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Data from: Extreme copy number variation at a tRNA ligase gene affecting phenology and fitness in yellow monkeyflowers
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tRNA-derived fragment tRF-Glu49 inhibits cell proliferation, migration and invasion in cervical cancer by targeting FGL1
<p>A transfer RNA (tRNA)-derived fragment was found to be a new possible biological marker and target in carcinoma therapy. However, the effect exerted by tRFs on cervical carcinoma is still unclear. We identify the potential tumor suppressor gene tRF-Glu49 in cervical carcinoma through tRF and ti-RNA microarray investigation. We then demonstrated that tRF-Glu49 showed downregulation within the cervical carcinoma tissue and was associated with less aggressive clinical features and a better prognosis. Phenotypic studies revealed that tRF-Glu49 inhibited cervical cell proliferation, migration, and invasion processes. Mechanistic investigation revealed that tRF-Glu49 directly regulated the oncogene, fibrinogen-like protein-1 (FGL1). In general, according to the result achieved in this study, tRF-Glu49 can modulate cervical cell proliferation, migration, and invasion processes through the target process for FGL1, and tRF-Glu49 is likely to be a possible prognostic biological marker in patients with cervical carcinoma.</p>
Aminoacyl-tRNA synthetase gene alignments from multiple Sileneae species generated from full-length transcripts using Iso-Seq and raw microscopy image files
<p>Trimmed and untrimmed alignments for the final aminoacyl-tRNA synthetases in <em>Sileneae </em>species and <em>Arabidopsis thaliana. W</em>e investigated the evolution of subcellular localization of aaRS enzymes in five different species from the plant lineage <em>Sileneae</em> that has experienced extensive and rapid mitochondrial tRNA loss. By analyzing full-length mRNA transcripts with single-molecule sequencing technology (PacBio Iso-Seq) and searching genome sequences, we found instances of predicted retargeting of an ancestrally cytosolic aaRS to the mitochondrion as well as scenarios where enzyme localization does not appear to change despite functional tRNA replacement.</p> <p>Nikon .nd2 raw microscopy files for the transient expression and imaging of predicted transit peptides and colocalization assays in <em>N. benthamiana</em> epithelial cells. The amino acid sequence plus 10 upstream amino acids of the protein body were fused to GFP and co-transfected with an eqFP611-tagged transit peptide from a known mitochondrially localized protein (isovaleryl-CoA dehydrogenase).</p>
A translation-independent directed evolution strategy to engineer aminoacyl-tRNA synthetases_NGS data analysis
<p>These data files are associated with the NGS analysis done in the publication :"A translation-independent directed evolution strategy to engineer aminoacyl-tRNA synthetases". This compressed file contains the raw file as well as the processed files to arrive at the conclusions published. The python scripts used for processing the data are available on github (link provided in the manuscript).</p>
Fig. 3 in An exceptional case of mitochondrial tRNA duplication-deletion events in blood-feeding leeches
Fig. 3 Genetic signature of the trnD1/trnD2 genes of Placobdella species highlighted in an alignment
