New Phytol , IF:8.512 , 2021 Apr , V230 (2) : P612-628 doi: 10.1111/nph.17179
Growth-regulating factor 5 (GRF5)-mediated gene regulatory network promotes leaf growth and expansion in poplar.
Beijing Advanced Innovation Center for Tree Breeding by Molecular Design, Beijing Forestry University, Beijing, 100083, China.; State Key Laboratory of Tree Genetics and Breeding, Chinese Academy of Forestry, Beijing, 100091, China.; State Key Laboratory of Tree Genetics and Breeding, Northeast Forestry University, Harbin, Heilongjiang, 150040, China.; State Key Laboratory for Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, Jiangsu, 210095, China.; College of Forest Resources and Environmental Science, Michigan Technological University, Houghton, MI, 49931, USA.
Although polyploid plants have larger leaves than their diploid counterparts, the molecular mechanisms underlying this difference (or trait) remain elusive. Differentially expressed genes (DEGs) between triploid and full-sib diploid poplar trees were identified from two transcriptomic data sets followed by a gene association study among DEGs to identify key leaf growth regulators. Yeast one-hybrid system, electrophoretic mobility shift assay, and dual-luciferase assay were employed to substantiate that PpnGRF5-1 directly regulated PpnCKX1. The interactions between PpnGRF5-1 and growth-regulating factor (GRF)-interacting factors (GIFs) were experimentally validated and a multilayered hierarchical regulatory network (ML-hGRN)-mediated by PpnGRF5-1 was constructed with top-down graphic Gaussian model (GGM) algorithm by combining RNA-sequencing data from its overexpression lines and DAP-sequencing data. PpnGRF5-1 is a negative regulator of PpnCKX1. Overexpression of PpnGRF5-1 in diploid transgenic lines resulted in larger leaves resembling those of triploids, and significantly increased zeatin and isopentenyladenine in the apical buds and third leaves. PpnGRF5-1 also interacted with GIFs to increase its regulatory diversity and capacity. An ML-hGRN-mediated by PpnGRF5-1 was obtained and could largely elucidate larger leaves. PpnGRF5-1 and the ML-hGRN-mediated by PpnGRF5-1 were underlying the leaf growth and development.
PMID: 33423287
Crit Rev Biotechnol , IF:8.108 , 2021 Apr : P1-24 doi: 10.1080/07388551.2021.1898332
Can omics deliver temperature resilient ready-to-grow crops?
Key Lab of Biology and Genetic Improvement of Oil Crops, Oil Crops Research Institute, Chinese Academy of Agricultural Sciences (CAAS), Wuhan, China.; State Key Laboratory of Rice Biology, China National Rice Research Institute, Chinese Academy of Agricultural Science (CAAS), Hangzhou, China.; Center of Excellence in Genomics & Systems Biology, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, India.; The UWA Institute of Agriculture, The University of Western Australia, Perth, Australia.
Plants are extensively well-thought-out as the main source for nourishing natural life on earth. In the natural environment, plants have to face several stresses, mainly heat stress (HS), chilling stress (CS) and freezing stress (FS) due to adverse climate fluctuations. These stresses are considered as a major threat for sustainable agriculture by hindering plant growth and development, causing damage, ultimately leading to yield losses worldwide and counteracting to achieve the goal of "zero hunger" proposed by the Food and Agricultural Organization (FAO) of the United Nations. Notably, this is primarily because of the numerous inequities happening at the cellular, molecular and/or physiological levels, especially during plant developmental stages under temperature stress. Plants counter to temperature stress via a complex phenomenon including variations at different developmental stages that comprise modifications in physiological and biochemical processes, gene expression and differences in the levels of metabolites and proteins. During the last decade, omics approaches have revolutionized how plant biologists explore stress-responsive mechanisms and pathways, driven by current scientific developments. However, investigations are still required to explore numerous features of temperature stress responses in plants to create a complete idea in the arena of stress signaling. Therefore, this review highlights the recent advances in the utilization of omics approaches to understand stress adaptation and tolerance mechanisms. Additionally, how to overcome persisting knowledge gaps. Shortly, the combination of integrated omics, genome editing, and speed breeding can revolutionize modern agricultural production to feed millions worldwide in order to accomplish the goal of "zero hunger."
