Comprehensive genotyping of the USA national maize inbred seed bank

Regulatory variation controlling architectural pleiotropy in maize

An early event in plant organogenesis is establishment of a boundary between the stem cell containing meristem and differentiating lateral organ. In maize (Zea mays), evidence suggests a common gene network functions at boundaries of distinct organs and contributes to pleiotropy between leaf angle and tassel branch number, two agronomic traits. To uncover regulatory variation at the nexus of these two traits, we use regulatory network topologies derived from specific developmental contexts to guide multivariate genome-wide association analyses. In addition to defining network plasticity around core pleiotropic loci, we identify new transcription factors that contribute to phenotypic variation in canopy architecture, and structural variation that contributes to cis-regulatory control of pleiotropy between tassel branching and leaf angle across maize diversity. Results demonstrate the power of informing statistical genetics with context-specific developmental networks to pinpoint pleiotropic loci and their cis-regulatory components, which can be used to fine-tune plant architecture for crop improvement.

Characterization of Indian waxy and non-waxy maize germplasm for genetic differentiation through SNP genotyping

Waxy maize characterized by high amylopectin content resulting from a recessive wx1 gene, is important for both dietary and industrial applications, yet it suffers from low yields and limited breeding options. This study aims to develop a thorough understanding of the underlying genetics for successful hybridization experiments in waxy maize and the identification of potential cross combinations to derive high-yielding waxy maize hybrids in India. Here, we evaluated the kernel starch composition, yield-related traits, molecular diversity, kinship, LD, population structure, and selection signatures in a panel of 11 waxy and 37 non-waxy maize genotypes. The starch content in the panel ranged from 57.85 to 66.96%, while the amylopectin ranged from 70.65% to 96.32%. A significant positive correlation between kernel starch and amylopectin (0.39**) was identified suggesting the potential for simultaneous improvement of both these traits. The 48 maize lines were genotyped with 24,477 highly polymorphic single nucleotide polymorphisms (SNPs). Seventy-eight per cent of the pair-wise relative kinship values were less than or equal to 0, indicating minimal redundancy in the genomic composition of the inbred lines. The range of genetic distance among the pairs of waxy lines was 0.190 to 0.231 as compared to 0.076-0.264 in the non-waxy genotypes suggesting a greater genetic variation among the non-waxy genotypes. The mean LD value across the genome was 0.44. Two to four groups were identified using the model-based population structure, phylogenetic analysis and principal component analysis with no clear pattern of clustering based on the type of corn. Pairwise comparisons using the SNP dataset between waxy and non-waxy maize detected 27 loci under positive selection. The information generated in this study will be useful in the diversification of Indian waxy maize lines and the development of superior waxy maize hybrids.

Impact of High-Temperature Stress on Maize Seed Setting: Cellular and Molecular Insights of Thermotolerance

Global warming poses a significant threat to crop production and food security, with maize (Zay mays L.) particularly vulnerable to high-temperature stress (HTS). This review explores the detrimental impacts of elevated temperatures on maize development across various growth stages, analyzed within the source-sink framework, with a particular focus on seed setting and yield reduction. It provides a broad analysis of maize cellular and molecular responses to HTS, highlighting the key roles of plant hormone abscisic acid (ABA) signaling, calcium signaling, chloroplast, and the DNA damage repair (DDR) system in maize. HTS disrupts ABA signaling pathways, impairing stomatal regulation and reducing water-use efficiency, while calcium signaling orchestrates stress responses by activating heat shock proteins and other protective mechanisms. Chloroplasts, as central to photosynthesis, are particularly sensitive to HTS, often exhibiting photosystem II damage and chlorophyll degradation. Recent studies also highlight the significance of the DDR system, with genes like ZmRAD51C playing crucial roles in maintaining genomic stability during reproductive organ development. DNA damage under HTS conditions emerges as a key factor contributing to reduced seed set, although the precise molecular mechanisms remain to be fully elucidated. Furthermore, the review examines cutting-edge genetic improvement strategies, aimed at developing thermotolerant maize cultivars. These recent research advances underscore the need for further investigation into the molecular basis of thermotolerance and open the door for future advancements in breeding thermotolerant crops.

Genome-Wide Association Study and Genomic Predictions for Hydroxycinnamate Concentrations in Maize Stover

Hydroxycinnamates, like ferulate (FA) and p-coumarate (pCA), are important components of maize cell walls, which influence pest resistance, ruminal digestibility, and biofuel production. Increasing their concentration has been linked to increased pest resistance, but also may lead to a decrease in nutritional value or bioethanol production efficiency. Therefore, improving forage quality or biofuel production without compromising plant resistance and a thorough understanding of the biosynthesis and deposition of these compounds is necessary, especially in stover, which is the feedstock for second-generation biofuel production and determines animal forage quality. This study aimed to identify genomic regions associated with hydroxycinnamates and to develop genomic prediction models to determine the best selection approach to modify hydroxycinnamate content. Although heritability estimates for hydroxycinnamates were moderate, direct phenotypic selection is discouraged because hydroxycinnamate quantification is laborious and time-consuming. Negative genotypic correlations were observed between animal digestibility and pCA content and positive with diferulates content, suggesting differing effects compared to previous studies on maize pith. However, no colocalizations with digestibility QTLs were found, highlighting the need for further research. Given the moderate predictive capacity of GBLUP prediction models, genotypic selection is proposed as the most promising alternative for modifying hydroxycinnamate content.

Genotyping Genebank Collections: Strategic Approaches and Considerations for Optimal Collection Management

The maintenance of plant germplasm and its genetic diversity is critical to preserving and making it available for food security, so this invaluable diversity is not permanently lost due to population growth and development, climate change, or changing needs from the growers and/or the marketplace. There are numerous genebanks worldwide that serve to preserve valuable plant germplasm for humankind's future and to serve as a resource for research, breeding, and training. The United States Department of Agriculture (USDA) National Plant Germplasm System (NPGS) and the Consultative Group for International Agricultural Research (CGIAR) both have a network of plant germplasm collections scattered across varying geographical locations preserving genetic resources for the future. Besides the USDA and CGIAR, there are germplasm collections established in many countries across the world that also aim to preserve crop and plant collections. Due to the advancement of technology, genotyping and sequencing whole genomes of plant germplasm collections is now feasible. Data from genotyping can help define genetic diversity within a collection, identify genetic gaps, reveal genetic redundancies and verify uniqueness, enable the comparison of collections of the same crop across genebanks (rationalization), and determine errors or mix-ups in genetic identity that may have occurred in a germplasm collection. Large-scale projects, such as genotyping germplasm collections, require strategic planning and the development of best practices. This article details strategies and best practices to consider when genotyping whole collections, considerations for the identity verification of germplasm and determining genetic replicates, quality management systems (QMS)/QC genotyping, and some use cases.

Promises and challenges of crop translational genomics

Crop translational genomics applies breeding techniques based on genomic datasets to improve crops. Technological breakthroughs in the past ten years have made it possible to sequence the genomes of increasing numbers of crop varieties and have assisted in the genetic dissection of crop performance. However, translating research findings to breeding applications remains challenging. Here we review recent progress and future prospects for crop translational genomics in bringing results from the laboratory to the field. Genetic mapping, genomic selection and sequence-assisted characterization and deployment of plant genetic resources utilize rapid genotyping of large populations. These approaches have all had an impact on breeding for qualitative traits, where single genes with large phenotypic effects exert their influence. Characterization of the complex genetic architectures that underlie quantitative traits such as yield and flowering time, especially in newly domesticated crops, will require further basic research, including research into regulation and interactions of genes and the integration of genomic approaches and high-throughput phenotyping, before targeted interventions can be designed. Future priorities for translation include supporting genomics-assisted breeding in low-income countries and adaptation of crops to changing environments.

