1. Introduction
Maize is the world’s leading cereal in terms of production, with 1093 million metric tons produced on 186 million hectares globally. Maize is grown in both temperate and tropical areas of the world and is largely (around 80%) produced under rainy conditions in sub-Saharan Africa, South and Southeast Asia, and Latin America. It is particularly susceptible to abiotic and biotic stress. Eight major countries growing maize (China, India, Indonesia, Nepal, Pakistan, the Philippines, Thailand, and Vietnam) produce 98% of Asia’s and 28% of the world’s maize yield. Heavy economic and yield losses have been recorded due to infection by downy mildew (DM) agents in the Philippines, Taiwan, Indonesia, Thailand, India, Japan, Australia, Venezuela, North America, Europe, West Africa, and other parts of the world [
1,
2,
3,
4,
5,
6].
DM is caused by obligate pathogens that cannot be cultured in the laboratory, and its sporulation prefers high relative humidity, a night temperature of 21–23 °C, and light drizzle with cool weather. It is spread by oospores that survive in the soil [
7] and can be spread through infected seeds or from plant-to-plant by airborne conidia. Because of the systemic nature of DM, susceptible lines usually die when infected in the seedling emergence stage, and when plants are infected during later growth stages, they cannot develop the maize ear despite having survived. At least six pathogens that cause DM infection of maize in Asia have been reported, including sorghum DM (
P. sorghi (Weston & Uppal)), Philippine DM (
P. philippinensis (Weston) Shaw), Java DM (
P. maydis (Raciborski)), sugarcane DM (
P. sacchari (Miyabe) Shirai and Hara), brown stripe DM (
Sclerophthora rayssiae var.
zeae), crazy top DM (
S. macrospora), and Rajasthan DM (
P. heteropogoni) [
2,
6,
8,
9,
10,
11,
12,
13,
14,
15]. DM is widespread in tropical regions, although its origin is conjectural, and because of the diversity of the DM pathogens and their systemic nature, the development of resistant varieties is needed. Moreover, a renewed emphasis on cost-effectiveness and environmental safety that has brought about the application of DM management by the development of resistant varieties. According to studies on the interaction of maize and the pathogens, resistance to DM is polygenically controlled [
7,
13,
16,
17,
18,
19,
20,
21,
22,
23].
Quantitative trait locus (QTL) mapping enables the detection, localization, and characterization of genetic factors contributing to polygenically inherited variation [
24]. In QTL studies, the use of recombinant inbred lines (RILs) has more advantages than F
2 or backcross populations [
25,
26,
27]. Furthermore, RILs have been used to identify QTLs for the European corn borer [
28], thermotolerance [
29], and grain yield [
30] in maize.
Several groups have performed QTL mapping using diverse mapping populations. George et al. [
2] reported six QTLs on five chromosomes (1, 2, 6, 7, and 10) in RILs from the cross Ki3 (resistant) × CML139 (susceptible) of advanced inbred lines from the International Maize and Wheat Improvement Center (CIMMYT) in Indonesia, the Philippines, and Thailand. A QTL on chromosome 6 at bin 6.05 was found to majorly affect resistance to five DM pathogens (
P. sorghi, P. philippinensis, P. maydis, S. rayssiae var.
zeae, and
P. heteropogoni). Agrama et al. [
31] reported three QTLs on chromosomes 1 and 9 utilizing RILs derived from a cross between G62 (resistant) and G58 (susceptible) Egyptian inbreds. Two QTLs on chromosome 1 had a minor effect and one on chromosome 9 had a major effect. Sabry et al. [
32] reported three QTLs on chromosomes 2, 3, and 9 utilizing F
3 in Egypt, Thailand, and southern Texas. One QTL on chromosome 2 had a major effect and the two on chromosomes 3 and 9 had minor effects. Other studies have reported QTLs for
P. sorghi (sorghum DM) resistance on chromosomes 2, 3, 4, 5, 6, and 9 [
21,
33,
34].
Considering the complexity of quantitative traits, these QTLs can be used for introgression by marker-assisted selection with further validation [
33]. It is difficult to estimate disease reaction accurately because of the factors influencing DM, such as plant maturity and the amount of pathogen inoculum. If there are differences in the pathogen populations or environment by genotype interactions in different locations, the analysis of simple and accurately scored molecular markers for the resistance genes of DM could greatly benefit future efforts to prevent loss to disease [
32]. In addition, the evaluation of several DM strains using a mapping population could contribute to the accurate assessment of genetic contributions to resistance.
