New sources of lentil germplasm for aluminium toxicity tolerance identified by high throughput hydroponic screening.

Aluminium (Al) toxicity in acid soils inhibits root elongation and development causing reduced water and nutrient uptake by the root system, which ultimately reduces the crop yield. This study established a high throughput hydroponics screening method and identified Al toxicity tolerant accessions from a set of putative acid tolerant lentil accessions. Four-day old lentil seedlings were screened at 5 µM Al (pH 4.5) for three days in hydroponics. Measured pre and post treatment root length was used to calculate the change in root length (ΔRL) and relative root growth (RRG%). A subset of 15 selected accessions were used for acid soil Al screening, and histochemical and biochemical analyses. Al treatment significantly reduced the ΔRL with an average of 32.3% reduction observed compared to the control. Approximately 1/4 of the focused identification of germplasm strategy accessions showed higher RRG% than the known tolerant line ILL6002 which has the RRG% of 37.9. Very tolerant accessions with RRG% of > 52% were observed in 5.4% of the total accessions. A selection index calculated based on all root traits in acid soil screening was highest in AGG70137 (636.7) whereas it was lowest in Precoz (76.3). All histochemical and biochemical analyses supported the hydroponic results as Northfield, AGG70137, AGG70561 and AGG70281 showed consistent good performance. The identified new sources of Al tolerant lentil germplasm can be used to breed new Al toxicity tolerant lentil varieties. The established high throughput hydroponic method can be routinely used for screening lentil breeding populations for Al toxicity tolerance. Future recommendations could include evaluation of the yield potential of the selected subset of accessions under acid soil field conditions, and the screening of a wider range of landrace accessions originating from areas with Al toxic acid soils.

Improving the analysis of low heritability complex traits for enhanced genetic gain in potato.

KEY MESSAGE: Best linear unbiased prediction (BLUP), which uses pedigree to estimate breeding values, can result in increased genetic gains for low heritability traits in autotetraploid potato. Conventional potato breeding strategies, based on outcrossing followed by phenotypic recurrent selection over a number of generations, can result in slow but steady improvements of traits with moderate to high heritability. However, faster gains, particularly for low heritability traits, could be made by selection on estimated breeding values (EBVs) calculated using more complete pedigree information in best linear unbiased prediction (BLUP) analysis. One complication in applying BLUP predictions of breeding value to potato breeding programs is the autotetraploid inheritance pattern of this species. Here we have used a large pedigree, dating back to 1908, to estimate heritability for nine key traits for potato breeding, modelling autotetraploid inheritance. We estimate the proportion of double reduction in potatoes from our data, and across traits, to be in the order of 10 %. Estimates of heritability ranged from 0.21 for breeder's visual preference, 0.58 for tuber yield, to 0.83 for plant maturity. Using the accuracies of the EBVs determined by cross generational validation, we model the genetic gain that could be achieved by selection of genotypes for breeding on BLUP EBVs and demonstrate that gains can be greater than in conventional schemes.

Improving breeding efficiency in potato using molecular and quantitative genetics.

KEY MESSAGE: Potatoes are highly heterozygous and the conventional breeding of superior germplasm is challenging, but use of a combination of MAS and EBVs can accelerate genetic gain. Cultivated potatoes are highly heterozygous due to their outbreeding nature, and suffer acute inbreeding depression. Modern potato cultivars also exhibit tetrasomic inheritance. Due to this genetic heterogeneity, the large number of target traits and the specific requirements of commercial cultivars, potato breeding is challenging. A conventional breeding strategy applies phenotypic recurrent selection over a number of generations, a process which can take over 10 years. Recently, major advances in genetics and molecular biology have provided breeders with molecular tools to accelerate gains for some traits. Marker-assisted selection (MAS) can be effectively used for the identification of major genes and quantitative trait loci that exhibit large effects. There are also a number of complex traits of interest, such as yield, that are influenced by a large number of genes of individual small effect where MAS will be difficult to deploy. Progeny testing and the use of pedigree in the analysis can provide effective identification of the superior genetic factors that underpin these complex traits. Recently, it has been shown that estimated breeding values (EBVs) can be developed for complex potato traits. Using a combination of MAS and EBVs for simple and complex traits can lead to a significant reduction in the length of the breeding cycle for the identification of superior germplasm.

