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BOLD release 5 April 2024, curated with pipeline commit d7f034f1e14f15daed708bb3e0e8ddf1b50e0249
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FIGURE Phylogenetic relationships of the Coelastrella genus inferred from the 18S-ITS1-5.8S-ITS2 region. The Neighbor-Joining (NJ), Maximum Likelihood (ML) bootstrap values and Bayesian posterior probabilities (PP) are presented at the nodes (NJ/ML/PP). Only values above 75 are shown. Strains provided in this study are indicated in bold font. Authentic strains marked with asterisks. The scale bar represents the number of substitutions per site. The GenBank accession numbers of Coelastrella can be found in the Table 3. in Morphological and phylogenetic relations of members of the genus Coelastrella (Scenedesmaceae, Chlorophyta) from the Ural and Khentii Mountains (Russia, Mongolia)
FIGURE Phylogenetic relationships of the Coelastrella genus inferred from the 18S-ITS1-5.8S-ITS2 region. The Neighbor-Joining (NJ), Maximum Likelihood (ML) bootstrap values and Bayesian posterior probabilities (PP) are presented at the nodes (NJ/ML/PP). Only values above 75 are shown. Strains provided in this study are indicated in bold font. Authentic strains marked with asterisks. The scale bar represents the number of substitutions per site. The GenBank accession numbers of Coelastrella can be found in the Table 3.
FIGURE. Variable positions in the ITS2 secondary structure of some Coelastrella sensu lato species. The ITS2 model of Coelastrella striolata strain CAUP H 3602 (JX513881) was used to map sequence differences. Variable positions of analyzed strains (GenBank numbers can be found in Table 3, 4 are given next to the main structure and are marked in bold. Hemi- Compensatory Base Changes in conservative regions are circled and Compensatory Base Change is contoured. Sequences of strains with GenBank numbers JX513879 (C. aeroterrestrica), JX513882 (C. terrestris), JX513884 (C. rubescens), MH176120 (C. rubescens var. oocystiformis), JX513880 (C. multistriata), JX513887 (C. oocystiformis) were used as representatives of Coelastrella species. The strains analyzed in this study are underlined. in Morphological and phylogenetic relations of members of the genus Coelastrella (Scenedesmaceae, Chlorophyta) from the Ural and Khentii Mountains (Russia, Mongolia)
FIGURE. Variable positions in the ITS2 secondary structure of some Coelastrella sensu lato species. The ITS2 model of Coelastrella striolata strain CAUP H 3602 (JX513881) was used to map sequence differences. Variable positions of analyzed strains (GenBank numbers can be found in Table 3, 4 are given next to the main structure and are marked in bold. Hemi- Compensatory Base Changes in conservative regions are circled and Compensatory Base Change is contoured. Sequences of strains with GenBank numbers JX513879 (C. aeroterrestrica), JX513882 (C. terrestris), JX513884 (C. rubescens), MH176120 (C. rubescens var. oocystiformis), JX513880 (C. multistriata), JX513887 (C. oocystiformis) were used as representatives of Coelastrella species. The strains analyzed in this study are underlined.
NanoClass-compatible BOLD CO1 databases
<p>BOLD CO1 databases reformatted to use in NanoClass (https://github.com/ejongepier/NanoClass; version 0.3.0-beta or higher) and QIIME2. Three separate databases are included for use in combination with primers mtD, LCO-HCO and CI. Databases include reference sequences and reference taxonomies for the use in NanoClass, as well as pre-trained classifiers for use in QIIME2. See usage instructions below.</p> <p>For questions, please contact e.jongepier@uva.nl.</p> <p>==========================================<br> WARNING<br> ==========================================</p> <p>Please note this version of a custom BOLD CO1 db comes with absolutely no warranties.</p> <p>When using this db in NanoClass, mind that it has only been tested with methods: ["megablast","minimap","spingo"]<br> NanoClass cannot be run in combination with these BOLD CO1 databases using methods ["mothur","centrifuge","kraken"].<br> Compatibility with ["blast","dcmegablast","qiime","rdp"] is untested.<br> Just remove the tools you want to skip from the NanoClass/config.yaml (see also the NanoClass documentation here: https://ejongepier.github.io/NanoClass/)</p> <p>Never use this data base in combination with the NanoClass snakemake -F parameter or this BOLD CO1 database will be overwriten by the default 16S SILVA database.