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Review

An Overview of Rice QTLs Associated with Disease Resistance to Three Major Rice Diseases: Blast, Sheath Blight, and Bacterial Panicle Blight

by
Seyedeh Soheila Zarbafi
1,2 and
Jong Hyun Ham
1,*
1
Department of Plant Pathology and Crop Physiology, Louisiana State University Agricultural Center, Baton Rouge, LA 70803, USA
2
Department of Agronomy and Plant Breeding, Faculty of Agricultural Sciences, University of Guilan, Rasht 41635-1314, Iran
*
Author to whom correspondence should be addressed.
Agronomy 2019, 9(4), 177; https://doi.org/10.3390/agronomy9040177
Submission received: 15 March 2019 / Revised: 29 March 2019 / Accepted: 2 April 2019 / Published: 6 April 2019
(This article belongs to the Special Issue Genetics and Genomics of Disease Resistance in Crops)
Versions Notes

Abstract

:
Rice (Oryza sativa L.) is one of the most important crops that are produced as human food, directly feeding people more than any other crop. Hence, it is important to increase the yield potential of rice through improving the disease resistance to prevailing rice diseases. Blast caused by the fungus Magnaporthe oryzae, sheath blight caused by the fungus Rhizoctonia solani Kühn, and bacterial panicle blight caused by the bacteria Burkholderia glumae and B. gladioli are serious rice diseases in many rice-producing regions. In spite of the chronic damages from these major diseases, the quantitative resistance to each of them is not known very well and any available disease-resistant varieties are rare or not stable. Although gene-for-gene resistance that is mediated by an R-Avr interaction has been intensively studied for blast, quantitative (or horizontal) resistance to a broad spectrum of races in M. oryzae is still poorly understood. Identification of the quantitative trait loci (QTLs) related to these diseases and using marker technology can facilitate marker-assisted selection to screen resistant traits in individual resources, which could ultimately lead to the development of novel disease-resistant rice varieties. This article is a summary of identified QTLs that are associated with rice diseases, including blast, sheath blight, and bacterial panicle blight that can be used in breeding programs.

1. Introduction

Rice (Oryza sativa L.) is one of the most important crops in the world, which feeds more than half of the world population and provides 20% of the energy that is required for humans [1]. A mediocre projection of the United Nations predicted that the human population would reach 10 billion by the mid-21st century, which would require an approximately 70% increase of food production by 2050 [2]. Due to the importance of rice in global food supply, it is critical to promote rice production through improvements and innovations in agronomic practices and rice varieties [3]. Reinforcing rice varieties against common diseases can be an effective breeding method that ultimately affects the quantitative and qualitative performance of rice. Fungi, bacteria, viruses, and nematodes cause more than 70 diseases of rice [4], and global losses from various pests in rice were reported to be around 30% [1]. Using varieties with modified agronomic characteristics can help in increasing rice yield with little additional inputs, such as fertilizers and pesticides. However, it should be noted that important agronomic characteristics of crops, such as yield and stress tolerance, are controlled by numerous quantitative trait loci (QTLs) and they are also strongly influenced by the environment [5]. Although environmental factors are important for rice disease resistance, not much information has been reported regarding this issue [6,7].
Qualitative or single-gene traits are strongly affected by single locus changes, but traits, such as yield, quality, and some of the traits associated with disease resistance are multi-gene or multi-locus traits and are known as quantitative or polygenic traits. A QTL is an intra-genomic region that contains gene(s) that are associated with a specific quantitative trait, and it is a factor that links the molecular markers to a quantitative phenotype in a mapping population. The improvement of crops will not be achieved without their genetic information and examination of its relation to agronomic traits [8,9,10]. Great progress was made in identifying QTLs for important traits of crops during the 1980′s through the development of useful molecular markers [10]. Tracking complex traits by examining the relationship between phenotypic diversity and molecular markers facilitated their control sites in the genome [10]. Identification and use of resistant varieties against disease and examination of resistance genes associated with known resistance loci allows for the identification of QTLs that are associated with resistance and, in general, increases the information regarding the resistance mechanism [7,11,12,13,14]. Researchers use linkage maps through different statistical methods, such as interval mapping, composite interval mapping, single marker analysis, etc., to identify QTLs. Through these methods, the relationship between markers and phenotypic data is investigated. QTL mapping is important for marker-assisted selection (MAS), because it identifies the molecular markers that are associated with a specific trait [15]. The amount of phenotypic variance that is described by most of the identified QTLs is generally low. In addition, due to the lack of information about the responsible gene(s) within a QTL, the molecular mechanisms underlying the functions of identified QTLs on given phenotypes are still unknown in most cases. Regarding the limited influence of individual QTL, in general, pyramiding of multiple QTLs from different origins is necessary for significant improvement of certain traits [16]. Gene pyramiding increases the resistance to blast disease in rice [17]. This article summarizes and presents the QTLs that are associated with three important rice diseases: blast, sheath blight, and bacterial panicle blight.

2. Rice Disease Resistance to Blast

Among the biotic stresses of rice [18,19], blast disease that is caused by the fungus Magnaporthe oryzae can decrease rice yield up to 70–80% in most rice growing areas in the world [20,21]. Actually, this disease affects a large proportion of cultivated rice, which can feed 60 million people per year and makes a loss over 70 billion dollars of economic value [22].
Magnaporthe oryzae is also called as Magnaporthe grisea or Pyricularia oryzae. Magnaporthe includes two different species; one infects crabgrass (Digitaria sangunalis L.), being called M. grisea, and the other infects rice and millet being determined as M. oryzae. Actually, the rice blast is a disease that is caused by M. oryzae [23]. This fungal pathogen is a haploid filamentous Ascomycete that contains seven chromosomes and its genome size is about 40 Mb [24]. The conidia of M. oryzae is 20–22 × 10–12 µm and the life cycle of this fungus has two types of reproduction, including sexual and asexual [25].

2.1. Epidemiology and Symptoms of Blast Disease

The blast pathogen is seed-borne, which makes its management difficult [26]. This pathogen was determined as the most harmful fungus in the word in 2012 due to its economic and scientific importance. This appellation of the pathogen indicates its damaging nature and influence on the feeding of the world’s population. Besides, the scientific significance of the pathogen is noteworthy, because a model system to study the plant-fungal interactions has been established with rice and M. oryzae [27].
Blast can affect all parts of plant but most damage has been observed in the leaf area. This disease is seen as diamond-shaped lesions, in which the centers of lesions are gray and white. Additionally, the disease has also been observed at the surface of the panicles, causing the seeds to not be filled [28]. Size, color, and shape of spots represent the age of spots, environmental conditions, and resistance level of varieties [29].
Asexual spore can cause rice blast disease when placed on the leaf surface and attached to the cuticle. The attachment of the spore is through the distribution of a sticky material in the apical section of spore [30]. Dew drops is an important factor in transferring conidiospores from a plant to another plant. Conidiospore germination also requires water [30,31]. In such circumstances, spore germination will start very rapidly and a polarized germ tube will be established approximately two hours after landing on the surface of the leaf. The amount of germ tube extension is so short (15–30 µm) and its appearance is typically through one apical cell [31]. This procedure is called hooking and this is actually a recognition phase before appressorium expansion. Actually, the substratum features are investigated before appressorium development [31]. Hard and hydrophobic surface of the level and lack of nutrients are the factors that impose a positive effect on appressorium development [32].

2.2. Conducive Environmental Conditions for Blast Disease

Conidia in mature lesions grow in conditions with a relative humidity greater than 89% and maximum sporulation occurs at 20 °C [33]. Water is an important factor for conidial growth of M. grisea. More conidia release is directly related to water droplets on the leaf surface [34]. The low temperature at about 15–20 °C is not a good condition for blast lesion development, and blast lesions were seen in the same plants into higher temperature, at about 25–30 °C [4]. Wind is one of the climate factors that has the potential to reduce the damage of rice blast disease in two ways. The first way is to reduce the possibility of sticking the spores of the fungus to the leaf surface, and the second way is helping to dry the leaf surface and reduce deposition time of dew drops on the leaf surface, which is an important factor in disease infection [35,36].
When M. grisea attaches through its conidium to the surface of a rice leaf, the blast disease will emerge. Blast disease creates a great deal of damage in cold temperatures with high moisture, whereas direct sunlight is a barrier to germination [29]. Disease level will increase in cloudy weather. Dew is also an important factor in increasing the blast disease. Snow and cold weather of winter cannot destroy the conidia of the fungus. The remainder components of infected host are the main source of elementary inoculum, which causes epidemic [37]. According to Harmon and Latin [38], the survival of fungus was decreased in winter and the life cycle of fungus begins through its sporulation on plant remainder components in spring. A wide range of plants is the host of this fungal pathogen, which contributes to the wide spreading of the pathogen [39].
Fukuoka et al. [17] reported that the resistances granted by each of the four QTL alleles (pi21, Pi34, qBR4-2, and qBR12-1) were exclusively sensitive to environmental conditions, indicating that the effects of the QTLs should be studied in conjunction with environmental factors.

