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opencc-by-4.0Sep 2021View details →

dataset related to article "Multiple Genetic Rare Variants in Autism Spectrum Disorders: A Single-Center Targeted NGS Study"

dataset contains: NGS data (.vcf; .bam; .bam.bai) of all 40 ASD patients analysed in the study at title

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 →

Consequences of the Last Glacial Period on the Genetic Diversity of Southeast Asians

********* Observed data ********* The file ObsData.arp contains the sequences of the mtDNA hypervariable I region from 720 individuals belonging to 25 Southeast Asian populations used as input file to compute the summary statistics with Arlequin. For further details on the format and available Summary statistics see the manual of Arlequin.   ********* Input files for simulations ********* For each evolutionary scenario (NONE, LGP, LDD and LGP&LDD) find a folder (named after the scenario) containing the input files to perform 100 simulations. To run the simulations one should access the command line and execute:  ./ABCsampler abc_sensitivity.input Input files for SPLATCHE3, Arlequin and ABCtoolbox are included (for further details on them see the manual of these software). ********* Selection of the best-fitting evolutionary scenario ********* The R script (ModelSelection.R) can be used to select the evolutionary scenario that better fits the observed data, using the multinomial logistic regression method and the neural networks based method. Firstly, one will need the summary statistics obtained from observed data (the file entitled ObsSS.txt). Then, one will need the files containing the output files of the simulations under each scenario, i.e., the genetic parameters used under each simulation and the computed summary statistics. Please, note that the output of the ABCtoolbox is a single file containing all this information, but we prefer to use a file with the summary statistics and another with the parameters. Here, we provide example files obtained from 100 simulations of each scenario: - ssNONE.txt, the summary statistics computed from 100 simulations under the scenario NONE - parNONE.txt, the genetic and demographic parameters per simulation under the scenario NONE - ssLGP.txt, the summary statistics computed from 100 simulations under the scenario LGP - parLGP.txt, the genetic and demographic parameters per simulation under the scenario LGP - ssLDD.txt, the summary statistics computed from 100 simulations under the scenario LDD - parLDD.txt, the genetic and demographic parameters per simulation under the scenario LDD - ssLGP_LDD.txt, the summary statistics computed from 100 simulations under the scenario LGP&LDD - parLGP_LDD.txt, the genetic and demographic parameters per simulation under the scenario LGP&LDD To run the script the directory containing these files has to be specified in the script. For details see Csilléry, et al. (2012): "Approximate Bayesian computation (ABC) in R: a Vignette." ********* Parameters estimation ********* The folder named ParametersEstimation contains all the input files to estimate the genetic and demographic parameters under the selected evolutionary scenario (LGP&LDD). Within the folder, one will find the summary statistics obtained under the selected scenario and the corresponding parameters (completeEstimator_LGP-LDD.txt), the summary statists from observed data (obs11SS.txt) and all the remaining input files to run ABCestimator (for further detail on these files see the manual of ABCtoolbox).

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-zeroOct 2021View details →

Contributions of genetic and non-genetic sources to variation in cooperative behaviour in a cooperative mammal

The evolution of cooperative behaviour is a major area of research among evolutionary biologists and behavioural ecologists, yet there are few estimates of its heritability or of its evolutionary potential and long-term studies of identifiable individuals are required to disentangle genetic and non-genetic components of cooperative behaviour. Here we use long-term data on over 1800 individually recognisable wild meerkats (Suricata suricatta) collected over 30 years and a multi-generational genetic pedigree to partition phenotypic variation in three cooperative behaviours (babysitting, pup feeding and sentinel behaviour) into individual, additive genetic and other sources, and to assess their repeatability and heritability. In addition to strong effects of sex, age and dominance status, we found significant repeatability in individual contributions to all three types of cooperative behaviour both within and across breeding seasons. Like most other studies of the heritability of social behaviour, we found that the heritability of cooperative behaviour was low. However, our analysis suggests that a substantial component of the repeatable individual differences in cooperative behaviour that we observed was a consequence of additive genetic variation. Our results consequently indicate that cooperative behaviour can respond to selection, and suggest scope for further exploration of the genetic basis of social behaviour.

