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FIGURE 6 in Mitochondrial genome of Abraxas suspecta (Lepidoptera: Geometridae) and comparative analysis with other Lepidopterans
FIGURE 6. Alignment of overlapping region between atp8 and atp6 across Lepidoptera and other insects. The numbers on the right refer to intergenic nucleotides.
FIGURE 7 in Mitochondrial genome of Abraxas suspecta (Lepidoptera: Geometridae) and comparative analysis with other Lepidopterans
FIGURE 7. (A) Alignment of the intergenic spacer region between trnS2 (UCN) and nad1 of several Lepidopteran insects. The shaded 'ATACTAA' motif is conserved across the Lepidoptera order. (B) Features present in the A+T-rich region of A. suspecta. The sequence is shown in the reverse strand. The ATATG motif is shaded. The poly-T stretch is underlined while the poly-A stretch is double underlined. The single microsatellite T/A repeats sequence are indicated by dotted underlining.
FIGURE 4 in Mitochondrial genome of Abraxas suspecta (Lepidoptera: Geometridae) and comparative analysis with other Lepidopterans
FIGURE 4. The Relative Synonymous Codon Usage (RSCU) of the mitochondrial genome of five superfamilies in the Lepidoptera. Codon families are plotted on the X axis. Codons indicated above the bar are not present in the mitogenome.
FIGURE 2 in Mitochondrial genome of Abraxas suspecta (Lepidoptera: Geometridae) and comparative analysis with other Lepidopterans
FIGURE 2. Comparison of codon usage within the mitochondrial genome of members of the Lepidoptera. Lowercase letters (a, b, c, d and e) above species name represent the superfamily to which the species belongs (a: Geometroidea, b: Bombycoidea, c: Noctuoidea, d: Tortricoidea, e Hepialoidea:).
FIGURE 1 in Mitochondrial genome of Abraxas suspecta (Lepidoptera: Geometridae) and comparative analysis with other Lepidopterans
FIGURE 1. Map of the mitogenome of A. suspecta. The tRNA genes are labeled according to the IUPAC-IUB single-letter amino acids: cox1, cox2 and cox3 refer to the cytochrome c oxidase subunits; cob refers to cytochrome b; nad1-nad6 refer to NADH dehydrogenase components; rrnL and rrnS refer to ribosomal RNAs.
Pissodes strobi v1, White pine weevil - genome resources and analysis
<p>BTL lab at the GSC, Vancouver Canada</p><p>Curated and released by K.K. Gagalova</p><p>Please cite "<strong>The genome of the forest insect pest </strong><i><strong>Pissodes strobi</strong></i><strong> reveals genome expansion and evidence of a </strong><i><strong>Wolbachia</strong></i><strong> endosymbiont</strong>" Gagalova & Whitehill, et al., 2022 <a href="https://doi.org/10.1093/g3journal/jkac038">https://doi.org/10.1093/g3journal/jkac038</a></p><ol><li>wpw resources publication - genomics and annotation resources used in the paper</li><li>Phylogeny beetles - raw data for Figure 1</li><li>Repeats analysis - raw data for Figure 2</li><li>Repeat explorer comparative - RepeatExplorer analysis as in "<a href="https://open.library.ubc.ca/soa/cIRcle/collections/ubctheses/24/items/1.0412903">Annotation of complex genomes for comparative genomics</a>"</li><li>Phylogeny Wolbachia - raw data for Figure 3</li><li>Genome annotation - raw data and step-by-step annotations for protein coding genes. Includes structural, funnctional and polishing steps</li><li> Sex determination - analysis of genome coverage for sex determination (hypothesis)</li></ol>
High genomic plasticity and unique features of Xanthomonas translucens pv. graminis revealed through comparative analysis of complete genome sequences
<p><strong>Background:</strong> <i>Xanthomonas</i> <i>translucens</i> pv. <i>graminis</i> (<i>Xtg</i>) is a major bacterial pathogen of economically important forage grasses, causing severe yield losses. So far, genomic resources for this pathovar consisted mostly of draft genome sequences, and only one complete genome sequence was available, preventing comprehensive comparative genomic analyses. Such comparative analyses are essential in understanding the mechanisms involved in the virulence of pathogens and to identify virulence factors involved in pathogenicity.