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67 results for “Temporal genomics”
Tracking Selection using Temporal Population Genomics Data
<p>This repository contains the implementation of a pipeline to run the simulations and to produce a reference table for the ABC-RF inference of demography and selection. In its new release, this repository contains the whole-genome polymorphism of contemporary and museum specimens of <em>Apis mellifera</em> feral populations analyzed by Cridland et al. (2018).</p>
The practice and promise of temporal genomics for measuring evolutionary responses to global change
<p>Understanding the evolutionary consequences of anthropogenic change is imperative for estimating long-term species resilience. While contemporary genomic data can provide us with important insights into recent demographicic histories, investigating past change using present genomic data alone has limitations. In comparison, temporal genomics studies, defined herein as those that incorporate time series genomic data, leverage museum collections and repeated field sampling to directly examine evolutionary change. As temporal genomics is applied to more systems, species, and questions, best practices can be helpful guides to make the most efficient use of limited resources. Here, we conduct a systematic literature review to synthesize the effects of temporal genomics methodology on our ability to detect evolutionary changes. We focus on studies investigating recent change within the past 200 years, highlighting evolutionary processes that have occurred during the past two centuries of accelerated anthropogenic pressure. We first identify the most frequently studied taxa, systems, questions, and drivers, before highlighting overlooked areas where further temporal genomics studies may be particularly enlightening. Then, we provide guidelines for future study and sample designs while identifying key considerations that may influence statistical and analytical power. Our aim is to provide recommendations to a broad array of researchers interested in using temporal genomics in their work.</p>
Temporal population structure, a genetic dating method for ancient Eurasian genomes from the past 10,000 years
<p>Radiocarbon dating is the gold standard in archeology to estimate the age of skeletons, a key to studying their origins. Many published ancient genomes lack reliable and direct dates, which results in obscure and contradictory reports. Here, we developed the Temporal Population Structure (TPS), the first DNA-based dating method for ancient genomes ranging from the Late Mesolithic to modern-days, and applied it to 3,591 ancient and 1,307 modern Eurasians. We show that TPS predictions align with their known dates and correctly account for kin relationships. TPS dating of poorly dated Eurasian samples resolved conflicting reports in the literature, as illustrated by one test case. We demonstrated how TPS improved the ability to study phenotypic traits over time.</p>
The practice and promise of temporal genomics for measuring evolutionary responses to global change
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Temporal population structure, a genetic dating method for ancient Eurasian genomes from the past 10,000 years
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Common barriers, but temporal dissonance: genomic tests suggest ecological and paleo-landscape sieves structure a coastal riverine fish community
<p>Assessments of spatial and temporal congruency across taxa from genetic data provide insights into the extent to which similar processes structure communities. However, for coastal regions that are affected continuously by cyclical sea-level changes over the Pleistocene, congruent interspecific response will not only depend upon co-distributions, but also on similar dispersal histories among taxa. Here, we use SNPs to test for concordant genetic structure among four co-distributed taxa of freshwater fishes (Teleostei: Characidae) along the Brazilian Atlantic coastal drainages. Based on population relationships and hierarchical genetic structure analyses, we identify all taxa share the same geographic structure suggesting the fish utilized common passages in the past to move between river basins. In contrast to this strong spatial concordance, model-based estimates of divergence times indicate that despite common routes for dispersal, these passages were traversed by each of the taxa at different times resulting in varying degrees of genetic differentiation across barriers with most divergences dating to the Upper Pleistocene, even when accounting for divergence with gene flow. Interestingly, when this temporal dissonance is viewed through the lens of the species-specific ecologies, it suggests that an ecological sieve influenced whether species dispersed readily, with an ecological generalist showing the highest propensity for historical dispersal among the isolated rivers of the Brazilian coast (i.e., the most recent divergence times and frequent gene flow estimated for barriers). We discuss how our findings, and in particular what the temporal dissonance, despite common geographic passages, suggest about past dispersal structuring coastal communities as a function of ecological and paleo-landscape sieves.</p>
