Congruence between selection on breeding values and farmers' selection criteria in sheep breeding under conventional nucleus breeding schemes

Designing breeding schemes suitable for smallholder livestock production systems in developing regions has hitherto been a challenge. The suggested schemes either do not address farmers' breeding goals (centralized station-based nucleus schemes) or yield slow genetic progress (village-based schemes). A new breeding scheme that integrates the merits of previously suggested schemes has been designed for Menz sheep improvement in Ethiopia. It involves selection based on breeding values in nucleus flocks to produce elite rams, a one-time only provision of improved rams to villagers and a follow-up village-based selection to sustain genetic progress in village flocks. Here, we assessed whether conventional selection of breeding rams based on breeding values for production traits, which is the practice in station-based nucleus flocks, meets farmers' breeding objectives. We also elicited determinants of farmers' ram choice. Low but significant correlations were found between rankings of rams based on farmers' selection criteria, estimated breeding values (EBV) and body weight (BW). Appearance traits (such as color and horn) and meat production traits (BW and linear size traits) significantly determined farmers' breeding ram choice. The results imply that conventional selection criteria based solely on EBV for production traits do not address farmers' trait preferences fully, but only partially. Thus, a two-stage selection procedure involving selection on breeding values in nucleus centers followed by farmers' selection among top- ranking candidate rams is recommended. This approach accommodates farmers' preferences and speeds up genetic progress in village-based selection. The Menz sheep scheme could be applied elsewhere with similar situations to transform conventional station-based nucleus breeding activities into participatory breeding programs.     

Optimising multi-tier open nucleus breeding schemes

Summary The constant migration (CM) method and the ebv migration (EBVM) method of optimising the design of multi-tier open nucleus breeding schemes are presented and compared. The equation for the equilibrium rate of genetic gain of a three-tier open nucleus scheme is determined using the CM method. The major advantage of the EBVM method is the reduction in the number of parameters which have to be varied in order to locate the maximum equilibrium rate of genetic gain. For the CM method for the number of variable parameters is 5, 14, 27 and (2n + 1) (n - 1) for unrestricted male and female migration in schemes with 2, 3, 4 and n tiers respectively. The corresponding number of variable parameters for the EBVM method is 1, 2, 3 and n-1 respectively. A procedure is given for the EBVM method so as to accomodate variance loss due to selection and variance gain due to the mixing of groups with a different mean breeding value.     

Optimising two-stage independent culling selection in tree and animal breeding

Summary Theory is given for a simple practical method of predicting gain from two-stage independent culling, where stage 1 of selection is for individual performance and stage 2 is for either progeny performance only, or an index combining individual and progeny performance. Expected gain is determined as a direct function of heritabilities, genetic correlations, selection intensities and progeny-testing capacity. Results show the effect these parameters can have on proportions selected at each stage and, if multiple selection criteria are used, traits selected for first. Methods are discussed in the context of tree and animal breeding, with an example taken from forestry.     

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.     

Simulation study on the efficiencies of MOET nucleus breeding schemes applying marker assisted selection in dairy cattle

Advantages of breeding schemes using genetic marker information and/or multiple ovulation and embryo transfer (MOET) technology over the traditional approach were extensively evaluated through simulation. Milk yield was the trait of interest and QTL was the genetic marker utilized. Eight dairy cattle breeding scenarios were considered, i.e., traditional progeny testing breeding scheme (denoted as STANPT), GASPT scheme including a pre-selection of young bulls entering progeny testing based on their own QTL information, MOETPT scheme using MOET technology to generate young bulls and a selection of young bulls limited within the full-sib family, GAMOPT scheme adopting both QTL pre-selection and MOET technology, COMBPT scheme using a mixed linear model which considered QTL genotype instead of the BLUP model in GAMOPT, and three non-progeny testing schemes, i.e. the MOET, GAMO and COMB schemes, corresponding to MOETPT, GAMOPT and COMBPT with progeny testing being part of the system. Animals were selected based on their breeding value which was estimated under an animal model framework. Sequential selection over 17 years was performed in the simulations and 30 replicates were designed for each scenario. The influences of using QTL information and MOET technology on favorable QTL allele frequency, true breeding values, polygenetic breeding values and the accumulated genetic superiority were extensively evaluated, for five different populations including active sires, lactating cows, bull dams, bull sires, and young bulls. The results showed that the combined schemes significantly outperformed other approaches wherein accumulated true breeding value progressed. The difference between schemes exclusively using QTL information or MOET technology was not significant. The STANPT scheme was the least efficient among the 8 schemes. The schemes using MOET technology had a higher polygenetic response than others in the 17th year. The increases of frequency of the favorable QTL allele varied more greatly across the 3 male groups than in the lactating cows group. The accumulated genetic superiorities of the GASPT scheme, MOETPT scheme, GAMOPT scheme, COMBPT scheme, MOET scheme, GAMO scheme and COMB scheme over the STANPT scheme were 8.42%, 3.59%, 14.58%, 18.54%, 4.12%, 14.12%, 16.50% in active sires and 2.70%, 5.00%, 11.05%, 12.78%, 7.51%, 17.12%, 25.38% in lactating cows. Supported by Key Project for Introducing Advanced International Agriculture Science & Technologies (Grant No. 2006-G48), the National Key Basic Research and Development Program of China (Grant No. 2006CB102107) and National Key Technology Research and Development Program of China (Grant No. 2006BAD04A01).     

