Progress 11/19/13 to 09/30/18
Outputs
Target Audience: Initially, the target audience has been fellow scientists in the field of plant biology, especially those focused on understanding the mechanistic basis for a) resistance to drought in model systems, including trees and b) the regulatory mechanisms by which seeds acquire their reserves, acquire desiccation tolerance and become dormant. Subsequently, researchers directly involved in testing the hypotheses that arise from analysis of the data in the context of improving the production of seed storage reserves, and/or the abilities of crop plants to withstand drought stress, either at the seed or the whole plant level, will be included. Crop physiologists and geneticists will be approached to test the validity of the results in field trials. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided?Graduate students in computer science and plant biology have been trained and have graduated. The project has been interdisciplanary throughout and has afforded a sound foundation for students in both discplines. How have the results been disseminated to communities of interest?Publications in refereed journals. What do you plan to do during the next reporting period to accomplish the goals?
Nothing Reported
Impacts
What was accomplished under these goals?
Training of graduate students in plant biology and computer science. Publications in refereed journals.
Publications
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Progress 10/01/16 to 09/30/17
Outputs
Target Audience:Community of plant biologists and bioinformaticians. Changes/Problems:Dr. Collakova's and my NSF grant has expired, so I am no longer working with her. My current project with Drs. Li and Heath is an outgrowth of my work with her on gene regulatory networks. What opportunities for training and professional development has the project provided?A Computer Science graduate student worked to complete the Beacon tool. The student graduated in 2017. A current GBCB student worked to complete CoReg. A second, current, GBCB student worked on developing a method for the discovery of common GRNregulatory networks across plant species. How have the results been disseminated to communities of interest?The CoReg work has been published. A methods chapter, on the development of a tool for the discovery of common stress signaling pathways across plant species, has been submitted for publication, and is under review. What do you plan to do during the next reporting period to accomplish the goals?The Beacon simulation capacity will be submitted for publication in early 2018. Continue to work with Drs. Li and Heath and two GBCB students on the further development of capacities for the discovery of gene regultory networks, including a tool to infer common aspects of development and/or stress-related pathways across plants.
Impacts
What was accomplished under these goals?
Work was conducted in a group project with Dr. S. Li (Crop, Soils and Environmental Sciences) and Dr. L. Heath, (Computer Science). Combinatorial regulation by transcription factors (TFs) of common target genes underlies the functioning of gene regulatory networks (GRN). A computational tool was developed to identify several co-regulatory modules in GRNs, inferred from data from Arabidopsis. The tool is now available at github. In other collaborative work with Drs. Li and Heath, Beacon, a software tool for drawing and storing signaling pathways in plants, was published. Current work involves developing a simulation capacity within Beacon.
Publications
- Type:
Journal Articles
Status:
Published
Year Published:
2017
Citation:
Expresso: A database and web server for exploring the interaction of transcription factors and their target genes in Arabidopsis thaliana using ChIP-Seq peak data. Aghamirzaie D, Raja Velmurugan K, Wu S, Altarawy D, Heath LS, Grene R. F1000Res. 2017 Mar 28;6:372. doi: 10.12688/f1000research.10041.1. eCollection 2017.
- Type:
Journal Articles
Status:
Published
Year Published:
2017
Citation:
Beacon Editor: Capturing Signal Transduction Pathways Using the Systems Biology Graphical Notation Activity Flow Language. Elmarakeby H, Arefiyan M, Myers E, Li S, Grene R, Heath LS. J Comput Biol. 2017 Aug 28. doi: 10.1089/cmb.2017.0095. [Epub ahead of print]
- Type:
Journal Articles
Status:
Published
Year Published:
2017
Citation:
Multilevel Regulation of Abiotic Stress Responses in Plants. Haak DC, Fukao T, Grene R, Hua Z, Ivanov R, Perrella G, Li S. Front Plant Sci. 2017 Sep 20;8:1564. doi: 10.3389/fpls.2017.01564. eCollection 2017. Review.
