Maize Populations Research Articles

Calibration and validation of predicted genomic breeding values in an advanced cycle maize population

Key messageModel training on data from all selection cycles yielded the highest prediction accuracy by attenuating specific effects of individual cycles. Expected reliability was a robust predictor of accuracies obtained with different calibration sets.The transition from phenotypic to genome-based selection requires a profound understanding of factors that determine genomic prediction accuracy. We analysed experimental data from a commercial maize breeding programme to investigate if genomic measures can assist in identifying optimal calibration sets for model training. The data set consisted of six contiguous selection cycles comprising testcrosses of 5968 doubled haploid lines genotyped with a minimum of 12,000 SNP markers. We evaluated genomic prediction accuracies in two independent prediction sets in combination with calibration sets differing in sample size and genomic measures (effective sample size, average maximum kinship, expected reliability, number of common polymorphic SNPs and linkage phase similarity). Our results indicate that across selection cycles prediction accuracies were as high as 0.57 for grain dry matter yield and 0.76 for grain dry matter content. Including data from all selection cycles in model training yielded the best results because interactions between calibration and prediction sets as well as the effects of different testers and specific years were attenuated. Among genomic measures, the expected reliability of genomic breeding values was the best predictor of empirical accuracies obtained with different calibration sets. For grain yield, a large difference between expected and empirical reliability was observed in one prediction set. We propose to use this difference as guidance for determining the weight phenotypic data of a given selection cycle should receive in model retraining and for selection when both genomic breeding values and phenotypes are available.

EARLYTROP: A PROGRAM TO ADAPT 100% TROPICAL MAIZE GERMPLASM TO SHORT-SEASON ENVIRONMENTS

Tropical maize germplasm can contribute useful and unique genes. It can provide greater resistance to pests and diseases, better quality crops, and trait genes and combinations not often present in commercially available northern U.S. temperate hybrids. Uniform farmer fields with genetically identical hybrids have a high risk of genetic vulnerabilities due to disease epidemics and abiotic stresses, especially after the recent major industry mergers. The EarlyTROP program was created with the long-term goal to increase the genetic diversity of short-season maize carrying 100% tropical germplasm. Five tropical maize populations were assessed for adaptation to ND short-season environments: NDSHLC (an improved composite from highland Mexico), BS16 (an improved strain of ETO from Colombia), BS28 (an improved strain of Tuxpeño from Mexico), BS29 (an improved strain of Suwan-1 from Thailand), and BS39 (an improved strain of Tusón mainly from Brazil and Cuba). The program conducted three cycles of stratified mass selection for days to silking near Casselton and Prosper, ND for all varieties except for NDSHLC, which had six selection cycles of stratified mass selection. Selected populations (NDHighland, NDEto, NDTuxpeño, NDSuwan-1, and NDTusón), and 31 checks including standard known and commercialized population and single-cross hybrids were evaluated across 12 short-season environmend. Stratified mass selection was a cost-effective and successful breeding procedure for adapting tropical populations to short-season environments without exceptions. NDTuxpeño is ready to be used in very short-season areas. It has shown to be the driest population of the experiment with 17.6% grain moisture at harvest time, statistically lower than 18 checks. Thus, confirming its adaptation to short-season environments. NDHighland, NDEto, NDSuwan-1, and NDTusón also showed evidence of adaptation. Adapted varieties represent unique new options for maize breeders to expand the genetic base of their current breeding programs. This gene pool, not present in current U.S. genome sequences or short-season areas, will offer unique early maturing competitive genes and products not available in the northern U.S. industry.

Introgression of Maize Lethal Necrosis Resistance Quantitative Trait Loci Into Susceptible Maize Populations and Validation of the Resistance Under Field Conditions in Naivasha, Kenya.

