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CNV discovery for milk composition traits in dairy cattle using whole genome resequencing
BACKGROUND: Copy number variations (CNVs) are important and widely distributed in the genome. CNV detection opens a new avenue for exploring genes associated with complex traits in humans, animals and plants. Herein, we present a genome-wide assessment of CNVs that are potentially associated with mi...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5371188/ https://www.ncbi.nlm.nih.gov/pubmed/28356085 http://dx.doi.org/10.1186/s12864-017-3636-3 |
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author | Gao, Yahui Jiang, Jianping Yang, Shaohua Hou, Yali Liu, George E Zhang, Shengli Zhang, Qin Sun, Dongxiao |
author_facet | Gao, Yahui Jiang, Jianping Yang, Shaohua Hou, Yali Liu, George E Zhang, Shengli Zhang, Qin Sun, Dongxiao |
author_sort | Gao, Yahui |
collection | PubMed |
description | BACKGROUND: Copy number variations (CNVs) are important and widely distributed in the genome. CNV detection opens a new avenue for exploring genes associated with complex traits in humans, animals and plants. Herein, we present a genome-wide assessment of CNVs that are potentially associated with milk composition traits in dairy cattle. RESULTS: In this study, CNVs were detected based on whole genome re-sequencing data of eight Holstein bulls from four half- and/or full-sib families, with extremely high and low estimated breeding values (EBVs) of milk protein percentage and fat percentage. The range of coverage depth per individual was 8.2–11.9×. Using CNVnator, we identified a total of 14,821 CNVs, including 5025 duplications and 9796 deletions. Among them, 487 differential CNV regions (CNVRs) comprising ~8.23 Mb of the cattle genome were observed between the high and low groups. Annotation of these differential CNVRs were performed based on the cattle genome reference assembly (UMD3.1) and totally 235 functional genes were found within the CNVRs. By Gene Ontology and KEGG pathway analyses, we found that genes were significantly enriched for specific biological functions related to protein and lipid metabolism, insulin/IGF pathway-protein kinase B signaling cascade, prolactin signaling pathway and AMPK signaling pathways. These genes included INS, IGF2, FOXO3, TH, SCD5, GALNT18, GALNT16, ART3, SNCA and WNT7A, implying their potential association with milk protein and fat traits. In addition, 95 CNVRs were overlapped with 75 known QTLs that are associated with milk protein and fat traits of dairy cattle (Cattle QTLdb). CONCLUSIONS: In conclusion, based on NGS of 8 Holstein bulls with extremely high and low EBVs for milk PP and FP, we identified a total of 14,821 CNVs, 487 differential CNVRs between groups, and 10 genes, which were suggested as promising candidate genes for milk protein and fat traits. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-017-3636-3) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5371188 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-53711882017-03-30 CNV discovery for milk composition traits in dairy cattle using whole genome resequencing Gao, Yahui Jiang, Jianping Yang, Shaohua Hou, Yali Liu, George E Zhang, Shengli Zhang, Qin Sun, Dongxiao BMC Genomics Research Article BACKGROUND: Copy number variations (CNVs) are important and widely distributed in the genome. CNV detection opens a new avenue for exploring genes associated with complex traits in humans, animals and plants. Herein, we present a genome-wide assessment of CNVs that are potentially associated with milk composition traits in dairy cattle. RESULTS: In this study, CNVs were detected based on whole genome re-sequencing data of eight Holstein bulls from four half- and/or full-sib families, with extremely high and low estimated breeding values (EBVs) of milk protein percentage and fat percentage. The range of coverage depth per individual was 8.2–11.9×. Using CNVnator, we identified a total of 14,821 CNVs, including 5025 duplications and 9796 deletions. Among them, 487 differential CNV regions (CNVRs) comprising ~8.23 Mb of the cattle genome were observed between the high and low groups. Annotation of these differential CNVRs were performed based on the cattle genome reference assembly (UMD3.1) and totally 235 functional genes were found within the CNVRs. By Gene Ontology and KEGG pathway analyses, we found that genes were significantly enriched for specific biological functions related to protein and lipid metabolism, insulin/IGF pathway-protein kinase B signaling cascade, prolactin signaling pathway and AMPK signaling pathways. These genes included INS, IGF2, FOXO3, TH, SCD5, GALNT18, GALNT16, ART3, SNCA and WNT7A, implying their potential association with milk protein and fat traits. In addition, 95 CNVRs were overlapped with 75 known QTLs that are associated with milk protein and fat traits of dairy cattle (Cattle QTLdb). CONCLUSIONS: In conclusion, based on NGS of 8 Holstein bulls with extremely high and low EBVs for milk PP and FP, we identified a total of 14,821 CNVs, 487 differential CNVRs between groups, and 10 genes, which were suggested as promising candidate genes for milk protein and fat traits. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-017-3636-3) contains supplementary material, which is available to authorized users. BioMed Central 2017-03-29 /pmc/articles/PMC5371188/ /pubmed/28356085 http://dx.doi.org/10.1186/s12864-017-3636-3 Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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 Gao, Yahui Jiang, Jianping Yang, Shaohua Hou, Yali Liu, George E Zhang, Shengli Zhang, Qin Sun, Dongxiao CNV discovery for milk composition traits in dairy cattle using whole genome resequencing |
title | CNV discovery for milk composition traits in dairy cattle using whole genome resequencing |
title_full | CNV discovery for milk composition traits in dairy cattle using whole genome resequencing |
title_fullStr | CNV discovery for milk composition traits in dairy cattle using whole genome resequencing |
title_full_unstemmed | CNV discovery for milk composition traits in dairy cattle using whole genome resequencing |
title_short | CNV discovery for milk composition traits in dairy cattle using whole genome resequencing |
title_sort | cnv discovery for milk composition traits in dairy cattle using whole genome resequencing |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5371188/ https://www.ncbi.nlm.nih.gov/pubmed/28356085 http://dx.doi.org/10.1186/s12864-017-3636-3 |
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