Abstract
During the last decade, a large number of QTLs and candidate genes for rice tolerance to salinity have been reported. Using 124 SNP and 52 SSR markers, we targeted 14 QTLs and 65 candidate genes for association mapping within the European Rice Core collection (ERCC) comprising 180 japonica accessions. Significant differences in phenotypic response to salinity were observed. Nineteen distinct loci significantly associated with one or more phenotypic response traits were detected. Linkage disequilibrium between these loci was extremely low, indicating a random distribution of favourable alleles in the ERCC. Analysis of the function of these loci indicated that all major tolerance mechanisms were present in the ERCC although the useful level of expression of the different mechanisms was scattered among different accessions. Under moderate salinity stress some accessions achieved the same level of control of Na+ concentration and Na+/K+ equilibrium as the indica reference variety for salinity tolerance Nona Bokra, although without sharing the same alleles at several loci associated with Na+ concentration. This suggests (a) differences between indica and japonica subspecies in the effect of QTLs and genes involved in salinity tolerance and (b) further potential for the improvement of tolerance to salinity above the tolerance level of Nona Bokra, provided the underlying mechanisms are complementary at the whole plant level. No accession carried all favourable alleles, or showed the best phenotypic responses for all traits measured. At least nine accessions were needed to assemble the favourable alleles and all the best phenotypic responses. An effective strategy for the accumulation of the favourable alleles would be marker-assisted population improvement.
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References
Akbar M, Yabuno T, Nakao S (1972) Breeding for saline-resistant varieties of rice. I. Variability for salt tolerance among some rice varieties. Japan J Breed 22:277–284
Ammar MH, Singh RK, Singh AK, Mohapatra T, Sharma TR, Singh NK (2007) Mapping QTLs for salinity tolerance at seedling stage in rice. African Crop Sci Conf Proc 8:617–620
Asch F, Dingkuhn M, Dörffling K, Miezan K (2000) Leaf K/Na ratio predicts salinity induced yield loss in irrigated rice. Euphytica 113:109–118
Berthomieu P, Conéjéro G, Nublat A, Brackenbury W, Lambert C, Savio C, Uozumi N, Oiki S, Yamada K, Cellier F, Gosti F, Simonneau T, Essah P, Tester M, Very AA, Hand-Casse FS (2003) Functional analysis of AtHKT1 in Arabidopsis shows that Na+ recirculation by the phloem is crucial for salt tolerance. EMBO J 22:2004–2014
Bhumbla DR, Abrol IP (1978) Saline and sodic soils. In: Soils and rice. Proceedings of the IRRI symposium on soils and rice. International Rice Research Institute, Manila, Philippines, pp 719–738
Bonilla P, Dvorak J, Mackill D, Deal K, Gregorio G (2002) RFLP and SSLP mapping of salinity tolerance genes in chromosome 1 of rice (Oryza sativa L.) using recombinant inbred lines. Philip Agric Sci 85:68–76
Boonburapong B, Buaboocha T (2007) Genome-wide identification and analyses of the rice calmodulin and related potential calcium sensor proteins. BMC Plant Biol 7:4
Chantereau J (2001) The rice genetic resources at Cirad and the European rice collection. In: Actes du Symposium de Krasnodar “Ressources génétique riz à vocation européenne”, Krasnodar, Russia
