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788 results for “genotypic data”
Data for: Birth order as a source of within-genotype diversification in the clonal duckweed, Spirodela polyrhiza (Araceae: Lemnoideae)
<p>Organismal persistence attests to adaptive response to environmental variation. Diversification bet hedging, in which risk is reduced at the cost of expected fitness, is increasingly recognized as an adaptive response, yet mechanisms by which a single genotype generates diversification remain obscure. The clonal greater duckweed, <i>Spirodela polyrhiza </i>(L.), facultatively expresses a seed-like but vegetative form, the "turion", that allows survival through otherwise lethal conditions. Turion reactivation phenology is a key fitness component, yet little is known about turion reactivation phenology in the field, or sources of variation. Here, using floating traps deployed in the field, we find a remarkable extent of variation in natural reactivation phenology that cannot be explained solely by spring cues, occurring over a period of at least 200 days. Under controlled laboratory conditions, we find support for the hypothesis that turion phenology is influenced jointly by phenotypic plasticity to temperature and diversification within clones. Turion "birth order" consistently accounted for a difference in reactivation time of 46 days at temperatures between 10° and 18°C, with early birth-order turions reactivating more rapidly than late birth-order turions. These results should motivate future work to formally evaluate turion phenology variance as a bet-hedging trait.</p>
Raw data used in: Variations in effects of ectosymbiotic microbes on the growth rates among different species and genotypes of Daphnia fed different algal diets
<p>Several recent studies have shown that ectosymbiotic bacterial microbiota, including gut microbes, affect the growth and reproduction of <span class="MsoSubtleEmphasis">Daphnia</span>, a key organism in lake ecosystems. However, these studies examined specific species, such as the model organism, <i>D. magna,</i> and used green algae as food. It is unclear if symbiotic bacteria affect fitness in other <span class="MsoSubtleEmphasis">Daphnia</span> species common in lakes and ponds in Japan. In this study, we examined the growth rates of sterilized individuals of two <i>D. pulex</i> genotypes with <i>D. magna</i> using the green algae <i>Scenedesmus</i> and the diatom <i>Cyclotella</i> as algal diets. In addition, we examined the growth rate of the sterilized <span class="MsoSubtleEmphasis">Daphnia</span><i> pulex</i> individuals infected by <i>Limnohabitans</i> spp., previously reported to promote the fitness of <i>D. magna</i> as ectosymbiotic bacteria. We found that the effects of ectosymbiotic bacteria on growth rate differed not only between different genotypes of <i>D. pulex</i> but also between individuals fed the different algal diets. The results suggest that the genotype- and diet-specific differences in fitness-dependency on the ectosymbiotic microbiota can be factors affecting the genetic structures of <i>D. pulex</i> populations.</p>
Data from: Whole-genome duplication and host genotype affect rhizosphere microbial communities
<p>The composition of microbial communities found in association with plants is influenced by host phenotype and genotype. Yet, the ways in which specific genetic architectures of host plants shape microbiomes is unknown. Genome duplication events are common in the evolutionary history of plants, influence many important plant traits, and, thus, they may affect associated microbial communities. Using experimentally induced whole genome duplication (WGD), we tested the effect of WGD on rhizosphere bacterial communities in<i> Arabidopsis thaliana</i>. We performed 16S rRNA amplicon sequencing to characterize differences between microbiomes associated with specific host genetic backgrounds (Columbia <i>vs</i>. Landsberg) and ploidy levels (diploid <i>vs</i>. tetraploid). We modeled relative abundances of bacterial taxa using the Dirichlet and multinomial distributions via a hierarchical Bayesian approach. We found that host genetic background and ploidy level affected rhizosphere community composition. We then tested to what extent microbiomes derived from a specific genetic background or ploidy level affected plant performance by inoculating sterile seedlings with microbial communities harvested from a prior generation. We found a negative effect of the tetraploid Columbia microbiome on growth of all four plant genetic backgrounds. These findings suggest an interplay between host genetic architecture and bacterial community assembly with potential ramifications for host fitness. Moreover, we uncovered an intriguing role of ploidy-level for shaping plant microbiomes. Given the prevalence of ploidy-level variation in both wild and managed plant populations, the effects on microbiomes of this aspect of host genetic architecture could be a widespread driver of differences in plant microbiomes.</p>
