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Starch serves functions that range over a timescale of minutes to years, according to the cell type from which it is derived. In guard cells, starch is rapidly mobilized by the synergistic action of β-AMYLASE1 (BAM1) and α-AMYLASE3 (AMY3) to promote stomatal opening. In the leaves, starch typically accumulates gradually during the day and is degraded at night by BAM3 to support heterotrophic metabolism. During osmotic stress, starch is degraded in the light by stress-activated BAM1 to release sugar and sugar-derived osmolytes. Here, we report that AMY3 is also involved in stress-induced starch degradation. Recently isolated Arabidopsis thaliana amy3 bam1 double mutants are hypersensitive to osmotic stress, showing impaired root growth. amy3 bam1 plants close their stomata under osmotic stress at similar rates as the wild type but fail to mobilize starch in the leaves. 14C labeling showed that amy3 bam1 plants have reduced carbon export to the root, affecting osmolyte accumulation and root growth during stress. Using genetic approaches, we further demonstrate that abscisic acid controls the activity of BAM1 and AMY3 in leaves under osmotic stress through the AREB/ABF-SnRK2 kinase-signaling pathway. We propose that differential regulation and isoform subfunctionalization define starch-adaptive plasticity, ensuring an optimal carbon supply for continued growth under an ever-changing environment.

[beta]-Amylases (BAMs) are a multigene family of glucan hydrolytic enzymes playing a key role not only for plant biology but also for many industrial applications, such as the malting process in the brewing and distilling industries. BAMs have been extensively studied in Arabidopsis thaliana where they show a surprising level of complexity in terms of specialization within the different isoforms as well as regulatory functions played by at least three catalytically inactive members. Despite the importance of BAMs and the fact that multiple BAM proteins are also present in other angiosperms, little is known about their phylogenetic history or functional relationship. Here, we examined 961 [beta]-amylase sequences from 136 different algae and land plant species, including 66 sequenced genomes and many transcriptomes. The extraordinary number and the diversity of organisms examined allowed us to reconstruct the main patterns of [beta]-amylase evolution in land plants. We identified eight distinct clades in angiosperms, which results from extensive gene duplications and sub- or neo-functionalization. We discovered a novel clade of BAM, absent in Arabidopsis, which we called BAM10. BAM10 emerged before the radiation of seed plants and has the feature of an inactive enzyme. Furthermore, we report that BAM4 - an important protein regulating Arabidopsis starch metabolism - is absent in many relevant starch-accumulating crop species, suggesting that starch degradation may be differently regulated between species. BAM proteins originated sometime more than 400 million years ago and expanded together with the differentiation of plants into organisms of increasing complexity. Our phylogenetic analyses provide essential insights for future functional studies of this important class of storage glucan hydrolases and regulatory proteins.

Background β-Amylases (BAMs) are a multigene family of glucan hydrolytic enzymes playing a key role not only for plant biology but also for many industrial applications, such as the malting process in the brewing and distilling industries. BAMs have been extensively studied in Arabidopsis thaliana where they show a surprising level of complexity in terms of specialization within the different isoforms as well as regulatory functions played by at least three catalytically inactive members. Despite the importance of BAMs and the fact that multiple BAM proteins are also present in other angiosperms, little is known about their phylogenetic history or functional relationship. Results Here, we examined 961 β-amylase sequences from 136 different algae and land plant species, including 66 sequenced genomes and many transcriptomes. The extraordinary number and the diversity of organisms examined allowed us to reconstruct the main patterns of β-amylase evolution in land plants. We identified eight distinct clades in angiosperms, which results from extensive gene duplications and sub- or neo-functionalization. We discovered a novel clade of BAM, absent in Arabidopsis, which we called BAM10. BAM10 emerged before the radiation of seed plants and has the feature of an inactive enzyme. Furthermore, we report that BAM4 – an important protein regulating Arabidopsis starch metabolism – is absent in many relevant starch-accumulating crop species, suggesting that starch degradation may be differently regulated between species. Conclusions BAM proteins originated sometime more than 400 million years ago and expanded together with the differentiation of plants into organisms of increasing complexity. Our phylogenetic analyses provide essential insights for future functional studies of this important class of storage glucan hydrolases and regulatory proteins.

