Computational analysis of core promoters in the Drosophila genome

By Uwe Ohler, Guo-chun Liao, Heinrich Niemann, Gerald M. Rubin. Genome Biology, 2002

481 citations recorded by the source corpus.

BackgroundThe core promoter, a region of about 100 base-pairs flanking the transcription start site (TSS), serves as the recognition site for the basal transcription apparatus. Drosophila TSSs have generally been mapped by individual experiments; the low number of accurately mapped TSSs has limited analysis of promoter sequence motifs and the training of computational prediction tools.ResultsWe identified TSS candidates for about 2,000 Drosophila genes by aligning 5' expressed sequence tags (ESTs) from cap-trapped cDNA libraries to the genome, while applying stringent criteria concerning coverage and 5'-end distribution. Examination of the sequences flanking these TSSs revealed the presence of well-known core promoter motifs such as the TATA box, the initiator and the downstream promoter element (DPE). We also define, and assess the distribution of, several new motifs prevalent in core promoters, including what appears to be a variant DPE motif. Among the prevalent motifs is the DNA-replication-related element DRE, recently shown to be part of the recognition site for the TBP-related factor TRF2. Our TSS set was then used to retrain the computational promoter predictor McPromoter, allowing us to improve the recognition performance to over 50% sensitivity and 40% specificity. We compare these computational results to promoter prediction in vertebrates.ConclusionsThere are relatively few recognizable binding sites for previously known general transcription factors in Drosophila core promoters. However, we identified several new motifs enriched in promoter regions. We were also able to significantly improve the performance of computational TSS prediction in Drosophila.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/a79c0a66a8f838770fc30fa419612938b70ae62a

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Citations in the corpus

Apollo: a sequence annotation editor (2002, background): “There are other useful predictive programs for tRNA genes [16] and promoters [17-20], but a large number of biological features still cannot be recognized by computational methods alone.”
High-resolution TADs reveal DNA sequences underlying genome organization in flies (2017, methodology): “The promoter boundary motifs we identified belong to the list of core-promoter motifs 1, 2, 6, 7 and 8 from (Ohler et al. 2002).”
Structure and mechanism of the RNA polymerase II transcription machinery (2004, background): “It was initially believed that most Pol II promoters contained a TATA element; however, subsequent sequence analysis has shown that only ∼30% of mRNA genes analyzed in Drosophila melanogaster contain a recognizable TAT”
Machine learning in genetics and genomics (2015, methodology): “For example, machine learning methods can be used to ‘learn’ how to recognize the locations of transcription start sites (TSSs) in a genome sequence 2 .”
Annotation of the Drosophila melanogaster euchromatic genome: a systematic review (2002, methodology): “Many of these sequence features are already in the FlyBase genetic data tables and gene annotation reports, based on data from literature curation, computational analyses (for example [77]), and large-scale projects such as the BDGP Gene Disruption Project.”
POIMs: positional oligomer importance matrices—understanding support vector machine-based signal detectors (2008, methodology): “For (i) there are the popular spectrum kernel without (Leslie et al., 2002) and with mismatches (Leslie et al., 2003); for (ii) we use the weighted degree kernel without (WD; Ratsch and Sonnenburg, 2004 ) and with shift (WDS; Ratsch et al., 2005).”
The General Transcription Machinery and General Cofactors (2006, background): “The finding of multiple core promoter elements (BREu, TATA, BREd, Inr, MTE, DPE and DCE) and core promoter-binding activity exhibited by TFIIB, TBP family members (TBP and TRF1-4) and distinct TAF complexes (TFIID, TFTC and SAGA/STAGA/SLIK) further exemplifies the diversity and specificity of core p”
Determination and Inference of Eukaryotic Transcription Factor Sequence Specificity (2014, unknown): “Motifs Display Positional Bias in Promoters across Eukaryotes Enrichment and positional bias of TF motifs in promoters has been reported in several model species and human (FitzGerald et al., 2004; Lee et al., 2007; Mariño-Ramı́rez et al., 2004; Ohler et al., 2002), and in some cases TFs appear to b”
Dynamic reprogramming of chromatin accessibility during Drosophila embryo development (2011, background): “In addition, six novel core promoter motifs have been defined on the basis of intra-genomic TSS comparisons and evolutionary conservation [44], of which one (MTE) was subsequently shown to facilitate INR-mediated transcription [45].”
EPD and EPDnew, high-quality promoter resources in the next-generation sequencing era (2012, methodology): “Because prominent promoter motifs differ between distant taxonomic groups, we use a different motif collection for Drosophila (Supplementary Figure S2) partly based on a study by Ohler et al. (29).”