ArticleBiology direct2010
Relating underrepresented genomic DNA patterns and tiRNAs: the rule behind the observation and beyond.
Article in Biology direct, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Article
- Transcription start site associated RNAs (TSSaRNAs) are ubiquitous in all domains of life.PloS one · 2014Article
- Transcription start site associated RNAs in bacteria.Molecular systems biology · 2012Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundOne of the central problems of post-genomic biology is the understanding of regulatory network of genes. Traditionally the problem is approached from the protein-DNA interaction perspective. In recent years various types of noncoding RNAs appeared on the scene as new potent players of the game. The exact role of these molecules in gene expression control is mostly unknown at present, while their importance is generally recognized.
resultsThe Human and Mouse genomes have been screened with a statistical model for sequence patterns underrepresented in these genomes, and a subset of motifs, named spanions, has been identified. The common portion of the motif lists of the two species is 75% indicating evolutionary conservation of this feature. These motifs are arranged in clusters at close proximity of distinct genetic landmarks: 5' ends of genes, exon side of the exon/intron junctions and 5' ends of 3' UTRs. The length of the clusters is typically in the 20 to 25 bases range. The findings are in agreement with the known C/G bias of promoter regions while access much more sequential information than the simple composition based model.In the Human genome the recently reported transcription initiation RNAs (tiRNAs) are typically transcribed from these spanion clusters according to the presented results. The spanion clusters account for 70% of the published tiRNAs. Apparently, the model access the common statistical feature of this new and mostly uncharacterized non-coding RNA class and, in this way, supports the experimental observations with theoretical background.
conclusionsThe presented results seem to support the emerging model of the RNA-driven eukaryotic gene expression control. Beyond that, the model detects spanion clusters at genetic positions where no tiRNA counterpart was considered and reported. The GO-term analysis of genes with high concentration of spanion clusters in their promoter proximal region indicates involvement in gene regulatory processes. The results of the analysis suggest that the gene regulatory potential of the small non-coding RNAs is grossly underestimated at present. REVIEWERS: This article was reviewed by Frank Eisenhaber, Sandor Pongor and Rotem Sorek (nominated by Doron Lancet).
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.