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How to feed 10 billion human populations is one of the challenges that need to be addressed in the following decades, especially under an unpredicted climate change. Crop breeding, initiating from the phenotype-based selection by local farmers and developing into current biotechnology-based breeding, has played a critical role in securing the global food supply. However, regarding the changing environment and ever-increasing human population, can we breed outstanding crop varieties fast enough to achieve high productivity, good quality, and widespread adaptability? This review outlines the recent achievements in understanding cereal crop breeding, including the current knowledge about crop agronomic traits, newly developed techniques, crop big biological data research, and the possibility of integrating them for intelligence-driven breeding by design, which ushers in a new era of crop breeding practice and shapes the novel architecture of future crops. This review focuses on the major cereal crops, including rice, maize, and wheat, to explain how intelligence-driven breeding by design is becoming a reality., Competing Interests: Conflict of interest The authors declared that they have no conflicts of interest to this work., (Copyright © 2024 Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, and Genetics Society of China. Published by Elsevier Ltd. All rights reserved.)

Doubled haploid (DH) technology and synthetic apomixis approaches can considerably shorten breeding cycles and enhance breeding efficiency. Compared with traditional breeding methods, DH technology offers the advantage of rapidly generating inbred lines, while synthetic apomixis can effectively fix hybrid vigor. In this review, we focus on (i) recent advances in identifying and characterizing genes responsible for haploid induction (HI), (ii) the molecular mechanisms of HI, (iii) spontaneous haploid genome doubling, and (iv) crop synthetic apomixis. We also discuss the challenges and potential solutions for future crop breeding programs utilizing DH technology and synthetic apomixis. Finally, we provide our perspectives about how to integrate DH and synthetic apomixis for precision breeding and de novo domestication., (Copyright © 2024 The Author. Published by Elsevier Inc. All rights reserved.)

Maize is a globally valuable commodity and one of the most extensively studied genetic model organisms. However, we know surprisingly little about the extent and potential utility of the genetic variation found in wild relatives of maize. Here, we characterize a high-density genomic variation map from 744 genomes encompassing maize and all wild taxa of the genus Zea, identifying over 70 million single-nucleotide polymorphisms. The variation map reveals evidence of selection within taxa displaying novel adaptations. We focus on adaptive alleles in highland teosinte and temperate maize, highlighting the key role of flowering-time-related pathways in their adaptation. To show the utility of variants in these data, we generate mutant alleles for two flowering-time candidate genes. This work provides an extensive sampling of the genetic diversity of Zea, resolving questions on evolution and identifying adaptive variants for direct use in modern breeding., (© 2022. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Haploid induction (HI) is an important tool in crop breeding. Phospholipase A1 (ZmPLA1)/NOT LIKE DAD (NLD)/MATRILINEAL (MTL) is a key gene controlling HI in maize; however, the underlying molecular mechanism remains unclear. In this study, to dissect why loss of ZmPLA1 function could mediate HI we performed a comprehensive multiple omics analysis of zmpla1 mutant anthers by integrating transcriptome, metabolome, quantitative proteome, and protein modification data. Functional classes of significantly enriched or differentially abundant molecular entities were found to be associated with the oxidative stress response, suggesting that a reactive oxygen species (ROS) burst plays a critical role in HI. In support of this, we further discovered that a simple chemical treatment of pollen with ROS reagents could lead to HI. Moreover, we identified ZmPOD65, which encodes a sperm-specific peroxidase, as a new gene controlling HI. Taken together, our study revealed a likely mechanism of HI, discovered a new gene controlling HI, and created a new method for HI in maize, indicating the importance of ROS balance in maintaining normal reproduction and providing a potential route to accelerate crop breeding., (Copyright © 2022 The Author. Published by Elsevier Inc. All rights reserved.)

Genomic prediction in crop breeding is hindered by modeling on limited phenotypic traits. We propose an integrative multi-trait breeding strategy via machine learning algorithm, target-oriented prioritization (TOP). Using a large hybrid maize population, we demonstrate that the accuracy for identifying a candidate that is phenotypically closest to an ideotype, or target variety, achieves up to 91%. The strength of TOP is enhanced when omics level traits are included. We show that TOP enables selection of inbreds or hybrids that outperform existing commercial varieties. It improves multiple traits and accurately identifies improved candidates for new varieties, which will greatly influence breeding., (© 2022. The Author(s).)

