Fine-mapping the recently discovered QTL qMrdd2 that confers resistance to maize rough dwarf disease

Background: Maize rough dwarf disease (MRDD) is a disease caused by a virus that seriously affects maize yield and quality worldwide. Rice black streaked dwarf virus (RBSDV) in the Fijivirus genus in the Reoviridae family causes MRDD in maize. Typical MRDD symptoms of include severe dwarfing of plants, shortening of internodes. MRDD resistance is a complex trait that is quantitatively inherited and is controlled by several quantitative trait loci (QTL). MRDD is most efficiently controlled by the cultivation of disease-resistant corn hybrids. Results: Disease resistance in the MRDD-resistant Qi319 and -susceptible Ye478 parental inbred lines and the 314 recombinant inbred lines (RILs) that were derived from a cross between them was evaluated across three environments. A stable resistance QTL, qMrdd2 , which explained 8.64 to 11.02% of the total phenotypic variance in MRDD resistance, was identified repeatedly and was mapped using BLUP values to a 0.55-Mb region between the markers MK807 and MK811 on chromosome 2. We validated the effect of qMrdd2 using a chromosome segment substitution line population that were derived from a cross between maize inbred Qi319 as the resistance donor and Ye478 as the recipient. The disease-severity index (DSI) of CSSL haplotype II harboring qMrdd2 was significantly lower than the DSI of susceptible parent Ye478 ( P < 0.05). Mapping results using CSSLs were consistent with localization interval determined using RILs. The qMrdd2 locus acted with an additive effect but no significant dominant gene action in conferring MRDD resistance. We fine-mapped qMrdd2 locus into a 315-kb region flanked by the markers RD81 and RD87 by testing recombinant-derived progeny using selfed backcrossed families. Conclusions: qMrdd2 is a recently discovered QTL from Qi319 for resistance to MRDD with an additive effect but no significant dominant gene action for MRDD resistance. qMrdd2 was fine-mapped to a 315-kb interval on maize chromosome 2. Introgression of the MRDD resistance allele at the qMrdd2 locus of CSSL haplotype 2 using linked markers umc1824 and bnlg125 will be useful for maize breeding to reduce yield losses caused by MRDD.


Phenotypic evaluation of resistance to MRDD in parents and RILs
The MRDD resistance of parental inbred lines Qi319 (MRDD-resistant) and Ye478 (MRDD-susceptible) and 314 RILs derived from a cross between them was evaluated at Xuzhou in 2015 and 2016 and at Xinxiang in 2016. Descriptive statistics for MRDD resistance in the three environments are shown in Table 1, and in Figure 2A and 2B. ANOVA revealed highly significant differences (P < 0.01) between the resistant inbred line Qi319, with an average DSI of 13.75, and the susceptible inbred line Ye478, with an average DSI of 71. 35 in the three environments. The parental lines Qi319 and Ye478 consistently exhibited either MRDD resistance or susceptibility in each year and location ( Figure 2A and 2B). The average DSI of each RIL was used to represent the disease resistance of each line. The continuous, normal distributions of phenotypes in the field from highly MRDD resistant to completely susceptible reflected the quantitative control of MRDD resistance in maize ( Figure 2C). The broadsense heritability (H 2 ) of resistance to MRDD ranged from 76.98 % to 81.67 % in the RILs (Table 1).
Meanwhile, the parents Qi319, Ye478, and their F 1 were also mock-inoculated by virus-free SBPH as a control. The numbers of surviving virus-free SBPH did not differ significantly (P > 0.05) among Qi319, Ye478, and their F 1 from the first day to the seventh day ( Figure 2D), which implied that the QTL controls resistance to MRDD, not to the SBPH pest.

