Are scurs in heterozygous polled (Pp) cattle a complex quantitative trait?

Abstract

Background Breeding genetically hornless, i.e. polled, cattle provides an animal welfare-friendly and non-invasive alternative to the dehorning of calves. However, the molecular regulation of the development of horns in cattle is still poorly understood. Studying genetic characters such as polledness and scurs, can provide valuable insights into this process. Scurs are hornlike formations that occur occasionally in a wide variety of sizes and forms as an unexpected phenotype when breeding polled cattle. Methods We present a unique dataset of 885 Holstein–Friesian cattle with polled parentage. The horn phenotype was carefully examined, and the phenotypic heterogeneity of the trait is described. Using a direct gene test for polledness, the polled genotype of the animals was determined. Subsequently, the existence of a putative scurs locus was investigated using high-density genotype data of a selected subset of 232 animals and two mapping approaches: mixed linear model-based association analyses and combined linkage disequilibrium and linkage analysis. Results The results of an exploratory data analysis indicated that the expression of scurs depends on age at phenotyping, sex and polled genotype. Scurs were more prevalent in males than in females. Moreover, homozygous polled animals did not express any pronounced scurs and we found that the Friesian polled allele suppresses the development of scurs more efficiently than the Celtic polled allele. Combined linkage and linkage disequilibrium mapping revealed four genome-wide significant loci that affect the development of scurs, one on BTA5 and three on BTA12. Moreover, suggestive associations were detected on BTA16, 18 and 23. The mixed linear model-based association analysis supports the results of the combined linkage and linkage disequilibrium analysis. None of the mapping approaches provided convincing evidence for a monogenic inheritance of scurs. Conclusions Our results contradict the initial and still broadly accepted model for the inheritance of horns and scurs. We hypothesise an oligogenetic model to explain the development of scurs and polledness.

A scalable, clinically severe pig model for Duchenne muscular dystrophy

“…A subset of n =98 DMD Y/− pigs was selected for genome-wide mapping to ensure that only animals that died spontaneously or had to be euthanized in a terminal condition were included. The genome-wide mapping of QTL was performed using a combined linkage disequilibrium and linkage analysis (cLDLA) approach, as reported in Meuwissen et al (2002) and adapted by Medugorac et al (2017) and Gehrke et al (2020) . First, a genomic relationship matrix ( Powell et al, 2010 ) was estimated and used for prediction of random polygenic effects.…”

A scalable, clinically severe pig model for Duchenne muscular dystrophy

“…A subset of n = 98 DMD Y/pigs was selected for genome-wide mapping to ensure that only animals which died spontaneously or had to be euthanized in a terminal condition were included. The genome-wide mapping of quantitative trait loci (QTL) was performed using a combined linkage disequilibrium and linkage analysis (cLDLA) approach, as reported in Meuwissen,et al (59) and adapted by Medugorac,et al (60) and Gehrke, et al (61). First, a genomic relationship matrix (62) was estimated and used for prediction of random polygenic effects.…”

“…p < 0.000049 divided by the number of genome-wide independent 40 SNP windows. Gehrke, et al (61) demonstrated that cLDLA can be used for mapping of quantitative (as well as binary) traits. In the present study, the cLDLA mapping was performed with life expectancy as quantitative variable, i.e., length of life in days.…”

A de novo frameshift mutation in ZEB2 causes polledness, abnormal skull shape, small body stature and subfertility in Fleckvieh cattle

“…Mapping of the de novo polled locus was carried out using combined linkage disequilibrium and linkage analysis (cLDLA) corresponding to the method proposed by Meuwissen et al 50 . This procedure has already been described in Medugorac et al 25 and Gehrke et al 51 . The procedure required the phase data; the inference of haplotypes and imputation of missing genotypes were carried out using hidden Markov models as implemented in BEAGLE 4.1 52 .…”