Comparison of methods for deriving phenotypes from incomplete observation data with an application to age at puberty in dairy cattle.

BACKGROUND: Many phenotypes in animal breeding are derived from incomplete measures, especially if they are challenging or expensive to measure precisely. Examples include time-dependent traits such as reproductive status, or lifespan. Incomplete measures for these traits result in phenotypes that are subject to left-, interval- and right-censoring, where phenotypes are only known to fall below an upper bound, between a lower and upper bound, or above a lower bound respectively. Here we compare three methods for deriving phenotypes from incomplete data using age at first elevation (> 1 ng/mL) in blood plasma progesterone (AGEP4), which generally coincides with onset of puberty, as an example trait. METHODS: We produced AGEP4 phenotypes from three blood samples collected at about 30-day intervals from approximately 5,000 Holstein-Friesian or Holstein-Friesian × Jersey cross-bred dairy heifers managed in 54 seasonal-calving, pasture-based herds in New Zealand. We used these actual data to simulate 7 different visit scenarios, increasing the extent of censoring by disregarding data from one or two of the three visits. Three methods for deriving phenotypes from these data were explored: 1) ordinal categorical variables which were analysed using categorical threshold analysis; 2) continuous variables, with a penalty of 31 d assigned to right-censored phenotypes; and 3) continuous variables, sampled from within a lower and upper bound using a data augmentation approach. RESULTS: Credibility intervals for heritability estimations overlapped across all methods and visit scenarios, but estimated heritabilities tended to be higher when left censoring was reduced. For sires with at least 5 daughters, the correlations between estimated breeding values (EBVs) from our three-visit scenario and each reduced data scenario varied by method, ranging from 0.65 to 0.95. The estimated breed effects also varied by method, but breed differences were smaller as phenotype censoring increased. CONCLUSION: Our results indicate that using some methods, phenotypes derived from one observation per offspring for a time-dependent trait such as AGEP4 may provide comparable sire rankings to three observations per offspring. This has implications for the design of large-scale phenotyping initiatives where animal breeders aim to estimate variance parameters and estimated breeding values (EBVs) for phenotypes that are challenging to measure or prohibitively expensive.

Genetic and economic benefits of foreign sire contributions to a domestic sheep industry; including an Ireland-New Zealand case study.

BACKGROUND: Importation of foreign genetics is a widely used genetic improvement strategy. However, even if the foreign genetic merit is currently greater than the domestic genetic merit, differences in foreign and domestic trends mean that the long-term competitiveness of an importation strategy cannot be guaranteed. Gene flow models are used to quantify the impact that a specific subpopulation, such as foreign genetics, can have over time on the genetic or economic benefit of a domestic industry. METHODS: We used a deterministic recursive gene flow model to predict the commercial performance of lambs born across various subpopulations. Numerous breeding strategies were evaluated by varying market share, proportions of rams selected for mating, genetic trend, superiority of foreign genetics over domestic genetics and frequency of importation. Specifically, an Ireland-New Zealand case study was simulated to quantify the potential gain that could be made by using foreign sire contributions (New Zealand) in a domestic sheep industry (Ireland). RESULTS: Genetic and economic gains were generated from alternative breeding strategies. The 'base scenario' (i.e. representing the current industry) predicted an average genetic merit value of €2.51 for lambs born and an annualised cumulative benefit of €45 million (m) after 20 years. Maximum genetic (€9.45 for lambs born) and economic (annualised cumulative benefit of €180 m after 20 years) benefits were achieved by implementing the 'PRO-intense-market scenario' which involved shifting market share away from conservative domestic breeders and reducing the proportion of rams that were selected for mating by progressive domestic breeders from the top 40% to the top 20%, without the use of any foreign genetics. The 'PROFOR scenario', which considered the use of foreign and progressive domestic genetics, predicted an average genetic merit value of €7.37 for lambs born and an annualised cumulative benefit of €144 m, after 20 years. CONCLUSIONS: Our results demonstrate that there is opportunity for a domestic industry to increase industry benefits without the use of foreign genetics but through an attempt to shift the market share away from conservative domestic breeders towards progressive domestic breeders. However, the importation and use of progressive foreign genetics may be an effective method to trigger a change in behaviour of conservative domestic breeders towards the use of progressive genetics.

