The most reliable and effective approach to address the damage caused by GLS in maize is the identification of disease-resistant QTLs and the breeding of GLS-resistant varieties. In this study, eight tropical and subtropical inbred lines were used as female parents, and a temperate inbred line was used as the male parent to construct eight RIL subpopulations consisting of 1653 RILs, thereby developing a NAM population. The NAM population and individual RIL subpopulations were used to map QTLs that were linked to GLS resistance and identify functional genes. Two candidate genes associated with GLS resistance in maize were identified using a combined approach of QTL mapping and GWAS. Additionally, four co-localized genes were detected across the four environments in the GWAS analysis.
Previous studies have identified several QTLs associated with GLS resistance in various populations and environments; however, these QTLs were located in different physical positions. As the candidate genes identified in this study were located on chromosomes 4 and 9, we focused on summarizing the QTLs and genes that have previously been mapped to these two chromosomes by other researchers (Table 7). To date, various researchers have repeatedly identified five loci from different maize inbred lines: bin1.05-1.06, bin2.03-2.05, bin4.05-4.08, bin5.03-5.06, and bin7.02-7.03 (Du et al. 2020; Lennon et al. 2016; Mammadov et al. 2015). Our study identified two QTLs, qGLS4-1 and qGLS4-2, on chromosome 4 in different environments, which overlapped with the SNPs significantly associated with GLS resistance during GWAS, with the QTL qGLS4-2 spanning a physical distance of 134,003,583 − 147,691,355 bp. Comparative analysis revealed that the QTLs identified in this study were located in a hotspot region on chromosome 4 that overlapped with previously mapped intervals (Table 7). This suggests that the candidate region at this locus likely contains genes that confer resistance to GLS. However, QTLs identified previously spanned broad intervals ranging from 64.39-187.46Mb (Benson et al. 2015; Kibe et al. 2020), whereas the QTL identified in the present study spanned a narrow interval of 13.69Mb. Combined with GWAS analysis, SNPs overlapping the QTL interval were targeted, which were novel and have not been reported previously. We hypothesized that the two SNPs overlapping the QTL interval could be novel candidate loci for GLS resistance, which holds significant implications for further research on candidate genes regulating GLS resistance in maize. Additionally, SNP-5,043,412, identified through GWAS across the four environments on chromosome 9, did not overlap within the genomic regions identified in previous studies (Table 7), indicating that this SNP may be a novel locus controlling GLS resistance.
Table 7
Previous research progress in identifying QTLs linked to GLS-resistance and candidate genes on chromosomes 4 and 9
Population type | Chr | QTL/bin/gene | Marker/Physical position | R (%) | References |
NILS/NAM | 4 | qGLS4.05 | 9,759,854–178,889,832 | - | (Benson et al. 2015) |
RIL/F8:6 | 4 | Bin4.05 | PZA00445.22-PZA00057.2 | 6.7 | (Zwonitzer et al. 2010) |
21DH/BC3 | 4 | qGLS_Y4-1 | 0-7.8Mb | 6.7 | (Du et al. 2020) |
4 | qGLS_Y4-2 | 12.6-15.1Mb | 8.8 |
4 | qGLS_Y4-3 | 19.6-39.9Mb | 15.7 |
21DH/F3 | 4 | qGLS4-190 | 4,754,149–192,217,274 | 14.36 | (Benson et al. 2015) |
4 | qGLS4-157 | 93,244,319 − 157,631,182 | 6.26 |
4 | qGLS4-154 | S4-154,047,619 | 0.1 |
4 | qGLS4-163 | S4-163,681,762 | 15.7 |
inbred lines | 4 | GRMZMZG476902 | 185,934,762 | 8.53 | (Kuki et al. 2018) |
DRIL/BC3F4:5 | 9 | Bin9.03 | 28,413,009 | - | (Omondi et al. 2023) |
21DH/BC3 | 9 | qGLS_Y9-1 | 108.5-147.4Mb | 10.5 | (Du et al. 2020) |
F2:3 | 9 | JAGLS9a | Umc2338-bnlg1270 | - | (Qiu et al. 2021) |
21DH、F3 | 9 | Qgls9-143 | 143,037,428 − 143,894,887 | 4.19 | (Kibe et al. 2020) |
A critical step in the successful infection of hosts by conidial spores is the penetration of the plant cell wall. Enzymes play a central role in host-pathogen interactions by degrading plant cell wall polysaccharides and other carbohydrates. Additionally, pathogens utilize enzymes that degrade cellulose and pectin to break down plant polysaccharides, thereby obtaining nutrients and enhancing host infection (Ronnie et al. 2018; Shim and Dunkle 2003; Zerillo et al. 2013).
