Find research datasets worth reusing

Figure 4. Haplotype network for Rattus rattus Complex II in Expanding Population Edge Craniometrics and Genetics Provide Insights into Dispersal of Commensal Rats through Nusa Tenggara, Indonesia

Figure 4. Haplotype network for Rattus rattus Complex II. The Nusa Tenggara samples are illustrated on the right of the network.

Figure 1 in Expanding Population Edge Craniometrics and Genetics Provide Insights into Dispersal of Commensal Rats through Nusa Tenggara, Indonesia

Figure 1. Cranial measurements taken for each specimen: supraoccipital height (BH), basal length (BLL), basilar length (BRL), length of the bullae (BULL), condylobasal length (CBL), condylobasilar length (CBRL), minimum corpus length (CL), length of the diastema (DA), foramen magnum height (FMH), foramen magnum width (FMW), length of the incisive foramina (FOR), length of the face (GES), length of the braincase (HKL), thickness of the incisor (ID), interorbital breadth (IOB), mandibular diastema length (LAL), thickness lower incisor (LID), mandibular alveoli length (MAL), mandibular toothrow length (crown) (MCL),mandibular depth (MD), maximum mandibular height (MDL), mandibular depth at M1 (MID), mandibular length (ML), nasal length (NAS), nasal breadth (NASB), occipital breadth (OCB), occipital length (OCN), supraoccipital width at the occipital condyles (OCW), length of the upper molar row (alveoli) (OZRA), length of the upper molar row (crown) (OZRK), palatal length (PL), palatine breadth (PRL), rostral breadth (RB), rostral height (RH), breadth of braincase (SKB), height of braincase with bullae (SKH), zygomatic plate (ZP), zygomatic breadth (ZYG).

Figure 3. Haplotype networks for Rattus exulans, R in Expanding Population Edge Craniometrics and Genetics Provide Insights into Dispersal of Commensal Rats through Nusa Tenggara, Indonesia

Figure 3. Haplotype networks for Rattus exulans, R. argentiventer, and Rattus rattus Complex LIV. Sunda refers to the islands of Borneo, Java, and Sumatra; the Indonesian sample (brown) lacks further collection information.

Figure 6 in Expanding Population Edge Craniometrics and Genetics Provide Insights into Dispersal of Commensal Rats through Nusa Tenggara, Indonesia

Figure 6. Summary of likely movements of the three commensal rodents through the Nusa Tenggara island chain. Rat illustrations redrawn and adapted from R. Budden, location of RS3 Dong Song drums from Calo (2014).

Figure 4. Bayesian Inference phylogenetic tree inferred from 1039 in Genetic Relationships of Long-nosed Potoroos Potorous tridactylus (Kerr, 1792) from the Bass Strait Islands, with Notes on the Subspecies Potorous tridactylus benormi Courtney, 1963

Figure 4. Bayesian Inference phylogenetic tree inferred from 1039 bp of concatenated CO1 and ND2 mitochondrial DNA sequence data. Posterior probabilities for major lineages are shown. A similar tree topology was also inferred from Maximum Likelihood.

Figure 3. Maximum Likelihood phylogenetic tree inferred from 695 in Genetic Relationships of Long-nosed Potoroos Potorous tridactylus (Kerr, 1792) from the Bass Strait Islands, with Notes on the Subspecies Potorous tridactylus benormi Courtney, 1963

Figure 3. Maximum Likelihood phylogenetic tree inferred from 695 bp of CO1 mtDNA sequence, including data from the Potorous tridactylus benormi Holotype (AM M.8319) and Paratype (AM M.8373). Bootstrap values for major lineages are shown. A similar tree topology was inferred from Bayesian inference.

Figure 2 in Genetic Relationships of Long-nosed Potoroos Potorous tridactylus (Kerr, 1792) from the Bass Strait Islands, with Notes on the Subspecies Potorous tridactylus benormi Courtney, 1963

Figure 2. Holotype of Potorous tridactylus benormi AM M.8319 dorsal view (top) and lateral view (bottom). Photography by Sally Cowan.

opencc-by-4.0Dec 2022View details →

Genetic differentiation following recent domestication events: A study of farmed Nile tilapia (Oreochromis niloticus) populations

SNP array data from our research article. It contains the SNP markers in common across the different Nile tilapia (Oreochromis niloticus) populations assessed in the study

opencc-by-4.0May 2023View details →

Growing Arabidopsis pollen tubes expressing genetically encoded reporters for calcium and pH