2.3. QTLs of Rice Associated with the Disease Resistance to Blast

Accurate information regarding the QTL profiles is very beneficial in sustainable crop production. Of course, the use of synthetic fungicides is the most effective way of controlling blast disease, but the farmers in developing countries do not use them due to the high cost. On the other hand, there are some reasons that can limit the usage of the chemicals, including the devastating effects that could have on the environment. Additionally, the excessive use of chemicals leads to the emergence of resistant strains due to selection pressure. Although many biological control agents have shown to be effective under laboratory, field, and greenhouse conditions, successful cases in a commercial scale are still limited [40,41,42]. Regarding these circumstances, the use of resistant varieties is the most effective approach in managing blast disease. Changes in the cultivation system, such as changing in planting times, amount and time of fertilization, and water management, can also be effective [43,44,45,46].
As mentioned above, use of resistant varieties is the best and most economical way of managing blast disease. Numerous resistant varieties have been developed for major rice diseases. However, in the case of blast disease, resistant varieties have been very short-lived due to the diversity of physiological races [47]. The prevalence and spread of previously rare pathotypes or the development of new pathotypes are the reasons for the failure of rice resistance to blast disease. Therefore, it is imperative to develop more stable resistant varieties that are based on quantitative disease resistance traits [48].
The selection of resistant rice lines for blast disease through their phenotypic characteristics is a very difficult and costly process, because it takes a lot of time and needs large research farms. One of the effective and efficient methods for identifying resistant lines is to use highly consistent DNA markers that are associated with resistant genes [49]. This marker assisted selection (MAS) is used to identify new rice lines that carry resistance genes in many breeding programs [50].
Improving the resistance to blast disease is a main objective in rice breeding [51]. Introgression of multiple resistance genes into elite lines is an effective way to develop rice varieties with durable disease resistance [49]. Qualitative resistance that is dependent on a single gene is not very stable, but it would give great outcomes in the improvement of disease resistance if multiple resistance genes are properly selected and simultaneously introduced [52,53]. Both qualitative (complete) and quantitative (partial) resistance to blast disease has been identified in different rice germplasm [29]. In general, quantitative resistance is effective to a broad range of pathogen races and more stable than qualitative resistance. However, the identification of QTLs for quantitative resistance without regarding the effect of major resistance genes is very complex. Low resolution of QTL mapping and a lack of knowledge regarding fundamental genetic control are the barriers to accumulation of quantitative resistance [54]. Nevertheless, the improvement of quantitative resistance is an ideal approach, because it is wider in scope (broad-spectrum or horizontal) or non-specific and more stable [55,56].
Although hundreds of QTLs that are associated with quantitative resistance to blast disease have been identified, and most of them have not been molecularly characterized well so far [57,58]. This is mostly due to the partial effect of each QTL and the interference of complex genetic and environmental factors in experimental conditions [17]. Genetic studies of the rice-M. oryzae interaction have identified almost 100 race-specific resistance genes and over 350 QTLs on the entire rice genome, except chromosome 3 [59,60,61,62,63,64].
This article does not cover all of those resistance genes, which can be found elsewhere, including the following review article [62]. Among the QTLs that are associated with the quantitative resistance to blast, twenty-five QTLs have been molecularly characterized by an identification of the responsible genes (Table 1) [65,66].
Each of these resistant genes is effective to a series of blast pathogen races, so gene pyramiding is still a useful method for breeding new resistant varieties [110]. A number of studies show a wide range of resistance of Piz-5 that is combined with Pi1 to blast pathogens [111,112]. Thippeswamy et al. [113] also reported that the CO39 pyramid carrying Pi-1 and Piz-5 genes showed higher resistance in comparison with Pi-1 or Piz-5.
Nucleotide-binding sites (NBS) and leucine rich repeats (LRR) are two factors encoded in many genes for race-specific resistance to pathogens. The discovery of these two factors has prompted rapid progress in the manipulation of major resistance genes to control crop disease. However, the disease resistance that is conferred by this type of resistance gene is often vulnerable to rapidly changing pathogen populations. Approximately 500 NBS-LRR sequences have been identified in the rice plant [114]. The molecular recognition of the pathogen avirulence (Avr) proteins by NBS-LRR proteins either directly or indirectly result in the gene for gene resistance, which accounts for most cases of the race-specific resistance of rice to blast. The LRR domain is often involved in the molecular recognition process. Mutations in Avr proteins that cause an avoidance of molecular recognition is a reason to break the resistance. The NBS-LRR proteins are classified into two groups that are based on their amino-terminal sequences, CC-NBS-LRR that is plentiful and diverse in monocots, and TIR-NBS-LRR that is not yet identified in monocots [115,116].

3. Rice Disease Resistance to Sheath Blight

Sheath blight is another important disease of rice, which is caused by Rhizoctonia solani Kühn, a soil-borne necrotrophic fungus [117]. This disease was first reported in Japan in 1910 [118], but it had been negligible in the United States until the 1970s, when the soybean-rice rotation planting started. It seems that the observed blight in the aerial part of soybean plant, which is also caused by R. solani, was a major cause of increasing the sheath blight disease of rice [119].

3.1. Epidemiology and Symptoms of Sheath Blight Disease

In severe infection, most leaves of the plant may be damaged. Sclerotia are formed within the lesions and their size and color depend on soil factors, rice varieties, and environmental conditions [120]. The primary symptoms of the disease are lesions in the lower part of the plant and, under favorable environmental conditions, including low sunlight, humidity equal or more than 95%, and a temperature between 28 °C to 32 °C, the pathogen spreads to the upper parts of the plant through the use of runner hyphae. Lesions cause stem softness and ultimately stem lodging. Lesions may surround the entire abaxial and adaxial leaf sheath surfaces and the stem of the leaf. Through forming infection cushions, the pathogen attaches appressoria on the leaf sheath [117,121,122]. Sheath blight disease in the beginning of panicle existence or flowering can reduce the weight of total seeds by reducing the percentage of spikelets, which results in a significant reduction in grain yield [123]. The intense lodging that is caused by sheath blight epidemics blocks the translocation of water, food, and carbohydrates via the xylem and phloem canals, which ultimately affects the filling of seeds [122].
To know the structure of resistance and build resistance systems in rice varieties, knowledge regarding pathogen population structure and diversity is very important. R. solani is a plant pathogenic fungus and its host range is very wide. R. solani can cause various symptoms on the sheath and the blade of plant leaf. Symptoms may also appear in other aerial parts of the rice [124]. The virulence, physiology, and appearance of the disease are different in a similar pathogen population. This pathogen usually overwinters in the form of mycelium or sclerotia in the soil or plant residues [125,126]. The lesions of this disease are observed on the leaf sheath from the water level or above the water level of the rice field. Lesion color is apparently greenish grey, and the lesion shape is diverse (circular to rectangular or oval to ovoid). The lesions are separated from each other with narrow brown margins. The rate of lesion expansion is intense and it also spreads to leaf blade, panicles, and seeds [124]. The interaction between rice and R. solani has not been studied much at a molecular level, but is thought to be similar to that of other pathosystems, which involve various defense mechanisms of the host and the counteracts of the pathogen against them [127,128,129].

3.2. Conducive Environmental Conditions for Sheath Blight and Benefits of Sheath Blight Resistance

High plant density, closed canopy, and high levels of nitrogen fertilizer promote the disease progression of sheath blight [130], as well as high levels of pathogen in the soil increase the disease pressure. Premature infections, damp environments, and the cultivation of sensitive varieties are other reasons for the exacerbation of the disease [131]. Some researchers showed that farm soil type can also affect the severity of the disease [132,133]. The environmental benefits of resistance to sheath blight disease include two critical aspects. The first aspect is the effect on yield potential to improve the input efficiency per each output unit and reduce the environmental impacts. The second aspect is the reducing of the detrimental effects of fungicides on the environment. According to the simulations, the production of resistant varieties to sheath blight has the potential to reduce global warming, eutrophication, carcinogenicity, ecotoxicity, fossil fuels, and ozone deficiency [134].

