Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Computational pipeline for designing guide RNAs for mismatch-CRISPRi.

ABSTRACT: CRISPR interference is an increasingly popular method for perturbing gene expression. Guided by single-guide RNAs (sgRNAs), nuclease-deficient Cas9 proteins bind to specific DNA sequences and hinder transcription. Specificity is achieved through complementarity of the sgRNAs to the DNA. Changing complementarity by introducing single-nucleotide mismatches can be exploited to tune knockdown. Here, we present a computational pipeline to identify sgRNAs targeting specific genes in a bacterial genome, filter them, and titrate their activity by introducing mismatches. For complete details on the use and execution of this protocol, please refer to Hawkins et al. (2020).

SUBMITTER: van Gestel J

PROVIDER: S-EPMC8121773 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

Computational pipeline for designing guide RNAs for mismatch-CRISPRi.

van Gestel Jordi J Hawkins John S JS Todor Horia H Gross Carol A CA

STAR protocols 20210505 2

CRISPR interference is an increasingly popular method for perturbing gene expression. Guided by single-guide RNAs (sgRNAs), nuclease-deficient Cas9 proteins bind to specific DNA sequences and hinder transcription. Specificity is achieved through complementarity of the sgRNAs to the DNA. Changing complementarity by introducing single-nucleotide mismatches can be exploited to tune knockdown. Here, we present a computational pipeline to identify sgRNAs targeting specific genes in a bacterial genome ...[more]

PMID: 34027480

Similar Datasets

beditor: A Computational Workflow for Designing Libraries of Guide RNAs for CRISPR-Mediated Base Editing.

Project description:CRISPR-mediated base editors have opened unique avenues for scar-free genome-wide mutagenesis. Here, we describe a comprehensive computational workflow called beditor that can be broadly adapted for designing guide RNA libraries with a range of CRISPR-mediated base editors, Protospacer Adjacent Motif (PAM) recognition sequences, and genomes of many species. Additionally, to assist users in selecting the best sets of guide RNAs for their experiments, a priori estimates of editing efficiency, called beditor scores, are calculated. These beditor scores are intended to select guide RNAs that conform to requirements for optimal base editing: the editable base falls within maximum activity window of the CRISPR-mediated base editor and produces nonconfounding mutational effects with minimal predicted off-target effects. We demonstrate the utility of the software by designing guide RNAs for base editing to model or correct thousands of clinically important human disease mutations.

| S-EPMC6553823 | biostudies-other

Computational design of CRISPR guide RNAs to enable strain-specific control of microbial consortia.

Project description:Microbes naturally coexist in complex, multistrain communities. However, extracting individual microbes from and specifically manipulating the composition of these consortia remain challenging. The sequence-specific nature of CRISPR guide RNAs can be leveraged to accurately differentiate microorganisms and facilitate the creation of tools that can achieve these tasks. We developed a computational program, ssCRISPR, which designs strain-specific CRISPR guide RNA sequences with user-specified target strains, protected strains, and guide RNA properties. We experimentally verify the accuracy of the strain specificity predictions in both Escherichia coli and Pseudomonas spp. and show that up to three nucleotide mismatches are often required to ensure perfect specificity. To demonstrate the functionality of ssCRISPR, we apply computationally designed CRISPR-Cas9 guide RNAs to two applications: the purification of specific microbes through one- and two-plasmid transformation workflows and the targeted removal of specific microbes using DNA-loaded liposomes. For strain purification, we utilize gRNAs designed to target and kill all microbes in a consortium except the specific microbe to be isolated. For strain elimination, we utilize gRNAs designed to target only the unwanted microbe while protecting all other strains in the community. ssCRISPR will be of use in diverse microbiota engineering applications.

| S-EPMC9910470 | biostudies-literature

A technical guide to TRITEX, a computational pipeline for chromosome-scale sequence assembly of plant genomes.

