Diagnosis of Alzheimer's disease specific phospholipase c gamma-1 SNV by deep-learning based approach for high throughput screening
Alzheimer's disease (AD) is a multifactorial disease which is caused by inherited autosomal recessive as familial and late-onset as non-familial changes. However, the genetics of AD underlining variation or mutation are not well understood. Exon skipping through the occurrence of the unpredicted genetic events leads to variation of translation, but the event does not can be exploited for AD diagnosis. We identified a gene as phospholipase c gamma-1 (PLC?1) with severe genetic modification in AD through deep-learning based high throughput screening which showed single nucleotide variants (SNVs). Genome-wide association study (GWAS) data from AD mouse model demonstrated that AD specific novel SNVs are preferentially occurred H3K27ac accumulated region at PLC?1 gene body during the brain development. Moreover, exon skipping in mature mRNA was caused by single nucleotide insertion at 27th exon of PLC?1 gene. In addition, we show mutation site was evolutionally conserved in various species included human which means important region for homeostasis. Collectively, our findings suggest the genetic variation and possibility of diagnosis potent of PLC?1 for AD. Overall design: Examination of PLCg1 and PLC beta submailies gene expression and SNVs profiling from 5xFAD mouse cortex