2019] [Indexed: 12/29/2022] Open
Abstract
Carcass quality traits such as back fat (BF), loin depth (LD), and ADG are of extreme economic importance for the swine industry. This study aimed to (i) estimate the genetic parameters for such traits and (ii) conduct a single-step genome-wide association study (ssGWAS) to identify genomic regions that affect carcass quality and growth traits in purebred (PB) and three-way crossbred (CB) pigs. A total of 28,497 PBs and 135,768 CBs pigs were phenotyped for BF, LD, and ADG. Of these, 4,857 and 3,532 were genotyped using the Illumina PorcineSNP60K Beadchip. After quality control, 36,328 SNPs were available and were used to perform an ssGWAS. A bootstrap analysis (n = 1,000) and a signal enrichment analysis were performed to declare SNP significance. Genome regions were based on the variance explained by significant 10-SNP sliding windows. Estimates of PB heritability (SE) were 0.42 (0.019) for BF, 0.39 (0.020) for LD, and 0.35 (0.021) for ADG. Estimates of CB heritability were 0.49 (0.042) for BF, 0.27 (0.029) for LD, and 0.12 (0.021) for ADG. Genetic correlations (SE) across the two populations were 0.81 (0.02), 0.79 (0.04), and 0.56 (0.05), for BF, LD, and ADG, respectively. The variance explained by significant regions for each trait in PBs ranged from 1.51% to 1.35% for BF, from 4.02% to 3.18% for LD, and from 2.26% to 1.45% for ADG. In CBs, the variance explained by significant regions ranged from 1.88% to 1.37% for BF, from 1.29% to 1.23% for LD, and from 1.54% to 1.32% for ADG. In this study, we have described regions of the genome that determine carcass quality and growth traits of PB and CB pigs. These results provide evidence that there are overlapping and nonoverlapping regions in the genome influencing carcass quality and growth traits in PBs and three-way CB pigs.
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Affiliation(s)
| | - Christian Maltecca
- Department of Animal Science, North Carolina State University, Raleigh, NC
| | | | | | - Francesco Tiezzi
- Department of Animal Science, North Carolina State University, Raleigh, NC
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24
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de las Heras-Saldana S, Clark SA, Duijvesteijn N, Gondro C, van der Werf JHJ, Chen Y. Combining information from genome-wide association and multi-tissue gene expression studies to elucidate factors underlying genetic variation for residual feed intake in Australian Angus cattle. BMC Genomics 2019; 20:939. [PMID: 31810463 PMCID: PMC6898931 DOI: 10.1186/s12864-019-6270-4] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2019] [Accepted: 11/07/2019] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Genome-wide association studies (GWAS) are extensively used to identify single nucleotide polymorphisms (SNP) underlying the genetic variation of complex traits. However, much uncertainly often still exists about the causal variants and genes at quantitative trait loci (QTL). The aim of this study was to identify QTL associated with residual feed intake (RFI) and genes in these regions whose expression is also associated with this trait. Angus cattle (2190 steers) with RFI records were genotyped and imputed to high density arrays (770 K) and used for a GWAS approach to identify QTL associated with RFI. RNA sequences from 126 Angus divergently selected for RFI were analyzed to identify the genes whose expression was significantly associated this trait with special attention to those genes residing in the QTL regions. RESULTS The heritability for RFI estimated for this Angus population was 0.3. In a GWAS, we identified 78 SNPs associated with RFI on six QTL (on BTA1, BTA6, BTA14, BTA17, BTA20 and BTA26). The most significant SNP was found on chromosome BTA20 (rs42662073) and explained 4% of the genetic variance. The minor allele frequencies of significant SNPs ranged from 0.05 to 0.49. All regions, except on BTA17, showed a significant dominance effect. In 1 Mb windows surrounding the six significant QTL, we found 149 genes from which OAS2, STC2, SHOX, XKR4, and SGMS1 were the closest to the most significant QTL on BTA17, BTA20, BTA1, BTA14, and BTA26, respectively. In a 2 Mb windows around the six significant QTL, we identified 15 genes whose expression was significantly associated with RFI: BTA20) NEURL1B and CPEB4; BTA17) RITA1, CCDC42B, OAS2, RPL6, and ERP29; BTA26) A1CF, SGMS1, PAPSS2, and PTEN; BTA1) MFSD1 and RARRES1; BTA14) ATP6V1H and MRPL15. CONCLUSIONS Our results showed six QTL regions associated with RFI in a beef Angus population where five of these QTL contained genes that have expression associated with this trait. Therefore, here we show that integrating information from gene expression and GWAS studies can help to better understand the genetic mechanisms that determine variation in complex traits.
