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Pocrnic I, Lourenco D, Misztal I. Single nucleotide polymorphism profile for quantitative trait nucleotide in populations with small effective size and its impact on mapping and genomic predictions. Genetics 2024; 227:iyae103. [PMID: 38913695 PMCID: PMC11304960 DOI: 10.1093/genetics/iyae103] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2024] [Revised: 06/07/2024] [Accepted: 06/16/2024] [Indexed: 06/26/2024] Open
Abstract
Increasing SNP density by incorporating sequence information only marginally increases prediction accuracies of breeding values in livestock. To find out why, we used statistical models and simulations to investigate the shape of distribution of estimated SNP effects (a profile) around quantitative trait nucleotides (QTNs) in populations with a small effective population size (Ne). A QTN profile created by averaging SNP effects around each QTN was similar to the shape of expected pairwise linkage disequilibrium (PLD) based on Ne and genetic distance between SNP, with a distinct peak for the QTN. Populations with smaller Ne showed lower but wider QTN profiles. However, adding more genotyped individuals with phenotypes dragged the profile closer to the QTN. The QTN profile was higher and narrower for populations with larger compared to smaller Ne. Assuming the PLD curve for the QTN profile, 80% of the additive genetic variance explained by each QTN was contained in ± 1/Ne Morgan interval around the QTN, corresponding to 2 Mb in cattle and 5 Mb in pigs and chickens. With such large intervals, identifying QTN is difficult even if all of them are in the data and the assumed genetic architecture is simplistic. Additional complexity in QTN detection arises from confounding of QTN profiles with signals due to relationships, overlapping profiles with closely spaced QTN, and spurious signals. However, small Ne allows for accurate predictions with large data even without QTN identification because QTNs are accounted for by QTN profiles if SNP density is sufficient to saturate the segments.
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Affiliation(s)
- Ivan Pocrnic
- Department of Animal and Dairy Science, University of Georgia, Athens, GA 30602, USA
| | - Daniela Lourenco
- Department of Animal and Dairy Science, University of Georgia, Athens, GA 30602, USA
| | - Ignacy Misztal
- Department of Animal and Dairy Science, University of Georgia, Athens, GA 30602, USA
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2
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Kalbfleisch TS, McKay SD, Murdoch BM, Adelson DL, Almansa-Villa D, Becker G, Beckett LM, Benítez-Galeano MJ, Biase F, Casey T, Chuong E, Clark E, Clarke S, Cockett N, Couldrey C, Davis BW, Elsik CG, Faraut T, Gao Y, Genet C, Grady P, Green J, Green R, Guan D, Hagen D, Hartley GA, Heaton M, Hoyt SJ, Huang W, Jarvis E, Kalleberg J, Khatib H, Koepfi KP, Koltes J, Koren S, Kuehn C, Leeb T, Leonard A, Liu GE, Low WY, McConnell H, McRae K, Miga K, Mousel M, Neibergs H, Olagunju T, Pennell M, Petry B, Pewsner M, Phillippy AM, Pickett BD, Pineda P, Potapova T, Rachagani S, Rhie A, Rijnkels M, Robic A, Rodriguez Osorio N, Safonova Y, Schettini G, Schnabel RD, Sirpu Natesh N, Stegemiller M, Storer J, Stothard P, Stull C, Tosser-Klopp G, Traglia GM, Tuggle CK, Van Tassell CP, Watson C, Weikard R, Wimmers K, Xie S, Yang L, Smith TPL, O'Neill RJ, Rosen BD. The Ruminant Telomere-to-Telomere (RT2T) Consortium. Nat Genet 2024:10.1038/s41588-024-01835-2. [PMID: 39103649 DOI: 10.1038/s41588-024-01835-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Accepted: 06/14/2024] [Indexed: 08/07/2024]
Abstract
Telomere-to-telomere (T2T) assemblies reveal new insights into the structure and function of the previously 'invisible' parts of the genome and allow comparative analyses of complete genomes across entire clades. We present here an open collaborative effort, termed the 'Ruminant T2T Consortium' (RT2T), that aims to generate complete diploid assemblies for numerous species of the Artiodactyla suborder Ruminantia to examine chromosomal evolution in the context of natural selection and domestication of species used as livestock.
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Affiliation(s)
| | - Stephanie D McKay
- Division of Animal Sciences, University of Missouri, Columbia, MO, USA
| | - Brenda M Murdoch
- Department of Animal, Veterinary and Food Sciences, University of Idaho, Moscow, ID, USA
| | - David L Adelson
- School of Biological Sciences, the University of Adelaide, North Terrace, Adelaide, South Australia, Australia
| | - Diego Almansa-Villa
- Genomics and Bioinformatics Unit, Departamento de Ciencias Biológicas, CENUR Litoral Norte, Universidad de la República, Salto, Uruguay
| | - Gabrielle Becker
- Department of Animal, Veterinary and Food Sciences, University of Idaho, Moscow, ID, USA
| | - Linda M Beckett
- Department of Animal Sciences, Purdue University, West Lafayette, IN, USA
| | - María José Benítez-Galeano
- Genomics and Bioinformatics Unit, Departamento de Ciencias Biológicas, CENUR Litoral Norte, Universidad de la República, Salto, Uruguay
| | - Fernando Biase
- School of Animal Sciences, Virginia Polytechnic Institute and State University, Blacksburg, VA, USA
| | - Theresa Casey
- Department of Animal Sciences, Purdue University, West Lafayette, IN, USA
| | - Edward Chuong
- BioFrontiers Institute, Department of Molecular Cellular and Developmental Biology, University of Colorado Boulder, Boulder, CO, USA
| | - Emily Clark
- The Roslin Institute, University of Edinburgh, Edinburgh, UK
| | - Shannon Clarke
- Invermay Agricultural Centre, AgResearch Ltd, Mosgiel, New Zealand
| | - Noelle Cockett
- Department of Animal, Dairy and Veterinary Sciences, Utah State University, Logan, UT, USA
| | | | - Brian W Davis
- Department of Veterinary Pathobiology, School of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX, USA
| | - Christine G Elsik
- Division of Animal Sciences, University of Missouri, Columbia, MO, USA
| | - Thomas Faraut
- GenPhySE, Université de Toulouse, INRAE, ENVT, Castanet Tolosan, France
| | - Yahui Gao
- Animal Genomics and Improvement Laboratory, USDA ARS, Beltsville, MD, USA
| | - Carine Genet
- GenPhySE, Université de Toulouse, INRAE, ENVT, Castanet Tolosan, France
| | - Patrick Grady
- Institute for Systems Genomics, University of Connecticut, Storrs, CT, USA
| | - Jonathan Green
- Division of Animal Sciences, University of Missouri, Columbia, MO, USA
| | - Richard Green
- Institute for Systems Genomics, University of Connecticut, Storrs, CT, USA
| | - Dailu Guan
- Department of Animal Science, University of California, Davis, Davis, CA, USA
| | - Darren Hagen
- Department of Animal and Food Sciences, Oklahoma State University, Stillwater, OK, USA
| | | | - Mike Heaton
- U.S. Meat Animal Research Center, USDA ARS, Clay Center, NE, USA
| | - Savannah J Hoyt
- Institute for Systems Genomics, University of Connecticut, Storrs, CT, USA
| | - Wen Huang
- Department of Animal Science, Michigan State University, East Lansing, MI, USA
| | - Erich Jarvis
- Vertebrate Genome Laboratory, the Rockefeller University, New York, NY, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
| | - Jenna Kalleberg
- Division of Animal Sciences, University of Missouri, Columbia, MO, USA
| | - Hasan Khatib
- Department of Animal and Dairy Sciences, the University of Wisconsin-Madison, Madison, WI, USA
| | - Klaus-Peter Koepfi
- Smithsonian-Mason School of Conservation, George Mason University, Front Royal, VA, USA
- Center for Species Survival, Smithsonian's National Zoo and Conservation Biology Institute, Front Royal, VA, USA
| | - James Koltes
- Department of Animal Science, Iowa State University, Ames, IA, USA
| | - Sergey Koren
- Genome Informatics Section, Center for Genomics and Data Science Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Christa Kuehn
- Friedrich-Loeffler-Institute (German Federal Research Institute for Animal Health), Greifswald-Insel Riems, Germany
| | - Tosso Leeb
- Institute of Genetics, Vetsuisse Faculty, University of Bern, Bern, Switzerland
| | | | - George E Liu
- Animal Genomics and Improvement Laboratory, USDA ARS, Beltsville, MD, USA
| | - Wai Yee Low
- The Davies Research Centre, School of Animal and Veterinary Sciences, University of Adelaide, Roseworthy, South Australia, Australia
| | - Hunter McConnell
- Division of Animal Sciences, University of Missouri, Columbia, MO, USA
| | - Kathryn McRae
- Invermay Agricultural Centre, AgResearch Ltd, Mosgiel, New Zealand
| | - Karen Miga
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
- Biomolecular Engineering Department, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Michelle Mousel
- Animal Disease Research Unit, USDA ARS, Pullman, WA, USA
- School for Global Animal Health, Washington State University, Pullman, WA, USA
| | - Holly Neibergs
- Department of Animal Science, Washington State University, Pullman, WA, USA
| | - Temitayo Olagunju
- Department of Animal, Veterinary and Food Sciences, University of Idaho, Moscow, ID, USA
| | - Matt Pennell
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA
| | - Bruna Petry
- Department of Animal Science, Iowa State University, Ames, IA, USA
| | - Mirjam Pewsner
- Institute of Fish and Wildlife Health, Vetsuisse Faculty, University of Bern, Bern, Switzerland
| | - Adam M Phillippy
- Genome Informatics Section, Center for Genomics and Data Science Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Brandon D Pickett
- Genome Informatics Section, Center for Genomics and Data Science Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Paulene Pineda
- The Davies Research Centre, School of Animal and Veterinary Sciences, University of Adelaide, Roseworthy, South Australia, Australia
| | - Tamara Potapova
- Stowers Institute for Medical Research, Kansas City, MO, USA
| | - Satyanarayana Rachagani
- Veterinary Medicine and Surgery, NextGen Precision Health Institute, University of Missouri, Columbia, MO, USA
| | - Arang Rhie
- Genome Informatics Section, Center for Genomics and Data Science Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Monique Rijnkels
- Department of Veterinary Integrative Biosciences, School of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX, USA
| | - Annie Robic
- GenPhySE, Université de Toulouse, INRAE, ENVT, Castanet Tolosan, France
| | - Nelida Rodriguez Osorio
- Genomics and Bioinformatics Unit, Departamento de Ciencias Biológicas, CENUR Litoral Norte, Universidad de la República, Salto, Uruguay
| | - Yana Safonova
- Computer Science and Engineering Department, Huck Institutes of the Life Sciences, Pennsylvania State University, State College, PA, USA
| | - Gustavo Schettini
- School of Animal Sciences, Virginia Polytechnic Institute and State University, Blacksburg, VA, USA
| | - Robert D Schnabel
- Division of Animal Sciences, University of Missouri, Columbia, MO, USA
| | | | - Morgan Stegemiller
- Department of Animal, Veterinary and Food Sciences, University of Idaho, Moscow, ID, USA
| | - Jessica Storer
- Department of Molecular and Cell Biology, University of Connecticut, Storrs, CT, USA
| | - Paul Stothard
- Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, Alberta, Canada
| | - Caleb Stull
- Division of Animal Sciences, University of Missouri, Columbia, MO, USA
| | | | - Germán M Traglia
- Genomics and Bioinformatics Unit, Departamento de Ciencias Biológicas, CENUR Litoral Norte, Universidad de la República, Salto, Uruguay
| | | | | | - Corey Watson
- Department of Biochemistry and Molecular Genetics, University of Louisville, Louisville, KY, USA
| | - Rosemarie Weikard
- Institute of Genome Biology, Research Institute for Farm Animal Biology (FBN), Dummerstorf, Germany
| | - Klaus Wimmers
- Institute of Genome Biology, Research Institute for Farm Animal Biology (FBN), Dummerstorf, Germany
| | - Shangqian Xie
- Department of Animal, Veterinary and Food Sciences, University of Idaho, Moscow, ID, USA
| | - Liu Yang
- Animal Genomics and Improvement Laboratory, USDA ARS, Beltsville, MD, USA
| | | | - Rachel J O'Neill
- Institute for Systems Genomics, University of Connecticut, Storrs, CT, USA.
- Department of Molecular and Cell Biology, University of Connecticut, Storrs, CT, USA.
| | - Benjamin D Rosen
- Animal Genomics and Improvement Laboratory, USDA ARS, Beltsville, MD, USA.
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3
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Leonard AS, Mapel XM, Pausch H. RNA-DNA differences in variant calls from cattle tissues result in erroneous eQTLs. BMC Genomics 2024; 25:750. [PMID: 39090567 PMCID: PMC11295900 DOI: 10.1186/s12864-024-10645-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2024] [Accepted: 07/22/2024] [Indexed: 08/04/2024] Open
Abstract
BACKGROUND Association testing between molecular phenotypes and genomic variants can help to understand how genotype affects phenotype. RNA sequencing provides access to molecular phenotypes such as gene expression and alternative splicing while DNA sequencing or microarray genotyping are the prevailing options to obtain genomic variants. RESULTS We genotype variants for 74 male Braunvieh cattle from both DNA (~ 13-fold coverage) and deep total RNA sequencing from testis, vas deferens, and epididymis tissue (~ 250 million reads per tissue). We show that RNA sequencing can be used to identify approximately 40% of variants (7-10 million) called from DNA sequencing, with over 80% precision. Within highly expressed coding regions, over 92% of expected variants were called with nearly 98% precision. Allele-specific expression and putative post-transcriptional modifications negatively impact variant genotyping accuracy from RNA sequencing and contribute to RNA-DNA differences. Variants called from RNA sequencing detect roughly 75% of eGenes identified using variants called from DNA sequencing, demonstrating a nearly 2-fold enrichment of eQTL variants. We observe a moderate-to-strong correlation in nominal association p-values (Spearman ρ2 ~ 0.6), although only 9% of eGenes have the same top associated variant. CONCLUSIONS We find hundreds of thousands of RNA-DNA differences in variants called from RNA and DNA sequencing on the same individuals. We identify several highly significant eQTL when using RNA sequencing variant genotypes which are not found with DNA sequencing variant genotypes, suggesting that using RNA sequencing variant genotypes for association testing results in an increased number of false positives. Our findings demonstrate that caution must be exercised beyond filtering for variant quality or imputation accuracy when analysing or imputing variants called from RNA sequencing.
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Affiliation(s)
- Alexander S Leonard
- Animal Genomics, ETH Zurich, Universitaetstrasse 2, Zurich, 8092, Switzerland.
| | - Xena M Mapel
- Animal Genomics, ETH Zurich, Universitaetstrasse 2, Zurich, 8092, Switzerland
| | - Hubert Pausch
- Animal Genomics, ETH Zurich, Universitaetstrasse 2, Zurich, 8092, Switzerland.
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4
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Mulim HA, Pedrosa VB, Pinto LFB, Tiezzi F, Maltecca C, Schenkel FS, Brito LF. Detection and evaluation of parameters influencing the identification of heterozygous-enriched regions in Holstein cattle based on SNP chip or whole-genome sequence data. BMC Genomics 2024; 25:726. [PMID: 39060982 PMCID: PMC11282608 DOI: 10.1186/s12864-024-10642-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2023] [Accepted: 07/19/2024] [Indexed: 07/28/2024] Open
Abstract
BACKGROUND A heterozygous-enriched region (HER) is a genomic region with high variability generated by factors such as balancing selection, introgression, and admixture processes. In this study, we evaluated the genomic background of HERs and the impact of different parameters (i.e., minimum number of SNPs in a HER, maximum distance between two consecutive SNPs, minimum length of a HER, maximum number of homozygous allowed in a HER) and scenarios [i.e., different SNP panel densities and whole-genome sequence (WGS)] on the detection of HERs. We also compared HERs characterized in Holstein cattle with those identified in Angus, Jersey, and Norwegian Red cattle using WGS data. RESULTS The parameters used for the identification of HERs significantly impact their detection. The maximum distance between two consecutive SNPs did not impact HERs detection as the same average of HERs (269.31 ± 787.00) was observed across scenarios. However, the minimum number of markers, maximum homozygous markers allowed inside a HER, and the minimum length size impacted HERs detection. For the minimum length size, the 10 Kb scenario showed the highest average number of HERs (1,364.69 ± 1,483.64). The number of HERs decreased as the minimum number of markers increased (621.31 ± 1,271.83 to 6.08 ± 21.94), and an opposite pattern was observed for the maximum homozygous markers allowed inside a HER (54.47 ± 195.51 to 494.89 ± 1,169.35). Forty-five HER islands located in 23 chromosomes with high Tajima's D values and differential among the observed and estimated heterozygosity were detected in all evaluated scenarios, indicating their ability to potentially detect regions under balancing selection. In total, 3,440 markers and 28 genes previously related to fertility (e.g., TP63, ZSCAN23, NEK5, ARHGAP44), immunity (e.g., TP63, IGC, ARHGAP44), residual feed intake (e.g., MAYO9A), stress sensitivity (e.g., SERPINA6), and milk fat percentage (e.g., NOL4) were identified. When comparing HER islands among breeds, there were substantial overlaps between Holstein with Angus (95.3%), Jersey (94.3%), and Norwegian Red cattle (97.1%), indicating conserved HER across taurine breeds. CONCLUSIONS The detection of HERs varied according to the parameters used, but some HERs were consistently identified across all scenarios. Heterozygous genotypes observed across generations and breeds appear to be conserved in HERs. The results presented could serve as a guide for defining HERs detection parameters and further investigating their biological roles in future studies.
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Affiliation(s)
- Henrique A Mulim
- Department of Animal Sciences, Federal University of Bahia, Salvador, Bahia, 40110-909, Brazil.
- Department of Animal Sciences, Purdue University, West Lafayette, Indiana, 47907, USA.
| | - Victor B Pedrosa
- Department of Animal Sciences, Purdue University, West Lafayette, Indiana, 47907, USA
- Department of Animal Sciences, State University of Ponta Grossa, Ponta Grossa, Parana, 84010-330, Brazil
| | | | - Francesco Tiezzi
- Department of Agriculture, Food, Environment and Forestry, University of Florence, 50121, Florence, Italy
- Department of Animal Science, North Carolina State University, Raleigh, NC, 27607, USA
| | - Christian Maltecca
- Department of Animal Science, North Carolina State University, Raleigh, NC, 27607, USA
| | - Flavio S Schenkel
- Centre for Genetic Improvement of Livestock (CGIL), Department of Animal Biosciences, University of Guelph, Ontario, N1G 2W1, Canada
| | - Luiz F Brito
- Department of Animal Sciences, Purdue University, West Lafayette, Indiana, 47907, USA.
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5
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Chang WJ, Baker MS, Laritsky E, Gunasekara CJ, Maduranga U, Galliou JC, McFadden JW, Waltemyer JR, Berggren-Thomas B, Tate BN, Zhang H, Rosen BD, Van Tassell CP, Liu GE, Coarfa C, Ren YA, Waterland RA. Systemic interindividual DNA methylation variants in cattle share major hallmarks with those in humans. Genome Biol 2024; 25:185. [PMID: 39004763 PMCID: PMC11247883 DOI: 10.1186/s13059-024-03307-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Accepted: 06/13/2024] [Indexed: 07/16/2024] Open
Abstract
BACKGROUND We recently identified ~ 10,000 correlated regions of systemic interindividual epigenetic variation (CoRSIVs) in the human genome. These methylation variants are amenable to population studies, as DNA methylation measurements in blood provide information on epigenetic regulation throughout the body. Moreover, establishment of DNA methylation at human CoRSIVs is labile to periconceptional influences such as nutrition. Here, we analyze publicly available whole-genome bisulfite sequencing data on multiple tissues of each of two Holstein cows to determine whether CoRSIVs exist in cattle. RESULTS Focusing on genomic blocks with ≥ 5 CpGs and a systemic interindividual variation index of at least 20, our approach identifies 217 cattle CoRSIVs, a subset of which we independently validate by bisulfite pyrosequencing. Similar to human CoRSIVs, those in cattle are strongly associated with genetic variation. Also as in humans, we show that establishment of DNA methylation at cattle CoRSIVs is particularly sensitive to early embryonic environment, in the context of embryo culture during assisted reproduction. CONCLUSIONS Our data indicate that CoRSIVs exist in cattle, as in humans, suggesting these systemic epigenetic variants may be common to mammals in general. To the extent that individual epigenetic variation at cattle CoRSIVs affects phenotypic outcomes, assessment of CoRSIV methylation at birth may become an important tool for optimizing agriculturally important traits. Moreover, adjusting embryo culture conditions during assisted reproduction may provide opportunities to tailor agricultural outcomes by engineering CoRSIV methylation profiles.
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Affiliation(s)
- Wen-Jou Chang
- Department of Pediatrics, USDA/ARS Children's Nutrition Research Center, Baylor College of Medicine, Houston, TX, United States
| | - Maria S Baker
- Department of Pediatrics, USDA/ARS Children's Nutrition Research Center, Baylor College of Medicine, Houston, TX, United States
| | - Eleonora Laritsky
- Department of Pediatrics, USDA/ARS Children's Nutrition Research Center, Baylor College of Medicine, Houston, TX, United States
| | - Chathura J Gunasekara
- Department of Pediatrics, USDA/ARS Children's Nutrition Research Center, Baylor College of Medicine, Houston, TX, United States
| | - Uditha Maduranga
- Department of Pediatrics, USDA/ARS Children's Nutrition Research Center, Baylor College of Medicine, Houston, TX, United States
| | - Justine C Galliou
- Department of Animal Science, Cornell University, Ithaca, NY, United States
| | - Joseph W McFadden
- Department of Animal Science, Cornell University, Ithaca, NY, United States
| | | | | | - Brianna N Tate
- Department of Animal Science, Cornell University, Ithaca, NY, United States
| | - Hanxue Zhang
- Department of Animal Science, Cornell University, Ithaca, NY, United States
| | - Benjamin D Rosen
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, MD, United States
| | - Curtis P Van Tassell
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, MD, United States
| | - George E Liu
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, MD, United States
| | - Cristian Coarfa
- Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX, United States
- Dan L Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX, United States
| | - Yi Athena Ren
- Department of Animal Science, Cornell University, Ithaca, NY, United States.
| | - Robert A Waterland
- Department of Pediatrics, USDA/ARS Children's Nutrition Research Center, Baylor College of Medicine, Houston, TX, United States.