Data from: Unlocking the story in the swab: A new genotyping assay for the amphibian chytrid fungus Batrachochytrium dendrobatidis
One of the most devastating emerging pathogens of wildlife is the chytrid fungus, Batrachochytrium dendrobatidis (Bd), which affects hundreds of amphibian species around the world. Genomic data from pure Bd cultures has advanced our understanding of Bd phylogenetics, genomic architecture, and mechanisms of virulence. However pure cultures are laborious to obtain and whole genome sequencing is comparatively expensive, so relatively few isolates have been genetically characterized. Thus we still know little about the genetic diversity of Bd in natural systems. The most common non-invasive method of sampling Bd from natural populations is to swab amphibian skin. Hundreds of thousands of swabs have been collected from amphibians around the world, but Bd DNA collected via swabs is often low in quality and/or quantity. In this study, we developed a custom Bd genotyping assay using the Fluidigm Access Array platform to amplify 192 carefully-selected regions of the Bd genome. We obtained robust sequence data for pure Bd cultures and field-collected skin swabs. This new assay has the power to accurately discriminate among the major Bd clades, recovering the basic tree topology previously revealed using whole genome data. Additionally, we established a critical value for initial Bd load for swab samples (150 Bd genomic equivalents) above which our assay performs well. By leveraging advances in microfluidic multiplex PCR technology and the globally distributed resource of amphibian swab samples, non-invasive skin swabs can now be used to address critical spatial and temporal questions about Bd and its effects on declining amphibian populations.
Data from: Differences in Al sensitivity affect establishment of Populus genotypes on acidic forest land
Forest lands hold great potential for Populus plantations, but in native boreal forests, soils normally have low pH and thus higher levels of aluminum ions (Al3+ and hydroxides). Aluminum (Al) is one of the major factors limiting plant growth on these soils by inhibiting root growth, thus reducing water and nutrient uptake and slowing growth. There is a large variation in Al resistance both among and within species. In this study, growth responses of greenhouse-grown hybrid aspen (P. tremula × tremuloides) and poplar (P. trichocarpa hybrids) were monitored in relation to changes in Al concentrations. In quartz sand, hybrid aspen was more tolerant to exogenous application of Al than P. trichocarpa hybrids. This difference in Al-tolerance was further confirmed by hematoxylin staining of the roots, with hybrid aspen displaying less staining after Al treatment than poplar clones. When planted on forest land with low pH, hybrid aspen increased growth after planting and showed low mortality. This was not the case for poplar clones; plant height decreased after planting and mortality increased. Together, our results suggest that differences in initial growth and survival on forest land among hybrid aspen and the tested poplar clones may be connected to differences in Al tolerance. Our findings that staining with hematoxylin can identify Al-tolerant Populus genotypes may help identify Al-tolerant genotypes suitable for forest land.
Data from: Connecting thermal performance curve variation to the genotype: a multivariate QTL approach
Thermal performance curves (TPCs) are continuous reaction norms that describe the relationship between organismal performance and temperature and are useful for understanding trade-offs involved in thermal adaptation. While thermal trade-offs such as those between generalists and specialists or between hot- and cold-adapted phenotypes are known to be genetically variable and evolve during thermal adaptation, little is known of the genetic basis to TPCs – specifically, the loci involved and the directionality of their effects across different temperatures. To address this, we took a multivariate approach, mapping QTL for locomotor activity TPCs in the fly, Drosophila serrata using a panel of 76 recombinant inbred lines. The distribution of additive genetic (co)variance in the mapping population was remarkably similar to the distribution of mutational (co)variance for these traits. We detected 11 TPC-QTLs in females and 4 in males. Multivariate QTL effects were closely aligned with the major axes genetic (co)variation between temperatures; most QTL effects corresponded to variation for either overall increases or decreases in activity with a smaller number indicating possible trade-offs between activity at high and low temperatures. QTLs representing changes in curve shape such as the 'generalist-specialist' trade-off, thought key to thermal adaptation, were poorly represented in the data. We discuss these results in light of genetic constraints on thermal adaptation.
