Benchmarking sample pooling for epigenomics of natural populations

Area of Science:

• Environmental epigenetics
• Ecological genomics

Background:

• DNA methylation (DNAm) is crucial for rapid acclimation to environmental changes.
• Detecting subtle DNAm differences in natural populations requires large sample sizes, which are costly with individual sequencing.
• Pooling DNA before library preparation is a potential cost-saving strategy for ecological epigenetics, but lacks established protocols.

Purpose of the Study:

• To evaluate the efficacy of pooled versus individual DNA libraries for capturing DNA methylation signals in natural populations.
• To compare the cost-efficiency and data yield of pooled and individual library preparation methods.
• To provide recommendations for future epigenomic studies in ecological research.

Main Methods:

• Whole-epigenome sequencing of DNA from two invasive mollusc species (Corbicula fluminea, Dreissena polymorpha) from polluted and unpolluted sites in Italy.
• Generation of both pooled and individual DNA libraries from the same individuals.
• Comparison of DNA methylation patterns, data yield, and differentially methylated regions (DMRs) between pooled and individual library approaches.

Main Results:

• Pooled DNA libraries effectively capture genome-wide and global DNA methylation signals comparable to individual libraries.
• Pooled libraries provide significantly higher data yield and detect more differentially methylated regions (DMRs) than individual libraries.
• Computationally pooled data from individual libraries showed lower DMR detection and overlap compared to wet-lab pooled libraries.

Conclusions:

• DNA pooling is a viable and cost-effective strategy for ecological epigenetics research, offering increased power for DMR detection.
• High initial coverage (15×) is recommended for individual libraries to maximize data quality.
• Further research is needed to optimize computational pooling strategies and understand discrepancies between wet-lab and computational pooling methods.