Commercial Breeding Programs Research Articles

Genome-Wide Association Analysis of the Anthocyanin and Carotenoid Contents of Rose Petals.

Petal color is one of the key characteristics determining the attractiveness and therefore the commercial value of an ornamental crop. Here, we present the first genome-wide association study for the important ornamental crop rose, focusing on the anthocyanin and carotenoid contents in petals of 96 diverse tetraploid garden rose genotypes. Cultivated roses display a vast phenotypic and genetic diversity and are therefore ideal targets for association genetics. For marker analysis, we used a recently designed Axiom SNP chip comprising 68,000 SNPs with additionally 281 SSRs, 400 AFLPs and 246 markers from candidate genes. An analysis of the structure of the rose population revealed three subpopulations with most of the genetic variation between individual genotypes rather than between clusters and with a high average proportion of heterozygous loci. The mapping of markers significantly associated with anthocyanin and carotenoid content to the related Fragaria and Prunus genomes revealed clusters of associated markers indicating five genomic regions associated with the total anthocyanin content and two large clusters associated with the carotenoid content. Among the marker clusters associated with the phenotypes, we found several candidate genes with known functions in either the anthocyanin or the carotenoid biosynthesis pathways. Among others, we identified a glutathione-S-transferase, 4CL, an auxin response factor and F3'H as candidate genes affecting anthocyanin concentration, and CCD4 and Zeaxanthine epoxidase as candidates affecting the concentration of carotenoids. These markers are starting points for future validation experiments in independent populations as well as for functional genomic studies to identify the causal factors for the observed color phenotypes. Furthermore, validated markers may be interesting tools for marker-assisted selection in commercial breeding programmes in that they provide the tools to identify superior parental combinations that combine several associated markers in higher dosages.

Wheat variety yield data: Do commercial and public performance tests provide the same information?

AbstractWheat yields from reported performance test results are of economic importance to wheat producers, since their profits depend on selecting the optimal variety for their location. However, our data shows differences in absolute and relative wheat yields between commercial and public wheat breeding program's performance test data in Kansas. Newly available data are used to test if the difference in yields arose from potential selectivity bias, and to determine the contribution of private and public wheat breeding programs to varietal yield improvement during 2007–2012. Both Heckman selection models and multiple regression showed no statistical evidence of the potential presence of selectivity bias rather, managerial practices, agronomic conditions, field location, and inherent genetic traits of the seed variety were identify as the source of yield differences.

Population extremes for assessing trait value and correlated response of genetically complex traits

Physiological studies have led to the identification of many traits hypothesized to be useful for breeding improved crop performance. The effect of selection for these traits on yield across breeding populations and across target environments is generally unknown, such that crop breeders may have difficulty in prioritizing evaluation resources among potentially many traits. A simple method to estimate the effect on crop performance from selection on a proposed trait would facilitate trait adoption toward implementation and delivery in improved varieties. The response to indirect selection for different traits can be accurately predicted with nearly-isogenic lines differing for only small regions of the genome and those traits under investigation. An alternative approach better suited to complex, polygenic traits is the assessment of direct and indirect response in ‘tails’ representing phenotypic extremes from a distribution for a target trait. The smaller set of lines representing the two tail groups can then be evaluated more extensively for yield or other expensive and difficult to phenotype traits. Assuming an infinitesimal model appropriate for polygenic traits, we used simulations to understand the influence of population size, proportion of lines sampled in each tail group, trait heritability, and the genotypic correlation between the selection and evaluation trait on the resulting difference between tail means. The power of the tail comparison test was closely related to the heritability of the selection trait and its genotypic correlation with the evaluation trait, demonstrating that the tail comparison test can appropriately evaluate and rank the potential utility of different selection traits. Increasing the entry-mean heritability through multiple environment testing can be coupled with larger population and tail group sizes to increase power and confidence in assessment of both selection and response trait values. We assessed the selection of phenotypic distribution tails for water productivity traits in wheat. Reduced-tillering tails were associated with an average 14% reduction in tiller number and significantly reduced yields (−5%), particularly at wider row-spacings. High vigour tails were associated with a 49% increase in early ground cover, 40% increase in NDVI score, and greater yields (+18%) across all sampled environments. Assessment of population tails across multiple genetic backgrounds will guide selection in commercial breeding programs and facilitate trait delivery in improved cultivars.