- Department of Molecular & Human Genetics, Baylor College of Medicine, Houston, TX, United States.
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Jacinto JGP, Letko A, Häfliger IM, Drögemüller C, Agerholm JS. Congenital syndromic Chiari-like malformation (CSCM) in Holstein cattle: towards unravelling of possible genetic causes. Acta Vet Scand 2024; 66:29. [PMID: 38965607 PMCID: PMC11229497 DOI: 10.1186/s13028-024-00752-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2024] [Accepted: 07/01/2024] [Indexed: 07/06/2024] Open
Abstract
BACKGROUND Chiari malformation type II (CMII) was originally reported in humans as a rare disorder characterized by the downward herniation of the hindbrain and towering cerebellum. The congenital brain malformation is usually accompanied by spina bifida, a congenital spinal anomaly resulting from incomplete closure of the dorsal aspect of the spinal neural tube, and occasionally by other lesions. A similar disorder has been reported in several animal species, including cattle, particularly as a congenital syndrome. A cause of congenital syndromic Chiari-like malformation (CSCM) in cattle has not been reported to date. We collected a series of 14 CSCM-affected Holstein calves (13 purebred, one Red Danish Dairy F1 cross) and performed whole-genome sequencing (WGS). WGS was performed on 33 cattle, including eight cases with parents (trio-based; group 1), three cases with one parent (group 2), and three single cases (solo-based; group 3). RESULTS Sequencing-based genome-wide association study of the 13 Holstein calves with CSCM and 166 controls revealed no significantly associated genome region. Assuming a single Holstein breed-specific recessive allele, no region of shared homozygosity was detected suggesting heterogeneity. Subsequent filtering for protein-changing variants that were only homozygous in the genomes of the individual cases allowed the identification of two missense variants affecting different genes, SHC4 in case 4 in group 1 and WDR45B in case 13 in group 3. Furthermore, these two variants were only observed in Holstein cattle when querying WGS data of > 5,100 animals. Alternatively, potential de novo mutational events were assessed in each case. Filtering for heterozygous private protein-changing variants identified one DYNC1H1 frameshift variant as a candidate causal dominant acting allele in case 12 in group 3. Finally, the presence of larger structural DNA variants and chromosomal abnormalities was investigated in all cases. Depth of coverage analysis revealed two different partial monosomies of chromosome 2 segments in cases 1 and 7 in group 1 and a trisomy of chromosome 12 in the WDR45B homozygous case 13 in group 3. CONCLUSIONS This study presents for the first time a detailed genomic evaluation of CSCM in Holstein cattle and suggests an unexpected genetic and allelic heterogeneity considering the mode of inheritance, as well as the type of variant. For the first time, we propose candidate causal variants that may explain bovine CSCM in a certain proportion of affected calves. We present cattle as a large animal model for human CMII and propose new genes and genomic variants as possible causes for related diseases in both animals and humans.
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Affiliation(s)
- Joana Goncalves Pontes Jacinto
- Institute of Genetics, Vetsuisse Faculty, University of Bern, Bremgartenstrasse 109a, Bern, 3012, Switzerland
- Clinic for Ruminants, Vetsuisse Faculty, University of Bern, Bremgartenstrasse 109a, Bern, 3012, Switzerland
| | - Anna Letko
- Institute of Genetics, Vetsuisse Faculty, University of Bern, Bremgartenstrasse 109a, Bern, 3012, Switzerland
| | - Irene Monika Häfliger
- Institute of Genetics, Vetsuisse Faculty, University of Bern, Bremgartenstrasse 109a, Bern, 3012, Switzerland
| | - Cord Drögemüller
- Institute of Genetics, Vetsuisse Faculty, University of Bern, Bremgartenstrasse 109a, Bern, 3012, Switzerland.
| | - Jørgen Steen Agerholm
- Department of Veterinary Clinical Sciences, University of Copenhagen, Højbakkegaard Allé 5A, Taastrup, 2630, Denmark
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7
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Ooi E, Xiang R, Chamberlain AJ, Goddard ME. Archetypal clustering reveals physiological mechanisms linking milk yield and fertility in dairy cattle. J Dairy Sci 2024; 107:4726-4742. [PMID: 38369117 DOI: 10.3168/jds.2023-23699] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Accepted: 01/11/2024] [Indexed: 02/20/2024]
Abstract
Fertility in dairy cattle has declined as an unintended consequence of single-trait selection for high milk yield. The unfavorable genetic correlation between milk yield and fertility is now well documented; however, the underlying physiological mechanisms are still uncertain. To understand the relationship between these traits, we developed a method that clusters variants with similar patterns of effects and, after the integration of gene expression data, identifies the genes through which they are likely to act. Biological processes that are enriched in the genes of each cluster were then identified. We identified several clusters with unique patterns of effects. One of the clusters included variants associated with increased milk yield and decreased fertility, where the "archetypal" variant (i.e., the one with the largest effect) was associated with the GC gene, whereas others were associated with TRIM32, LRRK2, and U6-associated snRNA. These genes have been linked to transcription and alternative splicing, suggesting that these processes are likely contributors to the unfavorable relationship between the 2 traits. Another cluster, with archetypal variant near DGAT1 and including variants associated with CDH2, BTRC, SFRP2, ZFHX3, and SLITRK5, appeared to affect milk yield but have little effect on fertility. These genes have been linked to insulin, adipose tissue, and energy metabolism. A third cluster with archetypal variant near ZNF613 and including variants associated with ROBO1, EFNA5, PALLD, GPC6, and PTPRT were associated with fertility but not milk yield. These genes have been linked to GnRH neuronal migration, embryonic development, or ovarian function. The use of archetypal clustering to group variants with similar patterns of effects may assist in identifying the biological processes underlying correlated traits. The method is hypothesis generating and requires experimental confirmation. However, we have uncovered several novel mechanisms potentially affecting milk production and fertility such as GnRH neuronal migration. We anticipate our method to be a starting point for experimental research into novel pathways, which have been previously unexplored within the context of dairy production.
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Affiliation(s)
- E Ooi
- Faculty of Veterinary and Agricultural Sciences, University of Melbourne, Melbourne, Victoria 3010, Australia; Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, Victoria 3083, Australia.
| | - R Xiang
- Faculty of Veterinary and Agricultural Sciences, University of Melbourne, Melbourne, Victoria 3010, Australia; Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, Victoria 3083, Australia
| | - A J Chamberlain
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, Victoria 3083, Australia; School of Applied Systems Biology, La Trobe University, Bundoora, Victoria 3083, Australia
| | - M E Goddard
- Faculty of Veterinary and Agricultural Sciences, University of Melbourne, Melbourne, Victoria 3010, Australia; Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, Victoria 3083, Australia
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8
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van den Berg I, Nguyen TV, Nguyen TTT, Pryce JE, Nieuwhof GJ, MacLeod IM. Imputation accuracy and carrier frequency of deleterious recessive defects in Australian dairy cattle. J Dairy Sci 2024:S0022-0302(24)00968-8. [PMID: 38945256 DOI: 10.3168/jds.2024-24780] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2024] [Accepted: 06/04/2024] [Indexed: 07/02/2024]
Abstract
Widespread genotyping has enabled the identification of putative recessive mutations that affect fertility through early embryonic fetal loss, or compromise neonate or calf viability. The use of artificial insemination in the global dairy population can rapidly spread these harmful mutations, and testing for multiple mutations can become relatively expensive if not all tests are available on the same SNP panel. However, it is possible to provide heifer and cow predicted carrier status to farmers at no additional cost if the animals are genotyped with a standard SNP panel. Additionally, for defects where the causal mutation is unknown, but a haplotype of markers has been associated with the defect, the carrier status can be predicted based on that haplotype. The aims of this study were 3-fold: 1) to determine the accuracy of imputation of putative causal mutations for recessive deleterious conditions in Australian dairy cattle, 2) to impute carrier status for known recessive deleterious conditions in all genotyped Australian Holstein, Jersey and Red breed cows, and 3) to determine the changes in carrier frequencies across time for these recessive deleterious mutations. We used the F1 statistic, combining precision and recall, to assess the accuracy of carrier status prediction. We showed that known deleterious mutations can be accurately imputed in Australian Holstein and Jersey cattle that are not directly genotyped for the causal mutation, with F1 ranging between 0.88 and 0.99. For recessive deleterious conditions not included on the standard Australian SNP panel, carrier status could be predicted using a marker haplotype, with F1 ranging from 0.91 to 0.92. Most putative causals and haplotypes were either stable with a low carrier percentage or had a declining carrier percentage. However, several recessive mutations showed a relatively high or increasing percentage, highlighting the importance of detecting carriers to reduce the number of at risk matings. Furthermore, the high carrier percentage of the recently identified Bovine Lymphocyte Intestinal Retention Defect (BLIRD) mutation emphasizes the importance of detection of novel mutations.
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Affiliation(s)
- I van den Berg
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, 5 Ring Road, Bundoora, Victoria, 3083, Australia.
| | - T V Nguyen
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, 5 Ring Road, Bundoora, Victoria, 3083, Australia
| | - T T T Nguyen
- DataGene, 5 Ring Road, Bundoora, Victoria, 3083, Australia
| | - J E Pryce
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, 5 Ring Road, Bundoora, Victoria, 3083, Australia; School of Applied Systems Biology, La Trobe University, Bundoora, Victoria, 3083, Australia
| | - G J Nieuwhof
- DataGene, 5 Ring Road, Bundoora, Victoria, 3083, Australia
| | - I M MacLeod
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, 5 Ring Road, Bundoora, Victoria, 3083, Australia; School of Applied Systems Biology, La Trobe University, Bundoora, Victoria, 3083, Australia
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9
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Forutan M, Engle BN, Chamberlain AJ, Ross EM, Nguyen LT, D'Occhio MJ, Snr AC, Kho EA, Fordyce G, Speight S, Goddard ME, Hayes BJ. Genome-wide association and expression quantitative trait loci in cattle reveals common genes regulating mammalian fertility. Commun Biol 2024; 7:724. [PMID: 38866948 PMCID: PMC11169601 DOI: 10.1038/s42003-024-06403-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Accepted: 05/31/2024] [Indexed: 06/14/2024] Open
Abstract
Most genetic variants associated with fertility in mammals fall in non-coding regions of the genome and it is unclear how these variants affect fertility. Here we use genome-wide association summary statistics for Heifer puberty (pubertal or not at 600 days) from 27,707 Bos indicus, Bos taurus and crossbred cattle; multi-trait GWAS signals from 2119 indicine cattle for four fertility traits, including days to calving, age at first calving, pregnancy status, and foetus age in weeks (assessed by rectal palpation of the foetus); and expression quantitative trait locus for whole blood from 489 indicine cattle, to identify 87 putatively functional genes affecting cattle fertility. Our analysis reveals a significant overlap between the set of cattle and previously reported human fertility-related genes, impling the existence of a shared pool of genes that regulate fertility in mammals. These findings are crucial for developing approaches to improve fertility in cattle and potentially other mammals.
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Affiliation(s)
- Mehrnush Forutan
- Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, St Lucia, QLD, Australia.
| | - Bailey N Engle
- Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, St Lucia, QLD, Australia
- USDA,ARS, U.S. Meat Animal Research Center, Clay Center, NE, 68933, USA
| | - Amanda J Chamberlain
- Agriculture Victoria, Centre for AgriBiosciences, Bundoora, VIC, Australia
- School of Applied Systems Biology, La Trobe University, Bundoora, VIC, 3083, Australia
| | - Elizabeth M Ross
- Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, St Lucia, QLD, Australia
| | - Loan T Nguyen
- Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, St Lucia, QLD, Australia
| | - Michael J D'Occhio
- School of Life and Environmental Sciences, Faculty of Science, The University of Sydney, Sydney, NSW, Australia
| | - Alf Collins Snr
- Collins Belah Valley Brahman Stud, Marlborough, 4705, QLD, Australia
| | - Elise A Kho
- Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, St Lucia, QLD, Australia
| | - Geoffry Fordyce
- Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, St Lucia, QLD, Australia
| | | | - Michael E Goddard
- Agriculture Victoria, Centre for AgriBiosciences, Bundoora, VIC, Australia
- University of Melbourne, Melbourne, Australia
| | - Ben J Hayes
- Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, St Lucia, QLD, Australia
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10
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van den Berg I, Chamberlain AJ, MacLeod IM, Nguyen TV, Goddard ME, Xiang R, Mason B, Meier S, Phyn CVC, Burke CR, Pryce JE. Using expression data to fine map QTL associated with fertility in dairy cattle. Genet Sel Evol 2024; 56:42. [PMID: 38844868 PMCID: PMC11154999 DOI: 10.1186/s12711-024-00912-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Accepted: 05/13/2024] [Indexed: 06/09/2024] Open
Abstract
BACKGROUND Female fertility is an important trait in dairy cattle. Identifying putative causal variants associated with fertility may help to improve the accuracy of genomic prediction of fertility. Combining expression data (eQTL) of genes, exons, gene splicing and allele specific expression is a promising approach to fine map QTL to get closer to the causal mutations. Another approach is to identify genomic differences between cows selected for high and low fertility and a selection experiment in New Zealand has created exactly this resource. Our objective was to combine multiple types of expression data, fertility traits and allele frequency in high- (POS) and low-fertility (NEG) cows with a genome-wide association study (GWAS) on calving interval in Australian cows to fine-map QTL associated with fertility in both Australia and New Zealand dairy cattle populations. RESULTS Variants that were significantly associated with calving interval (CI) were strongly enriched for variants associated with gene, exon, gene splicing and allele-specific expression, indicating that there is substantial overlap between QTL associated with CI and eQTL. We identified 671 genes with significant differential expression between POS and NEG cows, with the largest fold change detected for the CCDC196 gene on chromosome 10. Our results provide numerous candidate genes associated with female fertility in dairy cattle, including GYS2 and TIGAR on chromosome 5 and SYT3 and HSD17B14 on chromosome 18. Multiple QTL regions were located in regions with large numbers of copy number variants (CNV). To identify the causal mutations for these variants, long read sequencing may be useful. CONCLUSIONS Variants that were significantly associated with CI were highly enriched for eQTL. We detected 671 genes that were differentially expressed between POS and NEG cows. Several QTL detected for CI overlapped with eQTL, providing candidate genes for fertility in dairy cattle.
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Affiliation(s)
- Irene van den Berg
- Agriculture Victoria, AgriBio, Centre of AgriBioscience, 5 Ring Road, Bundoora, VIC, 3082, Australia.
| | - Amanda J Chamberlain
- Agriculture Victoria, AgriBio, Centre of AgriBioscience, 5 Ring Road, Bundoora, VIC, 3082, Australia
- School of Applied Systems Biology, La Trobe University, Bundoora, VIC, 3083, Australia
| | - Iona M MacLeod
- Agriculture Victoria, AgriBio, Centre of AgriBioscience, 5 Ring Road, Bundoora, VIC, 3082, Australia
| | - Tuan V Nguyen
- Agriculture Victoria, AgriBio, Centre of AgriBioscience, 5 Ring Road, Bundoora, VIC, 3082, Australia
| | - Mike E Goddard
- Agriculture Victoria, AgriBio, Centre of AgriBioscience, 5 Ring Road, Bundoora, VIC, 3082, Australia
- Faculty of Veterinary & Agricultural Science, University of Melbourne, Parkville, VIC, 3010, Australia
| | - Ruidong Xiang
- Agriculture Victoria, AgriBio, Centre of AgriBioscience, 5 Ring Road, Bundoora, VIC, 3082, Australia
- Faculty of Veterinary & Agricultural Science, University of Melbourne, Parkville, VIC, 3010, Australia
| | - Brett Mason
- Agriculture Victoria, AgriBio, Centre of AgriBioscience, 5 Ring Road, Bundoora, VIC, 3082, Australia
| | | | | | | | - Jennie E Pryce
- Agriculture Victoria, AgriBio, Centre of AgriBioscience, 5 Ring Road, Bundoora, VIC, 3082, Australia
- School of Applied Systems Biology, La Trobe University, Bundoora, VIC, 3083, Australia
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11
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Badia-Bringué G, Canive M, Vázquez P, Garrido JM, Fernández A, Juste RA, Jiménez JA, González-Recio O, Alonso-Hearn M. Genome-Wide Association Study Reveals Quantitative Trait Loci and Candidate Genes Associated with High Interferon-gamma Production in Holstein Cattle Naturally Infected with Mycobacterium Bovis. Int J Mol Sci 2024; 25:6165. [PMID: 38892353 PMCID: PMC11172856 DOI: 10.3390/ijms25116165] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2024] [Revised: 05/27/2024] [Accepted: 05/29/2024] [Indexed: 06/21/2024] Open
Abstract
Mycobacterium bovis (Mb) is the causative agent of bovine tuberculosis (bTb). Genetic selection aiming to identify less susceptible animals has been proposed as a complementary measure in ongoing programs toward controlling Mb infection. However, individual animal phenotypes for bTb based on interferon-gamma (IFNɣ) and its use in bovine selective breeding programs have not been explored. In the current study, IFNɣ production was measured using a specific IFNɣ ELISA kit in bovine purified protein derivative (bPPD)-stimulated blood samples collected from Holstein cattle. DNA isolated from the peripheral blood samples collected from the animals included in the study was genotyped with the EuroG Medium Density bead Chip, and the genotypes were imputed to whole-genome sequences. A genome-wide association analysis (GWAS) revealed that the IFNɣ in response to bPPD was associated with a specific genetic profile (heritability = 0.23) and allowed the identification of 163 SNPs, 72 quantitative trait loci (QTLs), 197 candidate genes, and 8 microRNAs (miRNAs) associated with this phenotype. No negative correlations between this phenotype and other phenotypes and traits included in the Spanish breeding program were observed. Taken together, our results define a heritable and distinct immunogenetic profile associated with strong production of IFNɣ in response to Mb.
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Affiliation(s)
- Gerard Badia-Bringué
- Department of Animal Health, NEIKER-Basque Institute for Agricultural Research and Development, Basque Research and Technology Alliance (BRTA), 48160 Derio, Bizkaia, Spain
| | - María Canive
- Department of Animal Health, NEIKER-Basque Institute for Agricultural Research and Development, Basque Research and Technology Alliance (BRTA), 48160 Derio, Bizkaia, Spain
| | - Patricia Vázquez
- Department of Animal Health, NEIKER-Basque Institute for Agricultural Research and Development, Basque Research and Technology Alliance (BRTA), 48160 Derio, Bizkaia, Spain
| | - Joseba M. Garrido
- Department of Animal Health, NEIKER-Basque Institute for Agricultural Research and Development, Basque Research and Technology Alliance (BRTA), 48160 Derio, Bizkaia, Spain
| | - Almudena Fernández
- Departamento de Mejora Genética Animal, Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA), 28040 Madrid, Spain
| | - Ramón A. Juste
- Department of Animal Health, NEIKER-Basque Institute for Agricultural Research and Development, Basque Research and Technology Alliance (BRTA), 48160 Derio, Bizkaia, Spain
| | | | - Oscar González-Recio
- Departamento de Mejora Genética Animal, Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA), 28040 Madrid, Spain
| | - Marta Alonso-Hearn
- Department of Animal Health, NEIKER-Basque Institute for Agricultural Research and Development, Basque Research and Technology Alliance (BRTA), 48160 Derio, Bizkaia, Spain
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12
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Sztuka M, Kotlarz K, Mielczarek M, Hajduk P, Liu J, Szyda J. Nextflow vs. plain bash: different approaches to the parallelization of SNP calling from the whole genome sequence data. NAR Genom Bioinform 2024; 6:lqae040. [PMID: 38686136 PMCID: PMC11057021 DOI: 10.1093/nargab/lqae040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2023] [Revised: 03/28/2024] [Accepted: 04/15/2024] [Indexed: 05/02/2024] Open
Abstract
This study compared computational approaches to parallelization of an SNP calling workflow. The data comprised DNA from five Holstein-Friesian cows sequenced with the Illumina platform. The pipeline consisted of quality control, alignment to the reference genome, post-alignment, and SNP calling. Three approaches to parallelization were compared: (i) a plain Bash script in which a pipeline for each cow was executed as separate processes invoked at the same time, (ii) a Bash script wrapped in a single Nextflow process and (iii) a Nextflow script with each component of the pipeline defined as a separate process. The results demonstrated that on average, the multi-process Nextflow script performed 15-27% faster depending on the number of assigned threads, with the biggest execution time advantage over the plain Bash approach observed with 10 threads. In terms of RAM usage, the most substantial variation was observed for the multi-process Nextflow, for which it increased with the number of assigned threads, while RAM consumption of the other setups did not depend much on the number of threads assigned for computations. Due to intermediate and log files generated, disk usage was markedly higher for the multi-process Nextflow than for the plain Bash and for the single-process Nextflow.
