Search

Background: The tetraploid durum wheat (Triticum turgidum L. ssp. durum Desf. Husnot) is an important crop which provides the raw material for pasta production and a valuable source of genetic diversity for breeding hexaploid wheat (Triticum aestivum L.). Future breeding efforts to enhance yield potential and climate resilience will increasingly rely on genomics-based approaches to identify and select beneficial alleles. A deeper characterisation of the molecular and functional diversity of the durum wheat transcriptome will be instrumental to more effectively harness its genetic diversity., Results: We report on the de novo transcriptome assembly of durum wheat cultivar 'Svevo'. The transcriptome of four tissues/organs (shoots and roots at the seedling stage, reproductive organs and developing grains) was assembled de novo, yielding 180,108 contigs, with a N50 length of 1121 bp and mean contig length of 883 bp. Alignment against the transcriptome of nine plant species identified 43% of transcripts with homology to at least one reference transcriptome. The functional annotation was completed by means of a combination of complementary software. The presence of differential expression between the A- and B-homoeolog copies of the durum wheat tetraploid genome was ascertained by phase reconstruction of polymorphic sites based on the T. urartu transcripts and inferring homoeolog-specific sequences. We observed greater expression divergence between A and B homoeologs in grains rather than in leaves and roots. The transcriptomes of 13 durum wheat cultivars spanning the breeding period from 1969 to 2005 were analysed for SNP diversity, leading to 95,358 non-rare, hemi-SNPs shared among two or more cultivars and 33,747 locus-specific (diploid inheritance) SNPs., Conclusions: Our study updates and expands the de novo transcriptome reference assembly available for durum wheat. Out of 180,108 assembled transcripts, 13,636 were specific to the Svevo cultivar as compared to the only other reference transcriptome available for durum, thus contributing to the identification of the tetraploid wheat pan-transcriptome. Additionally, the analysis of 13 historically relevant hallmark varieties produced a SNP dataset that could successfully validate the genotyping in tetraploid wheat and provide a valuable resource for genomics-assisted breeding of both tetraploid and hexaploid wheats.

Key Message: Genomic selection had a higher selection response for FHB resistance than phenotypic selection, while association mapping identified major QTL on chromosome 3B unaffected by plant height and flowering date. Fusarium head blight (FHB) is one of the most destructive diseases of durum wheat. Hence, minimizing losses in yield, quality and avoiding contamination with mycotoxins are of pivotal importance, as durum wheat is mostly used for human consumption. While growing resistant varieties is the most promising approach for controlling this fungal disease, FHB resistance breeding in durum wheat is hampered by the limited variation in the elite gene pool and difficulties in efficiently combining the numerous small-effect resistance quantitative trait loci (QTL) in the same line. We evaluated an international collection of 228 genotyped durum wheat cultivars for FHB resistance over 3 years to investigate the genetic architecture and potential of genomic-assisted breeding for FHB resistance in durum wheat. Plant height was strongly positively correlated with FHB resistance and led to co-localization of plant height and resistance QTL. Nevertheless, a major QTL on chromosome 3B independent of plant height was identified in the same chromosomal interval as reported for the prominent hexaploid resistance QTL Fhb1, though haplotype analysis highlighted the distinctiveness of both QTL. Comparison between phenotypic and genomic selection for FHB resistance revealed a superior prediction ability of the former. However, simulated selection experiments resulted in higher selection responses when using genomic breeding values for early generation selection. An earlier identification of the most promising lines and crossing parents was feasible with a genomic selection index, which suggested a much faster short-term population improvement than previously possible in durum wheat, complementing long-term strategies with exotic resistance donors.

Agriculture is now facing the 'perfect storm' of climate change, increasing costs of fertilizer and rising food demands from a larger and wealthier human population. These factors point to a global food deficit unless the efficiency and resilience of crop production is increased. The intensification of agriculture has focused on improving production under optimized conditions, with significant agronomic inputs. Furthermore, the intensive cultivation of a limited number of crops has drastically narrowed the number of plant species humans rely on. A new agricultural paradigm is required, reducing dependence on high inputs and increasing crop diversity, yield stability and environmental resilience. Genomics offers unprecedented opportunities to increase crop yield, quality and stability of production through advanced breeding strategies, enhancing the resilience of major crops to climate variability, and increasing the productivity and range of minor crops to diversify the food supply. Here we review the state of the art of genomic-assisted breeding for the most important staples that feed the world, and how to use and adapt such genomic tools to accelerate development of both major and minor crops with desired traits that enhance adaptation to, or mitigate the effects of climate change., (© 2015 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.)

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., (© 2014 Society for Experimental Biology, Association of Applied Biologists and John Wiley & Sons Ltd.)