Spatiotemporal dynamics of intracellular pH (H+) and calcium (Ca2+) in growing Arabidopsis pollen tubes. Fluorescence time-lapses of pollen tubes expressing ratiometric sensors under the pollen-specific LAT52 promoter, namely CaMeleon (Ca2+) [Damineli et al., 2017; DOI: 10.1093/jxb/erx032] and pHluorin (pH) [Hoffmann et al., 2020; DOI: 10.1038/s41467-020-16253-1], were acquired every 4 seconds with an inverted microscope equipped with a front-illuminated camera (2560 × 2160, pixel size 6.45 μm), a fluorescence illuminator, and a ×63 1.2NA water immersion objective lens. The CaMeleon filters were set as follows: excitation 426-450 nm (CFP) and 505-515 nm (YFP), emission 458-487 nm (CFP) and 520-550 nm (YFP). As for pHluorin, the filter settings were: excitation 318-390 nm (DAPI) and 428-475 nm (FITC), emission 435-448 nm (DAPI) and 523-536 nm (FITC) [from Damineli et al., 2017; Hoffmann et al., 2020].

Genetic and phenotypic consequences of local transitions between sexual and parthenogenetic reproduction in the wild

Transitions from sexual to asexual reproduction have occurred in numerous lineages across the tree of life, but many questions remain about how such transitions occur and why asexual populations rarely persist. In facultatively parthenogenetic animals, all-female populations can arise when males are absent or become extinct and, if such populations can persist asexually for many generations, they could ultimately give rise to obligately asexual species. However, the initial stages of this process remain poorly understood. The facultatively parthenogenetic Australian phasmid Megacrania batesii exhibits a spatial mosaic of mixed-sex populations that reproduce predominantly sexually and all-female sites that reproduce exclusively via parthenogenesis. We used this system to compare genetic and phenotypic parameters among multiple natural populations that vary in reproductive mode and geographic location. Analysis of single nucleotide polymorphisms (SNPs) collected from reduced representation whole genome data showed populations grouping by geographic location rather than reproductive mode, with little gene-flow between them. Mixed-sex populations had drastically higher heterozygosities than all-female populations. Phenotypic analysis revealed considerable inter-population variation in rates of deformities in (non-functional) wings, with higher mean frequency and severity of deformities in all-female sites. All-female sites also harbored more parasites, but only in swamp habitats. However, reproductive mode did not explain variation in mean female fecundity, egg hatching success, or missing appendages. These results indicate that local transitions to parthenogenetic reproduction can lead to increased rates of developmental abnormalities and increased vulnerability to disease but can also occur without substantial fitness consequences despite dramatic reductions in genetic diversity and heterozygosity.

opencc-by-4.0Jun 2023View details →

Spatial Mapping and Host Linking of Mobile Genetic Elements in Complex Microbiomes - Visualizing phage infection

We staged infections at four multiplicities of infection (MOI 0, 0.01, 0.1, and 1), and took snapshots every ten minutes over a 40-minute period. We designed FISH probes targeting the non-coding strand of the gp34 gene, which encodes a tail fiber protein and quantified cells with 5 or more MGE spots, less than 5 spots, and no spots

Data from: Past forest-cover explains current genetic differentiation in the Carpathian newt (Lissotriton montandoni), but not in the smooth newt (L. vulgaris)

Aim: Current genetic variation and differentiation are expected to reflect the effects of past rather than present landscapes due to time lags, i.e., the time necessary for genetic diversity to reach equilibrium and reflect demography. Time lags can affect our ability to infer landscape use and model connectivity, and also obscure the genetic consequences of recent landscape changes. In this work, we test if past forest-cover better explains contemporary patterns of genetic differentiation in two closely related but ecologically distinct newt species – Lissotriton montandoni and L. vulgaris. Location: Carpathian Mountains and foothills. Methods: Genetic differentiation between populations was related with landscape resistance optimized with tools from landscape genetics, for multiple timeframes, using forest-cover data from 1963 to 2015. Analyses were conducted for pairs of populations at distances from 1 to 50 km. Results: We find evidence for a time lag in L. montandoni, with forest-cover from 40 years ago (ca. 10 newt generations) better explaining current genetic differentiation. In L. vulgaris, current genetic differentiation was better predicted by present land-cover models with lower resistance given to open-forests. This result may reflect the generalist ecology of L. vulgaris, its lower effective population sizes and exposure to habitat destruction and fragmentation. Main conclusions: Our study provides evidence for time lags in L. montandoni, showing that the genetic consequences of landscape change for some species are not yet evident. Our findings highlight the interspecific variation in time lag prevalence, and demonstrate that current patterns of genetic differentiation should be interpreted in the context of historical landscape changes.

