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Gene Annotations of 49 Bacillariophyta Genome Assemblies
<div>Contact: katharina.hoff@uni-greifswald.de.</div> <div> </div> <div> <h2>Manuscript</h2> <p>The data hosted here is associated with the preprint <a href="https://doi.org/10.48550/arXiv.2410.05467">https://doi.org/10.48550/arXiv.2410.05467</a></p> </div> <h2>Files</h2> <div>The following gff3-files with structural and functional genome annotation are included in the compressed archive Bacillariophyta_annotations.tar.gz:</div> <div> </div> <div>Asterionella_formosa.gff3<br>Asterionellopsis_glacialis.gff3<br>Bacterosira_constricta.gff3<br>Chaetoceros_muellerii.gff3<br>concatenated_output.gff3<br>Conticribra_guillardii.gff3<br>Conticribra_weissflogii.gff3<br>Craspedostauros_australis.gff3<br>Cyclostephanos_invisitatus.gff3<br>Cyclostephanos_tholiformis.gff3<br>Cyclotella_atomus.gff3<br>Cyclotella_baltica.gff3<br>Cyclotella_choctawhatcheeana.gff3<br>Cyclotella_cryptica.gff3<br>Cylindrotheca_fusiformis.gff3<br>Detonula_confervacea.gff3<br>Discostella_pseudostelligera.gff3<br>Discostella_stelligera.gff3<br>Discostella_stelligeroides.gff3<br>Epithemia_pelagica.gff3<br>Fistulifera_pelliculosa.gff3<br>Fistulifera_solaris.gff3<br>Fragilaria_radians.gff3<br>Fragilariopsis_cylindrus.gff3<br>Licmophora_abbreviata.gff3<br>Mediolabrus_comicus.gff3<br>Nitzschia_palea.gff3<br>Nitzschia_putrida.gff3<br>Porosira_glacialis.gff3<br>Psammoneis_japonica.gff3<br>Pseudo-nitzschia_multiseries.gff3<br>Pseudo-nitzschia_pungens.gff3<br>Skeletonema_costatum.gff3<br>Skeletonema_marinoi.gff3<br>Skeletonema_menzelii.gff3<br>Skeletonema_potamos.gff3<br>Skeletonema_tropicum.gff3<br>Stephanocyclus_meneghinianus.gff3<br>Stephanodiscus_minutulus.gff3<br>Stephanodiscus_triporus.gff3<br>Thalassiosira_allenii.gff3<br>Thalassiosira_delicatula.gff3<br>Thalassiosira_exigua.gff3<br>Thalassiosira_gravida.gff3<br>Thalassiosira_livingstoniorum.gff3<br>Thalassiosira_mediterranea.gff3<br>Thalassiosira_oceanica.gff3<br>Thalassiosira_ordinaria.gff3<br>Thalassiosira_pacifica.gff3<br>Thalassiosira_profunda.gff3</div> <div> </div> <div>To extract the dataset, execute the following command:</div> <div> </div> <div><code>tar -xvf Bacillariophyta_annotations.tar.gz</code></div> <h2>Genome Assemblies</h2> <div>The files in this folder attain to genome assemblies are publicly available at NCBI datasets (https://www.ncbi.nlm.nih.gov/datasets/). We used the following versions:</div> <div> </div> <div>Asterionella formosa GCA_002256025.1</div> <div>Asterionellopsis glacialis GCA_014885115.2</div> <div>Bacterosira constricta GCA_037356235.1</div> <div>Chaetoceros muellerii GCA_019693545.1</div> <div>Conticribra guillardii GCA_036939335.1</div> <div>Conticribra weissflogii GCA_036940025.1</div> <div>Craspedostauros australis GCA_026770025.1</div> <div>Cyclostephanos invisitatus GCA_036939675.1</div> <div>Cyclostephanos tholiformis GCA_036939975.1</div> <div>Cyclotella atomus GCA_036939935.1</div> <div>Cyclotella baltica GCA_036939635.1</div> <div>Cyclotella choctawhatcheeana GCA_036939855.1</div> <div>Cyclotella cryptica GCA_013187285.1</div> <div>Cylindrotheca fusiformis GCA_019693525.1</div> <div>Detonula confervacea GCA_036939415.1</div> <div>Discostella pseudostelligera GCA_036940085.1</div> <div>Discostella stelligera GCA_036939735.1</div> <div>Discostella stelligeroides GCA_036939555.1</div> <div>Epithemia pelagica GCA_946965045.2</div> <div>Fistulifera pelliculosa GCA_026008555.1</div> <div>Fistulifera solaris GCA_030295235.1</div> <div>Fragilaria radians GCA_900642245.1</div> <div>Fragilariopsis cylindrus GCA_900095095.1</div> <div>Licmophora abbreviata GCA_900291995.1</div> <div>Mediolabrus comicus GCA_036940125.1</div> <div>Nitzschia palea GCA_019593585.1</div> <div>Nitzschia putrida GCA_016586335.1</div> <div>Porosira glacialis GCA_036939395.1</div> <div>Psammoneis japonica GCA_008632985.1</div> <div>Pseudo-nitzschia multiseries GCA_037355745.1</div> <div>Pseudo-nitzschia pungens GCA_037355855.1</div> <div>Skeletonema costatum GCA_018806925.1</div> <div>Skeletonema marinoi GCA_030544225.1</div> <div>Skeletonema menzelii GCA_036940005.1</div> <div>Skeletonema potamos GCA_036940105.1</div> <div>Skeletonema tropicum GCA_037178625.1</div> <div>Stephanocyclus meneghinianus GCA_036940045.1</div> <div>Stephanodiscus minutulus GCA_036939435.1</div> <div>Stephanodiscus triporus GCA_036939755.1</div> <div>Thalassiosira allenii GCA_036939655.1</div> <div>Thalassiosira delicatula GCA_036939835.1</div> <div>Thalassiosira exigua GCA_036939895.1</div> <div>Thalassiosira gravida GCA_037356215.1</div> <div>Thalassiosira livingstoniorum GCA_036939595.1</div> <div>Thalassiosira mediterranea GCA_036939795.1</div> <div>Thalassiosira oceanica GCA_019693575.1</div> <div>Thalassiosira ordinaria GCA_036939695.1</div> <div>Thalassiosira pacifica GCA_036939875.1</div> <div>Thalassiosira profunda GCA_036939355.1</div> <p> </p> <h2>Converting to Protein FASTA and Coding Sequences FASTA</h2> <p> </p> <div>To save storage place at Zenodo, we did not upload the protein FASTA and coding sequence FASTA files. They can easily be generated from the genome FASTA file in combination with the respective GFF3 file. To do this, you can use the following commands:</div> <p> </p> <div><code># assume that genome.fa ist you respective genome FASTA file downloaded from NCBI datasets</code></div> <div><code>sed '/^>/ s/ .*//' genome.fasta > genome_short_headers.fasta</code></div> <div><code># assume that file.gff is the respective GFF3 file</code></div> <div><code>getAnnoFastaFromJoingenes.py -g genome_short_headers.fasta -3 file.gff -o nameStem</code></div> <div> </div> <div>This will produce the following files: nameStem.aa (protein FASTA file) and nameStem.codingseq (coding sequence FASTA file).</div> <div> </div> <div>The getAnnoFastaFromJoingenes.py script is available at https://raw.githubusercontent.com/Gaius-Augustus/Augustus/master/scripts/getAnnoFastaFromJoingenes.py . It is part of the AUGUSTUS software package.</div> <h2>Release notes</h2> <p>This release contains a gene set where a results of an OrthoFinder run that did not include genes on contigs that are suspected to be contaminants or horizontal gene transfer candidates were used to filter single exon genes. This means the gene and transcript counts changed compared to the previous release.</p> <h2>License</h2> <div>The genome annotation files are licensed under the Creative Commons Attribution 4.0 International License (CC BY 4.0). To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ or send a letter to Creative Commons, PO Box 1866, Mountain View, CA 94042, USA.</div>
