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Tan WLA, Hudson NJ, Porto Neto LR, Reverter A, Afonso J, Fortes MRS. An association weight matrix identified biological pathways associated with bull fertility traits in a multi-breed population. Anim Genet 2024; 55:495-510. [PMID: 38692842 DOI: 10.1111/age.13431] [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: 11/16/2023] [Revised: 02/26/2024] [Accepted: 04/01/2024] [Indexed: 05/03/2024]
Abstract
Using seven indicator traits, we investigated the genetic basis of bull fertility and predicted gene interactions from SNP associations. We used percent normal sperm as the key phenotype for the association weight matrix-partial correlation information theory (AWM-PCIT) approach. Beyond a simple list of candidate genes, AWM-PCIT predicts significant gene interactions and associations for the selected traits. These interactions formed a network of 537 genes: 38 genes were transcription cofactors, and 41 genes were transcription factors. The network displayed two distinct clusters, one with 294 genes and another with 243 genes. The network is enriched in fertility-associated pathways: steroid biosynthesis, p53 signalling, and the pentose phosphate pathway. Enrichment analysis also highlighted gene ontology terms associated with 'regulation of neurotransmitter secretion' and 'chromatin formation'. Our network recapitulates some genes previously implicated in another network built with lower-density genotypes. Sequence-level data also highlights additional candidate genes relevant to bull fertility, such as FOXO4, FOXP3, GATA1, CYP27B1, and EBP. A trio of regulatory genes-KDM5C, LRRK2, and PME-was deemed core to the network because of their overarching connections. This trio probably influences bull fertility through their interaction with genes, both known and unknown as to their role in male fertility. Future studies may target the trio and their target genes to enrich our understanding of male fertility further.
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Affiliation(s)
- Wei Liang Andre Tan
- School of Chemistry and Molecular Bioscience, The University of Queensland, St Lucia, Queensland, Australia
| | - Nicholas James Hudson
- School of Agriculture and Food Sustainability, The University of Queensland, Gatton, Queensland, Australia
| | | | | | - Juliana Afonso
- School of Chemistry and Molecular Bioscience, The University of Queensland, St Lucia, Queensland, Australia
- Empresa Brasileira de Pesquisa Agropecuária, Pecuária Sudeste, São Carlos, São Paulo, Brazil
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2
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Cai Z, Iso-Touru T, Sanchez MP, Kadri N, Bouwman AC, Chitneedi PK, MacLeod IM, Vander Jagt CJ, Chamberlain AJ, Gredler-Grandl B, Spengeler M, Lund MS, Boichard D, Kühn C, Pausch H, Vilkki J, Sahana G. Meta-analysis of six dairy cattle breeds reveals biologically relevant candidate genes for mastitis resistance. Genet Sel Evol 2024; 56:54. [PMID: 39009986 PMCID: PMC11247842 DOI: 10.1186/s12711-024-00920-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2023] [Accepted: 06/26/2024] [Indexed: 07/17/2024] Open
Abstract
BACKGROUND Mastitis is a disease that incurs significant costs in the dairy industry. A promising approach to mitigate its negative effects is to genetically improve the resistance of dairy cattle to mastitis. A meta-analysis of genome-wide association studies (GWAS) across multiple breeds for clinical mastitis (CM) and its indicator trait, somatic cell score (SCS), is a powerful method to identify functional genetic variants that impact mastitis resistance. RESULTS We conducted meta-analyses of eight and fourteen GWAS on CM and SCS, respectively, using 30,689 and 119,438 animals from six dairy cattle breeds. Methods for the meta-analyses were selected to properly account for the multi-breed structure of the GWAS data. Our study revealed 58 lead markers that were associated with mastitis incidence, including 16 loci that did not overlap with previously identified quantitative trait loci (QTL), as curated at the Animal QTLdb. Post-GWAS analysis techniques such as gene-based analysis and genomic feature enrichment analysis enabled prioritization of 31 candidate genes and 14 credible candidate causal variants that affect mastitis. CONCLUSIONS Our list of candidate genes can help to elucidate the genetic architecture underlying mastitis resistance and provide better tools for the prevention or treatment of mastitis, ultimately contributing to more sustainable animal production.
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Affiliation(s)
- Zexi Cai
- Center for Quantitative Genetics and Genomics, Aarhus University, 8000, Aarhus, Denmark.
| | - Terhi Iso-Touru
- Natural Resources Institute Finland (Luke), 31600, Jokioinen, Finland
| | - Marie-Pierre Sanchez
- Université Paris-Saclay, INRAE, AgroParisTech, GABI, 78350, Jouy-en-Josas, France
| | - Naveen Kadri
- Animal Genomics, ETH Zurich, 8092, Zurich, Switzerland
| | - Aniek C Bouwman
- Wageningen University and Research, Animal Breeding and Genomics, P.O. Box 338, 6700, AH, Wageningen, The Netherlands
| | - Praveen Krishna Chitneedi
- Institute of Genome Biology, Research Institute for Farm Animal Biology (FBN), 18196, Dummerstorf, Germany
| | - Iona M MacLeod
- Agriculture Victoria, AgriBio, Centre for AgriBiosciences, Bundoora, VIC, Australia
- School of Applied Systems Biology, La Trobe University, Bundoora, VIC, 3083, Australia
| | | | - Amanda J Chamberlain
- Agriculture Victoria, AgriBio, Centre for AgriBiosciences, Bundoora, VIC, Australia
| | - Birgit Gredler-Grandl
- Wageningen University and Research, Animal Breeding and Genomics, P.O. Box 338, 6700, AH, Wageningen, The Netherlands
| | | | - Mogens Sandø Lund
- Center for Quantitative Genetics and Genomics, Aarhus University, 8000, Aarhus, Denmark
| | - Didier Boichard
- Université Paris-Saclay, INRAE, AgroParisTech, GABI, 78350, Jouy-en-Josas, France
| | - Christa Kühn
- Institute of Genome Biology, Research Institute for Farm Animal Biology (FBN), 18196, Dummerstorf, Germany
- Agricultural and Environmental Faculty, University Rostock, 18059, Rostock, Germany
| | - Hubert Pausch
- Animal Genomics, ETH Zurich, 8092, Zurich, Switzerland
| | - Johanna Vilkki
- Natural Resources Institute Finland (Luke), 31600, Jokioinen, Finland
| | - Goutam Sahana
- Center for Quantitative Genetics and Genomics, Aarhus University, 8000, Aarhus, Denmark
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3
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Fernandes AC, Reverter A, Keogh K, Alexandre PA, Afonso J, Palhares JCP, Cardoso TF, Malheiros JM, Bruscadin JJ, de Oliveira PSN, Mourão GB, de Almeida Regitano LC, Coutinho LL. Transcriptional response to an alternative diet on liver, muscle, and rumen of beef cattle. Sci Rep 2024; 14:13682. [PMID: 38871745 PMCID: PMC11176196 DOI: 10.1038/s41598-024-63619-2] [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: 12/05/2023] [Accepted: 05/30/2024] [Indexed: 06/15/2024] Open
Abstract
Feed cost represents a major economic determinant within cattle production, amounting to an estimated 75% of the total variable costs. Consequently, comprehensive approaches such as optimizing feed utilization through alternative feed sources, alongside the selection of feed-efficient animals, are of great significance. Here, we investigate the effect of two diets, traditional corn-grain fed and alternative by-product based, on 14 phenotypes related to feed, methane emission and production efficiency and on multi-tissue transcriptomics data from liver, muscle, and rumen wall, derived from 52 Nellore bulls, 26 on each diet. To this end, diets were contrasted at the level of phenotype, gene expression, and gene-phenotype network connectivity. As regards the phenotypic level, at a P value < 0.05, significant differences were found in favour of the alternative diet for average daily weight gain at finishing, dry matter intake at finishing, methane emission, carcass yield and subcutaneous fat thickness at the rib-eye muscle area. In terms of the transcriptional level of the 14,776 genes expressed across the examined tissues, we found 487, 484, and 499 genes differentially expressed due to diet in liver, muscle, and rumen, respectively (P value < 0.01). To explore differentially connected phenotypes across both diet-based networks, we focused on the phenotypes with the largest change in average number of connections within diets and tissues, namely methane emission and carcass yield, highlighting, in particular, gene expression changes involving SREBF2, and revealing the largest differential connectivity in rumen and muscle, respectively. Similarly, from examination of differentially connected genes across diets, the top-ranked most differentially connected regulators within each tissue were MEOX1, PTTG1, and BASP1 in liver, muscle, and rumen, respectively. Changes in gene co-expression patterns suggest activation or suppression of specific biological processes and pathways in response to dietary interventions, consequently impacting the phenotype. The identification of genes that respond differently to diets and their associated phenotypic effects serves as a crucial stepping stone for further investigations, aiming to build upon our discoveries. Ultimately, such advancements hold the promise of improving animal welfare, productivity, and sustainability in livestock farming.
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Affiliation(s)
- Anna Carolina Fernandes
- Department of Animal Science, Luiz de Queiroz College of Agriculture, University of São Paulo (ESALQ-USP), Piracicaba, São Paulo, Brazil
- CSIRO Agriculture & Food, Queensland Bioscience Precinct, 306 Carmody Rd., St. Lucia, Brisbane, QLD, 4067, Australia
| | - Antonio Reverter
- CSIRO Agriculture & Food, Queensland Bioscience Precinct, 306 Carmody Rd., St. Lucia, Brisbane, QLD, 4067, Australia
| | - Kate Keogh
- CSIRO Agriculture & Food, Queensland Bioscience Precinct, 306 Carmody Rd., St. Lucia, Brisbane, QLD, 4067, Australia
- Animal and Bioscience Research Department, Teagasc, Animal & Grassland Research and Innovation Centre, Grange, Dunsany, Co. Meath, Ireland
| | - Pâmela Almeida Alexandre
- CSIRO Agriculture & Food, Queensland Bioscience Precinct, 306 Carmody Rd., St. Lucia, Brisbane, QLD, 4067, Australia
| | - Juliana Afonso
- Brazilian Agricultural Research Corporation, Embrapa Pecuária Sudeste, São Carlos, São Paulo, Brazil
| | | | - Tainã Figueiredo Cardoso
- Brazilian Agricultural Research Corporation, Embrapa Pecuária Sudeste, São Carlos, São Paulo, Brazil
| | - Jessica Moraes Malheiros
- Brazilian Agricultural Research Corporation, Embrapa Pecuária Sudeste, São Carlos, São Paulo, Brazil
- Beef Cattle Research Center, Animal Science Institute (IZ), Sertãozinho, São Paulo, Brazil
| | - Jennifer Jessica Bruscadin
- Center of Biological and Health Sciences, Federal University of São Carlos, São Carlos, São Paulo, Brazil
| | | | - Gerson Barreto Mourão
- Department of Animal Science, Luiz de Queiroz College of Agriculture, University of São Paulo (ESALQ-USP), Piracicaba, São Paulo, Brazil
| | | | - Luiz Lehmann Coutinho
- Department of Animal Science, Luiz de Queiroz College of Agriculture, University of São Paulo (ESALQ-USP), Piracicaba, São Paulo, Brazil.
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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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Fonseca PAS, Suárez-Vega A, Arranz JJ, Gutiérrez-Gil B. Integration of selective sweeps across the sheep genome: understanding the relationship between production and adaptation traits. Genet Sel Evol 2024; 56:40. [PMID: 38773423 PMCID: PMC11106937 DOI: 10.1186/s12711-024-00910-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2023] [Accepted: 05/07/2024] [Indexed: 05/23/2024] Open
Abstract
BACKGROUND Livestock populations are under constant selective pressure for higher productivity levels for different selective purposes. This pressure results in the selection of animals with unique adaptive and production traits. The study of genomic regions associated with these unique characteristics has the potential to improve biological knowledge regarding the adaptive process and how it is connected to production levels and resilience, which is the ability of an animal to adapt to stress or an imbalance in homeostasis. Sheep is a species that has been subjected to several natural and artificial selective pressures during its history, resulting in a highly specialized species for production and adaptation to challenging environments. Here, the data from multiple studies that aim at mapping selective sweeps across the sheep genome associated with production and adaptation traits were integrated to identify confirmed selective sweeps (CSS). RESULTS In total, 37 studies were used to identify 518 CSS across the sheep genome, which were classified as production (147 prodCSS) and adaptation (219 adapCSS) CSS based on the frequency of each type of associated study. The genes within the CSS were associated with relevant biological processes for adaptation and production. For example, for adapCSS, the associated genes were related to the control of seasonality, circadian rhythm, and thermoregulation. On the other hand, genes associated with prodCSS were related to the control of feeding behaviour, reproduction, and cellular differentiation. In addition, genes harbouring both prodCSS and adapCSS showed an interesting association with lipid metabolism, suggesting a potential role of this process in the regulation of pleiotropic effects between these classes of traits. CONCLUSIONS The findings of this study contribute to a deeper understanding of the genetic link between productivity and adaptability in sheep breeds. This information may provide insights into the genetic mechanisms that underlie undesirable genetic correlations between these two groups of traits and pave the way for a better understanding of resilience as a positive ability to respond to environmental stressors, where the negative effects on production level are minimized.
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Affiliation(s)
- Pablo A S Fonseca
- Departamento de Producción Animal, Facultad de Veterinaria, Universidad de León, Campus de Vegazana S/N, 24071, León, Spain
| | - Aroa Suárez-Vega
- Departamento de Producción Animal, Facultad de Veterinaria, Universidad de León, Campus de Vegazana S/N, 24071, León, Spain
| | - Juan J Arranz
- Departamento de Producción Animal, Facultad de Veterinaria, Universidad de León, Campus de Vegazana S/N, 24071, León, Spain
| | - Beatriz Gutiérrez-Gil
- Departamento de Producción Animal, Facultad de Veterinaria, Universidad de León, Campus de Vegazana S/N, 24071, León, Spain.
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de Oliveira LF, Veroneze R, Sousa KRS, Mulim HA, Araujo AC, Huang Y, Johnson JS, Brito LF. Genomic regions, candidate genes, and pleiotropic variants associated with physiological and anatomical indicators of heat stress response in lactating sows. BMC Genomics 2024; 25:467. [PMID: 38741036 DOI: 10.1186/s12864-024-10365-4] [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: 02/12/2024] [Accepted: 04/29/2024] [Indexed: 05/16/2024] Open
Abstract
BACKGROUND Heat stress (HS) poses significant threats to the sustainability of livestock production. Genetically improving heat tolerance could enhance animal welfare and minimize production losses during HS events. Measuring phenotypic indicators of HS response and understanding their genetic background are crucial steps to optimize breeding schemes for improved climatic resilience. The identification of genomic regions and candidate genes influencing the traits of interest, including variants with pleiotropic effects, enables the refinement of genotyping panels used to perform genomic prediction of breeding values and contributes to unraveling the biological mechanisms influencing heat stress response. Therefore, the main objectives of this study were to identify genomic regions, candidate genes, and potential pleiotropic variants significantly associated with indicators of HS response in lactating sows using imputed whole-genome sequence (WGS) data. Phenotypic records for 18 traits and genomic information from 1,645 lactating sows were available for the study. The genotypes from the PorcineSNP50K panel containing 50,703 single nucleotide polymorphisms (SNPs) were imputed to WGS and after quality control, 1,622 animals and 7,065,922 SNPs were included in the analyses. RESULTS A total of 1,388 unique SNPs located on sixteen chromosomes were found to be associated with 11 traits. Twenty gene ontology terms and 11 biological pathways were shown to be associated with variability in ear skin temperature, shoulder skin temperature, rump skin temperature, tail skin temperature, respiration rate, panting score, vaginal temperature automatically measured every 10 min, vaginal temperature measured at 0800 h, hair density score, body condition score, and ear area. Seven, five, six, two, seven, 15, and 14 genes with potential pleiotropic effects were identified for indicators of skin temperature, vaginal temperature, animal temperature, respiration rate, thermoregulatory traits, anatomical traits, and all traits, respectively. CONCLUSIONS Physiological and anatomical indicators of HS response in lactating sows are heritable but highly polygenic. The candidate genes found are associated with important gene ontology terms and biological pathways related to heat shock protein activities, immune response, and cellular oxidative stress. Many of the candidate genes with pleiotropic effects are involved in catalytic activities to reduce cell damage from oxidative stress and cellular mechanisms related to immune response.
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Affiliation(s)
- Letícia Fernanda de Oliveira
- Department of Animal Science, Federal University of Viçosa, Viçosa, MG, Brazil
- Department of Animal Sciences, Purdue University, West Lafayette, IN, USA
| | - Renata Veroneze
- Department of Animal Science, Federal University of Viçosa, Viçosa, MG, Brazil
| | - Katiene Régia Silva Sousa
- Department of Animal Sciences, Purdue University, West Lafayette, IN, USA
- Department of Oceanography and Limnology, Federal University of Maranhão, São Luís, MA, Brazil
| | - Henrique A Mulim
- Department of Animal Sciences, Purdue University, West Lafayette, IN, USA
| | | | | | - Jay S Johnson
- USDA-ARS Livestock Behavior Research Unit, West Lafayette, IN, USA
| | - Luiz F Brito
- Department of Animal Sciences, Purdue University, West Lafayette, IN, USA.
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Balech R, Maalouf F, Kaur S, Jighly A, Joukhadar R, Alsamman AM, Hamwieh A, Khater LA, Rubiales D, Kumar S. Identification of novel genes associated with herbicide tolerance in Lentil (Lens culinaris ssp. culinaris Medik.). Sci Rep 2024; 14:10215. [PMID: 38702403 PMCID: PMC11068770 DOI: 10.1038/s41598-024-59695-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: 07/05/2023] [Accepted: 04/15/2024] [Indexed: 05/06/2024] Open
Abstract
Weeds pose a major constraint in lentil cultivation, leading to decrease farmers' revenues by reducing the yield and increasing the management costs. The development of herbicide tolerant cultivars is essential to increase lentil yield. Even though herbicide tolerant lines have been identified in lentils, breeding efforts are still limited and lack proper validation. Marker assisted selection (MAS) can increase selection accuracy at early generations. Total 292 lentil accessions were evaluated under different dosages of two herbicides, metribuzin and imazethapyr, during two seasons at Marchouch, Morocco and Terbol, Lebanon. Highly significant differences among accessions were observed for days to flowering (DF) and maturity (DM), plant height (PH), biological yield (BY), seed yield (SY), number of pods per plant (NP), as well as the reduction indices (RI) for PH, BY, SY and NP. A total of 10,271 SNPs markers uniformly distributed along the lentil genome were assayed using Multispecies Pulse SNP chip developed at Agriculture Victoria, Melbourne. Meta-GWAS analysis was used to detect marker-trait associations, which detected 125 SNPs markers associated with different traits and clustered in 85 unique quantitative trait loci. These findings provide valuable insights for initiating MAS programs aiming to enhance herbicide tolerance in lentil crop.
