1
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Ward JA, Ng'ang'a SI, Randhawa IAS, McHugo GP, O'Grady JF, Flórez JM, Browne JA, Pérez O’Brien AM, Landaeta-Hernández AJ, Garcia JF, Sonstegard TS, Frantz LAF, Salter-Townshend M, MacHugh DE. Genomic insights into the population history and adaptive traits of Latin American Criollo cattle. R Soc Open Sci 2024; 11:231388. [PMID: 38571912 PMCID: PMC10990470 DOI: 10.1098/rsos.231388] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Revised: 01/04/2024] [Accepted: 01/31/2024] [Indexed: 04/05/2024]
Abstract
Criollo cattle, the descendants of animals brought by Iberian colonists to the Americas, have been the subject of natural and human-mediated selection in novel tropical agroecological zones for centuries. Consequently, these breeds have evolved distinct characteristics such as resistance to diseases and exceptional heat tolerance. In addition to European taurine (Bos taurus) ancestry, it has been proposed that gene flow from African taurine and Asian indicine (Bos indicus) cattle has shaped the ancestry of Criollo cattle. In this study, we analysed Criollo breeds from Colombia and Venezuela using whole-genome sequencing (WGS) and single-nucleotide polymorphism (SNP) array data to examine population structure and admixture at high resolution. Analysis of genetic structure and ancestry components provided evidence for African taurine and Asian indicine admixture in Criollo cattle. In addition, using WGS data, we detected selection signatures associated with a myriad of adaptive traits, revealing genes linked to thermotolerance, reproduction, fertility, immunity and distinct coat and skin coloration traits. This study underscores the remarkable adaptability of Criollo cattle and highlights the genetic richness and potential of these breeds in the face of climate change, habitat flux and disease challenges. Further research is warranted to leverage these findings for more effective and sustainable cattle breeding programmes.
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Affiliation(s)
- James A. Ward
- Animal Genomics Laboratory, School of Agriculture and Food Science, University College Dublin, DublinD04 V1W8, Ireland
| | - Said I. Ng'ang'a
- Palaeogenomics Group, Department of Veterinary Sciences, Ludwig Maximilian University, MunichD-80539, Germany
- School of Biological and Chemical Sciences, Queen Mary University of London, LondonE1 4NS, UK
| | | | - Gillian P. McHugo
- Animal Genomics Laboratory, School of Agriculture and Food Science, University College Dublin, DublinD04 V1W8, Ireland
| | - John F. O'Grady
- Animal Genomics Laboratory, School of Agriculture and Food Science, University College Dublin, DublinD04 V1W8, Ireland
| | - Julio M. Flórez
- Acceligen, Eagan, MN55121, USA
- Department of Preventive Veterinary Medicine and Animal Reproduction, School of Agricultural and Veterinarian Sciences, São Paulo State University (Unesp), Jaboticabal, Brazil
| | - John A. Browne
- Animal Genomics Laboratory, School of Agriculture and Food Science, University College Dublin, DublinD04 V1W8, Ireland
| | | | - Antonio J. Landaeta-Hernández
- Unidad de Investigaciones Zootécnicas, Facultad de Ciencias Veterinarias, Universidad del Zulia, Maracaibo, Venezuela
| | - Jóse F. Garcia
- Department of Preventive Veterinary Medicine and Animal Reproduction, School of Agricultural and Veterinarian Sciences, São Paulo State University (Unesp), Jaboticabal, Brazil
| | | | - Laurent A. F. Frantz
- Palaeogenomics Group, Department of Veterinary Sciences, Ludwig Maximilian University, MunichD-80539, Germany
- School of Biological and Chemical Sciences, Queen Mary University of London, LondonE1 4NS, UK
| | | | - David E. MacHugh
- Animal Genomics Laboratory, School of Agriculture and Food Science, University College Dublin, DublinD04 V1W8, Ireland
- Conway Institute of Biomolecular and Biomedical Research, University College Dublin, DublinD04 V1W8, Ireland
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2
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Salgado B, Rivas RB, Pinto D, Sonstegard TS, Carlson DF, Martins K, Bostrom JR, Sinebo Y, Rowland RRR, Brandariz-Nuñez A. Genetically modified pigs lacking CD163 PSTII-domain-coding exon 13 are completely resistant to PRRSV infection. Antiviral Res 2024; 221:105793. [PMID: 38184111 DOI: 10.1016/j.antiviral.2024.105793] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Revised: 12/18/2023] [Accepted: 01/02/2024] [Indexed: 01/08/2024]
Abstract
CD163 expressed on cell surface of porcine alveolar macrophages (PAMs) serves as a cellular entry receptor for porcine reproductive and respiratory syndrome virus (PRRSV). The extracellular portion of CD163 contains nine scavenger receptor cysteine-rich (SRCR) and two proline-serine-threonine (PST) domains. Genomic editing of pigs to remove the entire CD163 or just the SRCR5 domain confers resistance to infection with both PRRSV-1 and PRRSV-2 viruses. By performing a mutational analysis of CD163, previous in vitro infection experiments showed resistance to PRRSV infection following deletion of exon 13 which encodes the first 12 amino acids of the 16 amino acid PSTII domain. These findings predicted that removal of exon 13 can be used as a strategy to produce gene-edited pigs fully resistant to PRRSV infection. In this study, to determine whether the deletion of exon 13 is sufficient to confer resistance of pigs to PRRSV infection, we produced pigs possessing a defined CD163 exon 13 deletion (ΔExon13 pigs) and evaluated their susceptibility to viral infection. Wild type (WT) and CD163 modified pigs, placed in the same room, were infected with PRRSV-2. The modified pigs remained PCR and serologically negative for PRRSV throughout the study; whereas the WT pigs supported PRRSV infection and showed PRRSV related pathology. Importantly, our data also suggested that removal of exon 13 did not affect the main physiological function associated with CD163 in vivo. These results demonstrate that a modification of CD163 through a precise deletion of exon 13 provides a strategy for protection against PRRSV infection.
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Affiliation(s)
- Brianna Salgado
- Department of Pathobiology, College of Veterinary Medicine, University of Illinois at Urbana-Champaign, Champaign, IL, USA
| | - Rafael Bautista Rivas
- Department of Pathobiology, College of Veterinary Medicine, University of Illinois at Urbana-Champaign, Champaign, IL, USA
| | - Derek Pinto
- Department of Pathobiology, College of Veterinary Medicine, University of Illinois at Urbana-Champaign, Champaign, IL, USA
| | | | | | | | | | | | - Raymond R R Rowland
- Department of Pathobiology, College of Veterinary Medicine, University of Illinois at Urbana-Champaign, Champaign, IL, USA
| | - Alberto Brandariz-Nuñez
- Department of Pathobiology, College of Veterinary Medicine, University of Illinois at Urbana-Champaign, Champaign, IL, USA.
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3
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Woodward-Greene MJ, Kinser JM, Huson HJ, Sonstegard TS, Soelkner J, Vaisman II, Boettcher P, Masiga CW, Mukasa C, Abegaz S, Agaba M, Ahmed SS, Maminiaina OF, Getachew T, Gondwe TN, Haile A, Hassan Y, Kihara A, Kouriba A, Mruttu HA, Mujibi D, Nandolo W, Rischkowsky BA, Rosen BD, Sayre B, Taela M, Van Tassell CP. Using the community-based breeding program (CBBP) model as a collaborative platform to develop the African Goat Improvement Network-Image collection protocol (AGIN-ICP) with mobile technology for data collection and management of livestock phenotypes. Front Genet 2023; 14:1200770. [PMID: 37745840 PMCID: PMC10512022 DOI: 10.3389/fgene.2023.1200770] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Accepted: 07/25/2023] [Indexed: 09/26/2023] Open
Abstract
Introduction: The African Goat Improvement Network Image Collection Protocol (AGIN-ICP) is an accessible, easy to use, low-cost procedure to collect phenotypic data via digital images. The AGIN-ICP collects images to extract several phenotype measures including health status indicators (anemia status, age, and weight), body measurements, shapes, and coat color and pattern, from digital images taken with standard digital cameras or mobile devices. This strategy is to quickly survey, record, assess, analyze, and store these data for use in a wide variety of production and sampling conditions. Methods: The work was accomplished as part of the multinational African Goat Improvement Network (AGIN) collaborative and is presented here as a case study in the AGIN collaboration model and working directly with community-based breeding programs (CBBP). It was iteratively developed and tested over 3 years, in 12 countries with over 12,000 images taken. Results and discussion: The AGIN-ICP development is described, and field implementation and the quality of the resulting images for use in image analysis and phenotypic data extraction are iteratively assessed. Digital body measures were validated using the PreciseEdge Image Segmentation Algorithm (PE-ISA) and software showing strong manual to digital body measure Pearson correlation coefficients of height, length, and girth measures (0.931, 0.943, 0.893) respectively. It is critical to note that while none of the very detailed tasks in the AGIN-ICP described here is difficult, every single one of them is even easier to accidentally omit, and the impact of such a mistake could render a sample image, a sampling day's images, or even an entire sampling trip's images difficult or unusable for extracting digital phenotypes. Coupled with tissue sampling and genomic testing, it may be useful in the effort to identify and conserve important animal genetic resources and in CBBP genetic improvement programs by providing reliably measured phenotypes with modest cost. Potential users include farmers, animal husbandry officials, veterinarians, regional government or other public health officials, researchers, and others. Based on these results, a final AGIN-ICP is presented, optimizing the costs, ease, and speed of field implementation of the collection method without compromising the quality of the image data collection.
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Affiliation(s)
- M. Jennifer Woodward-Greene
- National Agricultural Library, USDA Agricultural Research Service, Beltsville, MD, United States
- Animal Genomics Improvement Laboratory, USDA Agricultural Research Service, Beltsville, MD, United States
- Bioinformatics and Computational Biology Program, School of Systems Biology, College of Science, George Mason University, Manassas, VA, United States
| | - Jason M. Kinser
- School of Physics, Astronomy, and Computational Sciences, College of Science, George Mason University, Fairfax, VA, United States
| | - Heather J. Huson
- Department of Animal Science, College of Agriculture and Life Sciences, Cornell University, Ithaca, NY, United States
| | | | - Johann Soelkner
- Department of Sustainable Agricultural Systems, Division of Livestock Sciences, BOKU—University of Natural Resources and Life Sciences, Vienna, Austria
| | - Iosif I. Vaisman
- Bioinformatics and Computational Biology Program, School of Systems Biology, College of Science, George Mason University, Manassas, VA, United States
| | - Paul Boettcher
- Food and Agriculture Organization of the United Nations, Animal Production and Health Division, Rome, Italy
| | - Clet W. Masiga
- Association for Strengthening Agricultural Research in Eastern and Central Africa (ASARECA), Entebbe, Uganda
| | | | - Solomon Abegaz
- Ethiopian Institute of Agricultural Research, Addis Ababa, Ethiopia
| | - Morris Agaba
- Nelson Mandela African Institution of Science and Technology, Arusha, Tanzania
| | - Sahar S. Ahmed
- Cell Biology Department, Biotechnology Research Institute, National Research Centre, Giza, Egypt
| | - Oliver F. Maminiaina
- Department of Zootechnical, Veterinary and Piscicultural Research (DRZVP), National Center for Applied Research in Rural Development (CENRADERU), Antananarivo, Madagascar
| | - Tesfaye Getachew
- International Center for Agricultural Research in the Dry Areas (ICARDA), Addis Ababa, Ethiopia
| | - Timothy N. Gondwe
- Department of Animal Science, Lilongwe University of Agriculture and Natural Resources, Lilongwe, Malawi
| | - Aynalem Haile
- International Center for Agricultural Research in the Dry Areas (ICARDA), Addis Ababa, Ethiopia
| | - Yassir Hassan
- Department of Animal Genetic Resources Development, Animal Production Research Center, Ministry of Animal Resources, Khartoum North, Sudan
| | | | | | | | - Denis Mujibi
- International Livestock Research Institute, Nairobi, Kenya
| | - Wilson Nandolo
- Department of Animal Science, Lilongwe University of Agriculture and Natural Resources, Lilongwe, Malawi
| | - Barbara A. Rischkowsky
- International Center for Agricultural Research in the Dry Areas (ICARDA), Addis Ababa, Ethiopia
| | - Benjamin D. Rosen
- Animal Genomics Improvement Laboratory, USDA Agricultural Research Service, Beltsville, MD, United States
| | - Brian Sayre
- Department of Biology, Virginia State University, Petersburg, VA, United States
| | - Maria Taela
- Agrarian Research Institute of Mozambique, Directorate of Animal Science, Maputo, Mozambique
| | - Curtis P. Van Tassell
- Animal Genomics Improvement Laboratory, USDA Agricultural Research Service, Beltsville, MD, United States
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Van Tassell CP, Rosen BD, Woodward-Greene MJ, Silverstein JT, Huson HJ, Sölkner J, Boettcher P, Rothschild MF, Mészáros G, Nakimbugwe HN, Gondwe TN, Muchadeyi FC, Nandolo W, Mulindwa HA, Banda LJ, Kaumbata W, Getachew T, Haile A, Soudre A, Ouédraogo D, Rischkowsky BA, Mwai AO, Dzomba EF, Nash O, Abegaz S, Masiga CW, Wurzinger M, Sayre BL, Stella A, Tosser-Klopp G, Sonstegard TS. The African Goat Improvement Network: a scientific group empowering smallholder farmers. Front Genet 2023; 14:1183240. [PMID: 37712066 PMCID: PMC10497955 DOI: 10.3389/fgene.2023.1183240] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Accepted: 07/27/2023] [Indexed: 09/16/2023] Open
Abstract
The African Goat Improvement Network (AGIN) is a collaborative group of scientists focused on genetic improvement of goats in small holder communities across the African continent. The group emerged from a series of workshops focused on enhancing goat productivity and sustainability. Discussions began in 2011 at the inaugural workshop held in Nairobi, Kenya. The goals of this diverse group were to: improve indigenous goat production in Africa; characterize existing goat populations and to facilitate germplasm preservation where appropriate; and to genomic approaches to better understand adaptation. The long-term goal was to develop cost-effective strategies to apply genomics to improve productivity of small holder farmers without sacrificing adaptation. Genome-wide information on genetic variation enabled genetic diversity studies, facilitated improved germplasm preservation decisions, and provided information necessary to initiate large scale genetic improvement programs. These improvements were partially implemented through a series of community-based breeding programs that engaged and empowered local small farmers, especially women, to promote sustainability of the production system. As with many international collaborative efforts, the AGIN work serves as a platform for human capacity development. This paper chronicles the evolution of the collaborative approach leading to the current AGIN organization and describes how it builds capacity for sustained research and development long after the initial program funds are gone. It is unique in its effectiveness for simultaneous, multi-level capacity building for researchers, students, farmers and communities, and local and regional government officials. The positive impact of AGIN capacity building has been felt by participants from developing, as well as developed country partners.
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Affiliation(s)
- Curtis P. Van Tassell
- Animal Genomics and Improvement Laboratory, USDA Agricultural Research Service, Beltsville, MD, United States
| | - Benjamin D. Rosen
- Animal Genomics and Improvement Laboratory, USDA Agricultural Research Service, Beltsville, MD, United States
| | - M. Jennifer Woodward-Greene
- Animal Genomics and Improvement Laboratory, USDA Agricultural Research Service, Beltsville, MD, United States
- National Agricultural Library, USDA Agricultural Research Service, Beltsville, MD, United States
| | - Jeffrey T. Silverstein
- Office of National Programs, USDA Agricultural Research Service, Beltsville, MD, United States
| | - Heather J. Huson
- Department of Animal Science, Cornell University, Ithaca, NY, United States
| | - Johann Sölkner
- Division of Livestock Sciences, University of Natural Resources and Life Sciences, Vienna, Austria
| | - Paul Boettcher
- Animal Production and Health Division, Food and Agriculture Organization of the United Nations, Rome, Italy
| | - Max F. Rothschild
- Department of Animal Science, Iowa State University, Ames, IA, United States
| | - Gábor Mészáros
- Division of Livestock Sciences, University of Natural Resources and Life Sciences, Vienna, Austria
| | | | - Timothy N. Gondwe
- Department of Animal Science, Lilongwe University of Agriculture and Natural Resources, Lilongwe, Malawi
| | - Farai C. Muchadeyi
- Biotechnology Platform, Agricultural Research Council, Pretoria, South Africa
| | - Wilson Nandolo
- Department of Animal Science, Lilongwe University of Agriculture and Natural Resources, Lilongwe, Malawi
| | | | - Liveness J. Banda
- Department of Animal Science, Lilongwe University of Agriculture and Natural Resources, Lilongwe, Malawi
| | - Wilson Kaumbata
- Department of Animal Science, Lilongwe University of Agriculture and Natural Resources, Lilongwe, Malawi
| | - Tesfaye Getachew
- International Center for Agricultural Research in the Dry Areas, Addis Ababa, Ethiopia
| | - Aynalem Haile
- International Center for Agricultural Research in the Dry Areas, Addis Ababa, Ethiopia
| | - Albert Soudre
- Unité de Formation et de Recherches - Sciences et Technologies, Université Norbert ZONGO, Koudougou, Burkina Faso
| | | | | | | | - Edgar Farai Dzomba
- Discipline of Genetics, School of Life Sciences, University of KwaZulu-Natal, Pietermaritzburg, South Africa
| | - Oyekanmi Nash
- National Biotechnology Development Agency, Abuja, Nigeria
| | - Solomon Abegaz
- Ethiopian Institute of Agricultural Research, Addis Ababa, Ethiopia
| | | | - Maria Wurzinger
- Division of Livestock Sciences, University of Natural Resources and Life Sciences, Vienna, Austria
| | - Brian L. Sayre
- Department of Biology, Virginia State University, Petersburg, VA, United States
| | - Alessandra Stella
- Institute of Agricultural Biology and Biotechnology (IBBA), Milano, Italy
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Workman AM, Heaton MP, Vander Ley BL, Webster DA, Sherry L, Bostrom JR, Larson S, Kalbfleisch TS, Harhay GP, Jobman EE, Carlson DF, Sonstegard TS. First gene-edited calf with reduced susceptibility to a major viral pathogen. PNAS Nexus 2023; 2:pgad125. [PMID: 37181049 PMCID: PMC10167990 DOI: 10.1093/pnasnexus/pgad125] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/03/2023] [Revised: 01/03/2023] [Accepted: 04/06/2023] [Indexed: 05/16/2023]
Abstract
Bovine viral diarrhea virus (BVDV) is one of the most important viruses affecting the health and well-being of bovine species throughout the world. Here, we used CRISPR-mediated homology-directed repair and somatic cell nuclear transfer to produce a live calf with a six amino acid substitution in the BVDV binding domain of bovine CD46. The result was a gene-edited calf with dramatically reduced susceptibility to infection as measured by reduced clinical signs and the lack of viral infection in white blood cells. The edited calf has no off-target edits and appears normal and healthy at 20 months of age without obvious adverse effects from the on-target edit. This precision bred, proof-of-concept animal provides the first evidence that intentional genome alterations in the CD46 gene may reduce the burden of BVDV-associated diseases in cattle and is consistent with our stepwise, in vitro and ex vivo experiments with cell lines and matched fetal clones.
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Affiliation(s)
- Aspen M Workman
- US Meat Animal Research Center, United States Department of Agriculture (USDA), Agricultural Research Service (ARS), 844 Road 313 Clay Center, NE 68933, USA
| | - Michael P Heaton
- US Meat Animal Research Center, United States Department of Agriculture (USDA), Agricultural Research Service (ARS), 844 Road 313 Clay Center, NE 68933, USA
| | - Brian L Vander Ley
- Great Plains Veterinary Educational Center, University of Nebraska–Lincoln, 820 Road 313 Clay Center, NE 68933, USA
| | - Dennis A Webster
- Recombinetics Inc., 3388 Mike Collins Drive, Eagan, MN 55121, USA
| | - Luke Sherry
- Recombinetics Inc., 3388 Mike Collins Drive, Eagan, MN 55121, USA
| | | | - Sabreena Larson
- Acceligen Inc., 3388 Mike Collins Drive, Eagan, MN 55121, USA
| | - Theodore S Kalbfleisch
- Department of Veterinary Science, Gluck Equine Research Center, University of Kentucky, 1400 Nicholasville Rd Lexington, KY 40546, USA
| | - Gregory P Harhay
- US Meat Animal Research Center, United States Department of Agriculture (USDA), Agricultural Research Service (ARS), 844 Road 313 Clay Center, NE 68933, USA
| | - Erin E Jobman
- Great Plains Veterinary Educational Center, University of Nebraska–Lincoln, 820 Road 313 Clay Center, NE 68933, USA
| | - Daniel F Carlson
- Recombinetics Inc., 3388 Mike Collins Drive, Eagan, MN 55121, USA
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6
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Flórez JM, Martins K, Solin S, Bostrom JR, Rodríguez-Villamil P, Ongaratto F, Larson SA, Ganbaatar U, Coutts AW, Kern D, Murphy TW, Kim ES, Carlson DF, Huisman A, Sonstegard TS, Lents CA. CRISPR/Cas9-editing of KISS1 to generate pigs with hypogonadotropic hypogonadism as a castration free trait. Front Genet 2023; 13:1078991. [PMID: 36685939 PMCID: PMC9854396 DOI: 10.3389/fgene.2022.1078991] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Accepted: 12/05/2022] [Indexed: 01/05/2023] Open
Abstract
Introduction: Most male pigs are surgically castrated to avoid puberty-derived boar taint and aggressiveness. However, this surgical intervention represents a welfare concern in swine production. Disrupting porcine KISS1 is hypothesized to delay or abolish puberty by inducing variable hypogonadotropism and thus preventing the need for castration. Methods: To test this hypothesis, we generated the first KISS1-edited large animal using CRISPR/Cas9-ribonucleoproteins and single-stranded donor oligonucleotides. The targeted region preceded the sequence encoding a conserved core motif of kisspeptin. Genome editors were intracytoplasmically injected into 684 swine zygotes and transferred to 19 hormonally synchronized surrogate sows. In nine litters, 49 American Yorkshire and 20 Duroc liveborn piglets were naturally farrowed. Results: Thirty-five of these pigs bore KISS1-disruptive alleles ranging in frequency from 5% to 97% and did not phenotypically differ from their wild-type counterparts. In contrast, four KISS1-edited pigs (two boars and two gilts) with disruptive allele frequencies of 96% and 100% demonstrated full hypogonadotropism, infantile reproductive tracts, and failed to reach sexual maturity. Change in body weight during development was unaffected by editing KISS1. Founder pigs partially carrying KISS1-disruptive alleles were bred resulting in a total of 53 KISS1 +/+, 60 KISS1 +/-, and 34 KISS1 -/- F1 liveborn piglets, confirming germline transmission. Discussion: Results demonstrate that a high proportion of KISS1 alleles in pigs must be disrupted before variation in gonadotropin secretion is observed, suggesting that even a small amount of kisspeptin ligand is sufficient to confer proper sexual development and puberty in pigs. Follow-on studies will evaluate fertility restoration in KISS1 KO breeding stock to fully realize the potential of KISS1 gene edits to eliminate the need for surgical castration.