PMID: 33827346
Sci Total Environ , IF:6.551 , 2021 Apr , V766 : P142609 doi: 10.1016/j.scitotenv.2020.142609
Microbial community structure in the river sediments from upstream of Guanting Reservoir: Potential impacts of reclaimed water recharge.
College of Water Resources and Civil Engineering, China Agricultural University, Beijing, China.; Department of Water Ecology and Environment, China Institute of Water Resources and Hydropower Research, Beijing 100038, China. Electronic address: zhaoxiaocunforever@163.com.; Department of Water Ecology and Environment, China Institute of Water Resources and Hydropower Research, Beijing 100038, China.; College of Water Resources and Civil Engineering, China Agricultural University, Beijing, China. Electronic address: xiaozhao88@cau.edu.cn.
This work systematically investigated the microbial community structure in the river sediments from upstream of Guanting Reservoir, Beijing, China. A total of 6 wastewater treatment plants (WWTPs) locate along the main rivers connected to the reservoir. Water and sediment samples were collected at sites near the effluents of WWTPs (regarded as W groups) or at the upstream/downstream rivers (R groups) to reveal the roles of the reclaimed water recharge. Multivariate techniques including typical statistical analysis, redundancy analysis (RDA), nonmetric multidimensional scaling analysis, and molecular ecological network analysis were used to evaluate the results and their relationships. The representative C/N/P water parameters and concentrations of target organic contaminants kept stable for W and R sites, while the microbial community parameters varied greatly for two groups. The microbial population at W sites were higher but with a lower biological diversity (with a lower Shannon index) than that at R sites, indicating WWTPs greatly altered the microbial community structure at the local reach. RDA results revealed that total organic carbon (TOC) and organophosphorus pesticides (OPPs) were two dominant factors affecting the function and composition of microbial communities at the phylum level. The network analysis revealed that the microbes with the most interactions mainly from R sites and they had closer relationships with each other.
PMID: 33069478
Cell Biol Toxicol , IF:6.284 , 2021 Apr doi: 10.1007/s10565-021-09599-9
Pyrrolizidine alkaloids cause cell cycle and DNA damage repair defects as analyzed by transcriptomics in cytochrome P450 3A4-overexpressing HepG2 clone 9 cells.
Department of Pharmaceutical Biology, Institute of Pharmaceutical and Biomedical Science, Johannes Gutenberg University, Mainz, Germany.; Division of Cancer Genome Research, German Cancer Research Center (DKFZ), German Cancer Consortium (DKTK), National Center for Tumor Diseases (NCT), Heidelberg, Germany.; Institute of Biotechnology, Brandenburg University of Technology Cottbus-Senftenberg, Senftenberg, Germany.; Department of Pharmaceutical Biology, Institute of Pharmaceutical and Biomedical Science, Johannes Gutenberg University, Mainz, Germany. efferth@uni-mainz.de.
Pyrrolizidine alkaloids (PAs) are a large group of highly toxic chemical compounds, which are found as cross-contaminants in numerous food products (e.g., honey), dietary supplements, herbal teas, and pharmaceutical herbal medicines. PA contaminations are responsible for serious hepatotoxicity and hepatocarcinogenesis. Health authorities have to set legal limit values to guarantee the safe consumption of plant-based nutritional and medical products without harmful health. Toxicological and chemical analytical methods are conventionally applied to determine legally permitted limit values for PAs. In the present investigation, we applied a highly sensitive transcriptomic approach to investigate the effect of low concentrations of five PAs (lasiocarpine, riddelliine, lycopsamine, echimidine, and monocrotaline) on human cytochrome P450 3A4-overexpressing HepG2 clone 9 hepatocytes. The transcriptomic profiling of deregulated gene expression indicated that the PAs disrupted important signaling pathways related to cell cycle regulation and DNA damage repair in the transfected hepatocytes, which may explain the carcinogenic PA effects. As PAs affected the expression of genes that involved in cell cycle regulation, we applied flow cytometric cell cycle analyses to verify the transcriptomic data. Interestingly, PA treatment led to an arrest in the S phase of the cell cycle, and this effect was more pronounced with more toxic PAs (i.e., lasiocarpine and riddelliine) than with the less toxic monocrotaline. Using immunofluorescence, high fractions of cells were detected with chromosome congression defects upon PA treatment, indicating mitotic failure. In conclusion, the tested PAs revealed threshold concentrations, above which crucial signaling pathways were deregulated resulting in cell damage and carcinogenesis. Cell cycle arrest and DNA damage repair point to the mutagenicity of PAs. The disturbance of chromosome congression is a novel mechanism of Pas, which may also contribute to PA-mediated carcinogenesis. Transcriptomic, cell cycle, and immunofluorescence analyses should supplement the standard techniques in toxicology to unravel the biological effects of PA exposure in liver cells as the primary target during metabolization of PAs.
