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Ren J, Gao Z, Lu Y, Li M, Hong J, Wu J, Wu D, Deng W, Xi D, Chong Y. Application of GWAS and mGWAS in Livestock and Poultry Breeding. Animals (Basel) 2024; 14:2382. [PMID: 39199916 PMCID: PMC11350712 DOI: 10.3390/ani14162382] [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: 06/18/2024] [Revised: 08/04/2024] [Accepted: 08/15/2024] [Indexed: 09/01/2024] Open
Abstract
In recent years, genome-wide association studies (GWAS) and metabolome genome-wide association studies (mGWAS) have emerged as crucial methods for investigating complex traits in animals and plants. These have played pivotal roles in research on livestock and poultry breeding, facilitating a deeper understanding of genetic diversity, the relationship between genes, and genetic bases in livestock and poultry. This article provides a review of the applications of GWAS and mGWAS in animal genetic breeding, aiming to offer reference and inspiration for relevant researchers, promote innovation in animal genetic improvement and breeding methods, and contribute to the sustainable development of animal husbandry.
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Affiliation(s)
- Jing Ren
- Key Laboratory of Animal Genetics, Breeding and Reproduction in the Plateau Mountainous Region, Ministry of Education, Guizhou University, Guiyang 550025, China;
- Yunnan Provincial Key Laboratory of Animal Nutrition and Feed, Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China; (Z.G.); : (M.L.); (J.H.); (J.W.); (D.W.); (W.D.)
| | - Zhendong Gao
- Yunnan Provincial Key Laboratory of Animal Nutrition and Feed, Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China; (Z.G.); : (M.L.); (J.H.); (J.W.); (D.W.); (W.D.)
| | - Ying Lu
- Yunnan Provincial Key Laboratory of Animal Nutrition and Feed, Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China; (Z.G.); : (M.L.); (J.H.); (J.W.); (D.W.); (W.D.)
| | - Mengfei Li
- Yunnan Provincial Key Laboratory of Animal Nutrition and Feed, Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China; (Z.G.); : (M.L.); (J.H.); (J.W.); (D.W.); (W.D.)
| | - Jieyun Hong
- Yunnan Provincial Key Laboratory of Animal Nutrition and Feed, Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China; (Z.G.); : (M.L.); (J.H.); (J.W.); (D.W.); (W.D.)
| | - Jiao Wu
- Yunnan Provincial Key Laboratory of Animal Nutrition and Feed, Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China; (Z.G.); : (M.L.); (J.H.); (J.W.); (D.W.); (W.D.)
| | - Dongwang Wu
- Yunnan Provincial Key Laboratory of Animal Nutrition and Feed, Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China; (Z.G.); : (M.L.); (J.H.); (J.W.); (D.W.); (W.D.)
| | - Weidong Deng
- Yunnan Provincial Key Laboratory of Animal Nutrition and Feed, Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China; (Z.G.); : (M.L.); (J.H.); (J.W.); (D.W.); (W.D.)
| | - Dongmei Xi
- Yunnan Provincial Key Laboratory of Animal Nutrition and Feed, Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China; (Z.G.); : (M.L.); (J.H.); (J.W.); (D.W.); (W.D.)
| | - Yuqing Chong
- Yunnan Provincial Key Laboratory of Animal Nutrition and Feed, Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China; (Z.G.); : (M.L.); (J.H.); (J.W.); (D.W.); (W.D.)