The LCZ4r is a novel toolkit designed to streamline Local Climate Zones (LCZ) classification and Urban Heat Island (UHI) analysis. Built on the open-source R statistical programming platform, the LCZ4r package aims to improve the usability of the LCZ framework for climate and environment researchers. The suite of LCZ4r functions is categorized into general and local functions ( https://bymaxanjos.github.io/LCZ4r/index.html ). General functions enable users to quickly extract LCZ maps for any landmass of the world at different scales, without requiring extensive GIS expertise. They also generate a series of urban canopy parameter maps, such as impervious fractions, albedo, and sky view factor, and calculate LCZ-related area fractions. Local functions require measurement data to perform advanced geostatistical analysis, including time series, thermal anomalies, air temperature interpolation, and UHI intensity. By integrating LCZ data with interpolation techniques, LCZ4r enhances air temperature modeling, capturing well-defined thermal patterns, such as vegetation-dominated areas, that traditional methods often overlook. The openly available and reproducible R-based scripts ensure consistent results and broad applicability, making LCZ4r a valuable tool for researchers studying the relationship between land use-cover and urban climates.

There is a need to strengthen maize (Zea mays L.) breeding strategies based on multivariate selection to obtain high‐yielding hybrids that are more stable and resilient to contrasting environmental conditions. Here, we show how the multi‐trait stability index (MTSI) can be used to select maize hybrids for mean performance and stability of multiple traits. A set of 10 traits, including grain yield (GY), yield components, and plant‐related traits with negative and positive desired selection gains (SGs), were accessed in 90 F1 hybrids conducted in multi‐environment trials. Hybrid and hybrid × location interaction effects were significant (p ≤ .001) for all analyzed traits. The MTSI provided positive gains for all the four traits that were wanted to increase (2.52% ≤ SG ≤ 4.86; mean, 3.28%), including GY (SG, 4.86%), and negative gains for all the six traits that were wanted to decrease (–20.28% ≤ SG ≤ –0.09%; mean, –6.70%), including tassel branch number (SG, –20.28%) and plant height (SG, –1.2%). We also observed desired gains for the stability of all traits. Direct and univariate selection for GY solely was not efficient to provide desired gains for all traits. The MTSI provides a unique, robust, and easy‐to‐handle selection process that allows identifying the strengths and weaknesses of hybrids. The index was found to be a powerful tool to develop better selection strategies, optimizing the use of resources and time, thus contributing to the sustainability of maize breeding programs worldwide. Core Ideas The selection of maize hybrids in multi‐environment trials was performed using the multi‐trait stability index (MTSI). Direct and univariate selection for grain yield is not efficient. The MTSI provided desired gains for both mean performance and stability of all studied traits. The MTSI allows identifying the strengths and weaknesses of hybrids graphically.

The objective of this work was to select black oat genotypes using the MGIDI for simultaneous selection, comparing it with the Smith-Hazel index. The experiment was carried out in Frederico Westphalen/RS and Pato Branco/PR, in a randomized block design, with three replications, with 9 genotypes tested. Days from emergence to flowering and maturation; cutting and plant height; number of tillers; panicle length; tiller, plant, panicle, panicle seed mass, green and dry; and seed yield were obtained. MGIDI selected the genotypes UFSMFW 2-01 and UFSMFW 2-04 for Frederico Westphalen and UFSMFW 2-07 and UFSMFW 2-04 for Pato Branco, which varied compared to the Smith-Hazel index in both environments. MGIDI was efficient in selecting the best black oat genotypes, showing desirable selection gains for most traits.