PMID: 33884520
Plant J , IF:6.141 , 2021 Apr , V106 (1) : P23-40 doi: 10.1111/tpj.15144
Acclimation in plants - the Green Hub consortium.
Plant Molecular Biology, Faculty of Biology, Ludwig-Maximilians-Universitat Munchen, Planegg-Martinsried, 82152, Germany.; Plant Evolutionary Cell Biology, Faculty of Biology, Ludwig-Maximilians-Universitat Munchen, Planegg-Martinsried, Munich, 82152, Germany.; Plant Physiology, Department of Biology, Technische Universitat Kaiserslautern, Kaiserslautern, 67663, Germany.; Molecular Genetics, Institute of Biology, Humboldt-Universitat zu Berlin, Berlin, 10115, Germany.; Central Metabolism, Max-Planck-Institut fur Molekulare Pflanzenphysiologie, Potsdam-Golm, 14476, Germany.; Plant Metabolism, Faculty of Biology, Ludwig-Maximilians-Universitat Munchen, Planegg-Martinsried, Munich, 82152, Germany.; Plant Physiology, Institute of Biology, Humboldt-Universitat zu Berlin, Berlin, 10115, Germany.; Plant Cell and Molecular Biology, Institute of Biology, Humboldt-Universitat zu Berlin, Berlin, 10115, Germany.; Theoretical Biophysics, Institute of Biology, Humboldt-Universitat zu Berlin, Berlin, 10115, Germany.; Computational Systems Biology, Department of Biology, Technische Universitat Kaiserslautern, Kaiserslautern, 67663, Germany.; Molecular Plant Science, Faculty of Biology, Ludwig-Maximilians-Universitat Munchen, Planegg-Martinsried, Munich, 82152, Germany.; Physiology of Plant Organelles, Institute of Biology, Humboldt-Universitat zu Berlin, Berlin, 10115, Germany.; Molecular Biotechnology & Systems Biology, Department of Biology, Technische Universitat Kaiserslautern, Kaiserslautern, 67663, Germany.; Plant Biochemistry and Physiology, Faculty of Biology, Ludwig-Maximilians-Universitat Munchen, Planegg-Martinsried, Munich, 82152, Germany.; Molecular Genetics of Eukaryotes, Department of Biology, Technische Universitat Kaiserslautern, Kaiserslautern, 67663, Germany.; Translational Regulation in Plants, Max-Planck-Institut fur Molekulare Pflanzenphysiologie, Potsdam-Golm, 14476, Germany.
Acclimation is the capacity to adapt to environmental changes within the lifetime of an individual. This ability allows plants to cope with the continuous variation in ambient conditions to which they are exposed as sessile organisms. Because environmental changes and extremes are becoming even more pronounced due to the current period of climate change, enhancing the efficacy of plant acclimation is a promising strategy for mitigating the consequences of global warming on crop yields. At the cellular level, the chloroplast plays a central role in many acclimation responses, acting both as a sensor of environmental change and as a target of cellular acclimation responses. In this Perspective article, we outline the activities of the Green Hub consortium funded by the German Science Foundation. The main aim of this research collaboration is to understand and strategically modify the cellular networks that mediate plant acclimation to adverse environments, employing Arabidopsis, tobacco (Nicotiana tabacum) and Chlamydomonas as model organisms. These efforts will contribute to 'smart breeding' methods designed to create crop plants with improved acclimation properties. To this end, the model oilseed crop Camelina sativa is being used to test modulators of acclimation for their potential to enhance crop yield under adverse environmental conditions. Here we highlight the current state of research on the role of gene expression, metabolism and signalling in acclimation, with a focus on chloroplast-related processes. In addition, further approaches to uncovering acclimation mechanisms derived from systems and computational biology, as well as adaptive laboratory evolution with photosynthetic microbes, are highlighted.