3.3. QTLs of Rice Associated with the Disease Resistance to Sheath Blight

Different degrees of susceptibility to sheath blight disease have been observed in rice varieties under field conditions [135,136]. Wild rice accessions seem to be a potential source of resistant genes to sheath blight disease, especially because only a limited number of resistant loci have been observed for sheath blight disease among commercial rice varieties [137]. Unlike the situation for blast, there are few rice varieties that are resistant to sheath blight, which is due to the lack of resistance resources [138].
Sheath blight had not been a limiting disease for rice before semi-dwarf varieties were planted. However, sheath blight became one of the most damaging diseases that affects the quality and quantity of rice when semi-dwarf varieties were c dominantly ultivated. In contrast to the case for blast, major R genes (nor Avr genes of the pathogen) that are associated with sheath blight resistance have not been identified in rice varieties. Nevertheless, genes with minor and major effects have been identified in various rice germplasm, some of which are closely linked to molecular markers [139]. In a study of 6000 rice varieties from 40 countries, those varieties had partial resistance, but none of the varieties had a major gene for resistance to sheath blight [140].
Plant height and heading date are the morphological characteristics of rice that are associated with the resistance to sheath blight. Only one of the six QTLs associated with sheath blight resistance is independent of plant height [141,142,143]. Sheath blight-related QTLs are commonly found in areas of the rice genome where the QTLs that are associated with heading date are located [144,145]. When the varieties with different maturity are planted, so that their heading time is the same, the difference in their resistance level will be smaller [119].
A wide range of susceptibility/resistance to sheath blight is present among the rice varieties in the world, from high susceptibility to moderate but stable resistance. Researchers have been able to commercially produce resistant varieties using breeding programs and manipulated resistant genes, but so far these efforts have been ineffective [146]. It may be because multiple genes (or QTLs) control the sheath blight resistance [144]. Mapping populations that are derived from relatively resistant species as a parent can be used to identify new QTLs related to sheath blight resistance. These new QTLs can be combined with known resistant QTLs to generate rice varieties with higher resistance to sheath blight [147,148].
More than 200 QTLs associated with sheath blight resistance have been identified while using different populations, such as double haploid lines (DHLs), recombinant inbred lines (RILs), near-isogenic introgression lines (NILs), and backcross populations [143,144,145,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171]. Table 2 lists these QTLs.
Li et al. [143] identified the first QTL that was associated with sheath blight while using RFLP markers in field conditions. In this experiment, 255 F4 bulked lines that were derived from a cross between Teqing (resistant variety) and Lemont (susceptible variety) were evaluated for their sheath blight resistance phenotypes for two years, and six QTLs were identified in six chromosomes (chromosomes 2, 3, 4, 8, 9, and 12), which explained 60% and 47% of genotypic and phenotypic variation, respectively [143].
In another study that was performed by Pan et al. [150], three QTLs related to sheath blight disease were identified on chromosomes 2, 3, and 7. A F2 clonal population derived from a cross of Jasmin 85 and Lemont was used and the source of the resistance allele for all the QTLs was from Jasmin 85. The Rh-7 (sheath blight resistant related QTL) was located close to the interval of HD7 (heading date related QTL), but other Rh-2 and Rh-3 were located far from of the QTLs that were related to heading date [150].
During a study investigating the positions of QTLs that are related to sheath blight resistance, six QTLs were identified by using 128 lines of the F2 clonal population from a cross between Jasmin 85 and Lemont, which are resistant and susceptible to sheath blight disease, respectively. qSB-2 and qSB-11 were two QTLs on chromosomes 2 and 11, which were found in both years of experiment (1997 and 1998). Jasmin 85 was the donor parent of resistance for qSB-2, qSB-3, qSB-7, and qSB-9-2, but qSB-9-1 and qSB-11 were attributed to the parent Lemont. The amount of phenotypic variation explained by the QTLs were in the range of 9.8 to 31.2% belonged to qSB-9-1 and qSB-11, respectively [151].
The population of 240 F11–12 recombinant inbred lines from a cross between Minghui as resistant parent and Zhenshan as susceptible parent was used to identify the QTLs related to sheath blight disease resistance. qSB-5 and qSB-9 were the two QTLs found through this research and explained 9.5–10.5 and 6.9–10.1% of phenotypic variance, respectively. The source of resistant allele in both QTLs was from Minghui [152].
Kunihiro et al. [153] identified four QTLs on chromosomes 2, 3, 7, and 11 by using a double haploid population from a cross of Zhai Ye Qing 8 and Jingxi (resistant and susceptible varieties, respectively). The source of resistant allele was from the resistant parent in all QTLs and the amount of phenotypic variation explained by the QTLs was in the range of 2.4 to 4.3% [153].
Some studies developed special markers that are linked to sheath blight resistance genes by tagging and mapping methods, which can be used for marker assisted selection (MAS) of major sheath blight resistance genes in rice breeding. Che et al. [154] used a population of 1030 F2 lines derived from a cross of 4011 (resistant variety) and Xiangzaoxian19 (susceptible variety) to identify the molecular markers linked to the resistance trait. In that study, three RFLP markers converted from the RAPD and AFLP markers (OPN-162000, AT:MCTA230 and E-AT:M-CAC120) and two SSR markers (RM164320 and RM39300) were linked to the resistance gene Rsb 1 on chromosome 5. The linkage distances of these molecular markers to Rsb 1 were 1.6 cM (E-AT:M-CAC120, OPN-162000, and RM39300), 9.9 cM (AT:MCTA230), and 15.2 cM (RM164320) [154]. The three molecular markers that are tightly linked to the resistance gene (E-AT:M-CAC120, OPN-162000, and RM39300) will be particularly useful, not only the map-based cloning of Rsb 1, but also the MAS of sheath blight resistant lines in rice breeding.
Sato et al. [155] used 60 BC1F1 lines that were derived from a cross of Hinohikari/WSS2//Hinohikari for mapping QTLs related to sheath blight. The resistant variety WSS2 was crossed with the susceptible variety Hinohikari to make a F1 population. Subsequently, the F1 population was back-crossed with Hinohikari to make a BC1F1 population. In that study, two QTLs were identified on chromosomes 3 and 12, and their contributions to the sheath blight resistance phenotypic variations were 19.4 and 12.9%, respectively. Moreover, sheath blight resistance exhibited significant levels of correlation with culm length and heading date [155].
In research that was conducted by Pinson et al. [144], 15 QTLs related to sheath blight were identified by using a recombinant inbred line (RIL) population that was derived from a cross of Teqing (resistant variety) and Lemont (susceptible variety). Among the QTLs identified, six QTLs (qSB-2, qSB-3-1, qSB-3-2, qSB-4-2, qSB-8-1, and qSB-9) had been found in previous researches and showed overlap in genomic location with previously reported QTLs. A QTL was detected on chromosome 7, but it was unable to be confirmed as qSB-7, which was identified in previous researches [143,151], due to gaps on chromosome preventing precise mapping [144]. The remaining eight QTLs on chromosomes 1, 4, 5, 6, 8, 10, and 12 were identified as novel QTLs [144]. Thus, this study not only confirmed the previously reported QTLs related to sheath blight, but also identified new ones.
Two QTLs on chromosomes 9 and 11 were identified by using a 115 F2 clonal population that was derived from a cross of Teqing (resistant parent) and Lemont (susceptible parent), which explained 11.8-22.2 and 12.5–12.3% of phenotypic variance in sheath blight resistance, respectively. The source of resistant allele was from Teqing in both QTLs [156].
qSB-11LE is a QTL located on chromosome 11, which was identified in different researches and different populations for sheath blight study [157,160]. Zuo et al. [157] used a BC4F1 population that was derived from a cross of Lemont and Teqing (susceptible and resistant varieties, respectively) to identify this QTL on chromosome 11. Zuo et al. [172] investigated the breeding potential of this QTL by using near isogenic lines (NILs) of Lemont, which carries qSB-11LE. According to the results of their research, the resistant allele of this QTL had a notable and additive effect on the sheath blight resistance. After transferring the QTL by the same research group, six O. indica varieties, six BC1F1 populations, and one BC2F1 population (derived from the backcross between Lemont and six O. indica rice varieties) were investigated [172]. The results showed significant increase of sheath blight resistance depending on the presence of qSB-11LE, indicating the probable lack of this favorable allele in O. indica varieties and the importance of the QTL in breeding programs for the improvement of sheath blight resistance, and thus the usefulness of the molecular markers close to the QTL region in MAS [172].
Li et al. [158] used four populations of BC2F5 introgression lines (ILs) from the crosses among IR64/Tarom Molaii, Teqing/Tarom Molaii, IR64/Binam, and Teqing/Binam to identify QTLs that are related to sheath blight resistance and relative lesion height. Four populations derived from the cross between two elite varieties (IR64 and Teqing) as recurrent parents and two tall varieties (Tarom Molaii and Binam) as donors. In that study, four to six QTLs were identified from each IL population and, overall, nine and 11 QTLs were related to sheath blight resistance and relative lesion height traits, respectively [158].
Liu et al. [159] performed a genetic research with 250 F5 RILs that were derived from a cross of Jasmin 85 and Lemont, which are sheath blight resistant and susceptible varieties, respectively. In that study, two different assays, including micro-chamber and mist-chamber, were conducted in greenhouse conditions and, overall, 10 QTLs were identified on chromosomes 1, 2, 3, 5, 6, and 9 through this two sheath blight assays. The QTLs qShB1 and qShB9-2 were identified in two assays and both of them were attributed to the Jasmin 85 parent. The amount of phenotypic variation that was explained by qShB9-2 was the highest (24.3% and 27.2% in the micro-chamber and the mist-chamber conditions, respectively). The sources of resistant allele in qShB2-1, qShB2-2, qShB3-1, qShB3-2, and qShB3-3 were from Jasmin 85, while those in qShB5, qShB6, and qShB9-1 were from Lemont [159].
In a study by Sharma et al. [145], four QTLs were identified by using 279 lines of F2:3 from a cross of the rice varieties Rosemont and Pecos, which are relatively susceptible and resistant to sheath blight, respectively. This population was planted in two years, and two procedures, including interval mapping and composite interval mapping, were used to map the loci for sheath blight resistance. The resistant parent Pecos was attributed to the resistant alleles of three QTLs on chromosomes 1, 3, and 9, while the source of QTL that was located on chromosome 2 was from the susceptible parent Rosemont. The QTLs that were identified in that study explained 5.8 to 36.4% of phenotypic variation of sheath blight resistance in the interval mapping procedure, and 2.4 to 35% in the composite interval mapping procedure [145].
Channamallikarjuna et al. [160] identified eight QTLs on chromosomes 1, 3, 7, 8, 9, and 11 by using a population of 127 F2:10 RILs from a cross of Tetep (resistant variety) and HP2216 (susceptible variety). This study was performed in a four-year period at three locations while using two QTL mapping approaches, including single marker analysis and composite interval mapping. Among the identified QTLs, qSBR11-1 on the long arm of chromosome 11 was the only QTL that was stable in three years (2004, 2005, and 2007). Another F2 population that was derived from a cross of Tetep and Pusa Basmati-1 was used to validate the markers (RM1233 to RM224) that were linked to the sheath blight resistance QTL. The great genetic variation observed at the RM224 locus indicated the existence of allele related to sheath blight resistance [160].
Fu et al. [161] identified 28 QTLs for sheath blight resistance in two different environments by using a population of 121 RILs from a cross of HH1B (susceptible variety) and RSB03 (partially resistant variety). The QTLs were identified on nine chromosomes (i.e., chromosomes 1, 2, 4, 5, 6, 7, 8, 9, and 12), among which 11, 5, 3, 6, and 3 QTLs were related to disease rating, lesion length, lesion height, relative lesion length, and relative lesion height, respectively [161]. Most of the QTLs were specific to the given environments and previously reported by other research groups, and only two QTLs, including qSBR2-2 and qSBR9, were newly identified in that study [161].
Xu et al. [162] used a population of 251 double haploid lines (DHLs) that were derived from a cross of Baiyeqiu (resistant variety) and Maybelle (susceptible variety) for identifying QTLs controlling sheath blight resistance. The experiment was performed for two years (2007–2008) and four QTLs (i.e., qShB1, qShB2, qShB3, and qShB5) were identified on chromosomes 1, 2, 3, and 5, respectively. Among the four QTLs, just qShB1 was the only QTL that was identified in both years and it explained 8.9% and 13.2% of the phenotypic variation in 2007 and 2008, respectively. The sources of resistant allele in qShB1, qShB3, and qShB5 were from Baiyeqiu because of the positive additive effect and in qShB2 were from Maybelle, because of the negative additive effect [162].
Identifying resistant alleles for sheath blight disease is an excellent approach for marker-assisted breeding by pyramiding the alleles in a variety. Jia et al. [163] identified ten marker loci on seven chromosomes 1, 2, 4, 5, 6, 8, and 11, which were significantly related to sheath blight resistance, using 217 sub-core entries from the USDA Rice Core Collection through association mapping. RM11229 and RM7203 were two novel markers that were associated with sheath blight resistance. However, other eight QTLs were quite near to the QTLs identified in previous studies. The amount of phenotypic variation explained by the QTLs were in the range of 1.9 to 9.5% [163]. The names of QTLs were not mentioned in the article, and only the names of markers were expressed.
For investigation of the QTLs that were related to sheath blight, Nelson et al. [164] evaluated the disease traits of 197 DHL derived from a cross between MCR10277 and Cocodrie (resistant and susceptible verity, respectively) in both the field and the greenhouse. Overall, four QTLs related to sheath blight were identified in that study, and the resistant alleles of these QTLs were all from MCR10277 and explained 47% of genetic variation in the field assay [164].
As wild rice species tend to be resistant to sheath blight, the wild rice species O. nivara was used as a resistant parent in a cross with the susceptible US variety Bengal [165]. The first population, named ‘wild-1′, contained 252 BC2F1 lines, for which the accession IRGC100898 was used as the wild donor parent. The second population, named ‘wild-2′, included 253 BC2F1 lines, in which the accession IRGC104705 was used as the wild donor parent. The evaluation of sheath blight phenotype was performed in the greenhouse while using micro-chambers and in the field in 2008 and 2009. Four QTLs were identified on the chromosomes 5, 6, 7, and 12 in the greenhouse assay. qShB5-mc was identified in both wild-1 and wild-2 and its source of resistant allele was Bengal. qShB6-mc was identified just in the wild-1 population and the source of resistant allele was O. nivara. The wild-2 population did not identify this QTL. qShB7-mc and qShB12-mc were only identified in the wild-2 population and the donor of resistant allele was Bengal in both QTLs. According to the results of field assays, five and four QTLs were identified in 2008 and 2009, respectively. qShB1 was identified in both years and both populations and O. nivara was the donor of resistant allele in the wild-2 population in the 2008 assay. However, in other assays, Bengal was the source of resistant allele of qShB1. qShB3 was identified in four experiments and O. nivara was the source of resistant allele in the wild-2 populations in both years, while Bengal was the source of resistant allele in the wild-1 population in both years. qShB6 was identified in both populations and both years, and the source of resistant allele was O. nivara in all four assays. qShB7 was just identified in the wild-2 population in both years and the donor of resistant allele was Bengal and O. nivara in 2008 and 2009, respectively. qShB11 was the only QTL that was only identified in one assay (wild-2/2008) and the source of resistant allele was Bengal [165].
In the study by Liu et al. [166], a 216 RIL population derived a cross of Jasmin 85 and Lemont (resistant and susceptible varieties, respectively) were evaluated in two years (2008 and 2009) at three different locations (Arkansas, Texas, and Louisiana) to identify QTLs that are related to sheath blight resistance under field condition. Fourteen QTLs were identified in this study, which also confirmed the 10 QTLs that were previously identified by the same research group from greenhouse assays using a 250-RIL population derived from the same parents [159]. For example, qShB9-2 was identified as a major sheath blight QTL in both the greenhouse and the field studies [159,166].
Taguchi-Shiobara et al. [167] conducted an experiment by using a backcross inbred line (BIL) population of a cross between Jarjian (resistant variety) and Koshihikari (susceptible variety) to investigate QTLs that are related to sheath blight during three years from 2009 to 2011. In that study, eight QTLs were found in chromosomes 3, 5, 6, 9, and 12. However, only qSBR-9, which is located on chromosome 9 and between the markers Nag08KK18184 and Nag08KK18871, was identified in all [167].
Zhu et al. [168] used 63 chromosome segment substitution lines (CSSLs) carrying the genetic background of HJX74 as a resistant variety and Amol3 (sona) as the donor parent in order to identify the sheath blight QTLs. qSB11HJX74, qSB1-1HJX74, qSB1-2HJX74, qSB2AM, and qSB3AM were identified on chromosomes 11, 1, 1, 2, and 3, respectively. A F2 segregation population from a cross of NIL P271 and HJX74 was used for further mapping of qSB11HJX74, which revealed the location of this QTL in the region of 430 kb between two molecular markers ZY27.49 and ZY27.92-11. The total phenotypic variation that was explained by qSB11HJX74 and the amount of additive effect of this QTL was 12.08% and 0.76, respectively. Two CSSLs, CSSL-P272 (resistant) and CSSL-P274 (susceptible), were also used for the further mapping of qSB1-1HJX74 within the region of 930 kb between the markers RM490 and ZY7.7-1-5 [168].
In a genetic study for sheath blight resistance by Wen et al. [169], three traits that were related to sheath blight (i.e., disease rating, lesion height, and percentage of lesion height) were evaluated in three field environments with two F2 and one F2:3 populations from a cross of Yangdao 4 (resistant chinese variety) and Lemont (susceptible US japonica variety). Among the 21 QTLs that were identified in that study, 8, 6, and 7 QTLs were related to disease rating, lesion height, and percentage of lesion height, respectively, and two QTLs from chromosome 7 and 12 were newly identified [169]. Furthermore, a significant negative correlation was detected between plant height and disease rating in the same study, which was congruent with previous studies [153,155].
Yadav et al. [170] performed a composite interval mapping analysis with two mapping populations that were derived from two germplasm, ‘BPT-5204 (susceptible)’ and ‘ARC10531 (moderately resistant)’, in which one population was 210 F2:3 lines from a cross between BPT-5204 and ARC10531 and the other one was 150 BC1F2 lines from the same cross. Nine QTLs and their associated markers were identified in that study from chromosomes 1, 6, 7, 8, and 9, which can be used for pyramiding sheath blight resistance through MAS [170].
Zeng et al. [171] used a doubled haploid population that was derived from a cross of CJ06 and TN1 (susceptible and resistant varieties, respectively) for QTL mapping of sheath blight resistance. In that study, two traits, including lesion height and disease rating, were investigated in three environments, and finally 16 QTLs were identified, including eight QTLs related to lesion height and eight QTLs related to disease rating on chromosomes 1, 3, 4, 5, 6, 8, 9, 11 and, 12 [171]. QTLs that were related to lesion height and disease rating explained 4.35–17.53% and 2–11.27% of the total phenotypical variation, respectively [171].
qSB-9TQ is a QTL that was identified from Teqing (an indica variety) in different studies [144,156,173]. The results of the studies, which commonly presented the high impact of qSB-9Tq on sheath blight, indicated the importance of the fine mapping and cloning of this QTL for rice breeding to elevate sheath blight resistance. Pinson et al. [174] used molecular markers that are linked to qSB-9Tq to perform marker-assisted selection for identifying the resistant alleles and to introgress the alleles to some rice germplasm, including TIL:455, TIL:514, and TIL:642 [174].
Zuo et al. investigated the precise location of qSB-11LE [175] using a near isogenic line that was developed through MAS. In the following, a fine mapping population inclusive of chromosome segment substitution lines was used and the region of qSB-11LE was localized in a 78.871kb region that was covered by two markers Z22-27C and Z23-33C by genotypic and phenotypic comparisons. Among the twelve possible genes in this region, it seems that three genes are most likely to be present. Six of the genes encode proteins with predicted function and the others encode unknown or hypothetical proteins. The results will facilitate the cloning of the responsible gene of QTL in the breeding programs [175].

