2021
DOI: 10.1101/2021.10.27.465964
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Universal features shaping organelle gene retention

Abstract: Mitochondria and plastids power complex life, and retain their own organelle DNA (oDNA) genomes, with highly reduced gene contents compared to their endosymbiont ancestors. Why some protein-coding genes are retained in oDNA and some lost remains a debated question. Here we harness over 15k oDNA sequences and over 300 whole genome sequences with tools from structural biology, bioinformatics, machine learning, and Bayesian model selection to reveal the properties of genes, and associated underlying mechanisms, t… Show more

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Cited by 7 publications
(11 citation statements)
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“…In correcting for systematic differences in gene count between deep-branching clades (Giannakis et al 2022;Janouškovec et al 2017) and additionally for the phylogenetic relationship between samples, we have attempted to align with the picture in (Maddison and FitzJohn 2015), of both identifying independent subsets of data and then accounting "internally" for phylogenetic signal. However, how best to account for dependencies across phylogenetically-embedded data is a topic of substantial discussion (Uyeda, Zenil-Ferguson, and Pennell 2018;Losos 2011); even well-principled comparative methods have shortcomings in the face of singular evolutionary events (Uyeda, Zenil-Ferguson, and Pennell 2018) and imperfect phylogenetic estimates (as we have here) and the distinction between pattern and process can challenge the application of these methods (Losos 2011)discussed further in an oDNA context in (Giannakis, Richards, and Johnston 2023). In taking different combinations of clade-based and phylogenetic correction, and considering different subtrees of our data, we have attempted to be robust to particular choices of method.…”
Section: Discussionmentioning
confidence: 98%
See 1 more Smart Citation
“…In correcting for systematic differences in gene count between deep-branching clades (Giannakis et al 2022;Janouškovec et al 2017) and additionally for the phylogenetic relationship between samples, we have attempted to align with the picture in (Maddison and FitzJohn 2015), of both identifying independent subsets of data and then accounting "internally" for phylogenetic signal. However, how best to account for dependencies across phylogenetically-embedded data is a topic of substantial discussion (Uyeda, Zenil-Ferguson, and Pennell 2018;Losos 2011); even well-principled comparative methods have shortcomings in the face of singular evolutionary events (Uyeda, Zenil-Ferguson, and Pennell 2018) and imperfect phylogenetic estimates (as we have here) and the distinction between pattern and process can challenge the application of these methods (Losos 2011)discussed further in an oDNA context in (Giannakis, Richards, and Johnston 2023). In taking different combinations of clade-based and phylogenetic correction, and considering different subtrees of our data, we have attempted to be robust to particular choices of method.…”
Section: Discussionmentioning
confidence: 98%
“…Following findings in (Giannakis, Richards, and Johnston 2023), aligned with the features that most broadly distinguished entries in our dataset, we tested for differences between organisms with different characteristics: algae, unicellularity, green plants/algae, herbaceousness, annual/perennial lifestyle. For clade-corrected oDNA counts (ΔMT and ΔPT), a linear mixed model with random and gradients assigned to the algal category was slightly favoured by AIC over the fixed linear model (1154.7 vs 1157.5 for the fixed model).…”
Section: Ecological and Species-specific Factorsmentioning
confidence: 99%
“…Hence, organisms experiencing highly variable bioenergetic and metabolic demands from their environment would retain more oDNA genes, and those experiencing lower and more stable demands would retain fewer. This picture is supported to some extent by mathematical modeling ( García-Pascual et al 2022 ) and comparative analysis of links between ecological traits and oDNA gene counts ( Giannakis et al 2023 )—although we must point out that this picture does not and probably cannot explain the full diversity of oDNA retention profiles across eukaryotes. Although this theoretical picture predicts that similar factors shape—to some extent—mtDNA and ptDNA evolution, this prediction has to our knowledge yet to be tested with data.…”
Section: Introductionmentioning
confidence: 99%
“…Intergenomic coevolution between the nucleus and organelle(s) is a common feature among eukaryotes. Gene loss and transfers to the nucleus have greatly reduced the coding regions of modern mitochondrial and plastid genomes to a limited number of essential genes ( Greiner and Bock 2013 ; Budar and Mireau 2018 ; Giannakis et al 2021 ). Consequently, these organelles must coordinate transcripts and protein products from 2 or more different genomic compartments to carry out essential cellular functions.…”
Section: Introductionmentioning
confidence: 99%