</p><p><strong>Results:</strong> In this study, we produced high-quality, complete genome sequences of four strains of <i>Xtg</i>, complementing the recently obtained complete genome sequence of the <i>Xtg </i>pathotype strain. These genomic resources allowed for a comprehensive comparative analysis, which revealed a high genomic plasticity with many chromosomal rearrangements, although the strains were highly related, with 99.9 to 100% average nucleotide identity. A high number of transposases were exclusively found in <i>Xtg </i>and corresponded to 413 to 457 insertion/excision transposable elements per strain. These mobile genetic elements are likely to be involved in the observed genomic plasticity and may play an important role in the adaptation of <i>Xtg</i>. The pathovar was found to lack a type IV secretion system, and it possessed the smallest set of type III effectors in the species. However, three XopE and XopX family effectors were found, while in the other pathovars of the species two or less were present. Additional genes that were specific to the pathovar were identified, including a unique set of minor pilins of the type IV pilus, 17 TonB-dependent receptors (TBDRs), and 11 degradative enzymes. </p><p><strong>Conclusion:</strong> These results suggest a high adaptability of <i>Xtg</i>, conferred by the abundance of mobile genetic elements, which may have led to the loss of many features. Conserved features that were specific to <i>Xtg </i>were identified, and further investigation will help to determine genes that are essential to pathogenicity and host adaptation of <i>Xtg</i>.</p>
Streptococcus Pneumoniae ST556 Vs Mycoplasma Pneumoniae M129 genome by Blastn analysis
<p><strong>Introduction:</strong> The overlap between Streptococcus pneumoniae and Mycoplasma pneumoniae genome was studied by Blastn analysis. Mycoplasma is an intracellular pathogen causing pneumonia with staccato cough, predominantly handled by T cell immunity. </p><p><strong>Methods:</strong> Through the NCBI website, the overlap of genome sequences of Streptococcus pneumoniae Taiwan (PT 306), and mycoplasma pneumoniae were studied using Blastn. The accession number for the Streptococcus pneumoniae ST556 was CP003357, and the Mycoplasma pneumoniae strain M129 was U00089, respectively. DNA alignments and nucleotide overlapping alignment sequences were studied.</p><p><strong>Results:</strong> There were significant overlaps between the genome sequences of these two organisms by blastn. The overlapping sequences and dot analysis are shown in the files attached in this accompanying document. The overlapping nucleotides involved with high significance (expect values = 0.0).</p><p><strong>Conclusion:</strong> There are overlaps in genome sequences between Streptococcus pneumoniae and mycoplasma genomes. Further studies are required to study the significance of the COVID-19 context and the recent outbreak of mycoplasma in the community across various countries. The overlap can throw some ideas of the use of the potential of streptococcus pneumoniae vaccines for prevention. If not a prevention Streptococcus pneumonia vaccinations can facilitate a deceleration in the spread of mycoplasma infections.</p><p> </p>
Pan-genomic analysis highlights genes associated with agronomic traits and enhances genomics-assisted breeding in alfalfa
Open the record for dataset details and reuse information.
Lemonade Creek, Yellowstone National Park, USA - Microbial Community Analysis - Genome and Transcriptome Data
<p>Genome and Transcriptome data used for analysis of microbial community function over a diurnal cycle in Lemonade Creek, Yellowstone National Park, USA.</p> <p> </p> <p><code>mags.tar</code> Non-redundant metagenome data (genome assemblies, predicted genes, and gene functional annotations).</p> <p> </p> <p>In each directory are the the following files:</p> <p>- <code>*.mRNA.faa</code> protein sequences of protein-coding genes</p> <p>- <code>*.mRNA.fna</code> nucleotide sequences of protein-coding genes</p> <p>- <code>*.mRNA.gff3</code> genomic location of protein-coding genes</p> <p>- <code>*.mRNA.emapper.tsv</code> eggNOG-mapper annotations for the protein-coding genes</p> <p>- <code>*.mRNA.interproscan.gff3</code> InterProScan annotations for the protein-coding genes</p> <p> </p> <p>In the <code>prokaryote</code> directory there are the following files:</p> <p>- <code>*.rRNA.fna</code> nucleotide sequences of rRNA genes</p> <p>- <code>*.rRNA.gff3</code> genomic location of rRNA genes</p> <p>- <code>*.tRNA.fna</code> nucleotide sequences of tRNA genes</p> <p>- <code>*.tRNA.gff3</code> genomic location of tRNA genes</p> <p>- <code>*.other.fna</code> nucleotide sequences of other genes (i.e., CRISPR, ncRNA, oriC, regulatory_region, repeat_region, tmRNA - if any were predicted)</p> <p>- <code>*.other.gff3</code> genomic location of other genes</p> <p> </p> <p><strong>Eukaryotes</strong></p> <p>Five MAGs from other eukaryotes that were assembled from a coassembly of the Soil samples.</p> <p> </p> <p><strong>Prokaryotes</strong></p> <p>The final dereplicated prokaryote MAGs (at 95% ID). The two <code>*stats*</code> files list the taxonomic information (from <code>GTDB-Tk</code>), completeness (from <code>CheckM</code>), and assembly stats (from the <code>stats.sh</code> script from the <code>bbmap</code> package) for each of the prokaryotic MAGs + the number of predicted protein-coding and non-protein-coding genes predicted in each MAG.