Advances in Omics Approaches for Abiotic Stress Tolerance in Tomato.

Clicks: 555
ID: 70361
2019
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Abstract
Tomato, one of the most important crops worldwide, has a high demand in the fresh fruit market and processed food industries. Despite having considerably high productivity, continuous supply as per the market demand is hard to achieve, mostly because of periodic losses occurring due to biotic as well as abiotic stresses. Although tomato is a temperate crop, it is grown in almost all the climatic zones because of widespread demand, which makes it challenge to adapt in diverse conditions. Development of tomato cultivars with enhanced abiotic stress tolerance is one of the most sustainable approaches for its successful production. In this regard, efforts are being made to understand the stress tolerance mechanism, gene discovery, and interaction of genetic and environmental factors. Several omics approaches, tools, and resources have already been developed for tomato growing. Modern sequencing technologies have greatly accelerated genomics and transcriptomics studies in tomato. These advancements facilitate Quantitative trait loci (QTL) mapping, genome-wide association studies (GWAS), and genomic selection (GS). However, limited efforts have been made in other omics branches like proteomics, metabolomics, and ionomics. Extensive cataloging of omics resources made here has highlighted the need for integration of omics approaches for efficient utilization of resources and a better understanding of the molecular mechanism. The information provided here will be helpful to understand the plant responses and the genetic regulatory networks involved in abiotic stress tolerance and efficient utilization of omics resources for tomato crop improvement.
Reference Key
chaudhary2019advancesbiology Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Chaudhary, Juhi;Khatri, Praveen;Singla, Pankaj;Kumawat, Surbhi;Kumari, Anu;R, Vinaykumar;Vikram, Amit;Jindal, Salesh Kumar;Kardile, Hemant;Kumar, Rahul;Sonah, Humira;Deshmukh, Rupesh;
Journal Biology
Year 2019
DOI
E90
URL
Keywords
Proteomics genome-wide association study metabolomics quantitative trait loci genotyping by sequencing ionomics

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