Abstract
High-throughput molecular markers with high genotyping accuracy will be helpful for genetic analysis, mapping of interesting genes, and rice breeding program. To develop high-throughput and cost-effective molecular markers for Korean japonica rice varieties, which are closely-related genetically, we designed kompetitive allele-specific polymerase chain reaction (KASP) assays from the sequence data of 13 Korean japonica rice varieties. Of the 504 new KASP assays, 371 (73.6%) showed polymorphisms among the tested varieties. In addition to the 400 previously developed KASP markers, this resulted in 771 KASP markers being applicable for Korean japonica rice varieties. These KASP markers were used to map the quantitative trait loci (QTLs) for rice bakanae disease (BD) resistance. From the results of QTL mapping and determination of the mortality rate of BD in two F2:F3 populations, a major QTL, qFfR1-1, and a novel QTL, qFfR6, were revealed on chromosome 1 in the Junam/Nampyeong F2:F3 population and on chromosome 6 in the Saenuri/Nampyeong F2:F3 population, respectively. Further, the insertion/deletion markers in the qFfR1-1 region were developed to select BD-resistant japonica rice varieties. The 771 developed KASP markers will accelerate the molecular breeding in Korean japonica rice varieties, and the detected QTLs will be helpful in identifying candidate genes for BD resistance.
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Key words: High-throughput, KASP marker, Genetic map, Quantitative trait loci, Bakanae disease
INTRODUCTION
Cultivated rice (
Oryza sativa L.) is a major global food staple and is classified into two subspecies,
indica and
japonica. In the two different subspecies, a high genetic diversity has been observed among
indica varieties where-as a low genetic diversity is observed among
japonica varieties (
Glaszmann 1987;
Ni et al. 2002;
Gao and Innan 2008). For rice molecular breeding, populations derived from crosses between
indica and
japonica varieties have been used to create new rice varieties with agronomic traits, such as grain yield and quality. However, despite
japonica rice varieties exhibiting noticeable phenotypic variances in important agronomic traits (
Hori et al. 2017), genetic analyses related to phenotypic variation among
japonica rice varieties have been limited because of their narrow genetic diversity. To resolve this problem in
japonica rice breeding, next-generation sequencing (NGS) has enabled the identification of numerous single nucleotide polymorphisms (SNPs) and insertion/deletions (indels) between highly homologous genomes via resequencing. Subsequently, high-throughput platforms of molecular markers have been rapidly developed for molecular breeding, quantitative trait loci (QTL) mapping, and gene identification in populations derived from crosses between closely-related varieties.
Of the high-throughput genotyping methods, kompetitive allele-specific polymerase chain reaction (KASP) assay is a single-step genotyping technology for the detection of both SNP and indel variants between parents and progenies (
Semagn et al. 2014). Its scalability makes it suitable over a broad range of experimental designs with widely different target loci and sample numbers (
Semagn et al. 2014;
Steele et al. 2018). Furthermore, the KASP marker system has a major advantage of improved cost-effectiveness because it is cheaper than other high-throughput SNP marker technologies (
Yuan et al. 2014). Thus, the KASP marker system has already been applied for improved plant breeding in pigeonpea (
Saxena et al. 2012), chickpea (
Hiremath et al. 2012), and
indica rice (
Pariasca-Tanaka et al. 2015;
Steele et al. 2018).
Rice bakanae disease (BD; “bakanae” means foolish seedling in Japanese) is a seed-borne disease that causes serious problems in rice production, and increasing prevalence of BD has been reported in cultivation areas worldwide (
Gupta et al. 2015;
Matić et al. 2017). BD is a fungal disease caused by
Fusarium fujikuroi (
Gupta et al. 2015). It affects rice plants from the germination stage to the mature stage with the severe infection of rice seeds. Highly infected plants eventually wither, while panicles on surviving plants do not develop any grains, resulting in yield loss (
Desjardins et al. 2000). Thus, healthy seeds must be used to prevent BD in rice cultivation. However, routine management which is based on hot water and fungicides is sometimes ineffective or detrimental to the seeds (
Park et al. 2008). Consequently, the identification of BD genetic resistance in rice varieties has become more critical, and several studies have revealed candidate genes and QTLs governing BD resistance in rice. In RNA sequencing analysis, there were 3,119 differentially expressed genes identified in resistant rice variety Selenio and 5,095 in susceptible variety Dorella. PR1, germin-like proteins, glycoside hydrolases, mitogen-activated protein kinases (MAPKs), and WRKY transcriptional factors were up-regulated in the resistant variety Selenio upon infection with
F. fujikuroi. Furthermore, the up-regulation of chitinases and down-regulation of MAPKs and WRKY transcriptional factors were observed in the susceptible rice variety Dorella (
Matić et al. 2016). Moreover, different expression patterns were identified for the resistant rice variety 93-11 (
indica rice) and the susceptible rice variety Nipponbare (
japonica rice) through comparative transcriptome analysis. The results revealed that certain WRKYs, wall-associated kinase, and MAP3Ks were responsible for the BD resistance of 93-11 and showed that the defense-related genes (WRKYs and microtubule affinity-regulating kinases) on chromosome 1 that are modulated in 93–11 upon infection might play a crucial role in the rice-
F. fujikuroi interaction (
Ji et al. 2016). Using QTL mapping,
Yang et al. (2006) discovered two QTLs, namely,
qB1 on chromosome 1 and
qB10 on chromosome 10, associated with > 13% of the expressed variance for BD resistance via artificial inoculation at the seedling stage using a
japonica/indica double haploid population derived from Chunjiang 06 and TN1.
