Genome-wide association analysis and genomic prediction of Mycobacterium avium subspecies paratuberculosis infection in US Jersey cattle
Paratuberculosis (Johne's disease), an enteric disorder in ruminants caused by Mycobacterium avium subspecies paratuberculosis (MAP), causes economic losses in excess of $200 million annually to the US dairy industry. To identify genomic regions underlying susceptibility to MAP infection in Jer...
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| description | Paratuberculosis (Johne's disease), an enteric disorder in ruminants caused by Mycobacterium avium subspecies paratuberculosis (MAP), causes economic losses in excess of $200 million annually to the US dairy industry. To identify genomic regions underlying susceptibility to MAP infection in Jersey cattle, a case-control genome-wide association study (GWAS) was performed. Blood and fecal samples were collected from ∼ 5,000 mature cows in 30 commercial Jersey herds from across the US. Discovery data consisted of 450 cases and 439 controls genotyped with the Illumina BovineSNP50 BeadChip. Cases were animals with positive ELISA and fecal culture (FC) results. Controls were animals negative to both ELISA and FC tests that matched cases on birth date and herd. Validation data consisted of 180 animals including 90 cases (positive to FC) and 90 controls (negative to ELISA and FC), selected from discovery herds and genotyped by Illumina BovineLD BeadChip (∼ 7K SNPs). Two analytical approaches were used: single-marker GWAS using the GRAMMAR-GC method and Bayesian variable selection (Bayes C) using GenSel software. GRAMMAR-GC identified one SNP on BTA7 at 68 megabases (Mb) surpassing a significance threshold of 5 × 10(-5). ARS-BFGL-NGS-11887 on BTA23 (27.7 Mb) accounted for the highest percentage of genetic variance (3.3%) in the Bayes C analysis. SNPs identified in common by GRAMMAR-GC and Bayes C in both discovery and combined data were mapped to BTA23 (27, 29 and 44 Mb), 3 (100, 101, 106 and 107 Mb) and 17 (57 Mb). Correspondence between results of GRAMMAR-GC and Bayes C was high (70-80% of most significant SNPs in common). These SNPs could potentially be associated with causal variants underlying susceptibility to MAP infection in Jersey cattle. Predictive performance of the model developed by Bayes C for prediction of infection status of animals in validation set was low (55% probability of correct ranking of paired case and control samples). |
| doi_str_mv | 10.1371/journal.pone.0088380 |
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To identify genomic regions underlying susceptibility to MAP infection in Jersey cattle, a case-control genome-wide association study (GWAS) was performed. Blood and fecal samples were collected from ∼ 5,000 mature cows in 30 commercial Jersey herds from across the US. Discovery data consisted of 450 cases and 439 controls genotyped with the Illumina BovineSNP50 BeadChip. Cases were animals with positive ELISA and fecal culture (FC) results. Controls were animals negative to both ELISA and FC tests that matched cases on birth date and herd. Validation data consisted of 180 animals including 90 cases (positive to FC) and 90 controls (negative to ELISA and FC), selected from discovery herds and genotyped by Illumina BovineLD BeadChip (∼ 7K SNPs). Two analytical approaches were used: single-marker GWAS using the GRAMMAR-GC method and Bayesian variable selection (Bayes C) using GenSel software. GRAMMAR-GC identified one SNP on BTA7 at 68 megabases (Mb) surpassing a significance threshold of 5 × 10(-5). ARS-BFGL-NGS-11887 on BTA23 (27.7 Mb) accounted for the highest percentage of genetic variance (3.3%) in the Bayes C analysis. SNPs identified in common by GRAMMAR-GC and Bayes C in both discovery and combined data were mapped to BTA23 (27, 29 and 44 Mb), 3 (100, 101, 106 and 107 Mb) and 17 (57 Mb). Correspondence between results of GRAMMAR-GC and Bayes C was high (70-80% of most significant SNPs in common). These SNPs could potentially be associated with causal variants underlying susceptibility to MAP infection in Jersey cattle. Predictive performance of the model developed by Bayes C for prediction of infection status of animals in validation set was low (55% probability of correct ranking of paired case and control samples).