Skip to main content
Log in

Genetic dissection of grain traits in Yamadanishiki, an excellent sake-brewing rice cultivar

  • Original Article
  • Published:
Theoretical and Applied Genetics Aims and scope Submit manuscript

Abstract

Key message

The grain traits of Yamadanishiki, an excellent sake-brewing rice cultivar in Japan, are governed by multiple QTLs, namely, a total of 42 QTLs including six major QTLs.

Abstract

Japanese rice wine (sake) is produced using brewing rice (Oryza sativa L.) that carries traits desirable for sake-brewing, such as a larger grain size and higher white-core expression rate (WCE) compared to cooking rice cultivars. However, the genetic basis for these traits in brewing rice cultivars is still unclear. We performed analyses of quantitative trait locus (QTL) of grain and days to heading over 3 years on populations derived from crosses between Koshihikari, a cooking rice, and Yamadanishiki, an excellent sake-brewing rice. A total of 42 QTLs were detected for the grain traits, and the Yamadanishiki alleles at 16 QTLs contributed to larger grain size. Two major QTLs essential for regulating both 100-grain weight (GWt) and grain width (GWh) were harbored in the same regions on chromosomes 5 and 10. An interaction was noted between the environment and the QTL associated with WCE on chromosome 6, which was detected in two of 3 years. In addition, two QTLs for WCE on chromosomes 3 and 10 overlapped with the QTLs for GWt and GWh, suggesting that QTLs associated with grain size also play an important role in the formation of white-core. Despite differences in the rate of grain growth in both Koshihikari and Yamadanishiki across 2 years, the WCE in Yamadanishiki remained consistent, thus demonstrating that the formation of white-core does not depend on grain filling speed. These data can be informative for programs involved in breeding better cooking and brewing rice cultivars.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  • Ando T, Ichikawa K (1974) An examination of the endosperm structure of rice grain with a transmission and a scanning electron microscope. J Ferment Technol 52:46–57 (in Japanese)

    Google Scholar 

  • Aramaki K, Ogawa K, Yamamoto K, Suzuki J, Kanno M, Kizaki Y, Okazaki N (1995) Polishing properties of white-core and non-white-core grains fractionated from the same variety of rice. Seibutsu-kogaku 73:381–386 (in Japanese)

    CAS  Google Scholar 

  • Arcade A, Labourdette A, Falque M, Mangin B, Chardon F, Charcosset A, Joets J (2004) BioMercator: integrating genetic maps and QTL towards discovery of candidate genes. Bioinformatics 20:2324–2326

    Article  PubMed  CAS  Google Scholar 

  • Bai XF, Luo LJ, Yan WH, Kovi MR, Xing YZ (2011) Quantitative trait loci for rice yield-related traits using recombinant inbred lines derived from two diverse cultivars. J Genet 90:209–215

    Article  PubMed  CAS  Google Scholar 

  • Churchill GA, Doerge RW (1994) Empirical threshold values for quantitative trait mapping. Genetics 138:963–971

    PubMed  PubMed Central  CAS  Google Scholar 

  • Fitzgerald MA, McCouch SR, Hall RD (2008) Not just a grain of rice: the quest for quality. Trends Plant Sci 14:133–139

    Article  CAS  Google Scholar 

  • Fujita N, Yoshida M, Kondo T, Saito K, Utsumi Y, Tokunaga T, Nishi A, Satoh H, Park JH, Jane JL, Miyao A, Hirochika H, Nakamura Y (2007) Characterization of SSIIIa-deficient mutants of rice: the function of SSIIIa and pleiotropic effects by SSIIIa deficiency in the rice endosperm. Plant Physiol 144:2009–2023

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Hamajima N, Saito T, Matsuo K, Kozaki K, Takahashi T, Tajima K (2000) Polymerase chain reaction with confronting two-pair primers for polymorphism genotyping. Jpn J Cancer Res 91:865–868

