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Distinguishing between canonical and non-canonical tRNA genes reveals that Thermococcaceae adhere to the standard archaeal tRNA gene set
<p><strong>Abstract</strong></p> <p>Automated genome annotation is an essential tool for extracting biological information from sequence data. The identification and annotation of tRNA genes is frequently performed by the software package tRNAscan-SE, the output of which is listed – for selected genomes – in the Genomic tRNA database (GtRNAdb). Given the central role of tRNA in molecular biology, the accuracy and proper application of tRNAscan-SE is important for both interpretation of the output, and continued improvement of the software. Here, we report a manual annotation of the predicted tRNA gene sets for 20 complete genomes from the archaeal taxon Thermococcaceae. According to GtRNAdb, these 20 genomes contain a number of putative deviations from the standard set of canonical tRNA genes in Archaea. However, manual annotation reveals that only one represents a true divergence; the other instances are either (i) non-canonical tRNA genes resulting from the integration of horizontally transferred genetic elements, or CRISPR-Cas activity, or (ii) attributable to errors in the input DNA sequence. To distinguish between canonical and non-canonical archaeal tRNA genes, we recommend using a combination of automated pseudogene detection by tRNAscan-SE and the tRNAscan-SE isotype score, greatly reducing manual annotation efforts and leading to improved predictions of tRNA gene sets in Archaea.</p> <p> </p> <p><strong>Repository contents</strong></p> <p><strong>01_workflow_tRNAscanSE_predictions_210archaea.html </strong>contains the workflow and graphical output for tRNA gene set predictions in 20 Thermococcaceae genomes and 210 archaeal genomes. Files 03 to 06 below are the files quoted in this workflow.</p> <p><strong>02_workflow_tRNAscanSE_predictions_210archaea.Rmd </strong>contains the markdown file associated with 01_workflow_tRNAscanSE_predictions_210archaea.html above.</p> <p><strong>03_thermo_trnas_GtRNAdb.txt</strong><strong> </strong>contains the predicted tRNA gene sets of 20 Thermococcaceae genomes as listed on GtRNAdb (Data Release 19 (June 2021)).</p> <p><strong>04_Archaea_genome_list.txt </strong>contains the details of all 217 archaeal genomes listed on GtRNAdb (Data Release 19 (June 2021)). The seven genomes for which the NCBI genome sequences were no longer available are indicated by #### preceding the name.</p> <p><strong>05_thermo_tRNAs_genome.txt</strong><strong> </strong>contains the predicted tRNA gene sets of 20 Thermococcaceae genomes as predicted by locally run tRNAscan-SE (version 2.0.6), with standard settings for Archaea (option -A). To display the output, options -H and --detail were added. We note that pseudogene detection is active under these conditions.</p> <p><strong>06_Archaea_210_GtRNAdb_tRNAs.txt </strong>contains the predicted tRNA gene sets of the 210 archaeal genomes as listed on GtRNAdb (Data Release 19 (June 2021)).</p> <p><strong>07_Archaea_210genomes_tRNAs.txt</strong> contains the predicted tRNA gene sets of the 210 archaeal genomes as predicted by locally run tRNAscan-SE (version 2.0.6), with standard settings for Archaea (option -A). To display the output, options -H and --detail were added. We note that pseudogene detection is active under these conditions.</p> <p><strong>08_NCBI_genomes.zip</strong> contains the NCBI GenBank genome sequence files used in this study. These include the 20 Thermococcaceae genomes, the wider 210 archaeal genomes, and several others of interest. </p> <p><strong>09_phylogeny.tar.zip</strong> contains the data used to draw a phylogenetic tree for the 20 Thermococcaceae organisms. The folder includes a file listing the details of all data in the folder (Readme.md), a workflow file (workflow_UndinMarkers_v2.md), and data folders.</p> <p> </p> <p><strong>Notes</strong></p> <p>The extended TIGRFAM database referred to in the phylogenetic tree construction process can be found at <a href="https://zenodo.org/record/3839790#.YjByaVzMI3g">https://zenodo.org/record/3839790#.YjByaVzMI3g</a></p> <p>The perl script used during phylogenetic tree construction, catfasta2phyml.pl, is available in the GitHub repository <a href="https://github.com/nylander/catfasta2phyml">https://github.com/nylander/catfasta2phyml</a></p> <p>tRNAscan-SE is a freely available resource available online (<a href="http://lowelab.ucsc.edu/tRNAscan-SE/">http://lowelab.ucsc.edu/tRNAscan-SE/</a>)</p> <p>GtRNAdb is a publicly accessible resource available online (<a href="http://gtrnadb.ucsc.edu/">http://gtrnadb.ucsc.edu/</a>)</p> <p>NCBI is a publicly accessible resource available online (<a href="https://www.ncbi.nlm.nih.gov/">https://www.ncbi.nlm.nih.gov/</a>)</p> <p>rrnDB is a publicly accessible resource available online (<a href="https://rrndb.umms.med.umich.edu/">https://rrndb.umms.med.umich.edu/</a>)</p> <p>BLAST is a publicly accessible resource available online (<a href="https://blast.ncbi.nlm.nih.gov/Blast.cgi">https://blast.ncbi.nlm.nih.gov/Blast.cgi</a>)</p>
Fig. 5 in The complete mitochondrial genome of Platygaster robiniae (Hymenoptera: Platygastridae): A novel tRNA secondary structure, gene rearrangements and phylogenetic implications
Fig. 5. Phylogenetic tree Note: (A): Maximum likelihood (ML) phylogenetic tree inferred from the mitochondrial genome based on the 13 PCGs dataset; (B): Bayesian inference (BI) phylogenetic tree inferred from the mitochondrial genome based on the 13 PCGs dataset.