Project description:BackgroundAs complete and accurate genome sequences are becoming easier to obtain, more researchers wish to get one or more of them to support their research endeavors. Reliable and well-documented sequence assembly workflows find use in reference or pangenome projects.ResultsWe describe modifications to the TRITEX genome assembly workflow motivated by the rise of fast and easy long-read contig assembly of inbred plant genomes and the routine deployment of the toolchains in pangenome projects. New features include the use as surrogates of or complements to dense genetic maps and the introduction of user-editable tables to make the curation of contig placements easier and more intuitive.ConclusionEven maximally contiguous sequence assemblies of the telomere-to-telomere sort, and to a yet greater extent, the fragmented kind require validation, correction, and comparison to reference standards. As pangenomics is burgeoning, these tasks are bound to become more widespread and TRITEX is one tool to get them done. This technical guide is supported by a step-by-step computational tutorial accessible under https://tritexassembly.bitbucket.io/ . The TRITEX source code is hosted under this URL: https://bitbucket.org/tritexassembly .

| S-EPMC9719158 | biostudies-literature

A combined computational pipeline to detect circular RNAs in human cancer cells under hypoxic stress.

Project description:Hypoxia is associated with several diseases, including cancer. Cells that are deprived of adequate oxygen supply trigger transcriptional and post-transcriptional responses, which control cellular pathways such as angiogenesis, proliferation, and metabolic adaptation. Circular RNAs (circRNAs) are a novel class of mainly non-coding RNAs, which have been implicated in multiple cancers and attract increasing attention as potential biomarkers. Here, we characterize the circRNA signatures of three different cancer cell lines from cervical (HeLa), breast (MCF-7), and lung (A549) cancer under hypoxia. In order to reliably detect circRNAs, we integrate available tools with custom approaches for quantification and statistical analysis. Using this consolidated computational pipeline, we identify ~12000 circRNAs in the three cancer cell lines. Their molecular characteristics point to an involvement of complementary RNA sequences as well as trans-acting factors in circRNA biogenesis, such as the RNA-binding protein HNRNPC. Notably, we detect a number of circRNAs that are more abundant than their linear counterparts. In addition, 64 circRNAs significantly change in abundance upon hypoxia, in most cases in a cell type-specific manner. In summary, we present a comparative circRNA profiling in human cancer cell lines, which promises novel insights into the biogenesis and function of circRNAs under hypoxic stress.

| S-EPMC6884703 | biostudies-literature

A scalable pipeline for designing reconfigurable organisms.

Project description:Living systems are more robust, diverse, complex, and supportive of human life than any technology yet created. However, our ability to create novel lifeforms is currently limited to varying existing organisms or bioengineering organoids in vitro. Here we show a scalable pipeline for creating functional novel lifeforms: AI methods automatically design diverse candidate lifeforms in silico to perform some desired function, and transferable designs are then created using a cell-based construction toolkit to realize living systems with the predicted behaviors. Although some steps in this pipeline still require manual intervention, complete automation in future would pave the way to designing and deploying unique, bespoke living systems for a wide range of functions.

| S-EPMC6994979 | biostudies-literature

Computational approach for designing tumor homing peptides.

Project description:Tumor homing peptides are small peptides that home specifically to tumor and tumor associated microenvironment i.e. tumor vasculature, after systemic delivery. Keeping in mind the huge therapeutic importance of these peptides, we have made an attempt to analyze and predict tumor homing peptides. It was observed that certain types of residues are preferred in tumor homing peptides. Therefore, we developed support vector machine based models for predicting tumor homing peptides using amino acid composition and binary profiles of peptides. Amino acid composition, dipeptide composition and binary profile-based models achieved a maximum accuracy of 86.56%, 82.03%, and 84.19% respectively. These methods have been implemented in a user-friendly web server, TumorHPD. We anticipate that this method will be helpful to design novel tumor homing peptides. TumorHPD web server is freely accessible at http://crdd.osdd.net/raghava/tumorhpd/.

| S-EPMC3617442 | biostudies-other

Designing small multiple-target artificial RNAs.

Project description:MicroRNAs (miRNAs) are naturally occurring small RNAs that regulate the expression of several genes. MiRNAs' targeting rules are based on sequence complementarity between their mature products and targeted genes' mRNAs. Based on our present understanding of those rules, we developed an algorithm to design artificial miRNAs to target simultaneously a set of predetermined genes. To validate in silico our algorithm, we tested different sets of genes known to be targeted by a single miRNA. The algorithm finds the seed of the corresponding miRNA among the solutions, which also include the seeds of new artificial miRNA sequences potentially capable of targeting these genes as well. We also validated the functionality of some artificial miRNAs designed to target simultaneously members of the E2F family. These artificial miRNAs reproduced the effects of E2Fs inhibition in both normal human fibroblasts and prostate cancer cells where they inhibited cell proliferation and induced cellular senescence. We conclude that the current miRNA targeting rules based on the seed sequence work to design multiple-target artificial miRNAs. This approach may find applications in both research and therapeutics.

| S-EPMC2910070 | biostudies-literature

Exploring the hidden hot world of long non-coding RNAs in thermophilic fungus using a robust computational pipeline.