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Affiliation(s)
- Rind Balech
- International Center for Agricultural Research in the Dry Areas (ICARDA), Terbol, Lebanon.
| | - Fouad Maalouf
- International Center for Agricultural Research in the Dry Areas (ICARDA), Terbol, Lebanon.
| | - Sukhjiwan Kaur
- Department of Energy, AgriBio, Environment and Climate Action, Centre for AgriBioscience, 5 Ring Road, Bundoora, VIC, 3083, Australia
| | - Abdulqader Jighly
- Department of Energy, AgriBio, Environment and Climate Action, Centre for AgriBioscience, 5 Ring Road, Bundoora, VIC, 3083, Australia
| | - Reem Joukhadar
- Department of Energy, AgriBio, Environment and Climate Action, Centre for AgriBioscience, 5 Ring Road, Bundoora, VIC, 3083, Australia
| | | | | | - Lynn Abou Khater
- International Center for Agricultural Research in the Dry Areas (ICARDA), Terbol, Lebanon
| | - Diego Rubiales
- Institute for Sustainable Agriculture, CSIC, Córdoba, Spain
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Majeres LE, Dilger AC, Shike DW, McCann JC, Beever JE. Defining a Haplotype Encompassing the LCORL-NCAPG Locus Associated with Increased Lean Growth in Beef Cattle. Genes (Basel) 2024; 15:576. [PMID: 38790206 PMCID: PMC11121065 DOI: 10.3390/genes15050576] [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: 04/23/2024] [Accepted: 04/28/2024] [Indexed: 05/26/2024] Open
Abstract
Numerous studies have shown genetic variation at the LCORL-NCAPG locus is strongly associated with growth traits in beef cattle. However, a causative molecular variant has yet to be identified. To define all possible candidate variants, 34 Charolais-sired calves were whole-genome sequenced, including 17 homozygous for a long-range haplotype associated with increased growth (QQ) and 17 homozygous for potential ancestral haplotypes for this region (qq). The Q haplotype was refined to an 814 kb region between chr6:37,199,897-38,014,080 and contained 218 variants not found in qq individuals. These variants include an insertion in an intron of NCAPG, a previously documented mutation in NCAPG (rs109570900), two coding sequence mutations in LCORL (rs109696064 and rs384548488), and 15 variants located within ATAC peaks that were predicted to affect transcription factor binding. Notably, rs384548488 is a frameshift variant likely resulting in loss of function for long isoforms of LCORL. To test the association of the coding sequence variants of LCORL with phenotype, 405 cattle from five populations were genotyped. The two variants were in complete linkage disequilibrium. Statistical analysis of the three populations that contained QQ animals revealed significant (p < 0.05) associations with genotype and birth weight, live weight, carcass weight, hip height, and average daily gain. These findings affirm the link between this locus and growth in beef cattle and describe DNA variants that define the haplotype. However, further studies will be required to define the true causative mutation.
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Affiliation(s)
- Leif E. Majeres
- UTIA Genomics Center for the Advancement of Agriculture, Institute of Agriculture, University of Tennessee, Knoxville, TN 37996, USA;
| | - Anna C. Dilger
- Department of Animal Sciences, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA; (A.C.D.); (D.W.S.); (J.C.M.)
| | - Daniel W. Shike
- Department of Animal Sciences, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA; (A.C.D.); (D.W.S.); (J.C.M.)
| | - Joshua C. McCann
- Department of Animal Sciences, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA; (A.C.D.); (D.W.S.); (J.C.M.)
| | - Jonathan E. Beever
- UTIA Genomics Center for the Advancement of Agriculture, Institute of Agriculture, University of Tennessee, Knoxville, TN 37996, USA;
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Xu H, Akhmet N, Luo Y, Guo Z, Pan C, Song E, Malmakov N, Akhatayeva Z, Lan X. Are two beneficial mutations (p.Q249R and 90-bp Indel) within the ovine BMPRIB gene associated with growth traits? Front Vet Sci 2024; 10:1280548. [PMID: 38644960 PMCID: PMC11027740 DOI: 10.3389/fvets.2023.1280548] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2023] [Accepted: 10/18/2023] [Indexed: 04/23/2024] Open
Abstract
Background The problem of achieving economic efficiency in sheep breeding can be largely solved by increasing sheep productivity. Recently, the BMPRIB gene has been revealed by GWAS as a potential candidate gene for sheep body morphometric traits. Therefore, the present study aimed to investigate whether genetic polymorphisms (p.Q249R SNP and 90-bp deletion) in the BMPRIB gene are associated with sheep growth traits. Methods PCR-based genotyping was performed on 1,875 sheep, including 1,191 Guiqian semi-fine wool (GQSFW), 560 Luxi Blackhead (LXBH), 55 Lanzhou fat-tailed (LZFT), and 69 Weining (WN) sheep. Genotype-phenotype association was assessed using the independent samples t-test and ANOVA. The significance level was set at αoriginal < 0.05. The threshold p-value for significance was adjusted after correction for multiple comparisons using the Bonferroni correction. Results After the Bonferroni correction, it was found that individuals with FecB+/FecB+ genotypes of the p.Q249R had significantly better growth traits in LXBH ewe lambs, including the body length, chest width, paunch girth, cannon circumference, and hip width (P<0.0005). Meanwhile, associations were observed between 90-bp deletion polymorphism and several growth traits (body length, body height, chest depth, and canon circumference) in GQSFW ewe adults after the Bonferroni correction (P < 0.0002), and individuals with the "DD" genotypes had greater growth traits. Conclusion Our findings align with the experimental observations from GWAS, which identified the BMPRIB gene as a potential candidate gene for body measurement traits. These findings not only confirm the previous study's results but also expand on them. Therefore, further investigations regarding the impact of BMPRIB polymorphisms on growth traits are necessary in other sheep breeds.
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Affiliation(s)
- Hongwei Xu
- College of Life Science and Engineering, Northwest Minzu University, Lanzhou, Gansu, China
| | - Nazar Akhmet
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, China
| | - Yunyun Luo
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, China
| | - Zhenggang Guo
- Bijie Animal Husbandry and Veterinary Science Research Institute, Bijie, Guizhou, China
| | - Chuanying Pan
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, China
| | - Enliang Song
- Shandong Key Lab of Animal Disease Control and Breeding, Institute of Animal Science and Veterinary Medicine, Shandong Academy of Agricultural Sciences, Jinan, China
| | - Nurlan Malmakov
- Scientific Research Institute of Sheep Breeding Branch, Kazakh Scientific Research Institute of Animal Husbandry and Fodder Production, Mynbaev, Almaty Region, Kazakhstan
| | - Zhanerke Akhatayeva
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, China
- Scientific Research Institute of Sheep Breeding Branch, Kazakh Scientific Research Institute of Animal Husbandry and Fodder Production, Mynbaev, Almaty Region, Kazakhstan
| | - Xianyong Lan
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, China
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10
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Wang SZ, Wang MD, Wang JY, Yuan M, Li YD, Luo PT, Xiao F, Li H. Genome-wide association study of growth curve parameters reveals novel genomic regions and candidate genes associated with metatarsal bone traits in chickens. Animal 2024; 18:101129. [PMID: 38574453 DOI: 10.1016/j.animal.2024.101129] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Revised: 03/02/2024] [Accepted: 03/05/2024] [Indexed: 04/06/2024] Open
Abstract
The growth and development of chicken bones have an enormous impact on the health and production performance of chickens. However, the development pattern and genetic regulation of the chicken skeleton are poorly understood. This study aimed to evaluate metatarsal bone growth and development patterns in chickens via non-linear models, and to identify the genetic determinants of metatarsal bone traits using a genome-wide association study (GWAS) based on growth curve parameters. Data on metatarsal length (MeL) and metatarsal circumference (MeC) were obtained from 471 F2 chickens (generated by crossing broiler sires, derived from a line selected for high abdominal fat, with Baier layer dams) at 4, 6, 8, 10, and 12 weeks of age. Four non-linear models (Gompertz, Logistic, von Bertalanffy, and Brody) were used to fit the MeL and MeC growth curves. Subsequently, the estimated growth curve parameters of the mature MeL or MeC (A), time-scale parameter (b), and maturity rate (K) from the non-linear models were utilized as substitutes for the original bone data in GWAS. The Logistic and Brody models displayed the best goodness-of-fit for MeL and MeC, respectively. Single-trait and multi-trait GWASs based on the growth curve parameters of the Logistic and Brody models revealed 4 618 significant single nucleotide polymorphisms (SNPs), annotated to 332 genes, associated with metatarsal bone traits. The majority of these significant SNPs were located on Gallus gallus chromosome (GGA) 1 (167.433-176.318 Mb), GGA2 (96.791-103.543 Mb), GGA4 (65.003-83.104 Mb) and GGA6 (64.685-95.285 Mb). Notably, we identified 12 novel GWAS loci associated with chicken metatarsal bone traits, encompassing 35 candidate genes. In summary, the combination of single-trait and multi-trait GWASs based on growth curve parameters uncovered numerous genomic regions and candidate genes associated with chicken bone traits. The findings benefit an in-depth understanding of the genetic architecture underlying metatarsal growth and development in chickens.
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Affiliation(s)
- S Z Wang
- Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs, Harbin 150030, PR China; Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province, Harbin 150030, PR China; College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, PR China
| | - M D Wang
- Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs, Harbin 150030, PR China; Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province, Harbin 150030, PR China; College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, PR China
| | - J Y Wang
- Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs, Harbin 150030, PR China; Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province, Harbin 150030, PR China; College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, PR China
| | - M Yuan
- Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs, Harbin 150030, PR China; Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province, Harbin 150030, PR China; College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, PR China
| | - Y D Li
- Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs, Harbin 150030, PR China; Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province, Harbin 150030, PR China; College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, PR China
| | - P T Luo
- Fujian Sunnzer Biotechnology Development Co. Ltd, Guangze, Fujian Province 354100, PR China
| | - F Xiao
- Fujian Sunnzer Biotechnology Development Co. Ltd, Guangze, Fujian Province 354100, PR China
| | - H Li
- Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs, Harbin 150030, PR China; Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province, Harbin 150030, PR China; College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, PR China.
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11
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Heaton MP, Harhay GP, Bassett AS, Clark HJ, Carlson JM, Jobman EE, Sadd HR, Pelster MC, Workman AM, Kuehn LA, Kalbfleisch TS, Piscatelli H, Carrie M, Krafsur GM, Grotelueschen DM, Vander Ley BL. Association of ARRDC3 and NFIA variants with bovine congestive heart failure in feedlot cattle. F1000Res 2024; 11:385. [PMID: 38680232 PMCID: PMC11046187 DOI: 10.12688/f1000research.109488.1] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 02/14/2024] [Indexed: 06/24/2024] Open
Abstract
BACKGROUND Bovine congestive heart failure (BCHF) has become increasingly prevalent among feedlot cattle in the Western Great Plains of North America with up to 7% mortality in affected herds. BCHF is an untreatable complex condition involving pulmonary hypertension that culminates in right ventricular failure and death. Genes associated with BCHF in feedlot cattle have not been previously identified. Our aim was to search for genomic regions associated with this disease. METHODS A retrospective, matched case-control design with 102 clinical BCHF cases and their unaffected pen mates was used in a genome-wide association study. Paired nominal data from approximately 560,000 filtered single nucleotide polymorphisms (SNPs) were analyzed with McNemar's test. RESULTS Two independent genomic regions were identified as having the most significant association with BCHF: the arrestin domain-containing protein 3 gene ( ARRDC3), and the nuclear factor IA gene ( NFIA, mid- p-values, 1x10 -8 and 2x10 -7, respectively). Animals with two copies of risk alleles at either gene were approximately eight-fold more likely to have BCHF than their matched pen mates with either one or zero risk alleles at both genes (CI 95 = 3-17). Further, animals with two copies of risk alleles at both genes were 28-fold more likely to have BCHF than all others ( p-value = 1×10 -7, CI 95 = 4-206). A missense variant in ARRDC3 (C182Y) represents a potential functional variant since the C182 codon is conserved among all other jawed vertebrate species observed. A two-SNP test with markers in both genes showed 29% of 273 BCHF cases had homozygous risk genotypes in both genes, compared to 2.5% in 198 similar unaffected feedlot cattle. This and other DNA tests may be useful for identifying feedlot animals with the highest risk for BCHF in the environments described here. CONCLUSIONS Although pathogenic roles for variants in the ARRDC3 and NFIA genes are unknown, their discovery facilitates classifying animals by genetic risk and allows cattle producers to make informed decisions for selective breeding and animal health management.
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Affiliation(s)
- Michael P. Heaton
- USDA, ARS, US Meat Animal Research Center, Clay Center, Nebraska, 68933, USA
| | - Gregory P. Harhay
- USDA, ARS, US Meat Animal Research Center, Clay Center, Nebraska, 68933, USA
| | - Adam S. Bassett
- University of Nebraska-Lincoln, Great Plains Veterinary Educational Center, Clay Center, Nebraska, 68933, USA
| | - Halden J. Clark
- University of Nebraska-Lincoln, Great Plains Veterinary Educational Center, Clay Center, Nebraska, 68933, USA
| | - Jaden M. Carlson
- University of Nebraska-Lincoln, Great Plains Veterinary Educational Center, Clay Center, Nebraska, 68933, USA
| | - Erin E. Jobman
- University of Nebraska-Lincoln, Great Plains Veterinary Educational Center, Clay Center, Nebraska, 68933, USA
| | - Helen R. Sadd
- USDA, ARS, US Meat Animal Research Center, Clay Center, Nebraska, 68933, USA
| | - Madeline C. Pelster
- University of Nebraska-Lincoln, Great Plains Veterinary Educational Center, Clay Center, Nebraska, 68933, USA
| | - Aspen M. Workman
- USDA, ARS, US Meat Animal Research Center, Clay Center, Nebraska, 68933, USA
| | - Larry A. Kuehn
- USDA, ARS, US Meat Animal Research Center, Clay Center, Nebraska, 68933, USA
| | | | | | | | - Greta M. Krafsur
- Anschutz Medical Campus, University of Colorado Denver, Aurora, Colorado, 80045, USA
| | - Dale M. Grotelueschen
- University of Nebraska-Lincoln, Great Plains Veterinary Educational Center, Clay Center, Nebraska, 68933, USA
| | - Brian L. Vander Ley
- University of Nebraska-Lincoln, Great Plains Veterinary Educational Center, Clay Center, Nebraska, 68933, USA
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12
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Heaton MP, Harhay GP, Bassett AS, Clark HJ, Carlson JM, Jobman EE, Sadd HR, Pelster MC, Workman AM, Kuehn LA, Kalbfleisch TS, Piscatelli H, Carrie M, Krafsur GM, Grotelueschen DM, Vander Ley BL. Association of ARRDC3 and NFIA variants with bovine congestive heart failure in feedlot cattle. F1000Res 2024; 11:385. [PMID: 38680232 PMCID: PMC11046187 DOI: 10.12688/f1000research.109488.2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 02/14/2024] [Indexed: 05/01/2024] Open
Abstract
Background Bovine congestive heart failure (BCHF) has become increasingly prevalent among feedlot cattle in the Western Great Plains of North America with up to 7% mortality in affected herds. BCHF is an untreatable complex condition involving pulmonary hypertension that culminates in right ventricular failure and death. Genes associated with BCHF in feedlot cattle have not been previously identified. Our aim was to search for genomic regions associated with this disease. Methods A retrospective, matched case-control design with 102 clinical BCHF cases and their unaffected pen mates was used in a genome-wide association study. Paired nominal data from approximately 560,000 filtered single nucleotide polymorphisms (SNPs) were analyzed with McNemar's test. Results Two independent genomic regions were identified as having the most significant association with BCHF: the arrestin domain-containing protein 3 gene ( ARRDC3), and the nuclear factor IA gene ( NFIA, mid- p-values, 1x10 -8 and 2x10 -7, respectively). Animals with two copies of risk alleles at either gene were approximately eight-fold more likely to have BCHF than their matched pen mates with either one or zero risk alleles at both genes (CI 95 = 3-17). Further, animals with two copies of risk alleles at both genes were 28-fold more likely to have BCHF than all others ( p-value = 1×10 -7, CI 95 = 4-206). A missense variant in ARRDC3 (C182Y) represents a potential functional variant since the C182 codon is conserved among all other jawed vertebrate species observed. A two-SNP test with markers in both genes showed 29% of 273 BCHF cases had homozygous risk genotypes in both genes, compared to 2.5% in 198 similar unaffected feedlot cattle. This and other DNA tests may be useful for identifying feedlot animals with the highest risk for BCHF in the environments described here. Conclusions Although pathogenic roles for variants in the ARRDC3 and NFIA genes are unknown, their discovery facilitates classifying animals by genetic risk and allows cattle producers to make informed decisions for selective breeding and animal health management.