Hur et al. (2015), using 168 near-isogenic lines derived from a cross between the resistant
indica variety Shingwang and the susceptible
japonica variety Ilpum, identified a major QTL, named
qBK1, on chromosome 1, explaining 65% of the phenotypic variation.
Ji et al. (2018) used 188 F
2 progenies derived from a cross between the resistant
japonica variety Nampyeong and the
japonica susceptible line DongjinAD for QTL mapping and identified a major QTL,
qFfR1, on rice chromosome 1.
Fiyaz et al. (2016) identified three QTLs on chromosome 1 using 168 F
14 recombinant inbred lines (RILs) derived from two
indica rice parents, namely, a highly resistant variety Pusa 1342 and a highly susceptible variety Pusa Basmati 1121. Of them,
qBK1.2 and
qBK1.3 were novel QTLs, while
qBK1.1 was mapped as a major QTL at similar location with
qBK1.
Lee et al. (2018) identified QTLs using the genotypes/phenotypes of 200 RILs and identified locus
qBK1WD on chromosome 1, which conferred BD resistance in the Wonseadaesoo variety. Furthermore, a genome-wide association study with 138
japonica rice varieties revealed two genomic regions,
qBK1_628091 and
qBK4_31750955, associated with BD resistance, located on chromosome 1 and chromosome 4, respectively (
Volante et al. 2017).
To fully elucidate the underlying molecular biological mechanism of BD resistance, it is necessary to identify more resistant genes that can be used for rice breeding. Previously, we analyzed genome sequence data from 13 Korean
japonica rice varieties to reveal 740,566 SNPs. Of them, we selected 1,014 SNP sites, based on a polymorphism information content (PIC) value > 0.4 per 200-kbp interval, to develop 400 KASP markers from 506 KASP assays with the 13 sequenced Korean
japonica rice varieties (
Cheon et al. 2018). In this study, we further developed KASP markers to improve genetic mapping in 13
japonica rice varieties. Those KASP markers were successfully used for the identification of two QTLs conferring BD resistance in
japonica varieties.
MATERIALS AND METHODS
Plant materials and DNA extraction
For the BD bioassay, three Korean
japonica varieties, namely, Nampyeong, Saenuri, and Junam, were used for crossing. Nampyeong is a Korean
japonica variety resistant to BD, while Junam is susceptible, and Saenuri is moderately resistant (
Lee et al. 2011;
Hur et al. 2016). The three parental varieties were crossed in a greenhouse at the National Institute of Agricultural Sciences (NAS) of the RDA (Jeonju, Korea). Subsequently, F
1 and F
2 plants were grown in the NAS experimental field, and F
3 seeds were harvested from each F
2 plant. For KASP marker development, 13 Korean
japonica rice varieties (Samgwang, Saenuri, Odae, Nampyeong, Junam, Ilpum, Hwayeong, Hwacheong, Hiami, Joun, Dongjin, Giho, and Dongan) were grown in a greenhouse at NAS. The genomic DNA was extracted from the leaves of each of the 13 Korean
japonica rice varieties and each of the 188 F
2 progeny from Junam/Nampyeong and Saenuri/Nampyeong using a Plant gDNA Extraction Kit (Biomedic, Bucheon, Korea).
For the development of potential KASP markers based on the SNPs detected among the 13 Korean
japonica rice varieties, SNP sites were selected from each chromosome (
Cheon et al. 2018). The SNP sequence, 100-bp left-flanking sequence, and 100-bp right-flanking sequence of each SNP site were used to design and manufacture two allele-specific forward primers and a common reverse primer (LGC Genomics, London, UK). The markers are listed in
Supplementary Table S1 along with their chromosomal location and primer sequences. The polymerase chain reaction (PCR) profile and composition of KASP reactions are described at
https://www.lgcgroup.com/. KASP amplifications and allelic discriminations were performed using the Nexar system (LGC Douglas Scientific, Alexandria, USA) at the Seed Industry Promotion Center of the Foundation of Agricultural Technology Commercialization and Transfer (Gimje, Korea). An aliquot (0.8 μL) of 2× Master mix, 0.02 μL of 72× KASP assay mix (both LGC Genomics), and 5 ng genomic DNA template were mixed into 1.6 μL of KASP reaction mixture in a 384-well Array Tape. Duplicate reactions were run, and non-template controls were included in each run. KASP amplification was performed using the following thermal cycling profile: 15 minutes at 94°C, a touchdown phase of 10 cycles at 94°C for 20 seconds and at 61°C −55°C (dropping 0.6°C per cycle) for 60 seconds, and 26 cycles at 94°C for 20 seconds and 55°C for 60 seconds (first PCR stage). Next, recycling was performed at three cycles of 9 4°C for 20 seconds and 57°C for 60 seconds (second PCR stage). The recycling was performed twice, and the fluorescence read was taken for KASP genotyping after PCR amplification.
