Multiple novel promoter-architectures revealed by decoding the hidden heterogeneity within the genome

Abstract

An important question in biology is how different promoter-architectures contribute to the diversity in regulation of transcription initiation. A step forward has been the production of genome-wide maps of transcription start sites (TSSs) using high-throughput sequencing. However, the subsequent step of characterizing promoters and their functions is still largely done on the basis of previously established promoter-elements like the TATA-box in eukaryotes or the -10 box in bacteria. Unfortunately, a majority of promoters and their activities cannot be explained by these few elements. Traditional motif discovery methods that identify novel elements also fail here, because TSS neighborhoods are often highly heterogeneous containing no overrepresented motif. We present a new, organism-independent method that explicitly models this heterogeneity while unraveling different promoter-architectures. For example, in five bacteria, we detect the presence of a pyrimidine preceding the TSS under very specific circumstances. In tuberculosis, we show for the first time that the spacing between the bacterial 10-motif and TSS is utilized by the pathogen for dynamic gene-regulation. In eukaryotes, we identify several new elements that are important for development. Identified promoter-architectures show differential patterns of evolution, chromatin structure and TSS spread, suggesting distinct regulatory functions. This work highlights the importance of characterizing heterogeneity within high-throughput genomic data rather than analyzing average patterns of nucleotide composition.

Transcriptome analysis of Mastomys natalensis papillomavirus in productive lesions after natural infection

“…given that P78 is associated with a TATA-box, it would be favoured that transcription initiation occurs exactly at one position (Narlikar, 2014). In particular cases, e.g.…”

Genome‐wide mapping of transcription start sites yields novel insights into the primary transcriptome of Pseudomonas putida

“…For this search, TSSs of tRNA and rRNA genes were also included (1676 total input sequences). It has been noted previously that TSS neighborhoods can be highly heterogeneous with different promoter architectures affecting the position of transcription initiation depending on the growth phase and the environment (Narlikar, 2014). 2B).…”

The origins of developmental gene regulation

“…At least the TATA box and BRE (transcription factor IIB recognition element) sequence motifs, along with their interacting proteins, the TATA binding protein (TBP), and transcription factor IIB (TFIIB), respectively, are conserved in eukaryotes and archaea (Juven-Gershon and Kadonaga 2010), suggesting the deep origins of inducible-type promoters. The "inducible" and "constitutive" promoter categories possibly include broader diversity of promoter structures and roles, which are identified by knowledge-unbiased joint architecture and position learning (JAPL) methods that prime deciphering promoter diversity over bulk average trends and prevalent motifs (Narlikar 2014); this diversity should be given full consideration in future functional and evolutionary studies. For example, heat shock not only triggers the activation of inducible heat shock response genes, but also the downregulation of "constitutive" genes related to metabolism and other "housekeeping" functions, which are fully activated when the environment is favorable for cell growth and proliferation (Li et al 2015;Mahat et al 2016).…”

“…Despite the constitutive-inducible divide, one should keep in mind that transcription rates of so-called "constitutive" genes are oftentimes modulated over a broader range. Nevertheless, the two major promoter groups are validated by JAPL analysis and generally coincide with the inducible and constitutive categories (Narlikar 2014). The "inducible" and "constitutive" promoter categories possibly include broader diversity of promoter structures and roles, which are identified by knowledge-unbiased joint architecture and position learning (JAPL) methods that prime deciphering promoter diversity over bulk average trends and prevalent motifs (Narlikar 2014); this diversity should be given full consideration in future functional and evolutionary studies.…”