Genome-wide association study (GWAS) reveals the genetic architecture of four husk traits in maize

A combination of QTL mapping and genome-wide association study revealed the key gene for husk number in maize

KEY MESSAGE

Two key genes Zm00001d021232 and Zm00001d048138 were identified by QTL mapping and GWAS. Additionally, they were verified to be significantly associated with maize husk number (HN) using gene-based association study. As a by-product of maize production, maize husk is an important industrial raw material. Husk layer number (HN) is an important trait that affects the yield of maize husk. However, the genetic mechanism underlying HN remains unclear. Herein, a total of 13 quantitative trait loci (QTL) controlling HN were identified in an IBM Syn 10 DH population across different locations. Among these, three QTL were individually repeatedly detected in at least two environments. Meanwhile, 26 unique single nucleotide polymorphisms (SNPs) were detected to be significantly (p < 2.15 × 10-6) associated with HN in an association pool. Of these SNPs, three were simultaneously detected across multiple environments or environments and best linear unbiased prediction (BLUP). We focused on these environment-stable and population-common genetic loci for excavating the candidate genes responsible for maize HN. Finally, 173 initial candidate genes were identified, of which 22 were involved in both multicellular organism development and single-multicellular organism process and thus confirmed as the candidate genes for HN. Gene-based association analyses revealed that the variants in four genes were significantly (p < 0.01/N) correlated with HN, of which Zm00001d021232 and Zm00001d048138 were highly expressed in husks and early developing ears among different maize tissues. Our study contributes to the understanding of genetic and molecular mechanisms of maize husk yield and industrial development in the future.

Advancements and Prospects of Genome-Wide Association Studies (GWAS) in Maize

Genome-wide association studies (GWAS) have emerged as a powerful tool for unraveling intricate genotype-phenotype association across various species. Maize (Zea mays L.), renowned for its extensive genetic diversity and rapid linkage disequilibrium (LD), stands as an exemplary candidate for GWAS. In maize, GWAS has made significant advancements by pinpointing numerous genetic loci and potential genes associated with complex traits, including responses to both abiotic and biotic stress. These discoveries hold the promise of enhancing adaptability and yield through effective breeding strategies. Nevertheless, the impact of environmental stress on crop growth and yield is evident in various agronomic traits. Therefore, understanding the complex genetic basis of these traits becomes paramount. This review delves into current and future prospectives aimed at yield, quality, and environmental stress resilience in maize and also addresses the challenges encountered during genomic selection and molecular breeding, all facilitated by the utilization of GWAS. Furthermore, the integration of omics, including genomics, transcriptomics, proteomics, metabolomics, epigenomics, and phenomics has enriched our understanding of intricate traits in maize, thereby enhancing environmental stress tolerance and boosting maize production. Collectively, these insights not only advance our understanding of the genetic mechanism regulating complex traits but also propel the utilization of marker-assisted selection in maize molecular breeding programs, where GWAS plays a pivotal role. Therefore, GWAS provides robust support for delving into the genetic mechanism underlying complex traits in maize and enhancing breeding strategies.

Genome-wide association study of agronomic traits related to nitrogen use efficiency in Henan wheat

BACKGROUND

Nitrogen use efficiency (NUE) is closely related to crop yield and nitrogen fertilizer application rate. Although NUE is susceptible to environments, quantitative trait nucleotides (QTNs) for NUE in wheat germplasm populations have been rarely reported in genome-wide associated study.

RESULTS

In this study, 244 wheat accessions were phenotyped by three NUE-related traits in three environments and genotyped by 203,224 SNPs. All the phenotypes for each trait were used to associate with all the genotypes of these SNP markers for identifying QTNs and QTN-by-environment interactions via 3VmrMLM. Among 279 QTNs and one QTN-by-environment interaction for low nitrogen tolerance, 33 were stably identified, especially, one large QTN (r2 > 10%), qPHR3A.2, was newly identified for plant height ratio in one environment and multi-environment joint analysis. Among 52 genes around qPHR3A.2, four genes (TraesCS3A01G101900, TraesCS3A01G102200, TraesCS3A01G104100, and TraesCS3A01G105400) were found to be differentially expressed in low-nitrogen-tolerant wheat genotypes, while TaCLH2 (TraesCS3A01G101900) was putatively involved in porphyrin metabolism in KEGG enrichment analyses.

CONCLUSIONS

This study identified valuable candidate gene for low-N-tolerant wheat breeding and provides new insights into the genetic basis of low N tolerance in wheat.

Genome-wide association study and pathway analysis to decipher loci associated with Fusarium ear rot resistance in tropical maize germplasm

Breeding for host resistance is the most efficient and environmentally safe method to curb the spread of fusarium ear rot (FER). However, conventional breeding for resistance to FER is hampered by the complex polygenic nature of this trait, which is highly influenced by environmental conditions. This study aimed to identify genomic regions, single nucleotide polymorphisms (SNPs), and putative candidate genes associated with FER resistance as well as candidate metabolic pathways and pathway genes involved in it. A panel of 151 tropical inbred maize lines were used to assess the genetic architecture of FER resistance over two seasons. During the study period, seven SNPs associated with FER resistance were identified on chromosomes 1, 2, 4, 5, and 9, accounting for 4-11% of the phenotypic variance. These significant markers were annotated into four genes. Seven significant metabolic pathways involved in FER resistance were identified using the Pathway Association Study Tool, the most significant being the superpathway of the glyoxylate cycle. Overall, this study confirmed that resistance to FER is indeed a complex mechanism controlled by several small to medium-effect loci. Our findings may contribute to fast-tracking the efforts to develop disease-resistant maize lines through marker-assisted selection.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10722-023-01793-4.

The RHW1-ZCN4 regulatory pathway confers natural variation of husk leaf width in maize

Maize husk leaf - the outer leafy layers covering the ear - modulates kernel yield and quality. Despite its importance, however, the genetic controls underlying husk leaf development remain elusive. Our previous genome-wide association study identified a single nucleotide polymorphism located in the gene RHW1 (Regulator of Husk leaf Width) that is significantly associated with husk leaf-width diversity in maize. Here, we further demonstrate that a polymorphic 18-bp InDel (insertion/deletion) variant in the 3' untranslated region of RHW1 alters its protein abundance and accounts for husk leaf width variation. RHW1 encodes a putative MYB-like transcriptional repressor. Disruption of RHW1 altered cell proliferation and resulted in a narrower husk leaf, whereas RHW1 overexpression yielded a wider husk leaf. RHW1 positively regulated the expression of ZCN4, a well-known TFL1-like protein involved in maize ear development. Dysfunction of ZCN4 reduced husk leaf width even in the context of RHW1 overexpression. The InDel variant in RHW1 is subject to selection and is associated with maize husk leaf adaption from tropical to temperate regions. Overall, our results identify that RHW1-ZCN4 regulates a pathway conferring husk leaf width variation at a very early stage of husk leaf development in maize.

Investigating the genetic basis of maize ear characteristics: a comprehensive genome-wide study utilizing high-throughput phenotypic measurement method and system

The morphology of maize ears plays a critical role in the breeding of new varieties and increasing yield. However, the study of traditional ear-related traits alone can no longer meet the requirements of breeding. In this study, 20 ear-related traits, including size, shape, number, and color, were obtained in 407 maize inbred lines at two sites using a high-throughput phenotypic measurement method and system. Significant correlations were found among these traits, particularly the novel trait ear shape (ES), which was correlated with traditional traits: kernel number per row and kernel number per ear. Pairwise comparison tests revealed that the inbred lines of tropical-subtropical were significantly different from other subpopulations in row numbers per ear, kernel numbers per ear, and ear color. A genome-wide association study identified 275, 434, and 362 Single nucleotide polymorphisms (SNPs) for Beijing, Sanya, and best linear unbiased prediction scenarios, respectively, explaining 3.78% to 24.17% of the phenotypic variance. Furthermore, 58 candidate genes with detailed functional descriptions common to more than two scenarios were discovered, with 40 genes being associated with color traits on chromosome 1. After analysis of haplotypes, gene expression, and annotated information, several candidate genes with high reliability were identified, including Zm00001d051328 for ear perimeter and width, zma-MIR159f for ear shape, Zm00001d053080 for kernel width and row number per ear, and Zm00001d048373 for the blue color channel of maize kernels in the red-green-blue color model. This study emphasizes the importance of researching novel phenotypic traits in maize by utilizing high-throughput phenotypic measurements. The identified genetic loci enrich the existing genetic studies related to maize ears.

