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2,785 results for “genotyping”
Data from: Genome assembly improvement and mapping convergently evolved skeletal traits in sticklebacks with genotyping-by-sequencing
Marine populations of the threespine stickleback (Gasterosteus aculeatus) have repeatedly colonized and rapidly adapted to freshwater habitats, providing a powerful system to map the genetic architecture of evolved traits. Here, we developed and applied a binned genotyping-by-sequencing (GBS) method to build dense genome-wide linkage maps of sticklebacks using two large marine by freshwater F2 crosses of more than 350 fish each. The resulting linkage maps significantly improve the genome assembly by anchoring 78 new scaffolds to chromosomes, reorienting 40 scaffolds, and rearranging scaffolds in 4 locations. In the revised genome assembly, 94.6% of the assembly was anchored to a chromosome. To assess linkage map quality, we mapped quantitative trait loci (QTL) controlling lateral plate number, which mapped as expected to a 200-kb genomic region containing Ectodysplasin, as well as a chromosome 7 QTL overlapping a previously identified modifier QTL. Finally, we mapped eight QTL controlling convergently evolved reductions in gill raker length in the two crosses, which revealed that this classic adaptive trait has a surprisingly modular and nonparallel genetic basis.
Data from: The mouse universal genotyping array: from substrains to subspecies
Genotyping microarrays are an important resource for genetic mapping, population genetics, and monitoring of the genetic integrity of laboratory stocks. We have developed the third generation of the Mouse Universal Genotyping Array (MUGA) series, GigaMUGA, a 143,259-probe Illumina Infinium II array for the house mouse (Mus musculus). The bulk of the content of GigaMUGA is optimized for genetic mapping in the Collaborative Cross and Diversity Outbred populations, and for substrain-level identification of laboratory mice. In addition to 141,090 single nucleotide polymorphism probes, GigaMUGA contains 2006 probes for copy number concentrated in structurally polymorphic regions of the mouse genome. The performance of the array is characterized in a set of 500 high-quality reference samples spanning laboratory inbred strains, recombinant inbred lines, outbred stocks, and wild-caught mice. GigaMUGA is highly informative across a wide range of genetically diverse samples, from laboratory substrains to other Mus species. In addition to describing the content and performance of the array, we provide detailed probe-level annotation and recommendations for quality control.
Data from: Partial genotyping at polymorphic markers can improve heritability estimates in sibling groups
Accurate estimates of heritability (h²) are necessary to assess adaptive responses of populations and evolution of fitness-related traits in changing environments. For plants, h² estimates generally rely on maternal progeny designs, assuming that offspring are either half-sibs or unrelated. However, plant mating systems often depart from half-sib assumptions, this can bias h² estimates. Here, we investigate how to accurately estimate h² in non-model species through the analysis of sibling designs with a moderate genotyping effort. We performed simulations to investigate how microsatellite marker information available for only a subset of offspring can improve h² estimates based on maternal progeny designs in presence of non-random mating, inbreeding in the parental population or maternal effects. We compared the basic family method, considering or not adjustments based on average relatedness coefficients, and methods based on the animal model. The animal model was used with average relatedness information, or with hybrid relatedness information: associating one-generation pedigree and family assumptions, or associating one-generation pedigree and average relatedness coefficients. Our results highlighted that methods using marker-based relatedness coefficients performed as well as pedigree-based methods in presence of non-random mating (i.e. unequal male reproductive contributions, selfing), offering promising prospects to investigate in situ heritabilities in natural populations. In presence of maternal effects, only the use of pairwise relatednesses through pedigree information improved the accuracy of h² estimates. In that case the amount of father-related offspring in the sibling design is the most critical. Overall, we showed that the method using both one-generation pedigree and average relatedness coefficients was the most robust to various ecological scenarios.
Data from: Inferring the potentially complex genetic architectures of adaptation, sexual dimorphism, and genotype by environment interactions by partitioning of mean phenotypes.
