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. 2023 Jun 1:16:2357-2374.
doi: 10.2147/JIR.S406484. eCollection 2023.

Systematic and Comprehensive Analysis of tRNA-Derived Small RNAs Reveals Their Potential Regulatory Roles and Clinical Relevance in Sarcoidosis

Affiliations

Systematic and Comprehensive Analysis of tRNA-Derived Small RNAs Reveals Their Potential Regulatory Roles and Clinical Relevance in Sarcoidosis

Min Zhao et al. J Inflamm Res. .

Abstract

Introduction: The pathogenesis of sarcoidosis, which involves several systems, is unclear, and its pathological type is non-caseating epithelioid granulomas. tRNA-derived small RNA (tsRNA) is a novel class of short non-coding RNAs with potential regulatory functions. However, whether tsRNA contributes to sarcoidosis pathogenesis remains unclear.

Methods: Deep sequencing technology was used to identify alterations in tsRNA relative abundance profiles between patients with sarcoidosis and healthy controls and quantitative real-time polymerase chain reaction (qRT-PCR) was used to validate. The clinical parameters were analysis to evaluate the clinical feature correlations initially. Target prediction and bioinformatics analysis of validated tsRNA were conducted to explore the mechanisms of tsRNAs in sarcoidosis pathogenesis.

Results: A total of 360 tsRNAs were identified for exact matches. Among them, the relative abundance of three tRNAs (tiRNA-Glu-TTC-001, tiRNA-Lys-CTT-003, and tRF-Ser-TGA-007) was markedly regulated in sarcoidosis. The levels of various tsRNAs were significantly correlated with age, the number of affected systems, and calcium levels in the blood. Additionally, target prediction and bioinformatics analyses revealed that these tsRNAs may play roles in chemokine, cAMP, cGMP-PKG, retrograde endorphin, and FoxO signalling pathways. The related genes, APP, PRKACB, ARRB2, and NR5A1 finding may participate in the occurrence and development of sarcoidosis through immune inflammation.

Conclusion: This study provides novel insights to explore tsRNA as a novel and efficacious pathogenic target of sarcoidosis.

Keywords: bioinformatics analysis; noncoding RNAs; sarcoidosis; tRNA-derived small RNA; tsRNA.

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Conflict of interest statement

The authors declare no conflicts of interest in this work.

Figures

Figure 1
Figure 1
Subtype tsRNAs distribution between sarcoidosis and control samples by small RNA-Seq. (A and B) Pie chart of the distribution of subtype tsRNAs number in sarcoidosis group and control group. (C and D) The numbers of tsRNAs derived from the variable anticodon tRNAs are demonstrated in sarcoidosis group and control group.
Figure 2
Figure 2
Differentially expressed tsRNAs between sarcoidosis and control samples. (A) Heat map and hierarchical clustering analysis of differentially expressed tsRNAs between sarcoidosis and control samples. (B) The volcano plots of differentially expressed tsRNAs. The green line shows the default 1.5-fold change. The red and green plots indicate the significantly upregulated and downregulated genes, respectively (fold change ≥ 1.5, P < 0.05).
Figure 3
Figure 3
(A-C) The qPCR results showed that tiRNA-Glu-TTC-001, tiRNA-Lys-CTT-003, and tRF-Ser-TGA-007 were consistent with tsRNA-Seq data. Thus, the 3 tsRNAs were confirmed as sarcoidosis related tsRNAs and used for further analysis. (D-F) ROC curves for tiRNA-Glu-TTC-001, tiRNA-Lys-CTT-003, and tRF-Ser-TGA-007. Data were presented as mean ± SD, **P < 0.01, ***P < 0.001.
Figure 4
Figure 4
Correlation between differentially expressed tsRNAs and the clinical parameters of sarcoidosis. (A) Correlation between tiRNA-Glu-TTC-001 and age. (B) Correlation between tiRNA-Lys-CTT-003 and age. (C) Correlation between tiRNA-Lys-CTT-003 and the number of affected systems. (D) Correlation between tRF-Ser-TGA-007 and blood calcium levels.
Figure 5
Figure 5
Targets genes of differentially expressed tsRNAs. (A) The targets of each tsRNA were shown respectively. (B) Venn plot to indicate that 96 mRNA targets of three tsRNAs were predicted by two prediction software simultaneously.
Figure 6
Figure 6
GO terms of the target mRNA of tsRNAs. (A-C) tiRNA-Glu-TTC-001. (D-F) tiRNA-Lys-CTT-003. (G-I) tRF-Ser-TGA-007. (A, D and G) biological process; (B, E and H) cellular component; (C, F and I) molecular function. GO, Gene ontology.
Figure 7
Figure 7
The diagnosis information of the hub genes. (A) The ROC curves were used to identify the diagnosis information of the hub genes associated with tiRNA-Glu-TTC-001 and, except SIRT1 and CBL, hub genes had a significantly diagnostic value (AUCs > 0.50). (B) The ROC curves were used to identify the diagnosis information of the hub genes associated with tiRNA-Lys-CTT-003 and, except KIAA0101, which was not expressed in the serum of patients with sarcoidosis, all hub genes had a significantly diagnostic value (AUCs > 0.50). (C) The ROC curves were used to identify the diagnosis information of the hub genes associated with tRF-Ser-TGA-007 and NR5A1, SPI1, TKTL2, FMN1, MNDA, and NCOR2 had a significantly diagnostic value (AUCs > 0.50). (D-G) The binding region of tsRNA and seed sequence were exhibited. (D-F) The base complementary pairing model between tiRNA-Glu-TTC-001 and APP, PRKACB, and ARRB2. (G) The base complementary pairing model between tRF-Ser-TGA-007 and NR5A1. Green: the binding region of tsRNA; Red: seed sequence of target gene; mfe: minimum free energy.

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