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • He P, Li SG, Qian Q, Ma YQ, Li JZ, Wang WM, Chen Y, Zhu LH (1999) Genetic analysis of rice grain quality. Theor Appl Genet 98:502–508

    Article  CAS  Google Scholar 

  • Higuchi K, Ikegami M, Seko H, Aramaki I, Samuta T (1998) Carbohydrate metabolism at early stage of endosperm development of brewers’ rice cultivars. Kinki J Crop Sci Breed 43:45–47 (in Japanese)

    Google Scholar 

  • Hirose T, Scofield GN, Terao T (2008) An expression analysis profile for the entire sucrose synthase gene family in rice. Plant Sci 174:534–543

    Article  CAS  Google Scholar 

  • Hori K, Kataoka T, Miura K, Yamaguchi M, Saka N, Nakahara T, Sunohara Y, Ebana K, Yano M (2012) Variation in heading date conceals quantitative trait loci for other traits of importance in breeding selection of rice. Breed Sci 62:223–234

    Article  PubMed  PubMed Central  Google Scholar 

  • Hori K, Ogiso-Tanaka E, Matsubara K, Yamanouchi U, Ebana K, Yano M (2013) Hd16, a gene for casein kinase I, is involved in the control of rice flowering time by modulating the day-length response. Plant J 76:36–46

    PubMed  PubMed Central  CAS  Google Scholar 

  • Horigane KA, Suzuki K, Yoshida M (2014) Moisture distribution in rice grains used for sake brewing analyzed by magnetic resonance imaging. J Cereal Sci 60:193–201

    Article  CAS  Google Scholar 

  • Huang N, Parco A, Mew T, Magpantay G, McCouch S, Guiderdoni E, Xu J, Subudhi P, Angeles ER, Khush GS (1997) RFLP mapping of isozymes, RAPD and QTLs for grain shape, brown planthopper resistance in a doubled haploid rice population. Mol Breed 3:105–113

    Article  CAS  Google Scholar 

  • Huang R, Jiang L, Zheng J, Wang T, Wang H, Huang Y, Hong Z (2013) Genetic bases of rice grain shape: so many genes, so little known. Trends Plant Sci 18:218–226

    Article  PubMed  CAS  Google Scholar 

  • Ikegami M, Seko H (1995) Varietal difference of white-core expression in rice for sake brewery. Rep Soc Crop Sci Breed Kinki 40:47–51 (in Japanese)

    Google Scholar 

  • Ishii K, Oba K, Maruyyama A, Katano M (2008) Effect of high temperature at grain filling period in TGC on grain texture of brewers’ rice “Yamada-nishiki”. Rep Kyushu Br Crop Sci Soc Japan 74:24–26 (in Japanese)

    Google Scholar 

  • Ishimaru K, Ujiie K (2014) Identification of genes for rice grain size their function. Jpn J Crop Sci 83:299–304 (in Japanese)

    Article  CAS  Google Scholar 

  • Ishimaru K, Hirotsu N, Madoka Y, Murakami N, Hara N, Onodera H, Kashiwagi T, Ujiie K, Shimizu B, Onishi A, Miyagawa H, Katoh E (2013) Loss of function of the IAA-glucose hydrolase gene TGW6 enhances rice grain weight and increases yield. Nat Genet 45:707–711

    Article  PubMed  CAS  Google Scholar 

  • Kamijima O, Takaya N (1984) Relationships between kernel weight and occurrence of white-core in kernel of rice. Sci Rep Fac Agric Kobe Univ 16:19–25 (in Japanese)

    Google Scholar 

  • Kobayashi A, Genliang B, Shenghai Y, Tomita K (2007) Detection of quantitative trait loci for white-back and basal-white kernels under high temperature stress in japonica rice varieties. Breed Sci 57:107–116

