Insilico analysis of drought tolerant genes in rice

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					                                                                             Int J Biol Med Res. 2010; 1(3): 36-40.
                                                                                                                                                                  Int J Biol Med Res   
                                                                                                                                                                  Volume 3, Issue 3, July 2010

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Original article

Insilico analysis of drought tolerant genes in rice
                                           a,b,                                                  a                                                 b
Mathiyalagan Ramya *, Muthurajan Raveendran , Subramaniyam Sathiyamoorthy ,
Jegadeesan Ramalingama
  Department of Plant Molecular Biology and Biotechnology, Tamil Nadu Agricultural University, Coimbatore-641 003, Tamil Nadu, India.
 Korean Ginseng Center and Ginseng Genetic Resource Bank, Kyung Hee University, 1 Seocheon, Giheung-gu, Yongin-si, Gyeonggi-do, 449-701, South Korea.

ARTICLE INFO                                                       ABSTRACT

Keywords:                                                          Rice (Oryza sativa L.) is the important cereal food crop and model crop for plant genome
Abiotic stress                                                     analysis. Drought remains as one of the major constraints limiting rice productivity.
Drought                                                            Conventional breeding approaches are slow in progress towards developing drought tolerant
Quantitative trait loci                                            rice varieties due to complex nature of drought tolerance mechanism. The understanding of
Insilico                                                           plant responses to abiotic stresses at the genomic level provides a foundation for gene
DRE-cis element
                                                                   discovery and genetic engineering of rice for drought tolerance. Identifying quantitative trait
                                                                   loci (QTLs) controlling drought tolerance related traits will help in precise introgression of
                                                                   desired genomic regions (QTLs) through marker assisted selection and genetic engineering.
                                                                   The genomic region on chromosome 9 (73 - 95 cM) controlling drought tolerant related traits
                                                                   were selected and attempts were made through insilico methods to understand the putative
                                                                   candidate genes controlling drought tolerance. Through literature survey and database search,
                                                                   QTL located on chromosome 9 (73 to 95 cM) linked to drought tolerance related traits was
                                                                   selected. About 145 drought responsive genes were found to be located in this region as
                                                                   reported in a publicly available microarray data. The drought responsive genes were classified
                                                                   according to their function and presence of cis elements. Detailed analyses revealed that
                                                                   majority of these drought responsive genes are involved in important cellular functions and
                                                                   enriched with DRE-cis elements. Aquaporin (OsPIP2; 7) and cytochromeP450 (OsCYP78A3)
                                                                   genes were selected for functional validation. Semi-quantitative RT-PCR analysis revealed the
                                                                   differential expression of these genes between contrasting rice genotypes IR64 and
                                                                   Nootripathu for drought tolerance at vegetative stage.
                                                                                                                   c Copyright 2010 BioMedSciDirect Publications. All rights reserved.

1. Introduction
   “Rice is life”- This slogan of the international year of rice (2004)                                  One of the most exciting developments in rice biotechnology is
outlines the importance of rice. Rice (Oryza sativa L.) is one of the                                 the advent of molecular markers. A series of molecular markers,
important cereal food crops in the world and serves as a model                                        e.g. random fragment length polymorphism (RFLP), random
monocot crop for plant genome analysis due to the availability of                                     amplified polymorphic DNA (RAPD), amplified fragment length
whole genome sequence information, high throughput molecular                                          polymorphism (AFLP) and microsatellites have become available.
biological tools and large number of targeted mutant collections.                                     The technology of quantitative trait loci analysis could be usefully
Rice is sensitive to a variety of abiotic stresses including salinity,                                employed to analyze the genetics of complex traits. Identifying and
drought, submergence and cold [1]. Among these stresses, drought                                      analyzing the traits and genes present in the genomic region (QTL)
stress is a serious limiting factor to rice production and yield                                      will help in improve the plants through marker-assisted breeding.
stability in rainfed rice areas [2]. Conventional breeding                                            Genome wide identification of genes regulated by drought or high
approaches towards developing drought tolerant rice varieties are                                     salinity conditions has manifold significance. First, it provides a
resulting in slow progress due to complex nature of drought                                           more comprehensive understanding of the transcriptional
tolerance mechanism(s). In this context, biotechnology offers us a                                    responses to those stresses. Second, it provides a starting point for
powerful means of manipulating drought tolerance in rice through                                      further elucidating the role of individual genes in stress responses,
QTL mapping and genetic transformation.                                                               which will be of great value in crop engineering. Third, it aids in the
                                                                                                      identification of stress responsive promoters and responsible cis
    * Corresponding Author : Mathiyalagan Ramya
        Korean Ginseng Center and Ginseng Genetic Resource Bank,
                                                                                                      elements within them that are important both for basic study and
        Kyung Hee University, 1 Seocheon, Giheung-gu, Yongin-si, Gyeonggi-do, 449-701, South Korea.   crop engineering applications. Genetic Engineering provides us
        Mobile: +0082-10-5578-5385, E-mail:                                      the powerful way of improving/incorporating drought tolerance
    c Copyright 2010 BioMedSciDirect Publications. All rights reserved.
                                            M Ramya et al. / Int J Biol Med Res. 2010; 1(3): 36-40.

