The analysis of large scale data taken from the world groundnut (Arachis hypogaea L.) germplasm collection I. Two-way quantitative data

Data associated with germplasm collections are typically large and multivariate with a considerable number of descriptors measured on each of many accessions. Pattern analysis methods of clustering and ordination have been identified as techniques for statistically evaluating the available diversity in germplasm data. While used in many studies, the approaches have not dealt explicitly with the computational consequences of large data sets (i.e. greater than 5000 accessions). To consider the application of these techniques to germplasm evaluation data, 11328 accessions of groundnut (Arachis hypogaea L) from the International Research Institute for the Semi-Arid Tropics, Andhra Pradesh, India were examined. Data for nine quantitative descriptors measured in the rainy and post-rainy growing seasons were used. The ordination technique of principal component analysis was used to reduce the dimensionality of the germplasm data. The identification of phenotypically similar groups of accessions within large scale data via the computationally intensive hierarchical clustering techniques was not feasible and non-hierarchical techniques had to be used. Finite mixture models that maximise the likelihood of an accession belonging to a cluster were used to cluster the accessions in this collection. The patterns of response for the different growing seasons were found to be highly correlated. However, in relating the results to passport and other characterisation and evaluation descriptors, the observed patterns did not appear to be related to taxonomy or any other well known characteristics of groundnut.

The analysis of large scale data taken from the world groundnut (Arachis hypogaea L.) germplasm collection. II. Two-way data with mixed data types

As a sequel to a paper that dealt with the analysis of two-way quantitative data in large germplasm collections, this paper presents analytical methods appropriate for two-way data matrices consisting of mixed data types, namely, ordered multicategory and quantitative data types. While various pattern analysis techniques have been identified as suitable for analysis of the mixed data types which occur in germplasm collections, the clustering and ordination methods used often can not deal explicitly with the computational consequences of large data sets (i.e. greater than 5000 accessions) with incomplete information. However, it is shown that the ordination technique of principal component analysis and the mixture maximum likelihood method of clustering can be employed to achieve such analyses. Germplasm evaluation data for 11436 accessions of groundnut (Arachis hypogaea L.) from the International Research Institute of the Semi-Arid Tropics, Andhra Pradesh, India were examined. Data for nine quantitative descriptors measured in the post-rainy season and five ordered multicategory descriptors were used. Pattern analysis results generally indicated that the accessions could be distinguished into four regions along the continuum of growth habit (or plant erectness). Interpretation of accession membership in these regions was found to be consistent with taxonomic information, such as subspecies. Each growth habit region contained accessions from three of the most common groundnut botanical varieties. This implies that within each of the habit types there is the full range of expression for the other descriptors used in the analysis. Using these types of insights, the patterns of variability in germplasm collections can provide scientists with valuable information for their plant improvement programs.

Patterns of diversity in fatty acid composition in the Australian groundnut germplasm collection

Knowledge of the amounts and types of fatty acids in groundnut oil is beneficial, particularly from a nutritional standpoint. Germplasm evaluation data for fatty acid composition on 819 accessions of groundnut (Arachis hypogaea L.) from the Australian Tropical Field Crops Genetic Resource Centre, Biloela, Queensland were examined. Data for eight quantitative fatty acid descriptors have been documented. Statistical assessment, via methods of pattern analysis, summarised and described the patterns of variation in fatty acid composition of the groundnut accessions in the Australian germplasm collection. Presentation of the results from principal components analysis and hierarchical cluster analysis using a biplot was shown to be a very useful interpretative tool. Such a biplot enables a simultaneous examination of the relationships among all the accessions and the fatty acids. Unlike that information available via database searches, the results from contribution analysis together with the biplot provide a global picture of the diversity available for use in plant breeding programs. The use of standardised data for eight fatty acids, compared to using three specific fatty acids, provided a better description of the total diversity available because it remains relevant with possible changes in the nutritional preferences for fatty acids. Fatty acid composition was found to vary in relation to the branching pattern of the accessions. This pattern is generally indicative of the botanical types of groundnuts; Virginia (alternate) compared to Spanish and Valencia (sequential) botanical types.

Outbreak of angular leaf spot, caused by Xanthomonas fragariae, in a Queensland strawberry germplasm collection.

Strawberry (Fragaria (x) ananassa) plants exhibiting leaf lesions consistent with angular leaf spot (ALS, caused by Xanthomonas fragariae Kennedy and King 1962) were identified in the Queensland strawberry germplasm at Bundeberg in May 2010. Water suspensions of bacterial ooze tested positive using a previously described primer set. However, the slow growth rate of X. fragariae and the presence of a fast-growing, non-pathogenic, undescribed Xanthomonas species presented problems that were overcome by dilution plating and DNA sequence analysis. Sequencing of the gyrB locus of putative colonies of X. fragariae indicated 100% sequence similarity to other X. fragariae isolates. A new set of diagnostic primers for X. fragariae based on the gyrB locus is presented.

