Mol Breeding (2015)35:129 DOI 10.1007/s11032-015-0323-4
Development and validation of SNP-based functional codominant markers for two major disease resistance genes in rice (O. sativa L.) G. Ramkumar . G. D. Prahalada . Sherry Lou Hechanova . Ricky Vinarao . Kshirod K. Jena
Received: 13 November 2014 / Accepted: 8 May 2015 Ó Springer Science+Business Media Dordrecht 2015
Abstract Blast and bacterial leaf blight are major diseases of rice that limit grain yield significantly. These two devastating biotic stresses have to be controlled to meet the demand for 23 % more rice production by 2035 to feed the increasing number of rice consumers. Incorporating appropriate disease resistance genes into elite varieties is considered as the best method to enhance crop resistance. Molecular markers play an important role in multiple gene pyramiding programs to select desirable genotypes with targeted genes. Two major resistance genes, Pita and xa5, for blast and bacterial leaf blight races, respectively, have been used in many gene pyramiding programs. However, simple PCR-based functional codominant markers have not been reported for these genes. Hence, in the present study, time- and costeffective codominant markers for Pita and xa5 have been developed and validated in segregating populations. High-throughput screening has been demonstrated using parallel capillary electrophoresis to
Electronic supplementary material The online version of this article (doi:10.1007/s11032-015-0323-4) contains supplementary material, which is available to authorized users. G. Ramkumar G. D. Prahalada S. L. Hechanova R. Vinarao K. K. Jena (&) Novel Gene Resources Laboratory, Plant Breeding, Genetics, and Biotechnology Division, International Rice Research Institute, DAPO Box 7777, Metro Manila, Philippines e-mail:
[email protected]
replace laborious gel-based electrophoresis. Additionally, the presence of Pita and xa5 alleles was evaluated with 260 diverse rice varieties that were collected from different parts of the world. Of the 260 cultivars tested, 55 were identified with the Pita resistance allele while all the tested cultivars had the susceptible Xa5 allele. The identified Pita allele-derived cultivars can be used as an alternative resistance source for blast disease. The newly developed Pita and xa5 functional markers will help toward tracking the two target genes for blast and bacterial leaf blight resistance in breeding programs. Keywords Rice blast Bacterial leaf blight Codominant marker Pita xa5
Introduction Rice is an important cereal crop that feeds more than half of the world population (Wang and Li 2005). Demand for rice is steadily increasing, as the number of rice consumers is increasing, especially in developing countries (Khush and Jena 2009). However, rice production is severely affected by biotic and abiotic stresses. Among the biotic stresses, rice blast and bacterial leaf blight (BB) are major devastating diseases that limit rice yield significantly (Ou 1985; Mew et al. 1993). Enhancement of host plant resistance is one of the best methods to control these
123
129
Page 2 of 11
two major biotic stresses. Pyramiding of multiple disease resistance genes into elite cultivars could provide durable and broad-spectrum resistance. Among the biotic stresses, blast is the most devastating disease. It is caused by the filamentous ascomycete fungus Magnaporthe oryzae (anamorph Pyricularia oryzae), which leads to multiple social crises. Yield losses from this fungal disease were estimated to be 157 million tons per year (Lin et al. 2007). Nearly 100 resistance genes have been reported and 19 of these genes have been cloned and characterized at the molecular level (Ramkumar et al. 2014). Among the resistance genes, Pita is one of the major genes that was characterized by a map-based cloning strategy (Bryan et al. 2000). Pita is a single-copy gene, located on rice chromosome 12, where a few other blast resistance genes are also located (Jia et al. 2003). The Pita resistance allele has three exons and encodes for 928 amino acids; a single amino acid change (serine instead of alanine) at the 918 amino acid position leads to the susceptible pita allele (Bryan et al. 2000). Since the gene provides broad-spectrum resistance against different blast isolates, it is used to control blast disease worldwide (Lee et al. 2011). Moreover, it is one of the most common genes used in blast gene pyramiding programs (Hittalmani et al. 2000; Hayashi et al. 2006) and allele mining studies (Jia et al. 2003; Wang et al. 2008; Ramkumar et al. 2010a; 2014). BB disease caused by Xanthomonas oryzae pv. oryzae (Xoo) limits rice production up to 81 % (Kumar et al. 2012). Thirty-eight different resistance genes have been identified to combat this serious disease of rice (Suh et al. 2013). Among them, xa5 is one of the major recessive resistance genes that provide a high degree of resistance to a wide range of Xoo races (Suh et al. 2013). The xa5 gene was cloned and characterized by Iyer and McCouch (2004), and it encodes a small subunit of transcription factor IIA. This gene is located on rice chromosome 5 and has four exons and three introns. Two nucleotide substitutions at the second exon lead to one amino acid change (valine to glutamic acid at position 39), which leads to the resistance allele xa5 locus. It has also been observed that the reported amino acid change is consistent among all 27 different resistant rice varieties tested and nine susceptible ones belonging to the Aus-Boro group (Iyer and McCouch 2004). This gene is also used in many bacterial resistance gene
