02224naa a2200277 a 450000100080000000500110000800800410001902400540006010000200011424501320013426000090026652013800027565000130165565000190166865000270168765000220171465000240173670000250176070000190178570000240180470000180182870000190184670000190186570000190188477300430190321393252022-01-26 2021 bl uuuu u00u1 u #d7 ahttps://doi.org/10.1371/journal.pone.02436662DOI1 aOLIVEIRA, G. F. aQuantile regression in genomic selection for oligogenic traits in autogamous plantsba simulation study.h[electronic resource] c2021 aThis study assessed the efficiency of Genomic selection (GS) or genome‐wide selection (GWS), based on Regularized Quantile Regression (RQR), in the selection of genotypes to breed autogamous plant populations with oligogenic traits. To this end, simulated data of an F2 population were used, with traits with different heritability levels (0.10, 0.20 and 0.40), controlled by four genes. The generations were advanced (up to F6) at two selection intensities (10% and 20%). The genomic genetic value was computed by RQR for different quantiles (0.10, 0.50 and 0.90), and by the traditional GWS methods, specifically RR-BLUP and BLASSO. A second objective was to find the statistical methodology that allows the fastest fixation of favorable alleles. In general, the results of the RQR model were better than or equal to those of traditional GWS methodologies, achieving the fixation of favorable alleles in most of the evaluated scenarios. At a heritability level of 0.40 and a selection intensity of 10%, RQR (0.50) was the only methodology that fixed the alleles quickly, i.e., in the fourth generation. Thus, it was concluded that the application of RQR in plant breeding, to simulated autogamous plant populations with oligogenic traits, could reduce time and consequently costs, due to the reduction of selfing generations to fix alleles in the evaluated scenarios. aGenomics aPlant breeding aPlant selection guides aRegressão Linear aSeleção Genótipa1 aNASCIMENTO, A. C. C.1 aNASCIMENTO, M.1 aSANT'ANNA, I. de C.1 aROMERO, J. V.1 aAZEVEDO, C. F.1 aBHERING, L. L.1 aCAIXETA, E. T. tPlos Onegv. 16, n. 1, e0243666, 2021.