Data from: Paired-end analysis of transcription start sites in Arabidopsis reveals plant-specific promoter signatures

Understanding plant gene promoter architecture has long been a challenge
due to the lack of relevant large-scale data sets and analysis methods.
Here, we present a publicly available, large-scale transcription start
site (TSS) data set in plants using a high-resolution method for analysis
of 5′ ends of mRNA transcripts. Our data set is produced using the
paired-end analysis of transcription start sites (PEAT) protocol,
providing millions of TSS locations from wild-type Columbia-0 Arabidopsis
thaliana whole root samples. Using this data set, we grouped TSS reads
into “TSS tag clusters” and categorized clusters into three spatial
initiation patterns: narrow peak, broad with peak, and weak peak. We then
designed a machine learning model that predicts the presence of TSS tag
clusters with outstanding sensitivity and specificity for all three
initiation patterns. We used this model to analyze the transcription
factor binding site content of promoters exhibiting these initiation
patterns. In contrast to the canonical notions of TATA-containing and more
broad “TATA-less” promoters, the model shows that, in plants, the vast
majority of transcription start sites are TATA free and are defined by a
large compendium of known DNA sequence binding elements. We present
results on the usage of these elements and provide our Plant PEAT Peaks
(3PEAT) model that predicts the presence of TSSs directly from sequence.