Chen F, Li Q, Sun L, He Z (2006) The rice 14-3-3 gene family and its involvement in responses to biotic and abiotic stress. DNA Res 13:53–63
Claes B, Dekeyser R, Villarroel R, Vandenbulcke M, Bauw G, Vanmontagu M, Caplan A (1990) Characterization of a rice gene showing organ-specific expression in response to salt stress and drought. Plant Cell 2:19–27
Clarkson DT, Hanson JB (1980) The mineral-nutrition of higher plants. Annu Rev Plant Physiol Plant Mol Biol 31:239–298
Courtois B, Filloux D, Ahmadi N, Noyer JL, Billot C, Guimaraes EP (2005) Using Molecular markers in rice population improvement through recurrent selection. In: Guimaraes EP (ed) Population improvement: away of exploiting the rice genetic resources of Latin America. FAO, Rome, pp 56–94
Courtois B, Ahmadi N, Khowaja FS, Price AH, Rami J-F, Frouin J, Hamelin C, Ruiz M (2009) Rice root genetic architecture: meta-analysis from a drought QTL database. Rice 2:115–118
Dai X, Xu Y, Ma Q, Xu W, Wang T, Xue Y, Chong K (2007) Overexpression of an R1R2R3 MYB gene, OsMYB3R–2, increases tolerance to freezing, drought, and salt stress in transgenic Arabidopsis. Plant Physiol 143:1739–1751
Dubouzet JG, Sakuma Y, Ito Y, Kasuga M, Dubouzet EG, Miura S, Seki M, Shinozaki K, Yamaguchi-Shinozaki K (2003) OsDREB genes in rice. Oryza sativa L., encode transcription activators that function in drought-, high-salt- and cold-responsive gene expression. Plant J 33:751–763
Evanno G, Regnaut S, Goudet J (2005) Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Mol Ecol 14:2611–2620
Ferrero A (2007) Rice scenario in the European Union. Agricultures 16(4):272–277
Flowers TJ, Yeo AR (1981) Variability in the resistance of sodium chloride salinity within rice (Oryza sativa L.) varieties. New Phytol 81:363–373
Flowers TJ, Koyama ML, Flowers SA, Sudhakar C, Singh KP, Yeo AR (2000) QTL: their place in engineering tolerance of rice to salinity. J Exp Botany 51(342):99–106
Fukuda A, Nakamura A, Tagiri A, Tanaka H, Miyao A, Hirochika H, Tanaka Y (2004) Function, intracellular localization and the importance in salt tolerance of a vacuolar Na(+)/H(+) antiporter from rice. Plant Cell Physiol 45:146–159
Fukuda A, Nakamura A, Hara N, Toki S, Tanaka Y (2010) Molecular and functional analyses of rice NHX-type Na+/H+ antiporter genes. Planta. doi:10.1007/s00425-010-1289-4
Garciadeblas B, Senn ME, Banuelos MA, Rodriguez-Navarro A (2003) Sodium transport and HKT transporters: the rice model. Plant J 34:788–801
Golldack D, Quigley F, Michalowski CB, Kamasani UR, Bohnert HJ (2003) Salinity stress-tolerant and -sensitive rice (Oryza sativa L.) regulate AKT1-type potassium channel transcripts differently. Plant Mol Biol 51:71–81
Greenland DG (1984) Exploited plants: rice. Biologist 31:291–295
Haq TU, Gorham J, Akhtar J, Akhtar N, Steele KA (2010) Dynamic quantitative trait loci for salt stress components on chromosome 1 of rice. Funct Plant Biol 37:634–645
Hillel D, Rosenzweig C (2002) Desertification in relation to climate variability and change. In: Sparks DI (ed) Advances in agronomy, vol 77. Academic Press Inc., San Diego, pp 1–38
Hoagland DR, Arnon DI (1950) The water-culture method for growing plants without soil. Circular 347. The College of Agriculture, University of California, Berkeley
Horie T, Yoshida K, Nakayama H, Yamada K, Oiki S, Shinmyo A (2001) Two types of HKT transporters with different properties of Na+ and K+ transport in Oryza sativa. Plant J 27:129–138
