Next Article in Journal
Sphingosine-1-Phosphate Receptor 3 Induces Endothelial Barrier Loss via ADAM10-Mediated Vascular Endothelial-Cadherin Cleavage
Next Article in Special Issue
Glutaredoxin in Rice Growth, Development, and Stress Resistance: Mechanisms and Research Advances
Previous Article in Journal
Natural Anticancer Molecules and Their Therapeutic Potential
Previous Article in Special Issue
Regulation of Grain Chalkiness and Starch Metabolism by FLO2 Interaction Factor 3, a bHLH Transcription Factor in Oryza sativa
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
IJMS
Volume 24
Issue 22
10.3390/ijms242216081
ijms-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Genetic Enhancement for Biotic Stress Resistance in Basmati Rice through Marker-Assisted Backcross Breeding

by
Gagandeep Singh
1,†,
Niraj Singh
1,†,
Ranjith Kumar Ellur
1,
Alexander Balamurugan
2,
G. Prakash
2,
Rajeev Rathour
3,
Kalyan Kumar Mondal
2,
Prolay Kumar Bhowmick
1,
S. Gopala Krishnan
1,
Mariappan Nagarajan
4,
Rakesh Seth
5,
K. K. Vinod
1,
Varsha Singh
1,
Haritha Bollinedi
1 and
Ashok Kumar Singh
1,*
1
Division of Genetics, ICAR-Indian Agricultural Research Institute, New Delhi 110012, India
2
Division of Plant Pathology, ICAR-Indian Agricultural Research Institute, New Delhi 110012, India
3
Department of Agriculture Biotechnology, CSKHPKV, Palampur 176062, Himachal Pradesh, India
4
Rice Breeding and Genetics Research Centre, ICAR-Indian Agricultural Research Institute, Aduthurai 612101, Tamil Nadu, India
5
Regional Station, ICAR-Indian Agricultural Research Institute, Karnal 132001, Haryana, India
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Int. J. Mol. Sci. 2023, 24(22), 16081; https://doi.org/10.3390/ijms242216081
Submission received: 24 July 2023 / Revised: 11 August 2023 / Accepted: 17 August 2023 / Published: 8 November 2023
(This article belongs to the Special Issue Molecular Research in Rice, 2nd Edition)
Browse Figures
Review Reports Versions Notes

Abstract

:
Pusa Basmati 1509 (PB1509) is one of the major foreign-exchange-earning varieties of Basmati rice; it is semi-dwarf and early maturing with exceptional cooking quality and strong aroma. However, it is highly susceptible to various biotic stresses including bacterial blight and blast. Therefore, bacterial blight resistance genes, namely, xa13 + Xa21 and Xa38, and fungal blast resistance genes Pi9 + Pib and Pita were incorporated into the genetic background of recurrent parent (RP) PB1509 using donor parents, namely, Pusa Basmati 1718 (PB1718), Pusa 1927 (P1927), Pusa 1929 (P1929) and Tetep, respectively. Foreground selection was carried out with respective gene-linked markers, stringent phenotypic selection for recurrent parent phenotype, early generation background selection with Simple sequence repeat (SSR) markers, and background analysis at advanced generations with Rice Pan Genome Array comprising 80K SNPs. This has led to the development of Near isogenic lines (NILs), namely, Pusa 3037, Pusa 3054, Pusa 3060 and Pusa 3066 carrying genes xa13 + Xa21, Xa38, Pi9 + Pib and Pita with genomic similarity of 98.25%, 98.92%, 97.38% and 97.69%, respectively, as compared to the RP. Based on GGE-biplot analysis, Pusa 3037-1-44-3-164-20-249-2 carrying xa13 + Xa21, Pusa 3054-2-47-7-166-24-261-3 carrying Xa38, Pusa 3060-3-55-17-157-4-124-1 carrying Pi9 + Pib, and Pusa 3066-4-56-20-159-8-174-1 carrying Pita were identified to be relatively stable and better-performing individuals in the tested environments. Intercrossing between the best BC3F1s has led to the generation of Pusa 3122 (xa13 + Xa21 + Xa38), Pusa 3124 (Xa38 + Pi9 + Pib) and Pusa 3123 (Pi9 + Pib + Pita) with agronomy, grain and cooking quality parameters at par with PB1509. Cultivation of such improved varieties will help farmers reduce the cost of cultivation with decreased pesticide use and improve productivity with ensured safety to consumers.

1. Introduction

Basmati rice is uniquely characterized by very-long cooked grains, delicious taste and exquisite aroma. It is a high-quality specialty rice from the Indo-Gangetic Plains, appreciated by consumers all over the world. The export of Indian Basmati rice earns more than US$ 4.7 billion annually [1]. However, this crop is constantly threatened by various biotic stresses of bacterial and fungal origin. Of them, bacterial blight (BB) disease caused by the Xanthomonas oryzae pv. oryzae (Xoo), a Gram-negative bacterium, and the rice blast caused by the heterothallic ascomycete fungal pathogen Magnaporthe oryzae, cause yield losses up to 50 to 90% [2]. These diseases are usually managed by the application of chemical pesticides. Pesticide residue in Basmati rice is one of the major concerns for the rejection of Basmati rice consignments. Furthermore, the application of chemical pesticides is not an ecologically friendly approach [3].
One of the leading Basmati rice varieties, Pusa Basmati 1509 (PB1509), with sturdy stem, semi-dwarf plant height (95–100 cm), early maturity (115–120 days), and non-shattering and exceptional grains [4], has contributed significantly to the financial reserves of the country through its export earnings. Further, due to early maturity, it provides enough opportunity to take up the timely sowing of subsequent crops. However, PB1509 is a potential target for incorporating genes for BB and blast resistance as it is highly susceptible to these diseases.
To date, 46 BB resistance genes have been mapped on various chromosomes, of which 28 genes are dominant and 18 genes are recessive in nature [5,6,7]. Among the mapped genes, eleven genes have been functionally characterized [8,9], and 15 R-genes were fine-mapped [6,7,10,11,12]. The BB resistance genes Xa4, xa5, Xa7, xa13, Xa21 and Xa38 were most frequently used in marker-assisted backcross breeding (MABB) programs for developing BB-resistant cultivars [13,14]. The BB resistance genes Xa8, xa13, Xa21 and Xa38 were effective for the isolates prevalent in the Basmati GI region [13].
The BB resistance gene xa13 was identified in the genotype BJ1 and mapped onto the chromosome [15]. This gene interacts strongly with other resistance genes, namely, Xa4, xa5 and Xa21 [16]. Studies based on the pathogenicity analysis have revealed that xa13 activates unique defense genes as compared to other major dominant R genes, namely Xa4, Xa10 and Xa26, suggesting a unique resistance mechanism of the gene [17]. Another important broad-spectrum BB resistance gene Xa21 was discovered in an accession of Oryza longistaminata. The Xa21 gene was mapped to the long arm of chromosome 11 and a functional marker, pTA248 was developed for its effective deployment through marker-assisted selection [18]. Another dominant BB resistance gene Xa38, located on the long arm of chromosome 4, was identified from an accession of Oryza nivara, and a tightly linked InDel marker (marker-LOC_Os04g53050-1) co-segregating with the BB resistance was developed [19,20]. Moreover, pyramiding two or more BB resistance genes is considered effective as it increases the spectrum of resistance and reduces the speed of evolution of isolates virulent against the deployed genes. A combination of xa13 and Xa21 has been widely utilized in rice breeding programs and several varieties have been released [21,22]. The importance of another BB resistance gene, Xa38, in rice breeding programs, is highlighted by its utilization in the development of several BB-resistant genotypes [13,23]. Considering the resistant spectrum of xa13, Xa21 and Xa38, the present study was targeted to introgress them into the genetic background of PB1509.
Another profoundly serious and devastating disease of rice is blast. Yield losses due to blast disease are variable depending on the genotype and environment, reaching up to 100% under disease-friendly conditions [24]. Similar to BB, the development of host plant resistance is the most effective strategy for the management of blast disease [25]. So far, more than 100 resistance genes have been identified and 37 of them have been cloned [26]. Although several blast resistance genes have been identified, only a few of them were used in breeding programs for blast disease management in India [27]. The major blast resistance gene, Pi9, mapped to the Piz locus on chromosome 6 confers resistance to 43 M. oryzae isolates prevalent in 13 countries. Of the six NBS-LRR domains present in this locus, Nbs2-Pi9 is the functional blast resistance gene Pi9 [28]. The Pib gene in rice is known to confer resistance to a wide range of races of the rice blast pathogen, including race IE1k [29]. Another blast resistance gene Pita located on chromosome 12 adjacent to the centromere in the genotype ‘Tetep’ [30] was found to encode a cytoplasmic protein-containing NBS-LRR domain [31,32]. The pyramiding of Pi9, Pib and Pita is a promising strategy to widen the resistant profile of genotypes as well as to achieve substantial resistance. There have been several reports of the successful incorporation of blast resistance genes into the genetic background of different rice varieties [33,34].
Considering the prevailing diseases in the Basmati growing regions of the country, developing resistance to both BB and blast diseases can prove to be an effective strategy as it can significantly reduce the use of chemical pesticides while reducing the cost of cultivation. Therefore, we attempted to incorporate BB (xa13, Xa21 and Xa38) and blast (Pi9, Pib and Pita) resistance genes into the genetic background of PB1509 through MABB.

