In smallholder farming systems, traditional farmer varieties of neglected and underutilized species (NUS) support the livelihoods of millions of growers and consumers. NUS combine cultural and agronomic value with local adaptation, and transdisciplinary methods are needed to fully evaluate their breeding potential. Here, we assembled and characterized the genetic diversity of a representative collection of 366 Ethiopian teff (Eragrostis tef) farmer varieties and breeding materials, describing their phylogenetic relations and local adaptation on the Ethiopian landscape. We phenotyped the collection for its agronomic performance, involving local teff farmers in a participatory variety evaluation. Our analyses revealed environmental patterns of teff genetic diversity and allowed us to identify 10 genetic clusters associated with climate variation and with uneven spatial distribution. A genome-wide association study was used to identify loci and candidate genes related to phenology, yield, local adaptation, and farmers’ appreciation. The estimated teff genomic offset under climate change scenarios highlighted an area around lake Tana where teff cropping may be most vulnerable to climate change. Our results show that transdisciplinary approaches may efficiently propel untapped NUS farmer varieties into modern breeding to foster more resilient and sustainable cropping systems.

Summary: Modern plant breeding can benefit from the allelic variation that exists in natural populations of crop wild relatives that evolved under natural selection in varying pedoclimatic conditions. In this study, next‐generation sequencing was used to generate 1.3 million genome‐wide single nucleotide polymorphisms (SNPs) on ex situ collections of Triticum urartu L., the wild donor of the A^u subgenome of modern wheat. A set of 75 511 high‐quality SNPs were retained to describe 298 T. urartu accessions collected throughout the Fertile Crescent. Triticum urartu showed a complex pattern of genetic diversity, with two main genetic groups distributed sequentially from west to east. The incorporation of geographical information on sampling points showed that genetic diversity was correlated to the geographical distance (R² = 0.19) separating samples from Jordan and Lebanon, from Syria and southern Turkey, and from eastern Turkey, Iran and Iraq. The wild emmer genome was used to derive the physical positions of SNPs on the seven chromosomes of the A^u subgenome, allowing us to describe a relatively slow decay of linkage disequilibrium in the collection. Outlier loci were described on the basis of the geographic distribution of the T. urartu accessions, identifying a hotspot of directional selection on chromosome 4A. Bioclimatic variation was derived from grid data and related to allelic variation using a genome‐wide association approach, identifying several marker–environment associations (MEAs). Fifty‐seven MEAs were associated with altitude and temperature measures while 358 were associated with rainfall measures. The most significant MEAs and outlier loci were used to identify genomic loci with adaptive potential (some already reported in wheat), including dormancy and frost resistance loci. We advocate the application of genomics and landscape genomics on ex situ collections of crop wild relatives to efficiently identify promising alleles and genetic materials for incorporation into modern crop breeding.

SUMMARY: The characterization of the genetic basis of maize (Zea mays) leaf development may support breeding efforts to obtain plants with higher vigor and productivity. In this study, a mapping panel of 197 biparental and multiparental maize recombinant inbred lines (RILs) was analyzed for multiple leaf traits at the seedling stage. RNA sequencing was used to estimate the transcription levels of 29 573 gene models in RILs and to derive 373 769 single nucleotide polymorphisms (SNPs), and a forward genetics approach combining these data was used to pinpoint candidate genes involved in leaf development. First, leaf traits were correlated with gene expression levels to identify transcript–trait correlations. Then, leaf traits were associated with SNPs in a genome‐wide association (GWA) study. An expression quantitative trait locus mapping approach was followed to associate SNPs with gene expression levels, prioritizing candidate genes identified based on transcript–trait correlations and GWAs. Finally, a network analysis was conducted to cluster all transcripts in 38 co‐expression modules. By integrating forward genetics approaches, we identified 25 candidate genes highly enriched for specific functional categories, providing evidence supporting the role of vacuolar proton pumps, cell wall effectors, and vesicular traffic controllers in leaf growth. These results tackle the complexity of leaf trait determination and may support precision breeding in maize.

The increasing frequency and intensity of extreme climate events are driving significant biodiversity shifts across ecosystems. Yet, the extent to which these climate legacies will shape the response of ecosystems to future perturbations remains poorly understood. Here, we tracked taxon and trait dynamics of rocky intertidal biofilm communities under contrasting regimes of warming (fixed vs. fluctuating) and assessed how they influenced stability dimensions in response to temperature extremes. Fixed warming enhanced the resistance of biofilm by promoting the functional redundancy of stress-tolerance traits. In contrast, fluctuating warming boosted recovery rate through the selection of fast-growing taxa at the expense of functional redundancy. This selection intensified a trade-off between stress tolerance and growth further limiting the ability of biofilm to cope with temperature extremes. Anticipating the challenges posed by future extreme events, our findings offer a forward-looking perspective on the stability of microbial communities in the face of ongoing climatic change.

Background: The cultivation of maize (Zea mays L.), one of the most important crops worldwide for food, feed, biofuels, and industrial applications, faces significant constraints due to Fusarium verticillioides, a fungus responsible for severe diseases including seedling blights, stalk rot, and ear rot. Its impact is worsened by the fact that chemical and agronomic measures used to control the infection are often inefficient. Hence, genetic resistance is considered the most reliable resource to reduce the damage. This study aims to elucidate the genetic basis of F. verticillioides resistance in maize. Results: Young seedlings of eight divergent maize lines, founders of the MAGIC population, were artificially inoculated with a F. verticillioides strain. Phenotypic analysis and transcriptome sequencing of both control and treated samples identified several hundred differentially expressed genes enriched in metabolic processes associated with terpene synthesis. A WGCNA further refined the pool of genes with potential implications in disease response and found a limited set of hub genes, encoding bZIP and MYB transcription factors, or involved in carbohydrate metabolism, solute transport processes, calcium signaling, and lipid pathways. Finally, additional gene resources were provided by combining transcriptomic data with previous QTL mapping, thereby shedding light on the molecular mechanisms in the maize-F. verticillioides interaction. Conclusions: The transcriptome profiling of eight divergent MAGIC maize founder lines with contrasting levels of Fusarium verticillioides resistance combined with phenotypic analysis, clarifies the molecular mechanisms underlying the maize-F. verticillioides interaction.