Identification of QTL for MRDD resistance
In the present study, a stable QTL for resistance to MRDD that explained 8.17 to 11.02 % of the total phenotypic variation in MRDD resistance across three environments was identified on chromosome 2 using genotypes and phenotypic values in the 314 RILs (Table 2 and Figure 3A). Alleles for MRDD resistance came from the resistant parent Qi319 and increased phenotypic values for MRDD resistance in all three environments. In 2015, the significant QTL qMrdd2 was identified between MK806 and MK811 on chromosome 2 (LOD score = 5.83) and explained 8.17% of the phenotypic variation in MRDD resistance (Table 2). In 2016, another significant QTL for resistance to MRDD was detected in the same region and explained 8.64% and 11.02% of the total phenotypic variance at Xuzhou and Xinxiang, respectively. The CIs for these two QTL covered average physical distances of 0.15 Mb on the B73 RefGen_v3 reference genome ( Table 2). The stable resistance QTL, designated qMrdd2, was identified repeatedly and was mapped using BLUP values into a 0.55-Mb region between the bin markers MK807 and MK811 on the B73 RefGen_v3 genome.

Validation the effect of qMrdd2 in CSSL populations
The effect of qMrdd2 was investigated in a CSSL population derived from a cross between Qi319 and Ye478 that carried different haplotypes for the segments covering chromosome 2. The average background recovery rates by molecular MAS (BC 5 F 2 ) of these eight CSSLs ranged from 91.45% to 99.62% (Table 4). Combined with the DSI (%) field phenotypic values for plants in three different environments, we found that CSSL haplotype II, which carries the introgressed segment including qMrdd2 flanked by linked markers umc1824 and bnlg125, was associated with MRDD resistance, with DSIs of 20.01%, 56.73%, and 51.71%, respectively (Table 4, Figure 3B and 3C). The DSI of CSSL haplotype II harboring qMrdd2 was significantly lower than that of the MRDD-susceptible parent Ye478 (P < 0.05) in three different environments ( Figure 3B and 3C). The length of the introgressed qMrdd2 fragment in CSSL haplotype II was about 7.0 Mb, according to B73 RefGen_v3 (Table 4).
These mapping results were consistent with the mapping of this interval using RILs and indicate that qMrdd2 could be used to improve resistance to MRDD. Therefore, we knew that the introgression of CSSL haplotype II using the linked markers umc1824 and bnlg125 could be performed to construct secondary backcross populations or selfed segregating populations for fine-mapping of qMrdd2.

Fine-mapping of qMrdd2
To fine-map qMrdd2, we designed 150 InDel primer pairs within the qMrdd2 region based on 30× genome sequencing of the resistant parent Qi319 and the susceptible parent Ye478, and detected 13 polymorphic InDel markers between Qi319 and Ye478, as shown in Table 3. The flanking SSR markers umc1824a and bnlg125 were first used to identify recombinants from 6000 BC 1 F 2 plants and 6000 F 3 plants in the winter nursery of Hainan in 2016. The recombinants were self-pollinated to generate BC 1 F 3 and F 4 families and their genotypes were resolved using the 13 polymorphic InDel markers distributed throughout the qMrdd2 region. Finally, a total of 16 recombinant haplotypes were detected ( Figure 4).
In 2017, the recombinant-derived families represented 16 haplotypes, 10 of which were homozygous, were selected and planted for fine-mapping of qMrdd2 in three locations. The MRDD resistance of each of the 10 homozygous recombinant-derived families (Haplotypes VII-XVI) were evaluated for under conditions of natural infection and planted with Ye478 in a 1:1 ratio (Figure 4). Most of the haplotypes VII-XI were highly susceptible to MRDD and most of the haplotypes XII-XVI were highly resistant to MRDD regardless of genotype in three locations. The exceptions were haplotype X in Xuzhou, for which the DSI did not significantly differ from Ye478 (Student's t-test, P > 0.05), and haplotypes XII-XVI, for which DSIs differed significantly from Ye478 (Student's t-test, P < 0.05) (Fig.   4). These results indicated that qMrdd2 was located between RD56 and RD114. The DSIs of haplotype X in Xuzhou differed significantly from that of Ye478. At the same time, 1079 BC 1 F 3 individuals derived from 28 recombinants including six haplotypes I-Ⅵ were selected and planted in Xinxiang, Xuzhou, and Jining. Within the heterozygous region of qMrdd2, the three genotypes of the BC 1 F 3 individuals were Qi319/Qi319, Ye478/Ye478, or heterozygous Qi319/Ye478. The DSIs of these three genotypes were evaluated separately under conditions of natural infection and calculated for each BC 1 F 3 family. Analyzing the combined genotypic and phenotypic data revealed significant differences in DSI among the three genotypes for haplotype I at any field location. This result implied that qMrdd2 could be located within the heterozygous region but not in the homozygous Qi319 region. The remaining haplotypes (II-VI) were resistant to MRDD as no significant differences were detected among the three genotypes according to one-way ANOVA (P > 0.05). This result implied that qMrdd2 could be located within the homozygous Qi319 region but not in the heterozygous region. Based the above results, the qMrdd2 was fine-mapped into a 315-kb interval between the markers RD81 and RD87.