Data from: Establishment and maintenance of aphid endosymbionts after horizontal transfer is dependent on host genotype
Animal-associated microbial communities have important effects on host phenotypes. Individuals within and among species differ in the strains and species of microbes that they harbour, but how natural selection shapes the distribution and abundance of symbionts in natural populations is not well understood. Symbionts can be beneficial in certain environments but also impose costs on their hosts. Consequently, individuals that can or cannot associate with symbionts will be favoured under different ecological circumstances. As a result, we predict that individuals within a species vary in terms of how well they accept and maintain symbionts. In pea aphids, the frequency of endosymbionts varies among host-plant-associated populations ('biotypes'). We show that aphid genotypes from different biotypes vary in how well they accept and maintain symbionts after horizontal transfer. We find that aphids from biotypes that frequently harbour symbionts are better able to associate with novel symbionts than those from biotypes that less frequently harbour symbionts. Intraspecific variation in the ability of hosts to interact with symbionts is an understudied factor explaining patterns of host–symbiont association.
Data from: Proteomic analysis of barley mapping population subjected to drought identifies proteins with genotype×environment interaction and pQTLs
Drought is one of the major abiotic stresses negatively influencing crop yield and is a serious issue in modern agriculture. To achieve further substantial crop improvements in terms of drought resistance it is necessary to incorporate scientific results into breeding strategies. However, most of the data on plant drought responses arises mostly from small-scale studies and, therefore, its use in breeding programs is very limited. Here, we present the results of the large-scale proteomic analysis performed on barley recombinant inbred lines (RILs) and their parental genotypes subjected to drought, applied shortly before tillering. The conducted proteomic analyses enabled us to monitor drought-induced proteome changes in leaf and root tissue, and to identify proteins that responded to drought in a genotype-specific manner, for instance Rubisco activase, luminal binding protein, phosphoglycerate mutase, glutathione S-transferase, heat shock proteins as well as enzymes involved in phenylpropanoid biosynthesis. We also demonstrated feasibility of incorporating proteomic data resulting from large-scale study into genetic linkage analysis, which constitutes a fundament in biotechnology-driven breeding strategies.
Data from: Genotype-by-genotype interactions between an insect and its pathogen
Genotype-by-genotype (G×G) interactions are an essential requirement for the coevolution of hosts and parasites, but have only been documented in a small number of animal model systems. G×G effects arise from interactions between host and pathogen genotypes, such that some pathogen strains are more infectious in certain hosts and some hosts are more susceptible to certain pathogen strains. We tested for G×G interactions in the gypsy moth (Lymantria dispar) and its baculovirus. We infected 21 full-sib families of gypsy moths with each of 16 isolates of baculovirus and measured the between-isolate correlations of infection rate across host families for all pairwise combinations of isolates. Mean infectiousness varied among isolates and disease susceptibility varied among host families. Between-isolate correlations of infection rate were generally less than one, indicating nonadditive effects of host and pathogen type consistent with G×G interactions. Our results support the presence of G×G effects in the gypsy moth–baculovirus interaction and provide empirical evidence that correlations in infection rates between field-collected isolates are consistent with values that mathematical models have previously shown to increase the likelihood of pathogen polymorphism.
Data from: Reconstruction of paternal genotypes over multiple breeding seasons reveals male green turtles do not breed annually
For species of conservation concern, knowledge of key life-history and demographic components, such as the number and sex ratio of breeding adults, is essential for accurate assessments of population viability. Species with temperature-dependent sex determination can produce heavily biased primary sex ratios, and there is concern that adult sex ratios may be similarly skewed or will become so as a result of climate warming. Prediction and mitigation of such impacts are difficult when life-history information is lacking. In marine turtles, owing to the difficultly in observing males at sea, the breeding interval of males is unknown. It has been suggested that male breeding periodicity may be shorter than that of females, which could help to compensate for generally female-biased sex ratios. Here we outline how the use of molecular-based paternity analysis has allowed us, for the first time, to assess the breeding interval of male marine turtles across multiple breeding seasons. In our study rookery of green turtles (Chelonia mydas), 97% of males were assigned offspring in only one breeding season within the 3-year study period, strongly suggesting that male breeding intervals are frequently longer than 1 year at this site. Our results also reveal a sex ratio of breeding adults of at least 1.3 males to each female. This study illustrates the utility of molecular-based parentage inference using reconstruction of parental genotypes as a method for monitoring the number and sex ratio of breeders in species where direct observations or capture are difficult.
