Conservation Genetics Resources

, Volume 6, Issue 3, pp 535–538

Hundreds of SNPs for the Endangered pygmy hippopotamus (Choeropsis liberiensis)

  • Helen Senn
  • Paul O’Donoghue
  • Ross McEwing
  • Rob Ogden
Technical Note

DOI: 10.1007/s12686-014-0178-8

Cite this article as:
Senn, H., O’Donoghue, P., McEwing, R. et al. Conservation Genet Resour (2014) 6: 535. doi:10.1007/s12686-014-0178-8


The pygmy hippo is an Endangered mammal endemic to West Africa, of which only 2,000–3,000 are left in the wild. Until now genetic resources to conduct monitoring of wild populations and to facilitate captive breeding have been lacking. In this study we used restriction-site associated DNA sequencing of five pygmy hippo samples to generate 1,619 high confidence candidate single nucleotide polymorphisms (SNPs) suitable for population genetic analysis. A subset of 10 of SNPs generated were validated via resequencing with 100 % success rate and through the use of KASPar DNA probes (Kbiosciences) with 90 % success rate. To facilitate future research we present the list of 1,619 SNPs ranked according to mean genotype confidence and mean coverage.


RAD sequencing SNP discovery Conservation genetics Pygmy hippopotamus Sequence data 

Supplementary material

12686_2014_178_MOESM1_ESM.xls (1.9 mb)
Supplementary Material 1: list of 1,619 SNP genotypes. (XLS 1980 kb)
12686_2014_178_MOESM2_ESM.txt (14.9 mb)
Supplementary Material 2: Fasta file of tags with single contigs (TXT 15304 kb)
12686_2014_178_MOESM3_ESM.txt (7.4 mb)
Supplementary Material 3: VCF file of unfiltered SNPS (TXT 7607 kb)
12686_2014_178_MOESM4_ESM.xls (26 kb)
Supplementary Material 4: Primers used for validations. (XLS 26 kb)

Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  • Helen Senn
    • 1
  • Paul O’Donoghue
    • 2
  • Ross McEwing
    • 1
  • Rob Ogden
    • 1
  1. 1.WildGenes LaboratoryRoyal Zoological Society of ScotlandEdinburghUK
  2. 2.Department of Biological SciencesUniversity of ChesterChesterUK

Personalised recommendations