Haplotyping of Rice Genotypes Using Simple Sequence Repeat Markers Associated with Salt Tolerance

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ScienceDirect

Rice Science, 2016, 23(6): 317–325

Haplotyping of Rice Genotypes Using Simple Sequence Repeat

Markers Associated with Salt Tolerance

A. D. C

HOWDHURY1, #

, G. H

ARITHA1, #

, T. S

UNITHA1

, S. L. K

RISHNAMURTHY2

, B. D

IVYA1

,

G. P

ADMAVATHI1

, T. R

AM1

, N. S

ARLA1

(1ICAR-Indian Institute of Rice Research, Hyderabad 500030, India; 2Division of Crop Improvement, Central Soil Salinity Research Institute, Karnal 132001, India; #These authors contribute equally to this study)

Abstract: Salt stress is a major problem in most of the rice growing areas in the world. A major QTL Saltol associated with salt tolerance at the seedling stage has been mapped on chromosome 1 in rice.

This study aimed to characterize the haplotype diversity at Saltol and additional QTLs associated with salt tolerance. Salt tolerance at the seedling stage was assessed in 54 rice genotypes in the scale of 1 to 9 score at EC = 10 dSm-1 under controlled environmental conditions. Seven new breeding lines including three KMR3/O. rufipogon introgression lines showed similar salt tolerant ability as FL478 and can be good sources of new genes/alleles for salt tolerance. Simple sequence repeat (SSR) marker RM289 showed only two alleles and RM8094 showed seven alleles. Polymorphic information content value varied from 0.55 for RM289 to 0.99 for RM8094 and RM493. Based on 14 SSR markers, the 54 lines were clearly separated into two major clusters. Fourteen haplotypes were identified based on

Saltol linked markers with FL478 as the reference. Alleles of RM8094 and RM3412 can discriminate

between the salt tolerant and susceptible genotypes clearly and hence can be useful in marker-assisted selection at the seedling stage. Other markers RM10720 on chromosome 1 and RM149 and RM264 on chromosome 8 can also distinguish tolerant and susceptible lines but with lesser stringency.

Key words: haplotype; rice; salt tolerance; Saltol; simple sequence repeat marker

Soil salinity is one of the major factors limiting rice productivity around the world. Majority of the rice growing region in Asia is confined to south and southeast regions, where 20% of the area covering about 4.7 × 107 hm2 is affected by salt stress. These problem areas consist of warm humid coastal regions and marshy inlands (Das et al, 2015; Kumar et al, 2015). Salt stress is also an alarming problem in inland areas because of the build-up of salinity as a consequence of excessive use of irrigation water with improper drainage or coupled with the use of poor quality irrigation water or both (Ismail et al, 2010).

Rice is central to the lives of billions of people around the world. According to International Rice Research Institute, 50% more rice needs to be grown

with less water, land, fertilizer and pesticide to keep up with the average annual population growth rate of 1.9%. In India, 9.04 million hectares of rice growing area is affected by salinity (Ganeshan et al, 2016). Rice is considered sensitive to salinity, particularly during the early-vegetative and late-reproductive stages, and is also one of the few crops that can thrive on salt-affected soils. Its ability to grow well in standing water can help leach salts from topsoil, and therefore, rice is recommended as an entry crop for desalinization of salt affected lands (Ismail et al, 2007; Singh and Flowers, 2010). However, breeding for salt tolerant rice varieties has been a difficult task, owing to complex inheritance of salt tolerance, strong genotype and environmental interaction and problems

Received: 26 March 2016; Accepted: 24 May 2016

Corresponding author: N. SARLA ([email protected])

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) Peer review under responsibility of China National Rice Research Institute

http://dx.doi.org/

http://dx.doi.org/10.1016/j.rsci.2016.05.003

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in phenotyping different stages of growth under varying salinity levels accurately (Kumar et al, 2015).