2. Results

2.1. Generation of PB1509-NILs Carrying BB and Blast Resistance Genes

For the development of NILs with resistance to biotic stresses, four donor parents (DPs), namely, PB1718, P1927, P1929 and Tetep, were crossed with the RP (PB 1509) to generate F1s, which were designated as Pusa 3037, Pusa 3054, Pusa 3060 and Pusa 3066, respectively. The list of polymorphic markers obtained in all the cross combinations is presented in Supplementary Tables S1–S4.
The BC1F1 plants generated from the cross PB1509/PB1718 carrying the target genes xa13 and Xa21 in a heterozygous state were identified through foreground selection using the markers xa13prom and pTA248, respectively, and the recurrent parent genome (RPG) recovery estimated using 74 polymorphic SSR markers ranged from 64.8% to 84.2% (Table 1). Similarly, in BC1F1s from the cross PB1509/P1927, foreground selection with marker-Os04g53050 led to the identification of plants carrying Xa38 in a heterozygous state and RPG recovery estimated using 83 polymorphic SSR markers ranged from 73.8% to 88.6%. In the BC1F1s from the cross PB1509/P1929, the plants carrying Pi9 and Pib were found to have RPG recovery of 70.7% to 81.0% with 84 polymorphic SSR markers. In the case of PB1509/Tetep, the BC1F1s carrying Pita in a heterozygous state had RPG recovery ranging from 57.3 to 87.5%. Further, based on RPG and RP phenotype recovery, the best plants in each of the cross combinations were identified for backcrossing to generate BC2F1s.
During BC2F1 generation, background selection with the remaining polymorphic markers and the markers that were heterozygous in the BC1F1 generation revealed RPG recovery of up to 94.4%, 93.3%, 91.9% and 86.4% in the cross combinations PB1509/P1927, PB1509/ PB1718, PB1509/P1929 and PB1509/Tetep, respectively. In each of the combinations, a BC2F1 plant with maximum resemblance to the phenotype of RP coupled with maximum RPG recovery was selected and backcrossed to generate BC3F1 seeds. The best BC3F1 plant was selfed to generate BC3F2 populations. A total of 12, 15, 14 and 15 plants homozygous for Pusa 3037, Pusa 3054, Pusa 3060 and Pusa 3066, respectively, were identified through foreground selection using gene-linked markers. Stringent phenotypic screening for RP phenotype was carried out till BC3F5 generation. A total of four NILs for Pusa 3037 and 5 NILs each for Pusa 3054, Pusa 3060 and Pusa 3066 were identified and subjected to multi-location evaluation for yield and its component traits, grain and cooking quality parameters.

2.2. Background Analysis of NILs

The NILs were genotyped using Rice Pan Genome Array (RPGA) (Figure 1). Among the PB1509-NILs carrying blast resistance genes Pi9 + Pib and Pita, Pusa 3060-3-55-17-157-4-138-3 (G5) and Pusa 3066-4-56-20-158-7-170-2 (G6) possessed maximum genomic resemblance of 97.38% and 97.69%, respectively, with the RP. Of the NILs carrying BB resistance gene Xa38, a maximum genomic similarity of 98.92% was observed in the NIL Pusa 3054-2-47-7-166-24-261-2 (G16). Among the NILs carrying bacterial blight resistance genes xa13 + Xa21, Pusa 3037-1-44-3-164-21-255-1 (G12) had a maximum similarity of 98.25% with the RP genome.

2.3. Agronomic, Grain and Cooking Quality Parameters of NILs

The agro-morphological, grain and cooking quality revealed the on-par performance of NILs with the RP but for some exceptions (Table 2). Days to fifty percent flowering (DF) is the vital parameter that determines the maturity duration of the crop. DF was significantly lower in Pusa 3066-4-56-20-159-8-174-1 (G10) (81.0 days), Pusa 3060-3-55-17-157-4-138-1 (G3) (83.3 days) and Pusa 3060-3-55-17-157-4-138-2 (G4) (83.0 days) as compared to PB1509 (85.0 days). Pusa 3060-3-55-17-157-4-138-2 (G4) and Pusa 3054-2-47-7-166-24-261-2 (G16) possessed significantly higher test weight (TW) as compared to RP.
The NILs were either at par or significantly superior to RP (Table 3; Figure 2). Pusa 3066-4-56-20-158-7-172-1 (G8) possessed significantly higher hulling recovery (HR); the NILs Pusa 3066-4-56-20-158-7-171-4 (G7), Pusa 3037-1-44-3-164-21-255-1 (G12), Pusa 3037-1-44-3-164-21-256-4 (G13), Pusa 3037-1-45-5-165-22-259-4 (G14), Pusa 3054-2-47-7-166-24-261-1 (G15) and Pusa 3054-2-47-7-166-24-262-3 (G19) possessed higher milling recovery (MR) as compared to the RP. Another important quality parameter, Kernel length before cooking (KLBC), was significantly higher for the NILs, Pusa 3037-1-45-5-165-22-259-4 (G14), Pusa 3054-2-47-7-166-24-261-1 (G15) and Pusa 3054-2-47-7-166-24-262-3 (G19). The NIL Pusa 3054-2-47-7-166-24-262-2 (G18) possessed significantly higher Kernel length after cooking (KLAC). All the NILs exhibited an elongation ratio (ER) of more than two except Pusa 3060-3-55-17-157-4-138-2 (G4).

2.4. Multi-Location Evaluation

A set of 19 NILs were evaluated under three environments, viz., New Delhi (Env1), Karnal (Env2) and Urlana (Env3), in randomized complete block design (RCBD) with three replications during kharif 2021. The yield data for NILs evaluated at three locations are presented in Table 4. Three NILs for xa13 + Xa21, Pusa 3037-1-44-3-164-20-249-2 (G11), Pusa 3037-1-44-3-164-21-255-1 (G12) and Pusa 3037-1-44-3-164-21-256-4 (G13) were significantly higher yielding under the conditions of Env1. Among the NILs carrying Xa38, Pusa 3054-2-47-7-166-24-261-1 (G15), Pusa 3054-2-47-7-166-24-261-2 (G16) and Pusa 3054-2-47-7-166-24-262-2 (G18) significantly outyielded RP in Env1. NILs carrying blast resistance gene Pita, viz., Pusa 3066-4-56-20-158-7-171-4 (G7) and Pusa 3066-4-56-20-158-7-172-2 (G9), yielded significantly higher as compared to the RP. In Env2, all the NILs performed on par except for Pusa 3060-3-55-17-157-4-138-2 (G4), which was inferior to RP. Under Env3, all the NILs were on par with RP, except Pusa 3060-3-55-17-157-4-138-1, Pusa 3060-3-55-17-157-4-138-2 and Pusa 3060-3-55-17-157-4-138-3 carrying blast resistance genes Pi9 + Pib and Pusa 3054-2-47-7-166-24-262-3 carrying Xa38, which significantly underperformed.
Genotype ranking biplot detects ideal genotypes in comparison to the other evaluated genotypes. The cumulative variation explained by two components in a GGE biplot was 91.19%. NILs carrying BB resistance genes xa13 + Xa21, namely, Pusa 3037-1-44-3-164-20-249-2 (G11) and Pusa 3037-1-44-3-164-21-256-4 (G13); and the NILs carrying Xa38, viz., Pusa 3054-2-47-7-166-24-261-2 (G16), Pusa 3054-2-47-7-166-24-261-3 (G17) and Pusa 3054-2-47-7-166-24-262-2 (G18), could be considered as the best-performing genotypes owing to their presence in the innermost circle (Figure 3). The genotypes located in the inner circle are highly desirable as compared to the ones in the outer circle. Among the NILs with blast resistance genes Pi9 + Pib, Pusa 3060-3-55-17-157-4-124-1 (G1) was found to be desirable owing to its presence in the circle next to the innermost circle (Figure 3).
In the polygon pattern plot, the environmental indicators were positioned into two segments with different genotypes winning in each segment. The biplot was divided into six clockwise fan-shaped sections. Two NILs, Pusa 3037-1-44-3-164-21-255-1 (G12) and Pusa 3037-1-44-3-164-20-249-2 (G11) were high yielding and stable in Env1 and Env3, whereas one NIL, Pusa 3054-2-47-7-166-24-261-3 (G17), outperformed other genotypes and was found to be highly stable in Env2. The mean vs. stability analysis plot (Figure 4) identified Pusa 3054-2-47-7-166-24-261-2 (G16) followed by Pusa 3037-1-44-3-164-21-256-4 (G13) and Pusa 3054-2-47-7-166-24-262-2 (G18) to be high performing in Env1 and Env3, while in case of Env2, Pusa 3037-1-44-3-164-20-249-2 (G11) was the highest performer followed by Pusa 3054-2-47-7-166-24-261-3 (G17). Apart from these NILs, Pusa 3037-1-44-3-164-21-255-1 (G12) and Pusa 3060-3-55-17-157-4-124-1 (G1) provided acceptable yield but low stability because of their position away from the Average Environment Coordinate (AEC) line. We recorded Env1 and Env2 as independent and unique locations for the yield due to their shorter vector length. However, the shorter-angled-lengthy environment vector with the AEC line is ideal for the selection of suitable genotypes among the total genotypes. Thus, the greater representation and discrimination are indicated by the test environment, Env3.

2.5. Combining Genes Governing Multiple Disease Resistance

Simultaneously, the best BC3F1 plant with maximum RPG and RP phenotype recovery were intercrossed to generate Pusa 3122 (Pusa 3037/Pusa 3054), Pusa 3123 (Pusa 3037/Pusa 3060) and Pusa 3124 (Pusa 3054/Pusa 3060), carrying xa13 + Xa21 + Xa38, Pi9 + Pib + Pita and Xa38 + Pi9 + Pib, respectively. All the NILs developed were on par with PB1509 for agronomic, yield and yield-related traits (Table 5). DF was significantly lower (82.5 days) in the NIL for Pi9 + Pib + Pita and Pusa 3123-33-13-312-25 (G29) in comparison to RP (85.5 days). The trait affecting the yield of the crop, NT, was significantly higher in Pusa 3124-38-19-176-5 (G24) with an average of 20.5 productive tillers/plant. In terms of their grain and cooking quality, all the NILs exhibited grain parameters similar to PB1509 and had an excellent cooking quality with an elongation ratio of greater than two (Table 6 and Figure 4).