</p> <p> </p> <p><strong>Viruses</strong></p> <p>The final dereplicated viral MAGs and vOTUs.</p> <p> </p> <p> </p> <p> </p> <p><code>read_mapping.tar</code> Abundance results from metagenome and metatranscriptome read mapping analysis against the non-redundant metagenome data and predicted genes (respectively). This analysis includes the cyanidiophyceae reference nuclear and organelle genomes.</p> <p> </p> <p><strong>mags</strong></p> <p>Results from <code>bbmaps</code> alignment of metagenome reads against a database of non-redudant metagenome MAGs + cyanidiophyceae reference nuclear and organelle genomes. <code>CoverM</code> was used to calculate MAG abundances.</p> <p> </p> <p><strong>genes</strong></p> <p><code>Salmon</code> abundance quantification of PolyA and RiboMinus metatranscriptome reads mapped against the predicted genes in the non-redudant metagenome MAGs + cyanidiophyceae reference nuclear and organelle genomes.</p>
Source data of the MultiSTAAR manuscript "A statistical framework for multi-trait rare variant analysis in large-scale whole-genome sequencing studies".
<p>This dataset serves as the source data for Figures 2-3 and Extended Data Figures 1-2 of the MultiSTAAR manuscript titled "A statistical framework for multi-trait rare variant analysis in large-scale whole-genome sequencing studies". MultiSTAAR is a statistical framework and computationally-scalable analytical pipeline for functionally-informed multi-trait rare variant analysis in large-scale WGS studies.<br><br><strong>Figure 2.</strong> Manhattan plots and Q-Q plots for unconditional gene-centric coding, noncoding and ncRNA multi-trait analysis of low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C) and triglycerids (TG) using TOPMed data (<em>n</em> = 61,838).<br><br><strong>Figure 3.</strong> TOPMed genetic region (2-kb sliding window) unconditional multi-trait analysis results of low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C) and triglycerides (TG) using TOPMed data (<em>n</em> = 61,838).<br><br><strong>Extended Data Figure 1.</strong> Manhattan plots and Q-Q plots for unconditional gene-centric coding, noncoding and genetic region (2-kb sliding window) multi-trait analysis of fasting glucose (FG) and fasting insulin (FI) using TOPMed data (<em>n</em> = 21,731).<br><br><strong>Extended Data Figure 2.</strong> Manhattan plots and Q-Q plots for unconditional gene-centric coding, noncoding and genetic region (2-kb sliding window) multi-trait analysis of C-reactive protein (CRP), interleukin 6 (IL-6), lipoprotein-associated phospholipase A2 (Lp-PLA2) activity, and lipoprotein-associated phospholipase A2 (Lp-PLA2) mass using TOPMed data (<em>n</em> = 9,380).</p>
BactPrep: A user-friendly whole-genome sequencing analysis platform for the detection of homologous recombination and horizontal gene transfer in bacteria - Sample Dataset
<p>This is the dataset used as the sample dataset for the pipeline BactPrep. This dataset consists of 218 <em>Streptococcus pneumoniae</em> PMEN1 WGS assemblies collected from the year 1984 - 2008 from 22 unique countries globally. The raw sequencing data was originally published in the work: Rapid pneumococcal evolution in response to clinical interventions (doi: 10.1371/journal.ppat.1002745) under the bioproject PRJEB2085.</p> <p>We have assembled the raw sequences records with the following steps: 1) raw reads were first quality checked using fastQC 0.11.9; 2) adapters and low quality reads were removed using Trimmomatic 0.39 with parameter “ILLUMINACLIP:TruSeq2-PE.fa:2:30:10:2:keepBothReads LEADING:3 TRAILING:3 SLIDINGWINDOW:4:15 MINLEN:36”; 3) trimmed reads were error-corrected and assembled into WGS assemblies using SPAdes 3.15.0 with parameters "--careful --mismatch-correction”.</p>
GNOSIS: an R Shiny app supporting cancer genomics survival analysis with cBioPortal
<p>GNOSIS Instructional videos.</p>
Genome-wide analysis of natural and restored eastern oyster populations reveals local adaptation and positive impacts of planting frequency and broodstock number
<p>The release of captive-bred plants and animals has increased worldwide to augment declining species. However, insufficient attention has been given to understanding how neutral and adaptive genetic variation are partitioned within and among proximal natural populations, and the patterns and drivers of gene flow over small spatial scales, which can be important for restoration success. A seascape genomics approach was used to investigate population structure, local adaptation, and the extent to which environmental gradients influence genetic variation among natural and restored populations of Chesapeake Bay eastern oysters <i>Crassostrea virginica</i>. We also investigated the impact of hatchery practices on neutral genetic diversity of restored reefs and quantified the broader genetic impacts