Open Access Research article

Molecular response to the pathogen Phytophthora sojae among ten soybean near isogenic lines revealed by comparative transcriptomics

Feng Lin1, Meixia Zhao1, Douglas D Baumann2, Jieqing Ping1, Lianjun Sun1, Yunfeng Liu1, Biao Zhang1, Zongxiang Tang1, Elisa Hughes1, Rebecca W Doerge3, Teresa J Hughes45* and Jianxin Ma1*

Author Affiliations

1 Department of Agronomy, Purdue University, West Lafayette, IN 47907, USA

2 Department of Mathematics, University of Wisconsin – La Crosse, La Crosse, WI 54601, USA

3 Department of Statistics, Purdue University, West Lafayette, IN 47907, USA

4 Department of Botany and Plant Pathology, Purdue University, West Lafayette, IN 47907, USA

5 USDA-ARS Crop Production and Pest Control Research Unit, Purdue University, West Lafayette, IN 47907, USA

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BMC Genomics 2014, 15:18  doi:10.1186/1471-2164-15-18

Published: 10 January 2014

Abstract

Background

Phytophthora root and stem rot (PRR) of soybean, caused by Phytophthora sojae, is controlled by Rps genes. However, little is known regarding the Rps-induced molecular responses to P. sojae and how they actually overlap. We thus sequenced, analyzed, and compared the transcriptomes of 10 near isogenic lines (NILs), each with a unique Rps gene/allele, and the susceptible parent Williams, pre- and post-inoculation with the pathogen.

Results

A total of 4,330 differentially expressed genes (DEGs) were identified in Williams versus 2,014 to 5,499 DEGs in individual NILs upon inoculation with the pathogen. Comparisons of the DEGs between the NILs and Williams identified incompatible interaction genes (IIGs) and compatible interaction genes (CIGs). Hierarchical cluster and heatmap analyses consistently grouped the NILs into three clusters: Cluster I (Rps1-a), Cluster II (Rps1-b, 1-c and 1-k) and Cluster III (Rps3-a, 3-b, 3-c, 4, 5, and 6), suggesting an overlap in Rps-induced defense signaling among certain NILs. Gene ontology (GO) analysis revealed associations between members of the WRKY family and incompatible reactions and between a number of phytohormone signaling pathways and incompatible/compatible interactions. These associations appear to be distinguished according to the NIL clusters.

Conclusions

This study characterized genes and multiple branches of putative regulatory networks associated with resistance to P. sojae in ten soybean NILs, and depicted functional “fingerprints” of individual Rps-mediated resistance responses through comparative transcriptomic analysis. Of particular interest are dramatic variations of detected DEGs, putatively involved in ethylene (ET)-, jasmonic acid (JA)-, (reactive oxygen species) ROS-, and (MAP-kinase) MAPK- signaling, among these soybean NILs, implicating their important roles of these signaling in differentiating molecular defense responses. We hypothesize that different timing and robustness in defense signaling to the same pathogen may be largely responsible for such variations.

Keywords:
Comparative transcriptomics; Resistance to Phytophthora sojae; Soybean