Assessment of alternative genotyping strategies to maximize imputation accuracy at minimal cost

Background

Commercial breeding programs seek to maximise the rate of genetic gain while minimizing the costs of attaining that gain. Genomic information offers great potential to increase rates of genetic gain but it is expensive to generate. Low-cost genotyping strategies combined with genotype imputation offer dramatically reduced costs. However, both the costs and accuracy of imputation of these strategies are highly sensitive to several factors. The objective of this paper was to explore the cost and imputation accuracy of several alternative genotyping strategies in pedigreed populations.

Methods

Pedigree and genotype data from a commercial pig population were used. Several alternative genotyping strategies were explored. The strategies differed in the density of genotypes used for the ancestors and the individuals to be imputed. Parents, grandparents, and other relatives that were not descendants, were genotyped at high-density, low-density, or extremely low-density, and associated costs and imputation accuracies were evaluated.

Results

Imputation accuracy and cost were influenced by the alternative genotyping strategies. Given the mating ratios and the numbers of offspring produced by males and females, an optimized low-cost genotyping strategy for a commercial pig population could involve genotyping male parents at high-density, female parents at low-density (e.g. 3000 SNP), and selection candidates at very low-density (384 SNP).

Conclusions

Among the selection candidates, 95.5 % and 93.5 % of the genotype variation contained in the high-density SNP panels were recovered using a genotyping strategy that costs respectively, $24.74 and $20.58 per candidate.     

Economic aspects of implementing genomic evaluations in a pig sire line breeding scheme

Background

Replacing pedigree-based BLUP evaluations by genomic evaluations in pig breeding schemes can result in greater selection accuracy and genetic gains, especially for traits with limited phenotypes. However, this methodological change would generate additional costs. The objective of this study was to determine whether additional expenditures would be more profitably devoted to implementing genomic evaluations or to increasing phenotyping capacity while retaining traditional evaluations.

Methods

Stochastic simulation was used to simulate a population with 1050 breeding females and 50 boars that was selected for 10 years for a breeding goal with two uncorrelated traits with heritabilities of 0.4. The reference breeding scheme was based on phenotyping 13 770 candidates per year for trait 1 and 270 sibs of candidates per year for trait 2, with selection based on pedigree-based BLUP estimated breeding values. Increased expenditures were allocated to either increasing the phenotyping capacity for trait 2 while maintaining traditional evaluations, or to implementing genomic selection. The genomic scheme was based on two training populations: one for trait 2, consisting of phenotyped sibs of the candidates whose number increased from 1000 to 3430 over time, and one for trait 1, consisting of the selection candidates. Several genomic scenarios were tested, where the size of the training population for trait 1, and the number of genotyped candidates pre-selected based on their parental estimated breeding value, varied.

Results

Both approaches resulted in higher genetic trends for the population breeding goal and lower rates of inbreeding compared to the reference scheme. However, even a very marked increase in phenotyping capacity for trait 2 could not match improvements achieved with genomic selection when the number of genotyped candidates was large. Genotyping just a limited number of pre-selected candidates significantly reduced the extra costs, while preserving most of the benefits in terms of genetic trends and inbreeding. Implementing genomic evaluations was the most efficient approach when major expenditure was possible, whereas increasing phenotypes was preferable when limited resources were available.

Conclusions

Economic decisions on implementing genomic evaluations in a pig nucleus population must take account of population characteristics, phenotyping and genotyping costs, and available funds.     

Genomic selection using low density marker panels with application to a sire line in pigs

Background

Genomic selection has become a standard tool in dairy cattle breeding. However, for other animal species, implementation of this technology is hindered by the high cost of genotyping. One way to reduce the routine costs is to genotype selection candidates with an SNP (single nucleotide polymorphism) panel of reduced density. This strategy is investigated in the present paper. Methods are proposed for the approximation of SNP positions, for selection of SNPs to be included in the low-density panel, for genotype imputation, and for the estimation of the accuracy of genomic breeding values. The imputation method was developed for a situation in which selection candidates are genotyped with an SNP panel of reduced density but have high-density genotyped sires. The dams of selection candidates are not genotyped. The methods were applied to a sire line pig population with 895 German Piétrain boars genotyped with the PorcineSNP60 BeadChip.

