Moderate drought stress increases resistance of Brassica napus to subsequent infection by Leptosphaeria maculans DOI Creative Commons
Barbora Jindřichová,

Marzieh Mohri,

Tetiana Kalachova

et al.

Biologia Plantarum, Journal Year: 2025, Volume and Issue: 69, P. 1 - 11

Published: Feb. 22, 2025

Language: Английский

Transcriptomics, proteomics, and metabolomics interventions prompt crop improvement against metal(loid) toxicity DOI Creative Commons
Ali Raza, Hajar Salehi, Shanza Bashir

et al.

Plant Cell Reports, Journal Year: 2024, Volume and Issue: 43(3)

Published: Feb. 27, 2024

The escalating challenges posed by metal(loid) toxicity in agricultural ecosystems, exacerbated rapid climate change and anthropogenic pressures, demand urgent attention. Soil contamination is a critical issue because it significantly impacts crop productivity. widespread threat of can jeopardize global food security due to contaminated supplies pose environmental risks, contributing soil water pollution thus impacting the whole ecosystem. In this context, plants have evolved complex mechanisms combat stress. Amid array innovative approaches, omics, notably transcriptomics, proteomics, metabolomics, emerged as transformative tools, shedding light on genes, proteins, key metabolites involved stress responses tolerance mechanisms. These identified candidates hold promise for developing high-yielding crops with desirable agronomic traits. Computational biology tools like bioinformatics, biological databases, analytical pipelines support these omics approaches harnessing diverse information facilitating mapping genotype-to-phenotype relationships under conditions. This review explores: (1) multifaceted strategies that use adapt their environment; (2) latest findings metal(loid)-mediated metabolomics studies across various plant species; (3) integration data artificial intelligence high-throughput phenotyping; (4) bioinformatics single and/or multi-omics integration; (5) insights into adaptations future outlooks; (6) capacity advances creating sustainable resilient thrive metal(loid)-contaminated environments.

Language: Английский

Citations

25

The plant disease triangle facing climate change: a molecular perspective DOI
Charles Roussin‐Léveillée,

Christina A. M. Rossi,

Christian Danve M. Castroverde

et al.

Trends in Plant Science, Journal Year: 2024, Volume and Issue: 29(8), P. 895 - 914

Published: April 4, 2024

Language: Английский

Citations

23

Drought: A context‐dependent damper and aggravator of plant diseases DOI
Aanchal Choudhary, Muthappa Senthil‐Kumar

Plant Cell & Environment, Journal Year: 2024, Volume and Issue: 47(6), P. 2109 - 2126

Published: Feb. 26, 2024

Abstract Drought dynamically influences the interactions between plants and pathogens, thereby affecting disease outbreaks. Understanding intricate mechanistic aspects of multiscale among plants, environment—known as triangle—is paramount for enhancing climate resilience crop plants. In this review, we systematically compile comprehensively analyse current knowledge on influence drought severity plant diseases. We emphasise that studying these stresses in isolation is not sufficient to predict how respond combined stress from both pathogens. The impact pathogens complex multifaceted, encompassing activation antagonistic signalling cascades response factors. nature, intensity, temporality pathogen occurrence significantly outcome delineate drought‐sensitive nodes immunity highlight emerging points crosstalk defence under stress. limited understanding acknowledged a key research gap area. information synthesised herein will be crucial crafting strategies accurate prediction mitigation future risks, particularly context changing climate.

Language: Английский

Citations

20

Enhancing Tolerance to Combined Heat and Drought Stress in Cool‐Season Grain Legumes: Mechanisms, Genetic Insights, and Future Directions DOI Creative Commons
M. Shanthi Priya, Muhammad Farooq, Kadambot H. M. Siddique

et al.

