PRIESSTESS: interpretable, high-performing models of the sequence and structure preferences of RNA binding proteins
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB47428 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| ERR7416990.fastq.gz | Fastqsanger.gz | |||
| ERR7417000.fastq.gz | Fastqsanger.gz | |||
| ERR7417010.fastq.gz | Fastqsanger.gz | |||
| ERR7417020.fastq.gz | Fastqsanger.gz | |||
| ERR7417030.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 92 |
Similar Datasets
Project description:We performed the high-throughput RNA-SELEX (HTR-SELEX) to determine the RNA-binding specificity of the N proteins of various SARS-CoV-2 variants as well as other β-coronaviruses and showed that N proteins could bind two unrelated sequences, both of which were highly conserved across all variants and species.
2022-09-06 | GSE209797 | GEO
Project description:We report the DNA binding preferences of 4 NF-kappaB dimers (p52p52, RELARELA, RELAp50, RELAp52) Proteins of the Nf-kappab family were bound to DNA oligonucleotides containing a degenerate region. The protein-DNA complexes were selected after one or multiple rounds of SELEX and the DNA molecules were deep sequenced.
2011-05-24 | E-GEOD-29460 | biostudies-arrayexpress
Project description:Roquin proteins target specific RNA stem-loop motifs with their unique ROQ domain for mRNA degradation. The cellular levels of mRNAs are controlled by these post-transcriptional cis-regulatory stem-loop elements in the 3'-untranslated region (3'-UTR). Here, we first provide an RBNS (RNA Bind-n-Seq) experiment using pre-structured RNA libraries as input. This sRBNS (structured RBNS) was used to map Roquin's RNA binding preferences at nucleotide resolution, revealing preferences for loop sizes and consensus motifs for CDEs and ADEs.
2024-10-03 | GSE270841 | GEO
Project description:Floral organ identities in plants are specified by the combinatorial action of homeotic master regulatory transcription factors (TFs). How these factors achieve their regulatory specificities is however still largely unclear. Genome-wide in vivo DNA binding data show that homeotic MADS-domain proteins recognize partly distinct genomic regions, suggesting that DNA binding specificity contributes to functional differences of homeotic protein complexes. We used in vitro systematic evolution of ligands by exponential enrichment followed by high throughput DNA sequencing (SELEX-seq) on several floral MADS-domain protein homo- and heterodimers to measure their DNA-binding specificities. We show that specification of reproductive organs is associated with distinct binding preferences of a complex formed by SEPALLATA3 (SEP3) and AGAMOUS (AG). Binding specificity is further modulated by different binding site (BS) spacing preferences. Combination of SELEX-seq and genome-wide DNA binding data allows to differentiate between targets in specification of reproductive versus perianth organs in the flower. We validate the importance of DNA-binding specificity for organ-specific gene regulation by modulating promoter activity through targeted mutagenesis. Our study shows that intrafamily protein interactions affect DNA-binding specificity of floral MADS-domain proteins. DNA-binding specificity of individual dimers, as well as DNA-binding preferences of higher-order complexes differ between floral homeotic protein complexes. Differential DNA-binding of MADS-domain protein complexes plays a role in the specificity of target gene regulation.
2017-10-16 | GSE95730 | GEO
Project description:Quantifying the preferences of DNA binding proteins is an essential step in determining how transcription factors (TFs) interact with their targets in the genome. High-throughput in vitro binding assays have been used to identify the inherent DNA preferences of TFs in a controlled environment isolated from confounding factors such as genome accessibility, DNA methylation, and TF binding cooperativity. Unfortunately, the limited variable region or sequencing depth typically utilized by many of the available experimental approaches makes it difficult to measure the preferences of moderate- to low-affinity binding sites, and impossible to measure small-scale differences between closely related homologs. The Forkhead box (FOX) family of TFs is known to play a crucial role in regulating a variety of key processes from proliferation and development, to tumor suppression and aging. By using the high-sequencing depth SELEX-seq approach to study all four FOX homologs in Saccharomyces cerevisiae, we have been able to precisely quantify the contribution and importance of nucleotide positions flanking the core of the binding sites. Essential to this process was the alignment of our SELEX-seq reads to a set of candidate core sequences determined by two newly developed strategies of alignment and reprioritization applied to enriched k-mers.
