Systematic assays and resources for the functional annotation of non-coding variants

Area of Science:

• Genomics
• Bioinformatics
• Molecular Biology

Background:

• Genetic variation identification is routine in human genetics and diagnostics.
• Many variants, particularly in non-coding regions, lack sufficient evidence for pathogenicity.
• The high number of candidate variants hinders individual assay testing and limits translation of genomic study results.

Purpose of the Study:

• To discuss computational and experimental approaches for functional annotation of non-coding genetic variation.
• To address challenges in selecting methods and resources for variant interpretation.
• To facilitate the translation of findings from genome-wide association studies and genome sequencing.

Main Methods:

• Review of computational tools for variant annotation.
• Discussion of experimental validation techniques for non-coding variants.
• Exploration of frameworks for applying annotation to specific diseases or traits.

Main Results:

• Overview of diverse methods for functional annotation of non-coding variants.
• Identification of key challenges in variant interpretation and resource selection.
• Highlighting the need for scalable approaches to assess variant effects.

Conclusions:

• Functional annotation is crucial for interpreting non-coding genetic variation.
• A combination of computational and experimental approaches is often necessary.
• Standardized frameworks are needed to improve the clinical utility of genomic data.