GENOMICS-ASSISTED ALLELE MINING AND ITS INTEGRATION TO BREEDING IN RICE

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1 GENOMICS-ASSISTED ALLELE MINING AND ITS INTEGRATION TO BREEDING IN RICE Masahiro Yano, Yusaku Uga, Shuichi Fukuoka, Kaoru Ebana, Jun-ichi Yonemaru, Toshio Yamamoto AgroGenomics Research Center, National Institute of Agrobiological Sciences, Tsukuba, Japan ABSTRACT Since whole genome sequence of rice has been decoded, it has been more than years. Rice sequence information has contributed on innovation of selection strategy in rice breeding (marker assisted selection) as well as functional analysis of rice genes. Elucidation of the association between nucleotide and phenotypic changes is inevitable to this end and has been a big challenge in molecular genetics and breeding of rice. Toward this goal, we have been involved in the genetic dissection of natural phenotypic variations in rice and have identified several genes involved in complex traits, including heading date, pre-harvest sprouting, root morphology, disease resistance and eating quality. To enhance the power of genetic dissection of complex phenotypes, we are developing several mapping populations, such as recombinant inbred lines and chromosome segment substitution lines, which will allow us to extract the useful alleles from natural variants. Recently, QTL for durable resistance to rice blast has been cloned from Japanese upland rice. This finding has opened new opportunity to introduction of the unique blast resistance gene without a linkage drag of low eating quality. We have also detected a major QTL for deeper rooting on chromosome 9. Based on the MAS, near-isogenic lines of with deeper root has been developed and is now under evaluation of its potential of drought avoidance. To facilitate allele mining using novel plant materials, we have also embarked on the genome-wide discovery of single nucleotide polymorphisms (SNPs). These SNP explore new strategy of genetic and breeding study. We have already revealed genomic sequences of several cultivars to detect SNP and definition of haplotype block of Japanese rice cultivars and high-yielding cultivars for forage use. Currently association between these particular haplotypes and phenotypic performance is investigated. These progresses have gradually acted as a force to change a landscape of selection in rice breeding. KEYWORDS Single nucleotide polymorphism (SNP), marker assisted selection, quantitative trait locus (QTL), mapping population REFERENCES Fukuoka S, N. Saka, H. Koga, T. Shimizu, K. Ebana, N. Hayashi, A. Takahashi, H. Hirochika, K. Okuno and M. Yano, 9: Science. 3, Yamamoto T, H. Nagasaki, J. Yonemaru, K. Ebana, M. Nakajima, T. Shibaya and M. Yano, 1, BMC Genomics. 11:. Nagasaki H, K. Ebana, T. Shibaya, J. Yonemaru and M. Yano, 1, Breed. Sci., : -. Fukuoka S, Y. Nonoue and M. Yano, 1, Breed. Sci., : 9-1. Uga Y, K. Okuno and M. Yano, 11, J. Exp. Bot., : -9. 3

