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Molecular Plant 2019年第11期12卷 1515-1523页

作者： Zai Zheng Zhen Wang Xiaoyue Wang Dong Liu MOE Key Laboratory of bioinformatics Center for Plant BiologySchool of Life SciencesTsinghua UniversityBeijing 100084China

To tolerate phosphate(Pi)deficiency in the environment,plants alter their developmental and metabolic *** the past two decades,researchers have extensively used Petri dish-grown seedlings of the model plant Arabidopsis thaliana to study the molecular mechanisms underlying root developmental responses to Pi deficiency.A typical developmental response of the Petri dish-grown Arabidopsis seedlings to Pi deficiency is the inhibited growth of primary root(PR).This response is generally thought to enhance the production of lateral roots and root hairs,which increases the plant’s ability to obtain Pi and is therefore regarded as an active cellular ***,we report that direct illumination of root surface with blue light is critical and sufficient for Pi deficiency-induced inhibition of PR growth in Arabidopsis *** further show that a blue light-triggered malate-mediated photo-Fenton reaction and a canonical Fenton reaction form an Fe redox cycle in the root *** Fe redox cycle results in the production of hydroxyl radicals that inhibit PR *** addition to revealing the molecular mechanism underlying Pi deficiency-induced inhibition of PR growth,our work demonstrated that this developmental change is not an active cellular response;instead,it is a phenotype resulting from root growth in transparent Petri *** finding is significant because illuminated,transparent Petri dishes have been routinely used to study Arabidopsis root responses to environmental changes.

关键词： phosphate deficiency root response blue light Fe redox cycle hydroxyl radicals

Advances and challenges towards the study of RNA-RNA interactions in a transcriptome-wide scale

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Frontiers of Electrical and Electronic Engineering in China 2018年第3期6卷 239-252页

作者： Jing Gongt Yanyan Jut Di Shao Qiangfeng Cliff Zhang MOE Key Laboratory of bioinformatics Beijing Advanced Innovation Center for Structural BiologyCenter for Synthetic and Systems BiologyTsinghua-Peking Joint Center for Life SciencesSchool of Life SciencesTsinghua UniversityBeijing 100084China

RNA molecules play crucial roles in various biological processes. Their regulation and function are mediated by interacting with other molecules. Among them RNA-RNA interactions （RRIs） are important in many basic cellular activities including transcription, RNA processing, localization, and translation. However, we just start to unveil the complexity of the knowledge and underlying mechanisms of RRIs. Results： In this review, we will summarize approaches for RRI identifications, including both conventional, focused biophysical and biochemical methods and recently developed large scale sequencing-based techniques. We will also discuss discoveries per RRI type revealed by using these technologies, as well as challenges towards a systematic and functional understanding of RRIs. Conclusions： The development of sequencing-based techniques has revolutionized the study of RRIs. Applying these techniques in multiple organisms has identified thousands of RRls, many of which could potentially regulate multiple aspects of gene expression. However, despite the great breakthrough, the RNA-RNA interactome of any species remains far from complete due to intrinsic complex nature of RRI and limitations in current techniques. More efficient experimental methods and computational framework are needed to obtain the full image of RRI networks, and their possible regulatory roles in biology and medicine.

关键词： RNA-RNA interactions PARIS SPLASH LIGR-seq next generation sequencing

scEpiTools: a database to comprehensively interrogate analytic tools for single-cell epigenomic data

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Journal of Genetics and Genomics 2024年第4期51卷 462-465页

作者： Zijing Gao Xiaoyang Chen Zhen Li Xuejian Cui Qun Jiang Keyi Li Shengquan Chen Rui Jiang Ministry of Education Key Laboratory of bioinformatics Bioinformatics Division at the Beijing National Research Center for Information Science and TechnologyCenter for Synthetic and Systems BiologyDepartment of AutomationTsinghua UniversityBeijing 100084China School of Mathematical Sciences and LPMC Nankai UniversityTianjin 300071China

Recent advances in single-cell sequencing technologies provide significant implications for understanding cellular heterogeneity,developmental biology,and disease *** fully exploit the potential of these data,numerous tools have been proposed for upstream and downstream *** the the single-cell RNA sequencing(scRNA-seq)community,scRNA-tools(Zappia et al.,2018)was proposed to help researchers navigate the plethora of tools by *** its inception,scRNA-tools has been widely used and its updated version further reveals trends in the field with over 1000 collected tools(Zappia and Theis,2021),providing a valuable guidance in selecting tools for analyses.

