Promootorite kasutust mõjutavate geneetiliste variantide leidmine CAGE tehnoloogia abil

Abstract

Gene expression is heavily influenced by promoters, which are special DNA regions near the starts of genes. Differential promoter usage has been associated with multiple complex diseases. Among other things, promoters dictate the transcripts that are created based on DNA. Although RNA sequencing (RNA-seq) is commonly used to measure transcription, its signal is relatively weak at the start of transcripts. Cap analysis of gene expression (CAGE) is a method that focuses on the beginnings of transcripts and can thus better measure promoter usage. The goal of this work was to investigate whether CAGE technology is superior to RNA-seq in detecting genetic variants that influence promoter usage. It was found that CAGE is likely somewhat better for this task. Additional RNA–seq transcript annotations were also created based on promoter annotations made using CAGE. These new annotations improved the ability of RNA-seq to detect genetic effects on promoter usage, but the annotations need to be still revised to reduce the number of false positives.