Assessment of genetic variation within a global collection of lentil (Lens culinaris Medik.) cultivars and landraces using SNP markers.

BACKGROUND: Lentil is a self-pollinated annual diploid (2n = 2× = 14) crop with a restricted history of genetic improvement through breeding, particularly when compared to cereal crops. This limited breeding has probably contributed to the narrow genetic base of local cultivars, and a corresponding potential to continue yield increases and stability. Therefore, knowledge of genetic variation and relationships between populations is important for understanding of available genetic variability and its potential for use in breeding programs. Single nucleotide polymorphism (SNP) markers provide a method for rapid automated genotyping and subsequent data analysis over large numbers of samples, allowing assessment of genetic relationships between genotypes. RESULTS: In order to investigate levels of genetic diversity within lentil germplasm, 505 cultivars and landraces were genotyped with 384 genome-wide distributed SNP markers, of which 266 (69.2%) obtained successful amplification and detected polymorphisms. Gene diversity and PIC values varied between 0.108-0.5 and 0.102-0.375, with averages of 0.419 and 0.328, respectively. On the basis of clarity and interest to lentil breeders, the genetic structure of the germplasm collection was analysed separately for cultivars and landraces. A neighbour-joining (NJ) dendrogram was constructed for commercial cultivars, in which lentil cultivars were sorted into three major groups (G-I, G-II and G-III). These results were further supported by principal coordinate analysis (PCoA) and STRUCTURE, from which three clear clusters were defined based on differences in geographical location. In the case of landraces, a weak correlation between geographical origin and genetic relationships was observed. The landraces from the Mediterranean region, predominantly Greece and Turkey, revealed very high levels of genetic diversity. CONCLUSIONS: Lentil cultivars revealed clear clustering based on geographical origin, but much more limited correlation between geographic origin and genetic diversity was observed for landraces. These results suggest that selection of divergent parental genotypes for breeding should be made actively on the basis of systematic assessment of genetic distance between genotypes, rather than passively based on geographical distance.

Making the most of all data: Combining non-genotyped and genotyped potato individuals with HBLUP.

Using genomic information to predict phenotypes can improve the accuracy of estimated breeding values and can potentially increase genetic gain over conventional breeding. In this study, we investigated the prediction accuracies achieved by best linear unbiased prediction (BLUP) for nine potato phenotypic traits using three types of relationship matrices pedigree ABLUP, genomic GBLUP, and a hybrid matrix (H) combining pedigree and genomic information (HBLUP). Deep pedigree information was available for >3000 different potato breeding clones evaluated over four years. Genomic relationships were estimated from >180,000 informative SNPs generated using a genotyping-by-sequencing transcriptome (GBS-t) protocol for 168 cultivars, many of which were parents of clones. Two validation scenarios were implemented, namely "Genotyped Cultivars Validation" (a subset of genotyped lines as validation set) and "Non-genotyped 2009 Progenies Validation". Most of the traits showed moderate to high narrow sense heritabilities (range 0.22-0.72). In the Genotyped Cultivars Validation, HBLUP outperformed ABLUP on prediction accuracies for all traits except early blight, and outperformed GBLUP for most of the traits except tuber shape, tuber eye depth and boil after-cooking darkening. This is evidence that the in-depth relationship within the H matrix could potentially result in better prediction accuracy in comparison to using A or G matrix individually. The prediction accuracies of the Non-genotyped 2009 Progenies Validation were comparable between ABLUP and HBLUP, varying from 0.17-0.70 and 0.18-0.69, respectively. Better prediction accuracy and less bias in prediction using HBLUP is of practical utility to breeders as all breeding material is ranked on the same scale leading to improved selection decisions. In addition, our approach provides an economical alternative to utilize historic breeding data with current genotyped individuals in implementing genomic selection.

Screening for Resistance to PVY in Australian Potato Germplasm.