Maize lethal necrosis (MLN), resulting from co-infection by maize chlorotic mottle virus (MCMV) and sugarcane mosaic virus (SCMV) can cause up to 100% yield losses in maize in Africa under serious disease conditions. Maize improvement through conventional backcross (BC) takes many generations but can significantly be shortened when molecular tools are utilized in the breeding process. We used a donor parent (KS23-6) to transfer quantitative trait loci (QTL) for resistance to MLN into nine adapted but MLN susceptible lines. Nurseries were established in Kiboko, Kenya during 2015–2017 seasons and BC3F2 progeny were developed using marker assisted backcrossing (MABC) approach. Six single nucleotide polymorphism (SNP) markers linked to QTL for resistance to MLN were used to genotype 2,400 BC3F2 lines using Kompetitive Allele Specific PCR (KASP) platform. We detected that two of the six QTL had major effects for resistance to MLN under artificial inoculation field conditions in 56 candidate BC3F2 lines. To confirm whether these two QTL are reproducible under different field conditions, the 56 BC3F2 lines including their parents were evaluated in replicated trials for two seasons under artificial MLN inoculations in Naivasha, Kenya in 2018. Strong association of genotype with phenotype was detected. Consequently, 19 superior BC3F2 lines with favorable alleles and showing improved levels of resistance to MLN under artificial field inoculation were identified. These elite lines represent superior genetic resources for improvement of maize hybrids for resistance to MLN. However, 20 BC3F2 lines were fixed for both KASP markers but were susceptible to MLN under field conditions, which could suggest weak linkage between the KASP markers and target genes. The validated two major QTL can be utilized to speed up the breeding process but additional loci need to be identified between the KASP markers and the resistance genes to strengthen the linkage.

Molecular Parallelism Underlies Convergent Highland Adaptation of Maize Landraces.

Convergent phenotypic evolution provides some of the strongest evidence for adaptation. However, the extent to which recurrent phenotypic adaptation has arisen via parallelism at the molecular level remains unresolved, as does the evolutionary origin of alleles underlying such adaptation. Here, we investigate genetic mechanisms of convergent highland adaptation in maize landrace populations and evaluate the genetic sources of recurrently selected alleles. Population branch excess statistics reveal substantial evidence of parallel adaptation at the level of individual single-nucleotide polymorphism (SNPs), genes, and pathways in four independent highland maize populations. The majority of convergently selected SNPs originated via migration from a single population, most likely in the Mesoamerican highlands, while standing variation introduced by ancient gene flow was also a contributor. Polygenic adaptation analyses of quantitative traits reveal that alleles affecting flowering time are significantly associated with elevation, indicating the flowering time pathway was targeted by highland adaptation. In addition, repeatedly selected genes were significantly enriched in the flowering time pathway, indicating their significance in adapting to highland conditions. Overall, our study system represents a promising model to study convergent evolution in plants with potential applications to crop adaptation across environmental gradients.

Genetic architecture affecting maize agronomic traits identified by variance heterogeneity association mapping

Conventional genome-wide association studies (GWAS) focused on the phenotypic mean differences (mGWAS) but often ignored genetic variants influencing differences in the variance between genotypes. In this study, we performed variance heterogeneity GWAS (vGWAS) analysis for 13 previously measured agronomic traits in a maize population. We discovered a total of 129 significant SNPs. We demonstrated that the genetic loci influencing mean differences and variance heterogeneity formed distinct groups, suggesting that breeders were able to independently select for phenotype mean and variance values. Moreover, vGWAS served as a tractable approach to effectively identify 214 epistatic interaction pairs. In addition, we documented four agronomic traits with decreasing phenotype variance during modern maize breeding history and identified the potential genetic variants influencing this process. In summary, we discovered additional non-additive effects contributing to missing heritability and valuable genetic variants used for breeding varieties with desired phenotypic variance.

Screening of suitable genotype for Bangladesh conditions based on genetic variability and path analysis in F2 white maize populations

AbstractWhite maize is the new maize (Zea mays L.) cultivar in Bangladesh. The country needs high‐yielding white maize varieties for farmers’ cultivation, but developing such variety requires appropriate inbred lines. Here, nine F2 populations of white maize were evaluated through assessment of their genetic variability, heritability, and character association for selection of promising lines based on yield and growth parameters. Analysis of genetic variability showed that there were significant variations among the various genotypes of F2 populations. High heritability coupled with large genetic advances in percentage means were obtained in plant height, cob height, number of branches per tassel, number of cobs bearing node, leaf blade area, and grain yield per plant. The analysis of path coefficient indicated positive direct contribution towards yield per plant through days to 50% tasseling, days to 50% silking, cob height, days to maturity, number of branches of the tassel, cob breadth, and number of grains per row. The results thus indicated that indirect selection based on plant height, days to maturity, cob height, leaves per plants, cob length, number of rows per cob, and number of grains per row are reliable to select the appropriate lines for yield improvement in white maize. In view of the yield and its contributing characteristics, the population of KS 510 has a high yield potential for improvement of the varietal performance of white maize.