Plant regeneration in leaf culture of Centaurium erythraea Rafn. Part 3: de novo transcriptome assembly and validation of housekeeping genes for studies of in vitro morphogenesis
<p>Six centaury transcriptomes (embryogenic calli, globular somatic embryos, cotyledonary somatic embryos, adventitious buds, leaves and roots of <em>in vitro</em> grown plants) were sequenced and <em>de novo</em> assembled using <a href="https://github.com/trinityrnaseq/trinityrnaseq/wiki">Trinity</a> .</p> <p><a href="https://zenodo.org/api/files/a0546879-e382-4cf9-8185-f188d1a0c5f0/CE_Assembly.tar.gz">CE_Assembly.tar.gz</a> - Centaury referent transcriptome comprises of 160.839 Trinity transcripts grouped in 105.726 Trinity genes.</p> <p><a href="https://zenodo.org/api/files/a0546879-e382-4cf9-8185-f188d1a0c5f0/CE_Assembly_fpkm.tar.gz">CE_Assembly_fpkm.tar.gz</a> - fpkm normalized read counts of the assembled transcripts in the six sequenced centaury tissues.</p> <p><a href="https://zenodo.org/api/files/a0546879-e382-4cf9-8185-f188d1a0c5f0/nt.db_CE_assembly.tar.gz">nt.db_CE_assembly.tar.gz</a> - annotation of assembled transcripts by mapping them against NCBI nucleotide (NT) database using BLASTn . The obtained results were filtered with E-value E ≤ 10<sup>-3</sup>.</p> <p><a href="https://zenodo.org/api/files/a0546879-e382-4cf9-8185-f188d1a0c5f0/swissprot.db_CE_assembly.tar.gz">swissprot.db_CE_assembly.tar.gz</a> - annotation of assembled transcripts by mapping them against NCBI nucleotide (<a href="https://zenodo.org/api/files/a0546879-e382-4cf9-8185-f188d1a0c5f0/swissprot.db_CE_assembly.tar.gz">s</a>wissprot) database using BLASTx . The obtained results were filtered with E-value E ≤ 10<sup>-3</sup>.</p> <p><a href="https://zenodo.org/api/files/a0546879-e382-4cf9-8185-f188d1a0c5f0/pfam30.db_CE_assembly.tar.gz">pfam30.db_CE_assembly.tar.gz</a> - annotation of assembled transcripts by mapping them against Pfam30 domain database using hmmer3. The obtained results were filtered with independent E-value E ≤ 10<sup>-3</sup>.</p>
The North Pacific Eukaryotic Gene Catalog: Raw assemblies from Gradients 1, 2 and 3
<p>The North Pacific Eukaryotic Gene Catalog consolidates eukaryotic metatranscriptome data from three latitudinal transects of the North Pacific transition zone and one cruise in the subtropical gyre. Metatranscriptomes were gathered from latitudinally-resolved surface samples, and diel-resolved temporal studies, with samples taken in triplicate or duplicate and collected on 0.2-100 μm, 0.2-3 μm, and 3 μm-100 or 200 μm size fractions. These metatranscriptome data were <em>de novo</em> assembled into 175 independent assemblies, totalling 182 million clustered nucleotide contigs. Assemblies were annotated by taxonomy and function. This catalog provides assembled environmental contigs, their translated peptide sequences, and their taxonomic and functional annotations with the aim of facilitating continued discoveries about the molecular ecology of microbial eukaryotes in the North Pacific.<br><br>A full description of this data is published in Scientific Data, available here: <a href="https://www.nature.com/articles/s41597-024-04005-5" target="_blank" rel="noopener">The North Pacific Eukaryotic Gene Catalog of metatranscriptome assemblies and annotations</a>. Please cite this publication if your research uses this data:<br><br>Groussman, R. D., Coesel, S. N., Durham, B. P., Schatz, M. J., & Armbrust, E. V. (2024). The North Pacific Eukaryotic Gene Catalog of metatranscriptome assemblies and annotations. <em>Scientific Data</em>, <em>11</em>(1), 1161.</p> <div> <p>This dataset repository is associated with a codebase and documentation repository:<br><a href="https://github.com/armbrustlab/NPac_euk_gene_catalog" target="_blank" rel="noopener">https://github.com/armbrustlab/NPac_euk_gene_catalog</a><br>Please see this code repository for additional data and project updates<br><br>Translated and processed protein sequences and their annotations are available in this repository: <br><a href="../doi/10.5281/zenodo.10472589">https://zenodo.org/doi/10.5281/zenodo.10472589</a><br><br>99% identity clustered nucleotide sequences and kallisto enumerations are available here:<br><a href="../doi/10.5281/zenodo.10570448">https://zenodo.org/doi/10.5281/zenodo.10570448</a></p> </div> <div> <p>File contents: this repository contains five .tar.gz compressed tarballs with raw de novo Trinity assemblies of poly-A selected metatranscriptomes from the Gradients 1 through 3 cruises, and a plain-text file with the custom spike-in mRNA standards (CustomStandardSequences.txt)</p> </div> <div> <p><strong><br>Gradients1.KOK1606.PA.assemblies.tar.gz</strong><br>- Link to <a href="https://github.com/armbrustlab/NPac_euk_gene_catalog/tree/main/projects/G1PA" target="_blank" rel="noopener">G1PA project github page</a><br>- Simons CMAP cruise page and datasets: <a href="https://simonscmap.com/catalog/cruises/KOK1606" target="_blank" rel="noopener">https://simonscmap.com/catalog/cruises/KOK1606</a><br>- Short read processing code: <a href="https://github.com/armbrustlab/NPac_euk_gene_catalog/blob/main/scripts/G1PA.process_short_reads.sh" target="_blank" rel="noopener">G1PA.process_short_reads.sh</a><br>- Trinity assembly code: <a href="https://github.com/armbrustlab/NPac_euk_gene_catalog/blob/main/scripts/G1PA.trinity_assemblies.sh" target="_blank" rel="noopener">G1PA.trinity_assemblies.sh</a></p> </div> <div> <p><strong><br>Gradients2.MGL1704.PA.assemblies.tar.gz</strong><br>- Link to <a href="https://github.com/armbrustlab/NPac_euk_gene_catalog/tree/main/projects/G2PA" target="_blank" rel="noopener">G2PA project github page</a><br>- Simons CMAP cruise page and datasets: <a href="https://simonscmap.com/catalog/cruises/MGL1704" target="_blank" rel="noopener">https://simonscmap.com/catalog/cruises/MGL1704</a><br>- Short read processing code: <a href="https://github.com/armbrustlab/NPac_euk_gene_catalog/blob/main/scripts/G2PA.process_short_reads.sh" target="_blank" rel="noopener">G2PA.process_short_reads.sh</a><br>- Trinity assembly code: <a href="https://github.com/armbrustlab/NPac_euk_gene_catalog/blob/main/scripts/G2PA.trinity_assemblies.sh" target="_blank" rel="noopener">G2PA.trinity_assemblies.sh</a></p> </div> <div> <p><strong><br>Gradients3.KM1906.PA.assemblies.tar.gz</strong><br>- Link go <a href="https://github.com/armbrustlab/NPac_euk_gene_catalog/tree/main/projects/G3PA" target="_blank" rel="noopener">G3PA project github page</a><br>- Simons CMAP cruise page and datasets: <a href="https://simonscmap.com/catalog/cruises/KM1906" target="_blank" rel="noopener">https://simonscmap.com/catalog/cruises/KM1906</a><br>- Short read processing code: <a href="https://github.com/armbrustlab/NPac_euk_gene_catalog/blob/main/scripts/G3PA_UW.process_short_reads.sh" target="_blank" rel="noopener">G3PA_UW.process_short_reads.sh</a><br>- Trinity assembly code: <a href="https://github.com/armbrustlab/NPac_euk_gene_catalog/blob/main/scripts/G3PA_UW.trinity_assemblies.sh" target="_blank" rel="noopener">G3PA_UW.trinity_assemblies.sh</a></p> </div> <div> <p><strong><br>G3_diel.KM1906.PA.assemblies.tar.gz</strong><br>- Link go <a href="https://github.com/armbrustlab/NPac_euk_gene_catalog/tree/main/projects/G3PA" target="_blank" rel="noopener">G3PA project github page</a><br>- Simons CMAP cruise page and datasets: <a href="https://simonscmap.com/catalog/cruises/KM1906" target="_blank" rel="noopener">https://simonscmap.com/catalog/cruises/KM1906</a><br>- Short read processing code: <a href="https://github.com/armbrustlab/NPac_euk_gene_catalog/blob/main/scripts/G3PA_diel.process_short_reads.sh" target="_blank" rel="noopener">G3PA_diel.process_short_reads.sh</a><br>- Trinity assembly code: <a href="https://github.com/armbrustlab/NPac_euk_gene_catalog/blob/main/scripts/G3PA_diel.trinity_assemblies.sh" target="_blank" rel="noopener">G3PA_diel.trinity_assemblies.sh</a></p> </div> <div> <p><strong><br>CustomStandardSequences.txt<br></strong>- Plain-text FASTA file with the spike-in standards used during mRNA extraction and sequencing prep<br>- Link to publication of spike-in standards methods: <a href="https://www.nature.com/articles/s41564-019-0507-5" target="_blank" rel="noopener">https://www.nature.com/articles/s41564-019-0507-5</a></p> </div> <div> <p>The 2015 SCOPE Diel metatranscriptome raw assemblies have been released in a previous Zenodo repository, and are not included again in this deposition. We provide the links to the Diel1 resources here:<br>- Diel1 raw metatranscriptome assembly Zenodo repository: <a href="../records/5009803" target="_blank" rel="noopener">https://zenodo.org/records/5009803</a><br>- Dataset DOI: <a href="https://doi.org/10.5281/zenodo.5009803" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.5009803</a><br>- Associated publication: <a href="https://www.frontiersin.org/articles/10.3389/fmicb.2021.682651/full" target="_blank" rel="noopener">https://www.frontiersin.org/articles/10.3389/fmicb.2021.682651/full</a><br>- Codebase: <a href="https://github.com/armbrustlab/diel_eukaryotes" target="_blank" rel="noopener">https://github.com/armbrustlab/diel_eukaryotes</a><br>- Simons CMAP cruise page and datasets: <a href="https://simonscmap.com/catalog/cruises/KM1513" target="_blank" rel="noopener">https://simonscmap.com/catalog/cruises/KM1513</a><br>- Short read processing code: <a href="https://github.com/armbrustlab/NPac_euk_gene_catalog/blob/main/scripts/D1PA.process_short_reads.sh" target="_blank" rel="noopener">D1PA.process_short_reads.sh</a><br>- Trinity assembly code: <a href="https://github.com/armbrustlab/NPac_euk_gene_catalog/blob/main/scripts/D1PA.trinity_assemblies.sh" target="_blank" rel="noopener">D1PA.trinity_assemblies.sh</a></p> </div> <p><br><br></p>
Predicted genes from the Amblyomma americanum draft genome assembly
<p>Data for pub "Predicted genes from the <em>Amblyomma americanum </em>draft genome assembly."</p> <ul> <li>Amblyomma_americanum_filtered_assembly.fasta: Decontaminated A. americanum genome with bacterial contigs removed</li> <li>Amblyomma_americanum_bacterial_contigs_info.tsv: Information about contigs classified as bacteria that were removed</li> <li>Amblyomma_americanum_annotation_data.tar.gz: Directory of annotation data produced by EvidenceModeler as part of the nf-core/genomeannotator workflow. Includes files in FASTA format (predicted genes and proteins), set of proteins clustered at 99% identity in FASTA format, and annotations in both GFF3 and GTF formats. GTF file produced from the GFF3 file with AGAT.</li> <li>Amblyomma_americanum_transcriptome_assembly_data.tar.gz: Directory of data generated for the transcriptome assembly that was used for gene prediction</li> </ul>
Gene annotation files for Fraxinus excelsior (European ash) genome assembly BATG-0.5
<p>Gene annotation files for <em>Fraxinus excelsior</em> genome assembly v. BATG-0.5, published in Nature (doi:10.1038/nature20786). These files were previously hosted on the Ash Tree Genomes website (http://www.ashgenome.org/transcriptomes) and first made available for download via that site on 2016-02-08.</p> <p>The following annotation files are available:</p> <p>### GFF file of all gene models (all isoforms)<br> Fraxinus_excelsior_38873_TGAC_v2.gff3</p> <p>### FASTA file of all cDNA sequences (all isoforms)<br> Fraxinus_excelsior_38873_TGAC_v2.gff3.cdna.fa</p> <p>### FASTA file of all CDS DNA sequences (all isoforms)<br> Fraxinus_excelsior_38873_TGAC_v2.gff3.cds.fa</p> <p>### FASTA file of all peptide sequences (all isoforms)<br> Fraxinus_excelsior_38873_TGAC_v2.gff3.pep.fa</p> <p>### Functional annotation for each gene model (all isoforms)<br> Fraxinus_excelsior_38873_TGAC_v2.gff3.functional_annotation.tsv</p> <p>### GFF file of all gene models (longest isoform only)<br> Fraxinus_excelsior_38873_TGAC_v2.longestCDStranscript.gff3</p> <p>### FASTA file of all cDNA sequences (longest isoform only)<br> Fraxinus_excelsior_38873_TGAC_v2.longestCDStranscript.gff3.cdna.fa</p> <p>### FASTA file of all CDS DNA sequences (longest isoform only)<br> Fraxinus_excelsior_38873_TGAC_v2.longestCDStranscript.gff3.cds.fa</p> <p>### FASTA file of all peptide sequences (longest isoform only)<br> Fraxinus_excelsior_38873_TGAC_v2.longestCDStranscript.gff3.pep.fa</p> <p>### GFF file for gene models identified as probable transposable element related sequences (excluded from the other files)<br> Fraxinus_excelsior_38873_TGAC_v2.transposable_elements.gff3</p> <p><br> NB: The annotation files include preliminary annotations for genes within the organellar scaffolds (gene models FRAEX38873_v2_000400370-FRAEX38873_v2_000401330), which were not reported in the publication of the BATG0.5 assembly (doi:10.1038/nature20786).</p>
Cladonema radiatum Alr and IgSF genes assembly and domain predictions
