Evolution and maintenance of mtDNA gene content across eukaryotes

This is a Preprint and has not been peer reviewed. This is version 1 of this Preprint.

Add a Comment

You must log in to post a comment.


Comments

There are no comments or no comments have been made public for this article.

Downloads

Download Preprint

Authors

Shibani Veeraragavan, Maria Johansen, Iain Johnston 

Abstract

Across eukaryotes, most genes required for mitochondrial function have been transferred to, or otherwise acquired by, the nucleus. Encoding genes in the nucleus has many advantages. So why do mitochondria retain any genes at all? Why does the set of mtDNA genes vary so much across different species? And how do species maintain functionality in the mtDNA genes they do retain? In this review we will discuss some possible answers to these questions, attempting a broad perspective across eukaryotes. We hope to cover some interesting features which may be less familiar from the perspective of particular species, including the ubiquity of recombination outside bilaterian animals, encrypted chainmail-like mtDNA, single genes split over multiple mtDNA chromosomes, triparental inheritance, gene transfer by grafting, gain of mtDNA recombination factors, social networks of mitochondria, and the role of mtDNA disease in feeding the world. We will discuss a unifying picture where organismal ecology and gene-specific features together influence whether organism X retains mtDNA gene Y, and where ecology and development together determine which strategies, importantly including recombination, are used to maintain the mtDNA genes that are retained.

DOI

https://doi.org/10.32942/X2HS53

Subjects

Evolution, Genetics, Genomics

Keywords

mitochondria, mtDNA, evolution, Maintenance

Dates

Published: 2024-04-22 17:30

License

CC BY Attribution 4.0 International

Additional Metadata

Language:
English

Conflict of interest statement:
None

Data and Code Availability Statement:
Code to reproduce the paper visualisations is freely available at https://github.com/StochasticBiology/mt-gene-stats.