The association of markers with Drought Susceptibility Index (DSI) in rice (Oryza sativa L.)

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1 2015; 3 (2): ISSN: EJBB 2015; 3 (2): Received: Accepted: Ajay Prakash Lincoln Mandal India. Satish B. Verulkar Correspondence: Ajay Prakash The association of markers with Drought Susceptibility Index (DSI) in rice (Oryza sativa L.) Ajay Prakash, Lincoln Mandal, Satish B. Verulkar Abstract Rice (Oryza sativa L.) is the staple food of half of the world's human population. Drought is one of the major limited factors for growth of high-yielding rice varieties in drought-prone rainfed environments. The selected 48 lines of F6 generation were used for analysis derived from a cross between Mahamaya Budda cultivar. Based on the yield of each line, the drought susceptibility index (DSI) was calculated for both situations i.e. rainfed as well as terminal stage drought. The graph for both the situations showed variation for DSI which indicate the polygenic nature drought tolerance. SMA and t-test were done for detecting the association between marker and Drought susceptibility index (DSI). The five SSR markers such as RM202, RM212, RM258, RM264 and RM279 were found polymorphic among the 66 SSR markers screened between parents. The markers RM 202 and RM 258 showed significant linkage with DSI at 5% level of significance. The data of five SSR markers were used to identify QTLs for drought susceptibility index. Two QTLs were detected for DSI on chromosome 10 and 11 on rice genome. These closely linked SSR markers with drought tolerance will facilitate early selection of drought tolerant lines and shorten breeding period. Keywords: Rice, Single marker analysis, QTL, Drought susceptibility index (DSI) 1. Introduction Rice (Oryza sativa L.) is one of the oldest domesticated crops, which provides food for more than half of the world s population and constitutes a major source of calories for urban and rural inhabitants (Khush, 2005). Drought, defined as the occurrence of a substantial water deficit in the soil or atmosphere, is an increasingly important constraint to crop productivity and yield stability worldwide (Ceccarelli and Grando, 1996). It is by far the leading environmental stress in agriculture and the worldwide losses in yield owing to this stress probably exceed the losses from all other causes combined (Schonfield et al., 1988). The term drought tolerance has been considered in term of final yield rather than to the capacity of the plant to survive in water limited conditions (Tuberosa and Salvi, 2006). Accumulating evidence suggests that plant response to drought tolerance is controlled by more than one gene (Subudhi et al., 2000; Zhang et al., 2001) and is highly influenced by environmental variation (Ceccarelli and Grando, 1996). A promising approach to facilitate selection and breeding for complex traits like drought tolerance is to identify simply inherited genetic markers that are linked with the traits of interest and to use them as indirect selection criteria (Dudley, 1993). During the past two decades, DNA markers have been successfully used for screening plant genomes for quantitative trait loci (QTLs) controlling complex traits, including tolerance to abiotic stresses (Zhang et al., 2001). The progress in molecular biology and DNA marker techniques provides powerful tools to allow molecular dissection of the complex traits. The drought susceptibility index (DSI) is a measure, based on yield per se under stress and non-stress conditions. The drought susceptibility indexes (DSIGY) were calculated by determining the changes in grain yield (GY) under two soil moisture levels (irrigated and drought) and confirmed that they are good indicators of drought tolerance in plants (Grzesiak et al., 2013). The identification of marker-qtl association not only allows genetic dissection of physiological mechanisms underlying complex traits but also expedites transfer of QTLs through a process known as marker assisted selection (MAS). Furthermore, MAS may reduce both the number of generation required to transfer a trait and the extent of linkage ~ 10 ~

