Combining genetic resources and elite material populations to improve the accuracy of genomic prediction in apple

Genomic selection is an attractive strategy for apple breeding that could reduce the length of breeding cycles. A possible limitation to the practical implementation of this approach lies in the creation of a training set large and diverse enough to ensure accurate predictions. In this study, we investigated the potential of combining two available populations, i.e., genetic resources and elite material, in order to obtain a large training set with a high genetic diversity. We compared the predictive ability of genomic predictions within-population, across-population or when combining both populations, and tested a model accounting for population-specific marker effects in this last case. The obtained predictive abilities were moderate to high according to the studied trait and small increases in predictive ability could be obtained for some traits when the two populations were combined into a unique training set. We also investigated the potential of such a training set to predict hybrids resulting from crosses between the two populations, with a focus on the method to design the training set and the best proportion of each population to optimize predictions. The measured predictive abilities were very similar for all the proportions, except for the extreme cases where only one of the two populations was used in the training set, in which case predictive abilities could be lower than when using both populations. Using an optimization algorithm to choose the genotypes in the training set also led to higher predictive abilities than when the genotypes were chosen at random. Our results provide guidelines to initiate breeding programs that use genomic selection when the implementation of the training set is a limitation

Molecular and farmer-based comparison of a wild-weed and landrace complex of watermelon in Zimbabwe

Traditional farming systems have been associated with the occurrence of intervarietal and interspecific natural crosses in many crop plants, thus contributing to the genetic diversity of the crop through genetic exchange. In this study, a combination of farmerpreferred morphological traits and RAPD markers were used to evaluate the dynamics of genetic diversity in 43 watermelon accessions collected at a single village level with a traditional farming system. The molecular variability assessed with RAPD markers and analyzed with multidimensional scaling and cluster analysis, demonstrated a substantial differentiation among the accessions. Population structure analysis also demonstrated the existence of three major forms of watermelon, identified by a set of alleles predominant within each form. Dendrograms based on RAPD data and on farmer-preferred traits data were positively correlated according to a Mantel test. Although cultivated cow-melons were genetically most similar to wild-weedy plants at molecular level, they grouped more similar to sweet watermelons based on farmer-preferred traits. The present study revealed limited gene flow between three forms of watermelon and provides insight into how the genetic differentiation corresponds to farmers’ classification of watermelon

Genotype calling in tetraploid species from bi-allelic marker data using mixture models

<p>Abstract</p> <p>Background</p> <p>Automated genotype calling in tetraploid species was until recently not possible, which hampered genetic analysis. Modern genotyping assays often produce two signals, one for each allele of a bi-allelic marker. While ample software is available to obtain genotypes (homozygous for either allele, or heterozygous) for diploid species from these signals, such software is not available for tetraploid species which may be scored as five alternative genotypes (aaaa, baaa, bbaa, bbba and bbbb; nulliplex to quadruplex).</p> <p>Results</p> <p>We present a novel algorithm, implemented in the R package fitTetra, to assign genotypes for bi-allelic markers to tetraploid samples from genotyping assays that produce intensity signals for both alleles. The algorithm is based on the fitting of several mixture models with five components, one for each of the five possible genotypes. The models have different numbers of parameters specifying the relation between the five component means, and some of them impose a constraint on the mixing proportions to conform to Hardy-Weinberg equilibrium (HWE) ratios. The software rejects markers that do not allow a reliable genotyping for the majority of the samples, and it assigns a missing score to samples that cannot be scored into one of the five possible genotypes with sufficient confidence.</p> <p>Conclusions</p> <p>We have validated the software with data of a collection of 224 potato varieties assayed with an Illumina GoldenGate™ 384 SNP array and shown that all SNPs with informative ratio distributions are fitted. Almost all fitted models appear to be correct based on visual inspection and comparison with diploid samples. When the collection of potato varieties is analyzed as if it were a population, almost all markers seem to be in Hardy-Weinberg equilibrium. The R package fitTetra is freely available under the GNU Public License from <url>http://www.plantbreeding.wur.nl/UK/software_fitTetra.html</url> and as Additional files with this article.</p

Reconstruction of multi-generation pedigrees involving numerous old apple cultivars thanks to whole-genome SNP data

