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1,337 results for “genetic variation”
Gene expression plasticity, genetic variation and fatty acid remodelling in divergent populations of a tropical bivalve species: lipid profiles
<p><span>Ocean warming challenges marine organisms' resilience, especially for species experiencing temperatures close to their upper thermal limits. A potential increase in thermal tolerance might significantly reduce the risk of population decline, which is intrinsically linked to variability in local habitat temperatures.</span></p> <p><span>Our goal was to assess the plastic and genetic potential of response to elevated temperatures in a tropical bivalve model, <em>Pinctada margaritifera</em>. We benefit from two ecotypes for which local environmental conditions are characterized by either large diurnal variations in the tide-pools (Marquesas archipelago) or lower mean temperature with stable to moderate seasonal variations (Gambier archipelago).</span><br><br><span>We explored the physiological basis of individual responses to elevated temperature<em>, </em>genetic divergence as well as plasticity and acclimation by combining lipidomic and transcriptomic approaches.</span><br><br><span>We show that <em>P. margaritifera</em> has certain capacities to adjust to long-term elevated temperatures that was thus far largely underestimated. Genetic variation across populations overlaps with gene expression and involves the mitochondrial respiration machinery, a central physiological process that contributes to species thermal sensitivity and their distribution ranges.</span><br><br><span>Our results present evidence for acclimation potential in <em>P. margaritifera</em> and urge for longer term studies to assess populations resilience in face of climate change.</span></p>
Additive genetic variation, but not temperature, influences warning signal expression in Amata nigriceps moths (Lepidoptera: Arctiinae)
<p>Many aposematic species show variation in their colour patterns even though selection by predators is expected to stabilise warning signals towards a common phenotype. Warning signal variability can be explained by trade-offs with other functions of colouration, such as thermoregulation, that may constrain warning signal expression by favouring darker individuals. Here, we investigated the effect of temperature on warning signal expression in aposematic <em>Amata nigriceps</em> moths that vary in their black and orange wing patterns. We sampled moths from two flight seasons that differed in the environmental temperatures and also reared different families under controlled conditions at three different temperatures. Against our prediction that lower developmental temperatures would reduce the warning signal size of the adult moths, we found no effect of temperature on warning signal expression in either wild or laboratory-reared moths. Instead, we found sex- and population-level differences in wing patterns. Our rearing experiment indicated that ~70% of the variability in the trait is genetic but understanding what signalling and non-signalling functions of wing colouration maintain the genetic variation requires further work. Our results emphasise the importance of considering both genetic and plastic components of warning signal expression when studying intraspecific variation in aposematic species.</p>
Can disease resistance evolve independently at different ages? Genetic variation in age-dependent resistance to disease in three wild plant species
<p>1. Juveniles are typically less resistant (more susceptible) to infectious disease than adults, and this difference in susceptibility can help fuel the spread of pathogens in age-structured populations. However evolutionary explanations for this variation in resistance across age remain to be tested.</p> <p>2. One hypothesis is that natural selection has optimized resistance to peak at ages where disease exposure is greatest. A central assumption of this hypothesis is that hosts have the capacity to evolve resistance independently at different ages. This would mean that hosts populations have a) standing genetic variation in resistance at both juvenile and adult stages, and b) that this variation is not strongly correlated between age-classes so that selection acting at one age does not produce a correlated response at the other age</p> <p>3. Here we evaluated the capacity of three wild plant species (Silene latifolia, S. vulgaris, and Dianthus pavonius) to evolve resistance to their anther-smut pathogens (Microbotryum fungi), independently at different ages. The pathogen is pollinator-transmitted, and thus exposure risk is considered to be highest at the adult flowering stage.</p> <p>4. Within each species we grew families to different ages, inoculated individuals with anther smut, and evaluated the effects of age, family and their interaction on infection.</p> <p>5. In two of the plant species, S. latifolia and D. pavonius, resistance to smut at the juvenile stage was not correlated with resistance to smut at the adult stage. In all three species, we show there are significant age*family interaction effects, indicating that age-specificity of resistance varies among the plant families.</p> <p>6. Synthesis: These results indicate that different mechanisms likely underlie resistance at juvenile and adult stages and support the hypothesis that resistance can evolve independently in response to differing selection pressures as hosts age. Taken together our results provide new insight into the structure of genetic variation in age-dependent resistance in three well-studied wild host-pathogen systems.</p>
Alternative splicing and genetic variation of MHC-E: Implications for rhesus cytomegalovirus-based vaccines
<p>We used long-read sequencing to interrogate rhesus macaque (RM) MHC-E (Mamu-E) alternative splicing and genetic variations. Full-length Mamu-E RNA isoforms were recovered using the PacBio Iso-Seq method. Incomplete 5' ends of Mamu-E isoforms were confirmed using Sanger sequencing, where we identified three additional isoforms. Full-length human MHC-E (HLA-E) isoforms were also recovered using the PacBio Iso-Seq method. Isoform sequences and annotations are provided for both Mamu-E and HLA-E in addition to Mamu-E Sanger sequencing data. HLA-E annotations are reported using the hg38 reference, while Mamu-E annotations are shown using rhesus MHC Class I and II assemblies previously generated using Bacterial Artificial Cloning (BAC) technology (https://www.ncbi.nlm.nih.gov/nuccore/AC148696.1).</p> <p>Using PacBio Long Amplicon Analysis, we sequenced complete Mamu-E coding regions of 59 RMs and additionally captured 3' UTR polymorphism using mRNA-seq haplotype phasing analysis. The complete genotyping data for these animals are provided as well as animal metadata. Genotyping data is shown using the Mamu-E canonical isoform (Mamu-E1 from Iso-Seq analysis) as reference.</p>
Figure 2 in Variations in heterochromatin content reveal important polymorphisms for studies of genetic improvement in garlic (Allium sativum L.)