An index framework founded on the future profit potential of female beef cattle to aid the identification of candidates for culling.

Meticulous culling decisions, coupled with careful breeding decisions, are fundamental to shifting a population distribution in the favorable direction and improving profit per cow. Nevertheless, there is a paucity of easy-to-use dynamic tools to aid in culling decisions in beef cattle. The motivation for the present study was to develop a monetary-based culling tool, here referred to as the Beef Female's Profit Potential (BFPP), to identify females for culling. The BFPP reflects the expected lifetime profitability of an individual female in a herd for the expected remainder of her lifetime; this profit included that of the beef female herself as well as her progeny. The BFPP index framework was composed of 4 subindexes reflecting the value of an animal: (1) as a nulliparae (this was voided if the cow had already calved), (2) for the remainder of her current parity, (3) summed across each of her expected remaining parities, and (4) when she is retained within the herd and not voluntarily culled. Each subindex was comprised of different components reflecting both genetic and non-genetic effects associated with each female. Transition matrices predicting the expected longevity of each female and their expected month of calving were also utilized in calculating the expected remaining lifetime profitability of each female. The BFPP index was validated on 21,102 beef cows as well as their harvested progeny from 875 herds by stratifying the cows, within herd, into 4 strata based on their BFPP. The mean of the within-herd correlation between the BFPP and the Irish national replacement (i.e., breeding) index was, on average, 0.45 indicating the shortcomings of the breeding index as a culling tool. Cows within the top BFPP stratum had a genetic expectation of accruing almost an additional €36 profit per calving, relative to cows within the worst stratum; when validated on the cow's own calving interval and survival performance as well as their progeny's carcass performance, the actual phenotypic value was estimated to be an additional €32 profit per calving. A proportion of this additional profit was due to the harvested progeny of the high BFPP cows having, on average, heavier, more conformed carcasses with less fat cover relative to their poor BFPP contemporaries. This BFPP framework is a useful and easy-to-use tool to aid in producer decision making on the choice of females to voluntarily cull but also on which replacement heifers to graduate into the mature herd.

Genetic benefits of genomic selection breeding programmes considering foreign sire contributions.

BACKGROUND: In modern dairy breeding programmes, high contributions from foreign sires are nearly always present. Genotyping, and therefore genomic selection (GS), concern only a subpopulation of the breeding programme's wider dairy population. These features of a breeding programme contribute in different ways to the rate of genetic gain for the wider industry. METHODS: A deterministic recursive gene flow model across subpopulations of animals in a dairy industry was created to predict the commercial performance of replacement heifers and future artificial insemination bulls. Various breeding strategies were assessed by varying the reliability of breeding values, the genetic contributions from subpopulations, and the genetic trend and merit of the foreign subpopulation. RESULTS: A higher response in the true breeding goal measured in standard deviations (SD) of true merit (G) after 20 years of selection can be achieved when genetic contributions shift towards higher merit alternatives compared to keeping them fixed. A foreign annual genetic trend of 0.08 SD of the breeding goal, while the domestic genetic trend is 0.10 SD, results in the overall net present value of genetic gain increasing by 1.2, 2.3, and 3.4% after 20 years as the reliability of GS in the domestic population increased from 0.3 to 0.45, 0.60 and 0.75. With a foreign genetic trend of 0.10 SD, these increases are more modest; 0.9, 1.7, and 2.4%. Increasing the foreign genetic trend so that it is higher than the domestic trend erodes the benefits of increasing the reliability of domestic GS further. CONCLUSIONS: Having a foreign source of genetic material with a high rate of genetic progress contributes substantially to the benefits of domestic genetic progress while at the same time reducing the expected returns from investments to improve the accuracy of genomic prediction in the home country.

