The Tbx1 gene is haploinsufficient in mice and in humans, where it causes a DiGeorge syndrome phenotype characterized by developmental deficits of the pharyngeal apparatus. TBX1 plays a critical role in the differentiation and regionalization of the cardiopharyngeal mesoderm lineage and its derivatives. Nevertheless, its regulation is incompletely understood. Here we used a combination of computational and wet-lab approaches to identify regulatory sequences of the Tbx1 gene, and we use single-cell molecular analysis as a read-out and to establish the consequences of their deletion. Results revealed a cluster of regulatory sequences with at least three distinct elements. Elimination of the entire cluster caused a near shut down of the gene, while individual deletions had milder, quantitative effects. Transcriptomic analyses of the deletion mutants revealed the down regulation of genes related to cardiopharyngeal lineage specification and, more surprisingly, up regulation and anteriorization of genes related to embryonic patterning, thereby providing a rationale for the severe dysmorphogenesis of the posterior pharyngeal apparatus observed in Tbx1 mutant mice.
S. Allegretti, O. Lanzetta, M. Bilio et al.· bioRxiv· 0 citations
Abstract Motivation Inferring gene networks from single-cell RNA sequencing data is challenging due to high sparsity, dimensionality, and technical noise. Current pipelines lack the multi-dataset integration and comprehensive post-processing analysis. Results scGraphVerse is an R package that integrates multiple algorithms (GENIE3, GRNBoost2, ZILGM, PCzinb, and JRF) with extensive evaluation and visualization tools. Its modular workflow supports early, late, and joint integration strategies for multi-dataset analysis, providing standardized input/output interfaces and biological interpretation tools, including community detection, pathway enrichment, and literature mining. Benchmarking on simulated data showed model-based methods (PCzinb and ZILGM) perform well with limited sample sizes, while JRF performs best as the network size and dataset numbers increase. A PBMC case study demonstrates JRF’s ability to identify literature-supported regulatory communities across donors. Availability and implementation The package is available in Bioconductor 3.22 at https://bioconductor.org/packages/release/bioc/html/scGraphVerse.html. Code and examples: https://github.com/ngsFC/scGV_analysis.
Francesco Cecere, D. De Canditiis, Annamaria Carissimo et al.· Bioinformatics Advances· 0 citations
The results indicate that GmGM provides a unified, reproducible framework for joint cell clustering and gene-network inference, capable of revealing cellular structure beyond that captured by conventional pipelines.
O. Lanzetta, L. Cutillo, Bailey Andrew et al.· 0 citations
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