T. Nepolean

Genomic Selection for Drought Tolerance Using Genome-Wide SNPs in Maize

Traditional breeding strategies for selecting superior genotypes depending on phenotypic traits have proven to be of limited success, as this direct selection is hindered by low heritability, genetic interactions such as epistasis, environmental-genotype interactions, and polygenic effects. With the advent of new genomic tools, breeders have paved a way for selecting superior breeds. Genomic selection (GS) has emerged as one of the most important approaches for predicting genotype performance. Here, we tested the breeding values of 240 maize subtropical lines phenotyped for drought at different environments using 29,619 cured SNPs. Prediction accuracies of seven genomic selection models (ridge regression, LASSO, elastic net, random forest, reproducing kernel Hilbert space, Bayes A and Bayes B) were tested for their agronomic traits. Though prediction accuracies of Bayes B, Bayes A and RKHS were comparable, Bayes B outperformed the other models by predicting highest Pearson correlation coefficient in all three environments. From Bayes B, a set of the top 1053 significant SNPs with higher marker effects was selected across all datasets to validate the genes and QTLs. Out of these 1053 SNPs, 77 SNPs associated with 10 drought-responsive transcription factors. These transcription factors were associated with different physiological and molecular functions (stomatal closure, root development, hormonal signaling and photosynthesis). Of several models, Bayes B has been shown to have the highest level of prediction accuracy for our data sets. Our experiments also highlighted several SNPs based on their performance and relative importance to drought tolerance. The result of our experiments is important for the selection of superior genotypes and candidate genes for breeding drought-tolerant maize hybrids.

Identification, Characterization, and Functional Validation of Drought-responsive MicroRNAs in Subtropical Maize Inbreds

MicroRNA-mediated gene regulation plays a crucial role in controlling drought tolerance. In the present investigation, 13 drought-associated miRNA families consisting of 65 members and regulating 42 unique target mRNAs were identified from drought-associated microarray expression data in maize and were subjected to structural and functional characterization. The largest number of members (14) was found in the zma-miR166 and zma-miR395 families, with several targets. However, zma-miR160, zma-miR390, zma-miR393, and zma-miR2275 each showed a single target. Twenty-three major drought-responsive cis-regulatory elements were found in the upstream regions of miRNAs. Many drought-related transcription factors, such as GAMYB, HD-Zip III, and NAC, were associated with the target mRNAs. Furthermore, two contrasting subtropical maize genotypes (tolerant: HKI-1532 and sensitive: V-372) were used to understand the miRNA-assisted regulation of target mRNA under drought stress. Approximately 35 and 31% of miRNAs were up-regulated in HKI-1532 and V-372, respectively. The up-regulation of target mRNAs was as high as 14.2% in HKI-1532 but was only 2.38% in V-372. The expression patterns of miRNA-target mRNA pairs were classified into four different types: Type I- up-regulation, Type II- down-regulation, Type III- neutral regulation, and Type IV- opposite regulation. HKI-1532 displayed 46 Type I, 13 Type II, and 23 Type III patterns, whereas V-372 had mostly Type IV interactions (151). A low level of negative regulations of miRNA associated with a higher level of mRNA activity in the tolerant genotype helped to maintain crucial biological functions such as ABA signaling, the auxin response pathway, the light-responsive pathway and endosperm expression under stress conditions, thereby leading to drought tolerance. Our study identified candidate miRNAs and mRNAs operating in important pathways under drought stress conditions, and these candidates will be useful in the development of drought-tolerant maize hybrids.

Molecular characterization and assessment of genetic diversity of inbred lines showing variability for drought tolerance in maize

A set of 24 genotypes bred at different centres in India as well as in CIMMYT showing variability for drought tolerance were selected for molecular and morpho-physiological characterization. A set of 35 SSR markers, having genome-wide coverage, was chosen for genotyping the inbreds. These markers generated a total of 111 polymorphic alleles with an average of 3.17 alleles per locus. The minimum and maximum PIC value was 0.27 and 0.77 with a mean of 0.5. A total of 13 unique alleles were found in the 24 inbred lines. The coefficient of genetic dissimilarity ranged from 0.192 to 0.803. NJ-based tree suggested the presence of three major clusters of which, two of them had subgroups. Phenotyping of inbreds by morpho-physiological traits revealed that there was a positive relationship among root length, chlorophyll content, relative water content while anthesis-silking interval was negative relationship with all these traits. Genotyping data complemented by morpho-physiological parameters were used to identify a number of pair-wise combinations for the development of mapping population segregating for drought tolerance and potential heterotic pairs for the development of drought tolerant hybrids.