Potatoes are an important human food crop, but have a number of yield limiting factors, including disease susceptibility. Potato virus Y (PVY) is found worldwide, and is one of the main virus problems for potato growers. PVY is transmitted by aphids and mechanically by machinery, tools and people, and symptoms are variable across cultivars and strains, including being symptomless in some cultivars. Therefore, breeding resistant cultivars is the best way to control this virus. This study phenotypically screened 74 of the main commercial cultivars and a few other select cultivars grown in Australia, in order to identify sources of resistance to PVY. The cultivars were screened against PVYO and PVYNTN, with 23 out of 71 resistant to PVYO and 13 out of 74 resistant to PVYNTN, and all these 13 were resistant to both strains. When the phenotypic screening was compared to the results listed on the European Cultivated Potato Database, the majority of results were found to be consistent. We then evaluated three molecular markers RYSC3, M45, and STM0003 for the extreme resistance genes Ryadg and Rysto, to validate the usefulness of the markers for marker-assisted selection (MAS) on Australian germplasm. The degree of correlation between the resistance phenotypes and the RYSC3, M45, and STM0003 markers for Ryadg and Rysto conferred PVY resistance was determined. Three cultivars amplified the RYSC3 marker, while the M45 marker amplified the same 3 and an additional 9. Of the 12 cultivars, 11 phenotyped as resistant, but 1 was susceptible. The STM0003 marker was amplified from only 2 cultivars that both had resistant phenotypes. The RYSC3, M45, and STM0003 markers were therefore able to identify all the 13 cultivars that were resistant to both strains of PVY. Therefore, these markers will enable the identification of genotypes with resistance to PVY, and enable PVY resistant parents to be used for the development of superior progeny; these genetic markers can be used for MAS in the Australian potato breeding program.

Automated phenotyping for early vigour of field pea seedlings in controlled environment by colour imaging technology.

Early vigour of seedlings is a beneficial trait of field pea (Pisum sativum L.) that contributes to weed control, water use efficiency and is likely to contribute to yield under certain environments. Although breeding is considered the most effective approach to improve early vigour of field pea, the absence of a robust and high-throughput phenotyping tool to dissect this complex trait is currently a major obstacle of genetic improvement programs to address this issue. To develop this tool, separate trials on 44 genetically diverse field pea genotypes were conducted in the automated plant phenotyping platform of Plant Phenomics Victoria, Horsham and in the field, respectively. High correlation between estimated plant parameters derived from the automated phenotyping platform and important early vigour traits such as shoot biomass, leaf area and plant height indicated that the derived plant parameters can be used to predict vigour traits in field pea seedlings. Plant growth analysis demonstrated that the "broken-stick" model fitted well with the growth pattern of all field pea genotypes and can be used to determine the linear growth phase. Further analysis suggested that the estimated plant parameters collected at the linear growth phase can effectively differentiate early vigour across field pea genotypes. High correlation between normalised difference vegetation indices captured from the field trial and estimated shoot biomass and top-view area confirmed the consistent performance of early vigour field pea genotypes under controlled and field environments. Overall, our results demonstrated that this robust screening tool is highly applicable and will enable breeding programs to rapidly identify early vigour traits and utilise germplasm to contribute to the genetic improvement of field peas.

Genomic Prediction Using Prior Quantitative Trait Loci Information Reveals a Large Reservoir of Underutilised Blackleg Resistance in Diverse Canola (Brassica napus L.) Lines.

