Bioinformatics for plant and agricultural discoveries in the age of multiomics: A review and case study of maize nodal root growth under water deficit

Abstract

Advances in next‐generation sequencing and other high‐throughput technologies have facilitated multiomics research, such as genomics, epigenomics, transcriptomics, proteomics, metabolomics, and phenomics. The resultant emerging multiomics data have brought new challenges as well as opportunities, as seen in the plant and agriculture science domains. We reviewed several bioinformatic and computational methods, models, and platforms, and we have highlighted some of our in‐house developed efforts aimed at multiomics data analysis, integration, and management issues faced by the research community. A case study using multiomics datasets generated from our studies of maize nodal root growth under water deficit stress demonstrates the power of these datasets and some other publicly available tools. This analysis also sheds light on the landscape of such applied bioinformatic tools currently available for plant and crop science studies and introduces emerging trends and how they may affect the future.

The Promises, Challenges, and Opportunities of Omics for Studying the Plant Holobiont

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LettuceDB: an integrated multi-omics database for cultivated lettuce

“…Focusing solely on individual data types leads to a limited and incomplete understanding biological process, while integrating multiple omics datasets enables a more comprehensive interpretation ( 3 , 4 ). With advancing sequencing technologies and bioinformatics tools, extensive multi-omics studies have been conducted on various crop species and abundant omics data have been generated in the last decade ( 5–7 ). The first steps to break the barriers of multi-omics data is to integrate such data and promote data sharing through public databases.…”

Molecular Mechanisms Underlying the Progression of Aortic Valve Stenosis: Bioinformatic Analysis of Signal Pathways and Hub Genes

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