Both transcriptomics and proteomics are important tools to obtain information about gene expression. From a biological point of view, the transcriptome represents the intermediate state of gene expression and can reflect mechanisms such as transcriptional regulation and post-transcriptional regulation. Proteins are the direct functional performers of an organism, and thus the study of their expression levels has an irreplaceable advantage. To comprehensively investigate plant pathogenesis and stress mechanisms, and precisely study the expression patterns and regulatory mechanisms of important genes, only by combining transcriptomic and proteomic expression data to systematically study samples, can we truly observe the mRNA-protein correlation, and then explain various problems in botanical research from a holistic perspective.

What We Offer

Lifeasible offers combined plant proteomic and transcriptomic analyses designed to combine data from proteomics and transcriptomics for analysis. Currently, it is possible to capture almost the entire transcriptome through strategies similar to those used to screen DNA, namely microarray and sequencing technologies. Among them, transcriptome sequencing is more comprehensive and can achieve higher coverage to capture essentially any form of RNA. studies that can be performed in proteomics include qualitative and quantitative studies of the proteome, mainly achieved using mass spectrometry-based techniques. The services can be applied to a variety of fields, including studies of stress resistance mechanisms, growth and development mechanisms, and breeding conservation studies.

Category	Content
Expression association analysis	Association number statistics
	Expression correlation analysis
	Expression clustering analysis
Functional annotation and enrichment analysis of association results	GO association analysis
	KEGG association analysis

We Do Better

Transcriptomics and proteomics are two different molecular levels reflecting the expression of genes in an organism. The purpose of Lifeasible' association analysis is to achieve comparison and complementarity between the two sets of data, to gain a deeper understanding of the intrinsic relationship between protein and gene expression in plants, to reveal gene expression and post-transcriptional regulatory status, and to obtain more complete expression information of plant samples.

• We analyze expression levels at different layers to build a panorama of plant expression.
• We perform cross-validation based on multi-omics findings to deeply explore regulatory mechanisms.
• We build protein and RNA databases, which can significantly improve the quantity and speed of protein and RNA identification.
• We can validate gene mutation information at the protein level to refine the research results.

Reference

1. Nobori T., et al., "Multidimensional gene regulatory landscape of a bacterial pathogen in plants." Nature Plants, 2020, 6:883-896.

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For research or industrial use.

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