The genomic structure of isolation across breed, country and strain for important South African and Australian sheep populations

Abstract

Background South Africa and Australia shares multiple important sheep breeds. For some of these breeds, genomic breeding values are provided to breeders in Australia, but not yet in South Africa. Combining genomic resources could facilitate development for across country selection, but the influence of population structures could be important to the compatability of genomic data from varying origins. The genetic structure within and across breeds, countries and strains was evaluated in this study by population genomic parameters derived from SNP-marker data. Populations were first analysed by breed and country of origin and then by subpopulations of South African and Australian Merinos. Results Mean estimated relatedness according to the genomic relationship matrix varied by breed (-0.11 to 0.16) and bloodline (-0.08 to 0.06) groups and depended on co-ancestry as well as recent genetic links. Measures of divergence across bloodlines (FST: 0.04–0.12) were sometimes more distant than across some breeds (FST: 0.05–0.24), but the divergence of common breeds from their across-country equivalents was weak (FST: 0.01–0.04). According to mean relatedness, FST, PCA and Admixture, the Australian Ultrafine line was better connected to the SA Cradock Fine Wool flock than with other AUS bloodlines. Levels of linkage disequilibrium (LD) between adjacent markers was generally low, but also varied across breeds (r2: 0.14–0.22) as well as bloodlines (r2: 0.15–0.19). Patterns of LD decay was also unique to breeds, but bloodlines differed only at the absolute level. Estimates of effective population size (Ne) showed genetic diversity to be high for the majority of breeds (Ne: 128–418) but also for bloodlines (Ne: 137–369). Conclusions This study reinforced the genetic complexity and diversity of important sheep breeds, especially the Merino breed. The results also showed that implications of isolation can be highly variable and extended beyond breed structures. However, knowledge of useful links across these population substructures allows for a fine-tuned approach in the combination of genomic resources. Isolation across country rarely proved restricting compared to other structures considered. Consequently, research into the accuracy of across-country genomic prediction is recommended.

Including genomic information in the genetic evaluation of production and reproduction traits in South African Merino sheep

“…With a high level of genetic diversity for sheep (Kijas et al, 2009), and especially Merinos (Al-Mamun et al, 2015;Ciani et al, 2015;Nel, Gurman, et al, 2022;Prieur et al, 2017), it is expected that a large reference population is needed to achieve useful levels of accuracy by genomic selection (GS). However, despite a relatively modest reference population size in this study, the use of genomic information benefited the accuracy of prediction meeting or exceeding the expected gain amounting to between +5 and +15% for sheep (van der Werf et al, 2014).…”

“…Animals in this study can be partitioned by sector of origin as five 'resource' flocks maintained by various research initiatives in SA and five commercial flocks (out of about 231 registered at the SA Merino breeding society) currently contributing records to the NSIS. The general history of the flocks are outlined by Schoeman et al (2010) with some updates presented by Nel, Gurman, et al (2022). The flocks are known as the Elsenburg Merino selection experiment (Cloete et al, 2004(Cloete et al, , 2009Nel, 2022); the Grootfontein Merino stud (Olivier et al, 1995;Snyman et al, 1998); the Cradock fine wool Merino stud (Olivier, 2014;Schoeman et al, 2010); the Tygerhoek fine wool experimental flock (Cloete et al, 2013) and the Langgewens resource population (Cloete & Cloete, 2015).…”

“…Similar to the developments seen for Australian Merinos (Swan et al, 2012(Swan et al, , 2014, the research sector could directly contribute to the development of GS methods for SA, but this objective could face various challenges. Generally managed as selection experiments (Schoeman et al, 2010), some resource flocks risk being genetically isolated from the general population of SA Merinos (Nel, Gurman, et al, 2022). Quantitative studies of South African Merinos have been largely limited to within flock analyses of resource flock data, and a combined dataset containing information from both the research and commercial sector has not been tested.…”

“…In order to develop more sophisticated breeding programmes in SA, the use of GS methods requires validation on a local basis. A large effective population size is common for sheep (Kijas et al, 2009(Kijas et al, , 2012, and particularly so for the Merino breed (Al-Mamun et al, 2015;Ciani et al, 2015;Kijas et al, 2012;Prieur et al, 2017) including SA Merinos (Nel, Gurman, et al, 2022). The high genetic diversity means that relatively lower expectations apply to the realized accuracy from GS, or that a large reference population would be needed (Goddard, 2009).…”

Identification of Selection Signals on the X-Chromosome in East Adriatic Sheep: A New Complementary Approach

“…The sheep (Ovis aries) was domesticated along with the goat and cattle around 11–12 kyBP on the Fertile Crescent from the wild Asian mouflon ( Zeder, 2008 ). Today, more than 1,000 breeds of sheep are distributed in Asia ( Lv et al, 2015 ), Europe ( Ciani et al, 2020 ), Africa ( Muigai and Hanotte, 2013 ), North America ( Thorne et al, 2021 ), South America ( McManus et al, 2010 ), and Australia ( Nel et al, 2022 ), mainly because of their high multipurpose value as a source of milk, meat, wool, and fur ( Lv et al, 2022 ), but also because of their high adaptability to different environments. Sheep are one of the most important livestock species in Croatia, found mainly in the coastal and mountainous regions along the East Adriatic and mostly kept extensively.…”