Morpho-Phenological, Chemical, and Genetic Characterization of Italian Maize Landraces from the Lazio Region

In the framework of a Collaboration Agreement between CREA and ARSIAL, a morpho-phenological, chemical, and genetic characterization of maize populations native to the Lazio region was carried out. During 2022 and 2023, a set of 50 accessions, belonging both to ARSIAL and CREA maize collections, were multiplied in Bergamo. Morpho-phenological descriptors were recorded in the field: plant height, ear height, and male and female flowering time. The grain chemical composition in terms of protein, lipid, starch, ash and fiber was evaluated by near-infrared spectroscopy (NIRS). A double-digest restriction-site-associated DNA sequencing (ddRADseq) strategy was used to genotype the landraces. The two collections were not significantly different in terms of grain chemical composition. On the other hand, the ARSIAL and CREA germplasm showed a different distribution in the three cluster-based population structure obtained by ddRADseq, which largely corresponded to the distribution map of their collection sites. The materials from the Lazio region maintained by ARSIAL and CREA were revealed to be different. The comparison between the two groups of landraces showed the importance of characterizing germplasm collections to promote the recovery and valorization of local biodiversity.

Genomic prediction of cereal crop architectural traits using models informed by gene regulatory circuitries from maize

Plant architecture is a major determinant of planting density, which enhances productivity potential for crops per unit area. Genomic prediction is well positioned to expedite genetic gain of plant architectural traits since they are typically highly heritable. Additionally, the adaptation of genomic prediction models to query predictive abilities of markers tagging certain genomic regions could shed light on the genetic architecture of these traits. Here, we leveraged transcriptional networks from a prior study that contextually described developmental progression during tassel and leaf organogenesis in maize (Zea mays) to inform genomic prediction models for architectural traits. Since these developmental processes underlie tassel branching and leaf angle, 2 important agronomic architectural traits, we tested whether genes prioritized from these networks quantitatively contribute to the genetic architecture of these traits. We used genomic prediction models to evaluate the ability of markers in the vicinity of prioritized network genes to predict breeding values of tassel branching and leaf angle traits for 2 diversity panels in maize and diversity panels from sorghum (Sorghum bicolor) and rice (Oryza sativa). Predictive abilities of markers near these prioritized network genes were similar to those using whole-genome marker sets. Notably, markers near highly connected transcription factors from core network motifs in maize yielded predictive abilities that were significantly greater than expected by chance in not only maize but also closely related sorghum. We expect that these highly connected regulators are key drivers of architectural variation that are conserved across closely related cereal crop species.

Data-driven identification of environmental variables influencing phenotypic plasticity to facilitate breeding for future climates

Phenotypic plasticity describes a genotype's ability to produce different phenotypes in response to different environments. Breeding crops that exhibit appropriate levels of plasticity for future climates will be crucial to meeting global demand, but knowledge of the critical environmental factors is limited to a handful of well-studied major crops. Using 727 maize (Zea mays L.) hybrids phenotyped for grain yield in 45 environments, we investigated the ability of a genetic algorithm and two other methods to identify environmental determinants of grain yield from a large set of candidate environmental variables constructed using minimal assumptions. The genetic algorithm identified pre- and postanthesis maximum temperature, mid-season solar radiation, and whole season net evapotranspiration as the four most important variables from a candidate set of 9150. Importantly, these four variables are supported by previous literature. After calculating reaction norms for each environmental variable, candidate genes were identified and gene annotations investigated to demonstrate how this method can generate insights into phenotypic plasticity. The genetic algorithm successfully identified known environmental determinants of hybrid maize grain yield. This demonstrates that the methodology could be applied to other less well-studied phenotypes and crops to improve understanding of phenotypic plasticity and facilitate breeding crops for future climates.

Differences in activity and stability drive transposable element variation in tropical and temperate maize

Much of the profound interspecific variation in genome content has been attributed to transposable elements (TEs). To explore the extent of TE variation within species, we developed an optimized open-source algorithm, panEDTA, to de novo annotate TEs in a pangenome context. We then generated a unified TE annotation for a maize pangenome derived from 26 reference-quality genomes, which reveals an excess of 35.1 Mb of TE sequences per genome in tropical maize relative to temperate maize. A small number (n = 216) of TE families, mainly LTR retrotransposons, drive these differences. Evidence from the methylome, transcriptome, LTR age distribution, and LTR insertional polymorphisms reveals that 64.7% of the variability is contributed by LTR families that are young, less methylated, and more expressed in tropical maize, whereas 18.5% is driven by LTR families with removal or loss in temperate maize. Additionally, we find enrichment for Young LTR families adjacent to nucleotide-binding and leucine-rich repeat (NLR) clusters of varying copy number across lines, suggesting TE activity may be associated with disease resistance in maize.

Multi-locus genome-wide association study for phosphorus use efficiency in a tropical maize germplasm

Phosphorus (P) is an essential macronutrient for maize (Zea mays L.) growth and development. Therefore, generating cultivars with upgraded P use efficiency (PUE) represents one of the main strategies to reduce the global agriculture dependence on phosphate fertilizers. In this work, genome-wide association studies (GWAS) were performed to detect quantitative trait nucleotide (QTN) and potential PUE-related candidate genes and associated traits in greenhouse and field trials under contrasting P conditions. The PUE and other agronomy traits of 132 maize inbred lines were assessed in low and normal P supply through the greenhouse and field experiments and Multi-locus GWAS was used to map the associated QTNs. Wide genetic variability was observed among the maize inbred lines under low and normal P supply. In addition, we confirm the complex and quantitative nature of PUE. A total of 306 QTNs were associated with the 24 traits evaluated using different multi-locus GWAS methods. A total of 186 potential candidate genes were identified, mainly involved with transcription regulator, transporter, and transference activity. Further studies are still needed to elucidate the functions and relevance of these genes regarding PUE. Nevertheless, pyramiding the favorable alleles pinpointed in the present study can be considered an efficient strategy for molecular improvement to increase maize PUE.

Short-term responses of spider mites inform mechanisms of maize resistance to a generalist herbivore

Plants are attacked by diverse herbivorous pests with different host specializations. While host plant resistance influences pest pressure, how resistance impacts the behaviors of generalist and specialist herbivores, and the relationship to resistance, is less well known. Here, we investigated the short-term (< 1 h) behavioral changes of a generalist herbivore, the two-spotted spider mite (TSM), and a specialist herbivore, the Banks grass mite (BGM), after introduction to no-choice Tanglefoot leaf-arenas (2 × 2 cm) of three maize inbred lines (B73, B75, and B96). The widely-used inbred line B73 is susceptible to spider mites, while B75 and B96 are known to be mite resistant, especially to TSM. Video tracking was used to record TSM and BGM walking, probing, feeding, resting, web-building and travel distance on arenas of each line. Mite oviposition was also recorded after 72 h. B75, a resistant line, decreased the feeding behavior (i.e., time) of both mite species compared to B73 (susceptible control) and B96. Moreover, TSM appeared to be sensitive to both resistant lines (B75 and B96) with reduced oviposition, and increased resting and web-building times compared to susceptible B73. In contrast, the specialist BGM showed no difference in oviposition, resting and web-building time across all maize inbred lines. Our findings of quite broad and short-term responses of TSM to B75 and B96 are consistent with a role for constitutive or rapidly induced plant defenses in maize in conferring TSM resistance. Other mechanisms of plant resistance may be needed, however, for defense against specialists like BGM.

Insights into maydis leaf blight resistance in maize: a comprehensive genome-wide association study in sub-tropics of India

BACKGROUND

In the face of contemporary climatic vulnerabilities and escalating global temperatures, the prevalence of maydis leaf blight (MLB) poses a potential threat to maize production. This study endeavours to discern marker-trait associations and elucidate the candidate genes that underlie resistance to MLB in maize by employing a diverse panel comprising 336 lines. The panel was screening for MLB across four environments, employing standard artificial inoculation techniques. Genome-wide association studies (GWAS) and haplotype analysis were conducted utilizing a total of 128,490 SNPs obtained from genotyping-by-sequencing (GBS).