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Affiliation(s)
- Michael P. Heaton
- USDA, ARS, US Meat Animal Research Center, Clay Center, Nebraska, 68933, USA
| | - Gregory P. Harhay
- USDA, ARS, US Meat Animal Research Center, Clay Center, Nebraska, 68933, USA
| | - Adam S. Bassett
- University of Nebraska-Lincoln, Great Plains Veterinary Educational Center, Clay Center, Nebraska, 68933, USA
| | - Halden J. Clark
- University of Nebraska-Lincoln, Great Plains Veterinary Educational Center, Clay Center, Nebraska, 68933, USA
| | - Jaden M. Carlson
- University of Nebraska-Lincoln, Great Plains Veterinary Educational Center, Clay Center, Nebraska, 68933, USA
| | - Erin E. Jobman
- University of Nebraska-Lincoln, Great Plains Veterinary Educational Center, Clay Center, Nebraska, 68933, USA
| | - Helen R. Sadd
- USDA, ARS, US Meat Animal Research Center, Clay Center, Nebraska, 68933, USA
| | - Madeline C. Pelster
- University of Nebraska-Lincoln, Great Plains Veterinary Educational Center, Clay Center, Nebraska, 68933, USA
| | - Aspen M. Workman
- USDA, ARS, US Meat Animal Research Center, Clay Center, Nebraska, 68933, USA
| | - Larry A. Kuehn
- USDA, ARS, US Meat Animal Research Center, Clay Center, Nebraska, 68933, USA
| | | | | | | | - Greta M. Krafsur
- Anschutz Medical Campus, University of Colorado Denver, Aurora, Colorado, 80045, USA
| | - Dale M. Grotelueschen
- University of Nebraska-Lincoln, Great Plains Veterinary Educational Center, Clay Center, Nebraska, 68933, USA
| | - Brian L. Vander Ley
- University of Nebraska-Lincoln, Great Plains Veterinary Educational Center, Clay Center, Nebraska, 68933, USA
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13
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Qiu Z, Cai W, Liu Q, Liu K, Liu C, Yang H, Huang R, Li P, Zhao Q. Unravelling novel and pleiotropic genes for cannon bone circumference and bone mineral density in Yorkshire pigs. J Anim Sci 2024; 102:skae036. [PMID: 38330300 PMCID: PMC10914368 DOI: 10.1093/jas/skae036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2023] [Accepted: 02/03/2024] [Indexed: 02/10/2024] Open
Abstract
Leg weakness is a prevalent health condition in pig farms. The augmentation of cannon bone circumference and bone mineral density can effectively improve limb strength in pigs and alleviate leg weakness. This study measured forelimb cannon bone circumference (fCBC) and rear limb cannon bone circumference (rCBC) using an inelastic tapeline and rear limb metatarsal area bone mineral density (raBMD) using a dual-energy X-ray absorptiometry bone density scanner. The samples of Yorkshire castrated boars were genotyped using a 50K single-nucleotide polymorphism (SNP) array. The SNP-chip data were imputed to the level of whole-genome sequencing data (iWGS). This study used iWGS data to perform genome-wide association studies and identified novel significant SNPs associated with fCBC on SSC6, SSC12, and SSC13, rCBC on SSC12 and SSC14, and raBMD on SSC7. Based on the high phenotypic and genetic correlations between CBC and raBMD, multi-trait meta-analysis was performed to identify pleiotropic SNPs. A significant potential pleiotropic quantitative trait locus (QTL) regulating both CBC and raBMD was identified on SSC15. Bayes fine mapping was used to establish the confidence intervals for these novel QTLs with the most refined confidence interval narrowed down to 56 kb (15.11 to 15.17 Mb on SSC12 for fCBC). Furthermore, the confidence interval for the potential pleiotropic QTL on SSC15 in the meta-analysis was narrowed down to 7.45 kb (137.55 to137.56 Mb on SSC15). Based on the biological functions of genes, the following genes were identified as novel regulatory candidates for different phenotypes: DDX42, MYSM1, FTSJ3, and MECOM for fCBC; SMURF2, and STC1 for rCBC; RGMA for raBMD. Additionally, RAMP1, which was determined to be located 23.68 kb upstream of the confidence interval of the QTL on SSC15 in the meta-analysis, was identified as a potential pleiotropic candidate gene regulating both CBC and raBMD. These findings offered valuable insights for identifying pathogenic genes and elucidating the genetic mechanisms underlying CBC and BMD.
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Affiliation(s)
- Zijian Qiu
- Key Laboratory in Nanjing for Evaluation and Utilization of Pigs Resources, Ministry of Agriculture and Rural Areas of China, Institute of Swine Science, Nanjing Agricultural University, Nanjing 210095, China
| | - Wenwu Cai
- Key Laboratory in Nanjing for Evaluation and Utilization of Pigs Resources, Ministry of Agriculture and Rural Areas of China, Institute of Swine Science, Nanjing Agricultural University, Nanjing 210095, China
| | - Qian Liu
- Key Laboratory in Nanjing for Evaluation and Utilization of Pigs Resources, Ministry of Agriculture and Rural Areas of China, Institute of Swine Science, Nanjing Agricultural University, Nanjing 210095, China
| | - Kaiyue Liu
- Key Laboratory in Nanjing for Evaluation and Utilization of Pigs Resources, Ministry of Agriculture and Rural Areas of China, Institute of Swine Science, Nanjing Agricultural University, Nanjing 210095, China
| | - Chenxi Liu
- Key Laboratory in Nanjing for Evaluation and Utilization of Pigs Resources, Ministry of Agriculture and Rural Areas of China, Institute of Swine Science, Nanjing Agricultural University, Nanjing 210095, China
| | - Huilong Yang
- Key Laboratory in Nanjing for Evaluation and Utilization of Pigs Resources, Ministry of Agriculture and Rural Areas of China, Institute of Swine Science, Nanjing Agricultural University, Nanjing 210095, China
| | - Ruihua Huang
- Key Laboratory in Nanjing for Evaluation and Utilization of Pigs Resources, Ministry of Agriculture and Rural Areas of China, Institute of Swine Science, Nanjing Agricultural University, Nanjing 210095, China
- Huaian Academy, Nanjing Agricultural University, Huaian 223005, China
| | - Pinghua Li
- Key Laboratory in Nanjing for Evaluation and Utilization of Pigs Resources, Ministry of Agriculture and Rural Areas of China, Institute of Swine Science, Nanjing Agricultural University, Nanjing 210095, China
- Huaian Academy, Nanjing Agricultural University, Huaian 223005, China
| | - Qingbo Zhao
- Key Laboratory in Nanjing for Evaluation and Utilization of Pigs Resources, Ministry of Agriculture and Rural Areas of China, Institute of Swine Science, Nanjing Agricultural University, Nanjing 210095, China
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14
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Ma Z, Chang Y, Brito LF, Li Y, Yang T, Wang Y, Yang N. Multitrait meta-analyses identify potential candidate genes for growth-related traits in Holstein heifers. J Dairy Sci 2023; 106:9055-9070. [PMID: 37641329 DOI: 10.3168/jds.2023-23462] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Accepted: 06/20/2023] [Indexed: 08/31/2023]
Abstract
Understanding the underlying pleiotropic relationships among growth and body size traits is important for refining breeding strategies in dairy cattle for optimal body size and growth rate. Therefore, we performed single-trait GWAS for monthly-recorded body weight (BW), hip height, body length, and chest girth from birth to 12 mo of age in Holstein animals, followed by stepwise multiple regression of independent or lowly-linked markers from GWAS loci using conditional and joint association analyses (COJO). Subsequently, we conducted a multitrait meta-analysis to detect pleiotropic markers. Based on the single-trait GWAS, we identified 170 significant SNPs, in which 59 of them remained significant after the COJO analyses. The most significant SNP, located at BTA7:3,676,741, explained 2.93% of the total phenotypic variance for BW6 (BW at 6 mo of age). We identified 17 SNPs with potential pleiotropic effects based on the multitrait meta-analyses, which resulted in 3 additional SNPs in comparison to those detected based on the single-trait GWAS. The identified quantitative trait loci regions overlap with genes known to influence human growth-related traits. According to positional and functional analyses, we proposed HMGA2, HNF4G, MED13L, BHLHE40, FRZB, DMP1, TRIB3, and GATAD2A as important candidate genes influencing the studied traits. The combination of single-trait GWAS and meta-analyses of GWAS results improved the efficiency of detecting associated SNPs, and provided new insights into the genetic mechanisms of growth and development in Holstein cattle.
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Affiliation(s)
- Z Ma
- Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture of China, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, 100193, Beijing, China; Beijing Sunlon Livestock Development Co. Ltd., 100029, Beijing, China
| | - Y Chang
- Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture of China, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, 100193, Beijing, China
| | - Luiz F Brito
- Department of Animal Sciences, Purdue University, West Lafayette, IN 47907
| | - Y Li
- Beijing Sunlon Livestock Development Co. Ltd., 100029, Beijing, China
| | - T Yang
- Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture of China, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, 100193, Beijing, China
| | - Y Wang
- Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture of China, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, 100193, Beijing, China.
| | - N Yang
- Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture of China, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, 100193, Beijing, China.
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15
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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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16
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Sanchez MP, Tribout T, Kadri NK, Chitneedi PK, Maak S, Hozé C, Boussaha M, Croiseau P, Philippe R, Spengeler M, Kühn C, Wang Y, Li C, Plastow G, Pausch H, Boichard D. Sequence-based GWAS meta-analyses for beef production traits. Genet Sel Evol 2023; 55:70. [PMID: 37828440 PMCID: PMC10568825 DOI: 10.1186/s12711-023-00848-5] [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: 06/11/2023] [Accepted: 10/04/2023] [Indexed: 10/14/2023] Open
Abstract
BACKGROUND Combining the results of within-population genome-wide association studies (GWAS) based on whole-genome sequences into a single meta-analysis (MA) is an accurate and powerful method for identifying variants associated with complex traits. As part of the H2020 BovReg project, we performed sequence-level MA for beef production traits. Five partners from France, Switzerland, Germany, and Canada contributed summary statistics from sequence-based GWAS conducted with 54,782 animals from 15 purebred or crossbred populations. We combined the summary statistics for four growth, nine morphology, and 15 carcass traits into 16 MA, using both fixed effects and z-score methods. RESULTS The fixed-effects method was generally more informative to provide indication on potentially causal variants, although we combined substantially different traits in each MA. In comparison with within-population GWAS, this approach highlighted (i) a larger number of quantitative trait loci (QTL), (ii) QTL more frequently located in genomic regions known for their effects on growth and meat/carcass traits, (iii) a smaller number of genomic variants within the QTL, and (iv) candidate variants that were more frequently located in genes. MA pinpointed variants in genes, including MSTN, LCORL, and PLAG1 that have been previously associated with morphology and carcass traits. We also identified dozens of other variants located in genes associated with growth and carcass traits, or with a function that may be related to meat production (e.g., HS6ST1, HERC2, WDR75, COL3A1, SLIT2, MED28, and ANKAR). Some of these variants overlapped with expression or splicing QTL reported in the cattle Genotype-Tissue Expression atlas (CattleGTEx) and could therefore regulate gene expression. CONCLUSIONS By identifying candidate genes and potential causal variants associated with beef production traits in cattle, MA demonstrates great potential for investigating the biological mechanisms underlying these traits. As a complement to within-population GWAS, this approach can provide deeper insights into the genetic architecture of complex traits in beef cattle.
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Affiliation(s)
- Marie-Pierre Sanchez
- Université Paris-Saclay, INRAE, AgroParisTech, GABI, 78350, Jouy-en-Josas, France.
| | - Thierry Tribout
- Université Paris-Saclay, INRAE, AgroParisTech, GABI, 78350, Jouy-en-Josas, France
| | | | - Praveen K Chitneedi
- Research Institute for Farm Animal Biology (FBN), 18196, Dummerstorf, Germany
| | - Steffen Maak
- Research Institute for Farm Animal Biology (FBN), 18196, Dummerstorf, Germany
| | - Chris Hozé
- Université Paris-Saclay, INRAE, AgroParisTech, GABI, 78350, Jouy-en-Josas, France
- Eliance, 75595, Paris, France
| | - Mekki Boussaha
- Université Paris-Saclay, INRAE, AgroParisTech, GABI, 78350, Jouy-en-Josas, France
| | - Pascal Croiseau
- Université Paris-Saclay, INRAE, AgroParisTech, GABI, 78350, Jouy-en-Josas, France
| | - Romain Philippe
- INRAE, USC1061 GAMAA, Université de Limoges, 87060, Limoges, France
| | | | - Christa Kühn
- Research Institute for Farm Animal Biology (FBN), 18196, Dummerstorf, Germany
- Agricultural and Environmental faculty, University Rostock, 18059, Rostock, Germany
- Friedrich-Loeffler-Institut (FLI), 17493, Greifswald, Insel Riems, Germany
| | - Yining Wang
- Lacombe Research and Development Centre, Agriculture and Agri-Food Canada, Lacombe, AB, T4L 1W1, Canada
| | - Changxi Li
- Lacombe Research and Development Centre, Agriculture and Agri-Food Canada, Lacombe, AB, T4L 1W1, Canada
- Department of Agricultural, Food and Nutritional Science, Livestock Gentec, University of Alberta, Edmonton, AB, T6G 2HI, Canada
| | - Graham Plastow
- Department of Agricultural, Food and Nutritional Science, Livestock Gentec, University of Alberta, Edmonton, AB, T6G 2HI, Canada
| | - Hubert Pausch
- Animal Genomics, ETH Zurich, 8092, Zurich, Switzerland
| | - Didier Boichard
- Université Paris-Saclay, INRAE, AgroParisTech, GABI, 78350, Jouy-en-Josas, France
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17
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Roth K, Pröll-Cornelissen MJ, Henne H, Appel AK, Schellander K, Tholen E, Große-Brinkhaus C. Multivariate genome-wide associations for immune traits in two maternal pig lines. BMC Genomics 2023; 24:492. [PMID: 37641029 PMCID: PMC10463314 DOI: 10.1186/s12864-023-09594-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Accepted: 08/16/2023] [Indexed: 08/31/2023] Open
Abstract
BACKGROUND Immune traits are considered to serve as potential biomarkers for pig's health. Medium to high heritabilities have been observed for some of the immune traits suggesting genetic variability of these phenotypes. Consideration of previously established genetic correlations between immune traits can be used to identify pleiotropic genetic markers. Therefore, genome-wide association study (GWAS) approaches are required to explore the joint genetic foundation for health biomarkers. Usually, GWAS explores phenotypes in a univariate (uv), trait-by-trait manner. Besides two uv GWAS methods, four multivariate (mv) GWAS approaches were applied on combinations out of 22 immune traits for Landrace (LR) and Large White (LW) pig lines. RESULTS In total 433 (LR: 351, LW: 82) associations were identified with the uv approach implemented in PLINK and a Bayesian linear regression uv approach (BIMBAM) software. Single Nucleotide Polymorphisms (SNPs) that were identified with both uv approaches (n = 32) were mostly associated with immune traits such as haptoglobin, red blood cell characteristics and cytokines, and were located in protein-coding genes. Mv GWAS approaches detected 647 associations for different mv immune trait combinations which were summarized to 133 Quantitative Trait Loci (QTL). SNPs for different trait combinations (n = 66) were detected with more than one mv method. Most of these SNPs are associated with red blood cell related immune trait combinations. Functional annotation of these QTL revealed 453 immune-relevant protein-coding genes. With uv methods shared markers were not observed between the breeds, whereas mv approaches were able to detect two conjoint SNPs for LR and LW. Due to unmapped positions for these markers, their functional annotation was not clarified. CONCLUSIONS This study evaluated the joint genetic background of immune traits in LR and LW piglets through the application of various uv and mv GWAS approaches. In comparison to uv methods, mv methodologies identified more significant associations, which might reflect the pleiotropic background of the immune system more accurately. In genetic research of complex traits, the SNP effects are generally small. Furthermore, one genetic variant can affect several correlated immune traits at the same time, termed pleiotropy. As mv GWAS methods consider strong dependencies among traits, the power to detect SNPs can be boosted. Both methods revealed immune-relevant potential candidate genes. Our results indicate that one single test is not able to detect all the different types of genetic effects in the most powerful manner and therefore, the methods should be applied complementary.
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Affiliation(s)
- Katharina Roth
- Institute of Animal Science, University of Bonn, Endenicher Allee 15, 53115, Bonn, Germany
| | | | - Hubert Henne
- BHZP GmbH, An der Wassermühle 8, 21368, Dahlenburg-Ellringen, Germany
| | | | - Karl Schellander
- Institute of Animal Science, University of Bonn, Endenicher Allee 15, 53115, Bonn, Germany
| | - Ernst Tholen
- Institute of Animal Science, University of Bonn, Endenicher Allee 15, 53115, Bonn, Germany
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18
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Li Y, Yang H, Guo J, Yang Y, Yu Q, Guo Y, Zhang C, Wang Z, Zuo P. Uncovering the candidate genes related to sheep body weight using multi-trait genome-wide association analysis. Front Vet Sci 2023; 10:1206383. [PMID: 37662987 PMCID: PMC10469697 DOI: 10.3389/fvets.2023.1206383] [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: 04/15/2023] [Accepted: 08/04/2023] [Indexed: 09/05/2023] Open
Abstract
In sheep, body weight is an economically important trait. This study sought to map genetic loci related to weaning weight and yearling weight. To this end, a single-trait and multi-trait genome-wide association study (GWAS) was performed using a high-density 600 K single nucleotide polymorphism (SNP) chip. The results showed that 43 and 56 SNPs were significantly associated with weaning weight and yearling weight, respectively. A region associated with both weaning and yearling traits (OARX: 6.74-7.04 Mb) was identified, suggesting that the same genes could play a role in regulating both these traits. This region was found to contain three genes (TBL1X, SHROOM2 and GPR143). The most significant SNP was Affx-281066395, located at 6.94 Mb (p = 1.70 × 10-17), corresponding to the SHROOM2 gene. We also identified 93 novel SNPs elated to sheep weight using multi-trait GWAS analysis. A new genomic region (OAR10: 76.04-77.23 Mb) with 22 significant SNPs were discovered. Combining transcriptomic data from multiple tissues and genomic data in sheep, we found the HINT1, ASB11 and GPR143 genes may involve in sheep body weight. So, multi-omic anlaysis is a valuable strategy identifying candidate genes related to body weight.
