New Phytologist最新文献

RNA-dependent RNA Polymerases (RdRPs) synthesize double-stranded RNA (dsRNA) from a single-stranded RNA (ssRNA) template. In plants, dsRNAs produced by RdRPs can be further processed into small interfering RNA (siRNAs) with different lengths, ranging from 21 to 24 nucleotides (nt). These siRNAs play a pivotal role in various biological processes, including antiviral responses, transposable elements silencing, DNA methylation, and the regulation of plant reproduction and development. Recent research has reported significant progress in uncovering the molecular mechanisms of plant RNA-DEPENDENT RNA POLYMERASE 2 (RDR2), a representative RdRP involved in the RNA-directed DNA methylation (RdDM) pathway. These discoveries provide a molecular basis underlying the principles of RdRP function and offer insights into potential advancements in crop breeding and antiviral defense strategies.

In the marine environment, seaweeds (i.e. marine macroalgae) provide a wide range of ecological services and economic benefits. Like land plants, seaweeds do not provide these services in isolation, rather they rely on their associated microbial communities, which together with the host form the seaweed holobiont. However, there is a poor understanding of the mechanisms shaping these complex seaweed-microbe interactions, and of the evolutionary processes underlying these interactions. Here, we identify the current research challenges and opportunities in the field of seaweed holobiont biology. We argue that identifying the key microbial partners, knowing how they are recruited, and understanding their specific function and their relevance across all seaweed life history stages are among the knowledge gaps that are particularly important to address, especially in the context of the environmental challenges threatening seaweeds. We further discuss future approaches to study seaweed holobionts, and how we can apply the holobiont concept to natural or engineered seaweed ecosystems.

The globally changing climatic condition is increasing the incidences of drought in several parts of the world. This is predicted and already shown to not only impact plant growth and flower development, but also plant-pollinator interactions and the pollination success of entomophilous plants. However, there is a large gap in our understanding of how drought affects the different flowers and pollen transfer among flowers in sexually polymorphic species. Here, we evaluated in monoecious Styrian oil pumpkin, and separately for female and male flowers, the responses of drought stress on flower production, petal size, nectar, floral scent and visitation by bumblebee pollinators. Drought stress adversely affected all floral traits studied, except floral scent. Although both flower sexes were adversely affected by drought stress, the effects were more severe on female flowers, with most of the female flowers even aborted before opening. The drought had negative effects on floral visitation by the pollinators, which generally preferred female flowers. Overall, our study highlights that the two flower sexes of a monoecious plant species are differently affected by drought stress and calls for further investigations to better understand the cues used by the pollinators to discriminate against male flowers and against flowers of drought-stressed plants.

Forests face many threats. While traditional breeding may be too slow to deliver well-adapted trees, genomic selection (GS) can accelerate the process. We describe a comprehensive study of GS from proof of concept to operational application in western redcedar (WRC, Thuja plicata). Using genomic data, we developed models on a training population (TrP) of trees to predict breeding values (BVs) in a target seedling population (TaP) for growth, heartwood chemistry, and foliar chemistry traits. We used cross-validation to assess prediction accuracy (PACC) in the TrP; we also validated models for early-expressed foliar traits in the TaP. Prediction accuracy was high across generations, environments, and ages. PACC was not reduced to zero among unrelated individuals in TrP and was only slightly reduced in the TaP, confirming strong linkage disequilibrium and the ability of the model to generate accurate predictions across breeding generations. Genomic BV predictions were correlated with those from pedigree but displayed a wider range of within-family variation due to the ability of GS to capture the Mendelian sampling term. Using predicted TaP BVs in multi-trait selection, we functionally implemented and integrated GS into an operational tree-breeding program.