RESULTS

GWAS identified 26 highly significant SNPs associated with MLB resistance, among the markers examined. Seven of these SNPs, reported in novel chromosomal bins (9.06, 5.01, 9.01, 7.04, 4.06, 1.04, and 6.05) were associated with genes: bzip23, NAGS1, CDPK7, aspartic proteinase NEP-2, VQ4, and Wun1, which were characterized for their roles in diminishing fungal activity, fortifying defence mechanisms against necrotrophic pathogens, modulating phyto-hormone signalling, and orchestrating oxidative burst responses. Gene mining approach identified 22 potential candidate genes associated with SNPs due to their functional relevance to resistance against necrotrophic pathogens. Notably, bin 8.06, which hosts five SNPs, showed a connection to defense-regulating genes against MLB, indicating the potential formation of a functional gene cluster that triggers a cascade of reactions against MLB. In silico studies revealed gene expression levels exceeding ten fragments per kilobase million (FPKM) for most genes and demonstrated coexpression among all candidate genes in the coexpression network. Haplotype regression analysis revealed the association of 13 common significant haplotypes at Bonferroni ≤ 0.05. The phenotypic variance explained by these significant haplotypes ranged from low to moderate, suggesting a breeding strategy that combines multiple resistance alleles to enhance resistance to MLB. Additionally, one particular haplotype block (Hap_8.3) was found to consist of two SNPs (S8_152715134, S8_152460815) identified in GWAS with 9.45% variation explained (PVE).

CONCLUSION

The identified SNPs/ haplotypes associated with the trait of interest contribute to the enrichment of allelic diversity and hold direct applicability in Genomics Assisted Breeding for enhancing MLB resistance in maize.

Plant pangenomes for crop improvement, biodiversity and evolution

Plant genome sequences catalogue genes and the genetic elements that regulate their expression. Such inventories further research aims as diverse as mapping the molecular basis of trait diversity in domesticated plants or inquiries into the origin of evolutionary innovations in flowering plants millions of years ago. The transformative technological progress of DNA sequencing in the past two decades has enabled researchers to sequence ever more genomes with greater ease. Pangenomes - complete sequences of multiple individuals of a species or higher taxonomic unit - have now entered the geneticists' toolkit. The genomes of crop plants and their wild relatives are being studied with translational applications in breeding in mind. But pangenomes are applicable also in ecological and evolutionary studies, as they help classify and monitor biodiversity across the tree of life, deepen our understanding of how plant species diverged and show how plants adapt to changing environments or new selection pressures exerted by human beings.

Are cereal grasses a single genetic system?

In 1993, a passionate and provocative call to arms urged cereal researchers to consider the taxon they study as a single genetic system and collaborate with each other. Since then, that group of scientists has seen their discipline blossom. In an attempt to understand what unity of genetic systems means and how the notion was borne out by later research, we survey the progress and prospects of cereal genomics: sequence assemblies, population-scale sequencing, resistance gene cloning and domestication genetics. Gene order may not be as extraordinarily well conserved in the grasses as once thought. Still, several recurring themes have emerged. The same ancestral molecular pathways defining plant architecture have been co-opted in the evolution of different cereal crops. Such genetic convergence as much as cross-fertilization of ideas between cereal geneticists has led to a rich harvest of genes that, it is hoped, will lead to improved varieties.

Use of remote sensing for linkage mapping and genomic prediction for common rust resistance in maize

Breeding for disease resistance is a central component of strategies implemented to mitigate biotic stress impacts on crop yield. Conventionally, genotypes of a plant population are evaluated through a labor-intensive process of assigning visual scores (VS) of susceptibility (or resistance) by specifically trained staff, which limits manageable volumes and repeatability of evaluation trials. Remote sensing (RS) tools have the potential to streamline phenotyping processes and to deliver more standardized results at higher through-put. Here, we use a two-year evaluation trial of three newly developed biparental populations of maize doubled haploid lines (DH) to compare the results of genomic analyses of resistance to common rust (CR) when phenotyping is either based on conventional VS or on RS-derived (vegetation) indices. As a general observation, for each population × year combination, the broad sense heritability of VS was greater than or very close to the maximum heritability across all RS indices. Moreover, results of linkage mapping as well as of genomic prediction (GP), suggest that VS data was of a higher quality, indicated by higher - log p values in the linkage studies and higher predictive abilities for genomic prediction. Nevertheless, despite the qualitative differences between the phenotyping methods, each successfully identified the same genomic region on chromosome 10 as being associated with disease resistance. This region is likely related to the known CR resistance locus Rp1. Our results indicate that RS technology can be used to streamline genetic evaluation processes for foliar disease resistance in maize. In particular, RS can potentially reduce costs of phenotypic evaluations and increase trialing capacities.

The genetics of Ug99 stem rust resistance in spring wheat variety 'Linkert'

Wheat stem rust caused by Puccinia graminis f. sp. tritici (Pgt) threatens wheat production worldwide. The objective of this study was to characterize wheat stem rust resistance in 'Linkert', a variety with adult plant resistance effective to emerging wheat stem rust pathogen strain Ug99. Two doubled haploid (DH) populations and one recombinant inbred line (RIL) population were developed with 'Linkert' as a stem rust resistant parent. Hard red spring wheat variety 'Forefront' and genetic stock 'LMPG' were used as stem rust susceptible parents of the DH populations. Breeding line 'MN07098-6' was used as a susceptible parent of the RIL population. Both DH and RIL populations with their parents were evaluated both at the seedling stage and in the field against Pgt races. Genotyping data of the DH populations were generated using the wheat iSelect 90k SNP assay. The RIL population was genotyped by genotyping-by-sequencing. We found QTL consistently associated with wheat stem rust resistance on chromosome 2BS for the Linkert/Forefront DH population and the Linkert/MN07098-6 RIL population both in Ethiopia and Kenya. Additional reliable QTL were detected on chromosomes 5BL (125.91 cM) and 4AL (Sr7a) for the Linkert/LMPG population in Ethiopia and Kenya. Different QTL identified in the populations reflect the importance of examining the genetics of resistance in populations derived from adapted germplasm (Forefront and MN07098-6) in addition to a genetic stock (LMPG). The associated markers in this study could be used to track and select for the identified QTL in wheat breeding programs.

Genetic analysis of pericarp pigmentation variation in Corn Belt dent maize

The US standard for maize commercially grown for grain specifies that yellow corn can contain at maximum 5% corn of other colors. Inbred parents of commercial hybrids typically have clear pericarp, but transgressive segregants in breeding populations can display variation in pericarp pigmentation. We identified 10 doubled haploid biparental populations segregating for pigmented pericarp and evaluated qualitative genetic models using chi-square tests of observed and expected frequencies. Pigmentation ranged from light to dark brown color, and pigmentation intensity was quantitatively measured across 1,327 inbred lines using hue calculated from RGB pixel values. Genetic mapping was used to identify loci associated with pigmentation intensity. For 9 populations, pigmentation inheritance best fit a hypothesis of a 2- or 3-gene epistatic model. Significant differences in pigment intensity were observed across populations. W606S-derived inbred lines with the darkest pericarp often had clear glumes, suggesting the presence of a novel P1-rw allele, a hypothesis supported by a significant quantitative trait locus peak at P1. A separate quantitative trait locus region on chromosome 2 between 221.64 and 226.66 Mbp was identified in LH82-derived populations, and the peak near p1 was absent. A genome-wide association study using 416 inbred lines from the Wisconsin Diversity panel with full genome resequencing revealed 4 significant associations including the region near P1. This study supports that pericarp pigmentation among dent maize inbreds can arise by transgressive segregation when pigmentation in the parental generation is absent and is partially explained by functional allelic variation at the P1 locus.

Genome-wide association analysis of plant architecture traits using doubled haploid lines derived from different cycles of the Iowa Stiff Stalk Synthetic maize population

Selection in the Iowa Stiff Stalk Synthetic (BSSS) maize population for high yield, grain moisture, and root and stalk lodging has indirectly modified plant architecture traits that are important for adaptation to high plant density. In this study, we developed doubled haploid (DH) lines from the BSSS maize population in the earliest cycle of recurrent selection (BSSS), cycle 17 of reciprocal recurrent selection, [BSSS(R)17] and the cross between the two cycles [BSSS/BSSS(R)C17]. We aimed to determine the phenotypic variation and changes in agronomic traits that have occurred through the recurrent selection program in this population and to identify genes or regions in the genome associated with the plant architecture changes observed in the different cycles of selection. We conducted a per se evaluation of DH lines focusing on high heritability traits important for adaptation to high planting density and grain yield. Trends for reducing flowering time, anthesis-silking interval, ear height, and the number of primary tassel branches in BSSS(R)17 DH lines compared to BSSS and BSSS/BSSS(R)C17 DH lines were observed. Additionally, the BSSS(R)C17 DH lines showed more upright flag leaf angles. Using the entire panel of DH lines increased the number of SNP markers identified within candidate genes associated with plant architecture traits. The genomic regions identified for plant architecture traits in this study may help to elucidate the genetic basis of these traits and facilitate future work about marker-assisted selection or map-based cloning in maize breeding programs.

