General mechanisms of drought response and their application in drought resistance improvement in plants

Comprehensive assessment of drought resistance and recovery in kiwifruit genotypes using multivariate analysis

As global climate change persists, ongoing warming exposes plants, including kiwifruit, to repeated cycles of drought stress and rewatering, necessitating the identification of drought-resistant genotypes for breeding purposes. To better understand the physiological mechanisms underlying drought resistance and recovery in kiwifruit, moderate (40-45% field capacity) and severe (25-30% field capacity) drought stresses were applied, followed by rewatering (80-85% field capacity) to eight kiwifruit rootstocks in this study. We then conducted a multivariate analysis of 20 indices for the assessment of drought resistance and recovery capabilities. Additionally, we identified four principal components, each playing a vital role in coping with diverse water conditions. Three optimal indicator groups were pinpointed, enhancing precision in kiwifruit drought resistance and recovery assessment and simplifying the evaluation system. Finally, MX-1 and HW were identified as representative rootstocks for future research on kiwifruit's responses to moderate and severe drought stresses. This study not only enhances our understanding of the response mechanisms of kiwifruit rootstocks to progressive drought stress and recovery but also provides theoretical guidance for reliable screening of drought-adaptive kiwifruit genotypes.

Integrative leaf anatomy structure, physiology, and metabolome analyses revealed the response to drought stress in sainfoin at the seedling stage

INTRODUCTION

Sainfoin (Onobrychis viciaefolia) is a vital legume forage, and drought is the primary element impeding sainfoin growth.

OBJECTIVE

The anatomical structure, physiological indexes, and metabolites of the leaves of sainfoin seedlings with a drought-resistant line of P1 (DRL) and a drought-sensitive material of 2049 (DSM) were analyzed under drought (-1.0 MPa) with polyethylene glycol-6000 (PEG-6000).

METHODS

The leaf anatomy was studied by the paraffin section method. The related physiological indexes were measured by the hydroxylamine oxidation method, titanium sulfate colorimetric method, thiobarbituric acid method, acidic ninhydrin colorimetric method, and Coomassie brilliant blue method. The metabolomics analysis was composed of liquid chromatography tandem high-resolution mass spectrometry (LC-MS/MS).

RESULTS

The results revealed that the thickness of the epidermis, palisade tissue, and sponge tissue of DRL were significantly greater than those of DSM. The leaves of DRL exhibited lower levels of superoxide anion (O2 •-) production rate, hydrogen peroxide (H2O2) content, and malondialdehyde (MDA) content compared with DSM, while proline (Pro) content and soluble protein (SP) content were significantly higher than those of DSM. A total of 391 differential metabolites were identified in two samples. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment showed that the primary differential metabolites were concentrated into the tyrosine metabolism; isoquinoline alkaloid biosynthesis; ubiquinone and other terpenoid quinone biosynthesis; neomycin, kanamycin, and gentamicin biosynthesis; and anthocyanin biosynthesis metabolic pathways.

CONCLUSION

Compared with DSM, DRL had more complete anatomical structure, lower active oxygen content, and higher antioxidant level. The results improved our insights into the drought-resistant mechanisms in sainfoin.

Metabolome profiling of cacao (Theobroma cacao L.) callus under drought stress conditions induced by polyethylene glycol (PEG) as osmoticant

INTRODUCTION

The cacao tree (Theobroma cacao), a perennial crop that serves as a source of cacao beans, can suffer from drastic climate changes such as irregular rainfall and shorter rainy seasons. The search for hybrids which are capable of producing specific metabolites favoring adaptation in new climatic conditions is a challenge in cacao farming.

OBJECTIVES

We aimed to (1) analyze the metabolic changes in calli of three cacao genotypes during water deficit induced by incubation with polyethylene glycol and (2) assess their response to water deficit stress with regard to somatic embryo differentiation.

METHODS

Metabolic profiling was carried out using 1H-NMR spectroscopy and multivariate data analysis was applied to crude extracts of calli grown in non-stress or water deficit stress conditions.

RESULTS

Water deficit stress influences the capacity of calli to produce embryos. The SCA12 genotype exhibited the best conversion capacity under severe conditions and was considered as tolerant to drought, followed by the SCA6 genotype (mid-tolerant) and the MA12 genotype (sensitive). Fifty-four metabolites were identified in the three cacao genotypes and discriminant metabolites were identified. Metabolites involved in water stress tolerance such as fructose, trans-aconitic acid, leucine, and hydroxybenzene derivatives were observed in SCA12, the tolerant genotype.

CONCLUSION

These results demonstrate the utility of 1H-NMR metabolomics as an essential tool for the analysis of the drought tolerance characteristics of T. cacao.

GBS-Based Genomic Selection for Pea Grain Yield under Severe Terminal Drought

Terminal drought is the main stress that limits pea ( L.) grain yield in Mediterranean-climate regions. This study provides an unprecedented assessment of the predictive ability of genomic selection (GS) for grain yield under severe terminal drought using genotyping-by-sequencing (GBS) data. Additional aims were to assess the GS predictive ability for different GBS data quality filters and GS models, comparing intrapopulation with interpopulation GS predictive ability and to perform genome-wide association (GWAS) studies. The yield and onset of flowering of 315 lines from three recombinant inbred line (RIL) populations issued by connected crosses between three elite cultivars were assessed under a field rainout shelter. We defined an adjusted yield, which is associated with intrinsic drought tolerance, as the yield deviation from the value expected as a function of onset of flowering (which correlated negatively with grain yield). Total polymorphic markers ranged from approximately 100 (minimum of eight reads per locus, maximum 10% genotype missing data) to over 7500 markers (minimum of four reads, maximum 50% missing rate). Best predictions were provided by Bayesian Lasso (BL) or ridge regression best linear unbiased prediction (rrBLUP), rather than support vector regression (SVR) models, with at least 400-500 markers. Intrapopulation GS predictive ability exceeded 0.5 for yield and onset of flowering in all populations and approached 0.4 for the adjusted yield of a population with high trait variation. Genomic selection was preferable to phenotypic selection in terms of predicted yield gains. Interpopulation GS predictive ability varied largely depending on the pair of populations. GWAS revealed extensive colocalization of markers associated with high yield and early flowering and suggested that they are concentrated in a few genomic regions.