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Affiliation(s)
- Julio M. Flórez
- Acceligen Inc., Eagan, MN, United States,Department of Preventive Veterinary Medicine and Animal Reproduction, School of Agricultural and Veterinarian Sciences, São Paulo State University (Unesp), Jaboticabal, Brazil
| | | | - Staci Solin
- Recombinetics Inc., Eagan, MN, United States
| | | | | | | | | | | | | | - Doug Kern
- Recombinetics Inc., Eagan, MN, United States
| | - Thomas W. Murphy
- USDA, ARS, U.S. Meat Animal Research Center, Clay Center, NE, United States
| | | | | | - Abe Huisman
- Hypor, Hendrix Genetics, Boxmeer, Netherlands
| | - Tad S. Sonstegard
- Acceligen Inc., Eagan, MN, United States,*Correspondence: Tad S. Sonstegard,
| | - Clay A. Lents
- USDA, ARS, U.S. Meat Animal Research Center, Clay Center, NE, United States
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7
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Woodward-Greene MJ, Kinser JM, Sonstegard TS, Sölkner J, Vaisman II, Van Tassell CP. PreciseEdge raster RGB image segmentation algorithm reduces user input for livestock digital body measurements highly correlated to real-world measurements. PLoS One 2022; 17:e0275821. [PMID: 36227957 PMCID: PMC9560539 DOI: 10.1371/journal.pone.0275821] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2021] [Accepted: 09/24/2022] [Indexed: 11/25/2022] Open
Abstract
Computer vision is a tool that could provide livestock producers with digital body measures and records that are important for animal health and production, namely body height and length, and chest girth. However, to build these tools, the scarcity of labeled training data sets with uniform images (pose, lighting) that also represent real-world livestock can be a challenge. Collecting images in a standard way, with manual image labeling is the gold standard to create such training data, but the time and cost can be prohibitive. We introduce the PreciseEdge image segmentation algorithm to address these issues by employing a standard image collection protocol with a semi-automated image labeling method, and a highly precise image segmentation for automated body measurement extraction directly from each image. These elements, from image collection to extraction are designed to work together to yield values highly correlated to real-world body measurements. PreciseEdge adds a brief preprocessing step inspired by chromakey to a modified GrabCut procedure to generate image masks for data extraction (body measurements) directly from the images. Three hundred RGB (red, green, blue) image samples were collected uniformly per the African Goat Improvement Network Image Collection Protocol (AGIN-ICP), which prescribes camera distance, poses, a blue backdrop, and a custom AGIN-ICP calibration sign. Images were taken in natural settings outdoors and in barns under high and low light, using a Ricoh digital camera producing JPG images (converted to PNG prior to processing). The rear and side AGIN-ICP poses were used for this study. PreciseEdge and GrabCut image segmentation methods were compared for differences in user input required to segment the images. The initial bounding box image output was captured for visual comparison. Automated digital body measurements extracted were compared to manual measures for each method. Both methods allow additional optional refinement (mouse strokes) to aid the segmentation algorithm. These optional mouse strokes were captured automatically and compared. Stroke count distributions for both methods were not normally distributed per Kolmogorov-Smirnov tests. Non-parametric Wilcoxon tests showed the distributions were different (p< 0.001) and the GrabCut stroke count was significantly higher (p = 5.115 e-49), with a mean of 577.08 (std 248.45) versus 221.57 (std 149.45) with PreciseEdge. Digital body measures were highly correlated to manual height, length, and girth measures, (0.931, 0.943, 0.893) for PreciseEdge and (0.936, 0. 944, 0.869) for GrabCut (Pearson correlation coefficient). PreciseEdge image segmentation allowed for masks yielding accurate digital body measurements highly correlated to manual, real-world measurements with over 38% less user input for an efficient, reliable, non-invasive alternative to livestock hand-held direct measuring tools.
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Affiliation(s)
- M. Jennifer Woodward-Greene
- USDA-ARS-NEA Animal Genomics and Improvement Laboratory, Beltsville, MD, United States of America
- Bioinformatics and Computational Biology Department, George Mason University, Manassas, VA, United States of America
| | - Jason M. Kinser
- Department of Computational and Data Sciences, George Mason University, Fairfax, VA, United States of America
| | - Tad S. Sonstegard
- Recombinetics at Acceligen, St. Paul, Minnesota, United States of America
| | - Johann Sölkner
- BOKU University of Natural Resources and Life Sciences, Vienna, Austria
| | - Iosif I. Vaisman
- Bioinformatics and Computational Biology Department, George Mason University, Manassas, VA, United States of America
| | - Curtis P. Van Tassell
- USDA-ARS-NEA Animal Genomics and Improvement Laboratory, Beltsville, MD, United States of America
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8
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Milanesi M, Obrien AMP, Utsunomiya AT, Feres LF, Sonstegard TS, Garcia JF. Genomic breed composition of pure registered Brazilian Gir. Trop Anim Health Prod 2022; 54:310. [PMID: 36123551 DOI: 10.1007/s11250-022-03299-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2022] [Accepted: 08/31/2022] [Indexed: 11/25/2022]
Abstract
INTRODUCTION Gir is a Bos indicus breed originally from India, first imported to Brazil in 1850. High-performance Dairy Gir has been systematically selected in Brazil from its arrival. Since the major phenotypic difference between Gir in India and Brazil is a higher milk production in the former, it is speculated that Brazilian Gir was strategically crossed with Holstein or another Bos taurus to improve milk yield. This study evaluated the purity of Brazilian Gir breed stocks from BASA Farms in Brazil, trying to identify possible admixture events with other cattle breeds based on DNA analysis. MATERIALS AND METHODS The population included 1061 pure registered individuals genotyped using two commercial platforms with 37 k and 25 k SNPs. Admixture analysis was performed individually to estimate levels of genomic composition derived from six different reference populations, three indicine and three taurine breeds. RESULTS A Gir ancestry of 99% or higher was found for 94.2% of the population, while the remaining showed levels of non-Gir ancestry up to 6.8%. Only five individuals were identified with possible taurine ancestry, all of them exhibiting levels lower than 2%. The remaining non-Gir ancestry identified was derived from indicine breeds. The levels of admixture observed in the population were from low to non-detectable. No consistent patterns of admixture were observed indicating sustained introgression of taurine lines as means of genetic improvement. CONCLUSION According to these results, genetic improvement achieved by Brazilian Gir breeders is the result of within-breed selection methods applied intensively over the past five decades, rather than the result from sustained introgression.
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Affiliation(s)
- M Milanesi
- AgroPartners Consulting, Araçatuba, SP, Brazil. .,Department of Animal Production and Health, School of Veterinary Medicine of Araçatuba, São Paulo State University (UNESP), Araçatuba, SP, Brazil. .,International Atomic Energy Agency (IAEA) Collaborating Centre On Animal Genomics and Bioinformatics, Araçatuba, Brazil.
| | - A M Pérez Obrien
- BASA Farms, Leopoldina, MG, Brazil.,Acceligen, Eagan, MN, 55121, USA
| | - A T Utsunomiya
- AgroPartners Consulting, Araçatuba, SP, Brazil.,International Atomic Energy Agency (IAEA) Collaborating Centre On Animal Genomics and Bioinformatics, Araçatuba, Brazil
| | | | | | - J F Garcia
- Department of Animal Production and Health, School of Veterinary Medicine of Araçatuba, São Paulo State University (UNESP), Araçatuba, SP, Brazil.,International Atomic Energy Agency (IAEA) Collaborating Centre On Animal Genomics and Bioinformatics, Araçatuba, Brazil
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9
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Sosa F, Carmickle AT, Oliveira LJ, Sagheer M, Saleem M, Yu FH, Altman MD, Dikmen S, Denicol AC, Sonstegard TS, Larson CC, Hansen PJ. Effects of the bovine SLICK1 mutation in PRLR on sweat gland area, FOXA1 abundance, and global gene expression in skin. J Dairy Sci 2022; 105:9206-9215. [PMID: 36085108 DOI: 10.3168/jds.2022-22272] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Accepted: 06/14/2022] [Indexed: 11/19/2022]
Abstract
The SLICK1 mutation in the prolactin receptor (PRLR) results in a short-hair coat and increased ability to regulate body temperature during heat stress. It is unclear whether the mutation affects capacity for sweating. The objective of this observational study was to evaluate whether the SLICK1 mutation in PRLR alters characteristics of skin related to sweat gland abundance or function. Skin biopsies from 31 Holstein heifers, including 14 wild-type (SL-/-) and 17 heterozygous slick (SL+/-), were subjected to histological analysis to determine the percent of the surface area of skin sections that are occupied by sweat glands. We detected no effect of genotype on this variable. Immunohistochemical analysis of the forkhead transcription factor A1 (FOXA1), a protein essential for sweating in mice, from 6 SL-/- and 6 SL+/- heifers indicated twice as much FOXA1 in sweat glandular epithelia of SL+/- heifers as in SL-/- heifers. Results from RNA sequencing of skin biopsies from 5 SL-/- and 7 SL+/- heifers revealed few genes that were differentially expressed and none that have been associated with sweat gland development or function. In conclusion, results do not support the idea that the SLICK1 mutation changes the abundance of sweat glands in skin, but do show that functional properties of sweat glands, as indicated by increased abundance of immunoreactive FOXA1, are modified by inheritance of the mutation in PRLR.
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Affiliation(s)
- F Sosa
- Department of Animal Sciences, D.H. Barron Reproductive and Perinatal Biology Research Program, and Genetics Institute, University of Florida, Gainesville 32611-0910
| | - A T Carmickle
- Department of Animal Science, University of California-Davis, Davis 95616
| | - L J Oliveira
- Department of Pathology, College of Veterinary Medicine, University of Georgia, Athens 30602
| | - M Sagheer
- Department of Animal Sciences, D.H. Barron Reproductive and Perinatal Biology Research Program, and Genetics Institute, University of Florida, Gainesville 32611-0910
| | - M Saleem
- Department of Animal Sciences, D.H. Barron Reproductive and Perinatal Biology Research Program, and Genetics Institute, University of Florida, Gainesville 32611-0910; Department of Theriogenology, Faculty of Veterinary Science, University of Veterinary and Animal Sciences, Lahore 54000, Pakistan
| | - F H Yu
- Interdisciplinary Center for Biotechnology Research, University of Florida, Gainesville 32610
| | - M D Altman
- Department of Animal Science, University of California-Davis, Davis 95616
| | - S Dikmen
- Faculty of Veterinary Medicine, Department of Animal Science, University of Uludag, Bursa, 16059, Turkey
| | - A C Denicol
- Department of Animal Science, University of California-Davis, Davis 95616
| | | | - C C Larson
- Okeechobee County Cooperative Extension Service, Institute of Food and Agricultural Sciences, University of Florida, Okeechobee 34972
| | - P J Hansen
- Department of Animal Sciences, D.H. Barron Reproductive and Perinatal Biology Research Program, and Genetics Institute, University of Florida, Gainesville 32611-0910.
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10
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Low WY, Rosen BD, Ren Y, Bickhart DM, To TH, Martin FJ, Billis K, Sonstegard TS, Sullivan ST, Hiendleder S, Williams JL, Heaton MP, Smith TPL. Gaur genome reveals expansion of sperm odorant receptors in domesticated cattle. BMC Genomics 2022; 23:344. [PMID: 35508966 PMCID: PMC9069736 DOI: 10.1186/s12864-022-08561-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Accepted: 04/13/2022] [Indexed: 02/08/2023] Open
Abstract
Background The gaur (Bos gaurus) is the largest extant wild bovine species, native to South and Southeast Asia, with unique traits, and is listed as vulnerable by the International Union for Conservation of Nature (IUCN). Results We report the first gaur reference genome and identify three biological pathways including lysozyme activity, proton transmembrane transporter activity, and oxygen transport with significant changes in gene copy number in gaur compared to other mammals. These may reflect adaptation to challenges related to climate and nutrition. Comparative analyses with domesticated indicine (Bos indicus) and taurine (Bos taurus) cattle revealed genomic signatures of artificial selection, including the expansion of sperm odorant receptor genes in domesticated cattle, which may have important implications for understanding selection for male fertility. Conclusions Apart from aiding dissection of economically important traits, the gaur genome will also provide the foundation to conserve the species. Supplementary Information The online version contains supplementary material available at 10.1186/s12864-022-08561-1.
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Affiliation(s)
- Wai Yee Low
- The Davies Research Centre, School of Animal and Veterinary Sciences, University of Adelaide, Roseworthy, SA, 5371, Australia.
| | - Benjamin D Rosen
- Animal Genomics and Improvement LaboratoryARS USDA, Beltsville, MD, USA
| | - Yan Ren
- The Davies Research Centre, School of Animal and Veterinary Sciences, University of Adelaide, Roseworthy, SA, 5371, Australia
| | | | - Thu-Hien To
- Norwegian University of Life Sciences: NMBU, Universitetstunet 3, 1430, Ås, Norway
| | - Fergal J Martin
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Konstantinos Billis
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | | | - Shawn T Sullivan
- Phase Genomics, 4000 Mason Road, Suite 225, Seattle, WA, 98195, USA
| | - Stefan Hiendleder
- The Davies Research Centre, School of Animal and Veterinary Sciences, University of Adelaide, Roseworthy, SA, 5371, Australia
| | - John L Williams
- The Davies Research Centre, School of Animal and Veterinary Sciences, University of Adelaide, Roseworthy, SA, 5371, Australia.,Department of Animal Science, Food and Nutrition, Università Cattolica del Sacro Cuore, 29122, Piacenza, Italy
| | - Michael P Heaton
- U.S. Department of Agriculture, Agricultural Research Service, U.S. Meat Animal Research Center, Clay Center, Nebraska, USA
| | - Timothy P L Smith
- U.S. Department of Agriculture, Agricultural Research Service, U.S. Meat Animal Research Center, Clay Center, Nebraska, USA.
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11
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Notter DR, Heidaritabar M, Burke JM, Shirali M, Murdoch BM, Morgan JLM, Morota G, Sonstegard TS, Becker GM, Spangler GL, MacNeil MD, Miller JE. Single Nucleotide Polymorphism Effects on Lamb Fecal Egg Count Estimated Breeding Values in Progeny-Tested Katahdin Sires. Front Genet 2022; 13:866176. [PMID: 35591856 PMCID: PMC9110833 DOI: 10.3389/fgene.2022.866176] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2022] [Accepted: 04/14/2022] [Indexed: 01/31/2023] Open
Abstract
Estimated breeding values (EBV) for fecal egg counts (FEC) at 42–90 days of age (WFEC) and 91–150 days of age (PFEC) for 84 progeny-tested Katahdin sires were used to identify associations of deregressed EBV with single-nucleotide polymorphisms (SNP) using 388,000 SNP with minor-allele frequencies ≥0.10 on an Illumina high-density ovine array. Associations between markers and FEC EBV were initially quantified by single-SNP linear regression. Effects of linkage disequilibrium (LD) were minimized by assigning SNP to 2,535 consecutive 1-Mb bins and focusing on the effect of the most significant SNP in each bin. Bonferroni correction was used to define bin-based (BB) genome- and chromosome-wide significance. Six bins on chromosome 5 achieved BB genome-wide significance for PFEC EBV, and three of those SNP achieved chromosome-wide significance after Bonferroni correction based on the 14,530 total SNP on chromosome 5. These bins were nested within 12 consecutive bins between 59 and 71 Mb on chromosome 5 that reached BB chromosome-wide significance. The largest SNP effects were at 63, 67, and 70 Mb, with LD among these SNP of r2 ≤ 0.2. Regional heritability mapping (RHM) was then used to evaluate the ability of different genomic regions to account for additive variance in FEC EBV. Chromosome-level RHM indicated that one 500-SNP window between 65.9 and 69.9 Mb accounted for significant variation in PFEC EBV. Five additional 500-SNP windows between 59.3 and 71.6 Mb reached suggestive (p < 0.10) significance for PFEC EBV. Although previous studies rarely identified markers for parasite resistance on chromosome 5, the IL12B gene at 68.5 Mb codes for the p40 subunit of both interleukins 12 and 23. Other immunoregulatory genes are also located in this region of chromosome 5, providing opportunity for additive or associative effects.
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Affiliation(s)
- David R. Notter
- Department of Animal and Poultry Sciences, Virginia Tech, Blacksburg, VA, United States
- *Correspondence: David R. Notter,
| | - Marzieh Heidaritabar
- Livestock Gentec, Department of Agricultural, Food, and Nutritional Science, University of Alberta, Edmonton, AB, Canada
| | - Joan M. Burke
- United States Department of Agriculture, Agricultural Research Service, Dale Bumpers Small Farms Research Center, Booneville, AR, United States
| | - Masoud Shirali
- Agri-Food and Biosciences Institute, Belfast, United Kingdom
- School of Biological Sciences, Queen’s University Belfast, Belfast, United Kingdom
| | - Brenda M. Murdoch
- Department of Animal, Veterinary and Food Sciences, University of Idaho, Moscow, ID, United States
| | | | - Gota Morota
- Department of Animal and Poultry Sciences, Virginia Tech, Blacksburg, VA, United States
| | | | - Gabrielle M. Becker
- Department of Animal, Veterinary and Food Sciences, University of Idaho, Moscow, ID, United States
| | - Gordon L. Spangler
- Animal Genomics and Improvement Laboratory, United States Department of Agriculture, Agricultural Research Service, Beltsville, MD, United States
| | - Michael D. MacNeil
- Delta G, Miles City, MT, United States
- Department of Animal, Wildlife and Grassland Sciences, University of the Free State, Bloemfontein, South Africa
| | - James E. Miller
- Department of Pathobiological Sciences, School of Veterinary Medicine, Louisiana State University, Baton Rouge, LA, United States
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12
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Sosa F, Santos JEP, Rae DO, Larson CC, Macchietto M, Abrahante JE, Amaral TF, Denicol AC, Sonstegard TS, Hansen PJ. Effects of the SLICK1 mutation in PRLR on regulation of core body temperature and global gene expression in liver in cattle. Animal 2022; 16:100523. [PMID: 35468510 DOI: 10.1016/j.animal.2022.100523] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Revised: 03/18/2022] [Accepted: 03/21/2022] [Indexed: 11/01/2022] Open
Abstract
The SLICK1 mutation in bovine PRLR (c.1382del; rs517047387) is a deletion mutation resulting in a protein with a truncated intracellular domain. Cattle carrying at least one allele have a phenotype characterized by a short hair coat (slick phenotype) and increased resistance to heat stress. Given the pleiotropic nature of prolactin, the mutation may affect other physiological characteristics. The liver is one organ that could potentially be affected because of the expression of PRLR. The mutation is a dominant allele, and heterozygous animals have a similar hair coat to that of animals homozygous for the mutation. Present objectives were to determine whether inheritance of the SLICK1 mutation affects liver gene expression and if animals homozygous for the SLICK1 allele differ from heterozygotes in liver gene expression and regulation of body temperature during heat stress. In one experiment, rectal and ruminal temperatures were less for Holstein heifers that were heterozygous for the SLICK1 allele compared with wildtype heifers. There were 71 differentially expressed genes in liver, with 13 upregulated and 58 downregulated in SLICK1 heterozygotes. Among the ontologies characteristic of differentially expressed genes were those related to immune function and fatty acid and amino acid metabolism. In a prospective cohort study conducted with adult Senepol cattle, body temperature and hepatic gene expression were compared between animals heterozygous or homozygous for the SLICK1 mutation. There were no differences in ruminal temperatures between genotypes, rectal temperature was higher in animals homozygous for the SLICK1 mutation, and there was only one gene in liver that was differentially expressed. It was concluded that inheritance of the SLICK1 allele can exert functional changes beyond those related to hair growth although changes in liver gene expression were not extensive. Results are also consistent with the SLICK1 allele being dominant because there were few differences in phenotype between animals inheriting one or two copies of the allele.