Hybrid maize breeding with doubled haploids: I. One-stage versus two-stage selection for testcross performance

Optimum allocation of resources is of fundamental importance for the efficiency of breeding programs. The objectives of our study were to (1) determine the optimum allocation for the number of lines and test locations in hybrid maize breeding with doubled haploids (DHs) regarding two optimization criteria, the selection gain ΔG _k and the probability P _k of identifying superior genotypes, (2) compare both optimization criteria including their standard deviations (SDs), and (3) investigate the influence of production costs of DHs on the optimum allocation. For different budgets, number of finally selected lines, ratios of variance components, and production costs of DHs, the optimum allocation of test resources under one- and two-stage selection for testcross performance with a given tester was determined by using Monte Carlo simulations. In one-stage selection, lines are tested in field trials in a single year. In two-stage selection, optimum allocation of resources involves evaluation of (1) a large number of lines in a small number of test locations in the first year and (2) a small number of the selected superior lines in a large number of test locations in the second year, thereby maximizing both optimization criteria. Furthermore, to have a realistic chance of identifying a superior genotype, the probability P _k of identifying superior genotypes should be greater than 75%. For budgets between 200 and 5,000 field plot equivalents, P _k > 75% was reached only for genotypes belonging to the best 5% of the population. As the optimum allocation for P _k (5%) was similar to that for ΔG _k , the choice of the optimization criterion was not crucial. The production costs of DHs had only a minor effect on the optimum number of locations and on values of the optimization criteria. C. Friedrich H. Longin and H. Friedrich Utz contributed equally to this work.     

Hybrid maize breeding with doubled haploids. IV. Number versus size of crosses and importance of parental selection in two-stage selection for testcross performance

Parental selection influences the gain from selection and the optimum allocation of test resources in breeding programs. We compared two hybrid maize (Zea mays L.) breeding schemes with evaluation of testcross progenies: (a) doubled haploid (DH) lines in both stages (DHTC) and (b) S₁ families in the first stage and DH lines within S₁ families in the second stage (S₁TC-DHTC). Our objectives were to (1) determine the optimum allocation regarding the number of crosses, S₁ families, DH lines, and test locations, (2) investigate the impact of parental selection on the optimum allocation and selection gain (ΔG), and (3) compare the maximum ΔG achievable with each breeding scheme. Selection gain was calculated by numerical integration. Different assumptions were made regarding the budget, variance components, correlation between the mean phenotypic performance of the parents and the mean genotypic value of the testcross performance of their progenies (ρ _P ), and the composition of the finally selected test candidates. In comparison with randomly chosen crosses, maximum ΔG was largely increased with parental selection in both breeding schemes. With an increasing correlation ρ _P , this superiority increased strongly, while the optimum number of crosses decreased in favor of an increased number of test candidates within crosses. Thus, concentration on few crosses among the best parental lines might be a promising approach for short-term success in advanced cycle breeding. Breeding scheme S₁TC-DHTC led to a larger ΔG but had a longer cycle length than DHTC. However, with further improvements in the DH technique and the realization of more than two generations per year, early testing of S₁ families prior to production of DH lines would become very attractive in hybrid maize breeding. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users. T. Wegenast and C. F. H. Longin contributed equally to this work.     