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Affiliation(s)
- Yunna Li
- College of Animal Science and Technology, Northeast Agricultural University,, Harbin, China
- State Key Laboratory of Sheep Genetic Improvement and Healthy Production, Xinjiang Academy of Agricultural and Reclamation Science,, Shihezi, China
| | - Hua Yang
- State Key Laboratory of Sheep Genetic Improvement and Healthy Production, Xinjiang Academy of Agricultural and Reclamation Science,, Shihezi, China
| | - Jing Guo
- College of Animal Science and Technology, Northeast Agricultural University,, Harbin, China
- State Key Laboratory of Sheep Genetic Improvement and Healthy Production, Xinjiang Academy of Agricultural and Reclamation Science,, Shihezi, China
| | - Yonglin Yang
- State Key Laboratory of Sheep Genetic Improvement and Healthy Production, Xinjiang Academy of Agricultural and Reclamation Science,, Shihezi, China
| | - Qian Yu
- State Key Laboratory of Sheep Genetic Improvement and Healthy Production, Xinjiang Academy of Agricultural and Reclamation Science,, Shihezi, China
| | - Yuanyuan Guo
- College of Animal Science and Technology, Northeast Agricultural University,, Harbin, China
- State Key Laboratory of Sheep Genetic Improvement and Healthy Production, Xinjiang Academy of Agricultural and Reclamation Science,, Shihezi, China
| | - Chaoxin Zhang
- College of Animal Science and Technology, Northeast Agricultural University,, Harbin, China
- State Key Laboratory of Sheep Genetic Improvement and Healthy Production, Xinjiang Academy of Agricultural and Reclamation Science,, Shihezi, China
| | - Zhipeng Wang
- College of Animal Science and Technology, Northeast Agricultural University,, Harbin, China
- State Key Laboratory of Sheep Genetic Improvement and Healthy Production, Xinjiang Academy of Agricultural and Reclamation Science,, Shihezi, China
| | - Peng Zuo
- State Key Laboratory of Sheep Genetic Improvement and Healthy Production, Xinjiang Academy of Agricultural and Reclamation Science,, Shihezi, China
- College of Science, Northeast Agricultural University, Harbin, China
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19
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Sahana G, Cai Z, Sanchez MP, Bouwman AC, Boichard D. Invited review: Good practices in genome-wide association studies to identify candidate sequence variants in dairy cattle. J Dairy Sci 2023:S0022-0302(23)00357-0. [PMID: 37349208 DOI: 10.3168/jds.2022-22694] [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: 08/24/2022] [Accepted: 02/01/2023] [Indexed: 06/24/2023]
Abstract
Genotype data from dairy cattle selection programs have greatly facilitated GWAS to identify variants related to economic traits. Results can enhance the accuracy of genomic prediction, analyze more complex models that go beyond additive effects, elucidate the genetic architecture of a trait, and finally, decipher the underlying biology of traits. The entire process, comprising data generation, quality control, statistical analyses, interpretation of association results, and linking results to biology should be designed and executed to minimize the generation of false-positive and false-negative associations and misleading links to biological processes. This review aims to provide general guidelines for data analysis that address data quality control, association tests, adjustment for population stratification, and significance evaluation to improve the reliability of conclusions. We also provide guidance on post-GWAS strategy and the interpretation of results. These guidelines are tailored to dairy cattle, which are characterized by long-range linkage disequilibrium, large half-sib families, and routinely collected phenotypes, requiring different approaches than those applied in human GWAS. We discuss common limitations and challenges that have been overlooked in the analysis and interpretation of GWAS to identify candidate sequence variants in dairy cattle.
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Affiliation(s)
- G Sahana
- Aarhus University, Center for Quantitative Genetic and Genomics, 8830 Tjele, Denmark.
| | - Z Cai
- Aarhus University, Center for Quantitative Genetic and Genomics, 8830 Tjele, Denmark
| | - M P Sanchez
- Université Paris-Saclay, INRAE, AgroParisTech, GABI, 78350 Jouy-en-Josas, France
| | - A C Bouwman
- Wageningen University & Research, Animal Breeding and Genomics, 6700 AH Wageningen, the Netherlands
| | - D Boichard
- Université Paris-Saclay, INRAE, AgroParisTech, GABI, 78350 Jouy-en-Josas, France
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20
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Pausch H, Mapel XM. Review: Genetic mutations affecting bull fertility. Animal 2023; 17 Suppl 1:100742. [PMID: 37567657 DOI: 10.1016/j.animal.2023.100742] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Revised: 01/23/2023] [Accepted: 01/24/2023] [Indexed: 08/13/2023] Open
Abstract
Cattle are a well-suited "model organism" to study the genetic underpinnings of variation in male reproductive performance. The adoption of artificial insemination and genomic prediction in many cattle breeds provide access to microarray-derived genotypes and repeated measurements for semen quality and insemination success in several thousand bulls. Similar-sized mapping cohorts with phenotypes for male fertility are not available for most other species precluding powerful association testing. The repeated measurements of the artificial insemination bulls' semen quality enable the differentiation between transient and biologically relevant trait fluctuations, and thus, are an ideal source of phenotypes for variance components estimation and genome-wide association testing. Genome-wide case-control association testing involving bulls with either aberrant sperm quality or low insemination success revealed several causal recessive loss-of-function alleles underpinning monogenic reproductive disorders. These variants are routinely monitored with customised genotyping arrays in the male selection candidates to avoid the use of subfertile or infertile bulls for artificial insemination and natural service. Genome-wide association studies with quantitative measurements of semen quality and insemination success revealed quantitative trait loci for male fertility, but the underlying causal variants remain largely unknown. Moreover, these loci explain only a small part of the heritability of male fertility. Integrating genome-wide association studies with gene expression and other omics data from male reproductive tissues is required for the fine-mapping of candidate causal variants underlying variation in male reproductive performance in cattle.
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Affiliation(s)
- Hubert Pausch
- Animal Genomics, Department of Environmental Systems Science, ETH Zurich, Universitaetstrasse 2, 8092 Zurich, Switzerland.
| | - Xena Marie Mapel
- Animal Genomics, Department of Environmental Systems Science, ETH Zurich, Universitaetstrasse 2, 8092 Zurich, Switzerland
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21
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Cheng J, Cao X, Wang X, Wang J, Yue B, Sun W, Huang Y, Lan X, Ren G, Lei C, Chen H. Dynamic chromatin architectures provide insights into the genetics of cattle myogenesis. J Anim Sci Biotechnol 2023; 14:59. [PMID: 37055796 PMCID: PMC10103417 DOI: 10.1186/s40104-023-00855-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2022] [Accepted: 02/16/2023] [Indexed: 04/15/2023] Open
Abstract
BACKGROUND Sharply increased beef consumption is propelling the genetic improvement projects of beef cattle in China. Three-dimensional genome structure is confirmed to be an important layer of transcription regulation. Although genome-wide interaction data of several livestock species have already been produced, the genome structure states and its regulatory rules in cattle muscle are still limited. RESULTS Here we present the first 3D genome data in Longissimus dorsi muscle of fetal and adult cattle (Bos taurus). We showed that compartments, topologically associating domains (TADs), and loop undergo re-organization and the structure dynamics were consistent with transcriptomic divergence during muscle development. Furthermore, we annotated cis-regulatory elements in cattle genome during myogenesis and demonstrated the enrichments of promoter and enhancer in selection sweeps. We further validated the regulatory function of one HMGA2 intronic enhancer near a strong sweep region on primary bovine myoblast proliferation. CONCLUSIONS Our data provide key insights of the regulatory function of high order chromatin structure and cattle myogenic biology, which will benefit the progress of genetic improvement of beef cattle.
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Affiliation(s)
- Jie Cheng
- College of Animal Science and Technology, Northwest A&F University, No.22 Xinong Road, Yangling district, Yangling, Shaanxi province, 712100, China
| | - Xiukai Cao
- College of Animal Science and Technology, Northwest A&F University, No.22 Xinong Road, Yangling district, Yangling, Shaanxi province, 712100, China
- Joint International Research Laboratory of Agriculture and Agri-Product Safety of Ministry of Education of China, Yangzhou University, Yangzhou, 225009, China
| | - Xiaogang Wang
- College of Animal Science and Technology, Northwest A&F University, No.22 Xinong Road, Yangling district, Yangling, Shaanxi province, 712100, China
| | - Jian Wang
- College of Animal Science and Technology, Northwest A&F University, No.22 Xinong Road, Yangling district, Yangling, Shaanxi province, 712100, China
| | - Binglin Yue
- College of Animal Science and Technology, Northwest A&F University, No.22 Xinong Road, Yangling district, Yangling, Shaanxi province, 712100, China
- Key Laboratory of Qinghai-Tibetan Plateau Animal Genetic Resource Reservation and Utilization, Southwest Minzu University, Chengdu, 610225, China
| | - Wei Sun
- College of Animal Science and Technology, Yangzhou University, Yangzhou, 225009, China
| | - Yongzhen Huang
- College of Animal Science and Technology, Northwest A&F University, No.22 Xinong Road, Yangling district, Yangling, Shaanxi province, 712100, China
| | - Xianyong Lan
- College of Animal Science and Technology, Northwest A&F University, No.22 Xinong Road, Yangling district, Yangling, Shaanxi province, 712100, China
| | - Gang Ren
- College of Animal Science and Technology, Northwest A&F University, No.22 Xinong Road, Yangling district, Yangling, Shaanxi province, 712100, China
| | - Chuzhao Lei
- College of Animal Science and Technology, Northwest A&F University, No.22 Xinong Road, Yangling district, Yangling, Shaanxi province, 712100, China
| | - Hong Chen
- College of Animal Science and Technology, Northwest A&F University, No.22 Xinong Road, Yangling district, Yangling, Shaanxi province, 712100, China.
- College of Animal Science, Xinjiang Agricultural University, Urumqi, 830052, China.
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22
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Wang J, Yang H, Chen S, Li W, Yu J, Hu Z, Zhuo Y, Huang Q, Liu Z, Zhou L, Wu J, Wang Z, Guo F, Yun P, Wang X, Liu JF. Genome-wide association study reveals candidate genes for pollution excreta traits in pigs. Anim Genet 2023. [PMID: 37040927 DOI: 10.1111/age.13323] [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: 06/16/2022] [Revised: 11/13/2022] [Accepted: 03/18/2023] [Indexed: 04/13/2023]
Abstract
Excreta traits comprise a very important characteristic in breeding that have been neglected for a long time. With the growth of intensive pig farming, plenty of environment problems have been raised, and people have begun to pay attention to pig excreta behaviors from genetics and breeding perspectives. However, the genetic architecture of excreta traits remains unclear. To investigate the genetic architecture of excreta traits in pigs, eight excreta traits and feed conversion ratio (FCR) were analyzed in this study. We performed genome-wide association studies (GWASs) on 213 Yorkshire pigs and estimated genetic parameters for a total number of 290 pigs, comprising 213 Yorkshire, 52 Landrace and 25 Duroc. After analysis, eight and 22 genome-wide significant SNPs were detected for FCR and the eight excreta traits in single-trait GWASs separately, and 18 were detected in a multi-trait meta-analysis for excreta traits, six of which were detected in both the single-trait and the multi-trait GWAS. Eighty, 182 and 133 genes were detected within 1 Mb of the genome-wide significant SNPs for FCR, excreta traits and multi-trait meta-analysis, respectively. Five candidate genes (BCKDC, DBT, ANKRD7, SHPRH and HCRT) with biochemical and physiological effects relevant to feed efficiency and excreta traits might be interesting markers for future breeding. Meanwhile, functional enrichment analysis indicates that most of the significant pathways are associated with the glutathione catabolic process, DNA topological change and replication fork protection complex. This study reveals the architecture of excreta traits in commercial pigs and offers an opportunity for decreasing the pollution from excreta using genomic selection in pigs.
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Affiliation(s)
- Junjian Wang
- State Key Laboratory of animal Biotech Breeding, Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Huawei Yang
- Shenzhen Kingsino Technology Co., Ltd., 518107, Shenzhen, No.18 Guangdian North Rd, High-Tech Industrial Park, Guangming District, China
| | - Shaokang Chen
- Beijing General Station of Animal Husbandry, 100107, Beijing, China
| | - Weining Li
- State Key Laboratory of animal Biotech Breeding, Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Jian Yu
- State Key Laboratory of animal Biotech Breeding, Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Zhengzheng Hu
- State Key Laboratory of animal Biotech Breeding, Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Yue Zhuo
- State Key Laboratory of animal Biotech Breeding, Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Qianqian Huang
- State Key Laboratory of animal Biotech Breeding, Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Zhen Liu
- State Key Laboratory of animal Biotech Breeding, Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Lei Zhou
- State Key Laboratory of animal Biotech Breeding, Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Jianliang Wu
- Beijing Zhongyu Pig Breeding Co. Ltd., 100194, Beijing, China
| | - Zhaojun Wang
- Beijing Zhongyu Pig Breeding Co. Ltd., 100194, Beijing, China
| | - Feng Guo
- Beijing General Station of Animal Husbandry, 100107, Beijing, China
| | - Peng Yun
- Beijing General Station of Animal Husbandry, 100107, Beijing, China
| | - Xiaofeng Wang
- Beijing General Station of Animal Husbandry, 100107, Beijing, China
| | - Jian-Feng Liu
- State Key Laboratory of animal Biotech Breeding, Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture, College of Animal Science and Technology, China Agricultural University, Beijing, China
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23
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Nosková A, Mehrotra A, Kadri NK, Lloret-Villas A, Neuenschwander S, Hofer A, Pausch H. Comparison of two multi-trait association testing methods and sequence-based fine mapping of six additive QTL in Swiss Large White pigs. BMC Genomics 2023; 24:192. [PMID: 37038103 PMCID: PMC10084639 DOI: 10.1186/s12864-023-09295-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Accepted: 04/04/2023] [Indexed: 04/12/2023] Open
Abstract
BACKGROUND Genetic correlations between complex traits suggest that pleiotropic variants contribute to trait variation. Genome-wide association studies (GWAS) aim to uncover the genetic underpinnings of traits. Multivariate association testing and the meta-analysis of summary statistics from single-trait GWAS enable detecting variants associated with multiple phenotypes. In this study, we used array-derived genotypes and phenotypes for 24 reproduction, production, and conformation traits to explore differences between the two methods and used imputed sequence variant genotypes to fine-map six quantitative trait loci (QTL). RESULTS We considered genotypes at 44,733 SNPs for 5,753 pigs from the Swiss Large White breed that had deregressed breeding values for 24 traits. Single-trait association analyses revealed eleven QTL that affected 15 traits. Multi-trait association testing and the meta-analysis of the single-trait GWAS revealed between 3 and 6 QTL, respectively, in three groups of traits. The multi-trait methods revealed three loci that were not detected in the single-trait GWAS. Four QTL that were identified in the single-trait GWAS, remained undetected in the multi-trait analyses. To pinpoint candidate causal variants for the QTL, we imputed the array-derived genotypes to the sequence level using a sequenced reference panel consisting of 421 pigs. This approach provided genotypes at 16 million imputed sequence variants with a mean accuracy of imputation of 0.94. The fine-mapping of six QTL with imputed sequence variant genotypes revealed four previously proposed causal mutations among the top variants. CONCLUSIONS Our findings in a medium-size cohort of pigs suggest that multivariate association testing and the meta-analysis of summary statistics from single-trait GWAS provide very similar results. Although multi-trait association methods provide a useful overview of pleiotropic loci segregating in mapping populations, the investigation of single-trait association studies is still advised, as multi-trait methods may miss QTL that are uncovered in single-trait GWAS.
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Affiliation(s)
- A Nosková
- ETH Zürich, Universitätstrasse 2, 8092, Zürich, Switzerland.
| | - A Mehrotra
- ETH Zürich, Universitätstrasse 2, 8092, Zürich, Switzerland
| | - N K Kadri
- ETH Zürich, Universitätstrasse 2, 8092, Zürich, Switzerland
| | | | | | - A Hofer
- SUISAG, Allmend 10, 6204, Sempach, Switzerland
| | - H Pausch
- ETH Zürich, Universitätstrasse 2, 8092, Zürich, Switzerland
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24
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Han P, Wang C, Zhang W, Wu Y, Wang D, Zhao S, Zhu M. Pleiotropic architectures of porcine immune and growth trait pairs revealed by a self-product-based transcriptome method. Anim Genet 2023; 54:123-131. [PMID: 36478569 DOI: 10.1111/age.13282] [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: 07/06/2022] [Revised: 09/18/2022] [Accepted: 11/24/2022] [Indexed: 12/12/2022]
Abstract
Pleiotropy is an important biological phenomenon with complicated genetic architectures for multiple traits. To date, pleiotropy has been mainly identified by multi-trait genome-wide association studies, but this method has its disadvantages, and new developments for pleiotropy detection methods are needed. Here we define a novel metric, self-product, to measure individual-level co-variation of two traits, and develop a novel self-product-based transcriptome method to detect pleiotropic genes (PGs). Our method was tested using four immune-growth trait pairs and four immune-immune trait pairs in pigs. Comparative transcriptome analyses identified hundreds of candidate PGs related to eight trait pairs from two tails of self-product distribution. Gene Ontology enrichment analysis indicated that most of identified PGs were involved in immune- or growth-related biological processes. We established PG interaction networks to exhibit core genes shared by eight trait pairs, of which CCL5 and IL-10 genes were the hub genes. Genetic association analyses showed that SmaI-polymorphisms of CCL5 and IL-10 genes had significant associations with phenotypic co-variations of multiple trait pairs, indicating that the variants in pleiotropic genes were also pleiotropic variants. Taken together, the validity of our proposed method was preliminarily verified, and our findings provide new insights into the genetic basis of pleiotropic architectures of immune and growth trait pairs in pigs.