A BD response bioassay was designed based on the
in vitro seedling screening method (
Ji et al. 2018). Briefly, three parents (Junam, Saenuri, and Nampyeong) and F
3 progeny seeds were sterilized in a 2% sodium hypochlorite solution for 30 minutes and washed with sterile distilled water. Then, the sterilized seeds were immersed in sterile distilled water and placed in a tissue culture room at 28°C for 2 days to expedite germination. Thereafter, the seeds were inoculated into a spore solution at a concentration of 1 × 10
6 spores/mL. The spores were harvested from
F. fujikuroi strain CF283 (
Kim et al. 2014) grown on potato dextrose agar media for 1 week in an incubator at 28°C. One day after inoculation, the seeds were planted on solid Murashige and Skoog (MS) medium. The solid MS medium was made as follows: 4.4 g of MS medium and 4 g of Gelrite (both Duchefa Biochemie, Haarlem, The Netherlands) were dissolved per 1 L of distilled water, the pH was adjusted to 5.8, and the solution was sterilized by autoclaving. We planted 20 seeds in an Incu Tissue jar (72 × 72 × 100 mm; SPL Life Sciences Co., Ltd., Pocheon, Korea) containing 100 mL of solid MS media. The Incu Tissue jars were then placed in a tissue culture room at 28°C under a 16:8 hour light/dark cycle. To determine the mortality rate of each F
2 plant derived from the Junam/Nampyeong and Saenuri/Nampyeong cross, 60 F
3 seeds from each F
2 plant were inoculated with
F. fujikuroi strain CF283 by the abovementioned method and were planted in three Incu Tissue jars. At 4 weeks after inoculation, the survived and dead seedlings were individually counted, and the mortality rates were calculated by dividing the number of dead seedlings by the total number of seedlings.
We genotyped 188 F
2 progenies of Saenuri/Nampyeong using the 192 KASP markers that showed polymorphisms between the parental varieties. Based on the genotype data of Saenuri/Nampyeong, a genetic map was constructed using MapDisto 1.7 (
Lorieux 2012) with MapChart software (
Voorrips 2002). The Kosambi function was used for mapping. Based on the constructed genetic map and BD response data, QTL analysis was performed by composite interval mapping (CIM) using Windows QTL Cartographer 2.5 (
Basten et al. 1996). The logarithm of odds (LOD) threshold was calculated through 1000 permutations with a probability level of 0.05. CIM was performed with the default conditions of Windows QTL Cartographer (walk speed: 1.0 centimorgan [cM], CIM model: standard model, control marker number: 5, window size: 10.0 cM, regression method: backward regression). We also used a genetic map that was previously constructed using 205 KASP markers with 188 F
2 progenies of Junam/Nampyeong (
Cheon et al. 2018) for BD resistance QTL mapping in this study.
Primers for
Os01g0601625 and
Os01g0601675 of full-length target genes, including a 5′ upstream region (approximately 2 kb) and 3′ downstream region (approximately 1 kb), were designed based on the
O. sativa Nipponbare reference genome of RAP-DB (
https://rapdb.dna.affrc.go.jp/download/irgsp1.html). Primers of
Os01g0601625 (forward 5′-GCAGGCATGCAAGCTTTGTCGATCACCACCACCGTCCCGAA-3′ and reverse 5′-GGCCAGTGCCAAGCTTTCATCTGCAGGGCCGGCGTTCTTTC-3′) and
Os01g0601675 (forward 5′-GCAGG CATGCAAGCTTATGTGAAGAAAGGCAAGAAAAAACACGCGAACA-3′ and reverse 5′-GGCCAGTGCCAAGCTTGATGAACGAAATGGATCAAAGGTACTGAGAAATG-3′) were used for PCR amplification. Each 25 μl reaction mixture contained 5× PrimeSTAR GXL Buffer, 200 μM dNTPs, and 1.25 U PrimeSTAR GXL DNA Polymerase (Takara Bio Inc., Shiga, Japan) along with 0.2 μM of each primer and 100 ng Nampyeong gDNA template. PCR amplification was performed as follows: preheating at 98°C for 3 minutes; 30 cycles of denaturation at 98°C for 10 seconds and extension at 68°C for 8 minutes. The cloning of fragments was performed using a pCAMBIA1300 vector with an In-Fusion HD Cloning Kit (Clontech, CA, USA), transformed into
Escherichia coli DH5α competent cells, and subsequently sequenced.
