Advanced omics: from single-cell to meta-omics approaches

Omics technologies have revolutionized our ways of looking at the relationship between genotype and phenotype of living organisms. Those technologies are nowadays widely applied to many organisms (bacteria, plants, animals, human). Yet for many years researchers have been looking only at average effects by analysing bulk samples. Recently, single-cell analyses have become available for many cell types in different organisms. Today these technologies are mostly employed in the form of single-cell transcriptomics, and can provide information about, for instance, spatiotemporal development of an infection or of an organism or tissue (e.g. plant’s root). However, new methods are currently being implemented for the study of the proteome and metabolome at a single cell resolution.
Single cells can also compose individual organisms (i.e. bacteria) that can live in communities such as the human or animal microbiomes or the rhizosphere of plant. Knowing the composition and quantitative traits of these communities at different levels (genomics, transcriptomics, proteomics, and metabolomics) can tell us about the functions of the system as a whole and help us in designing interventions for the enhancement or removal of specific characteristics.
Therefore, single-cells and meta-omics methods are enabling researcher to investigate challenging questions such as defining tumour or patient heterogeneity. Besides their use can result in the development of applications such as biofertilizers or tools for biopest control.
In this course you as a student will have the chance to discover the new developments in the field of single-cell and multi-organism omics with a focus on exploring the technologies but more deeply the data analysis connected to the complex information produced. Together with your colleagues you will investigate and report on the analysis of such data highlighting the richness of the biological information contained.

After successful completion of this course students are expected to be able to:

• Define the meta- and single-cell omics approaches currently available
• Illustrate the questions answered by meta- and single-cell omics approaches
• Execute basic and advanced analysis of meta- and single-cell omics data
• Develop a professional notebook containing data, code and descriptions to report on project’s results considering FAIR principles
• Assess limitation and applicability of meta- and single-cell omics approaches

Assumed Knowledge:
Molecular Systems Biology (SSB30306), Advanced Bioinformatics (BIF30806)