Genetic analyses can identify the scale at which wildlife species are impacted by human activities, and provide demographic information useful for management. Here, we use thousands of nuclear DNA genetic loci to assess whether genetic structure occurs within Lasiurus cinereus (Hoary Bat), L. borealis (Red Bat), and Lasionycteris noctivagans (Silver-Haired Bat) bats found at a wind turbine site in Ohio, and to also estimate demographic parameters in each of these three groups. Our specific goals are to: 1) demonstrate the feasibility of isolating RADseq loci from these tree bat species, 2) test for genetic structure within each species, including any structure that may be associated with time (migration period), and 3) use coalescent-based modeling approaches to estimate genetically-effective population sizes and patterns of population size changes over evolutionary timescales. Thousands of loci were successfully genotyped for each species, demonstrating the value of RADseq for generating polymorphic loci for population genetic analyses in these bats. There was no evidence for genetic differentiation between groups of samples collected at different times throughout spring and fall migration, suggesting that individuals from each species found at the wind facility are from single panmictic populations. Estimates of present-day effective population sizes varied across species, but were consistently large, on the order of 10(5)-10(6). All populations show evidence of expansions that date to the Pleistocene. These results, along with recent work also suggesting limited genetic structure in bats across North America, argue that additional biomarker systems such as stable-isotopes or trace elements should be investigated as alternative and/or complementary approaches to genetics for sourcing individuals collected at single wind farm sites.
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http://dx.doi.org/10.7717/peerj.1647 | DOI Listing |
Invest Ophthalmol Vis Sci
January 2025
Southwest Hospital/Southwest Eye Hospital, Third Military Medical University (Army Medical University), Chongqing, China.
Purpose: Previous studies have reported divergent sexual responses to aging; however, specific variations in gene expression between aging males and females and their potential association with age-related retinal diseases remain unclear. This study collected data from public databases and developed a comprehensive comparison of retina between aging females and males.
Methods: Single-cell RNA (scRNA) and bulk RNA sequencing data of the aging retina from females and males in public databases were utilized for integrated analysis to investigate sex-biased expression in retina.
Mikrochim Acta
January 2025
Department of Chemistry and Biochemistry, National Chung Cheng University, 621301, Chia-Yi, Taiwan.
A fluorescent aptasensor was developed based on target-induced hairpin conformation switch coupled with nicking enzyme-assisted signal amplification (NESA) to detect the oligomeric form of ß-amyolid peptide (AβO) in cerebrospinal fluid. The hairpin DNA probe (HP) was specifically designed to recognize AβO. When AβO is present in the sensing system, it induces an HP conformational switch and triggers the NESA reaction.
View Article and Find Full Text PDFNeurogenetics
January 2025
Department of Biomedical Science, Faculty of Medicine, University of Malaya, Kuala Lumpur, 50603, Malaysia.
Intermediate CAG repeats from 29 to 33 in the ATXN2 gene contributes to the risk of amyotrophic lateral sclerosis (ALS) in European and Asian populations. In this study, 148 ALS patients of multiethnic descent: Chinese (56.1%), Malay (24.
View Article and Find Full Text PDFJ Gen Virol
January 2025
Laboratory of Virology, Wageningen University and Research, 6708 PB Wageningen, Netherlands.
Nudiviruses (family ) are double-stranded DNA viruses that infect various insects and crustaceans. Among them, Heliothis zea nudivirus 1 (HzNV-1) represents the rare case of a lepidopteran nudivirus inducing a sexual pathology. Studies about molecular pathological dynamics of HzNV-1 or other nudiviruses are scarce.
View Article and Find Full Text PDFJ Gen Virol
January 2025
Department of Infection Biology, Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, UK.
The complexity and speed of evolution in viruses with RNA genomes makes predictive identification of variants with epidemic or pandemic potential challenging. In recent years, machine learning has become an increasingly capable technology for addressing this challenge, as advances in methods and computational power have dramatically improved the performance of models and led to their widespread adoption across industries and disciplines. Nascent applications of machine learning technology to virus research have now expanded, providing new tools for handling large-scale datasets and leading to a reshaping of existing workflows for phenotype prediction, phylogenetic analysis, drug discovery and more.
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