Accuracy of Genomic Prediction in a Commercial Perennial Ryegrass Breeding Program.

The implementation of genomic selection (GS) in plant breeding, so far, has been mainly evaluated in crops farmed as homogeneous varieties, and the results have been generally positive. Fewer results are available for species, such as forage grasses, that are grown as heterogenous families (developed from multiparent crosses) in which the control of the genetic variation is far more complex. Here we test the potential for implementing GS in the breeding of perennial ryegrass ( L.) using empirical data from a commercial forage breeding program. Biparental F and multiparental synthetic (SYN) families of diploid perennial ryegrass were genotyped using genotyping-by-sequencing, and phenotypes for five different traits were analyzed. Genotypes were expressed as family allele frequencies, and phenotypes were recorded as family means. Different models for genomic prediction were compared by using practically relevant cross-validation strategies. All traits showed a highly significant level of genetic variance, which could be traced using the genotyping assay. While there was significant genotype × environment (G × E) interaction for some traits, accuracies were high among F families and between biparental F and multiparental SYN families. We have demonstrated that the implementation of GS in grass breeding is now possible and presents an opportunity to make significant gains for various traits.

Overview of Turkey Semen Storage: Focus on Cryopreservation – A Review

Abstract This review updates the current state of technologies available for turkey semen storage (hypothermic- liquid storage and cryopreservation), with special attention paid to cryopreservation. Liquid semen can be stored for up to 24 or 48 h at temperatures around 5°C, while cryopreservation allows long-term storage at -196°C. The possibility of using frozen turkey semen for artificial insemination (AI) would have practical benefits for turkey production. Reported fertility rates in response to AI using frozen/thawed semen range from 15.8 to 84.3%. Unsatisfactory fertility may be attributed to an inability of turkey spermatozoa to successfully survive the freezing/thawing process, and this, along with the high variability observed, makes this technique unacceptable for commercial breeding programs. There is therefore a need to standardize the whole freezing and thawing process to improve the post-thaw quality of turkey semen and minimize variability in results. Finding an efficient freezing protocol for turkey semen will allow for the creation of a sperm cryobank, improving current prospects for the commercial use of frozen turkey semen and also for the long-term conservation of the genetic diversity of this bird.

Genetic characteristics of broodstock and offspring of the seven-band grouper (Hyporthodus septemfasciatus) using fluorescent-AFLP markers

Seven-band grouper (Hyporthodus septemfasciatus) is a commercial rocky reef fish in East Asia that has been regarded as a promising species for aquaculture. To investigate the broodstock contributions to offspring for the sustainability of fry production, 62 individuals ofH. septemfasciatusfrom two broodstocks and one offspring population were analysed using fluorescent-AFLP. A total of 602 bands were amplified and 70.10% of them were polymorphic. The numbers of polymorphic loci were 308 (Pbroodstock I= 55.50%) and 356 (Pbroodstock II= 63.12%) in the two broodstocks, and 294 (Poffspring= 52.88%) in the offspring, respectively. The average values of Shannon diversity index (I) and expected heterozygosity (H) were higher in the broodstock (Ibroodstock I= 0.281,Ibroodstock II= 0.244,Hbroodstock I= 0.185,Hbroodstock II= 0.161) than those in the offspring (Ioffspring= 0.243,Hoffspring= 0.161). AMOVA and FSTanalyses showed that significant genetic differentiation between broodstock and offspring populations, and limited effective broodstock population size has contributed to the offspring. Both STRUCTURE and Principal Coordinates Analysis (PCoA) also showed the three populations composed of two stocks and most offspring individuals (95.0%) only originated from 44.0% of the individuals of broodstock I, which may have negative effects on sustainable fry production. Therefore, genetic variation between broodstock and offspring should be monitored, and large effective size of broodstock should be employed to ensure the success of commercial breeding programmes. Our data provide a useful genetic basis for future planning of sustainable culture and management ofH. septemfasciatus.

