Int J Mol Sci , IF:4.556 , 2019 Sep , V20 (18) doi: 10.3390/ijms20184491
Identification of Long Non-Coding RNAs and the Regulatory Network Responsive to Arbuscular Mycorrhizal Fungi Colonization in Maize Roots.
School of Life Sciences, Anhui Agricultural University, Hefei 230036, China. guominhan@ahau.edu.cn.; National Engineering Laboratory of Crop Stress Resistance Breeding, Anhui Agricultural University, Hefei 230036, China. guominhan@ahau.edu.cn.; School of Life Sciences, Anhui Agricultural University, Hefei 230036, China. funkii@live.com.; School of Life Sciences, Anhui Agricultural University, Hefei 230036, China. 18119675403@163.com.; Department of Genetics, University of Georgia, Athens, GA 30602, USA. xwwang@uga.edu.; School of Life Sciences, Anhui Agricultural University, Hefei 230036, China. xuyunjian1992@163.com.; School of Life Sciences, Anhui Agricultural University, Hefei 230036, China. wangweisys@ahau.edu.cn.; National Engineering Laboratory of Crop Stress Resistance Breeding, Anhui Agricultural University, Hefei 230036, China. wangweisys@ahau.edu.cn.; School of Life Sciences, Anhui Agricultural University, Hefei 230036, China. zhusuwen@126.com.; National Engineering Laboratory of Crop Stress Resistance Breeding, Anhui Agricultural University, Hefei 230036, China. zhusuwen@126.com.; School of Life Sciences, Anhui Agricultural University, Hefei 230036, China. bjchengahau@163.com.; National Engineering Laboratory of Crop Stress Resistance Breeding, Anhui Agricultural University, Hefei 230036, China. bjchengahau@163.com.
Recently, long noncoding RNAs (lncRNAs) have emerged as vital regulators of many biological processes in animals and plants. However, to our knowledge no investigations on plant lncRNAs which respond to arbuscular mycorrhizal (AM) fungi have been reported thus far. In this study, maize roots colonized with AM fungus were analyzed by strand-specific RNA-Seq to identify AM fungi-responsive lncRNAs and construct an associated regulatory network. A total of 1837 differentially expressed protein coding genes (DEGs) were identified from maize roots with Rhizophagus irregularis inoculation. Many AM fungi-responsive genes were homologs to MtPt4, STR, STR2, MtFatM, and enriched pathways such as fatty acid biosynthesis, response to phosphate starvation, and nitrogen metabolism are consistent with previous studies. In total, 5941 lncRNAs were identified, of which more than 3000 were new. Of those, 63 lncRNAs were differentially expressed. The putative target genes of differentially expressed lncRNAs (DELs) were mainly related to phosphate ion transmembrane transport, cellular response to potassium ion starvation, and lipid catabolic processes. Regulatory network analysis showed that DELs might be involved in the regulation of bidirectional nutrient exchange between plant and AM fungi as mimicry of microRNA targets. The results of this study can broaden our knowledge on the interaction between plant and AM fungi.
PMID: 31514333
Genes (Basel) , IF:3.759 , 2019 Sep , V10 (9) doi: 10.3390/genes10090719
WGCNA Analysis of Salt-Responsive Core Transcriptome Identifies Novel Hub Genes in Rice.
Hunan Agricultural University, Changsha 410128, China. uhz_uhz@hotmail.com.; Hunan Rice Research Institute, Changsha 410125, China. uhz_uhz@hotmail.com.; Hunan Rice Research Institute, Changsha 410125, China. xhj1110@126.com.; China National Rice Research Institute, Hangzhou 311401, China. weixiangjin@caas.cn.; Wuhan Benagen Tech Solutions Company Limited, Wuhan 430070, China. komiri.dossa@ucad.edu.sn.; Hunan Agricultural University, Changsha 410128, China. villy816@163.com.; Hunan Agricultural University, Changsha 410128, China. huisuozhen@126.com.; Hunan Rice Research Institute, Changsha 410125, China. tgh579@hotmail.com.; Hunan Rice Research Institute, Changsha 410125, China. zengxiaoshan11@outlook.com.; Hunan Academy of Agricultural Sciences, Changsha 410125, China. yyh30678@163.com.; China National Rice Research Institute, Hangzhou 311401, China. hupeisong@caas.cn.; Hunan Agricultural University, Changsha 410128, China. wjl9678@outlook.com.