Genetic architecture fundamentally affects the way that traits evolve. However, the mapping of genotype to phenotype includes complex interactions with the environment or even the sex of an organism that can modulate the expressed phenotype. Line cross analysis is a powerful quantitative genetics method to infer genetic architecture by analyzing the mean phenotype value of two diverged strains and a series of subsequent crosses and backcrosses. However, it has been difficult to account for complex interactions with the environment or sex within this framework. We have developed extensions to line cross analysis that allow for gene by environment and gene by sex interactions. Using extensive simulations studies and reanalysis of empirical data, we show that our approach can account for both unintended environmental variation when crosses cannot be reared in a common garden and can be used to test for the presence of gene by environment or gene by sex interactions. In analyses that fail to account for environmental variation between crosses we find that line cross analysis has low power and high false positive rates. However, we illustrate that accounting for environmental variation allows for the inference of adaptive divergence, and that accounting for sex differences in phenotypes allows practitioners to infer the genetic architecture of sexual dimorphism.
Data from: Polyploidy and microsatellite variation in the relict tree Prunus lusitanica L.: how effective are refugia in preserving genotypic diversity of clonal taxa?
Refugia are expected to preserve genetic variation of relict taxa, especially in polyploids, because high gene dosages could prevent genetic erosion in small isolated populations. However, other attributes linked to polyploidy, such as asexual reproduction, may strongly limit the levels of genetic variability in relict populations. Here, ploidy levels and patterns of genetic variation at nuclear microsatellite loci were analysed in Prunus lusitanica, a polyploid species with clonal reproduction that is considered a paradigmatic example of a Tertiary relict. Sampling in this study considered a total of 20 populations of three subspecies: mainland lusitanica (Iberian Peninsula and Morocco), and island azorica (Azores) and hixa (Canary Islands and Madeira). Flow cytometry results supported an octoploid genome for lusitanica and hixa, whereas a 16-ploid level was inferred for azorica. Fixed heterozygosity of a few allele variants at most microsatellite loci resulted in levels of allelic diversity much lower than those expected for a high-order polyploid. Islands as a whole did not contain higher levels of genetic variation (allelic or genotypic) than mainland refuges, but island populations displayed more private alleles and higher genotypic diversity in old volcanic areas. Patterns of microsatellite variation were compatible with the occurrence of clonal individuals in all but two island populations, and the incidence of clonality within populations negatively correlated with the estimated timing of colonization. Our results also suggest that gene flow has been very rare among populations, and thus population growth following founder events was apparently mediated by clonality rather than seed recruitment, especially in mainland areas. This study extends to clonal taxa the idea of oceanic islands as important refugia for biodiversity, since the conditions for generation and maintenance of clonal diversity (i.e. occasional events of sexual reproduction, mutation and/or seed immigration) appear to have been more frequent in these enclaves than in mainland areas.
Data from: Insect mating signal and mate preference phenotypes covary among host plant genotypes
Sexual selection acting on small initial differences in mating signals and mate preferences can enhance signal-preference co-divergence and reproductive isolation during speciation. However, the origin of initial differences in sexual traits remains unclear. We asked whether biotic environments, a source of variation in sexual traits, may provide a general solution to this problem. Specifically, we asked whether genetic variation in biotic environments provided by host plants can result in signal-preference phenotypic covariance in a host-specific, plant-feeding insect. We used a member of the Enchenopa binotata species complex of treehoppers (Hemiptera: Membracidae) to assess patterns of variation in male mating signals and female mate preferences induced by genetic variation in host plants. We employed a novel implementation of a quantitative genetics method, rearing field-collected treehoppers on a sample of naturally-occurring replicated host plant clone lines. We found remarkably high signal-preference covariance among host plant genotypes. Thus, genetic variation in biotic environments influences the sexual phenotypes of organisms living on those environment in a way that promotes assortative mating among environments. This consequence arises from conditions likely to be common in nature (phenotypic plasticity and variation in biotic environments). It therefore offers a general answer to how divergent sexual selection may begin.
