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281 results for “genetic sequence”
Supplementary dataset to publication: Oxford nanopore technologies - a valuable tool to generate whole-genome sequencing data for in silico serotyping and the detection of genetic markers in Salmonella, Thomas et al 2023
<p>Bacteria of the genus <em>Salmonella</em> pose a major risk to livestock, the food economy, and public health. <em>Salmonella</em> infections are one of the leading causes of food poisoning. The identification of serovars of <em>Salmonella</em> achieved by their diverse surface antigens is essential to gain information on their epidemiological context. Traditionally, slide agglutination has been used for serotyping. In recent years, whole-genome sequencing (WGS) followed by <em>in silico</em> serotyping has been established as an alternative method for serotyping and the detection of genetic markers for <em>Salmonella</em>. Until now, WGS data generated with Illumina sequencing are used to validate <em>in silico</em> serotyping methods. Oxford Nanopore Technologies (ONT) opens the possibility to sequence ultra-long reads and has frequently been used for bacterial sequencing. In this study, ONT sequencing data of 28 <em>Salmonella</em> strains of different serovars with epidemiological relevance in humans, food, and animals were taken to investigate the performance of the <em>in silico</em> serotyping tools SISTR and SeqSero2 compared to traditional slide agglutination tests. Moreover, the detection of genetic markers for resistance against antimicrobial agents, virulence, and plasmids was studied by comparing WGS data based on ONT with WGS data based on Illumina. Based on the ONT data from flow cell version R9.4.1, <em>in silico</em> serotyping achieved an accuracy of 96.4 and 92% for the tools SISTR and SeqSero2, respectively. Highly similar sets of genetic markers comparing both sequencing technologies were identified. Taking the ongoing improvement of basecalling and flow cells into account, ONT data can be used for <em>Salmonella in silico</em> serotyping and genetic marker detection.</p>
Whole genome sequencing of Turkish genomes reveals functional private alleles and impact of genetic interactions with Europe, Asia and Africa.
<p>BACKGROUND:</p> <p>Turkey is a crossroads of major population movements throughout history and has been a hotspot of cultural interactions. Several studies have investigated the complex population history of Turkey through a limited set of genetic markers. However, to date, there have been no studies to assess the genetic variation at the whole genome level using whole genome sequencing. Here, we present whole genome sequences of 16 Turkish individuals resequenced at high coverage (32×-48×).</p> <p>RESULTS:</p> <p>We show that the genetic variation of the contemporary Turkish population clusters with South European populations, as expected, but also shows signatures of relatively recent contribution from ancestral East Asian populations. In addition, we document a significant enrichment of non-synonymous private alleles, consistent with recent observations in European populations. A number of variants associated with skin color and total cholesterol levels show frequency differentiation between the Turkish populations and European populations. Furthermore, we have analyzed the 17q21.31 inversion polymorphism region (MAPT locus) and found increased allele frequency of 31.25% for H1/H2 inversion polymorphism when compared to European populations that show about 25% of allele frequency.</p> <p>CONCLUSION:</p> <p>This study provides the first map of common genetic variation from 16 western Asian individuals and thus helps fill an important geographical gap in analyzing natural human variation and human migration. Our data will help develop population-specific experimental designs for studies investigating disease associations and demographic history in Turkey.</p>
GWAS Summary Statistics for Publication: Identifying novel genetic and phenotypic associations to genomic features by leveraging off-target reads in exome sequencing data
<p>This dataset contains summary statistics for genome-wide association studies (GWAS) conducted on genomic features derived from off-target reads in whole-exome sequencing (WES) data. The study utilized tools like Seeing Beyond the Target (SBT) and ImReP to construct novel phenotypic features from unmapped reads in ~50,000 participants in the UK Biobank. Features include mitochondrial DNA (mtDNA) copy number, ribosomal DNA (rDNA) copy number (5S, 18S, 28S), immune repertoire metrics (e.g., T-cell receptor alpha diversity), and microvial genome load (viral and fungal).</p> <p>Summary statistics can be used for replication studies, meta-analyses, or further exploration of these phenotypes.</p>
Lepidoptera genomics based on 88 chromosomal reference sequences informs population genetic parameters for conservation
<p>This repository contains (1) germline mutations called by the DeepVariant (v1.1.0) pipeline in VCF format; (2) rejected substitution scores calculated by the Genomic Evolutionary Rate Profiling (GERP++) software on each species and chromosome; and (3) the phylogenetic tree used as guide tree in the Cactus alignment.</p>
Appendix. List of the 28S and 16S rRNA sequences recovered from GenBank. 28S = 28S rRNA GenBank accession number; 16S = 16S rRNA GenBank accession number. in Genetic and morphological evidence for cryptic species in Macrobrachium australe and resurrection of M. ustulatum (Crustacea, Palaemonidae)
Appendix. List of the 28S and 16S rRNA sequences recovered from GenBank. 28S = 28S rRNA GenBank accession number; 16S = 16S rRNA GenBank accession number.
