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Sea lettuce (Ulva spp.), with its worldwide distribution and remarkable ability to grow rapidly under various conditions, represents an important natural resource that is still under-exploited. Its biomass can be used for a wide range of applications in the food/feed, pharmaceutical, nutraceutical, biofuel, and bioremediation industries. However, knowledge of the factors affecting Ulva biomass yield and composition is far from complete. Indeed, the respective contributions of the microbiome, natural genetic variation in Ulva species, environmental conditions and importantly, the interactions between these three factors on the Ulva biomass, have been only partially elucidated. Further investigation is important for the implementation of large-scale Ulva aquaculture, which requires stable and controlled biomass composition and yields. In this review, we document Ulva biomass composition, describe the uses of Ulva biomass and we propose different strategies for developing a sustainable and profitable Ulva aquaculture industry.

Plants display enormous diversity in their metabolism. Although the biosynthesis and function of the myriads of plant metabolites has been studied for decades, we have little understanding of the interactions between metabolites, metabolite signaling, interactions with development and the role of metabolism in genotype-to-phenotype relationships. Technologies for the analysis of metabolites have made tremendous progress in recent years, both in terms of the number of metabolites that are identified and of throughput. Recent developments allow the construction of metabolic networks, and study of the role of these networks in plant growth and development. In this review, we discuss what types of information can be obtained from measurements of metabolites and what requirements they have with respect comprehensiveness of coverage and precision of identification and quantification, and outline procedures that can be implemented to validate the measurements. We then discuss what sorts of perturbations can be used to disturb metabolic networks, including environmental and physiological treatments, chemicals, reverse genetics and the use of natural genetic diversity.

Incidence of natural light stress renders it important to enhance our understanding of the mechanisms by which plants protect themselves from harmful effects of UV-B irradiation, as this is critical for fitness of land plant species. Here we describe natural variation of a class of phenylacylated-flavonols (saiginols), which accumulate to high levels in floral tissues of Arabidopsis . They were identified in a subset of accessions, especially those deriving from latitudes between 16° and 43° North. Investigation of introgression line populations using metabolic and transcript profiling, combined with genomic sequence analysis, allowed the identification of flavonol-phenylacyltransferase 2 ( FPT2 ) that is responsible for the production of saiginols and conferring greater UV light tolerance in planta . Furthermore, analysis of polymorphism within the FPT duplicated region provides an evolutionary framework of the natural history of this locus in the Brassicaceae. Protection from UV-B is critical for land plant survival. Here Tohge et al. show that saiginols, a novel class of flavonols that efficiently absorb UV-B, accumulate in Arabidopsis accessions collected from high irradiance regions and identify a flavonol phenylacyltransferase gene required for saiginol production.

Growth and carbon (C) fluxes are severely altered in plants exposed to soil water deficit. Correspondingly, it has been suggested that plants under water deficit suffer from C shortage. In this study, we test this hypothesis in Arabidopsis (Arabidopsis thaliana) by providing an overview of the responses of growth, C balance, metabolites, enzymes of the central metabolism, and a set of sugar-responsive genes to a sustained soil water deficit. The results show that under drought, rosette relative expansion rate is decreased more than photosynthesis, leading to a more positive C balance, while root growth is promoted. Several soluble metabolites accumulate in response to soil water deficit, with K⁺ and organic acids as the main contributors to osmotic adjustment. Osmotic adjustment costs only a small percentage of the daily photosynthetic C fixation. All C metabolites measured (not only starch and sugars but also organic acids and amino acids) show a diurnal turnover that often increased under water deficit, suggesting that these metabolites are readily available for being metabolized in situ or exported to roots. On the basis of 30 enzyme activities, no in-depth reprogramming of C metabolism was observed. Water deficit induces a shift of the expression level of a set of sugar-responsive genes that is indicative of increased, rather than decreased, C availability. These results converge to show that the differential impact of soil water deficit on photosynthesis and rosette expansion results in an increased availability of C for the roots, an increased turnover of C metabolites, and a low-cost C-based osmotic adjustment, and these responses are performed without major reformatting of the primary metabolism machinery.

Albrecht Melchinger and colleagues report a complementary approach to phenotype-based screening for hybrid maize. The new approach accurately predicts the combining abilities of agronomical traits based on genomic and metabolomic information comprising 56,110 SNPs and 130 metabolite measurements. Maize is both an exciting model organism in plant genetics and also the most important crop worldwide for food, animal feed and bioenergy production. Recent genome-wide association and metabolic profiling studies aimed to resolve quantitative traits to their causal genetic loci and key metabolic regulators. Here we present a complementary approach that exploits large-scale genomic and metabolic information to predict complex, highly polygenic traits in hybrid testcrosses. We crossed 285 diverse Dent inbred lines from worldwide sources with two testers and predicted their combining abilities for seven biomass- and bioenergy-related traits using 56,110 SNPs and 130 metabolites. Whole-genome and metabolic prediction models were built by fitting effects for all SNPs or metabolites. Prediction accuracies ranged from 0.72 to 0.81 for SNPs and from 0.60 to 0.80 for metabolites, allowing a reliable screening of large collections of diverse inbred lines for their potential to create superior hybrids.

