Biology subjects

Albert, C.

Publications and source records attributed to Albert, C..

10 recordsLinked to original sources

bioRxiv2026

Big data analysis of animal movements in aquatic ecosystems with acoustic telemetry

Underwater receiver networks (passive acoustic telemetry systems) are deployed to track animals in aquatic habitats all over the world, but remarkably limited attention has been given over to how we can strengthen the value of these networks through statistical and computational advances. Here, we upscale state-of-the-art methods of Bayesian inference to big animal-tracking datasets from acoustic telemetry, with the largest geolocation analysis in a sparse passive acoustic telemetry system (with non-overlapping receivers) to date. Using four years of data from 93 lake trout (Salvelinus namaycush) in North Americas Lake Champlain (657,360 timesteps per individual), we formulate and fit state-space models to reconstruct animal movements through time. Uniquely, we directly embed biological expertise and detailed complementary datasets from fine-scale positioning systems, accelerometry, swim-tunnel experiments and field range tests in our analysis. Using simulated and real-world datasets, we map movement patterns and estimate residency in distinct management zones. We quantify array precision and deliver maps and residency estimates with a median error and precision (standard error) below 1 %. These results strengthen the evidence base for management. This work takes us a step towards robust inference of movement patterns at scale in acoustic telemetry systems across the world. We can, and should, build on prior scientific progress and extend the value of hard-earned data beyond individual studies to refine inferences for ecology and management. Significance statementAcoustic receivers are deployed across the globe to track aquatic animals, but reconstructing detailed movement patterns from detections at receivers remains a considerable challenge. Here, we upscale state-of-the-art methods of Bayesian inference by two orders of magnitude to analyse big, real-world datasets, using an extensive case study of lake trout (Salvelinus namaycush) in Lake Champlain. By directly integrating diverse complementary datasets from animal-borne tags, swim-tunnel experiments, field studies and close-kin mark-recapture in our analysis, we resolve detailed movement patterns over a four-year period, with broad implications for ecology and management. This work provides a powerful framework for acoustic telemetry studies that strives to meet the challenges of big, real-world datasets from telemetry networks across the world.

ecology↗

bioRxiv2025

Animal geolocation with convolution algorithms in Julia and R via Wahoo.jl

O_LIAnimal geolocation is the core of movement ecology. In aquatic ecosystems, electronic tagging and tracking technologies, such as passive acoustic telemetry systems and biologging sensors, are widely deployed. However, statistical estimation of individual locations from these datasets can be challenging and computationally expensive. C_LIO_LIHere, we introduce Wahoo.jl, a Julia package that fits state-space models to animal-tracking data via convolution algorithms. Wahoo.jl supports passive acoustic telemetry (detection/non-detection) and biologging (i.e., depth) datasets; implements grid-based filtering, smoothing and sampling of trajectories; and exploits GPU acceleration. C_LIO_LIUsing simulations, we illustrate how to use Wahoo.jl from Julia and R to reconstruct movements for an example individual tagged with an acoustic transmitter and an archival depth tag. We also provide validation and sensitivity analyses. C_LIO_LIWahoo.jl fills a key gap in the animal-tracking toolbox. The package provides an accessible, flexible and performant interface for an inference methodology that reliably handles multimodal inference problems that challenge other approaches. We discuss the approachs pros and cons and provide guidance to readers on when to reach for Wahoo.jl. C_LI

ecology↗

bioRxiv2025

Animal tracking with particle algorithms for conservation

The movements of aquatic animals affect their exposure to threats and the efficacy of conservation measures, such as Marine Protected Areas (MPAs). However, many species movements remain poorly understood and difficult to reconstruct from available datasets, hampering conservation efforts. This is especially the case for species that rarely surface, for which data are often limited to observations from acoustic telemetry (detections) and ancillary sensors, such as archival tags. Here, we pioneer the use of state-of-the-art particle algorithms to model animal movement, integrate datasets and assess MPA design, using a case study of the Critically Endangered flapper skate (Dipturus intermedius) in Scotland. Our algorithms led to 5-fold improvements in maps of space use and 30-fold improvements in residency estimates (lower mean error) compared to prevailing heuristic methods. By formally integrating tracking datasets, we were uniquely able to examine movements beyond receivers into fished zones, MPA-scale residency and specific habitats beyond protected areas that may warrant protection. This work showcases a probabilistically sound modelling framework that is sufficiently fast, flexible and accessible to meet the demands of modern animal-tracking datasets in acoustic telemetry systems. This represents a marked advance for analyses of animal movements and MPA efficacy worldwide.