Data from: Genotyping-by-sequencing for Populus population genomics: an assessment of genome sampling patterns and filtering approaches
Continuing advances in nucleotide sequencing technology are inspiring a suite of genomic approaches in studies of natural populations. Researchers are faced with data management and analytical scales that are increasing by orders of magnitude. With such dramatic advances comes a need to understand biases and error rates, which can be propagated and magnified in large-scale data acquisition and processing. Here we assess genomic sampling biases and the effects of various population-level data filtering strategies in a genotyping-by-sequencing (GBS) protocol. We focus on data from two species of Populus, because this genus has a relatively small genome and is emerging as a target for population genomic studies. We estimate the proportions and patterns of genomic sampling by examining the Populus trichocarpa genome (Nisqually-1), and demonstrate a pronounced bias towards coding regions when using the methylation-sensitive ApeKI restriction enzyme in this species. Using population-level data from a closely related species (P. tremuloides), we also investigate various approaches for filtering GBS data to retain high-depth, informative SNPs that can be used for population genetic analyses. We find a data filter that includes the designation of ambiguous alleles resulted in metrics of population structure and Hardy-Weinberg equilibrium that were most consistent with previous studies of the same populations based on other genetic markers. Analyses of the filtered data (27,910 SNPs) also resulted in patterns of heterozygosity and population structure similar to a previous study using microsatellites. Our application demonstrates that technically and analytically simple approaches can readily be developed for population genomics of natural populations.
Data from: Hepatitis B virus sero-profiles and genotypes in HIV-1 infected and uninfected injection and non-injection drug users from coastal Kenya
Background: Information about HBV sero-markers, infection stages and genotypes in HIV-1 infected and uninfected injection and non-injection drug users (IDUs) in Kenya remains elusive. Methods: A cross-sectional study examining HBV sero-marker, infection stages and genotypes was conducted among HIV-1 infected and uninfected, respectively, IDUs (n = 157 and n = 214) and non-IDUs (n = 139 and n = 48), and HIV-1 uninfected non-drug using controls (n = 194) from coastal, Kenya. HBV sero-marker and infection stages were based on HBV 5-panel rapid test plasma sero-reactivity. DNA was extracted from acute and chronic plasma samples and genotypes established by nested-PCR and direct sequencing. Results: HBsAg positivity was higher in HIV-1 infected IDUs (9.6 %) relative to HIV-1 uninfected IDUs (2.3 %), HIV-1 infected non-IDUs (3.6 %), HIV-1 uninfected non-IDUs (0.0 %) and non-drug users (2.6 %; P = 0.002). Contrastingly, HBsAb positivity was higher in HIV-1 uninfected IDUs (14.6 %) and non-IDUs (16.8) in comparison to HIV-1 infected IDUs (8.3 %), and non-IDUs (8.6 %), and non-drug users (8.2 %; P = 0.023). HBcAb positivity was higher in HIV-1 infected IDUs (10.2 %) compared to HIV-1 uninfected IDUs (3.3 %), HIV-1 infected non-IDUs (6.5 %), HIV-1 uninfected non-IDUs (2.1 %) and non-drug users (4.6 %; P = 0.038). Acute (5.7 %, 1.4 %, 0.0 %, 0.0 % and 1.5 %) and chronic (5.1 %, 0.9 %, 3.6 %, 0.0 % and 1.5 %) stages were higher in HIV-1 infected IDUs, compared to HIV-1 uninfected IDUs, HIV-1 infected and uninfected non-IDUs and non-drug users, respectively. However, vaccine type response stage was higher in HIV-1 uninfected IDUs (15.4 %) relative to HIV-1 infected IDUs (6.4 %), and HIV-1 infected (6.5 %), and uninfected (10.4 %) non-IDUs, and non-drug users (5.7 %; P = 0.003). Higher resolved infection rates were also recorded in HIV-1 uninfected IDUs (11.2 %) compared to HIV-1 infected IDUs (8.3 %), and HIV-1 infected (7.2 %), uninfected (6.3 %) non-IDUs, and non-drug users (6.7 %; P = 0.479), respectively. Only A1 genotype showing minimal diversity was detected among the study participants. Conclusion: HBV sero-markers and infection staging are valuable in diagnosis and genotyping of HBV infections. Among IDUs, higher HBsAg and HBcAb positivity in HIV-1 infected and higher HBsAb positivity in HIV-1 negative IDUs suggests frequent exposure. Additionally, HBV genotype A is the dominant circulating genotype in both high and low risk populations of Kenya.
