An interdisciplinary network for 3D genomics

Context and challenges

In the nucleus of an or plant cell, the three-dimensional conformation of the genome has a major impact on how it functions, affecting key processes such as cell differentiation, embryonic development and organism survival. It is known that the 3D structures regulating these processes are organised hierarchically at various levels of scale. However, little is known about the multi-scale dynamics of these structures and their interactions, limiting our understanding of the links between genome structure and function.
Recent advances in molecular biology have made it possible to change the way in which the spatial organisation of chromosomes is studied, thanks to DNA sequencing technology known as Hi-C (High-throughput chromosome conformation capture).
However, the data generated in this way is difficult to analyse, mainly because of its particular format: the distances between genome positions form a matrix. Identifying significant differences between groups of large matrices, for example, represents a significant methodological challenge.

Objectives

The CHROCONET (CHROmatin COnformation NETwork) aims to bring together an interdisciplinary community and promote scientific exchanges around the comparative analysis of 3D genomics data.  

The nature of the project and the issues at stake require collaboration between different fields. The consortium therefore involves several complementary disciplines:

• cell biology and molecular genetics, for data production and interpretation of results
• mathematics and statistics, for methodological developments, in particular concerning the modelling and statistical validity of the tests to be carried out
• bioinformatics, for processing sequencing data, implementing software and organising data, metadata and results.

Building on this original collaboration, the CHROCONET consortium aims to improve Hi-C data analysis methods to better understand the links between the 3D structure of the genome and its functioning.

Contacts :

Units involved and partnerships

INRAE participants

Partners

Publications

Journal Articles

• Neuvial, P., Randriamihamison, N., Chavent, M., Foissac, S., & Vialaneix, N. (2024). A two-sample tree-based test for hierarchically organized genomic signals. Journal of the Royal Statistical Society: Series C Applied Statistics, pp. qlae011. https://doi.org/10.1093/jrsssc/qlae011. HAL: hal-04516167.
• Jorge E., Foissac S., Neuvial P., Zytnicki M., Vialaneix N. A comprehensive review and benchmark of differential analysis tools for Hi-C data. Briefings in Bioinformatics, 2025, vol. 26(2). DOI : 10.1093/bib/bbaf074. HAL : hal-04989132.

Communications and posters

• Jorge É., Hocking T. D., Neuvial P., Vialaneix N., Foissac S. HICREAM : Méthode d'analyse différentielle de données Hi-C par inférence post hoc et visualisation interactive. 57e Journées de Statistique de la SFdS (JdS 2026), Société Française de Statistique, Clermont-Ferrand, France, juin 2026. HAL : hal-05651523.
• Jorge É., Foissac S., Neuvial P., Zytnicki M., Vialaneix N. A comprehensive review and benchmark of differential analysis tools for Hi-C data. ISMB/ECCB 2025, Liverpool, Royaume-Uni, juillet 2025. HAL : hal-05185342.

R Packages Developed by Network Members on the CHROCONET Theme

- treediff: Testing Differences Between Families of Trees

- hicream: HIC diffeREntial Analysis Method

- HiCDOC: A/B compartment detection and differential analysis