Dynamique et synchronisme de réplication de l'ADN dans des cellules vivantes -- Analyse de marqueurs fluorescents

International audienceThis communication deals with the analysis of cellular biology data, for the analysis of replication timing and synchonization between allels. Data are obtained via cytometric imaging. The analysis include the development of a statistical model, the estimation of the parameter of a mixture of distributions. Results are validated through statistical tests and quantified using a bootstrap technique. From the biological point of view, new mechanisms involved in replication are exhibited.Cette communication présente l'analyse de données de biologie cellulaire en vue de l'étude du \textit{timing} et de la synchronie de réplication des allèles. Les données disponibles sont acquises massivement par une technique d'imagerie cytométrique. L'analyse fait notamment intervenir la définition d'un modèle statistique et l'identification des paramètres d'un mélange de distributions. Les résultats sont validés par des tests statistiques et quantifiés par bootstrap. Du point de vue biologique, des nouveaux mécanismes intervenant dans la réplication sont exhibés

Clustering of strong replicators associated with active promoters is sufficient to establish an early-replicating domain

Vertebrate genomes replicate according to a precise temporal program strongly correlated with their organization into A/B compartments. Until now, the molecular mechanisms underlying the establishment of early-replicating domains remain largely unknown. We defined two minimal cis-element modules containing a strong replication origin and chromatin modifier binding sites capable of shifting a targeted mid-late-replicating region for earlier replication. The two origins overlap with a constitutive or a silent tissue-specific promoter. When inserted side-by-side, these modules advance replication timing over a 250 kb region through the cooperation with one endogenous origin located 30 kb away. Moreover, when inserted at two chromosomal sites separated by 30 kb, these two modules come into close physical proximity and form an early-replicating domain establishing more contacts with active A compartments. The synergy depends on the presence of the active promoter/origin. Our results show that clustering of strong origins located at active promoters can establish early-replicating domains

Evolution of replication origins in vertebrate genomes: rapid turnover despite selective constraints

The replication program of vertebrate genomes is driven by the chromosomal distribution and timing of activation of tens of thousands of replication origins. Genome-wide studies have shown the association of origins with promoters and CpG islands, and their enrichment in G-quadruplex motifs (G4). However, the genetic determinants driving their activity remain poorly understood. To gain insight on the constraints operating on origins, we conducted the first evolutionary comparison of origins across vertebrates. We generated a genome-wide map of chicken origins (the first of a bird genome), and performed a comparison with human and mouse maps. The analysis of intra-species polymorphism revealed a strong depletion of genetic diversity at the core of replication initiation loci. This depletion is not linked to the presence of G4 motifs, promoters or CpG islands. In contrast, we show that origins experienced a rapid turnover during vertebrate evolution, since pairwise comparisons of origin maps revealed that <24% of them are conserved among vertebrates. This study unravels the existence of a novel determinant of origins, the precise functional role of which remains to be determined. Despite the importance of replication initiation for the fitness of organisms, the distribution of origins along vertebrate chromosomes is highly flexible.Association pour la Recherche sur le Cancer [Labellisation PGA120150202272 to M.-N.P., F.P.]; Agence Nationale de la Recherche [ANR-15-CE12-0004, OriMolMech to F.M., M.-N.P., F.P.]; Spanish Ministry of Economy and Competitiveness [BFU2016-78849-P, co-financed by the European UnionFEDERfunds to J.M.F.-J., M.G.

Association of replication origins with chromatin states and timing.

<p>Origins associated with a given chromatin state (in percent) correspond to origins that overlap with published chromatin state coordinates <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004282#pgen.1004282-Ernst1" target="_blank">[22]</a>, from the UCSC Genome Browser with chromHMM 1: active promoter, chromHMM 2: weak promoter, chromHMM 3: inactive/poised promoter, chromHMM 4: strong enhancer, chromHMM 5: strong enhancer, chromHMM 6: weak/poised enhancer, chromHMM 7: weak/poised enhancer, chromHMM 8: insulator, chromHMM 9: transcriptional transition, chromHMM 10: transcriptional elongation, chromHMM 11: weak transcribed, chromHMM 12: Polycomb-repressed, chromHMM 13: heterochromatin; low signal, chromHMM 14: repetitive/copy number variation, chromHMM 15: repetitive/copy number variation. The expected (Exp.) percentage and significance of association ( for significant enrichment, with and for significant depletion) were calculated with random genomic segments sampled from mappable regions (see <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004282#s4" target="_blank">Materials and Methods</a>).</p

Comparison of SNS-scan origins and SNS-SoleS origins.

<p>Overlap between SNS-Scan origins and SNS-SoleS origins <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004282#pgen.1004282-Besnard1" target="_blank">[10]</a>. % Overlap (SoleS in scan) corresponds to the number of scan origins that overlap with SoleS origins divided by the total number of scan origins. Expectations are assessed by randomly sampling genomic intervals on the mappable fraction of the human genome (see <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004282#s4" target="_blank">Materials and Methods</a>). SNS-SoleS were clustered so that origins less than 12 kb apart were clustered into one single (larger) origin.</p

Constitutive, common and cell specific replication origins (K562) and association with CGIs.

<p>A: Percentage of constitutive/common/K562-specific origins in each timing category (from early to late origins, as explained in the Methods Section). Constitutive origins are determined by the intersection of the origins from the five cell lines -H9, HeLa, IMR90, K562 and iPS- with Galaxy <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004282#pgen.1004282-Giardine1" target="_blank">[47]</a>. B: Number of constitutive/common/K562-specific origins in each timing category, with distinction between origins associated and not associated with CGIs. Origins classified as CGIs correspond to origins strictly overlapping a CGI. Positions of CGIs are taken from UCSC Genome Browser annotation. C: Boxplots of origin efficiency according to timing, constitutive/common/K562-specific nature and association with CGIs. Origin efficiency is defined as the number of reads within the origin interval divided by the length of the origin (i.e. the density of reads within a given origin). D: Proportion of CGIs overlapping with an origin in at least one cell line, according to the number of cell lines analyzed.</p

Global view of origins datasets and detections characteristics.

<p>Global view of origins datasets and detections characteristics.</p

Correlation between discriminant axis and distance to chromatin marks on K562 cells.

<p>Correlation coefficients between the distance of origins to chromatin marks and the discriminant axis (DA), as provided by the MixOmics Package <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004282#pgen.1004282-LeCao1" target="_blank">[46]</a>. Note that origins (detected on K562 cells) associated with chromatin marks correspond to distance 0 (strict overlap). Large distances therefore correspond to origins that are strictly not associated with a given mark. The sign of the correlation coefficient is important. If a discriminant axis is positively correlated with a distance, when the value along this axis increases the distance to the corresponding mark increases as well. Similarly, if it is negatively correlated, when the value along the axis decreases, the distance to the corresponding mark increases.</p