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Biology subjects

Kan, R. L.

Publications and source records attributed to Kan, R. L..

2 recordsLinked to original sources

A Meta-Atlas of the Developing Human Cortex Identifies Modules Driving Cell Subtype Specification

Human brain development requires the generation of hundreds of diverse cell types, a process targeted by recent single-cell transcriptomic profiling efforts. Through a meta-analysis of seven of these published datasets, we have generated 225 meta-modules - gene co-expression networks that can describe mechanisms underlying cortical development. Several meta-modules have potential roles in both establishing and refining cortical cell type identities, and we validated their spatiotemporal expression in primary human cortical tissues. These include meta-module 20, associated with FEZF2+ deep layer neurons. Half of meta-module 20 genes are putative FEZF2 targets, including TSHZ3, a transcription factor associated with neurodevelopmental disorders. Human cortical organoid experiments validated that both factors are necessary for deep layer neuron specification. Importantly, subtle manipulations of these factors drive slight changes in meta-module activity that cascade into strong differences in cell fate - demonstrating how of our meta-atlas can engender further mechanistic analyses of cortical fate specification.

developmental biology↗

A gene silencing screen uncovers diverse tools for targeted gene repression in Arabidopsis

DNA methylation has been utilized for target gene silencing in plants, however its not well-understood whether other silencing pathways can be also used to manipulate gene expression. Here we performed a gain of function screen for proteins that could silence a target gene when fused to an artificial zinc finger. We uncovered many proteins that suppressed gene expression either through the establishment of DNA methylation, or via DNA methylation-independent processes including histone H3K27me3 deposition, H3K4me3 demethylation, H3K9, H3K14, H3K27, and H4K16 deacetylation, inhibition of RNA Polymerase II transcription elongation or Ser-5 dephosphorylation. The silencing fusion proteins also silenced many other genes with different efficacy, and a machine learning model could accurately predict the efficacy of each silencer based on various chromatin features of the target loci. These results provide a more comprehensive understanding of epigenetic regulatory pathways and provide an armament of tools for targeted manipulation of gene expression.

plant biology↗