%0 Journal Article %A Ruchi Lohia %A Nathan Fox %A Jesse Gillis %T A global high-density chromatin interaction network reveals functional long-range and trans-chromosomal relationships %D 2022 %R 10.1101/2022.03.24.485503 %J bioRxiv %P 2022.03.24.485503 %X Chromatin contacts are essential for gene-expression regulation, however, obtaining a high-resolution genome-wide chromatin contact map is still prohibitively expensive owing to large genome sizes and the quadratic scale of pairwise data. Chromosome conformation capture (3C) based methods such as Hi-C have been extensively used to obtain chromatin contacts. However, since the sparsity of these maps increases with an increase in genomic distance between contacts, long-range or trans chromatin contacts are especially challenging to sample.Here, we created a high density reference genome-wide chromatin contact map using a meta-analytic approach. We integrate 3600 Human, 6700 Mouse, and 500 Fly 3C experiments to create species-specific meta-3C contact maps with 304 billion, 193 billion, and 19 billion contacts in respective species. We validate that meta-3C are uniquely powered to capture functional chromatin contacts in both cis and trans. Unlike individual experiments, meta-3C gene contacts predict gene coexpression for long-range and trans chromatin contacts. Similarly, for long-range cis-regulatory interactions, meta-3C contacts outperform both all individual experiments, providing an improvement over the conventionally used linear genomic distance-based association. Assessing between species, we find patterns of chromatin contacts conservation in both cis and trans and strong associations with coexpression even in species for which 3C data is lacking.We have generated an integrated chromatin interaction network which complements a large number of methodological and analytic approaches focused on improved specificity or interpretation. This high-depth “super-experiment” is surprisingly powerful in capturing long-range functional relationships of chromatin interactions, which are now able to predict coexpression, expression quantitative trait loci (eQTL), and cross-species relationships.Competing Interest StatementThe authors have declared no competing interest. %U https://www.biorxiv.org/content/biorxiv/early/2022/03/27/2022.03.24.485503.full.pdf