bioRxiv Science⌕ Search

Biology subjects

Alsheikh, T.

Publications and source records attributed to Alsheikh, T..

2 recordsLinked to original sources

Six novel nsSNPs affect RUNX1 gene may leading to Acute Myeloid Leukemia (AML) using Bioinformatics approach

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.

bioinformatics↗

Twenty novel nsSNPs may affect FLT3 gene leading to Acute Myeloid Leukemia (AML) using in silico analysis

Background: Mutations within the FMS-like tyrosine kinase 3 (FLT3) gene represent one of the most common genetic alteration that disturb intracellular signaling networks with a key role in leukemia pathogenesis. laboratory studies considerable obstacle to identify functional SNPs in a specific gene. Thus, the "in silico" technique is possible now to carry out research investigations without the need for extensive lab work. Methodology: data retrieved from NCBI database and different algorithm used to analyse nsSNPs which they are: SIFT, Polyphen-2, Provean, SNAP2, P-Mut, I-Mutant, Project Hope, Raptor X, PolymiRTS and Gene MANIA. Result: Our study reveals twenty novel SNPs regarded to be the most damaging SNPs that affect structure and function of FLT3 gene using different bioinformatics algorithm. Conclusion: This study revealed 20 damaging SNPs considered to be novel nsSNP in FLT3 gene that leads to AML, by using different algorithms. Additionally, 69 functional classes were predicted in 12 SNPs in the 3UTR, among them, 31 alleles disrupted a conserved miRNA site and 37 derived alleles created a new site of miRNA. This might result in the de regulation of the gene function. These results could be valuable for molecular studying, diagnosis and treatment of AML patients.

bioinformatics↗