ecology↗

bioRxiv2024

Particle algorithms for animal movement modelling in autonomous receiver networks

1. Particle filters and smoothers are powerful sequential Monte Carlo algorithms used to fit non-linear, non-Gaussian state-space models. These algorithms are well placed to fit process-orientated models to animal-tracking data, especially in autonomous receiver networks, but to date they have received limited attention in the ecological literature. 2. Here, we introduce a Bayesian filtering-smoothing algorithm that reconstructs individual movements and patterns of space use from animal-tracking data, with a focus on passive acoustic telemetry systems. Within a sound probabilistic framework, the methodology uniquely integrates the movement process and the observation processes of disparate datasets, while correctly representing uncertainty. In a comprehensive simulation-based analysis, we compare the performance of our algorithm to the prevailing, heuristic methods used in passive acoustic telemetry systems and analyse algorithm sensitivity. 3. We find the particle smoothing methodology outperforms heuristic methods across the board. Particle-based maps consistently represent simulated movements more accurately, even in dense receiver networks, and are better suited to analyses of home ranges, residency and habitat preferences. 4. This study sets a new state-of-the-art for movement modelling in autonomous receiver networks. Particle algorithms provide a flexible and intuitive modelling framework with potential applications in many ecological settings.

animal behavior and cognition↗

bioRxiv2024

patter: particle algorithms for animal tracking in R and Julia

O_LIIn the field of movement ecology, state-space models have emerged as a powerful modelling framework that represents individual movements and the processes that connect movements to observations. However, fitting state-space models to animal tracking data is often difficult and computationally expensive. C_LIO_LIHere, we introduce patter, a package that provides particle filtering and smoothing algorithms that fit Bayesian state-space models to tracking data, with a focus on data from aquatic animals in autonomous receiver arrays. patter is written in R, with a high-performance Julia backend. Package functionality supports data simulation, preparation, filtering, smoothing and mapping. C_LIO_LIIn two worked examples, we demonstrate how to implement patter to reconstruct the movements of a tagged animal in an acoustic telemetry system from acoustic detections and ancillary observations. With perfect information, the particle filter reconstructs the true (unobserved) movement path (Example One). More generally, particle-based methods represent an individuals possible location probabilistically as a weighted series of samples ( particles). In our illustration, we resolve an individuals (unobserved) location every two minutes during one month in minutes and use particles to visualise movements, map space use and quantify residency (Example Two). C_LIO_LIpatter facilitates robust, flexible and efficient analyses of animal tracking data. The methods are widely applicable and enable refined analyses of home ranges, residency and habitat preferences. C_LI

ecology↗

bioRxiv2023

Validation of human telomere length trans-ancestry meta-analysis association signals identifies POP5 and KBTBD6 as novel human telomere length regulation genes

Telomere length genome-wide association studies (GWAS) have become well-powered to detect novel genes in telomere length regulation. However, no prior work has validated these putative novel genes to confirm the contribution of GWAS loci to telomere length regulation. We conducted a trans-ancestry meta-analysis of 211,369 individuals. Through enrichment analyses of chromatin state and cell-type heritability we identified blood and immune cells as the most relevant cell type to examine telomere length association signals. We validated specific GWAS associations by overexpressing KBTBD6, a component of an E3 ubiquitin ligase complex, and POP5, a component of the Ribonuclease P/MRP complex, and demonstrating that both lengthened telomeres as predicted by our statistical analyses. CRISPR/Cas9 deletion of the predicted causal regions of these association peaks in K562 immortalized blood cells reduced expression of these genes, demonstrating that these loci are related to transcriptional regulation of KBTBD6 and POP5, respectively. Together our results demonstrate the utility of telomere length GWAS in the identification of novel telomere length regulation mechanisms and highlight the importance of the proteasome-ubiquitin pathway in telomere length regulation.

genetics↗

bioRxiv2019

Towards standardization of immune functional assays

Recent advances in the immunotherapy field require evaluation of the immune function to adapt therapeutic decisions. Immune functional assays (IFA) are able to reveal the immune status and would be useful to further adapt/improve patients care. However, standardized methods are needed to implement IFA in clinical settings. We carried out an independent validation of a published method used to characterize the underlying host response to infectious conditions using an IFA. We evaluate the reproducibility and robustness of this IFA and associated readout using an independent healthy volunteers (HV) cohort. Expression of a 44 genes-signatures and IFN{gamma} protein secretion and gene-expression was assessed after stimulation. We observed a strong host-response correlation between the two cohorts. We also highlight that standardized methods for immune function evaluation exist and could be implemented in larger-scale studies. This IFA could be a relevant tool to reveal innate/adaptive immune dysfunction in immune-related disorders patients.

