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3,584 results for “genomic analysis”
Supplementary files for the Xenoturbella bocki genome analysis
<p><strong>Supplementary files.</strong></p> <p> </p> <p><strong>Abstract</strong></p> <p>The evolutionary origins of Bilateria remain enigmatic. One of the more enduring proposals highlights similarities between a<br> cnidarian-like planula larva and simple acoel-like flatworms. This idea is based in part on the view of the Xenacoelomorpha as an outgroup to all other bilaterians which are themselves designated the Nephrozoa (protostomes and deuterostomes). Genome data, which can help to elucidate phylogenetic relationships and provide important comparative data, remain sparse for early branching bilaterians. Here we assemble and analyse the genome of the simple, marine xenacoelomorph <em>Xenoturbella bocki</em>, a key species for our understanding of early bilaterian and deuterostome evolution. Our highly contiguous genome assembly of <em>X. bocki</em> has a size of ~110 Mbp in 18 chromosome like scaffolds, with repeat content, and intron, exon and intergenic space comparable to other bilaterian invertebrates. We find <em>X. bocki</em> to have a similar number of genes to other bilaterians and to have retained ancestral metazoan synteny. Key bilaterian signalling pathways are also largely complete and most bilaterian miRNAs are present. We conclude that <em>X. bocki</em> has a complex genome typical of bilaterians, in contrast to the apparent simplicity of its body plan. Overall, our data do not provide evidence supporting the idea that Xenacoelomorpha are a primitively simple outgroup to other bilaterians and gene presence/absence data support a relationship with Ambulacraria.</p>
Determination of traits responding to iron toxicity stress at different stages and genome-wide association analysis for iron toxicity tolerance in rice (Oryza sativa L.)
<p>This vcf file constitute underlying raw data material for the manuscript "Determination of traits responding to iron toxicity stress at different stages and genome-wide association analysis for iron toxicity tolerance in rice (Oryza sativa L.)". <br> The SNP genotype data came from a whole-genome resequencing and were called using the Nipponbare IRGSP 1.0 rice reference genome. SNPs with a miss rate greater than 30% and minor allele frequency (MAF) less than 5% were removed. Heterozygous alleles were also excluded. Finally, 160,498 SNPs were selected and used in the GWAS analysis. </p>
Raw RADseq data for: Population genomics analysis with RAD, reprised: Stacks 2
<p>Restriction enzymes have been one of the primary tools in the population genetics toolkit for 50 years, being coupled with each new generation of technology to provide a more detailed view into the genetics of natural populations. Restriction site-Associated DNA protocols, which joined enzymes with short-read sequencing technology, have democratized the field of population genomics, providing a means to assay the underlying alleles in scores of populations. More than 10 years on, the technique has been widely applied across the tree of life and served as the basis for many different analysis techniques. Here, we provide a detailed protocol to conduct a RAD analysis from experimental design to de novo analysis—including parameter optimization—as well as reference-based analysis, all in Stacks version 2, which is designed to work with paired-end reads to assemble RAD loci up to 1000 nucleotides in length. The protocol focuses on major points of friction in the molecular approaches and downstream analysis, with special attention given to validating experimental analyses. Finally, the protocol provides several points of departure for further analysis.</p>
Meta-analysis reveals challenges and gaps for genome-to-phenome research underpinning plant drought response.
<p>Data used to identify species occurring in hyperarid environments for analyses described in "Meta-analysis reveals challenges and gaps for genome-to-phenome research underpinning plant drought response." The "PlantsLackingHumanUse_PrelimQCd_Data.csv" contains data for all plants queried, while "HyperArid_Occurrences.csv" contains the subset of data corresponding to plants occurring in hyperarid environments.</p>
Fig. 3 in Sequencing and analysis of the complete mitochondrial genome of the giant dobsonfly Acanthacorydalis orientalis (McLachlan) (Insecta: Megaloptera: Corydalidae)
Fig. 3. Predicted secondary structure of the rrnl in the Acanthacorydalis orientalis mt genome. Roman numerals denote the conserved Watson-Crick base pairing and dot (•) indicates G-U base pairing.
Fig. 4 in Sequencing and analysis of the complete mitochondrial genome of the giant dobsonfly Acanthacorydalis orientalis (McLachlan) (Insecta: Megaloptera: Corydalidae)
Fig. 4. Predicted secondary structure of the rrns in the A. orientalis mt genome. Roman numerals denote the conserved domain structure. Dash (-) indicates Watson-Crick base pairing and dot (•) indicates G-U base pairing.
