Sugarcane Mosaic Virus Resistance in the Wisconsin Sweet Corn Diversity Panel

in Journal of the American Society for Horticultural Science
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  • 1 Department of Agronomy, College of Agricultural and Life Sciences, University of Wisconsin–Madison, Madison, WI 53706
  • | 2 Plant Breeding and Genetics Section, School of Integrative Plant Science, Cornell University, Ithaca, NY 14853
  • | 3 Department of Agronomy, College of Agricultural and Life Sciences, University of Wisconsin–Madison, Madison, WI 53706

Sugarcane mosaic virus [SCMV (Potyvirus sugarcane mosaic virus)] is an ssRNA virus that negatively affects yield in maize (Zea mays) worldwide. Resistance to SCMV is controlled primarily by a single dominant gene (Scm1). The goal of this study was to identify sweet corn (Z. mays) inbreds that demonstrate resistance to SCMV, confirm the presence of genomic regions previously identified in maize associated with resistance, and identify other resistant loci in sweet corn. Eight plants from each of 563 primarily sweet corn inbred lines were tested for SCMV resistance. Plants were inoculated 14 d after planting and observed for signs of infection 24 d after planting. A subset of 420 inbred lines were genotyped using 7504 high-quality genotyping-by-sequencing single-nucleotide polymorphism markers. Population structure of the panel was observed, and a genome-wide association study was conducted to identify loci associated with SCMV resistance. Forty-six of the inbreds were found to be resistant to SCMV 10 d after inoculation. The Scm1 locus was confirmed with the presence of two significant loci on chromosome 6 (P = 2.5 × 10−8 and 1.6 × 10−8), 5 Mb downstream of the Scm1 gene previously located at Chr6: 14194429.14198587 and the surrounding 2.7-Mb presence–absence variation. We did not identify other loci associated with resistance. This research has increased information on publicly available SCMV-resistant germplasm useful to future breeding projects and demonstrated that SCMV resistance in this sweet corn panel is driven by the Scm1 gene.

Abstract

Sugarcane mosaic virus [SCMV (Potyvirus sugarcane mosaic virus)] is an ssRNA virus that negatively affects yield in maize (Zea mays) worldwide. Resistance to SCMV is controlled primarily by a single dominant gene (Scm1). The goal of this study was to identify sweet corn (Z. mays) inbreds that demonstrate resistance to SCMV, confirm the presence of genomic regions previously identified in maize associated with resistance, and identify other resistant loci in sweet corn. Eight plants from each of 563 primarily sweet corn inbred lines were tested for SCMV resistance. Plants were inoculated 14 d after planting and observed for signs of infection 24 d after planting. A subset of 420 inbred lines were genotyped using 7504 high-quality genotyping-by-sequencing single-nucleotide polymorphism markers. Population structure of the panel was observed, and a genome-wide association study was conducted to identify loci associated with SCMV resistance. Forty-six of the inbreds were found to be resistant to SCMV 10 d after inoculation. The Scm1 locus was confirmed with the presence of two significant loci on chromosome 6 (P = 2.5 × 10−8 and 1.6 × 10−8), 5 Mb downstream of the Scm1 gene previously located at Chr6: 14194429.14198587 and the surrounding 2.7-Mb presence–absence variation. We did not identify other loci associated with resistance. This research has increased information on publicly available SCMV-resistant germplasm useful to future breeding projects and demonstrated that SCMV resistance in this sweet corn panel is driven by the Scm1 gene.

Sugarcane mosaic virus [SCMV (Potyvirus sugarcane mosaic virus)] has a worldwide geographic range and causes significant yield losses in maize [Zea mays (Kuntze et al., 1995; Shukla et al., 1989)]. SCMV causes an average of 10% to 15% yield loss in maize grown in China and is said to be the most important viral maize disease in Europe (Kuntze et al., 1997; Zhang et al., 2003). If plants are infected when young, SCMV can reduce ear weight, plant height, and total plant weight (Johnson et al., 1972; Kuntze et al., 1995). When SCMV coinfects with Machlomovirus maize chlorotic mottle virus, it can result in maize lethal necrosis disease (MLN), causing total yield loss (Wangai et al., 2012). SCMV is one of the positive-sense, single-strand RNA viruses found within the Potyviridae family, previously denoted as Maize dwarf mosaic virus-B (Shukla et al., 1989). Other viruses within the Potyviridae include Potyvirus johnsongrass mosaic virus, and Potyvirus maize dwarf mosaic virus (Shukla et al., 1989, 1992). In addition to maize, SCMV also infects sugarcane (Saccharum sp.) and sorghum (Sorghum sp.), causing stunting and chlorosis (Kuntze et al., 1995; Shukla et al., 1989). The virus is transmitted by corn leaf aphids (Rhopalosiphum maidis) in a nonpersistent manner, and it is diagnosed with symptoms such as chlorosis, stunting, and reduced plant weight (Knoke et al., 1974). Chemical or agronomic control of aphids are not effective at eliminating transmission of SCMV (Charpentier, 1956). However, genetic resistance has proven to be an effective means of controlling SCMV (Liu et al., 2017; Xing et al., 2006). Genetic resistance is primarily linked with the Scm1 gene within a large presence–absence variation (PAV) on chromosome 6 (Gustafson et al., 2018). Mosaic virus genetic resistance was transferred intentionally into sweet corn (Z. mays) as early as 1983 (Mikel et al., 1984).

