The MORPH Algorithm: Ranking Candidate Genes for Membership in <i>Arabidopsis</i> and Tomato Pathways

Tzfadia, Oren; Amar, David; Bradbury, Louis Mt; Wurtzel, Eleanore T.; Shamir, Ron

doi:10.1105/tpc.112.104513

Cited by 23 publications

(36 citation statements)

References 93 publications

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“…First, it is robust to noisy biological network data (Vlasblom and Wodak, 2009) and has been successfully used in previous plant molecular network research (Tzfadia et al, 2012). Second, it has shown to be more accurate compared with other algorithms (Nepusz et al, 2012).…”

Section: Detection Of Network Modulesmentioning

confidence: 99%

“…The modularity of cellular networks provides a feasible entry point to simultaneously analyze the complicated behaviors of many genes. This concept is helpful in understanding plant development (He et al, 2010;Bassel et al, 2011b), predicting gene functions (Heyndrickx and Vandepoele, 2012;Tzfadia et al, 2012), and comparing stress responses (Shaik and Ramakrishna, 2013). Technically, machinelearning algorithms are very good at extracting information from a large amount of data in an automated way.…”

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confidence: 99%

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Revealing Shared and Distinct Gene Network Organization in Arabidopsis Immune Responses by Integrative Analysis

et al. 2015

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Pattern-triggered immunity (PTI) and effector-triggered immunity (ETI) are two main plant immune responses to counter pathogen invasion. Genome-wide gene network organizing principles leading to quantitative differences between PTI and ETI have remained elusive. We combined an advanced machine learning method and modular network analysis to systematically characterize the organizing principles of Arabidopsis (Arabidopsis thaliana) PTI and ETI at three network resolutions. At the single network node/ edge level, we ranked genes and gene interactions based on their ability to distinguish immune response from normal growth and successfully identified many immune-related genes associated with PTI and ETI. Topological analysis revealed that the top-ranked gene interactions tend to link network modules. At the subnetwork level, we identified a subnetwork shared by PTI and ETI encompassing 1,159 genes and 1,289 interactions. This subnetwork is enriched in interactions linking network modules and is also a hotspot of attack by pathogen effectors. The subnetwork likely represents a core component in the coordination of multiple biological processes to favor defense over development. Finally, we constructed modular network models for PTI and ETI to explain the quantitative differences in the global network architecture. Our results indicate that the defense modules in ETI are organized into relatively independent structures, explaining the robustness of ETI to genetic mutations and effector attacks. Taken together, the multiscale comparisons of PTI and ETI provide a systems biology perspective on plant immunity and emphasize coordination among network modules to establish a robust immune response.

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Section: Detection Of Network Modulesmentioning

confidence: 99%

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confidence: 99%

Revealing Shared and Distinct Gene Network Organization in Arabidopsis Immune Responses by Integrative Analysis

et al. 2015

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“…The datasets and the pathway from PMN have been applied for in-depth investigation of plant metabolism including pathway predictions, metabolic network reconstructions and developing bioinformatics tools [33,[39][40][41][42][43][44], etc. For instance, in [43] PMN was used to investigate genomic signatures of specialized metabolism in plants.…”

Section: Pmnmentioning

confidence: 99%

“…For instance, in [43] PMN was used to investigate genomic signatures of specialized metabolism in plants. The MORPH algorithm [44], ranking candidate …”

Section: Pmnmentioning

confidence: 99%

Metabolic pathway databases and model repositories

et al. 2018

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Background: The number of biological Knowledge bases/databases storing metabolic pathway information and models has been growing rapidly. These resources are diverse in the type of information/data, the analytical tools, and objectives. Here we present a review of the most popular metabolic pathway databases and model repositories, focusing on their scope, content including reactions, enzymes, compounds, and genes, and applicability. The review aims to help researchers choose a suitable database or model repository according to the information and data required, by providing an insight look of each pathway resource. Results: Four pathways databases and three model repositories were selected on the basis of popularity and diversity. Our review showed that the pathway resources vary in many aspects, such as their scope, content, access to data and the tools. In addition, inconsistencies have been observed in nomenclature and representation of database entities. The three model repositories reviewed do not offer a brief description of the models' characteristics such as simulation conditions. Conclusions: The inconsistencies among the databases in representing their contents may hamper the maximal use of the knowledge accumulated in these databases in particular and the area of systems biology at large. Therefore, it is strongly recommended that the database creators and the metabolic network models developers should follow international standards for the nomenclature of reactions and metabolites. Besides, computationally generated models that could be obtained from model repositories should be utilized with manual curations as they lack some important components that are necessary for full functionality of the models.Keywords: metabolic pathway; database; model repository Author summary: Four metabolic pathway databases and three model repositories were reviewed with regard to their scope, content, and applicability. Despite their innumerable use in the fields of systems biology and metabolic engineering, these pathway databases and model repositories are not in harmony with each other due to the inconsistencies in the way they represent their contents. Besides, the automatically generated metabolic models that can be obtained from the model repositories are not accurate enough for further scientific usage without additional manual curation. Therefore, international standards such as IUBMB principles should be strictly obeyed in creating such metabolic pathway resources.

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“…Several Web-based tools have been developed to allow users to exploit such relationships (Mutwil et al, 2010;Obayashi et al, 2011;Lee et al, 2015). Some of these tools offer the possibility to extend the analyses to species that only recently have emerged as tractable systems for genetic engineering, such as several plant crop species (Ficklin and Feltus, 2011;Movahedi et al, 2011;Mutwil et al, 2011;Tzfadia et al, 2012). Coexpression patterns may also be conserved across species barriers (Stuart et al, 2003;Bergmann et al, 2004).…”

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confidence: 99%

FamNet: A Framework to Identify Multiplied Modules Driving Pathway Expansion in Plants

et al. 2016

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Gene duplications generate new genes that can acquire similar but often diversified functions. Recent studies of gene coexpression networks have indicated that, not only genes, but also pathways can be multiplied and diversified to perform related functions in different parts of an organism. Identification of such diversified pathways, or modules, is needed to expand our knowledge of biological processes in plants and to understand how biological functions evolve. However, systematic explorations of modules remain scarce, and no user-friendly platform to identify them exists. We have established a statistical framework to identify modules and show that approximately one-third of the genes of a plant's genome participate in hundreds of multiplied modules. Using this framework as a basis, we implemented a platform that can explore and visualize multiplied modules in coexpression networks of eight plant species. To validate the usefulness of the platform, we identified and functionally characterized pollen-and root-specific cell wall modules that multiplied to confer tip growth in pollen tubes and root hairs, respectively. Furthermore, we identified multiplied modules involved in secondary metabolite synthesis and corroborated them by metabolite profiling of tobacco (Nicotiana tabacum) tissues. The interactive platform, referred to as FamNet, is available at http://www.gene2function.de/famnet.html.

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The MORPH Algorithm: Ranking Candidate Genes for Membership in Arabidopsis and Tomato Pathways

Cited by 23 publications

References 93 publications

Revealing Shared and Distinct Gene Network Organization in Arabidopsis Immune Responses by Integrative Analysis

Revealing Shared and Distinct Gene Network Organization in Arabidopsis Immune Responses by Integrative Analysis

Metabolic pathway databases and model repositories

FamNet: A Framework to Identify Multiplied Modules Driving Pathway Expansion in Plants

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