GRASSY TILLERS1 (GT1) and SIX-ROWED SPIKE1 (VRS1) homologs share conserved roles in growth repression.

Crop engineering and de novo domestication using gene editing are new frontiers in agriculture. However, outside of well-studied crops and model systems, prioritizing engineering targets remains challenging. Evolution can guide us, revealing genes with deeply conserved roles that have repeatedly been selected in the evolution of plant form. Homologs of the transcription factor genes GRASSY TILLERS1 (GT1) and SIX-ROWED SPIKE1 (VRS1) have repeatedly been targets of selection in domestication and evolution, where they repress growth in many developmental contexts. This suggests a conserved role for these genes in regulating growth repression. To test this, we determined the roles of GT1 and VRS1 homologs in maize (Zea mays) and the distantly related grass brachypodium (Brachypodium distachyon) using gene editing and mutant analysis. In maize, gt1; vrs1-like1 (vrl1) mutants have derepressed growth of floral organs. In addition, gt1; vrl1 mutants bore more ears and more branches, indicating broad roles in growth repression. In brachypodium, Bdgt1; Bdvrl1 mutants have more branches, spikelets, and flowers than wild-type plants, indicating conserved roles for GT1 and VRS1 homologs in growth suppression over ca. 59 My of grass evolution. Importantly, many of these traits influence crop productivity. Notably, maize GT1 can suppress growth in arabidopsis (Arabidopsis thaliana) floral organs, despite ca. 160 My of evolution separating the grasses and arabidopsis. Thus, GT1 and VRS1 maintain their potency as growth regulators across vast timescales and in distinct developmental contexts. This work highlights the power of evolution to inform gene editing in crop improvement.

Nationwide Trends in COVID-19 Cases and SARS-CoV-2 RNA Wastewater Concentrations in the United States.

Wastewater-based epidemiology has emerged as a promising technology for population-level surveillance of COVID-19. In this study, we present results of a large nationwide SARS-CoV-2 wastewater monitoring system in the United States. We profile 55 locations with at least six months of sampling from April 2020 to May 2021. These locations represent more than 12 million individuals across 19 states. Samples were collected approximately weekly by wastewater treatment utilities as part of a regular wastewater surveillance service and analyzed for SARS-CoV-2 RNA concentrations. SARS-CoV-2 RNA concentrations were normalized to pepper mild mottle virus, an indicator of fecal matter in wastewater. We show that wastewater data reflect temporal and geographic trends in clinical COVID-19 cases and investigate the impact of normalization on correlations with case data within and across locations. We also provide key lessons learned from our broad-scale implementation of wastewater-based epidemiology, which can be used to inform wastewater-based epidemiology approaches for future emerging diseases. This work demonstrates that wastewater surveillance is a feasible approach for nationwide population-level monitoring of COVID-19 disease. With an evolving epidemic and effective vaccines against SARS-CoV-2, wastewater-based epidemiology can serve as a passive surveillance approach for detecting changing dynamics or resurgences of the virus.