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Affiliation(s)
- Froylan Sosa
- Department of Animal Sciences, D.H. Barron Reproductive and Perinatal Biology Research Program, and Genetics Institute, University of Florida, Gainesville, FL 32611-0910, USA
| | - José E P Santos
- Department of Animal Sciences, D.H. Barron Reproductive and Perinatal Biology Research Program, and Genetics Institute, University of Florida, Gainesville, FL 32611-0910, USA
| | - D Owen Rae
- Department of Large Animal Clinical Sciences, College of Veterinary Medicine, University of Florida, Gainesville 32610-0136, USA
| | - Colleen C Larson
- Okeechobee County Cooperative Extension Service, University of Florida/Institute of Food and Agricultural Sciences, Okeechobee, FL 34972, USA
| | - Marissa Macchietto
- Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, MN, USA
| | - Juan E Abrahante
- Informatics Institute, University of Minnesota, Minneapolis, MN 55455, USA
| | - Thiago F Amaral
- Department of Animal Sciences, D.H. Barron Reproductive and Perinatal Biology Research Program, and Genetics Institute, University of Florida, Gainesville, FL 32611-0910, USA
| | - Anna C Denicol
- Department of Animal Science, University of California Davis, Davis, CA 95616, USA
| | | | - Peter J Hansen
- Department of Animal Sciences, D.H. Barron Reproductive and Perinatal Biology Research Program, and Genetics Institute, University of Florida, Gainesville, FL 32611-0910, USA.
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13
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Utsunomiya YT, Fortunato AAAD, Milanesi M, Trigo BB, Alves NF, Sonstegard TS, Garcia JF. Bos taurus haplotypes segregating in Nellore (Bos indicus) cattle. Anim Genet 2021; 53:58-67. [PMID: 34921423 DOI: 10.1111/age.13164] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/10/2021] [Indexed: 11/29/2022]
Abstract
Brazil is the largest exporter of beef in the world, and most of that beef derives from Nellore cattle. Although considered a zebu breed (Bos indicus), the history of Nellore cattle in Brazil is marked by the importation of bulls from India, the use of a Creole taurine (Bos taurus) maternal lineage to quickly expand the herds and backcrossing to Nellore bulls to recover zebu ancestry. As a consequence, the current Brazilian Nellore population carries an average taurine ancestry of approximately 1%. Although that percentage seems small, some taurine variants deviate substantially from that average, with the better-known cases being the PLAG1-Q haplotype involved with body size variation and the Guarani (PG ) polled variant producing hornless animals. Here, we report taurine haplotypes in 9074 Nellore animals genotyped for 539 657 imputed SNP markers. Apart from PLAG1-Q and PG , our analysis further revealed common taurine haplotypes (>3%) spanning genes related to immunity, growth, reproduction and hair and skin phenotypes. Using data from 22 economically important traits, we showed that many of the major QTL previously reported in the breed are at least partially driven by taurine haplotypes. As B. taurus and B. indicus haplotypes are highly divergent, presenting widely different sets of functional variants, our results provide promising targets for future scrutiny in Nellore cattle.
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Affiliation(s)
- Y T Utsunomiya
- Department of Production and Animal Health, School of Veterinary Medicine of Araçatuba, São Paulo State University, 16050-680 R. Clovis Pestana 793 - Dona Amelia, Araçatuba, SP, Brazil.,International Atomic Energy Agency Collaborating Centre on Animal Genomics and Bioinformatics, 16050-680 R. Clovis Pestana 793 - Dona Amelia, Araçatuba, SP, Brazil.,AgroPartners Consulting. R. Floriano Peixoto, 120 - Sala 43A - Centro, Araçatuba, SP, 16010-220, Brazil
| | - A A A D Fortunato
- Department of Production and Animal Health, School of Veterinary Medicine of Araçatuba, São Paulo State University, 16050-680 R. Clovis Pestana 793 - Dona Amelia, Araçatuba, SP, Brazil.,International Atomic Energy Agency Collaborating Centre on Animal Genomics and Bioinformatics, 16050-680 R. Clovis Pestana 793 - Dona Amelia, Araçatuba, SP, Brazil.,Personal-PEC. R. Sebastião Lima, 1336 - Centro, Campo Grande, MS, 79004-600, Brazil
| | - M Milanesi
- AgroPartners Consulting. R. Floriano Peixoto, 120 - Sala 43A - Centro, Araçatuba, SP, 16010-220, Brazil.,Department for Innovation in Biological, Agro-Food and Forest Systems, Università Della Tuscia, Via S. Camillo de Lellis snc, Viterbo, 01100, Italy
| | - B B Trigo
- Department of Production and Animal Health, School of Veterinary Medicine of Araçatuba, São Paulo State University, 16050-680 R. Clovis Pestana 793 - Dona Amelia, Araçatuba, SP, Brazil.,International Atomic Energy Agency Collaborating Centre on Animal Genomics and Bioinformatics, 16050-680 R. Clovis Pestana 793 - Dona Amelia, Araçatuba, SP, Brazil
| | - N F Alves
- Department of Production and Animal Health, School of Veterinary Medicine of Araçatuba, São Paulo State University, 16050-680 R. Clovis Pestana 793 - Dona Amelia, Araçatuba, SP, Brazil.,International Atomic Energy Agency Collaborating Centre on Animal Genomics and Bioinformatics, 16050-680 R. Clovis Pestana 793 - Dona Amelia, Araçatuba, SP, Brazil
| | | | - J F Garcia
- Department of Production and Animal Health, School of Veterinary Medicine of Araçatuba, São Paulo State University, 16050-680 R. Clovis Pestana 793 - Dona Amelia, Araçatuba, SP, Brazil.,International Atomic Energy Agency Collaborating Centre on Animal Genomics and Bioinformatics, 16050-680 R. Clovis Pestana 793 - Dona Amelia, Araçatuba, SP, Brazil.,AgroPartners Consulting. R. Floriano Peixoto, 120 - Sala 43A - Centro, Araçatuba, SP, 16010-220, Brazil.,Department of Preventive Veterinary Medicine and Animal Reproduction, School of Agricultural and Veterinarian Sciences, São Paulo State University, 14884-900 Via de Acesso Prof. Paulo Donato Castellane s/n, Jaboticabal, SP, Brazil
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14
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Sosa F, Carmickle AT, Jiménez-Cabán E, Ortega MS, Dikmen S, Negrón-Pérez V, Jannaman EA, Baktula A, Rincon G, Larson CC, Pagán-Morales M, Denicol AC, Sonstegard TS, Hansen PJ. Inheritance of the SLICK1 allele of PRLR in cattle. Anim Genet 2021; 52:887-890. [PMID: 34642995 DOI: 10.1111/age.13145] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/23/2021] [Indexed: 11/30/2022]
Abstract
The slick-hair phenotype in cattle is due to one of a series of mutations in the prolactin receptor (PRLR) that cause truncation of the C-terminal region of the protein involved in JAK2/STAT5 activation during prolactin signaling. Here we evaluated whether the inheritance of the SLICK1 allele, the first slick mutation discovered, is inherited in a fashion consistent with Hardy-Weinberg equilibrium. It was hypothesized that any deleterious effect of inheriting the allele on embryonic or fetal function would result in reduced frequency of the allele in offspring. A total of 525 Holstein and Senepol cattle produced from matings involving one or both parents with the SLICK1 allele were genotyped. The observed frequency of the SLICK1 allele (0.247) was not significantly different than the expected frequency of 0.269. These results support the idea that inheritance of the SLICK1 allele does not act in the embryo or fetus to modify its competence to complete development to term.
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Affiliation(s)
- F Sosa
- Department of Animal Sciences, University of Florida, Gainesville, FL, 32611-0910, USA
| | - A T Carmickle
- Department of Animal Science, University of California, Davis, CA, 95616, USA
| | - E Jiménez-Cabán
- Department of Animal Science, University of Puerto Rico-Mayagüez, Mayagüez, PR, 00680, USA
| | - M S Ortega
- Division of Animal Sciences, University of Missouri, Columbia, MI, 65211, USA
| | - S Dikmen
- Department of Animal Science, Faculty of Veterinary Medicine, Bursa Uludağ University, Bursa, 16059, Turkey
| | - V Negrón-Pérez
- Department of Animal Science, University of Puerto Rico-Mayagüez, Mayagüez, PR, 00680, USA
| | - E A Jannaman
- Department of Animal Sciences, University of Florida, Gainesville, FL, 32611-0910, USA
| | | | - G Rincon
- Zoetis, Kalamazoo, MI, 49007, USA
| | - C C Larson
- Okeechobee County Cooperative Extension Service, University of Florida/Institute of Food and Agricultural Sciences, Okeechobee, FL, 34972, USA
| | - M Pagán-Morales
- Department of Animal Science, University of Puerto Rico-Mayagüez, Mayagüez, PR, 00680, USA
| | - A C Denicol
- Department of Animal Science, University of California, Davis, CA, 95616, USA
| | | | - P J Hansen
- Department of Animal Sciences, University of Florida, Gainesville, FL, 32611-0910, USA
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15
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Landaeta-Hernández AJ, Zambrano-Nava S, Verde O, Pinto-Santini L, Montero-Urdaneta M, Hernández-Fonseca JP, Fuenmayor-Morales C, Sonstegard TS, Huson HJ, Olson TA. Heat stress response in slick vs normal-haired Criollo Limonero heifers in a tropical environment. Trop Anim Health Prod 2021; 53:445. [PMID: 34427775 DOI: 10.1007/s11250-021-02856-3] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2020] [Accepted: 07/09/2021] [Indexed: 12/01/2022]
Abstract
To assess the effect of hair type on the heat stress response, 20 Criollo Limonero heifers with slick (n = 11) or normal hair (n = 9) were studied. Under a high temperature-humidity index (THI) environment, heat stress response was assessed through physiological variables that included respiration rate (RR), heart rate (HR), ruminal frequency (RMF), rectal temperature (RT), saliva pH (SPH), and lymphocyte count (LC) in the morning (5:00 AM, 27.4 °C, 64% relative humidity, THI = 77) and afternoon (1:00 PM, 34.5 °C, 70% relative humidity, THI = 88). A case-control study using a split plot design was used. Data were analyzed using ANOVA (PROC MIXED SAS 2010) and a statistical model comprising the fixed effects of hair length, sampling hour, interaction of hair length by sampling hour, and the random effect of animal nested within hair type on physiological variables associated with heat stress response. Sampling hour influenced (P < 0.0001) RR, RT, and (P < 0.003) SPH. Hair length influenced RR (P < 0.01) and RT (P < 0.04) and tended to influence LC (P < 0.07). The interaction of sampling hour by hair influenced RR (P < 0.04), RT (P < 0.0002), and both SPH and LC (P < 0.05). During afternoon hours, slick-haired heifers had lower values for RR (81 ± 4.2 vs 102 ± 4.7 bpm; P < 0.01), RT (39.5 ± 0.1 vs 40.3 ± 0.1 C°; P < 0.002), and LC (60 ± 3.2 vs 72.3 ± 3.6; P < 0.09) than normal-haired heifers. In normal-haired heifers, SPH increased during afternoon compared to morning-hours (8.66 ± 0.1 vs 9.11 ± 0.1; P < 0.04). It was concluded that slick-coated heifers exhibited an enhanced capability to cope with heat stress compared to normal-haired heifers likely due to an enhanced capacity for heat dissipation.
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Affiliation(s)
- A J Landaeta-Hernández
- Universidad del Zulia, Facultad de Ciencias Veterinarias, Unidad de Investigaciones Zootécnicas (UNIZ), Maracaibo, Venezuela.
| | - S Zambrano-Nava
- Universidad del Zulia, Facultad de Ciencias Veterinarias, Unidad de Investigaciones Zootécnicas (UNIZ), Maracaibo, Venezuela.,Instituto Nacional de Investigaciones Agrícolas (INIA), Maracaibo, Venezuela
| | - O Verde
- Facultad de Ciencias Veterinarias, Universidad Central de Venezuela, Maracay, Venezuela
| | - L Pinto-Santini
- Facultad de Veterinaria, Universidad de La República, Montevideo, Uruguay
| | - M Montero-Urdaneta
- Universidad del Zulia, Facultad de Ciencias Veterinarias, Unidad de Investigaciones Zootécnicas (UNIZ), Maracaibo, Venezuela
| | - J P Hernández-Fonseca
- Facultad de Medicina, Unidad de Investigaciones Clínicas Dr. Américo Negrette, Universidad del Zulia, Maracaibo, Venezuela
| | - C Fuenmayor-Morales
- Universidad del Zulia, Facultad de Ciencias Veterinarias, Unidad de Investigaciones Zootécnicas (UNIZ), Maracaibo, Venezuela
| | - T S Sonstegard
- Acceligen of Recombinetics Inc, 3388 Mike Collins Drive, Eagan, MN, USA
| | - H J Huson
- Department of Animal Sciences, University of Cornell, Ithaca, NY, USA
| | - T A Olson
- Department of Animal Sciences, University of Florida, P.O. Box 110920, Gainesville, FL, 32611-0910, USA
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16
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Trigo BB, Utsunomiya ATH, Fortunato AAAD, Milanesi M, Torrecilha RBP, Lamb H, Nguyen L, Ross EM, Hayes B, Padula RCM, Sussai TS, Zavarez LB, Cipriano RS, Caminhas MMT, Lopes FL, Pelle C, Leeb T, Bannasch D, Bickhart D, Smith TPL, Sonstegard TS, Garcia JF, Utsunomiya YT. Variants at the ASIP locus contribute to coat color darkening in Nellore cattle. Genet Sel Evol 2021; 53:40. [PMID: 33910501 PMCID: PMC8082809 DOI: 10.1186/s12711-021-00633-2] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2021] [Accepted: 04/16/2021] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Nellore cattle (Bos indicus) are well-known for their adaptation to warm and humid environments. Hair length and coat color may impact heat tolerance. The Nellore breed has been strongly selected for white coat, but bulls generally exhibit darker hair ranging from light grey to black on the head, neck, hump, and knees. Given the potential contribution of coat color variation to the adaptation of cattle populations to tropical and sub-tropical environments, our aim was to map positional and functional candidate genetic variants associated with darkness of hair coat (DHC) in Nellore bulls. RESULTS We performed a genome-wide association study (GWAS) for DHC using data from 432 Nellore bulls that were genotyped for more than 777 k single nucleotide polymorphism (SNP) markers. A single major association signal was detected in the vicinity of the agouti signaling protein gene (ASIP). The analysis of whole-genome sequence (WGS) data from 21 bulls revealed functional variants that are associated with DHC, including a structural rearrangement involving ASIP (ASIP-SV1). We further characterized this structural variant using Oxford Nanopore sequencing data from 13 Australian Brahman heifers, which share ancestry with Nellore cattle; we found that this variant originates from a 1155-bp deletion followed by an insertion of a transposable element of more than 150 bp that may impact the recruitment of ASIP non-coding exons. CONCLUSIONS Our results indicate that the variant ASIP sequence causes darker coat pigmentation on specific parts of the body, most likely through a decreased expression of ASIP and consequently an increased production of eumelanin.
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Affiliation(s)
- Beatriz B Trigo
- School of Veterinary Medicine, Araçatuba, Department of Production and Animal Health, São Paulo State University (Unesp), Araçatuba, SP, Brazil.,International Atomic Energy Agency (IAEA) Collaborating Centre On Animal Genomics and Bioinformatics, Araçatuba, SP, Brazil
| | - Adam T H Utsunomiya
- International Atomic Energy Agency (IAEA) Collaborating Centre On Animal Genomics and Bioinformatics, Araçatuba, SP, Brazil.,AgroPartners Consulting, R. Floriano Peixoto, 120-Sala 43a-Centro, Araçatuba, SP, 16010-220, Brazil
| | - Alvaro A A D Fortunato
- School of Veterinary Medicine, Araçatuba, Department of Production and Animal Health, São Paulo State University (Unesp), Araçatuba, SP, Brazil.,International Atomic Energy Agency (IAEA) Collaborating Centre On Animal Genomics and Bioinformatics, Araçatuba, SP, Brazil.,Personal-PEC, R. Sebastião Lima, 1336-Centro, Campo Grande, MS, 79004-600, Brazil
| | - Marco Milanesi
- School of Veterinary Medicine, Araçatuba, Department of Production and Animal Health, São Paulo State University (Unesp), Araçatuba, SP, Brazil.,International Atomic Energy Agency (IAEA) Collaborating Centre On Animal Genomics and Bioinformatics, Araçatuba, SP, Brazil.,AgroPartners Consulting, R. Floriano Peixoto, 120-Sala 43a-Centro, Araçatuba, SP, 16010-220, Brazil
| | - Rafaela B P Torrecilha
- International Atomic Energy Agency (IAEA) Collaborating Centre On Animal Genomics and Bioinformatics, Araçatuba, SP, Brazil.,AgroPartners Consulting, R. Floriano Peixoto, 120-Sala 43a-Centro, Araçatuba, SP, 16010-220, Brazil
| | - Harrison Lamb
- Centre for Animal Science, Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, Brisbane, Australia
| | - Loan Nguyen
- Centre for Animal Science, Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, Brisbane, Australia
| | - Elizabeth M Ross
- Centre for Animal Science, Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, Brisbane, Australia
| | - Ben Hayes
- Centre for Animal Science, Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, Brisbane, Australia
| | | | - Thayla S Sussai
- Centro Universitário Católico Salesiano, Araçatuba, SP, Brazil
| | - Ludmilla B Zavarez
- International Atomic Energy Agency (IAEA) Collaborating Centre On Animal Genomics and Bioinformatics, Araçatuba, SP, Brazil
| | | | - Maria M T Caminhas
- School of Veterinary Medicine, Araçatuba, Department of Production and Animal Health, São Paulo State University (Unesp), Araçatuba, SP, Brazil
| | - Flavia L Lopes
- School of Veterinary Medicine, Araçatuba, Department of Production and Animal Health, São Paulo State University (Unesp), Araçatuba, SP, Brazil
| | | | - Tosso Leeb
- Institute of Genetics, Vetsuisse-Faculty, University of Bern, Bremgartenstrasse 109A, 3012, Bern, Switzerland.,Dermfocus, University of Bern, Bremgartenstrasse 109A, 3012, Bern, Switzerland
| | - Danika Bannasch
- Institute of Genetics, Vetsuisse-Faculty, University of Bern, Bremgartenstrasse 109A, 3012, Bern, Switzerland.,Department of Population Health and Reproduction, School of Veterinary Medicine, University of California, Davis, CA, 95616, USA
| | - Derek Bickhart
- Dairy Forage Research Center, USDA-ARS, 1925 Linden Drive, Madison, WI, 53706, USA
| | - Timothy P L Smith
- US. Meat Animal Research Center, USDA-ARS, 844 Road 313, Clay Center, NE, 68933, USA
| | | | - José F Garcia
- School of Veterinary Medicine, Araçatuba, Department of Production and Animal Health, São Paulo State University (Unesp), Araçatuba, SP, Brazil.,International Atomic Energy Agency (IAEA) Collaborating Centre On Animal Genomics and Bioinformatics, Araçatuba, SP, Brazil.,AgroPartners Consulting, R. Floriano Peixoto, 120-Sala 43a-Centro, Araçatuba, SP, 16010-220, Brazil.,School of Agriculture and Veterinarian Sciences, Jaboticabal, Department of Preventive Veterinary Medicine and Animal Reproduction, São Paulo State University (Unesp), Jaboticabal, SP, Brazil
| | - Yuri T Utsunomiya
- School of Veterinary Medicine, Araçatuba, Department of Production and Animal Health, São Paulo State University (Unesp), Araçatuba, SP, Brazil. .,International Atomic Energy Agency (IAEA) Collaborating Centre On Animal Genomics and Bioinformatics, Araçatuba, SP, Brazil. .,AgroPartners Consulting, R. Floriano Peixoto, 120-Sala 43a-Centro, Araçatuba, SP, 16010-220, Brazil.
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17
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Flórez Murillo JM, Landaeta-Hernández AJ, Kim ES, Bostrom JR, Larson SA, Pérez O'Brien AM, Montero-Urdaneta MA, Garcia JF, Sonstegard TS. Three novel nonsense mutations of prolactin receptor found in heat-tolerant Bos taurus breeds of the Caribbean Basin. Anim Genet 2020; 52:132-134. [PMID: 33259090 DOI: 10.1111/age.13027] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/10/2020] [Indexed: 12/24/2022]
Affiliation(s)
- Julio M Flórez Murillo
- Acceligen Inc., Eagan, MN, 55121, USA.,Department of Preventive Veterinary Medicine and Animal Reproduction, School of Agricultural and Veterinarian Sciences, São Paulo State University (Unesp), 14884-900 Via de Acesso Prof. Paulo Donato Castellane s/n, Jaboticabal, São Paulo, Brazil
| | - Antonio J Landaeta-Hernández
- School of Veterinary Sciences, Zootechnical Research Unit, University of Zulia, Av. Guajira, Maracaibo, Zulia, Venezuela
| | | | | | | | | | - Merilio A Montero-Urdaneta
- School of Veterinary Sciences, Zootechnical Research Unit, University of Zulia, Av. Guajira, Maracaibo, Zulia, Venezuela
| | - José F Garcia
- Department of Preventive Veterinary Medicine and Animal Reproduction, School of Agricultural and Veterinarian Sciences, São Paulo State University (Unesp), 14884-900 Via de Acesso Prof. Paulo Donato Castellane s/n, Jaboticabal, São Paulo, Brazil.,Department of Animal Production and Health, School of Veterinary Medicine, São Paulo State University (Unesp), 16050-680 R. Clóvis Pestana 793 - Dona Amelia, Araçatuba, São Paulo, Brazil.,International Atomic Energy Agency Collaborating Centre on Animal Genomics and Bioinformatics, 16050-680 R. Clóvis Pestana 793 - Dona Amelia, Araçatuba, São Paulo, Brazil
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18
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Hu Y, Xia H, Li M, Xu C, Ye X, Su R, Zhang M, Nash O, Sonstegard TS, Yang L, Liu GE, Zhou Y. Comparative analyses of copy number variations between Bos taurus and Bos indicus. BMC Genomics 2020; 21:682. [PMID: 33004001 PMCID: PMC7528262 DOI: 10.1186/s12864-020-07097-6] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2020] [Accepted: 09/23/2020] [Indexed: 12/15/2022] Open
Abstract
Background Bos taurus and Bos indicus are two main sub-species of cattle. However, the differential copy number variations (CNVs) between them are not yet well studied. Results Based on the new high-quality cattle reference genome ARS-UCD1.2, we identified 13,234 non-redundant CNV regions (CNVRs) from 73 animals of 10 cattle breeds (4 Bos taurus and 6 Bos indicus), by integrating three detection strategies. While 6990 CNVRs (52.82%) were shared by Bos taurus and Bos indicus, large CNV differences were discovered between them and these differences could be used to successfully separate animals into two subspecies. We found that 2212 and 538 genes uniquely overlapped with either indicine-specific CNVRs and or taurine-specific CNVRs, respectively. Based on FST, we detected 16 candidate lineage-differential CNV segments (top 0.1%) under selection, which overlapped with eight genes (CTNNA1, ENSBTAG00000004415, PKN2, BMPER, PDE1C, DNAJC18, MUSK, and PLCXD3). Moreover, we obtained 1.74 Mbp indicine-specific sequences, which could only be mapped on the Bos indicus reference genome UOA_Brahman_1. We found these sequences and their associated genes were related to heat resistance, lipid and ATP metabolic process, and muscle development under selection. We further analyzed and validated the top significant lineage-differential CNV. This CNV overlapped genes related to muscle cell differentiation, which might be generated from a retropseudogene of CTH but was deleted along Bos indicus lineage. Conclusions This study presents a genome wide CNV comparison between Bos taurus and Bos indicus. It supplied essential genome diversity information for understanding of adaptation and phenotype differences between the Bos taurus and Bos indicus populations.