In the present study, we combined QTL mapping with GWAS to identify three candidate genes responsible for GLS resistance. SNP-138,153,206 identified through GWAS, explained 14.56% of the phenotypic variance in three environments (21BS, 22YS and BLUP) and was located 0.499kb downstream of the candidate gene Zm00001d051039. This gene encodes the Protein IN2-1 homolog B, which activates glutathione transferase activity and is regulated by protein glutathionylation in rice plants (Boorboori et al. 2021). This protein is as a homolog of glutathione S-transferase (GST). In addition to their roles in herbicide detoxification, stress signal transduction, and apoptosis regulation, GSTs and Protein IN2-1 homolog B also function as glutathione peroxidases, capable of scavenging reactive oxygen species (ROS) under various stress conditions (Dixon et al. 2002; Li et al. 2013). GSTs are thought to protect plants from a wide range of biotic and abiotic stresses by detoxifying reactive electrophilic compounds (Sappl et al. 2009). Wisser et al. found that the GST gene is associated with moderate resistance to SLB, GLS, and NLB diseases and is a member of a previously identified defense-related plant-specific clade (Wisser et al. 2011; Wisser et al. 2005). GSTs play crucial roles in plant xenobiotic detoxification system (Neuefeind et al. 1997; Pang et al. 2012). Furthermore, we identified a terminal inverted repeat (TIR) spanning a length of 0.318 kb, located 0.499 kb downstream of the candidate gene. SNP-138,153,206, which was significantly associated with GLS resistance, was located within the TIR. Transposons and TIRs are crucial components of the maize genome. They play key roles in the regulation of gene expression, structural variations in the genome, and evolutionary processes. Studies have shown that MuDR TIRs possess enhancer motifs that are active during the plant cell cycle, and specific pollen enhancers that are regulated in both somatic and germinal tissues (Raizada et al. 2001). Furthermore, TIR transposable elements may play significant roles in genome evolution, including creating allelic diversity, inducing structural variations, and regulating gene expression (Su et al. 2019). Therefore, we hypothesized that this TIR element might affect the expression of the candidate gene Zm00001d051039, thereby controlling maize resistance to GLS.
SNP-145,813,215 was identified in two environments during QTL mapping (21BS and 21DH), and in one environment during GWAS (21BS). This SNP is located 2.69 Kb downstream of the candidate gene Zm00001d051147 and explained 7.24% of the phenotypic variance during GWAS in the 21BS environment. Zm00001d051147 encodes the probable beta-1,4-xylosyltransferase GT43E. This enzyme is involved in the biosynthesis of xylan in the cell wall, and xylan metabolism plays an important role in plant disease resistance, as seen in resistance to southern corn leaf blight (Chen et al. 2023). Xylan is the primary hemicellulose found in both the primary and secondary cell walls of the nutritional tissues in rice. Studies have shown that lignin and xylan are the two main polymers in grass cell walls, that contribute to biomass resistance (Bureau and Wessler 1994; Lee et al. 2014). Xylan is crucial for cell wall strength and biomass resistance (Anders et al. 2023; Scheller and Ulvskov 2010). In Arabidopsis, there are four GT43 members, all of which have been demonstrated to participate in the biosynthesis of the xylan backbone. Previous genetic and biochemical analyses have indicated that these members form two functionally non-redundant groups, IRX9/IRX9 homologs and IRX14/IRX14 homologs, which synergistically work in the elongation of the xylan backbone (Lee et al. 2012; Wu et al. 2010). It has been hypothesized that xylosyltransferases enhance cell wall strength and biomass resistance by participating in xylan synthesis, thereby improving disease resistance.
During GWAS analysis, four candidate genes were identified across the three environments and BLUP values. Through candidate gene prediction and functional annotation, we found that only the protein regulated by the candidate gene, Zm00001d044845, located in close proximity to SNP-5,043,412, was associated with GLS resistance. Consequently, haplotype analysis of this SNP was performed. SNP-5,043,412 explained a total of 16.41% the phenotypic variation and was located 8.788 kb downstream of the candidate gene Zm00001d044845 on chromosome 9. This gene encodes the U-box domain-containing protein 4 (PUB4). PUB4 is a unique E3 ubiquitin ligase that is involved in the regulation of plant immunity, growth, and development (Trenner et al. 2022; Wang et al. 2022). PUB4 positively influences pattern-triggered immunity (PTI) by modulating homeostasis of the central immune kinase BIK1. BIK1, a convergence substrate for multiple receptors, acts as a rate-limiting factor in Arabidopsis immune signaling. Detailed analysis showed that PUB4 facilitates the degradation of inactive BIK1 but supports the accumulation of activated BIK1, ultimately enhancing its signaling capability. These findings reveal the role of PUB4 in immune modulation (Yu et al. 2022). Desaki et al. (2019) also reported that the E3 ubiquitin ligase, PUB4, which interacts with CERK1, positively regulates immune modulation.
The tropical and subtropical maize germplasms exhibit high genetic variation and diversity. In the present study, hybridization of tropical and subtropical maize germplasms with temperate germplasms, followed by multiple generations of self-pollination, contributed to the enhancement of genetic variability. Furthermore, considering that GLS in maize occurs naturally and is susceptible to high temperature and humidity (Paul and Munkvold 2005), conducting trials across diverse climatic and altitudinal environments would introduce broader environmental variability. This could potentially account for the discrepancies between the findings of this study and those of previous studies.
Rapid and high-throughput sequencing technologies, such as GBS, can generate a large number of SNP markers, thereby eliminating ascertainment bias. This technique has been used in several studies. In the present study, a significant number of SNPs were identified through GBS. GWAS was conducted using a large population of RILs derived from tropical, subtropical, and temperate germplasms, and a higher number of SNPs. Q-Q plots indicated that the population structure and kinship matrix were well-fitted to the model used during GWAS. This study demonstrated high QTL detection efficiency combined with high mapping resolution during GWAS. This approach was found to be effective as it avoids the time and cost required for fine mapping and facilitates robust marker-assisted selection. Additionally, using a larger population of advanced-generation subpopulations with diverse genetic backgrounds ensured a higher mapping resolution, further benefiting the exploration and utilization of maize genetic resources.
Our research group, led by Prof. Xingming Fan from the Yunnan Academy of Agricultural Sciences, Kunming, China, is focused on the development of new disease-resistant cultivars and hybrids through molecular breeding. Cultivars with superior resistance and yield, such as Yunrui 62 and Dedan 5, have been developed using a GLS-resistant tropical maize inbred line TML139. Additionally, employing YML32 led to the development of the GLS-resistant hybrid maize Yunrui 88, which was selected for two consecutive years as a leading variety by the Ministry of Agriculture, China.