|
|
|
题名
|
作者
|
年代
|
出处
|
被引量
|
| 1 | Amplicon-Based Illumina Sequencing and Quantitative PCR Reveals Nanoplankton Diversity and Biomass in Surface Water of Qinhuangdao Coastal Area, China显示文摘Aureococcus anophagefferens caused brown tides for three consecutive years from 2009 to 2011 in the coastal waters of Qinhuangdao, China, with numerous, widespread ecological and economic impact on ecosystems. To understand the population dy- namics of nanoplankton during the brown tides, sequences of the V9 region of the 18S rDNA gene, used as a marker, were analyzed by Illumina sequencing to assess nanoplankton biomass, and real-time fluorescence quantitative PCR was performed to analyze spa- tial variation in the 18S rDNA copy concentrations of nanoplankton off the Qinhuangdao coast in July, 2011. The results showed that A. anophagefferens and Minutocellus polymorphus were the dominant species in the local phytoplankton community during the brown tide in July 2011. The highest 18S rDNA copy concentrations of A. anophagefferens and M. polymorphus were detected at stations SHG and FN, respectively. The central area most strongly affected by the brown tide migrated southward from 2011 to 2013. Redundancy analysis (RDA) showed that the decreasing NOx concentration might provide suitable nutrient conditions for the A. anophagefferens outbreak. During the brown tide caused by A. anophagefferens, other phytoplankton, such as diatoms, cryptophytes, chlorophytes, dinoflagellates and other flagellates, could co-occur with it. For zooplankton, due to less selective feeding behavior, Amoebozoa was the most abundant zooplankton at station SHG, while Ciliophora was the most abundant zooplankton at other sta- tions for its more selective feeding. | QIAO Ling YU Jie LI Ying GUO Haobing ZHEN Yu ZHANG Lingling MI Tiezhu BAO Zhenmin XU Xiaochun | 2019 | Journal of Ocean University of China2019，18，4： | 2 |
| 2 | Machine-learning based ocean atmospheric duct forecasting:a hybrid model-data-driven approach显示文摘The atmospheric duct is a vital radio wave environment.Conventional methods of forecasting the atmospheric duct mainly include statistical analysis based on sounding observation data and mesoscale numerical model-based prediction.The former can provide accurate duct information but is highly dependent on the acquisition of data sets.The latter is more practical but still lacks accuracy.This paper introduces machine learning to establish a novel meteorological parameter correction model for atmospheric duct prediction.In detail,using the weather research and forecasting(WRF)model data and spatiotemporal characteristics as input,sounding data as label and extreme gradient boosting(XGBoost)model for training,the meteorological parameter correction effect is the best,i.e.,the accuracy of forecast meteorological parameters is improved by about 65.4%.Combining the mapping relationship between meteorological parameters and corrected atmospheric refractive index(CARI),and the transition mechanism of CARI to duct parameters,a new duct forecasting mechanism is proposed.Due to the high efficiency of numerical model and the accuracy of sounding data,the new duct forecasting mechanism has excellent performance.By comparing the duct forecasting results,the forecasting accuracy of the new duct forecasting model is significantly higher than that of the mesoscale model. | Feng Yuting Gong Haobing Hao Xiaojing Gao Hui Guo Xiangming | 2023 | The Journal of China Universities of Posts and Telecommunications2023，30，4： | 0 |
| 3 | Chromosome-scale assembly reveals asymmetric paleo-subgenome evolution and targets for the acceleration of fungal resistance breeding in the nut crop, pecan显示文摘Pecan(Carya illinoinensis)is a tree nut crop of worldwide economic importance that is rich in healthpromoting factors.However,pecan production and nut quality are greatly challenged by environmental stresses such as the outbreak of severe fungal diseases.Here,we report a high-quality,chromosome-scale genome assembly of the controlled-cross pecan cultivar‘Pawnee’constructed by integrating Nanopore sequencing and Hi-C technologies.Phylogenetic and evolutionary analyses reveal two whole-genome duplication(WGD)events and two paleo-subgenomes in pecan and walnut.Time estimates suggest that the recent WGD event and considerable genome rearrangements in pecan and walnut account for expansions in genome size and chromosome number after the divergence from bayberry.The two paleo-subgenomes differ in size and protein-coding gene sets.They exhibit uneven ancient gene loss,asymmetrical distribution of transposable elements(especially LTR/Copia and LTR/Gypsy),and expansions in transcription factor families(such as the extreme pecan-specific expansion in the far-red impaired response 1 family),which are likely to reflect the long evolutionary history of species in the Juglandaceae.A whole-genome scan of resequencing data from 86 pecan scab-associated core accessions identified 47 chromosome regions containing 185 putative candidate genes.Significant changes were detected in the expression of candidate genes associated with the chitin response pathway under chitin treatment in the scab-resistant and scabsusceptible cultivars‘Excell’and‘Pawnee’.These findings enable us to identify key genes that may be important susceptibility factors for fungal diseases in pecan.The high-quality sequences are valuable resources for pecan breeders and will provide a foundation for the production and quality improvement of tree nut crops. | Lihong Xiao Mengjun Yu Ying Zhang Jie Hu Rui Zhang Jianhua Wang Haobing Guo He Zhang Xinyu Guo Tianquan Deng Saibin Lv Xuan Li Jianqin Huang Guangyi Fan | 2021 | Plant Communications2021，2，6： | 0 |
您所在的机构暂未开通此部分的功能，请联系管理员