Molecular fingerprinting of highly resistant maize lines to turcicum leaf blight

Abstract

The present study generates information related to the molecular divergence between turcicum leaf blight (TLB)-resistant and -susceptible lines. During molecular diversity studies, a total of 212 alleles were detected at 75 marker loci and ranged from two to five with an average of 2.83 alleles per locus. A direct correlation for the number of alleles and polymorphism information content (PIC) values was ascertained. For instance, marker phi123 produced high number of alleles (5) with PIC values of 0.77. Using the DARwin 6.0 programme, the UPGMA dendrogram grouped 40 maize inbreds into two distinct clusters, cluster-I (36 inbreds) and cluster-II (4 inbreds). Cluster-I contained two subclusters; the first subcluster contained 28 inbreds and the second subcluster contained eight inbreds whereas cluster-II contained four inbreds. This major cluster-II was further classified into two subclusters which contained two inbreds each. Most of the inbred lines except V-25 from cluster-II were highly resistant to TLB disease. These inbred lines can be used in crossing programmes to develop TLB-resistant hybrids by using divergent parents. In this study, allelic diversity and PIC values indicated a good efficiency of markers for studying the polymorphism level available in studied inbred lines. High level of diversity among the inbreds detected with simple sequence repeat markers indicated their suitability for the further breeding programme.

Introduction

Turcicum leaf blight (TLB), a significant foliar disease caused by Exserohilum turcicum (Pass.), can significantly reduce the yield of maize (Zea mays L.), the third-most important grain crop in the world (Leonard and Suggs, 1974; Jakhar et al., 2022). Grain yield can be reduced up to 80% when TLB becomes severe (Tefferi et al., 1996). Long, elliptical, brown or greyish green leaf lesions that begin on the lower leaves and eventually spread throughout the foliage are the characteristic features of the disease. Blighted leaves die too soon if the disease is not treated in early stages (Jakhar et al., 2017; Keerthana et al., 2023). Therefore, planting resistant cultivars is a widely accepted strategy that can reduce the rate at which diseases emerge (Keerthana et al., 2023). Disease resistance is classified as either qualitative or quantitative. Qualitative disease resistance is exclusive to a certain race, but quantitative or polygenic disease resistance is typically non-specific to a particular race and is more common in the Indian subcontinent (St. Clair, 2010). The initial study on E. turcicum in several Indian races was carried out by Payak and Sharma (1985). Gowda et al. (1993) found the four maize differentials, A-503HtN, H-4460Ht, H-4460Ht2 and H-4460Ht3, that include the numerous Ht resistance genes (Ht for Helminthosporium turcicum). A longer incubation period and fewer, usually smaller disease lesions are characteristics of quantitative TLB resistance, which is durable (Brewster et al., 1992; Smith and Kinsey, 1993; Abebe et al., 2008; Gulzar et al., 2018). Jakhar et al. (2021) screened 40 maize inbreds for the TLB resistance in Varanasi and Nagenahalli under artificially inoculated field conditions and observed that 10 inbreds viz., HKI-586, HUZM-53, CM-145, V-336, V-338, HKI-PC-8, HUZM-47, CM-104, CM-105 and CML-192 were resistant for the TLB disease. Similarly, Alemayehu et al. (2018) also evaluated the disease reaction of maize lines against common leaf rust and TLB under field conditions with artificial inoculation. The development of resistance against TLB disease will have a significant effect on the maize breeding programmes.

The presence of distinct genetic groups among maize inbreds is characterized to increase gene diversity that is helpful in optimizing hybrid vigour. Using molecular markers to create diversity among maize inbred lines is a valuable tool (Singh and Srivastava, 2017). Because it is highly polymorphic, repeatable and co-dominant in nature, the microsatellite marker is determined to be the most appropriate molecular marker among the many classes for screening TLB resistance (De Loose and Gheysen, 1995; Singh and Srivastava, 2017; Keerthana et al., 2023). The microsatellite markers are useful in characterizing maize inbreds and in establishing distinct clusters based on genetic diversity and also useful in maize breeding programmes (Nikolic et al., 2015). Likewise, based on UPGMA clustering method, the inbred lines were categorized into various clusters and cluster A was solitary, and the inbred line VL171488-2 exhibited a resistant reaction against leaf blight (Keerthana et al., 2023). The simple sequence repeat (SSR) markers will allow detection of polymorphisms at the DNA level which will make it easier to distinguish among inbreds. Keerthana et al. (2023) reported 26 SSR markers for the assessment of molecular diversity in maize inbred lines for resistance to TLB. Additionally, microsatellite markers have been used by many earlier researchers to analyse the quantitative traits, i.e. TLB resistance and to identify the quantitative trait loci (QTLs) for TLB resistance in maize (Jakhar et al., 2022, 2024). QTLs identification helps in marker-assisted selection process for improving genetic traits in crop plants (Singh and Srivastava, 2017). SSR marker system could be used to evaluate TLB-resistant lines because they have a distinct molecular fingerprint compared to susceptible lines. Therefore, the present study was planned to study molecular diversity to identify polymorphic SSR markers for TLB resistance.

