Climate change is affecting all regions of the world with different climates, and the scale of damage is increasing due to the occurrence of various natural disasters. In particular, maize production is highly affected by abnormal climate events such as heat waves and droughts. Increasing temperatures can accelerate growth and shorten the growing season, potentially reducing productivity. Additionally, enhanced temperatures during the ripening period can accelerate the process, reducing crop yields. In addition, drought stress due to water deficit can greatly affect seedling formation, early plant growth, photosynthesis, reproductive growth, and yield, so proper water management is critical to maize growth. Maize, in particular, is tall and broad-leaved, so extreme drought stress at planting can cause leaves to curl and stunt growth. It is important to understand that severe drought can have a detrimental effect on the growth and reproduction of maize. In addition, high temperatures caused by drought stress can inhibit the induction of flowering in male flowers and cause factors that interfere with pollen development. It is therefore important to increase the productivity of all food crops, including maize, while maintaining them in the face of persistent drought caused by climate change. This requires a strategy to develop genetically modified crops and drought-tolerant maize that can effectively respond to climate change. The aim of this paper is to investigate the effects of climate change and drought tolerance on maize growth. We also reviewed molecular breeding techniques to develop drought-tolerant maize varieties in response to climate change.

Flowering time is a critical aspect of maize production that has been shown to impact crop yield, and drought is a major abiotic stress that can cause early arrest of maize flower. Drought increases the anthesis-silking interval (ASI), resulting in negative effects on maize yields. To understand the molecular mechanisms underlying the effects of drought on ASI, we used RNA sequencing technology and bioinformatics tools. Our results identified a total of 619 genes and 126 transcripts whose expression was altered by drought stress in the maize B73 leaves under short-day condition. Among drought responsive genes, we also identified 20 genes involved in flowering times. Gene Ontology (GO) enrichment analysis was used to predict the functions of the drought-responsive genes and transcripts. GO categories related to flowering time included reproduction, flower development, pollen-pistil interaction, and post-embryonic development. Transcript levels of several genes that have previously been shown to affect flowering time, such as PRR37, transcription factor HY5, and CONSTANS, were significantly altered by drought conditions. Furthermore, we also identified several drought-responsive transcripts containing C2H2 zinc finger, CCCH, and NAC domains, which are frequently involved in transcriptional regulation and may thus have potential to alter gene expression programs to change maize flowering time. Overall, our results provide a genome-wide analysis of differentially expressed genes, novel transcripts, and isoform variants expressed during the reproductive stage of maize plants subjected to drought stress and short-day condition. Further characterization of the drought-responsive transcripts identified in this study has the potential to advance our understanding of the mechanisms that regulate flowering time under drought stress.

Background: The PLAnt co-EXpression database (PLANEX) is a new internet-based database for plant gene analysis. PLANEX (http://planex.plantbioinformatics.org) contains publicly available GeneChip data obtained from the Gene Expression Omnibus (GEO) of the National Center for Biotechnology Information (NCBI). PLANEX is a genome-wide co-expression database, which allows for the functional identification of genes from a wide variety of experimental designs. It can be used for the characterization of genes for functional identification and analysis of a gene’s dependency among other genes. Gene co-expression databases have been developed for other species, but gene co-expression information for plants is currently limited. Description: We constructed PLANEX as a list of co-expressed genes and functional annotations for Arabidopsis thaliana, Glycine max, Hordeum vulgare, Oryza sativa, Solanum lycopersicum, Triticum aestivum, Vitis vinifera and Zea mays. PLANEX reports Pearson’s correlation coefficients (PCCs; r-values) that distribute from a gene of interest for a given microarray platform set corresponding to a particular organism. To support PCCs, PLANEX performs an enrichment test of Gene Ontology terms and Cohen’s Kappa value to compare functional similarity for all genes in the co-expression database. PLANEX draws a cluster network with co-expressed genes, which is estimated using the k-mean method. To construct PLANEX, a variety of datasets were interpreted by the IBM supercomputer Advanced Interactive eXecutive (AIX) in a supercomputing center. Conclusion: PLANEX provides a correlation database, a cluster network and an interpretation of enrichment test results for eight plant species. A typical co-expressed gene generates lists of co-expression data that contain hundreds of genes of interest for enrichment analysis. Also, co-expressed genes can be identified and cataloged in terms of comparative genomics by using the ‘Co-expression gene compare’ feature. This type of analysis will help interpret experimental data and determine whether there is a common term among genes of interest.

Kitae Song, Won Cheol Yim, and Byung-Moo Lee. Plant Breeding and Biotechnology 2017;5:344-53. https://doi.org/10.9787/PBB.2017.5.4.344