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Field Crops Research 137 (2012) 89–96

Contents lists available at SciVerse ScienceDirect

Field Crops Research

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valuation of rice (Oryza sativa L.) near iso-genic lines with root QTLs for plantroduction and root traits in rainfed target populations of environment

.K. Suji1, K. Silvas Jebakumar Prince1, P. Sumeet Mankhar, P. Kanagaraj, R. Poornima, K. Amutha,. Kavitha, K.R. Biji, S. Michael Gomez, R. Chandra Babu ∗

epartment of Plant Molecular Biology and Bioinformatics, Center for Plant Molecular Biology and Biotechnology, Tamil Nadu Agricultural University, Coimbatore 641 003, India

r t i c l e i n f o

rticle history:eceived 23 April 2012eceived in revised form 24 July 2012ccepted 2 August 2012

eywords:iceainfed ecosystemroughtoot traitsTLs

a b s t r a c t

Drought stress is the major constraint in rainfed rice production. Deep and thick roots are thought tocontribute in drought resilience. Selection for root traits is hampered by difficulty in phenotypic mea-surements. Mapping quantitative trait loci (QTLs) for root traits and their use in marker assisted breeding(MAB) will hasten the development of genotypes with improved root system. Consistent QTLs for roottraits have been mapped in rice. Developing and testing near iso-genic lines (NILs) with QTLs for roottraits in target populations of environment (TPE) will help to verify the agronomic value of the QTLs. NILswere developed by introgression of three root QTLs from CT9993, an upland japonica into IR20, a lowlandindica cultivar through MAB. Considerable variation in drought response and grain yield under rainfedcondition in TPE was observed among the NILs. Five out of 41 NILs gave higher yields under rain-fedand irrigated conditions as compared to IR20. Two NILs viz., 212 and 297, with three and two root QTLs,

ear-isogenic linesarker-assisted breeding

PE

respectively had thicker and longer nodal roots and higher total and deep nodal root weights than IR20.In addition, NIL 297 had more nodal root volume and surface area, while NIL 212 had more number ofnodal roots compared to IR20. Further evaluation of the NILs with farmers for yield and grain quality mayhelp in identification of high-yielding, resilient rice suitable for drought-prone rainfed ecosystems. TheNILs may also be useful to study the genes underlying the QTLs and their functions for drought resilience

improvement in rice.

. Introduction

Rice is one of the most important crops for world’s food secu-ity (Lobell et al., 2011). Drought stress is the major abiotic stressimiting rice production (Luo, 2010), especially in rainfed ecosys-ems. Rainfed lowland and upland systems contribute only 21%f the total rice production from more than 38% of the croppedrea (Vikram et al., 2011). Developing cultivars combining droughtesilience and high yield potential will help to increase rice pro-uction in rainfed target population of environments (TPEs). TPE

s the set of all environments, farms and future seasons in whichn improved variety will be grown (IRRI, 2006). In rainfed TPE,he variation in available soil moisture is a major determinant ofrop growth and breeding cultivars with specific adaptation to therevalent water supply is key for yield increase (Fischer et al., 2003).

rought avoidance is considered more relevant for mitigating agri-ultural drought and maintaining crop performance (Serraj et al.,011). Roots are important for maintaining crop yields, especially

∗ Corresponding author. Tel.: +91 422 6611353; fax: +91 422 2431672.E-mail address: chandrarc2000@yahoo.com (R.C. Babu).

1 These authors contributed equally to this work.

378-4290/$ – see front matter © 2012 Elsevier B.V. All rights reserved.ttp://dx.doi.org/10.1016/j.fcr.2012.08.006

© 2012 Elsevier B.V. All rights reserved.

when plants are grown in soils with insufficient water and nutrients(Bengough et al., 2011). Deep and thick roots have been proposed tocontribute in drought resistance (Fukai and Cooper, 1995; Nguyenet al., 1997; Liu et al., 2008; Li et al., 2011) and were shown to havepositive correlations with yield under drought in rice (Babu et al.,2003; Ling et al., 2002; Cairns et al., 2009). Rice has remarkable levelof genetic variation in root morphology (Babu et al., 2001; Lafitteet al., 2001) and can be harnessed for improving rice adaptationto drought (Gowda et al., 2011). However, genetic improvementof root system through conventional breeding is impractical dueto difficulty in phenotyping root traits (Pennisi, 2008). Mappingquantitative trait loci (QTLs) for root traits and their use in markerassisted breeding (MAB) is an alternate approach in selecting forroot traits that are difficult to phenotype (Coudert et al., 2010).