Model of gene action for MRDD resistance controlled by qMrdd2
We examined the nature of the gene action controlling resistance to MRDD by qMrdd2 in F 2 families categorized according to their genotypes within qMrdd2 region between markers RD81 and RD87,

A recently discovered QTL conferring MRDD resistance in maize
The genetic basis for quantitative genetic traits often involves multiple QTL, including those with large and small effects [28][29][30][31][32]. Relative to traits controlled by one or a few genes, quantitative genetic traits controlled by QTL, especially major QTL, are vital genetic resources for improving crop traits.
Because MRDD is a complex viral disease, it was important to choose a suitable resistant parent for identifying disease resistance in segregating progeny as the basis for QTL mapping. Several MRDDresistance loci have so far been reported in the maize genome. Several of these candidate genes for disease resistance loci have been fine-mapped or cloned. For example, as mentioned above, a major recessive QTL, qMrdd1, explaining 24.6 to 37.3 % of the phenotypic variance in resistance to MRDD, originated from the MRDD-resistant inbred X178 and was identified in a 1.2-Mb region of bin 8.03 [29]. Later, qMrdd8 was fine-mapped into a 347-kb interval in which one SNP and two InDels were significantly associated with MRDD resistance [30]. Five other QTL located on chromosome 2 (bin 2.02), 6 (bin 6.02), 7 (bin 7.02), 8 (bin 8.07), and 10 (bin 10.05) that explained 11.9 to 34.8 % of the phenotypic variance in MRDD resistance, were identified using F 2 and BC 1 populations combined with bulked segregate analysis (BSA) [27]. Many screens for MRDD resistance in maize germplasm have been conducted in China under natural MRDD infection conditions. The major sources of MRDD resistance currently used in China have been derived from the US maize hybrid P78599 and include Shen137, SH15, 89-1, Golden 59, X178, and P138 [19][20][21][22]. In our study, we consistently detected a stable resistance QTL, derived from the inbred Qi319 in the PB heterotic group and mapped qMrdd2 using BLUP values ( Table 2) to a 0.55-Mb region between the bin markers MK807 and MK811, according to the B73 RefGen_v3 genome. The PB group includes tropical maize germplasm from the Americas. However, the haplotypes carrying the resistance gene qMrdd8 derived from X178 are different from the haplotypes carrying the resistance gene qMrdd2 derived from Qi319, which suggests that these two MRDD-resistant materials (X178 and Qi319) might possess different mechanisms of resistance to MRDD [30]. These results further suggest that Qi319 could serve as a parent for breeding new disease-resistant hybrids. Future experiments using lines derived from X178 and Qi319 should also help clarify the genetic mechanisms of MRDD resistance and will have important theoretical and applied consequences for breeding maize varieties resistant to MRDD.

