Evolutionary Bioinformatics (Aug 2023)

Transposable Elements-Derived MicroRNA Expression Patterns in TCGA Dataset for 10 Species

  • Chan-Mi Lee,
  • Sang Woo Jin,
  • Byunghyun Jang,
  • Young Kyung Ko,
  • Jeong-An Gim

DOI
https://doi.org/10.1177/11769343231194020
Journal volume & issue
Vol. 19

Abstract

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MicroRNAs (miRNAs) are a class of non-coding RNAs that act as regulators of disease. An evolutionary approach to the disease could reveal factors such as diagnosis, treatment, and prognosis prediction. The expression patterns of transposable element (TEs)-derived miRNAs could help elucidate diseases, and their evolutionary patterns are also valuable. The 34 miRNAs were compared in terms of stage survival and tumor status in 33 carcinomas from TCGA. Expression levels were compared using a t -test and presented as differentially expressed miRNAs (DEMs). For DEMs showing statistically specific expression patterns for 3 conditions (normal and cancer, early and advanced stage, and survival), interactions with related genes in 10 species, including humans, were compared. The enrichment term was discovered for the gene-miRNA interactions. In 18 out of the 33 carcinomas, at least one miRNA was retrieved with P .05. A total of 128 DEMs for the 9 miRNAs were identified. Based on the TargetScan database, interactions between miRNAs and genes in 10 species, including humans, were confirmed. The evolutionarily conserved miR-130a was observed in all 10 species, whereas miR-151a was only observed in humans. GO terms of related genes were selected for the miRNAs commonly found in each species. Evolutionary analysis of TE-derived disease-associated miRNAs was performed, and the evolutionarily conserved miR-130a-related carcinomas included renal and thyroid cancers. Human and rhesus monkey-specific miR-625 is associated with various carcinomas.