4. Rice Disease Resistance to Bacterial Panicle Blight

Bacterial panicle blight of rice is one of the major diseases of rice and Burkholderia glumae (a gram-negative bacterial pathogen) is the main causal agent [176]. This bacterial disease was first reported in Japan in the 1950s and it is considered to be one of the most important emerging diseases in rice-growing regions around the world [177]. Severe yield losses from this disease were experienced in the southeastern United States over the years of 1996 through 2000, and lately 2010 [178].
According to the result of researches conducted on rice fields in southern states of the USA, including Louisiana, Texas, and Arkansas, more than 300 strains of Burkholdria spp. were isolated from rice [179]. In that study and additional studies, two bacterial species, B. glumae and B. gladioli, were identified as the causal agents of bacterial panicle blight [179,180,181]. The lack of effective management tool makes this disease more problematic when a severe epidemic occurs. The antibiotic, oxolinic acid, is practically the only effective chemical agent for the disease in the field, but it is not permitted to use for agricultural purposes in some countries, including the U.S. [178]. More importantly, the long-term and sustainable efficacy of oxolinic acid is doubtful due to the frequent occurrence of antibiotic-resistant strains [182,183].
Biological control could be an alternative approach in managing bacterial panicle blight. Shrestha et al. [184] isolated 26 strains of Bacillus spp. that exhibited high levels of antagonistic activity to both B. glumae (bacterial blight pathogen) and Rhizoctonia solani (sheath blight pathogen) from rice plants in the field, and they tested their biological control activities with the five selected strains in the field for two years. All five strains tested significantly suppressed both bacterial panicle blight and sheath blight [184]. Miyagawa and Takaya [185] observed in a field test that avirulent strains of B. gladioli (the other species causing bacterial panicle blight) effectively suppressed the symptom development that is caused by the inoculation of a virulent B. glumae strain. Nevertheless, to the best of our knowledge, there is no effective biological product currently commercially available. Thus, breeding of elite disease-resistant lines is imperative to mitigate the problem of bacterial panicle blight, for which a better understanding of the QTLs for the resistance to this disease is very critical.

4.1. Symptoms and Infection Process of Bacterial Panicle Blight

Changes in panicle color, discoloration of rice seeds, and sterility of spikelet are symptoms of bacterial panicle blight [177]. The presence of pathogen cells in the leaf sheath cause primary infection, which can be the source of infection in emerging panicles [182,186]. Pathogen (B. glumae or B. gladioli) can grow and survive in the sheath of the plant leaves without showing signs of rot and disease. At the flowering stage of the plant’s spikelets, which is the most sensitive growing stage to the pathogen, the pathogen attacks to emerging spikelets, which eventually causes the rot in the grains [182,187,188,189,190,191]. The most important part of the plant for pathogen invasion is lemma and palea, and the pathogen is propagated in the parenchymatous intercellular space, causing the infection of healthy tissue [192].

4.2. Conducive Environmental Conditions for Bacterial Panicle Blight

The bacterial pathogen rapidly multiplies in emerging panicles, which ultimately leads to the infection of flowers just after their emergence [193]. Long-term warm weather conditions, including prolonged high night temperatures during the reproductive stage usually affects the onset of disease, and it has caused a widespread outbreak of the disease and severe yield losses over the past 20 years [176,179,194]. This disease can be a big threat to rice production since we are facing global warming in the years to come [176]. Outbreak of bacterial panicle blight can be even more severe when the favorable conditions for disease coincides with the rice heading time [195]. Although environmental effects can affect the resistance to the disease, there are few reports on this issue [6,7].

4.3. QTLs of Rice Associated with the Disease Resistance to Bacterial Panicle Blight

So far, only a few reports of quantitative trait loci for bacterial panicle blight disease resistance have been presented (Table 3). Pinson et al. [7] found twelve QTLs by researching a RIL population that contains 300 RILs from a cross between the resistant and susceptible varieties, TeQing and Lemont. The twelve defined QTLs related to bacterial panicle blight resistance are located on chromosomes 1, 2, 3, 7, 8, 10, and 11. These QTLs include qBPB-1-1, qBPB-1-2, and qBPB-1-3 that were located on chromosome 1, qBPB-2-1 and qBPB-2-2 on chromosome 2, qBPB-3-1 and qBPB-3-2 on chromosome 3, qBPB-7 on chromosome 7, qBPB-8-1 and qBPB-8-2 on chromosome 8, qBPB-10 on chromosome 10, and qBPB-11 on chromosome 11 [7]. According to the statistical analysis of the QTLs, qBPB-3-1 was the most significant QTL, which explained 14% of phenotypic variation in both years of experiment (2001 and 2002) and it had the highest amount of LOD. qBPB-3-1 and qBPB-3-2 were statistically significant in both years of experiment. The qBPB-1-3 was also significant in both years. Those QTLs that were identified in both years confirm the existence of QTLs for bacterial panicle blight resistance. According to the analysis that was conducted in that study, resistant alleles were from TeQing and Lemont for eight and four QTLs, respectively [7]. In the same study, 30% of the total phenotypic variance was explained by six QTLs in the first year (2001), while 36% was explained by seven QTLs in the second year (2002). Overall, eight QTLs explained 35% of the total phenotypic variance. Among the twelve QTLs that were identified by Pinson et al. [7], four QTLs were mapped near to other previously mapped QTLs that are related to resistance to other diseases, including blast, sheath blight, and bacterial leaf blight [144,196,197]. Three of the QTLs (including qBPB-3-1, which explained the highest phenotypic variation) were also mapped near to the QTLs related to the days to heading [144]. It was also stated in another research article that there is a direct relationship between the severity of bacterial panicle blight and the night temperature during the period of grain filling [198].
Through a study with a backcross inbred line (BIL) population that was generated from cross-breeds between Kele (resistant, indica variety) and Hitomebore (susceptible, japonica variety), Mizobuchi et al. [13] identified a QTL associated with the resistance to bacterial panicle blight on the long arm of chromosome 1, which explained 25.7% and 12.1% of the total phenotypic variation in the ratio of diseased spikelets and in the ratio of diseased spikelet area, respectively. The allele of Kele (resistant variety) played a big role in increasing the resistance to bacterial panicle blight, because the ratio of the diseased spikelets and the ratio of diseased spikelet area decreased in the presence of Kele allele [13]. Later, Mizobuchi et al. [199] performed fine mapping of this QTL by using homozygous recombinant and non-recombinant varieties to define the accurate region on the chromosome 1 underlying the QTL, which is called RBG2. For minimizing the environmental effects, a varied cut-panicle inoculation procedure was used to identify this QTL. Miyagawa and Kimura [200] created this method, in which panicles with spikelets at one day after anthesis collected from the plants in the field and inoculated under controlled conditions at the flowering stage [13,199,200].
Chromosome segment substitution lines (CSSLs) are very useful for QTL mapping, especially for QTLs with small effects [201,202]. Mizobuchi et al. [14] used chromosome segment substitution lines (CSSLs) that were derived from a cross between a resistant and a susceptible variety (Nona Bokra and Koshihikari, respectively) and for further scrutiny used the F5 population derived from a cross between a resistant chromosome segment substitution lines and Koshihikari to investigate the resistance QTLs that were related to bacterial panicle blight resistance. In that study, the QTL, qRBS1 (QTL Resistance to Burkholderia glumae 1), was identified on the short arm of chromosome 10 [14]. qRBS1 accounted for 22% of phenotypic changes in bacterial panicle blight, confirming its importance for bacterial panicle blight resistance [14].
B. glumae can infect both seedlings and panicles, but there is no relationship in disease resistance between the two types of disease that are caused by the same pathogen (seedling rot vs. panicle blight/grain rot) [203]. Similarly, varieties that are resistant to bacterial grain rot (another name of bacterial panicle blight) were not always resistant to bacterial seedling rot, indicating different mechanisms of resistance to the pathogen in two different developmental stages [13].