Long-read sequencing reveals extensive gut phageome structural variations driven by genetic exchange with bacterial hosts
<p><span>Genetic variations are instrumental for unraveling phage evolution and deciphering their functional implications. Here we explore the underlying fine-scale genetic variations in the gut phageome, especially structural variations (SVs). By employing virome-enriched long-read metagenomics sequencing across 91 individuals, we identified a total of 14,438 non-redundant phage SVs, and revealed their prevalence within the human gut phageome. These SVs are mainly enriched in genes involved in recombination, DNA methylation, and antibiotic resistance. Strikingly, a substantial fraction of phage SV sequences share close homology with bacterial fragments, with most SVs enriched for horizontal gene transfer (HGT) mechanism. Further investigations showed that these SV sequences were genetic exchanged between specific phage-bacteria pairs, particularly between phages and their respective bacterial hosts. Temperate phages exhibits a higher frequency of genetic exchange with bacterial chromosomes then virulent phages. Collectively, our findings provide novel insights into the genetic landscape of the human gut phageome.</span></p>
Figure 2 in Examining metrics and magnitudes of molecular genetic differentiation used to delimit cetacean subspecies based on mitochondrial DNA control region sequences
Figure 2. Relationship between ΦST and Nei's estimate of net divergence (dA) among cetacean population, subspecies, and species pairs estimated using mitochondrial DNA control region sequence data. Specific values mentioned in the text are numbered: 1 = Neophocaena species; 2 = killer whale populations. The three green squares in the left-hand side of the figure (ΦST <0.07) represent, from bottom to top, the subspecies comparisons for S. attenuata, S. longirostris, and L. obscurus, respectively.
Figure 1 in Examining metrics and magnitudes of molecular genetic differentiation used to delimit cetacean subspecies based on mitochondrial DNA control region sequences
Figure 1. Box and whisker plots showing median and 1st and 3rd quartiles, and minimum and maximum values for six metrics of genetic divergence among cetacean population, subspecies, and species pairs estimated using mitochondrial DNA control region sequence data.
Fig. 1. Collectionsitesfor 91 specimensfrom 29 locationsof Apodemusagrarius, usedin thisstudy. ThespecimennumberforeachlocationarelistedinTable 1 in Comparative Genetics Of Apodemus Agrarius (Rodentia: Mammalia) From Insular And Continental Eurasian Populations: Cytochrome B Sequence Analyses
Fig. 1. Collectionsitesfor 91 specimensfrom 29 locationsof Apodemusagrarius, usedin thisstudy. ThespecimennumberforeachlocationarelistedinTable 1, andminimum Jukes-Cantordistancesbetween 17 haplotypesfrommainlandKoreaandother 49 haplo- typesfromsevenregions (Taiwan, Jeju, northeasternChina, easternChina, centralChina, Far-easternRussia, andEurope) basedonthecytochrome b completesequencesaregiven
Deep-sequencing of viral genomes from treatment-naive HIV-infected persons shows positive association between intrahost genetic diversity and viral load
<p><strong><span>Background:</span></strong><span> Infection with human immunodeficiency virus type 1 (HIV) typically results from transmission of a small and genetically uniform viral population. Following transmission, the virus population becomes more diverse because of recombination and acquired mutations through genetic drift and selection. Viral intrahost genetic diversity remains a major obstacle to the cure of HIV; however, there is a disagreement whether intrahost viral genetic diversification associates positively or negatively with disease progression and progression markers. Viral load is a key progression marker and understanding its relationship to viral intrahost genetic diversity could help design future strategies for HIV monitoring and treatment.</span></p> <p><span><strong>Methods:</strong> </span><span>We analyzed deep-sequenced viral genomes from 2,650 treatment-naive HIV-infected persons to measure the intrahost genetic diversity of 2,447 genomic codon positions as calculated by Shannon entropy. We tested for associations between viral load (VL) and amino acid (AA) entropy accounting for sex, age, race, duration of infection, and HIV population structure.</span></p> <p><strong><span>Results:</span></strong><span><strong> </strong>We confirmed that the intrahost genetic diversity is highest in the <em>env</em> gene. Furthermore, we showed that mean Shannon entropy is significantly associated with VL, especially in infections of >24 months duration. We identified 16 significant associations between VL (p-value<2.0x10<sup>-5</sup>) and Shannon entropy at AA positions which in our association analysis explained 13% of the variance in VL.</span></p> <p><strong><span>Conclusions: </span></strong><span>Our results elucidate that viral intrahost genetic diversity is associated with VL and could be used as a better disease progression marker than HIV consensus sequence variants, especially in infections of longer duration. We emphasize that viral intrahost diversity should be considered when studying viral genomes and infection outcomes.</span></p>
Figure 5 in Genetic difference between two Schistosoma japonicum isolates with contrasting cercarial shedding patterns revealed by whole genome sequencing
Figure 5. Gene ontology enrichment analysis of genes from genome regions with strong selective signals.