Horie T, Costa A, Kim TH, Han MJ, Horie R, Leung HY, Miyao A, Hirochika H, An G, Schroeder JI (2007) Rice OsHKT2;1 transporter mediates large Na+ influx component into K+-starved roots for growth. Embo J 26:3003–3014
Ismail AM, Heuer S, Thomson MJ, Wissuwa M (2007) Genetic and genomic approaches to develop rice germplasm for problem soils. Plant Mol Biol 65:547–570
Jannink JL, Bink M, Jansen RC (2001) Using complex plant pedigrees to map valuable genes. Trends Plant Sci 6(8):337–342
Jena KK, Mackill DJ (2008) Molecular markers and their use in marker-assisted selection in rice. Crop Sci 48:1266–1276
Khan M, Takasaki H, Komatsu S (2005) Comprehensive phosphoproteome analysis in rice and identification of phosphoproteins responsive to different hormones/stresses. J Proteom Res 4:1592–1599
Kim BG, Waadt R, Cheong YH, Pandey GK, Dominguez-Solis JR, Schultke S, Lee SC, Kudla J, Luan S (2007) The calcium sensor CBL10 mediates salt tolerance by regulating ion homeostasis in Arabidopsis. Plant J 52:473–484
Kim DM, Ju HG, Kwon TR, Oh CS, Ahn SN (2009) Mapping QTLs for salt tolerance in an introgression line population between japonica cultivars in rice. J Crop Sci Biotech 12:121–128
Koyama ML, Levesley A, Koebner RMD, Flowers TJ, Yeo AR (2001) Quantitative trait loci for component physiological traits determining salt tolerance in rice. Plant Physiol 125:406–422
Koh S, Lee SC, Kim MK, Koh JH, Lee S, An G, Choe S, Kim SR (2007) T-DNA tagged knockout mutation of rice OsGSK1, an orthologue of Arabidopsis BIN2, with enhanced tolerance to various abiotic stresses. Plant Mol Biol 65:453–466
Kumari S, Panjabi V, Kushwaha H, Sopory S, Singla-Pareek S, Pareek A (2009) Transcriptome map for seedling stage specific salinity stress response indicates a specific set of genes as candidate for saline tolerance in Oryza sativa L. Funct Integ Genom 9(1):109–123
Lang NT, Buu BC, Ismail A (2008) Molecular mapping and marker-assisted selection for salt tolerance in rice. Omonrice 16:50–56
Lee SY, Ahn JH, Cha YS, Yun DW, Lee MC, Ko JC, Lee KS, Eun MY (2007) Mapping QTLs related to salinity tolerance of rice at the young seedling stage. Plant Breed 126:43–46
Le Quang H, Brasileiro ACM, Severac D, Aknin C, Guiderdoni E, Perin C (2008) Identification des gènes impliqués dans la tolérance du riz à la salinité par l’approche SSH-microarray. In: Biotechnologies végétales et gestion durable des résistances face à des stress biotiques et abiotiques chez les plantes/Biotechnologies, 30 juin au 3 juillet 2008, Rennes. P-117
Lin HX, Zhu MZ, Yano M, Gao JP, Liang ZW, Su WA, Hu XH, Ren ZH, Chao DY (2004) QTL for Na+ and K+ uptake of the shoots and roots controlling rice salt tolerance. Theor Appl Genet 108:253–260
Liu J, Ishitani M, Halfter U, Kim C, Zhu JK (2000) The Arabidopsis thaliana SOS2 gene encodes a protein kinase that is required for salt tolerance. PNAS 97(7):3730–3734
Liu JG, Zhang Z, Qin QL, Peng RH, Xiong AS, Chen JM, Xu F, Zhu H, Yao QH (2007) Isolated and characterization of a cDNA encoding ethylene-responsive element binding protein (EREBP)/AP2-type protein, RCBF2, in Oryza sativa L. Biotechnol Lett 29:165–173
Lynch M, Ritland K (1999) Estimation of relatedness with molecular markers. Genetics 152:1753–1766
Mackill DJ (2007) Molecular markers and marker-assisted selection in rice. In: Varshney RK, Tuberosa R (eds) Genomics assisted crop improvement. Vol 2. Genomics applications in crops. Springer, New York, pp 147–168