5. Conclusions

To date, almost 100 blast resistance genes and over 350 quantitative trait loci that are related to blast have been identified. More than 200 QTLs for sheath blight resistance and 14 QTLs for bacterial panicle blight resistance have been recognized on the 12 chromosomes of rice by using different populations, such as double haploid lines (DHLs), recombinant inbred lines (RILs), near-isogenic lines (NILs), and backcross populations. Some of the QTLs were commonly identified across several research projects that were performed with different populations, while others were identified in a single study as novel QTLs. QTLs for disease resistance explained different ranges of phenotypic variation, and some of them explained about 50% of phenotypic variation, showing significant impacts on disease resistance. It is important to use these QTLs to advance breeding programs through marker-assisted selection and gene pyramiding, which could ultimately lead to the production of new resistant varieties to overcome prevalent rice diseases.

Author Contributions

S.S.Z searched literatures and wrote the first draft of the manuscript. J.H.H. reviewed and edited to finalize the manuscript. All authors approved the final manuscript.

Funding

This research was funded by USDA NIFA (Hatch project: 1015305) and the Louisiana Rice Research Board (GR-00000984).

Acknowledgments

The authors greatly appreciated the University of Guilan, Iran, for its financial support for S.S.Z.

Conflicts of Interest

The authors declare no conflict of interest.