2.6. Screening for BB and Blast Resistance

During kharif 2020 and 2021, the NILs were evaluated for BB resistance using the Xoo race 4 (Supplementary Table S5, Figure 5 and Figure 6). The RP was highly susceptible with lesion lengths of 14.37 ± 0.71 cm, while the DPs, PB1718 (xa13 + Xa21) and P1927 (Xa38), were highly resistant with lesion lengths of 1.77 ± 0.45 cm and 0.61 ± 0.17 cm, respectively. The NILs carrying xa13 + Xa21 showed highly resistant reactions with the lesion lengths ranging from 1.68 ± 0.44 cm in the NIL, Pusa 3037-1-45-5-165-22-259-4 (G14) to 3.49 ± 0.80 cm in Pusa 3037-1-44-3-164-20-249-2 (G11). The Xa38-carrying NILs possessed lesion lengths ranging from 0.33 ± 0.06 cm in Pusa 3054-2-47-7-166-24-262-2 (G18) to 2.76 ± 0.80 cm in Pusa 3054-2-47-7-166-24-261-3 (G17). In the NILs carrying xa13 + Xa21 + Xa38, the lesion length ranged from 0.25 ± 0.05 cm in Pusa 3122-27-16-166-1 (G21) to 0.49 ± 0.11 cm in Pusa 3122-27-15-165-2 (G20). In the NILs carrying Xa38 + Pi9 + Pib for bacterial blight resistance, lesion lengths ranged from 0.21 ± 0.008 cm in Pusa 3124-40-21-179-4 (G25) to 0.43 ± 0.09 cm in Pusa 3124-40-22-180-2 (G26).
Screening for the blast resistance was carried out at IARI, New Delhi, and CSKHPKV, Palampur, for two seasons. All the NILs carrying blast resistance genes Pi9 + Pib and Pita exhibited resistance reactions for the isolate Mo-ei-MB20 under artificial epiphytotics at New Delhi (Table 7). The PB1509-NILs carrying Pi9 + Pib, namely, Pusa 3060-3-55-17-157-4-124-1 (G1), Pusa 3060-3-55-17-157-4-124-6 (G2), Pusa 3060-3-55-17-157-4-138-1 (G3), Pusa 3060-3-55-17-157-4-138-3 (G5) and Pita-carrying NILs, viz., Pusa 3066-4-56-20-158-7-171-4 (G7) and Pusa 3066-4-56-20-158-7-172-2 (G9), produced a resistant reaction with the disease score of one. The NILs carrying Pi9 + Pib + Pita were highly resistant with a disease score of zero. Among the NILs carrying Xa38 + Pi9 + Pib, viz., Pusa 3124-38-19-176-5 (G24) and Pusa 3124-40-22-180-2 (G26), maximum resistance was shown to the blast isolate with a disease score of one. With the mixture of five races, viz., Po-RML21, Po-RML29, Po-HP5-2, Po-NWI-102 and Po-NWI-141, all the NILs tested were found to be resistant.

3. Discussion

PB1509 is an elite Basmati rice variety and is popular among farmers owing to its early maturity, semi-dwarfness, exquisite grain and cooking qualities. Furthermore, it contributes immensely to the national exchequer due to its export potential. However, it suffers adversely due to biotic stresses imposed by disease-causing organisms such as Xoo and M. oryzae. Choosing pesticides wisely and their timely application is essential for the management of this disease. However, there are several concerns associated with environmental hazards and consumer safety. Additionally, the rise in the stringency of pesticide residue limits by importing nations has led to concerns of the rejection of Basmati rice consignments. Therefore, developing inbuilt genetic resistance is the only viable option for the maintenance of healthy international trade, the environment, and satisfied consumers. MABB is considered an effective approach for arming the Basmati rice cultivars with inbuilt disease resistance [35]. To ameliorate the issue of susceptibility to diseases, the present study was aimed at incorporating three bacterial blight resistance genes, namely, xa13, Xa21 and Xa38, and blast resistance genes, namely, Pi9, Pib and Pita, in various combinations, into the genetic background of PB1509.
The Xoo pathogen is known to secrete transcription-activator-like effectors (TALEs), which target promoters for induction of one of the SWEET genes (SWEET11, SWEET13 and SWEET14). The major BB resistance gene xa13 provides race-specific resistance and it is also referred to as SWEET11. The other dominant gene Xa21 is known to encode a receptor kinase with the NBS-LRR domain, which recognizes a conserved determinant present in multiple races of Xoo [36]. The combination of xa13 and Xa21 has been proven to provide synergistic action in imparting elevated levels of resistance to the Xoo isolates. Therefore, xa13 + Xa21 has been widely deployed into rice varieties such as Pusa Basmati 1, Ranbir Basmati, PRR78, Pusa 6B, etc. [37,38]. However, recently there have been reports of the breakdown of resistance governed by xa13 + Xa21 [39]. Subsequently, a major dominant BB resistance gene Xa38 with broad-spectrum resistance mapped on chromosome 4 [19] was incorporated into a series of elite rice varieties, viz., Pusa Basmati 1121, Super Basmati and Improved Samba Mahsuri [13,23,40]. The NILs carrying Xa38 were resistant to a greater number of races of Xoo as compared to the NILs carrying xa13 + Xa21, indicating a wider spectrum of resistance governed by the gene Xa38 [13]. The pyramiding of multiple genes improves the resistance spectrum of a genotype as well as reduces the speed of evolution of pathogens. Therefore, incorporating xa13 + Xa21 and Xa38 into the genetic background of PB1509 was considered a better choice to have prolonged resistance against multiple races of Xoo. We used PB1718 and P1927, carrying BB resistance genes xa13 + Xa21 and Xa38, respectively, as DPs.
For blast resistance, Pi9 and Pita were identified as effective against the M. oryzae isolates prevalent in the Basmati rice growing region of the country, which includes the states of Punjab, Haryana, Delhi, Jammu and Kashmir, Himachal Pradesh, Western Uttar Pradesh and Uttarakhand [41,42,43]. Therefore, Pusa 1929 carrying Pi9 and Pib in the genetic background of Pusa Basmati 1, and Tetep carrying Pita, was used as DPs. The successful incorporation of blast resistance genes, namely, Pi9, Pi2, Pi54, Pita, Pib and Pi1 in Basmati varieties, has been demonstrated earlier [41]. Several blast-resistant varieties, namely, Pusa Basmati 1609, Pusa Basmati 1637, Pusa 1612, Pusa Basmati 1847, etc., have been developed and released for commercial cultivation [34,44].
Marker-assisted backcross breeding is the effective approach for defect correction in the otherwise agronomically superior varieties. Three rounds of backcrossing were employed to ensure sufficient recovery of the RP genome. In each of the backcross generations, foreground selection ensured the incorporation of the target gene, and background and phenotypic selection identified the plant with maximum recovery for the RP genome and phenotype, respectively. The current strategy has led to the development of five NILs carrying Xa38 (Pusa 3054) and four NILs carrying xa13 + Xa21 (Pusa 3037), which exhibited an RP genome similarity of more than 97%. The NILs carrying xa13 + Xa21 were highly resistant with BB lesion lengths ≤ 3.5 cm, while the NILs carrying Xa38 possessed lesion lengths of ≤3.0 cm. The NILs carrying xa13 + Xa21 + Xa38 possessed lesion lengths of ≤1.0 cm. This indicates that xa13 + Xa21, Xa38 and xa13 + Xa21 + Xa38 were effective in conferring resistance against the virulent isolates dominant in Basmati-producing regions of the country. The successful introgression of bacterial blight resistance genes xa13, Xa21, Xa4, xa5, Xa33, Xa40, etc., has been earlier reported [14,45,46,47]. Similarly, five NILs both for Pi9 + Pib (Pusa 3060) and Pita (Pusa 3066) were developed, which were highly resistant to the prevalent isolates Mo-ei-MB20, Po-RML21, Po-RML29, Po-HP5-2, Po-NWI-102 and Po-NWI-14 under artificial inoculated conditions.
Background selection using SSR markers during early backcross generations has led to maximizing RPG recovery, which ranged from 86.1% to 99.6% during BC3F1 generation. SSR markers were cost-effective, accessible, and with better ease of handling in the laboratory [48]. Therefore, SSRs were suited for background selection during backcross generations. Further, high-density SNP assays aid in having accurate estimates of background recovery as well as DP introgressions [49]. Therefore, RPGA comprising 80K SNPs was used for background analysis in the advanced generations for identifying the lines with maximum similarity to RP [38]. The effectiveness of the approach was evident from the genome similarity values of more than 96% observed in NILs as compared to RP, with a maximum similarity of 98.92% in the NIL, Pusa 3054-2-47-7-166-24-261-2 (G16).
An ideal genotype should possess better stability with high per se performance. Therefore, multi-environment testing of NILs was performed. In ranking genotypes of GGE biplot, the ring at the head of the arrow on the horizontal axis represents an ideal genotype [50]. The NILs, Pusa 3037-1-44-3-164-20-249-2 (G11), Pusa 3037-1-44-3-164-21-256-4 (G13), Pusa 3054-2-47-7-166-24-261-2 (G16), Pusa 3054-2-47-7-166-24-261-3 (G17) and Pusa 3054-2-47-7-166-24-262-2 (G18) were identified as near ideal genotypes for yield per hectare as they were placed in the innermost circle near to the hypothetical ideal genotype.
Considering the mean vs. stability analysis plot, the arrow sign on the AEC line ranks the genotypes in increasing order. The NILs, G16, G13 and G18 were high-yielding in Env1 and Env3, while G11 and G17 were the genotypes with higher yield in Env2. Pusa 3037-1-44-3-164-21-255-1 (G12) and Pusa 3060-3-55-17-157-4-124-1 (G1) were less stable but with a high yield. Therefore, this genotype can be a potential line for the crop improvement program. A genotype placed on the horizontal axis with zero vertical projection is considered more stable, while a genotype with a lengthy direction from the AEC abscissa is treated as an unstable genotype [51]. In the ‘which-won-where’ pattern plot, the environmental indicators are positioned into two segments, confirming the presence of distinct interaction between genotype and environment. The genotype that is attached to the vertex of polygon where the environmental marker drops suggests that the genotype gives a high yield and performs best in that environment [52]. Therefore, G11 was the best performer in Env 1 and 3, whereas G1 was best for Env 2.
Several rice varieties with resistance to either bacterial blight or blast have been developed and released for cultivation, which provides farmers an opportunity to choose according to the disease prevalence in their growing environment. However, in the majority of the Basmati growing regions, BB and blast co-exist, which raises the need for combining bacterial blight and blast resistance into high-yielding varieties [53]. Therefore, PB1509 NILs carrying xa13 + Xa21 + Xa38, Pi9 + Pib + Pita and Xa38 + Pi9 + Pib were developed. These lines were effective against the BB and blast isolates prevalent in the Basmati growing regions of the country. The adoption of multi-disease resistant NILs would reduce the application of chemical pesticides, paving the way for eco-friendly rice cultivation, which is safe for consumers, while strengthening the international trade of Basmati.