关键词： analytic selecting Tools

Variable importance-weighted Random Forests

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Frontiers of Electrical and Electronic Engineering in China 2017年第4期5卷 338-351页

作者： Yiyi Liu Hongyu Zhao Department of Biostatistics School of Public Health Yale University New Haven CT 06511 USA program of Computational biology and bioinformatics Yale University New Haven CT 06511 USA

Background： Random Forests is a popular classification and regression method that has proven powerful for various prediction problems in biological studies. However, its performance often deteriorates when the number of features increases. To address this limitation, feature elimination Random Forests was proposed that only uses features with the largest variable importance scores. Yet the performance of this method is not satisfying, possibly due to its rigid feature selection, and increased correlations between trees of forest. Methods： We propose variable importance-weighted Random Forests, which instead of sampling features with equal probability at each node to build up trees, samples features according to their variable importance scores, and then select the best split from the randomly selected features. Results： We evaluate the performance of our method through comprehensive simulation and real data analyses, for both regression and classification. Compared to the standard Random Forests and the feature elimination Random Forests methods, our proposed method has improved performance in most cases. Conclusions： By incorporating the variable importance scores into the random feature selection step, our method can better utilize more informative features without completely ignoring less informative ones, hence has improved prediction accuracy in the presence of weak signals and large noises. We have implemented an R package ＂viRandomForests＂ based on the original R package ＂randomForest＂ and it can be freely downloaded from http：// ***/software.

关键词： Random Forests variable importance score classification regression

Mammalian mitochondrial RNAs are degraded in the mitochondrial intermembrane space by RNASET2

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Protein & Cell 2017年第10期8卷 735-749页

作者： Peipei Liu Jinliang Huang Qian Zheng Leiming Xie Xinping Lu Jie Jin Geng Wang MOE Key laboratory of bioinformatics Cell Biology and Development Center School of Life Sciences Tsinghua University Beijing 100084 China

Mammalian mitochondrial genome encodes a small set of tRNAs, rRNAs, and mRNAs. The RNA synthesis process has been well characterized. How the RNAs are degraded, however, is poorly understood. It was long assumed that the degradation happens in the matrix where transcription and translation machineries reside. Here we show that contrary to the assumption, mammalian mitochondrial RNA degradation occurs in the mitochondrial intermembrane space （IMS） and the IMS- localized RNASET2 is the enzyme that degrades the RNAs. This provides a new paradigm for understanding mitochondrial RNA metabolism and transport.

关键词： mitochondria intermembrane space ribonuclease mtRNA RNA degradation decay RNASET2 RNase T2 inner membrane transport RNA trafficking

STOCHASTIC SYNCHRONIZATION OF CIRCADIAN RHYTHMS

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Journal of systems Science & Complexity 2010年第5期23卷 978-988页

作者： RajKumar Brojen SINGH Vikram SINGH Ram RAMASWAMY Centre for Interdisciplinary Research in Basic Sciences Jamia Milia Islamia New Delhi 110025 India Center for Computational biology and bioinformatics School of Information Technology Jawaharlal Nehru University New Delhi 110067 India Center for Computational biology and bioinformatics School of Information Technology and School of Physical Sciences Jawaharlal Nehru University New Delhi 110067 India

Models of circadian genetic oscillators involving interlinked feedback processes in molecular level genetic networks in Drosophila melanogaster and Neurospora crassa are studied, and mechanisms whereby synchronization can arise in an assembly of cells are examined. The individual subcellular circadian oscillatory processes are stochastic in nature due to the small numbers of molecules that are involved, and are subject to large fluctuations. The authors investigate and present the simulations of the stochastic dynamics of ensembles of clock-regulating proteins in different nuclei that communicate via ancillary small molecules, environmental parameters, additive cellular noise, or through diffusive processes. The results show that the emergence of collective oscillations is a macroscopic observable which has its origins in the microscopic coupling between distinct cellular oscillators.

关键词： Coupling stochastic dynamics synchrony.

Population dynamics inside cancer biomass driven by repeated hypoxia-reoxygenation cycles

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Frontiers of Electrical and Electronic Engineering in China 2014年第3期9卷 85-99页

作者： Chi Zhang Sha Cao Ying Xu Computational systems biology Lab Department of Biochemistry and Molecular Biology Institute of Bioinformatics Universityof Georgia Athens GA 30602 USA Collegeof Computer Science and Technology Jilin University Changchun 130012 China

A computational analysis of genome-scale transcriptomic data collected on -1,700 tissue samples of three cancer types： breast carcinoma, colon adenocarcinoma and lung adenocarcinoma, revealed that each tissue consists of （at least） two major subpopulations of cancer cells with different capabilities to handle fluctuating Oz levels. The two populations have distinct genomic and transcriptomic characteristics, one accelerating its proliferation under hypoxic conditions and the other proliferating faster with higher O2 levels, referred to as the hypoxia and the reoxygenation subpopulations, respectively. The proportions of the two subpopulations within a cancer tissue change as the average 02 level changes. They both contribute to cancer development but in a complementary manner. The hypoxia subpopulation tends to have higher proliferation rates than the reoxygenation one as well as higher apoptosis rates; and it is largely responsible for the acidic environment that enables tissue invasion and provides protection against attacks from T-cells. In comparison, the reoxygenation subpopulation generates new extracellular matrices in support of further growth of the tumor and strengthens cell-cell adhesion to provide scaffolds to keep all the cells connected. This subpopulation also serves as the major source of growth factors for tissue growth. These data and observations strongly suggest that these two major subpopulations within each tumor work together in a conjugative relationship to allow the tumor to overcome stresses associated with the constantly changing Oz level due to repeated growth and angiogenesis. The analysis results not only reveal new insights about the population dynamics within a tumor but also have implications to our understanding of possible causes of different cancer phenotypes such as diffused versus more tightly connected tumor tissues.