Data from: Genomic prediction accuracies in space and time for height and wood density of Douglas-fir using exome capture as the genotyping platform
Background Genomic selection (GS) can offer unprecedented gains, in terms of cost efficiency and generation turnover, to forest tree selective breeding; especially for late expressing and low heritability traits. Here, we used: 1) exome capture as a genotyping platform for 1372 Douglas-fir trees representing 37 full-sib families growing on three sites in British Columbia, Canada and 2) height growth and wood density (EBVs), and deregressed estimated breeding values (DEBVs) as phenotypes. Representing models with (EBVs) and without (DEBVs) pedigree structure. Ridge regression best linear unbiased predictor (RR-BLUP) and generalized ridge regression (GRR) were used to assess their predictive accuracies over space (within site, cross-sites, multi-site, and multi-site to single site) and time (age-age/ trait-trait). Results The RR-BLUP and GRR models produced similar predictive accuracies across the studied traits. Within-site GS prediction accuracies with models trained on EBVs were high (RR-BLUP: 0.79–0.91 and GRR: 0.80–0.91), and were generally similar to the multi-site (RR-BLUP: 0.83–0.91, GRR: 0.83–0.91) and multi-site to single-site predictive accuracies (RR-BLUP: 0.79–0.92, GRR: 0.79–0.92). Cross-site predictions were surprisingly high, with predictive accuracies within a similar range (RR-BLUP: 0.79–0.92, GRR: 0.78–0.91). Height at 12 years was deemed the earliest acceptable age at which accurate predictions can be made concerning future height (age-age) and wood density (trait-trait). Using DEBVs reduced the accuracies of all cross-validation procedures dramatically, indicating that the models were tracking pedigree (family means), rather than marker-QTL LD. Conclusions While GS models' prediction accuracies were high, the main driving force was the pedigree tracking rather than LD. It is likely that many more markers are needed to increase the chance of capturing the LD between causal genes and markers.
Data from: A high-density exome capture genotype-by-sequencing panel for forestry breeding in Pinus radiata
Development of genome-wide resources for application in genomic selection or genome-wide association studies, in the absences of full reference genomes, present a challenge to the forestry industry, where longer breeding cycles could benefit from the accelerated selection possible through marker-based breeding value predictions. In particular, large conifer megagenomes require a strategy to reduce complexity, whilst ensuring genome-wide coverage is achieved. Using a transcriptome-based reference template, we have successfully developed a high density exome capture genotype-by-sequencing panel for radiata pine (Pinus radiata D.Don), capable of capturing in excess of 80,000 single nucleotide polymorphism (SNP) markers with a minor allele frequency above 0.03 in the population tested. This represents approximately 29,000 gene models from a core set of 48,914 probes. A set of 704 SMP markers capable of pedigree reconstruction and differentiating individual genotypes were tested within two full-sib mapping populations. While as few as 70 markers could reconstruct parentage in almost all cases, the impact of missing genotypes was noticeable in several offspring. Therefore, sets of 60 sets of 110 randomly selected SNP markers were compared for both parentage reconstruction and clone differentiation. The performance in parentage reconstruction showed little variation over 60 iterations. However, there was notable variation in discriminatory power between closely related individuals, indicating a higher density SNP marker panel may be required to elucidate hidden relationships in complex pedigrees.
