Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
1,344
datasets available to search
ShareScore release 0.9.0
Dataset results
1,344 results for “ribosome”
Data from: Phylogenetic inferences using nuclear ribosomal ITS and chloroplast sequences provide insights into the biogeographic origins, diversification timescales and trait evolution of Rubus in the Japanese Archipelago
Open the record for dataset details and reuse information.
Ribosomal stalk proteins RPLP1 and RPLP2 promote biogenesis of flaviviral and cellular multi-pass transmembrane proteins
Open the record for dataset details and reuse information.
Data from: The evolutionary dynamics of ribosomal genes, histone H3, and transposable Rex elements in the genome of Atlantic snappers
Open the record for dataset details and reuse information.
The ribosome-inactivating proteins MAP30 and Momordin inhibit SARS-CoV-2
Open the record for dataset details and reuse information.
Ribosome profiling reveals a functional role for autophagy in protein translational control
Open the record for dataset details and reuse information.
Figure 3 from: Maurin KJL (2020) A dated phylogeny of the genus Pennantia (Pennantiaceae) based on whole chloroplast genome and nuclear ribosomal 18S–26S repeat region sequences. PhytoKeys 155: 15-32. https://doi.org/10.3897/phytokeys.155.53460
Figure 3 Undated 18S–26S nuclear DNA repeat region BEAST 2 phylogeny of Pennantia, under the Birth-Death model. The tree was rooted to make P. cunninghamii sister to the other species of Pennantia, in accordance with the chloroplast DNA tree and the ITS tree of Keeling et al. (2004). Node posterior probability is shown next to the corresponding node. The sequences downloaded from GenBank have their accession number in round brackets; the others were generated from the samples used in this study.
Supplementary material 2 from: Maurin KJL (2020) A dated phylogeny of the genus Pennantia (Pennantiaceae) based on whole chloroplast genome and nuclear ribosomal 18S–26S repeat region sequences. PhytoKeys 155: 15-32. https://doi.org/10.3897/phytokeys.155.53460
BEAST2 and RAxML files
Figure 2 from: Maurin KJL (2020) A dated phylogeny of the genus Pennantia (Pennantiaceae) based on whole chloroplast genome and nuclear ribosomal 18S–26S repeat region sequences. PhytoKeys 155: 15-32. https://doi.org/10.3897/phytokeys.155.53460
Figure 2 Dated chloroplast DNA BEAST 2 phylogeny of Pennantia, under the Birth-Death model. Mean node age and 95% HPD (in My) is given in the table embedded in the figure under the corresponding letter code. 95% HPD is also represented by blue bars. All node posterior probabilities are equal to 1 except if indicated otherwise. The calibrated nodes (see text) are indicated by red dots.
Supplementary material 1 from: Maurin KJL (2020) A dated phylogeny of the genus Pennantia (Pennantiaceae) based on whole chloroplast genome and nuclear ribosomal 18S–26S repeat region sequences. PhytoKeys 155: 15-32. https://doi.org/10.3897/phytokeys.155.53460
Figs S1–S5; Tables S1–S3
Figure 1 from: Maurin KJL (2020) A dated phylogeny of the genus Pennantia (Pennantiaceae) based on whole chloroplast genome and nuclear ribosomal 18S–26S repeat region sequences. PhytoKeys 155: 15-32. https://doi.org/10.3897/phytokeys.155.53460
Figure 1 General distribution of the four Pennantia species. TKI = Three Kings Islands. Generated in QGIS 3.0.1 from Google Satellite data obtained through the XYZ Tiles tool (https://mt1.google.com/vt/lyrs=s&x={x}&y={y}&z={z}).