123
Mol Breeding (2015)35:129
pyramiding programs worldwide (Sundaram et al. 2008; 2009; Kottapalli et al. 2010; Suh et al. 2013). Recessive resistance genes are preferable, as those genes provide resistance to different pathogenic races with mechanisms of action different from those of the dominant resistance genes. A high degree of durable resistance could be achieved by using recessive genes in breeding programs (Li et al. 2012). Molecular markers play a significant role in gene pyramiding programs, and the availability of appropriate and functional gene-derived markers facilitates tracking the target alleles in segregating populations. Dominant molecular markers were reported for the blast resistance gene Pita (Jia et al. 2002; Hayashi et al. 2006). However, these markers could not differentiate the homozygous and heterozygous status of the alleles in the segregating populations, which is a significant limitation of the dominant markers. CAPS markers were reported to track BB resistance gene xa5, which was functional and could differentiate the allelic homo-/heterozygous status (Iyer and McCouch 2007). However, genotyping with CAPS markers involves many additional steps, that is, confirmation of success of the PCR amplification, digestion of amplicons with restriction enzymes, and incubation of digestion mixture for a proper enzymatic reaction, and the digested products have to be usually separated in a high percentage of agarose or polyacrylamide gels. These additional steps make the genotyping process costly, time-consuming, and laborious (Ramkumar et al. 2010b). High-throughput screening for traits is preferred in the molecular marker development process. Screening of PCR products is one of the crucial steps in genotyping samples. Conventional agarose/acrylamide gel-based electrophoresis is linked with considerable time, cost, and labor. Moreover, this method of electrophoresis is associated with mutagens and carcinogens such as ethidium bromide and acrylamide. Hence, the demonstrated applicability of markers using recent technology such as parallel capillary electrophoresis is appropriate to avoid gel-based genotyping. Information regarding the number of genes present/ absent in a given rice cultivar is often lacking, which is critical for rice breeding programs. It is often difficult to screen plant materials in the field because of quarantine restrictions that inhibit the exchange of different M. oryzae races (Wang et al. 2007). However, the availability of functional markers helps
Mol Breeding (2015)35:129
immensely to screen a wide range of diverse plants to detect the presence of particular genes with less cost and effort (Ramkumar et al. 2011). Based on the status of Pita and xa5 resistance genes and the available molecular markers, this study was designed with the following objectives: 1. Development of simple PCR-based functional codominant molecular markers for Pita and xa5; 2. validation of accuracy and usability of the markers in crosssegregating populations; 3. applicability of the markers in high-throughput genotyping; and 4. analysis of Pita and xa5 distribution in a wide range of diverse rice cultivars collected from different parts of the world. The newly developed Pita and xa5 functional markers will help to track the favorable alleles in disease resistance breeding programs, while the identified 55 Pita alleles can be used as new sources for blast resistance.
Materials and methods Plant materials The plant materials used in this study include segregating populations for validating the accuracy and specificity of newly developed Pita and xa5 functional markers and a panel of highly diverse plant materials to analyze the distribution of candidate genes. A BC1F2 segregating population, derived from a cross between IR95440-1-26-1-4 (possessing Pita-gene-derived blast resistance) and IR72 (susceptible to blast), was used to validate the newly developed Pita marker. Another BC2F2 segregating population, derived from a cross between IR90751-1-14-1-2 (possessing xa5-derived BB resistance) and IR72 (susceptible to BB), was used to validate the newly developed xa5 markers. These materials were obtained from the Plant Breeding, Genetics, and Biotechnology Division of the International Rice Research Institute (IRRI), Los Ban˜os, Laguna, Philippines. Highly diverse cultivars that were collected from different parts of the world have been obtained from the International Rice Genebank collection of IRRI (Supplementary Table 1). Seed materials were germinated in seedbeds, and 21-day-old seedlings were transplanted in the field. DNA was extracted using the standard protocol with minor modifications (Dellaporta et al. 1983).
