Biology subjects

Brown, J. M.

Publications and source records attributed to Brown, J. M..

4 recordsLinked to original sources

bioRxiv2018

Single-cell chromatin interactions reveal regulatory hubs in dynamic compartmentalized domains

The promoters of mammalian genes are commonly regulated by multiple distal enhancers, which physically interact within discrete chromatin domains. How such domains form and how the regulatory elements within them interact within single cells is not understood. To address this we developed Tri-C, a new Chromosome Conformation Capture (3C) approach to identify concurrent chromatin interactions at individual alleles within single cells. The heterogeneity of interactions observed between such cells shows that CTCF-mediated formation of chromatin domains and interactions within them are dynamic processes. Importantly, our analyses reveal higher-order structures involving simultaneous interactions between multiple enhancers and promoters within individual cells. This provides a structural basis for understanding how multiple cis-elements act together to establish robust regulation of gene expression.

genetics↗

bioRxiv2018

Dispersal limitation and thermodynamic constraints govern spatial structure of permafrost microbial communities

Understanding drivers of permafrost microbial community composition is critical for understanding permafrost microbiology and predicting ecosystem responses to thaw, however studies describing ecological controls on these communities are lacking. We hypothesize that permafrost communities are uniquely shaped by constraints imposed by prolonged freezing, and decoupled from factors that influence non-permafrost soil communities. To test this hypothesis, we characterized patterns of environmental variation and microbial community composition in permafrost across an Alaskan boreal forest landscape. We used null modeling to estimate the relative importance of selective and neutral assembly processes on community composition, and identified environmental factors influencing ecological selection through regression and structural equation modeling (SEM). Proportionally, the strongest process influencing community composition was dispersal limitation (0.36), exceeding the influence of homogenous selection (0.21), variable selection (0.16), and homogenizing dispersal (0.05). Fe(II) content was the most important factor explaining variable selection, and was significantly associated with total selection by univariate regression (R2=0.14, p=0.003). SEM supported a model in which Fe(II) content mediated influences of the Gibbs free energy of the organic matter pool and organic acid concentration on total selection. These findings reveal that the processes shaping microbial communities in permafrost are distinct from those in non-permafrost soils, as the stability of the permafrost environment imposes dispersal and thermodynamic constraints on permafrost communities. Models of permafrost community composition will need to account for these unique drivers in order to predict community characteristics across permafrost landscapes, and in efforts to understand how pre-thaw conditions will influence post-thaw ecological and biogeochemical processes.

ecology↗

bioRxiv2017

A tissue-specific self-interacting chromatin domain forms independently of enhancer-promoter interactions

A variety of self-interacting domains, defined at different levels of resolution, have been described in mammalian genomes. These include Chromatin Compartments (A and B)1, Topologically Associated Domains (TADs)2,3, contact domains4,5, sub-TADs6, insulated neighbourhoods7 and frequently interacting regions (FIREs)8. Whereas many studies have found the organisation of self-interacting domains to be conserved across cell types389, some do form in a lineage-specific manner6710. However, it is not clear to what degree such tissue-specific structures result from processes related to gene activity such as enhancer-promoter interactions or whether they form earlier during lineage commitment and are therefore likely to be prerequisite for promoting gene expression. To examine these models of genome organisation in detail, we used a combination of high-resolution chromosome conformation capture, a newly-developed form of quantitative fluorescence in-situ hybridisation and super-resolution imaging to study a 70 kb self-interacting domain containing the mouse -globin locus. To understand how this self-interacting domain is established, we studied the region when the genes are inactive and during erythroid differentiation when the genes are progressively switched on. In contrast to many current models of long-range gene regulation, we show that an erythroid-specific, decompacted self-interacting domain, delimited by convergent CTCF/cohesin binding sites, forms prior to the onset of robust gene expression. Using previously established mouse models we show that formation of the self-interacting domain does not rely on interactions between the -globin genes and their enhancers. As there are also no tissue-specific changes in CTCF binding, then formation of the domain may simply depend on the presence of activated lineage-specific cis-elements driving a transcription-independent mechanism for opening chromatin throughout the 70 kb region to create a permissive environment for gene expression. These findings are consistent with a model of loop-extrusion in which all segments of chromatin, within a region delimited by CTCF boundary elements, can contact each other. Our findings suggest that activation of tissue-specific element(s)within such a self-interacting region is sufficient to influence all chromatin within the domain.

cell biology↗

bioRxiv2017

Unexpected variation across mitochondrial gene trees and evidence for systematic error: How much gene tree variation is biological?

The use of large genomic datasets in phylogenetics has highlighted extensive topological variation across genes. Much of this discordance is assumed to result from biological processes. However, variation among gene trees can also be a consequence of systematic error driven by poor model fit, and the relative importance of these biological versus methodological factors in explaining gene tree variation is a major unresolved question in phylogenetics. Using mitochondrial genomes to control for biological causes of gene tree variation, we estimate the extent of gene tree discordance driven by systematic error and employ posterior prediction to highlight the role of model fit. We find that the amount of discordance among mitochondrial gene trees is similar to the amount of discordance found in other studies that assume only biological causes of variation. This similarity suggests that the role of systematic error in generating gene tree variation is underappreciated and that critical evaluation of the fit between assumed models and the data used for inference is important for the resolution of unresolved phylogenetic questions.

evolutionary biology↗