Epidemiology of Ostertagia ostertagi in dairy cow from different breeding systems

The epidemiology of Trichostrongylidae infections in three dairy cow groups reared under different conditions and in different habitats was studied with particular emphasis on Ostertagia ostertagi. In cows bred intensively in swampy lowlands (Po River Valley) the prevalence of infection was 43% and the mean intensity 567. In cows bred traditionally (Friuli, Northern-Eastern Italy), the prevalence in permanently housed cows was 24% (mean intensity: 13). In grazing cows, it was 68% (mean intensity: 120). The distribution of parasite numbers (O. ostertagi) per host was studied with the negative binomial model. The observed data were also compared by the method of cumulative relative frequencies. The results suggest that parasitism is also important in cows reared intensively.     

Using vegetation indices derived from conventional digital cameras as selection criteria for wheat breeding in water-limited environments

The ability to assess green biomass is of particular interest in a number of wheat breeding environments. However, the measurement of this and similar traits is either tedious and time-consuming or requires the use of expensive, sophisticated equipment, such as field-based spectroradiometers to measure vegetation indices (VIs). Here, conventional digital cameras are proposed as affordable and easy-to-use tools for gathering field data in wheat breeding programmes. Using appropriate software, a large set of images can be automatically processed to calculate a number of VIs, based on the performance of simple colour operations on each picture. The purpose of this study was to identify a set of picture-derived vegetation indices (picVIs) and to evaluate their performance in durum wheat trials growing under rainfed and supplementary irrigation conditions. Here, zenithal pictures of each plot were obtained roughly 2 weeks after anthesis, and the picVIs that were calculated were compared with the normalised difference vegetation index (NDVI), an index derived from spectroradiometrical measurements, and with the grain yield (GY) from the same plots. The picVIs that performed best were the Hue, CIE-Lab a* and CIE-Luv u* components of the average colour of each picture, the relative green area (GA) and the 'greener area', similar to GA but excluding the more yellowish-green pixels. Our results showed a high correlation between all these picVIs and the NDVI. Moreover, in rainfed conditions, each picVI provided an estimation of GY similar to or slightly better than that provided by the NDVI. However, in irrigated conditions during anthesis, neither these picVIs nor the NDVI provided a good estimation of GY, apparently because of the saturation of the VI response in conditions of complete soil cover and high plant density.     

Selection indices for quality evaluation in wheat breeding

Summary From multilocation trials involving 125 cultivars of wheat of mainly French and European origin four tests — protein content, Pelshenke, modified Zeleny and the mixograph — were used to establish six selection indices. Three of these indices — IW₁, IW₂ and IW₃ — were calculated in order to evaluate the genetic potentiality of the lines for dough strength as given by the Chopin alveograph. The indices IV₁, IV₂ and IV₃ were established to evaluate loaf volume as measured by the French bread-making standard. A quality index IQ was calculated from the allelic effects of the high-molecular-weight (HMW) subunits of glutenin from 195 cultivars assessed by the Chopin alveograph and the Pelshenke test. Comparison of the relative efficiency of each of the six indices to the individual tests revealed the superiority of the indices over one or several technological parameters. The six selection indices and the quality index were compared using 30 very diverse F₄ lines. Their ability to retain the good quality lines is discussed in particular.     

Genomic selection in forest tree breeding

Genomic selection (GS) involves selection decisions based on genomic breeding values estimated as the sum of the effects of genome-wide markers capturing most quantitative trait loci (QTL) for the target trait(s). GS is revolutionizing breeding practice in domestic animals. The same approach and concepts can be readily applied to forest tree breeding where long generation times and late expressing complex traits are also a challenge. GS in forest trees would have additional advantages: large training populations can be easily assembled and accurately phenotyped for several traits, and the extent of linkage disequilibrium (LD) can be high in elite populations with small effective population size (N _e) frequently used in advanced forest tree breeding programs. Deterministic equations were used to assess the impact of LD (modeled by N _e and intermarker distance), the size of the training set, trait heritability, and the number of QTL on the predicted accuracy of GS. Results indicate that GS has the potential to radically improve the efficiency of tree breeding. The benchmark accuracy of conventional BLUP selection is reached by GS even at a marker density ~2 markers/cM when N _e ≤ 30, while up to 20 markers/cM are necessary for larger N _e. Shortening the breeding cycle by 50% with GS provides an increase ≥100% in selection efficiency. With the rapid technological advances and declining costs of genotyping, our cautiously optimistic outlook is that GS has great potential to accelerate tree breeding. However, further simulation studies and proof-of-concept experiments of GS are needed before recommending it for operational implementation.     