Response to five generations of selection for growth performance traits in rainbow trout (Oncorhynchus mykiss)

A pedigreed rainbow trout population (~100 families per generation) was selected for five generations to improve growth performance to the standard ~500-gram US market weight and beyond (>1kg). Body weights (BW) were recorded each generation at 5, 8, 10, and 13months post-hatch. Selection was applied to a two-trait index of estimated breeding values for 10-month body weight (i.e., approximate market weight) and thermal growth coefficient between 10 and 13months, and both traits were given equal weighting in the index. Objectives of this study were to estimate direct selection responses for BW traits and thermal growth coefficient, and correlated response for condition factor traits. Heritability estimates were 0.28±0.08 to 0.43±0.14 for BW between 5 and 13months post-hatch, 0.12±0.03 for thermal growth coefficient, and 0.40±0.04 and 0.36±0.04 for condition factor at 10 and 13months post-hatch, respectively. Genetic correlations among the four BW measures were highest between adjacent BW measures (0.54±0.19 to 0.82±0.05) and decreased as time between measures increased. Genetic correlation between thermal growth coefficient and 10-month BW was low (0.18±0.13), and genetic correlations between condition factor and BW measured at the same age were moderate (0.39±0.09 to 0.45±0.08). Compared to randomly-mated control lines, selection response in the selected line averaged 10.6% (5-month BW), 9.8% (8-month BW), 12.7% (10-month BW), 11.9% (13-month BW), 2.1% (thermal growth coefficient), 3.4% (10-month condition factor), and 3.3% (13-month condition factor) per generation. The rate of inbreeding averaged 0.86% per generation in the selection line, with a cumulative inbreeding estimate of 4.5% in the last generation. The low heritability of thermal growth coefficient, and low genetic correlation with 10-month BW, resulted in only modest selection response for thermal growth coefficient. Larger heritabilities of BW measured at fixed ages, and large genetic correlations between serial BW measures, suggest that direct selection on BW will be more favorable than selection on TGC. This study demonstrates the large and sustained potential for genetic improvement of growth performance in domesticated rainbow trout with only modest accumulation of inbreeding, and provides empirical selection response estimates that have direct inference to commercial breeding programs aiming to select for growth to larger market BW. Statement of relevanceQuantitative genetics data from this relatively long-term and large-scale selective breeding program have direct inference to commercial breeding programs selecting for improved growth, but for which maintenance of control lines is not practical.

Genomic Prediction of Barley Hybrid Performance.

Hybrid breeding in barley ( L.) offers great opportunities to accelerate the rate of genetic improvement and to boost yield stability. A crucial requirement consists of the efficient selection of superior hybrid combinations. We used comprehensive phenotypic and genomic data from a commercial breeding program with the goal of examining the potential to predict the hybrid performances. The phenotypic data were comprised of replicated grain yield trials for 385 two-way and 408 three-way hybrids evaluated in up to 47 environments. The parental lines were genotyped using a 3k single nucleotide polymorphism (SNP) array based on an Illumina Infinium assay. We implemented ridge regression best linear unbiased prediction modeling for additive and dominance effects and evaluated the prediction ability using five-fold cross validations. The prediction ability of hybrid performances based on general combining ability (GCA) effects was moderate, amounting to 0.56 and 0.48 for two- and three-way hybrids, respectively. The potential of GCA-based hybrid prediction requires that both parental components have been evaluated in a hybrid background. This is not necessary for genomic prediction for which we also observed moderate cross-validated prediction abilities of 0.51 and 0.58 for two- and three-way hybrids, respectively. This exemplifies the potential of genomic prediction in hybrid barley. Interestingly, prediction ability using the two-way hybrids as training population and the three-way hybrids as test population or vice versa was low, presumably, because of the different genetic makeup of the parental source populations. Consequently, further research is needed to optimize genomic prediction approaches combining different source populations in barley.

Genomic prediction of host resistance to sea lice in farmed Atlantic salmon populations.