Data from: Male-benefit sexually antagonistic genotypes show elevated vulnerability to inbreeding
Background: There is theoretical and empirical evidence for strong sexual selection in males having positive effects on population viability by serving to purify the genome of its mutation load at a low demographic cost. However, there is also theoretical and empirical evidence for negative effects of sexual selection on female fitness, and therefore population viability, known as the gender load. This can take the form of sexually antagonistic (SA) genetic variation where alleles with a selective advantage in males pose a detriment to female fitness, and vice versa. Here, using seed beetles, we shed light on a previously unexplored manifestation of the gender load: the effect of SA genetic variation on tolerance to inbreeding. Results: We found that genotypes encoding high male, but low female fitness exhibited significantly greater rates of extinction upon enforced inbreeding relative to genotypes encoding high female but low male fitness. Also, genotypes encoding low fitness in both sexes exhibited greater rates of extinction relative to generally high-fitness genotypes (though marginally non-significant), an expected finding attributable to variation in mutation load across genotypes. Despite follow-up investigations aiming to identify the mechanism(s) underlying these findings, it remains unclear whether the gender load and the mutation load have independent consequences for tolerance to inbreeding, or whether these two types of genetic architecture interact epistatically to render male-benefit genetic variation relatively intolerant to inbreeding. Conclusions: Regardless of the underlying mechanism(s), our results show that male-benefit/female-detriment SA genetic variation poses a previously unseen detriment to population viability due to its elevated vulnerability to inbreeding/homozygosity. This suggests that sexual selection in the context of SA genetic variance for fitness may enhance the gender load on population viability more than previously appreciated, due to selecting for male-benefit SA genetic variation that engenders lineages to extinction upon inbreeding. We note that our results imply that SA alleles that are sexually selected for in males may be underrepresented or even lacking in panels of inbred lines.
Data from: High-throughput genotyping for species identification and diversity assessment in germplasm collections
Germplasm collections provide an extremely valuable resource for breeders and researchers. However, misclassification of accessions by species often hinders the effective use of these collections. We propose that use of high-throughput genotyping tools can provide a fast, efficient and cost-effective way of confirming species in germplasm collections, as well as providing valuable genetic diversity data. We genotyped 180 Brassicaceae samples sourced from the Australian Grains Genebank across the recently released Illumina Infinium Brassica 60K SNP array. Of these, 76 were provided on the basis of suspected misclassification and another 104 were sourced independently from the germplasm collection. Presence of the A- and C-genomes combined with principle components analysis clearly separated Brassica rapa, B. oleracea, B. napus, B. carinata and B. juncea samples into distinct species groups. Several lines were further validated using chromosome counts. Overall, 18% of samples (32/180) were misclassified on the basis of species. Within these 180 samples, 23/76 (30%) supplied on the basis of suspected misclassification were misclassified, and 9/105 (9%) of the samples randomly sourced from the Australian Grains Genebank were misclassified. Surprisingly, several individuals were also found to be the product of interspecific hybridization events. The SNP (single nucleotide polymorphism) array proved effective at confirming species, and provided useful information related to genetic diversity. As similar genomic resources become available for different crops, high-throughput molecular genotyping will offer an efficient and cost-effective method to screen germplasm collections worldwide, facilitating more effective use of these valuable resources by breeders and researchers.
