Open access peer-reviewed chapter

Maize (Zea mays L.) as a Model System for Plant Genetic, Genomic, and Applied Research

Written By

Fakhriddin N. Kushanov, Ozod S. Turaev, Oybek A. Muhammadiyev, Ramziddin F. Umarov, Nargiza M. Rakhimova and Noilabonu N. Mamadaliyeva

Submitted: 17 October 2021 Reviewed: 24 March 2022 Published: 23 June 2022

DOI: 10.5772/intechopen.104658

From the Edited Volume

Model Organisms in Plant Genetics

Edited by Ibrokhim Y. Abdurakhmonov

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Maize leads the world’s cereals after wheat and rice in terms of cultivated area, because of its economic importance for the production of both food purposes and raw materials for industry. The maize genus Zea L. belonging to the family of cereals (Poaceae or Graminaceae) includes six species. However, all cultivated maize belongs specifically to Zea mays L. subsp. mays (2n = 2× = 20) is the only cultivated species of the genus Zea L., and the remaining species of this genus are mostly wild herbaceous plants. In addition to meeting the nutritional needs of the world’s population, Zea mays L. is one of the classic model objects of genetic and physiological research, as well as in the field of breeding not only cereals but also other important agricultural plants. Especially, this model object has been used in genetic mapping of loci of quantitative traits and genes associated with economically valuable traits, such as yield, resistance to diseases and pests, grain quality, etc. in cereal crops.


  • Zea mays L.
  • hybridization
  • cytoplasmic male sterility
  • QTL
  • mapping
  • GWAS

1. Introduction

Due to the constant growth of the world’s population, the demand for high-calorie foods is increasing. Although maize was developed as an American crop, it is now grown all over the world and today it has become the third most important food crop after wheat and rice [1, 2]. Maize is the world’s leading cereal after wheat and rice in terms of sown area, as currently makes up about 21% of the human diet worldwide and more than 500 different staples and additives are produced from it (FAOSTAT data). According to the International Grains Council (IGC), the corn grain harvest in 2021 was about 1.12 billion tons.

A special role in the genetic analysis is played by model objects, by working with which the researcher can significantly speed up and facilitate the process of analysis. Maize (Zea mays L.) is one of the main classical models for fundamental research in the fields of plant genetics and breeding. Especially, this model object has been used in genetic mapping of loci of quantitative traits and genes associated with economically valuable traits, such as yield, resistance to diseases and pests, grain quality, etc. in cereal crops. Since its chromosomes are easily analyzed under an optical microscope, maize is also suitable for plant cytogenetic analysis. The simplicity of castration (removal of male inflorescences—panicle), the presence of mutations that cause male sterility, the possibility of setting seeds both during cross-pollination and during self-pollination, the presence of a huge number of various mutations facilitates hybridization.

The genus Zea L. from the grass family (Poaceae or Graminaceae) is represented by four diploid (2n = 2× = 20) and one tetraploid (2n = 4× = 40) species;

  1. Zea diploperennis—diploperennial teosinte,

  2. Zea luxurians—teosinte,

  3. Zea nicaraguensis,

  4. Zea mays L.—corn are diploids, and

  5. Zea perennis—perennial teosinte is a tetraploid species.

In turn, Zea mays L. is divided into three subspecies, such as,

  1. Zea mays subsp. huehuetenangensis—maize,

  2. Zea mays L. subsp. mays and

  3. Zea mays subsp. parviglumis.

As well as there are three subspecies including

  1. Zea mays subsp. mays—corn,

  2. Zea mays subsp. mexicana (Schrad.), and

  3. Zea mays subsp. parviglumis.

All species belonging to the genus Zea L. cross with other maize diploid species, except the perennial tetraploid Z. perennis. While, the diploid maize and its wild relative, teosinte Zea perennis (Hitchc.) Reeves & Mangelsd, readily intercrossing [3].

