Regulators of early maize leaf development inferred from transcriptomes of laser capture microdissection (LCM)-isolated embryonic leaf cells.

The superior photosynthetic efficiency of C4 leaves over C3 leaves is owing to their unique Kranz anatomy, in which the vein is surrounded by one layer of bundle sheath (BS) cells and one layer of mesophyll (M) cells. Kranz anatomy development starts from three contiguous ground meristem (GM) cells, but its regulators and underlying molecular mechanism are largely unknown. To identify the regulators, we obtained the transcriptomes of 11 maize embryonic leaf cell types from five stages of pre-Kranz cells starting from median GM cells and six stages of pre-M cells starting from undifferentiated cells. Principal component and clustering analyses of transcriptomic data revealed rapid pre-Kranz cell differentiation in the first two stages but slow differentiation in the last three stages, suggesting early Kranz cell fate determination. In contrast, pre-M cells exhibit a more prolonged transcriptional differentiation process. Differential gene expression and coexpression analyses identified gene coexpression modules, one of which included 3 auxin transporter and 18 transcription factor (TF) genes, including known regulators of Kranz anatomy and/or vascular development. In situ hybridization of 11 TF genes validated their expression in early Kranz development. We determined the binding motifs of 15 TFs, predicted TF target gene relationships among the 18 TF and 3 auxin transporter genes, and validated 67 predictions by electrophoresis mobility shift assay. From these data, we constructed a gene regulatory network for Kranz development. Our study sheds light on the regulation of early maize leaf development and provides candidate leaf development regulators for future study.

Maize ANT1 modulates vascular development, chloroplast development, photosynthesis, and plant growth.

Arabidopsis AINTEGUMENTA (ANT), an AP2 transcription factor, is known to control plant growth and floral organogenesis. In this study, our transcriptome analysis and in situ hybridization assays of maize embryonic leaves suggested that maize ANT1 (ZmANT1) regulates vascular development. To better understand ANT1 functions, we determined the binding motif of ZmANT1 and then showed that ZmANT1 binds the promoters of millet SCR1, GNC, and AN3, which are key regulators of Kranz anatomy, chloroplast development, and plant growth, respectively. We generated a mutant with a single-codon deletion and two frameshift mutants of the ANT1 ortholog in the C4 millet Setaria viridis by the CRISPR/Cas9 technique. The two frameshift mutants displayed reduced photosynthesis efficiency and growth rate, smaller leaves, and lower grain yields than wild-type (WT) plants. Moreover, their leaves sporadically exhibited distorted Kranz anatomy and vein spacing. Conducting transcriptomic analysis of developing leaves in the WT and the three mutants we identified differentially expressed genes (DEGs) in the two frameshift mutant lines and found many down-regulated DEGs enriched in photosynthesis, heme, tetrapyrrole binding, and antioxidant activity. In addition, we predicted many target genes of ZmANT1 and chose 13 of them to confirm binding of ZmANT1 to their promoters. Based on the above observations, we proposed a model for ANT1 regulation of cell proliferation and leaf growth, vascular and vein development, chloroplast development, and photosynthesis through its target genes. Our study revealed biological roles of ANT1 in several developmental processes beyond its known roles in plant growth and floral organogenesis.

Comparative transcriptomics method to infer gene coexpression networks and its applications to maize and rice leaf transcriptomes.

Time-series transcriptomes of a biological process obtained under different conditions are useful for identifying the regulators of the process and their regulatory networks. However, such data are 3D (gene expression, time, and condition), and there is currently no method that can deal with their full complexity. Here, we developed a method that avoids time-point alignment and normalization between conditions. We applied it to analyze time-series transcriptomes of developing maize leaves under light-dark cycles and under total darkness and obtained eight time-ordered gene coexpression networks (TO-GCNs), which can be used to predict upstream regulators of any genes in the GCNs. One of the eight TO-GCNs is light-independent and likely includes all genes involved in the development of Kranz anatomy, which is a structure crucial for the high efficiency of photosynthesis in C4 plants. Using this TO-GCN, we predicted and experimentally validated a regulatory cascade upstream of SHORTROOT1, a key Kranz anatomy regulator. Moreover, we applied the method to compare transcriptomes from maize and rice leaf segments and identified regulators of maize C4 enzyme genes and RUBISCO SMALL SUBUNIT2 Our study provides not only a powerful method but also novel insights into the regulatory networks underlying Kranz anatomy development and C4 photosynthesis.

Transcriptome dynamics of developing maize leaves and genomewide prediction of cis elements and their cognate transcription factors.

Maize is a major crop and a model plant for studying C4 photosynthesis and leaf development. However, a genomewide regulatory network of leaf development is not yet available. This knowledge is useful for developing C3 crops to perform C4 photosynthesis for enhanced yields. Here, using 22 transcriptomes of developing maize leaves from dry seeds to 192 h post imbibition, we studied gene up- and down-regulation and functional transition during leaf development and inferred sets of strongly coexpressed genes. More significantly, we developed a method to predict transcription factor binding sites (TFBSs) and their cognate transcription factors (TFs) using genomic sequence and transcriptomic data. The method requires not only evolutionary conservation of candidate TFBSs and sets of strongly coexpressed genes but also that the genes in a gene set share the same Gene Ontology term so that they are involved in the same biological function. In addition, we developed another method to predict maize TF-TFBS pairs using known TF-TFBS pairs in Arabidopsis or rice. From these efforts, we predicted 1,340 novel TFBSs and 253 new TF-TFBS pairs in the maize genome, far exceeding the 30 TF-TFBS pairs currently known in maize. In most cases studied by both methods, the two methods gave similar predictions. In vitro tests of 12 predicted TF-TFBS interactions showed that our methods perform well. Our study has significantly expanded our knowledge on the regulatory network involved in maize leaf development.