There has been considerable progress in mapping QTLs forroot traits and several of them are consistent across genetic back-grounds and environments in rice (Kamoshita et al., 2008; Courtoiset al., 2009; Khowaja et al., 2009). Introgression of these rootQTLs into elite varieties through MAB may have impact on the

sustainability of rice production in drought-prone rainfed envi-ronments (Venuprasad et al., 2011). Attempts have been made toimprove yield under drought with the introgression of root QTLsinto elite lines through MAB (Shen et al., 2001) and develop a few

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ntrogression lines with improved root phenotype (Steele et al.,006) and yield under rainfed environments (Steele et al., 2007).owever, it is not clear whether the higher yields of the introgres-

ion lines were primarily due to improved root phenotype, sinceertain other lines without the root QTLs also gave higher yieldsnder rainfed conditions (Steele et al., 2007). Small phenotypicffect (some <10%) and large intervals (3.7–7.3 Mb) of the root QTLssed in MAB are more likely to confer linkage drag of unwantedffects (Shen et al., 2001; Steele et al., 2006, 2007). Further, loweritability of certain root traits is also a common breeding con-ern (Gowda et al., 2011). Identifying large effect QTLs with narrowntervals are critical for improving the efficacy of MAB (Berniert al., 2008).

In most rainfed lowland rice growing areas of Asia, the soil den-ity increases under drought leading to soil compaction (Ingramt al., 1994) and root elongation is limited by both water deficitnd mechanical impedance (Bengough et al., 2011). Rice plantsith thicker roots are able to better penetrate hardpans and

ccess soil moisture at depth (Yu et al., 1995). A large effect QTL37.6%) for basal root thickness was detected on chromosome 4n CT9993/IR62266 doubled haploid (DH) rice lines (Zhang et al.,001). The same QTL was also linked to root pulling force in theseH lines (Nguyen et al., 2004). High root pulling force is associatedith ability of the rice plant to develop deep and large diameter

oots with greater penetration ability (Lafitte et al., 2001; Clarkt al., 2008). Root pulling force had positive correlations with plantater status and yield stability under drought in rice (Kumar et al.,

004). The QTLs for basal root thickness and root pulling force onhromosome 4 co-located with QTLs for grain yield under droughttress in these rice DH lines (Babu et al., 2003). QTLs for putativeraits overlapping with QTLs for yield under drought stress are goodandidates for MAB for drought resistance (O’Toole, 2004). The co-ocation of QTLs for putative traits with QTLs for yield provides cluesn the casual relationships (Hochholdinger and Tuberosa, 2009)nd assist breeders in identifying the best QTL alleles for a success-ul MAB program (Landi et al., 2010). A QTL for penetrated roothickness was mapped on chromosome 9 in CT9993/IR62266 DHines (Zhang et al., 2001). These QTLs on chromosomes 4 and 9 wereound to be meta-QTLs (Courtois et al., 2009) and are thought tomprove rice yields under drought through increased water uptakey roots (Kamoshita et al., 2008). Developing and testing NILs forhese QTLs will help to verify their agronomic value and also tonderstand the mechanism of drought resistance in rice.

In the present study, efforts were made to develop NILs for rootrait QTLs using IR20 as recurrent parent. IR20 is drought sensi-ive (Kanbar and Shashidhar, 2011) and has shallow and fine rootystem (Ekanayake et al., 1985). Developing IR20 NILs with rootTLs and evaluating them for drought response in TPE is likely torovide the proof of the concept that improved roots are key com-onents of drought resilience in rice. Thus, the present study wasonducted with the objectives: (i) to develop IR20 NILs by intro-ressing QTLs for root traits from CT9993 using MAB and (ii) tonderstand the agronomic value of the QTLs by evaluating the NILsor drought resistance and root traits under rainfed condition inPE.

. Materials and methods

.1. Parental lines

CT9993-5-10-1-M (abbreviated CT9993), an upland-adapted

ropical japonica ecotype from Columbia was used as a donor.T9993 is drought resistant and known for its deep and thick rootystem, hardpan penetration ability and root proliferation to depthBabu et al., 2001; Kamoshita et al., 2004; Siopongco et al., 2009),

earch 137 (2012) 89–96

but low yielding. IR20, a lowland indica cultivar from Philippineswas used as a recurrent parent. IR20 is drought sensitive (Kanbarand Shashidhar, 2011) and has shallow and thin roots (Ekanayakeet al., 1985). IR20 is grown on considerable area under semi-drycondition in south Tamil Nadu, India representing the rainfed TPEand is preferred by farmers and consumers for its high yield poten-tial and superior grain quality.

2.2. Root QTLs for introgression

QTLs for root traits have been mapped in CT9993/IR62266 riceDH lines (Zhang et al., 2001; Nguyen et al., 2004). Three QTLs onchromosomes 4 and 9 linked to basal root thickness, root pullingforce and penetrated root thickness were chosen for develop-ment of NILs using MAB strategy. The selected QTLs had relativelysmall confidence interval (5.2–9.7 cM; 1.1–3.1 Mb) and large phe-notypic effect, 16.3–37.6% (Table 1). The flanking SSR markers,RM252–RM348 and RM348–RM280 for basal root thickness androot pulling force QTLs on chromosome 4 and RM257–RM242 forpenetrated root thickness QTL on chromosome 9 were used in fore-ground selection of backcross progenies (Table 1). Introgression ofnon target region from the donor parent was prevented throughbackground selection of the genome of the selected backcross prog-enies using SSR markers from rice linkage map (Temnykh et al.,2001)

