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CRISPRO: identification of functional protein coding sequences based on genome editing dense mutagenesis
CRISPR/Cas9 pooled screening permits parallel evaluation of comprehensive guide RNA libraries to systematically perturb protein coding sequences in situ and correlate with functional readouts. For the analysis and visualization of the resulting datasets, we develop CRISPRO, a computational pipeline...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6195731/ https://www.ncbi.nlm.nih.gov/pubmed/30340514 http://dx.doi.org/10.1186/s13059-018-1563-5 |
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author | Schoonenberg, Vivien A. C. Cole, Mitchel A. Yao, Qiuming Macias-Treviño, Claudio Sher, Falak Schupp, Patrick G. Canver, Matthew C. Maeda, Takahiro Pinello, Luca Bauer, Daniel E. |
author_facet | Schoonenberg, Vivien A. C. Cole, Mitchel A. Yao, Qiuming Macias-Treviño, Claudio Sher, Falak Schupp, Patrick G. Canver, Matthew C. Maeda, Takahiro Pinello, Luca Bauer, Daniel E. |
author_sort | Schoonenberg, Vivien A. C. |
collection | PubMed |
description | CRISPR/Cas9 pooled screening permits parallel evaluation of comprehensive guide RNA libraries to systematically perturb protein coding sequences in situ and correlate with functional readouts. For the analysis and visualization of the resulting datasets, we develop CRISPRO, a computational pipeline that maps functional scores associated with guide RNAs to genomes, transcripts, and protein coordinates and structures. No currently available tool has similar functionality. The ensuing genotype-phenotype linear and three-dimensional maps raise hypotheses about structure-function relationships at discrete protein regions. Machine learning based on CRISPRO features improves prediction of guide RNA efficacy. The CRISPRO tool is freely available at gitlab.com/bauerlab/crispro. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13059-018-1563-5) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6195731 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-61957312018-10-30 CRISPRO: identification of functional protein coding sequences based on genome editing dense mutagenesis Schoonenberg, Vivien A. C. Cole, Mitchel A. Yao, Qiuming Macias-Treviño, Claudio Sher, Falak Schupp, Patrick G. Canver, Matthew C. Maeda, Takahiro Pinello, Luca Bauer, Daniel E. Genome Biol Method CRISPR/Cas9 pooled screening permits parallel evaluation of comprehensive guide RNA libraries to systematically perturb protein coding sequences in situ and correlate with functional readouts. For the analysis and visualization of the resulting datasets, we develop CRISPRO, a computational pipeline that maps functional scores associated with guide RNAs to genomes, transcripts, and protein coordinates and structures. No currently available tool has similar functionality. The ensuing genotype-phenotype linear and three-dimensional maps raise hypotheses about structure-function relationships at discrete protein regions. Machine learning based on CRISPRO features improves prediction of guide RNA efficacy. The CRISPRO tool is freely available at gitlab.com/bauerlab/crispro. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13059-018-1563-5) contains supplementary material, which is available to authorized users. BioMed Central 2018-10-19 /pmc/articles/PMC6195731/ /pubmed/30340514 http://dx.doi.org/10.1186/s13059-018-1563-5 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Method Schoonenberg, Vivien A. C. Cole, Mitchel A. Yao, Qiuming Macias-Treviño, Claudio Sher, Falak Schupp, Patrick G. Canver, Matthew C. Maeda, Takahiro Pinello, Luca Bauer, Daniel E. CRISPRO: identification of functional protein coding sequences based on genome editing dense mutagenesis |
title | CRISPRO: identification of functional protein coding sequences based on genome editing dense mutagenesis |
title_full | CRISPRO: identification of functional protein coding sequences based on genome editing dense mutagenesis |
title_fullStr | CRISPRO: identification of functional protein coding sequences based on genome editing dense mutagenesis |
title_full_unstemmed | CRISPRO: identification of functional protein coding sequences based on genome editing dense mutagenesis |
title_short | CRISPRO: identification of functional protein coding sequences based on genome editing dense mutagenesis |
title_sort | crispro: identification of functional protein coding sequences based on genome editing dense mutagenesis |
topic | Method |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6195731/ https://www.ncbi.nlm.nih.gov/pubmed/30340514 http://dx.doi.org/10.1186/s13059-018-1563-5 |
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