Defining the fine structure of promoter activity on a genome-wide scale with CISSECTOR

Classic promoter mutagenesis strategies can be used to study how proximal promoter regions regulate the expression of particular genes of interest. This is a laborious process, in which the smallest sub-region of the promoter still capable of recapitulating expression in an ectopic setting is first identified, followed by targeted mutation of putative transcription factor binding sites. Massively parallel reporter assays such as Survey of Regulatory Elements (SuRE) provide an alternative way to study millions of promoter fragments in parallel. Here we show how a generalized linear model (GLM) can be used to transform genome-scale SuRE data into a high-resolution genomic track that quantifies the contribution of local sequence to promoter activity. This coefficient track helps identify regulatory elements and can be used to predict promoter activity of any sub-region in the genome. It thus allows in silico dissection of any promoter in the human genome to be performed. We developed a web application, available at cissector.nki.nl, that lets researchers easily perform this analysis as a starting point for their research into any promoter of interest. For generating the model, previously published SuRE-seq analysis was used (GSE128325). For validation of our GLM models, a second SuRE dataset was generated in K562 cells from a focused SuRE library consisting of fragments from 4 bacterial artificial chromosomes (BACs; CTD-3252A18, CTD-3156P24, CTD-2153L18, CTD-3075C4) containing 4 genomic regions covering several housekeeping genes (chr5:139,961,667-140,166,117; chr1:109,571,381-109,687,521; chr6:26,115,655-26,242,415; chr1:155,087,497-155,235,687, respectively). Mapping errors cause a small number of BAC fragments to map to positions outside the original BAC regions; these elements were excluded from our analysis.