The employment of doubled-haploid (DH) technology in maize has vastly accelerated the efficiency of developing inbred lines. The selection of superior lines has to rely on genotypes with genomic selection (GS) model, rather than phenotypes due to the high expense of field phenotyping. In this work, we implemented 'genome optimization via virtual simulation (GOVS)' using the genotype and phenotype data of 1404 maize lines and their F1 progeny. GOVS simulates a virtual genome encompassing the most abundant 'optimal genotypes' or 'advantageous alleles' in a genetic pool. Such a virtually optimized genome, although can never be developed in reality, may help plot the optimal route to direct breeding decisions. GOVS assists in the selection of superior lines based on the genomic fragments that a line contributes to the simulated genome. The assumption is that the more fragments of optimal genotypes a line contributes to the assembly, the higher the likelihood of the line favored in the F1 phenotype, e.g. grain yield. Compared to traditional GS method, GOVS-assisted selection may avoid using an arbitrary threshold for the predicted F1 yield to assist selection. Additionally, the selected lines contributed complementary sets of advantageous alleles to the virtual genome. This feature facilitates plotting the optimal route for DH production, whereby the fewest lines and F1 combinations are needed to pyramid a maximum number of advantageous alleles in the new DH lines. In summary, incorporation of DH production, GS and genome optimization will ultimately improve genomically designed breeding in maize. Short abstract: Doubled-haploid (DH) technology has been widely applied in maize breeding industry, as it greatly shortens the period of developing homozygous inbred lines via bypassing several rounds of self-crossing. The current challenge is how to efficiently screen the large volume of inbred lines based on genotypes. We present the toolbox of genome optimization via virtual simulation (GOVS), which complements the traditional genomic selection model. GOVS simulates a virtual genome encompassing the most abundant 'optimal genotypes' in a breeding population, and then assists in selection of superior lines based on the genomic fragments that a line contributes to the simulated genome. Availability of GOVS (https://govs-pack.github.io/) to the public may ultimately facilitate genomically designed breeding in maize., (© The Author(s) 2021. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

LightGBM is an ensemble model of decision trees for classification and regression prediction. We demonstrate its utility in genomic selection-assisted breeding with a large dataset of inbred and hybrid maize lines. LightGBM exhibits superior performance in terms of prediction precision, model stability, and computing efficiency through a series of benchmark tests. We also assess the factors that are essential to ensure the best performance of genomic selection prediction by taking complex scenarios in crop hybrid breeding into account. LightGBM has been implemented as a toolbox, CropGBM, encompassing multiple novel functions and analytical modules to facilitate genomically designed breeding in crops., (© 2021. The Author(s).)

Crops feed the world's population and shape human civilization. The improvement of crop productivity has been ongoing for almost 10,000 years and has evolved from an experience-based to a knowledge-driven practice over the past three decades. Natural alleles and their reshuffling are long-standing genetic changes that affect how crops respond to various environmental conditions and agricultural practices. Decoding the genetic basis of natural variation is central to understanding crop evolution and, in turn, improving crop breeding. Here, we review current advances in the approaches used to map the causal alleles of natural variation, provide refined insights into the genetics and evolution of natural variation, and outline how this knowledge promises to drive the development of sustainable agriculture under the dome of emerging technologies.

Crops are the foundation of human society, not only by providing needed nutrition, but also by feeding livestock and serving as raw materials for industry. Cereal crops, which supply most of our calories, have been supporting humans for thousands of years. However food security is facing many challenges nowadays, including growing populations, water shortage, and increased incidence of biotic and abiotic stresses. According to statistical data from the Food and Agriculture Organization of the United Nations (FAO, http://www.fao.org/), the people suffering severe food insecurity increased from 7.9 % in 2015 to 9.7 % in 2019 and the number of people exposed to moderate or severe food insecurity have increased by 400 million over the same time period. Although there are many ways to cope with these challenges, crop breeding remains the most crucial and direct manner. With the development of molecular genetics, the speed of cloning genetic variations underlying corresponding phenotypes of agricultural importance is considerably more rapid. As a consequence breeding methods have evolved from phenotype-based to genome-based selection. In the future, knowledge-driven crop design, which integrates multi-omics data to reveal the connections between genotypes and phenotypes and to build selection models, will undoubtedly become the most efficient way to shape plants, to improve crops, and to ensure food security., (Copyright © 2020 Elsevier GmbH. All rights reserved.)