Advancement in rice breeding for salt tolerance has accelerated since the identification of major loci conferring salt tolerance especially at the seedling stage. Microsatellite markers have been used to map QTLs associated with salt tolerance (Lang et al, 2000, 2001; Singh et al, 2007; Mohammadi-Nejad et al, 2008; Hossain et al, 2015). A major QTL for salt tolerance at the seedling stage, Saltol, was identified using F8 recombinant inbred lines (RILs) of Pokkali/

IR29 (Gregorio et al, 1997). This QTL governs the Na+/K+ uptake and accounts for 64.3% to 80.2% of the phenotypic variation in salt tolerance at the seedling stage (Mohammadi-Nejad et al, 2008). This segment was further saturated using restriction fragment length polymorphism and simple sequence repeat (SSR) markers using RILs (Bonilla et al, 2002). A newly developed RIL FL478 with Saltol derived from IR29 and Pokkali was used as a novel source of salt tolerance at the seedling stage (Walia et al, 2005). Recently, genome-wide single nucleotide polymorphism (SNPs) associated with salt tolerance have also been identified (Mishra et al, 2016; Rahman et al, 2016; Tiwari et al, 2016).

RIL FL478 has been widely used to introgress

Saltol into elite varieties such as BR11, BRRI Dhan 28, IR64, AS996 and Pusa Basmati 1121 (Huyen et al, 2012) and seven popular local varieties ADT45, CR1009, Gayatri, MTU1010, PR114, Pusa 44 and Sarjoo 52 in India (Singh et al, 2016) through marker assisted backcross breeding. Eight QTLs are responsible for the variation in the K+ and Na+ content, among which

SKC1 is distinguished as a major QTL for the K+ and Na+ content in shoot and is mapped on chromosome 1, using F2 populations derived from Nipponbare and

Koshihikari (Ren et al, 2005; Thomson et al, 2010; Emon et al, 2015; Rahman et al, 2016).

Babu et al (2014) conducted marker based haplotype diversity of Saltol in 23 rice genotypes and obtained 14 different haplotypes. Krishnamurthy et al (2015) evaluated a set of 94 rice accessions including advanced breeding lines, landraces, released varieties and wild species with FL478 as a reference using SSRs in Saltol region with phenotypic score for salt tolerance at the seedling stage and suggested the presence of novel QTLs for salt tolerance in some of the accessions. These accessions were salt tolerant but did not have FL478 alleles in Saltol region. In this study, a different set of genotypes including introgression lines derived from elite × wild crosses

and advanced breeding lines were phenotyped and genotyped using SSR markers linked to Saltol. In addition, markers for other QTLs linked to salt tolerance on chromosomes 5, 8 and 10 were also used. The objectives of this study were to identify novel SSR alleles at the known loci for salt tolerance in diverse rice germplasm including introgression lines from elite × wild crosses and select most discriminating SSR markers for salt tolerance.

MATERIALS AND METHODS

Plant materials and phenotyping for salt tolerance at seedling stage

A set of 54 elite breeding lines or varieties with salt tolerance were obtained from ICAR-Indian Institute of Rice Research (IIRR), India and International Rice Research Institute (IRRI), the Philippines. The rice accessions were grown in salinized hydroponics conditions (EC = 10 dSm-1) using Yoshida nutrient solution (Yoshida et al, 1976) and screened for salinity tolerance at the seedling stage using the IRRI standard protocol (Gregorio et al, 1997). The experiment was conducted in hydroponics at the seedling stage in a controlled glasshouse at Central Soil Salinity Research Institute (CSSRI), Karnal (29°43′ N, 76°58′ E), India. The nutrient solution was salinized by adding NaCl and induced at the seedling stage (14 d after sowing), and salinity was maintained for the next 14 d. Modified standard evaluation system was used in rating the visual symptoms of salt toxicity (IRRI, 1997). Each genotype was scored for vigour after two weeks of salinization. The nutrient solution was renewed weekly and the desired pH and EC were maintained regularly.

