Landscape genomics can harness environmental and genetic data to inform conservation decisions by providing essential insights into how landscapes shape biodiversity. The massive increase in genetic data afforded by the genomic era provides exceptional resolution for answering critical conservation genetics questions. The accessibility of genomic data for non-model systems has also enabled a shift away from population-based sampling to individual-based sampling, which now provides accurate and robust estimates of genetic variation that can be used to examine the spatial structure of genomic diversity, population connectivity and the nature of environmental adaptation. Nevertheless, the adoption of individual-based sampling in conservation genetics has been slowed due, in large part, to concerns over how to apply methods developed for population-based sampling to individual-based sampling schemes. Here, we discuss the benefits of individual-based sampling for conservation and describe how landscape genomic methods, paired with individual-based sampling, can answer fundamental conservation questions. We have curated key landscape genomic methods into a user-friendly, open-source workflow, which we provide as a new R package, A Landscape Genomics Analysis Toolkit in R (algatr). The algatr package includes novel added functionality for all of the included methods and extensive vignettes designed with the primary goal of making landscape genomic approaches more accessible and explicitly applicable to conservation biology.
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http://dx.doi.org/10.1111/1755-0998.13884 | DOI Listing |
Partial migration is a phenomenon where migratory and resident individuals of the same species co-exist within a population, and has been linked to both intrinsic (e.g., genetic) as well as environmental factors.
View Article and Find Full Text PDFInbreeding depression poses a severe threat to small populations, leading to the fixation of deleterious mutations and decreased survival probability. While the establishment of natural gene flow between populations is an ideal long-term solution, its practical implementation is often challenging. Reinforcement of populations by translocating individuals from larger populations is a viable strategy for reducing inbreeding, increasing genetic diversity and potentially saving populations from extinction.
View Article and Find Full Text PDFCureus
November 2024
Department of Internal Medicine, M. S. Ramaiah Medical College, Bengaluru, IND.
Introduction: Metabolic syndrome (MS), identified by abdominal obesity, insulin resistance, hypertension, and/or dyslipidemia, occurs across all BMI (body mass index) ranges and increases the risk of atherosclerotic cardiovascular (CV) diseases and type II diabetes. The Atherogenic Index of Plasma (AIP) and Castelli Risk Index (CRI) I & II are ratios that can be calculated from a simple lipid profile test. These ratios are independent risk factors for CV diseases and have been shown to be increased in angiographically confirmed coronary artery disease (CAD) patients.
View Article and Find Full Text PDFDiscov Oncol
December 2024
Department of Electrical Engineering, Assam Engineering College, Assam, India.
Radiomics is a method that extracts many features from medical images using various algorithms. Medical nomograms are graphical representations of statistical predictive models that produce a likelihood of a clinical event for a specific individual based on biological and clinical data. The radiomic nomogram was first introduced in 2016 to study the integration of specific radiomic characteristics with clinically significant risk factors for patients with colorectal cancer lymph node metastases.
View Article and Find Full Text PDFBMC Med Res Methodol
December 2024
School of Allied Health, Ageing Research Centre, Health Research Institute, University of Limerick, Limerick, Ireland.
Background: Physical activity (PA) is often the cornerstone in risk-reduction interventions for the prevention and treatment of many chronic health conditions. PA interventions are inherently multi-dimensional and complex in nature. Thus, study designs used in the evaluation of PA interventions must be adaptive to intervention components and individual capacities.
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