Maize (Zea mays L. subsp. mays) is the single cultivated species of the genus Zea L. The genome size of the diploid maize species ranges from 2.2 to 2.7 GB, including approximately 32.000–42.000 protein-coding genes [4, 5]. The first tetraploid species of Zea mays L. was obtained by Randolph (1932), using the heat shock method [6]. The tetraploid species is characterized by the strong development of all plant organs, resistance to abiotic and biotic environmental factors, and increased content of nutrients compared to diploid species [7].

Currently, genetic, chromosomal, genomic, and cytoplasmic modifications have been identified in maize, in particular, gene mutations have been best studied [489]. Especially, the genes that control the behavior of chromosomes in mitosis and meiosis, enzyme systems, the formation of chlorophyll and other pigments have been studied and described; structures and functions of vegetative organs, structure, and color of the endosperm, regulatory systems responsible for the mutability and expression of other genes, for the development of various elements of the reproductive system, which determine male and female sterility, selective fertilization, etc. [4, 8, 10].

Moreover, in maize were found and well-studied spontaneous and induced chromosome rearrangements such as deficiencies, translocations, duplications, and inversions [4]. In recent years, translocations have been widely used in maize to determine linkage groups [8].

Since the discovery of polyploidy forms of maize, many of them have been well studied. They are found in the aneuploids—trisomics, and monosomics in maize [8]. On maize, cytological evidence of crossing over was obtained for the first time in plants and mobile genetic elements were discovered [8, 11]. It studied the influence of long-term inbreeding and the effects of heterosis in plants and developed hybrid breeding techniques based on obtaining and crossing pure lines (interline and double interline hybrids); cytoplasmic mutations are well studied, especially mutations associated with cytoplasmic male sterility (CMS), the use of which is one of the achievements of maize genetics and plant genetics in general.


2. The origin and evolution of maize

Even though the origin of maize has been studied in-depth, it remains controversial. Prehistoric breeder practitioners who cannot live and reproduce in their current form without human help [12] domesticated maize (Zea mays L.). After the American continent was discovered, it became clear that corn was the staple food of the endemic Indians on the continent. According to several authors, maize was introduced into cultivation 7–12.000 years ago in the territory of southwestern Mexico. Cave excavations in arid regions of Mexico have unearthed small grains of corn grown for food 5.000 years ago [13]. The oldest finds of cultivated corn kernels were discovered in the caves of Gwila Nakitz and Tehuacan, located in the northwestern state of Oaxaca and the southeastern state of Puebla in central Mexico. In addition, according to archaeobotanists Ranere et al. (2009), the first straight there is evidence that maize was domesticated about 8.700 years ago in the Balsas region from the wild teosinte plant [14].

Taxonomic and evolutionary studies indicate that the teosinte is the closest wild relative of four annual and perennial maize species of the genus Zea L. [3]. However, according to the authors, some species of teosinte are genetically and taxonomically differing from Zea mays L. While, in the study of maize genetics, researchers consider teosinte to be an important resource.

Thus, according to archaeobotanical findings and the results of traditional analyzes [12, 13], there are various theories about the origin of Zea mays L. ssp. mays:

  1. As a result of the selection of the wild subspecies Zea mays ssp. parviglumis. In addition, due to the possible introgressive hybridization with the ancestral form Z. mays ssp. mexicana, the genetic material of up to 12% of cultivated form might be obtained from this subspecies.

  2. Caused by the hybridization of small cultivated wild form with another species of this genus—either Z. luxurians or Z. diploperennis.

  3. One wild form has been introduced into the crop several times.

  4. From the hybridization of Zea diploperennis with some representatives of the closely related genus Tripsacum.


3. Maize polyploidy studies

Polyploidy or whole-genome duplication (WGD) is considered as a major process in plant evolution. A polyploidy event 160 million years ago is theorized to have created the ancestral line that led to all modern flowering plants [15]. Genome duplication is categorized into two events paleopolyploidy (ancient polyploidy) and neopolyploidy (recent polyploidy). Ancient genome duplications are widespread throughout eukaryotic lineages, particularly in plants. Paleopolyploidy has occurred at least several million years ago. Both phenomena, ancient and recent polyploids could occur through the doubling of the genome of single species (autopolyploidy) or combining genomes of two different species (allopolyploidy).

