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Transcriptional Regulatory Network of Arabidopsis Starch Metabolism under Extensive Light Condition: A Potential Model of Transcription-modulated Starch Metabolism in Roots of Starchy Crops

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Procedia Computer Science 2013年 23卷 113-121页

作者： Somkid Bumee Papapit Ingkasuwan Saowalak Kalapanulak Asawin Meechai Supapon Cheevadhanarak Treenut Saithong Systems Biology and Bioinformatics Research Laboratory Pilot Plant Development and Training Institute King Mongkut's University of Technology Thonburi Bangkhuntien campus Bangkok Thailand 10150 Bioinformatics and Systems Biology Program School of Bioresources and Technology King Mongkut's University of Technology Thonburi Bangkhuntien campus Bangkok Thailand 10150 Department of Chemical Engineering Faculty of Engineering King Mongkut's University of Technology Thonburi Bangkok Thailand 10140 Division of Biotechnology School of Bioresources and Technology King Mongkut's University of Technology Thonburi Bangkhuntien campus Bangkok Thailand 10150

Starchy root crops are a major carbohydrates source for being both human food and animal feed. The increasing demand of such crops has been a driving force of studies and research in biology of the crops. However, the related-knowledge as well as the existing information is still very few in comparison with the Arabidopsis model plant. Accordingly, the aims of this work are (1) to attempt to exploit the enormous data of Arabidopsis model plant to infer the regulation in the starchy root crops, and (2) to investigate the possibility and plausibility of the inference. Here, the transcriptional regulatory network of starch metabolism of Arabidopsis under extensive light condition was performed through the modified graphical Gaussian model (GGM) to infer the regulation of the similar process in root crops. The resulting correlation network of the significant genes includes 70 transcription factors and two starch-related genes, alpha-Glucosidase-like3 ( AGL3:At3g45940 ) and beta-Amylase 5 ( BAM5:At4g15210 ). Though the results provided the potential transcription factors of starch-related genes, which could be useful for further investigation, it is more likely that the selected condition of data is not appropriate to represent the starch metabolism in root crops. The results showed that greater than 70% of the significant genes were related to the starch degradation process which might reflect that the plants were under stress. This observation was supported by the Gene Ontology (GO) enrichment analysis that found many enriched GO terms relevant to the stress response. In conclusion, we believe that the data of the model plant are useful for gaining more understanding into the regulation in other plants, including root crops, but the suitable condition of data measurement in use need to be well defined.

关键词： transcriptional regulatory network graphical Gaussian model starch metabolism

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Reconstructing the Lineage Histories and Differentiation Trajectories of Individual Hematopoietic Stem Cells in JAK2-Mutant Myeloproliferative Neoplasms

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BLOOD 2020年 136卷 7-8页

作者： Van Egeren, Debra Escabi, Javier Nguyen, Maximilian Liu, Shichen Reilly, Christopher R. Patel, Sachin Kamaz, Baransel Kalyva, Maria DeAngelo, Daniel J. Galinsky, Ilene Wadleigh, Martha Winer, Eric S. Luskin, Marlise R. Stone, Richard M. Garcia, Jacqueline S. Hobbs, Gabriela S. Camargo, Fernando D. Michor, Franziska Mullally, Ann Cortes-Ciriano, Isidro Hormoz, Sahand Department of Systems Biology Harvard Medical School Boston Princeton University Princeton Department of Biostatistics and Computational Biology Dana-Farber Cancer Institute Boston Department of Medical Oncology Dana-Farber Cancer Institute Boston Hematology/Oncology Department and Stem Cell Program Boston Children's Hospital Boston Division of Hematology Brigham and Women's Hospital Boston European Bioinformatics Institute Cambridge United Kingdom Department of Medical Oncology Dana-Farber Cancer Inst. Boston MA Department of Medical Oncology Dana-Farber Cancer Institute Boston MA Leukemia Center Massachusetts General Hospital Boston MA

