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Wang XG, Shen MM, Lu J, Dou TC, Ma M, Guo J, Wang KH, Qu L. Genome-wide association analysis of eggshell color of an F2 generation population reveals candidate genes in chickens. Animal 2024; 18:101167. [PMID: 38762993 DOI: 10.1016/j.animal.2024.101167] [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: 10/26/2023] [Revised: 04/11/2024] [Accepted: 04/12/2024] [Indexed: 05/21/2024] Open
Abstract
Eggshell color is an important visual characteristic that affects consumer preferences for eggs. Eggshell color, which has moderate to high heritability, can be effectively enhanced through molecular marker selection. Various studies have been conducted on eggshell color at specific time points. However, few longitudinal data are available on eggshell color. Therefore, the objective of this study was to investigate eggshell color using the Commission International de L'Eclairage L*a*b* system with multiple measurements at different ages (age at the first egg and at 32, 36, 40, 44, 48, 52, 56, 60, 66, and 72 weeks) within the same individuals from an F2 resource population produced by crossing White Leghorn and Dongxiang Blue chicken. Using an Affymetrix 600 single nucleotide polymorphism (SNP) array, we estimated the genetic parameters of the eggshell color trait, performed genome-wide association studies (GWASs), and screened for the potential candidate genes. The results showed that pink-shelled eggs displayed a significant negative correlation between L* values and both a* and b* values. Genetic heritability based on SNPs showed that the heritability of L*, a*, and b* values ranged from 0.32 to 0.82 for pink-shelled eggs, indicating a moderate to high level of genetic control. The genetic correlations at each time point were mostly above 0.5. The major-effect regions affecting the pink eggshell color were identified in the 10.3-13.0 Mb interval on Gallus gallus chromosome 20, and candidate genes were selected, including SLC35C2, PCIF1, and SLC12A5. Minor effect polygenic regions were identified on chromosomes 1, 6, 9, 12, and 15, revealing 11 candidate genes, including MTMR3 and SLC35E4. Members of the solute carrier family play an important role in influencing eggshell color. Overall, our findings provide valuable insights into the phenotypic and genetic aspects underlying the variation in eggshell color. Using GWAS analysis, we identified multiple quantitative trait loci (QTLs) for pink eggshell color, including a major QTL on chromosome 20. Genetic variants associated with eggshell color may be used in genomic breeding programs.
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Affiliation(s)
- X G Wang
- Jiangsu Institute of Poultry Science, Yangzhou 225125, China
| | - M M Shen
- Jiangsu Key Laboratory of Sericultural and Animal Biotechnology, School of Biotechnology, Jiangsu University of Science and Technology, Zhenjiang 212100, China
| | - J Lu
- Jiangsu Institute of Poultry Science, Yangzhou 225125, China
| | - T C Dou
- Jiangsu Institute of Poultry Science, Yangzhou 225125, China
| | - M Ma
- Jiangsu Institute of Poultry Science, Yangzhou 225125, China
| | - J Guo
- Jiangsu Institute of Poultry Science, Yangzhou 225125, China
| | - K H Wang
- Jiangsu Institute of Poultry Science, Yangzhou 225125, China
| | - L Qu
- Jiangsu Institute of Poultry Science, Yangzhou 225125, China.
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Ma X, Ying F, Li Z, Bai L, Wang M, Zhu D, Liu D, Wen J, Zhao G, Liu R. New insights into the genetic loci related to egg weight and age at first egg traits in broiler breeder. Poult Sci 2024; 103:103613. [PMID: 38492250 PMCID: PMC10959720 DOI: 10.1016/j.psj.2024.103613] [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: 12/19/2023] [Revised: 02/29/2024] [Accepted: 02/29/2024] [Indexed: 03/18/2024] Open
Abstract
Egg weight (EW) and age at first egg (AFE) are economically important traits in breeder chicken production. The genetic basis of these traits, however, is far from understood, especially for broiler breeders. In this study, genetic parameter estimation, genome-wide association analysis, meta-analysis, and selective sweep analysis were carried out to identify genetic loci associated with EW and AFE in 6,842 broiler breeders. The study found that the heritability of EW ranged from 0.42 to 0.44, while the heritability of AFE was estimated at 0.33 in the maternal line. Meta-analysis and selective sweep analysis identified two colocalized regions on GGA4 that significantly influenced EW at 32 wk (EW32W) and at 43 wk (EW43W) with both paternal and maternal lines. The genes AR, YIPF6, and STARD8 were located within the significant region (GGA4: 366.86-575.50 kb), potentially affecting EW through the regulation of follicle development, cell proliferation, and lipid transfer etc. The promising genes LCORL and NCAPG were positioned within the significant region (GGA4:75.35-75.42 Mb), potentially influencing EW through pleiotropic effects on growth and development. Additionally, 3 significant regions were associated with AFE on chromosomes GGA7, GGA19, and GGA27. All of these factors affected the AFE by influencing ovarian development. In our study, the genomic information from both paternal and maternal lines was used to identify genetic regions associated with EW and AFE. Two genomic regions and eight genes were identified as the most likely candidates affecting EW and AFE. These findings contribute to a better understanding of the genetic basis of egg production traits in broiler breeders and provide new insights into future technology development.
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Affiliation(s)
- Xiaochun Ma
- State Key Laboratory of Animal Biotech Breeding; State Key Laboratory of Animal Nutrition and Feeding; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture; Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Fan Ying
- Foshan Gaoming Xinguang Agricultural and Animal Industrials Corporation, Foshan 528515, China
| | - Zhengda Li
- State Key Laboratory of Animal Biotech Breeding; State Key Laboratory of Animal Nutrition and Feeding; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture; Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Lu Bai
- State Key Laboratory of Animal Biotech Breeding; State Key Laboratory of Animal Nutrition and Feeding; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture; Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Mengjie Wang
- State Key Laboratory of Animal Biotech Breeding; State Key Laboratory of Animal Nutrition and Feeding; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture; Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Dan Zhu
- Foshan Gaoming Xinguang Agricultural and Animal Industrials Corporation, Foshan 528515, China
| | - Dawei Liu
- Foshan Gaoming Xinguang Agricultural and Animal Industrials Corporation, Foshan 528515, China
| | - Jie Wen
- State Key Laboratory of Animal Biotech Breeding; State Key Laboratory of Animal Nutrition and Feeding; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture; Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Guiping Zhao
- State Key Laboratory of Animal Biotech Breeding; State Key Laboratory of Animal Nutrition and Feeding; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture; Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Ranran Liu
- State Key Laboratory of Animal Biotech Breeding; State Key Laboratory of Animal Nutrition and Feeding; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture; Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China.
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3
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Xie L, Qin J, Rao L, Cui D, Tang X, Chen L, Xiao S, Zhang Z, Huang L. Genetic dissection and genomic prediction for pork cuts and carcass morphology traits in pig. J Anim Sci Biotechnol 2023; 14:116. [PMID: 37660101 PMCID: PMC10475202 DOI: 10.1186/s40104-023-00914-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Accepted: 07/02/2023] [Indexed: 09/04/2023] Open
Abstract
BACKGROUND As pre-cut and pre-packaged chilled meat becomes increasingly popular, integrating the carcass-cutting process into the pig industry chain has become a trend. Identifying quantitative trait loci (QTLs) of pork cuts would facilitate the selection of pigs with a higher overall value. However, previous studies solely focused on evaluating the phenotypic and genetic parameters of pork cuts, neglecting the investigation of QTLs influencing these traits. This study involved 17 pork cuts and 12 morphology traits from 2,012 pigs across four populations genotyped using CC1 PorcineSNP50 BeadChips. Our aim was to identify QTLs and evaluate the accuracy of genomic estimated breed values (GEBVs) for pork cuts. RESULTS We identified 14 QTLs and 112 QTLs for 17 pork cuts by GWAS using haplotype and imputation genotypes, respectively. Specifically, we found that HMGA1, VRTN and BMP2 were associated with body length and weight. Subsequent analysis revealed that HMGA1 primarily affects the size of fore leg bones, VRTN primarily affects the number of vertebrates, and BMP2 primarily affects the length of vertebrae and the size of hind leg bones. The prediction accuracy was defined as the correlation between the adjusted phenotype and GEBVs in the validation population, divided by the square root of the trait's heritability. The prediction accuracy of GEBVs for pork cuts varied from 0.342 to 0.693. Notably, ribs, boneless picnic shoulder, tenderloin, hind leg bones, and scapula bones exhibited prediction accuracies exceeding 0.600. Employing better models, increasing marker density through genotype imputation, and pre-selecting markers significantly improved the prediction accuracy of GEBVs. CONCLUSIONS We performed the first study to dissect the genetic mechanism of pork cuts and identified a large number of significant QTLs and potential candidate genes. These findings carry significant implications for the breeding of pork cuts through marker-assisted and genomic selection. Additionally, we have constructed the first reference populations for genomic selection of pork cuts in pigs.