Mackay I, Powell W (2006) Methods for linkage disequilibrium mapping in crops. Trends Plant Sci 12(2):57–63
Martinez-Atienza J, Jiang X, Garciadeblas B, Mendoza I, Zhu JK, Pardo JM, Quintero FJ (2007) Conservation of the salt overly sensitive pathway in rice. Plant Physiol 143:1001–1012
Mather KA, Caicedo AL, Polato NR, Olsen KM, McCouch S, Purugganan MD (2007) The extent of linkage disequilibrium in rice (Oryza sativa L.). Genetics 177:2223–2232
Matsukura S, Mizoi J, Yoshida T, Todaka D, Ito Y, Maruyama K, Shinozaki K, Yamaguchi-Shinozaki K (2010) Comprehensive analysis of rice DREB2-type genes that encode transcription factors involved in the expression of abiotic stress-responsive genes. Mol Genet Genom 283:185–196
Mie K, Liu Q, Miura S, Shinozaki KY, Shinozaki K (1999) Improving plant drought, salt, and freezing tolerance by gene transfer of a single stress-inducible transcription factor. Nat Biotech 17:287–291
Moradi F, Ismail AM, Gregorio GB, Egdane JA (2003) Salinity tolerance of rice during reproductive development and association with tolerance at the seedling stage. Indian J Plant Physiol 8:276–287
Moradi F, Ismail AM (2007) Responses of photosynthesis, chlorophyll fluorescence and ROS scavenging system to salt stress during seedling and reproductive stages in rice. Ann Bot 99:1161–1173
Munns R, James RA, Laüchli A (2006) Approaches to increasing the salt tolerance of wheat and other cereals. J Exp Bot 57:1025–1043
Munns R, Tester M (2008) Mechanisms of salinity tolerance. Annu Rev Plant Biol 59:651–681
Negrão S, Courtois B, Ahmadi N, Abreu I, Saibo N, Oliveira MM (2011) Recent updates on salinity stress in rice: from physiological to molecular responses. Crit Rev Plant Sci (in press)
Oka HI (1983) The indica-japonica differentiation of rice cultivars. A review. In: Proceedings of the 4th international SABRAO congress, pp 117–128
Okada T, Nakayama H, Shinmyo A, Yoshida K (2008) Expression of OsHAK genes encoding potassium ion transporters in rice. Plant Biotech 25:241–245
Prasad SR, Bagali PG, Hittalmani S, Shashidhar SE (1999) Molecular mapping of quantitative trait loci associated with seedling tolerance of salt stress in rice. Curr Sci 78:162–164
Pritchard JK, Stephens M, Donnelly P (2000) Inference of population structure using multilocus genotype data. Genetics 155:945–959
Ren ZH, Gao JP, Li LG, Cai XL, Huang W, Chao DY, Zhu MZ, Wang ZY, Luan S, Lin HX (2005) A rice quantitative trait locus for salt tolerance encodes a sodium transporter. Nat Genet 37(10):1141–1146
Risch N, Merikangas K (1996) The future of genetic studies of complex human diseases. Science 273:1516–1517
Risterucci AM, Grivet L, N’Goran JAK, Pieretti I, Flament MH, Lanaud C (2000) A high-density linkage map of Theobroma cacao L. Theor Appl Genet 101:948–955
Rus A, Lee BH, Munoz-Mayor A, Sharkhuu A, Miura K, Zhu JK, Bressan RA, Hasegawa PM (2004) AtHKT1 facilitates Na+ homeostasis and K+ nutrition in planta. Plant Physiol 136:2500–2511
Sabouri H, Rezai AM, Moumeni A, Kavousi A, Katouzi M, Sabouri A (2009) QTLs mapping of physiological traits related to salt tolerance in young rice seedlings. Biol Plantarum 53:657–662
Sahi C, Singh A, Kumar K, Blumwald E, Grover A (2006) Salt stress response in rice: genetics, molecular biology, and comparative genomics. Funct Integr Genom 6:263–284
Senadheera P, Singh RK, Maathuis FJM (2009) Differentially expressed membrane transporters in rice roots may contribute to cultivar dependent salt tolerance. J Exp Bot 60(9):2553–2563
