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3,584 results for “genomic analysis”
Figure 6 from: Yang M, Hu B, Zhou L, Liu X, Shi Y, Song L, Wei Y, Cao J (2019) First mitochondrial genome from Yponomeutidae (Lepidoptera, Yponomeutoidea) and the phylogenetic analysis for Lepidoptera. ZooKeys 879: 137-156. https://doi.org/10.3897/zookeys.879.35101
Figure 6 ML tree inferred from RAxML method based on PCG123R dataset. Numbers separated by slash (/) on node represent bootstrap replicates based on PCG123, PCGAA and PCG123R datasets, respectively. The dash (-) represents unrecovered node in ML tree based on the PCG123 or PCGAA dataset.
Figure 7 from: Yang M, Hu B, Zhou L, Liu X, Shi Y, Song L, Wei Y, Cao J (2019) First mitochondrial genome from Yponomeutidae (Lepidoptera, Yponomeutoidea) and the phylogenetic analysis for Lepidoptera. ZooKeys 879: 137-156. https://doi.org/10.3897/zookeys.879.35101
Figure 7 ML tree inferred from IQ-TREE method based on PCG123R dataset. Numbers separated by slash (/) on node represent bootstrap replicates based on PCG123, PCGAA and PCG123R datasets, respectively. The dash (-) represents unrecovered node in ML tree based on the PCG123 or PCGAA dataset.
Figure 5 from: Yang M, Hu B, Zhou L, Liu X, Shi Y, Song L, Wei Y, Cao J (2019) First mitochondrial genome from Yponomeutidae (Lepidoptera, Yponomeutoidea) and the phylogenetic analysis for Lepidoptera. ZooKeys 879: 137-156. https://doi.org/10.3897/zookeys.879.35101
Figure 5 A The overlapping region between atp8 and atp6. The nucleotides colored red indicate the sequence of overlapping region; the nucleotides with green underline indicate partial sequence of the atp8 gene, and the nucleotides with blue underline indicate the partial sequence of the atp6 gene B The intergenic region between nad6 and cob. The microsatellite (TA)n are marked red C The intergenic region between trnQ and nad2D The intergenic region between trnS2 and nad1. The nucleotides colored red indicate the conserved motif sequence E Schematic illustration of the A + T-rich region from all yponomeutoid mitogenomes. The conserved motif ATAG (colored red) and subsequent poly-T stretch (colored green), the conserved motif ATTTA (colored blue) and subsequent (TA)n sequence (colored orange) are emphasized. Dots indicate omitted sequences, and the number of dot is not proportional to nucleotide number of corresponding part.
Figure 4 from: Yang M, Hu B, Zhou L, Liu X, Shi Y, Song L, Wei Y, Cao J (2019) First mitochondrial genome from Yponomeutidae (Lepidoptera, Yponomeutoidea) and the phylogenetic analysis for Lepidoptera. ZooKeys 879: 137-156. https://doi.org/10.3897/zookeys.879.35101
Figure 4 Putative secondary structures of tRNAs from Yponomeuta montanatus mitogenome. The tRNAs are labeled with the abbreviations of their corresponding amino acids. The tRNA arms are illustrated as for trnV. Dashes indicate the Watson-Crick base pairs; dots indicate the wobble GU pairs; and the other non-canonical pairs are not marked. The nucleotides marked indicate the variable sites among published yponomeutoid mitogenomes.
Figure 3 from: Yang M, Hu B, Zhou L, Liu X, Shi Y, Song L, Wei Y, Cao J (2019) First mitochondrial genome from Yponomeutidae (Lepidoptera, Yponomeutoidea) and the phylogenetic analysis for Lepidoptera. ZooKeys 879: 137-156. https://doi.org/10.3897/zookeys.879.35101
Figure 3 Evolutionary rate of each PCG among yponomeutoid mitogenomes. Ka, non-synonymous substitution; Ks, synonymous substitution.
Figure 2 from: Yang M, Hu B, Zhou L, Liu X, Shi Y, Song L, Wei Y, Cao J (2019) First mitochondrial genome from Yponomeutidae (Lepidoptera, Yponomeutoidea) and the phylogenetic analysis for Lepidoptera. ZooKeys 879: 137-156. https://doi.org/10.3897/zookeys.879.35101
Figure 2 Relative synonymous codon usages (RSCU) in PCGs of Yponomeuta montanatus and other published yponomeutoid mitogenomes. Codon families are indicated below the X-axis.