4. Materials and Methods

4.1. Plant Material

PB1509, an elite Basmati rice variety was used as RP; PB1718 carrying BB resistance genes xa13 +Xa21, P1927 carrying BB resistance gene Xa38, P1929 carrying blast resistance genes Pi9 + Pib, and Tetep possessing blast resistance gene Pita were used as the DPs.

4.2. Breeding Strategy

The breeding methodology adopted is presented in Figure 7. RP was crossed with four different DPs to generate F1 seeds. The F1 plant was selected based on a test of hybridity and backcrossed with RP to produce BC1F1 seeds. Foreground selection was then carried out on BC1F1 plants to identify the heterozygous plants, which were then subjected to background selection followed by phenotypic selection for agro-morphological and grain quality parameters. A BC1F1 plant with maximum resemblance to recurrent parent was backcrossed to generate BC2F1 seeds. Subsequently, same strategy was followed to generate BC3F1 seeds. The BC3F1 plant with superiority was selfed, and the plants homozygous for genes of interest were identified in BC3F2 populations. These lines were tested for grain and cooking quality traits and advanced through pedigree selection till BC3F5 generation.
Simultaneously, intercrosses were made between the best BC3F1s plants to generate intercross F1s carrying xa13 + Xa21 + Xa38, Xa38 + Pi9 + Pib and Pi9 + Pib + Pita. The plants homozygous for the respective genes were identified in the intercross F2 populations and were advanced till F6 generation through pedigree selection. The developed NILs were evaluated before being nominated into the national system of varietal release.

4.3. DNA Extraction and PCR

The genomic DNA was extracted from 15-day-old seedlings using CTAB buffer with slight modification to the protocol [54]. PCR of 10 μL volume was set up using 20–30 ng template DNA, 5 pmol of each primer and EmeraldAmp Max PCR Master Mix (2X Premix, Takara) using the Biorad T100TM thermal cycler with the standard PCR program and electrophoresis was carried out using Metaphor™ agarose gel and visualized on Gel DocTM XR+ documentation System.

4.4. Foreground Selection

Foreground selection for the genes xa13, Xa21 and Pi9 was carried out using the gene-based markers, namely, xa13prom, pTA248 and Pi9STS1, respectively. The selection for the genes Xa38, Pib and Pita was conducted using gene-linked markers, viz., marker-Os04g53050-1, RM535 and RRS12, respectively.

4.5. Recurrent Parent Genome Recovery Using SSR and SNP Markers

The RP and the DPs were surveyed for polymorphic markers using 735 genome-wide SSR markers from the URL link http://www.gramene.org (accessed on 22 August 2016) and the primers were synthesized. A final set of developed NILs were subjected to estimation of RPG similarity using Affymetrix based 80K RPGA [55]. The genome similarity was visualized using the Phenogram software from the URL link http://visualization.ritchielab.psu.edu/phenograms/plot (accessed on 12 February 2023). The similarity to the genome of RP was obtained using the formula, (R + 1/2H) X 100/P, where R = Number of markers amplifying homozygous allele for recurrent parent, H = number of heterozygous markers and P = total number of markers.

4.6. Screening for Disease Resistance

For evaluation of BB resistance, the parental lines and NILs were grown in the field conditions. The suspension of Xoo race 4 with a density of 109 cells/mL was prepared. Inoculation was performed with the isolate by clip inoculation method wherein top five leaves from every entry were clipped [56]. The length of BB lesion was measured post-21 days of inoculation. The genotype with a lesion length of up to 5 cm was considered to be resistant, 5–10 cm was considered to be moderately resistant reaction, 10–15 cm was considered to be moderately susceptible response, and more than 15 cm to be as completely susceptible [57].
To screen for blast resistance, the NILs carrying blast resistance genes along with the RP and DPs were grown in pro-trays as per the protocol [58]. The seedlings were grown under optimum conditions at temperature of 28 °C and 95% relative humidity. At three-leaf stage, the inoculum of M. oryzae isolate comprising of approximately 5 × 104 conidia per ml was mixed with 0.02% tween 20 and sprayed on the seedlings. At IARI, New Delhi, M. oryzae isolate Mo-ei-MB20 was used for screening. Mixture of five isolates, namely, Po-RML21, Po-RML29, Po-HP5-2, Po-NWI-102 and Po-NWI-141, constituted the inoculum for screening at Palampur. The seedlings were scored for the blast resistance 7 days post-inoculation following Bonman’s scale. Scores of 0–3 were considered resistant reactions, and scores of 4 and 5 were considered susceptible reactions.

4.7. Multi-Environment Agro-Morphological Evaluation of Developed NILs

The NILs along with the RP and DPs were evaluated for agronomic performance with three replications in RCBD at three different environments, namely, IARI-New Delhi (Env1), IARI Regional Station-Karnal (Env2), and Urlana (Env3), during kharif 2021 following recommended agronomic practices. Data for traits, viz., DF, PH, PL, NT, NFG, SF, TW and grain yield, were recorded. DF was recorded on a plot basis. A representative ten plants from each of the NILs were considered for measurement of other traits.

4.8. Grain and Cooking Quality Evaluation of Developed NILs

Traits related to quality, namely, HR, MR, HRR, KLBC, KBBC, KLAC, KBAC, ER, and aroma, were recorded following standard protocol. HR was calculated in percentage as the ratio of the weight of whole polished grains to the weight of the raw grains. Grain parameters such as KLBC and KBBC were recorded on a photo enlarger using ten grains from each of the NILs. For the recording of cooking quality characteristics, namely, KLAC and KBAC, ten whole milled kernels were selected and soaked for 30 min in 10 mL of distilled water taken in test tubes. The lower part of the tubes with rice kernels was then immersed in a boiling water bath for 8–10 min. The cooked kernels were cooled to room temperature after transferring the contents into a Petri plate, and data were recorded. The data were subjected to statistical analysis using the package CropStat 7.2 [59], and stability analysis was carried out using the Metan package v 1.18.0 [60].

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ijms242216081/s1.

Author Contributions

A.K.S.: Conceptualization and Funding Acquisition. G.S., N.S., R.K.E., V.S., P.K.B., A.B., M.N., A.B., G.P., R.R. and K.K.M.: Investigation. G.S. and R.K.E.: Formal Analysis. R.K.E., S.G.K., K.K.V., R.S., H.B.: Supervision. G.S. and N.S.: Writing-original draft. R.K.E., and G.S.: Writing—review and edit. R.K.E. and A.K.S.: methodology and project administration. All authors have read and agreed to the published version of the manuscript.

Funding

This research received funding from the DBT project entitled “Incorporation of biotic stress resistance in the genetic background of Pusa Basmati 1509 through marker assisted backcross breeding” (BT/PR13578/AG/106/991/2015 dated 05/01/2016).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data are contained within the article or Supplementary Materials.