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Table
Table 1. Identified genes responsible for the quantitative resistance of rice to blast.
Table 1. Identified genes responsible for the quantitative resistance of rice to blast.
Gene NameChromosomeMolecular FunctionSource (Variety/Line)Reference
Pi-sh1Protein binding (Diacylglycerol kinase)Shin-2[67,68]
Pi-t1Nucleotide binding (NBS-LRR disease resistance protein)Tjahaja, K59[69,70,71]
Pi-371Protein binding (rp1)St. No.1[72,73]
Pi-b2Nucleotide bindingTohoku IL9[74,75]
pi-214Binding (Basic prolin-rich protein)Owarihatamochi[58,76]
Pi-634-Kahei[77]
Pi-z6Protein binding, Nucleotide binding (Disease resistance protein RPM1)Zenith, Fukunishiki, Toride 1, Tadukan[78,79,80]
Pi-26Protein binding, Nucleotide binding (Disease resistance protein RPM1)Fukunishiki[80]
Pi-96Protein binding, Nucleotide binding (Disease resistance protein RPM1)O. minuta (wild rice)[81,82]
Piz-t6Protein binding, Nucleotide binding (Disease resistance protein RPM1)TKM.1[80]
Pi-d26Carbohydrate binding, Kinase activity, Protein binding
(Lectin protein kinase family protein)		Digu[83]
Pi-d36Protein binding, nucleotide binding (Disease resistance protein RPM1)-[84]
Pi-256Protein binding, nucleotide binding (Disease resistance protein RPM1)Gumei 2[85,86]
Pi-368F-box domain (Cyclin-like domain containing protein)Q61[87,88]
Pi5/Pi3/Pi-i9Nucleotide binding (NBS-LRR disease resistance protein)Moroberekan[89,90]
pi-569Nucleotide binding (NBS-LRR disease resistance protein)-[91]
Pi-a11Protein binding, Nucleotide binding
(NBS-LRR type disease resistance protein)		Aichi Asahi[92,93]
Pi-C03911-CO39[94,95]
Pi-k11Protein binding, Nucleotide binding
(NB-ARC domain containing protein)		Kusabue[96,97,98]
Pi-111-LAC23[99,100]
Pik-h/Pi-5411Nucleotide binding (NBS-LRR disease resistance protein)Tetep[101,102,103]
Pik-m11Nucleotide binding (NBS-LRR disease resistance protein)Tsuyuake[104,105]
Pik-p11-HR22[69,106]
pb111Protein binding (PB1 domain containing protein)Modan[107,108]
Pi-ta12Nucleotide binding (NB-ARC domain containing protein)Tadukan, Yashiro-mochi[109]
Table
Table 2. Quantitative trait loci (QTLs) for resistance to sheath blight disease in rice.
Table 2. Quantitative trait loci (QTLs) for resistance to sheath blight disease in rice.
ChromosomeQTLSource of Resistance AlleleMaterial Used for QTL AnalysisFlanking Markers or Nearest MarkerPhenotypic Variance (%)Ref.
1qSB-1Teqing216 Recombinant inbred lines population from a cross of Teqing (R) and Lemont (S)RG532x [144]
1QRh1IR64BC2F5 introgression lines from a cross of Binam (R) and IR64 (S)RM265 [158]
1qShB1Jasmine 85 (Microchamber and Mist chamber)250 Recombinant inbred lines population from a cross of Jasmine 85 (R) and Lemont (S)RM1361–RM104 (Microchamber)
RM1361–RM104 (Mist chamber)		3.4 (Microchamber)
3.6 (Mist chamber)		[159]
1-Pecos279 F2:3 population from a cross of Pecos (R) and Rosemont (S)RM1339 (Interval mapping & Composite interval mapping)36.4 (Interval mapping)
35 (Composite interval mapping)		[145]
1qSBR1-1-127 F2:10 recombinant inbred lines population from a cross of Tetep (R) and HP2216 (S)Hvssr68-RM306 (2004/New Delhi)
RM1232-Hvssr68 (2006/Hyderabad)		15.01 (2004/New Delhi)
8.13 (2006/Hyderabad)		[160]
1qSBR1-1RSB03Recombinant inbred line population from a cross of RSB03 (RR) and HH1B (S)RM5389-RM382512.7[161]
1qSBR1-2RSB03Recombinant inbred line population from a cross of RSB03 (RR) and HH1B (S)RM3825-RM827842.6[161]
1qShB1BaiyeqiuDouble haploid population from a cross of Baiyeqiu (R) and Maybelle (S)RM431-RM120178.9 (2007)/13.2 (2008)[162]
1--217 sub-core entries from the USDA rice core collectionRM112299.5[163]
1--217 sub-core entries from the USDA rice core collectionRM2376.9[163]
1qShB1O. nivara (Wild2/2008)
Bengal (Wild-1/2008, Wild-1/2009, Wild-2/2009)		253 BC2F1 lines populations from a cross of O. nivara (acc. IRGC104705) (R) and Bengal (S) as wild-2 population.RM1361-RM104 (Wild-1/2008, 2009)
RM431-RM1361 (Wild-2/2008)
RM403-RM431 (Wild-2/2009)		3.4 (Wild-1/2008)
8.2 (Wild-2/2008)
4 (Wild-1/2009)
3 (Wild-2/2009)		[165]
1qSB1-1HJX74HJX7463 chromosome segment substitution lines carrying the genetic background of HJX74 (R) and the donor parent Amol3(sona) (S)--[168]
1qSB1-2HJX74HJX7463 chromosome segment substitution lines carrying the genetic background of HJX74 (R) and the donor parent Amol3(sona) (S)--[168]
1qSBD-1Lemont2 F2 and 1 F2:3 Populations from a cross of Yangdao 4 (R) and Lemont (S)D134B-D140A5.53[169]
1qshb1.1 F2:3 and BC1F2 populations from a cross of ARC10531 (R) and BPT-5204 (S)RM151-RM1225310.99[170]
1qHZaLH1CJ06Double haploid population from a cross of TN1 (R) and CJ06 (S)RM428B-RM53026.12[171]
1qHNDR1CJ06Double haploid population from a cross of TN1 (R) and CJ06 (S)RM259-RM6002[171]
2QSbr2aTeqingF4 bulked populations from a cross of Teqing (R) and Lemont (S)RG654-RZ260-[143]
2Rh-2Jasmin 85128 F2 clonal population from a cross of Jasmine 85 (R) and Lemont (S)G243-RM2914.4[150]
2qSB-2Jasmin 85 (1997 & 1998)128 F2 clonal population from a cross of Jasmine 85 (R) and Lemont (S)G243–RM29 (1997)
RM29–RG171 (1998)		14.4 (1997)
21.2 (1998)		[151]
2qSB-2Zhai Ye Qing 8Double haploid population from a cross of Zhai Ye Qing 8 (R) and Jingxi 17 (S)RG171-G243A2.5-2.6[153]
2qSB-2Teqing216 Recombinant inbred lines population from a cross of Teqing (R) and Lemont (S)C624x-[144]
2QDs2bTarom MolaiiBC2F5 introgression lines from a cross of Tarom Molaii (R) and Teqing (S)RM208-[158]
2QRh2bTarom MolaiiBC2F5 introgression lines from a cross of Tarom Molaii (R) and Teqing (S)RM208-[158]
2QDs2aBinamBC2F5 introgression lines from a cross of Binam (R) and IR64 (S)RM279-[158]
2QRh2aIR64BC2F5 introgression lines from a cross of Binam (R) and IR64 (S)RM341-[158]
2qShB2-1Jasmine 85250 Recombinant inbred lines population from a cross of Jasmine 85 (R) and Lemont (S)RM424–RM54276.9[159]
2qShB2-2Jasmine 85250 Recombinant inbred lines population from a cross of Jasmine 85 (R) and Lemont (S)RM112–RM2503.2[159]
2-Rosemont279 F2:3 population from a cross of Pecos (R) and Rosemont (S)RM3685 (Interval mapping & Composite interval mapping)5.8 (Interval mapping & Composite interval mapping)[145]
2qSBR2-1HH1BRecombinant inbred line population from a cross of RSB03 (RR) and HH1B (S)RM5340-RM5218.2[161]
2qSBR2-2RSB03Recombinant inbred line population from a cross of RSB03 (RR) and HH1B (S)RM110-osr145.3[161]
2qSBR2-3HH1BRecombinant inbred line population from a cross of RSB03 (RR) and HH1B (S)RM7245-RM53034.3[161]
2qLL2-1HH1BRecombinant inbred line population from a cross of RSB03 (RR) and HH1B (S)RM1106-RM35497.8[161]
2qLL2-2RSB03Recombinant inbred line population from a cross of RSB03 (RR) and HH1B (S)RIO02051-RIO020538.9[161]
2qRLL2-1HH1BRecombinant inbred line population from a cross of RSB03 (RR) and HH1B (S)RM1106-RM354922.1[161]
2qRLL2-2RSB03Recombinant inbred line population from a cross of RSB03 (RR) and HH1B (S)RIO02044-RIO0204671.1[161]
2qShB2MaybelleDouble haploid population from a cross of Baiyeqiu (R) and Maybelle (S)RM174-RM1457.3[162]
2--217 sub-core entries from the USDA rice core collectionRM3414.1[163]
2qsbr_2.1MCR10277Double haploid lines population from a cross of MCR10277 (R) and Cocodrie (S)RM8254-RM8252-[164]
2qsbr_2.2MCR10277Double haploid lines population from a cross of MCR10277 (R) and Cocodrie (S)RM3857*RM5404-[164]
2qSB2.1-ARJasmine 85216 Recombinant inbred lines population from a cross of Jasmine 85 (R) and Lemont (S)RM279–RM71/RM5556.82[166]
2qSB2.2-ARJasmine 85216 Recombinant inbred lines population from a cross of Jasmine 85 (R) and Lemont (S)RM221–RM112/RM2216.50[166]
2qSB2.1-TXJasmine 85216 Recombinant inbred lines population from a cross of Jasmine 85 (R) and Lemont (S)RM424–RM341/RM5618.64[166]
2qSB2.2-TXJasmine 85216 Recombinant inbred lines population from a cross of Jasmine 85 (R) and Lemont (S)RM221–RM250/RM5306.64[166]
2qSB2-LAJasmine 85216 Recombinant inbred lines population from a cross of Jasmine 85 (R) and Lemont (S)RM221–RM112/RM5305.70[166]
2qSB2AMAmol3(sona)63 chromosome segment substitution lines carrying the genetic background of HJX74 (R) and the donor parent Amol3(sona) (S)--[168]
3QSbr3aTeqingF4 bulked populations from a cross of Teqing (R) and Lemont (S)RG348-RG944-[143]
3Rh-3Jasmin 85128 F2 clonal population from a cross of Jasmine 85 (R) and Lemont (S)R250-C74626.1[150]
3qSB-3Jasmin 85 (1997)
Not identified in 1998		128 F2 clonal population from a cross of Jasmine 85 (R) and Lemont (S)R250–C746 (1997)
Not identified in 1998		26.5 (1997)
Not identified in 1998		[151]
3qSB-3Zhai Ye Qing 8Double haploid population from a cross of Zhai Ye Qing 8 (R) and Jingxi 17 (S)G249-G1642.4-2.5[153]
3qSB-3WSS260 BC1F1 population from a cross of Hinohikari (S) /WSS2 (R)//Hinohikari (S)RM385619.4[155]
3qSB-3-1Teqing216 Recombinant inbred lines population from a cross of Teqing (R) and Lemont (S)RG348x-[144]
3qSB-3-2Teqing216 Recombinant inbred lines population from a cross of Teqing (R) and Lemont (S)RZ474-[144]
3QDs3IR64BC2F5 introgression lines from a cross of Tarom Molaii (R) and IR64 (S)RM22-[158]
3QRh3IR64BC2F5 introgression lines from a cross of Tarom Molaii (R) and IR64 (S)RM22-[158]
3qShB3-1Jasmine 85250 Recombinant inbred lines population from a cross of Jasmine 85 (R) and Lemont (S)RM16–RM4263.7[159]
3qShB3-2Jasmine 85250 Recombinant inbred lines population from a cross of Jasmine 85 (R) and Lemont (S)RM5626–RM4263.3[159]
3qShB3-3Jasmine 85250 Recombinant inbred lines population from a cross of Jasmine 85 (R) and Lemont (S)RM514–RM853[159]
3-Pecos279 F2:3 population from a cross of Pecos (R) and Rosemont (S)RM3117 (Interval mapping)
RM7072 (Composite interval mapping)		6.4 (Interval mapping)
2.4 (Composite interval mapping)		[145]
3qSBR3-1-127 F2:10 recombinant inbred lines population from a cross of Tetep (R) and HP2216 (S)RM251-RM338 (2007/Cuttack)9.96 (2007/Cuttack)[160]
3qShB3BaiyeqiuDouble haploid population from a cross of Baiyeqiu (R) and Maybelle (S)RM135-RM1866.1[162]
3qShB3O. nivara (Wild2/2008, Wild-2/2009)
Bengal (Wild-1/2008, Wild-1/2009)		252 BC2F1 lines populations from a cross of O. nivara (acc. IRGC100898) (R) and Bengal (S) as wild-1 population andRM232-282 (All assays including two populations and two years)3.7 (Wild-1/2008)
9.3 (Wild-2/2008)
2.5 (Wild-1/2009)
3.5 (Wild-2/2009)		[165]
3qSB3-ARJasmine 85216 Recombinant inbred lines population from a cross of Jasmine 85 (R) and Lemont (S)RM5626–RM55/RM555.82[166]
3qSB3-TXJasmine 85216 Recombinant inbred lines population from a cross of Jasmine 85 (R) and Lemont (S)RM5626–RM55/RM555.62[166]
3-JarjianBackcross inbred lines population from a cross of Jarjian (R) and Koshihikari (S)RM570-[167]
