Optimization of genomic selection training populations with a genetic algorithm, Genetics Selection Evolution, vol.88, issue.1, p.38, 2015. ,
DOI : 10.1093/biomet/88.1.53
URL : https://hal.archives-ouvertes.fr/hal-01312353
Genome-based prediction of testcross values in maize, Theoretical and Applied Genetics, vol.182, issue.2, pp.339-350, 2011. ,
DOI : 10.1534/genetics.108.098277
Genome-based prediction of maize hybrid performance across genetic groups, testers, locations, and years, Theoretical and Applied Genetics, vol.2, issue.6, pp.1375-1386, 2014. ,
DOI : 10.1534/g3.112.003699
Model training across multiple breeding cycles significantly improves genomic prediction accuracy in rye (Secale cereale L.), Theoretical and Applied Genetics, vol.134, issue.11, pp.2043-2053, 2016. ,
DOI : 10.1111/pbr.12231
URL : http://doi.org/10.1007/s00122-016-2756-5
Intraspecific variation of recombination rate in maize, Genome Biology, vol.14, issue.9, pp.10-1186, 2013. ,
DOI : 10.1101/gr.094052.109
Genomewide Selection when Major Genes Are Known, Crop Science, vol.54, issue.1, pp.68-75, 2014. ,
DOI : 10.2135/cropsci2013.05.0315
Improvement of Predictive Ability by Uniform Coverage of the Target Genetic Space, G3: Genes|Genomes|Genetics, vol.6, pp.3733-37437, 2016. ,
DOI : 10.1534/g3.116.035410
Single nucleotide polymorphism genotyping: biochemistry, protocol, cost and throughput, The Pharmacogenomics Journal, vol.3, issue.2, pp.77-96, 2003. ,
DOI : 10.1038/sj.tpj.6500167
Genomic selection prediction accuracy in a perennial crop: case study of oil palm (Elaeis guineensis Jacq.), Theoretical and Applied Genetics, vol.8, issue.3, pp.397-410, 2015. ,
DOI : 10.1007/s11295-012-0516-5
Genomic Prediction of Gene Bank Wheat Landraces, G3: Genes|Genomes|Genetics, vol.6, issue.7, pp.1819-1834, 2016. ,
DOI : 10.1534/g3.116.029637
Graph drawing by force-directed placement, Software: Practice and Experience, vol.41, issue.11, pp.1129-1164, 1991. ,
DOI : 10.1007/978-1-4613-1627-5
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.13.8444
A Large Maize (Zea mays L.) SNP Genotyping Array: Development and Germplasm Genotyping, and Genetic Mapping to Compare with the B73 Reference Genome, PLoS ONE, vol.21, issue.12, 2011. ,
DOI : 10.1371/journal.pone.0028334.s020
Linkage Disequilibrium with Linkage Analysis of Multiline Crosses Reveals Different Multiallelic QTL for Hybrid Performance in the Flint and Dent Heterotic Groups of Maize, Genetics, vol.198, issue.4, pp.1717-1734, 2014. ,
DOI : 10.1534/genetics.114.169367
The impact of genetic relationship information on genomic breeding values in German Holstein cattle, Genetics Selection Evolution, vol.42, issue.1, pp.5-10, 2010. ,
DOI : 10.1186/1297-9686-42-5
Invited review: Genomic selection in dairy cattle: Progress and challenges, Journal of Dairy Science, vol.92, issue.2, pp.433-443, 2009. ,
DOI : 10.3168/jds.2008-1646
Genomic selection in a commercial winter wheat population, Theoretical and Applied Genetics, vol.182, issue.3, pp.641-651, 2016. ,
DOI : 10.1534/genetics.108.098277
Genomic Selection for Crop Improvement, Crop Science, vol.49, issue.1, 2009. ,
DOI : 10.2135/cropsci2008.08.0512
URL : https://naldc.nal.usda.gov/naldc/download.xhtml?id=27989&content=PDF
Plant Breeding with Genomic Selection: Gain per Unit Time and Cost, Crop Science, vol.50, issue.5, 2010. ,
DOI : 10.2135/cropsci2009.11.0662
Applications of linear models in animal breeding, 1984. ,
An alternative covariance estimator to investigate genetic heterogeneity in populations, Genetics Selection Evolution, vol.8, issue.1, p.93, 2015. ,
DOI : 10.1371/journal.pone.0074612
URL : https://hal.archives-ouvertes.fr/hal-01341327
Genomic Selection in Plant Breeding: A Comparison of Models, Crop Science, vol.52, issue.1, 2012. ,
DOI : 10.2135/cropsci2011.06.0297
Training set optimization under population structure in genomic selection, Theoretical and Applied Genetics, vol.182, issue.7, pp.145-158, 2015. ,
DOI : 10.1534/genetics.108.098277
URL : http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4282691
Dynamics of long-term genomic selection, Genetics Selection Evolution, vol.42, issue.1, pp.35-45, 2010. ,
DOI : 10.1186/1297-9686-42-35
URL : http://doi.org/10.1186/1297-9686-42-35