Evaluation of salt tolerance score

The visual symptoms of salt injury were observed on individual seedlings and the salt tolerance scores of 1, 3, 5, 7 and 9 were assigned (Table 1) based on the

Table 1. Scoring criteria for salt tolerance (Gregorio et al, 1997).

Score Observation Tolerance

1 Normal growth, no leaf symptoms Highly tolerant 3 Nearly normal growth, only the tips of few

leaves whitish and rolled

Tolerant

5 Growth severely retarded, most leaves rolled, the two youngest leaves were still elongating

Moderately tolerant 7 Complete cessation of growth, all lower

leaves dried out, the two youngest leaves started to wilt

Susceptible

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standard evaluation system (Gregorio et al, 1997).

DNA extraction and SSR genotyping

Genomic DNA was extracted from 25-day-old seedlings using the CTAB mini preparation method (Dellaporta et al, 1983). Its quantity was estimated spectrophotometrically using NanoDrop (ND 1000, Thermo Scientific, Madison, USA). DNA was diluted to uniform concentration of about 50 ng/μL. SSR primers, RM493, RM3412, RM7075, RM8094, RM10694, RM10720, RM10793, RM10843 and RM10852 on chromosome 1, RM413 and RM289 on chromosome 5, RM264 and RM149 on chromosome 8, and RM222 on chromosome 10, were obtained from Integrated DNA Technology (IDT, USA) and used. Each reaction mix of 15 μL contained 3 μL genomic DNA (50 ng/μL), 0.5 μL each of forward and reverse primers (20 mmol/L), 1.5 μL of 10× buffer (0.1 mol/L Tris, pH 8.3, 0.5 mol/L KCl, 7.5 mmol/L MgCl2 and

0.1% gelatin), 1.0 μL of dNTPs from 2.5 mmol/L stock, 1 U of Taq polymerase (0.3 μL), and 8.2 μL sterile distilled water. All the PCR reagents were purchased from Merck Genei, India. PCR conditions were initial denaturation at 94 °C for 5 min, followed by 35 cycles of denaturation at 94 °C for 1 min, annealing at 55 °C for 1 min, extension at 72 °C for 2 min, followed by a final extension at 72 °C for 7 min. The amplification products were mixed with loading buffer (40% sucrose and 0.25% bromophenol blue) and resolved on 4.5% agarose gel in 0.5× TBE buffer under room temperature at a constant voltage of 150 V, and detected by ethidium bromide staining. The resolved bands were documented using a gel documentation system Alpha imager HP (Alpha Innotech, Fisher Scientifics, USA).

Data analysis

The banding patterns were scored in a binary matrix based on the presence (1) or the absence (0) of a particular band across the 54 rice genotypes keeping FL478 as tolerant and IR28 as susceptible genotypes, respectively. SSR allelic composition for each genotype at each marker locus was determined by counting the number of alleles per locus. Polymorphism information content (PIC) value was used to indicate the ability of a primer combination to distinguish between genotypes (Liu and Muse, 2005). Haplotype diversity was studied according to Liu and Anderson (2003), McCartney et al (2004), Eliades and Eliades (2009) and Babu et al (2014). Genetic relatedness among the genotypes was

calculated using the unweighted pair group method with arithmetic averages algorithm (UPGMA) cluster analysis by using the program Graphical Genotypes (GGT2.0) software (van Berloo, 2008).

RESULTS

Salt tolerance at the seedling stage

The phenotypic response of rice genotypes to salt stress at the seedling stage showed a range of variation (Table 2). The 54 genotypes were classified into four groups from tolerant (score 3) to highly susceptible (score 9), and 12 genotypes were tolerant, 24 moderately tolerant, 11 susceptible and 7 highly susceptible. The salt tolerant varieties FL478, CSR27, CSR36, Pokkali and Nonabokra cultivated in saline-prone regions were used as checks for salt tolerance with a score of 3. Interestingly, three introgression lines IET21943, IET21944 and IET21940 developed at IIRR, India and four lines from IRRI, the Phillipines also showed a score of 3.