- Type:
Journal Articles
Status:
Awaiting Publication
Year Published:
2017
Citation:
Identification of regulatory modules in genome scale transcription regulatory networks Song, Q. Grene, R. Heath, LS, Li, S BMC Systems Biology
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Progress 10/01/15 to 09/30/16
Outputs
Target Audience:Readers of peer-reviewed publications. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided?1. The splicing project provided training for a graduate student who earned her doctorate in May, 2016. 2. The Beacon project provided training for a master's student who graduated in August, 2016. A doctoral student is currently working on the Beacon project, and is expected to graduate in May, 2017. How have the results been disseminated to communities of interest?
Nothing Reported
What do you plan to do during the next reporting period to accomplish the goals?We plan to release the Beacon tool in 2017. Additionally, we are planning to develop a simulation capacity for Beacon in 2017, and invite those members of the plant biology community who participated in the workshop in 2012 to apply our tool to the signaling pathways that are of interest to them.
Impacts
What was accomplished under these goals?
1. Gene expression is regulated at multiple levels, requiring systems biology approaches to understand these combinatorial molecular interactions. We have generated CoSpliceNet, a publicly available network inference tool that integrates transcript co-expression and conserved RNA-binding motif discovery at splicing regions to infer undirected mixed transcriptional-splicing networks. Analysis of inferred splicing factor targets revealed an unexpected role for extra-nuclear splicing and the unfolded protein response (UPR) in developing Arabidopsis embryos. Specific predictions regarding the interactions of selected components of UPR during seed maturation and desiccation, obtained using CoSpliceNet, will be experimentally validated in Arabidopsis using genetic, molecular, cell biology, and biochemical tools. 2. Gene regulatory networks (GRNs) provide a representation of relationships between regulators and their target genes. Several methods for GRN inference, both unsupervised and supervised, have been developed to date. Because regulatory relationships consistently reprogram in diverse tissues or under different conditions, GRNs inferred without specific biological contexts are of limited applicability. In this report, a machine learning approach is presented to predict GRNs specific to developing Arabidopsis thaliana embryos. We developed the Beacon GRN inference tool to predict GRNs occurring during seed development in Arabidopsis based on a support vector machine (SVM) model. We developed both global and local inference models and compared their performance, demonstrating that local models are generally superior for our application. Using both the expression levels of the genes expressed in developing embryos and prior known regulatory relationships, GRNs were predicted for specific embryonic developmental stages. The targets that are strongly positively correlated with their regulators are mostly expressed at the beginning of seed development. Potential direct targets were identified based on a match between the promoter regions of these inferred targets and the cis elements recognized by specific regulators. Our analysis also provides evidence for previously unknown inhibitory effects of three positive regulators of gene expression. The Beacon GRN inference tool provides a valuable model system for context-specific GRN inference and is freely available at https://github.com/BeaconProjectAtVirginiaTech/beacon_network_inference.git. 3. "omics" "what-if""experiments"
Publications
- Type:
Journal Articles
Status:
Published
Year Published:
2016
Citation:
Aghamirzaie D, Collakova E, Li S, Grene R. (2016) CoSpliceNet: A framework for co-splicing network inference from transcriptomics data. BMC Genomics, Oct 28;17(1):845.
- Type:
Journal Articles
Status:
Under Review
Year Published:
2016
Citation:
Ying Ni, Delasa Aghamirzaie, Haitham Elmarakeby, Eva Collakova, Song Li, Ruth Grene, and Lenwood S. Heath. 2016. A Machine Learning Approach to Predict Gene Regulatory Networks in Seed Development in Arabidopsis.
