Early Drought-Responsive Genes Are Variable and Relevant to Drought Tolerance

Identification of the maize drought-resistant gene Zinc-finger Inflorescence Meristem 23 through high-resolution temporal transcriptome analysis

Drought is a major abiotic stress that significantly limits maize productivity. However, previous transcriptomic studies with limited time-point sampling have hindered the construction of robust co-expression networks, making it challenging to identify reliable hub genes involved in drought tolerance. To overcome this limitation, we generated a high-temporal-resolution transcriptome dataset spanning 108 time points from maize seedlings subjected to two consecutive rounds of drought and re-watering treatments. A total of 8477 drought-responsive genes (DRGs) were identified by comparing drought-stressed and well-watered controls. Using weighted gene co-expression network analysis (WGCNA), we constructed 17 co-expression modules, of which 8 were strongly associated with drought stress responses and collectively contained 353 hub genes. Among them, we validated the drought resistance functions of ZmCPK35, a known drought-responsive gene, and Zinc-finger Inflorescence Meristem 23 (ZmZIM23), a newly identified drought-regulatory gene, within the M10 module. Functional analysis revealed that ZmZIM23 enhances drought tolerance by improving water-use efficiency, reducing transpiration rates, and promoting biomass accumulation. Furthermore, yeast one-hybrid (Y1H) and dual-luciferase (LUC) assays demonstrated that ZmWRKY40, another M10 module member, transcriptionally regulates both ZmZIM23 and ZmCPK35. By integrating high-resolution transcriptomic data with co-expression network analyses, this study unveils key drought-responsive regulatory networks in maize and identifies novel candidate genes for improving drought tolerance. These findings provide valuable insights into the genetic foundation of drought adaptation and offer potential targets for the development of drought-resistant maize cultivars.

Tensor decomposition reveals trans-regulated gene modules in maize drought response

When plants respond to drought stress, dynamic cellular changes occur, accompanied by alterations in gene expression, which often act through trans-regulation. However, the detection of trans-acting genetic variants and networks of genes is challenged by the large number of genes and markers. Using a tensor decomposition method, we identify trans-acting expression quantitative trait loci (trans-eQTLs) linked to gene modules, rather than individual genes, which were associated with maize drought response. Module-to-trait association analysis demonstrates that half of the modules are relevant to drought-related traits. Genome-wide association studies of the expression patterns of each module identify 286 trans-eQTLs linked to drought-responsive modules, the majority of which cannot be detected based on individual gene expression. Notably, the trans-eQTLs located in the regions selected during maize improvement tend towards relatively strong selection. We further prioritize the genes that affect the transcriptional regulation of multiple genes in trans, as exemplified by two transcription factor genes. Our analyses highlight that multidimensional reduction could facilitate the identification of trans-acting variations in gene expression in response to dynamic environments and serve as a promising technique for high-order data processing in future crop breeding.

GWAS for Drought Resilience Traits in Red Clover (Trifolium pratense L.)