After being domesticated from teosinte, cultivated maize ( Zea mays ssp. mays ) spread worldwide and now is one of the most important staple crops. Due to its tremendous phenotypic and genotypic diversity, maize also becomes to be one of the most widely used model plant species for fundamental research, with many important discoveries reported by maize researchers. Here, we provide an overview of the history of maize domestication and key genes controlling major domestication-related traits, review the currently available resources for functional genomics studies in maize, and discuss the functions of most of the maize genes that have been positionally cloned and can be used for crop improvement. Finally, we provide some perspectives on future directions regarding functional genomics research and the breeding of maize and other crops., (© 2019 Huazhong Agricultural University.)

Background: Root systems play important roles in crop growth and stress responses. Although genetic mechanism of root traits in maize (Zea mays L.) has been investigated in different mapping populations, root traits have rarely been utilized in breeding programs. Elucidation of the genetic basis of maize root traits and, more importantly, their connection to other agronomic trait(s), such as grain yield, may facilitate root trait manipulation and maize germplasm improvement. In this study, we analyzed genome-wide genetic loci for maize seedling root traits at three time-points after seed germination to identify chromosomal regions responsible for both seedling root traits and other agronomic traits in a recombinant inbred line (RIL) population (Zong3 × Yu87-1)., Results: Eight seedling root traits were examined at 4, 9, and 14 days after seed germination, and thirty-six putative quantitative trait loci (QTLs), accounting for 9.0-23.2% of the phenotypic variation in root traits, were detected. Co-localization of root trait QTLs was observed at, but not between, the three time-points. We identified strong or moderate correlations between root traits controlled by each co-localized QTL region. Furthermore, we identified an overlap in the QTL locations of seedling root traits examined here and six other traits reported previously in the same RIL population, including grain yield-related traits, plant height-related traits, and traits in relation to stress responses. Maize chromosomal bins 1.02-1.03, 1.07, 2.06-2.07, 5.05, 7.02-7.03, 9.04, and 10.06 were identified QTL hotspots for three or four more traits in addition to seedling root traits., Conclusions: Our identification of co-localization of root trait QTLs at, but not between, each of the three time-points suggests that maize seedling root traits are regulated by different sets of pleiotropic-effect QTLs at different developmental stages. Furthermore, the identification of QTL hotspots suggests the genetic association of seedling root traits with several other traits and reveals maize chromosomal regions valuable for marker-assisted selection to improve root systems and other agronomic traits simultaneously.

Key Message: Genetic relationships among Chinese maize germplasms reveal historical trends in heterotic patterns from Chinese breeding programs and identify line Dan340 as a potential genome donor for elite inbred line Zheng58. The characterization of the genetic relationships, heterotic patterns and breeding history of lines in maize breeding programs allows breeders to efficiently use maize germplasm for line improvement over time. In this study, 269 temperate inbred lines, most of which have been widely used in Chinese maize breeding programs since the 1970s, were genotyped using the Illumina MaizeSNP50 BeadChip, which contains 56,110 single-nucleotide polymorphisms. The STRUCTURE analysis, cluster analysis and principal coordinate analysis results consistently revealed seven groups, of which five were consistent with known heterotic groups within the Chinese maize germplasm-Domestic Reid, Lancaster, Zi330, Tang SPT and Tem-tropic I (also known as "P"). These genetic relationships also allowed us to determine the historical trends in heterotic patterns during the three decades from 1970 to 2000, represented by Mo17 from Lancaster, HuangZaoSi (HZS) from Tang SPT, Ye478 from Domestic Reid and P178 from Tem-tropic I heterotic groups. Mo17-related commercial hybrids were widely used in the 1970s and 1980s, followed by the release of HZS- and Ye478-related commercial hybrids in the 1980s and 1990s, and the introduction of Tem-tropic I group in the 1990s and 2000s. Additionally, we identified inbred line Dan340 as a potential genome donor for Zheng58, which is the female parent of the most widely grown commercial hybrid ZhengDan958 in China. We also reconstructed the recombination events of elite line HZS and its 14 derived lines. These findings provide useful information to direct future maize breeding efforts.