Page 3 of 11
129
Evaluation for BB resistance A BC2F2 population derived from IR90751-1-14-1-2 and IR72 and the diversity panel were screened with Xoo race 9A (PX0339) (incompatible with xa5). Taichung Native 1 (TN 1) was included as a susceptible check. The overnight-grown race 9A culture (incompatible with xa5) was diluted into 1 9 109 cfu/ ml and was used to inoculate 8–10 leaves of 60-dayold plants by clip inoculation (Kauffman et al. 1973). The lesions were scored 14 days after inoculation (IRRI, 2006). The experiments were performed in two randomized replications. Development of allele-specific functional markers The Pita resistance allelic sequence (Acc. No. AF207842) was obtained from NCBI (http://www. ncbi.nlm.nih.gov/) and compared with the Nipponbare genome sequence. The xa5 resistance and susceptible allelic sequences (Acc. No. AY643716 and AY643717, respectively) were aligned using the bioinformatic tool MEGA (Tamura et al. 2011). The functional polymorphic regions of the Pita and xa5 alleles as reported by Bryan et al. (2000) and Iyer and McCouch (2004), respectively, were targeted to design primers by following the strategy as illustrated in Fig. 1. In brief, external forward and external reverse primers are not allele-specific and common for both (resistance and susceptible) alleles; internal forward and internal reverse primers are allele-specific (Table 1). In the case of the Pita SNP marker, the common band of 759 bp was amplified irrespective of the Pita/pita allele. The internal forward primer and external reverse primer produce a 302-bp amplicon if the resistance (Pita) allele is present, and a 500-bp amplicon is produced by the external forward primer and internal reverse primer if the susceptible (pita) allele is present. In the case of the xa5 SNP marker, primers were designed in such a way that the common band (873 bp) was produced, irrespective of the (xa5/ Xa5) alleles, while 338- and 577-bp amplicons were produced for xa5 and Xa5 alleles, respectively. Care was taken that the size difference between the amplicons was at least 100 bp, so that the amplicons could be separated in a low-percentage (*1 %) agarose gel. The PCR conditions were standardized to differentiate the resistance and susceptible alleles with different annealing temperature by gradient PCR. The Pita
123
129
Page 4 of 11
Mol Breeding (2015)35:129
Fig. 1 Primer designing strategy to develop codominant molecular markers for Pita and xa5 genes. External forward and external reverse primers are not allele-specific and common for both (resistance and susceptible) alleles; internal forward and internal reverse primers are allele-specific. In case of Pita, a common band (759 bp) will be amplified irrespective of the Pita/pita allele. The internal forward primer and external reverse primer will produce a 302-bp amplicon if a resistance
(Pita) allele is present, and a 500-bp amplicon is produced by the external forward primer and internal reverse primer if a susceptible (pita) allele is present. For xa5, primers were designed in such a way that the common band (873 bp) will be produced, irrespective of the (xa5/Xa5) alleles, while 338- and 577-bp amplicons will be produced for xa5 and Xa5 alleles, respectively
Table 1 Primers used to develop Pita and xa5 molecular markers S. no.
Primer name
Primer sequence
Annealing temperature (°C)
Role
1
Pita Ext F
TGCGCAAAGAATCGTCGCTGC
62
Pita external forward
2
Pita Ext R
TCTTTGATCCAAGTGTTAGGGCC
62
Pita external reverse
3
Pita Int F
CCGTGGCTTCTATCTTTACCTG
62
Pita internal forward
4
Pita Int R
AGTCAGGTTGAAGATGCATAGA
62
Pita internal reverse
5
xa5 Ext F
CGGATAGCAGCATTTCCAAGAG
57
xa5 external forward
6 7
xa5 Ext R xa5 Int F
GGAGAAATTACATCACAAGCGC GCTCGCCATTCAAGTTCTTGAG
57 57
xa5 external reverse xa5 internal forward
8
xa5 Int R
GTAGATACCTTATCAAACTGGA
57
xa5 internal reverse
and xa5 markers’ PCR was performed in a 15 ll PCR mix containing 1X buffer (20 mM Tris–HCl (pH 8.8 at 25 °C), 10 mM (NH4)2SO4, 10 mM KCl, 0.1 mg/ mL BSA, 0.1 % (v/v) Triton X-100, 2 mM MgSO4, 0.25 mM of each dNTPs, 5 pM of each primer, and 1 U of DNA polymerase (Invitrogen, USA). Template quantity was *50 ng of genomic DNA per PCR. PCR was performed with the following thermal profile: initial denaturation at 94 °C for 5 min followed by 35
123
cycles of denaturation at 94 °C for 30 s, primer annealing at 62 °C (for Pita)/57 °C (for xa5) for 30 s, and extension at 72 °C for 1 min, followed by final extension at 72 °C for 7 min. Comparative genotyping of gene-specific markers Genotyping data of the newly developed Pita SNP marker were compared with those of the Pita
Mol Breeding (2015)35:129
dominant marker (Jia et al. 2002). The new xa5 marker genotypic results were also compared with those of the xa5 CAPS marker 10603.T10Dw (Suh et al. 2013) and phenotypic results of the BC2F2 population. The BC2F2 DNA samples were amplified with 10603.T10Dw primers, and the amplicons were digested with the RsaI restriction enzyme and incubated for 3 h; the digested products were resolved through 8 % polyacrylamide/3 % agarose gel electrophoresis. Application in high-throughput genotyping To test the applicability of newly developed Pita and xa5 markers in high-throughput genotyping, and to lower the cost and time of the laborious gel electrophoresis process, the amplicons were analyzed with Fragment Analyzer (Ames, Iowa, USA), which works by parallel capillary electrophoresis. The experiment was performed following the manufacturer’s instructions, with 35 and 1500 bp as lower and upper limits, respectively.
