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Non-invasive genotyping with a massively parallel sequencing panel for the detection of SNPs in HPA-axis genes
We designed a genotyping panel for the investigation of the genetic underpinnings of inter-individual differences in aggression and the physiological stress response. The panel builds on single nucleotide polymorphisms (SNPs) in genes involved in the three subsystems of the hypothalamic-pituitary-ad...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6206064/ https://www.ncbi.nlm.nih.gov/pubmed/30374157 http://dx.doi.org/10.1038/s41598-018-34223-y |
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author | Gutleb, D. R. Ostner, J. Schülke, O. Wajjwalku, W. Sukmak, M. Roos, C. Noll, A. |
author_facet | Gutleb, D. R. Ostner, J. Schülke, O. Wajjwalku, W. Sukmak, M. Roos, C. Noll, A. |
author_sort | Gutleb, D. R. |
collection | PubMed |
description | We designed a genotyping panel for the investigation of the genetic underpinnings of inter-individual differences in aggression and the physiological stress response. The panel builds on single nucleotide polymorphisms (SNPs) in genes involved in the three subsystems of the hypothalamic-pituitary-adrenal (HPA)-axis: the catecholamine, serotonin and corticoid metabolism. To promote the pipeline for use with wild animal populations, we used non-invasively collected faecal samples from a wild population of Assamese macaques (Macaca assamensis). We targeted loci of 46 previously reported SNPs in 21 candidate genes coding for elements of the HPA-axis and amplified and sequenced them using next-generation Illumina sequencing technology. We compared multiple bioinformatics pipelines for variant calling and variant effect prediction. Based on this strategy and the application of different quality thresholds, we identified up to 159 SNPs with different types of predicted functional effects among our natural study population. This study provides a massively parallel sequencing panel that will facilitate integrating large-scale SNP data into behavioural and physiological studies. Such a multi-faceted approach will promote understanding of flexibility and constraints of animal behaviour and hormone physiology. |
format | Online Article Text |
id | pubmed-6206064 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-62060642018-11-01 Non-invasive genotyping with a massively parallel sequencing panel for the detection of SNPs in HPA-axis genes Gutleb, D. R. Ostner, J. Schülke, O. Wajjwalku, W. Sukmak, M. Roos, C. Noll, A. Sci Rep Article We designed a genotyping panel for the investigation of the genetic underpinnings of inter-individual differences in aggression and the physiological stress response. The panel builds on single nucleotide polymorphisms (SNPs) in genes involved in the three subsystems of the hypothalamic-pituitary-adrenal (HPA)-axis: the catecholamine, serotonin and corticoid metabolism. To promote the pipeline for use with wild animal populations, we used non-invasively collected faecal samples from a wild population of Assamese macaques (Macaca assamensis). We targeted loci of 46 previously reported SNPs in 21 candidate genes coding for elements of the HPA-axis and amplified and sequenced them using next-generation Illumina sequencing technology. We compared multiple bioinformatics pipelines for variant calling and variant effect prediction. Based on this strategy and the application of different quality thresholds, we identified up to 159 SNPs with different types of predicted functional effects among our natural study population. This study provides a massively parallel sequencing panel that will facilitate integrating large-scale SNP data into behavioural and physiological studies. Such a multi-faceted approach will promote understanding of flexibility and constraints of animal behaviour and hormone physiology. Nature Publishing Group UK 2018-10-29 /pmc/articles/PMC6206064/ /pubmed/30374157 http://dx.doi.org/10.1038/s41598-018-34223-y Text en © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as 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 images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Gutleb, D. R. Ostner, J. Schülke, O. Wajjwalku, W. Sukmak, M. Roos, C. Noll, A. Non-invasive genotyping with a massively parallel sequencing panel for the detection of SNPs in HPA-axis genes |
title | Non-invasive genotyping with a massively parallel sequencing panel for the detection of SNPs in HPA-axis genes |
title_full | Non-invasive genotyping with a massively parallel sequencing panel for the detection of SNPs in HPA-axis genes |
title_fullStr | Non-invasive genotyping with a massively parallel sequencing panel for the detection of SNPs in HPA-axis genes |
title_full_unstemmed | Non-invasive genotyping with a massively parallel sequencing panel for the detection of SNPs in HPA-axis genes |
title_short | Non-invasive genotyping with a massively parallel sequencing panel for the detection of SNPs in HPA-axis genes |
title_sort | non-invasive genotyping with a massively parallel sequencing panel for the detection of snps in hpa-axis genes |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6206064/ https://www.ncbi.nlm.nih.gov/pubmed/30374157 http://dx.doi.org/10.1038/s41598-018-34223-y |
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