Key Message: Thirty loci for fertility restoration of pollen fertility, anther exsertion and pollen shedding to maize CMS-S were identified by GWAS. S type cytoplasmic male sterile (CMS-S) is the main type of CMS in maize; poor understanding of the genetic architecture of fertility restoration to CMS-S is one of the reasons to impede its utility in hybrid breeding. In this study, genome-wide identification of genetic loci for fertility restoration ability to CMS-S was firstly conducted with a set of testcrossing association mapping panel in three environments. A total of 19, 3 and 8 significant loci (P < 1.8 × 10(-6), α = 1) for pollen fertility, anther exsertion and pollen shedding were identified, respectively, and individual locus explained up to 28.26% of phenotypic variation. Of them, only Rf3, the main restorer-fertility gene of CMS-S, was identified for the three traits simultaneously. In addition, 83 candidate genes within the 100 kb extension regions of these loci were predicted. These results revealed that besides Rf3 multiple genetic loci and mechanisms are involved in the fertility restoration ability to CMS-S. Results in this study would provide important information for understanding the genetic architecture of fertility restoration to CMS-S in maize.

CRISPR/Cas9, Genome-editing, Fluorescence protein, Visualization, Zea mays Keywords: CRISPR/Cas9; Genome-editing; Fluorescence protein; Visualization; Zea mays EN CRISPR/Cas9 Genome-editing Fluorescence protein Visualization Zea mays 872 874 3 05/20/21 20210501 NES 210501 The emerging and promising biotechnology methodology of CRISPR/Cas9 gene editing is revolutionizing crop improvement. [Extracted from the article]

Summary: It is generally recognized that many favorable genes which were lost during domestication, including those related to both nutritional value and stress resistance, remain hidden in wild relatives. To uncover such genes in teosinte, an ancestor of maize, we conducted metabolite profiling in a BC2F7 population generated from a cross between the maize wild relative (Zea mays ssp. mexicana) and maize inbred line Mo17. In total, 65 primary metabolites were quantified in four tissues (seedling‐stage leaf, grouting‐stage leaf, young kernel and mature kernel) with clear tissue‐specific patterns emerging. Three hundred and fifty quantitative trait loci (QTLs) for these metabolites were obtained, which were distributed unevenly across the genome and included two QTL hotspots. Metabolite concentrations frequently increased in the presence of alleles from the teosinte genome while the opposite was observed for grain yield and shape trait QTLs. Combination of the multi‐tissue transcriptome and metabolome data provided considerable insight into the metabolic variations between maize and its wild relatives. This study thus identifies favorable genes hidden in the wild relative which should allow us to balance high yield and quality in future modern crop breeding programs. Significance Statement: A large scale QTL mapping of primary metabolite traits in a teosinte‐maize population reveals robust advantages existing in teosinte primary metabolism. [ABSTRACT FROM AUTHOR]

Key message: Genetic basis of grain yield heterosis relies on the cumulative effects of dominance, overdominance, and epistasis in maize hybrid Yuyu22. Abstract: Heterosis, i.e., when F hybrid phenotypes are superior to those of the parents, continues to play a critical role in boosting global grain yield. Notwithstanding our limited insight into the genetic and molecular basis of heterosis, it has been exploited extensively using different breeding approaches. In this study, we investigated the genetic underpinnings of grain yield and its components using 'immortalized F' and recombinant inbred line populations derived from the elite hybrid Yuyu22. A high-density linkage map consisting of 3,184 bins was used to assess (1) the additive and additive-by-additive effects determined using recombinant inbred lines; (2) the dominance and dominance-by-dominance effects from a mid-parent heterosis dataset; and (3) the various genetic effects in the 'immortalized F' population. Compared with a low-density simple sequence repeat map, the bin map identified more quantitative trait loci, with higher LOD scores and better accuracy of detecting quantitative trait loci. The bin map showed that, among all traits, dominance was more important to heterosis than other genetic effects. The importance of overdominance/pseudo-overdominance was proportional to the amount of heterosis. In addition, epistasis contributed to heterosis as well. Phenotypic variances explained by the QTLs detected were close to the broad-sense heritabilities of the observed traits. Comparison of the analyzed results obtained for the 'immortalized F' population with those for the mid-parent heterosis dataset indicated identical genetic modes of action for mid-parent heterosis and grain yield performance of the hybrid. [ABSTRACT FROM AUTHOR]