PMID: 33368770
J Integr Plant Biol , IF:4.885 , 2021 Apr , V63 (4) : P613-627 doi: 10.1111/jipb.13069
Maize endosperm development.
State Key Laboratory of Plant Physiology and Biochemistry, National Maize Improvement Center, Beijing Key Laboratory of Crop Genetic Improvement, Joint International Research Laboratory of Crop Molecular Breeding, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China.; Shanghai Key Laboratory of Bio-Energy Crops, Plant Science Center, School of Life Sciences, Shanghai University, Shanghai, 200444, China.
Recent breakthroughs in transcriptome analysis and gene characterization have provided valuable resources and information about the maize endosperm developmental program. The high temporal-resolution transcriptome analysis has yielded unprecedented access to information about the genetic control of seed development. Detailed spatial transcriptome analysis using laser-capture microdissection has revealed the expression patterns of specific populations of genes in the four major endosperm compartments: the basal endosperm transfer layer (BETL), aleurone layer (AL), starchy endosperm (SE), and embryo-surrounding region (ESR). Although the overall picture of the transcriptional regulatory network of endosperm development remains fragmentary, there have been some exciting advances, such as the identification of OPAQUE11 (O11) as a central hub of the maize endosperm regulatory network connecting endosperm development, nutrient metabolism, and stress responses, and the discovery that the endosperm adjacent to scutellum (EAS) serves as a dynamic interface for endosperm-embryo crosstalk. In addition, several genes that function in BETL development, AL differentiation, and the endosperm cell cycle have been identified, such as ZmSWEET4c, Thk1, and Dek15, respectively. Here, we focus on current advances in understanding the molecular factors involved in BETL, AL, SE, ESR, and EAS development, including the specific transcriptional regulatory networks that function in each compartment during endosperm development.
PMID: 33448626
Mol Plant Pathol , IF:4.326 , 2021 Apr , V22 (4) : P465-479 doi: 10.1111/mpp.13040
Analysis of the transcriptomic, metabolomic, and gene regulatory responses to Puccinia sorghi in maize.
Department of Entomology and Plant Pathology, NC State University, Raleigh, North Carolina, USA.; Department of Plant and Microbial Biology, NC State University, Raleigh, North Carolina, USA.; Research Institute of Agriculture and Life Sciences, College of Agriculture and Life Sciences, Seoul National University, Seoul, Republic of Korea.; Chemistry Research Unit, Department of Agriculture-Agricultural Research Service (USDA-ARS), Center for Medical, Agricultural, and Veterinary Entomology, Gainesville, Florida, USA.; The Key Laboratory of Plant Development and Environmental Adaptation Biology, Ministry of Education, School of Life Sciences, Shandong University, Qingdao, China.; Plant Science Research Unit USDA-ARS, Raleigh, North Carolina, USA.
Common rust, caused by Puccinia sorghi, is a widespread and destructive disease of maize. The Rp1-D gene confers resistance to the P. sorghi IN2 isolate, mediating a hypersensitive cell death response (HR). To identify differentially expressed genes (DEGs) and metabolites associated with the compatible (susceptible) interaction and with Rp1-D-mediated resistance in maize, we performed transcriptomics and targeted metabolome analyses of P. sorghi IN2-infected leaves from the near-isogenic lines H95 and H95:Rp1-D, which differed for the presence of Rp1-D. We observed up-regulation of genes involved in the defence response and secondary metabolism, including the phenylpropanoid, flavonoid, and terpenoid pathways. Metabolome analyses confirmed that intermediates from several transcriptionally up-regulated pathways accumulated during the defence response. We identified a common response in H95:Rp1-D and H95 with an additional H95:Rp1-D-specific resistance response observed at early time points at both transcriptional and metabolic levels. To better understand the mechanisms underlying Rp1-D-mediated resistance, we inferred gene regulatory networks occurring in response to P. sorghi infection. A number of transcription factors including WRKY53, BHLH124, NKD1, BZIP84, and MYB100 were identified as potentially important signalling hubs in the resistance-specific response. Overall, this study provides a novel and multifaceted understanding of the maize susceptible and resistance-specific responses to P. sorghi.
PMID: 33641256
Plant Physiol Biochem , IF:3.72 , 2021 Apr , V161 : P248-258 doi: 10.1016/j.plaphy.2021.02.016
Rubisco activase A (RcaA) is a central node in overlapping gene network of drought and salinity in Barley (Hordeum vulgare L.) and may contribute to combined stress tolerance.