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Affiliation(s)
- Lei Xie
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045 China
| | - Jiangtao Qin
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045 China
| | - Lin Rao
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045 China
| | - Dengshuai Cui
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045 China
| | - Xi Tang
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045 China
| | - Liqing Chen
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045 China
| | - Shijun Xiao
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045 China
| | - Zhiyan Zhang
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045 China
| | - Lusheng Huang
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045 China
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Roth K, Pröll-Cornelissen MJ, Henne H, Appel AK, Schellander K, Tholen E, Große-Brinkhaus C. Multivariate genome-wide associations for immune traits in two maternal pig lines. BMC Genomics 2023; 24:492. [PMID: 37641029 PMCID: PMC10463314 DOI: 10.1186/s12864-023-09594-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Accepted: 08/16/2023] [Indexed: 08/31/2023] Open
Abstract
BACKGROUND Immune traits are considered to serve as potential biomarkers for pig's health. Medium to high heritabilities have been observed for some of the immune traits suggesting genetic variability of these phenotypes. Consideration of previously established genetic correlations between immune traits can be used to identify pleiotropic genetic markers. Therefore, genome-wide association study (GWAS) approaches are required to explore the joint genetic foundation for health biomarkers. Usually, GWAS explores phenotypes in a univariate (uv), trait-by-trait manner. Besides two uv GWAS methods, four multivariate (mv) GWAS approaches were applied on combinations out of 22 immune traits for Landrace (LR) and Large White (LW) pig lines. RESULTS In total 433 (LR: 351, LW: 82) associations were identified with the uv approach implemented in PLINK and a Bayesian linear regression uv approach (BIMBAM) software. Single Nucleotide Polymorphisms (SNPs) that were identified with both uv approaches (n = 32) were mostly associated with immune traits such as haptoglobin, red blood cell characteristics and cytokines, and were located in protein-coding genes. Mv GWAS approaches detected 647 associations for different mv immune trait combinations which were summarized to 133 Quantitative Trait Loci (QTL). SNPs for different trait combinations (n = 66) were detected with more than one mv method. Most of these SNPs are associated with red blood cell related immune trait combinations. Functional annotation of these QTL revealed 453 immune-relevant protein-coding genes. With uv methods shared markers were not observed between the breeds, whereas mv approaches were able to detect two conjoint SNPs for LR and LW. Due to unmapped positions for these markers, their functional annotation was not clarified. CONCLUSIONS This study evaluated the joint genetic background of immune traits in LR and LW piglets through the application of various uv and mv GWAS approaches. In comparison to uv methods, mv methodologies identified more significant associations, which might reflect the pleiotropic background of the immune system more accurately. In genetic research of complex traits, the SNP effects are generally small. Furthermore, one genetic variant can affect several correlated immune traits at the same time, termed pleiotropy. As mv GWAS methods consider strong dependencies among traits, the power to detect SNPs can be boosted. Both methods revealed immune-relevant potential candidate genes. Our results indicate that one single test is not able to detect all the different types of genetic effects in the most powerful manner and therefore, the methods should be applied complementary.
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Affiliation(s)
- Katharina Roth
- Institute of Animal Science, University of Bonn, Endenicher Allee 15, 53115, Bonn, Germany
| | | | - Hubert Henne
- BHZP GmbH, An der Wassermühle 8, 21368, Dahlenburg-Ellringen, Germany
| | | | - Karl Schellander
- Institute of Animal Science, University of Bonn, Endenicher Allee 15, 53115, Bonn, Germany
| | - Ernst Tholen
- Institute of Animal Science, University of Bonn, Endenicher Allee 15, 53115, Bonn, Germany
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Yang W, He X, Yao Y, Lu H, Wang Y, Zhang Z, Wang Y, Wang L, He Y, Yuan D, Jin T. Genome-Wide Association Study on the Hematological Phenotypic Characteristics of the Han Population from Northwest China. Pharmgenomics Pers Med 2022; 15:743-763. [PMID: 35945964 PMCID: PMC9357418 DOI: 10.2147/pgpm.s361809] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Accepted: 06/14/2022] [Indexed: 11/23/2022] Open
Abstract
Background Hematological characteristics have positive reference value as clinical indicators in the evaluation of various diseases. The purpose of this study was to determine the gene loci associated with 20 hematological phenotypes in the Han population from northwest China. Methods A genome-wide association study (GWAS) was conducted on hematological indicators of 1005 Han people from northwest China. Genotyping was performed with a GeneTitan multichannel instrument and Axiom Analysis Suite 6.0. Using the 1000 Genomes Project (phase 3) as a reference, haplotype imputation was performed with IMPUTE2. SNVs (single nucleotide variants) significantly associated with hematological phenotypes were identified. The top SNV (p < 5E-7) was then selected for replication detection. Results Ninety genetic variations identified in the GWAS were significantly associated with hematological indicators. Among them, only rs35289401 (CCDC157) was significantly associated (genome-wide) with red blood cell distribution width (RDW) (p = 4.21E-08). The fourteen top SNVs were selected for replication verification and were significantly associated with hematological phenotypes. However, only HBS1 L-MYB rs1331309 was significantly associated with the mean hemoglobin content (p = 6.42E-07). We also found that the mean corpuscular hemoglobin (MCH) level in the rs1331309 GG/GT genotype was significantly higher than that in the TT genotype (p = 0.023). Conclusion The GWAS identified a total of 90 genetic variants significantly associated with hematological phenotypic indicators. In particular, rs1331309 (HBS1 L-MYB) is expected to be a biomarker for monitoring the dynamics of MCH levels. This study provides a reference for related studies on the genetic structure of hematological characteristics. It provides a valuable reference for the clinical diagnosis or prediction of a variety of diseases.
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Affiliation(s)
- Wei Yang
- Key Laboratory of Molecular Mechanism and Intervention Research for Plateau Diseases of Tibet Autonomous Region, School of Medicine, Xizang Minzu University, Xianyang, Shaanxi, 712082, People’s Republic of China
- School of Basic Medical Sciences, Xizang Minzu University, Xianyang, Shaanxi, 712082, People’s Republic of China
- Department of Emergency, The Affiliated Hospital of Xizang Minzu University, Xianyang, Shaanxi, 712082, People’s Republic of China
| | - Xue He
- Key Laboratory of Molecular Mechanism and Intervention Research for Plateau Diseases of Tibet Autonomous Region, School of Medicine, Xizang Minzu University, Xianyang, Shaanxi, 712082, People’s Republic of China
- School of Basic Medical Sciences, Xizang Minzu University, Xianyang, Shaanxi, 712082, People’s Republic of China
| | - Yuying Yao
- School of Basic Medical Sciences, Xizang Minzu University, Xianyang, Shaanxi, 712082, People’s Republic of China
| | - Hongyan Lu
- School of Basic Medical Sciences, Xizang Minzu University, Xianyang, Shaanxi, 712082, People’s Republic of China
| | - Yuliang Wang
- School of Basic Medical Sciences, Xizang Minzu University, Xianyang, Shaanxi, 712082, People’s Republic of China
| | - Zhanhao Zhang
- School of Basic Medical Sciences, Xizang Minzu University, Xianyang, Shaanxi, 712082, People’s Republic of China
| | - Yuhe Wang
- Key Laboratory of Molecular Mechanism and Intervention Research for Plateau Diseases of Tibet Autonomous Region, School of Medicine, Xizang Minzu University, Xianyang, Shaanxi, 712082, People’s Republic of China
- School of Basic Medical Sciences, Xizang Minzu University, Xianyang, Shaanxi, 712082, People’s Republic of China
- Department of Clinical Laboratory, The Affiliated Hospital of Xizang Minzu University, Xianyang, Shaanxi, 712082, People’s Republic of China
| | - Li Wang
- Key Laboratory of Molecular Mechanism and Intervention Research for Plateau Diseases of Tibet Autonomous Region, School of Medicine, Xizang Minzu University, Xianyang, Shaanxi, 712082, People’s Republic of China
- School of Basic Medical Sciences, Xizang Minzu University, Xianyang, Shaanxi, 712082, People’s Republic of China
| | - Yongjun He
- Key Laboratory of Molecular Mechanism and Intervention Research for Plateau Diseases of Tibet Autonomous Region, School of Medicine, Xizang Minzu University, Xianyang, Shaanxi, 712082, People’s Republic of China
- School of Basic Medical Sciences, Xizang Minzu University, Xianyang, Shaanxi, 712082, People’s Republic of China
| | - Dongya Yuan
