Short communication: Phenotypic and genetic effects of the polled haplotype on yield, longevity, and fertility in US Brown Swiss, Holstein, and Jersey cattle

Uncovering Novel Features of the Pc Locus in Horn Development from Gene-Edited Holstein Cattle by RNA-Sequencing Analysis

The Polled Celtic (Pc) mutation locus is a genetically simple single mutation that is the best choice for breeding polled cattle using gene editing. However, the mechanism of the Pc locus for regulating horn development is unclear, so we used gene editing, somatic cell nuclear transfer and embryo transfer to obtain polled Holstein fetal bovine (gestation time 90 days) with a homozygous Pc insertion (gene-edited Holstein fetal bovine, EH) and the wild-type 90 days Holstein fetal bovine (WH) as controls. The hematoxylin-eosin (HE) staining results showed that, compared to the WH, the EH horn buds had no white keratinized projections or vacuolated keratinocytes and no thick nerve bundles under the dermal tissue. Furthermore, DNA sequencing results showed that the Pc locus was homozygously inserted into the fetal bovine genome. A total of 791 differentially expressed genes were identified by transcriptome sequencing analysis. Enrichment analysis and protein interaction analysis results of differentially expressed genes showed that abundant gene changes after Pc insertion were associated with the adhesion molecule regulation, actin expression, cytoskeletal deformation and keratin expression and keratinization. It was also noted that the results contained several genes that had been reported to be associated with the development of horn traits, such as RXFP2 and TWIST1. This study identified these changes for the first time and summarized them. The results suggested that the Pc mutant locus may inhibit neural crest cell EMT generation and keratin expression, leading to failures in neural crest cell migration and keratinization of the horn bud tissue, regulating the production of the polled phenotype.

A variance component estimation approach to infer associations between Mendelian polledness and quantitative production and female fertility traits in German Simmental cattle

Background

Managing beneficial Mendelian characteristics in dairy cattle breeding programs implies that the correlated genetic effects are considered to avoid possible adverse effects in selection processes. The Mendelian trait polledness in cattle is traditionally associated with the belief that the polled locus has unfavorable effects on breeding goal traits. This may be due to the inferior breeding values of former polled bulls and cows in cattle breeds, such as German Simmental, or to pleiotropic or linkage effects of the polled locus.

Methods

We focused on a variance component estimation approach that uses a marker-based numerator relationship matrix reflecting gametic relationships at the polled locus to test for direct pleiotropic or linked quantitative trait loci (QTL) effects of the polled locus on relevant traits. We applied the approach to performance, health, and female fertility traits in German Simmental cattle.

Results

Our results showed no evidence for any pleiotropic QTL effects of the polled locus on test-day production traits milk yield and fat percentage, on the mastitis indicator ‘somatic cell score’, and on several female fertility traits, i.e. 56 days non return rate, days open and days to first service. We detected a significant and unfavorable QTL effect accounting for 6.6% of the genetic variance for protein percentage only.

Conclusions

Pleiotropy does not explain the lower breeding values and phenotypic inferiority of polled German Simmental sires and cows relative to the horned population in the breed. Thus, intensified selection in the polled population will contribute to increased selection response in breeding goal traits and genetic merit and will narrow the deficit in breeding values for production traits.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12711-021-00652-z.

Genomic Analysis, Progress and Future Perspectives in Dairy Cattle Selection: A Review

Genomics comprises a set of current and valuable technologies implemented as selection tools in dairy cattle commercial breeding programs. The intensive progeny testing for production and reproductive traits based on genomic breeding values (GEBVs) has been crucial to increasing dairy cattle productivity. The knowledge of key genes and haplotypes, including their regulation mechanisms, as markers for productivity traits, may improve the strategies on the present and future for dairy cattle selection. Genome-wide association studies (GWAS) such as quantitative trait loci (QTL), single nucleotide polymorphisms (SNPs), or single-step genomic best linear unbiased prediction (ssGBLUP) methods have already been included in global dairy programs for the estimation of marker-assisted selection-derived effects. The increase in genetic progress based on genomic predicting accuracy has also contributed to the understanding of genetic effects in dairy cattle offspring. However, the crossing within inbred-lines critically increased homozygosis with accumulated negative effects of inbreeding like a decline in reproductive performance. Thus, inaccurate-biased estimations based on empirical-conventional models of dairy production systems face an increased risk of providing suboptimal results derived from errors in the selection of candidates of high genetic merit-based just on low-heritability phenotypic traits. This extends the generation intervals and increases costs due to the significant reduction of genetic gains. The remarkable progress of genomic prediction increases the accurate selection of superior candidates. The scope of the present review is to summarize and discuss the advances and challenges of genomic tools for dairy cattle selection for optimizing breeding programs and controlling negative inbreeding depression effects on productivity and consequently, achieving economic-effective advances in food production efficiency. Particular attention is given to the potential genomic selection-derived results to facilitate precision management on modern dairy farms, including an overview of novel genome editing methodologies as perspectives toward the future.