In eukaryotic cells, 3D genome plays an important role in the regulation of gene spatiotemporal expression, which is essential for the biological and developmental processes in a life cycle. In the past decade, the development of high-throughput technologies greatly enhances our ability to map the 3D genome organization, identifies multiple 3D genome structures, and investigates the functional role of 3D genome organization in gene regulation, which facilitates our understandings of -regulatory landscape and biological development. Comparing with the comprehensive analyses of 3D genome in mammals and model plants, the progress in soybean is much less. Future development and application of tools to precisely manipulate 3D genome structure at different levels will significantly strengthen the functional genome study and molecular breeding in soybean. Here, we review the recent progresses in 3D genome study and discuss future directions, which may help to improve soybean 3D functional genome study and molecular breeding.
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http://dx.doi.org/10.1007/s11032-023-01374-4 | 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
Department of Immunology and Regenerative Biology, Weizmann Institute of Science, Rehovot 7610001, Israel.
Malignant gliomas are heterogeneous tumors, mostly incurable, arising in the central nervous system (CNS) driven by genetic, epigenetic, and metabolic aberrations. Mutations in isocitrate dehydrogenase (IDH1/2) enzymes are predominantly found in low-grade gliomas and secondary high-grade gliomas, with IDH1 mutations being more prevalent. Mutant-IDH1/2 confers a gain-of-function activity that favors the conversion of a-ketoglutarate (α-KG) to the oncometabolite 2-hydroxyglutarate (2-HG), resulting in an aberrant hypermethylation phenotype.
View Article and Find Full Text PDFProc Natl Acad Sci U S A
January 2025
Department of Biology, Faculty of Science and Technology, Mount Royal University, Calgary, AB T3E 6K6, Canada.
With over 14 million people living above 3,500 m, the study of acclimatization and adaptation to high altitude in human populations is of increasing importance, where exposure to high altitude (HA) imposes a blood oxygenation and acid-base challenge. A sustained and augmented hypoxic ventilatory response protects oxygenation through ventilatory acclimatization, but elicits hypocapnia and respiratory alkalosis. A subsequent renally mediated compensatory metabolic acidosis corrects pH toward baseline values, with a high degree of interindividual variability.
View Article and Find Full Text PDFPLoS 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 Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan, China.
Transfer learning aims to integrate useful information from multi-source datasets to improve the learning performance of target data. This can be effectively applied in genomics when we learn the gene associations in a target tissue, and data from other tissues can be integrated. However, heavy-tail distribution and outliers are common in genomics data, which poses challenges to the effectiveness of current transfer learning approaches.
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