Fig. 4 in The complete mitochondrial genome of Platygaster robiniae (Hymenoptera: Platygastridae): A novel tRNA secondary structure, gene rearrangements and phylogenetic implications
Fig. 4. Mitochondrial genome organization of Platygaster robiniae and 11 species of Platygastroidea, compared with the ancestral pancrustacean mt genome organization. Note: tRNA genes are indicated by single letter amino acid codes, L1, L2, S1 and S2 denote tRNALeu(CUN), tRNALeu(UUR), tRNASer(AGN) and tRNASer(UCN), respectively. Genes are transcribed from left to right except those indicated by underlining. Gene movements, relative to the ancestral organization, are indicated with arrows.
Fig. 2 in The complete mitochondrial genome of Platygaster robiniae (Hymenoptera: Platygastridae): A novel tRNA secondary structure, gene rearrangements and phylogenetic implications
Fig. 2. Amino acids (A) and relative synonymous codons (B) of protein-coding genes of the mitochondrial genome of Platygaster robiniae.
Fig. 1 in The complete mitochondrial genome of Platygaster robiniae (Hymenoptera: Platygastridae): A novel tRNA secondary structure, gene rearrangements and phylogenetic implications
Fig. 1. Genetic map of the complete mitochondrial genome of Platygaster robiniae. Notes: the blue arrow represents the direction of gene transcription; the black peak represents the deviation of GC%; the purple and green peaks represent the deviation in GC skew; green refers to positive skew, and purple indicates negative skew. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
In silico subcellular targeting predictions for cytosolic aminoacyl tRNA-synthetases (aaRS) in parasitic plants
<p>Eukaryotic nuclear genomes often encode distinct sets of protein translation machinery for function in the cytosol vs. organelles (mitochondria and plastids). This phenomenon raises questions about why multiple translation systems are maintained even though they are capable of comparable functions, and whether they evolve differently depending on the compartment where they operate. These questions are particularly interesting in land plants because translation machinery, including aminoacyl-tRNA synthetases (aaRS), is often dual-targeted to both the plastids and mitochondria. These two organelles have quite different metabolisms, with much higher rates of translation in plastids to supply the abundant, rapid-turnover proteins required for photosynthesis. Previous studies have indicated that plant organellar aaRS evolve more slowly compared to mitochondrial aaRS in other eukaryotes that lack plastids. Thus, we investigated the evolution of nuclear-encoded organellar and cytosolic translation machinery across a broad sampling of angiosperms, including non-photosynthetic (heterotrophic) plant species with reduced rates of plastid gene expression to test the hypothesis that translational demands associated with photosynthesis constrain the evolution of bacterial-like enzymes involved in organellar tRNA metabolism. Remarkably, heterotrophic plants exhibited wholesale loss of many organelle-targeted aaRS and other enzymes, even though translation still occurs in their mitochondria and plastids. These losses were often accompanied by apparent retargeting of cytosolic enzymes and tRNAs to the organelles, sometimes preserving aaRS-tRNA charging relationships but other times creating surprising mismatches between cytosolic aaRS and mitochondrial tRNA substrates. Our findings indicate that the presence of a photosynthetic plastid drives the retention of specialized systems for organellar tRNA metabolism.</p>
Finding orthologs for aminoacyl tRNA synthetases in parasitic plants
<p>Eukaryotic nuclear genomes often encode distinct sets of protein translation machinery for function in the cytosol vs. organelles (mitochondria and plastids). This phenomenon raises questions about why multiple translation systems are maintained even though they are capable of comparable functions, and whether they evolve differently depending on the compartment where they operate. These questions are particularly interesting in land plants because translation machinery, including aminoacyl-tRNA synthetases (aaRS), is often dual-targeted to both the plastids and mitochondria. These two organelles have quite different metabolisms, with much higher rates of translation in plastids to supply the abundant, rapid-turnover proteins required for photosynthesis. Previous studies have indicated that plant organellar aaRS evolve more slowly compared to mitochondrial aaRS in other eukaryotes that lack plastids. Thus, we investigated the evolution of nuclear-encoded organellar and cytosolic translation machinery across a broad sampling of angiosperms, including non-photosynthetic (heterotrophic) plant species with reduced rates of plastid gene expression to test the hypothesis that translational demands associated with photosynthesis constrain the evolution of bacterial-like enzymes involved in organellar tRNA metabolism. Remarkably, heterotrophic plants exhibited wholesale loss of many organelle-targeted aaRS and other enzymes, even though translation still occurs in their mitochondria and plastids. These losses were often accompanied by apparent retargeting of cytosolic enzymes and tRNAs to the organelles, sometimes preserving aaRS-tRNA charging relationships but other times creating surprising mismatches between cytosolic aaRS and mitochondrial tRNA substrates. Our findings indicate that the presence of a photosynthetic plastid drives the retention of specialized systems for organellar tRNA metabolism.</p>