- Key Laboratory of Molecular Mechanism and Intervention Research for Plateau Diseases of Tibet Autonomous Region, School of Medicine, Xizang Minzu University, Xianyang, Shaanxi, 712082, People’s Republic of China
- School of Basic Medical Sciences, Xizang Minzu University, Xianyang, Shaanxi, 712082, People’s Republic of China
| | - Tianbo Jin
- Key Laboratory of Molecular Mechanism and Intervention Research for Plateau Diseases of Tibet Autonomous Region, School of Medicine, Xizang Minzu University, Xianyang, Shaanxi, 712082, People’s Republic of China
- School of Basic Medical Sciences, Xizang Minzu University, Xianyang, Shaanxi, 712082, People’s Republic of China
- Correspondence: Tianbo Jin, Key Laboratory of Molecular Mechanism and Intervention Research for Plateau Diseases of Tibet Autonomous Region, School of Medicine, Xizang Minzu University, #6 East Wenhui Road, Xianyang, Shaanxi, 712082, People’s Republic of China, Tel/Fax +86-29-88895902, Email
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Krayem I, Sohrabi Y, Javorková E, Volkova V, Strnad H, Havelková H, Vojtíšková J, Aidarova A, Holáň V, Demant P, Lipoldová M. Genetic Influence on Frequencies of Myeloid-Derived Cell Subpopulations in Mouse. Front Immunol 2022; 12:760881. [PMID: 35154069 PMCID: PMC8826059 DOI: 10.3389/fimmu.2021.760881] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2021] [Accepted: 12/06/2021] [Indexed: 11/13/2022] Open
Abstract
Differences in frequencies of blood cell subpopulations were reported to influence the course of infections, atopic and autoimmune diseases, and cancer. We have discovered a unique mouse strain B10.O20 containing extremely high frequency of myeloid-derived cells (MDC) in spleen. B10.O20 carries 3.6% of genes of the strain O20 on the C57BL/10 genetic background. It contains much higher frequency of CD11b+Gr1+ cells in spleen than both its parents. B10.O20 carries O20-derived segments on chromosomes 1, 15, 17, and 18. Their linkage with frequencies of blood cell subpopulations in spleen was tested in F2 hybrids between B10.O20 and C57BL/10. We found 3 novel loci controlling MDC frequencies: Mydc1, 2, and 3 on chromosomes 1, 15, and 17, respectively, and a locus controlling relative spleen weight (Rsw1) that co-localizes with Mydc3 and also influences proportion of white and red pulp in spleen. Mydc1 controls numbers of CD11b+Gr1+ cells. Interaction of Mydc2 and Mydc3 regulates frequency of CD11b+Gr1+ cells and neutrophils (Gr1+Siglec-F- cells from CD11b+ cells). Interestingly, Mydc3/Rsw1 is orthologous with human segment 6q21 that was shown previously to determine counts of white blood cells. Bioinformatics analysis of genomic sequence of the chromosomal segments bearing these loci revealed polymorphisms between O20 and C57BL/10 that change RNA stability and genes’ functions, and we examined expression of relevant genes. This identified potential candidate genes Smap1, Vps52, Tnxb, and Rab44. Definition of genetic control of MDC can help to personalize therapy of diseases influenced by these cells.
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Affiliation(s)
- Imtissal Krayem
- Laboratory of Molecular and Cellular Immunology, Institute of Molecular Genetics of the Czech Academy of Sciences, Prague, Czechia
| | - Yahya Sohrabi
- Laboratory of Molecular and Cellular Immunology, Institute of Molecular Genetics of the Czech Academy of Sciences, Prague, Czechia
| | - Eliška Javorková
- Department of Cell Biology, Faculty of Science, Charles University, Prague, Czechia.,Department of Nanotoxicology and Molecular Epidemiology, Institute of Experimental Medicine of the Czech Academy of Sciences, Prague, Czechia
| | - Valeriya Volkova
- Laboratory of Molecular and Cellular Immunology, Institute of Molecular Genetics of the Czech Academy of Sciences, Prague, Czechia
| | - Hynek Strnad
- Department of Genomics and Bioinformatics, Institute of Molecular Genetics of the Czech Academy of Sciences, Prague, Czechia
| | - Helena Havelková
- Laboratory of Molecular and Cellular Immunology, Institute of Molecular Genetics of the Czech Academy of Sciences, Prague, Czechia
| | - Jarmila Vojtíšková
- Laboratory of Molecular and Cellular Immunology, Institute of Molecular Genetics of the Czech Academy of Sciences, Prague, Czechia
| | - Aigerim Aidarova
- Laboratory of Molecular and Cellular Immunology, Institute of Molecular Genetics of the Czech Academy of Sciences, Prague, Czechia
| | - Vladimír Holáň
- Department of Cell Biology, Faculty of Science, Charles University, Prague, Czechia.,Department of Nanotoxicology and Molecular Epidemiology, Institute of Experimental Medicine of the Czech Academy of Sciences, Prague, Czechia
| | - Peter Demant
- Department of Molecular and Cellular Biology, Roswell Park Comprehensive Cancer Center, Buffalo, NY, United States
| | - Marie Lipoldová
- Laboratory of Molecular and Cellular Immunology, Institute of Molecular Genetics of the Czech Academy of Sciences, Prague, Czechia
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Mi S, Tang Y, Dari G, Shi Y, Zhang J, Zhang H, Liu X, Liu Y, Tahir U, Yu Y. Transcriptome sequencing analysis for the identification of stable lncRNAs associated with bovine Staphylococcus aureus mastitis. J Anim Sci Biotechnol 2021; 12:120. [PMID: 34895356 PMCID: PMC8667444 DOI: 10.1186/s40104-021-00639-2] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2021] [Accepted: 10/01/2021] [Indexed: 02/06/2023] Open
Abstract
Background Staphylococcus aureus (S. aureus) mastitis is one of the most difficult diseases to treat in lactating dairy cows worldwide. S. aureus with different lineages leads to different host immune responses. Long non-coding RNAs (lncRNAs) are reported to be widely involved in the progress of inflammation. However, no research has identified stable lncRNAs among different S. aureus strain infections. In addition, folic acid (FA) can effectively reduce inflammation, and whether the inflammatory response caused by S. aureus can be reduced by FA remains to be explored. Methods lncRNA transcripts were identified from Holstein mammary gland tissues infected with different concentrations of S. aureus (in vivo) and mammary alveolar cells (Mac-T cells, in vitro) challenged with different S. aureus strains. Differentially expressed (DE) lncRNAs were evaluated, and stable DE lncRNAs were identified in vivo and in vitro. On the basis of the gene sequence conservation and function conservation across species, key lncRNAs with the function of potentially immune regulation were retained for further analysis. The function of FA on inflammation induced by S. aureus challenge was also investigated. Then, the association analysis between these keys lncRNA transcripts and hematological parameters (HPs) was carried out. Lastly, the knockdown and overexpression of the important lncRNA were performed to validate the gene function on the regulation of cell immune response. Results Linear regression analysis showed a significant correlation between the expression levels of lncRNA shared by mammary tissue and Mac-T cells (P < 0.001, R2 = 0.3517). lncRNAs PRANCR and TNK2–AS1 could be regarded as stable markers associated with bovine S. aureus mastitis. Several HPs could be influenced by SNPs around lncRNAs PRANCR and TNK2–AS1. The results of gene function validation showed PRANCR regulates the mRNA expression of SELPLG and ITGB2 within the S. aureus infection pathway and the Mac-T cells apoptosis. In addition, FA regulated the expression change of DE lncRNA involved in toxin metabolism and inflammation to fight against S. aureus infection. Conclusions The remarkable association between SNPs around these two lncRNAs and partial HP indicates the potentially important role of PRANCR and TNK2–AS1 in immune regulation. Stable DE lncRNAs PRANCR and TNK2–AS1 can be regarded as potential targets for the prevention of bovine S. aureus mastitis. FA supplementation can reduce the negative effect of S. aureus challenge by regulating the expression of lncRNAs. Supplementary Information The online version contains supplementary material available at 10.1186/s40104-021-00639-2.
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Affiliation(s)
- Siyuan Mi
- Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture & National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Yongjie Tang
- Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture & National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Gerile Dari
- Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture & National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Yuanjun Shi
- Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture & National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Jinning Zhang
- Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture & National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Hailiang Zhang
- Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture & National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Xueqin Liu
- Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture & National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Yibing Liu
- Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture & National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Usman Tahir
- College of Veterinary Sciences and Animal Husbandry, Abdul Wali Khan University, Mardan, 23200, Pakistan
| | - Ying Yu
- Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture & National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China.
