Find research datasets worth reusing

opencc-by-4.0Jan 2020View details →

Genome-wide structure and function modeling of SARS-COV-2

Homology models and function annotation for all proteins in the SARS-CoV-2 genome. For a description of each file, follow <a href="https://zhanglab.ccmb.med.umich.edu/COVID-19/">this link</a>.

openmit-licenseApr 2024View details →

Long-read sequencing and structural variant characterization in 1,019 samples from the 1000 Genomes Project

SV analysis of the long-read sequencing data of 1,019 samples from the 1000 Genomes Project. The data is hosted at the International Genome Sample Resource (IGSR) in the <a href="https://ftp.1000genomes.ebi.ac.uk/vol1/ftp/data_collections/1KG_ONT_VIENNA/">1KG_ONT_VIENNA</a> directory. Please see the <a href="https://ftp.1000genomes.ebi.ac.uk/vol1/ftp/data_collections/1KG_ONT_VIENNA/README_1KG_ONT_VIENNA.md">README</a> and <a href="https://ftp.1000genomes.ebi.ac.uk/vol1/ftp/data_collections/1KG_ONT_VIENNA/README_1KG_ONT_VIENNA_datareuse_statement.md">data reuse statement</a> for further information about this dataset.

opencc-by-4.0Jul 2021View details →

Large structural variations in the haplotype-resolved African cassava genome

Cassava TME7 haplotype resolved assemblies and annotation   ABSTRACT: Cassava (Manihot esculenta Crantz, 2n=36) is a global food security crop. Cassava has a highly heterozygous genome, high genetic load, and genotype-dependent asynchronous flowering. It is typically propagated by stem cuttings and any genetic variation between haplotypes, including large structural variations, is preserved by such clonal propagation. Traditional genome assembly approaches generate a collapsed haplotype representation of the genome. In highly heterozygous plants, this results in artifacts and an oversimplification of heterozygous regions. We used a combination of Pacific Biosciences (PacBio), Illumina, and Hi-C to resolve each haplotype of the genome of a farmer-preferred cassava line, TME7 (Oko-iyawo). PacBio reads were assembled using the FALCON suite. Phase switch errors were corrected using FALCON-Phase and Hi-C read data. The ultra-long-range information from Hi-C sequencing was also used for scaffolding. Comparison of the two phases revealed more than 5,000 large haplotype-specific structural variants affecting over 8 Mb, including insertions and deletions spanning thousands of base pairs. The potential of these variants to affect allele specific expression was further explored. RNA-seq data from 11 different tissue types were mapped against the scaffolded haploid assembly and gene expression data are incorporated into our existing easy-to-use web-based interface to facilitate use by the broader plant science community. These two assemblies provide an excellent means to study the effects of heterozygosity, haplotype-specific structural variation, gene hemizygosity, and allele specific gene expression contributing to important agricultural traits and further our understanding of the genetics and domestication of cassava.

opencc-by-4.0Oct 2021View details →

Datasets for 'Mandrake: visualising microbial population structure by embedding millions of genomes into a low-dimensional representation'

Datasets for the paper 'Mandrake: visualising microbial population structure by embedding millions of genomes into a low-dimensional representation' Files: <ul> <li>616k* - Files for the analysis of 661k bacterial genomes from the SRA (note typo 616-661k). Includes mandrake output and input files (.npz)</li> <li>gps_acc - Files for the analysis of 20k S. pneumoniae accessory genomes from the GPS project. Original accessory matrix is gps_gene_presence_absence.Rtab</li> <li>sc2million_v1* - Files for the analysis of ~1M SARS-CoV-2 genomes. sc2million_v3.npz are the input distances.</li> <li>sce<commit hash>.qdrep - Nvidia systems profile of code at that commit hash</li> <li>sce<commit hash>.ncu-rep - Nvidia kernel profile of code at that commit hash</li> </ul>

opencc-by-4.0Jul 2023View details →

ScRAPv20230731: Telomere-to-telomere assemblies of 142 strains characterize the genome structural landscape in Saccharomyces cerevisiae

Saccharomyces cerevisiae Reference Assembly Panel (ScRAP) v20230731 > The haplotype-resolved and/or collapsed T2T genome assemblies for 142 S. cerevisiae strains isolated from diverse geographical and ecological niches.

