Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
537
datasets available to search
ShareScore release 0.9.0
Dataset results
537 results for “structural genomics”
Data from: Effects of assortative mate choice on the genomic and morphological structure of a hybrid zone between two bird subspecies
Phenotypic differentiation plays an important role in the formation and maintenance of reproductive barriers. In some cases, variation in a few key aspects of phenotype can promote and maintain divergence; hence the identification of these traits and their associations with patterns of genomic divergence are crucial for understanding the patterns and processes of population differentiation. We studied hybridization between the alba and personata subspecies of the white wagtail (Motacilla alba), and quantified divergence and introgression of multiple morphological traits and 19,437 SNP loci on a 3000 km transect. Our goal was to identify traits that may contribute to reproductive barriers and to assess how variation in these traits corresponds to patterns of genome-wide divergence. Variation in only one trait – head plumage patterning – was consistent with reproductive isolation. Transitions in head plumage were steep and occurred over otherwise morphologically and genetically homogeneous populations, whereas cline centers for other traits and genomic ancestry were displaced over one hundred kilometers from the head cline. Field observational data show that social pairs mated assortatively by head plumage, suggesting that these phenotypes are maintained by divergent mating preferences. In contrast, variation in all other traits and genetic markers could be explained by neutral diffusion, although weak ecological selection cannot be ruled out. Our results emphasize that assortative mating may maintain phenotypic differences independent of other processes shaping genome-wide variation, consistent with other recent findings that raise questions about the relative importance of mate choice, ecological selection and selectively neutral processes for divergent evolution.
Data from: The role of parasite-driven selection in shaping landscape genomic structure in red grouse (Lagopus lagopus scotica)
Landscape genomics promises to provide novel insights into how neutral and adaptive processes shape genome-wide variation within and among populations. However, there has been little emphasis on examining whether individual-based phenotype-genotype relationships derived from approaches such as genome-wide association (GWAS) manifest themselves as a population-level signature of selection in a landscape context. The two may prove irreconcilable as individual-level patterns may become diluted by high levels of gene flow and complex phenotypic or environmental heterogeneity. We illustrate this issue with a case study that examines the role of the highly prevalent gastrointestinal nematode Trichostrongylus tenuis in shaping genomic signatures of selection in red grouse (Lagopus lagopus scotica). Individual-level GWAS involving 384 SNPs has previously identified five SNPs that explain variation in T. tenuis burden. Here, we examine whether these same SNPs display population-level relationships between T. tenuis burden and genetic structure across a small-scale landscape of 21 sites with heterogeneous parasite pressure. Moreover, we identify adaptive SNPs showing signatures of directional selection using FST outlier analysis and relate population- and individual-level patterns of multi-locus neutral and adaptive genetic structure to T. tenuis burden. The five candidate SNPs for parasite-driven selection were neither associated with T. tenuis burden on a population level, nor under directional selection. Similarly, there was no evidence of parasite-driven selection in SNPs identified as FST outliers. We discuss these results in the context of red grouse ecology and highlight the broader consequences for the utility of landscape genomics approaches for identifying signatures of selection.
Data from: The role of selection in driving landscape genomic structure of the waterflea Daphnia magna
The combined analysis of neutral and adaptive genetic variation is crucial to reconstruct the processes driving population genetic structure of natural populations. However, such combined analysis is challenging because of the complex interaction among neutral and selective processes in the landscape. Overcoming this level of complexity requires an unbiased search for the evidence of selection in the genomes of populations sampled from their natural habitats and the identification of demographic processes that lead to present-day populations genetic structure. Ecological model species with a suite of genomic tools and well-understood ecologies are best suited to resolve this complexity and elucidate the role of selective and demographic processes in the landscape genomic structure of natural populations. Here we investigate the water flea Daphnia magna, an emerging model system in genomics and a renowned ecological model system. We infer past and recent demographic processes by contrasting patterns of local and regional neutral genetic diversity at markers with different mutation rates. We assess the role of the environment in driving genetic variation in our study system by identifying correlates between biotic and abiotic variables naturally occurring in the landscape and patterns of neutral and adaptive genetic variation. Our results indicate that selection plays a major role in determining the population genomic structure of D. magna. First, environmental selection directly impacts genetic variation at loci hitchhiking with genes under selection. Secondly, priority effects enhanced by local genetic adaptation (cf. monopolization) affect neutral genetic variation by reducing gene flow among populations and genetic diversity within populations.