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Affiliation(s)
- Marek Sztuka
- Wroclaw University of Environmental and Life Sciences, Department of Genetics, the Biostatistics Group Kozuchowska 7, Wroclaw PL-51631, Poland
| | - Krzysztof Kotlarz
- Wroclaw University of Environmental and Life Sciences, Department of Genetics, the Biostatistics Group Kozuchowska 7, Wroclaw PL-51631, Poland
- University Cancer Diagnostic Center, Poznan University of Medical Science, Fredry 10, Poznan 61-701, Poland
| | - Magda Mielczarek
- Wroclaw University of Environmental and Life Sciences, Department of Genetics, the Biostatistics Group Kozuchowska 7, Wroclaw PL-51631, Poland
- University Cancer Diagnostic Center, Poznan University of Medical Science, Fredry 10, Poznan 61-701, Poland
| | - Piotr Hajduk
- Wroclaw University of Environmental and Life Sciences, Department of Genetics, the Biostatistics Group Kozuchowska 7, Wroclaw PL-51631, Poland
| | - Jakub Liu
- University Cancer Diagnostic Center, Poznan University of Medical Science, Fredry 10, Poznan 61-701, Poland
- Wroclaw University of Environmental and Life Sciences, Department of Genetics, the Biostatistics Group Kozuchowska 7, Wroclaw PL-51631, Poland
| | - Joanna Szyda
- Wroclaw University of Environmental and Life Sciences, Department of Genetics, the Biostatistics Group Kozuchowska 7, Wroclaw PL-51631, Poland
- University Cancer Diagnostic Center, Poznan University of Medical Science, Fredry 10, Poznan 61-701, Poland
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13
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Corbeau J, Grohs C, Jourdain J, Boussaha M, Besnard F, Barbat A, Plassard V, Rivière J, Hamelin C, Mortier J, Boichard D, Guatteo R, Capitan A. A recurrent de novo missense mutation in COL1A1 causes osteogenesis imperfecta type II and preterm delivery in Normande cattle. Genet Sel Evol 2024; 56:39. [PMID: 38773368 PMCID: PMC11107018 DOI: 10.1186/s12711-024-00909-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Accepted: 05/07/2024] [Indexed: 05/23/2024] Open
Abstract
BACKGROUND Nine male and eight female calves born to a Normande artificial insemination bull named "Ly" were referred to the French National Observatory of Bovine Abnormalities for multiple fractures, shortened gestation, and stillbirth or perinatal mortality. RESULTS Using Illumina BovineSNP50 array genotypes from affected calves and 84 half-sib controls, the associated locus was mapped to a 6.5-Mb interval on chromosome 19, assuming autosomal inheritance with germline mosaicism. Subsequent comparison of the whole-genome sequences of one case and 5116 control genomes, followed by genotyping in the affected pedigree, identified a de novo missense substitution within the NC1 domain of the COL1A1 gene (Chr19 g.36,473,965G > A; p.D1412N) as unique candidate variant. Interestingly, the affected residue was completely conserved among 243 vertebrate orthologs, and the same substitution in humans has been reported to cause type II osteogenesis imperfecta (OI), a connective tissue disorder that is characterized primarily by bone deformity and fragility. Moreover, three COL1A1 mutations have been described to cause the same syndrome in cattle. Necropsy, computed tomography, radiology, and histology confirmed the diagnosis of type II OI, further supporting the causality of this variant. In addition, a detailed analysis of gestation length and perinatal mortality in 1387 offspring of Ly and more than 160,000 progeny of 63 control bulls allowed us to statistically confirm in a large pedigree the association between type II OI and preterm delivery, which is probably due to premature rupture of fetal membranes and has been reported in several isolated cases of type II OI in humans and cattle. Finally, analysis of perinatal mortality rates and segregation distortion supported a low level of germ cell mosaicism in Ly, with an estimate of 4.5% to 7.7% of mutant sperm and thus 63 to 107 affected calves born. These numbers contrast with the 17 cases reported and raise concerns about the underreporting of congenital defects to heredo-surveillance platforms, even for textbook genetic syndromes. CONCLUSIONS In conclusion, we describe a large animal model for a recurrent substitution in COL1A1 that is responsible for type II OI in humans. More generally, this study highlights the utility of such datasets and large half-sib families available in livestock species to characterize sporadic genetic defects.
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Affiliation(s)
- Julien Corbeau
- BioEpAR, INRAE, Oniris, CS, 40706, Nantes, France.
- INRAE, AgroParisTech, GABI, Université Paris Saclay, 78350, Jouy-en-Josas, France.
| | - Cécile Grohs
- INRAE, AgroParisTech, GABI, Université Paris Saclay, 78350, Jouy-en-Josas, France.
| | | | - Mekki Boussaha
- INRAE, AgroParisTech, GABI, Université Paris Saclay, 78350, Jouy-en-Josas, France
| | | | - Anne Barbat
- INRAE, AgroParisTech, GABI, Université Paris Saclay, 78350, Jouy-en-Josas, France
| | | | - Julie Rivière
- INRAE, AgroParisTech, GABI, Université Paris Saclay, 78350, Jouy-en-Josas, France
- INRAE, AgroParisTech, MICALIS, Université Paris-Saclay, 78350, Jouy-en-Josas, France
| | | | - Jeremy Mortier
- Ecole Nationale Vétérinaire d'Alfort, Maisons-Alfort, France
| | - Didier Boichard
- INRAE, AgroParisTech, GABI, Université Paris Saclay, 78350, Jouy-en-Josas, France
| | | | - Aurélien Capitan
- INRAE, AgroParisTech, GABI, Université Paris Saclay, 78350, Jouy-en-Josas, France.
- ELIANCE, 75012, Paris, France.
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14
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Erven JAM, Scheu A, Verdugo MP, Cassidy L, Chen N, Gehlen B, Street M, Madsen O, Mullin VE. A High-Coverage Mesolithic Aurochs Genome and Effective Leveraging of Ancient Cattle Genomes Using Whole Genome Imputation. Mol Biol Evol 2024; 41:msae076. [PMID: 38662789 PMCID: PMC11090068 DOI: 10.1093/molbev/msae076] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2024] [Revised: 04/05/2024] [Accepted: 04/09/2024] [Indexed: 05/14/2024] Open
Abstract
Ancient genomic analyses are often restricted to utilizing pseudohaploid data due to low genome coverage. Leveraging low-coverage data by imputation to calculate phased diploid genotypes that enables haplotype-based interrogation and single nucleotide polymorphism (SNP) calling at unsequenced positions is highly desirable. This has not been investigated for ancient cattle genomes despite these being compelling subjects for archeological, evolutionary, and economic reasons. Here, we test this approach by sequencing a Mesolithic European aurochs (18.49×; 9,852 to 9,376 calBCE) and an Early Medieval European cow (18.69×; 427 to 580 calCE) and combine these with published individuals: two ancient and three modern. We downsample these genomes (0.25×, 0.5×, 1.0×, and 2.0×) and impute diploid genotypes, utilizing a reference panel of 171 published modern cattle genomes that we curated for 21.7 million (Mn) phased SNPs. We recover high densities of correct calls with an accuracy of >99.1% at variant sites for the lowest downsample depth of 0.25×, increasing to >99.5% for 2.0× (transversions only, minor allele frequency [MAF] ≥ 2.5%). The recovery of SNPs correlates with coverage; on average, 58% of sites are recovered for 0.25× increasing to 87% for 2.0×, utilizing an average of 3.5 million (Mn) transversions (MAF ≥2.5%), even in the aurochs, despite the highest temporal distance from the modern reference panel. Our imputed genomes behave similarly to directly called data in allele frequency-based analyses, for example consistently identifying runs of homozygosity >2 Mb, including a long homozygous region in the Mesolithic European aurochs.
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Affiliation(s)
- Jolijn A M Erven
- Groningen Institute of Archaeology, University of Groningen, Groningen, The Netherlands
- Smurfit Institute of Genetics, Trinity College Dublin, Dublin D02 PN40, Ireland
| | - Amelie Scheu
- Smurfit Institute of Genetics, Trinity College Dublin, Dublin D02 PN40, Ireland
- Palaeogenetics Group, Institute of Organismic and Molecular Evolution (iOME), Johannes Gutenberg-University Mainz, 55099 Mainz, Germany
| | | | - Lara Cassidy
- Smurfit Institute of Genetics, Trinity College Dublin, Dublin D02 PN40, Ireland
| | - Ningbo 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
| | - Birgit Gehlen
- Institute for Prehistory and Protohistory, University of Cologne, 50931 Cologne, Germany
| | - Martin Street
- LEIZA, Archaeological Research Centre and Museum for Human Behavioural Evolution, Schloss Monrepos, D - 56567 Neuwied, Germany
| | - Ole Madsen
- Animal Breeding and Genomics, Wageningen University and Research, Wageningen, The Netherlands
| | - Victoria E Mullin
- Smurfit Institute of Genetics, Trinity College Dublin, Dublin D02 PN40, Ireland
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15
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Kotlarz K, Mielczarek M, Biecek P, Wojdak-Maksymiec K, Suchocki T, Topolski P, Jagusiak W, Szyda J. An Explainable Deep Learning Classifier of Bovine Mastitis Based on Whole-Genome Sequence Data-Circumventing the p >> n Problem. Int J Mol Sci 2024; 25:4715. [PMID: 38731932 PMCID: PMC11083318 DOI: 10.3390/ijms25094715] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2024] [Revised: 04/19/2024] [Accepted: 04/23/2024] [Indexed: 05/13/2024] Open
Abstract
The serious drawback underlying the biological annotation of whole-genome sequence data is the p >> n problem, which means that the number of polymorphic variants (p) is much larger than the number of available phenotypic records (n). We propose a way to circumvent the problem by combining a LASSO logistic regression with deep learning to classify cows as susceptible or resistant to mastitis, based on single nucleotide polymorphism (SNP) genotypes. Among several architectures, the one with 204,642 SNPs was selected as the best. This architecture was composed of two layers with, respectively, 7 and 46 units per layer implementing respective drop-out rates of 0.210 and 0.358. The classification of the test data resulted in AUC = 0.750, accuracy = 0.650, sensitivity = 0.600, and specificity = 0.700. Significant SNPs were selected based on the SHapley Additive exPlanation (SHAP). As a final result, one GO term related to the biological process and thirteen GO terms related to molecular function were significantly enriched in the gene set that corresponded to the significant SNPs. Our findings revealed that the optimal approach can correctly predict susceptibility or resistance status for approximately 65% of cows. Genes marked by the most significant SNPs are related to the immune response and protein synthesis.
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Affiliation(s)
- Krzysztof Kotlarz
- Biostatistics Group, Department of Genetics, Wroclaw University of Environmental and Life Sciences, Kozuchowska 7, 51-631 Wroclaw, Poland; (K.K.); (M.M.); (T.S.)
- University Cancer Diagnostic Center, Poznan University of Medical Science, 61-701 Poznan, Poland
| | - Magda Mielczarek
- Biostatistics Group, Department of Genetics, Wroclaw University of Environmental and Life Sciences, Kozuchowska 7, 51-631 Wroclaw, Poland; (K.K.); (M.M.); (T.S.)
- University Cancer Diagnostic Center, Poznan University of Medical Science, 61-701 Poznan, Poland
| | - Przemysław Biecek
- Faculty of Mathematics, Informatics and Mechanics, University of Warsaw, Banacha 2, 02-097 Warsaw, Poland;
- Faculty of Mathematics and Information Science, Warsaw University of Technology, 00-662 Warsaw, Poland
| | - Katarzyna Wojdak-Maksymiec
- Department of Genetics and Animal Breeding, West Pomeranian University of Technology, Aleja Piastow 45, 70-311 Szczecin, Poland;
| | - Tomasz Suchocki
- Biostatistics Group, Department of Genetics, Wroclaw University of Environmental and Life Sciences, Kozuchowska 7, 51-631 Wroclaw, Poland; (K.K.); (M.M.); (T.S.)
- University Cancer Diagnostic Center, Poznan University of Medical Science, 61-701 Poznan, Poland
| | - Piotr Topolski
- National Research Institute of Animal Production, Krakowska 1, 32-083 Balice, Poland; (P.T.); (W.J.)
| | - Wojciech Jagusiak
- National Research Institute of Animal Production, Krakowska 1, 32-083 Balice, Poland; (P.T.); (W.J.)
- Faculty of Animal Science, University of Agriculture in Krakow, al. Mickiewicza 24/28, 30-059 Kraków, Poland
| | - Joanna Szyda
- Biostatistics Group, Department of Genetics, Wroclaw University of Environmental and Life Sciences, Kozuchowska 7, 51-631 Wroclaw, Poland; (K.K.); (M.M.); (T.S.)
- University Cancer Diagnostic Center, Poznan University of Medical Science, 61-701 Poznan, Poland
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16
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Wong Y, Ignatieva A, Koskela J, Gorjanc G, Wohns AW, Kelleher J. A general and efficient representation of ancestral recombination graphs. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.11.03.565466. [PMID: 37961279 PMCID: PMC10635123 DOI: 10.1101/2023.11.03.565466] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
As a result of recombination, adjacent nucleotides can have different paths of genetic inheritance and therefore the genealogical trees for a sample of DNA sequences vary along the genome. The structure capturing the details of these intricately interwoven paths of inheritance is referred to as an ancestral recombination graph (ARG). Classical formalisms have focused on mapping coalescence and recombination events to the nodes in an ARG. This approach is out of step with modern developments, which do not represent genetic inheritance in terms of these events or explicitly infer them. We present a simple formalism that defines an ARG in terms of specific genomes and their intervals of genetic inheritance, and show how it generalises these classical treatments and encompasses the outputs of recent methods. We discuss nuances arising from this more general structure, and argue that it forms an appropriate basis for a software standard in this rapidly growing field.
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Affiliation(s)
- Yan Wong
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, UK
| | - Anastasia Ignatieva
- School of Mathematics and Statistics, University of Glasgow, UK
- Department of Statistics, University of Oxford, UK
| | - Jere Koskela
- School of Mathematics, Statistics and Physics, Newcastle University, UK
- Department of Statistics, University of Warwick, UK
| | - Gregor Gorjanc
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, UK
| | - Anthony W. Wohns
- Broad Institute of MIT and Harvard, Cambridge, USA
- Department of Genetics, Stanford University School of Medicine, Stanford, USA
| | - Jerome Kelleher
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, UK
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17
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Kalleberg J, Rissman J, Schnabel RD. Overcoming Limitations to Deep Learning in Domesticated Animals with TrioTrain. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.15.589602. [PMID: 38659907 PMCID: PMC11042298 DOI: 10.1101/2024.04.15.589602] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/26/2024]
Abstract
Variant calling across diverse species remains challenging as most bioinformatics tools default to assumptions based on human genomes. DeepVariant (DV) excels without joint genotyping while offering fewer implementation barriers. However, the growing appeal of a "universal" algorithm has magnified the unknown impacts when used with non-human genomes. Here, we use bovine genomes to assess the limits of human-genome-trained models in other species. We introduce the first multi-species DV model that achieves a lower Mendelian Inheritance Error (MIE) rate during single-sample genotyping. Our novel approach, TrioTrain, automates extending DV for species without Genome In A Bottle (GIAB) resources and uses region shuffling to mitigate barriers for SLURM-based clusters. To offset imperfect truth labels for animal genomes, we remove Mendelian discordant variants before training, where models are tuned to genotype the offspring correctly. With TrioTrain, we use cattle, yak, and bison trios to build 30 model iterations across five phases. We observe remarkable performance across phases when testing the GIAB human trios with a mean SNP F1 score >0.990. In HG002, our phase 4 bovine model identifies more variants at a lower MIE rate than DeepTrio. In bovine F1-hybrid genomes, our model substantially reduces inheritance errors with a mean MIE rate of 0.03 percent. Although constrained by imperfect labels, we find that multi-species, trio-based training produces a robust variant calling model. Our research demonstrates that exclusively training with human genomes restricts the application of deep-learning approaches for comparative genomics.
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Affiliation(s)
- Jenna Kalleberg
- University of Missouri, Division of Animal Sciences, Columbia, MO, 65201 USA
| | - Jacob Rissman
- University of Missouri, Division of Animal Sciences, Columbia, MO, 65201 USA
| | - Robert D Schnabel
- University of Missouri, Division of Animal Sciences, Columbia, MO, 65201 USA
- University of Missouri, Genetics Area Program, Columbia, MO, 65201 USA
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18
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Du X, Sun Y, Fu T, Gao T, Zhang T. Research Progress and Applications of Bovine Genome in the Tribe Bovini. Genes (Basel) 2024; 15:509. [PMID: 38674443 PMCID: PMC11050176 DOI: 10.3390/genes15040509] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2024] [Revised: 04/16/2024] [Accepted: 04/17/2024] [Indexed: 04/28/2024] Open
Abstract
Various bovine species have been domesticated and bred for thousands of years, and they provide adequate animal-derived products, including meat, milk, and leather, to meet human requirements. Despite the review studies on economic traits in cattle, the genetic basis of traits has only been partially explained by phenotype and pedigree breeding methods, due to the complexity of genomic regulation during animal development and growth. With the advent of next-generation sequencing technology, genomics projects, such as the 1000 Bull Genomes Project, Functional Annotation of Animal Genomes project, and Bovine Pangenome Consortium, have advanced bovine genomic research. These large-scale genomics projects gave us a comprehensive concept, technology, and public resources. In this review, we summarize the genomics research progress of the main bovine species during the past decade, including cattle (Bos taurus), yak (Bos grunniens), water buffalo (Bubalus bubalis), zebu (Bos indicus), and gayal (Bos frontalis). We mainly discuss the development of genome sequencing and functional annotation, focusing on how genomic analysis reveals genetic variation and its impact on phenotypes in several bovine species.
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Affiliation(s)
- Xingjie Du
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450046, China; (X.D.); (Y.S.); (T.F.); (T.G.)
- Henan International Joint Laboratory of Nutrition Regulation and Ecological Raising of Domestic Animal, College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450046, China
| | - Yu Sun
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450046, China; (X.D.); (Y.S.); (T.F.); (T.G.)
- Henan International Joint Laboratory of Nutrition Regulation and Ecological Raising of Domestic Animal, College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450046, China
| | - Tong Fu
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450046, China; (X.D.); (Y.S.); (T.F.); (T.G.)
- Henan International Joint Laboratory of Nutrition Regulation and Ecological Raising of Domestic Animal, College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450046, China
| | - Tengyun Gao
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450046, China; (X.D.); (Y.S.); (T.F.); (T.G.)
- Henan International Joint Laboratory of Nutrition Regulation and Ecological Raising of Domestic Animal, College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450046, China
| | - Tianliu Zhang
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450046, China; (X.D.); (Y.S.); (T.F.); (T.G.)
- Henan International Joint Laboratory of Nutrition Regulation and Ecological Raising of Domestic Animal, College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450046, China
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19
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Jacinto JGP, Häfliger IM, Letko A, Weber J, Freick M, Gentile A, Drögemüller C, Agerholm JS. Multiple independent de novo mutations are associated with the development of schistosoma reflexum, a lethal syndrome in cattle. Vet J 2024; 304:106069. [PMID: 38281659 DOI: 10.1016/j.tvjl.2024.106069] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Revised: 01/22/2024] [Accepted: 01/23/2024] [Indexed: 01/30/2024]
Abstract
Schistosoma reflexum (SR) is a lethal congenital syndrome characterized by U-shaped dorsal retroflexion of the spine and exposure of abdominal viscera. SR is usually associated with severe dystocia. The syndrome is thought to be inherited as a Mendelian trait. We collected a series of 23 SR-affected calves from four breeds (20 Holstein, one Red Danish, one Limousin, one Romagnola) and performed whole-genome sequencing (WGS). WGS was performed on 51 cattle, including 14 cases with parents (trio-based; Group 1) and nine single cases (solo-based; Group 2). Sequencing-based genome-wide association studies with 20 Holstein cases and 154 controls showed no association (above Bonferroni threshold; P-value<3 ×10-09). Assuming a monogenic recessive inheritance, no region of shared homozygosity was observed, suggesting heterogeneity. Alternatively, the presence of possible dominant acting de novo mutations were assessed. In Group 1, heterozygous private variants, absent in both parents, were found in seven cases. These involved the ACTL6A, FLNA, GLG1, IQSEC2, MAST3, MBTPS2, and MLLT1 genes. In addition, heterozygous private variants affecting the genes DYNC1LI1, PPP2R2B, SCAF8, SUGP1, and UBP1 were identified in five cases from Group 2. The detected frameshift and missense variants are predicted to cause haploinsufficiency. Each of these 12 affected genes belong to the class of haploinsufficient loss-of-function genes or are involved in embryonic and pre-weaning lethality or are known to be associated with severe malformation syndromes in humans and/or mice. This study presents for the first time a detailed genomic evaluation of bovine SR, suggesting that independent de novo mutations may explain the sporadic occurrence of SR in cattle.