opencc-zeroOct 2021View details →

Species ecology explains the various spatial components of genetic diversity in tropical reef fishes

Generating genomic data for 19 tropical reef fish species of the Western Indian Ocean, we investigate how species ecology influences genetic diver- sity patterns from local to regional scales. We distinguish between the α, β and γ components of genetic diversity, which we subsequently link to six ecological traits. We find that the α and γ components of genetic diversity are strongly correlated so that species with a high total regional genetic diversity display systematically high local diversity. The α and γ diversity components are negatively associated with species abundance recorded using underwater visual surveys and positively with body size. Pelagic larval duration is found to be negatively related to genetic β diversity supporting its role as a dispersal trait in marine fishes. Deviation from the neutral theory of molecular evolution motivates further effort to understand the processes shaping genetic diversity and ultimately the diversification of the exceptional diversity of tropical reef fishes.

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-by-4.0Oct 2022View details →

Association of genetic variation at the GJA5 locus with motor progression in Parkinson's

These are the GWAS summary statistics generated from the study described in the title

opencc-by-4.0Nov 2022View details →

Deep ecomorphological and genetic divergence in Steller's Jays (Cyanocitta stelleri, Aves: Corvidae)

The relationship between ecology and morphology is a cornerstone of evolutionary biology, and quantifying variation across environments can shed light on processes that give rise to biodiversity. Three morphotypes of the Steller’s Jay (Cyanocitta stelleri) occupy different ecoregions in western North America that vary in climate and landcover. These morphotypes (Coastal, Interior, Rocky Mountain) differ in size, plumage coloration, and head pattern. We sampled 1,080 Steller’s Jays from 68 populations (plus 11 outgroups) to address three main questions using data on morphology, plumage, genetics (mtDNA, microsatellites), and ecological niches: (1) How do phenotypic and genetic traits vary within and among populations, morphotypes, and ecoregions? (2) How do population-level differences in Steller’s Jays compare to other sister species pairs of North American birds? (3) What can we infer about the population history of Steller’s Jays in relation to past climates, paleoecology, and niche evolution? We found substantial morphological, genetic, and ecological differentiation among morphotypes. The greatest genetic divergence separated Coastal and Interior morphotypes from the Rocky Mountain morphotype, which was associated with warmer, drier, and more open habitats. Microsatellites revealed additional structure between Coastal and Interior groups. The deep mtDNA split between Coastal/Interior and Rocky Mountain lineages of Steller’s Jay (ND2 ~7.8%) is older than most North American avian sister species and dates to approximately 4.3 mya. Interior and Rocky Mountain morphotypes contact across a narrow zone with steep clines in traits and reduced gene flow. The distribution of the three morphotypes coincides with divergent varieties of ponderosa pine and Douglas fir. Species distribution models support multiple glacial refugia for Steller’s Jays. Our integrative dataset combined with extensive geographic sampling provides compelling evidence for recognizing at least two species of Steller’s Jay.

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-4.0Nov 2020View details →

Full dataset for 'RNA-binding proteins in human genetic disease'

This extended version of the Supplementary Table S1  of the publicaiton "RNA-binding proteins in human genetic disease" (Gebauer, F., Schwarzl, T., Valcárcel, J. et al. Nat Rev Genet 22, 185–198 (2021). https://doi.org/10.1038/s41576-020-00302-y) contains all human RNA-binding proteins (RBPs) found in at least one high-throughput RNA interactome caputure study with all their annotation along with known RBP. The whole set is available as download on RBPbase with additional annotation and additional studies. This table contains the version used in the original publication

opencc-by-4.0Dec 2021View details →

Integrative genetic analyses illuminates ALS heritability and identifies novel risk genes