The reaction to SCMV infection in field maize has been studied extensively. Kuntze et al. (1995) tested 124 European flint and dent maize inbreds for lasting resistance to SCMV under multiple conditions. Twenty-four inbreds showed resistance in both greenhouse and field conditions 4 weeks after inoculation. They also found only three inbreds completely resistant to SCMV 7 weeks after inoculation. Nineteen inbreds displayed delayed symptom expression (Kuntze et al., 1995). Subsequently, Kuntze et al. (1997) screened 122 European maize inbreds in greenhouse conditions and showed 34 inbreds had no symptoms 10 to 14 d after inoculation (DAI). A second experiment in field conditions found only three inbreds (D21, D32, and FAP1360A) that were completely resistant to SCMV and four inbreds (D06, D09, R2306, and FAP1396A) with partial resistance when evaluated 28 and 49 DAI (Kuntze et al., 1997).

Gustafson et al. (2018) evaluated SCMV resistance in field maize within the Wisconsin Diversity Panel under inoculated field conditions and found that 31 of the 578 inbreds tested were resistant to SCMV at 35 DAI. Gustafson et al. (2018) found that when inoculation was delayed from the three- to the six-leaf growth stage, symptom development was reduced, but inbreds that did not have the Scm1 gene, due to the absence variant, were susceptible regardless of inoculation time points. In agreement, an earlier study found that younger plants are most susceptible to infection through inoculation, and that incidence of disease was halved when susceptible maize hybrids were inoculated at 11-leaf stage compared with five-leaf stage (Rosenkranz and Scott, 1978). Previous studies have determined that evaluation of SCMV resistance is not influenced significantly by testing in the field compared with greenhouse or by methods of manual inoculation, such as the rub method or the air-brush method (Kuntze et al., 1995).

Two loci conferring resistance to SCMV are known in maize, Scm1 and Scm2 (or Scmv1 and Scmv2), on the short arm of chromosome 6 and the centromeric region of chromosome 3, respectively (Gustafson et al., 2018; McMullen and Louie, 1989; Melchinger et al., 1998; Simcox et al., 1995). Scm1 and Scm2 were first mapped in association with SCMV in 1989, and both were identified as dominant genes (McMullen and Louie, 1989). Scm1 is a dominant gene, conferring resistance to infection at all developmental stages, especially resistance in early stages of development (Dußle et al., 2000; Gustafson et al., 2018; Jones et al., 2007; Tao et al., 2013). Scm2 is associated with higher degree of resistance to SCMV infection in populations, especially at later stages of development and behaves epistatically with Scm1 (Dußle et al., 2000; Xing et al., 2006). Scm1 is located at Chr6: 14194429.14198587 in B73 v3 and is within a 2.7-Mb PAV spanning from 12.9 to 15.4 Mb. Gustafson et al. (2018), showed that all susceptible lines with the absence variant were found to be susceptible to SCMV and had an allele associated with susceptibility downstream at 19.4 Mb, due to the inability of making associations with missing single-nucleotide polymorphisms (SNPs). Liu et al. (2017) determined the casual gene at Scm1 to be Zmtrxh which encodes an atypical h-type thioredoxin and suppresses viral RNA accumulation in the cytoplasm. Scm2 is partially dominant for resistance to SCMV but often does not appear in association with resistance at early time points (Xia et al., 1999). Minor quantitative trait loci (QTL) have also been identified on chromosomes 1, 3, 5, and 10 that explain 6% to 10% of phenotypic variance in total (Gustafson et al., 2018; Melchinger et al., 1998; Xia et al., 1999).

Genome-wide association studies (GWAS) are frequently used in maize research to detect associations of genetic markers with traits of interest (Xiao et al., 2017). GWAS can identify associated loci with high resolution by using diverse populations that have undergone many generations of recombination, leading to a more rapid decay of linkage disequilibrium (LD; Flint-Garcia et al., 2003). Association mapping panels combined with GWAS have been used to gain insights on the genetic architecture of MLN and have found 24 SNPs associated with MLN resistance linked to 20 putative candidate genes that can potentially be used in MLN resistance breeding programs (Gowda et al., 2015). Although GWAS identifies associated loci and candidate genes, follow-up is often required to directly connect those loci with causal genes, making it useful predictively in many cases but not always immediately applicable (Broekema et al., 2020; Pierce et al., 2020). Additionally, GWAS has trouble identifying rare alleles or alleles that are highly fixed in the population (Hamazaki et al., 2020). Three GWAS have been done previously on the Wisconsin Sweet Corn Diversity Panel (WSCDP), investigating loci associated with tocochromanols, carotenoid, and elemental variation in fresh sweet corn kernels. These studies suggest that GWAS are effective in the WSCDP (Baseggio et al., 2019, 2020, 2021).

The objectives of this study were to identify sweet corn inbreds with genetic resistance to SCMV, confirm the presence of genomic regions previously identified in field maize associated with resistance (the Scm1 and Scm2 loci), and determine if there were other putative resistance loci unique to the sweet corn panel.

Materials and Methods

Germplasm.

In 2019, 563 sweet corn inbreds from the WSCDP were evaluated for resistance to SCMV under greenhouse conditions (Supplemental Table 1). These inbreds were part of the WSCDP, a diversity panel designed to evaluate the genetic architecture and breadth of molecular and phenotypic diversity within public, temperate, sweet corn germplasm. The WSCDP has 581 inbreds in the full panel, through the size and composition of the inbreds used in WSCDP experiments depending on the experiment’s focus, germplasm availability, and resources (Baseggio et al., 2019, 2020, 2021). The pedigrees of many of the inbreds within the panel are known through internal records. Inbreds found to be SCMV-resistant had their pedigree traced for obvious inherited sources of genetic resistance. A large portion of the lines within the WSCDP are sourced from the University of Illinois–Urbana and University of Wisconsin–Madison sweet corn breeding programs (330 of the 563 in this study), due to availability and the extent of modern sweet corn germplasm derived from those programs.