Evolutionary rate analysis of aminoacyl tRNA synthetases
<p>Eukaryotic nuclear genomes often encode distinct sets of protein translation machinery for function in the cytosol vs. organelles (mitochondria and plastids). This phenomenon raises questions about why multiple translation systems are maintained even though they are capable of comparable functions, and whether they evolve differently depending on the compartment where they operate. These questions are particularly interesting in land plants because translation machinery, including aminoacyl-tRNA synthetases (aaRS), is often dual-targeted to both the plastids and mitochondria. These two organelles have quite different metabolisms, with much higher rates of translation in plastids to supply the abundant, rapid-turnover proteins required for photosynthesis. Previous studies have indicated that plant organellar aaRS evolve more slowly compared to mitochondrial aaRS in other eukaryotes that lack plastids. Thus, we investigated the evolution of nuclear-encoded organellar and cytosolic translation machinery across a broad sampling of angiosperms, including non-photosynthetic (heterotrophic) plant species with reduced rates of plastid gene expression to test the hypothesis that translational demands associated with photosynthesis constrain the evolution of bacterial-like enzymes involved in organellar tRNA metabolism. Remarkably, heterotrophic plants exhibited wholesale loss of many organelle-targeted aaRS and other enzymes, even though translation still occurs in their mitochondria and plastids. These losses were often accompanied by apparent retargeting of cytosolic enzymes and tRNAs to the organelles, sometimes preserving aaRS-tRNA charging relationships but other times creating surprising mismatches between cytosolic aaRS and mitochondrial tRNA substrates. Our findings indicate that the presence of a photosynthetic plastid drives the retention of specialized systems for organellar tRNA metabolism.</p>
Finding orthologs for aminoacyl tRNA synthetases in parasitic plants
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In silico subcellular targeting predictions for cytosolic aminoacyl tRNA-synthetases (aaRS) in parasitic plants
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tRNA anticodon cleavage by target-activated CRISPR-Cas13a effector
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Evolutionary rate analysis of aminoacyl tRNA synthetases
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The Structural Basis of the Genetic Code: Amino Acid Recognition by Aminoacyl-tRNA Synthetases
<p>Data sets for the characterization of amino acid recognition in aminoacyl-tRNA synthetases:</p> <ul> <li>multiple-sequence alignment files in FASTA format</li> <li>Excel tables to infer original sequence positions from renumbered positions</li> </ul> <p>Accompanying the paper: <a href="https://www.biorxiv.org/content/10.1101/606459v1">https://www.biorxiv.org/content/10.1101/606459v1</a></p>
Data from: Extreme copy number variation at a tRNA ligase gene affecting phenology and fitness in yellow monkeyflowers
Copy number variation (CNV) is a major part of the genetic diversity segregating within populations, but remains poorly understood relative to single nucleotide variation. Here, we report on a tRNA ligase gene (RLG1a) exhibiting unprecedented, and fitness-relevant, CNV within an annual population of the yellow monkeyflower Mimulus guttatus. Variation at RLG1a was associated with multiple traits in pooled population resequencing (PoolSeq) scans of phenotypic and phenological cohorts. Five of 35 (14%) of resequenced inbred lines carried three-copy variants of RLG1a (trip+), and trip+ lines exhibited elevated RLG1a expression. trip+ carriers, in addition to being over-represented in late-flowering and large-flowered PoolSeq populations, flowered later under stressful conditions in a greenhouse experiment (P < 0.05). In early-flowering wild cohorts, we discovered an additional rare variant (high+) that carries 250-300 copies of RLG1a totaling ~5.7Mb, equivalent to 20-40% of a chromosome. Mendelian segregation of diagnostic alleles and qPCR-based copy counts In the progeny of a high+ carrier, indicate that high+ is a single tandem array unlinked from the single copy RLG1a locus in the reference genome. In the wild, high+ carriers had highest fitness in two dry and/or hot years (2015 and 2017; both P < 0.01), while single copy individuals were twice as fecund as either CNV genotype in a lush year (2016: p < 0.005). Our results demonstrate fluctuating selection on CNVs affecting phenological traits in a wild population, suggest that plant tRNA ligases mediate stress-responsive life-history traits, and introduce a novel system for investigating the molecular mechanisms of gene amplification.
