Brooklyn plots to identify co-expression dysregulation in single cell sequencing.

Area of Science:

• Genomics
• Molecular Biology
• Computational Biology

Background:

• Altered open chromatin regions are implicated in human disorders by affecting gene expression.
• Detecting global changes in gene co-expression within single-cell RNA sequencing (scRNA-seq) data is challenging.

Purpose of the Study:

• To develop a method for detecting global changes in genomically-related adjacent gene co-expression in scRNA-seq data.
• To identify altered patterns of open chromatin in disease states.

Main Methods:

• Developed a software package to analyze scRNA-seq data.
• Utilized 'Brooklyn plots' to test for non-randomness in gene co-expression within chromosomal intervals.
• Quantified the percentage of significantly co-expressed genes from the same chromosome in ~10 MB intervals.

Main Results:

• Established a low baseline of co-expression in scRNA-seq data for most cell types.
• Observed altered co-expression patterns in dilated cardiomyopathy cardiomyocytes, indicative of changes in open chromatin.
• Identified potential links between altered chromatin and transcriptional bursting at a single-cell level.

Conclusions:

• The developed method can detect global changes in gene co-expression from scRNA-seq data.
• Altered open chromatin patterns, associated with specific human disorders like dilated cardiomyopathy, can be identified.
• This approach may reveal disease-specific transcriptional bursting phenomena not detectable by bulk analysis.