According to the maize DNA sequence data, the genome duplications event occurred after the divergence between sorghum and maize [10]. The duplications event that happened approximately 11.4 million years ago resulted from an ancient polyploid [16]. The maize WGD resulted in the subgenomes maize1 and maize2 [17]. Polyploids are found almost in all groups of eukaryotic organisms as a result of incorrect meiosis, fertilization, or cell division [18]. Polyploids can be obtained experimentally by treatment with chemicals such as colchicine, oryzalin, trifluralin and amiprophosmethyl or by combining diploid nuclei.

Niazi et al. (2014) have studied induced polyploidy in maize hybrids to increase heterosis and restore reproductive fertility [19]. The seeds of open-pollinated maize breeding lines and a maize × teosinte cross were germinated in colchicine solution (0.25, 0.5, or 1.0%) until they had a thick radical and protruded plumule. The highest number of tetraploids with the lowest number of chimeric plants induced at 0.5% colchicine. Scientists have reported that the leaf area, total soluble solids, leaf oil percentage, and leaf crude protein contents were significantly increased in leaves of the induced tetraploids of maize and maize × teosinte crosses relative to the diploid subspecies.

Iqbal et al. (2018) have conducted research aimed to clarify the mysterious meiotic behavior of autopolyploid and allopolyploid maize [20]. Scientists have explored the stability of the chromosomes during meiosis in both auto- and allopolyploid maize. Furthermore, they have identified an association of chromosomes between maize and Z. perennis by obtaining a numerous of auto- and allopolyploid maize hybrids. The results showed a higher level of chromosome stability in allopolyploid maize during meiosis than in autopolyploid maize. Additionally, the meiotic behavior of Z. perennis was relatively more stable than the allopolyploid maize. As well as, 10 chromosomes of maize “A” subgenomes were homologous to 20 chromosomes of Z. perennis genome with little evolutionary differentiation and a higher pairing frequency. However, “A” subgenome chromosomes have shown a little evolutionary differentiation, while “B” subgenome chromosomes had a lower pairing frequency and higher evolutionary differentiation in maize.

The diversity analysis of wild relatives of maize showed that various genes have different histories and domestication such as intensive breeding processes have had heterogeneous effects on genetic diversity across genes [10].


4. Maize is a model in genetic mapping studies for cereal crop improvement

4.1 QTL mapping and GWAS for dissecting genetic architecture of complex traits

A quantitative trait is a measurable phenotype and varies continuously among individuals in a population. Quantitative trait loci (QTL) are genomic regions in which genetic segregation within a population is statistically associated with variation in a quantitative trait. Genetic mapping of QTL is a process of locating genes with effects on quantitative traits using molecular markers. QTL mapping is a powerful method for improving agricultural crops, which allows using marker-assisted selection technology to introgression the genes of interest from one genotype to another [21].

QTL mapping and genome-wide association study (GWAS) both are similar and they typically measure the associations between genotype and phenotype [21, 22]. GWAS is a powerful tool for dissecting the genetic architecture of complex traits in many crop species [22, 23, 24]. The main goal of GWAS is to link genotypic variations with phenotypic differences. With the development of whole-genome sequencing technology and high-density single-nucleotide polymorphism (SNP) BeadCap, GWAS has also begun to be widely used to identify candidate genes that control quantitative traits in crops [22].

Maize is a suitable crop for the GWAS approach and considerable progress has been made over the last decade [25]. GWAS has been successfully used in maize to detect a great many candidate QTL/genes attending to control diverse morpho-biological and economically important traits, such as salt [26, 27, 28] and drought tolerance [8, 23, 29, 30, 31], kernel traits [32, 33, 34, 35, 36] and many other traits of interest. GWAS facilitates to achieve advances in current studies in quantitative genetics.

4.2 Genetic analysis and fine mapping of QTL for kernel traits

Grain traits are the most important in maize commercialization over the world. Kernel sizes and weight are major traits for grain yield in maize. Liu et al. (2014) was conducted the genetic analysis and identified major QTL for maize kernel size and weight [37]. They have identified a total of 55 and 28 QTL of maize kernel-size traits and kernel weight using composite interval mapping (CIM) for single-environment analysis along with mixed linear model-based CIM for joint analysis, respectively.