<p><span>This dataset is related to the </span><span>submitted paper</span><span> " A single gene determines allorecognition in hydrozoan jellyfish <em>Cladonema radiatum</em> inbred lines ".</span></p> <h1><span>Abstract:</span></h1> <p><strong><span> </span></strong></p> <p><span>Allorecognition—the ability of an organism to discriminate between self and non-self—is crucial to colonial marine animals to avoid invasion by other individuals in the same habitat. The cnidarian hydroid <em>Hydractinia</em> has long been a major research model in studying invertebrate allorecognition, establishing a rich knowledge foundation. In this study, we introduce a new cnidarian model <em>Cladonema radiatum</em> (<em>C. radiatum</em>). <em>C. radiatum</em> is a hydroid jellyfish which also forms polyp colonies interconnected with stolons. Allorecognition responses, fusion or regression of stolons, are observed when stolons encounter each other. By transmission electron microscopy, we observe rapid tissue remodelling contributing to gastrovascular system connection in fusion. Rejection responses are regulated by reconstruction of the chitinous exoskeleton perisarc, and induction of necrotic and autophagic cellular responses at cells in contact with the opponent. Genetic analysis identifies allorecognition genes: six<em> Alr </em>genes located on the putative Allorecognition Complex (ARC) and four immunoglobulin superfamily genes on a separate genome region. C. radiatum allorecognition genes show notable conservation with the <em>Hydractinia Alr</em> family. Remarkedly, stolon encounter assays of inbred lines reveal that genotypes of Alr1 solely determine allorecognition outcomes in <em>C. radiatum</em>.</span></p>
Gene Annotations of 49 Bacillariophyta Genome Assemblies (Individual gff3 files)
<div>Contact: katharina.hoff@uni-greifswald.de.</div> <div> </div> <div> <h2>Manuscript</h2> <p>The data hosted here is associated with the preprint <a href="https://doi.org/10.48550/arXiv.2410.05467">https://doi.org/10.48550/arXiv.2410.05467</a> . It is a copy of the data hostet at <a href="https://zenodo.org/records/13933292">https://zenodo.org/records/13933292</a> , but instead of storing one archive will all gff3 files included, the gff3 files are here hosted, individually. This copy was made upon request from the RDA Working Group "FAIRification of Genomic Annotations – metadata harmonisation at scale".</p> <div> <h2>Files</h2> <div>The following gzip-compressed gff3-files with structural and functional genome annotation are included:</div> <div> </div> <div>Asterionella_formosa.gff3.gz<br>Asterionellopsis_glacialis.gff3.gz<br>Bacterosira_constricta.gff3.gz<br>Chaetoceros_muellerii.gff3.gz<br>concatenated_output.gff3.gz<br>Conticribra_guillardii.gff3.gz<br>Conticribra_weissflogii.gff3.gz<br>Craspedostauros_australis.gff3.gz<br>Cyclostephanos_invisitatus.gff3.gz<br>Cyclostephanos_tholiformis.gff3.gz<br>Cyclotella_atomus.gff3.gz<br>Cyclotella_baltica.gff3.gz<br>Cyclotella_choctawhatcheeana.gff3.gz<br>Cyclotella_cryptica.gff3.gz<br>Cylindrotheca_fusiformis.gff3.gz<br>Detonula_confervacea.gff3.gz<br>Discostella_pseudostelligera.gff3.gz<br>Discostella_stelligera.gff3.gz<br>Discostella_stelligeroides.gff3.gz<br>Epithemia_pelagica.gff3.gz<br>Fistulifera_pelliculosa.gff3.gz<br>Fistulifera_solaris.gff3.gz<br>Fragilaria_radians.gff3.gz<br>Fragilariopsis_cylindrus.gff3.gz<br>Licmophora_abbreviata.gff3.gz<br>Mediolabrus_comicus.gff3.gz<br>Nitzschia_palea.gff3.gz<br>Nitzschia_putrida.gff3.gz<br>Porosira_glacialis.gff3.gz<br>Psammoneis_japonica.gff3.gz<br>Pseudo-nitzschia_multiseries.gff3.gz<br>Pseudo-nitzschia_pungens.gff3.gz<br>Skeletonema_costatum.gff3.gz<br>Skeletonema_marinoi.gff3.gz<br>Skeletonema_menzelii.gff3.gz<br>Skeletonema_potamos.gff3.gz<br>Skeletonema_tropicum.gff3.gz<br>Stephanocyclus_meneghinianus.gff3.gz<br>Stephanodiscus_minutulus.gff3.gz<br>Stephanodiscus_triporus.gff3.gz<br>Thalassiosira_allenii.gff3.gz<br>Thalassiosira_delicatula.gff3.gz<br>Thalassiosira_exigua.gff3.gz<br>Thalassiosira_gravida.gff3.gz<br>Thalassiosira_livingstoniorum.gff3.gz<br>Thalassiosira_mediterranea.gff3.gz<br>Thalassiosira_oceanica.gff3.gz<br>Thalassiosira_ordinaria.gff3.gz<br>Thalassiosira_pacifica.gff3.gz<br>Thalassiosira_profunda.gff3.gz</div> <div> </div> <div>To extract individual files after download execute the following command:</div> <div> </div> <div><code>gunzip *.gff3.gz</code></div> <h2>Genome Assemblies</h2> <p> </p> <div>The files in this folder attain to genome assemblies are publicly available at NCBI datasets (https://www.ncbi.nlm.nih.gov/datasets/). We used the following versions:</div> <p> </p> <div>Asterionella formosa GCA_002256025.1</div> <div>Asterionellopsis glacialis GCA_014885115.2</div> <div>Bacterosira constricta GCA_037356235.1</div> <div>Chaetoceros muellerii GCA_019693545.1</div> <div>Conticribra guillardii GCA_036939335.1</div> <div>Conticribra weissflogii GCA_036940025.1</div> <div>Craspedostauros australis GCA_026770025.1</div> <div>Cyclostephanos invisitatus GCA_036939675.1</div> <div>Cyclostephanos tholiformis GCA_036939975.1</div> <div>Cyclotella atomus GCA_036939935.1</div> <div>Cyclotella baltica GCA_036939635.1</div> <div>Cyclotella choctawhatcheeana GCA_036939855.1</div> <div>Cyclotella cryptica GCA_013187285.1</div> <div>Cylindrotheca fusiformis GCA_019693525.1</div> <div>Detonula confervacea GCA_036939415.1</div> <div>Discostella pseudostelligera GCA_036940085.1</div> <div>Discostella stelligera GCA_036939735.1</div> <div>Discostella stelligeroides GCA_036939555.1</div> <div>Epithemia pelagica GCA_946965045.2</div> <div>Fistulifera pelliculosa GCA_026008555.1</div> <div>Fistulifera solaris GCA_030295235.1</div> <div>Fragilaria radians GCA_900642245.1</div> <div>Fragilariopsis cylindrus GCA_900095095.1</div> <div>Licmophora abbreviata GCA_900291995.1</div> <div>Mediolabrus comicus GCA_036940125.1</div> <div>Nitzschia palea GCA_019593585.1</div> <div>Nitzschia putrida GCA_016586335.1</div> <div>Porosira glacialis GCA_036939395.1</div> <div>Psammoneis japonica GCA_008632985.1</div> <div>Pseudo-nitzschia multiseries GCA_037355745.1</div> <div>Pseudo-nitzschia pungens GCA_037355855.1</div> <div>Skeletonema costatum GCA_018806925.1</div> <div>Skeletonema marinoi GCA_030544225.1</div> <div>Skeletonema menzelii GCA_036940005.1</div> <div>Skeletonema potamos GCA_036940105.1</div> <div>Skeletonema tropicum GCA_037178625.1</div> <div>Stephanocyclus meneghinianus GCA_036940045.1</div> <div>Stephanodiscus minutulus GCA_036939435.1</div> <div>Stephanodiscus triporus GCA_036939755.1</div> <div>Thalassiosira allenii GCA_036939655.1</div> <div>Thalassiosira delicatula GCA_036939835.1</div> <div>Thalassiosira exigua GCA_036939895.1</div> <div>Thalassiosira gravida GCA_037356215.1</div> <div>Thalassiosira livingstoniorum GCA_036939595.1</div> <div>Thalassiosira mediterranea GCA_036939795.1</div> <div>Thalassiosira oceanica GCA_019693575.1</div> <div>Thalassiosira ordinaria GCA_036939695.1</div> <div>Thalassiosira pacifica GCA_036939875.1</div> <div>Thalassiosira profunda GCA_036939355.1</div> <p> </p> <h2>Converting to Protein FASTA and Coding Sequences FASTA</h2> <p> </p> <div>To save storage place at Zenodo, we did not upload the protein FASTA and coding sequence FASTA files. They can easily be generated from the genome FASTA file in combination with the respective GFF3 file. To do this, you can use the following commands:</div> <p> </p> <div><code># assume that genome.fa ist you respective genome FASTA file downloaded from NCBI datasets</code></div> <div><code>sed '/^>/ s/ .