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Affiliation(s)
| | - Samuel A. Clark
- School of Environmental and Rural Science, University of New England, Armidale, NSW Australia
| | - Naomi Duijvesteijn
- School of Environmental and Rural Science, University of New England, Armidale, NSW Australia
| | - Cedric Gondro
- School of Environmental and Rural Science, University of New England, Armidale, NSW Australia
- Department of Animal Science, Michigan State University, East Lansing, MI USA
| | | | - Yizhou Chen
- Department of Primary Industries, Elizabeth Macarthur Agricultural Institute, Menangle, NSW Australia
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25
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Oliveira HR, Brito LF, Lourenco DAL, Silva FF, Jamrozik J, Schaeffer LR, Schenkel FS. Invited review: Advances and applications of random regression models: From quantitative genetics to genomics. J Dairy Sci 2019; 102:7664-7683. [PMID: 31255270 DOI: 10.3168/jds.2019-16265] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2019] [Accepted: 05/02/2019] [Indexed: 12/23/2022]
Abstract
An important goal in animal breeding is to improve longitudinal traits; that is, traits recorded multiple times during an individual's lifetime or physiological cycle. Longitudinal traits were first genetically evaluated based on accumulated phenotypic expression, phenotypic expression at specific time points, or repeatability models. Until now, the genetic evaluation of longitudinal traits has mainly focused on using random regression models (RRM). Random regression models enable fitting random genetic and environmental effects over time, which results in higher accuracy of estimated breeding values compared with other statistical approaches. In addition, RRM provide insights about temporal variation of biological processes and the physiological implications underlying the studied traits. Despite the fact that genomic information has substantially contributed to increase the rates of genetic progress for a variety of economically important traits in several livestock species, less attention has been given to longitudinal traits in recent years. However, including genomic information to evaluate longitudinal traits using RRM is a feasible alternative to yield more accurate selection and culling decisions, because selection of young animals may be based on the complete pattern of the production curve with higher accuracy compared with the use of traditional parent average (i.e., without genomic information). Moreover, RRM can be used to estimate SNP effects over time in genome-wide association studies. Thus, by analyzing marker associations over time, regions with higher effects at specific points in time are more likely to be identified. Despite the advances in applications of RRM in genetic evaluations, more research is needed to successfully combine RRM and genomic information. Future research should provide a better understanding of the temporal variation of biological processes and their physiological implications underlying the longitudinal traits.
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Affiliation(s)
- H R Oliveira
- Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, ON, N1G2W1, Canada; Department of Animal Science, Universidade Federal de Viçosa, Viçosa, Minas Gerais, 36570-000, Brazil
| | - L F Brito
- Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, ON, N1G2W1, Canada; Department of Animal Sciences, Purdue University, West Lafayette, IN 47907
| | - D A L Lourenco
- Department of Animal and Dairy Science, University of Georgia, Athens 30602
| | - F F Silva
- Department of Animal Science, Universidade Federal de Viçosa, Viçosa, Minas Gerais, 36570-000, Brazil
| | - J Jamrozik
- Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, ON, N1G2W1, Canada; Canadian Dairy Network, Guelph, ON, N1K 1E5, Canada
| | - L R Schaeffer
- Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, ON, N1G2W1, Canada
| | - F S Schenkel
- Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, ON, N1G2W1, Canada.