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8
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Dauben CM, Pröll-Cornelissen MJ, Heuß EM, Appel AK, Henne H, Roth K, Schellander K, Tholen E, Große-Brinkhaus C. Genome-wide associations for immune traits in two maternal pig lines. BMC Genomics 2021; 22:717. [PMID: 34610786 PMCID: PMC8491387 DOI: 10.1186/s12864-021-07997-1] [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: 04/24/2021] [Accepted: 09/09/2021] [Indexed: 11/13/2022] Open
Abstract
Background In recent years, animal welfare and health has become more and more important in pig breeding. So far, numerous parameters have been considered as important biomarkers, especially in the immune reaction and inflammation. Previous studies have shown moderate to high heritabilities in most of these traits. However, the genetic background of health and robustness of pigs needs to be extensively clarified. The objective of this study was to identify genomic regions with a biological relevance for the immunocompetence of piglets. Genome-wide Association Studies (GWAS) in 535 Landrace (LR) and 461 Large White (LW) piglets were performed, investigating 20 immune relevant traits. Besides the health indicators of the complete and differential blood count, eight different cytokines and haptoglobin were recorded in all piglets and their biological dams to capture mediating processes and acute phase reactions. Additionally, all animals were genotyped using the Illumina PorcineSNP60v2 BeadChip. Results In summary, GWAS detected 25 genome-wide and 452 chromosome-wide significant SNPs associated with 17 immune relevant traits in the two maternal pig lines LR and LW. Only small differences were observed considering the maternal immune records as covariate within the statistical model. Furthermore, the study identified across- and within-breed differences as well as relevant candidate genes. In LR more significant associations and related candidate genes were detected, compared with LW. The results detected in LR and LW are partly in accordance with previously identified quantitative trait loci (QTL) regions. In addition, promising novel genomic regions were identified which might be of interest for further detailed analysis. Especially putative pleiotropic regions on SSC5, SSC12, SSC15, SSC16 and SSC17 are of major interest with regard to the interacting structure of the immune system. The comparison with already identified QTL gives indications on interactions with traits affecting piglet survival and also production traits. Conclusion In conclusion, results suggest a polygenic and breed-specific background of immune relevant traits. The current study provides knowledge about regions with biological relevance for health and immune traits. Identified markers and putative pleiotropic regions provide first indications in the context of balancing a breeding-based modification of the porcine immune system. Supplementary Information The online version contains supplementary material available at (10.1186/s12864-021-07997-1).
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Affiliation(s)
- Christina M Dauben
- Institute of Animal Sciences, University of Bonn, Endenicher Allee 15, Bonn, 53115, Germany
| | | | - Esther M Heuß
- Institute of Animal Sciences, University of Bonn, Endenicher Allee 15, Bonn, 53115, Germany
| | - Anne K Appel
- BHZP GmbH, An der Wassermühle 8, Dahlenburg-Ellringen, 21368, Germany
| | - Hubert Henne
- BHZP GmbH, An der Wassermühle 8, Dahlenburg-Ellringen, 21368, Germany
| | - Katharina Roth
- Institute of Animal Sciences, University of Bonn, Endenicher Allee 15, Bonn, 53115, Germany
| | - Karl Schellander
- Institute of Animal Sciences, University of Bonn, Endenicher Allee 15, Bonn, 53115, Germany
| | - Ernst Tholen
- Institute of Animal Sciences, University of Bonn, Endenicher Allee 15, Bonn, 53115, Germany
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9
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Yan G, Liu X, Xiao S, Xin W, Xu W, Li Y, Huang T, Qin J, Xie L, Ma J, Zhang Z, Huang L. An imputed whole-genome sequence-based GWAS approach pinpoints causal mutations for complex traits in a specific swine population. SCIENCE CHINA-LIFE SCIENCES 2021; 65:781-794. [PMID: 34387836 DOI: 10.1007/s11427-020-1960-9] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/17/2021] [Accepted: 05/19/2021] [Indexed: 01/08/2023]
Abstract
Sequencing-based genome-wide association studies (GWAS) have facilitated the identification of causal associations between genetic variants and traits in diverse species. However, it is cost-prohibitive for the majority of research groups to sequence a large number of samples. Here, we carried out genotype imputation to increase the density of single nucleotide polymorphisms in a large-scale Swine F2 population using a reference panel including 117 individuals, followed by a series of GWAS analyses. The imputation accuracies reached 0.89 and 0.86 for allelic concordance and correlation, respectively. A quantitative trait nucleotide (QTN) affecting the chest vertebrate was detected directly, while the investigation of another QTN affecting the residual glucose failed due to the presence of similar haplotypes carrying wild-type and mutant allelesin the reference panel used in this study. A high imputation accuracy was confirmed by Sanger sequencing technology for the most significant loci. Two candidate genes, CPNE5 and MYH3, affecting meat-related traits were proposed. Collectively, we illustrated four scenarios in imputation-based GWAS that may be encountered by researchers, and our results will provide an extensive reference for future genotype imputation-based GWAS analyses in the future.
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Affiliation(s)
- Guorong Yan
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China
- Institute of Photomedicine, Shanghai Skin Disease Hospital, School of Medicine, Tongji University, Shanghai, 200092, China
| | - Xianxian Liu
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China
| | - Shijun Xiao
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China
| | - Wenshui Xin
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China
| | - Wenwu Xu
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China
| | - Yiping Li
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China
| | - Tao Huang
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China
| | - Jiangtao Qin
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China
| | - Lei Xie
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China
| | - Junwu Ma
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China.
| | - Zhiyan Zhang
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China.
| | - Lusheng Huang
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China
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10
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Genetic parameters and associated genomic regions for global immunocompetence and other health-related traits in pigs. Sci Rep 2020; 10:18462. [PMID: 33116177 PMCID: PMC7595139 DOI: 10.1038/s41598-020-75417-7] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2020] [Accepted: 10/15/2020] [Indexed: 12/16/2022] Open
Abstract
The inclusion of health-related traits, or functionally associated genetic markers, in pig breeding programs could contribute to produce more robust and disease resistant animals. The aim of the present work was to study the genetic determinism and genomic regions associated to global immunocompetence and health in a Duroc pig population. For this purpose, a set of 30 health-related traits covering immune (mainly innate), haematological, and stress parameters were measured in 432 healthy Duroc piglets aged 8 weeks. Moderate to high heritabilities were obtained for most traits and significant genetic correlations among them were observed. A genome wide association study pointed out 31 significantly associated SNPs at whole-genome level, located in six chromosomal regions on pig chromosomes SSC4, SSC6, SSC17 and SSCX, for IgG, γδ T-cells, C-reactive protein, lymphocytes phagocytic capacity, total number of lymphocytes, mean corpuscular volume and mean corpuscular haemoglobin. A total of 16 promising functionally-related candidate genes, including CRP, NFATC2, PRDX1, SLA, ST3GAL1, and VPS4A, have been proposed to explain the variation of immune and haematological traits. Our results enhance the knowledge of the genetic control of traits related with immunity and support the possibility of applying effective selection programs to improve immunocompetence in pigs.
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11
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Bovo S, Ballan M, Schiavo G, Gallo M, Dall'Olio S, Fontanesi L. Haplotype-based genome-wide association studies reveal new loci for haematological and clinical-biochemical parameters in Large White pigs. Anim Genet 2020; 51:601-606. [PMID: 32511786 DOI: 10.1111/age.12959] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2019] [Revised: 02/24/2020] [Accepted: 05/02/2020] [Indexed: 01/21/2023]
Abstract
We report haplotype-based GWASs for 33 blood parameters measured in 843 Italian Large White pigs. In the single-trait analysis, a total of 30 QTL for number of basophils, six erythrocyte traits (haemoglobin, haematocrit, mean corpuscular haemoglobin, mean corpuscular haemoglobin concentration, mean corpuscular volume and red blood cell count) and two clinical-biochemical traits (alkaline phosphatase and Ca2+ contents) were identified. In the multiple-trait analysis, a total of five QTL affected three different clusters of traits. Only four of these QTL were already reported in the single-marker and multi-marker GWASs we previously carried out on the same pig population. QTL on SSC11 and SSC17 showed effects on multiple traits. These results further dissected the genetic architecture of parameters that could be used as proxies in breeding programmes for more complex traits. In addition, these results might help to better define the pig as an animal model for several blood-related biological functions.