Molecular diversity and haplotype analysis of Saltol

SSR markers were found to be highly polymorphic among the 54 rice genotypes. SSR markers based on allele diversity ranged from 2 at RM289 to 7 at RM8094. Four markers had five alleles each, one marker RM149 had four alleles and seven markers had three alleles each (Table 3). PIC values varied from 0.55 (RM289) to 0.99 (RM8094). Fig. 1 shows the amplification pattern of RM8094 in all the 54 genotypes. The dendrogram generated using UPGMA grouped all genotypes into two major clusters (Fig. 2). Cluster I comprised 14 Indian and IRRI lines improved for salt tolerance, including Pokkali and Nonabokra. Cluster II comprised of 8 highly susceptible genotypes grouped as one sub-cluster, 14 moderately susceptible genotypes, 9 moderately tolerant genotypes and 6 susceptible genotypes which were clearly delineated from each other within cluster II. Two susceptible genotypes IET22627 and IET22624 separated from other susceptible lines and grouped separately but within the second cluster. All the five introgression lines derived from O. nivara were found to be susceptible to salinity but two introgression lines IET21943 and IET21940 out of seven from KMR3 ×

O. rufipogon were as tolerant as FL478.

Markers within the Saltol QTL region, RM8094, RM10720, RM3412, RM493, RM10694 (5′-end of

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14 haplotypes were identified (Fig. 3). The remaining markers with high PIC values (RM10843, RM10852, RM7075, RM413 and RM222) which are not linked to the Saltol QTL or are on different chromosomes were used and 18 haplotypes were identified among 54

genotypes. None of the 54 genotypes showed all the marker alleles of FL478. Pokkali and FL478 had the same alleles at RM8094, RM10720, RM3412, RM493 and RM10793. It may be noted that FL478 is an RIL from the cross Pokkali × IR29. Likewise, another salt tolerant line CSR27 had the same alleles with FL478 at RM10694, RM8094, RM10720, RM3412 and RM493.

Genotypes such as Pokkali, Nonabokra, CSR27, CSR36 and IET21943 were tolerant to salinity at the seedling stage and also showed the FL478 allele for the most informative locus RM8094 (Tables 2 and 3). Therefore, this marker appears to have a strong and positive association with seedling salt tolerance in rice. Genotypes, which had the same FL478 at marker RM3412, showed different reaction to salinity stress. It was present not only in salt tolerant lines such as Pokkali and Nonabokra but also in a susceptible line IRT11133. Similarly, at RM10720 and RM10793, the FL478 alleles were found in both salt tolerant and salt susceptible lines. Two genotypes IR45427-2B-2-2B-1-1 Table 2. Salinity stress reaction (EC = 10 dSm-1_{) of 54 rice genotypes at the seedling stage.}

Genotype Designation Source Score Reaction to

salinity Genotype Designation Source Score

Reaction to salinity IRSSTN25 (CK) FL478 (IR66946-3R-178-1-1) IRRI 3 T KMR3 KMR3 India 9 HS

IRSSTN24 (CK) IR28 IRRI 7 S IET19543 DRRH3 India 5 MT

IET22631 RP Bio 4919-13-5 (KMR3 × O. rufipogon)

India 5 MT IET23124 RP Bio 4918-7-1 (Swarna × O. nivara)

India 9 HS

IET22625 RP Bio 4918-250 (Swarna × O. nivara)

India 7 S IET21542 RP Bio 4918-248 (Swarna × O. nivara)

India 9 HS

India 3 T IET21944 RP Bio 4919-13-7 (KMR3 × O. rufipogon)

India 3 T

India 5 MT IET21940 RP Bio 4919-463 (KMR3 × O. rufipogon)

India 3 T

India 9 HS IET22628 RP Bio 4919-50-12 (KMR3 × O. rufipogon)

India 5 MT

India 7 S IET22633 RP Bio 4919-495 (KMR3 × O. rufipogon)

