Quantifying mitochondrial heteroplasmy diversity: A computational approach.

Hill numbers alpha diversity beta diversity biodiversity mitochondrial heteroplasmy

Journal

Molecular ecology resources

ISSN: 1755-0998

Titre abrégé: Mol Ecol Resour

Pays: England

ID NLM: 101465604

Informations de publication

Date de publication:
Jan 2024

Historique:

received: 30 05 2023

accepted: 22 09 2023

pubmed: 10 10 2023

medline: 10 10 2023

entrez: 10 10 2023

Statut: ppublish

Résumé

Biodiversity plays a pivotal role in sustaining ecosystem processes, encompassing diverse biological species, genetic types and the intricacies of ecosystem composition. However, the precise definition of biodiversity at the individual level remains a challenging endeavour. Hill numbers, derived from Rényi's entropy, have emerged as a popular measure of diversity, with a recent unified framework extending their application across various levels, from genetics to ecosystems. In this study, we employ a computational approach to exploring the diversity of mitochondrial heteroplasmy using real-world data. By adopting Hill numbers with q = 2, we demonstrate the feasibility of quantifying mitochondrial heteroplasmy diversity within and between individuals and populations. Furthermore, we investigate the alpha diversity of mitochondrial heteroplasmy among different species, revealing heterogeneity at multiple levels, including mitogenome components and protein-coding genes (PCGs). Our analysis explores large-scale mitochondrial heteroplasmy data in humans, examining the relationship between alpha diversity at the mitogenome components and PCGs level. Notably, we do not find a significant correlation between these two levels. Additionally, we observe significant correlations in alpha diversity between mothers and children in blood samples, exceeding the reported R

Identifiants

DOI: 10.1111/1755-0998.13874 PMID: 37815422

pubmed: 37815422

doi: 10.1111/1755-0998.13874

doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

Pagination

e13874

Subventions

Organisme : Earmarked Fund for China Agriculture Research System

ID : CARS-45-38

Organisme : Science & Technology Innovation Program of Hangzhou Academy of Agricultural Sciences

ID : 2022HNCT-01

Informations de copyright

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