3-KoshihikariBackcross inbred lines population from a cross of Jarjian (R) and Koshihikari (S)RM16200-[167]
3qSB3AMAmol3(sona)63 chromosome segment substitution lines carrying the genetic background of HJX74 (R) and the donor parent Amol3(sona) (S)--[168]
3qSBD-3-1Yangdao 42 F2 and 1 F2:3 Populations from a cross of Yangdao 4 (R) and Lemont (S)D328B-D331B10.51 (E1) / 14.66 (E3)[169]
3qSBD-3-2Yangdao 42 F2 and 1 F2:3 Populations from a cross of Yangdao 4 (R) and Lemont (S)D333B-D3349.84 (E2) / 11.25 (E3)[169]
3qSBL-3-1Yangdao 42 F2 and 1 F2:3 Populations from a cross of Yangdao 4 (R) and Lemont (S)D333B-D3347.93[169]
3qSBL-3-2Yangdao 42 F2 and 1 F2:3 Populations from a cross of Yangdao 4 (R) and Lemont (S)D328B-D331B31.53[169]
3qSBPL-3-1Yangdao 42 F2 and 1 F2:3 Populations from a cross of Yangdao 4 (R) and Lemont (S)D333B-D3348.70[169]
3qSBPL-3-2Lemont2 F2 and 1 F2:3 Populations from a cross of Yangdao 4 (R) and Lemont (S)D336B-RM358515.90[169]
3qSBPL-3-3Yangdao 42 F2 and 1 F2:3 Populations from a cross of Yangdao 4 (R) and Lemont (S)D328B-D331B29.81[169]
3qHNLH3TN1Double haploid population from a cross of TN1 (R) and CJ06 (S)RM6759-STS146.18.46[171]
3qHZaLH3TN1Double haploid population from a cross of TN1 (R) and CJ06 (S)RM143-RM5145.57[171]
4QSbr4aTeqingF4 bulked populations from a cross of Teqing (R) and Lemont (S)RG143-RG214-[143]
4qSB-4-1Teqing216 Recombinant inbred lines population from a cross of Teqing (R) and Lemont (S)RG1094e-[144]
4qSB-4-2Teqing216 Recombinant inbred lines population from a cross of Teqing (R) and Lemont (S)RZ590x-[144]
4qSBR4RSB03Recombinant inbred line population from a cross of RSB03 (RR) and HH1B (S)RM3288-RM718712.4[161]
4qRLH4RSB03Recombinant inbred line population from a cross of RSB03 (RR) and HH1B (S)RM3288-RM718715.7[161]
4--217 sub-core entries from the USDA rice core collectionRM82173.2[163]
4qSBL-4Yangdao 42 F2 and 1 F2:3 Populations from a cross of Yangdao 4 (R) and Lemont (S)RM1113-D4684.15[169]
4qHNLH4TN1Double haploid population from a cross of TN1 (R) and CJ06 (S)RM255-SSIII-117.53[171]
5qSB-5Minghui 63240 F11-12 recombinant inbred lines population from a cross of Minghui 63 (R) and Zhenshan 97 (S)C624-RM269.5-10.5[152]
5Rsb 1 1030 F2 population from a cross of 4011 (R) and Xiangzaoxian 19 (S)RM173, C624-[154]
5qSB-5Teqing216 Recombinant inbred lines population from a cross of Teqing (R) and Lemont (S)Y1049-[144]
5QDs5TeqingBC2F5 introgression lines from a cross of Binam (R) and Teqing (S)RM161-[158]
5QRh5TeqingBC2F5 introgression lines from a cross of Binam (R) and Teqing (S)RM161-[158]
5qShB5Lemont250 Recombinant inbred lines population from a cross of Jasmine 85 (R) and Lemont (S)RM507–RM73495.1[159]
5qSBR5-1HH1BRecombinant inbred line population from a cross of RSB03 (RR) and HH1B (S)RM421-RM654512.3[161]
5qSBR5-2RSB03Recombinant inbred line population from a cross of RSB03 (RR) and HH1B (S)RM7446-RM362015.7[161]
5qLL5HH1BRecombinant inbred line population from a cross of RSB03 (RR) and HH1B (S)RM6545-RM744610[161]
5qRLL5HH1BRecombinant inbred line population from a cross of RSB03 (RR) and HH1B (S)RM6545-RM74465.7[161]
5qShB5BaiyeqiuDouble haploid population from a cross of Baiyeqiu (R) and Maybelle (S)RM18872-RM4217.8[162]
5--217 sub-core entries from the USDA rice core collectionRM1463.8[163]
5qShB5-mc
(Green house assay)		Bengal (Wild-1 and wild-2)252 BC2F1 lines populations from a cross of O. nivara (acc. IRGC100898) (R) and Bengal (S) as wild-1 population and
253 BC2F1 lines populations from a cross of O. nivara (acc. IRGC104705) (R) and Bengal (S) as wild-2 population.		RM122-RM5796 (Wild-1), RM122-RM413 (Wild-2)3 (Wild-1) and 5.4 (Wild-2)[165]
5-KoshihikariBackcross inbred lines population from a cross of Jarjian (R) and Koshihikari (S)RM5784 (2009) / RM3286 (2011) [167]
5qHZbLH5CJ06Double haploid population from a cross of TN1 (R) and CJ06 (S)RM3321-RM36167.15[171]
5qHZbDR5CJ06Double haploid population from a cross of TN1 (R) and CJ06 (S)RM3321-RM36168.97[171]
6qSB-6-1Teqing216 Recombinant inbred lines population from a cross of Teqing (R) and Lemont (S)C-[144]
6qSB-6-2Teqing216 Recombinant inbred lines population from a cross of Teqing (R) and Lemont (S)RZ508-[144]
6QRh6IR64BC2F5 introgression lines from a cross of Binam (R) and IR64 (S)RM30-[158]
6qShB6Lemont250 Recombinant inbred lines population from a cross of Jasmine 85 (R) and Lemont (S)RM435–RM1903.4[159]
6qLH6HH1BRecombinant inbred line population from a cross of RSB03 (RR) and HH1B (S)RM508-RM136914.1[161]
6- 217 sub-core entries from the USDA rice core collectionRM1332.4[163]
6qShB6-mc
(Green house assay)		O. nivara (Wild-1)
Not identified in other assay		252 BC2F1 lines populations from a cross of O. nivara (acc. IRGC100898) (R) and Bengal (S) as wild-1 population andRM3183-RM541 (Wild-1)
Not identified in other assay		5.8 (Wild-1)
Not identified in other assay		[165]
6qShB6O. nivara (All assays including two populations and two years)253 BC2F1 lines populations from a cross of O. nivara (acc. IRGC104705) (R) and Bengal (S) as wild-2 population.RM3431-RM3183 (Wild-1- 2008, 2009)
RM253-RM3431 (Wild-2- 2008, 2009)		8.2 (Wild-1/2008)
18.2 (Wild-2/2008)
13.3 (Wild-1/2009)
32 (Wild-2/2009)		[165]
6-KoshihikariBackcross inbred lines population from a cross of Jarjian (R) and Koshihikari (S)RM1161-[167]
6-KoshihikariBackcross inbred lines population from a cross of Jarjian (R) and Koshihikari (S)RM2615-[167]
6-JarjianBackcross inbred lines population from a cross of Jarjian (R) and Koshihikari (S)RM6395-[167]
6qshb6.1-F2:3 and BC1F2 populations from a cross of ARC10531 (R) and BPT-5204 (S)RM400-RM25313.25[170]
6qHNLH6TN1Double haploid population from a cross of TN1 (R) and CJ06 (S)AP3510-AP49914.35[171]
6qHZaLH6CJ06Double haploid population from a cross of TN1 (R) and CJ06 (S)WX-RM5876.79[171]
6qHNDR6CJ06Double haploid population from a cross of TN1 (R) and CJ06 (S)AP3510-AP49912.38[171]
7Rh-7Jasmin 85128 F2 clonal population from a cross of Jasmine 85 (R) and Lemont (S)RG30-RG47722.2[150]
7qSB-7Jasmin 85 (1997)
Not identified in 1998		128 F2 clonal population from a cross of Jasmine 85 (R) and Lemont (S)RG30–RG477 (1997)
Not identified in 1998		22.2 (1997)
Not identified in 1998		[151]
7qSB-7Zhai Ye Qing 8Double haploid population from a cross of Zhai Ye Qing 8 (R) and Jingxi 17 (S)RG511-TCT1223.9-4.3[153]
7qSB-7Teqing216 Recombinant inbred lines population from a cross of Teqing (R) and Lemont (S)C285-[144]
7QRh7IR64BC2F5 introgression lines from a cross of Tarom Molaii (R) and IR64 (S)RM180-[158]
7QDs7IR64BC2F5 introgression lines from a cross of Binam (R) and IR64 (S)RM11-[158]
7qSBR7-1-127 F2:10 recombinant inbred lines population from a cross of Tetep (R) and HP2216 (S)RM3691-RM336 (2007/Hyderabad)
RM5481-RM3691 (2007/Cuttack)		10.02 (2007/Hyderabad)
26.05 (2007/Cuttack)		[160]
7qSBR7RSB03Recombinant inbred line population from a cross of RSB03 (RR) and HH1B (S)RM1132-RM4735.9[161]
7qLL7RSB03Recombinant inbred line population from a cross of RSB03 (RR) and HH1B (S)RM1253-RM113239.3[161]
7qLH7RSB03Recombinant inbred line population from a cross of RSB03 (RR) and HH1B (S)RM1253-RM113212.8[161]
7qRLL7RSB03Recombinant inbred line population from a cross of RSB03 (RR) and HH1B (S)RM1253-RM113223.4[161]
7qRLH7RSB03Recombinant inbred line population from a cross of RSB03 (RR) and HH1B (S)RM1132-RM47310.5[161]
7qShB7-mc
(Green house assay)		Bengal (Wild-2)
Not identified in other assay		253 BC2F1 lines populations from a cross of O. nivara (acc. IRGC104705) (R) and Bengal (S) as wild-2 population.RM295-RM5711 (Wild-2)
Not identified in other assay		5.6 (Wild-2)
Not identified in other assay		[165]
7qShB7O. nivara (Wild2/2009)
Bengal (Wild-2/2008)
Not identified in two other assays		252 BC2F1 lines populations from a cross of O. nivara (acc. IRGC100898) (R) and Bengal (S) as wild-1 population andRM295-RM5711 (Wild-2-2008)
RM5711-RM2 (Wild-2-2009)Not identified in two other assays		6.5 (Wild-2/2008)
4.3 (Wild-1/2009)
Not identified in two other assays		[165]
7qSB7-ARJasmine 85216 Recombinant inbred lines population from a cross of Jasmine 85 (R) and Lemont (S)RM5711–RM2/RM1257.41[166]
7qSB7-LAJasmine 85216 Recombinant inbred lines population from a cross of Jasmine 85 (R) and Lemont (S)RM5711–RM2/RM12511.54[166]
7qSBD-7Yangdao 42 F2 and 1 F2:3 Populations from a cross of Yangdao 4 (R) and Lemont (S)RM505-RM2341.12[169]
7qSBL-7Yangdao 42 F2 and 1 F2:3 Populations from a cross of Yangdao 4 (R) and Lemont (S)D760-RM2484.82[169]
7qSBPL-7Yangdao 42 F2 and 1 F2:3 Populations from a cross of Yangdao 4 (R) and Lemont (S)D760-RM2486.97[169]
7qshb7.1 F2:3 and BC1F2 populations from a cross of ARC10531 (R) and BPT-5204 (S)RM81-RM615210.52[170]
7qshb7.2 F2:3 and BC1F2 populations from a cross of ARC10531 (R) and BPT-5204 (S)RM10-RM216939.72[170]
7qshb7.3 F2:3 and BC1F2 populations from a cross of ARC10531 (R) and BPT-5204 (S)RM336-RM42721.76[170]
8QSbr8aLemontF4 bulked populations from a cross of Teqing (R) and Lemont (S)RG20-RG1034-[143]
8qSB-8-1Lemont216 Recombinant inbred lines population from a cross of Teqing (R) and Lemont (S)G104-[144]
8qSB-8-2Lemont216 Recombinant inbred lines population from a cross of Teqing (R) and Lemont (S)R662-[144]
8QDs8Tarom MolaiiBC2F5 introgression lines from a cross of Tarom Molaii (R) and IR64 (S)RM25-[158]
8QRh8bTarom MolaiiBC2F5 introgression lines from a cross of Tarom Molaii (R) and IR64 (S)RM25-[158]
8QRh8aBinamBC2F5 introgression lines from a cross of Binam (R) and IR64 (S)RM407-[158]
8qSBR8-1-127 F2:10 recombinant inbred lines population from a cross of Tetep (R) and HP2216 (S)RM210-Hvssr47 (2007/Hyderabad)8.37 (2007/Hyderabad)[160]
8qSBR8HH1BRecombinant inbred line population from a cross of RSB03 (RR) and HH1B (S)RM8264-RM110912.7[161]
8qLL8HH1BRecombinant inbred line population from a cross of RSB03 (RR) and HH1B (S)RM8271-RM826418.4[161]
8qLH8HH1BRecombinant inbred line population from a cross of RSB03 (RR) and HH1B (S)RM8271-RM826423.5[161]
8qRLL8HH1BRecombinant inbred line population from a cross of RSB03 (RR) and HH1B (S)RM8264-RM11095.8[161]
8qRLH8HH1BRecombinant inbred line population from a cross of RSB03 (RR) and HH1B (S)RM8271-RM826417.4[161]
8--217 sub-core entries from the USDA rice core collectionRM4084[163]
8qshb8.1-F2:3 and BC1F2 populations from a cross of ARC10531 (R) and BPT-5204 (S)RM21792-RM31010.52[170]
8qHZaLH8CJ06Double haploid population from a cross of TN1 (R) and CJ06 (S)RM1376-RM408516.71[171]
8qHZaDR8CJ06Double haploid population from a cross of TN1 (R) and CJ06 (S)RM1376-RM408511.27[171]
9QSbr9aTeqingF4 bulked populations from a cross of Teqing (R) and Lemont (S)RG910b-RZ777-[143]
9qSB-9-1Lemont (1998)