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Affiliation(s)
- Yan Hu
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070, China
| | - Han Xia
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070, China
| | - Mingxun Li
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Building 306, Room 111, BARC-East, Beltsville, MD, 20705, USA.,College of Animal Science and Technology, Yangzhou University, Yangzhou, 225009, China
| | - Chang Xu
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070, China
| | - Xiaowei Ye
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070, China
| | - Ruixue Su
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070, China
| | - Mai Zhang
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070, China
| | - Oyekanmi Nash
- Centre for Genomics Research and Innovation, National Biotechnology Development Agency, Abuja, Nigeria
| | | | - Liguo Yang
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070, China
| | - George E Liu
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Building 306, Room 111, BARC-East, Beltsville, MD, 20705, USA.
| | - Yang Zhou
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070, China.
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19
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Zheng Z, Wang X, Li M, Li Y, Yang Z, Wang X, Pan X, Gong M, Zhang Y, Guo Y, Wang Y, Liu J, Cai Y, Chen Q, Okpeku M, Colli L, Cai D, Wang K, Huang S, Sonstegard TS, Esmailizadeh A, Zhang W, Zhang T, Xu Y, Xu N, Yang Y, Han J, Chen L, Lesur J, Daly KG, Bradley DG, Heller R, Zhang G, Wang W, Chen Y, Jiang Y. The origin of domestication genes in goats. Sci Adv 2020; 6:eaaz5216. [PMID: 32671210 PMCID: PMC7314551 DOI: 10.1126/sciadv.aaz5216] [Citation(s) in RCA: 62] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/16/2019] [Accepted: 03/06/2020] [Indexed: 05/22/2023]
Abstract
Goat domestication was critical for agriculture and civilization, but its underlying genetic changes and selection regimes remain unclear. Here, we analyze the genomes of worldwide domestic goats, wild caprid species, and historical remains, providing evidence of an ancient introgression event from a West Caucasian tur-like species to the ancestor of domestic goats. One introgressed locus with a strong signature of selection harbors the MUC6 gene, which encodes a gastrointestinally secreted mucin. Experiments revealed that the nearly fixed introgressed haplotype confers enhanced immune resistance to gastrointestinal pathogens. Another locus with a strong signal of selection may be related to behavior. The selected alleles at these two loci emerged in domestic goats at least 7200 and 8100 years ago, respectively, and increased to high frequencies concurrent with the expansion of the ubiquitous modern mitochondrial haplogroup A. Tracking these archaeologically cryptic evolutionary transformations provides new insights into the mechanisms of animal domestication.
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Affiliation(s)
- Zhuqing Zheng
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Xihong Wang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Ming Li
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Yunjia Li
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Zhirui Yang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Xiaolong Wang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Xiangyu Pan
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Mian Gong
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Yu Zhang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Yingwei Guo
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Yu Wang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Jing Liu
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Yudong Cai
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Qiuming Chen
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Moses Okpeku
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
- Discipline of Genetics, School of Life Science, University of Kwazulu-Natal, Durban 4000, South Africa
| | - Licia Colli
- Dipartimento di Scienze Animali, della Nutrizione e degli Alimenti, Facoltà di Scienze Agrarie, Alimentari e Ambientali, Università Cattolica del S. Cuore, via Emilia Parmense n. 84, 29122, Piacenza (PC), Italy
- BioDNA–Centro di Ricerca sulla Biodiversità e sul DNA Antico, Facoltà di Scienze Agrarie, Alimentari e Ambientali, Università Cattolica del S. Cuore, via Emilia Parmense n. 84, 29122, Piacenza (PC), Italy
| | - Dawei Cai
- Research Center for Chinese Frontier Archaeology, Jilin University, Changchun 130012, China
| | - Kun Wang
- Center for Ecological and Environmental Sciences, Northwestern Polytechnical University, Xi’an 710072, China
| | - Shisheng Huang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | | | - Ali Esmailizadeh
- Department of Animal Science, Faculty of Agriculture, Shahid Bahonar University of Kerman, Kerman, PB 76169-133, Iran
| | - Wenguang Zhang
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot 010018, China
| | - Tingting Zhang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Yangbin Xu
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Naiyi Xu
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Yi Yang
- Institute of Preventive Veterinary Medicine, Zhejiang Provincial Key Laboratory of Preventive Veterinary Medicine, College of Animal Sciences, Zhejiang University, Hangzhou 310058, China
| | - Jianlin Han
- CAAS-ILRI Joint Laboratory on Livestock and Forage Genetic Resources, Institute of Animal Science, Chinese Academy of Agriculture Sciences (CAAS), Beijing 100193, China
- International Livestock Research Institute (ILRI), Nairobi 00100, Kenya
| | - Lei Chen
- Center for Ecological and Environmental Sciences, Northwestern Polytechnical University, Xi’an 710072, China
| | | | - Kevin G. Daly
- Smurfit Institute of Genetics, Trinity College Dublin, Dublin 2, Ireland
| | - Daniel G. Bradley
- Smurfit Institute of Genetics, Trinity College Dublin, Dublin 2, Ireland
| | - Rasmus Heller
- Section for Computational and RNA Biology, Department of Biology, University of Copenhagen, Copenhagen N 2200, Denmark
| | - Guojie Zhang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
- China National GeneBank, BGI-Shenzhen, Shenzhen 518083, China
- Section for Ecology and Evolution, Department of Biology, University of Copenhagen, DK-2100 Copenhagen, Denmark
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming 650223, China
| | - Wen Wang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
- Center for Ecological and Environmental Sciences, Northwestern Polytechnical University, Xi’an 710072, China
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming 650223, China
| | - Yulin Chen
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Yu Jiang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
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20
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Fang L, Cai W, Liu S, Canela-Xandri O, Gao Y, Jiang J, Rawlik K, Li B, Schroeder SG, Rosen BD, Li CJ, Sonstegard TS, Alexander LJ, Van Tassell CP, VanRaden PM, Cole JB, Yu Y, Zhang S, Tenesa A, Ma L, Liu GE. Comprehensive analyses of 723 transcriptomes enhance genetic and biological interpretations for complex traits in cattle. Genome Res 2020; 30:790-801. [PMID: 32424068 PMCID: PMC7263193 DOI: 10.1101/gr.250704.119] [Citation(s) in RCA: 72] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2019] [Accepted: 05/01/2020] [Indexed: 12/13/2022]
Abstract
By uniformly analyzing 723 RNA-seq data from 91 tissues and cell types, we built a comprehensive gene atlas and studied tissue specificity of genes in cattle. We demonstrated that tissue-specific genes significantly reflected the tissue-relevant biology, showing distinct promoter methylation and evolution patterns (e.g., brain-specific genes evolve slowest, whereas testis-specific genes evolve fastest). Through integrative analyses of those tissue-specific genes with large-scale genome-wide association studies, we detected relevant tissues/cell types and candidate genes for 45 economically important traits in cattle, including blood/immune system (e.g., CCDC88C) for male fertility, brain (e.g., TRIM46 and RAB6A) for milk production, and multiple growth-related tissues (e.g., FGF6 and CCND2) for body conformation. We validated these findings by using epigenomic data across major somatic tissues and sperm. Collectively, our findings provided novel insights into the genetic and biological mechanisms underlying complex traits in cattle, and our transcriptome atlas can serve as a primary source for biological interpretation, functional validation, studies of adaptive evolution, and genomic improvement in livestock.
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Affiliation(s)
- Lingzhao Fang
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, Maryland 20705, USA
- Department of Animal and Avian Sciences, University of Maryland, College Park, Maryland 20742, USA
- The Roslin Institute, Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Midlothian EH25 9RG, United Kingdom
- Medical Research Council Human Genetics Unit at the Medical Research Council Institute of Genetics and Molecular Medicine, The University of Edinburgh, Edinburgh EH4 2XU, United Kingdom
| | - Wentao Cai
- Department of Animal and Avian Sciences, University of Maryland, College Park, Maryland 20742, USA
- College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Shuli Liu
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, Maryland 20705, USA
- College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Oriol Canela-Xandri
- The Roslin Institute, Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Midlothian EH25 9RG, United Kingdom
- Medical Research Council Human Genetics Unit at the Medical Research Council Institute of Genetics and Molecular Medicine, The University of Edinburgh, Edinburgh EH4 2XU, United Kingdom
| | - Yahui Gao
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, Maryland 20705, USA
- Department of Animal and Avian Sciences, University of Maryland, College Park, Maryland 20742, USA
| | - Jicai Jiang
- Department of Animal and Avian Sciences, University of Maryland, College Park, Maryland 20742, USA
| | - Konrad Rawlik
- The Roslin Institute, Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Midlothian EH25 9RG, United Kingdom
| | - Bingjie Li
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, Maryland 20705, USA
| | - Steven G Schroeder
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, Maryland 20705, USA
| | - Benjamin D Rosen
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, Maryland 20705, USA
| | - Cong-Jun Li
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, Maryland 20705, USA
| | | | - Leeson J Alexander
- Fort Keogh Livestock and Range Research Laboratory, Agricultural Research Service, USDA, Miles City, Montana 59301, USA
| | - Curtis P Van Tassell
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, Maryland 20705, USA
| | - Paul M VanRaden
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, Maryland 20705, USA
| | - John B Cole
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, Maryland 20705, USA
| | - Ying Yu
- College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Shengli Zhang
- College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Albert Tenesa
- The Roslin Institute, Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Midlothian EH25 9RG, United Kingdom
- Medical Research Council Human Genetics Unit at the Medical Research Council Institute of Genetics and Molecular Medicine, The University of Edinburgh, Edinburgh EH4 2XU, United Kingdom
| | - Li Ma
- Department of Animal and Avian Sciences, University of Maryland, College Park, Maryland 20742, USA
| | - George E Liu
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, Maryland 20705, USA
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21
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Huson HJ, Sonstegard TS, Godfrey J, Hambrook D, Wolfe C, Wiggans G, Blackburn H, VanTassell CP. A Genetic Investigation of Island Jersey Cattle, the Foundation of the Jersey Breed: Comparing Population Structure and Selection to Guernsey, Holstein, and United States Jersey Cattle. Front Genet 2020; 11:366. [PMID: 32362912 PMCID: PMC7181675 DOI: 10.3389/fgene.2020.00366] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2019] [Accepted: 03/25/2020] [Indexed: 11/15/2022] Open
Abstract
For two centuries, Jersey cattle were exported globally, adapting to varying climates and production systems, yet the founding population remained genetically isolated on the Island of Jersey. The Island of Jersey formally allowed the importation of pure Jersey cattle in 2008. This study characterized the genetic variation of 49 popular bulls from the Island of Jersey born from 1964 to 2004 and compared them to 47 non-Island Jersey bulls and cows, primarily from the United States In addition, 21 Guernsey cattle derived from the Island of Guernsey and 71 Holstein cattle served as reference populations for genetic comparison. Cattle were genotyped on the Illumina BovineHD Beadchip producing 777,962 SNPs spanning the genome. Principal component analysis revealed population stratification within breed reflective of individual animal’s continental origin. When compared to Holstein and Guernsey, all Jersey clustered together by breed. The Jersey breed demonstrated increased inbreeding in comparison to Holstein or Guernsey with slightly higher estimates of inbreeding coefficients and identity-by-descent. The Island and United States Jersey have relatively similar, yet statistically different inbreeding estimates despite vastly different population sizes and gene flow. Signatures of selection within Island Jersey were identified using genome-wide homozygosity association and marker-based FST that provided population informative single-nucleotide polymorphism (SNPs). Biological significance of the homozygosity association results identified multiple genes on chromosomes 5, 24, and 27, involved in immune function and cellular processes. Overall, genomic variation was identified between the Island and non-Island Jersey cattle producing population informative SNPs and differing runs of homozygosity (ROH) over immune regulation and metabolic genes. Results on inbreeding measures and ROH may reflect varying effective population size or differential selection with grazing systems promoting natural selection for traits such as parasite resistance, whereas confinement systems demonstrate a more intensive artificial selection. More broadly, differences in breed formation, particularly between the two Channel Island breeds, likely contributed to the variation in ROH and inbreeding. This research provides a reference for the Jersey breed based on the genetic foundation of the Island cattle as compared to the intensively selected United States cattle, and identifies regions of the genome for future investigation of immune regulation and metabolic processes.
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Affiliation(s)
- Heather J Huson
- Department of Animal Science, Cornell University, Ithaca, NY, United States
| | | | - James Godfrey
- Royal Jersey Agricultural & Horticultural Society, Trinity, Jersey, United Kingdom
| | - David Hambrook
- Royal Jersey Agricultural & Horticultural Society, Trinity, Jersey, United Kingdom
| | - Cari Wolfe
- American Jersey Cattle Association, Reynoldsburg, OH, United States
| | - George Wiggans
- Council on Dairy Cattle Breeding, Bowie, MD, United States
| | - Harvey Blackburn
- National Animal Germplasm Program, USDA-ARS, Fort Collins, CO, United States
| | - Curtis P VanTassell
- Animal Genomics and Improvement Laboratory, USDA-ARS, Beltsville, MD, United States
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22
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Wang Y, Zhang C, Wang N, Li Z, Heller R, Liu R, Zhao Y, Han J, Pan X, Zheng Z, Dai X, Chen C, Dou M, Peng S, Chen X, Liu J, Li M, Wang K, Liu C, Lin Z, Chen L, Hao F, Zhu W, Song C, Zhao C, Zheng C, Wang J, Hu S, Li C, Yang H, Jiang L, Li G, Liu M, Sonstegard TS, Zhang G, Jiang Y, Wang W, Qiu Q. Genetic basis of ruminant headgear and rapid antler regeneration. Science 2020; 364:364/6446/eaav6335. [PMID: 31221830 DOI: 10.1126/science.aav6335] [Citation(s) in RCA: 98] [Impact Index Per Article: 24.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2018] [Accepted: 05/16/2019] [Indexed: 12/11/2022]
Abstract
Ruminants are the only extant mammalian group possessing bony (osseous) headgear. We obtained 221 transcriptomes from bovids and cervids and sequenced three genomes representing the only two pecoran lineages that convergently lack headgear. Comparative analyses reveal that bovid horns and cervid antlers share similar gene expression profiles and a common cellular basis developed from neural crest stem cells. The rapid regenerative properties of antler tissue involve exploitation of oncogenetic pathways, and at the same time some tumor suppressor genes are under strong selection in deer. These results provide insights into the evolutionary origin of ruminant headgear as well as mammalian organ regeneration and oncogenesis.
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Affiliation(s)
- Yu Wang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Chenzhou Zhang
- Center for Ecological and Environmental Sciences, Northwestern Polytechnical University, Xi'an 710072, China
| | - Nini Wang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Zhipeng Li
- Department of Special Animal Nutrition and Feed Science, Institute of Special Animal and Plant Sciences, Chinese Academy of Agricultural Sciences, Changchun 130112, China
| | - Rasmus Heller
- Section for Computational and RNA Biology, Department of Biology, University of Copenhagen, DK-2100 Copenhagen, Denmark
| | - Rong Liu
- Key Laboratory of Animal Models and Human Disease Mechanisms of Chinese Academy of Sciences and Yunnan Province, Chinese Academy of Sciences, Kunming Institute of Zoology, Kunming, Yunnan 650223, China.,Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming 650223, China
| | - Yue Zhao
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Jiangang Han
- Institute of Animal Science (IAS), Chinese Academy of Agricultural Sciences (CAAS), Beijing 100193, China
| | - Xiangyu Pan
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Zhuqing Zheng
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Xueqin Dai
- Key Laboratory of Animal Models and Human Disease Mechanisms of Chinese Academy of Sciences and Yunnan Province, Chinese Academy of Sciences, Kunming Institute of Zoology, Kunming, Yunnan 650223, China.,Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming 650223, China
| | - Ceshi Chen
- Key Laboratory of Animal Models and Human Disease Mechanisms of Chinese Academy of Sciences and Yunnan Province, Chinese Academy of Sciences, Kunming Institute of Zoology, Kunming, Yunnan 650223, China.,Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming 650223, China
| | - Mingle Dou
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Shujun Peng
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Xianqing Chen
- Center for Ecological and Environmental Sciences, Northwestern Polytechnical University, Xi'an 710072, China
| | - Jing Liu
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Ming Li
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Kun Wang
- Center for Ecological and Environmental Sciences, Northwestern Polytechnical University, Xi'an 710072, China
| | - Chang Liu
- Center for Ecological and Environmental Sciences, Northwestern Polytechnical University, Xi'an 710072, China
| | - Zeshan Lin
- Center for Ecological and Environmental Sciences, Northwestern Polytechnical University, Xi'an 710072, China
| | - Lei Chen
- Center for Ecological and Environmental Sciences, Northwestern Polytechnical University, Xi'an 710072, China
| | - Fei Hao
- Center of Special Environmental Biomechanics and Biomedical Engineering, School of Life Sciences, Northwestern Polytechnical University, Xi'an 710072, China
| | - Wenbo Zhu
- Center for Ecological and Environmental Sciences, Northwestern Polytechnical University, Xi'an 710072, China
| | - Chengchuang Song
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Chen Zhao
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Chengli Zheng
- Sichuan Institute of Musk Deer Breeding, Sichuan 610000, China
| | - Jianming Wang
- Sichuan Institute of Musk Deer Breeding, Sichuan 610000, China
| | - Shengwei Hu
- College of Life Sciences, Shihezi University, Shihezi, Xinjiang 832003, China
| | - Cunyuan Li
- College of Life Sciences, Shihezi University, Shihezi, Xinjiang 832003, China
| | - Hui Yang
- Center of Special Environmental Biomechanics and Biomedical Engineering, School of Life Sciences, Northwestern Polytechnical University, Xi'an 710072, China
| | - Lin Jiang
- Institute of Animal Science (IAS), Chinese Academy of Agricultural Sciences (CAAS), Beijing 100193, China
| | - Guangyu Li
- Department of Special Animal Nutrition and Feed Science, Institute of Special Animal and Plant Sciences, Chinese Academy of Agricultural Sciences, Changchun 130112, China
| | - Mingjun Liu
- The Key Laboratory of Animal Biotechnology of Xinjiang, Xinjiang Academy of Animal Science, Xinjiang, Urumqi 830026, China
| | | | - Guojie Zhang
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming 650223, China.,China National GeneBank, BGI-Shenzhen, Shenzhen 518083, China.,State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China.,Section for Ecology and Evolution, Department of Biology, University of Copenhagen, DK-2100 Copenhagen, Denmark
| | - Yu Jiang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China.
| | - Wen Wang
- Center for Ecological and Environmental Sciences, Northwestern Polytechnical University, Xi'an 710072, China. .,Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming 650223, China.,State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
| | - Qiang Qiu
- Center for Ecological and Environmental Sciences, Northwestern Polytechnical University, Xi'an 710072, China.
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23
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Chen N, Fu W, Zhao J, Shen J, Chen Q, Zheng Z, Chen H, Sonstegard TS, Lei C, Jiang Y. BGVD: An Integrated Database for Bovine Sequencing Variations and Selective Signatures. Genomics Proteomics Bioinformatics 2020; 18:186-193. [PMID: 32540200 PMCID: PMC7646086 DOI: 10.1016/j.gpb.2019.03.007] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/30/2018] [Revised: 11/16/2018] [Accepted: 03/29/2019] [Indexed: 11/30/2022]
Abstract
Next-generation sequencing has yielded a vast amount of cattle genomic data for global characterization of population genetic diversity and identification of genomic regions under natural and artificial selection. However, efficient storage, querying, and visualization of such large datasets remain challenging. Here, we developed a comprehensive database, the Bovine Genome Variation Database (BGVD). It provides six main functionalities: gene search, variation search, genomic signature search, Genome Browser, alignment search tools, and the genome coordinate conversion tool. BGVD contains information on genomic variations comprising ~60.44 M SNPs, ~6.86 M indels, 76,634 CNV regions, and signatures of selective sweeps in 432 samples from modern cattle worldwide. Users can quickly retrieve distribution patterns of these variations for 54 cattle breeds through an interactive source of breed origin map, using a given gene symbol or genomic region for any of the three versions of the bovine reference genomes (ARS-UCD1.2, UMD3.1.1, and Btau 5.0.1). Signals of selection sweep are displayed as Manhattan plots and Genome Browser tracks. To further investigate and visualize the relationships between variants and signatures of selection, the Genome Browser integrates all variations, selection data, and resources, from NCBI, the UCSC Genome Browser, and Animal QTLdb. Collectively, all these features make the BGVD a useful archive for in-depth data mining and analyses of cattle biology and cattle breeding on a global scale. BGVD is publicly available at http://animal.nwsuaf.edu.cn/BosVar.