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Affiliation(s)
- Pingping Han
- Key Lab of Agricultural Animal Genetics, Breeding, and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan, China
| | - Chao Wang
- Key Lab of Agricultural Animal Genetics, Breeding, and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan, China
| | - Wei Zhang
- Key Lab of Agricultural Animal Genetics, Breeding, and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan, China
| | - Yalan Wu
- Key Lab of Agricultural Animal Genetics, Breeding, and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan, China
| | - Daoyuan Wang
- Key Lab of Agricultural Animal Genetics, Breeding, and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan, China
| | - Shuhong Zhao
- Key Lab of Agricultural Animal Genetics, Breeding, and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan, China.,The Cooperative Innovation Center for Sustainable Pig Production, Huazhong Agricultural University, Wuhan, China
| | - Mengjin Zhu
- Key Lab of Agricultural Animal Genetics, Breeding, and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan, China.,The Cooperative Innovation Center for Sustainable Pig Production, Huazhong Agricultural University, Wuhan, China
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25
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Identification of Candidate Genes and Functional Pathways Associated with Body Size Traits in Chinese Holstein Cattle Based on GWAS Analysis. Animals (Basel) 2023; 13:ani13060992. [PMID: 36978532 PMCID: PMC10044097 DOI: 10.3390/ani13060992] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2023] [Revised: 03/01/2023] [Accepted: 03/07/2023] [Indexed: 03/12/2023] Open
Abstract
Body size is one of the most economically important traits of dairy cattle, as it is significantly associated with cow longevity, production, health, fertility, and environmental adaptation. The identification and application of genetic variants using a novel genetic approach, such as genome-wide association studies (GWASs), may give more insights into the genetic architecture of complex traits. The identification of genes, single nucleotide polymorphisms (SNPs), and pathways associated with the body size traits may offer a contribution to genomic selection and long-term planning for selection in dairy cows. In this study, we performed GWAS analysis to identify the genetic markers and genes associated with four body size traits (body height, body depth, chest width, and angularity) in 1000 Chinese Holstein cows. We performed SNPs genotyping in 1000 individuals, based on the GeneSeek Genomic Profiler Bovine 100 K. In total, we identified 11 significant SNPs in association with body size traits at the threshold of Bonferroni correction (5.90 × 10−7) using the fixed and random model circulating probability unification (FarmCPU) model. Several genes within 200 kb distances (upstream or downstream) of the significant SNPs were identified as candidate genes, including MYH15, KHDRBS3, AIP, DCC, SQOR, and UBAP1L. Moreover, genes within 200 kb of the identified SNPs were significantly enriched (p ≤ 0.05) in 25 Gene Ontology terms and five Kyoto Encyclopedia of Genes and Genomes pathways. We anticipate that these results provide a foundation for understanding the genetic architecture of body size traits. They will also contribute to breeding programs and genomic selection work on Chinese Holstein cattle.
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26
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Porto-Neto LR, Alexandre PA, Hudson NJ, Bertram J, McWilliam SM, Tan AWL, Fortes MRS, McGowan MR, Hayes BJ, Reverter A. Multi-breed genomic predictions and functional variants for fertility of tropical bulls. PLoS One 2023; 18:e0279398. [PMID: 36701372 PMCID: PMC9879470 DOI: 10.1371/journal.pone.0279398] [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: 03/28/2022] [Accepted: 12/07/2022] [Indexed: 01/27/2023] Open
Abstract
Worldwide, most beef breeding herds are naturally mated. As such, the ability to identify and select fertile bulls is critically important for both productivity and genetic improvement. Here, we collected ten fertility-related phenotypes for 6,063 bulls from six tropically adapted breeds. Phenotypes were comprised of four bull conformation traits and six traits directly related to the quality of the bull's semen. We also generated high-density DNA genotypes for all the animals. In total, 680,758 single nucleotide polymorphism (SNP) genotypes were analyzed. The genomic correlation of the same trait observed in different breeds was positive for scrotal circumference and sheath score on most breed comparisons, but close to zero for the percentage of normal sperm, suggesting a divergent genetic background for this trait. We confirmed the importance of a breed being present in the reference population to the generation of accurate genomic estimated breeding values (GEBV) in an across-breed validation scenario. Average GEBV accuracies varied from 0.19 to 0.44 when the breed was not included in the reference population. The range improved to 0.28 to 0.59 when the breed was in the reference population. Variants associated with the gene HDAC4, six genes from the spermatogenesis-associated (SPATA) family of proteins, and 29 transcription factors were identified as candidate genes. Collectively these results enable very early in-life selection for bull fertility traits, supporting genetic improvement strategies currently taking place within tropical beef production systems. This study also improves our understanding of the molecular basis of male fertility in mammals.
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Affiliation(s)
| | | | - Nicholas J. Hudson
- School of Animal Studies, The University of Queensland, Gatton, QLD, Australia
| | - John Bertram
- Agriculture Consultant, Livestock Management and Breeding, Toowoomba, QLD, Australia
| | | | - Andre W. L. Tan
- School of Chemistry and Molecular Bioscience, The University of Queensland, St Lucia, QLD, Australia
| | - Marina R. S. Fortes
- School of Chemistry and Molecular Bioscience, The University of Queensland, St Lucia, QLD, Australia
| | - Michael R. McGowan
- School of Veterinary Sciences, The University of Queensland, Gatton, QLD, Australia
| | - Ben J. Hayes
- Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, St Lucia, QLD, Australia
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Kulminski AM, Feng F, Loiko E, Nazarian A, Loika Y, Culminskaya I. Prevailing Antagonistic Risks in Pleiotropic Associations with Alzheimer's Disease and Diabetes. J Alzheimers Dis 2023; 94:1121-1132. [PMID: 37355909 PMCID: PMC10666173 DOI: 10.3233/jad-230397] [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] [Indexed: 06/26/2023]
Abstract
BACKGROUND The lack of efficient preventive interventions against Alzheimer's disease (AD) calls for identifying efficient modifiable risk factors for AD. As diabetes shares many pathological processes with AD, including accumulation of amyloid plaques and neurofibrillary tangles, insulin resistance, and impaired glucose metabolism, diabetes is thought to be a potentially modifiable risk factor for AD. Mounting evidence suggests that links between AD and diabetes may be more complex than previously believed. OBJECTIVE To examine the pleiotropic architecture of AD and diabetes mellitus (DM). METHODS Univariate and pleiotropic analyses were performed following the discovery-replication strategy using individual-level data from 10 large-scale studies. RESULTS We report a potentially novel pleiotropic NOTCH2 gene, with a minor allele of rs5025718 associated with increased risks of both AD and DM. We confirm previously identified antagonistic associations of the same variants with the risks of AD and DM in the HLA and APOE gene clusters. We show multiple antagonistic associations of the same variants with AD and DM in the HLA cluster, which were not explained by the lead SNP in this cluster. Although the ɛ2 and ɛ4 alleles played a major role in the antagonistic associations with AD and DM in the APOE cluster, we identified non-overlapping SNPs in this cluster, which were adversely and beneficially associated with AD and DM independently of the ɛ2 and ɛ4 alleles. CONCLUSION This study emphasizes differences and similarities in the heterogeneous genetic architectures of AD and DM, which may differentiate the pathogenic mechanisms of these diseases.
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Affiliation(s)
- Alexander M Kulminski
- Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC, 27705, USA
| | - Fan Feng
- Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC, 27705, USA
| | - Elena Loiko
- Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC, 27705, USA
| | - Alireza Nazarian
- Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC, 27705, USA
| | - Yury Loika
- Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC, 27705, USA
| | - Irina Culminskaya
- Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC, 27705, USA
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28
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Xiong Z, Gao X, Chen Y, Feng Z, Pan S, Lu H, Uitterlinden AG, Nijsten T, Ikram A, Rivadeneira F, Ghanbari M, Wang Y, Kayser M, Liu F. Combining genome-wide association studies highlight novel loci involved in human facial variation. Nat Commun 2022; 13:7832. [PMID: 36539420 PMCID: PMC9767941 DOI: 10.1038/s41467-022-35328-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2022] [Accepted: 11/28/2022] [Indexed: 12/24/2022] Open
Abstract
Standard genome-wide association studies (GWASs) rely on analyzing a single trait at a time. However, many human phenotypes are complex and composed by multiple correlated traits. Here we introduce C-GWAS, a method for combining GWAS summary statistics of multiple potentially correlated traits. Extensive computer simulations demonstrated increased statistical power of C-GWAS compared to the minimal p-values of multiple single-trait GWASs (MinGWAS) and the current state-of-the-art method for combining single-trait GWASs (MTAG). Applying C-GWAS to a meta-analysis dataset of 78 single trait facial GWASs from 10,115 Europeans identified 56 study-wide suggestively significant loci with multi-trait effects on facial morphology of which 17 are novel loci. Using data from additional 13,622 European and Asian samples, 46 (82%) loci, including 9 (53%) novel loci, were replicated at nominal significance with consistent allele effects. Functional analyses further strengthen the reliability of our C-GWAS findings. Our study introduces the C-GWAS method and makes it available as computationally efficient open-source R package for widespread future use. Our work also provides insights into the genetic architecture of human facial appearance.
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Affiliation(s)
- Ziyi Xiong
- grid.5645.2000000040459992XDepartment of Genetic Identification, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands ,grid.5645.2000000040459992XDepartment of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Xingjian Gao
- grid.9227.e0000000119573309CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China ,grid.440259.e0000 0001 0115 7868National Clinical Research Center of Kidney Diseases, Jinling Hospital, Nanjing, Jiangsu China
| | - Yan Chen
- grid.5645.2000000040459992XDepartment of Genetic Identification, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands ,grid.9227.e0000000119573309CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China
| | - Zhanying Feng
- grid.9227.e0000000119573309CEMS, NCMIS, HCMS, MDIS, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China
| | - Siyu Pan
- grid.9227.e0000000119573309CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China
| | - Haojie Lu
- grid.5645.2000000040459992XDepartment of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands ,grid.5645.2000000040459992XDepartment of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Andre G. Uitterlinden
- grid.5645.2000000040459992XDepartment of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands ,grid.5645.2000000040459992XDepartment of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Tamar Nijsten
- grid.5645.2000000040459992XDepartment of Dermatology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Arfan Ikram
- grid.5645.2000000040459992XDepartment of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Fernando Rivadeneira
- grid.5645.2000000040459992XDepartment of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands ,grid.5645.2000000040459992XDepartment of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands ,grid.5645.2000000040459992XDepartment of Oral and Maxillofacial Surgery, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Mohsen Ghanbari
- grid.5645.2000000040459992XDepartment of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Yong Wang
- grid.9227.e0000000119573309CEMS, NCMIS, HCMS, MDIS, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China
| | - Manfred Kayser
- grid.5645.2000000040459992XDepartment of Genetic Identification, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Fan Liu
- grid.5645.2000000040459992XDepartment of Genetic Identification, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands ,grid.9227.e0000000119573309CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China
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Binversie EE, Momen M, Rosa GJM, Davis BW, Muir P. Across-breed genetic investigation of canine hip dysplasia, elbow dysplasia, and anterior cruciate ligament rupture using whole-genome sequencing. Front Genet 2022; 13:913354. [PMID: 36531249 PMCID: PMC9755188 DOI: 10.3389/fgene.2022.913354] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Accepted: 11/07/2022] [Indexed: 12/03/2022] Open
Abstract
Here, we report the use of genome-wide association study (GWAS) for the analysis of canine whole-genome sequencing (WGS) repository data using breed phenotypes. Single-nucleotide polymorphisms (SNPs) were called from WGS data from 648 dogs that included 119 breeds from the Dog10K Genomes Project. Next, we assigned breed phenotypes for hip dysplasia (Orthopedic Foundation for Animals (OFA) HD, n = 230 dogs from 27 breeds; hospital HD, n = 279 dogs from 38 breeds), elbow dysplasia (ED, n = 230 dogs from 27 breeds), and anterior cruciate ligament rupture (ACL rupture, n = 279 dogs from 38 breeds), the three most important canine spontaneous complex orthopedic diseases. Substantial morbidity is common with these diseases. Previous within- and between-breed GWAS for HD, ED, and ACL rupture using array SNPs have identified disease-associated loci. Individual disease phenotypes are lacking in repository data. There is a critical knowledge gap regarding the optimal approach to undertake categorical GWAS without individual phenotypes. We considered four GWAS approaches: a classical linear mixed model, a haplotype-based model, a binary case-control model, and a weighted least squares model using SNP average allelic frequency. We found that categorical GWAS was able to validate HD candidate loci. Additionally, we discovered novel candidate loci and genes for all three diseases, including FBX025, IL1A, IL1B, COL27A1, SPRED2 (HD), UGDH, FAF1 (ED), TGIF2 (ED & ACL rupture), and IL22, IL26, CSMD1, LDHA, and TNS1 (ACL rupture). Therefore, categorical GWAS of ancestral dog populations may contribute to the understanding of any disease for which breed epidemiological risk data are available, including diseases for which GWAS has not been performed and candidate loci remain elusive.
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Affiliation(s)
- Emily E. Binversie
- Comparative Orthopaedic and Genetics Research Laboratory, School of Veterinary Medicine, University of Wisconsin-Madison, Madison, WI, United States
| | - Mehdi Momen
- Comparative Orthopaedic and Genetics Research Laboratory, School of Veterinary Medicine, University of Wisconsin-Madison, Madison, WI, United States
| | - Guilherme J. M. Rosa
- Department of Animal and Dairy Sciences, College of Agricultural and Life Sciences, University of Wisconsin-Madison, Madison, WI, United States
| | - Brian W. Davis
- Department of Veterinary Integrative Biosciences, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX, United States
| | - Peter Muir
- Comparative Orthopaedic and Genetics Research Laboratory, School of Veterinary Medicine, University of Wisconsin-Madison, Madison, WI, United States,*Correspondence: Peter Muir,
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Martinez Boggio G, Meynadier A, Buitenhuis AJ, Marie-Etancelin C. Host genetic control on rumen microbiota and its impact on dairy traits in sheep. Genet Sel Evol 2022; 54:77. [PMID: 36434501 PMCID: PMC9694848 DOI: 10.1186/s12711-022-00769-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2022] [Accepted: 11/09/2022] [Indexed: 11/27/2022] Open
Abstract
BACKGROUND Milk yield and fine composition in sheep depend on the volatile and long-chain fatty acids, microbial proteins, vitamins produced through feedstuff digestion by the rumen microbiota. In cattle, the host genome has been shown to have a low to moderate genetic control on rumen microbiota abundance but a high control on dairy traits with heritabilities higher than 0.30. There is little information on the genetic correlations and quantitative trait loci (QTL) that simultaneously affect rumen microbiota abundance and dairy traits in ruminants, especially in sheep. Thus, our aim was to quantify the effect of the host genetics on rumen bacterial abundance and the genetic correlations between rumen bacterial abundance and several dairy traits, and to identify QTL that are associated with both rumen bacterial abundance and milk traits. RESULTS Our results in Lacaune sheep show that the heritability of rumen bacterial abundance ranges from 0 to 0.29 and that the heritability of 306 operational taxonomic units (OTU) is significantly different from 0. Of these 306 OTU, 96 that belong mainly to the Prevotellaceae, Lachnospiraceae and Ruminococcaceae bacterial families show strong genetic correlations with milk fatty acids and proteins (absolute values ranging from 0.33 to 0.99). Genome-wide association studies revealed a QTL for alpha-lactalbumin concentration in milk on Ovis aries chromosome (OAR) 11, and six QTL for rumen bacterial abundances i.e., for two OTU belonging to the genera Prevotella (OAR3 and 5), Rikeneleaceae_RC9_gut_group (OAR5), Ruminococcus (OAR5), an unknown genus of order Clostridia UCG-014 (OAR10), and CAG-352 (OAR11). None of these detected regions are simultaneously associated with rumen bacterial abundance and dairy traits, but the bacterial families Prevotellaceae, Lachnospiraceae and F082 show colocalized signals on OAR3, 5, 15 and 26. CONCLUSIONS In Lacaune dairy sheep, rumen microbiota abundance is partially controlled by the host genetics and is poorly genetically linked with milk protein and fatty acid compositions, and three main bacterial families, Prevotellaceae, Lachnospiraceae and F082, show specific associations with OAR3, 5, 15 and 26.
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Affiliation(s)
- Guillermo Martinez Boggio
- grid.508721.9GenPhySE, INRAE, ENVT, Université de Toulouse, 24 Chemin de Borde Rouge, 31326 Castanet-Tolosan, France
| | - Annabelle Meynadier
- grid.508721.9GenPhySE, INRAE, ENVT, Université de Toulouse, 24 Chemin de Borde Rouge, 31326 Castanet-Tolosan, France
| | - Albert Johannes Buitenhuis
- grid.7048.b0000 0001 1956 2722Center for Quantitative Genetics and Genomics, Aarhus University, Blichers Allé 20, 8830 Foulum, Denmark
| | - Christel Marie-Etancelin
- grid.508721.9GenPhySE, INRAE, ENVT, Université de Toulouse, 24 Chemin de Borde Rouge, 31326 Castanet-Tolosan, France
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Taraszka K, Zaitlen N, Eskin E. Leveraging pleiotropy for joint analysis of genome-wide association studies with per trait interpretations. PLoS Genet 2022; 18:e1010447. [PMID: 36342933 PMCID: PMC9671458 DOI: 10.1371/journal.pgen.1010447] [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: 02/28/2022] [Revised: 11/17/2022] [Accepted: 09/27/2022] [Indexed: 11/09/2022] Open
Abstract
We introduce pleiotropic association test (PAT) for joint analysis of multiple traits using genome-wide association study (GWAS) summary statistics. The method utilizes the decomposition of phenotypic covariation into genetic and environmental components to create a likelihood ratio test statistic for each genetic variant. Though PAT does not directly interpret which trait(s) drive the association, a per trait interpretation of the omnibus p-value is provided through an extension to the meta-analysis framework, m-values. In simulations, we show PAT controls the false positive rate, increases statistical power, and is robust to model misspecifications of genetic effect. Additionally, simulations comparing PAT to three multi-trait methods, HIPO, MTAG, and ASSET, show PAT identified 15.3% more omnibus associations over the next best method. When these associations were interpreted on a per trait level using m-values, PAT had 37.5% more true per trait interpretations with a 0.92% false positive assignment rate. When analyzing four traits from the UK Biobank, PAT discovered 22,095 novel variants. Through the m-values interpretation framework, the number of per trait associations for two traits were almost tripled and were nearly doubled for another trait relative to the original single trait GWAS.