DArTseq genetic dataset associated with the article "Hybrids as mirrors of the past: genomic footprints reveal spatio-temporal dynamics and extinction risk of alpine extremophytes in the mountains of Central Asia"
<p>Description: This file stores genetic information on the single nucleotide polymorphism markers (SNPs) in the examined alkali grasses (Poaceae: Puccinellia). The dataset was generetad by Genome-Wide Restriction Fragment Analysis via the DArTseq platform (Diversity Arrays Technology Pty Ltd, Canberra, Australia), which combines complexity reduction methods, fragment size selection, and high-throughput sequencing, optimised for a target organism. The file contains raw data.<br> <br>Usage notes: We used R (version 4.2.2, 2022-10-31; https://www.R-project.org/) and RStudio (version 2022.07.2+576 "Spotted Wakerobin" Release (e7373ef832b49b2a9b88162cfe7eac5f22c40b34, 2022-09-06; http://www.rstudio.com/) on Windows 8.1 to handle this file. We used the dartR R-package (version 2.7.2) with necessary dependencies to import, proccess and analyse this data file as an object of a class genlight (dartR) in the R environment. You may also handle the file as an object of a class genlight using the adegenet and ade4 R-packages. To learn more about installation procedure and how to use of the R-packages visit: https://cran.r-project.org/web/packages/available_packages_by_name.html.<br> </p>
Data for: Leveraging spatio-temporal genomic breeding value estimates of dry matter yield and herbage quality in ryegrass via random regression models
<p>Joint modeling of correlated multi-environment and multi-harvest data of perennial crop species may offer advantages in prediction schemes and a better understanding of the underlying dynamics in space and time. The goal of the present study was to investigate the relevance of incorporating the longitudinal dimension of within-season multiple measurements of forage perennial ryegrass traits in a reaction norm model setup that additionally accounts for genotype-environment interactions (G×E). Genetic parameters and accuracy of genomic breeding value (gEBV) predictions were investigated by fitting three random regression models (gRRM) using Legendre polynomial functions to the data. Genomic DNA sequencing of family pools of diploid perennial ryegrass was performed using DNA nanoball-based technology and yielded 56,645 single nucleotide polymorphisms which were used to calculate the allele frequency-based genomic relationship matrix. Biomass yield's estimated additive genetic variance and heritability values were higher in later harvests. The additive genetic correlations were moderate to low in early measurements and peaked at intermediates, with fairly stable values across the environmental gradient, except for the initial harvest data collection. This led to the conclusion that complex (G×E) arises from spatial and temporal dimensions in the early season, with lower re-ranking trends thereafter. In general, modeling the temporal dimension with a second-order orthogonal polynomial improved the accuracy of gEBV prediction for nutritive quality traits, but no gain in prediction accuracy was detected for dry matter yield. This study leverages the flexibility and usefulness of gRRM models for perennial ryegrass breeding and can be readily extended to other multi-harvest crops.</p>
Museum genomics of reveals temporal genetic stasis and global genetic diversity in Arabidopsis thaliana
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Data for: Leveraging spatio-temporal genomic breeding value estimates of dry matter yield and herbage quality in ryegrass via random regression models
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Common barriers, but temporal dissonance: genomic tests suggest ecological and paleo-landscape sieves structure a coastal riverine fish community
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The Pacific lamprey genomic divergence, association mapping, temporal Willamette Falls, spatial rangewide datasets
<p>High rates of dispersal can breakdown coadapted gene complexes. However, concentrated genomic architecture (i.e., genomic islands of divergence) can suppress recombination to allow evolution of local adaptations despite high gene flow. Pacific lamprey (<em>Entosphenus tridentatus</em>) is a highly dispersive anadromous fish. Observed trait diversity and evidence for genetic basis of traits suggests it may be locally adapted. We addressed whether concentrated genomic architecture could influence local adaptation for Pacific lamprey. Using two new whole genome assemblies and genotypes from 7,716 single nucleotide polymorphism (SNP) loci in 518 individuals from across the species range, we identified four genomic islands of divergence (on chromosomes 01, 02, 04, and 22). We determined robust phenotype-by-genotype relationships by testing multiple traits across geographic sites. These trait associations likely explain genomic divergence across the species' range. We genotyped a subset of 302 broadly distributed SNPs in 2,145 individuals for association testing for adult body size, sexual maturity, migration distance and timing, adult swimming ability, and larval growth. Body size traits were strongly associated with SNPs on chromosomes 02 and 04. Moderate associations also implicated SNPs on chromosome 01 as being associated with variation in female maturity. Finally, we used candidate SNPs to extrapolate a heterogeneous spatiotemporal distribution of these predicted phenotypes based on independent datasets of larval and adult collections. These maturity and body size results guide future elucidation of factors driving regional optimization of these traits for fitness. Pacific lamprey is culturally important and imperiled. This research addresses biological uncertainties that challenge restoration efforts.</p>