2.3. Development of IR20 NILs

IR20 (female) was crossed with CT9993 (male) by hand emas-culation and artificial pollination as described by Chaisang et al.(1967). The F1 hybrids were fixed morphologically based on plantheight, tiller number and leaf size at maximum tillering and days toheading. The hybridity was also verified using SSR markers flank-ing the root QTLs. Back crossing was done using true F1 hybrids asmale and IR20 as recurrent female. In the BC1F1 generation, indi-vidual plants that were heterozygous at the loci flanking the rootQTLs were identified through foreground selection. Subsequentback cross was made between the selected BC1F1 hybrids carryingthe root QTLs and recurrent parent to get BC2F1 progenies. Simi-lar strategy was followed to get BC3F1 and BC4F1 progenies (Fig. 1).Two backcross progenies, BC4F1-(2) and BC4F1-(16), with three andtwo root QTLs, respectively were selected. These two BC4F1 proge-nies were generation advanced by selfing and evaluated for droughtresponse, plant production and root traits under rainfed conditionin TPE.

2.4. Genotyping

Leaf samples of F1s, backcross progenies and parents werecollected from field-grown seedlings and freeze dried. DNA wasextracted from the leaf tissues using cetyl trimethyl ammoniumborate buffer (Gawel and Jarret, 1991). The quantity and qualityof DNA was assessed in 0.8% agarose gel and concentration wasadjusted to 50 ng/�l by comparing DNA standards. Polymerasechain reactions (PCR) were performed in a volume of 15 �l in ther-mal cycler (DNA Engine®, Peltier Thermal Cycler, BIO-RAD, USAor Eppendorf Master Cycler Gradient, Eppendorf, Germany). Thereaction mixture contained each primer of 1 �M (Sigma Aldrich,USA), 100 �M deoxy nucleotide, 1× Taq buffer, 0. 02 U Taq poly-merase (Bangalore Genei, India) and 50 ng of template DNA. After5 min at 94 ◦C, the PCR involved 36 cycles of amplification, each

cycle comprising 1 min at 94 ◦C, 1 min at 57 ◦C, 1 min at 72 ◦C andwith a final extension step of 5 min at 72 ◦C. Foreground and back-ground selection for target root QTL regions were made with primeramplicons separated on 3% Metaphor agarose gels (Bio-Whittaker

K.K. Suji et al. / Field Crops Research 137 (2012) 89–96 91

Table 1Root trait QTLs chosen for development of IR20 near isogenic lines (NILs) through marker-assisted breeding.

Trait Chr. Marker interval Physical mapposition (Mbp)a

Length (cM)b LOD R2 (%) Effectc Reference

Basal root thickness 4 RM 252/RG 476–RM 348/RG 939 24.0–31.8 6.1 14.0 37.6 0.12 Zhang et al. (2001)Root pulling force 4 RM 348/RG214–R2017/RM 280 31.8–34.9 9.7 7.98 25.0 14.5 Nguyen et al. (2004)Grain yield under drought 4 RM 252/RG 476–RM 348/RG 939 24.0–31.8 6.1 4.75 15.8 9.9 Babu et al. (2003)Penetrated root thickness 9 RM257–RM242 16.3–17.4 5.2 5.96 16.3 0.09 Zhang et al. (2001)

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a Obtained from indica rice genome sequence information available at Gramene (b Calculated based on CT9993/IR62266 linkage map.c The positive alleles contributed by CT9993, the japonica parent.

olecular Applications, Vallensbaek Strand, Denmark) (Sambrooknd Russell, 2006).

.5. Evaluation of NILs in rain-fed and irrigated environments

Two backcross progenies viz., BC4F1-(2) and BC4F1-(16) withhree and two root QTLs, respectively were evaluated underrrigated condition in experimental fields of Tamil Nadu Agricul-ural University, Coimbatore, India and under rainfed conditionn Agricultural Research Station, Paramakudi, India located in TPETable 2). Briefly, the two backcross progenies viz., BC4F1-(2) andC4F1-(16) were selfed and 25 days old BC4F2 seedlings were trans-lanted along with parents in rows of 1.2 m length unreplicatedith a spacing of 20 cm × 10 cm, between and within rows, respec-

ively under non-stress condition in Trial 1 at Coimbatore (Table 2).ach BC4F2 progeny was observed for IR20 phenotype in terms ofays to heading, plant height, number of tillers and grain size. Those

IR20 x CT9993

F1 x IR20

BC1F1 (234) x IR20

BC2F1 (117) x IR20

BC3F1 (110) x IR20

BC4F1 (16)

BC4F2 (2 & 16)

BC4F3 (2 & 16)

BC4F4 (2)

BC4F5 (2)

Foreground selection

Foreground and background selection

Foreground selection

Foreground selection

Foreground selection

ig. 1. Schematic representation of development of IR20 NILs through markerssisted backcross breeding strategy. The flanking markers used in foreground selec-ion were: RM 252–RM 348 for basal root thickness, RM 348–RM 280 for root pullingorce and RM 242–RM 257 for penetrated root thickness. The numbers in the paren-hesis indicate the number of progenies studied till BC4F1 and progeny numberelected from BC4F2 onwards.

.gramene.org).

BC progenies similar to IR20 phenotype in these traits alone wereselfed and selected for further studies.

