FlyCADD scores can give insights into the impact of genetic variation at single nucleotide resolution. We describe FlyCADD and demonstrate its application to study naturally segregating SNPs, interpret GWAS-identified SNPs, rank SNPs prior to follow-up, and improve genome-editing experiments 🧬🧬

FlyCADD scores can give insights into the impact of genetic variation at single nucleotide resolution. We describe FlyCADD and demonstrate its application to study naturally segregating SNPs, interpret GWAS-identified SNPs, rank SNPs prior to follow-up, and improve genome-editing experiments 🧬🧬

With @geneticjulia.bsky.social @bernardkim.bsky.social @jellers.bsky.social Katja Hoedjes, Mirte Bosse

FlyCADD was developed by applying the CADD framework (Kircher et al. 2014) for the first time to an insect genome, using available genome annotations for D. melanogaster and a drosophilid whole genome alignment.

All FlyCADD impact prediction scores are available on Zenodo!

FlyCADD provides impact prediction scores for any SNP on the D. melanogaster genome! We show FlyCADDs abilities in:
- ranking candidate SNPs (from GWAS/E&R) for variant prioritization
- interpretation of naturally occuring SNPs
- refining of CRISPR-Cas9 experimental design