关键词： cancer population dynamics intratumor heterogeneity cancer cell subpopulations hypoxia reoxygenation cancer evolution

Patterns of Chromatin-Modifications Discriminate Different Genomic Features in Arabidopsis

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Tsinghua Science and Technology 2013年第5期18卷 431-440页

作者： Anuj Srivastava Xiaoyu Zhang Sal LaMarca Liming Cai Russell L. Malmberg Institute of bioinformatics University of Georgia The Jackson Laboratory Department of Plant biology University of Georgia Department of Computer Science University of Georgia

Dynamic regulation and packaging of genetic information is achieved by the organization of DNA into chromatin. Nucleosomal core histones, which form the basic repeating unit of chromatin, are subject to various post-translational modifications such as acetylation, methylation, phosphorylation, and ubiquitinylation. These modifications have effects on chromatin structure and, along with DNA methylation, regulate gene *** goal of this study was to determine if patterns in modifications were related to different categories of genomic features, and, if so, if the patterns had predictive value. In this study, we used publically available data（ChIP-chip）for different types of histone modifications（methylation and acetylation） and for DNA methylation for Arabidopsis thaliana and then applied a machine learning based approach（a support vector machine） to demonstrate that patterns of these modifications are very different among different kinds of genomic feature categories（protein, RNA,pseudogene, and transposon elements）. These patterns can be used to distinguish the types of genomic *** methylation and H3K4me3 methylation emerged as features with most discriminative power. From our analysis on Arabidopsis, we were able to predict 33 novel genomic features, whose existence was also supported by analysis of RNA-seq experiments. In summary, we present a novel approach which can be used to discriminate/detect different categories of genomic features based upon their patterns of chromatin modification and DNA methylation.

关键词： chromatin modification DNA methylation support vector machine machine learning Arabidopsis

EMT transcription factors activated circuits:A novel tool to study EMT dynamics and its therapeutic implications

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Synthetic and systems Biotechnology 2024年第1期9卷 1-10页

作者： Tianying Chen Wangyue Jia Bo Zhang Hanqi Xie Qiong Wu MOE Key Laboratory of bioinformatics Center for Synthetic and System BiologySchool of Life SciencesTsinghua UniversityBeijing100084China

The epithelial mesenchymal transition(EMT)plays significant roles in the progression of cancer and fibrotic ***,this process is reversible,resulting in mesenchymal epithelial transition(MET),which plays an important role in cancer *** is a lack of methods to trace and target EMT cells using synthetic biology circuits,which makes it difficult to study the cell fate or develop targeted *** this study,we introduced responsive EMT sensing circuits,which sense the EMT using specific promoters that respond to transcription factors typical of EMT activation(EMT-TFs).The transcriptional strength of EMT-sensing promoters decreased more than 13-fold in response to the overexpression of the ***,the NOT gate circuits were built by placing the tetR transcription repressor under the control of EMT sensing promoters and expressed an output signal using the constitutive CMV promoter modified with tetO sites This circuit is named EMT sensing and responding *** the EMT transcription factors was present,we observed a 5.8-fold signal increase in the ***,we successfully distinguished mesenchymal breast cancer cells from epithelial cancer cells and repressed the proliferation of EMT tumor cells using our *** EMT sensing and responding circuits are promising tools for the identification of EMT cells,which is crucial for EMT-related disease therapy and investigating the mechanisms underlying the reversible EMT process.

关键词： Epithelial mesenchymal transition Synthetic biology Tumor killing

Building digital life systems for future biology and medicine

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Quantitative biology 2023年第3期11卷 207-213页

作者： Xuegong Zhang Lei Wei Rui Jiang Xiaowo Wang Jin Gu Zhen Xie Hairong Lv MOE Key Lab of bioinformatics and bioinformatics Division of BNRIST Department of AutomationTsinghua UniversityBeijing 100084China Center of Synthetic and systems biology Tsinghua UniversityBeijing 100084China School of Life Sciences and School of Medicine Tsinghua UniversityBeijing 100084China

The rapid development of biological technology (BT) and information technology (IT) especially of genomics and artificial intelligence (AI) is bringing great potential for revolutionizing future medicine. We propose the concept and framework of Digital Life systems or dLife as a new paradigm to unleash this potential. It includes the multi-scale and multi-granule measure and representation of life in the digital space, the mathematical and/or computational modeling of the biology behind physiological and pathological processes, and ultimately cyber twins of healthy or diseased human body in the virtual space that can be used to simulate complex biological processes and deduce effects of medical treatments. We advocate that dLife is the route toward future AI precision medicine and should be the new paradigm for future biological and medical research.

关键词： digital life systems digital twin aritificial intelligence precision medicine