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Open Access Review

Molecular Marker Analysis of Genetic Diversity in Maize: A Review

Anand Kumar 1, Ningthai Longmei 2, Pardeep Kumar 2, Prashant Kaushik 3,4,*

  1. Department of Genetics and Plant Breeding, Chandra Shekhar Azad University of Agriculture and Technology, Kanpur, India

  2. ICAR-Indian Institute of Maize Research, Ludhiana, India

  3. Kikugawa Research Station, Yokohama Ueki, 2265, Kamo, Kikugawa City, Shizuoka 439-0031, Japan

  4. Instituto de Conservación y Mejora de la Agrodiversidad Valenciana, Universitat Politècnica de València, Valencia, Spain

Correspondence: Prashant Kaushik

Academic Editors: Ioannis Ν. Xynias and Theano. B. Lazaridou

Special Issue: Genetics, Genomics, and Breeding Crop Cultivars for the Novel Changing World

Received: July 25, 2021 | Accepted: March 15, 2022 | Published: March 21, 2022

OBM Genetics 2022, Volume 6, Issue 1, doi:10.21926/obm.genet.2201150

Recommended citation: Kumar A, Longmei N, Kumar P, Kaushik P. Molecular Marker Analysis of Genetic Diversity in Maize: A Review. OBM Genetics 2022; 6(1): 150; doi:10.21926/obm.genet.2201150.

© 2022 by the authors. This is an open access article distributed under the conditions of the Creative Commons by Attribution License, which permits unrestricted use, distribution, and reproduction in any medium or format, provided the original work is correctly cited.

Abstract

Maize is consumed as a food and used as an industrial product in the form of starch, pharmaceuticals, alcoholic beverages, oil, cosmetics, and textiles. In ancient times, landraces were more popular due to the presence of high genetic variability, resistance to biotic and abiotic factors, and the heterogeneous nature of maize; however, it has been replaced by improved and uniform cultivars with a higher yield. Modern maize has more homogeneity that enhances its vulnerability to biotic and abiotic stresses. Thus, we need to study the diversity in maize to successfully use its characteristics. Several markers such as morphological, biochemical, and DNA-based markers/molecular markers are utilized to study the germplasm diversity. Although extensively used, morphological and biochemical markers were highly sensitive to the environment because of which, these are being replaced by molecular markers. In the current era of molecular markers, DNA markers play an important role in identifying diverse germplasms because of high precision and accuracy. In this review, we focused on the types of markers utilized to accelerate the knowledge of maize genetic diversity and the prospect of genetic diversity.

Keywords

Maize; genetic diversity; molecular marker

1. Introduction

Maize (Zea maize L.) is one of the important economic and staple food crops and an energy plant among cereals that is cultivated globally for fulfilling the requirements of human beings [1]. It is a vital source of the income-overwhelming population [2]. With a high yield potential, it has become a model crop among cereals and is therefore called the queen of cereal crops [3]. In addition, it is utilized as an industrial resource for the production of starch, pharmaceuticals, alcoholic beverages, oil, cosmetics, and textiles [4]. Due to the diverse uses of maize and its products, its demand has been increasing continuously globally [5]. In ancient times, landraces were more popular, and maize was highly resistant to biotic and abiotic factors due to its heterogeneous nature, although the yield was low [6]. Now, the landraces are being replaced with hybrid maize, which has a higher yield as compared to landraces [7]. The present cultivated form of maize is originated from its wild relative teosinte (Zea mays ssp. parviglumis), but cultivated maize is considerably different from teosinte in terms of morphology and several other characteristics [8]. The production of high-yielding maize cultivars has always been the primary objective of breeding. For increasing the production of maize, several varieties, including sweet corn, popcorn, and high-quality protein corn, are being developed globally [9]. In spite of huge work on developed varieties of maize, its yields are below their potential because of abiotic and biotic stresses, indicating the need to assess the genetic diversity. Knowledge of genetic diversity in maize crop, especially of germplasm and inbred lines, have significantly impacted crop improvement [10]. Maize is characterized by tremendous genetic diversity [4].