Dataset for "NanoVar: a Comprehensive Workflow for Structural Variant Detection to uncover the Genome's Hidden Patterns"
<h2><strong>Output Files for Long-Read Structural Variant and Repeat Analysis in Colorectal Cancer Samples (HRR698464, HRR698460, C586, C588)</strong></h2> <h3>Description:</h3> <p>This Zenodo dataset includes comprehensive output files generated during the application of a long-read sequencing analysis protocol for structural variant (SV) detection and repeat element characterization in colorectal cancer samples. The dataset is organized into two main directories:</p> <p><strong>1. HRR698464_MSI-H_Tumor</strong><br>This directory contains all primary output files generated from the analysis pipeline applied to the MSI-H tumor sample HRR698464 (also referred to as patient C586.T). Each subdirectory corresponds to a specific stage in the protocol:</p> <ul> <li>NanoPlot_output<br>Output from Stage 1 – Quality assessment of raw reads using NanoPlot.</li> <li>SAMtools_output<br>BAM file processing outputs from Stage 2 – Alignment of long reads to the reference genome using SAMtools.</li> <li>NanoVar_output<br>Output from Stage 3 – Structural variant calling using NanoVar.</li> <li>VCF_filtering_output<br>Output from Stage 4 – Filtering of structural variants using SURVIVOR and BCFtools; includes the filtered VCF files.</li> <li>NanoINSight_output<br>Output from Stage 5 – Characterization of repeat elements using NanoINSight.</li> <li>VEP_output<br>Output from Stage 6 – Annotation of structural variants using Ensembl Variant Effect Predictor (VEP).</li> </ul> <p> </p> <p><strong>2. Additional_output_files</strong><br>This directory contains supplementary output files used for comparison and visualization in Figures 4–7 of the associated publication. These include:</p> <ul> <li>HRR698460.NanoPlot.report.html<br>NanoPlot quality summary of a lower-quality tumor sample (HRR698460), used in Figure 4 for comparison with HRR698464.</li> <li>C586.N.nanovar.pass.vcf<br>NanoVar VCF output for the matched normal sample of patient C586, used to filter somatic calls in Stage 4.</li> <li>C586.N.nanovar.pass.report.html<br>NanoVar summary report of the normal sample of C586; used in Figure 5a.</li> <li>C588.N.nanovar.pass.vcf<br>NanoVar VCF output of the MSS normal sample (C588) for comparison with the MSI-H patient (C586).</li> <li>C588.N.nanovar.pass.report.html<br>NanoVar summary report of the MSS normal sample; used in Figure 5b.</li> <li>C588.T.nanovar.pass.vcf<br>NanoVar VCF output of the MSS tumor sample (C588); used in comparative analyses with the MSI-H sample.</li> <li>C588.T.nanovar.pass.report.html<br>NanoVar summary report of the MSS tumor sample; used in Figure 5b.</li> <li>MSS.tumor.unique.vcf<br>VCF file of somatic SVs in the MSS sample, generated by comparing matched tumor and normal pairs.</li> <li>MSS.tumor.unique.RepeatMasker.tbl<br>RepeatMasker output annotating somatic insertions in the MSS tumor sample; used in Figure 6.</li> <li>MSS.tumor.unique.vep.html<br>Ensembl VEP annotation report of somatic SVs in the MSS patient; used in Figures 7a and 7b.</li> <li>This dataset supports reproducibility and transparency of the protocol and offers a valuable resource for researchers interested in long-read-based SV detection, repeat annotation, and comparative cancer genomics.</li> </ul>
Duck pan-genome reveals two transposon-derived structural variations caused bodyweight enlarging and white plumage phenotype formation during evolution
<p><span>Structural variations (SVs) are a major source of domestication and improvement traits. We present the first duck pan-genome constructed using five genome assemblies capturing ~40.98 Mb new sequences. This pan-genome together with high-depth sequencing data (>46.5X) identified 101,041 SVs, of which substantial proportions were derived from transposable element (TE) activity. Many TE-derived SVs anchored in a gene body or regulatory region are linked to domestication and improvement. By combining quantitative genetics with molecular experiments, we dissect how TE-derived SVs change gene expression of <em>IGF2BP1</em> and generate novel transcripts of <em>MITF</em>, shaping body weight and plumage color. In the <em>IGF2BP1</em> locus, the TE-derived SV explains the largest effect on body weight among avian species (27.61% of phenotypic variation). Our findings highlight the </span><span>importance of using a pan-genome as a reference in genomics studies</span><span> and explore the roles of TE-derived SVs in trait formation and in livestock breeding.</span></p>
Dataset from: Distinct patterns of genetic variation at low-recombining genomic regions represent haplotype structure