The worldwide production of maize (Zea mays L.) is frequently impacted by water scarcity and as a result, increased drought tolerance is a priority target in maize breeding programs. While DREB transcription factors have been demonstrated to play a central role in desiccation tolerance, whether or not natural sequence variations in these genes are associated with the phenotypic variability of this trait is largely unknown. In the present study, eighteen ZmDREB genes present in the maize B73 genome were cloned and systematically analyzed to determine their phylogenetic relationship, synteny with rice, maize and sorghum genomes; pattern of drought-responsive gene expression, and protein transactivation activity. Importantly, the association between the nucleic acid variation of each ZmDREB gene with drought tolerance was evaluated using a diverse population of maize consisting of 368 varieties from tropical and temperate regions. A significant association between the genetic variation of ZmDREB2.7 and drought tolerance at seedling stage was identified. Further analysis found that the DNA polymorphisms in the promoter region of ZmDREB2.7, but not the protein coding region itself, was associated with different levels of drought tolerance among maize varieties, likely due to distinct patterns of gene expression in response to drought stress. In vitro, protein-DNA binding assay demonstrated that ZmDREB2.7 protein could specifically interact with the target DNA sequences. The transgenic Arabidopsis overexpressing ZmDREB2.7 displayed enhanced tolerance to drought stress. Moreover, a favorable allele of ZmDREB2.7, identified in the drought-tolerant maize varieties, was effective in imparting plant tolerance to drought stress. Based upon these findings, we conclude that natural variation in the promoter of ZmDREB2.7 contributes to maize drought tolerance, and that the gene and its favorable allele may be an important genetic resource for the genetic improvement of drought tolerance in maize. [ABSTRACT FROM AUTHOR]

Meta-analysis was performed for three major foliar diseases with the aim to find out the total number of QTL responsible for these diseases and depict some real QTL for molecular breeding and marker assisted selection (MAS) in maize. Furthermore, we confirmed our results with some major known disease resistance genes and most well-known gene family of nucleotide binding site (NBS) encoding genes. Our analysis revealed that disease resistance QTL were randomly distributed in maize genome, but were clustered at different regions of the chromosomes. Totally 389 QTL were observed for these three major diseases in diverse maize germplasm, out of which 63 QTL were controlling more than one disease revealing the presence of multiple disease resistance (MDR). 44 real-QTLs were observed based on 4 QTL as standard in a specific region of genome. We also confirmed the Ht1 and Ht2 genes within the region of real QTL and 14 NBS-encoding genes. On chromosome 8 two NBS genes in one QTL were observed and on chromosome 3, several cluster and maximum MDR QTL were observed indicating that the apparent clustering could be due to genes exhibiting pleiotropic effect. Significant relationship was observed between the number of disease QTL and total genes per chromosome based on the reference genome B73. Therefore, we concluded that disease resistance genes are abundant in maize genome and these results can unleash the phenomenon of MDR. Furthermore, these results could be very handy to focus on hot spot on different chromosome for fine mapping of disease resistance genes and MAS. [ABSTRACT FROM AUTHOR]

Vitamin A deficiency (VAD) compromises immune function and is the leading cause of preventable blindness in children in many developing countries. Biofortification, or breeding staple food crops that are rich in micronutrients, provides a sustainable way to fight VAD and other micronutrient malnutrition problems. Polymorphisms, with associated molecular markers, have recently been identified for two loci, LcyE (lycopene epsilon cyclase) and CrtRB1 (β-carotene hydroxylase 1) that govern critical steps in the carotenoid biosynthetic pathway in maize endosperm, thereby enabling the opportunity to integrate marker-assisted selection (MAS) into carotenoid breeding programs. We validated the effects of 3 polymorphisms (LcyE5′TE, LcyE3′Indel and CrtRB1-3′TE) in 26 diverse tropical genetic backgrounds. CrtRB1-3′TE had a two-ten fold effect on enhancing beta-carotene (BC) and total provitamin A (proA) content. Reduced-function, favorable polymorphisms within LcyE resulted in 0-30 % reduction in the ratio of alpha- to beta-branch carotenoids, and increase in proA content (sometimes statistically significant). CrtRB1-3′TE had large, significant effect on enhancing BC and total ProA content, irrespective of genetic constitution for LcyE5′TE. Genotypes with homozygous favorable CrtRB1-3′TE alleles had much less zeaxanthin and an average of 25 % less total carotenoid than other genotypes, suggesting that feedback inhibition may be reducing the total flux into the carotenoid pathway. Because this feedback inhibition was most pronounced in the homozygous favorable LcyE (reduced-function) genotypes, and because maximum total proA concentrations were achieved in genotypes with homozygous unfavorable or heterozygous LcyE, we recommend not selecting for both reduced-function genes in breeding programs. LcyE exhibited significant segregation distortion (SD) in all the eight, while CrtRB1 in five of eight digenic populations studied, with favorable alleles of both the genes frequently under-represented. MAS using markers reported herein can efficiently increase proA carotenoid concentration in maize. [ABSTRACT FROM AUTHOR]