Fig. 4 in An exceptional case of mitochondrial tRNA duplication-deletion events in blood-feeding leeches
Fig. 4 Position of the conserved nucleotides in the P. parasitica trnD product (highlighted in purple)
Fig. 1 in An exceptional case of mitochondrial tRNA duplication-deletion events in blood-feeding leeches
Fig. 1 Maximum Likelihood tree built based on 4 concatenated molecular markers (cox1, nad1, ITS and 12S). Taxon names in orange correspond to specimens in which trnD2 was found. Taxon names in pink and blue possess, respectively, a trnD3 or trnD4 locus. Taxon names in black possess only trnD1 and the gray taxon names indicate lack of data. Horizontal bars next to taxon names represent the order and relative length of genes between atp8 and cox2. Cox2 segment is 530 bp long and the sizes of the other genes in each diagram are proportional to it. Pie charts in nodes represent the character state predicted for that node by a parsimony approach, where purple indicates presence of additional loci (trnD2–4) and white, absence. Node A represents the last common ancestor of all leeches, node B is the ancestor of all Placobdella species and node C is the first node in Placobdella which represents an ancestor with almost 100% certainty of having multiple trnD copies
Fig. 2 in An exceptional case of mitochondrial tRNA duplication-deletion events in blood-feeding leeches
Fig. 2 Predicted secondary structures of the products of trnD2 in samples that present substitutions in the GUC canonical anticodon. (A) P. rugosa, samples from Ontario, Manitoba, and Nebraska; (B) Placobdella sp. 1 AL; (C) P. kwetlumye
Rationally Designed Pooled CRISPRi-Seq Uncovers an Inhibitor of Bacterial Peptidyl-tRNA Hydrolase
<p>This dataset contains the raw read counts from the CRISPRi-Seq experiments.</p>
Figure 1 in Complete mitochondrial genome of the terrestrial isopod Cubaris murina Brandt, 1833: new family gene order and novel tRNA secondary structures
Figure 1. Mitochondrial genome synteny in Cubaris murina and closely related species. A dash (-) before the gene name means that the gene is encoded on the light strand. NCR means a non-coding region that is longer than 100 bp. Cubaris murina is marked in bold black and shades of grey.
Figure 2 in Complete mitochondrial genome of the terrestrial isopod Cubaris murina Brandt, 1833: new family gene order and novel tRNA secondary structures
Figure 2. Secondary structure of each transfer RNA (tRNA) visualised in Forna (http://rna.tbi.univie.ac. at/forna).
Table 3 in Complete mitochondrial genome of the terrestrial isopod Cubaris murina Brandt, 1833: new family gene order and novel tRNA secondary structures
<p><b>Table 3.</b> Characteristic (AT content, repeat, number of predicted secondary structure, range of <i>ΔG</i> value (kcal/mol)) of control region of <i>Cubaris murina</i> by RNAstructure.