<p>Genetic variation of the entire genome represents population structure, yet individual loci can show distinct patterns. Such deviations identified through genome scans have often been attributed to effects of selection instead of randomness. This interpretation assumes that long enough genomic intervals average out randomness in underlying genealogies, which represent local genetic ancestries. However, an alternative explanation to distinct patterns has not been fully addressed: too few genealogies to average out the effect of randomness. Specifically, distinct patterns of genetic variation may be due to reduced local recombination rate, which<br>reduces the number of genealogies in a genomic window. Here, we associate distinct patterns of local genetic variation with reduced recombination rates in a songbird, the Eurasian blackcap (<em>Sylvia atricapilla</em>), using genome sequences and recombination maps. We find that distinct patterns of local genetic variation reflect haplotype structure at low-recombining regions either shared in most populations or found only in a few populations. At the former species-wide low-recombining regions, genetic variation depicts conspicuous haplotypes segregating in multiple populations. At the latter population-specific low-recombining regions, genetic variation represents variance among cryptic haplotypes within the low-recombining populations. With simulations, we confirm that these distinct patterns of haplotype structure evolve due<br>to reduced recombination rate, on which the effects of selection can be overlaid. Our results highlight that distinct patterns of genetic variation can emerge through evolution of reduced local recombination rate. Recombination landscape as an evolvable trait therefore plays an important role determining the heterogeneous distribution of genetic variation along the genome.</p>
The de novo assembly of a European wild boar genome revealed unique patterns of chromosomal structural variations and segmental duplications
<div> <div> <p><a href="https://onlinelibrary.wiley.com/doi/10.1111/age.13181">https://onlinelibrary.wiley.com/doi/10.1111/age.13181</a></p> <h1>The de novo assembly of a European wild boar genome revealed unique patterns of chromosomal structural variations and segmental duplications</h1> <div> </div> <div> <div> <div> <div><a href="https://onlinelibrary.wiley.com/authored-by/Chen/Jianhai">Jianhai Chen</a>, <a href="https://onlinelibrary.wiley.com/authored-by/Zhong/Jie">Jie Zhong</a>, <a href="https://onlinelibrary.wiley.com/authored-by/He/Xuefei">Xuefei He</a>, <a href="https://onlinelibrary.wiley.com/authored-by/Li/Xiaoyu">Xiaoyu Li</a>, <a href="https://onlinelibrary.wiley.com/authored-by/Ni/Pan">Pan Ni</a>, <a href="https://onlinelibrary.wiley.com/authored-by/Safner/Toni">Toni Safner</a>, <a href="https://onlinelibrary.wiley.com/authored-by/%C5%A0prem/Nikica">Nikica Šprem</a>, <a href="https://onlinelibrary.wiley.com/authored-by/Han/Jianlin">Jianlin Han</a></div> </div> </div> </div> <p>The rapid progress of sequencing technology has greatly facilitated the de novo genome assembly of pig breeds. However, the assembly of the wild boar genome is still lacking, hampering our understanding of chromosomal and genomic evolution during domestication from wild boars into domestic pigs. Here, we sequenced and de novo assembled a European wild boar genome (ASM2165605v1) using the long-range information provided by 10× Linked-Reads sequencing. We achieved a high-quality assembly with contig N50 of 26.09 Mb. Additionally, 1.64% of the contigs (222) with lengths from 107.65 kb to 75.36 Mb covered 90.3% of the total genome size of ASM2165605v1 (~2.5 Gb). Mapping analysis revealed that the contigs can fill 24.73% (93/376) of the gaps present in the orthologous regions of the updated pig reference genome (Sscrofa11.1). We further improved the contigs into chromosome level with a reference-assistant scaffolding method. Using the ‘assembly-to-assembly’ approach, we identified intra-chromosomal large structural variations (SVs, length >1 kb) between ASM2165605v1 and Sscrofa11.1 assemblies. Interestingly, we found that the number of SV events on the X chromosome deviated significantly from the linear models fitting autosomes (<em>R</em><sup>2</sup> > 0.64, <em>p</em> < 0.001). Specifically, deletions and insertions were deficient on the X chromosome by 66.14 and 58.41% respectively, whereas duplications and inversions were excessive on the X chromosome by 71.96 and 107.61% respectively. We further used the large segmental duplications (SDs, >1 kb) events as a proxy to understand the large-scale inter-chromosomal evolution, by resolving parental-derived relationships for SD pairs. We revealed a significant excess of SD movements from the X chromosome to autosomes (<em>p</em> < 0.001), consistent with the expectation of meiotic sex chromosome inactivation. Enrichment analyses indicated that the genes within derived SD copies on autosomes were significantly related to biological processes involving nervous system, lipid biosynthesis and sperm motility (<em>p</em> < 0.01). Together, our analyses of the de novo assembly of ASM2165605v1 provides insight into the SVs between European wild boar and domestic pig, in addition to the ongoing process of meiotic sex chromosome inactivation in driving inter-chromosomal interaction between the sex chromosome and autosomes.