• Energy Research

Senescence is the process that marks the end of a leaf's lifespan. As it progresses, the massive macromolecular catabolism dismantles the chloroplasts and, consequently, decreases the photosynthetic capacity of these organs. Thus, senescence manipulation is a strategy to improve plant yield by extending the leaf's photosynthetically active window of time. However, it remains to be addressed if this approach can improve fleshy fruit production and nutritional quality. One way to delay senescence initiation is by regulating key transcription factors (TFs) involved in triggering this process, such as the NAC TF ORESARA1 (ORE1). Here, three senescence-related NAC TFs from tomato (Solanum lycopersicum) were identified, namely SlORE1S02, SlORE1S03, and SlORE1S06. All three genes were shown to be responsive to senescence-inducing stimuli and posttranscriptionally regulated by the microRNA miR164 Moreover, the encoded proteins interacted physically with the chloroplast maintenance-related TF SlGLKs. This characterization led to the selection of a putative tomato ORE1 as target gene for RNA interference knockdown. Transgenic lines showed delayed senescence and enhanced carbon assimilation that, ultimately, increased the number of fruits and their total soluble solid content. Additionally, the fruit nutraceutical composition was enhanced. In conclusion, these data provide robust evidence that the manipulation of leaf senescence is an effective strategy for yield improvement in fleshy fruit-bearing species.

Abstract Agaves have been used for centuries as a feedstock in dryland areas for fibers, food, and beverages, and have enormous potential for biofuel production. Brazil is the world's largest producer of Agave fiber (sisal). However, since the development of synthetic fibers, the national investment in Agave research has decreased drastically, leading to the cessation of the country's breeding programs. What is left of the Brazilian elite cultivars were planted at a germplasm bank in the middle of the semiarid. Surprisingly, after 7 years of abandonment, the plants were still healthy and did not show any clear signs of stress. Here, we aimed to investigate how these plants managed to cope with this environment and the molecular basis of their biomass traits. We assembled the transcriptomic atlas of Agave sisalana, Agave fourcroydes, and Agave hybrid 11648 ((A. amaniensis x A. angustifolia) x A. amaniensis). We observed that the cultivars activated a highly overlapping set of stress-response genes, which were the most expressed transcripts. Also, raffinose was detected at high concentrations, possibly acting as an osmolyte, though differences at its biosynthesis have been found depending on cultivar. Finally, we observed differences in recalcitrance that could be attributed to lignin composition and its biosynthetic pathway. Our data contribute new insights that can help molecular breeders to correspond to emerging expectations for Agave as biorenewables feedstocks for dryland areas.

SummaryCrassulacean acid metabolism (CAM) is a specialized mode of photosynthesis that features nocturnal CO2 uptake, facilitates increased water‐use efficiency (WUE), and enables CAM plants to inhabit water‐limited environments such as semi‐arid deserts or seasonally dry forests. Human population growth and global climate change now present challenges for agricultural production systems to increase food, feed, forage, fiber, and fuel production. One approach to meet these challenges is to increase reliance on CAM crops, such as Agave and Opuntia, for biomass production on semi‐arid, abandoned, marginal, or degraded agricultural lands. Major research efforts are now underway to assess the productivity of CAM crop species and to harness the WUE of CAM by engineering this pathway into existing food, feed, and bioenergy crops. An improved understanding of CAM has potential for high returns on research investment. To exploit the potential of CAM crops and CAM bioengineering, it will be necessary to elucidate the evolution, genomic features, and regulatory mechanisms of CAM. Field trials and predictive models will be required to assess the productivity of CAM crops, while new synthetic biology approaches need to be developed for CAM engineering. Infrastructure will be needed for CAM model systems, field trials, mutant collections, and data management.