Results

Genotype imputation error rates were 0.133 for a 384 marker panel, 0.079 for a 768 marker panel, and 0.022 for a 3000 marker panel. Error rates for markers with approximated positions were slightly larger. Availability of high-density genotypes for close relatives of the selection candidates reduced the imputation error rate. The estimated decrease in the accuracy of genomic breeding values due to imputation errors was 3% for the 384 marker panel and negligible for larger panels, provided that at least one parent of the selection candidates was genotyped at high-density.Genomic breeding values predicted from deregressed breeding values with low reliabilities were more strongly correlated with the estimated BLUP breeding values than with the true breeding values. This was not the case when a shortened pedigree was used to predict BLUP breeding values, in which the parents of the individuals genotyped at high-density were considered unknown.

Conclusions

Genomic selection with imputation from very low- to high-density marker panels is a promising strategy for the implementation of genomic selection at acceptable costs. A panel size of 384 markers can be recommended for selection candidates of a pig breeding program if at least one parent is genotyped at high-density, but this appears to be the lower bound.     

A low-marker density implementation of genomic selection in aquaculture using within-family genomic breeding values

Background

Genomic selection can increase genetic gain within aquaculture breeding programs, but the high costs related to high-density genotyping of a large number of individuals would make the breeding program expensive. In this study, a low-cost method using low-density genotyping of pre-selected candidates and their sibs was evaluated by stochastic simulation.

Methods

A breeding scheme with selection for two traits, one measured on candidates and one on sibs was simulated. Genomic breeding values were estimated within families and combined with conventional family breeding values for candidates that were pre-selected based on conventional BLUP breeding values. This strategy was compared with a conventional breeding scheme and a full genomic selection program for which genomic breeding values were estimated across the whole population. The effects of marker density, level of pre-selection and number of sibs tested and genotyped for the sib-trait were studied.

Results

Within-family genomic breeding values increased genetic gain by 15% and reduced rate of inbreeding by 15%. Genetic gain was robust to a reduction in marker density, with only moderate reductions, even for very low densities. Pre-selection of candidates down to approximately 10% of the candidates before genotyping also had minor effects on genetic gain, but depended somewhat on marker density. The number of test-individuals, i.e. individuals tested for the sib-trait, affected genetic gain, but the fraction of the test-individuals genotyped only affected the relative contribution of each trait to genetic gain.

Conclusions

A combination of genomic within-family breeding values, based on low-density genotyping, and conventional BLUP family breeding values was shown to be a possible low marker density implementation of genomic selection for species with large full-sib families for which the costs of genotyping must be kept low without compromising the effect of genomic selection on genetic gain.     

Optimising multistage dairy cattle breeding schemes including genomic selection using decorrelated or optimum selection indices

Background

The prediction of the outcomes from multistage breeding schemes is especially important for the introduction of genomic selection in dairy cattle. Decorrelated selection indices can be used for the optimisation of such breeding schemes. However, they decrease the accuracy of estimated breeding values and, therefore, the genetic gain to an unforeseeable extent and have not been applied to breeding schemes with different generation intervals and selection intensities in each selection path.

Methods

A grid search was applied in order to identify optimum breeding plans to maximise the genetic gain per year in a multistage, multipath dairy cattle breeding program. In this program, different values of the accuracy of estimated genomic breeding values and of their costs per individual were applied, whereby the total breeding costs were restricted. Both decorrelated indices and optimum selection indices were used together with fast multidimensional integration algorithms to produce results.

Results

In comparison to optimum indices, the genetic gain with decorrelated indices was up to 40% less and the proportion of individuals undergoing genomic selection was different. Additionally, the interaction between selection paths was counter-intuitive and difficult to interpret. Independent of using decorrelated or optimum selection indices, genomic selection replaced traditional progeny testing when maximising the genetic gain per year, as long as the accuracy of estimated genomic breeding values was ≥ 0.45. Overall breeding costs were mainly generated in the path "dam-sire". Selecting males was still the main source of genetic gain per year.

Conclusion

Decorrelated selection indices should not be used because of misleading results and the availability of accurate and fast algorithms for exact multidimensional integration. Genomic selection is the method of choice when maximising the genetic gain per year but genotyping females may not allow for a reduction in overall breeding costs. Furthermore, the economic justification of genotyping females remains questionable.     

