Using triallelic SNPs for determining parentage in North American yak (Bos grunniens) and estimating cattle (B. taurus) introgression

Background: Genetic testing for pedigree accuracy is critical for managing genetic diversity in North American (NA) yak (Bos grunniens), a population expanded mostly from imported zoological park specimens.  DNA testing also enhances species conservation by identifying recent B. taurus F1 hybrid ancestors (within three generations).  Biallelic single nucleotide polymorphisms (SNPs) can accomplish either task, but increases the marker count and costs necessary to achieve both.  Our aim was to identify novel, multifunctional, triallelic yak SNPs (tySNPs), with each having two alleles for yak parentage testing, and a third allele for identifying recent cattle introgression. 
Methods:  Genome sequences were aligned to the cattle UMD3.1 assembly and SNPs were screened for 1) heterozygosity in a NA and a Chinese yak, 2) a third allele at high frequency in cattle, and 3) flanking sequences conserved in both species.  Subsequently, tySNPs were filtered for unique alignment to the haplotype-resolved F1 yak assembly.  Allele frequencies were estimated in a subset of 87 tySNPs by genotyping 170 NA yak.
Results:  We identified 610 autosomal tySNPs, distributed in 441 clusters with 5 Mb average genome spacing.  The average NA yak minor allele frequency was high (0.296), while average introgressed cattle alleles were low (0.004).  In simulations with tySNPs, 28 were sufficient for globally-unique animal identification (P_I=5.81x10^-12), 87 were able to exclude 19 random bulls from parentage at the 99% level without using the dam’s genotype (P_E=5.3x10^-4), and 87 were able to detect F1 hybridization events after three generations of yak backcrosses (1/16th B. taurus germplasm).
Conclusions:  Identifying animals, determining parentage and detecting recent hybridization events was efficient with as few as 87 tySNPs.  A similar triallelic approach could be used with other bottlenecked Bos species that hybridize with cattle, such as NA plains bison (B. bison).

Online Bioinformatics Course at UofL

Professor Ted Kalbfleisch will be instructing an online Bioinformatics course for UKY faculty, postdocs, staff, and students.

Participants

Kalbfleisch, Ted - Instructor, UofL
Esteller-Vico, Alejandro - Faculty, UKY Veterinary Science
Ball, Barry A - Faculty, Veterinary Science
Loux, Savahn C - Postdoc, Veterinary Science
Scoggin, Kirsten E - Staff, Veterinary Science
Thampi, Parrathy - Student, Veterinary Science
Mok, Chanhee - Student, Veterinary Science
Adam, Emma N - Student, Veterinary Science
Fleming, Blaire O - Student, Veterinary Science
Goedde, Lauren D - Student, UK Veterinary Science
Fedorka, Carleigh E - Student, Veterinary Science
Dini, Pouya - Visiting Scholar, Veterinary Science
Linhares Boakari, Yatta - Student, Veterinary Science
Fernandes, Claudia B - Visiting Scholar, Veterinary Science
Wynn, Michelle A A - Student, Veterinary Science
MacLeod, James - Faculty, UKY Veterinary Science

Kandauda Malinika Kalpani De Silva

Kai Li, LCC/MCC Clusters, Added 10/04/2021

Jeffrey M Mitchell, Jr. - Grad Student, Veterinary Science - Added 10/05/2020

Erica T Jacquay, Grad Student, Veterinary Sciences - Added 11/04/2020

Nahla A Hussien, Sr., Added 10/26/2021

Lauren C Johnson, Grad Student, Added on MCC cluster, 09/06/2022 

Xiomara R Arias, Added on MCC cluster, 05/08/2023 

Lindsay Whitaker, Added on MCC cluster, 06/08/2023, Added on Gemini 1-1 and KCC on 06/15/2023  

Judith Nikly, Added on MCC cluster, 06/08/2023, Added on Gemini 1-1 and KCC on 06/15/2023 

Kailey Ratcliff, Added on MCC cluster, 06/08/2023, Added on Gemini 1-1 and KCC on 06/15/2023 

Julia L Ciosek, Added on MCC cluster, 09/05/2023, Added on Gemini 1-Storage

Publications:

Kalbfleisch T, Petersen JL, Tait Jr. RG, Qiu J, Basnayake V., Hackett P, Heaton MP. Using triallelic SNPs for determining parentage in North American yak (Bos grunniens) and estimating cattle (B. taurus) introgression [version 2; peer review: 2 approved]. F1000Research 2020, 9:1096 (https://doi.org/10.12688/f1000research.25803.2)