  in rice by introducing foreign genes conferring stress tolerance. In    Table 1. Details of QTLs of 73-95 cM region in Chromosome 9
 this context, availability of suitable candidate gene(s) is highly
 necessary before adapting this strategy. Both traditional breeding          QTL ID   Trait         Flankig Marker     cM      Parents        Refe-
 and genetic engineering of crop plants have been utilized to                         Name          Markes ID                                 rence
 improve drought and high salinity tolerance or resistance with the
 goal of increasing agricultural productivity in affected regions [3].      DQE53     Relative       RFLP   RG451    86.2-91 IR64/AzU(DH)     [22]
                                                                                      water          RFLP   RZ404
    Most of the drought tolerance related QTLs reported in different                                 RFLP   RG667
 studies [4-6] but they are larger in size and needs fine mapping                                    RFLP   RZ972
 procedures to narrow down it to smaller region(s) amenable for             DQE30     leaf-          RFLP   RZ12     74-77.6 IR64/AzU(DH)     [22]
 introgression. This will also help in identifying candidate genes                                   RFLP   RG667
 underlying the molecular basis of QTLs, which can be used for                                       RFLP   RZ228
 genetic engineering experiments. Now with the availability of                                       RFLP   RG451
 whole genome sequence information, expression profiling tools              DQE31     leaf-          RFLP   RZ12     74-77.6 IR64/AzU(DH)     [22]
                                                                                      rolling        RFLP   RG667
 and updated annotation, it is possible to align the genetic map with
                                                                                                     RFLP   RZ228
 the physical map, which will lead to the identification of putative
                                                                                                     RFLP   RG451
 candidate genes. Integration of QTL map data with the physical
                                                                            AQAA07    Relative       RFLP   RG667    77.8-   CT9993/IR6226 [23]
 map and expression (whole genome transcript profiling) map will                      root-          SSR    RM215    82.9
 be a powerful way of short-listing the putative candidate genes                      length
                                                                                                     SSR    RM201
 which can be then taken for further downstream analysis for                                         RFLP   RG358
 validation. Here, we identify a major effect QTL linked to drought                                  RFLP   RZ792
 tolerance related traits in rice, drought responsive genes in the          CQ19      Potassium      SSR    RM205   77.3-    Sussex IR55178   [24]
 QTL region, functional characterization, promoter analysis and                       uptake         RFLP   E12M311 116.4
 validation of select genes by RT-PCR.                                                               SSR    RM189
                                                                            CQQ16     Root dry       RFLP   RZ228    65.7-   IR64/Azu(DH)     [25]
    In this study, a major effect QTL on chromosome 9 (73 to 95 cM)                   weight to      RFLP   RZ422    71.3
 linked to various drought tolerances related traits in rice were                     tiller
                                                                                      number         RFLP   RZ12
 selected. Detailed bioinformatics analyses were carried out to                       ratio
 identify the genes located in the QTL region, to analyse the
 presence of cis elements in the promoter region(s) and map them            AQEZOO7 Aluminum         RFLP   RZ698    34.4-   IR1552/Azu(RI) [26]
                                                                                    sensitivity      RFLP   RG757    73.1
 onto metabolic pathways. Finally drought responsiveness of few
                                                                                                     RFLP   RZ422
 selected genes was studied by RT-PCR in a set of contrasting rice
 genotypes.                                                                 AQEZOO3 Aluminum         RFLP   RZ698    34.4-   IR1552/Azu(RI) [26]
