Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1014465 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR25974000.fastq.gz | Fastqsanger.gz | |||
| SRR25974001.fastq.gz | Fastqsanger.gz | |||
| SRR25974002.fastq.gz | Fastqsanger.gz | |||
| SRR25974003.fastq.gz | Fastqsanger.gz | |||
| SRR25974004.fastq.gz | Fastqsanger.gz |
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Project description:Computational design of sequence-specific DNA-binding proteins
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Project description:Sequence-specific DNA-binding proteins (DBPs) play critical roles in biology and biotechnology, and there has been considerable interest in the engineering of DBPs with new or altered specificities for genome editing and other applications. While there has been some success in reprogramming naturally occurring DBPs using selection methods, the computational design of new DBPs that recognize arbitrary target sites remains an outstanding challenge. We describe a computational method for the design of small DBPs that recognize specific target sequences through interactions with bases in the major groove.
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Project description:Eukaryotic transcription factors (TFs) form complexes with various partner proteins to recognize their genomic target sites. Yet, how the DNA sequence determines which TF complex forms at any given site is poorly understood. Here, we demonstrate that high-throughput in vitro DNA binding assays coupled with unbiased computational analysis provide unprecedented insight into how different DNA sequences select distinct compositions and configurations of homeodomain TF complexes. Using inferred knowledge about minor groove width readout, we design targeted protein mutations that destabilize homeodomain binding both in vitro and in vivo in a complex-specific manner. By performing parallel systematic evolution of ligands by exponential enrichment sequencing (SELEX-seq), chromatin immunoprecipitation sequencing (ChIP-seq), RNA sequencing (RNA-seq), and Hi-C assays, we not only classify the majority of in vivo binding events in terms of complex composition but also infer complex-specific functions by perturbing the gene regulatory network controlled by a single complex.
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Project description:C2H2 zinc fingers (C2H2-ZFs) are the most prevalent type of vertebrate DNA-binding domain, and typically appear in tandem arrays (ZFAs), with sequential C2H2-ZFs each contacting 3 (or more) sequential bases. C2H2-ZFs can be assembled in a modular fashion, providing one explanation for their remarkable evolutionary success. Given a set of modules with defined 3-base specificities, modular assembly also presents a way to construct artificial proteins with specific DNA-binding preferences. However, a recent survey of a large number of three-finger ZFAs engineered by modular assembly reported high failure rates (~70%), casting doubt on the generality of modular assembly. Here, we used protein-binding microarrays to analyze 28 ZFAs that failed in the aforementioned study. Most (17) preferred specific sequences, which in all but one case resembled the intended target sequence. Like natural ZFAs, the engineered ZFAs typically yielded degenerate motifs, binding dozens to hundreds of related individual sequences. Thus, the failure of these proteins in previous assays is not due to lack of sequence-specific DNA-binding activity. Our findings underscore the relevance of individual C2H2-ZF sequence specificities within tandem arrays, and support the general ability of modular assembly to produce ZFAs with sequence-specific DNA-binding activity. Protein binding microarray (PBM) experiments were performed for a set of 20 artificial zinc finger arrays (ZFAs). Briefly, the PBMs involved binding GST-tagged DNA-binding proteins to two double-stranded 44K Agilent microarrays, each containing a different DeBruijn sequence design, in order to determine their sequence preferences. The method is described in Berger et al., Nature Biotechnology 2006.
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Project description:We propose an interacting barrier mechanism for cooperation between Isw2-related proteins and sequence-specific DNA binding factors.
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Project description:We propose an interacting barrier mechanism for cooperation between Isw2-related proteins and sequence-specific DNA binding factors.
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Project description:High-throughput (HT) in vitro methods for measuring protein-DNA binding have become invaluable for characterizing transcription factor (TF) complexes and modeling gene regulation. However, current methods do not utilize endogenous proteins and, therefore, do not quantify the impact of cell-specific post-translational modifications (PTMs) and cooperative cofactors. We introduce the HT nextPBM (nuclear extract protein-binding microarray) approach to study DNA binding of native cellular TFs that accounts for PTMs and cell-specific cofactors. We integrate immune-depletion and phosphatase-treatment steps into our nextPBM pipeline to characterize the impact of cofactors and phosphorylation on TF binding. We analyze binding of PU.1/SPI1 and IRF8 from human monocytes, delineate DNA-sequence determinants for their cooperativity, and show how PU.1 affinity correlates with enhancer status and the presence of cooperative and collaborative cofactors. We describe how nextPBMs, and our accompanying computational framework, can be used to discover cell-specific cofactors, screen for synthetic cooperative DNA elements, and characterize TF cooperativity at single-nucleotide resolution.
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Project description:DNase I footprinting is an established assay for identifying transcription factor (TF)-DNA interactions with single base pair resolution. High throughput DNase-seq assays have recently been used to detect in vivo DNase footprints across the genome. A number of computational approaches have been developed to accurately identify DNase-seq footprints and these methods have been used as a predictor of TF-DNA interactions by itself or in combination with other epigenetic features. However, recent studies have pointed to a substantial cleavage bias of DNase and its impact on footprinting, casting doubts on its predictive performance. To assess the potential for using DNaseI to identify individual binding sites, we performed DNase-seq experiments on deproteinized naked genomic DNA isolated from two different cell types and determined sequence cleavage bias associated with the DNase-seq protocol. This allowed us to build cleavage bias corrected footprint models specific to individual transcription factors. The predictive performance of these DNase-seq-based binding site models demonstrated that predicted footprints corresponded to high confidence TF-DNA interactions. To quantify the DNase I sequence-dependent cleavage bias, we performed DNase-seq experiments using deproteinized DNA from K562 and MCF7 cell lines.
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