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Forutan M, Engle BN, Chamberlain AJ, Ross EM, Nguyen LT, D'Occhio MJ, Snr AC, Kho EA, Fordyce G, Speight S, Goddard ME, Hayes BJ. Genome-wide association and expression quantitative trait loci in cattle reveals common genes regulating mammalian fertility. Commun Biol 2024; 7:724. [PMID: 38866948 PMCID: PMC11169601 DOI: 10.1038/s42003-024-06403-2] [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: 04/20/2023] [Accepted: 05/31/2024] [Indexed: 06/14/2024] Open
Abstract
Most genetic variants associated with fertility in mammals fall in non-coding regions of the genome and it is unclear how these variants affect fertility. Here we use genome-wide association summary statistics for Heifer puberty (pubertal or not at 600 days) from 27,707 Bos indicus, Bos taurus and crossbred cattle; multi-trait GWAS signals from 2119 indicine cattle for four fertility traits, including days to calving, age at first calving, pregnancy status, and foetus age in weeks (assessed by rectal palpation of the foetus); and expression quantitative trait locus for whole blood from 489 indicine cattle, to identify 87 putatively functional genes affecting cattle fertility. Our analysis reveals a significant overlap between the set of cattle and previously reported human fertility-related genes, impling the existence of a shared pool of genes that regulate fertility in mammals. These findings are crucial for developing approaches to improve fertility in cattle and potentially other mammals.
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Affiliation(s)
- Mehrnush Forutan
- Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, St Lucia, QLD, Australia.
| | - Bailey N Engle
- Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, St Lucia, QLD, Australia
- USDA,ARS, U.S. Meat Animal Research Center, Clay Center, NE, 68933, USA
| | - Amanda J Chamberlain
- Agriculture Victoria, Centre for AgriBiosciences, Bundoora, VIC, Australia
- School of Applied Systems Biology, La Trobe University, Bundoora, VIC, 3083, Australia
| | - Elizabeth M Ross
- Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, St Lucia, QLD, Australia
| | - Loan T Nguyen
- Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, St Lucia, QLD, Australia
| | - Michael J D'Occhio
- School of Life and Environmental Sciences, Faculty of Science, The University of Sydney, Sydney, NSW, Australia
| | - Alf Collins Snr
- Collins Belah Valley Brahman Stud, Marlborough, 4705, QLD, Australia
| | - Elise A Kho
- Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, St Lucia, QLD, Australia
| | - Geoffry Fordyce
- Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, St Lucia, QLD, Australia
| | | | - Michael E Goddard
- Agriculture Victoria, Centre for AgriBiosciences, Bundoora, VIC, Australia
- University of Melbourne, Melbourne, Australia
| | - Ben J Hayes
- Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, St Lucia, QLD, Australia
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Duan Y, Su P, Gu Y, Lv X, Cao X, Wang S, Yuan Z, Sun W. A Study of the Resistance of Hu Sheep Lambs to Escherichia coli F17 Based on Whole Genome Sequencing. Animals (Basel) 2024; 14:161. [PMID: 38200892 PMCID: PMC10778179 DOI: 10.3390/ani14010161] [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: 11/20/2023] [Revised: 12/27/2023] [Accepted: 12/29/2023] [Indexed: 01/12/2024] Open
Abstract
This study aims to analyze the whole genome sequencing of E. coli F17 in antagonistic and susceptible Hu sheep lambs. The objective is to investigate the critical mutation loci in sheep and understand the genetic mechanism of sheep resistance to E. coli F17 at the genome level. Antagonist and susceptible venous blood samples were collected from Hu sheep lambs for whole genome sequencing and whole genome association analysis. A total of 466 genes with significant SNPs (p < 1.0 × 10-3) were found. GO and KEGG enrichment analysis and protein interaction network analysis were performed on these genes, and preliminary investigations showed that SNPs on CTNNB1, CDH8, APOD, HCLS1, Tet2, MTSS1 and YAP1 genes may be associated with the antagonism and susceptibility of Hu sheep lambs to E. coli F17. There are still some shortcomings that have not been explored via in vivo and in vitro functional experiments of the candidate genes, which will be our next research work. This study provides genetic loci and candidate genes for resistance of Hu sheep lambs to E. coli F17 infection, and provides a genetic basis for breeding disease-resistant sheep.
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Affiliation(s)
- Yanjun Duan
- College of Veterinary Medicine, Yangzhou University, Yangzhou 225009, China;
| | - Pengwei Su
- College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China; (P.S.); (Y.G.); (S.W.)
| | - Yifei Gu
- College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China; (P.S.); (Y.G.); (S.W.)
| | - Xiaoyang Lv
- Joint International Research Laboratory of Agriculture and Agri-Product Safety of Ministry of Education of China, Yangzhou University, Yangzhou 225009, China; (X.L.); (X.C.); (Z.Y.)