Wang et al. (2020) have conducted QTL analysis and fine mapping using a composite interval mapping (CIM) method aimed to map QTLs and predict candidate genes for kernel size in maize [38]. Five QTL were identified for kernel length and five QTL for kernel width out of 10 QTL.

Pan et al. (2017) reported the results of QTL mapping in six environments and consensus loci for grain weight detected by meta-analysis [39]. Subsequently, a meta-analysis was performed and 62 QTLs were determined for grain weight, ear weight, and kernel weight per plant in six environments.

Li et al. (2010) have carried out QTL mapping for grain yield and yield components under high and low phosphorus treatments in maize [40]. 69 QTL were identified for the six traits at two sites. Thirty-six distinct QTL were identified from Taian, in which 7 out of 36 for grain yield, 7 for 100 kernel weight, 5 for ear length, 5 for per ear, 6 for kernel number per row, and 6 for ear diameter, while 33 distinct QTLs were identified at Yantai, in which 6 out of 33 for grain yield, 5 for 100 kernel weight, 5 for ear length, 7 for row number per ear, 5 for kernel number per row and 5 for ear diameter.

Liu et al. (2020) have identification of QTL for kernel-related traits and the heterosis for these traits [34]. They developed and evaluated 301 RILs population for six kernel-related traits and the mid-parent heterosis (MPH) for these traits. A total of 100 QTLs were identified in both mapping populations. As well, 20 QTL clusters including 46 QTLs were identified across ten chromosomes. These results may provide additional insights into the genetic basis for the mid-parent heterosis for kernel-related traits.

Liu et al. (2015) conducted a genetic analysis of kernel traits in maize-teosinte introgression populations [33]. Scientists have analyzed kernel morphological traits in 10 maize-teosinte introgression populations using digital imaging software. QTLs were identified for kernel area and length with moderate allelic effects that colocalize with kernel weight QTL.

Another group of researchers has conducted linkage and association mapping aims to the analysis of the genetic architecture of maize kernel size [34]. Three kernel traits of maize, kernel length, kernel width, and kernel thickness, were studied in germplasm accessions and a biparental population. A total of 21 SNPs were identified under four environments. Besides, 50 QTL were determined in seven environments doubled haploid population. Combining the two mapping populations revealed that 56 SNPs fell within 18 of the QTL confidence intervals. A total of 73 candidate genes were detected, regulating seed development. As well, seven miRNAs were found to locate within the linkage disequilibrium regions of the colocalized SNPs.

Jiang et al. (2013) performed a meta-analysis of 584 QTLs related to grain yield components [41]. A total of 73 Meta-QTLs for grain yield components such as 22 QTLs for row number, 7 QTLs for kernel number per row, and 44 QTLs for kernel weight were estimated. Another group of Chinese scientists carried out combining meta-QTL with RNA-seq data to identify candidate genes of kernel row number traits [42]. A total of 373 QTL for grain yield and kernel row number was meta-analyzed. Fifty-four meta-QTL were determined, including 19 for grain yield and 35 for kernel row number. A total of 1.588 genes located in the kernel row number meta-QTL regions were identified by gene expression data.

DNA markers associated with kernel traits could be applied to marker-assisted selection (MAS) to facilitate yield architecture, QTL fine mapping, and gene cloning in the maize community [42].

4.3 The maize multiparental populations advance mapping resolution and power

4.3.1 Maize-NAM population as a template for other crops

Molecular mapping is typically carried out using genetically segregated F2, backcross (BC), recombinant inbred lines (RIL), doubled haploids (DH), and near-isogenic lines (NIL). These commonly used biparental populations have their weaknesses such as lower power, limited recombination, temporary nature, the impossibility of estimation of dominant effects, time requirement, and expense. To overcome some of the shortcomings in quantitative trait locus (QTL) mapping in biparental populations, schemes for creating mapping populations with multiple parental genotypes have been developed. The genetic diversity of these types of populations along with causing a wide range of phenotypes, it makes possible to identify QTLs with high accuracy.