Genome-wide comparative transcriptome analysis has been performed by using an RNA-seq method in cabbage [
35], cucumber [
36], grapevine [
37], and pearl millet [
38]. DM resistance has been identified using the mutants at DM genes in lettuce [
39]. Interaction between genes and pathways related to resistance against powdery mildew (PM) in melon has been profiled through comparative transcriptome analysis [
40]. In maize, most studies on DM resistance have been performed using QTL analysis. In addition, there is a lack of information on the candidate genes and pathways for DM resistance in maize.
The main objective of this study is to validate candidate genes for P. sorghi, P. maydis, and S. macrospora resistance obtained from the QTL information of DM generated by using 192 F7 families derived from the cross B73 × Ki11. Our approach to the location of the QTLs for resistance to P. sorghi, P. maydis, and S. macrospora in maize is based on restriction fragment length polymorphism (RFLP) and simple sequence repeat (SSR) markers. We obtained candidate genes for P. sorghi, P. maydis, and S. macrospora resistance near the flanked markers of the QTL positions. The candidate genes were validated via quantitative real-time polymerase chain reaction (qRT-PCR) using resistant (CML228, Ki3, and Ki11) and susceptible (B73 and CML270) genotypes and identified by Pfam analysis.
4. Discussion
DM, caused by
Peronosclerospora species in maize, causes severe yield loss despite the use of chemical pesticides and has spread in many tropical and subtropical regions throughout the world. The lack of suitable studies for gene diversity in DM has been a major constraint in tropical Asia, especially in the maize-growing environments of South and Southeast Asia [
61]. The results from a great many studies on
P. sorghi (sorghum DM) resistance have been reported because it is widely distributed throughout Asia, Africa, and America, where it is easier to perform experiments than in other regions. However, we need to evaluate various DM species because the fungus can easily spread to other regions through the movement of spores in the air.
We screened resistance for
P. sorghi (sorghum DM)
, P. maydis (Java DM)
, and
S. macrospora (crazy top DM) using 192 F
7 families derived from B73 (susceptible) × Ki11 (resistant) in Phnom Penh, Cambodia. The distribution of the F
7 families was skewed toward the susceptible lines. According to previous studies, it is not uncommon that phenotype values of mapping populations do not follow a normal distribution [
2,
21,
30]. The phenotype data for the DM of the F
7 families leaned more toward susceptible because of the response to the three DM pathogens. We used 691 SSR and 36 RFLP markers from MaizeGDB (B73 RefGen_v2) for parental polymorphism. We performed polymorphism analysis by electrophoresis using 3% agarose gel with 1× TAE buffer at 100 V for 1 h. It is necessary that a difference of greater than 20 bp between PCR products could be detected by using 3% agarose gel and loading for 1 h. Additionally, we analyzed flanked markers in the QTL regions by using QiaXcel advanced system (Qiagen, Hilden, Germany). The constructed linkage map covered around 2042.51 cM at average intervals of 9.12 cM between markers for 228 SSR and six RFLP markers on 10 chromosomes. Around one-third of the markers showed to be polymorphic; this result was considered an average ratio when compared to references [
21,
32,
33,
34,
62]. These markers were distributed over 79 bins among around 120 bin locations. Approximately 85.04% of the markers were within 20 cM of the nearest interval (
Table S5). In QTL analysis, it is likely that RILs (F
7 families (B73 × Ki11)) made a significant contribution because the use of RILs is more powerful than F
2 or backcross populations in QTL analysis [
25,
26,
27]. However, in this study, phenotype data for
P. sorghi,
P. maydis, and
S. macrospora resistance showed recessive trait. In analysis of recessive traits, backcross inbred lines (BILs) derived from resistant genotype have more power to detect recessive QTLs because they have an advantage in segregation ratio compared to F
2 or RILs [
63].
The seven QTLs for
P. sorghi,
P. maydis, and
S. macrospora resistance were identified on 4 of 10 chromosomes (
Table 3). A major QTL was identified in bin 2.01 (
qDM1) on chromosome 2, while the other QTLs were detected in bins
qDM2 (2.02),
qDM3 (3.04),
qDM4 (3.05),
qDM5 (6.05/6.06),
qDM6 (9.05), and
qDM7 (9.07). All of the DM-resistant alleles were obtained from Ki11. According to previous studies, the QTLs for DM resistance have been detected in chromosomes 2, 3, 6, and 9, and several flanked markers of QTL regions have been reported. We considered that these seven QTLs affected
P. sorghi (sorghum DM),
P. maydis (Java DM), and
S. macrospora (crazy top DM) from Cambodia. The QTL regions found in the present study were similar to those in previous studies for
P. sorghi (sorghum DM) and
P. heteropogoni (Rajasthan DM) resistance [
21,
32,
33,
34,
49] (
Table S7).
qDM1 and
qDM2 shared the same flanked markers (umc1165 and umc2363 in bins 2.01 and 2.02, respectively) [
34].
qDM3 had flanked marker umc1030 in bin 3.04 [
62].
