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A collective diabetes cross in combination with a computational framework to dissect the genetics of human obesity and Type 2 diabetes
To explore the genetic determinants of obesity and Type 2 diabetes (T2D), the German Center for Diabetes Research (DZD) conducted crossbreedings of the obese and diabetes-prone New Zealand Obese mouse strain with four different lean strains (B6, DBA, C3H, 129P2) that vary in their susceptibility to...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6097155/ https://www.ncbi.nlm.nih.gov/pubmed/29893858 http://dx.doi.org/10.1093/hmg/ddy217 |
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author | Vogel, Heike Kamitz, Anne Hallahan, Nicole Lebek, Sandra Schallschmidt, Tanja Jonas, Wenke Jähnert, Markus Gottmann, Pascal Zellner, Lisa Kanzleiter, Timo Damen, Mareike Altenhofen, Delsi Burkhardt, Ralph Renner, Simone Dahlhoff, Maik Wolf, Eckhard Müller, Timo D Blüher, Matthias Joost, Hans-Georg Chadt, Alexandra Al-Hasani, Hadi Schürmann, Annette |
author_facet | Vogel, Heike Kamitz, Anne Hallahan, Nicole Lebek, Sandra Schallschmidt, Tanja Jonas, Wenke Jähnert, Markus Gottmann, Pascal Zellner, Lisa Kanzleiter, Timo Damen, Mareike Altenhofen, Delsi Burkhardt, Ralph Renner, Simone Dahlhoff, Maik Wolf, Eckhard Müller, Timo D Blüher, Matthias Joost, Hans-Georg Chadt, Alexandra Al-Hasani, Hadi Schürmann, Annette |
author_sort | Vogel, Heike |
collection | PubMed |
description | To explore the genetic determinants of obesity and Type 2 diabetes (T2D), the German Center for Diabetes Research (DZD) conducted crossbreedings of the obese and diabetes-prone New Zealand Obese mouse strain with four different lean strains (B6, DBA, C3H, 129P2) that vary in their susceptibility to develop T2D. Genome-wide linkage analyses localized more than 290 quantitative trait loci (QTL) for obesity, 190 QTL for diabetes-related traits and 100 QTL for plasma metabolites in the outcross populations. A computational framework was developed that allowed to refine critical regions and to nominate a small number of candidate genes by integrating reciprocal haplotype mapping and transcriptome data. The efficiency of the complex procedure was demonstrated for one obesity QTL. The genomic interval of 35 Mb with 502 annotated candidate genes was narrowed down to six candidates. Accordingly, congenic mice retained the obesity phenotype owing to an interval that contains three of the six candidate genes. Among these the phospholipase PLA2G4A exhibited an elevated expression in adipose tissue of obese human subjects and is therefore a critical regulator of the obesity locus. Together, our broad and complex approach demonstrates that combined- and comparative-cross analysis exhibits improved mapping resolution and represents a valid tool for the identification of disease genes. |
format | Online Article Text |
id | pubmed-6097155 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-60971552018-08-22 A collective diabetes cross in combination with a computational framework to dissect the genetics of human obesity and Type 2 diabetes Vogel, Heike Kamitz, Anne Hallahan, Nicole Lebek, Sandra Schallschmidt, Tanja Jonas, Wenke Jähnert, Markus Gottmann, Pascal Zellner, Lisa Kanzleiter, Timo Damen, Mareike Altenhofen, Delsi Burkhardt, Ralph Renner, Simone Dahlhoff, Maik Wolf, Eckhard Müller, Timo D Blüher, Matthias Joost, Hans-Georg Chadt, Alexandra Al-Hasani, Hadi Schürmann, Annette Hum Mol Genet Association Studies Article To explore the genetic determinants of obesity and Type 2 diabetes (T2D), the German Center for Diabetes Research (DZD) conducted crossbreedings of the obese and diabetes-prone New Zealand Obese mouse strain with four different lean strains (B6, DBA, C3H, 129P2) that vary in their susceptibility to develop T2D. Genome-wide linkage analyses localized more than 290 quantitative trait loci (QTL) for obesity, 190 QTL for diabetes-related traits and 100 QTL for plasma metabolites in the outcross populations. A computational framework was developed that allowed to refine critical regions and to nominate a small number of candidate genes by integrating reciprocal haplotype mapping and transcriptome data. The efficiency of the complex procedure was demonstrated for one obesity QTL. The genomic interval of 35 Mb with 502 annotated candidate genes was narrowed down to six candidates. Accordingly, congenic mice retained the obesity phenotype owing to an interval that contains three of the six candidate genes. Among these the phospholipase PLA2G4A exhibited an elevated expression in adipose tissue of obese human subjects and is therefore a critical regulator of the obesity locus. Together, our broad and complex approach demonstrates that combined- and comparative-cross analysis exhibits improved mapping resolution and represents a valid tool for the identification of disease genes. Oxford University Press 2018-09-01 2018-06-08 /pmc/articles/PMC6097155/ /pubmed/29893858 http://dx.doi.org/10.1093/hmg/ddy217 Text en © The Author(s) 2018. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Association Studies Article Vogel, Heike Kamitz, Anne Hallahan, Nicole Lebek, Sandra Schallschmidt, Tanja Jonas, Wenke Jähnert, Markus Gottmann, Pascal Zellner, Lisa Kanzleiter, Timo Damen, Mareike Altenhofen, Delsi Burkhardt, Ralph Renner, Simone Dahlhoff, Maik Wolf, Eckhard Müller, Timo D Blüher, Matthias Joost, Hans-Georg Chadt, Alexandra Al-Hasani, Hadi Schürmann, Annette A collective diabetes cross in combination with a computational framework to dissect the genetics of human obesity and Type 2 diabetes |
title | A collective diabetes cross in combination with a computational framework to dissect the genetics of human obesity and Type 2 diabetes |
title_full | A collective diabetes cross in combination with a computational framework to dissect the genetics of human obesity and Type 2 diabetes |
title_fullStr | A collective diabetes cross in combination with a computational framework to dissect the genetics of human obesity and Type 2 diabetes |
title_full_unstemmed | A collective diabetes cross in combination with a computational framework to dissect the genetics of human obesity and Type 2 diabetes |
title_short | A collective diabetes cross in combination with a computational framework to dissect the genetics of human obesity and Type 2 diabetes |
title_sort | collective diabetes cross in combination with a computational framework to dissect the genetics of human obesity and type 2 diabetes |
topic | Association Studies Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6097155/ https://www.ncbi.nlm.nih.gov/pubmed/29893858 http://dx.doi.org/10.1093/hmg/ddy217 |
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