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Affiliation(s)
- Kodi Taraszka
- Department of Computer Science, University of California, Los Angeles, California, United States of America
| | - Noah Zaitlen
- Department of Neurology, University of California, Los Angeles, California, United States of America
- Department of Computational Medicine, University of California, Los Angeles, California, United States of America
| | - Eleazar Eskin
- Department of Computer Science, University of California, Los Angeles, California, United States of America
- Department of Computational Medicine, University of California, Los Angeles, California, United States of America
- Department of Human Genetics, University of California, Los Angeles, California, United States of America
- * E-mail:
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32
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Bolormaa S, MacLeod IM, Khansefid M, Marett LC, Wales WJ, Miglior F, Baes CF, Schenkel FS, Connor EE, Manzanilla-Pech CIV, Stothard P, Herman E, Nieuwhof GJ, Goddard ME, Pryce JE. Sharing of either phenotypes or genetic variants can increase the accuracy of genomic prediction of feed efficiency. Genet Sel Evol 2022; 54:60. [PMID: 36068488 PMCID: PMC9450441 DOI: 10.1186/s12711-022-00749-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Accepted: 08/17/2022] [Indexed: 11/16/2022] Open
Abstract
Background Sharing individual phenotype and genotype data between countries is complex and fraught with potential errors, while sharing summary statistics of genome-wide association studies (GWAS) is relatively straightforward, and thus would be especially useful for traits that are expensive or difficult-to-measure, such as feed efficiency. Here we examined: (1) the sharing of individual cow data from international partners; and (2) the use of sequence variants selected from GWAS of international cow data to evaluate the accuracy of genomic estimated breeding values (GEBV) for residual feed intake (RFI) in Australian cows. Results GEBV for RFI were estimated using genomic best linear unbiased prediction (GBLUP) with 50k or high-density single nucleotide polymorphisms (SNPs), from a training population of 3797 individuals in univariate to trivariate analyses where the three traits were RFI phenotypes calculated using 584 Australian lactating cows (AUSc), 824 growing heifers (AUSh), and 2526 international lactating cows (OVE). Accuracies of GEBV in AUSc were evaluated by either cohort-by-birth-year or fourfold random cross-validations. GEBV of AUSc were also predicted using only the AUS training population with a weighted genomic relationship matrix constructed with SNPs from the 50k array and sequence variants selected from a meta-GWAS that included only international datasets. The genomic heritabilities estimated using the AUSc, OVE and AUSh datasets were moderate, ranging from 0.20 to 0.36. The genetic correlations (rg) of traits between heifers and cows ranged from 0.30 to 0.95 but were associated with large standard errors. The mean accuracies of GEBV in Australian cows were up to 0.32 and almost doubled when either overseas cows, or both overseas cows and AUS heifers were included in the training population. They also increased when selected sequence variants were combined with 50k SNPs, but with a smaller relative increase. Conclusions The accuracy of RFI GEBV increased when international data were used or when selected sequence variants were combined with 50k SNP array data. This suggests that if direct sharing of data is not feasible, a meta-analysis of summary GWAS statistics could provide selected SNPs for custom panels to use in genomic selection programs. However, since this finding is based on a small cross-validation study, confirmation through a larger study is recommended. Supplementary Information The online version contains supplementary material available at 10.1186/s12711-022-00749-z.
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Affiliation(s)
| | - Iona M MacLeod
- Agriculture Victoria Research, Agribio, Bundoora, VIC, 3083, Australia
| | - Majid Khansefid
- Agriculture Victoria Research, Agribio, Bundoora, VIC, 3083, Australia
| | - Leah C Marett
- Agriculture Victoria Research, Ellinbank Centre, Ellinbank, Gippsland, VIC, 3821, Australia.,School of Agriculture and Food, University of Melbourne, Parkville, VIC, 3010, Australia
| | - William J Wales
- Agriculture Victoria Research, Ellinbank Centre, Ellinbank, Gippsland, VIC, 3821, Australia.,School of Agriculture and Food, University of Melbourne, Parkville, VIC, 3010, Australia
| | - Filippo Miglior
- LACTANET, Sainte-Anne-de-Bellevue, QC, H9X 3R4, Canada.,CGIL, University of Guelph, Guelph, ON, N1G 2W1, Canada
| | - Christine F Baes
- CGIL, University of Guelph, Guelph, ON, N1G 2W1, Canada.,Institute of Genetics, Vetsuisse Faculty, University of Bern, 3002, Bern, Switzerland
| | | | - Erin E Connor
- Animal Genomics and Improvement Laboratory, USDA, Agricultural Research Service, Beltsville Agricultural Research Center, Beltsville, MD, 20705, USA.,Department of Animal and Food Sciences, University of Delaware, Newark, DE, 19716, USA
| | | | - Paul Stothard
- Faculty of Agricultural, Life & Environmental Sciences, University of Alberta, Edmonton, AB, T6G 2R3, Canada
| | - Emily Herman
- Faculty of Agricultural, Life & Environmental Sciences, University of Alberta, Edmonton, AB, T6G 2R3, Canada
| | - Gert J Nieuwhof
- Agriculture Victoria Research, Agribio, Bundoora, VIC, 3083, Australia.,DataGene Ltd, Agribio, Bundoora, VIC, 3083, Australia
| | - Michael E Goddard
- Agriculture Victoria Research, Agribio, Bundoora, VIC, 3083, Australia.,School of Veterinary and Agricultural Sciences, University of Melbourne, Parkville, VIC, 3052, Australia
| | - Jennie E Pryce
- Agriculture Victoria Research, Agribio, Bundoora, VIC, 3083, Australia.,School of Applied Systems Biology, La Trobe University, Bundoora, VIC, 3083, Australia
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Álvarez Cecco P, Rogberg Muñoz A, Balbi M, Bonamy M, Munilla S, Forneris NS, Peral García P, Cantet RJC, Giovambattista G, Fernández ME. Genome-wide scan for signatures of selection in the Brangus cattle genome. J Anim Breed Genet 2022; 139:679-694. [PMID: 35866697 DOI: 10.1111/jbg.12733] [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: 11/05/2021] [Accepted: 07/01/2022] [Indexed: 11/28/2022]
Abstract
Brangus is a composite cattle breed developed with the objective of combining the advantages of Angus and Zebuine breeds (Brahman, mainly) in tropical climates. The aim of this work was to estimate breed composition both genome-wide and locally, at the chromosome level, and to uncover genomic regions evidencing positive selection in the Argentinean Brangus population/nucleus. To do so, we analysed marker data from 478 animals, including Brangus, Angus and Brahman. Average breed composition was 35.0% ± 9.6% of Brahman, lower than expected according to the theoretical fractions deduced by the usual cross-breeding practice in this breed. Local ancestry analysis evidenced that breed composition varies between chromosomes, ranging from 19.6% for BTA26 to 56.1% for BTA5. Using approaches based on allelic frequencies and linkage disequilibrium, genomic regions with putative selection signatures were identified in several chromosomes (BTA1, BTA5, BTA6 and BTA14). These regions harbour genes involved in horn development, growth, lipid metabolism, reproduction and immune response. We argue that the overlapping of a chromosome segment originated in one of the parental breeds and over-represented in the sample with the location of a signature of selection constitutes evidence of a selection process that has occurred in the breed since its take off in the 1950s. In this regard, our results could contribute to the understanding of the genetic mechanisms involved in cross-bred cattle adaptation and productivity in tropical environments.
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Affiliation(s)
- Paulo Álvarez Cecco
- IGEVET - Instituto de Genética Veterinaria (UNLP - CONICET), Facultad de Ciencias Veterinarias, Universidad Nacional de La Plata, La Plata, Argentina
| | - Andrés Rogberg Muñoz
- Facultad de Agronomía, Universidad de Buenos Aires, Buenos Aires, Argentina.,INPA - Instituto de Investigaciones en Producción Animal (UBA - CONICET), Facultad de Ciencias Veterinarias, Universidad de Buenos Aires, Buenos Aires, Argentina
| | - Marianela Balbi
- IGEVET - Instituto de Genética Veterinaria (UNLP - CONICET), Facultad de Ciencias Veterinarias, Universidad Nacional de La Plata, La Plata, Argentina
| | - Martín Bonamy
- IGEVET - Instituto de Genética Veterinaria (UNLP - CONICET), Facultad de Ciencias Veterinarias, Universidad Nacional de La Plata, La Plata, Argentina
| | - Sebastián Munilla
- Facultad de Agronomía, Universidad de Buenos Aires, Buenos Aires, Argentina.,INPA - Instituto de Investigaciones en Producción Animal (UBA - CONICET), Facultad de Ciencias Veterinarias, Universidad de Buenos Aires, Buenos Aires, Argentina
| | - Natalia Soledad Forneris
- Facultad de Agronomía, Universidad de Buenos Aires, Buenos Aires, Argentina.,INPA - Instituto de Investigaciones en Producción Animal (UBA - CONICET), Facultad de Ciencias Veterinarias, Universidad de Buenos Aires, Buenos Aires, Argentina
| | - Pilar Peral García
- IGEVET - Instituto de Genética Veterinaria (UNLP - CONICET), Facultad de Ciencias Veterinarias, Universidad Nacional de La Plata, La Plata, Argentina
| | - Rodolfo Juan Carlos Cantet
- Facultad de Agronomía, Universidad de Buenos Aires, Buenos Aires, Argentina.,INPA - Instituto de Investigaciones en Producción Animal (UBA - CONICET), Facultad de Ciencias Veterinarias, Universidad de Buenos Aires, Buenos Aires, Argentina
| | - Guillermo Giovambattista
- IGEVET - Instituto de Genética Veterinaria (UNLP - CONICET), Facultad de Ciencias Veterinarias, Universidad Nacional de La Plata, La Plata, Argentina
| | - María Elena Fernández
- IGEVET - Instituto de Genética Veterinaria (UNLP - CONICET), Facultad de Ciencias Veterinarias, Universidad Nacional de La Plata, La Plata, Argentina
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Xu P, Li D, Wu Z, Ni L, Liu J, Tang Y, Yu T, Ren J, Zhao X, Huang M. An imputation-based genome-wide association study for growth and fatness traits in Sujiang pigs. Animal 2022; 16:100591. [PMID: 35872387 DOI: 10.1016/j.animal.2022.100591] [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: 12/23/2021] [Revised: 06/15/2022] [Accepted: 06/16/2022] [Indexed: 11/01/2022] Open
Abstract
Sujiang pigs are a synthetic breed derived from Jiangquhai, Fengjing, and Duroc pigs. In this study, we sequenced the genome of 62 pigs with a coverage depth of 10× to 20×, including 27 Sujiang and 35 founder breed pigs, and we collected 360 global pigs' genome sequence data from public databases including 39 Duroc pigs. We obtained a high-quality variant dataset of 365 Sujiang pigs by imputing the porcine 80 K single nucleotide polymorphism (SNP) Beadchip to the whole-genome scale with a total of 422 pigs as a reference panel. A dataset of 365 imputated Sujiang pigs was used to perform single-trait genome-wide association study (GWAS) and meta-analyses for growth and fatness traits. Single-trait GWAS identified 1 907, 18, and 14 SNPs surpassing the suggestively significant threshold for backfat thickness, chest circumference, and chest width, respectively. Meta-analyses identified 2 400 genome-wide significant SNPs and 520 suggestively significant SNPs for backfat thickness and chest circumference, and 719 genome-wide significant SNPs and 1 225 suggestively significant SNPs for all seven traits. According to the meta-analysis of backfat thickness and chest circumference, a remarkable region of 2.69 Mb on Sus scrofa chromosome 4 containing FAM110B, IMPAD1, LYN, MOS, PENK, PLAG1, SDR16C5 and XKR4 was identified as a candidate region. The haplotype heat map of the 2.69 Mb region verified that Sujiang pigs were derived from Duroc and Chinese indigenous pigs, especially Jiangquhai pigs. The Kruskal-Wallis test showed that haplotypes of the 2.69 Mb region significantly affected backfat thickness and chest circumference traits. We then focused on PLAG1, an important growth-related gene, and identified two synonymous SNPs with obvious differences among different breeds in the PLAG1 gene. We then performed genotyping of 365 Sujiang, 150 Duroc, 95 Jiangquhai, and 100 Fengjing pigs to confirm the above result and verified that the two variants significantly affected phenotypes of growth and fatness traits. Our findings not only provide insights into the genetic architecture of porcine growth and fatness traits but also provide potential markers for selective breeding of these traits in Sujiang pigs.
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Affiliation(s)
- Pan Xu
- School of Animal Science and Technology, Jiangsu Agri-animal Husbandry Vocational College, Taizhou, PR China
| | - Desen Li
- College of Animal Science, South China Agricultural University, Guangzhou, PR China
| | - Zhongping Wu
- Zhongkai University of Agriculture and Engineering, Guangzhou, PR China
| | - Ligang Ni
- School of Animal Science and Technology, Jiangsu Agri-animal Husbandry Vocational College, Taizhou, PR China
| | - Jiaxing Liu
- School of Animal Science and Technology, Jiangsu Agri-animal Husbandry Vocational College, Taizhou, PR China
| | - Ying Tang
- School of Animal Science and Technology, Jiangsu Agri-animal Husbandry Vocational College, Taizhou, PR China
| | - Tongshun Yu
- School of Animal Science and Technology, Jiangsu Agri-animal Husbandry Vocational College, Taizhou, PR China
| | - Jun Ren
- College of Animal Science, South China Agricultural University, Guangzhou, PR China
| | - Xuting Zhao
- School of Animal Science and Technology, Jiangsu Agri-animal Husbandry Vocational College, Taizhou, PR China
| | - Min Huang
- College of Animal Science, South China Agricultural University, Guangzhou, PR China.
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Smith JL, Wilson ML, Nilson SM, Rowan TN, Schnabel RD, Decker JE, Seabury CM. Genome-wide association and genotype by environment interactions for growth traits in U.S. Red Angus cattle. BMC Genomics 2022; 23:517. [PMID: 35842584 PMCID: PMC9287884 DOI: 10.1186/s12864-022-08667-6] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2021] [Accepted: 05/27/2022] [Indexed: 11/10/2022] Open
Abstract
Background Genotypic information produced from single nucleotide polymorphism (SNP) arrays has routinely been used to identify genomic regions associated with complex traits in beef and dairy cattle. Herein, we assembled a dataset consisting of 15,815 Red Angus beef cattle distributed across the continental U.S. and a union set of 836,118 imputed SNPs to conduct genome-wide association analyses (GWAA) for growth traits using univariate linear mixed models (LMM); including birth weight, weaning weight, and yearling weight. Genomic relationship matrix heritability estimates were produced for all growth traits, and genotype-by-environment (GxE) interactions were investigated. Results Moderate to high heritabilities with small standard errors were estimated for birth weight (0.51 ± 0.01), weaning weight (0.25 ± 0.01), and yearling weight (0.42 ± 0.01). GWAA revealed 12 pleiotropic QTL (BTA6, BTA14, BTA20) influencing Red Angus birth weight, weaning weight, and yearling weight which met a nominal significance threshold (P ≤ 1e-05) for polygenic traits using 836K imputed SNPs. Moreover, positional candidate genes associated with Red Angus growth traits in this study (i.e., LCORL, LOC782905, NCAPG, HERC6, FAM184B, SLIT2, MMRN1, KCNIP4, CCSER1, GRID2, ARRDC3, PLAG1, IMPAD1, NSMAF, PENK, LOC112449660, MOS, SH3PXD2B, STC2, CPEB4) were also previously associated with feed efficiency, growth, and carcass traits in beef cattle. Collectively, 14 significant GxE interactions were also detected, but were less consistent among the investigated traits at a nominal significance threshold (P ≤ 1e-05); with one pleiotropic GxE interaction detected on BTA28 (24 Mb) for Red Angus weaning weight and yearling weight. Conclusions Sixteen well-supported QTL regions detected from the GWAA and GxE GWAA for growth traits (birth weight, weaning weight, yearling weight) in U.S. Red Angus cattle were found to be pleiotropic. Twelve of these pleiotropic QTL were also identified in previous studies focusing on feed efficiency and growth traits in multiple beef breeds and/or their composites. In agreement with other beef cattle GxE studies our results implicate the role of vasodilation, metabolism, and the nervous system in the genetic sensitivity to environmental stress. Supplementary Information The online version contains supplementary material available at 10.1186/s12864-022-08667-6.
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Affiliation(s)
- Johanna L Smith
- Department of Veterinary Pathobiology, Texas A&M University, College Station, 77843, USA
| | - Miranda L Wilson
- Department of Veterinary Pathobiology, Texas A&M University, College Station, 77843, USA
| | - Sara M Nilson
- Division of Animal Sciences, University of Missouri, Columbia, 65211, USA
| | - Troy N Rowan
- Division of Animal Sciences, University of Missouri, Columbia, 65211, USA.,Genetics Area Program, University of Missouri, Columbia, 65211, USA
| | - Robert D Schnabel
- Division of Animal Sciences, University of Missouri, Columbia, 65211, USA.,Genetics Area Program, University of Missouri, Columbia, 65211, USA.,Informatics Institute, University of Missouri, Columbia, 65211, USA
| | - Jared E Decker
- Division of Animal Sciences, University of Missouri, Columbia, 65211, USA.,Genetics Area Program, University of Missouri, Columbia, 65211, USA.,Informatics Institute, University of Missouri, Columbia, 65211, USA
| | - Christopher M Seabury
- Department of Veterinary Pathobiology, Texas A&M University, College Station, 77843, USA.
