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Genome-wide analysis of the CCCH zinc finger family in longan:Characteristic identification and expression profiles in Dimocarpus longan Lour 被引量:1
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作者 SU Li-yao XIAO Xue-chen +5 位作者 JIANG Meng-qi HUANG Shu-qi XUE Xiao-dong LI Xue LAI Zhong-xiong LIN Yu-ling 《Journal of Integrative Agriculture》 SCIE CAS CSCD 2022年第1期113-130,共18页
CCCH(C3 H) Zinc finger(Znf) transcription factors(TFs), as a novel type of Znf gene, regulate the expression of genes by binding to their mRNAs and play important roles in plant growth and development and abiotic stre... CCCH(C3 H) Zinc finger(Znf) transcription factors(TFs), as a novel type of Znf gene, regulate the expression of genes by binding to their mRNAs and play important roles in plant growth and development and abiotic stress resistance.Longan(Dimocarpous longan) is a tropical/subtropical fruit tree of great economic importance in Southeast Asia.However, genomic information on C3 H and their functions in longan are still unknown. In this study, a comprehensive analysis of the longan C3 H(DlC3 H) gene family was carried out. A total of 49 DlC3 H genes in three clades were identified from the longan genome database. Characteristics of the genes were analyzed with respect to gene structure,motif composition, phylogenetic tree and potential functions. The analysis of alternative splicing(AS) events suggested that AS events in DlC3 H genes were related to the transformation from longan non-embryonic to embryonic cultures.Promoter analysis indicated that most of the DlC3 H genes included cis-acting elements associated with hormones and stresses responses. Quantitative real-time PCR(qRT-PCR) analysis indicated that 26 of the 49 DlC3 Hs, which possess methyl jasmonate(MeJA) and abscisic acid(ABA) responsive cis-acting elements, showed differential expression patterns under treatment with ABA, MeJA and their endogenous inhibitors, suggesting that DlC3 Hs might be involved in the ABA and MeJA signaling pathways. The expression profiles of 17 of the 49 DlC3 Hs in non-embryonic callus and three tissues of embryonic cultures showed that only five of the 17 DlC3 Hs had the same expression trends as the FPKM trends in transcriptome data;the expression levels of DlC3 H07/14/16/36/49 in embryogenic callus and DlC3 H04/38 in globular embryos were high, suggesting that they have different functions in embryonic development. Further, we verified that DlC3 H01/03/05/11/19/39 were regulated by sRNAs by a modified 5’ RLM-RACE method. This study provides the first systematic analysis of C3 H genes in longan, and found that C3 H genes may be involved in hormone and stress responses, and somatic embryogenesis. Our preliminary investigation may provide clues to further studies on the characteristics and functions of this family in longan. 展开更多
关键词 Dimocarpus longan Lour CCCH Zinc finger characteristic identification expression profile
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Nonlinear Systems Identification via an Input-Output Model Based on a Feedforward Neural Network
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作者 O. L. Shuai South China University of Technology, Gungzhou, 510641, P.R. China S. C. Zhou S. K. Tso T. T. Wong T.P. Leung The Hong Kong Polytechnic University, HungHom, Kowloon, HK 《International Journal of Plant Engineering and Management》 1997年第4期45-50,共6页
This paper develops a feedforward neural network based input output model for a general unknown nonlinear dynamic system identification when only the inputs and outputs are accessible observations. In the developed m... This paper develops a feedforward neural network based input output model for a general unknown nonlinear dynamic system identification when only the inputs and outputs are accessible observations. In the developed model, the size of the input space is directly related to the system order. By monitoring the identification error characteristic curve, we are able to determine the system order and subsequently an appropriate network structure for systems identification. Simulation results are promising and show that generic nonlinear systems can be identified, different cases of the same system can also be discriminated by our model. 展开更多
关键词 nonlinear dynamic systems identification neural networks based Input Output Model identification error characteristic curve
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Quantifying the characteristics of particulate matters captured by urban plants using an automatic approach 被引量:3
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作者 Jingli Yan Lin Lin +2 位作者 Weiqi Zhou Lijian Han Keming Ma 《Journal of Environmental Sciences》 SCIE EI CAS CSCD 2016年第1期259-267,共9页
It is widely accepted that urban plant leaves can capture airborne particles. Previous studies on the particle capture capacity of plant leaves have mostly focused on particle mass and/or size distribution. Fewer stud... It is widely accepted that urban plant leaves can capture airborne particles. Previous studies on the particle capture capacity of plant leaves have mostly focused on particle mass and/or size distribution. Fewer studies, however, have examined the particle density, and the size and shape characteristics of particles, which may have important implications for evaluating the particle capture efficiency of plants, and identifying the particle sources. In addition, the role of different vegetation types is as yet unclear. Here, we chose three species of different vegetation types, and firstly applied an object-based classification approach to automatically identify the particles from scanning electron microscope(SEM)micrographs. We then quantified the particle capture efficiency, and the major sources of particles were identified. We found(1) Rosa xanthina Lindl(shrub species) had greater retention efficiency than Broussonetia papyrifera(broadleaf species) and Pinus bungeana Zucc.(coniferous species), in terms of particle number and particle area cover.(2) 97.9% of the identified particles had diameter ≤10 μm, and 67.1% of them had diameter ≤2.5 μm. 89.8% of the particles had smooth boundaries, with 23.4% of them being nearly spherical.(3) 32.4%–74.1% of the particles were generated from bare soil and construction activities, and 15.5%–23.0% were mainly from vehicle exhaust and cooking fumes. 展开更多
关键词 Particulate matter retention Urban vegetation Object-based classification Size and shape characteristics Source identification
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