- International Joint Research Laboratory in Universities of Jiangsu Province of China for Domestic Animal Germplasm Resources and Genetic Improvement, Yangzhou University, Yangzhou 225009, China
| | - Xiukai Cao
- Joint International Research Laboratory of Agriculture and Agri-Product Safety of Ministry of Education of China, Yangzhou University, Yangzhou 225009, China; (X.L.); (X.C.); (Z.Y.)
- International Joint Research Laboratory in Universities of Jiangsu Province of China for Domestic Animal Germplasm Resources and Genetic Improvement, Yangzhou University, Yangzhou 225009, China
| | - Shanhe Wang
- College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China; (P.S.); (Y.G.); (S.W.)
- International Joint Research Laboratory in Universities of Jiangsu Province of China for Domestic Animal Germplasm Resources and Genetic Improvement, Yangzhou University, Yangzhou 225009, China
| | - Zehu Yuan
- Joint International Research Laboratory of Agriculture and Agri-Product Safety of Ministry of Education of China, Yangzhou University, Yangzhou 225009, China; (X.L.); (X.C.); (Z.Y.)
- International Joint Research Laboratory in Universities of Jiangsu Province of China for Domestic Animal Germplasm Resources and Genetic Improvement, Yangzhou University, Yangzhou 225009, China
| | - Wei Sun
- College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China; (P.S.); (Y.G.); (S.W.)
- Joint International Research Laboratory of Agriculture and Agri-Product Safety of Ministry of Education of China, Yangzhou University, Yangzhou 225009, China; (X.L.); (X.C.); (Z.Y.)
- International Joint Research Laboratory in Universities of Jiangsu Province of China for Domestic Animal Germplasm Resources and Genetic Improvement, Yangzhou University, Yangzhou 225009, China
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More M, Veli E, Cruz A, Gutiérrez JP, Gutiérrez G, Ponce de León FA. Genome-Wide Association Study of Fiber Diameter in Alpacas. Animals (Basel) 2023; 13:3316. [PMID: 37958071 PMCID: PMC10648856 DOI: 10.3390/ani13213316] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2023] [Revised: 10/13/2023] [Accepted: 10/20/2023] [Indexed: 11/15/2023] Open
Abstract
The aim of this study was the identification of candidate genomic regions associated with fiber diameter in alpacas. DNA samples were collected from 1011 female Huacaya alpacas from two geographical Andean regions in Peru (Pasco and Puno), and three alpaca farms within each region. The samples were genotyped using an Affymetrix Custom Alpaca genotyping array containing 76,508 SNPs. After the quality controls, 960 samples and 51,742 SNPs were retained. Three association study methodologies were performed. The GWAS based on a linear model allowed us to identify 11 and 35 SNPs (-log10(p-values) > 4) using information on all alpacas and alpacas with extreme values of fiber diameter, respectively. The haplotype and marker analysis method allowed us to identify nine haplotypes with standardized haplotype heritability higher than six standard deviations. The selection signatures based on cross-population extended haplotype homozygosity (XP-EHH) allowed us to identify 180 SNPs with XP-EHH values greater than |3|. Four candidate regions with adjacent SNPs identified via two association methods of analysis are located on VPA6, VPA9, VPA29 and one chromosomally unassigned scaffold. This study represents the first analysis of alpaca whole genome association with fiber diameter, using a recently assembled alpaca SNP microarray.
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Affiliation(s)
- Manuel More
- Facultad de Agronomía y Zootecnia, Universidad Nacional de San Antonio Abad del Cusco, Cusco 08006, Peru;
- Facultad de Zootecnia, Universidad Nacional Agraria La Molina, Lima 15024, Peru; (A.C.); (F.A.P.d.L.)
| | - Eudosio Veli
- Centro Experimental La Molina, Dirección de Recursos Genéticos y Biotecnología, Instituto Nacional de Innovación Agraria (INIA), Lima 15024, Peru;
| | - Alan Cruz
- Facultad de Zootecnia, Universidad Nacional Agraria La Molina, Lima 15024, Peru; (A.C.); (F.A.P.d.L.)