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Mota LFM, Santos SWB, Júnior GAF, Bresolin T, Mercadante MEZ, Silva JAV, Cyrillo JNSG, Monteiro FM, Carvalheiro R, Albuquerque LG. Meta-analysis across Nellore cattle populations identifies common metabolic mechanisms that regulate feed efficiency-related traits. BMC Genomics 2022; 23:424. [PMID: 35672696 PMCID: PMC9172108 DOI: 10.1186/s12864-022-08671-w] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2021] [Accepted: 05/03/2022] [Indexed: 11/28/2022] Open
Abstract
Background Feed efficiency (FE) related traits play a key role in the economy and sustainability of beef cattle production systems. The accurate knowledge of the physiologic background for FE-related traits can help the development of more efficient selection strategies for them. Hence, multi-trait weighted GWAS (MTwGWAS) and meta-analyze were used to find genomic regions associated with average daily gain (ADG), dry matter intake (DMI), feed conversion ratio (FCR), feed efficiency (FE), and residual feed intake (RFI). The FE-related traits and genomic information belong to two breeding programs that perform the FE test at different ages: post-weaning (1,024 animals IZ population) and post-yearling (918 animals for the QLT population). Results The meta-analyze MTwGWAS identified 14 genomic regions (-log10(p -value) > 5) regions mapped on BTA 1, 2, 3, 4, 7, 8, 11, 14, 15, 18, 21, and 29. These regions explained a large proportion of the total genetic variance for FE-related traits across-population ranging from 20% (FCR) to 36% (DMI) in the IZ population and from 22% (RFI) to 28% (ADG) in the QLT population. Relevant candidate genes within these regions (LIPE, LPL, IGF1R, IGF1, IGFBP5, IGF2, INS, INSR, LEPR, LEPROT, POMC, NPY, AGRP, TGFB1, GHSR, JAK1, LYN, MOS, PLAG1, CHCD7, LCAT, and PLA2G15) highlighted that the physiological mechanisms related to neuropeptides and the metabolic signals controlling the body's energy balance are responsible for leading to greater feed efficiency. Integrated meta-analysis results and functional pathway enrichment analysis highlighted the major effect of biological functions linked to energy, lipid metabolism, and hormone signaling that mediates the effects of peptide signals in the hypothalamus and whole-body energy homeostasis affecting the genetic control of FE-related traits in Nellore cattle. Conclusions Genes and pathways associated with common signals for feed efficiency-related traits provide better knowledge about regions with biological relevance in physiological mechanisms associated with differences in energy metabolism and hypothalamus signaling. These pleiotropic regions would support the selection for feed efficiency-related traits, incorporating and pondering causal variations assigning prior weights in genomic selection approaches. Supplementary Information The online version contains supplementary material available at 10.1186/s12864-022-08671-w.
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Affiliation(s)
- Lucio F M Mota
- School of Agricultural and Veterinarian Sciences, São Paulo State University (UNESP), Jaboticabal - SP, São Paulo, 14884-900, Brazil.
| | - Samuel W B Santos
- School of Agricultural and Veterinarian Sciences, São Paulo State University (UNESP), Jaboticabal - SP, São Paulo, 14884-900, Brazil
| | - Gerardo A Fernandes Júnior
- School of Agricultural and Veterinarian Sciences, São Paulo State University (UNESP), Jaboticabal - SP, São Paulo, 14884-900, Brazil
| | - Tiago Bresolin
- School of Agricultural and Veterinarian Sciences, São Paulo State University (UNESP), Jaboticabal - SP, São Paulo, 14884-900, Brazil
| | - Maria E Z Mercadante
- Institute of Animal Science, Beef Cattle Research Center, Sertãozinho - SP, São Paulo, 14174-000, Brazil.,National Council for Science and Technological Development, Brasilia - DF, 71605-001, Brazil
| | - Josineudson A V Silva
- National Council for Science and Technological Development, Brasilia - DF, 71605-001, Brazil.,School of Veterinary Medicine and Animal Science, São Paulo State University (UNESP), Botucatu - SP, 18618-681, Brazil
| | - Joslaine N S G Cyrillo
- Institute of Animal Science, Beef Cattle Research Center, Sertãozinho - SP, São Paulo, 14174-000, Brazil
| | - Fábio M Monteiro
- Institute of Animal Science, Beef Cattle Research Center, Sertãozinho - SP, São Paulo, 14174-000, Brazil
| | - Roberto Carvalheiro
- School of Agricultural and Veterinarian Sciences, São Paulo State University (UNESP), Jaboticabal - SP, São Paulo, 14884-900, Brazil.,National Council for Science and Technological Development, Brasilia - DF, 71605-001, Brazil
| | - Lucia G Albuquerque
- School of Agricultural and Veterinarian Sciences, São Paulo State University (UNESP), Jaboticabal - SP, São Paulo, 14884-900, Brazil. .,National Council for Science and Technological Development, Brasilia - DF, 71605-001, Brazil.
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Jighly A, Benhajali H, Liu Z, Goddard ME. MetaGS: an accurate method to impute and combine SNP effects across populations using summary statistics. Genet Sel Evol 2022; 54:37. [PMID: 35655152 PMCID: PMC9164759 DOI: 10.1186/s12711-022-00725-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2021] [Accepted: 05/02/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Meta-analysis describes a category of statistical methods that aim at combining the results of multiple studies to increase statistical power by exploiting summary statistics. Different industries that use genomic prediction do not share their raw data due to logistic or privacy restrictions, which can limit the size of their reference populations and creates a need for a practical meta-analysis method. RESULTS We developed a meta-analysis, named MetaGS, that duplicates the results of multi-trait best linear unbiased prediction (mBLUP) analysis without accessing raw data. MetaGS exploits the correlations among different populations to produce more accurate population-specific single nucleotide polymorphism (SNP) effects. The method improves SNP effect estimations for a given population depending on its relations to other populations. MetaGS was tested on milk, fat and protein yield data of Australian Holstein and Jersey cattle and it generated very similar genomic estimated breeding values to those produced using the mBLUP method for all traits in both breeds. One of the major difficulties when combining SNP effects across populations is the use of different variants for the populations, which limits the applications of meta-analysis in practice. We solved this issue by developing a method to impute missing summary statistics without using raw data. Our results showed that imputing summary statistics can be done with high accuracy (r > 0.9) even when more than 70% of the SNPs were missing with a minimal effect on prediction accuracy. CONCLUSIONS We demonstrated that MetaGS can replace the mBLUP model when raw data cannot be shared, which can lead to more flexible collaborations compared to the single-trait BLUP model.
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Affiliation(s)
- Abdulqader Jighly
- Agriculture Victoria, AgriBio, Centre for AgriBiosciences, Bundoora, VIC, 3083, Australia.
| | - Haifa Benhajali
- Department of Animal Breeding and Genetics, Interbull Centre, Swedish University of Agricultural Sciences, Box 7023, 750 07, Uppsala, Sweden
| | - Zengting Liu
- IT Solutions for Animal Production (vit), Heinrich-Schroeder-Weg 1, 27283, Verden, Germany
| | - Mike E Goddard
- Agriculture Victoria, AgriBio, Centre for AgriBiosciences, Bundoora, VIC, 3083, Australia.,Faculty of Veterinary and Agricultural Science, University of Melbourne, Parkville, VIC, 3010, Australia
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Wolc A, Dekkers JCM. Application of Bayesian genomic prediction methods to genome-wide association analyses. Genet Sel Evol 2022; 54:31. [PMID: 35562659 PMCID: PMC9103490 DOI: 10.1186/s12711-022-00724-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Accepted: 04/27/2022] [Indexed: 11/19/2022] Open
Abstract
Background Bayesian genomic prediction methods were developed to simultaneously fit all genotyped markers to a set of available phenotypes for prediction of breeding values for quantitative traits, allowing for differences in the genetic architecture (distribution of marker effects) of traits. These methods also provide a flexible and reliable framework for genome-wide association (GWA) studies. The objective here was to review developments in Bayesian hierarchical and variable selection models for GWA analyses. Results By fitting all genotyped markers simultaneously, Bayesian GWA methods implicitly account for population structure and the multiple-testing problem of classical single-marker GWA. Implemented using Markov chain Monte Carlo methods, Bayesian GWA methods allow for control of error rates using probabilities obtained from posterior distributions. Power of GWA studies using Bayesian methods can be enhanced by using informative priors based on previous association studies, gene expression analyses, or functional annotation information. Applied to multiple traits, Bayesian GWA analyses can give insight into pleiotropic effects by multi-trait, structural equation, or graphical models. Bayesian methods can also be used to combine genomic, transcriptomic, proteomic, and other -omics data to infer causal genotype to phenotype relationships and to suggest external interventions that can improve performance. Conclusions Bayesian hierarchical and variable selection methods provide a unified and powerful framework for genomic prediction, GWA, integration of prior information, and integration of information from other -omics platforms to identify causal mutations for complex quantitative traits.
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Affiliation(s)
- Anna Wolc
- Department of Animal Science, Iowa State University, 806 Stange Road, 239 Kildee Hall, Ames, IA, 50010, USA.,Hy-Line International, 2583 240th Street, Dallas Center, IA, 50063, USA
| | - Jack C M Dekkers
- Department of Animal Science, Iowa State University, 806 Stange Road, 239 Kildee Hall, Ames, IA, 50010, USA.
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Chen SY, Schenkel FS, Melo ALP, Oliveira HR, Pedrosa VB, Araujo AC, Melka MG, Brito LF. Identifying pleiotropic variants and candidate genes for fertility and reproduction traits in Holstein cattle via association studies based on imputed whole-genome sequence genotypes. BMC Genomics 2022; 23:331. [PMID: 35484513 PMCID: PMC9052698 DOI: 10.1186/s12864-022-08555-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Accepted: 04/12/2022] [Indexed: 02/06/2023] Open
Abstract
Background Genetic progress for fertility and reproduction traits in dairy cattle has been limited due to the low heritability of most indicator traits. Moreover, most of the quantitative trait loci (QTL) and candidate genes associated with these traits remain unknown. In this study, we used 5.6 million imputed DNA sequence variants (single nucleotide polymorphisms, SNPs) for genome-wide association studies (GWAS) of 18 fertility and reproduction traits in Holstein cattle. Aiming to identify pleiotropic variants and increase detection power, multiple-trait analyses were performed using a method to efficiently combine the estimated SNP effects of single-trait GWAS based on a chi-square statistic. Results There were 87, 72, and 84 significant SNPs identified for heifer, cow, and sire traits, respectively, which showed a wide and distinct distribution across the genome, suggesting that they have relatively distinct polygenic nature. The biological functions of immune response and fatty acid metabolism were significantly enriched for the 184 and 124 positional candidate genes identified for heifer and cow traits, respectively. No known biological function was significantly enriched for the 147 positional candidate genes found for sire traits. The most important chromosomes that had three or more significant QTL identified are BTA22 and BTA23 for heifer traits, BTA8 and BTA17 for cow traits, and BTA4, BTA7, BTA17, BTA22, BTA25, and BTA28 for sire traits. Several novel and biologically important positional candidate genes were strongly suggested for heifer (SOD2, WTAP, DLEC1, PFKFB4, TRIM27, HECW1, DNAH17, and ADAM3A), cow (ANXA1, PCSK5, SPESP1, and JMJD1C), and sire (ELMO1, CFAP70, SOX30, DGCR8, SEPTIN14, PAPOLB, JMJD1C, and NELL2) traits. Conclusions These findings contribute to better understand the underlying biological mechanisms of fertility and reproduction traits measured in heifers, cows, and sires, which may contribute to improve genomic evaluation for these traits in dairy cattle. Supplementary Information The online version contains supplementary material available at 10.1186/s12864-022-08555-z.
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Affiliation(s)
- Shi-Yi Chen
- Department of Animal Sciences, Purdue University, 270 S. Russell Street, West Lafayette, IN, 47907-2041, USA.,Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, 611130, Sichuan, China
| | - Flavio S Schenkel
- Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, ON, N1G 2W1, Canada
| | - Ana L P Melo
- Department of Reproduction and Animal Evaluation, Rural Federal University of Rio de Janeiro, Seropédica, RJ, 23897-000, Brazil
| | - Hinayah R Oliveira
- Department of Animal Sciences, Purdue University, 270 S. Russell Street, West Lafayette, IN, 47907-2041, USA.,Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, ON, N1G 2W1, Canada
| | - Victor B Pedrosa
- Department of Animal Sciences, Purdue University, 270 S. Russell Street, West Lafayette, IN, 47907-2041, USA.,Department of Animal Sciences, State University of Ponta Grossa, Ponta Grossa, PR, 84030-900, Brazil
| | - Andre C Araujo
- Department of Animal Sciences, Purdue University, 270 S. Russell Street, West Lafayette, IN, 47907-2041, USA
| | - Melkaye G Melka
- Department of Animal and Food Science, University of Wisconsin River Falls, River Falls, WI, 54022, USA
| | - Luiz F Brito
- Department of Animal Sciences, Purdue University, 270 S. Russell Street, West Lafayette, IN, 47907-2041, USA. .,Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, ON, N1G 2W1, Canada.
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40
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Identification of Candidate Genes Regulating Carcass Depth and Hind Leg Circumference in Simmental Beef Cattle Using Illumina Bovine Beadchip and Next-Generation Sequencing Analyses. Animals (Basel) 2022; 12:ani12091103. [PMID: 35565529 PMCID: PMC9102740 DOI: 10.3390/ani12091103] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2022] [Revised: 04/14/2022] [Accepted: 04/21/2022] [Indexed: 12/27/2022] Open
Abstract
Genome-wide association studies are a robust means of identifying candidate genes that regulate economically important traits in farm animals. The aim of this study is to identify single-nucleotide polymorphisms (SNPs) and candidate genes potentially related to carcass depth and hind leg circumference in Simmental beef cattle. We performed Illumina Bovine HD Beadchip (~670 k SNPs) and next-generation sequencing (~12 million imputed SNPs) analyses of data from 1252 beef cattle, to which we applied a linear mixed model. Using a statistical threshold (p = 0.05/number of SNPs identified) and adopting a false discovery rate (FDR), we identified many putative SNPs on different bovine chromosomes. We identified 12 candidate genes potentially annotated with the markers identified, including CDKAL1 and E2F3, related to myogenesis and skeletal muscle development. The identification of such genes in Simmental beef cattle will help breeders to understand and improve related traits, such as meat yield.
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41
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An integrated framework for local genetic correlation analysis. Nat Genet 2022; 54:274-282. [PMID: 35288712 DOI: 10.1038/s41588-022-01017-y] [Citation(s) in RCA: 95] [Impact Index Per Article: 47.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2021] [Accepted: 01/20/2022] [Indexed: 12/16/2022]
Abstract
Genetic correlation (rg) analysis is used to identify phenotypes that may have a shared genetic basis. Traditionally, rg is studied globally, considering only the average of the shared signal across the genome, although this approach may fail when the rg is confined to particular genomic regions or in opposing directions at different loci. Current tools for local rg analysis are restricted to analysis of two phenotypes. Here we introduce LAVA, an integrated framework for local rg analysis that, in addition to testing the standard bivariate local rgs between two phenotypes, can evaluate local heritabilities and analyze conditional genetic relations between several phenotypes using partial correlation and multiple regression. Applied to 25 behavioral and health phenotypes, we show considerable heterogeneity in the bivariate local rgs across the genome, which is often masked by the global rg patterns, and demonstrate how our conditional approaches can elucidate more complex, multivariate genetic relations.
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42
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Mapel XM, Hiltpold M, Kadri NK, Witschi U, Pausch H. Bull fertility and semen quality are not correlated with dairy and production traits in Brown Swiss cattle. JDS COMMUNICATIONS 2022; 3:120-125. [PMID: 36339738 PMCID: PMC9623726 DOI: 10.3168/jdsc.2021-0164] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Accepted: 11/21/2021] [Indexed: 05/31/2023]
Abstract
Undisturbed reproduction is key for successful breeding of beef and dairy cattle. Improving reproductive ability can be difficult because of antagonistic relationships with other economically relevant traits. In cattle, thorough investigation of female fertility revealed unfavorable genetic correlations with various production phenotypes. However, the correlation between male reproductive ability and production traits remains poorly understood. Here, we investigated the genetic relationships among and between male fertility characteristics and economically relevant traits in a population of Brown Swiss cattle. We performed GWAS with imputed genotypes at nearly 12 million sequence variants for semen quality (sperm head and tail anomalies, motility, concentration, and volume), male fertility, and 57 production phenotypes. Allele substitution effects were then correlated on a trait-by-trait basis to estimate genetic correlations. Correlations between male reproductive characteristics and traits of economic value were small and ranged from -0.0681 to 0.0787. Among the semen quality parameters, sperm motility was negatively correlated with anomalies (head: r = -0.7083 ± 0.0002; tail: r = -0.7739 ± 0.0002) and volume (r = -0.1266 ± 0.0003), whereas volume was negatively correlated with concentration (r = -0.3503 ± 0.0002). Sire nonreturn rate was negatively correlated with sperm anomalies (head: r = -0.1640 ± 0.0002; tail: r = -0.1580 ± 0.0002) and positively correlated with motility (r = 0.1598 ± 0.0002). A meta-analysis of male reproductive traits identified 2 quantitative trait loci: a previously described region on chromosome 6 showed pleiotropic effects and a novel region on chromosome 11 was associated with sperm head anomalies. In conclusion, our results suggest that selection for economically important dairy and production phenotypes has little impact on semen quality and fertility of Brown Swiss bulls.
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Affiliation(s)
- Xena Marie Mapel
- Animal Genomics, ETH Zürich, Universitätsstrasse 2, 8006 Zürich, Switzerland
| | - Maya Hiltpold
- Animal Genomics, ETH Zürich, Universitätsstrasse 2, 8006 Zürich, Switzerland
| | - Naveen Kumar Kadri
- Animal Genomics, ETH Zürich, Universitätsstrasse 2, 8006 Zürich, Switzerland
| | - Ulrich Witschi
- Swissgenetics, Meielenfeldweg 12, 3052 Zollikofen, Switzerland
| | - Hubert Pausch
- Animal Genomics, ETH Zürich, Universitätsstrasse 2, 8006 Zürich, Switzerland
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Cheruiyot EK, Haile-Mariam M, Cocks BG, MacLeod IM, Mrode R, Pryce JE. Functionally prioritised whole-genome sequence variants improve the accuracy of genomic prediction for heat tolerance. Genet Sel Evol 2022; 54:17. [PMID: 35183109 PMCID: PMC8858496 DOI: 10.1186/s12711-022-00708-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2021] [Accepted: 02/03/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Heat tolerance is a trait of economic importance in the context of warm climates and the effects of global warming on livestock production, reproduction, health, and well-being. This study investigated the improvement in prediction accuracy for heat tolerance when selected sets of sequence variants from a large genome-wide association study (GWAS) were combined with a standard 50k single nucleotide polymorphism (SNP) panel used by the dairy industry. METHODS Over 40,000 dairy cattle with genotype and phenotype data were analysed. The phenotypes used to measure an individual's heat tolerance were defined as the rate of decline in milk production traits with rising temperature and humidity. We used Holstein and Jersey cows to select sequence variants linked to heat tolerance. The prioritised sequence variants were the most significant SNPs passing a GWAS p-value threshold selected based on sliding 100-kb windows along each chromosome. We used a bull reference set to develop the genomic prediction equations, which were then validated in an independent set of Holstein, Jersey, and crossbred cows. Prediction analyses were performed using the BayesR, BayesRC, and GBLUP methods. RESULTS The accuracy of genomic prediction for heat tolerance improved by up to 0.07, 0.05, and 0.10 units in Holstein, Jersey, and crossbred cows, respectively, when sets of selected sequence markers from Holstein cows were added to the 50k SNP panel. However, in some scenarios, the prediction accuracy decreased unexpectedly with the largest drop of - 0.10 units for the heat tolerance fat yield trait observed in Jersey cows when 50k plus pre-selected SNPs from Holstein cows were used. Using pre-selected SNPs discovered on a combined set of Holstein and Jersey cows generally improved the accuracy, especially in the Jersey validation. In addition, combining Holstein and Jersey bulls in the reference set generally improved prediction accuracy in most scenarios compared to using only Holstein bulls as the reference set. CONCLUSIONS Informative sequence markers can be prioritised to improve the genomic prediction of heat tolerance in different breeds. In addition to providing biological insight, these variants could also have a direct application for developing customized SNP arrays or can be used via imputation in current industry SNP panels.