2023-04-26 | GSE178811 | GEO
Project description:DNA binding preferences of fungal SREBP transcription regulators
| PRJNA485525 | ENA
Project description:Binding of transcription factors to DNA is mediated by the recognition of the chemical signatures of the DNA bases and the three-dimensional shape of the DNA molecule. The direct contribution of DNA shape to DNA-binding specificity has been difficult to assess, as DNA shape is a consequence of its sequence. Here, we teased apart these two modes of recognition in the context of Hox-DNA binding. We made a series of mutations in Hox residues that, in a co-crystal structure, only recognize DNA shape, and tested the effect on DNA binding preferences using SELEX-seq. Analysis of shape features of selected sequences revealed that these residues are both necessary and sufficient for selection of sequences with distinct shape features. We used statistical machine learning to show that the accuracy of binding specificity predictions improves by adding shape features to a model that only depends on sequence. We conclude that shape readout is a direct and critical component of binding site selection by Hox proteins. Three rounds of SELEX were performed on a series of Hox mutants as described in Slattery et al, Cell, 2011 (PMID 22153072) and Riley et al, Methods in molecular Biology, 2014 (PMID 25151169). Briefly, His-tagged Scr and Antp mutant proteins were incubated with a randomized 16mer oligonucleotide library, and bound DNA was amplified and sequenced as described (PMID 22153072, PMID 25151169).
2015-01-21 | E-GEOD-65073 | biostudies-arrayexpress
Project description:Evaluation of DNA-binding preferences of non-metazoan C2H2 zinc finger proteins by PBM
| PRJNA296081 | ENA
Project description:Most homeodomains are unique within a genome, yet many are highly conserved across vast evolutionary distances, implying strong selection on their precise DNA-binding specificities. We determined the binding preferences of the majority (168) of mouse homeodomains to all possible 8-base sequences, revealing rich and complex patterns of sequence specificity, and showing for the first time that there are at least 65 distinct homeodomain DNA-binding activities. We developed a computational system that successfully predicts binding sites for homeodomain proteins as distant from mouse as Drosophila and C. elegans, and we infer full 8-mer binding profiles for the majority of known animal homeodomains. Our results provide an unprecedented level of resolution in the analysis of this simple domain structure and suggest that variation in sequence recognition may be a factor in its functional diversity and evolutionary success. Keywords: Mouse homeodomain protein binding microarrays 178 Protein binding microarray (PBM) experiments of mouse homeodomains were performed, with 10 proteins done in replicate. Briefly, the PBMs involved binding GST-tagged mouse homeodomains to custom-designed, double-stranded 44K Agilent microarrays in order to determine their sequence preferences. The method is described in Berger et al., Nature Biotechnology 2006. A key feature is that the microarrays are composed of de Bruijn sequences that contain each 10-base sequence once and only once, providing an evenly balanced sequence distribution. Individual de Bruijn sequences have different properties, including representation of gapped patterns. The array sequences as well as the primary array data are available via a EULA at http://the_brain.bwh.harvard.edu/pbms/webworks2/. Here we provide the data transformed into median intensities (after normalization and detrending of the original array data) for all 32,896 8-base sequences, Z-scores for these intensities, and E-scores. E-scores are a modified version of AUC, and describe how well each 8-mer ranks the intensities of the spots. In general the E-scores are slightly more reproducible than Z-scores, but contain less information about relative binding affinity. Additional experimental details are found in Berger et al., Nature Biotechnology 2006, Berger et al., Cell 2008, and the accompanying Supplementary information.
2010-06-26 | E-GEOD-11239 | biostudies-arrayexpress
Project description:Single-stranded DNA (ssDNA) containing guanine repeats can form G-quadruplex (G4) structures. While cellular proteins and small molecules can bind G4s, it has been difficult to broadly assess their sequence specificity. Here, we use custom DNA microarrays to examine the binding specificities of proteins, small molecules, and antibodies across ~15,000 G4 structures. Molecules used include fluorescently labeled pyridostatin (Cy5-PDS, a small molecule), BG4 (Cy5-BG4, a G4-specific antibody), and eight proteins (GST-tagged nucleolin, IGF2, CNBP, FANCJ, PIF1, BLM, DHX36, and WRN). Cy5-PDS and Cy5-BG4 selectively bind sequences known to form G4s, confirming their formation on the microarrays. Cy5-PDS binding decreased when G4 formation was inhibited using lithium or when ssDNA features on the microarray were made double-stranded. Similar conditions inhibited the binding of all other molecules except for CNBP and PIF1. We report that proteins have different G4 binding preferences suggesting unique cellular functions. Finally, competition experiments are used to assess the binding of an unlabeled small molecule, revealing the structural features in the G4 required to achieve selectivity. These data demonstrate that the microarray platform can be used to assess the binding preferences of molecules to G4s on a broad scale, helping to understand the properties that govern molecular recognition.
2020-03-27 | GSE133367 | GEO