Polyploidy is a common phenomenon among willow species. In this study, genome sequencing was conducted for Salix matsudana Koidz (also named Chinese willow), an important greening and arbor tree species, and the genome of this species was compared with those of four other tree species in Salicaceae. The total genome sequence of S. matsudana was 655.72 Mb in size, with repeated sequences accounting for 45.97% of the total length. In total, 531.43 Mb of the genome sequence could be mapped onto 38 chromosomes using the published genetic map as a reference. The genome of S. matsudana could be divided into two groups, the A and B genomes, through homology analysis with the genome of Populus trichocarpa, and the A and B genomes contained 23,985 and 25,107 genes, respectively. 4DTv combined transposon analysis predicted that allotetraploidy in S. matsudana appeared ~4 million years ago. The results from this study will help reveal the evolutionary history of S. matsudana and lay a genetic basis for its breeding.
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http://dx.doi.org/10.1038/s41438-020-00424-8 | DOI Listing |
Proc Natl Acad Sci U S A
January 2025
Zhejiang Key Laboratory of Biology and Ecological Regulation of Crop Pathogens and Insects, Institute of Insect Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, China.
The harlequin ladybird, , is a predatory beetle used globally to control pests such as aphids and scale insects. Originating from East Asia, this species has become highly invasive since its introduction in the late 19th century to Europe and North America, posing a threat to local biodiversity. Intraguild predation is hypothesized to drive the success of this invasive species, but the underlying mechanisms remain unknown.
View Article and Find Full Text PDFProc Natl Acad Sci U S A
January 2025
Innovative Genomics Institute, University of California, Berkeley, CA 94720.
The widespread application of genome editing to treat and cure disease requires the delivery of genome editors into the nucleus of target cells. Enveloped delivery vehicles (EDVs) are engineered virally derived particles capable of packaging and delivering CRISPR-Cas9 ribonucleoproteins (RNPs). However, the presence of lentiviral genome encapsulation and replication proteins in EDVs has obscured the underlying delivery mechanism and precluded particle optimization.
View Article and Find Full Text PDFInt J Radiat Biol
January 2025
Chungbuk National University College of Medicine, Cheongju, Republic of Korea.
Purpose: We aimed to identify the transcriptomic signatures of soft tissue sarcoma (STS) related to radioresistance and establish a model to predict radioresistance.
Materials And Methods: Nine STS cell lines were cultured. Adenosine triphosphate-based viability was determined 5 days after irradiation with 8 Gy of X-rays in a single fraction.
PLoS Negl Trop Dis
January 2025
Laboratorio de Ingeniería Genética y Biología Celular y Molecular-Área de virus de insectos, Departamento de Ciencia y Tecnología, Universidad Nacional de Quilmes, Quilmes, Buenos Aires, Argentina.
Mosquitoes are the primary vectors of arthropod-borne pathogens. Aedes aegypti is one of the most widespread mosquito species worldwide, responsible for transmitting diseases such as Dengue, Zika, and Chikungunya, among other medically significant viruses. Characterizing the array of viruses circulating in mosquitoes, particularly in Aedes aegypti, is a crucial tool for detecting and developing novel strategies to prevent arbovirus outbreaks.
View Article and Find Full Text PDFPLoS Comput Biol
January 2025
Department of Computer Science, Colorado State University, Fort Collins, Colorado, United States of America.
Complex deep learning models trained on very large datasets have become key enabling tools for current research in natural language processing and computer vision. By providing pre-trained models that can be fine-tuned for specific applications, they enable researchers to create accurate models with minimal effort and computational resources. Large scale genomics deep learning models come in two flavors: the first are large language models of DNA sequences trained in a self-supervised fashion, similar to the corresponding natural language models; the second are supervised learning models that leverage large scale genomics datasets from ENCODE and other sources.
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