Proanthocyanidin diversity in the EU 'HealthyHay' sainfoin (onobrychis viciifolia) germplasm collection

This study investigated 37 diverse sainfoin (Onobrychis viciifolia Scop.) accessions from the EU ‘HealthyHay’ germplasm collection for proanthocyanidin (PA) content and composition. Accessions displayed a wide range of differences: PA contents varied from 0.57 to 2.80 g/100 g sainfoin; the mean degree of polymerisation from 12 to 84; the proportion of prodelphinidin tannins from 53% to 95%, and the proportion of trans-flavanol units from 12% to 34%. A positive correlation was found between PA contents (thiolytic versus acid–butanol degradation; P < 0.001; R2 = 0.49). A negative correlation existed between PA content (thiolysis) and mDP (P < 0.05; R2 = −0.30), which suggested that accessions with high PA contents had smaller PA polymers. Cluster analysis revealed that European accessions clustered into two main groups: Western Europe and Eastern Europe/Asia. In addition, accessions from USA, Canada and Armenia tended to cluster together. Overall, there was broad agreement between tannin clusters and clusters that were based on morphological and agronomic characteristics.

Identification of common bean resistant sources to angular leaf spot disease in a brazilian germplasm collection.

The aim of this study was to identify sources of resistance in the germplasm collection providing information of potential sources of resistance to introduce in breeding programs.

Pattern analysis of the diversity of morphological plant attributes and herbage yield in a world collection of white clover (Trifolium repens L.) germplasm characterised in a summer moisture stress environment of Australia

Information on the variation available for different plant attributes has enabled germplasm collections to be effectively utilised in plant breeding. A world sourced collection of white clover germplasm has been developed at the White Clover Resource Centre at Glen Innes, New South Wales. This collection of 439 accessions was characterised under field conditions as a preliminary study of the genotypic variation for morphological attributes; stolon density, stolon branching, number of nodes. number of rooted nodes, stolon thickness, internode length, leaf length, plant height and plant spread, together with seasonal herbage yield. Characterisation was conducted on different batches of germplasm (subsets of accessions taken from the complete collection) over a period of five years. Inclusion of two check cultivars, Haifa and Huia, in each batch enabled adjustment of the characterisation data for year effects and attribute-by-year interaction effects. The component of variance for seasonal herbage yield among batches was large relative to that for accessions. Accession-by-experiment and accession-by-season interactions for herbage yield were not detected. Accession mean repeatability for herbage yield across seasons was intermediate (0.453). The components of genotypic variance among accessions for all attributes, except plant height, were larger than their respective standard errors. The estimates of accession mean repeatability for the attributes ranged from low (0.277 for plant height) to intermediate (0.544 for internode length). Multivariate techniques of clustering and ordination were used to investigate the diversity present among the accessions in the collection. Both cluster analysis and principal component analysis suggested that seven groups of accessions existed. It was also proposed from the pattern analysis results that accessions from a group characterised by large leaves, tall plants and thick stolons could be crossed with accessions from a group that had above average stolon density and stolon branching. This material could produce breeding populations to be used in recurrent selection for the development of white clover cultivars for dryland summer moisture stress environments in Australia. The germplasm collection was also found to be deficient in genotypes with high stolon density, high number of branches high number of rooted nodes and large leaves. This warrants addition of new germplasm accessions possessing these characteristics to the present germplasm collection.

Mixed data types and the use of pattern analysis on the Australian groundnut germplasm data

Data in germplasm collections contain a mixture of data types; binary, multistate and quantitative. Given the multivariate nature of these data, the pattern analysis methods of classification and ordination have been identified as suitable techniques for statistically evaluating the available diversity. The proximity (or resemblance) measure, which is in part the basis of the complementary nature of classification and ordination techniques, is often specific to particular data types. The use of a combined resemblance matrix has an advantage over data type specific proximity measures. This measure accommodates the different data types without manipulating them to be of a specific type. Descriptors are partitioned into their data types and an appropriate proximity measure is used on each. The separate proximity matrices, after range standardisation, are added as a weighted average and the combined resemblance matrix is then used for classification and ordination. Germplasm evaluation data for 831 accessions of groundnut (Arachis hypogaea L.) from the Australian Tropical Field Crops Genetic Resource Centre, Biloela, Queensland were examined. Data for four binary, five ordered multistate and seven quantitative descriptors have been documented. The interpretative value of different weightings - equal and unequal weighting of data types to obtain a combined resemblance matrix - was investigated by using principal co-ordinate analysis (ordination) and hierarchical cluster analysis. Equal weighting of data types was found to be more valuable for these data as the results provided a greater insight into the patterns of variability available in the Australian groundnut germplasm collection. The complementary nature of pattern analysis techniques enables plant breeders to identify relevant accessions in relation to the descriptors which distinguish amongst them. This additional information may provide plant breeders with a more defined entry point into the germplasm collection for identifying sources of variability for their plant improvement program, thus improving the utilisation of germplasm resources.