Phenotypic evaluation.

The experiment was conducted at the University of Wisconsin–Madison Walnut Street Greenhouses (Madison). The greenhouse was kept at 24 to 28 °C during the day and 18 °C at night. Lighting was supplied by 400-W high-pressure sodium lights, four lights over each bench of 60 pots. Lights remained on for 16 h·d−1 or until 400 μmol of natural light was reached. One hundred twenty inbreds were planted at a time in sets of 60 pots per bench and with the inbred’s planting order determined at random. Eight kernels of each inbred were planted in 19.7-cm-diameter pots about 2 cm deep in media composed of 65% to 75% sphagnum peatmoss and 8% to 35% perlite (ProMix HP, Premier Tech Horticulture, Quakertown, PA). Plants were fertilized three times per week with 20N–4.4P–16.6K fertilizer (Peters Professional 20–10–20 Peat Lite Special Fertilizer; ICL Specialty Fertilizers, Summerville, SC).

Seedlings were inoculated 14 d after planting (DAP), when all inbreds were around the three-leaf stage to maximize susceptibility (Rosenkranz and Scott, 1978). The SCMV isolate used for inoculation was collected in 1996 from a Wisconsin sweet corn field. The amplified isolate was confirmed to be a SCMV isolate via RNA sequencing analysis and enzyme-linked immunoassay (Agdia, Elkhart, IN) and tested negative for Maize dwarf mosaic virus, Wheat mosaic virus, and Wheat streak mosaic virus (Gustafson et al., 2018). SCMV inoculum was maintained on a susceptible sweet corn hybrid, GH4927 (Syngenta, Basel, Switzerland), under isolated greenhouse conditions. A cycle of available inoculum was maintained by inoculating uninfected GH4927 14 DAP and planting new GH4927 every 14 d. Inoculum was prepared by grinding six to 10 leaves of the 21-d-old infected hybrid, with ≈250 mL of municipal water and 5 g of carborundum using a mortar and pestle. Inoculation was done mechanically with the carborundum creating injury points by dipping a gloved hand in the inoculum and running the seedlings’ leaves through pinched fingers, known as the rub-inoculation method (Knoke et al., 1974). Stand count was recorded for each pot on the same day as inoculation. Inbreds with zero germination were dropped from the study.

Symptoms were visually scored 10 DAI, and the number of plants per pot displaying any symptoms were recorded. Diagnostic symptoms were mosaic chlorosis on leaves with contrasting green on a background of paler green or yellow chlorotic areas, occasionally with streaks or stripes (Fuchs and Grüntzig, 1995). Uninfected plants did not show signs of chlorosis or mosaic patterning. To eliminate the possibility of false resistance ratings due to mistakenly uninoculated pots, inbreds that displayed no symptoms on any seedlings were tested again with three additional pots of eight kernels each planted all within the same round. Four control pots of GH4927 were included at random on each bench of 60 pots. The control pots were inoculated and served as a check for inoculation effectiveness. Each seedling was either rated as symptomatic or asymptomatic regardless of intensity of symptoms. Each pot of eight kernels was considered an experimental unit. The percentage of symptomatic plants for each inbred was calculated by dividing the total number of symptomatic seedlings by the total number of seedlings grown across all replicates. Inbreds with no symptomatic plants 10 DAI within their first planting and no symptomatic plants 10 DAI in their three follow-up replicates were labeled as resistant to SCMV. The rates of germination and symptomatic plants were evaluated for the susceptible control and for the panel at large. Correlation between rates of symptomatic plants and planting order or bench position were assessed, and no correlation was found.

Genotyping.

In 2013, samples from each inbred in the WSCDP were taken and sequenced at the Cornell Biotechnology Resource Center (Ithaca, NY) using genotyping-by-sequencing (GBS) as described previously (Baseggio et al., 2019; Elshire et al., 2011). The sequence data used in this study has been archived in the National Center of Biotechnology Information (Bethesda, MD) BioProject under accession number PRJNA482446 and in the Sequence Read Archives under accession SRP154923. The raw GBS sequence data consisted of 955,690 SNPs called using the default parameters in the TASSEL 5 GBSv1 production pipeline (Bradbury et al., 2007) with the ZeaGBSv2.7 Production TagsOnPhysicalMap file in B73 RefGen_v2 coordinates (Panzea, Ithaca, NY). The SNP genotype calls from this study were combined with the raw sequencing data of inbreds included in this screening within the genotyping study of the U.S. Department of Agriculture, Agriculture Research Service, North Central Regional Plant Introduction Station collection in Ames, IA (Romay et al., 2013). The raw SNP genotype calls from the combined set were filtered to retain only biallelic SNPs with greater than 10% call rate. This raw combined sequencing dataset has been used previously in several studies when analyzing the WSCDP for other traits (Baseggio et al., 2019, 2020, 2021). Markers were further filtered by removing SNPs with minor allele frequency of less than 5%, and SNPs with call rates of less than 90%—percentage of SNPs successfully genotyped for each inbred—within TASSEL and were pruned for LD at a rate of 0.98 or higher within SNPRelate (Bradbury et al., 2007; Zheng et al., 2012). The result was a set of 7504 non-imputed high-quality marker sites for 420 of the inbreds tested. Previous studies involving the WSCDP used the same GBS data, filtered differently and imputed (Baseggio et al., 2019, 2020, 2021). We avoided imputation and worked with the raw sequencing data to ensure PAVs were maintained correctly.

