106 research outputs found

    Hybrid performance and heterosis in spring bread wheat, and their relations to SSR-based genetic distances and coefficients of parentage

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    Development of hybrids is considered to be a promising avenue to enhance the yield potential of crops. We investigated (i) the amount of heterosis observed in hybrid progeny, (ii) relative importance of general (GCA) versus specific (SCA) combining ability, and (iii) the relationship between heterosis and genetic distance measures in four agronomic traits of spring bread wheat. Eight male and 14 female lines, as well as 112 hybrids produced in a factorial design were grown in replicated trials at two environments in Mexico. Principal coordinate analysis based on Rogers’ distance (RD) estimates calculated from 113 SSRs revealed three different groups of parents. Mid-parent heterosis (MPH) for grain yield averaged 0.02 t ha−1 (0.5%) and varied from−15.33% to 14.13%. MPH and hybrid performance (F1P) were higher for intra-group hybrids than for inter-group hybrids, with low values observed in inter-group crosses involving two non-adapted Chinese parents. Combined analyses of variance revealed significant differences among parents and among hybrids. Estimates of GCA variances were more important than SCA variances for all traits. Tight correlations of GCA with line per se performance, and mid-parent value with F1P were observed for all traits. In contrast, correlations of MPH with RD and coefficient of parentage were not significant. It was concluded that the level of heterosis in spring wheat was too low to warrant a commercial exploitation in hybrids. SSRs proved to be a powerful tool for the identification of divergent groups in advanced wheat breeding materials

    Haplotypes-based genetic analysis: benefits and challenges

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    The increasing availability of Single Nucleotide Polymorphisms (SNPs) discovered by Next Generation Sequencing will enable a range of new genetic analyses in crops, which was not possible before. Concomitantly, researchers will face the challenge of handling large data sets at the whole-genome level. By grouping thousands of SNPs into a few hundred haplotype blocks, complexity of the data can be reduced with fewer statistical tests and a lower probability of spurious associations. Owing to the strong genome structure present in breeding lines of most crops, the deployment of haplotypes could be a powerful complement to improve efficiency of marker-assisted and genomic selection. This review describes in brief the commonly used approaches to construct haplotype blocks and some examples in animals and crops are cited where haplotype-based dissection of traits were proven beneficial. Some important considerations and facts while working with haplotypes in crops are reviewed at the end

    SSR and Pedigree Analyses of Genetic Diversity among CIMMYT Wheat Lines Targeted to Different Megaenvironments

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    Improved bread wheat (Triticum aestivum L.) cultivars for diverse agroecological environments are important for success in the effort to increase food production. In the 1980s, CIMMYT introduced the megaenvironment (ME) concept to breed wheats specifically adapted to different areas. Our objective was to analyze the genetic diversity among 68 advanced CIMMYT wheat lines targeted to different MEs by using 99 simple sequence repeats (SSRs) and the coefficient of parentage (COP). The average number of alleles detected was higher for the 47 genomic SSRs (5.4) than for the 52 SSRs derived from expressed sequence tags (EST) (3.3), but gene diversity between MEs was similar for both types of markers. No significant differences among the five MEs were observed for the means of SSR-based genetic similarities (GS), calculated as 1 − Rogers' distance, and COP values. Both measures showed a low correlation (r = 0.43). High levels of genetic diversity were found within the germplasm targeted to each ME. However, principle coordinate analysis based on modified Rogers' distances did not separate the genotypes according to their targeted MEs. We conclude that presence of a single core germplasm can reflect large phenotypic differences. A sufficient number of diverse breeding lines for each ME is required because MEs generally combine various production areas. SSRs represent a powerful tool to quantify genetic diversity in wheat, but genotypic differentiation for adaptation to specific MEs in the CIMMYT program could not be proven

    Allelic Variation at the Vernalization Response (Vrn-1) and Photoperiod Sensitivity (Ppd-1) Genes and Their Association With the Development of Durum Wheat Landraces and Modern Cultivars

