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Toledano, M.

Publications and source records attributed to Toledano, M..

2 recordsLinked to original sources

Mapping mitonuclear epistasis using a novel recombinant yeast population

Natural genetic variation in mitochondrial and nuclear genomes can influence phenotypes by perturbing coadapted mitonuclear interactions. Mitonuclear epistasis, i.e. non-additive phenotype effects of interacting mitochondrial and nuclear alleles, is emerging as a general feature in eukaryotes, yet very few mitonuclear loci have been identified. Here, we present a novel advanced intercrossed population of S. cerevisiae yeasts, called the Mitonuclear Recombinant Collection (MNRC), designed explicitly for detecting mitonuclear loci contributing to complex traits, and use this population to map the genetic basis to mtDNA loss. In yeast, spontaneous deletions within mtDNAs lead to the petite phenotype that heralded mitochondrial research. We show that in natural populations, rates of petite formation are variable and influenced by genetic variation in nuclear, mtDNAs and mitonuclear interactions. We then mapped nuclear and mitonuclear alleles contributing mtDNA stability using the MNRC by integrating mitonuclear epistasis into a genome-wide association model. We found that associated mitonuclear loci play roles in mitotic growth most likely responding to retrograde signals from mitochondria, while associated nuclear loci with main effects are involved in genome replication. We observed a positive correlation between growth rates and petite frequencies, suggesting a fitness tradeoff between mitotic growth and mtDNA stability. We also found that mtDNA stability was influenced by a mobile mitochondrial GC-cluster that is expanding in certain populations of yeast and that selection for nuclear alleles that stabilize mtDNA may be rapidly occurring. The MNRC provides a powerful tool for identifying mitonuclear interacting loci that will help us to better understand genotype-phenotype relationships and coevolutionary trajectories. Author SummaryGenetic variation in mitochondrial and nuclear genomes can perturb mitonuclear interactions and lead to phenotypic differences between individuals and populations. Despite their importance to most complex traits, it has been difficult to identify the interacting loci. Here, we created a novel population of yeast designed explicitly for mapping mitonuclear loci contributing to complex traits and used this population to map genes influencing the stability of mitochondrial DNA (mtDNA). We found that mitonuclear interacting loci were involved in mitotic growth while non-interacting loci were involved in genome replication. We also found evidence that selection for mitonuclear loci that stabilize mtDNAs occurs rapidly. This work provides insight into mechanisms underlying maintenance of mtDNAs. The mapping population presented here is an important new resource that will help to understand genotype/phenotype relationships and coevolutionary trajectories.

evolutionary biology↗

Federated analysis in COINSTAC reveals functional network connectivity and spectral links to smoking and alcohol consumption in nearly 2,000 adolescent brains

With the growth of decentralized/federated analysis approaches in neuroimaging, the opportunities to study brain disorders using data from multiple sites has grown multi-fold. One such initiative is the Neuromark, a fully automated spatially constrained independent component analysis (ICA) that is used to link brain network abnormalities among different datasets, studies, and disorders while leveraging subject-specific networks. In this study, we implement the neuromark pipeline in COINSTAC, an open-source neuroimaging framework for collaborative/decentralized analysis. Decentralized analysis of nearly 2000 resting-state functional magnetic resonance imaging datasets collected at different sites across two cohorts and co-located in different countries was performed to study the resting brain functional network connectivity changes in adolescents who smoke and consume alcohol. Results showed hypoconnectivity across the majority of networks including sensory, default mode, and subcortical domains, more for alcohol than smoking, and decreased low frequency power. These findings suggest that global reduced synchronization is associated with both tobacco and alcohol use. This work demonstrates the utility and incentives associated with large-scale decentralized collaborations spanning multiple sites.

bioinformatics↗