The nested association mapping (NAM) population is also an example of the experimental design for multiparental populations (Figure 1). The NAM strategy was first developed in collaboration with researchers Buckler et al. [43] to study the genetic architecture of complex traits of maize (Zea mays L.). It should be noted that, unlike association mapping, NAM is a unique method that is performed only in a specially developed population [43].

Figure 1.

The nested association mapping (NAM) population scheme.

The theory of nested association mapping

The main goal of the NAM is to efficiently link phenotypic traits with genotypic data, as in a traditional QTL mapping strategy. The NAM method with low marker density, high allele richness, high mapping resolution, and high statistical power overcomes the disadvantages of Linkage analysis and Association mapping as well took advantages of both methods.

The NAM strategy allows researchers to effectively apply systematic methods of genetics and genomics and create sources such as general mapping populations as well to explore complex traits of plants at the fundamental level.

The NAM strategy involves the following stages [43]:

  1. Selection of diverse founders and the development of a mapping population (RILs with a stable set of phenotypic traits are preferred);

  2. Sequencing or high-density genotyping of parental genotypes;

  3. Genotyping of both the founders and the progenies with a smaller number of tagging markers to explain the inheritance of chromosome segments and to project the high-density marker information from the founders to the progenies;

  4. Phenotyping of hybrids/RILs for various complex traits;

  5. Conducting genome-wide association analysis using genotypic and phenotypic data.

The maize-NAM population was developed by crossing 25 diverse founders to a single common inbred line, B73, resulting in 5.000 RILs. Buckler et al. (2009) reported the results of the study on the genetic architecture of flowering time using the maize-NAM population [44, 45]. Subsequently, several NAM populations in maize were developed such as in Dent and Flint maize [46], Chinese inbred lines population-based NAM [47], and teosinte [48].

The maize-NAM design served as a model for other crops such as sorghum [149, 50, 51], peanut [52, 53], barley [11, 54, 55, 56, 57], oilseed rape [22, 58], wheat [59, 60, 61, 62, 63], rice [64, 65], soybean [66, 67] and cotton [68, 69] as well as NAM were developed in the model plant Arabidopsis thaliana [70, 71].

4.3.2 MAGIC population with greatly reduce mating design

Over the past decade, the use of multiparental populations was increased in plant genetic research. The two most popular multiparental population designs in crops are NAM and MAGIC (multi-parent advanced generation inter-cross) populations (Figure 2) [72]. MAGIC populations offer new opportunities in genetic mapping strategies and crop breeding approaches due to their complex pedigree structure [73]. MAGIC was first proposed and applied in mice [74], as well as Mackay and Powell (2007), and Cavanagh et al. (2008) first discussed in plants [75, 76]. The first plant-MAGIC population was developed in A. thaliana parents [77].

Figure 2.

Multi-parent advanced generation inter-cross (MAGIC) population scheme.

According to the MAGIC designs [75], several inbred lines are intercrossed many times over in aiming to assemble mosaic parental alleles in a single line (Figure 1). Two different MAGIC populations were developed in maize [78, 79, 80].

Dell’Acqua et al. (2015) produced 1.636 MAGIC maize RILs derived from eight genetically diverse inbred lines [79]. They show how MAGIC maize may find strong candidate genes by incorporating genome sequencing and transcriptomics data. They discuss several QTL for grain yield and flowering time, reporting candidate genes. Anderson et al. (2018) were developed four parent maize populations with five different mating designs used in MAGIC and bi-parental populations including 1.149 individuals [78]. The combined population here is comprised of 118.509 genetic markers. They conducted association mapping and identified 2, 5, 7, and 6 QTL for plant height, ear height, days to anthesis, and silking, respectively [78].


5. “Omics” tools to understand molecular mechanisms of major traits

5.1 RNAi and genome editing tools for control gene expression

The possibility of using an organism’s own gene and systematically inducing and triggering RNA interference (RNAi) for any desired sequence made RNAi an effective approach for functional genomics [81]. RNAi is a major biological process in plants that causes gene silencing both transcriptionally and post-transcriptionally. RNAi has been widely used in crops since its discovery. To date, this approach has been conventionally based on the use of transgenic plants expressing double-stranded RNAs (dsRNAs) against selected targets [82].