Genome-Wide Association Study Identified Novel SNPs Associated with Chlorophyll Content in Maize

Chlorophyll is an essential component that captures light energy to drive photosynthesis. Chlorophyll content can affect photosynthetic activity and thus yield. Therefore, mining candidate genes of chlorophyll content will help increase maize production. Here, we performed a genome-wide association study (GWAS) on chlorophyll content and its dynamic changes in 378 maize inbred lines with extensive natural variation. Our phenotypic assessment showed that chlorophyll content and its dynamic changes were natural variations with a moderate genetic level of 0.66/0.67. A total of 19 single-nucleotide polymorphisms (SNPs) were found associated with 76 candidate genes, of which one SNP, 2376873-7-G, co-localized in chlorophyll content and area under the chlorophyll content curve (AUCCC). Zm00001d026568 and Zm00001d026569 were highly associated with SNP 2376873-7-G and encoded pentatricopeptide repeat-containing protein and chloroplastic palmitoyl-acyl carrier protein thioesterase, respectively. As expected, higher expression levels of these two genes are associated with higher chlorophyll contents. These results provide a certain experimental basis for discovering the candidate genes of chlorophyll content and finally provide new insights for cultivating high-yield and excellent maize suitable for planting environment.

Identification and validation of a key genomic region on chromosome 6 for resistance to Fusarium stalk rot in tropical maize

A key genomic region was identified for resistance to FSR at 168 Mb on chromosome 6 in GWAS and haplotype regression analysis, which was validated by QTL mapping in two populations. Fusarium stalk rot (FSR) of maize is an economically important post-flowering stalk rot (PFSR) disease caused by Fusarium verticillioides. The pathogen invades the plant individually, or in combination with other stalk rot pathogens or secondary colonizers, thereby making it difficult to make accurate selection for resistance. For identification and validation of genomic regions associated with FSR resistance, a genome-wide association study (GWAS) was conducted with 342 maize lines. The panel was screened for FSR in three environments using standard artificial inoculation methodology. GWAS using the mixed linear model corrected for population structure and kinship was done, in which 290,626 SNPs from genotyping-by-sequencing were used. A total of 7 SNPs, five on chromosome 6 showing strong LD at 168 Mb, were identified to be associated with FSR. Haplotype regression analysis identified 32 haplotypes with a significant effect on the trait. In a QTL mapping experiment in two populations for validating the identified variants, QTLs were identified with confidence intervals having overlapped physical coordinates in both the populations on chromosome 6, which was closely located to the GWAS-identified variants on chromosome 6. It makes this genomic region a crucial one to further investigate the possibility of developing trait markers for deployment in breeding pipelines. It was noted that previously reported QTLs for other stalk rots in maize mapped within the same physical intervals of several haplotypes identified for FSR resistance in this study. The possibility of QTLs controlling broad-spectrum resistance for PFSR in general requires further investigation.

Genome-wide analyses using multi-locus models revealed marker-trait associations for major agronomic traits in Sorghum bicolor

Globally, sorghum is the fifth most important cereal crop, and it is a major crop in Ethiopia, where it has a high genetic diversity. The country's sorghum gene pool contributes significantly to sorghum improvement worldwide. This study aimed to identify genomic regions and candidate genes associated with major agronomic traits in sorghum by using its genetic resources in Ethiopia for a genome-wide association study (GWAS). Phenotypic data of days to flowering (DTF), plant height (PH), panicle length (PALH), panicle width (PAWD), panicle weight (PAWT), and grain yield (GY) were collected from a GWAS panel comprising 324 sorghum accessions grown in three environments. SeqSNP, a targeted genotyping method, was used to genotype the panel using 5,000 gene-based single nucleotide polymorphism (SNP) markers. For marker-trait association (MTA) analyses, fixed and random model circulating probability unification (FarmCPU), and Bayesian-information and linkage-disequilibrium iteratively nested keyway (BLINK) models were used. In all traits, high phenotypic variation was observed, with broad-sense heritability ranging from 0.32 (for GY) to 0.90 (for PALH). A population structure, principal component analysis, and kinship analysis revealed that the accessions could be divided into two groups. In total, 54 MTAs were identified, 11 of which were detected by both BLINK and farmCPU. MTAs identified for each trait ranged from five (PAWT and GY) to fourteen (PH) representing both novel and previously identified quantitative trait loci (QTLs). Three SNPs were associated with more than one trait, including a SNP within the Sobic.004G189200 gene that was associated with PH and PAWT. Major effect SNP loci, Sbi2393610 (PVE = 23.3%), Sbi10438246 (PVE = 35.2%), Sbi17789352 (PVE = 11.9%) and Sbi30169733 (PVE = 18.9%) on chromosomes 1, 3, 5 and 9 that showed strong association signals for PAWD, DTF, GY and PALH, respectively, were major findings of this study. The SNP markers and candidate genes identified in this study provide insights into the genetic control of grain yield and related agronomic traits, and once validated, the markers could be used in genomics-led breeding.

Genome-wide association study reveals the genetic basis of brace root angle and diameter in maize

Brace roots are the main organ to support the above-ground part of maize plant. It involves in plant growth and development by water absorption and lodging resistance. The bracing root angle (BRA) and diameter (BRD) are important components of brace root traits. Illuminating the genetic basis of BRA and BRD will contribute the improvement for mechanized harvest and increasing production. A GWAS of BRA and BRD was conducted using an associated panel composed of 508 inbred lines of maize. The broad-sense heritability of BRA and BRD was estimated to be respectively 71% ± 0.19 and 52% ± 0.14. The phenotypic variation of BRA and BRD in the non-stiff stalk subgroup (NSS) and the stiff stalk subgroup (SS) subgroups are significantly higher than that in the tropical/subtropical subgroup (TST) subgroups. In addition, BRA and BRD are significantly positive with plant height (PH), ear length (EL), and kernel number per row (KNPR). GWAS revealed 27 candidate genes within the threshold of p < 1.84 × 10⁻⁶ by both MLM and BLINK models. Among them, three genes, GRMZM2G174736, GRMZM2G445169 and GRMZM2G479243 were involved in cell wall function, and GRMZM2G038073 encoded the NAC transcription factor family proteins. These results provide theoretical support for clarifying the genetic basis of brace roots traits.

Dissecting the Genetic Structure of Maize Leaf Sheaths at Seedling Stage by Image-Based High-Throughput Phenotypic Acquisition and Characterization

The rapid development of high-throughput phenotypic detection techniques makes it possible to obtain a large number of crop phenotypic information quickly, efficiently, and accurately. Among them, image-based phenotypic acquisition method has been widely used in crop phenotypic identification and characteristic research due to its characteristics of automation, non-invasive, non-destructive and high throughput. In this study, we proposed a method to define and analyze the traits related to leaf sheaths including morphology-related, color-related and biomass-related traits at V6 stage. Next, we analyzed the phenotypic variation of leaf sheaths of 418 maize inbred lines based on 87 leaf sheath-related phenotypic traits. In order to further analyze the mechanism of leaf sheath phenotype formation, 25 key traits (2 biomass-related, 19 morphology-related and 4 color-related traits) with heritability greater than 0.3 were analyzed by genome-wide association studies (GWAS). And 1816 candidate genes of 17 whole plant leaf sheath traits and 1,297 candidate genes of 8 sixth leaf sheath traits were obtained, respectively. Among them, 46 genes with clear functional descriptions were annotated by single nucleotide polymorphism (SNPs) that both Top1 and multi-method validated. Functional enrichment analysis results showed that candidate genes of leaf sheath traits were enriched into multiple pathways related to cellular component assembly and organization, cell proliferation and epidermal cell differentiation, and response to hunger, nutrition and extracellular stimulation. The results presented here are helpful to further understand phenotypic traits of maize leaf sheath and provide a reference for revealing the genetic mechanism of maize leaf sheath phenotype formation.