opencc-by-4.0Feb 2020View details →

Dataset for "Whole-genome de novo assemblies reveal structural variations and organelle-to-nucleus DNA transfers in Asian and African rice""

DXCWR_O.rufipogon_scaffolded_anchored.fa.gz --Scaffolded and anchored genome assembly for O. rufipogon  DXCWR. DXCWR_O.rufipogon_scaffolded_anchored.gff.gz --Gene annotation for the genome assembly DXCWR_O.rufipogon_scaffolded_anchored.fa. DXCWR_O.rufipogon_scaffolded_anchored_repeatmasker.gff.gz --Repeat annotation for the genome assembly DXCWR_O.rufipogon_scaffolded_anchored.fa. IRGC104165_O.glaberrima_scaffolded_anchored.fa.gz --Scaffolded and anchored genome assembly for O. glaberrima  IRGC104165. IRGC104165_O.glaberrima_scaffolded_anchored.gff.gz --Gene annotation for the genome assembly IRGC104165_O.glaberrima_scaffolded_anchored.fa. IRGC104165_O.glaberrima_scaffolded_anchored_repeatmasker.gff.gz --Repeat annotation for the genome assembly IRGC104165_O.glaberrima_scaffolded_anchored.fa. W1411_O.barthii_scaffolded_anchored.fa.gz --Scaffolded and anchored genome assembly for O. barthii  W1411. W1411_O.barthii_scaffolded_anchored.gff.gz --Gene annotation for the genome assembly W1411_O.barthii_scaffolded_anchored.fa. W1411_O.barthii_scaffolded_anchored_repeatmasker.gff.gz --Repeat annotation for the genome assembly W1411_O.barthii_scaffolded_anchored.fa. W2014_O.nivara_scaffolded_anchored.fa.gz --Scaffolded and anchored genome assembly for O. nivara  W2014. W2014_O.nivara_scaffolded_anchored.gff.gz --Gene annotation for the genome assembly  W2014_O.nivara_scaffolded_anchored.fa. W2014_O.nivara_scaffolded_anchored_repeatmasker.gff.gz --Repeat annotation for the genome assembly  W2014_O.nivara_scaffolded_anchored.fa.

opencc-zeroDec 2020View details →

Analysis of copy number variation in dogs implicates genomic structural variation in the development of anterior cruciate ligament rupture

Anterior cruciate ligament (ACL) rupture is an important condition of the human knee. Second ruptures are common and societal costs are substantial. Canine cranial cruciate ligament (CCL) rupture closely models the human disease. CCL rupture is common in the Labrador Retriever (5.79% prevalence), ~100-fold more prevalent than in humans. Labrador Retriever CCL rupture is a polygenic complex disease, based on genome-wide association study (GWAS) of single nucleotide polymorphism (SNP) markers. Dissection of genetic variation in complex traits can be enhanced by studying structural variation, including copy number variants (CNVs). Dogs are an ideal model for CNV research because of reduced genetic variability within breeds and extensive phenotypic diversity across breeds. We studied the genetic etiology of CCL rupture by association analysis of CNV regions (CNVRs) using 110 case and 164 control Labrador Retrievers. CNVs were called from SNPs using three different programs (PennCNV, CNVPartition, and QuantiSNP). After quality control, CNV calls were combined to create CNVRs using ParseCNV and an association analysis was performed. We found no strong effect CNVRs but found 46 small effect (max(T) permutation P<0.05) CCL rupture associated CNVRs in 22 autosomes; 25 were deletions and 21 were duplications. Of the 46 CCL rupture associated CNVRs, we identified 39 unique regions. Thirty four were identified by a single calling algorithm, 3 were identified by two calling algorithms, and 2 were identified by all three algorithms. For 42 of the associated CNVRs, frequency in the population was <10% while 4 occurred at a frequency in the population ranging from 10-25%. Average CNVR length was 198,872bp and CNVRs covered 0.11 to 0.15% of the genome. All CNVRs were associated with case status. CNVRs did not overlap previous canine CCL rupture risk loci identified by GWAS. Associated CNVRs contained 152 annotated genes; 12 CNVRs did not have genes mapped to CanFam3.1. Using pathway analysis, a cluster of 19 homeobox domain transcript regulator genes was associated with CCL rupture (P=6.6E-13). This gene cluster influences cranial-caudal body pattern formation during embryonic limb development. Clustered genes were found in 3 CNVRs on chromosome 14 (HoxA), 28 (NKX6-2), and 36 (HoxD). When analysis was limited to deletion CNVRs, the association was strengthened (P=8.7E-16). This study suggests a component of the polygenic risk of CCL rupture in Labrador Retrievers is associated with small effect CNVs and may include aspects of stifle morphology regulated by homeobox domain transcript regulator genes.

