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opencc-zeroSep 2021View details →

Data from: Genetic diversity in a long-lived mammal is explained by the past's demographic shadow and current connectivity

Within-species genetic diversity is crucial for the persistence and integrity of populations and ecosystems. Conservation actions require an understanding of factors influencing genetic diversity, especially in the context of global change. Both population size and connectivity are factors greatly influencing genetic diversity; the relative importance of these factors can however change through time. Hence, quantifying the degree to which population size or genetic connectivity are shaping genetic diversity, and at which ecological time scale (past or present), is challenging, yet essential for the development of efficient conservation strategies. In this study, we estimated the genetic diversity of 42 colonies of Rhinolophus hipposideros, a long-lived mammal vulnerable to global change, sampling locations spanning its continental northern range. We present an integrative approach that disentangles and quantifies the contribution of different connectivity measures in addition to contemporary colony size and historic bottlenecks in shaping genetic diversity. In our study, the best model explained 64% of the variation in genetic diversity. It included historic bottlenecks, contemporary colony sizes, connectivity and a negative interaction between the latter two. Contemporary connectivity explained most genetic diversity when considering a 65 km radius around the focal colonies, emphasizing the large geographic scale at which the positive impact of connectivity on genetic diversity is most profound and hence the minimum scale at which conservation should be planned. Our results highlight that the relative importance of the two main factors shaping genetic diversity varies through time, emphasizing the relevance of disentangling them to ensure appropriate conservation strategies.

opencc-by-4.0Sep 2021View details →

Data related to research article: Towards mouse genetic-specific RNA-sequencing read mapping

This dataset contains data related to the research article: "Towards mouse genetic-specific RNA-sequencing read mapping".

opencc-by-4.0Oct 2021View details →

Genetic Algorithm-Based Fuzzy Inference System for Describing Execution Tracing Quality - Collected Data

The deposited data files were used to perform the analysis introduced in the paper: Tamas Galli, Francisco Chiclana and Francois Siewe, "Genetic Algorithm Based Fuzzy Inference System for Describing Execution Tracing Quality", Mathematics, MDPI, 2021. The data were collected through an online questionnaire. The questionnaire has been exported in pdf format and uploaded as file: form_data_collection.pdf. The paper above introduces the steps of analysing, processing the data, constructing, pre-validating the model. The final validation was done over the online questionnaire exported and uploaded in pdf format as form_model_validation.pdf. Questionnaire Part 1, data file: all_usecases_wide.csv The CSV file contains the responses for each use case of part 1 of the online questionnaire enclosed. The columns contain the assigned values from the respondents, on a scale [0; 100]. The following variables are linked to each use case: Accuracy, Legibility, DesignAndImplementation, and Security. These form the input variables of execution tracing quality, while the variable Quality designates the quality of execution tracing. Each fifth column is followed by a column UseCase to designate the use case which is described by the previous five columns. The definitions of the variables can be found in the questionnaire. Questionnaire Part 2, data file: all_real_projects_scores.csv The CSV file contains the responses for real projects in part 2 of the online questionnaire enclosed. The columns contain the assigned values from the respondents, on a scale [0; 100]. Six variables are linked to each response: Accuracy, Legibility, DesignAndImplementation, and Security, which form the input variables of execution tracing quality, while the variable Quality designates the quality of execution tracing. In addition, the variable Type indicates the type of the project, such as server application, desktop application, web UI, mobile application, or embedded application. The definitions of the variables can be found in the questionnaire. Questionnaire Part 3, data file: all_extrem_values_wide.csv The CSV file contains the assigned execution tracing quality value to the provided combination of extreme input values in part 3 of the online questionnaire enclosed. The column IDs represent the question IDs in the survey. The definitions of the variables can be found in the questionnaire.

opencc-zeroOct 2021View details →

Data and code for: Plastic and quantitative genetic divergence mirror environmental gradients among wild, fragmented populations of Impatiens capensis