                                                                                    sensitivity      RFLP            73.1
 2. Materials and Methods                                                                            RFLP   RZ422
 2.1. Selection of target QTL
                                                                            DQF12     Penetrated     RFLP   RZ228    65.7-   IR64/Azu(DH)     [27]
                                                                                      root thick-
     QTLs linked to various drought tolerance related traits in rice                  ness
                                                                                                     RFLP   RZ422    71.3
were selected from various resources viz., literature, QTL                                           RFLP   RZ12
databases ( and publicly available
                                                                            AQBD006 Phosphor-        RFLP   RG451    47.8-   IR20/IR55178     [28]
experimental data. The QTLs were analyzed for their significant                     our sensi-       RFLP   RZ401    94.2    (RI)
association with drought tolerance related traits across different                  tivity
genetic backgrounds and effect on the phenotype [4]. Among them,            AQBD007 Salt sen-        RFLP   R1751    60.9-   CNSIPPE Non/Kos [29]
a major effect QTL located on chromosome 9 (flanked by the                          sitivity         RFLP   R2638    82
markers RM 219 and RM 201; 73 - 95 cM) was selected for further                                      RFLP   R79
analysis based on its association with Relative water content, leaf                                  RFLP   C609
rolling, relative root length, etc., (Table 1)
                                                                          pairs were identified in genome annotation download for osa1 in
2.2. In silico analysis of the QTL region                                 TIGR database. Using the BAC/PAC clones the gene position in base
      Putative genes present in the QTL region were identified            pairs were converted into corresponding cM distance. The
from the TIGR rice database (TIGR Rice Pseudomolecule version             updated annotation provided in the TIGR Rice Psedomolecule
5). Drought responsiveness of the genes located in this QTL region        Version 5.0 was considered for analysis. The putative function of
was predicted by aligning this physical map with a publicly               annotated genes was identified using gene ontology database in
available expression (transcriptome) map obtained through                 Gramene ( and TIGR rice database.
microarray analysis [3]. 145 drought responsive genes were found          2.4. Promoter analysis of drought responsive genes
to be located in this region. These drought responsive genes were
used for further downstream analysis.                                           To analyze the cis regulatory elements in the promoter
                                                                          region of the drought responsive genes, the 1 kb upstream
2.3. Functional categorization of drought responsive genes                sequences of the 145 drought responsive genes were downloaded
                                                                          using TIGR database. Analyzed for the presence of drought related
       Drought responsive genes (145 genes) located in the target
                                                                          DRE, ABRE, MYB and MYC conserved motif cis sequences, their
QTL region were classified according to their cellular and
                                                                          exact position and their repeated number of occurrence of
physiological functions using gene ontology database and
                                                                          conserved cis elements were also identified using PLACE database
literature search. The oligo ID represented in the microarray data
                                                                          ( and literature search. The
was converted into TIGR ID using rice array database in TIGR. The
                                                                          conserved cis motif sequences used in this study is presented in
gene name and position of particular gene from 5' to 3' in base
                                                                          Table 2.
                                                M Ramya et al. / Int J Biol Med Res. 2010; 1(3): 36-40.