Rice, being a major staple food crop and sensitive to salinity conditions, bears heavy yield losses due to saline soil. Although some salt responsive genes have been identified in rice, their applications in developing salt tolerant cultivars have resulted in limited achievements. Herein, we used bioinformatic approaches to perform a meta-analysis of three transcriptome datasets from salinity and control conditions in order to reveal novel genes and the molecular pathways underlying rice response to salt. From a total of 28,432 expressed genes, we identify 457 core differentially expressed genes (DEGs) constitutively responding to salt, regardless of the stress duration, genotype, or the tissue. Gene co-expression analysis divided the core DEGs into three different modules, each of them contributing to salt response in a unique metabolic pathway. Gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses highlighted key biological processes and metabolic pathways involved in the salt response. We identified important novel hub genes encoding proteins of different families including CAM, DUF630/632, DUF581, CHL27, PP2-13, LEA4-5, and transcription factors, which could be functionally characterized using reverse genetic experiments. This novel repertoire of candidate genes related to salt response in rice will be useful for engineering salt tolerant varieties.
PMID: 31533315
J Ethnopharmacol , IF:3.69 , 2019 Sep , V241 : P111905 doi: 10.1016/j.jep.2019.111905
Network pharmacology-based analysis on bioactive anti-diabetic compounds in Potentilla discolor bunge.
Institute of Life Sciences, Jiangsu University, Zhenjiang, Jiangsu, 212013, China. Electronic address: nnw@ujs.edu.cn.; Institute of Life Sciences, Jiangsu University, Zhenjiang, Jiangsu, 212013, China. Electronic address: feifzhu@ujs.edu.cn.; Institute of Life Sciences, Jiangsu University, Zhenjiang, Jiangsu, 212013, China. Electronic address: 1185255941@qq.com.; Institute of Life Sciences, Jiangsu University, Zhenjiang, Jiangsu, 212013, China. Electronic address: tulip_lipeng@163.com.; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York City, NY, 10029, USA. Electronic address: boymin2010@163.com.; Institute of Life Sciences, Jiangsu University, Zhenjiang, Jiangsu, 212013, China. Electronic address: hchxia@ujs.edu.cn.; Institute of Life Sciences, Jiangsu University, Zhenjiang, Jiangsu, 212013, China. Electronic address: oochen@ujs.edu.cn.; Institute of Life Sciences, Jiangsu University, Zhenjiang, Jiangsu, 212013, China. Electronic address: yuanxiaoyi130704@163.com.; Institute of Life Sciences, Jiangsu University, Zhenjiang, Jiangsu, 212013, China. Electronic address: 1326056784@qq.com.; Institute of Life Sciences, Jiangsu University, Zhenjiang, Jiangsu, 212013, China. Electronic address: kpchen@ujs.edu.cn.
ETHNOPHARMACOLOGICAL RELEVANCE: Potentilla discolor Bunge (PDB) is a commonly used herbal for alleviating diabetes mellitus and its complications. Although accumulating evidences show the anti-diabetic efficacy of PDB, the vital anti-diabetic compounds and their functional targets remain elusive. AIM OF THE STUDY: To investigate the anti-diabetic ingredients and their functional mechanisms in PDB, gas chromatograph-mass spectrometry analysis was performed on PDB extract and 21 were testified as anti-diabetic compounds. MATERIALS AND METHODS: Subsequently their potential protein targets were also identified. The bioinformatics analysis was implemented by network pharmacology-based approaches. STRING analysis was performed to reveal enrichment of these target proteins, protein-protein interactions, pathways and related diseases. Cytoscape was used to determine the potential protein targets for these components in PDB, indicating that 21 anti-diabetic compounds in PDB regulate 33 diabetes-related proteins in 28 signal pathways and involve 21 kinds of diabetes-related diseases. Among the 21 potential anti-diabetic components predicted by network analysis, tricetin was firstly experimentally validated at the molecular and cellular level. RESULTS: Results indicated that this active small-molecule compound may have beneficial effects on improving glucose uptake. CONCLUSIONS: We envisage that network analysis will be useful in screening bioactive compounds of medicinal plants.
