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Updated: Jul 7, 2025

Biotin-based Pulldown Assay to Validate mRNA Targets of Cellular miRNAs
Published on: June 12, 2018
Impact of MICA 3'UTR allelic variability on miRNA binding prediction, a bioinformatic approach
Karen Toledo-Stuardo1, Carolina H Ribeiro1, Ivo Campos1
1Faculty of Medicine, Immunology Program, Institute of Biomedical Sciences (ICBM), Universidad de Chile, Santiago, Chile.
Abstract:
MicroRNAs (miRNAs) are small non-coding RNAs that participate as powerful genetic regulators. MiRNAs can interfere with cellular processes by interacting with a broad spectrum of target genes under physiological and pathological states, including cancer development and progression. Major histocompatibility complex major histocompatibility complex class I-related chain A (MICA) belongs to a family of proteins that bind the natural-killer group 2, member D (NKG2D) receptor on Natural Killer cells and other cytotoxic lymphocytes. MICA plays a crucial role in the host's innate immune response to several disease settings, including cancer. MICA harbors various single nucleotide polymorphisms (SNPs) located in its 3'-untranslated region (3'UTR), a characteristic that increases the complexity of MICA regulation, favoring its post-transcriptional modulation by miRNAs under physiological and pathological conditions. Here, we conducted an in-depth analysis of MICA 3'UTR sequences according to each MICA allele described to date using NCBI database. We also systematically evaluated interactions between miRNAs and their putative targets on MICA 3'UTR containing SNPs using in silico analysis. Our in silico results showed that MICA SNPs rs9266829, rs 1880, and rs9266825, located in the target sequence of miRNAs hsa-miR-106a-5p, hsa-miR-17-5p, hsa-miR-20a-5p, hsa-miR-20b-5p, hsa-miR-93, hsa-miR-1207.5p, and hsa-miR-711 could modify the binding free energy between -8.62 and -18.14 kcal/mol, which may affect the regulation of MICA expression. We believe that our results may provide a starting point for further exploration of miRNA regulatory effects depending on MICA allelic variability; they may also be a guide to conduct miRNA in silico analysis for other highly polymorphic genes.
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