A Genome-Wide Association Study Dissects the Genetic Architecture of the Metaxylem Vessel Number in Maize Brace Roots

Metaxylem vessels in maize brace roots are key tissue, and their number (MVN) affects plant water and inorganic salt transportation and lodging resistance. Dissecting the genetic basis of MVN in maize brace roots can help guide the genetic improvement of maize drought resistance and lodging resistance during late developmental stages. In this study, we used 508 inbred lines with tropical, subtropical, and temperate backgrounds to analyze the genetic architecture of MVN in maize brace roots. The phenotypic variation in MVN in brace roots was evaluated in three environments, which revealed broad natural variation and relative low levels of heritability (h ² = 0.42). Stiff-stalk lines with a temperate background tended to have higher MVNs than plants in other genetic backgrounds. MVN was significantly positively correlated with plant height, tassel maximum axis length, ear length, and kernel number per row, which indicates that MVN may affect plant morphological development and yield. In addition, MVN was extremely significantly negatively correlated with brace root radius, but significantly positively correlated with brace root angle (BRA), diameter, and number, thus suggesting that the morphological function of some brace root traits may be essentially determined by MVN. Association analysis of MVN in brace roots combined 1,253,814 single nucleotide polymorphisms (SNPs) using FarmCPU revealed a total of nine SNPs significantly associated with MVN at P < 7.96 × 10^-7. Five candidate genes for MVN that may participate in secondary wall formation (GRMZM2G168365, GRMZM2G470499, and GRMZM2G028982) and regulate flowering time (GRMZM2G381691 and GRMZM2G449165). These results provide useful information for understanding the genetic basis of MVN in brace root development. Further functional studies of identified candidate genes should help elucidate the molecular pathways that regulate MVN in maize brace roots.

Identification of Genomic Regions Associated with Agronomic and Disease Resistance Traits in a Large Set of Multiple DH Populations

Breeding maize lines with the improved level of desired agronomic traits under optimum and drought conditions as well as increased levels of resistance to several diseases such as maize lethal necrosis (MLN) is one of the most sustainable approaches for the sub-Saharan African region. In this study, 879 doubled haploid (DH) lines derived from 26 biparental populations were evaluated under artificial inoculation of MLN, as well as under well-watered (WW) and water-stressed (WS) conditions for grain yield and other agronomic traits. All DH lines were used for analyses of genotypic variability, association studies, and genomic predictions for the grain yield and other yield-related traits. Genome-wide association study (GWAS) using a mixed linear FarmCPU model identified SNPs associated with the studied traits i.e., about seven and eight SNPs for the grain yield; 16 and 12 for anthesis date; seven and eight for anthesis silking interval; 14 and 5 for both ear and plant height; and 15 and 5 for moisture under both WW and WS environments, respectively. Similarly, about 13 and 11 SNPs associated with gray leaf spot and turcicum leaf blight were identified. Eleven SNPs associated with senescence under WS management that had depicted drought-stress-tolerant QTLs were identified. Under MLN artificial inoculation, a total of 12 and 10 SNPs associated with MLN disease severity and AUDPC traits, respectively, were identified. Genomic prediction under WW, WS, and MLN disease artificial inoculation revealed moderate-to-high prediction accuracy. The findings of this study provide useful information on understanding the genetic basis for the MLN resistance, grain yield, and other agronomic traits under MLN artificial inoculation, WW, and WS conditions. Therefore, the obtained information can be used for further validation and developing functional molecular markers for marker-assisted selection and for implementing genomic prediction to develop superior elite lines.

Insights into the effect of human civilization on Malus evolution and domestication

The evolutionary history of the Malus genus has not been well studied. In the current study, we presented genetic evidence on the origin of the Malus genus based on genome sequencing of 297 Malus accessions, revealing the genetic relationship between wild species and cultivated apples. Our results demonstrated that North American and East Asian wild species are closer to the outgroup (pear) than Central Asian species, and hybrid species including natural (separated before the Pleistocene, about 2.5 Mya) and artificial hybrids (including ornamental trees and rootstocks) are between East and Central Asian wild species. Introgressions from M. sylvestris in cultivated apples appeared to be more extensive than those from M. sieversii, whose genetic background flowed westward across Eurasia and eastward to wild species including M. prunifolia, M. × asiatica, M. × micromalus, and M. × robust. Our results suggested that the loss of ancestral gene flow from M. sieversii in cultivated apples accompanied the movement of European traders around the world since the Age of Discovery. Natural SNP variations showed that cultivated apples had higher nucleotide diversity than wild species and more unique SNPs than other apple groups. An apple ERECTA-like gene that underwent selection during domestication on 15^th chromosome was identified as a likely major determinant of fruit length and diameter, and an NB-ARC domain-containing gene was found to strongly affect anthocyanin accumulation using a genome-wide association approach. Our results provide new insights into the origin and domestication of apples and will be useful in new breeding programmes and efforts to increase fruit crop productivity.

Identification and Validation of Genomic Regions Associated With Charcoal Rot Resistance in Tropical Maize by Genome-Wide Association and Linkage Mapping

Charcoal rot is a post-flowering stalk rot (PFSR) disease of maize caused by the fungal pathogen, Macrophomina phaseolina. It is a serious concern for smallholder maize cultivation, due to significant yield loss and plant lodging at harvest, and this disease is expected to surge with climate change effects like drought and high soil temperature. For identification and validation of genomic variants associated with charcoal rot resistance, a genome-wide association study (GWAS) was conducted on CIMMYT Asia association mapping panel comprising 396 tropical-adapted lines, especially to Asian environments. The panel was phenotyped for disease severity across two locations with high disease prevalence in India. A subset of 296,497 high-quality SNPs filtered from genotyping by sequencing was correcting for population structure and kinship matrices for single locus mixed linear model (MLM) of GWAS analysis. A total of 19 SNPs were identified to be associated with charcoal rot resistance with P-value ranging from 5.88 × 10^-06 to 4.80 × 10^-05. Haplotype regression analysis identified 21 significant haplotypes for the trait with Bonferroni corrected P ≤ 0.05. For validating the associated variants and identifying novel QTLs, QTL mapping was conducted using two F_2:3 populations. Two QTLs with overlapping physical intervals, qMSR6 and qFMSR6 on chromosome 6, identified from two different mapping populations and contributed by two different resistant parents, were co-located with the SNPs and haplotypes identified at 103.51 Mb on chromosome 6. Similarly, several SNPs/haplotypes identified on chromosomes 3, 6 and 8 were also found to be physically co-located within QTL intervals detected in one of the two mapping populations. The study also noted that several SNPs/haplotypes for resistance to charcoal rot were located within physical intervals of previously reported QTLs for Gibberella stalk rot resistance, which opens up a new possibility for common disease resistance mechanisms for multiple stalk rots.

Genome-wide association study reveals the genetic architecture of root hair length in maize

Background

Root hair, a special type of tubular-shaped cell, outgrows from root epidermal cell and plays important roles in the acquisition of nutrients and water, as well as interactions with biotic and abiotic stress. Although many genes involved in root hair development have been identified, genetic basis of natural variation in root hair growth has never been explored.

Results

Here, we utilized a maize association panel including 281 inbred lines with tropical, subtropical, and temperate origins to decipher the phenotypic diversity and genetic basis of root hair length. We demonstrated significant associations of root hair length with many metabolic pathways and other agronomic traits. Combining root hair phenotypes with 1.25 million single nucleotide polymorphisms (SNPs) via genome-wide association study (GWAS) revealed several candidate genes implicated in cellular signaling, polar growth, disease resistance and various metabolic pathways.