Identity-by-descent genomic selection using selective and sparse genotyping

Background

Genomic selection methods require dense and widespread genotyping data, posing a particular challenge if both sexes are subject to intense selection (e.g., aquaculture species). This study focuses on alternative low-cost genomic selection methods (IBD-GS) that use selective genotyping with sparse marker panels to estimate identity-by-descent relationships through linkage analysis. Our aim was to evaluate the potential of these methods in selection programs for continuous traits measured on sibs of selection candidates in a typical aquaculture breeding population.

Methods

Phenotypic and genomic data were generated by stochastic simulation, assuming low to moderate heritabilities (0.10 to 0.30) for a Gaussian trait measured on sibs of the selection candidates in a typical aquaculture breeding population that consisted of 100 families (100 training animals and 20 selection candidates per family). Low-density marker genotype data (~ 40 markers per Morgan) were used to trace genomic identity-by-descent relationships. Genotyping was restricted to selection candidates from 30 phenotypically top-ranking families and varying fractions of their phenotypically extreme training sibs. All phenotypes were included in the genetic analyses. Classical pedigree-based and IBD-GS models were compared based on realized genetic gain over one generation of selection.

Results

Genetic gain increased substantially (13 to 32%) with IBD-GS compared to classical selection and was greatest with higher heritability. Most of the extra gain from IBD-GS was obtained already by genotyping the 5% phenotypically most extreme sibs within the pre-selected families. Additional genotyping further increased genetic gains, but these were small when going from genotyping 20% of the extremes to all phenotyped sibs. The success of IBD-GS with sparse and selective genotyping can be explained by the fact that within-family haplotype blocks are accurately traced even with low-marker densities and that most of the within-family variance for normally distributed traits is captured by a small proportion of the phenotypically extreme sibs.

Conclusions

IBD-GS was substantially more effective than classical selection, even when based on very few markers and combined with selective genotyping of small fractions of the population. The study shows that low-cost GS programs can be successful by combining sparse and selective genotyping with pedigree and linkage information.     

Breeding replacement gilts for organic pig herds

In this study, breeding structures and commercial sow lines were evaluated by economic and genetic simulation studies for their suitability to provide the Dutch organic pig sector with replacement gilts. Sow and litter performance from over 2000 crossbred sows from 2006 to 2007 were collected on 11 to 14 Dutch organic pig herds, respectively, and compared with conventional herds. Results showed that organic herds had lower farrowing rates (3.6% to 7.5%), more live born piglets per litter (0.4% to 1.2%) and higher preweaning mortality rates (7% to 13%) compared to conventional herds. These results were used to simulate economic performance of various combinations of breeding structures and sow lines under organic conditions, under the assumption of absence of genotype-environment interactions. Sow and litter performance data under organic conditions (total piglets born/litter, stillborn piglets/litter, mortality until weaning, lactation length, interval weaning-oestrus and sow culling rate) and the costprice calculation for the Dutch organic pig sector were used as input for the economic simulation studies. The expected genetic progress was simulated for three potential breeding structures of the organic sector: organic breeding herds producing F1 gilts (OrgBS), a flower breeding system (FlowerBS) and a two-line rotation breeding system (RotBS). In FlowerBS, an organic purebred sow line is bred, using on-farm gilt replacement. The OrgBS with a Yorkshire × Landrace cross had the highest margin per sow place (€779), followed by RotBS with Yorkshire × Landrace cross (€706) and FlowerBS with Yorkshire sow line (€677). In case that an organic purebred sow population of 5000 sows would be available, FlowerBS gave the highest genetic progress in terms of cost price reduction (€3.72/slaughter pig per generation), followed by RotBS and OrgBS (€3.60/slaughter pig per generation). For FlowerBS, additional costs will be involved for maintaining a dedicated breeding programme. In conclusion, OrgBS using conventional genetics is economically the most viable option for the organic pig sector. However, this structure has clear disadvantages in terms of risks with regard to disease transmission and market demand. FlowerBS using a dedicated purebred organic line will only be cost-effective if sow population size is sufficiently large. RotBS might be a viable alternative, especially in combination with artificial insemination (AI) boars that are ranked according to an organic selection index. Regardless of breeding structure, the Yorkshire sow line gave the highest prolificacy and the highest economic returns on organic herds.     

