Bioinformatic analysis for age prediction using epigenetic clocks: Application to fisheries management and conservation biology

Author:

Anastasiadi Dafni,Piferrer Francesc

Abstract

Epigenetic clocks are accurate tools for age prediction and are of great interest for fisheries management and conservation biology. Here, we review the necessary computational steps and tools in order to build an epigenetic clock in any species focusing on fish. Currently, a bisulfite conversion method which allows the distinction of methylated and unmethylated cytosines is the recommended method to be performed at single nucleotide resolution. Typically, reduced representation bisulfite sequencing methods provide enough coverage of CpGs to select from for age prediction while the exact implemented method depends on the specific objectives and cost of the study. Sequenced reads are controlled for their quality, aligned to either a reference or a deduced genome and methylation levels of CpGs are extracted. Methylation values are obtained in biological samples of fish that cover the widest age range possible. Using these datasets, machine learning statistical procedures and, in particular, penalized regressions, are applied in order to identify a set of CpGs the methylation of which in combination is enough to accurately predict age. Training and test datasets are used to build the optimal model or “epigenetic clock”, which can then be used to predict age in independent samples. Once a set of CpGs is robustly identified to predict age in a given species, DNA methylation in only a small number of CpGs is necessary, thus, sequencing efforts including data and money resources can be adjusted to interrogate a small number of CpGs in a high number of samples. Implementation of this molecular resource in routine evaluations of fish population structure is expected to increase in the years to come due to high accuracy, robustness and decreasing costs of sequencing. In the context of overexploited fish stocks, as well as endangered fish species, accurate age prediction with easy-to-use tools is much needed for improved fish populations management and conservation.

Publisher

Frontiers Media SA

Subject

Ocean Engineering,Water Science and Technology,Aquatic Science,Global and Planetary Change,Oceanography

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3