Dataset and R code: Genetic diversity of lion populations in Kenya: evaluating past management practices and recommendations for future conservation actions by Chege M et.al
Data files
Mar 14, 2024 version files 354.60 KB
Abstract
The decline of lions (Panthera leo) in Kenya has raised conservation concerns on their overall population health and long-term survival. This study aimed to assess the genetic structure, differentiation, and diversity of lion populations in the country, while considering the influence of past management practices. Using a lion-specific Single Nucleotide Polymorphism (SNP) panel, we genotyped 171 individuals from 12 populations representative of areas with permanent lion presence. Our results revealed a distinct genetic pattern with pronounced population structure, confirmed a north-south split, and found no indication of inbreeding in any of the tested populations. Differentiation seems to be primarily driven by geographical barriers, human presence, and climatic factors, but management practices may have also affected the observed patterns. Notably, the Tsavo population displayed evidence of admixture, perhaps attributable to its geographic location as a suture zone, vast size, or to past translocations, while the fenced populations of Lake Nakuru National Park and Solio Ranch exhibited reduced genetic diversity due to restricted natural dispersal. The Amboseli population had a high number of monomorphic loci likely reflecting a historical population decline. This illustrates that patterns of genetic diversity should be seen in the context of population histories, and that future management decisions should take these insights into account. To address the conservation implications of our findings, we recommend prioritizing the maintenance of suitable habitats to facilitate population connectivity. Initiation of genetic restoration efforts and separately managing populations with unique evolutionary histories is crucial for preserving genetic diversity and promoting long-term population viability.
README: dataset and r code associated with the publication entitled "Genetic diversity of lion populations in Kenya: evaluating past management practices and recommendations for future conservation actions" by Chege M et.al.
https://doi.org/10.5061/dryad.s4mw6m9d8
We provide the following description of the dataset and scripts for analysis carried out in R: We have split the data and scripts for ease of reference i.e.,
1.) Script 1: titled ‘Calc_He_Ho_Ar_Fis’. For calculating the genetic diversity indices i.e. allelic richness (AR), Private alleles (AP), Inbreeding coefficients (FIS), expected (HE) and observed heterozygosity (HO). This script uses:
“data_HoHeAr.txt” dataset. This dataset has information on individual samples, including their geographical area (population) of origin and the corresponding 335 autosomal single nucleotide polymorphism (SNP) reads.
‘shompole2.txt’ this bears the dataset from the Shompole lion population that was separated from “data_HoHeAr.txt” file. SNP 81 and 82 were removed from this file as they were causing an error in the calculation of allelic richness.
‘diversityKenya_lions.csv’ data file contains the genetic diversity scores for each of the 12 populations for carrying out the two sample t-test to test for significant genetic differences between closed and open lion populations.
2.) Script 2:titled ‘Calc_PCA_DAPC_Kenya’. For calculating Principal Component Analysis (PCA) and Discriminant Analysis of Principal Components (DAPC). This script uses:
- “data_DAPC_PCA.txt” dataset. This dataset also has information on the individual samples, including their geographical area (population) of origin and the corresponding 335 autosomal single nucleotide polymorphism (SNP) reads. In this dataset we removed sample Ke02 as it was an outlier.
3.) Script 3: titled ‘supplementary_snmf’. The code detailed in this script was used to estimate individual ancestry coefficients using Sparse Nonnegative Matrix Factorization algorithms (sNMF). To run this analysis GPS coordinates of the corresponding samples are required, we however cannot provide these due to the threatened status of lions in Kenya. We have made the script quite self explanatory, it follows similar methodology as that is detailed in François 2016 i.e. http://membres-timc.imag.fr/Olivier.Francois/tutoRstructure.pdf.
Methods
This dataset was obtained from 12 kenyan lion populations. After DNA extraction, SNP genotyping was performed using an allele-specific KASP technique.
The attached datasets includes the .txt and .str versions of the autosomal SNPs to aid in reproducing the results.