Segal et al. (2003) have conducted initial studies on RNAi mechanisms in maize [83]. They found that maize transformed RNAi constructs for 22-kD zein gene suppression could produce a dominant opaque phenotype. This phenotype suppresses 22-kD zeins without affecting the accumulation of other zein proteins.

Casati et al. (2006) have conducted GWAS of high-altitude maize and gene knockdown stocks implicate chromatin-remodeling proteins in response to UV-B [84]. They implemented comparative analysis by expression profiling of maize aim to determine new components in the mechanisms of maize responses to UV-B. Microarray analysis illustrated that among the UV-B responsive transcripts, various types of genes implicated in chromatin remodeling are differentially expressed before and after UV-B treatment in high-altitude lines. Transgenic RNAi plants with lower expression of four chromatin-associated genes showed hypersensitivity to UV-B, and altered UV-B regulation of selected genes. The results showed that genes attended in chromatin remodeling are crucial for UV-B acclimation and that some lines illustrate adaptations to this challenge.

Besides, Casati and Walbot (2008) have reported different transcriptome changes in RNAi lines. They used 44 K Agilent oligonucleotide array platform to compare RNAi lines to each other and to UV-B tolerant nontransgenic siblings both before and after 8 h of UV-B exposure [85]. Maize leaves express more than 20.000 different transcripts under greenhouse conditions; after UV-B exposure 267 transcripts exhibit expression changes in control genotypes of B73.

In recent years, RNAi research in maize has been developing rapidly. One of the agricultural economic problem is aflatoxins that are produced by fungus species such as Aspergillus. In spite of control efforts, aflatoxin contamination is causing the global loss of crops productions each year. Thakare et al. (2017) have obtained aflatoxin-free transgenic maize using host-induced gene silencing [86]. Scientists show that host-induced gene silencing is an effective method for eliminating this toxin in transgenic maize. They transformed RNAi-gene cassette targeting aflC gene, which encodes an enzyme in the Aspergillus aflatoxin biosynthetic pathway to the maize plants. The aflatoxin was not be detected in kernels of RNAi-maize plants after pathogen infection, while toxin loads reached thousands of parts per billion in nontransgenic control kernels. The results show that siRNA molecules can be used to silence aflatoxin biosynthesis in maize.

Velez et al. (2020) have studied the lethal and sublethal effects of Sec23 dsRNA in maize RNAi lines to control western corn rootworm (WCR) [87]. They determined Sec23 as a highly lethal RNAi target using WCR adult feeding assays. Scientists explain Sec23 dsRNA as an RNAi target for planta rootworm control.

In the last few years, new genome editing methods have emerged that use four types of engineered nucleases: Meganucleases, ZFN (Zinc-Finger Nucleases), TALENs (Transcription Activator Like Effector Nucleases), and the CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) system. Among model plants, including maize, all kinds of nucleases mentioned above have been used to create targeted genome modifications [88, 89]. For example, D’Halluin et al. (2008) reported the first use of targeted genome modification using customizable endonucleases in maize. They succeeded in inserting a 35S promoter upstream of a promoterless herbicide resistance transgene using a meganuclease [90]. Later, Shukla et al. (2009) reported the first use of ZFNs for site-directed mutagenesis at the maize IPK1 gene as well as site-directed DNA insertion of a PAT gene [91]. Especially, among the DNA-Free Genome Editing technologies TALEN and CRISPR/cas9 technologies, have become powerful tools for genomic research. For the first time in maize, a group of scientists [92] using both TALEN and CRISPR systems reported the results of site-directed mutagenesis in maize. They designed 5 TALEN and two CRISPR constructions that target three genes involved in phytic acid (PA) biosynthesis. The results of this study served to reduce the content of PA in the seed and this led the authors to conclude that both technologies can be used to modify the maize genome. The following year, using this technology has been obtained the generation of stable, heritable mutations at the maize glossy2 locus [93]. As a result of this study, transgenic plants containing mono- or diallelic mutations were obtained with a frequency of about 10%. However, the TALEN method is more labor-intensive, requiring more time for construction than CRISPR/Cas9.

