Linkage disequilibrium estimates of contemporary <i>N</i>_e using highly variable genetic markers: a largely untapped resource for applied conservation and evolution

TLDR

Let's parse content. Background: "Abstract Genetic methods are routinely used to estimate contemporary effective population size ( N e ) in natural populations, but the vast majority of applications have used only the temporal (two‐sample) method." Purpose+Mechanism: "We use simulated data to evaluate how highly polymorphic molecular markers affect precision and bias in the single‐sample method based on linkage disequilibrium (LD)." Findings: multiple sentences. Need to condense into one sentence summarizing all findings. Let's combine key points: bias from low-frequency alleles can be reduced to <10%; with 10-20 loci and 50 individuals, precise estimates for Ne<200; difficult for large populations; microsatellite data gives greater precision than temporal method unless temporal samples many generations apart; LD method widely applicable to conservation and evolutionary studies; opportunity to extract more info by wider use and combining methods.

Abstract

Abstract Genetic methods are routinely used to estimate contemporary effective population size ( N e ) in natural populations, but the vast majority of applications have used only the temporal (two‐sample) method. We use simulated data to evaluate how highly polymorphic molecular markers affect precision and bias in the single‐sample method based on linkage disequilibrium (LD). Results of this study are as follows: (1) Low‐frequency alleles upwardly bias , but a simple rule can reduce bias to &lt;about 10% without sacrificing much precision. (2) With datasets routinely available today (10–20 loci with 10 alleles; 50 individuals), precise estimates can be obtained for relatively small populations ( N e &lt; 200), and small populations are not likely to be mistaken for large ones. However, it is very difficult to obtain reliable estimates for large populations. (3) With ‘microsatellite’ data, the LD method has greater precision than the temporal method, unless the latter is based on samples taken many generations apart. Our results indicate the LD method has widespread applicability to conservation (which typically focuses on small populations) and the study of evolutionary processes in local populations. Considerable opportunity exists to extract more information about N e in nature by wider use of single‐sample estimators and by combining estimates from different methods.