No abstract

Significantly improved crop varieties are urgently needed to feed the rapidly growing human population under changing climates. While genome sequence information and excellent genomic tools are in place for major crop species, the systematic quantification of phenotypic traits or components thereof in a high-throughput fashion remains an enormous challenge. In order to help bridge the genotype to phenotype gap, we developed a comprehensive framework for highthroughput phenotype data analysis in plants, which enables the extraction of an extensive list of phenotypic traits from nondestructive plant imaging over time. As a proof of concept, we investigated the phenotypic components of the drought responses of 18 different barley (Hordeum vulgare) cultivars during vegetative growth. We analyzed dynamic properties of trait expression over growth time based on 54 representative phenotypic features. The data are highly valuable to understand plant development and to further quantify growth and crop performance features. We tested various growth models to predict plant biomass accumulation and identified several relevant parameters that support biological interpretation of plant growth and stress tolerance. These image-based traits and model-derived parameters are promising for subsequent genetic mapping to uncover the genetic basis of complex agronomic traits. Taken together, we anticipate that the analytical framework and analysis results presented here will be useful to advance our views of phenotypic trait components underlying plant development and their responses to environmental cues.

The centromeric histone H3 variant cenH3 is an essential centromeric protein required for assembly, maintenance, and proper function of kinetochores during mitosis and meiosis. We identified a KINETOCHORE NULL2 (KNL2) homolog in Arabidopsis thaliana and uncovered features of its role in cenH3 loading at centromeres. We show that Arabidopsis KNL2 colocalizes with cenH3 and is associated with centromeres during all stages of the mitotic cell cycle, except from metaphase to mid-anaphase. KNL2 is regulated by the proteasome degradation pathway. The KNL2 promoter is mainly active in meristematic tissues, similar to the cenH3 promoter. A knockout mutant for KNL2 shows a reduced level of cenH3 expression and reduced amount of cenH3 protein at chromocenters of meristematic nuclei, anaphase bridges during mitosis, micronuclei in pollen tetrads, and 30% seed abortion. Moreover, knl2 mutant plants display reduced expression of suppressor of variegation 3-9 homologs2, 4, and 9 and reduced DNA methylation, suggesting an impact of KNL2 on the epigenetic environment for centromere maintenance.

SUMMARYHeterosis-associated cellular and molecular processes were analyzed in seeds and seedlings of Arabidopsis thaliana accessions Col-0 and C24 and their heterotic hybrids. Microscopic examination revealed no advantages in terms of hybrid mature embryo organ sizes or cell numbers. Increased cotyledon sizes were detectable 4 days after sowing. Growth heterosis results from elevated cell sizes and numbers, and is well established at 10 days after sowing. The relative growth rates of hybrid seedlings were most enhanced between 3 and 4 days after sowing. Global metabolite profiling and targeted fatty acid analysis revealed maternal inheritance patterns for a large proportion of metabolites in the very early stages. During developmental progression, the distribution shifts to dominant, intermediate and heterotic patterns, with most changes occurring between 4 and 6 days after sowing. The highest incidence of heterotic patterns coincides with establishment of size differences at 4 days after sowing. In contrast, overall transcript patterns at 4, 6 and 10 days after sowing are characterized by intermediate to dominant patterns, with parental transcript levels showing the largest differences. Overall, the results suggest that, during early developmental stages, intermediate gene expression and higher metabolic activity in the hybrids compared to the parents lead to better resource efficiency, and therefore enhanced performance in the hybrids.

Phenotyping large numbers of genotypes still represents the rate-limiting step in many plant genetic experiments and in breeding. To address this issue, novel automated phenotyping technologies have been developed. We investigated for a core set of barley cultivars if high-throughput image analysis can help to dissect vegetative biomass accumulation in response to two different watering regimes under semi-controlled greenhouse conditions. We found that experiments, treatments, genotypes and genotype by environment interaction (G × E) can be characterized at any time point by certain digital traits. Biomass accumulation under control and stress conditions was highly heritable. Growth model-derived maximum vegetative biomass (K max), inflection point (I) and regrowth rate (k) were identified as promising candidate traits for genome-wide association studies. Drought stress symptoms can be visualized, dissected and modelled. Especially the highly heritable regrowth rate, which had the biggest influence on biomass accumulation in stress treatment, seems promising for future studies to improve drought tolerance in different crop species. A proof of concept study revealed potential correlations between digital traits obtained from pot experiments under greenhouse conditions and agronomic traits from field experiments. Overall, non-invasive, imaging-based phenotyping platforms under greenhouse conditions offer excellent possibilities for trait discovery, trait development and industrial applications.