Development and evaluation of a novel single nucleotide polymorphism panel for North American bison.
North American bison
conservation genetics
population genetics – empirical
wildlife management
Journal
Evolutionary applications
ISSN: 1752-4571
Titre abrégé: Evol Appl
Pays: England
ID NLM: 101461828
Informations de publication
Date de publication:
Feb 2024
Feb 2024
Historique:
received:
23
05
2023
revised:
17
11
2023
accepted:
09
01
2024
medline:
23
2
2024
pubmed:
23
2
2024
entrez:
23
2
2024
Statut:
epublish
Résumé
Genome-wide single nucleotide polymorphism (SNP) genotyping platforms have become increasingly popular in characterizing livestock and wildlife populations, replacing traditional methods such as microsatellite fragment analysis. Herein, we report the development and evaluation of a novel bison SNP panel for population management and conservation. Initially, 2474 autosomal SNPs were selected from existing bison whole-genome sequences and variable sites among bison on the GGSP bovine 50K Chip, based on minor allele frequency, data completeness, and chromosome location. Additionally, 20 mitochondrial SNPs were chosen to identify known mitochondrial haplotypes in bison according to previous research. The SNPs were further evaluated using genotyping-by-sequencing with 190 bison, representing the historical lineages that survived the major population crash of the late 1800s. Variants with high potential for genotyping error were filtered out, and the remaining SNPs were placed on a custom Illumina™ array. The final panel consisting of 798 autosomal and 13 mitochondrial SNPs was used to establish baseline genetic parameters, compare populations, and assign mitochondrial haplotypes in 995 bison across ten populations. These SNPs were also found to be highly informative for individual animal identification and parentage assignment. This SNP panel provides a powerful new method to establish a baseline for estimating genetic health of bison populations and a new tool for bison managers to make informed management decisions based on genetic information specific to their populations.
Identifiants
pubmed: 38390379
doi: 10.1111/eva.13658
pii: EVA13658
pmc: PMC10883761
doi:
Types de publication
Journal Article
Langues
eng
Pagination
e13658Informations de copyright
© 2024 The Authors. Evolutionary Applications published by John Wiley & Sons Ltd.
Déclaration de conflit d'intérêts
The authors declare no conflicts of interest.