Conclusions

These results illustrate the genetic basis of root hair length in maize, offering a list of candidate genes predictably contributing to root hair growth, which are invaluable resource for the future functional investigation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07961-z.

Identification of Candidate Genes for Drought Tolerance at Maize Seedlings Using Genome-Wide Association

BACKGROUND

Drought stress is a serious threat that limit maize growth and production.

OBJECTIVES

The assessment tolerance level of maize by measuring changes in the main biochemical and physiological indicators under drought stress.

MATERIAL AND METHODS

We performed a genome-wide association analysis of biochemical and physiological indicators using an elite association panel.

RESULTS

The results revealed that eight significant SNPs (p<0.05/N) located in eight genes that are distributed on different chromosomes were associated with drought resistance indices under drought stress. Among these genes, four genes were linked via the associated SNPs with drought-resistance indices of the malondialdehyde activity (MDA), three genes were linked with drought resistance indexes of the superoxide dismutase activity (SOD), and one gene was linked with drought resistance indexes of relative conductivity (REC). The candidate genes functioned as transcription factors, enzymes, and transporters, which included trehalase, the AP2/EREB160 transcription factor, and glutathione S-transferase and also encoded a gene of unknown function. These genes may be directly or indirectly involved in drought resistance. The expression levels of ZmEREB160 responded to ABA and drought stress.

CONCLUSIONS

These results provided good information to understand the genetic basis of variation in drought resistance indices of biochemical and physiological indicators during drought stress.

Genetic analysis of three maize husk traits by QTL mapping in a maize-teosinte population

BACKGROUND

The maize husk consists of numerous leafy layers and plays vital roles in protecting the ear from pathogen infection and dehydration. Teosinte, the wild ancestor of maize, has about three layers of small husk outer covering the ear. Although several quantitative trait loci (QTL) underlying husk morphology variation have been reported, the genetic basis of husk traits between teosinte and maize remains unclear.

RESULTS

A linkage population including 191 BC₂F₈ inbred lines generated from the maize line Mo17 and the teosinte line X26-4 was used to identify QTL associated with three husk traits: i.e., husk length (HL), husk width (HW) and the number of husk layers (HN). The best linear unbiased predictor (BLUP) depicted wide phenotypic variation and high heritability of all three traits. The HL exhibited greater correlation with HW than HN. A total of 4 QTLs were identified including 1, 1, 2, which are associated with HL, HW and HN, respectively. The proportion of phenotypic variation explained by these QTLs was 9.6, 8.9 and 8.1% for HL, HN and HW, respectively.

CONCLUSIONS

The QTLs identified in this study will pave a path to explore candidate genes regulating husk growth and development, and benefit the molecular breeding program based on molecular marker-assisted selection to cultivate maize varieties with an ideal husk morphology.

Genetic dissection of Striga hermonthica (Del.) Benth. resistance via genome-wide association and genomic prediction in tropical maize germplasm

KEY MESSAGE

Genome-wide association revealed that resistance to Striga hermonthica is influenced by multiple genomic regions with moderate effects. It is possible to increase genetic gains from selection for Striga resistance using genomic prediction. Striga hermonthica (Del.) Benth., commonly known as the purple witchweed or giant witchweed, is a serious problem for maize-dependent smallholder farmers in sub-Saharan Africa. Breeding for Striga resistance in maize is complicated due to limited genetic variation, complexity of resistance and challenges with phenotyping. This study was conducted to (i) evaluate a set of diverse tropical maize lines for their responses to Striga under artificial infestation in three environments in Kenya; (ii) detect quantitative trait loci associated with Striga resistance through genome-wide association study (GWAS); and (iii) evaluate the effectiveness of genomic prediction (GP) of Striga-related traits. An association mapping panel of 380 inbred lines was evaluated in three environments under artificial Striga infestation in replicated trials and genotyped with 278,810 single-nucleotide polymorphism (SNP) markers. Genotypic and genotype x environment variations were significant for measured traits associated with Striga resistance. Heritability estimates were moderate (0.42) to high (0.92) for measured traits. GWAS revealed 57 SNPs significantly associated with Striga resistance indicator traits and grain yield (GY) under artificial Striga infestation with low to moderate effect. A set of 32 candidate genes physically near the significant SNPs with roles in plant defense against biotic stresses were identified. GP with different cross-validations revealed that prediction of performance of lines in new environments is better than prediction of performance of new lines for all traits. Predictions across environments revealed high accuracy for all the traits, while inclusion of GWAS-detected SNPs led to slight increase in the accuracy. The item-based collaborative filtering approach that incorporates related traits evaluated in different environments to predict GY and Striga-related traits outperformed GP for Striga resistance indicator traits. The results demonstrated the polygenic nature of resistance to S. hermonthica, and that implementation of GP in Striga resistance breeding could potentially aid in increasing genetic gain for this important trait.

Genome-Wide Association Study of Maize Aboveground Dry Matter Accumulation at Seedling Stage

Dry matter accumulation and partitioning during the early phases of development could significantly affect crop growth and productivity. In this study, the aboveground dry matter (DM), the DM of different organs, and partition coefficients of a maize association mapping panel of 412 inbred lines were evaluated at the third and sixth leaf stages (V3 and V6). Further, the properties of these phenotypic traits were analyzed. Genome-wide association studies (GWAS) were conducted on the total aboveground biomass and the DM of different organs. Analysis of GWAS results identified a total of 1,103 unique candidate genes annotated by 678 significant SNPs (P value < 1.28e-6). A total of 224 genes annotated by SNPs at the top five of each GWAS method and detected by multiple GWAS methods were regarded as having high reliability. Pathway enrichment analysis was also performed to explore the biological significance and functions of these candidate genes. Several biological pathways related to the regulation of seed growth, gibberellin-mediated signaling pathway, and long-day photoperiodism were enriched. The results of our study could provide new perspectives on breeding high-yielding maize varieties.

Genetic Dissection of Hybrid Performance and Heterosis for Yield-Related Traits in Maize

Heterosis contributes a big proportion to hybrid performance in maize, especially for grain yield. It is attractive to explore the underlying genetic architecture of hybrid performance and heterosis. Considering its complexity, different from former mapping method, we developed a series of linear mixed models incorporating multiple polygenic covariance structures to quantify the contribution of each genetic component (additive, dominance, additive-by-additive, additive-by-dominance, and dominance-by-dominance) to hybrid performance and midparent heterosis variation and to identify significant additive and non-additive (dominance and epistatic) quantitative trait loci (QTL). Here, we developed a North Carolina II population by crossing 339 recombinant inbred lines with two elite lines (Chang7-2 and Mo17), resulting in two populations of hybrids signed as Chang7-2 × recombinant inbred lines and Mo17 × recombinant inbred lines, respectively. The results of a path analysis showed that kernel number per row and hundred grain weight contributed the most to the variation of grain yield. The heritability of midparent heterosis for 10 investigated traits ranged from 0.27 to 0.81. For the 10 traits, 21 main (additive and dominance) QTL for hybrid performance and 17 dominance QTL for midparent heterosis were identified in the pooled hybrid populations with two overlapping QTL. Several of the identified QTL showed pleiotropic effects. Significant epistatic QTL were also identified and were shown to play an important role in ear height variation. Genomic selection was used to assess the influence of QTL on prediction accuracy and to explore the strategy of heterosis utilization in maize breeding. Results showed that treating significant single nucleotide polymorphisms as fixed effects in the linear mixed model could improve the prediction accuracy under prediction schemes 2 and 3. In conclusion, the different analyses all substantiated the different genetic architecture of hybrid performance and midparent heterosis in maize. Dominance contributes the highest proportion to heterosis, especially for grain yield, however, epistasis contributes the highest proportion to hybrid performance of grain yield.

Genome-Wide Association Analysis Coupled With Transcriptome Analysis Reveals Candidate Genes Related to Salt Stress in Alfalfa (Medicago sativa L.)