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26
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E GX, Zhao YJ, Huang YF. Selection signatures of litter size in Dazu black goats based on a whole genome sequencing mixed pools strategy. Mol Biol Rep 2019; 46:5517-5523. [DOI: 10.1007/s11033-019-04904-6] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2019] [Accepted: 06/01/2019] [Indexed: 12/19/2022]
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27
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Yu Y, Wang Q, Zhang Q, Luo Z, Wang Y, Zhang X, Huang H, Xiang J, Li F. Genome Scan for Genomic Regions and Genes Associated with Growth Trait in Pacific White Shrimp Litopeneaus vannamei. MARINE BIOTECHNOLOGY (NEW YORK, N.Y.) 2019; 21:374-383. [PMID: 30887268 DOI: 10.1007/s10126-019-09887-w] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/11/2019] [Accepted: 02/18/2019] [Indexed: 06/09/2023]
Abstract
The Pacific white shrimp Litopeneaus vannmei (L. vannmei) is a predominant aquaculture shrimp species worldwide, and it is considered as the aquaculture species with the highest single output value. Advances in selective breeding have accelerated the development of L. vannmei aquaculture. Recently, the genome-wide association studies (GWAS) have been applied in aquaculture animals and markers associated with economic traits were identified. In this study, we focused on the growth trait of L. vannamei and performed GWAS to identify SNPs or genes associated with growth. Genomic regions in linkage group 7, 27, 33, and 38 were identified to be associated with body weight and body length of the shrimp. Further, candidate gene association analysis was performed in two independent populations and the result demonstrated that the SNPs in the genes protein kinase C delta type and ras-related protein Rap-2a were significantly associated with the growth trait of L. vannamei. This study showed that GWAS analysis is an efficient approach for screening trait-related markers or genes. The genomic regions and genes identified in this study are essential for further fine mapping of growth-related genes. The identified markers will provide useful information for marker-assisted selection in L. vannamei.
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Affiliation(s)
- Yang Yu
- Key Laboratory of Experimental Marine Biology, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, 266071, China
- Laboratory for Marine Biology and Biotechnology, Qingdao National Laboratory for Marine Science and Technology, Qingdao, China
| | - Quanchao Wang
- Key Laboratory of Experimental Marine Biology, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, 266071, China
| | - Qian Zhang
- Key Laboratory of Experimental Marine Biology, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, 266071, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Zheng Luo
- Key Laboratory of Experimental Marine Biology, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, 266071, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Yue Wang
- Key Laboratory of Experimental Marine Biology, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, 266071, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Xiaojun Zhang
- Key Laboratory of Experimental Marine Biology, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, 266071, China
- Laboratory for Marine Biology and Biotechnology, Qingdao National Laboratory for Marine Science and Technology, Qingdao, China
| | - Hao Huang
- Hainan Grand Suntop Ocean Breeding Co., Ltd, Wenchang, 571300, China
| | - Jianhai Xiang
- Key Laboratory of Experimental Marine Biology, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, 266071, China
- Laboratory for Marine Biology and Biotechnology, Qingdao National Laboratory for Marine Science and Technology, Qingdao, China
- Center for Ocean Mega-Science, Chinese Academy of Sciences, Qingdao, 266071, China
| | - Fuhua Li
- Key Laboratory of Experimental Marine Biology, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, 266071, China.
- Laboratory for Marine Biology and Biotechnology, Qingdao National Laboratory for Marine Science and Technology, Qingdao, China.
- Center for Ocean Mega-Science, Chinese Academy of Sciences, Qingdao, 266071, China.
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28
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Tang Z, Xu J, Yin L, Yin D, Zhu M, Yu M, Li X, Zhao S, Liu X. Genome-Wide Association Study Reveals Candidate Genes for Growth Relevant Traits in Pigs. Front Genet 2019; 10:302. [PMID: 31024621 PMCID: PMC6459934 DOI: 10.3389/fgene.2019.00302] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2018] [Accepted: 03/19/2019] [Indexed: 12/02/2022] Open
Abstract
Improvement of the growth rate is a challenge in the pig industry, the Average Daily Gain (ADG) and Days (AGE) to 100 kg are directly related to growth performance. We performed genome-wide association study (GWAS) and genetic parameters estimation for ADG and AGE using the genomic and phonemic from four breed (Duroc, Yorkshire, Landrace, and Pietrain) populations. All analyses were performed by a multi-loci GWAS model, FarmCPU. The GWAS results of all four breeds indicate that five genome-wide significant SNPs were associated with ADG, and the nearby genomic regions explained 4.08% of the genetic variance and 1.90% of the phenotypic variance, respectively. For AGE, six genome-wide significant SNPs were detected, and the nearby genomic regions explained 8.09% of the genetic variance and 3.52% of phenotypic variance, respectively. In total, nine candidate genes were identified to be associated with growth and metabolism. Among them, TRIB3 was reported to associate with pig growth, GRP, TTR, CNR1, GLP1R, BRD2, HCRTR2, SEC11C, and ssc-mir-122 were reported to associate with growth traits in human and mouse. The newly detected candidate genes will advance the understanding of growth related traits and the identification of the novel variants will suggest a potential use in pig genomic breeding programs.
