Biology subjects

Jhanwar, S.

Publications and source records attributed to Jhanwar, S..

3 recordsLinked to original sources

bioRxiv2024

TBX3 is essential to establish the posterior boundary of anterior genes and up-regulate posterior genes with HAND2 during onset of limb bud development

During limb bud formation, axes polarities are established as evidenced by the spatially restricted expression of key regulator genes. In particular, the mutually antagonistic interaction between the GLI3 repressor and HAND2 results in the distinct and non-overlapping anterior-distal Gli3 and posterior Hand2 expression domains. This hallmarks establishment of antero-posterior (AP) limb axis polarity together with spatially restricted expression of homeodomain and other transcriptional regulators. Here, we identify TBX3 as the transcription factor to initiate AP axis polarity in mouse limb buds. ChIP-seq and differential gene expression analysis of wildtype and mutant limb buds identifies the TBX3-specific and shared TBX3-HAND2 target genes. High sensitivity fluorescent whole mount in situ hybridisation shows that the posterior expression boundaries of anterior genes are positioned by TBX3-mediated repression, which excludes anterior genes such as Gli3, Alx4, Hand1 and Irx3/5 from the posterior limb bud mesenchyme. This exclusion delineates the posterior mesenchymal territory competent to establish the Shh-expressing limb bud organiser. In turn, HAND2 is required for Shh activation and cooperates with TBX3 to up-regulate shared posterior identity target genes in early limb buds.

developmental biology↗

bioRxiv2021

Environmental enrichment induces epigenomic and genome organization changes relevant for cognitive function

In early development, the environment triggers mnemonic epigenomic programs resulting in memory and learning experiences to confer cognitive phenotypes into adulthood. To uncover how environmental stimulation impacts the epigenome and genome organization, we used the paradigm of environmental enrichment (EE) in young mice constantly receiving novel stimulation. We profiled epigenome and chromatin architecture in whole cortex and sorted neurons by deep-sequencing techniques. Specifically, we studied chromatin accessibility, gene and protein regulation, and 3D genome conformation, combined with predicted enhancer and chromatin interactions. We identified increased chromatin accessibility, transcription factor binding including CTCF-mediated insulation, differential occupancy of H3K36me3 and H3K79me2, and changes in transcriptional programs required for neuronal development. EE stimuli led to local genome re-organization by inducing increased contacts between chromosomes 7 and 17 (inter-chromosomal). Our findings support the notion that EE-induced learning and memory processes are directly associated with the epigenome and genome organization. Highlights- Environmental enrichment (EE) alters chromatin conformation, CTCF binding, and spatially 3D genome changes, thereby regulating cognitive function during the first steps of life after birth. - Transcription-associated gene body marks H3K79me2 and H3K36me3 are differently influenced by EE in cortical brain cells and binding is exacerbated upon stimulation in an age-dependent manner. - EE-induced changes of 3D genome organization increase inter-chromosomal interactions of genes associated with synaptic transmission and AMPA receptor genes on chromosomes 7 and 17.

neuroscience↗

bioRxiv2018

Genome-wide active enhancer identification using cell type-specific signatures of epigenomic activity

Recently enhancers have emerged as key players regulating crucial mechanisms such as cell fate determination and establishment of spatiotemporal patterns of gene expression during development. Due to their functional and structural complexity, an accurate in silico identification of active enhancers under specific conditions remain challenging. We present a novel machine learning based method that derives epigenomic patterns exclusively from experimentally characterized active enhancers contrasted with a weighted set of non-enhancer genomic regions. We demonstrate better predictive performance over previous methods, as well as wide generalizability by identifying and annotating active enhancers genome-wide across different tissues/cell types in human and mouse.

bioinformatics↗