Table 2. Details of conserved cis motif sequences                               both years had large effects on the traits as reflected by the large
                                                                               proportions of the phenotypic variation explained (10% or more).
  Cis-acting elements Conserved cis motif sequence Reference
                                                                               The region RM219-RM296 on chromosome 9 showed a large
  DRE/CRT                        A/GCCGAC                       [16]           effect on number of days to leaf rolling (QDlr9)and QTL for leaf
  ABRE                           ACGTGGC, ACGTGTC               [30]           drying score (QLds3b) had a large effect on the trait in two
                                                                               consecutive years (2003-2004) [4]. The region between RM160-
  MYBR                           C/TAACG/TG
  MYCR                           CACATG/CATGTG                  [31-32]        RM215 on chromosome 9, contributing to maximum root depth
                                                                               under both control and drought stress [8]. In near to the genomic
2.5. Differential gene expression and drought stress conditions                region RM316-RM219 on chromosome 9, a QTL for cell
                                                                               membrane stability (marked by RZ698-RM219) was also
     Two genes namely an Aquaporin (OsPIP2; 7) and a                           reported [9]. In another study, a QTL for OA was identified in this
cytochrome P450 (OsCYP78A3) genes were studied in detail to                    region, and it was also shown that this region corresponded to a
test their role in drought tolerance. Gene specific primers were               region in wheat where a QTL for ABA content was detected [10].
designed based on gene structure (OsPIP2; 7 {Forward (5'-3')-
G T G A G G A A G A C G A C G AT G T T C a n d R e v e r s e ( 5 ' - 3 ' ) -          This region was found to harbour key drought tolerance
CAGATACATACAGGCACTCCAC}; OsCYP78A3 {Forward (5'-3') -                          related genes namely, DREB1A, DREB1B, MYB, MYC, Phytoene
ACTTCACCGACGTCTTGCT and Reverse (5'-3')-                                       synthase, Aquaporin etc. Alignment of physical map of this QTL
ATGACGTAGCTTGGACACGT}. Genomic DNA was isolated from                           region with a publicly available microarray data revealed the
leaf samples of two contrasting rice genotypes namely IR 64                    presence of 145 drought responsive genes in this region and Out
(drought susceptible) and Nootripathu (drought tolerant) using                 of these, 53 was found to be up-regulated and 52 were down-
CTAB method. Specificity of designed primers was tested by PCR                 regulated during drought. Similar prediction was made during in
amplification of the above genes with PCR program: Initial                     silico analysis of rice semi dwarf locus flanked by the markers
denaturing-94°C (5 min) leading to 42 cycles of amplification                  RM212 and RM319 on rice chromosome 1 which resulted in the
{denaturation-94°C (1 min), annealing-51°C (OsPIP2; 7), 52°C                   prediction of 16 drought responsive genes [11].
(OsCYP78A3) for 1 min and extension-72°C (2 min)}final                               Metabolic pathway mapping of drought responsive genes in
extension- 72°C (10 min). The resultant products were visualized               this region revealed that they found to be involved in diverse
by agarose gel electrophoresis. Differential expression of the                 metabolic functions viz., transport (13%), cellular metabolism
putative candidates was tested in a set of contrasting rice                    and signal transduction (12 %), transcription activity (11%) and
genotypes namely IR64 (drought susceptible) and Nootripathu                    plant hormonal regulation (6%). Remaining genes were to be
(drought tolerant). Plants were grown under green house                        involved in biotic and abiotic stress response, structural and
conditions with normal watering. Drought stress was imposed to                 regulatory functions, and transcriptional and post transcriptional
a set of plants at 52 DAS by withholding water and the intensity of            regulation (Fig 1). The mechanism of stress perception and cell
drought was monitored by measuring the relative water content                  signaling plays an important role in altering the ability of the plant
(RWC) of the leaves [7]. Leaf samples were collected from both                 to survive under abiotic stress conditions. The present study
control and drought stressed plants of both the varieties when the             revealed the presence of key signaling genes namely,
RWC of the drought stressed plants reached around 50 per cent.                 phospholipase, serine /threonine protein kinase (SRPKI),
                                                                               calcium dependent protein kinases, phosphate DCR 2 and OsWAK
2.6. Semi-quantitative RT-PCR
                                                                               receptor like protein kinase in the QTL region (73 to 95 cM on
      Total RNA was extracted from both control and drought                    chromosome 9). These protein kinase such as mitogen activated
stressed leaves of IR64 and Nootripathu by TRIzol reagent                      protein (MAP) kinases, calcium dependent protein kinase (CDPK)
method (Sigma Aldrich Inc., USA). RNA was quantified using                     and protein phosphates were demonstrated to be either stress
nanodrop spectrometer ND-2000 (A260/A280~ 2.0) and its                         inducible or up regulated by dehydration [12].
quality was assessed by agarose gel electrophoresis (1.5 %).
                                                                               Figure1. Functional classification of selected drought tolerant
Transcript abundance of OsPIP2;7 and OsCYP78A3 was
monitored in the RNA samples extracted from control and
drought stressed plants of IR64 and Nootripathu by One-step
Superscript-II RT-PCR kit from Invitrogen Inc., USA using the
following thermal cycle program: Initial reverse transcription at                        Regulatery