</p> <p>==========================================<br> DESCRIPTION<br> ==========================================</p> <p>BOLD CO1 database (last) downloaded on 20210420 and reformatted for use in QIIME2 and NanoClass.<br> To clean-up BOLD CO1 db these steps were taken (step 7 to 11 were repeated for each of the 3 primers):<br> - remove identical duplicates [3597874]<br> - drop seqs with non-IUPAC characters [3597839]<br> - remove leading and trailing ambiguous bases [3597839]<br> - remove low quality reads<br> - remove reads with homopolymer runs<br> - filter by length<br> - extract fragments between primer sequences [mtD:112450; CI:121391; LCO-HCO:65307]<br> - dereplicate / cluster [mtD:55075; CI:46470; LCO-HCO:24835]<br> - remove uninformative taxonomic labels [mtD:55073; CI:46466; LCO-HCO:24832]<br> - reformat db for use in NanoClass<br> - train classifier based on fragments</p> <p> </p> <p>==========================================<br> HOW TO USE THESE DBS<br> ==========================================</p> <p>Use in NanoClass:</p> <p>Unzip the database and copy the reference taxonomy and (unzipped) reference sequences to the NanoClass/db/common directory, like so:</p> <p>$ cp mtD/bold-v20210421-taxonomy-mtD.tsv /path/to/NanoClass/db/common/ref-taxonomy.txt<br> $ gzip -d -c mtD/bold-v20210421-frags-mtD.fa.gz > /path/to/NanoClass/db/common/ref-seqs.fna</p> <p>Something similar can be done for the other two primers (CI or LCO-HCO). Only these three primers are supported at this point.</p> <p>Next, create an (empty) ref-seqs.aln file just to prevent NanoClass from automatically downloading the default 16S SILVA database, which would overwrite the BOLD db you just copied into NanoClass/db/common.</p> <p>$ touch /path/to/NanoClass/db/common/ref-seqs.aln</p> <p>Finally, you need to make a change to the NanoClass/Snakefile (i.e change first line into the second).</p> <p>optrules.extend(["plots/precision.pdf"] if len(config["methods"]) > 2 else [])<br> optrules.extend(["plots/precision.pdf"] if len(config["methods"]) > 200 else [])</p> <p>This will disable the computation of precision plots by NanoClass as this is not supported in combination with the custom BOLD CO1 databases.</p> <p>Also mind that you need to change the nanofilt minlen and maxlen in the NanoClass/config.yaml to capture the appropriate fragment length for your primer. For the mtD primer I used minlen 600 and maxlen 900 for testing.</p> <p><br> Use in QIIME2:</p> <p>You can use the trained classifier directly in QIIME2, like so:</p> <p>$ qiime feature-classifier classify-sklearn \<br> --i-classifier mtD/bold-v20210421-classifier-mtD.qza \<br> --i-reads <your-reprseqs>.qza \<br> --o-classification <your-classification>.qza \<br> --verbose</p> <p>Something similar can be done for the other two primers (CI or LCO-HCO). Only these three primers are supported at this point.<br> The classifiers have only been tested with with the sklearn algorithm.<br> </p>
FIGURE. Phylogenetic tree based on RAxML analyses of a combined LSU, ITS and SSU dataset. Bootstrap support values for ML and MP equal to or greater than 75% and PP value greater than 0.95 are in thickened. Ex-type isolates are in bold, and new taxa are indicated in red. The tree is rooted with Atractospora aquatica (S-1297) and A. aquatica (MFLU 18–2322). in Conlarium sichuanense sp. nov., on Ficus virens from Sichuan Province, China
FIGURE. Phylogenetic tree based on RAxML analyses of a combined LSU, ITS and SSU dataset. Bootstrap support values for ML and MP equal to or greater than 75% and PP value greater than 0.95 are in thickened. Ex-type isolates are in bold, and new taxa are indicated in red. The tree is rooted with Atractospora aquatica (S-1297) and A. aquatica (MFLU 18–2322).
FIGURE. Phylogenetic analysis of Chrysosporium spp. based on ITS sequences. Statistical support values (≥50 %) are shown at nodes, and presented as ML bootstrap support/Bayesian posterior probabilities. Names in black bold are the strains isolated in this study, the coloured names are the new species. in Morphological and phylogenetic characterisations reveal nine new species of Chrysosporium (Onygenaceae, Onygenales) in China
FIGURE. Phylogenetic analysis of Chrysosporium spp. based on ITS sequences. Statistical support values (≥50 %) are shown at nodes, and presented as ML bootstrap support/Bayesian posterior probabilities. Names in black bold are the strains isolated in this study, the coloured names are the new species.