Red clover (Trifolium pratense L.) is a well-appreciated grassland crop in temperate climates but suffers from increasingly frequent and severe drought periods. Molecular markers for drought resilience (DR) would benefit breeding initiatives for red clover, as would a better understanding of the genes involved in DR. Two previous studies, as follows, have: (1) identified phenotypic DR traits in a diverse set of red clover accessions; and (2) produced genotypic data using a pooled genotyping-by-sequencing (GBS) approach in the same collection. In the present study, we performed genome-wide association studies (GWAS) for DR using the available phenotypic and genotypic data. Single nucleotide polymorphism (SNP) calling was performed using GBS data and the following two red clover genome assemblies: the recent HEN-17 assembly and the Milvus assembly. SNP positions with significant associations were used to delineate flanking regions in both genome assemblies, while functional annotations were retrieved from Medicago truncatula orthologs. GWAS revealed 19 significant SNPs in the HEN-17-derived SNP set, explaining between 5.3 and 23.2% of the phenotypic variation per SNP-trait combination for DR traits. Among the genes in the SNP-flanking regions, we identified candidate genes related to cell wall structuring, genes encoding sugar-modifying proteins, an ureide permease gene, and other genes linked to stress metabolism pathways. GWAS revealed 29 SNPs in the Milvus-derived SNP set that explained substantially more phenotypic variation for DR traits, between 5.3 and 42.3% per SNP-trait combination. Candidate genes included a DEAD-box ATP-dependent RNA helicase gene, a P-loop nucleoside triphosphate hydrolase gene, a Myb/SANT-like DNA-binding domain protein, and an ubiquitin-protein ligase gene. Most accessions in this study are genetically more closely related to the Milvus genotype than to HEN-17, possibly explaining how the Milvus-derived SNP set yielded more robust associations. The Milvus-derived SNP set pinpointed 10 genomic regions that explained more than 25% of the phenotypic variation for DR traits. A possible next step could be the implementation of these SNP markers in practical breeding programs, which would help to improve DR in red clover. Candidate genes could be further characterized in future research to unravel drought stress resilience in red clover in more detail.

The reference genome and abiotic stress responses of the model perennial grass Brachypodium sylvaticum

Perennial grasses are important forage crops and emerging biomass crops and have the potential to be more sustainable grain crops. However, most perennial grass crops are difficult experimental subjects due to their large size, difficult genetics, and/or their recalcitrance to transformation. Thus, a tractable model perennial grass could be used to rapidly make discoveries that can be translated to perennial grass crops. Brachypodium sylvaticum has the potential to serve as such a model because of its small size, rapid generation time, simple genetics, and transformability. Here, we provide a high-quality genome assembly and annotation for B. sylvaticum, an essential resource for a modern model system. In addition, we conducted transcriptomic studies under 4 abiotic stresses (water, heat, salt, and freezing). Our results indicate that crowns are more responsive to freezing than leaves which may help them overwinter. We observed extensive transcriptional responses with varying temporal dynamics to all abiotic stresses, including classic heat-responsive genes. These results can be used to form testable hypotheses about how perennial grasses respond to these stresses. Taken together, these results will allow B. sylvaticum to serve as a truly tractable perennial model system.

Genetic and transcriptomic dissection of host defense to Goss's bacterial wilt and leaf blight of maize

Goss's wilt, caused by the Gram-positive actinobacterium Clavibacter nebraskensis, is an important bacterial disease of maize. The molecular and genetic mechanisms of resistance to the bacterium, or, in general, Gram-positive bacteria causing plant diseases, remain poorly understood. Here, we examined the genetic basis of Goss's wilt through differential gene expression, standard genome-wide association mapping (GWAS), extreme phenotype (XP) GWAS using highly resistant (R) and highly susceptible (S) lines, and quantitative trait locus (QTL) mapping using 3 bi-parental populations, identifying 11 disease association loci. Three loci were validated using near-isogenic lines or recombinant inbred lines. Our analysis indicates that Goss's wilt resistance is highly complex and major resistance genes are not commonly present. RNA sequencing of samples separately pooled from R and S lines with or without bacterial inoculation was performed, enabling identification of common and differential gene responses in R and S lines. Based on expression, in both R and S lines, the photosynthesis pathway was silenced upon infection, while stress-responsive pathways and phytohormone pathways, namely, abscisic acid, auxin, ethylene, jasmonate, and gibberellin, were markedly activated. In addition, 65 genes showed differential responses (up- or down-regulated) to infection in R and S lines. Combining genetic mapping and transcriptional data, individual candidate genes conferring Goss's wilt resistance were identified. Collectively, aspects of the genetic architecture of Goss's wilt resistance were revealed, providing foundational data for mechanistic studies.