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Affiliation(s)
- Evans K Cheruiyot
- School of Applied Systems Biology, La Trobe University, Bundoora, VIC, 3083, Australia.,Agriculture Victoria Research, AgriBio, Centre for AgriBiosciences, Bundoora, VIC, 3083, Australia
| | - Mekonnen Haile-Mariam
- Agriculture Victoria Research, AgriBio, Centre for AgriBiosciences, Bundoora, VIC, 3083, Australia.
| | - Benjamin G Cocks
- School of Applied Systems Biology, La Trobe University, Bundoora, VIC, 3083, Australia.,Agriculture Victoria Research, AgriBio, Centre for AgriBiosciences, Bundoora, VIC, 3083, Australia
| | - Iona M MacLeod
- Agriculture Victoria Research, AgriBio, Centre for AgriBiosciences, Bundoora, VIC, 3083, Australia
| | - Raphael Mrode
- International Livestock Research Institute, Nairobi, Kenya.,Scotland's Rural College, Edinburgh, UK
| | - Jennie E Pryce
- School of Applied Systems Biology, La Trobe University, Bundoora, VIC, 3083, Australia.,Agriculture Victoria Research, AgriBio, Centre for AgriBiosciences, Bundoora, VIC, 3083, Australia
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44
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Kulminski AM, Loiko E, Loika Y, Culminskaya I. Pleiotropic predisposition to Alzheimer's disease and educational attainment: insights from the summary statistics analysis. GeroScience 2022; 44:265-280. [PMID: 34743297 PMCID: PMC8572080 DOI: 10.1007/s11357-021-00484-1] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2021] [Accepted: 10/28/2021] [Indexed: 12/25/2022] Open
Abstract
Epidemiological studies report beneficial associations of higher educational attainment (EDU) with Alzheimer's disease (AD). Prior genome-wide association studies (GWAS) also reported variants associated with AD and EDU separately. The analysis of pleiotropic associations with these phenotypes may shed light on EDU-related protection against AD. We performed pleiotropic meta-analyses using Fisher's method and omnibus test applied to summary statistics for single nucleotide polymorphisms (SNPs) associated with AD and EDU in large-scale univariate GWAS at suggestive-effect (5 × 10-8 < p < 0.1) and genome-wide (p ≤ 5 × 10-8) significance levels. We report 53 SNPs that attained p ≤ 5 × 10-8 at least in one of the pleiotropic meta-analyses and were reported in the univariate GWAS at 5 × 10-8 < p < 0.1. Of them, there were 46 pleiotropic SNPs according to Fisher's method. Additionally, Fisher's method identified 25 of 206 SNPs with pleiotropic effects, which attained p ≤ 5 × 10-8 in the univariate GWAS. We showed that a large fraction of the pleiotropic associations was affected by a counterintuitive phenomenon of antagonistic genetic heterogeneity, which explains the increase, rather than decrease, of the significance of the pleiotropic associations in the omnibus test. Functional enrichment analysis showed that apart from cancers, gene set harboring the non-pleiotropic SNPs was characterized by late-onset AD and neurodevelopmental disorders. The pleiotropic gene set was characterized by a broad spectrum of progressive neurological and neuromuscular diseases and immune-mediated conditions, including progressive motor neuropathy, multiple sclerosis, Parkinson's disease, and severe AD. Our results suggest that disentangling genes harboring variants with and without pleiotropic associations with AD and EDU is promising for dissecting heterogeneity in biological mechanisms of AD.
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Affiliation(s)
- Alexander M Kulminski
- Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC, 27708-0408, USA.
| | - Elena Loiko
- Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC, 27708-0408, USA
| | - Yury Loika
- Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC, 27708-0408, USA
| | - Irina Culminskaya
- Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC, 27708-0408, USA
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45
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Sustainable Intensification of Beef Production in the Tropics: The Role of Genetically Improving Sexual Precocity of Heifers. Animals (Basel) 2022; 12:ani12020174. [PMID: 35049797 PMCID: PMC8772995 DOI: 10.3390/ani12020174] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2021] [Revised: 01/07/2022] [Accepted: 01/08/2022] [Indexed: 12/16/2022] Open
Abstract
Simple Summary Tropical pasture-based beef production systems play a vital role in global food security. The importance of promoting sustainable intensification of such systems has been debated worldwide. Demand for beef is growing together with concerns over the impact of its production on the environment. Implementing sustainable livestock intensification programs relies on animal genetic improvement. In tropical areas, the lack of sexual precocity is a bottleneck for cattle efficiency, directly impacting the sustainability of production systems. In the present review we present and discuss the state of the art of genetic evaluation for sexual precocity in Bos indicus beef cattle, covering the definition of measurable traits, genetic parameter estimates, genomic analyses, and a case study of selection for sexual precocity in Nellore breeding programs. Abstract Increasing productivity through continued animal genetic improvement is a crucial part of implementing sustainable livestock intensification programs. In Zebu cattle, the lack of sexual precocity is one of the main obstacles to improving beef production efficiency. Puberty-related traits are complex, but large-scale data sets from different “omics” have provided information on specific genes and biological processes with major effects on the expression of such traits, which can greatly increase animal genetic evaluation. In addition, genetic parameter estimates and genomic predictions involving sexual precocity indicator traits and productive, reproductive, and feed-efficiency related traits highlighted the feasibility and importance of direct selection for anticipating heifer reproductive life. Indeed, the case study of selection for sexual precocity in Nellore breeding programs presented here show that, in 12 years of selection for female early precocity and improved management practices, the phenotypic means of age at first calving showed a strong decreasing trend, changing from nearly 34 to less than 28 months, with a genetic trend of almost −2 days/year. In this period, the percentage of early pregnancy in the herds changed from around 10% to more than 60%, showing that the genetic improvement of heifer’s sexual precocity allows optimizing the productive cycle by reducing the number of unproductive animals in the herd. It has a direct impact on sustainability by better use of resources. Genomic selection breeding programs accounting for genotype by environment interaction represent promising tools for accelerating genetic progress for sexual precocity in tropical beef cattle.
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46
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Fonseca PADS, Caldwell T, Mandell I, Wood K, Cánovas A. Genome-wide association study for meat tenderness in beef cattle identifies patterns of the genetic contribution in different post-mortem stages. Meat Sci 2022; 186:108733. [PMID: 35007800 DOI: 10.1016/j.meatsci.2022.108733] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2021] [Revised: 01/01/2022] [Accepted: 01/03/2022] [Indexed: 12/13/2022]
Abstract
The beef tenderization process during the post-mortem period is one of the most important sensorial attributes and it is well-established. The aim of this study was to identify the genetic contribution pattern to meat tenderness at 7-(LMD7), 14-(LMD14), and 21-(LMD21) days post-mortem. The heritabilities for LMD7 (0.194), LMD14 (0.142) and LMD21 (0.048) are well established in the population evaluated here. However, its genetic contribution in terms of genomic candidate regions is still poorly understood. Tenderness was measured in the Longissiums thoracis using Warner-Bratzler shear force in the three post-mortem periods. A total of 4323 crossbred beef cattle were phenotyped and genotyped using the Illumina BovineSNP50K. The percentage of the total genetic variance was estimated using the weighted single-step genomic best linear unbiased prediction method. The main candidate windows for LMD7 were associated with proteolysis of myofibrillar structures and the weakening endomysium and perimysium. Candidate windows for LMD14 and LMD21 were mapped in bovine QTLs for body composition, height and growth. Results presented herein highlight, the largest contribution of proteolysis related processes before 14-days post-mortem and body composition characteristics in later stages for meat tenderness.
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Affiliation(s)
- Pablo Augusto de Souza Fonseca
- Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, Ontario N1G 2W1, Canada
| | - Tim Caldwell
- Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, Ontario N1G 2W1, Canada
| | - Ira Mandell
- Centre for Nutrition Modelling, Department of Animal Biosciences, University of Guelph, Guelph, Ontario N1G 2W1, Canada
| | - Katharine Wood
- Centre for Nutrition Modelling, Department of Animal Biosciences, University of Guelph, Guelph, Ontario N1G 2W1, Canada
| | - Angela Cánovas
- Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, Ontario N1G 2W1, Canada.
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47
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Joukhadar R, Daetwyler HD. Data Integration, Imputation, and Meta-analysis for Genome-Wide Association Studies. Methods Mol Biol 2022; 2481:173-183. [PMID: 35641765 DOI: 10.1007/978-1-0716-2237-7_11] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Growing genomic and phenotypic datasets require different groups around the world to collaborate and integrate these valuable resources to maximize their benefit and increase reference population sizes for genomic prediction and genome-wide association studies (GWAS). However, different studies use different genotyping techniques which requires a synchronizing step for the genotyped variants called "imputation" before combining them. Optimally, different GWAS datasets can be analysed within a meta-analysis, which recruits summary statistics instead of actual data. This chapter describes the general principles for genotypic imputation and meta-GWAS analysis with a description of study designs and command lines required for such analyses.
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Affiliation(s)
- Reem Joukhadar
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC, Australia
| | - Hans D Daetwyler
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC, Australia.
- School of Applied Systems Biology, La Trobe University, Bundoora, VIC, Australia.
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48
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Huang C, Butterly CR, Moody D, Pourkheirandish M. Mini review: Targeting below-ground plant performance to improve nitrogen use efficiency (NUE) in barley. Front Genet 2022; 13:1060304. [PMID: 36935938 PMCID: PMC10017981 DOI: 10.3389/fgene.2022.1060304] [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: 10/03/2022] [Accepted: 12/19/2022] [Indexed: 03/06/2023] Open
Abstract
Nitrogen (N) fertilizer is one of the major inputs for grain crops including barley and its usage is increasing globally. However, N use efficiency (NUE) is low in cereal crops, leading to higher production costs, unfulfilled grain yield potential and environmental hazards. N uptake is initiated from plant root tips but a very limited number of studies have been conducted on roots relevant to NUE specifically. In this review, we used barley, the fourth most important cereal crop, as the primary study plant to investigate this topic. We first highlighted the recent progress and study gaps in genetic analysis results, primarily, the genome-wide association study (GWAS) regarding both biological and statistical considerations. In addition, different factors contributing to NUE are discussed in terms of root morphological and anatomical traits, as well as physiological mechanisms such as N transporter activities and hormonal regulation.
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Affiliation(s)
- Claire Huang
- Faculty of Veterinary and Agricultural Sciences, The University of Melbourne, Melbourne, VIC, Australia
| | - Clayton R. Butterly
- Faculty of Veterinary and Agricultural Sciences, The University of Melbourne, Melbourne, VIC, Australia
- *Correspondence: Clayton R. Butterly, ; Mohammad Pourkheirandish,
| | - David Moody
- InterGrain Pty Ltd., Bibra Lake, WA, Australia
| | - Mohammad Pourkheirandish
- Faculty of Veterinary and Agricultural Sciences, The University of Melbourne, Melbourne, VIC, Australia
- *Correspondence: Clayton R. Butterly, ; Mohammad Pourkheirandish,
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49
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Abstract
With the advancements in next-generation sequencing technologies, leading to millions of single nucleotide polymorphisms in all crop species including wheat, genome-wide association study (GWAS) has become a leading approach for trait dissection. In wheat, GWAS has been conducted for a plethora of traits and more and more studies are being conducted and reported in journals. While application of GWAS has become a routine in wheat using the standardized approaches, there has been a great leap forward using newer models and combination of GWAS with other sets of data. This chapter has reviewed all these latest advancements in GWAS in wheat by citing the most important studies and their outputs. Specially, we have focused on studies that conducted meta-GWAS, multilocus GWAS, haplotype-based GWAS, Environmental- and Eigen-GWAS, and/or GWAS combined with gene regulatory network and pathway analyses or epistatic interactions analyses; all these have taken the association mapping approach to new heights in wheat.
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Affiliation(s)
- Deepmala Sehgal
- International Maize and Wheat Improvement Center (CIMMYT), Carretera Mex-Veracruz, Texcoco, CP, Mexico.
| | - Susanne Dreisigacker
- International Maize and Wheat Improvement Center (CIMMYT), Carretera Mex-Veracruz, Texcoco, CP, Mexico.
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50
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Schiavo G, Bovo S, Ribani A, Moscatelli G, Bonacini M, Prandi M, Mancin E, Mantovani R, Dall'Olio S, Fontanesi L. Comparative analysis of inbreeding parameters and runs of homozygosity islands in 2 Italian autochthonous cattle breeds mainly raised in the Parmigiano-Reggiano cheese production region. J Dairy Sci 2021; 105:2408-2425. [PMID: 34955250 DOI: 10.3168/jds.2021-20915] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Accepted: 10/25/2021] [Indexed: 01/19/2023]
Abstract
Reggiana and Modenese are autochthonous cattle breeds, reared in the North of Italy, that can be mainly distinguished for their standard coat color (Reggiana is red, whereas Modenese is white with some pale gray shades). Almost all milk produced by these breeds is transformed into 2 mono-breed branded Parmigiano-Reggiano cheeses, from which farmers receive the economic incomes needed for the sustainable conservation of these animal genetic resources. After the setting up of their herd books in 1960s, these breeds experienced a strong reduction in the population size that was subsequently reverted starting in the 1990s (Reggiana) or more recently (Modenese) reaching at present a total of about 2,800 and 500 registered cows, respectively. Due to the small population size of these breeds, inbreeding is a very important cause of concern for their conservation programs. Inbreeding is traditionally estimated using pedigree data, which are summarized in an inbreeding coefficient calculated at the individual level (FPED). However, incompleteness of pedigree information and registration errors can affect the effectiveness of conservation strategies. High-throughput SNP genotyping platforms allow investigation of inbreeding using genome information that can overcome the limits of pedigree data. Several approaches have been proposed to estimate genomic inbreeding, with the use of runs of homozygosity (ROH) considered to be the more appropriate. In this study, several pedigree and genomic inbreeding parameters, calculated using the whole herd book populations or considering genotyping information (GeneSeek GGP Bovine 150K) from 1,684 Reggiana cattle and 323 Modenese cattle, were compared. Average inbreeding values per year were used to calculate effective population size. Reggiana breed had generally lower genomic inbreeding values than Modenese breed. The low correlation between pedigree-based and genomic-based parameters (ranging from 0.187 to 0.195 and 0.319 to 0.323 in the Reggiana and Modenese breeds, respectively) reflected the common problems of local populations in which pedigree records are not complete. The high proportion of short ROH over the total number of ROH indicates no major recent inbreeding events in both breeds. ROH islands spread over the genome of the 2 breeds (15 in Reggiana and 14 in Modenese) identified several signatures of selection. Some of these included genes affecting milk production traits, stature, body conformation traits (with a main ROH island in both breeds on BTA6 containing the ABCG2, NCAPG, and LCORL genes) and coat color (on BTA13 in Modenese containing the ASIP gene). In conclusion, this work provides an extensive comparative analysis of pedigree and genomic inbreeding parameters and relevant genomic information that will be useful in the conservation strategies of these 2 iconic local cattle breeds.
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Affiliation(s)
- Giuseppina Schiavo
- Department of Agricultural and Food Sciences, Division of Animal Sciences, University of Bologna, Viale Giuseppe Fanin 46, 40127 Bologna, Italy
| | - Samuele Bovo
- Department of Agricultural and Food Sciences, Division of Animal Sciences, University of Bologna, Viale Giuseppe Fanin 46, 40127 Bologna, Italy
| | - Anisa Ribani
- Department of Agricultural and Food Sciences, Division of Animal Sciences, University of Bologna, Viale Giuseppe Fanin 46, 40127 Bologna, Italy
| | - Giulia Moscatelli
- Department of Agricultural and Food Sciences, Division of Animal Sciences, University of Bologna, Viale Giuseppe Fanin 46, 40127 Bologna, Italy
| | - Massimo Bonacini
- Associazione Nazionale Allevatori Bovini di Razza Reggiana (ANABORARE), Via Masaccio 11, 42124 Reggio Emilia, Italy
| | - Marco Prandi
- Associazione Nazionale Allevatori Bovini di Razza Reggiana (ANABORARE), Via Masaccio 11, 42124 Reggio Emilia, Italy
| | - Enrico Mancin
- Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, Viale dell'Università 16, 35020 Legnaro (PD), Italy
| | - Roberto Mantovani
- Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, Viale dell'Università 16, 35020 Legnaro (PD), Italy
| | - Stefania Dall'Olio
- Department of Agricultural and Food Sciences, Division of Animal Sciences, University of Bologna, Viale Giuseppe Fanin 46, 40127 Bologna, Italy
| | - Luca Fontanesi
- Department of Agricultural and Food Sciences, Division of Animal Sciences, University of Bologna, Viale Giuseppe Fanin 46, 40127 Bologna, Italy.
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