Biology subjects

Bhakta, M. S.

Publications and source records attributed to Bhakta, M. S..

2 recordsLinked to original sources

bioRxiv2023

High-resolution CTCF footprinting reveals impact of chromatin state on cohesin extrusion dynamics

DNA looping is vital for establishing many enhancer-promoter interactions. While CTCF is known to anchor many cohesin-mediated loops, the looped chromatin fiber appears to predominantly exist in a poorly characterized actively extruding state. To better characterize extruding chromatin loop structures, we used CTCF MNase HiChIP data to determine both CTCF binding at high resolution and 3D contact information. Here we present FactorFinder, a tool that identifies CTCF binding sites at near base-pair resolution. We leverage this substantial advance in resolution to determine that the fully extruded (CTCF-CTCF) state is rare genome-wide with locus-specific variation from ~1-10%. We further investigate the impact of chromatin state on loop extrusion dynamics, and find that active enhancers and RNA Pol II impede cohesin extrusion, facilitating an enrichment of enhancer-promoter contacts in the partially extruded loop state. We propose a model of topological regulation whereby the transient, partially extruded states play active roles in transcription.

genomics↗

bioRxiv2021

Dynamic Gene-Based Ecophysiological Models to Predict Phenotype from Genotype and Environment Data

Predicting the phenotype from the genotype is one of the major contemporary challenges in biology. This challenge is greater in plants because their development occurs mostly post-embryonically under diurnal and seasonal environmental fluctuations. Current phenotype prediction models do not adequately capture all of these fluctuations or effectively use genotype information. Instead, we have developed a dynamic modular approach that captures the genotype, environment, and Genotype-by-Environment effects to express the time-to-flowering phenotype in real time in Phaseolus vulgaris. The module we describe can be applied to different plant processes and can gradually replace processes in existing crop models. Our model can enable accelerated progress in diverse breeding programs, particularly with the prospects of climate change. Finally, a gene-based simulation model can assist policy decision makers in matters pertaining to prediction of food supplies.

plant biology↗