</p><table><tbody><tr><th></th><th></th><th></th><th></th><th>Length</th><th></th><th></th><th></th><th>Number of predicted</th><th></th></tr></tbody><tbody><tr><th>Species [reference]</th><td>Name</td><td>Start</td><td>Stop</td><td>(bp)</td><td>Location</td><td>%AT</td><td>Repeat</td><td>secondary structures</td><td><i>ΔG</i> value (kcal/mol)</td></tr><tr><th><i>Cubaris murina</i></th><td>NCR1</td><td>5219</td><td>5360</td><td>142</td><td>Between <i>nad1</i> and <i>trnN</i></td><td>52.80%</td><td></td><td>7</td><td>−16.9 to −15.4</td></tr><tr><th>[present study]</th><td>NCR2</td><td>6297</td><td>6666</td><td>370</td><td>Between <i>trnS1</i> and <i>trnL1</i></td><td>59.70%</td><td>CT-rich & AT-loop</td><td>20</td><td>−103.7 to −101.0</td></tr><tr><th></th><td>NCR3</td><td>12,550</td><td>12,753</td><td>204</td><td>Between <i>rrnL</i> and <i>trnE</i></td><td>71.10%</td><td>poly-A</td><td>7</td><td>−17.5 to −17.1</td></tr><tr><th></th><td>NCR4</td><td>12,813</td><td>12,950</td><td>138</td><td>Between <i>trnE</i> and <i>trnV</i></td><td>71.70%</td><td>AG-rich</td><td>5</td><td>−13.4 to −12.3</td></tr><tr><th><i>Panulirus argus</i> [Baeza, 2018]</th><td>NCR</td><td>13,525</td><td>14,326</td><td>801</td><td>Between <i>rrnS</i> and <i>trnI</i></td><td>69.60%</td><td>AT-rich</td><td>7</td><td>−99.20 to −94.52</td></tr><tr><th><i>Synalpheus microneptunus</i> [Chak <i>et al.</i>, 2020]</th><td>NCR</td><td>13,365</td><td>14,198</td><td>834</td><td>Between <i>rrnS</i> and <i>trnI</i></td><td>79.50%</td><td>AT-rich</td><td>20</td><td>− 104 (lowest)</td></tr></tbody></table>
Ultradeep characterisation of translational sequence determinants refutes rare-codon hypothesis and unveils quadruplet base pairing of initiator tRNA and transcript
<p>## Overview</p> <p>This repository contains the data and R-scripts to reproduce the figures in the main text of the manuscript "Ultradeep characterisation of translational sequence determinants refutes rare-codon hypothesis and unveils quadruplet base pairing of initiator tRNA and transcript", which can be found here: (https://doi.org/10.1093/nar/gkad040).</p> <p> </p> <p>## Additional information</p> <p>The data can also be found on github via https://github.com/JeschekLab/uASPIre_UTR_CDS. The github repository also includes updates, scripts for NGS data analysis and additional code for data processing.</p> <p> </p>
Data for: Engineering tRNA abundances for synthetic cellular systems
<p>Data for publication:<strong> Engineering tRNA abundances for synthetic cellular systems</strong></p> <p><strong>Abstract</strong></p> <p>Routinizing the engineering of synthetic cells requires specifying determining beforehand how many of each molecule are needed. First-principles tools for specifying molecular abundances enabling whole-cell synthetic biology are missing. We use a colloidal dynamics simulator to make predictions for how tRNA abundances impact protein synthesis rates. We use rational design and direct RNA synthesis to make 21 synthetic tRNA surrogates from scratch. We use evolutionary algorithms within a computer aided design framework to design engineer translation systems predicted to work faster or slower depending on tRNA abundance differences. We build and test the so-specified synthetic systems and find that qualitative agreement between expected and observed systems performance matchqualitatively match. First-principles modeling combined with bottom-up experiments can help molecular-to-cellular scale synthetic biology realize “design, build, work” frameworks that transcend tinker-and-test.</p> <p><strong>Data description</strong></p> <p>The data here consists of (1) All Colloidal Smoldyn & CD-CAD simulation input parameter and output files & (2) experimental data used for the associated publication. Simulation data was produced using Colloidal Dynamics modeling and Colloidal Dyamics-CAD (CD-CAD) as described in the associated manuscript. Data folders should be used directly with modeling and analysis code provided on Github: https://github.com/EndyLab/tRNACAD.</p>