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Affiliation(s)
- Zhenshuang Tang
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, China.,Key Laboratory of Swine Genetics and Breeding, Ministry of Agriculture, Huazhong Agricultural University, Wuhan, China
| | - Jingya Xu
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, China.,Key Laboratory of Swine Genetics and Breeding, Ministry of Agriculture, Huazhong Agricultural University, Wuhan, China
| | - Lilin Yin
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, China.,Key Laboratory of Swine Genetics and Breeding, Ministry of Agriculture, Huazhong Agricultural University, Wuhan, China
| | - Dong Yin
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, China.,Key Laboratory of Swine Genetics and Breeding, Ministry of Agriculture, Huazhong Agricultural University, Wuhan, China
| | - Mengjin Zhu
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, China.,Key Laboratory of Swine Genetics and Breeding, Ministry of Agriculture, Huazhong Agricultural University, Wuhan, China
| | - Mei Yu
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, China.,Key Laboratory of Swine Genetics and Breeding, Ministry of Agriculture, Huazhong Agricultural University, Wuhan, China
| | - Xinyun Li
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, China.,Key Laboratory of Swine Genetics and Breeding, Ministry of Agriculture, Huazhong Agricultural University, Wuhan, China
| | - Shuhong Zhao
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, China.,Key Laboratory of Swine Genetics and Breeding, Ministry of Agriculture, Huazhong Agricultural University, Wuhan, China
| | - Xiaolei Liu
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, China.,Key Laboratory of Swine Genetics and Breeding, Ministry of Agriculture, Huazhong Agricultural University, Wuhan, China
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Gong H, Xiao S, Li W, Huang T, Huang X, Yan G, Huang Y, Qiu H, Jiang K, Wang X, Zhang H, Tang J, Li L, Li Y, Wang C, Qiao C, Ren J, Huang L, Yang B. Unravelling the genetic loci for growth and carcass traits in Chinese Bamaxiang pigs based on a 1.4 million SNP array. J Anim Breed Genet 2019; 136:3-14. [PMID: 30417949 DOI: 10.1111/jbg.12365] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2018] [Revised: 08/29/2018] [Accepted: 09/22/2018] [Indexed: 12/21/2022]
Abstract
Bamaxiang pig is from Guangxi province in China, characterized by its small body size and two-end black coat colour. It is an important indigenous breed for local pork market and excellent animal model for biomedical research. In this study, we performed genomewide association studies (GWAS) on 43 growth and carcass traits in 315 purebred Bamaxiang pigs based on a 1.4 million SNP array. We observed considerable phenotypic variability in the growth and carcass traits in the Bamaxiang pigs. The corresponding SNP based heritability varied greatly across the 43 traits and ranged from 9.0% to 88%. Through a conditional GWAS, we identified 53 significant associations for 35 traits at p value threshold of 10-6 . Among which, 26 associations on chromosome 3, 7, 14 and X passed a genomewide significance threshold of 5 × 10-8 . The most remarkable loci were at around 30.6 Mb on chromosome 7, which had growth stage-dependent effects on body lengths and cannon circumferences and showed large effects on multiple carcass traits. We discussed HMGA1 NUDT3, EIF2AK1, TMEM132C and AFF2 that near the lead SNP of significant loci as plausible candidate genes for corresponding traits. We also showed that including phenotypic covariate in GWAS can help to reveal additional significant loci for the target traits. The results provide insight into the genetic architecture of growth and carcass traits in Bamaxiang pigs.