Genomic data used for analysis including treatment with Operon Mapper
<p>Genomic data and their respective treatment by the Operon Mapper webserver used for analysis.</p>
Supporting data and results for manuscript: "Analysis of the limited M. tuberculosis accessory genome reveals potential pitfalls of pan-genome analysis approaches"
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Data from: comparative genomic analysis of Salmonella enterica subsp. enterica serovar Abortusequi
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Gene Ontology Enrichment Analysis of High and Moderate Impact SNPs and InDels in CHMX_Ch1 and QO Genomes
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Genomic analysis of T cell receptors in a cohort of Lynch Syndrome carriers distinguishes pre-malignant and malignant status
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Pan-genomic analysis highlights genes associated with agronomic traits and enhances genomics-assisted breeding in alfalfa
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Data from: Combined analysis of variation in core, accessory and regulatory genome regions provides a super-resolution view into the evolution of bacterial populations
The use of whole-genome phylogenetic analysis has revolutionized our understanding of the evolution and spread of many important bacterial pathogens due to the high resolution view it provides. However, the majority of such analyses do not consider the potential role of accessory genes when inferring evolutionary trajectories. Moreover, the recently discovered importance of the switching of gene regulatory elements suggests that an exhaustive analysis, combining information from core and accessory genes with regulatory elements could provide unparalleled detail of the evolution of a bacterial population. Here we demonstrate this principle by applying it to a worldwide multi-host sample of the important pathogenic E. coli lineage ST131. Our approach reveals the existence of multiple circulating subtypes of the major drug–resistant clade of ST131 and provides the first ever population level evidence of core genome substitutions in gene regulatory regions associated with the acquisition and maintenance of different accessory genome elements.
Genome-wide association analysis reveals QTL and candidate mutations involved in white spotting in cattle
<p><b>Background</b></p> <p>White spotting of the coat is a characteristic trait of various domestic species including cattle and other mammals. It is a hallmark of Holstein-Friesian cattle, and several previous studies have detected genetic loci with major effects for white spotting in animals with Holstein-Friesian ancestry. Here, our aim was to better understand the underlying genetic and molecular mechanisms of white spotting, by conducting the largest mapping study for this trait in cattle, to date.</p> <p><b>Results</b></p> <p>Using imputed whole-genome sequence data, we conducted a genome-wide association analysis in 2,973 mixed-breed cows and bulls. Highly significant quantitative trait loci (QTL) were found on chromosomes 6 and 22, highlighting the well-established coat color genes <i>KIT</i> and <i>MITF</i> as likely responsible for these effects. These results are in broad agreement with previous studies, although we also report a third significant QTL on chromosome 2 that appears to be novel. This signal maps immediately adjacent to the <i>PAX3</i> gene, which encodes a known transcription factor that controls <i>MITF </i>expression and is the causal locus for white spotting in horses. More detailed examination of these loci revealed a candidate causal mutation in <i>PAX3</i> (p.Thr424Met), and another candidate mutation (rs209784468) within a conserved element in intron 2 of <i>MITF</i> transcripts expressed in the skin. These analyses also revealed a mechanistic ambiguity at the chromosome 6 locus, where highly dispersed association signals suggested multiple or multiallelic QTL involving <i>KIT </i>and/or other genes in this region.</p> <p><b>Conclusions</b></p> <p>Our findings extend those of previous studies that reported <i>KIT</i> as a likely causal gene for white spotting, and report novel associations between candidate causal mutations in both the <i>MITF</i> and <i>PAX3</i> genes. The sizes of the effects of these QTL are substantial, and could be used to select animals with darker, or conversely whiter, coats depending on the desired characteristics.</p>
Data from: Genome-scale phylogenetic analysis finds extensive gene transfer among fungi
Although the role of lateral gene transfer is well recognized in the evolution of bacteria, it is generally assumed that it has had less influence among eukaryotes. To explore this hypothesis, we compare the dynamics of genome evolution in two groups of organisms: cyanobacteria and fungi. Ancestral genomes are inferred in both clades using two types of methods: first, Count, a gene tree unaware method that models gene duplications, gains and losses to explain the observed numbers of genes present in a genome; second, ALE, a more recent gene tree-aware method that reconciles gene trees with a species tree using a model of gene duplication, loss and transfer. We compare their merits and their ability to quantify the role of transfers, and assess the impact of taxonomic sampling on their inferences. We present what we believe is compelling evidence that gene transfer plays a significant role in the evolution of fungi.
