Find research datasets worth reusing

opencc-by-4.0Apr 2013View details →

Fig. 8. Protanais ligniamator Larsen, 2006 in A new polymorphic species of Leptochelia (Crustacea: Tanaidacea) from Guinea Bissau, West Africa, with comments on genetic variation within Leptochelia

Fig. 8. Protanais ligniamator Larsen, 2006, SEM: (A) pleopod 1; (B) same, exopod, higher magnification.

opencc-by-4.0Apr 2013View details →

Fig. 5 in A new polymorphic species of Leptochelia (Crustacea: Tanaidacea) from Guinea Bissau, West Africa, with comments on genetic variation within Leptochelia

Fig. 5. Leptochelia africana sp. n., primary male, paratype: (A) cheliped; (B) pereopod 1; (C) pereopod 2; (D) pereopod 3; (E) pereopod 4; (F) pereopod 5; (G) pereopod 6; (H) uropod. Scale bar = 0.5 mm.

opencc-by-4.0Apr 2013View details →

Fig. 4 in A new polymorphic species of Leptochelia (Crustacea: Tanaidacea) from Guinea Bissau, West Africa, with comments on genetic variation within Leptochelia

Fig. 4. Leptochelia africana sp. n., male paratypes: (A) secondary male, lateral view; (B–J) primary male: (B) dorsal view, (C) lateral view, (D) antennule, (E) antenna, (F) labrum, (G) maxillule palp, (H) maxilliped, (I) epignath, (J) pleopod. Scale bars = 1.0 mm (A–C), 0.5 mm (D, E, J) and 0.1 mm (F–H).

opencc-by-4.0Mar 2023View details →

Supplementary data and code to "Known allosteric proteins have central roles in genetic disease" by G. Abrusan, D. Ascher and M. Inouye, PLOS Computational Biology 18(2):e1009806.

Scripts and data to reproduce the figures and supplementary figures of "G. Abrusan, D. Ascher and M. Inouye (2022) Known allosteric proteins have central roles in genetic disease." PLOS Computational Biology 18(2):e1009806. https://doi.org/10.1371/journal.pcbi.1009806.

opencc-by-4.0Mar 2024View details →

Key triggers of adaptive genetic variability of sessile oak [Q. petraea (Matt.) Liebl.] from the Balkan refugia: outlier detection and association of SNP loci from ddRAD-seq data

Knowledge on the genetic composition of Quercus petraea in south-eastern Europe is limited despite the species' significant role in the re-colonisation of Europe during the Holocene, and the diverse climate and physical geography of the region. Therefore, it is imperative to conduct research on adaptation in sessile oak to better understand its ecological significance in the region. While large sets of SNPs have been developed for the species, there is a continued need for smaller sets of SNPs that are highly informative about the possible adaptation to this varied landscape. By using double digest restriction site associated DNA sequencing data from our previous study, we mapped RAD-tag sequences to the Quercus robur reference genome and identified a set of SNPs putatively related to drought stress-response. A total of 179 individuals from eighteen natural populations at sites covering heterogeneous climatic conditions in the southeastern natural distribution range of Q. petraea were genotyped. The detected highly polymorphic variant sites revealed three genetic clusters with a generally low level of genetic differentiation and balanced diversity among them but showed a north–southeast gradient. Selection tests showed nine outlier SNPs positioned in different functional regions. Genotype-environment association analysis of these markers yielded a total of 53 significant associations, explaining 2.4–16.6% of the total genetic variation. Our work exemplifies that adaptation to drought may be under natural selection in the examined Q. petraea populations.

opencc-zeroMar 2023View details →

Genetic variation in mouse islet Ca2+ oscillations reveals novel regulators of islet function

Insufficient insulin secretion to meet metabolic demand results in diabetes. The intracellular flux of Ca2+ into β-cells triggers insulin release. Since genetics strongly influences variation in islet secretory responses, we surveyed islet Ca2+ dynamics in eight genetically diverse mouse strains. We found high strain variation in response to four conditions: 1) 8 mM glucose; 2) 8 mM glucose plus amino acids; 3) 8 mM glucose, amino acids, plus 10nM GIP; and 4) 2 mM glucose. These stimuli interrogate β-cell function, α-cell to β-cell signaling, and incretin responses. We then correlated components of the Ca2+ waveforms to islet protein abundances in the same strains used for the Ca2+ measurements. To focus on proteins relevant to human islet function, we identified human orthologues of correlated mouse proteins that are proximal to glycemic-associated SNPs in human GWAS. Several orthologues have previously been shown to regulate insulin secretion (e.g. ABCC8, PCSK1, and GCK), supporting our mouse-to-human integration as a discovery platform. By integrating these data, we nominated novel regulators of islet Ca2+ oscillations and insulin secretion with potential relevance for human islet function. We also provide a resource for identifying appropriate mouse strains in which to study these regulators.

