The goal of this project in quantitative genomics was to identify core pathways that underlie myopathy and evaluate differences in gene expressions of mTORC1 in different treatment conditions and in the different subjects.

The signaling pathway regulating the activity of the mammalian target of rapamycin complex 1 (mTORC1) controls skeletal muscle homeostasis, which is determined by the difference in the rates of protein synthesis and degradation.

🌟 Highlights:

1. An effect on gene expression levels from the treatment of Rapamycin was found
2. Key genes in the molecular pathway of mTOR could be identified
3. Dimensionality reduction by PCA made the data easier to process
4. The K-means algorithm allowed to cluster the subjects and conditions by similarity

File structure:

.
├── Gene Expression PCA.ipynb     # Jupyter Notebook with Data Analysis                                         
├── GeneExpressionTable.tsv       # Gene expression data
├── Images                        # Images
│   ├── ConditionPCA.png            # Plot of 3 first principal components by condition
│   ├── GeneExpression.png          # Header image
│   └── mTOR.jpg                    # mTOR pathway
└── * README.md                   # Project overview and instructions                    

The signaling pathway regulating the activity of the mammalian target of rapamycin complex 1 (mTORC1) controls skeletal muscle homeostasis, which is determined by the difference in the rates of protein synthesis and degradation. In the skeletal muscle, mTORC1 activation occurs in response to a variety of signals, including growth factors, nutrients, energy state and mechanical load.

To study the function of mTORC1 in the skeletal muscle, the laboratory of Dr. Markus Rüegg (Biozentrum) has developed a mouse model called TSCmKO, in which the TORC1 inhibitor Tsc1 was selectively deleted in skeletal muscles. It was found that these mice develop precocious sarcopenia, characterized by fragmentation of the neuromuscular junction, progressive loss of muscle mass and loss of muscle force.

Treatment of TSCmKO mice with rapamycin, an mTORC1 inhibitor, ameliorated the myopathy. To identify core pathways that underlie myopathy in TSCmKO mice, mRNA-seq samples from EDL muscle of TSCmKO mice and wild-type mice of the age of 3 months (young phase in both TSCmKO and wild-type mice) and 9 months (adult phase in wild-type mice and sarcopenic phase in TSCmKO mice) in combination with rapamycin treatment were generated and sequenced at the Quantitative Genomics facility of the Biozentrum.

The table called “GeneExpressionTable.tsv” contains the information about the expression of 117 genes in log2[TPM] units measured in the Musculus extensor digitorum longus of the following mice:

• Condition 1: 5 replicates of 3 months old wild-type mice
• Condition 2: 5 replicates of 3 months old wild-type mice treated with rapamycin
• Condition 3: 5 replicates of 3 months old TSCmKO mice
• Condition 4: 5 replicates of 3 months old TSCmKO mice treated with rapamycin
• Condition 5: 5 replicates of 9 months old wild-type mice
• Condition 6: 5 replicates of 9 months old wild-type mice treated with rapamycin
• Condition 7: 5 replicates of 9 months old TSCmKO mice
• Condition 8: 5 replicates of 9 months old TSCmKO mice treated with rapamycin

To run or interact with the code, run the following command from the command line (CLI):

jupyter lab

In case you still have installed the old version of Jupyter you might still use:

jupyter notebook

From your browser you can then access the notebook.

A notebook is a shareable document that combines computer code, plain language descriptions, data, rich visualizations like 3D models, charts, graphs and figures, and interactive controls.

The PCA was performed in both directions (conditions and genes). The first three Principal Components were examined and the variance explained by it was calculated. The replicates were clustered with a k-means algorithm according to their expression levels.

• The data was provided by the Quantitative Genomics facility of the Biozentrum at the University of Basel.

Found a bug? Want more features? Find something missing in the documentation? Let us know! Please don't hesitate to file an issue and make a recommendation.

GeneExpressionPCA - Principal Component Analysis of Gene Expression data

The MIT License (MIT)

Copyright (c) 2019 Thierry Grimm

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