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Twisted-wing insects (Strepsiptera) are an enigmatic order of parasites with unusual life histories and striking sexual dimorphism. Males emerge from hosts as free-living winged adults, while females from most species remain as endoparasites that retain larval traits. Due to scarce genomic data and phylogenetic controversies, Strepsiptera was only recently placed as the closest living relative to beetles (Coleoptera). Here, we report the first PacBio HiFi genome assembly of the strepsipteran Xenos peckii (Xenidae). This de novo assembly size is 72.1 Mb, with a BUSCO score of 87.4%, N50 of 7.3 Mb, 23.4% GC content, and 38.41% repeat content. We identified 8 contigs that contain >75% of the assembly and reflect the haploid chromosome number reported from karyotypic data, and 3 contigs that exhibit sex chromosome coverage patterns. Additionally, the mitochondrial genome is 16,111 bp long and has 37 genes. This long-read assembly for Strepsiptera reveals a miniature genome and provides a unique tool to understand complex genome evolution associated with a parasitic lifestyle and extreme sexual dimorphism.
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http://dx.doi.org/10.1038/s41597-024-03808-w | DOI Listing |
Med Sci (Paris)
September 2025
CIRI, Centre international de recherche en infectiologie Université de Lyon, Inserm U1111, Université Claude Bernard Lyon 1, CNRS UMR5308, ENS de Lyon, Lyon, France.
The accumulated knowledge on the biology of the HIV-1 virus has led to the emergence of technologies that exploit the architecture of retroviruses and their integration or vectorization properties. This field of study constitutes retroviral vectorology, democratized in laboratories by the use of lentiviral vectors. By hijacking retroviral assembly, other systems are emerging and are increasingly mentioned in recent literature.
View Article and Find Full Text PDFPLoS Biol
September 2025
Environmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, Berkeley, California, United States of America.
Inter-laboratory replicability is crucial yet challenging in microbiome research. Leveraging microbiomes to promote soil health and plant growth requires understanding underlying molecular mechanisms using reproducible experimental systems. In a global collaborative effort involving five laboratories, we aimed to help advance reproducibility in microbiome studies by testing our ability to replicate synthetic community assembly experiments.
View Article and Find Full Text PDFArch Microbiol
September 2025
College of Agriculture and Biology, Zhongkai University of Agriculture and Engineering, Guangzhou, 510225, People's Republic of China.
Cystofilobasidium infirmominiatum, biotechnologically significant yeast, is increasingly garnering attention due to its superior ability to produce valuable carotenoids and lipids. Nonetheless, until now, the reference genome that governs the biosynthesis of carotenoids and lipids in C. infirmominiatum remains unreported.
View Article and Find Full Text PDFMicrobiol Spectr
September 2025
Department of Viral Transformation, Leibniz Institute of Virology (LIV), Martinistraße, Hamburg, Germany.
Unlabelled: Human adenoviruses (HAdVs) induce significant reorganization of the nuclear environment, leading to the formation of virus-induced subnuclear structures known as replication compartments (RCs). Within these RCs, viral genome replication, gene expression, and modulation of cellular antiviral responses are tightly coordinated, making them valuable models for studying virus-host interactions. In a recent study, we analyzed the protein composition of HAdV type 5 (HAdV-C5) RCs isolated from infected primary cells at different time points during infection using quantitative proteomics.
View Article and Find Full Text PDFmSystems
September 2025
Genome Biology Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany.
Genome-scale metabolic models (GEMs) are widely used in systems biology to investigate metabolism and predict perturbation responses. Automatic GEM reconstruction tools generate GEMs with different properties and predictive capacities for the same organism. Since different models can excel at different tasks, combining them can increase metabolic network certainty and enhance model performance.
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