This research evaluated the agronomic performance through mixed models, and determined the genetic divergence between black oat genotypes. The experiment was carried out at Federal University of Santa Maria, Frederico Westphalen/RS. Fourteen black oat genotypes were evaluated, being 11 lines developed by Breeding Program of University, and three commercial cultivars (IAPAR 61, UPFA 21 - Moreninha and, IPR Cabocla). We evaluated quantitative traits associated to plant height, cycle, dry mass yield and seeds yield; and 19 qualitative traits, being these morphological descriptors. The results showed that lines UFSMFW 2-05 and UFSMFW 2-07 stand out with characteristics such as early cycle, higher dry mass and grain yield. Divergence analysis revealed the formation of three distinct groups, indicating the presence of variability. These results suggested the potential for the development of new cultivars of black oat, presenting early cycle and good grain yield. RESUMO: O objetivo deste trabalho foi avaliar o desempenho agronômico por meio de modelos mistos e determinar a divergência genética entre genótipos de aveia preta. O experimento foi conduzido na Universidade Federal de Santa Maria, campus de Frederico Westphalen/RS. Catorze genótipos de aveia preta foram avaliados, sendo 11 linhagens desenvolvidas pelo Programa de Melhoramento da Universidade e três cultivares comercias (IAPAR 61, UPFA 21 - Moreninha e IPR Cabocla). Foram avaliadas características agronômicas quantitativas relacionadas ao porte, ciclo e produtividade de massa seca e de sementes; e 19 características qualitativas, sendo estes descritores morfológicos. Os resultados mostraram que as linhagens UFSMFW 2-05 e UFSMFW 2-07 se destacam com características como ciclo precoce, elevada produtividade de massa seca e de sementes. A análise de divergência revelou a formação de três grupos distintos, indicando presença de variabilidade. Os resultados demonstram o potencial de desenvolvimento de novas cultivares de aveia preta, apresentando precocidade e boa produtividade de sementes.

UFSMFW 2202 is an early black oat cultivar with high dry matter and grain yield potential. When used in rotation systems, the early cycle has the immediate advantage of allowing anticipated sowing of subsequent crop. Initially, the cultivar is recommended for the North and Northwest of Rio Grande do Sul.

ABSTRACT The agronomic traits have complex quantitative inheritance, wheat breeding has a highly cost and time expending to achieve advanced lines, and new cultivars. The objective of this work was to estimate the phenotypic (rp), genotypic (rg) and environmental (re) correlation coefficients and the genetic parameters, as well as to estimate the selection gains between agronomic traits in wheat using multivariate analysis. F6 generation was carried out in a randomized block experimental design, with fifteen wheat genotypes arranged in three replications. The traits measured were days of emergence to flowering, plant height, number of tillers, spike length, number of spikelets, kernel weight and thousand kernel weight. Correlation coefficients, variance components, genetic parameters, selection gain, Euclidiana’s distance, relative contribution of traits and canonical variables were estimated. Selection based on number of tillers, kernel weight and thousand kernel weight may result in expressive selection gains. The number of fertile tillers per plant showed a significant and positive intermediate association with kernel weight and positive correlation with number of spikelets. The cycle showed greater contribution to the genetic divergence among genotypes studied. Distinct groups highlighted the genetic variability among genotypes.

Neuronal guidance proteins (NGP) were originally described in the context of axonal growth and migration. Yet recent work has demonstrated that NGPs also serve as guidance cues for immune competent cells. A crucial target receptor for NGPs during embryonic development is the neogenin receptor, however its role during acute inflammation is unknown. We report here that neogenin is abundantly expressed outside the nervous system and that animals with endogenous repression of neogenin (Neo1(-/-)) demonstrate attenuated changes of acute inflammation. Studies using functional inhibition of neogenin resulted in a significant attenuation of inflammatory peritonitis. In studies employing bone marrow chimeric animals we found the hematopoietic presence of Neo1(-/-) to be responsible for the attenuated inflammatory response. Taken together our studies suggest that the guidance receptor neogenin holds crucial importance for the propagation of an acute inflammatory response and further define mechanisms shared between the nervous and the immune system.