urum wheat (DW), Triticum turgidum L. ssp. durum (Desf.) Husn., genome BBAA, is a cereal grain mainly used for pasta production and evolved from domesticated emmer wheat (DEW), T. turgidum ssp. dicoccum (Schrank ex Schübl.) Thell. DEW itself derived from wild emmer wheat (WEW), T. turgidum ssp. dicoccoides (Körn. ex Asch. & Graebn.

Summary Consensus linkage maps are important tools in crop genomics. We have assembled a high‐density tetraploid wheat consensus map by integrating 13 data sets from independent biparental populations involving durum wheat cultivars (Triticum turgidum ssp. durum), cultivated emmer (T. turgidum ssp. dicoccum) and their ancestor (wild emmer, T. turgidum ssp. dicoccoides). The consensus map harboured 30 144 markers (including 26 626 SNPs and 791 SSRs) half of which were present in at least two component maps. The final map spanned 2631 cM of all 14 durum wheat chromosomes and, differently from the individual component maps, all markers fell within the 14 linkage groups. Marker density per genetic distance unit peaked at centromeric regions, likely due to a combination of low recombination rate in the centromeric regions and even gene distribution along the chromosomes. Comparisons with bread wheat indicated fewer regions with recombination suppression, making this consensus map valuable for mapping in the A and B genomes of both durum and bread wheat. Sequence similarity analysis allowed us to relate mapped gene‐derived SNPs to chromosome‐specific transcripts. Dense patterns of homeologous relationships have been established between the A‐ and B‐genome maps and between nonsyntenic homeologous chromosome regions as well, the latter tracing to ancient translocation events. The gene‐based homeologous relationships are valuable to infer the map location of homeologs of target loci/QTLs. Because most SNP and SSR markers were previously mapped in bread wheat, this consensus map will facilitate a more effective integration and exploitation of genes and QTL for wheat breeding purposes.

BackgroundApparent Amylose Content (AAC), regulated by the Waxy gene, represents the key determinant of rice cooking properties. In occidental countries high AAC rice represents the most requested market class but the availability of molecular markers allowing specific selection of high AAC varieties is limited.ResultsIn this study, the effectiveness of available molecular markers in predicting AAC was evaluated in a collection of 127 rice accessions (125 japonica ssp. and 2 indica ssp.) characterized by AAC values from glutinous to 26%. The analyses highlighted the presence of several different allelic patterns identifiable by a few molecular markers, and two of them, i.e., the SNPs at intron1 and exon 6, were able to explain a maximum of 79.5% of AAC variation. However, the available molecular markers haplotypes did not provide tools for predicting accessions with AAC higher than 24.5%. To identify additional polymorphisms, the re-sequencing of the Waxy gene and 1kbp of the putative upstream regulatory region was performed in 21 genotypes representing all the AAC classes identified. Several previously un-characterized SNPs were identified and four of them were used to develop dCAPS markers.ConclusionsThe addition of the SNPs newly identified slightly increased the AAC explained variation and allowed the identification of a haplotype almost unequivocally associated to AAC higher than 24.5%. Haplotypes at the waxy locus were also associated to grain length and length/width (L/W) ratio. In particular, the SNP at the first intron, which identifies the Wx a and Wx b alleles, was associated with differences in the width of the grain, the L/W ratio and the length of the kernel, most likely as a result of human selection.

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Evolutionary studies that are aimed at defining the processes behind the present level and organization of crop genetic diversity represent the fundamental bases for biodiversity conservation and use. A Mesoamerican origin of the common bean Phaseolus vulgaris was recently suggested through analysis of nucleotide polymorphism at the nuclear level. Here, we have used chloroplast microsatellites to investigate the origin of the common bean, on the basis of the specific characteristics of these markers (no recombination, haploid genome, uniparental inheritance), to validate these recent findings. Indeed, comparisons of the results obtained through analysis of nuclear and cytoplasmic DNA should allow the resolution of some of the contrasting information available on the evolutionary processes. The main outcomes of the present study are: (i) confirmation at the chloroplast level of the results obtained through nuclear data, further supporting the Mesoamerican origin of P. vulgaris, with central Mexico representing the cradle of its diversity; (ii) identification of a putative ancestral plastidial genome, which is characteristic of a group of accessions distributed from central Mexico to Peru, but which have not been highlighted beforehand through analyses at the nuclear level. Finally, the present study suggests that when a single species is analyzed, there is the need to take into account the complexity of the relationships between P. vulgaris and its closely related and partially intercrossable species P. coccineus and P. dumosus. Thus, the present study stresses the importance for the investigation of the speciation processes of these taxa through comparisons of both plastidial and nuclear variability. This knowledge will be fundamental not only from an evolutionary point of view, but also to put P. coccineus and P. dumosus germplasm to better use as a source of useful diversity for P. vulgaris breeding.

