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Physiological Stressors and Invasive Plant Infections Alter the Small RNA Transcriptome of the Rice Blast Fungus, Magnaporthe Oryzae

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Physiological Stressors and Invasive Plant Infections Alter the Small RNA Transcriptome of the Rice Blast Fungus, Magnaporthe Oryzae

Vidhyavathi Raman et al. BMC Genomics.

Abstract

Background: The rice blast fungus, Magnaporthe oryzae is a destructive pathogen of rice and other related crops, causing significant yield losses worldwide. Endogenous small RNAs (sRNAs), including small interfering RNAs (siRNAs) and microRNAs (miRNAs) are critical components of gene regulation in many eukaryotic organisms. Recently several new species of sRNAs have been identified in fungi. This fact along with the availability of genome sequence makes M. oryzae a compelling target for sRNA profiling. We have examined sRNA species and their biosynthetic genes in M. oryzae, and the degree to which these elements regulate fungal stress responses. To this end, we have characterized sRNAs under different physiological stress conditions, which had not yet been examined in this fungus.

Results: The resulting libraries are composed of more than 37 million total genome matched reads mapping to intergenic regions, coding sequences, retrotransposons, inverted, tandem, and other repeated regions of the genome with more than half of the small RNAs arising from intergenic regions. The 24 nucleotide (nt) size class of sRNAs was predominant. A comparison to transcriptional data of M. oryzae undergoing the same physiological stresses indicates that sRNAs play a role in transcriptional regulation for a small subset of genes. Support for this idea comes from generation and characterization of mutants putatively involved in sRNAs biogenesis; our results indicate that the deletion of Dicer-like genes and an RNA-Dependent RNA Polymerase gene increases the transcriptional regulation of this subset of genes, including one involved in virulence.

Conclusions: Various physiological stressors and in planta conditions alter the small RNA profile of the rice blast fungus. Characterization of sRNA biosynthetic mutants helps to clarify the role of sRNAs in transcriptional control.

Figures

Figure 1
Figure 1
Proportion of sRNAs in each size class for the environmental mycelial libraries. Proportion of sRNAs for total genome-matched reads (top panel) and distinct-genome matched reads (bottom panel). Total genome-matched reads shows a peak at 24 nt for the starvation libraries, CS and NS, while the other libraries are roughly evenly distributed. Distinct genome-matched reads shows a relatively even distribution, except for NS and PQ, which have the highest peaks between 19–20 nt. CM = complete media; CS = carbon starved; MM = minimal media; NS = nitrogen starved; PQ = paraquat.
Figure 2
Figure 2
Proportion of sRNAs in each size class for the in planta libraries.M. oryzae - specific reads were parsed out from the total reads by aligning them to the M. oryzae genome. Top panel: Proportion of total genome-matched reads shows a peak at 26 nt for the LMg72 and LMg96 libraries. Bottom panel: Proportion of distinct genome-matched reads shows peaks at 23 and 24-nt for the in planta libraries (bottom panel). LMg0 = mock inoculated; LMg72 = 72 hpi; LMg96 = 96 hpi.
Figure 3
Figure 3
5’ nucleotide preference for sRNAs in M. oryzae mycelial libraries (left panels) and in planta libraries (right panels). In the mycelial libraries, there was a strong preference shown for G, while in the in planta libraries, there was a preference shown for A followed by U.
Figure 4
Figure 4
Association between transcriptional control of genes within the different environmental conditions and post-transcriptional control of the same set of genes under the same conditions. Genes from three different environmental conditions are negatively regulated in the microarray study for that condition, while they showed an abundance of small RNAs associated with the gene for that condition compared to the complete media (CM) control (A); Genes from four different environmental conditions were induced in the microarray for that condition, while they showed a low amount of sRNAs associated with the gene compared to the CM control (B). CS = carbon starved; MM = minimal media; NS = nitrogen starved; PQ = paraquat; T72 = Infected rice leaf at 72hpi.
Figure 5
Figure 5
Expression of selected genes in different mutant backgrounds. In order to understand the regulation of genes with a negative correlation between sRNA levels and microarray expression, seven genes were selected and analyzed in wild type and in RNAi mutant backgrounds using real time qRT-PCR; expression levels were calculated using 2-ΔΔCT method. MoDcl1: Dicer1; MoDcl2: Dicer2; RdRP: RNA-dependent RNA polymerase (MGG_13453); MoDcl2/MoDcl1: Dicer2 knock-out in a Dicer1 knock-out background (the reciprocal was also performed and showed similar results); KO: knock-out; ECT: ectopic. MGG numbers correspond to the following genes: MGG_08843 = magnesium transporter ALR2; MGG_01596 = damage-response protein DUN1; MGG_04428 = ACE1; MGG_06609 = acetyl-CoA hydrolase; MGG_05869 = importin domain-containing; MGG_01439 = inorganic phosphate transporter; MGG_04470 = nucleolar complex protein 14.

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