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Affiliation(s)
- J G P Jacinto
- Department of Veterinary Medical Sciences, University of Bologna, Via Tolara di Sopra 50, 40064 Ozzano dell'Emilia (Bologna), Italy; Institute of Genetics, Vetsuisse Faculty, University of Bern, Bremgartenstrasse 109a, 3012 Bern, Switzerland
| | - I M Häfliger
- Institute of Genetics, Vetsuisse Faculty, University of Bern, Bremgartenstrasse 109a, 3012 Bern, Switzerland
| | - A Letko
- Institute of Genetics, Vetsuisse Faculty, University of Bern, Bremgartenstrasse 109a, 3012 Bern, Switzerland
| | - J Weber
- Clinic for Ruminants, Department of Clinical Veterinary Medicine, Vetsuisse Faculty, University of Bern, Bremgartenstrasse 109a, 3012 Bern, Switzerland
| | - M Freick
- Faculty of Agriculture/Environment/Chemistry, HTW Dresden-University of Applied Sciences, 01326 Dresden, Germany
| | - A Gentile
- Department of Veterinary Medical Sciences, University of Bologna, Via Tolara di Sopra 50, 40064 Ozzano dell'Emilia (Bologna), Italy
| | - C Drögemüller
- Institute of Genetics, Vetsuisse Faculty, University of Bern, Bremgartenstrasse 109a, 3012 Bern, Switzerland.
| | - J S Agerholm
- Department of Veterinary Clinical Sciences, University of Copenhagen, Højbakkegaard Allé 5A, 2630 Taastrup, Denmark
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20
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González-Cano R, González-Martínez A, Ramón M, González Serrano M, Moreno Millán M, Rubio de Juan A, Rodero Serrano E. Exploring the Effects of Robertsonian Translocation 1/29 (Rob (1;29)) on Genetic Diversity in Minor Breeds of Spanish Berrenda Cattle via Genome-Wide Analysis. Animals (Basel) 2024; 14:793. [PMID: 38473178 DOI: 10.3390/ani14050793] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2024] [Revised: 02/25/2024] [Accepted: 03/02/2024] [Indexed: 03/14/2024] Open
Abstract
Most of the previous studies on the genetic variability in Spanish "Berrenda" breeds have been carried out using DNA microsatellites. The present work aimed to estimate the genetic diversity, population structure, and potential genetic differences among individuals of both Berrenda breeds and groups based on the presence of the Robertsonian chromosomal translocation, rob (1;29). A total of 373 samples from animals belonging to the two breeds, including 169 cases diagnosed as rob (1;29)-positive, were genotyped using an SNP50K chip. The genetic diversity at the breed level did not show significant differences, but it was significantly lower in those subpopulations containing the rob (1;29). Runs of homozygosity identified a region of homozygosity on chromosome 6, where the KIT (KIT proto-oncogene, receptor tyrosine kinase) gene, which determines the typical spotted coat pattern in both breeds, is located. The four subpopulations considered showed minor genetic differences. The regions of the genome that most determined the differences between the breeds were observed on chromosomes 4, 6, 18, and 22. The presence of this Robertsonian translocation did not result in sub-structuring within each of the breeds considered. To improve the reproductive performance of Berrenda breeds, it would be necessary to implement strategies considering the involvement of potential breeding stock carrying rob (1;29).
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Affiliation(s)
- Rafael González-Cano
- Ministry of Agriculture, Fisheries and Food, Paseo Infanta Isabel 1, 28014 Madrid, Spain
- Regional Center of Animal Breeding and Reproduction (CERSYRA-IRIAF), Avenida del Vino 10, 13300 Ciudad Real, Spain
| | - Ana González-Martínez
- Department of Animal Production, Faculty of Veterinary Sciences, University of Cordoba, 14071 Córdoba, Spain
| | - Manuel Ramón
- Department of Animal Breeding and Genetics, National Institute for Agricultural and Food Research and Technology (INIA-CSIC), 28040 Madrid, Spain
| | - Miriam González Serrano
- Department of Animal Production, Faculty of Veterinary Sciences, University of Cordoba, 14071 Córdoba, Spain
| | - Miguel Moreno Millán
- Department of Genetic, Faculty of Veterinary Sciences, University of Cordoba, 14071 Córdoba, Spain
| | - Alejandro Rubio de Juan
- Regional Center of Animal Breeding and Reproduction (CERSYRA-IRIAF), Avenida del Vino 10, 13300 Ciudad Real, Spain
| | - Evangelina Rodero Serrano
- Department of Animal Production, Faculty of Veterinary Sciences, University of Cordoba, 14071 Córdoba, Spain
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21
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Kamprasert N, Aliloo H, van der Werf JHJ, Clark SA. Short communication: Accuracy of whole-genome sequence imputation in Angus cattle using within-breed and multi breed reference populations. Animal 2024; 18:101087. [PMID: 38364656 DOI: 10.1016/j.animal.2024.101087] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Revised: 01/16/2024] [Accepted: 01/19/2024] [Indexed: 02/18/2024] Open
Abstract
Genotype imputation is a standard approach used in the field of genetics. It can be used to fill in missing genotypes or to increase genotype density. Accurate imputed genotypes are required for downstream analyses. In this study, the accuracy of whole-genome sequence imputation for Angus beef cattle was examined using two different ways to form the reference panel, a within-breed reference population and a multi breed reference population. A stepwise imputation was conducted by imputing medium-density (50k) genotypes to high-density, and then to the whole genome sequence (WGS). The reference population consisted of animals with WGS information from the 1 000 Bull Genomes project. The within-breed reference panel comprised 396 Angus cattle, while an additional 2 380 Taurine cattle were added to the reference population for the multi breed reference scenario. Imputation accuracies were variant-wise average accuracies from a 10-fold cross-validation and expressed as concordance rates (CR) and Pearson's correlations (PR). The two imputation scenarios achieved moderate to high imputation accuracies ranging from 0.896 to 0.966 for CR and from 0.779 to 0.834 for PR. The accuracies from two different scenarios were similar, except for PR from WGS imputation, where the within-breed scenario outperformed the multi breed scenario. The result indicated that including a large number of animals from other breeds in the reference panel to impute purebred Angus did not improve the accuracy and may negatively impact the results. In conclusion, the imputed WGS in Angus cattle can be obtained with high accuracy using a within-breed reference panel.
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Affiliation(s)
- N Kamprasert
- School of Environmental and Rural Science, University of New England, 2351, Armidale, NSW, Australia.
| | - H Aliloo
- School of Environmental and Rural Science, University of New England, 2351, Armidale, NSW, Australia
| | - J H J van der Werf
- School of Environmental and Rural Science, University of New England, 2351, Armidale, NSW, Australia
| | - S A Clark
- School of Environmental and Rural Science, University of New England, 2351, Armidale, NSW, Australia
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22
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Dorji J, Reverter A, Alexandre PA, Chamberlain AJ, Vander-Jagt CJ, Kijas J, Porto-Neto LR. Ancestral alleles defined for 70 million cattle variants using a population-based likelihood ratio test. Genet Sel Evol 2024; 56:11. [PMID: 38321371 PMCID: PMC10848479 DOI: 10.1186/s12711-024-00879-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Accepted: 01/30/2024] [Indexed: 02/08/2024] Open
Abstract
BACKGROUND The study of ancestral alleles provides insights into the evolutionary history, selection, and genetic structures of a population. In cattle, ancestral alleles are widely used in genetic analyses, including the detection of signatures of selection, determination of breed ancestry, and identification of admixture. Having a comprehensive list of ancestral alleles is expected to improve the accuracy of these genetic analyses. However, the list of ancestral alleles in cattle, especially at the whole genome sequence level, is far from complete. In fact, the current largest list of ancestral alleles (~ 42 million) represents less than 28% of the total number of detected variants in cattle. To address this issue and develop a genomic resource for evolutionary studies, we determined ancestral alleles in cattle by comparing prior derived whole-genome sequence variants to an out-species group using a population-based likelihood ratio test. RESULTS Our study determined and makes available the largest list of ancestral alleles in cattle to date (70.1 million) and includes 2.3 million on the X chromosome. There was high concordance (97.6%) of the determined ancestral alleles with those from previous studies when only high-probability ancestral alleles were considered (29.8 million positions) and another 23.5 million high-confidence ancestral alleles were novel, expanding the available reference list to improve the accuracies of genetic analyses involving ancestral alleles. The high concordance of the results with previous studies implies that our approach using genomic sequence variants and a likelihood ratio test to determine ancestral alleles is appropriate. CONCLUSIONS Considering the high concordance of ancestral alleles across studies, the ancestral alleles determined in this study including those not previously listed, particularly those with high-probability estimates, may be used for further genetic analyses with reasonable accuracy. Our approach that used predetermined variants in species and the likelihood ratio test to determine ancestral alleles is applicable to other species for which sequence level genotypes are available.
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Affiliation(s)
- Jigme Dorji
- CSIRO, Agriculture & Food, St. Lucia, QLD, 4067, Australia.
| | | | | | - Amanda J Chamberlain
- AgriBio, Centre for AgriBioscience, Agriculture Victoria, Bundoora, VIC, 3083, Australia
| | - Christy J Vander-Jagt
- AgriBio, Centre for AgriBioscience, Agriculture Victoria, Bundoora, VIC, 3083, Australia
| | - James Kijas
- CSIRO, Agriculture & Food, St. Lucia, QLD, 4067, Australia
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Veshkini A, Dengler F, Bachmann L, Liermann W, Helm C, Ulrich R, Delling C, Kühn C, Hammon HM. Cryptosporidium parvum infection alters the intestinal mucosa transcriptome in neonatal calves: implications for immune function. Front Immunol 2024; 15:1351427. [PMID: 38318169 PMCID: PMC10839036 DOI: 10.3389/fimmu.2024.1351427] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2023] [Accepted: 01/05/2024] [Indexed: 02/07/2024] Open
Abstract
One of the leading causes of infectious diarrhea in newborn calves is the apicomplexan protozoan Cryptosporidium parvum (C. parvum). However, little is known about its immunopathogenesis. Using next generation sequencing, this study investigated the immune transcriptional response to C. parvum infection in neonatal calves. Neonatal male Holstein-Friesian calves were either orally infected (N = 5) or not (CTRL group, N = 5) with C. parvum oocysts (gp60 subtype IIaA15G2R1) at day 1 of life and slaughtered on day 7 after infection. Total RNA was extracted from the jejunal mucosa for short read. Differentially expressed genes (DEGs) between infected and CTRL groups were assessed using DESeq2 at a false discovery rate < 0.05. Infection did not affect plasma immunohematological parameters, including neutrophil, lymphocyte, monocyte, leucocyte, thrombocyte, and erythrocyte counts as well as hematocrit and hemoglobin concentration on day 7 post infection. The immune-related DEGs were selected according to the UniProt immune system process database and were used for gene ontology (GO) and pathway enrichment analysis using Cytoscape (v3.9.1). Based on GO analysis, DEGs annotated to mucosal immunity, recognizing and presenting antigens, chemotaxis of neutrophils, eosinophils, natural killer cells, B and T cells mediated by signaling pathways including toll like receptors, interleukins, tumor necrosis factor, T cell receptor, and NF-KB were upregulated, while markers of macrophages chemotaxis and cytosolic pattern recognition were downregulated. This study provides a holistic snapshot of immune-related pathways induced by C. parvum in calves, including novel and detailed feedback and feedforward regulatory mechanisms establishing the crosstalk between innate and adaptive immune response in neonate calves, which could be utilized further to develop new therapeutic strategies.
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Affiliation(s)
- Arash Veshkini
- Research Institute for Farm Animal Biology, Institute of Nutritional Physiology “Oskar Kellner”, Dummerstorf, Germany
| | - Franziska Dengler
- Institute of Physiology, Pathophysiology and Biophysics, University of Veterinary Medicine, Vienna, Austria
| | - Lisa Bachmann
- Research Institute for Farm Animal Biology, Institute of Nutritional Physiology “Oskar Kellner”, Dummerstorf, Germany
- Faculty of Agriculture and Food Science, University of Applied Science Neubrandenburg, Neubrandenburg, Germany
| | - Wendy Liermann
- Research Institute for Farm Animal Biology, Institute of Nutritional Physiology “Oskar Kellner”, Dummerstorf, Germany
| | - Christiane Helm
- Institutue for Veterinary Pathology, Leipzig University, Leipzig, Germany
| | - Reiner Ulrich
- Institutue for Veterinary Pathology, Leipzig University, Leipzig, Germany
| | - Cora Delling
- Institute of Veterinary Parasitology, Leipzig University, Leipzig, Germany
| | - Christa Kühn
- Research Institute for Farm Animal Biology, Institute of Genome Biology, Dummerstorf, Germany
- Agricultural and Environmental Faculty, University Rostock, Rostock, Germany
| | - Harald M. Hammon
- Research Institute for Farm Animal Biology, Institute of Nutritional Physiology “Oskar Kellner”, Dummerstorf, Germany
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24
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Krull F, Bleyer M, Schäfer J, Brenig B. A missense mutation in the highly conserved TNF-like domain of Ectodysplasin A is the candidate causative variant for X-linked hypohidrotic ectodermal dysplasia in Limousin cattle: Clinical, histological, and molecular analyses. PLoS One 2024; 19:e0291411. [PMID: 38252617 PMCID: PMC10802946 DOI: 10.1371/journal.pone.0291411] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Accepted: 08/29/2023] [Indexed: 01/24/2024] Open
Abstract
Ectodysplasin A related hypohidrotic ectodermal dysplasia (XLHED) is a well-studied fetal developmental disorder in mammals that mainly affects ectodermal structures. It has been identified in a variety of species, including mice, rats, dogs, cattle, and humans. Here, we report the clinical, histological, and molecular biological analyses of a case of XLHED in Limousin cattle. An affected Limousin calf showed pathognomonic signs of ectodermal dysplasia, i.e. sparse hair and characteristic dental aplasia. Histopathologic comparison of hairy and glabrous skin and computed tomography of the mandible confirmed the phenotypic diagnosis. In addition, a keratoconjunctivitis sicca was noted in one eye, which was also confirmed histopathologically. To identify the causative variant, we resequenced the bovine X-chromosomal ectodysplasin A gene (EDA) of the affected calf and compared the sequences to the bovine reference genome. A single missense variant (rs439722471) at position X:g.80411716T>C (ARS-UCD1.3) was identified. The variant resulted in an amino acid substitution from glutamic acid to glycine within the highly conserved TNF-like domain. To rule out the possibility that the variant was relatively common in the cattle population we genotyped 2,016 individuals including 40% Limousin cattle by fluorescence resonance energy transfer analysis. We also tested 5,116 multibreed samples from Run9 of the 1000 Bull Genomes Project for the said variant. The variant was not detected in any of the cattle tested, confirming the assumption that it was the causative variant. This is the first report of Ectodysplasin A related hypohidrotic ectodermal dysplasia in Limousin cattle and the description of a novel causal variant in cattle.
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Affiliation(s)
- Frederik Krull
- Institute of Veterinary Medicine, Georg-August University Goettingen, Goettingen, Germany
| | - Martina Bleyer
- German Primate Center, Pathology Unit, Goettingen, Germany
| | - Jana Schäfer
- Institute of Veterinary Medicine, Georg-August University Goettingen, Goettingen, Germany
| | - Bertram Brenig
- Institute of Veterinary Medicine, Georg-August University Goettingen, Goettingen, Germany
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Harish A, Lopes Pinto FA, Eriksson S, Johansson AM. Genetic diversity and recent ancestry based on whole-genome sequencing of endangered Swedish cattle breeds. BMC Genomics 2024; 25:89. [PMID: 38254050 PMCID: PMC10802049 DOI: 10.1186/s12864-024-09959-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2023] [Accepted: 01/01/2024] [Indexed: 01/24/2024] Open
Abstract
Several indigenous cattle breeds in Sweden are endangered. Conservation of their genetic diversity and genomic characterization is a priority.Whole-genome sequences (WGS) with a mean coverage of 25X, ranging from 14 to 41X were obtained for 30 individuals of the breeds Fjällko, Fjällnära, Bohuskulla, Rödkulla, Ringamåla, and Väneko. WGS-based genotyping revealed 22,548,028 variants in total, comprising 18,876,115 single nucleotide polymorphisms (SNPs) and 3,671,913 indels. Out of these, 1,154,779 SNPs and 304,467 indels were novel. Population stratification based on roughly 19 million SNPs showed two major groups of the breeds that correspond to northern and southern breeds. Overall, a higher genetic diversity was observed in the southern breeds compared to the northern breeds. While the population stratification was consistent with previous genome-wide SNP array-based analyses, the genealogy of the individuals inferred from WGS based estimates turned out to be more complex than expected from previous SNP-array based estimates. Polymorphisms and their predicted phenotypic consequences were associated with differences in the coat color phenotypes between the northern and southern breeds. Notably, these high-consequence polymorphisms were not represented in SNP arrays, which are used routinely for genotyping of cattle breeds.This study is the first WGS-based population genetic analysis of Swedish native cattle breeds. The genetic diversity of native breeds was found to be high. High-consequence polymorphisms were linked with desirable phenotypes using whole-genome genotyping, which highlights the pressing need for intensifying WGS-based characterization of the native breeds.
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Affiliation(s)
- Ajith Harish
- Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, 75007, Uppsala, Sweden.
| | - Fernando A Lopes Pinto
- Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, 75007, Uppsala, Sweden
| | - Susanne Eriksson
- Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, 75007, Uppsala, Sweden
| | - Anna M Johansson
- Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, 75007, Uppsala, Sweden.
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Zhang K, Liang J, Fu Y, Chu J, Fu L, Wang Y, Li W, Zhou Y, Li J, Yin X, Wang H, Liu X, Mou C, Wang C, Wang H, Dong X, Yan D, Yu M, Zhao S, Li X, Ma Y. AGIDB: a versatile database for genotype imputation and variant decoding across species. Nucleic Acids Res 2024; 52:D835-D849. [PMID: 37889051 PMCID: PMC10767904 DOI: 10.1093/nar/gkad913] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Revised: 10/05/2023] [Accepted: 10/11/2023] [Indexed: 10/28/2023] Open
Abstract
The high cost of large-scale, high-coverage whole-genome sequencing has limited its application in genomics and genetics research. The common approach has been to impute whole-genome sequence variants obtained from a few individuals for a larger population of interest individually genotyped using SNP chip. An alternative involves low-coverage whole-genome sequencing (lcWGS) of all individuals in the larger population, followed by imputation to sequence resolution. To overcome limitations of processing lcWGS data and meeting specific genotype imputation requirements, we developed AGIDB (https://agidb.pro), a website comprising tools and database with an unprecedented sample size and comprehensive variant decoding for animals. AGIDB integrates whole-genome sequencing and chip data from 17 360 and 174 945 individuals, respectively, across 89 species to identify over one billion variants, totaling a massive 688.57 TB of processed data. AGIDB focuses on integrating multiple genotype imputation scenarios. It also provides user-friendly searching and data analysis modules that enable comprehensive annotation of genetic variants for specific populations. To meet a wide range of research requirements, AGIDB offers downloadable reference panels for each species in addition to its extensive dataset, variant decoding and utility tools. We hope that AGIDB will become a key foundational resource in genetics and breeding, providing robust support to researchers.