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    Wheat adaptability to a wide range of environmental conditions is mostly determined by allelic diversity within genes controlling vernalization requirement (Vrn-1) and photoperiod sensitivity (Ppd-1). We characterized a panel of 151 durum wheat Mediterranean landraces and 20 representative locally adapted modern cultivars for their allelic composition at Vrn-1 and Ppd-1 gene using diagnostic molecular markers and studied their association with the time needed to reach six growth stages under field conditions over 6 years. Compared with the more diverse and representative landrace collection, the set of modern cultivars were characterized by a reduction of 50% in the number of allelic variants at the Vrn-A1 and Vrn-B1 genes, and the high frequency of mutant alleles conferring photoperiod insensitivity at Ppd-A1, which resulted on a shorter cycle length. Vrn-A1 played a greater role than Vrn-B1 in regulating crop development (Vrn-A1 > Vrn-B1). The results suggest that mutations in the Vrn-A1 gene may have been the most important in establishing the spring growth habit of Mediterranean landraces and modern durum cultivars. The allele Vrn-A1d, found in 10 landraces, delayed development. The relative effects of single Vrn-A1 alleles on delaying the development of the landraces were vrn-A1 = Vrn-A1d > Vrn-A1b > Vrn-A1c. Allele vrn-B1 was present in all except two landraces and in all modern cultivars. The null allele at Ppd-A1 (a deletion first observed in the French bread wheat cultivar ‘Capelle-Desprez’) was found for the first time in durum wheat in the present study that identified it in 30 landraces from 13 Mediterranean countries. Allele Ppd-A1a (GS105) was detected in both germplasm types, while the allele Ppd-A1a (GS100) was found only in modern North American and Spanish cultivars. The relative effect of single Ppd-A1 alleles on extending phenological development was Ppd-A1(DelCD) > Ppd-A1b > Ppd-A1a (GS105) > Ppd-A1a (GS100). Sixteen Vrn-1+Ppd-1 allelic combinations were found in landraces and six in modern cultivars, but only three were common to both panels. Differences in the number of days to reach anthesis were 10 days in landraces and 3 days in modern cultivars. Interactive effects between Vrn-1 and Ppd-1 genes were detected.info:eu-repo/semantics/publishedVersio

    Multi-environment QTL analysis using an updated genetic map of a widely distributed Seri × Babax spring wheat population

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    Seri/Babax spring wheat RIL population was developed to minimize the confounding effect of phenology in the genetic dissection of abiotic stress traits. An existing linkage map (< 500 markers) was updated with 6470 polymorphic Illumina iSelect 90K array and DArTseq SNPs to a genetic map of 5576.5 cM with 1748 non-redundant markers (1165 90K SNPs, 207 DArTseq SNPs, 183 AFLP, 111 DArT array, and 82 SSR) assigned to 31 linkage groups. We conducted QTL mapping for yield and related traits phenotyped in several major wheat growing areas in Egypt, Sudan, Iran, India, and Mexico (nine environments: heat, drought, heat plus drought, and yield potential). QTL analysis identified 39 (LOD 2.5–23.6; PVE 4.8–21.3%), 36 (LOD 2.5–15.4; PVE 2.9–21.4%), 30 (LOD 2.5–13.1; PVE 3.6–26.8%), 39 (LOD 2.7–14.4; PVE 2.6–15.9%), and 22 (LOD 2.8–4.8; PVE 6.8–12.9%) QTLs for grain yield, thousand-grain weight, grain number, days to heading, and plant height, respectively. The present study confirmed QTLs from previous studies and identified novel QTLs. QTL analysis based on high-yielding and low-yielding environmental clusters identified 11 QTLs (LOD 2.6–14.9; PVE 2.7–19.7%). The updated map thereby provides a better genome coverage (3.5-fold) especially on the D genome (4-fold), higher density (1.1-fold), and a good collinearity with the IWGSC RefSeq v1.0 genome, and increased the number of detected QTLs (5-fold) compared with the earlier map. This map serves as a useful genomic resource for genetic analyses of important traits on this wheat population that was widely distributed around the world.info:eu-repo/semantics/acceptedVersio

    Wheat quality improvement at CIMMYT and the use of genomic selection on it

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    Citation: Guzman, C., Pena, R. J., Singh, R., Autrique, E., Dreisigacker, S., Crossa, J., . . . Battenfield, S. (2016). Wheat quality improvement at CIMMYT and the use of genomic selection on it. Applied and Translational Genomics, 11, 3-8. https://doi.org/10.1016/j.atg.2016.10.004The International Center for Maize and Wheat Improvement (CIMMYT) leads the Global Wheat Program, whose main objective is to increase the productivity of wheat cropping systems to reduce poverty in developing countries. The priorities of the program are high grain yield, disease resistance, tolerance to abiotic stresses (drought and heat), and desirable quality. The Wheat Chemistry and Quality Laboratory has been continuously evolving to be able to analyze the largest number of samples possible, in the shortest time, at lowest cost, in order to deliver data on diverse quality traits on time to the breeders formaking selections for advancement in the breeding pipeline. The participation of wheat quality analysis/selection is carried out in two stages of the breeding process: evaluation of the parental lines for new crosses and advanced lines in preliminary and elite yield trials. Thousands of lines are analyzed which requires a big investment in resources. Genomic selection has been proposed to assist in selecting for quality and other traits in breeding programs. Genomic selection can predict quantitative traits and is applicable to multiple quantitative traits in a breeding pipeline by attaining historical phenotypes and adding high-density genotypic information. Due to advances in sequencing technology, genome-wide single nucleotide polymorphism markers are available through genotyping-by-sequencing at a cost conducive to application for genomic selection. At CIMMYT, genomic selection has been applied to predict all of the processing and end-use quality traits regularly tested in the spring wheat breeding program. These traits have variable levels of prediction accuracy, however, they demonstrated that most expensive traits, dough rheology and baking final product, can be predicted with a high degree of confidence. Currently it is being explored how to combine both phenotypic and genomic selection to make more efficient the genetic improvement for quality traits at CIMMYT spring wheat breeding program. (C) 2016 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license

    The effects of brief heat during early booting on reproductive, developmental and chlorophyll physiological performance in common wheat (Triticum aestivum L.)

