Genome-wide analysis of promoter architecture in Drosophila melanogaster

Abstract

Core promoters are critical regions for gene regulation in higher eukaryotes. However, the boundaries of promoter regions, the relative rates of initiation at the transcription start sites (TSSs) distributed within them, and the functional significance of promoter architecture remain poorly understood. We produced a high-resolution map of promoters active in the Drosophila melanogaster embryo by integrating data from three independent and complementary methods: 21 million cap analysis of gene expression (CAGE) tags, 1.2 million RNA ligase mediated rapid amplification of cDNA ends (RLM-RACE) reads, and 50,000 cap-trapped expressed sequence tags (ESTs). We defined 12,454 promoters of 8037 genes. Our analysis indicates that, due to non-promoter-associated RNA background signal, previous studies have likely overestimated the number of promoter-associated CAGE clusters by fivefold. We show that TSS distributions form a complex continuum of shapes, and that promoters active in the embryo and adult have highly similar shapes in 95% of cases. This suggests that these distributions are generally determined by static elements such as local DNA sequence and are not modulated by dynamic signals such as histone modifications. Transcription factor binding motifs are differentially enriched as a function of promoter shape, and peaked promoter shape is correlated with both temporal and spatial regulation of gene expression. Our results contribute to the emerging view that core promoters are functionally diverse and control patterning of gene expression in Drosophila and mammals.

Promoter architectures and developmental gene regulation

“…They share several characteristics with type II promoters, including a broad transcription initiation pattern and a well-defined NFR with positioned flanking nucleosomes, but also exhibit systematic differences that set them apart from the ubiquitously expressed class. The width of their transcription start region tends to be even broader than in Type II promoters [25]. Although their association with CpG islands in mammals is similar to type II promoters, developmental genes have longer or multiple CpG islands that often extend into the gene body [92].…”

“…High resolution TSS mapping by PET [22] and CAGE [25] in Drosophila revealed analogous transcription initiation patterns, separating promoters into "sharp" and "broad" class. Unlike mammalian genome, the fly genome does not contain CpG islands; however, the two promoter classes were shown to be associated with distinct core promoter elements.…”

“…Even though most of the strong promoter motifs and their respective locations were estimated from relatively modest amounts of pre-genome data, CAGE has provided evidence that the distance between TSS and the motifs such as TATA box or DPE is much more constrained than thought previously [24,25] -indeed, promoters with single well defined TSS are usually characterised by a fixed spacing from a motif that defines them. In addition, even weaker motifs such as nucleosome positioning sequence and general GC composition have been shown to line up precisely with most commonly used TSS position in promoters with broader initiation pattern [26,27], revealing hitherto unknown global features of this type of promoter.…”

“…Thus, CAGE provides information on two aspects of the capped transcriptome: 1) genome-wide single basepair resolution map of transcription start sites, and 2) relative levels of transcripts initiated at each CTSS. This information can be used for various analyses, from 5' end centred expression profiling [30,31] to studying promoter architecture [12,25].…”

Comparative validation of the D. melanogaster modENCODE transcriptome annotation

“…In order to map TSSs, modENCODE has performed extensive sequencing of D. melanogaster 59 transcript ends using CAGE-seq (Hoskins et al 2011). We performed CAGE-seq analysis on D. pseudoobscura, the most extensively annotated member of the genus outside of D. melanogaster and with the most RNA-seq reads in this study (>1.5 billion).…”