The Economic Burden of Malaria on Households and the Health System in Enugu State Southeast Nigeria

Background

Malaria is the number one public health problem in Nigeria, responsible for about 30% of deaths in under-fives and 25% of deaths in infants and 11% maternal mortality. This study estimated the economic burden of malaria in Nigeria using the cost of illness approach.

Methods

A cross-sectional study was undertaken in two malaria holo-endemic communities in Nigeria, involving both community and hospital based surveys. A random sample of 500 households was interviewed using interviewer administered questionnaire. In addition, 125 exit interviews for inpatient department stays (IPD) and outpatient department visits (OPD) were conducted and these were complemented with data abstraction from 125 patient records.

Results

From the household survey, over half of the households (57.6%) had an episode of malaria within one month to the date of the interview. The average household expenditure per case was 12.57US$ and 23.20US$ for OPD and IPD respectively. Indirect consumer costs of treatment were higher than direct consumer medical costs. From a health system perspective, the recurrent provider costs per case was 30.42 US$ and 48.02 US$ for OPD and IPD while non recurrent provider costs were 133.07US$ and 1857.15US$ for OPD and IPD. The mode of payment was mainly through out-of-pocket spending (OOPS).

Conclusion

Private expenditure on treatment of malaria constitutes a high economic burden to households and to the health system. Removal of user fees and interventions that will decrease the use of OOPS for treatment of malaria will significantly decrease the economic burden of malaria to both households and the health system.     

Reliability of pedigree-based and genomic evaluations in selected populations

Background

Reliability is an important parameter in breeding. It measures the precision of estimated breeding values (EBV) and, thus, potential response to selection on those EBV. The precision of EBV is commonly measured by relating the prediction error variance (PEV) of EBV to the base population additive genetic variance (base PEV reliability), while the potential for response to selection is commonly measured by the squared correlation between the EBV and breeding values (BV) on selection candidates (reliability of selection). While these two measures are equivalent for unselected populations, they are not equivalent for selected populations. The aim of this study was to quantify the effect of selection on these two measures of reliability and to show how this affects comparison of breeding programs using pedigree-based or genomic evaluations.

Methods

Two scenarios with random and best linear unbiased prediction (BLUP) selection were simulated, where the EBV of selection candidates were estimated using only pedigree, pedigree and phenotype, genome-wide marker genotypes and phenotype, or only genome-wide marker genotypes. The base PEV reliabilities of these EBV were compared to the corresponding reliabilities of selection. Realized genetic selection intensity was evaluated to quantify the potential of selection on the different types of EBV and, thus, to validate differences in reliabilities. Finally, the contribution of different underlying processes to changes in additive genetic variance and reliabilities was quantified.

Results

The simulations showed that, for selected populations, the base PEV reliability substantially overestimates the reliability of selection of EBV that are mainly based on old information from the parental generation, as is the case with pedigree-based prediction. Selection on such EBV gave very low realized genetic selection intensities, confirming the overestimation and importance of genotyping both male and female selection candidates. The two measures of reliability matched when the reductions in additive genetic variance due to the Bulmer effect, selection, and inbreeding were taken into account.

Conclusions

For populations under selection, EBV based on genome-wide information are more valuable than suggested by the comparison of the base PEV reliabilities between the different types of EBV. This implies that genome-wide marker information is undervalued for selected populations and that genotyping un-phenotyped female selection candidates should be reconsidered.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-015-0145-1) contains supplementary material, which is available to authorized users.     

The Economic Burden of Meningitis to Households in Kassena-Nankana District of Northern Ghana

Objective

To estimate the direct and indirect costs of meningitis to households in the Kassena-Nankana District of Ghana.

Methods

A Cost of illness (COI) survey was conducted between 2010 and 2011. The COI was computed from a retrospective review of 80 meningitis cases answers to questions about direct medical costs, direct non-medical costs incurred and productivity losses due to recent meningitis incident.

Results

The average direct and indirect costs of treating meningitis in the district was GH¢152.55 (US$101.7) per household. This is equivalent to about two months minimum wage earned by Ghanaians in unskilled paid jobs in 2009. Households lost 29 days of work per meningitis case and thus those in minimum wage paid jobs lost a monthly minimum wage of GH¢76.85 (US$51.23) due to the illness. Patients who were insured spent an average of GH¢38.5 (US$25.67) in direct medical costs whiles the uninsured patients spent as much as GH¢177.9 (US$118.6) per case. Patients with sequelae incurred additional costs of GH¢22.63 (US$15.08) per case. The least poor were more exposed to meningitis than the poorest.