To confirm detected indel regions among japonica varieties, 1625IND (forward 5′-AAACAAGTTGGTTGGCGAGCTAC-3′ and reverse 5′-AGATTACGCCTTGGAACCTGTTA-3′) and 1675IND (forward 5′-TTTCTACTAAGTCACGTAGCATGCTCC-3′ and reverse 5′-ATGTTCGTCGTATGCATAGCCAAAC-3′) primers were designed based on Os01g0601625 and Os01g0601675, respectively, and then PCR was performed using the two primer sets with gDNAs of 27 Korean japonica varieties. The PCR conditions were as follows: preheating at 94°C for 3 minutes; 35 cycles of denaturation at 94°C for 40 seconds, annealing at 62°C for 40 seconds, and extension at 72°C for 100 seconds; and a final extension at 72°C for 5 minutes.
RESULTS
Development of KASP markers
Of the 740,566 SNP sites detected from the resequencing data of 13 Korean
japonica rice varieties by
Cheon et al. (2018), 1,014 were chosen for KASP marker development by selecting SNP sites with PIC values > 0.4 per 200 kbp, and 506 of them were used for KASP marker design, converting to 400 KASP markers. In this study, another 504 of the 1,014 SNP sites selected by
Cheon et al. (2018) were newly used for designing additional
japonica KASP markers. The list of the 504 KASP assays in this study is shown in
Supplementary Table S1 and includes primer sequences and chromosomal locations. Of the 504 KASP assays, amplification of seven assays (1.4%) failed in the 13 Korean
japonica varieties. Among the remaining 497 KASP assays, 126 assays (25.0%) showed monomorphism or a heterozygous type and were deemed unusable as DNA markers. The remaining 371 KASP assays (73.6%) showed polymorphisms among the tested varieties (
Table 1,
Supplementary Table S2). In total, 771 KASP markers, including the previous 400 KASP markers, were developed from the resequencing data of the 13 Korean
japonica rice varieties (
Fig. 1). In the annotation of the 771 KASP marker sites, 600 (77.8%) intergenic and 171 (22.2%) genic sites were identified. In the genic regions, we identified 5′ untranslated regions (UTRs), coding sequences (CDSs), introns, 3′ UTRs, and exons (11, 48, 89, 21, and 2 sites, respectively) (
Table 2).
The BD responses of three parental varieties, namely, Junam, Nampyeong, and Saenuri, and F
3 families of Junam/Nampyeong and Saenuri/Nampyeong were evaluated using
in vitro seedling screening. The mortality rates of the three control parental plants were 0% throughout the testing period (
Fig. 2A). Most of the BD-treated Junam plants died, while approximately 90% Nampyeong and 50% Saenuri plants survived at 4 weeks after inoculation (
Fig. 2A). The degree of BD susceptibility of each F
2 plant was evaluated based on the mortality rate measured with the corresponding F
3 progeny seedlings by
in vitro seedling screening at 4 weeks after inoculation. The F
3 mortality rate of Junam/Nampyeong was distributed from 0% to 100% with a peak in the 41%–50% range, whereas the F
3 mortality rate of Saenuri/Nampyeong was distributed from 0% to 90% and showed the maximum in 31%–40% range (
Fig. 2B).
After genotyping 188 F
2 progenies of Saenuri/Nampyeong with 192 KASP markers, 158 (82.3%) KASP markers produced reliable genotype data and were mapped in the genetic map of Saenuri/Nampyeong. The total genetic distance of the constructed genetic map was 1631.9 cM, and the average genetic distance between markers was 11.18 cM (
Supplementary Fig. S1).
QTL mapping using the genetic map and mortality data revealed a major QTL in Junam/Nampyeong on chromosome 1 and a novel QTL in Saenuri/Nampyeong on chromosome 6, which were named
qFfR1-1 and
qFfR6, respectively, meaning “QTL for
F. fujikuroi resistance [chromosome number]” (
Fig. 3,
Table 3).
qFfR1-1 was located at 98.9 cM on chromosome 1 (
Fig. 3A) with an LOD score of 21.4. The additive effect of this QTL was 19.45, and its dominance effect was −7.44, with an
R2 value of 0.499, while the LOD threshold was calculated at 3.7 through 1000 permutations with a probability level of 0.05. The QTL interval at 95% probability was 95.8–100.7 cM (
Table 3). Another QTL,
qFfR6 was located at 61.7 cM on chromosome 6 (
Fig. 3B) with an LOD score of 5.99. The additive effect of this QTL was 9.44, and its dominance effect was −0.74, with an
R2 value of 0.124, while the LOD threshold was calculated at 4.5 through 1000 permutations with a probability level of 0.05. The QTL interval at 95% probability was 57.1–62.7 cM (
Table 3).