Premise of the study: Habitat fragmentation generates molecular genetic divergence among isolated populations but few studies have assessed phenotypic divergence and fitness in populations where the genetic consequences of habitat fragmentation are known. Phenotypic divergence could reflect plasticity, local adaptation, and/or genetic drift. Methods: We examined patterns and potential drivers of phenotypic divergence among 12 populations of jewelweed (Impatiens capensis Meerb.) that show strong molecular genetic signals of isolation and drift among fragmented habitats. We measured morphological and reproductive traits in both maternal plants within natural populations and their self-fertilized progeny grown together in a common garden. We also quantified environmental divergence between home sites and the common garden. Key results: Populations with less molecular genetic variation expressed less maternal phenotypic variation. Progeny in the common garden converged in phenotypes relative to their wild mothers but retained among-population differences in morphology, survival, and reproduction. Among-population phenotypic variance was 3-10x greater in home sites than in the common garden for 6 of 7 morphological traits measured. Patterns of phenotypic divergence paralleled environmental gradients in ways suggestive of adaptation. Progeny resembled their mothers less as the environmental distance between their home site and the common garden increased. Conclusions: Despite strong molecular signatures of isolation and drift, phenotypic differences among these Impatiens populations appear to reflect both adaptive quantitative genetic divergence and plasticity. Quantifying the extent of local adaptation and plasticity and how these covary with molecular and phenotypic variation help us predict when populations may lose their adaptive capacity.

opencc-zeroNov 2022View details →

Data for: Inferring population connectivity in Eastern Massasauga Rattlesnakes (Sistrurus catenatus) using landscape genetics

Assessing the environmental factors that influence the ability of a threatened species to move through the landscape can be used to identify conservation actions that connect isolated populations. However, direct observations of species' movement are often limited making the development of alternate approaches necessary. Here we use landscape genetic analyses to assess the impact of landscape features on the movement of individuals between local populations of a threatened snake, the Eastern Massasauga Rattlesnake (Sistrurus catenatus). We linked connectivity data with habitat information from two landscapes of similar size: a large region of unfragmented habitat and a previously studied fragmented landscape consisting of isolated patches of habitat. We used this analysis to identify features of the landscape where modification or acquisition would enhance population connectivity in the fragmented region. We found evidence that current connectivity is impacted by both contemporary landcover features, especially roads, and inherent landscape features such as elevation. Next, we derived estimates of expected movement ability using a recently developed pedigree-based approach and Least Cost Paths through the unfragmented landscape. We then used our pedigree and resistance map to estimate resistance polygons of the potential extent for S. catenatus movement in the fragmented landscape. These polygons identify possible sites for future corridors connecting currently isolated populations in this landscape by linking the impact of future habitat modification or land acquisition to dispersal ability in this species. Overall, our study shows how modeling landscape resistance across differently fragmentated landscapes can identify habitat features that affect contemporary movement in threatened species in fragmented landscapes and how this information can be used to guide mitigation actions whose goal is to connect isolated populations.

opencc-zeroNov 2022View details →

Data for: Spatial and temporal genetic stock composition of river herring bycatch in southern New England Atlantic herring and mackerel fisheries

Anadromous river herring (alewife and blueback herring) persist at historically low abundances and are caught as bycatch in commercial fisheries, potentially preventing recovery despite conservation efforts. We used newly established single-nucleotide polymorphism genetic baselines for alewife and blueback herring to define fine-scale reporting groups for each species. We then determined the occurrence of fish from these reporting groups in bycatch samples from a Northwest Atlantic fishery over four years.Within sampled bycatch events, the highest proportions of alewife were from the Block Island (34%) and Long Island Sound (22%) reporting groups, while for blueback herring the highest proportions were from the Mid-Atlantic (47%) and Northern New England (24%) reporting groups. We then quantified stock-specific mortality in a focal geographic area (~3500 km2 including Block Island Sound) of high bycatch incidence and sampling effort, where the most accurate estimates of mortality could be made. During this period, we estimate that bycatch took about 4.6 million alewife and 1.2 million blueback herring, highlighting the need to reduce bycatch mortality for the most depleted river herring stocks.

opencc-by-3.0-usJul 2022View details →

Yield Prediction Through Integration of Genetic, Environment, and Management Data Through Deep Learning: Cleaned Data