    Article  Google Scholar 

  • Kobayashi A, Sonoda J, Sugimoto K, Kondo M, Iwasawa N, Hayashi T, Tomita K, Yano M, Shimizu T (2013) Detection and verification of QTLs associated with heat-induced quality decline of rice (Oryza sativa L.) using recombinant inbred lines and near-isogenic lines. Breed Sci 63:339–346

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Kosambi DD (1944) The estimation of map distances from recombination values. Ann Eugen 12:172–175

    Article  Google Scholar 

  • Lander ES, Green P, Abrahamson J, Barlow A, Daly MJ, Lincoln SE, Newburg L (1987) MAPMAKER: an interactive computer package for constructing primary genetic linkage maps of experimental and natural populations. Genomics 1:174–181

    Article  PubMed  CAS  Google Scholar 

  • Li Y, Fan C, Xing Y, Jiang Y, Lno L, Sun L, Shao D, Xu C, Li X, Xiao J, He Y, Zhang Q (2011) Natural variation in GS5 plays an important role in regulating grain size and yield in rice. Nat Genet 43:1266–1269

    Article  PubMed  CAS  Google Scholar 

  • Li Y, Fan C, Xing Y, Yun P, Luo L, Yan B, Peng B, Xie W, Wang G, Li X, Xiao J, Xu C, He Y (2014) Chalk5 encodes a vacuolar H+-translocating pyrophosphatase influencing grain chalkiness in rice. Nat Genet 46:398–404

    Article  PubMed  CAS  Google Scholar 

  • Matsubara K, Kono I, Hori K, Nonoue Y, Ono N, Shomura A, Mizubayashi T, Yamamoto S, Yamanouchi U, Shirasawa K, Nishio T, Yano M (2008) Novel QTLs for photoperiodic flowering revealed by using reciprocal backcross inbred lines from crosses between japonica rice cultivars. Theor Appl Genet 117:935–945

    Article  PubMed  CAS  Google Scholar 

  • Matsubara K, Ogiso-Tanaka E, Hori K, Ebana K, Ando T, Yano M (2012) Natural variation in Hd17, a homolog of Arabidopsis ELF3 that is involved in rice photoperiodic flowering. Plant Cell Physiol 53:709–716

    Article  PubMed  CAS  Google Scholar 

  • McCouch SR, Cho YG, Yano M, Paul E, Blinstrub M, Morishima H, Kinoshita T (1997) Report on QTL nomenclature. Rice Genet Newsl 14:11–131

    Google Scholar 

  • Murray MG, Thompson WF (1980) Rapid isolation of high molecular weight plant DNA. Nucleic Acids Res 8:4321–4325

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Nagasaki H, Ebana K, Shibaya T, Yonemaru J, Yano M (2010) Core single-nucleotide polymorphisms—a tool for genetic analysis of the Japanese rice population. Breed Sci 60:648–655

    Article  Google Scholar 

  • Nagata K, Ando T, Nonoue Y, Mizubayashi T, Kitazawa N, Shomura A, Matsubara K, Ono N, Mizobuchi R, Shibaya T, Ogiso-Tanaka E, Hori K, Yano M, Fukuoka S (2015) Advanced backcross QTL analysis reveals complicated genetic control of rice grain shape in a japonica × indica cross. Breed Sci 65:308–318

    Article  PubMed  PubMed Central  Google Scholar 

  • Nagato K, Ebata M (1958) Studies on white-core rice kernel I. On the occurrence of white core. Jpn J Crop Sci 27:49–51 (in Japanese)

    Article  Google Scholar 

  • Nagato K, Ebata M (1959) Studies on white-core rice kernel II. On the physical properties of the kernel. Jpn J Crop Sci 28:46–50 (in Japanese)

    Article  Google Scholar 

  • Nagato K, Kobayashi Y (1959) On varietal differences in the tissue of starch-cell of rice kernels. Jpn J Crop Sci 27:443–445 (in Japanese)