Understanding Genetic and Molecular Bases of Fe and Zn Accumulation Towards Development of Micronutrient-Enriched Maize

Micronutrient malnutrition is a global problem afflicting billions of people worldwide. The effects are more prevalent in developing countries where people rely upon cereal-based diets that are inherently deficient in micronutrients. Micronutrients are required in less quantity but play critical role in the growth and development of humans. Since human body cannot synthesize micronutrients, they must be made available through diet. Among micronutrients, deficiency of iron (Fe) and zinc (Zn) has profound effects and require urgent attention. Development of micronutrient-rich staple plant foods through plant breeding, a process referred to as “biofortification,” holds promise for sustainable food-based solutions to combat micronutrient deficiency. Maize is the third most important crop of the world, serving as staple food to billions of people in sub-Saharan Africa, Latin America and Asia. The development of Fe- and Zn-rich maize cultivar(s) would therefore have positive effects on health and well-being of humans. Wide variability has been reported for Fe and Zn in maize, which can be explored for genetic improvement of the trait. Genetics of Fe and Zn has been well elucidated, and genes/QTLs governing high Fe and Zn accumulation in maize have been identified. Moreover, by targeting the genes involved in Fe and Zn uptake, transportation and translocation, concentration of the same can be increased in the maize endosperm. Further, manipulating genes for promoter and antinutritional factors, bioavailability of Fe and Zn can be enhanced. Quality protein maize (QPM) genotype reported to have higher concentration of Fe and Zn provides opportunity to develop multinutrient-rich maize through a systematic breeding approach. We discussed here available genetic variation for Fe and Zn and their interactions with environments, relationship among micronutrients and grain yield, summary of research efforts with specific emphasis on mechanism of uptake and translocation, genetic and molecular basis of Fe and Zn accumulation, and the strategies that can be explored to breed for high Fe and Zn maize.

Quantitative trait loci associated with constitutive traits control water use in pearl millet [Pennisetum glaucum (L.) R. Br.]

There is substantial genetic variation for drought adaption in pearl millet in terms of traits controlling plant water use. It is important to understand genomic regions responsible for these traits. Here, F7 recombinant inbred lines were used to identify quantitative trait loci (QTL) and allelic interactions for traits affecting plant water use, and their relevance is discussed for crop productivity in water-limited environments. Four QTL contributed to increased transpiration rate under high vapour pressure deficit (VPD) conditions, all with alleles from drought-sensitive parent ICMB 841. Of these four QTL, a major QTL (35.7%) was mapped on linkage group (LG) 6. The alleles for 863B at this QTL decreased transpiration rate and this QTL co-mapped to a previously detected LG 6 QTL, with alleles from 863B for grain weight and panicle harvest index across severe terminal drought stress environments. This provided additional support for a link between water saving from a lower transpiration rate under high VPD and drought tolerance. 863B alleles in this same genomic region also increased shoot weight, leaf area and total transpiration under well-watered conditions. One unexpected outcome was reduced transpiration under high VPD (15%) from the interaction of two alleles for high VPD transpiration (LG 6 (B), 40.7) and specific leaf mass and biomass (LG 7 (A), 35.3), (A, allele from ICMB 841, B, allele from 863B, marker position). The LG 6 QTL appears to combine alleles for growth potential, beneficial for non-stress conditions, and for saving water under high evaporative demand, beneficial under stressful conditions. Mapping QTL for water-use traits, and assessing their interactions offers considerable potential for improving pearl millet adaptation to specific stress conditions through physiology-informed marker-assisted selection.

