Tempo and mode of plant RNA virus escape from RNA interference-mediated resistance

Abstract

A biotechnological application of artificial microRNAs (amiRs) is the generation of plants that are resistant to virus infection. This resistance has proven to be highly effective and sequence specific. However, before these transgenic plants can be deployed in the field, it is important to evaluate the likelihood of the emergence of resistance-breaking mutants. Two issues are of particular interest: (i) whether such mutants can arise in nontransgenic plants that may act as reservoirs and (ii) whether a suboptimal expression level of the transgene, resulting in subinhibitory concentrations of the amiR, would favor the emergence of escape mutants. To address the first issue, we experimentally evolved independent lineages of Turnip mosaic virus (TuMV) (family Potyviridae) in fully susceptible wild-type Arabidopsis thaliana plants and then simulated the spillover of the evolving virus to fully resistant A. thaliana transgenic plants. To address the second issue, the evolution phase took place with transgenic plants that expressed the amiR at subinhibitory concentrations. Our results show that TuMV populations replicating in susceptible hosts accumulated resistance-breaking alleles that resulted in the overcoming of the resistance of fully resistant plants. The rate at which resistance was broken was 7 times higher for TuMV populations that experienced subinhibitory concentrations of the antiviral amiR. A molecular characterization of escape alleles showed that they all contained at least one nucleotide substitution in the target sequence, generally a transition of the G-to-A and C-to-U types, with many instances of convergent molecular evolution. To better understand the viral population dynamics taking place within each host, as well as to evaluate relevant population genetic parameters, we performed in silico simulations of the experiments. Together, our results contribute to the rational management of amiR-based antiviral resistance in plants.

Fig. 1.

(A) Schematic representation of the experimental design. For illustrative purposes we show only one of the WT A. thaliana-evolved lineages. The same protocol was repeated for the 10-4 lineages, with the exception that serial passages were performed on A. thaliana 10-4 transgenic plants. In the illustrated example, resistance breaking occurred at passage 2 (note symptoms in the corresponding 12-4 plants). (B) Schematic diagram of the in silico simulation model. (a) Each lineage was considered a population of bit-strings containing the 21 bits of the target region plus 10 loci, each corresponding to the different cistrons in the TuMV genome. The model simulated within-host viral replication with mutation and bottleneck transmission between passages. For the simulations of virus evolution in WT A. thaliana plants, we did not consider target-specific degradation of strings, while for simulating the evolution in 10-4 plants, we included a degradation probability, ε, for strings with a WT target sequence. (b) Digital genome of TuMV where the target sequence has been explicitly considered.

Fig. 2.

Pattern of amiR159-HCPro accumulation in the partially resistant transgenic lineage 10-4. (A) Curve of amiR159-HCPro accumulation in the leaf inoculated in the pathogenicity tests (units of picograms of amiR159-HCPro per nanogram of total plant RNA). The dashed line represents the fit to a two-parameter exponential growth model (R² = 0.990; F_1,4 = 405.167; P < 0.001). (B) Pattern of amiR159-HCPro accumulation in six leaves that differ in their developmental stages from four different plants (units of amiR159-HCPro molecules per nanogram of total plant RNA). Each plant is represented by a different color. In all cases, error bars represent ±1 SEM.

Fig. 3.

Cumulative frequency of lineages capable of escaping from amiR159-HCPro resistance. The black line corresponds to the lineages evolved in WT A. thaliana plants. The red line corresponds to the lineages evolved in partially resistant A. thaliana 10-4 plants. The ability of evolving TuMV populations to escape from amiR159-HCPro was evaluated in 12-4 plants that were fully resistant to the ancestral TuMV genotype. A population was considered to be able to escape from resistance when at least one 12-4 plant was infected.

Fig. 4.

Distribution of mutations in escape viruses along the amiR159-HCPro target sequence. Black bars correspond to the frequency of mutations that arose in WT A. thaliana plants; white bars correspond to those observed for the 10-4 transgenic line.

Fig. 5.

Results of the simulation studies for the set of parameters that showed the best fit to data shown in Fig. 3. (A) Simulation results for the WT A. thaliana-evolved TuMV lineages. (B) Simulation results for the TuMV lineages evolved in partially resistant 10-4 plants. The red dots correspond to the best-fitting trajectory obtained from the most optimized parameter set. Red bars indicate the standard deviations among 10³ runs of the simulation model using the best-fitting parameters.