Basic Information

Symbol
hsa-let-7e
RNA class
miRNA miRNA hairpin
Alias
MIRLET7E MicroRNA Let-7e Hsa-Let-7e-3p Hsa-Let-7e-5p Hsa-Let-7e MIRNLET7E Hsa-Let-7-P1b_pre MIMAT0004485 MIMAT0000066 MI0000066 Let-7e LET7E
Location (GRCh38)
Forensic tag(s)
Mechanical injury analysis Postmortem interval inference Cause of death analysis

Sequence & Structure

Transcript ID
hsa-let-7e
Sequence length
79 nt
GC content
0.5696

Secondary Structure

Generated by RNAfold
Minimum free energy (MFE) structure:
Secondary structure that contributes a minimum of free energy.
Ensemble properties:
Thermodynamic properties of the Boltzmann ensemble.
Minimum free energy
-36.70 kcal/mol
Thermodynamic ensemble
Free energy: -38.36 kcal/mol
Frequency: 0.0674
Diversity: 7.64
MFE Structure Visualization
Structure Prediction
MFE Structure Prediction
((.(((..(((.((((((((((((((((.((((.(....))).......)))))))))))))))))).)))..))).))
Thermodynamic Ensemble Prediction
{(.(((..(((.((((((((((((((({{(({{.{....,)).......)))))))))))))))))).)))..))).))
Forensic Context

A study in human trauma patients demonstrated that the let-7e was more abundant in circulating T cells during the injury stage compared to the recovery stage according to next-generation sequencing, though this upregulation was not significant in subsequent RT-qPCR validation [Rau et al. DOI:10.2147/JIR.S375881]. A separate meta-analysis in humans with mild traumatic brain injury identified the let-7e as downregulated in plasma, where it targets 1387 genes and is part of deregulated signaling pathways [Matyasova et al. DOI:10.4149/gpb_2021038]. A study in humans demonstrated that the expression of the let-7e in bone tissue negatively correlates with increasing post-mortem interval (PMI), showing significantly different levels in samples from less than one month compared to longer PMIs, suggesting its utility for PMI estimation [Joo-Young Na 10.1016/j.jflm.2020.102049]. Research in mice identified the let-7e as a member of the Let-7 family predicting high-dose and high-risk radiation exposure, where it was an important component in accurate decision tree models for biodosimetry classification [Martello et al. 10.1667/RADE-23-00007.1].