Optimized public databases for genomic prediction of tropical maize lines

Published: 7 October 2019| Version 1 | DOI: 10.17632/tpdnbh29jn.1
Pedro Patric Pinho Morais, Deniz Akdemir, Jean-Luc Jannink, Aluízio Borém, Roberto Fritsche-Neto


Throughout this dataset we proposed a hypothetical and realistic scenario in order to apply Genomic Selection (GS) - use of a limited budget and the need to increase genetic variability. To reach that we tested the feasibility of using genomic and phenotypic information from public databases for prediction of tropical maize inbred lines, seeking to identify how the population structure, the use of optimized training sets (OTS), and the amount of information coming from public databases affect the predictive ability. The results were encouraging, opening up possibilities to others replicate the same approach with different crops or dataset.



Cornell University, Universidade Federal de Vicosa, Universidade de Sao Paulo Escola Superior de Agricultura Luiz de Queiroz


Quantitative Genetics, Plant Breeding