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Long M, Wang B, Yang Z, Lu X. Genome-Wide Association Study as an Efficacious Approach to Discover Candidate Genes Associated with Body Linear Type Traits in Dairy Cattle. Animals (Basel) 2024; 14:2181. [PMID: 39123707 PMCID: PMC11311069 DOI: 10.3390/ani14152181] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2024] [Revised: 07/19/2024] [Accepted: 07/23/2024] [Indexed: 08/12/2024] Open
Abstract
Body shape traits are very important and play a crucial role in the economic development of dairy farming. By improving the accuracy of selection for body size traits, we can enhance economic returns across the dairy industry and on farms, contributing to the future profitability of the dairy sector. Registered body conformation traits are reliable and cost-effective tools for use in national cattle breeding selection programs. These traits are significantly related to the production, longevity, mobility, health, fertility, and environmental adaptation of dairy cows. Therefore, they can be considered indirect indicators of economically important traits in dairy cows. Utilizing efficacious genetic methods, such as genome-wide association studies (GWASs), allows for a deeper understanding of the genetic architecture of complex traits through the identification and application of genetic markers. In the current review, we summarize information on candidate genes and genomic regions associated with body conformation traits in dairy cattle worldwide. The manuscript also reviews the importance of body conformation, the relationship between body conformation traits and other traits, heritability, influencing factors, and the genetics of body conformation traits. The information on candidate genes related to body conformation traits provided in this review may be helpful in selecting potential genetic markers for the genetic improvement of body conformation traits in dairy cattle.
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Affiliation(s)
- Mingxue Long
- College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China; (M.L.); (Z.Y.)
| | - Bo Wang
- College of Food Science and Engineering, Yangzhou University, Yangzhou 225009, China;
| | - Zhangping Yang
- College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China; (M.L.); (Z.Y.)
| | - Xubin Lu
- College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China; (M.L.); (Z.Y.)
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2
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Cai Z, Iso-Touru T, Sanchez MP, Kadri N, Bouwman AC, Chitneedi PK, MacLeod IM, Vander Jagt CJ, Chamberlain AJ, Gredler-Grandl B, Spengeler M, Lund MS, Boichard D, Kühn C, Pausch H, Vilkki J, Sahana G. Meta-analysis of six dairy cattle breeds reveals biologically relevant candidate genes for mastitis resistance. Genet Sel Evol 2024; 56:54. [PMID: 39009986 PMCID: PMC11247842 DOI: 10.1186/s12711-024-00920-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2023] [Accepted: 06/26/2024] [Indexed: 07/17/2024] Open
Abstract
BACKGROUND Mastitis is a disease that incurs significant costs in the dairy industry. A promising approach to mitigate its negative effects is to genetically improve the resistance of dairy cattle to mastitis. A meta-analysis of genome-wide association studies (GWAS) across multiple breeds for clinical mastitis (CM) and its indicator trait, somatic cell score (SCS), is a powerful method to identify functional genetic variants that impact mastitis resistance. RESULTS We conducted meta-analyses of eight and fourteen GWAS on CM and SCS, respectively, using 30,689 and 119,438 animals from six dairy cattle breeds. Methods for the meta-analyses were selected to properly account for the multi-breed structure of the GWAS data. Our study revealed 58 lead markers that were associated with mastitis incidence, including 16 loci that did not overlap with previously identified quantitative trait loci (QTL), as curated at the Animal QTLdb. Post-GWAS analysis techniques such as gene-based analysis and genomic feature enrichment analysis enabled prioritization of 31 candidate genes and 14 credible candidate causal variants that affect mastitis. CONCLUSIONS Our list of candidate genes can help to elucidate the genetic architecture underlying mastitis resistance and provide better tools for the prevention or treatment of mastitis, ultimately contributing to more sustainable animal production.
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Affiliation(s)
- Zexi Cai
- Center for Quantitative Genetics and Genomics, Aarhus University, 8000, Aarhus, Denmark.
| | - Terhi Iso-Touru
- Natural Resources Institute Finland (Luke), 31600, Jokioinen, Finland
| | - Marie-Pierre Sanchez
- Université Paris-Saclay, INRAE, AgroParisTech, GABI, 78350, Jouy-en-Josas, France
| | - Naveen Kadri
- Animal Genomics, ETH Zurich, 8092, Zurich, Switzerland
| | - Aniek C Bouwman
- Wageningen University and Research, Animal Breeding and Genomics, P.O. Box 338, 6700, AH, Wageningen, The Netherlands
| | - Praveen Krishna Chitneedi
- Institute of Genome Biology, Research Institute for Farm Animal Biology (FBN), 18196, Dummerstorf, Germany
| | - Iona M MacLeod
- Agriculture Victoria, AgriBio, Centre for AgriBiosciences, Bundoora, VIC, Australia
- School of Applied Systems Biology, La Trobe University, Bundoora, VIC, 3083, Australia
| | | | - Amanda J Chamberlain
- Agriculture Victoria, AgriBio, Centre for AgriBiosciences, Bundoora, VIC, Australia
| | - Birgit Gredler-Grandl
- Wageningen University and Research, Animal Breeding and Genomics, P.O. Box 338, 6700, AH, Wageningen, The Netherlands
| | | | - Mogens Sandø Lund
- Center for Quantitative Genetics and Genomics, Aarhus University, 8000, Aarhus, Denmark
| | - Didier Boichard
- Université Paris-Saclay, INRAE, AgroParisTech, GABI, 78350, Jouy-en-Josas, France
| | - Christa Kühn
- Institute of Genome Biology, Research Institute for Farm Animal Biology (FBN), 18196, Dummerstorf, Germany
- Agricultural and Environmental Faculty, University Rostock, 18059, Rostock, Germany
| | - Hubert Pausch
- Animal Genomics, ETH Zurich, 8092, Zurich, Switzerland
| | - Johanna Vilkki
- Natural Resources Institute Finland (Luke), 31600, Jokioinen, Finland
| | - Goutam Sahana
- Center for Quantitative Genetics and Genomics, Aarhus University, 8000, Aarhus, Denmark
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Bucher EA, Mészáros G, Gebre KT, Emmerling R, Sölkner J. Genome-wide association study for milking speed in Fleckvieh cattle. J Dairy Sci 2024:S0022-0302(24)00960-3. [PMID: 38908711 DOI: 10.3168/jds.2024-24854] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2024] [Accepted: 05/24/2024] [Indexed: 06/24/2024]
Abstract
Milking speed is an important trait influencing udder health of dairy cows as well as labor efficiency. Yet, it has received little attention in genomic association studies. The main objective of this study was to determine regions and genes on the genome with a potential effect on milking speed in Fleckvieh (dual purpose Simmental) cattle. Genome-wide association studies were conducted using de-regressed breeding values of bulls as phenotypes. Six SNP on 4 autosomes were significantly associated with milking speed for additive effects. Significant regions on BTA4 and BTA19 correspond with findings for other dairy cattle breeds. Based on the observation of Fleckvieh breed managers, variation of milking speed in batches of daughters of some bulls is much higher than in daughter groups of other bulls. This difference in within family variation may be caused by transmission of alternative alleles of bulls being heterozygous for a gene affecting milking speed. To check on this, we considered standard deviation of yield deviations in milking speed of half-sib daughters as a new trait and performed GWAS for dominance effects. One signal on BTA5 passed the genome wide Bonferroni threshold that corresponded to the significant signal from standard GWAS on de-regressed breeding values. The key conclusion of this study is that several strong genomic signals were found for milking speed in Fleckvieh cattle and that the strongest of them are supported by similar findings in Brown Swiss and Holstein Friesian cattle. Milking speed is a complex trait whose sub-processes have not yet been elucidated in detail. Hence, it remains a challenge to link the associated regions on the genome with causal genes and their functions.