Conclusion

Meningitis is a debilitating but preventable disease that affects people living in the Sahel and in poorer conditions. The cost of meningitis treatment may further lead to impoverishment for these households. Widespread mass vaccination will save households'' an equivalent of GH¢175.18 (US$117) and impairment due to meningitis.     

The Costs of Scaling Up HIV Prevention for High Risk Groups: Lessons Learned from the Avahan Programme in India

Objective

The study objective is to measure, analyse costs of scaling up HIV prevention for high-risk groups in India, in order to assist the design of future HIV prevention programmes in South Asia and beyond.

Design

Prospective costing study.

Methods

This study is one of the most comprehensive studies of the costs of HIV prevention for high-risk groups to date in both its scope and size. HIV prevention included outreach, sexually transmitted infections (STI) services, condom provision, expertise enhancement, community mobilisation and enabling environment activities. Economic costs were collected from 138 non-government organisations (NGOs) in 64 districts, four state level lead implementing partners (SLPs), and the national programme level (Bill and Melinda Gates Foundation (BMGF)) office over four years using a top down costing approach, presented in US$ 2011.

Results

Mean total unit costs (2004–08) per person reached at least once a year and per monthly contact were US$ 235(56–1864) and US$ 82(12–969) respectively. 35% of the cost was incurred by NGOs, 30% at the state level SLP and 35% at the national programme level. The proportion of total costs by activity were 34% for expertise enhancement, 37% for programme management (including support and supervision), 22% for core HIV prevention activities (outreach and STI services) and 7% for community mobilisation and enabling environment activities. Total unit cost per person reached fell sharply as the programme expanded due to declining unit costs above the service level (from US$ 477 per person reached in 2004 to US$ 145 per person reached in 2008). At the service level also unit costs decreased slightly over time from US$ 68 to US$ 64 per person reached.

Conclusions

Scaling up HIV prevention for high risk groups requires significant investment in expertise enhancement and programme administration. However, unit costs decreased with programme expansion in spite of an increase in the scope of activities.     

Costs of Promoting Exclusive Breastfeeding at Community Level in Three Sites in South Africa

Background

Community-based peer support has been shown to be effective in improving exclusive breastfeeding rates in a variety of settings.

Methods

We conducted a cost analysis of a community cluster randomised-controlled trial (Promise-EBF), aimed at promoting exclusive infant feeding in three sites in South Africa. The costs were considered from the perspective of health service providers. Peer supporters in this trial visited women to support exclusive infant feeding, once antenatally and four times postpartum.

Results

The total economic cost of the Promise-EBF intervention was US$393 656, with average costs per woman and per visit of US$228 and US$52, respectively. The average costs per woman and visit in an operational ‘non research’ scenario were US$137 and US$32 per woman and visit, respectively. Investing in the promotion of exclusive infant feeding requires substantial financial commitment from policy makers. Extending the tasks of multi-skilled community health workers (CHWs) to include promoting exclusive infant feeding is a potential option for reducing these costs. In order to avoid efficiency losses, we recommend that the time requirements for delivering the promotion of exclusive infant feeding are considered when integrating it within the existing activities of CHWs.

Discussion

This paper focuses on interventions for exclusive infant feeding, but its findings more generally illustrate the importance of documenting and quantifying factors that affect the feasibility and sustainability of community-based interventions, which are receiving increased focus in low income settings.     

The use of communal rearing of families and DNA pooling in aquaculture genomic selection schemes

Background

Traditional family-based aquaculture breeding programs, in which families are kept separately until individual tagging and most traits are measured on the sibs of the candidates, are costly and require a high level of reproductive control. The most widely used alternative is a selection scheme, where families are reared communally and the candidates are selected based on their own individual measurements of the traits under selection. However, in the latter selection schemes, inclusion of new traits depends on the availability of non-invasive techniques to measure the traits on selection candidates. This is a severe limitation of these schemes, especially for disease resistance and fillet quality traits.

Methods

Here, we present a new selection scheme, which was validated using computer simulations comprising 100 families, among which 1, 10 or 100 were reared communally in groups. Pooling of the DNA from 2000, 20000 or 50000 test individuals with the highest and lowest phenotypes was used to estimate 500, 5000 or 10000 marker effects. One thousand or 2000 out of 20000 candidates were preselected for a growth-like trait. These pre-selected candidates were genotyped, and they were selected on their genome-wide breeding values for a trait that could not be measured on the candidates.

