Genomic Selection in Plant Breeding

By A. Lorenz, S. Chao, Franco G. Asoro, E. Heffner, Takeshi Hayashi, Hiroyoshi Iwata, Kevin P. Smith, M. Sorrells, Jean-Luc Jannink. 2011

421 citations recorded by the source corpus.

Subfields: Genetics, Plant Science

View Paper: https://www.semanticscholar.org/paper/04297e23e9658067136304452dd9f6114b870ab1

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Citations in the corpus

Achievements and Challenges in Improving Temperate Perennial Forage Legumes (2015, background): “Genomic selection (GS) (also known as “whole-genome selection”) (Heffner et al., 2009; Jannink et al., 2010; Lorenz et al., 2011; Hayes et al., 2013) is based on the premise that markers saturating the entire genome can reliably provide an estimate, in aggregate, of the breeding value of an individu”
Development of genome-wide SNP assays for rice (2010, background): “…used in breeding programs for markerassisted and genomic selection, association and QTL mapping, positional cloning, haplotype and pedigree analysis, seed purity testing and variety identification (Bernardo 2008, Eathington et al. 2007, Jannink et al. 2010, Lorenz et al. 2010, Moose and Mumm 2008).”
Evaluation of genomic selection training population designs and genotyping strategies in plant breeding programs using simulation (2014, background): “Genomic selection offers new opportunities for increasing the efficiency of plant breeding programs (e.g., Bernardo and Yu, 2007; Heffner et al., 2009; Crossa et al., 2010; Lorenz et al., 2011).”
Evaluation of Genomic Prediction Methods for Fusarium Head Blight Resistance in Wheat (2012, methodology): “For a detailed description of RR, BL, and RKHS methods refer to Lorenz et al. (2011).”
Genomic Selection in Plant Breeding: A Comparison of Models (2012, background): “Several recent reviews are available on GS in plant breeding, in particular Heff ner et al. (2009), Jannink et al. (2010), Xu and Hu (2010), and Lorenz et al. (2011).”
Genomic Selection Accuracy using Multifamily Prediction Models in a Wheat Breeding Program (2011, background): “Th e diminishing return from increasing NM has been seen in other empirical studies (Lorenzana and Bernardo, 2009; VanRaden et al., 2009; Lorenz et al., 2011; Heff ner et al., unpublished data, 2010) and suggests the advantage of high NM will be realized only if NTP scales with NM (Muir, 2007).”
Research Advances in Mechanisms of Turfgrass Tolerance to Abiotic Stresses: From Physiology to Molecular Biology (2014, background): “…such as high throughput technologies, greater availability of data for detection of synteny, and several recent successes in fine mapping have allowed QTL detection and genomic selection utilizing markers to be considered an effective means in molecular-assisted breeding (Lorenz et al., 2011).”
Accuracy of Genomewide Selection for Different Traits with Constant Population Size, Heritability, and Number of Markers (2013, background): “, 2012), and as the number of QTL decreases (Zhong et al., 2009; Grattapaglia et al., 2009; Lorenz et al., 2011).”
Genomic Prediction of Hybrid Wheat Performance (2013, methodology): “Therefore, RR-BLUP can be interpreted as an approximation of the infinitesimal model (Lorenz et al., 2011).”
Accuracy and Training Population Design for Genomic Selection on Quantitative Traits in Elite North American Oats (2011, background): “In GS, while population structure is still relevant, the focus shift s to maintaining the accuracy across diff erent subpopulations or germplasm groupings (Lorenz et al., 2011).”