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Affiliation(s)
- E A Bucher
- University of Natural Resources and Life Sciences of Vienna, Department of Sustainable Agricultural Systems, Gregor-Mendel-Strasse 33, 1180, Vienna, Austria
| | - G Mészáros
- University of Natural Resources and Life Sciences of Vienna, Department of Sustainable Agricultural Systems, Gregor-Mendel-Strasse 33, 1180, Vienna, Austria.
| | - K T Gebre
- University of Natural Resources and Life Sciences of Vienna, Department of Sustainable Agricultural Systems, Gregor-Mendel-Strasse 33, 1180, Vienna, Austria; Mekelle University, Department of Animal, Rangeland and Wildlife Sciences (ARWS), Enda-Eyesus campus, P.O Box 231, Mekelle, Ethiopia
| | - R Emmerling
- Institute of Animal Breeding, Bavarian State Research Center for Agriculture, 85586 Poing-Grub, Germany
| | - J Sölkner
- University of Natural Resources and Life Sciences of Vienna, Department of Sustainable Agricultural Systems, Gregor-Mendel-Strasse 33, 1180, Vienna, Austria
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Leonard AS, Mapel XM, Pausch H. Pangenome-genotyped structural variation improves molecular phenotype mapping in cattle. Genome Res 2024; 34:300-309. [PMID: 38355307 PMCID: PMC10984387 DOI: 10.1101/gr.278267.123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2023] [Accepted: 02/01/2024] [Indexed: 02/16/2024]
Abstract
Expression and splicing quantitative trait loci (e/sQTL) are large contributors to phenotypic variability. Achieving sufficient statistical power for e/sQTL mapping requires large cohorts with both genotypes and molecular phenotypes, and so, the genomic variation is often called from short-read alignments, which are unable to comprehensively resolve structural variation. Here we build a pangenome from 16 HiFi haplotype-resolved cattle assemblies to identify small and structural variation and genotype them with PanGenie in 307 short-read samples. We find high (>90%) concordance of PanGenie-genotyped and DeepVariant-called small variation and confidently genotype close to 21 million small and 43,000 structural variants in the larger population. We validate 85% of these structural variants (with MAF > 0.1) directly with a subset of 25 short-read samples that also have medium coverage HiFi reads. We then conduct e/sQTL mapping with this comprehensive variant set in a subset of 117 cattle that have testis transcriptome data, and find 92 structural variants as causal candidates for eQTL and 73 for sQTL. We find that roughly half of the top associated structural variants affecting expression or splicing are transposable elements, such as SV-eQTL for STN1 and MYH7 and SV-sQTL for CEP89 and ASAH2 Extensive linkage disequilibrium between small and structural variation results in only 28 additional eQTL and 17 sQTL discovered when including SVs, although many top associated SVs are compelling candidates.
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Affiliation(s)
| | - Xena M Mapel
- Animal Genomics, ETH Zurich, 8092 Zurich, Switzerland
| | - Hubert Pausch
- Animal Genomics, ETH Zurich, 8092 Zurich, Switzerland
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5
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Qiu Z, Cai W, Liu Q, Liu K, Liu C, Yang H, Huang R, Li P, Zhao Q. Unravelling novel and pleiotropic genes for cannon bone circumference and bone mineral density in Yorkshire pigs. J Anim Sci 2024; 102:skae036. [PMID: 38330300 PMCID: PMC10914368 DOI: 10.1093/jas/skae036] [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: 10/07/2023] [Accepted: 02/03/2024] [Indexed: 02/10/2024] Open
Abstract
Leg weakness is a prevalent health condition in pig farms. The augmentation of cannon bone circumference and bone mineral density can effectively improve limb strength in pigs and alleviate leg weakness. This study measured forelimb cannon bone circumference (fCBC) and rear limb cannon bone circumference (rCBC) using an inelastic tapeline and rear limb metatarsal area bone mineral density (raBMD) using a dual-energy X-ray absorptiometry bone density scanner. The samples of Yorkshire castrated boars were genotyped using a 50K single-nucleotide polymorphism (SNP) array. The SNP-chip data were imputed to the level of whole-genome sequencing data (iWGS). This study used iWGS data to perform genome-wide association studies and identified novel significant SNPs associated with fCBC on SSC6, SSC12, and SSC13, rCBC on SSC12 and SSC14, and raBMD on SSC7. Based on the high phenotypic and genetic correlations between CBC and raBMD, multi-trait meta-analysis was performed to identify pleiotropic SNPs. A significant potential pleiotropic quantitative trait locus (QTL) regulating both CBC and raBMD was identified on SSC15. Bayes fine mapping was used to establish the confidence intervals for these novel QTLs with the most refined confidence interval narrowed down to 56 kb (15.11 to 15.17 Mb on SSC12 for fCBC). Furthermore, the confidence interval for the potential pleiotropic QTL on SSC15 in the meta-analysis was narrowed down to 7.45 kb (137.55 to137.56 Mb on SSC15). Based on the biological functions of genes, the following genes were identified as novel regulatory candidates for different phenotypes: DDX42, MYSM1, FTSJ3, and MECOM for fCBC; SMURF2, and STC1 for rCBC; RGMA for raBMD. Additionally, RAMP1, which was determined to be located 23.68 kb upstream of the confidence interval of the QTL on SSC15 in the meta-analysis, was identified as a potential pleiotropic candidate gene regulating both CBC and raBMD. These findings offered valuable insights for identifying pathogenic genes and elucidating the genetic mechanisms underlying CBC and BMD.
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Affiliation(s)
- Zijian Qiu
- Key Laboratory in Nanjing for Evaluation and Utilization of Pigs Resources, Ministry of Agriculture and Rural Areas of China, Institute of Swine Science, Nanjing Agricultural University, Nanjing 210095, China
| | - Wenwu Cai
- Key Laboratory in Nanjing for Evaluation and Utilization of Pigs Resources, Ministry of Agriculture and Rural Areas of China, Institute of Swine Science, Nanjing Agricultural University, Nanjing 210095, China
| | - Qian Liu
- Key Laboratory in Nanjing for Evaluation and Utilization of Pigs Resources, Ministry of Agriculture and Rural Areas of China, Institute of Swine Science, Nanjing Agricultural University, Nanjing 210095, China
| | - Kaiyue Liu
- Key Laboratory in Nanjing for Evaluation and Utilization of Pigs Resources, Ministry of Agriculture and Rural Areas of China, Institute of Swine Science, Nanjing Agricultural University, Nanjing 210095, China
| | - Chenxi Liu
- Key Laboratory in Nanjing for Evaluation and Utilization of Pigs Resources, Ministry of Agriculture and Rural Areas of China, Institute of Swine Science, Nanjing Agricultural University, Nanjing 210095, China
| | - Huilong Yang
- Key Laboratory in Nanjing for Evaluation and Utilization of Pigs Resources, Ministry of Agriculture and Rural Areas of China, Institute of Swine Science, Nanjing Agricultural University, Nanjing 210095, China
| | - Ruihua Huang
- Key Laboratory in Nanjing for Evaluation and Utilization of Pigs Resources, Ministry of Agriculture and Rural Areas of China, Institute of Swine Science, Nanjing Agricultural University, Nanjing 210095, China
- Huaian Academy, Nanjing Agricultural University, Huaian 223005, China
| | - Pinghua Li
- Key Laboratory in Nanjing for Evaluation and Utilization of Pigs Resources, Ministry of Agriculture and Rural Areas of China, Institute of Swine Science, Nanjing Agricultural University, Nanjing 210095, China
- Huaian Academy, Nanjing Agricultural University, Huaian 223005, China
| | - Qingbo Zhao
- Key Laboratory in Nanjing for Evaluation and Utilization of Pigs Resources, Ministry of Agriculture and Rural Areas of China, Institute of Swine Science, Nanjing Agricultural University, Nanjing 210095, China
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6
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Ma Z, Chang Y, Brito LF, Li Y, Yang T, Wang Y, Yang N. Multitrait meta-analyses identify potential candidate genes for growth-related traits in Holstein heifers. J Dairy Sci 2023; 106:9055-9070. [PMID: 37641329 DOI: 10.3168/jds.2023-23462] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Accepted: 06/20/2023] [Indexed: 08/31/2023]
Abstract
Understanding the underlying pleiotropic relationships among growth and body size traits is important for refining breeding strategies in dairy cattle for optimal body size and growth rate. Therefore, we performed single-trait GWAS for monthly-recorded body weight (BW), hip height, body length, and chest girth from birth to 12 mo of age in Holstein animals, followed by stepwise multiple regression of independent or lowly-linked markers from GWAS loci using conditional and joint association analyses (COJO). Subsequently, we conducted a multitrait meta-analysis to detect pleiotropic markers. Based on the single-trait GWAS, we identified 170 significant SNPs, in which 59 of them remained significant after the COJO analyses. The most significant SNP, located at BTA7:3,676,741, explained 2.93% of the total phenotypic variance for BW6 (BW at 6 mo of age). We identified 17 SNPs with potential pleiotropic effects based on the multitrait meta-analyses, which resulted in 3 additional SNPs in comparison to those detected based on the single-trait GWAS. The identified quantitative trait loci regions overlap with genes known to influence human growth-related traits. According to positional and functional analyses, we proposed HMGA2, HNF4G, MED13L, BHLHE40, FRZB, DMP1, TRIB3, and GATAD2A as important candidate genes influencing the studied traits. The combination of single-trait GWAS and meta-analyses of GWAS results improved the efficiency of detecting associated SNPs, and provided new insights into the genetic mechanisms of growth and development in Holstein cattle.
