scholarly journals Inference of CRISPR Edits from Sanger Trace Data

2018 ◽  
Author(s):  
Tim Hsiau ◽  
David Conant ◽  
Nicholas Rossi ◽  
Travis Maures ◽  
Kelsey Waite ◽  
...  

AbstractEfficient precision genome editing requires a quick, quantitative, and inexpensive assay of editing outcomes. Here we present ICE (Inference of CRISPR Edits), which enables robust analysis of CRISPR edits using Sanger data. ICE proposes potential outcomes for editing with guide RNAs (gRNAs) and then determines which are supported by the data via regression. Additionally, we develop a score called ICE-D (Discordance) that can provide information on large or unexpected edits. We empirically confirm through over 1,800 edits that the ICE algorithm is robust, reproducible, and can analyze CRISPR experiments within days after transfection. We also confirm that ICE strongly correlates with next-generation sequencing of amplicons (Amp-Seq). The ICE tool is free to use and offers several improvements over current analysis tools. For instance, ICE can analyze individual experiments as well as multiple experiments simultaneously (batch analysis). ICE can also detect a wider variety of outcomes, including multi-guide edits (multiple gRNAs per target) and edits resulting from homology-directed repair (HDR), such as knock-ins and base edits. ICE is a reliable analysis tool that can significantly expedite CRISPR editing workflows. It is available online at ice.synthego.com, and the source code is at github.com/synthego-open/ice

2020 ◽  
Author(s):  
Hong You ◽  
Johannes U. Mayer ◽  
Rebecca L. Johnston ◽  
Haran Sivakumaran ◽  
Shiwanthi Ranasinghe ◽  
...  

AbstractCRISPR/Cas9-mediated genome editing shows cogent potential for the genetic modification of helminth parasites. Here we report successful gene knock-in (KI) into the genome of the egg of Schistosoma mansoni by combining CRISPR/Cas9 with single-stranded oligodeoxynucleotides (ssODNs). We edited the acetylcholinesterase (AChE) gene of S. mansoni targeting two guide RNAs (gRNAs), X5 and X7, located on exon 5 and exon 7 of Smp_154600, respectively. A CRISPR/Cas9-vector encoding gRNA X5 or X7 was introduced by electroporation into eggs recovered from livers of experimentally infected mice. Simultaneously, eggs were transfected with a ssODN donor encoding a stop codon in all six frames, flanked by 50 nt-long 5’- and 3’-homology arms matching the predicted Cas9-catalyzed double stranded break at X5 or X7. Next generation sequencing analysis of reads of amplicon libraries spanning targeted regions revealed that the major modifications induced by CRISPR/Cas9 in the eggs were generated by homology directed repair (HDR). Furthermore, soluble egg antigen from AChE-edited eggs exhibited markedly reduced AChE activity, indicative that programmed Cas9 cleavage mutated the AChE gene. Following injection of AChE-edited schistosome eggs into the tail veins of mice, a significant decrease in circumoval granuloma size was observed in the lungs of the mice. Notably, there was an enhanced Th2 response involving IL-4, −5, −10, and-13 induced by lung cells and splenocytes in mice injected with X5-KI eggs in comparison to control mice injected with unmutated eggs. A Th2-predominant response, with increased levels of IL-4, −13 and GATA3, also was induced by X5 KI eggs in small intestine-draining mesenteric lymph node cells when the gene-edited eggs were introduced into the subserosa of the ileum of the mice. These findings confirmed the potential and the utility of CRISPR/Cas9-mediated genome editing for functional genomics in schistosomes.Author SummarySchistosomiasis is the most devastating of the parasitic helminth diseases. Currently, no vaccines are available for human use and praziquantel is the only available treatment raising considerable concern that drug resistance will develop. A major challenge faced by the schistosomiasis research community is the lack of suitable tools to effectively characterise schistosome gene products as potential new drug and/or vaccine targets. We introduced CRISPR/Cas9 mediated editing into S. mansoni eggs targeting the gene encoding acetylcholinesterase (AChE), a recognized anthelminthic drug target. We found that the major modifications induced by CRISPR/Cas9 in the eggs were generated by homology directed repair (HDR). This platform provides a unique opportunity to generate precise loss-of-function insertions into the schistosome genome. We pre-screened the activity of two guide RNAs of the AChE gene and compared/validated the mutation efficacy using next-generation sequencing analysis at the genomic level and phenotypic modifications at the protein level. That resulted in reduced AChE activity observed in AChE-edited eggs, and decreased lung circumoval granuloma size in mice injected with those edited eggs. The CRISPR/Cas9-genome editing system we established in this study provides a pivotal platform for gene functional studies to identify and test new anti-schistosome intervention targets, which can be extended to the other human schistosome species and other important parasitic helminths.


