pBAR–H3.2, a native-optimized binary vector to bypass transgene silencing in alfalfa

Abstract

Alfalfa is the main forage worldwide due to its high biomass production, excellent nutritional qualities and adaptation to a wide range of environments (Singer et al. 2018). Besides, due to its ability to grow without nitrogen fertilizers derived from fossil fuels and conditions of long-duration perennial crop, alfalfa is a natural candidate for large production of renewable raw materials and vaccines at extremely low cost (Aguirreburualde et al. 2013; Saruul et al. 2002). However, the potential impact of alfalfa in agroindustrial processes is limited by strong transgene silencing. In the absence of genetic tools to bypass this constraint, the identification of alfalfa events with suitable transgene expression for commercial uses (e.g., high expression of transgenic traits) requires the production and analysis of a large number (e.g., 2000–3000) of transgenic events (Barros et al. 2019; Jozefkowicz et al. 2018; McCaslin et al. 2002). Naturally, this is an expensive empirical approach restricted to projects with high budget.