*equal contribution, # co-corresponding authors Although the JAK2V617F mutation is the most common MPN phenotypic driver mutation, the precise consequences of the mutation on the behavior of individual human hematopoietic stem cells (HSCs) in vivo remains unknown. We used whole genome sequencing and single-cell profiling of hematopoietic stem and progenitor cells (HSPCs) to quantify the impact of JAK2V617F on the proliferation dynamics of HSCs and the differentiation trajectories of their progenies in individual newly diagnosed MPN patients. We reconstructed the lineage history of individual HSCs obtained from patients with newly diagnosed essential thrombocythemia (ET), using the pattern of spontaneous somatic mutations accrued in their genomes over decades (Figure 1). Intriguingly, our analysis indicates that the JAK2V617F mutation occurred in a single HSC many years before MPN diagnosis - at age 9±2 years in a 34 year-old patient, and at age 19±3 years in a 63 year-old patient. In each patient, we inferred the number of mutated HSCs over the years and computed their fitness. After escaping stochastic extinction, the population of mutated HSCs grew exponentially by 63±15% and 44±13% every year in the two patients respectively. To contrast the differentiation trajectories of the JAK2 -mutant HSCs with those of healthy HSCs, we simultaneously measured the full transcriptome and somatic mutations in single HSPCs in the two ET patients in whom we had performed whole genome sequencing and in one additional ET patient (N=3 total) and also in patients with polycythemia vera (PV) (N=3). We observed, at the time of MPN diagnosis, a consistent lineage bias of JAK2 -mutant HSPCs toward megakaryocyte-erythrocyte fate, across ET and PV patients. Exploiting our ability to discriminate JAK2 -mutant cells from JAK2 wild-type cells within individual MPN patients, we identified genes involved in antigen presentation and inflammation as differentially up-regulated in JAK2 -mutant HS

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Single-cell RNA-sequencing and subcellular spatial transcriptomics facilitate the translation of liver microphysiological systems for regulatory application

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Journal of Pharmaceutical Analysis 2023年第7期13卷 691-693页

作者： Dan Li Zhou Fang Qiang Shi Nicholas Zhang Binsheng Gong Weida Tong Ahmet F.Coskun Joshua Xu Division of Bioinformatics and Biostatistics National Center for Toxicological ResearchU.S.Food and Drug AdministrationJeffersonAR72079USA Wallace H.Coulter Department of Biomedical Engineering Georgia Institute of Technology and Emory UniversityAtlantaGA30332USA Machine Learning Graduate Program Georgia Institute of TechnologyAtlantaGA30332USA Division of Systems Biology National Center for Toxicological ResearchU.S.Food and Drug AdministrationJeffersonAR72079USA Interdisciplinary Bioengineering Graduate Program Georgia Institute of TechnologyAtlantaGA30332USA Parker H.Petit Institute for Bioengineering and Bioscience Georgia Institute of TechnologyAtlantaGA30332USA

Reducing the use of animal models in drug development and safety assessment has long been supported by the *** and Drug Administration(FDA).The report by Royal Society for the Prevention of Cruelty to Animals indicates that in 2020,experiments involved the use of over 100 million animals,with the United States leading the list by utilizing 20 million *** ethical considerations associated with animal testing and the costs in terms of time and money,animal models are not always effective in predicting human reactions to drug *** animal testing has been the traditional method for assessing the safety and efficacy of drugs.

关键词： money utilizing testing

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Context-dependent gene regulatory network reveals regulation dynamics and cell trajectories using unspliced transcripts

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Briefings in bioinformatics 2023年第2期24卷 bbac633-bbac633页

作者： Tu, Yueh-Hua Juan, Hsueh-Fen Huang, Hsuan-Cheng The Bioinformatics Program Taiwan International Graduate Program Academia Sinica Taiwan Department of Life Science Center for Computational and Systems Biology National Taiwan University Taiwan Institute of Biomedical Informatics National Yang Ming Chiao Tung University Taiwan

