CRISPRCloud2: A cloud-based platform for deconvolving CRISPR screen data

Jeong, Hyun-Hwan; Kim, Seon‐Young; Rousseaux, Maxime W.C.; Zoghbi, Huda Y.; Liu, Zhandong

doi:10.1101/309302

Cited by 7 publications

(5 citation statements)

References 39 publications

(44 reference statements)

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“…Samples were then diluted to 2-4 nM, pooled, and denatured and diluted according to the instructions for single-end sequencing on a MiSeq (Illumina) with a MiSeq-v2 50 cycles or a MiSeq-v3-150 cycles kit (Illumina) and 10% PhiX (Illumina) spike-in. FastQ files were further analyzed with CRISPRCloud2 (Jeong et al, 2018).…”

Section: Author Contributionsmentioning

confidence: 99%

Identification of TMEM106B as proviral host factor for SARS-CoV-2

Baggen

Persoons

Jansen

et al. 2020

Preprint

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SUMMARYThe ongoing COVID-19 pandemic is responsible for worldwide economic damage and nearly one million deaths. Potent drugs for the treatment of severe SARS-CoV-2 infections are not yet available. To identify host factors that support coronavirus infection, we performed genome-wide functional genetic screens with SARS-CoV-2 and the common cold virus HCoV-229E in non-transgenic human cells. These screens identified PI3K type 3 as a potential drug target against multiple coronaviruses. We discovered that the lysosomal protein TMEM106B is an important host factor for SARS-CoV-2 infection. Furthermore, we show that TMEM106B is required for replication in multiple human cell lines derived from liver and lung and is expressed in relevant cell types in the human airways. Our results identify new coronavirus host factors that may potentially serve as drug targets against SARS-CoV-2 or to quickly combat future zoonotic coronavirus outbreaks.

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Section: Author Contributionsmentioning

confidence: 99%

Identification of TMEM106B as proviral host factor for SARS-CoV-2

Baggen

Persoons

Jansen

et al. 2020

Preprint

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“…Analysis was performed using the web-based CRISPRCloud2 38 . Dropout for both the in vivo and in vitro screens were calculated compared to an input day 0 timepoint.…”

Section: In Vivo Crispr Drop Out Screenmentioning

confidence: 99%

Temporal chromatin accessibility changes define transcriptional states essential for osteosarcoma metastasis

Pontius

Hong

Faber

et al. 2022

Preprint

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The metastasis-invasion cascade describes the series of steps required for a cancer cell to successfully spread from its primary tumor and ultimately grow within a secondary organ. Despite metastasis being a dynamic, multistep process, most omics studies to date have focused on comparing primary tumors to the metastatic deposits that define end-stage disease. This static approach means we lack information about the genomic and epigenomic changes that occur during the majority of tumor progression. One particularly understudied phase of tumor progression is metastatic colonization, during which cells must adapt to the new microenvironment of the secondary organ. Through temporal profiling of chromatin accessibility and gene expression in vivo, we identify dynamic changes in the epigenome that occur as osteosarcoma tumors form and grow within the lung microenvironment. Furthermore, we show through paired in vivo and in vitro CRISPR drop-out screens and pharmacological validation that the upstream transcription factors represent a class of metastasis-specific dependency genes. While current models depict lung colonization as a discrete step within the metastatic cascade, our study shows it is a defined trajectory through multiple epigenetic states, revealing new therapeutic opportunities undetectable with standard approaches.

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“…Several tools developed for such purposes such as like MAGeCK and BAGEL utilize a command line interface, which may limit their accessibility for less experienced users [93,94]. Newly developed programs that offer web-based and user-friendly interfaces for the deconvolution of pooled screening data, such as CRISPRAnalyzeR, CRISPRcloud2 and PinAPL-Py, are addressed for researchers with zero programming background [95][96][97]. Each of these platforms requires uploading FASTQ files with NGS data and a gRNA library file (predefined gRNA libraries are also provided on websites) to start the workflow.…”

Section: Outcomes Analysismentioning

confidence: 99%

Computational Tools and Resources Supporting CRISPR-Cas Experiments

Śledziński

Nowaczyk

Olejniczak

2020

Cells

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The CRISPR-Cas system has become a cutting-edge technology that revolutionized genome engineering. The use of Cas9 nuclease is currently the method of choice in most tasks requiring a specific DNA modification. The rapid development in the field of CRISPR-Cas is reflected by the constantly expanding ecosystem of computational tools aimed at facilitating experimental design and result analysis. The first group of CRISPR-Cas-related tools that we review is dedicated to aid in guide RNA design by prediction of their efficiency and specificity. The second, relatively new group of tools exploits the observed biases in repair outcomes to predict the results of CRISPR-Cas edits. The third class of tools is developed to assist in the evaluation of the editing outcomes by analysis of the sequencing data. These utilities are accompanied by relevant repositories and databases. Here we present a comprehensive and updated overview of the currently available CRISPR-Cas-related tools, from the perspective of a user who needs a convenient and reliable means to facilitate genome editing experiments at every step, from the guide RNA design to analysis of editing outcomes. Moreover, we discuss the current limitations and challenges that the field must overcome for further improvement in the CRISPR-Cas endeavor.

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CRISPRCloud2: A cloud-based platform for deconvolving CRISPR screen data

Cited by 7 publications

References 39 publications

Identification of TMEM106B as proviral host factor for SARS-CoV-2

Identification of TMEM106B as proviral host factor for SARS-CoV-2

Temporal chromatin accessibility changes define transcriptional states essential for osteosarcoma metastasis

Computational Tools and Resources Supporting CRISPR-Cas Experiments

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