Data from: Additive genetic and environmental variation interact to shape the dynamics of seasonal migration in a wild bird population

Dissecting joint micro-evolutionary and plastic responses to environmental perturbations requires quantifying interacting components of genetic and environmental variation underlying expression of key traits. This ambition is particularly challenging for phenotypically discrete traits where multiscale decompositions are required to reveal non-linear transformations of underlying genetic and environmental variation into phenotypic variation, and when effects must be estimated from incomplete field observations. We devised a joint multistate capture-recapture and quantitative genetic animal model and fitted this model to full-annual-cycle resighting data from partially-migratory European shags (Gulosus aristotelis) to estimate key components of genetic, environmental and phenotypic variance in the ecologically critical discrete trait of seasonal migration versus residence. We demonstrate non-negligible additive genetic variance in latent liability for migration, resulting in detectable micro-evolutionary responses following two episodes of strong survival selection. Further, liability-scale additive genetic effects interacted with substantial permanent individual and temporary environmental effects to generate complex non-additive effects on expressed phenotypes, causing substantial intrinsic gene-by-environment interaction variance on the phenotypic scale. Our analyses therefore reveal how temporal dynamics of partial seasonal migration arise from combinations of instantaneous micro-evolution and within-individual phenotypic consistency, and highlight how intrinsic phenotypic plasticity could expose genetic variation underlying discrete traits to complex forms of selection.

What Darwin couldn't see: Island formation and historical sea levels shape genetic divergence and island biogeography in a coastal marine species

Oceanic islands play a central role in the study of evolution and island biogeography. The Galapagos Islands are one of the most studied oceanic archipelagos but research has almost exclusively focused on terrestrial organisms compared to marine species. Here we used the Galapagos bullhead shark (Heterodontus quoyi) and single nucleotide polymorphisms (SNPs) to examine evolutionary processes and their consequences for genetic divergence and island biogeography in a shallow-water marine species without larval dispersal. The sequential separation of individual islands from a central island cluster gradually established different ocean depths between islands that pose barriers to dispersal in H. quoyi. Isolation-by-resistance analysis suggested that ocean bathymetry and historical sea level fluctuations modified genetic connectivity. These processes resulted in at least three genetic clusters that exhibit low genetic diversity and effective population sizes that scale with island size and the level of geographic isolation. Our results exemplify that island formation and climatic cycles shape genetic divergence and biogeography of coastal marine organisms with limited dispersal comparable to terrestrial taxa. Because similar scenarios exist in oceanic islands around the globe our research provides a new perspective on marine evolution and biogeography with implications for the conservation of island biodiversity.

opencc-by-4.0Dec 2022View details →

Data and Code for Publication "Inferring human neutral genetic variation from craniodental phenotypes"