Gene regulatory networks govern complex gene expression programs in various biological phenomena, including embryonic development, cell fate decisions and oncogenesis. Single-cell techniques are increasingly being used to study gene expression, providing higher resolution than traditional approaches. However, inferring a comprehensive gene regulatory network across different cell types remains a challenge. Here, we propose to construct context-dependent gene regulatory networks (CDGRNs) from single-cell RNA sequencing data utilizing both spliced and unspliced transcript expression levels. A gene regulatory network is decomposed into subnetworks corresponding to different transcriptomic contexts. Each subnetwork comprises the consensus active regulation pairs of transcription factors and their target genes shared by a group of cells, inferred by a Gaussian mixture model. We find that the union of gene regulation pairs in all contexts is sufficient to reconstruct differentiation trajectories. Functions specific to the cell cycle, cell differentiation or tissue-specific functions are enriched throughout the developmental process in each context. Surprisingly, we also observe that the network entropy of CDGRNs decreases along differentiation trajectories, indicating directionality in differentiation. Overall, CDGRN allows us to establish the connection between gene regulation at the molecular level and cell differentiation at the macroscopic level. © The Author(s) 2023.

关键词： Gaussian mixture model gene regulatory network single-cell RNA sequencing trajectory analysis

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Origin of Overstretching Transitions in Single-Stranded Nucleic Acids

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Physical Review Letters 2013年第18期111卷 188302-188302页

作者： Zackary N. Scholl Mahir Rabbi David Lee Laura Manson Hanna S-Gracz Piotr E. Marszalek Program in Computational Biology and Bioinformatics Duke University Durham North Carolina 27708 USA Department of Mechanical Engineering and Materials Science Center for Biologically Inspired Materials and Material Systems Duke University Durham North Carolina 27708 USA Department of Molecular and Structural Biochemistry North Carolina State University Raleigh North Carolina 27708 USA

We combined single-molecule force spectroscopy with nuclear magnetic resonance measurements and molecular mechanics simulations to examine overstretching transitions in single-stranded nucleic acids. In single-stranded DNA and single-stranded RNA there is a low-force transition that involves unwinding of the helical structure, along with base unstacking. We determined that the high-force transition that occurs in polydeoxyadenylic acid single-stranded DNA is caused by the cooperative forced flipping of the dihedral angle formed between four atoms, O5’-C5’-C4’-C3’ (γ torsion), in the nucleic acid backbone within the canonical B-type helix. The γ torsion also flips under force in A-type helices, where the helix is shorter and wider as compared to the B-type helix, but this transition is less cooperative than in the B type and does not generate a high-force plateau in the force spectrums of A-type helices. We find that a similar high-force transition can be induced in polyadenylic acid single-stranded RNA by urea, presumably due to disrupting the intramolecular hydrogen bonding in the backbone. We hypothesize that a pronounced high-force transition observed for B-type helices of double stranded DNA also involves a cooperative flip of the γ torsion. These observations suggest new fundamental relationships between the canonical structures of single-and double-stranded DNA and the mechanism of their molecular elasticity.

关键词： NUCLEAR magnetic resonance spectroscopy SINGLE-stranded DNA NUCLEOTIDE sequence DEOXYRIBOSE ATOMIC force microscopy

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Single-cell analysis of experience-dependent transcriptomic states in the mouse visual cortex (vol 21, pg 120, 2018)

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NATURE NEUROSCIENCE 2018年第7期21卷 1017-1017页

作者： Hrvatin, Sinisa Hochbaum, Daniel R. Nagy, M. Aurel Cicconet, Marcelo Robertson, Keiramarie Cheadle, Lucas Zilionis, Rapolas Ratner, Alex Borges-Monroy, Rebeca Klein, Allon M. Sabatini, Bernardo L. Greenberg, Michael E. Department of Neurobiology Harvard Medical School Boston MA USA Society of Fellows Harvard University Cambridge MA USA Department of Neurobiology Howard Hughes Medical Institute Harvard Medical School Boston MA USA Image and Data Analysis Core Harvard Medical School Boston MA USA Department of Systems Biology Harvard Medical School Boston MA USA Vilnius University Institute of Biotechnology Vilnius Lithuania ICCB-L Single Cell Core Harvard Medical School Boston MA USA Program for Bioinformatics and Integrative Genomics Graduate School of Arts and Science Division of Medical Sciences Harvard University Cambridge MA USA