</p> </div> </div> <div>The work has been pulished here: https://onlinelibrary.wiley.com/doi/full/10.1111/age.13181</div> <div> </div> <div>The current dataset include the genome annotation files.</div> <div> </div> <div>For the whole-genomic assembly, please check NCBI: </div> <div>https://www.ncbi.nlm.nih.gov/datasets/genome/GCA_021656055.1/</div> <div> <table> <tbody> <tr> <th> </th> <th>GenBank</th> </tr> </tbody> <tbody> <tr> <td>Genome size</td> <td>2.5 Gb</td> </tr> <tr> <td>Total ungapped length</td> <td>2.4 Gb</td> </tr> <tr> <td>Number of scaffolds</td> <td>12,642</td> </tr> <tr> <td>Scaffold N50</td> <td>28.3 Mb</td> </tr> <tr> <td>Scaffold L50</td> <td>25</td> </tr> <tr> <td>Number of contigs</td> <td>41,323</td> </tr> <tr> <td>Contig N50</td> <td>157.9 kb</td> </tr> <tr> <td>Contig L50</td> <td>4,562</td> </tr> <tr> <td>GC percent</td> <td>42</td> </tr> <tr> <td>Genome coverage</td> <td>56.0x</td> </tr> <tr> <td>Assembly level</td> <td>Scaffold</td> </tr> </tbody> </table> <p> </p> <h2>Assembly methods</h2> <div>Sequencing technology 10xgenomics Assembly method Supernova v. 2.1.1 <p> </p> <p>part_** are genome fasta for the GCA_021656055.1</p> <p>You could use the following to combine and uncompress.</p> </div> </div> <div> <div> <div><code><span>cat</span> part_* > archive_combined.zip </code></div> </div> <div> <div> </div> <div><code>unzip archive_combined.zip</code></div> </div> </div> <div> </div> <div> </div>
Data from: Population genomic evidence of selection on structural variants in a natural hybrid zone
<p><span>Structural variants (SVs) can promote speciation by directly causing reproductive isolation or by suppressing recombination across large genomic regions. Whereas examples of each mechanism have been documented, systematic tests of the role of SVs in speciation are lacking. Here, we take advantage of long-read (Oxford nanopore) whole-genome sequencing and a hybrid zone between two </span><em>Lycaeides</em> butterfly taxa (<em>L. melissa</em> and Jackson Hole <em>Lycaeides</em>) to comprehensively evaluate genome-wide patterns of introgression for SVs and relate these patterns to hypotheses about speciation. We found >100,000 SVs segregating within or between the two hybridizing species. SVs and SNPs exhibited similar levels of genetic differentiation between species, with the exception of inversions, which were more differentiated. We detected credible variation in patterns of introgression among SV loci in the hybrid zone, with 562 of 1419 ancestry-informative SVs exhibiting genomic clines that deviated from null expectations based on genome-average ancestry. Overall, hybrids exhibited a directional shift towards Jackson Hole <em>Lycaeides</em> ancestry at SV loci, consistent with the hypothesis that these loci experienced more selection on average than SNP loci. Surprisingly, we found that deletions, rather than inversions, showed the highest skew towards excess ancestry from Jackson Hole <em>Lycaeides</em>. Excess Jackson Hole <em>Lycaeides</em> ancestry in hybrids was also especially pronounced for Z-linked SVs and inversions containing many genes. In conclusion, our results show that SVs are ubiquitous and suggest that SVs in general, but especially deletions, might disproportionately affect hybrid fitness and thus contribute to reproductive isolation.</p>
Genome-scale phylogeography resolves the native population structure of the Asian longhorned beetle, Anoplophora glabripennis (Motschulsky)
<p><span>Human assisted movement has allowed the Asian longhorned beetle (ALB, <em>Anoplophora glabripennis</em> (Motschulsky)) to spread beyond its native range and become a globally regulated invasive pest. Within its native range of China and the Korean peninsula, human-mediated dispersal has also caused cryptic translocation of insects, resulting in population structure complexity. Previous studies used genetic methods to detangle this complexity but were unable to clearly delimit native populations which is needed to develop downstream biosurveillance tools. We used genome-wide markers to define historical population structure in native ALB populations and contemporary movement between regions. We used genotyping-by-sequencing to generate 6,102 single