Genome reduction is associated with bacterial pathogenicity across different scales of temporal and ecological divergence - between species core gene alignments
<p><span>Emerging bacterial pathogens threaten global health and food security, and so it is important to ask whether these transitions to pathogenicity have any common features. We present a systematic study of the claim that pathogenicity is associated with genome reduction and gene loss. We compare broad-scale patterns across all bacteria, with detailed analyses of <i>Streptococcus suis</i>, an emerging zoonotic pathogen of pigs, which has undergone multiple transitions between disease and carriage forms. We find that pathogenicity is consistently associated with reduced genome size across three scales of divergence (between species within genera, and between and within genetic clusters of <i>S. suis</i>). While genome reduction is also found in mutualist and commensal bacterial endosymbionts, genome reduction in pathogens cannot be solely attributed to the features of their ecology that they share with these species, i.e. host restriction or intracellularity. Moreover, other typical correlates of genome reduction in endosymbionts (reduced metabolic capacity, reduced GC content, and the transient expansion of non-functional elements) are not consistently observed in pathogens. Together, our results indicate that genome reduction is a predictive marker of pathogenicity in bacteria.</span></p>
Plasmodium falciparum genomic surveillance reveals spatial and temporal trends, association of genetic and physical distance, and household clustering
<p>Molecular epidemiology using genomic data can help identify relationships between malaria parasite population structure, malaria transmission intensity, and ultimately help generate actionable data to assess the effectiveness of malaria control strategies. Genomic data, coupled with geographic information systems data, can further identify clusters or hotspots of malaria transmission, parasite genetic and spatial connectivity, and parasite movement by human or mosquito mobility over time and space. In this study, we performed longitudinal genomic surveillance in a cohort of 70 participants over four years from different neighborhoods and households in Thiès, Senegal—a region of exceptionally low malaria transmission (entomological inoculation rate (EIR) less than 1). Genetic identity (identity by state) was established using a 24 single nucleotide polymorphism molecular barcode and a multivariable linear regression model was used to establish genetic and spatial relationships. Our results show clustering of genetically similar parasites within households and a decline in genetic similarity of parasites with increasing distance. One household showed extremely high diversity and warrants further investigation as to the source of these diverse genetic types. This study illustrates the utility of genomic data with traditional epidemiological approaches for surveillance and detection of trends and patterns in malaria transmission not only by neighborhood but also by household. This approach can be implemented regionally and countrywide to strengthen and support malaria control and elimination efforts. </p>
Data from: Patterns of cyto-nuclear linkage disequilibrium in Silene latifolia: genomic heterogeneity and temporal stability
Non-random association of alleles in the nucleus and cytoplasmic organelles, or cyto-nuclear linkage disequilibrium (LD), is both an important component of a number of evolutionary processes and a statistical indicator of others. The evolutionary significance of cyto-nuclear LD will depend on both its magnitude and how stable those associations are through time. Here, we use a longitudinal population genetic data set to explore the magnitude and temporal dynamics of cyto-nuclear disequilibria through time. We genotyped 135 and 170 individuals from 16 and 17 patches of the plant species Silene latifolia in Southwestern VA, sampled in 1993 and 2008, respectively. Individuals were genotyped at 14 highly polymorphic microsatellite markers and a single-nucleotide polymorphism (SNP) in the mitochondrial gene, atp1. Normalized LD (D′) between nuclear and cytoplasmic loci varied considerably depending on which nuclear locus was considered (ranging from 0.005–0.632). Four of the 14 cyto-nuclear associations showed a statistically significant shift over approximately seven generations. However, the overall magnitude of this disequilibrium was largely stable over time. The observed origin and stability of cyto-nuclear LD is most likely caused by the slow admixture between anciently diverged lineages within the species' newly invaded range, and the local spatial structure and metapopulation dynamics that are known to structure genetic variation in this system.
