Transcriptome and metabolome profiling of interspecific CSSLs reveals general and specific mechanisms of drought resistance in cotton

Dissecting the Superior Drivers for the Simultaneous Improvement of Fiber Quality and Yield Under Drought Stress Via Genome-Wide Artificial Introgressions of Gossypium barbadense into Gossypium hirsutum

Global water scarcity and extreme weather intensify drought stress, significantly reducing cotton yield and quality worldwide. Drought treatments are conducted using a population of chromosome segment substitution lines generated from E22 (G. hirsutum) and 3-79 (G. barbadense) as parental lines either show superior yields or fiber quality under both control and drought conditions. Fourteen datasets, covering 4 yields and 4 quality traits, are compiled and assessed for drought resistance using the drought resistance coefficient (DRC) and membership function value of drought resistance (MFVD). Genome-wide association studies, linkage analysis, and bulked segregant analysis are combined to analyze the DR-related QTL. A total of 121 significant QTL are identified by DRC and MFVD of the 8 traits. CRISPR/Cas9 and virus-induced gene silencing techniques verified DRR1 and DRT1 as pivotal genes in regulating drought resistant of cotton, with hap3-79 exhibiting greater drought resistance than hapE22 concerning DRR1 and DRT1. Moreover, 14 markers with superior yield and fiber quality are selected for drought treatment. This study offers valuable insights into yield and fiber quality variations between G. hirsutum and G. barbadense amid drought, providing crucial theoretical and technological backing for developing cotton varieties resilient to drought, with high yield and superior fiber quality.

Metabolomics reveal root differential metabolites of different root-type alfalfa under drought stress

Introduction

Alfalfa (Medicago sativa L.) is the favored premium feed ingredient in animal husbandry production which is in serious jeopardy due to soil moisture shortages. It is largely unknown how different root types of alfalfa respond to arid-induced stress in terms of metabolites and phytohormones.

Methods

Therefore, rhizomatous rooted M. sativa 'Qingshui' (or QS), tap-rooted M. sativa 'Longdong' (or LD), and creeping rooted M. varia 'Gannong No. 4' (or GN) were investigated to identify metabolites and phytohormones responses to drought conditions.

Results

We found 164, 270, and 68 significantly upregulated differential metabolites were categorized into 35, 38, and 34 metabolic pathways in QS, LD, and GN within aridity stress, respectively. Amino acids, organic acids, sugars, and alkaloids were the four categories of primary differential metabolites detected, which include 6-gingerol, salicylic acid (SA), indole-3-acetic acid (IAA), gibberellin A4 (GA4), abscisic acid (ABA), trans-cinnamic acid, sucrose, L-phenylalanine, L-tyrosine, succinic acid, and nicotinic acid and so on, turns out these metabolites are essential for the resistance of three root-type alfalfa to aridity coercing.

Discussion

The plant hormone signal transduction (PST) pathway was dramatically enriched after drought stress. IAA and ABA were significantly accumulated in the metabolites, indicating that they play vital roles in the response of three root types of alfalfa to water stress, and QS and LD exhibit stronger tolerance than GN under drought stress.

Multi-Omics Pipeline and Omics-Integration Approach to Decipher Plant's Abiotic Stress Tolerance Responses

The present day's ongoing global warming and climate change adversely affect plants through imposing environmental (abiotic) stresses and disease pressure. The major abiotic factors such as drought, heat, cold, salinity, etc., hamper a plant's innate growth and development, resulting in reduced yield and quality, with the possibility of undesired traits. In the 21st century, the advent of high-throughput sequencing tools, state-of-the-art biotechnological techniques and bioinformatic analyzing pipelines led to the easy characterization of plant traits for abiotic stress response and tolerance mechanisms by applying the 'omics' toolbox. Panomics pipeline including genomics, transcriptomics, proteomics, metabolomics, epigenomics, proteogenomics, interactomics, ionomics, phenomics, etc., have become very handy nowadays. This is important to produce climate-smart future crops with a proper understanding of the molecular mechanisms of abiotic stress responses by the plant's genes, transcripts, proteins, epigenome, cellular metabolic circuits and resultant phenotype. Instead of mono-omics, two or more (hence 'multi-omics') integrated-omics approaches can decipher the plant's abiotic stress tolerance response very well. Multi-omics-characterized plants can be used as potent genetic resources to incorporate into the future breeding program. For the practical utility of crop improvement, multi-omics approaches for particular abiotic stress tolerance can be combined with genome-assisted breeding (GAB) by being pyramided with improved crop yield, food quality and associated agronomic traits and can open a new era of omics-assisted breeding. Thus, multi-omics pipelines together are able to decipher molecular processes, biomarkers, targets for genetic engineering, regulatory networks and precision agriculture solutions for a crop's variable abiotic stress tolerance to ensure food security under changing environmental circumstances.