Large-scale interplant exchange of macromolecules between soybean and dodder under nutrient stresses

Parasitic plants and their hosts communicate through haustorial connections.Nutrient deficiency is a common stress for plants,yet little is known about whether and how host plants and parasites communicate during adaptation to such nutrient stresses.In this study,we used transcriptomics and proteomics to analyze how soybean(Glycine max)and its parasitizing dodder(Cuscuta australis)respond to nitrate and phosphate deficiency(-N and-P).After-N and-P treatment,the soybean and dodder plants exhibited substantial changes of transcriptome and proteome,although soybean plants showed very few transcriptional responses to-P and dodder did not show any transcriptional changes to either-N or-P.Importantly,large-scale interplant transport of mRNAs and proteins was detected.Although the mobile mRNAs only comprised at most 0.2%of the transcriptomes,the foreign mobile proteins could reach 6.8%of the total proteins,suggesting that proteins may be the major forms of interplant communications.Furthermore,the interplant mobility of macromolecules was specifically affected by the nutrient regimes and the transport of these macromolecules was very likely independently regulated.This study provides new insight into the communication between host plants and parasites under stress conditions.

Current understanding of maize and rice defense against insect herbivores

Plants have sophisticated defense systems to fend off insect herbivores. How plants defend against herbivores in dicotyledonous plants, such as Arabidopsis and tobacco, have been relatively well studied,yet little is known about the defense responses in monocotyledons. Here, we review the current understanding of rice(Oryza sativa) and maize(Zea mays) defense against insects. In rice and maize,elicitors derived from insect herbivore oral secretions or oviposition fluids activate phytohormone signaling, and transcriptomic changes mediated mainly by transcription factors lead to accumulation of defense-related secondary metabolites. Direct defenses, such as trypsin protein inhibitors in rice and benzoxazinoids in maize, have anti-digestive or toxic effects on insect herbivores. Herbivory-induced plant volatiles, such as terpenes, are indirect defenses, which attract the natural enemies of herbivores. R gene-mediated defenses against herbivores are also discussed.

Elevated CO2 differentially affects tobacco and rice defense against lepidopteran larvae via the jasmonic acid signaling pathway

Atmospheric CO_2 levels are rapidly increasing due to human activities. However, the effects of elevated CO_2(ECO_2) on plant defense against insects and the underlying mechanisms remain poorly understood. Here we show that ECO_2 increased the photosynthetic rates and the biomass of tobacco and rice plants, and the chewing lepidopteran insects Spodoptera litura and Mythimna separata gained less and more mass on tobacco and rice plants, respectively. Consistently, under ECO_2, the levels of jasmonic acid(JA), the main phytohormone controlling plant defense against these lepidopteran insects, as well as the main defense-related metabolites, were increased and decreased in insectdamaged tobacco and rice plants. Importantly, bioassaysand quantification of defense-related metabolites in tobacco and rice silenced in JA biosynthesis and perception indicate that ECO_2 changes plant resistance mainly by affecting the JA pathway. We further demonstrate that the defensive metabolites, but not total N or protein, are the main factors contributing to the altered defense levels under ECO_2. This study illustrates that ECO_2 changes the interplay between plants and insects, and we propose that crops should be studied for their resistance to the major pests under ECO_2 to predict the impact of ECO_2 on future agroecosystems.

Extensive Inter-plant Protein Transfer between Cuscuta Parasites and Their Host Plants

Cuscuta species(dodders)are holoparasites that totally rely on host plants to survive.Although various mobile proteins have been identified to travel within a plant,whether and to what extent protein transfer between Cuscuta and host plants remain unclear.We found that hundreds to more than 1500 proteins were transferred between Cuscuta and the host plants Arabidopsis and soybean,and hundreds of interplant mobile proteins were even detected in the seeds of Cuscuta and the host soybean.Different hosts bridge-connected by dodder were also found to exchange hundreds of proteins.Quantitatively,the mobile proteins represent a few to more than 10%of the proteomes of foreign plants.Using Arabidopsis plants expressing different reporter proteins,we further showed that these reporter proteins could travel between plants and,importantly,retained their activity in the foreign plants.Comparative analysis between the interplant mobile proteins and mRNAs indicated that the majority of mobile proteins were not de novo synthesized from the translocated mRNAs,but bona fide mobile proteins.We propose that large-scale inter-plant protein translocation may play an important role in the interactions between host plants and dodder and even among the dodder bridge-connected hosts.