Accurate genome-wide predictions of spatio-temporal gene expression during embryonic development
<p>This upload contains the expression prediction dataset discussed in the manuscript "Accurate genome-wide predictions of spatio-temporal gene expression during embryonic development" and used by the webserver https://find.princeton.edu.</p> <p>Abstract:</p> <p>Comprehensive information on the timing and location of gene expression is fundamental to our understanding of embryonic development and tissue formation. While high-throughput <em>in situ</em> hybridization projects provide invaluable information about developmental gene expression patterns for model organisms like <em>Drosophila</em>, the output of these experiments is primarily qualitative, and a high proportion of protein coding genes and most non-coding genes lack any annotation. Accurate data-centric predictions of spatio-temporal gene expression will therefore complement current <em>in situ</em> hybridization efforts. Here, we applied a machine learning approach by training models on all public gene expression and chromatin data, even from whole-organism experiments, to provide genome-wide, quantitative spatio-temporal predictions for all genes. We developed structured in silico nano-dissection, a computational approach that predicts gene expression in >200 tissue-developmental stages. The algorithm integrates expression signals from a compendium of 6,378 genome-wide expression and chromatin profiling experiments in a cell lineage-aware fashion. We systematically evaluated our performance via cross-validation and experimentally confirmed 22 new predictions for four different embryonic tissues. The model also predicts complex, multi-tissue expression and developmental regulation with high accuracy. We further show the potential of applying these genome-wide predictions to extract tissue specificity signals from non-tissue-dissected experiments, and to prioritize tissues and stages for disease modeling. This resource, together with the exploratory tools are freely available at our webserver <a href="http://find.princeton.edu/">http://find.princeton.edu</a>, which provides a valuable tool for a range of applications, from predicting spatio-temporal expression patterns to recognizing tissue signatures from differential gene expression profiles.</p>
Data from: Genomic regions underlying metabolic and neuronal signaling pathways are temporally consistent outliers in a moving avian hybrid zone
The study of hybrid zones can provide insight into the genetic basis of species differences that are relevant for the maintenance of reproductive isolation. Hybrid zones can also provide insight into climate change, species distributions, and evolution. The hybrid zone between black-capped chickadees (Poecile atricapillus) and Carolina chickadees (P. carolinensis) is shifting northward in response to increasing winter temperatures but is not increasing in width. This pattern indicates strong selection against chickadees with admixed genomes. Using high-resolution genomic data, we identified regions of the genomes that are outliers in both time points and do not introgress between the species; these regions may be involved in the maintenance of reproductive isolation. Genes involved in metabolic regulation processes were overrepresented in this dataset. Several gene ontology categories were also temporally consistent—including glutamate signaling, synaptic transmission, and catabolic processes—but the nucleotide variants leading to this pattern were not. Our results support recent findings that hybrids between black-capped and Carolina chickadees have higher basal metabolic rates than either parental species and suffer spatial memory and problem-solving deficits. Metabolic breakdown, as well as spatial memory and problem-solving, in hybrid chickadees may act as strong postzygotic isolation mechanisms in this moving hybrid zone.
Data from: Patterns of cyto-nuclear linkage disequilibrium in Silene latifolia: genomic heterogeneity and temporal stability
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Data from: Detecting selection on temporal and spatial scales: a genomic time-series assessment of selective responses to devil facial tumor disease
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The Pacific lamprey genomic divergence, association mapping, temporal Willamette Falls, spatial rangewide datasets
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.