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A novel approach for a joint analysis of isomiR and mRNA expression data reveals features of isomiR targeting in breast cancer
A widely used procedure for selecting significant miRNA-mRNA or isomiR-mRNA pairs out of predicted interactions involves calculating the correlation between expression levels of miRNAs/isomiRs and mRNAs in a series of samples. In this manuscript, we aimed to assess the validity of this procedure by...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9751988/ https://www.ncbi.nlm.nih.gov/pubmed/36531236 http://dx.doi.org/10.3389/fgene.2022.1070528 |
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author | Nersisyan, Stepan Zhiyanov, Anton Engibaryan, Narek Maltseva, Diana Tonevitsky, Alexander |
author_facet | Nersisyan, Stepan Zhiyanov, Anton Engibaryan, Narek Maltseva, Diana Tonevitsky, Alexander |
author_sort | Nersisyan, Stepan |
collection | PubMed |
description | A widely used procedure for selecting significant miRNA-mRNA or isomiR-mRNA pairs out of predicted interactions involves calculating the correlation between expression levels of miRNAs/isomiRs and mRNAs in a series of samples. In this manuscript, we aimed to assess the validity of this procedure by comparing isomiR-mRNA correlation profiles in sets of sequence-based predicted target mRNAs and non-target mRNAs (negative controls). Target prediction was carried out using RNA22 and TargetScan algorithms. Spearman’s correlation analysis was conducted using miRNA and mRNA sequencing data of The Cancer Genome Atlas Breast Invasive Carcinoma (TCGA-BRCA) project. Luminal A, luminal B, basal-like breast cancer subtypes, and adjacent normal tissue samples were analyzed separately. Using the sets of putative targets and non-targets, we introduced adjusted isomiR targeting activity (ITA)—the number of negatively correlated potential isomiR targets adjusted by the background (estimated using non-target mRNAs). We found that for most isomiRs a significant negative correlation between isomiR-mRNA expression levels appeared more often in a set of predicted targets compared to the non-targets. This trend was detected for both classical seed region binding types (8mer, 7mer-m8, 7mer-A1, 6mer) predicted by TargetScan and the non-classical ones (G:U wobbles and up to one mismatch or unpaired nucleotide within seed sequence) predicted by RNA22. Adjusted ITA distributions were similar for target sites located in 3′-UTRs and coding mRNA sequences, while 5′-UTRs had much lower scores. Finally, we observed strong cancer subtype-specific patterns of isomiR activity, highlighting the differences between breast cancer molecular subtypes and normal tissues. Surprisingly, our target prediction- and correlation-based estimates of isomiR activities were practically non-correlated with the average isomiR expression levels neither in cancerous nor in normal samples. |
format | Online Article Text |
id | pubmed-9751988 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-97519882022-12-16 A novel approach for a joint analysis of isomiR and mRNA expression data reveals features of isomiR targeting in breast cancer Nersisyan, Stepan Zhiyanov, Anton Engibaryan, Narek Maltseva, Diana Tonevitsky, Alexander Front Genet Genetics A widely used procedure for selecting significant miRNA-mRNA or isomiR-mRNA pairs out of predicted interactions involves calculating the correlation between expression levels of miRNAs/isomiRs and mRNAs in a series of samples. In this manuscript, we aimed to assess the validity of this procedure by comparing isomiR-mRNA correlation profiles in sets of sequence-based predicted target mRNAs and non-target mRNAs (negative controls). Target prediction was carried out using RNA22 and TargetScan algorithms. Spearman’s correlation analysis was conducted using miRNA and mRNA sequencing data of The Cancer Genome Atlas Breast Invasive Carcinoma (TCGA-BRCA) project. Luminal A, luminal B, basal-like breast cancer subtypes, and adjacent normal tissue samples were analyzed separately. Using the sets of putative targets and non-targets, we introduced adjusted isomiR targeting activity (ITA)—the number of negatively correlated potential isomiR targets adjusted by the background (estimated using non-target mRNAs). We found that for most isomiRs a significant negative correlation between isomiR-mRNA expression levels appeared more often in a set of predicted targets compared to the non-targets. This trend was detected for both classical seed region binding types (8mer, 7mer-m8, 7mer-A1, 6mer) predicted by TargetScan and the non-classical ones (G:U wobbles and up to one mismatch or unpaired nucleotide within seed sequence) predicted by RNA22. Adjusted ITA distributions were similar for target sites located in 3′-UTRs and coding mRNA sequences, while 5′-UTRs had much lower scores. Finally, we observed strong cancer subtype-specific patterns of isomiR activity, highlighting the differences between breast cancer molecular subtypes and normal tissues. Surprisingly, our target prediction- and correlation-based estimates of isomiR activities were practically non-correlated with the average isomiR expression levels neither in cancerous nor in normal samples. Frontiers Media S.A. 2022-12-01 /pmc/articles/PMC9751988/ /pubmed/36531236 http://dx.doi.org/10.3389/fgene.2022.1070528 Text en Copyright © 2022 Nersisyan, Zhiyanov, Engibaryan, Maltseva and Tonevitsky. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Genetics Nersisyan, Stepan Zhiyanov, Anton Engibaryan, Narek Maltseva, Diana Tonevitsky, Alexander A novel approach for a joint analysis of isomiR and mRNA expression data reveals features of isomiR targeting in breast cancer |
title | A novel approach for a joint analysis of isomiR and mRNA expression data reveals features of isomiR targeting in breast cancer |
title_full | A novel approach for a joint analysis of isomiR and mRNA expression data reveals features of isomiR targeting in breast cancer |
title_fullStr | A novel approach for a joint analysis of isomiR and mRNA expression data reveals features of isomiR targeting in breast cancer |
title_full_unstemmed | A novel approach for a joint analysis of isomiR and mRNA expression data reveals features of isomiR targeting in breast cancer |
title_short | A novel approach for a joint analysis of isomiR and mRNA expression data reveals features of isomiR targeting in breast cancer |
title_sort | novel approach for a joint analysis of isomir and mrna expression data reveals features of isomir targeting in breast cancer |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9751988/ https://www.ncbi.nlm.nih.gov/pubmed/36531236 http://dx.doi.org/10.3389/fgene.2022.1070528 |
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