CLASH (Chromatin Loop Across-sample Score Harmonizer) quantifies the relative contributions of genetic variation, methylation, and CTCF occupancy on chromatin loop strength across individuals

Three-dimensional genome organization constrains the regulatory interactions that govern vital cellular processes. Chromatin loops are key features of genome folding, yet it is unclear how genetic and epigenetic variation influences differential loop formation across individuals. Loops primarily form between two CTCF binding proteins, which recognize a specific motif at loop anchors. CTCF binding site motifs are frequently altered by base substitutions, structural variation, and 5-methylcytosine (mC) CpG methylation, yet no study has comprehensively profiled this variation across diverse individuals. Moreover, existing approaches relying on binary loop calls fail to capture subtle changes in genetic and epigenetic features, as well as CTCF occupancy, that drive variation in loop strength. Here, we combined high-resolution Hi-C, Fiber-seq, near telomere-to-telomere phased assemblies, and mC methylation maps across five lymphoblastoid cell lines to quantify how genetic and epigenetic variation shape genome folding. We used DiffHiC to identify 367 differential pixels and found that sequence variation, chromatin accessibility, and mC CpG methylation are each significantly associated with differential chromatin contacts. Next, we developed CLASH (Chromatin Loop Across-sample Score Harmonizer) to harmonize loop calls across samples and enable robust comparisons of loop strengths across individuals. CLASH substantially improved loop calls and loop score calibration with respect to the classification boundary over existing methods and confirmed a significant relationship between CTCF occupancy and loop strength. We then characterized independent contributions of sequence and epigenetic variation to differential loop formation, demonstrating that 57% of sequence variation- and 40% of methylation-associated effects on loop formation acted through CTCF occupancy. Together, we present a multimodal dataset and computational approach to facilitate the study of 3D genome structure across human populations.