The allocation of carbon and nitrogen resources to the synthesis of plant proteins, carbohydrates, and lipids is complex and under the control of many genes; much remains to be understood about this process. QQS (Qua-Quine Starch; At3g30720), an orphan gene unique to Arabidopsis thaliana, regulates metabolic processes affecting carbon and nitrogen partitioning among proteins and carbohydrates, modulating leaf and seed composition in Arabidopsis and soybean. Here the universality of QQS function in modulating carbon and nitrogen allocation is exemplified by a series of transgenic experiments. We show that ectopic expression of QQS increases soybean protein independent of the genetic background and original protein content of the cultivar. Furthermore, transgenic QQS expression increases the protein content of maize, a C4 species (a species that uses 4-carbon photosynthesis), and rice, a proteinpoor agronomic crop, both highly divergent from Arabidopsis. We determine that QQS protein binds to the transcriptional regulator AtNF-YC4 (Arabidopsis nuclear factor Y, subunit C4). Overexpression of AtNF-YC4 in Arabidopsis mimics the QQS-overexpression phenotype, increasing protein and decreasing starch levels. NF-YC, a component of the NF-Y complex, is conserved across eukaryotes. The NF-YC4 homologs of soybean, rice, and maize also bind to QQS, which provides an explanation of how QQS can act in species where it does not occur endogenously. These findings are, to our knowledge, the first insight into the mechanism of action of QQS in modulating carbon and nitrogen allocation across species. They have major implications for the emergence and function of orphan genes, and identify a nontransgenic strategy for modulating protein levels in crop species, a trait of great agronomic significance.QQS | NF-YC4 | carbon allocation | nitrogen allocation | orphan C arbon and nitrogen allocation to plant proteins, carbohydrates, and lipids is not controlled by a single gene but by many (1). Most of the enzymes promoting accumulation of these products have been identified; however, much less is understood about the mechanisms that regulate this complex metabolic network (2-8).Arabidopsis thaliana QQS (Qua-Quine Starch; At3g30720) lacks sequence similarity to any other protein-coding genes, and is considered an orphan gene that has arisen de novo from noncoding sequence since the divergence of A. thaliana from other species (9, 10). Although orphans typically comprise 2-8% of the genome of eukaryotic and prokaryotic species, their origin and biological function have not been well-explored (11)(12)(13)(14). Proteins encoded by some orphan genes provide a defensive capability by binding to a receptor of a predator organism (11). In contrast, QQS action is endogenous (3): Overexpression of QQS in Arabidopsis increases total protein content and decreases total starch content in leaf, whereas down-regulation of QQS has the converse effect. The increased starch content in QQS RNAi (RNA interference) mutants is due to increased starch accumu...

Multiple genomic regions explain variation in the carbon fixation response to non-stress and cold stress in Sorghum bicolor, with some of these regions simultaneously controlling multiple traits.

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Openly shared low-cost electronic hardware applications, known as open electronics, have sparked a new open-source movement, with much untapped potential to advance scientific research. Initially designed to appeal to electronic hobbyists, open electronics have formed a global “maker” community and are increasingly used in science and industry. In this perspective article we review the current costs and benefits of open electronics for use in scientific research ranging from the experimental to the theoretical sciences. We discuss how user-made electronic applications can help (I) individual researchers, by increasing the customization, efficiency, and scalability of experiments, while improving data quantity and quality; (II) scientific institutions, by improving access to customizable high-end technologies, sustainability, visibility, and interdisciplinary collaboration potential; and (III) the scientific community, by improving transparency and reproducibility, helping decouple research capacity from funding, increasing innovation, and improving collaboration potential among researchers and the public. We further discuss how current barriers like poor awareness, knowledge access and time investments can be resolved by increased documentation and collaboration and provide guidelines for academics to enter this emerging field. We highlight that open electronics are a promising and powerful tool to help scientific research to become more innovative and reproducible and offers a key practical solution to improve democratic access to science.

The development of high-yielding crops with drought tolerance is necessary to increase food, feed, fiber and fuel production. Methods that create similar environmental conditions for a large number of genotypes are essential to investigate plant responses to drought in gene discovery studies. Modern facilities that control water availability for each plant remain cost-prohibited to some sections of the research community. We present an alternative cost-effective automated irrigation system scalable for a high-throughput and controlled dry-down treatment of plants. This system was tested in sorghum using two experiments. First, four genotypes were subjected to ten days of dry-down to achieve three final Volumetric Water Content (VWC) levels: drought (0.10 and 0.20 m3 m-3) and control (0.30 m3 m-3). The final average VWC was 0.11, 0.22, and 0.31 m3 m-3, respectively, and significant differences in biomass accumulation were observed between control and drought treatments. Second, 42 diverse sorghum genotypes were subjected to a seven-day dry-down treatment for a final drought stress of 0.15 m3 m-3 VWC. The final average VWC was 0.17 m3 m-3, and plants presented significant differences in photosynthetic rate during the drought period. These results demonstrate that cost-effective automation systems can successfully control substrate water content for each plant, to accurately compare their phenotypic responses to drought, and be scaled up for high-throughput phenotyping studies.