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Affiliation(s)
- S Bovo
- Department of Agricultural and Food Sciences, Division of Animal Sciences, University of Bologna, Viale G. Fanin 46, Bologna, 40127, Italy
| | - M Ballan
- Department of Agricultural and Food Sciences, Division of Animal Sciences, University of Bologna, Viale G. Fanin 46, Bologna, 40127, Italy
| | - G Schiavo
- Department of Agricultural and Food Sciences, Division of Animal Sciences, University of Bologna, Viale G. Fanin 46, Bologna, 40127, Italy
| | - M Gallo
- Associazione Nazionale Allevatori Suini, Via Nizza 53, Roma, 00198, Italy
| | - S Dall'Olio
- Department of Agricultural and Food Sciences, Division of Animal Sciences, University of Bologna, Viale G. Fanin 46, Bologna, 40127, Italy
| | - L Fontanesi
- Department of Agricultural and Food Sciences, Division of Animal Sciences, University of Bologna, Viale G. Fanin 46, Bologna, 40127, Italy
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12
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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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13
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Ma X, Jia C, Fu D, Chu M, Ding X, Wu X, Guo X, Pei J, Bao P, Liang C, Yan P. Analysis of Hematological Traits in Polled Yak by Genome-Wide Association Studies Using Individual SNPs and Haplotypes. Genes (Basel) 2019; 10:E463. [PMID: 31212963 PMCID: PMC6627507 DOI: 10.3390/genes10060463] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2019] [Revised: 06/11/2019] [Accepted: 06/12/2019] [Indexed: 12/21/2022] Open
Abstract
Yak (Bos grunniens) is an important domestic animal living in high-altitude plateaus. Due to inadequate disease prevention, each year, the yak industry suffers significant economic losses. The identification of causal genes that affect blood- and immunity-related cells could provide preliminary reference guidelines for the prevention of diseases in the population of yaks. The genome-wide association studies (GWASs) utilizing a single-marker or haplotype method were employed to analyze 15 hematological traits in the genome of 315 unrelated yaks. Single-marker GWASs identified a total of 43 significant SNPs, including 35 suggestive and eight genome-wide significant SNPs, associated with nine traits. Haplotype analysis detected nine significant haplotype blocks, including two genome-wide and seven suggestive blocks, associated with seven traits. The study provides data on the genetic variability of hematological traits in the yak. Five essential genes (GPLD1, EDNRA,APOB, HIST1H1E, and HIST1H2BI) were identified, which affect the HCT, HGB, RBC, PDW, PLT, and RDWSD traits and can serve as candidate genes for regulating hematological traits. The results provide a valuable reference to be used in the analysis of blood properties and immune diseases in the yak.
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Affiliation(s)
- Xiaoming Ma
- Animal Science Department, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China.
- Key Laboratory for Yak Genetics, Breeding, and Reproduction Engineering of Gansu Province, Lanzhou 730050, China.
| | - Congjun Jia
- Animal Science Department, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China.
- Key Laboratory for Yak Genetics, Breeding, and Reproduction Engineering of Gansu Province, Lanzhou 730050, China.
| | - Donghai Fu
- Animal Science Department, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China.
- Key Laboratory for Yak Genetics, Breeding, and Reproduction Engineering of Gansu Province, Lanzhou 730050, China.
| | - Min Chu
- Animal Science Department, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China.
- Key Laboratory for Yak Genetics, Breeding, and Reproduction Engineering of Gansu Province, Lanzhou 730050, China.
| | - Xuezhi Ding
- Animal Science Department, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China.
- Key Laboratory for Yak Genetics, Breeding, and Reproduction Engineering of Gansu Province, Lanzhou 730050, China.
| | - Xiaoyun Wu
- Animal Science Department, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China.
- Key Laboratory for Yak Genetics, Breeding, and Reproduction Engineering of Gansu Province, Lanzhou 730050, China.
| | - Xian Guo
- Animal Science Department, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China.
- Key Laboratory for Yak Genetics, Breeding, and Reproduction Engineering of Gansu Province, Lanzhou 730050, China.
| | - Jie Pei
- Animal Science Department, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China.
- Key Laboratory for Yak Genetics, Breeding, and Reproduction Engineering of Gansu Province, Lanzhou 730050, China.
| | - Pengjia Bao
- Animal Science Department, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China.
- Key Laboratory for Yak Genetics, Breeding, and Reproduction Engineering of Gansu Province, Lanzhou 730050, China.
| | - Chunnian Liang
- Animal Science Department, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China.
- Key Laboratory for Yak Genetics, Breeding, and Reproduction Engineering of Gansu Province, Lanzhou 730050, China.
| | - Ping Yan
- Animal Science Department, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China.
- Key Laboratory for Yak Genetics, Breeding, and Reproduction Engineering of Gansu Province, Lanzhou 730050, China.
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14
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Bovo S, Mazzoni G, Bertolini F, Schiavo G, Galimberti G, Gallo M, Dall'Olio S, Fontanesi L. Genome-wide association studies for 30 haematological and blood clinical-biochemical traits in Large White pigs reveal genomic regions affecting intermediate phenotypes. Sci Rep 2019; 9:7003. [PMID: 31065004 PMCID: PMC6504931 DOI: 10.1038/s41598-019-43297-1] [Citation(s) in RCA: 40] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2018] [Accepted: 04/16/2019] [Indexed: 12/20/2022] Open
Abstract
Haematological and clinical-biochemical parameters are considered indicators of the physiological/health status of animals and might serve as intermediate phenotypes to link physiological aspects to production and disease resistance traits. The dissection of the genetic variability affecting these phenotypes might be useful to describe the resilience of the animals and to support the usefulness of the pig as animal model. Here, we analysed 15 haematological and 15 clinical-biochemical traits in 843 Italian Large White pigs, via three genome-wide association scan approaches (single-trait, multi-trait and Bayesian). We identified 52 quantitative trait loci (QTLs) associated with 29 out of 30 analysed blood parameters, with the most significant QTL identified on porcine chromosome 14 for basophil count. Some QTL regions harbour genes that may be the obvious candidates: QTLs for cholesterol parameters identified genes (ADCY8, APOB, ATG5, CDKAL1, PCSK5, PRL and SOX6) that are directly involved in cholesterol metabolism; other QTLs highlighted genes encoding the enzymes being measured [ALT (known also as GPT) and AST (known also as GOT)]. Moreover, the multivariate approach strengthened the association results for several candidate genes. The obtained results can contribute to define new measurable phenotypes that could be applied in breeding programs as proxies for more complex traits.
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Affiliation(s)
- Samuele Bovo
- Department of Agricultural and Food Sciences, Division of Animal Sciences, University of Bologna, Viale G. Fanin 46, 40127, Bologna, Italy
| | - Gianluca Mazzoni
- Department of Health Technology, Technical University of Denmark (DTU), Lyngby, 2800, Denmark
| | - Francesca Bertolini
- National Institute of Aquatic Resources, Technical University of Denmark (DTU), Lyngby, 2800, Denmark
| | - Giuseppina Schiavo
- Department of Agricultural and Food Sciences, Division of Animal Sciences, University of Bologna, Viale G. Fanin 46, 40127, Bologna, Italy
| | - Giuliano Galimberti
- Department of Statistical Sciences "Paolo Fortunati", University of Bologna, Via delle Belle Arti 41, 40126, Bologna, Italy
| | - Maurizio Gallo
- Associazione Nazionale Allevatori Suini (ANAS), Via Nizza 53, 00198, Roma, Italy
| | - Stefania Dall'Olio
- Department of Agricultural and Food Sciences, Division of Animal Sciences, University of Bologna, Viale G. Fanin 46, 40127, Bologna, Italy
| | - Luca Fontanesi
- Department of Agricultural and Food Sciences, Division of Animal Sciences, University of Bologna, Viale G. Fanin 46, 40127, Bologna, Italy.
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15
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New world goat populations are a genetically diverse reservoir for future use. Sci Rep 2019; 9:1476. [PMID: 30728441 PMCID: PMC6365549 DOI: 10.1038/s41598-019-38812-3] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2018] [Accepted: 10/30/2018] [Indexed: 01/02/2023] Open
Abstract
Western hemisphere goats have European, African and Central Asian origins, and some local or rare breeds are reported to be adapted to their environments and economically important. By-in-large these genetic resources have not been quantified. Using 50 K SNP genotypes of 244 animals from 12 goat populations in United States, Costa Rica, Brazil and Argentina, we evaluated the genetic diversity, population structure and selective sweeps documenting goat migration to the "New World". Our findings suggest the concept of breed, particularly among "locally adapted" breeds, is not a meaningful way to characterize goat populations. The USA Spanish goats were found to be an important genetic reservoir, sharing genomic composition with the wild ancestor and with specialized breeds (e.g. Angora, Lamancha and Saanen). Results suggest goats in the Americas have substantial genetic diversity to use in selection and promote environmental adaptation or product driven specialization. These findings highlight the importance of maintaining goat conservation programs and suggest an awaiting reservoir of genetic diversity for breeding and research while simultaneously discarding concerns about breed designations.
