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      Genome selection in fruit breeding: application to table grapes

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          ABSTRACT Genomic selection (GS) has recently been proposed as a new selection strategy which represents an innovative paradigm in crop improvement, now widely adopted in animal breeding. Genomic selection relies on phenotyping and high-density genotyping of a sufficiently large and representative sample of the target breeding population, so that the majority of loci that regulate a quantitative trait are in linkage disequilibrium with one or more molecular markers and can thus be captured by selection. In this study we address genomic selection in a practical fruit breeding context applying it to a breeding population of table grape obtained from a cross between the hybrid genotype D8909-15 (Vitis rupestris × Vitis arizonica/girdiana), which is resistant to dagger nematode and Pierce’s disease (PD), and ‘B90-116’, a susceptible Vitis vinifera cultivar with desirable fruit characteristics. Our aim was to enhance the knowledge on the genomic variation of agronomical traits in table grape populations for future use in marker-assisted selection (MAS) and GS, by discovering a set of molecular markers associated with genomic regions involved in this variation. A number of Quantitative Trait Loci (QTL) were discovered but this method is inaccurate and the genetic architecture of the studied population was better captured by the BLasso method of genomic selection, which allowed for efficient inference about the genetic contribution of the various marker loci. The technology of genomic selection afforded greater efficiency than QTL analysis and can be very useful in speeding up the selection procedures for agronomic traits in table grapes.

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          Genetic linkage maps of Eucalyptus grandis and Eucalyptus urophylla using a pseudo-testcross: mapping strategy and RAPD markers.

          We have used a "two-way pseudo-testcross" mapping strategy in combination with the random amplified polymorphic DNA (RAPD) assay to construct two moderate density genetic linkage maps for species of Eucalyptus. In the cross between two heterozygous individuals many single-dose RAPD markers will be heterozygous in one parent, null in the other and therefore segregate 1:1 in their F1 progeny following a testcross configuration. Meiosis and gametic segregation in each individual can be directly and efficiently analyzed using RAPD markers. We screened 305 primers of arbitrary sequence, and selected 151 to amplify a total of 558 markers. These markers were grouped at LOD 5.0, theta = 0.25, resulting in the maternal Eucalyptus grandis map having a total of 240 markers into 14 linkage groups (1552 cM) and the paternal Eucalyptus urophylla map with 251 markers in 11 linkage groups (1101 cM) (n = 11 in Eucalyptus). Framework maps ordered with a likelihood support > or = 1000:1 were assembled covering 95% of the estimated genome size in both individuals. Characterization of genome complexity of a sample of 48 mapped random amplified polymorphic DNA (RAPD) markers indicate that 53% amplify from low copy regions. These are the first reported high coverage linkage maps for any species of Eucalyptus and among the first for any hardwood tree species. We propose the combined use of RAPD markers and the pseudo-testcross configuration as a general strategy for the construction of single individual genetic linkage maps in outbred forest trees as well as in any highly heterozygous sexually reproducing living organisms. A survey of the occurrence of RAPD markers in different individuals suggests that the pseudo-testcross/RAPD mapping strategy should also be efficient at the intraspecific level and increasingly so with crosses of genetically divergent individuals. The ability to quickly construct single-tree genetic linkage maps in any forest species opens the way for a shift from the paradigm of a species index map to the heterodox proposal of constructing several maps for individual trees of a population, therefore mitigating the problem of linkage equilibrium between marker and trait loci for the application of marker assisted strategies in tree breeding.
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            Accuracy of Genomic Selection Methods in a Standard Data Set of Loblolly Pine (Pinus taeda L.)

            Genomic selection can increase genetic gain per generation through early selection. Genomic selection is expected to be particularly valuable for traits that are costly to phenotype and expressed late in the life cycle of long-lived species. Alternative approaches to genomic selection prediction models may perform differently for traits with distinct genetic properties. Here the performance of four different original methods of genomic selection that differ with respect to assumptions regarding distribution of marker effects, including (i) ridge regression–best linear unbiased prediction (RR–BLUP), (ii) Bayes A, (iii) Bayes Cπ, and (iv) Bayesian LASSO are presented. In addition, a modified RR–BLUP (RR–BLUP B) that utilizes a selected subset of markers was evaluated. The accuracy of these methods was compared across 17 traits with distinct heritabilities and genetic architectures, including growth, development, and disease-resistance properties, measured in a Pinus taeda (loblolly pine) training population of 951 individuals genotyped with 4853 SNPs. The predictive ability of the methods was evaluated using a 10-fold, cross-validation approach, and differed only marginally for most method/trait combinations. Interestingly, for fusiform rust disease-resistance traits, Bayes Cπ, Bayes A, and RR–BLUB B had higher predictive ability than RR–BLUP and Bayesian LASSO. Fusiform rust is controlled by few genes of large effect. A limitation of RR–BLUP is the assumption of equal contribution of all markers to the observed variation. However, RR-BLUP B performed equally well as the Bayesian approaches.The genotypic and phenotypic data used in this study are publically available for comparative analysis of genomic selection prediction models.
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              Genomic selection for growth and wood quality in Eucalyptus: capturing the missing heritability and accelerating breeding for complex traits in forest trees.

              • Genomic selection (GS) is expected to cause a paradigm shift in tree breeding by improving its speed and efficiency. By fitting all the genome-wide markers concurrently, GS can capture most of the 'missing heritability' of complex traits that quantitative trait locus (QTL) and association mapping classically fail to explain. Experimental support of GS is now required. • The effectiveness of GS was assessed in two unrelated Eucalyptus breeding populations with contrasting effective population sizes (N(e) = 11 and 51) genotyped with > 3000 DArT markers. Prediction models were developed for tree circumference and height growth, wood specific gravity and pulp yield using random regression best linear unbiased predictor (BLUP). • Accuracies of GS varied between 0.55 and 0.88, matching the accuracies achieved by conventional phenotypic selection. Substantial proportions (74-97%) of trait heritability were captured by fitting all genome-wide markers simultaneously. Genomic regions explaining trait variation largely coincided between populations, although GS models predicted poorly across populations, likely as a result of variable patterns of linkage disequilibrium, inconsistent allelic effects and genotype × environment interaction. • GS brings a new perspective to the understanding of quantitative trait variation in forest trees and provides a revolutionary tool for applied tree improvement. Nevertheless population-specific predictive models will likely drive the initial applications of GS in forest tree breeding. © 2012 The Authors. New Phytologist © 2012 New Phytologist Trust.
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                Author and article information

                Contributors
                Role: ND
                Role: ND
                Role: ND
                Role: ND
                Journal
                sa
                Scientia Agricola
                Sci. agric. (Piracicaba, Braz.)
                São Paulo - Escola Superior de Agricultura "Luiz de Queiroz"
                1678-992X
                April 2016
                : 73
                : 2
                : 142-149
                Affiliations
                [1 ] Universidade Estadual do Norte Fluminense Brazil
                [2 ] Embrapa Florestas Brazil
                [3 ] University of California United States
                Article
                S0103-90162016000200142
                10.1590/0103-9016-2014-0323
                4c844c6e-3c1e-44be-83d5-0c7b6b87b7af

                This work is licensed under a Creative Commons Attribution 4.0 International License.

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                SciELO Brazil

                Self URI (journal page): http://www.scielo.br/scielo.php?script=sci_serial&pid=0103-9016&lng=en
                Categories
                AGRICULTURE, MULTIDISCIPLINARY

                General agriculture
                MAS,SSR markers,linkage disequilibrium,genomic selection
                General agriculture
                MAS, SSR markers, linkage disequilibrium, genomic selection

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