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    Rising temperatures due to climate change threaten agricultural crop productivity. As a cool-season crop wheat is heat-sensitive, but often exposed to high temperatures during crop growing period. In the current study, a bread wheat panel of spring wheat genotypes, including putatively heat-tolerant Australian and CIMMYT genotypes, was exposed to a 5-day mild (34oC/28oC, day/night) or extreme (37oC/27oC) heat stress during the sensitive pollen developmental stage. Worsening effects on anther morphology were observed as heat stress increased from mild to extreme. Even under mild heat a significant decrease in pollen viability and number of grains per spike from primary spike was observed compared with the control (21oC/15oC), with Sunstar and two CIMMYT breeding lines performing well. A heat-specific positive correlation between the two traits indicates the important role of pollen fertility for grain setting. Interestingly, both mild and extreme heat induced development of new tillers after the heat stress, providing an alternative sink for accumulated photosynthates and significantly contributing to the final yield. Measurements of flag leaf maximum potential quantum efficiency of Photosystem II (Fv/Fm) showed an initial inhibition after the heat treatment, followed by a full recovery within a few days. Despite this, model fitting using chlorophyll SPAD measurements showed an earlier onset or faster senescence rate under heat stress. The data presented here provide interesting entry points for further research into pollen fertility, tillering dynamics and leaf senescence under heat. The identified heat-tolerant wheat genotypes can be used to dissect the underlying mechanisms and breed climate-resilient wheat

    Bayesian multitrait kernel methods improve multienvironment genome-based prediction

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    When multitrait data are available, the preferred models are those that are able to account for correlations between phenotypic traits because when the degree of correlation is moderate or large, this increases the genomic prediction accuracy. For this reason, in this article, we explore Bayesian multitrait kernel methods for genomic prediction and we illustrate the power of these models with three-real datasets. The kernels under study were the linear, Gaussian, polynomial, and sigmoid kernels; they were compared with the conventional Ridge regression and GBLUP multitrait models. The results show that, in general, the Gaussian kernel method outperformed conventional Bayesian Ridge and GBLUP multitrait linear models by 2.2–17.45% (datasets 1–3) in terms of prediction performance based on the mean square error of prediction. This improvement in terms of prediction performance of the Bayesian multitrait kernel method can be attributed to the fact that the proposed model is able to capture nonlinear patterns more efficiently than linear multitrait models. However, not all kernels perform well in the datasets used for evaluation, which is why more than one kernel should be evaluated to be able to choose the best kernel

    Diversity analysis of 80,000 wheat accessions reveals consequences and opportunities of selection footprints

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    Undomesticated wild species, crop wild relatives, and landraces represent sources of variation for wheat improvement to address challenges from climate change and the growing human population. Here, we study 56,342 domesticated hexaploid, 18,946 domesticated tetraploid and 3,903 crop wild relatives in a massive-scale genotyping and diversity analysis. Using DArTseqTM technology, we identify more than 300,000 high-quality SNPs and SilicoDArT markers and align them to three reference maps: the IWGSC RefSeq v1.0 genome assembly, the durum wheat genome assembly (cv. Svevo), and the DArT genetic map. On average, 72% of the markers are uniquely placed on these maps and 50% are linked to genes. The analysis reveals landraces with unexplored diversity and genetic footprints defined by regions under selection. This provides fertile ground to develop wheat varieties of the future by exploring specific gene or chromosome regions and identifying germplasm conserving allelic diversity missing in current breeding programs

    Wheat genetic diversity trends during domestication and breeding

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    It has been claimed that plant breeding reduces genetic diversity in elite germplasm which could seriously jeopardize the continued ability to improve crops. The main objective of this study was to examine the loss of genetic diversity in spring bread wheat during (1) its domestication, (2) the change from traditional landrace cultivars (LCs) to modern breeding varieties, and (3) 50 years of international breeding. We studied 253 CIMMYT or CIMMYT-related modern wheat cultivars, LCs, and Triticum tauschii accessions, the D-genome donor of wheat, with 90 simple sequence repeat (SSR) markers dispersed across the wheat genome. A loss of genetic diversity was observed from T. tauschii to the LCs, and from the LCs to the elite breeding germplasm. Wheats genetic diversity was narrowed from 1950 to 1989, but was enhanced from 1990 to 1997. Our results indicate that breeders averted the narrowing of the wheat germplasm base and subsequently increased the genetic diversity through the introgression of novel materials. The LCs and T. tauschii contain numerous unique alleles that were absent in modern spring bread wheat cultivars. Consequently, both the LCs and T. tauschii represent useful sources for broadening the genetic base of elite wheat breeding germplasm
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