Data from: The effects of model choice and mitigating bias on the ribosomal tree of life
Deep-level relationships within Bacteria, Archaea, and Eukarya as well as the relationships of these three domains to each other require resolution. The ribosomal machinery, universal to all cellular life, represents a protein repertoire resistant to horizontal gene transfer, which provides a largely congruent signal necessary for reconstructing a tree suitable as a backbone for life's reticulate history. Here, we generate a ribosomal tree of life from a robust taxonomic sampling of Bacteria, Archaea, and Eukarya to elucidate deep-level intra-domain and inter-domain relationships. Lack of phylogenetic information and systematic errors caused by inadequate models (that cannot account for substitution rate or compositional heterogeneities) or improper model selection compound conflicting phylogenetic signals from HGT and/or paralogy. Thus, we tested several models of varying sophistication on three different datasets, performed removal of fast-evolving or long-branched Archaea and Eukarya, and employed three different strategies to remove compositional heterogeneity to examine their effects on the topological outcome. Our results support a two-domain topology for the tree of life, where Eukarya emerges from within Archaea as sister to a Korarchaeota/Thaumarchaeota (KT) or Crenarchaeota/KT clade for all models under all or at least one of the strategies employed. Taxonomic manipulation allows single-matrix and certain mixture models to vacillate between two-domain and three-domain phylogenies. We find that models vary in their ability to resolve different areas of the tree of life, which does not necessarily correlate with model complexity. For example, both single-matrix and some mixture models recover monophyletic Crenarchaeota and Euryarchaeota archaeal phyla. In contrast, the most sophisticated model recovers a paraphyletic Euryarchaeota but detects two large clades that comprise the Bacteria, which were recovered separately but never together in the other models. Overall, models recovered consistent topologies despite dataset modifications due to the removal of compositional bias, which reflects either ineffective bias reduction or robust datasets that allow models to overcome reconstruction artifacts. We recommend a comparative approach for evolutionary models to identify model weaknesses as well as consensus relationships.
Data from: Super-resolution ribosome profiling reveals unannotated translation events in Arabidopsis
Deep sequencing of ribosome footprints (ribosome profiling) maps and quantifies mRNA translation. Because ribosomes decode mRNA every 3 nt, the periodic property of ribosome footprints could be used to identify novel translated ORFs. However, due to the limited resolution of existing methods, the 3-nt periodicity is observed mostly in a global analysis, but not in individual transcripts. Here, we report a protocol applied to Arabidopsis that maps over 90% of the footprints to the main reading frame and thus offers super-resolution profiles for individual transcripts to precisely define translated regions. The resulting data not only support many annotated and predicted noncanonical translation events but also uncover small ORFs in annotated noncoding RNAs and pseudogenes. A substantial number of these unannotated ORFs are evolutionarily conserved, and some produce stable proteins. Thus, our study provides a valuable resource for plant genomics and an efficient optimization strategy for ribosome profiling in other organisms.
Data from: Testing hypotheses of chaetognath origins: long branches revealed by 18S ribosomal DNA
Many hypotheses regarding the phylogenetic position of the Chaetognatha (arrow worms) have been proposed; these organisms are problematic primarily because their morphology offers few unambiguous systematic characters that ally them with other taxa. Early researchers proposed a plethora of phylogenetic placements for the Chaetognatha, grouping them with such divergent taxa as acanthocephalans and mollusks, but more traditional hypotheses posit that chaetognaths are, in fact, deuterostomes. Recently, Telford and Holland (1993, Mol. Biol. Evol. 10:660--676) and Wada and Satoh (1994, Proc. Natl. Acad. Sci. USA 91:1801--1804) disputed the deuterostome affinities of chaetognaths based on 18S nuclear ribosomal RNA (rDNA) gene sequence data. By employing published 18S rDNA gene sequence data, I extended these previous analyses by testing specific hypotheses of chaetognath affinities to nematodes, mollusks, acanthocephalans, and deuterostomes. Both parsimony and neighbor-joining analyses supported the monophyly of a chaetognath--nematode clade. Faith's T-PTP test and winning-sites analyses were employed to discriminate among competing hypotheses. The possibility of long-branch attraction accounting for the chaetognath--nematode relationship was explored by analyzing alternative four-taxon trees. An evolutionary scenario for the origin of the chaetognath lineage from a vermiform benthic organism is presented.
