Genetic and molecular control of grain yield in maize

Systematic optimization of Cas12a base editors in wheat and maize using the ITER platform

BACKGROUND

Testing an ever-increasing number of CRISPR components is challenging when developing new genome engineering tools. Plant biotechnology has few high-throughput options to perform iterative design-build-test-learn cycles of gene-editing reagents. To bridge this gap, we develop ITER (Iterative Testing of Editing Reagents) based on 96-well arrayed protoplast transfections and high-content imaging.

RESULTS

We validate ITER in wheat and maize protoplasts using Cas9 cytosine and adenine base editors (ABEs), allowing one optimization cycle - from design to results - within 3 weeks. Given that previous LbCas12a-ABEs have low or no activity in plants, we use ITER to develop an optimized LbCas12a-ABE. We show that sequential improvement of five components - NLS, crRNA, LbCas12a, adenine deaminase, and linker - leads to a remarkable increase in activity from almost undetectable levels to 40% on an extrachromosomal GFP reporter. We confirm the activity of LbCas12a-ABE at endogenous targets in protoplasts and obtain base-edited plants in up to 55% of stable wheat transformants and the edits are transmitted to T1 progeny. We leverage these improvements to develop a highly mutagenic LbCas12a nuclease and a LbCas12a-CBE demonstrating that the optimizations can be broadly applied to the Cas12a toolbox.

CONCLUSION

Our data show that ITER is a sensitive, versatile, and high-throughput platform that can be harnessed to accelerate the development of genome editing technologies in plants. We use ITER to create an efficient Cas12a-ABE by iteratively testing a large panel of vector components. ITER will likely be useful to create and optimize genome editing reagents in a wide range of plant species.

Dissection of the Genetic Basis of Yield Traits in Line per se and Testcross Populations and Identification of Candidate Genes for Hybrid Performance in Maize

Dissecting the genetic basis of yield traits in hybrid populations and identifying the candidate genes are important for molecular crop breeding. In this study, a BC1F3:4 population, the line per se (LPS) population, was constructed by using elite inbred lines Zheng58 and PH4CV as the parental lines. The population was genotyped with 55,000 SNPs and testcrossed to Chang7-2 and PH6WC (two testers) to construct two testcross (TC) populations. The three populations were evaluated for hundred kernel weight (HKW) and yield per plant (YPP) in multiple environments. Marker-trait association analysis (MTA) identified 24 to 151 significant SNPs in the three populations. Comparison of the significant SNPs identified common and specific quantitative trait locus/loci (QTL) in the LPS and TC populations. Genetic feature analysis of these significant SNPs proved that these SNPs were associated with the tested traits and could be used to predict trait performance of both LPS and TC populations. RNA-seq analysis was performed using maize hybrid varieties and their parental lines, and differentially expressed genes (DEGs) between hybrid varieties and parental lines were identified. Comparison of the chromosome positions of DEGs with those of significant SNPs detected in the TC population identified potential candidate genes that might be related to hybrid performance. Combining RNA-seq analysis and MTA results identified candidate genes for hybrid performance, providing information that could be useful for maize hybrid breeding.