Variant pathogenicity classifiers such as SIFT, PolyPhen-2, CADD, and MetaLR assist in interpretation of the hundreds of rare, missense variants in the typical patient genome by deprioritizing some ...variants as likely benign. These widely used methods misclassify 26 to 38% of known pathogenic mutations, which could lead to missed diagnoses if the classifiers are trusted as definitive in a clinical setting. We developed M-CAP, a clinical pathogenicity classifier that outperforms existing methods at all thresholds and correctly dismisses 60% of rare, missense variants of uncertain significance in a typical genome at 95% sensitivity.
Single-cell RNA sequencing (scRNA-seq) is a powerful approach for reconstructing cellular differentiation trajectories. However, inferring both the state and direction of differentiation is ...challenging. Here, we demonstrate a simple, yet robust, determinant of developmental potential-the number of expressed genes per cell-and leverage this measure of transcriptional diversity to develop a computational framework (CytoTRACE) for predicting differentiation states from scRNA-seq data. When applied to diverse tissue types and organisms, CytoTRACE outperformed previous methods and nearly 19,000 annotated gene sets for resolving 52 experimentally determined developmental trajectories. Additionally, it facilitated the identification of quiescent stem cells and revealed genes that contribute to breast tumorigenesis. This study thus establishes a key RNA-based feature of developmental potential and a platform for delineation of cellular hierarchies.
•Generally small differences (less than 10%) between static B0 and dynamic B0 for 18 examined groundfish species (though up to 72%).•Directional productivity shifts imposed greater differences ...between stock status approaches than cyclic or white noise scenarios.•Trends in productivity paired with large contrasts in fishing mortality resulted in the largest differences between stock status approaches.•Uncertainty from incorrectly identifying changes in stock productivity generally outweighed that from initial equilibrium conditions.•Understanding ecosystem productivity is crucial for management based on current stock reproductive potential and related sustainable harvest.
Reference points identify benchmarks, thresholds, or decision points for fisheries management, and are commonly defined by stock status indicators that presume equilibrium population conditions in the absence of fishing (e.g., equilibrium biomass, B0). However, equilibrium population biomass may be an inappropriate reference level when stock productivity is influenced by environmental change, predator-prey dynamics, ecosystem thresholds, and myriad other factors. Simulations were conducted to compare equilibrium-based (static B0) and non-equilibrium based (dynamic B0) indicators of stock status under alternative states of nature driven by time-varying recruitment dynamics (productivity regime), fishing dynamics (mortality regime), and species life history. Using dynamic B0 often implied a different state of the stock under directional productivity regime shifts, but was more similar to static B0 reference points under cyclic or white noise productivity scenarios. Uncertainty in stock status arising from incorrectly identifying changes in system productivity generally outweighed the uncertainty associated with initial equilibrium conditions. Empirical results across 18 U.S. West Coast groundfish stock assessments indicated predominantly small differences (<10%) between static B0 and dynamic B0 indicators of stock status, although in some cases differences were large (up to 72%) or spanned reference points that trigger management action. Although caution is warranted when considering dynamic reference points, this paper shows these approaches are likely to be most useful when stock productivity shifts directionally, if that productivity signal can be correctly ascertained.
Misidentifying spatial population structure may result in harvest levels that are unable to achieve management goals. We developed a spatially explicit simulation model to determine how biological ...reference points differ among common population structures and to investigate the performance of management quantities that were calculated assuming incorrect spatial population dynamics. Simulated reference points were compared across a range of population structures and connectivity scenarios demonstrating the influence of spatial assumptions on management benchmarks. Simulations also illustrated that applying a harvest level based on misdiagnosed spatial structure leads to biased stock status indicators, overharvesting, or foregone yield. Across the scenarios examined, incorrectly specifying the connectivity dynamics (particularly misdiagnosing source-sink dynamics) was often more detrimental than ignoring spatial structure altogether. However, when the true dynamics exhibited spatial structure, incorrectly assuming panmictic structure resulted in severe depletion if harvesting concentrated on more productive population units (instead of being homogeneously distributed). Incorporating spatially generalized operating models, such as the one developed here, into management strategy evaluations will help develop management procedures that are more robust to spatial complexities.
Space oddity: The mission for spatial integration Berger, Aaron M; Goethel, Daniel R; Lynch, Patrick D ...
Canadian journal of fisheries and aquatic sciences,
11/2017, Letnik:
74, Številka:
11
Journal Article
Recenzirano
Odprti dostop
Fishery management decisions are commonly guided by stock assessment models that aggregate outputs across the spatial domain of the species. With refined understanding of spatial population ...structures, scientists have begun to address how spatiotemporal mismatches among the scale of ecological processes, data collection programs, and stock assessment methods (or assumptions) influence the reliability and, ultimately, appropriateness of regional fishery management (e.g., assigning regional quotas). Development and evaluation of spatial modeling techniques to improve fisheries assessment and management have increased rapidly in recent years. We overview the historical context of spatial models in fisheries science, highlight recent advances in spatial modeling, and discuss how spatial models have been incorporated into the management process. Despite limited examples where spatial assessment models are used as the basis for management advice, continued investment in fine-scale data collection and associated spatial analyses will improve integration of spatial dynamics and ecosystem-level interactions in stock assessment. In the near future, spatiotemporal fisheries management advice will increasingly rely on fine-scale outputs from spatial analyses.