Results Based on the Pita- and xa5-gene-derived resistance and susceptible allelic sequence information, primers were designed targeting the reported functional polymorphism of the genes (Table 1) and PCR conditions of those primers have been standardized. The SNP marker for the Pita gene could differentiate the parental genotypes (IR95440-1-26-1-4 and IR72). To check the accuracy and reliability of the newly developed Pita marker, a BC1F2 population derived from crosses among IR95440-1-26-1-4 and IR72 was screened with the new Pita allele-specific marker. The genotyping analysis revealed that, among the 200 genotypes analyzed, 48 had Pita alleles, 56 had pita alleles, and 96 had Pita/pita (heterozygous) alleles (Fig. 2a). In order to confirm the results of the newly developed Pita marker, the same samples were screened with the Pita dominant marker (Jia et al. 2002), and the genotyping results of the dominant Pita marker showed agreement with the new Pita marker. However, the dominant marker could not differentiate the homozygous/ heterozygous conditions of the Pita allele, and, for the susceptible pita allele, the marker did not produce any amplicons (Supplementary Fig. 1).
Page 5 of 11
129
The newly developed xa5 SNP marker could differentiate the parental genotypes, that is, IR90751-1-14-1-2 and IR72. The xa5 marker was also validated in a BC2F2 segregating population (derived from crosses of IR90751-1-14-1-2 and IR72). The xa5 allele-specific marker identified 54 Xa5, 97 Xa5/xa5 (heterozygous), and 49 xa5 alleles from the BC2F2 population of 200 genotypes (Fig. 2b). A comparison of genotype and phenotype data revealed a perfect co-segregation among them. To confirm the accuracy of the xa5 marker further, the BC2F2 samples were screened with the reported CAPS marker (10603.T10Dw; Suh et al. 2013) and the results of 10603.T10Dw perfectly matched with the newly developed xa5 marker.
Applicability in high-throughput genotyping The applicability of the newly developed Pita and xa5 markers was checked by analyzing the amplicons with Fragment Analyzer (Ames, Iowa, USA) to replace the cumbersome gel-based electrophoresis as an optional choice. This experiment clearly distinguished the specific resistance and susceptible amplicons. In the case of the Pita-resistant genotype, the Fragment Analyzer detected two peaks: one peak for the resistance allele-specific band (302 bp) and the other one for the common band (759 bp). In the susceptible genotype, it detected two bands again, but of different sizes, one of 500 bp (susceptible allele-specific) and the other a common band. For the heterozygous genotype, it detected three peaks: one each for the resistance and susceptible allele-specific band and another for a common band (Fig. 3). In the case of xa5 also, the Fragment Analyzer was used and could differentiate the resistance and susceptible-specific amplicons clearly. In the resistant genotypes, it detected two different amplicons of 338 and 873 bp band sizes, which are resistance allelespecific and a common band, respectively. In the case of susceptible samples, it also detected two different amplicons of different sizes: a 577-bp band (susceptible allele-specific band) and the other a common band. For heterozygous samples, all three peaks (for resistance, susceptible, and common bands) were found at the respective bp lengths (Fig. 3). The analysis was performed with five replications, and similar results were obtained in all the replications.
123
129
Page 6 of 11
Mol Breeding (2015)35:129
Fig. 2 Amplification pattern of newly developed Pita and xa5 gene markers in segregating populations. a A set of BC1F2 populations derived from crosses among IR95440-1-26-1-4 (possessing Pita and resistant to blast) and IR72 (susceptible to blast) was screened with the new Pita marker. 1 IR95440-1-261-4, 2 IR72. b The new xa5 marker was also validated in a
BC2F2 segregating population derived from crosses of IR907511-14-1-2 (possessing xa5; resistant to bacterial blight) and IR72 (susceptible to bacterial blight). 1 IR72, 2 IR90751-1-14-1-2. RR homozygous resistant, Rr heterozygous allele, S homozygous susceptible
Screening of diverse plant materials
agreement with genotype data. However, 68 cultivars showed resistance against race 9A, while the marker revealed a susceptible Xa5 allele for those genotypes. The resistance of these exceptional cultivars might be due to the presence of BB resistance genes other than the xa5 gene.