of large-scale hatchery-based bivalve restoration. Restored reefs showed similar levels of diversity as natural reefs, and striking relationships were found between planting frequency and broodstock numbers and genetic diversity metrics (effective population size and relatedness), suggesting that hatchery practices can have a major impact on diversity. Despite long-term restoration activities, haphazard historical translocations, and high dispersal potential of larvae that could homogenize allele frequencies among populations, moderate neutral population genetic structure was uncovered. Moreover, environmental factors, namely salinity, pH, and temperature, play a major role in the distribution of neutral and adaptive genetic variation. For marine invertebrates in heterogeneous seascapes, collecting broodstock from large populations experiencing similar environments to candidate sites may provide the most appropriate sources for restoration and ensure population resilience in the face of rapid environmental change. This is one of a few studies to demonstrate empirically that hatchery practices have a major impact on the retention of genetic diversity. Overall, these results contribute to the growing body of evidence for fine-scale genetic structure and local adaptation in broadcast-spawning marine species and provide novel information for the management of an important fisheries resource.</p>
Fig. 1 in Genome analysis reveals that Nocardiopsis baichengensis Li et al. 2006 is a later heterotypic synonym of Nocardiopsis halophila Al-Tai and Ruan 1994
Fig. 1. RAxML phylogenomic tree showing the phylogenetic positions of Nocardiopsis halophila DSM 44494T and Nocardiopsis baichengensis YIM 90130 among members of the genus Nocardiopsis. Values are the nodes are bootstrap support (%). The genome of Streptosporangium roseum DSM 43021T (GCA_000024865.1) is used as the outgroup. Bar, 0.01 substitutions per nucleotide position. The genome size of all the Nocardiopsis type strains in the phylogenomic tree is compared using the grey lines against each name.
Single cell Iso-Sequencing enables rapid genome annotation for scRNAseq analysis
<p>Single <span>cell RNA sequencing (scRNAseq) is a powerful technique that continues to expand across various biological applications. However, incomplete 3' UTR annotations can impede single cell analysis resulting in genes that are partially or completely uncounted. Performing scRNAseq with incomplete 3' UTR annotations can hinder the identification of cell identities and gene expression patterns and lead to erroneous biological inferences. We demonstrate that performing single cell isoform sequencing (ScISOr-Seq) in tandem with scRNAseq can rapidly improve 3' UTR annotations. Using threespine stickleback fish (</span><em>Gasterosteus aculeatus</em><span>), we show that gene models resulting from a minimal embryonic ScISOr-Seq dataset retained 26.1% greater scRNAseq reads than gene models from Ensembl alone. Furthermore, pooling our ScISOr-Seq isoforms with a previously published adult bulk Iso-Seq dataset from stickleback, and merging the annotation with the Ensembl gene models, resulted in a marginal improvement (+0.8%) over the ScISOr-Seq only dataset. In addition, isoforms identified by ScISOr-Seq included thousands of new splicing variants. The improved gene models obtained using ScISOr-Seq lead to successful identification of cell types and increased the reads identified of many genes in our scRNAseq stickleback dataset. Our work illuminates ScISOr-Seq as a cost-effective and efficient mechanism to rapidly annotate genomes for scRNAseq.</span></p>
Supplementary Figure 1: The road to FAIR genomes: a gap analysis of NGS data generation and sharing in the Netherlands
<p><em>Supplementary Figure 1: a flow chart conceptualizing the gap analysis. A generic NGS process diagram was created, based on a commonly used care workflow (Step 1). Next, a questionnaire about the inventory of (meta)data standards and retrieval of gaps was drafted (Step 2), which together with the process diagram was used as a basis for the subsequent interviews (Step 3). In parallel with the first three steps, a short literature review was performed (Step 4). The interviews were processed and current gaps were identified, anonymized and classified (Step 5). Finally, the results are shared with the community through presentations, publications and suggestions for next steps for addressing the identified gaps.</em></p>
Data from: Whole genome sequencing and phylogenomic analysis show support for the splitting of genus Pythium