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Progress 10/01/14 to 09/30/15
Outputs
Target Audience:Results were presented at several conferences, and in graduate courses. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided?One GBCB student will graduate in 2016. She has developed the bioinformatics tools described above, and has mastered life science and many computational tools to do so. Another graduate student, in Computer Science, is rapidly developing her skills in network inference to address our current objective, described above. How have the results been disseminated to communities of interest?Our results have been presented at several conferences, and, altogether, we have published four papers on our work to date, over the life of the project. Two more papers are planned for 2016. What do you plan to do during the next reporting period to accomplish the goals?We will work on the network inference approach described above, and will use an in-house tool, developed in another project, to depict and store the results that we obtain in a form readily available to the scientific community.
Impacts
What was accomplished under these goals?
As a result of intensive data mining on the part of plant biologists, coupled with the application of in house and available computational tools, we have succeeded in gaining new insights into the relationships of specific splice variants of regulatory genes and their targets in the context of seed development. A pipeline for the detailed analysis of high throughput transcriptomics data has been crafted, and soon will become available to our peers in the life sciences community. Our current objective is to apply several different network inference tools to our data in order to assess which computational approach, yields the most useful results in terms of hypothesis generation for future wet lab work. We are especially interested in the role of specific splicing factor proteins as they act during defined stages of seed development, and have already planned experimentation to test our hypotheses concerning splicing events and the regulation of gene expression.
Publications
- Type:
Journal Articles
Status:
Accepted
Year Published:
2015
Citation:
Aghamirzaie D, Batra D, Heath LS, Schneider A, Grene R, Collakova E. Transcriptome-wide functional characterization reveals novel relationships among differentially expressed transcripts in developing soybean embryos. BMC Genomics. 2015 Nov 14;16(1):928. doi: 10.1186/s12864-015-2108-x
- Type:
Journal Articles
Status:
Accepted
Year Published:
2015
Citation:
Andrew Schneider, Delasa Aghamirzaie, Haitham Elmarakeby, Arati N. Poudel, Abraham J. Koo, Lenwood S. Heath, Ruth Grene and Eva Collakova. Potential targets of VAL1 repression in developing Arabidopsis thaliana embryos. The Plant Journal, in press
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Progress 11/19/13 to 09/30/14
Outputs
Target Audience: Initially, the target audience will be colleagues in the field of plant biology, especially those focused on understanding the mechanistic basis for a) resistance to drought in model systems, including trees and b) the regulatory mechanisms by which seeds acquire their reserves, acquire desiccation tolerance and become dormant. Subsequently, those directly involved in testing the hypotheses that arise from analysis of the data in the context of improving the production of seed storage reserves, and/or the abilities of crop plants to withstand drought stress, either at the seed or the whole plant level, will be included. Crop physiologists and geneticists will be approached to test the validity of the results in field trials. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided? The two graduate students working on the project function in an interdisciplinary environment in which expertise in bioinformatics and plant science are exchanged and melded. How have the results been disseminated to communities of interest? The results have been presented at the Plant Genomics Congress, at the q-bio conference, and at an international conference on RNA sequencing in London, UK. What do you plan to do during the next reporting period to accomplish the goals? A third manuscript will be submitted in December in which results obtained from applying the machine learning tool to the soybean data described above will be presented. A dataset from Arabidopsis is now available and will be analyzed using the tools developed for the soybean project.
Impacts
What was accomplished under these goals?
We have developed a pipeline for the detailed analysis of transcriptomics data to functionally characterize splice variants, using a variety of comparative tools. We havecollaborated with a machine-learning expert in the Computer Engineering department at Virginia Tech to develop an accurate support vector machine classifier to classify members of transcriptome populations into coding or non-coding categories. Our method outperforms current, published, tools.
Publications
- Type:
Journal Articles
Status:
Published
Year Published:
2013
Citation:
Changes in RNA Splicing in Developing Soybean (Glycine max) Embryos.
Aghamirzaie D, Nabiyouni M, Fang Y, Klumas C, Heath LS, Grene R, Collakova E. Biology (Basel). 2013 Nov 21;2(4):1311-37. doi: 10.3390/biology2041311.
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