A set of 260 highly diverse materials collected from 32 different countries were screened using the standardized new Pita and xa5 markers. Among the diverse cultivars, 55 showed the presence of the Pita resistance allele (Table 2), which can be used as an alternative source of the Pita gene for blast resistance, while 205 showed the susceptible pita allele (Supplementary Table 1). Though the highest number of entries was collected from the Philippines (36), the highest number of 13 Pita-derived resistant entries was found in the germplasm from China (Supplementary Fig. 2). This was followed by six Pita-resistant cultivars from Vietnam (Supplementary Table 2). In order to confirm the genotyping data, the Pita dominant marker was also used for genotyping and the results were in agreement with those of the newly developed Pita marker. In the case of xa5, other than the known resistant controls, interestingly, all the 260 cultivars showed susceptible Xa5 alleles with the new marker. The diverse genotypes were screened with race 9A (incompatible with xa5 and Xa21) to know their phenotypic reaction to BB resistance. Most of the phenotypic reactions of the cultivars were in
123
Discussion Biotic stresses caused by fungal and bacterial diseases are serious threats to rice crop production and productivity. Among the biotic stresses, blast and BB are the most devastating diseases that lead to severe yield and economic losses (Ou 1985; Mew et al. 1993; Lin et al. 2007; Kumar et al. 2012). Enhancement of host plant resistance by means of incorporating resistance genes is the best strategy to control biotic stresses. The incorporation of major resistance genes will enhance the durability and degree of resistance of the crop, in which molecular markers play a vital role for the rapid selection of genotypes having the targeted genes (Jena and Mackill 2008). The Pita gene is one of the major blast resistance genes as it provides resistance against a wide range of blast isolates (Bryan et al. 2000; Jia et al. 2003), and
Mol Breeding (2015)35:129
Page 7 of 11
129
Fig. 3 Applicability of new Pita and xa5 markers in highthroughput genotyping. The experiment was performed with Fragment Analyzer (Ames, USA) by following the manufacturer’s
instructions, with 35 and 1500 bp as lower and upper limits, respectively. R = resistant allele; S = susceptible allele
hence, this gene has been used in many resistance breeding programs for more than a decade (Hittalmani et al. 2000; Hayashi et al. 2006). However, to select the favorable Pita gene-specific allele in segregating breeding populations, appropriate codominant functional molecular markers are not yet reported even though the gene has been cloned and characterized. A fluorescence primer-based non-functional marker (targeting the intronic region of the allele) was reported (Jia et al. 2004), which needs expensive primers and chemicals and a costly instrument to resolve single nucleotide differences in amplicon length (Wang et al. 2007), which may not be practical and affordable for most of the laboratories in developing countries. Though normal PCR-based dominant markers are reported, those markers are not appropriate for a molecular breeding program as the dominant marker cannot differentiate homozygous and heterozygous Pita alleles (Jia et al. 2002; Hayashi et al. 2006). For instance, in a segregating population, if the target is
the homozygous Pita allele, it is not possible with a dominant marker to select the Pita/Pita allele accurately. As the phenotypic reaction also cannot differentiate the heterozygous and homozygous condition of a dominant gene, selection of a Pita/pita genotype leads to additional time and cost to achieve the target (Pita/Pita). Moreover, for a susceptible genome, the marker would not produce any amplicons, which could lead to ambiguity of PCR failure (Wang et al. 2007). Hence, the development of a codominant Pita marker is imperative to enhance molecular breeding efficiency. The BB resistance gene xa5 is also one of the most used resistance genes in rice breeding programs. The recessive resistance gene is preferable in gene pyramiding programs, as it provides a wide range of resistance to different races by a different mechanism (Li et al. 2012). The availability of an appropriate marker system enhances the efficiency of a markerassisted breeding program. Though CAPS markers
123
129
Page 8 of 11
Mol Breeding (2015)35:129
Table 2 List of diverse cultivars possessing Pi-ta resistance allele S. no.
IRGC no.
Variety name
Source country
S. no.
IRGC no.
Variety name
Source country
1
121034
Lal Bagdar
Bangladesh
29
121771
Jamajigi
Mali
2
121035
Lalbajam
Bangladesh
30
122093
IR22/Kulu
Philippines
3
121099
Ray Jazaykayz
Bhutan
31
121591
Peta/Tangkai Rotan
Philippines
4
121701
91-385
Bhutan
32
