How have breeders adapted rice flowering to the growing region?

Abstract

Flowering time is a crucial rice trait that influences its adaptation to various environments, cropping schedules, and agronomic characteristics. Rice breeders have exploited spontaneous mutations in heading date genes to regulate the flowering time. In the present study, we investigated how breeders in Fukui Prefecture regulated days to heading while developing promising rice varieties. Genome-wide association studies (GWAS) identified Hd1, Hd16, and Hd18 as the major genes controlling days to heading in the population. However, we suspected that this highly bred population might exhibit genomic stratification, which could lead to spurious or false correlations in the GWAS. Thus, we also conducted correlation and partial correlation analyses, which uncovered another key heading date gene,Hd17, that GWAS failed to detect because of its linkage disequilibrium with the major effect gene Hd16. Examination of haplotype frequencies across different breeding periods revealed that the early-heading Hd16 (Hd16(E)) and late-heading Hd17 (Hd17(L)) were increasingly co-selected in the Hd1 functional population. Varieties carrying this Hd16(E)/Hd17(L) combination exhibited days to heading in the range of 70–80, which corresponds to the peak temperature and sunshine period and is also optimal for grain quality and yield components in the Fukui environment. The present study highlights that it is imperative to remain vigilant for Type I (false positives) and Type II (false negatives) errors when performing GWAS on highly bred populations and to implement appropriate countermeasures by accounting for gene-by-gene interactions established through the breeding process. We also discuss the effectiveness of Hd16(E), which is not used outside Japan for subtle days to heading control but is widely used in Japan at certain latitudes.

Keywords

breeding / flowering / GWAS / heading date / partial correlation analysis / rice

References

[1] Chen,Z.,Bu,Q., Liu,G.,Wang, M.,Wang,H.,Liu,H.,Li,X., Li,H.,Fang, J.,Liang,Y., et al. (2023) Genomic decoding of breeding history to guide breeding-by-design in rice. Natl. Sci. Rev. 10:nwad029.

[2] Cingolani,P.,Platts,A., Wang,L.L.,Coon, M.,Nguyen,T.,Wang,L.,Land,S.J., Lu,X., and Ruden, D.M (2012). A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff. Fly 6:80–92.

[3] Fujino,K.,Nishimura, T.,Kiuchi,H.,Hirayama,Y., and Sato, T. (2017). Phenotypic changes during 100-year rice breeding programs in Hokkaido. Breed. Sci. 67:528–534.

[4] Fujino,K.,Yamanouchi, U.,Nonoue,Y.,Obara,M., and Yano, M. (2019). Switching genetic effects of the flowering time gene Hd1 in LD conditions by Ghd7 and OsPRR37 in rice. Breed. Sci. 69:127–132.

[5] Fukui Agricultural Experiment Station. (1950–2020). The breeding reports of new paddy rice line (in Japanese). Fukui Agricultural Experiment Station,Fukui, Japan.

[6] Heilongjiang Provincial Government. (2022). Planting Zoning layout of high-quality and high-efficiency rice varieties in Heilongjiang Province in 2022. Heilongjiang Provincial Government,Heilongjiang, China.

[7] Hori,K.,Kataoka, T.,Miura,K.,Yamaguchi,M.,Saka,N., Nakahara,T.,Sunohara, Y.,Ebana,K., and 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.

[8] Hori,K.,Matsubara, K., and Yano,M. (2016). Genetic control of flowering time in rice: Integration of Mendelian genetics and genomics. Theor. Appl. Genet. 129:2241–2252.

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

[10] Hori,K.,Takamatsu, M.,Hosoi,J.,Tsugane,T.,Hayashi, R.,Watanabe,M.,Mizubayashi,T.,Ando,T., Shomura,A.,Mukai, Y., et al. (2023). Fluctuation in genetic effects with introduced early-or late-heading-date gene alleles in near isogenic lines with different genetic background in rice. Breed. Res. 25:123–139 (in Japanese with English summary).

[11] Horiuchi,H.,Mizuno,S., Nakagawa,N.,Terada, K.,Tomita,K.,Ikeda,I.,Aoki,K., Minobe,T.,Tanoi, M.,Ishikawa,B., et al. (1992). Breeding process and characteristics of a new rice variety “Hanaechizen”. Hokuriku Crop Sci. 27:1–4 (in Japanese).

