bioRxivBioinformaticsPreprint
In silico analysis and cluster validation of potential breast cancer nsSNPs of serological tumor marker CA27.29
Abstract
Background & ObjectivesCA27.29 is a breast cancer-associated glycoprotein. Many genetic variations caused by non-synonymous nucleotide polymorphisms (nsSNPs) are known to affect the functionality of the CA27.29 protein. MethodsIn the present manuscript, an in silico analysis of the genetic variations in CA27.29 was done to observe functional nsSNPs that possibly alter its stability. Among 2205 SNPs identified from the publically available SNP database (dbSNP), 213 (9.66%) synonymous SNPs, 24 (1.09%) non-synonymous SNPs, and 1351 (61.27%) noncoding intronic SNPs were observed. The function predictability tools SIFT, Provean and Polyphen2 were used to uncover variations in the analyzed nsSNPs and their functionality. ResultsA total of 16, 20 and 10 non-synonymous SNPs (nsSNPs) were predicted to be damaging or deleterious by SIFT, Polyphen, and Provean tools respectively. Intriguingly, 9 nsSNPs were predicted to be damaging by all the three tools used while 4 nsSNPs were predicted to be damaging by SIFT and Polyphen tools. The substitutions C/G->T and G->A/T were observed to be dominant in the analyzed nsSNPs that probably have damaging role to CA27.29 glycoprotein. Moreover, the validation of results using ClinVar tool revealed that all the analyzed possibly, probably and highly damaging nsSNPs are yet to be reported and studied. Besides this, we found Global minor allele frequency (Global MAF) for only 11 nsSNPs, the values of which were observed to be <0.1% that further confirmed the novelty of the analyzed variants. Interpretation & ConclusionsAmong the analyzed nsSNPs, 3 nsSNPs rs145691584, rs148332231 and rs191544901 were found to be located in 3UTR region of CA27.29 gene that were assumed to have the possible functional roles in altering the protein stability. The present study is useful to gain useful insights into the genetic variations in nsSNPs that may playing a critical role in determining the susceptibility to breast cancer.
- organism: human
- assay: GWAS summary statistics
- research focus: differential expression
- approach: statistical model
- Citations
- 1
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Predicting functionally important breast cancer SNPs using pleiotropy, conservation, and protein structure
Meredith A. Carpenter, Alan C. Cheng·bioRxiv·Jan 1, 2024
- A Simulation Analysis and Screening of Deleterious Non-Synonymous Single Nucleotide Polymorphisms (SNPs) in Human CDKN1A Gene
G. M. Shazzad Hossain Prince, T.G. Murali Dhar·bioRxiv·Jan 3, 2018
- Saturation genome editing-based functional evaluation and clinical classification of BRCA2 single nucleotide variants
Huaizhi Huang, Chunling Hu, … Fergus J. Couch·bioRxiv·Dec 14, 2023
- Meta analysis of variant predictions in congenital adrenal hyperplasia caused by mutations in CYP21A2.
Mayara Jorgens Prado, Rodrigo Ligabue‐Braun, … Amit V. Pandey·bioRxiv·Dec 21, 2021
- Independent and Combined Associations of 677C/T and 1298A/C Polymorphisms in the MTHFR gene with Breast Cancers in a South-Asian Population
Sadia Ajaz, Sani-e-Zehra Zaidi, … Shagufta Khaliq·medRxiv·Mar 13, 2021
- AVENGERS: Analysis of Variant Effects using Next Generation sequencing to Enhance BRCA2 Stratification
Sounak Sahu, Melissa Galloux, … Shyam K. Sharan·bioRxiv·Dec 14, 2023