New wild Brassica oleracea L. germplasm at its western distribution limit in the Iberian Peninsula

An exploration and collection mission for wild Brassica oleracea populations was carried out in spring and summer of 2013. The aim of this collection was to expand the number of accessions of wild Brassica oleracea available for basic and applied research in plant breeding. In this paper we report a new accession of wild Brassica oleracea in an unexplored coastal area of Galicia, NW Iberian Peninsula. Details of population ecology and vegetation, soil, climate and geographic data were recorded for this population. The “Endangered” threat category for the region is proposed, and actions for in situ and ex situ conservation are proposed. Seeds will be added to the germplasm collections of University of Santiago de Compostela and Misión Biológica de Galicia (CSIC) for further research on diverse aspects of the dynamics and ecophysiology of the population along with characterization and evaluation of useful traits.

Correction of the misclassification of species in the Portuguese collection of Cucurbita pepo L. using DNA markers

In this study, the genetic variability among 130 accessions of the Portuguese germplasm collection of Cucurbita pepo L. maintained at the Banco Portugues de Germoplasma Vegetal was assessed using AFLP (amplified fragment length polymorphism) and RAPD (random amplified polymorphic DNA) techniques for the identification of a genetically diverse core group of accessions for field phenotypic analysis. The surprisingly completely different molecular patterns exhibited by multiple accessions was later confirmed in the distribution of the putative C. pepo plants into two clusters drastically separated at a very low level of genetic similarity (DICE coefficient = 0.37). Additional analyses with RAPD and ISSR (inter single sequence repeat) markers and the introduction of standard genotypes of C. maxima L. and C. moschata L. into the analyses allowed the identification of multiple accessions of the last species wrongly included in the C. pepo collection. This study is a good example of the usefulness of DNA markers in the establishment and management of plant germplasm collections.

Correction of the misclassification of species in the Portuguese collection of Cucurbita pepo L. using DNA markers

In this study, the genetic variability among 130 accessions of the Portuguese germplasm collection of Cucurbita pepo L. maintained at the Banco Portugues de Germoplasma Vegetal was assessed using AFLP (amplified fragment length polymorphism) and RAPD (random amplified polymorphic DNA) techniques for the identification of a genetically diverse core group of accessions for field phenotypic analysis. The surprisingly completely different molecular patterns exhibited by multiple accessions was later confirmed in the distribution of the putative C. pepo plants into two clusters drastically separated at a very low level of genetic similarity (DICE coefficient = 0.37). Additional analyses with RAPD and ISSR (inter single sequence repeat) markers and the introduction of standard genotypes of C. maxima L. and C. moschata L. into the analyses allowed the identification of multiple accessions of the last species wrongly included in the C. pepo collection. This study is a good example of the usefulness of DNA markers in the establishment and management of plant germplasm collections.

Genome-wide SNP detection, validation, and development of an 8K SNP array for apple

As high-throughput genetic marker screening systems are essential for a range of genetics studies and plant breeding applications, the International RosBREED SNP Consortium (IRSC) has utilized the Illumina Infinium® II system to develop a medium- to high-throughput SNP screening tool for genome-wide evaluation of allelic variation in apple (Malus×domestica) breeding germplasm. For genome-wide SNP discovery, 27 apple cultivars were chosen to represent worldwide breeding germplasm and re-sequenced at low coverage with the Illumina Genome Analyzer II. Following alignment of these sequences to the whole genome sequence of 'Golden Delicious', SNPs were identified using SoapSNP. A total of 2,113,120 SNPs were detected, corresponding to one SNP to every 288 bp of the genome. The Illumina GoldenGate® assay was then used to validate a subset of 144 SNPs with a range of characteristics, using a set of 160 apple accessions. This validation assay enabled fine-tuning of the final subset of SNPs for the Illumina Infinium® II system. The set of stringent filtering criteria developed allowed choice of a set of SNPs that not only exhibited an even distribution across the apple genome and a range of minor allele frequencies to ensure utility across germplasm, but also were located in putative exonic regions to maximize genotyping success rate. A total of 7867 apple SNPs was established for the IRSC apple 8K SNP array v1, of which 5554 were polymorphic after evaluation in segregating families and a germplasm collection. This publicly available genomics resource will provide an unprecedented resolution of SNP haplotypes, which will enable marker-locus-trait association discovery, description of the genetic architecture of quantitative traits, investigation of genetic variation (neutral and functional), and genomic selection in apple.