Previously, the peak point of the
qFfR1 region in Nampyeong was located at 23.41–23.63 Mb, and 15 putative disease resistance genes were found in the region. Among them, two genes encoding leucine-rich repeat N-terminal domain-containing protein (
Os01g0601625 and
Os01g0601675) are close to the
qFfR1 peak region and were considered the most probable candidate genes for
qFfR1 (
Ji et al. 2018). Because
qFfR1-1, which was located between KJ01_071 and KJ01_079 markers (21.36–24.37 Mb) on chromosome 1 (
Fig. 1 and
3A), overlapped with the
qFfR1 region, two target genes (
Os01g0601625 and
Os01g0601675) were analyzed to detect polymorphisms for the development of a selection marker related to BD-resistant varieties (
Fig. 4).
Os01g0601625 and
Os01g0601675 regions including 5′ upstream and 3′ downstream regions were isolated from gDNA of Nampyeong to develop gene-based DNA markers for the selection of BD-resistant varieties, and the predicted full-lengths of these two regions were approximately 6,247 bp and 5,889 bp, respectively (
Fig. 4A). In comparison with the Nipponbare and Nampyeong sequences, indel regions were detected in the genetic region of
Os01g0601625 and predicted promoter region of
Os01g0601675 (
Fig. 4B). An indel of 216 bp was found in
Os01g0601625, and 1625IND primers were designed to amplify an approximately 374 bp region around the indel in Nampyeong (
Fig. 4C). Also, an indel of 231 bp was detected in
Os01g0601675, and 1675IND sprimers were designed to amplify an approximately 817 bp region around the indel in Nampyeong (
Fig. 4D). When PCR amplifications were performed using the 1625IND and 1675IND primers with 27 Korean
japonica varieties, the band pattern that was observed with Nampyeong was only observed with Saenuri (
Fig. 4E and 4F).
DISCUSSION
We performed polymorphism screening of KASP assays with 13 Korean japonica rice varieties to develop high-throughput DNA markers enabling the genetic analysis of japonica rice varieties. Moreover, to validate the applicability of the developed KASP markers, QTL mapping was carried out with two F2 populations derived from crosses between Korean japonica rice varieties.
Rice varieties derived from crosses between distantly-related varieties (
indica/japonica) have been used more than those derived from crosses between closely-related varieties (
indica/indica or
japonica/japonica) for gene mapping because DNA markers, such as restriction fragment length polymorphisms (RFLP) and simple sequence repeats (SSR), are usually polymorphic between
indica and
japonica. However, those DNA markers have limited polymorphisms among genetically closely related varieties which show remarkable phenotypic difference in agronomically important traits (
Jeong et al. 2015;
Hori et al. 2017). To develop DNA markers for genetic mapping in closely-related
japonica varieties, 13 Korean
japonica varieties were re-sequenced and SNPs were found. These SNPs were converted to KASP markers for high-throughput genotyping in
japonica rice. This resulted in the successful conversion of 506 SNP sites to 400 KASP markers (
Cheon et al. 2018). In this study, we selected 504 additional SNP sites from the closely-related 13 Korean
japonica varieties to develop 371 new KASP markers (
Table 1,
Supplementary Table S2), bringing the total number of KASP markers developed in Korean
japonica rice varieties to 771 (
Table 1). Although KASP assays were designed for 1,010 SNPs identified as polymorphic among the 13
japonica rice genotypes, only 771 markers (76.3%) showed polymorphism in the tested varieties. The remaining 239 markers (23.7%), including those with monomorphism and missing data, did not show polymorphism, indicating that either the SNP detection or KASP assay may have been partly incorrect. For the application of the 771 developed KASP markers, a genetic map of Saenuri/Nampyeong including 158 KASP markers was constructed (
Supplementary Fig. S1). Successful KASP makers have been similarly developed for 1,616 SNPs in pigeonpea, and screening of KASP markers in 24 genotypes, including 23 cultivated species and one wild species (
Cajanus scarabaeoides), defined a set of 1,154 polymorphic markers (71.4%) with a PIC value of 0.04–0.38. Of them, 1,094 (94.8%) showed polymorphisms between the parental lines (
C. cajan ICP 28 ×
C. scarabaeoides ICPW 94) of the reference-mapped population. A comprehensive genetic map comprising 875 KASP markers was developed using high-quality marker genotyping data of 167 F
2 lines from the population (
Saxena et al. 2012). The results of our QTL mapping using KASP markers and an F
2 population derived from the cross between Junam and Nampyeong (
Fig. 3A) were similar to a QTL mapping result with other SNP markers and an F
2 population derived from the cross between DongjinAD and Nampyeong (
Ji et al. 2018). These results indicate that the 771 KASP markers, including the 371 newly-developed markers in this study, enabled genetic mapping of useful QTLs with populations derived from crosses between Korean
japonica rice varieties. Therefore, the KASP makers developed here will be helpful in conducting mapping studies and identifying useful genes present in Korean
japonica rice varieties, ultimately accelerating the molecular breeding of
japonica rice varieties.