Amyotrophic lateral sclerosis (ALS), the major adult onset motor neuron disease, has substantial heritability, in part shared with fronto-temporal dementia (FTD). We show here that ALS heritability is enriched in splicing variants and in binding sites of 6 RNA binding proteins including TDP-43 and FUS. A discovery and replication transcriptome wide association study (TWAS) identified 6 loci associated with ALS, 3 in known ALS loci (C9ORF72, SCFD1, SLC9A8) and 3 novel loci including NUP50 encoding for the nucleopore basket protein NUP50 In our meta-analysis of TWAS cohorts, NUP50 common variant was associated with ALS and to decreased expression of NUP50 in the central nervous system. Independently, we further show association of rare variants in NUP50 with ALS risk (P = 3.71.10-03; odds ratio  = 3.29; 95%CI, 1.37 to 7.87) in a cohort of 9,390 ALS/FTD patients and 4,594 controls. Cells from one patient carrying a NUP50 frameshift mutation displayed a decreased levels of NUP50. Loss of NUP50 leads to neuronal death in cultured neurons, and motor defects in Drosophila and zebrafish models. Thus, our study identifies alterations in splicing in neurons as a critical pathogenic process in ALS, uncovers several new loci potentially contributing to ALS, and provides genetic evidence linking nuclear pore defects to ALS.

Fig. 2. a in Updated distribution of the endangered freshwater stingray Urogymnus polylepis in Malaysia, with notes on biology and genetics

Fig. 2. a, Size range (left—weight in kg, right—disc width in cm) by sex for Urogymnus polylepis sighted in Malaysia in comparison with maximum sizes reported from specimens in Thailand (Weight of 600 kg in Monkolprasit & Roberts, 1990; Disc width of 250 cm in Phomikong et al., 2019). b, Number of sightings over period of time and size range of animals sighted in Malaysia.

Fig. 5 in Updated distribution of the endangered freshwater stingray Urogymnus polylepis in Malaysia, with notes on biology and genetics

Fig. 5. COI gene phylogenetic relationships and genetic distance of Urogymnus polylepis and its sister species. The bootstrap values (ML/ Bayesian Inference) are shown at the branches.

Fig. 1 in Updated distribution of the endangered freshwater stingray Urogymnus polylepis in Malaysia, with notes on biology and genetics

Fig. 1. Updated distribution map of Urogymnus polylepis in Malaysia based on citizen reports and direct sightings between 2011–2021). Blue = published sightings, red = unpublished sightings (see Appendices 3 and 4 for detailed information on individual sightings and river location).

Fig. 4. a in Updated distribution of the endangered freshwater stingray Urogymnus polylepis in Malaysia, with notes on biology and genetics

Fig. 4. a, Butchered female Urogymnus polylepis (disc width ca 190 cm) caught in the waters near Mukah, Sarawak in 2016 together with 4 fully developed pups. b, Underside of one of the pups. c, Butchered male U. polylepis (disc width ca 120 cm) caught in the waters near Sandakan, Sabah in 2018.

opencc-zeroDec 2022View details →

From high masked to high realized genetic load in inbred Scandinavian wolves

When new mutations arise at functional sites they are more likely to impair than improve fitness. If not removed by purifying selection, such deleterious mutations will generate a genetic load that can have negative fitness effects in small populations and increase the risk of extinction. This is relevant for the highly inbred Scandinavian wolf (Canis lupus) population, founded by only three wolves in the 1980s and suffering from inbreeding depression. We used functional annotation and evolutionary conservation scores to study deleterious variation in a total of 209 genomes from both the Scandinavian and neighboring wolf populations in northern Europe. The masked load (deleterious mutations in heterozygote state) was highest in Russia and Finland with deleterious alleles segregating at lower frequency than neutral variation. Genetic drift in the Scandinavian population led to the loss of ancestral alleles, fixation of deleterious variants and a significant increase in the per-individual realized load (deleterious mutations in homozygote state; an increase by 45% in protein-coding genes) over five generations of inbreeding. Arrival of immigrants gave a temporary genetic rescue effect with ancestral alleles re-entering the population and thereby shifting deleterious alleles from homozygous into heterozygote genotypes. However, in the absence of permanent connectivity to Finnish and Russian populations, inbreeding has then again led to the exposure of deleterious mutations. These observations provide genome-wide insight into the magnitude of genetic load and genetic rescue at the molecular level, and in relation to population history. They emphasize the importance of securing gene flow in the management of endangered populations.