Assessment of genetic diversity of Turkish maize landraces for phytic acid and total phenolic contents

Assessment of genetic diversity of Turkish maize landraces for phytic acid and total phenolic contents

Diversification of maize (Zea mays L.) through teosinte (Zea mays subsp. parviglumis Iltis & Doebley) allelic

Zea mays ssp. parviglumis is the progenitor of maize and assume to have tolerance against various biotic and abiotic stresses. It grows without human intervention in Southern Mexico at the bank of Balsas river and maintains sufficient genetic diversity that can help in maize diversification and domestication of wild alleles. To develop the uniform near to homozygous line the maize inbred parent DI-103 (seed parent) was crossed with teosinte (pollen parent) to produce F1s followed by one generation of backcrossing with DI-103. Subsequently, selfing was done to produce 126 BC1F3 and BC1F4 generations, which were evaluated in the Kharif 2017 and Rabi 2017–2018 for 12 characters. Large variations were observed for all the characters in BC1F3 and BC1F4 generations of teosinte derived maize population and depicted by box-plots. In addition to above, some lines with unique features such as protogynous behaviour in 76 lines, short ASI (0–1 days) in 20 lines and > 3 ears per plant in 21 lines were noted in both BC1F3 and BC1F4 generations. Allelic reshuffling between maize and teosinte genome is assume as a probable cause for wide range of variation among the lines. For inheritance of anthesis-silking interval and ear/plant in both the generations and for silking duration in BC1F3 generation complementary gene interaction is involved whereas for days to 50% anthesis, 50% silking duplicate gene interaction is involved in BC1F4 generations. The results of the investigation are unique and promising and it further indicates that teosinte can be used efficiently as a donor in diversification of maize germplasm and domestication of wild alleles particularly of those which are adaptive in nature and comply with climatic resiliency.

Manipulating ZmEXPA4 expression ameliorates the drought-induced prolonged anthesis and silking interval in maize.

Drought poses a major environmental threat to maize (Zea mays) production worldwide. Since maize is a monoecious plant, maize grain yield is dependent on the synchronous development of male and female inflorescences. When a drought episode occurs during flowering, however, an asynchronism occurs in the anthesis and silking interval (ASI) that results in significant yield losses. The underlying mechanism responsible for this asynchronism is still unclear. Here, we obtained a comprehensive development-drought transcriptome atlas of maize ears. Genes that function in cell expansion and growth were highly repressed by drought in 50 mm ears. Notably, an association study using a natural-variation population of maize revealed a significant relationship between the level of α-expansin4 (ZmEXPA4) expression and drought-induced increases in ASI. Furthermore, genetic manipulation of ZmEXPA4 expression using a drought-inducible promoter in developing maize ears reduced the ASI under drought conditions. These findings provide important insights into the molecular mechanism underlying the increase in ASI in maize ears subjected to drought and provide a promising strategy that can be used for trait improvement.

Effect of uniconazole and nitrogen level on lodging resistance and yield potential of maize under medium and high plant density.

Lodging in maize results in grain yield reduction. This experiment investigated the effects of different application rates of the growth retardant, uniconazole (UCZ), and nitrogen (N) on medium and high maize population densities on lodging resistance and yield. UCZ was applied to maize seeds at concentrations of 0 (U0 ) and 25 (U25 ) mg kg-1 , and three different N application rates, 0 (N0 ), 150 (N150 ) and 225 (N225 ) kg ha-1 , at plant densities of 75,000 (D1 ) and 105,000 plants ha-1 (D2 ). UCZ application, different N rates and plant population density affected the lodging resistance and yield attributes of maize. The diameter, plumpness, cortex penetration and bending strengths of the internodes were enhanced with UCZ and N application at medium and high plant density, where maximum values were obtained with U25 N150 D1 . Internode length increased in the high-density population and higher N rate, whereas UCZ reduced internode length, where maximum internode length was obtained with U0 N225 D2 . Plant height, centre of gravity height, ear and height above ear-bearing node were higher with the high N rate, while UCZ reduced it significantly. UCZ, N rate and plant density enhanced lignin accumulation in the third internode and ear-bearing internode, where maximum values were obtained with U25 N150 D1 . Yield and yield attributes were also improved by UCZ, N rate and population density. Treatment with U25 N150 D2 significantly improved grain yield of maize compared with the other treatments.

