2021/10/25 by Konstantinos Giannakis, Giannakis, Konstantinos, Joanna M. Chustecki +3
Biochemistry, Genetics and Molecular Biology · #Arabidopsis thaliana #Bioinformatics and Genomic Networks #Biology #Computational biology #Evolutionary biology #FOS: Biological sciences #Gene #Genetics #Genome #Mitochondrial DNA #Mitochondrial Function and Pathology #Mitochondrion #Organelle #Photosynthetic Processes and Mechanisms #Subcellular Processes (q-bio.SC)
paper · pdf · doi:10.48550/arxiv.2110.12736
openalex publication_date 2021/10/25 · openalex created_date 2022/07/25 · openalex updated_date 2026/08/05
Mitochondria in plant cells form strikingly dynamic populations of largely\nindividual organelles. Each mitochondrion contains on average less than a full\ncopy of the mitochondrial DNA (mtDNA) genome. Here, we asked whether\nmitochondrial dynamics may allow individual mitochondria to `collect' a full\ncopy of the mtDNA genome over time, by facilitating exchange between\nindividuals. Akin to trade on a social network, exchange of mtDNA fragments\nacross organelles may lead to the emergence of full `effective' genomes in\nindividuals over time. We characterise the collective dynamics of mitochondria\nin \Arabidopsis thaliana hypocotyl cells using a recent approach\ncombining single-cell timelapse microscopy, video analysis, and network\nscience. We then use a quantitative model to predict the capacity for the\nsharing and accumulation of genetic information through the networks of\nencounters between mitochondria. We find that biological encounter networks are\nstrikingly well predisposed to support the collection of full genomes over\ntime, outperforming a range of other networks generated from theory and\nsimulation. Using results from the coupon collector's problem, we show that the\nupper tail of the degree distribution is a key determinant of an encounter\nnetwork's performance at this task and discuss how features of mitochondrial\ndynamics observed in biology facilitate the emergence of full effective\ngenomes.\n