Salt stress is the main abiotic factor affecting alfalfa yield and quality. However, knowledge of the genetic basis of the salt stress response in alfalfa is still limited. Here, a genome-wide association study (GWAS) involving 875,023 single-nucleotide polymorphisms (SNPs) was conducted on 220 alfalfa varieties under both normal and salt-stress conditions. Phenotypic analysis showed that breeding status and geographical origin play important roles in the alfalfa salt stress response. For germination ability under salt stress, a total of 15 significant SNPs explaining 9%-14% of the phenotypic variation were identified. For tolerance to salt stress in the seedling stage, a total of 18 significant SNPs explaining 12%-23% of the phenotypic variation were identified. Transcriptome analysis revealed 2,097 and 812 differentially expressed genes (DEGs) that were upregulated and 2,445 and 928 DEGs that were downregulated in the leaves and roots, respectively, under salt stress. Among these DEGs, many encoding transcription factors (TFs) were found, including MYB-, CBF-, NAC-, and bZIP-encoding genes. Combining the results of our GWAS analysis and transcriptome analysis, we identified a total of eight candidate genes (five candidate genes for tolerance to salt stress and three candidate genes for germination ability under salt stress). Two SNPs located within the upstream region of MsAUX28, which encodes an auxin response protein, were significantly associated with tolerance to salt stress. The two significant SNPs within the upstream region of MsAUX28 existed as three different haplotypes in this panel. Hap 1 (G/G, A/A) was under selection in the alfalfa domestication and improvement process.

Benefiting others and self: Production of vitamins in plants

Vitamins maintain growth and development in humans, animals, and plants. Because plants serve as essential producers of vitamins, increasing the vitamin contents in plants has become a goal of crop breeding worldwide. Here, we begin with a summary of the functions of vitamins. We then review the achievements to date in elucidating the molecular mechanisms underlying how vitamins are synthesized, transported, and regulated in plants. We also stress the exploration of variation in vitamins by the use of forward genetic approaches, such as quantitative trait locus mapping and genome-wide association studies. Overall, we conclude that exploring the diversity of vitamins could provide new insights into plant metabolism and crop breeding.

Genome-wide association studies in tropical maize germplasm reveal novel and known genomic regions for resistance to Northern corn leaf blight

Northern Corn Leaf Blight (NCLB) caused by Setosphaeria turcica, is one of the most important diseases of maize world-wide, and one of the major reasons behind yield losses in maize crop in Asia. In the present investigation, a high-resolution genome wide association study (GWAS) was conducted for NCLB resistance in three association mapping panels, predominantly consisting of tropical lines adapted to different agro-ecologies. These panels were phenotyped for disease severity across three locations with high disease prevalence in India. High density SNPs from Genotyping-by-sequencing were used in GWAS, after controlling for population structure and kinship matrices, based on single locus mixed linear model (MLM). Twenty-two SNPs were identified, that revealed a significant association with NCLB in the three mapping panels. Haplotype regression analysis revealed association of 17 significant haplotypes at FDR ≤ 0.05, with two common haplotypes across three maize panels. Several of the significantly associated SNPs/haplotypes were found to be co-located in chromosomal bins previously reported for major genes like Ht2, Ht3 and Htn1 and QTL for NCLB resistance and multiple foliar disease resistance. Phenotypic variance explained by these significant SNPs/haplotypes ranged from low to moderate, suggesting a breeding strategy of combining multiple resistance alleles towards resistance for NCLB.

Genetic Dissection of Resistance to Gray Leaf Spot by Combining Genome-Wide Association, Linkage Mapping, and Genomic Prediction in Tropical Maize Germplasm

Gray leaf spot (GLS) is one of the major maize foliar diseases in sub-Saharan Africa. Resistance to GLS is controlled by multiple genes with additive effect and is influenced by both genotype and environment. The objectives of the study were to dissect the genetic architecture of GLS resistance through linkage mapping and genome-wide association study (GWAS) and assessing the potential of genomic prediction (GP). We used both biparental populations and an association mapping panel of 410 diverse tropical/subtropical inbred lines that were genotyped using genotype by sequencing. Phenotypic evaluation in two to four environments revealed significant genotypic variation and moderate to high heritability estimates ranging from 0.43 to 0.69. GLS was negatively and significantly correlated with grain yield, anthesis date, and plant height. Linkage mapping in five populations revealed 22 quantitative trait loci (QTLs) for GLS resistance. A QTL on chromosome 7 (qGLS7-105) is a major-effect QTL that explained 28.2% of phenotypic variance. Together, all the detected QTLs explained 10.50, 49.70, 23.67, 18.05, and 28.71% of phenotypic variance in doubled haploid (DH) populations 1, 2, 3, and F3 populations 4 and 5, respectively. Joint linkage association mapping across three DH populations detected 14 QTLs that individually explained 0.10-15.7% of phenotypic variance. GWAS revealed 10 significantly (p < 9.5 × 10-6) associated SNPs distributed on chromosomes 1, 2, 6, 7, and 8, which individually explained 6-8% of phenotypic variance. A set of nine candidate genes co-located or in physical proximity to the significant SNPs with roles in plant defense against pathogens were identified. GP revealed low to moderate prediction correlations of 0.39, 0.37, 0.56, 0.30, 0.29, and 0.38 for within IMAS association panel, DH pop1, DH pop2, DH pop3, F3 pop4, and F3 po5, respectively, and accuracy was increased substantially to 0.84 for prediction across three DH populations. When the diversity panel was used as training set to predict the accuracy of GLS resistance in biparental population, there was 20-50% reduction compared to prediction within populations. Overall, the study revealed that resistance to GLS is quantitative in nature and is controlled by many loci with a few major and many minor effects. The SNPs/QTLs identified by GWAS and linkage mapping can be potential targets in improving GLS resistance in breeding programs, while GP further consolidates the development of high GLS-resistant lines by incorporating most of the major- and minor-effect genes.

Assessment of the Potential for Genomic Selection To Improve Husk Traits in Maize

Husk has multiple functions such as protecting ears from diseases, infection, and dehydration during development. Additionally, husks comprised of fewer, shorter, thinner, and narrower layers allow faster moisture evaporation of kernels prior to harvest. Intensive studies have been conducted to identify appropriate husk architecture by understanding the genetic basis of related traits, including husk length, husk layer number, husk thickness, and husk width. However, marker-assisted selection is inefficient because the identified quantitative trait loci and associated genetic loci could only explain a small proportion of total phenotypic variation. Genomic selection (GS) has been used successfully on many species including maize on other traits. Thus, the potential of using GS for husk traits to directly identify superior inbred lines, without knowing the specific underlying genetic loci, is well worth exploring. In this study, we compared four GS models on a maize association population with 498 inbred lines belonging to four subpopulations, including 27 lines in stiff stalk, 67 lines in non-stiff stalk, 193 lines in tropical-subtropical, and 211 lines in mixture subpopulations. Genomic Best Linear Unbiased Prediction with principal components as cofactor, performed the best and was selected to examine the impact of interaction between sampling proportions and subpopulations. We found that predictions on inbred lines in a subpopulation were benefited from excluding individuals from other subpopulations for training if the training population within the subpopulation was large enough. Husk thickness exhibited the highest prediction accuracy among all husk traits. These results gave strategic insight to improve husk architecture.