2018 ◽  
Author(s):  
Berke Ç. Toptaş ◽  
Goran Rakocevic ◽  
Péter Kómár ◽  
Deniz Kural

AbstractMotivation: Several tools exist to count Mendelian violations in family trios by comparing variants at the same genomic positions. This naive variant comparison however, fails to assess regions where multiple variants need to be examined together, resulting in reduced accuracy of existing Mendelian violation checking tools.Results: We introduce VBT, a trio concordance analysis tool, that identifies Mendelian violations by approximately solving the 3-way variant matching problem to resolve variant representation differences in family trios. We show that VBT outperforms previous trio comparison methods by accuracy.Availability: VBT is implemented in C++ and source code is available under GNU GPLv3 license at the following URL: https://github.com/sbg/VBT-TrioAnalysis.gitContact:[email protected] information: Supplementary materials are available at Biorxiv.


Author(s):  
Artem Babaian ◽  
Robert C. Edgar

Abstract RNA viruses encoding a polymerase gene (riboviruses) dominate the known eukaryotic virome. Next-generation sequencing is revealing a wealth of new riboviruses with uncharacterised phenotypes, precluding classification by traditional taxonomic methods. These are often classified on the basis of polymerase sequence identity, but standardised methods to support this approach are currently lacking. To address this need, we describe the polymerase palmprint, a well-defined segment of the palm sub-domain delineated by well-conserved catalytic motifs. We present a novel algorithm, Palmscan, which identifies palmprints in nucleotide and amino acid sequences. We describe PALMdb, a reference database of palmprints derived from public sequence databases. Palmscan source code and PALMdb data are deposited at https://github.com/rcedgar/palmscan and https://github.com/rcedgar/palmdb, respectively.


2017 ◽  
Author(s):  
Christopher M. Gibb ◽  
Robert Jackson ◽  
Sabah Mohammed ◽  
Jinan Fiaidhi ◽  
Ingeborg Zehbe

AbstractSummaryThe Pathogen-Host Analysis Tool (PHAT) is an application for processing and analyzing next-generation sequencing (NGS) data as it relates to relationships between pathogen and host organisms. Unlike custom scripts and tedious pipeline programming, PHAT provides an integrative platform encompassing raw and aligned sequence and reference file input, quality control (QC) reporting, alignment and variant calling, linear and circular alignment viewing, and graphical and tabular output. This novel tool aims to be user-friendly for life scientists studying diverse pathogen-host relationships.Availability and ImplementationThe project is publicly available on GitHub (https://github.com/chgibb/PHAT) and includes convenient installers, as well as portable and source versions, for both Windows and Linux (Debian and RedHat). Up-to-date documentation for PHAT, including user guides and development notes, can be found at https://chgibb.github.io/PHATDocs/. We encourage users and developers to provide feedback (error reporting, suggestions, and comments) using GitHub Issues.ContactLead software developer: [email protected]


2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Danying Shao ◽  
Nabeel Ahmed ◽  
Nishant Soni ◽  
Edward P. O’Brien

Abstract Background Translation is a fundamental process in gene expression. Ribosome profiling is a method that enables the study of transcriptome-wide translation. A fundamental, technical challenge in analyzing Ribo-Seq data is identifying the A-site location on ribosome-protected mRNA fragments. Identification of the A-site is essential as it is at this location on the ribosome where a codon is translated into an amino acid. Incorrect assignment of a read to the A-site can lead to lower signal-to-noise ratio and loss of correlations necessary to understand the molecular factors influencing translation. Therefore, an easy-to-use and accurate analysis tool is needed to accurately identify the A-site locations. Results We present RiboA, a web application that identifies the most accurate A-site location on a ribosome-protected mRNA fragment and generates the A-site read density profiles. It uses an Integer Programming method that reflects the biological fact that the A-site of actively translating ribosomes is generally located between the second codon and stop codon of a transcript, and utilizes a wide range of mRNA fragment sizes in and around the coding sequence (CDS). The web application is containerized with Docker, and it can be easily ported across platforms. Conclusions The Integer Programming method that RiboA utilizes is the most accurate in identifying the A-site on Ribo-Seq mRNA fragments compared to other methods. RiboA makes it easier for the community to use this method via a user-friendly and portable web application. In addition, RiboA supports reproducible analyses by tracking all the input datasets and parameters, and it provides enhanced visualization to facilitate scientific exploration. RiboA is available as a web service at https://a-site.vmhost.psu.edu/. The code is publicly available at https://github.com/obrien-lab/aip_web_docker under the MIT license.