Activity-dependent transcriptional responses shape cortical function. However, a comprehensive understanding of the diversity of these responses across the full range of cortical cell types, and how these changes contribute to neuronal plasticity and disease, is lacking. To investigate the breadth of transcriptional changes that occur across cell types in the mouse visual cortex after exposure to light, we applied high-throughput single-cell RNA sequencing. We identified significant and divergent transcriptional responses to stimulation in each of the 30 cell types characterized, thus revealing 611 stimulus-responsive genes. Excitatory pyramidal neurons exhibited inter- and intralaminar heterogeneity in the induction of stimulus-responsive genes. Non-neuronal cells showed clear transcriptional responses that may regulate experience-dependent changes in neurovascular coupling and myelination. Together, these results reveal the dynamic landscape of the stimulus-dependent transcriptional changes occurring across cell types in the visual cortex; these changes are probably critical for cortical function and may be sites of deregulation in developmental brain disorders.

关键词： Gene expression analysis Molecular neuroscience Oligodendrocyte Transcriptomics Visual system

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systems biology applications to study mechanisms of human immunodeficiency virus latency and reactivation

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World Journal of Clinical Infectious Diseases 2016年第2期6卷 6-21页

作者： Cory H White Bastiaan Moesker Angela Ciuffi Nadejda Beliakova-Bethell Graduate Program in Bioinformatics and Systems Biology University of California San Diego San Diego VA Medical Center and Veterans Medical Research Foundation Clinical and Experimental Sciences Faculty of Medicine University of Southampton Institute of Microbiology University Hospital of Lausanne (CHUV) and University of Lausanne Department of Medicine Univer-sity of California San Diego

Eradication of human immunodeficiency virus(HIV) in infected individuals is currently not possible because of the presence of the persistent cellular reservoir of latent infection. The identification of HIV latency biomarkers and a better understanding of the molecular mechanisms contributing to regulation of HIV expression might provide essential tools to eliminate these latently infected cells. This review aims at summarizing gene expression profiling and systems biology applications to studies of HIV latency and eradication. Studies comparing gene expression in latently infected and uninfected cells identify candidate latency biomarkers and novel mechanisms of latency control. Studies that profiled gene expression changes induced by existing latency reversing agents(LRAs) highlight uniting themes driving HIV reactivation and novel mechanisms that contribute to regulation of HIV expression by different LRAs. Among the reviewed gene expression studies, the common approaches included identification of differentially expressed genes and gene functional category assessment. Integration of transcriptomic data with other biological data types is presently scarce, and the field would benefit from increased adoption of these methods in future studies. In addition, designing prospective studies that use the same methods of data acquisition and statistical analyses will facilitate a more reliableidentification of latency biomarkers using different model systems and the comparison of the effects of different LRAs on host factors with a role in HIV reactivation. The results from such studies would have the potential to significantly impact the process by which candidate drugs are selected and combined for future evaluations and advancement to clinical trials.

关键词： Gene expression Microarrays RNA-Seq systems biology Human immunodeficiency virus Viral latency Disease eradication Biomarkers Molecular mechanisms Latency reversing agents

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A biocomputational platform for the automated construction of large-scale mathematical models of miRNA-transcription factor networks for studies on gene dosage compensation

A biocomputational platform for the automated construction o...

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IEEE Central America and Panama Convention (CONCAPAN)

作者： Acón Man-Sai Siles-Canales Francisco RA Mora-Rodriguez Master Program on Bioinformatics and Systems Biology University of Costa Rica (UCR) San José Costa Rica Faculty of Engineering University of Costa Rica (UCR) San José Costa Rica Faculty of Microbiology University of Costa Rica (UCR) San José Costa Rica

ISBN: (纸本)9781467395793

Cancer complexity and resistance is mediated by cell-to-cell heterogeneity, which is the consequence of the enormous instability of its genetic material. It is unknown how cancer cells are able to withstand the effects of these alterations, while normal cells are typically very sensitive. We hypothesize that cancer requires specific type of stability to survive the enormous chromosomal alterations. This stability may be mediated by a group of genes, whose expression is tightly regulated to maintain viability through a process called gene dosage compensation. This mechanism could be mediated by systems-level properties of complex networks of microRNAs (miRNA) and transcription factors (TF), regulating gene expression despite changes in copy number. Therefore, we designed a biocomputational platform to automatically construct large-scale mathematical models regulating the expression of several candidate genes under dosage compensation. This platform has a broader potential application to other scientific questions involving miRNA and TF networks.