Data from: Phylogenetic relationships of Agaric fungi based on nuclear large subunit ribosomal DNA sequences
Phylogenetic relationships of mushrooms and their relatives within the order Agaricales were addressed using nuclear large subunit ribosomal DNA sequences. Approximately 900 bases of the 5' end of the nucleus-encoded large subunit RNA gene (nLSU-rDNA) were sequenced for 154 selected taxa representing most families within the Agaricales. Several phylogenetic methods were used, including weighted and equally weighted parsimony (MP), maximum likelihood (ML), and distance methods (NJ). The starting tree for branch swapping in the ML analyses was the tree with the highest ML score among previously produced MP and NJ trees. A high degree of consensus was observed between phylogenetic estimates obtained through MP and ML. NJ trees differed according to the distance model that was used, however, all NJ trees still supported most of the same terminal groupings as MP and ML trees. NJ trees were always significantly suboptimal when evaluated against the best MP and ML trees, using both parsimony and likelihood tests. Our analyses suggest that weighted parsimony and ML provide the best estimates of Agaricales phylogeny. Similar support was observed between bootstrapping and jackknifing methods for evaluation of tree robustness. Phylogenetic analyses revealed many groups of agaricoid fungi that are supported by moderate to high bootstrap or jackknife levels or are consistent with morphology-based classification schemes. Analyzes also support separate placement of the boletes and russules, which are basal to the main core group of gilled mushrooms (the Agaricineae of Singer). Examples of monophyletic groups include the families Amanitaceae, Coprinaceae (excluding Coprinus comatus and subfamily Panaeolideae), Agaricaceae (excluding the Cystodermateae), and Strophariaceae pro parte (Stropharia, Pholiota, and Hypholoma); the mycorrhizal species of Tricholoma (including Leucopaxillus, also mycorrhizal); Mycena and Resinomycena; Termitomyces, Podabrella, and Lyophyllum; and Pleurotus with Hohenbuehelia. Several nonmonophyletic groups revealed by these data include the families Tricholomataceae, Cortinariaceae, and Hygrophoraceae and the genera Clitocybe, Omphalina, and Marasmius. This study provides a framework for future systematics studies in the Agaricales and suggestions for analyzing large molecular data sets.
Data from: Decrease in ribosomal RNA in Candida albicans induced by serum exposure
Candida albicans is an important polymorphic human pathogen. It can switch from a unicellular yeast form to germinating hypha, which may play a role in making it the successful pathogen it is. This hyphal transformation can be triggered by various extracellular stimuli, the most potent one being serum from any source. We have previously reported that Candida albicans transiently polyadenylates portions of both the large and small subunits of ribosomal RNA, shortly after serum exposure. Northern blots at the same time suggested that serum might induce a decrease in total ribosomal RNA. We have carried out a number of experiments to carefully assess this possibility and now report that serum significantly reduces ribosomal RNA in Candida albicans. Fluorometric measurements, Northern blotting and quantitative RT-PCR, have all confirmed this decrease. Timed experiments show that serum induces this decrease rapidly, as it was seen in as early as five minutes. Cell mass is not decreased as total cellular protein content remains the same and metabolic activity does not appear to slow, as assessed by XTT assay, and by the observation that cells form hyphal structures robustly. Another hyphal inducer, N-acetylglucosamine, also caused RNA decrease, but to a lesser extent. We also observed it in non-germinating yeast, such as Candida glabrata. The reason for this decrease is unknown and overall our data suggests that decrease in rRNA does not play a causal role in hyphal transformation. Rapid and significant decrease in a molecule so central to the yeast's biology is of some importance, and further studies, such as its effect on protein metabolism, will be required to better understand its purpose.