Genomic prediction is becoming a popular plant breeding method to predict the genetic merit of lines. While some genomic prediction results have been reported in canola, none have been evaluated for blackleg disease. Here, we report genomic prediction for seedling emergence, survival rate, and internal infection), using 532 Spring and Winter canola lines. These lines were phenotyped in two replicated blackleg disease nurseries grown at Wickliffe and Green Lake, Victoria, Australia. A transcriptome genotyping-by-sequencing approach revealed 98,054 single nucleotide polymorphisms (SNPs) after quality control. We assessed various genomic prediction scenarios based on Genomic Best Linear Unbiased Prediction (GBLUP), BayesR and BayesRC, which can make use of prior quantitative trait loci information, via cross-validation. Clustering based on genomic relationships showed that Winter and Spring lines were genetically distinct, indicating limited gene flow between sets. Genetic correlations within traits between Spring and Winter lines ranged from 0.68 and 0.90 (mean = 0.76). Based on GBLUP in the whole population, moderate to high genomic prediction accuracies were achieved within environments (0.35-0.74) and were reduced across environments (0.28-0.58). Prediction accuracy within the Spring set ranged from 0.30-0.69, and from 0.19-0.71 within the Winter set. The BayesR model resulted in slightly lower accuracy to GBLUP. The proportion of genetic variance explained by known blackleg quantitative trait loci (QTL) was < 30%, indicating that there is a large reservoir of genetic variation in blackleg traits that remains to be discovered, but can be captured with genomic prediction. However, providing prior information of known QTL in the BayesRC method resulted in an increased prediction accuracy for survival and internal infection, particularly with Spring lines. Overall, these promising results indicate that genomic prediction will be a valuable tool to make use of all genetic variation to improve blackleg resistance in canola.

A multiplex PCR for rapid identification of Brassica species in the triangle of U.

BACKGROUND: Within the Brassicaceae, six species from the genus Brassica are widely cultivated throughout the world as oilseed, condiment, fodder or vegetable crops. The genetic relationships among the six Brassica species are described by U's triangle model. Extensive shared traits and diverse morphotypes among Brassica species make identification and classification based on phenotypic data alone challenging and unreliable, especially when dealing with large germplasm collections. Consequently, a major issue for genebank collections is ensuring the correct identification of species. Molecular genotyping based on simple sequence repeat (SSR) marker sequencing or the Illumina Infinium Brassica napus 60K single nucleotide polymorphism (SNP) array has been used to identify species and assess genetic diversity of Brassica collections. However, these methods are technically challenging, expensive and time-consuming, making them unsuitable for routine or rapid screening of Brassica accessions for germplasm management. A cheaper, faster and simpler method for Brassica species identification is described here. RESULTS: A multiplex polymerase chain reaction (MPCR) consisting of new and existing primers specific to the Brassica A, B and C genomes was able to reliably distinguish all six Brassica species in the triangle of U with 16 control samples of known species identity. Further validation against 120 Brassica accessions previously genotyped showed that the MPCR is highly accurate and comparable to more advanced techniques such as SSR marker sequencing or the Illumina Infinium B. napus 60K SNP array. In addition, the MPCR was sensitive enough to detect seed contaminations in pooled seed samples of Brassica accessions. CONCLUSION: A cheap and fast multiplex PCR assay for identification of Brassica species in the triangle of U was developed and validated in this study. The MPCR assay can be readily implemented in any basic molecular laboratory and should prove useful for the management of Brassica germplasm collections in genebanks.

Pterostilbene Is a Potential Candidate for Control of Blackleg in Canola.

Two stilbenes, resveratrol and pterostilbene, exhibit antifungal activity against Leptosphaeria maculans, the fungal pathogen responsible for blackleg (stem canker) in canola (Brassica napus). In vitro studies on the effect of these stilbenes on L. maculans mycelial growth and conidia germination showed that pterostilbene is a potent fungicide and sporicide, but resveratrol only exerted minor inhibition on L. maculans. Cell viability of hyphae cultures was markedly reduced by pterostilbene and SYTOX green staining showed that cell membrane integrity was compromised. We demonstrate that pterostilbene exerts fungicidal activity across 10 different L. maculans isolates and the compound confers protection to the blackleg-susceptible canola cv. Westar seedlings. The potential of pterostilbene as a control agent against blackleg in canola is discussed.

Improving Genetic Gain with Genomic Selection in Autotetraploid Potato.