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Affiliation(s)
- Kaili Zhang
- Key Laboratory of Agricultural Animal Genetics, Breeding, and Reproduction of the Ministry of Education & Key Laboratory of Swine Genetics and Breeding of the Ministry of Agriculture, Huazhong Agricultural University, Wuhan 430070, China
| | - Jiete Liang
- Key Laboratory of Agricultural Animal Genetics, Breeding, and Reproduction of the Ministry of Education & Key Laboratory of Swine Genetics and Breeding of the Ministry of Agriculture, Huazhong Agricultural University, Wuhan 430070, China
| | - Yuhua Fu
- Key Laboratory of Agricultural Animal Genetics, Breeding, and Reproduction of the Ministry of Education & Key Laboratory of Swine Genetics and Breeding of the Ministry of Agriculture, Huazhong Agricultural University, Wuhan 430070, China
| | - Jinyu Chu
- Key Laboratory of Agricultural Animal Genetics, Breeding, and Reproduction of the Ministry of Education & Key Laboratory of Swine Genetics and Breeding of the Ministry of Agriculture, Huazhong Agricultural University, Wuhan 430070, China
| | - Liangliang Fu
- Key Laboratory of Agricultural Animal Genetics, Breeding, and Reproduction of the Ministry of Education & Key Laboratory of Swine Genetics and Breeding of the Ministry of Agriculture, Huazhong Agricultural University, Wuhan 430070, China
- Hubei Hongshan Laboratory, Wuhan 430070, China
- The Cooperative Innovation Center for Sustainable Pig Production, Huazhong Agricultural University, Wuhan 430070, China
| | - Yongfei Wang
- Key Laboratory of Agricultural Animal Genetics, Breeding, and Reproduction of the Ministry of Education & Key Laboratory of Swine Genetics and Breeding of the Ministry of Agriculture, Huazhong Agricultural University, Wuhan 430070, China
| | - Wangjiao Li
- Key Laboratory of Agricultural Animal Genetics, Breeding, and Reproduction of the Ministry of Education & Key Laboratory of Swine Genetics and Breeding of the Ministry of Agriculture, Huazhong Agricultural University, Wuhan 430070, China
| | - You Zhou
- Key Laboratory of Agricultural Animal Genetics, Breeding, and Reproduction of the Ministry of Education & Key Laboratory of Swine Genetics and Breeding of the Ministry of Agriculture, Huazhong Agricultural University, Wuhan 430070, China
| | - Jinhua Li
- Key Laboratory of Agricultural Animal Genetics, Breeding, and Reproduction of the Ministry of Education & Key Laboratory of Swine Genetics and Breeding of the Ministry of Agriculture, Huazhong Agricultural University, Wuhan 430070, China
| | - Xiaoxiao Yin
- Key Laboratory of Agricultural Animal Genetics, Breeding, and Reproduction of the Ministry of Education & Key Laboratory of Swine Genetics and Breeding of the Ministry of Agriculture, Huazhong Agricultural University, Wuhan 430070, China
| | - Haiyan Wang
- Key Laboratory of Agricultural Animal Genetics, Breeding, and Reproduction of the Ministry of Education & Key Laboratory of Swine Genetics and Breeding of the Ministry of Agriculture, Huazhong Agricultural University, Wuhan 430070, China
- College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
| | - Xiaolei Liu
- Key Laboratory of Agricultural Animal Genetics, Breeding, and Reproduction of the Ministry of Education & Key Laboratory of Swine Genetics and Breeding of the Ministry of Agriculture, Huazhong Agricultural University, Wuhan 430070, China
- Hubei Hongshan Laboratory, Wuhan 430070, China
| | - Chunyan Mou
- College of Animal Science and Technology, Southwest University, Chongqing 402460, China
| | - Chonglong Wang
- Key Laboratory of Pig Molecular Quantitative Genetics of Anhui Academy of Agricultural Sciences, Anhui Provincial Key Laboratory of Livestock and Poultry Product Safety Engineering, Institute of Animal Husbandry and Veterinary Medicine, Anhui Academy of Agricultural Sciences, Hefei 230031, China
| | - Heng Wang
- College of Animal Science and Technology, Shandong Agricultural University, Taian 271018, China
| | - Xinxing Dong
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China
| | - Dawei Yan
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China
| | - Mei Yu
- Key Laboratory of Agricultural Animal Genetics, Breeding, and Reproduction of the Ministry of Education & Key Laboratory of Swine Genetics and Breeding of the Ministry of Agriculture, Huazhong Agricultural University, Wuhan 430070, China
- Hubei Hongshan Laboratory, Wuhan 430070, China
| | - Shuhong Zhao
- Key Laboratory of Agricultural Animal Genetics, Breeding, and Reproduction of the Ministry of Education & Key Laboratory of Swine Genetics and Breeding of the Ministry of Agriculture, Huazhong Agricultural University, Wuhan 430070, China
- Hubei Hongshan Laboratory, Wuhan 430070, China
- Lingnan Modern Agricultural Science and Technology Guangdong Laboratory, Guangzhou 510642, China
| | - Xinyun Li
- Key Laboratory of Agricultural Animal Genetics, Breeding, and Reproduction of the Ministry of Education & Key Laboratory of Swine Genetics and Breeding of the Ministry of Agriculture, Huazhong Agricultural University, Wuhan 430070, China
- Hubei Hongshan Laboratory, Wuhan 430070, China
| | - Yunlong Ma
- Key Laboratory of Agricultural Animal Genetics, Breeding, and Reproduction of the Ministry of Education & Key Laboratory of Swine Genetics and Breeding of the Ministry of Agriculture, Huazhong Agricultural University, Wuhan 430070, China
- Lingnan Modern Agricultural Science and Technology Guangdong Laboratory, Guangzhou 510642, China
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Misztal I, Lourenco D. Potential negative effects of genomic selection. J Anim Sci 2024; 102:skae155. [PMID: 38847068 PMCID: PMC11229339 DOI: 10.1093/jas/skae155] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Accepted: 06/05/2024] [Indexed: 07/10/2024] Open
Abstract
Initial findings on genomic selection (GS) indicated substantial improvement for major traits, such as performance, and even successful selection for antagonistic traits. However, recent unofficial reports indicate an increased frequency of deterioration of secondary traits. This phenomenon may arise due to the mismatch between the accelerated selection process and resource allocation. Traits explicitly or implicitly accounted for by a selection index move toward the desired direction, whereas neglected traits change according to the genetic correlations with selected traits. Historically, the first stage of commercial genetic selection focused on production traits. After long-term selection, production traits improved, whereas fitness traits deteriorated, although this deterioration was partially compensated for by constantly improving management. Adding these fitness traits to the breeding objective and the used selection index also helped offset their decline while promoting long-term gains. Subsequently, the trend in observed fitness traits was a combination of a negative response due to genetic antagonism, positive response from inclusion in the selection index, and a positive effect of improving management. Under GS, the genetic trends accelerate, especially for well-recorded higher heritability traits, magnifying the negatively correlated responses for fitness traits. Then, the observed trend for fitness traits can become negative, especially because management modifications do not accelerate under GS. Additional deterioration can occur due to the rapid turnover of GS, as heritabilities for production traits can decline and the genetic antagonism between production and fitness traits can intensify. If the genetic parameters are not updated, the selection index will be inaccurate, and the intended gains will not occur. While the deterioration can accelerate for unrecorded or sparsely recorded fitness traits, GS can lead to an improvement for widely recorded fitness traits. In the context of GS, it is crucial to look for unexpected changes in relevant traits and take rapid steps to prevent further declines, especially in secondary traits. Changes can be anticipated by investigating the temporal dynamics of genetic parameters, especially genetic correlations. However, new methods are needed to estimate genetic parameters for the last generation with large amounts of genomic data.
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Affiliation(s)
- Ignacy Misztal
- Department of Animal and Dairy Science, University of Georgia, Athens, GA 30602, USA
| | - Daniela Lourenco
- Department of Animal and Dairy Science, University of Georgia, Athens, GA 30602, USA
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Li Y, Xiao P, Boadu F, Goldkamp AK, Nirgude S, Cheng J, Hagen DE, Kalish JM, Rivera RM. The counterpart congenital overgrowth syndromes Beckwith-Wiedemann Syndrome in human and large offspring syndrome in bovine involve alterations in DNA methylation, transcription, and chromatin configuration. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.12.14.23299981. [PMID: 38168424 PMCID: PMC10760283 DOI: 10.1101/2023.12.14.23299981] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2024]
Abstract
Beckwith-Wiedemann Syndrome (BWS, OMIM #130650) is a congenital epigenetic disorder in humans which affects approximately 1 in 10,340 children. The incidence is likely an underestimation as the condition is usually recognized based on observable phenotypes at birth. BWS children have up to a 28% risk of developing tumors and currently, only 80% of patients can be corroborated molecularly (epimutations/variants). It is unknown how the subtypes of this condition are molecularly similar/dissimilar globally, therefore there is a need to deeply characterize the syndrome at the molecular level. Here we characterize the methylome, transcriptome and chromatin configuration of 18 BWS individuals together with the animal model of the condition, the bovine large offspring syndrome (LOS). Sex specific comparisons are performed for a subset of the BWS patients and LOS. Given that this epigenetic overgrowth syndrome has been characterized as a loss-of-imprinting condition, parental allele-specific comparisons were performed using the bovine animal model. In general, the differentially methylated regions (DMRs) detected in BWS and LOS showed significant enrichment for CTCF binding sites. Altered chromosome compartments in BWS and LOS were positively correlated with gene expression changes, and the promoters of differentially expressed genes showed significant enrichment for DMRs, differential topologically associating domains, and differential A/B compartments in some comparisons of BWS subtypes and LOS. We show shared regions of dysregulation between BWS and LOS, including several HOX gene clusters, and also demonstrate that altered DNA methylation differs between the clinically epigenetically identified BWS patients and those identified as having DNA variants (i.e. CDKN1C microdeletion). Lastly, we highlight additional genes and genomic regions that have the potential to serve as targets for biomarker development to improve current molecular methodologies. In summary, our results suggest that genome-wide alternation of chromosome architecture, which is partially caused by DNA methylation changes, also contribute to the development of BWS and LOS.
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Novo LC, Poindexter MB, Rezende FM, Santos JEP, Nelson CD, Hernandez LL, Kirkpatrick BW, Peñagaricano F. Identification of genetic variants and individual genes associated with postpartum hypocalcemia in Holstein cows. Sci Rep 2023; 13:21900. [PMID: 38082150 PMCID: PMC10713536 DOI: 10.1038/s41598-023-49496-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Accepted: 12/08/2023] [Indexed: 12/18/2023] Open
Abstract
Periparturient hypocalcemia is a complex metabolic disorder that occurs at the onset of lactation because of a sudden irreversible loss of Ca incorporated into colostrum and milk. Some cows are unable to quickly adapt to this demand and succumb to clinical hypocalcemia, commonly known as milk fever, whereas a larger proportion of cows develop subclinical hypocalcemia. The main goal of this study was to identify causative mutations and candidate genes affecting postpartum blood calcium concentration in Holstein cows. Data consisted of blood calcium concentration measured in 2513 Holstein cows on the first three days after parturition. All cows had genotypic information for 79 k SNP markers. Two consecutive rounds of imputation were performed: first, the 2513 Holstein cows were imputed from 79 k to 312 k SNP markers. This imputation was performed using a reference set of 17,131 proven Holstein bulls with 312 k SNP markers. Then, the 2513 Holstein cows were imputed from 312 k markers to whole-genome sequence data. This second round of imputation used 179 Holstein animals from the 1000 Bulls Genome Project as a reference set. Three alternative phenotypes were evaluated: (1) total calcium concentration in the first 24 h postpartum, (2) total calcium concentration in the first 72 h postpartum calculated as the area under the curve; and (3) the recovery of total calcium concentration calculated as the difference in total calcium concentration between 72 and 24 h. The identification of genetic variants associated with these traits was performed using a two-step mixed model-based approach implemented in the R package MixABEL. The most significant variants were located within or near genes involved in calcium homeostasis and vitamin D transport (GC), calcium and potassium channels (JPH3 and KCNK13), energy and lipid metabolism (CA5A, PRORP, and SREBP1), and immune response (IL12RB2 and CXCL8), among other functions. This work provides the foundation for the development of novel breeding and management tools for reducing the incidence of periparturient hypocalcemia in dairy cattle.
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Affiliation(s)
- Larissa C Novo
- Department of Animal and Dairy Sciences, University of Wisconsin, Madison, WI, 53706, USA
| | - Michael B Poindexter
- Department of Animal Sciences, University of Florida, Gainesville, FL, 32611, USA
| | - Fernanda M Rezende
- Department of Animal Sciences, University of Florida, Gainesville, FL, 32611, USA
| | - José E P Santos
- Department of Animal Sciences, University of Florida, Gainesville, FL, 32611, USA
| | - Corwin D Nelson
- Department of Animal Sciences, University of Florida, Gainesville, FL, 32611, USA
| | - Laura L Hernandez
- Department of Animal and Dairy Sciences, University of Wisconsin, Madison, WI, 53706, USA
| | - Brian W Kirkpatrick
- Department of Animal and Dairy Sciences, University of Wisconsin, Madison, WI, 53706, USA
| | - Francisco Peñagaricano
- Department of Animal and Dairy Sciences, University of Wisconsin, Madison, WI, 53706, USA.
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30
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Lamb HJ, Nguyen LT, Copley JP, Engle BN, Hayes BJ, Ross EM. Imputation strategies for genomic prediction using nanopore sequencing. BMC Biol 2023; 21:286. [PMID: 38066581 PMCID: PMC10709982 DOI: 10.1186/s12915-023-01782-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Accepted: 11/27/2023] [Indexed: 12/18/2023] Open
Abstract
BACKGROUND Genomic prediction describes the use of SNP genotypes to predict complex traits and has been widely applied in humans and agricultural species. Genotyping-by-sequencing, a method which uses low-coverage sequence data paired with genotype imputation, is becoming an increasingly popular SNP genotyping method for genomic prediction. The development of Oxford Nanopore Technologies' (ONT) MinION sequencer has now made genotyping-by-sequencing portable and rapid. Here we evaluate the speed and accuracy of genomic predictions using low-coverage ONT sequence data in a population of cattle using four imputation approaches. We also investigate the effect of SNP reference panel size on imputation performance. RESULTS SNP array genotypes and ONT sequence data for 62 beef heifers were used to calculate genomic estimated breeding values (GEBVs) from 641 k SNP for four traits. GEBV accuracy was much higher when genome-wide flanking SNP from sequence data were used to help impute the 641 k panel used for genomic predictions. Using the imputation package QUILT, correlations between ONT and low-density SNP array genomic breeding values were greater than 0.91 and up to 0.97 for sequencing coverages as low as 0.1 × using a reference panel of 48 million SNP. Imputation time was significantly reduced by decreasing the number of flanking sequence SNP used in imputation for all methods. When compared to high-density SNP arrays, genotyping accuracy and genomic breeding value correlations at 0.5 × coverage were also found to be higher than those imputed from low-density arrays. CONCLUSIONS Here we demonstrated accurate genomic prediction is possible with ONT sequence data from sequencing coverages as low as 0.1 × , and imputation time can be as short as 10 min per sample. We also demonstrate that in this population, genotyping-by-sequencing at 0.1 × coverage can be more accurate than imputation from low-density SNP arrays.
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Affiliation(s)
- H J Lamb
- Centre for Animal Science, Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, St. Lucia, QLD, 4067, Australia.
| | - L T Nguyen
- Centre for Animal Science, Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, St. Lucia, QLD, 4067, Australia
| | - J P Copley
- Centre for Animal Science, Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, St. Lucia, QLD, 4067, Australia
| | - B N Engle
- USDA, ARS, U.S. Meat Animal Research Centre, Clay Centre, NE, 68933, USA
| | - B J Hayes
- Centre for Animal Science, Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, St. Lucia, QLD, 4067, Australia
| | - E M Ross
- Centre for Animal Science, Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, St. Lucia, QLD, 4067, Australia
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Widmer S, Seefried FR, Häfliger IM, Signer-Hasler H, Flury C, Drögemüller C. WNT10B: A locus increasing risk of brachygnathia inferior in Brown Swiss cattle. J Dairy Sci 2023; 106:8969-8978. [PMID: 37641348 DOI: 10.3168/jds.2023-23315] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Accepted: 05/15/2023] [Indexed: 08/31/2023]
Abstract
Shortening of the mandible (brachygnathia inferior) is a congenital, often inherited and variably expressed craniofacial anomaly in domestic animals including cattle. Brachygnathia inferior can lead to poorer animal health and welfare and reduced growth, which ultimately affects productivity. Within the course of the systematic conformation scoring, cases with a frequency of about 0.1% were observed in the Brown Swiss cattle population of Switzerland. In contrast, this anomaly is almost unknown in the Original Braunvieh population, representing the breed of origin. Because none of the individually examined 46 living offspring of our study cohort of 145 affected cows showed the trait, we can most likely exclude a monogenic-dominant mode of inheritance. We hypothesized that either a monogenic recessive or a complex mode of inheritance was underlying. Through a genome-wide association study of 145 cases and 509 controls with imputed 624k SNP data, we identified a 4.5 Mb genomic region on bovine chromosome 5 significantly associated with this anomaly. This locus was fine-mapped using whole-genome sequencing data. A run of homozygosity analysis revealed a critical interval of 430 kb. A breed specific frameshift duplication in WNT10B (rs525007739; c.910dupC; p.Arg304ProfsTer14) located in this genomic region was found to be associated with a 21.5-fold increased risk of brachygnathia inferior in homozygous carriers. Consequently, we present for the first time a genetic locus associated with this well-known anomaly in cattle, which allows DNA-based selection of Brown Swiss animals at decreased risk for mandibular shortening. In addition, this study represents the first large animal model of a WNT10B-related inherited developmental disorder in a mammalian species.
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Affiliation(s)
- Sarah Widmer
- Institute of Genetics, Vetsuisse Faculty, University of Bern, 3012 Bern, Switzerland; Qualitas AG, 6300 Zug, Switzerland
| | | | - Irene M Häfliger
- Institute of Genetics, Vetsuisse Faculty, University of Bern, 3012 Bern, Switzerland
| | - Heidi Signer-Hasler
- School of Agricultural, Forest and Food Sciences, Bern University of Applied Sciences, 3052 Zollikofen, Switzerland
| | - Christine Flury
- School of Agricultural, Forest and Food Sciences, Bern University of Applied Sciences, 3052 Zollikofen, Switzerland
| | - Cord Drögemüller
- Institute of Genetics, Vetsuisse Faculty, University of Bern, 3012 Bern, Switzerland.
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Woolley SA, Salavati M, Clark EL. Recent advances in the genomic resources for sheep. Mamm Genome 2023; 34:545-558. [PMID: 37752302 PMCID: PMC10627984 DOI: 10.1007/s00335-023-10018-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Accepted: 08/30/2023] [Indexed: 09/28/2023]
Abstract
Sheep (Ovis aries) provide a vital source of protein and fibre to human populations. In coming decades, as the pressures associated with rapidly changing climates increase, breeding sheep sustainably as well as producing enough protein to feed a growing human population will pose a considerable challenge for sheep production across the globe. High quality reference genomes and other genomic resources can help to meet these challenges by: (1) informing breeding programmes by adding a priori information about the genome, (2) providing tools such as pangenomes for characterising and conserving global genetic diversity, and (3) improving our understanding of fundamental biology using the power of genomic information to link cell, tissue and whole animal scale knowledge. In this review we describe recent advances in the genomic resources available for sheep, discuss how these might help to meet future challenges for sheep production, and provide some insight into what the future might hold.
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Affiliation(s)
- Shernae A Woolley
- The Roslin Institute, University of Edinburgh, Easter Bush, Midlothian, EH25 9RG, UK
| | - Mazdak Salavati
- The Roslin Institute, University of Edinburgh, Easter Bush, Midlothian, EH25 9RG, UK
- Scotland's Rural College, Parkgate, Barony Campus, Dumfries, DG1 3NE, UK
| | - Emily L Clark
- The Roslin Institute, University of Edinburgh, Easter Bush, Midlothian, EH25 9RG, UK.
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Gualdrón Duarte JL, Yuan C, Gori AS, Moreira GCM, Takeda H, Coppieters W, Charlier C, Georges M, Druet T. Sequenced-based GWAS for linear classification traits in Belgian Blue beef cattle reveals new coding variants in genes regulating body size in mammals. Genet Sel Evol 2023; 55:83. [PMID: 38017417 PMCID: PMC10683324 DOI: 10.1186/s12711-023-00857-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Accepted: 11/17/2023] [Indexed: 11/30/2023] Open
Abstract
BACKGROUND Cohorts of individuals that have been genotyped and phenotyped for genomic selection programs offer the opportunity to better understand genetic variation associated with complex traits. Here, we performed an association study for traits related to body size and muscular development in intensively selected beef cattle. We leveraged multiple trait information to refine and interpret the significant associations. RESULTS After a multiple-step genotype imputation to the sequence-level for 14,762 Belgian Blue beef (BBB) cows, we performed a genome-wide association study (GWAS) for 11 traits related to muscular development and body size. The 37 identified genome-wide significant quantitative trait loci (QTL) could be condensed in 11 unique QTL regions based on their position. Evidence for pleiotropic effects was found in most of these regions (e.g., correlated association signals, overlap between credible sets (CS) of candidate variants). Thus, we applied a multiple-trait approach to combine information from different traits to refine the CS. In several QTL regions, we identified strong candidate genes known to be related to growth and height in other species such as LCORL-NCAPG or CCND2. For some of these genes, relevant candidate variants were identified in the CS, including three new missense variants in EZH2, PAPPA2 and ADAM12, possibly two additional coding variants in LCORL, and candidate regulatory variants linked to CCND2 and ARMC12. Strikingly, four other QTL regions associated with dimension or muscular development traits were related to five (recessive) deleterious coding variants previously identified. CONCLUSIONS Our study further supports that a set of common genes controls body size across mammalian species. In particular, we added new genes to the list of those associated with height in both humans and cattle. We also identified new strong candidate causal variants in some of these genes, strengthening the evidence of their causality. Several breed-specific recessive deleterious variants were identified in our QTL regions, probably as a result of the extreme selection for muscular development in BBB cattle.
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Affiliation(s)
- José Luis Gualdrón Duarte
- Unit of Animal Genomics, GIGA-R & Faculty of Veterinary Medicine, University of Liège, Avenue de l'Hôpital, 1, Liège, 4000, Belgium.
- Walloon Breeders Association, Rue des Champs Elysées, 4, 5590, Ciney, Belgium.
| | - Can Yuan
- Unit of Animal Genomics, GIGA-R & Faculty of Veterinary Medicine, University of Liège, Avenue de l'Hôpital, 1, Liège, 4000, Belgium
| | - Ann-Stephan Gori
- Walloon Breeders Association, Rue des Champs Elysées, 4, 5590, Ciney, Belgium
| | - Gabriel C M Moreira
- Unit of Animal Genomics, GIGA-R & Faculty of Veterinary Medicine, University of Liège, Avenue de l'Hôpital, 1, Liège, 4000, Belgium
| | - Haruko Takeda
- Unit of Animal Genomics, GIGA-R & Faculty of Veterinary Medicine, University of Liège, Avenue de l'Hôpital, 1, Liège, 4000, Belgium
| | - Wouter Coppieters
- GIGA Genomic Platform, GIGA-R, University of Liège, Avenue de l'Hôpital, 1, 4000, Liège, Belgium
| | - Carole Charlier
- Unit of Animal Genomics, GIGA-R & Faculty of Veterinary Medicine, University of Liège, Avenue de l'Hôpital, 1, Liège, 4000, Belgium
| | - Michel Georges
- Unit of Animal Genomics, GIGA-R & Faculty of Veterinary Medicine, University of Liège, Avenue de l'Hôpital, 1, Liège, 4000, Belgium
| | - Tom Druet
- Unit of Animal Genomics, GIGA-R & Faculty of Veterinary Medicine, University of Liège, Avenue de l'Hôpital, 1, Liège, 4000, Belgium
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Marašinskienė Š, Šveistienė R, Razmaitė V, Račkauskaitė A, Juškienė V. Genetic Variability and Conservation Challenges in Lithuanian Dairy Cattle Populations. Animals (Basel) 2023; 13:3506. [PMID: 38003124 PMCID: PMC10668635 DOI: 10.3390/ani13223506] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Revised: 10/27/2023] [Accepted: 11/08/2023] [Indexed: 11/26/2023] Open
Abstract
The purpose of the study was to investigate the genetic variability of open Lithuanian Red and Red-and-White (LRWP) and Lithuanian Black-and-White (LBWP) dairy cattle populations and indicate the differences from the old genotypes of Lithuanian Black-and-White (LBW) and Lithuanian Red cattle (LR), which are currently under a conservation program. In order to gain a better understanding of the populations under conservation and to minimize the potential influence of other breeds, a distinct subgroup was formed that comprised animals whose father and mother belonged to the same breed (LR_pure and LBW_pure). The genetic variability was estimated using the number of founders, pedigree completeness, number of males and females in reproduction and age distribution, generation interval (GI), inbreeding coefficient (F) and effective population size (Ne). The highest average pedigree completeness values in the second generations of the old genotype LR and LBW were 100%. Higher ages of females in the populations under conservation were related to a higher GI and their longer life expectancy. In 2021, the reproductive age of bulls used for insemination within these populations ranged from 5.1 to 27.8 years. The proportions of males producing offspring in their older age indicate that the semen was used from the national gene bank of commercial artificial insemination companies. The GI (>5) in LR and LBW females was higher than that in LRWP and LBWP. The analysis of the data over the 15-year period showed that the GI of males in LRWP and LBWP decreased equally by 38%, while in LR_pure population, it increased by 80%. A high (9.24%) average inbreeding coefficient (F) was found in inbred animals of LR_pure population, while in LBW_pure, it was 5.35% in 2021. The coefficient of inbreeding varied within the different cattle populations. In the open LR population, it ranged from 1.48% to 2.7%, while in the LRWP population, it fell between 2.12% and 3.72%. The lowest effective population size (Ne) concerning the rate of inbreeding was observed in LBW_pure (23) and LR_pure (59), with the highest Ne identified in the LBWP population (462). When considering Ne based on the number of parents, LR_pure displayed the lowest Ne (42), while the highest Ne was found in LBWP (4449). An analysis of local cattle populations reveals that LR faces the most critical situation. This particular population has been steadily declining for a number of years, necessitating additional measures and efforts to safeguard the LR's ancestral genetic makeup. The results of the LBWP analysis also highlight a concerning trend. Even in very large populations with open breeding programs, the effective population size per generation can experience a significant decrease.
