Next-generation sequencing for molecular ecology: a caveat regarding pooled samples.

Area of Science:

• Population genetics
• Bioinformatics
• Genomics

Background:

• Next-generation sequencing (NGS) enables large-scale genetic analysis.
• Pooled sequencing reduces costs but can complicate data interpretation.
• Identifying population structure relies on accurately detecting genetic variation.

Purpose of the Study:

• To develop a model predicting fixed single nucleotide polymorphism (SNP) loci in pooled samples.
• To assess the contribution of population structure versus sampling artifacts to observed SNP patterns.
• To evaluate the reliability of using NGS on pooled samples for population genetics.

Main Methods:

• Development of a model based on Dirichlet-compound multinomial distribution (CMD) and Ewens sampling formula.
• Application of the model to analyze NGS data from Baltic Sea herring.
• Utilizing coalescent simulations to test hypotheses about population structure and sampling effects.

Main Results:

• The model predicted a fraction of fixed SNP loci between two pooled samples.
• Observed fixed loci in Baltic Sea herring data exceeded expectations under simple population structure.
• Coalescent simulations indicated that limited gene copy representation in pooled samples, rather than high population structure, likely explains the surplus of fixed SNPs.

Conclusions:

• The use of NGS on pooled samples for identifying divergent SNPs requires caution.
• Low read depth and limited individuals in pooled NGS data can lead to misinterpretations of population differentiation.
• Individually barcoded samples offer more reliable and potentially cost-effective data analysis for certain population genetics scenarios.