- Estación Científica de Pacomarca, Inca Tops S.A., Arequipa 04007, Peru
| | - Juan Pablo Gutiérrez
- Departamento de Producción Animal, Facultad de Veterinaria, Universidad Complutense de Madrid, 28040 Madrid, Spain;
| | - Gustavo Gutiérrez
- Facultad de Zootecnia, Universidad Nacional Agraria La Molina, Lima 15024, Peru; (A.C.); (F.A.P.d.L.)
- Instituto de Investigación de Bioquímica y Biología Molecular, Universidad Nacional Agraria La Molina, Lima 15024, Peru
| | - F. Abel Ponce de León
- Facultad de Zootecnia, Universidad Nacional Agraria La Molina, Lima 15024, Peru; (A.C.); (F.A.P.d.L.)
- Department of Animal Science, University of Minnesota, Minneapolis, MN 55108, USA
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Xie S, Isaacs K, Becker G, Murdoch BM. A computational framework for improving genetic variants identification from 5,061 sheep sequencing data. J Anim Sci Biotechnol 2023; 14:127. [PMID: 37779189 PMCID: PMC10544426 DOI: 10.1186/s40104-023-00923-3] [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: 03/25/2023] [Accepted: 08/01/2023] [Indexed: 10/03/2023] Open
Abstract
BACKGROUND Pan-genomics is a recently emerging strategy that can be utilized to provide a more comprehensive characterization of genetic variation. Joint calling is routinely used to combine identified variants across multiple related samples. However, the improvement of variants identification using the mutual support information from multiple samples remains quite limited for population-scale genotyping. RESULTS In this study, we developed a computational framework for joint calling genetic variants from 5,061 sheep by incorporating the sequencing error and optimizing mutual support information from multiple samples' data. The variants were accurately identified from multiple samples by using four steps: (1) Probabilities of variants from two widely used algorithms, GATK and Freebayes, were calculated by Poisson model incorporating base sequencing error potential; (2) The variants with high mapping quality or consistently identified from at least two samples by GATK and Freebayes were used to construct the raw high-confidence identification (rHID) variants database; (3) The high confidence variants identified in single sample were ordered by probability value and controlled by false discovery rate (FDR) using rHID database; (4) To avoid the elimination of potentially true variants from rHID database, the variants that failed FDR were reexamined to rescued potential true variants and ensured high accurate identification variants. The results indicated that the percent of concordant SNPs and Indels from Freebayes and GATK after our new method were significantly improved 12%-32% compared with raw variants and advantageously found low frequency variants of individual sheep involved several traits including nipples number (GPC5), scrapie pathology (PAPSS2), seasonal reproduction and litter size (GRM1), coat color (RAB27A), and lentivirus susceptibility (TMEM154). CONCLUSION The new method used the computational strategy to reduce the number of false positives, and simultaneously improve the identification of genetic variants. This strategy did not incur any extra cost by using any additional samples or sequencing data information and advantageously identified rare variants which can be important for practical applications of animal breeding.
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Affiliation(s)
- Shangqian Xie
- Department of Animal, Veterinary & Food Sciences, University of Idaho, Moscow, ID, USA
| | | | - Gabrielle Becker
- Department of Animal, Veterinary & Food Sciences, University of Idaho, Moscow, ID, USA
| | - Brenda M Murdoch
- Department of Animal, Veterinary & Food Sciences, University of Idaho, Moscow, ID, USA.