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Affiliation(s)
- Huanfa Gong
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, China
| | - Shijun Xiao
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, China
| | - Wanbo Li
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, China
| | - Tao Huang
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, China
| | - Xiaochang Huang
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, China
| | - Guorong Yan
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, China
| | - Yizhong Huang
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, China
| | - Hengqing Qiu
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, China
| | - Kai Jiang
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, China
| | - Xiaopeng Wang
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, China
| | - Hui Zhang
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, China
| | - Jianhong Tang
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, China
| | - Lin Li
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, China
| | - Yiping Li
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, China
| | - Chenbin Wang
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, China
| | - Chuanmin Qiao
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, China
| | - Jun Ren
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, China
| | - Lusheng Huang
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, China
| | - Bin Yang
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, China
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30
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Yurchenko AA, Daetwyler HD, Yudin N, Schnabel RD, Vander Jagt CJ, Soloshenko V, Lhasaranov B, Popov R, Taylor JF, Larkin DM. Scans for signatures of selection in Russian cattle breed genomes reveal new candidate genes for environmental adaptation and acclimation. Sci Rep 2018; 8:12984. [PMID: 30154520 PMCID: PMC6113280 DOI: 10.1038/s41598-018-31304-w] [Citation(s) in RCA: 65] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2018] [Accepted: 08/16/2018] [Indexed: 01/08/2023] Open
Abstract
Domestication and selective breeding has resulted in over 1000 extant cattle breeds. Many of these breeds do not excel in important traits but are adapted to local environments. These adaptations are a valuable source of genetic material for efforts to improve commercial breeds. As a step toward this goal we identified candidate regions to be under selection in genomes of nine Russian native cattle breeds adapted to survive in harsh climates. After comparing our data to other breeds of European and Asian origins we found known and novel candidate genes that could potentially be related to domestication, economically important traits and environmental adaptations in cattle. The Russian cattle breed genomes contained regions under putative selection with genes that may be related to adaptations to harsh environments (e.g., AQP5, RAD50, and RETREG1). We found genomic signatures of selective sweeps near key genes related to economically important traits, such as the milk production (e.g., DGAT1, ABCG2), growth (e.g., XKR4), and reproduction (e.g., CSF2). Our data point to candidate genes which should be included in future studies attempting to identify genes to improve the extant breeds and facilitate generation of commercial breeds that fit better into the environments of Russia and other countries with similar climates.
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Affiliation(s)
- Andrey A Yurchenko
- The Federal Research Center Institute of Cytology and Genetics, The Siberian Branch of the Russian Academy of Sciences (ICG SB RAS), 630090, Novosibirsk, Russia
- Institute of Biodiversity, Animal Health and Comparative Medicine, University of Glasgow, Glasgow, G12 8QQ, UK
| | - Hans D Daetwyler
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, 3083, Victoria, Australia
- School of Applied Systems Biology, La Trobe University, Bundoora, 3083, Victoria, Australia
| | - Nikolay Yudin
- The Federal Research Center Institute of Cytology and Genetics, The Siberian Branch of the Russian Academy of Sciences (ICG SB RAS), 630090, Novosibirsk, Russia
| | - Robert D Schnabel
- Division of Animal Sciences, University of Missouri, Columbia, MO, 65211-5300, USA
| | - Christy J Vander Jagt
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, 3083, Victoria, Australia
| | | | | | - Ruslan Popov
- Yakutian Research Institute of Agriculture, 677001, Yakutsk, Russia
| | - Jeremy F Taylor
- Division of Animal Sciences, University of Missouri, Columbia, MO, 65211-5300, USA
| | - Denis M Larkin
- The Federal Research Center Institute of Cytology and Genetics, The Siberian Branch of the Russian Academy of Sciences (ICG SB RAS), 630090, Novosibirsk, Russia.
- Royal Veterinary College, University of London, NW01 0TU, London, UK.
