Carotenoids are isoprenoid pigments synthesized by all photosynthetic organisms and many heterotrophic microorganisms. They are equipped with a conjugated double-bond system that builds the basis for their role in harvesting light energy and in protecting the cell from photo-oxidation. In addition, the carotenoids polyene makes them susceptible to oxidative cleavage, yielding carbonyl products called apocarotenoids. This oxidation can be catalyzed by carotenoid cleavage dioxygenases or triggered nonenzymatically by reactive oxygen species. The group of plant apocarotenoids includes important phytohormones, such as abscisic acid and strigolactones, and signaling molecules, such as β-cyclocitral. Abscisic acid is a key regulator of plant's response to abiotic stress and is involved in different developmental processes, such as seed dormancy. Strigolactone is a main regulator of plant architecture and an important signaling molecule in the plant-rhizosphere communication. β-Cyclocitral, a volatile derived from β-carotene oxidation, mediates the response of cells to singlet oxygen stress. Besides these wellknown examples, recent research unraveled novel apocarotenoid growth regulators and suggests the presence of yet unidentified ones. In this review, we describe the biosynthesis and biological functions of established regulatory apocarotenoids and touch on the recently identified anchorene and zaxinone, with emphasis on their role in plant growth, development, and stress response.

Strigolactones (SLs) are a plant hormone inhibiting shoot branching/tillering and a rhizospheric, chemical signal that triggers seed germination of the noxious root parasitic plant Striga and mediates symbiosis with beneficial arbuscular mycorrhizal fungi. Identifying specific roles of canonical and noncanonical SLs, the two SL subfamilies, is important for developing Striga -resistant cereals and for engineering plant architecture. Here, we report that rice mutants lacking canonical SLs do not show the shoot phenotypes known for SL-deficient plants, exhibiting only a delay in establishing arbuscular mycorrhizal symbiosis, but release exudates with a significantly decreased Striga seed–germinating activity. Blocking the biosynthesis of canonical SLs by TIS108, a specific enzyme inhibitor, significantly lowered Striga infestation without affecting rice growth. These results indicate that canonical SLs are not the determinant of shoot architecture and pave the way for increasing crop resistance by gene editing or chemical treatment.

The plant hormones strigolactones (SLs) regulate shoot branching and mediate the communication with symbiotic mycorrhizal fungi, but also with noxious root parasitic weeds, such as Striga spp. SLs derive from carlactone (CL) and are divided structurally into canonical and non-canonical SLs. However, the questions about particular biological functions of the two groups and the identification of the SL that inhibits shoot branching are still unanswered, hampering targeted modification of SL pattern towards improving plant architecture and resistance against Striga. Here, we reported that 4-deoxyorobanchol (4DO) and orobanchol, the two canonical SLs in rice, do not have major role in determining rice shoot architecture. CRISPR/Cas9 mediated Osmax1-900 mutants, lacking these two SLs, do not show the high tillering and dwarf phenotype typical for SL-deficient plants. However, the absence of 4DO and orobanchol in root exudates significantly decreased their capability in inducing Striga seed germination, while caused only a delay in root colonization by mycorrhizal fungi. To confirm the genetic evidence, we used the SL-biosynthesis inhibitor TIS108. Our results showed that TIS108 is a MAX1-specific inhibitor that lowers 4DO and orobanchol synthesis, conferring a resistance to Striga without a severe impact on rice architecture. Hence, our work uncovers the specific function of canonical SLs as rhizospheric signals and paves the way for establishing chemical and genetic based approaches for combating the root parasitic weeds, by targeted depletion of their release.

Witchweeds (Striga spp.) and broomrapes (Orobanchaceae and Phelipanche spp.) are root parasitic plants that infest many crops in warm and temperate zones, causing enormous yield losses and endangering global food security. Seeds of these obligate parasites require rhizospheric, host-released stimulants to germinate, which opens up possibilities for controlling them by applying specific germination inhibitors or synthetic stimulants that induce lethal germination in host’s absence. To determine their effect on germination, root exudates or synthetic stimulants/inhibitors are usually applied to parasitic seeds in in vitro bioassays, followed by assessment of germination ratios. Although these protocols are very sensitive, the germination recording process is laborious, representing a challenge for researchers and impeding high-throughput screens. Here, we developed an automatic seed census tool to count and discriminate germinated from non-germinated seeds. We combined deep learning, a powerful data-driven framework that can accelerate the procedure and increase its accuracy, for object detection with computer vision latest development based on the Faster R-CNN algorithm. Our method showed an accuracy of 94% in counting seeds of Striga hermonthica and reduced the required time from ˜5 minutes to 5 seconds per image. Our proposed software, SeedQuant, will be of great help for seed germination bioassays and enable high-throughput screening for germination stimulants/inhibitors. ​SeedQuant is an open-source software that can be further trained to count different types of seeds for research purposes.

With increasing throughput in both the generation and phenotyping of mutant lines in plants, it is important to have an efficient and reliable genotyping method. Traditional workflows, still commonly used in many labs, have time-consuming and expensive steps, such as DNA purification, cloning and growing E. coli cultures. We propose an alternative workflow where these steps are bypassed, using Phire polymerase on fresh plant tissue, and ExoProStar treatment as preparation for sequencing. We generated CRISPR-Cas9 mutants for ZAS (ZAXINONE SYNTHASE) in rice with two guide RNAs. Using both a traditional workflow and our proposed workflow, we genotyped nine T1 plants. To interpret the sequencing output, which is often complex in CRISPR-generated mutants, we used free online automatic analysis systems and compared the results. Our proposed workflow produces results of the same quality as the old workflow, but in 1 day instead of 3 days and about 35 times cheaper. This workflow also consists of fewer steps and reduces the risk of cross contamination and mistakes. Furthermore, the automated sequence analysis packages are mostly accurate and could easily be used for bulk analysis. Based on these advantages, we encourage academic and commercial labs conducting genotyping to consider switching over to our proposed workflow.