    Article  Google Scholar 

  • National tax agency in Japan (2016) Sake report. https://www.nta.go.jp/shiraberu/senmonjoho/sake/shiori-gaikyo/shiori/2016/pdf/000.pdf (in Japanese)

  • Nishi A, Nakamura Y, Tanaka N, Satoh H (2001) Biochemical and genetic analysis of the effects of Amylose-extender mutation in rice endosperm. Plant Physiol 127:459–472

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Nyquist WE (1991) Estimation of heritability and prediction of selection response in plant populations. Crit Rev Plant Sci 10:235–322

    Article  Google Scholar 

  • Peng B, Wang L, Fan C, Jiang G, Luo L, Li Y, He Y (2014) Comparative mapping of chalkiness components in rice using five populations across two environments. BMC Genet 15:49

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Qin Y, Kim S, Sohn J (2009) Genetic analysis and QTL mapping for grain chalkiness characteristics of brown rice (Oryza sativa L). Genes Genom 31:155–164

    Article  Google Scholar 

  • Qiu X, Chen K, Lv W, Ou X, Zhu Y, Xing D, Yang L, Fan F, Yang L, Xu J, Zheng T, Li Z (2017) Examining two sets of introgression lines reveals background-independent and stably expressed QTL that improve grain appearance quality in rice (Oryza sativa L.). Theor Appl Genet 130:951–967

    Article  PubMed  PubMed Central  Google Scholar 

  • Shibaya T, Hori K, Ogiso-Tanaka E, Yamanouchi U, Shu K, Kitazawa N, Shomura A, Ando T, Ebana K, Wu J, Yamazaki T, Yano M (2016) Hd18, encoding histone acetylase related to Arabidopsis FLOWERING LOCUS D, is involved in the control of flowering time in rice. Plant Cell Physiol 57:1828–1828

    Article  PubMed  CAS  Google Scholar 

  • Shomura A, Izawa T, Ebana K, Ebitani T, Kanegae H, Konishi S, Yano M (2008) Deletion in a gene associated with grain size increased yields during rice domestication. Nat Genet 40:1023–1028

    Article  PubMed  CAS  Google Scholar 

  • Song XJ, Huang W, Shi M, Zhu MZ, Lin HX (2007) A QTL for rice grain width and weight encodes a previously unknown RING-type E3 ubiquitin ligase. Nat Genet 39:623–630

    Article  PubMed  CAS  Google Scholar 

  • Song XJ, Kuroha T, Ayano M, Furuta T, Nagai K, Komeda N, Segami S, Miura K, Ogawa D, Kamura T, Suzuki T, Higashiyama T, Yamasaki M, Mori H, Inukai Y, Wu J, Kitano H, Sakakibara H, Jacobsen SE, Ashikari M (2015) Rare allele of a previously unidentified histone H4 acetyltransferase enhances grain weight, yield, and plant biomass in rice. Proc Natl Acad Sci USA 112:76–81

    Article  PubMed  CAS  Google Scholar 

  • Takahashi Y, Shomura A, Sasaki T, Yano M (2001) Hd6, a rice quantitative trait locus involved in photoperiod sensitivity, encodes the α subunit of protein kinase CK2. Proc Natl Acad Sci USA 98:7922–7927

    Article  PubMed  CAS  Google Scholar 

  • Tan YF, Xing YZ, Li JX, Yu SB, Xu CG, Zhang Q (2000) Genetic bases of appearance quality of rice grains in Shanyou 63, an elite rice hybrid. Theor Appl Genet 101:823–829

    Article  CAS  Google Scholar 

  • Tanabata T, Shibaya T, Hori K, Ebana K, Yano M (2012) SmartGrain: high-throughput phenotyping software for measuring seed shape through image analysis. Plant Physiol 160:1871–1880

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Tashiro T, Ebata M (1975) Studies on white belly rice kernel III. Effect of ripening conditions on occurrence of white belly kernel. Jpn J Crop Sci 44:86–92 (in Japanese)

