Biology subjects

Forneris, M.

Publications and source records attributed to Forneris, M..

5 recordsLinked to original sources

bioRxiv2025

Heterotypic directional motifs contribute to TAD boundary function in Drosophila

While convergent CTCF binding sites are essential for topologically associating domain (TAD) formation in mammals, how TADs are formed in other species remains unclear. In Drosophila, TAD boundaries lack convergent CTCF sites and are occupied by different insulator protein combinations with no obvious pairing rules. To identify sequence features required for boundary pairing, we inserted different endogenous boundaries into two Drosophila TADs in both orientations, creating 53 ectopic insertions and measured their ability to form interactions with the endogenous boundaries to their left and right. 70% of inserted boundaries had context- and/or orientation-dependent effects, indicating specificity and directionality encoded in their sequence. Known insulator motifs or promoters could not explain boundary specificity. Instead, we identified heterotypic pairs of directional motifs that predict compatible boundary pairs. Our results indicate that directional motif pairs are a conserved property of boundaries from flies to mammals, but gained complexity in Drosophila through heterotypic combinations.

genomics↗

bioRxiv2025

SPT5 regulates Pol II pausing and elongation in different ways at early versus late embryonic stages

Transcription involves a cycle of initiation, pausing, elongation, and termination. SPT5 regulates both promoter proximal pausing and elongation, but how it orchestrates both steps during dynamic changes in gene expression remains unclear. Here, using Drosophila embryogenesis, we show that pausing both precedes and follows gene expression, while active transcription is accompanied by pause release. Optogenetic rapid depletion of SPT5 from the nucleus uncovered different sensitivities at different developmental stages. In early embryogenesis, SPT5 depletion caused a downstream shift in Pol II pausing to the +1 nucleosome, resulting in defective elongation and early termination. In late embryogenesis, it led to both up- and downregulation of expression, depending on the genes transcriptional and pausing state - upregulation is caused by pause release while downregulation is due to defective elongation. These changes are intensified when genes are increasing or decreasing their transcriptional state, indicating that SPT5 contributes to fine-tuning dynamic changes in gene expression.

genomics↗

bioRxiv2025

Chip (Ldb1) is a new cofactor of Zelda forming a functional bridge to CBP during zygotic genome activation

The cofactor Ldb1 (Chip) is linked to many processes in gene regulation, including enhancer-promoter communication, inter-chromosomal interactions and enhanceosome-cofactor-like activity. However, its functional requirement and molecular role during embryogenesis has not been assessed to date. Here, we used optogenetics (iLEXY), to rapidly deplete Drosophila Ldb1 (Chip) from the nucleus at precise time windows. Remarkably, this pinpointed the essential window of Chips function in just one-hour of embryogenesis, overlapping zygotic genome activation (ZGA). We show that Zelda, a pioneer factor essential for ZGA, recruits Chip to chromatin, and both factors regulate concordant changes in gene expression, suggesting that Chip is a cofactor of Zelda. Surprisingly, Chip is not required for chromatin architecture at these stages, instead it recruits CBP, and is essential for the placement of H3K27ac. Taken together, our results identify Chip (Ldb1) as a functional bridge between Zelda and the coactivator CBP to regulate gene expression in early embryogenesis.

genomics↗

bioRxiv2024

Contextualising transcription factor binding during embryogenesis using natural sequence variation

Understanding how genetic variation impacts transcription factor (TF) binding remains a major challenge, limiting our ability to model disease-associated variants. Here, we used a highly controlled system of F1 crosses with extensive genetic diversity to profile allele-specific binding of four TFs at several embryonic time-points, using Drosophila as a model. Using a combined haplotype test, we identified 9-18% of TF bound regions impacted by genetic variation. By expanding WASP (a tool for allele-specific read mapping) to examine INDELs, we increased detection of allele imbalanced (AI) peaks by 30-50%. This fine-grained mutagenesis could reconstruct functionalized binding motifs of all factors. To prioritise potential causal variants, we trained a convolutional neural network (Basenji) to predict TF binding from DNA sequence. The model could accurately predict experimental AI for strong effect variants, providing a mechanistic interpretation for how genetic variation impacted TF binding. This revealed unexpected relationships between TFs, including potential cooperative pairs, and mechanisms of tissue specific recruitment of the ubiquitous factor CTCF.

genetics↗

bioRxiv2020

Predictive features of gene expression variation reveal a mechanistic link between expression variation and differential expression

For most biological processes, organisms must respond to extrinsic cues, while maintaining essential gene expression programs. Although studied extensively in single cells, it is still unclear how variation is controlled in multicellular organisms. Here, we used a machine-learning approach to identify genomic features that are predictive of genes with high versus low variation in their expression across individuals, using bulk data to remove stochastic cell-to-cell variation. Using embryonic gene expression across 75 Drosophila isogenic lines, we identify features predictive of expression variation, while controlling for expression level. Genes with low variation fall into two classes, indicating they employ different mechanisms to maintain a robust expression. In contrast, genes with high variation seem to lack both types of stabilizing mechanisms. Applying the framework to human tissues from GTEx revealed similar predictive features, indicating that promoter architecture is an ancient mechanism to control expression variation. Remarkably, expression variation features could also predict differential expression upon stress in both Drosophila and human. Differential gene expression signatures may therefore be partially explained by genetically encoded gene-specific features, unrelated to the studied treatment.

genomics↗