Aminoacyl-tRNA synthetase gene alignments from multiple Sileneae species generated from full-length transcripts using Iso-Seq and raw microscopy image files
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Stable Trajectory of tRNA_HRM, PolyA_HRM, PGC_HRM
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Fig. 6 Bayesian Inference relationships obtained for all the trnD1–4 in An exceptional case of mitochondrial tRNA duplication-deletion events in blood-feeding leeches
Fig. 6 Bayesian Inference relationships obtained for all the trnD1–4 sequences known to date
Fig. 5 Maximum Likelihood inferred relationships for all the trnD1–4 in An exceptional case of mitochondrial tRNA duplication-deletion events in blood-feeding leeches
Fig. 5 Maximum Likelihood inferred relationships for all the trnD1–4 sequences known to date
Table 1 in Complete mitochondrial genome of the terrestrial isopod Cubaris murina Brandt, 1833: new family gene order and novel tRNA secondary structures
<p><b>Table 1.</b> Arrangement and annotation of the mitochondrial genome of Cubaris murina.</p><table><tbody><tr><th></th><th></th><th></th><th></th><th></th><th>Length</th><th></th><th></th><th></th><th></th></tr></tbody><tbody><tr><th>Name</th><td>Type</td><td>Start</td><td>Stop</td><td>Strand</td><td>(bp)</td><td>Start</td><td>Stop</td><td>Inter-genic space</td><td>Overlap</td></tr><tr><th>Cox1</th><td>Coding</td><td>1</td><td>1536</td><td>+</td><td>1536</td><td>ATG</td><td>TAA</td><td>1</td><td></td></tr><tr><th>trnL2(tta)</th><td>tRNA</td><td>1538</td><td>1598</td><td>+</td><td>61</td><td></td><td></td><td>48</td><td></td></tr><tr><th>Cox2</th><td>Coding</td><td>1647</td><td>2282</td><td>+</td><td>636</td><td>ATA</td><td>TAG</td><td></td><td>2</td></tr><tr><th>trnK(aaa)</th><td>tRNA</td><td>2281</td><td>2336</td><td>+</td><td>56</td><td></td><td></td><td></td><td>8</td></tr><tr><th>trnD(gac)</th><td>tRNA</td><td>2329</td><td>2403</td><td>+</td><td>75</td><td></td><td></td><td></td><td>17</td></tr><tr><th>atp8</th><td>Coding</td><td>2387</td><td>2533</td><td>+</td><td>147</td><td>ATA</td><td>TAA</td><td></td><td>4</td></tr><tr><th>atp6</th><td>Coding</td><td>2530</td><td>3192</td><td>+</td><td>663</td><td>ATA</td><td>TAA</td><td>2</td><td></td></tr><tr><th>Cox3</th><td>Coding</td><td>3195</td><td>3989</td><td>+</td><td>795</td><td>ATG</td><td>TAG</td><td></td><td>2</td></tr><tr><th>trnR(cga)</th><td>tRNA</td><td>3988</td><td>4055</td><td>+</td><td>68</td><td></td><td></td><td>55</td><td></td></tr><tr><th>nad3</th><td>Coding</td><td>4111</td><td>4407</td><td>+</td><td>297</td><td>ATA</td><td>TAA</td><td></td><td>9</td></tr><tr><th>trnA(gca)</th><td>tRNA</td><td>4399</td><td>4446</td><td>+</td><td>48</td><td></td><td></td><td></td><td>8</td></tr><tr><th>nad1 CR putative</th><td>Coding</td><td>4439 5219</td><td>5218 5360</td><td>−</td><td>780 