PMID: 31022565
Sensors (Basel) , IF:3.275 , 2019 Sep , V19 (18) doi: 10.3390/s19183886
Heuristic Approaches for Enhancing the Privacy of the Leader in IoT Networks.
School of Cyberspace, Hangzhou Dianzi University, Hangzhou 310018, Zhejiang, China. 171270004@hdu.edu.cn.; School of Cyberspace, Hangzhou Dianzi University, Hangzhou 310018, Zhejiang, China. wugh@hdu.edu.cn.; School of Cyberspace, Hangzhou Dianzi University, Hangzhou 310018, Zhejiang, China. shuaijinguo@aliyun.com.; School of Cyberspace, Hangzhou Dianzi University, Hangzhou 310018, Zhejiang, China. zhangzhen@hud.edu.cn.; School of Cyberspace, Hangzhou Dianzi University, Hangzhou 310018, Zhejiang, China. wangzhen@hdu.edu.cn.; School of Cyberspace, Hangzhou Dianzi University, Hangzhou 310018, Zhejiang, China. renyz@hdu.edu.cn.
The privacy and security of the Internet of Things (IoT) are emerging as popular issues in the IoT. At present, there exist several pieces of research on network analysis on the IoT network, and malicious network analysis may threaten the privacy and security of the leader in the IoT networks. With this in mind, we focus on how to avoid malicious network analysis by modifying the topology of the IoT network and we choose closeness centrality as the network analysis tool. This paper makes three key contributions toward this problem: (1) An optimization problem of removing k edges to minimize (maximize) the closeness value (rank) of the leader; (2) A greedy (greedy and simulated annealing) algorithm to solve the closeness value (rank) case of the proposed optimization problem in polynomial time; and (3)UpdateCloseness (FastTopRank)-algorithm for computing closeness value (rank) efficiently. Experimental results prove the efficiency of our pruning algorithms and show that our heuristic algorithms can obtain accurate solutions compared with the optimal solution (the approximation ratio in the worst case is 0.85) and outperform the solutions obtained by other baseline algorithms (e.g., choose k edges with the highest degree sum).
PMID: 31505866
Prog Biophys Mol Biol , IF:2.175 , 2019 Sep , V146 : P37-49 doi: 10.1016/j.pbiomolbio.2018.11.006
Insights into ABA-mediated regulation of guard cell primary metabolism revealed by systems biology approaches.
Max-Planck-Institut fur Molekulare Pflanzenphysiologie, Potsdam, Golm, 14476, Germany. Electronic address: Yoshida@mpimp-golm.mpg.de.; Departamento de Biologia Vegetal, Universidade Federal de Lavras, Lavras, Minas Gerais, 62700-000, Brazil.; Max-Planck-Institut fur Molekulare Pflanzenphysiologie, Potsdam, Golm, 14476, Germany; Max-Planck Partner Group at the Departamento de Biologia Vegetal, Universidade Federal de Vicosa, Vicosa, Minas Gerais, 36570-900, Brazil.; Max-Planck Partner Group at the Departamento de Biologia Vegetal, Universidade Federal de Vicosa, Vicosa, Minas Gerais, 36570-900, Brazil.; Max-Planck-Institut fur Molekulare Pflanzenphysiologie, Potsdam, Golm, 14476, Germany.; Departamento de Bioquimica e Biologia Molecular, Universidade Federal do Ceara, Fortaleza, Ceara, 60451-970, Brazil. Electronic address: daloso@ufc.br.