Genetic diversity is defined as the total variability present in an individual or organism/population [11]. Genetic diversity is an important aspect of breeding programs to develop high-yielding varieties [12]. The potential of genetic diversity of maize has reduced drastically due to the continuous use of homogeneous varieties [10]. To conserve the diversity, breeders need to study its huge germplasm [13] and inbreds [14]. To obtain the knowledge of genetic diversity in maize, that is, which lines have more diversity than others, several studies have been conducted to study the morphological, biochemical, and molecular characteristics of maize [15]. Although morphological and biochemical methods are being extensively used [16], these approaches are highly sensitive to environmental effects [17]. To address the challenges of morphological and biochemical methods, a new approach based on molecular markers is being utilized to study the relationship among lines and varieties [15]. The expression of DNA markers/molecular markers is rarely influenced by the environment and avoid genotypic × environmental interactions; hence, these markers could reveal the actual level of different population analysis. Thus, these markers are being utilized in populations (Table 1), resulting in huge progress [18,19,20]. In this review, we focused on the potential role of genetic diversity for starting breeding programs and the kinds of markers being used to assess genetic diversity.

Table 1 Various markers used in maize for genetic diversity, genetic purity, and DNA fingerprinting.

2. Classification of Molecular Markers

In the case of plant breeding, several molecular markers have been utilized for the analysis of genetic diversity [18,19]. Molecular markers can highlight the differences (polymorphisms) within a nucleic acid sequence between different individuals. These differences include insertions, deletions, translocations, duplications, and point mutations. They do not, however, encompass the activity of specific genes [71]. To aggregate the knowledge of molecular markers is a difficult but necessary task. Several molecular markers have been classified for maize.

2.1 Analysis of Maize Diversity through Restriction Fragment Length Polymorphism (RFLP)

Restriction fragment length polymorphism (RFLP) was the first genetic marker, developed by Botstein et al. in 1980 [72] to detect DNA polymorphism. RFLP technique depends on the short southern blot technique. In this technique, DNA is digested using a restriction endonuclease enzyme, which cleaves the DNA into different fragments to detect the polymorphism [72]. For example, 148 American maize populations [73] and 488 European maize populations [74] were characterized at the molecular level using RFLP (for more detail, see paper). RFLP is highly reproducible, codominant, highly inherited [75], locus-specific, and highly heritable. Armstrong and Romero-Severson used it to determine the locations and effects of the introgressed A188 chromosomal segments. Five segments were retained through at least the fifth backcross generation. The hypothesis that one or more of these five regions contain genes controlling somatic embryogenesis in maize was tested using an F2 population of the cross A188 × Mo17. A set of five DNA markers (three of them linked) explained 82% of the observed phenotypic variance for the percentage of immature embryos forming the embryogenic callus. Four of the five markers were located in or near introgressed A188 chromosome segments were studied [76]. Bentolila et al. (1991) identified a tight linkage of an RFLP marker to the Htl gene of maize that confers resistance to the fungal pathogen Helminthosporium turcicum race 1. This was accomplished by using four pairs of near-isogenic lines (NILs; B73, A619, W153R, and CM105), each differing by the presence or the absence of the gene Htl [77]. Moreover, the mean phenotypic performances of F3 families were compared based on genotypic classification at each of the 70 RFLP marker loci. The genetic linkage map assembled from these markers was in good agreement with the previously published maps. In the combined analyses, genomic regions significantly affecting the tolerance to drought were found on chromosomes 1, 3, 5, 6, and 8. For yield, 50% of the phenotypic variance could be explained by five putative QTLs [78].

2.2 Analysis of Maize Diversity through Random Amplified Polymorphism DNA (RAPDs)

Random amplified polymorphism DNA (RAPDs) was the first PCR-based molecular marker to be employed in genetic variation analyses [79,80]. RAPD markers are generated through the random amplification of genomic DNA using short primers (decamers), separation of the obtained fragments on agarose gel in the presence of ethidium bromide, and, finally, visualization under ultraviolet light [80]. The use of short primers is necessary to increase the probability; although the sequences are random, they can find homologous sequences suitable for annealing [80]. DNA polymorphisms are subsequently produced by “rearrangements or deletions or between oligonucleotide primer binding sites in the genome” [80]. Moreover, earlier knowledge of the genome is not required in this approach; hence, it could be employed across the species using universal primers. RAPD has been extensively used due to its high efficiency, speed, and density for the genetic diversity of landraces and inbred lines in maize [63,81]. RAPD is used for the analysis of genetic distance; it has been found useful to assess the genetic diversity of 81 landraces and 2 improved varieties by southern Brazilian farmers [82]. Carvalho et al. (2004) studied 32 highly informative RAPD primers amplified 255 markers, of which 184 (72.2%) were polymorphic [59]. A comparative characterization of 17 flint maize landraces (Zea mays L.) was carried out using RAPD markers. Fourteen primers provided reliable and consistent polymorphic bands, amplifying 125 fragments (89%). Moreover, previously the genetic variation in 17 maize landraces was characterized based on dissimilarity matrix using the UPGMA based clustering approach[83]. Bruel et al. (2007) analyzed the genetic diversity between 16 corn lines. Twenty-two primers were used, resulting in the amplification of 265 fragments, of which 237 (84.44%) were polymorphic [84].

