Genomic Selection Outperforms Marker Assisted Selection for Grain Yield and Physiological Traits in a Maize Doubled Haploid Population Across Water Treatments

Abstract

To increase genetic gain for tolerance to drought, we aimed to identify environmentally stable QTL in per se and testcross combination under well-watered (WW) and drought stressed (DS) conditions and evaluate the possible deployment of QTL using marker assisted and/or genomic selection (QTL/GS-MAS). A total of 169 doubled haploid lines derived from the cross between CML495 and LPSC7F64 and 190 testcrosses (tester CML494) were evaluated in a total of 11 treatment-by-population combinations under WW and DS conditions. In response to DS, grain yield (GY) and plant height (PHT) were reduced while time to anthesis and the anthesis silking interval (ASI) increased for both lines and hybrids. Forty-eight QTL were detected for a total of nine traits. The allele derived from CML495 generally increased trait values for anthesis, ASI, PHT, the normalized difference vegetative index (NDVI) and the green leaf area duration (GLAD; a composite trait of NDVI, PHT and senescence) while it reduced trait values for leaf rolling and senescence. The LOD scores for all detected QTL ranged from 2.0 to 7.2 explaining 4.4 to 19.4% of the observed phenotypic variance with R2 ranging from 0 (GY, DS, lines) to 37.3% (PHT, WW, lines). Prediction accuracy of the model used for genomic selection was generally higher than phenotypic variance explained by the sum of QTL for individual traits indicative of the polygenic control of traits evaluated here. We therefore propose to use QTL-MAS in forward breeding to enrich the allelic frequency for a few desired traits with strong additive QTL in early selection cycles while GS-MAS could be used in more mature breeding programs to additionally capture alleles with smaller additive effects.

Evaluation of genomic selection and marker-assisted selection in Miscanthus and energycane

“…The comparison of GS to MAS has been the subject of previous studies in various crop species, including maize (Massman et al 2013;Owens et al 2014;Cao et al 2017;Cerrudo et al 2018), wheat (Arruda et al 2015), rye (Wang et al 2014), and cowpea (Olatoye et al 2019). The results of this prior work was consistent with the simulation study conducted by Bernardo and Yu (2007) in that the number of underlying causal mutations, their effect sizes, and the heritability of the studied traits have a major influence on MAS and GS performance.…”

Genetic mapping and genomic selection for maize stalk strength

“…Genomic selection has been recognized as an efficient approach to select for complex traits in comparison with conventional marker-assisted selection [37,38,56,57]. In the present study, the prediction accuracy estimated in each stage and population was obviously different when the UV model was used to perform crossvalidation, which was likely attributed to the different estimates of broad-sense heritability in various situations.…”

Genetic mapping and genomic selection for maize stalk strength

“…Genomic selection has been recognized as an efficient approach to select for complex traits in comparison with conventional marker-assisted selection [36,37,55,56]. In the present study, the prediction accuracy estimated in each stage and population was obviously different when the UV model was used to perform cross-validation, which was likely attributed to the different estimates of broad-sense heritability in various situations.…”