Estimation of contemporary effective population size in plant populations: Limitations of genomic datasets

Abstract

Effective population size (<i>N</i> _e) is a pivotal evolutionary parameter with crucial implications in conservation practice and policy. Genetic methods to estimate <i>N</i> _e have been preferred over demographic methods because they rely on genetic data rather than time-consuming ecological monitoring. Methods based on linkage disequilibrium (LD), in particular, have become popular in conservation as they require a single sampling and provide estimates that refer to recent generations. A software program based on the LD method, GONE, looks particularly promising to estimate contemporary and recent-historical <i>N</i> _e (up to 200 generations in the past). Genomic datasets from non-model species, especially plants, may present some constraints to the use of GONE, as linkage maps and reference genomes are seldom available, and SNP genotyping is usually based on reduced-representation methods. In this study, we use empirical datasets from four plant species to explore the limitations of plant genomic datasets when estimating <i>N</i> _e using the algorithm implemented in GONE, in addition to exploring some typical biological limitations that may affect <i>N</i> _e estimation using the LD method, such as the occurrence of population structure. We show how accuracy and precision of <i>N</i> _e estimates potentially change with the following factors: occurrence of missing data, limited number of SNPs/individuals sampled, and lack of information about the location of SNPs on chromosomes, with the latter producing a significant bias, previously unexplored with empirical data. We finally compare the <i>N</i> _e estimates obtained with GONE for the last generations with the contemporary <i>N</i> _e estimates obtained with the programs <i>currentNe</i> and NeEstimator.