*//' genome.fasta > genome_short_headers.fasta</code></div> <div><code># assume that file.gff is the respective GFF3 file</code></div> <div><code>getAnnoFastaFromJoingenes.py -g genome_short_headers.fasta -3 file.gff -o nameStem</code></div> <p> </p> <div>This will produce the following files: nameStem.aa (protein FASTA file) and nameStem.codingseq (coding sequence FASTA file).</div> <p> </p> <div>The getAnnoFastaFromJoingenes.py script is available at https://raw.githubusercontent.com/Gaius-Augustus/Augustus/master/scripts/getAnnoFastaFromJoingenes.py . It is part of the AUGUSTUS software package.</div> <h2>Release notes</h2> <p>The submission and release was made upon request of the RDA working group "FAIRification of Genomic Annotations – metadata harmonisation at scale". The contained data is identical to <a href="https://zenodo.org/records/13933292">https://zenodo.org/records/13933292</a></p> <h2>License</h2> <p> </p> <div>The genome annotation files are licensed under the Creative Commons Attribution 4.0 International License (CC BY 4.0). To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ or send a letter to Creative Commons, PO Box 1866, Mountain View, CA 94042, USA.</div> <p> </p> </div> </div>
Worldwide Fraxinus Genome Assemblies, Annotations, and Gene Families v0.2
<p>The worldwide <em>Fraxinus</em> genome project was conducted to assess the pathogenic resistance of 34 Ash tree species to Ash Dieback and Emerald Ash Borer. The project is led by Dr. Richard Buggs. v0.1 genomes are available at ashgenome.org and on ENA. As part of Josiah Seaman's PhD thesis, he improved the assembly of 13 genomes included here as v0.2. New de novo annotations, gene families, and all associated files are included for future studies and reproducibility. </p> <p>Annotations are done with GeMoMa using F. excelsior as a reference (Keilwagen et al. 2016). Gene families are defined as genes originating from a single copy at the last common ancestor with Solanum. Orthofinder outputs reconciled gene trees, aligned CDS, and gene families (Emms and Kelly 2015; Tekaia 2016). Species tree was calibrated based on fossil evidence using r8s, RAxML across 25,182,399 sites (SpeciesTreeAlignment.fa). More methods details can be found in the full Chapter two of Josiah Seaman's PhD thesis (2021).</p> <p>I'd be happy to talk with you if you'd like any additional information or help visualizing your genomic data. You can find the tools used to browse this data at https://fluentdna.com/ and http://graphgenome.org/ Contact me at josiah@newline.us</p>
Data from "Corset: enabling differential gene expression analysis for de novo assembled transcriptomes"
<p>This dataset contains de novo transcriptome assemblies for three publicly available RNA-seq dataset (SRA055442, SRR453566-SRR453571 and GSE37704 ). For each assembly we also provide a table with the read counts per contig, the output from corset (clusters and counts), and the results from a genome-based analysis. This dataset was used to assess the performance of the corset software. More detail is provided in the paper: Nadia M Davidson and Alicia Oshlack,<strong> </strong>Corset: enabling differential gene expression analysis for de novo assembled transcriptomes, <em>Genome Biology</em> 2014, <strong>15</strong>:410. http://genomebiology.com/2014/15/7/410/abstract</p>
De novo transcriptome assembly and discovery of drought-responsive genes in eastern white spruce (Picea glauca)
<p>Forests face an escalating threat from the increasing frequency of extreme drought events driven by climate change. To address this challenge, it is crucial to understand how widely distributed species of economic or ecological importance may respond to drought stress. Here, we used RNA-sequencing to investigate transcriptome responses at increasing levels of water stress in white spruce (<em>Picea glauca</em> (Moench) Voss), distributed across North America. We began by generating an expanded transcriptome assembly emphasizing short-term drought stress at different developmental stages. We also analyzed differential gene expression at four time points over 22 days in a controlled drought stress experiment involving 2-year-old plants and three genetically unrelated clones. De novo transcriptome assembly and gene expression analysis revealed a total of 33,287 transcripts (18,934 annotated unique genes), with 4,425 unique drought-responsive genes. Many transcripts that had predicted functions associated with photosynthesis, cell wall organization, and water transport were down-regulated under drought conditions, while transcripts linked to abscisic acid response and defense response were up-regulated. Our study highlights a previously uncharacterized effect of drought stress on lipid metabolism genes in conifers and significant changes in the expression of several transcription factors, suggesting a regulatory response potentially linked to drought response or acclimation. Our research represents a fundamental step in unraveling the molecular mechanisms underlying short-term drought responses in white spruce seedlings. In addition, it provides a valuable source of new genetic data that could contribute to genetic selection strategies aimed at enhancing the drought resistance and resilience of white spruce to changing climates.</p>
The North Pacific Eukaryotic Gene Catalog: metatranscriptome assemblies with taxonomy, function and abundance annotations
