Effects of CRISPR/Cas9 generated drooping leaf (dl) alleles on midrib and carpel formations in Oryza sativa Nipponbare.

MAIN CONCLUSION: We generated drooping leaf rice mutants by CRISPR/Cas and identified two novel alleles with specific editing that allow underpinning of the function of the DL protein domain towards midrib and carpel formations. The DROOPING LEAF (DL) gene plays an essential role in regulating midrib formation and carpel specification in rice and other grass species, but the specific function of DL protein domains in different developmental processes is unclear. Analysis of different dl mutant alleles will allow dissecting the function of DL. Here, we generated Nipponbare rice dl mutants using CRISPR/Cas gene editing and identified two novel dl alleles with different effects on midrib formation and carpel development. Phenotypic and genotypic analysis of T0 and segregated T1 edited lines showed that while dl-51S allele (a 3 bp deletion and a serine deletion at position 51) reduces midrib sizes and produces normal carpels, the dl-50LS allele (a 6 bp deletion and a leucine-serine deletion at position 50-51) causes the lack of midribs and abnormal stigma. This result indicates that the 51-serine is important for midrib formation and the 50-leucine is essential for midrib and carpel development. These dl mutant alleles contribute to the DL gene functional analysis and to gain insights into possible modifications of leaf architecture of rice and other grass species.

Cassava root crown phenotyping using three-dimension (3D) multi-view stereo reconstruction.

Phenotypic analysis of cassava root crowns (CRCs) so far has been limited to visual inspection and very few measurements due to its laborious process in the field. Here, we developed a platform for acquiring 3D CRC models using close-range photogrammetry for phenotypic analysis. The state of the art is a low cost and easy to set up 3D acquisition requiring only a background sheet, a reference object and a camera, compatible with field experiments in remote areas. We tested different software with CRC samples, and Agisoft and Blender were the most suitable software for generating high-quality 3D models and data analysis, respectively. We optimized the workflow by testing different numbers of images for 3D reconstruction and found that a minimum of 25 images per CRC can provide high quality 3D models. Up to ten traits, including 3D crown volumes, 3D crown surface, root density, surface-to-volume ratio, root numbers, root angle, crown diameter, cylinder soil volume, CRC compactness and root length can be extracted providing novel parameters for studying cassava storage roots. We applied this platform to partial-inbred cassava populations and demonstrated that our platform provides reliable 3D CRC modelling for phenotypic analysis, analysis of genetic variances and supporting breeding selection.