nucleotide polymorphisms (SNPs) and amplicon sequencing to genotype 53 microsatellites. In total, we genotyped</span> <span>712 individuals from</span> <span>ALB's native distribution. We observed six distinct population clusters among native ALB populations, with a clear delineation between northern and southern groups. Most of the individuals from South Korea were distinct from populations in China. Our results also indicate historical divergence among populations and suggest limited large-scale admixture, but we did identify a restricted number of cases of contemporary movement between regions. We identified SNPs under selection and describe a clinal allele frequency pattern in a missense variant associated with glycerol kinase, an important enzyme in the utilization of an insect cryoprotectant. We further demonstrate that small numbers of SNPs can assign individuals to geographic regions with high probability, paving the way for novel ALB biosurveillance tools.</span></p>
Addiitional Files: The diagrams of population structure, highly divergent regions, GC content and Nanopore reads depth, SNP number and Nanopore reads depth, and analyses of co-linearity against Nipponbare reference genome in 251 accessions.
<p>Additional Files for " <strong>A Super Pan-Genomic Landscape of Rice".</strong></p> <p>Addtional File1: Supplementary File1.Population structure of 251 rice accessions inferred by ADMIXTURE from K=6 to K=15.</p> <p>Additional File2: Supplementary File2.The diagram of co-linearity for assembled genome against Nipponbare refercne genome in 251 rice accessions.</p> <p>Additional File3: Supplementary File3. Highly divergent regions based on SV.</p> <p>Additional File4: Supplementary File4. The diagram of SNP number and Nanopore reads depth per 100kb windows in 251 rice accessions.</p> <p>Additonal File5:Supplementary File5. The diagram of GC content and the Nanopore reads depth per 10kb windows in 251 rice accessions.</p> <p> </p>
Genome-structural analyses support an allotetraploid origin of the walnut family from within Myricaceae and shared genome duplications reveal substitution rate variation
<p><span>In lineages of allopolyploid origin, entire parental subgenomes may coexist, with two or more sets of homoeologous chromosomes that differ in gene content and syntenic structure. Presence or absence of genes, and microsynteny along chromosomal blocks, can be used to differentiate subgenomes and can be coded as phylogenetic data. We assembled chromosome-level genomes of representative species across an ancient allopolyploid lineage, the walnut family (Juglandaceae)</span><span>, with <em>Myrica</em> and other Fagales as outgroups, and used genome-structural data to infer a phylogeny. </span><span>Microsynteny (with various collinear block sizes) and gene content analyses, using the dominant or recessive progenitor subgenomes or both, all yielded identical topologies that place <em>Engelhardia</em> (a SE Asian and Central American clade) with <em>Platycarya</em>, an </span><span>enigmatic monospecific taxon endemic in </span><span>East</span> <span>Asia</span><span>, but well-represented in the Paleocene-Eocene of North America and Europe. </span><span>Morphological studies including fossils also found the <em>Platycarya</em>/<em>Engelhardia</em> clade because of leaf architecture, floral morphology, and nut walls without lacunae, but DNA-alignment-based phylogenetics carried out here and in previous studies never detected this uniformly wind-dispersed clade, instead grouping <em>Platycarya</em> with <em>Carya</em> and <em>Juglans</em>. The novel analyses further reveal </span><span>the family's hybrid origin from extinct or unsampled progenitors nested within Myricaceae and that <em>Rhoiptelea</em> <em>chiliantha</em></span><span>, the Chinese sister species to all other Juglandaceae, </span><span>contains proportionally more genes related to DNA repair and evolved at a rate 2.6- to 3.5-times slower than the remaining species</span><span>. Our results have implications for the molecular clock hypothesis and suggest that genomic structure contains so-far undervalued phylogenetic signal</span><span>.</span></p>
Spruce giga-genomes: structurally similar yet distinctive with differentially expanding gene families and rapidly evolving genes - orthogroups dataset
<p>Orthogroups clustering and analysis of pines and spruces, as reported in Gagalova et al., 2022</p>
SNiffles structural variant vcf SHRSP genome
<p>Variant cell format file generated by Sniffles2/SURVIVOR analysis</p>
Insights into Mus musculus population structure across Eurasia revealed by whole-genome analysis