Data from: Thermal plasticity in postembryonic life history traits of a widely distributed Collembola: Effects of macroclimate and microhabitat on genotypic differences
Life history traits in many ectotherms show complex patterns of variation among conspecific populations sampled along wide latitudinal or climatic gradients. However, few studies have assessed whether these patterns can be explained better by thermal reaction norms of multiple life history traits, covering major aspects of the life cycle. In this study, we compared five populations of a Holarctic, numerically dominant soil microarthropod species, Folsomia quadrioculata, sampled from a wide latitudinal gradient (56–81°N), for growth, development, fecundity, and survival across four temperatures (10, 15, 20, and 25°C) in common garden experiments. We evaluated the extent to which macroclimate could explain differences in thermal adaptation and life history strategies among populations. The common garden experiments revealed large genotypic differences among populations in all the traits, which were little explained by latitude and macroclimate. In addition, the life history strategies (traits combined) hardly revealed any systematic difference related to latitude and macroclimate. The overall performance of the northernmost population from the most stochastic microclimate and the southernmost population, which remains active throughout the year, was least sensitive to the temperature treatments. In contrast, performance of the population from the most predictable microclimate peaked within a narrow temperature range (around 15°C). Our findings revealed limited support for macroclimate-based predictions, and indicated that local soil habitat conditions related to predictability and seasonality might have considerable influence on the evolution of life history strategies of F. quadrioculata. This study highlights the need to combine knowledge on microhabitat characteristics, and demography, with findings from common garden experiments, for identifying the key drivers of life history evolution across large spatial scales, and wide climate gradients. We believe that similar approaches may substantially improve the understanding of adaptation in many terrestrial ectotherms with low dispersal ability.
Genotypes of Merinoland sheep, lambs and F1 crosses
<p>HD (50K) SNP panel and LD (384) SNP panel of Merinoland sheep, lambs and F1 crosses</p>
FIGURES 1‒3 in A revision of the genus Lepidobrya Womersley (Collembola: Entomobryidae) based on morphology and sequence data of the genotype
FIGURES 1‒3. Colour pattern of two individuals in Lepidobrya mawsoni. Scale bars: 1 mm.
Fig. 3 in Host-adapted Cryptosporidium and Enterocytozoon bieneusi genotypes in straw-colored fruit bats in Nigeria
Fig. 3. Phylogeny of Cryptosporidium genotypes in bats based on Bayesian inference of sequences of the small subunit rRNA gene. The posterior probability values are indicated on the branches. Red ones are Cryptosporidium genotypes identified in straw-colored fruit bats in the present study, while blue ones are known Cryptosporidium genotypes previously reported in bats. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
lcUMAPtSNE: Use of non-linear dimensionality reduction techniques with genotype likelihoods
<p>This repository contains genotype likelihood estimations derived from open-access whole-genome re-sequencing datasets of the scimitar-horned oryx (SO). The dataset was downsampled to exhibit varying coverage levels, including 6x, 2x, and 0.5x. Genotype likelihoods were estimated, followed by the calculation of principal components and subsequent application of UMAP and t-SNE with varying parameter settings, as detailed in Uzel et al. (2025). All intermediate and input files generated from these datasets are available here. Genotype likelihood estimations are provided in the formats '.beagle.gz' and '.mafs.gz'. Additionally, the repository contains the input covariance matrix ('.cov') for each dataset and the population information file for each group, which were employed in the non-linear dimensionality reduction steps described in Uzel et al. (2025).</p> <h3>Raw data resources</h3> <p>All raw sequencing data we used in this study were downloaded from public databases, and no new data were generated.</p> <p>The scimitar-horned oryx data were acquired from NCBI BioProject PRJEB37295 (Humble et al. 2023)</p> <h3>Code/Software</h3> <p>All bioinformatic codes used for generating the results and guidelines presented in Çilingir et al. (2024) are available at <strong><a href="https://github.com/fgcilingir/lcUMAPtSNE">https://github.com/fgcilingir/lcUMAPtSNE</a>.</strong></p> <h3>Literature Cited</h3> <p>Humble, E., Stoffel, M. A., Dicks, K., Ball, A. D., Gooley, R. M., Chuven, J., Pusey, R., Remeithi, M. A., Koepfli, K.-P., Pukazhenthi, B., Senn, H., & Ogden, R. (2023). Conservation management strategy impacts inbreeding and mutation load in scimitar-horned oryx. <em>Proceedings of the National Academy of Sciences of the United States of America</em>, <em>120</em>(18), e2210756120.<br><br>Uzel, K., Grossen, C., Çilingir, F.G. (2025) lcUMAPtSNE: Use of non-linear dimensionality reduction techniques with genotype likelihoods. <em>bioRxiv,</em> https://doi.org/10.1101/2024.04.01.587545.</p>
Genotype data for ECG traits prediction
Open the record for dataset details and reuse information.