In QTL analyses, a major
qFfR1-1 and a novel
qFfR6 were identified from Junam/Nampyeong and Saenuri/Nampyeong F
2:F
3 populations, respectively (
Fig. 3,
Table 3). The QTL
qFfR6, detected on chromosome 6, was novel, as there are no previous reports of QTLs contributing to BD resistance in this region of chromosome 6. The position of the
qFfR1-1 (21.36–24.37 Mb region between markers KJ01_071 and KJ01_079) on chromosome 1 was almost the same as that of three previously identified QTLs for BD resistance:
qBK1 (
Hur et al. 2015),
qBK1.1 (
Fiyaz et al. 2016), and
qFfR1 (
Ji et al. 2018). On rice chromosome 1,
qBK1 was mapped to a 23.20–23.72 Mb region between markers RM8144 and RM11295 with RM9 as the peak marker, and
qBK1.1 and
qFfR1 were mapped to a 23.32–23.34 Mb region between markers RM9 and RM11282 and a 22.56–24.10 Mb region between markers JND01005 and JNC010809, respectively. Additionally,
qBK1 and
qBK1.1 were identified in the Korean
indica variety Shingwang and Indian
indica variety Pusa 1342, respectively, whereas
qFfR1 and
qFfR1-1 were detected in the Korean
japonica variety Nampyeong. Therefore, because these four QTLs on chromosome 1 (
qBK1,
qBK1.1,
qFfR1, and
qFfR1-1) were detected in almost the same region despite the different source varieties, they indicate a QTL that is important to BD resistance. Interestingly,
qFfR1-1 was detected in Junam/Nampyeong but not in Saenuri/Nampyeong despite the use of the same resistant variety, Nampyeong (
Table 3). When confirmation PCR was performed among 27 Korean
japonica rice varieties, including Junam, for the two indel markers 1625IND and 1675IND that had been developed from candidate genes in the
qFfR1-1 region, only Saenuri demonstrated bands of same size as Nampyeong (
Fig. 4E and 4F). This suggests that Saenuri and Nampyeong might have almost the same
qFfR1-1 region on chromosome 1. However, a novel
qFfR6 was detected from the mapped population as conferring moderate resistance/ resistance to BD (
Fig. 3), and these varieties showed a different mortality rate at 4 weeks after artificial infection by
F. fujikuroi (
Fig. 2), suggesting that
qFfR6 may be partly responsible for the difference in BD resistance levels between Saenuri and Nampyeong. Further research will be conducted to elucidate the different phenotypes of these two varieties at a molecular level.
Supplementary Information
ACKNOWLEDGEMENTS
This work was supported by a grant from the Next-Generation BioGreen 21 Program (Plant Molecular Breedsing Center No PJ01323401), Rural Development Administration, Korea.
Fig. 1Construction of a physical map of
japonica genome with 771 KASP markers which include 400 markers from
Cheon et al. (2018), and 371 new KASP markers. Numbers on the left side and letters on the right side of each chromosome (Chr) indicate the physical location (bp) and the name of each marker, respectively. Black and red letters on the right side represent KASP markers developed in previous and present studies, respectively.
Fig. 2Phenotypic differences of parental varieties and F3 families to BD. (A) Plants at 4 weeks after inoculation with BD show the different responses to BD. (B) Distribution of the mortality rate of the F3 families from Junam/Nampyeong and Saenuri/Nampyeong. Solid inverse triangles indicate the average mortality values of the three parents.
Fig. 3A genetic map of KASP markers identified in the F2 families of Junam/Nampyeong (A), Saenuri/Nampyeong (B), and position of QTLs for BD resistance. The numbers on the left side and letters on the right side of each chromosome (Chr) indicate the genetic distance of each marker from the first marker at the top of each chromosome and the name of each marker, respectively. The genetic distance (cM) was calculated by the Kosambi function. Genetic maps of 12 chromosomes are presented in
Fig. S1 and in the previous study (
Cheon et al. 2018). The QTL interval at 95% probability is indicated by the filled black box
.