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Affiliation(s)
- Ningbo Chen
- Key Laboratory of Animal Genetics, Breeding and Reproduction Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Weiwei Fu
- Key Laboratory of Animal Genetics, Breeding and Reproduction Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Jianbang Zhao
- College of Information Engineering, Northwest A&F University, Yangling 712100, China
| | - Jiafei Shen
- Key Laboratory of Animal Genetics, Breeding and Reproduction Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Qiuming Chen
- Key Laboratory of Animal Genetics, Breeding and Reproduction Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Zhuqing Zheng
- Key Laboratory of Animal Genetics, Breeding and Reproduction Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Hong Chen
- Key Laboratory of Animal Genetics, Breeding and Reproduction Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | | | - Chuzhao Lei
- Key Laboratory of Animal Genetics, Breeding and Reproduction Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Yu Jiang
- Key Laboratory of Animal Genetics, Breeding and Reproduction Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China.
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24
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Abstract
Horns are paired appendages on the head of bovine species, comprising an inner bony core and outer keratin sheath. The horn bud forms during early fetal development but ossification of the developing horn does not occur until approximately 1 month after birth. Little is known about the genetic pathways that lead to horn growth. Hornless, or polled, animals are found in all domestic bovids. Histological studies of bovine fetuses have shown that the horn bud does not form in polled individuals. There are currently four known genetic variants for polledness in cattle on BTA1. All of the variants are intergenic, but probably affect regulation of nearby genes or long non-coding RNAs. Transcriptomic studies suggest that the expression of two nearby long non-coding RNAs are affected by the Celtic POLLED variant, but further studies are required to confirm these data. Candidate genes located elsewhere in the genome are involved in regulating bone formation and epithelial-to-mesenchymal transition. Expression of one of these candidate genes, RXFP2, appears to be reduced in the fetal horn bud of polled animals carrying the Celtic variant compared with horned individuals. Investigating horn ontogenesis and the genetic pathway by which the POLLED variants prevent horn development has implications for cattle breeding. If the genetic basis of horn bud formation and polledness is better understood, then new targets may be identified for precision genome editing to create polled individuals.
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Affiliation(s)
- J E Aldersey
- Davies Research Centre, School of Animal and Veterinary Sciences, University of Adelaide, Roseworthy Campus, Adelaide, SA, 5371, Australia
| | | | - J L Williams
- Davies Research Centre, School of Animal and Veterinary Sciences, University of Adelaide, Roseworthy Campus, Adelaide, SA, 5371, Australia
| | - C D K Bottema
- Davies Research Centre, School of Animal and Veterinary Sciences, University of Adelaide, Roseworthy Campus, Adelaide, SA, 5371, Australia
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25
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McCarthy FM, Pendarvis K, Cooksey AM, Gresham CR, Bomhoff M, Davey S, Lyons E, Sonstegard TS, Bridges SM, Burgess SC. Chickspress: a resource for chicken gene expression. Database (Oxford) 2020; 2019:5512474. [PMID: 31210271 PMCID: PMC6556980 DOI: 10.1093/database/baz058] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/13/2018] [Revised: 03/07/2019] [Accepted: 04/15/2019] [Indexed: 12/12/2022]
Abstract
High-throughput sequencing and proteomics technologies are markedly increasing the amount of RNA and peptide data that are available to researchers, which are typically made publicly available via data repositories such as the NCBI Sequence Read Archive and proteome archives, respectively. These data sets contain valuable information about when and where gene products are expressed, but this information is not readily obtainable from archived data sets. Here we report Chickspress (http://geneatlas.arl.arizona.edu), the first publicly available gene expression resource for chicken tissues. Since there is no single source of chicken gene models, Chickspress incorporates both NCBI and Ensembl gene models and links these gene sets with experimental gene expression data and QTL information. By linking gene models from both NCBI and Ensembl gene prediction pipelines, researchers can, for the first time, easily compare gene models from each of these prediction workflows to available experimental data for these products. We use Chickspress data to show the differences between these gene annotation pipelines. Chickspress also provides rapid search, visualization and download capacity for chicken gene sets based upon tissue type, developmental stage and experiment type. This first Chickspress release contains 161 gene expression data sets, including expression of mRNAs, miRNAs, proteins and peptides. We provide several examples demonstrating how researchers may use this resource.
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Affiliation(s)
- Fiona M McCarthy
- School of Animal and Comparative Biomedical Sciences, University of Arizona, Tucson AZ, USA
| | - Ken Pendarvis
- School of Animal and Comparative Biomedical Sciences, University of Arizona, Tucson AZ, USA
| | - Amanda M Cooksey
- School of Animal and Comparative Biomedical Sciences, University of Arizona, Tucson AZ, USA
| | - Cathy R Gresham
- Institute of Genomics, Biocomputing & Biotechnology, Mississippi State University, Starkville MS, USA
| | - Matt Bomhoff
- School of Plant Sciences, CyVerse, University of Arizona, Tucson AZ , USA
| | - Sean Davey
- School of Plant Sciences, CyVerse, University of Arizona, Tucson AZ , USA
| | - Eric Lyons
- School of Plant Sciences, CyVerse, University of Arizona, Tucson AZ , USA
| | - Tad S Sonstegard
- United States Department of Agriculture Agricultural Research Service Beltsville Agricultural Research Center, Beltsville MD, USA
| | - Susan M Bridges
- Department of Computer Science and Engineering, Mississippi State University, Starkville MS, USA
| | - Shane C Burgess
- School of Animal and Comparative Biomedical Sciences, University of Arizona, Tucson AZ, USA
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26
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Upadhyay M, Bortoluzzi C, Barbato M, Ajmone‐Marsan P, Colli L, Ginja C, Sonstegard TS, Bosse M, Lenstra JA, Groenen MAM, Crooijmans RPMA. Deciphering the patterns of genetic admixture and diversity in southern European cattle using genome-wide SNPs. Evol Appl 2019; 12:951-963. [PMID: 31080507 PMCID: PMC6503822 DOI: 10.1111/eva.12770] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2018] [Revised: 12/23/2018] [Accepted: 12/27/2018] [Indexed: 01/10/2023] Open
Abstract
The divergence between indicine cattle (Bos indicus) and taurine cattle (Bos taurus) is estimated to have occurred approximately 250,000 years ago, but a small number of European cattle breeds still display shared ancestry with indicine cattle. Additionally, following the divergence of African and European taurine, the gene flow between African taurine and southern European cattle has also been proposed. However, the extent to which non-European cattle ancestry is diffused across southern European cattle has not been investigated thoroughly. Also, in recent times, many local breeds have suffered severe reductions in effective population size. Therefore, in the present study, we investigated the pattern of genetic diversity in various European cattle based on single nucleotide polymorphisms (SNP) identified from whole-genome sequencing data. Additionally, we also employed unlinked and phased SNP-based approaches on high-density SNP array data to characterize non-European cattle ancestry in several southern European cattle breeds. Using heterozygosity-based parameters, we concluded that, on average, nucleotide diversity is greater in southern European cattle than western European (British and commercial) cattle. However, an abundance of long runs of homozygosity (ROH) and the pattern of Linkage disequilibrium decay suggested recent bottlenecks in Maltese and Romagnola. High nucleotide diversity outside ROH indicated a highly diverse founder population for southern European and African taurine. We also show that Iberian cattle display shared ancestry with African cattle. Furthermore, we show that Podolica is an ancient cross-bred between Indicine zebu and European taurine. Additionally, we also inferred similar ancestry profile of non-European cattle ancestry in different Balkan and Italian cattle breeds which might be an indication of the common origin of indicine ancestry in these breeds. Finally, we discuss several plausible demographic scenarios which might account for the presence of non-European cattle ancestry in these cattle breeds.
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Affiliation(s)
- Maulik Upadhyay
- Animal Breeding and GenomicsWageningen University & ResearchWageningenThe Netherlands
- Department of Animal Breeding and GeneticsSwedish University of Agricultural SciencesUppsalaSweden
| | - Chiara Bortoluzzi
- Animal Breeding and GenomicsWageningen University & ResearchWageningenThe Netherlands
| | - Mario Barbato
- Department of Animal Science, Food and Nutrition – DIANA, Nutrigenomics and Proteomics Research Centre – PRONUTRIGEN, Biodiversity and Ancient DNA Research Centre – BioDNAUniversità Cattolica del Sacro CuorePiacenzaItaly
| | - Paolo Ajmone‐Marsan
- Department of Animal Science, Food and Nutrition – DIANA, Nutrigenomics and Proteomics Research Centre – PRONUTRIGEN, Biodiversity and Ancient DNA Research Centre – BioDNAUniversità Cattolica del Sacro CuorePiacenzaItaly
| | - Licia Colli
- Department of Animal Science, Food and Nutrition – DIANA, Nutrigenomics and Proteomics Research Centre – PRONUTRIGEN, Biodiversity and Ancient DNA Research Centre – BioDNAUniversità Cattolica del Sacro CuorePiacenzaItaly
| | - Catarina Ginja
- CIBIO‐InBIO—Centro de Investigação em Biodiversidade e Recursos GenéticosUniversidade do PortoVairaoPortugal
| | | | - Mirte Bosse
- Animal Breeding and GenomicsWageningen University & ResearchWageningenThe Netherlands
| | | | - Martien A. M. Groenen
- Animal Breeding and GenomicsWageningen University & ResearchWageningenThe Netherlands
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27
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Mueller ML, Cole JB, Sonstegard TS, Van Eenennaam AL. Comparison of gene editing versus conventional breeding to introgress the POLLED allele into the US dairy cattle population. J Dairy Sci 2019; 102:4215-4226. [PMID: 30852022 DOI: 10.3168/jds.2018-15892] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2018] [Accepted: 01/21/2019] [Indexed: 12/17/2022]
Abstract
Disbudding and dehorning are commonly used cattle management practices to protect animals and humans from injury. They are unpleasant, costly processes subject to increased public scrutiny as an animal welfare issue. Horns are a recessively inherited trait, so one option to eliminate dehorning is to breed for polled (hornlessness). However, due to the low genetic merit and scarcity of polled dairy sires, this approach has not been widely adopted. In March 2018, only 3 Holstein and 0 Jersey active homozygous polled sires were registered with the National Association of Animal Breeders. Alternatively, gene editing to produce high-genetic-merit polled sires has been proposed. To further explore this concept, introgression of the POLLED allele into both the US Holstein and Jersey cattle populations via conventional breeding or gene editing (top 1% of bulls/year) was simulated for 3 polled mating schemes and compared with baseline selection on lifetime net merit (NM$) alone, over the course of 20 yr. Scenarios were replicated 10 times and the changes in HORNED allele frequency, inbreeding, genetic gain (NM$), and number of unique sires used were calculated. Gene editing decreased the frequency of the HORNED allele to <0.1 after 20 yr, which was as fast or faster than conventional breeding for both breeds. In the mating scheme that required the use of only existing homozygous polled sires, inbreeding reached 17% (Holstein) and 14% (Jersey), compared with less than 7% in the baseline scenarios. However, gene editing in the same mating scheme resulted in significantly less inbreeding, 9% (Holstein) and 8% (Jersey). Also, gene editing resulted in significantly higher NM$ after 20 yr compared with conventional breeding for both breeds. Additionally, the gene editing scenarios of both breeds used a significantly greater number of unique sires compared with either the conventional breeding or baseline scenarios. Overall, our simulations show that, given the current genetic merit of horned and polled dairy sires, the use of conventional breeding methods to decrease the frequency of the HORNED allele will increase inbreeding and slow genetic improvement. Furthermore, this study demonstrates how gene editing could be used to rapidly decrease the frequency of the HORNED allele in US dairy cattle populations while maintaining the rate of genetic gain, constraining inbreeding to acceptable levels, and simultaneously addressing an emerging animal welfare concern.
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Affiliation(s)
- M L Mueller
- Department of Animal Science, University of California, Davis 95616
| | - J B Cole
- USDA, Agricultural Research Service, Animal Genomics and Improvement Laboratory, Beltsville, MD 20705-2350
| | | | - A L Van Eenennaam
- Department of Animal Science, University of California, Davis 95616.
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28
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Ma L, Sonstegard TS, Cole JB, VanTassell CP, Wiggans GR, Crooker BA, Tan C, Prakapenka D, Liu GE, Da Y. Genome changes due to artificial selection in U.S. Holstein cattle. BMC Genomics 2019; 20:128. [PMID: 30744549 PMCID: PMC6371544 DOI: 10.1186/s12864-019-5459-x] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2018] [Accepted: 01/17/2019] [Indexed: 01/13/2023] Open
Abstract
Background The availability of a unique unselected Holstein line since 1964 provided a direct comparison between selected and unselected Holstein genomes whereas large Holstein samples provided unprecedented statistical power for identifying high-confidence SNP effects. Utilizing these unique resources, we aimed to identify genome changes affected by selection since 1964. Results Direct comparison of genome-wide SNP markers between a Holstein line unselected since 1964 and contemporary Holsteins showed that the 40 years of artificial selection since 1964 resulted in genome landscape changes. Among the regions affected by selection, the regions containing 198 genes with fertility functions had a larger negative correlation than that of all SNPs between the SNP effects on milk yield and daughter pregnancy rate. These results supported the hypothesis that hitchhiking of genetic selection for milk production by negative effects of fertility genes contributed to the unintended declines in fertility since 1964. The genome regions subjected to selection also contained 67 immunity genes, the bovine MHC region of Chr23 with significantly decreased heterozygosity in contemporary Holsteins, and large gene clusters including T-cell receptor and immunoglobulin genes. Conclusions This study for the first time provided direct evidence that genetic selection for milk production affected fertility and immunity genes and that the hitchhiking of genetic selection for milk production by negative fertility effects contributed to the fertility declines since 1964, and identified a large number of candidate fertility and immunity genes affected by selection. The results provided novel understanding about genome changes due to artificial selection and their impact on fertility and immunity genes and could facilitate developing genetic methods to reverse the declines in fertility and immunity in Holstein cattle. Electronic supplementary material The online version of this article (10.1186/s12864-019-5459-x) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Li Ma
- Department of Animal and Avian Sciences, University of Maryland, College Park, MD, USA
| | | | - John B Cole
- Animal Genomics and Improvement Laboratory, USDA-ARS, Beltsville, MD, USA
| | | | - George R Wiggans
- Animal Genomics and Improvement Laboratory, USDA-ARS, Beltsville, MD, USA
| | - Brian A Crooker
- Department of Animal Science, University of Minnesota, Saint Paul, MN, USA
| | - Cheng Tan
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, People's Republic of China
| | - Dzianis Prakapenka
- Department of Animal Science, University of Minnesota, Saint Paul, MN, USA
| | - George E Liu
- Animal Genomics and Improvement Laboratory, USDA-ARS, Beltsville, MD, USA
| | - Yang Da
- Department of Animal Science, University of Minnesota, Saint Paul, MN, USA.
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29
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Liu S, Kang X, Catacchio CR, Liu M, Fang L, Schroeder SG, Li W, Rosen BD, Iamartino D, Iannuzzi L, Sonstegard TS, Van Tassell CP, Ventura M, Low WY, Williams JL, Bickhart DM, Liu GE. Computational detection and experimental validation of segmental duplications and associated copy number variations in water buffalo ( Bubalus bubalis ). Funct Integr Genomics 2019; 19:409-419. [PMID: 30734132 DOI: 10.1007/s10142-019-00657-4] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2018] [Revised: 12/13/2018] [Accepted: 01/09/2019] [Indexed: 01/25/2023]
Abstract
Duplicated sequences are an important source of gene evolution and structural variation within mammalian genomes. Using a read depth approach based on next-generation sequencing, we performed a genome-wide analysis of segmental duplications (SDs) and associated copy number variations (CNVs) in the water buffalo (Bubalus bubalis). By aligning short reads of Olimpia (the reference water buffalo) to the UMD3.1 cattle genome, we identified 1,038 segmental duplications comprising 44.6 Mb (equivalent to ~1.73% of the cattle genome) of the autosomal and X chromosomal sequence in the buffalo genome. We experimentally validated 70.3% (71/101) of these duplications using fluorescent in situ hybridization. We also detected a total of 1,344 CNV regions across 14 additional water buffaloes, amounting to 59.8 Mb of variable sequence or the equivalent of 2.2% of the cattle genome. The CNV regions overlap 1,245 genes that are significantly enriched for specific biological functions including immune response, oxygen transport, sensory system and signal transduction. Additionally, we performed array Comparative Genomic Hybridization (aCGH) experiments using the 14 water buffaloes as test samples and Olimpia as the reference. Using a linear regression model, a high Pearson correlation (r = 0.781) was observed between the log2 ratios between copy number estimates and the log2 ratios of aCGH probes. We further designed Quantitative PCR assays to confirm CNV regions within or near annotated genes and found 74.2% agreement with our CNV predictions. These results confirm sub-chromosome-scale structural rearrangements present in the cattle and water buffalo. The information on genome variation that will be of value for evolutionary and phenotypic studies, and may be useful for selective breeding of both species.
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Affiliation(s)
- Shuli Liu
- USDA-ARS, Animal Genomics and Improvement Laboratory, Beltsville, Maryland, 20705, USA
- College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Xiaolong Kang
- USDA-ARS, Animal Genomics and Improvement Laboratory, Beltsville, Maryland, 20705, USA
- College of Agriculture, Ningxia University, Yinchuan, 750021, China
| | | | - Mei Liu
- USDA-ARS, Animal Genomics and Improvement Laboratory, Beltsville, Maryland, 20705, USA
- College of Animal Science and Technology, Shaanxi Key Laboratory of Agricultural Molecular Biology, Northwest A&F University, Yangling, 712100, Shaanxi, China
| | - Lingzhao Fang
- USDA-ARS, Animal Genomics and Improvement Laboratory, Beltsville, Maryland, 20705, USA
- Department of Animal and Avian Sciences, University of Maryland, College Park, Maryland, 20742, USA
| | - Steven G Schroeder
- USDA-ARS, Animal Genomics and Improvement Laboratory, Beltsville, Maryland, 20705, USA
| | - Wenli Li
- The Cell Wall Utilization and Biology Laboratory, US Dairy Forage Research Center, USDA, ARS, Madison, WI 53706, USA
| | - Benjamin D Rosen
- USDA-ARS, Animal Genomics and Improvement Laboratory, Beltsville, Maryland, 20705, USA
| | - Daniela Iamartino
- AIA-LGS, Associazione Italiana Allevatori - Laboratorio Genetica e Servizi, Via Bergamo 292, 26100 (CR), Cremona, Italy
- Parco Tecnologico Padano, Via Einstein, Polo Universitario, 26900, Lodi, Italy
| | - Leopoldo Iannuzzi
- Laboratory of Animal Cytogenetics and Gene Mapping, Nationa Research Council (CNR), ISPAAM, Via Argine 1085, 80147, Naples, Italy
| | | | - Curtis P Van Tassell
- USDA-ARS, Animal Genomics and Improvement Laboratory, Beltsville, Maryland, 20705, USA
| | - Mario Ventura
- Department of Biology, University of Bari, 70126, Bari, Italy
| | - Wai Yee Low
- Davies Research Centre, School of Animal and Veterinary Sciences, University of Adelaide, Roseworthy, SA, 5371, Australia
| | - John L Williams
- Davies Research Centre, School of Animal and Veterinary Sciences, University of Adelaide, Roseworthy, SA, 5371, Australia
| | - Derek M Bickhart
- The Cell Wall Utilization and Biology Laboratory, US Dairy Forage Research Center, USDA, ARS, Madison, WI 53706, USA.
| | - George E Liu
- USDA-ARS, Animal Genomics and Improvement Laboratory, Beltsville, Maryland, 20705, USA.
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30
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Bertolini F, Servin B, Talenti A, Rochat E, Kim ES, Oget C, Palhière I, Crisà A, Catillo G, Steri R, Amills M, Colli L, Marras G, Milanesi M, Nicolazzi E, Rosen BD, Van Tassell CP, Guldbrandtsen B, Sonstegard TS, Tosser-Klopp G, Stella A, Rothschild MF, Joost S, Crepaldi P. Signatures of selection and environmental adaptation across the goat genome post-domestication. Genet Sel Evol 2018; 50:57. [PMID: 30449276 PMCID: PMC6240954 DOI: 10.1186/s12711-018-0421-y] [Citation(s) in RCA: 88] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2017] [Accepted: 10/15/2018] [Indexed: 01/03/2023] Open
Abstract
BACKGROUND Since goat was domesticated 10,000 years ago, many factors have contributed to the differentiation of goat breeds and these are classified mainly into two types: (i) adaptation to different breeding systems and/or purposes and (ii) adaptation to different environments. As a result, approximately 600 goat breeds have developed worldwide; they differ considerably from one another in terms of phenotypic characteristics and are adapted to a wide range of climatic conditions. In this work, we analyzed the AdaptMap goat dataset, which is composed of data from more than 3000 animals collected worldwide and genotyped with the CaprineSNP50 BeadChip. These animals were partitioned into groups based on geographical area, production uses, available records on solid coat color and environmental variables including the sampling geographical coordinates, to investigate the role of natural and/or artificial selection in shaping the genome of goat breeds. RESULTS Several signatures of selection on different chromosomal regions were detected across the different breeds, sub-geographical clusters, phenotypic and climatic groups. These regions contain genes that are involved in important biological processes, such as milk-, meat- or fiber-related production, coat color, glucose pathway, oxidative stress response, size, and circadian clock differences. Our results confirm previous findings in other species on adaptation to extreme environments and human purposes and provide new genes that could explain some of the differences between goat breeds according to their geographical distribution and adaptation to different environments. CONCLUSIONS These analyses of signatures of selection provide a comprehensive first picture of the global domestication process and adaptation of goat breeds and highlight possible genes that may have contributed to the differentiation of this species worldwide.
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Affiliation(s)
- Francesca Bertolini
- Department of Animal Science, Iowa State University, Ames, IA 50011 USA
- National Institute of Aquatic Resources, Technical University of Denmark (DTU), 2800 Lyngby, Denmark
| | - Bertrand Servin
- GenPhySE, INRA, Université de Toulouse, INPT, ENVT, 31326 Castanet Tolosan, France
| | - Andrea Talenti
- Dipartimento di Medicina Veterinaria, Università degli Studi di Milano, 20133 Milan, Italy
| | - Estelle Rochat
- Laboratory of Geographic Information Systems (LASIG), School of Architecture, Civil and Environmental Engineering (ENAC), Ecole Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland
| | | | - Claire Oget
- GenPhySE, INRA, Université de Toulouse, INPT, ENVT, 31326 Castanet Tolosan, France
| | - Isabelle Palhière
- GenPhySE, INRA, Université de Toulouse, INPT, ENVT, 31326 Castanet Tolosan, France
| | - Alessandra Crisà
- Consiglio per la ricerca in agricoltura e l’analisi dell’economia agraria (CREA) - Research Centre for Animal Production and Acquaculture, 00015 Monterotondo, Roma, Italy
| | - Gennaro Catillo
- Consiglio per la ricerca in agricoltura e l’analisi dell’economia agraria (CREA) - Research Centre for Animal Production and Acquaculture, 00015 Monterotondo, Roma, Italy
| | - Roberto Steri
- Consiglio per la ricerca in agricoltura e l’analisi dell’economia agraria (CREA) - Research Centre for Animal Production and Acquaculture, 00015 Monterotondo, Roma, Italy
| | - Marcel Amills
- Centre for Research in Agricultural Genomics (CRAG), CSIC-IRTA-UAB-UB, Campus Universitat Autonoma de Barcelona, Bellaterra, 08193 Barcelona, Spain
| | - Licia Colli
- DIANA Dipartimento di Scienze Animali, della Nutrizione e degli Alimenti, Università Cattolica del S. Cuore, 29100 Piacenza, Italy
- BioDNA Centro di Ricerca sulla Biodiversità e sul DNA Antico, Università Cattolica del S. Cuore, 29100 Piacenza, Italy
| | - Gabriele Marras
- Fondazione Parco Tecnologico Padano (PTP), 26900 Lodi, Italy
| | - Marco Milanesi
- DIANA Dipartimento di Scienze Animali, della Nutrizione e degli Alimenti, Università Cattolica del S. Cuore, 29100 Piacenza, Italy
- Department of Support, Production and Animal Health, School of Veterinary Medicine, São Paulo State University (UNESP), Araçatuba, Brazil
| | | | - Benjamin D. Rosen
- Animal Genomics and Improvement Laboratory, ARS USDA, Beltsville, MD 20705 USA
| | | | - Bernt Guldbrandtsen
- Center for Quantitative Genetics and Genomics, Aarhus University, 8830 Tjele, Denmark
| | | | - Gwenola Tosser-Klopp
- GenPhySE, INRA, Université de Toulouse, INPT, ENVT, 31326 Castanet Tolosan, France
| | - Alessandra Stella
- BioDNA Centro di Ricerca sulla Biodiversità e sul DNA Antico, Università Cattolica del S. Cuore, 29100 Piacenza, Italy
| | - Max F. Rothschild
- Department of Animal Science, Iowa State University, Ames, IA 50011 USA
| | - Stéphane Joost
- Laboratory of Geographic Information Systems (LASIG), School of Architecture, Civil and Environmental Engineering (ENAC), Ecole Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland
| | - Paola Crepaldi
- Dipartimento di Medicina Veterinaria, Università degli Studi di Milano, 20133 Milan, Italy
| | - the AdaptMap consortium
- Department of Animal Science, Iowa State University, Ames, IA 50011 USA
- National Institute of Aquatic Resources, Technical University of Denmark (DTU), 2800 Lyngby, Denmark
- GenPhySE, INRA, Université de Toulouse, INPT, ENVT, 31326 Castanet Tolosan, France
- Dipartimento di Medicina Veterinaria, Università degli Studi di Milano, 20133 Milan, Italy
- Laboratory of Geographic Information Systems (LASIG), School of Architecture, Civil and Environmental Engineering (ENAC), Ecole Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland
- Recombinetics Inc, St Paul, 55104 MN USA
- Consiglio per la ricerca in agricoltura e l’analisi dell’economia agraria (CREA) - Research Centre for Animal Production and Acquaculture, 00015 Monterotondo, Roma, Italy
- Centre for Research in Agricultural Genomics (CRAG), CSIC-IRTA-UAB-UB, Campus Universitat Autonoma de Barcelona, Bellaterra, 08193 Barcelona, Spain
- DIANA Dipartimento di Scienze Animali, della Nutrizione e degli Alimenti, Università Cattolica del S. Cuore, 29100 Piacenza, Italy
- BioDNA Centro di Ricerca sulla Biodiversità e sul DNA Antico, Università Cattolica del S. Cuore, 29100 Piacenza, Italy
- Fondazione Parco Tecnologico Padano (PTP), 26900 Lodi, Italy
- Department of Support, Production and Animal Health, School of Veterinary Medicine, São Paulo State University (UNESP), Araçatuba, Brazil
- Animal Genomics and Improvement Laboratory, ARS USDA, Beltsville, MD 20705 USA
- Center for Quantitative Genetics and Genomics, Aarhus University, 8830 Tjele, Denmark
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31
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Colli L, Milanesi M, Talenti A, Bertolini F, Chen M, Crisà A, Daly KG, Del Corvo M, Guldbrandtsen B, Lenstra JA, Rosen BD, Vajana E, Catillo G, Joost S, Nicolazzi EL, Rochat E, Rothschild MF, Servin B, Sonstegard TS, Steri R, Van Tassell CP, Ajmone-Marsan P, Crepaldi P, Stella A. Genome-wide SNP profiling of worldwide goat populations reveals strong partitioning of diversity and highlights post-domestication migration routes. Genet Sel Evol 2018; 50:58. [PMID: 30449284 PMCID: PMC6240949 DOI: 10.1186/s12711-018-0422-x] [Citation(s) in RCA: 67] [Impact Index Per Article: 11.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2018] [Accepted: 10/15/2018] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Goat populations that are characterized within the AdaptMap project cover a large part of the worldwide distribution of this species and provide the opportunity to assess their diversity at a global scale. We analysed genome-wide 50 K single nucleotide polymorphism (SNP) data from 144 populations to describe the global patterns of molecular variation, compare them to those observed in other livestock species, and identify the drivers that led to the current distribution of goats. RESULTS A high degree of genetic variability exists among the goat populations studied. Our results highlight a strong partitioning of molecular diversity between and within continents. Three major gene pools correspond to goats from Europe, Africa and West Asia. Dissection of sub-structures disclosed regional gene pools, which reflect the main post-domestication migration routes. We also identified several exchanges, mainly in African populations, and which often involve admixed and cosmopolitan breeds. Extensive gene flow has taken place within specific areas (e.g., south Europe, Morocco and Mali-Burkina Faso-Nigeria), whereas elsewhere isolation due to geographical barriers (e.g., seas or mountains) or human management has decreased local gene flows. CONCLUSIONS After domestication in the Fertile Crescent in the early Neolithic era (ca. 12,000 YBP), domestic goats that already carried differentiated gene pools spread to Europe, Africa and Asia. The spread of these populations determined the major genomic background of the continental populations, which currently have a more marked subdivision than that observed in other ruminant livestock species. Subsequently, further diversification occurred at the regional level due to geographical and reproductive isolation, which was accompanied by additional migrations and/or importations, the traces of which are still detectable today. The effects of breed formation were clearly detected, particularly in Central and North Europe. Overall, our results highlight a remarkable diversity that occurs at the global scale and is locally partitioned and often affected by introgression from cosmopolitan breeds. These findings support the importance of long-term preservation of goat diversity, and provide a useful framework for investigating adaptive introgression, directing genetic improvement and choosing breeding targets.
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Affiliation(s)
- Licia Colli
- DIANA Dipartimento di Scienze Animali, della Nutrizione e degli Alimenti, Università Cattolica del S. Cuore, Piacenza, Italy. .,BioDNA Centro di Ricerca sulla Biodiversità e sul DNA Antico, Università Cattolica del S. Cuore, Piacenza, Italy.
| | - Marco Milanesi
- DIANA Dipartimento di Scienze Animali, della Nutrizione e degli Alimenti, Università Cattolica del S. Cuore, Piacenza, Italy.,School of Veterinary Medicine, Department of Support, Production and Animal Health, São Paulo State University (UNESP), Araçatuba, Brazil
| | - Andrea Talenti
- Dipartimento di Medicina Veterinaria, University of Milan, Milan, Italy
| | - Francesca Bertolini
- Department of Animal Science, Iowa State University, Ames, IA, USA.,National Institute of Aquatic Resources, Technical University of Denmark, DTU, Lyngby, Denmark
| | - Minhui Chen
- Department of Molecular Biology and Genetics, Center for Quantitative Genetics and Genomics, Aarhus University, Århus, Denmark.,Center for Genetic Epidemiology, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Alessandra Crisà
- Consiglio per la Ricerca in Agricoltura e l'Analisi dell'Economia Agraria (CREA) - Research Centre for Animal Production and Aquaculture, Monterotondo, Rome, Italy
| | - Kevin Gerard Daly
- Population Genetics Lab, Smurfit Institute of Genetics, Trinity College of Dublin, Dublin, Ireland
| | - Marcello Del Corvo
- DIANA Dipartimento di Scienze Animali, della Nutrizione e degli Alimenti, Università Cattolica del S. Cuore, Piacenza, Italy
| | - Bernt Guldbrandtsen
- Department of Molecular Biology and Genetics, Center for Quantitative Genetics and Genomics, Aarhus University, Århus, Denmark
| | - Johannes A Lenstra
- Faculty of Veterinary Medicine, Utrecht University, Utrecht, Netherlands
| | - Benjamin D Rosen
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, United States Department of Agriculture, Beltsville, MD, USA
| | - Elia Vajana
- DIANA Dipartimento di Scienze Animali, della Nutrizione e degli Alimenti, Università Cattolica del S. Cuore, Piacenza, Italy.,Laboratory of Geographic Information Systems (LASIG), School of Architecture, Civil and Environmental Engineering (ENAC), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Gennaro Catillo
- Consiglio per la Ricerca in Agricoltura e l'Analisi dell'Economia Agraria (CREA) - Research Centre for Animal Production and Aquaculture, Monterotondo, Rome, Italy
| | - Stéphane Joost
- Laboratory of Geographic Information Systems (LASIG), School of Architecture, Civil and Environmental Engineering (ENAC), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | | | - Estelle Rochat
- Laboratory of Geographic Information Systems (LASIG), School of Architecture, Civil and Environmental Engineering (ENAC), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Max F Rothschild
- Department of Animal Science, Iowa State University, Ames, IA, USA
| | - Bertrand Servin
- GenPhySE, INRA, Université de Toulouse, INPT, ENVT, 31326, Castanet Tolosan, France
| | | | - Roberto Steri
- Consiglio per la Ricerca in Agricoltura e l'Analisi dell'Economia Agraria (CREA) - Research Centre for Animal Production and Aquaculture, Monterotondo, Rome, Italy
| | - Curtis P Van Tassell
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, United States Department of Agriculture, Beltsville, MD, USA
| | - Paolo Ajmone-Marsan
- DIANA Dipartimento di Scienze Animali, della Nutrizione e degli Alimenti, Università Cattolica del S. Cuore, Piacenza, Italy.,BioDNA Centro di Ricerca sulla Biodiversità e sul DNA Antico, Università Cattolica del S. Cuore, Piacenza, Italy
| | - Paola Crepaldi
- Dipartimento di Medicina Veterinaria, University of Milan, Milan, Italy
| | - Alessandra Stella
- Fondazione Parco Tecnologico Padano, Lodi, Italy.,Istituto di Biologia e Biotecnologia Agraria, Consiglio Nazionale delle Ricerche, Milan, Italy
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32
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Mueller ML, Cole JB, Sonstegard TS, Van Eenennaam AL. Simulation of introgression of the POLLED allele into the Jersey breed via conventional breeding vs. gene editing. Transl Anim Sci 2018; 2:S57-S60. [PMID: 32704737 PMCID: PMC7200810 DOI: 10.1093/tas/txy054] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2018] [Accepted: 04/14/2018] [Indexed: 01/24/2023] Open
Affiliation(s)
- Maci L Mueller
- Department of Animal Science, University of California, Davis, CA
| | - John B Cole
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, United States Department of Agriculture, Beltsville, MD
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33
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Edea Z, Dadi H, Dessie T, Uzzaman MR, Rothschild MF, Kim ES, Sonstegard TS, Kim KS. Genome-wide scan reveals divergent selection among taurine and zebu cattle populations from different regions. Anim Genet 2018; 49:550-563. [PMID: 30246258 DOI: 10.1111/age.12724] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/06/2018] [Indexed: 01/02/2023]
Abstract
In this study, to identify genomic signatures of divergent selection, we genotyped 10 cattle breeds/populations (n = 275), representing eight Ethiopian cattle populations (n = 229) and two zebu populations (n = 46) adapted to tropical and sub-tropical environments, using the high-density single-nucleotide polymorphisms (SNPs) derived mainly from Bos indicus breeds, and using five reference taurine breeds (n = 212). Population genetic differentiation (FST ) values across sliding windows were estimated between zebu and reference combined taurine breeds. The most differentiated regions (FST ≥ 0.53), representing the top 1% smoothed FST values, were considered to represent regions under diversifying selection. In total, 285 and 317 genes were identified in the comparisons of Ethiopian cattle with taurine and Asian zebu with taurine respectively. Some of these genes are involved in stress responses/thermo-tolerance and DNA damage repair (HSPA4, HSF1, CMPK1 and EIF2AK4), pigmentation (ERBB3 and MYO1A), reproduction/fertility (UBE2D3, ID3 and PSPC1), immune response (PIK3CD and AKIRIN2) and body stature and size (MBP2, LYN and NPM1). Additionally, the candidate genes were associated with functional terms (e.g. cellular response to stress, DNA repair, inflammatory response) important for physiological adaptation to environmental stresses. The results of our study may shed light on the influence of artificial and natural selection in shaping the genomic diversity of modern cattle breeds and also may serve as a basis for further genetic investigation of traits of tropical adaptation in cattle.
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Affiliation(s)
- Z Edea
- Department of Animal Science, Chungbuk National University, Cheongju, 28644, Korea
| | - H Dadi
- Department of Biotechnology, Addis Ababa Science and Technology University, P.O. Box 16417, Addis Ababa, Ethiopia
| | - T Dessie
- International Livestock Research Institute (ILRI), P.O. Box 5689, Addis Ababa, Ethiopia
| | - M R Uzzaman
- Department of Animal Science, Chungbuk National University, Cheongju, 28644, Korea.,Animal Genomics & Bioinformatics Division, National Institute of Animal Science, RDA, Wanju, 55365, S. Korea
| | - M F Rothschild
- Department of Animal Science, Iowa State University, Ames, IA, 50011, USA
| | - E-S Kim
- Recombinetics, Inc., Saint Paul, MN, 55104, USA
| | | | - K-S Kim
- Department of Animal Science, Chungbuk National University, Cheongju, 28644, Korea
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34
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Porto-Neto LR, Bickhart DM, Landaeta-Hernandez AJ, Utsunomiya YT, Pagan M, Jimenez E, Hansen PJ, Dikmen S, Schroeder SG, Kim ES, Sun J, Crespo E, Amati N, Cole JB, Null DJ, Garcia JF, Reverter A, Barendse W, Sonstegard TS. Convergent Evolution of Slick Coat in Cattle through Truncation Mutations in the Prolactin Receptor. Front Genet 2018. [PMID: 29527221 PMCID: PMC5829098 DOI: 10.3389/fgene.2018.00057] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
Evolutionary adaptations are occasionally convergent solutions to the same problem. A mutation contributing to a heat tolerance adaptation in Senepol cattle, a New World breed of mostly European descent, results in the distinct phenotype known as slick, where an animal has shorter hair and lower follicle density across its coat than wild type animals. The causal variant, located in the 11th exon of prolactin receptor, produces a frameshift that results in a truncated protein. However, this mutation does not explain all cases of slick coats found in criollo breeds. Here, we obtained genome sequences from slick cattle of a geographically distinct criollo breed, namely Limonero, whose ancestors were originally brought to the Americas by the Spanish. These data were used to identify new causal alleles in the 11th exon of the prolactin receptor, two of which also encode shortened proteins that remove a highly conserved tyrosine residue. These new mutations explained almost 90% of investigated cases of animals that had slick coats, but which also did not carry the Senepol slick allele. These results demonstrate convergent evolution at the molecular level in a trait important to the adaptation of an animal to its environment.
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Affiliation(s)
| | - Derek M Bickhart
- US Dairy Forage Research Center, United States Department of Agriculture, Agricultural Research Service, Madison, WI, United States
| | - Antonio J Landaeta-Hernandez
- Unidad de Investigaciones Zootécnicas, Facultad de Ciencias Veterinarias, Universidad del Zulia, Maracaibo, Venezuela
| | - Yuri T Utsunomiya
- Department of Preventive Veterinary Medicine and Animal Reproduction, School of Agricultural and Veterinarian Sciences, São Paulo State University, São Paulo, Brazil.,International Atomic Energy Agency, Collaborating Centre on Animal Genomics and Bioinformatics, Araçatuba, Brazil
| | - Melvin Pagan
- Department of Animal Science, University of Puerto Rico-Mayagüez, Mayagüez, Puerto Rico
| | - Esbal Jimenez
- Department of Animal Science, University of Puerto Rico-Mayagüez, Mayagüez, Puerto Rico
| | - Peter J Hansen
- Department of Animal Sciences, University of Florida, Gainesville, FL, United States
| | - Serdal Dikmen
- Department of Animal Science, Faculty of Veterinary Medicine, Uludağ University, Bursa, Turkey
| | - Steven G Schroeder
- Animal Genomics and Improvement Laboratory, United States Department of Agriculture, Agricultural Research Service, Beltsville, MD, United States
| | - Eui-Soo Kim
- Recombinetics, Inc., Saint Paul, MN, United States
| | - Jiajie Sun
- College of Animal Science, South China Agricultural University, Guangzhou, China
| | - Edward Crespo
- Unidad de Investigaciones Zootécnicas, Facultad de Ciencias Veterinarias, Universidad del Zulia, Maracaibo, Venezuela
| | - Norman Amati
- Unidad de Investigaciones Zootécnicas, Facultad de Ciencias Veterinarias, Universidad del Zulia, Maracaibo, Venezuela
| | - John B Cole
- Animal Genomics and Improvement Laboratory, United States Department of Agriculture, Agricultural Research Service, Beltsville, MD, United States
| | - Daniel J Null
- Animal Genomics and Improvement Laboratory, United States Department of Agriculture, Agricultural Research Service, Beltsville, MD, United States
| | - Jose F Garcia
- Department of Preventive Veterinary Medicine and Animal Reproduction, School of Agricultural and Veterinarian Sciences, São Paulo State University, São Paulo, Brazil.,International Atomic Energy Agency, Collaborating Centre on Animal Genomics and Bioinformatics, Araçatuba, Brazil.,Department of Support, Production and Animal Health, School of Veterinary Medicine, São Paulo State University, São Paulo, Brazil
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35
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Xu L, Haasl RJ, Sun J, Zhou Y, Bickhart DM, Li J, Song J, Sonstegard TS, Van Tassell CP, Lewin HA, Liu GE. Systematic Profiling of Short Tandem Repeats in the Cattle Genome. Genome Biol Evol 2018; 9:20-31. [PMID: 28172841 PMCID: PMC5381564 DOI: 10.1093/gbe/evw256] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/21/2016] [Indexed: 12/13/2022] Open
Abstract
Short tandem repeats (STRs), or microsatellites, are genetic variants with repetitive 2–6 base pair motifs in many mammalian genomes. Using high-throughput sequencing and experimental validations, we systematically profiled STRs in five Holsteins. We identified a total of 60,106 microsatellites and generated the first high-resolution STR map, representing a substantial pool of polymorphism in dairy cattle. We observed significant STRs overlap with functional genes and quantitative trait loci (QTL). We performed evolutionary and population genetic analyses using over 20,000 common dinucleotide STRs. Besides corroborating the well-established positive correlation between allele size and variance in allele size, these analyses also identified dozens of outlier STRs based on two anomalous relationships that counter expected characteristics of neutral evolution. And one STR locus overlaps with a significant region of a summary statistic designed to detect STR-related selection. Additionally, our results showed that only 57.1% of STRs located within SNP-based linkage disequilibrium (LD) blocks whereas the other 42.9% were out of blocks. Therefore, a substantial number of STRs are not tagged by SNPs in the cattle genome, likely due to STR's distinct mutation mechanism and elevated polymorphism. This study provides the foundation for future STR-based studies of cattle genome evolution and selection.