India 7 S

India 7 S IET22626 RP Bio 4919-50-7 (KMR3 × O. rufipogon)

India 5 MT

IET3116 Vikas India 5 MT IRSSTN19 IRT11173 IRRI 5 MT

IET19487 DRR Dhan 39 India 5 MT IRSSTN5 IRT11237 IRRI 7 S

IET9341 CST7-1 India 5 MT IRSSTN14 IRT11160 IRRI 5 MT

IRSSTN15 IRT11176 IRRI 5 MT IRSSTN3 IRT11239 IRRI 5 MT

IRSSTN29 IR45427-2B-2-2B-1-1 IRRI 3 T IRSSTN21 Pokkali (ACC108921) IRRI 3 T

IRSSTN6 BR11-Saltol IRRI 9 HS IRSSTN1 IRT11169 IRRI 5 MT

IRSSTN11 IRT11236 IRRI 7 S IRSSTN9 IRT11149 IRRI 5 MT

IRSSTN13 IRT11260 IRRI 5 MT IRSSTN22 Nonabokra IRRI 3 T

IRSSTN10 IRT11133 IRRI 7 S IET18076 DRRH2 India 5 MT

IRSSTN30 A69-1 India 5 MT IET5656 Swarna India 9 HS

IET19046 Sambha Mahsuri India 9 HS IET17340 CSR36 India 3 T

IRSSTN28 AT401 India 3 T IRSSTN8 IRT11252 IRRI 7 S

IRSSTN12 IRT11254 IRRI 5 MT IRSSTN7 IRT11170 IRRI 7 S

IRSSTN27 IR55179-3B-11-3 IRRI 3 T IET15420 Jarava India 5 MT

IRSSTN2 IRT11158 IRRI 5 MT IRSSTN18 IRT11141 IRRI 3 T

IRSSTN23 IR29 IRRI 7 S IET13765 CSR27 India 3 T

T, Tolerant; MT, Moderately tolerant; S, Susceptible; HS, Highly susceptible; IRRI, International Rice Research Institute.

Table 3. Frequency of major allele and polymorphic information content (PIC) value of SSR markers for 54 rice genotypes. Marker Chromosome Frequency of

major allele

Number

of alleles PIC value

RM493 1 0.46 3 0.96 RM3412 1 0.53 3 0.96 RM7075 1 0.26 5 0.97 RM8094 1 0.24 7 0.99 RM10694 1 0.57 3 0.97 RM10720 1 0.43 3 0.95 RM10793 1 0.32 5 0.97 RM10843 1 0.39 3 0.95 RM10852 1 0.35 3 0.94 RM289 5 0.70 2 0.55 RM413 5 0.56 5 0.96 RM264 8 0.70 3 0.90 RM149 8 0.20 4 0.77 RM222 10 0.35 5 0.96

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and CST7-1 showing seedling stage salinity tolerance had FL478 alleles at RM7075 on chromosome 1 and RM264 on chromosome 8.

IET21943 showed new alleles for the SSR markers RM8094, RM10720 and RM10852 at Saltol region compared to the alleles of FL478. Tolerant line IET21943 had a novel rare allele of RM8094 that was

not present in FL478 but present in CST7-1 and IET22631. One FL478 allele of RM3412 was present in 10 salt tolerant genotypes but absent in all the 7 highly susceptible lines and also in 15 out of 16 moderately tolerant lines. Conversely, one allele of RM10720 was found only in five highly susceptible lines. Likewise, allele 3 of RM149 was present in all

Fig. 1. Gel picture showing amplification pattern of locus RM8094 in all 54 genotypes.

Fig. 2. Dendrogram showing grouping of 54 rice genotypes based on unweighted pair group method with arithmetic averages algorithm clustering and Jaccard coefficient analysis using 14 SSR markers.

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highly susceptible lines and in 4 out of 11 tolerant lines, too.