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Affiliation(s)
- Šarūnė Marašinskienė
- Animal Science Institute, Lithuanian University of Health Sciences, R. Žebenkos 12, LT 82317 Baisogala, Lithuania; (R.Š.); (V.R.); (A.R.); (V.J.)
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O’Callaghan E, Navarrete-Lopez P, Štiavnická M, Sánchez JM, Maroto M, Pericuesta E, Fernández-González R, O’Meara C, Eivers B, Kelleher MM, Evans RD, Mapel XM, Lloret-Villas A, Pausch H, Balastegui-Alarcón M, Avilés M, Sanchez-Rodriguez A, Roldan ERS, McDonald M, Kenny DA, Fair S, Gutiérrez-Adán A, Lonergan P. Adenylate kinase 9 is essential for sperm function and male fertility in mammals. Proc Natl Acad Sci U S A 2023; 120:e2305712120. [PMID: 37812723 PMCID: PMC10589668 DOI: 10.1073/pnas.2305712120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2023] [Accepted: 08/23/2023] [Indexed: 10/11/2023] Open
Abstract
Despite passing routine laboratory tests for semen quality, bulls used in artificial insemination exhibit significant variation in fertility. Routine analysis of fertility data identified a dairy bull with extreme subfertility (10% pregnancy rate). To characterize the subfertility phenotype, a range of in vitro, in vivo, and molecular assays were carried out. Sperm from the subfertile bull exhibited reduced motility and severely reduced caffeine-induced hyperactivation compared to controls. Ability to penetrate the zona pellucida, cleavage rate, cleavage kinetics, and blastocyst yield after IVF or AI were significantly lower than in control bulls. Whole-genome sequencing from semen and RNA sequencing of testis tissue revealed a critical mutation in adenylate kinase 9 (AK9) that impaired splicing, leading to a premature termination codon and a severely truncated protein. Mice deficient in AK9 were generated to further investigate the function of the gene; knockout males were phenotypically indistinguishable from their wild-type littermates but produced immotile sperm that were incapable of normal fertilization. These sperm exhibited numerous abnormalities, including a low ATP concentration and reduced motility. RNA-seq analysis of their testis revealed differential gene expression of components of the axoneme and sperm flagellum as well as steroid metabolic processes. Sperm ultrastructural analysis showed a high percentage of sperm with abnormal flagella. Combined bovine and murine data indicate the essential metabolic role of AK9 in sperm motility and/or hyperactivation, which in turn affects sperm binding and penetration of the zona pellucida. Thus, AK9 has been found to be directly implicated in impaired male fertility in mammals.
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Affiliation(s)
- Elena O’Callaghan
- Animal and Crop Sciences, School of Agriculture and Food Science, University College Dublin, Belfield, DublinD04 V1W8, Ireland
| | - Paula Navarrete-Lopez
- Departamento de Reproducción Animal, Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria-Centro Nacional integrado en la Agencia Estatal Consejo Superior de Investigaciones Científicas, Madrid28040, Spain
| | - Miriama Štiavnická
- Department of Biological Sciences, Bernal Institute, Faculty of Science and Engineering, University of Limerick, LimerickV94 T9PX, Ireland
| | - José M. Sánchez
- Animal and Crop Sciences, School of Agriculture and Food Science, University College Dublin, Belfield, DublinD04 V1W8, Ireland
- Departamento de Reproducción Animal, Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria-Centro Nacional integrado en la Agencia Estatal Consejo Superior de Investigaciones Científicas, Madrid28040, Spain
| | - Maria Maroto
- Departamento de Reproducción Animal, Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria-Centro Nacional integrado en la Agencia Estatal Consejo Superior de Investigaciones Científicas, Madrid28040, Spain
| | - Eva Pericuesta
- Departamento de Reproducción Animal, Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria-Centro Nacional integrado en la Agencia Estatal Consejo Superior de Investigaciones Científicas, Madrid28040, Spain
| | - Raul Fernández-González
- Departamento de Reproducción Animal, Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria-Centro Nacional integrado en la Agencia Estatal Consejo Superior de Investigaciones Científicas, Madrid28040, Spain
| | - Ciara O’Meara
- National Cattle Breeding Centre, County KildareW91 WF59, Ireland
| | - Bernard Eivers
- National Cattle Breeding Centre, County KildareW91 WF59, Ireland
| | - Margaret M. Kelleher
- Irish Cattle Breeding Federation, Link Road, Ballincollig, County CorkP31 D452, Ireland
| | - Ross D. Evans
- Irish Cattle Breeding Federation, Link Road, Ballincollig, County CorkP31 D452, Ireland
| | - Xena M. Mapel
- Animal Genomics, Institute of Agricultural Sciences, ETH Zürich, Zürich8092, Switzerland
| | - Audald Lloret-Villas
- Animal Genomics, Institute of Agricultural Sciences, ETH Zürich, Zürich8092, Switzerland
| | - Hubert Pausch
- Animal Genomics, Institute of Agricultural Sciences, ETH Zürich, Zürich8092, Switzerland
| | - Miriam Balastegui-Alarcón
- Departamento de Biología Celular e Histología, Universidad de Murcia-Instituto Murciano de Investigación Biosanitaria Pascual Parrilla, Murcia30120, Spain
| | - Manuel Avilés
- Departamento de Biología Celular e Histología, Universidad de Murcia-Instituto Murciano de Investigación Biosanitaria Pascual Parrilla, Murcia30120, Spain
| | - Ana Sanchez-Rodriguez
- Departmento de Biodiversidad y Biología Evolutiva, Museo Nacional de Ciencias Naturales, Madrid28006, Spain
| | - Eduardo R. S. Roldan
- Departmento de Biodiversidad y Biología Evolutiva, Museo Nacional de Ciencias Naturales, Madrid28006, Spain
| | - Michael McDonald
- Animal and Crop Sciences, School of Agriculture and Food Science, University College Dublin, Belfield, DublinD04 V1W8, Ireland
| | - David A. Kenny
- Animal and Bioscience Department, Teagasc, Animal and Grassland Research and Innovation Centre, Grange, Dunsany, County MeathC15 PW93, Ireland
| | - Sean Fair
- Department of Biological Sciences, Bernal Institute, Faculty of Science and Engineering, University of Limerick, LimerickV94 T9PX, Ireland
| | - Alfonso Gutiérrez-Adán
- Departamento de Reproducción Animal, Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria-Centro Nacional integrado en la Agencia Estatal Consejo Superior de Investigaciones Científicas, Madrid28040, Spain
| | - Patrick Lonergan
- Animal and Crop Sciences, School of Agriculture and Food Science, University College Dublin, Belfield, DublinD04 V1W8, Ireland
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Hayes BJ, Copley J, Dodd E, Ross EM, Speight S, Fordyce G. Multi-breed genomic evaluation for tropical beef cattle when no pedigree information is available. Genet Sel Evol 2023; 55:71. [PMID: 37845626 PMCID: PMC10578004 DOI: 10.1186/s12711-023-00847-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Accepted: 10/04/2023] [Indexed: 10/18/2023] Open
Abstract
BACKGROUND It has been challenging to implement genomic selection in multi-breed tropical beef cattle populations. If commercial (often crossbred) animals could be used in the reference population for these genomic evaluations, this could allow for very large reference populations. In tropical beef systems, such animals often have no pedigree information. Here we investigate potential models for such data, using marker heterozygosity (to model heterosis) and breed composition derived from genetic markers, as covariates in the model. Models treated breed effects as either fixed or random, and included genomic best linear unbiased prediction (GBLUP) and BayesR. A tropically-adapted beef cattle dataset of 29,391 purebred, crossbred and composite commercial animals was used to evaluate the models. RESULTS Treating breed effects as random, in an approach analogous to genetic groups allowed partitioning of the genetic variance into within-breed and across breed-components (even with a large number of breeds), and estimation of within-breed and across-breed genomic estimated breeding values (GEBV). We demonstrate that moderately-accurate (0.30-0.43) GEBV can be calculated using these models. Treating breed effects as random gave more accurate GEBV than treating breed as fixed. A simple GBLUP model where no breed effects were fitted gave the same accuracy (and correlations of GEBV very close to 1) as a model where GEBV for within-breed and the GEBV for (random) across-breed effects were included. When GEBV were predicted for herds with no data in the reference population, BayesR resulted in the highest accuracy, with 3% accuracy improvement averaged across traits, especially when the validation population was less related to the reference population. Estimates of heterosis from our models were in line with previous estimates from beef cattle. A method for estimating the number of effective breed comparisons for each breed combination accumulated across contemporary groups is presented. CONCLUSIONS When no pedigree is available, breed composition and heterosis for inclusion in multi-breed genomic evaluation can be estimated from genotypes. When GEBV were predicted for herds with no data in the reference population, BayesR resulted in the highest accuracy.
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Affiliation(s)
- Ben J Hayes
- Centre for Animal Science, Queensland Alliance for Agriculture and Food Innovation, University of Queensland, St Lucia, QLD, 4067, Australia.
| | - James Copley
- Centre for Animal Science, Queensland Alliance for Agriculture and Food Innovation, University of Queensland, St Lucia, QLD, 4067, Australia
| | - Elsie Dodd
- Centre for Animal Science, Queensland Alliance for Agriculture and Food Innovation, University of Queensland, St Lucia, QLD, 4067, Australia
| | - Elizabeth M Ross
- Centre for Animal Science, Queensland Alliance for Agriculture and Food Innovation, University of Queensland, St Lucia, QLD, 4067, Australia
| | - Shannon Speight
- Centre for Animal Science, Queensland Alliance for Agriculture and Food Innovation, University of Queensland, St Lucia, QLD, 4067, Australia
- BlackBox Co, Mareeba, QLD, 4880, Australia
| | - Geoffry Fordyce
- Centre for Animal Science, Queensland Alliance for Agriculture and Food Innovation, University of Queensland, St Lucia, QLD, 4067, Australia
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Badia-Bringué G, Canive M, Fernandez-Jimenez N, Lavín JL, Casais R, Blanco-Vázquez C, Vázquez P, Fernández A, Bilbao JR, Garrido JM, Juste RA, González-Recio O, Alonso-Hearn M. Summary-data based Mendelian randomization identifies gene expression regulatory polymorphisms associated with bovine paratuberculosis by modulation of the nuclear factor Kappa β (NF-κß)-mediated inflammatory response. BMC Genomics 2023; 24:605. [PMID: 37821814 PMCID: PMC10568764 DOI: 10.1186/s12864-023-09710-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Accepted: 10/02/2023] [Indexed: 10/13/2023] Open
Abstract
Genome-wide association studies (GWAS) have identified host genetic variants associated with paratuberculosis (PTB) susceptibility. Most of the GWAS-identified SNPs are in non-coding regions. Connecting these non-coding variants and downstream affected genes is a challenge and, up to date, only a few functional mutations or expression quantitative loci (cis-eQTLs) associated with PTB susceptibility have been identified. In the current study, the associations between imputed whole-genome sequence genotypes and whole RNA-Sequencing data from peripheral blood (PB) and ileocecal valve (ICV) samples of Spanish Holstein cows (N = 16) were analyzed with TensorQTL. This approach allowed the identification of 88 and 37 cis-eQTLs regulating the expression levels of 90 and 37 genes in PB and ICV samples, respectively (False discorey rate, FDR ≤ 0.05). Next, we applied summary-based data Mendelian randomization (SMR) to integrate the cis-eQTL dataset with GWAS data obtained from a cohort of 813 culled cattle that were classified according to the presence or absence of PTB-associated histopathological lesions in gut tissues. After multiple testing corrections (FDR ≤ 0.05), we identified two novel cis-eQTLs affecting the expression of the early growth response factor 4 (EGR4) and the bovine neuroblastoma breakpoint family member 6-like protein isoform 2 (MGC134040) that showed pleiotropic associations with the presence of multifocal and diffuse lesions in gut tissues; P = 0.002 and P = 0.017, respectively. While EGR4 acts as a brake on T-cell proliferation and cytokine production through interaction with the nuclear factor Kappa β (NF-κß), MGC134040 is a target gene of NF-κß. Our findings provide a better understanding of the genetic factors influencing PTB outcomes, confirm that the multifocal lesions are localized/confined lesions that have different underlying host genetics than the diffuse lesions, and highlight regulatory SNPs and regulated-gene targets to design future functional studies.
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Affiliation(s)
- Gerard Badia-Bringué
- Department of Animal Health, NEIKER- Basque Institute for Agricultural Research and Development, Basque Research and Technology Alliance (BRTA), Derio, Bizkaia, Spain
- Doctoral Program in Molecular Biology and Biomedicine, Universidad del País Vasco/Euskal Herriko Unibertsitatea (UPV/EHU), Leioa, Bizkaia, Spain
| | - Maria Canive
- Department of Animal Health, NEIKER- Basque Institute for Agricultural Research and Development, Basque Research and Technology Alliance (BRTA), Derio, Bizkaia, Spain
| | - Nora Fernandez-Jimenez
- Department of Genetics, Physical Anthropology and Animal Physiology, University of the Basque Country (UPV/EHU), Biocruces-Bizkaia HRI, Leioa, Bizkaia, Spain
| | - José Luis Lavín
- Department of Applied Mathematics, NEIKER- Basque Institute for Agricultural Research and Development, Basque Research and Technology Alliance (BRTA), Derio, Bizkaia, Spain
| | - Rosa Casais
- Center of Animal Biotechnology, SERIDA, Servicio Regional de Investigación y Desarrollo Agroalimentario, Deva, Asturias, Spain
| | - Cristina Blanco-Vázquez
- Center of Animal Biotechnology, SERIDA, Servicio Regional de Investigación y Desarrollo Agroalimentario, Deva, Asturias, Spain
| | - Patricia Vázquez
- Department of Animal Health, NEIKER- Basque Institute for Agricultural Research and Development, Basque Research and Technology Alliance (BRTA), Derio, Bizkaia, Spain
| | - Almudena Fernández
- Departamento de Mejora Genética Animal, Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria, CSIC, Madrid, Spain
| | - Jose Ramón Bilbao
- Department of Genetics, Physical Anthropology and Animal Physiology, University of the Basque Country (UPV/EHU), Biocruces-Bizkaia HRI, Leioa, Bizkaia, Spain
| | - Joseba M Garrido
- Department of Animal Health, NEIKER- Basque Institute for Agricultural Research and Development, Basque Research and Technology Alliance (BRTA), Derio, Bizkaia, Spain
| | - Ramón A Juste
- Department of Animal Health, NEIKER- Basque Institute for Agricultural Research and Development, Basque Research and Technology Alliance (BRTA), Derio, Bizkaia, Spain
| | - Oscar González-Recio
- Departamento de Mejora Genética Animal, Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria, CSIC, Madrid, Spain
| | - Marta Alonso-Hearn
- Department of Animal Health, NEIKER- Basque Institute for Agricultural Research and Development, Basque Research and Technology Alliance (BRTA), Derio, Bizkaia, Spain.
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Xiang R, Fang L, Liu S, Macleod IM, Liu Z, Breen EJ, Gao Y, Liu GE, Tenesa A, Mason BA, Chamberlain AJ, Wray NR, Goddard ME. Gene expression and RNA splicing explain large proportions of the heritability for complex traits in cattle. CELL GENOMICS 2023; 3:100385. [PMID: 37868035 PMCID: PMC10589627 DOI: 10.1016/j.xgen.2023.100385] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Revised: 08/10/2022] [Accepted: 07/26/2023] [Indexed: 10/24/2023]
Abstract
Many quantitative trait loci (QTLs) are in non-coding regions. Therefore, QTLs are assumed to affect gene regulation. Gene expression and RNA splicing are primary steps of transcription, so DNA variants changing gene expression (eVariants) or RNA splicing (sVariants) are expected to significantly affect phenotypes. We quantify the contribution of eVariants and sVariants detected from 16 tissues (n = 4,725) to 37 traits of ∼120,000 cattle (average magnitude of genetic correlation between traits = 0.13). Analyzed in Bayesian mixture models, averaged across 37 traits, cis and trans eVariants and sVariants detected from 16 tissues jointly explain 69.2% (SE = 0.5%) of heritability, 44% more than expected from the same number of random variants. This 69.2% includes an average of 24% from trans e-/sVariants (14% more than expected). Averaged across 56 lipidomic traits, multi-tissue cis and trans e-/sVariants also explain 71.5% (SE = 0.3%) of heritability, demonstrating the essential role of proximal and distal regulatory variants in shaping mammalian phenotypes.
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Affiliation(s)
- Ruidong Xiang
- Faculty of Veterinary & Agricultural Science, the University of Melbourne, Parkville, VIC 3052, Australia
- Agriculture Victoria, AgriBio, Centre for AgriBiosciences, Bundoora, VIC 3083, Australia
- Cambridge-Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, VIC 3004, Australia
| | - Lingzhao Fang
- MRC Human Genetics Unit at the Institute of Genetics and Cancer, the University of Edinburgh, Edinburgh, UK
- Center for Quantitative Genetics and Genomics, Aarhus University, Aarhus, Denmark
| | - Shuli Liu
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang 310024, China
| | - Iona M. Macleod
- Agriculture Victoria, AgriBio, Centre for AgriBiosciences, Bundoora, VIC 3083, Australia
| | - Zhiqian Liu
- Agriculture Victoria, AgriBio, Centre for AgriBiosciences, Bundoora, VIC 3083, Australia
| | - Edmond J. Breen
- Agriculture Victoria, AgriBio, Centre for AgriBiosciences, Bundoora, VIC 3083, Australia
| | - Yahui Gao
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, MD 20705, USA
| | - George E. Liu
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, MD 20705, USA
| | - Albert Tenesa
- MRC Human Genetics Unit at the Institute of Genetics and Cancer, the University of Edinburgh, Edinburgh, UK
- The Roslin Institute, Royal (Dick) School of Veterinary Studies, the University of Edinburgh, Midlothian EH25 9RG, UK
| | - CattleGTEx Consortium
- Faculty of Veterinary & Agricultural Science, the University of Melbourne, Parkville, VIC 3052, Australia
- Agriculture Victoria, AgriBio, Centre for AgriBiosciences, Bundoora, VIC 3083, Australia
- Cambridge-Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, VIC 3004, Australia
- MRC Human Genetics Unit at the Institute of Genetics and Cancer, the University of Edinburgh, Edinburgh, UK
- Center for Quantitative Genetics and Genomics, Aarhus University, Aarhus, Denmark
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang 310024, China
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, MD 20705, USA
- The Roslin Institute, Royal (Dick) School of Veterinary Studies, the University of Edinburgh, Midlothian EH25 9RG, UK
- Institute for Molecular Bioscience, the University of Queensland, Brisbane, QLD 4072, Australia
- Queensland Brain Institute, the University of Queensland, Brisbane, QLD 4072, Australia
- School of Applied Systems Biology, La Trobe University, Bundoora, VIC 3083, Australia
| | - Brett A. Mason
- Agriculture Victoria, AgriBio, Centre for AgriBiosciences, Bundoora, VIC 3083, Australia
| | - Amanda J. Chamberlain
- Agriculture Victoria, AgriBio, Centre for AgriBiosciences, Bundoora, VIC 3083, Australia
- School of Applied Systems Biology, La Trobe University, Bundoora, VIC 3083, Australia
| | - Naomi R. Wray
- Institute for Molecular Bioscience, the University of Queensland, Brisbane, QLD 4072, Australia
- Queensland Brain Institute, the University of Queensland, Brisbane, QLD 4072, Australia
| | - Michael E. Goddard
- Faculty of Veterinary & Agricultural Science, the University of Melbourne, Parkville, VIC 3052, Australia
- Agriculture Victoria, AgriBio, Centre for AgriBiosciences, Bundoora, VIC 3083, Australia
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Xie S, Isaacs K, Becker G, Murdoch BM. A computational framework for improving genetic variants identification from 5,061 sheep sequencing data. J Anim Sci Biotechnol 2023; 14:127. [PMID: 37779189 PMCID: PMC10544426 DOI: 10.1186/s40104-023-00923-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2023] [Accepted: 08/01/2023] [Indexed: 10/03/2023] Open
Abstract
BACKGROUND Pan-genomics is a recently emerging strategy that can be utilized to provide a more comprehensive characterization of genetic variation. Joint calling is routinely used to combine identified variants across multiple related samples. However, the improvement of variants identification using the mutual support information from multiple samples remains quite limited for population-scale genotyping. RESULTS In this study, we developed a computational framework for joint calling genetic variants from 5,061 sheep by incorporating the sequencing error and optimizing mutual support information from multiple samples' data. The variants were accurately identified from multiple samples by using four steps: (1) Probabilities of variants from two widely used algorithms, GATK and Freebayes, were calculated by Poisson model incorporating base sequencing error potential; (2) The variants with high mapping quality or consistently identified from at least two samples by GATK and Freebayes were used to construct the raw high-confidence identification (rHID) variants database; (3) The high confidence variants identified in single sample were ordered by probability value and controlled by false discovery rate (FDR) using rHID database; (4) To avoid the elimination of potentially true variants from rHID database, the variants that failed FDR were reexamined to rescued potential true variants and ensured high accurate identification variants. The results indicated that the percent of concordant SNPs and Indels from Freebayes and GATK after our new method were significantly improved 12%-32% compared with raw variants and advantageously found low frequency variants of individual sheep involved several traits including nipples number (GPC5), scrapie pathology (PAPSS2), seasonal reproduction and litter size (GRM1), coat color (RAB27A), and lentivirus susceptibility (TMEM154). CONCLUSION The new method used the computational strategy to reduce the number of false positives, and simultaneously improve the identification of genetic variants. This strategy did not incur any extra cost by using any additional samples or sequencing data information and advantageously identified rare variants which can be important for practical applications of animal breeding.
