Hi-C Data from 1,025 Species Reveal Distinct Trends in the Evolution of 3D Genome Organization in Plants and Animals

Background: Genome Organization Differs Across Biological Lineages
A study comparing Hi-C data from 1,025 species, from archaea to animals, found that three-dimensional genome organization follows different patterns across biological lineages. Global folding structures were commonly observed in bacteria, while a rough checkerboard pattern predominated in archaea. Plant and animal evolution also showed distinct structural trends.
Three-dimensional genome organization is closely linked to key cellular processes, including DNA replication and gene regulation. Yet the evolutionary patterns of genome architecture across diverse lineages had not been fully characterized. Kai Ye and colleagues broadened the scope of comparison by assembling and analyzing Hi-C data from a range of lineages. The study included archaea, bacteria, fungi, plants, and animals.
The study was featured in a research highlight by Tiago Faial published in Nature Genetics. The original research covered by the highlight was published in Cell.
Key Findings: Contrasting Global Folding and Checkerboard Structures
The analysis focused on two forms of higher-order genome organization. Global folding refers to the spatial organization of the karyotype, while checkerboard structure refers to the spatial organization of chromatin compartments. The researchers compared genome organization across multiple lineages with a focus on these two structures.
Many bacteria showed global folding, whereas a rough checkerboard pattern appeared in most archaea. In plants, global folding gradually became the most prominent observed structure over the course of evolution. Animal evolution showed a tendency toward more complex checkerboard structures. The findings provide a basis for distinguishing the spatial organization prominent in each lineage rather than explaining all organisms with a single folding type.
The researchers also proposed that the genome organization of ancestral unicellular organisms may have been random. This is an inference about an ancestral state; the available highlight does not describe the detailed methods behind the inference or provide quantified uncertainty.
Significance and Outlook: Value as a Comparative Resource and Scope of Interpretation
The analysis is valuable for comparing the evolution of genome architecture using data spanning 1,025 species. Examining which structures are prominent in different lineages can help refine questions for follow-up studies. The highlight described the dataset as a useful resource for understanding genome evolution across multiple dimensions.
However, observations of lineage-specific structural differences alone do not establish that a particular structure caused changes in gene expression or traits. The material available for this review was a public highlight rather than the full original study, so species-level sample composition, data resolution, analytical conditions, and statistical uncertainty could not be verified. There is also no basis here to interpret the findings as demonstrating predictive performance for disease-associated variants or the effectiveness of gene therapy design.
Source: Nature Genetics research highlight, “Evolution of genome architecture”. The DOI of the original Cell study covered by the highlight is 10.1016/j.cell.2026.03.042; the full original study was outside the scope of this review.
EMOTION_TAG: interesting
Nature Genetics, Published online: 14 May 2026. DOI: 10.1038/s41588-026-02623-w
Summary: Integrating high-resolution Hi-C sequencing and AI-driven structural modeling, this study uncovers the 3D design principles of genome evolution. Transposable elements (TEs) are identified as key architectural drivers that reshape topologically associating domains (TADs) and create novel regulatory loops. This 3D perspective explains how structural variations drive evolutionary innovation and provides a predictive framework for disease-associated genomic rearrangements.
Comparative genomics researchers can use this dataset as a starting point for comparing the spatial organization of genomes across lineages, including plants and animals. For example, they could examine whether a structure observed in an organism of interest aligns with the global folding or checkerboard trends reported for that lineage and, if differences exist, select them for follow-up analysis. Before reanalysis, they should check the original study’s sample composition, data-processing conditions, data accessibility, and reuse terms. Separate evidence is also needed to test whether differences in spatial structure lead to functional differences. The practical significance supported by the available highlight lies in extending basic comparative research.