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16
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Yan G, Guo T, Xiao S, Zhang F, Xin W, Huang T, Xu W, Li Y, Zhang Z, Huang L. Imputation-Based Whole-Genome Sequence Association Study Reveals Constant and Novel Loci for Hematological Traits in a Large-Scale Swine F 2 Resource Population. Front Genet 2018; 9:401. [PMID: 30405681 PMCID: PMC6204663 DOI: 10.3389/fgene.2018.00401] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2018] [Accepted: 09/03/2018] [Indexed: 11/13/2022] Open
Abstract
The whole-genome sequences of progenies with low-density single-nucleotide polymorphism (SNP) genotypes can be imputed with high accuracy based on the deep-coverage sequences of key ancestors. With this imputation technology, a more powerful genome-wide association study (GWAS) can be carried out using imputed whole-genome variants and the phenotypes of interest to overcome the shortcomings of low-power detection and the large confidence interval derived from low-density SNP markers in classic association studies. In this study, 19 ancestors of a large-scale swine F2 White Duroc × Erhualian population were deeply sequenced for their genome with an average coverage of 25×. Considering 98 pigs from 10 different breeds with high-quality deep sequenced genomes, we imputed the whole genomic variants of 1020 F2 pigs genotyped by the PorcineSNP60 BeadChip with high accuracy and obtained 14,851,440 sequence variants after quality control. Based on this, 87 novel quantitative traits loci (QTLs) for 18 hematological traits at three different physiological stages of the F2 pigs were identified, among which most of the novel QTLs have been repeated in two of the three stages. Literature mining pinpointed that the FGF14 and LCLAT1 genes at SSC11 and SSC3 may affect the MCH at day 240 and MCV at day 18, respectively. The present study shows that combining high-quality imputed genomic variants and correlated phenomic traits into GWAS can improve the capability to detect QTL considerably. The large number of different QTLs for hematological traits identified at multiple growth stages implies the complexity and time specificity of these traits.
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Affiliation(s)
- Guorong Yan
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, China
| | - Tianfu Guo
- 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
| | - Feng Zhang
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, China
| | - Wenshui Xin
- 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
| | - Wenwu Xu
- 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
| | - Zhiyan Zhang
- 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
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17
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Zhang J, Chen JH, Liu XD, Wang HY, Liu XL, Li XY, Wu ZF, Zhu MJ, Zhao SH. Genomewide association studies for hematological traits and T lymphocyte subpopulations in a Duroc × Erhualian F resource population. J Anim Sci 2017; 94:5028-5041. [PMID: 28046140 DOI: 10.2527/jas.2016-0924] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023] Open
Abstract
It has been shown that hematological traits can act as important indicators of immune function in both humans and livestock. T lymphocytes are key components of the adaptive immune system, playing a critical role in immune response. To identify genomic regions affecting hematological traits and T lymphocyte subpopulations, we performed both a SNP-based genomewide association study (GWAS) and a haplotype analysis for 20 hematological traits and 8 T cell subpopulations at 3 different time points (d 20, 33, and 35) in a Duroc × Erhualian F intercross population. Bonferroni correction was used to calculate the threshold -values for suggestive and 5% genomewide significance levels. In total, for SNP-based GWAS, we detected 96 significant SNP, including 15 genomewide-significant SNP, associated with 23 hematological traits and 234 significant SNP, including 27 genomewide-significant SNP, associated with 8 T cell subpopulations. Meanwhile, we identified 563 significant SNP, including 7 genomewide-significant SNP, associated with 5 hematological traits and 2,407 significant SNP, including 1,261 genomewide-significant SNP, associated with 8 T cell subpopulations by haplotype analysis. Among the significant regions detected, we propose both the () gene and the () gene on SSC3 as plausible candidate genes associated with CD/CD T lymphocytes at d 20. The findings provide insights into the basis of molecular mechanisms that are involved with immune response in the domestic pig and would aid further identification of causative mutations.
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18
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Xu P, Cui L, Huang T, Zhang Z, Yang B, Chen C, Huang L, Duan Y. Genome-wide identification of quantitative trait transcripts for blood traits in the liver samples of a White Duroc × Erhualian F2 pig resource population. Physiol Genomics 2016; 48:573-9. [PMID: 27260842 DOI: 10.1152/physiolgenomics.00123.2015] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2015] [Accepted: 05/31/2016] [Indexed: 11/22/2022] Open
Abstract
Blood cell counts are important clinical indicators for health status. The liver plays a crucial role in food digestion and metabolism and is also a blood-forming organ. Here, we conducted a whole-genome quantitative trait transcript (QTT) analysis on 497 liver samples for 16 hematological traits in a White Duroc × Erhualian F2 pig resource population. A total of 20,108 transcripts were explored to detect their association with hematological traits. By using Spearman correlation coefficients, we identified 1,267 QTTs for these 16 hematological traits at the significance threshold of P < 0.001. We found 31 candidate genes for erythrocyte and leukocyte-related traits by a look-up of human and pig genome-wide association study results. Furthermore, we constructed coexpression networks for leukocyte-related QTTs using weighted gene coexpression analysis. These QTTs were clustered into two to eight modules. The highest connection strength in intramodules was identified in a module for white blood cell count. In the module, USP18, RSAD2, and OAS1 appeared to be important genes involved in interferon-stimulated innate immune system. The findings improve our understanding of intrinsic relationships between the liver and blood cells and provide novel insights into the potential therapeutic targets of hematologic diseases.
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Affiliation(s)
- Pan Xu
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, People's Republic of China
| | - Leilei Cui
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, People's Republic of China
| | - Tao Huang
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, People's Republic of China
| | - Zhen Zhang
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, People's Republic of China
| | - Bin Yang
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, People's Republic of China
| | - Congying Chen
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, People's Republic of China
| | - Lusheng Huang
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, People's Republic of China
| | - Yanyu Duan
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, People's Republic of China
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Ponsuksili S, Reyer H, Trakooljul N, Murani E, Wimmers K. Single- and Bayesian Multi-Marker Genome-Wide Association for Haematological Parameters in Pigs. PLoS One 2016; 11:e0159212. [PMID: 27434032 PMCID: PMC4951017 DOI: 10.1371/journal.pone.0159212] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2016] [Accepted: 06/28/2016] [Indexed: 12/15/2022] Open
Abstract
Haematological traits are important traits that show associations with immune and metabolic status, as well as diseases in humans and animals. Mapping genome regions that affect the blood cell traits can contribute to the identification of genomic features useable as biomarkers for immune, disease and metabolic status. A genome-wide association study (GWAS) was conducted using PorcineSNP60 BeadChips. Single-marker and Bayesian multi-marker approaches were integrated to identify genomic regions and corresponding genes overlapping for both methods. GWAS was performed for haematological traits of 591 German Landrace pig. Heritability estimates for haematological traits were medium to high. In total 252 single SNPs associated with 12 haematological traits were identified (NegLog10 of p-value > 5). The Bayesian multi-marker approach revealed 102 QTL regions across the genome, indicated by 1-Mb windows with contribution to additive genetic variance above 0.5%. The integration of both methods resulted in 24 overlapping QTL regions. This study identified overlapping QTL regions from single- and multi-marker approaches for haematological traits. Identifying candidate genes that affect blood cell traits provides the first step towards the understanding of the molecular basis of haematological phenotypes.