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Affiliation(s)
- Z Ma
- Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture of China, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, 100193, Beijing, China; Beijing Sunlon Livestock Development Co. Ltd., 100029, Beijing, China
| | - Y Chang
- Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture of China, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, 100193, Beijing, China
| | - Luiz F Brito
- Department of Animal Sciences, Purdue University, West Lafayette, IN 47907
| | - Y Li
- Beijing Sunlon Livestock Development Co. Ltd., 100029, Beijing, China
| | - T Yang
- Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture of China, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, 100193, Beijing, China
| | - Y Wang
- Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture of China, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, 100193, Beijing, China.
| | - N Yang
- Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture of China, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, 100193, Beijing, China.
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Hu M, Jiang H, Lai W, Shi L, Yi W, Sun H, Chen C, Yuan B, Yan S, Zhang J. Assessing Genomic Diversity and Signatures of Selection in Chinese Red Steppe Cattle Using High-Density SNP Array. Animals (Basel) 2023; 13:ani13101717. [PMID: 37238146 DOI: 10.3390/ani13101717] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Revised: 05/13/2023] [Accepted: 05/19/2023] [Indexed: 05/28/2023] Open
Abstract
Chinese Red Steppe Cattle (CRS), a composite cattle breed, is well known for its milk production, high slaughter rate, carcass traits, and meat quality. Nowadays, it is widely bred in Jilin and Hebei Province and the Inner Mongolia Autonomous region. However, the population structure and the genetic basis of prominent characteristics of CRS are still unknown. In this study, we systematically describe their population structure, genetic diversity, and selection signature based on genotyping data from 61 CRS individuals with GGP Bovine 100 K chip. The results showed that CRS cattle had low inbreeding levels and had formed a unique genetic structure feature. Using two complementary methods (including comprehensive haplotype score and complex likelihood ratio), we identified 1291 and 1285 potentially selected genes, respectively. There were 141 genes annotated in common 106 overlapping genomic regions covered 5.62 Mb, including PLAG1, PRKG2, DGAT1, PARP10, TONSL, ADCK5, and BMP3, most of which were enriched in pathways related to muscle growth and differentiation, milk production, and lipid metabolism. This study will contribute to understanding the genetic mechanism behind artificial selection and give an extensive reference for subsequent breeding.
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Affiliation(s)
- Mingyue Hu
- College of Animal Science, Jilin University, Changchun 130062, China
| | - Hao Jiang
- College of Animal Science, Jilin University, Changchun 130062, China
| | - Weining Lai
- College of Animal Science, Jilin University, Changchun 130062, China
| | - Lulu Shi
- College of Animal Science, Jilin University, Changchun 130062, China
| | - Wenfeng Yi
- College of Animal Science, Jilin University, Changchun 130062, China
| | - Hao Sun
- College of Animal Science, Jilin University, Changchun 130062, China
| | - Chengzhen Chen
- College of Animal Science, Jilin University, Changchun 130062, China
| | - Bao Yuan
- College of Animal Science, Jilin University, Changchun 130062, China
| | - Shouqing Yan
- College of Animal Science, Jilin University, Changchun 130062, China
| | - Jiabao Zhang
- College of Animal Science, Jilin University, Changchun 130062, China
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8
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The association of gene polymorphisms with milk production and mastitis resistance phenotypic traits in dairy cattle. ANNALS OF ANIMAL SCIENCE 2023. [DOI: 10.2478/aoas-2022-0091] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/10/2023]
Abstract
Abstract
The aim of this study was to evaluate the association between gene polymorphisms (SNPs) and mastitis indicators and their relationship with milk production profitability in dairy herd.A functional analysis was also performed of five genes containing the studied SNPs and those located close by. DNA was isolated from the hair bulb of 320 dairy cows kept in three herds and SNP-microarray analysis was performed. The data on 299 cows was subjected to final statistical analysis using AI-REML method with one-trait repeatability test-day animal model and pedigree information using the DMU4 package. Five from 35 SNPs significantly associated with mastitis indicators or production traits and located within a gene or no more than 500,000 nucleotides from the gene were selected for the functional and economic analysis. A questionnaire was also developed to collect associated economic data of 219 cows from three herds, such as the value of milk production and direct costs incurred over three years; this allowed the gross margin, direct profitability index and direct costs incurred to produce one liter of milk to be determined, among others. None of the five studied SNPs were related to protein content. The rs110785912(T/A), found near CXCR4, and rs136813430(T/C), located in the TLR4 gene exon, were associated with lnSCC, while rs110455063(C/G), located near IGFI, was associated with milk yield, fat and total solid contents. rs109421300(T/C), associated with fat/protein content ratio, as well as fat and total solid content, is located in the DGAT1 gene intron. rs41587003(A/C), located in the DLG2 gene intron, was associated with lactose content. The economic analysis revealed differences between the variants of the three tested SNPs. The T/C variant of the rs136813430(T/C) SNP was characterized by the highest gross margin, the highest direct profitability index and the lowest costs incurred to produce 1 liter of milk. The T/A variant of rs110785912(T/A) was related to low lnSCC and was characterized by the highest direct profitability index. In turn, the C/C variant of the rs41587003(T/C) was related to the lowest level of lactose and the highest costs of milk production. It appears that rs136813430(T/C) may be the most promising of the tested SNPs for increasing the profitability of milk production. To our knowledge, it is the first effort to assess directly a correlation between the DNA polymorphism and economic output of a dairy enterprise.
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Čítek J, Brzáková M, Bauer J, Tichý L, Sztankóová Z, Vostrý L, Steyn Y. Genome-Wide Association Study for Body Conformation Traits and Fitness in Czech Holsteins. Animals (Basel) 2022; 12:ani12243522. [PMID: 36552441 PMCID: PMC10375906 DOI: 10.3390/ani12243522] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Revised: 12/07/2022] [Accepted: 12/12/2022] [Indexed: 12/15/2022] Open
Abstract
The aim of this study was a genome-wide association study (GWAS) on conformation traits using 25,486 genotyped Czech Holsteins, with 35,227 common SNPs for each genotype. Linear trait records were collected between 1995 and 2020. The Interbull information from Multiple Across Country Evaluation (MACE) was included for bulls that mostly had daughter records in a foreign country. When using the Bonferroni correction, the number of SNPs that were either significant or approached the significance threshold was low-dairy capacity composite on BTA4, feet and legs composite BTA21, total score BTA10, stature BTA24, body depth BTA6, angularity BTA20, fore udder attachment BTA10. Without the Bonferroni correction, the total number of significant or near of significance SNPs was 32. The SNPs were localized on BTA1,2,4,5,6,7,8,18,22,25,26,28 for dairy capacity composite, BTA15,21 for feet and legs composite, BTA10 for total score, BTA24 stature, BTA6,23 body depth, BTA20 angularity, BTA2 rump angle, BTA9,10 rear legs rear view, BTA2,19 rear legs side view, BTA10 fore udder attachment, BTA2 udder depth, BTA10 rear udder height, BTA12 central alignment, BTA24 rear teat placement, BTA8,29 rear udder width. The results provide biological information for the improvement of body conformation and fitness in the Holstein population.
