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SPOROS: A pipeline to analyze DISE/6mer seed toxicity
microRNAs (miRNAs) are (18-22nt long) noncoding short (s)RNAs that suppress gene expression by targeting the 3’ untranslated region of target mRNAs. This occurs through the seed sequence located in position 2-7/8 of the miRNA guide strand, once it is loaded into the RNA induced silencing complex (RI...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9004739/ https://www.ncbi.nlm.nih.gov/pubmed/35358200 http://dx.doi.org/10.1371/journal.pcbi.1010022 |
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author | Bartom, Elizabeth T. Kocherginsky, Masha Paudel, Bidur Vaidyanathan, Aparajitha Haluck-Kangas, Ashley Patel, Monal O’Shea, Kaitlyn L. Murmann, Andrea E. Peter, Marcus E. |
author_facet | Bartom, Elizabeth T. Kocherginsky, Masha Paudel, Bidur Vaidyanathan, Aparajitha Haluck-Kangas, Ashley Patel, Monal O’Shea, Kaitlyn L. Murmann, Andrea E. Peter, Marcus E. |
author_sort | Bartom, Elizabeth T. |
collection | PubMed |
description | microRNAs (miRNAs) are (18-22nt long) noncoding short (s)RNAs that suppress gene expression by targeting the 3’ untranslated region of target mRNAs. This occurs through the seed sequence located in position 2-7/8 of the miRNA guide strand, once it is loaded into the RNA induced silencing complex (RISC). G-rich 6mer seed sequences can kill cells by targeting C-rich 6mer seed matches located in genes that are critical for cell survival. This results in induction of Death Induced by Survival gene Elimination (DISE), through a mechanism we have called 6mer seed toxicity. miRNAs are often quantified in cells by aligning the reads from small (sm)RNA sequencing to the genome. However, the analysis of any smRNA Seq data set for predicted 6mer seed toxicity requires an alternative workflow, solely based on the exact position 2–7 of any short (s)RNA that can enter the RISC. Therefore, we developed SPOROS, a semi-automated pipeline that produces multiple useful outputs to predict and compare 6mer seed toxicity of cellular sRNAs, regardless of their nature, between different samples. We provide two examples to illustrate the capabilities of SPOROS: Example one involves the analysis of RISC-bound sRNAs in a cancer cell line (either wild-type or two mutant lines unable to produce most miRNAs). Example two is based on a publicly available smRNA Seq data set from postmortem brains (either from normal or Alzheimer’s patients). Our methods (found at https://github.com/ebartom/SPOROS and at Code Ocean: https://doi.org/10.24433/CO.1732496.v1) are designed to be used to analyze a variety of smRNA Seq data in various normal and disease settings. |
format | Online Article Text |
id | pubmed-9004739 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-90047392022-04-13 SPOROS: A pipeline to analyze DISE/6mer seed toxicity Bartom, Elizabeth T. Kocherginsky, Masha Paudel, Bidur Vaidyanathan, Aparajitha Haluck-Kangas, Ashley Patel, Monal O’Shea, Kaitlyn L. Murmann, Andrea E. Peter, Marcus E. PLoS Comput Biol Research Article microRNAs (miRNAs) are (18-22nt long) noncoding short (s)RNAs that suppress gene expression by targeting the 3’ untranslated region of target mRNAs. This occurs through the seed sequence located in position 2-7/8 of the miRNA guide strand, once it is loaded into the RNA induced silencing complex (RISC). G-rich 6mer seed sequences can kill cells by targeting C-rich 6mer seed matches located in genes that are critical for cell survival. This results in induction of Death Induced by Survival gene Elimination (DISE), through a mechanism we have called 6mer seed toxicity. miRNAs are often quantified in cells by aligning the reads from small (sm)RNA sequencing to the genome. However, the analysis of any smRNA Seq data set for predicted 6mer seed toxicity requires an alternative workflow, solely based on the exact position 2–7 of any short (s)RNA that can enter the RISC. Therefore, we developed SPOROS, a semi-automated pipeline that produces multiple useful outputs to predict and compare 6mer seed toxicity of cellular sRNAs, regardless of their nature, between different samples. We provide two examples to illustrate the capabilities of SPOROS: Example one involves the analysis of RISC-bound sRNAs in a cancer cell line (either wild-type or two mutant lines unable to produce most miRNAs). Example two is based on a publicly available smRNA Seq data set from postmortem brains (either from normal or Alzheimer’s patients). Our methods (found at https://github.com/ebartom/SPOROS and at Code Ocean: https://doi.org/10.24433/CO.1732496.v1) are designed to be used to analyze a variety of smRNA Seq data in various normal and disease settings. Public Library of Science 2022-03-31 /pmc/articles/PMC9004739/ /pubmed/35358200 http://dx.doi.org/10.1371/journal.pcbi.1010022 Text en © 2022 Bartom et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Bartom, Elizabeth T. Kocherginsky, Masha Paudel, Bidur Vaidyanathan, Aparajitha Haluck-Kangas, Ashley Patel, Monal O’Shea, Kaitlyn L. Murmann, Andrea E. Peter, Marcus E. SPOROS: A pipeline to analyze DISE/6mer seed toxicity |
title | SPOROS: A pipeline to analyze DISE/6mer seed toxicity |
title_full | SPOROS: A pipeline to analyze DISE/6mer seed toxicity |
title_fullStr | SPOROS: A pipeline to analyze DISE/6mer seed toxicity |
title_full_unstemmed | SPOROS: A pipeline to analyze DISE/6mer seed toxicity |
title_short | SPOROS: A pipeline to analyze DISE/6mer seed toxicity |
title_sort | sporos: a pipeline to analyze dise/6mer seed toxicity |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9004739/ https://www.ncbi.nlm.nih.gov/pubmed/35358200 http://dx.doi.org/10.1371/journal.pcbi.1010022 |
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