120984
China 1039 DWF MUT//IR3186864-2-3-3-3/Pinidua
Philippines
5
121161
Zalcha
Bhutan
33
120987
IR64 (WH)/Aday Sel//3IR64
Philippines
6
120972
Hong Zui Zao
China
34
121753
IR4432-53-33/PTB 33//IR36
Philippines
7
121111
San Ri Qi
China
35
121819
Safari
Portugal
8
121040
Liu Xu
China
36
121854
Was 207-B-B-3-1-1
Senegal
9
120861
Ai Lan Ke 1110
China
37
121849
Was 183-B-6-2-3
Senegal
10
121163
Zao Shou 691-11
China
38
121846
Was 169-B-B-4-2-1
Senegal
11 12
121145 120912
Tung Chiu Ai China 98-45-1::IRGC 1598-1
China China
39 40
121848 122284
Was 182-B-1-1 Was 170-B-B-1-1
Senegal Senegal
13
120970
Hong Mi Dong Mao Zhan
China
41
121011
Karayal
Sri Lanka
14
120925
Da Nuo
China
42
121153
Wanni Dahanala
Sri Lanka
15
121164
Zi Gan Nan Gu
China
43
117525
Madael
Sri Lanka
16
117280
Zhenshan 97B
China
44
121094
Race
Sri Lanka
17
121162
Zao Shao Zhan
China
45
121059
Motta Samba
Sri Lanka
18 19
117881 120979
Shai Kuh P 738-137-4-1/ P 723-6-3-1
China Ecuador
46 47
117848 121019
Peh Kuh Khao Daw Tai
Taiwan Thailand
20
120998
Jariyu
India
48
122179
Nam Sagui
Thailand
21
122258
Vasistha/Mahsuri
India
49
121662
Daw Leuang Nam Pueng 29-314::IRGC 24301-1
Thailand
22
117817
Garikasannavari
India
50
121642
Som Cau 70 A
Vietnam
23
117501
JC 92
India
51
117682
Chau
Vietnam
24
121418
Madhuri::IRGC 67730-1
India
52
117478
Gie 57
Vietnam
25
117880
Seratoes Hari
Indonesia
53
117589
Tetep
Vietnam
26
121990
Botramaitso
Madagascar
54
121599
Bat DO::IRGC 7014-1
Vietnam
27
121136
Telovolana
Madagascar
55
121919
Khau Muong Pieng::IRGC 78333-1
Vietnam
28
121811
Rojofotsy 693
Madagascar
have been reported (Iyer and McCouch 2007; Suh et al. 2013), they need laborious additional steps in comparison with simple PCR-based markers, such as confirmation of PCR successive amplification and digestion with a restriction enzyme of the specific amplicons with incubation of 1–3 h for proper digestion of the amplicons, which requires more cost and time.
123
To overcome these limitations of using Pita and xa5 markers, we have designed PCR-based codominant markers, targeting the functional polymorphism of those genes. Also, care was taken to have at least a 100-bp difference between the amplicons so that those amplicons could be separated in low-percentage agarose gels in less time. The newly developed molecular markers for Pita and xa5 genes differentiate
Mol Breeding (2015)35:129
the resistance and susceptible alleles and provide more details on homozygous and heterozygous status of the alleles without any restriction digestion. The Pita marker, which targeted the well-established polymorphic SNP, was validated by comparing with the reported dominant marker, which revealed that both marker data were in agreement with each other (Bryan et al. 2000; Jia et al. 2002). The xa5 marker has been validated in the segregating population, which revealed that the genotype and phenotype data perfectly co-segregated. In addition, co-segregation of the newly developed marker for the xa5 gene and CAPS marker (10603.T10Dw; Suh et al. 2013) was confirmed, which revealed that the newly developed marker is accurate and reliable to use in molecular breeding applications. High-throughput marker technology is one of the preferable choices in molecular marker-assisted rice breeding programs. The reduction in time, cost, and cumbersome molecular activity can lead to highthroughput screening of the marker. Gel electrophoresis is a time-consuming, cumbersome, and laborious job, which is vulnerable to manual error. Recent technology such as capillary electrophoresis facilitates screening of amplicons without gel electrophoresis. This method is cheaper and saves significant time and energy compared with gel electrophoresis in the long run. We have demonstrated the applicability of the newly developed markers in recent technology— capillary electrophoresis, using Fragment Analyzer (Ames, Iowa, USA). This experiment clearly differentiated the resistance and susceptible alleles and the homozygous and heterozygous status of the alleles. The rice varieties, which were collected from 32 different countries, were screened with the newly developed markers as well as available markers for Pita and xa5 genes. This experiment not only revealed the agreement among the new and available markers but also revealed 55 genotypes as new sources of Pita resistance alleles. In a previous study, with Pita resistance alleles evaluated in 141 rice varieties using Pita dominant markers, 20 rice accessions possessed Pita resistance alleles (Wang et al. 2007). However, the authors used four pairs of markers to screen the Pita allele-specific to resistance and susceptibility independently. In the present study, a wide range of rice varieties was assessed with a single codominant marker set that detected the presence of Pita and pita alleles.