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Affiliation(s)
- Siriluck Ponsuksili
- Research Unit ‘Functional Genome Analyses’, Institute for Genome Biology, Leibniz Institute for Farm Animal Biology (FBN), Wilhelm-Stahl-Allee 2, D-18196, Dummerstorf, Germany
| | - Henry Reyer
- Research Unit ‘Genomics’, Institute for Genome Biology, Leibniz Institute for Farm Animal Biology (FBN), Wilhelm-Stahl-Allee 2, D-18196, Dummerstorf, Germany
| | - Nares Trakooljul
- Research Unit ‘Genomics’, Institute for Genome Biology, Leibniz Institute for Farm Animal Biology (FBN), Wilhelm-Stahl-Allee 2, D-18196, Dummerstorf, Germany
| | - Eduard Murani
- Research Unit ‘Genomics’, Institute for Genome Biology, Leibniz Institute for Farm Animal Biology (FBN), Wilhelm-Stahl-Allee 2, D-18196, Dummerstorf, Germany
| | - Klaus Wimmers
- Research Unit ‘Genomics’, Institute for Genome Biology, Leibniz Institute for Farm Animal Biology (FBN), Wilhelm-Stahl-Allee 2, D-18196, Dummerstorf, Germany
- * E-mail:
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He Y, Li X, Zhang F, Su Y, Hou L, Chen H, Zhang Z, Huang L. Multi-breed genome-wide association study reveals novel loci associated with the weight of internal organs. Genet Sel Evol 2015; 47:87. [PMID: 26576866 PMCID: PMC4647478 DOI: 10.1186/s12711-015-0168-7] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2014] [Accepted: 10/30/2015] [Indexed: 12/01/2022] Open
Abstract
Background Recently, many genome-wide association studies (GWAS) have been conducted to understand the genetic architecture of economic important traits in farm animals. Pig is widely used as a biomedical animal model for its similarity with humans in terms of organ formation and disease mechanisms. Moreover, understanding the mechanisms that underlie the development of internal organs will impact the productive potential of pigs. Our aim was to uncover new single nucleotide polymorphisms (SNPs) associated with the weight of internal organs and carcass and also potential candidate genes. Methods We performed GWAS for the weight of heart, liver, spleen, kidney and carcass on five pig populations (White Duroc × Erhualian F2 intercross, Sutai population, Laiwu population, Erhualian population and commercial population, for a total of 2650 individuals). Genotype data was produced using the PorcineSNP60 Beadchip array. After quality control, the data was used for association tests under a general linear mixed model. Population stratification was adjusted by including a random polygenic effect based on a matrix of genotypic relationships. A meta-analysis of our GWAS datasets was conducted by summing up the Chi square values across breeds, with the degrees of freedom of the Chi square distribution equal to the effective number of breeds. Results Thirty-nine quantitative trait loci (QTL) located on 15 chromosomes were identified by the single-population GWAS at the suggestive level. Among these, nine QTL surpassed the 5 % genome-wide significance threshold, including four for heart weight on SSC (Sus scrofa chromosome) 2, 4, 7 and 10, two for liver weight on SSC7, two for spleen weight on SSC5 and SSC7 and one for carcass weight on SSC11. The QTL on SSC7 showed pleiotropic effects for heart, liver and spleen weights in the F2 population. In addition, two QTL were detected in several populations, including one on SSC2 for heart weight in the F2 and Sutai populations and one on SSC7 for liver weight in the F2 and Laiwu populations. The meta-analysis detected four novel QTL on SSC1, 3, 8 and 16 for carcass weight. Electronic supplementary material The online version of this article (doi:10.1186/s12711-015-0168-7) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Yuna He
- National Key Laboratory for Swine Genetics, Breeding and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China.
| | - Xinjian Li
- National Key Laboratory for Swine Genetics, Breeding and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China.
| | - Feng Zhang
- National Key Laboratory for Swine Genetics, Breeding and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China.
| | - Ying Su
- National Key Laboratory for Swine Genetics, Breeding and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China.
| | - Lijuan Hou
- National Key Laboratory for Swine Genetics, Breeding and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China.
| | - Hao Chen
- National Key Laboratory for Swine Genetics, Breeding and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China.
| | - Zhiyan Zhang
- National Key Laboratory for Swine Genetics, Breeding and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China.
| | - Lusheng Huang
- National Key Laboratory for Swine Genetics, Breeding and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China.
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Yi G, Shen M, Yuan J, Sun C, Duan Z, Qu L, Dou T, Ma M, Lu J, Guo J, Chen S, Qu L, Wang K, Yang N. Genome-wide association study dissects genetic architecture underlying longitudinal egg weights in chickens. BMC Genomics 2015; 16:746. [PMID: 26438435 PMCID: PMC4595193 DOI: 10.1186/s12864-015-1945-y] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2014] [Accepted: 09/22/2015] [Indexed: 11/22/2022] Open
Abstract
BACKGROUND As a major economic trait in chickens, egg weight (EW) receives widespread interests in breeding, production and consumption. However, limited information is available for underlying genetic architecture of longitudinal trend in EW. Herein, we measured EWs at nine time points from onset of laying to 60 week of age, and conducted comprehensive genome-wide association studies (GWAS) in 1,534 F2 hens derived from reciprocal crosses between White Leghorn and Dongxiang chickens. RESULTS Egg weights at all ages except the first egg weight (FEW) exhibited high SNP-based heritability estimates (0.47~0.60). Strong pair-wise genetic correlations (0.77~1.00) were found among all EWs. Nine separate univariate genome-wide screens suggested 73 signals showing significant associations with longitudinal EWs. After multivariate and conditional analyses, four variants on three chromosomes remained independent contributions. The minor alleles at two loci exerted consistent and positive substitution effects on EWs, and other two were negative. The four loci together accounted for 3.84 % of the phenotypic variance for FEW and 7.29~11.06 % for EWs from 32 to 60 week of age. We obtained five candidate genes, of which NCAPG harbors a non-synonymous SNP (rs14491030) causing a valine-to-alanine amino-acid substitution. Genome partitioning analysis indicated a strong linear correlation between the variance explained by each chromosome and its length, which provided evidence that EW follows a highly polygenic nature of inheritance. CONCLUSIONS Identification of significant genetic causes that together implicate EWs at different ages will greatly advance our understanding of the genetic basis behind longitudinal EWs, and would be helpful to illuminate the future breeding direction on how to select desired egg size.
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Affiliation(s)
- Guoqiang Yi
- Department of Animal Genetics and Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China.
| | - Manman Shen
- Jiangsu Institute of Poultry Science, Yangzhou, Jiangsu, 225125, China.
| | - Jingwei Yuan
- Department of Animal Genetics and Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China.
| | - Congjiao Sun
- Department of Animal Genetics and Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China.
| | - Zhongyi Duan
- Department of Animal Genetics and Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China.
| | - Liang Qu
- Jiangsu Institute of Poultry Science, Yangzhou, Jiangsu, 225125, China.
| | - Taocun Dou
- Jiangsu Institute of Poultry Science, Yangzhou, Jiangsu, 225125, China.
| | - Meng Ma
- Jiangsu Institute of Poultry Science, Yangzhou, Jiangsu, 225125, China.
| | - Jian Lu
- Jiangsu Institute of Poultry Science, Yangzhou, Jiangsu, 225125, China.
| | - Jun Guo
- Jiangsu Institute of Poultry Science, Yangzhou, Jiangsu, 225125, China.
| | - Sirui Chen
- Department of Animal Genetics and Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China.
| | - Lujiang Qu
- Department of Animal Genetics and Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China.
| | - Kehua Wang
- Jiangsu Institute of Poultry Science, Yangzhou, Jiangsu, 225125, China.
| | - Ning Yang
- Department of Animal Genetics and Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China.
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Liu X, Xiong X, Yang J, Zhou L, Yang B, Ai H, Ma H, Xie X, Huang Y, Fang S, Xiao S, Ren J, Ma J, Huang L. Genome-wide association analyses for meat quality traits in Chinese Erhualian pigs and a Western Duroc × (Landrace × Yorkshire) commercial population. Genet Sel Evol 2015; 47:44. [PMID: 25962760 PMCID: PMC4427942 DOI: 10.1186/s12711-015-0120-x] [Citation(s) in RCA: 51] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2014] [Accepted: 04/09/2015] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Understanding the genetic mechanisms that underlie meat quality traits is essential to improve pork quality. To date, most quantitative trait loci (QTL) analyses have been performed on F2 crosses between outbred pig strains and have led to the identification of numerous QTL. However, because linkage disequilibrium is high in such crosses, QTL mapping precision is unsatisfactory and only a few QTL have been found to segregate within outbred strains, which limits their use to improve animal performance. To detect QTL in outbred pig populations of Chinese and Western origins, we performed genome-wide association studies (GWAS) for meat quality traits in Chinese purebred Erhualian pigs and a Western Duroc × (Landrace × Yorkshire) (DLY) commercial population. METHODS Three hundred and thirty six Chinese Erhualian and 610 DLY pigs were genotyped using the Illumina PorcineSNP60K Beadchip and evaluated for 20 meat quality traits. After quality control, 35 985 and 56 216 single nucleotide polymorphisms (SNPs) were available for the Chinese Erhualian and DLY datasets, respectively, and were used to perform two separate GWAS. We also performed a meta-analysis that combined P-values and effects of 29 516 SNPs that were common to Erhualian, DLY, F2 and Sutai pig populations. RESULTS We detected 28 and nine suggestive SNPs that surpassed the significance level for meat quality in Erhualian and DLY pigs, respectively. Among these SNPs, ss131261254 on pig chromosome 4 (SSC4) was the most significant (P = 7.97E-09) and was associated with drip loss in Erhualian pigs. Our results suggested that at least two QTL on SSC12 and on SSC15 may have pleiotropic effects on several related traits. All the QTL that were detected by GWAS were population-specific, including 12 novel regions. However, the meta-analysis revealed seven novel QTL for meat characteristics, which suggests the existence of common underlying variants that may differ in frequency across populations. These QTL regions contain several relevant candidate genes. CONCLUSIONS These findings provide valuable insights into the molecular basis of convergent evolution of meat quality traits in Chinese and Western breeds that show divergent phenotypes. They may contribute to genetic improvement of purebreds for crossbred performance.