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Affiliation(s)
- Jindřich Čítek
- Department of Genetics and Agricultural Biotechnology, Faculty of Agriculture, University of South Bohemia in České Budějovice, Studentská 1668, 370 05 České Budějovice, Czech Republic
- Veterinary Research Institute, Hudcova 296, 621 00 Brno, Czech Republic
| | - Michaela Brzáková
- Institute of Animal Science, Přátelství 815, 104 00 Praha, Czech Republic
| | - Jiří Bauer
- Czech Moravian Breeders' Corporation, Benešovská 123, 252 09 Hradištko, Czech Republic
| | - Ladislav Tichý
- Institute of Animal Science, Přátelství 815, 104 00 Praha, Czech Republic
- Faculty of Agrobiology, Food and Natural Resources, Czech University of Life Sciences Prague, 165 00 Praha, Czech Republic
| | - Zuzana Sztankóová
- Institute of Animal Science, Přátelství 815, 104 00 Praha, Czech Republic
| | - Luboš Vostrý
- Faculty of Agrobiology, Food and Natural Resources, Czech University of Life Sciences Prague, 165 00 Praha, Czech Republic
| | - Yvette Steyn
- Department of Animal and Dairy Science, University of Georgia, 425 River Road, Athens, GA 30602, USA
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Narayana SG, de Jong E, Schenkel FS, Fonseca PA, Chud TC, Powel D, Wachoski-Dark G, Ronksley PE, Miglior F, Orsel K, Barkema HW. Underlying genetic architecture of resistance to mastitis in dairy cattle: A systematic review and gene prioritization analysis of genome-wide association studies. J Dairy Sci 2022; 106:323-351. [DOI: 10.3168/jds.2022-21923] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2022] [Accepted: 08/01/2022] [Indexed: 11/05/2022]
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11
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Ayajuddin M, Phom L, Koza Z, Modi P, Das A, Chaurasia R, Thepa A, Jamir N, Neikha K, Yenisetti SC. Adult health and transition stage-specific rotenone-mediated Drosophila model of Parkinson’s disease: Impact on late-onset neurodegenerative disease models. Front Mol Neurosci 2022; 15:896183. [PMID: 36017079 PMCID: PMC9398202 DOI: 10.3389/fnmol.2022.896183] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Accepted: 07/18/2022] [Indexed: 11/17/2022] Open
Abstract
Parkinson’s disease (PD) affects almost 1% of the population worldwide over the age of 50 years. Exposure to environmental toxins like paraquat and rotenone is a risk factor for sporadic PD which constitutes 95% of total cases. Herbicide rotenone has been shown to cause Parkinsonian symptoms in multiple animal models. Drosophila is an excellent model organism for studying neurodegenerative diseases (NDD) including PD. The aging process is characterized by differential expression of genes during different life stages. Hence it is necessary to develop life-stage-matched animal models for late-onset human disease(s) such as PD. Such animal models are critical for understanding the pathophysiology of age-related disease progression and important to understand if a genotropic drug/nutraceutical can be effective during late stages. With this idea, we developed an adult life stage-specific (health and transition phase, during which late-onset NDDs such as PD sets in) rotenone-mediated Drosophila model of idiopathic PD. Drosophila is susceptible to rotenone in dose-time dependent manner. Rotenone-mediated fly model of sporadic PD exhibits mobility defects (independent of mortality), inhibited mitochondrial complex I activity, dopaminergic (DAergic) neuronal dysfunction (no loss of DAergic neuronal number; however, reduction in rate-limiting enzyme tyrosine hydroxylase (TH) synthesis), and alteration in levels of dopamine (DA) and its metabolites; 3,4-Dihydroxyphenylacetic acid (DOPAC) and Homovanilic acid (HVA) in brain-specific fashion. These PD-linked behaviors and brain-specific phenotypes denote the robustness of the present fly model of PD. This novel model will be of great help to decipher life stage-specific genetic targets of small molecule mediated DAergic neuroprotection; understanding of which is critical for formulating therapeutic strategies for PD.
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12
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Chen Q, Xu L, Zhang M, Zhang T, Yan M, Zhai M, Huang X. Whole genome resequencing reveals the genetic contribution of Kazakh and Swiss Brown cattle to a population of Xinjiang Brown cattle. Gene 2022; 839:146725. [PMID: 35840005 DOI: 10.1016/j.gene.2022.146725] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2022] [Revised: 06/21/2022] [Accepted: 07/08/2022] [Indexed: 11/04/2022]
Abstract
Xinjiang Brown cattle is characterized by wide environmental adaptation from its female parent (Kazakh cattle) and good production performance from its male parent (Swiss Brown cattle). However, the genetic basis underlying these characteristics hasnotbeenexplored. Here we compared 50 genomes of Xinjiang Brown cattle to the genomes of other eight breeds worldwide to analyze patterns of genetic variation in the Xinjiang Brown cattle. We found canonical genomic characteristics of cross breed with the lowest linkage disequilibrium and the highest effective population size. At the global level, Xinjiang Brown cattle had 9.88% Kazakh cattle and 90.12% Swiss Brown cattle inheritance. Our local ancestry inference revealed the segments with the excess of Kazakh cattle blood enriched in genes or pathways involved in digestion,absorption,metabolism and disease. More importantly, we also observed the completely fixed haplotypes inherited from Swiss Brown cattle harboring genes (LCORL, GHR, MEF2D, PCSK1 and MSRB3), KEGG pathways, cattle QTLs or human NHGRIGWAS catalog related to body measurement and growth traits. Our findings will not only help understand the process of cross breeding but can provide basic materials for further QTL mapping and improvement of important traits in Xinjiang Brown cattle.
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Affiliation(s)
- Qiuming Chen
- College of Animal Science, Xinjiang Agricultural University, Urumqi, Xinjiang, China
| | - Lei Xu
- College of Animal Science, Xinjiang Agricultural University, Urumqi, Xinjiang, China
| | - Menghua Zhang
- College of Animal Science, Xinjiang Agricultural University, Urumqi, Xinjiang, China
| | - Tao Zhang
- College of Animal Science, Xinjiang Agricultural University, Urumqi, Xinjiang, China
| | - Mengjie Yan
- College of Animal Science, Xinjiang Agricultural University, Urumqi, Xinjiang, China
| | - Manjun Zhai
- College of Animal Science, Xinjiang Agricultural University, Urumqi, Xinjiang, China
| | - Xixia Huang
- College of Animal Science, Xinjiang Agricultural University, Urumqi, Xinjiang, China.
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13
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Chen SY, Schenkel FS, Melo ALP, Oliveira HR, Pedrosa VB, Araujo AC, Melka MG, Brito LF. Identifying pleiotropic variants and candidate genes for fertility and reproduction traits in Holstein cattle via association studies based on imputed whole-genome sequence genotypes. BMC Genomics 2022; 23:331. [PMID: 35484513 PMCID: PMC9052698 DOI: 10.1186/s12864-022-08555-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Accepted: 04/12/2022] [Indexed: 02/06/2023] Open
Abstract
Background Genetic progress for fertility and reproduction traits in dairy cattle has been limited due to the low heritability of most indicator traits. Moreover, most of the quantitative trait loci (QTL) and candidate genes associated with these traits remain unknown. In this study, we used 5.6 million imputed DNA sequence variants (single nucleotide polymorphisms, SNPs) for genome-wide association studies (GWAS) of 18 fertility and reproduction traits in Holstein cattle. Aiming to identify pleiotropic variants and increase detection power, multiple-trait analyses were performed using a method to efficiently combine the estimated SNP effects of single-trait GWAS based on a chi-square statistic. Results There were 87, 72, and 84 significant SNPs identified for heifer, cow, and sire traits, respectively, which showed a wide and distinct distribution across the genome, suggesting that they have relatively distinct polygenic nature. The biological functions of immune response and fatty acid metabolism were significantly enriched for the 184 and 124 positional candidate genes identified for heifer and cow traits, respectively. No known biological function was significantly enriched for the 147 positional candidate genes found for sire traits. The most important chromosomes that had three or more significant QTL identified are BTA22 and BTA23 for heifer traits, BTA8 and BTA17 for cow traits, and BTA4, BTA7, BTA17, BTA22, BTA25, and BTA28 for sire traits. Several novel and biologically important positional candidate genes were strongly suggested for heifer (SOD2, WTAP, DLEC1, PFKFB4, TRIM27, HECW1, DNAH17, and ADAM3A), cow (ANXA1, PCSK5, SPESP1, and JMJD1C), and sire (ELMO1, CFAP70, SOX30, DGCR8, SEPTIN14, PAPOLB, JMJD1C, and NELL2) traits. Conclusions These findings contribute to better understand the underlying biological mechanisms of fertility and reproduction traits measured in heifers, cows, and sires, which may contribute to improve genomic evaluation for these traits in dairy cattle. Supplementary Information The online version contains supplementary material available at 10.1186/s12864-022-08555-z.
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Affiliation(s)
- Shi-Yi Chen
- Department of Animal Sciences, Purdue University, 270 S. Russell Street, West Lafayette, IN, 47907-2041, USA.,Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, 611130, Sichuan, China
| | - Flavio S Schenkel
- Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, ON, N1G 2W1, Canada
| | - Ana L P Melo
- Department of Reproduction and Animal Evaluation, Rural Federal University of Rio de Janeiro, Seropédica, RJ, 23897-000, Brazil
| | - Hinayah R Oliveira
- Department of Animal Sciences, Purdue University, 270 S. Russell Street, West Lafayette, IN, 47907-2041, USA.,Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, ON, N1G 2W1, Canada
| | - Victor B Pedrosa
- Department of Animal Sciences, Purdue University, 270 S. Russell Street, West Lafayette, IN, 47907-2041, USA.,Department of Animal Sciences, State University of Ponta Grossa, Ponta Grossa, PR, 84030-900, Brazil
| | - Andre C Araujo
- Department of Animal Sciences, Purdue University, 270 S. Russell Street, West Lafayette, IN, 47907-2041, USA
| | - Melkaye G Melka
- Department of Animal and Food Science, University of Wisconsin River Falls, River Falls, WI, 54022, USA
| | - Luiz F Brito
- Department of Animal Sciences, Purdue University, 270 S. Russell Street, West Lafayette, IN, 47907-2041, USA. .,Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, ON, N1G 2W1, Canada.