<p>The genus <em>Pythium</em><span> (nom. cons.) sensu lato (s.l.) is composed of many important species of plant pathogens. Early molecular phylogenetic studies suggested paraphyly of </span><em>Pythium</em><span>, which led to a formal proposal by Uzuhashi and colleagues in 2010 to split the genus into </span><em>Pythium</em><span> sensu stricto (s.s.), </span><em>Elongisporangium, Globisporangium, Ovatisporangium</em><span> (= </span><em>Phytopythium</em><span>), and </span><em>Pilasporangium</em><span> using morphological characters and phylogenies of the mt cytochrome </span><em>c</em><span> oxidase subunit 2 (</span><em>cox2</em><span>) and D1–D2 domains of nuc 28S rDNA. Although the split was fairly justified by the delineating morphological characters, there were weaknesses in the molecular analyses, which created reluctance in the scientific community to adopt these new genera for the description of new species. In this study, this issue was addressed using phylogenomics. Whole genomes of 109 strains of </span><em>Pythium</em><span> and close relatives were sequenced, assembled, and annotated. These data were combined with 10 genomes sequenced in previous studies. Phylogenomic analyses were performed with 148 single-copy genes represented in at least 90% of the taxa in the data set. The results showed support for the division of </span><em>Pythium</em><span> s.l. The status of alternative generic names that have been used for species of </span><em>Pythium</em><span> in the past (e.g., </span><em>Artotrogus, Cystosiphon, Eupythium, Nematosporangium, Rheosporangium, Sphaerosporangium</em><span>) was investigated. Based on our molecular analyses and review of the </span><em>Pythium</em><span> generic concepts, we urge the scientific community to adopt the generic names </span><em>Pythium, Elongisporangium, Globisporangium</em><span>, and their concepts as proposed by Uzuhashi and colleagues in 2010 in their work going forward. In order to consolidate the taxonomy of these genera, some of the recently described </span><em>Pythium</em><span> spp. are transferred to </span><em>Elongisporangium</em><span> and </span><em>Globisporangium</em><span>.</span></p>
Data from: Genome-wide analysis reveals demographic and life history patterns associated with habitat modification in land-locked, deep-spawning sockeye salmon (Oncorhynchus nerka)
<p>Human-mediated habitat fragmentation in freshwater ecosystems can negatively impact genetic diversity, demography and life history of native biota, while disrupting the behaviour of species that are dependent on spatial connectivity to complete their life cycles. In the Alouette River system (British Columbia, Canada), dam construction in 1928 impacted passage of anadromous sockeye salmon (<i>Oncorhynchus nerka</i>), with the last records of migrants occurring in the 1930's. Since that time, <i>O. nerka</i> persisted as a resident population in Alouette Reservoir until experimental water releases beginning in 2005 created conditions for migration; two years later, returning migrants were observed for the first time in ~70 years, raising important basic and applied questions regarding life history variation and population structure in this system. Here, we investigated the genetic distinctiveness and population history of Alouette Reservoir <i>O. nerka</i> using genome-wide SNP data (n=7,709 loci) collected for resident and migrant individuals, as well as for neighbouring anadromous sockeye salmon and resident kokanee populations within the Fraser River drainage (n=312 individuals). Bayesian clustering and principal components analyses based on neutral loci revealed five distinct clusters, largely associated with geography, and clearly demonstrated that Alouette Reservoir resident and migrant individuals are genetically distinct from other <i>O. nerka</i> populations in the Fraser River drainage. At a finer-level, there was no clear evidence for differentiation between Alouette Reservoir residents and migrants; although we detected eight high-confidence outlier loci, they all mapped to sex chromosomes suggesting that differences were likely due to uneven sex ratios rather than life history. Taken together, these data suggest that contemporary Alouette Reservoir <i>O. nerka</i> represents a landlocked sockeye salmon population, constituting the first reported instance of deep-water spawning behaviour associated with this life history form. This finding punctuates the need for re-assessment of conservation status and supports on-going fisheries management activities in Alouette Reservoir. </p>
The ancestral origin of the critically endangered Quadricorna sheep as revealed by genome-wide analysis.
<p>These data were used in "The ancestral origin of the critically endangered Quadricorna sheep as revealed by genome-wide analysis" by Senczuk et al.</p> <p>ARSIAL.ped and ARSIAL.map contains genotypes information (64.734 SNPs) of 47 individuals of the Quadricorna breed in Plink ped format.</p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.