Fig. 1 in Sequencing and analysis of the complete mitochondrial genome of the giant dobsonfly Acanthacorydalis orientalis (McLachlan) (Insecta: Megaloptera: Corydalidae)
Fig. 1. Mitochondrial genome map of Acanthacorydalis orientalis. The tRNAs are denoted by the color blocks and are labeled according to the IUPACIUB single-letter amino acid codes. Gene name without underline indicates the direction of transcription
Fig. 2 in Sequencing and analysis of the complete mitochondrial genome of the giant dobsonfly Acanthacorydalis orientalis (McLachlan) (Insecta: Megaloptera: Corydalidae)
Fig. 2. Inferred secondary structure of 22 tRNAs of the Acanthacorydalis orientalis mt genome. The tRNAs are labeled with the abbreviations of their corresponding amino acids. Dash (-) indicates Watson-Crick bonds and dot (·) indicates GU bonds.
Fig. 5 in Sequencing and analysis of the complete mitochondrial genome of the giant dobsonfly Acanthacorydalis orientalis (McLachlan) (Insecta: Megaloptera: Corydalidae)
Fig. 5. Phylogenetic relationships among the sequenced Megaloptera insects. Numbers at the nodes are Bayesian posterior probabilities (left) and ML bootstrap values (right).
Fig. 6 in Complete mitochondrial genome sequence of Bonasa sewerzowi (Galliformes: Phasianidae) and phylogenetic analysis
Fig. 6. The phylogenetic relationship of Bonasa among Galliformes based on the complete mitogenome. Branch lengths and topologies were obtained from Maximum Likelihood analyses. The numbers were the bootstrap values of MP/ML/BI trees in turn. * indicates that MP or BI tree was inconsistent with ML tree.
Fig. 4 in Complete mitochondrial genome sequence of Bonasa sewerzowi (Galliformes: Phasianidae) and phylogenetic analysis
Fig. 4. The structure of CR in Bonasa sewerzowi mitochondrial genome and comparasion with B. bonasia.
Fig. 5 in Complete mitochondrial genome sequence of Bonasa sewerzowi (Galliformes: Phasianidae) and phylogenetic analysis
Fig. 5. Nucleotide composition of different partitions from two Bonasa mitogenomes. AT-skew, (A-T)/(A+T); GC-skew, (G-C)/(G+C); PCG-1st, the first codon positions of PCGs; PCG-2nd, the second codon positions of PCGs; PCG-3rd, the third codon positions of PCGs.
Fig. 3 in Complete mitochondrial genome sequence of Bonasa sewerzowi (Galliformes: Phasianidae) and phylogenetic analysis
Fig. 3. The srRNA secondary structure of Bonasa sewerzowi mitogenome and comparasion with B. bonasia. The different nucleotides in B. bonasia was pointed out.
Fig. 1 in Complete mitochondrial genome sequence of Bonasa sewerzowi (Galliformes: Phasianidae) and phylogenetic analysis
Fig. 1. Gene map of the B. sewerzowi mitochondrial genome. Transfer RNA genes are designated by single-letter amino acid codes. L1, L2, S1, and S2 denote trnL (uur), trnL (cun), trnS (ucn) and trnS (agy), respectively.
Fig. 2 in Complete mitochondrial genome sequence of Bonasa sewerzowi (Galliformes: Phasianidae) and phylogenetic analysis
Fig. 2. The lrRNA secondary structure of Bonasa sewerzowi mitogenome and comparasion with B. bonasia. The different nucleotides in B.