Department of Crop Production and Plant Breeding, Shiraz University, Shiraz, Iran.; Department of Plant Pathology, The Ohio State University, OH, 43210, USA.; School of Bioscience, University of Skovde, Skovde, Sweden.; Department of Agriculture and Natural Resources, Higher Education Center of Eghlid, Eghlid, Iran. Electronic address: shamloo.r@gmail.com.
Co-occurrence of abiotic stresses, especially drought and salinity, is a natural phenomenon in field conditions and is worse for crop production than any single stress. Nowadays, rigorous methods of meta-analysis and systems biology have made it possible to perform cross-study comparisons of single stress experiments, which can uncover main overlapping mechanisms underlying tolerance to combined stress. In this study, a meta-analysis of RNA-Seq data was conducted to obtain the overlapping gene network of drought and salinity stresses in barley (Hordeum vulgare L.), which identified Rubisco activase A (RcaA) as a hub gene in the dual-stress response. Thereafter, a greenhouse experiment was carried out using two barley genotypes with different abiotic stress tolerance and evaluated several physiochemical properties as well as the expression profile and protein activity of RcaA. Finally, machine learning analysis was applied to uncover relationships among combined stress tolerance and evaluated properties. We identified 441 genes which were differentially expressed under both drought and salinity stress. Results revealed that the photosynthesis pathway and, in particular, the RcaA gene are major components of the dual-stress responsive transcriptome. Comparative physiochemical and molecular evaluations further confirmed that enhanced photosynthesis capability, mainly through regulation of RcaA expression and activity as well as accumulation of proline content, have a significant association with combined drought and salinity stress tolerance in barley. Overall, our results clarify the importance of RcaA in combined stress tolerance and may provide new insights for future investigations.
PMID: 33652257
Expert Rev Proteomics , IF:3.614 , 2021 Apr : P1-11 doi: 10.1080/14789450.2021.1910028
Proteomics and plant biology: contributions to date and a look towards the next decade.
Dpt. Biochemistry and Molecular Biology, Agroforestry and Plant Biochemistry, Proteomics and Systems Biology, ETSIAM, University of Cordoba, Cordoba , Spain.
INTRODUCTION: This review presents the view of the author, that is opinionable and even speculative, on the field of proteomics, its application to plant biology knowledge, and translation to biotechnology. Written in a more academic than scientific style, it is based on past original and review articles by the author s group, and those published by leading scientists in the last two years. AREAS COVERED: Starting with a general definition and references to historical milestones, it covers sections devoted to the different platforms employed, the plant biology discourse in the protein language, challenges and future prospects, ending with the author opinion. EXPERT OPINION: In 25 years, five proteomics platform generations have appeared. We are now moving from proteomics to Systems Biology. While feasible with model organisms, proteomics of orphan species remains challenging. Proteomics, even in its simplest approach, sheds light on plant biological processes, central dogma, and molecular bases of phenotypes of interest, and it can be translated to areas such as food traceability and allergen detection. Proteomics should be validated and optimized to each experimental system, objectives, and hypothesis. It has limitations, artifacts, and biases. We should not blindly accept proteomics data and just create a list of proteins, networks, and avoid speculative biological interpretations. From the hundred to thousand proteins identified and quantified, it is important to obtain a focus and validate some of them, otherwise it is merely. We are starting to have the protein pieces, so let, from now, build the proteomics and biological puzzle.
PMID: 33770454
BMC Genomics , IF:3.594 , 2021 Apr , V22 (1) : P236 doi: 10.1186/s12864-021-07510-8
Gene co-expression network analysis reveals key pathways and hub genes in Chinese cabbage (Brassica rapa L.) during vernalization.
Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, 100081, China.; College of Horticulture, Vegetable Genetics and Breeding Laboratory, Anhui Agricultural University, Changjiang West Road, NO.130, Hefei, 230036, Anhui, China.; Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, 100081, China. shujiang_zhang@163.com.
