Integration of Web-Based Tools to Visualize, Integrate, and Interpret Glycogene Expression and Glycomics Data.
Sabarinath Peruvemba SubramanianRebekah L GundryPublished in: Methods in molecular biology (Clifton, N.J.) (2024)
Glycosylation is the most abundant and diverse post-translational modification occurring on proteins. Glycans play important roles in modulating cell adhesion, growth, development, and differentiation. Changes in glycosylation affect protein structure and function and contribute to disease processes. Therefore, understanding glycosylation patterns is key for the identification of targets for the diagnosis of diseases, cellular states, and therapy. Glycosylation is a non template-driven process governed by the action of numerous enzymes and substrate availability that varies among cell types and species. Therefore, qualitative and quantitative assessment of global glycosylation and individual glycans remains challenging because it requires integration of multiple complex data types. Glycan structure and quantity data are often integrated with assessments of gene expression to aid contextualization of observed glycosylation changes within biological processes. However, correlating glycogene expression to the glycan structure is challenging because transcriptional changes may not always concur with the final gene product; there is often a lack of information on nucleotide sugar pools, and the final glycan structure is the result of many different glycogenes acting in concert. To overcome these challenges, interactive online tools are emerging as key resources for facilitating the analysis and integration of glycomics and glycogene expression data. Importantly, these tools work in concurrence with glycan biosynthetic schemes and therefore provide a clear indication of the molecular pathways where the glycan and glycogene are involved. In this chapter, we describe the applications of four freely available online tools that can be used for integrated visualization, interpretation, and presentation of RNAseq and glycomics results.
Keyphrases
- cell surface
- gene expression
- poor prognosis
- electronic health record
- big data
- binding protein
- health information
- social media
- systematic review
- stem cells
- healthcare
- data analysis
- long non coding rna
- bone marrow
- transcription factor
- copy number
- amino acid
- mesenchymal stem cells
- mass spectrometry
- deep learning
- genetic diversity
- genome wide identification