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14
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Rajawat D, Panigrahi M, Kumar H, Nayak SS, Parida S, Bhushan B, Gaur GK, Dutt T, Mishra BP. Identification of important genomic footprints using eight different selection signature statistics in domestic cattle breeds. Gene 2022; 816:146165. [PMID: 35026292 DOI: 10.1016/j.gene.2021.146165] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2021] [Revised: 12/13/2021] [Accepted: 12/20/2021] [Indexed: 12/25/2022]
Abstract
In the present study, the population genomic data of different cattle breeds were explored to decipher the genomic regions affected due to selective events and reflected in the productive, reproductive, thermo-tolerance, and health-related traits. To find out these genomic deviations due to selective sweeps, we used eight different statistical tools (Tajima's D, Fu & Li's D*, CLR, ROH, iHS, FST, FLK, and hapFLK) on seven indigenous and five exotic cattle breeds. We further performed composite analysis by comparing their covariance matrix. Several candidate genes were found to be related to milk production (ADARB, WDR70, and CA8), reproductive (PARN, FAM134B2, and ZBTB20), and health-related traits (SP110, CXCL2, CLXCL3, CXCL5, IRF8, and MYOM1). The outcome of this investigation provides a basis for detecting selective sweeps that explain the genetic variation of traits. They may possess functional importance for multiple cattle breeds in different subcontinents. However, further studies are required to improve the findings using high-density arrays or whole-genome sequencing with higher resolution and greater sample sizes.
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Affiliation(s)
- Divya Rajawat
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India
| | - Manjit Panigrahi
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India.
| | - Harshit Kumar
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India
| | - Sonali Sonejita Nayak
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India
| | - Subhashree Parida
- Division of Pharmacology & Toxicology, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India
| | - Bharat Bhushan
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India
| | - G K Gaur
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India
| | - Triveni Dutt
- Livestock Production and Management Section, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India
| | - B P Mishra
- Division of Animal Biotechnology, Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India
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15
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Hiltpold M, Janett F, Mapel XM, Kadri NK, Fang ZH, Schwarzenbacher H, Seefried FR, Spengeler M, Witschi U, Pausch H. A 1-bp deletion in bovine QRICH2 causes low sperm count and immotile sperm with multiple morphological abnormalities. Genet Sel Evol 2022; 54:18. [PMID: 35255804 PMCID: PMC8900305 DOI: 10.1186/s12711-022-00710-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Accepted: 02/17/2022] [Indexed: 12/16/2022] Open
Abstract
Abstract
Background
Semen quality and insemination success are monitored in artificial insemination bulls to ensure high male fertility rates. Only ejaculates that fulfill minimum quality requirements are processed and eventually used for artificial inseminations. We examined 70,990 ejaculates from 1343 Brown Swiss bulls to identify bulls from which all ejaculates were rejected due to low semen quality. This procedure identified a bull that produced 12 ejaculates with an aberrantly small number of sperm (0.2 ± 0.2 × 109 sperm per mL) which were mostly immotile due to multiple morphological abnormalities.
Results
The genome of this bull was sequenced at a 12× coverage to investigate a possible genetic cause. Comparing the sequence variant genotypes of this bull with those from 397 fertile bulls revealed a 1-bp deletion in the coding sequence of the QRICH2 gene which encodes the glutamine rich 2 protein, as a compelling candidate causal variant. This 1-bp deletion causes a frameshift in translation and a premature termination codon (ENSBTAP00000018337.1:p.Cys1644AlafsTer52). The analysis of testis transcriptomes from 76 bulls showed that the transcript with the premature termination codon is subject to nonsense-mediated mRNA decay. The 1-bp deletion resides in a 675-kb haplotype that includes 181 single nucleotide polymorphisms (SNPs) from the Illumina BovineHD Bead chip. This haplotype segregates at a frequency of 5% in the Brown Swiss cattle population. Our analysis also identified another bull that carried the 1-bp deletion in the homozygous state. Semen analyses from the second bull confirmed low sperm concentration and immotile sperm with multiple morphological abnormalities that primarily affect the sperm flagellum and, to a lesser extent, the sperm head.
Conclusions
A recessive loss-of-function allele of the bovine QRICH2 gene likely causes low sperm concentration and immotile sperm with multiple morphological abnormalities. Routine sperm analyses unambiguously identify homozygous bulls for this allele. A direct gene test can be implemented to monitor the frequency of the undesired allele in cattle populations.
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16
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Mapel XM, Hiltpold M, Kadri NK, Witschi U, Pausch H. Bull fertility and semen quality are not correlated with dairy and production traits in Brown Swiss cattle. JDS COMMUNICATIONS 2022; 3:120-125. [PMID: 36339738 PMCID: PMC9623726 DOI: 10.3168/jdsc.2021-0164] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Accepted: 11/21/2021] [Indexed: 05/31/2023]
Abstract
Undisturbed reproduction is key for successful breeding of beef and dairy cattle. Improving reproductive ability can be difficult because of antagonistic relationships with other economically relevant traits. In cattle, thorough investigation of female fertility revealed unfavorable genetic correlations with various production phenotypes. However, the correlation between male reproductive ability and production traits remains poorly understood. Here, we investigated the genetic relationships among and between male fertility characteristics and economically relevant traits in a population of Brown Swiss cattle. We performed GWAS with imputed genotypes at nearly 12 million sequence variants for semen quality (sperm head and tail anomalies, motility, concentration, and volume), male fertility, and 57 production phenotypes. Allele substitution effects were then correlated on a trait-by-trait basis to estimate genetic correlations. Correlations between male reproductive characteristics and traits of economic value were small and ranged from -0.0681 to 0.0787. Among the semen quality parameters, sperm motility was negatively correlated with anomalies (head: r = -0.7083 ± 0.0002; tail: r = -0.7739 ± 0.0002) and volume (r = -0.1266 ± 0.0003), whereas volume was negatively correlated with concentration (r = -0.3503 ± 0.0002). Sire nonreturn rate was negatively correlated with sperm anomalies (head: r = -0.1640 ± 0.0002; tail: r = -0.1580 ± 0.0002) and positively correlated with motility (r = 0.1598 ± 0.0002). A meta-analysis of male reproductive traits identified 2 quantitative trait loci: a previously described region on chromosome 6 showed pleiotropic effects and a novel region on chromosome 11 was associated with sperm head anomalies. In conclusion, our results suggest that selection for economically important dairy and production phenotypes has little impact on semen quality and fertility of Brown Swiss bulls.
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Affiliation(s)
- Xena Marie Mapel
- Animal Genomics, ETH Zürich, Universitätsstrasse 2, 8006 Zürich, Switzerland
| | - Maya Hiltpold
- Animal Genomics, ETH Zürich, Universitätsstrasse 2, 8006 Zürich, Switzerland
| | - Naveen Kumar Kadri
- Animal Genomics, ETH Zürich, Universitätsstrasse 2, 8006 Zürich, Switzerland
| | - Ulrich Witschi
- Swissgenetics, Meielenfeldweg 12, 3052 Zollikofen, Switzerland
| | - Hubert Pausch
- Animal Genomics, ETH Zürich, Universitätsstrasse 2, 8006 Zürich, Switzerland
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17
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Niu Q, Zhang T, Xu L, Wang T, Wang Z, Zhu B, Gao X, Chen Y, Zhang L, Gao H, Li J, Xu L. Identification of Candidate Variants Associated With Bone Weight Using Whole Genome Sequence in Beef Cattle. Front Genet 2021; 12:750746. [PMID: 34912371 PMCID: PMC8667311 DOI: 10.3389/fgene.2021.750746] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2021] [Accepted: 10/18/2021] [Indexed: 11/13/2022] Open
Abstract
Bone weight is critical to affect body conformation and stature in cattle. In this study, we conducted a genome-wide association study for bone weight in Chinese Simmental beef cattle based on the imputed sequence variants. We identified 364 variants associated with bone weight, while 350 of them were not included in the Illumina BovineHD SNP array, and several candidate genes and GO terms were captured to be associated with bone weight. Remarkably, we identified four potential variants in a candidate region on BTA6 using Bayesian fine-mapping. Several important candidate genes were captured, including LAP3, MED28, NCAPG, LCORL, SLIT2, and IBSP, which have been previously reported to be associated with carcass traits, body measurements, and growth traits. Notably, we found that the transcription factors related to MED28 and LCORL showed high conservation across multiple species. Our findings provide some valuable information for understanding the genetic basis of body stature in beef cattle.
