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Paper text:
transfer rnas , a central component of protein translation , represent a highly complex class of genes that are ancient yet still evolving . trnascan - se remains the de facto tool for identifying trna genes encoded in genomes with over 5000 citations ( 1 ) , and has a wide variety of users including sequencing centers , biological database annotators , rna biologists and computational biology researchers .
transfer rnas predicted using trnascan - se are currently available for thousands of genomes in the gtrnadb ( 2,3 ) , yet the gtrnadb is not designed for user - driven trna gene detection .
we previously described the trnascan - se web server 11 years ago ( 4 ) , a publication that has garnered over 750 citations ( google scholar ) and has been downloaded for full - text viewing more than 7500 times ( nucleic acids research article metrics ) .
the original trnascan - se web server currently receives about 1000 unique visitors a month , aiding a large swath of the research community that may not have computational resources or expertise to install and run the unix - based software . here
, we describe a new web analysis server in conjunction with the development of trnascan - se 2.0 ( chan et  al .
the new version of trnascan - se has improved covariance model search technology enabled by the infernal 1.1 software ( 5 ) ; updated covariance models for more sensitive trna searches , leveraging a much broader diversity of trna genes from thousands of sequenced genomes ; better functional classification of trnas , based on comparative analysis using a suite of 22 isotype - specific trna covariance models for each domain of life ; and ability to detect mitochondrial trnas ( in addition to cytosolic eukaryotic , archaeal and bacterial trnas ) , with high accuracy using new mitochondrial - specific models . in addition to new search capabilities
, the web server now enables users to place their trna predictions in similarity context within the gtrnadb , as well as genomic context within available ucsc genome browsers .
similar to the original version of the trnascan - se search server ( 4 ) , users may select among multiple types of trnas ( mixed / general , eukaryotic , bacterial , archaeal or mitochondrial ) as well as different search modes to identify trna genes in their provided sequences .
, in preparation ) utilizes the latest version of the infernal software package ( v1.1.1 ) ( 5 ) to search dna sequences for trna - like structure and sequence similarities .
the infernal software implements a special case of profile stochastic context - free grammars called covariance models , which can be trained to have different specificities depending on the selection of structurally aligned rna sequences which serve as training sets .
trnascan - se 2.0 employs a suite of covariance models in multiple analysis steps to maximize sensitivity and classification accuracy . in an initial first - pass scan , infernal
is used with a relatively permissive score threshold ( 10 bits ) in combination with a search model trained on trnas from all trna isotypes in order to obtain high sensitivity .
the mid - level strictness filter (  -  -mid ) is also used to accelerate search speed at minimal cost to sensitivity .
the user can choose to search with a trna model trained on trnas from all domains of life (  mixed ) , or preferably , select from one of three domain - specific models trained on trnas exclusively from archaea , bacteria or eukarya .
a second - pass scan of individual candidates detected in the first - pass also uses infernal ( 5 ) but with a higher score threshold to increase selectivity , no acceleration filter to increase alignment accuracy and multiple isotype - specific covariance models to better determine isotype identity .
these changes in the trnascan - se 2.0 software and search models produce slightly different bit scores relative to trnascan - se 1.2.1 ( 1 ) , although the relative rankings of previously detected trnas should largely be unchanged . in order to provide backward comparisons
legacy search mode which uses the trnascan - se 1.2.1 search software . for users who need maximum search sensitivity for low - scoring trna - like sequences ( e.g. trna - derived sines or pseudogenes )
, we include the search mode option  infernal without hmm which is only recommended for very short sequence queries due to the slow search speed .
sequence and structure - based determinants , both positive and negative , are used by aminoacyl - trna synthetases to establish trna identity , and have been characterized in a number of model species ( 6 ) .
previously , we used the anticodon exclusively to predict trna isotype because the anticodon can be easily identified within a trna gene candidate and nearly always gives unambiguous identification of the trna isotype . however , there exist cases of  chimeric trnas in which point mutation(s ) in the anticodon sequence could result in  recoding events ( 7,8 ) . in this case
, the body of the trna contains identity elements recognized by one type of trna synthetase , yet the altered anticodon  reads the mrna codon corresponding to a different amino acid .
the decoding behavior of such trnas could theoretically be modulated by post - transcriptional anticodon modifications that either preserve or alter the genetic code .
the full biological scope and significance of chimeric trnas is not well understood because of the historical lack of large - scale , systematic detection methods , but it is now possible and valuable to detect these potentially important chimeric trnas which could result in tissue or condition - specific recoding of proteins .
thus , we developed a new multi - model annotation strategy for trnascan - se 2.0 where , after establishing trna gene coordinates and predicting function by anticodon , we also analyze the gene prediction with a full set of isotype - specific covariance models , in a strategy similar to tfam ( 9 ) .
these 20 + models are built by simply sub - dividing the original trna training set into subgroups of the universal 20 amino acids ( ala , arg , cys , etc ) , plus one for initiator / formyl - methionine ( imet / fmet ) , one to identify prokaryotic ile trnas genomically encoded with a cat anticodon , and one to recognize selenocysteine trnas .
