QTL analysis
The parents along with RILs exhibited marked variation for the reaction to bacterial blight. Differences were observed for the lesion size between the two parents (Danteshwari and Dagaddeshi). The RILs exhibited transgressive segregation in both directions, which indicated that neither parent contained all the alleles for resistance or susceptibility. Reaction of RILs, for bacterial blight, could not be classified into discrete classes of resistance and susceptibility as they showed continuous variation and skewed distribution that suggested the inheritance is quantitative. Transgressive segregations among the RILs were observed for the Lesion length.
The genotypic data and field based phenotypic data of bacterial blight (Lesion Length) was analyzed using QTL cartographer” 2.5. Six QTL‘s “were identified on chromosome1, 5, & 9 for bacterial blight tolerance (Lesion Length) under artificial inoculated conditions (Table 1).
Table 1. Identified QTL on D × D derived genotyped RIL population
S. No.
|
CH #
|
No. of QTLs
|
1
|
1
|
3
|
2
|
5
|
1
|
3
|
9
|
2
|
|
Total
|
6
|
QTL mapping was carried out by Wang et al [20] (“Composite Interval Mapping) with a threshold value of 2.5 to 3.0 LOD, was used for declaring the presence of a suggestive QTL. Contribution rate” (R2) “was estimated as the percentage of the total phenotypic variation explained by each locus. The LOD score and phenotypic variance for QTL (LOD 2.5 to 3) ranged from 2.569565217 to 4.434782609 (Table” 3). “One QTL influencing lesion length was with positive additive effect and five QTLs with negative additive effects influencing lesion length was identified indicating that alleles at these loci are being contributed by either of the parents respectively (table 2)
Table 2:-Identified QTL influencing bacterial blight lesion size on D × D derived genotyped RIL population under artificial inoculated conditions expressing positive and negative additive effects
QTL's associated with bacterial leaf blight tolerance
Six QTL’s on D × D derived genotyped RIL population under artificial inoculated condition was identified. Three QTL’s were on CH# 1 (marker interval RM259 to RM243, RM572 to 58.61 cM and RM3825” o “147.21 cM), one on CH#5 (marker interval RM188 to 101.01cM) and two on CH#9 (marker interval HvSSR937 to 67.61 cM, and RM242 to RM278) which influenced lesion length with LOD values 3.565217391, 2.845652174, 2.569565217, 2.919565217, 4.434782609, 3.52826087 which explained 0.1789, 0.702, 1.1285, 4.4068, 8.242, 7.0316 % phenotypic variation respectively (Table 3).
Plants or plant populations exposed to a certain pathogen or pest organism often differ in degree of infestation or infection in quantitative ways. Such differences may be due to environmental or plant development stage differences between plots or to differences in inherited levels of plant defense. Several cultural measures may be applied to reduce the development of foliar diseases, but they have their limitations Jorgensen et al” [3] “The most reliable and environmentally friendly way to protect crops is the growth of cultivars with genetic resistance against their attackers. Breeding for adequate levels of resistance is indeed one of the most important goals in crop breeding. More and more breeders are recognizing the use of quantitative resistance (QR) as a valuable approach to protect crops. In case the level of resistance achieved in a particular plant-pathosystem is not sufficient in some seasons or regions to protect the crop sufficiently, QR is still useful because of the reduction in required pesticide applications Naerstad” et al, [10]. “Screening a panel of accessions of a crop species against propagules of a pathogenic organism (inoculum) nearly always reveals diversity in quality and quantity of infection. Some plants may seem to be not infected at all (immune), others show at most some flecks but no reproduction of pathogens (full resistance), and again others show various levels of infections and pathogen reproduction. Two recent reviews, by Zhang” et al. [22] and by Poland et al. [13], “discuss the genetic and molecular basis of qualitative and quantitative resistances to biotrophic and necrotrophic pathogens, and a review by St. Clair” [15] “discusses particularly the quantitative aspect of resistance.
The presence of two major types of disease resistance to plant pathogens ± vertical resistance and horizontal resistance ± has long been recognized in interactions between plant hosts and their pathogens” Vander Plank [18]; Nelson [11]; Simmonds [14]. “Vertical resistance in many plant host-pathogen relationships is hypersensitive, race- specific, and governed by interactions between avirulence genes in pathogens and resistance genes in plant hosts Van der Plank” [18]. “In contrast, horizontal resistance is quantitative, presumably non-race specific, and controlled by polygenes Van der Plank” [18]; Nelson [11], “though these assumptions have not been actively tested. In the genetics of host-pathogen interactions, a long-standing controversial issue is the nature of the genetic basis of `stabilizing selection'' which largely determines the co- evolution of many plant host-pathogen relationships, Van der Plank” [17], [18]; Leonard and Czochor [9]. “This theory states that new pathogenic race(s) will suffer a loss in general fitness when they acquire new virulence genes by mutation. Genetically, this implies that conversion of avirulence genes into corresponding virulence genes by mutation is expected to result in lower fitness of the pathogen. Unfortunately, direct evidence to support this theory has been difficult to obtain. Rice (Oryza sativa L.) bacterial blight caused by Xanthomonas oryzae pv. oryzae (Xoo) is a devastating disease in Asia. Two types of resistance to Xoo, vertical (VR, complete whole-life resistance) and horizontal (HR, quantitative resistance), have been recognized in rice Zhang and Mew” [23]. “VR to Xoo is controlled by at least 20 major genes that are usually race specific Causse et al”. [1]; Q. “Zhang et al. [21]. However, resistance of a segregating rice population to specific Xoo strains often shows both qualitative and quantitative components Koch and Parlevliet” [7]. “These characteristics of the relationship between O. sativa and Xoo offer a unique opportunity to study the genetics of the interaction between host plants and their pathogens.
The rapid progress in the development of molecular marker technique has led to the intensive use of quantitative trait loci (QTL) mapping for quantitative resistance against pathogen. Identification and mapping of QTLs is a valuable starting point for positional cloning of genes present in the QTL region of the genomes. It can also help in the interpretation of the molecular and biochemical mechanisms involved in host-pathogen interaction. The QTL studies that are conducted over several years and locations, provided information about which regions of the genome are consistently associated with the target traits. In rice about 8646 QTLs have been reported. Of these 38 QTLs have been identified for sheath blight resistance by using various types of mapping populations (www.gramene.org)
Table 3:-Identified QTL influencing bacterial leaf blight lesion size on D×D derived genotyped RIL population under artificial inoculated conditions
Tying genetic linkage map to physical map
Identification of map position was accomplished by identifying BAC or PAC clones that simultaneously contained a hit from the microsatellite marker. Forward primer sequences of genotyped polymorphic marker(s) were used for blast analysis to detect the physical position of the molecular markers and the BAC / PAC clones to which they were anchored. By way of these co-mapped markers, the map in this study is tied to the physical and sequence map developed by the International Rice Genome Sequencing Project (http://rgp.dna.affrc.go.jp/; http://www.usricegenome.org/; http://genome.arizona.edu/fpc/rice/; http://www .gramene. org/) and the principal mapping populations used by the rice scientific community. The BAC / PAC clone to which the molecular marker was anchored also contained an anchored RFLP marker along with its cM distance on the IRGSP Build 5 BAC / PAC map. The cM distance of the RFLP marker was extrapolated / assumed for the genotyped polymorphic marker(s) anchored to the clone. In the order of their occurrence on the BAC /PAC map the cM distance generated for each genotyped polymorphic marker(s) was used for developing linkage map and for QTL analysis in QTL cartographer.