Genetic architecture of source-sink-regulated senescence in maize

Source and sink interactions play a critical but mechanistically poorly understood role in the regulation of senescence. To disentangle the genetic and molecular mechanisms underlying source-sink-regulated senescence (SSRS), we performed a phenotypic, transcriptomic, and systems genetics analysis of senescence induced by the lack of a strong sink in maize (Zea mays). Comparative analysis of genotypes with contrasting SSRS phenotypes revealed that feedback inhibition of photosynthesis, a surge in reactive oxygen species, and the resulting endoplasmic reticulum (ER) stress were the earliest outcomes of weakened sink demand. Multienvironmental evaluation of a biparental population and a diversity panel identified 12 quantitative trait loci and 24 candidate genes, respectively, underlying SSRS. Combining the natural diversity and coexpression networks analyses identified 7 high-confidence candidate genes involved in proteolysis, photosynthesis, stress response, and protein folding. The role of a cathepsin B like protease 4 (ccp4), a candidate gene supported by systems genetic analysis, was validated by analysis of natural alleles in maize and heterologous analyses in Arabidopsis (Arabidopsis thaliana). Analysis of natural alleles suggested that a 700-bp polymorphic promoter region harboring multiple ABA-responsive elements is responsible for differential transcriptional regulation of ccp4 by ABA and the resulting variation in SSRS phenotype. We propose a model for SSRS wherein feedback inhibition of photosynthesis, ABA signaling, and oxidative stress converge to induce ER stress manifested as programed cell death and senescence. These findings provide a deeper understanding of signals emerging from loss of sink strength and offer opportunities to modify these signals to alter senescence program and enhance crop productivity.

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.

Genetic and transcriptomic dissection of host defense to Goss's bacterial wilt and leaf blight of maize

Goss's wilt, caused by the Gram-positive actinobacterium Clavibacter nebraskensis, is an important bacterial disease of maize. The molecular and genetic mechanisms of resistance to the bacterium, or, in general, Gram-positive bacteria causing plant diseases, remain poorly understood. Here, we examined the genetic basis of Goss's wilt through differential gene expression, standard genome-wide association mapping (GWAS), extreme phenotype (XP) GWAS using highly resistant (R) and highly susceptible (S) lines, and quantitative trait locus (QTL) mapping using 3 bi-parental populations, identifying 11 disease association loci. Three loci were validated using near-isogenic lines or recombinant inbred lines. Our analysis indicates that Goss's wilt resistance is highly complex and major resistance genes are not commonly present. RNA sequencing of samples separately pooled from R and S lines with or without bacterial inoculation was performed, enabling identification of common and differential gene responses in R and S lines. Based on expression, in both R and S lines, the photosynthesis pathway was silenced upon infection, while stress-responsive pathways and phytohormone pathways, namely, abscisic acid, auxin, ethylene, jasmonate, and gibberellin, were markedly activated. In addition, 65 genes showed differential responses (up- or down-regulated) to infection in R and S lines. Combining genetic mapping and transcriptional data, individual candidate genes conferring Goss's wilt resistance were identified. Collectively, aspects of the genetic architecture of Goss's wilt resistance were revealed, providing foundational data for mechanistic studies.

Regularized multi-trait multi-locus linear mixed models for genome-wide association studies and genomic selection in crops

BACKGROUND

We consider two key problems in genomics involving multiple traits: multi-trait genome wide association studies (GWAS), where the goal is to detect genetic variants associated with the traits; and multi-trait genomic selection (GS), where the emphasis is on accurately predicting trait values. Multi-trait linear mixed models build on the linear mixed model to jointly model multiple traits. Existing estimation methods, however, are limited to the joint analysis of a small number of genotypes; in fact, most approaches consider one SNP at a time. Estimating multi-dimensional genetic and environment effects also results in considerable computational burden. Efficient approaches that incorporate regularization into multi-trait linear models (no random effects) have been recently proposed to identify genomic loci associated with multiple traits (Yu et al. in Multitask learning using task clustering with applications to predictive modeling and GWAS of plant varieties. arXiv:1710.01788 , 2017; Yu et al in Front Big Data 2:27, 2019), but these ignore population structure and familial relatedness (Yu et al in Nat Genet 38:203-208, 2006).

RESULTS

This work addresses this gap by proposing a novel class of regularized multi-trait linear mixed models along with scalable approaches for estimation in the presence of high-dimensional genotypes and a large number of traits. We evaluate the effectiveness of the proposed methods using datasets in maize and sorghum diversity panels, and demonstrate benefits in both achieving high prediction accuracy in GS and in identifying relevant marker-trait associations.

CONCLUSIONS

The proposed regularized multivariate linear mixed models are relevant for both GWAS and GS. We hope that they will facilitate agronomy-related research in plant biology and crop breeding endeavors.

Identifying QTLs involved in hybrid performance and heterotic group complementarity: new GWAS models applied to factorial and admixed diallel maize hybrid panels

KEY MESSAGE

An original GWAS model integrating the ancestry of alleles was proposed and allowed the detection of background specific additive and dominance QTLs involved in heterotic group complementarity and hybrid performance. Maize genetic diversity is structured into genetic groups selected and improved relative to each other. This process increases group complementarity and differentiation over time and ensures that the hybrids produced from inter-group crosses exhibit high performances and heterosis. To identify loci involved in hybrid performance and heterotic group complementarity, we introduced an original association study model that disentangles allelic effects from the heterotic group origin of the alleles and compared it with a conventional additive/dominance model. This new model was applied on a factorial between Dent and Flint lines and a diallel between Dent-Flint admixed lines with two different layers of analysis: within each environment and in a multiple-environment context. We identified several strong additive QTLs for all traits, including some well-known additive QTLs for flowering time (in the region of Vgt1/2 on chromosome 8). Yield trait displayed significant non-additive effects in the diallel panel. Most of the detected Yield QTLs exhibited overdominance or, more likely, pseudo-overdominance effects. Apparent overdominance at these QTLs contributed to a part of the genetic group complementarity. The comparison between environments revealed a higher stability of additive QTL effects than non-additive ones. Several QTLs showed variations of effects according to the local heterotic group origin. We also revealed large chromosomic regions that display genetic group origin effects. Altogether, our results illustrate how admixed panels combined with dedicated GWAS modeling allow the identification of new QTLs that could not be revealed by a classical hybrid panel analyzed with traditional modeling.

Enhancing adaptation of tropical maize to temperate environments using genomic selection

Tropical maize can be used to diversify the genetic base of temperate germplasm and help create climate-adapted cultivars. However, tropical maize is unadapted to temperate environments, in which sensitivities to long photoperiods and cooler temperatures result in severely delayed flowering times, developmental defects, and little to no yield. Overcoming this maladaptive syndrome can require a decade of phenotypic selection in a targeted, temperate environment. To accelerate the incorporation of tropical diversity in temperate breeding pools, we tested if an additional generation of genomic selection can be used in an off-season nursery where phenotypic selection is not very effective. Prediction models were trained using flowering time recorded on random individuals in separate lineages of a heterogenous population grown at two northern U.S. latitudes. Direct phenotypic selection and genomic prediction model training was performed within each target environment and lineage, followed by genomic prediction of random intermated progenies in the off-season nursery. Performance of genomic prediction models was evaluated on self-fertilized progenies of prediction candidates grown in both target locations in the following summer season. Prediction abilities ranged from 0.30 to 0.40 among populations and evaluation environments. Prediction models with varying marker effect distributions or spatial field effects had similar accuracies. Our results suggest that genomic selection in a single off-season generation could increase genetic gains for flowering time by more than 50% compared to direct selection in summer seasons only, reducing the time required to change the population mean to an acceptably adapted flowering time by about one-third to one-half.

Genome-wide association study of resistance to anthracnose in pepper (Capsicum chinense) germplasm

BACKGROUND

Anthracnose is a fungal disease caused by Colletotrichum spp. that has a significant impact on worldwide pepper production. Colletotrichum scovillei is the most common pathogenic anthracnose-causing species in the Republic of Korea.

