Gene regulatory network analysis of somatic embryogenesis identifies morphogenic genes that increase maize transformation frequency
Renema, J.; Luckicheva, S.; Verwaerde, I.; Aesaert, S.; Coussens, G.; De Block, J.; Grones, C.; Eekhout, T.; De Rybel, B.; Brew-Appiah, R. A. T.; Bagley, C. A.; Hoengenaert, L.; Vandepoele, K.; Pauwels, L.
Show abstract
Somatic embryogenesis allows a somatic plant cell to develop into an embryo, and potentially into a fertile plant. Transcription factors such as BABY BOOM can induce somatic embryogenesis when ectopically expressed and are widely used for aiding regeneration in tissue culture for transformation and gene editing of crops. Nevertheless, regeneration remains a bottleneck and alternative morphogenic genes are highly desired. Here, we co-expressed BABY BOOM and WUSCHEL2 in zygotic maize (Zea mays L.) embryos and studied gene regulatory networks in induced somatic embryos at the single-cell level. By inferring cell-type-specific regulons, we prioritized candidate regulators and confirmed functionality of four transcription factors, bHLH48, EREB152, GRF4, and HB77, for enhanced maize transformation frequency, leading to fertile, transgenic plants. Interestingly, the basic helix-loop-helix and homeodomain-leucine zipper families had previously not been associated with induced somatic embryogenesis. Our work will contribute to more efficient transformation, much needed to deliver on the promise of gene editing for agriculture.
Matching journals
The top 3 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Increased and ectopic expression of Triticum polonicum VRT-A2 underlies elongated glumes and grains in hexaploid wheat in a dosage-dependent manner 97%
- CRISPR-TSKO facilitates efficient cell type-, tissue-, or organ-specific mutagenesis in Arabidopsis 97%
- Systematic histone H4 replacement in Arabidopsis thaliana reveals a role for H4R17 in regulating flowering time 96%
Similar papers in this journal
Similar papers in this journal
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.