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Sampled ensemble neutrality as a feature to classify potential structured RNAs

Overview of attention for article published in BMC Genomics, January 2015
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Sampled ensemble neutrality as a feature to classify potential structured RNAs
Published in
BMC Genomics, January 2015
DOI 10.1186/s12864-014-1203-8
Pubmed ID

Shermin Pei, Jon S Anthony, Michelle M Meyer


BackgroundStructured RNAs have many biological functions ranging from catalysis of chemical reactions to gene regulation. Yet, many homologous structured RNAs display most of their conservation at the secondary or tertiary structure level. As a result, strategies for structured RNA discovery rely heavily on identification of sequences sharing a common stable secondary structure. However, correctly distinguishing structured RNAs from surrounding genomic sequence remains challenging, especially during de novo discovery. RNA also has a long history as a computational model for evolution due to the direct link between genotype (sequence) and phenotype (structure). From these studies it is clear that evolved RNA structures, like protein structures, can be considered robust to point mutations. In this context, an RNA sequence is considered robust if its neutrality (extent to which single mutant neighbors maintain the same secondary structure) is greater than that expected for an artificial sequence with the same minimum free energy structure.ResultsIn this work, we bring concepts from evolutionary biology to bear on the structured RNA de novo discovery process. We hypothesize that alignments corresponding to structured RNAs should consist of neutral sequences. We evaluate several measures of neutrality for their ability to distinguish between alignments of structured RNA sequences drawn from Rfam and various decoy alignments. We also introduce a new measure of RNA structural neutrality, the structure ensemble neutrality (SEN). SEN seeks to increase the biological relevance of existing neutrality measures in two ways. First, it uses information from an alignment of homologous sequences to identify a conserved biologically relevant structure for comparison. Second, it only counts base-pairs of the original structure that are absent in the comparison structure and does not penalize the formation of additional base-pairs.ConclusionWe find that several measures of neutrality are effective at separating structured RNAs from decoy sequences, including both shuffled alignments and flanking genomic sequence. Furthermore, as an independent feature classifier to identify structured RNAs, SEN yields comparable performance to current approaches that consider a variety of features including stability and sequence identity. Finally, SEN outperforms other measures of neutrality at detecting mutational robustness in bacterial regulatory RNA structures.

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Geographical breakdown

Country Count As %
Canada 1 6%
Unknown 16 94%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 29%
Student > Ph. D. Student 4 24%
Student > Bachelor 3 18%
Professor > Associate Professor 2 12%
Professor 1 6%
Other 2 12%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 7 41%
Agricultural and Biological Sciences 5 29%
Computer Science 2 12%
Engineering 2 12%
Chemistry 1 6%
Other 0 0%

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This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 05 February 2015.
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