Phenotypic and genotypic data of genomic selection study of spring frost tolerance of Norway spruce
Open the record for dataset details and reuse information.
Figure 4 from: Moreno-González JA, Pinto-da-Rocha R, Gallão JE (2021) Bringing order to a complex system: phenotypic and genotypic evidence contribute to the taxonomy of Tityus (Scorpiones, Buthidae) and support the description of a new species. ZooKeys 1075: 33-75. https://doi.org/10.3897/zookeys.1075.67459
Figure 4 Tityus C. L. Koch, 1836, telotarsi IV, showing ventral macrosetae A, C, E, G, I, K white light B, D, F, H, J, L UV light A, BTityus (Tityus) brazilae Lourenço & Eickstedt, 1984 (type II) (MZSP 75619) C, DTityus (Archaeotityus) clathratus C. L. Koch, 1844 (type I) (MZSP 31468) E, FTityus (Atreus) forcipula (Gervais, 1843) (type II) (MZSP) G, HTityus (Atreus) obscurus Gervais, 1843 (type I) (MNRJ 07610) I, JTityus (Tityus) serrulatus Lutz & Mello, 1922 (type II) (MZSP 28205) K, LTityus (Tityus) spelaeus sp. nov. (MZSP 74633) (type II). Observations = telotarsi I–IV ventral setae distribution: Type I = tuft of irregularly distributed setae. Type II = two discrete ventrosubmedian rows of setae. Scale bars: 500 μm.
Figure 14 from: Moreno-González JA, Pinto-da-Rocha R, Gallão JE (2021) Bringing order to a complex system: phenotypic and genotypic evidence contribute to the taxonomy of Tityus (Scorpiones, Buthidae) and support the description of a new species. ZooKeys 1075: 33-75. https://doi.org/10.3897/zookeys.1075.67459
Figure 14 Habitat of Tityus (Tityus) spelaeus sp. nov. in the Russão cave A inside landscape of the cave B females on the cave walls.
Figure 11 from: Moreno-González JA, Pinto-da-Rocha R, Gallão JE (2021) Bringing order to a complex system: phenotypic and genotypic evidence contribute to the taxonomy of Tityus (Scorpiones, Buthidae) and support the description of a new species. ZooKeys 1075: 33-75. https://doi.org/10.3897/zookeys.1075.67459
Figure 11 Tityus (Tityus) spelaeus sp. nov., female paratype (MZSP 74633) genital area and pectines A genital operculum and pectinal basal piece B closeup of the pectinal basal piece, showing cuticular pores on glandular region C right pectine D peg sensillae, distribution E closeup of a peg sensilla. Scale bars: 800 µm (A); 60 µm (B); 1000 µm (C); 20 µm (D); 3 µm (E).
Figure 10 from: Moreno-González JA, Pinto-da-Rocha R, Gallão JE (2021) Bringing order to a complex system: phenotypic and genotypic evidence contribute to the taxonomy of Tityus (Scorpiones, Buthidae) and support the description of a new species. ZooKeys 1075: 33-75. https://doi.org/10.3897/zookeys.1075.67459
Figure 10 Tityus (Tityus) spelaeus sp. nov., female holotype (MZSP 74633), chela A external view B dorsal view C ventral view. Scale bar: 3 mm.
Figure 8 from: Moreno-González JA, Pinto-da-Rocha R, Gallão JE (2021) Bringing order to a complex system: phenotypic and genotypic evidence contribute to the taxonomy of Tityus (Scorpiones, Buthidae) and support the description of a new species. ZooKeys 1075: 33-75. https://doi.org/10.3897/zookeys.1075.67459
Figure 8 Tityus (Tityus) spelaeus sp. nov., female holotype (MZSP 74633), carapace, dorsal view A white light B UV light. Scale bars: 2 mm.
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.