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Affiliation(s)
- Qunhao Niu
- Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Tianliu Zhang
- Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Ling Xu
- Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Tianzhen Wang
- Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Zezhao Wang
- Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Bo Zhu
- Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Xue Gao
- Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Yan Chen
- Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Lupei Zhang
- Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Huijiang Gao
- Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Junya Li
- Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Lingyang Xu
- Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
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18
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Ma J, Gao X, Li J, Gao H, Wang Z, Zhang L, Xu L, Gao H, Li H, Wang Y, Zhu B, Cai W, Wang C, Chen Y. Assessing the Genetic Background and Selection Signatures of Huaxi Cattle Using High-Density SNP Array. Animals (Basel) 2021; 11:ani11123469. [PMID: 34944246 PMCID: PMC8698132 DOI: 10.3390/ani11123469] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2021] [Revised: 11/24/2021] [Accepted: 12/02/2021] [Indexed: 11/16/2022] Open
Abstract
Huaxi cattle, a specialized beef cattle breed in China, has the characteristics of fast growth, high slaughter rate, and net meat rate, good reproductive performance, strong stress resistance, and wide adaptability. In this study, we evaluated the genetic diversity, population structure, and genetic relationships of Huaxi cattle and its ancestor populations at the genome-wide level, as well as detecting the selection signatures of Huaxi cattle. Principal component analysis (PCA) and phylogenetic analysis revealed that Huaxi cattle were obviously separated from other cattle populations. The admixture analysis showed that Huaxi cattle has distinct genetic structures among all populations at K = 4. It can be concluded that Huaxi cattle has formed its own unique genetic features. Using integrated haplotype score (iHS) and composite likelihood ratio (CLR) methods, we identified 143 and 199 potentially selected genes in Huaxi cattle, respectively, among which nine selected genes (KCNK1, PDLIM5, CPXM2, CAPN14, MIR2285D, MYOF, PKDCC, FOXN3, and EHD3) related to ion binding, muscle growth and differentiation, and immunity were detected by both methods. Our study sheds light on the unique genetic feature and phylogenetic relationship of Huaxi cattle, provides a basis for the genetic mechanism analysis of important economic traits, and guides further intensive breeding improvement of Huaxi cattle.
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Affiliation(s)
- Jun Ma
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (J.M.); (X.G.); (J.L.); (H.G.); (Z.W.); (L.Z.); (L.X.); (H.G.); (H.L.); (Y.W.); (B.Z.); (W.C.)
| | - Xue Gao
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (J.M.); (X.G.); (J.L.); (H.G.); (Z.W.); (L.Z.); (L.X.); (H.G.); (H.L.); (Y.W.); (B.Z.); (W.C.)
| | - Junya Li
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (J.M.); (X.G.); (J.L.); (H.G.); (Z.W.); (L.Z.); (L.X.); (H.G.); (H.L.); (Y.W.); (B.Z.); (W.C.)
| | - Huijiang Gao
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (J.M.); (X.G.); (J.L.); (H.G.); (Z.W.); (L.Z.); (L.X.); (H.G.); (H.L.); (Y.W.); (B.Z.); (W.C.)
| | - Zezhao Wang
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (J.M.); (X.G.); (J.L.); (H.G.); (Z.W.); (L.Z.); (L.X.); (H.G.); (H.L.); (Y.W.); (B.Z.); (W.C.)
| | - Lupei Zhang
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (J.M.); (X.G.); (J.L.); (H.G.); (Z.W.); (L.Z.); (L.X.); (H.G.); (H.L.); (Y.W.); (B.Z.); (W.C.)
| | - Lingyang Xu
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (J.M.); (X.G.); (J.L.); (H.G.); (Z.W.); (L.Z.); (L.X.); (H.G.); (H.L.); (Y.W.); (B.Z.); (W.C.)
| | - Han Gao
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (J.M.); (X.G.); (J.L.); (H.G.); (Z.W.); (L.Z.); (L.X.); (H.G.); (H.L.); (Y.W.); (B.Z.); (W.C.)
| | - Hongwei Li
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (J.M.); (X.G.); (J.L.); (H.G.); (Z.W.); (L.Z.); (L.X.); (H.G.); (H.L.); (Y.W.); (B.Z.); (W.C.)
| | - Yahui Wang
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (J.M.); (X.G.); (J.L.); (H.G.); (Z.W.); (L.Z.); (L.X.); (H.G.); (H.L.); (Y.W.); (B.Z.); (W.C.)
| | - Bo Zhu
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (J.M.); (X.G.); (J.L.); (H.G.); (Z.W.); (L.Z.); (L.X.); (H.G.); (H.L.); (Y.W.); (B.Z.); (W.C.)
| | - Wentao Cai
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (J.M.); (X.G.); (J.L.); (H.G.); (Z.W.); (L.Z.); (L.X.); (H.G.); (H.L.); (Y.W.); (B.Z.); (W.C.)
| | - Congyong Wang
- Beijing Lianyu Beef Cattle Breeding Technology Limited Company, Beijing 100193, China;
| | - Yan Chen
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (J.M.); (X.G.); (J.L.); (H.G.); (Z.W.); (L.Z.); (L.X.); (H.G.); (H.L.); (Y.W.); (B.Z.); (W.C.)
- Correspondence:
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19
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Pedrosa VB, Schenkel FS, Chen SY, Oliveira HR, Casey TM, Melka MG, Brito LF. Genomewide Association Analyses of Lactation Persistency and Milk Production Traits in Holstein Cattle Based on Imputed Whole-Genome Sequence Data. Genes (Basel) 2021; 12:genes12111830. [PMID: 34828436 PMCID: PMC8624223 DOI: 10.3390/genes12111830] [Citation(s) in RCA: 40] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2021] [Revised: 11/13/2021] [Accepted: 11/17/2021] [Indexed: 12/22/2022] Open
Abstract
Lactation persistency and milk production are among the most economically important traits in the dairy industry. In this study, we explored the association of over 6.1 million imputed whole-genome sequence variants with lactation persistency (LP), milk yield (MILK), fat yield (FAT), fat percentage (FAT%), protein yield (PROT), and protein percentage (PROT%) in North American Holstein cattle. We identified 49, 3991, 2607, 4459, 805, and 5519 SNPs significantly associated with LP, MILK, FAT, FAT%, PROT, and PROT%, respectively. Various known associations were confirmed while several novel candidate genes were also revealed, including ARHGAP35, NPAS1, TMEM160, ZC3H4, SAE1, ZMIZ1, PPIF, LDB2, ABI3, SERPINB6, and SERPINB9 for LP; NIM1K, ZNF131, GABRG1, GABRA2, DCHS1, and SPIDR for MILK; NR6A1, OLFML2A, EXT2, POLD1, GOT1, and ETV6 for FAT; DPP6, LRRC26, and the KCN gene family for FAT%; CDC14A, RTCA, HSTN, and ODAM for PROT; and HERC3, HERC5, LALBA, CCL28, and NEURL1 for PROT%. Most of these genes are involved in relevant gene ontology (GO) terms such as fatty acid homeostasis, transporter regulator activity, response to progesterone and estradiol, response to steroid hormones, and lactation. The significant genomic regions found contribute to a better understanding of the molecular mechanisms related to LP and milk production in North American Holstein cattle.
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Affiliation(s)
- Victor B. Pedrosa
- Department of Animal Sciences, Purdue University, West Lafayette, IN 47907, USA; (V.B.P.); (S.-Y.C.); (H.R.O.); (T.M.C.)
- Department of Animal Sciences, State University of Ponta Grossa, Ponta Grossa 84030-900, Brazil
| | - Flavio S. Schenkel
- Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, ON N1G2W1, Canada;
| | - Shi-Yi Chen
- Department of Animal Sciences, Purdue University, West Lafayette, IN 47907, USA; (V.B.P.); (S.-Y.C.); (H.R.O.); (T.M.C.)
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, College of Animal Science & Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Hinayah R. Oliveira
- Department of Animal Sciences, Purdue University, West Lafayette, IN 47907, USA; (V.B.P.); (S.-Y.C.); (H.R.O.); (T.M.C.)
- Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, ON N1G2W1, Canada;
| | - Theresa M. Casey
- Department of Animal Sciences, Purdue University, West Lafayette, IN 47907, USA; (V.B.P.); (S.-Y.C.); (H.R.O.); (T.M.C.)
| | - Melkaye G. Melka
- Department of Animal and Food Science, University of Wisconsin River Falls, River Falls, WI 54022, USA;
| | - Luiz F. Brito
- Department of Animal Sciences, Purdue University, West Lafayette, IN 47907, USA; (V.B.P.); (S.-Y.C.); (H.R.O.); (T.M.C.)
