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      Integrative Transcriptomic Analysis Uncovers Novel Gene Modules That Underlie the Sulfate Response in Arabidopsis thaliana

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          Abstract

          Sulfur is an essential nutrient for plant growth and development. Sulfur is a constituent of proteins, the plasma membrane and cell walls, among other important cellular components. To obtain new insights into the gene regulatory networks underlying the sulfate response, we performed an integrative meta-analysis of transcriptomic data from five different sulfate experiments available in public databases. This bioinformatic approach allowed us to identify a robust set of genes whose expression depends only on sulfate availability, indicating that those genes play an important role in the sulfate response. In relation to sulfate metabolism, the biological function of approximately 45% of these genes is currently unknown. Moreover, we found several consistent Gene Ontology terms related to biological processes that have not been extensively studied in the context of the sulfate response; these processes include cell wall organization, carbohydrate metabolism, nitrogen compound transport, and the regulation of proteolysis. Gene co-expression network analyses revealed relationships between the sulfate-responsive genes that were distributed among seven function-specific co-expression modules. The most connected genes in the sulfate co-expression network belong to a module related to the carbon response, suggesting that this biological function plays an important role in the control of the sulfate response. Temporal analyses of the network suggest that sulfate starvation generates a biphasic response, which involves that major changes in gene expression occur during both the early and late responses. Network analyses predicted that the sulfate response is regulated by a limited number of transcription factors, including MYBs, bZIPs, and NF-YAs. In conclusion, our analysis identified new candidate genes and provided new hypotheses to advance our understanding of the transcriptional regulation of sulfate metabolism in plants.

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          Most cited references113

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          Lethality and centrality in protein networks

          In this paper we present the first mathematical analysis of the protein interaction network found in the yeast, S. cerevisiae. We show that, (a) the identified protein network display a characteristic scale-free topology that demonstrate striking similarity to the inherent organization of metabolic networks in particular, and to that of robust and error-tolerant networks in general. (b) the likelihood that deletion of an individual gene product will prove lethal for the yeast cell clearly correlates with the number of interactions the protein has, meaning that highly-connected proteins are more likely to prove essential than proteins with low number of links to other proteins. These results suggest that a scale-free architecture is a generic property of cellular networks attributable to universal self-organizing principles of robust and error-tolerant networks and that will likely to represent a generic topology for protein-protein interactions.
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            Comprehensive algorithm for quantitative real-time polymerase chain reaction.

            Quantitative real-time polymerase chain reactions (qRT-PCR) have become the method of choice for rapid, sensitive, quantitative comparison of RNA transcript abundance. Useful data from this method depend on fitting data to theoretical curves that allow computation of mRNA levels. Calculating accurate mRNA levels requires important parameters such as reaction efficiency and the fractional cycle number at threshold (CT) to be used; however, many algorithms currently in use estimate these important parameters. Here we describe an objective method for quantifying qRT-PCR results using calculations based on the kinetics of individual PCR reactions without the need of the standard curve, independent of any assumptions or subjective judgments which allow direct calculation of efficiency and CT. We use a four-parameter logistic model to fit the raw fluorescence data as a function of PCR cycles to identify the exponential phase of the reaction. Next, we use a three-parameter simple exponent model to fit the exponential phase using an iterative nonlinear regression algorithm. Within the exponential portion of the curve, our technique automatically identifies candidate regression values using the P-value of regression and then uses a weighted average to compute a final efficiency for quantification. For CT determination, we chose the first positive second derivative maximum from the logistic model. This algorithm provides an objective and noise-resistant method for quantification of qRT-PCR results that is independent of the specific equipment used to perform PCR reactions.
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              Sulfur assimilation in photosynthetic organisms: molecular functions and regulations of transporters and assimilatory enzymes.

              Sulfur is required for growth of all organisms and is present in a wide variety of metabolites having distinctive biological functions. Sulfur is cycled in ecosystems in nature where conversion of sulfate to organic sulfur compounds is primarily dependent on sulfate uptake and reduction pathways in photosynthetic organisms and microorganisms. In vascular plant species, transport proteins and enzymes in this pathway are functionally diversified to have distinct biochemical properties in specific cellular and subcellular compartments. Recent findings indicate regulatory processes of sulfate transport and metabolism are tightly connected through several modes of transcriptional and posttranscriptional mechanisms. This review provides up-to-date knowledge in functions and regulations of sulfur assimilation in plants and algae, focusing on sulfate transport systems and metabolic pathways for sulfate reduction and synthesis of downstream metabolites with diverse biological functions.
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                Author and article information

                Contributors
                Journal
                Front Plant Sci
                Front Plant Sci
                Front. Plant Sci.
                Frontiers in Plant Science
                Frontiers Media S.A.
                1664-462X
                10 April 2018
                2018
                : 9
                : 470
                Affiliations
                [1] 1Instituto de Bioquímica y Microbiología, Facultad de Ciencias, Universidad Austral de Chile , Valdivia, Chile
                [2] 2Instituto de Producción y Sanidad Vegetal, Facultad de Ciencias Agrarias, Universidad Austral de Chile , Valdivia, Chile
                [3] 3Centro de Biotecnología y Genómica de Plantas, Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria, Universidad Politécnica de Madrid , Madrid, Spain
                [4] 4Millennium Institute for Integrative Systems and Synthetic Biology (MIISSB) , Santiago, Chile
                Author notes

                Edited by: Stanislav Kopriva, Universität zu Köln, Germany

                Reviewed by: Masami Yokota Hirai, RIKEN Center for Sustainable Resource Science (CSRS), Japan; Rainer Hoefgen, Max Planck Institute of Molecular Plant Physiology (MPG), Germany

                *Correspondence: Javier Canales, javier.canales@ 123456uach.cl

                These authors have contributed equally to this work.

                This article was submitted to Plant Physiology, a section of the journal Frontiers in Plant Science

                Article
                10.3389/fpls.2018.00470
                5902692
                2f5dc346-baf8-4d80-9f50-4506ca78ce9e
                Copyright © 2018 Henríquez-Valencia, Arenas-M, Medina and Canales.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 05 January 2018
                : 26 March 2018
                Page count
                Figures: 8, Tables: 3, Equations: 0, References: 131, Pages: 20, Words: 0
                Funding
                Funded by: Fondo Nacional de Desarrollo Científico y Tecnológico 10.13039/501100002850
                Award ID: 11150070
                Award ID: 3160336
                Award ID: 3180269
                Funded by: Comisión Nacional de Investigación Científica y Tecnológica 10.13039/501100002848
                Award ID: REDI170024
                Funded by: Ministerio de Economía, Fomento y Turismo 10.13039/501100005886
                Award ID: Millennium Institute for Integrative Systems and Synthetic Biology
                Categories
                Plant Science
                Original Research

                Plant science & Botany
                gene co-expression analysis,sulfur,sulfate assimilation,microarray analysis,network analysis,transcription factors

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