Selected BC4F3 lines were tested along with the parents underrainfed condition in Trial 2 at Paramakudi (Table 2). The backcrosslines were sown in dry soil unreplicated in rows of 2.0 m length atthe seed rate of 80 kg ha−1 with a spacing of 20 cm × 10 cm, betweenand within rows, respectively. There was a total of 483 mm rain-fall during the cropping period with a continuous dry spell for 25days during grain filling stage. 41 BC4F3 lines derived from BC4F1-(2) were selected based on days to heading, IR20 plant type, lowdrought score and yield under rainfed condition. All the BC4F3 linesderived from BC4F1-(16) flowered very late and were extremelydrought sensitive, recording higher drought score (data not shown).Hence all the BC lines derived from progeny BC4F1-(16) were notevaluated further.

The 41 BC4F4s were transplanted along with parents, unrepli-cated each in 2 rows of 1.2 m length with a spacing of 20 cm × 10 cm,under non-stress condition in Trial 3 at Coimbatore (Table 2).Genomic DNA was extracted from the 41 BC4F4-(2) entries andamplified using the SSR markers flanking the root QTLs for fore-ground selection.

The same 41 BC4F5 progenies were again tested along with theparents under rainfed condition in Trial 4 at Paramakudi. The back-cross lines were sown in alpha lattice design in 2.0 m × 0.4 m plots,replicated twice with a spacing of 20 cm × 10 cm. There was a totalof 790 mm rainfall during the cropping period with a dry spell for27 days during grain filling stage. In all the trials, fertilization, insectand weed control measures were applied periodically as required.

2.6. Field measurements

Days to 50 per cent flowering was recorded as number of daysfrom sowing to panicle emergence in 50 per cent of plants of eachbackcross entry. At maturity, plant height, number of productivetillers, panicle length and yield per plant were measured from ran-domly selected three plants per backcross entry. All plants withineach plot were harvested to measure grain and straw yields, fromwhich above-ground biomass was determined. Harvest index wasobtained from the ratio of grain weight to the weight of aboveground biomass. Drought score was taken during peak stress inTrial 2 alone using a scale of 1–9 based on intensity of leaf dryingstandardized for rice (IRRI, 1996).

2.7. Evaluation of NILs for root traits

Based on foreground selection for the root QTLs, BC4F4-212 hadthree QTLs for basal root thickness, root pulling force and pene-trated root thickness and BC4F4-297 had two QTLs for basal rootthickness and root pulling force. The two NILs were not positivefor the background markers from CT9993. These two lines were

evaluated for root and yield traits under rainfed condition in Trial5 at Paramakudi (Table 2). Seeds of BC4F5 NILs and parents weresown in dry soil in 2.0 m × 0.4 m size plots. The lines were repli-cated thrice in a randomized complete block design. Since the plant

92 K.K. Suji et al. / Field Crops Res

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growth was poor in this field, 25 days old seedlings were trans-planted to another field and recovered growth. During this croppingperiod, a total rainfall of 790 mm was recorded with a dry spell of27 days during grain filling. At maturity, the experimental plotswere irrigated to field capacity to loosen the soil to excavate rootsfrom individual plants with minimal disturbance. Following day,a 50 cm deep trench was dug up from one side of the experimen-tal plots and slowly proceeded toward the plants to sample theroots apparently intact as much as possible. Data on root traits andyield were collected from three plants per replication. The rootswere cleaned off soil particles with fine jet of water and broughtto lab in poly bags over ice. The nodal roots were dispersed over aflat glass tray for imaging analysis as described by Kato and Okami(2011). Root samples were scanned at 400 dpi on a flatbed imagescanner with a positive film transparency unit (Epson Expression10000XL, Epson America Inc., San Jose, USA). Scanned images wereanalyzed for root traits using WinRhizo v.2009b (Regent Instru-ments, Montreal, Canada) by assigning an equal soil volume of1 cm3 for all the genotypes. Data for maximum root length, nodalroot thickness, total and deep root dry weights were also collected.The maximum root length was measured from collar region to thetip of longest root with a ruler. The thickness of nodal roots (threeroots/plant/replication) at 2 cm below the stem base was measuredthrough an ocularmeter (Champoux et al., 1995) using stage micro-scope (model: CH2Oi BIMF, Olympus, India). Total and deep root dryweights were determined with whole roots and the single longestnodal root, respectively after oven drying at 70 ◦C for two days.

2.8. Statistical analysis

Descriptive statistical analysis was performed using SPSS (v 19)statistical package for various traits measured under rain-fed andnon-stress conditions.