Supporting code and data to reproduce analysis for: Genomic signatures of past megafrugivore-mediated dispersal in Malagasy palms
<p>Seed dispersal affects gene flow and hence genetic differentiation of plant populations. During the Late Quaternary, most fruit-eating and seed-dispersing megafauna went extinct, but whether these animals have left signatures in the population genetics of their food plants, particularly those with large, 'megafaunal' fruits (i.e., > 4 cm – megafruits), remains unclear.</p> <p>Here, we assessed the population history, genetic differentiation, and recent migration among populations of four animal-dispersed palm (Arecaceae) species with large (<em>Borassus madagascariensis</em>), medium-sized (<em>Hyphaene coriacea,</em> <em>Bismarckia nobilis</em>), and small (<em>Chrysalidocarpus madagascariensis</em>) fruits on Madagascar. We integrated double-digest restriction-site-associated DNA sequencing (ddRAD) of 167 individuals from 25 populations with (past) distribution ranges for extinct and extant seed-dispersing animals (e.g., giant lemurs, elephant birds), landscape and human impact data, and applied linear mixed-effects models to explore the drivers of genetic variation in Malagasy palms.</p> <p>Palm populations that shared more megafrugivore species in the past had lower genetic differentiation than populations that shared fewer megafrugivore species. This suggests that megafrugivore-mediated seed dispersal in the past may have led to frequent gene flow among populations. In comparison, extant frugivore diversity only decreased genetic differentiation in the small-fruited palm. Furthermore, genetic differentiation decreased with landscape connectivity (i.e., environmental suitability, forest cover and river density), and human impact (i.e., road density) has decreased genetic differentiation among populations.</p> <p><em>Synthesis: </em>Our results suggest that the legacy of megafrugivores regularly achieving long dispersal distances is still reflected in the population genetics of palms that were formerly dispersed by such animals. Furthermore, low genetic differentiation was possibly maintained after the megafauna extinctions through alternative dispersal (e.g., human- or river-mediated), long generation times, and long lifespans of these megafruit palms. Our study illustrates how species interactions that happened >1000 years ago can leave imprints in population genetics.</p>
Data for publication: A pipeline for in-depth analysis of DNA virus populations by profiling the low abundant virus variants and partial genomic components
<p>Raw and processed sequence data from Oxford Nanopore and BGI short read sequencing platforms used in the publication: "A pipeline for in-depth analysis of DNA virus populations by profiling the low abundant virus variants and partial genomic components".</p>
Supplemental Results for Assembly, Annotation, and Analysis from HiFi reads of Gulf Toadfish Genome and Transcriptome fOpsBet2.1
<p>This repository contains gzipped tarballs of the results of the various assembly, annotation, and analysis steps performed during the assembly of the fOpsBet2.1 genome assembly for Opsanus beta at the University of Miami Rosenstiel School of Marine, Atmospheric, and Earth Science for the McDonald Toadfish Lab. These results are too numerous to include as supplemental data for a journal publication and so are available here for review. In this repository you will find results for:</p><p>Scripts:</p><p>-all bash and LSF scheduler job scripts used as part of the analysis, both exploratory and final. </p><p>QC:</p><p>-GenomeScope2 estimation of genome metrics from HiFi Reads</p><p>-QUAST genome statistics for each assembly step</p><p>-BUSCO completeness assessments for each assembly step </p><p>-inspector logs for polishing of initial assembly</p><p>-logs from Kraken2 contaminant screen</p><p>Assembly and Scaffolding:</p><p>-ntLINKS logs and intermediates for initial scaffolding</p><p>-ragtag logs and metrics for super-scaffolding to the ThaAma1.1 T. amazonica reference assembly</p><p>-mitoHIFI results for mitogenome assembly from HiFi reads, primary assembly, and purged alternate assembly</p><p>Annotation:</p><p>-PASA directory with full input and output for SQLite PASA assembly of transcriptome for gene predictors</p><p>-Results folder for Funannotate::annotate for gene models, annotations, and CDS/mRNA/protein fastas</p><p>-InterProSCan5 results for protein annotation used as input into Funannotate</p><p>-ghostKOALA KEGG assignment results for predicted proteins from funannotate results</p><p>Repetitive Elements:</p><p>-tidk telomere repeat analysis results</p><p>-TRAH satellite DNA analysis with subsequent analysis with HiCAT and StainedGlass</p><p>-RepeatModeler results for de novo TE prediction</p><p>-repclassifier results for TE curation</p><p>Comparative Analysis:</p><p>-OrthoFinder ortholog search for O. beta to several other vertebrates</p><p>-CAFE5 gene family expansion and contraction of Orthogroups from OrthoFinder results</p><p> </p>