Despite the fact that guard cell abscisic acid (ABA) signalling pathway is well documented, our understanding concerning how and to which extent ABA regulates guard cell metabolism remains fragmentary. Here we have adopted different systems approaches to investigate how ABA modulates guard cell central metabolism by providing genes that are possibly ABA-regulated. By using previous published Arabidopsis guard cell transcript profiling data, we carried out an extensive co-expression network analysis using ABA-related genes and those related to the metabolism and transport of sugars, starch and organic acids. Next, we investigated the presence of ABA responsive elements (ABRE) in the promoter of genes that are highly expressed in guard cells, responsive to ABA and co-expressed with ABA-related genes. Together, these analyses indicated that 44 genes are likely regulated by ABA and 8 of them are highly expressed in guard cells in both the presence and absence of ABA, including genes of the tricarboxylic acid cycle and those related to sucrose and hexose transport and metabolism. It seems likely that ABA may modulate both sucrose transport through guard cell plasma membrane and sucrose metabolism within guard cells. In this context, genes associated with sucrose synthase, sucrose phosphate synthase, trehalose-6-phosphate, invertase, UDP-glucose epimerase/pyrophosphorylase and different sugar transporters contain ABRE in their promoter and are thus possibly ABA regulated. Although validation experiments are required, our study highlights the importance of systems biology approaches to drive new hypothesis and to unravel genes and pathways that are regulated by ABA in guard cells.
PMID: 30447225
Bot Stud , IF:2.163 , 2019 Sep , V60 (1) : P22 doi: 10.1186/s40529-019-0268-8
Construction of gene causal regulatory networks using microarray data with the coefficient of intrinsic dependence.
Department of Agronomy, National Taiwan University, Taipei, 106, Taiwan. lyliu@ntu.edu.tw.; Department of Agronomy, National Taiwan University, Taipei, 106, Taiwan.; Department of Horticulture and Landscape Architecture, National Taiwan University, Taipei, 106, Taiwan.
BACKGROUND: In the past two decades, biologists have been able to identify the gene signatures associated with various phenotypes through the monitoring of gene expressions with high-throughput biotechnologies. These gene signatures have in turn been successfully applied to drug development, disease prevention, crop improvement, etc. However, ignoring the interactions among genes has weakened the predictive power of gene signatures in practical applications. Gene regulatory networks, in which genes are represented by nodes and the associations between genes are represented by edges, are typically constructed to analyze and visualize such gene interactions. More specifically, the present study sought to measure gene-gene associations by using the coefficient of intrinsic dependence (CID) to capture more nonlinear as well as cause-effect gene relationships. RESULTS: A stepwise procedure using the CID along with the partial coefficient of intrinsic dependence (pCID) was demonstrated for the rebuilding of simulated networks and the well-known CBF-COR pathway under cold stress using Arabidopsis microarray data. The procedure was also applied to the construction of bHLH gene regulatory pathways under abiotic stresses using rice microarray data, in which OsbHLH104, a putative phytochrome-interacting factor (OsPIF14), and OsbHLH060, a positive regulator of iron homeostasis (OsPRI1) were inferred as the most affiliated genes. The inferred regulatory pathways were verified through literature reviews. CONCLUSIONS: The proposed method can efficiently decipher gene regulatory pathways and may assist in achieving higher predictive power in practical applications. The lack of any mention in the literature of some of the regulatory event may have been due to the high complexity of the regulatory systems in the plant transcription, a possibility which could potentially be confirmed in the near future given ongoing rapid developments in bio-technology.
PMID: 31512008
Heliyon , 2019 Sep , V5 (9) : Pe02347 doi: 10.1016/j.heliyon.2019.e02347
Dynamic ecological system analysis: A holistic analysis of compartmental systems.
Department of Mathematics, University of Georgia, Athens, GA 30602, USA.
This article develops a new mathematical method for holistic analysis of nonlinear dynamic compartmental systems in the context of ecology. The method is based on the novel dynamic system and subsystem partitioning methodologies through which compartmental systems are decomposed to the utmost level. The dynamic system and subsystem partitioning enable tracking the evolution of the initial stocks, environmental inputs, and intercompartmental system flows, as well as the associated storages derived from these stocks, inputs, and flows individually and separately within the system. Moreover, the transient and the dynamic direct, indirect, acyclic, cycling, and transfer (diact) flows and associated storages transmitted along a given flow path or from one compartment, directly or indirectly, to any other are analytically characterized, systematically classified, and mathematically formulated. Further, the article develops a dynamic technique based on the diact transactions for the quantitative classification of interspecific interactions and the determination of their strength within food webs. Major concepts and quantities of the current static network analyses are also extended to nonlinear dynamic settings and integrated with the proposed dynamic measures and indices within the proposed unifying mathematical framework. Therefore, the proposed methodology enables a holistic view and analysis of ecological systems. We consider that this methodology brings a novel complex system theory to the service of urgent and challenging environmental problems of the day and has the potential to lead the way to a more formalistic ecological science.