<p>For more than 100 years, house mice (Mus musculus) have been used as a key animal model in biomedical research. House mice are genetically diverse, yet their genetic background at the global level has not been fully understood. Previous studies suggested that they originated in South Asia and diverged into three major subspecies almost simultaneously, approximately 350,000–500,000 years ago; however, they have spread across the world with the migration of modern humans in prehistoric and historic times (∼10,000 years ago to present), and undergone secondary contact, which have complicated the genetic landscape of wild house mice. In this study, we sequenced the whole genomes of 98 wild house mice collected from Eurasia, particularly East Asia, Southeast Asia, and South Asia. We found that although wild house mice consist of three major genetic groups corresponding to the three major subspecies, individuals representing admixture between subspecies are much more ubiquitous than previously recognized. Furthermore, several samples showed an incongruent pattern of genealogies between mitochondrial and autosomal genomes. Using samples likely retaining the original genetic components of subspecies with least admixture, we estimated the pattern and timing of divergence among the subspecies. The results are important for understanding the genetic diversity of wild mice on a global level and the information will be particularly useful in future biomedical and evolutionary studies using laboratory mice established from these wild mice.</p>
FIGURE 5. The secondary structures for 22 in A new species of the genus Xistra (Orthoptera: Tetrigoidea: Metrodorinae) with comments on the characters of mitochondrial genome
FIGURE 5. The secondary structures for 22 tRNA genes of the Xistra zhengi, sp. nov. Watson–Crick base pairings and mismatches are represented by dashes (-) and pluses (★).
Data from "Population genomic structure of Lemna minor and the cryptic species L. japonica in Switzerland"
<p>SNP data and sample annotation:</p> <ul> <li>sampleTab.csv contains the sample annotation (species and population)</li> <li>L.minor.reference.bcftools.snps.vcf.gz(.tbi) contains SNPs from all samples using the L. minor reference genome (Lm7210)</li> <li>L.japonica.reference.bcftools.snps.vcf.gz(.tbi) contains SNPs from all samples using the L. japonica reference genome (Lj9421)</li> </ul>
The gene structure annotation, gene function annotation and TE annatition files of the Glyphodes pyloalis's genome
Open the record for dataset details and reuse information.
FIGURE 2. Predicted secondary structures for 22 in The complete mitochondrial genome of the jumping grasshopper Sinopodisma pieli (Orthoptera: Acrididae) and the phylogenetic analysis of Melanoplinae
FIGURE 2. Predicted secondary structures for 22 tRNA genes of the S. pieli mitogenome. The tRNAs are labeled with the abbreviations of their corresponding amino acids. The minus sign (-) indicates Watson-Crick base pairing and plus sign (.) indicates G-U base pairing.
Fig. 1 Mitochondrial genome structure and genes variability. a in Historical biogeography and mitogenomics of two endemic Mediterranean gorgonians (Holaxonia, Plexauridae)
Fig. 1 Mitochondrial genome structure and genes variability. a Mitogenomes of Paramuricea clavata and Paramuricea macrospina with genome size and gene annotation. GC-content and AT-content are shown in blue and green on the inner and outer surface of the ring, respectively. b Sliding window analysis of the complete mitochondrial genomes of P. clavata and P. macrospina. The black line indicates
The gene structure annotation, gene function annotation and TE annatition files for the Cibotium barometz isolate CiBa-2024 genome
<p>This dataset comprises comprehensive annotation files for the genome of Cibotium barometz (Golden Chicken Fern), isolate CiBa-2024. It includes gene structure predictions, functional annotations, and transposable element (TE) identifications, complementing the chromosome-level genome assembly. The gene structure annotation provides detailed information on predicted gene models, including exon-intron boundaries and coding sequences. Functional annotations offer insights into the potential roles of identified genes, including Gene Ontology (GO) terms, protein domains, and pathway associations. The TE annotation file details the classification and distribution of transposable elements within the genome. These annotations were generated using state-of-the-art bioinformatics tools and databases, offering a valuable resource for researchers studying fern genomics, plant evolution, and the genetic basis of C. barometz's unique biological features, including its medicinal properties. This dataset aims to facilitate further research in comparative genomics, functional studies, and the exploration of fern biology and evolution.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.