A number of European apple cultivars are old, some of them dating back to the Renaissance, Middle Ages or even earlier. Many other cultivars have been developed during subsequent times. In order to decipher the relationships that link some of these old cultivars, whole-genome SNP data (~ 250K) for over 1400 genotypes were analyzed to infer first-degree relationships and reconstruct pedigrees. We used simple exclusion tests based on a count of Mendelian error to identify up to a thousand potential parent-offspring duos, including 295 complete parent-offspring trios and a hundred duos that could be oriented. grand-parents for some missing parents could also be inferred. Combining all this information allowed us to reconstruct pedigrees (up to 6 generations) highlighting the central role of major founders such as ‘Reinette Franche’, ‘Margil’, and ‘Alexander’. Haplotypes were deduced from genotypic data and pedigrees, and used to measure haplotype sharing between supposedly unrelated cultivars, allowing investigating further links between them.To our knowledge, such a large analysis to reconstruct multigeneration pedigrees involving (very) old cultivars selected over such time has never before been performed in perennial fruit species

Consequences of in-situ strategies for the conservation of plant genetic diversity

Conservation biologists have drawn up a range of guidelines for the conservation of genetic diversity—to maximise the chances that populations of threatened species persist, and to conserve this variation for its potential utility. However, our understanding of the effectiveness of conservation guidelines for maintaining genetic diversity in situ is limited. Furthermore, we lack information on how species-level variation in mating system affects these genetic conservation strategies. We used the British geographical ranges of eight widespread but declining plant species, varying in breeding system, as a model to assess the effectiveness of guidelines for the in-situ conservation of neutral genetic diversity. By applying simulated in-situ conservation scenarios to amplified fragment length polymorphism data, we show that the conservation of one population (the “minimum-set” approach) would retain ~ 70% of common allelic variation, but few or no rare alleles (alleles with frequency ≤ 0.05). Our results indicate that the conservation of > 35% of populations would be needed to reach the Convention on Biological Diversity's recommendation to conserve 70% of genetic diversity in situ, as applied to rare alleles (~ 10 populations within each species' British range). The capture of genetic variation in simulated conservation networks was insensitive to breeding system. However, a spatially stratified approach to population selection led to significantly greater capture rates for common alleles in two of our study species, relative to a spatially random strategy. Our study highlights the challenges of conserving genetic variation, and emphasises the vulnerability of genetic biodiversity to reductions in the extent of species' ranges

Genetic assessment of the pomological classification of plum Prunus domestica L. accessions sampled across Europe

The genotyping of European fruit tree collections has helped to identify synonyms, determine parentage, reveal key specimens in the collections and provide information on the development of modern cultivars from one or several progenitors. However, studies on European plum Prunus domestica have been lagging behind, mainly because of the hexaploid chromosome number. In this co-operative study, 104 accessions conserved by 14 partners across Europe were phenotyped for 20 descriptors, and genotyped for 8 SSR loci together with 8 reference cultivars. Based on the descriptors as well as additional information supplied by the partners, as well as the scientific and horticultural literature, each accession was assigned to one of six pomological groups; (1) egg plums sensu lato (E), (2) prunes of the French d’Agen type (P/A), (3) prunes of the Central-Southeast European Zwetschen type (P/Z), (4) greengages (G), (5) mirabelles (M) and (6) bullaces, damsons and var. pomariorum (D/B). A MANOVA conducted on descriptor data revealed significant differentiation among the pomological groups as well as a geographic impact on the differentiation of local plum accessions in Europe. SSR data showed that two trios and seven pairs of genotypes had very similar allele profiles and possibly are genetically identical in spite of different accession names. An AMOVA indicated sparse genetic differentiation when accessions were grouped according to geographic origin whereas significant differences were obtained among pomological groups. A Bayesian analysis of genetic structure, as well as a discriminant analysis of principal components (DAPC), further revealed levels of similarity among and within the different pomological groups, suggesting that egg plums sensu lato (E) and greengages (G) can be referred to subsp. domestica while damsons and bullaces (D/B) but also Central-Southeast European prunes (P/Z) show more affinity to subsp. insititia. The small and possibly heterogeneous groups with mirabelles (M) and prunes of the d’Agen type (P/A) take an intermediate position suggesting a hybridogenic origin