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31
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Lee SM, Oh JD, Park KD, Do KT. Analysis of genetic characteristics of pig breeds using information on single nucleotide polymorphisms. ASIAN-AUSTRALASIAN JOURNAL OF ANIMAL SCIENCES 2018; 32:485-493. [PMID: 30145872 PMCID: PMC6409452 DOI: 10.5713/ajas.18.0304] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/19/2018] [Accepted: 08/06/2018] [Indexed: 11/29/2022]
Abstract
Objective This study was undertaken to investigate the genetic characteristics of Berkshire (BS), Landrace (LR), and Yorkshire (YS) pig breeds raised in the Great Grandparents pig farms using the single nucleotide polymorphisms (SNP) information. Methods A total of 25,921 common SNP genotype markers in three pig breeds were used to estimate the expected heterozygosity (HE), polymorphism information content, F-statistics (FST), linkage disequilibrium (LD) and effective population size (Ne). Results The chromosome-wise distribution of FST in BS, LR, and YS populations were within the range of 0–0.36, and the average FST value was estimated to be 0.07±0.06. This result indicated some level of genetic segregation. An average LD (r2) for the BS, LR, and YS breeds was estimated to be approximately 0.41. This study also found an average Ne of 19.9 (BS), 31.4 (LR), and 34.1 (YS) over the last 5th generations. The effective population size for the BS, LR, and YS breeds decreased at a consistent rate from 50th to 10th generations ago. With a relatively faster Ne decline rate in the past 10th generations, there exists possible evidence for intensive selection practices in pigs in the recent past. Conclusion To develop customized chips for the genomic selection of various breeds, it is important to select and utilize SNP based on the genetic characteristics of each breed. Since the improvement efficiency of breed pigs increases sharply by the population size, it is important to increase test units for the improvement and it is desirable to establish the pig improvement network system to expand the unit of breed pig improvement through the genetic connection among breed pig farms.
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Affiliation(s)
- Sang-Min Lee
- Department of Animal Biotechnology, Chonbuk National University, Jeonju 54896, Korea
| | - Jae-Don Oh
- Department of Animal Biotechnology, Chonbuk National University, Jeonju 54896, Korea
| | - Kyung-Do Park
- Department of Animal Biotechnology, Chonbuk National University, Jeonju 54896, Korea
| | - Kyoung-Tag Do
- Department of Animal Biotechnology, Jeju National University, Jeju 63243, Korea
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32
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Shin D, Won KH, Kim SH, Kim YM. Extent of linkage disequilibrium and effective population size of Korean Yorkshire swine. ASIAN-AUSTRALASIAN JOURNAL OF ANIMAL SCIENCES 2018; 31:1843-1851. [PMID: 30056677 PMCID: PMC6212734 DOI: 10.5713/ajas.17.0258] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/31/2017] [Accepted: 06/22/2018] [Indexed: 11/27/2022]
Abstract
Objective We aimed to characterize linkage disequilibrium (LD) and effective population size (Ne) in a Korean Yorkshire population using genomic data from thousands of individuals. Methods We genotyped 2,470 Yorkshire individuals from four major Grand-Grand-Parent farms in Korea using the Illumina PorcineSNP60 version2 BeadChip, which covers >61,565 single nucleotide polymorphisms (SNPs) located across all chromosomes and mitochondria. We estimated the expected LD and inferred current Ne as well as ancestral Ne. Results We identified 61,565 SNP from autosomes, mitochondria, and sex chromosomes and characterized the LD of the Yorkshire population, which was relatively high between closely linked markers (>0.55 at 50 kb) and declined with increasing genetic distance. The current Ne of this Korean Yorkshire population was 122.87 (106.90; 138.84), while the historical Ne of Yorkshire pigs suggests that the ancestor Ne has decreased by 99.6% over the last 10,000 generations. Conclusion To maintain genetic diversity of a domesticated animal population, we must carefully consider appropriate breed management methods to avoid inbreeding. Although attenuated selection can affect short-term genetic gain, it is essential for maintaining the long-term genetic variability of the Korean Yorkshire population. Continuous and long-term monitoring would also be needed to maintain the pig population to avoid an unintended reduction of Ne. The best way to preserve a sustainable population is to maintain a sufficient Ne.