2 drag, which is often a problem when transferring genes from exotic sources (Dudley, 1993). The development of phenotypic and genotypic data based on molecular markers will help in identifying QTLs for traits of economic importance. The present study was under taken to carry out the molecular studies on drought susceptibility index (DSI) under managed two levels of water stress conditions. Materials and Methods Materials The plant materials used for this study were 48 selected lines derived from a cross between Mahamaya Budda rice cultivar developed by Dr. S. B. Verulkar, Department of Plant Biotechnology, College of Agriculture, IGKV, Raipur, The Mahamaya variety is moderately susceptible and Budda resistance to water stress under field conditions. These selected 48 lines of F 6 generation were grown in the field under two different levels of stress and one irrigated control during wet season 2006 to record the grain yield. Field evaluation of selected lines The selected lines derived from a cross between Mahamaya Budda rice cultivar of F 6 generation were evaluated in the field during wet season The field trails were conducted under transplanted condition. Under rainfed and irrigated condition, nursery was grown on 25 th June, Transplantation was done on 20 th July and 26 th July for rainfed and irrigated condition respectively. The sowing and transplanting of the crop was delayed by approximately 20 days under terminal stage drought condition to increase the chance of exposure of plant materials at terminal stage to water stress. The nursery for this condition was sown on 15 th July and transplantation was done on 4 th August, Each genotype was sown in two row of 2m length. All the genotypes were replicated twice. All normal packages of practices were followed to raise a good crop. The actual yield in gram per plot was recorded and later converted to gram per square meter for further analysis. Molecular studies All 48 selected lines from the cross between Mahamaya and Budda were used for molecular studies. The leaves of 10 day old seedlings were used for DNA isolation (Dellaporta et al., 1983). The quantity of DNA samples was estimated by quantifing on Nano Drop Spectrophotoscopy and 5 l of DNA from stock was diluted up to 20 times using 95 l of double distilled water (Nano pure). The diluted DNA was subsequently used for PCR amplification. PCR amplified SSR product was mixed with 2 l of 10x loading dye and loaded on 2.5% Agarose gel along with sample for separation. Development of genotypic data of population The marker exhibiting polymorphism on parents were further used for PCR amplification on all of the 48 selected lines of rice. The genotypic data were generating with a set of 5 polymorphic markers. The scoring SSR banding pattern in population taken as A for Mahamaya like allele, B for Budda like allele and H mean both alleles. Statistical analysis Analysis of Drought Susceptibility Index (DSI) Drought tolerance was viewed in terms of drought susceptibility index (S) proposed by Fischer and Mauror (1978) which is a standardized ratio of drought stress yield to irrigated yield S is defined as follows: S = (1 Y s /Y i ) / (1 - Ys / Yi) Where, Ys = Yield in stress condition Ys = Mean yield in stress condition. Yi = Yield in irrigated condition. Yi = Mean yield irrigated condition. QTL analysis In selected lines, single marker analysis was used to estimate linkage between marker and trait by using t- test formula given below: Where, X = Mean of lines having female allele Y = Mean of lines having male allele n 1 and n 2 = number of female and male alleles respectively S= Population Variance Results and discussion The selected lines were evaluated in the field during wet season 2006 under two different levels of water stress along with irrigated control and the observations were recorded on yield. The mean data of stress Vs irrigated control was used for calculation of DSI and QTL analysis. The results thus obtained are presented under following headings: General observations During wet season 2006 around mm of rainfall was received and the distribution of rainfall was even. During the season a period of 7-9 days was common when there was no rainfall inducing water stress in the field. Under rainfed condition, the crop was sown at last week of June with normal agronomic practices and transplanted after 15 days. The field was never irrigated and rain water was drained off effectively on the same day. During this period short dry spell of 7 and 9 days were prevailed in the field which induced significant water stress. Because of this management in the field drought occurred resulting into reduction in grain yield. Another set of condition was created through exposing the crop to terminal stage drought. The nursery sowing and transplanting were delayed by days and irrigation was given up to one month after transplanting. Then the same management practice was followed as in case of rainfed condition in order to induce drought at the terminal stage i.e. reproductive stage. However, during this season rain was received after draining off the field which in turn reduced the severity of water stress compared to our anticipation. Therefore, yield under terminal stage drought condition reduced up to certain level. ~ 11 ~