Genotype and genetic diversity data for: Contrasts in riverscape patterns of intraspecific genetic variation in a diverse Neotropical fish community of high conservation value

Spatial patterns in genetic variation compared across species provide information about the predictability of genetic diversity of natural populations and areas requiring conservation measures. Due to their remarkable fish diversity, rivers in Neotropical regions are ideal systems to confront theory with observations and would benefit greatly from such approaches given their increasing vulnerability to anthropogenic pressures. We used SNP data from 18 fish species with contrasting life-history traits, co-sampled across 12 sites in the Maroni – a major river system from the Guiana Shield – to compare patterns of intraspecific genetic variation and identify their underlying drivers. Analyses of covariance revealed a decrease in genetic diversity as distance from the river outlet increased for 5 of the 18 species, illustrating a pattern commonly observed in riverscapes for species with low-to-medium dispersal abilities. However, mean within-site genetic diversity was lowest in the two easternmost tributaries of the Upper Maroni and around an urbanized location downstream, indicating the need to address the potential influence of local pressures in these areas, such as goldmining or fishing. Finally, the relative influence of isolation by stream distance, isolation by discontinuous river flow and isolation by spatial heterogeneity in effective size on pairwise genetic differentiation varied across species. Species with similar dispersal and reproductive guilds did not necessarily display shared patterns of population structure. Increasing the knowledge of specific life history traits and ecological requirements of fish species in these remote areas should help further understand factors that influence their current patterns of genetic variation.

Density and genetic diversity of grizzly bears at the northern edge of their distribution

Species at the periphery of their range are typically limited in density by lower habitat quality. As a result, the Central-Marginal Hypothesis (CMH) predicts a decline in genetic diversity of populations towards the periphery of a species' range. Grizzly bears (Ursus arctos) once ranged throughout most of North America but have been extirpated from nearly half of their former range, mainly in the south. They are considered a species at risk even in Canada's remote North, where they occupy the northernmost edge of the species' continental distribution in a low-productivity tundra environment. With climate change, one of their main food items in the tundra (caribou), which has always shown yearly fluctuations, is declining, but simultaneously, grizzlies appear to be expanding their range northward, in tundra environment. Yet, a lack of population density estimates across the North is hindering effective conservation action. The CMH has implications for the viability of peripheral populations, and the links between population fluctuations, potential bottlenecks and genetic diversity need to be determined to contribute to species' conservation. Using non-invasive genetic sampling from 2012 to 2014, and autosomal DNA genotyping (via-microsatellites), we estimated bear density using a spatial capture-recapture framework and analysed genetic diversity using observed heterozygosity (Ho), Allelic Richness (AR), and expected heterozygosity (He). We compared our findings to other studies that used comparable methodologies on this and a related species (Black bears; Ursus americanus). We found densities of grizzly bears that were low for the species but characteristic for the region (5.9 ± 0.4 bears/1000 km2), but with high Ho (0.81 ± 0.05), AR (7 ± 0.78) and He (0.71 ± 0.03), despite a signal of recent bottlenecks. In both species, peripherality was not correlated with Ho but was negatively correlated with density. We suggest that the apparent growth of this expanding population of grizzlies offsets the negative impacts of recent bottlenecks on Ho. Indigenous Knowledge provides historical context (on the order of centuries – e.g., arctic large mammal fluctuations, grizzly bear bottlenecks) for the current bear population dynamics (on the order of decades – e.g., climate change, northern grizzly bear expansion).

Data for: Natural genetic variation in a dopamine receptor is associated with variation in female fertility in Drosophila melanogaster

Fertility is a major component of fitness but its genetic architecture remains poorly understood. Using a full diallel cross of 50 Drosophila melanogaster Genetic Reference Panel inbred lines with whole genome sequences, we found substantial genetic variation in fertility largely attributable to females. We mapped genes associated with variation in female fertility by genome-wide association analysis of common variants in the fly genome. Validation of candidate genes by RNAi knockdown confirmed the role of the dopamine 2-like receptor (Dop2R) in promoting egg laying. We replicated the Dop2R effect in an independently collected productivity dataset and showed that the effect of the Dop2R variant was mediated in part by regulatory gene expression variation. This study demonstrates the strong potential of genome-wide association analysis in this diverse panel of inbred strains and subsequent functional analyses for understanding the genetic architecture of fitness traits.

