Doubled-haploid lines (DHs) are normally produced from F1 plants in maize (Zea mays L.). Several studies have found a low frequency of recombinants in doubled haploids produced from F1 plants that could limit the selection response. Hence, an attempt was made to produce doubled haploids from the F2 generation to verify whether one more round of meiotic recombination could lead to increased genetic variability and assess the response to selection. The F1 and F2 plants of two cross-combinations, VL1043 × CM212 and VL121096 × CM202, were subjected to doubled-haploid production and evaluated in terms of their reaction to Fusarium stalk rot and yield traits along with F2 individuals of the same two crosses. There was significant variation in the number of DHs produced when F1 and F2 plants were subjected to DH production in the cross VL121096 × CM202. Furthermore, substantial genetic variability was observed among the DHs produced from the F1 generation (DHF1s), F2 generation (DHF2s), and F2s for Fusarium stalk rot (FSR) resistance. The genetic variance was more extensive in DHF2 compared to DHF1 plants in the cross VL1043 × CM212. Extreme candidate plants (highly resistant, resistant, and highly susceptible) were found in the F2 generation with a more standardized range than in the DHs. In the DH populations, the close correspondence between the phenotypic coefficient of variability (PCV) and the genotypic coefficient of variability (GCV) indicated less influence from the environment compared to the F2 plants. The heritability estimates in the DHs were greater than in the F2 plants of the VL1043 × CM212 cross, while in the VL121096 × CM202 cross, the heritability was almost the same between the DHs and F2 plants due to the relatively small population size of the DHs. The positively skewed leptokurtic distribution of the DH populations indicated the role of fewer genes, with the majority of them exhibiting complementary epistasis with decreasing effects in response to FSR. The mean estimated yield and genotypic variance in the top crosses produced from randomly chosen DHF1 and DHF2 plants of the cross VL1043 × CM212 were similar in magnitude.
Background: Northern corn leaf blight (NCLB) of maize caused by Exserohilum turcicum is a serious foliar disease. Resistance to NCLB is complexly inherited and the highly significant genotype x environment interaction effect makes selection of resistant genotypes difficult through conventional breeding methods. Hence an attempt was made to identify the genomic regions associated with NCLB resistance and perform genomic selection (GS) in two F2:3 populations derived from the crosses CM212 × MAI172 (Population-1) and CM202 × SKV50 (Population-2). Results: Two populations, each comprising of 366 progenies, were phenotyped at three different locations in the disease screening nurseries. Linkage analysis using 297 polymorphic SNPs in Population-1 and 290 polymorphic SNPs in Population-2 revealed 10 linkage groups spanning 3623.88cM and 4261.92cM with an average distance of 12.40 cM and 14.9 cM, respectively. Location-wise and pooled data across locations indicated that QTL expression was population and environment specific. The genomic prediction accuracies of 0.83 and 0.79 were achieved for NCLB Population 1 and Population 2, respectively. The resistant progenies from both populations were advanced to derive inbred lines and crossed with four different testers in line x tester mating design to test for their combining ability. High overall general combining ability was exhibited by 21 inbred lines. Among crosses 48 % were assigned high overall specific combining ability status. Out of 136 single crosses, seven recorded significant positive standard heterosis over the best check for grain yield. The clustering pattern of inbred lines developed from the two populations revealed high molecular diversity. Conclusions: In this study, comparatively better genomic prediction accuracies were achieved for NCLB and the worth of F3 progenies with high genomic predictions was proved by advancing them to derive inbred lines and establishing their higher combining ability for yield and yield related traits.
The most important applications of genomic selection (GS) in maize breeding is to predict and identify the best untested lines from biparental populations, when the training and validation sets are derived from the same cross. A total of 300 hybrids were generated using doubled haploid lines crossed to single known tester. The test hybrids and checks were evaluated for drought tolerance, grain yield and yield attributes under well‐watered (WW) and water stress at flowering (WSF) conditions during rabi 2018 at Hyderabad and Aurangabad locations. The study was further deep dived and practiced GS using 3352 single‐nucleotide polymorphism (SNP) markers. An extension of the genomic best linear unbiassed predictor that incorporates genotype × environment (GE) interaction was used to predict genotypic values; cross‐validation methods were applied to quantify prediction accuracy. Our results showed that the highest cross‐validation prediction accuracy for grain yield was 0.47 under WSF condition in TPS3, whereas under WW condition, prediction accuracy was 0.44 in TPS2, which is statistically on par with WSF condition. Among the secondary traits, the peak GS accuracies recorded for the traits anthesis silking interval (0.52) and ears per plant (0.48) under WSF. Under both the water regimes, anthesis silking interval and plant height recorded higher prediction accuracy when compared with grain yield. Hence, GS could be practiced for anthesis silking interval and ears per plant under stress condition in maize. Further while optimizing the population size, it was revealed from the study that increasing size of the population increases GS accuracy and TPS2 considered as optimum size of population for GS prediction.
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