RESULTS

The resistances of 197 pepper (Capsicum chinense) accessions deposited in Korea's National Agrobiodiversity Center were evaluated for their response against the virulent pathogens Colletotrichum acutatum isolate 'KSCa-1' and C. scovillei isolate 'Hana') in the field and in vitro methods for three consecutive years (2018 to 2020). The severity of the disease was recorded and compared between inoculation methods. Six phenotypically resistant pepper accessions were selected based on three years of disease data. All of the selected resistant pepper accessions outperformed the control resistant pepper in terms of resistance (PI 594,137). A genome-wide association study (GWAS) was carried out to identify single nucleotide polymorphisms (SNPs) associated with anthracnose resistance. An association analysis was performed using 53,518 SNPs and the disease score of the 2020 field and in vitro experiment results. Both field and in vitro experiments revealed 25 and 32 significantly associated SNPs, respectively. These SNPs were found on all chromosomes except Ch06 and Ch07 in the field experiment, whereas in the in vitro experiment they were found on all chromosomes except Ch04 and Ch11.

CONCLUSION

In this study, six resistant C. chinense accessions were selected. Additionally, in this study, significantly associated SNPs were found in a gene that codes for a protein kinase receptor, such as serine/threonine-protein kinase, and other genes that are known to be involved in disease resistance. This may strengthen the role of these genes in the development of anthracnose resistance in Capsicum spp. As a result, the SNPs discovered to be strongly linked in this study can be used to identify a potential marker for selecting pepper material resistant to anthracnose, which will assist in the development of resistant varieties.

Unraveling Prevalence and Effects of Deleterious Mutations in Maize Elite Lines across Decades of Modern Breeding

Future breeding is likely to involve the detection and removal of deleterious alleles, which are mutations that negatively affect crop fitness. However, little is known about the prevalence of such mutations and their effects on phenotypic traits in the context of modern crop breeding. To address this, we examined the number and frequency of deleterious mutations in 350 elite maize inbred lines developed over the past few decades in China and the United States. Our findings reveal an accumulation of weakly deleterious mutations and a decrease in strongly deleterious mutations, indicating the dominant effects of genetic drift and purifying selection for the two types of mutations, respectively. We also discovered that slightly deleterious mutations, when at lower frequencies, were more likely to be heterozygous in the developed hybrids. This is consistent with complementation as a potential explanation for heterosis. Subsequently, we found that deleterious mutations accounted for more of the variation in phenotypic traits than nondeleterious mutations with matched minor allele frequencies, especially for traits related to leaf angle and flowering time. Moreover, we detected fewer deleterious mutations in the promoter and gene body regions of differentially expressed genes across breeding eras than in nondifferentially expressed genes. Overall, our results provide a comprehensive assessment of the prevalence and impact of deleterious mutations in modern maize breeding and establish a useful baseline for future maize improvement efforts.

Molecular characterization of doubled haploid lines derived from different cycles of the Iowa Stiff Stalk Synthetic (BSSS) maize population

Molecular characterization of a given set of maize germplasm could be useful for understanding the use of the assembled germplasm for further improvement in a breeding program, such as analyzing genetic diversity, selecting a parental line, assigning heterotic groups, creating a core set of germplasm and/or performing association analysis for traits of interest. In this study, we used single nucleotide polymorphism (SNP) markers to assess the genetic variability in a set of doubled haploid (DH) lines derived from the unselected Iowa Stiff Stalk Synthetic (BSSS) maize population, denoted as C0 (BSSS(R)C0), the seventeenth cycle of reciprocal recurrent selection in BSSS (BSSS(R)C17), denoted as C17 and the cross between BSSS(R)C0 and BSSS(R)C17 denoted as C0/C17. With the aim to explore if we have potentially lost diversity from C0 to C17 derived DH lines and observe whether useful genetic variation in C0 was left behind during the selection process since C0 could be a reservoir of genetic diversity that could be untapped using DH technology. Additionally, we quantify the contribution of the BSSS progenitors in each set of DH lines. The molecular characterization analysis confirmed the apparent separation and the loss of genetic variability from C0 to C17 through the recurrent selection process. Which was observed by the degree of differentiation between the C0_DHL versus C17_DHL groups by Wright's F-statistics (FST). Similarly for the population structure based on principal component analysis (PCA) revealed a clear separation among groups of DH lines. Some of the progenitors had a higher genetic contribution in C0 compared with C0/C17 and C17 derived DH lines. Although genetic drift can explain most of the genetic structure genome-wide, phenotypic data provide evidence that selection has altered favorable allele frequencies in the BSSS maize population through the reciprocal recurrent selection program.

Genetic structure analysis and identifying key founder inbred lines in diverse elite sub-tropical maize inbred lines

Understanding the genetic relationships between the key founder inbred lines and derived inbred lines could provide insight into the breeding history and the structure of genetic diversity of the available elite inbred lines with desirable target traits. The maize improvement program at the International Institute of Tropical Agriculture (IITA) analyzed the pedigree information of 623 sub-tropical maize inbred lines generated at the IITA maize breeding program to identify the key founder inbred lines. We also used 5032 SNP markers to assess the genetic similarities of the founder inbred lines with their progenies subsequently developed for specific target traits. The results of pedigree analysis and SNP markers-based similarity scores identified 20 key founder inbred lines with significant contributions to the development of drought tolerant, early maturing, productive, Striga resistant, provitamin A enriched, and quality protein maize inbred lines. In our breeding program, line TZMi501 belonging to a flint heterotic group (HGA), and TZMi407-S and TZMi214, representing the dent heterotic group (HGB), were identified as the most useful founder inbred lines. The 623 inbred lines were consistently separated into four clusters based on Ward's hierarchical clustering, structure, and principal component analyses, with the 20 founder inbred lines spread into all clusters. The founder inbred lines were more genetically related to the productive inbred lines but showed genetic divergence from the provitamin A enriched inbred lines. These results provide a better understanding of the breeding history of the sub-tropical maize inbred lines to facilitate parental selection aligned to existing heterotic groups for use in breeding programs targeting the improvement of essential traits in maize.

On the usefulness of mock genomes to define heterotic pools, testers, and hybrid predictions in orphan crops

The advances in genomics in recent years have increased the accuracy and efficiency of breeding programs for many crops. Nevertheless, the adoption of genomic enhancement for several other crops essential in developing countries is still limited, especially for those that do not have a reference genome. These crops are more often called orphans. This is the first report to show how the results provided by different platforms, including the use of a simulated genome, called the mock genome, can generate in population structure and genetic diversity studies, especially when the intention is to use this information to support the formation of heterotic groups, choice of testers, and genomic prediction of single crosses. For that, we used a method to assemble a reference genome to perform the single-nucleotide polymorphism (SNP) calling without needing an external genome. Thus, we compared the analysis results using the mock genome with the standard approaches (array and genotyping-by-sequencing (GBS)). The results showed that the GBS-Mock presented similar results to the standard methods of genetic diversity studies, division of heterotic groups, the definition of testers, and genomic prediction. These results showed that a mock genome constructed from the population's intrinsic polymorphisms to perform the SNP calling is an effective alternative for conducting genomic studies of this nature in orphan crops, especially those that do not have a reference genome.

Genotyping of DNA pools identifies untapped landraces and genomic regions to develop next-generation varieties

Landraces, that is, traditional varieties, have a large diversity that is underexploited in modern breeding. A novel DNA pooling strategy was implemented to identify promising landraces and genomic regions to enlarge the genetic diversity of modern varieties. As proof of concept, DNA pools from 156 American and European maize landraces representing 2340 individuals were genotyped with an SNP array to assess their genome-wide diversity. They were compared to elite cultivars produced across the 20th century, represented by 327 inbred lines. Detection of selective footprints between landraces of different geographic origin identified genes involved in environmental adaptation (flowering times, growth) and tolerance to abiotic and biotic stress (drought, cold, salinity). Promising landraces were identified by developing two novel indicators that estimate their contribution to the genome of inbred lines: (i) a modified Roger's distance standardized by gene diversity and (ii) the assignation of lines to landraces using supervised analysis. It showed that most landraces do not have closely related lines and that only 10 landraces, including famous landraces as Reid's Yellow Dent, Lancaster Surecrop and Lacaune, cumulated half of the total contribution to inbred lines. Comparison of ancestral lines directly derived from landraces with lines from more advanced breeding cycles showed a decrease in the number of landraces with a large contribution. New inbred lines derived from landraces with limited contributions enriched more the haplotype diversity of reference inbred lines than those with a high contribution. Our approach opens an avenue for the identification of promising landraces for pre-breeding.

