regSNPs: a strategy for prioritizing regulatory single nucleotide substitutions

Area of Science:

• Genetics
• Bioinformatics
• Molecular Biology

Background:

• Identifying functional DNA variants is essential for understanding disease and phenotypes.
• Genome-wide association studies (GWAS) and high-throughput sequencing generate numerous variants.
• Developing robust informatics methods is necessary to prioritize these variants.

Purpose of the Study:

• To present regSNPs, an informatics strategy for prioritizing regulatory single nucleotide polymorphisms (SNPs).
• To identify SNPs in promoter regions that may affect phenotypes by altering gene transcription.
• To integrate computational approaches for variant prioritization.

Main Methods:

• regSNPs integrates multiple established bioinformatics tools.
• It calculates differences in binding affinity due to candidate variants, considering motif degeneracy.
• It incorporates potential phenotypic effects of various transcription factors.

Main Results:

• regSNPs demonstrated variable performance across different diseases when tested with known disease-causing variants.
• The tool predicted three SNPs potentially affecting bone density in a previously identified linkage region.
• Experimental validation using luciferase reporter assay supported the functional impact of one predicted variant.

Conclusions:

• regSNPs offers a novel approach to prioritize regulatory SNPs by considering binding affinity and transcription factor effects.
• The strategy shows promise in identifying variants with potential phenotypic consequences.
• Further validation and application across diverse genetic studies are warranted.