Validation of the genetic action of qMrdd2 in both RILs and CSSLs
Both genetic background and the environment can influence the resistance of plants to viruses [33,34]. Choosing a suitable mapping population for phenotyping disease resistance is essential for QTL mapping. Compared with traditional mapping populations, the number of markers used to construct genetic linkage maps is relatively small, so their resolution is low and the confidence intervals for targeted QTL are typically between 10 and 20 cM. Such large intervals make molecular markerassisted breeding difficult and imprecise and also limits the deep analysis of genes conferring disease resistance in maize. Genotyping-by-sequencing (GBS) has become a popular new method for acquiring dense genome-wide markers and has been successfully used for genetic studies in a variety of species [35,36]. In two studies, an F 2 and the US-NAM population were subjected to GBS to increase marker densities to 6533 and 5296 markers, respectively [37,38]. A high-density linkage map with 4183 bin markers and an average marker interval of 0.37 cM was constructed to map QTL for flowering and plant architecture-related traits in a maize RIL population [39]. In the present study, a stable QTL on chromosome 2 that explained 8.17 to 11.02% of the total phenotypic variation in MRDD resistance was identified in three environments using genotypes and phenotypic BLUP values in 314 RILs (Table 2 and Fig. 3A). The studies have fully demonstrated the feasibility, accuracy, and efficiency of GBS technology for the construction of genetic maps in maize.
The phenotypic differences between CSSLs and their recurrent parents can be considered to be due to the introduction of the fragment [40]. Therefore, a QTL located in the chromosome segment carried by the introduced fragment can be identified by analyzing the phenotypic differences between a CSSL and its recurrent parent, and provides material for the exploration of the QTL controlling a target trait [40]. Because CSSLs can eliminate most of the interference from the genetic background the gene/QTL introduced by the fragment can be regarded as a single Mendelian factor in a near-isogenic line, which lays the foundation for fine mapping of the gene responsible for the QTL [41][42][43]. CSSLs allow genetic effects to be more accurately estimated in particular backgrounds [40]. Stepwise regression in data from 130 CSSLs was used to detect 11 QTL for kernel row number (KRN) in three environments, that explained from 9.87 to 19.44% of phenotypic variation in KRN [43]. In the present study, eight CSSLs covering chromosome 2 were identified to detect and validate the genetic effects of qMrdd2 on MRDD. The DSI of CSSL haplotype II harboring qMrdd2.02 differed significantly from that of the susceptible parent Ye478 (P < 0.05) in three environments ( Figure.3B and 3C). The consistent results for QTL mapping in our study between RILs and the CSSLs further verify the presence of qMrdd2 in the segment and demonstrate the feasibility of identifying QTL for resistance to diseases using a combination of RILs and CSSLs.

Application of QTL for resistance to MRDD in maize breeding
By using molecular MAS technology, the breeding of maize for MRDD resistance could be accomplished quickly by searching for molecular markers closely linked to the target gene and then screening for maize plants carrying the target fragment. Despite the great successes in identifying QTL for different traits in many different species and identifying the functional genetic variants behind these QTL, the success of molecular MAS has sometimes been limited [44]. When MAS was used to introgress the major QTL qHSR1 for resistance to head smut into 10 smut-susceptible maize inbreds, the head smut resistance of all 10 of these converted inbreds and their hybrids was improved substantially, while other agronomic traits were mostly unchanged [45]. The gibberella stalk rot resistance of elite maize ZmCCT haplotypes without transposable elements in their promoters was enhanced and yield-related traits were also improved, without changes in flowering time [46]. The QTL qMrdd8 from the donor parent X178 was introgressed into seven elite inbred lines from three maize heterotic groups using multi-generation backcrossing and MAS. The seven converted inbred lines and five converted hybrids exhibited enhanced resistance to MRDD across different environments, while other agronomic traits were not affected under non-pathogenic stress conditions [16]. A wheat line carrying the gene for resistance to powdery mildew, Pm21, as donor parent was backcrossed to three spring wheat varieties by combining evaluation for disease resistance with selection using molecular markers. After five backcrosses and four generations of self-pollination, nine converted lines with high resistance to PM and good agronomic traits were developed [47]. As mentioned above, here, the DSI of CSSL haplotype II harboring qMrdd2 significantly differed from that of the susceptible parent Ye478 (P < 0.05) in three different environments ( Fig.3B and 3C). This result was consistent with localization qMrdd2 the RIL population and indicated that qMrdd2 could improve resistance to MRDD. Thus, introgression of the MRDD resistance allele at the qMrdd2 locus or the introgression of CSSL haplotype II using linked markers umc1824 and bnlg125 will be useful for improving the MRDD resistance of hybrid maize adapted to growing regions in China. Ye478 as the recurrent parent, 200 CSSLs were developed using a combination of crossing, selfing, and molecular MAS. Detection of SSR markers was performed as described by Wang et al [48]. The lengths of substituted chromosomal segments were assessed using graphical genotypes [49].