Complexity of animal breeding choice making.

The last decades of developments in animal breeding, genetics, genomics and data recording technologies have allowed the evaluation of larger numbers of animal and animal traits than ever before. This should help make animal breeding choices more informed, but it also makes them far more complex. This complexity may be overwhelming farmers, thus compromising realization of potential genetic gain in livestock industries. However, the effect of complexity of animal breeding choices on farmers' selection of animals has received very little theoretical consideration to date. This paper reviews the theoretical principles of complex decisions, contextualizes the findings to the field of animal breeding, and analyses how farmers and the animal breeding industry are currently dealing with complexity. According to the findings of the analyses of complex decisions in other fields, the complexity of animal breeding choices is likely to lead to farmers using conscious or unconscious simplifying strategies (heuristics) to handle such complexity. When these heuristics are ineffective, poor selection decisions and a potential loss of genetic progress can be expected. Further, studies using survey experiments to understand farmer behaviour and selection preferences may be compromised by the complexity of the survey´s choice tasks. Thus, while many animal breeding industries recognize the complexity of animal breeding choices for farmers and attempts are made to assist farmers in their choice making, the effectiveness of these attempts is not well quantified and understood. We discuss three areas of research that could be key to disentangling how, and by how much, animal breeding choice complexity affects farmers' decisions.

Genetic and economic benefits of selection based on performance recording and genotyping in lower tiers of multi-tiered sheep breeding schemes.

BACKGROUND: Performance recording and genotyping in the multiplier tier of multi-tiered sheep breeding schemes could potentially reduce the difference in the average genetic merit between nucleus and commercial flocks, and create additional economic benefits for the breeding structure. METHODS: The genetic change in a multiple-trait breeding objective was predicted for various selection strategies that included performance recording, parentage testing and genomic selection. A deterministic simulation model was used to predict selection differentials and the flow of genetic superiority through the different tiers. Cumulative discounted economic benefits were calculated based on trait gains achieved in each of the tiers and considering the extra revenue and associated costs of applying recording, genotyping and selection practices in the multiplier tier of the breeding scheme. RESULTS: Performance recording combined with genomic or parentage information in the multiplier tier reduced the genetic lag between the nucleus and commercial flock by 2 to 3 years. The overall economic benefits of improved performance in the commercial tier offset the costs of recording the multiplier. However, it took more than 18 years before the cumulative net present value of benefits offset the costs at current test prices. Strategies in which recorded multiplier ewes were selected as replacements for the nucleus flock did modestly increase profitability when compared to a closed nucleus structure. Applying genomic selection is the most beneficial strategy if testing costs can be reduced or by genotyping only a proportion of the selection candidates. When the cost of genotyping was reduced, scenarios that combine performance recording with genomic selection were more profitable and reached breakeven point about 10 years earlier. CONCLUSIONS: Economic benefits can be generated in multiplier flocks by implementing performance recording in conjunction with either DNA pedigree recording or genomic technology. These recording practices reduce the long genetic lag between the nucleus and commercial flocks in multi-tiered breeding programs. Under current genotyping costs, the time to breakeven was found to be generally very long, although this varied between strategies. Strategies using either genomic selection or DNA pedigree verification were found to be economically viable provided the price paid for the tests is lower than current prices, in the long-term.

Using genetic markers in unpedigreed populations to detect a heritable trait.

Before a breeder invests selection pressure on a trait of interest, it needs to be established whether that trait is actually heritable. Some traits may not have been measured widely in pedigreed populations, for example, a disease or deformity may become more prevalent than previously, but is still relatively rare. One approach to detect inheritance would be to screen a commercial population to obtain a sample of "affecteds" (the test group) and to also obtain a random control group. These individuals are then genotyped with a set of genetic markers and the relationships between individuals within each group estimated. If the relatedness is higher in the test group than in the control group, this provides initial evidence for the trait being heritable. A power simulation shows that this approach is feasible with moderate resources.