3. Results and discussion

3.1. Development of NILs for root trait QTLs through MABCscheme

Root traits based approach with precise understanding of thetarget environment, including temporal and spatial heterogeneity,is considered a feasible strategy to improve drought resistance inrice (Gowda et al., 2011). QTLs for basal root thickness, root pullingforce and penetrated root thickness from CT9993 are introgressedin to IR20 and NILs for root QTLs were developed using MAB. Pre-vious studies reported that NILs for certain root trait QTLs did nothave desired improvement in root system due to large intervals(some 36.4 cM; 7.3 Mb) and low phenotypic effect (some <10.0 percent) (Shen et al., 2001; Steele et al., 2006). Fine mapped alleles withlarge consistent effects across genetic backgrounds and environ-ments are appropriate targets for MAB (Bernier et al., 2008). In thepresent study, the QTLs selected for development of NILs had rela-tively small confidence intervals and large effect on the root traits(Table 1) and are meta-QTLs (Kamoshita et al., 2008; Courtois et al.,2009). Use of DNA markers flanking the QTLs in backcross greatlyincreases the efficiency and reliability of selection (Collard andMackill, 2008). The early selection of carrier chromosome using SSRmarkers flanking the root QTLs (Table 1) for foreground selection ofbackcross progenies in each backcross generation and at the laterstage of development of NILs (Fig. 1) and the verification of the sta-tus of the non-carrier chromosome through background selection

allowed to monitor the amount and quality of the donor genomethat was retained throughout the backcross program in this study.Among the 234 BC1F1 plants genotyped, only three BC progenieswere heterozygous for the markers flanking the root QTLs and were

K.K. Suji et al. / Field Crops Research 137 (2012) 89–96 93

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root QTLs on chromosome 4 (Table 6). Four BC4F4 progenies (125,172, 182 and 354) were found positive for the QTL on chromosome9 and two BC4F4 progenies (65 and 121) were found positive for QTLfor basal root thickness on chromosome 4 (Supplementary figure).

Table 3Trait mean values of parents and the BC4F3 NILs with yields on par and greater thanIR20 under rainfed condition in Trial 2.

Entry DS DFF PH NPT YPP GY ABM HI

IR20 9 107 73.0 6.0 11.6 3.8 10.6 0.35CT9993 5 113 73.2 4.0 6.6 0.8 2.6 0.29125qtl+ 7 110 76.5 4.7 18.5 4.3 13.2 0.3242 7 110 80.9 5.3 13.1 3.5 12.8 0.2780 9 105 70.4 5.3 11.6 3.4 9.8 0.3559 3 107 80.8 6.7 11.6 3.3 9.6 0.347 9 107 66.8 5.0 22.8 3.3 10.1 0.32297qtl+ 5 107 85.8 6.7 19.6 3.1 11.5 0.27323 5 107 80.8 5.0 13.2 3.1 10.0 0.31359 5 99 75.6 6.3 24.1 3.1 10.8 0.29162 7 110 72.4 6.0 13.6 3.1 10.3 0.30124 9 103 79.5 4.7 18.3 3.1 7.8 0.40137 9 103 71.8 5.3 19.1 3.1 9.6 0.32

Mean 7.3 104.2 74.3 5.4 13.8 2.5 10.8 0.31SD 1.89 4.83 4.50 0.95 4.40 0.6 2.0 0.02

Fig. 2. True BC4F1 progenies of the cross IR20/CT9

urther backcrossed with IR20 and advanced to BC2F1. Low fre-uency of heterozygous genotypes for specific QTL markers waseported in indica/japonica backcross progenies (Taguchi-Shiobarat al., 1997). Among 117 BC2F1 plants, only four BC progenies hadll three root QTLs. These four BC2F1s were also genotyped with aubset of 100 SSR markers that cover the rest of the genome (back-round selection), in order to analyze the allelic composition of thenselected region. As the recovery of the recurrent parent rangedrom 95 to 100 per cent (data not shown), all four BC2F1 proge-ies were further backcrossed with IR20 and advanced to BC3F1.mong 110 BC3F1 plants, two plants – one with three root QTLs onhromosomes 4 and 9 and another with two root QTLs on chromo-ome 4, were detected. Further backcrossing of these two BC3F1sith IR20 produced 16 BC4F1 plants. Foreground selection identi-ed two BC4F1 progenies positive for the root QTLs. Among the two,C4F1-(2) was positive for the three root QTLs on chromosomes 4nd 9 and BC4F1-(16) was positive for two QTLs on chromosome 4Fig. 2). These two BC4F1 progenies were generation advanced andvaluated further.

.2. Evaluation of NILs under rainfed and irrigated environments

Two BC progenies viz., BC4F1-(2) and BC4F1-(16) with three andwo root QTLs, respectively were further evaluated for droughtesponse under rainfed conditions in TPE and for yield potentialnder irrigated (non-stress) conditions. The two progenies wereelfed and the BC4F2 progenies were initially screened and selectedor IR20 phenotype under non-stress condition in Trial 1 (Table 2).60 BC4F3 progenies were tested along with the parents underainfed condition in Trial 2 at TPE (Table 2). Drought stress wasevere with a continuous stress period for 25 days coinciding withrain filling stage. CT9993 had low drought score with more num-er of turgid leaves, while IR20 had high drought score with severe

eaf drying (Table 3). Significant variation in drought score, dayso heading, biomass and yield was observed among the BC4F3rogenies. 41 BC4F3-(2) progenies with IR20 phenotype and bet-er performance under rainfed condition were selected. Among theelected progenies, BC4F3-(2) progeny #125 gave higher yield asompared to IR20 and data for entries with yield on par with IR20re presented (Table 3). The parents and few of the selected NILsere dug out at random to see their root growth in situ under

ainfed condition in TPE. CT9993 and the NILs had deeper rootss compared to IR20 (data not shown), which might have enabledhem to extract water from depth and maintain higher plant watertatus.

