Abstract
Linear type traits describing the skeletal characteristics of an animal are moderately to strongly genetically correlated with a range of other performance traits in cattle including feed intake, reproduction traits and carcass merit; thus, type traits could also provide useful insights into the morphological differences among animals underpinning phenotypic differences in these complex traits. The objective of the present study was to identify genomic regions associated with five subjectively scored skeletal linear traits, to determine if these associated regions are common in multiple beef and dairy breeds, and also to determine if these regions overlap with those proposed elsewhere to be associated with correlated performance traits. Analyses were carried out using linear mixed models on imputed whole genome sequence data separately in 1,444 Angus, 1,129 Hereford, 6,433 Charolais, 8,745 Limousin, 1,698 Simmental, and 4,494 Holstein-Friesian cattle, all scored for the linear type traits. There was, on average, 18 months difference in age at assessment of the beef versus the dairy animals. While the majority of the identified quantitative trait loci (QTL), and thus genes, were both trait-specific and breed-specific, a large-effect pleiotropic QTL on BTA6 containing the NCAPG and LCORL genes was associated with all skeletal traits in the Limousin population and with wither height in the Angus. Other than that, little overlap existed in detected QTLs for the skeletal type traits in the other breeds. Only two QTLs overlapped the beef and dairy breeds; both QTLs were located on BTA5 and were associated with height in both the Angus and the Holstein-Friesian, despite the difference in age at assessment. Several detected QTLs in the present study overlapped with QTLs documented elsewhere that are associated with carcass traits, feed intake, and calving difficulty. While most breeding programs select for the macro-traits like carcass weight, carcass conformation, and feed intake, the higher degree of granularity with selection on the individual linear type traits in a multi-trait index underpinning the macro-level goal traits, presents an opportunity to help resolve genetic antagonisms among morphological traits in the pursuit of the animal with optimum performance metrics.
Highlights
Linear type traits have been used in both beef and dairy cattle since the early 20th century to characterize the skeletal characteristics of an animal (Berry et al, 2019)
While many genomic studies have been carried out on stature in both beef and dairy cattle (Pryce et al, 2011; Bolormaa et al, 2014), few studies have been published on the underlying genomic features contributing to differences in other skeletal linear type traits in either beef (Vallée et al, 2016) or dairy (Cole et al, 2011; Wu et al, 2013; Sahana et al, 2015) cattle
The objective of the present study was to identify genomic regions associated with five subjectively scored skeletal linear traits to determine if these associated regions are common in multiple beef and dairy breeds and to determine if these regions overlapped with previously identified quantitative trait loci (QTL) associated with other correlated performance traits
Summary
Linear type traits have been used in both beef and dairy cattle since the early 20th century to characterize the skeletal characteristics of an animal (Berry et al, 2019) These type traits have previously been identified as being moderately to strongly genetically correlated with a range of performance traits in cattle including feed intake (Veerkamp and Brotherstone, 1997; Crowley et al, 2011), reproductive traits (Berry et al, 2004; Wall et al, 2005; Carthy et al, 2016), carcass merit (Mukai et al, 1995; Berry et al, 2019), animal value (Mc Hugh et al, 2010), and health (Ring et al, 2018). The objective of the present study was to identify genomic regions associated with five subjectively scored skeletal linear traits to determine if these associated regions are common in multiple beef and dairy breeds and to determine if these regions overlapped with previously identified QTLs associated with other correlated performance traits
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