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Association analysis for udder health based on SNP-panel and sequence data in Danish Holsteins
BACKGROUND: The sensitivity of genome-wide association studies for the detection of quantitative trait loci (QTL) depends on the density of markers examined and the statistical models used. This study compares the performance of three marker densities to refine six previously detected QTL regions fo...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4472403/ https://www.ncbi.nlm.nih.gov/pubmed/26087655 http://dx.doi.org/10.1186/s12711-015-0129-1 |
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author | Wu, Xiaoping Lund, Mogens S Sahana, Goutam Guldbrandtsen, Bernt Sun, Dongxiao Zhang, Qin Su, Guosheng |
author_facet | Wu, Xiaoping Lund, Mogens S Sahana, Goutam Guldbrandtsen, Bernt Sun, Dongxiao Zhang, Qin Su, Guosheng |
author_sort | Wu, Xiaoping |
collection | PubMed |
description | BACKGROUND: The sensitivity of genome-wide association studies for the detection of quantitative trait loci (QTL) depends on the density of markers examined and the statistical models used. This study compares the performance of three marker densities to refine six previously detected QTL regions for mastitis traits: 54 k markers of a medium-density SNP (single nucleotide polymorphism) chip (MD), imputed 777 k markers of a high-density SNP chip (HD), and imputed whole-genome sequencing data (SEQ). Each dataset contained data for 4496 Danish Holstein cattle. Comparisons were performed using a linear mixed model (LM) and a Bayesian variable selection model (BVS). RESULTS: After quality control, 587, 7825, and 78 856 SNPs in the six targeted regions remained for MD, HD, and SEQ data, respectively. In general, the association patterns between SNPs and traits were similar for the three marker densities when tested using the same statistical model. With the LM model, 120 (MD), 967 (HD), and 7209 (SEQ) SNPs were significantly associated with mastitis, whereas with the BVS model, 43 (MD), 131 (HD), and 1052 (SEQ) significant SNPs (Bayes factor > 3.2) were observed. A total of 26 (MD), 75 (HD), and 465 (SEQ) significant SNPs were identified by both models. In addition, one, 16, and 33 QTL peaks for MD, HD, and SEQ data were detected according to the QTL intensity profile of SNP bins by post-analysis of the BVS model. CONCLUSIONS: The power to detect significant associations increased with increasing marker density. The BVS model resulted in clearer boundaries between linked QTL than the LM model. Using SEQ data, the six targeted regions were refined to 33 candidate QTL regions for udder health. The comparison between these candidate QTL regions and known genes suggested that NPFFR2, SLC4A4, DCK, LIFR, and EDN3 may be considered as candidate genes for mastitis susceptibility. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12711-015-0129-1) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4472403 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-44724032015-06-20 Association analysis for udder health based on SNP-panel and sequence data in Danish Holsteins Wu, Xiaoping Lund, Mogens S Sahana, Goutam Guldbrandtsen, Bernt Sun, Dongxiao Zhang, Qin Su, Guosheng Genet Sel Evol Research Article BACKGROUND: The sensitivity of genome-wide association studies for the detection of quantitative trait loci (QTL) depends on the density of markers examined and the statistical models used. This study compares the performance of three marker densities to refine six previously detected QTL regions for mastitis traits: 54 k markers of a medium-density SNP (single nucleotide polymorphism) chip (MD), imputed 777 k markers of a high-density SNP chip (HD), and imputed whole-genome sequencing data (SEQ). Each dataset contained data for 4496 Danish Holstein cattle. Comparisons were performed using a linear mixed model (LM) and a Bayesian variable selection model (BVS). RESULTS: After quality control, 587, 7825, and 78 856 SNPs in the six targeted regions remained for MD, HD, and SEQ data, respectively. In general, the association patterns between SNPs and traits were similar for the three marker densities when tested using the same statistical model. With the LM model, 120 (MD), 967 (HD), and 7209 (SEQ) SNPs were significantly associated with mastitis, whereas with the BVS model, 43 (MD), 131 (HD), and 1052 (SEQ) significant SNPs (Bayes factor > 3.2) were observed. A total of 26 (MD), 75 (HD), and 465 (SEQ) significant SNPs were identified by both models. In addition, one, 16, and 33 QTL peaks for MD, HD, and SEQ data were detected according to the QTL intensity profile of SNP bins by post-analysis of the BVS model. CONCLUSIONS: The power to detect significant associations increased with increasing marker density. The BVS model resulted in clearer boundaries between linked QTL than the LM model. Using SEQ data, the six targeted regions were refined to 33 candidate QTL regions for udder health. The comparison between these candidate QTL regions and known genes suggested that NPFFR2, SLC4A4, DCK, LIFR, and EDN3 may be considered as candidate genes for mastitis susceptibility. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12711-015-0129-1) contains supplementary material, which is available to authorized users. BioMed Central 2015-06-19 /pmc/articles/PMC4472403/ /pubmed/26087655 http://dx.doi.org/10.1186/s12711-015-0129-1 Text en © Wu et al. 2015 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Wu, Xiaoping Lund, Mogens S Sahana, Goutam Guldbrandtsen, Bernt Sun, Dongxiao Zhang, Qin Su, Guosheng Association analysis for udder health based on SNP-panel and sequence data in Danish Holsteins |
title | Association analysis for udder health based on SNP-panel and sequence data in Danish Holsteins |
title_full | Association analysis for udder health based on SNP-panel and sequence data in Danish Holsteins |
title_fullStr | Association analysis for udder health based on SNP-panel and sequence data in Danish Holsteins |
title_full_unstemmed | Association analysis for udder health based on SNP-panel and sequence data in Danish Holsteins |
title_short | Association analysis for udder health based on SNP-panel and sequence data in Danish Holsteins |
title_sort | association analysis for udder health based on snp-panel and sequence data in danish holsteins |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4472403/ https://www.ncbi.nlm.nih.gov/pubmed/26087655 http://dx.doi.org/10.1186/s12711-015-0129-1 |
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