However, all lines of BC4F3-(16) flowered late and showedevere leaf drying under rainfed condition and hence were dis-ontinued from further evaluation. Though the NILs were screenedsing 100 SSR markers for background selection, the NILs may still

iffer in genetic background in other regions and this may be a rea-on for late flowering. Late flowering of NILs for root QTLs underainfed condition in TPE was reported earlier in rice (Steele et al.,007). IR64 rice introgression lines also showed wide variation in

R20 for the markers flanking the target root QTLs.

days to heading (Fujita et al., 2011). The 41 BC4F3-(2) lines werefurther generation advanced and evaluated under irrigated (non-stress) condition for phenology and yield traits in Trial 3. The yieldof IR20 was low since few tillers in 2–3 plants were damaged byrodents. Data for the BC4F4 progenies that gave yields higher thanIR20 under non-stress condition are presented (Table 4). The same41 BC progenies were again evaluated under rainfed condition inTrial 4 at TPE. The BC4F5 progenies which gave yields higher thanIR20 under rainfed condition are presented (Table 5).

Among the selected 41 BC progenies, certain entries showedbetter performance compared to IR20 under rainfed and non stressconditions. The backcross progenies, #7, 42, 59, 80, 124, 137, 162,297, 323 and 359 consistently gave yields higher or on par withIR20 under rainfed conditions in TPE across two years. The entries#1, 10, 42, 121, 125, 152, 162, 186, 212, 273, 297, 323, 340 and 359gave higher yields both under rainfed and non-stress conditions,as compared to IR20. The entries, #42, 162, 297, 323 and 359 gaveyields either higher or on par with IR20 across the environments.Similarly, IR64-introgression lines that yielded better under stressdid exhibit a loss in yield potential in favorable environments, butother lines were found to have equal or even better performancethan IR64 in favorable sites (Lafitte et al., 2007).

To monitor the presence of target QTLs segments in theseprogenies which were selected based on their IR20 phenotype,foreground selection was performed in selected BC4F4 entries. Oneprogeny, BC4F4-(212) was positive for all three root QTLs on chro-mosomes 4 and 9 and another, BC4F4-(297) was positive for two

DS, drought score; DFF, days to 50 per cent flowering; PH, plant height (cm);NPT, number of productive tillers; YPP, yield per plant (g); GY, grain yield (t/ha);ABM, above-ground biomass (t/ha); HI, harvest index; SD, standard deviation. ‘qtl+’denotes NILs with root QTLs.

94 K.K. Suji et al. / Field Crops Research 137 (2012) 89–96

Table 4Trait mean values of parents and the BC4F4 NILs with yields greater than IR20 undernon-stress condition in Trial 3.

Entry DFF PH NPT PL YPP GY ABM HI

IR20 101 91.8 13 24.2 35.9 3.9 9.0 0.44CT9993 94 95.3 9 22.8 22.3 2.4 7.2 0.33121qtl+ 87 98.3 14 23.7 40.9 6.9 17.1 0.4042 109 107.7 17 23.3 31.3 6.8 14.1 0.48273 109 112.3 12 22.7 41.1 6.2 14.5 0.43323 107 115.0 11 25.7 35.2 6.1 17.7 0.34186 99 107.0 12 23.0 30.3 5.6 15.8 0.36359 92 100.3 13 23.3 38.8 5.4 13.7 0.39297qtl+ 105 104.7 10 25.7 26.1 4.9 12.5 0.39162 102 101.3 14 24.7 35.3 4.9 11.9 0.4110 97 107.3 11 24.0 24.4 4.7 10.0 0.47260 83 104.7 14 25.0 40.4 4.7 17.1 0.271 104 106.7 10 24.7 42.0 4.6 13.5 0.34340 94 100.7 11 28.0 33.7 4.6 11.7 0.39152 101 103.3 13 22.7 41.3 4.4 14.5 0.30212qtl+ 87 104.0 14 23.7 32.5 4.2 11.2 0.37125qtl+ 96 107.3 12 24.3 38.2 4.0 13.3 0.30

Mean 91.9 102.1 11.8 24.4 31.1 3.6 11.2 0.32SD 8.80 6.52 2.51 1.48 6.67 1.47 3.28 0.08

DFF, days to 50 per cent flowering; PH, plant height (cm); NPT, number of produc-tive tillers; PL, panicle length (cm); YPP, yield per plant (g); GY, grain yield (t/ha);Ad

Tfras

isemtgmwIisNF

hwubrl

Table 5Trait mean values of parents and the BC4F5 NILs with yields greater than IR20 underrainfed condition in Trial 4.