Conflicts of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

References

  1. APEDA. India Export of Agro Food Products—Basmati Rice. Available online: https://agriexchange.apeda.gov.in/indexp/Product_description_32headChart.aspx?gcode=0601 (accessed on 26 October 2022).
  2. Ellur, R.K.; Khanna, A.; Yadav, A.; Pathania, S.; Rajashekara, H.; Singh, V.K.; Gopala Krishnan, S.; Bhowmick, P.K.; Nagarajan, M.; Vinod, K.K.; et al. Improvement of Basmati Rice Varieties for Resistance to Blast and Bacterial Blight Diseases Using Marker Assisted Backcross Breeding. Plant. Sci. 2016, 242, 330–341. [Google Scholar] [CrossRef]
  3. Khanna, A.; Sharma, V.; Ellur, R.K.; Shikari, A.B.; Gopala Krishnan, S.; Singh, U.D.; Prakash, G.; Sharma, T.R.; Rathour, R.; Variar, M.; et al. Development and Evaluation of Near-Isogenic Lines for Major Blast Resistance Gene(s) in Basmati Rice. Theor. Appl. Genet. 2015, 128, 1243–1259. [Google Scholar] [CrossRef]
  4. Singh, A.; Krishnan, S.; Nagarajan, M.; Kurungara, V.; Bhowmick, P.; Atwal, S.; Seth, R.; Chopra, N.; Chander, S.; Singh, V.; et al. Variety Pusa Basmati 1509. Indian J. Genet. Plant Breed. 2014, 74, 123. [Google Scholar]
  5. Kim, S.-M.; Reinke, R.F. A Novel Resistance Gene for Bacterial Blight in Rice, Xa43(t) Identified by GWAS, Confirmed by QTL Mapping Using a Bi-Parental Population. PLoS ONE 2019, 14, e0211775. [Google Scholar] [CrossRef]
  6. Chen, S.; Wang, C.; Yang, J.; Chen, B.; Wang, W.; Su, J.; Feng, A.; Zeng, L.; Zhu, X. Identification of the Novel Bacterial Blight Resistance Gene Xa46(t) by Mapping and Expression Analysis of the Rice Mutant H120. Sci. Rep. 2020, 10, 12642. [Google Scholar] [CrossRef]
  7. Neelam, K.; Mahajan, R.; Gupta, V.; Bhatia, D.; Gill, B.K.; Komal, R.; Lore, J.S.; Mangat, G.S.; Singh, K. High-Resolution Genetic Mapping of a Novel Bacterial Blight Resistance Gene Xa-45(t) Identified from Oryza Glaberrima and Transferred to Oryza sativa. Theor. Appl. Genet. 2020, 133, 689–705. [Google Scholar] [CrossRef]
  8. Iyer, A.S.; McCouch, S.R. The Rice Bacterial Blight Resistance Gene Xa5 Encodes a Novel Form of Disease Resistance. Mol. Plant Microbe Interact. 2004, 17, 1348–1354. [Google Scholar] [CrossRef] [PubMed]
  9. Chu, Z.; Fu, B.; Yang, H.; Xu, C.; Li, Z.; Sanchez, A.; Park, Y.J.; Bennetzen, J.L.; Zhang, Q.; Wang, S. Targeting xa13, a Recessive Gene for Bacterial Blight Resistance in Rice. Theor. Appl. Genet. 2006, 112, 455–461. [Google Scholar] [CrossRef] [PubMed]
  10. Zhang, F.; Zhuo, D.-L.; Zhang, F.; Huang, L.-Y.; Wang, W.-S.; Xu, J.-L.; Vera Cruz, C.; Li, Z.-K.; Zhou, Y.-L. Xa39, a Novel Dominant Gene Conferring Broad-Spectrum Resistance to Xanthomonas Oryzae Pv. Oryzae in Rice. Plant Pathol. 2015, 64, 568–575. [Google Scholar] [CrossRef]
  11. Liang, L.Q.; Wang, C.Y.; Zeng, L.X.; Wang, W.J.; Feng, J.Q.; Chen, B.; Su, J.; Chen, S.; Shang, F.D.; Zhu, X.Y.; et al. The Rice Cultivar Baixiangzhan Harbours a Recessive Gene Xa42(t) Determining Resistance against Xanthomonas oryzae pv. oryzae. Plant Breed. 2017, 136, 603–609. [Google Scholar] [CrossRef]
  12. Kim, S.-M. Identification of Novel Recessive Gene Xa44(t) Conferring Resistance to Bacterial Blight Races in Rice by QTL Linkage Analysis Using an SNP Chip. Theor. Appl. Genet. 2018, 131, 2733–2743. [Google Scholar] [CrossRef]
  13. Ellur, R.K.; Khanna, A.; Bhowmick, P.K.; Vinod, K.K.; Nagarajan, M.; Mondal, K.K.; Singh, N.K.; Singh, K.; Prabhu, K.V.; Singh, A.K. Marker-Aided Incorporation of Xa38, a Novel Bacterial Blight Resistance Gene, in PB1121 and Comparison of Its Resistance Spectrum with xa13 + Xa21. Sci. Rep. 2016, 6, 29188. [Google Scholar] [CrossRef]
  14. Hsu, Y.-C.; Chiu, C.-H.; Yap, R.; Tseng, Y.-C.; Wu, Y.-P. Pyramiding Bacterial Blight Resistance Genes in Tainung82 for Broad-Spectrum Resistance Using Marker-Assisted Selection. Int. J. Mol. Sci. 2020, 21, 1281. [Google Scholar] [CrossRef]
  15. Zhang, G.; Angeles, E.R.; Abenes, M.L.P.; Khush, G.S.; Huang, N. RAPD and RFLP Mapping of the Bacterial Blight Resistance Gene Xa-13 in Rice. Theor. Appl. Genet. 1996, 93, 65–70. [Google Scholar] [CrossRef]
  16. Li, Z.K.; Sanchez, A.; Angeles, E.; Singh, S.; Domingo, J.; Huang, N.; Khush, G.S. Are the Dominant and Recessive Plant Disease Resistance Genes Similar? A Case Study of Rice R Genes and Xanthomonas Oryzae Pv. Oryzae Races. Genetics 2001, 159, 757–765. [Google Scholar] [CrossRef]
  17. Chu, Z.; Ouyang, Y.; Zhang, J.; Yang, H.; Wang, S. Genome-Wide Analysis of Defense-Responsive Genes in Bacterial Blight Resistance of Rice Mediated by the Recessive R Gene Xa13. Mol. Genet. Genomics 2004, 271, 111–120. [Google Scholar] [CrossRef]
  18. Ronald, P.C.; Albano, B.; Tabien, R.; Abenes, L.; Wu, K.; McCouch, S.; Tanksley, S.D. Genetic and Physical Analysis of the Rice Bacterial Blight Disease Resistance Locus, Xa21. Mol. Gen. Genet. 1992, 236, 113–120. [Google Scholar] [CrossRef]
  19. Cheema, K.K.; Grewal, N.K.; Vikal, Y.; Sharma, R.; Lore, J.S.; Das, A.; Bhatia, D.; Mahajan, R.; Gupta, V.; Bharaj, T.S.; et al. A Novel Bacterial Blight Resistance Gene from Oryza Nivara Mapped to 38 Kb Region on Chromosome 4L and Transferred to Oryza sativa L. Genet. Res. 2008, 90, 397–407. [Google Scholar] [CrossRef]
  20. Bhasin, H.; Bhatia, D.; Raghuvanshi, S.; Lore, J.S.; Sahi, G.K.; Kaur, B.; Vikal, Y.; Singh, K. New PCR-Based Sequence-Tagged Site Marker for Bacterial Blight Resistance Gene Xa38 of Rice. Mol. Breed. 2012, 30, 607–611. [Google Scholar] [CrossRef]
  21. Singh, A.; Krishnan, S.; Ellur, R.K.; Bhowmick, P.K.; Nagarajan, M.; Vinod, K.K.; Haritha, B.; Prabhu, K.V.; Khanna, A.; Yadav, A.; et al. Notification of Basmati Rice Variety, Pusa Basmati 1728. Indian J. Genet. Plant Breed. 2017, 77, 584. [Google Scholar]
  22. Singh, A.K.; Ellur, R.K.; Krishnan, S.; Bhowmick, P.K.; Nagarajan, M.; Vinod, K.K.; Haritha, B.; Singh, V.K.; Khanna, A.; Pathania, S.; et al. Basmati Rice Variety Pusa Basmati 1718. Indian J. Genet. Plant Breed. 2018, 78, 151. [Google Scholar]
  23. Yugander, A.; Sundaram, R.M.; Singh, K.; Ladhalakshmi, D.; Rao, L.V.S.; Madhav, M.S.; Badri, J.; Prasad, M.S.; Laha, G.S. Incorporation of the Novel Bacterial Blight Resistance Gene Xa38 into the Genetic Background of Elite Rice Variety Improved Samba Mahsuri. PLoS ONE 2018, 13, e0198260. [Google Scholar] [CrossRef] [PubMed]
  24. Agbowuro, G.; Michael, A.; Olamiriki, E.; Awoyemi, S. Rice Blast Disease (Magnaporthe oryzae): A Menace to Rice Production and Humanity. Int. J. Pathog. Res. 2020, 4, 32–39. [Google Scholar] [CrossRef]
  25. Sharma, T.; Rai, A.; Gupta, S.; Vijayan, J.; Devanna, B.N.; Ray, S. Rice Blast Management Through Host-Plant Resistance: Retrospect and Prospects. Agric. Res. 2012, 1, 37–52. [Google Scholar] [CrossRef]
  26. Zhang, M.; Wang, S.; Yuan, M. An Update on Molecular Mechanism of Disease Resistance Genes and Their Application for Genetic Improvement of Rice. Mol. Breed. 2019, 39, 154. [Google Scholar] [CrossRef]
  27. Singh, A.K.; Gopalakrishnan, S.; Singh, V.P.; Prabhu, K.V.; Mohapatra, T.; Singh, N.K.; Sharma, T.R.; Nagarajan, M.; Vinod, K.K.; Singh, D.; et al. Marker Assisted Selection: A Paradigm Shift in Basmati Breeding. Indian J. Genet. Plant Breed. 2011, 71, 120. [Google Scholar]
  28. Qu, S.; Liu, G.; Zhou, B.; Bellizzi, M.; Zeng, L.; Dai, L.; Han, B.; Wang, G.-L. The Broad-Spectrum Blast Resistance Gene Pi9 Encodes a Nucleotide-Binding Site-Leucine-Rich Repeat Protein and Is a Member of a Multigene Family in Rice. Genetics 2006, 172, 1901–1914. [Google Scholar] [CrossRef]