Data from: Finding the right coverage: The impact of coverage and sequence quality on SNP genotyping error rates
Restriction-enzyme-based sequencing methods enable the genotyping of thousands of single nucleotide polymorphism (SNP) loci in non-model organisms. However, in contrast to traditional genetic markers, genotyping error rates in SNPs derived from restriction-enzyme-based methods remain largely unknown. Here, we estimated genotyping error rates in SNPs genotyped with double digest RAD sequencing from Mendelian incompatibilities in known mother-offspring dyads of Hoffman's two-toed sloth (Choloepus hoffmanni) across a range of coverage and sequence quality criteria, for both reference-aligned and de novo-assembled datasets. Genotyping error rates were more sensitive to coverage than sequence quality and low coverage yielded high error rates, particularly in de novo-assembled datasets. For example, coverage ≥5 yielded median genotyping error rates of ≥0.03 and ≥0.11 in reference-aligned- and de novo-assembled datasets, respectively. Genotyping error rates declined to ≤0.01 in reference-aligned datasets with a coverage >30, but remained >0.04 in the de novo-assembled datasets. We observed approximately 10- and 13-fold declines in the number of loci sampled in the reference-aligned and de novo-assembled datasets when coverage was increased from >5 to >30 at quality score ≥30, respectively. Finally, we assessed the effects of genotyping coverage on a common population genetic application, parentage assignments, and showed that the proportion of incorrectly assigned maternities was relatively high at low coverage. Overall, our results suggest that the tradeoff between sample size and genotyping error rates be considered prior to building sequencing libraries, reporting genotyping error rates become standard practice, and that effects of genotyping errors on inference be evaluated in restriction-enzyme-based SNP studies.
Data from: High genotypic diversity and strong spatial structure in populations of Trifolium alpestre with low seed production
The studies on clonal plant populations indicate that the proportion between clonal and sexual reproduction may be highly variable, depending on the biological characteristics of species and the ecological conditions of habitats. We focused on the genotypic diversity of Trifolium alpestre populations in Estonia. We assayed the genetic diversity, spatial genotypic structure and diversity with the use of allozyme markers. Populations revealed high levels of genotypic diversity and showed strong spatial structure of MLGs. The values of genetic diversity were moderately high. Spatially aggregated, identical genotypes spread up to 15 meters along the linear transects and in 4 m2 plots indicate extensive clonal propagation in populations. However, numerous unique and small-sized clones in transects and quadrates reflect significant contribution from the sexual reproduction. The spatially and temporarily stochastic soil disturbances have evidently opened new opportunities for the successful sexual reproduction from the permanent soil seed bank and have thus avoided the losses of genotypic and genetic diversity. The seed production in all populations during the three study years was low, in average up to 1.5-2.4 seeds per shoot. The almost total lack of seed set from all 57 bagged flower heads of genets grown in a common garden indicates that T. alpestre needs pollinators for the seed production.
Data from: Field measurements of genotype by environment interaction for fitness caused by spontaneous mutations in Arabidopsis thaliana
As the ultimate source of genetic diversity, spontaneous mutation is critical to the evolutionary process. The fitness effects of spontaneous mutations are almost always studied under controlled laboratory conditions rather than under the evolutionarily relevant conditions of the field. Of particular interest is the conditionality of new mutations - i.e., is a new mutation harmful regardless of the environment in which it is found? In other words, what is the extent of genotype-environment interaction for spontaneous mutations? We studied the fitness effects of 25 generations of accumulated spontaneous mutations in Arabidopsis thaliana in two geographically widely separated field environments, in Michigan and Virginia. At both sites, mean total fitness of MA lines exceeded that of the ancestors, contrary to the expected decrease in the mean due to new mutations but in accord with prior work on these MA lines. We observed genotype-environment interactions in the fitness effects of new mutations, such that the effects of mutations in Michigan were a poor predictor of their effects in Virginia and vice versa. In particular, mutational variance for fitness was much larger in Virginia compared to Michigan. This strong genotype-environment interaction would increase the amount of genetic variation maintained by mutation-selection balance.