Potato ( L.) breeders consider a large number of traits during cultivar development and progress in conventional breeding can be slow. There is accumulating evidence that some of these traits, such as yield, are affected by a large number of genes with small individual effects. Recently, significant efforts have been applied to the development of genomic resources to improve potato breeding, culminating in a draft genome sequence and the identification of a large number of single nucleotide polymorphisms (SNPs). The availability of these genome-wide SNPs is a prerequisite for implementing genomic selection for improvement of polygenic traits such as yield. In this review, we investigate opportunities for the application of genomic selection to potato, including novel breeding program designs. We have considered a number of factors that will influence this process, including the autotetraploid and heterozygous genetic nature of potato, the rate of decay of linkage disequilibrium, the number of required markers, the design of a reference population, and trait heritability. Based on estimates of the effective population size derived from a potato breeding program, we have calculated the expected accuracy of genomic selection for four key traits of varying heritability and propose that it will be reasonably accurate. We compared the expected genetic gain from genomic selection with the expected gain from phenotypic and pedigree selection, and found that genetic gain can be substantially improved by using genomic selection.

SNP-Based Linkage Mapping for Validation of QTLs for Resistance to Ascochyta Blight in Lentil.

Lentil (Lens culinaris Medik.) is a self-pollinating, diploid, annual, cool-season, food legume crop that is cultivated throughout the world. Ascochyta blight (AB), caused by Ascochyta lentis Vassilievsky, is an economically important and widespread disease of lentil. Development of cultivars with high levels of durable resistance provides an environmentally acceptable and economically feasible method for AB control. A detailed understanding of the genetic basis of AB resistance is hence highly desirable, in order to obtain insight into the number and influence of resistance genes. Genetic linkage maps based on single nucleotide polymorphisms (SNP) and simple sequence repeat (SSR) markers have been developed from three recombinant inbred line (RIL) populations. The IH × NF map contained 460 loci across 1461.6 cM, while the IH × DIG map contained 329 loci across 1302.5 cM and the third map, NF × DIG contained 330 loci across 1914.1 cM. Data from these maps were combined with a map from a previously published study through use of bridging markers to generate a consensus linkage map containing 689 loci distributed across seven linkage groups (LGs), with a cumulative length of 2429.61 cM at an average density of one marker per 3.5 cM. Trait dissection of AB resistance was performed for the RIL populations, identifying totals of two and three quantitative trait loci (QTLs) explaining 52 and 69% of phenotypic variation for resistance to infection in the IH × DIG and IH × NF populations, respectively. Presence of common markers in the vicinity of the AB_IH1- and AB_IH2.1/AB_IH2.2-containing regions on both maps supports the inference that a common genomic region is responsible for conferring resistance and is associated with the resistant parent, Indianhead. The third QTL was derived from Northfield. Evaluation of markers associated with AB resistance across a diverse lentil germplasm panel revealed that the identity of alleles associated with AB_IH1 predicted the phenotypic responses with high levels of accuracy (~86%), and therefore have the potential to be widely adopted in lentil breeding programs. The availability of RIL-based maps, a consensus map, and validated markers linked to AB resistance provide important resources for lentil improvement.

Validation of molecular markers associated with boron tolerance, powdery mildew resistance and salinity tolerance in field peas.

Field pea (Pisum sativum L.) is an important grain legume consumed both as human food and animal feed. However, productivity in low rainfall regions can be significantly reduced by inferior soils containing high levels of boron and/or salinity. Furthermore, powdery mildew (PM) (Erysiphe pisi) disease also causes significant yield loss in warmer regions. Breeding for tolerance to these abiotic and biotic stresses are major aims for pea breeding programs and the application of molecular markers for these traits could greatly assist in developing improved germplasm at a faster rate. The current study reports the evaluation of a near diagnostic marker, PsMlo, associated with PM resistance and boron (B) tolerance as well as linked markers associated with salinity tolerance across a diverse set of pea germplasm. The PsMlo1 marker predicted the PM and B phenotypic responses with high levels of accuracy (>80%) across a wide range of field pea genotypes, hence offers the potential to be widely adapted in pea breeding programs. In contrast, linked markers for salinity tolerance were population specific; therefore, application of these markers would be suitable to relevant crosses within the program. Our results also suggest that there are possible new sources of salt tolerance present in field pea germplasm that could be further exploited.