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Affiliation(s)
- Donghyun Shin
- Department of Animal Biotechnology, Chonbuk National University, Jeonju, 54896, Korea
| | - Kyeong-Hye Won
- Department of Animal Biotechnology, Chonbuk National University, Jeonju, 54896, Korea
| | | | - Yong-Min Kim
- Korean Bioinformation Center, Korea Research Institute of Bioscience and Biotechnology, Daejeon 34141, Korea
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33
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Ding R, Yang M, Wang X, Quan J, Zhuang Z, Zhou S, Li S, Xu Z, Zheng E, Cai G, Liu D, Huang W, Yang J, Wu Z. Genetic Architecture of Feeding Behavior and Feed Efficiency in a Duroc Pig Population. Front Genet 2018; 9:220. [PMID: 29971093 PMCID: PMC6018414 DOI: 10.3389/fgene.2018.00220] [Citation(s) in RCA: 54] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2018] [Accepted: 05/29/2018] [Indexed: 11/13/2022] Open
Abstract
Increasing feed efficiency is a major goal of breeders as it can reduce production cost and energy consumption. However, the genetic architecture of feeding behavior and feed efficiency traits remains elusive. To investigate the genetic architecture of feed efficiency in pigs, three feeding behavior traits (daily feed intake, number of daily visits to feeder, and duration of each visit) and two feed efficiency traits (feed conversion ratio and residual feed intake) were considered. We performed genome-wide association studies (GWASs) of the five traits using a population of 1,008 Duroc pigs genotyped with an Illumina Porcine SNP50K BeadChip. A total of 9 genome-wide (P < 1.54E-06) and 35 suggestive (P < 3.08E-05) single nucleotide polymorphisms (SNPs) were detected. Two pleiotropic quantitative trait loci (QTLs) on SSC 1 and SSC 7 were found to affect more than one trait. Markers WU_10.2_7_18377044 and DRGA0001676 are two key SNPs for these two pleiotropic QTLs. Marker WU_10.2_7_18377044 on SSC 7 contributed 2.16 and 2.37% of the observed phenotypic variance for DFI and RFI, respectively. The other SNP DRGA0001676 on SSC 1 explained 3.22 and 5.46% of the observed phenotypic variance for FCR and RFI, respectively. Finally, functions of candidate genes and gene set enrichment analysis indicate that most of the significant pathways are associated with hormonal and digestive gland secretion during feeding. This study advances our understanding of the genetic mechanisms of feeding behavior and feed efficiency traits and provide an opportunity for increasing feeding efficiency 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, China
| | - Ming Yang
- National Engineering Research Center for Breeding Swine Industry, Guangdong Wens Foodstuffs Group, Co., Ltd., Guangdong, China
| | - Xingwang Wang
- 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
| | - Zhanwei Zhuang
- 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
| | - Shaoyun Li
- 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.,National Engineering Research Center for Breeding Swine Industry, Guangdong Wens Foodstuffs Group, Co., Ltd., Guangdong, China
| | - Dewu Liu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, China
| | - Wen Huang
- Department of Animal Science, 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, Guangdong, China
| | - Zhenfang Wu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, China.,National Engineering Research Center for Breeding Swine Industry, Guangdong Wens Foodstuffs Group, Co., Ltd., Guangdong, China
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34
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Miao J, Wang X, Bao J, Jin S, Chang T, Xia J, Yang L, Zhu B, Xu L, Zhang L, Gao X, Chen Y, Li J, Gao H. Multimarker and rare variants genomewide association studies for bone weight in Simmental cattle. J Anim Breed Genet 2018; 135:159-169. [DOI: 10.1111/jbg.12326] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2017] [Accepted: 03/27/2018] [Indexed: 12/30/2022]
Affiliation(s)
- J. Miao
- Laboratory of Molecular Biology and Bovine Breeding; Institute of Animal Sciences; Chinese Academy of Agricultural Sciences; Beijing China
- College of Animal Sciences; Fujian Agriculture and Forestry University; Fujian China
| | - X. Wang
- Laboratory of Molecular Biology and Bovine Breeding; Institute of Animal Sciences; Chinese Academy of Agricultural Sciences; Beijing China
| | - J. Bao
- Veterinary Bureau of Wulagai Precinct in Xilin Gol League; Wulagai China
| | - S. Jin
- Veterinary Bureau of Wulagai Precinct in Xilin Gol League; Wulagai China
| | - T. Chang
- Laboratory of Molecular Biology and Bovine Breeding; Institute of Animal Sciences; Chinese Academy of Agricultural Sciences; Beijing China
