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. 2024 Sep 13;24(1):1147.
doi: 10.1186/s12885-024-12900-8.

Genetic polymorphism in untranslated regions of PRKCZ influences mRNA structure, stability and binding sites

Aneela Mustafa  1 , Maria Shabbir  2 , Yasmin Badshah  1 , Khushbukhat Khan  3 , Fizzah Abid  1 , Janeen H Trembley  4   5   6 , Tayyaba Afsar  7 , Ali Almajwal  7 , Suhail Razak  8
Affiliations

Genetic polymorphism in untranslated regions of PRKCZ influences mRNA structure, stability and binding sites

Aneela Mustafa et al. BMC Cancer. .

Abstract

Background: Variations in untranslated regions (UTR) alter regulatory pathways impacting phenotype, disease onset, and course of disease. Protein kinase C Zeta (PRKCZ), a serine-threonine kinase, is implicated in cardiovascular, neurological and oncological disorders. Due to limited research on PRKCZ, this study aimed to investigate the impact of UTR genetic variants' on binding sites for transcription factors and miRNA. RNA secondary structure, eQTLs, and variation tolerance analysis were also part of the study.

Methods: The data related to PRKCZ gene variants was downloaded from the Ensembl genome browser, COSMIC and gnomAD. The RegulomeDB database was used to assess the functional impact of 5' UTR and 3'UTR variants. The analysis of the transcription binding sites (TFBS) was done through the Alibaba tool, and the Kyoto Encyclopaedia of Genes and Genomes (KEGG) was employed to identify pathways associated with PRKCZ. To predict the effect of variants on microRNA binding sites, PolymiRTS was utilized for 3' UTR variants, and the SNPinfo tool was used for 5' UTR variants.

Results: The results obtained indicated that a total of 24 variants present in the 3' UTR and 25 variants present in the 5' UTR were most detrimental. TFBS analysis revealed that 5' UTR variants added YY1, repressor, and Oct1, whereas 3' UTR variants added AP-2alpha, AhR, Da, GR, and USF binding sites. The study predicted TFs that influenced PRKCZ expression. RNA secondary structure analysis showed that eight 5' UTR and six 3' UTR altered the RNA structure by either removal or addition of the stem-loop. The microRNA binding site analysis highlighted that seven 3' UTR and one 5' UTR variant altered the conserved site and also created new binding sites. eQTLs analysis showed that one variant was associated with PRKCZ expression in the lung and thyroid. The variation tolerance analysis revealed that PRKCZ was an intolerant gene.

Conclusion: This study laid the groundwork for future studies aimed at targeting PRKCZ as a therapeutic target.

Keywords: In-silico tools; Non-coding SNPs; Oncological disorders; PRKCZ; UTR; miRNA.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
PRKCZ corresponding UTR variants data retrieved from multiple sources, i.e., Ensembl genome browser, genomeAD, and Cosmic Panel (A) shows the number of 3’ and 5’ UTR variants obtained from databases, while (B) exhibits the UTR variants chosen for further analysis
Fig. 2
Fig. 2
Functional analysis of UTR variants by RegulomeDB. The data is segmented by score and rank for both 3’ UTR and 5’ UTR. (A) displays the score-wise category for 3’ UTR variants, while (B) shows the score-wise classification for 5’ UTR variants. A score of 1 or near 1 indicates a higher probability of affecting miRNA function. (C) demonstrates the rank-wise categorization for different classes for both 3’ UTRs and 5’ UTRs
Fig. 3
Fig. 3
UTR variants included for further analysis based on score and rank. A) selected 5’ UTRs along with their score probability, (B) selected 3’ UTRs along with their score probability, (C) the identified variant’s class ranking, and (D) the percentage distribution of both 5’ and 3’ UTR variants across the rank classes
Fig. 4
Fig. 4
Comparative analysis of TFBS by Alibaba web server for wild type and variant. (A) illustrates the comparative analysis of 5’ UTR for wildtype and variant, (B) showcases the mutant TFBS induced by 5’ UTR variants (rs1389053287, rs1282623960, rs192386882, and, rs57743955) C) displays the comparative study of the 3’ UTRs for wildtype and variant and (D) illustrates the mutant TFBs induced by 3’ UTR variants (rs1017752535, rs755735985, rs375170466, rs1006027187, and rs371058786)
Fig. 5
Fig. 5
PRKCZ signaling schematic representation constructed using the KEGG database. P13K, MAPK, NFKB WNT canonical and planner polarity pathway regulate PRKCZ transcription. Furthermore, PRKCZ interacts with ERK and CDC42/RAC1 to maintain positive feedback
Fig. 6
Fig. 6
PRKCZ RNA secondary prediction and positional entropy by RNAFold. (A) Shows RNA secondary structure for both wild type (W) and mutant (M) for 3’ UTR variants, while (B) Shows RNA secondary structure for both wild type (W) and mutant (M) for 5’ UTR variants. Positional entropy entropy is denoted with different colors; red depicts the highest, and blue represents the lowest positional entropy
Fig. 7
Fig. 7
Minimum Free Energy calculation by RNAFold due to UTR variants (A) variation in MFE in 5’ UTR mutations, (B) variation in MFE in 3’ UTR, and (c) shows a collective analysis of the decrease, increase, and no change in mRNA stability upon 5’ UTR and 3’ UTR variations
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