Combining Ability and Heterosis of Algerian Saharan Maize Populations (Zea mays L.) for Tolerance to No-Nitrogen Fertilization and Drought

Drought and low nitrogen are major stresses for maize (Zea mays L.), and maize populations from the Sahara Desert are potential sources of stress tolerance. The objectives were to assess the tolerance and varietal and heterosis effects of Algerian populations under no-nitrogen fertilization and water stress. A diallel among six Algerian maize population was evaluated under drought (300 mm irrigation) vs. control (600 mm) and no-nitrogen fertilization vs. 120 kh ha−1 N fertilization. Genotypes showed significant differences and genetic effects for water- and nitrogen-stress tolerance. We propose a reciprocal recurrent selection to take advantage of additive and non-additive effects, using AOR and IGS, since they showed good performance in optimum and stress conditions, for improving yield heterosis for AOR × IGS. Negative effects are not expected on plant height, anthesis–silking interval or early vigor. These populations and BAH could be sources of inbred lines tolerant to drought and no-nitrogen fertilization. There was no relationship between origin and genetic group and stress tolerance per se or as parents of tolerant crosses. These populations and crosses could be used as base material among Algerian populations, for breeding programs focusing on tolerance to water or nitrogen stress.

Effect of Low-Input Organic and Conventional Farming Systems on Maize Rhizosphere in Two Portuguese Open-Pollinated Varieties (OPV), "Pigarro" (Improved Landrace) and "SinPre" (a Composite Cross Population).

Maize is one of the most important crops worldwide and is the number one arable crop in Portugal. A transition from the conventional farming system to organic agriculture requires optimization of cultivars and management, the interaction of plant–soil rhizosphere microbiota being pivotal. The objectives of this study were to unravel the effect of population genotype and farming system on microbial communities in the rhizosphere of maize. Rhizosphere soil samples of two open-pollinated maize populations (“SinPre” and “Pigarro”) cultivated under conventional and organic farming systems were taken during flowering and analyzed by next-generation sequencing (NGS). Phenological data were collected from the replicated field trial. A total of 266 fungi and 317 bacteria genera were identified in “SinPre” and “Pigarro” populations, of which 186 (69.9%) and 277 (87.4%) were shared among them. The microbiota of “Pigarro” showed a significant higher (P < 0.05) average abundance than the microbiota of “SinPre.” The farming system had a statistically significant impact (P < 0.05) on the soil rhizosphere microbiota, and several fungal and bacterial taxa were found to be farming system-specific. The rhizosphere microbiota diversity in the organic farming system was higher than that in the conventional system for both varieties. The presence of arbuscular mycorrhizae (Glomeromycota) was mainly detected in the microbiota of the “SinPre” population under the organic farming systems and very rare under conventional systems. A detailed metagenome function prediction was performed. At the fungal level, pathotroph–saprotroph and pathotroph–symbiotroph lifestyles were modified by the farming system. For bacterial microbiota, the main functions altered by the farming system were membrane transport, transcription, translation, cell motility, and signal transduction. This study allowed identifying groups of microorganisms known for their role as plant growth-promoting rhizobacteria (PGPR) and with the capacity to improve crop tolerance for stress conditions, allowing to minimize the use of synthetic fertilizers and pesticides. Arbuscular mycorrhizae (phyla Glomeromycota) were among the most important functional groups in the fungal microbiota and Achromobacter, Burkholderia, Erwinia, Lysinibacillus, Paenibacillus, Pseudomonas, and Stenotrophomonas in the bacterial microbiota. In this perspective, the potential role of these microorganisms will be explored in future research.

Response to Selection for Reduced Anthesis-Silking Interval in Four Algerian Maize Populations

Drought is the main constraint to maize production in the Mediterranean area. This is the first report of breeding temperate maize populations from the Algerian desert. The objective of this study was to evaluate response to selection for reduced anthesis-silking interval (ASI) in Algerian maize under drought and control conditions. Three cycles of selection for reduced ASI were carried out in four populations under control and drought conditions, and the breeding program was evaluated under both conditions. Selection under drought was more efficient than under control conditions, particularly for the LOM and TAO populations. Selection for low ASI reduced ASI and days per cycle for BTM and IGS, respectively, under drought conditions. Selection for ASI reduced anthesis in BTM, when selected under drought and evaluated under control conditions. Significant yield increase was observed for BTM under optimal conditions. Significant genetic gain for yield was observed for the population LOM under drought. Therefore, the improved Algerian populations BTM and TAO could be a novel source for reducing ASI and for earlier flowering time as a mechanism for avoiding drought. Furthermore, we propose these populations as sources to develop tolerant inbred lines and to find quantitative trait loci for drought tolerance.