PMID: 31517112
J Intell , 2019 Sep , V7 (3) doi: 10.3390/jintelligence7030021
Psychometric Network Analysis of the Hungarian WAIS.
Department of Psychology, Claremont Graduate University, Claremont 91711, CA, USA. christopher.schmank@cgu.edu.; Department of Psychology, Claremont Graduate University, Claremont 91711, CA, USA. sara.goring@cgu.edu.; Institute of Psychology, ELTE Eotvos Lorand University of Applied Sciences, 1053 Budapest, Hungary. kristof340@googlemail.com.; Department of Psychology, Claremont Graduate University, Claremont 91711, CA, USA. andrew.conway@cgu.edu.
The positive manifold-the finding that cognitive ability measures demonstrate positive correlations with one another-has led to models of intelligence that include a general cognitive ability or general intelligence (g). This view has been reinforced using factor analysis and reflective, higher-order latent variable models. However, a new theory of intelligence, Process Overlap Theory (POT), posits that g is not a psychological attribute but an index of cognitive abilities that results from an interconnected network of cognitive processes. These competing theories of intelligence are compared using two different statistical modeling techniques: (a) latent variable modeling and (b) psychometric network analysis. Network models display partial correlations between pairs of observed variables that demonstrate direct relationships among observations. Secondary data analysis was conducted using the Hungarian Wechsler Adult Intelligence Scale Fourth Edition (H-WAIS-IV). The underlying structure of the H-WAIS-IV was first assessed using confirmatory factor analysis assuming a reflective, higher-order model and then reanalyzed using psychometric network analysis. The compatibility (or lack thereof) of these theoretical accounts of intelligence with the data are discussed.
PMID: 31505834
Behav Res Ther , 2019 Sep , V120 : P103419 doi: 10.1016/j.brat.2019.103419
Exploring the psychology of suicidal ideation: A theory driven network analysis.
Netherlands Institute for Health Services Research, Otterstraat, 118-124, Utrecht, the Netherlands. Electronic address: d.debeurs@nivel.nl.; Leiden University, Clinical Psychology, Netherlands.; Suicidal Behaviour Research Laboratory, Institute of Health & Wellbeing, University of Glasgow, UK.; School of Psychology, University of Leeds, UK.; School of Psychology, University of Nottingham, UK.; Division of Psychology, School of Natural Sciences, University of Stirling, UK.
Two leading theories within the field of suicide prevention are the interpersonal psychological theory of suicidal behaviour (IPT) and the integrated motivational-volitional (IMV) model. The IPT posits that suicidal thoughts emerge from high levels of perceived burdensomeness and thwarted belongingness. The IMV model is a multivariate framework that conceptualizes defeat and entrapment as key drivers of suicide ideation. We applied network analysis to cross-sectional data collected as part of the Scottish Wellbeing Study, in which a nationally representative sample of 3508 young adults (18-34 years) completed a battery of psychological measures. Network analysis can help us to understand how the different theoretical components interact and how they relate to suicide ideation. Within a network that included only the core factors from both models, internal entrapment and perceived burdensomeness were most strongly related to suicide ideation. The core constructs defeat, external entrapment and thwarted belonginess were mainly related to other factors than suicide ideation. Within the network of all available psychological factors, 12 of the 20 factors were uniquely related to suicide ideation, with perceived burdensomeness, internal entrapment, depressive symptoms and history of suicide ideation explaining the most variance. None of the factors was isolated, and we identified four larger clusters: mental wellbeing, interpersonal needs, personality, and suicide-related factors. Overall, the results suggest that relationships between suicide ideation and psychological risk factors are complex, with some factors contributing direct risk, and others having indirect impact.
PMID: 31238299