Page 9 of 11
129
Among the 260 diverse rice varieties, the highest number of entries (36) came from the Philippines, followed by China (32) and India (28). The Pita alleles were identified from 55 different cultivars of 15 different countries out of 260 cultivars from 32 countries. The highest number of Pita resistance alleles was found from cultivars collected from China (13), followed by Vietnam (6) and the Philippines (5). Among the analyzed cultivars, it was revealed that, though the Pita resistance alleles were accumulated in Asian countries, the Pita alleles were distributed throughout the world, including Africa and South America (Table 2; Supplementary Fig. 2). This experiment indicates that the Pita gene might have originated long ago in Asia and migrated to different parts of the world. As it is found in a wide range of cultivars, it should be an important resistance gene that may provide a wide spectrum of resistance against various blast isolates (Wang et al. 2008). Moreover, the identified novel Pitaresistant cultivars can be validated and used in blast resistance breeding programs, and also these novel Pita alleles open the way for an intensive Pita allele mining strategy (Ramkumar et al. 2014). The evaluation of xa5 gene-specific alleles reveals that all the diverse materials have the susceptible Xa5 allele, indicating either its limited distribution or that it originated recently. Earlier studies reported that the xa5 resistance allele is limited to the Aus-Boro group, originating from Bangladesh and Nepal (Garris et al. 2003; Iyer and McCouch 2007). Phenotypic screening of diverse cultivars for BB resistance revealed that most of the cultivars’ phenotype reaction was in agreement with the genotype of the respective cultivars. However, 68 cultivars showed resistance against race 9A, while the marker revealed those cultivars to have the susceptible Xa5 allele. This can be explained by the resistance of those exceptional cultivars perhaps coming from other BB resistance genes such as Xa21, as race 9A is incompatible with Xa21. Moreover, the disease reaction pattern of race 9A with recently identified known resistance genes is unknown (IRRI 2006). In addition, as the cultivars are highly diverse, there is a strong possibility that they may possess novel kinds of genes with disease resistance to BB pathotypes. Although the Pita and xa5 genes are used in many gene pyramiding breeding programs, simple and appropriate PCR-based codominant markers have not been reported until this study. Unlike the available dominant and CAPS markers, the newly developed
123
129
Page 10 of 11
Mol Breeding (2015)35:129
PCR-based codominant Pita and xa5 markers could differentiate resistant and susceptible genotypes without any further restriction digestion and they provide more details on the homozygous and heterozygous status of the alleles. Our study has validated the newly developed molecular markers in segregating populations, and high-throughput genotyping has also demonstrated using capillary electrophoresis. The presence of Pita alleles in diverse rice varieties was analyzed, and novel Pita resistance sources were revealed. The cultivars possessing the identified Pitagene-specific allele can be used in resistance breeding programs. The identified cultivars with BB resistance to race 9A can be analyzed further to identify novel BB resistance genes. We strongly believe that the newly developed Pita and xa5 markers will immensely help molecular breeders to track the targeted Pita and xa5 gene-specific alleles using a more convenient and simpler method in blast and bacterial leaf blight resistance breeding programs. Acknowledgments We are grateful to the Global Rice Science Partnership (GRiSP) program of IRRI for financially supporting this project. We thank Bill Hardy for editing the manuscript. Conflict of interest
The authors declare no conflict of interest.
References Bryan GT, Wu KS, Farrall L, Jia Y, Hershey HP, McAdams SA, Faulk KN, Donaldson GK, Tarchini R, Valent B (2000) A single amino acid difference distinguishes resistant and susceptible alleles of the rice blast resistance gene Pi-ta. Plant Cell 12:2033–2045 Dellaporta SL, Wood J, Hicks JB (1983) A plant DNA minipreparation: version II. Plant Mol Biol Rep 1:19–21 Garris AJ, McCouch SR, Kresovich S (2003) Population structure and its effect on haplotype diversity and linkage disequilibrium surrounding the xa5 locus of rice (Oryza sativa L.). Genetics 165:759–769 Hayashi K, Yoshida H, Ashikawa I (2006) Development of PCR-based allele-specific and InDel marker sets for nine rice blast resistance genes. Theor Appl Genet 113:251–260 Hittalmani S, Parco A, Mew TV, Zeigler RS, Huang N (2000) Fine mapping and DNA marker-assisted pyramiding of the three major genes for blast resistance in rice. Theor Appl Genet 100:1121–1128 IRRI (2006) Stress and disease tolerance. http://www. knowledgebank.irri.org/ricebreedingcourse/Breeding_for_ disease_resistance_Blight.htm. Accessed 28 August 2014 Iyer AS, McCouch SR (2004) The rice bacterial blight resistance gene xa5 encodes a novel form of disease resistance. Mol Plant-Microbe Interact 17:1348–1354