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Affiliation(s)
- Lingyang Xu
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, Beltsville, MD.,Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China.,Department of Animal and Avian Sciences, University of Maryland, College Park, MD
| | - Ryan J Haasl
- Department of Biology, University of Wisconsin - Platteville, WI
| | - Jiajie Sun
- College of Animal Science, South China Agricultural University, Guangzhou, China
| | - Yang Zhou
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, Beltsville, MD.,College of Animal Science and Technology, Northwest A&F University, Shaanxi Key Laboratory of Molecular Biology for Agriculture, Yangling, Shannxi, China
| | - Derek M Bickhart
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, Beltsville, MD
| | - Junya Li
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Jiuzhou Song
- Department of Animal and Avian Sciences, University of Maryland, College Park, MD
| | - Tad S Sonstegard
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, Beltsville, MD
| | - Curtis P Van Tassell
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, Beltsville, MD
| | - Harris A Lewin
- Department of Evolution and Ecology, University of California, Davis, CA
| | - George E Liu
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, Beltsville, MD
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Iamartino D, Nicolazzi EL, Van Tassell CP, Reecy JM, Fritz-Waters ER, Koltes JE, Biffani S, Sonstegard TS, Schroeder SG, Ajmone-Marsan P, Negrini R, Pasquariello R, Ramelli P, Coletta A, Garcia JF, Ali A, Ramunno L, Cosenza G, de Oliveira DAA, Drummond MG, Bastianetto E, Davassi A, Pirani A, Brew F, Williams JL. Design and validation of a 90K SNP genotyping assay for the water buffalo (Bubalus bubalis). PLoS One 2017; 12:e0185220. [PMID: 28981529 PMCID: PMC5628821 DOI: 10.1371/journal.pone.0185220] [Citation(s) in RCA: 50] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2016] [Accepted: 09/10/2017] [Indexed: 11/28/2022] Open
Abstract
Background The availability of the bovine genome sequence and SNP panels has improved various genomic analyses, from exploring genetic diversity to aiding genetic selection. However, few of the SNP on the bovine chips are polymorphic in buffalo, therefore a panel of single nucleotide DNA markers exclusive for buffalo was necessary for molecular genetic analyses and to develop genomic selection approaches for water buffalo. The creation of a 90K SNP panel for river buffalo and testing in a genome wide association study for milk production is described here. Methods The genomes of 73 buffaloes of 4 different breeds were sequenced and aligned against the bovine genome, which facilitated the identification of 22 million of sequence variants among the buffalo genomes. Based on frequencies of variants within and among buffalo breeds, and their distribution across the genome, inferred from the bovine genome sequence, 90,000 putative single nucleotide polymorphisms were selected to create an Axiom® Buffalo Genotyping Array 90K. Results This 90K “SNP-Chip” was tested in several river buffalo populations and found to have ∼70% high quality and polymorphic SNPs. Of the 90K SNPs about 24K were also found to be polymorphic in swamp buffalo. The SNP chip was used to investigate the structure of buffalo populations, and could distinguish buffalo from different farms. A Genome Wide Association Study identified genomic regions on 5 chromosomes putatively involved in milk production. Conclusion The 90K buffalo SNP chip described here is suitable for the analysis of the genomes of river buffalo breeds, and could be used for genetic diversity studies and potentially as a starting point for genome-assisted selection programmes. This SNP Chip could also be used to analyse swamp buffalo, but many loci are not informative and creation of a revised SNP set specific for swamp buffalo would be advised.
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Affiliation(s)
- Daniela Iamartino
- AIA-LGS Associazione Italiana Allevatori–Laboratorio Genetica e Servizi, Cremona, Italy
- Fondazione Parco Tecnologico Padano, Lodi, Italy
- * E-mail:
| | | | - Curtis P. Van Tassell
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Beltsville, Maryland, United States of America
| | - James M. Reecy
- Department of Animal Science, Iowa State University, Ames, IA, United States of America
| | - Eric R. Fritz-Waters
- Department of Animal Science, Iowa State University, Ames, IA, United States of America
| | - James E. Koltes
- Department of Animal Science, Iowa State University, Ames, IA, United States of America
| | | | - Tad S. Sonstegard
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Beltsville, Maryland, United States of America
| | - Steven G. Schroeder
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Beltsville, Maryland, United States of America
| | - Paolo Ajmone-Marsan
- Institute of Zootechnics, Università Cattolica del S. Cuore, Piacenza, Italy
| | - Riccardo Negrini
- AIA-LGS Associazione Italiana Allevatori–Laboratorio Genetica e Servizi, Cremona, Italy
- Institute of Zootechnics, Università Cattolica del S. Cuore, Piacenza, Italy
| | | | | | - Angelo Coletta
- ANASB-Associazione Nazionale Allevatori Specie Bufalina, Centurano—Caserta, Italy
| | - José F. Garcia
- Universidade Estadual Paulista (UNESP), Câmpus de Araçatuba, Sao Paulo, Brazil
| | - Ahmad Ali
- COMSATS Institute of Information Technology, Sahiwal, Pakistan
| | - Luigi Ramunno
- Dipartimento di Scienze Zootecniche ed Ispezione degli Alimenti, Facoltà di Agraria, Università degli Studi di Napoli Federico II, Portici (NA), Italy
| | - Gianfranco Cosenza
- Dipartimento di Scienze Zootecniche ed Ispezione degli Alimenti, Facoltà di Agraria, Università degli Studi di Napoli Federico II, Portici (NA), Italy
| | | | | | | | | | - Ali Pirani
- Affymetrix UK Ltd, High Wycombe, United Kingdom
| | - Fiona Brew
- Affymetrix UK Ltd, High Wycombe, United Kingdom
| | - John L. Williams
- Davies Research Centre, School of Animal and Veterinary Sciences, University of Adelaide, Roseworthy, SA, Australia
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Spangler GL, Rosen BD, Ilori MB, Hanotte O, Kim ES, Sonstegard TS, Burke JM, Morgan JLM, Notter DR, Van Tassell CP. Whole genome structural analysis of Caribbean hair sheep reveals quantitative link to West African ancestry. PLoS One 2017; 12:e0179021. [PMID: 28662044 PMCID: PMC5490989 DOI: 10.1371/journal.pone.0179021] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2016] [Accepted: 05/23/2017] [Indexed: 01/05/2023] Open
Abstract
Hair sheep of Caribbean origin have become an important part of the U.S. sheep industry. Their lack of wool eliminates a number of health concerns and drastically reduces the cost of production. More importantly, Caribbean hair sheep demonstrate robust production performance even in the presence of drug-resistant gastrointestinal nematodes, a rising concern to the industry. Despite the growing importance of hair sheep in the Americas their genetic origins have remained speculative. Prior to this report no genetic studies were able to identify a unique geographical origin of hair sheep in the New World. Our study clarifies the African and European ancestry of Caribbean hair sheep. Whole-genome structural analysis was conducted on four established breeds of hair sheep from the Caribbean region. Using breeds representing Africa and Europe we establish an objective measure indicating Caribbean hair sheep are derived from Iberian and West African origins. Caribbean hair sheep result from West African introgression into established ecotypes of Iberian descent. Genotypes from 47,750 autosomal single nucleotide polymorphism markers scored in 290 animals were used to characterize the population structure of the St. Croix, Barbados Blackbelly, Morada Nova, and Santa Ines. Principal components, admixture, and phylogenetic analyses results correlate with historical patterns of colonization and trade. These patterns support co-migration of these sheep with humans.
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Affiliation(s)
- Gordon L. Spangler
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, United States Department of Agriculture, Beltsville, Maryland, United States of America
| | - Benjamin D. Rosen
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, United States Department of Agriculture, Beltsville, Maryland, United States of America
| | | | - Olivier Hanotte
- School of Life Sciences, University of Nottingham, Nottingham, United Kingdom
| | - Eui-Soo Kim
- Acceligen of Recombinetics Incorporated, Saint Paul, Minnesota, United States of America
| | - Tad S. Sonstegard
- Acceligen of Recombinetics Incorporated, Saint Paul, Minnesota, United States of America
| | - Joan M. Burke
- Dale Bumpers Small Farms Research Station, Agricultural Research Service, United States Department of Agriculture, Booneville, Arkansas, United States of America
| | - James L. M. Morgan
- Katahdin Hair Sheep International, Fayetteville, Arkansas, United States of America
| | - David R. Notter
- Department of Animal and Poultry Sciences, Virginia Tech, Blacksburg, Virginia, United States of America
| | - Curtis P. Van Tassell
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, United States Department of Agriculture, Beltsville, Maryland, United States of America
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38
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Braud M, Magee DA, Park SDE, Sonstegard TS, Waters SM, MacHugh DE, Spillane C. Genome-Wide microRNA Binding Site Variation between Extinct Wild Aurochs and Modern Cattle Identifies Candidate microRNA-Regulated Domestication Genes. Front Genet 2017; 8:3. [PMID: 28197171 PMCID: PMC5281612 DOI: 10.3389/fgene.2017.00003] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2016] [Accepted: 01/09/2017] [Indexed: 12/21/2022] Open
Abstract
The domestication of cattle from the now-extinct wild aurochs (Bos primigenius) involved selection for physiological and behavioral traits, with underlying genetic factors that remain largely unknown. Non-coding microRNAs have emerged as key regulators of the spatio-temporal expression of target genes controlling mammalian growth and development, including in livestock species. During the domestication process, selection of mutational changes in miRNAs and/or miRNA binding sites could have provided a mechanism to generate some of the traits that differentiate domesticated cattle from wild aurochs. To investigate this, we analyzed the open reading frame DNA sequence of 19,994 orthologous protein-coding gene pairs from extant Bos taurus genomes and a single extinct B. primigenius genome. We identified miRNA binding site polymorphisms in the 3′ UTRs of 1,620 of these orthologous genes. These 1,620 genes with altered miRNA binding sites between the B. taurus and B. primigenius lineages represent candidate domestication genes. Using a novel Score Site ratio metric we have ranked these miRNA-regulated genes according to the extent of divergence between miRNA binding site presence, frequency and copy number between the orthologous genes from B. taurus and B. primigenius. This provides an unbiased approach to identify cattle genes that have undergone the most changes in miRNA binding (i.e., regulation) between the wild aurochs and modern-day cattle breeds. In addition, we demonstrate that these 1,620 candidate domestication genes are enriched for roles in pigmentation, fertility, neurobiology, metabolism, immunity and production traits (including milk quality and feed efficiency). Our findings suggest that directional selection of miRNA regulatory variants was important in the domestication and subsequent artificial selection that gave rise to modern taurine cattle.
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Affiliation(s)
- Martin Braud
- Genetics and Biotechnology Lab, Plant and AgriBiosciences Research Centre, School of Natural Sciences, National University of Ireland Galway, University Road Galway, Ireland
| | - David A Magee
- Animal Genomics Laboratory, UCD School of Agriculture and Food Science, University College Dublin Dublin, Ireland
| | - Stephen D E Park
- IdentiGEN Ltd, Unit 2, Trinity Enterprise Centre Dublin, Ireland
| | | | - Sinead M Waters
- Animal and Bioscience Research Department, Animal and Grassland Research and Innovation Centre, Teagasc Dunsany, Ireland
| | - David E MacHugh
- Animal Genomics Laboratory, UCD School of Agriculture and Food Science, University College DublinDublin, Ireland; UCD Conway Institute of Biomolecular and Biomedical Research, University College DublinDublin, Ireland
| | - Charles Spillane
- Genetics and Biotechnology Lab, Plant and AgriBiosciences Research Centre, School of Natural Sciences, National University of Ireland Galway, University Road Galway, Ireland
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Whitacre LK, Hoff JL, Schnabel RD, Albarella S, Ciotola F, Peretti V, Strozzi F, Ferrandi C, Ramunno L, Sonstegard TS, Williams JL, Taylor JF, Decker JE. Elucidating the genetic basis of an oligogenic birth defect using whole genome sequence data in a non-model organism, Bubalus bubalis. Sci Rep 2017; 7:39719. [PMID: 28045068 PMCID: PMC5206621 DOI: 10.1038/srep39719] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2016] [Accepted: 11/25/2016] [Indexed: 12/30/2022] Open
Abstract
Recent strong selection for dairy traits in water buffalo has been associated with higher levels of inbreeding, leading to an increase in the prevalence of genetic diseases such as transverse hemimelia (TH), a congenital developmental abnormality characterized by absence of a variable distal portion of the hindlimbs. Limited genomic resources available for water buffalo required an original approach to identify genetic variants associated with the disease. The genomes of 4 bilateral and 7 unilateral affected cases and 14 controls were sequenced. A concordance analysis of SNPs and INDELs requiring homozygosity unique to all unilateral and bilateral cases revealed two genes, WNT7A and SMARCA4, known to play a role in embryonic hindlimb development. Additionally, SNP alleles in NOTCH1 and RARB were homozygous exclusively in the bilateral cases, suggesting an oligogenic mode of inheritance. Homozygosity mapping by whole genome de novo assembly also supported oligogenic inheritance; implicating 13 genes involved in hindlimb development in bilateral cases and 11 in unilateral cases. A genome-wide association study (GWAS) predicted additional modifier genes. Although our data show a complex inheritance of TH, we predict that homozygous variants in WNT7A and SMARCA4 are necessary for expression of TH and selection against these variants should eradicate TH.
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Affiliation(s)
- Lynsey K Whitacre
- Informatics Institute, University of Missouri, Columbia, Missouri, USA.,Division of Animal Sciences, University of Missouri, Columbia, Missouri, USA
| | - Jesse L Hoff
- Division of Animal Sciences, University of Missouri, Columbia, Missouri, USA
| | - Robert D Schnabel
- Informatics Institute, University of Missouri, Columbia, Missouri, USA.,Division of Animal Sciences, University of Missouri, Columbia, Missouri, USA
| | - Sara Albarella
- Department of Veterinary Medicine and Animal Production, University of Naples Federico II, Naples, Italy
| | - Francesca Ciotola
- Department of Veterinary Medicine and Animal Production, University of Naples Federico II, Naples, Italy
| | - Vincenzo Peretti
- Department of Veterinary Medicine and Animal Production, University of Naples Federico II, Naples, Italy
| | | | | | - Luigi Ramunno
- Department of Agriculture, University of Naples Federico II, Portici, Napoli, Italy
| | | | - John L Williams
- Davies Research Centre, School of Animal and Veterinary Sciences, University of Adelaide, Roseworthy, Australia
| | - Jeremy F Taylor
- Division of Animal Sciences, University of Missouri, Columbia, Missouri, USA
| | - Jared E Decker
- Informatics Institute, University of Missouri, Columbia, Missouri, USA.,Division of Animal Sciences, University of Missouri, Columbia, Missouri, USA
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Abstract
Genomic selection has revolutionized dairy cattle breeding. Since 2000, assays have been developed to genotype large numbers of single-nucleotide polymorphisms (SNPs) at relatively low cost. The first commercial SNP genotyping chip was released with a set of 54,001 SNPs in December 2007. Over 15,000 genotypes were used to determine which SNPs should be used in genomic evaluation of US dairy cattle. Official USDA genomic evaluations were first released in January 2009 for Holsteins and Jerseys, in August 2009 for Brown Swiss, in April 2013 for Ayrshires, and in April 2016 for Guernseys. Producers have accepted genomic evaluations as accurate indications of a bull's eventual daughter-based evaluation. The integration of DNA marker technology and genomics into the traditional evaluation system has doubled the rate of genetic progress for traits of economic importance, decreased generation interval, increased selection accuracy, reduced previous costs of progeny testing, and allowed identification of recessive lethals.
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Affiliation(s)
- George R Wiggans
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, US Department of Agriculture, Beltsville, Maryland 20705-2350; , ,
| | - John B Cole
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, US Department of Agriculture, Beltsville, Maryland 20705-2350; , ,
| | - Suzanne M Hubbard
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, US Department of Agriculture, Beltsville, Maryland 20705-2350; , ,
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41
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Zhou Y, Xu L, Bickhart DM, Abdel Hay EH, Schroeder SG, Connor EE, Alexander LJ, Sonstegard TS, Van Tassell CP, Chen H, Liu GE. Reduced representation bisulphite sequencing of ten bovine somatic tissues reveals DNA methylation patterns and their impacts on gene expression. BMC Genomics 2016; 17:779. [PMID: 27716143 PMCID: PMC5053184 DOI: 10.1186/s12864-016-3116-1] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2016] [Accepted: 09/23/2016] [Indexed: 01/16/2023] Open
Abstract
Background As a major epigenetic component, DNA methylation plays important functions in individual development and various diseases. DNA methylation has been well studied in human and model organisms, but only limited data exist in economically important animals like cattle. Results Using reduced representation bisulphite sequencing (RRBS), we obtained single-base-resolution maps of bovine DNA methylation from ten somatic tissues. In total, we evaluated 1,868,049 cytosines in CG-enriched regions. While we found slightly low methylation levels (29.87 to 38.06 %) in cattle, the methylation contexts (CGs and non-CGs) of cattle showed similar methylation patterns to other species. Non-CG methylation was detected but methylation levels in somatic tissues were significantly lower than in pluripotent cells. To study the potential function of the methylation, we detected 10,794 differentially methylated cytosines (DMCs) and 836 differentially methylated CG islands (DMIs). Further analyses in the same tissues revealed many DMCs (including non-CGs) and DMIs, which were highly correlated with the expression of genes involved in tissue development. Conclusions In summary, our study provides a baseline dataset and essential information for DNA methylation profiles of cattle. Electronic supplementary material The online version of this article (doi:10.1186/s12864-016-3116-1) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Yang Zhou
- Shaanxi Key Laboratory of Agricultural Molecular Biology, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, 712100, People's Republic of China.,Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Building 306, Room 111, BARC-East, Beltsville, MD, 20705, USA
| | - Lingyang Xu
- Institute of Animal Science, Chinese Academy of Agricultural Science, Beijing, 100193, People's Republic of China
| | - Derek M Bickhart
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Building 306, Room 111, BARC-East, Beltsville, MD, 20705, USA
| | - El Hamidi Abdel Hay
- USDA Agricultural Research Service, Fort Keogh Livestock and Range Research Laboratory, Miles City, MT, 59301, USA
| | - Steven G Schroeder
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Building 306, Room 111, BARC-East, Beltsville, MD, 20705, USA
| | - Erin E Connor
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Building 306, Room 111, BARC-East, Beltsville, MD, 20705, USA
| | - Leeson J Alexander
- USDA Agricultural Research Service, Fort Keogh Livestock and Range Research Laboratory, Miles City, MT, 59301, USA
| | | | - Curtis P Van Tassell
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Building 306, Room 111, BARC-East, Beltsville, MD, 20705, USA
| | - Hong Chen
- Shaanxi Key Laboratory of Agricultural Molecular Biology, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, 712100, People's Republic of China.
| | - George E Liu
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Building 306, Room 111, BARC-East, Beltsville, MD, 20705, USA.
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42
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Adams HA, Sonstegard TS, VanRaden PM, Null DJ, Van Tassell CP, Larkin DM, Lewin HA. Identification of a nonsense mutation in APAF1 that is likely causal for a decrease in reproductive efficiency in Holstein dairy cattle. J Dairy Sci 2016; 99:6693-6701. [DOI: 10.3168/jds.2015-10517] [Citation(s) in RCA: 51] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2015] [Accepted: 04/23/2016] [Indexed: 11/19/2022]
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43
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G. T. Pereira A, Utsunomiya YT, Milanesi M, Torrecilha RBP, Carmo AS, Neves HHR, Carvalheiro R, Ajmone-Marsan P, Sonstegard TS, Sölkner J, Contreras-Castillo CJ, Garcia JF. Pleiotropic Genes Affecting Carcass Traits in Bos indicus (Nellore) Cattle Are Modulators of Growth. PLoS One 2016; 11:e0158165. [PMID: 27410030 PMCID: PMC4943724 DOI: 10.1371/journal.pone.0158165] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2016] [Accepted: 06/10/2016] [Indexed: 12/19/2022] Open
Abstract
Two complementary methods, namely Multi-Trait Meta-Analysis and Versatile Gene-Based Test for Genome-wide Association Studies (VEGAS), were used to identify putative pleiotropic genes affecting carcass traits in Bos indicus (Nellore) cattle. The genotypic data comprised over 777,000 single-nucleotide polymorphism markers scored in 995 bulls, and the phenotypic data included deregressed breeding values (dEBV) for weight measurements at birth, weaning and yearling, as well visual scores taken at weaning and yearling for carcass finishing precocity, conformation and muscling. Both analyses pointed to the pleomorphic adenoma gene 1 (PLAG1) as a major pleiotropic gene. VEGAS analysis revealed 224 additional candidates. From these, 57 participated, together with PLAG1, in a network involved in the modulation of the function and expression of IGF1 (insulin like growth factor 1), IGF2 (insulin like growth factor 2), GH1 (growth hormone 1), IGF1R (insulin like growth factor 1 receptor) and GHR (growth hormone receptor), suggesting that those pleiotropic genes operate as satellite regulators of the growth pathway.
