bioRxivBioinformaticsPreprint
Six novel nsSNPs affect RUNX1 gene may leading to Acute Myeloid Leukemia (AML) using Bioinformatics approach
Dalia OmeriD, Tebyan Ameer, Tarig Alsheikh, Ahmed NjmEldin, Zeinab Abdalmonem, Hadil Suliman, Abubaker Agbash, Howaida Hamad, Baha Aldeen Abdalaziz AlshareifiD, Mohammed Abd El Malik HassaniD
Abstract
BackgroundRUNX1 is one of the most frequently mutated genes in human AMLs, most of RUNX1 mutations in acute myeloid leukemia (AML) are missense or deletion-truncation and behave as loss-of-function mutations. The molecular consequences of cancer associated mutations in Acute myeloid leukemia (AML) linked factors are not very well understood. Here, we recognize possible pathogenic SNPs in the RUNX1 gene as Functional differences caused by SNPs might have harmful effects on protein structure and function using various computational tools. MethodologyData gained from NCBI database and various tools used to study nsSNPs which they are: SIFT, Polyphen-2, Provean, SNAP2, I-Mutant, Project Hope, Raptor X, PolymiRTS and Gene MANIA. ResultOur study reveals six novel SNPs observed to be the most damaging SNPs that affect structure and function of RUNX1 gene using various bioinformatics tools. ConclusionThis study revealed 7 damaging SNPs, 6 novel nsSNP out of them in the RUNX1 gene that leads to AML, by using different bioinformatics tools. Also, 23 functional classes were predicted in 8 SNPs in the 3UTR, among them, 6 alleles disrupted a conserved miRNA site and 16 derived alleles created a new site of miRNA. This might result in the de regulation of the gene function. Hopefully, these results will help in genetic studying and diagnosis of AML improvement.
- organism: human
- assay: DNA methylation
- research focus: variant effect prediction
- approach: statistical model
- Citations
- 0
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