2.3 Analysis of Maize Diversity through Amplified Fragment Length Polymorphism (AFLPs)

To address the challenge of RAPD and RFLP, amplified fragment length polymorphism (AFLP) was introduced [85]. It is considered an intermediate between RFLPs and RAPDs methodologies as it combines the power of RFLP with the flexibility of PCR-based technology. This method is based on the combination of the two primary analysis techniques: digestion of DNA through restriction endonuclease enzymes and PCR Diversity [71]. The AFLP may produce 51 to 100 bp per assay, in primers pairs. This technique distinguishes the closely related individual of the species [86]. For instance, 96 tropical inbreds [57], 77 inbred lines [71], and 183 inbreds [87] were analyzed using AFLP. To improve the knowledge of the genetic diversity in tropical maize inbred lines, Laborda et al. (2005) fingerprinted 85 lines with 569 AFLP bands and 50 microsatellite loci. These markers revealed substantial variability among lines, with high rates of polymorphism [65]. The 21 inbred lines were fingerprinted, including parents and 210 F1 progeny were evaluated in the field. Joint data analysis mostly revealed a close association between GD and the F1 performance or mid-parent heterosis in the intergroup than in the intragroup crosses [88]. Several studies were investigated to map the QTLs of Fusarium moniliforme ear rot resistance; 230 F2 individuals, derived from a single cross between inbred maize lines R15 (resistant) and Ye478 (susceptible), were genotyped for genetic map construction. They used 63 combinations of AFLP primers to detect the polymorphisms between parents, R15 and Ye478 [89]. The various AFLP marker used for the diversity analysis in maize are mentioned in Table 1.

2.4 Analysis of Maize Diversity through Simple Sequence Repeats (SSRs)

Simple sequence repeats (SSR) are found in both prokaryotic and eukaryotic genomes [90,91]. These are known by several others names, such as short tandem repeat markers, microsatellite markers, and sequence-tagged microsatellite (STMS) markers. These consist of sequences of repetitions, comprising basic short motifs generally between two and six bp long. Polymorphisms associated with a specific locus are due to diversity variation in the length of the microsatellite, which in turn depends on the number of repetitions of the basic motif. Variations in the number of tandemly repeated units are largely attributed to strand slippage during DNA replication, where the repeats allow matching via excision or addition of repeats [92]. It is a hypervariable marker available in nature [93]. Microsatellites are differentiated based on inter individuals that have unique loci called polymorphism and could be analyzed by PCR. SSR or microsatellite is codominant, highly abundant, with an enormous extent of allelic diversity and ease of assessing SSR size variation due to locus specificity [94]. SSR markers are used for the analysis of genetic diversity and characterization of the germplasm, investigating the genomic diversity of maize landraces, inbred lines, and open pollination. SSR has been employed for characterizing 94 inbreds [21], 65 inbreds [22], 6 inbreds [23], 61 diverse array maize [24], and 54 inbreds [25]. Sharopova et al. (2002) developed 1,051 novel SSR markers for maize from microsatellite-enriched libraries and by identification of microsatellite-containing sequences in public and private databases. Three mapping populations were used to derive map positions for 978 such markers [95]. Stagnati et al. (2022) studied the genetic characterization in 455 individuals using 10 SSR markers and revealed 62 different alleles ranging from four for markers phi127, phi076, and phi084 to nine for marker p-bnlg176 [96]. Adu et al. (2019) assessed the diversity of 70 white maize populations for resistance/tolerance to drought and low soil nitrogen (low-N) using 31 SSR markers. A total of 288 alleles were detected among the germplasm used with a range of 4 to 17 alleles per locus and an average allele number of 9.60 alleles per locus. Polymorphic information content values for the SSR markers ranged from 0.32 to 0.85, with a mean value of 0.68 [97]. Andejelkovic et al. (2018) studied 22 SSRs for phenotypic characterization of 2,217 maize landraces. According to the collecting site and kernel type, 14 samples from the Faculty of Agricultural Sciences and Food, Republic of Macedonia, were selected to compare and identify possible duplicates through coupling with 16 MRIZP gene bank accessions from the same area and kernel characteristics. Phenotypic characterization was performed for 21 traits according to the International Board for Plant Genetic Resources descriptors for maize. The principal component analysis (PCA) identified five PCs with Eigenvalue > 1, explaining 80% of the total phenotypic variation [98]. SSR is a commonly used marker for genetic diversity in maize [99,100]. Recently, SSR markers have become commonly used in plant breeding programs due to their capability to differentiate desirable genotypes from undesirable ones [101].

