A systems genetics approach reveals environment-dependent associations between SNPs, protein coexpression, and drought-related traits in maize

High-dimensional multi-omics measured in controlled conditions are useful for maize platform and field trait predictions

KEY MESSAGE

Transcriptomics and proteomics information collected on a platform can predict additive and non-additive effects for platform traits and additive effects for field traits. The effects of climate change in the form of drought, heat stress, and irregular seasonal changes threaten global crop production. The ability of multi-omics data, such as transcripts and proteins, to reflect a plant's response to such climatic factors can be capitalized in prediction models to maximize crop improvement. Implementing multi-omics characterization in field evaluations is challenging due to high costs. It is, however, possible to do it on reference genotypes in controlled conditions. Using omics measured on a platform, we tested different multi-omics-based prediction approaches, using a high dimensional linear mixed model (MegaLMM) to predict genotypes for platform traits and agronomic field traits in a panel of 244 maize hybrids. We considered two prediction scenarios: in the first one, new hybrids are predicted (CV-NH), and in the second one, partially observed hybrids are predicted (CV-POH). For both scenarios, all hybrids were characterized for omics on the platform. We observed that omics can predict both additive and non-additive genetic effects for the platform traits, resulting in much higher predictive abilities than GBLUP. It highlights their efficiency in capturing regulatory processes in relation to growth conditions. For the field traits, we observed that the additive components of omics only slightly improved predictive abilities for predicting new hybrids (CV-NH, model MegaGAO) and for predicting partially observed hybrids (CV-POH, model GAOxW-BLUP) in comparison to GBLUP. We conclude that measuring the omics in the fields would be of considerable interest in predicting productivity if the costs of omics drop significantly.

Regulatory mechanisms used by ZmMYB39 to enhance drought tolerance in maize (Zea mays) seedlings

Drought is a significant abiotic stressor that limits maize (Zea mays L.) growth and development. Thus, enhancing drought tolerance is critical for promoting maize production. Our findings demonstrated that ZmMYB39 is an MYB transcription factor with transcriptional activation activity. Drought stress experiments involving ZmMYB39 overexpression and knockout lines indicated that ZmMYB39 positively regulated drought stress tolerance in maize. DAP-Seq, EMSA, dual-LUC, and RT-qPCR provided initial insights into the molecular regulatory mechanisms by which ZmMYB39 enhances drought tolerance in maize. ZmMYB39 directly promoted the expression of ZmP5CS1, ZmPOX1, ZmSOD2, ZmRD22, ZmNAC49, and ZmDREB2A, which are involved in stress resistance. ZmMYB39 enhanced drought tolerance by interacting with and promoting the expression of ZmFNR1, ZmHSP20, and ZmDOF6. Our study offers a theoretical basis for understanding the molecular regulatory networks involved in maize drought stress response. Furthermore, ZmMYB39 serves as a valuable genetic resource for breeding drought-resistant maize.

A gain-of-function allele of a DREB transcription factor gene ameliorates drought tolerance in wheat

Drought is a major environmental factor limiting wheat production worldwide. However, the genetic components underlying wheat drought tolerance are largely unknown. Here, we identify a DREB transcription factor gene (TaDTG6-B) by genome-wide association study that is tightly associated with drought tolerance in wheat. Candidate gene association analysis revealed that a 26-bp deletion in the TaDTG6-B coding region induces a gain-of-function for TaDTG6-BDel574, which exhibits stronger transcriptional activation, protein interactions, and binding activity to dehydration-responsive elements (DRE)/CRT cis-elements than the TaDTG6-BIn574 encoded by the allele lacking the deletion, thus conferring greater drought tolerance in wheat seedlings harboring this variant. Knockdown of TaDTG6-BDel574 transcripts attenuated drought tolerance in transgenic wheat, whereas its overexpression resulted in enhanced drought tolerance without accompanying phenotypic abnormalities. Furthermore, the introgression of the TaDTG6-BDel574 elite allele into drought-sensitive cultivars improved their drought tolerance, thus providing a valuable genetic resource for wheat breeding. We also identified 268 putative target genes that are directly bound and transcriptionally regulated by TaDTG6-BDel574. Further analysis showed that TaDTG6-BDel574 positively regulates TaPIF1 transcription to enhance wheat drought tolerance. These results describe the genetic basis and accompanying mechanism driving phenotypic variation in wheat drought tolerance, and provide a novel genetic resource for crop breeding programs.

Overexpression of a Zea mays Brassinosteroid-Signaling Kinase Gene ZmBSK1 Confers Salt Stress Tolerance in Maize

Salinity has become a crucial environmental factor seriously restricting maize (Zea mays L.) growth, development and productivity. However, how plants respond to salt stress is still poorly understood. In this study, we report that a maize brassinosteroid-signaling kinase gene ZmBSK1 plays a significant role in salt stress response. Expression pattern analysis revealed that the transcript level of ZmBSK1 was upregulated by NaCl treatment both in maize leaves, roots, and stems. Phenotypic and physiological analysis showed that overexpression of ZmBSK1 in maize improved salt tolerance by reducing the malondialdehyde (MDA) content, the percentage of electrolyte leakage, O₂ ^- and H₂O₂ accumulation under salt stress, relying on the increases of antioxidant defense enzyme activities and proline content. qRT-PCR analysis showed that overexpression of ZmBSK1 also positively modulated the expression levels of reactive oxygen species (ROS)-scavenging and proline biosynthesis-related genes under salt stress. Moreover, immunoprecipitation-mass spectrometry (IP-MS) assay and firefly luciferase complementation imaging (LCI) assay showed that ZmBSK1 could associate with heat shock protein ZmHSP8 and 14-3-3-like protein ZmGF14-6, and their gene expression levels could be significantly induced by NaCl treatment in different maize tissues. Our findings unravel the new function of ZmBSK1 in salt stress response, which provides the theoretical bases for the improvement of maize salt resistance.

Large-scale translatome profiling annotates the functional genome and reveals the key role of genic 3' untranslated regions in translatomic variation in plants

The translatome, a profile of the translational status of genetic information within cells, provides a new perspective on gene expression. Although many plant genomes have been sequenced, comprehensive translatomic annotations are not available for plants due to a lack of efficient translatome profiling techniques. Here, we developed a new technique termed 3' ribosome-profiling sequencing (3'Ribo-seq) for reliable, robust translatomic profiling. 3'Ribo-seq combines polysome profiling and 3' selection with a barcoding and pooling strategy. Systematic translatome profiling of different tissues of Arabidopsis, rice, and maize using conventional ribosome profiling (Ribo-seq) and 3'Ribo-seq revealed many novel translational genomic loci, thereby complementing functional genome annotation in plants. Using the low-cost, efficient 3'Ribo-seq technique and genome-wide association mapping of translatome expression (eGWAS), we performed a population-level dissection of the translatomes of 159 diverse maize inbred lines and identified 1,777 translational expression quantitative trait loci (eQTLs). Notably, local eQTLs are significantly enriched in the 3' untranslated regions of genes. Detailed eQTL analysis suggested that sequence variation around the polyadenylation (polyA) signal motif plays a key role in translatomic variation. Our study provides a comprehensive translatome annotation of plant functional genomes and introduces 3'Ribo-seq, which paves the way for deep translatomic analysis at the population level.