Data and code for publication: H. Rathmann et al., Inferring human neutral genetic variation from craniodental phenotypes. PNAS Nexus. The repository contains: <ul> <li>“R code for DP-DG analysis.txt”: R code for testing levels of neutral evolutionary signals preserved in five craniodental data types: cranial metrics, dental metrics, cranial non-metric traits, dental non-metric traits, and craniodental metrics and non-metric traits combined.</li> </ul> <ul> <li>“Cranial metric data.csv”: Dataset consisting of 37 cranial metric variables for 26 worldwide modern populations, provided in a comma-separated values file format. The data were collected by T. Hanihara and originally presented in the publication titled: T. Hanihara, Comparison of craniofacial features of major human groups. Am. J. Phys. Anthropol. 99, 389–412 (1996) (<a href="https://doi.org/10.1002/(SICI)1096-8644(199603)99:3%3c389::AID-AJPA3%3e3.0.CO;2-S">https://doi.org/10.1002/(SICI)1096-8644(199603)99:3<389::AID-AJPA3>3.0.CO;2-S</a>).</li> </ul> <ul> <li>“Dental metric data.csv”: Dataset comprising 28 dental metric variables for 26 worldwide modern populations, provided in a comma-separated values file format. The data were collected by T. Hanihara and originally presented in the publication titled: T. Hanihara, H. Ishida, Metric dental variation of major human populations. Am. J. Phys. Anthropol. 128, 287–298 (2005) (<a href="https://doi.org/10.1002/ajpa.20080">https://doi.org/10.1002/ajpa.20080</a>).</li> </ul> <ul> <li>“Cranial non-metric trait data.csv”: Dataset consisting of 24 cranial non-metric trait variables for 26 worldwide modern populations, provided in a comma-separated values file format. The data were collected for the most part by T. Hanihara and presented in the publication titled: T. Hanihara, H. Ishida, Y. Dodo, Characterization of biological diversity through analysis of discrete cranial traits. Am. J. Phys. Anthropol. 121, 241–251 (2003) (<a href="https://doi.org/10.1002/ajpa.10233">https://doi.org/10.1002/ajpa.10233</a>).</li> </ul> <ul> <li>“Dental non-metric trait data.csv”: Dataset comprising 25 dental non-metric trait variables for 26 worldwide modern populations, provided in a comma-separated values file format. The data were collected by C. G. Turner II, G. R. Scott, and J. D. Irish. This individual-level dataset was artificially created from population-level trait frequency information presented in the publications: G. R. Scott, J. D. Irish, Human Tooth Crown and Root Morphology (Cambridge University Press, 2017) (<a href="https://doi.org/10.1017/9781316156629">https://doi.org/10.1017/9781316156629</a>); and: J. D. Irish, A. Morez, L. Girdland Flink, E. L. W. Phillips, G. R. Scott, Do dental nonmetric traits actually work as proxies for neutral genomic data? Some answers from continental- and global-level analyses. Am. J. Phys. Anthropol. 172, 347–375 (2020) (<a href="https://doi.org/10.1002/ajpa.24052">https://doi.org/10.1002/ajpa.24052</a>).</li> </ul> <ul> <li>“SNP data.txt”: Dataset comprising 8,821 SNP markers for 26 worldwide modern populations, provided in a genepop file format. The data were obtained from various published sources: I. Lazaridis et al., Ancient human genomes suggest three ancestral populations for present-day Europeans. Nature 513, 409–413 (2014) (<a href="https://doi.org/10.1038/nature13673">https://doi.org/10.1038/nature13673</a>); P. Qin, M. Stoneking, Denisovan ancestry in east Eurasian and native American populations. Mol. Biol. Evol. 32, 2665–2674 (2015) (<a href="https://doi.org/10.1093/molbev/msv141">https://doi.org/10.1093/molbev/msv141</a>); P. Skoglund et al., Genomic insights into the peopling of the Southwest Pacific. Nature 538, 510–513 (2016) (<a href="https://doi.org/10.1038/nature19844">https://doi.org/10.1038/nature19844</a>); M. R. Nelson et al., The Population Reference Sample, POPRES: a resource for population, disease, and pharmacological genetics research. Am. J. Hum. Genet. 83, 347–358 (2008) (<a href="https://doi.org/10.1016/j.ajhg.2008.08.005">https://doi.org/10.1016/j.ajhg.2008.08.005</a>); J. K. Pickrell, J. K. Pritchard, Inference of population splits and mixtures from genome-wide allele frequency data. PLoS Genet. 8, e1002967 (2012) (<a href="https://doi.org/10.1371/journal.pgen.1002967">https://doi.org/10.1371/journal.pgen.1002967</a>); A. Bergström et al., Insights into human genetic variation and population history from 929 diverse genomes. Science 367 (2020) (<a href="https://doi.org/10.1126/science.aay5012">https://doi.org/10.1126/science.aay5012</a>); B. M. Henn et al., Genomic ancestry of North Africans supports back-to-Africa migrations. PLoS Genet. 8, e1002397 (2012) (<a href="https://doi.org/10.1371/journal.pgen.1002397">https://doi.org/10.1371/journal.pgen.1002397</a>); S. Mallick et al., The Simons Genome Diversity Project: 300 genomes from 142 diverse populations. Nature 538, 201–206 (2016) (<a href="https://doi.org/10.1038/nature18964">https://doi.org/10.1038/nature18964</a>); Lao et al., Correlation between genetic and geographic structure in Europe. Curr. Biol. 18, 1241–1248 (2008) (<a href="https://doi.org/10.1016/j.cub.2008.07.049">https://doi.org/10.1016/j.cub.2008.07.049</a>); and M. Lipson et al., Population Turnover in Remote Oceania Shortly after Initial Settlement. Curr. Biol. 28, 1157-1165.e7 (2018) (<a href="https://doi.org/10.1016/j.cub.2018.02.051">https://doi.org/10.1016/j.cub.2018.02.051</a>).</li> </ul> For population and variable names and abbreviations, see Supplementary Information in: H. Rathmann et al., Inferring human neutral genetic variation from craniodental phenotypes. PNAS Nexus.

