BREEDIT: a multiplex genome editing strategy to improve complex quantitative traits in maize

Ensuring food security for an ever-growing global population while adapting to climate change is the main challenge for agriculture in the 21st century. Although new technologies are being applied to tackle this problem, we are approaching a plateau in crop improvement using conventional breeding. Recent advances in CRISPR/Cas9-mediated gene engineering have paved the way to accelerate plant breeding to meet this increasing demand. However, many traits are governed by multiple small-effect genes operating in complex interactive networks. Here, we present the gene discovery pipeline BREEDIT, which combines multiplex genome editing of whole gene families with crossing schemes to improve complex traits such as yield and drought tolerance. We induced gene knockouts in 48 growth-related genes into maize (Zea mays) using CRISPR/Cas9 and generated a collection of over 1,000 gene-edited plants. The edited populations displayed (on average) 5%-10% increases in leaf length and up to 20% increases in leaf width compared with the controls. For each gene family, edits in subsets of genes could be associated with enhanced traits, allowing us to reduce the gene space to be considered for trait improvement. BREEDIT could be rapidly applied to generate a diverse collection of mutants to identify promising gene modifications for later use in breeding programs. BREEDIT is a gene discovery pipeline that combines multiplex CRISPR/Cas9 genome editing of whole gene families with crossing schemes to improve complex quantitative traits.

Automated summary

Ensuring food security while adapting to climate change is the main challenge for agriculture in the 21st century. Recent advances in CRISPR/Cas9 gene engineering have provided a way to accelerate plant breeding to meet the increasing demand. The gene discovery pipeline BREEDIT combines multiplex genome editing with crossing schemes to improve complex traits such as yield and drought tolerance.