Agronomic and chemical description of open-pollinated varieties of opaque-2 and purple maize (Zea mays L.) adapted to semiarid region of Argentina

The objective of this study was to compare the evolution of two populations of opaque-2 and purple maize in the central semiarid region of Argentina, and to characterize the agronomic traits and grain chemical attributes to conclude the varietal description of each population. Introduced germplasm of both varietal types was grown under rainfed conditions during four crop years (2011/12, 2013/14, 2014/15 and 2015/16) and characterized both agronomically and chemically. Significant differences were observed between varietal types in the morphological traits of plants and cobs, but did not differ in male flowering or female flowering. Purple maize exhibited taller plants with thicker stems and smaller cobs with heavier grains than opaque-2 maize. Purple maize showed lower grain yields (mean of 4.84 vs. 6.16 tn ha−1 in opaque-2 maize) with more marked variations between cycles (3.02 to 6.62 vs. 5.47 to 7.28 tn ha−1 in opaque-2 maize). The effects of the environment and genotype x environment interaction (G × E) were more notable for grain yield and grain chemical features such us protein, amylose and phenolic compound contents. Nonetheless, most of the agronomic traits in each varietal type showed higher genetic effects (67–92% in opaque-2 maize and 55–82% in purple maize) and a lower G × E (3–14% in opaque-2 maize and 7–19% in purple maize). The advances of this study represent substantial efforts on the development, characterization and description of maize genetic resources in Argentina, which represent potential raw materials for the functional-foods industry.

Optimizing dry land through the implementation of maize and rice multiple cropping system in Pemalang Regency

Maize is one of the food crops as the second staple food after rice in Indonesia. Efforts that can be done are not only to increase maize production but also increases the cropping index as through intercropping in dry-land. This study aims to determine the production of maize intercropped with rice. The research was carried out on the farmer’s-land at Planting Season (PS-2) on April-October 2019 in Pemalang. The maize variety planted were farmers existing varieties Bisi-18 and introduced variety (Nasa-29 varieties). The rice varieties planted are Inpari-42 and Inpago-10. Corn spacing (120x30x20 cm) and rice spacing (20x20 cm). The study used a randomized block design with 4 treatments (was repeated 6 times). The results showed that the intercropping system affected the yield of maize productivity and rice. The highest maize production (5.96 t ha−1) was obtained for intercropping maize (Bisi-18) and rice (Inpago-10) while for the highest rice production (1.76 t ha−1) was intercropping Bisi-18 with Inpari-42. The intercropping of maize and upland rice with a population of maize (81%) and a population of rice (62%) with a total of both 143%, and can increase the cropping index (CI) by 100-143% compared to the existing zero planting of PS-2.

A new feasible method for yield gap analysis in regions dominanted by smallholder farmers, with a case study of Jiangsu Province, China

In the regions where crops were mostly produced by smallholder farmers, the analysis of yield gap is difficult due to diverse cultivars, crop managements and yield levels. In order to find an effective method that can reasonably verify the yield gap and the limiting cultivation factors in narrowing yield gaps in areas that are dominanted by smallholder farmers, we worked out a method consisting five progressive procedures as follows: questionnaire investigation of farmer cultivation regime, identification of yield levels and yield gaps, generalization of key cultivation measurements, reconstruction of representative maize populations, and process-based analysis of yield gap. A case study was carried out in Jiangsu Province, China, in which maize is mostly produced by smallholder farmers. A questionnaire investigation of 1 023 smallholder farmers was carried out firstly, then the frequency distribution of maize yield was simulated by an normal distribution function, and then the covering range and average value of the basic yield, farmer yield and high-yield farmer yield levels were calculated out from the equation. Hereby, the yield gaps 1, 2 and 3 were calculated along with the record highest yield from literature and experts, which were 2 564, 2 346 and 2 073 kg ha–1, respectively. Moreover, with the covering range of each yield level, the suveyed farmers belonging to each yield level were grouped together and then their major cultivation measures were traced and generalized. With the generalized cultivation measures, representative maize populations of the four yield levels were reconstructed, and thereby clarifing lots of characters of the populations or single plant of each population with process-based analysis of the reconstructed populations. In this case, the main factors causing the yield gap were plant density, fertilizer application rate, logging caused by hurricane, and damages caused by pests. The case study primarily indicated that this five-step method is feasible and effective in yield gap study, especially in smallholder farmers dominant regions.

Local adaptation contributes to gene expression divergence in maize.