Figure 2 in Genetic difference between two Schistosoma japonicum isolates with contrasting cercarial shedding patterns revealed by whole genome sequencing
Figure 2. Box plots of diversity, Tajima's D of S. japonicum and their FST. (A) Nucleotide diversity estimated in 100-kb windows sliding in 10-kb steps throughout the genome. (B) Tajima's D estimated within a nonoverlapping 100-kb window throughout the genome. (C) pairwise FST computed in 100-kb windows sliding in 10-kb steps throughout the genome.
Figure 4 in Genetic difference between two Schistosoma japonicum isolates with contrasting cercarial shedding patterns revealed by whole genome sequencing
Figure 4. Distribution of p ratios (pST/pHX) and FST values calculated in 100-kb windows sliding in 10-kb steps throughout the genome. Data points colored red and blue were identified as selected regions in ST (red dots) and in HX (blue dots), respectively. These points correspond to the 5% left and right tails of the empirical p ratio distribution, where the p ratios are 0.092 and 1.643, respectively (vertical dashed lines), and the 5% right tail of the empirical FST distribution, where FST is 0.965 (horizontal dashed line).
Figure 3 in Genetic difference between two Schistosoma japonicum isolates with contrasting cercarial shedding patterns revealed by whole genome sequencing
Figure 3. Box plots of diversity and relationship of two sample groups. (A) Nucleotide diversity estimated in 100-kb windows sliding in 10-kb steps throughout the genome. (B) Tajima's D estimated within a nonoverlapping 100-kb window throughout the genome. (C) FST between computed in 100-kb windows sliding in 10-kb steps throughout the genome.
Fig. 2a in Prevalence of a new genetic group, MEAM-K, of the whitefly Bemisia tabaci (Hemiptera: Aleyrodidae) in Karnataka, India, as evident from mtCOI sequences
Fig. 2a. Phylogenetic tree showing the relationship of the Bemisia tabacimt mtCOI sequences collected in this study to consensus sequences of Dinsdale et al. (2010). Bayesian analyses were performed employing MrBayes under the best-fit model GTR+I+G of molecular evolution for 20 million generations and 25% discarded as burn-in. Posterior probabilities are shown above the branches and maximum likelihood scores from RaxML indicated below the branches. Asia-I condensed is shown in Fig. 2b.
Fig. 1 in Prevalence of a new genetic group, MEAM-K, of the whitefly Bemisia tabaci (Hemiptera: Aleyrodidae) in Karnataka, India, as evident from mtCOI sequences
Fig. 1. Map indicating different locations of Bemisia tabaci sampling and distribution of genetic groups in Karnataka, India.
Fig. 2b. Phylogenetic tree indicating the Asia-I in Prevalence of a new genetic group, MEAM-K, of the whitefly Bemisia tabaci (Hemiptera: Aleyrodidae) in Karnataka, India, as evident from mtCOI sequences
Fig. 2b. Phylogenetic tree indicating the Asia-I group, which was the most abundant genetic group in this study.
Fig. 5. Sequence variation among 4 28S in Population genetics of Oligonychus perseae (Acari: Tetranychidae) collected from avocados in Mexico and California
Fig. 5. Sequence variation among 4 28S genotypes identified from Oligonychus perseae populations in California, Mexico, and Costa Rica. Genotypes are named according to 3 genetic clusters identified from cytochrome oxidase subunit 1 (COI) haplotypes (see Fig. 2).
Fig. 3. Sequence variation among 4 internal transcribed spacer 2 in Population genetics of Oligonychus perseae (Acari: Tetranychidae) collected from avocados in Mexico and California
Fig. 3. Sequence variation among 4 internal transcribed spacer 2 (ITS2) genotypes identified from Oligonychus perseae populations in California,Mexico, and Costa Rica. Genotypes are named according to 3 genetic clusters identified from cytochrome oxidase subunit 1 (COI) haplotypes (see Fig. 2).
Fig. 4 in Marked genetic diversity within Blastocystis in Australian wildlife revealed using a next generation sequencing-phylogenetic approach
Fig. 4. Relative abundance of Blastocystis subtypes (STs) in marsupial and deer species. Marsupials are represented by eastern grey kangaroos and wallabies; deer are represented by red, fallow and sambar deer. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
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.