Biology subjects

Charlotte Proudhon

Publications and source records attributed to Charlotte Proudhon.

3 recordsLinked to original sources

bioRxiv2016

AN INTERNATIONAL INTER-LABORATORY DIGITAL PCR STUDY DEMONSTRATES HIGH REPRODUCIBILITY FOR THE MEASUREMENT OF A RARE SEQUENCE VARIANT

This study tested the claim that digital PCR (dPCR) can offer highly reproducible quantitative measurements in disparate labs. Twenty-one laboratories measured four blinded samples containing different quantities of a KRAS fragment encoding G12D, an important genetic marker for guiding therapy of certain cancers. This marker is challenging to quantify reproducibly using qPCR or NGS due to the presence of competing wild type sequences and the need for calibration. Using dPCR, eighteen laboratories were able to quantify the G12D marker within 12% of each other in all samples. Three laboratories appeared to measure consistently outlying results; however, proper application of a follow-up analysis recommendation rectified their data. Our findings show that dPCR has demonstrable reproducibility across a large number of laboratories without calibration and could enable the reproducible application of molecular stratification to guide therapy, and potentially for molecular diagnostics.\n\nSIGNIFICANCE STATEMENTThe poor reproducibility of molecular diagnostic methods limits their application in part due to the challenges associated with calibration of what are relative measurement approaches. In this study we investigate the performance of one of the only absolute measurement methods available today, digital PCR (dPCR), and demonstrated that when compared across twenty-one laboratories, dPCR has unprecedented reproducibility. These results were achieved when measuring a challenging single nucleotide variant and without calibration to any reference samples. This opens the possibility for dPCR to offer a method to transform reproducibility in the molecular diagnostic field, both by direct use as well as in support of other currently used clinical methods.

Molecular Biology↗

bioRxiv2015

4C-ker: A method to reproducibly identify genome-wide interactions captured by 4C-Seq experiments

4C-Seq has proven to be a powerful technique to identify genome-wide interactions with a single locus of interest (or \"bait\") that can be important for gene regulation. However, analysis of 4C-Seq data is complicated by the many biases inherent to the technique. An important consideration when dealing with 4C-Seq data is the differences in resolution of signal across the genome that result from differences in 3D distance separation from the bait. This leads to the highest signal in the region immediately surrounding the bait and increasingly lower signals in far-cis and trans. Another important aspect of 4C-Seq experiments is the resolution, which is greatly influenced by the choice of restriction enzyme and the frequency at which it can cut the genome. Thus, it is important that a 4C-Seq analysis method is flexible enough to analyze data generated using different enzymes and to identify interactions across the entire genome. Current methods for 4C-Seq analysis only identify interactions in regions near the bait or in regions located in far-cis and trans, but no method comprehensively analyzes 4C signals of different length scales. In addition, some methods also fail in experiments where chromatin fragments are generated using frequent cutter restriction enzymes. Here, we describe 4C-ker, a Hidden-Markov Model based pipeline that identifies regions throughout the genome that interact with the 4C bait locus. In addition we incorporate methods for the identification of differential interactions in multiple 4C-seq datasets collected from different genotypes or experimental conditions. Adaptive window sizes are used to correct for differences in signal coverage in near-bait regions, far-cis and trans chromosomes. Using several datasets, we demonstrate that 4C-ker outperforms all existing 4C-Seq pipelines in its ability to reproducibly identify interaction domains at all genomic ranges with different resolution enzymes.\n\nAUTHORS SUMMARYCircularized chromosome conformation capture, or 4C-Seq is a technique developed to identify regions of the genome that are in close spatial proximity to a single locus of interest ( bait). This technique is used to detect regulatory interactions between promoters and enhancers and to characterize the nuclear environment of different regions within and across different cell types. So far, existing methods for 4C-Seq data analysis do not comprehensively identify interactions across the entire genome due to biases in the technique that are related to the decrease in 4C signal that results from increased 3D distance from the bait. To compensate for these weaknesses in existing methods we developed 4C-ker, a method that explicitly models these biases to improve the analysis of 4C-Seq to better understand the genome wide interaction profile of an individual locus.

Bioinformatics↗

bioRxiv2015

The interdependent nature of multi-loci associations can be revealed by 4C-Seq

Use of low resolution single cell DNA FISH and population based high resolution chromosome conformation capture techniques have highlighted the importance of pairwise chromatin interactions in gene regulation. However, it is unlikely that these associations act in isolation of other interacting partners within the genome. Indeed, the influence of multi-loci interactions in gene control remains something of an enigma as beyond low-resolution DNA FISH we do not have the appropriate tools to analyze these. Here we present a method that uses standard 4C-seq data to identify multi-loci interactions from the same cell. We demonstrate the feasibility of our method using 4C-seq data sets that identify known pairwise interactions involving the Tcrb and Igk antigen receptor enhancers, in addition to novel tri-loci associations. We further show that enhancer deletions not only interfere with tri-loci interactions in which they participate, but they also disrupt pairwise interactions between other partner enhancers and this disruption is linked to a reduction in their transcriptional output. These findings underscore the functional importance of hubs and provide new insight into chromatin organization as a whole. Our method opens the door for studying multi-loci interactions and their impact on gene regulation in other biological settings.

Genomics↗