- Correspondence:
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20
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Rafter P, Gormley IC, Purfield D, Parnell AC, Naderi S, Berry DP. Genome-wide association analyses of carcass traits using copy number variants and raw intensity values of single nucleotide polymorphisms in cattle. BMC Genomics 2021; 22:757. [PMID: 34688258 PMCID: PMC8542340 DOI: 10.1186/s12864-021-08075-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2021] [Accepted: 10/07/2021] [Indexed: 12/03/2022] Open
Abstract
BACKGROUND The carcass value of cattle is a function of carcass weight and quality. Given the economic importance of carcass merit to producers, it is routinely included in beef breeding objectives. A detailed understanding of the genetic variants that contribute to carcass merit is useful to maximize the efficiency of breeding for improved carcass merit. The objectives of the present study were two-fold: firstly, to perform genome-wide association analyses of carcass weight, carcass conformation, and carcass fat using copy number variant (CNV) data in a population of 923 Holstein-Friesian, 945 Charolais, and 974 Limousin bulls; and secondly to perform separate association analyses of carcass traits on the same population of cattle using the Log R ratio (LRR) values of 712,555 single nucleotide polymorphisms (SNPs). The LRR value of a SNP is a measure of the signal intensity of the SNP generated during the genotyping process. RESULTS A total of 13,969, 3,954, and 2,805 detected CNVs were tested for association with the three carcass traits for the Holstein-Friesian, Charolais, and Limousin, respectively. The copy number of 16 CNVs and the LRR of 34 SNPs were associated with at least one of the three carcass traits in at least one of the three cattle breeds. With the exception of three SNPs, none of the quantitative trait loci detected in the CNV association analyses or the SNP LRR association analyses were also detected using traditional association analyses based on SNP allele counts. Many of the CNVs and SNPs associated with the carcass traits were located near genes related to the structure and function of the spliceosome and the ribosome; in particular, U6 which encodes a spliceosomal subunit and 5S rRNA which encodes a ribosomal subunit. CONCLUSIONS The present study demonstrates that CNV data and SNP LRR data can be used to detect genomic regions associated with carcass traits in cattle providing information on quantitative trait loci over and above those detected using just SNP allele counts, as is the approach typically employed in genome-wide association analyses.
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Affiliation(s)
- Pierce Rafter
- Animal & Grassland Research and Innovation Centre, Teagasc, Moorepark, Cork, Fermoy, Ireland
- School of Mathematics and Statistics, University College Dublin, Belfield, Dublin 4, Ireland
| | - Isobel Claire Gormley
- School of Mathematics and Statistics, University College Dublin, Belfield, Dublin 4, Ireland
| | - Deirdre Purfield
- Department of Biological Sciences, Munster Technological University Institute, Cork, Bishopstown, Ireland
| | - Andrew C Parnell
- Hamilton Institute, Insight Centre for Data Analytics, Maynooth University, Kildare, Ireland
| | - Saeid Naderi
- Irish Cattle Breeding Federation, Cork, Bandon, Ireland
| | - Donagh P Berry
- Animal & Grassland Research and Innovation Centre, Teagasc, Moorepark, Cork, Fermoy, Ireland.
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21
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Denoyelle L, de Villemereuil P, Boyer F, Khelifi M, Gaffet C, Alberto F, Benjelloun B, Pompanon F. Genetic Variations and Differential DNA Methylation to Face Contrasted Climates in Small Ruminants: An Analysis on Traditionally-Managed Sheep and Goats. Front Genet 2021; 12:745284. [PMID: 34650601 PMCID: PMC8508783 DOI: 10.3389/fgene.2021.745284] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2021] [Accepted: 09/02/2021] [Indexed: 12/13/2022] Open
Abstract
The way in which living organisms mobilize a combination of long-term adaptive mechanisms and short-term phenotypic plasticity to face environmental variations is still largely unknown. In the context of climate change, understanding the genetic and epigenetic bases for adaptation and plasticity is a major stake for preserving genomic resources and the resilience capacity of livestock populations. We characterized both epigenetic and genetic variations by contrasting 22 sheep and 21 goats from both sides of a climate gradient, focusing on free-ranging populations from Morocco. We produced for each individual Whole-Genome Sequence at 12X coverage and MeDIP-Seq data, to identify regions under selection and those differentially methylated. For both species, the analysis of genetic differences (FST) along the genome between animals from localities with high vs. low temperature annual variations detected candidate genes under selection in relation to environmental perception (5 genes), immunity (4 genes), reproduction (8 genes) and production (11 genes). Moreover, we found for each species one differentially methylated gene, namely AGPTA4 in goat and SLIT3 in sheep, which were both related, among other functions, to milk production and muscle development. In both sheep and goats, the comparison between genomic regions impacted by genetic and epigenetic variations suggests that climatic variations impacted similar biological pathways but different genes.
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Affiliation(s)
- Laure Denoyelle
- Univ. Grenoble Alpes, Univ. Savoie Mont Blanc, CNRS, LECA, Grenoble, France.,GenPhySE, Université de Toulouse, INRAE, ENVT, Castanet Tolosan, France
| | - Pierre de Villemereuil
- Institut de Systématique, Évolution, Biodiversité (ISYEB), École Pratique des Hautes Études
- PSL, MNHN, CNRS, SU, UA, Paris, France
| | - Frédéric Boyer
- Univ. Grenoble Alpes, Univ. Savoie Mont Blanc, CNRS, LECA, Grenoble, France
| | - Meidhi Khelifi
- Univ. Grenoble Alpes, Univ. Savoie Mont Blanc, CNRS, LECA, Grenoble, France
| | - Clément Gaffet
- Univ. Grenoble Alpes, Univ. Savoie Mont Blanc, CNRS, LECA, Grenoble, France
| | - Florian Alberto
- Univ. Grenoble Alpes, Univ. Savoie Mont Blanc, CNRS, LECA, Grenoble, France
| | - Badr Benjelloun
- Univ. Grenoble Alpes, Univ. Savoie Mont Blanc, CNRS, LECA, Grenoble, France.,Institut National de la Recherche Agronomique Maroc (INRA-Maroc), Centre Régional de Beni Mellal, Beni Mellal, Morocco
| | - François Pompanon
- Univ. Grenoble Alpes, Univ. Savoie Mont Blanc, CNRS, LECA, Grenoble, France
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22
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Martinez-Castillero M, Then C, Altarriba J, Srihi H, López-Carbonell D, Díaz C, Martinez P, Hermida M, Varona L. Detection of Genomic Regions with Pleiotropic Effects for Growth and Carcass Quality Traits in the Rubia Gallega Cattle Breed. Animals (Basel) 2021; 11:ani11061682. [PMID: 34200089 PMCID: PMC8227173 DOI: 10.3390/ani11061682] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2021] [Revised: 05/25/2021] [Accepted: 06/02/2021] [Indexed: 11/16/2022] Open
Abstract
Simple Summary The breeding scheme in the Rubia Gallega cattle population is based upon traits measured in farms and slaughterhouses. We have developed a ssGWAS by backsolving the SNP effects after implementing a ssGBLUP. The results showed an apparent heterogeneity of the additive genetic variance across the genome. Some of the genomic regions explaining the most of this additive variance were shared across traits, indicating the presence of pleiotropic effects, which were reflected in their genetic correlations. Abstract The breeding scheme in the Rubia Gallega cattle population is based upon traits measured in farms and slaughterhouses. In recent years, genomic evaluation has been implemented by using a ssGBLUP (single-step Genomic Best Linear Unbiased Prediction). This procedure can reparameterized to perform ssGWAS (single-step Genome Wide Association Studies) by backsolving the SNP (single nucleotide polymorphisms) effects. Therefore, the objective of this study was to identify genomic regions associated with the genetic variability in growth and carcass quality traits. We implemented a ssGBLUP by using a database that included records for Birth Weight (BW-327,350 records-), Weaning Weight (WW-83,818-), Cold Carcass Weight (CCW-91,621-), Fatness (FAT-91,475-) and Conformation (CON-91,609-). The pedigree included 464,373 individuals, 2449 of which were genotyped. After a process of filtering, we ended up using 43,211 SNP markers. We used the GBLUP and SNPBLUP model equivalences to obtain the effects of the SNPs and then calculated the percentage of variance explained by the regions of the genome between 1 Mb. We identified 7 regions of the genome for CCW; 8 regions for BW, WW, FAT and 9 regions for CON, which explained the percentage of variance above 0.5%. Furthermore, a number of the genome regions had pleiotropic effects, located at: BTA1 (131–132 Mb), BTA2 (1–11 Mb), BTA3 (32–33 Mb), BTA6 (36–38 Mb), BTA16 (24–26 Mb), and BTA 21 (56–57 Mb). These regions contain, amongst others, the following candidate genes: NCK1, MSTN, KCNA3, LCORL, NCAPG, and RIN3.
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Affiliation(s)
- Maria Martinez-Castillero
- Instituto Agroalimentario de Aragón (IA2), Universidad de Zaragoza, 50013 Zaragoza, Spain; (C.T.); (J.A.); (H.S.); (D.L.-C.); (L.V.)