Genome-Wide Association Study for Root Morphology and Phosphorus Acquisition Efficiency in Diverse Maize Panels

Maximizing soil exploration through modifications of the root system is a strategy for plants to overcome phosphorus (P) deficiency. Genome-wide association with 561 tropical maize inbred lines from Embrapa and DTMA panels was undertaken for root morphology and P acquisition traits under low- and high-P concentrations, with 353,540 SNPs. P supply modified root morphology traits, biomass and P content in the global maize panel, but root length and root surface area changed differentially in Embrapa and DTMA panels. This suggests that different root plasticity mechanisms exist for maize adaptation to low-P conditions. A total of 87 SNPs were associated to phenotypic traits in both P conditions at −log10(p-value) ≥ 5, whereas only seven SNPs reached the Bonferroni significance. Among these SNPs, S9_137746077, which is located upstream of the gene GRMZM2G378852 that encodes a MAPKKK protein kinase, was significantly associated with total seedling dry weight, with the same allele increasing root length and root surface area under P deficiency. The C allele of S8_88600375, mapped within GRMZM2G044531 that encodes an AGC kinase, significantly enhanced root length under low P, positively affecting root surface area and seedling weight. The broad genetic diversity evaluated in this panel suggests that candidate genes and favorable alleles could be exploited to improve P efficiency in maize breeding programs of Africa and Latin America.

A role for heritable transcriptomic variation in maize adaptation to temperate environments

Background

Transcription bridges genetic information and phenotypes. Here, we evaluated how changes in transcriptional regulation enable maize (Zea mays), a crop originally domesticated in the tropics, to adapt to temperate environments.

Result

We generated 572 unique RNA-seq datasets from the roots of 340 maize genotypes. Genes involved in core processes such as cell division, chromosome organization and cytoskeleton organization showed lower heritability of gene expression, while genes involved in anti-oxidation activity exhibited higher expression heritability. An expression genome-wide association study (eGWAS) identified 19,602 expression quantitative trait loci (eQTLs) associated with the expression of 11,444 genes. A GWAS for alternative splicing identified 49,897 splicing QTLs (sQTLs) for 7614 genes. Genes harboring both cis-eQTLs and cis-sQTLs in linkage disequilibrium were disproportionately likely to encode transcription factors or were annotated as responding to one or more stresses. Independent component analysis of gene expression data identified loci regulating co-expression modules involved in oxidation reduction, response to water deprivation, plastid biogenesis, protein biogenesis, and plant-pathogen interaction. Several genes involved in cell proliferation, flower development, DNA replication, and gene silencing showed lower gene expression variation explained by genetic factors between temperate and tropical maize lines. A GWAS of 27 previously published phenotypes identified several candidate genes overlapping with genomic intervals showing signatures of selection during adaptation to temperate environments.

Conclusion

Our results illustrate how maize transcriptional regulatory networks enable changes in transcriptional regulation to adapt to temperate regions.

Supplementary information

The online version contains supplementary material available at 10.1186/s13059-023-02891-3.

Elucidating the patterns of pleiotropy and its biological relevance in maize

Pleiotropy-when a single gene controls two or more seemingly unrelated traits-has been shown to impact genes with effects on flowering time, leaf architecture, and inflorescence morphology in maize. However, the genome-wide impact of biological pleiotropy across all maize phenotypes is largely unknown. Here, we investigate the extent to which biological pleiotropy impacts phenotypes within maize using GWAS summary statistics reanalyzed from previously published metabolite, field, and expression phenotypes across the Nested Association Mapping population and Goodman Association Panel. Through phenotypic saturation of 120,597 traits, we obtain over 480 million significant quantitative trait nucleotides. We estimate that only 1.56-32.3% of intervals show some degree of pleiotropy. We then assess the relationship between pleiotropy and various biological features such as gene expression, chromatin accessibility, sequence conservation, and enrichment for gene ontology terms. We find very little relationship between pleiotropy and these variables when compared to permuted pleiotropy. We hypothesize that biological pleiotropy of common alleles is not widespread in maize and is highly impacted by nuisance terms such as population structure and linkage disequilibrium. Natural selection on large standing natural variation in maize populations may target wide and large effect variants, leaving the prevalence of detectable pleiotropy relatively low.

A common resequencing-based genetic marker data set for global maize diversity

Maize (Zea mays ssp. mays) populations exhibit vast ranges of genetic and phenotypic diversity. As sequencing costs have declined, an increasing number of projects have sought to measure genetic differences between and within maize populations using whole-genome resequencing strategies, identifying millions of segregating single-nucleotide polymorphisms (SNPs) and insertions/deletions (InDels). Unlike older genotyping strategies like microarrays and genotyping by sequencing, resequencing should, in principle, frequently identify and score common genetic variants. However, in practice, different projects frequently employ different analytical pipelines, often employ different reference genome assemblies and consistently filter for minor allele frequency within the study population. This constrains the potential to reuse and remix data on genetic diversity generated from different projects to address new biological questions in new ways. Here, we employ resequencing data from 1276 previously published maize samples and 239 newly resequenced maize samples to generate a single unified marker set of approximately 366 million segregating variants and approximately 46 million high-confidence variants scored across crop wild relatives, landraces as well as tropical and temperate lines from different breeding eras. We demonstrate that the new variant set provides increased power to identify known causal flowering-time genes using previously published trait data sets, as well as the potential to track changes in the frequency of functionally distinct alleles across the global distribution of modern maize.

De novo genome assembly and analyses of 12 founder inbred lines provide insights into maize heterosis

Hybrid maize displays superior heterosis and contributes over 30% of total worldwide cereal production. However, the molecular mechanisms of heterosis remain obscure. Here we show that structural variants (SVs) between the parental lines have a predominant role underpinning maize heterosis. De novo assembly and analyses of 12 maize founder inbred lines (FILs) reveal abundant genetic variations among these FILs and, through expression quantitative trait loci and association analyses, we identify several SVs contributing to genomic and phenotypic differentiations of various heterotic groups. Using a set of 91 diallel-cross F₁ hybrids, we found strong positive correlations between better-parent heterosis of the F₁ hybrids and the numbers of SVs between the parental lines, providing concrete genomic support for a prevalent role of genetic complementation underlying heterosis. Further, we document evidence that SVs in both ZAR1 and ZmACO2 contribute to yield heterosis in an overdominance fashion. Our results should promote genomics-based breeding of hybrid maize.

Maize cytolines as models to study the impact of different cytoplasms on gene expression under heat stress conditions

BACKGROUND

Crops are under constant pressure due to global warming, which unfolds at a much faster pace than their ability to adapt through evolution. Agronomic traits are linked to cytoplasmic-nuclear genome interactions. It thus becomes important to understand the influence exerted by the organelles on gene expression under heat stress conditions and profit from the available genetic diversity. Maize (Zea mays) cytolines allow us to investigate how the gene expression changes under heat stress conditions in three different cytoplasmic environments, but each having the same nucleus. Analyzing retrograde signaling in such an experimental set-up has never been done before. Here, we quantified the response of three cytolines to heat stress as differentially expressed genes (DEGs), and studied gene expression patterns in the context of existing polymorphism in their organellar genomes.

RESULTS

Our study unveils a plethora of new genes and GO terms that are differentially expressed or enriched, respectively, in response to heat stress. We report 19,600 DEGs as responding to heat stress (out of 30,331 analyzed), which significantly enrich 164 GO biological processes, 30 GO molecular functions, and 83 GO cell components. Our approach allowed for the discovery of a significant number of DEGs and GO terms that are not common in the three cytolines and could therefore be linked to retrograde signaling. Filtering for DEGs with a fold regulation > 2 (absolute values) that are exclusive to just one of the cytolines, we find a total of 391 up- and down-DEGs. Similarly, there are 19 GO terms with a fold enrichment > 2 that are cytoline-specific. Using GBS data we report contrasting differences in the number of DEGs and GO terms in each cytoline, which correlate with the genetic distances between the mitochondrial genomes (but not chloroplast) and the original nuclei of the cytolines, respectively.