Association mapping.

This study’s GWAS was conducted on these markers using the general P + K mixed model through the genetic analysis R package GWASpoly (Rosyara et al., 2016) with three principal components and the kinship matrix calculated by the realized relationship matrix based on VanRaden’s method (VanRaden, 2008). The GWAS was run using a general model, meaning all heterozygotes have the same effect and there is no weighting based on allelic dosage. GWAS was run on the 420 inbreds with GBS data. One hundred forty-three inbred lines did not have associated genetic information because sequencing was conducted before the SCMV screening. These lines were screened despite the lack of sequencing data for the purpose of identifying their SCMV resistance status for the benefit of sweet corn breeding programs.

We estimated the presence of Scm1 in the inbreds by comparing their haplotype near the Scm1 locus to IL793a, an inbred with known Scm1 presence in its pedigree and 0% symptomatic plants in this screening. We will refer to this haplotype as the Scm1- IL793a haplotype. The Scm1- IL793a haplotype was classified by three loci: the locus at 19.9 Mb which was associated with resistance during the initial GWAS that was closest to the Scm1 gene and two SNPs nearest that 19.9-Mb locus. The locus at 19.9 Mb was chosen as the basis for the haplotype due to a lack of SNP coverage in the PAV where Scm1 is located. A closer haplotype could not be used to infer Scm1 presence because there was only one SNP within the PAV sequenced, and it was not enough of a high-quality locus to be included within our filtering parameters. Due to the commonality of the absence variation within the diversity panel, the PAV was not able to be captured by our GBS technique. Previous studies used a similar associated locus at 19.4 Mb to infer Scm1 presence (Gustafson et al., 2018). A simple t test of the percentage of symptomatic plants was conducted between the inbreds with and without the Scm1- IL793a haplotype. We also conducted GWAS on the subset of 360 inbreds that did not have the Scm1- IL793a haplotype. Population structure analysis and visualization in the form of principal component analysis (PCA) was conducted with TASSEL (Bradbury et al., 2007), and R packages SNPRelate (Zheng et al., 2012) on the 420 inbred group. Population structure analysis was done specifically for this study due to our unique filtering parameters.

Associated gene discovery.

Linkage disequilibrium decay was calculated using a full matrix comparison in TASSEL and visualized in R (Bradbury et al., 2007). We used the same filtering as described earlier, without LD pruning for a total of 12,012 marker sites to calculate the genome-wide LD within the 420 inbreds genetically analyzed. The LD decay was used to inform our candidate gene window of 250 kb. The loci of interest that scored above the 5% Bonferroni threshold were deemed significant, and gene models within a 250-kb window of the loci’s flanking region were recorded as associated genes. The Maize B73 RefGen_v3 genome assembly was consulted for associated genes through MaizeGDB (Portwood et al., 2019).

Results

Variation in resistance.

Germination among the screened inbreds was strong with 96% of inbreds germinating three or more seedlings, the median stand count being seven seedlings from eight planted kernels, and the mean being 6.6 seedlings. Ninety-six percent of the control plants (Syngenta GH4927), which has the scm1 allele, were symptomatic and 21% of the control pots had one or more asymptomatic plants (Fig. 1A). Given that Scm1 confers a dominant form of resistance, asymptomatic plants among the controls are likely due to inoculation escapes or minor seed lot impurity.

Fig. 1.
Fig. 1.

Number of percent symptomatic inbred sweet corn plants among (A) the susceptible controls and (B) all screened inbreds.

Citation: Journal of the American Society for Horticultural Science 146, 6; 10.21273/JASHS05097-21

Among the 563 inbreds tested, 559 germinated adequately for screening. From those 559 inbreds, at 10 DAI, 46 inbreds had 0% symptomatic plants. Forty-eight inbreds had fewer than 10% symptomatic plants at 10 DAI. Notably, C.I.540 was included and screened twice, and was rated as 0% and 6.7% symptomatic in the two screenings. Sixty-two inbreds had between 10% and ≤50% plants showing symptoms (Supplemental Table 1). Two hundred and thirty-six inbreds had between 50% and 90% plants with symptoms and 211 inbreds were >90% symptomatic (Fig. 1B).

Of the 46 inbreds that were classified as resistant to SCMV, 33 inbreds had associated GBS data. Within our sequenced panel, 60 inbreds were found with the Scm1- IL793a haplotype and 360 without. Our t test between the inbreds with and without the Scm1- IL793a haplotype found that the groups had significantly different percent symptoms [t = 5.0, P = 4.6 × 10−6 (Fig. 2)]. The group with the Scm1- IL793a haplotype had a mean symptomatic plant percentage of 50% and the group without had a mean percentage of 77%. Twenty-one of the 60 inbreds with the Scm1- IL793a haplotype had no plants that showed symptoms and were therefore classified as resistant.

Fig. 2.
Fig. 2.

Number of percent symptomatic inbred sweet corn plants among the screened inbreds (A) with the Scm1- IL793a associated haplotype and (B) without the Scm1- IL793a associated haplotype.

Citation: Journal of the American Society for Horticultural Science 146, 6; 10.21273/JASHS05097-21

Population structure.

Population structure was observed among the 420 sequenced inbreds (Fig. 3). Inbreds developed by the University of Illinois–Urbana/Champaign program are visibly distinct from the inbreds developed by the University of Wisconsin–Madison Sweet Corn Breeding Program, especially along the principal component two axis. The distinction between the Illinois and Wisconsin inbreds is also reflected in the PCA when labeled by endosperm type, indicating that Wisconsin and Illinois breeding programs have focused on breeding for different endosperm mutants (Fig. 4). Variance explained by the first principal component is equal to 4.5%, and the variance explained by the second principal component equaled 3.3%. Many of the resistant inbreds share similar ancestry as indicated by the pedigree analysis (Table 1).