BACKGROUND: Vernalization is a type of low temperature stress used to promote rapid bolting and flowering in plants. Although rapid bolting and flowering promote the reproduction of Chinese cabbages (Brassica rapa L. ssp. pekinensis), this process causes their commercial value to decline. Clarifying the mechanisms of vernalization is essential for its further application. We performed RNA sequencing of gradient-vernalization in order to explore the reasons for the different bolting process of two Chinese cabbage accessions during vernalization. RESULTS: There was considerable variation in gene expression between different-bolting Chinese cabbage accessions during vernalization. Comparative transcriptome analysis and weighted gene co-expression network analysis (WGCNA) were performed for different-bolting Chinese cabbage during different vernalization periods. The biological function analysis and hub gene annotation of highly relevant modules revealed that shoot system morphogenesis and polysaccharide and sugar metabolism caused early-bolting 'XBJ' to bolt and flower faster; chitin, ABA and ethylene-activated signaling pathways were enriched in late-bolting 'JWW'; and leaf senescence and carbohydrate metabolism enrichment were found in the two Chinese cabbage-related modules, indicating that these pathways may be related to bolting and flowering. The high connectivity of hub genes regulated vernalization, including MTHFR2, CPRD49, AAP8, endoglucanase 10, BXLs, GATLs, and WRKYs. Additionally, five genes related to flower development, BBX32 (binds to the FT promoter), SUS1 (increases FT expression), TSF (the closest homologue of FT), PAO and NAC029 (plays a role in leaf senescence), were expressed in the two Chinese cabbage accessions. CONCLUSION: The present work provides a comprehensive overview of vernalization-related gene networks in two different-bolting Chinese cabbages during vernalization. In addition, the candidate pathways and hub genes related to vernalization identified here will serve as a reference for breeders in the regulation of Chinese cabbage production.
PMID: 33823810
Plant Mol Biol , IF:3.302 , 2021 Apr , V105 (6) : P655-684 doi: 10.1007/s11103-021-01121-3
Genome-wide identification and characterization of long non-coding RNAs involved in flag leaf senescence of rice.
Key Laboratory of Crop Physiology, Ecology and Genetic Breeding (Jiangxi Agricultural University), Ministry of Education of the P.R. China, Nanchang, 330045, Jiangxi Province, China.; Key Laboratory of Agriculture Responding to Climate Change (Jiangxi Agricultural University), Nanchang City, 330045, Jiangxi Province, China.; Southern Regional Collaborative Innovation Center for Grain and Oil Crops in China, Changsha, 410128, Hunan Province, China.; Key Laboratory of Crop Physiology, Ecology and Genetic Breeding (Jiangxi Agricultural University), Ministry of Education of the P.R. China, Nanchang, 330045, Jiangxi Province, China. yjhuang_cn@126.com.; Key Laboratory of Agriculture Responding to Climate Change (Jiangxi Agricultural University), Nanchang City, 330045, Jiangxi Province, China. yjhuang_cn@126.com.; Southern Regional Collaborative Innovation Center for Grain and Oil Crops in China, Changsha, 410128, Hunan Province, China. yjhuang_cn@126.com.; Key Laboratory of Crop Physiology, Ecology and Genetic Breeding (Jiangxi Agricultural University), Ministry of Education of the P.R. China, Nanchang, 330045, Jiangxi Province, China. zhaohai_wang@163.com.; Key Laboratory of Agriculture Responding to Climate Change (Jiangxi Agricultural University), Nanchang City, 330045, Jiangxi Province, China. zhaohai_wang@163.com.; Southern Regional Collaborative Innovation Center for Grain and Oil Crops in China, Changsha, 410128, Hunan Province, China. zhaohai_wang@163.com.