CONCLUSIONS

The experimental design used here adds a new facet to the paradigm used to explain how gene expression changes in response to heat stress, capturing the influence exerted by different organelles upon one nucleus rather than investigating the response of several nuclei in their innate cytoplasmic environments.

Genotype-environment associations to reveal the molecular basis of environmental adaptation

A fundamental goal in plant biology is to identify and understand the variation underlying plants' adaptation to their environment. Climate change has given new urgency to this goal, as society aims to accelerate adaptation of ecologically important plant species, endangered plant species, and crops to hotter, less predictable climates. In the pre-genomic era, identifying adaptive alleles was painstaking work, leveraging genetics, molecular biology, physiology, and ecology. Now, the rise of genomics and new computational approaches may facilitate this research. Genotype-environment associations (GEAs) use statistical associations between allele frequency and environment of origin to test the hypothesis that allelic variation at a given gene is adapted to local environments. Researchers may scan the genome for GEAs to generate hypotheses on adaptive genetic variants (environmental genome-wide association studies). Despite the rapid adoption of these methods, many important questions remain about the interpretation of GEA findings, which arise from fundamental unanswered questions on the genetic architecture of adaptation and limitations inherent to association-based analyses. We outline strategies to ground GEAs in the underlying hypotheses of genetic architecture and better test GEA-generated hypotheses using genetics and ecophysiology. We provide recommendations for new users who seek to learn about the molecular basis of adaptation. When combined with a rigorous hypothesis testing framework, GEAs may facilitate our understanding of the molecular basis of climate adaptation for plant improvement.

Genome-Wide Association Analysis of Senescence-Related Traits in Maize

Senescence is a programmed process that involves the destruction of the photosynthesis apparatus and the relocation of nutrients to the grain. Identifying senescence-associated genes is essential to adapting varieties for the duration of the cultivation cycle. A genome-wide association study (GWAS) was performed using 400 inbred maize lines with 156,164 SNPs to study the genetic architecture of senescence-related traits and their relationship with agronomic traits. We estimated the timing of senescence to be 45 days after anthesis in the whole plant and specifically in the husks. A list of genes identified in a previous RNAseq experiment as involved in senescence (core senescence genes) was used to propose candidate genes in the vicinity of the significant SNPs. Forty-six QTLs of moderate to high effect were found for senescence traits, including specific QTLs for husk senescence. The allele that delayed senescence primarily increased grain yield and moisture. Seven and one significant SNPs were found in the coding and promoter regions of eight core senescence genes, respectively. These genes could be potential candidates for generating a new variation by genome editing for functional analysis and breeding purposes, particularly Zm00001d014796, which could be responsible for a QTL of senescence found in multiple studies.

Fighting Death for Living: Recent Advances in Molecular and Genetic Mechanisms Underlying Maize Lethal Necrosis Disease Resistance

Maize Lethal Necrosis (MLN) disease, caused by a synergistic co-infection of maize chlorotic mottle virus (MCMV) and any member of the Potyviridae family, was first reported in EasternAfrica (EA) a decade ago. It is one of the most devastating threats to maize production in these regions since it can lead up to 100% crop loss. Conventional counter-measures have yielded some success; however, they are becoming less effective in controlling MLN. In EA, the focus has been on the screening and identification of resistant germplasm, dissecting genetic and the molecular basis of the disease resistance, as well as employing modern breeding technologies to develop novel varieties with improved resistance. CIMMYT and scientists from NARS partner organizations have made tremendous progresses in the screening and identification of the MLN-resistant germplasm. Quantitative trait loci mapping and genome-wide association studies using diverse, yet large, populations and lines were conducted. These remarkable efforts have yielded notable outcomes, such as the successful identification of elite resistant donor lines KS23-5 and KS23-6 and their use in breeding, as well as the identification of multiple MLN-tolerance promising loci clustering on Chr 3 and Chr 6. Furthermore, with marker-assisted selection and genomic selection, the above-identified germplasms and loci have been incorporated into elite maize lines in a maize breeding program, thus generating novel varieties with improved MLN resistance levels. However, the underlying molecular mechanisms for MLN resistance require further elucidation. Due to third generation sequencing technologies as well functional genomics tools such as genome-editing and DH technology, it is expected that the breeding time for MLN resistance in farmer-preferred maize varieties in EA will be efficient and shortened.

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.

Gene-Based Genome-Wide Association Study Identified Genes for Agronomic Traits in Maize

A gene integrates the effects of all SNPs in its sequence span, which benefits the genome-wide association study. To explore gene-level variations affecting economic traits in maize, we extended the SNP-based GWAS analysis software Single-RunKing developed by our team to gene-based GWAS, which used the FaST-LMM algorithm to convert the linear mixed model into simple linear model association analysis. An F-test statistic was formulated to test and identify candidate genes. We compared the statistical efficiency of using 80% principal components (EPC), the first principal component (FPC), and all SNP markers (ALLSNP) as independent variables, which predecessors commonly used to integrate SNPs and represent genes. With a Huazhong Agricultural University (HAU) genomic dataset of 2.65M SNPs from 540 maize plants, 34,774 genes were annotated across the whole genome. Genome-wide association studies with 20 agronomic traits were performed using the software developed here. Another maize dataset from the Ames panel (AP) was also analyzed. The EPC method fits the model well and has good statistical efficiency. It not only overcomes the false negative problem when using all SNP markers for analysis (ALLSNP) but also solves the false positive problem of its corresponding simple linear model method EPCLM. Compared with FPC, the EPC method has higher statistical efficiency. A total of 132 quantitative trait genes (QTG) were identified for the 20 traits from HAU maize dataset and one trait of AP maize.

Molecular mapping of quantitative trait loci for 3 husk traits using genotyping by sequencing in maize (Zea mays L.)

The maize (Zea mays L.) husk consists of multiple leaf layers and plays an important role in grain growth and development. Despite significant achievements in physiological and morphological research, few studies have focused on the detection of genetic loci underlying husk-related traits due to the lack of efficient tools. In this study, we constructed an ultra-high-density linkage map using genotyping by sequencing based on a recombinant inbred line population to estimate the genetic variance and heritability of 3 husk traits, i.e. husk length, husk width, and husk layer number in 3 field environments and the combined environment. The 3 husk traits showed broad phenotypic variation and high heritability; the broad-sense heritability (H²) was 0.92, 0.84, and 0.86. Twenty quantitative trait loci were consistently detected more than 1 environment, including 9 for husk length, 6 for husk width, and 5 for husk layer number. These loci were considered as stable quantitative trait loci. Based on the quantitative trait loci mapping in the recombinant inbred line population, qHL6 and qHN4 were detected across all environments and inferred to be reliable and major-effect quantitative trait loci for husk length and husk layer number, respectively. In addition, several predicted candidate genes were identified in the region of qHL6 and qHN4, of which 17 candidate genes potentially play a role in biological processes related to development process and energy metabolism. These results will be as a useful resource for performing functional studies aimed at understanding the molecular pathways involved in husk growth and development.

Combining datasets for maize root seedling traits increases the power of GWAS and genomic prediction accuracies

The identification of genomic regions associated with root traits and the genomic prediction of untested genotypes can increase the rate of genetic gain in maize breeding programs targeting roots traits. Here, we combined two maize association panels with different genetic backgrounds to identify single nucleotide polymorphisms (SNPs) associated with root traits, and used a genome-wide association study (GWAS) and to assess the potential of genomic prediction for these traits in maize. For this, we evaluated 377 lines from the Ames panel and 302 from the Backcrossed Germplasm Enhancement of Maize (BGEM) panel in a combined panel of 679 lines. The lines were genotyped with 232 460 SNPs, and four root traits were collected from 14-day-old seedlings. We identified 30 SNPs significantly associated with root traits in the combined panel, whereas only two and six SNPs were detected in the Ames and BGEM panels, respectively. Those 38 SNPs were in linkage disequilibrium with 35 candidate genes. In addition, we found higher prediction accuracy in the combined panel than in the Ames or BGEM panel. We conclude that combining association panels appears to be a useful strategy to identify candidate genes associated with root traits in maize and improve the efficiency of genomic prediction.