| | - J. Xia
- Laboratory of Molecular Biology and Bovine Breeding; Institute of Animal Sciences; Chinese Academy of Agricultural Sciences; Beijing China
| | - L. Yang
- Laboratory of Molecular Biology and Bovine Breeding; Institute of Animal Sciences; Chinese Academy of Agricultural Sciences; Beijing China
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province; Sichuan Agricultural University; Sichuan China
| | - B. Zhu
- Laboratory of Molecular Biology and Bovine Breeding; Institute of Animal Sciences; Chinese Academy of Agricultural Sciences; Beijing China
| | - L. Xu
- Laboratory of Molecular Biology and Bovine Breeding; Institute of Animal Sciences; Chinese Academy of Agricultural Sciences; Beijing China
| | - L. Zhang
- Laboratory of Molecular Biology and Bovine Breeding; Institute of Animal Sciences; Chinese Academy of Agricultural Sciences; Beijing China
| | - X. Gao
- Laboratory of Molecular Biology and Bovine Breeding; Institute of Animal Sciences; Chinese Academy of Agricultural Sciences; Beijing China
| | - Y. Chen
- Laboratory of Molecular Biology and Bovine Breeding; Institute of Animal Sciences; Chinese Academy of Agricultural Sciences; Beijing China
| | - J. Li
- Laboratory of Molecular Biology and Bovine Breeding; Institute of Animal Sciences; Chinese Academy of Agricultural Sciences; Beijing China
| | - H. Gao
- Laboratory of Molecular Biology and Bovine Breeding; Institute of Animal Sciences; Chinese Academy of Agricultural Sciences; Beijing China
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Quan J, Ding R, Wang X, Yang M, Yang Y, Zheng E, Gu T, Cai G, Wu Z, Liu D, Yang J. Genome-wide association study reveals genetic loci and candidate genes for average daily gain in Duroc pigs. ASIAN-AUSTRALASIAN JOURNAL OF ANIMAL SCIENCES 2017; 31:480-488. [PMID: 29059722 PMCID: PMC5838319 DOI: 10.5713/ajas.17.0356] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/09/2017] [Revised: 08/08/2017] [Accepted: 10/09/2017] [Indexed: 12/28/2022]
Abstract
Objective Average daily gain (ADG) is an important target trait of pig breeding programs. We aimed to identify single nucleotide polymorphisms (SNPs) and genomic regions that are associated with ADG in the Duroc pig population. Methods We performed a genome-wide association study involving 390 Duroc boars and by using the PorcineSNP60K Beadchip and two linear models. Results After quality control, we detected 3,5971 SNPs, which included seven SNPs that are significantly associated with the ADG of pigs. We identified six quantitative trait loci (QTL) regions for ADG. These QTLs included four previously reported QTLs on Sus scrofa chromosome (SSC) 1, SSC5, SSC9, and SSC13, as well as two novel QTLs on SSC6 and SSC16. In addition, we selected six candidate genes (general transcription factor 3C polypeptide 5, high mobility group AT-hook 2, nicotinamide phosphoribosyltransferase, oligodendrocyte transcription factor 1, pleckstrin homology and RhoGEF domain containing G4B, and ENSSSCG00000031548) associated with ADG on the basis of their physiological roles and positional information. These candidate genes are involved in skeletal muscle cell differentiation, diet-induced obesity, and nervous system development. Conclusion This study contributes to the identification of the casual mutation that underlies QTLs associated with ADG and to future pig breeding programs based on marker-assisted selection. Further studies are needed to elucidate the role of the identified candidate genes in the physiological processes involved in ADG regulation.
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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 510642, China
| | - Rongrong Ding
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, 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
| | - Ming Yang
- National Engineering Research Center for Breeding Swine Industry, Guangdong Wens Foodstuffs Co., Ltd, Yunfu 527400, China
| | - Yang Yang
- 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
| | - Ting Gu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou 510642, China
| | - Gengyuan Cai
- National Engineering Research Center for Breeding Swine Industry, Guangdong Wens Foodstuffs Co., Ltd, Yunfu 527400, China
| | - Zhenfang Wu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou 510642, China.,National Engineering Research Center for Breeding Swine Industry, Guangdong Wens Foodstuffs Co., Ltd, Yunfu 527400, China
| | - Dewu Liu
- 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
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