isomiRs-specific differential expression is the rule, not the exception: Are we missing hundreds of species in microRNA analysis?

Abstract

MicroRNAs (miRNAs) are small RNA molecules that act as regulators of gene expression through targeted mRNA degradation. They are involved in many biological and pathophysiological processes and are widely studied as potential biomarkers and therapeutics agents for human diseases, including cardiovascular disorders. Recently discovered isoforms of miRNAs (isomiRs) exist in high quantities and are very diverse. Despite having few differences with their corresponding reference miRNAs, they display specific functions and expression profiles, across tissues and conditions. However, they are still overlooked and understudied, as we lack a comprehensive view on their condition-specific regulation and impact on differential expression analysis. Here, we show that isomiRs can have major effects on differential expression analysis results, as their expression is independent of their host miRNA genes or reference sequences. We present two miRNA-seq datasets from human umbilical vein endothelial cells, and assess isomiR expression in response to senescence and compartment-specificity (nuclear/cytosolic) under hypoxia. We compare three different methods for miRNA analysis, including isomiR-specific analysis, and show that ignoring isomiRs induces major biases in differential expression. Moreover, isomiR analysis permits higher resolution of complex signal dissection, such as the impact of hypoxia on compartment localization, and differential isomiR type enrichments between compartments. Finally, we show important distribution differences across conditions, independently of global miRNA expression signals. Our results raise concerns over the quasi exclusive use of miRNA reference sequences in miRNA-seq processing and experimental assays. We hope that our work will guide future isomiR expression studies, which will correct some biases introduced by golden standard analysis, improving the resolution of such assays and the biological significance of their downstream studies.

miRglmm: a generalized linear mixed model of isomiR-level counts improves estimation of miRNA-level differential expression and uncovers variable differential expression between isomiRs

“…With miRglmm, we address the need for a DE tool specifically suited for miRNA-seq data that can also utilize information from isomiRs in estimating miRNA-level DE estimates (10). Commonly used DE tools, such as DESeq2 (15), edgeR (16) and limma-voom (17), were built for analysis of mRNA-seq data, and some key features of miRNA-seq violate the independence between features assumption of these methods.…”

“…The collection of isomiRs that align to a given miRNA are often referred to as the miRgroup (Schmauch, Attia et al 2024). As an example of isomiR diversity within miRgroup, Supplemental Tables 1 and 2 display isomiR-level read counts produced by small RNA sequencing for two miRgroups: hsa-let-7a-5p and hsa-miR-26a-5p.…”

“…Maintaining and analyzing sequence level data at the scale needed for mRNA analysis would be computationally burdensome. Recent work has highlighted the importance of analyzing miRNA-seq data at the isomiR level (10). Through the analysis of 28 public miRNA-seq datasets and a newly generated human endothelial cell hypoxia data set, the authors show substantial differences between isomiR expression and their corresponding canonical miRNAs when applying DESeq2 to miRNA counts versus isomiR counts.…”