Results

A high accuracy of selection, i.e. 0.60-0.88 was obtained with 20000-50000 test individuals but it was reduced when only 2000 test individuals were used. This shows the importance of having large numbers of phenotypic records to accurately estimate marker effects. The accuracy of selection decreased with increasing numbers of families per group.

Conclusions

This new selection scheme combines communal rearing of families, pre-selection of candidates, DNA pooling and genomic selection and makes multi-trait selection possible in aquaculture selection schemes without keeping families separately until individual tagging is possible. The new scheme can also be used for other farmed species, for which the cost of genotyping test individuals may be high, e.g. if trait heritability is low.     

Patients' costs and cost-effectiveness of tuberculosis treatment in DOTS and non-DOTS facilities in Rio de Janeiro, Brazil

Background

Costs of tuberculosis diagnosis and treatment may represent a significant burden for the poor and for the health system in resource-poor countries.

Objectives

The aim of this study was to analyze patients'' costs of tuberculosis care and to estimate the incremental cost-effectiveness ratio (ICER) of the directly observed treatment (DOT) strategy per completed treatment in Rio de Janeiro, Brazil.

Methods

We interviewed 218 adult patients with bacteriologically confirmed pulmonary tuberculosis. Information on direct (out-of-pocket expenses) and indirect (hours lost) costs, loss in income and costs with extra help were gathered through a questionnaire. Healthcare system additional costs due to supervision of pill-intake were calculated considering staff salaries. Effectiveness was measured by treatment completion rate. The ICER of DOT compared to self-administered therapy (SAT) was calculated.

Principal Findings

DOT increased costs during the treatment phase, while SAT increased costs in the pre-diagnostic phase, for both the patient and the health system. Treatment completion rates were 71% in SAT facilities and 79% in DOT facilities. Costs per completed treatment were US$ 194 for patients and U$ 189 for the health system in SAT facilities, compared to US$ 336 and US$ 726 in DOT facilities. The ICER was US$ 6,616 per completed DOT treatment compared to SAT.

Conclusions

Costs incurred by TB patients are high in Rio de Janeiro, especially for those under DOT. The DOT strategy doubles patients'' costs and increases by fourfold the health system costs per completed treatment. The additional costs for DOT may be one of the contributing factors to the completion rates below the targeted 85% recommended by WHO.     

Design of reference populations for genomic selection in crossbreeding programs

Background

In crossbreeding programs, genomic selection offers the opportunity to make efficient use of information on crossbred (CB) individuals in the selection of purebred (PB) candidates. In such programs, reference populations often contain genotyped PB animals, although the breeding objective is usually more focused on CB performance. The question is what would be the benefit of including a larger proportion of CB individuals in the reference population.

Methods

In a deterministic simulation study, we evaluated the benefit of including various proportions of CB animals in a reference population for genomic selection of PB animals in a crossbreeding program. We used a pig breeding scheme with selection for a moderately heritable trait and a size of 6000 for the reference population.

Results

Applying genomic selection to improve the performance of CB individuals, with a genetic correlation between PB and CB performance (r_PC) of 0.7, selection accuracy of PB candidates increased from 0.49 to 0.52 if the reference population consisted of PB individuals, it increased to 0.55 if the reference population consisted of the same number of CB individuals, and to 0.60 if the size of the CB reference population was twice that of the reference population for each PB line. The advantage of using CB rather than PB individuals increased linearly with the proportion of CB individuals in the reference population. This advantage disappeared quickly if r_PC was higher or if the breeding objective put some emphasis on PB performance. The benefit of adding CB individuals to an existing PB reference population was limited for high r_PC.

Conclusions

Using CB rather than PB individuals in a reference population for genomic selection can provide substantial advantages, but only when correlations between PB and CB performances are not high and PB performance is not part of the breeding objective.     

Response and inbreeding from a genomic selection experiment in layer chickens

Background

Genomic selection (GS) using estimated breeding values (GS-EBV) based on dense marker data is a promising approach for genetic improvement. A simulation study was undertaken to illustrate the opportunities offered by GS for designing breeding programs. It consisted of a selection program for a sex-limited trait in layer chickens, which was developed by deterministic predictions under different scenarios. Later, one of the possible schemes was implemented in a real population of layer chicken.

