Effective Population Size Estimation in Large Marine Populations: Considering Current Challenges and Opportunities...

Area of Science:

• Population genetics
• Genomics
• Bioinformatics

Background:

• Next-generation sequencing (NGS) provides high-density genomic data, enhancing effective population size (Ne) estimation.
• Traditional Ne estimation methods face challenges with large populations and complex factors like migration.
• Computer simulations are crucial for assessing Ne estimation methods' robustness.

Purpose of the Study:

• To present a simulation framework for generating realistic genomic data for large populations.
• To evaluate the performance and limitations of various Ne estimation methods.
• To provide reproducible resources for Ne estimation research and validation.

Main Methods:

• Developed a simulation framework using computational genomic tools to create biologically realistic datasets.
• Generated genotype data with varying sample sizes and locus numbers.
• Analyzed simulated data using NeEstimator2, GONE, and GADMA software.

Main Results:

• The simulation framework successfully reproduces key features of large natural population data.
• Demonstrated the application of the framework for evaluating Ne estimation methods.
• Provided detailed, annotated simulation scripts for reproducibility.

Conclusions:

• The developed simulation framework is a valuable tool for studying Ne estimation methods in population genetics.
• This resource supports method comparison and validation, particularly for conservation practitioners and students.
• Enhances the understanding and application of Ne estimation in high-abundance populations.