  29. Roychowdhury, M.; Jia, Y.; Jia, M.H.; Fjellstrom, R.; Cartwright, R.D. Identification of the Rice Blast Resistance Gene Pib in the National Small Grains Collection. Phytopathology 2012, 102, 700–706. [Google Scholar] [CrossRef]
  30. Jia, Y.; Wang, Z.; Fjellstrom, R.G.; Moldenhauer, K.A.K.; Azam, M.A.; Correll, J.; Lee, F.N.; Xia, Y.; Rutger, J.N. Rice Pi-Ta Gene Confers Resistance to the Major Pathotypes of the Rice Blast Fungus in the United States. Phytopathology® 2004, 94, 296–301. [Google Scholar] [CrossRef]
  31. Bryan, G.T.; Wu, K.-S.; Farrall, L.; Jia, Y.; Hershey, H.P.; McAdams, S.A.; Faulk, K.N.; Donaldson, G.K.; Tarchini, R.; Valent, B. TA Single Amino Acid Difference Distinguishes Resistant and Susceptible Alleles of the Rice Blast Resistance Gene Pi-Ta. Plant Cell 2000, 12, 2033–2045. [Google Scholar] [CrossRef]
  32. Jia, Y.; Bryan, G.T.; Farrall, L.; Valent, B. Natural Variation at the Pi-Ta Rice Blast Resistance Locus. Phytopathology® 2003, 93, 1452–1459. [Google Scholar] [CrossRef]
  33. Hittalmani, S.; Parco, A.; Mew, T.V.; Zeigler, R.S.; Huang, N. Fine Mapping and DNA Marker-Assisted Pyramiding of the Three Major Genes for Blast Resistance in Rice. Theor. Appl. Genet. 2000, 100, 1121–1128. [Google Scholar] [CrossRef]
  34. Khanna, A.; Sharma, V.; Ellur, R.; Shikari, A.; Krishnan, S.; Singh, U.; Ganesan, P.; Sharma, T.; Rathour, R.; Variar, M.; et al. Marker Assisted Pyramiding of Major Blast Resistance Genes Pi9 and Pita in the Genetic Background of an Elite Basmati Rice Variety, Pusa Basmati 1. Indian J. Genet. Plant Breed. 2015, 75, 417. [Google Scholar] [CrossRef]
  35. Ramalingam, J.; Raveendra, C.; Savitha, P.; Vidya, V.; Chaithra, T.L.; Velprabakaran, S.; Saraswathi, R.; Ramanathan, A.; Arumugam Pillai, M.P.; Arumugachamy, S.; et al. Gene Pyramiding for Achieving Enhanced Resistance to Bacterial Blight, Blast, and Sheath Blight Diseases in Rice. Front. Plant Sci. 2020, 11. [Google Scholar] [CrossRef]
  36. Ercoli, M.F.; Luu, D.D.; Rim, E.Y.; Shigenaga, A.; Teixeira de Araujo, A.; Chern, M.; Jain, R.; Ruan, R.; Joe, A.; Stewart, V.; et al. Plant Immunity: Rice XA21-Mediated Resistance to Bacterial Infection. Proc. Natl. Acad. Sci. USA 2022, 119, e2121568119. [Google Scholar] [CrossRef]
  37. Shanti, M.L.; Shenoy, V.V.; Devi, G.L.; Kumar, V.M.; Premalatha, P.; Kumar, G.N.; Shashidhar, H.E.; Zehr, U.B.; Freeman, W.H. Marker-Assisted Breeding for Resistance to Bacterial Leaf Blight in Popular Cultivar and Parental Lines of Hybrid Rice. J. Plant Pathol. 2010, 92, 495–501. [Google Scholar]
  38. Raina, M.; Salgotra, R.K.; Pandotra, P.; Rathour, R.; Singh, K. Genetic Enhancement for Semi-Dwarf and Bacterial Blight Resistance with Enhanced Grain Quality Characteristics in Traditional Basmati Rice through Marker-Assisted Selection. Comptes Rendus Biol. 2019, 342, 142–153. [Google Scholar] [CrossRef]
  39. Mishra, D.; Vishnupriya, M.R.; Anil, M.G.; Konda, K.; Raj, Y.; Sonti, R.V. Pathotype and Genetic Diversity amongst Indian Isolates of Xanthomonas oryzae pv. oryzae. PLoS ONE 2013, 8, e81996. [Google Scholar] [CrossRef]
  40. Babar, A.D.; Zaka, A.; Naveed, S.A.; Ahmad, N.; Aslam, K.; Asif, M.; Maqsood, U.; Vera Cruz, C.M.; Arif, M. Development of Basmati Lines by the Introgression of Three Bacterial Blight Resistant Genes through Marker-Assisted Breeding. Euphytica 2022, 218, 59. [Google Scholar] [CrossRef]
  41. Samal, P.; Pote, T.D.; Krishnan, S.G.; Singh, A.K.; Salgotra, R.K.; Rathour, R. Integrating Marker-Assisted Selection and Doubled Haploidy for Rapid Introgression of Semi-Dwarfing and Blast Resistance Genes into a Basmati Rice Variety ‘Ranbir Basmati’. Euphytica 2019, 215, 149. [Google Scholar] [CrossRef]
  42. Dixit, S.; Singh, U.M.; Singh, A.K.; Alam, S.; Venkateshwarlu, C.; Nachimuthu, V.V.; Yadav, S.; Abbai, R.; Selvaraj, R.; Devi, M.N.; et al. Marker Assisted Forward Breeding to Combine Multiple Biotic-Abiotic Stress Resistance/Tolerance in Rice. Rice 2020, 13, 29. [Google Scholar] [CrossRef]
  43. Singh, U.M.; Dixit, S.; Alam, S.; Yadav, S.; Prasanth, V.V.; Singh, A.K.; Venkateshwarlu, C.; Abbai, R.; Vipparla, A.K.; Badri, J.; et al. Marker-Assisted Forward Breeding to Develop a Drought-, Bacterial-Leaf-Blight-, and Blast-Resistant Rice Cultivar. Plant Genome 2022, 15, e20170. [Google Scholar] [CrossRef]
  44. Sagar, V.; Krishnan, S.G.; Dwivedi, P.; Mondal, K.K.; Prakash, G.; Nagarajan, M.; Singh, A.K. Development of Basmati Rice Genotypes with Resistance to Both Bacterial Blight and Blast Diseases Using Marker Assisted Restricted Backcross Breeding. Indian J. Genet. Plant Breed. 2017, 78, 36. [Google Scholar] [CrossRef]
  45. Reinke, R.; Kim, S.-M.; Kim, B.-K. Developing Japonica Rice Introgression Lines with Multiple Resistance Genes for Brown Planthopper, Bacterial Blight, Rice Blast, and Rice Stripe Virus Using Molecular Breeding. Mol. Genet Genom. 2018, 293, 1565–1575. [Google Scholar] [CrossRef]
  46. Chukwu, S.C.; Rafii, M.Y.; Ramlee, S.I.; Ismail, S.I.; Oladosu, Y.; Kolapo, K.; Musa, I.; Halidu, J.; Muhammad, I.; Ahmed, M. Marker-Assisted Introgression of Multiple Resistance Genes Confers Broad Spectrum Resistance against Bacterial Leaf Blight and Blast Diseases in PUTRA-1 Rice Variety. Agronomy 2020, 10, 42. [Google Scholar] [CrossRef]
  47. Biswas, P.L.; Nath, U.K.; Ghosal, S.; Goswami, G.; Uddin, M.S.; Ali, O.M.; Latef, A.A.H.A.; Laing, A.M.; Gao, Y.-M.; Hossain, A. Introgression of Bacterial Blight Resistance Genes in the Rice Cultivar Ciherang: Response against Xanthomonas Oryzae Pv. Oryzae in the F6 Generation. Plants 2021, 10, 2048. [Google Scholar] [CrossRef] [PubMed]
  48. Miah, G.; Rafii, M.Y.; Ismail, M.R.; Puteh, A.B.; Rahim, H.A.; Islam, K.N.; Latif, M.A. A Review of Microsatellite Markers and Their Applications in Rice Breeding Programs to Improve Blast Disease Resistance. Int. J. Mol. Sci. 2013, 14, 22499–22528. [Google Scholar] [CrossRef]
  49. Khan, G.H.; Shikari, A.B.; Vaishnavi, R.; Najeeb, S.; Padder, B.A.; Bhat, Z.A.; Parray, G.A.; Bhat, M.A.; Kumar, R.; Singh, N.K. Marker-Assisted Introgression of Three Dominant Blast Resistance Genes into an Aromatic Rice Cultivar Mushk Budji. Sci. Rep. 2018, 8, 4091. [Google Scholar] [CrossRef] [PubMed]
  50. Esan, V.I.; Oke, G.O.; Ogunbode, T.O.; Obisesan, I.A. AMMI and GGE Biplot Analyses of Bambara Groundnut [Vigna Subterranea (L.) Verdc.] for Agronomic Performances under Three Environmental Conditions. Front. Plant Sci. 2023, 13. [Google Scholar] [CrossRef]
  51. Okello-Anyanga, W.; Rubaihayo, P.; Gibson, P.; Okori, P. Genotype by Environment Interaction in Sesame (Sesamum Indicum L.) Cultivars in Uganda. Afr. J. Plant Sci. 2016, 10, 189–202. [Google Scholar] [CrossRef]
  52. Pour-Aboughadareh, A.; Ghazvini, H.; Jasemi, S.; Mohammadi, S.; Razavi, S.; Chaichi, M.; Kalkhoran, M.; Monirifar, H.; Tajali, H.; Fathihafshejani, A.; et al. Selection of High-Yielding and Stable Genotypes of Barley for the Cold Climate in Iran. Plants 2023, 12, 2410. [Google Scholar] [CrossRef]
  53. Jamaloddin, M.; Durga Rani, C.V.; Swathi, G.; Anuradha, C.; Vanisri, S.; Rajan, C.P.D.; Krishnam Raju, S.; Bhuvaneshwari, V.; Jagadeeswar, R.; Laha, G.S.; et al. Marker Assisted Gene Pyramiding (MAGP) for Bacterial Blight and Blast Resistance into Mega Rice Variety “Tellahamsa”. PLoS ONE 2020, 15, e0234088. [Google Scholar] [CrossRef]
  54. Murray, M.G.; Thompson, W.F. Rapid Isolation of High Molecular Weight Plant DNA. Nucleic Acids Res. 1980, 8, 4321–4325. [Google Scholar] [CrossRef]