3 Calculation of Drought Susceptibility Index (DSI) The experimental materials including segregating population of cross between Mahamaya and Budda were grown under three sets of conditions, (1) irrigated (2) absolutely rainfed condition and (3) terminal stage drought, during wet season Based on the yield of each line, the drought susceptibility index (DSI) was calculated. The DSI was calculated for both situations i.e. rainfed as well as terminal stage drought. The data generated for DSI along with grain yield of three sets of conditions. In the rainfed condition the DSI ranged from to where minimum was under line no. 319 and maximum was under line 343 (21.765). On the other hand, under terminal stage drought condition, the DSI ranged from to where minimum and maximum were worked out in line no. 333 and 319 respectively. The graphical presentation of this data is presented in Fig.1. The graph for both the situations indicates the variation among the DSI which in turn indicate the polygenic nature drought tolerance and these results are in agreement with the number of other studies including (Ekanayake et al., 1985). The advantage of this parameter is that it considers the potential yield under irrigated condition and its relative reduction under stress. The polygenic nature of DSI indicates that in this cross either number of traits contribute towards drought tolerance or even if single traits effect, which must be a polygenic trait. Parental polymorphism analysis using SSR markers A set of 66 primers were used in this study for amplification of genomic DNA of Mahamaya and Budda through PCR. Out of 66 SSR primers RM 202, RM 212, RM 258, RM 264 and RM 279 showed polymorphism in banding pattern between the two parents, remaining 61 primers showed no difference among the parent. Thus 7.6% of primer exhibited parental polymorphism. As expected single band was observed for all primers in both the genotypes. SSR based population analysis The five primers exhibiting polymorphism were selected and used for PCR amplification on all of the 48 selected lines along with parents using standardized PCR protocol. On an average, the frequency of female allele was more (52.50%) compared to the frequency of male allele (47.07%). These values deviated slightly from the theoretical expected of 50 % each from both the parents. The marker RM-264 produces more female parent type alleles (66.67%) than male and RM- 279 produces more number of alleles like male parent (58.33%). The segregation pattern of A and B type bands followed 1:1 ratio, (except RM-264) indicated this population is segregate normally. Only one primer RM 202 exhibited only 2.08% heterozygous individuals and the remaining population under study is almost homozygous. This frequency is as per expected the predicted value of homozygosity for F 6 population (Allard, 1960). All five primers used in the study were tested for segregation with a 2 test for goodness of fit. Statistical analysis revelled that out of five primers, RM 243 marker deviated from the expected Mendelian 1:1 ratio. The different markers however exhibited difference in distribution of alleles. The frequency of female allele ranged from 41.67% for RM 279 to 66.67% for RM 264. Similarly, the frequency of male alleles ranged from 33.33% for RM 264 to 58.33% for RM 279. Identification of QTL for DSI The concept of detecting QTLs using linked major genes was given by Sax (1923). Recent progress in DNA markers and development of high-density molecular maps of rice (Causse et al., 1994) has allowed the localization of QTL and determination of relative magnitudes of their effect on the trait in rice. In selected lines of cross between Mahamaya and Budda, single marker analysis was used to estimate association between marker and trait. For the single marker analysis, t- test is followed to find out the significant association between trait and marker. Two means are calculated from the lines, which show male like and female like microsatellite allele. The mean difference was subjected to t-test analysis. The results of t test are presented in Table 1. The marker RM 202 and RM 258 shows significant linkage with drought susceptibility index (DSI) at 5% level of significance. The data of five SSR markers were used to identify QTLs for drought susceptibility index. Since marker data is not enough so single marker analysis by t- test was used for the purpose of QTL identification. Single marker analysis some time gives better results compared to interval mapping (Coffman et al., 2003). The significant of t-test indicates the significant association of trait with the marker. In present study, the significant association was identified between the DSI and two markers RM 202 and RM 258. Two QTL for DSI were detected. QTL were restricted to only two chromosomes one at chromosome 10 and other at chromosome 11 shown in Fig. 2. Table 1: The t-test analysis of 5 primers t - Value S. No. RM Primers RF TDS Ch. No. 1 RM * 3.544* 11 2 RM RM * RM RM ~ 12 ~

4 Fig 1: The graphical presentation of Drought Susceptibility index (DSI) for rainfed (RF) and terminal stage drought (TSD) condition of 48 lines Fig 2: The comparative QTLs location on chromosome 10 and 11 DSI is worked out using yield under stressed and irrigated environments. Although QTLs for DSI have been reported earlier on chromosome 4 and 12 in the rice genome ( however, some QTLs have been identified for gain yield on chromosome number 10 and 11 under different environments (Benmoussa et al., 2005). Apart from this, there were several QTLs have been identified for different traits which are related to drought tolerance in rice. ~ 13 ~ QTLs were identified in RIL population of a cross between Co39 and Moroberekan for tiller, root number, thickness and dry weight in rice (Champoux et al., 1995). QTLs for root morphology and root distribution in DHL mapping population of a cross between IR64 and Azucena in rice were detected (Yadav et al., 1997). On the same DHL population of IR64 X Azucena, (Hemamalini et al., 2000) identified 15 QTLs for morphological and physiological traits related to drought resistance in rice. Venuprasad et al. (2001) worked on IR64 X Azucena DH mapping population of rice in three diverse environments and detected QTLs for ten traits at a threshold. The QTLs were spread across six chromosomes 1, 3, 4, 5, 6, and 7. Three QTLs for grain yield were detected one each on chromosome 3, 4 and 5. QTLs for root thickness and root penetration index in rice were detected (Zhang et al., 2001). Price et al also reported 24 QTLs for various root growth traits in RIL population of a cross between Azucena and Bala in rice for drought tolerance. QTLs for yield, biomass, osmotic adjustment and roots in rice reported (Chandra Babu et al., 2003). Lafitte et al. (2004) identified 31 QTLs for yield and its components under rice drought on working with RIL population of Bala X Azucena. QTLs for yield; yield components, panicle sterility etc in rice was identified (Jonaliza et al., 2004) in RIL population of a cross between CT9993 and IR Xu et al. (2005) identified 36 QTLs in introgression indica lines of rice for yield and its components under drought.

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