Improved detection of gene-microbe interactions in the mouse skin microbiota using high-resolution QTL mapping of 16S rRNA transcripts

Abstract Background Recent studies highlight the utility of quantitative trait locus (QTL) mapping for determining the contribution of host genetics to interindividual variation in the microbiota. We previously demonstrated that similar to the gut microbiota, abundances of bacterial taxa in the skin...

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Main Authors: Meriem Belheouane, Yask Gupta, Sven Künzel, Saleh Ibrahim, John F. Baines
Format: Article
Language:English
Published: BMC 2017-06-01
Series:Microbiome
Subjects:
Online Access:http://link.springer.com/article/10.1186/s40168-017-0275-5
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spelling doaj-60b78e53da7f4fde9932b8732bee9cae2020-11-24T22:17:22ZengBMCMicrobiome2049-26182017-06-015111710.1186/s40168-017-0275-5Improved detection of gene-microbe interactions in the mouse skin microbiota using high-resolution QTL mapping of 16S rRNA transcriptsMeriem Belheouane0Yask Gupta1Sven Künzel2Saleh Ibrahim3John F. Baines4Max Planck Institute for Evolutionary BiologyLübeck Institute of Experimental Dermatology, University of LübeckMax Planck Institute for Evolutionary BiologyLübeck Institute of Experimental Dermatology, University of LübeckMax Planck Institute for Evolutionary BiologyAbstract Background Recent studies highlight the utility of quantitative trait locus (QTL) mapping for determining the contribution of host genetics to interindividual variation in the microbiota. We previously demonstrated that similar to the gut microbiota, abundances of bacterial taxa in the skin are significantly influenced by host genetic variation. In this study, we analyzed the skin microbiota of mice from the 15th generation of an advanced intercross line using a novel approach of extending bacterial trait mapping to both the 16S rRNA gene copy (DNA) and transcript (RNA) levels, which reflect relative bacterial cell number and activity, respectively. Results Remarkably, the combination of highly recombined individuals and 53,203 informative SNPs allowed the identification of genomic intervals as small as <0.1 megabases containing single genes. Furthermore, the inclusion of 16S rRNA transcript-level mapping dramatically increased the number of significant associations detected, with five versus 21 significant SNP-bacterial trait associations based on DNA- compared to RNA-level profiling, respectively. Importantly, the genomic intervals identified contain many genes involved in skin inflammation and cancer and are further supported by the bacterial traits they influence, which in some cases have known genotoxic or probiotic capabilities. Conclusions These results indicate that profiling based on the relative activity levels of bacterial community members greatly enhances the capability of detecting interactions between the host and its associated microbes. Finally, the identification of several genes involved in skin cancer suggests that similar to colon carcinogenesis, the resident microbiota may play a role in skin cancer susceptibility and its potential prevention and/or treatment.http://link.springer.com/article/10.1186/s40168-017-0275-5QTL mappingSkin microbiota16S rRNA transcriptSkin cancer
collection DOAJ
language English
format Article
sources DOAJ
author Meriem Belheouane
Yask Gupta
Sven Künzel
Saleh Ibrahim
John F. Baines
spellingShingle Meriem Belheouane
Yask Gupta
Sven Künzel
Saleh Ibrahim
John F. Baines
Improved detection of gene-microbe interactions in the mouse skin microbiota using high-resolution QTL mapping of 16S rRNA transcripts
Microbiome
QTL mapping
Skin microbiota
16S rRNA transcript
Skin cancer
author_facet Meriem Belheouane
Yask Gupta
Sven Künzel
Saleh Ibrahim
John F. Baines
author_sort Meriem Belheouane
title Improved detection of gene-microbe interactions in the mouse skin microbiota using high-resolution QTL mapping of 16S rRNA transcripts
title_short Improved detection of gene-microbe interactions in the mouse skin microbiota using high-resolution QTL mapping of 16S rRNA transcripts
title_full Improved detection of gene-microbe interactions in the mouse skin microbiota using high-resolution QTL mapping of 16S rRNA transcripts
title_fullStr Improved detection of gene-microbe interactions in the mouse skin microbiota using high-resolution QTL mapping of 16S rRNA transcripts
title_full_unstemmed Improved detection of gene-microbe interactions in the mouse skin microbiota using high-resolution QTL mapping of 16S rRNA transcripts
title_sort improved detection of gene-microbe interactions in the mouse skin microbiota using high-resolution qtl mapping of 16s rrna transcripts
publisher BMC
series Microbiome
issn 2049-2618
publishDate 2017-06-01
description Abstract Background Recent studies highlight the utility of quantitative trait locus (QTL) mapping for determining the contribution of host genetics to interindividual variation in the microbiota. We previously demonstrated that similar to the gut microbiota, abundances of bacterial taxa in the skin are significantly influenced by host genetic variation. In this study, we analyzed the skin microbiota of mice from the 15th generation of an advanced intercross line using a novel approach of extending bacterial trait mapping to both the 16S rRNA gene copy (DNA) and transcript (RNA) levels, which reflect relative bacterial cell number and activity, respectively. Results Remarkably, the combination of highly recombined individuals and 53,203 informative SNPs allowed the identification of genomic intervals as small as <0.1 megabases containing single genes. Furthermore, the inclusion of 16S rRNA transcript-level mapping dramatically increased the number of significant associations detected, with five versus 21 significant SNP-bacterial trait associations based on DNA- compared to RNA-level profiling, respectively. Importantly, the genomic intervals identified contain many genes involved in skin inflammation and cancer and are further supported by the bacterial traits they influence, which in some cases have known genotoxic or probiotic capabilities. Conclusions These results indicate that profiling based on the relative activity levels of bacterial community members greatly enhances the capability of detecting interactions between the host and its associated microbes. Finally, the identification of several genes involved in skin cancer suggests that similar to colon carcinogenesis, the resident microbiota may play a role in skin cancer susceptibility and its potential prevention and/or treatment.
topic QTL mapping
Skin microbiota
16S rRNA transcript
Skin cancer
url http://link.springer.com/article/10.1186/s40168-017-0275-5
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