Barley grain starch is formed by amylose and amylopectin in a 1:3 ratio, and is packed into granules of different dimensions. The distribution of granule dimension is bimodal, with a majority of small spherical B-granules and a smaller amount of large discoidal A-granules containing the majority of the starch. Starch granules are semi-crystalline structures with characteristic X-ray diffraction patterns. Distinct features of starch granules are controlled by different enzymes and are relevant for nutritional value or industrial applications. Here, the Targeting-Induced Local Lesions IN Genomes (TILLING) approach was applied on the barley TILLMore TILLING population to identify 29 new alleles in five genes related to starch metabolism known to be expressed in the endosperm during grain filling: BMY1 (Beta-amylase 1), GBSSI (Granule Bound Starch Synthase I), LDA1 (Limit Dextrinase 1), SSI (Starch Synthase I), SSIIa (Starch Synthase IIa). Reserve starch of nine M3 mutant lines carrying missense or nonsense mutations was analysed for granule size, crystallinity and amylose/amylopectin content. Seven mutant lines presented starches with different features in respect to the wild-type: (i) a mutant line with a missense mutation in GBSSI showed a 4-fold reduced amylose/amylopectin ratio; (ii) a missense mutations in SSI resulted in 2-fold increase in A:B granule ratio; (iii) a nonsense mutation in SSIIa was associated with shrunken seeds with a 2-fold increased amylose/amylopectin ratio and different type of crystal packing in the granule; (iv) the remaining four missense mutations suggested a role of LDA1 in granule initiation, and of SSIIa in determining the size of A-granules. We demonstrate the feasibility of the TILLING approach to identify new alleles in genes related to starch metabolism in barley. Based on their novel physicochemical properties, some of the identified new mutations may have nutritional and/or industrial applications.

The complex architecture and plasticity of the maize root system is controlled by a plethora of genes. Mutant analyses have identified genes regulating shoot-borne root initiation (RTCS) and root hair elongation (RTH1 and RTH3). Quantitative trait locus (QTL) studies have highlighted the importance of seminal roots, lateral roots, and root hairs in phosphorus acquisition. Additionally, QTLs that influence root features were shown to affect yield under different water regimes and under flooding conditions. Finally, proteome and transcriptome analyses provided insights into maize root development and identified candidate genes associated with cell specification, and lateral root initiation in pericycle cells. The targeted application of forward-genetics and reverse-genetics approaches will accelerate the unraveling of the functional basis of root development and architecture.

The genetic bases of the molecular, cellular and developmental responses to drought involve many gene functions regulated by water availability. Genomics-based approaches provide access to agronomically desirable alleles present at quantitative trait loci (QTLs) that affect such responses, thus enabling us to improve the drought tolerance and yield of crops under water-limited conditions more effectively. Marker-assisted selection is already helping breeders improve drought-related traits. Analysis of sequence data and gene products should facilitate the identification and cloning of genes at target QTLs. Based on such premises, we envision a quick broadening of our understanding of the genetic and functional basis of drought tolerance. Novel opportunities will be generated for tailoring new genotypes "by design". Harnessing the full potential of genomics-assisted breeding will require a multidisciplinary approach and an integrated knowledge of the molecular and physiological processes influencing tolerance to drought.

Climate change affects agricultural productivity worldwide. Increased prices of food commodities are the initial indication of drastic edible yield loss, which is expected to increase further due to global warming. This situation has compelled plant scientists to develop climate change-resilient crops, which can withstand broad-spectrum stresses such as drought, heat, cold, salinity, flood, submergence and pests, thus helping to deliver increased productivity. Genomics appears to be a promising tool for deciphering the stress responsiveness of crop species with adaptation traits or in wild relatives toward identifying underlying genes, alleles or quantitative trait loci. Molecular breeding approaches have proven helpful in enhancing the stress adaptation of crop plants, and recent advances in high-throughput sequencing and phenotyping platforms have transformed molecular breeding to genomics-assisted breeding (GAB). In view of this, the present review elaborates the progress and prospects of GAB for improving climate change resilience in crops, which is likely to play an ever increasing role in the effort to ensure global food security.

The marker x environment interaction (MxE) genomic model can be used to generate predictions for untested individuals and identify genomic regions in which effects are stable across environments and others that show environmental specificity. The objectives of this study were (i) to extend the MxE model using priors that produce shrinkage and variable selection such as Bayesian ridge regression (BRR) and BayesB (BB), respectively, and (ii) to evaluate the genomic prediction accuracy of MxE, single-environment, and across-environment models using a multiparental durum wheat (Triticum turgidum L. spp. duram) population characterized for grain yield (GY), grain volume weight (GVW), 1000-kernel weight (GWT), and heading date (HD) in four environments. Breeding value predictions were generated for two prediction problems: cross-validation problem 1 (CV1) and cross-validation problem 2 (CV2). In general, results showed that the MxE model performed better than the single-environment and across-environment models, in terms of minimizing the model residual variance, for both CV1 and CV2. The improved data-fitting gain over the other models was more evident for GWT and HD (up to twofold differences) than to GY and GVW, which showed more complex genetic bases and smaller single-marker effects. Considering the Bayesian models used, BB showed better overall prediction accuracy than BRR. As proof-of-concept for the MxE model, the major controllers of HD--Ppd and FT on chromosomes 2A, 2B, and 7A--showed stable effects across environments as well as environment-specific effects. For GY, besides the regions on chromosomes 2B and 7A, additional chromosome regions with large marker effects were detected in all chromosome groups. [ABSTRACT FROM AUTHOR]

