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Orthologs, turn-over, and remolding of tRNAs in primates and fruit flies

Overview of attention for article published in BMC Genomics, August 2016
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Title
Orthologs, turn-over, and remolding of tRNAs in primates and fruit flies
Published in
BMC Genomics, August 2016
DOI 10.1186/s12864-016-2927-4
Pubmed ID
Authors

Cristian A. Velandia-Huerto, Sarah J. Berkemer, Anne Hoffmann, Nancy Retzlaff, Liliana C. Romero Marroquín, Maribel Hernández-Rosales, Peter F. Stadler, Clara I. Bermúdez-Santana

Abstract

Transfer RNAs (tRNAs) are ubiquitous in all living organism. They implement the genetic code so that most genomes contain distinct tRNAs for almost all 61 codons. They behave similar to mobile elements and proliferate in genomes spawning both local and non-local copies. Most tRNA families are therefore typically present as multicopy genes. The members of the individual tRNA families evolve under concerted or rapid birth-death evolution, so that paralogous copies maintain almost identical sequences over long evolutionary time-scales. To a good approximation these are functionally equivalent. Individual tRNA copies thus are evolutionary unstable and easily turn into pseudogenes and disappear. This leads to a rapid turnover of tRNAs and often large differences in the tRNA complements of closely related species. Since tRNA paralogs are not distinguished by sequence, common methods cannot not be used to establish orthology between tRNA genes. In this contribution we introduce a general framework to distinguish orthologs and paralogs in gene families that are subject to concerted evolution. It is based on the use of uniquely aligned adjacent sequence elements as anchors to establish syntenic conservation of sequence intervals. In practice, anchors and intervals can be extracted from genome-wide multiple sequence alignments. Syntenic clusters of concertedly evolving genes of different families can then be subdivided by list alignments, leading to usually small clusters of candidate co-orthologs. On the basis of recent advances in phylogenetic combinatorics, these candidate clusters can be further processed by cograph editing to recover their duplication histories. We developed a workflow that can be conceptualized as stepwise refinement of a graph of homologous genes. We apply this analysis strategy with different types of synteny anchors to investigate the evolution of tRNAs in primates and fruit flies. We identified a large number of tRNA remolding events concentrated at the tips of the phylogeny. With one notable exception all phylogenetically old tRNA remoldings do not change the isoacceptor class. Gene families evolving under concerted evolution are not amenable to classical phylogenetic analyses since paralogs maintain identical, species-specific sequences, precluding the estimation of correct gene trees from sequence differences. This leaves conservation of syntenic arrangements with respect to "anchor elements" that are not subject to concerted evolution as the only viable source of phylogenetic information. We have demonstrated here that a purely synteny-based analysis of tRNA gene histories is indeed feasible. Although the choice of synteny anchors influences the resolution in particular when tight gene clusters are present, and the quality of sequence alignments, genome assemblies, and genome rearrangements limits the scope of the analysis, largely coherent results can be obtained for tRNAs. In particular, we conclude that a large fraction of the tRNAs are recent copies. This proliferation is compensated by rapid pseudogenization as exemplified by many very recent alloacceptor remoldings.

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The data shown below were compiled from readership statistics for 25 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Denmark 1 4%
Unknown 24 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 24%
Student > Master 6 24%
Student > Bachelor 2 8%
Student > Ph. D. Student 2 8%
Professor > Associate Professor 1 4%
Other 1 4%
Unknown 7 28%
Readers by discipline Count As %
Agricultural and Biological Sciences 4 16%
Computer Science 4 16%
Biochemistry, Genetics and Molecular Biology 3 12%
Engineering 2 8%
Nursing and Health Professions 1 4%
Other 3 12%
Unknown 8 32%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 23 May 2017.
All research outputs
#14,718,998
of 23,577,654 outputs
Outputs from BMC Genomics
#5,804
of 10,777 outputs
Outputs of similar age
#209,736
of 358,203 outputs
Outputs of similar age from BMC Genomics
#143
of 265 outputs
Altmetric has tracked 23,577,654 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,777 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 42nd percentile – i.e., 42% of its peers scored the same or lower than it.
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We're also able to compare this research output to 265 others from the same source and published within six weeks on either side of this one. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.