2.5 Analysis of Maize Diversity through Single Nucleotide Polymorphism (SNPs)

Single nucleotide variation in the genome sequence of individuals of a population is known as single nucleotide polymorphism (SNPs). SNPs are produced due to the addition or deletion of single nucleotide base pairs [102]. SNPs vary from individual to individual among species and constitute the most suitable marker in the genome. SNPs are usually more prevalent in the non-coding regions of the genome. Within the coding regions, when an SNP is present, it can generate either non-synonymous mutations that result in an amino acid sequence change [102] or synonymous mutations that do not alter the amino acid sequence. Synonymous changes can, however, modify mRNA splicing, resulting in phenotypic differences [103]. These are widely dispersed throughout genomes with variable distribution among species. In maize, one SNP is found over 60 to 120 base pairs [104], whereas in humans, it is estimated that one SNP is found over 1,000 base pairs [105]. SNP marker is widely accepted by plant breeders because this is a highly rapid method and provides appropriate results; in addition, this is a biallelic and codominant marker [106]. Six inbred lines [49], 95 inbred lines [50], 63 inbred lines [40], and 89 double haploids [52] were analyzed using SNPs (for more detail, see review paper). Boakyewaa et al. (2019) assessed the genetic diversity of 94 early-maturing white and yellow tropical maize inbred lines using SNP markers. The larger number of SNP markers used in this study showed the population structure of the 94 inbred lines. Cluster analysis resolved the inbred lines into different clusters based on their pedigree, selection history, and endosperm color. However, three heterotic groups were revealed by population structure analysis; additional field evaluation could be more informative to confirm the heterotic groups identified [107]. Zhang et al. (2022) studied 30 main waxy maize inbred lines; genetic analysis of the tested waxy corn materials was performed using the high-quality SNP marker technology. A total of 15,111 SNPs were obtained from 30 test materials [108]. Osuman et al. (2022) evaluated 162 tropical maize inbred lines under combined heat and drought (CHD) and terminal drought (TD) conditions. The mixed linear model was employed for the genome-wide association study using 7,834 SNP markers and several phenotypic data, including days to 50% anthesis (AD) and silking (SD), husk cover (HUSKC), and grain yield (GY). In total, 66, 27, and 24 SNPs were associated with the traits evaluated under CHD, TD, and their combined effects, respectively. SNPs and candidate genes identified in the study will provide invaluable information for breeding climate-smart maize varieties under tropical conditions following the validation of SNP markers [109]. SNPs used for genetic diversity analysis in maize are mentioned in Table 1.

3. Application of Molecular Markers

The main aim of a plant breeder is to improve the exotic cultivar that is deficient for one or more characteristics through crossing from the new germplasm having new traits of interest [110]. In conventional breeding, the whole genome can be developed by crossing between traits of interest through recombination; however, conventional breeding takes more time, and it is laborious to select phenotypes for the trait of interest that could be misleading due to environmental effects [9]. To address these problems, conventional breeding is now being replaced with molecular breeding. Molecular breeding has been employed by several plant breeders and researchers. Several molecular markers have been identified to control disease resistance and agronomic characteristics in maize [9,110,111].

Other uses of molecular markers are developing backcrossing programs for the characterization of germplasms, disease diagnosis, and phylogenetic relationships to study evolutionary processes [9]. In addition, SSR and AFLP are reliable markers to estimate the substantial polymorphism; however, SSR is more automated than AFLP in the maize crop [112].

