Cargando…

A tool for rapid, automated characterization of population epigenomics in plants

Epigenetic variation in plant populations is an important factor in determining phenotype and adaptation to the environment. However, while advances have been made in the molecular and computational methods to analyze the methylation status of a given sample of DNA, tools to profile and compare the...

Descripción completa

Detalles Bibliográficos
Autores principales: Colicchio, Jack M., Amstutz, Cynthia L., Garcia, Nelson, Prabhu, Keerthana N., Cairns, Thomas M., Akman, Melis, Gottilla, Thomas, Gollery, Twyla, Stricklin, Shawn L., Bayer, Travis S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10435466/
https://www.ncbi.nlm.nih.gov/pubmed/37591855
http://dx.doi.org/10.1038/s41598-023-38356-7
_version_ 1785092103559184384
author Colicchio, Jack M.
Amstutz, Cynthia L.
Garcia, Nelson
Prabhu, Keerthana N.
Cairns, Thomas M.
Akman, Melis
Gottilla, Thomas
Gollery, Twyla
Stricklin, Shawn L.
Bayer, Travis S.
author_facet Colicchio, Jack M.
Amstutz, Cynthia L.
Garcia, Nelson
Prabhu, Keerthana N.
Cairns, Thomas M.
Akman, Melis
Gottilla, Thomas
Gollery, Twyla
Stricklin, Shawn L.
Bayer, Travis S.
author_sort Colicchio, Jack M.
collection PubMed
description Epigenetic variation in plant populations is an important factor in determining phenotype and adaptation to the environment. However, while advances have been made in the molecular and computational methods to analyze the methylation status of a given sample of DNA, tools to profile and compare the methylomes of multiple individual plants or groups of plants at high resolution and low cost are lacking. Here, we describe a computational approach and R package (sounDMR) that leverages the benefits of long read nanopore sequencing to enable robust identification of differential methylation from complex experimental designs, as well as assess the variability within treatment groups and identify individual plants of interest. We demonstrate the utility of this approach by profiling a population of Arabidopsis thaliana exposed to a demethylating agent and identify genomic regions of high epigenetic variability between individuals. Given the low cost of nanopore sequencing devices and the ease of sample preparation, these results show that high resolution epigenetic profiling of plant populations can be made more broadly accessible in plant breeding and biotechnology.
format Online
Article
Text
id pubmed-10435466
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Nature Publishing Group UK
record_format MEDLINE/PubMed
spelling pubmed-104354662023-08-19 A tool for rapid, automated characterization of population epigenomics in plants Colicchio, Jack M. Amstutz, Cynthia L. Garcia, Nelson Prabhu, Keerthana N. Cairns, Thomas M. Akman, Melis Gottilla, Thomas Gollery, Twyla Stricklin, Shawn L. Bayer, Travis S. Sci Rep Article Epigenetic variation in plant populations is an important factor in determining phenotype and adaptation to the environment. However, while advances have been made in the molecular and computational methods to analyze the methylation status of a given sample of DNA, tools to profile and compare the methylomes of multiple individual plants or groups of plants at high resolution and low cost are lacking. Here, we describe a computational approach and R package (sounDMR) that leverages the benefits of long read nanopore sequencing to enable robust identification of differential methylation from complex experimental designs, as well as assess the variability within treatment groups and identify individual plants of interest. We demonstrate the utility of this approach by profiling a population of Arabidopsis thaliana exposed to a demethylating agent and identify genomic regions of high epigenetic variability between individuals. Given the low cost of nanopore sequencing devices and the ease of sample preparation, these results show that high resolution epigenetic profiling of plant populations can be made more broadly accessible in plant breeding and biotechnology. Nature Publishing Group UK 2023-08-17 /pmc/articles/PMC10435466/ /pubmed/37591855 http://dx.doi.org/10.1038/s41598-023-38356-7 Text en © The Author(s) 2023, corrected publication 2023 https://creativecommons.org/licenses/by/4.0/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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Colicchio, Jack M.
Amstutz, Cynthia L.
Garcia, Nelson
Prabhu, Keerthana N.
Cairns, Thomas M.
Akman, Melis
Gottilla, Thomas
Gollery, Twyla
Stricklin, Shawn L.
Bayer, Travis S.
A tool for rapid, automated characterization of population epigenomics in plants
title A tool for rapid, automated characterization of population epigenomics in plants
title_full A tool for rapid, automated characterization of population epigenomics in plants
title_fullStr A tool for rapid, automated characterization of population epigenomics in plants
title_full_unstemmed A tool for rapid, automated characterization of population epigenomics in plants
title_short A tool for rapid, automated characterization of population epigenomics in plants
title_sort tool for rapid, automated characterization of population epigenomics in plants
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10435466/
https://www.ncbi.nlm.nih.gov/pubmed/37591855
http://dx.doi.org/10.1038/s41598-023-38356-7
work_keys_str_mv AT colicchiojackm atoolforrapidautomatedcharacterizationofpopulationepigenomicsinplants
AT amstutzcynthial atoolforrapidautomatedcharacterizationofpopulationepigenomicsinplants
AT garcianelson atoolforrapidautomatedcharacterizationofpopulationepigenomicsinplants
AT prabhukeerthanan atoolforrapidautomatedcharacterizationofpopulationepigenomicsinplants
AT cairnsthomasm atoolforrapidautomatedcharacterizationofpopulationepigenomicsinplants
AT akmanmelis atoolforrapidautomatedcharacterizationofpopulationepigenomicsinplants
AT gottillathomas atoolforrapidautomatedcharacterizationofpopulationepigenomicsinplants
AT gollerytwyla atoolforrapidautomatedcharacterizationofpopulationepigenomicsinplants
AT stricklinshawnl atoolforrapidautomatedcharacterizationofpopulationepigenomicsinplants
AT bayertraviss atoolforrapidautomatedcharacterizationofpopulationepigenomicsinplants
AT colicchiojackm toolforrapidautomatedcharacterizationofpopulationepigenomicsinplants
AT amstutzcynthial toolforrapidautomatedcharacterizationofpopulationepigenomicsinplants
AT garcianelson toolforrapidautomatedcharacterizationofpopulationepigenomicsinplants
AT prabhukeerthanan toolforrapidautomatedcharacterizationofpopulationepigenomicsinplants
AT cairnsthomasm toolforrapidautomatedcharacterizationofpopulationepigenomicsinplants
AT akmanmelis toolforrapidautomatedcharacterizationofpopulationepigenomicsinplants
AT gottillathomas toolforrapidautomatedcharacterizationofpopulationepigenomicsinplants
AT gollerytwyla toolforrapidautomatedcharacterizationofpopulationepigenomicsinplants
AT stricklinshawnl toolforrapidautomatedcharacterizationofpopulationepigenomicsinplants
AT bayertraviss toolforrapidautomatedcharacterizationofpopulationepigenomicsinplants