Data from: Delimitation of the Thoracosphaeraceae (Dinophyceae), including the calcareous dinoflagellates, based on large amounts of ribosomal RNA sequence data
The phylogenetic relationships of the Dinophyceae (Alveolata) are not sufficiently resolved at present. The Thoracosphaeraceae (Peridiniales) are the only group of the Alveolata that include members with calcareous coccoid stages; this trait is considered apomorphic. Although the coccoid stage apparently is not calcareous, Bysmatrum has been assigned to the Thoracosphaeraceae based on thecal morphology. We tested the monophyly of the Thoracosphaeraceae using large sets of ribosomal RNA sequence data of the Alveolata including the Dinophyceae. Phylogenetic analyses were performed using Maximum Likelihood and Bayesian approaches. The Thoracosphaeraceae were monophyletic, but included also a number of non-calcareous dinophytes (such as Ensiculifera and Pfiesteria) and even parasites (such as Duboscquodinium and Tintinnophagus). Bysmatrum had an isolated and uncertain phylogenetic position outside the Thoracosphaeraceae. The phylogenetic relationships among calcareous dinophytes appear complex, and the assumption of the single origin of the potential to produce calcareous structures is challenged. The application of concatenated ribosomal RNA sequence data may prove promising for phylogenetic reconstructions of the Dinophyceae in future.
Data from: The Strepsiptera Problem: Phylogeny of the Holometabolous Insect Orders Inferred from 18S and 28S Ribosomal DNA Sequences and Morphology
Phylogenetic relationships among the holometabolous insect orders were inferred from cladistic analysis of nucleotide sequences of 18S ribosomal DNA (rDNA) (85 exemplars) and 28S rDNA (52 exemplars) and morphological characters. Exemplar outgroup taxa were Collembola (1 sequence), Archaeognatha (1), Ephemerida (1), Odonata (2), Plecoptera (2), Blattodea (1), Mantodea (1), Dermaptera (1), Orthoptera (1), Phasmatodea (1), Embioptera (1), Psocoptera (1), Phthiraptera (1), Hemiptera (4), and Thysanoptera (1). Exemplar ingroup taxa were Coleoptera: Archostemata (1), Adephaga (2), and Polyphaga (7); Megaloptera (1); Raphidioptera (1); Neuroptera (sensu stricto ;eq Planipennia): Mantispoidea (2), Hemerobioidea (2), and Myrmeleontoidea (2); Hymenoptera: Symphyta (4) and Apocrita (19); Trichoptera: Hydropsychoidea (1) and Limnephiloidea (2); Lepidoptera: Ditrysia (3); Siphonaptera: Pulicoidea (1) and Ceratophylloidea (2); Mecoptera: Meropeidae (1), Boreidae (1), Panorpidae (1), and Bittacidae (2); Diptera: Nematocera (1), Brachycera (2), and Cyclorrhapha (1); and Strepsiptera: Corioxenidae (1), Myrmecolacidae (1), Elenchidae (1), and Stylopidae (3). We analyzed ~1 kilobase of 18S rDNA, starting 398 nucleotides downstream of the 5' end, and ~400 bp of 28S rDNA in expansion segment D3. Multiple alignment of the 18S and 28S sequences resulted in 1,116 nucleotide positions with 24 insert regions and 398 positions with 14 insert regions, respectively. All Strepsiptera and Neuroptera have large insert regions in 18S and 28S. The secondary structure of 18S insert 23 is composed of long stems that are GC rich in the basal Strepsiptera and AT rich in the more derived Strepsiptera. A matrix of 176 morphological characters was analyzed for holometabolous orders. Incongruence length difference tests indicate that the 28S + morphological data sets are incongruent but that 28S + 18S, 18S + morphology, and 28S + 18S + morphology fail to reject the hypothesis of congruence. Phylogenetic trees were generated by parsimony analysis, and clade robustness was evaluated by branch length, Bremer support, percentage of extra steps required to force paraphyly, and sensitivity analysis using the following parameters: gap weights, morphological character weights, methods of data set combination, removal of key taxa, and alignment region. The following are monophyletic under most or all combinations of parameter values: Holometabola, Polyphaga, Megaloptera + Raphidioptera, Neuroptera, Hymenoptera, Trichoptera, Lepidoptera, Amphiesmenoptera (Trichoptera + Lepidoptera), Siphonaptera, Siphonaptera + Mecoptera, Strepsiptera, Diptera, and Strepsiptera + Diptera (Halteria). Antliophora (Mecoptera + Diptera + Siphonaptera + Strepsiptera), Mecopterida (Antliophora + Amphiesmenoptera), and Hymenoptera + Mecopterida are supported in the majority of total evidence analyses. Mecoptera may be paraphyletic because Boreus is often placed as sister group to the fleas; hence, Siphonaptera may be subordinate within Mecoptera. The 18S sequences for Priacma (Coleoptera: Archostemata), Colpocaccus (Coleoptera: Adephaga), Agulla (Raphidioptera), and Corydalus (Megaloptera) are nearly identical, and Neuropterida are monophyletic only when those two beetle sequences are removed from the analysis. Coleoptera are therefore paraphyletic under almost all combinations of parameter values. Halteria and Amphiesmenoptera have high Bremer support values and long branch lengths. The data do not support placement of Strepsiptera outside of Holometabola nor as sister group to Coleoptera. We reject the notion that the monophyly of Halteria is due to long branch attraction because Strepsiptera and Diptera do not have the longest branches and there is phylogenetic congruence between molecules, across the entire parameter space, and between morphological and molecular data.
Data from: Ribosomal RNA gene repeats associate with the nuclear pore complex for maintenance after DNA damage
The ribosomal RNA genes (rDNA) comprise a highly repetitive gene cluster. The copy number of genes at this locus can readily change and is therefore one of the most unstable regions of the genome. DNA damage in rDNA occurs after binding of the replication fork blocking protein Fob1 in S phase, which triggers unequal sister chromatid recombination. However, the precise mechanisms by which such DNA double-strand breaks (DSBs) are repaired is not well understood. Here, we demonstrate that the conserved protein kinase Tel1 maintains rDNA stability after replication fork arrest. We show that rDNA associates with nuclear pores, which is dependent on DNA damage checkpoint kinases Mec1/Tel1 and replisome component Tof1. These findings suggest that rDNA-nuclear pore association is due to a replication fork block and subsequent DSB. Indeed, quantitative microscopy revealed that rDNA is relocated to the nuclear periphery upon induction of a DSB. Finally, rDNA stability was reduced in strains where this association with the nuclear envelope was prevented, which suggests its importance for avoiding improper recombination repair that could induce repeat instability.
Rapid discovery of high-affinity antibodies via massively parallel sequencing, ribosome display and affinity screening
<p>Deep screening datasets for experiments conducted in Porebski et al., (2023) Rapid discovery of high-affinity antibodies via massively parallel sequencing, ribosome display and affinity screening. <em>Nat. Biol. Eng., doi: 10.1038/s41551-023-01093-3</em>.</p> <p>Datasets are made available under a CC BY-NC-ND 4.0 licence.</p>
Exploring the Roles of Ribosomal Peptides in Prokaryote-Phage Interactions through Deep Learning-Enabled Metagenome Mining
<ol> <li><a href="../api/records/10202404/draft/files/OVD.fa.gz/content">OVD.fa.gz: The Ocean Virus Database containing the identified viral sequences</a></li> </ol> <p><a href="../api/records/8138131/draft/files/OVD_taxonomy.upload.txt/content">2. OVD_taxonomy.upload.txt: The taxonomic information of the OVD.</a></p> <p>3. <a href="../api/records/8138131/draft/files/host_phage_pair_summary.upload.txt/content">host_phage_pair_summary.upload.txt: The phage-host relationships.</a></p> <p>4. <a href="../api/records/8138131/draft/files/RiPP_vpf_host_phage_summary.upload.txt/content">RiPP_vpf_host_phage_summary.upload.txt: The RiPP-involving phage-host interaction network.</a></p> <p>5. virus_db_checkv_quality_summary_upload.tsv: The quality assessment of GOV2 and the identified phages in this study using CheckV.</p>
ScienceDex guides
Understand access before you commit
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.