[12] Inatsu,O. (1988). Studies on improving the eating quality of Hokkaido rice. Rep. Hokkaido Prefect. Agric. Exp. Stn. 66:1–89 (in Japanese).

[13] Ishimori,Y.,Saeki,K., Endo,T.,Nakagomi, Y.,Sato,H.,Mizobuchi,R.,Taguchi-Shiobara, F.,Fukuoka,S.,Yamanouchi,U.,Ando,T., et al. (2020). Conversion effect of Hd1,Hd16, and Hd18 on the heading date of the rice line “Tohoku 206” which has high temperature tolerance during the ripening stage. Breed. Res. 22:149–158 (in Japanese with English summary).

[14] Itoh,H.,Tanaka,Y., and Izawa,T. (2019). Genetic relationship between phytochromes and OsELF3-1 reveals the mode of regulation for the suppression of phytochrome signaling in rice. Plant Cell Physiol. 60:549–561.

[15] Kim,S.R.,Torollo, G.,Yoon,M.R.,Kwak,J.,Lee,C.K., Prahalada,G.,Choi,I.R.,Yeo,U.S., Jeong,O.Y.,Jena, K.K., et al. (2018). Loss-of-function alleles of heading date 1 (Hd1) are associated with adaptation of temperate Japonica rice plants to the tropical region. Front. Plant Sci. 9:1827.

[16] Kobayashi,A. (2012). Breeding and genetics of heat-induced quality decline of rice. Hokuriku Crop Sci. 47:132–136 (in Japanese).

[17] Kobayashi,A.,Hori,K., Yamamoto,T., and Yano, M. (2018). Koshihikari: A premium short-grain rice cultivar—its expansion and breeding in Japan. Rice 11:15.

[18] Koo,B.H.,Yoo,S.C., Park,J.W.,Kwon, C.T.,Lee,B.D.,An,G.,Zhang,Z., Li,J.,Li, Z., and Paek,N.C (2013). Natural variation in OsPRR37 regulates heading date and contributes to rice cultivation at a wide range of latitudes. Mol. Plant 6:1877–1888.

[19] Kwon,C.T.,Koo,B.H., Kim,D.,Yoo, S.C., and Paek,N.C (2015). Casein kinases I and 2α phosphorylate oryza sativa pseudo-response regulator 37 (OsPRR37) in photoperiodic flowering in rice. Mol. Cells 38:81–88.

[20] Lee,Y.S., and An, G. (2015). Complex regulatory networks of flowering time in rice. J. Rice Res. 3:141.

[21] Li,X.,Liu,H., Wang,M.,Liu, H.,Tian,X.,Zhou,W.,Lü T.,Wang,Z.,Chu,C.,Fang,J., et al. (2015). Combinations of Hd2 and Hd4 genes determine rice adaptability to Heilongjiang Province, northern limit of China. J. Integr. Plant Biol. 57:698–707.

[22] Li,X.,Sun,Y., Tian,X.,Ren, Y.,Tang,J.,Wang,Z.,Cheng,Y., and Bu,Q. (2018). Comprehensive identification of major flowering time genes and their combinations, which determined rice distribution in Northeast China. Plant Growth Regul. 84:593–602.

[23] Matsubara,K.,Ogiso-Tanaka, E.,Hori,K.,Ebana,K.,Ando,T., and 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.

[24] Nemoto,Y.,Hori,K., and Izawa,T. (2018). Fine-tuning of the setting of critical day length by two casein kinases in rice photoperiodic flowering. J. Exp. Bot. 69:553–565.

[25] Nishio,T., and Fujimaki, H. (2020). Small dictionary of Japanese native rice varieties—records of 295 varieties and breeding farmers. Rural Culture Association,Saitama (in Japanese).

[26] Okuno,K.,Fuwa,H., and Yano,M. (1983). A new mutant gene lowering amylose content in endosperm starch of rice,Oryza sativa L. Japanese J. Breed. 33:387–394 (in Japanese with English summary).

[27] Ouyang,S.,Zhu,W., Hamilton,J.,Lin, H.,Campbell,M.,Childs,K.,Thibaud-Nissen, F.,Malek,R.L.,Lee,Y.,Zheng,L., et al. (2007). The TIGR rice genome annotation resource: Improvements and new features. Nucleic Acids Res. 35:883–887.

