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Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization
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Field-omics-understanding large-scale molecular data from field crops.

Erik Alexandersson1, Dan Jacobson2, Melané A Vivier2

  • 1Department of Plant Protection Biology, Swedish University of Agricultural Sciences Alnarp, Sweden.

Frontiers in Plant Science
|July 8, 2014
PubMed
Summary

Field-omics integrates genome-scale molecular data (genomics, transcriptomics, proteomics, metabolomics, metagenomics) with crop field trials. This approach aims to unravel the complex interactions between genotype, environment, and management in agriculture.

Keywords:
bioinformaticscropsfield samplingfield trialsfield-omicsmetabolomicsproteomicstranscriptomics

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Area of Science:

  • Agricultural Science
  • Molecular Biology
  • Bioinformatics

Background:

  • Advances in molecular analysis enable genome-scale data capture in crop field trials.
  • Understanding genotype-environment interactions in multi-stress field conditions remains challenging.
  • Integrating diverse molecular and field data requires innovative approaches.

Purpose of the Study:

  • To address the challenge of integrating large-scale molecular data from crop field trials.
  • To propose a framework for combining multi-omics data with field-based research.
  • To introduce the concept and term 'field-omics'.

Main Methods:

  • Highlighting the need for cross-disciplinary platforms for experimental design, sampling, and analysis.
  • Advocating for the integration of genomics, transcriptomics, proteomics, metabolomics, and metagenomics.
  • Adapting current field data recording and analysis strategies for omics data integration.

Main Results:

  • The study defines 'field-omics' as a novel approach.
  • It emphasizes the coupling of multi-omics information with traditional field trial practices.
  • It calls for the adaptation of field data analysis to facilitate omics data integration.

Conclusions:

  • Field-omics provides a pathway to understand complex molecular and environmental interactions in crops.
  • This integrated approach is crucial for deciphering the genotype-environment-management nexus.
  • The proposed framework facilitates the biological interpretation of large-scale field trial datasets.