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Pearl millet is a non-model grain and fodder crop adapted to extremely hot and dry environments globally. In India, a great deal of public and private sectors’ investment has focused on developing pearl millet single cross hybrids based on the cytoplasmic-genetic male sterility (CMS) system, while in Africa most pearl millet production relies on open pollinated varieties. Pearl millet lines were phenotyped for both the inbred parents and hybrids stage. Many breeding efforts focus on phenotypic selection of inbred parents to generate improved parental lines and hybrids. This study evaluated two genotyping techniques and four genomic selection schemes in pearl millet. Despite the fact that 6× more sequencing data were generated per sample for RAD-seq than for tGBS, tGBS yielded more than 2× as many informative SNPs (defined as those having MAF > 0.05) than RAD-seq. A genomic prediction scheme utilizing only data from hybrids generated prediction accuracies (median) ranging from 0.73-0.74 (1000-grain weight), 0.87-0.89 (days to flowering time), 0.48-0.51 (grain yield) and 0.72-0.73 (plant height). For traits with little to no heterosis, hybrid only and hybrid/inbred prediction schemes performed almost equivalently. For traits with significant mid-parent heterosis, the direct inclusion of phenotypic data from inbred lines significantly (P < 0.05) reduced prediction accuracy when all lines were analyzed together. However, when inbreds and hybrid trait values were both scored relative to the mean trait values for the respective populations, the inclusion of inbred phenotypic datasets moderately improved genomic predictions of the hybrid genomic estimated breeding values. Here we show that modern approaches to genotyping by sequencing can enable genomic selection in pearl millet. While historical pearl millet breeding records include a wealth of phenotypic data from inbred lines, we demonstrate that the naive incorporation of this data into a hybrid breeding program can reduce prediction accuracy, while controlling for the effects of heterosis per se allowed inbred genotype and trait data to improve the accuracy of genomic estimated breeding values for pearl millet hybrids.

Background Heat tolerance is becoming increasingly important where maize is grown under spring season in India which coincide with grain filling stage of crop resulting in tassel blast, reduced pollen viability, pollination failure and barren ears that causes devastating yield losses. So, there is need to identify the genomic regions associated with heat tolerance component traits which could be further employed in maize breeding program. Results An association mapping panel, consisting of 662 doubled haploid (DH) lines, was evaluated for yield contributing traits under normal and natural heat stress conditions. Genome wide association studies (GWAS) carried out using 187,000 SNPs and 130 SNPs significantly associated for grain yield (GY), days to 50% anthesis (AD), days to 50% silking (SD), anthesis-silking interval (ASI), plant height (PH), ear height (EH) and ear position (EPO) were identified under normal conditions. A total of 46 SNPs strongly associated with GY, ASI, EH and EPO were detected under heat stress conditions. Fifteen of the SNPs was found to have common association with more than one trait such as two SNPs viz. S10_1,905,273 and S10_1,905,274 showed colocalization with GY, PH and EH whereas S10_7,132,845 SNP associated with GY, AD and SD under normal conditions. No such colocalization of SNP markers with multiple traits was observed under heat stress conditions. Haplotypes trend regression analysis revealed 122 and 85 haplotype blocks, out of which, 20 and 6 haplotype blocks were associated with more than one trait under normal and heat stress conditions, respectively. Based on SNP association and haplotype mapping, nine and seven candidate genes were identified respectively, which belongs to different gene models having different biological functions in stress biology. Conclusions The present study identified significant SNPs and haplotype blocks associated with yield contributing traits that help in selection of donor lines with favorable alleles for multiple traits. These results provided insights of genetics of heat stress tolerance. The genomic regions detected in the present study need further validation before being applied in the breeding pipelines.