qDM4 and
qDM5 shared the same flanked markers (bnlg420 and umc1859 in bins 3.05 and 6.05/6.06, respectively) [
21]. In addition,
qDM6 and
qDM7 shared the same flanked markers (umc2343 and dupssr29 in bins 9.05 and 9.07, respectively) [
33]. The bin locations (3.04 and 3.05, respectively) of
qDM3 and
qDM4 matched with other reports on QTLs [
21,
32,
33,
49]. The other QTLs were identified from five different DM strains (
P. sorghi and
P. heteropogoni from India,
P. zeae from Thailand,
P. philippinensis from the Philippines, and
P. maydis from Indonesia) and sorghum DM on bin 6.05 using RILs (derived from Ki3) and backcross populations [
2,
21]. Ki3 and Ki11 were developed as DM-resistant lines derived from the Suwan1 strain from Thailand. These results suggest that it should be possible to detect candidate genes for
P. sorghi,
P. maydis, and
S. macrospora resistance near these bin positions. Although the QTL analysis was performed using different mapping populations, the results of this study are well matched with previously reported ones.
We analyzed 19 DM-related genes from
Arabidopsis thaliana,
Oryza sativa, and
Zea mays (
Table 4):
EDM2,
SGT1B,
LOC100191339,
HSK,
DMR6,
IDC1, and
LOC103642860, among others. Among the 19 genes, five were upregulated in the DM-resistant genotypes, two of which (
LOC103632498 and
LOC103647182) are located on chromosomes 2 and 7 of maize, respectively.
LOC100191339 was located on nearby
qDM4 and was highly upregulated in DM-infected CML270 (susceptible). Two genes (
LOC107275878 and
LOC4345309) and
HSK, originating from
Arabidopsis thaliana and
Oryza sativa, were significantly upregulated in the DM-infected DM-resistant genotypes. Hence, we considered that these genes are conserved in monocotyledon and dicotyledon plants [
64,
65].
We obtained 62 candidate genes for
P. sorghi,
P. maydis, and
S. macrospora resistance near the flanked markers in the QTL region; these genes were validated by comparing their relative expression levels in the control and DM-infected groups. The physical locations of candidate genes were continually updated from B73 RefGen_v1 to B73 RefGen_v4, but updating the genetic information of the genomic markers is slower than the transcripts. Hence, we used B73 RefGen_v2 to set the physical locations of the genomic markers and candidate genes. The annotations of 45 genes were analyzed to predict their functions using the Pfam database. The annotations and functions of these genes were identified as being related to DM resistance (
Table 6 and
Table S8). There are various factors involved in DM resistance, such as POX (peroxidase), MYB (transcriptional activator Myb), GSO1 (LRR receptor-like serine/threonine protein kinases (STKs), (LRR-STKs)), plant RLKs, polygalacturonase inhibitor protein (PGIP), polyphenol oxidase (PPO), NAC, WRKY transcription factors, and pathogenesis-related (PR) protein [
66,
67,
68,
69,
70,
71,
72].
Three genes (
AC210003.2_FG004,
AC191071.3_FG001, and
GRMZM2G039345) were annotated as POX, FMO, and RuBisCO (ribulose-1,5-bisphosphate carboxylase/oxygenase), respectively. The activities of POX and PPO, along with b-1,3-glucanase, are associated with DM resistance in sunflowers [
73]. Plants can implement DM post-infection mechanisms such as an increase in localized callose deposition to fortify plant cell walls [
74,
75], reactive oxygen species (ROS), peroxidase activity, and hypersensitive response activation [
74,
76]. When a resistant grapevine is infected with DM, it produces high concentrations of resveratrol that can be oxidized by induced peroxidase [
77]. In broccoli, BoAPX (ascorbate peroxidase) genes contribute enhanced both DM and heat tolerance, and play important roles in cellular defense against ROS-mediate oxidative damage [
68]. In previous studies, high POX activity has been associated with resistance to PM [
78] in lettuce [
79] and melon [
80] and to
Verticillium dahlia in tomatoes [
81]. PM is very similar to DM in that both are caused by fungi and are widespread under humid and low temperature conditions; the disease symptoms are also similar. FMO1 positively regulates the enhanced disease susceptibility1 (EDS1) pathway in
Arabidopsis thaliana. The EDS1 pathway controls defense activation and programmed cell death against pathogens [
82]. In addition, a defect in FMO1 partially disables toll interleukin 1 receptor nucleotide binding sites leucine-rich repeat (TIR-NB-LRR) resistance and basal defense. In
Arabidopsis thaliana, RPP4, which has been identified as a TIR-NB-LRR protein coupled with its dependence on signaling components in leaves, confers resistance to DM [
83]. RPP4-mediated resistance is regulated by interaction between EDS1 and NDR1 signaling in cotyledons.
