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Detection of copy number variations in brown and white layers based on genotyping panels with different densities
BACKGROUND: Copy number variations (CNV) are an important source of genetic variation that has gained increasing attention over the last couple of years. In this study, we performed CNV detection and functional analysis for 18,719 individuals from four pure lines and one commercial cross of layer ch...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6219011/ https://www.ncbi.nlm.nih.gov/pubmed/30400769 http://dx.doi.org/10.1186/s12711-018-0428-4 |
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author | Drobik-Czwarno, Wioleta Wolc, Anna Fulton, Janet E. Dekkers, Jack C. M. |
author_facet | Drobik-Czwarno, Wioleta Wolc, Anna Fulton, Janet E. Dekkers, Jack C. M. |
author_sort | Drobik-Czwarno, Wioleta |
collection | PubMed |
description | BACKGROUND: Copy number variations (CNV) are an important source of genetic variation that has gained increasing attention over the last couple of years. In this study, we performed CNV detection and functional analysis for 18,719 individuals from four pure lines and one commercial cross of layer chickens. Samples were genotyped on four single nucleotide polymorphism (SNP) genotyping platforms, i.e. the Illumina 42K, Affymetrix 600K, and two different customized Affymetrix 50K chips. CNV recovered from the Affymetrix chips were identified by using the Axiom(®) CNV Summary Tools and PennCNV software and those from the Illumina chip were identified by using the cnvPartition in the Genome Studio software. RESULTS: The mean number of CNV per individual varied from 0.50 to 4.87 according to line or cross and size of the SNP genotyping set. The length of the detected CNV across all datasets ranged from 1.2 kb to 3.2 Mb. The number of duplications exceeded the number of deletions for most lines. Between the lines, there were considerable differences in the number of detected CNV and their distribution. Most of the detected CNV had a low frequency, but 19 CNV were identified with a frequency higher than 5% in birds that were genotyped on the 600K panel, with the most common CNV being detected in 734 birds from three lines. CONCLUSIONS: Commonly used SNP genotyping platforms can be used to detect segregating CNV in chicken layer lines. The sample sizes for this study enabled a detailed characterization of the CNV landscape within commercially relevant lines. The size of the SNP panel used affected detection efficiency, with more CNV detected per individual on the higher density 600K panel. In spite of the high level of inter-individual diversity and a large number of CNV observed within individuals, we were able to detect 19 frequent CNV, of which, 57.9% overlapped with annotated genes and 89% overlapped with known quantitative trait loci. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12711-018-0428-4) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6219011 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-62190112018-11-08 Detection of copy number variations in brown and white layers based on genotyping panels with different densities Drobik-Czwarno, Wioleta Wolc, Anna Fulton, Janet E. Dekkers, Jack C. M. Genet Sel Evol Research Article BACKGROUND: Copy number variations (CNV) are an important source of genetic variation that has gained increasing attention over the last couple of years. In this study, we performed CNV detection and functional analysis for 18,719 individuals from four pure lines and one commercial cross of layer chickens. Samples were genotyped on four single nucleotide polymorphism (SNP) genotyping platforms, i.e. the Illumina 42K, Affymetrix 600K, and two different customized Affymetrix 50K chips. CNV recovered from the Affymetrix chips were identified by using the Axiom(®) CNV Summary Tools and PennCNV software and those from the Illumina chip were identified by using the cnvPartition in the Genome Studio software. RESULTS: The mean number of CNV per individual varied from 0.50 to 4.87 according to line or cross and size of the SNP genotyping set. The length of the detected CNV across all datasets ranged from 1.2 kb to 3.2 Mb. The number of duplications exceeded the number of deletions for most lines. Between the lines, there were considerable differences in the number of detected CNV and their distribution. Most of the detected CNV had a low frequency, but 19 CNV were identified with a frequency higher than 5% in birds that were genotyped on the 600K panel, with the most common CNV being detected in 734 birds from three lines. CONCLUSIONS: Commonly used SNP genotyping platforms can be used to detect segregating CNV in chicken layer lines. The sample sizes for this study enabled a detailed characterization of the CNV landscape within commercially relevant lines. The size of the SNP panel used affected detection efficiency, with more CNV detected per individual on the higher density 600K panel. In spite of the high level of inter-individual diversity and a large number of CNV observed within individuals, we were able to detect 19 frequent CNV, of which, 57.9% overlapped with annotated genes and 89% overlapped with known quantitative trait loci. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12711-018-0428-4) contains supplementary material, which is available to authorized users. BioMed Central 2018-11-06 /pmc/articles/PMC6219011/ /pubmed/30400769 http://dx.doi.org/10.1186/s12711-018-0428-4 Text en © The Author(s) 2018 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 Drobik-Czwarno, Wioleta Wolc, Anna Fulton, Janet E. Dekkers, Jack C. M. Detection of copy number variations in brown and white layers based on genotyping panels with different densities |
title | Detection of copy number variations in brown and white layers based on genotyping panels with different densities |
title_full | Detection of copy number variations in brown and white layers based on genotyping panels with different densities |
title_fullStr | Detection of copy number variations in brown and white layers based on genotyping panels with different densities |
title_full_unstemmed | Detection of copy number variations in brown and white layers based on genotyping panels with different densities |
title_short | Detection of copy number variations in brown and white layers based on genotyping panels with different densities |
title_sort | detection of copy number variations in brown and white layers based on genotyping panels with different densities |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6219011/ https://www.ncbi.nlm.nih.gov/pubmed/30400769 http://dx.doi.org/10.1186/s12711-018-0428-4 |
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