Deciphering Genomic Regions for High Grain Iron and Zinc Content Using Association Mapping in Pearl Millet

Micronutrient malnutrition, especially deficiency of two mineral elements, iron [Fe] and zinc [Zn] in the developing world needs urgent attention. Pearl millet is one of the best crops with many nutritional properties and is accessible to the poor. We report findings of the first attempt to mine favorable alleles for grain iron and zinc content through association mapping in pearl millet. An association mapping panel of 130 diverse lines was evaluated at Delhi, Jodhpur and Dharwad, representing all the three pearl millet growing agro-climatic zones of India, during 2014 and 2015. Wide range of variation was observed for grain iron (32.3–111.9 ppm) and zinc (26.6–73.7 ppm) content. Genotyping with 114 representative polymorphic SSRs revealed 0.35 mean gene diversity. STRUCTURE analysis revealed presence of three sub-populations which was further supported by Neighbor-Joining method of clustering and principal coordinate analysis (PCoA). Marker-trait associations (MTAs) were analyzed with 267 markers (250 SSRs and 17 genic markers) in both general linear model (GLM) and mixed linear model (MLM), however, MTAs resulting from MLM were considered for more robustness of the associations. After appropriate Bonferroni correction, Xpsmp 2261 (13.34% R2-value), Xipes 0180 (R2-value of 11.40%) and Xipes 0096 (R2-value of 11.38%) were consistently associated with grain iron and zinc content for all the three locations. Favorable alleles and promising lines were identified for across and specific environments. PPMI 1102 had highest number (7) of favorable alleles, followed by four each for PPMFeZMP 199 and PPMI 708 for across the environment performance for both grain Fe and Zn content, while PPMI 1104 had alleles specific to Dharwad for grain Fe and Zn content. When compared with the reference genome Tift 23D2B1-P1-P5, Xpsmp 2261 amplicon was identified in intergenic region on pseudomolecule 5, while the other marker, Xipes 0810 was observed to be overlapping with aspartic proteinase (Asp) gene on pseudomolecule 3. Thus, this study can help in breeding new lines with enhanced micronutrient content using marker-assisted selection (MAS) in pearl millet leading to improved well-being especially for women and children.

Variable Level of Dominance of Candidate Genes Controlling Drought Functional Traits in Maize Hybrids

Breeding maize for drought tolerance necessitates the knowledge on tolerant genotypes, molecular basis of drought tolerance mechanism, action, and expression pattern of genes. Studying the expression pattern and gene action of candidate genes during drought stress in the hybrids will help in choosing target genes for drought tolerance breeding. In the present investigation, a set of five hybrids and their seven parents with a variable level of tolerance to drought stress was selected to study the magnitude and the direction of 52 drought-responsive candidate genes distributed across various biological functions, viz., stomatal regulation, root development, detoxification, hormone signaling, photosynthesis, and sugar metabolism. The tolerant parents, HKI1105 and CML425, and their hybrid, ADWLH2, were physiologically active under drought stress, since vital parameters viz., chlorophyll, root length and relative water content, were on par with the respective well-watered control. All the genes were up-regulated in ADWLH2, many were down-regulated in HM8 and HM9, and most were down-regulated in PMH1 and PMH3 in the shoots and roots. The nature of the gene action was controlled by the parental combination rather than the parent per se. The differentially expressed genes in all five hybrids explained a mostly non-additive gene action over additivity, which was skewed toward any of the parental lines. Tissue-specific gene action was also noticed in many of the genes. The non-additive gene action is driven by genetic diversity, allele polymorphism, events during gene regulation, and small RNAs under the stress condition. Differential regulation and cross-talk of genes controlling various biological functions explained the basis of drought tolerance in subtropical maize hybrids. The nature of the gene action and the direction of the expression play crucial roles in designing introgression and hybrid breeding programmes to breed drought tolerant maize hybrids.

Genetic variability and correlation of kernel micronutrients among exotic quality protein maize inbreds and their utility in breeding programme

Micronutrient malnutrition is a widespread problem known to affect millions of children and women. However, the adverse effects of micronutrient deficiency can be overcome through self-targeting, cost-effective and sustainable genetic biofortification approach, which is mainly based on staple food crops. Since maize has emerged as a prominent future crop especially for India, developing maize hybrids that are rich in kernel micronutrients will help in reducing the problems of micronutrient malnutrition. Here, we report variability of kernel Fe and Zn in 120 exotic Quality Protein Maize (QPM) inbreds and kernel Mn and Cu in a representative subset of 68 lines. A wide range of genetic variation was found among genotypes for all the kernel micronutrients: Fe (16.6–83.4 ppm), Zn (16.4–53.2 ppm), Mn (1.7–34.8 ppm) and Cu (0.5–9.5 ppm). Higher mean for kernel Fe and Zn in QPM inbreds suggests possible influence of opaque2 gene and/or modifiers present in them. Significant and positive correlation was observed among kernel Fe, Zn, Mn and Cu. Genetic diversity based on all four micronutrients grouped 68 lines into three major clusters with a mean coefficient of genetic dissimilarity of 2.46. Parental combinations were selected from different heterotic pools and maturity groups to develop high-yielding hybrids enriched with micronutrients.

