Fulai Jin

The paper identifies functional insulators (FINs) through Hi-C meta-analysis, showing they block enhancer-promoter interactions and are distinct from TAD boundaries.

This study shows that restoring STAG2 in STAG2-mutant cancer cells rapidly reduces global chromatin loop size, with limited transcriptional changes, including induction of EFEMP1.

This study uses eHiCA to identify regulatory interactions at the PICALM-EED locus, showing distinct chromatin interactions for SNPs within a segregating haplotype.

The paper identifies EGFR as a potential therapeutic target in Alzheimer's disease by linking a risk variant to increased EGFR expression in brain cell types through genomic analysis and CRISPRi validation.

The paper identifies ancestry-specific chromatin architecture differences in Alzheimer's Disease using Hi-C and ATAC-seq data from African and European ancestry individuals.

This study shows that H3K79 methylation and H3K36 tri-methylation work together to control gene expression and neural cell fate in pluripotent stem cells.

This study investigates the role of ORC2 in epigenetic regulation and chromosome structure through a multi-omics analysis of a human cell line with ORC mutations.

magpie evaluates statistical power for differential RNA methylation analysis in m6A sequencing by simulating data and assessing factors like sample size and effect size.

This study conducts a GWAS in Peruvians, identifying a novel AD risk locus in NFASC and replicating known loci, highlighting the importance of diverse populations in AD genetics.

The paper shows that ELA-associated increased chromatin accessibility and expression of APOE4 in astrocytes contribute to higher AD risk in APOE4/4 carriers.

INFIMA identifies effector genes of GWAS variants by integrating multi-omics data from mice and applying it to diabetes-associated variants.

The paper identifies differential regulatory control of APOEε4 on African versus European haplotypes through enhancer activity and promoter interactions analyses.

TWO-SIGMA is a single-cell RNA-seq differential expression method that handles drop-out, overdispersion, and within-sample correlation, outperforming existing methods in simulations and real data.

The paper develops an improved Hi-C protocol and bias-correction pipeline to map chromatin loops in human neurogenesis and brain tissues, showing their role in neural differentiation and GWAS gene identification.

Genome-wide association meta-analysis of 130,664 major depression cases and 330,470 controls identifies 44 independent risk loci enriched in cortical neurons, conserved mammalian regions, splicing networks, and antidepressant targets.

This paper introduces eHi-C, a protocol for 3D genome mapping using small cell populations, achieving high-quality results comparable to traditional Hi-C with fewer cells.