2 JIRCAS International Symposium 11, Tsukuba Trends of International Rice Research and Japanese Scientific Contribution - Support to GRiSP and CARD Whole rice genome has been decoded by International Rice Genome Sequencing Project (IRGSP) Genomics-assisted allele mining and its integration to breeding in rice Nature 3: 3- () Masahiro Yano, Yusaku Uga, Shuichi Fukuoka, Kaworu Ebana, Jun-ichi Yonemaru, Toshio Yamamoto AgroGenomics Research Center, National Institute of Agrobiological Sciences Genes identified in Japanese research activities Genes contribute on improvement of rice cultivars Hd1, Plant Cell () Hd, PNAS (1) Hd3a, PCP () Ehd1, Genes Dev () Ehd, Plant Physiol () Ehd3, Plant J (11) PAIR1, Plant Cell () MEL1, Plant Cell () MSP1, Plant Cell (3) RMS, PNAS (9) Xa1, PNAS (199) Pib, Plant J (1999) OsRac1, PNAS () WRKY Plant Cell () RACK1A,Plant Cell () pi1, Science (9) Spl, PNAS () quvr1, Genetics () OsDREB1A-D, OsDREBA, Plant J (3) POLLUX, CYCLOPS, Plant Cell () Lsi1, Lsi, Nature () () Lsi, Plant Cell () qsw, Nat genet () qsh1, Science () Gn1, Science () qltg3-1, PNAS () Sdr, PNAS (1) SSI, SSIII, Plant Physiol (, ) d1, PNAS (1999) d11, Plant Cell () gid1, Nature () gid, Science (3) OsBRox, Plant Physiol () P, Plant Physiol () LOG, Nature () OsGAox1, Nature Biotech (3) SNORKEL1, SNOKEL, Nature (9) Seed size(gw, GS3, qsw) Seen number (Gn1a) Salinity (SKC1) Shattering (qsh1) Semi dwarf (sd1) Insect resistance (bph11) Low temp. germinability (qltg-3-1) Cool temp. (Ctb1, qct,) Heading date(hd, Hd1, Ghd, DTH(Hd), Ehd1) Seed number (WFP1) : Marker assisted breeding (MAS) has been progressed. : New cultivars has been developed by MAS Deeper rooting (Dro1) Submergence (Sub1A) Insect resistance (Grh, Grh3) Deep water rice (SK1, SK) Blast resistance (pi1, Pb1) Natural variations in rice Drought avoidance using root traits QTL in rice O. sativa japonica indica O. nivara O. rufipogon O. glaberrima O. glumaepatula O. barthii O. meridionalis O. longistaminata Global warming and spreading desertification are causing serious drought damage in rice-growing areas in many developing countries that rely solely on rain to grow rice. Therefore, breeding of drought-resistant lowland rice is becoming an important research topic. Topics Discovery of useful allele and its introduction to elite cultivars (root morphology) Plant materials development for the allele mining Establishment of a platform of genome wide SNP typing for genetic analysis and marker assisted selection A deeper and thicker root system is an important component associated with avoiding drought stress in rice QTL cloning and its utilization may be useful to improve drought avoidance in rice Dry Wet

3 Phenotypic difference between and Kinandang Patong Evaluation system of deeper rooting n = 3 1 Lowland indica µm 1 High yield Shallow root Dro1-1 1 µm Root growth angle Root length Stele size (root thickness) Dro1-1 Photo at DAS Kinandang Patong () Dro1- Dro1-1 Dro1-Hetero 1 Hetero 1 µm upland Tropical Dro1-Hetero 1 japonica 1 1 Hetero Deep root 1 Uga et al. JXB (11) 9S allele at the Dro1 increase deep roots INDEL1 INDEL LOD =.9 R =.% AE = 1.1% 3 Uga et al. JXB (11) Positional cloning of Dro1 (Deeper rooting 1) Fine QTL mapping in mapping in RIL BCF Ratio of deeper roots (%) 1 µm.9. Ave. = 11.% Dro1 INDEL INDEL9 CAPS1 CAPS INDEL INDEL LOD 1 9L Dro1 gene CAPS INDEL1 Ave. =.1% (cm) INDEL1 Dro1 Uga et al. JXB (11) Ratio of deeper rooting (%) Dro1 can reach in deep soil layer without root elongation Survey of diversity in root morphology in rice cm cm Trench method is an appropriate way to directly measure root distribution in the field. cm cm Kinandang Patong