Methods

In the simulation, the aim was to double the response to selection per year by reducing the generation interval by 50 %, while maintaining the same rate of inbreeding per year. We found that GS with retraining could achieve the set objectives while requiring 75 % fewer reared birds and 82 % fewer phenotyped birds per year. A multi-trait GS scenario was subsequently implemented in a real population of brown egg laying hens. The population was split into two sub-lines, one was submitted to conventional phenotypic selection, and one was selected based on genomic prediction. At the end of the 3-year experiment, the two sub-lines were compared for multiple performance traits that are relevant for commercial egg production.

Results

Birds that were selected based on genomic prediction outperformed those that were submitted to conventional selection for most of the 16 traits that were included in the index used for selection. However, although the two programs were designed to achieve the same rate of inbreeding per year, the realized inbreeding per year assessed from pedigree was higher in the genomic selected line than in the conventionally selected line.

Conclusions

The results demonstrate that GS is a promising alternative to conventional breeding for genetic improvement of layer chickens.     

Genetic diversity,population structure and subdivision of local Balkan pig breeds in Austria,Croatia, Serbia and Bosnia-Herzegovina and its practical value in conservation programs

Background

At present the Croatian Turopolje pig population comprises about 157 breeding animals. In Austria, 324 Turopolje pigs originating from six Croatian founder animals are registered. Multiple bottlenecks have occurred in this population, one major one rather recently and several more older and moderate ones. In addition, it has been subdivided into three subpopulations, one in Austria and two in Croatia, with restricted gene flow. These specificities explain the delicate situation of this endangered Croatian lard-type pig breed.

Methods

In order to identify candidate breeding animals or gene pools for future conservation breeding programs, we studied the genetic diversity and population structure of this breed using microsatellite data from 197 individuals belonging to five different breeds.

Results

The genetic diversity of the Turopolje pig is dramatically low with observed heterozygosities values ranging from 0.38 to 0.57. Split into three populations since 1994, two genetic clusters could be identified: one highly conserved Croatian gene pool in Turopoljski Lug and the"Posavina" gene pool mainly present in the Austrian population. The second Croatian subpopulation in Lonjsko Polje in the Posavina region shows a constant gene flow from the Turopoljski Lug animals.

Conclusions

One practical conclusion is that it is necessary to develop a "Posavina" boar line to preserve the "Posavina" gene pool and constitute a corresponding population in Croatia. Animals of the highly inbred herd in Turopoljski Lug should not be crossed with animals of other populations since they represent a specific phenotype-genotype combination. However to increase the genetic diversity of this herd, a program to optimize its sex ratio should be carried out, as was done in the Austrian population where the level of heterozygosity has remained moderate despite its heavy bottleneck in 1994.     

Prioritizing animals for dense genotyping in order to impute missing genotypes of sparsely genotyped animals

Background

Genotyping accounts for a substantial part of the cost of genomic selection (GS). Using both dense and sparse SNP chips, together with imputation of missing genotypes, can reduce these costs. The aim of this study was to identify the set of candidates that are most important for dense genotyping, when they are used to impute the genotypes of sparsely genotyped animals. In a real pig pedigree, the 2500 most recently born pigs of the last generation, i.e. the target animals, were used for sparse genotyping. Their missing genotypes were imputed using either Beagle or LDMIP from T densely genotyped candidates chosen from the whole pedigree. A new optimization method was derived to identify the best animals for dense genotyping, which minimized the conditional genetic variance of the target animals, using either the pedigree-based relationship matrix (MCA), or a genotypic relationship matrix based on sparse marker genotypes (MCG). These, and five other methods for selecting the T animals were compared, using T = 100 or 200 animals, SNP genotypes were obtained assuming Ne =100 or 200, and MAF thresholds set to D = 0.01, 0.05 or 0.10. The performances of the methods were compared using the following criteria: call rate of true genotypes, accuracy of genotype prediction, and accuracy of genomic evaluations using the imputed genotypes.

Results

For all criteria, MCA and MCG performed better than other selection methods, significantly so for all methods other than selection of sires with the largest numbers of offspring. Methods that choose animals that have the closest average relationship or contribution to the target population gave the lowest accuracy of imputation, in some cases worse than random selection, and should be avoided in practice.

