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Loblolly pine (Pinus taeda) epigenetic clock

dataset
posted on 2024-09-29, 06:51 authored by University of Georgia
Biological aging is connected to life history variation across ecological scales, with implications for conservation and management applications, as well as informing a basic understanding of age-related declines to organismal function. Altered DNA methylation dynamics are a conserved aspect of biological aging and have recently been modeled to predict chronological age among vertebrate species. In addition to their utility in estimating individual age, differences between chronological and predicted ages arise due to acceleration or deceleration of epigenetic aging, and these discrepancies are linked to disease risk and multiple life history traits. Although evidence suggests that patterns of DNA methylation can describe aging in plants, predictions with epigenetic clocks have yet to be performed.This project was done to investigate the DNA methylome across CpG, CHG, and CHH-methylation contexts in the loblolly pine tree (Pinus taeda) and construct epigenetic clocks. This study reports one of the first epigenetic clocks in plants and demonstrates the universality of age-associated DNA methylation dynamics which can inform conservation and management practices, as well as our ecological and evolutionary understanding of biological aging in plants.

Funding

DOE/USDA: DE-EM0003622

NSF: 2026210

History

Data contact name

BioProject Curation Staff

Publisher

National Center for Biotechnology Information

Temporal Extent Start Date

2022-07-27

Theme

  • Non-geospatial

ISO Topic Category

  • biota

National Agricultural Library Thesaurus terms

sequence analysis

Pending citation

  • No

Public Access Level

  • Public

Accession Number

PRJNA862919

Preferred dataset citation

It is recommended to cite the accession numbers that are assigned to data submissions, e.g. the GenBank, WGS or SRA accession numbers. If individual BioProjects need to be referenced, state that "The data have been deposited with links to BioProject accession number PRJNA862919 in the NCBI BioProject database (https://www.ncbi.nlm.nih.gov/bioproject/)."

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