196 research outputs found
Genetic Regulatory Perturbation of Gene Expression Impacted by Genomic Introgression in Fiber Development of Allotetraploid Cotton
Get PDFInterspecific genomic introgression is an important evolutionary process with respect to the generation of novel phenotypic diversity and adaptation. A key question is how gene flow perturbs gene expression networks and regulatory interactions. Here, an introgression population of two species of allopolyploid cotton (Gossypium) to delineate the regulatory perturbations of gene expression regarding fiber development accompanying fiber quality change is utilized. De novo assembly of the recipient parent (G. hirsutum Emian22) genome allowed the identification of genomic variation and introgression segments (ISs) in 323 introgression lines (ILs) from the donor parent (G. barbadense 3–79). It documented gene expression dynamics by sequencing 1,284 transcriptomes of developing fibers and characterized genetic regulatory perturbations mediated by genomic introgression using a multi-locus model. Introgression of individual homoeologous genes exhibiting extreme low or high expression bias can lead to a parallel expression bias in their non-introgressed duplicates, implying a shared yet divergent regulatory fate of duplicated genes following allopolyploidy. Additionally, the IL N182 with improved fiber quality is characterized, and the candidate gene GhFLAP1 related to fiber length is validated. This study outlines a framework for understanding introgression-mediated regulatory perturbations in polyploids, and provides insights for targeted breeding of superior upland cotton fiber.This article is published as Chen, Xinyuan, Xiubao Hu, Guo Li, Corrinne E. Grover, Jiaqi You, Ruipeng Wang, Zhenping Liu et al. "Genetic Regulatory Perturbation of Gene Expression Impacted by Genomic Introgression in Fiber Development of Allotetraploid Cotton." Advanced Science (2024): 2401549. doi:10.1002/advs.202401549. © 2024 The Author(s). This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited
Experimental investigation of a modified Beckmann–Kirchhoff scattering theory for the in-process optical measurement of surface quality
No full textAnalysis of the Current Indications for Microfracture of Chondral Lesions in the Hip Joint: Letter to the Editor
No full textNotice of Retraction: A study of support vector regression for surface characteristics in-process optical measurement
No full textProtocol for near-infrared optogenetics manipulation of neurons and motor behavior in C. elegans using emissive upconversion nanoparticles
No full textSummary: In deep tissue, optogenetics faces limitations with visible light. Here, we present a protocol for near-infrared (NIR) optogenetics manipulation of neurons and motor behavior in Caenorhabditis elegans using emissive upconversion nanoparticles (UCNPs). We describe steps for synthesizing and modifying UCNPs. We then detail procedures for regulating neurons using these UCNPs in the model organism C. elegans. Using NIR light allows for superior tissue penetration to manipulate neuronal activities and locomotion behavior.For complete details on the use and execution of this protocol, please refer to Guo et al.,1 Ao et al.,2 and Zhang et al.3 : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics
Generative Adversarial Network of Industrial Positron Images on Memory Module
No full textPET (Positron Emission Computed Tomography) imaging is a challenge due to the ill-posed nature and the low data of photo response lines. Generative adversarial networks have been widely used in computer vision and made great success recently. In our paper, we trained an adversarial model to improve the industrial positron images quality based on the attention mechanism. The innovation of the proposed method is that we build a memory module that focuses on the contribution of feature details to interested parts of images. We use an encoder to get the hidden vectors from a basic dataset as the prior knowledge and train the nets jointly. We evaluate the quality of the simulation positron images by MS-SSIM and PSNR. At the same time, the real industrial positron images also show a good visual effect
Mechanisms of Peritoneal Mesothelial Cells in Peritoneal Adhesion
No full textA peritoneal adhesion (PA) is a fibrotic tissue connecting the abdominal or visceral organs to the peritoneum. The formation of PAs can induce a variety of clinical diseases. However, there is currently no effective strategy for the prevention and treatment of PAs. Damage to peritoneal mesothelial cells (PMCs) is believed to cause PAs by promoting inflammation, fibrin deposition, and fibrosis formation. In the early stages of PA formation, PMCs undergo mesothelial–mesenchymal transition and have the ability to produce an extracellular matrix. The PMCs may transdifferentiate into myofibroblasts and accelerate the formation of PAs. Therefore, the aim of this review was to understand the mechanism of action of PMCs in PAs, and to offer a theoretical foundation for the treatment and prevention of PAs
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