Fig. 3.
Fig. 3.

Principal component (PC) analysis of 420 sweet corn inbreds within the Wisconsin Sweet Corn Diversity Panel, labeled with their program of origin: CT = University of Connecticut–Storrs; IA = Iowa State University–Ames; IL = University of Illinois–Urbana/Champaign (Champaign, IL); IN = Purdue University (West Lafayette, IN); MN = University of Minnesota–Twin Cities (Minneapolis, MN); SD = South Dakota State University (Brookings, SD); WI = University of Wisconsin–Madison; Other = all other programs within the panel.

Citation: Journal of the American Society for Horticultural Science 146, 6; 10.21273/JASHS05097-21

Fig. 4.
Fig. 4.

Principal component (PC) analysis of 420 sweet corn inbreds within the Wisconsin Sweet Corn Diversity Panel. Inbreds are labeled with their endosperm mutants’ categorization. aeduwx = amylose-extender: dull: waxy; se = sugary enhancer; sh2 = shrunken2; sh2i = shrunken2 intermediate; su1 = sugary1.

Citation: Journal of the American Society for Horticultural Science 146, 6; 10.21273/JASHS05097-21

Table 1.

The 46 identified resistant sweet corn inbreds, with any known resistant ancestors, notation of whether the inbred has associated genotyping-by-sequencing (GBS) data, and the inbreds’ endosperm mutant type.

Table 1.

Linkage disequilibrium.

Within the WSCDP, we found that the median (50th percentile) of the 12,012 pre-LD-pruned high-quality SNP markers showed LD decay to R2 < 0.1 levels by ≈1 kb. However, there were large variances in the structure of LD and LD persisted at higher percentile cutoffs. Ninety percent of the SNPs reached R2 < 0.2 levels by ≈250 kb. Given this, candidate genes were included within a ±250 kb window of the GWAS detected loci. Previous studies have also found loci as far away as 5 Mb downstream of the 2.7-Mb PAV on chromosome 6 to be in strong LD with the PAV (Gustafson et al., 2018).

Association analysis.

Genome-wide association was conducted using 420 inbreds scored with SNP markers. Through the R package GWASpoly, loci of interest using the general model were identified as SNP marker S6_19987285 and S6_36947510 on chromosome 6 at position and 36,947,510 all above the Bonferroni threshold of 5.13 -log10(P) [P = 2.5 × 10−8 and 1.6 × 10−8 (Fig. 5)]. These loci are downstream of the PAV spanning from 12.9 to 15.4 Mb. No SNPs within the PAV were present after filtering due to the prevalence of the absence variation in the panel. Due to the rate of LD decay within these samples, a 250-kb window surrounding the two loci was used to identify nearby associated genes (Supplemental Fig. 1). Thirty-one associated gene models were found (Supplemental Tables 2 and 3). Due to the nature of the nearby PAV and previous research on downstream loci being linked with the PAV and causal genes within it, these genes are associated with the significant loci but are not necessarily candidate genes (Gustafson et al., 2018).

Fig. 5.
Fig. 5.

Manhattan plot of susceptibility to Sugarcane mosaic virus genome-wide association study of 420 sweet corn inbreds within the Wisconsin Sweet Corn Diversity Panel. Logarithm of odds value with a 5% Bonferroni threshold identified two loci within chromosome 6 in sweet corn.

Citation: Journal of the American Society for Horticultural Science 146, 6; 10.21273/JASHS05097-21

A second GWAS was conducted on only the 360 inbreds without the Scm1 haplotype within the WSCDP for the symptomatic percentage trait. No significant loci were found (Fig. 6).

Fig. 6.
Fig. 6.

Manhattan plot of susceptibility to Sugarcane mosaic virus genome-wide association study of 360 sweet corn inbreds within the Wisconsin Sweet Corn Diversity Panel that do not have the Scm1- IL793a haplotype. Logarithm of odds value with a 5% Bonferroni threshold identified no significant loci.

Citation: Journal of the American Society for Horticultural Science 146, 6; 10.21273/JASHS05097-21

Discussion

Phenotypic analysis.

