Elucidation of Novel cis-Regulatory Elements and Promoter Structures Involved in Iron Excess Response Mechanisms in Rice Using a Bioinformatics Approach

被引:18
|
作者
Kakei, Yusuke [1 ]
Masuda, Hiroshi [2 ]
Nishizawa, Naoko K. [3 ]
Hattori, Hiroyuki [2 ]
Aung, May Sann [2 ,3 ]
机构
[1] Natl Agr & Food Res Org, Inst Vegetable & Floriculture Sci, Res Ctr Agr Informat Technol, Tsukuba, Ibaraki, Japan
[2] Akita Prefectural Univ, Fac Bioresource Sci, Dept Biol Prod, Akita, Japan
[3] Ishikawa Prefectural Univ, Res Inst Bioresources & Biotechnol, Nonoichi, Ishikawa, Japan
来源
FRONTIERS IN PLANT SCIENCE | 2021年 / 12卷
关键词
cis-regulatory elements (CREs); motifs; iron toxicity; rice; bioinformatics; promoter sequence; iron; zinc; BHLH TRANSCRIPTION FACTOR; DEFICIENCY; HOMEOSTASIS; TOXICITY; PLANTS; GENES; FE; IDENTIFICATION; STORAGE; STRESS;
D O I
10.3389/fpls.2021.660303
中图分类号
Q94 [植物学];
学科分类号
071001 ;
摘要
Iron (Fe) excess is a major constraint on crop production in flooded acidic soils, particularly in rice cultivation. Under Fe excess, plants activate a complex mechanism and network regulating Fe exclusion by roots and isolation in various tissues. In rice, the transcription factors and cis-regulatory elements (CREs) that regulate Fe excess response mechanisms remain largely elusive. We previously reported comprehensive microarray analyses of several rice tissues in response to various levels of Fe excess stress. In this study, we further explored novel CREs and promoter structures in rice using bioinformatics approaches with this microarray data. We first performed network analyses to predict Fe excess-related CREs through the categorization of the gene expression patterns of Fe excess-responsive transcriptional regulons, and found four major expression clusters: Fe storage type, Fe chelator type, Fe uptake type, and WRKY and other co-expression type. Next, we explored CREs within these four clusters of gene expression types using a machine-learning method called microarray-associated motif analyzer (MAMA), which we previously established. Through a comprehensive bioinformatics approach, we identified a total of 560 CRE candidates extracted by MAMA analyses and 42 important conserved sequences of CREs directly related to the Fe excess response in various rice tissues. We explored several novel cis-elements as candidate Fe excess CREs including GCWGCWGC, CGACACGC, and Myb binding-like motifs. Based on the presence or absence of candidate CREs using MAMA and known PLACE CREs, we found that the Boruta-XGBoost model explained expression patterns with high accuracy of about 83%. Enriched sequences of both novel MAMA CREs and known PLACE CREs led to high accuracy expression patterns. We also found new roles of known CREs in the Fe excess response, including the DCEp2 motif, IDEF1-, Zinc Finger-, WRKY-, Myb-, AP2/ERF-, MADS- box-, bZIP and bHLH- binding sequence-containing motifs among Fe excess-responsive genes. In addition, we built a molecular model and promoter structures regulating Fe excess-responsive genes based on new finding CREs. Together, our findings about Fe excess-related CREs and conserved sequences will provide a comprehensive resource for discovery of genes and transcription factors involved in Fe excess-responsive pathways, clarification of the Fe excess response mechanism in rice, and future application of the promoter sequences to produce genotypes tolerant of Fe excess.
引用
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页数:19
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