Chloroplast microsatellites (cpSSRs) provide a powerful tool to study the genetic variation and evolution of plants. We have investigated the usefulness of 39 primer pairs tagging cpSSR loci on a set of eight different genera of Leguminosae (Papilionoideae subfamily) and five species belonging to the genus Phaseolus. Thirty-six 'universal' primer pairs were retrieved from the literature, one was re-designed and a further two were designed de novo. The cpSSR loci analysed were highly polymorphic across the individuals examined. Twenty-seven primer pairs were polymorphic in the overall sample, 18 within Phaseolus, and 16 in both P. vulgaris and P. coccineus. Analysis of the plastome sequences of four Leguminosae species (obtained from GenBank) showed that in the loci targeted by universal primer pairs: (i) the originally tagged cpSSRs can be lost; (ii) other cpSSRs can be present; and (iii) polymorphism arises not only from differences in the numbers of cpSSR repeats, but often from other insertion/deletion events. Multilocus linkage disequilibrium analysis suggests that homoplasy is not a major problem in our dataset, and principal component analysis indicates intelligible relationships among the species considered. Our study demonstrates that this set of chloroplast markers provides a useful tool to study the diversity and the evolution of several legumes, and particularly P. vulgaris and P. coccineus.

A rice GWAS panel of 281 accessions of japonica rice was phenotypically characterized for 26 traits related to phenology, plant and seed morphology, physiology and yield for 2 years in field conditions under permanent flooding (PF) and limited water (LW). A genome-wide analysis uncovered a total of 160 significant marker-trait associations (MTAs), of which 32 were LW-specific, 59 were PF-specific, and 69 were in common between the two water management systems. LW-specific associations were identified for several agronomic traits including days to maturation, days from flowering to maturation, leaf traits, plant height, panicle and seed traits, hundred grain weight, yield and tillering. Significant MTAs were detected across all the 12 rice chromosomes, while clusters of effects influencing different traits under LW or in both watering conditions were, respectively, observed on chromosomes 4, 8, and 12 and on chromosomes 1, 3, 4, 5, and 8. The analysis of genes annotated in the Nipponbare reference sequence and included in the regions associated to traits related to plant morphology, grain yield, and physiological parameters allowed the identification of genes that were demonstrated to affect the respective traits. Among these, three (OsOFP2, Dlf1, OsMADS56) and seven (SUI1, Sd1, OsCOL4, Nal1, OsphyB, GW5, Ehd1) candidate genes were, respectively, identified to co-localize with LW-specific associations and associations in common between the two water treatments. For several LW-specific MTAs, or in common among the two treatments, positional co-localizations with previously identified QTLs for rice adaptation to water shortages were observed, a result that further supports the role of the loci identified in this work in conferring adaptation to LW. The most robust associations identified here could represent suitable targets for genomic selection approaches to improve yield-related traits under LW.

Key messageRice breeding programs based on pedigree schemes can use a genomic model trained with data from their working collection to predict performances of progenies produced through rapid generation advancement.AbstractSo far, most potential applications of genomic prediction in plant improvement have been explored using cross validation approaches. This is the first empirical study to evaluate the accuracy of genomic prediction of the performances of progenies in a typical rice breeding program. Using a cross validation approach, we first analyzed the effects of marker selection and statistical methods on the accuracy of prediction of three different heritability traits in a reference population (RP) of 284 inbred accessions. Next, we investigated the size and the degree of relatedness with the progeny population (PP) of sub-sets of the RP that maximize the accuracy of prediction of phenotype across generations, i.e., for 97 F5–F7 lines derived from biparental crosses between 31 accessions of the RP. The extent of linkage disequilibrium was high (r 2 = 0.2 at 0.80 Mb in RP and at 1.1 Mb in PP). Consequently, average marker density above one per 22 kb did not improve the accuracy of predictions in the RP. The accuracy of progeny prediction varied greatly depending on the composition of the training set, the trait, LD and minor allele frequency. The highest accuracy achieved for each trait exceeded 0.50 and was only slightly below the accuracy achieved by cross validation in the RP. Our results thus show that relatively high accuracy (0.41–0.54) can be achieved using only a rather small share of the RP, most related to the PP, as the training set. The practical implications of these results for rice breeding programs are discussed.Electronic supplementary materialThe online version of this article (10.1007/s00122-017-3011-4) contains supplementary material, which is available to authorized users.