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Navandar, M.

Publications and source records attributed to Navandar, M..

2 recordsLinked to original sources

16p11.2 Copy Number Variation Alters Genome Architecture and Transcriptional Regulation During Neurodevelopment

Microdeletions and microduplications in 16p11.2 are responsible for a spectrum of neurodevelopmental disorders (NDDs) with partially reciprocal and overlapping symptoms. However, the clinical variability in 16p11.2 microduplication patients is significantly greater than that in patients carrying a microdeletion. Here, we use iPSCs derived from members of a family carrying a 16p11.2 microduplication and model neurodevelopment through in vitro differentiation into neural progenitor cells (NPCs) and neurons. The analysis is complemented by reanalysis of publicly available data from 16p11.2 microdeletion patients. Transcriptome analysis revealed MAPK3-centered hubs of upregulated genes in the microduplication-carrying and downregulated in the microdeletion-carrying cells, indicating that MAPK3 is a central driver of 16p11.2 Copy Number Variation (CNV) pathology. While genes within the 16p11.2 region showed about a two-fold reduction in expression in cells carrying the microdeletion, their expression levels in microduplication-derived NPCs and neurons, but not in iPSCs, were elevated to a degree much higher than expected. This observation was accompanied by a substantial number of dysregulated genes unrelated to the genes in the critical region or their interaction networks. To further investigate whether altered chromatin organization may accompany these transcriptional changes, we generated Hi-C data from patient and control iPSCs and NPCs. This revealed increased chromatin contacts within the duplicated 16p11.2 region in patient-derived iPSCs, while genome-wide compartment analysis showed that increased compartments preferentially co-occurred with upregulated differentially expressed genes, particularly in NPCs. Together, these findings suggest that 16p11.2 microduplication may influence gene expression through both local dosage-dependent mechanisms and broader, differentiation-associated changes in chromatin organization. Our data support a model in which CNV-associated genome architecture changes may modulate transcriptional dysregulation and contribute to the variable neurodevelopmental phenotypes associated with 16p11.2 rearrangements.

pathology↗

Low-cost scalable discretization, prediction and feature selection for complex systems

Finding reliable discrete approximations of complex systems is a key prerequisite when applying many of the most popular modeling tools. Common discretization approaches (for example, the very popular K-means clustering) are crucially limited in terms of quality and cost. We introduce a low-cost improved-quality Scalable Probabilistic Approximation (SPA) algorithm, allowing for simultaneous data-driven optimal discretization, feature selection and prediction. Cross-validated applications of SPA to a range of large realistic data classification and prediction problems reveal drastic cost and performance improvements. For example, SPA allows the unsupervised next-day surface temperature predictions for Europe with the mean crossvalidated one-day prediction error of 0.75{degrees}C on a common PC (being around 40% better in terms of errors and five to six orders-of-magnitude cheaper than the next-day surface temperature predictions calculated on supercomputers and provided by the weather services).\n\nOne Sentence SummaryIntroduced computational tool allows obtaining drastic cost and quality gains for a broad range of science applications.

bioinformatics↗