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Ceccobelli S, Landi V, Senczuk G, Mastrangelo S, Sardina MT, Ben-Jemaa S, Persichilli C, Karsli T, Bâlteanu VA, Raschia MA, Poli MA, Ciappesoni G, Muchadeyi FC, Dzomba EF, Kunene NW, Lühken G, Deniskova TE, Dotsev AV, Zinovieva NA, Zsolnai A, Anton I, Kusza S, Carolino N, Santos-Silva F, Kawęcka A, Świątek M, Niżnikowski R, Špehar M, Anaya G, Granero A, Perloiro T, Cardoso P, Grande S, de Los Santos BL, Danchin-Burge C, Pasquini M, Martínez Martínez A, Delgado Bermejo JV, Lasagna E, Ciani E, Sarti FM, Pilla F. A comprehensive analysis of the genetic diversity and environmental adaptability in worldwide Merino and Merino-derived sheep breeds. Genet Sel Evol 2023; 55:24. [PMID: 37013467 PMCID: PMC10069132 DOI: 10.1186/s12711-023-00797-z] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Accepted: 03/24/2023] [Indexed: 04/05/2023] Open
Abstract
BACKGROUND To enhance and extend the knowledge about the global historical and phylogenetic relationships between Merino and Merino-derived breeds, 19 populations were genotyped with the OvineSNP50 BeadChip specifically for this study, while an additional 23 populations from the publicly available genotypes were retrieved. Three complementary statistical tests, Rsb (extended haplotype homozygosity between-populations), XP-EHH (cross-population extended haplotype homozygosity), and runs of homozygosity (ROH) islands were applied to identify genomic variants with potential impact on the adaptability of Merino genetic type in two contrasting climate zones. RESULTS The results indicate that a large part of the Merino's genetic relatedness and admixture patterns are explained by their genetic background and/or geographic origin, followed by local admixture. Multi-dimensional scaling, Neighbor-Net, Admixture, and TREEMIX analyses consistently provided evidence of the role of Australian, Rambouillet and German strains in the extensive gene introgression into the other Merino and Merino-derived breeds. The close relationship between Iberian Merinos and other South-western European breeds is consistent with the Iberian origin of the Merino genetic type, with traces from previous contributions of other Mediterranean stocks. Using Rsb and XP-EHH approaches, signatures of selection were detected spanning four genomic regions located on Ovis aries chromosomes (OAR) 1, 6 and 16, whereas two genomic regions on OAR6, that partially overlapped with the previous ones, were highlighted by ROH islands. Overall, the three approaches identified 106 candidate genes putatively under selection. Among them, genes related to immune response were identified via the gene interaction network. In addition, several candidate genes were found, such as LEKR1, LCORL, GHR, RBPJ, BMPR1B, PPARGC1A, and PRKAA1, related to morphological, growth and reproductive traits, adaptive thermogenesis, and hypoxia responses. CONCLUSIONS To the best of our knowledge, this is the first comprehensive dataset that includes most of the Merino and Merino-derived sheep breeds raised in different regions of the world. The results provide an in-depth picture of the genetic makeup of the current Merino and Merino-derived breeds, highlighting the possible selection pressures associated with the combined effect of anthropic and environmental factors. The study underlines the importance of Merino genetic types as invaluable resources of possible adaptive diversity in the context of the occurring climate changes.
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Affiliation(s)
- Simone Ceccobelli
- Department of Agricultural, Food and Environmental Sciences, Università Politecnica delle Marche, 60131, Ancona, Italy.