The organization of maize ( Zea mays L.) germplasm into genetically divergent heterotic groups is the foundation of a successful hybrid maize breeding program. In this study, 94 CIMMYT maize lines (CMLs) and 54 United States germplasm enhancement of maize (GEM) lines were assembled and characterized using 1,266 single nucleotide polymorphisms (SNPs) with high quality. Based on principal component analysis (PCA), the GEM lines and CMLs were clearly separated. In the GEM lines, there were two groups classified by PCA corresponding to the heterotic groups 'stiff stalk' and 'non-stiff stalk'. CMLs did not form obvious subgroups by PCA. The allelic frequency of each SNP differed in GEM lines and CMLs. In total, 3.6% alleles (46/1,266) of CMLs are absent in GEM lines and 4.4% alleles (56/1,266) of GEM lines are absent in CMLs. The performance of F1 plants ( n = 654) produced by crossing between different groups based on pedigree information was evaluated at the breeding nurseries of two CIMMYT stations. Genomic estimated phenotypic values of plant height and days to anthesis for a testing set of 45 F1 crosses were predicted based on the training data of 600 F1 crosses using a best linear unbiased prediction method. The prediction accuracy benefitted from the adoption of the markers associated with quantitative trait loci for both traits; however, it does not necessarily increase with an increase in marker density. It is suggested that genomic selection combined with association analysis could improve prediction efficiency and reduce cost. For hybrid maize breeding in the tropics, incorporating GEM lines which have unique alleles and clear heterotic patterns into tropically adapted lines could be beneficial for enhancing heterosis in grain yields. [ABSTRACT FROM AUTHOR]

The gene encoding acyl-CoA:diacylglycerol acyltransferase ( DGAT1- 2) is a key quantitative trait locus that controls oil content and oleic acid composition in maize kernels. Here we re-sequenced the DGAT1- 2 region responsible for oil variation in a maize landrace set and in 155 inbred lines (35 high-oil and 120 normal lines). The high-oil DGAT1- 2 allele was present in most Northern Flint and Southern Dent populations but was absent in five of eight Corn Belt Dent open-pollinated populations and in most of the earlier inbred lines. Loss of the high-oil DGAT1- 2 allele possibly resulted from genetic drift in the early twentieth century when a few Corn Belt Dent populations were selected for the development of high-grain-yield inbred lines. Association analysis detected significant effects of two PCR-based functional markers (HO06 and DGAT04; developed based on DGAT1- 2 polymorphisms) on kernel oil content and oleic acid composition using the 155 inbred lines. Zheng58 and Chang7-2, the parent inbred lines of elite hybrid Zhengdan958, were used to transfer the favorable allele from the high-oil line By804 using marker-assisted backcrossing with the two functional markers. In BC5F2:3 populations, oil content of the three genotypes (−/−, +/−, and +/+) was, respectively, 3.37, 4.20, and 4.61% (Zheng58 recipient line) and 4.14, 4.67, and 5.25% (Chang7-2 recipient line). Oil content of homozygous kernels containing the high-oil DGAT1- 2 allele increased by 27-37% compared with recurrent parents. Hence, these functional markers can be used to re-introduce the high-oil DGAT1- 2 allele into modern inbred lines for increased oil content through marker-assisted backcrossing. [ABSTRACT FROM AUTHOR]

Diseases are a potential threat to global food security but plants have evolved an extensive array of methodologies to cope with the invading pathogens. Non-host resistance and quantitative resistance are broad spectrum forms of resistance, and all kinds of resistances are controlled by extremely diverse genes called 'R-genes'. R-genes follow different mechanisms to defend plants and PAMP-induced defenses in susceptible host plants are referred to as basal resistance. Genetic and phenotypic diversity are vital in maize ( Zea mays L.); as such, genome wide association study (GWAS) along with certain other methodologies can explore the maximum means of genetic diversity. Exploring the complete genetic architecture to manipulate maize genetically reduces the losses from hazardous diseases. Genomic studies can reveal the interaction between different genes and their pathways. By confirming the specific role of these genes and protein-protein interaction (proteomics) via advanced molecular and bioinformatics tools, we can shed a light on the most complicated and abstruse phenomena of resistance. [ABSTRACT FROM AUTHOR]