Transcriptome profiling, physiological, and biochemical analyses provide new insights towards drought stress response in sugar maple (Acer saccharum Marshall) saplings

Sugar maple (Acer saccharum Marshall) is a temperate tree species in the northeastern parts of the United States and is economically important for its hardwood and syrup production. Sugar maple trees are highly vulnerable to changing climatic conditions, especially drought, so understanding the physiological, biochemical, and molecular responses is critical. The sugar maple saplings were subjected to drought stress for 7, 14, and 21 days and physiological data collected at 7, 14, and 21 days after stress (DAS) showed significantly reduced chlorophyll and Normalized Difference Vegetation Index with increasing drought stress time. The drought stress-induced biochemical changes revealed a higher accumulation of malondialdehyde, proline, and peroxidase activity in response to drought stress. Transcriptome analysis identified a total of 14,099 differentially expressed genes (DEGs); 328 were common among all stress periods. Among the DEGs, transcription factors (including NAC, HSF, ZFPs, GRFs, and ERF), chloroplast-related and stress-responsive genes such as peroxidases, membrane transporters, kinases, and protein detoxifiers were predominant. GO enrichment and KEGG pathway analysis revealed significantly enriched processes related to protein phosphorylation, transmembrane transport, nucleic acids, and metabolic, secondary metabolite biosynthesis pathways, circadian rhythm-plant, and carotenoid biosynthesis in response to drought stress. Time-series transcriptomic analysis revealed changes in gene regulation patterns in eight different clusters, and pathway analysis by individual clusters revealed a hub of stress-responsive pathways. In addition, qRT-PCR validation of selected DEGs revealed that the expression patterns were consistent with transcriptome analysis. The results from this study provide insights into the dynamics of physiological, biochemical, and gene responses to progressive drought stress and reveal the important stress-adaptive mechanisms of sugar maple saplings in response to drought stress.

Brassinosteroids induced drought resistance of contrasting drought-responsive genotypes of maize at physiological and transcriptomic levels

The present study investigated the brassinosteroid-induced drought resistance of contrasting drought-responsive maize genotypes at physiological and transcriptomic levels. The brassinosteroid (BR) contents along with different morphology characteristics, viz., plant height (PH), shoot dry weight (SDW), root dry weight (RDW), number of leaves (NL), the specific mass of the fourth leaf, and antioxidant activities, were investigated in two maize lines that differed in their degree of drought tolerance. In response to either control, drought, or brassinosteroid treatments, the KEGG enrichment analysis showed that plant hormonal signal transduction and starch and sucrose metabolism were augmented in both lines. In contrast, the phenylpropanoid biosynthesis was augmented in lines H21L0R1 and 478. Our results demonstrate drought-responsive molecular mechanisms and provide valuable information regarding candidate gene resources for drought improvement in maize crop. The differences observed for BR content among the maize lines were correlated with their degree of drought tolerance, as the highly tolerant genotype showed higher BR content under drought stress.

Identification and mapping of QTL associated with some traits related for drought tolerance in wheat using SSR markers

Background

Wheat is the most important crop around the world. Drought stresses affect wheat production and their characterization. Most of the traits that are affected by drought are quantitative traits, so detection of the quantitative trait’s loci (QTLs) related to these traits is very important for breeder and wheat producers. In this trend, 285 F2 individuals from crosses between four bread wheat genotypes (Triticum aestivum L.), i.e., Sakha93, Sids1, Sakha94, and Gemmiza9, were used for identified QTLs associated with plant height (PH) and leaf wilting (LW). Single marker analysis and composite interval mapping (CIM) were used.

Results

A total of 116 QTLs loci were detected which covered 19 chromosomes out of the 21 chromosomes of wheat. PH and LW had 74 and 42 QTLs loci, respectively. On the other hand, chromosome 7A showed to bear the highest number of QTLs loci (15 loci). While chromosome 1A beard the highest number of QTLs loci related to PH (10 loci), chromosome 2B and 7A beard the highest number of QTLs related LW. We highly recommend our finding to help breeders in wheat breeding programs to improve plant height and leaf wilting.

Conclusion

Our investigation concluded that SSR markers have high efficiency in the identification of QTLs related to abiotic stress; also the CIM method had more advanced priority for QTLs mapping.