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197 results for “time estimation”

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dryad36/100

Influence of RNA-Seq library construction, sampling methods, and tissue harvesting time on gene expression estimation

RNA sequencing (RNA-Seq) is popular for measuring gene expression in non-model organisms, including wild populations. While RNA-Seq can detect gene expression variation among wild-caught individuals and yield important insights into biological function, sampling methods may influence gene expression estimates. We examined the influence of multiple technical variables on estimated gene expression in a non-model fish, the westslope cutthroat trout (Oncorhynchus clarkii lewisi), using two RNA-Seq library types: 3' RNA-Seq (QuantSeq) and whole mRNA-Seq (NEB). We evaluated effects of dip netting versus electrofishing, and of harvesting tissue immediately versus 5 minutes after euthanasia on estimated gene expression in blood, gill, and muscle. We found no significant differences in gene expression between sampling methods or tissue collection times with either library type. When library types were compared using the same blood samples, 58% of genes detected by both NEB and QuantSeq showed significantly different expression between library types, and NEB detected 31% more genes than QuantSeq. Although QuantSeq and NEB recovered different numbers of genes and expression levels, there were no differences in gene expression between sampling methods and tissue harvesting time for either library type. Our study suggests that researchers can safely rely on different fish sampling strategies in the field. In addition, while QuantSeq is more cost-effective, NEB detects more expressed genes. Therefore, when it is crucial to detect as many genes as possible (especially low expressed genes), when alternative splicing is of interest, or when working with an organism lacking good genomic resources, whole mRNA-Seq is more powerful.

opencc-zeroJan 2023View details →

zenodo36/100

Real-time frequency estimation of a qubit without single-shot-readout

Dataset for figures 3a, 3b and 4b in our manuscript.

opencc-by-4.0Mar 2023View details →

dryad36/100

Estimation of species divergence times in presence of cross-species gene flow

Cross-species introgression can have significant impacts on phylogenomic reconstruction of species divergence events. Here, we used simulations to show how the presence of even a small amount of introgression can bias divergence time estimates when gene flow is ignored in the analysis. Using advances in analytical methods under the multispecies coalescent (MSC) model, we demonstrate that by accounting for incomplete lineage sorting and introgression using large phylogenomic data sets this problem can be avoided. The multispecies-coalescent with-introgression (MSci) model is capable of accurately estimating both divergence times and ancestral effective population sizes, even when only a single diploid individual per species is sampled. We characterize some general expectations for biases in divergence time estimation under three different scenarios: 1) introgression between sister species, 2) introgression between non-sister species, and 3) introgression from an unsampled (i.e., ghost) outgroup lineage. We also conducted simulations under the isolation-with-migration (IM) model, and found that the MSci model assuming episodic gene flow was able to accurately estimate species divergence times despite high levels of continuous gene flow. We estimated divergence times under the MSC and MSci models from two published empirical datasets with previous evidence of introgression, one of 372 target enrichment loci from baobabs (Adansonia), and another of 1,000 transcriptome loci from fourteen species of the tomato relative, Jaltomata. The empirical analyses not only confirm our findings from simulations, demonstrating that the MSci model can reliably estimate divergence times, but also show that divergence time estimation under the MSC can be robust to the presence of small amounts of introgression in empirical datasets with extensive taxon sampling.

opencc-zeroMar 2023View details →

dryad36/100

Scalable Bayesian divergence time estimation with ratio transformations

<div class="page"> <div class="layoutArea"> <div class="column"> Divergence time estimation is crucial to provide temporal signals for dating biologically important events, from species divergence to viral transmissions in space and time. With the advent of high-throughput sequencing, recent Bayesian phylogenetic studies have analyzed hundreds to thousands of sequences. Such large-scale analyses challenge divergence time reconstruction by requiring inference on highly-correlated internal node heights that often become computationally infeasible. To overcome this limitation, we explore a ratio transformation that maps the original N - 1 internal node heights into a space of one height parameter and N - 2 ratio parameters. To make the analyses scalable, we develop a collection of linear-time algorithms to compute the gradient and Jacobian-associated terms of the log-likelihood with respect to these ratios. We then apply Hamiltonian Monte Carlo sampling with the ratio transform in a Bayesian framework to learn the divergence times in four pathogenic viruses (West Nile virus, rabies virus, Lassa virus and Ebola virus) and the coralline red algae. Our method both resolves a mixing issue in the West Nile virus example and improves inference efficiency by at least 5-fold for the Lassa and rabies virus examples as well as for the algae example. Our method now also makes it computationally feasible to incorporate mixed-effects molecular clock models for the Ebola virus example, confirms the findings from the original study and reveals clearer multimodal distributions of the divergence times of some clades of interest. </div> </div> </div>

opencc-zeroJun 2023View details →

zenodo36/100

Apulian Aqueduct demo site: daily time series of estimated inflows (natural springs and reservoirs) for climate projections

This dataset contains the daily time series of net estimated inflows (natural springs and main reservoirs of Apulian aqueduct - demo site 1) computed with a lumped rainfall-runoff model starting from climate projections of precipitation and temperature. This dataset considers two representative concentration pathways (RCP 4.5 and 8.5) and two decades, in the medium (2050-2059) and long-term future (2090-2099). <ul> <li>Temporal coverage: 2050-2059; 2090-2099</li> <li>Spatial coverage: Springs: Sele, Calore; Reservoirs: Conza, Locone, Monte Cotugno, Occhito, Pertusillo</li> <li>Unit of measure: m3/s</li> </ul> More information and details on the content of this dataset can be found in Project Ô <a href="https://zenodo.org/record/7576611">Deliverable D4.4</a>.

opencc-by-4.0Nov 2022View details →

dryad36/100

Genetic monitoring of steelhead in the Klickitat River to estimate productivity, straying, and migration timing

<div> Salmonids with complex life history variation present challenges for conservation management, but genetic approaches alongside fisheries monitoring can address questions regarding viability of natural populations. We genotyped adult (n=3,108) and juvenile (n=2,624) samples of anadromous Oncorhynchus mykiss that were collected in the Klickitat River, WA, USA at traps in the lower drainage to examine tributary level productivity, straying from outside sources and variation in adult migration timing. Genetic assignment of steelhead from this system indicated that the majority were produced within or near tributaries of the middle Klickitat River (juvenile mean = 72.8%; adult mean = 87.3%). Analyses with parentage-based tagging identified that most hatchery-origin adults were assigned to the Skamania Hatchery (80.8%) as expected since this has been the release stock for decades within the Klickitat River drainage. Hatchery-origin adults were also identified from programs operating outside the Klickitat River, which were primarily strays from Snake River hatcheries. Most natural-origin steelhead were assigned to the Klickitat River, but there were also natural-origin fish identified as strays from other regions of the Columbia River (22.3% of natural returns). We also examined genes known to be associated with migration timing in adult steelhead observed at the trap and observed a strong relationship between migration date and alleles for early and late migration, but individual outliers were detected across seasons. Our results indicate that genetic variation of steelhead in the Klickitat River has been influenced by hatchery programs as well as natural-origin straying from other sub-basins, but genetic diversity remains high throughout the sub-basin, and both early and late migration alleles are maintained. The genetic diversity present in Klickitat River steelhead may enable this Endangered Species Act listed (threatened) species to better adapt to stochastic environmental conditions compared to less diverse populations. </div>

opencc-zeroAug 2023View details →

dryad36/100