Mikhail Spivakov

SPARK reconstructs enhancer-based gene regulatory networks using single-cell multiomics data and prior knowledge, revealing regulatory links associated with immune disease GWAS variants.

This study shows that the FACT complex regulates cohesin dynamics on chromatin, facilitating loop extrusion and preventing cohesin accumulation in transcribed regions.

The paper investigates the chromosomal contacts of poised enhancers during the transition from naive to primed human pluripotency, revealing their dynamics and functional significance.

This study reveals a unique 3D genome architecture in premeiotic gonadal germ cells, linked to epigenetic reprogramming and loss of TADs, alongside DNA demethylation.

The paper combines natural and engineered genetic variation to identify 22 non-coding variants affecting haematological traits and shows how a CUX1 variant impacts megakaryopoiesis.

This study identifies causal genes and mechanisms for juvenile idiopathic arthritis by integrating GWAS, PCHi-C, ATAC-seq, and CRISPRa/i in CD4+ T cells from JIA patients.

This study shows ZKSCAN3 represses enhancers by targeting retrotransposons without forming heterochromatin, linking it to neurodevelopmental processes and schizophrenia.

The paper identifies trimodal QTLs that jointly affect enhancer accessibility, promoter contacts, and gene expression in monocytes, revealing genetic links between enhancer activity and chromatin boundaries.

This study identifies rapid brain-wide synaptic remodeling in hyperacute stroke, showing structural and functional changes in the ischemic core, penumbra, and contralateral cortex.

The paper identifies and validates novel regulators of vascular smooth muscle cell proliferation using network analysis and experimental validation, highlighting RUNX1 and the TIMP1-CD74 axis as potential therapeutic targets.

The paper maps promoter interactions in human ILC3s using PCHi-C and links GWAS risk variants to target genes, identifying new autoimmune disease risk genes.

The paper investigates chromosomal contacts between promoters and enhancers using Capture Hi-C, showing that cohesin depletion affects long-range contacts but not shorter-range ones.

The paper identifies over 1300 transcription factor binding variants in CRMs associated with gene expression in human LCLs, revealing epromoters as dual-action regulatory elements.

Chicdiff detects differential chromosomal interactions in Capture Hi-C data by improving normalization and statistical methods, identifying cell type-specific interactions in human Monocytes and CD4+ T cells.

The paper identifies how variation in PU.1 binding and chromatin looping at neutrophil enhancers influences autoimmune disease susceptibility and cell count differences.

This paper introduces GRN-loop, a method combining 3D chromatin architecture with gene expression data to identify key transcription factors and DNA elements driving neural lineage commitment.

The paper identifies DNA methylation oscillations as a marker for enhancer classification, showing high predictive power compared to other methods.

The paper identifies autoimmune disease candidate genes by integrating promoter capture Hi-C data with genetic associations in activated CD4+ T cells.

CHiCAGO detects DNA looping interactions in Capture Hi-C data by addressing statistical challenges with a background model and normalization algorithms, showing enrichment for regulatory features and disease SNPs.