Habitat transformation is one of the leading drivers of biodiversity loss. The ecological effects of this transformation have mainly been addressed at the demographic level, for example, finding extinction thresholds. However, interpopulation genetic variability and the subsequent potential for adaptation can be eroded before effects are noticed on species abundances. To what degree this is the case has been difficult to evaluate, partly because of the lack of both spatially extended genetic data and an appropriate framework to map and analyse such data. Here, we extend recent work on the analysis of networks of spatial genetic variation to address the robustness of these networks in the face of perturbations. We illustrate the potential of this framework using the case study of an amphibian metapopulation. Our results show that while the disappearance of some spatial sites barely changes the modular structure of the genetic network, other sites have a much stronger effect. Interestingly, these consequences can not be anticipated using topological, static measures. Mapping these networks of spatial genetic variation will allow identifying significant evolutionary units and how they vanish, merge and reorganise following perturbations.
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http://dx.doi.org/10.1111/ele.12061 | DOI Listing |
Environ Monit Assess
December 2024
Chongqing Key Laboratory of Non-Linear Circuit and Intelligent Information Processing, College of Electronic and Information Engineering, Southwest University, Chongqing, 400715, China.
Waste sorting is a key part of sustainable development. To maximize the recovery of resources and reduce labor costs, a waste management and classification system is established. In the system, we use Internet of Things (IoT) and edge computing to implement waste sorting and the systematic long-distance information transmission and monitoring.
View Article and Find Full Text PDFGenomics Proteomics Bioinformatics
December 2024
Monash Biomedicine Discovery Institute and Department of Biochemistry and Molecular Biology, Monash University, Clayton, VIC 3800, Australia.
Unlabelled: The accurate identification of catalytic residues contributes to our understanding of enzyme functions in biological processes and pathways. The increasing number of protein sequences necessitates computational tools for the automated prediction of catalytic residues in enzymes. Here, we introduce SCREEN, a graph neural network for the high-throughput prediction of catalytic residues via the integration of enzyme functional and structural information.
View Article and Find Full Text PDFBiol Psychol
December 2024
Big Data Analytics and Web Intelligence Laboratory, Department of Computer Science & Engineering, Delhi Technological University, New Delhi, India. Electronic address:
Within the domain of neurodevelopmental disorders, autism spectrum disorder (ASD) emerges as a distinctive neurological condition characterized by multifaceted challenges. The delayed identification of ASD poses a considerable hurdle in effectively managing its impact and mitigating its severity. Addressing these complexities requires a nuanced understanding of data modalities and the underlying patterns.
View Article and Find Full Text PDFNew Phytol
December 2024
IPSiM, Univ Montpellier, CNRS, INRAE, Institut Agro, Montpellier, 34000, France.
Plasma membrane (PM) nanodomains have emerged as pivotal elements in the regulation of plant cellular functions and signal transduction. These nanoscale membrane regions, enriched in specific lipids and proteins, behave as regulatory/signaling hubs spatially and temporally coordinating critical cellular functions. In this review, we first examine the mechanisms underlying the formation and maintenance of PM nanodomains in plant cells, highlighting the roles of PM lipid composition, protein oligomerization and interactions with cytoskeletal and cell wall components.
View Article and Find Full Text PDFInfect Dis Poverty
December 2024
Ecosystem Change and Population Health Research Group, Centre for Immunology and Infection Control, School of Public Health and Social Work, Queensland University of Technology, Kelvin Grove, Brisbane, QLD, 4059, Australia.
Background: Rapid human movement plays a crucial role in the spatial dissemination of the dengue virus. Nevertheless, robust quantification of this relationship using both spatial and temporal models remains necessary. This study aims to explore the spatial and temporal patterns of dengue transmission under various human movement contexts.
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