Background Sea lice have significant negative economic and welfare impacts on marine Atlantic salmon farming. Since host resistance to sea lice has a substantial genetic component, selective breeding can contribute to control of lice. Genomic selection uses genome-wide marker information to predict breeding values, and can achieve markedly higher accuracy than pedigree-based methods. Our aim was to assess the genetic architecture of host resistance to sea lice, and test the utility of genomic prediction of breeding values. Individual lice counts were measured in challenge experiments using two large Atlantic salmon post-smolt populations from a commercial breeding programme, which had genotypes for ~33 K single nucleotide polymorphisms (SNPs). The specific objectives were to: (i) estimate the heritability of host resistance; (ii) assess its genetic architecture by performing a genome-wide association study (GWAS); (iii) assess the accuracy of predicted breeding values using varying SNP densities (0.5 to 33 K) and compare it to that of pedigree-based prediction; and (iv) evaluate the accuracy of prediction in closely and distantly related animals.ResultsHeritability of host resistance was significant (0.22 to 0.33) in both populations using either pedigree or genomic relationship matrices. The GWAS suggested that lice resistance is a polygenic trait, and no genome-wide significant quantitative trait loci were identified. Based on cross-validation analysis, genomic predictions were more accurate than pedigree-based predictions for both populations. Although prediction accuracies were highest when closely-related animals were used in the training and validation sets, the benefit of having genomic-versus pedigree-based predictions within a population increased as the relationships between training and validation sets decreased. Prediction accuracy reached an asymptote with a SNP density of ~5 K within populations, although higher SNP density was advantageous for cross-population prediction.ConclusionsHost resistance to sea lice in farmed Atlantic salmon has a significant genetic component. Phenotypes relating to host resistance can be predicted with moderate to high accuracy within populations, with a major advantage of genomic over pedigree-based methods, even at relatively sparse SNP densities. Prediction accuracies across populations were low, but improved with higher marker densities. Genomic selection can contribute to lice control in salmon farming.Electronic supplementary materialThe online version of this article (doi:10.1186/s12711-016-0226-9) contains supplementary material, which is available to authorized users.

DNA marker-assisted evaluation of fruit acidity in diverse peach (Prunus persica) germplasm

Fruit acidity is a major determinant of consumer-perceived fruit quality in peach. The non-acid peaches are preferred in the market and this trait is usually selected in commercial breeding programs. A major gene (D/d) located on chromosome 5 of peach has been described for this character, where the non-acid character is determined by the dominant D allele. The corresponding physical location estimated through linkage analysis is 0.9 Mb of the chromosome 5. In our study, we identified a SNP from re-sequencing 129 varieties through genome-wide association studies, and then genotyped a collection of 436 varieties on the Sequenom MassArray platform to verify the single nucleotide polymorphism (SNP) marker for this character. Two hundred and twelve accessions from 224 accessions tasting acid are TT. Two hundred accessions from 212 accessions tasting non-acid are TC or CC. The accuracy rate was 94.5 %. Based on the SNP marker, we also designed primers used for PCR to identify non-acid peaches. This approach was validated on 169 cultivars and 84 offspring. Data were always consistent and 160 cultivars (94.7 %) and 80 offspring (95.2 %) fit the expectations. These three methods of selecting non-acid plants are convenient and readily useful for peach molecular assisted selection.

Genetic diversity analysis of two commercial breeds of pigs using genomic and pedigree data.

BackgroundGenetic improvement in livestock populations can be achieved without significantly affecting genetic diversity if mating systems and selection decisions take genetic relationships among individuals into consideration. The objective of this study was to examine the genetic diversity of two commercial breeds of pigs. Genotypes from 1168 Landrace (LA) and 1094 Large White (LW) animals from a commercial breeding program in Brazil were obtained using the Illumina PorcineSNP60 Beadchip. Inbreeding estimates based on pedigree (Fx) and genomic information using runs of homozygosity (FROH) and the single nucleotide polymorphisms (SNP) by SNP inbreeding coefficient (FSNP) were obtained. Linkage disequilibrium (LD), correlation of linkage phase (r) and effective population size (Ne) were also estimated.ResultsEstimates of inbreeding obtained with pedigree information were lower than those obtained with genomic data in both breeds. We observed that the extent of LD was slightly larger at shorter distances between SNPs in the LW population than in the LA population, which indicates that the LW population was derived from a smaller Ne. Estimates of Ne based on genomic data were equal to 53 and 40 for the current populations of LA and LW, respectively. The correlation of linkage phase between the two breeds was equal to 0.77 at distances up to 50 kb, which suggests that genome-wide association and selection should be performed within breed. Although selection intensities have been stronger in the LA breed than in the LW breed, levels of genomic and pedigree inbreeding were lower for the LA than for the LW breed.ConclusionsThe use of genomic data to evaluate population diversity in livestock animals can provide new and more precise insights about the effects of intense selection for production traits. Resulting information and knowledge can be used to effectively increase response to selection by appropriately managing the rate of inbreeding, minimizing negative effects of inbreeding depression and therefore maintaining desirable levels of genetic diversity.