142</td><td>ATG</td><td>TAG</td><td></td><td>14</td></tr><tr><th>NCR1</th><td>tRNA</td><td>5361</td><td>5429</td><td>+</td><td>69</td><td></td><td></td><td></td><td>17</td></tr><tr><th>rrnS</th><td>rRNA</td><td>5413</td><td>6139</td><td>+</td><td>727</td><td></td><td></td><td>48</td><td></td></tr><tr><th>trnW(tga)</th><td>tRNA</td><td>6188</td><td>6244</td><td>+</td><td>57</td><td></td><td></td><td></td><td>7</td></tr><tr><th>trnS1(aga)</th><td>tRNA</td><td>6238</td><td>6296</td><td>−</td><td>59</td><td></td><td></td><td></td><td></td></tr><tr><th>NCR2</th><td></td><td>6297</td><td>6666</td><td></td><td>370</td><td></td><td></td><td></td><td></td></tr><tr><th>trnL1(cta)</th><td>tRNA</td><td>6667</td><td>6731</td><td>−</td><td>65</td><td></td><td></td><td>29</td><td></td></tr><tr><th>cob</th><td>Coding</td><td>6759</td><td>7907</td><td>−</td><td>1,149</td><td>ATA</td><td>TAG</td><td>38</td><td></td></tr><tr><th>trnT(aca)</th><td>tRNA</td><td>7946</td><td>8017</td><td>−</td><td>72</td><td></td><td></td><td>29</td><td></td></tr><tr><th>nad5</th><td>Coding</td><td>8047</td><td>9648</td><td>+</td><td>1,602</td><td>ATG</td><td>TAG</td><td></td><td>3</td></tr><tr><th>trnF(ttc)</th><td>tRNA</td><td>9646</td><td>9707</td><td>+</td><td>62</td><td></td><td></td><td></td><td>15</td></tr><tr><th>trnH(cac)</th><td>tRNA</td><td>9693</td><td>9758</td><td>−</td><td>66</td><td></td><td></td><td></td><td>23</td></tr><tr><th>nad4</th><td>Coding</td><td>9736</td><td>11,082</td><td>−</td><td>1,312</td><td>ATA</td><td>TAA</td><td>13</td><td></td></tr><tr><th>nad4L</th><td>Coding</td><td>11,096</td><td>11,374</td><td>−</td><td>279</td><td>ATA</td><td>TAA</td><td></td><td>13</td></tr><tr><th>trnP(cca)</th><td>tRNA</td><td>11,362</td><td>11,422</td><td>−</td><td>61</td><td></td><td></td><td>25</td><td></td></tr><tr><th>nad6</th><td>Coding</td><td>11,448</td><td>11,903</td><td>+</td><td>456</td><td>ATA</td><td>TAG</td><td></td><td>2</td></tr><tr><th>trnS2(tca)</th><td>tRNA</td><td>11,902</td><td>11,962</td><td>+</td><td>61</td><td></td><td></td><td>17</td><td></td></tr><tr><th>rrnL</th><td>rRNA</td><td>11,980</td><td>12,549</td><td>−</td><td>570</td><td></td><td></td><td></td><td></td></tr><tr><th>NCR3</th><td></td><td>12,550</td><td>12,753</td><td></td><td>204</td><td></td><td></td><td></td><td></td></tr><tr><th>trnE(gaa)</th><td>tRNA</td><td>12,754</td><td>12,812</td><td>−</td><td>59</td><td></td><td></td><td></td><td></td></tr><tr><th>NCR4</th><td></td><td>12,813</td><td>12,950</td><td></td><td>138</td><td></td><td></td><td></td><td></td></tr><tr><th>trnV(gta)</th><td>tRNA</td><td>12,951</td><td>13,019</td><td>−</td><td>69</td><td></td><td></td><td></td><td>5</td></tr><tr><th>trnQ(caa)</th><td>tRNA</td><td>13,015</td><td>13,077</td><td>−</td><td>63</td><td></td><td></td><td></td><td>6</td></tr><tr><th>trnM(atg)</th><td>tRNA</td><td>13,072</td><td>13,141</td><td>+</td><td>70</td><td></td><td></td><td>25</td><td></td></tr><tr><th>nad2</th><td>Coding</td><td>13,167</td><td>14,123</td><td>+</td><td>978</td><td>ATA</td><td>TAG</td><td></td><td>15</td></tr><tr><th>trnC(tgc)</th><td>tRNA</td><td>14,109</td><td>14,158</td><td>−</td><td>50</td><td></td><td></td><td></td><td></td></tr><tr><th>trnY(tac)</th><td>tRNA</td><td>14,159</td><td>14,205</td><td>−</td><td>47</td><td></td><td></td><td>7</td><td></td></tr></tbody></table>