Combination of Linkage Mapping, GWAS, and GP to Dissect the Genetic Basis of Common Rust Resistance in Tropical Maize Germplasm

Common rust (CR) caused by Puccina sorghi is one of the destructive fungal foliar diseases of maize and has been reported to cause moderate to high yield losses. Providing CR resistant germplasm has the potential to increase yields. To dissect the genetic architecture of CR resistance in maize, association mapping, in conjunction with linkage mapping, joint linkage association mapping (JLAM), and genomic prediction (GP) was conducted on an association-mapping panel and five F₃ biparental populations using genotyping-by-sequencing (GBS) single-nucleotide polymorphisms (SNPs). Analysis of variance for the biparental populations and the association panel showed significant genotypic and genotype x environment (GXE) interaction variances except for GXE of Pop4. Heritability (h²) estimates were moderate with 0.37-0.45 for the individual F₃ populations, 0.45 across five populations and 0.65 for the association panel. Genome-wide association study (GWAS) analyses revealed 14 significant marker-trait associations which individually explained 6-10% of the total phenotypic variances. Individual population-based linkage analysis revealed 26 QTLs associated with CR resistance and together explained 14-40% of the total phenotypic variances. Linkage mapping revealed seven QTLs in pop1, nine QTL in pop2, four QTL in pop3, five QTL in pop4, and one QTL in pop5, distributed on all chromosomes except chromosome 10. JLAM for the 921 F3 families from five populations detected 18 QTLs distributed in all chromosomes except on chromosome 8. These QTLs individually explained 0.3 to 3.1% and together explained 45% of the total phenotypic variance. Among the 18 QTL detected through JLAM, six QTLs, qCR1-78, qCR1-227, qCR3-172, qCR3-186, qCR4-171, and qCR7-137 were also detected in linkage mapping. GP within population revealed low to moderate correlations with a range from 0.19 to 0.51. Prediction correlation was high with r = 0.78 for combined analysis of the five F₃ populations. Prediction of biparental populations by using association panel as training set reveals positive correlations ranging from 0.05 to 0.22, which encourages to develop an independent but related population as a training set which can be used to predict diverse but related populations. The findings of this study provide valuable information on understanding the genetic basis of CR resistance and the obtained information can be used for developing functional molecular markers for marker-assisted selection and for implementing GP to improve CR resistance in tropical maize.

PANOMICS meets germplasm

Genotyping-by-sequencing has enabled approaches for genomic selection to improve yield, stress resistance and nutritional value. More and more resource studies are emerging providing 1000 and more genotypes and millions of SNPs for one species covering a hitherto inaccessible intraspecific genetic variation. The larger the databases are growing, the better statistical approaches for genomic selection will be available. However, there are clear limitations on the statistical but also on the biological part. Intraspecific genetic variation is able to explain a high proportion of the phenotypes, but a large part of phenotypic plasticity also stems from environmentally driven transcriptional, post-transcriptional, translational, post-translational, epigenetic and metabolic regulation. Moreover, regulation of the same gene can have different phenotypic outputs in different environments. Consequently, to explain and understand environment-dependent phenotypic plasticity based on the available genotype variation we have to integrate the analysis of further molecular levels reflecting the complete information flow from the gene to metabolism to phenotype. Interestingly, metabolomics platforms are already more cost-effective than NGS platforms and are decisive for the prediction of nutritional value or stress resistance. Here, we propose three fundamental pillars for future breeding strategies in the framework of Green Systems Biology: (i) combining genome selection with environment-dependent PANOMICS analysis and deep learning to improve prediction accuracy for marker-dependent trait performance; (ii) PANOMICS resolution at subtissue, cellular and subcellular level provides information about fundamental functions of selected markers; (iii) combining PANOMICS with genome editing and speed breeding tools to accelerate and enhance large-scale functional validation of trait-specific precision breeding.

PANOMICS meets germplasm

Genotyping-by-sequencing has enabled approaches for genomic selection to improve yield, stress resistance and nutritional value. More and more resource studies are emerging providing 1000 and more genotypes and millions of SNPs for one species covering a hitherto inaccessible intraspecific genetic variation. The larger the databases are growing, the better statistical approaches for genomic selection will be available. However, there are clear limitations on the statistical but also on the biological part. Intraspecific genetic variation is able to explain a high proportion of the phenotypes, but a large part of phenotypic plasticity also stems from environmentally driven transcriptional, post-transcriptional, translational, post-translational, epigenetic and metabolic regulation. Moreover, regulation of the same gene can have different phenotypic outputs in different environments. Consequently, to explain and understand environment-dependent phenotypic plasticity based on the available genotype variation we have to integrate the analysis of further molecular levels reflecting the complete information flow from the gene to metabolism to phenotype. Interestingly, metabolomics platforms are already more cost-effective than NGS platforms and are decisive for the prediction of nutritional value or stress resistance. Here, we propose three fundamental pillars for future breeding strategies in the framework of Green Systems Biology: (i) combining genome selection with environment-dependent PANOMICS analysis and deep learning to improve prediction accuracy for marker-dependent trait performance; (ii) PANOMICS resolution at subtissue, cellular and subcellular level provides information about fundamental functions of selected markers; (iii) combining PANOMICS with genome editing and speed breeding tools to accelerate and enhance large-scale functional validation of trait-specific precision breeding.

Genome-Wide Association Study Dissects the Genetic Architecture of Maize Husk Tightness

The husk is a leafy outer tissue that encloses a maize ear. Previously, we identified the optimum husk structure by measuring the husk length, husk layer number, husk thickness and husk width. Husk tightness (HTI) is a combined trait based on the above four husk measurements. Unveiling the genetic basis of HTI will aid in guiding the genetic improvement of maize for mechanical harvesting and for protecting the ear from pest damage and pathogen infection. Here, we used a maize associate population of 508 inbred lines with tropical, subtropical and temperate backgrounds to analyze the genetic architecture of HTI. Evaluating the phenotypic diversity in three different environments showed that HTI exhibited broad natural variations and a moderate heritability level of 0.41. A diversity analysis indicated that the inbred lines having a temperate background were more loosely related than those having a tropical or subtropical background. HTI showed significant negative correlations with husk thickness and width, which indicates that thicker and wider husks wrapped the ear tighter than thinner and slimmer husks. Combining husk traits with ∼1.25 million single nucleotide polymorphisms in a genome-wide association study revealed 27 variants that were significantly associated with HTI above the threshold of P < 7.26 × 10^-6. We found 27 candidate genes for HTI that may participate in (1) husk senescence involving lipid peroxidation (GRMZM2G017616) and programmed cell death (GRMZM2G168898 and GRMZM2G035045); (2) husk morphogenesis involving cell division (GRMZM5G869246) and cell wall architecture (GRMZM2G319798); and (3) cell signal transduction involving protein phosphorylation (GRMZM2G149277 and GRMZM2G004207) and the ABSISIC ACID INSENSITIVE3/VIVIPAROUS1 transcription factor (GRMZM2G088427). These results provide useful information for understanding the genetic basis of husk development. Further studies of identified candidate genes will help elucidate the molecular pathways that regulate HTI in maize.

Denser Markers and Advanced Statistical Method Identified More Genetic Loci Associated with Husk Traits in Maize

The husk—the leaf-like outer covering of maize ear—has multiple functions, including protecting the ear from diseases infection and dehydration. In previous studies, we genotyped an association panel of 508 inbred lines genotyped with a total of ~550,000 SNPs (Illumina 50 K SNP Chip and RNA-seq). Genome-Wide Association Studies (GWAS) were conducted on four husk traits: husk length (HL), husk layer number (HN), husk thickness (HT), and husk width (HW). Minimal associations were identified and none of them passed the P-value threshold after a Bonferroni multiple-test correction using a single locus test in framework of mixed linear model. In this study, we doubled the number of SNPs (~1,250,000 in total) by adding GBS and 600 K SNP Chip. GWAS, performed with the recently developed multiple loci model (BLINK), revealed six genetic loci associated with HN and HT above the Bonferroni multiple-test threshold. Five candidate genes were identified based on the linkage disequilibrium with these loci, including GRMZM2G381691 and GRMZM2G012416. These two genes were up-regulation and down-regulation in all husk related tissues, respectively. GRMZM2G381691 associated with HT encoded a CCT domain protein, which expressed higher in tropical than temperate maize. GRMZM2G012416 associated with HN encoded an Armadillo (ARM) repeat protein, which regulated GA signal pathway. These associated SNPs and candidate genes paved a path to understand the genetic architecture of husk in maize.

