Predicting the functional impact of single nucleotide variants in Drosophila melanogaster with FlyCADD
Understanding how genetic variants drive phenotypic differences is a major challenge in molecular biology. Single nucleotide polymorphisms form the vast majority of genetic variation and play critical roles in complex, polygenic phenotypes, yet their functional impact is poorly understood from traditional gene-level analyses. In-depth knowledge about the impact of single nucleotide polymorphisms has broad applications in health and disease, population genomic and evolution studies. The wealth of genomic data and available functional genetic tools make Drosophila melanogaster an ideal model species for studies at single nucleotide resolution. However, to leverage these resources for genotype-phenotype research and potentially combine it with the power of functional genetics, it is essential to develop techniques to predict functional impact and causality of single nucleotide variants. Here, we present FlyCADD, a functional impact prediction tool for single nucleotide variants in D. melanogaster. FlyCADD, based on the Combined Annotation-Dependent Depletion (CADD) framework, integrates over 650 genomic features - including conservation scores, GC content, and DNA secondary structure - into a single metric reflecting a variants predicted impact on evolutionary fitness. FlyCADD provides impact prediction scores for any single nucleotide variant on the D. melanogaster genome. We demonstrate the power of FlyCADD for typical applications, such as the ranking of phenotype-associated variants to prioritize variants for follow-up studies, evaluation of naturally occurring polymorphisms, and refining of CRISPR-Cas9 experimental design. FlyCADD provides a powerful framework for interpreting the functional impact of any single nucleotide variant in D. melanogaster, thereby improving our understanding of genotype-phenotype connections. Article summarySingle nucleotide polymorphisms (SNPs), the most common form of genomic variation, drive micro-evolution and adaptation. In Drosophila melanogaster, many SNPs are associated with phenotypes, yet functional validation is rare and experimentally challenging. FlyCADD is a new impact prediction tool that integrates D. melanogaster genome annotations into a single score predicting SNP impact. FlyCADD can be applied to distinguish causal from neutral variants, prioritize variants prior to functional studies, and to interpret natural variation, thereby improving understanding of genotype-phenotype relationships.