bioRxivBiophysicsPreprint
Formation of homolog pairing-induced domains in early Drosophila embryo genome
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Abstract
Somatic homolog pairing is a defining feature of the diploid genome organization in Drosophila and underlies its transvection-based gene regulation. Here, to understand the physical effect of homolog pairing on the resulting three-dimensional (3D) organization, we employ the heterogeneous loop model and reconstruct 3D structures of the Drosophila embryo genome based on its haplotype-resolved Hi-C data. The resulting structures reveal robust end-to-end juxtaposition between homologous chromosomes amid substantial cell-to-cell variability. On sub-megabase scales, tight pairing between homologous loci at domain boundaries give rise to significant coincidence between cis and trans-homolog domain boundaries in the Hi-C map, while interior regions remain loosely associated. To uncover the physical origin of this organization, we compare the contact maps resulting from the polymer models implementing specific and non-specific button-mediated pairing mechanisms with Hi-C, finding that the intra-chromosomal contacts constrained by specifically paired inter-chromosomal buttons give rise to pairing-induced domains (PIDs). Our study suggests specific adhesive interactions as a central organizing principle of the diploid genome in Drosophila embryos. SignificanceSomatic homolog pairing distinguishes Drosophila from most eukaryotes; yet how the homolog pairing organizes Drosophila genome has remained elusive due to the lack of explicit model. By analyzing 3D structures reconstructed from haplotype-resolved Hi-C data, we clarify that specific homolog-recognizing buttons should generate pairing-induced domains that simultaneously organize cis and trans-homolog contacts. Our study provides a physical explanation on how a single molecular mechanism can simultaneously coordinate homolog pairing and architecture of chromatin domain in the diploid genome.
- organism: Drosophila
- assay: Hi-C
- research focus: chromatin & epigenetic regulation
- approach: statistical model
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