    Article  Google Scholar 

  • Wada T, Miyahara K, Sonoda J, Tsukaguchi T, Miyazaki M, Tsubone M, Ando T, Ebana K, Yamamoto T, Iwasawa N, Umemoto T, Kondo M, Yano M (2015) Detection of QTLs for white-back and basal-white grains caused by high temperature during ripening period in japonica rice. Breed Sci 65:216–225

    Article  PubMed  PubMed Central  Google Scholar 

  • Wan XY, Wan JM, Weng JF, Jiang L, Bi JC, Wang CM, Zhai HQ (2005) Stability of QTLs for rice grain dimension and endosperm chalkiness characteristics across eight environments. Theor Appl Genet 110:1334–1346

    Article  PubMed  CAS  Google Scholar 

  • Wang E, Wang J, Zhu X, Hao W, Wang L, Li Q, Zhang L, He W, Lu B, Lin H, Ma H, Zhang G, He Z (2008) Control of rice grain-filling and yield by a gene with a potential signature of domestication. Nat Genet 40:1370–1374

    Article  PubMed  CAS  Google Scholar 

  • Wang S, Basten CJ, Zeng ZB (2012a) Windows QTL Cartographer 25. Department of Statistics, North Carolina State University, Raleigh

    Google Scholar 

  • Wang S, Wu K, Yuan Q, Liu X, Liu X, Liu Z, Zeng R, Zhu H, Dong G, Qian Q, Zhang G, Fu X (2012b) Control of grain size, shape and quality by OsSPL16 in rice. Nat Genet 44:950–954

    Article  PubMed  CAS  Google Scholar 

  • Wang Y, Xiong G, Hu J, Jiang L, Yu H, Xu J, Fang Y, Zeng L, Xu E, Xu J, Ye W, Meng X, Liu R, Chen H, Jing Y, Wang Y, Zhu X, Li J, Qian Q (2015a) Copy number variation at the GL7 locus contributes to grain size diversity in rice. Nat Genet 47:944–948

    Article  PubMed  CAS  Google Scholar 

  • Wang S, Li S, Liu Q, Wu K, Zhang J, Wang S, Wand Y, Chen X, Zhang Y, Gao C, Wang F, Huang H, Fu X (2015b) The OsSPL16-GW7 regulatory module determines grain shape and simultaneously improves rice yield and grain quality. Nat Genet 47:949–954

    Article  PubMed  CAS  Google Scholar 

  • Yamakawa H, Hirose T, Kuroda M, Yamaguchi T (2007) Comprehensive expression profiling of rice grain filling-related genes under high temperature using DNA microarray. Plant Physiol 144:258–277

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Yamakawa H, Ebitani T, Terao T (2008) Comparison between locations of QTLs for grain chalkiness and genes responsive to high temperature during grain filling on the rice chromosome map. Breed Sci 58:337–343

    Article  Google Scholar 

  • Yamamoto T, Nagasaki H, Yonemaru J, Ebana K, Nalajima M, Shibaya T, Yano M (2010) Fine definition of the pedigree haplotypes of closely related rice cultivars by means of genome-wide discovery of single-nucleotide polymorphisms. BMC Genom 11:267

    Article  CAS  Google Scholar 

  • Yanagiuchi T, Yamamoto H, Miyazaki N, Nagano T, Mizuma T, Wakai Y (1997) Influence of grain type on suitability of rice for sake brewing. Seibutsu-kogaku 75:169–176 (in Japanese)

    CAS  Google Scholar 

  • Yang J, Hu C, Hu H, Yu R, Xia Z, Ye Z, Zhu J (2008) QTLNetwork: mapping and visualizing genetic architecture of complex traits in experimental populations. Bioinformatics 25:721–723