| | - Vincenzo Landi
- Department of Veterinary Medicine, University of Bari ''Aldo Moro", 70010, Valenzano, Italy
| | - Gabriele Senczuk
- Department of Agricultural, Environmental and Food Sciences, University of Molise, 86100, Campobasso, Italy
| | - Salvatore Mastrangelo
- Department of Agricultural, Food and Forest Sciences, University of Palermo, 90128, Palermo, Italy
| | - Maria Teresa Sardina
- Department of Agricultural, Food and Forest Sciences, University of Palermo, 90128, Palermo, Italy
| | - Slim Ben-Jemaa
- Laboratoire des Productions Animales et Fourragères, Institut National de la Recherche Agronomique de Tunisie, Université de Carthage, 2049, Ariana, Tunisia
| | - Christian Persichilli
- Department of Agricultural, Environmental and Food Sciences, University of Molise, 86100, Campobasso, Italy
| | - Taki Karsli
- Department of Animal Science, Faculty of Agriculture, Eskisehir Osmangazi University, 26040, Eskisehir, Turkey
| | - Valentin-Adrian Bâlteanu
- Laboratory of Genomics, Biodiversity, Animal Breeding and Molecular Pathology, Institute of Life Sciences, University of Agricultural Sciences and Veterinary Medicine of Cluj-Napoca, 400372, Cluj-Napoca, Romania
| | - María Agustina Raschia
- Instituto de Genética "Ewald A. Favret", Instituto Nacional de Tecnología Agropecuaria, CICVyA-CNIA, B1686, Hurlingham, Buenos Aires, Argentina
| | - Mario Andrés Poli
- Instituto de Genética "Ewald A. Favret", Instituto Nacional de Tecnología Agropecuaria, CICVyA-CNIA, B1686, Hurlingham, Buenos Aires, Argentina
| | - Gabriel Ciappesoni
- Instituto Nacional de Investigación Agropecuaria, 90200, Canelones, Uruguay
| | | | - Edgar Farai Dzomba
- Discipline of Genetics, School of Life Sciences, University of KwaZulu-Natal, 3209, Scottsville, Pietermaritzburg, South Africa
| | | | - Gesine Lühken
- Institute of Animal Breeding and Genetics, Justus Liebig University, 35390, Giessen, Germany
| | | | | | | | - Attila Zsolnai
- Department of Animal Breeding, Institute of Animal Science, Hungarian University of Agriculture and Life Sciences, Kaposvár Campus, 2053, Herceghalom, Hungary
| | - István Anton
- Department of Animal Breeding, Institute of Animal Science, Hungarian University of Agriculture and Life Sciences, Kaposvár Campus, 2053, Herceghalom, Hungary
| | - Szilvia Kusza
- Centre for Agricultural Genomics and Biotechnology, Faculty of Agricultural and Food Sciences and Environmental Management, University of Debrecen, 4032, Debrecen, Hungary
| | - Nuno Carolino
- Instituto Nacional de Investigação Agrária e Veterinária, 2005-048, Vale de Santarém, Portugal
| | - Fátima Santos-Silva
- Instituto Nacional de Investigação Agrária e Veterinária, 2005-048, Vale de Santarém, Portugal
| | - Aldona Kawęcka
- Department of Sheep and Goat Breeding, National Research Institute of Animal Production, 32-083, Kraków, Poland
| | - Marcin Świątek
- Department of Animal Breeding, Institute of Animal Sciences, Warsaw University of Life Sciences-SGGW, 02-786, Warsaw, Poland
| | - Roman Niżnikowski
- Department of Animal Breeding, Institute of Animal Sciences, Warsaw University of Life Sciences-SGGW, 02-786, Warsaw, Poland
| | - Marija Špehar
- Croatian Agency for Agriculture and Food, 10000, Zagreb, Croatia
| | - Gabriel Anaya
- MERAGEM Group, Department of Genetics, University of Córdoba, 14071, Córdoba, Spain
| | - Antonio Granero
- Asociación Nacional de Criadores de Ganado Merino (ACME), 28028, Madrid, Spain
| | - Tiago Perloiro
- Associação Nacional de Criadores de Ovinos da Raça Merina (ANCORME), 7005-665, Évora, Portugal
| | - Pedro Cardoso
- Associação de Produtores Agropecuários (OVIBEIRA), 6000-244, Castelo Branco, Portugal
| | - Silverio Grande
- Associazione Nazionale della Pastorizia (ASSONAPA), 00187, Rome, Italy
| | | | | | - Marina Pasquini
- Department of Agricultural, Food and Environmental Sciences, Università Politecnica delle Marche, 60131, Ancona, Italy
| | | | | | - Emiliano Lasagna
- Department of Agricultural, Food and Environmental Sciences, University of Perugia, 06121, Perugia, Italy
| | - Elena Ciani
- Department of Bioscience, Biotechnology and Biopharmaceutics, University of Bari "Aldo Moro", 70124, Bari, Italy
| | - Francesca Maria Sarti
- Department of Agricultural, Food and Environmental Sciences, University of Perugia, 06121, Perugia, Italy
| | - Fabio Pilla
- Department of Agricultural, Environmental and Food Sciences, University of Molise, 86100, Campobasso, Italy
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Becker GM, Woods JL, Schauer CS, Stewart WC, Murdoch BM. Genetic association of wool quality characteristics in United States Rambouillet sheep. Front Genet 2023; 13:1081175. [PMID: 36755873 PMCID: PMC9901206 DOI: 10.3389/fgene.2022.1081175] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Accepted: 12/20/2022] [Indexed: 01/24/2023] Open
