Population structure and breed composition prediction in a multi-breed sheep population using genome-wide single nucleotide polymorphism genotypes

Animal board invited review: Practical applications of genomic information in livestock

Access to high-dimensional genomic information in many livestock species is accelerating. This has been greatly aided not only by continual reductions in genotyping costs but also an expansion in the services available that leverage genomic information to create a greater return-on-investment. Genomic information on individual animals has many uses including (1) parentage verification and discovery, (2) traceability, (3) karyotyping, (4) sex determination, (5) reporting and monitoring of mutations conferring major effects or congenital defects, (6) better estimating inbreeding of individuals and coancestry among individuals, (7) mating advice, (8) determining breed composition, (9) enabling precision management, and (10) genomic evaluations; genomic evaluations exploit genome-wide genotype information to improve the accuracy of predicting an animal's (and by extension its progeny's) genetic merit. Genomic data also provide a huge resource for research, albeit the outcome from this research, if successful, should eventually be realised through one of the ten applications already mentioned. The process for generating a genotype all the way from sample procurement to identifying erroneous genotypes is described, as are the steps that should be considered when developing a bespoke genotyping panel for practical application.

Evaluating the use of statistical and machine learning methods for estimating breed composition of purebred and crossbred animals in thirteen cattle breeds using genomic information

Introduction: The ability to accurately predict breed composition using genomic information has many potential uses including increasing the accuracy of genetic evaluations, optimising mating plans and as a parameter for genotype quality control. The objective of the present study was to use a database of genotyped purebred and crossbred cattle to compare breed composition predictions using a freely available software, Admixture, with those from a single nucleotide polymorphism Best Linear Unbiased Prediction (SNP-BLUP) approach; a supplementary objective was to determine the accuracy and general robustness of low-density genotype panels for predicting breed composition. Methods: All animals had genotype information on 49,213 autosomal single nucleotide polymorphism (SNPs). Thirteen breeds were included in the analysis and 500 purebred animals per breed were used to establish the breed training populations. Accuracy of breed composition prediction was determined using a separate validation population of 3,146 verified purebred and 4,330 two and three-way crossbred cattle. Results: When all 49,213 autosomal SNPs were used for breed prediction, a minimal absolute mean difference of 0.04 between Admixture vs. SNP-BLUP breed predictions was evident. For crossbreds, the average absolute difference in breed prediction estimates generated using SNP-BLUP and Admixture was 0.068 with a root mean square error of 0.08. Breed predictions from low-density SNP panels were generated using both SNP-BLUP and Admixture and compared to breed prediction estimates using all 49,213 SNPs (representing the gold standard). Breed composition estimates of crossbreds required more SNPs than predicting the breed composition of purebreds. SNP-BLUP required ≥3,000 SNPs to predict crossbred breed composition, but only 2,000 SNPs were required to predict purebred breed status. The absolute mean (standard deviation) difference across all panels <2,000 SNPs was 0.091 (0.054) and 0.315 (0.316) when predicting the breed composition of all animals using Admixture and SNP-BLUP, respectively compared to the gold standard prediction. Discussion: Nevertheless, a negligible absolute mean (standard deviation) difference of 0.009 (0.123) in breed prediction existed between SNP-BLUP and Admixture once ≥3,000 SNPs were considered, indicating that the prediction of breed composition could be readily integrated into SNP-BLUP pipelines used for genomic evaluations thereby avoiding the necessity for a stand-alone software.

Genomic Population Structure of the Main Historical Genetic Lines of Spanish Merino Sheep

Simple Summary

Historical documentation shows that the Spanish Merino sheep was selected over many centuries due to the quality of wool, following which it was used to originate all other Merino breeds around the world, mainly by crossbreeding with local breeds. Today, the historical genetic lines that originated the Spanish Merino are still preserved in several closed herds in which they have been bred for nearly 200 years, maintaining their original genetic purity. Our study demonstrates, using a genomic approach, the exceptional genetic richness and variability of these lines, which are clearly differentiated from modern Merino breeds, and must therefore be protected to safeguard the large genetic pool they represent.

Abstract

According to historiographical documentation, the Romans first began to select Merino sheep in the Iberian Peninsula during the first century, with the aim of obtaining a breed appreciated for the quality of its wool. This process continued locally during the Middle Ages, when Spanish sheep were protected, and their export to foreign countries was banned. It was during the 16th century when individual Merino sheep were allowed to spread around the world to be used to improve the wool quality of local breeds. However, the wool crisis of the 1960s shifted the selection criteria of the Merino breed towards meat production at the expenses of wool. Consequently, individuals that display the genetic and phenotypic characteristics of those sheep originally bred in the kingdom of Spain in the Middle Ages are extremely difficult to find in commercial herds. In this study, we characterized the genetic basis of 403 individuals from the main historical Spanish Merino genetic lines (Granda, Hidalgo, Lopez-Montenegro, Maeso, Donoso and Egea), which were bred in isolation over the last 200 years, using a genomic approach based on genotyping data from the Axiom™ Ovine 50K SNP Genotyping Array. Our analysis included measuring population structure, genomic differentiation indexes, runs of homozygosity (ROH) patterns, and an analysis of molecular variance (AMOVA). The results showed large genetic differences between the historical lines, even though they belong to the same breed. In addition, ROH analysis showed differences due to increased inbreeding among the ancient generations compared with the modern Merino lines, confirming the breed’s ancestral and closed origin. However, our results also showed a high variability and richness within the Spanish historical Merino lines from a genetic viewpoint. This fact, together with their great ability to produce high-quality wool, suggests that ancestral Merino lines from Spain should be considered a valuable genetic population to be maintained as a resource for the improvement of wool-producing sheep breeds all around the world.