MADS-box genes have a wide range of functions in plant reproductive development and grain production. The ABCDE model of floral organ development shows that MADS-box genes are central players in these events in dicotyledonous plants but the applicability of this model remains largely unknown in many grass crops. Here, we show that transcript analysis of all MIKCc MADS-box genes through barley (Hordeum vulgare L.) inflorescence development reveals co-expression groups that can be linked to developmental events. Thirty-four MIKCc MADS-box genes were identified in the barley genome and single-nucleotide polymorphism (SNP) scanning of 22,626 barley varieties revealed that the natural variation in the coding regions of these genes is low and the sequences have been extremely conserved during barley domestication. More detailed transcript analysis showed that MADS-box genes are generally expressed at key inflorescence developmental phases and across various floral organs in barley, as predicted by the ABCDE model. However, expression patterns of some MADS genes, for example HvMADS58 (AGAMOUS subfamily) and HvMADS34 (SEPALLATA subfamily), clearly deviate from predicted patterns. This places them outside the scope of the classical ABCDE model of floral development and demonstrates that the central tenet of antagonism between A- and C-class gene expression in the ABC model of other plants does not occur in barley. Co-expression across three correlation sets showed that specifically grouped members of the barley MIKCc MADS-box genes are likely to be involved in developmental events driving inflorescence meristem initiation, floral meristem identity and floral organ determination. Based on these observations, we propose a potential floral ABCDE working model in barley, where the classic model is generally upheld, but that also provides new insights into the role of MIKCc MADS-box genes in the developing barley inflorescence.

The rice Zaxinone Synthase (ZAS) gene encodes a carotenoid cleavage dioxygenase (CCD) that forms the apocarotenoid growth regulator zaxinone in vitro. Here, we generated and characterized constitutive ZAS‐overexpressing rice lines, to better understand ZAS role in determining zaxinone content and regulating growth and architecture. ZAS overexpression enhanced endogenous zaxinone level, promoted root growth and increased the number of productive tillers, leading to about 30% higher grain yield per plant. Hormone analysis revealed a decrease in strigolactone (SL) content, which we confirmed by rescuing the high‐tillering phenotype through application of a SL analogue. Metabolomics analysis revealed that ZAS overexpressing plants accumulate higher amounts of monosaccharide sugars, in line with transcriptome analysis. Moreover, transgenic plants showed higher carbon (C) assimilation rate and elevated root phosphate, nitrate and sulphate level, enhancing the tolerance towards low phosphate (Pi). Our study confirms ZAS as an important determinant of rice growth and architecture and shows that ZAS regulates hormone homoeostasis and a combination of physiological processes to promote growth and grain yield, which makes this gene an excellent candidate for sustainable crop improvement.

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.