3.1 Genetic Diversity

For plant breeders, the characterization of germplasm is a critical step to identify the variations within the natural population and between lines for the conservation of biodiversity and the use of germplasm in the future. The genetic variation could be fully exploited using molecular characterization [113,114]. Genetic variation is detected using SSR markers in maize that could easily detect the phenotypic variations and desirable biological functions [114]. For example, 94 inbreds lines were investigated using 120 SSRs by Senior et al. [21]. Similarly, 65 inbreds lines were investigated using 60 SSRs by Enoki et al. [22]. Gethi et al. [23] investigated diversity in six inbreds lines using 44 SSRs. Moreover, 95 inbred lines were investigated using 1,536 SNPs by Hao et al. [50]. Sharma et al. (2018) detected 191 alleles showing a range of two to six alleles per marker and an average value of 3.82 alleles per locus. The PIC value showed a range of 0.050 (umc1069) to 0.817 (bnlg1823) with an average value of 0.585, indicating the efficiency of markers to study the level of polymorphism available in the maize inbred lines [115]. Sathua et al. (2018) analyzed the diversity using 40 SSR markers. Among the 40 SSR markers, only 20 were found informative (polymorphic) with a total of 70 alleles, providing a reference for determining the SSR allele number in genetic relationship analysis of maize inbred lines and other crop germplasms [116]. Adeyemo and Omidiji (2019) assayed the flanking markers of previously mapped quantitative trait loci linked with the oil and protein or oil/protein contents with 20 SSRs. All SSR markers were polymorphic with a mean PIC value of 0.75. Based on the SSR genotyping data, 183 alleles, ranging from 3 to 18 and averaging 9.15 were detected. A moderately high number of unique alleles was present in three farmers' varieties (EK04, EK06, and KW11) and a hybrid variety (LW18) [117]. Joshi et al. (2020) used five SSR markers to develop the DNA fingerprints and assess the diversity of 23 Nepalese maize landraces. Five locus-based DNA fingerprints have been used to distinguish the majority of landraces. At the landrace level, the highest gene diversity, heterozygosity, and PIC values were found in Seto Local and Seti Makai-3. Furthermore, 23 maize landraces formed four clusters, which were related to seed color [118]. Shinde et al. (2021) assessed the hybrid purity of maize hybrid Hyd.18227 × Hyd.10306 (Tall) and their parental line Hyd.18227 (Dwarf) and Hyd.10306 (Tall) using RAPD and SSR markers. The DNA was extracted from young leaves, and PCR was conducted using 24 RAPD and 18 SSR markers. Out of these, 15 RAPD markers and five SSR markers showed polymorphism between the maize parental lines, and the remaining markers produced a monomorphic banding pattern [119]. Kamra et al. (2021) assessed general (GCA) and specific (SCA) combining abilities for agronomic traits and resistance to LWD, identifying high-yielding hybrids with high resistance to LWD, determining the parental genetic distance (GD) using SSR markers, and investigating its relationship with hybrid performance and SCA effects. Earliness and agronomic traits were evaluated in two different locations [120]. For more information, see these papers.

3.2 Selection of Early Generation

Breeders could select the trait of interest in early generation based on visual heritability [121]; however, it provides biased results; to overcome this problem, selection should be performed using molecular markers, and simultaneous characteristics should be selected in early generation in maize [122]. Selection can be done using molecular markers is more effective for traits having a low heritability as compared to phenotypic selection [121]. Hence, breeders and researchers are required to develop an authentic strategy to select complex traits such as yield using a marker in early generations. Weldekidan et al. (2022) used a standardized protocol to recurrently select for the early flowering time at eight locations for two generations, resulting in location-specific lineages [123]. Dari et al. (2010) compared the weevil resistance of S1, S2, S3, and S4 inbred lines with that of their testcross hybrids, studied the gene action for resistance, and developed recommendations for weevil resistance breeding in maize. Weevil resistance was evaluated for lines and hybrids from two maize populations by infesting the F2 grain samples with weevils and incubating the samples in a controlled temperature and humidity laboratory. Useful genetic variation exists, and maize breeding programs can address weevil resistance with strategies that use both additive and non-additive gene actions [124]. Bernardo (1992) calculated the probabilities of retaining genetically superior lines during early testing and examined the selection intensities appropriate for different testing generations and levels of heritability. He found that larger proportions of lines need to be retained earlier than at later selfing generations to prevent excessive loss of genetically superior lines [125]. Eathington et al. (1997) worked on early generation testing and discarded lines with poor combining ability early in the inbreeding process. Molecular markers can be used to locate quantitative trait loci (QTL) and measure marker effects in early generations. For marker-assisted selection to be useful in improving the efficiency of early generation testing, marker effects estimated in early generations must agree with those in later generations. A total of 146 probe-enzyme combinations were used [126]. The selection for early generation could be done using single-seed descent and through double haploids [121].