Takehisa H, Shimodate T, Fukuta Y, Ueda T, Yano M, Ymaya T, Kameya T, Sato (2004) Identification of quantitative trait loci for plant growth of rice in paddy field flooded with salt water. Field Crop Res 89:85–95
Thomson M, de Ocampo M, Egdane J, Rahman M, Sajise A, Adorada D, Tumimbang-Raiz E, Blumwald E, Seraj Z, Singh R, Gregorio G, Ismail A (2010) Characterizing the Saltol quantitative trait locus for salinity tolerance in rice. Rice 3:148–160
Uozumi N, Kim EJ, Rubio F, Yamaguchi T, Muto S, Tsuboi A, Bakker EP, Nakamura T, Schroeder JI (2000) The Arabidopsis HKT1 gene homolog mediates inward Na+ currents in Xenopus laevis oocytes and Na+ uptake in Saccharomyces cerevisiae. Plant Physiol. 122:1249–1259
Walia H, Wilson C, Condamine P, Liu X, Ismail AM, Zeng LH, Wanamaker SI, Mandal J, Xu J, Cui XP, Close TJ (2005) Comparative transcriptional profiling of two contrasting rice genotypes under salinity stress during the vegetative growth stage. Plant Physiol 139:822–835
Walia H, Wilson C, Zeng L, Ismail AM, Condamine P, Close TJ (2007) Genome-wide transcriptional analysis of salinity stressed japonica and indica rice genotypes during panicle initiation stage. Plant Mol Biol 63:609–623
Wan B, Lin Y, Mou T (2007) Expression of rice Ca(2+)-dependent protein kinases (CDPKs) genes under different environmental stresses. FEBS Lett 581:1179–1189
Wang XS, Zhu HB, Jin GL, Liu HL, Wu WR, Zhu J (2007) Genome-scale identification and analysis of LEA genes in rice (Oryza sativa L.). Plant Sci 172:414–420
Wassmann R, Hien NX, Hoan CT, Tuong TP (2004) Sea level rise affecting the Vietnamese Mekong Delta: water elevation in the flood season and implications for rice production. Climate Change 66:89–107
Yamaguchi-Shinozaki K, Shinozaki K (1994) A novel cis-acting element in an Arabidopsis gene is involved in responsiveness to drought, low-temperature or high-salt stress. Plant Cell 6:251–264
Yeo AR, Flowers TJ (1986) Salinity resistance in rice (Oryza sativa L.) and a pyramiding approach to breeding varieties for saline soils. Aust J Plant Physiol 13:161–173
Yeo AR, Yeo ME, Flowers SA, Flowers TJ (1990) Screening rice (Oryza sativa L.) genotypes for physiological characters contributing to salinity tolerance and their relationship to overall performance. Theor Appl Genet 79:377–384
Yeo AR (1998) Molecular biology of salt tolerance in the context of whole-plant physiology. J Exp Bot 49:915–929
Yu J, Pressoir G, Briggs WH, Vroh Bi I, Yamasaki M, Doebley JF, McMullen MD, Gaut BS, Nielsen DM, Holland JB, Kresovich S, Buckler ES (2006) A unified mixed-model method for association mapping that accounts for multiple levels of relatedness. Nat Genet 38(2):203–208
Zeng LH, Shannon MC (2000) Salinity effects on seedling growth and yield components of rice. Crop Sci 40:996–1003
Zhao K, Aranzana MJ, Kim S, Lister C, Shindo C, Tang C, Toomajian C, Zheng H, Dean C, Marjoram P, Nordborg P (2007) An Arabidopsis example of association mapping in structured samples. PLoS Genet 3(1):71–82
Zhu C, Gore M, Buckler ES, Yu J (2008) Status and prospects of association mapping in plants. Plant Genom 1:5–20
Acknowledgments
This research was implemented in the framework of EURIGEN project funded by European Commission—DG Agriculture and Rural Development within the AGRI GEN RES program. Sónia Negrão also thanks FCT-Portugal for the Post-Doc fellowship SFRH/BPD/34593/2007.
