Bioinformatics pipeline to identify candidate regulatory variants in late‐onset Alzheimer’s disease (LOAD) associated regions

Background Small insertions and deletions (indels) in the human genome are substantial contributors to genetic variation impact traits diseases. The role of indels late onset Alzheimer’s disease has been understudied. Few examples, such as intronic poly-T variant TOMM40 gene, suggest that systematic exploration within LOAD risk regions will advance understanding architecture LOAD. Previously we developed a bioinformatics pipeline characterizes prioritizes candidate regulatory SNPs enhancers located LOAD-GWAS regions. Here extend analysis indels. proposed progresses from filtered set variants have predicted strong effect on transcription factor (TFs) binding. Method utilized publicly available functional genomics data sources. Primarily, cis-regulatory elements (cCREs) ENCODE single-cell RNA-seq patient samples (synapse: syn22079621). For TF binding employed motifs MotifDb. In addition, used various software including motifbreakR. Result We catalogued 1230 proximal CTCF-bound regions, 912 showed epigenetic evidence relevant brain tissue. 426 these cCREs. These disrupted 391 TFs, 362 had snRNA-seq samples. Of note, APOE-TOMM40, SPI1 MS4A2 were significantly by Amongst TFs RUNX3, SMAD3. Interestingly, significant findings with consistent our prior results for SNPs. Conclusion This study provides an analytical framework catalogue noncoding indel loci characterize their likelihood perturb approach integrates multiple types prioritize genes validation experiments using models gene editing technologies.