Armando Caballero

A new method is developed to estimate the contemporary effective population size ( N e ) from linkage disequilibrium (LD) between SNPs without information on their location, which is the usual scenario in non‐model species. The general theory of linkage disequilibrium is extended to include the contribution of full‐sibs to the measure of LD, leading naturally to the estimation of N e in monogamous and polygamous mating systems, as well as in multiparous species, and with non‐random distributions of full‐sib family size due to selection or other causes. Prediction of confidence intervals for N e estimates was solved using a small artificial neural network trained on a dataset of over 10 5 simulation results. The method, implemented in a user‐friendly and fast software ( currentNe ), is able to estimate N e even in problematic scenarios with large population sizes or small sample sizes and provides confidence intervals that are more consistent than resampling methods.

The availability of a large number of high‐density markers (SNPs) allows the estimation of historical effective population size ( N e ) from linkage disequilibrium between loci. A recent refinement of methods to estimate historical N e from the recent past has been shown to be rather accurate with simulation data. The method has also been applied to real data for numerous species. However, the simulation data cannot encompass all the complexities of real genomes, and the performance of any estimation method with real data is always uncertain, as the true demography of the populations is not known. Here, we carried out an experimental design with Drosophila melanogaster to test the method with real data following a known demographic history. We used a population maintained in the laboratory with a constant census size of about 2800 individuals and subjected the population to a drastic decline to a size of 100 individuals. After a few generations, the population was expanded back to the previous size and after a few further generations again expanded to twice the initial size. Estimates of historical N e were obtained with the software GONE both for autosomal and X chromosomes from samples of 17 individuals sequenced for the whole genome. Estimates of the historical effective size were able to infer the patterns of changes that occurred in the populations showing generally good performance of the method. We discuss the limitations of the method and the application of the software carried out so far.