TRFs and tiRNAs sequence in acute rejection for vascularized composite allotransplantation

Abstract

Illumina tRFs & tiRNAs-seq analysis was used to characterize the whole transcriptomes of acute rejection caused by vascularized composite allotransplantation (VCA). tRFs & tiRNAs-seq information for muscle samples with VCA was obtained and compared with similar information for same age- and sex-matched healthy control subjects. The expression of 16 tRFs and tiRNAs, including 5 up-regulated target genes and 11 down-regulated target genes, were significantly different. According to bioinformatics analysis and reverse transcription quantitative polymerase chain reaction, we speculate that tiRNA-1-34-Glu-CTC-1 plays an important role in VCA-induced acute rejection by regulating the CACNA1D gene in the MAPK signaling pathway The findings provide the whole-transcriptome signatures of acute rejection for VCA, allowing further exploration of gene expression patterns/signatures associated with the various clinical symptoms of acute rejection for VCA.

Fig. 1

tRF & tiRNA-seq experiment workflow.

Fig. 2

Surgical procedures. (A) Prepare the donor site for amputation. (B) Prepare the receptor. (C) Perform vascular anastomoses. (D) Close muscles and skin.

Fig. 3

Hematoxylin and eosin staining of muscle samples. Allograft skin tissues at Ctrl (days 0) (A) day 7 (B) day 10 (C) and day 14 (D) Bar; 250 μm.

Fig. 4

tRF & tiRNA-seq quality score.

Fig. 5

The analysis of tRF & tiRNA. (A) Heatmap of correlation coefficient from all samples. The color in the panel represents the correlation coefficient of the two samples. Blue represents the two samples with a high correlation coefficient, and the white represents the low similarity of the two samples. (B) Venn diagram based on number of commonly expressed and specifically expressed tRF & tiRNA. (C) Venn diagram based on number of tRFdb tRFs and Fang et. tRFs. tRFdb tRFs represent the tRFs from the tRFdb database and Fang et. tRFs represent the tRFs from our detected tRFs. (D,E) The distribution of tRF & tiRNA subtypes. (F,G) The number of subtype tRF & tiRNA against tRNA isodecoders. (H,I) The Frequency of Subtype against Length of the tRF & tiRNA.

Fig. 6

(A) The hierarchical clustering heatmap for tRF & tiRNA. (B) The scatter plot between two groups for tRF & tiRNA. (C) The volcano plot of tRF & tiRNA. (Red: up-regulated; Green: down-regulated).

Fig. 7

Bioinformatic Prediction. GO (A) and Pathway (C) analysis for up-regulated tRF & tiRNA. GO (B) and Pathway (D) analysis for down-regulated tRF & tiRNA.

Fig. 8

RT-qPCR verification. Compared with the control gourp (day 0), (A–C) tiRNA-1:33-Gly-GCC-1, tiRNA-1-34-Glu-CTC-1 and tRF-1-32-Gly-GCC-2-M2 were up-regulated; (D,E) tRF-59-75-Gln-CTG-2-M2 and tRF-59:76-Val-AAC-1-M2 were down-regulated. (F) The relative expression level of CACNA1D gene. The data were normalized using the mean ± standard error of the mean (SEM). *P ≤ 0.05, **P ≤ 0.01, ***P ≤ 0.001.