Materials and methods

Plant materials and layout

A set of 40 inbred lines including checks (V-336 and CM-145 as resistant check, and CM-212 as susceptible check) were obtained from DMR, New Delhi; VPKAS, Almora and Maize programme, BHU, Varanasi subjected to molecular divergence in maize (Table 1). A study on molecular characterization was carried out in Kharif 2015 at the Agricultural Research Farm, Institute of Agricultural Sciences, BHU, Varanasi (located at 25.18°N latitude, 83.03°E longitude and 123.23 m above sea level) using randomized block design with two replications. Each genotype consists of two rows spaced 70 cm apart and 25 cm between plants. Adopting recommended agronomic practices helped to produce a good crop (Mallikarjuna et al., 2018). Additionally, at the same time, an investigation was carried out in 2015 to examine TLB reactions with a pure culture of E. turcicum in maize under artificial inoculation conditions at two different locations: Nagenahalli, Karnataka, and Varanasi, Uttar Pradesh (Jakhar et al., 2021).

Table 1. List of 40 maize inbreds used in this study and their pedigree/source germplasm details, major characteristics along with TLB disease reaction

HR, highly resistant; R, resistant; PR, partial resistant; PS, partial susceptible; S, susceptible; HS, highly susceptible.

DNA extraction and quantification

Total genomic DNA was isolated from 100 mg (21–24 days old) healthy leaf samples collected from individual plants of each inbred lines and stored in a deep freezer at −80°C. The DNA extraction was carried out by using the CTAB procedure described by Saghai-Maroof et al. (1984).

SSR marker assay

In the present study, a set of 75 SSR markers (Table 2) were evaluated for 40 maize inbred lines. These SSR markers were received from Applied Biotechnology Centre, CIMMYT, Mexico and the Asian Maize Biotechnology Network (AMBIONET). The primer details for the selected microsatellite markers were retrieved from the maizeGDB (Maize Genetics and Genomics Database) and are publicly accessible (https://www.maizegdb.org/).

Table 2. List of microsatellite markers used for molecular divergence among TLB-resistant and -susceptible lines of maize

SSR fragment analysis

The polymerase chain reaction (PCR) amplicons of SSR markers were electrophoretically fractionated on a 2.5% agarose gel that was stained with ethidium bromide in 1x TAE buffer. The PCR amplicons were visualized under UV light and photographed using Alpha imager gel documentation system. The 100 bp DNA ladder was used as a molecular weight marker for the analysis of SSR. The distinct PCR amplified products were scored as ‘1’ for the presence and ‘0’ for the absence of DNA bands for each SSR marker genotype combination (Anderson et al., 1993).

Data analysis

The informativeness of SSR markers in terms of polymorphism was determined by calculating polymorphic information content (PIC) for each SSR marker loci according to the formula (Anderson et al., 1993):

$${\rm PI}{\rm C}_i = 1-\sum {\,p_{ij}^2 } $$

where p_ij is the frequency of the jth microsatellite allele for locus i.

The DNA data of microsatellite primers for maize inbred lines were clustered by using the UPGMA with the module of DARwin 6.0 software. The principal coordinate analysis (PCoA) was estimated to depict the diverse origin of the genotypes by using DARwin 6.0 software (Perrier et al., 2003).

Results

Allelic diversity and PIC value

A survey of the molecular profiles generated by the evaluation of amplified products clearly indicated that altogether 212 alleles were detected with an average of 2.83 alleles per markers. Allelic diversity was observed with the number of alleles ranged from two to five. In this study, a direct correlation for the number of alleles and polymorphism information content (PIC) values was observed. For instance, marker phi123 produced high number of alleles (5) with PIC values of 0.77. Similarly other markers such as bnlg1812, umc1097, umc1027, dupssr1, umc1042, bnlg1136, bnlg1043, umc1051, bnlg1885, nc005, phi112, bnlg1138, bnlg1331 and bnlg1396 which also produced higher number of alleles (4) also exhibited high PIC values viz., 0.78, 0.80, 0.72, 0.73, 0.73, 0.74, 0.74, 0.73, 0.74, 0.75, 0.74, 0.75, 0.75 and 0.75, respectively (Table 3 and Fig. 1). Furthermore, SSR loci with tetra-nucleotide sequence motifs detected a greater number of alleles than the repeated loci with di-nucleotide, tri-nucleotide and complex sequence motifs.

Table 3. Allelic distributions and PIC values of 75 microsatellite markers among 40 TLB-resistant and -susceptible lines

Figure 1. Radar chart for allelic distributions and PIC values of 75 microsatellite markers.