<p>This data continues with the development of the unprocessed NPEGC Trinity <em>de novo</em> metatranscriptome assemblies, uploaded to this Zenodo repository for raw assemblies: <a href="../records/7332796">The North Pacific Eukaryotic Gene Catalog: Raw assemblies from Gradients 1, 2 and 3</a><br><br>A full description of this data is published in Scientific Data, available here: <a href="https://www.nature.com/articles/s41597-024-04005-5" target="_blank" rel="noopener">The North Pacific Eukaryotic Gene Catalog of metatranscriptome assemblies and annotations</a>. Please cite this publication if your research uses this data:<br><br>Groussman, R. D., Coesel, S. N., Durham, B. P., Schatz, M. J., & Armbrust, E. V. (2024). The North Pacific Eukaryotic Gene Catalog of metatranscriptome assemblies and annotations. <em>Scientific Data</em>, <em>11</em>(1), 1161.</p> <p><br>Excerpts of key processing steps are sampled below with links to the detailed code on the main github code repository: <a href="https://github.com/armbrustlab/NPac_euk_gene_catalog">https://github.com/armbrustlab/NPac_euk_gene_catalog</a></p> <p><br>Processing and annotation of protein-level NPEGC metatranscripts is done in 6 primary steps:<br>1. Six-frame translation into protein sequences<br>2. Frame-selection of protein-coding translation frames<br>3. Clustering of protein sequences at 99% sequence identity<br>4. Taxonomic annotation against MarFERReT v1.1 + MARMICRODB v1.0 multi-kingdom marine reference protein sequence library with DIAMOND<br>5. Functional annotation against Pfam 35.0 protein family HMM profiles using HMMER3<br>6. Functional annotation against KOfam HMM profiles (KEGG release 104.0) using KofamScan v1.3.0<br><br><code># Define local NPEGC base directory here:</code><br><code>NPEGC_DIR="/mnt/nfs/projects/armbrust-metat"</code></p> <p><code># Raw assemblies are located in the /assemblies/raw/ directory</code><br><code># for each of the metatranscriptome projects</code><br><code>PROJECT_LIST="D1PA G1PA G2PA G3PA G3PA_diel"</code></p> <p><code># raw Trinity assemblies:</code><br><code>RAW_ASSEMBLY_DIR="${NPEGC_DIR}/${PROJECT}/assemblies/raw"</code><br><br><strong>Translation</strong><br>We began processing the raw metatranscriptome assemblies by six-frame translation from nucleotide transcripts into three forward and three reverse reading frame translations, using the transeq function in the EMBOSS package. We add a cruise and sample prefix to the sequence IDs to ensure unique identification downstream (ex, `>TRINITY_DN2064353_c0_g1_i1_1` to `>G1PA_S09C1_3um_TRINITY_DN2064353_c0_g1_i1_1` for the S09C1_3um sample in the G1PA assemblies). See <a href="https://github.com/armbrustlab/NPac_euk_gene_catalog/blob/main/scripts/aa_data/NPEGC.6tr_frame_selection_clustering.sh">NPEGC.6tr_frame_selection_clustering.sh</a> for full code description.<br><br>Example of six-frame translation using transeq<br><code>transeq -auto -sformat pearson -frame 6 -sequence 6tr/${PREFIX}.Trinity.fasta -outseq 6tr/${PREFIX}.Trinity.6tr.fasta</code><br><br><strong>Frame selection</strong><br>We use a custom frame-selection python script <a href="https://github.com/armbrustlab/marferret/blob/main/scripts/python/keep_longest_frame.py">keep_longest_frame.py</a> to determine the longest coding length in each open reading frame and retain this sequence (or multiple sequences if there is a tie) for downstream analyses. See <a href="https://github.com/armbrustlab/NPac_euk_gene_catalog/blob/main/scripts/aa_data/NPEGC.6tr_frame_selection_clustering.sh">NPEGC.6tr_frame_selection_clustering.sh</a> for full code description.<br><br><strong>Clustering by sequence identity</strong><br>To reduce sequence redundancy and near-identical sequences, we cluster protein sequences at the 99% sequence identity level and retain the sequence cluster representative in a reduced-size FASTA output file. See <a href="https://github.com/armbrustlab/NPac_euk_gene_catalog/blob/main/scripts/aa_data/NPEGC.6tr_frame_selection_clustering.sh">NPEGC.6tr_frame_selection_clustering.sh</a> for full code description of linclust/mmseqs clustering.<br><br>Sample of linclust clustering script: core mmseqs function<br><code>function NPEGC_linclust {</code><br><code># make an index of the fasta file:</code><br><code>$MMSEQS_DIR/mmseqs createdb $FASTA_PATH/$FASTA_FILE NPac.$STUDY.bf100.db</code><br><code># cluster sequences at $MIN_SEQ_ID</code><br><code>$MMSEQS_DIR/mmseqs linclust NPac.${STUDY}.bf100.db NPac.${STUDY}.clusters.db NPac_tmp --min-seq-id ${MIN_SEQ_ID}</code><br><code># retieve cluster representatives:</code><br><code>$MMSEQS_DIR/mmseqs result2repseq NPac.${STUDY}.bf100.db NPac.${STUDY}.clusters.db NPac.${STUDY}.clusters.rep</code><br><code># generate flat FASTA output with cluster reps</code><br><code>$MMSEQS_DIR/mmseqs result2flat NPac.${STUDY}.bf100.db NPac.${STUDY}.bf100.db NPac.${STUDY}.clusters.rep NPac.${STUDY}.bf100.id99.fasta --use-fasta-header</code><br><code>}</code><br><br>Corresponding files uploaded to this repository: Gzip-compressed FASTA files after translation, frame-selection, and clustering at 99% sequence identity (.bf100.id99.aa.fasta.gz)<br><strong> </strong><em> NPac.G1PA.bf100.id99.aa.fasta.gz</em><br><em> NPac.G2PA.bf100.id99.aa.fasta.gz</em><br><em> NPac.G3PA.bf100.id99.aa.fasta.gz</em><br><em> NPac.G3PA_diel.bf100.id99.aa.fasta.gz</em><br><em> NPac.D1PA.bf100.id99.aa.fasta.gz</em><br><br><strong>MarFERReT + MARMICRODB taxonomic annotation with DIAMOND</strong></p> <p>Taxonomy was inferred for the NPEGC metatranscripts with the DIAMOND fast read alignment software against the <a href="../records/10586950">MarFERReT v1.1 + MARMICRODB v1.0 multi-kingdom marine reference protein sequence library (v1.1)</a>, a combined database of the <a href="https://doi.org/10.1038/s41597-023-02842-4">MarFERReT v1.1 marine microbial eukaryote sequence library</a> and <a href="https://doi.org/10.5281/zenodo.3520509">MARMICRODB v1.0 </a>prokaryote-focused marine genome database. See <a href="https://github.com/armbrustlab/NPac_euk_gene_catalog/blob/main/scripts/aa_data/NPEGC.diamond_taxonomy.log.sh">NPEGC.diamond_taxonomy.log.sh</a> for full description of DIAMOND annotation.</p> <p>Excerpt of core DIAMOND function:<br><code>function NPEGC_diamond {</code><br><code># FASTA filename for $STUDY</code><br><code>FASTER_FASTA="NPac.${STUDY}.bf100.id99.aa.fasta"</code><br><code># Output filename for LCA results in lca.tab file:</code><br><code>LCA_TAB="NPac.