Discriminant Models for Uncertainty Characterization in Area Class Change Categorization

Discriminant space defining area classes is an important conceptual construct for uncertainty characterization in area-class maps.Discriminant models were promoted as they can enhance consistency in area-class mapping and replicability in error modeling.As area classes are rarely completely separable in empirically realized discriminant space,where class inseparabil-ity becomes more complicated for change categorization,we seek to quantify uncertainty in area classes(and change classes)due to measurement errors and semantic discrepancy separately and hence assess their relative margins objectively.Experiments using real datasets were carried out,and a Bayesian method was used to obtain change maps.We found that there are large differences be-tween uncertainty statistics referring to data classes and information classes.Therefore,uncertainty characterization in change categorization should be based on discriminant modeling of measurement errors and semantic mismatch analysis,enabling quanti-fication of uncertainty due to partially random measurement errors,and systematic categorical discrepancies,respectively.

Comparative genomics of orobanchaceous species with different parasitic lifestyles reveals the origin and stepwise evolution of plant parasitism

Orobanchaceae is the largest family of parasiticplants,containing autotrophic and parasiticplants with all degrees of parasitism.This makes it byfar the best family for studying the origin and evolution of plant parasitism.Here we provide three high-quality genomes of orobanchaceous plants,the autotrophic Lindenbergia luchunensis and the holoparasitic plants Phelipanche aegyptiaca and Orobanche cumana.Phylogenomic analysis of these three genomes together with those previously published and the transcriptomes of other orobanchaceous species createda robust phylogeneticframework forOrobanchaceae.We found that an ancient whole-genome duplication(WGD;about 73.48million years ago),which occurred earlierthan theoriginof Orobanchaceae,mighthave contributed totheemergence of parasitism.However,no WGD events occurred in any lineage of orobanchaceous parasites except for Striga after divergence from their autotrophic common ancestor,suggesting that,in contrast with previous speculations,WGD is not associated with the emergence of holoparasitism.We detected evident convergent gene loss in all parasites within Orobanchaceae and between Orobanchaceae and dodder Cuscuta australis.The gene families in the orobanchaceous parasites showed a clear pattern of recent gains and expansions.The expanded gene families are enriched in functions related to the development of the haustorium,suggesting that recent gene family expansions may have facilitated the adaptation of orobanchaceous parasites to different hosts.This study illustrates a stepwise pattern in the evolution of parasitism in the orobanchaceous parasites and will facilitate future studieson parasitism and the control of parasitic plants in agriculture.

Geostatistical approaches to refinement of digital elevation data

Data refinement refers to the processes by which a dataset’s resolution,in particular,the spatial one,is refined,and is thus synonymous to spatial downscaling.Spatial resolution indicates measurement scale and can be seen as an index for regular data support.As a type of change of scale,data refinement is useful for many scenarios where spatial scales of existing data,desired analyses,or specific applications need to be made commensurate and refined.As spatial data are related to certain data support,they can be conceived of as support-specific realizations of random fields,suggesting that multivariate geostatistics should be explored for refining datasets from their coarser-resolution versions to the finerresolution ones.In this paper,geostatistical methods for downscaling are described,and were implemented using GTOPO30 data and sampled Shuttle Radar Topography Mission data at a site in northwest China,with the latter’s majority grid cells used as surrogate reference data.It was found that proper structural modeling is important for achieving increased accuracy in data refinement;here,structural modeling can be done through proper decomposition of elevation fields into trends and residuals and thereafter.It was confirmed that effects of semantic differences on data refinement can be reduced through properly estimating and incorporating biases in local means.