FIGURE. Phylogenetic tree derived from Bayesian analysis, based on nrLSU data. Posterior probability (PP> 0.95) values from the Bayesian analysis are added at the nodes. The scale bar represents the number of nucleotide changes per site. (T) indicates the type specimen for this species. The new species are in bold. in Four new species of Entoloma (Entolomataceae, Agaricomycetes) subgenera Cyanula and Claudopus from Vietnam and their phylogenetic position
FIGURE. Phylogenetic tree derived from Bayesian analysis, based on nrLSU data. Posterior probability (PP> 0.95) values from the Bayesian analysis are added at the nodes. The scale bar represents the number of nucleotide changes per site. (T) indicates the type specimen for this species. The new species are in bold.
FIGURE. Multilocus phylogenetic tree inferred from Bayesian analysis based on the combined TEF1-α and ACT sequences. Bayesian posterior probabilities are indicated next to the nodes. The tree was rooted with Cladosporium herbarum CBS 121621. The species in this study are indicated in bold. Types of species are indicated after the culture collection number (T = ex-type, ex-epitype, ex-neotype, or reference strain). in Six new species of Cladosporium associated with decayed leaves of native bamboo (Bambusoideae) in a fragment of Brazilian Atlantic Forest
FIGURE. Multilocus phylogenetic tree inferred from Bayesian analysis based on the combined TEF1-α and ACT sequences. Bayesian posterior probabilities are indicated next to the nodes. The tree was rooted with Cladosporium herbarum CBS 121621. The species in this study are indicated in bold. Types of species are indicated after the culture collection number (T = ex-type, ex-epitype, ex-neotype, or reference strain).
FIGURE. (Continued) Multilocus phylogenetic tree inferred from Bayesian analysis based on the combined TEF1-α and ACT sequences. Bayesian posterior probabilities are indicated next to the nodes. The tree was rooted with Cladosporium herbarum CBS 121621. The species in this study are indicated in bold. Types of species are indicated after the culture collection number (T = ex-type, ex-epitype, exneotype, or reference strain). in Six new species of Cladosporium associated with decayed leaves of native bamboo (Bambusoideae) in a fragment of Brazilian Atlantic Forest
FIGURE. (Continued) Multilocus phylogenetic tree inferred from Bayesian analysis based on the combined TEF1-α and ACT sequences. Bayesian posterior probabilities are indicated next to the nodes. The tree was rooted with Cladosporium herbarum CBS 121621. The species in this study are indicated in bold. Types of species are indicated after the culture collection number (T = ex-type, ex-epitype, exneotype, or reference strain).
Supplementary material 1 from: Macher J, Macher T, Leese F (2017) Combining NCBI and BOLD databases for OTU assignment in metabarcoding and metagenomic datasets: The BOLD_NCBI _Merger. Metabarcoding and Metagenomics 1: e22262. https://doi.org/10.3897/mbmg.1.22262
The supplementary material contains the BOLD_NCBI_Merger script, the needed folder structure and the tutorial explaining how to use the script
BOLD release 5 April 2024, curated with pipeline commit aeda07ed466cf326bfc2cd6f7897f9f413480ac0
Open the record for dataset details and reuse information.
BOLD release 5 April 2024, curated with pipeline commit 3c74c5e91daa2ddccce41d38881edc2e242e9c81
Open the record for dataset details and reuse information.
BOLD release 5 April 2024, barcodes ranked, taxa BAGS graded
Open the record for dataset details and reuse information.
APPENDIX. List of sequenced specimens of Triphosa, with identification, Sampling sites collecting data, Accession numbers, and process ID in BOLD database. Data taken from BOLD and generated by Axel Hausmann (1); Bernd Müller (2); Dirk Stadie (3); Iva Mihoci 4); Marco Infusino, Stefano Scalercio (5); Norbert Poell (6); Wanke et al. (7). in An integrative taxonomic revision of the genus Triphosa Stephens, 1829 (Geometridae: Larentiinae) in the Middle East and Central Asia, with description of two new species
APPENDIX. List of sequenced specimens of Triphosa, with identification, Sampling sites collecting data, Accession numbers, and process ID in BOLD database. Data taken from BOLD and generated by Axel Hausmann (1); Bernd Müller (2); Dirk Stadie (3); Iva Mihoci 4); Marco Infusino, Stefano Scalercio (5); Norbert Poell (6); Wanke et al. (7).
