Biology subjects

Dunn, C.

Publications and source records attributed to Dunn, C..

22 records · Page 2Linked to original sources

bioRxiv2021

A functional bacterial-derived restriction modification system in the mitochondrion of a heterotrophic protist

The overarching trend in mitochondrial evolution is functional streamlining coupled with gene loss; therefore, gene acquisition by mitochondria is considered to be exceedingly rare. Selfish elements in the form of self-splicing introns occur in many organellar genomes, but the wider diversity of selfish elements, and how they persist in organellar genomes, has not been explored. In the mitochondrial genome of a marine heterotrophic katablepharid protist, we identify a functional type II restriction modification system originating from a horizontal gene transfer event involving bacteria related to flavobacteria. This restriction modification system consists of an HpaII-like endonuclease and a cognate cytosine methyltransferase. We demonstrate that these proteins are functional by heterologous expression in both bacterial and eukaryotic cells. These results suggest that toxin-antitoxin selfish elements, such as restriction modification systems, could be co-opted by eukaryotic genomes to drive uniparental organellar inheritance.

evolutionary biology↗

bioRxiv2020

A genome-scale phylogeny of Fungi; insights into early evolution, radiations, and the relationship between taxonomy and phylogeny

Phylogenomic studies based on genome-scale amounts of data have greatly improved understanding of the tree of life. Despite their diversity, ecological significance, and biomedical and industrial importance, large-scale phylogenomic studies of Fungi are lacking. Furthermore, several evolutionary relationships among major fungal lineages remain controversial, especially those at the base of the fungal phylogeny. To begin filling these gaps and assess progress toward a genome-scale phylogeny of the entire fungal kingdom, we compiled a phylogenomic data matrix of 290 genes from the genomes of 1,644 fungal species that includes representatives from most major fungal lineages; we also compiled 11 additional data matrices by subsampling genes or taxa based on filtering criteria previously shown to improve phylogenomic inference. Analyses of these 12 data matrices using concatenation- and coalescent-based approaches yielded a robust phylogeny of the kingdom in which [~]85% of internal branches were congruent across data matrices and approaches used. We found support for several relationships that have been historically contentious (e.g., for the placement of Wallemiomycotina (Basidiomycota), as sister to Agaricomycotina), as well as evidence for polytomies likely stemming from episodes of ancient diversification (e.g., at the base of Basidiomycota). By examining the relative evolutionary divergence of taxonomic groups of equivalent rank, we found that fungal taxonomy is broadly aligned with genome sequence divergence, but also identified lineages, such as the subphylum Saccharomycotina, where current taxonomic circumscription does not fully account for their high levels of evolutionary divergence. Our results provide a robust phylogenomic framework to explore the tempo and mode of fungal evolution and directions for future fungal phylogenetic and taxonomic studies.

evolutionary biology↗

bioRxiv2020

A rat epigenetic clock recapitulates phenotypic aging and co-localizes with heterochromatin-associated histone modifications

Aging has been shown to be a strong driver of DNA methylation changes, leading to the development of robust biomarkers in humans and more recently, in mice. This study aimed to generate a novel epigenetic clock in rats--a model with unique physical, physiological, and biochemical advantages for studying mammalian aging. Additionally, we incorporated behavioral data, unsupervised machine learning, and network analysis to identify epigenetic signals that not only track with age, but also relate to phenotypic aging and reflect higher-order molecular aging changes. We used DNAm data from reduced representation bisulfite sequencing (RRBS) to train an epigenetic age (DNAmAge) measure in Fischer 344 CDF (F344) rats. In an independent sample of n=32 F344 rats, we found that this measure correlated with age at (r=0.93), and related to physical functioning (5.9e-3), after adjusting for age and differential cell counts. DNAmAge was also found to correlate with age in C57BL/6 mice (r=0.79), and was decreased in response to caloric restriction (CR), such that the longer the animal was on a CR diet, the greater the decrease in DNAm. We also observed resetting of DNAm when kidney and lung fibroblasts when converted to induced pluripotent stem cells (iPSCs). Using weighted gene correlation network analysis (WGCNA) we identified two modules that appeared to drive our DNAmAge measure. These two modules contained CpGs in intergenic regions that showed substantial overlap with histone marks H3K9me3, H3K27me3, and E2F1 transcriptional factor binding. In moving forward, our ability to unravel the complex signals linking DNA methylation changes to functional aging would require experimental studies in model systems in which longitudinal epigenetic changes can be related to other molecular and physiological hallmarks of aging.

molecular biology↗

bioRxiv2017

Revising transcriptome assemblies with phylogenetic information in Agalma1.0

MotivationOne of the most common transcriptome assembly errors is to mistake different transcripts of the same gene as transcripts from multiple closely related genes. It is difficult to identify these errors during assembly, but in a phylogenetic analysis these errors can be diagnosed from gene trees containing clades of tips from the same species with improbably short branch lengths.\n\nResultstreeinform is a module implemented in Agalma1.0 that uses phylogenetic analyses across species to refine transcriptome assemblies. It identifies transcripts of the same gene that were incorrectly assigned to multiple genes and reassign them as transcripts of the same gene.\n\nAvailability and Implementationtreeinform is implemented in Agalma1.0, available at https://bitbucket.org/caseywdunn/agalma.\n\nContactaugust_guang@brown.edu\n\nSupplementary informationSupplementary information is available at bioRxiv.

bioinformatics↗