opencc-by-4.0Feb 2023View details →

Fig. 1 in Camera traps and genetic identification of faecal samples for detection and monitoring of an endangered ungulate

Fig. 1. Distribution of deployed camera traps showing presence (black circles) and non-detection (purple circles) and genetic sampling locations showing presence (black triangles) and non-detection (purple triangles) of Eld's deer. Inset map shows the location of Chhaeb Wildlife Sanctuary in Cambodia (black rectangle). Background shows proportion of tree cover from WorldCover land cover map (© ESA WorldCover project 2020 / Contains modified Copernicus Sentinel data (2020) processed by ESA WorldCover consortium).

FIG. 5 in Genetic affinities and biogeography of putative Levantine-endemic seaweed Treptacantha rayssiae (Ramon) M.Mulas, J.Neiva & Á.Israel, comb. nov. (Phaeophyceae)

FIG. 5. — Cross sections of the thallus of Treptacantha rayssiae (Ramon) M.Mulas, J.Neiva & Á.Israel, comb. nov.: A, primary branch; B, detail of the three vegetative tissues at Tel Shikmona; C, primary branch; D, detail of the three vegetative tissues from Achziv. Scale bars: A, 50 µm; B, 200 µm; C, 100 µm; D, 20 µm. Abbreviations: mt, meristoderm; c, cortex; m, medulla.

FIG. 4 in Genetic affinities and biogeography of putative Levantine-endemic seaweed Treptacantha rayssiae (Ramon) M.Mulas, J.Neiva & Á.Israel, comb. nov. (Phaeophyceae)

FIG. 4. — Morphology of Treptacantha rayssiae (Ramon) M.Mulas, J.Neiva & Á.Israel, comb. nov., at Tel Shikmona, Israel (May 2018, voucher IOLR-MM00641): A, habitus of specimen; B, holdfast; C, detail of apical part of branches with receptacles, packed, cylindrical and spiny. Scale bars: A, 4 cm; B, C, 2 cm.

FIG. 3 in Genetic affinities and biogeography of putative Levantine-endemic seaweed Treptacantha rayssiae (Ramon) M.Mulas, J.Neiva & Á.Israel, comb. nov. (Phaeophyceae)

FIG. 3. — Typical morphology of Treptacantha rayssiae (Ramon) M.Mulas, J.Neiva & Á.Israel, comb. nov., at Achziv, Israel (May 2019, voucher IOLR - AmR1652019): A, habitus of specimens; B, apex with smooth tophules; C, detail of apical part of slightly spiny branches with receptacles; D, holdfast. Scale bars: A, C, 2 cm; B, D, 1 cm.

FIG. 2 in Genetic affinities and biogeography of putative Levantine-endemic seaweed Treptacantha rayssiae (Ramon) M.Mulas, J.Neiva & Á.Israel, comb. nov. (Phaeophyceae)

FIG. 2. — Phylogenetic affinities of Treptacantha rayssiae (Ramon) M.Mulas, J.Neiva & Á.Israel, comb. nov. (synonym of C. rayssiae): A, bayesian 50% majority-rule consensus COI tree of selected species of Cystoseira sensu lato (including Cystoseira sensu stricto, Carpodesmia Greville and Treptacantha Kützing) and related genera, showing the phylogenetic position of Treptacantha rayssiae (Ramon) M.Mulas, J.Neiva & Á.Israel, comb. nov. Numbers above the branches are Bayesian posterior probabilities (>0.50) and maximum likelihood bootstrap support values, respectively. The outgroup used was represented by Stephanocystis Trevisan, C. compressa (Esper) Gerloff & Nizamuddin and Sargassum C.Agardh; B, neighbour-joining network of COI sequences of T. rayssiae (Ramon) M.Mulas, J.Neiva & Á.Israel, comb. nov., and related taxa. Terminal black circles correspond to unique sequences/taxa and are sized to their frequency. Small white circles represent internal nodes and perpendicular dashes along branches represent unique base-pair mutations between sequences/taxa. Branch lengths not to scale. Scale bar: A, 0.02 BIPP (Bayesian Inference Posterior Probability).