Metrics: BOLDS data coverage
Includes species-level taxa.
intraspecific the to correspond. outgroups bold: grey in in Values; retzii. ) pb Microphis 605 ( : alignment red in; . I nov . subunit sp oxydase arrakisae c Microphis cytochrome: blue the in; on torrentius based) Microphis p-distances: green uncorrected in; (nicoleae matrix distance Microphis : Pairwise yellow In. . 2 divergence TABLE in A new freshwater pipefish species (Syngnathidae: Microphis) from the Sunda shelf islands, Indonesia
intraspecific the to correspond. outgroups bold: grey in in Values; retzii. ) pb Microphis 605 ( : alignment red in; . I nov . subunit sp oxydase arrakisae c Microphis cytochrome: blue the in; on torrentius based) Microphis p-distances: green uncorrected in; (nicoleae matrix distance Microphis : Pairwise yellow In. . 2 divergence TABLE
Data from: Size doesn't matter, sex does: a test for boldness in sister species of Brachyrhaphis fishes
The effect of divergent natural selection on the evolution of behavioral traits has long been a focus of behavioral ecologists. Predation, due to its ubiquity in nature and strength as a selective agent, has been considered an important environmental driver of behavior. Predation is often confounded with other environmental factors that could also play a role in behavioral evolution. For example, environments that contain predators are often more ecologically complex and "risky" (i.e., exposed and dangerous). Previous work shows that individuals from risky environments are often more bold, active, and explorative than those from low-risk environments. To date, most comparative studies of environmentally driven behavioral divergence are limited to comparisons among populations within species that occur in divergent selective environments but neglect comparisons between species following speciation. This limits our understanding of how behavior evolves post-speciation. The Central American live-bearing fish genus Brachyrhaphis provides an ideal system for examining the relationship between selective environments and behavior, within and between species. Here, we test for differences in boldness between sister species B. roseni and B. terrabensis that occur in streams with and without piscivorous predators, respectively. We found that species do differ in boldness, with species that occur with predators being bolder than those that do not. Within each species, we found that sexes differed in boldness, with males being bolder than females. We also tested for a relationship between size (a surrogate for metabolic rate) and boldness, but found no size effects. Therefore, sex, not size, affects boldness. These results are consistent with the hypothesis that complex and risky environments favor individuals with more bold behavioral traits, but they are not consistent with the hypothesis that size (and therefore metabolic rate) drives divergence in boldness. Finally, our results provide evidence that behavioral trait divergence continues even after speciation is complete.
Linking behavioural thermoregulation, boldness and individual state in male Carpetan rock lizards
<p>Mechanisms affecting consistent inter-individual behavioural variation (i.e. animal personality) are of wide scientific interest. In poikilotherms, ambient temperature is one of the most important environmental factors with a direct link to a variety of fitness-related traits. Recent empirical evidence suggests that individual differences in boldness are linked to behavioural thermoregulation strategy in heliothermic species, as individuals are regularly exposed to predators during basking. Here, we tested for links between behavioural thermoregulation strategy, boldness and individual state in adult males of the high mountain Carpetan rock lizard (<i>Iberolacerta cyreni</i>). Principal Component Analysis revealed the following latent links in our data: (i) a positive relationship of activity with relative limb length and colour brightness (PC1, 23% variation explained), (ii) a negative relationship of thermoregulatory precision with parasite load and risk-taking (PC2, 20.98% variation explained) and (iii) a negative relationship between preferred body temperature and relative limb length (PC3, 19.23% variation explained). We conclude that differences in boldness and behavioural thermoregulatory strategy could be explained by both stable and labile state variables. The moderate link between behavioural thermoregulatory strategy and risk-taking personality in our system is plausibly the result of differences in reproductive state of individuals or variation in ecological conditions during the breeding season.</p>
Neurally Relevant BOLD Response Delay: Intermediary Dataset
<p>BOLD fMRI timeseries from V1 voxels, extracted from preprocessed BOLD volume timeseries.</p> <p>Accompanying a scientific article to be submitted to Neuroimage.</p> <p>Code will follow.</p>
FIGURE. RAxML tree based on a combined dataset of partial LSU and ITS sequence analyses. Bootstrap support values for ML equal to or greater than 60 %, Bayesian posterior probabilities (BYPP) equal to or greater than 0.95 are shown as ML/ BYPP above the nodes. New isolates are in red bold. The tree is rooted to Conioscypha lignicola and Conioschypha minutispora (FMR11245) and Conioscyphascus varius. The scale bar represents the expected number of nucleotide substitutions per site. in Yunnan-Guizhou Plateau: a mycological hotspot
FIGURE. RAxML tree based on a combined dataset of partial LSU and ITS sequence analyses. Bootstrap support values for ML equal to or greater than 60 %, Bayesian posterior probabilities (BYPP) equal to or greater than 0.95 are shown as ML/ BYPP above the nodes. New isolates are in red bold. The tree is rooted to Conioscypha lignicola and Conioschypha minutispora (FMR11245) and Conioscyphascus varius. The scale bar represents the expected number of nucleotide substitutions per site.
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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.