A persistent major mutation in canonical jasmonate signaling is embedded in an herbivory-elicited gene network.

When insect herbivores attack plants, elicitors from oral secretions and regurgitants (OS) enter wounds during feeding, eliciting defense responses. These generally require plant jasmonate (JA) signaling, specifically, a jasmonoyl-L-isoleucine (JA-Ile) burst, for their activation and are well studied in the native tobacco Nicotiana attenuata. We used intraspecific diversity captured in a 26-parent MAGIC population planted in nature and an updated genome assembly to impute natural variation in the OS-elicited JA-Ile burst linked to a mutation in the JA-Ile biosynthetic gene NaJAR4. Experiments revealed that NaJAR4 variants were associated with higher fitness in the absence of herbivores but compromised foliar defenses, with two NaJAR homologues (4 and 6) complementing each other spatially and temporally. From decade-long seed collections of natural populations, we uncovered enzymatically inactive variants occurring at variable frequencies, consistent with a balancing selection regime maintaining variants. Integrative analyses of OS-induced transcriptomes and metabolomes of natural accessions revealed that NaJAR4 is embedded in a nonlinear complex gene coexpression network orchestrating responses to OS, which we tested by silencing four hub genes in two connected coexpressed networks and examining their OS-elicited metabolic responses. Lines silenced in two hub genes (NaGLR and NaFB67) co-occurring in the NaJAR4/6 module showed responses proportional to JA-Ile accumulations; two from an adjacent module (NaERF and NaFB61) had constitutively expressed defenses with high resistance. We infer that mutations with large fitness consequences can persist in natural populations due to compensatory responses from gene networks, which allow for diversification in conserved signaling pathways and are generally consistent with predictions of an omnigene model.

Arbuscular mycorrhizal fungi-indicative blumenol-C-glucosides predict lipid accumulations and fitness in plants grown without competitors.

Hydroxy- and carboxyblumenol C-glucosides specifically accumulate in roots and leaves of plants harboring arbuscular mycorrhizal fungi (AMF). To explore blumenol function in AMF relationships, we silenced an early key-gene in blumenol biosynthesis, CCD1 (carotenoid cleavage dioxygenase 1), in the ecological model plant, Nicotiana attenuata, and analyzed whole-plant performance in comparison with control and CCaMK-silenced plants, unable to form AMF associations. Root blumenol accumulations reflected a plant's Darwinian fitness, as estimated by capsule production, and were positively correlated with AMF-specific lipid accumulations in roots, with relationships that changed as plants matured when grown without competitors. When grown with wild-type competitors, transformed plants with decreased photosynthetic capacity or increased carbon flux to roots had blumenol accumulations that predicted plant fitness and genotype trends in AMF-specific lipids, but had similar levels of AMF-specific lipids between competing plants, likely reflecting AMF-networks. We propose that when grown in isolation, blumenol accumulations reflect AMF-specific lipid allocations and plant fitness. When grown with competitors, blumenol accumulations predict fitness outcomes, but not the more complicated AMF-specific lipid accumulations. RNA-seq analysis provided candidates for the final biosynthetic steps of these AMF-indicative blumenol C-glucosides; abrogation of these steps will provide valuable tools for understanding blumenol function in this context-dependent mutualism.

An unbiased approach elucidates variation in (S)-(+)-linalool, a context-specific mediator of a tri-trophic interaction in wild tobacco.

Plant volatile organic compounds (VOCs) mediate many interactions, and the function of common VOCs is especially likely to depend on ecological context. We used a genetic mapping population of wild tobacco, Nicotiana attenuata, originating from a cross of 2 natural accessions from Arizona and Utah, separated by the Grand Canyon, to dissect genetic variation controlling VOCs. Herbivory-induced leaf terpenoid emissions varied substantially, while green leaf volatile emissions were similar. In a field experiment, only emissions of linalool, a common VOC, correlated significantly with predation of the herbivore Manduca sexta by native predators. Using quantitative trait locus mapping and genome mining, we identified an (S)-(+)-linalool synthase (NaLIS). Genome resequencing, gene cloning, and activity assays revealed that the presence/absence of a 766-bp sequence in NaLIS underlies the variation of linalool emissions in 26 natural accessions. We manipulated linalool emissions and composition by ectopically expressing linalool synthases for both enantiomers, (S)-(+)- and (R)-(-)-linalool, reported to oppositely affect M. sexta oviposition, in the Arizona and Utah accessions. We used these lines to test ovipositing moths in increasingly complex environments. The enantiomers had opposite effects on oviposition preference, but the magnitude of the effect depended strongly both on plant genetic background, and complexity of the bioassay environment. Our study reveals that the emission of linalool, a common VOC, differs by orders-of-magnitude among geographically interspersed conspecific plants due to allelic variation in a linalool synthase, and that the response of a specialist herbivore to linalool depends on enantiomer, plant genotype, and environmental complexity.

Using natural variation to achieve a whole-plant functional understanding of the responses mediated by jasmonate signaling.

The dramatic advances in our understanding of the molecular biology and biochemistry of jasmonate (JA) signaling have been the subject of several excellent recent reviews that have highlighted the phytohormonal function of this signaling pathway. Here, we focus on the responses mediated by JA signaling which have consequences for a plant's Darwinian fitness, i.e. the organism-level function of JA signaling. The most diverse module in the signaling cascade, the JAZ proteins, and their interactions with other proteins and transcription factors, allow this canonical signaling cascade to mediate a bewildering array of traits in different tissues at different times; the functional coherence of these diverse responses are best appreciated in an organismal/ecological context. From published work, it appears that jasmonates can function as the 'Swiss Army knife' of plant signaling, mediating many different biotic and abiotic stress and developmental responses that allow plants to contextualize their responses to their frequently changing local environments and optimize their fitness. We propose that a deeper analysis of the natural variation in both within-plant and within-population JA signaling components is a profitable means of attaining a coherent whole-plant functional perspective of this signaling cascade, and provide examples of this approach from the Nicotiana attenuata system.

piRNA analysis framework from small RNA-Seq data by a novel cluster prediction tool - PILFER.

With the increasing number of studies focusing on PIWI-interacting RNA (piRNAs), it is now pertinent to develop efficient tools dedicated towards piRNA analysis. We have developed a novel cluster prediction tool called PILFER (PIrna cLuster FindER), which can accurately predict piRNA clusters from small RNA sequencing data. PILFER is an open source, easy to use tool, and can be executed even on a personal computer with minimum resources. It uses a sliding-window mechanism by integrating the expression of the reads along with the spatial information to predict the piRNA clusters. We have additionally defined a piRNA analysis pipeline incorporating PILFER to detect and annotate piRNAs and their clusters from raw small RNA sequencing data and implemented it on publicly available data from healthy germline and somatic tissues. We compared PILFER with other existing piRNA cluster prediction tools and found it to be statistically more accurate and superior in many aspects such as the robustness of PILFER clusters is higher and memory efficiency is more. Overall, PILFER provides a fast and accurate solution to piRNA cluster prediction.