More than 80% of the 19 million ha of maize (Zea mays L.) in tropical Asia is rainfed and prone to drought. The breeding methods for improving drought tolerance (DT), including genomic selection (GS), are geared to increase the frequency of favorable alleles. Two biparental populations (CIMMYTAsia Population 1 [CAP1] and CAP2) were generated by crossing elite Asian-adapted yellow inbreds (CML470 and VL1012767) with an African white drought-tolerant line, CML444. Marker effects of polymorphic single-nucleotide polymorphisms (SNPs) were determined from testcross (TC) performance of F 2:3 families under drought and optimal conditions. Cycle 1 (C1) was formed by recombining the top 10% of the F 2:3 families based on TC data. Subsequently, (i) C2 [PerSe_PS] was derived by recombining those C1 plants that exhibited superior per se phenotypes (phenotype-only selection), and (ii) C2[TC-GS] was derived by recombining a second set of C1 plants with high genomic estimated breeding values (GEBVs) derived from TC phenotypes of F 2:3 families (marker-only selection). All the generations and their top crosses to testers were evaluated under drought and optimal conditions. Per se grain yields (GYs) of C2 [PerSe_PS] and that of C2[TC-GS] were 23 to 39 and 31 to 53% better, respectively, than that of the corresponding F 2 population. The C2[TC-GS] populations showed superiority of 10 to 20% over C2[PerSe-PS] of respective populations. Top crosses of C2[TC-GS] showed 4 to 43% superiority of GY over that of C2[PerSe_PS] of respective populations. Thus, GEBV-enabled selection of superior phenotypes (without the target stress) resulted in rapid genetic gains for DT.

With progressive climate change and the associated increase in mean temperature, heat stress tolerance has emerged as one of the key traits in the product profile of the maize breeding pipeline for lowland tropics. The present study aims to identify the genomic regions associated with heat stress tolerance in tropical maize. An association mapping panel, called the heat tolerant association mapping (HTAM) panel, was constituted by involving a total of 543 tropical maize inbred lines from diverse genetic backgrounds, test-crossed and phenotyped across nine locations in South Asia under natural heat stress. The panel was genotyped using a genotyping-by-sequencing (GBS) platform. Considering the large variations in vapor pressure deficit (VPD) at high temperature (Tmax) across different phenotyping locations, genome-wide association study (GWAS) was conducted separately for each location. The individual location GWAS identified a total of 269 novel significant single nucleotide polymorphisms (SNPs) for grain yield under heat stress at a p value of < 10–5. A total of 175 SNPs were found in 140 unique gene models implicated in various biological pathway responses to different abiotic stresses. Haplotype trend regression (HTR) analysis of the significant SNPs identified 26 haplotype blocks and 96 single SNP variants significant across one to five locations. The genomic regions identified based on GWAS and HTR analysis considering genomic region x environment interactions are useful for breeding efforts aimed at developing heat stress resilient maize cultivars for current and future climatic conditions through marker-assisted introgression into elite genetic backgrounds and/or genome-wide selection.

Rapid cycle genomic selection (RC-GS) helps to shorten the breeding cycle and reduce the costs of phenotyping, thereby increasing genetic gains in terms of both cost and time. We implemented RC-GS on two multi-parent yellow synthetic (MYS) populations constituted by intermating ten elite lines involved in each population, including four each of drought and waterlogging tolerant donors and two commercial lines, with proven commercial value. Cycle 1 (C 1) was constituted based on phenotypic selection and intermating of the top 5% of 500 S 2 families derived from each MYS population, test-crossed and evaluated across moisture regimes. C 1 was advanced to the next two cycles (C 2 and C 3) by intermating the top 5% selected individuals with high genomic estimated breeding values (GEBVs) for grain yield under drought and waterlogging stress. To estimate genetic gains, population bulks from each cycle were test-crossed and evaluated across locations under different moisture regimes. Results indicated that the realised genetic gain under drought stress was 0.110 t ha −1 yr −1 and 0.135 t ha −1 yr −1 , respectively, for MYS-1 and MYS-2. The gain was less under waterlogging stress, where MYS-1 showed 0.038 t ha −1 yr −1 and MYS-2 reached 0.113 t ha −1 yr −1. Genomic selection for drought and waterlogging tolerance resulted in no yield penalty under optimal moisture conditions. The genetic diversity of the two populations did not change significantly after two cycles of GS, suggesting that RC-GS can be an effective breeding strategy to achieve high genetic gains without losing genetic diversity.