Genomics

DNA replication STUDY and MODELING

The DNA replication initiation in metazoans is governed by a complex combination of factors,  not well described to a large extent. 
From our works on initiation probability landscape (IPL) for replication data, the methods developped in the previous period to extract the initiation probability landscape (IPL) from bulk experimental replication data, we deploy (i) Explainable AI to predict the IPL from chromatin mark profiles and learn the (epi)genomic rules contributing to this  for regulation and (ii) NN for imputation techniques to predict IPL from limited (epi)genomic data, even if not containing replication profiles (hard to obtain). Our replication model based on IPL allows to map replication stress in cancer samples, with impact on this health issue, and this has a societal implication in health. 

Development of signal processing for the analysis of single molecule and population profiling of DNA replication are also  continued.

Multiscale and multivariate methodologies for genomic data analysis

(ANR REFOPOL, O. Hyrien, ENS Paris, C. Thermes, CGM, Gif/Yvette, A. Goldar, CEA/Saclay) Multiscale and multivariate concepts and methodologies are necessary to account for the complexity of genome organization accommodating the tradeoff between DNA compaction and gene accessibility. We developed multiscale wavelet-based algorithms providing us with original clues about the mammalian DNA replication program. These signal-processing tools have now been accepted as bona fide molecular biology protocols. 
Using a wavelet-based multiscale pattern recognition framework, we described megabase sized replication domain covering about 1/3 of the human genome as N-shaped regions in DNA strand compositional asymmetry (skew) profiles. Determination of genome-wide replication timing profiles provided us with the experimental confirmation of that skew N-domain border are active replication origins. 
Further multiscale analysis of replication timing profiles lead us (i) to describe replication U-domains that display a characteristic U- shaped replication timing profile as the counter part to skew N-domains and (ii) to compute space-scale maps of effective DNA replication speed. These latter measurements are central to our modeling of DNA replication kinetic in mammalian genome. Using PCA, the apparent complexity of a dataset of 13 epigenetic marks was reduced to 4 epigenetic states. Each states correspond to a well defined replication timing window so that the progression of the replication along U-domains corresponds to a directional path across the four chromatin states. These results sheds a new light on the epigenetic regulation of the spatio-temporal replication program in human and provides a framework for further studies in different cell types, in both health and disease. 
Finally, in a preliminary work using a graph representation of high throughput chromatin conformation capture data, we showed that replication domain borders are hubs of the chromatin conformation interaction network.