[28] Rice Variety database, NARO (2023). Rice Variety database, https://ineweb.narcc.affrc.go.jp/ (in Japanese) (Accessed October 30, 2023).

[29] Richardson,K. (2017). GWAS and cognitive abilities: Why correlations are inevitable and meaningless: GWA studies to identify genetic factors for educational achievements largely ignore underlying social structures and dynamics. EMBO Rep. 18:1279–1283.

[30] Saito,H.,Ogiso-Tanaka, E.,Okumoto,Y.,Yoshitake,Y.,Izumi,H., Yokoo,T.,Matsubara, K.,Hori,K.,Yano,M.,Inoue,H., et al. (2012). Ef7 encodes an ELF3-like protein and promotes rice flowering by negatively regulating the floral repressor gene Ghd7 under both short-and long-day conditions. Plant Cell Physiol. 53:717–728.

[31] Segura,V.,Vilhjálmsson, B.J.,Platt,A.,Korte,A.,Seren,Ü., Long,Q., and Nordborg, M. (2012). An efficient multi-locus mixed-model approach for genome-wide association studies in structured populations. Nat. Genet. 44:825–830.

[32] Shibaya,T.,Hori,K., Ogiso-tanaka,E.,Yamanouchi,U.,Shu,K., Kitazawa,N.,Shomura, A.,Ando,T.,Ebara,K.,Wu,J., et al. (2016). Hd18, encoding histone acetylase related to Arabidopsis FLOWERING LOCUS D, is involved in the control of flowering time in rice. Plant Cell Physiol. 57:1828–1838.

[33] Suganami,M.,Kojima,S., Wang,F.,Yoshida, H.,Miura,K.,Morinaka,Y.,Watanabe, M.,Matsuda,T.,Yamamoto,E., and Matsuoka, M. (2023). Effective use of legacy data in a genome-wide association studies improves the credibility of quantitative trait loci detection in rice. Plant Physiol. 191:1561–1573.

[34] Suganami,M.,Yoshida, H.,Yoshida,S.,Kawamura,M.,Koketsu, E.,Matsuoka,M., and Kojima,S. (2024). Redefining awn development in rice through the breeding history of Japanese awn reduction. Front. Plant Sci. 15:1370956.

[35] Sun,K.,Zong,W., Xiao,D.,Wu, Z.,Guo,X.,Li,F.,Song,Y., Li,S.,Wei, G.,Hao,Y., et al. (2023). Effects of the core heading date genes Hd1, Ghd7, DTH8, and PRR37 on yield-related traits in rice. Theor. Appl. Genet. 136:227.

[36] Takahashi,Y.,Shouma,A., Sasaki,T., and 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. U. S. A. 98:7922–7927.

[37] Takahashi,Y.,Teshima, K.M.,Yokoi,S.,Innan,H., and Shimamoto, K. (2009). Variations in Hd1 proteins, Hd3a promoters, and Ehd1 expression levels contribute to diversity of flowering time in cultivated rice. Proc. Natl. Acad. Sci. U. S. A. 106:4555–4560.

[38] Takami,S. (1995). Weather in Hokuriku region. In Koshihikari Hokuriku Crop and Breeding Science Conference., ed, (Saitama: Rural Culture Association Japan), pp. 469–470. (in Japanese).

[39] Takeuchi,Y.,Kato,H., Nemoto,H.,Ohta, H.,Sato,H.,Hirayama,M.,Hirabayashi, H.,Ideta,O.,Aoki,N.,Sakai,M., et al. (2008). Breeding of “Koshihikari Kanto HD1” an isogenic line of the rice cultivar Koshihikari with early heading. Bull. Natl. Inst. Crop Sci. 9:1–25 (in Japanese with English summary).

[40] Tomita,K.,Horiuchi, H.,Kobayashi,A.,Tanoi,M.,Tanaka,I., Minobe,T.,Kanda, K.,Hayashi,T.,Terada,K.,Sugimoto, A., et al. (2009). “Akisakari” a new rice cultivar. Bull. Fukui Agr. Exp. Stn. 46:1–21. (in Japanese with English summary).