Most of the salt tolerant genotypes showed FL478 allele at RM264. Moderately tolerant genotypes IET22631, IET22626, IRT11254, IRT11169, IRT11149 and IRT11172 did not share any allele with FL478 at the 14 markers studied.

DISCUSSION

Pokkali and its derivative FL478 have been used as donors for salt tolerance in conventional breeding.

Saltol is located within a region consisting of RM8094, RM3412 and RM493 on chromosome 1. Among these, RM8094 is the most tightly linked marker with Saltol, with the highest LOD peak (Thomson et al, 2010; Islam et al, 2012; Samal et al, 2016). In this study, the maximum alleles were found for RM8094. Thus, RM8094 and RM3412 can be very useful for marker-assisted selection of Saltol QTL as the phenotypic screening requires more facilities. Mohammadi-Nejad et al (2008), Thomson et al (2010) and Babu et al (2014) used RM8094, RM3412 and RM493 for their discriminating ability in salt tolerance. Islam et al (2012) reported that RM8094 showed high PIC value (0.89) with a maximum of 15 alleles followed by two markers RM3412 and RM493 within Saltol QTL each showed PIC of 0.81 with 10 alleles and were used to identify haplotype diversity in salt tolerant varieties/lines. Similar to this study, but in a set of 142 diverse rice genotypes, RM8094 was reported as a suitable marker for discriminating salt tolerant genotypes from the susceptible ones, because it shows the highest number of alleles and PIC value (0.991) (Ganie et al, 2016).

RM8094 had the highest PIC value (0.99) with the maximum of seven alleles. RM3412 and RM493 had PIC value of 0.96 with three alleles. All tolerant lines with score 3 showed FL478 allele of RM8094 as common marker allele for salinity at the seedling stage. Thus, RM8094 was the most informative marker used to discriminate salt tolerant lines. Bimpong et al (2016) used RM493 which flanks the Saltol region to select the plants with homozygous recipient allele. Mishra et al (2016) showed that there is a significant level of diversity in HKT ion family transporter genes, especially for HKT1;5 and HKT2;3 and these genes are associated with high salinity tolerance among 95 Indian wild rice accessions including O. rufipogon. Interestingly, HKT1;5 gene was located 64 kb away at downstream of the marker RM10720 and 1.2 Mb away at upstream of RM3412 located within Saltol region.

Babu et al (2014) and Krishnamurthy et al (2015) reported that QTLs other than Saltol contribute to salt tolerance in the genotypes including advanced breeding lines, landraces, released varieties and wild species. Kordrostami et al (2016) showed that RM8094, RM3412, RM493 and RM10793 are associated with salt tolerance-related traits in 42 rice varieties. Linh et al (2012) used FL478 for transfer of Saltol QTL into an elite variety BT7 through marker-assisted backcross method. RM493 and RM3412 were used for foreground selection and RM10694 and RM7075 for recombinant selection along the Saltol region on chromosome 1, and concluded that all improved lines had Saltol allele and showed tolerance similar to FL478. Likewise, Huyen et al (2013) also used marker-assisted backcross method to introgress Saltol QTL from FL478 into an elite Vietnamese rice variety

Marker 1 2 3 4 5 6 7 8 9 10 11 12 13 14 RM10694 RM8094 RM10720 RM3412 RM493 RM10793 Genotype

IRSSTN25 IRSSTN21 IRSSTN18 IET

137 65 IRSSTN22 IET 219 43 IET23124 IET 219 44 IET 226 28

IRSSTN20 IRSSTN10 IRSSTN15 IET

173

40

IET3116 _IET

226

27

IRSSTN2 _IRSSTN13 _IRSSTN23 IET

194 87 IRSSTN19 IET 180 76 IET 190 46 T he ot he r ge not yp es

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Q5DB. Based on our studies, RM8094 and RM3412 in the Saltol region of chromosome 1 can reliably identify the salt tolerant genotypes. Other markers such as RM10720 and RM10852 on chromosome 1 and RM149 and RM264 on chromosome 8 can also differentiate between tolerant and highly susceptible lines but with lesser stringency. FL478 has been used as a reference in previous haplotype studies as well (Krishnamurthy et al, 2014; Ganie et al, 2016).