Abstract
Introduction: Fine wool production is an important source of revenue, accounting for up to 13% of total revenue in extensively managed wool sheep production systems of the United States. The Rambouillet are a predominant breed that excels in wool quality characteristics. Understanding the genetic basis of wool quality characteristics would aid in the development of genomic breeding strategies to facilitate genetic improvement. Methods: Wool characteristics and DNA were collected for rams enrolled in the North Dakota State University and University of Wyoming annual central performance ram tests over a three-year period (2019-2021, N = 313). The relationships of wool quality characteristics including grease fleece weight adjusted 365 days (wt. 365 adj.), clean fleece wt. 365 adj., staple length 365 adj., average fiber diameter, face wool cover, amount of skin wrinkles and belly wool were evaluated through genome-wide association studies (GWAS), Pearson correlation and ANOVA. Results: The GWAS identified four genome-wide significant genetic markers (p-value <1.19e-06) and five chromosome-wide significant markers (p-value <1.13e-05) on chromosomes 1, 2, 4, 15, and 19. Significant markers were associated with genes notable for relevant wool biological functions, including the gene ABCC8 which codes for SUR1, an ATP-sensitive potassium channel known to affect hair growth and 60S ribosomal protein L17-like, previously found to be expressed during follicle formation. The strongest Pearson correlation coefficients were identified between clean fleece wt. 365 adj. and grease fleece wt. 365 adj. (r = 0.83) and between clean fleece wt. 365 adj. and staple length 365 adj. (r = 0.53). Additionally, clean fleece wt. 365 adj. was correlated with final body weight (r = 0.35) and scrotal circumference (r = 0.16). Staple length 365 adj. (p-value = 5e-04), average fiber diameter (p-value = .0053) and clean fleece wt. 365 adj. (p-value = .014) were significantly associated with belly wool score. Discussion: The results of this study provide important insight into the relationships between wool quality characteristics and report specific markers that Rambouillet sheep producers may use to help inform selection and breeding decisions for improved wool quality.
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Affiliation(s)
- Gabrielle M. Becker
- Department of Animal, Veterinary and Food Science, University of Idaho, Moscow, ID, United States
| | - Julia L. Woods
- Department of Animal, Veterinary and Food Science, University of Idaho, Moscow, ID, United States
| | - Christopher S. Schauer
- Hettinger Research Extension Center, North Dakota State University, Hettinger, ND, United States
| | - Whit C. Stewart
- Department of Animal Science, University of Wyoming, Laramie, WY, United States
| | - Brenda M. Murdoch
- Department of Animal, Veterinary and Food Science, University of Idaho, Moscow, ID, United States,*Correspondence: Brenda M. Murdoch,
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Ramos Z, Garrick DJ, Blair HT, Vera B, Ciappesoni G, Kenyon PR. Genomic Regions Associated with Wool, Growth and Reproduction Traits in Uruguayan Merino Sheep. Genes (Basel) 2023; 14:167. [PMID: 36672908 PMCID: PMC9858812 DOI: 10.3390/genes14010167] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Revised: 12/29/2022] [Accepted: 01/04/2023] [Indexed: 01/11/2023] Open
Abstract
The aim of this study was to identify genomic regions and genes associated with the fiber diameter (FD), clean fleece weight (CFW), live weight (LW), body condition score (BCS), pregnancy rate (PR) and lambing potential (LP) of Uruguayan Merino sheep. Phenotypic records of approximately 2000 mixed-age ewes were obtained from a Merino nucleus flock. Genome-wide association studies were performed utilizing single-step Bayesian analysis. For wool traits, a total of 35 genomic windows surpassed the significance threshold (PVE ≥ 0.25%). The proportion of the total additive genetic variance explained by those windows was 4.85 and 9.06% for FD and CFW, respectively. There were 42 windows significantly associated with LWM, which collectively explained 43.2% of the additive genetic variance. For BCS, 22 relevant windows accounted for more than 40% of the additive genetic variance, whereas for the reproduction traits, 53 genomic windows (24 and 29 for PR and LP, respectively) reached the suggestive threshold of 0.25% of the PVE. Within the top 10 windows for each trait, we identified several genes showing potential associations with the wool (e.g., IGF-1, TGFB2R, PRKCA), live weight (e.g., CAST, LAP3, MED28, HERC6), body condition score (e.g., CDH10, TMC2, SIRPA, CPXM1) or reproduction traits (e.g., ADCY1, LEPR, GHR, LPAR2) of the mixed-age ewes.