opencc-by-4.0Jun 2023View details →

Human Genetics Influences Microbiome Composition Involved in Asthma Exacerbations despite Inhaled Corticosteroid Treatment

Additional Supplement Data of the manuscript Perez-Garcia J, Espuela-Ortiz A, Hernández-Pérez JM, et al. Human Genetics Influences Microbiome Composition Involved in Asthma Exacerbations despite Inhaled Corticosteroid Treatment (in press). J Allergy Clin Immunol. 2023;S0091-6749(23)00748-0. doi:10.1016/j.jaci.2023.05.021. This Supplement Data contains the following items: <table> <tbody> <tr> <td>Additional Table 1</td> <td>List of independent mbQTLs associated with p<1x10-5 in the mbGWAS from saliva samples in Europeans (discovery).</td> </tr> <tr> <td>Additional Table 2</td> <td>List of independent mbQTLs associated with p<1x10-5 in the mbGWAS from pharyngeal samples in Europeans (discovery).</td> </tr> <tr> <td>Additional Table 3</td> <td>List of independent mbQTLs associated with p<1x10-5 in the mbGWAS from nasal samples in Europeans (discovery).</td> </tr> <tr> <td>Additional Table 4</td> <td>Summary results of enrichment analyses using the Enrichr platform.</td> </tr> <tr> <td>Additional Table 5</td> <td>Summary results of stratified enrichment analyses by biological sample type.</td> </tr> <tr> <td>Additional Table 6</td> <td>List of independent mbQTLs associated with p<1x10-5 in the mbGWAS from saliva samples in African Americans (replication phase).</td> </tr> <tr> <td>Additional Table 7</td> <td>List of independent mbQTLs associated with p<1x10-5 in the mbGWAS from saliva samples in Latinos (replication phase).</td> </tr> <tr> <td>Additional Table 8</td> <td>Summary results of replication enrichment analyses in saliva samples.</td> </tr> <tr> <td>Additional Table 9</td> <td>Summary statistics of the mbQTL analysis of Streptococcus in nasal samples.</td> </tr> <tr> <td>Additional Table 10</td> <td>Summary statistics of the mbQTL analysis of Campylobacter in pharyngeal samples.</td> </tr> <tr> <td>Additional Table 11</td> <td>Summary statistics of the mbQTL analysis of Tannerella in pharyngeal samples.</td> </tr> <tr> <td>Additional Table 12</td> <td>Summary table of the different genetic models tested for each mbQTL pair.</td> </tr> </tbody> </table>

opencc-by-4.0Oct 2022View details →

Data from the manuscript 'Accurate detection of shared genetic architecture from GWAS summary statistics in the small-sample context'

Data sets from the manuscript 'Accurate detection of shared genetic architecture from GWAS summary statistics in the small-sample context'. These include the test statistics from analyses of real and simulated data, and the data used to generate the figures relating to the goodness-of-fit of the generalised extreme value distribution to the GPS test statistics under the null. Please see the enclosed README for more details.

opencc-by-4.0Mar 2023View details →

Figure 4 in Genetic diversity, phylogenetic and phylogeographic analyses of Oncideres impluviata (Germar, 1823) (Coleoptera: Cerambycidae) in Rio Grande do Sul state, Brazil

Figure 4 Phylogenetic tree summarizing the results of Bayesian inference (BI) and Maximum likelihood (ML). Tree shows the relationships among species of Oncideres along with the haplotype network of five populations of Oncideres impluviata from Rio Grande do Sul, Brazil. A, B and C depicts clades within Oncideres impluviata. The circle areas in the haplotype network are proportional to the frequencies of each haplotype and hatch markers represent the number of differences among haplotypes.

opencc-by-4.0Feb 2021View details →

Figure 5 Nav kdr 1016 and 1534 in Genetic study in Aedes (Stegomyia) aegypti (Linnaeus, 1762) from Londrina (Paraná State, Brazil): an approach to population structure and pyrethroid resistance

Figure 5 Nav kdr 1016 and 1534 site allele frequencies in UEL. Collection site locations were distributed in the three regions of the campus.