Project description:Long noncoding RNAs (lncRNAs) are versatile RNA molecules recently identified as key regulators of gene expression in response to environmental stress. Our primary focus in this study was to develop a robust computational pipeline for identifying structurally identical lncRNAs across replicates from publicly available bulk RNA-seq datasets. In order to demonstrate the effectiveness of the pipeline, we utilized the transcriptome of the thermophilic fungus Thermothelomyces thermophilus and assessed the expression pattern of lncRNAs in conjunction with Heat Shock Proteins (HSP), a well-known protein family critical for the cell's response to high temperatures. Our findings demonstrate that the identification of structurally identical transcripts among replicates in this thermophilic fungus ensures the reliability and accuracy of RNA studies, contributing to the validity of biological interpretations. Furthermore, the majority of lncRNAs exhibited a distinct expression pattern compared to HSPs. Our study contributes to advancing the understanding of the biological mechanisms comprising lncRNAs in thermophilic fungi.

| S-EPMC11347667 | biostudies-literature

CRISPRi screen of long non-coding RNAs identifies LINC03045 regulating glioblastoma invasion.

Project description:IntroductionGlioblastoma (GBM) invasion studies have focused on coding genes, while few studies evaluate long non-coding RNAs (lncRNAs), transcripts without protein-coding potential, for role in GBM invasion. We leveraged CRISPR-interference (CRISPRi) to evaluate invasive function of GBM-associated lncRNAs in an unbiased functional screen, characterizing and exploring the mechanism of identified candidates.MethodsWe implemented a CRISPRi lncRNA loss-of-function screen evaluating association of lncRNA knockdown (KD) with invasion capacity in Matrigel. Top screen candidates were validated using CRISPRi and oligonucleotide(ASO)-mediated knockdown in three tumor lines. Clinical relevance of candidates was assessed via The Cancer Genome Atlas(TCGA) and Genotype-Tissue Expression(GTEx) survival analysis. Mediators of lncRNA effect were identified via differential expression analysis following lncRNA KD and assessed for tumor invasion using knockdown and rescue experiments.ResultsForty-eight lncRNAs were significantly associated with 33-83% decrease in invasion (p<0.01) upon knockdown. The top candidate, LINC03045, identified from effect size and p-value, demonstrated 82.7% decrease in tumor cell invasion upon knockdown, while LINC03045 expression was significantly associated with patient survival and tumor grade(p<0.0001). RNAseq analysis of LINC03045 knockdown revealed that WASF3, previously implicated in tumor invasion studies, was highly correlated with lncRNA expression, while WASF3 KD was associated with significant decrease in invasion. Finally, WASF3 overexpression demonstrated rescue of invasive function lost with LINC03045 KD.ConclusionCRISPRi screening identified LINC03045, a previously unannotated lncRNA, as critical to GBM invasion. Gene expression is significantly associated with tumor grade and survival. RNA-seq and mechanistic studies suggest that this novel lncRNA may regulate invasion via WASF3.

| S-EPMC11192328 | biostudies-literature

Polyvalent guide RNAs for CRISPR antivirals.

Project description:CRISPR effector Cas13 recognizes and degrades RNA molecules that are complementary to its guide RNA (gRNA) and possesses potential as an antiviral biotechnology because it can degrade viral mRNA and RNA genomes. Because multiplexed targeting is a critical strategy to improve viral suppression, we developed a strategy to design of gRNAs where individual gRNAs have maximized activity at multiple viral targets, simultaneously, by exploiting the molecular biophysics of promiscuous target recognition by Cas13. These "polyvalent" gRNA sequences ("pgRNAs") provide superior antiviral elimination across tissue/organ scales in a higher organism (Nicotiana benthamiana) compared to conventionally-designed gRNAs-reducing detectable viral RNA by >30-fold, despite lacking perfect complementarity with either of their targets and, when multiplexed, reducing viral RNA by >99.5%. Pairs of pgRNA-targetable sequences are abundant in the genomes of RNA viruses, and this work highlights the need for specific approaches to the challenges of targeting viruses in eukaryotes using CRISPR.

| S-EPMC9618770 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data