Genetic Gain and Inbreeding from Genomic Selection in a Simulated Commercial Breeding Program for Perennial Ryegrass.

Genomic selection (GS) provides an attractive option for accelerating genetic gain in perennial ryegrass () improvement given the long cycle times of most current breeding programs. The present study used simulation to investigate the level of genetic gain and inbreeding obtained from GS breeding strategies compared with traditional breeding strategies for key traits (persistency, yield, and flowering time). Base population genomes were simulated through random mating for 60,000 generations at an effective population size of 10,000. The degree of linkage disequilibrium (LD) in the resulting population was compared with that obtained from empirical studies. Initial parental varieties were simulated to match diversity of current commercial cultivars. Genomic selection was designed to fit into a company breeding program at two selection points in the breeding cycle (spaced plants and miniplot). Genomic estimated breeding values (GEBVs) for productivity traits were trained with phenotypes and genotypes from plots. Accuracy of GEBVs was 0.24 for persistency and 0.36 for yield for single plants, while for plots it was lower (0.17 and 0.19, respectively). Higher accuracy of GEBVs was obtained for flowering time (up to 0.7), partially as a result of the larger reference population size that was available from the clonal row stage. The availability of GEBVs permit a 4-yr reduction in cycle time, which led to at least a doubling and trebling genetic gain for persistency and yield, respectively, than the traditional program. However, a higher rate of inbreeding per cycle among varieties was also observed for the GS strategy.

Exploring almond genetic variability useful for peach improvement: mapping major genes and QTLs in two interspecific almond × peach populations

Genetic analysis of a diverse set of 42 traits for flower (5), phenology (9), fruit quality (19), leaf (8) and disease resistance (1) was carried out in two interspecific almond × peach populations, an F2 (T × E) and a BC1 (T1E), from the cross between ‘Texas’ almond and ‘Earlygold’ peach. Traits related to flower, phenology, fruit quality, leaf morphology and resistance to powdery mildew were phenotyped over 3 years in two locations and studied for co-segregation with a large set of SNP and SSR markers. Three maps were used, one for the T × E and two for the T1E (T1E and E) population. Nine major genes were identified and mapped: anther color (Ag/ag and Ag2/ag2), flower color (Fc2/fc2), maturity date (MD/md), almond fruit type (almond vs. peach; Alf/alf), juiciness (Jui/jui), blood flesh (DBF2/dbf2), powdery mildew resistance (Vr3) and flower type (showy/non-showy; Sh/sh). These genes were often located in genome positions different from those for major genes for similar traits mapped before. Two of them explain fundamental aspects that define the fruit of peach with respect to that of almond: Alf and Jui, for its thick and juicy mesocarp, respectively. The genetics of quantitative traits was studied, and 32 QTLs were detected, with consistent behavior over the years. New alleles identified from almond for important traits such as red skin color, blood flesh, fruit weight and powdery mildew resistance may prove useful for the introduction of new variability into the peach gene pool used in commercial breeding programs.

Bridging the gap between ideotype and genotype: Challenges and prospects for modelling as exemplified by the case of adapting wheat (Triticum aestivum L.) phenology to climate change in France