Genome-wide SNP analysis of male and female rice field frogs, Hoplobatrachus rugulosus, supports a non-genetic sex determination system
<p>Sex determination systems (SDSs) in anurans are diverse and have undergone independent evolutionary transitions among species. The mode of sexual reproduction of the rice field frog (<i>Hoplobatrachus rugulosus</i>), an economically viable edible amphibian species, is not well known. Previous studies have proposed that threshold temperature conditions may determine sex in these frogs. To elucidate the SDS in <i>H. rugulosus</i>, we karyotyped 10 male and 12 female frogs, and performed fluorescence <i>in situ</i> hybridization combined with<b> </b>sequencing analyses using DArTseq™. Our results revealed a highly conserved karyotype with no sex chromosome heteromorphism, and the sequencing analyses did not identify any consistent sex-linked loci, supporting the hypothesis of temperature-dependent sex determination. The results of this study, and others, on SDSs in the rice field frog and related species also provides support for the theory that heteromorphic sex chromosomes may lead to an evolutionary trap that prevents variable SDSs. These findings add important information to the body of knowledge on <i>H. rugulosus</i> and are likely to have a significant impact on the productivity and economic success of rice field frog farming.</p>
Data from: Understanding the genomic basis of adaptive response to variable osmotic niches in freshwater prawns: a comparative intraspecific RNA-Seq analysis of Macrobrachium australiense
Understanding the molecular basis of adaptive response to variable environmental conditions is a central goal of evolutionary biology. Here we sought to identify potential outlier SNPs (single nucleotide polymorphisms) in three wild populations of a freshwater prawn (Macrobrachium australiense) that are exposed to differing osmotic niches by using a comparative transcriptomics approach. De novo assembly of approximately 542 million (75 nt) pair end reads collected from 10 individuals revealed 123,396 longer contigs/transcripts of variable length, that showed 97.38% transcriptome assembly completeness. Differential gene expression (DGE) analysis of major osmoregulatory genes revealed that Calreticulin, Na+/H+ exchanger and V-type (H+) ATPase showed the highest expression levels in the Blunder Creek (low ionic) population, while Crustacean cardiovascular peptide (CCP), Na+/K+-ATPase, Na+/K+/2Cl- Co-transporter (NKCC) and Na+/HCO3 exchanger showed the highest expression levels in the Bulimba Creek (higher ionic) population. In total, 16 gene ontology (GO) term categories were functionally enriched among the three studied populations. We identified 4144 raw and 835 high quality filtered SNPs in the three M. australiense populations, of which 84 SNPs were identified as outliers. Outliers were detected in 4 important osmoregulatory genes that include: Calreticulin, Na+/H+ exchanger, Na+/K+-ATPase and V-type-(H+)-ATPase. All outliers in the osmoregulatory genes were located in non-coding regulatory regions (untranslated regions, UTRs) of the gene. We hypothesize that the outlier SNPs identified here in M. australiense populations exposed naturally to different osmotic conditions influence specific gene expression patterns that allow individuals to respond to local environmental conditions.
Data from: Comparative analysis of 2D and 3D distance measurements to study spatial genome organization
The spatial organization of genomes is non-random, cell-type specific, and has been linked to cellular function. The investigation of spatial organization has traditionally relied extensively on fluorescence microscopy. The validity of the imaging methods used to probe spatial genome organization often depends on the accuracy and precision of distance measurements. Imaging-based measurements may either use 2 dimensional datasets or 3D datasets which include the z-axis information in image stacks. Here we compare the suitability of 2D vs 3D distance measurements in the analysis of various features of spatial genome organization. We find in general good agreement between 2D and 3D analysis with higher convergence of measurements as the interrogated distance increases, especially in flat cells. Overall, 3D distance measurements are more accurate than 2D distances, but are also more susceptible to noise. In particular, z-stacks are prone to error due to imaging properties such as limited resolution along the z-axis and optical aberrations, and we also find significant deviations from unimodal distance distributions caused by low sampling frequency in z. These deviations are ameliorated by significantly higher sampling frequency in the z-direction. We conclude that 2D distances are preferred for comparative analyses between cells, but 3D distances are preferred when comparing to theoretical models in large samples of cells. In general and for practical purposes, 2D distance measurements are preferable for many applications of analysis of spatial genome organization.
Figure 2 in The complete mitochondrial genome of Parnassius actius (Lepidoptera: Papilionidae: Parnassinae) with the related phylogenetic analysis
Figure 2. Codon distribution in nine Parnassiinae mitogenome (Numbers to the left refer to the total number of codons; CDspT— codons per thousand codons; codon families are provided on the x axis).
Genomes and annotation files for comparative circularome analysis
<p>Part of a manuscript on eccDNAs in Magnaporthe oryzae</p>
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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.