Precision and information in linear models of genetic evaluation, Genetics Selection Evolution, vol.25, issue.6, pp.557-576, 1993. ,
DOI : 10.1186/1297-9686-25-6-557
L.) for Genome-Based Prediction, Genetics, vol.198, issue.1, pp.3-16, 2014. ,
DOI : 10.1534/genetics.114.161943
Assesment of genetic heterogeneity in structured plant populations using multivariate whole-genome regression models, Genetics, vol.201115, pp.323-337, 2015. ,
Adding Genetically Distant Individuals to Training Populations Reduces Genomic Prediction Accuracy in Barley, Crop Science, vol.55, issue.6, 2015. ,
DOI : 10.2135/cropsci2014.12.0827
Graph-Based Data Selection for the Construction of Genomic Prediction Models, Genetics, vol.185, issue.4, pp.1463-1475, 2010. ,
DOI : 10.1534/genetics.110.116426
Prediction of total genetic value using genome-wide dense marker maps, Genetics, vol.157, pp.1819-1829, 2001. ,
Shrinkage estimation of the genomic relationship matrix can improve genomic estimated breeding values in the training set, Theoretical and Applied Genetics, vol.128, issue.4, pp.693-703, 2015. ,
DOI : 10.1038/ng.608
Genotyping-by-Sequencing for Plant Breeding and Genetics, The Plant Genome Journal, vol.5, issue.3, pp.92-102, 2012. ,
DOI : 10.3835/plantgenome2012.05.0005
URL : https://dl.sciencesocieties.org/publications/tpg/pdfs/5/3/92
Reliability of direct genomic values for animals with different relationships within and to the reference population, Journal of Dairy Science, vol.95, issue.1, pp.389-400, 2012. ,
DOI : 10.3168/jds.2011-4338
On the Accuracy of Genomic Selection, PLOS ONE, vol.112, issue.6, 2016. ,
DOI : 10.1371/journal.pone.0156086.s004
Genomic Predictability of Interconnected Biparental Maize Populations, Genetics, vol.194, issue.2, pp.493-503, 2013. ,
DOI : 10.1534/genetics.113.150227
URL : http://www.genetics.org/content/genetics/194/2/493.full.pdf
Maximizing the Reliability of Genomic Selection by Optimizing the Calibration Set of Reference Individuals: Comparison of Methods in Two Diverse Groups of Maize Inbreds (Zea mays L.), Genetics, vol.192, issue.2, pp.715-728, 2012. ,
DOI : 10.1534/genetics.112.141473
URL : https://hal.archives-ouvertes.fr/hal-01019845
Recovering Power in Association Mapping Panels with Variable Levels of Linkage Disequilibrium, Genetics, vol.197, issue.1, pp.375-387, 2014. ,
DOI : 10.1534/genetics.113.159731
Dent and Flint maize diversity panels reveal important genetic potential for increasing biomass production, Theoretical and Applied Genetics, vol.38, issue.4, pp.2313-2331, 2014. ,
DOI : 10.1038/ng1702
URL : https://digital.csic.es/bitstream/10261/115360/1/accesoRestringido.pdf
Network analysis identifies weak and strong links in a metapopulation system, Proceedings of the National Academy of Sciences, vol.40, issue.25, 2008. ,
DOI : 10.2307/3033543
Efficient Use of Historical Data for Genomic Selection: A Case Study of Stem Rust Resistance in Wheat, The Plant Genome, vol.8, issue.1, 2015. ,
DOI : 10.3835/plantgenome2014.09.0046
Genomic Prediction in Pea: Effect of Marker Density and Training Population Size and Composition on Prediction Accuracy, Frontiers in Plant Science, vol.28, 2015. ,
DOI : 10.1093/bioinformatics/bts335
On-farm dynamic management of genetic diversity: the impact of seed diffusions and seed saving practices on a population-variety of bread wheat, Evolutionary Applications, vol.53, issue.8, pp.779-795, 2012. ,
DOI : 10.1007/s10722-005-4675-1
URL : https://hal.archives-ouvertes.fr/hal-01252156
Efficient Methods to Compute Genomic Predictions, Journal of Dairy Science, vol.91, issue.11, pp.4414-4423, 2008. ,
DOI : 10.3168/jds.2007-0980
The Effect of Linkage Disequilibrium and Family Relationships on the Reliability of Genomic Prediction, Genetics, vol.193, issue.2, pp.621-631, 2013. ,
DOI : 10.1534/genetics.112.146290
Empirical and deterministic accuracies of across-population genomic prediction, Genetics Selection Evolution, vol.47, issue.1, 2015. ,
DOI : 10.1186/1297-9686-42-9
URL : https://hal.archives-ouvertes.fr/hal-01341284
Genomic prediction contributing to a promising global strategy to turbocharge gene banks, Nature Plants, vol.157, issue.10, 2016. ,
DOI : 10.1186/1471-2105-12-186