Plant Cell & Environment, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 20, 2025

ABSTRACT The increasing frequency of concurrent heat and drought stress poses a significant challenge to agricultural productivity, particularly for cool‐season grain legumes, including broad bean ( Vicia Faba L.), lupin Lupinus spp.), lentil Lens culinaris Medik), chickpea Cicer arietinum grasspea Lathyrus sativus pea Pisum sativum common vetch sativa L.). These legumes play vital role in sustainable systems due their nitrogen‐fixing ability high nutritional value. This review synthesizes current knowledge the impacts tolerance mechanisms associated with combined stresses these crops. We evaluate physiological biochemical responses stress, focusing on detrimental effects growth, development, yield. Key genetic molecular mechanisms, such as roles osmolytes, antioxidants, stress‐responsive genes, are explored. also discuss intricate interplay between signaling pathways, involvement Ca 2+ ions, reactive oxygen species, transcription factor DREB2A, endoplasmic reticulum mediating responses. comprehensive analysis offers new insights into developing resilient legume varieties enhance sustainability under climate change. Future research should prioritize integrating omics technologies unravel plant abiotic stresses.

Language: Английский

Citations

2

Creating Climate-Resilient Crops by Increasing Drought, Heat, and Salt Tolerance DOI Creative Commons
Tharanya Sugumar, Guoxin Shen, Jennifer Smith

et al.

Plants, Journal Year: 2024, Volume and Issue: 13(9), P. 1238 - 1238

Published: April 29, 2024

Over the years, changes in agriculture industry have been inevitable, considering need to feed growing population. As world population continues grow, food security has become challenged. Resources such as arable land and freshwater scarce due quick urbanization developing countries anthropologic activities; expanding agricultural production areas is not an option. Environmental climatic factors drought, heat, salt stresses pose serious threats worldwide. Therefore, utilize remaining water effectively efficiently maximize yield support increasing demand crucial. It essential develop climate-resilient crops that will outperform traditional under any abiotic stress conditions salt, well these combinations. This review provides a glimpse of how plant breeding evolved overcome harsh environmental what future would be like.

Language: Английский

Citations

10

Comprehensive approaches to heavy metal bioremediation: Integrating microbial insights and genetic innovations DOI

Mehran Khan,

Mir Muhammad Nizamani, Muhammad Asif

et al.

Journal of Environmental Management, Journal Year: 2025, Volume and Issue: 374, P. 123969 - 123969

Published: Jan. 8, 2025

Language: Английский

Citations

1

Efficient Agrobacterium mediated plant regeneration using petiole explants and plant transformation of GUS and Bar gene in Momordica charantia L. plants DOI
S. P. S. Kushwaha,

S. Vanchinathan,

S. S. Lele

et al.

Journal of Plant Biochemistry and Biotechnology, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 9, 2025

Language: Английский

Citations

1

Status and prospects of omics in lentil: understanding mechanisms and impact on stress breeding under changing climate DOI
Fawad Ali, Yiren Zhao, Arif Ali

et al.

Journal of Plant Biochemistry and Biotechnology, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 7, 2025

Language: Английский

Citations

1

Identification of the group III WRKY subfamily and preliminary functional characterization of CsWRKY59 in cucumber DOI
Ke Xia, Zuying Zhou, Ying-Hui Hu

et al.

Journal of Plant Biochemistry and Biotechnology, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 31, 2025

Language: Английский

Citations

1

Genomic prediction with NetGP based on gene network and multi‐omics data in plants DOI Creative Commons

Longyang Zhao,

Ping Tang, Jinjing Luo

et al.

Plant Biotechnology Journal, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 14, 2025

Summary Genomic selection (GS) is a new breeding strategy. Generally, traditional methods are used for predicting traits based on the whole genome. However, prediction accuracy of these models remains limited because they cannot fully reflect intricate nonlinear interactions between genotypes and traits. Here, novel single nucleotide polymorphism (SNP) feature extraction technique Pearson‐Collinearity Selection (PCS) firstly presented improves across several known models. Furthermore, gene network model (NetGP) deep learning approach designed phenotypic prediction. It utilizes transcriptomic dataset (Trans), genomic multi‐omics (Trans + SNP). The NetGP demonstrated better performance compared to other in predictions, predictions predictions. performed than independent or Prediction evaluations using plants' data showed good generalizability NetGP. Taken together, our study not only offers effective tool plant but also points avenues future research.

Language: Английский

Citations

1