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Affiliation(s)
- Zully Ramos
- School of Agriculture and Environment, Massey University, Palmerston North 4410, New Zealand
| | - Dorian J. Garrick
- School of Agriculture and Environment, Massey University, Palmerston North 4410, New Zealand
| | - Hugh T. Blair
- School of Agriculture and Environment, Massey University, Palmerston North 4410, New Zealand
| | - Brenda Vera
- National Research Program on Meat and Wool Production, Instituto Nacional de Investigación Agropecuaria, INIA Las Brujas, Ruta 48 Km 10, Canelones 90100, Uruguay
| | - Gabriel Ciappesoni
- National Research Program on Meat and Wool Production, Instituto Nacional de Investigación Agropecuaria, INIA Las Brujas, Ruta 48 Km 10, Canelones 90100, Uruguay
| | - Paul R. Kenyon
- School of Agriculture and Environment, Massey University, Palmerston North 4410, New Zealand
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Ros-Freixedes R, Johnsson M, Whalen A, Chen CY, Valente BD, Herring WO, Gorjanc G, Hickey JM. Genomic prediction with whole-genome sequence data in intensely selected pig lines. GENETICS SELECTION EVOLUTION 2022; 54:65. [PMID: 36153511 PMCID: PMC9509613 DOI: 10.1186/s12711-022-00756-0] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Accepted: 09/05/2022] [Indexed: 12/03/2022]
Abstract
Background Early simulations indicated that whole-genome sequence data (WGS) could improve the accuracy of genomic predictions within and across breeds. However, empirical results have been ambiguous so far. Large datasets that capture most of the genomic diversity in a population must be assembled so that allele substitution effects are estimated with high accuracy. The objectives of this study were to use a large pig dataset from seven intensely selected lines to assess the benefits of using WGS for genomic prediction compared to using commercial marker arrays and to identify scenarios in which WGS provides the largest advantage. Methods We sequenced 6931 individuals from seven commercial pig lines with different numerical sizes. Genotypes of 32.8 million variants were imputed for 396,100 individuals (17,224 to 104,661 per line). We used BayesR to perform genomic prediction for eight complex traits. Genomic predictions were performed using either data from a standard marker array or variants preselected from WGS based on association tests. Results The accuracies of genomic predictions based on preselected WGS variants were not robust across traits and lines and the improvements in prediction accuracy that we achieved so far with WGS compared to standard marker arrays were generally small. The most favourable results for WGS were obtained when the largest training sets were available and standard marker arrays were augmented with preselected variants with statistically significant associations to the trait. With this method and training sets of around 80k individuals, the accuracy of within-line genomic predictions was on average improved by 0.025. With multi-line training sets, improvements of 0.04 compared to marker arrays could be expected. Conclusions Our results showed that WGS has limited potential to improve the accuracy of genomic predictions compared to marker arrays in intensely selected pig lines. Thus, although we expect that larger improvements in accuracy from the use of WGS are possible with a combination of larger training sets and optimised pipelines for generating and analysing such datasets, the use of WGS in the current implementations of genomic prediction should be carefully evaluated against the cost of large-scale WGS data on a case-by-case basis. Supplementary Information The online version contains supplementary material available at 10.1186/s12711-022-00756-0.
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