[41] Uffelmann,E.,Huang,Q.Q., Munung,N.S.,Veris, J.,Okada,Y.,Martin,A.R.,Martin,H.C., Lappalainen,T., and Posthuma,D. (2021). Genome-wide association studies. Nat. Rev. Methods Primers 1:59.

[42] Vicentini,G.,Biancucci, M.,Mineri,L.,ChirivìD.,Giaume, F.,Miao,Y.,Kyozuka,J.,Brambilla, V.,Betti,C., and Fornara,F. (2023). Environmental control of rice flowering time. Plant Commun. 4:100610.

[43] Wang,W.,Mauleon, R.,Hu,Z.,Chebotarov,D.,Tai,S., Wu,Z.,Li, M.,Zheng,T.,Fuentes,R.R.,Zhang,F., et al. (2018). Genomic variation in 3, 010 diverse accessions of Asian cultivated rice. Nature 557:43–49.

[44] Wei,X.,Qiu,J., Yong,K.,Fan, J.,Zhang,Q.,Hua,H.,Liu,J., Wang,Q.,Olsen, K.M.,Han,B., et al. (2021). A quantitative genomics map of rice provides genetic insights and guides breeding. Nat. Genet. 53:243–253.

[45] Wu,C.C.,Wei,F.J., Chiou,W.Y.,Tsai, Y.C.,Wu,H.P.,Gotarkar,D.,Wei,Z.H., Lai,M.H., and Hsing, Y.C (2020). Studies of rice Hd1 haplotypes worldwide reveal adaptation of flowering time to different environments. PLoS ONE 15:e0239028.

[46] Yamamoto,R. (1992). Changes and prospects in rice breeding. In Rice Breeding in Japan. Kushibuchi, K., ed, (Tokyo: Nougyou Gijutu Kyoukai), pp. 1–33 (in Japanese).

[47] Yang,Y.,Peng,Q., Chen,G.X.,Li, X.H., and Wu,C.Y (2013). OsELF3 is involved in circadian clock regulation for promoting flowering under long-day conditions in rice. Mol. Plant 6:202–215.

[48] Yano,K.,Morinaka, Y.,Wang,F.,Huang,P.,Takehara, S.,Hirai,T.,Ito,A.,Koketsu, E.,Kawamura,M.,Kotake,K., et al. (2019). GWAS with principal component analysis identifies a gene comprehensively controlling rice architecture. Proc.Natl. Acad. Sci. U. S. A. 116:21262–21267.

[49] Yano,K.,Yamamoto, E.,Aya,K.,Takeuchi,H.,Lo,P., Hu,L.,Yamasaki, M.,Yoshida,S.,Kitano,H.,Hirano,K., et al. (2016). Genome-wide association study using whole-genome sequencing rapidly identifies new genes influencing agronomic traits in rice. Nat. Genet. 48:927–934.

[50] Yano,M.,Katayose, Y.,Ashikari,M.,Yamanouchi,U.,Monna,L., Fuse,T.,Baba, T.,Yamamoto,K.,Umehara,Y.,Nagamura, Y., et al. (2000). Hd1, a major photoperiod sensitivity quantitative trait locus in rice, is closely related to the Arabidopsis flowering time gene CONSTANS. Plant Cell 12:2473–2483.

[51] Yano,M.,Okuno,K., Satoh,H., and Omura, T. (1988). Chromosomal location of genes conditioning low amylose content of endosperm starches in rice,Oryza sativa L. Theor. Appl. Genet. 76:183–189.

[52] Zheng,X.,Levine,D., Shen,J.,Gogarten, S.M.,Laurie,C., and Weir,B.S (2012). A high-performance computing toolset for relatedness and principal component analysis of SNP data. Bioinformatics 28:3326–3328.

[53] Zhou,S.,Zhu,S., Cui,S.,Hou, H.,Wu,H.,Hao,B.,Cai,L., Xu,Z.,Liu, L.,Jiang,L., et al. (2021). Transcriptional and post-transcriptional regulation of heading date in rice. New Phytol. 230:943–956.

RIGHTS & PERMISSIONS

2024 The Author(s). Journal of Integrative Plant Biology published by John Wiley & Sons Australia, Ltd on behalf of Institute of Botany, Chinese Academy of Sciences.