The field of fisheries science and, in particular, fish population dynamics and stock assessment modeling has rapidly progressed over the last decade, largely due to advances in computing power, ...statistical theory, and data collection technology (Maunder and Punt 2013). Higher resolution data (e.g., catch locations or animal tracks collected via global positioning systems) along with continually improving computational ability have enabled new explorations into how best to model the complex biological and anthropological processes driving fish populations. The result has been a reemergence of modeling tools previously deemed too complex or data intensive, as well as the development of new methods to handle multidimensional, spatiotemporal parameter estimation in statistically rigorous ways.
Transcription factors (TFs) interact with specific DNA regulatory sequences to control gene expression throughout myriad cellular processes. However, the DNA binding specificities of only a small ...fraction of TFs are sufficiently characterized to predict the sequences that they can and cannot bind. We present a maximally compact, synthetic DNA sequence design for protein binding microarray (PBM) experiments that represents all possible DNA sequence variants of a given length k (that is, all 'k-mers') on a single, universal microarray. We constructed such all k-mer microarrays covering all 10-base pair (bp) binding sites by converting high-density single-stranded oligonucleotide arrays to double-stranded (ds) DNA arrays. Using these microarrays we comprehensively determined the binding specificities over a full range of affinities for five TFs of different structural classes from yeast, worm, mouse and human. The unbiased coverage of all k-mers permits high-throughput interrogation of binding site preferences, including nucleotide interdependencies, at unprecedented resolution.
Abstract
Genetic variation in cis-regulatory elements is thought to be a major driving force in morphological and physiological changes. However, identifying transcription factor binding events that ...code for complex traits remains a challenge, motivating novel means of detecting putatively important binding events. Using a curated set of 1154 high-quality transcription factor motifs, we demonstrate that independently eroded binding sites are enriched for independently lost traits in three distinct pairs of placental mammals. We show that these independently eroded events pinpoint the loss of hindlimbs in dolphin and manatee, degradation of vision in naked mole-rat and star-nosed mole, and the loss of external testes in white rhinoceros and Weddell seal. We additionally show that our method may also be utilized with more than two species. Our study exhibits a novel methodology to detect cis-regulatory mutations which help explain a portion of the molecular mechanism underlying complex trait formation and loss.
Environmental conditions can have spatially complex effects on the dynamics of marine fish stocks that change across life-history stages. Yet the potential for non-stationary environmental effects ...across multiple dimensions, e.g. space and ontogeny, are rarely considered. In this study, we examined the evidence for spatial and ontogenetic non-stationary temperature effects on Pacific hake Merluccius productus biomass along the west coast of North America. Specifically, we used Bayesian additive models to estimate the effects of temperature on Pacific hake biomass distribution and whether the effects change across space or life-history stage. We found latitudinal differences in the effects of temperature on mature Pacific hake distribution (i.e. age 3 and older); warmer than average subsurface temperatures were associated with higher biomass north of Vancouver Island, but lower biomass offshore of Washington and southern Vancouver Island. In contrast, immature Pacific hake distribution (i.e. age 2) was better explained by a nonlinear temperature effect; cooler than average temperatures were associated with higher biomass coastwide. Together, our results suggest that Pacific hake distribution is driven by interactions between age composition and environmental conditions and highlight the importance of accounting for varying environmental effects across multiple dimensions.
Abstract
The environmental conditions that marine populations experience are being altered because of climate change. In particular, changes in temperature and increased variability can cause shifts ...in spatial distribution, leading to changes in local physiological rates and recruitment success. Yet, management of fish stocks rarely accounts for variable spatial dynamics or changes in movement rates when estimating management quantities such as stock abundance or maximum sustainable yield. To address this concern, a management strategy evaluation (MSE) was developed to evaluate the robustness of the international management system for Pacific hake, an economically important migratory stock, by incorporating spatio-temporal population dynamics. Alternative hypotheses about climate-induced changes in age-specific movement rates, in combination with three different harvest control rules (HCR), were evaluated using a set of simulations that coupled single-area estimation models with alternative operating models representing spatial stock complexity. Movement rates intensified by climate change caused a median decline in catches, increased annual catch variability, and lower average spawning biomass. Impacts varied by area and HCR, underscoring the importance of spatial management. Incorporating spatial dynamics and climate change effects into management procedures for fish stocks with spatial complexity is warranted to mitigate risk and uncertainty for exploited marine populations.