Mining and genomic characterization of resistance to tan spot, Stagonospora nodorum blotch (SNB), and Fusarium head blight in Watkins core collection of wheat landraces

BACKGROUND

In the late 1920s, A. E. Watkins collected about 7000 landrace cultivars (LCs) of bread wheat (Triticum aestivum L.) from 32 different countries around the world. Among which 826 LCs remain viable and could be a valuable source of superior/favorable alleles to enhance disease resistance in wheat. In the present study, a core set of 121 LCs, which captures the majority of the genetic diversity of Watkins collection, was evaluated for identifying novel sources of resistance against tan spot, Stagonospora nodorum blotch (SNB), and Fusarium Head Blight (FHB).

RESULTS

A diverse response was observed in 121 LCs for all three diseases. The majority of LCs were moderately susceptible to susceptible to tan spot Ptr race 1 (84%) and FHB (96%) whereas a large number of LCs were resistant or moderately resistant against tan spot Ptr race 5 (95%) and SNB (54%). Thirteen LCs were identified in this study could be a valuable source for multiple resistance to tan spot Ptr races 1 and 5, and SNB, and another five LCs could be a potential source for FHB resistance. GWAS analysis was carried out using disease phenotyping score and 8807 SNPs data of 118 LCs, which identified 30 significant marker-trait associations (MTAs) with -log10 (p-value) > 3.0. Ten, five, and five genomic regions were found to be associated with resistance to tan spot Ptr race 1, race 5, and SNB, respectively in this study. In addition to Tsn1, several novel genomic regions Q.Ts1.sdsu-4BS and Q.Ts1.sdsu-5BS (tan spot Ptr race 1) and Q.Ts5.sdsu-1BL, Q.Ts5.sdsu-2DL, Q.Ts5.sdsu-3AL, and Q.Ts5.sdsu-6BL (tan spot Ptr race 5) were also identified. Our results indicate that these putative genomic regions contain several genes that play an important role in plant defense mechanisms.

CONCLUSION

Our results suggest the existence of valuable resistant alleles against leaf spot diseases in Watkins LCs. The single-nucleotide polymorphism (SNP) markers linked to the quantitative trait loci (QTLs) for tan spot and SNB resistance along with LCs harboring multiple disease resistance could be useful for future wheat breeding.

Genetic architecture of maize chlorotic mottle virus and maize lethal necrosis through GWAS, linkage analysis and genomic prediction in tropical maize germplasm

KEY MESSAGE

Analysis of the genetic architecture of MCMV and MLN resistance in maize doubled-haploid populations revealed QTLs with major effects on chromosomes 3 and 6 that were consistent across genetic backgrounds and environments. Two major-effect QTLs, qMCMV3-108/qMLN3-108 and qMCMV6-17/qMLN6-17, were identified as conferring resistance to both MCMV and MLN. Maize lethal necrosis (MLN) is a serious threat to the food security of maize-growing smallholders in sub-Saharan Africa. The ability of the maize chlorotic mottle virus (MCMV) to interact with other members of the Potyviridae causes severe yield losses in the form of MLN. The objective of the present study was to gain insights and validate the genetic architecture of resistance to MCMV and MLN in maize. We applied linkage mapping to three doubled-haploid populations and a genome-wide association study (GWAS) on 380 diverse maize lines. For all the populations, phenotypic variation for MCMV and MLN was significant, and heritability was moderate to high. Linkage mapping revealed 13 quantitative trait loci (QTLs) for MCMV resistance and 12 QTLs conferring MLN resistance. One major-effect QTL, qMCMV3-108/qMLN3-108, was consistent across populations for both MCMV and MLN resistance. Joint linkage association mapping (JLAM) revealed 18 and 21 main-effect QTLs for MCMV and MLN resistance, respectively. Another major-effect QTL, qMCMV6-17/qMLN6-17, was detected for both MCMV and MLN resistance. The GWAS revealed a total of 54 SNPs (MCMV-13 and MLN-41) significantly associated (P ≤ 5.60 × 10-05) with MCMV and MLN resistance. Most of the GWAS-identified SNPs were within or adjacent to the QTLs detected through linkage mapping. The prediction accuracy for within populations as well as the combined populations is promising; however, the accuracy was low across populations. Overall, MCMV resistance is controlled by a few major and many minor-effect loci and seems more complex than the genetic architecture for MLN resistance.

Genome-wide association study of kernel moisture content at harvest stage in maize

Kernel moisture content at harvest stage (KMC) is an important factor affecting maize production, especially for mechanical harvesting. We investigated the genetic basis of KMC using an association panel comprising of 144 maize inbred lines that were phenotypically evaluated at two field trial locations. Significant positive or negative correlations were identified between KMC and a series of other agronomic traits, indicating that KMC is associated with other such traits. Combining phenotypic values and the Maize SNP3K Beadchip to perform a genome-wide association study revealed eight single nucleotide polymorphisms (SNPs) associated with KMC at P ≤ 0.001 using a mixed linear model (PCA+K). These significant SNPs could be converted into five quantitative trait loci (QTLs) distributed on chromosomes 1, 5, 8, and 9. Of these QTLs, three were colocalized with genomic regions previously reported. Based on the phenotypic values of the alleles corresponding to significant SNPs, the favorable alleles were mined. Eight maize inbred lines with low KMC and harboring favorable alleles were identified. These QTLs and elite maize inbred lines with low KMC will be useful in maize breeding.

Comparative functional genomics analysis of bHLH gene family in rice, maize and wheat

BACKGROUND

The basic helix-loop-helix transcription factors play important roles in diverse cellular and molecular processes. Comparative functional genomics can provide powerful approaches to draw inferences about gene function and evolution among species. The comprehensive comparison of bHLH gene family in different gramineous plants has not yet been reported.

RESULTS

In this study, a total of 183, 231 and 571 bHLHs were identified in rice, maize and wheat genomes respectively, and 1154 bHLH genes from the three species and Arabidopsis were classified into 36 subfamilies. Of the identified genes, 110 OsbHLHs, 188 ZmbHLHs and 209 TabHLHs with relatively high mRNA abundances were detected in one or more tissues during development, and some of them exhibited tissue-specific expression such as TabHLH454-459, ZmbHLH099-101 and OsbHLH037 in root, TabHLH559-562, - 046, - 047 and ZmbHLH010, - 072, - 226 in leaf, TabHLH216-221, - 333, - 335, - 340 and OsbHLH005, - 141 in inflorescence, TabHLH081, ZmbHLH139 and OsbHLH144 in seed. Forty five, twenty nine and thirty one differentially expressed bHLHs were respectively detected in wheat, maize and rice under drought stresses using RNA-seq technology. Among them, the expressions of TabHLH046, - 047, ZmbHLH097, - 098, OsbHLH006 and - 185 were strongly induced, whereas TabHLH303, - 562, ZmbHLH155, - 154, OsbHLH152 and - 113 showed significant down-regulation. Twenty two TabHLHs were induced after stripe rust infection at 24 h and nine of them were suppressed at 72 hpi, whereas 28 and 6 TabHLHs exhibited obviously down- and up-regulation after powdery mildew attack respectively. Forty one ZmbHLHs were differentially expressed in response to F. verticillioides infection. Twenty two co-expression modules were identified by the WGCNA, some of which were associated with particular tissue types. And GO enrichment analysis for the modules showed that some TabHLHs were involved in the control of several biological processes, such as tapetal PCD, lipid metabolism, iron absorption, stress responses and signal regulation.

CONCLUSION

The present study identifies the bHLH family in rice, maize and wheat genomes, and detailedly discusses the evolutionary relationships, expression and function of bHLHs. This study provides some novel and detail information about bHLHs, and may facilitate understanding the molecular basis of the plant growth, development and stress physiology.

