A preliminary computational outputs versus experimental results: Application of sTRAP, a biophysical tool for the analysis of SNPs of transcription factor‐binding sites

• Published in: Molecular genetics & genomic medicine 2020-05, Vol.8 (5), p.e1219-n/a
• Main Authors: Moradifard, Shirin, Saghiri, Reza, Ehsani, Parastoo, Mirkhani, Fatemeh, Ebrahimi‐Rad, Mina
• Format: Article
• Language: English
• Subjects: Affinity; Binding sites; Bioinformatics; Clinical Report; Clinical Reports; Collagen (type I); Collagen Type I - genetics; Collagen Type I - metabolism; Collagen Type I, alpha 1 Chain; Computer applications; Crosstalk; Deoxyribonucleic acid; DNA; Electrophoretic mobility; EMSA; Enhancers; Experimental data; Genes; Genomes; Humans; Literature reviews; Mannose-Binding Lectin - genetics; Mannose-Binding Lectin - metabolism; Mutants; Nitric Oxide Synthase Type II - genetics; Nitric Oxide Synthase Type II - metabolism; Nucleotide Motifs; Nucleotides; Optimization; Polymorphism, Single Nucleotide; Promoter Regions, Genetic; Protein Binding; Sequence Analysis, DNA - methods; Single-nucleotide polymorphism; SNP; Software - standards; sTRAP; Studies; transcription factor; Transcription factors; Transcription Factors - genetics; Transcription Factors - metabolism; transcription factor‐binding site
• ISSN: 2324-9269; 2324-9269
• DOI: 10.1002/mgg3.1219

Background In the human genome, the transcription factors (TFs) and transcription factor‐binding sites (TFBSs) network has a great regulatory function in the biological pathways. Such crosstalk might be affected by the single‐nucleotide polymorphisms (SNPs), which could create or disrupt a TFBS, leading to either a disease or a phenotypic defect. Many computational resources have been introduced to predict the TFs binding variations due to SNPs inside TFBSs, sTRAP being one of them. Methods A literature review was performed and the experimental data for 18 TFBSs located in 12 genes was provided. The sequences of TFBS motifs were extracted using two different strategies; in the size similar with synthetic target sites used in the experimental techniques, and with 60 bp upstream and downstream of the SNPs. The sTRAP (http://trap.molgen.mpg.de/cgi-bin/trap_two_seq_form.cgi) was applied to compute the binding affinity scores of their cognate TFs in the context of reference and mutant sequences of TFBSs. The alternative bioinformatics model used in this study was regulatory analysis of variation in enhancers (RAVEN; http://www.cisreg.ca/cgi-bin/RAVEN/a). The bioinformatics outputs of our study were compared with experimental data, electrophoretic mobility shift assay (EMSA). Results In 6 out of 18 TFBSs in the following genes COL1A1, Hb ḉᴪ, TF, FIX, MBL2, NOS2A, the outputs of sTRAP were inconsistent with the results of EMSA. Furthermore, no p value of the difference between the two scores of binding affinity under the wild and mutant conditions of TFBSs was presented. Nor, were any criteria for preference or selection of any of the measurements of different matrices used for the same analysis. Conclusion Our preliminary study indicated some paradoxical results between sTRAP and experimental data. However, to link the data of sTRAP to the biological functions, its optimization via experimental procedures with the integration of expanded data and applying several other bioinformatics tools might be required. We tested sTRAP to do some analysis on DNA variations in the cognate binding sites of specific transcription factors, for which there were the results of the experimental approaches, in the literature. At the same time, we compared the results of both of the procedures with the data of another bioinformatics model RAVEN, as an alternative one.