We studied the species diversity and population genetic structure of isolates of fungi from the entomopathogenic genus Metarhizium that had been isolated from sugarcane crops and surrounding grass. Soil and leaf samples were taken on four sampling occasions over 13 months (October 2014-October 2015). Isolations were made using the Galleria mellonella baiting method and selective media. Phylogenetic placement of isolates was done by sequencing a fragment of the 5' of the elongation factor 1-α gene (EF1-α). Population genetic structure was determined by analysing this sequence information using AMOVA and Haplotype network analyses. Genotypic diversity was studied using microsatellite genotyping. The most abundant species was M. anisopliae s.s. (80 isolates), then M. pingshaense (three isolates), and M. guizhouense (one isolate). More than 50% of the genetic variation was explained by the time the samples were collected regardless of plant host association. Some haplotypes were found on the first sampling date and then not found on subsequent sampling dates, while other haplotypes were found initially, disappeared, but then found again on the last sampling date. To the best of our knowledge, this is the first report of the population genetic structure of M. anisopliae species in time and space. The effect of abiotic factors is discussed.
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http://dx.doi.org/10.1007/s00248-017-0942-x | DOI Listing |
BMC Public Health
December 2024
Upstream Lab, MAP Centre for Urban Health Solutions, Li Ka Shing Knowledge Institute, Unity Health Toronto, 30 Bond Street, Toronto, ON, M5B 1W8, Canada.
Background: Machine learning (ML) is increasingly used in population and public health to support epidemiological studies, surveillance, and evaluation. Our objective was to conduct a scoping review to identify studies that use ML in population health, with a focus on its use in non-communicable diseases (NCDs). We also examine potential algorithmic biases in model design, training, and implementation, as well as efforts to mitigate these biases.
View Article and Find Full Text PDFDiagn Microbiol Infect Dis
December 2024
Department of Molecular Epidemiology, National Institute of Malaria Research, Sector-8, Dwarka, Delhi 110077, India. Electronic address:
Microsatellites, or simple sequence repeats (SSRs), are short tandemly repeated DNA sequences widely dispersed throughout the genome. Their high variability, co-dominant inheritance, and ease of detection make them valuable genetic markers, frequently used to study genetic diversity, population structure, and evolutionary processes. In the context of malaria research, particularly with Plasmodium falciparum (P.
View Article and Find Full Text PDFTrends Endocrinol Metab
December 2024
Department of Physiology and Pharmacology, Karolinska Institutet, 171 77 Stockholm, Sweden. Electronic address:
Polycystic ovary syndrome (PCOS) is a prevalent endocrine and metabolic disorder, affecting approximately 11-13% of women of reproductive age. Women with PCOS experience a higher prevalence of infertility, pregnancy complications, and cardiometabolic disorders such as obesity, insulin resistance, and type 2 diabetes mellitus. Furthermore, psychiatric comorbidities, including depression and anxiety, significantly impact the quality of life in this population.
View Article and Find Full Text PDFJ Intern Med
December 2024
Fresenius Medical Care, Global Medical Office, Bad Homburg, Germany.
Background: Fluid overload remains critical in managing patients with end-stage kidney disease. However, there is limited empirical understanding of fluid overload's impact on mortality. This study analyzes fluid overload trajectories and their association with mortality in hemodialysis patients.
View Article and Find Full Text PDFBr J Ophthalmol
December 2024
Department of Ophthalmology and Medical Research Center, Oulu University Hospital; Research Unit of Clinical Medicine, University of Oulu, Oulu, Finland.
Background/aims: The purpose of this study is to define genetic factors associated with anterior uveitis through genome-wide association study (GWAS).
Methods: In this GWAS meta-analysis, we combined data from the FinnGen, Estonian Biobank and UK Biobank with a total of 12 205 anterior uveitis cases and 917 145 controls. We performed a phenome-wide association study (PheWAS) to investigate associations across phenotypes and traits.
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