关键词： RNA Proteins DNA Mathematical model Cancer Correlation Gene expression

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Transcriptomic Data Integration Inferring the Dominance of Starch Biosynthesis in Carbon Utilization of Developing Cassava Roots

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Procedia Computer Science 2012年 11卷 96-106页

作者： Wanatsanan Siriwat Saowalak Kalapanulak Malinee Suksangpanomrung Supatcharee Netrphan Asawin Meechai Treenut Saithong Bioinformatics and Systems Biology Program School of Bioresources and Technology and School of Information Technology King Mongkut's University of Technology Thonburi (Bang Khun Thian campus) Bangkok 10150 Thailand School of Bioresources and Technology King Mongkut's University of Technology Thonburi (Bang Khun Thian campus) Bangkok 10150 Thailand Systems Biology and Bioinformatics Research Group Pilot Plant Development and Training Institute King Mongkut's University of Technology Thonburi Bangkok 10150 Thailand National Center for Genetic Engineering and Biotechnology (BIOTEC) Pathumthani 12120 Thailand Department of Chemical Engineering King Mongkut's University of Technology Thonburi Bangkok 10140 Thailand

Carbon metabolism, which is an important process underlying the plant development, has been extensively studied in model plant Arabidopsis, however the understanding in this process for cassava root crop is very little. To enhance our understanding into the process, we studied carbon partitioning during cassava root development at the transcriptional level via transciptomic data integration into the metabolic pathways. The transcriptome data of three different developmental stages of cassava roots—fibrous root (FR), developing storage root (DR), and mature storage root (MR) from Yang et al. [1] —was integrated into the key carbon metabolism pathways reconstructed following the protocol of Rongsirikul et al. [2] . According to the 43 differentially expressed genes (56 proteins IDs) mapped into the pathways, we found that the genes involved in starch biosynthesis are more up-regulated, in contrast to the expression of genes in the cell wall biosynthesis and respiration. The results may imply the significance of starch biosynthesis among the carbon utilization processes in the developing cassava roots. In other words, the carbon source from α-D-glucose-1-phosphate (G1P) might be mostly used for starch biosynthesis rather than cell wall biosynthesis and respiration pathways during cassava root development.

关键词： carbon partitioning carbon metabolism pathway starch biosynthesis cassava root development data integration

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Study of enhancer-promoter interactome during mouse embryonic development with H3K4me3 PLAC-seq

Study of enhancer-promoter interactome during mouse embryoni...

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第十八次中国暨国际生物物理大会

作者： Miao Yu Rongxin Fang Ivan Juric Nathan Zemke Armen Abnousi Rong Hu Ming Hu Bing Ren School of Life Sciences Fudan University Ludwig Institute for Cancer Research Bioinformatics and Systems Biology Graduate Program University of California Department of Quantitative Health Sciences Lerner Research Institute Cleveland Clinic Foundation Center for Epigenomics Department of Cellular and Molecular Medicine University of California

Formation of long-range chromatin loops is a crucial step in transcriptional activation of target genes by distal enhancers. Mapping such structural features can help define target genes for enhancers and annotate non-coding sequence variants linked to human ***, we developed Proximity Ligation-Assisted ChIP-seq (PLAC-seq), which detects high-resolution long-range chromatin interactions at selected genomic regions through combination of in situ Hi-C and chromatin IP. We also developed a computational method, MAPS (Model-based Analysis of PLAC-seq and HiChIP) to process the data from such experiments and identify long-range chromatin interactions with high reproducibility and precision. By application of H3K4me3 PLAC-seq in mouse fetal tissues we identify182,403 long-range chromatin interactions at 10kb resolution. Through integrative analysis with RNA-seq, ATAC-seq and ChIP-seq data, we are able to link the genes with their potential regulatory enhancers.

关键词： Study of enhancer-promoter interactome during mouse embryonic development with H3K4me3 PLAC-seq

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