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Affiliation(s)
- Shangqian Xie
- Department of Animal, Veterinary & Food Sciences, University of Idaho, Moscow, ID, USA
| | | | - Gabrielle Becker
- Department of Animal, Veterinary & Food Sciences, University of Idaho, Moscow, ID, USA
| | - Brenda M Murdoch
- Department of Animal, Veterinary & Food Sciences, University of Idaho, Moscow, ID, USA.
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40
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Prowse-Wilkins CP, Wang J, Garner JB, Goddard ME, Chamberlain AJ. Allele specific binding of histone modifications and a transcription factor does not predict allele specific expression in correlated ChIP-seq peak-exon pairs. Sci Rep 2023; 13:15596. [PMID: 37730913 PMCID: PMC10511416 DOI: 10.1038/s41598-023-42637-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2022] [Accepted: 09/13/2023] [Indexed: 09/22/2023] Open
Abstract
Allele specific expression (ASE) is widespread in many species including cows. Therefore, regulatory regions which control gene expression should show cis-regulatory variation which mirrors this differential expression within the animal. ChIP-seq peaks for histone modifications and transcription factors measure activity at functional regions and the height of some peaks have been shown to correlate across tissues with the expression of particular genes, suggesting these peaks are putative regulatory regions. In this study we identified ASE in the bovine genome in multiple tissues and investigated whether ChIP-seq peaks for four histone modifications and the transcription factor CTCF show allele specific binding (ASB) differences in the same tissues. We then investigate whether peak height and gene expression, which correlates across tissues, also correlates within the animal by investigating whether the direction of ASB in putative regulatory regions, mirrors that of the ASE in the genes they are putatively regulating. We found that ASE and ASB were widespread in the bovine genome but vary in extent between tissues. However, even when the height of a peak was positively correlated across tissues with expression of an exon, ASE of the exon and ASB of the peak were in the same direction only half the time. A likely explanation for this finding is that the correlations between peak height and exon expression do not indicate that the height of the peak causes the extent of exon expression, at least in some cases.
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Affiliation(s)
- Claire P Prowse-Wilkins
- Faculty of Veterinary & Agricultural Science, The University of Melbourne, Parkville, VIC, 3010, Australia.
- Agriculture Victoria, AgriBio, Centre for AgriBiosciences, Bundoora, VIC, 3083, Australia.
| | - Jianghui Wang
- Agriculture Victoria, AgriBio, Centre for AgriBiosciences, Bundoora, VIC, 3083, Australia
| | - Josie B Garner
- Agriculture Victoria, Ellinbank Dairy Centre, Ellinbank, VIC, 3821, Australia
| | - Michael E Goddard
- Faculty of Veterinary & Agricultural Science, The University of Melbourne, Parkville, VIC, 3010, Australia
- Agriculture Victoria, AgriBio, Centre for AgriBiosciences, Bundoora, VIC, 3083, Australia
| | - Amanda J Chamberlain
- Agriculture Victoria, AgriBio, Centre for AgriBiosciences, Bundoora, VIC, 3083, Australia
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Gudra D, Valdovska A, Jonkus D, Galina D, Kairisa D, Ustinova M, Viksne K, Fridmanis D, Kalnina I. Genomic Characterization and Initial Insight into Mastitis-Associated SNP Profiles of Local Latvian Bos taurus Breeds. Animals (Basel) 2023; 13:2776. [PMID: 37685039 PMCID: PMC10487150 DOI: 10.3390/ani13172776] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Revised: 08/27/2023] [Accepted: 08/28/2023] [Indexed: 09/10/2023] Open
Abstract
Latvia has two local Bos taurus breeds-Latvian Brown (LBG) and Latvian Blue (LZG)-characterized by a good adaptation to the local climate, longevity, and high fat and protein contents in milk. Since these are desired traits in the dairy industry, this study investigated the genetic background of the LBG and LZG breeds and identified the genetic factors associated with mastitis. Blood and semen samples were acquired, and whole genome sequencing was then performed to acquire a genomic sequence with at least 35× or 10× coverage. The heterozygosity, nucleotide diversity, and LD analysis indicated that LBG and LZG cows have similar levels of genetic diversity compared to those of other breeds. An analysis of the population structure revealed that each breed clustered together, but the overall differentiation between the breeds was small. The highest genetic variance was observed in the LZG breed compared with the LBG breed. Our results show that SNP rs721295390 is associated with mastitis in the LBG breed, and SNPs rs383806754, chr29:43998719CG>C, and rs462030680 are associated with mastitis in the LZG breed. This study shows that local Latvian LBG and LZG breeds have a pronounced genetic differentiation, with each one suggesting its own mastitis-associated SNP profile.
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Affiliation(s)
- Dita Gudra
- Latvian Biomedical Research and Study Centre, LV-1067 Riga, Latvia; (D.G.); (M.U.); (K.V.); (D.F.)
| | - Anda Valdovska
- Faculty of Veterinary Medicine, Latvia University of Life Sciences and Technologies, LV-3001 Jelgava, Latvia
- Scientific Laboratory of Biotechnology, Latvia University of Life Sciences and Technologies, LV-3001 Jelgava, Latvia
| | - Daina Jonkus
- Faculty of Agriculture, Latvia University of Life Sciences and Technologies, LV-3001 Jelgava, Latvia (D.K.)
| | - Daiga Galina
- Faculty of Veterinary Medicine, Latvia University of Life Sciences and Technologies, LV-3001 Jelgava, Latvia
- Scientific Laboratory of Biotechnology, Latvia University of Life Sciences and Technologies, LV-3001 Jelgava, Latvia
| | - Daina Kairisa
- Faculty of Agriculture, Latvia University of Life Sciences and Technologies, LV-3001 Jelgava, Latvia (D.K.)
| | - Maija Ustinova
- Latvian Biomedical Research and Study Centre, LV-1067 Riga, Latvia; (D.G.); (M.U.); (K.V.); (D.F.)
| | - Kristine Viksne
- Latvian Biomedical Research and Study Centre, LV-1067 Riga, Latvia; (D.G.); (M.U.); (K.V.); (D.F.)
- Scientific Laboratory of Molecular Genetics, Riga Stradins University, LV-1007 Riga, Latvia
| | - Davids Fridmanis
- Latvian Biomedical Research and Study Centre, LV-1067 Riga, Latvia; (D.G.); (M.U.); (K.V.); (D.F.)
| | - Ineta Kalnina
- Latvian Biomedical Research and Study Centre, LV-1067 Riga, Latvia; (D.G.); (M.U.); (K.V.); (D.F.)
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Wong K, Abascal F, Ludwig L, Aupperle-Lellbach H, Grassinger J, Wright CW, Allison SJ, Pinder E, Phillips RM, Romero LP, Gal A, Roady PJ, Pires I, Guscetti F, Munday JS, Peleteiro MC, Pinto CA, Carvalho T, Cota J, Du Plessis EC, Constantino-Casas F, Plog S, Moe L, de Brot S, Bemelmans I, Amorim RL, Georgy SR, Prada J, Del Pozo J, Heimann M, de Carvalho Nunes L, Simola O, Pazzi P, Steyl J, Ubukata R, Vajdovich P, Priestnall SL, Suárez-Bonnet A, Roperto F, Millanta F, Palmieri C, Ortiz AL, Barros CSL, Gava A, Söderström ME, O'Donnell M, Klopfleisch R, Manrique-Rincón A, Martincorena I, Ferreira I, Arends MJ, Wood GA, Adams DJ, van der Weyden L. Cross-species oncogenomics offers insight into human muscle-invasive bladder cancer. Genome Biol 2023; 24:191. [PMID: 37635261 PMCID: PMC10464500 DOI: 10.1186/s13059-023-03026-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Accepted: 07/28/2023] [Indexed: 08/29/2023] Open
Abstract
BACKGROUND In humans, muscle-invasive bladder cancer (MIBC) is highly aggressive and associated with a poor prognosis. With a high mutation load and large number of altered genes, strategies to delineate key driver events are necessary. Dogs and cats develop urothelial carcinoma (UC) with histological and clinical similarities to human MIBC. Cattle that graze on bracken fern also develop UC, associated with exposure to the carcinogen ptaquiloside. These species may represent relevant animal models of spontaneous and carcinogen-induced UC that can provide insight into human MIBC. RESULTS Whole-exome sequencing of domestic canine (n = 87) and feline (n = 23) UC, and comparative analysis with human MIBC reveals a lower mutation rate in animal cases and the absence of APOBEC mutational signatures. A convergence of driver genes (ARID1A, KDM6A, TP53, FAT1, and NRAS) is discovered, along with common focally amplified and deleted genes involved in regulation of the cell cycle and chromatin remodelling. We identify mismatch repair deficiency in a subset of canine and feline UCs with biallelic inactivation of MSH2. Bovine UC (n = 8) is distinctly different; we identify novel mutational signatures which are recapitulated in vitro in human urinary bladder UC cells treated with bracken fern extracts or purified ptaquiloside. CONCLUSION Canine and feline urinary bladder UC represent relevant models of MIBC in humans, and cross-species analysis can identify evolutionarily conserved driver genes. We characterize mutational signatures in bovine UC associated with bracken fern and ptaquiloside exposure, a human-linked cancer exposure. Our work demonstrates the relevance of cross-species comparative analysis in understanding both human and animal UC.
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Affiliation(s)
- Kim Wong
- Experimental Cancer Genetics, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SA, UK
| | - Federico Abascal
- Experimental Cancer Genetics, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SA, UK
| | - Latasha Ludwig
- Department of Pathobiology, University of Guelph, Guelph, ON, Canada
| | - Heike Aupperle-Lellbach
- Laboklin GmbH & Co. KG, Bad Kissingen, Germany and Institute of Pathology, Department Comparative Experimental Pathology, School of Medicine, Technical University of Munich, Munich, Germany
| | - Julia Grassinger
- Laboklin GmbH & Co. KG, Bad Kissingen, Germany and Institute of Pathology, Department Comparative Experimental Pathology, School of Medicine, Technical University of Munich, Munich, Germany
| | - Colin W Wright
- School of Pharmacy and Medical Sciences, University of Bradford, West Yorkshire, UK
| | - Simon J Allison
- Department of Pharmacy, University of Huddersfield, Queensgate, Huddersfield, UK
| | - Emma Pinder
- Department of Pharmacy, University of Huddersfield, Queensgate, Huddersfield, UK
| | - Roger M Phillips
- Department of Pharmacy, University of Huddersfield, Queensgate, Huddersfield, UK
| | - Laura P Romero
- Departmento de Patología, Facultad de Medicina Veterinaria Y Zootecnia, Universidad Nacional Autónoma de México (UNAM), CDMX, Mexico City, México
| | - Arnon Gal
- Department of Veterinary Clinical Medicine, College of Veterinary Medicine, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Patrick J Roady
- Department of Veterinary Clinical Medicine, College of Veterinary Medicine, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Isabel Pires
- Department of Veterinary Science, CECAV-Veterinary and Animal Research Center, University of Trás-Os-Montes and Alto Douro, Vila Real, Portugal
| | - Franco Guscetti
- Institute of Veterinary Pathology, University of Zurich, Zurich, Switzerland
| | - John S Munday
- School of Veterinary Science, Massey University, Palmerston North, New Zealand
| | - Maria C Peleteiro
- Faculty of Veterinary Medicine, Centre for Interdisciplinary Research in Animal Health (CIISA), University of Lisbon, Lisbon, Portugal
| | - Carlos A Pinto
- Faculty of Veterinary Medicine, Centre for Interdisciplinary Research in Animal Health (CIISA), University of Lisbon, Lisbon, Portugal
| | | | - João Cota
- Faculty of Veterinary Medicine, Centre for Interdisciplinary Research in Animal Health (CIISA), University of Lisbon, Lisbon, Portugal
| | | | | | | | - Lars Moe
- Department of Companion Animal Clinical Sciences, Norwegian University of Life Sciences, Ås, Norway
| | - Simone de Brot
- Institute of Animal Pathology, COMPATH, University of Bern, Bern, Switzerland
| | | | - Renée Laufer Amorim
- Veterinary Clinic Department, School of Veterinary Medicine and Animal Science, São Paulo State University, Botucatu, Brazil
| | - Smitha R Georgy
- Department of Anatomic Pathology, Faculty of Veterinary and Agricultural Sciences, University of Melbourne, Victoria, Australia
| | - Justina Prada
- Department of Veterinary Science, CECAV-Veterinary and Animal Research Center, University of Trás-Os-Montes and Alto Douro, Vila Real, Portugal
| | - Jorge Del Pozo
- Royal Dick School of Veterinary Sciences, University of Edinburgh, Roslin, Scotland, UK
| | | | | | | | - Paolo Pazzi
- Department of Companion Animal Clinical Studies, Faculty of Veterinary Science, University of Pretoria, Pretoria, South Africa
| | - Johan Steyl
- Department of Paraclinical Sciences, Faculty of Veterinary Science, University of Pretoria, Pretoria, South Africa
| | - Rodrigo Ubukata
- E+ Especialidades Veterinárias - Veterinary Oncology, São Paulo, Brazil
| | - Peter Vajdovich
- Department of Clinical Pathology and Oncology, University of Veterinary Medicine Budapest, Budapest, Hungary
| | - Simon L Priestnall
- Department of Pathobiology and Population Sciences, The Royal Veterinary College, Hatfield, UK
| | - Alejandro Suárez-Bonnet
- Department of Pathobiology and Population Sciences, The Royal Veterinary College, Hatfield, UK
| | - Franco Roperto
- Dipartimento Di Biologia, Università Degli Studi Di Napoli Federico II, Napoli, Italy
| | | | - Chiara Palmieri
- School of Veterinary Science, The University of Queensland, Brisbane, QLD, Australia
| | - Ana L Ortiz
- School of Veterinary Medicine and Science, University of Nottingham, Nottingham, UK
| | - Claudio S L Barros
- Faculdade de Medicina Veterinária E Zootecnia, Universidade Federal de Mato Grosso Do Sul, Campo Grande, MS, Brazil
| | - Aldo Gava
- Pathology Laboratory of the Centro de Ciencias Agro-Veterinarias, Universidade Do Estado de Santa Catarina, Lages, SC, Brazil
| | - Minna E Söderström
- Department of Veterinary Biosciences, Faculty of Veterinary Medicine, University of Helsinki, Helsinki, Finland
| | - Marie O'Donnell
- Department of Pathology, Western General Hospital, Edinburgh, Scotland, UK
| | - Robert Klopfleisch
- Institute of Veterinary Pathology, Freie Universität Berlin, Berlin, Germany
| | - Andrea Manrique-Rincón
- Experimental Cancer Genetics, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SA, UK
| | - Inigo Martincorena
- Experimental Cancer Genetics, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SA, UK
| | - Ingrid Ferreira
- Experimental Cancer Genetics, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SA, UK
| | - Mark J Arends
- University of Edinburgh Division of Pathology, Cancer Research UK Edinburgh Cancer Centre, Institute of Genetics & Cancer, Edinburgh, Scotland, UK
| | - Geoffrey A Wood
- Department of Pathobiology, University of Guelph, Guelph, ON, Canada
| | - David J Adams
- Experimental Cancer Genetics, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SA, UK.
| | - Louise van der Weyden
- Experimental Cancer Genetics, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SA, UK
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Salavati M, Clark R, Becker D, Kühn C, Plastow G, Dupont S, Moreira GCM, Charlier C, Clark EL. Improving the annotation of the cattle genome by annotating transcription start sites in a diverse set of tissues and populations using Cap Analysis Gene Expression sequencing. G3 (BETHESDA, MD.) 2023; 13:jkad108. [PMID: 37216666 PMCID: PMC10411599 DOI: 10.1093/g3journal/jkad108] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 02/27/2023] [Accepted: 05/09/2023] [Indexed: 05/24/2023]
Abstract
Understanding the genomic control of tissue-specific gene expression and regulation can help to inform the application of genomic technologies in farm animal breeding programs. The fine mapping of promoters [transcription start sites (TSS)] and enhancers (divergent amplifying segments of the genome local to TSS) in different populations of cattle across a wide diversity of tissues provides information to locate and understand the genomic drivers of breed- and tissue-specific characteristics. To this aim, we used Cap Analysis Gene Expression (CAGE) sequencing, of 24 different tissues from 3 populations of cattle, to define TSS and their coexpressed short-range enhancers (<1 kb) in the ARS-UCD1.2_Btau5.0.1Y reference genome (1000bulls run9) and analyzed tissue and population specificity of expressed promoters. We identified 51,295 TSS and 2,328 TSS-Enhancer regions shared across the 3 populations (dairy, beef-dairy cross, and Canadian Kinsella composite cattle from 2 individuals, 1 of each sex, per population). Cross-species comparative analysis of CAGE data from 7 other species, including sheep, revealed a set of TSS and TSS-Enhancers that were specific to cattle. The CAGE data set will be combined with other transcriptomic information for the same tissues to create a new high-resolution map of transcript diversity across tissues and populations in cattle for the BovReg project. Here we provide the CAGE data set and annotation tracks for TSS and TSS-Enhancers in the cattle genome. This new annotation information will improve our understanding of the drivers of gene expression and regulation in cattle and help to inform the application of genomic technologies in breeding programs.
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Affiliation(s)
- Mazdak Salavati
- The Roslin Institute, University of Edinburgh, Edinburgh EH25 9RG, UK
| | - Richard Clark
- Edinburgh Clinical Research Facility, Genetics Core, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Doreen Becker
- Institute of Genome Biology, Research Institute for Farm Animal Biology (FBN), Dummerstorf 18196, Germany
| | - Christa Kühn
- Institute of Genome Biology, Research Institute for Farm Animal Biology (FBN), Dummerstorf 18196, Germany
- Faculty of Agricultural and Environmental Sciences, University Rostock, Rostock 18059, Germany
| | - Graham Plastow
- Department of Agricultural, Food and Nutritional Science, Livestock Gentec, University of Alberta, Edmonton T6G 2H1, Canada
| | - Sébastien Dupont
- Unit of Animal Genomics, GIGA Institute, University of Liège, Liège 4000, Belgium
| | | | - Carole Charlier
- Unit of Animal Genomics, GIGA Institute, University of Liège, Liège 4000, Belgium
- Faculty of Veterinary Medicine, University of Liège, Liège 4000, Belgium
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Badia-Bringué G, Canive M, Vázquez P, Garrido JM, Fernández A, Juste RA, Jiménez JA, González-Recio O, Alonso-Hearn M. Association between High Interferon-Gamma Production in Avian Tuberculin-Stimulated Blood from Mycobacterium avium subsp. paratuberculosis-Infected Cattle and Candidate Genes Implicated in Necroptosis. Microorganisms 2023; 11:1817. [PMID: 37512987 PMCID: PMC10384200 DOI: 10.3390/microorganisms11071817] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Revised: 07/07/2023] [Accepted: 07/13/2023] [Indexed: 07/30/2023] Open
Abstract
The mechanisms underlying host resistance to Mycobacterium avium subsp. paratuberculosis (MAP) infection are largely unknown. In the current study, we hypothesize that cows with an ability to produce higher levels of interferon-gamma (IFNɣ) might control MAP infection more successfully. To test this hypothesis, IFNɣ production was measured using a specific IFNɣ ELISA kit in avian purified protein derivative (aPPD)-stimulated blood samples collected from 152 Holstein cattle. DNA isolated from peripheral blood samples of the animals included in the study was genotyped with the EuroG Medium-Density Bead Chip, and the genotypes were imputed to whole-genome sequencing. A genome-wide association analysis (GWAS) revealed that high levels of IFNɣ in response to the aPPD were associated with a specific genetic profile (heritability = 0.64) and allowed the identification of 71 SNPs, 40 quantitative trait loci (QTL), and 104 candidate genes. A functional analysis using the 104 candidate genes revealed a significant enrichment of genes involved in the innate immune response and, more specifically, in necroptosis. Taken together, our results define a heritable and distinct immunogenetic profile associated with the production of high IFNɣ levels and with the capacity of the host to lyse MAP-infected macrophages by necroptosis.