Data from: Cell wall composition and bioenergy potential of rice straw tissues are influenced by environment, tissue type, and genotype
Breeding has transformed wild plant species into modern crops, increasing the allocation of their photosynthetic assimilate into grain, fiber, and other products for human use. Despite progress in increasing the harvest index, much of the biomass of crop plants is not utilized. Potential uses for the large amounts of agricultural residues that accumulate are animal fodder or bioenergy, though these may not be economically viable without additional efforts such as targeted breeding or improved processing. We characterized leaf and stem tissue from a diverse set of rice genotypes (varieties) grown in two environments (greenhouse and field) and report bioenergy-related traits across these variables. Among the 16 traits measured, cellulose, hemicelluloses, lignin, ash, total glucose, and glucose yield changed across environments, irrespective of the genotypes. Stem and leaf tissue composition differed for most traits, consistent with their unique functional contributions and suggesting that they are under separate genetic control. Plant variety had the least influence on the measured traits. High glucose yield was associated with high total glucose and hemicelluloses, but low lignin and ash content. Bioenergy yield of greenhouse-grown biomass was higher than field-grown biomass, suggesting that greenhouse studies overestimate bioenergy potential. Nevertheless, glucose yield in the greenhouse predicts glucose yield in the field (ρ = 0.85, p < 0.01) and could be used to optimize greenhouse (GH) and field breeding trials. Overall, efforts to improve cell wall composition for bioenergy require consideration of production environment, tissue type, and variety.
Data from: Genotypic diversity and trait variance interact to affect marsh plant performance
1. Intraspecific diversity can have important effects on population, community and ecosystem processes, yet we have little understanding of the relative importance of genetic- vs. trait-based measures of intraspecific diversity. 2. I conducted a manipulative field experiment of plant (Spartina alterniflora) genotypic diversity and trait diversity to examine their independent and interactive effects on plant performance and community structure. I focused on variation within and among genotypes in plant stem height, a trait that varies substantially across environmental gradients and can be an important predictor of plant competition intensity. 3. Trait and genotypic diversity interactively affected multiple metrics of plant performance. Both stem density and spatial spread increased with genotypic diversity in the low trait diversity combinations, yet there were negligible to weak negative effects in the high trait diversity treatments. S. alterniflora percent cover also varied with genotypic and trait diversity, but not in a clear linear pattern. 4. There were no effects of trait or genotypic diversity on associated macrofauna above-ground, yet they interactively affected below-ground measures. Infaunal abundance and sediment oxygen availability mirrored the idiosyncratic response of plant percent cover. 5. Despite the interactive effects of genotypic and trait diversity, high trait diversity consistently increased plant performance in genotypic monoculture. 6. Synthesis: The effects of intraspecific plant trait diversity on a range of plant and community responses in this study reinforce the premise that functional differences underlie ecological effects of genetic diversity and suggest that readily measured trait variance may serve as a valuable predictor of plant performance.
Data from: Identification and characterization of sex-associated loci in sockeye salmon using genotyping-by-sequencing and comparison with a sex-determining assay based on the sdY gene
Loci that can be used to screen for sex in salmon can provide important information for study of both wild and cultured populations. Here, we tested for associations between sex and genotypes at thousands of loci available from a genotyping-by-sequencing (GBS) dataset to discover sex-associated loci in sockeye salmon (Oncorhynchus nerka). We discovered seven sex-associated loci, developed high-throughput assays for two loci, and tested the utility of these two assays in eight collections of sockeye salmon sampled throughout North America. We also screened an existing assay based on the master sex-determining gene in salmon (sdY) in these collections. The ability of GBS-derived loci to assign fish to their phenotypic sex varied substantially among collections suggesting that recombination between the loci that we discovered and the sex-determining gene has occurred. Assignment accuracy to phenotypic sex was much higher with the sdY assay but was still less than 100%. Alignment of sequences from GBS-derived loci to draft genomes for two salmonids provided strong evidence that many of these loci are found on the chromosome orthologous to the known sex chromosome in sockeye salmon. Our study is the first to describe the approximate location of the sex-determining region in sockeye salmon and indicates that sdY is also the master sex-determining gene in this species. However, discordances between sdY genotypes and phenotypic sex and the variable performance of GBS-derived loci warrant more research.
ScienceDex guides
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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.