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

• Published in: Proceedings of the National Academy of Sciences - PNAS Vol. 112; no. 19; pp. E2477 - E2486
• Main Authors: Yu, Chun-Ping, Chen, Sean Chun-Chang, Chang, Yao-Ming, Liu, Wen-Yu, Lin, Hsin-Hung, Lin, Jinn-Jy, Chen, Hsiang June, Lu, Yu-Ju, Wu, Yi-Hsuan, Lu, Mei-Yeh Jade, Lu, Chen-Hua, Shih, Arthur Chun-Chieh, Ku, Maurice Sun-Ben, Shiu, Shin-Han, Wu, Shu-Hsing, Li, Wen-Hsiung
• Format: Journal Article
• Language: English
• Published: United States National Academy of Sciences 12-05-2015; National Acad Sciences
• Series: PNAS Plus
• Subjects: Amino Acid Motifs; Arabidopsis; Arabidopsis - genetics; Binding Sites; Biological Sciences; Computational Biology; Corn; Flowers & plants; Gene expression; Gene Expression Profiling; Gene Expression Regulation; Gene Expression Regulation, Plant; Genome, Plant; Genomics; Leaves; Multigene Family; Oryza - genetics; Photosynthesis; Plant Leaves - metabolism; PNAS Plus; Promoter Regions, Genetic; Protein Binding; Transcription Factors - metabolism; Transcription, Genetic; Transcriptome; Zea mays; Zea mays - genetics; coexpressed genes; cis binding site; maize transcriptomes
• ISSN: 0027-8424; 1091-6490
• DOI: 10.1073/pnas.1500605112

Significance Maize is a major crop and a model plant for studying C4 leaf development. However, its regulatory network of leaf development is poorly understood. We used transcriptomes of developing leaves to study gene-expression dynamics and coexpression to reveal functional transition during maize leaf development. More significantly, we developed methods to predict transcription factor-binding sites (TFBSs) and their cognate transcription factors (TFs) or to use the known Arabidopsis TF–TFBS pairs to predict the maize TF–TFBS pairs. In total, we predicted 1,340 novel TFBSs and 253 new TF–TFBS pairs in maize. Twelve predicted TF–TFBS interactions were validated by functional tests, suggesting that our methods perform well. Our study has significantly expanded our knowledge of the regulatory network of maize leaf development.
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.