Simulations using crop models can assist designing ideotypes for current and future agricultural conditions. This approach consists in running simulations for different “in silico genotypes” obtained by varying the most sensitive genotypic parameters of these models, and analyzing results obtained for different environments, so as to identify the best genotypes for a target population of environments. However, this approach has rarely been used to guide commercial breeding programs so far. In this paper, we attempt to address some of the gaps yet to be filled before this kind of approach can be implemented, and identify some remaining issues that should be addressed in future research. Our focus is on optimizing wheat phenology, integrating simulations from a modified version of the ARCWHEAT model of wheat growth stages with available knowledge on the genetic control of wheat phenology obtained via molecular markers. Based on simulations, stem extension could be advanced by 10 days in 2025–2049 without increasing frost risks, thus opening up opportunities for lengthening the rapid growth period. Analysis of the current genetic variability for major phenology genes in French elite varieties, showed that the insensitive PpdD1—spring Vrn3 allele combination appears undesirable and current genotypes with early stem extensions are unstable (i.e. show a strong response to temperature and can start the stem extension very early in case of mild winter temperatures). We finally use a case study on gene-based modelling of wheat phenology in France to illustrate how it can be used to dissect the genetic basis of the quantitative nature of the three components of earliness, beyond the effects of major genes. We identify the need to link the variability for optimized model parameters and the allelic variations at the gene level as a critical step of this type of approach.

Genomic selection in a commercial winter wheat population.

Genomic selection models can be trained using historical data and filtering genotypes based on phenotyping intensity and reliability criterion are able to increase the prediction ability. We implemented genomic selection based on a large commercial population incorporating 2325 European winter wheat lines. Our objectives were (1) to study whether modeling epistasis besides additive genetic effects results in enhancement on prediction ability of genomic selection, (2) to assess prediction ability when training population comprised historical or less-intensively phenotyped lines, and (3) to explore the prediction ability in subpopulations selected based on the reliability criterion. We found a 5 % increase in prediction ability when shifting from additive to additive plus epistatic effects models. In addition, only a marginal loss from 0.65 to 0.50 in accuracy was observed using the data collected from 1 year to predict genotypes of the following year, revealing that stable genomic selection models can be accurately calibrated to predict subsequent breeding stages. Moreover, prediction ability was maximized when the genotypes evaluated in a single location were excluded from the training set but subsequently decreased again when the phenotyping intensity was increased above two locations, suggesting that the update of the training population should be performed considering all the selected genotypes but excluding those evaluated in a single location. The genomic prediction ability was substantially higher in subpopulations selected based on the reliability criterion, indicating that phenotypic selection for highly reliable individuals could be directly replaced by applying genomic selection to them. We empirically conclude that there is a high potential to assist commercial wheat breeding programs employing genomic selection approaches.

Low-cost automated biochemical phenotyping for optimised nutrient quality components in ryegrass breeding

Quantification of forage quality is essential for the identification of elite genotypes in forage grass breeding. Perennial ryegrass is the most important temperate species for global pastoral agriculture. However, the protein content of ryegrass generally exceeds the requirements of a grazing animal, and the ratio of water soluble carbohydrate (WSC) to protein is too low for efficient protein utilisation. This results in poor nitrogen use efficiency (NUE) in the farming system by livestock, and hence limits optimal animal production. New ryegrass cultivars with optimised WSC and protein content are desirable for farming efficiencies. Several methods are available for quantification of WSC and plant protein (such as near-infrared spectroscopy [NIRS] and high performance liquid chromatography [HPLC]). However, such methods are labour-intensive, low-throughput and cost-prohibitive for commercial breeding programs, which typically need to assess thousands of samples annually. An accurate high-throughput micro-plate-based protocol has been developed and validated, with the ability to simultaneously process and quantify WSC and plant protein with a high level of automation, and an increase in sample processing of ~10-fold compared with commonly-used methods, along with a 3-fold cost reduction. As WSC and protein are extracted simultaneously and quantified within micro-plates, consumable costs are minimised with optimal reagent use efficiency, resulting in a low per sample cost that is suitable for commercial pasture breeding companies. This is the first demonstration of a forage quality phenotyping protocol suitable for broad-scale application, and will allow breeders to select elite genotypes based not only on visual assessment but also on WSC : protein ratios for improved ruminant nutrition.

