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Millman, B.

Publications and source records attributed to Millman, B..

2 recordsLinked to original sources

Development of male-sterile lines of Setaria viridis to accelerate C4 model plant genetics

Setaria viridis is a diploid C4 grass in the Poaceae family, notable for its rapid life cycle of 6-8 weeks from sowing to seed--much shorter than the 4-5 months required by crops such as Zea mays and Sorghum bicolor. This fast growth makes S. viridis a valuable model for C4 crop research. Genetic crosses are essential for studying gene function, but manual crossing is labor-intensive and time-consuming. To address this, we developed a male-sterile line by targeting the S. viridis ortholog of Setaria italica NO POLLEN 1 (SiNP1), which encodes a glucose-methanol-choline oxidoreductase required for pollen exine formation. Using Cas9 and TREX2-mediated genome editing, we generated SiNP1 knockouts in both the S. viridis ME034V and A10.1 backgrounds that were fully male-sterile. Backcrossing T0 male-sterile plants to ME034V yielded a stable line homozygous for a 59 bp deletion, easily genotyped by PCR. Using this line, we developed a simple and efficient crossing protocol that eliminates the need for emasculation. This method enables a single person to perform up to 100 crosses per day--compared to 15 using traditional methods--and yields 20-32 F1 hybrid seeds per panicle with 100% genetic purity. We also quantified pollen flow and outcrossing frequencies under greenhouse conditions to develop optimal bagging strategies and prevent unintended pollination.This resource accelerates genetic research in S. viridis, enhancing its utility as a premier C4 model for mapping and functional genomics.

plant biology↗

Competition for resources during development drives allometric patterns in the grass Setaria

Plant growth and resilience is greater than the sum of its component traits, with important traits influencing one another. This interdependency makes it challenging to identify the genetic determinants of key agronomic traits, such as water use efficiency. Measuring traits such as plant height and size is possible via image analysis software, such as PlantCV, but these traits are often highly correlated. Furthermore, plant size is estimated using a 2D projection of a 3D object, which is more difficult for plants with complex body plans. To address these problems, we developed a generalizable, biologically-informed model describing the temporal coordination of semi-sequential phytomeric growth in the model grass Setaria. Our approach integrates time dependence with water usage, the growth of phytomers, and the emergence of side shoots or tillers, improving our ability to estimate both phytomer-level phenotypes and water usage traits in high-throughput. We developed new PlantCV methods to inform the Phytomeric Growth Model, and estimated parameter traits using a high-throughput phenotyping dataset of a recombinant inbred line (RIL) panel in well-watered and drought conditions. Model parameter estimates identified additional quantitative trait loci (QTL) for new traits compared to the directly measured PlantCV-derived estimates, and predicted the relationships underlying QTL control of composite traits through co-localization of model parameters to loci controlling size and water use metrics. The Phytomeric Growth Model estimates improved our ability to estimate the growth of tillers and obtain a model-based estimate of marginal water use efficiency (defined here as the ratio of biomass gained per gram of water transpired), both identified as highly influential on plant drought responses through random forest classification. Our approach demonstrates the value of integrating mechanistic modeling with high-throughput imaging to extract new information at scale.

plant biology↗