A robust method for measuring aminoacylation through tRNA-Seq
<p>Raw data and code for processing and recreating plots shown in the associated article.</p> <p>The gzipped tar ball was split into 512 mb packs to enable easy upload/download.</p> <p>To download with <code>zenodo_get</code> run the command:</p> <p><code>pip3 install zenodo_get</code></p> <p><code>zenodo_get -r 10778311</code></p> <p>To merge and unzip run the command:</p> <p><code>cat tRNA-charge-seq.tar.gz.part-* | gunzip -c > tRNA-charge-seq.tar</code></p> <p><code>tar -xvf tRNA-charge-seq.tar</code></p>
Microscopy images and movies supporting the publication: "tRNA tracking for direct measurements of protein synthesis kinetics in live cells"
<p>This repository contains experimental and simulated microscopy movies and images supporting the publication: Volkov et al. (2018) tRNA tracking for direct measurements of protein synthesis kinetics in live cells. <em>Nat Chem Biol, </em>DOI: 10.1038/s41589-018-0063-y</p> <p>A detailed list of files and file organisation can be found in Repository_content.pdf.</p>
Fig. 4 in The complete mitochondrial genome of Platygaster robiniae (Hymenoptera: Platygastridae): A novel tRNA secondary structure, gene rearrangements and phylogenetic implications
Fig. 4. (continued).
Fig. 3 in The complete mitochondrial genome of Platygaster robiniae (Hymenoptera: Platygastridae): A novel tRNA secondary structure, gene rearrangements and phylogenetic implications
Fig. 3. The secondary structure of 22 tRNA in Platygaster robiniae.
Arabidopsis TRM5 encodes a nuclear-localised bifunctional tRNA guanine and inosine-N1-methyltransferase that is important for growth
<p>Modified nucleosides in tRNAs are critical for protein translation. N<sup>1</sup>-methylguanosine-37 and N<sup>1</sup>-methylinosine-37 in tRNAs, both located at the 3’-adjacent to the anticodon, are formed by Trm5. Here we describe <em>Arabidopsis thaliana AtTRM5</em> (At3g56120) as a Trm5 ortholog. <em>Attrm5</em> mutant plants have overall slower growth as observed by slower leaf initiation rate, delayed flowering and reduced primary root length. In <em>Attrm5</em> mutants, mRNAs of flowering time genes are less abundant and correlated with delayed flowering. We show that <em>AtTRM5</em> complements the yeast <em>trm5</em> mutant, and <em>in vitro</em> methylates tRNA guanosine-37 to produce N<sup>1</sup>-methylguanosine (m<sup>1</sup>G). We also show <em>in vitro</em> that AtTRM5 methylates tRNA inosine-37 to produce N<sup>1</sup>-methylinosine (m<sup>1</sup>I) and in <em>Attrm5</em> mutant plants, we show a reduction of both N<sup>1</sup>-methylguanosine and N<sup>1</sup>-methylinosine. We also show that AtTRM5 is localized to the nucleus in plant cells. Proteomics data showed that photosynthetic protein abundance is affected in <em>Attrm5</em> mutant plants. Finally, we show tRNA-Ala aminoacylation is not affected in <em>Attrm5</em> mutants. However the abundance of tRNA-Ala and tRNA-Asp 5’ half cleavage products are deduced. Our findings highlight the bifunctionality of AtTRM5 and the importance of the post-transcriptional tRNA modifications m<sup>1</sup>G and m<sup>1</sup>I at tRNA position 37 in general plant growth and development.</p>
Data from: Antibody production relies on the tRNA inosine wobble modification to meet biased codon demand
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