Estimation of contemporary effective population size in plant populations: Limitations of genomic datasets.
Name
Evolutionary_Applications_-_2024_-_Gargiulo_-_Estimation_of_contemporary_effective_population_size_in_plant_populations_.pdf
Description
visibility:open
Size
806.21 KB
Format
Adobe PDF
Checksum (CRC64NVME)
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Resource type
Journal article
Date published
May 3, 2024
Abstract
Effective population size ( ) is a pivotal evolutionary parameter with crucial implications in conservation practice and policy. Genetic methods to estimate 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 (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 using the algorithm implemented in GONE, in addition to exploring some typical biological limitations that may affect estimation using the LD method, such as the occurrence of population structure. We show how accuracy and precision of 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 estimates obtained with GONE for the last generations with the contemporary estimates obtained with the programs and NeEstimator.
Project(s)
Priority 1: Ecosystem Stewardship
Funder
| Funder name | Awards |
European Cooperation in Science and Technology, Belgium | “Estimating effective population size in genomic datasets: test of methods and assumptions”, CA18134 “Genomic Biodiversity Knowledge for Resilient Ecosystems (G-BiKE)” |
Genoscope, France | |
Commissariat à l'Énergie Atomique et aux Énergies Alternatives, France | |
France Génomique, France | ANR-10-INBS-09-08 |
Powell Center for Synthesis and Analysis, U.S. Geological Survey, United States | |
Journal title
Evolutionary Applications
Volume
17
Issue
5
Article number
e13691
Publisher
John Wiley & Sons Ltd.
Place of publication
UK
ISSN
1752-4571
eISSN
1752-4571
Date accepted
April 3, 2024
Official URL
Rights statement
In Copyright
Additional information
IF = 4.929 (2023-2024)