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Tensor Decomposition Reveals Concurrent Evolutionary Convergences and Divergences and Correlations with Structural Motifs in Ribosomal RNA

Overview of attention for article published in PLOS ONE, April 2011
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Title
Tensor Decomposition Reveals Concurrent Evolutionary Convergences and Divergences and Correlations with Structural Motifs in Ribosomal RNA
Published in
PLOS ONE, April 2011
DOI 10.1371/journal.pone.0018768
Pubmed ID
Authors

Chaitanya Muralidhara, Andrew M. Gross, Robin R. Gutell, Orly Alter

Abstract

Evolutionary relationships among organisms are commonly described by using a hierarchy derived from comparisons of ribosomal RNA (rRNA) sequences. We propose that even on the level of a single rRNA molecule, an organism's evolution is composed of multiple pathways due to concurrent forces that act independently upon different rRNA degrees of freedom. Relationships among organisms are then compositions of coexisting pathway-dependent similarities and dissimilarities, which cannot be described by a single hierarchy. We computationally test this hypothesis in comparative analyses of 16S and 23S rRNA sequence alignments by using a tensor decomposition, i.e., a framework for modeling composite data. Each alignment is encoded in a cuboid, i.e., a third-order tensor, where nucleotides, positions and organisms, each represent a degree of freedom. A tensor mode-1 higher-order singular value decomposition (HOSVD) is formulated such that it separates each cuboid into combinations of patterns of nucleotide frequency variation across organisms and positions, i.e., "eigenpositions" and corresponding nucleotide-specific segments of "eigenorganisms," respectively, independent of a-priori knowledge of the taxonomic groups or rRNA structures. We find, in support of our hypothesis that, first, the significant eigenpositions reveal multiple similarities and dissimilarities among the taxonomic groups. Second, the corresponding eigenorganisms identify insertions or deletions of nucleotides exclusively conserved within the corresponding groups, that map out entire substructures and are enriched in adenosines, unpaired in the rRNA secondary structure, that participate in tertiary structure interactions. This demonstrates that structural motifs involved in rRNA folding and function are evolutionary degrees of freedom. Third, two previously unknown coexisting subgenic relationships between Microsporidia and Archaea are revealed in both the 16S and 23S rRNA alignments, a convergence and a divergence, conferred by insertions and deletions of these motifs, which cannot be described by a single hierarchy. This shows that mode-1 HOSVD modeling of rRNA alignments might be used to computationally predict evolutionary mechanisms.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 5%
France 1 5%
Belgium 1 5%
Unknown 16 84%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 26%
Student > Ph. D. Student 4 21%
Student > Doctoral Student 2 11%
Professor > Associate Professor 2 11%
Lecturer 2 11%
Other 3 16%
Unknown 1 5%
Readers by discipline Count As %
Agricultural and Biological Sciences 9 47%
Mathematics 2 11%
Computer Science 2 11%
Business, Management and Accounting 1 5%
Immunology and Microbiology 1 5%
Other 3 16%
Unknown 1 5%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 19 May 2011.
All research outputs
#7,454,427
of 22,789,566 outputs
Outputs from PLOS ONE
#88,766
of 194,532 outputs
Outputs of similar age
#40,376
of 110,208 outputs
Outputs of similar age from PLOS ONE
#720
of 1,505 outputs
Altmetric has tracked 22,789,566 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 194,532 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.1. This one is in the 49th percentile – i.e., 49% of its peers scored the same or lower than it.
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