each of these subgroups forms the basis for 20 + models for each domain ( 22 for eukaryotes , 23 for bacteria , 23 for archaea ) .
now , alongside the predicted isotype based on the anticodon , the highest scoring isotype - specific model is also reported ; any disagreement between the two functional prediction methods is reported for closer user inspection
. there may be insufficient data to establish the true trna identity when there is disagreement because trna synthetase identity elements have only been experimentally verified in a small number of species .
however , we believe this supplemental isotype - specific model analysis will enable the trna research community to more readily identify and experimentally investigate potential trna chimeras in the future .
an example of this type of potential chimeric trna is human val - aac-6 - 1 (  gggggtgtagctcagtggtagagcgtatgcttaacattcatgaggctctgggttcgatccccagcacttcca ) that contains the anticodon aac ( in bold ) , but scores highest against the eukaryotic trna isotype model for alanine .
the resulting trnas identified in the user 's sequence can be searched against the gtrnadb ( 3 ) , yielding links to identical or highly similar trna genes found in the database ( figure 1 ) .
if a ucsc genome browser ( 10,11 ) exists for any identical or close trna matches , a direct link is provided to those matches , enabling the user to examine its genomic context and any additional information available in genome browser tracks . in the example given ( figure 1 ) , 
myseq3 contains one trna prediction yielding an infernal score of 71.6 bits , as scored by an  all - isotype eukaryotic trna model .
the identified trna has one intron and is predicted to be charged with serine based on the cga anticodon inferred from the predicted trna secondary structure . upon comparison to the full suite of specialized / isotype - specific models , the highest scoring model in second - pass analysis corresponded to trna - serine , at 117.9 bits .
trnas will usually get a higher score against their true isotype - specific model because specialized models are not  diluted by trna sequence features found only in other isotypes .
selecting the first button in each row visualizes the predicted secondary structure , while the second button executes a fast sequence similarity search to find identical or very similar trnas in the gtrnadb .
the figure shows perfect matches to ser - cga trnas in several saccharomyces species ; upon selecting the 
view link for saccharomyces cerevisiae ser - cga-1 - 1 , its individual gene page displays a wealth of information , including upstream and downstream genomic sequences , atypical features ( u51:u63 ) , 13 rna modifications previously characterized , a multiple sequence alignment with all other ser trna genes in this species ( not shown ) and trna - seq expression profiles for mature and pre - trnas mapped to this locus ( not shown ) . finally , links from either the gtrnadb gene page , or the list of perfect matching hits shows the trna gene in the interactive ucsc genome browser with tracks that show the level of multi - genome conservation among six other yeast species , the positions of previously noted modifications , trna - seq expression data and the  sgd genes track , aiding further exploration of this gene 's biological context .
the saccharomyces cerevisiae trna - ser is analyzed using the trnascan - se web server in default eukaryotic search mode .
the red arrows show the analysis path from viewing the predicted trna results to finding the matching trna gene in gtrnadb ( 3 ) , to exploring the trna gene in context with trna modifications and gene expression data in the ucsc genome browser ( 10 ) .
as the technology for sequencing and assembling genomes continues to improve , we anticipate that the demand to identify and annotate trna genes in new , complete genomes will continue to accelerate .
completeness report using phylogenetic patterns of trna set composition observed across all genomes represented in the gtrnadb . noting potential  missing or 
surplus trna gene decoding potential will be useful to assess genome quality and completeness , as well as recognizing potential genome assembly errors or sequencing contamination .
a second planned capability is metagenomic analysis of sequencing data containing an unknown mix of species . by doing comparative analysis using a suite of isotype - specific and phylum - specific covariance models ( under development now )
, we hope to offer a trna identification and phylogenetic classification service as part of the trnascan - se web server .
finally , with the increase in knowledge of functional trna fragments , we plan to offer detection and systematic classification of fragments in the context of full - length trna genes .
national human genome research institute , national institutes of health [ hg006753 - 02 to t.l . ] . funding for open access charge : nhgri / nih [ hg006753 - 02 ] ; university of california , santa cruz department chair research stipend .
high - throughput genome sequencing continues to grow the need for rapid , accurate genome annotation and trna genes constitute the largest family of essential , ever - present non - coding rna genes . 
 newly developed trnascan - se 2.0 has advanced the state - of - the - art methodology in trna gene detection and functional prediction , captured by rich new content of the companion genomic trna database . 
 previously , web - server trna detection was isolated from knowledge of existing trnas and their annotation . in this update of the trnascan - se on - line resource 
 , we tie together improvements in trna classification with greatly enhanced biological context via dynamically generated links between web server search results , the most relevant genes in the gtrnadb and interactive , rich genome context provided by ucsc genome browsers . 
 the trnascan - se on - line web server can be accessed at http://trna.ucsc.edu / trnascan - se/.