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Affiliation(s)
- Gerard Badia-Bringué
- Department of Animal Health, NEIKER-Basque Institute for Agricultural Research and Development, Basque Research and Technology Alliance (BRTA), 48160 Derio, Spain
- Doctoral Program in Molecular Biology and Biomedicine, Universidad del País Vasco/Euskal Herriko Unibertsitatea (UPV/EHU), 48940 Leioa, Spain
| | - María Canive
- Department of Animal Health, NEIKER-Basque Institute for Agricultural Research and Development, Basque Research and Technology Alliance (BRTA), 48160 Derio, Spain
| | - Patricia Vázquez
- Department of Animal Health, NEIKER-Basque Institute for Agricultural Research and Development, Basque Research and Technology Alliance (BRTA), 48160 Derio, Spain
| | - Joseba M Garrido
- Department of Animal Health, NEIKER-Basque Institute for Agricultural Research and Development, Basque Research and Technology Alliance (BRTA), 48160 Derio, Spain
| | - Almudena Fernández
- Departamento de Mejora Genética Animal, Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA), Consejo Superior de Investigaciones Científicas, 28040 Madrid, Spain
| | - Ramón A Juste
- Department of Animal Health, NEIKER-Basque Institute for Agricultural Research and Development, Basque Research and Technology Alliance (BRTA), 48160 Derio, Spain
| | | | - Oscar González-Recio
- Departamento de Mejora Genética Animal, Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA), Consejo Superior de Investigaciones Científicas, 28040 Madrid, Spain
| | - Marta Alonso-Hearn
- Department of Animal Health, NEIKER-Basque Institute for Agricultural Research and Development, Basque Research and Technology Alliance (BRTA), 48160 Derio, Spain
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González-Recio O, López-Catalina A, Peiró-Pastor R, Nieto-Valle A, Castro M, Fernández A. Evaluating the potential of (epi)genotype-by-low pass nanopore sequencing in dairy cattle: a study on direct genomic value and methylation analysis. J Anim Sci Biotechnol 2023; 14:98. [PMID: 37434255 PMCID: PMC10337168 DOI: 10.1186/s40104-023-00896-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Accepted: 05/17/2023] [Indexed: 07/13/2023] Open
Abstract
BACKGROUND Genotype-by-sequencing has been proposed as an alternative to SNP genotyping arrays in genomic selection to obtain a high density of markers along the genome. It requires a low sequencing depth to be cost effective, which may increase the error at the genotype assigment. Third generation nanopore sequencing technology offers low cost sequencing and the possibility to detect genome methylation, which provides added value to genotype-by-sequencing. The aim of this study was to evaluate the performance of genotype-by-low pass nanopore sequencing for estimating the direct genomic value in dairy cattle, and the possibility to obtain methylation marks simultaneously. RESULTS Latest nanopore chemistry (LSK14 and Q20) achieved a modal base calling accuracy of 99.55%, whereas previous kit (LSK109) achieved slightly lower accuracy (99.1%). The direct genomic value accuracy from genotype-by-low pass sequencing ranged between 0.79 and 0.99, depending on the trait (milk, fat or protein yield), with a sequencing depth as low as 2 × and using the latest chemistry (LSK114). Lower sequencing depth led to biased estimates, yet with high rank correlations. The LSK109 and Q20 achieved lower accuracies (0.57-0.93). More than one million high reliable methylated sites were obtained, even at low sequencing depth, located mainly in distal intergenic (87%) and promoter (5%) regions. CONCLUSIONS This study showed that the latest nanopore technology in useful in a LowPass sequencing framework to estimate direct genomic values with high reliability. It may provide advantages in populations with no available SNP chip, or when a large density of markers with a wide range of allele frequencies is needed. In addition, low pass sequencing provided nucleotide methylation status of > 1 million nucleotides at ≥ 10 × , which is an added value for epigenetic studies.
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Affiliation(s)
- Oscar González-Recio
- Dpt. Mejora Genética Animal, INIA-CSIC, Ctra La Coruña Km 7.5, 28040, Madrid, Spain.
| | | | - Ramón Peiró-Pastor
- Dpt. Mejora Genética Animal, INIA-CSIC, Ctra La Coruña Km 7.5, 28040, Madrid, Spain
| | - Alicia Nieto-Valle
- ETSIAAB, Universidad Politécnica de Madrid. Ciudad Universitaria S/N, 28040, Madrid, Spain
| | - Monica Castro
- Dpt. Mejora Genética Animal, INIA-CSIC, Ctra La Coruña Km 7.5, 28040, Madrid, Spain
| | - Almudena Fernández
- Dpt. Mejora Genética Animal, INIA-CSIC, Ctra La Coruña Km 7.5, 28040, Madrid, Spain
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Tan WLA, Neto LRP, Reverter A, McGowan M, Fortes MRS. Sequence level genome-wide associations for bull production and fertility traits in tropically adapted bulls. BMC Genomics 2023; 24:365. [PMID: 37386436 DOI: 10.1186/s12864-023-09475-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Accepted: 06/21/2023] [Indexed: 07/01/2023] Open
Abstract
BACKGROUND The genetics of male fertility is complex and not fully understood. Male subfertility can adversely affect the economics of livestock production. For example, inadvertently mating bulls with poor fertility can result in reduced annual liveweight production and suboptimal husbandry management. Fertility traits, such as scrotal circumference and semen quality are commonly used to select bulls before mating and can be targeted in genomic studies. In this study, we conducted genome-wide association analyses using sequence-level data targeting seven bull production and fertility traits measured in a multi-breed population of 6,422 tropically adapted bulls. The beef bull production and fertility traits included body weight (Weight), body condition score (CS), scrotal circumference (SC), sheath score (Sheath), percentage of normal spermatozoa (PNS), percentage of spermatozoa with mid-piece abnormalities (MP) and percentage of spermatozoa with proximal droplets (PD). RESULTS After quality control, 13,398,171 polymorphisms were tested for their associations with each trait in a mixed-model approach, fitting a multi-breed genomic relationship matrix. A Bonferroni genome-wide significance threshold of 5 × 10- 8 was imposed. This effort led to identifying genetic variants and candidate genes underpinning bull fertility and production traits. Genetic variants in Bos taurus autosome (BTA) 5 were associated with SC, Sheath, PNS, PD and MP. Whereas chromosome X was significant for SC, PNS, and PD. The traits we studied are highly polygenic and had significant results across the genome (BTA 1, 2, 4, 6, 7, 8, 11, 12, 14, 16, 18, 19, 23, 28, and 29). We also highlighted potential high-impact variants and candidate genes associated with Scrotal Circumference (SC) and Sheath Score (Sheath), which warrants further investigation in future studies. CONCLUSION The work presented here is a step closer to identifying molecular mechanisms that underpin bull fertility and production. Our work also emphasises the importance of including the X chromosome in genomic analyses. Future research aims to investigate potential causative variants and genes in downstream analyses.
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Affiliation(s)
- Wei Liang Andre Tan
- School of Chemistry and Molecular Biosciences, The University of Queensland, Chemistry Bld, 68 Cooper Rd, Brisbane City, QLD, 4072, Australia.
| | | | - Antonio Reverter
- CSIRO Agriculture and Food, 306 Carmody Road, St Lucia, QLD, 4067, Australia
| | - Michael McGowan
- School of Veterinary Science, The University of Queensland, Gatton, QLD, 4343, Australia
| | - Marina Rufino Salinas Fortes
- School of Chemistry and Molecular Biosciences, The University of Queensland, Chemistry Bld, 68 Cooper Rd, Brisbane City, QLD, 4072, Australia
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Sanchez MP, Escouflaire C, Baur A, Bottin F, Hozé C, Boussaha M, Fritz S, Capitan A, Boichard D. X-linked genes influence various complex traits in dairy cattle. BMC Genomics 2023; 24:338. [PMID: 37337145 DOI: 10.1186/s12864-023-09438-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Accepted: 06/08/2023] [Indexed: 06/21/2023] Open
Abstract
BACKGROUND The search for quantitative trait loci (QTL) affecting traits of interest in mammals is frequently limited to autosomes, with the X chromosome excluded because of its hemizygosity in males. This study aimed to assess the importance of the X chromosome in the genetic determinism of 11 complex traits related to milk production, milk composition, mastitis resistance, fertility, and stature in 236,496 cows from three major French dairy breeds (Holstein, Montbéliarde, and Normande) and three breeds of regional importance (Abondance, Tarentaise, and Vosgienne). RESULTS Estimates of the proportions of heritability due to autosomes and X chromosome (h²X) were consistent among breeds. On average over the 11 traits, h²X=0.008 and the X chromosome explained ~ 3.5% of total genetic variance. GWAS was performed within-breed at the sequence level (~ 200,000 genetic variants) and then combined in a meta-analysis. QTL were identified for most breeds and traits analyzed, with the exception of Tarentaise and Vosgienne and two fertility traits. Overall, 3, 74, 59, and 71 QTL were identified in Abondance, Montbéliarde, Normande, and Holstein, respectively, and most were associated with the most-heritable traits (milk traits and stature). The meta-analyses, which assessed a total of 157 QTL for the different traits, highlighted new QTL and refined the positions of some QTL found in the within-breed analyses. Altogether, our analyses identified a number of functional candidate genes, with the most notable being GPC3, MBNL3, HS6ST2, and DMD for dairy traits; TMEM164, ACSL4, ENOX2, HTR2C, AMOT, and IRAK1 for udder health; MAMLD1 and COL4A6 for fertility; and NRK, ESX1, GPR50, GPC3, and GPC4 for stature. CONCLUSIONS This study demonstrates the importance of the X chromosome in the genetic determinism of complex traits in dairy cattle and highlights new functional candidate genes and variants for these traits. These results could potentially be extended to other species as many X-linked genes are shared among mammals.
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Affiliation(s)
- Marie-Pierre Sanchez
- Université Paris-Saclay, INRAE, AgroParisTech, GABI, Jouy-en-Josas, 78350, France.
| | | | | | - Fiona Bottin
- Université Paris-Saclay, INRAE, AgroParisTech, GABI, Jouy-en-Josas, 78350, France
| | | | - Mekki Boussaha
- Université Paris-Saclay, INRAE, AgroParisTech, GABI, Jouy-en-Josas, 78350, France
| | | | - Aurélien Capitan
- Université Paris-Saclay, INRAE, AgroParisTech, GABI, Jouy-en-Josas, 78350, France
| | - Didier Boichard
- Université Paris-Saclay, INRAE, AgroParisTech, GABI, Jouy-en-Josas, 78350, France
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Boussaha M, Boulling A, Wolgust V, Bourgeois-Brunel L, Michot P, Grohs C, Gaiani N, Grivaud PY, Leclerc H, Danchin-Burge C, Vilotte M, Rivière J, Boichard D, Gourreau JM, Capitan A. Integrin alpha 6 homozygous splice-site mutation causes a new form of junctional epidermolysis bullosa in Charolais cattle. Genet Sel Evol 2023; 55:40. [PMID: 37308849 DOI: 10.1186/s12711-023-00814-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2022] [Accepted: 05/26/2023] [Indexed: 06/14/2023] Open
Abstract
BACKGROUND Inherited epidermolysis bullosa (EB) is a group of painful and life-threatening genetic disorders that are characterized by mechanically induced blistering of the skin and mucous membranes. Congenital skin fragility resembling EB was recently reported in three Charolais calves born in two distinct herds from unaffected parents. Phenotypic and genetic analyses were carried out to describe this condition and its molecular etiology. RESULTS Genealogical, pathological and histological investigations confirmed the diagnosis of recessive EB. However, the affected calves showed milder clinical signs compared to another form of EB, which was previously reported in the same breed and is caused by a homozygous deletion of the ITGB4 gene. Homozygosity mapping followed by analysis of the whole-genome sequences of two cases and 5031 control individuals enabled us to prioritize a splice donor site of ITGA6 (c.2160 + 1G > T; Chr2 g.24112740C > A) as the most compelling candidate variant. This substitution showed a perfect genotype-phenotype correlation in the two affected pedigrees and was found to segregate only in Charolais, and at a very low frequency (f = 1.6 × 10-4) after genotyping 186,154 animals from 15 breeds. Finally, RT-PCR analyses revealed increased retention of introns 14 and 15 of the ITGA6 gene in a heterozygous mutant cow compared with a matched control. The mutant mRNA is predicted to cause a frameshift (ITGA6 p.I657Mfs1) that affects the assembly of the integrin α6β4 dimer and its correct anchoring to the cell membrane. This dimer is a key component of the hemidesmosome anchoring complex, which ensures the attachment of basal epithelial cells to the basal membrane. Based on these elements, we arrived at a diagnosis of junctional EB. CONCLUSIONS We report a rare example of partial phenocopies observed in the same breed and due to mutations that affect two members of the same protein dimer, and provide the first evidence of an ITGA6 mutation that causes EB in livestock species.
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Affiliation(s)
- Mekki Boussaha
- Université Paris-Saclay, INRAE, AgroParisTech, GABI, 78350, Jouy-en-Josas, France
| | - Arnaud Boulling
- Université Paris-Saclay, INRAE, AgroParisTech, GABI, 78350, Jouy-en-Josas, France
| | - Valérie Wolgust
- Unité de Pathologie du Bétail, Ecole Nationale Vétérinaire d'Alfort, 94700, Maisons-Alfort, France
| | | | - Pauline Michot
- Université Paris-Saclay, INRAE, AgroParisTech, GABI, 78350, Jouy-en-Josas, France
- Eliance, 75012, Paris, France
- Herd Book Charolais, 58470, Magny-Cours, France
| | - Cécile Grohs
- Université Paris-Saclay, INRAE, AgroParisTech, GABI, 78350, Jouy-en-Josas, France
| | - Nicolas Gaiani
- Université Paris-Saclay, INRAE, AgroParisTech, GABI, 78350, Jouy-en-Josas, France
| | - Pierre-Yves Grivaud
- Cabinet Vétérinaire des Monts du Charolais, 71220, Saint Bonnet de Joux, France
| | - Hélène Leclerc
- Université Paris-Saclay, INRAE, AgroParisTech, GABI, 78350, Jouy-en-Josas, France
- Eliance, 75012, Paris, France
| | | | - Marthe Vilotte
- Université Paris-Saclay, INRAE, AgroParisTech, GABI, 78350, Jouy-en-Josas, France
| | - Julie Rivière
- Université Paris-Saclay, INRAE, AgroParisTech, GABI, 78350, Jouy-en-Josas, France
- Université Paris-Saclay, INRAE, AgroParisTech, MICALIS, 78350, Jouy-en-Josas, France
| | - Didier Boichard
- Université Paris-Saclay, INRAE, AgroParisTech, GABI, 78350, Jouy-en-Josas, France
| | - Jean-Marie Gourreau
- Unité de Pathologie du Bétail, Ecole Nationale Vétérinaire d'Alfort, 94700, Maisons-Alfort, France
| | - Aurélien Capitan
- Université Paris-Saclay, INRAE, AgroParisTech, GABI, 78350, Jouy-en-Josas, France.
- Eliance, 75012, Paris, France.
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Gonzalez-Recio O, Scrobota N, López-Paredes J, Saborío-Montero A, Fernández A, López de Maturana E, Villanueva B, Goiri I, Atxaerandio R, García-Rodríguez A. Review: Diving into the cow hologenome to reduce methane emissions and increase sustainability. Animal 2023; 17 Suppl 2:100780. [PMID: 37032282 DOI: 10.1016/j.animal.2023.100780] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2022] [Revised: 03/06/2023] [Accepted: 03/09/2023] [Indexed: 03/18/2023] Open
Abstract
Interest on methane emissions from livestock has increased in later years as it is an anthropogenic greenhouse gas with an important warming potential. The rumen microbiota has a large influence on the production of enteric methane. Animals harbour a second genome consisting of microbes, collectively referred to as the "microbiome". The rumen microbial community plays an important role in feed digestion, feed efficiency, methane emission and health status. This review recaps the current knowledge on the genetic control that the cow exerts on the rumen microbiota composition. Heritability estimates for the rumen microbiota composition range between 0.05 and 0.40 in the literature, depending on the taxonomical group or microbial gene function. Variables depicting microbial diversity or aggregating microbial information are also heritable within the same range. This study includes a genome-wide association analysis on the microbiota composition, considering the relative abundance of some microbial taxa previously associated to enteric methane in dairy cattle (Archaea, Dialister, Entodinium, Eukaryota, Lentisphaerae, Methanobrevibacter, Neocallimastix, Prevotella and Stentor). Host genomic regions associated with the relative abundance of these microbial taxa were identified after Benjamini-Hoschberg correction (Padj < 0.05). An in-silico functional analysis using FUMA and DAVID online tools revealed that these gene sets were enriched in tissues like brain cortex, brain amigdala, pituitary, salivary glands and other parts of the digestive system, and are related to appetite, satiety and digestion. These results allow us to have greater knowledge about the composition and function of the rumen microbiome in cattle. The state-of-the art strategies to include methane traits in the selection indices in dairy cattle populations is reviewed. Several strategies to include methane traits in the selection indices have been studied worldwide, using bioeconomical models or economic functions under theoretical frameworks. However, their incorporation in the breeding programmes is still scarce. Some potential strategies to include methane traits in the selection indices of dairy cattle population are presented. Future selection indices will need to increase the weight of traits related to methane emissions and sustainability. This review will serve as a compendium of the current state of the art in genetic strategies to reduce methane emissions in dairy cattle.
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Affiliation(s)
| | - Natalia Scrobota
- Departamento de Mejora Genética Animal, INIA-CSIC, 28040 Madrid, Spain; Universidad San Pablo-CEU, CEU Universities, Madrid, Spain
| | - Javier López-Paredes
- Confederación de Asociaciones de Frisona Española (CONAFE), Ctra. de Andalucía km 23600 Valdemoro, 28340 Madrid, Spain
| | - Alejandro Saborío-Montero
- Escuela de Zootecnia y Centro de Investigación en Nutrición Animal, Universidad de Costa Rica, 11501 San José, Costa Rica; Posgrado Regional en Ciencias Veterinarias Tropicales, Universidad Nacional de Costa Rica, 40104 Heredia, Costa Rica
| | | | - Evangelina López de Maturana
- Universidad San Pablo-CEU, CEU Universities, Madrid, Spain; Institute of Applied Molecular Medicine (IMMA), Department of Basic Medical Sciences. Facultad de Medicina. Universidad San Pablo-CEU, CEU Universities, ARADyAL, Madrid, Spain; Genetic and Molecular Epidemiology Group, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
| | | | - Idoia Goiri
- NEIKER - Instituto Vasco de Investigación y Desarrollo Agrario, Basque Research and Technology Alliance (BRTA), Campus Agroalimentario de Arkaute s/n, 01192 Arkaute, Spain
| | - Raquel Atxaerandio
- NEIKER - Instituto Vasco de Investigación y Desarrollo Agrario, Basque Research and Technology Alliance (BRTA), Campus Agroalimentario de Arkaute s/n, 01192 Arkaute, Spain
| | - Aser García-Rodríguez
- NEIKER - Instituto Vasco de Investigación y Desarrollo Agrario, Basque Research and Technology Alliance (BRTA), Campus Agroalimentario de Arkaute s/n, 01192 Arkaute, Spain
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Zhao C, Wang D, Teng J, Yang C, Zhang X, Wei X, Zhang Q. Breed identification using breed-informative SNPs and machine learning based on whole genome sequence data and SNP chip data. J Anim Sci Biotechnol 2023; 14:85. [PMID: 37259083 DOI: 10.1186/s40104-023-00880-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Accepted: 04/05/2023] [Indexed: 06/02/2023] Open
Abstract
BACKGROUND Breed identification is useful in a variety of biological contexts. Breed identification usually involves two stages, i.e., detection of breed-informative SNPs and breed assignment. For both stages, there are several methods proposed. However, what is the optimal combination of these methods remain unclear. In this study, using the whole genome sequence data available for 13 cattle breeds from Run 8 of the 1,000 Bull Genomes Project, we compared the combinations of three methods (Delta, FST, and In) for breed-informative SNP detection and five machine learning methods (KNN, SVM, RF, NB, and ANN) for breed assignment with respect to different reference population sizes and difference numbers of most breed-informative SNPs. In addition, we evaluated the accuracy of breed identification using SNP chip data of different densities. RESULTS We found that all combinations performed quite well with identification accuracies over 95% in all scenarios. However, there was no combination which performed the best and robust across all scenarios. We proposed to integrate the three breed-informative detection methods, named DFI, and integrate the three machine learning methods, KNN, SVM, and RF, named KSR. We found that the combination of these two integrated methods outperformed the other combinations with accuracies over 99% in most cases and was very robust in all scenarios. The accuracies from using SNP chip data were only slightly lower than that from using sequence data in most cases. CONCLUSIONS The current study showed that the combination of DFI and KSR was the optimal strategy. Using sequence data resulted in higher accuracies than using chip data in most cases. However, the differences were generally small. In view of the cost of genotyping, using chip data is also a good option for breed identification.
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Affiliation(s)
- Changheng Zhao
- Shandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention, College of Animal Science and Veterinary Medicine, Shandong Agricultural University, Tai'an, 271018, China
| | - Dan Wang
- Shandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention, College of Animal Science and Veterinary Medicine, Shandong Agricultural University, Tai'an, 271018, China
| | - Jun Teng
- Shandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention, College of Animal Science and Veterinary Medicine, Shandong Agricultural University, Tai'an, 271018, China
| | - Cheng Yang
- Shandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention, College of Animal Science and Veterinary Medicine, Shandong Agricultural University, Tai'an, 271018, China
| | - Xinyi Zhang
- Shandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention, College of Animal Science and Veterinary Medicine, Shandong Agricultural University, Tai'an, 271018, China
| | - Xianming Wei
- Shandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention, College of Animal Science and Veterinary Medicine, Shandong Agricultural University, Tai'an, 271018, China
| | - Qin Zhang
- Shandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention, College of Animal Science and Veterinary Medicine, Shandong Agricultural University, Tai'an, 271018, China.
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