Thus, the development of the TALEN and CRISPR/Cas9 systems is an important step in the development of modern genomic engineering. The emergence of these systems, due to their low cost and ease of design, has become a powerful impetus for the development of both fundamental and applied science. More precisely, directional editing of plant genomes can be used to solve both; the study of gene functions and obtain plants with new properties, such as resistance to pathogens, herbicides, metabolism changes, yield indicators, etc. [94].

5.2 Maize proteomics opens the way for an insight into the biology of cereal crop

In the natural conditions of growth or cultivation of a species, plants in the process of their growth and development are often affected by adverse environmental factors [95]. Under the influence of unfavorable conditions, the decrease in physiological processes and functions can reach critical levels that do not ensure the implementation of the genetic program of ontogenesis, energy metabolism, regulatory systems, protein metabolism, and other vital functions of the plant organism are disrupted [96].

The main feature of protein research at the end of the twentieth century is proteomics. Since proteomics complements the research of genomics, transcriptomics, and metabolomics, it plays a central role in systems biology. Over the past three decades, significant progress has been made in the proteomic studies of maize as a model object [97]. Maize proteomic studies can be divided into two categories [98]:

  1. Profiling (or mapping) of the identified proteins of biological material, with the aim of separating, identifying, and cataloging as many proteins as possible, and, thus, the most complete scanning of the expressed genome sequences in individual representatives, at certain phases of development.

  2. Functional (cell-mapped) proteomics—studies polymorphism between different protein populations. With the help of two-dimensional electrophoresis, a comparative analysis of protein extracts of control and experimental plants is carried out. Both types of analysis became more real and informative after the sequencing of the reference genotype of maize B73 was completed [10, 98].

To date, published maize proteomic studies have used major proteomic technologies such as SDS-PAGE and two-dimensional electrophoresis (2-DE), laser capture microdissection, a combination of 2-DE with time-of-flight mass spectrometry (MALDI TOF), gas chromatography-mass spectrometry technologies [99, 100, 101, 102, 103, 104]. The main proteomic studies served to study changes in the composition of proteins under the influence of biotic and abiotic factors. For example, the effect of salicylic acid under high-temperature stress on the growth of seedlings and the antioxidant defense system of corn was studied [105]. In addition, the effect of some phytohormones, such as salicylic acid (SA), abscisic acid (ABA), jasmonic acid (JA), and methyl jasmonate (MeJA), on the protein composition of corn roots and leaves has been studied, and their important role in plant defenses has been proven [7, 98, 101, 105, 106].

However, despite the potential role of proteomics in advancing the study of stress tolerance in plants (also in the model), little useful information has been obtained so far for crop improvement and breeding [99].

5.3 Maize is a paragon for investigation of epigenetic studies

Epigenetic gene regulation is essential for the proper development of organisms. Epigenetic changes such as DNA methylation, histone modification, and RNA processing influence gene expression without changing the DNA sequence. Epigenetic studies have been the focus of many questions in plant research over the last decade [107]. The maize genome is relatively large and complex that includes abundant repetitive sequences, which are regularly silenced by epigenetic changes, making it an ideal organism to study epigenetic gene regulation. The application of new technologies to characterize maize epigenomes allows an understanding of the relationship between epigenetic mechanisms and genome organization [108].

Initial examples of epigenetic regulation were related to the transposable elements, starting with McClintock’s early work in the 1950s [109]. Implementation of advanced technologies to describe maize epigenomes allows a more clear understanding of the association between epigenetic mechanisms and genome organization. In maize, the genome-wide analysis of cytosine methylation was carried out using the combination of high-throughput DNA sequencing with the enzymatic characterization of methylated bases through bisulfite conversion. In recent years, numerous genome-wide studies of cytosine methylation have been published in maize [30, 80, 110, 111, 112, 113, 114, 115].