opencc-zeroJul 2019View details →

Data from: Genomic data reveal deep genetic structure but no support for current taxonomic designation in a grasshopper species complex

Taxonomy has traditionally relied on morphological and ecological traits to interpret and classify biological diversity. Over the last decade, technological advances and conceptual developments in the field of molecular ecology and systematics have eased the generation of genomic data and changed the paradigm of biodiversity analysis. Here we illustrate how traditional taxonomy has led to species designations that are supported neither by high throughput sequencing data nor by the quantitative integration of genomic information with other sources of evidence. Specifically, we focus on Omocestus antigai and O. navasi, two montane grasshoppers from the Pyrenean region that were originally described based on quantitative phenotypic differences and distinct habitat associations (alpine vs. Mediterranean-montane habitats). To validate current taxonomic designations, test species boundaries, and understand the factors that have contributed to genetic divergence, we obtained phenotypic (geometric morphometrics) and genome-wide SNP data (ddRADSeq) from populations covering the entire known distribution of the two taxa. Coalescent-based phylogenetic reconstructions, integrative Bayesian model-based species delimitation, and landscape genetic analyses revealed that populations assigned to the two taxa show a spatial distribution of genetic variation that do not match with current taxonomic designations and is incompatible with ecological/environmental speciation. Our results support little phenotypic variation among populations and a marked genetic structure that is mostly explained by geographic distances and limited population connectivity across the abrupt landscapes characterizing the study region. Overall, this study highlights the importance of integrative approaches to identify taxonomic units and elucidate the evolutionary history of species.

opencc-by-4.0Mar 2024View details →

The structure of simple satellite variation in the human genome and its correlation with centromere ancestry (Supplemental Data)

Accompanying <a href="https://github.com/is-the-biologist/1KGP_SATS" target="_blank" rel="noopener">Github</a> Supplemental File 1. BLAST results of k-mer concatemers against T2T-CHM13-v2.0. Supplemental File 2. Annotations of centromeres, and telomeres of T2T-CHM13-v2.20. Table of abundance of k-mers in annotated regions as numpy file from BLAST hits. Abundance of k-mers across genome in 100kb bins from BLAST hits as .npz files accessible by example:     import numpy as np     dense = np.load("filename.npz")     dense["chr1"]    Supplemental File 3. Table of pairwise R2 between simple satellites and table of pairwise interspersion OR between simple satellites. Folder containing QQ plots of negative binomial fit of satellite copy number distribution used to qualitatively asses model fit. Supplemental File 4. Materials and results of cenGRM analysis. Boundaries used for centromeric regions of each cenGRM, cenGRMs in GCTA format, and tables with the results of cenGRM GCTA runs. Also provide pdfs of the dendrograms/heatmaps produced from UPGMA clustering of each cenGRM.  Supplemental File 5 Non-human significant BLAST hits from BLAST-ing k-mer concatamers to non-human sequences. Supplemental Table 1. Copy number normalized to 1x depth given GC bias of 126 most abundant satellites analyzed in paper in each individual. Additional columns represent metadata of the individual: <ul> <li>instrument: sequencer instrument name used to sequence library.</li> <li>run: sequencer run of the library.</li> <li>flow: flowcell ID of the ibrary.</li> <li>pop: 1,000 Genomes Project population ID.</li> <li>superpop: 1,000 Genomes Project superpopulation ID.</li> <li>reads: average autosomal read depth of the library.</li> </ul> Supplemental Table 2. Copy number normalized to 1x depth given GC bias of the top 126 most abundant satellites analyzed in paper in each individual of the 1KGP, plus estimates of the same satellites in CHM13 short-read libraries subsampled from 18x-0.5x, 18x depth simulated library of the T2T-CHM13v2.0 assembly analyzed using k-Seek, and Tandem Repeat Finder results of the T2T-CHM13v2.0 asembly <a href="https://doi.org/10.1126/science.abk3112" target="_blank" rel="noopener">Hoyt 2022</a>. Supplemental Table 3. Copy number normalized to 1x depth given GC bias of all tandem repeats with k-mer <= 20 (6,309) found collectively in the CHM13 short-read libraries subsampled from 18x-0.5x, 18x depth simulated library of the T2T-CHM13v2.0 assembly analyzed using k-Seek, and Tandem Repeat Finder results of the T2T-CHM13v2.0 asembly <a href="https://doi.org/10.1126/science.abk3112" target="_blank" rel="noopener">Hoyt 2022</a>.