Linkage mapping combined with association analysis reveals QTL and candidate genes for three husk traits in maize

Key message Combined linkage and association mapping analyses facilitate the emphasis on the candidate genes putatively involved in maize husk growth. The maize (Zea mays L.) husk consists of multiple leafy layers and plays important roles in protecting the ear from pathogen infection and in preventing grain dehydration. Although husk morphology varies widely among different maize inbred lines, the genetic basis of such variation is poorly understood. In this study, we used three maize recombinant inbred line (RIL) populations to dissect the genetic basis of three husk traits: i.e., husk length (HL), husk width (HW), and the number of husk layers (HN). Three husk traits in all three RIL populations showed wide phenotypic variation and high heritability. The HL showed stronger correlations with ear traits than did HW and HN. A total of 21 quantitative trait loci (QTL) were identified for the three traits in three RIL populations, and some of them were commonly observed for the same trait in different populations. The proportions of total phenotypic variation explained by QTL in three RIL populations were 31.8, 35.3, and 44.5% for HL, HW, and HN, respectively. The highest proportions of phenotypic variation explained by a single QTL were 14.7% for HL in the By815/K22 RIL population (BYK), 13.5% for HW in the By815/DE3 RIL population (BYD), and 19.4% for HN in the BYD population. A combined analysis of linkage mapping with a previous genome-wide association study revealed five candidate genes related to husk morphology situated within three QTL loci. These five genes were related to metabolism, gene expression regulation, and signal transduction.

Genetic characterization of inbred lines from Shaan A and B groups for identifying loci associated with maize grain yield

BACKGROUND

Increasing grain yield is a primary objective of maize breeding. Dissecting the genetic architecture of grain yield furthers genetic improvements to increase yield. Presented here is an association panel composed of 126 maize inbreds (AM126), which were genotyped by the genotyping-by-sequencing (tGBS) method. We performed genetic characterization and association analysis related to grain yield in the association panel.

RESULTS

In total, 46,046 SNPs with a minor allele frequency (MAF) ≥0.01 were used to assess genetic diversity and kinship in AM126. The results showed that the average MAF and polymorphism information content (PIC) were 0.164 and 0.198, respectively. The Shaan B group, with 11,284 unique SNPs, exhibited greater genetic diversity than did the Shaan A group, with 2644 SNPs. The 61.82% kinship coefficient in AM126 was equal to 0, and only 0.15% of that percentage was greater than 0.7. A total of 31,983 SNPs with MAF ≥0.05 were used to characterize population structure, LD decay and association mapping. Population structure analysis suggested that AM126 can be divided into 6 subgroups, which is consistent with breeding experience and pedigree information. The LD decay distance in AM126 was 150 kb. A total of 51 significant SNPs associated with grain yield were identified at P < 1 × 10- 3 across two environments (Yangling and Yulin). Among those SNPs, two loci displayed overlapping regions in the two environments. Finally, 30 candidate genes were found to be associated with grain yield.

CONCLUSIONS

These results contribute to the genetic characterization of this breeding population, which serves as a reference for hybrid breeding and population improvement, and demonstrate the genetic architecture of maize grain yield, potentially facilitating genetic improvement.

Identification and validation of genomic regions influencing kernel zinc and iron in maize

KEY MESSAGE

Genome-wide association study (GWAS) on 923 maize lines and validation in bi-parental populations identified significant genomic regions for kernel-Zinc and-Iron in maize. Bio-fortification of maize with elevated Zinc (Zn) and Iron (Fe) holds considerable promise for alleviating under-nutrition among the world's poor. Bio-fortification through molecular breeding could be an economical strategy for developing nutritious maize, and hence in this study, we adopted GWAS to identify markers associated with high kernel-Zn and Fe in maize and subsequently validated marker-trait associations in independent bi-parental populations. For GWAS, we evaluated a diverse maize association mapping panel of 923 inbred lines across three environments and detected trait associations using high-density Single nucleotide polymorphism (SNPs) obtained through genotyping-by-sequencing. Phenotyping trials of the GWAS panel showed high heritability and moderate correlation between kernel-Zn and Fe concentrations. GWAS revealed a total of 46 SNPs (Zn-20 and Fe-26) significantly associated (P ≤ 5.03 × 10-05) with kernel-Zn and Fe concentrations with some of these associated SNPs located within previously reported QTL intervals for these traits. Three double-haploid (DH) populations were developed using lines identified from the panel that were contrasting for these micronutrients. The DH populations were phenotyped at two environments and were used for validating significant SNPs (P ≤ 1 × 10-03) based on single marker QTL analysis. Based on this analysis, 11 (Zn) and 11 (Fe) SNPs were found to have significant effect on the trait variance (P ≤ 0.01, R2 ≥ 0.05) in at least one bi-parental population. These findings are being pursued in the kernel-Zn and Fe breeding program, and could hold great value in functional analysis and possible cloning of high-value genes for these traits in maize.

Genetic Diversity and Genome-Wide Association Study of Major Ear Quantitative Traits Using High-Density SNPs in Maize

Kernel and ear traits are key components of grain yield in maize (Zea mays L.). Investigation of these traits would help to develop high-yield varieties in maize. Genome-wide association study (GWAS) uses the linkage disequilibrium (LD) in the whole genome to determine the genes affecting certain phenotype. In this study, five ear traits (kernel length and width, ear length and diameter, cob diameter) were investigated across multi-environments for 2 years. Combining with the genotype obtained from Maize SNP50 chip, genetic diversity and association mapping in a set of 292 inbred lines were performed. Results showed that maize lines were clustered into seven subgroups and a total of 20 SNPs were found to be associated with ear traits significantly (P < 3.95E-05). The candidate genes identified by GWAS mainly encoded ubiquitin-activation enzymes (GRMZM2G015287), carotenoid cleavage dioxygenase (GRMZM2G446858), MYB-CC type transfactor, and phosphate starvation response protein 3, and they were associated with kernel length (KL) and ear diameter (ED), respectively. Moreover, two novel genes corresponding to RNA processing and fructose metabolism were found. Further, the SNPs detected by GWAS were confirmed by meta-QTL analysis. These genes and SNPs identified in the study would offer essential information for yield-related genes clone and breeding program in maize.

Genome-wide association analysis of lead accumulation in maize

Large phenotypic variations in the lead (Pb) concentration were observed in grains and leaves of maize plants. A further understanding of inheritance of Pb accumulation may facilitate improvement of low-Pb-accumulating cultivars in maize. A genome-wide association study was conducted in a population of 269 maize accessions with 43,737 single-nucleotide polymorphisms (SNPs). The Pb concentrations in leaves and kernels of 269 accessions were collected in pot-culture and field experiments in years of 2015 and 2016. Significant differences in Pb accumulation were found among individuals under different environments. Using the structure and kinship model, a total of 21 SNPs significantly associated with the Pb accumulation were identified with P < 2.28 × 10^-5 and FDR < 0.05 in the pot-culture and field experiments across 2 years. Three SNPs on chromosome 4 had significant associations simultaneously with the Pb concentrations of kernels and leaves and were co-localized with the previously detected quantitative trait loci. Through ridge regression best linear unbiased prediction Pb accumulation in the association population, the prediction accuracies by cross validation were 0.18-0.59 and 0.17-0.64, depending on the k-fold and the size of the training population. The results are helpful for genetic improvement and genomic prediction of Pb accumulation in maize.

Genome-wide Association Studies in Maize: Praise and Stargaze

Genome-wide association study (GWAS) has become a widely accepted strategy for decoding genotype-phenotype associations in many species thanks to advances in next-generation sequencing (NGS) technologies. Maize is an ideal crop for GWAS and significant progress has been made in the last decade. This review summarizes current GWAS efforts in maize functional genomics research and discusses future prospects in the omics era. The general goal of GWAS is to link genotypic variations to corresponding differences in phenotype using the most appropriate statistical model in a given population. The current review also presents perspectives for optimizing GWAS design and analysis. GWAS analysis of data from RNA, protein, and metabolite-based omics studies is discussed, along with new models and new population designs that will identify causes of phenotypic variation that have been hidden to date. The joint and continuous efforts of the whole community will enhance our understanding of maize quantitative traits and boost crop molecular breeding designs.