${STUDY}.MarFERReT_v1.1_MMDB.lca.tab"</code><br><code>echo "Beginning ${STUDY}"</code><br><code>singularity exec --no-home --bind ${DATA_DIR} \</code><br><code> "${CONTAINER_DIR}/diamond.sif" diamond blastp \</code><br><code> -c 4 --threads $N_THREADS \</code><br><code> --db $MFT_MMDB_DMND_DB -e $EVALUE --top 10 -f 102 \</code><br><code> --memory-limit 110 \</code><br><code> --query ${FASTER_FASTA} -o ${LCA_TAB} >> "${STUDY}.MarFERReT_v1.1_MMDB.log" 2>&1</code><br><code>}</code><br><br>Corresponding files uploaded to this repository: Gzip-compressed diamond lowest common ancestor predictions with NCBI Taxonomy against a combined MarFERReT + MARMICRODB taxonomic library (*.Pfam35.domtblout.tab.gz)<br><em> NPac.G1PA.MarFERReT_v1.1_MMDB.lca.tab.gz</em><br><em> NPac.G2PA.MarFERReT_v1.1_MMDB.lca.tab.gz</em><br><em> NPac.G3PA.MarFERReT_v1.1_MMDB.lca.tab.gz</em><br><em> NPac.G3PA_diel.MarFERReT_v1.1_MMDB.lca.tab.gz</em><br><em> NPac.D1PA.MarFERReT_v1.1_MMDB.lca.tab.gz</em><br><br><strong>Pfam 35.0 functional annotation using HMMER3</strong><br>Clustered protein sequences were annotated against the Pfam 35.0 collection of 19,179 protein family Hidden Markov Models (HMMs) using <a href="http://hmmer.org/">HMMER 3.3 </a> with the <a href="https://academic.oup.com/nar/article/49/D1/D412/5943818">Pfam 35.0 protein family database</a>. Pfam annotation code is documented here: <a href="https://github.com/armbrustlab/NPac_euk_gene_catalog/blob/main/scripts/aa_data/NPEGC.hmmer_function.sh">NPEGC.hmmer_function.sh</a><br><br>Excerpt of core hmmsearch function:<br><br><code>function NPEGC_hmmer {</code><br><code># Define input FASTA</code><br><code>INPUT_FASTA="NPac.${STUDY}.bf100.id99.aa.fasta"</code><br><code># hmmsearch call:</code><br><code>hmmsearch --cut_tc --cpu $NCORES --domtblout $ANNOTATION_DIR/${STUDY}.Pfam35.domtblout.tab $HMM_PROFILE ${INPUT_FASTA}</code><br><code># compress output file:</code><br><code>gzip $ANNOTATION_DIR/${STUDY}.Pfam35.domtblout.tab</code><br><code>}</code><br><br>Corresponding files uploaded to this repository: Gzip-compressed hmmsearch domain table files for Pfam35 queries (*.Pfam35.domtblout.tab.gz)<br><em> G1PA.Pfam35.domtblout.tab.gz</em><br><em> G2PA.Pfam35.domtblout.tab.gz</em><br><em> G3PA.Pfam35.domtblout.tab.gz</em><br><em> G3PA_diel.Pfam35.domtblout.tab.gz</em><br><em> D1PA.Pfam35.domtblout.tab.gz</em><br><br></p> <p><strong>KEGG functional annotation using KofamScan v1.3.0</strong></p> <p>Clustered protein sequences were annotated against the KEGG collection (release 104.0) of 20,819 protein family Hidden Markov Models (HMMs) using <a href="https://github.com/takaram/kofam_scan" target="_blank" rel="noopener">KofamScan </a>and KofamKOALA. Kofam annotation code is documented here: <a href="https://github.com/armbrustlab/NPac_euk_gene_catalog/blob/main/scripts/aa_data/NPEGC.kofamscan_function.sh">NPEGC.kofamscan_function.sh</a></p> <p>Excerpt of core NPEGC_kofam function:</p> <p><code># Core function to perform KofamScan annotation</code><br><code>function NPEGC_kofam {</code><br><code> # Define input FASTA</code><br><code> local INPUT_FASTA="NPac.${STUDY}.bf100.id99.aa.fasta"</code></p> <p><code> # KofamScan call</code><br><code> ${KOFAM_DIR}/kofam_scan-1.3.0/exec_annotation -f detail-tsv -E ${EVALUE} -o ${ANNOTATION_DIR}/NPac.${STUDY}.bf100.id99.aa.tsv ${FASTA_DIR}/${INPUT_FASTA}</code></p> <p><code> # Keep best hit (data is already sorted by KofamScan)</code><br><code> sort -uk1,1 ${ANNOTATION_DIR}/NPac.${STUDY}.bf100.id99.aa.tsv > ${ANNOTATION_DIR}/NPac.${STUDY}.bf100.id99.aa.best.kofam.tsv</code></p> <p><code> # Compress output file</code><br><code> gzip ${ANNOTATION_DIR}/NPac.${STUDY}.bf100.id99.aa.tsv</code></p> <p><code> # Compress best.kofam output file</code><br><code> gzip ${ANNOTATION_DIR}/NPac.${STUDY}.bf100.id99.aa.best.kofam.tsv</code><br><code>}</code></p> <p><br><code># filter hits with a score > 30 in R</code></p> <p>Corresponding files uploaded to this repository: Gzip-compressed KofamScan domain table files for Kofam queries (*.best.Kofam.incT30.csv.gz):<em><br> NPac.G1PA.bf100.id99.aa.best.Kofam.incT30.csv.gz</em><em><br> NPac.G2PA.bf100.id99.aa.best.Kofam.incT30.csv.gz</em><br><em> NPac.G3PA.UW.bf100.id99.aa.best.Kofam.incT30.csv.gz</em><br><em> NPac.G3PA.diel.bf100.id99.aa.best.kofam.incT30.csv.gz</em><br><em> NPac.D1PA.diel.bf100.id99.aa.best.kofam.incT30.csv.gz<br><br></em>The full kofamscan tables with score >30 are deposited here: <a title="The North Pacific Eukaryotic Gene Catalog: KOfam protein function annotations" href="../records/13743267" target="_blank" rel="noopener">https://zenodo.org/records/13743267</a></p>
Chromosome-scale genome assembly and insights into the metabolome and gene regulation of leaf color transition in an important oak species, Quercus dentata
<p><em>Quercus dentata</em> Thunb., a dominant forest tree species in northern China, has significant ecological and ornamental value due to its adaptability and beautiful autumn coloration, with color changes from green to yellow into red resulting from the autumnal shifts in leaf pigmentation. However, the key genes and molecular regulatory mechanisms for leaf color transition remain to be investigated. First, we presented a high-quality chromosome-scale assembly for <em>Q. dentata</em>. This 893.54 Mb sized genome (contig N50=4.21 Mb, scaffold N50=75.55 Mb; 2n=24) harbors 31,584 protein-coding genes. Second, our metabolome analyses uncovered pelargonidin-3-O-glucoside, cyanidin-3-O-arabinoside, and cyanidin-3-O-glucoside as the main pigments involved in leaf color transition. Third, gene co-expression further identified the MYB-bHLH-WD40 (MBW) transcription activation complex as central to anthocyanin biosynthesis regulation. Notably, transcription factor (TF) <em>QdNAC </em>(<em>QD08G038820</em>) was highly co-expressed with this MBW complex and may regulate anthocyanin accumulation and chlorophyll degradation during leaf senescence through direct interaction with another TF, <em>QdMYB </em>(<em>QD01G020890</em>), as revealed by our further protein-protein and DNA-protein interaction assays. Our high-quality genome assembly, metabolome and transcriptome resources further enrich <em>Quercus </em>genomics, and will facilitate upcoming exploration of ornamental values and environmental adaptability in this important genus.</p>
Supplementary data for: Chromosome-level genome assembly and circadian gene repertoire of the Patagonia blennie Eleginops maclovinus
<p>This dataset contains the genome assembly and associated annotation of the Patagonian Blennie (<em>Eleginops maclovinus</em>), the closest extant taxon to the Antarctic notothenioid radiation. In addition to the characterization of the <em>E. maclovinus </em>genome, the dataset includes a description of circadian rhythm orthologs for <em>E. maclovinus</em>, other notothenenioid taxa, and teleost outgroups, as well as a copy of the bioinformatic scripts used for the assembly, annotation, and other downstream analysis.</p>
De novo transcriptome assembly and discovery of drought-responsive genes in eastern white spruce (Picea glauca)
Open the record for dataset details and reuse information.