Two genes (
GRMZM2G342564 and
GRMZM2G040095) were identified as lipoxygenase (LOX)-producing. LOX is known to play a role in disease resistance for many host pathosystems. In earlier reports, LOX activity was found to increase in resistant plants and to decrease in susceptible plants. Also, LOX was reported to affect DM and PM resistance of pearl millet and wheat, respectively [
84,
85,
86,
87,
88].
GRMZM2G028643,
GRMZM2G128315, and
GRMZM2G330907 (identified as LRR) and
GRMZM2G363066 (identified as nonspecific STK) were associated with defense reactions against pathogens. PR protein are encoded by disease resistance (R) genes, responding to pathogenic microorganisms and signaling cascades that activate defense reactions [
89,
90]. The largest family of PR proteins is defined by the presence of 12 to 21 LRRs (it has been speculated that LRRs bind pathogen-derived ligands). A glutamate-to-lysine substitution in LRR partially compromises the function of R genes against DM [
91]. Several kinases (protein kinases, wall-associated kinases, calcium-dependent protein kinases, STKs, LRR-STKs, and mitogen-activated protein kinases (MAPKs)) are strongly associated with signal transduction mediated by Ca
2+ permeable channels [
90,
92,
93,
94]. It has been shown that the activation of the PR protein and phenylpropanoid pathway enzymes such as LRR-STKs and MAPKs responds to DM infection in pearl millet by inducing molecules for signal transduction [
95]. Also, nucleotide-binding site (NBS)-LRR and receptor-like proteins (RLP) were included in five classes of
R genes, these have been reported as resistance against DM [
70,
71]. RLKs are well known to play a role in many important signaling process such as plant growth, development, hormone signaling, and stress response. LRR-RLK family proteins regulate plant innate immunity and defense [
69]. PGIP is a defense protein consisting of an extra-cytoplasmic LRR which specifically binds the invading fungus cell wall to the host tissue [
96]. In previous studies, the transcription of PGIP and a cell wall glycoprotein were induced in DM-resistant strains of pearl millet [
38] and grape [
97]. In
Arabidopsis thaliana, homoserine accumulation in the chloroplast triggers a novel form of DM resistance that is independent of known immune responses [
98]. In pearl millet, the role of PGIP in resistance against DM pathogen (
Sclerospora graminicola) was reported by differential gene expression analysis between resistant and susceptible genotypes [
72].
GRMZM2G005984 was classified as a photosystem II protein. In grapevine, PM-responsive proteins are involved in photosynthesis, metabolism, disease/defense, protein destination, and protein synthesis [
99]. These proteins are associated with the plant defense response and slow down disease progression against
Erysiphe necator.
GRMZM2G314171 was classified as DEAD-box RNA helicase, one of which (OsBIRH1) has been found to modulate the defensive response to infection and oxidative stress in rice [
100]. The DEAD-box RNA helicase family functions in chloroplast biogenesis in maize [
101].
GRMZM2G178880 was classified as a GTF (general transcription factor); these proteins are probably involved in defense-related processes [
102]. It has been shown that GTF expression increases during the interaction between PM and barley [
103], and its expression level is induced after wounding and phytopathogenic bacteria attack [
104].
GRMZM2G024293 was identified as a conserved hypothetical adenosine triphosphate (ATP)-binding protein. Its downregulation brings about a decrease in ATP binding in DM-infected plants, which makes it possible to estimate DM susceptibility. Meanwhile, further study is needed to identify the functional characteristics of the uncharacterized genes.
Hence, we suggest that 10 genes (AC210003.2_FG004, AC191071.3_FG001, GRMZM2G039345, GRMZM2G028643, GRMZM2G128315, GRMZM2G330907, GRMZM2G363066, GRMZM2G005984, GRMZM2G178880, and GRMZM2G314171) are related to P. sorghi, P. maydis, and S. macrospora resistance. The downregulation of some of the P. sorghi, P. maydis, and S. macrospora resistance genes occurs in DM-infected plants. Moreover, it was shown that 30 genes are partially upregulated in DM-infected plants of resistant genotype. From these results, we predict the possibility that the phenotype of resistant plants shows resistance (R) or moderate resistance (MR).
Experiments on P. sorghi, P. maydis, and S. macrospora resistance have been limited to QTL analysis in previous studies. However, we focused on their great importance through the screening of candidate genes using qRT-PCR. The results of this study can serve as fine-mapping for DM and marker-assisted selection (MAS) in maize breeding. In further research, our approach could be used to screen other DM strains in different environments using RILs and to validate candidate genes using CRISPR/Cas9. In addition, the genes and pathways associated with resistance could be identified via comparative transcriptome profiling using RNA-seq.