Hybrid maize breeding with doubled haploids: II. Optimum type and number of testers in two-stage selection for general combining ability

Optimum allocation of test resources is of crucial importance for the efficiency of breeding programs. Our objectives were to (1) determine the optimum allocation of the number of lines, test locations, as well as number and type of testers in hybrid maize breeding using doubled haploids with two breeding strategies for improvement of general combining ability (GCA), (2) compare the maximum selection gain (ΔG) achievable under both strategies, and (3) give recommendations for the optimum implementation of doubled haploids in commercial hybrid maize breeding. We calculated ΔG by numerical integration for two two-stage selection strategies with evaluation of (1) testcross performance in both stages (BS1) or (2) line per se performance in the first stage followed by testcross performance in the second stage (BS2). Different assumptions were made regarding the budget, variance components (VCs), and the correlation between line per se performance and GCA. Selection gain for GCA increased with a broader genetic base of the tester. Hence, testers combining a large number of divergent lines are advantageous. However, in applied breeding programs, the use of single- or double-cross testers in the first and inbred testers in the second selection stage may be a good compromise between theoretical and practical requirements. With a correlation between line per se performance and GCA of 0.50, ΔG for BS1 is about 5% higher than for BS2, if an economic weight of line per se performance is neglected. With increasing economic weight of line per se performance, relative efficiency of BS2 increased rapidly resulting in a superiority of BS2 over BS1 already for an economic weight for line per se performance larger than 0.1. Considering the importance of an economic seed production, an economic weight larger than 0.1 seems realistic indicating the necessity of separate breeding strategies for seed and pollen parent heterotic groups. C. Friedrich H. Longin and H. Friedrich Utz have contributed equally to this work.     

Genome-wide association and genomic selection in animal breeding

Results from genome-wide association studies in livestock, and humans, has lead to the conclusion that the effect of individual quantitative trait loci (QTL) on complex traits, such as yield, are likely to be small; therefore, a large number of QTL are necessary to explain genetic variation in these traits. Given this genetic architecture, gains from marker-assisted selection (MAS) programs using only a small number of DNA markers to trace a limited number of QTL is likely to be small. This has lead to the development of alternative technology for using the available dense single nucleotide polymorphism (SNP) information, called genomic selection. Genomic selection uses a genome-wide panel of dense markers so that all QTL are likely to be in linkage disequilibrium with at least one SNP. The genomic breeding values are predicted to be the sum of the effect of these SNPs across the entire genome. In dairy cattle breeding, the accuracy of genomic estimated breeding values (GEBV) that can be achieved and the fact that these are available early in life have lead to rapid adoption of the technology. Here, we discuss the design of experiments necessary to achieve accurate prediction of GEBV in future generations in terms of the number of markers necessary and the size of the reference population where marker effects are estimated. We also present a simple method for implementing genomic selection using a genomic relationship matrix. Future challenges discussed include using whole genome sequence data to improve the accuracy of genomic selection and management of inbreeding through genomic relationships.     

Impact of selection and breeding on the genetic diversity in Douglas-fir

Genetic changes following domestication of Douglas-fir were studied using isozyme data derived from two generations of seed orchards and their 49 wild progenitor populations. In addition, the breeding, production, and infusion populations used in the seed orchards were compared to their wild counterparts. Several parameters of gene diversity were measured (number of alleles per locus N _a, per cent of polymorphic loci PLP, and expected heterozygosity H, and population divergence D). These measures were similar or higher in the domesticated populations compared to their natural progenitors, indicating that early selection and breeding of a highly polymorphic species does not significantly reduce genetic variation. The two generations of seed orchards also did not differ, indicating that genetic variation may remain stable over future generations of forest plantations. Interestingly, compared to the natural populations, heterozygosity was higher in the seed orchards, probably due to pooling of widely distributed natural populations; however, rare localized or private alleles seemed to be less frequent in the domesticated populations. Differentiation values were not significant between the first generation orchards and the natural populations, but significant differences were observed between the second generation orchards and the wild progenitor populations, probably due to the interbreeding that forms the advanced generation seed orchards.