123
Iyer AS, McCouch SR (2007) Functional markers for xa5-mediated resistance in rice (Oryza sativa L.). Mol Breed 19:291–296 Jena KK, Mackill DJ (2008) Molecular markers and their use in marker-assisted selection in rice. Crop Sci 48:1266–1276 Jia Y, Wang Z, Singh P (2002) Development of dominant rice blast Pi-ta resistance gene markers. Crop Sci 42:2145–2149 Jia Y, Bryan GT, Farrall L, Valent B (2003) Natural variation at the Pi-ta rice blast resistance locus. Phytopathology 93:1452–1459 Jia Y, Redus M, Wang Z, Rutger JN (2004) Development of a SNLP marker from the Pi-ta blast resistance gene by triprimer PCR. Euphytica 138:97–105 Kauffman HE, Reddy APK, Hsieh SPY, Merca SD (1973) An improved technique for evaluating resistance of rice varieties to Xanthomonas oryzae. Plant Dis Rep 57:537–541 Khush G, Jena KK (2009) Current status and future prospects for research on blast resistance in rice (Oryza sativa L.). In: Wang GL, Valent B (eds) Advances in genetics, genomics and control of rice blast disease. Springer, New York, pp 1–10 Kottapalli KR, Narasu ML, Jena KK (2010) Effective strategy for pyramiding three bacterial blight resistance genes into fine grain rice cultivar, Samba Mahsuri, using sequence tagged site markers. Biotechnol Lett 32:989–996 Kumar PN, Sujatha K, Laha GS, Rao KS, Mishra B, Viraktamath BC, Hari Y, Reddy CS, Balachandran SM, Ram T, Madhav MS, Rani NS, Neeraja CN, Reddy GA, Shaik H, Sundaram RM (2012) Identification and fine-mapping of Xa33, a novel gene for resistance to Xanthomonas oryzae pv. oryzae. Phytopathology 102:222–228 Lee S, Jia Y, Jia M, Gealy DR, Olsen KM, Caicedo AL (2011) Molecular evolution of the rice blast resistance gene Pi-ta in invasive weedy rice in the USA. PLoS One 6:e26260 Li C, Wei J, Lin Y, Chen H (2012) Gene silencing using the recessive rice bacterial blight resistance gene xa13 as a new paradigm in plant breeding. Plant Cell Rep 31:851–862 Lin F, Chen S, Que ZQ, Wang L, Liu XQ, Pan QH (2007) The blast resistance gene Pi37 encodes a nucleotide binding site-leucine-rich repeat protein and is a member of a resistance gene cluster on rice chromosome 1. Genetics 177:1871–1880 Mew T, Alvarez A, Leach J, Swings J (1993) Focus on bacterial blight of rice. Plant Dis 77:5–12 Ou SH (1985) Rice diseases, 2nd edn. Surrey Commonwealth Mycological Institute, Kew, p 380 Ramkumar G, Sakthivel K, Sundaram RM, Neeraja CN, Balachandran SM, Rani NS, Viraktamath BC, Madhav MS (2010a) Allele mining in crops: prospects and potentials. Biotechnol Adv 28:451–461 Ramkumar G, Sivaranjani AKP, Pandey MK, Sakthivel K, Rani NS, Sudarshan I, Prasad GSV, Neeraja CN, Sundaram RM, Viraktamath BC, Madhav MS (2010b) Development of a PCR-based SNP marker system for effective selection of kernel length and kernel elongation in rice. Mol Breed 26:735–740 Ramkumar G, Srinivasarao K, Mohan KM, Sudarshan I, Sivaranjani AKP, Gopalakrishna K, Neeraja CN, Balachandran SM, Sundaram RM, Prasad MS, Rani NS, Prasad AMR, Viraktamath BC, Madhav MS (2011) Development and validation of functional marker targeting an InDel in
Mol Breeding (2015)35:129 the major rice blast disease resistance gene Pi54 (Pikh). Mol Breed 27:129–135 Ramkumar G, Madhav MS, Devi SJSR, Manimaran P, Mohan KM, Prasad MS, Balachandran SM, Neeraja CN, Sundaram RM, Viraktamath BC (2014) Nucleotide diversity of Pita, a major blast resistance gene and identification of its minimal promoter. Gene 546:250–256. doi:10.1016/j.gene. 2014.06.001 Suh JP, Jeung JU, Noh TH, Cho YC, Park SH, Park HS, Shin MS, Kim CK, Jena KK (2013) Development of breeding lines with three pyramided resistance genes that confer broad-spectrum bacterial blight resistance and their molecular analysis in rice. Rice 6:5. doi:10.1186/1939-8433-6-5 Sundaram RM, Vishnupriya MR, Biradar SK, Laha GS, Reddy GA, Rani NS, Sarma NP, Sonti RV (2008) Marker assisted introgression of bacterial blight resistance in Samba Mahsuri, an elite indica rice variety. Euphytica 160:411–422 Sundaram RM, Vishnupriya MR, Laha GS, Rani NS, Rao PS, Balachandran SM, Reddy GA, Sarma NP, Sonti RV (2009)
Page 11 of 11
129
Introduction of bacterial blight resistance into Triguna, a high yielding, mid-early duration rice variety. Biotechnol J 4:400–407 Tamura K, Peterson D, Peterson N, Stecher G, Nei M, Kumar S (2011) MEGA5: molecular evolutionary genetics analysis using maximum likelihood, evolutionary distance, and maximum parsimony methods. Mol Biol Evol 28:2731–2739 Wang Y, Li J (2005) The plant architecture of rice (Oryza sativa). Plant Mol Biol 59:75–84 Wang Z, Jia Y, Rutger JN, Xia Y (2007) Rapid survey for presence of a blast resistance gene Pi-ta in rice cultivars using the dominant DNA markers derived from portions of the Pi-ta gene. Plant Breed 126:36–42 Wang X, Jia Y, Shu QY, Wu D (2008) Haplotype diversity at the Pi-ta locus in cultivated rice and its wild relatives. Phytopathology 98:1305–1311
123