Eichten et al. (2011) have studied heritable epigenetic variation among maize inbred lines [111]. The comparison analysis of the DNA methylation degree of B73 and Mo17 maize lines permitted determining of about 700 differentially methylated regions (DMRs). Some DMRs occur in genomic regions that are apparently identical by descent in B73 and Mo17 suggesting that they may be examples of pure epigenetic variation. The results of this study showed the naturally occurring epigenetic variation in maize, including a pure epigenetic variation that is not conditioned by genetic differences. The identified epigenetic variation may provide complex trait variation.

Regulski et al. (2013) present the genome-wide map of cytosine methylation for two maize inbred lines, B73 and Mo17 [116]. Results showed that CpG (65%) and CpHpG (50%) islands (where H = A, C, or T) are highest methylated in transposons while CpHpH methylated is likely guided by 24-nucleotide (nt), but not 21-nt, small interfering RNAs (siRNAs). Scientists concluded that CpG methylation in exons (8%) may deter insertion of Mutator transposon insertion, while CpHpG methylation at splice acceptor sites may inhibit RNA splicing. The methylation map developed in this study will be an invaluable resource for maize epigenetic studies.

West et al. (2014) have studied the genomic distribution of H3K9me2 and DNA methylation in a maize genome [117]. They have investigated H3K9me2 in seedling tissue for the maize inbred B73 and compared to patterns of these modifications observed in Arabidopsis thaliana. This study gives a clear view of the relationship between DNA methylation and H3K9me2 in the maize genome and how the distribution of these modifications is shaped by the interplay of genes and transposons.

Kravets and Sokolova (2020) have studied the relationship between epigenetic variability with different individual radiosensitivity and adaptive capacity [118]. The researchers found significant differences in chromosomal aberration yield and DNA methylation profile under control and UV-C exposure for seedlings of subpopulations that differed in germination time. These significant differences in the control seedlings of different germination terms show the effect of the DNA methylation profile on DNA damage by regular metabolic factors including reactive oxygen species or thermal vibrations. The results showed the importance of epigenetic factors in identifying the radio-resistance and adaptive capacity of organisms.

Han et al. (2021) have reported epigenetic links to inbreeding depression in maize [119]. Throughout the subsequent inbreeding between inbred lines, thousands of genomic regions across TPC (teosinte branched1/cycloidea/proliferating cell factor)-binding sites (TBS) are hypermethylated across the H3K9me2-mediated pathway. Thus, several hundred TCP-target genes attended in mitochondrion, chloroplast, and ribosome functions are down-regulated, causing decreased growth vigor. On the contrary, random mating can reverse corresponding hypermethylation sites and TCP-target gene expression, restoring growth vigor.

A sufficiently large and highly repetitive maize genome provides an excellent model for other crop genomes to study gene regulation.


6. Conclusion and future prospect

More recently, plants have not played an important role in various genetic research because of their large and complex plant genomes. The role of model objects in understanding the patterns of historical and individual development of organisms is exceptionally great. The choice of an object for experimental scientific research, as a rule, becomes a separate task that requires special attention. It is necessary to clearly understand the criteria that the object of study must meet in order not only to solve the scientific problem, but also in its own way to facilitate the direct setting of the experiment. Plant genetics, physiology, and biochemistry have developed along this path, and the formation of modern sections of the biology of individual development is proceeding along this path.

Gradual studies carried out on model objects such as Arabidopsis, tobacco, and rice, including corn, proved that plants could also play a key role in molecular genetic experiments. Currently, genetic, chromosomal, genomic, and cytoplasmic modifications have been identified in maize; in particular, gene mutations have been best studied. To date, Zea mays L. is widely used in scientific research of the plant world. Day after day, it becomes a real classical model in plant biology; it has unconditional advantages in solving many current issues of genetics and individual development of plants, including cereals. Nevertheless, world science is moving forward and posing tasks that are ever more complex for researchers, for which corn alone is not enough.


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Written By

Fakhriddin N. Kushanov, Ozod S. Turaev, Oybek A. Muhammadiyev, Ramziddin F. Umarov, Nargiza M. Rakhimova and Noilabonu N. Mamadaliyeva

Submitted: 17 October 2021 Reviewed: 24 March 2022 Published: 23 June 2022