52°C (40 min); initial denaturation - 95°C (5 min) leading to 40
cycles of amplification {(denaturation-95°C-30sec, annealing-
51°C (OsPIP2;7) and 52°C (OsCYP78A3)-1 min and extension-
72°C (1 min)}final extension-72°C (10 min)). The resultant RT-
PCR products were visualized by agarose gel electrophoresis.
Differential expression was assessed by visualizing the intensity
of bands.
3. Results and Discussion
      A major QTL (flanked by the markers RM219 and RM201)
located on 73-95 cM region in rice chromosome 9 was
contributing significant QTLs for drought stress improvements.
The region between RM316-RM219 on chromosome 9 was                             Plants respond to stress conditions through physiological,
particularly active by exhibiting significant effects simultaneously           morphological, and metabolic processes. The common response
on relative yield (QRy9), relative spikelet fertility (QRsf9), relative        to water deficit/drought stress is cellular dehydration. Plants
biomass (QRbm9) and relative harvest index (QRhi9) They                        have developed several strategies to protect their cells from the
explained the worth noting that almost all the QTL detected in                 damage caused by dehydration and ROS. These include the
                                            M Ramya et al. / Int J Biol Med Res. 2010; 1(3): 36-40.

 accumulation of stress responsive proteins and development of            Table 3.Information on physical location of putative candidate
ROS scavengers such as peroxidases and accumulation of                    genes
anthocyanins. The target QTL selected in this study was found to
harbour genes involved in these processes. Functions of novel              Gene        Chr.No Oligo Id        Locus Id        Base Pairs   cM
genes in drought stressed seedlings of rice encoding                       Name
metallothioneins, late embryogenic abundant proteins (LEA),                OsPIP2;7     9    Os024799_01   LOC_Os09g36930.1   21309685-    84.3
heat shock proteins, cytochrome p450 enzymes, catalases,                                                                      21310658
                                                                           OsCYP78A3    9    Os005906_0    LOC_Os09g35940.1   20690888-    -79.1
peroxidases, kinases, phosphatases and transcription factors
were reported [12-14].
                                                                          Figure 3. Location of Aquaporin (OsPIP2; 7) and Cytochrome p450
       Transcription factors are important components of signal
                                                                          (OsCYP78A3) in rice genome
transduction networks conveying diverse signals to specific
responses. Genetic modification of plant by altering the
expression of individual genes will take long time to make a plant
over-expressing a group of genes conferring drought tolerance.
Alternatively activation of a set of genes by engineering for their
transcriptional activation can confer much greater stress
tolerance [15-16]. Many times it was reported that a transcription
factor or a protein kinase will underlie the molecular basis of a
QTL. The target QTL on chromosome 9 was found to contain key
TFs namely sbCBF 6, NAC domain containing protein 18 and 78,
Ring H2 finger protein and zinc finger protein. Over expression of
OsDREB1A in Arabidopsis revealed its role in stress tolerance
[17]. Insilico analysis to predict the presence of cis elements in the
promoter region of the stress responsive genes revealed the
presence of various cis acting elements involved in abiotic stress
response. Among the 145 drought responsive genes (selected
from the publicly available microarray data), 21% genes were
found to possess DRE (A/GCCGAC) elements, 24% genes were
found to contain MYC (CACATG /CATGTG) elements, 15% genes
were found to contain MYB (C/TAACG/TG) elements and 8%
genes were found to possess ABRE (ACGTGGC, ACGTGTC)
elements (Figure2). Previously, cis acting regulatory elements
under various stresses viz., drought, salinity, cold and biotic stress         OsPIP 2; 7 was found in leaf blades by [18]. Down regulation
were reported [16]. Presence of abiotic stress related cis elements       of Aquaporin PIP genes were reported in rice [3][19] and
in the promoter regions of the genes harbored in the select QTL           arabidopsis [20] under drought stress conditions. For plant
region may be responsible for activation of more number of genes          growth and development, physiological processes namely water
in this region during drought.                                            uptake and flow across cellular membranes are essential and
                                                                          aquaporins are key proteins involved in water transport. It was
       To validate the microarray data and also to prove the              reported earlier that aquaporins may play a crucial role in cell
differential expression of key stress responsive genes between a          osmoregulation [21].
set of contrasting rice genotypes, expression pattern of two genes
namely an aquaporin (OsPIP2;7 accession no: AP006149 involved                  The OsCYP78A3 gene was highly expressed in drought
in transport and signaling) and a Cytochrome P450 (OsCYP78A3)             tolerant cultivar Nootripathu than drought susceptible cultivar
was studied by semi-quantitative RT-PCR. Information on the               IR64 during control and it was found to be down regulated in both
name, location, and gene size gene structure is provided in Table 3       the varieties during drought as reported in the microarray
and Figure 3. The results revealed that OsPIP2; 7 was found to be         experiment (Figure 4).
significantly down regulated during drought in the susceptible IR
64 whereas it was not affected significantly in the tolerant              Figure 4. RT-PCR analysis of OsPIP2; 7 and OsCYP78A3 genes.
Nootripathu (Figure 1).

Figure 2. Cis elements classification of selected drought tolerant

                                                                                  Lane: 1. Nootripathu control 2. Nootripathu drought
                                                                                             3. IR64 control 4. IR64 drought
                                                      M Ramya et al. / Int J Biol Med Res. 2010; 1(3): 36-40.

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