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Affiliation(s)
- Xianxian Liu
- Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, Nanchang, 330045, China.
| | - Xinwei Xiong
- Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, Nanchang, 330045, China.
| | - Jie Yang
- Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, Nanchang, 330045, China.
| | - Lisheng Zhou
- Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, Nanchang, 330045, China.
| | - Bin Yang
- Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, Nanchang, 330045, China.
| | - Huashui Ai
- Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, Nanchang, 330045, China.
| | - Huanban Ma
- Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, Nanchang, 330045, China.
| | - Xianhua Xie
- Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, Nanchang, 330045, China.
| | - Yixuan Huang
- Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, Nanchang, 330045, China.
| | - Shaoming Fang
- Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, Nanchang, 330045, China.
| | - Shijun Xiao
- Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, Nanchang, 330045, China.
| | - Jun Ren
- Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, Nanchang, 330045, China.
| | - Junwu Ma
- Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, Nanchang, 330045, China.
| | - Lusheng Huang
- Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, Nanchang, 330045, China.
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Qiao R, Gao J, Zhang Z, Li L, Xie X, Fan Y, Cui L, Ma J, Ai H, Ren J, Huang L. Genome-wide association analyses reveal significant loci and strong candidate genes for growth and fatness traits in two pig populations. Genet Sel Evol 2015; 47:17. [PMID: 25885760 PMCID: PMC4358731 DOI: 10.1186/s12711-015-0089-5] [Citation(s) in RCA: 50] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2014] [Accepted: 01/08/2015] [Indexed: 12/31/2022] Open
Abstract
BACKGROUND Recently, genome-wide association studies (GWAS) have been reported on various pig traits. We performed a GWAS to analyze 22 traits related to growth and fatness on two pig populations: a White Duroc × Erhualian F2 intercross population and a Chinese Sutai half-sib population. RESULTS We identified 14 and 39 loci that displayed significant associations with growth and fatness traits at the genome-wide level and chromosome-wide level, respectively. The strongest association was between a 750 kb region on SSC7 (SSC for Sus scrofa) and backfat thickness at the first rib. This region had pleiotropic effects on both fatness and growth traits in F2 animals and contained a promising candidate gene HMGA1 (high mobility group AT-hook 1). Unexpectedly, population genetic analysis revealed that the allele at this locus that reduces fatness and increases growth is derived from Chinese indigenous pigs and segregates in multiple Chinese breeds. The second strongest association was between the region around 82.85 Mb on SSC4 and average backfat thickness. PLAG1 (pleiomorphic adenoma gene 1), a gene under strong selection in European domestic pigs, is proximal to the top SNP and stands out as a strong candidate gene. On SSC2, a locus that significantly affects fatness traits mapped to the region around the IGF2 (insulin-like growth factor 2) gene but its non-imprinting inheritance excluded IGF2 as a candidate gene. A significant locus was also detected within a recombination cold spot that spans more than 30 Mb on SSCX, which hampered the identification of plausible candidate genes. Notably, no genome-wide significant locus was shared by the two experimental populations; different loci were observed that had both constant and time-specific effects on growth traits at different stages, which illustrates the complex genetic architecture of these traits. CONCLUSIONS We confirm several previously reported QTL and provide a list of novel loci for porcine growth and fatness traits in two experimental populations with Chinese Taihu and Western pigs as common founders. We showed that distinct loci exist for these traits in the two populations and identified HMGA1 and PLAG1 as strong candidate genes on SSC7 and SSC4, respectively.
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Affiliation(s)
- Ruimin Qiao
- Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, Nanchang, China.
| | - Jun Gao
- Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, Nanchang, China.
| | - Zhiyan Zhang
- Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, Nanchang, China.
| | - Lin Li
- Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, Nanchang, China.
| | - Xianhua Xie
- Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, Nanchang, China.
| | - Yin Fan
- Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, Nanchang, China.
| | - Leilei Cui
- Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, Nanchang, China.
| | - Junwu Ma
- Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, Nanchang, China.
| | - Huashui Ai
- Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, Nanchang, China.
| | - Jun Ren
- Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, Nanchang, China.
| | - Lusheng Huang
- Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, Nanchang, China.
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Cui L, Zhang J, Ma J, Guo Y, Li L, Xiao S, Ren J, Yang B, Huang L. Sexually dimorphic genetic architecture of complex traits in a large-scale F2 cross in pigs. Genet Sel Evol 2014; 46:76. [PMID: 25374066 PMCID: PMC4221709 DOI: 10.1186/s12711-014-0076-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2014] [Accepted: 10/20/2014] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND It is common for humans and model organisms to exhibit sexual dimorphism in a variety of complex traits. However, this phenomenon has rarely been explored in pigs. RESULTS To investigate the genetic contribution to sexual dimorphism in complex traits in pigs, we conducted a sex-stratified analysis on 213 traits measured in 921 individuals produced by a White Duroc × Erhualian F2 cross. Of the 213 traits examined, 102 differed significantly between the two sexes (q value <0.05), which indicates that sex is an important factor that influences a broad range of traits in pigs. We compared the estimated heritability of these 213 traits between males and females. In particular, we found that traits related to meat quality and fatty acid composition were significantly different between the two sexes, which shows that genetic factors contribute to variation in sexual dimorphic traits. Next, we performed a genome-wide association study (GWAS) in males and females separately; this approach allowed us to identify 13.6% more significant trait-SNP (single nucleotide polymorphism) associations compared to the number of associations identified in a GWAS that included both males and females. By comparing the allelic effects of SNPs in the two sexes, we identified 43 significant sexually dimorphic SNPs that were associated with 22 traits; 41 of these 43 loci were autosomal. The most significant sexually dimorphic loci were found to be associated with muscle hue angle and Minolta a* values (which are parameters that reflect the redness of meat) and were located between 9.3 and 10.7 Mb on chromosome 6. A nearby gene i.e. NUDT7 that plays an important role in heme synthesis is a strong candidate gene. CONCLUSIONS This study illustrates that sex is an important factor that influences phenotypic values and modifies the effects of the genetic variants that underlie complex traits in pigs; it also emphasizes the importance of stratifying by sex when performing GWAS.
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Affiliation(s)
- Leilei Cui
- Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, 330045 Nanchang, China
| | - Junjie Zhang
- Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, 330045 Nanchang, China
| | - Junwu Ma
- Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, 330045 Nanchang, China
| | - Yuanmei Guo
- Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, 330045 Nanchang, China
| | - Lin Li
- Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, 330045 Nanchang, China
| | - Shijun Xiao
- Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, 330045 Nanchang, China
| | - Jun Ren
- Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, 330045 Nanchang, China
| | - Bin Yang
- Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, 330045 Nanchang, China
| | - Lusheng Huang
- Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, 330045 Nanchang, China
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Zhang F, Zhang Z, Yan X, Chen H, Zhang W, Hong Y, Huang L. Genome-wide association studies for hematological traits in Chinese Sutai pigs. BMC Genet 2014; 15:41. [PMID: 24674592 PMCID: PMC3986688 DOI: 10.1186/1471-2156-15-41] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2013] [Accepted: 03/10/2014] [Indexed: 11/10/2022] Open
Abstract
Background It has been shown that hematological traits are strongly associated with the metabolism and the immune system in domestic pig. However, little is known about the genetic architecture of hematological traits. To identify quantitative trait loci (QTL) controlling hematological traits, we performed single marker Genome-wide association studies (GWAS) and haplotype analysis for 15 hematological traits in 495 Chinese Sutai pigs. Results We identified 161 significant SNPs including 44 genome-wide significant SNPs associated with 11 hematological traits by single marker GWAS. Most of them were located on SSC2. Meanwhile, we detected 499 significant SNPs containing 154 genome-wide significant SNPs associated with 9 hematological traits by haplotype analysis. Most of the identified loci were located on SSC7 and SSC9. Conclusions We detected 4 SNPs with pleiotropic effects on SSC2 by single marker GWAS and (or) on SSC7 by haplotype analysis. Furthermore, through checking the gene functional annotations, positions and their expression variation, we finally selected 7 genes as potential candidates. Specially, we found that three genes (TRIM58, TRIM26 and TRIM21) of them originated from the same gene family and executed similar function of innate and adaptive immune. The findings will contribute to dissection the immune gene network, further identification of causative mutations underlying the identified QTLs and providing insights into the molecular basis of hematological trait in domestic pig.
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Affiliation(s)
| | | | | | | | | | | | - Lusheng Huang
- Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, 330045 Nanchang, China.
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