Prediction of malting quality traits in barley based on genome-wide marker data to assess the potential of genomic selection

Genomic prediction of malting quality traits in barley shows the potential of applying genomic selection to improve selection for malting quality and speed up the breeding process. Genomic selection has been applied to various plant species, mostly for yield or yield-related traits such as grain dry matter yield or thousand kernel weight, and improvement of resistances against diseases. Quality traits have not been the main scope of analysis for genomic selection, but have rather been addressed by marker-assisted selection. In this study, the potential to apply genomic selection to twelve malting quality traits in two commercial breeding programs of spring and winter barley (Hordeum vulgare L.) was assessed. Phenotypic means were calculated combining multilocational field trial data from 3 or 4 years, depending on the trait investigated. Three to five locations were available in each of these years. Heritabilities for malting traits ranged between 0.50 and 0.98. Predictive abilities (PA), as derived from cross validation, ranged between 0.14 to 0.58 for spring barley and 0.40-0.80 for winter barley. Small training sets were shown to be sufficient to obtain useful PAs, possibly due to the narrow genetic base in this breeding material. Deployment of genomic selection in malting barley breeding clearly has the potential to reduce cost intensive phenotyping for quality traits, increase selection intensity and to shorten breeding cycles.

Methods of inoculation and evaluation of Erwinia psidii in eucalypt

SummaryThe dieback and wilting caused by Erwinia psidii are emerging eucalypt diseases that have been observed since 2014 in the south and central‐south regions of Brazil. Field observations have shown variability in disease severity resistance among Eucalyptus spp. clones and species. It is hypothesized that this variability is due to genetic resistance. To confirm this hypothesis, inoculations in genetically distinct eucalypt plants are necessary. However, lack of an inoculation method and disease assessment makes difficult to select resistant genotypes for use in commercial plantations or genetic breeding programmes. Three inoculation methods were tested on eight clones of Eucalyptus spp. Among them, inoculum deposition with bacteria‐impregnated toothpick on the axillary buds was the simplest and most effective, capable to reproduce the disease symptoms observed under conditions of natural infection. We also developed a rating scale for disease assessment. Among eight clones tested, only Clone 1 (Eucalyptus saligna) and Clone 2 (Eucalyptus urophylla) were resistant.

Accuracy and responses of genomic selection on key traits in apple breeding.

The application of genomic selection in fruit tree crops is expected to enhance breeding efficiency by increasing prediction accuracy, increasing selection intensity and decreasing generation interval. The objectives of this study were to assess the accuracy of prediction and selection response in commercial apple breeding programmes for key traits. The training population comprised 977 individuals derived from 20 pedigreed full-sib families. Historic phenotypic data were available on 10 traits related to productivity and fruit external appearance and genotypic data for 7829 SNPs obtained with an Illumina 20K SNP array. From these data, a genome-wide prediction model was built and subsequently used to calculate genomic breeding values of five application full-sib families. The application families had genotypes at 364 SNPs from a dedicated 512 SNP array, and these genotypic data were extended to the high-density level by imputation. These five families were phenotyped for 1 year and their phenotypes were compared to the predicted breeding values. Accuracy of genomic prediction across the 10 traits reached a maximum value of 0.5 and had a median value of 0.19. The accuracies were strongly affected by the phenotypic distribution and heritability of traits. In the largest family, significant selection response was observed for traits with high heritability and symmetric phenotypic distribution. Traits that showed non-significant response often had reduced and skewed phenotypic variation or low heritability. Among the five application families the accuracies were uncorrelated to the degree of relatedness to the training population. The results underline the potential of genomic prediction to accelerate breeding progress in outbred fruit tree crops that still need to overcome long generation intervals and extensive phenotyping costs.

Molecular marker-directed development of a novel cytoplasmic male sterile line in rice

In response to the challenge of food security in the new century, heterosis exploitation is being intensified as an effective way to increase grain yield of rice. Thus, breeding of new cytoplasmic male sterility (CMS) is necessary so as to prevent homog- enization of hybrid rice in commercial breeding programs. As the rapid development of molecular biology, molecular marker based selection can not only increase the efficiency and accuracy for breeding, but also provide us the possibility to create new CMS by genotypic identification. In this study, we devel- opedanovel CMSricebyscreeningricemalesterility- inducing cytoplasm and maintainer candidates using mitotype-specific and nuclear molecular markers, respectively. Field trials reveal that the newly bred CMS line has good general combining ability and special combining abilityfor generation of hybrid rice, which means that the molecular marker system provides us an efficient and practicable approach for development of new CMS in rice breeding programs.