Fig. 4Detection of indel regions and development of selection markers for BD resistance. (A) PCR amplification of Os01g0601625 and Os01g0601675 regions. (B) Positions of Os01g0601625 and Os01g0601675 regions in the Nipponbare reference genome (IRGSP-1.0) and each indel identified in the Os01g0601625 and Os01g0601675 regions on chromosome 1. The numbers in the upper line indicate the position on chromosome 1 of the Nipponbare reference genome. Gray areas and red boxes in the lower line indicate the predicted gene regions and indel positions, respectively. (C, D) Comparison with Nipponbare (Nip) and Nampyeong (Nam) sequences of Os01g0601625 (C) and Os01g0601675 (D) regions. Arrows indicate the direction and position of primers, and dots indicate the indel regions in each gene. (E, F) PCR band patterns of 1625IND (E) and 1675IND (F) in 27 Korean japonica varieties: 1, Dongjin; 2, DongjinAD; 3, Nampyeong; 4, Hwayeong; 5, Junam; 6, Hopum; 7, Anmi; 8, Ilmi; 9, Hiami; 10, Samgwang; 11, Ungwang; 12, Seolhyangchal; 13, Chilbo; 14, Saenuri; 15, Odae; 16, Joun; 17, Dongan; 18, Geumo; 19, Hwaseong; 20, Nagdong; 21, Giho; 22, Paldal; 23, Jinheung, 24, Jodongji; 25, Damageum; 26, Jungseangeunbangju; 27, Jujido; M, 1 kb Plus DNA ladder.
Table 1Summary of KASP assays from the resequencing data of 13 Korean japonica varieties.
Table 1
|
|
Assay (n) |
Polyz) (n, %) |
Monoy) (n, %) |
Nox) (n, %) |
Reference |
|
13 Korean japonica rice varieties |
1st |
506 |
400 (79.1) |
89 (17.6) |
17 (3.4) |
, Cheon et al. (2018)
|
|
2nd |
504 |
371 (73.6) |
126 (25.0) |
7 (1.4) |
In this study |
|
Total |
1010 |
771 (76.3) |
215 (21.3) |
24 (2.4) |
|
Table 2Summary of the 771 annotated KASP assay sites.
Table 2
|
Regions |
No. |
% |
|
Intergenic |
600 |
77.8 |
|
Genic |
|
5′ UTR |
11 |
1.4 |
|
CDS |
|
NSz)
|
31 |
4.0 |
|
SYy)
|
17 |
2.2 |
|
Intron |
89 |
11.5 |
|
3′ UTR |
21 |
2.7 |
|
Exons |
2 |
0.3 |
Table 3Identification of two QTLs related to BD resistance.
Table 3
|
Cross Combinationz)
|
QTL name |
Chry)
|
Location (cM) |
Closest marker |
QTL intervalx) (cM) |
LOD |
Additive |
Dominant |
R2
|
Reference |
|
J/N |
qFfR1-1
|
1 |
98.9 |
KJ01_075 |
95.8–100.7 |
21.4 |
19.45 |
−7.44 |
0.499 |
qBK1 (Hur et al. 2015) |
|
qBK1.1 (Fiayz et al. 2016) |
|
qFfR1 (Ji et al. 2018) |
|
S/N |
qFfR6
|
6 |
61.7 |
KJ06_055 |
57.1–62.7 |
5.99 |
9.44 |
0.74 |
0.124 |
|
|
KJ06_059 |
References
- Basten CJ, Weir BS, Zeng ZB. 1996. QTL cartographer: a reference manual and tutorial for QTL mapping. Department of Statistics, North Carolina State University. Raleigh.
- Cheon KS, Baek J, Cho YI, Jeong YM, Lee YY, Oh J, et al. 2018. Single nucleotide polymorphism (SNP) discovery and kompetitive allele-specific PCR (KASP) marker development with Korean japonica rice varieties. Plant Breed Biotech. 6: 391-403.
- Desjardins AE, Manandhar HK, Plattner RD, Manandhar GG, Poling SM, Maragos CM. 2000. Fusarium species from Nepalese rice and production of mycotoxins and gibberellic acid by selected species. Appl Environ Microbiol. 66: 1020-1025.
- Fiyaz RA, Yadav AK, Krishnan SG, Ellur RK, Bashyal BM, Grover N, et al. 2016. Mapping quantitative trait loci responsible for resistance to Bakanae disease in rice. Rice (N Y). 9: 45
- Gao LZ, Innan H. 2008. Nonindependent domestication of the two rice subspecies, Oryza sativa ssp. Indica and ssp. Japonica, demonstrated by multilocus microsatellites. Genetics. 179: 965-976.
- Glaszmann JC. 1987. Isozymes and classification of Asian rice varieties. Theor Appl Genet. 74: 21-30.
- Gupta AK, Solanki IS, Bashyal BM, Singh Y, Srivastava K. 2015. Bakanae of rice –An emerging disease in Asia. J Anim Plant Sci. 25: 1499-1514.
- Hiremath PJ, Kumar A, Penmetsa RV, Farmer A, Schlueter JA, Chamarthi SK, et al. 2012. Large-scale development of cost-effective SNP marker assays for diversity assessment and genetic mapping in chickpea and comparative mapping in legumes. Plant Biotechnol J. 10: 716-732.
- Hori K, Yamamoto T, Yano M. 2017. Genetic dissection of agronomically important traits in closely related temperate japonica rice cultivars. Breed Sci. 67: 427-434.