immunology↗

bioRxiv2019

Transcription factor NF-κB in a basal metazoan, the sponge, has conserved and unique sequences, activities, and regulation

Biological and biochemical functions of immunity transcription factor NF-{kappa}B in basal metazoans are largely unknown. Herein, we characterize transcription factor NF-{kappa}B from the demosponge Amphimedon queenslandica (Aq), in the phylum Porifera. Structurally and phylogenetically, the Aq-NF-{kappa}B protein is most similar to NF-{kappa}B p100 and p105 among vertebrate proteins, with an N-terminal DNA-binding/dimerization domain, a C-terminal Ankyrin (ANK) repeat domain, and a DNA binding-site profile more similar to human NF-{kappa}B proteins than Rel proteins. Aq-NF-{kappa}B also resembles the mammalian NF-{kappa}B protein p100 in that C-terminal truncation results in translocation of Aq-NF-{kappa}B to the nucleus and increases its transcriptional activation activity. Overexpression of a human or sea anemone I{kappa}B kinase (IKK) can induce C-terminal processing of Aq-NF-{kappa}B in vivo, and this processing requires C-terminal serine residues in Aq-NF-{kappa}B. Unlike human NF-{kappa}B p100, however, the C-terminal sequences of Aq-NF-{kappa}B do not effectively inhibit its DNA-binding activity when expressed in human cells. Tissue of another demosponge, a black encrusting sponge, contains NF-{kappa}B site DNA-binding activity and an NF-{kappa}B protein that appears mostly processed and in the nucleus of cells. NF-{kappa}B DNA-binding activity and processing is increased by treatment of sponge tissue with LPS. By transcriptomic analysis of A. queenslandica we identified likely homologs to many upstream NF-{kappa}B pathway components. These results present a functional characterization of the most ancient metazoan NF-{kappa}B protein to date, and show that many characteristics of mammalian NF-{kappa}B are conserved in sponge NF-{kappa}B, but the mechanism by which NF-{kappa}B functions and is regulated in the sponge may be somewhat different.

cell biology↗

bioRxiv2019

A Universal Phase Transition in Plankton Trait Dynamics

Key ecological traits, like cell size, often follow scale-free or self-similar distributions. This indicates that these systems might operate near a critical (i.e. second-order) phase transition where macroscopic system behaviour is largely decoupled from microscopic system details, allowing an extremely simple, yet accurate and robust mathematical system characterisation. However, how trait-distribution scaling results from a critical transition has not yet been explicitly demonstrated. Here, we demonstrate that a generic class of cell growth and division models exhibits a critical transition from a growth-dominated to a division-dominated phase. We find experimental evidence for this transition, both in the population dynamics and in the moment scaling of chlorophyll distributions, for prokaryotic and eukaryotic phytoplankton growth under different light intensities. Our approach offers testable predictions of the response of unicellular trait-distributions to perturbations.

ecology↗

bioRxiv2019

Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program

Summary paragraphThe Trans-Omics for Precision Medicine (TOPMed) program seeks to elucidate the genetic architecture and disease biology of heart, lung, blood, and sleep disorders, with the ultimate goal of improving diagnosis, treatment, and prevention. The initial phases of the program focus on whole genome sequencing of individuals with rich phenotypic data and diverse backgrounds. Here, we describe TOPMed goals and design as well as resources and early insights from the sequence data. The resources include a variant browser, a genotype imputation panel, and sharing of genomic and phenotypic data via dbGaP. In 53,581 TOPMed samples, >400 million single-nucleotide and insertion/deletion variants were detected by alignment with the reference genome. Additional novel variants are detectable through assembly of unmapped reads and customized analysis in highly variable loci. Among the >400 million variants detected, 97% have frequency <1% and 46% are singletons. These rare variants provide insights into mutational processes and recent human evolutionary history. The nearly complete catalog of genetic variation in TOPMed studies provides unique opportunities for exploring the contributions of rare and non-coding sequence variants to phenotypic variation. Furthermore, combining TOPMed haplotypes with modern imputation methods improves the power and extends the reach of nearly all genome-wide association studies to include variants down to ~0.01% in frequency.

genomics↗