4 well-photosynthesized under drought stress Drought condition Canopy temperature increased fertile seeds under drought condition Dro1 Dro1 Dro1 Dro1 Dro1 Culm length (cm) Panicle length (cm) Shoot biomass (g) Panicle No. Panicle weight (g) Canopy temp. at 13: Difference of canopy temp. of to that of ( ) Days 3日 3 日 日 日 stomatal conductance (mol m- s-1) Stomatal conductance DAS 1DAS photosynthesis rate (μmol m- s-1) Photosynthesis rate DAS 1DAS times Dro1 No. filled-seeds per plant Ongoing research activities on evaluation of performance of draught avoidance by Dro1 Plant materials and their utility in genetic mapping P 1 X P (donor) The International Center for Tropical Agriculture (CIAT) in Colombia Dro1- NIL has been tested under different level of draught stresses using experimental field with rain-out shelter. F 1 F BC 1 F 1 BC F 1 BC 3 F 1 BC F 1 The International Rice Research Institute (IRRI) in Phlippines Dro1- NIL will be tested under lowland condition and multiple locations in IRRI s drought breeding network. Dro1 will be introduced into other mega varieties to study the expression of drought in different genetic backgrounds. F n RIL Potential application BC 1 F n BC F n Primary mapping populations major QTLs genetic interaction BC F n BC F n CSSL / IL BC n F n NIL Advanced mapping populations minor QTLs Validation of major QTLs Substitution mapping BC F 1 Validation of genetic interaction Comparison of alleles among accessions Fine mapping Introgression, elimination of linkage drag Gene pyramiding Muha Naba Nona Bokra Kasalath LAC3 (Africa) Origins and genetic relationship among the donors used to develop CSSLs Deng Pao Zhai Tupa11-3 Khau Mac Kho Bleiyo Bei Khe Silewah Qiu Zhao Zong Khau Nam Jen Hayamasari Owarihatamochi Takanari Habataki Basilanon Kinandang Patong... Coefficient Accessions were selected based on trait of interests Accessions were selected based on sequence variations Acc.No. WRC99 WRC1 WRC9 WRC1 WRC WRC19 Deng Pao Zhai WRC WRC11 WRC1 WRC1 WRC13 Bleiyo WRC3 WRC Bei Khe WRC 3 WRC9 WRC1 WRC Naba WRC WRC WRC9 WRC WRC1 Qiu Zhao Zong WRC1 WRC1 9 WRC Muha WRC3 WRC WRC WRC WRC WRC33 WRC9 WRC WRC3 WRC3 WRC3 Tupa 11-3 WRC3 WRC3 WRC31 WRC3 WRC3 WRC39 Basilanon WRC WRC WRC1 Khano Nam Jen WRC WRC3 WRC 1 WRC Khau Mac Kho WRC WRC WRC WRC WRC1 WRC.9 WRC WRC9 WRC3 WRC Group C (Indica ) Group B (Aus) Group A (Japonica) Mapping populations available for genetic research Distributed from Rice Genome Resource Center (RGRC) at NIAS Cross Pop. structure Recurrent No. lines No of markers /Kasalath 9 /Kasalath CSSL /Kasalath 1 1 /Kasalath CSSL Sasanishiki/Habataki Sasanishiki 3 Sasanishiki/Habataki CSSL Sasanishiki 39 1 Akihikari/ DHL 1 19 /NonaBokra CSSL CSSL CSSL /Jarjan 9 19 /Kinandang Patong RIL : Backcross inbred line, CSSL: Chromosome segment substitution line. DHL:Doubled haploid line, RIL: Recombinant inbred Line

5 Re-sequencing of rice diverse accessions by NGS Asian accessions Temp. and Trop. Japonica Accession Seq(Gb) Seq. depth Method Kasalath 1. x.9 single & pair end Kao Mac Kho 31. x.1 single & pair end Naba 11. x 9.9 single & pair end Tupa x 31. pair end Khao Nam Jen. x 19. pair end Muha.9 x 3. pair end Bei Khe 1. x. pair end Basilanon. x 1. pair end Deng Pao Zhai.3 x 19. pair end Qiu Zao Zhong. x 1. pair end Accession Seq(Gb) Seq. depth Method コシヒカリ. x 1. single end 陸羽 13 号 1. x.9 single end 栄光. x. single end 嘉平.1 x 1. pair end 小白谷. x. pair end 雄町 1. x. pair end 雄町は東京農業大学により解読された情報 Development of platform of SNP analysis in genetic analysis and marker assisted breeding Next generation sequencer SNP typing array For genetically diverse accessions For Japanese cultivars 333 SNPs SNPs 1 SNPs SNPs Identification and utilization of natural variations Mapping populations (F, RILs etc ) using a wide range of natural variants Phenotyping: different methods and conditions More high-throughput and Successive backcrossing reliable CSSL of interests Target QTL Selection marker Nearly isogenic lines Contributors NIAS K. Ebana, K. Matsubara, T. Shibaya, U. Yamanouchi, K. Hori, Y. Uga, S. Yamamoto, S. Fukuoka, R. Mizobuchi, F. Taguchi-Shiobara, T. Yamamoto, J. Yonemaru, K. Sugimoto, J. Wu, K. Kondo, E. Ogiso, S. Marzougui, T. Tanabata, Y. Nonoue, T. Ando, I. Kono, N. Ono, S. Ito, A Shomura, T. Mizubayashi Funding Ministry of Agriculture, Forestry & Fisheries (MAFF), Japan Target QTL Fine mapping and cloning of QTL QTL pyramiding