</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0088380</identifier><identifier>PMID: 24523889</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Agriculture ; Analysis ; Animal sciences ; Animals ; Association analysis ; Bacterial infections ; Bayes Theorem ; Bayesian analysis ; Biology ; Bovidae ; Cattle ; Crohn's disease ; Crohns disease ; Dairy cattle ; Dairy industry ; Databases, Genetic ; Disease susceptibility ; Economic impact ; Enzyme-Linked Immunosorbent Assay ; Feces ; Gene expression ; Genetic diversity ; Genetic Predisposition to Disease ; Genetic variance ; Genetic Variation ; Genome-wide association studies ; Genome-Wide Association Study ; Genomes ; Genomics ; Genotype ; Health aspects ; Infection ; Infections ; Inflammatory bowel disease ; Johne's disease ; Language ; Life sciences ; Medical research ; Mycobacterium avium ; Mycobacterium avium - genetics ; Oligonucleotide Array Sequence Analysis ; Paratuberculosis ; Paratuberculosis - diagnosis ; Paratuberculosis - genetics ; Performance prediction ; Polymorphism, Single Nucleotide ; Population ; Single-nucleotide polymorphism ; Software ; United States ; Veterinary colleges ; Veterinary medicine ; Veterinary Science</subject><ispartof>PloS one, 2014-02, Vol.9 (2), p.e88380-e88380</ispartof><rights>COPYRIGHT 2014 Public Library of Science</rights><rights>2014 Zare et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. 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To identify genomic regions underlying susceptibility to MAP infection in Jersey cattle, a case-control genome-wide association study (GWAS) was performed. Blood and fecal samples were collected from ∼ 5,000 mature cows in 30 commercial Jersey herds from across the US. Discovery data consisted of 450 cases and 439 controls genotyped with the Illumina BovineSNP50 BeadChip. Cases were animals with positive ELISA and fecal culture (FC) results. Controls were animals negative to both ELISA and FC tests that matched cases on birth date and herd. Validation data consisted of 180 animals including 90 cases (positive to FC) and 90 controls (negative to ELISA and FC), selected from discovery herds and genotyped by Illumina BovineLD BeadChip (∼ 7K SNPs). Two analytical approaches were used: single-marker GWAS using the GRAMMAR-GC method and Bayesian variable selection (Bayes C) using GenSel software. 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Predictive performance of the model developed by Bayes C for prediction of infection status of animals in validation set was low (55% probability of correct ranking of paired case and control samples).</description><subject>Agriculture</subject><subject>Analysis</subject><subject>Animal sciences</subject><subject>Animals</subject><subject>Association analysis</subject><subject>Bacterial infections</subject><subject>Bayes Theorem</subject><subject>Bayesian analysis</subject><subject>Biology</subject><subject>Bovidae</subject><subject>Cattle</subject><subject>Crohn's disease</subject><subject>Crohns disease</subject><subject>Dairy cattle</subject><subject>Dairy industry</subject><subject>Databases, Genetic</subject><subject>Disease susceptibility</subject><subject>Economic impact</subject><subject>Enzyme-Linked Immunosorbent Assay</subject><subject>Feces</subject><subject>Gene expression</subject><subject>Genetic diversity</subject><subject>Genetic Predisposition to Disease</subject><subject>Genetic variance</subject><subject>Genetic Variation</subject><subject>Genome-wide association studies</subject><subject>Genome-Wide Association Study</subject><subject>Genomes</subject><subject>Genomics</subject><subject>Genotype</subject><subject>Health aspects</subject><subject>Infection</subject><subject>Infections</subject><subject>Inflammatory bowel disease</subject><subject>Johne's disease</subject><subject>Language</subject><subject>Life sciences</subject><subject>Medical research</subject><subject>Mycobacterium avium</subject><subject>Mycobacterium avium - genetics</subject><subject>Oligonucleotide Array Sequence Analysis</subject><subject>Paratuberculosis</subject><subject>Paratuberculosis - diagnosis</subject><subject>Paratuberculosis - genetics</subject><subject>Performance prediction</subject><subject>Polymorphism, Single Nucleotide</subject><subject>Population</subject><subject>Single-nucleotide 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Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zare, Yalda</au><au>Shook, George E</au><au>Collins, Michael T</au><au>Kirkpatrick, Brian W</au><au>Chakravortty, Dipshikha</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Genome-wide association analysis and genomic prediction of Mycobacterium avium subspecies paratuberculosis infection in US Jersey