Figure 2. Idiograms of the accessions "Sussuapara - PI" (A), "Santo Antônio de Lisboa - PI" (B), "Catetinho do Paraná 1254" (C), "Branco Mineiro - PI" (D), "Cateto Roxo 99" (E), "Roxo de Minas" (F), and "Sergipe" (G). Yellow dash and circle represent the CMA+/DAPI- band. Chromosomal order (CO), chromosome morphology (CM), metacentric (M), submetacentric (SM), short arm (p), and long arm (q). Vertical bar in karyogram and ideogram = 10 µm.
Figure 1. Allium sativum L in Variations in heterochromatin content reveal important polymorphisms for studies of genetic improvement in garlic (Allium sativum L.)
Figure 1. Allium sativum L.cytological data obtained by conventional Giemsa staining.Prophase and interphase nucleus (A), prometaphase (B), and metaphase (C) obtained with the use of antimitotic. Mitotic cycle is shown in d-f: anaphase (D), end of anaphase (E), and telophase (F). Dots and red arrow indicate the distended nucleolar organiser region (NOR). Bar = 10 µm.
Figure 3 in Genetic variation within a species of parasitic nematode, Skrjabingylus chitwoodorum, in skunks
Figure 3: Maximum likelihood phylogenetic tree of 492 base pair fragment of the cytochrome oxidase I gene for 44 samples of Skrjabingylus. Maximum likelihood analysis was performed using the best-fitting model, Hasegawa-Kishino-Yano of DNA substitution with Gamma distribution. Bootstrap values are based on 1000 replicates and values ≥70 are shown on branches. Number with prefix ASK identifies the specific host from which the sample was collected. Prefix KP is a Genbank accession number.
Figure 4 in Genetic variation within a species of parasitic nematode, Skrjabingylus chitwoodorum, in skunks
Figure 4: Median joining network showing the relationships among haplotypes of 44 samples of Skrjabingylus chitwoodorum from hosts Mephitis mephitis and Spilogale putorius interrupta using COI mtDNA. Sizes of solid black circles correlate to shared haplotypes among multiple counties. Small open circles represent hypothetical haplotypes and ticks on branches represent number of mutational steps.
Figure 2 in Genetic variation within a species of parasitic nematode, Skrjabingylus chitwoodorum, in skunks
Figure 2: Texas map showing the 25 counties represented in the analysis of Skrjabingylus within Mephitis mephitis hosts. Sample size included if greater than one.
Figure 1 in Genetic variation within a species of parasitic nematode, Skrjabingylus chitwoodorum, in skunks
Figure 1: Life cycle of Skrjabingylus chitwoodorum in Mephitis mephitis. Large gray arrows correspond to the movement of Skrjabingylus to an intermediate or paratenic host. Large black arrows correspond to the movement to the definitive host. Smaller arrows correspond to a molt occurring and the larva progressing to the next juvenile phase.
Fig. 3 in Haplotype variation in the Physa acuta group (Basommatophora): genetic diversity and distribution in Serbia Abstract
Fig. 3: Haplotype networks from 43 Physa acuta group specimens, obtained using statistical parsimony (TCS). Circles represent specific haplotypes; the size of the circles reflects the number of individuals with a particular haplotype (not to scale); the dots between the circles represent mutational steps.
Fig. 2 in Haplotype variation in the Physa acuta group (Basommatophora): genetic diversity and distribution in Serbia Abstract
Fig. 2: Phylogenetic trees based on mt16S rDNA, obtained using the Maximum Likelihood (ML) method. Bootstrap values are indicated below the branches. Scale bar indicates the number of substitutions per site.
Fig. 2 in Intraspecific Genetic Variation And Phylogeography Of The Oak Gallwasp Andricus Caputmedusae (Hymenoptera: Cynipidae): Effects Of The Anatolian Diagonal
Fig. 2. UPGMA dendrogram of A. caputmedusae populations (see Fig. 1 and Table 1) based on pair wise estimates of percentage sequence divergence. A. q. H-1, A. q. H-2 are the haplotypes of A. quercustozae and A. l. H is the haplotype of A. lucidus gall wasp species used as outgroups. Numbers above branches represent the bootstrap values obtained from 1000 replicates of the restriction fragment data between the haplotypes. Support
Fig. 4 in Intraspecific Genetic Variation And Phylogeography Of The Oak Gallwasp Andricus Caputmedusae (Hymenoptera: Cynipidae): Effects Of The Anatolian Diagonal
Fig. 4. Unrooted Dollo parsimony majority-rule consensus tree of mtDNA haplotypes. Numbers at nodes indicates bootstrap values. Support values <50% are not represented
Fig. 1 in Intraspecific Genetic Variation And Phylogeography Of The Oak Gallwasp Andricus Caputmedusae (Hymenoptera: Cynipidae): Effects Of The Anatolian Diagonal
Fig. 1. Geographic distribution of the twenty six Andricus caputmedusae populations used in the present study and the location of the Anatolian Diagonal (indicated by dashed line) shown in a topo-
Figure 3 in Infraspecific genetic variation and population structure of Salvia nemorosa L. (Lamiaceae) in Iran
Figure 3. PCoA plot of the studied populations based on ISSR data (population numbers are according to Table 1).
Figure 2 in Infraspecific genetic variation and population structure of Salvia nemorosa L. (Lamiaceae) in Iran
Figure 2. MDS plot of the studied populations based on ISSR data (population numbers are according to Table 1).
Figure 4 in Infraspecific genetic variation and population structure of Salvia nemorosa L. (Lamiaceae) in Iran
Figure 4. NJ tree of S. nemorosa populations based on ISSR results (population numbers are according to Table 1).
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).
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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.