Parental genome contribution in maize DH lines derived from six backcross populations using genotyping by sequencing

Abstract

Molecular characterization of doubled haploid (DH) maize lines and estimation of parental genome contribution (PGC) may be useful for choosing pairs of DH lines for hybrid make up and new pedigree starts. Six BC1-derived DH populations created by crossing two donor with three recurrent parents were genotyped with 97,190 polymorphic markers with the objectives of: (i) understanding genetic purity, genetic distance and relationship among 417 maize DH lines; (ii) estimating PGC of the DH lines derived from different genetic backgrounds; and (iii) understanding the correlation between donor parent introgression and testcross performance for grain yield and anthesis-silking interval (ASI) under managed drought and optimum environments. The DH lines were 97 % genetically pure, with 5 %, which is likely to be due to errors during seed multiplication or maintenance. Genetic distance between pairwise comparisons of the 417 DH lines ranged from 0.055 to 0.457; only 0.01 % showed a genetic distance <0.100, indicating large genetic differences among the DH lines. Both populations 1 and 6 showed significantly lower (p < 0.001) donor introgression than the other four populations. Donor parent contribution was significantly (p < 0.001) higher in the CML444 genetic background than CML395 and CML488. The average donor and recurrent PGC across all 417 DH lines was 31.7 and 64.3 %, respectively. Donor genome introgression was higher than expected in 82 % of the DH lines in the BC1 generation, possibly due to artificial selection during the DH process, during the development of F1 or BC1 seed, or during initial agronomic evaluation of the DH lines. Donor parent introgression up to 32 % showed significant positive correlation with grain yield under drought (r = 0.312, p < 0.001) and optimum (r = 0.142, p < 0.050) environments but negative correlation with ASI under drought (r = −0.276, p < 0.001). Additional multi-environment phenotype data under managed drought are needed to confirm the correlations reported in this study and to map the specific genomic regions associated with such correlations.