The UPGMA analysis delineated all 54 genotypes into two major clusters (Fig. 2). Cluster I consisted of only tolerant genotypes. In cluster II three Swarna × O.

nivara introgression lines IET23124, IET23183 and IET21542 which are highly susceptible to salinity grouped in sub-cluster I. Four O. rufipogon introgression lines IET22631, IET22628, IET21944 and IET22633 and one O. nivara introgression line IET22625 which are moderately susceptible to salinity grouped into sub-cluster II. Sub-cluster III consisted of moderately tolerant genotypes. Sub-cluster IV had only susceptible lines including one O. nivara introgression line IET22624 and three O. rufipogon introgression lines IET21940, IET22626 and IET22627.

It is significant to note that some of these introgression lines performed well in multi-location coastal and inland salinity trials conducted by IIRR. One introgression line IET21943 (KMR3/O. rufipogon, RP Bio 4919-50-13) which showed a score of 3 at the seedling stage in this study has recently been released as Chinsurah Nona 2 in West Bengal for coastal saline areas after four years of multi-location testing in AICRIP (All India Coordinated Rice Improvement Project) trials for high yield under saline conditions. It showed a high yield level of 5.4 t/hm2 at Canning West Bengal, in 2012 compared to the check variety CST7-1 (4.7 t/hm2) in coastal salinity trial. On overall basis it showed an average yield of 2.5, 2.4, 3.2 and 3.1 t/hm2 in 2010, 2011, 2012 and 2013, respectively, in trials for coastal salinity (AICRIP, 2013). Thus, IET21943 and its sister line IET21944 which also gave high yield in coastal salinity are good sources for not only new alleles in Saltol region but also for new QTLs/genes for salt tolerance at the reproductive stage. Out of 14 lines, two introgression lines IET21943 and IET22636 from the cross KMR3 × O. rufipogon are as tolerant to salinity as FL478 and grouped into cluster I. Ganeshan et al (2016) reported RP Bio 4919-50-13 maintains consistent level of chlorophyll and shows significant increase in yield than KMR3 under salinity of 150 mmol/L NaCl. They concluded that the

salt tolerance at the reproductive stage is mediated through Na+ exclusion from roots. Rai et al (2010) indicated that RP Bio 4919-50-13 also had drought tolerance under direct-seeded conditions. On the other hand, RP Bio 4918-230 was highly susceptible to salinity stress, though it showed resistance to brown planthopper (BPH) (Lakshmi et al, 2010). Likewise, another RP Bio 49189-248 was highly susceptible to salinity but it had high radiation use efficiency, nitrogen use efficiency and moderate resistance to leaf blast, neck blast, rice tungro disease, brown spot and sheath rot. It was released as DRR Dhan 40 for three states (Tamil Nadu, Maharastra and West Bengal) after completing three years of multi-locational testing (AICRIP, 2012). These high yielding contrasting lines derived from elite × wild crosses RP Bio 4919-50-13, RP Bio 4918-230 and RP Bio 4918-248 are good lines for studies on salt tolerance at the seedling and reproductive stages. Zhou et al (2016) elucidated the molecular genetic mechanisms of salt-stress tolerance in O. rufipogon compared to Nipponbare through transcriptome analysis. These results indicated that O.

rufipogon is a suitable donor for salt stress tolerance compared to cultivated rice. Thus, these tolerant genotypes may contain novel QTLs/genes at other loci for salt tolerance at the seedling and later growth stages also.

ACKNOWLEDGEMENTS

Financial support of Department of Biotechnology, Government of India [Grant Nos. BT/AB/FG-2 (PH-II) 2009 and BT/PR13357/AGR/02/695/2009] is gratefully acknowledged.

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