KEY MESSAGE: This study showed the systematic identification of long non-coding RNAs (lncRNAs) involving in flag leaf senescence of rice, providing the possible lncRNA-mRNA regulatory relationships and lncRNA-miRNA-mRNA ceRNA networks during leaf senescence. LncRNAs have been reported to play crucial roles in diverse biological processes. However, no systematic identification of lncRNAs associated with leaf senescence in plants has been studied. In this study, a genome-wide high throughput sequencing analysis was performed using rice flag leaves developing from normal to senescence. A total of 3953 lncRNAs and 38757 mRNAs were identified, of which 343 lncRNAs and 9412 mRNAs were differentially expressed. Through weighted gene co-expression network analysis (WGCNA), 22 continuously down-expressed lncRNAs targeting 812 co-expressed mRNAs and 48 continuously up-expressed lncRNAs targeting 1209 co-expressed mRNAs were considered to be significantly associated with flag leaf senescence. Gene Ontology results suggested that the senescence-associated lncRNAs targeted mRNAs involving in many biological processes, including transcription, hormone response, oxidation-reduction process and substance metabolism. Additionally, 43 senescence-associated lncRNAs were predicted to target 111 co-expressed transcription factors. Interestingly, 8 down-expressed lncRNAs and 29 up-expressed lncRNAs were found to separately target 12 and 20 well-studied senescence-associated genes (SAGs). Furthermore, analysis on the competing endogenous RNA (CeRNA) network revealed that 6 down-expressed lncRNAs possibly regulated 51 co-expressed mRNAs through 15 miRNAs, and 14 up-expressed lncRNAs possibly regulated 117 co-expressed mRNAs through 21 miRNAs. Importantly, by expression validation, a conserved miR164-NAC regulatory pathway was found to be possibly involved in leaf senescence, where lncRNA MSTRG.62092.1 may serve as a ceRNA binding with miR164a and miR164e to regulate three transcription factors. And two key lncRNAs MSTRG.31014.21 and MSTRG.31014.36 also could regulate the abscisic-acid biosynthetic gene BGIOSGA025169 (OsNCED4) and BGIOSGA016313 (NAC family) through osa-miR5809. The possible regulation networks of lncRNAs involving in leaf senescence were discussed, and several candidate lncRNAs were recommended for prior transgenic analysis. These findings will extend the understanding on the regulatory roles of lncRNAs in leaf senescence, and lay a foundation for functional research on candidate lncRNAs.
PMID: 33569692
BMC Bioinformatics , IF:3.242 , 2021 Apr , V22 (1) : P203 doi: 10.1186/s12859-021-04122-7
Constructing and analysing dynamic models with modelbase v1.2.3: a software update.
Institute of Quantitative and Theoretical Biology, Heinrich Heine University, Universitatsstr. 1, 40225, Dusseldorf, Germany.; CEPLAS - Cluster of Excellence on Plant Sciences, Universitatsstr. 1, 40225, Dusseldorf, Germany.; Institute of Quantitative and Theoretical Biology, Heinrich Heine University, Universitatsstr. 1, 40225, Dusseldorf, Germany. anna.matuszynska@hhu.de.; CEPLAS - Cluster of Excellence on Plant Sciences, Universitatsstr. 1, 40225, Dusseldorf, Germany. anna.matuszynska@hhu.de.
BACKGROUND: Computational mathematical models of biological and biomedical systems have been successfully applied to advance our understanding of various regulatory processes, metabolic fluxes, effects of drug therapies, and disease evolution and transmission. Unfortunately, despite community efforts leading to the development of SBML and the BioModels database, many published models have not been fully exploited, largely due to a lack of proper documentation or the dependence on proprietary software. To facilitate the reuse and further development of systems biology and systems medicine models, an open-source toolbox that makes the overall process of model construction more consistent, understandable, transparent, and reproducible is desired. RESULTS AND DISCUSSION: We provide an update on the development of modelbase, a free, expandable Python package for constructing and analysing ordinary differential equation-based mathematical models of dynamic systems. It provides intuitive and unified methods to construct and solve these systems. Significantly expanded visualisation methods allow for convenient analysis of the structural and dynamic properties of models. After specifying reaction stoichiometries and rate equations modelbase can automatically assemble the associated system of differential equations. A newly provided library of common kinetic rate laws reduces the repetitiveness of the computer programming code. modelbase is also fully compatible with SBML. Previous versions provided functions for the automatic construction of networks for isotope labelling studies. Now, using user-provided label maps, modelbase v1.2.3 streamlines the expansion of classic models to their isotope-specific versions. Finally, the library of previously published models implemented in modelbase is growing continuously. Ranging from photosynthesis to tumour cell growth to viral infection evolution, all these models are now available in a transparent, reusable and unified format through modelbase. CONCLUSION: With this new Python software package, which is written in currently one of the most popular programming languages, the user can develop new models and actively profit from the work of others. modelbase enables reproducing and replicating models in a consistent, tractable and expandable manner. Moreover, the expansion of models to their isotopic label-specific versions enables simulating label propagation, thus providing quantitative information regarding network topology and metabolic fluxes.
PMID: 33879053