Not identified in 1997		128 F2 clonal population from a cross of Jasmine 85 (R) and Lemont (S)C397–G103 (1998)
Not identified in 1997		9.8 (1998)
Not identified in 1997		[151]
9qSB-9-2Jasmin 85 (1998)
Not identified in 1997		128 F2 clonal population from a cross of Jasmine 85 (R) and Lemont (S)RG570–C356 (1998)
Not identified in 1997		10.1 (1998)
Not identified in 1997		[151]
9qSB-9Minghui 63240 F11-12 recombinant inbred lines population from a cross of Minghui 63 (R) and Zhenshan 97 (S)RM242-C4726.9-10.1[152]
9qSB-9Teqing216 Recombinant inbred lines population from a cross of Teqing (R) and Lemont (S)RZ404-[144]
9qSB-9Teqing115 F2 clonal population from a cross of Teqing (R) and Lemont (S)RM205-RM20111.8-22.2[156]
9qShB9-1Lemont250 Recombinant inbred lines population from a cross of Jasmine 85 (R) and Lemont (S)RM409–RM2575.4[159]
9qShB9-2Jasmine 85 (Microchamber and Mist chamber)250 Recombinant inbred lines population from a cross of Jasmine 85 (R) and Lemont (S)RM215–RM245 (Microchamber)
RM215–RM245 (Mist chamber)		24.3 (Microchamber)
27.2 (Mist chamber)		[159]
9-Pecos279 F2:3 population from a cross of Pecos (R) and Rosemont (S)RM3823 (Interval mapping & Composite interval mapping)7 (Interval mapping & Composite interval mapping)[145]
9qSBR9-1-127 F2:10 recombinant inbred lines population from a cross of Tetep (R) and HP2216 (S)Hvssr9-27-RM257 (2006/Cuttack)9.19 (2006/Cuttack)[160]
9qSBR9RSB03Recombinant inbred line population from a cross of RSB03 (RR) and HH1B (S)RM23869-RM376911.9[161]
9qsbr_9.1MCR10277Double haploid lines population from a cross of MCR10277 (R) and Cocodrie (S)RM24708-RM3823-[164]
9qSB9-ARJasmine 85216 Recombinant inbred lines population from a cross of Jasmine 85 (R) and Lemont (S)RM215–RM245/RM2458.55[166]
9qSB9-TXJasmine 85216 Recombinant inbred lines population from a cross of Jasmine 85 (R) and Lemont (S)RM215–RM245/RM24511.72[166]
9qSB9-LAJasmine 85216 Recombinant inbred lines population from a cross of Jasmine 85 (R) and Lemont (S)RM215–RM245/RM2454.56[166]
9qSBR-9JarjianBackcross inbred lines population from a cross of Jarjian (R) and Koshihikari (S)Nag08KK18184-Nag08KK18871-[167]
9qshb9.1-F2:3 and BC1F2 populations from a cross of ARC10531 (R) and BPT-5204 (S)RM257-RM2428.40[170]
9qshb9.2-F2:3 and BC1F2 populations from a cross of ARC10531 (R) and BPT-5204 (S)RM205-RM10519.81[170]
9qshb9.3-F2:3 and BC1F2 populations from a cross of ARC10531 (R) and BPT-5204 (S)RM24260-RM374412.58[170]
9qHZaDR9CJ06Double haploid population from a cross of TN1 (R) and CJ06 (S)RM444-AGPSMA4.26[171]
9qHZbDR9CJ06Double haploid population from a cross of TN1 (R) and CJ06 (S)RM278-RM3919B6.76[171]
10qSB-10Teqing216 Recombinant inbred lines population from a cross of Teqing (R) and Lemont (S)RG561-[144]
10QDs10BinamBC2F5 introgression lines from a cross of Binam (R) and Teqing (S)RM467-[158]
11qSB-11Lemont (1997 & 1998)128 F2 clonal population from a cross of Jasmine 85 (R) and Lemont (S)G44–RG118 (1997)
G44–RG118 (1998)		20.5 (1997)
31.2 (1998)		[151]
11qSB-11Zhai Ye Qing 8Double haploid population from a cross of Zhai Ye Qing 8 (R) and Jingxi 17 (S)CT224-CT442.8[153]
11qSB-11Teqing115 F2 clonal population from a cross of Teqing (R) and Lemont (S)RM167-Y52912.5-12.3[156]
11qSB11Le BC4F1 population from a cross of Teqing (R) and Lemont (S)Z405-Z286-[157]
11QDs11bTeqingBC2F5 introgression lines from a cross of Tarom Molaii (R) and Teqing (S)RM224-[158]
11QRh11TeqingBC2F5 introgression lines from a cross of Tarom Molaii (R) and Teqing (S)RM224-[158]
11QDs11aBinamBC2F5 introgression lines from a cross of Binam (R) and Teqing (S)RM187-[158]
11qSBR11-1-127 F2:10 recombinant inbred lines population from a cross of Tetep (R) and HP2216 (S)sbq1-RM224 (2004/New Delhi)
sbq11-RM224 (2005/New Delhi)
RM224-K39516 (2007/Cuttack)		13.99 (2004/New Delhi)
11.99 (2005/New Delhi)
13.38 (2007/Cuttack)		[160]
11qSBR11-2-127 F2:10 recombinant inbred lines population from a cross of Tetep (R) and HP2216 (S)RM3428-RM209 (2006/New Delhi)7.81 (2006/New Delhi)[160]
11qSBR11-3-127 F2:10 recombinant inbred lines population from a cross of Tetep (R) and HP2216 (S)RM536-RM202 (2007/Cuttack)13.38 (2007/Cuttack)[160]
11--217 sub-core entries from the USDA rice core collectionRM72031.9[163]
11--217 sub-core entries from the USDA rice core collectionRM2545.3[163]
11--217 sub-core entries from the USDA rice core collectionRM12335.1[163]
11qShB11Bengal (Wild2/2008)
Not identified in three other assays		253 BC2F1 lines populations from a cross of O. nivara (acc. IRGC104705) (R) and Bengal (S) as wild-2 population.RM5711-RM2 (Wild2/2008)
Not identified in three other assays		7.4 (Wild-2/2008)
Not identified in three other assays		[165]
11qSB11.1-TXLemont216 Recombinant inbred lines population from a cross of Jasmine 85 (R) and Lemont (S)RM7203–RM536/RM2024.79[166]
11qSB11.2-TXLemont216 Recombinant inbred lines population from a cross of Jasmine 85 (R) and Lemont (S)RM536–RM229/RM2875.29[166]
11qSB11HJX74HJX7463 chromosome segment substitution lines carrying the genetic background of HJX74 (R) and the donor parent Amol3(sona) (S)--[168]
11qSBD-11-1Lemont2 F2 and 1 F2:3 Populations from a cross of Yangdao 4 (R) and Lemont (S)D1103-RM261552.13 (E1)/1.56 (E2)[169]
11qSBD-11-2Lemont2 F2 and 1 F2:3 Populations from a cross of Yangdao 4 (R) and Lemont (S)RM26155-D111315.19[169]
11qSBL-11-1Lemont2 F2 and 1 F2:3 Populations from a cross of Yangdao 4 (R) and Lemont (S)D1103-RM261552.28[169]
11qSBL-11-2Lemont2 F2 and 1 F2:3 Populations from a cross of Yangdao 4 (R) and Lemont (S)RM26155-D111312.58[169]
11qSBPL-11-1Lemont2 F2 and 1 F2:3 Populations from a cross of Yangdao 4 (R) and Lemont (S)D1103-RM261552.82[169]
11qSBPL-11-2Lemont2 F2 and 1 F2:3 Populations from a cross of Yangdao 4 (R) and Lemont (S)RM26155-D111312.27[169]
11qHNDR11TN1Double haploid population from a cross of TN1 (R) and CJ06 (S)STS30-RM2029.77[171]
12QSbr12aTeqingF4 bulked populations from a cross of Teqing (R) and Lemont (S)RG214a-RZ397 [143]
12qSB-12WSS260 BC1F1 population from a cross of Hinohikari (S) /WSS2 (R)//Hinohikari (S)RM188012.9[155]
12qSB-12Teqing216 Recombinant inbred lines population from a cross of Teqing (R) and Lemont (S)G1106-[144]
12QRh12Tarom MolaiiBC2F5 introgression lines from a cross of Tarom Molaii (R) and Teqing (S)RM235-[158]
12qRLL12RSB03Recombinant inbred line population from a cross of RSB03 (RR) and HH1B (S)RM27404-RM274129.2[161]
12qsbr_12.1MCR10277Double haploid lines population from a cross of MCR10277 (R) and Cocodrie (S)RM3747-RM27608-[164]
12qShB12-mc
(Green house assay)		Bengal (Wild-2)
Not identified in other assay		252 BC2F1 lines populations from a cross of O. nivara (acc. IRGC100898) (R) and Bengal (S) as wild-1 population andRM5746-RM277 (Wild-2)
Not identified in other assay		5.3 (Wild-2)
Not identified in other assayq		[165]
12-KoshihikariBackcross inbred lines population from a cross of Jarjian (R) and Koshihikari (S)RM7025-[167]
12qSBD-12-1Yangdao 42 F2 and 1 F2:3 Populations from a cross of Yangdao 4 (R) and Lemont (S)D1239-D124610.49[169]
12qSBD-12-2Yangdao 42 F2 and 1 F2:3 Populations from a cross of Yangdao 4 (R) and Lemont (S)RM1246-D125211.95[169]
12qSBPL-12Yangdao 42 F2 and 1 F2:3 Populations from a cross of Yangdao 4 (R) and Lemont (S)RM1246-D12606.99[169]
12qHNDR12TN1Double haploid population from a cross of TN1 (R) and CJ06 (S)RM3226-RM129.15[171]
Table
Table 3. QTLs for resistance to bacterial panicle blight disease in rice.
Table 3. QTLs for resistance to bacterial panicle blight disease in rice.
ChromosomeQTLSource of Resistance AlleleMaterial Used for QTL AnalysisFlanking Markers or Nearest MarkerPhenotypic Variance (%)References
1qBPB-1-1TeQing300 Recombinant inbred lines from a cross of TeQing (R) and Lemont (S)RG472–C131 (2-year average)2.7 (2-year average)[7]
1qBPB-1-2TeQing300 Recombinant inbred lines from a cross of TeQing (R) and Lemont (S)CDO455–CDO118 (2002)4.6 (2002)[7]
1qBPB-1-3Lemont300 Recombinant inbred lines from a cross of TeQing (R) and Lemont (S)RG236–C112x (2-year average)
RG236–C112x (2001)
RZ14–RZ801 (2002)		3.6 (2-year average)
3 (2001)
3.4 (2002)		[7]
1RBG2Kele110 Backcrossed inbred lines from a cross of Kele (R) and Hitomebore (S)P068425.7 (ratio of diseased spikelets)
12.1 (ratio of diseased spikelets area)		[13,199]
2qBPB-2-1Lemont300 Recombinant inbred lines from a cross of TeQing (R) and Lemont (S)C624x–RG139 (2001)2.5 (2001)[7]
2qBPB-2-2TeQing300 Recombinant inbred lines from a cross of TeQing (R) and Lemont (S)on end at RG520 (2002)2.1 (2002)[7]
3qBPB-3-1TeQing300 Recombinant inbred lines from a cross of TeQing (R) and Lemont (S)C515–RG348x (2-year average)
C515–RG348x (2001)
C515–RG348x (2002)		13.8 (2-year average)
12.7 (2001)
9.8 (2002)		[7]
3qBPB-3-2Lemont300 Recombinant inbred lines from a cross of TeQing (R) and Lemont (S)G249–RG418 (2-year average)
G249–RG418 (2001)
G249–RG418 (2002)		3.6 (2-year average)
3.5 (2001)
3.2 (2002)		[7]
7qBPB-7TeQing300 Recombinant inbred lines from a cross of TeQing (R) and Lemont (S)BCD855–CDO497 (2001)2.8 (2001)[7]
8qBPB-8-1TeQing300 Recombinant inbred lines from a cross of TeQing (R) and Lemont (S)on end at C424x (2-year average)2.9 (2-year average)[7]
8qBPB-8-2Lemont300 Recombinant inbred lines from a cross of TeQing (R) and Lemont (S)C825x–G104 (2-year average)
C825x–G104 (2002)		3.8 (2-year average)
2.8 (2002)		[7]
10qBPB-10TeQing300 Recombinant inbred lines from a cross of TeQing (R) and Lemont (S)RG214x–CDO98 (2-year average)
CDO98–Y1065La (2001)		3.6 (2-year average)
5.7 (2001)		[7]
10RBG1 (qRBS1)Nona Bokra44 Chromosome segment substitution lines from a cross of Nona Bokra (R) and Koshihi-kari (S)RM474-RM736122[14]
11qBPB-11TeQing300 Recombinant inbred lines from a cross of TeQing (R) and Lemont (S)RZ900–G44 (2-year average)
RZ900–G44 (2002)		2.9 (2-year average)
4.6 (2002)		[7]

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Zarbafi, S.S.; Ham, J.H. An Overview of Rice QTLs Associated with Disease Resistance to Three Major Rice Diseases: Blast, Sheath Blight, and Bacterial Panicle Blight. Agronomy 2019, 9, 177. https://doi.org/10.3390/agronomy9040177

AMA Style

Zarbafi SS, Ham JH. An Overview of Rice QTLs Associated with Disease Resistance to Three Major Rice Diseases: Blast, Sheath Blight, and Bacterial Panicle Blight. Agronomy. 2019; 9(4):177. https://doi.org/10.3390/agronomy9040177

Chicago/Turabian Style

Zarbafi, Seyedeh Soheila, and Jong Hyun Ham. 2019. "An Overview of Rice QTLs Associated with Disease Resistance to Three Major Rice Diseases: Blast, Sheath Blight, and Bacterial Panicle Blight" Agronomy 9, no. 4: 177. https://doi.org/10.3390/agronomy9040177

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