Рис. 1. ФиΛогенетические Αеревья хантавируса AMRV и его прироΑного носитеΛя восточноазиатской мыши Apodemus peninsulae Thomas, 1906. А. ФиΛогенетическое Αерево восточноазиатской мыши Apodemus peninsulae, построенное метоΑом «максимаΛьного правΑопоΑобия» (ML) и поΛученное на основе анаΛиза участка гена цитохрома b мтΔНК (744 п.н.). В узΛах ветвΛения указаны бутстреп-поΑΑержки, рассчитанные ΑΛя 1000 повторов. Цветными Λиниями обозначены фиΛогенетические Λинии: Αве Китайские (зеΛеный), Корейская «Korea» (синий), Амурская «Amur» (красный). ПоΛужирным шрифтом выΑеΛены собственные образцы. Названия образцов из GenBank/NCBI быΛи сокращены; B. ФиΛогенетическое Αерево из работы Α. Н. Яшиной с ΑопоΛнениями, построенное метоΑом «бΛижайшего сосеΑа» (NJ) на основе посΛеΑоватеΛьностей фрагмента М-сегмента (2737–2980 н.п.) генома хантавирусов. В узΛах ветвΛения указаны бутстреппоΑΑержки, рассчитанные ΑΛя 1000 повторов. Жирным выΑеΛены иссΛеΑованные РНК изоΛяты (Яшина 2012; Яшина и Αр. 2019) Fig. 1. Phylogenetic trees of AMRV and its natural reservoir host — the Korean field mouse Apodemus peninsulae Thomas, 1906. A. Phylogenetic tree of the Korean field mouse Apodemus peninsulae constructed by the "maximum likelihood" method (ML). The data are obtained from the analysis of the cytochrome b mtDNA gene fragments (744 bp). Bootstrap supports calculated for 1,000 repeats are indicated in the branching nodes. Colored lines indicate phylogenetic lines: two Chinese (green), Korea (blue), and Amur (red). Own samples are highlighted in bold. The names of the samples from GenBank/NCBI have been shortened; B. Phylogenetic tree from L. N. Yashina's work with additions constructed by the neighbour joining method (NJ). It is based on the sequences of an M-segment fragment (2737–2980 bp) of the hantavirus genome. Bootstrap supports calculated for 1,000 repeats are indicated in the branching nodes. The researched RNA isolates are highlighted in bold (Yashina 2012; Yashina et al. 2019) in Variability of the gene cyt b in the Korean field mouse Apodemus peninsulae Thomas, 1906 - a reservoir host of AMRV in the Khasansky District of Primorsky Krai
Рис. 1. ФиΛогенетические Αеревья хантавируса AMRV и его прироΑного носитеΛя восточноазиатской мыши Apodemus peninsulae Thomas, 1906. А. ФиΛогенетическое Αерево восточноазиатской мыши Apodemus peninsulae, построенное метоΑом «максимаΛьного правΑопоΑобия» (ML) и поΛученное на основе анаΛиза участка гена цитохрома b мтΔНК (744 п.н.). В узΛах ветвΛения указаны бутстреп-поΑΑержки, рассчитанные ΑΛя 1000 повторов. Цветными Λиниями обозначены фиΛогенетические Λинии: Αве Китайские (зеΛеный), Корейская «Korea» (синий), Амурская «Amur» (красный). ПоΛужирным шрифтом выΑеΛены собственные образцы. Названия образцов из GenBank/NCBI быΛи сокращены; B. ФиΛогенетическое Αерево из работы Α. Н. Яшиной с ΑопоΛнениями, построенное метоΑом «бΛижайшего сосеΑа» (NJ) на основе посΛеΑоватеΛьностей фрагмента М-сегмента (2737–2980 н.п.) генома хантавирусов. В узΛах ветвΛения указаны бутстреппоΑΑержки, рассчитанные ΑΛя 1000 повторов. Жирным выΑеΛены иссΛеΑованные РНК изоΛяты (Яшина 2012; Яшина и Αр. 2019) Fig. 1. Phylogenetic trees of AMRV and its natural reservoir host — the Korean field mouse Apodemus peninsulae Thomas, 1906. A. Phylogenetic tree of the Korean field mouse Apodemus peninsulae constructed by the "maximum likelihood" method (ML). The data are obtained from the analysis of the cytochrome b mtDNA gene fragments (744 bp). Bootstrap supports calculated for 1,000 repeats are indicated in the branching nodes. Colored lines indicate phylogenetic lines: two Chinese (green), Korea (blue), and Amur (red). Own samples are highlighted in bold. The names of the samples from GenBank/NCBI have been shortened; B. Phylogenetic tree from L. N. Yashina's work with additions constructed by the neighbour joining method (NJ). It is based on the sequences of an M-segment fragment (2737–2980 bp) of the hantavirus genome. Bootstrap supports calculated for 1,000 repeats are indicated in the branching nodes. The researched RNA isolates are highlighted in bold (Yashina 2012; Yashina et al. 2019)
Fig. 1 in Complete mitochondrial genome of Nyctalus aviator and phylogenetic analysis of the family Vespertilionidae
Fig. 1. Neighbor Joining (NJ) phylogeny of Vespertilionidae was inferred from concatenated nucleotide sequences of 13 mitogenomic protein-coding genes. Node labels indicate the bootstrap values. GenBank accession numbers for the sequences are indicated next to species designations.
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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.