3.3 Selection of Donor Parent in Backcrossing

The marker helps to select the donor parent of desirable interest from large genetic diversity datasets. In backcrossing, the donor parent is selected to have a lower genetic distance to reduce backcross generation [127]. Genetic distance analyses can help in selecting suitable donor parents of unknown or diverse pedigree or where phenotypic information is limited. The maize genotype HP467-15 was used as the donor for transferring the β-carotene gene, crtRB1, into UMI1200 and UMI1230. In the MABB scheme, one gene-specific marker (crtRB1 3 ′TE) and 214 SSR markers for foreground and background selection, respectively, were used [128]. Backcross selection is a widely used method for introgressing LWD resistance into elite agronomic genetic backgrounds. LWD-tolerant donor parent, CV138811, and susceptible recurrent parent, CV143587, were used to develop BC1F1 plants at the Monsanto breeding station. BC1F1 plants were screened for responses to LWD infection under artificial inoculation conditions. Forty-three BC1F1 plants significantly different from susceptible parents but similar to the resistant parent for LWD tolerance were selected. BC1F2 families derived from 43 selected BC1F1 plants differed significantly. Forty-nine percent of BC1F2 families and 40% of BC1F2 plants transgressed the resistant parent for LWD tolerance [129], a (proA) resource for humans. In this study, one common corn line with favorable lcyE alleles was used as the donor parental line, and four elite sweet corn lines were employed as recipient lines. The favorable lcyE allele was introgressed into four sweet corn lines by marker-assisted selection (MAS) [130]. The molecular markers for mutant opaque2 allele and modifier loci (endosperm/amino acid) have provided an opportunity to apply marker-assisted backcross breeding to enhance essential amino acids (a.a.), lysine (lys) and tryptophan (trp) in the maize endosperm. In the present study, SSR phi057 that lie within opaque2, SSRs flanking opaque2, modifier loci, and genic SSRs unlinked to opaque2 were used for molecular characterization in backcrosses between opaque2 donor, CML142, and the recurrent parents, BML2 and BML15 (parental lines of DHM119). The trp and lys content in converted inbreds was significantly higher than in normal lines [131]. The recessive opaque-2 (o2) mutant has a greater content of lysine and tryptophan in their endosperm proteins, and their bioavailability is better. Therefore, marker-assisted backcross breeding (MABB) was attempted to incorporate the o2 allele from the donor line VQL 1 into the genetic background of UMI 1200 to develop quality protein maize (QPM) lines. Foreground selection for the gene o2 was effected using a tightly linked molecular marker umc1066, in UMI 1200 VQL 1 backcross series. Further, background selection was performed together with stringent phenotypic selection for agronomic traits to accelerate the recurrent parent phenome recovery. Background analysis using 250 SSRs revealed up to 97% recurrent parent genome recovery [132]. DNA fingerprinting approach could use for the selection of potential parents diverse genetic resources for analytical crosses [133].