Entry DFF PH NPT GY ABM HI

IR20 105 65.6 7.8 1.9 11.7 0.16CT9993 102 70.5 7.2 1.3 10.3 0.1211 97 87.5 7.0 3.7 14.6 0.2580 88 92.0 4.2 3.6 10.3 0.35124 93 83.4 6.3 3.6 13.6 0.2610 95 86.6 4.5 3.0 10.5 0.28152 103 85.7 5.5 2.9 9.8 0.30121qtl+ 96 81.2 5.2 2.8 10.0 0.287 89 83.9 5.5 2.8 12.4 0.2365qtl+ 96 93.3 6.2 2.8 11.4 0.2583 92 82.2 5.3 2.8 10.0 0.28166 93 77.6 5.7 2.8 10.3 0.271 98 78.5 6.2 2.8 11.2 0.25415 98 81.2 7.5 2.7 11.9 0.2342 96 78.3 5.8 2.7 12.2 0.2259 100 81.8 5.8 2.7 9.4 0.28354qtl+ 91 80.1 7.8 2.7 10.5 0.25365 87 80.9 6.0 2.6 10.0 0.26167 92 76.3 7.2 2.6 10.1 0.26340 104 83.2 5.5 2.5 11.3 0.22404 85 76.8 5.7 2.5 9.7 0.266 91 80.8 5.3 2.5 9.4 0.26172qtl+ 84 73.4 5.3 2.4 10.3 0.24374 91 82.0 6.0 2.3 9.2 0.25323 95 79.7 6.8 2.3 7.3 0.322 100 80.2 7.7 2.2 12.8 0.17137 93 74.1 6.8 2.2 8.9 0.25162 94 81.8 4.7 2.2 6.9 0.32297qtl+ 101 80.7 5.8 2.2 8.9 0.25398 105 80.7 5.3 2.2 10.0 0.23359 99 77.8 5.8 2.1 8.6 0.24233 94 80.6 5.3 2.1 8.5 0.24244 91 80.1 5.8 2.1 8.9 0.23165 87 78.4 5.2 2.0 8.6 0.24186 102 73.3 5.8 2.0 7.8 0.26273 87 78.2 7.3 2.0 10.0 0.20212qtl+ 96 77.5 6.3 1.9 9.3 0.21

Mean 94.4 80.3 6.05 2410.3 9.8 0.25SD 5.33 4.40 0.95 537.12 1.74 0.04

DFF, days to 50 per cent flowering; PH, plant height (cm); NPT, number of productive

TB

BM, above-ground biomass (t/ha); HI, harvest index; SD, standard deviation. ‘qtl+’enotes NILs with root QTLs.

hese eight NILs that differ at one or more QTLs for root traits allowor a more precise assessment of the effects of the individual QTLegions (Landi et al., 2010). The effects of those regions may be seenfter further evaluating the introgression lines for yield and yieldtability under drought stress in TPE.

Rest of the BC4F4 lines did not possess the root QTLs. Loss ofntrogressed QTLs during successive backcrossing and selfing, pos-ibly through double-crossovers between markers was reportedarlier in rice (Shen et al., 2001; Steele et al., 2007). However, theseay have segments of donors in many parts of the genome other

han the target QTLs. Siangliw et al. (2007) reported that the intro-ressed lines with segments of donor other than the target QTLsay contain genes or QTLs that may contribute to tolerance, whichere not targeted during the introgression and selection processes.

ntrogression of Azucena alleles at non target regions significantlymproved both grain and straw yields in Kalinga III rice introgres-ion lines (Steele et al., 2007). Similar variation for other traits in riceILs than for introgressed traits were reported (Ding et al., 2011;ujita et al., 2011).

The ability of rice plants to uptake water from deep soil mayelp to increase yield under drought (Gowda et al., 2011). The NILsith the root QTLs (212, 297, 121 and 125) gave higher yield both

nder rainfed and irrigated conditions as compared to IR20. Theetter performance of these NILs may be due to their improvedoot system, which enabled them to access water from deeperayers to sustain physiological processes under stress and uptake

able 6C4F4 progenies with root trait QTLs identified through foreground selection.

Progeny Chromosome 4

QTL trait: basal root thickness Root p

RM 252 RM348 RM34

65 Yes Yes Yes

121 Yes Yes Yes

125 No No No

172 No No No

182 No No No

212 Yes Yes Yes

297 Yes Yes Yes

354 No No No

tillers; GY, grain yield (t/ha); ABM, above-ground biomass (t/ha); HI, harvest index;SD, standard deviation. ‘qtl+’ denotes NILs with root QTLs.

more water and nutrients under non-stress conditions. The tar-get root QTL on chromosome 9 (RM242–RM201) improved rootlength in rice NILs (Steele et al., 2006). The consensus QTL regionon chromosome 4 (RM252–RM280) influenced root length underwell-watered and water stress conditions (Courtois et al., 2009).In silico analysis with Rice Gene Thresher (Thongjuea et al., 2008)revealed the QTLs on chromosome 4 to contain genes for catalytic

(73 genes; GO: 0003824), ATP binding (27 genes; GO: 0005524),DNA binding (18 genes; GO: 0003677), protein kinase (17 genes;GO: 0004672) and protein tyrosine kinase (15 genes; GO: 0004713)

Chromosome 9

ulling force Penetrated root thickness

8 RM280 RM257 RM242

No No NoNo No NoNo Yes YesNo Yes YesNo Yes YesYes Yes YesYes No NoNo Yes Yes

K.K. Suji et al. / Field Crops Res

Table 7Variation in nodal root traits, yield and biomass production among parents and twoBC4F5 NILs under rainfed condition in Trial 5.

