Relationships between gene expression variability, expression levels, and Protein-Protein interactions in mouse and...

Area of Science:

• Evolutionary biology
• Genomics
• Molecular biology

Background:

• Understanding gene expression evolution requires metrics independent of expression levels.
• The metric F* was previously developed to quantify gene expression variability.
• Interdependence of expression levels, variability, and evolutionary rates complicates analysis.

Purpose of the Study:

• To investigate the relationship between gene expression levels and variability.
• To assess the utility of the F* metric across different data types and organisms.
• To identify functional enrichments associated with low gene expression variability.

Main Methods:

• Analysis of single-cell RNA-sequencing data from Mus musculus and Saccharomyces cerevisiae.
• Comparison of single-cell data with non-single-cell and simulated bulk data.
• Gene Ontology (GO) enrichment analyses.

Main Results:

• The relationship between expression levels and variability is complex; F* is not fully separable from expression level.
• Single-cell data show higher apparent variability than bulk data.
• A conserved negative relationship exists between protein-protein interaction connectivity and F*.
• In M. musculus, low-F* genes are enriched for translation/ribosome functions, with additional enrichment for splicing/spliceosome genes when single-cell variability is isolated.
• No significant GO term enrichment was found for low-F* genes in S. cerevisiae.

Conclusions:

• The F* metric offers insights into gene expression variability but is influenced by expression levels.
• Conserved relationships suggest F* captures fundamental biological properties.
• Splicing and spliceosome genes in M. musculus may be under selection for low variation.
• Further research is needed to understand species-specific patterns in gene expression variability.