Biology subjects

Palenikova, P.

Publications and source records attributed to Palenikova, P..

3 recordsLinked to original sources

bioRxiv2025

Genome-wide rules of transcription factor cooperativity revealed through in silico binding site ablation

Transcription factor (TF) cooperativity plays a critical role in gene regulation. However, the underlying genomic rules remain unclear, calling for scalable methods to characterize the TF binding site (motif) syntax of regulatory elements. Here, we introduce DeepCompARE, a lightweight model paired with an in silico ablation (ISA) framework for genome-wide analysis of regulatory sequences. Our framework enables precise interpretation of the motif syntax governing chromatin accessibility, enhancer activity, and promoter function. We find that most TF motifs are pairwise independent, indicating a default additive behavior of TFs, and define a cooperativity score to quantify deviations from this baseline. This reveals synergy and redundancy as opposite effects along the same cooperative spectrum. TF redundancy is linked to promoter activity and broad expression, whereas TF synergy is associated with enhancer activity, physical interactions, and cell-type specificity. Our framework provides a quantitative model for TF cooperativity, offering new insights into gene regulatory logic.

bioinformatics↗

bioRxiv2020

CEDAR, an online resource for the reporting and exploration of complexome profiling data

Complexome profiling is an emerging omics approach that systematically interrogates the composition of protein complexes (the complexome) of a sample, by combining biochemical separation of native protein complexes with mass-spectrometry based quantitation proteomics. The resulting fractionation profiles hold comprehensive information on the abundance and composition of the complexome, and have a high potential for reuse by experimental and computational researchers. However, the lack of a central resource that provides access to these data, reported with adequate descriptions and an analysis tool, has limited their reuse. Therefore, we established the ComplexomE profiling DAta Resource (CEDAR, www3.cmbi.umcn.nl/cedar/), an openly accessible database for depositing and exploring mass spectrometry data from complexome profiling studies. Compatibility and reusability of the data is ensured by a standardized data and reporting format containing the "minimum information required for a complexome profiling experiment" (MIACE). The data can be accessed through a user-friendly web interface, as well as programmatically using the REST API portal. Additionally, all complexome profiles available on CEDAR can be inspected directly on the website with the profile viewer tool that allows the detection of correlated profiles and inference of potential complexes. In conclusion, CEDAR is a unique, growing and invaluable resource for the study of protein complex composition and dynamics across biological systems.

bioinformatics↗

bioRxiv2018

Mutations generated by repair of Cas9-induced double strand breaks are predictable from surrounding sequence

The exact DNA mutation produced by cellular repair of a CRISPR/Cas9-generated double strand break determines its phenotypic effect. It is known that the mutational outcomes are not random, and depend on DNA sequence at the targeted location. Here, we present a systematic study of this link. We created a high throughput assay to directly measure the edits generated by over 40,000 guide RNAs, and applied it in a range of genetic backgrounds and for alternative CRISPR/Cas9 reagents. In total, we gathered data for over 1,000,000,000 mutational outcomes in synthetic constructs, which mirror those at endogenous loci. The majority of reproducible mutations are insertions of a single base, short deletions, or long microhomology-mediated deletions. gRNAs have a cell-line dependent preference for particular outcomes, especially favouring single base insertions and microhomology-mediated deletions. We uncover sequence determinants of the produced mutations at individual loci, and use these to derive a predictor of Cas9 editing outcomes with accuracy close to the theoretical maximum. This improved understanding of sequence repair allows better design of editing experiments, and may lead to future therapeutic applications.

cell biology↗