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Updated: Dec 11, 2025

Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease
Published on: April 4, 2018
Prediction of potential deleterious nonsynonymous single nucleotide polymorphisms of HIF1A gene: A computational
Zeinab Jamali1, Mortaza Taheri-Anganeh2, Mona Entezam3
1Cardiovascular Research Center, Shiraz University of Medical Sciences, Shiraz, Iran.
Abstract:
Hypoxia-inducible factor-1α (HIF-1α) is the oxygen sensitive subunit of HIF1 transcription factor. Its variations is associated with several diseases including different type of cancer, cardiovascular diseases, and liver and kidney failure. Despite all the investigations carried out on the single nucleotide polymorphisms (SNPs) of HIF1A gene and diseases, there are many uncharacterized nonsynonymous SNPs of this gene, which might have damaging effect on the protein function. Therefore, it is worthwhile to analyze these potential damaging nsSNPs, using different bioinformatics tools before launching large population studies. The objective of the present study was to predict the possible deleterious nsSNPs of HIF1A gene and their effects on the function and structure of HIF-1alpha protein, using different bioinformatics tools. Various prediction servers were used including SIFT, PROVEAN, PolyPhen-2, PANTHER, phD-SNP, SNP-GO, I-Mutant 2.0, Fathmm, SNPeffect 4.0, Mutation taster, CADD and RAMPAGE in a stepwise approach. After analyzing all 454 missense variants of the HIF1A gene using the abovementioned tools, we reported 11 variants with a significant impact on the function or structure of HIF-1α protein. Furthermore, among these variants only S274 P was predicted as stability enhancing variant with effect on protein function by increasing its stability. Although there are many advantages for computational analysis, the results has to be confirmed by experimental investigations.