The objective of the InterDrought conferences is to be a platform for debating key issues that are relevant for increasing the yield and yield stability of crops under drought via integrated approaches. InterDrought-IV, held in Perth, Australia, in September 2013, followed previous InterDrought conferences in bringing together researchers in agronomy, soil science, modelling, physiology, biochemistry, molecular biology, genetics and plant breeding. Key themes were (i) maximising water productivity; (ii) maximising dryland crop production; (iii) adaptation to water-limited environments; (iv) plant productivity under drought through effective water capture, improved transpiration efficiency, and growth and yield; and (v) breeding for water-limited environments through variety development, and trait-based genomics-assisted and transgenic approaches. This paper highlights some key issues and presents recommendations for future action. Improved agronomic interventions were recognised as being important contributors to improved dryland crop yields in water-limited environments, and new methods for exploring root architecture and water capture were highlighted. The increase in crop yields under drought through breeding and selection, the development of high-throughput phenotyping facilities for field-grown and pot-grown plants, and advances in understanding the molecular basis of plant responses and resistance to drought stress were recognised. Managed environment phenotyping facilities, a range of field environments, modelling, and genomic molecular tools are being used to select and release drought-resistant cultivars of all major crops. Delegates discussed how individuals and small teams can contribute to progress, and concluded that interdisciplinary research, linkages to international agricultural research centres, public-private partnerships and continuation of the InterDrought conferences will be instrumental for progress. [ABSTRACT FROM AUTHOR]

Improving crops yield under water-limited conditions is the most daunting challenge faced by breeders. To this end, accurate, relevant phenotyping plays an increasingly pivotal role for the selection of drought-resilient genotypes and, more in general, for a meaningful dissection of the quantitative genetic landscape that underscores the adaptive response of crops to drought. A major and universally recognized obstacle to a more effective translation of the results produced by drought-related studies into improved cultivars is the difficulty in properly phenotyping in a high-throughput fashion in order to identify the quantitative trait loci that govern yield and related traits across different vvater regimes. This revievv provides basic principles and a broad set of references useful for the management of phenotyping practices for the study and genetic dissection of drought tolerance and, ultimately, for the release of drought-tolerant cultivars. [ABSTRACT FROM AUTHOR]

Recent technical advancements and refinement of analytical methods have enabled the loci (quantitative trait loci, QTLs) responsible for the genetic control of quantitative traits to be dissected molecularly. To date, most plant QTLs have been cloned using a positional cloning approach following identification in experimental crosses. In some cases, an association between sequence variation at a candidate gene and a phenotype has been established by analysing existing genetic accessions. These strategies can be refined using appropriate genetic materials and the latest developments in genomics platforms. We foresee that although QTL analysis and cloning addressing naturally occurring genetic variation should shed light on mechanisms of plant adaptation, a greater emphasis on approaches relying on mutagenesis and candidate gene validation is likely to accelerate the pace of discovering the genes underlying QTLs. [Copyright &y& Elsevier]

Comparative analysis of a number of studies in drought‐stressed maize (Zea mays L.) reporting quantitative trait loci (QTLs) for abscisic acid concentration, root characteristics, other morpho‐physiological traits (MPTs) and grain yield (GY) reveals their complex genetic basis and the influence of the genetic background and the environment on QTL effects. Chromosome regions (e.g. near umc11 on chromosome 1 and near csu133 on chromosome 2) with QTLs controlling a number of MPTs and GY across populations and conditions of different water supply have been identified. Examples are presented on the use of QTL information to elucidate the genetic and physiological bases of the association among MPTs and GY. The QTL approach allows us to develop hypotheses accounting for these associations which can be further tested by developing near isogenic lines (NILs) differing for the QTL alleles. NILs also allow for a more accurate assessment of the breeding value of MPTs and, in some cases, may allow for the map‐based cloning of the gene(s) underlying the QTL. Although QTL analysis is still time‐consuming and resource‐demanding, its integration with genomics and post‐genomics approaches (e.g. transcriptome, proteome and metabolome analyses) will play an increasingly important role for the identification and validation of candidate genes affecting MPTs and GY. [ABSTRACT FROM PUBLISHER]