The included files and script are to allow for reconstruction of the data directory and cleaned data used in "Yield Prediction Through Integration of Genetic, Environment, and Management Data Through Deep Learning" ( https://doi.org/10.1101/2022.07.29.502051 ). Code used is available at 10.5281/zenodo.7401113 . <table> <tbody> <tr> <th>Filename</th> <th>Description</th> </tr> <tr> <td>interim.tar.gz</td> <td>Contains site grouping dictonary</td> </tr> <tr> <td>processed.tar.gz</td> <td>Processed data</td> </tr> <tr> <td>raw.tar.gz</td> <td>Input data</td> </tr> <tr> <td>SetupInstructions.sh</td> <td>Bash script to prepare folders and unzipped data expected by code in 10.5281/zenodo.7401113</td> </tr> <tr> <td>SetupInstructions.txt</td> <td>Instructions for unzipping the data</td> </tr> <tr> <td>Train_Test_Split_Reference_Phenotypes.csv</td> <td>Reference spreadsheet to allow for easily exploring training and test set groupings</td> </tr> </tbody> </table> <ul> </ul> This work was supported through funding from the USDA Agricultural Research Service, ARS project number 5070-21000-041-000-D. Raw data provided by the [Genomes to Field Initiative](https://www.genomes2fields.org/) and the [Daymet database](https://daymet.ornl.gov/).

opencc-by-4.0Nov 2022View details →

Genetic Features of the Marine Polychaete Sirsoe methanicola from Metagenomic Data

WebAUGUSTUS input and output data used in for eukaryotic gene prediction in Sirsoe methanicola: WebAUGUSTUS input data: <ol> <li>capitella.fa - Nucleotide genomic sequence of Capitella teleta (NCBI accession: GCA_000328365.1)</li> <li>capitella-protein.faa - Protein sequences in the Capitella teleta genome (NCBI accession: GCA_000328365.1)</li> <li>big-contigs-wrapped.fa - Contigs >= 3,000 bp long assembled from the S. methanicola metagenomes (NCBI BioProject ID PRJNA689840) that did not bin into any bacterial MAGs</li> <li>small-contigs-wrapped.fa - Contigs< 3,000 bp long assembled from the S. methanicola metagenomes (NCBI BioProject ID PRJNA689840) that did not bin into any bacterial MAGs</li> </ol> WebAUGUSTUS output data: <ol> <li>augustus.bigcontigs.gff - WebAUGUSTUS GFF output file for contigs >=3,000 bp</li> <li>augustus.smallcontigs.gff - WebAUGUSTUS GFF output file for contigs <3,000 bp</li> <li>augustus.all.faa - All protein sequences predicted from the S. methanicola metagenomes using WebAUGUSTUS</li> </ol>

opencc-zeroFeb 2023View details →

Data for: Amazonian birds in more dynamic habitats have less population genetic structure and higher gene flow

Understanding the factors that govern variation in genetic structure across species is key to the study of speciation and population genetics. Genetic structure has been linked to several aspects of life history, such as foraging strategy, habitat association, migration distance, and dispersal ability, all of which might influence dispersal and gene flow. Comparative studies of population genetic data from species with differing life histories provide opportunities to tease apart the role of dispersal in shaping gene flow and population genetic structure. Here, we examine population genetic data from sets of bird species specialized on a series of Amazonian habitat types hypothesized to filter for species with dramatically different dispersal abilities: stable upland forest, dynamic floodplain forest, and highly dynamic riverine islands. Using genome-wide markers, we show that habitat type has a significant effect on population genetic structure, with species in upland forest, floodplain forest, and riverine islands exhibiting progressively lower levels of structure. Although morphological traits used as proxies for individual-level dispersal ability did not explain this pattern, population genetic measures of gene flow are elevated in species from more dynamic riverine habitats. Our results suggest that the habitat in which a species occurs drives the degree of population genetic structuring via its impact on long-term fluctuations in levels of gene flow, with species in highly dynamic habitats having particularly elevated gene flow. These differences in genetic variation across taxa specialized in distinct habitats may lead to disparate responses to environmental change or habitat-specific diversification dynamics over evolutionary time scales.

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.

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.

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.

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.