Trait IR20 CT9993 NIL 212 NIL 297 SD

Nodal root length (cm) 301 238 229 172 40.6Surface area (cm2) 571 572 473 782 218.4Nodal root volume (cm3) 89 110 78 284 145.4Nodal root number 2678 3130 3327 2369 677.8Nodal root thickness (�m) 560 937 887 820 47.4Root dry weight (g) 5.4 10.3 6.5 9.0 2.2Length of longest root (cm) 30.2 32.0 31.3 31.9 0.8Deep root dry weight (g) 1.8 3.4 2.2 3.0 0.7Grain yield (t/ha) 0.7 0.8 1.0 0.7 0.2

S

artasFe

3T

ywstThmsuraswrtatdvrtfANlNrewi

pgm6rQer

Above ground biomass (t/ha) 1.8 2.3 2.6 2.6 0.4

D, standard deviation.

ctivities. Similar genes were up/down regulated in a comparativeoot transcriptome analysis between drought tolerant and suscep-ible NILs in rice (Moumeni et al., 2011). The QTL on chromosome 9lso has genes for lateral root growth through ethylene-responsiveynthesis and transport of auxin under stress and genes encoding

box domain proteins (Courtois et al., 2009; Zhao, 2010; Gowdat al., 2011).

.3. Evaluation of NILs for root traits under rainfed condition inPE

To study the effect of the introgressed QTLs on root growth andield, two NILs viz., 212 and 297 (BC4F5) were field sown alongith the parents under rainfed condition in Trial 5 at TPE. Due

low growth of the seedlings in the first field with sandy soil,he seedlings were later replanted to another field with clay soil.hough the plants recovered growth, the replanting shock mayave affected the potential root growth. Further, root growth inajority of field soils, especially in dry soils with increased soil

trength was less than half of the potential growth measured usingnimpeded soils (Valentine et al., 2012). In addition, washing theoots off soil using fine get of water also resulted in loss of finer rootsnd hence all measurements pertain to nodal roots. However, con-iderable variation in growth of nodal roots among parents and NILsas noticed. CT9993 had larger roots than IR20 in terms of nodal

oot number, root volume, root thickness, maximum root length,otal and deep root dry weights, (Table 7). NILs showed consider-ble improvement in root traits as compared to IR20. Both NILs hadhicker and longer nodal roots and higher total and deep nodal rootry weights than IR20. In addition, NIL 297 had more nodal rootolume and surface area, while NIL 212 had more number of nodaloots as compared to IR20 (Table 7). NIL 212 and NIL 297 differ inhat NIL212 has all three root QTLs, while 297 has only two QTLsor basal root thickness and root pulling force on chromosome 4.dditional QTL for penetrated root thickness might have enabledIL 212 penetrate drier soil better to access water from deeper soil

ayers and yield more under stress as compared to NIL 297. RiceILs with QTLs for drought resistance had constitutively deeper

oots and gave higher yields under rainfed conditions (Venuprasadt al., 2011). A QTL for grain yield under drought stress is associatedith increased water uptake through improved root architecture

n rice (Bernier et al., 2009).A prospect for combining drought tolerance with high yield

otential under favorable conditions seems promising, because theenetic correlation between yield in stress and non stress environ-ents is usually positive (Atlin et al., 2004). The BC progenies, 42,

5, 121, 125, 212 and 297 gave higher yields than IR20 both under

ain-fed and irrigated conditions. These NILs had one or more rootTLs introgressed from CT9993 except for line 42 (Table 6). Prog-nies 212 and 297 had improved root traits when tested underainfed conditions in TPE. Developing high yielding rice variety with

earch 137 (2012) 89–96 95

grain quality of consumer preference is critical for wide spreadadoption among rainfed farmers (Boualaphanh et al., 2011). TheNILs have alleles for improved root phenotype from exotic japon-ica ecotype incorporated into locally adapted high yielding indicavariety, IR20 through MAB. Further, the NILs may add to the existinggenetic diversity of rice cultivars in TPE as shown in high altituderice in Nepal (Steele et al., 2009).

4. Conclusion

Three root QTLs from CT9993, a drought tolerant upland japon-ica were introgressed into IR20, a drought sensitive lowland indicacultivar through MAB and NILs with root QTLs were developed. NILswith improved root system and yield under drought in TPE werealso identified. Further testing these NILs with farmers for yieldstability and grain quality may help in identifying high yieldingdrought resilient rice suitable for drought-prone rainfed ecosys-tems. These NILs are ideal genetic material to study the biologicalvalue of the QTLs and underlying genes for rainfed rice improve-ment.

Acknowledgement

The research was supported by the Rockefeller Foundation,USA, Generation Challenge Program, Mexico and Department ofBiotechnology, New Delhi. RCB thanks the anonymous reviewersfor helpful comments on the manuscript.

Appendix A. Supplementary data

Supplementary data associated with this article can be found, inthe online version, at doi:10.1016/j.fcr.2012.08.006.

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