Conclusions
Detailed methods and processes we followed for developing CSSLs were described in a previous study in rice [50]. We characterized the 2 to 4 introgression segments in each CSSL in our study according Student's t-test were used to determine whether any differences in mean survival rate for virus-free SBPH were significant.

Linkage map construction and QTL detection
The 314 RILs were genotyped using a GBS approach on an Illumina HiSeq2500 platform. A highdensity genetic map was constructed from a total of 88,268 high-quality SNPs with 4183 bin markers.
The map of the RIL population comprised a total genetic distance of 1545.65 cM covering all 10 maize chromosomes with an average physical distance between adjacent markers of ~0.51 M. This detailed genetic map has been described in a previous study [39]. Phenotypic data for resistance to MRDD were collected from the population of 314 RILs during field experiments conducted from 2015 to 2016 in Xuzhou and Xinxiang. A linkage map was constructed by inclusive composite interval mapping (ICIM) using QTL IciMapping software 4.0 [51] and analyzed together with phenotypic information to identify QTL for resistance to MRDD. The positive and negative signs of the estimates indicated whether resistance effects for QTL with additive effects were inherited from Ye478 or Qi319, respectively. Taking each location as an environment and for each of the datasets (2015, 2016, and BLUP), the significance threshold for identifying a putative QTL was set at a logarithm of odds (LOD) score > 3 with 1000 permutations at P < 0.05 [51].

Validation of qMrdd2 using the CSSL populations
To validate the effect of qMrdd2, eight CSSLs that covered all of chromosome 2 were developed with

Genotyping and marker development
Genomic DNA was extracted from leaves of plants at the five-leaf stage using a CTAB procedure following the protocol of Murray and Thompson [52] with modifications. The quality and quantity of DNA samples used for marker genotyping was assessed by evaluating DNA samples on 1.0% agarose gels and by measuring absorbances using a spectrophotometer (Nanodrop 2000, Thermo Scientific, US). We obtained the SSR primer sequences for our study from the MaizeGDB (http://www.maizegdb.org/). InDel markers were developed from 30×genome sequence data for the resistant parent Qi319 and susceptible parent Ye478 [39]. These InDels were designated with the prefix RD and screened for polymorphisms between Qi319 and Ye478. SSR or InDel primers used for genotyping of plants were synthesized by AuGCT Biotechnology Co. Ltd., China. Each PCR reaction mixture contained 6.8 µL double-distilled water, 1.2 µL 10× Buffer, 0.5 µL dNTPs (2.5 mM), 0.15 µL each primer (0.01 nmol/µL), 0.2 µL Taq DNA polymerase (5 U/µL), and 1 µL template DNA in a 10-µL total volume. The touchdown PCR program for amplifying these markers included an initial denaturing step at 94 °C for 4 min, followed by 10 cycles of 30 s at 95 °C, 30 s at 65 °C, and 30 s at 72 °C, with the annealing temperature decreasing by 1 °C per cycle; followed by 30 cycles of 30 s at 94 °C, 30 s at 55 °C, and 30 s at 72 °C; and ending by extending for 5 min at 72 °C. The PCR products were then electrophoretically separated on 8% polyacrylamide gels in 1× TBE buffer that were then silver stained for visualization of PCR products.