Code and initial metapopulation data for model construction and simulation analyses for: Genetic rescue from protected areas is modulated by migration, hunting rate and timing of harvest

Migrants from protected areas may buffer the risk of harvest-induced evolutionary changes in exploited populations that face strong selective harvest pressures in both terrestrial and marine ecosystems. Understanding the mechanisms favouring genetic rescue through migration could help ensure sustainable harvest outside protected areas and conserve genetic diversity inside those areas. We developed a stochastic individual-based metapopulation model to evaluate the potential for migration from protected areas to mitigate the evolutionary consequences of selective harvest. We parameterized the model with detailed data from individual monitoring of two populations of bighorn sheep subjected to trophy hunting. We tracked horn length through time in a metapopulation including large protected and trophy-hunted populations connected through male breeding migrations. We quantified and compared declines in horn length and rescue potential under various combinations of migration rate, hunting rate in hunted areas and temporal overlap in timing of harvest and migrations, which affects the migrants' survival and chances to breed within exploited areas. Our simulations suggest that the effects of size-selective harvest on male horn length in hunted populations can be dampened or avoided if harvest pressure is low, migration rate is substantial, and migrants have a low risk of being shot. Intense size-selective harvest impacts the phenotypic and genetic diversity in horn length, and population structure through changes in proportions of large-horned males, sex ratio and age structure. When hunting pressure is high and overlaps with male migrations, effects of selective removal also emerge in the protected population, so that instead of a genetic rescue of hunted populations, our model predicts undesirable effects inside protected areas. Our results stress the importance of a metapopulational approach to management, to promote genetic rescue from protected areas and limit ecological and evolutionary impacts of harvest on both harvested and protected populations.

opencc-by-4.0Apr 2023View details →

Archived Data - Genetic breaks caused by ancient forest fragmentation: phylogeography of Staudtia kamerunensis (Myristicaceae) reveals distinct clusters in the Congo Basin

List of the 400 genotyped Staudtia kamerunensis accessions from Central Africa included in Vanden Abeele & Matvijev et al. 2023 - Tree Genetics & Genomes, and the corresponding alleles for each of the 14 microsatellite markers (0-0 indicates missing alleles)

opencc-zeroMay 2023View details →

Revisiting the historical scenario of a disease dissemination using genetic data and Approximate Bayesian Computation methodology: the case of Pseudocercospora fijiensis invasion in Africa

The reconstruction of geographic and demographic scenarios of dissemination for invasive pathogens of crops is a key step towards improving the management of emerging infectious diseases. Nowadays, the reconstruction of biological invasions typically uses the information of both genetic and historical information to test for different hypotheses of colonization. The Approximate Bayesian Computation framework and its recent Random Forest development (ABC-RF) have been successfully used in evolutionary biology to decipher multiple histories of biological invasions. Yet, for some organisms, typically plant pathogens, historical data may not be reliable notably because of the difficulty to identify the organism and the delay between the introduction and the first mention. We investigated the history of the invasion of Africa by the fungal pathogen of banana, Pseudocercospora fijiensis, by testing the historical hypothesis against other plausible hypotheses. We analysed the genetic structure of eight populations from six eastern and western African countries, using 20 microsatellite markers, and tested competing scenarios of population foundation using the ABC-RF methodology. We do find evidence for an invasion front consistent with the historical hypothesis, but also for the existence of another front never mentioned in historical records. We question the historical introduction point of the disease on the continent. Crucially, our results illustrate that even if ABC-RF inferences may sometimes fail to infer a single, well-supported scenario of invasion, they can be helpful in rejecting unlikely scenarios, which can prove much useful to shed light on disease dissemination routes.

opencc-zeroMay 2023View details →

Data for: Genetic control of grain amino acid composition in a UK soft wheat mapping population

Wheat is a major source of nutrients for populations across the globe, but the amino acid composition of wheat grain does not provide optimal nutrition. The nutritional value of wheat grain is limited by low concentrations of lysine (the most limiting essential amino acid) and high concentrations of free asparagine (precursor to the processing contaminant acrylamide). There are currently few available solutions for asparagine reduction and lysine biofortification through breeding. In this study, we investigated the genetic architecture controlling grain-free amino acid composition and its relationship to other traits in a Robigus × Claire doubled haploid population. Multivariate analysis of amino acids and other traits showed that the two groups are largely independent of one another, with the largest effect on amino acids being from the environment. Linkage analysis of the population allowed the identification of QTL controlling free amino acids and other traits, and this was compared against genomic prediction methods. Following the identification of a QTL controlling free lysine content, wheat pangenome resources facilitated analysis of candidate genes in this region of the genome. These findings can be used to select appropriate strategies for lysine biofortification and free asparagine reduction in wheat breeding programmes.

opencc-zeroJun 2023View details →

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.