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Polyploids are widespread in plants and are important drivers for evolution and biodiversity. Allopolyploidy activates transposable elements (TEs) and causes genomic shock. Plant genomes can regulate gene expression by changing the epigenetic modification of TEs, but the mechanism for TEs to capture genes remains to be explored. TEs used the 'peel-and-paste' mechanism to achieve gene capture. We identified 3156 capture events and 326 donor genes of TEs in (AACC). The donor genes captured by TEs were related to the number, length, and location of their exons. The gene-capturing TEs carrying donor gene fragments were evenly distributed on the genome, and more than half of them were involved in the construction of pseudogenes, becoming the reserve force for polyploid evolution. Gene fragment copies enhanced information storage, providing opportunities for gene mutation and the formation of new genes. Simultaneously, the siRNAs targeting TEs may act on the donor genes due to siRNA crosstalk, and the gene methylation levels increased and the expression levels decreased. The genome sought a balance between sacrificing donor gene expression and silencing TEs, allowing TEs to hide in the genome. In addition, epigenetic modifications may temporarily relax the control of gene capture during allopolyploidization. Our study identified and characterized gene capture events in , analyzed the effects of DNA methylation and siRNA on gene capture events, and explored the regulation mechanism of gene expression by TE epigenetic modification during allopolyploidization, which will contribute to understanding the formation and evolution mechanism of allopolyploidy.
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http://dx.doi.org/10.1093/hr/uhaf028 | DOI Listing |
PLoS One
September 2025
Smart Manufacturing and Artificial Intelligence, Micron Memory Malaysia Sdn. Bhd., Batu Kawan, Penang, Malaysia.
Advances in data collection have resulted in an exponential growth of high-dimensional microarray datasets for binary classification in bioinformatics and medical diagnostics. These datasets generally possess many features but relatively few samples, resulting in challenges associated with the "curse of dimensionality", such as feature redundancy and an elevated risk of overfitting. While traditional feature selection approaches, such as filter-based and wrapper-based approaches, can help to reduce dimensionality, they often struggle to capture feature interactions while adequately preserving model generalization.
View Article and Find Full Text PDFCancer Cell
July 2025
Department of Lymphoma and Myeloma, University of Texas (UT) MD Anderson Cancer Center, Houston, TX, USA; Lymphoid Malignancies Program, UT MD Anderson Cancer Center, Houston, TX, USA; Department of Genomic Medicine, UT MD Anderson Cancer Center, Houston, TX, USA. Electronic address: mgreen5@mdander
Large B cell lymphomas (LBCL) are clinically and biologically heterogeneous lymphoid malignancies with complex microenvironments that are central to disease etiology. Here, we have employed single-nucleus multiome profiling of 232 tumor and control biopsies to characterize diverse cell types and subsets that are present in LBCL tumors, effectively capturing the lymphoid, myeloid, and non-hematopoietic cell compartments. Cell subsets co-occurred in stereotypical lymphoma microenvironment archetype profiles (LymphoMAPs) defined by; (1) a sparsity of T cells and high frequencies of cancer-associated fibroblasts and tumor-associated macrophages (FMAC); (2) lymph node architectural cell types with naive and memory T cells (LN); or (3) activated macrophages and exhausted CD8 T cells (TEX).
View Article and Find Full Text PDFAm J Physiol Cell Physiol
September 2025
Humboldt-University zu Berlin, Berlin, Germany.
Skeletal muscle atrophy and weakness are major contributors to morbidity, prolonged recovery, and long-term disability across a wide range of diseases. Atrophy is caused by breakdown of sarcomeric proteins resulting in loss of muscle mass and strength. Molecular mechanism underlying the onset of muscle atrophy and its progression have been analysed in patients, mice, and cell culture but the complementarity of these model systems remains to be explored.
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.
View Article and Find Full Text PDFJBMR Plus
October 2025
Department of Endocrinology and Diabetes, Sir Charles Gairdner Hospital, Nedlands, WA, 6009, Australia.
Genome-wide association studies (GWAS) relevant to osteoporosis have identified hundreds of loci; however, understanding how these variants influence the phenotype is complicated because most reside in non-coding DNA sequence that serves as transcriptional enhancers and repressors. To advance knowledge on these regulatory elements in osteoclasts (OCs), we performed Micro-C analysis, which informs on the genome topology of these cells and integrated the results with transcriptome and GWAS data to further define loci linked to BMD. Using blood cells isolated from 4 healthy participants aged 31-61 yr, we cultured OC in vitro and generated a Micro-C chromatin conformation capture dataset.
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