We found 46 inbreds (or 8.2% of the panel) that qualified as resistant to SCMV, meaning totally asymptomatic 10 DAI with SCMV across four pot replications. Samples were inoculated at 14 DAP because younger plants are most susceptible to infection through inoculation (Rosenkranz and Scott, 1978). Many of the resistant inbreds had SCMV-resistance inbred parentage, according to their known pedigrees. Resistance to SCMV is an economically useful trait that has been bred into sweet corn inbreds, so it is unsurprising to find inbreds with known SCMV-resistant parents. However, there were several resistant inbreds such as We02412 and BST4 whose backgrounds reveal no known source of resistance. Of the susceptible inbreds, 509 inbreds were >10% symptomatic, meaning that among all the plants of each inbred, 10% or more of their plants showed symptoms of SCMV infection. Inbreds B73 and C.I.540 were 3% and 7% symptomatic, respectively. Each inbred had no symptomatic seedlings during the first planting. B73 has two symptomatic seedlings out of the 23 plants that germinated during the second planting. Inbred C.I.540 had one symptomatic seedling out of 22 during the second planting. C.I.540 was screened twice, with the other screening fully resistant with 0% symptomatic plants. C.I.540 and B73 were found to have the Scm1- IL793a haplotype. The implied partial resistance does not follow with how SCMV acts in most other inbreds, and the one or two symptomatic plants are more likely due to outcrosses or admixtures in the seed source than due to partial susceptibility. Ninety-six percent of control plants were symptomatic, indicating that our infection methods were effective, and inbreds with 0% symptomatic plants were not resistant due to inoculating error. Notably, however, 21% of the control pots had one or more asymptomatic plants. The asymptomatic plants among the controls were likely due to inoculation error, pollen contamination, or admixture. This indicated that some of the inbreds that had between 50% and 90% symptomatic plants might have had less than 100% symptomatic plants due to inoculation error or a contaminated seed source as opposed to partial susceptibility. Among the 420 inbreds that had associated GBS information, we were able to identify which inbreds had the Scm1- IL793a haplotype. The average percent symptomatic plants were significantly different between the group with the Scm1- IL793a haplotype and the group without the haplotype, indicating that the presence of the Scm1- IL793a haplotype is associated with more resistant inbreds. However, we expected the number of resistant inbreds with Scm1- IL793a haplotype to be higher, considering that seven inbreds without the Scm1- IL793a haplotype were resistant. One explanation may be that because we did not have GBS data within the PAV of those seven inbreds, they do have the Scm1 allele, but it is at linkage equilibrium with the Scm1- IL793a haplotype.

Population structure.

There were clear signs of population structure within the WSCDP. Within the PCA, the inbreds clustered within the different breeding programs of origin with distinction among inbreds created by the University of Illinois–Urbana/Champaign and the University of Wisconsin–Madison (Fig. 3). As previously mentioned, these distinctions correlate with the endosperm mutant types, indicating that Wisconsin and Illinois breeding programs have focused on breeding for different endosperm mutants resulting in consistent differences in the genetics of their germplasm and visible population structure (Fig. 4). The clustering within the PCA indicates that many of the resistant inbreds are closely related as indicated by the pedigrees (Table 1).

Candidate gene discovery.

Most of the SNPs used within the population in this analysis exhibited rapid linkage decay at most loci, likely due to the relatively few markers used within this study (R2 < 0.1 levels by ≈1 kb). We found variation in the LD decay rates in different regions and chromosomes. Ninety percent of SNPs were at R2 of about 0.1 × 1 Mb, or R2 < 0.2 × 250 kb, which, in addition to the precedent of previous WSCDP studies, led us to select a 250-kb window for finding associated genes (Baseggio et al., 2019). There were several gene models within the 250-kb window surrounding the two associated-with-resistance loci found in the GWAS study (Supplemental Tables 2 and 3). It is possible that these nearby genes could be used as markers in future studies. However, numerous previous studies confirm the importance of the Scm1 gene in conferring maize SCMV resistance (Dußle et al., 2000, 2003; Xu et al., 2000; Yuan et al., 2003). Additionally, the two identified SNP markers S6_19987285 and S6_36947510 are relatively near the PAV surrounding the Scm1 gene. Given these two factors, we believe that these associated loci are in LD with the Scm1 gene but not themselves indicative of other causal genes that are contributing to SCMV resistance. Note that the two significant loci are not within the 250-kb LD window of Scm1 nor within the PAV that encompasses Scm1. Previous studies have found that an associated locus at 19.4 Mb was in LD with the PAV, so we believe this is the case with our locus at 19.9 Mb as well (Gustafson et al., 2018). We did not find any associated loci closer to the Scm1, likely due to the lack of SNP coverage within the PAV spanning from 12.9 to 15.4 Mb. There were no SNPs from our GBS included within the 9.5- to 17.0-Mb positions on chromosome 6 as the commonality of the absence variation made that region difficult to genotype. Numerous studies have shown Scm1 is a dominant allele, vital to SCMV resistance in maize (Dußle et al., 2000; Melchinger et al., 1998; Użarowska et al., 2009; Xia et al., 1999; Xing et al., 2006). Finding that Scm1 is present within the resistant inbreds in the WSCDP and that it contributes to resistance corroborates those previous studies.

We did not detect SNP markers associated with Scm2 in any of the GWAS, despite its documented effects (Dußle et al., 2000, 2003; Xu et al., 2000; Yuan et al., 2003). Even when controlling for the presence of Scm1 by only analyzing those inbreds that do not have the Scm1- IL793a haplotype, association between loci near Scm2 and resistance was still not seen. This is likely because we only analyzed at one time point very early in development and Scm2 is associated with sustained resistance over maize’s development (Dußle et al., 2000; Xing et al., 2006). Alternatively, this may be due to Scm2 acting as a modifier to Scm1 and would only be detectable in a panel enriched for the Scm1 presence (Użarowska et al., 2009).

Because this was the first screening of sweet corn inbreds for SCMV resistance, this study had shortcomings that could be improved with future research. Planting more replicates of each inbred in a completely randomized design could increase the power of the analysis and increase confidence in percentage of symptomatic plants. The lack of SNP coverage within the PAV containing Scm1 was a study hinderance. Future studies should take special care to ensure SNP coverage of these area for more confidence in their categorization of inbreds having or not having the Scm1 gene. Additionally, higher SNP coverage overall would increase the likelihood of finding other genomic regions contributing to SCMV resistance. Finally, inoculating the inbreds at multiple time points and enriching the panel for inbreds with the Scm1 gene could lead to identifying association with Scm2 and resistance.