    Article  CAS  Google Scholar 

  • Yin C, Li H, Li S, Xu L, Zhao Z, Wang J (2015) Genetic dissection on rice grain shape by the two-dimensional image analysis in one japonica × indica population consisting of recombinant inbred lines. Theor Appl Genet 128:1969–1986

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Yoshida S, Ikegami M, Kuze J, Sawada K, Hashimoto Z, Ishii T, Nakamura C, Kamijima O (2002) QTL analysis for plant and grain characters of Sake-brewing rice using a doubled haploid population. Breed Sci 52:309–317

    Article  CAS  Google Scholar 

  • Yoshioka Y, Iwata H, Tabata M, Ninomiya S, Ohsawa R (2007) Chalkiness in rice: potential for evaluation with image analysis. Crop Sci 47:2113–2120

    Article  Google Scholar 

  • Zeng ZB (1994) Precision mapping of quantitative trait loci. Genetics 136:1457–1468

    PubMed  PubMed Central  CAS  Google Scholar 

  • Zhao XQ, Daygon VD, McNally KL, Hamilton RS, Xie FM, Reinke RF, Fitzgerald MA (2016) Identification of stable QTLs causing chalk in rice grains in nine environments. Theor Appl Genet 129:141–153

    Article  PubMed  CAS  Google Scholar 

  • Zheng Y, Ji Z, Wen Z, Liang Y, Yang C (2016) Combination of eight alleles at four quantitative trait loci determines grain length in rice. PLoS One 11:e0150832

    Article  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Masanori Yamasaki.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Additional information

Communicated by Dr. Michael Thomson.

Electronic supplementary material

Below is the link to the electronic supplementary material.

122_2017_2977_MOESM1_ESM.pptx

Supplementary Fig. 1 Classification of chalky grains (a)-(f), with reference to Yoshioka et al. (2007). Upper row shows grayscale images of rice grains, lower row shows the corresponding binary images. (a) Perfect grain, (b) white-back grain, (c) basal-white grain, (d) white-belly, (e) white-core grain, (f) milky-white grain. (g) Brown grains of Koshihikari (upper) and Yamadanishiki (lower). (PPTX 27391 kb)

122_2017_2977_MOESM2_ESM.pptx

Supplementary Fig. 2 Histograms of each trait for 2010, 2013, and 2014. White and black arrows indicate the average trait values of Koshihikari and Yamadanishiki respectively. DTH: days to heading, GWt: 100-grains weight, GWh: grain width, GL: grain length, LWR: grain length to width ratio, WCE: white-core expression rate. (PPTX 4531 kb)

122_2017_2977_MOESM3_ESM.pptx

Supplementary Fig. 3 Transition of daily mean air temperatures in 2010, 2013, and 2014, represented by black, blue, and red lines, respectively. The black double-headed arrow around August 19 indicates the period around the average heading date of Yamadanishiki. (PPTX 469 kb)

122_2017_2977_MOESM4_ESM.pptx

Supplementary Fig. 4 Linkage maps showing the positions of QTLs that were detected by QTL analysis with the effects of Hd6 and Hd16 on DTH taken into consideration. The left and right linkage maps were generated from the F2 generation and the RIL populations respectively. Bars beside the QTLs indicate 1-LOD support CI. QTLs are named according to the following convention: “(trait name) reg(year)-(number)”, e.g. the second QTL detected in GWt from 2013 data is named “GWt reg13-2”. GWt reg: residual value of 100-grains weight, GWh reg: residual value of grain width, LWR reg: residual value of grain length to width ratio, WCE reg: residual value of white-core expression rate. (PPTX 1725 kb)

Supplementary material 5 (XLSX 9 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Okada, S., Suehiro, M., Ebana, K. et al. Genetic dissection of grain traits in Yamadanishiki, an excellent sake-brewing rice cultivar. Theor Appl Genet 130, 2567–2585 (2017). https://doi.org/10.1007/s00122-017-2977-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00122-017-2977-2

Navigation