https://www.pierre-francois-roux.com/tags/functional-genomics/ Recent content in Functional genomics on Pierre-François Roux Hugo -- gohugo.io en-us © 2021 Pierre-François Roux Fri, 19 Jun 2026 09:50:00 +0000 https://www.pierre-francois-roux.com/2026/06/19/rank-transcription-factors-by-evidence-not-only-by-enrichment/ Fri, 19 Jun 2026 09:50:00 +0000 https://www.pierre-francois-roux.com/2026/06/19/rank-transcription-factors-by-evidence-not-only-by-enrichment/ Motif enrichment is a good starting point, but it is a weak ending point. A motif can be enriched because many related transcription factors share the same binding preference, because the region set is GC-rich, or because accessibility has changed without direct TF binding. When I try to prioritize candidate regulators, I prefer to build an evidence table. Each transcription factor gets several independent scores, and the interesting candidates are those supported by multiple layers. https://www.pierre-francois-roux.com/2026/06/19/atac-seq-is-more-than-a-peak-list/ Fri, 19 Jun 2026 09:30:00 +0000 https://www.pierre-francois-roux.com/2026/06/19/atac-seq-is-more-than-a-peak-list/ Many ATAC-seq analyses stop at peak calling: open regions in condition A, open regions in condition B, differential accessibility. That is useful, but it leaves a lot of information on the table. ATAC-seq libraries carry several layers of signal: chromatin accessibility, fragment architecture, nucleosome positioning, transcription factor footprints, and sometimes even useful genetic information. Look At Fragment Classes The fragment length distribution is one of the first things I inspect. https://www.pierre-francois-roux.com/2026/06/19/think-in-trajectories-not-only-in-contrasts/ Fri, 19 Jun 2026 09:00:00 +0000 https://www.pierre-francois-roux.com/2026/06/19/think-in-trajectories-not-only-in-contrasts/ Differential expression is often framed as a list of pairwise contrasts: treated versus control, late versus early, condition A versus condition B. That is useful, but it can flatten a time-course experiment into disconnected snapshots. When samples are ordered in time, a better first question is: which genes follow similar trajectories? A transient pulse, a delayed induction and a progressive repression can all have the same fold change in one contrast, but they usually mean different biology. https://www.pierre-francois-roux.com/project/atac-seq-as-an-integrative-assay-for-aging-and-cancer/ Fri, 19 Jun 2026 00:00:00 +0000 https://www.pierre-francois-roux.com/project/atac-seq-as-an-integrative-assay-for-aging-and-cancer/ ATAC-seq is widely used to map chromatin accessibility, but bulk ATAC-seq libraries contain much more information than accessible regulatory elements alone. In recent work, I benchmarked ATAC-seq against matched whole-genome sequencing to evaluate whether a single assay can also recover genetic information relevant to cancer and aging biology. Using paired datasets from patient-derived melanoma cell lines and TCGA brain tumors, we showed that ATAC-seq can support high-precision small variant detection within accessible regions, robust copy-number profiling, mitochondrial genome characterization and telomere-associated repeat quantification, while preserving its classical epigenomic readouts. https://www.pierre-francois-roux.com/project/p53-e4f1-metabolic-epigenetic-control-of-senescence/ Fri, 19 Jun 2026 00:00:00 +0000 https://www.pierre-francois-roux.com/project/p53-e4f1-metabolic-epigenetic-control-of-senescence/ My current research at the Montpellier Cancer Research Institute focuses on how metabolic rewiring is converted into durable chromatin and transcriptional states during senescence and aging. Cellular senescence relies on checkpoint pathways controlled by pRB and p53, but these regulators do more than arrest the cell cycle: they also control metabolic homeostasis, mitochondrial function, stress adaptation and chromatin regulation. A central entry point of this project is E4F1, a multifunctional component of the p53/pRB network. https://www.pierre-francois-roux.com/project/toward-a-systems-view-of-cellular-senescence/ Fri, 27 Apr 2018 00:00:00 +0000 https://www.pierre-francois-roux.com/project/toward-a-systems-view-of-cellular-senescence/ Cellular senescence is a stress response triggered by telomere dysfunction, oncogene activation, DNA damage, oxidative stress and other insults. It leads to a durable proliferative arrest, but also to profound changes in chromatin organization, transcription, metabolism and secretory activity. This dual nature makes senescence biologically fascinating: it contributes to tumor suppression, wound healing and development, yet persistent senescent cells can also promote chronic inflammation, tissue dysfunction, cancer progression and aging-related pathologies. https://www.pierre-francois-roux.com/project/combined-dna-and-rna-sequencing-for-rna-editing-event-discovery/ Wed, 27 Apr 2016 00:00:00 +0000 https://www.pierre-francois-roux.com/project/combined-dna-and-rna-sequencing-for-rna-editing-event-discovery/ RNA editing refers to post-transcriptional processes that modify mature RNA sequences relative to their genomic DNA template. In animals, the best-characterized events are A-to-I substitutions mediated by ADAR enzymes and C-to-U substitutions mediated by APOBEC enzymes. These modifications can diversify transcript sequences, alter coding potential, affect RNA stability and contribute to gene regulation. The rise of high-throughput sequencing made transcriptome-wide RNA editing screens possible, but it also exposed a difficult methodological problem. https://www.pierre-francois-roux.com/project/integrating-linkage-analysis-with-whole-genome-sequencing-to-dissect-complex-phenotypes/ Wed, 27 Apr 2016 00:00:00 +0000 https://www.pierre-francois-roux.com/project/integrating-linkage-analysis-with-whole-genome-sequencing-to-dissect-complex-phenotypes/ The ultimate goal of quantitative trait loci (QTL) mapping is not only to locate genomic regions associated with a phenotype, but to identify the genes and mechanisms that shape complex traits. This remains difficult because QTL intervals often span megabases and contain many positional candidates. Without additional information, causal inference tends to favor already-known functional candidates, which narrows discovery and can miss unexpected regulators. During my PhD, I worked on the genetic architecture of adiposity and energy metabolism in chicken models.