opencc-by-4.0Mar 2024View details →

Supporting data for the manuscript "Severus: accurate detection and characterization of somatic structural variation in tumor genomes using long reads"

Supporting data for the manuscript "Severus: accurate detection and characterization of somatic structural variation in tumor genomes using long reads". The archive contains files that are necessary to reproduce the cell line benchmarks from the paper, including: <ul> <li>Scripts and command lines</li> <li>Original VCF outpurs of all tools used in benchmarking</li> <li>Minda evaluations and truthset VCF files</li> <li>Full Severus outputs + visualizations</li> <li>truvari calls</li> </ul>

opencc-zeroMay 2022View details →

The chloroplast genomes of Sanicula (Apiaceae): plastome structure, comparative analyses, and phylogenetic relationships

Sanicula (Apiaceae subfamily Saniculoideae) is a taxonomically difficult genus of medicinal value. Its distribution center is in China, where there are 18 species (11 of which are endemic). To provide plastid genome resources, whole chloroplast genomes of five Sanicula species (S. flavovirens, S. giraldii, S. lamelligera, S. odorata, and S. rubriflora) were sequenced and compared to the previously published S. orthacantha plastome. These genomes exhibit a typical quadripartite structure. All contain 129 different genes, including 84 protein-coding, 37 tRNA, and 8 rRNA genes. Loci rpl2, matK, psbA, and ycf1 are the most variable. Results of maximum likelihood analysis of 90 whole plastome sequences from Apioideae and Saniculoideae and the outgroup Hydrocotyle (Araliaceae) reveal sectional relationships in Sanicula different from the traditional classification system, support the monophyly of Apioideae and its sister group relationship to Saniculoideae, and show concordant topologies to nrDNA ITS and other plastome-based phylogenies. Sanicula orthacantha and S. chinensis form a clade sister group to S. lamelligera and S. odorata, consecutively. These four species comprise a clade sister group to the clade of S. rubriflora and S. flavovirens, with this entire group sister to S. giraldii. The plastid genome resources provided herein will be important for future systematic, evolutionary, phylogenomic, and population-level studies of Sanicula.

opencc-zeroSep 2022View details →

Discordant population structure among rhizobium divided genomes and their legume hosts

Symbiosis often occurs between partners with distinct life history characteristics and dispersal mechanisms. Many bacterial symbionts have genomes comprised of multiple replicons with distinct rates of evolution and horizontal transmission. Such differences might drive differences in population structure between hosts and symbionts and among the elements of the divided genomes of bacterial symbionts. These differences might, in turn, shape the evolution of symbiotic interactions and bacterial evolution. Here we use whole-genome resequencing of a hierarchically-structured sample of 191 strains of Sinorhizobium meliloti collected from 21 locations in southern Europe to characterize the population structures of this bacterial symbiont and its host plant Medicago truncatula. Sinorhizobium meliloti genomes showed high local (within-site) variation and little isolation by distance. This was particularly true for the two symbiosis elements pSymA and pSymB, which have population structures that are similar to each other, but distinct from both the bacterial chromosome and the host plant. The differences in population structure may result from among-replicon differences in the extent of horizontal gene transfer, although given limited recombination of the chromosome, different levels of purifying or positive selection may also contribute to among-replicon differences. Discordant population structure between hosts and symbionts indicates that geographically and genetically distinct host populations in different parts of the range might interact with genetically similar symbionts, potentially minimizing local specialization.

openDec 2024View details →

Genomic Data for "Structure of Anellovirus-like Particles Reveal a Mechanism for Immune EvasionAnellovirus-like Particles Reveal a Mechanism for Immune Evasion"

