ONeSAMP 3.0: estimation of effective population size via single nucleotide polymorphism data from one population

Abstract The genetic effective size (Ne) is arguably one of the most important characteristics of a population as it impacts the rate of loss of genetic diversity. Methods that estimate Ne are important in population and conservation genetic studies as they quantify the risk of a population being in...

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Bibliographic Details
Published in:	G3 : genes - genomes - genetics Vol. 14; no. 10
Main Authors:	Hong, Aaron, Cheek, Rebecca G, De Silva, Suhashi Nihara, Mukherjee, Kingshuk, Yooseph, Isha, Oliva, Marco, Heim, Mark, W. Funk, Chris, Tallmon, David, Boucher, Christina
Format:	Journal Article
Language:	English
Published:	US Oxford University Press 07-10-2024
Subjects:	Algorithms Animals Bayes Theorem Genetics, Population Genomic Prediction Models, Genetic Polymorphism, Single Nucleotide Population Density Software single nucleotide polymorphism data effective population size genetic diversity conservation
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Summary:	Abstract The genetic effective size (Ne) is arguably one of the most important characteristics of a population as it impacts the rate of loss of genetic diversity. Methods that estimate Ne are important in population and conservation genetic studies as they quantify the risk of a population being inbred or lacking genetic diversity. Yet there are very few methods that can estimate the Ne from data from a single population and without extensive information about the genetics of the population, such as a linkage map, or a reference genome of the species of interest. We present ONeSAMP 3.0, an algorithm for estimating Ne from single nucleotide polymorphism data collected from a single population sample using approximate Bayesian computation and local linear regression. We demonstrate the utility of this approach using simulated Wright–Fisher populations, and empirical data from five endangered Channel Island fox (Urocyon littoralis) populations to evaluate the performance of ONeSAMP 3.0 compared to a commonly used Ne estimator. Our results show that ONeSAMP 3.0 is broadly applicable to natural populations and is flexible enough that future versions could easily include summary statistics appropriate for a suite of biological and sampling conditions. ONeSAMP 3.0 is publicly available under the GNU General Public License at https://github.com/AaronHong1024/ONeSAMP_3. The effective size (Ne) is crucial in population genetics for assessing genetic diversity loss. Estimating Ne are limited. Hong et al. introduce ONeSAMP 3.0, an algorithm using approximate bayesian computation and local linear regression to estimate Ne from single population SNP data without extensive genetic information. Tested on simulated and real data, ONeSAMP 3.0 outperforms traditional methods and is adaptable to various biological contexts. Moreover, with parallel processing, it is both time and memory efficient, allowing for estimations for large datasets.
Bibliography:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Conflicts of interest The author(s) declare no conflicts of interest.
ISSN:	2160-1836 2160-1836
DOI:	10.1093/g3journal/jkae153