- Correspondence:
| | - Carlos Then
- Instituto Agroalimentario de Aragón (IA2), Universidad de Zaragoza, 50013 Zaragoza, Spain; (C.T.); (J.A.); (H.S.); (D.L.-C.); (L.V.)
| | - Juan Altarriba
- Instituto Agroalimentario de Aragón (IA2), Universidad de Zaragoza, 50013 Zaragoza, Spain; (C.T.); (J.A.); (H.S.); (D.L.-C.); (L.V.)
| | - Houssemeddine Srihi
- Instituto Agroalimentario de Aragón (IA2), Universidad de Zaragoza, 50013 Zaragoza, Spain; (C.T.); (J.A.); (H.S.); (D.L.-C.); (L.V.)
| | - David López-Carbonell
- Instituto Agroalimentario de Aragón (IA2), Universidad de Zaragoza, 50013 Zaragoza, Spain; (C.T.); (J.A.); (H.S.); (D.L.-C.); (L.V.)
| | - Clara Díaz
- Instituto Nacional de Investigación y Tecnología Agraria (INIA), 28040 Madrid, Spain;
| | - Paulino Martinez
- Facultad de Veterinaria, Universidad de Santiago de Compostela, 27002 Lugo, Spain; (P.M.); (M.H.)
| | - Miguel Hermida
- Facultad de Veterinaria, Universidad de Santiago de Compostela, 27002 Lugo, Spain; (P.M.); (M.H.)
| | - Luis Varona
- Instituto Agroalimentario de Aragón (IA2), Universidad de Zaragoza, 50013 Zaragoza, Spain; (C.T.); (J.A.); (H.S.); (D.L.-C.); (L.V.)
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Silva R, Espigolan R, Berton M, Stafuzza N, Santos F, Negreiros M, Schuchmann R, Rodriguez J, Lôbo R, Banchero G, Pereira A, Bergmann J, Baldi F. Genetic parameters and genomic regions associated with calving ease in primiparous Nellore heifers. Livest Sci 2020. [DOI: 10.1016/j.livsci.2020.104183] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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24
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Hiltpold M, Niu G, Kadri NK, Crysnanto D, Fang ZH, Spengeler M, Schmitz-Hsu F, Fuerst C, Schwarzenbacher H, Seefried FR, Seehusen F, Witschi U, Schnieke A, Fries R, Bollwein H, Flisikowski K, Pausch H. Activation of cryptic splicing in bovine WDR19 is associated with reduced semen quality and male fertility. PLoS Genet 2020; 16:e1008804. [PMID: 32407316 PMCID: PMC7252675 DOI: 10.1371/journal.pgen.1008804] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2020] [Revised: 05/27/2020] [Accepted: 04/28/2020] [Indexed: 12/30/2022] Open
Abstract
Cattle are ideally suited to investigate the genetics of male reproduction, because semen quality and fertility are recorded for all ejaculates of artificial insemination bulls. We analysed 26,090 ejaculates of 794 Brown Swiss bulls to assess ejaculate volume, sperm concentration, sperm motility, sperm head and tail anomalies and insemination success. The heritability of the six semen traits was between 0 and 0.26. Genome-wide association testing on 607,511 SNPs revealed a QTL on bovine chromosome 6 that was associated with sperm motility (P = 2.5 x 10−27), head (P = 2.0 x 10−44) and tail anomalies (P = 7.2 x 10−49) and insemination success (P = 9.9 x 10−13). The QTL harbors a recessive allele that compromises semen quality and male fertility. We replicated the effect of the QTL on fertility (P = 7.1 x 10−32) in an independent cohort of 2481 Brown Swiss bulls. The analysis of whole-genome sequencing data revealed that a synonymous variant (BTA6:58373887C>T, rs474302732) in WDR19 encoding WD repeat-containing protein 19 was in linkage disequilibrium with the fertility-associated haplotype. WD repeat-containing protein 19 is a constituent of the intraflagellar transport complex that is essential for the physiological function of motile cilia and flagella. Bioinformatic and transcription analyses revealed that the BTA6:58373887 T-allele activates a cryptic exonic splice site that eliminates three evolutionarily conserved amino acids from WDR19. Western blot analysis demonstrated that the BTA6:58373887 T-allele decreases protein expression. We make the remarkable observation that, in spite of negative effects on semen quality and bull fertility, the BTA6:58373887 T-allele has a frequency of 24% in the Brown Swiss population. Our findings are the first to uncover a variant that is associated with quantitative variation in semen quality and male fertility in cattle. In cattle farming, artificial insemination is the most common method of breeding. To ensure high fertilization rates, ejaculate quality and insemination success are closely monitored in artificial insemination bulls. We analyse semen quality, insemination success and microarray-called genotypes at more than 600,000 genome-wide SNP markers of 794 bulls to identify a recessive allele that compromises semen quality. We take advantage of whole-genome sequencing to pinpoint a variant in the coding sequence of WDR19 encoding WD repeat-containing protein 19 that activates a novel exonic splice site. Our results indicate that cryptic splicing in WDR19 is associated with reduced male reproductive performance. This is the first report of a variant that contributes to quantitative variation in bovine semen quality.
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Affiliation(s)
| | - Guanglin Niu
- Livestock Biotechnology, TU München, Freising, Germany
| | | | | | - Zih-Hua Fang
- Animal Genomics, ETH Zürich, Lindau, Switzerland
| | | | | | | | | | | | - Frauke Seehusen
- Institute of Veterinary Pathology, University of Zurich, Zurich, Switzerland
| | | | | | - Ruedi Fries
- Animal Breeding, TU München, Freising, Germany
| | - Heinrich Bollwein
- Clinic of Reproductive Medicine, University of Zurich, Zürich, Switzerland
| | | | - Hubert Pausch
- Animal Genomics, ETH Zürich, Lindau, Switzerland
- * E-mail:
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25
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Hlongwane NL, Hadebe K, Soma P, Dzomba EF, Muchadeyi FC. Genome Wide Assessment of Genetic Variation and Population Distinctiveness of the Pig Family in South Africa. Front Genet 2020; 11:344. [PMID: 32457791 PMCID: PMC7221027 DOI: 10.3389/fgene.2020.00344] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2018] [Accepted: 03/23/2020] [Indexed: 12/12/2022] Open
Abstract
Genetic diversity is of great importance and a prerequisite for genetic improvement and conservation programs in pigs and other livestock populations. The present study provides a genome wide analysis of the genetic variability and population structure of pig populations from different production systems in South Africa relative to global populations. A total of 234 pigs sampled in South Africa and consisting of village (n = 91), commercial (n = 60), indigenous (n = 40), Asian (n = 5) and wild (n = 38) populations were genotyped using Porcine SNP60K BeadChip. In addition, 389 genotypes representing village and commercial pigs from America, Europe, and Asia were accessed from a previous study and used to compare population clustering and relationships of South African pigs with global populations. Moderate heterozygosity levels, ranging from 0.204 for Warthogs to 0.371 for village pigs sampled from Capricorn municipality in Eastern Cape province of South Africa were observed. Principal Component Analysis of the South African pigs resulted in four distinct clusters of (i) Duroc; (ii) Vietnamese; (iii) Bush pig and Warthog and (iv) a cluster with the rest of the commercial (SA Large White and Landrace), village, Wild Boar and indigenous breeds of Koelbroek and Windsnyer. The clustering demonstrated alignment with genetic similarities, geographic location and production systems. The PCA with the global populations also resulted in four clusters that where populated with (i) all the village populations, wild boars, SA indigenous and the large white and landraces; (ii) Durocs (iii) Chinese and Vietnamese pigs and (iv) Warthog and Bush pig. K = 10 (The number of population units) was the most probable ADMIXTURE based clustering, which grouped animals according to their populations with the exception of the village pigs that showed presence of admixture. AMOVA reported 19.92%-98.62% of the genetic variation to be within populations. Sub structuring was observed between South African commercial populations as well as between Indigenous and commercial breeds. Population pairwise F ST analysis showed genetic differentiation (P ≤ 0.05) between the village, commercial and wild populations. A per marker per population pairwise F ST analysis revealed SNPs associated with QTLs for traits such as meat quality, cytoskeletal and muscle development, glucose metabolism processes and growth factors between both domestic populations as well as between wild and domestic breeds. Overall, the study provided a baseline understanding of porcine diversity and an important foundation for porcine genomics of South African populations.
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Affiliation(s)
- Nompilo Lucia Hlongwane
- Biotechnology Platform, Agricultural Research Council, Onderstepoort, South Africa
- Discipline of Genetics, School of Life Sciences, University of KwaZulu-Natal, Pietermartizburg, South Africa
| | - Khanyisile Hadebe
- Biotechnology Platform, Agricultural Research Council, Onderstepoort, South Africa
| | - Pranisha Soma
- Animal Production Institute, Agricultural Research Council, Irene, South Africa
| | - Edgar Farai Dzomba
- Discipline of Genetics, School of Life Sciences, University of KwaZulu-Natal, Pietermartizburg, South Africa
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