Fine-mapping of qMrdd2
We carried out the recombinant-derived progeny tests to fine-map qMrdd2 (Fig. 1) [53]. Based on the QTL region mapped using RILs and CSSLs, CSSL-31 (haplotype II) was crossed as a male parent with Ye478 to produce an F 1 in Yunnan in 2015. The 25 F 1 progeny were then self-pollinated to produce the F 2 and crossed with Ye478 to produce the BC 1 F 1 in a winter nursery in Hainan in 2015. In the summer of 2016, 850 F 2 and 1000 BC 1 F 1 were genotyped, and new recombinants mapped within the region containing the QTL were self-pollinated to produce F 3 and BC 1 F 2 progenies at Jining and Xinxiang under natural infection conditions. In the winter of 2016, 6000 F 3 and 6000 BC 1 F 2 progeny were planted in the winter nursery and screened for new recombinants. F 3 and BC 1 F 2 recombinants with a homozygous Qi319 genotype at the flanking marker on one side and a homozygous Ye478 genotype of on the other side were then selfed. At the same time, we selfed the heterozygous recombinant BC 1 F 2 progenies to produce segregating BC 1 F 3 populations heterozygous at the flanking marker on one side and homozygous at the flanking marker on the other side. BC 1 F 3 recombinants and F 3 recombinants were then classified into different haplotypes by developing markers. These segregating populations and homozygous recombinants were then used to fine map qMrdd2.
In the summer of 2017, we detected differences in DSI under natural infection in Jining, Xinxiang, and Xuzhou between the homozygous families derived from recombinants and Ye478 using Student's ttest in SAS version 9.2. DSIs differing significantly (P < 0.05) between homozygous recombinantderived families and Ye478 indicated that qMrdd2 was located within a homozygous Qi319/Qi319 segment, whereas DSIs differing insignificantly (P ≥ 0.05) indicated that qMrdd2 was located within a homozygous Ye478/Ye478 segment. Each homozygous recombinant and Ye478 were grown in plots of approximately 17 plants in 4-m rows spaced 0.6 m apart with three replications per location. At the same time, 150-300 kernels randomly selected from each plot representing the progeny of diverse types of BC 1 F 2 recombinants were planted to evaluate for MRDD resistance under natural inoculation conditions in Jining, Xinxiang, and Xuzhou. Each BC 1 F 2 recombinant could be categorized as carrying one of two possible segments, heterozygous Qi319/Ye478 or homozygous Qi319/Qi319, flanking the recombination breakpoint. Individuals from the selfed BC 1 F 2 recombinant progeny were categorized into one of three possible genotypes in the qMrdd2 region: homozygous Qi319/Qi319, homozygous Ye478/Ye478, or heterozygous Qi319/Ye478. One-way ANOVA was used to compare the DSIs of these three genotypic classes in SAS version 9.2 (SAS Inc., Cary, NC, US, 2009). The DSIs of the three genotypic classes differing significantly (P < 0.05) indicated that the MRDD resistance gene was located within a heterozygous region, whereas the DSIs of three genotypic classes differing insignificantly (P ≥ 0.05) indicated that the MRDD resistance gene was located within a homozygous segment.

Analysis of phenotypic data
As described above, the disease response phenotypes of all recombinant-derived progenies were assessed in terms of DSI (See above for calculation of DSI). All of the genotypic and phenotypic datasets were calculated using Microsoft Excel 2010 software. We estimated the broad-sense heritability (H 2 ) of MRDD resistance across three environments according to Knapp et al. [54]. We calculated heritability as: H 2 = δ 2 g /(δ 2 g + δ 2 ge /e + δ 2 /er), where δ 2 g is the genetic variance, δ 2 ge is the genotype × environment interaction, δ 2 is error variance, e is the number of environments, and r    Table 3 Primers developed for fine-mapping qMrdd2 Primer positions are according to B73 RefGen_v3. allele of Ye478 (S). Recurrent parent Ye478 (S) was used as the control line for resistance evaluation.
"*" Significant at P < 0.05.  Fine-mapping qMrdd2 Fine-mapping of QTL qMrdd2 was performed using recombinant progeny and homozygous family verification.