Conclusion

Minimization of the conditional variance of the genotypes in target animals provided an effective optimization procedure for prioritizing animals for genotyping or sequencing.

Electronic supplementary material

The online version of this article (doi:10.1186/1297-9686-46-46) contains supplementary material, which is available to authorized users.     

Connectedness among herds of beef cattle bred under natural service

Background

A procedure to measure connectedness among herds was applied to a beef cattle population bred by natural service. It consists of two steps: (a) computing coefficients of determination (CDs) of comparisons among herds; and (b) building sets of connected herds.

Methods

The CDs of comparisons among herds were calculated using a sampling-based method that estimates empirical variances of true and predicted breeding values from a simulated n-sample. Once the CD matrix was estimated, a clustering method that can handle a large number of comparisons was applied to build compact clusters of connected herds of the Bruna dels Pirineus beef cattle. Since in this breed, natural service is predominant and there are almost no links with reference sires, to estimate CDs, an animal model was used taking into consideration all pedigree information and, especially, the connections with dams. A sensitivity analysis was performed to contrast single-trait sire and animal model evaluations with different heritabilities, multiple-trait animal model evaluations with different degrees of genetic correlations and models with maternal effects.

Results

Using a sire model, the percentage of connected herds was very low even for highly heritable traits whereas with an animal model, most of the herds of the breed were well connected and high CD values were obtained among them, especially for highly heritable traits (the mean of average CD per herd was 0.535 for a simulated heritability of 0.40). For the lowly heritable traits, the average CD increased from 0.310 in the single-trait evaluation to 0.319 and 0.354 in the multi-trait evaluation with moderate and high genetic correlations, respectively. In models with maternal effects, the average CD per herd for the direct effects was similar to that from single-trait evaluations. For the maternal effects, the average CD per herd increased if the maternal effects had a high genetic correlation with the direct effects, but the percentage of connected herds for maternal effects was very low, less than 12%.

Conclusions

The degree of connectedness in a bovine population bred by natural service mating, such as Bruna del Pirineus beef cattle, measured as the CD of comparisons among herds, is high. It is possible to define a pool of animals for which estimated breeding values can be compared after an across-herds genetic evaluation, especially for highly heritable traits.     

Cost-effectiveness of early versus standard antiretroviral therapy in HIV-infected adults in Haiti

Background

In a randomized clinical trial of early versus standard antiretroviral therapy (ART) in HIV-infected adults with a CD4 cell count between 200 and 350 cells/mm³ in Haiti, early ART decreased mortality by 75%. We assessed the cost-effectiveness of early versus standard ART in this trial.

Methods and Findings

Trial data included use of ART and other medications, laboratory tests, outpatient visits, radiographic studies, procedures, and hospital services. Medication, laboratory, radiograph, labor, and overhead costs were from the study clinic, and hospital and procedure costs were from local providers. We evaluated cost per year of life saved (YLS), including patient and caregiver costs, with a median of 21 months and maximum of 36 months of follow-up, and with costs and life expectancy discounted at 3% per annum. Between 2005 and 2008, 816 participants were enrolled and followed for a median of 21 months. Mean total costs per patient during the trial were US$1,381 for early ART and US$1,033 for standard ART. After excluding research-related laboratory tests without clinical benefit, costs were US$1,158 (early ART) and US$979 (standard ART). Early ART patients had higher mean costs for ART (US$398 versus US$81) but lower costs for non-ART medications, CD4 cell counts, clinically indicated tests, and radiographs (US$275 versus US$384). The cost-effectiveness ratio after a maximum of 3 years for early versus standard ART was US$3,975/YLS (95% CI US$2,129/YLS–US$9,979/YLS) including research-related tests, and US$2,050/YLS excluding research-related tests (95% CI US$722/YLS–US$5,537/YLS).

Conclusions

Initiating ART in HIV-infected adults with a CD4 cell count between 200 and 350 cells/mm³ in Haiti, consistent with World Health Organization advice, was cost-effective (US$/YLS <3 times gross domestic product per capita) after a maximum of 3 years, after excluding research-related laboratory tests.

Trial registration

ClinicalTrials.gov {"type":"clinical-trial","attrs":{"text":"NCT00120510","term_id":"NCT00120510"}}NCT00120510 Please see later in the article for the Editors'' Summary