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.

Summary 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.

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.

The present paper proposes a new method for hiding any encrypted secret message inside a text/ASCII or Microsoft word document file, by manipulating the blank/white space characters of a cover file. Initially the secret message is encrypted using Modified Generalized Vernam Cipher Method (MGVCM) proposed by Nath et. al. For hiding secret message inside any ASCII file we propose a new method in which the bits of each character of secret message file is inserted in place of eight randomly selected blank space characters of the cover file. For inserting bit-0 we choose one blank space inside the cover file and to embed bit-1 we convert the blank space to ASCII code 160 and this is will show as blank in the screen and while printing in paper also. To embed bit-0 and bit-1 in cover file we select the blank spaces from cover file in random manner. The randomly selected blank characters are read from cover file correspond to positions of a shuffled offset matrix starting from a certain base address in cover file. The offset matrix is randomized using the randomization method of the previously published MSA encryption algorithm. The randomized embedding of message in a cover file gives an additional layer of security over the encryption.

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