GONe: software for estimating effective population size in species with generational overlap

Area of Science:

• Population genetics
• Quantitative genetics
• Bioinformatics

Background:

• Estimating effective population size (N(e)) is crucial for understanding population dynamics and genetic diversity.
• Traditional methods often struggle with populations exhibiting overlapping generations and complex age structures.
• Accurate N(e) estimation informs conservation strategies and evolutionary studies.

Purpose of the Study:

• To introduce GONe, a user-friendly software for estimating N(e) in populations with overlapping generations.
• To implement the Jorde-Ryman modification of the temporal method, incorporating age-specific demographic data.
• To provide a robust tool for geneticists and ecologists studying population structure and change.

Main Methods:

• GONe utilizes the Jorde-Ryman modification of the temporal method, requiring age-specific survival and birth rates.
• Allele frequencies are imported from GENEPOP or TEMPOFS formatted files for consecutive cohorts.
• N(e) is estimated per locus and across all loci, with options for three genetic drift estimators (F(s), F(c), F(k)).

Main Results:

• The software estimates N(e) for each interval between consecutive cohorts.
• Confidence intervals for N(e) are calculated using a chi-square distribution.
• GONe has been validated across a wide range of N(e) values and demographic scenarios, including unequal sex ratios and differing reproductive variances.

Conclusions:

• GONe offers a reliable and accessible solution for estimating effective population size in complex populations.
• The program's validation confirms its accuracy and applicability to diverse demographic conditions.
• GONe is freely available, promoting wider use in population genetics research.