The diversity of metabolites found in plants is by far greater than in most other organisms. Metabolic profiling techniques, which measure many of these compounds simultaneously, enabled investigating the regulation of metabolic networks and proved to be useful for predicting important agronomic traits. However, little is known about the genetic basis of metabolites in crops such as maize. Here, a set of 289 diverse maize inbred lines was genotyped with 56,110 SNPs and assayed for 118 biochemical compounds in the leaves of young plants, as well as for agronomic traits of mature plants in field trials. Metabolite concentrations had on average a repeatability of 0.73 and showed a correlation pattern that largely reflected their functional grouping. Genome-wide association mapping with correction for population structure and cryptic relatedness identified for 26 distinct metabolites strong associations with SNPs, explaining up to 32.0% of the observed genetic variance. On nine chromosomes, we detected 15 distinct SNP-metabolite associations, each of which explained more then 15% of the genetic variance. For lignin precursors, including p-coumaric acid and caffeic acid, we found strong associations (P values 2.7 × 10⁻¹⁰ to 3.9 × 10⁻¹⁸) with a region on chromosome 9 harboring cinnamoyl-CoA reductase, a key enzyme in monolignol synthesis and a target for improving the quality of lignocellulosic biomass by genetic engineering approaches. Moreover, lignin precursors correlated significantly with lignin content, plant height, and dry matter yield, suggesting that metabolites represent promising connecting links for narrowing the genotypephenotype gap of complex agronomic traits.

Rising demand for food and bioenergy makes it imperative to breed for increased crop yield. Vegetative plant growth could be driven by resource acquisition or developmental programs. Metabolite profiling in 94 Arabidopsis accessions revealed that biomass correlates negatively with many metabolites, especially starch. Starch accumulates in the light and is degraded at night to provide a sustained supply of carbon for growth. Multivariate analysis revealed that starch is an integrator of the overall metabolic response. We hypothesized that this reflects variation in a regulatory network that balances growth with the carbon supply. Transcript profiling in 21 accessions revealed coordinated changes of transcripts of more than 70 carbon-regulated genes and identified 2 genes (myo-inositol-1-phosphate synthase, a Kelch-domain protein) whose transcripts correlate with biomass. The impact of allelic variation at these 2 loci was shown by association mapping, identifying them as candidate lead genes with the potential to increase biomass production.

The influence of arbuscular mycorrhizal fungi (AMF), Funneliformis mosseae and Rhizophagus intraradices, on plant growth, leaf water status, chlorophyll concentration, photosynthesis, nutrient concentration, and fractal dimension (FD) characteristics of black locust (Robinia pseudoacacia L.) seedlings was studied in pot culture under well-watered, moderate drought stress, and severe drought stress treatments. Mycorrhizal seedlings had higher dry biomass, leaf relative water content (RWC), and water use efficiency (WUE) compared with non-mycorrhizal seedlings. Under all treatments, AMF colonization notably enhanced net photosynthetic rate, stomatal conductance, and transpiration rate, but decreased intercellular CO₂ concentration. Leaf chlorophyll a and total chlorophyll concentrations were higher in AM seedlings than those in non-AM seedlings although there was no significant difference between AMF species. AMF colonization improved leaf C, N, and P concentrations, but decreased C:N, C:P, and N:P ratios. Mycorrhizal seedlings had a larger FD value than non-mycorrhizal seedlings. The FD value was positively and significantly correlated to the plant growth parameters, photosynthesis, RWC, WUE, and nutrient concentration but negatively correlated to leaf/stem ratio, C:N and C:P ratios, and intercellular CO₂ concentration. We conclude that AMF lead to an improvement of growth performance of black locust seedlings under all growth conditions, including drought stress via improving leaf water status, chlorophyll concentration, photosynthesis, and nutrient uptake. Moreover, FD technology proved to be a powerful non-destructive method to characterize the effect of AMF on the physiology of host plants during drought stress.

Light quality is a key factor affecting algal growth and biomass composition, particularly pigments such as carotenoids, known for their antioxidant properties. Light-emitting diodes (LEDs) are becoming a cost-effective solution for indoor seaweed production when compared to fluorescent bulbs, allowing full control of the light spectra. However, knowledge of its effects on Ulva biomass production is still scarce. In this study, we investigated the effects of LEDs on the phenotype of an Ulva lacinulata strain, collected on the Northern Portuguese coast. Effects of white (W), green (G), red (R), and blue (B) LEDs were evaluated for growth (fresh weight and area), photosynthetic activity, sporulation, and content of pigments and antioxidant compounds. The results showed that there were no significant differences in terms of fresh weight accumulation and reduced sporulation among the tested LEDs, while W light induced the highest expansion rate. Under G, U. lacinulata attained a quicker photoacclimation, and the highest content of pigments and total antioxidant activity; but with R and W, antioxidant compounds against the specific radicals O2•− and •NO were produced in a higher content when compared to other LEDs. Altogether, this study demonstrated that it is possible to modulate the bioactive properties of U. lacinulata by using W, R, and G light, opening the path to the production of biomass tailored for specific nutraceutical applications.

The difference between the potential yield of a crop and the yield obtained by farmers—often called the yield gap—is explained by environmental cues and/or deficient management practises. Up to now, it has been mostly addressed by mitigating stresses, i.e. by improving management practises, and little by the development of more resilient varieties. However, increasing the inputs in order to tackle the yield gap is getting less and less sustainable in the context of more frequent and stronger climate events, a growing population, and increasingly limited land and input availabilities. Thus, the aim should be for a more sustainable biomass production, which involves, among other strategies, the breeding of resilient crop varieties. Melandri et al. (2019) investigated the leaf metabolic parameters associated with yield loss of 292 rice varieties submitted to drought stress in the field.