Mapping QTLs Controlling Flowering Time and Important Agronomic Traits in Pearl Millet

Pearl millet [Pennisetum glaucum (L.) R. Br.] is a staple crop for the people of arid and semi-arid regions of the world. It is fast gaining importance as a climate resilient nutricereal. Exploiting the bold seeded, semi-dwarf, and early flowering genotypes in pearl millet is a key breeding strategy to enhance yield, adaptability, and for adequate food in resource-poor zones. Genetic variation for agronomic traits of pearl millet inbreds can be used to dissect complex traits through quantitative trait locus (QTL) mapping. This study was undertaken to map a set of agronomically important traits like flowering time (FT), plant height (PH), panicle length (PL), and grain weight (self and open-pollinated seeds) in the recombinant inbred line (RIL) population of ICMB 841-P3 × 863B-P2 cross. Excluding grain weight (open pollinated), heritabilities for FT, PH, PL, grain weight (selfed) were in high to medium range. A total of six QTLs for FT were detected on five chromosomes, 13 QTLs for PH on six chromosomes, 11 QTLs for PL on five chromosomes, and 14 QTLs for 1,000-grain weight (TGW) spanning five chromosomes. One major QTL on LG3 was common for FT and PH. Three major QTLs for PL, one each on LG1, LG2, and LG6B were detected. The large effect QTL for TGW (self) on LG6B had a phenotypic variance (R2) of 62.1%. The R2 for FT, TGW (self), and PL ranged from 22.3 to 59.4%. A total of 21 digenic interactions were discovered for FT (R2 = 18–40%) and PL (R2 = 13–19%). The epistatic effects did not reveal any significant QTL × QTL × environment (QQE) interactions. The mapped QTLs for flowering time and other agronomic traits in present experiment can be used for marker-assisted selection (MAS) and genomic selection (GS) breeding programs.

Mapping Grain Iron and Zinc Content Quantitative Trait Loci in an Iniadi-Derived Immortal Population of Pearl Millet

Pearl millet is a climate-resilient nutritious crop requiring low inputs and is capable of giving economic returns in marginal agro-ecologies. In this study, we report large-effect iron (Fe) and zinc (Zn) content quantitative trait loci (QTLs) using diversity array technology (DArT) and simple sequence repeats (SSRs) markers to generate a genetic linkage map using 317 recombinant inbred line (RIL) population derived from the (ICMS 8511-S1-17-2-1-1-B-P03 × AIMP 92901-S1-183-2-2-B-08) cross. The base map [seven linkage groups (LGs)] of 196 loci was 964.2 cM in length (Haldane). AIMP 92901-S1-183-2-2-B-08 is an Iniadi line with high grain Fe and Zn, tracing its origin to the Togolese Republic, West Africa. The content of grain Fe in the RIL population ranged between 20 and 131 ppm (parts per million), and that of Zn from 18 to 110 ppm. QTL analysis revealed a large number of QTLs for high grain iron (Fe) and zinc (Zn) content. A total of 19 QTLs for Fe and Zn were detected, of which 11 were for Fe and eight were for Zn. The portion of the observed phenotypic variance explained by different QTLs for grain Fe and Zn content varied from 9.0 to 31.9% (cumulative 74%) and from 9.4 to 30.4% (cumulative 65%), respectively. Three large-effect QTLs for both minerals were co-mapped in this population, one on LG1 and two on LG7. The favorable QTL alleles of both mineral micronutrients were contributed by the male parent (AIMP 92901-deriv-08). Three putative epistasis interactions were observed for Fe content, while a single digenic interaction was found for Zn content. The reported QTLs may be useful in marker-assisted selection (MAS) programs, in genomic selection (GS) breeding pipelines for seed and restorer parents, and in population improvement programs for pearl millet.