MF9395 In silico Study of Genome Regulation – Omics Data Analysis

University of Oslo, Faculty of Medicine

Course content

There are three main goals in the course "In silico study of genome regulation":

1) Overview of genome regulation in biomedical research (e.g., molecular biology of protein-DNA interactions, histone modification, DNA methylation, DNA mutations and 3- D genome regulation via chromatin-chromatin interactions), the effect of genome regulation in general and their association with disease, and the basic data analysis skills such as the application of Unix, R, and Python in high throughput sequencing.

2) Applications of statistical methods and data mining tools in big data analysis based on various experiments such as from the aforementioned topics in transcriptomics, epigenomics, and 3D genome regulation et al. For example, the application of various high throughput sequencing (e.g., RNA-seq, ChIP-seq, ATAC-seq, Hi-C, WGS, and WGBS etc) in molecular biology research and the relevant data analysis and result interpretation, and the understanding of data mining methods (e.g., regression, clustering, PCA, network prediction etc.) utilized in in silico genome regulation.

3) Integrated data analysis based on the above-mentioned multiple-omics datasets. This will be illustrated through advanced research topics from the earlier publications, where omics-datasets were used to tackle a specific biological problem such as network inference, tumor classification, regulatory mutation prediction, and differential methylation analysis et al.

Learning outcome

From the proposed course, students will acquire basic knowledge in in silico study of genome regulation such as the analysis of various experimental datasets (e.g., transcriptomics, epigenetics, 3D chromatin organization, protein-DNA interaction, and DNA mutations etc) and the application of multiple-omics datasets in biomedical research.

In the course, students will not only learn the theory of methods and tools in computational genome regulation, but also practice the computational analysis by using diverse genomic datasets. For example, analysis of gene expression, histone modifications/TF-binding, nucleosome density, DNA methylation profiles, DNA mutation, and 3D chromatin organization in RNA-seq, ChIP-seq, ATAC-seq, WGBS, WGS, and Hi-C experiments, respectively. Especially, real research examples of in silico genome regulation studies will be illustrated based on earlier publications.

After the course, students will understand the difference between the low-level analysis (e.g., quality assessment, alignment, normalization) and the high-level analysis (e.g., peak calling, visualization, differential analysis, genome annotation) in high throughput sequencing. For example, the former one is a routing work and time consuming but with standard pipelines, which are often done by an engineer in the core facility. The latter one requires a person with both domain specific knowledge and advanced bioinformatics skills such as a researcher. Finally, students will be able to design/plan/perform in silico study of genome regulation by using multiple-omics datasets, and will be capable of searching for correct external help (e.g., collaborators) in future.

Overall, the proposed course will be an excellent learning source for the next generation biologists or biomedical researchers for interested students locally at Campus Ahus. Nowadays, biology becomes more and more quantitative, there are far more datasets than qualified personnel can handle. It is essential for the future biologists or biomedical researchers to have sufficient knowledge in both molecular biology and quantitative data analysis. In a metaphor, people do not need to build a car but they have to learn to drive a car to their desired destination. That is all this course is designed for, the PhD/master students, who are devoted to molecular biology research.

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