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Darracq, A.

Publications and source records attributed to Darracq, A..

3 recordsLinked to original sources

Time-dependent chromatin maturation during 3D spheroid culture improves preclinical modeling of non-small cell lung cancer

Non-small cell lung cancer (NSCLC) is the deadliest cancer worldwide. Therapeutic progress stagnate, highlighting the complexity to replicate NSCLC in preclinical models. Drug discovery studies rely mostly on cancer cells in two-dimension (2D), which poorly predict drug efficacy in patients. There is a growing interest in three-dimensional (3D) preclinical models, such as 3D spheroids, to better model tumor phenotype and improve therapeutic prediction. However, a comprehensive view of 3D culture methods impact on transcriptomes, epigenomes and pharmacological responses and their correlations to NSCLC tumors is still missing. Here, we demonstrate that NSCLC spheroids undergo time-dependent transcriptomic and epigenomic changes, which peak after 3 weeks of culture. While DNA methylome remained stable, chromatin methylation and acetylation marks gained features of advanced NSCLC in a time-dependent manner. Single-cell transcriptomic profiling of spheroids demonstrated that time of 3D culture improved the correlation to NSCLC tumors. Moreover, long-term culture of 3D spheroids increased drug screening predictability, by showing resistance to drugs that failed in NSCLC patients (such as HDAC inhibitors) while demonstrating novel pharmacological vulnerabilities and synergistic interactions (such as combination of PRMT and HDAC inhibitors). Strikingly, reverting 3D spheroids back to 2D culture rapidly reversed transcriptomic, epigenetic and pharmacological signatures acquired after 3 weeks of 3D culture, highlighting the critical impact of cell culture conditions on NSCLC phenotype. Collectively, our findings demonstrate that implementing a time-dependent maturation process into 3D spheroid culture induces chromatin and transcriptomic changes that enhance NSCLC preclinical modeling.

cancer biology↗

A contiguous de novo genome assembly of sugar beet EL10 (Beta vulgaris L.)

A contiguous assembly of the inbred EL10 sugar beet (Beta vulgaris ssp. vulgaris) genome was constructed using PacBio long read sequencing, BioNano optical mapping, Hi-C scaffolding, and Illumina short read error correction. The EL10.1 assembly was 540 Mb, of which 96.7% was contained in nine chromosome-sized pseudomolecules with lengths from 52 to 65 Mb, and 31 contigs with a median size of 282 kb that remained unassembled. Gene annotation incorporating RNAseq data and curated sequences via the MAKER annotation pipeline generated 24,255 gene models. Results indicated that the EL10.1 genome assembly is a contiguous genome assembly highly congruent with the published sugar beet reference genome. Gross duplicate gene analyses of EL10.1 revealed little large-scale intra-genome duplication. Reduced gene copy number for well-annotated gene families relative to other core eudicots was observed, especially for transcription factors. Variation in genome size in B. vulgaris was investigated by flow cytometry among 50 individuals drawn from EL10 progeny and three unrelated germplasm accessions, producing estimates from 633 to 875 Mb/1C. Read depth mapping with short-read whole genome sequences from other sugar beet germplasm suggested that relatively few regions of the sugar beet genome appeared associated with high-copy number variation.

genomics↗

High throughput genotyping of structural variations in a complex plant genome using an original Affymetrix(R) Axiom(R) array

BackgroundInsertions/deletions (InDels) and more specifically presence/absence variations (PAVs) are pervasive in several species and have strong functional and phenotypic effect by removing or drastically modifying genes. Genotyping of such variants on large panels remains poorly addressed, while necessary for approaches such as association mapping or genomic selection.\n\nResultsWe have developed, as a proof of concept, a new high-throughput and affordable approach to genotype InDels. We first identified 141,000 InDels by aligning reads from the B73 line against the genome of three temperate maize inbred lines (F2, PH207, and C103) and reciprocally. Next, we designed an Affymetrix(R) Axiom(R) array to target these InDels, with a combination of probes selected at breakpoint sites (13%) or within the InDel sequence, either at polymorphic (25%) or non-polymorphic sites (63%) sites. The final array design is composed of 662,772 probes and targets 105,927 InDels, including PAVs ranging from 35bp to 129kbp. After Affymetrix(R) quality control, we successfully genotyped 86,648 polymorphic InDels (82% of all InDels interrogated by the array) on 445 maize DNA samples with 422,369 probes. Genotyping InDels using this approach produced a highly reliable dataset, with low genotyping error (~3%), high call rate (~98%), and high reproducibility (>95%). This reliability can be further increased by combining genotyping of several probes calling the same InDels (<0.1% error rate and >99.9% of call rate for 5 probes). This \"proof of concept\" tool was used to estimate the kinship matrix between 362 maize lines with 57,824 polymorphic InDels. This InDels kinship matrix was highly correlated with kinship estimated using SNPs from Illumina 50K SNP arrays.\n\nConclusionsWe efficiently genotyped thousands of small to large InDels on a sizeable number of individuals using a new Affymetrix(R) Axiom(R) array. This powerful approach opens the way to studying the contribution of InDels to trait variation and heterosis in maize. The approach is easily extendable to other species and should contribute to decipher the biological impact of InDels at a larger scale.

genomics↗