Integrative in silico analysis identifies functionally and regulatively relevant nsSNPs in the TRIB3 gene

Area of Science:

• Genetics
• Bioinformatics
• Molecular Biology

Background:

• Only one Tribbles pseudokinase 3 (TRIB3) missense variant (Q84R) has been experimentally characterized to date.
• The functional significance of most reported TRIB3 nonsynonymous single-nucleotide polymorphisms (nsSNPs) remains largely unknown.
• Understanding TRIB3 nsSNPs is crucial for elucidating their role in disease.

Purpose of the Study:

• To prioritize TRIB3 nsSNPs with a high probability of disrupting protein structure, stability, and function.
• To identify potential TRIB3 variants associated with metabolic dysfunction.
• To provide candidates for future experimental validation.

Main Methods:

• A comprehensive in silico analysis of 366 TRIB3 nsSNPs was performed.
• Multiple bioinformatics tools (SIFT, PolyPhen-2, SNAP, PhD-SNP, PANTHER, SNPs&GO, Jalview, HOPE, I-Mutant, MUpro, MEDUSA, MutPred2) were employed for prediction and evaluation.
• Tissue-specific expression, interaction networks, and regulatory annotations were examined using GTEx, GeneMANIA, STRING, HaploReg, and CMDKP.

Main Results:

• Twelve high-confidence deleterious TRIB3 nsSNPs were consistently predicted across all evaluated tools.
• These variants include rs1242438181 (G69R), rs1016761523 (G69V), rs534352037 (Y71C), rs376597508 (M144K), rs1164746151 (F163S), rs2014979681 (C173R), rs149447454 (R181C), rs1445306127 (R181H), rs1411860615 (K184R), rs139447354 (R303W), rs201359012 (R303Q), and rs766581672 (W314R).
• The study identified potential links between these nsSNPs and protein structure/function disruption.

Conclusions:

• An integrative in silico approach successfully identified 12 high-risk TRIB3 missense variants.
• These variants are potential contributors to metabolic dysfunction.
• The findings provide a focused set of TRIB3 nsSNPs for future functional studies and experimental validation.