  55. Daware, A.; Malik, A.; Srivastava, R.; Das, D.; Ellur, R.K.; Singh, A.K.; Tyagi, A.K.; Parida, S.K. Rice Pan-Genome Array (RPGA): An Efficient Genotyping Solution for Pan-Genome-Based Accelerated Crop Improvement in Rice. Plant J. 2022, 113, 26–46. [Google Scholar] [CrossRef]
  56. Kauffman, H.E.; Reddy, A.P.K.; Hsieh, S.P.Y.; Merca, S.D. Improved Technique for Evaluating Resistance of Rice Varieties to Xanthomonas Oryzae. Plant Dis. Rep. 1973, 57, 537–541. [Google Scholar]
  57. Mondal, K.K.; Meena, B.R.; Junaid, A.; Verma, G.; Mani, C.; Majumder, D.; Khicher, M.; Kumar, S.; Banik, S. Pathotyping and Genetic Screening of Type III Effectors in Indian Strains of Xanthomonas Oryzae Pv. Oryzae Causing Bacterial Leaf Blight of Rice. Physiol. Mol. Plant Pathol. 2014, 86, 98–106. [Google Scholar] [CrossRef]
  58. Bonman, J.M. Physiologic Specialization of Pyricularia Oryzae in the Philippines. Plant Dis. 1986, 70, 767. [Google Scholar] [CrossRef]
  59. Star, I. CropStat. In Biometrics and Breeding Informatics; PBGB Division, International Rice Research Institute: Los Baños, CA, USA, 2014. [Google Scholar]
  60. Olivoto, T.; Lúcio, A.D. Metan: An R Package for Multi-Environment Trial Analysis. Methods Ecol. Evol. 2020, 11, 783–789. [Google Scholar] [CrossRef]
Ijms 24 16081 g001
Figure 1. Representation of the recurrent parent similarity for Pusa 3054-2-47-7-166-24-261-3 (G17). 1–12 represents the chromosome numbers.
Figure 1. Representation of the recurrent parent similarity for Pusa 3054-2-47-7-166-24-261-3 (G17). 1–12 represents the chromosome numbers.
Ijms 24 16081 g001
Ijms 24 16081 g002
Figure 2. Grain and cooking quality of the parental lines and the NILs carrying Pita where G6 = Pusa 3066-4-56-20-158-7-170-2, G7 = Pusa 3066-4-56-20-158-7-171-4 and G9 = Pusa 3066-4-56-20-158-7-172-2.
Figure 2. Grain and cooking quality of the parental lines and the NILs carrying Pita where G6 = Pusa 3066-4-56-20-158-7-170-2, G7 = Pusa 3066-4-56-20-158-7-171-4 and G9 = Pusa 3066-4-56-20-158-7-172-2.
Ijms 24 16081 g002
Ijms 24 16081 g003
Figure 3. Genotype main effect (G) plus genotype by environment interaction (GE) biplot for the yield data of NILs evaluated during kharif 2021 at three different locations. G1 to G5 PB1509 + Pi9 + Pib, G6 to G10-PB1509 + Pita, G11 to G14 -PB1509 + xa13 + Xa21 and G15 to G19-PB1509 + Xa38.
Figure 3. Genotype main effect (G) plus genotype by environment interaction (GE) biplot for the yield data of NILs evaluated during kharif 2021 at three different locations. G1 to G5 PB1509 + Pi9 + Pib, G6 to G10-PB1509 + Pita, G11 to G14 -PB1509 + xa13 + Xa21 and G15 to G19-PB1509 + Xa38.
Ijms 24 16081 g003
Ijms 24 16081 g004
Figure 4. Grain and cooking quality of the parental lines and the NILs carrying Xa38, Pi9 and Pib where G24 = Pusa 3124-38-19-176-5 and G26 = Pusa 3124-40-22-180-2.
Figure 4. Grain and cooking quality of the parental lines and the NILs carrying Xa38, Pi9 and Pib where G24 = Pusa 3124-38-19-176-5 and G26 = Pusa 3124-40-22-180-2.
Ijms 24 16081 g004
Ijms 24 16081 g005
Figure 5. BB disease reaction under artificial inoculation conditions: (A) RP- PB1509, DP-PB1718, G13-Pusa 3037-1-44-3-164-21-256-4, G14-Pusa 3037-1-45-5-165-22-259-4 and G11-Pusa 3037-1-44-3-164-20-249-2. (B) RP-PB1509, DP-P1927, G26-Pusa 3124-40-22-180-2, G22-Pusa 3124-37-17-168-4, G24-Pusa 3124-38-19-176-5 and G25-Pusa 3124-40-21-179-4.
Figure 5. BB disease reaction under artificial inoculation conditions: (A) RP- PB1509, DP-PB1718, G13-Pusa 3037-1-44-3-164-21-256-4, G14-Pusa 3037-1-45-5-165-22-259-4 and G11-Pusa 3037-1-44-3-164-20-249-2. (B) RP-PB1509, DP-P1927, G26-Pusa 3124-40-22-180-2, G22-Pusa 3124-37-17-168-4, G24-Pusa 3124-38-19-176-5 and G25-Pusa 3124-40-21-179-4.
Ijms 24 16081 g005
Ijms 24 16081 g006
Figure 6. The bacterial blight lesion length in NILs and parental lines. The values represented are the mean of replicated data over two seasons and the standard error is shown as error bars.
Figure 6. The bacterial blight lesion length in NILs and parental lines. The values represented are the mean of replicated data over two seasons and the standard error is shown as error bars.
Ijms 24 16081 g006
Ijms 24 16081 g007
Figure 7. MABB scheme for development of NILs.
Figure 7. MABB scheme for development of NILs.
Ijms 24 16081 g007
Table 1. Recovery of recurrent parent genome (RPG) during different stages of backcross breeding using polymorphic SSR markers. Pusa 3037-PB1509 + xa13 + Xa21; Pusa 3054-PB1509 + Xa38; Pusa 3060-PB1509 + Pi9 + Pib; Pusa 3066-PB1509 + Pita.
Table 1. Recovery of recurrent parent genome (RPG) during different stages of backcross breeding using polymorphic SSR markers. Pusa 3037-PB1509 + xa13 + Xa21; Pusa 3054-PB1509 + Xa38; Pusa 3060-PB1509 + Pi9 + Pib; Pusa 3066-PB1509 + Pita.
GenotypeRPG Recovery (%)
BC1F1BC2F1BC3F1
Pusa 3037 64.8–84.283.3–93.386.1–99.6
Pusa 3054 73.8–88.691.7–94.491.3–99.4
Pusa 306070.7–81.081.8–86.491.7–98.3
Pusa 306657.3–87.586.5–91.992.4–97.8
Table 2. Agronomic performance of the PB1509-NILs carrying different resistance genes for blast and bacterial blight at IARI, New Delhi along with recurrent parent similarity.
Table 2. Agronomic performance of the PB1509-NILs carrying different resistance genes for blast and bacterial blight at IARI, New Delhi along with recurrent parent similarity.
NILGenotypeGenesDFPH (cm)NT (cm)PL
(cm)		FG SF (%)TW (g)Similarity
(%)
G1Pusa 3060-3-55-17-157-4-124-1Pi9 + Pib83.6102.4 *13.328.264.0 *75.8 *30.296.83
G2Pusa 3060-3-55-17-157-4-124-6Pi9 + Pib84.6104.4 *13.328.462.3 *79.333.096.13
G3Pusa 3060-3-55-17-157-4-138-1Pi9 + Pib83.3 *101.112.429.450.9 *61.9 *32.396.65
G4Pusa 3060-3-55-17-157-4-138-2Pi9 + Pib83.0 *102.6 *1328.964.2 *70.3 *33.3 *96.60
G5Pusa 3060-3-55-17-157-4-138-3Pi9 + Pib83.698.213.12960.5*72.8*32.397.38
G6Pusa 3066-4-56-20-158-7-170-2Pita85.697.813.229.471.878.931.897.69
G7Pusa 3066-4-56-20-158-7-171-4Pita86.3102.4 *12.730.3 *77.683.232.696.87
G8Pusa 3066-4-56-20-158-7-172-1Pita85.0101.613.128.775.380.129.897.35
G9Pusa 3066-4-56-20-158-7-172-2Pita84.6103.4 *12.429.178.282.631.497.23
G10Pusa 3066-4-56-20-159-8-174-1Pita81.0 *98.911.628.0 *66.9 *74.7 *30.686.38
G11Pusa 3037-1-44-3-164-20-249-2xa13 + Xa2185.6100.811.728.181.288.131.697.79
G12Pusa 3037-1-44-3-164-21-255-1xa13 + Xa2184.397.513.527.980.989.331.398.25
G13Pusa 3037-1-44-3-164-21-256-4xa13 + Xa2185.097.11328.370.6 *81.930.5-
G14Pusa 3037-1-45-5-165-22-259-4xa13 + Xa2184.698.213.027.4 *71.886.832.5-
G15Pusa 3054-2-47-7-166-24-261-1Xa3884.3102.6 *13.02974.885.431.798.77
G16Pusa 3054-2-47-7-166-24-261-2Xa3884.0101.312.828.679.288.733.4 *98.92
G17Pusa 3054-2-47-7-166-24-261-3Xa3883.0100.712.328.283.084.331.298.90
G18Pusa 3054-2-47-7-166-24-262-2Xa3884.3102.7 *11.629.175.486.531.3-
G19Pusa 3054-2-47-7-166-24-262-3Xa3884.3103 *12.028.975.383.331.998.11
PB1509- 85.098.812.829.178.883.231.3-
LSD (0.05)- 1.493.182.100.997.746.821.86-
Where DF = days to fifty percent flowering, PH = plant height, NT = number of tillers, PL = panicle length, FG = filled grains, SF = spikelet fertility and TW = test weight. * Significantly different from PB1509 at 5% level of significance.
Table 3. Grain and cooking quality of the PB1509-NILs.
Table 3. Grain and cooking quality of the PB1509-NILs.
NILGenotypeHRMRHRRKLBCKBBCKLACKBACERAroma
G1Pusa 3060-3-55-17-157-4-124-17869.351.08.141.6617.952.262.202
G2Pusa 3060-3-55-17-157-4-124-678.370.351.38.381.6617.532.332.092
G3Pusa 3060-3-55-17-157-4-138-178.57048.38.361.6617.972.332.142