Table 2 in Complete mitochondrial genome of the terrestrial isopod Cubaris murina Brandt, 1833: new family gene order and novel tRNA secondary structures
<p><b>Table 2.</b> Base composition (%) of nucleotide, AT content, and AT- and GC-skew of the mitochondrial genome of <i>Cubaris murina.</i> Values in bold indicate positive AT-skew.</p><table><tbody><tr><th></th><th></th><th></th><th>Base composition (%)</th><th></th><th></th><th></th><th></th></tr></tbody><tbody><tr><th>Total</th><td></td><td>A</td><td>C</td><td>G</td><td>T</td><td>%AT</td><td>AT skew</td><td>GC skew</td></tr><tr><th>14,212 bp</th><td>28.90%</td><td>15.80%</td><td>23.40%</td><td>31.90%</td><td>60.80%</td><td>−0.049</td><td>0.194</td></tr><tr><th></th><td></td><td></td><td>Base composition (%)</td><td></td><td></td><td></td><td></td></tr><tr><th>Gene Strand</th><td>A</td><td>C</td><td>G</td><td>T</td><td>%AT</td><td>AT skew</td><td>GC skew</td></tr><tr><th><i>cox1</i></th><td>(+)</td><td>22.4%</td><td>18.6%</td><td>24.2%</td><td>34.8%</td><td>57.2%</td><td>−0.217</td><td>0.131</td></tr><tr><th><i>cox2</i></th><td>(+)</td><td>20.6%</td><td>21.7%</td><td>27.7%</td><td>30.0%</td><td>50.6%</td><td>−0.186</td><td>0.121</td></tr><tr><th><i>atp8</i></th><td>(+)</td><td>21.1%</td><td>15.0%</td><td>34.7%</td><td>29.3%</td><td>50.4%</td><td>−0.163</td><td>0.396</td></tr><tr><th><i>atp6</i></th><td>(+)</td><td>20.4%</td><td>19.8%</td><td>29.1%</td><td>30.8%</td><td>51.2%</td><td>−0.203</td><td>0.190</td></tr><tr><th><i>cox3</i></th><td>(+)</td><td>17.2%</td><td>23.6%</td><td>28.6%</td><td>30.6%</td><td>47.8%</td><td>−0.280</td><td>0.096</td></tr><tr><th><i>nad3</i></th><td>(+)</td><td>20.2%</td><td>16.2%</td><td>32.3%</td><td>31.3%</td><td>51.5%</td><td>−0.216</td><td>0.332</td></tr><tr><th><i>nad1</i></th><td>(−)</td><td>31.7%</td><td>22.2%</td><td>27.6%</td><td>18.6%</td><td>50.3%</td><td><b>0.260</b></td><td>0.108</td></tr><tr><th><i>NCR1</i></th><td></td><td>28.9%</td><td>27.5%</td><td>19.7%</td><td>23.9%</td><td>52.8%</td><td>0.095</td><td>−0.165</td></tr><tr><th><i>NCR2</i></th><td></td><td>27.0%</td><td>22.2%</td><td>18.1%</td><td>32.7%</td><td>59.7%</td><td>−0.095</td><td>−0.102</td></tr><tr><th><i>cob</i></th><td>(−)</td><td>36.0%</td><td>12.0%</td><td>23.5%</td><td>28.5%</td><td>64.5%</td><td><b>0.116</b></td><td>0.324</td></tr><tr><th><i>nad5</i></th><td>(+)</td><td>28.5%</td><td>10.5%</td><td>21.7%</td><td>39.3%</td><td>67.8%</td><td>−0.159</td><td>0.348</td></tr><tr><th><i>nad4</i></th><td>(−)</td><td>38.4%</td><td>11.9%</td><td>22.8%</td><td>26.9%</td><td>65.3%</td><td><b>0.176</b></td><td>0.314</td></tr><tr><th><i>nad4L</i></th><td>(−)</td><td>41.9%</td><td>12.2%</td><td>17.6%</td><td>28.3%</td><td>70.2%</td><td><b>0.194</b></td><td>0.181</td></tr><tr><th><i>nad6</i></th><td>(+)</td><td>25.7%</td><td>10.5%</td><td>17.8%</td><td>46.1%</td><td>71.8%</td><td>−0.284</td><td>0.258</td></tr><tr><th><i>NCR3</i></th><td></td><td>36.8%</td><td>9.8%</td><td>19.1%</td><td>34.3%</td><td>71.1%</td><td>0.035</td><td>0.322</td></tr><tr><th><i>NCR4</i></th><td></td><td>35.5%</td><td>13.0%</td><td>15.2%</td><td>36.2%</td><td>71.7%</td><td>−0.010</td><td>0.078</td></tr><tr><th><i>nad2</i></th><td>(+)</td><td>28.9%</td><td>12.4%</td><td>22.6%</td><td>36.1%</td><td>65.0%</td><td>−0.111</td><td>0.291</td></tr></tbody></table>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.