cattle</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2014-02-11</date><risdate>2014</risdate><volume>9</volume><issue>2</issue><spage>e88380</spage><epage>e88380</epage><pages>e88380-e88380</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>Paratuberculosis (Johne's disease), an enteric disorder in ruminants caused by Mycobacterium avium subspecies paratuberculosis (MAP), causes economic losses in excess of $200 million annually to the US dairy industry. To identify genomic regions underlying susceptibility to MAP infection in Jersey cattle, a case-control genome-wide association study (GWAS) was performed. Blood and fecal samples were collected from ∼ 5,000 mature cows in 30 commercial Jersey herds from across the US. Discovery data consisted of 450 cases and 439 controls genotyped with the Illumina BovineSNP50 BeadChip. Cases were animals with positive ELISA and fecal culture (FC) results. Controls were animals negative to both ELISA and FC tests that matched cases on birth date and herd. Validation data consisted of 180 animals including 90 cases (positive to FC) and 90 controls (negative to ELISA and FC), selected from discovery herds and genotyped by Illumina BovineLD BeadChip (∼ 7K SNPs). Two analytical approaches were used: single-marker GWAS using the GRAMMAR-GC method and Bayesian variable selection (Bayes C) using GenSel software. GRAMMAR-GC identified one SNP on BTA7 at 68 megabases (Mb) surpassing a significance threshold of 5 × 10(-5). ARS-BFGL-NGS-11887 on BTA23 (27.7 Mb) accounted for the highest percentage of genetic variance (3.3%) in the Bayes C analysis. SNPs identified in common by GRAMMAR-GC and Bayes C in both discovery and combined data were mapped to BTA23 (27, 29 and 44 Mb), 3 (100, 101, 106 and 107 Mb) and 17 (57 Mb). Correspondence between results of GRAMMAR-GC and Bayes C was high (70-80% of most significant SNPs in common). These SNPs could potentially be associated with causal variants underlying susceptibility to MAP infection in Jersey cattle. Predictive performance of the model developed by Bayes C for prediction of infection status of animals in validation set was low (55% probability of correct ranking of paired case and control samples).</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>24523889</pmid><doi>10.1371/journal.pone.0088380</doi><tpages>e88380</tpages><oa>free_for_read</oa></addata></record> |
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| source | MEDLINE; DOAJ Directory of Open Access Journals; Public Library of Science (PLoS); EZB-FREE-00999 freely available EZB journals; PubMed Central; Free Full-Text Journals in Chemistry |
| subjects | Agriculture Analysis Animal sciences Animals Association analysis Bacterial infections Bayes Theorem Bayesian analysis Biology Bovidae Cattle Crohn's disease Crohns disease Dairy cattle Dairy industry Databases, Genetic Disease susceptibility Economic impact Enzyme-Linked Immunosorbent Assay Feces Gene expression Genetic diversity Genetic Predisposition to Disease Genetic variance Genetic Variation Genome-wide association studies Genome-Wide Association Study Genomes Genomics Genotype Health aspects Infection Infections Inflammatory bowel disease Johne's disease Language Life sciences Medical research Mycobacterium avium Mycobacterium avium - genetics Oligonucleotide Array Sequence Analysis Paratuberculosis Paratuberculosis - diagnosis Paratuberculosis - genetics Performance prediction Polymorphism, Single Nucleotide Population Single-nucleotide polymorphism Software United States Veterinary colleges Veterinary medicine Veterinary Science |
| title | Genome-wide association analysis and genomic prediction of Mycobacterium avium subspecies paratuberculosis infection in US Jersey cattle |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-07T01%3A17%3A38IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_plos_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Genome-wide%20association%20analysis%20and%20genomic%20prediction%20of%20Mycobacterium%20avium%20subspecies%20paratuberculosis%20infection%20in%20US%20Jersey%20cattle&rft.jtitle=PloS%20one&rft.au=Zare,%20Yalda&rft.date=2014-02-11&rft.volume=9&rft.issue=2&rft.spage=e88380&rft.epage=e88380&rft.pages=e88380-e88380&rft.issn=1932-6203&rft.eissn=1932-6203&rft_id=info:doi/10.1371/journal.pone.0088380&rft_dat=%3Cgale_plos_%3EA478813843%3C/gale_plos_%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1497182884&rft_id=info:pmid/24523889&rft_galeid=A478813843&rft_doaj_id=oai_doaj_org_article_e5b9d59343db42d7983cae28adebdd54&rfr_iscdi=true |