Mapping As You Go

By Dean W. Podlich, Christopher R. Winkler, Mark Cooper. 2004

164 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/37239108c4faf35e6b45303a41bf1bc13362276e

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In Genetics

In Plant Science

Citations in the corpus

Marker-assisted wheat breeding: present status and future possibilities (2010, unknown): “AB-QTL analysis and mapping-As-You-Go (MAYG) AB-QTL analysis and Mapping-As-You-Go (MAYG) are two novel marker-assisted approaches for crop breeding involving simultaneous QTL detection and MAS requiring no validation (Tanksley and Nelson 1996; Podlich et al. 2004).”
Genomic Selection Accuracy using Multifamily Prediction Models in a Wheat Breeding Program (2011, background): “…approach addresses the second limitation by re-estimating marker-eff ects in new breeding populations across target environments to capture changes in epistasis and G×E that will result from shift s in genetic backgrounds caused by selection (Podlich et al., 2004; Breseghello and Sorrells, 2006).”
Implementation of molecular markers for quantitative traits in breeding programs - challenges and opportunities (2004, background): “An added benefit of QTL effect updating should be improved gains from selection on epistatic QTL, since their effects depend on frequencies of alleles at other QTL, which will fluctuate over cycles of selection (Podlich et al. 2004).”
Marker-Assisted Selection in Plant Breeding: From Publications to Practice (2008, methodology): “Achieving this integration would rely on combining multiple approaches such as LD analysis of diverse genotypes, advanced backcross mapping (Tanksley and Nelson, 1996), and “mapping-asyou-go” (MAYG) (Podlich et al., 2004).”
Developments in breeding cereals for organic agriculture (2008, unknown): “Fortunately, methods are emerging that can improve the efficiency of selection for complex characters (Podlich et al. 2004) and provide a better understanding of the genetic architecture of such traits as observed across environments by incorporating QTL by Environment interactions (QxE).”
Applications of Linkage Disequilibrium and Association Mapping in Maize (2009, background): “Traditionally, genetic markers were mostly used for trait improvement through several breeding-based approaches, such as marker assisted selection (MAS), marker assisted breeding (MAB) and mapping as you go (MAYG) ( Podlich et al. 2004 ), as well as QTL”
Predicting the future of plant breeding: complementing empirical evaluation with genetic prediction (2014, background): “14a, Cooper et al. 2006; Podlich et al. 2004).”
Bayesian analysis of complex traits in pedigreed plant populations (2008, background): “…also means that it becomes feasible to utilize data from breeding programs and more importantly to accumulate data over time and to improve the accuracy of parameter estimates for QTL and polygenic background which likely improves the efficiency of the breeding program (Podlich et al. 2004).”
Model-assisted phenotyping and ideotype design (2015, methodology): “They used the aPSim-maize model (Keating et al., 2003) coupled to the breeding model QU-Gene (Podlich and Cooper, 1998; Podlich et al., 2004) to reveal interesting trajectories in maize breeding.”
Drought tolerance improvement in crop plants: An integrated view from breeding to genomics (2008, background): “The ‘‘Mapping As-You-Go’’ strategy (Podlich et al., 2004) involves repeated re-estimation and validation of the QTL effects throughout the breeding process to ensure that they remain relevant throughout.”
Molecular techniques in crop improvement (2002, background): “Therefore, when G × E and epistasis are important we should regularly re-estimate QTL effects within the breeding program (Podlich et al. 2004).”
Marker assisted selection in crop plants (2005, unknown): “…important traits (Breeding by design – Peleman and van der Voort, 2003), and selection schemes in which MAS operates by cyclically re-estimating the value of the QTL alleles each time a new set of germplasm is generated during the breeding process (Mapping as you go – Podlich et al., 2004).”