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Affiliation(s)
- Anirene G. T. Pereira
- Departamento de Agroindústria, Alimentos e Nutrição, Escola Superior de Agricultura “Luiz de Queiroz”, USP, Piracicaba, Brazil
- International Atomic Energy Agency (IAEA) Collaborating Centre on Animal Genomics and Bioinformatics, Araçatuba, São Paulo, Brazil
| | - Yuri T. Utsunomiya
- Departamento de Medicina Veterinária Preventiva e Reprodução Animal, UNESP–Univ Estadual Paulista, Faculdade de Ciências Agrárias e Veterinárias, Jaboticabal, São Paulo, Brazil
- International Atomic Energy Agency (IAEA) Collaborating Centre on Animal Genomics and Bioinformatics, Araçatuba, São Paulo, Brazil
| | - Marco Milanesi
- Departamento de Apoio, Produção e Saúde Animal, UNESP—Univ Estadual Paulista, Faculdade de Medicina Veterinária de Araçatuba, Araçatuba, São Paulo, Brazil
- International Atomic Energy Agency (IAEA) Collaborating Centre on Animal Genomics and Bioinformatics, Araçatuba, São Paulo, Brazil
| | - Rafaela B. P. Torrecilha
- Departamento de Medicina Veterinária Preventiva e Reprodução Animal, UNESP–Univ Estadual Paulista, Faculdade de Ciências Agrárias e Veterinárias, Jaboticabal, São Paulo, Brazil
- International Atomic Energy Agency (IAEA) Collaborating Centre on Animal Genomics and Bioinformatics, Araçatuba, São Paulo, Brazil
| | - Adriana S. Carmo
- Departamento de Medicina Veterinária Preventiva e Reprodução Animal, UNESP–Univ Estadual Paulista, Faculdade de Ciências Agrárias e Veterinárias, Jaboticabal, São Paulo, Brazil
- International Atomic Energy Agency (IAEA) Collaborating Centre on Animal Genomics and Bioinformatics, Araçatuba, São Paulo, Brazil
| | | | - Roberto Carvalheiro
- Departamento de Zootecnia, UNESP—Univ. Estadual Paulista, Faculdade de Ciências Agrárias e Veterinárias, Jaboticabal, São Paulo, Brazil
| | | | | | - Johann Sölkner
- BOKU—University of Natural Resources and Life Sciences, Department of Sustainable Agricultural Systems, Division of Livestock Sciences, Vienna, Austria
| | - Carmen J. Contreras-Castillo
- Departamento de Agroindústria, Alimentos e Nutrição, Escola Superior de Agricultura “Luiz de Queiroz”, USP, Piracicaba, Brazil
| | - José F. Garcia
- Departamento de Medicina Veterinária Preventiva e Reprodução Animal, UNESP–Univ Estadual Paulista, Faculdade de Ciências Agrárias e Veterinárias, Jaboticabal, São Paulo, Brazil
- Departamento de Apoio, Produção e Saúde Animal, UNESP—Univ Estadual Paulista, Faculdade de Medicina Veterinária de Araçatuba, Araçatuba, São Paulo, Brazil
- International Atomic Energy Agency (IAEA) Collaborating Centre on Animal Genomics and Bioinformatics, Araçatuba, São Paulo, Brazil
- * E-mail:
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Zhou Y, Utsunomiya YT, Xu L, Hay EHA, Bickhart DM, Alexandre PA, Rosen BD, Schroeder SG, Carvalheiro R, de Rezende Neves HH, Sonstegard TS, Van Tassell CP, Ferraz JBS, Fukumasu H, Garcia JF, Liu GE. Genome-wide CNV analysis reveals variants associated with growth traits in Bos indicus. BMC Genomics 2016; 17:419. [PMID: 27245577 PMCID: PMC4888316 DOI: 10.1186/s12864-016-2461-4] [Citation(s) in RCA: 49] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2015] [Accepted: 02/11/2016] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND Apart from single nucleotide polymorphism (SNP), copy number variation (CNV) is another important type of genetic variation, which may affect growth traits and play key roles for the production of beef cattle. To date, no genome-wide association study (GWAS) for CNV and body traits in beef cattle has been reported, so the present study aimed to investigate this type of association in one of the most important cattle subspecies: Bos indicus (Nellore breed). RESULTS We have used intensity data from over 700,000 SNP probes across the bovine genome to detect common CNVs in a sample of 2230 Nellore cattle, and performed GWAS between the detected CNVs and nine growth traits. After filtering for frequency and length, a total of 231 CNVs ranging from 894 bp to 4,855,088 bp were kept and tested as predictors for each growth trait using linear regression analysis with principal components correction. There were 49 significant associations identified among 17 CNVs and seven body traits after false discovery rate correction (P < 0.05). Among the 17 CNVs, three were significant or marginally significant for all the traits. We have compared the locations of associated CNVs with quantitative trait locus and the RefGene database, and found two sets of 9 CNVs overlapping with either known QTLs or genes, respectively. The gene overlapping with CNV100, KCNJ12, is a functional candidate for muscle development and plays critical roles in muscling traits. CONCLUSION This study presents the first CNV-based GWAS of growth traits using high density SNP microarray data in cattle. We detected 17 CNVs significantly associated with seven growth traits and one of them (CNV100) may be involved in growth traits through KCNJ12.
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Affiliation(s)
- Yang Zhou
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Room 111, BARC-East, Beltsville, Maryland, 20705, USA.,College of Animal Science and Technology, Northwest A&F University, Shaanxi Key Laboratory of Agricultural Molecular Biology, Yangling, Shaanxi, 712100, China
| | - Yuri T Utsunomiya
- Departamento de Medicina Veterinária Preventiva e Reprodução Animal, Faculdade de Ciências Agrárias e Veterinárias, UNESP - Univ Estadual Paulista, Jaboticabal, São Paulo, 14884-900, Brazil
| | - Lingyang Xu
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Room 111, BARC-East, Beltsville, Maryland, 20705, USA.,Institute of Animal Science, Chinese Academy of Agricultural Science, Beijing, 100193, China
| | - El Hamidi Abdel Hay
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Room 111, BARC-East, Beltsville, Maryland, 20705, USA
| | - Derek M Bickhart
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Room 111, BARC-East, Beltsville, Maryland, 20705, USA
| | - Pamela Almeida Alexandre
- Department of Veterinary Medicine, College of Animal Science and Food Engineering, University of São Paulo, Pirassununga, SP, 13635, Brazil
| | - Benjamin D Rosen
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Room 111, BARC-East, Beltsville, Maryland, 20705, USA
| | - Steven G Schroeder
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Room 111, BARC-East, Beltsville, Maryland, 20705, USA
| | - Roberto Carvalheiro
- Departamento de Zootecnia, Faculdade de Ciências Agrárias e Veterinárias, UNESP - Univ Estadual Paulista, Jaboticabal, São Paulo, 14884-900, Brazil
| | - Haroldo Henrique de Rezende Neves
- Departamento de Zootecnia, Faculdade de Ciências Agrárias e Veterinárias, UNESP - Univ Estadual Paulista, Jaboticabal, São Paulo, 14884-900, Brazil
| | - Tad S Sonstegard
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Room 111, BARC-East, Beltsville, Maryland, 20705, USA.,Present address: Recombinetics, Inc., St Paul, MN, 55104, USA
| | - Curtis P Van Tassell
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Room 111, BARC-East, Beltsville, Maryland, 20705, USA
| | - José Bento Sterman Ferraz
- Department of Veterinary Medicine, College of Animal Science and Food Engineering, University of São Paulo, Pirassununga, SP, 13635, Brazil
| | - Heidge Fukumasu
- Department of Veterinary Medicine, College of Animal Science and Food Engineering, University of São Paulo, Pirassununga, SP, 13635, Brazil
| | - Jose Fernando Garcia
- Departamento de Medicina Veterinária Preventiva e Reprodução Animal, Faculdade de Ciências Agrárias e Veterinárias, UNESP - Univ Estadual Paulista, Jaboticabal, São Paulo, 14884-900, Brazil. .,Departamento de Apoio, Produção e Saúde Animal, Faculdade de Medicina Veterinária de Araçatuba, UNESP - Univ Estadual Paulista, Araçatuba, São Paulo, 16050-680, Brazil. .,International Atomic Energy Agency (IAEA) Collaborating Centre on Animal Genomics and Bioinformatics, Araçatuba, SP, Brazil.
| | - George E Liu
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Room 111, BARC-East, Beltsville, Maryland, 20705, USA.
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45
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Carrillo JA, He Y, Li Y, Liu J, Erdman RA, Sonstegard TS, Song J. Integrated metabolomic and transcriptome analyses reveal finishing forage affects metabolic pathways related to beef quality and animal welfare. Sci Rep 2016. [PMID: 27185157 DOI: 10.1038/srep] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/03/2023] Open
Abstract
Beef represents a major dietary component and source of protein in many countries. With an increasing demand for beef, the industry is currently undergoing changes towards naturally produced beef. However, the true differences between the feeding systems, especially the biochemical and nutritional aspects, are still unclear. Using transcriptome and metabolome profiles, we identified biological pathways related to the differences between grass- and grain-fed Angus steers. In the latissimus dorsi muscle, we have recognized 241 differentially expressed genes (FDR < 0.1). The metabolome examinations of muscle and blood revealed 163 and 179 altered compounds in each tissue (P < 0.05), respectively. Accordingly, alterations in glucose metabolism, divergences in free fatty acids and carnitine conjugated lipid levels, and altered β-oxidation have been observed. The anti-inflammatory n3 polyunsaturated fatty acids are enriched in grass finished beef, while higher levels of n6 PUFAs in grain finished animals may promote inflammation and oxidative stress. Furthermore, grass-fed animals produce tender beef with lower total fat and a higher omega3/omega6 ratio than grain-fed ones, which could potentially benefit consumer health. Most importantly, blood cortisol levels strongly indicate that grass-fed animals may experience less stress than the grain-fed individuals. These results will provide deeper insights into the merits and mechanisms of muscle development.
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Affiliation(s)
- José A Carrillo
- Department of Animal &Avian Sciences, University of Maryland, College Park, MD 20742, USA
| | - Yanghua He
- Department of Animal &Avian Sciences, University of Maryland, College Park, MD 20742, USA
| | - Yaokun Li
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, P.R. China, 712100
| | - Jianan Liu
- Department of Animal &Avian Sciences, University of Maryland, College Park, MD 20742, USA
| | - Richard A Erdman
- Department of Animal &Avian Sciences, University of Maryland, College Park, MD 20742, USA
| | - Tad S Sonstegard
- Recombinetics Inc., 1246 University Ave. W, St. Paul, MN 55104, USA
| | - Jiuzhou Song
- Department of Animal &Avian Sciences, University of Maryland, College Park, MD 20742, USA
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46
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Carrillo JA, He Y, Li Y, Liu J, Erdman RA, Sonstegard TS, Song J. Integrated metabolomic and transcriptome analyses reveal finishing forage affects metabolic pathways related to beef quality and animal welfare. Sci Rep 2016; 6:25948. [PMID: 27185157 PMCID: PMC4869019 DOI: 10.1038/srep25948] [Citation(s) in RCA: 54] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2015] [Accepted: 04/18/2016] [Indexed: 11/09/2022] Open
Abstract
Beef represents a major dietary component and source of protein in many countries. With an increasing demand for beef, the industry is currently undergoing changes towards naturally produced beef. However, the true differences between the feeding systems, especially the biochemical and nutritional aspects, are still unclear. Using transcriptome and metabolome profiles, we identified biological pathways related to the differences between grass- and grain-fed Angus steers. In the latissimus dorsi muscle, we have recognized 241 differentially expressed genes (FDR < 0.1). The metabolome examinations of muscle and blood revealed 163 and 179 altered compounds in each tissue (P < 0.05), respectively. Accordingly, alterations in glucose metabolism, divergences in free fatty acids and carnitine conjugated lipid levels, and altered β-oxidation have been observed. The anti-inflammatory n3 polyunsaturated fatty acids are enriched in grass finished beef, while higher levels of n6 PUFAs in grain finished animals may promote inflammation and oxidative stress. Furthermore, grass-fed animals produce tender beef with lower total fat and a higher omega3/omega6 ratio than grain-fed ones, which could potentially benefit consumer health. Most importantly, blood cortisol levels strongly indicate that grass-fed animals may experience less stress than the grain-fed individuals. These results will provide deeper insights into the merits and mechanisms of muscle development.
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Affiliation(s)
- José A Carrillo
- Department of Animal &Avian Sciences, University of Maryland, College Park, MD 20742, USA
| | - Yanghua He
- Department of Animal &Avian Sciences, University of Maryland, College Park, MD 20742, USA
| | - Yaokun Li
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, P.R. China, 712100
| | - Jianan Liu
- Department of Animal &Avian Sciences, University of Maryland, College Park, MD 20742, USA
| | - Richard A Erdman
- Department of Animal &Avian Sciences, University of Maryland, College Park, MD 20742, USA
| | - Tad S Sonstegard
- Recombinetics Inc., 1246 University Ave. W, St. Paul, MN 55104, USA
| | - Jiuzhou Song
- Department of Animal &Avian Sciences, University of Maryland, College Park, MD 20742, USA
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47
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Benavides MV, Sonstegard TS, Van Tassell C. Genomic Regions Associated with Sheep Resistance to Gastrointestinal Nematodes. Trends Parasitol 2016; 32:470-480. [PMID: 27183838 DOI: 10.1016/j.pt.2016.03.007] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2015] [Revised: 01/14/2016] [Accepted: 03/16/2016] [Indexed: 12/18/2022]
Abstract
Genetic markers for sheep resistance to gastrointestinal parasites have long been sought by the livestock industry as a way to select more resistant individuals and to help farmers reduce parasite transmission by identifying and removing high egg shedders from the flock. Polymorphisms related to the major histocompatibility complex and interferon (IFN)-γ genes have been the most frequently reported markers associated with infection. Recently, a new picture is emerging from genome-wide studies, showing that not only immune mechanisms are important determinants of host resistance but that gastrointestinal mucus production and hemostasis pathways may also play a role.
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Affiliation(s)
| | | | - Curtis Van Tassell
- Animal Genomics and Improvement Laboratory, US Department of Agriculture (USDA)/Agricultural Research Service (ARS) Beltsville Agricultural Research Center, Beltsville, MD, USA
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48
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Bickhart DM, Xu L, Hutchison JL, Cole JB, Null DJ, Schroeder SG, Song J, Garcia JF, Sonstegard TS, Van Tassell CP, Schnabel RD, Taylor JF, Lewin HA, Liu GE. Diversity and population-genetic properties of copy number variations and multicopy genes in cattle. DNA Res 2016; 23:253-62. [PMID: 27085184 PMCID: PMC4909312 DOI: 10.1093/dnares/dsw013] [Citation(s) in RCA: 54] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2015] [Accepted: 02/29/2016] [Indexed: 11/14/2022] Open
Abstract
The diversity and population genetics of copy number variation (CNV) in domesticated animals are not well understood. In this study, we analysed 75 genomes of major taurine and indicine cattle breeds (including Angus, Brahman, Gir, Holstein, Jersey, Limousin, Nelore, and Romagnola), sequenced to 11-fold coverage to identify 1,853 non-redundant CNV regions. Supported by high validation rates in array comparative genomic hybridization (CGH) and qPCR experiments, these CNV regions accounted for 3.1% (87.5 Mb) of the cattle reference genome, representing a significant increase over previous estimates of the area of the genome that is copy number variable (∼2%). Further population genetics and evolutionary genomics analyses based on these CNVs revealed the population structures of the cattle taurine and indicine breeds and uncovered potential diversely selected CNVs near important functional genes, including AOX1, ASZ1, GAT, GLYAT, and KRTAP9-1. Additionally, 121 CNV gene regions were found to be either breed specific or differentially variable across breeds, such as RICTOR in dairy breeds and PNPLA3 in beef breeds. In contrast, clusters of the PRP and PAG genes were found to be duplicated in all sequenced animals, suggesting that subfunctionalization, neofunctionalization, or overdominance play roles in diversifying those fertility-related genes. These CNV results provide a new glimpse into the diverse selection histories of cattle breeds and a basis for correlating structural variation with complex traits in the future.
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Affiliation(s)
- Derek M Bickhart
- USDA-ARS, Animal Genomics and Improvement Laboratory, Beltsville, MD 20705, USA
| | - Lingyang Xu
- USDA-ARS, Animal Genomics and Improvement Laboratory, Beltsville, MD 20705, USA Department of Animal and Avian Sciences, University of Maryland, College Park, MD 20742, USA
| | - Jana L Hutchison
- USDA-ARS, Animal Genomics and Improvement Laboratory, Beltsville, MD 20705, USA
| | - John B Cole
- USDA-ARS, Animal Genomics and Improvement Laboratory, Beltsville, MD 20705, USA
| | - Daniel J Null
- USDA-ARS, Animal Genomics and Improvement Laboratory, Beltsville, MD 20705, USA
| | - Steven G Schroeder
- USDA-ARS, Animal Genomics and Improvement Laboratory, Beltsville, MD 20705, USA
| | - Jiuzhou Song
- Department of Animal and Avian Sciences, University of Maryland, College Park, MD 20742, USA
| | | | - Tad S Sonstegard
- USDA-ARS, Animal Genomics and Improvement Laboratory, Beltsville, MD 20705, USA
| | | | - Robert D Schnabel
- Division of Animal Sciences, University of Missouri, Columbia, MO 65211, USA Informatics Institute, University of Missouri, Columbia, MO, USA
| | - Jeremy F Taylor
- Division of Animal Sciences, University of Missouri, Columbia, MO 65211, USA
| | - Harris A Lewin
- Department of Evolution and Ecology, University of California, Davis, CA 95616, USA
| | - George E Liu
- USDA-ARS, Animal Genomics and Improvement Laboratory, Beltsville, MD 20705, USA
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Wiggans GR, Cooper TA, VanRaden PM, Van Tassell CP, Bickhart DM, Sonstegard TS. Increasing the number of single nucleotide polymorphisms used in genomic evaluation of dairy cattle. J Dairy Sci 2016; 99:4504-4511. [PMID: 27040793 DOI: 10.3168/jds.2015-10456] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2015] [Accepted: 02/14/2016] [Indexed: 11/19/2022]
Abstract
GeneSeek (Neogen Corp., Lexington, KY) designed a new version of the GeneSeek Genomic Profiler HD BeadChip for Dairy Cattle, which originally had >77,000 single nucleotide polymorphisms (SNP). A set of >140,000 SNP was selected that included all SNP on the existing GeneSeek chip, all SNP used in US national genomic evaluations, SNP that were possible functional mutations, and other informative SNP. Because SNP with a lower minor allele frequency might track causative variants better, 30,000 more SNP were selected from the Illumina BovineHD Genotyping BeadChip (Illumina Inc., San Diego, CA) by choosing SNP to maximize differences in minor allele frequency between a SNP being considered for the new chip and the 2 SNP that flanked it. Single-gene tests were included if their location was known and bioinformatics indicated relevance for dairy cattle. To determine which SNP from the new chip should be included in genomic evaluations, genotypes available from chips already in use were used to impute and evaluate the SNP set. Effects for 134,511 usable SNP were estimated for all breed-trait combinations; SNP with the largest absolute values for effects were selected (5,000 for Holsteins, 1,000 for Jerseys, and 500 each for Brown Swiss and Ayrshires for each trait). To increase overlap with the 60,671 SNP currently used for genomic evaluation, 12,094 more SNP with the largest effects were added. After removing SNP with many parent-progeny conflicts, 84,937 SNP remained. Three cutoff studies were conducted with 3 SNP sets to determine reliability gain over that for parent average when evaluations based on August 2011 data were used to predict December 2014 performance. Across all traits, mean Holstein reliability gains were 32.5, 33.4, and 32.0 percentage points for 60,671, 84,937, and 134,511 SNP, respectively. After genotypes from the new chip became available, the proposed set was reduced from 84,937 to 77,321 SNP to remove SNP that were not included during manufacture, reduce computing time, and improve imputation performance. The set of 77,321 SNP was evaluated using August 2011 data to predict April 2015 performance. Reliability gain over 60,671 SNP was 1.4 percentage points across traits for Holsteins. Improvement over 84,937 SNP was partially the result of 4mo of additional data and genotypes from the new chip. Revision of the SNP set used for genomic evaluation is expected to be an ongoing process to increase evaluation accuracy.
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Affiliation(s)
- G R Wiggans
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, MD 20705-2350.
| | - T A Cooper
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, MD 20705-2350
| | - P M VanRaden
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, MD 20705-2350
| | - C P Van Tassell
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, MD 20705-2350
| | - D M Bickhart
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, MD 20705-2350
| | - T S Sonstegard
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, MD 20705-2350
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50
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Xu L, Hou Y, Bickhart DM, Zhou Y, Hay EHA, Song J, Sonstegard TS, Van Tassell CP, Liu GE. Population-genetic properties of differentiated copy number variations in cattle. Sci Rep 2016; 6:23161. [PMID: 27005566 PMCID: PMC4804293 DOI: 10.1038/srep23161] [Citation(s) in RCA: 53] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2015] [Accepted: 02/25/2016] [Indexed: 01/24/2023] Open
Abstract
While single nucleotide polymorphism (SNP) is typically the variant of choice for population genetics, copy number variation (CNV) which comprises insertion, deletion and duplication of genomic sequence, is an informative type of genetic variation. CNVs have been shown to be both common in mammals and important for understanding the relationship between genotype and phenotype. However, CNV differentiation, selection and its population genetic properties are not well understood across diverse populations. We performed a population genetics survey based on CNVs derived from the BovineHD SNP array data of eight distinct cattle breeds. We generated high resolution results that show geographical patterns of variations and genome-wide admixture proportions within and among breeds. Similar to the previous SNP-based studies, our CNV-based results displayed a strong correlation of population structure and geographical location. By conducting three pairwise comparisons among European taurine, African taurine, and indicine groups, we further identified 78 unique CNV regions that were highly differentiated, some of which might be due to selection. These CNV regions overlapped with genes involved in traits related to parasite resistance, immunity response, body size, fertility, and milk production. Our results characterize CNV diversity among cattle populations and provide a list of lineage-differentiated CNVs.
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Affiliation(s)
- Lingyang Xu
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, Maryland 20705, USA.,Department of Animal and Avian Sciences, University of Maryland, College Park, Maryland 20742, USA
| | - Yali Hou
- Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, 100101, China
| | - Derek M Bickhart
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, Maryland 20705, USA
| | - Yang Zhou
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, Maryland 20705, USA.,College of Animal Science and Technology, Northwest A&F University, Shaanxi Key Laboratory of Agricultural Molecular Biology, Yangling, Shaanxi, 712100, China
| | - El Hamidi Abdel Hay
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, Maryland 20705, USA
| | - Jiuzhou Song
- Department of Animal and Avian Sciences, University of Maryland, College Park, Maryland 20742, USA
| | - Tad S Sonstegard
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, Maryland 20705, USA
| | - Curtis P Van Tassell
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, Maryland 20705, USA
| | - George E Liu
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, Maryland 20705, USA
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