G × EBLUP: A novel method for exploring genotype by environment interactions and genomic prediction

Genotype by environment (G × E) interaction is fundamental in the biology of complex traits and diseases. However, most of the existing methods for genomic prediction tend to ignore G × E interaction (GEI). In this study, we proposed the genomic prediction method G × EBLUP by considering GEI. Meanwhile, G × EBLUP can also detect the genome-wide single nucleotide polymorphisms (SNPs) subject to GEI. Using comprehensive simulations and analysis of real data from pigs and maize, we showed that G × EBLUP achieved higher efficiency in mapping GEI SNPs and higher prediction accuracy than the existing methods, and its superiority was more obvious when the GEI variance was large. For pig and maize real data, compared with GBLUP, G × EBLUP showed improvement by 3% in the prediction accuracy for backfat thickness, while our findings indicated that the trait of days to 100 kg of pig was not affected by GEI and G × EBLUP did not improve the accuracy of genomic prediction for the trait. A significant advantage was observed for G × EBLUP in maize; the prediction accuracy was improved by ∼5.0 and 7.7% for grain weight and water content, respectively. Furthermore, G × EBLUP was not influenced by the number of environment levels. It could determine a favourable environment using SNP Bayes factors for each environment, implying that it is a robust and useful method for market-specific animal and plant breeding. We proposed G × EBLUP, a novel method for the estimation of genomic breeding value by considering GEI. This method identified the genome-wide SNPs that were susceptible to GEI and yielded higher genomic prediction accuracies and lower mean squared error compared with the GBLUP method.

Identification of Loci Governing Agronomic Traits and Mutation Hotspots via a GBS-Based Genome-Wide Association Study in a Soybean Mutant Diversity Pool

In this study, we performed a genotyping-by-sequencing analysis and a genome-wide association study of a soybean mutant diversity pool previously constructed by gamma irradiation. A GWAS was conducted to detect significant associations between 37,249 SNPs, 11 agronomic traits, and 6 phytochemical traits. In the merged data set, 66 SNPs on 13 chromosomes were highly associated (FDR p < 0.05) with the following 4 agronomic traits: days of flowering (33 SNPs), flower color (16 SNPs), node number (6 SNPs), and seed coat color (11 SNPs). These results are consistent with the findings of earlier studies on other genetic features (e.g., natural accessions and recombinant inbred lines). Therefore, our observations suggest that the genomic changes in the mutants generated by gamma irradiation occurred at the same loci as the mutations in the natural soybean population. These findings are indicative of the existence of mutation hotspots, or the acceleration of genome evolution in response to high doses of radiation. Moreover, this study demonstrated that the integration of GBS and GWAS to investigate a mutant population derived from gamma irradiation is suitable for dissecting the molecular basis of complex traits in soybeans.

Association mapping across a multitude of traits collected in diverse environments in maize

Classical genetic studies have identified many cases of pleiotropy where mutations in individual genes alter many different phenotypes. Quantitative genetic studies of natural genetic variants frequently examine one or a few traits, limiting their potential to identify pleiotropic effects of natural genetic variants. Widely adopted community association panels have been employed by plant genetics communities to study the genetic basis of naturally occurring phenotypic variation in a wide range of traits. High-density genetic marker data-18M markers-from 2 partially overlapping maize association panels comprising 1,014 unique genotypes grown in field trials across at least 7 US states and scored for 162 distinct trait data sets enabled the identification of of 2,154 suggestive marker-trait associations and 697 confident associations in the maize genome using a resampling-based genome-wide association strategy. The precision of individual marker-trait associations was estimated to be 3 genes based on a reference set of genes with known phenotypes. Examples were observed of both genetic loci associated with variation in diverse traits (e.g., above-ground and below-ground traits), as well as individual loci associated with the same or similar traits across diverse environments. Many significant signals are located near genes whose functions were previously entirely unknown or estimated purely via functional data on homologs. This study demonstrates the potential of mining community association panel data using new higher-density genetic marker sets combined with resampling-based genome-wide association tests to develop testable hypotheses about gene functions, identify potential pleiotropic effects of natural genetic variants, and study genotype-by-environment interaction.

Descriptive Genomic Analysis and Sequence Genotyping of the Two Papaya Species (Vasconcellea pubescens and Vasconcellea chilensis) Using GBS Tools

A genotyping by sequencing (GBS) approach was used to analyze the organization of genetic diversity in V. pubescens and V. chilensis. GBS identified 4675 and 4451 SNPs/INDELs in two papaya species. The cultivated orchards of V. pubescens exhibited scarce genetic diversity and low but significant genetic differentiation. The neutrality test yielded a negative and significant result, suggesting that V. pubescens suffered a selective sweep or a rapid expansion after a bottleneck during domestication. In contrast, V. chilensis exhibited a high level of genetic diversity. The genetic differentiation among the populations was slight, but it was possible to distinguish the two genetic groups. The neutrality test indicated no evidence that natural selection and genetic drift affect the natural population of V. chilensis. Using the Carica papaya genome as a reference, we identified critical SNPs/INDELs associated with putative genes. Most of the identified genes are related to stress responses (salt and nematode) and vegetative and reproductive development. These results will be helpful for future breeding and conservation programs of the Caricaceae family.

Natural variation in root exudation of GABA and DIMBOA impacts the maize root endosphere and rhizosphere microbiomes

Root exudates are important for shaping root-associated microbiomes. However, studies on a wider range of metabolites in exudates are required for a comprehensive understanding about their influence on microbial communities. We identified maize inbred lines that differ in exudate concentrations of 2,4-dihydroxy-7-methoxy-1,4-benzoxazin-3-one (DIMBOA) and γ-aminobutyric acid (GABA) using a semi-hydroponic system. These lines were grown in the field to determine the changes in microbial diversity and gene expression due to varying concentrations of DIMBOA and GABA in exudates using 16S rRNA amplicon sequencing and metatranscriptomics. Results showed individual and interaction effects of DIMBOA and GABA on the rhizosphere and root endosphere β-diversity, most strongly at the V10 growth stage. The main bacterial families affected by both compounds were Ktedonobacteraceae and Xanthomonadaceae. Higher concentrations of DIMBOA in exudates affected the rhizosphere metatranscriptome, enriching for metabolic pathways associated with plant disease. This study validated the use of natural variation within plant species as a powerful approach for understanding the role of root exudates on microbiome selection. We also showed that a semi-hydroponic system can be used to identify maize genotypes that differ in GABA and DIMBOA exudate concentrations under field conditions. The impact of GABA exudation on root-associated microbiomes is shown for the first time.

Sorghum Association Panel whole-genome sequencing establishes cornerstone resource for dissecting genomic diversity

Association mapping panels represent foundational resources for understanding the genetic basis of phenotypic diversity and serve to advance plant breeding by exploring genetic variation across diverse accessions. We report the whole-genome sequencing (WGS) of 400 sorghum (Sorghum bicolor (L.) Moench) accessions from the Sorghum Association Panel (SAP) at an average coverage of 38× (25-72×), enabling the development of a high-density genomic marker set of 43 983 694 variants including single-nucleotide polymorphisms (approximately 38 million), insertions/deletions (indels) (approximately 5 million), and copy number variants (CNVs) (approximately 170 000). We observe slightly more deletions among indels and a much higher prevalence of deletions among CNVs compared to insertions. This new marker set enabled the identification of several novel putative genomic associations for plant height and tannin content, which were not identified when using previous lower-density marker sets. WGS identified and scored variants in 5-kb bins where available genotyping-by-sequencing (GBS) data captured no variants, with half of all bins in the genome falling into this category. The predictive ability of genomic best unbiased linear predictor (GBLUP) models was increased by an average of 30% by using WGS markers rather than GBS markers. We identified 18 selection peaks across subpopulations that formed due to evolutionary divergence during domestication, and we found six F_st peaks resulting from comparisons between converted lines and breeding lines within the SAP that were distinct from the peaks associated with historic selection. This population has served and continues to serve as a significant public resource for sorghum research and demonstrates the value of improving upon existing genomic resources.