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Table S1
: List of accessions of the European Rice Core Collection (ERCC) and their country of origin. (XLSX 44 kb)
Table S2
: List and characteristics of the 124 SNP markers targeting 47 candidate genes for salt tolerance, and list of SNPs significantly associated with tolerance to salinity. (PDF 83 kb)
Table S3
: List and characteristics of the 52 polymorphic SSRs targeting 18 candidate genes and 14 QTLs for salinity tolerance, and list of SSRs significantly associated with tolerance to salinity. (PDF 70 kb)
Table S4
: Response to salinity stress of the 200 accessions of the European Rice Core Collection. Experiment 1: SIS: salinity injury score; LCC_r: leaf chlorophyll content response; SDW16_r: shoot dry weight response at 16 days after sowing. Experiment 2: PH_r: plant height response; TN_r: tiller number response; LN_r: leaf number response; MRL_r: maximum root length response; RDW_r: root dry weight response; SDW_r: shoot dry weight response; K + and N + : leaf concentration of K + and N + ; PCA_1, PCA_2 and PCA_3: coordinates on the first, second and third axes of the Principal Component Analysis; HAC: Class of hierarchical ascendant classification.(PDF 83 kb)
Table S5
: Results of targeted association analysis using three different models: General Linear Model (GLM_Q), Mixed Linear Model (MLM_ K) and Mixed Linear Model (MLM_K + Q), with K kinship matrix and Q population membership matrix. PH_r: plant height response; TN_r: tiller number response; LN_r: leaf number response; MRL_r: maximum root length response; RDW_r: root dry weight response; SDW_r: shoot dry weight response; K+ and N+: leaf concentration of K+ and N+; PCA_1, PCA_2 and PCA_3: coordinates on the first, second and third axes of the Principal Component Analysis; HAC: Class of hierarchical ascendant classification, SIS: salt injury score. (PDF 68 kb)
Figure S1:
Location on the rice chromosomes of the candidate genes, molecular markers and QTLs for salinity tolerance. Positions are in Mb. Genes with validated function in rice are in yellow boxes. Other genes are in black. Molecular markers linked with QTLs are in black. Molecular markers genotyped in this study are in blue. Those for which significant associations were detected are in red. QTLs for K related traits are in red; QTL for Na related traits are in blue; QTLs for Na/K ratio are in violet; QTLs for relative traits (saline versus control conditions) are in grey. QTLs related to salt injury and salt tolerance are in green. For each QTL, the triangle area is proportional to the percentage of variance explained by the QTL. The QTL numbers correspond to their ID in the QTL module of TropgeneDB (http://tropgenedb.cirad.fr/html/rice_QTL.html) where additional details on the QTLs can be found. DSD: Days from Seedling to Death; KCR: K+ Concentration in Roots; KCS: K+ Concentration in Shoots; KQR: K+ Quantity in Roots; KUP: K+ Uptake; NA +/K + : Na+/K+ Ratio; NCR: Na+ Concentration in Roots; NCS: Na+ Concentration in Shoots; NQR: Na+ Quantity in Roots; NQS: Na+ Quantity in Shoots; NUP: Na+ Uptake; RBM: Relative Biomass; RDW: Relative Dry Weight; RFW: Relative Fresh Weight; RGRM: Relative Seed Germination; RLA: Relative Leaf Area; RSH: Relative Seedling Height; RSL: Relative Shoot Length; RSRL: Relative Seminal Root Length; RSV: Relative Seedling Vigor; RSVG: Relative Seedling Vigor; RTN: Relative Tiller Number; SI: Salt Injury; STOL: Salt Tolerance. Most of the information is extracted from Negrao et al (2011). (PDF 375 kb)
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Ahmadi, N., Negrão, S., Katsantonis, D. et al. Targeted association analysis identified japonica rice varieties achieving Na+/K+ homeostasis without the allelic make-up of the salt tolerant indica variety Nona Bokra. Theor Appl Genet 123, 881–895 (2011). https://doi.org/10.1007/s00122-011-1634-4
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DOI: https://doi.org/10.1007/s00122-011-1634-4