Conclusions

The purpose of this disease screening was to identify and study resistance to SCMV within temperate sweet corn. We used the WSCDP as a representative sample of the diversity found within sweet corn populations. We identified 46 inbreds that were fully resistant to SCMV when evaluated 10 DAI. Many of the inbreds we identified are publicly available and could be used by breeders interested in introducing SCMV resistance into their breeding programs. The role of Scm1 was confirmed within sweet corn, but we did not detect the effects of Scm2 or of any novel loci associated with resistance. Future studies to investigate Scm2 contributions to resistance may use the WSCDP to screen the panel at multiple time points to better measure SCMV response over time. Additionally, targeted genotyping of the resistant lines within the panel would provide better discernment between resistant lines with the Scm1 gene.

Literature Cited

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Supplemental Fig. 1.
Supplemental Fig. 1.

Linkage disequilibrium (LD) estimates among the 420 sequenced sweet corn inbreds. Mean decay of LD measured as pairwise R2 from the 12,012 high-quality single-nucleotide polymorphism (SNP) markers over physical distance. Different percentile cutoffs are indicated of the distribution of SNP markers among all chromosomes.

Citation: Journal of the American Society for Horticultural Science 146, 6; 10.21273/JASHS05097-21

Supplemental Table 1.

Phenotypic data for all sweet corn inbreds within screening, with information about planting order (pot label), ratio of sugarcane mosaic virus symptomatic plants, whether the line was sequence (genetic info), and had the haplotype associated with resistance within its sequence (Scm1- IL793a haplotype), the inbreds’ endosperm mutant type, and the inbreds’ program of origin.

Supplemental Table 1.
Supplemental Table 1.
Supplemental Table 1.
Supplemental Table 1.
Supplemental Table 1.
Supplemental Table 1.
Supplemental Table 1.
Supplemental Table 1.
Supplemental Table 1.
Supplemental Table 1.
Supplemental Table 1.
Supplemental Table 2.

Zea mays genes associated with the significant locus S6_19987285 found in the susceptibility-to-sugarcane mosaic virus genome-wide association study.

Supplemental Table 2.
Supplemental Table 3.

Zea mays genes associated with the significant locus S6_36947510 found in the susceptibility-to-sugarcane mosaic virus genome-wide association study.

Supplemental Table 3.

Contributor Notes

This article is based on research that is supported by the National Institute of Food and Agriculture (SCRI 2018-51181-28419) and the University of Wisconsin–Madison College of Agricultural and Life Sciences. Thank you to Tim Gustafson for providing pathogen inoculum and Gustafson and Natalia de Leon for review.

L.H. is the corresponding author. E-mail: lmhislop@wisc.edu.

  • View in gallery

    Number of percent symptomatic inbred sweet corn plants among (A) the susceptible controls and (B) all screened inbreds.

  • View in gallery

    Number of percent symptomatic inbred sweet corn plants among the screened inbreds (A) with the Scm1- IL793a associated haplotype and (B) without the Scm1- IL793a associated haplotype.

  • View in gallery

    Principal component (PC) analysis of 420 sweet corn inbreds within the Wisconsin Sweet Corn Diversity Panel, labeled with their program of origin: CT = University of Connecticut–Storrs; IA = Iowa State University–Ames; IL = University of Illinois–Urbana/Champaign (Champaign, IL); IN = Purdue University (West Lafayette, IN); MN = University of Minnesota–Twin Cities (Minneapolis, MN); SD = South Dakota State University (Brookings, SD); WI = University of Wisconsin–Madison; Other = all other programs within the panel.

  • View in gallery

    Principal component (PC) analysis of 420 sweet corn inbreds within the Wisconsin Sweet Corn Diversity Panel. Inbreds are labeled with their endosperm mutants’ categorization. aeduwx = amylose-extender: dull: waxy; se = sugary enhancer; sh2 = shrunken2; sh2i = shrunken2 intermediate; su1 = sugary1.

  • View in gallery

    Manhattan plot of susceptibility to Sugarcane mosaic virus genome-wide association study of 420 sweet corn inbreds within the Wisconsin Sweet Corn Diversity Panel. Logarithm of odds value with a 5% Bonferroni threshold identified two loci within chromosome 6 in sweet corn.

  • View in gallery

    Manhattan plot of susceptibility to Sugarcane mosaic virus genome-wide association study of 360 sweet corn inbreds within the Wisconsin Sweet Corn Diversity Panel that do not have the Scm1- IL793a haplotype. Logarithm of odds value with a 5% Bonferroni threshold identified no significant loci.

  • View in gallery

    Linkage disequilibrium (LD) estimates among the 420 sequenced sweet corn inbreds. Mean decay of LD measured as pairwise R2 from the 12,012 high-quality single-nucleotide polymorphism (SNP) markers over physical distance. Different percentile cutoffs are indicated of the distribution of SNP markers among all chromosomes.

  • Baseggio, M., Murray, M., Magallanes-Lundback, M., Kaczmar, N., Chamness, J., Buckler, E.S., Smith, M.E., DellaPenna, D., Tracy, W.F. & Gore, M.A. 2019 Genome-wide association and genomic prediction models of tocochromanols in fresh sweet corn kernels Plant Genome 12 1 1 17 https://doi.org/10.3835/plantgenome2018.06.0038

    • Search Google Scholar
    • Export Citation
  • Baseggio, M., Murray, M., Magallanes-Lundback, M., Kaczmar, N., Chamness, J., Buckler, E.S., Smith, M.E., DellaPenna, D., Tracy, W.F. & Gore, M.A. 2020 Natural variation for carotenoids in fresh kernels is controlled by uncommon variants in sweet corn Plant Genome 13 1 1 19 https://doi.org/10.1002/tpg2.20008