Supplementary data for: Chromosome-level genome assembly and circadian gene repertoire of the Patagonia blennie Eleginops maclovinus
Open the record for dataset details and reuse information.
Whole genome assembly and gene annotation of a diploid genotype of Brachiaria ruziziensis (syn. Urochloa ruziziensis)
<p>In this work, we have presented a comprehensive analysis of the molecular mechanism linked to aluminium tolerance in <em>Brachiaria</em> species. By assembling and annotating a diploid genotype of <em>B. ruziziensis</em> we have developed the capability for genomic-based studies of desirable phenotypic traits. Using this resource, we have identified three QTLs associated to root architecture and vigour during Al<sup>3+</sup> stress in a hybrid population from a high and low tolerant accession. We have also identified a number of genes and molecular responses that impact on different aspects of signalling, cell-wall composition and active transports as a response to aluminium stress. <em>Brachiaria </em>tolerance appears to build in the same genes than in rice. However, we found that external mechanisms such as sequestration of Al<sup>3+</sup> common in other grasses might be not that important in <em>Brachiaria. </em>Also, contrasting regulation in the same genotype after 8 or 72 hours of Al<sup>3+</sup> stress of numerous genes involved in RNA translation can explain the different levels of tolerance among different Brachiaria species. The newly annotated draft genome represents an important base upon which study other aspects of <em>Brachiaria</em> biology.</p>
Data from: A chromosomal-scale genome assembly of Tectona grandis reveals the importance of tandem gene duplication and enables discovery of genes in natural product biosynthetic pathways
Background: Teak, a member of the Lamiaceae family, produces one of the most expensive hardwoods in the world. High demand coupled with deforestation have caused a decrease in natural teak forests, and future supplies will be reliant on teak plantations. Hence, selection of teak tree varieties for clonal propagation with superior growth performance is of great importance, and access to high-quality genetic and genomic resources can accelerate the selection process by identifying genes underlying desired traits. Findings: To facilitate teak research and variety improvement, we generated a highly contiguous, chromosomal-scale genome assembly using high-coverage PacBio long reads coupled with high-throughput chromatin conformation capture. Of the 18 teak chromosomes, we generated 17 near-complete pseudomolecules with one chromosome present as two chromosome arm scaffolds. Genome annotation yielded 31,168 genes encoding 46,826 gene models, of which, 39,930 and 41,155 had Pfam domain and expression evidence, respectively. We identified 14 clusters of tandem-duplicated terpene synthases (TPSs), genes central to the biosynthesis of terpenes which are involved in plant defense and pollinator attraction. Transcriptome analysis revealed 10 TPSs highly expressed in woody tissues, of which, 8 were in tandem, revealing the importance of resolving tandemly duplicated genes and the quality of the assembly and annotation. We also validated the enzymatic activity of four TPSs to demonstrate the function of key TPSs. Conclusions: In summary, this high-quality chromosomal-scale assembly and functional annotation of the teak genome will facilitate the discovery of candidate genes related to traits critical for sustainable production of teak and for anti-insecticidal natural products.
Files used to develop and test SLAG, Seeded Local Assembly of Genes
<p>This dataset consists of configuration files and results files involved in developing and testing SLAG, an iterative Perl pipeline to construct local assemblies seeded on query sequences. SLAG is intended for situations where a full genome assembly is economically or technically infeasible, and thus it emphasizes methods that can deal with shallow read depth. SLAG and its user-runnable test suite have been deposited at https://github.com/cfcrane/SLAG. This Dryad repository contains files that were used in preparing a manuscript, "SLAG: A Program for Seeded Local Assembly of Genes in Complex Genomes", which has been submitted to Molecular Ecology Resources. The repository is divided into sections for scripts, simulated reads, real reads, and benchmarking against two functionally similar programs, aTRAM2 and SRAssembler.</p>
De novo assembly of 20 chicken genomes reveals the undetectable phenomenon for thousands of core genes on micro-chromosomes and sub-telomeric regions
<p>The gene numbers and evolutionary rates of birds were assumed to be much lower than those of mammals, which is in sharp contrast to the huge species number and morphological diversity of birds. It is therefore necessary to construct a complete avian genome and analyze its evolution. We constructed a chicken pan-genome from 20 <em>de novo</em> assembled genomes with high sequencing depth, and identified 1,335 protein-coding genes and 3,011 long noncoding RNAs not found in GRCg6a. The majority of these novel genes were detected across most individuals of the examined transcriptomes but were seldomly measured in each of the DNA sequencing data regardless of Illumina or PacBio technology. Furthermore, different from previous pan-genome models, most of these novel genes were overrepresented on chromosomal sub-telomeric regions and micro-chromosomes, surrounded by extremely high proportions of tandem repeats, which strongly blocks DNA sequencing. These hidden genes were proved to be shared by all chicken genomes, included many housekeeping genes, and enriched in immune pathways. Comparative genomics revealed the novel genes had three-fold elevated substitution rates than known ones, updating the knowledge about evolutionary rates in birds. Our study provides a framework for constructing a better chicken genome, which will contribute towards the understanding of avian evolution and improvement of poultry breeding.</p>
A complete list of filtered variants and gene lists of frequently and recurrently mutated genes in DLBCL, MCL, T-NHL, and BL, as well as pre-assembled CNV gene list
<p>A complete list of variants which passed filtering described in supplemental methods, that were found in both PDX model sample and patient’s sample from which it was derived (S1A) and variants which were gained (S1B) or lost (S1C) during PDX model derivation. Gene lists for filtration of variants in genes of special interest are included in the table (S1D). Gene list for filtration of CNV changes in genes of special interest is included in the table (S1E). Chr - Chromosome, REF - Reference allele, ALT - Alternative allele, AA change - Amino acid change, Patient AF - Allele frequency in the patient’s sample, Patient Depth – Read depth in patient’s sample, PDX AF- Allele frequency in PDX model sample, PDX Depth - Read depth in PDX sample, DLBCL - Diffuse Large B-cell lymphoma, MCL - Mantle Cell Lymphoma, TCL - T-cell lymphoma, BL – Burkitt Lymphoma, and CNV - Copy Number Variation.</p>
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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.