Gene expression links genotypes to phenotypes, so identifying genes whose expression is shaped by selection will be important for understanding the traits and processes underlying local adaptation. However, detecting local adaptation for gene expression will require distinguishing between divergence due to selection and divergence due to genetic drift. Here, we adapt a framework to detect local adaptation for transcriptome-wide gene expression levels in a population of diverse maize genotypes. We compare the number and types of selected genes across a wide range of maize populations and tissues, as well as selection on cold-response genes, drought-response genes, and coexpression clusters. We identify a number of genes whose expression levels are consistent with local adaptation and show that genes involved in stress response show enrichment for selection. Due to its history of intense selective breeding and domestication, maize evolution has long been of interest to researchers, and our study provides insight into the genes and processes important for in local adaptation of maize.

Environmental impact and genetic expressions of new drought tolerant maize genotypes in derived savannah agro-ecology

Reduced water resources in sub-Saharan Africa will not only pose threat to the livelihood of poor resource farmers, but also food security in the region. Drought tolerant (DT) maize varieties hold promise to reducing poor resourced farmers’ vulnerability and improve food security in sub-Saharan Africa. Ten maize genotypes obtained from the International Institute of Tropical Agriculture (IITA), were evaluated in 2015 and 2016 using a randomized complete block design experiment with three replications to estimate their genetic variability and predict their genetic advances in the derived savannah agro-ecology. Growth, phenological and yield data were collected from 10 middle row plants. Genetic advance, genotypic, phenotypic and environmental coefficients of variations and their variances were estimated. Principal component and hierarchical cluster analyses were also performed. The dendrogram showed that at 80% dissimilarity point, the genotypes were grouped into clusters A, B and C in both years. The first two principal components explained 91.8% and 93.3% of the total variation in 2015 and 2016, respectively. Number of grains cob-1, plant height and number of days to physiological maturity were consistent in explaining the variations observed in the maize population. Heritability estimates in broad sense ranged from 1.35% for number of leaves to 87.43% for grain yield per hectare. The genetic parameters studied showed significant variations among the growth, phenological and yield data collected that warrants selection and maize improvement program using the DT maize inbred lines in derived savannah agro-ecology.

High-throughput phenotyping analysis of maize at the seedling stage using end-to-end segmentation network.

Image processing technologies are available for high-throughput acquisition and analysis of phenotypes for crop populations, which is of great significance for crop growth monitoring, evaluation of seedling condition, and cultivation management. However, existing methods rely on empirical segmentation thresholds, thus can have insufficient accuracy of extracted phenotypes. Taking maize as an example crop, we propose a phenotype extraction approach from top-view images at the seedling stage. An end-to-end segmentation network, named PlantU-net, which uses a small amount of training data, was explored to realize automatic segmentation of top-view images of a maize population at the seedling stage. Morphological and color related phenotypes were automatic extracted, including maize shoot coverage, circumscribed radius, aspect ratio, and plant azimuth plane angle. The results show that the approach can segment the shoots at the seedling stage from top-view images, obtained either from the UAV or tractor-based high-throughput phenotyping platform. The average segmentation accuracy, recall rate, and F1 score are 0.96, 0.98, and 0.97, respectively. The extracted phenotypes, including maize shoot coverage, circumscribed radius, aspect ratio, and plant azimuth plane angle, are highly correlated with manual measurements (R2 = 0.96-0.99). This approach requires less training data and thus has better expansibility. It provides practical means for high-throughput phenotyping analysis of early growth stage crop populations.

Identification and meta-analysis of QTLs for four leaf shape traits in two maize populations under contracting watering environments

Maize leaf length, leaf width, leaf angle, and leaf orientation value are determinant traits influencing leaf shape, yield potential, and can sense water stress signals. However, little is known regarding their genetic controls under drought stress. Using two F3 populations, we identified 72 QTLs under contrasting environments at V18 and R1 stages by single-environment mapping, 58.3% QTLs were identified under drought-stressed environments. Thirty-three joint QTLs were detected by joint analysis of all environments, 7 QTLs involved in QTL-by-environment interactions, 11 pair epistasis exhibited additive-by-additive effects. Twelve constitutive QTLs were dissected that will be potentially useful for genetic improvement of maize leaf development through QTL pyramiding. Additionally, 13 meta-QTLs were identified via meta-analysis, 15 candidate genes were identified in these meta-QTLs. These results provide valuable information for QTLs fine mapping, revealing genetic mechanisms of leaf shape under contrasting watering environments, and alleles provide useful targets for marker-assisted selection breeding.