    • Search Google Scholar
    • Export Citation
  • Baseggio, M., Murray, M., Wu, D., Ziegler, G., Kaczmar, N., Chamness, J., Hamilton, J.P., Robin Buell, C., Vatamaniuk, O.K., Buckler, E.S., Smith, M.E., Baxter, I., Tracy, W.F., Gore, M.A. & Danforth, D. 2021 Genome-wide association study reveals an independent genetic basis of zinc and cadmium concentrations in fresh sweet corn kernels BioRxiv 2021.02.19.432009, https://doi.org/10.1101/2021.02.19.432009

    • Search Google Scholar
    • Export Citation
  • Bradbury, P.J., Zhang, Z., Kroon, D.E., Casstevens, T.M., Ramdoss, Y. & Buckler, E.S. 2007 TASSEL: Software for association mapping of complex traits in diverse samples Bioinformatics 23 19 2633 2635 https://doi.org/10.1093/bioinformatics/btm308

    • Search Google Scholar
    • Export Citation
  • Broekema, R.V., Bakker, O.B. & Jonkers, I.H. 2020 A practical view of fine-mapping and gene prioritization in the post-genome-wide association era Open Biol. 10 1 https://doi.org/10.1098/rsob.190221

    • Search Google Scholar
    • Export Citation
  • Charpentier, L.J 1956 Systemic insecticide studies for control of vectors and sugarcane mosaic in Louisiana J. Econ. Entomol. 49 3 413 414 https://doi.org/10.1093/jee/49.3.413

    • Search Google Scholar
    • Export Citation
  • Dußle, C.M., Melchinger, A.E., Kuntze, L., Stork, A. & Lübberstedt, T. 2000 Molecular mapping and gene action of Scm1 and Scm2, two major QTL contributing to SCMV resistance in maize Plant Breed. 119 4 299 303 https://doi.org/10.1046/j.1439-0523.2000.00509.x

    • Search Google Scholar
    • Export Citation
  • Dußle, C.M., Quint, M., Melchinger, A.E., Xu, M.L. & Lübberstedt, T. 2003 Saturation of two chromosome regions conferring resistance to SCMV with SSR and AFLP markers by targeted BSA Theor. Appl. Genet. 106 3 485 493 https://doi.org/10.1007/s00122-002-1107-x

    • Search Google Scholar
    • Export Citation
  • Elshire, R.J., Glaubitz, J.C., Sun, Q., Poland, J.A., Kawamoto, K., Buckler, E.S. & Mitchell, S.E. 2011 A robust, simple genotyping-by-sequencing (GBS) approach for high diversity species PLoS One 6 5 1 10 https://doi.org/10.1371/journal.pone.0019379

    • Search Google Scholar
    • Export Citation
  • Flint-Garcia, S.A., Thornsberry, J.M. & Buckler, E.S. 2003 Structure of linkage disequilibrium in plants Annu. Rev. Plant Biol. 54 357 374 https://doi.org/10.1146/annurev.arplant.54.031902.134907

    • Search Google Scholar
    • Export Citation
  • Fuchs, E. & Grüntzig, M. 1995 Influence of sugarcane mosaic virus (SCMV) and maize dwarf mosaic virus (MDMV) on the growth and yield of two maize varieties J. Plant Dis. Prot. 102 1 44 50 https://www.jstor.org/stable/43386365

    • Search Google Scholar
    • Export Citation
  • Gowda, M., Das, B., Makumbi, D., Babu, R., Semagn, K., Mahuku, G., Olsen, M.S., Bright, J.M., Beyene, Y. & Prasanna, B.M. 2015 Genome-wide association and genomic prediction of resistance to maize lethal necrosis disease in tropical maize germplasm Theor. Appl. Genet. 128 10 1957 1968 https://doi.org/10.1007/s00122-015-2559-0

    • Search Google Scholar
    • Export Citation
  • Gustafson, T.J., de Leon, N., Kaeppler, S.M. & Tracy, W.F. 2018 Genetic analysis of sugarcane mosaic virus resistance in the Wisconsin diversity panel of maize Crop Sci. 58 5 1853 1865 https://doi.org/10.2135/cropsci2017.11.0675

    • Search Google Scholar
    • Export Citation
  • Hamazaki, K., Kajiya-Kanegae, H., Yamasaki, M., Ebana, K., Yabe, S., Nakagawa, H. & Iwata, H. 2020 Choosing the optimal population for a genome-wide association study: A simulation of whole-genome sequences from rice Plant Genome 13 1 1 13 https://doi.org/10.1002/tpg2.20005

    • Search Google Scholar
    • Export Citation
  • Johnson, H., Hall, D.H., Claxton, W. & Ishisaka, W. 1972 Sugarcane mosaic virus tolerance in sweet corn Calif. Agr. 26 10 8 10

  • Jones, M.W., Redinbaugh, M.G. & Louie, R. 2007 The Mdm1 locus and maize resistance to maize dwarf mosaic virus Plant Dis. 91 2 185 190 https://doi.org/10.1094/PDIS-91-2-0185

    • Search Google Scholar
    • Export Citation
  • Knoke, J.K., Louie, R., Anderson, R.J. & Gordon, D.T. 1974 Distribution of MDMV and its aphid vectors in Ohio Phytopathology 64 639 645

  • Kuntze, L., Fuchs, E., Grüntzig, M., Schulz, B., Henning, U., Hohmann, F. & Melchinger, A. 1995 Evaluation of maize inbred Iines for resistance to sugarcane mosaic virus (SCMV) and maize dwarf mosaic virus (MDMV) Agronomie 15 463 467 https://doi.org/10.1051/agro:19950714

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