All genomic data supporting the paper 'Structure of Anellovirus-like Particles Reveal a Mechanism for Immune EvasionAnellovirus-like Particles Reveal a Mechanism for Immune Evasion'. Include amino acid sequence alignment used to produce supplemental figure 6 in the manuscript.

opencc-zeroMay 2024View details →

Data and code from: Evaluating genomic offset predictions in a forest tree with high population genetic structure

Predicting how tree populations will respond to climate change is an urgent societal concern. An increasingly popular way to make such predictions is the genomic offset (GO) approach, which aims to use genomic and climate data to identify populations that may experience climate maladaptation in the near future. More precisely, GO tries to represent the change in allele frequencies required to maintain the current gene-climate relationships under climate change. However, the GO approach has major limitations and, despite promising validation of its predictions using height data from common gardens, it still lacks broad empirical testing. In the present study, we evaluated the consistency and empirical validity of GO predictions in maritime pine (Pinus pinaster Ait.), a tree species from southwestern Europe and North Africa with a marked population genetic structure. First, gene-climate relationships were estimated using 9,817 SNPs genotyped in 454 trees from 34 populations; and candidate SNPs potentially involved in climate adaptation were identified. Second, GO was predicted using four methods, namely Gradient Forest (GF), Redundancy Analysis (RDA), latent factor mixed model (LFMM) and Generalised Dissimilarity Modeling (GDM), two sets of SNPs (candidate and control SNPs) and five climate general circulation models (GCMs) to account for uncertainty in future climate predictions. Last, the empirical validity of GO predictions was evaluated within a Bayesian framework by estimating the associations between GO predictions and two independent data sources: mortality data from National Forest Inventories (NFI), and mortality and height data from five common gardens in contrasting environments. We found high variability in GO predictions across methods, SNP sets and GCMs. Regarding validation, GO predictions with GDM and GF (and to a lesser extent RDA) based on the candidate SNPs showed the strongest and most consistent associations with mortality rates in common gardens and NFI plots. We found almost no association between GO predictions and tree height in common gardens, most likely due to the overwhelming effect of population genetic structure on tree height in this species. Our study demonstrates the imperative to validate GO predictions with a range of independent data sources before they can be used as informative and reliable metrics in conservation or management strategies.

opencc-by-4.0Sep 2019View details →

Dataset for the article: "Weak genetic structure despite strong genomic signal in lesser sandeel in the North Sea"

Dataset used for the article: "Weak genetic structure despite strong genomic signal in lesser sandeel in the North Sea". Dataset consists on a VCF file from 471 individuals of lesser sandeel, Ammodytes marinus (L.). This VCF is the end product of the bioinformatic analysis described in the paper Jimenez-Mena et al. (2019). Data was obtained from double-digest Restriction-site Associated DNA (ddRAD) sequencing. More information can be obtained in Methods of the article. The information of each of the individuals in the VCF is also included as a separate file, as well as the supplementary tables of the article.

opencc-by-4.0Aug 2022View details →

Fig. 5 in The complete mitochondrial genome of Platygaster robiniae (Hymenoptera: Platygastridae): A novel tRNA secondary structure, gene rearrangements and phylogenetic implications

Fig. 5. Phylogenetic tree Note: (A): Maximum likelihood (ML) phylogenetic tree inferred from the mitochondrial genome based on the 13 PCGs dataset; (B): Bayesian inference (BI) phylogenetic tree inferred from the mitochondrial genome based on the 13 PCGs dataset.

opencc-by-4.0Aug 2022View details →

Fig. 4 in The complete mitochondrial genome of Platygaster robiniae (Hymenoptera: Platygastridae): A novel tRNA secondary structure, gene rearrangements and phylogenetic implications

Fig. 4. Mitochondrial genome organization of Platygaster robiniae and 11 species of Platygastroidea, compared with the ancestral pancrustacean mt genome organization. Note: tRNA genes are indicated by single letter amino acid codes, L1, L2, S1 and S2 denote tRNALeu(CUN), tRNALeu(UUR), tRNASer(AGN) and tRNASer(UCN), respectively. Genes are transcribed from left to right except those indicated by underlining. Gene movements, relative to the ancestral organization, are indicated with arrows.