Objective:

To develop a platform for simultaneous analysis of genomic DNA and RNA in individual cells to link genotype to phenotype.

Approach:

Key Findings:

• SDR-seq identified how coding and noncoding variants influence gene expression patterns in human induced pluripotent stem cells (iPSCs).
• In B cell lymphoma samples, SDR-seq revealed a correlation between mutational burden and gene expression signatures related to tumor behavior.
• Cells with higher mutation counts showed increased B cell receptor signaling and elevated tumorigenesis-related gene expression.

Interpretation:

SDR-seq provides insights into the functional consequences of genetic variants and their impact on gene expression, which is crucial for understanding disease mechanisms.

Limitations:

• The study emphasizes SDR-seq as a research tool, with potential clinical applications yet to be fully realized.

Conclusion:

SDR-seq offers a scalable framework for dissecting regulatory networks in pathology, potentially aiding in the functional characterization of variants in clinical settings.

Sources:

• Nature Methods
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