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| 1 | p53-dependent upregulation of PIG3 transcription by γ-ray irradiation and its interaction with KAP1 in responding to DNA damage显示文摘PIG3 (p53-inducible gene 3), originally identified as one of a set of genes induced by p53 before the onset of apoptosis, was assumed to contribute to early cellular response to DNA damage. Here, we studied the relation between p53 status and the increased expression of PIG3 by ionizing radiation (IR), and the related clues regarding the involvement of PIG3 in the cellular response to IR-induced DNA damage signaling. We demonstrated that the pentanucleotide microsatellite sequence was responsible for the p53-dependent induction of PIG3 transcription after irradiation, while sequence upstream of PIG3 promoter could maintain the basal level of expression which was not inducible by irradiation. The interaction of PIG3 and the KRAB-ZFP-associated protein 1 (KAP1), a DNA damage response protein, was revealed. PIG3 nucleus foci were formed 15 min after γ-ray irradiation, and which were found to partially colocalize with the phospho-KAP-1 foci as well as γ-H2AX foci. Although the lac operator tagged EGFP based reporter system revealed that PIG3 does not remodel chromatin in large scale in the cells under normal growing condition, it indeed prompted the chromatin relaxation in the cellular response to DNA damage signaling. All these data suggest that PIG3 is involved in IR-induced DNA damage response, and which maybe partially attribute to its interaction with KAP1. | QIN Xia ZHANG ShiMeng LI Bingi LIU XiaoDan HE XingPeng SHANG ZengFu XU QinZhi ZHAO ZengQiang YE QiNong ZHOU PingKun | 2011 | Chinese Science Bulletin2011，56，30： | 2 |
| 2 | Identification of the clustering structure in microbiome data by density clustering on the Manhattan distance显示文摘Clustering technology is a method for grouping data points into clusters containing a group of similar data points. In a real dataset such as microbiome data, the data points are presented as profiles or a probability distribution. These data points form the periphery of a cluster, making it difficult to identify the real clustering structure. In this study, we used density clustering on several distance measures to overcome this difficulty. Experiments using a real dataset indicated that the Manhattan distance is an appropriate distance measure for clustering analysis of microbiome data. | Xingpeng JIANG Xiaohua HU Tingting HE | 2016 | Science China(Information Sciences)2016，59，7： | 2 |
| 3 | A comprehensive overview of cotton genomics,biotechnology and molecular biological studies显示文摘Cotton is an irreplaceable economic crop currently domesticated in the human world for its extremely elongated fiber cells specialized in seed epidermis,which makes it of high research and application value.To date,numerous research on cotton has navigated various aspects,from multi-genome assembly,genome editing,mechanism of fiber development,metabolite biosynthesis,and analysis to genetic breeding.Genomic and 3D genomic studies reveal the origin of cotton species and the spatiotemporal asymmetric chromatin structure in fibers.Mature multiple genome editing systems,such as CRISPR/Cas9,Cas12(Cpf1)and cytidine base editing(CBE),have been widely used in the study of candidate genes affecting fiber development.Based on this,the cotton fiber cell development network has been preliminarily drawn.Among them,the MYB-b HLH-WDR(MBW)transcription factor complex and IAA and BR signaling pathway regulate the initiation;various plant hormones,including ethylene,mediated regulatory network and membrane protein overlap fine-regulate elongation.Multistage transcription factors targeting Ces A 4,7,and 8 specifically dominate the whole process of secondary cell wall thickening.And fluorescently labeled cytoskeletal proteins can observe real-time dynamic changes in fiber development.Furthermore,research on the synthesis of cotton secondary metabolite gossypol,resistance to diseases and insect pests,plant architecture regulation,and seed oil utilization are all conducive to finding more high-quality breeding-related genes and subsequently facilitating the cultivation of better cotton varieties.This review summarizes the paramount research achievements in cotton molecular biology over the last few decades from the above aspects,thereby enabling us to conduct a status review on the current studies of cotton and provide strong theoretical support for the future direction. | Xingpeng Wen Zhiwen Chen Zuoren Yang Maojun Wang Shuangxia Jin Guangda Wang Li Zhang Lingjian Wang Jianying Li Sumbul Saeed Shoupu He Zhi Wang Kun Wang Zhaosheng Kong Fuguang Li Xianlong Zhang Xiaoya Chen Yuxian Zhu | 2023 | Science China(Life Sciences)2023，66，10： | 2 |
| 4 | Numerical modeling of the thermal lensing effect in a grazing-incidence laser显示文摘 | Yan Xingpeng Gong Mali He Fahong | 2009 | Optics Communications2009，282，： | 1 |
| 5 | miR-15b and miR-16 induce the apoptosis of rat activated pancreatic stellate cells by targeting Bcl-2 in vitro显示文摘 | Jie Shen Rong Wan Guoyong Hu Lijuan Yang Jie Xiong Feng Wang Jiaqing Shen Shanshan He Xiaoyan Guo Jianbo Ni Chuanyong Guo Xingpeng Wang | 2012 | Pancreatology2012，，： | 1 |
| 6 | A powerful adaptive microbiome-based association test for microbial association signals with diverse sparsity levels显示文摘The dysbiosis of microbiome may have negative effects on a host phenotype.The microbes related to the host phenotype are regarded as microbial association signals.Recently,statistical methods based on microbiome-phenotype association tests have been extensively developed to detect these association signals.However,the currently available methods do not perform well to detect microbial association signals when dealing with diverse sparsity levels(i.e.,sparse,low sparse,non-sparse).Actually,the real association patterns related to different host phenotypes are not unique.Here,we propose a powerful and adaptive microbiome-based association test to detect microbial association signals with diverse sparsity levels,designated as MiATDS.In particular,we define probability degree to measure the associations between microbes and the host phenotype and introduce the adaptive weighted sum of powered score tests by considering both probability degree and phylogenetic information.We design numerous simulation experiments for the task of detecting association signals with diverse sparsity levels to prove the performance of the method.We find that type I error rates can be well-controlled and MiATDS shows superior efficiency on the power.By applying to real data analysis,MiATDS displays reliable practicability too.The R package is available at http://gffzz188fe103f8f1460as90uwu50o6p9p6pb6.ffgz.tsg.suse.edu.cn/XiaoyunHuang33/MiATDS. | Han Sun Xiaoyun Huang Lingling Fu Ban Huo Tingting He Xingpeng Jiang | 2021 | Journal of Genetics and Genomics2021，48，9： | 0 |
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