Genetic relationship among diverse genotypes

The DARwin 6.0 software was used to prepare an UPGMA dendrogram. The genetic distance was used to prepare the UPGMA dendrogram to group 40 maize inbred lines into two major clusters (cluster-I and cluster-II). Cluster-I contained two subclusters, the first subcluster contained 28 genotypes and the second contained eight genotypes whereas cluster-II contained four inbreds. Most of the inbreds except V-25 from cluster-II were highly resistant to TLB disease. This major cluster-II was further classified into two subclusters which contained two genotypes each (Fig. 2).

Figure 2. Dendrogram indicating genetic relationship among 40 maize inbred lines generated by using UPGMA method.

The PCoA revealed that the 40 maize inbred lines were dispersed into four quadrangles and signifying complex genetic relationship among themselves (Fig. 3). The results of the PCoA supported the UPGMA dendrogram's clustering pattern and nearly coincided with the findings of the cluster analysis.

Figure 3. Principal coordinate analysis (PCoA) among 40 maize inbreds using 75 SSR markers.

Discussion

The UPGMA dendrogram grouped 40 maize inbreds into two major clusters (cluster-I and cluster-II). Cluster-I contained two subclusters, the first subcluster contained 28 genotypes and the second contained eight genotypes whereas cluster II contained 4 inbreds. This major cluster II was further classified into two subclusters which contained two genotypes each. Therefore, TLB-resistant maize inbreds were unambiguously differentiated from susceptible and partially resistant maize inbred lines.

The 75 microsatellite marker loci differed in their ability to determine the variability among 40 TLB-resistant and -susceptible lines of maize based on their genetic polymorphism. The value of PIC of a marker reflects primer specific gene diversity, and frequency among the inbreds. The higher value of PIC of a SSR marker indicated a higher number of alleles among inbreds (Kumari et al., 2018). A sum total of 212 alleles were found at 75 SSR loci with a mean of 2.83 alleles per SSR locus. The number of alleles ranged from two to five with an average of 2.83 alleles per markers. The average number of alleles in the present study is comparable with earlier genetic diversity analysis (Jaya Kumar, 2010), who reported 2–8 alleles per marker. Similar studies have also been conducted in maize (Yuan et al., 2000; Prasanna and Hoisington, 2003; Choukan et al., 2006).

In this study, a positive correlation for the number of alleles and PIC values was found. For instance, marker phi123 produced high number of alleles (5) with PIC values of 0.77. Furthermore, SSR loci with tetra-nucleotide sequence motifs found a maximum number of alleles than the repeated loci with di-nucleotide, tri-nucleotide and complex sequence motifs in the present investigation. Generally, the di-nucleotide repeat motifs were found to be more polymorphic than those with tri-nucleotide, tetra-nucleotide and complex repeat motifs (Lapitan et al., 2007; Kumar et al., 2018; Kumari et al., 2018). The importance of SSR markers for the assessment of genetic diversity has been reported by earlier workers (Li et al., 2002; Xia et al., 2004; Yu et al., 2007; Reid et al., 2011; Haasbroek et al., 2014) by using maize genotypes.

In the present investigation, 75 SSR markers revealed sufficiently high sensitivity for detecting DNA polymorphism among the 40 maize inbreds. The dendrogram revealed the genotypic relationship among each other to explore their utility for further studies.

The PCoA showed that the distributions of 40 maize inbreds in the four quadrangles were highly dispersed, signifying complex genetic relationship among themselves. In the present study, the results of PCoA also illustrated the diverse nature of the maize inbreds and agreed well with their cluster analysis pattern. The diverse nature of the maize inbreds has already been proven to be a good source for the development of superior heterotic hybrids by Solomon et al. (2012), Babic et al. (2014) and Mehta et al. (2017). Further investigations are required to evaluate whether the discrimination between resistant and susceptible genotypes is consistent for other isolates of E. turcicum and during natural infection in different environmental conditions in multiple years.

Conclusions

In the present investigation, 75 microsatellite markers were used for the assessment of molecular divergence among 40 TLB-resistant and -susceptible lines of maize. Among these SSR markers, Phi123 produced a large number of alleles (5) with PIC values of 0.77. Similarly, other markers that produced a greater number of alleles, such as bnlg1812, umc1097, umc1027, dupssr1, umc1042, bnlg1136, bnlg1043, umc1051, bnlg1885, nc005, phi112, bnlg1138, bnlg1331 and bnlg1396, also showed a high PIC value. Furthermore, these markers observed a significant amount of variation in the resistant genotypes indicating their usefulness. In this study, most of the inbred lines from cluster-II were highly resistant to TLB disease. These TLB-resistant lines can be used as the divergent parents to develop TLB-resistant hybrids. Allelic diversity and PIC values in this investigation showed that the markers used were effective in determining the polymorphism level found in the studied inbred lines. Furthermore, the notable level of divergence detected by SSR markers can be used in crossing programmes to develop TLB-resistant hybrids. The findings of this study can also be used to design efficient breeding programmes for resistance to TLB.