Factors affecting the optimum structure of A. I. breeding in dairy cattle

Skjervold, H.; Langholz, Hans Jürgen

doi:10.1111/j.1439-0388.1964.tb01071.x

Cited by 51 publications

(14 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Holstein-Friesian cattle have been intensively selected during the last centuries, especially in the last decades after the implementation of progeny-test-based breeding programmes in the 1960s (Skjervold & Langholz 1964). Consequently, genomic regions controlling traits of economic importance are expected to exhibit signatures of selective breeding.…”

Section: Introductionmentioning

confidence: 99%

A genome‐wide scan for signatures of recent selection in Holstein cattle

et al. 2010

View full text Add to dashboard Cite

The data from the newly available 50 K SNP chip was used for tagging the genome-wide footprints of positive selection in Holstein-Friesian cattle. For this purpose, we employed the recently described Extended Haplotype Homozygosity test, which detects selection by measuring the characteristics of haplotypes within a single population. To assess formally the significance of these results, we compared the combination of frequency and the Relative Extended Haplotype Homozygosity value of each core haplotype with equally frequent haplotypes across the genome. A subset of the putative regions showing the highest significance in the genome-wide EHH tests was mapped. We annotated genes to identify possible influence they have in beneficial traits by using the Gene Ontology database. A panel of genes, including FABP3, CLPN3, SPERT, HTR2A5, ABCE1, BMP4 and PTGER2, was detected, which overlapped with the most extreme P-values. This panel comprises some interesting candidate genes and QTL, representing a broad range of economically important traits such as milk yield and composition, as well as reproductive and behavioural traits. We also report high values of linkage disequilibrium and a slower decay of haplotype homozygosity for some candidate regions harbouring major genes related to dairy quality. The results of this study provide a genome-wide map of selection footprints in the Holstein genome, and can be used to better understand the mechanisms of selection in dairy cattle breeding.

show abstract

Section: Introductionmentioning

confidence: 99%

A genome‐wide scan for signatures of recent selection in Holstein cattle

et al. 2010

View full text Add to dashboard Cite

show abstract

“…Semen freezing coupled with voluntary culling of bulls early in life can be an effective cost cutting measure for both GS and PT schemes (Skjervold and Langholz, 1964). This measure reduced bull maintenance costs by 71% for both strategies.…”

Section: Semen Storagementioning

confidence: 99%

“…Bull maintenance costs can be reduced by early culling combined with semen storage. In addition, early storage of semen overcomes the decline in the number of selection candidates over time resulting from involuntary culling when using fresh semen (Skjervold and Langholz, 1964). We therefore compared the economic significance of a situation in which semen was frozen and stored and bulls culled (STOR) against the conventional system in which only fresh semen is used and bulls are maintained as live animals in the bull-station (CONV) for both GS and PT strategies.…”

mentioning

confidence: 99%

Economic evaluation of progeny-testing and genomic selection schemes for small-sized nucleus dairy cattle breeding programs in developing countries

Kariuki

Brascamp

Komen

et al. 2017

Journal of Dairy Science

View full text Add to dashboard Cite

In developing countries minimal and erratic performance and pedigree recording impede implementation of large-sized breeding programs. Small-sized nucleus programs offer an alternative but rely on their economic performance for their viability. We investigated the economic performance of 2 alternative small-sized dairy nucleus programs [i.e., progeny testing (PT) and genomic selection (GS)] over a 20-yr investment period. The nucleus was made up of 453 male and 360 female animals distributed in 8 non-overlapping age classes. Each year 10 active sires and 100 elite dams were selected. Populations of commercial recorded cows (CRC) of sizes 12,592 and 25,184 were used to produce test daughters in PT or to create a reference population in GS, respectively. Economic performance was defined as gross margins, calculated as discounted revenues minus discounted costs following a single generation of selection. Revenues were calculated as cumulative discounted expressions (CDE, kg) × 0.32 (€/kg of milk) × 100,000 (size commercial population). Genetic superiorities, deterministically simulated using pseudo-BLUP index and CDE, were determined using gene flow. Costs were for one generation of selection. Results show that GS schemes had higher cumulated genetic gain in the commercial cow population and higher gross margins compared with PT schemes. Gross margins were between 3.2-and 5.2-fold higher for GS, depending on size of the CRC population. The increase in gross margin was mostly due to a decreased generation interval and lower running costs in GS schemes. In PT schemes many bulls are culled before selection. We therefore also compared 2 schemes in which semen was stored instead of keeping live bulls. As expected, semen storage resulted in an increase in gross margins in PT schemes, but gross margins remained lower than those of GS schemes. We conclude that implementation of small-sized GS breeding schemes can be economically viable for developing countries.

show abstract

“…This relatively simple AI technique has made it easier for the farmer to inseminate his/her own ewes. By the use of AI with sheep, more accurate estimation of breeding values, intensified selection among progeny-tested -E-mail: sigbjorn.eikje@nsg.no rams and decreased generation interval between sires and progeny should also result, as it did with dairy cattle (Skjervold and Langholz, 1964). Thus, changing a breeding programme towards enlarged use of AI should increase the possibilities to advance genetic gain.…”

Section: Introductionmentioning

confidence: 99%

Sheep breeding schemes utilising artificial insemination; large-scale simulation with a complex breeding goal

Eikje

Schaeffer

Ådnøy

et al. 2011

Animal

View full text Add to dashboard Cite

Alternative Norwegian sheep breeding schemes were evaluated by stochastic simulation of a breeding population with about 120 000 ewes, considering the gain for an aggregate genotype including nine traits and also the rate of inbreeding. The schemes were: a scheme where both young unproven rams (test rams) and proven rams (elite rams) are used in artificial insemination (AI scheme), a scheme with test rams in natural mating in ram circles and elite rams (from one and a half years of age) in AI across all flocks in the country (NMAI2 scheme), a scheme where, in addition to testing rams, the youngest elite rams (one and a half years of age) are also used in natural mating in ram circles, while older elite rams are used in AI (NMAI1 scheme), and a scheme, acting as a control, where both test and elite rams are used in natural mating (NM scheme). Within the NMAI-and AI-schemes, experimentation was performed for percent ewes inseminated to elite rams v. test rams (EM%), numbers of ewes inseminated per elite ram (EAIn), and numbers of ewes mated per test ram by natural service (TNMn) or by AI (TAIn), respectively. With a restriction on the rate of inbreeding (<0.8% per generation), the AI scheme gave similar gain to the NMAI2 scheme (and about 40% more than did the NM scheme). Less gain was generated by the NMAI1 scheme, but it was still considerably more than for the NM scheme (about 25%). In the AI scheme, relatively few ewes (200/300) should be inseminated to each test/elite ram, and a low EM% should be chosen (10%). In the NMAI schemes, TNMn should be relatively high (40 to 50), combined with average and somewhat larger than average EAIn (NMAI2: 700 ewes, NMAI1: 900 ewes), and EM% medium (30%).

show abstract

Factors affecting the optimum structure of A. I. breeding in dairy cattle

Cited by 51 publications

References 3 publications

A genome‐wide scan for signatures of recent selection in Holstein cattle

A genome‐wide scan for signatures of recent selection in Holstein cattle

Economic evaluation of progeny-testing and genomic selection schemes for small-sized nucleus dairy cattle breeding programs in developing countries

Sheep breeding schemes utilising artificial insemination; large-scale simulation with a complex breeding goal

Contact Info

Product

Resources

About