- Hur YJ, Lee SB, Kim TH, Kwon T, Lee JH, Shin DJ, et al. 2015. Mapping of qBK1, a major QTL for bakanae disease resistance in rice. Mol Breed. 35: 78
- Hur YJ, Lee SB, Shin DJ, Kim TH, Cho JH, Han SI, et al. 2016. Screening of rice germplasm for Bakanae disease resistance in rice. Korean J Breed Sci. 48: 22-28.
- Jeong IS, Kim TH, Lee SB, Suh SC, Ji H. 2015. Genome-wide detection of DNA polymorphisms between two Korean japonica rice varieties. Plant Breed Biotech. 3: 208-215.
- Ji H, Kim TH, Lee GS, Kang HJ, Lee SB, Suh S, et al. 2018. Mapping of a major quantitative trait locus for bakanae disease resistance in rice by genome resequencing. Mol Genet Genomics. 293: 579-586.
- Ji Z, Zeng Y, Liang Y, Qian Q, Yang C. 2016. Transcriptomic dissection of the rice–Fusarium fujikuroi interaction by RNA-Seq. Euphytica. 211: 123-137.
- Kim MH, Hur YJ, Lee SB, Kwon T, Hwang UH, Park SK, et al. 2014. Large-scale screening of rice accessions to evaluate resistance to bakanae disease. J Gen Plant Pathol. 80: 408-414.
- Lee SB, Hur YJ, Cho JH, Lee JH, Kim TH, Cho SM, et al. 2018. Molecular mapping of qBK1WD, a major QTL for bakanae disease resistance in rice. Rice (N Y). 11: 3
- Lee YH, Lee MJ, Choi HW, Kim ST, Park JW, Myung IS, et al. 2011. Development of in vitro seedling screening method for selection of resistant rice against Bakanae disease. Res Plant Dis. 17: 288-294.
- Lorieux M. 2012. MapDisto: fast and efficient computation of genetic linkage maps. Mol Breed. 30: 1231-1235.
- Matić S, Bagnresi P, Biselli C, Orrú L, Carneiro GA, Siciliano I, et al. 2016. Comparative transcriptome profiling of resistant and susceptible rice genotypes in response to the seedborne pathogen Fusarium fujikuroi. BMC Genomics. 17: 608
- Matić S, Gullino ML, Spadaro D. 2017. The puzzle of bakanae disease through interactions between Fusarium fujikuroi and rice. Front Biosci (Elite Ed). 9: 333-344.
- Ni J, Colowit PM, Mackill DJ. 2002. Evaluation of genetic diversity in rice subspecies using microsatellite markers. Crop Sci. 42: 601-607.
- Pariasca-Tanaka J, Lorieux M, He C, McCouch S, Thomson MJ, Wissuwa M. 2015. Development of a SNP genotyping panel for detecting polymorphisms in Oryza glaberrima/O. sativa interspecific crosses. Euphytica. 201: 67-78.
- Park WS, Yeh YH, Lee SW, Han SS, Lee JS, Lim CK, et al. 2008. Electron microscopic study for the influence of soaking in hot water and prochloraz solution on spore and mycelium of Fusarium fujikuroi infected in rice seed. Res Plant Dis. 14: 176-181.
- Saxena RK, Penmetsa RV, Upadhyaya HD, Kumar A, Carrasquilla-Garcia N, Schlueter JA, et al. 2012. Large scale development of cost-effective single-nucleotide polymorphism marker assays for genetic mapping in pigeonpea and comparative mapping in legumes. DNA Res. 19: 449-461.
- Semagn K, Babu R, Hearne S, Olsen M. 2014. Single nucleotide polymorphism genotyping using Kompetitive Allele Specific PCR (KASP): overview of the technology and its application in crop improvement. Mol Breed. 33: 1-14.
- Steele KA, Quinton-Tulloch MJ, Amgai RB, Dhakal R, Khatiwada SP, Vyas D, et al. 2018. Accelerating public sector rice breeding with high-density KASP markers derived from whole genome sequencing of indica rice. Mol Breed. 38: 38
- Volante A, Tondelli A, Aragona M, Valente MT, Biselli C, Desiderio F, et al. 2017. Identification of bakanae disease resistance loci in japonica rice through genome wide association study. Rice (N Y). 10: 29
- Voorrips RE. 2002. MapChart: software for the graphical presentation of linkage maps and QTLs. J Hered. 93: 77-78.
- Yang CD, Guo LB, Qian Q, Li XM, Ji ZJ, Ma LY. 2006. Analysis of QTLs for resistance to rice bakanae disease. Chin J Rice Sci. 20: 657-659.
- Yuan J, Wen Z, Gu C, Wang D. 2014. Introduction of high throughput and cost effective SNP genotyping platforms in soybean. Plant Genet Genomics Biotech. 2: 90-94.
