Biology subjects

Head, R.

Publications and source records attributed to Head, R..

4 recordsLinked to original sources

bioRxiv2026

High-order enhancer hubs buffer allelic regulatory variation through kinetic compensation

Diploid genomes carry millions of heterozygous variants in cis-regulatory DNA, yet most genes produce similar RNA output from two parental alleles. How this balance is maintained is unclear. We developed Nanopore-HiChIP, a long-read method that maps high-order enhancer hubs on each haplotype. Over half of these enhancer hubs differ in chromatin architecture and transcription-factor occupancy between homologous chromosomes, but their target genes show substantially lower rates of allele-specific expression than genes lacking hub regulation. Single-cell kinetic modeling shows that burst frequency and burst size change in opposite directions, thereby preserving balanced transcriptional output. This hub-mediated kinetic buffering is enriched at haploinsufficient genes and coincides with smaller effects of expression quantitative trait loci. Enhancer hubs therefore absorb allelic regulatory variation through kinetic compensation, protecting dosage-sensitive transcription.

genomics↗

bioRxiv2026

SnakeHichipTF reveals transcription factor logic underlying enhancer-promoter wiring in the human brain

Enhancer-promoter interactions are a central feature of gene regulation, yet the regulatory logic that governs their selective formation in complex tissues remains poorly understood. To address this gap, we developed SnakeHichipTF, a reproducible and scalable framework that integrates multi-engine HiChIP analysis with AI-based footprinting to decode the transcription factor (TF) logic underlying enhancer-promoter wiring. Applying SnakeHichipTF to HiChIP datasets from the human Middle Frontal Gyrus (MFG) and Substantia Nigra (SN), we identified distinct region-biased enhancer interactions associated with differential gene expression. MFG-biased interactions were enriched for cognitive and psychiatric associated GWAS traits, whereas SN-biased interactions preferentially intersected lipid and metabolic trait architectures. Integration of TF footprinting revealed that these region-biased interaction networks are governed by distinct TF programs: MFG-biased interactions preferentially recruited TFs linked to neuronal signaling and transcriptional activation, whereas SN-biased interactions were associated with metabolic and stress-responsive regulators. Interestingly, MFG-biased regulatory interactions were significantly enriched for Human Accelerated Regions (HARs), and HAR-associated genes showed elevated expression in humans relative to non-human primates, indicating that cortical enhancer wiring is embedded within evolutionarily modified regulatory elements. Together, by linking 3D chromatin architecture, TF logic, genetic risk, and evolutionary regulatory elements, SnakeHichipTF provides a general framework for dissecting the mechanistic basis of spatial gene regulation.

genomics↗

bioRxiv2025

TET CpG sequence context specific DNA demeth-ylation shapes progression of IDH-mutant gliomas

BackgroundTreatment decisions in IDH-mutant oligodendrogliomas are shaped by tumor aggressiveness, underscoring the need for objective grading of these malignant brain tumors. Material and MethodsWe collected 302 primary and recurrent resections from oligodendrogliomas and performed Ki-67 staining, proteomics and DNA methylation profiling. Results & conclusionDuring tumor progression, DNA methylation of oligodendrogliomas changed along a continuum. This continuum is linked to increased epigenetic aging, methylation of transcription factors and Ki-67+ cell density, and to large scale DNA demethylation. Demethylation was correlated with CpGs flanking sequences preferred by TET enzymes. We confirmed these findings in previously profiled astrocytomas, indicating IDH-mutant gliomas progress along a shared epigenetic axis. We developed an objective DNA methylation based prognostic continuous grading coefficient (CGC{psi}) that captured these changes and outperformed WHO grading for oligodendrogliomas. Our findings underscore the potential of DNA methylation-based grading to more accurately reflect tumor biology and inform clinical decision-making in IDH-mutant gliomas.

cancer biology↗

bioRxiv2025

SnakeAltPromoter Facilitates Differential Alternative Promoter Analysis

BackgroundAlternative promoter usage regulates isoform diversity in mammals, playing critical roles in development, disease, and cellular reprogramming. While Cap Analysis of Gene Expression (CAGE) enables precise transcription start site mapping, its high cost and limited coverage hinder scalability. In contrast, RNA-seq is abundant across biological contexts; several algorithms (ProActiv, Salmon, DEXSeq) infer promoter activity from these data, yet no unified, reproducible framework exists to execute, benchmark, and compare them or to scale alternative promoter analyses across large compendia. ResultsWe developed snakeAltPromoter, an end-to-end Snakemake workflow that ingests raw FASTQ files, performs quality control and alignment, quantifies promoter activity using three complementary strategies (junction-based, transcript-based, and first-exon-based), classifies promoters into major, minor/alternative, and inactive categories, and conducts both differential promoter activity and usage analysis. Crucially, snakeAltPromoter integrates a systematic benchmarking module against matched CAGE profiles to reveal method-specific strengths and limitations. ProActiv showed the highest concordance with CAGE in promoter classification, activity and differential analysis, Salmon was robust at low coverage and intronless cases. Overall, the complete workflow recovered a majority of CAGE-validated active promoters and processed a 50 M-read RNA-seq sample in around 2h on a 32-core node, demonstrating both accuracy and scalability. ConclusionssnakeAltPromoter is, to our knowledge, the first reproducible framework that pairs comparative method evaluation with scalable differential alternative promoter analysis. It provides concrete guidance for method selection under different experimental scenarios and enables high-throughput mining of promoter-level regulation from public RNA-seq repositories. Code and example data are freely available at https://github.com/YidanSunResearchLab/SnakeAltPromoter.git.

bioinformatics↗