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Drought stress has severely hampered maize production, affecting the livelihood and economics of millions of people worldwide. In the future, as a result of climate change, unpredictable weather events will become more frequent hence the implementation of adaptive strategies will be inevitable. Through utilizing different genetic and breeding approaches, efforts are in progress to develop the drought tolerance in maize. The recent approaches of genomics-assisted breeding, transcriptomics, proteomics, transgenics, and genome editing have fast-tracked enhancement for drought stress tolerance under laboratory and field conditions. Drought stress tolerance in maize could be considerably improved by combining omics technologies with novel breeding methods and high-throughput phenotyping (HTP). This review focuses on maize responses against drought, as well as novel breeding and system biology approaches applied to better understand drought tolerance mechanisms and the development of drought-tolerant maize cultivars. Researchers must disentangle the molecular and physiological bases of drought tolerance features in order to increase maize yield. Therefore, the integrated investments in field-based HTP, system biology, and sophisticated breeding methodologies are expected to help increase and stabilize maize production in the face of climate change.

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Key message Pearl millet breeding programs can use this heterotic group information on seed and restorer parents to generate new series of pearl millet hybrids having higher yields than the existing hybrids. Abstract Five hundred and eighty hybrid parents, 320 R-and 260 B-lines, derived from 6 pearl millet breeding programs in India, genotyped following RAD-GBS (about 0.9 million SNPs) clustered into 12 R-and 7 B-line groups. With few exceptions, hybrid parents of all the breeding programs were found distributed across all the marker-based groups suggesting good diversity in these programs. Three hundred and twenty hybrids generated using 37 (22 R and 15 B) representative parents, evaluated for grain yield at four locations in India, showed significant differences in yield, heterosis, and combining ability. Across all the hybrids, mean mid-and better-parent heterosis for grain yield was 84.0% and 60.5%, respectively. Groups G12 B × G12 R and G10 B × G12 R had highest heterosis of about 10% over best check hybrid Pioneer 86M86. The parents involved in heterotic hybrids were mainly from the groups G4R, G10B, G12B, G12R, and G13B. Based on the heterotic performance and combining ability of groups, 2 B-line (HGB-1 and HGB-2) and 2 R-line (HGR-1 and HGR-2) heterotic groups were identified. Hybrids from HGB-1 × HGR-1 and HGB-2 × HGR-1 showed grain yield heterosis of 10.6 and 9.3%, respectively, over best hybrid check. Results indicated that parental groups can be formed first by molecular markers, which may not predict the best hybrid combination, but it can reveal a practical value of assigning existing and new hybrid pearl millet parental lines into heterotic groups to develop high-yielding hybrids from the different heterotic groups. Communicated by Alain Charcosset.

Most parts of the Asian tropics are hotspots of climate change effects and associated weather variabilities. One of the major challenges with climate change is the uncertainty and inter-annual variability in weather conditions as crops are frequently exposed to different weather extremes within the same season. Therefore, agricultural research must strive to develop new crop varieties with inbuilt resilience towards variable weather conditions rather than merely tolerance to individual stresses in a specific situation and/or at a specific crop stage. C4 crops are known for their wider adaptation to range of climatic conditions. However, recent climatic trends and associated variabilities seem to be challenging the threshold limit of wider adaptability of even C4 crops like maize. In collaboration with national programs and private sector partners in the region, CIMMYT-Asia maize program initiated research for development (R4D) projects largely focusing on saving achievable yields across range of variable environments by incorporating reasonable levels of tolerance/resistance to major abiotic and biotic stresses without compromising on grain yields under optimal growing conditions. By integrating novel breeding tools like - genomics, double haploid (DH) technology, precision phenotyping and reducing genotype × environment interaction effects, a new generation of maize germplasm with multiple stress tolerance that can grow well across variable weather conditions were developed. The new maize germplasm were targeted for stress-prone environments where maize is invariability exposed to a range of sub-optimal growing conditions, such as drought, heat, waterlogging and various virulent diseases. The overarching goal of the stress-resilient maize program has been to achieve yield potential with a downside risk reduction.