2020 ◽  
Vol 16 (12) ◽  
pp. e1008439
Author(s):  
Jennifer Lu ◽  
Steven L. Salzberg

GC skew is a phenomenon observed in many bacterial genomes, wherein the two replication strands of the same chromosome contain different proportions of guanine and cytosine nucleotides. Here we demonstrate that this phenomenon, which was first discovered in the mid-1990s, can be used today as an analysis tool for the 15,000+ complete bacterial genomes in NCBI’s Refseq library. In order to analyze all 15,000+ genomes, we introduce a new method, SkewIT (Skew Index Test), that calculates a single metric representing the degree of GC skew for a genome. Using this metric, we demonstrate how GC skew patterns are conserved within certain bacterial phyla, e.g. Firmicutes, but show different patterns in other phylogenetic groups such as Actinobacteria. We also discovered that outlier values of SkewIT highlight potential bacterial mis-assemblies. Using our newly defined metric, we identify multiple mis-assembled chromosomal sequences in previously published complete bacterial genomes. We provide a SkewIT web app https://jenniferlu717.shinyapps.io/SkewIT/ that calculates SkewI for any user-provided bacterial sequence. The web app also provides an interactive interface for the data generated in this paper, allowing users to further investigate the SkewI values and thresholds of the Refseq-97 complete bacterial genomes. Individual scripts for analysis of bacterial genomes are provided in the following repository: https://github.com/jenniferlu717/SkewIT.


2020 ◽  
Author(s):  
Xun Zhu ◽  
Ti-Cheng Chang ◽  
Richard Webby ◽  
Gang Wu

AbstractidCOV is a phylogenetic pipeline for quickly identifying the clades of SARS-CoV-2 virus isolates from raw sequencing data based on a selected clade-defining marker list. Using a public dataset, we show that idCOV can make equivalent calls as annotated by Nextstrain.org on all three common clade systems using user uploaded FastQ files directly. Web and equivalent command-line interfaces are available. It can be deployed on any Linux environment, including personal computer, HPC and the cloud. The source code is available at https://github.com/xz-stjude/idcov. A documentation for installation can be found at https://github.com/xz-stjude/idcov/blob/master/README.md.


2021 ◽  
Author(s):  
Jiyao Wang ◽  
Philippe Youkharibache ◽  
Aron Marchler-Bauer ◽  
Christopher Lanczycki ◽  
Dachuan Zhang ◽  
...  

AbstractiCn3D was originally released as a web-based 3D viewer, which allows users to create a custom view in a life-long, shortened URL to share with colleagues. Recently, iCn3D was converted to use JavaScript classes and could be used as a library to write Node.js scripts. Any interactive features in iCn3D can be converted to Node.js scripts to run in batch mode for a large data set. Currently the following Node.js script examples are available at https://github.com/ncbi/icn3d/tree/master/icn3dnode: ligand-protein interaction, protein-protein interaction, change of interactions due to residue mutations, DelPhi electrostatic potential, and solvent accessible surface area. iCn3D PNG images can also be exported in batch mode using a Python script. Other recent features of iCn3D include the alignment of multiple chains from different structures, realignment, dynamic symmetry calculation for any subsets, 2D cartoons at different levels, and interactive contact maps. iCn3D can also be used in Jupyter Notebook as described at https://pypi.org/project/icn3dpy.


2020 ◽  
Author(s):  
N Goonasekera ◽  
A Mahmoud ◽  
J Chilton ◽  
E Afgan

AbstractSummaryThe existence of more than 100 public Galaxy servers with service quotas is indicative of the need for an increased availability of compute resources for Galaxy to use. The GalaxyCloudRunner enables a Galaxy server to easily expand its available compute capacity by sending user jobs to cloud resources. User jobs are routed to the acquired resources based on a set of configurable rules and the resources can be dynamically acquired from any of 4 popular cloud providers (AWS, Azure, GCP, or OpenStack) in an automated fashion.Availability and implementationGalaxyCloudRunner is implemented in Python and leverages Docker containers. The source code is MIT licensed and available at https://github.com/cloudve/galaxycloudrunner. The documentation is available at http://gcr.cloudve.org/.ContactEnis Afgan ([email protected])Supplementary informationNone


2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Mikko Rautiainen ◽  
Tobias Marschall

Abstract Genome graphs can represent genetic variation and sequence uncertainty. Aligning sequences to genome graphs is key to many applications, including error correction, genome assembly, and genotyping of variants in a pangenome graph. Yet, so far, this step is often prohibitively slow. We present GraphAligner, a tool for aligning long reads to genome graphs. Compared to the state-of-the-art tools, GraphAligner is 13x faster and uses 3x less memory. When employing GraphAligner for error correction, we find it to be more than twice as accurate and over 12x faster than extant tools.Availability: Package manager: https://anaconda.org/bioconda/graphalignerand source code: https://github.com/maickrau/GraphAligner


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