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Original Research ARTICLE Provisionally accepted The full-text will be published soon. Notify me

Front. Plant Sci. | doi: 10.3389/fpls.2019.01409

Identifying Temporally Regulated Root Nodulation Biomarkers Using Time Series Gene Co-expression Network Analysis

  • 1Department of Genetics and Biochemistry, Clemson University, United States
  • 2Clemson University, United States

Root nodulation results from a symbiotic relationship between a plant host and rhizobium bacteria. Synchronized gene expression patterns over the course of rhizobial infection result in activation of pathways that are unique but overlapping with the highly conserved pathways that enable mycorrhizal symbiosis. We performed RNA sequencing of 30 Medicago truncatula root maturation zone samples at five distinct time points. These samples included plants inoculated with Sinorhizobium medicae and control plants that did not receive any rhizobium. Following gene expression quantification, we identified 1,758 differentially expressed genes at various time points. We constructed a gene co-expression network (GCN) from the same data and identified Link Community Modules (LCMs) that were comprised entirely of differentially expressed genes at specific time points post inoculation. One LCM included genes that were up-regulated at 24 hours following inoculation, suggesting an activation of allergen family genes and carbohydrate-binding gene products in response to rhizobium. We also identified two LCMs that were comprised entirely of genes that were down regulated at 24 and 48 hours post-inoculation. The identity of the genes in these modules suggest that down-regulating specific genes at 24 hours may result in decreased jasmonic acid production with an increase in cytokinin production. At 48 hours, coordinated down-regulation of a specific set of genes involved in lipid biosynthesis may play a role in nodulation. We show that GCN-LCM analysis is an effective method to preliminarily identify polygenic candidate biomarkers of root nodulation and develop hypotheses for future discovery.

Keywords: root, nodulation, Symbiosis, biomarker, network, Bioinformactics, KINC, RNA-Seq

Received: 20 May 2019; Accepted: 11 Oct 2019.

Copyright: © 2019 Poehlman, Schnabel, Chavan, Frugoli and Feltus. 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(s) 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.

* Correspondence: Dr. Julia A. Frugoli, Clemson University, Clemson, United States, jfrugol@clemson.edu