Annotation of Plant Gene Function via Combined Genomics, Metabolomics and Informatics

Abstract

Given the ever expanding number of model plant species for which complete genome sequences are available and the abundance of bioresources such as knockout mutants, wild accessions and advanced breeding populations, there is a rising burden for gene functional annotation. In this protocol, annotation of plant gene function using combined co-expression gene analysis, metabolomics and informatics is provided (Figure 1). This approach is based on the theory of using target genes of known function to allow the identification of non-annotated genes likely to be involved in a certain metabolic process, with the identification of target compounds via metabolomics. Strategies are put forward for applying this information on populations generated by both forward and reverse genetics approaches in spite of none of these are effortless. By corollary this approach can also be used as an approach to characterise unknown peaks representing new or specific secondary metabolites in the limited tissues, plant species or stress treatment, which is currently the important trial to understanding plant metabolism. Video LinkThe video component of this article can be found at https://www.jove.com/video/3487/ Protocol 1. Sample Preparation 1. Plant materials are harvested and frozen immediately. 2. Frozen plant materials are powdered by mixer mill (or mortar) and stored in Falcon tube or Eppendorf tube at -80 °C.

Large-Scale Multi-Omics Genome-Wide Association Studies (Mo-GWAS): Guidelines for Sample Preparation and Normalization

“…By performing the necessary correction for the analytical variations as described above, several integrated approaches can be performed in addition to GWAS, such as metabolitemetabolite, metabolite-lipid correlation analysis, correlation analysis to phenomic data to shed light on more complex traits, and/or co-expression analysis to further unravel the basis of biological systems 58 .…”

Co-regulation of Clustered and Neo-functionalized Genes in Plant-Specialized Metabolism

“…Co-expression network analysis, which is assessed via the analysis of large-scale transcriptomics data, has greatly aided the elucidation of gene annotation and functional genomics in a broad range of plant species [7,[43][44][45]. Co-expression network analysis is well-developed in plant science, however, such multi-gene coefficient based approaches can still be further refined by data optimization strategies, including the use of target-defined sub-datasets [43,46] and targeted gene network analysis [47,48]. Neighboring gene sets found in genome-wide gene annotation have been tested as an approach for the prediction of operon-like gene clusters in the Arabidopsis genome [30,49].…”

Plant genome and transcriptome annotations: from misconceptions to simple solutions

“…Indeed, tissue-specific data might even be helpful to unravel tissue-specific processes, as has been done for A. thaliana seed coat mucilage [ 75 , 76 ]. In the case where metabolic data are available, this might be used to complement the guilt-by-association approach using protocols described recently [ 77 , 78 ].…”