2025/08/06 by Eva K. Fischer, Youngseok Song, Wen Zhou +1 · 1 voice
Biochemistry, Genetics and Molecular Biology · #Bioinformatics and Genomic Networks #CRISPR and Genetic Engineering #Evolution and Genetic Dynamics
paper · doi:10.1093/molbev/msaf194
openalex publication_date 2025/08/06 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/01
The explosion of next-generation sequencing technologies has allowed researchers to move from studying single genes to studying thousands of genes, and thereby to also consider the relationships within gene networks. Like others, we are interested in understanding how developmental and evolutionary forces shape the expression of individual genes, as well as the interactions among genes. In pursuing these questions, we confronted the central challenge that standard approaches fail to control the Type I error and/or have low power in the presence of high dimensionality (i.e. large number of genes) and small sample size, as in many gene expression studies. To overcome these challenges, we used random projection tests and correlation network comparisons to characterize differences in network connectivity and density. We detail central challenges, discuss sample size guidelines, and provide rigorous statistical approaches for exploring coexpression differences with small sample sizes. We apply these approaches in a species known for rapid adaptation-the Trinidadian guppy (Poecilia reticulata)-and find evidence for coexpression network differences at developmental and evolutionary timescales. Our findings suggest that flexibility in gene coexpression relationships could promote evolvability.