APPENDIX 1. — Bayesian 50 in Genetic affinities and biogeography of putative Levantine-endemic seaweed Treptacantha rayssiae (Ramon) M.Mulas, J.Neiva & Á.Israel, comb. nov. (Phaeophyceae)

APPENDIX 1. — Bayesian 50% majority-rule consensus COI tree of Treptacantha Kützing (sensu Orellana et al. (2019) synonym of Cystoseira C.Agardh clade VI of Draisma et al. (2010), unique sequences only), showing the phylogenetic position of T. rayssiae (Ramon) M.Mulas, J.Neiva & Á.Israel, comb. nov. Bayesian posterior probabilities (>0.50) and maximum likelihood bootstrap support values, respectively. The outgroup used is T. abies-marina (S.G.Gmelin) C.Agardh, the most divergent of the genus (Bruno de Sousa et al. 2019). Scale bar: 0.006 BIPP (Bayesian Inference Posterior Probability).

FIG. 1 in Genetic affinities and biogeography of putative Levantine-endemic seaweed Treptacantha rayssiae (Ramon) M.Mulas, J.Neiva & Á.Israel, comb. nov. (Phaeophyceae)

FIG. 1. —Reported distribution of Treptacantha rayssiae (Ramon) M.Mulas, J.Neiva & Á.Israel, comb. nov. (synonym of Cystoseira rayssiae): A, occurrence records based on literature records; B, distribution (black dots) in Israeli Mediterranean Sea shores as reported in Ramon (2000) based on herbaria collections. The squares indicate the origin of samples analyzed in this study: Achziv (Gesher Haziv), Tel Shikmona and HaBonim.

opencc-by-4.0Aug 2018View details →

Fig. 2 in A coalescent-based estimator of genetic drift, and acoustic divergence in the Pteronotus parnellii species complex

Fig. 2 Echolocation call frequency by island by sex and its relation to mass on the call frequency (F(1, 49) = 0.435, P value = 0.512). The body dimensions. a Boxplots of echolocation frequency (summarizing 95% HPD of population differences in means for body mass was 10 calls/individual). Bayesian 95% high-probability density (HPD) of 0.89–2.29 g. c Call frequency as a function of forearm length. Anathe difference in call frequency means between Puerto Rico and Hislyses of covariance support little influence of forearm length on the call paniola was 5.2–6.0 kHz. b Call frequency as a function of body mass. frequency (F(1, 52) = 2.851, P value = 0.097). The 95% HPD of Analyses of covariance support very different call frequency for island population differences in means for forearm lengths was −1.82, groups (F(1, 49) = 704.260, P value = 0.000), but no influence of body 0.422 mm

opencc-by-4.0Aug 2018View details →

Fig. 1 Results from IMa2 in A coalescent-based estimator of genetic drift, and acoustic divergence in the Pteronotus parnellii species complex

Fig. 1 Results from IMa2 analyses of Pteronotus parnellii s.l. populations. a Joint posterior density of Ne estimates for island populations. b Divergence time estimates between Puerto Rican and Hispaniolan populations in thousands of years (Ka)

opencc-by-4.0Aug 2018View details →

Fig. 3 in A coalescent-based estimator of genetic drift, and acoustic divergence in the Pteronotus parnellii species complex

Fig. 3 Densities of Bayesian posteriors for FST based on betweenpopulation migration rates, and PST for relevant phenotypic variables (Brommer et al. 2014). The lines show the 95th percentile for the corresponding FST, and the 5% percentile for the PST. The overlap between PST body mass and FST Hispaniola was 0.023, for FST Puerto Rico it was 0.084; between PST call frequency and FST Hispaniola was <0.001, for FST Puerto Rico it was 0.003; and between PST forearm length and FST Hispaniola was 0.049, for FST Puerto Rico it was 0.125

Data from: Strong selection is poorly aligned with genetic variation in Ipomoea hederacea

The multivariate evolution of populations is the result of the interactions between natural selection, drift, and the underlying genetic structure of the traits involved. Covariances among traits bias responses to selection, and the multivariate axis which describes the greatest genetic variation is expected to be aligned with patterns of divergence across populations. An exception to this expectation is when selection acts on trait combinations lacking genetic variance, which limits evolutionary change. Here we used a common garden field experiment of individuals from 57 populations of Ipomoea hederacea to characterize linear and nonlinear selection on five quantitative traits in the field. We then formally compare patterns of selection to previous estimates of within-population genetic covariance structure (the G-matrix) and population divergence in these traits. We found that selection is poorly aligned with previous estimates of genetic covariance structure and population divergence. In addition, the trait combinations favoured by selection were generally lacking genetic variation, possessing approximately 15-30% as much genetic variation as the most variable combination of traits. Our results suggest that patterns of population divergence are likely the result of the interplay between adaptive responses, correlated response, and selection favoring traits lacking genetic variation.