3.4 Recovery of the Recurrent Parent

Background selection helps to reduce 50% of the donor parent genome in each backcrossing and provides the maximum recurrent parent. MAS always provides the donor parent whose closeness is the same as the recurrent parent to avoid other genomes of the donor parent [134]. MAS reduces the time of backcross generation as compared to conventional breeding. BC1 lines derived through MAS found the proportion of recurrent parent genome not significantly different as compared to BC3 from conventional backcross. The selection of individuals through MAS reduces the cycle of backcrossing. This result was in agreement with the studies conducted by Visscher et al. (1996) and Frisch et al. (1999) [135,136]. In addition, Singh et al. (2021) studied the introgression of favorable alleles of crtRB1 and lcyE genes into opaque2 (o2)-based four inbreds, namely, QLM11, QLM12, QLM13, and QLM14 using marker-assisted backcross breeding [137]. Awata et al. (2021) used marker-assisted backcross (MABC) and doubled haploid (DH) methods to transfer genes for resistance to maize lethal necrosis (MLN). Two maize panels consisting of four BC3F2 and six DH populations, separately developed through marker-assisted selection from crosses between susceptible CIMMYT lines and MLN-resistant donor parent (KS23-6), were used. The study identified genotypes with reduced MLN infections in both populations; however, lower means for MLN severity and area under disease progress curve (AUDPC) values, and higher heritability estimates were obtained in the DH populations than in the BC3F2 populations. Additionally, the DH populations showed higher relative genetic gains for resistance to MLN compared with the BC3F2 populations [138]. Sagare et al. (2019) analyzed and identified a promising β-carotene donor to introgress into QPM inbreds employing molecular breeding. Maize inbred MGU23379 (6.31 µg/g of βcarotene) was used as the β-carotene donor to cross with recurrent parents (RPs), CB6-36 (CBML6) and CB7-28 (CBML7). In conversion program, F1, BC1F1, BC2F1, BC2F2, BC2F3, and BC2F4 materials were generated. In each generation, foreground selection was performed with crtRB1-3′TE and umc1066. The crtRB1-3′TE segregated as per the expectation [139]. Sumathi et al. (2020) illustrated the transfer of two QTLs for SDM on chromosomes 3 and 6 from UMI 936 (w) into an elite maize inbred line UMI79 through MABC. For foreground selection, plants carrying the heterozygote allele for QTLs for SDM were selected from F1 and three back cross (BC1-BC3) generations using SSR markers linked to the targeted QTL region of SDM. Consequently, foreground positive plants from the BC3F1 generation selfed to produce BC3F2, and plants carrying the favorable alleles for the QTLs for SDM were selected, followed by stringent phenotyping against SDM and advanced to BC3F3. Thus, two improved lines possessing QTLs for SDM were obtained. Background selection using 146 SSR markers distributed evenly across the maize genome revealed 92.45% and 89.68% recovery of recurrent parent genome (RPG) in two improved lines. In conclusion, the newly developed SDM resistant inbred lines are a potential source for improving SDM resistance in maize breeding programs [140]. Chandran et al. (2019) improved the lysine and tryptophan content by transferring the o2 gene from donor HKI163 to β-carotene-rich inbred lines, namely, UMI1200β+ and UMI1230β+. These improved lines can be used as genetic resources for maize improvement [141].

3.5 Mapping and Tagging of Genes

Numerous genes have been manipulated by the force of natural selection or the force of plant breeders to create novel genetic variations and select the desirable alleles for existing variations [142]. Several markers are available to trace the new allele of genes from the segregating population. Genome map in plants was first reported in maize [143], followed by rice [144] using RFLP markers. Davis et al. (1999) [145] constructed a 1,736-locus maize genome map containing 1,156 loci probed by cDNAs, 545 probed by random genomic clones, 16 by SSRs, 14 by isozymes, and 5 by anonymous clones [145]. Isolation and mapping of genome-wide resistance (R) gene analogs (RGAs) are of importance in identifying candidate(s) for a particular resistance gene/QTL. The study revealed the mapping of 228 genome-wide RGAs in maize. By developing RGA-tagged markers and subsequent genotyping, a population consisting of 294 recombinant inbred lines (RILs), 67 RGAs were genetically mapped on the maize genome. Moreover, in silico mapping was conducted to anchor 113 RGAs by comparing all 228 RGAs to those anchored EST and BAC/BAC-end sequences via tblastx search (E-value < 10¡20). All RGAs from different mapping efforts were integrated into the existing SSR linkage map. After accounting for redundancy, the resultant RGA linkage map was composed of 153 RGAs that were mapped onto 172 loci on the maize genome, and the mapped RGAs accounted for approximately three-quarters of the genome-wide RGAs in maize [146].

4. Conclusion

Over the last 10,000 years, humans have used the enormous genetic diversity of the maize genome as the raw material for domestication and subsequent crop improvement, a process that took thousands of years. Molecular markers represent a class of molecular tools that are particularly sensitive to new genome-based discoveries and technological advancements and are, therefore, subjected to continuous evolution. Most molecular marker techniques are employed to evaluate the genetic diversity. This review focused on the maize genetic diversity, and several molecular markers such as RFLP, AFLP, SSR, and SNP have been used to detect varying degrees of genetic diversity; SSRs and SNPs are the most prevalent. Due to the bright future of maize research, we must continue to conduct in-depth genetic diversity studies.

Author Contributions

All authors contribute equally.

Competing Interests

No competing interests.

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