G4Pusa 3060-3-55-17-157-4-138-279.670.650.08.381.6616.642.331.982
G5Pusa 3060-3-55-17-157-4-138-380.371.351.38.341.6617.172.242.052
G6Pusa 3066-4-56-20-158-7-170-280.371.654.08.231.6616.952.332.052
G7Pusa 3066-4-56-20-158-7-171-480.372.0 *55.68.311.6616.802.312.022
G8Pusa 3066-4-56-20-158-7-172-180.6 *71.650.68.251.6616.572.332.002
G9Pusa 3066-4-56-20-158-7-172-279.370.649.38.171.6617.042.312.082
G10Pusa 3066-4-56-20-159-8-174-180.070.343.68.031.6616.37 *2.282.032
G11Pusa 3037-1-44-3-164-20-249-279.371.355.38.381.6617.482.332.082
G12Pusa 3037-1-44-3-164-21-255-179.672.0 *54.08.281.6618.062.312.172
G13Pusa 3037-1-44-3-164-21-256-480.372.3 *53.68.301.6617.312.312.082
G14Pusa 3037-1-45-5-165-22-259-480.372.0 *52.08.42 *1.6618.042.332.142
G15Pusa 3054-2-47-7-166-24-261-180.072.0 *54.68.42 *1.6616.912.332.002
G16Pusa 3054-2-47-7-166-24-261-277.670.054.08.281.6617.712.312.132
G17Pusa 3054-2-47-7-166-24-261-379.371.652.68.251.6617.752.282.152
G18Pusa 3054-2-47-7-166-24-262-278.370.352.68.371.6618.57 *2.312.212
G19Pusa 3054-2-47-7-166-24-262-379.672.3 *54.38.46 *1.6617.682.282.092
PB1509-78.669.851.18.211.6617.562.312.142
LSD (0.05)-1.991.865.670.180.000.650.670.93-
Where HR = hulling recovery, MR = milling recovery, HRR = head rice recovery, KLBC = kernel length before cooking (mm), KBBC = kernel breadth before cooking (mm), KLAC = kernel length after cooking (mm), KBAC = kernel breadth after cooking (mm) and ER = elongation ratio. * Significantly different from PB1509 at 5% level of significance.
Table 4. Yield performance of PB1509 NILs at three different locations namely, New Delhi (Env1), Karnal (Env2) and Urlana (Env3). * Represents the NILs with a significant difference in yield compared to RP PB1509.
Table 4. Yield performance of PB1509 NILs at three different locations namely, New Delhi (Env1), Karnal (Env2) and Urlana (Env3). * Represents the NILs with a significant difference in yield compared to RP PB1509.
NILsGenotypeGrain Yield (Kg/ha)
New DelhiKarnalUrlana
G1Pusa 3060-3-55-17-157-4-124-1500851859461
G2Pusa 3060-3-55-17-157-4-124-6529553298245
G3Pusa 3060-3-55-17-157-4-138-14322 *45147410 *
G4Pusa 3060-3-55-17-157-4-138-248413423 *8143 *
G5Pusa 3060-3-55-17-157-4-138-3491446488238 *
G6Pusa 3066-4-56-20-158-7-170-2522145228126 *
G7Pusa 3066-4-56-20-158-7-171-45559 *45548514
G8Pusa 3066-4-56-20-158-7-172-1552444908728
G9Pusa 3066-4-56-20-158-7-172-25544 *45658580
G10Pusa 3066-4-56-20-159-8-174-1545144548893
G11Pusa 3037-1-44-3-164-20-249-25712 *50999709
G12Pusa 3037-1-44-3-164-21-255-16267 *48719744
G13Pusa 3037-1-44-3-164-21-256-45749 *48049021
G14Pusa 3037-1-45-5-165-22-259-4551344699171
G15Pusa 3054-2-47-7-166-24-261-15606 *47678585
G16Pusa 3054-2-47-7-166-24-261-25712 *48189763
G17Pusa 3054-2-47-7-166-24-261-3546851269415
G18Pusa 3054-2-47-7-166-24-262-25781 *48309131
G19Pusa 3054-2-47-7-166-24-262-3537244458072 *
PB1509 499551549239
LSD (0.05) 545863959
Table 5. Agronomic performance of the PB1509 NILs carrying different combinations for blast and bacterial blight resistance genes.
Table 5. Agronomic performance of the PB1509 NILs carrying different combinations for blast and bacterial blight resistance genes.
NILGenotypeGenesDFPHNTPL (cm)TGSF (%)Yield (Kg/ha)
G20Pusa 3122-27-15-165-2xa13 + Xa21 + Xa3884.5103.512.528.081.574.1 *8272
G21Pusa 3122-27-16-166-1xa13 + Xa21 + Xa3885.5106.514.527.075.075.9 *7573
G22Pusa 3124-37-17-168-4Xa38 + Pi9 + Pib84.5110.513.528.091.088.67865
G23Pusa 3124-37-18-175-1Xa38 + Pi9 + Pib85.0104.015.525.089.088.37914
G24Pusa 3124-38-19-176-5Xa38 + Pi9 + Pib86.5109.520.5 *31.592.593.98406
G25Pusa 3124-40-21-179-4Xa38 + Pi9 + Pib88.5 *114.513.530.097.594.88260
G26Pusa 3124-40-22-180-2Xa38 + Pi9 + Pib85.5113.014.026.5101.089.08640
G27Pusa 3123-33-13-312-13Pi9 + Pib + Pita84.0113.014.029.591.084.78391
G28Pusa 3123-33-13-312-22Pi9 + Pib + Pita84.0116.015.528.578.578.8 *7862
G29Pusa 3123-33-13-312-25Pi9 + Pib + Pita82.5 *110.012.527.089.093.88598
PB1509 -85.5105.514.528.089.590.98568
LSD (0.05) 1.6410.505.104.1918.958.461039.62
Where DF = days to fifty percent flowering, PH = plant height, NT = number of tillers, PL = panicle length, TG = total grains, SF = spikelet fertility and TW = test weight. * Significantly different from PB1509 at 5% level of significance.
Table 6. Grain and cooking quality of the intercrossed NILs.
Table 6. Grain and cooking quality of the intercrossed NILs.
NILGenotypeKLBCKBBCKLACKBACERAroma
G20Pusa 3122-27-15-165-28.481.6617.242.272.032+
G21Pusa 3122-27-16-166-18.081.6617.762.332.192+
G22Pusa 3124-37-17-168-48.381.6617.892.272.132+
G23Pusa 3124-37-18-175-18.631.6617.892.332.072+
G24Pusa 3124-38-19-176-58.301.6617.272.332.082+
G25Pusa 3124-40-21-179-48.661.6617.292.331.992+
G26Pusa 3124-40-22-180-28.881.6617.512.331.972+
G27Pusa 3123-33-13-312-138.611.6617.512.332.032+
G28Pusa 3123-33-13-312-228.481.6617.572.272.072+
G29Pusa 3123-33-13-312-258.411.6617.872.332.122+
PB1509-8.451.6617.662.292.092+
LSD (0.05) 0.690.000.420.640.21-
Where KLBC = kernel length before cooking (mm), KBBC = kernel breadth before cooking (mm), KLAC = kernel length after cooking (mm), KBAC = kernel breadth after cooking (mm) and ER = elongation ratio.
Table 7. Blast reaction scores for the developed NILs with isolate Mo-ei-MB20 at New Delhi and mixture of five isolates at Palampur.
Table 7. Blast reaction scores for the developed NILs with isolate Mo-ei-MB20 at New Delhi and mixture of five isolates at Palampur.
NILGenotypeGenesNew Delhi Palampur
G1Pusa 3060-3-55-17-157-4-124-1Pi9 + Pib11
G2Pusa 3060-3-55-17-157-4-124-6Pi9 + Pib11
G3Pusa 3060-3-55-17-157-4-138-1Pi9 + Pib11
G4Pusa 3060-3-55-17-157-4-138-2Pi9 + Pib21
G5Pusa 3060-3-55-17-157-4-138-3Pi9 + Pib11
G6Pusa 3066-4-56-20-158-7-170-2Pita21
G7Pusa 3066-4-56-20-158-7-171-4Pita11
G8Pusa 3066-4-56-20-158-7-172-1Pita21
G9Pusa 3066-4-56-20-158-7-172-2Pita11
G10Pusa 3066-4-56-20-159-8-174-1Pita21
G22Pusa 3124-37-17-168-4Xa38 + Pi9 + Pib22
G23Pusa 3124-37-18-175-1Xa38 + Pi9 + Pib22
G24Pusa 3124-38-19-176-5Xa38 + Pi9 + Pib11
G25Pusa 3124-40-21-179-4Xa38 + Pi9 + Pib22
G26Pusa 3124-40-22-180-2Xa38 + Pi9 + Pib11
G27Pusa 3123-33-13-312-13Pi9 + Pib + Pita01
G28Pusa 3123-33-13-312-22Pi9 + Pib + Pita01
G29Pusa 3123-33-13-312-25Pi9 + Pib + Pita01
PB 1509--54
P1929-Pi9 + Pib11
Tetep-Pita21
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Singh, G.; Singh, N.; Ellur, R.K.; Balamurugan, A.; Prakash, G.; Rathour, R.; Mondal, K.K.; Bhowmick, P.K.; Gopala Krishnan, S.; Nagarajan, M.; et al. Genetic Enhancement for Biotic Stress Resistance in Basmati Rice through Marker-Assisted Backcross Breeding. Int. J. Mol. Sci. 2023, 24, 16081. https://doi.org/10.3390/ijms242216081

AMA Style

Singh G, Singh N, Ellur RK, Balamurugan A, Prakash G, Rathour R, Mondal KK, Bhowmick PK, Gopala Krishnan S, Nagarajan M, et al. Genetic Enhancement for Biotic Stress Resistance in Basmati Rice through Marker-Assisted Backcross Breeding. International Journal of Molecular Sciences. 2023; 24(22):16081. https://doi.org/10.3390/ijms242216081

Chicago/Turabian Style

Singh, Gagandeep, Niraj Singh, Ranjith Kumar Ellur, Alexander Balamurugan, G. Prakash, Rajeev Rathour, Kalyan Kumar Mondal, Prolay Kumar Bhowmick, S. Gopala Krishnan, Mariappan Nagarajan, and et al. 2023. "Genetic Enhancement for Biotic Stress Resistance in Basmati Rice through Marker-Assisted Backcross Breeding" International Journal of Molecular Sciences 24, no. 22: 16081. https://doi.org/10.3390/ijms242216081

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop