Marker-assisted selection in rice breeding programs in Hokkaido

Abstract

Rice breeding programs in Hokkaido over the past 100 years have dramatically increased productivity and improved the eating quality of rice. Commercial varieties with high yield and good eating quality, such as Kirara 397, Hoshinoyume, and Nanatsuboshi, have been continuously registered since 1990. Furthermore, varieties with better eating quality using Wx1-1, which reduces amylose content to improve the taste of sticky rice, such as Oborozuki and Yumepirika, were registered in 2006 and 2008, respectively. However, to the best of our knowledge the genomic changes associated with these improvements have not been determined. Better understanding of the relationships between DNA sequences and agricultural traits could facilitate rice breeding programs in Hokkaido. Marker-assisted selection (MAS), which can select the plants with chromosomal regions tagged with DNA markers for desirable traits, is an advanced technology to manage genetic improvements. Here, we summarize the current states of MAS in rice breeding programs in Hokkaido before huge data sets of genome sequences using next-generation sequencing technology come into practical use in rice breeding programs.

Introduction

Breeders for any crop species try to increase the productivity and to improve the quality of products to meet human demands in plant breeding programs. Rice, Oryza sativa L., is one of the most important cereal grains in the world today. During the last century, genetic improvements in local elite varieties and the modernization of cultivation systems have enabled stable rice production around the world, including in Japan. Crop breeding programs aim to control genetic diversity including the collection, induction, and combination among crop species for desirable phenotypes to meet human demands (Fu 2015, Louwaars 2018). The bottleneck effect on phenotypic selection in elite rice varieties during rice breeding programs in Japan have dramatically narrowed down their genetic diversity through the modernization of rice breeding programs in Japan to reach ideal types (Ebana et al. 2008, Fujino et al. 2015, 2017, Shinada et al. 2014, Yamamoto et al. 2010, Yonemaru et al. 2012). However, it is unclear which genes have generated the changes in desirable phenotypes in elite rice varieties.

Various rice varieties have been differentiated by natural selection and utilized to meet human demands in accordance with local cultures. The determination of genetic differentiation of rice varieties across latitudinal gradients may be the consequence of their adaptation to local ecological and environmental factors. Japan, which spans from 136°04W 20°25N to 148°45W 45°33N, encompasses a wide range of environmental conditions. Hokkaido, 139°45W 45°33N to 148°45W 45°33N, is the northern-most region of Japan and one of the northern limits of rice cultivation around the world (Fig. 1a, 1b). Rice breeding programs in Hokkaido have spanned 100 years, and seed yield and eating quality have been greatly improved due to intensive selection based on phenotypic dissection, involving both genomics and phenomics (Fujino et al. 2015, 2017, Shinada et al. 2014).

Fig. 1

The location of Hokkaido, Japan. A: Japan is indicated in the circle. The origin of rice domestication in China is indicated with a triangle. B: Hokkaido (enclosed) is the northern-most region of Japan. C: Rice plants at maturity (October) in conventional cultivation in a paddy field in Hokkaido. Hoshinoyume, a variety from Hokkaido (left), is fully ripened, whereas Koshihikari, from Niigata (right), is immature.

Over the 100 years of rice breeding programs in Hokkaido, desirable traits for productivity and quality have been improved (Fujino et al. 2017). In addition, genome-wide marker analysis has clearly demonstrated that shifts in genetic population structures have occurred five times (Shinada et al. 2014). The shift of genetic diversity in the local gene pool may be managed with the use of exotic germplasm for human demands in rice breeding programs in Hokkaido (Fujino et al. 2015, 2017, Shinada et al. 2014). Next-generation sequencing (NGS) technology is now available for both plant biology research and plant breeding (Kim et al. 2016, Wang et al. 2018, Zhang et al. 2016, Zhou et al. 2016). However, there still remain many gaps in the understanding of the relationships between DNA sequence alignments and agricultural traits.

Marker-assisted selection (MAS), which can select plants with chromosomal regions tagged with DNA markers for desirable traits to meet human demands, is an advanced technology for plant breeding programs. MAS could select plants based on genotype instead of phenotype. Furthermore, MAS could transfer precisely genes/quantitative trait loci (QTLs) for desirable traits into a single variety from donors within the shortest generation time possible. The theoretical role of MAS in plant breeding programs is described in elsewhere (Cobb et al. 2018, Das et al. 2017). Here, we summarized the current statue of MAS in rice breeding programs in Hokkaido before huge data sets of genome sequences generated by NGS come to the fore in practical rice breeding programs. In addition, we discuss the role of MAS in practical rice breeding programs in Hokkaido.

History of rice cultivation in Hokkaido

Recent genetic and archaeology findings demonstrated that Asian cultivated rice O. sativa japonica was domesticated in the Yangtze River valley in southern China 10,000 years ago (Choi et al. 2017, Fuller 2011, Huang et al. 2012, Yang et al. 2012). Rice cultivation subsequently expanded around the world along with human migrations. Rice cultivation was introduced to Japan around 1000 BC, and it then spread over Japan in the Middle Yayoi period around 350 BC (Fuller 2011, Takamiya 2001). Rice cultivation in Hokkaido has been tried since the 1600s. In addition to naturally long day length conditions, the climate in Hokkaido includes cold precipitation and chilling temperature in the spring and autumn, which are all unfavorable for rice growth. Furthermore, low temperature at the reproductive phase severely causes to impair rice yield.

Based on historical records, rice cultivation in Hokkaido was tried several times in southern Hokkaido in the 1600s but these attempts largely failed (Fig. 2A, 2D). In the 1800s, rice cultivation was attempted again in southern Hokkaido along with the expansion of the Japanese society. In the 1850s, rice cultivation was successfully carried out in Ono city, southern Hokkaido. A couple of rice cultivation systems and rice varieties with adaptability together contributed to the expansion of rice cultivation areas over Hokkaido. A farmer named Kyuzo Nakayama chose a rice variety named Akage for rice cultivation in 1873, which has an extremely early heading date due to its ghd7osprr37 genotype (Fig. 2B, 2D) (Fujino et al. 2019a). In addition, he facilitated seedling growth using warmed water during the low temperature period in spring. During the 1770s (Tenmei), rice varieties with extremely early heading date were cultivated in the Tohoku region to escape low temperature at the reproductive phase, which remarkably reduces yield. These might be the ancestors of Akage. Since then, rice cultivation had expanded even to northern Hokkaido. In 1927, rice cultivation was established in Enbetsu, the northern-limit of rice cultivation around the world (Fig. 2C, 2D).

Fig. 2

Key time points in the history of rice cultivation in Hokkaido, Japan. A: The start of rice cultivation in 1692 in Ono city (41.87N 140.63E) (Photo by Takashi Sato). B: The state of rice cultivation in Hokkaido in Kitahiroshima city (42.92N 141.54E) in 1873. Photo from http://www.city.kitahiroshima.hokkaido.jp/sightseeing/detail/00126033.html. C: A paddy field in the northern-most region of Hokkaido (44.45N 141.52E) (Photo by Hitoshi Kiuchi). D: The locations of these key events.

Rice breeding programs in Hokkaido in the 20th century

After the rediscovery of Mendel’s laws, the local government in Hokkaido commenced rice breeding programs in 1915. In 2017, Hokkaido was a significant rice productivity area in Japan (Supplemental Table 1). Three rice varieties, Nanatsuboshi, Yumepirika, and Kirara 397, represent 80.9% of rice grown in Hokkaido (Supplemental Table 2).

Phenotypic changes during rice breeding programs in Hokkaido were characterized in 26 agricultural traits (Fujino et al. 2017). Traits for plant architecture, which are visible, have been immediately improved in the initial phase in rice breeding programs. Conversely, traits for seed quality, which are measured experimentally, have been improved since the late 1900s. These phenotypic changes might be generated by the use of exotic germplasm rather than continuous phenotypic selection year by year (Shinada et al. 2014). Genetic diversity from exotic germplasm might cause shifts in population structures to generate improved phenotype (Fujino et al. 2015). These genomic views on rice breeding programs in Hokkaido shed light on conventional rice breeding programs based on selection according to phenotype. Because of the phenotypic changes in the 100 years of rice breeding programs in Hokkaido, we propose two categories for agricultural traits in rice breeding programs; breeding-syndrome traits and premium traits.

Breeding-syndrome traits

Optimizing the adaptability to local environmental conditions is the primary objective in plant breeding programs. Yield limits the adaptability in crops, and in rice this is determined by three major components; days to heading (DTH), panicle number (PN), and seeds per panicle. The expression of yield-related traits including these three major components can be affected by epistatic interactions and environmental conditions (Ando et al. 2010, Li et al. 2003, Liang et al. 2014, Wang et al. 2015, Wang and Li 2008, Xing et al. 2002, Zhou et al. 2018). We can categorize them into “breeding-syndrome traits”.

Together with the cultivation system, a genotype suited to improved productivity could be established by optimizing adaptability. In the initial phase of plant breeding programs, the main efforts focus on the maximization and stabilization of seed yield in local environmental conditions. Plant architecture including breeding-syndrome traits shifted dramatically over the short time span, from large to compact (Fujino et al. 2017). The rice variety Kitaake, which is the most significant variety in the genetic population structure of group V, showed compact plants during the rice growth compared with a rice landrace Akage, which belongs to group I (Table 1). Kitaake showed earlier heading date, shorter culm length (CL), and greater panicle number than Akage (Fig. 3A–3D, Table 1). Plants with shorter CL exhibit resistance to lodging, which causes a decrease in seed yield (Fig. 3C). Early heading in DTH is essential for adaptability to conditions in Hokkaido (Fujino et al. 2019a), and it controls yield-related traits. In particular, a negative correlation between DTH and PN is favored for rice cultivation in Hokkaido (Fujino et al. 2019a). These yield-related traits are also associated with various morphological components, including panicle architecture. Earlier DTH caused by Heading date 1 (Hd1) (Yano et al. 2000) is associated with greater PN and short panicle length (PL) (Fujino et al. 2019a). These yield-related traits exhibited a balance between them with a strong impact on not only yield but also seed quality. Altered panicle architecture might contribute to grain filling nature (Fig. 3D, Table 1), leading to high quality of the grains. Phenotypic changes are commonly observed between Akage and Kirara 397, which belongs to group V (Fig. 3A–3D).

Table 1 Changes in phenotype involved in yield related traits

Category	Trait	Phenotypic value
		Akage	Kitaake	Yumepirica
Yield	Total Yield (kg/a, YLDt)	57.3	50.5	72.6
		100	88.1	126.7
Plant architecture	Days to heading (day, DTH)	98	89	91
		100	90.8	92.9
	Culm length (cm, CL)	93.7	59.4	64.5
		100	63.4	68.8
	Panicle number (number, PN)	419	511	848
		100	122.0	202.4
Panicle architecture	Panicle length (cm, PL)	20.9	15.4	15.9
		100	73.7	76.1
	Seeds per panicle (number, SP)	92.4	58.3	59.3
		100	63.1	64.2

Phenotypic values are cited from Fujino et al. (2017), which were measured in 2013 at Kamikawa exp. Station, Pippu, Hokkaido, Japan.

Upper and lower rows indicate phenotypic values and ratio with “Akage” being 100, respectively.

Fig. 3

Phenotypic difference between genotypes. A–E: Rice plants (Kirara397 on the left and Akage on the right in each panel) grown in the experimental paddy field in natural environmental conditions (Sapporo, Hokkaido, 2018). Plants on 2018-07-04 (A), 2018-08-07 (B), and 2018-09-14 (C), panicles (D), grains (E). Bar indicates 1 cm. Sowing and transplanting were performed on 16 April and 22 May 2018, respectively. Cultivation management followed the standard procedures used at Hokkaido Agricultural Research Center. F: rice variety Hoshinoyume (three leaves on the left) and Kitakurin (right) in a field test for blast resistance in Kamikawa (Pippu, Hokkaido) (Photo by Hitoshi Kiuchi).

Various traits are involved in breeding-syndrome traits. A simple question arises as to how many genes contribute to improve breeding-syndrome traits during rice breeding programs in Hokkaido. A single gene for DTH, Hd1may function in these traits. Functional Hd1 exhibits earlier DTH with short CL, greater PN, and short PL (Fujino et al. 2019a). Functional Hd1 (allelic to Lm), versus a loss-of-function hd1, may contribute to the southern–northern distribution among Japanese rice varieties (Yokoo and Kikuchi 1977, Yokoo et al. 1980). Of note, functional Hd1 was transferred into the gene pool of rice breeding programs in Hokkaido (Fujino et al. 2019a). This could shape the fitness as adaptability to agriculture, leading to significant rice production in Japan. The de novo mutations in loss-of-function ghd7 and osprr37, which showed extremely early heading date, might be generated in rice varieties with loss-of-function hd1 in the northern distribution of rice.

Premium traits

In rice breeding programs in Hokkaido, the eating quality of rice, as part of the world heritage WASHOKU, was intensively improved in the late 1900s. Various traits may be involved as part of good eating quality such as amylose content, whiteness (white/dark with blight), stickiness (degree of stickiness), and hardness (soft/hard). The eating quality of cooked rice largely depends on degree of amylose content. Many genes that reduce the amylose content in rice grain have been identified and have contributed to improving the texture for better eating quality to favorable for the Japanese market (Ando et al. 2010, Sato et al. 2002, Takemoto-Kuno et al. 2015). The market in Japan evaluates rice products based on these traits. Amylose content of Akage (22.4%) was dramatically decreased in Kitaake (20.2%) and Yumepirika (16.1%) instead of grain shape (Table 2). In addition, grain appearance, which shows the perfect grain rate, was dramatically improved in Yumepirika (79.6%) and Kitaake (70.1%) rather than Akage (12.2%) (Table 2). We categorized the traits for seed quality into “premium traits”. The phenotype of premium traits could be expressed from novel genes/QTLs in genetic background improved by breeding-syndrome traits (Fig. 3E).

Table 2 Changes in phenotype involved in grain quality traits

Category	Trait	Phenotypic value
		Akage	Kitaake	Yumepirica
Grain shape	Grain length (mm, GL)	4.95	4.82	5.12
		100	97.4	103.4
	Grain width (mm, GW)	2.83	3.00	2.81
		100	106.0	99.3
	1000-grain weight (g, TGW)	22.3	24.2	23.0
		100	108.5	103.1
Grain quality	Witeness of brown rice (Number, WB)	21.8	19.1	20
		100	87.6	91.7
	Amylose content (%, AC)	22.4	20.2	16.1
		100	90.2	71.9
	Protein content (%, PC)	7.20	7.31	6.62
		100	101.5	91.9
	Grain appearance (%, GA)	12.2	70.1	79.6
		100	574.6	652.5

Phenotypic values are cited from Fujino et al. (2017), which were measured in 2013 at Kamikawa exp. Station, Pippu, Hokkaido, Japan.

Upper and lower rows indicate phenotypic values and ratio with “Akage” being 100, respectively.

Once the adaptability for local environments, breeding-syndrome traits, has been optimized, plant breeding programs will focus on the quality of the products, premium traits. For human demands as part of local culture, quality of products may be shaped by novel genes among local varieties.

MAS in rice breeding programs in Hokkaido

Phenotypic selection during the rice breeding programs in Hokkaido has improved various agronomic traits (Fujino et al. 2017). To facilitate rice breeding programs in Hokkaido, MAS has been actively carried out since the first attempt of MAS for a stripe resistance gene Stvb-i (Hayano-Saito et al. 2000) in 1996. In the initial phase, MAS was carried out for research purposes rather than for the development of new varieties due to the limited number of available DNA markers. Increased number of available DNA markers for various traits has given a great impact on the application of MAS in rice breeding programs (Table 3, Supplemental Table 3).

Table 3 MAS in rice breeding programs in Hokkaido

Year	Trait	Gene/QTL	Reference
2005	Blast resistance	Pb1	Hayashi et al. 2010
2005	Rice stripe virus resistance	Stvb-i	Hayano-Saito et al. 2000
2005	Low temperature tolerance	Ctb1·Ctb2	Saito et al. 2001
2005	Low temperature tolerance	qCTB-8	Kuroki et al. 2007
2010	Blast resistance	pi21	Fukuoka et al. 2009
2010	Blast resistance	Pi35	Nguyen et al. 2006
2010	Blast resistance	Pi39	Terashima et al. 2008
2010	Amylose content	qAC9.3	Ando et al. 2010
2010	Amylose content	Wx1-1	Ando et al. 2010
2010	Amylose content	Wx-mq	Sato et al. 2002
2010	Amylose content	Wx-a	Yamanaka et al. 2004
2017	Amylose content	qAC2	Takemoto-Kuno et al. 2015
2017	Amylose content	Wx-mq	Sato et al. 2002
2017	Amylose content	Wx1-1	Ando et al. 2010
2017	Amylose content	qAC9.3	Ando et al. 2010
2017	Blast resistance	pi21	Fukuoka et al. 2009
2017	Blast resistance	Pi-km	Costanzo and Jia 2010
2017	Blast resistance	Pb1	Hayashi et al. 2010
2017	Blast resistance	Pi35	Fukuoka et al. 2014
2017	Blast resistance	Pi39	Liu et al. 2007
2017	Blast resistance	Pi-cd	Shinada et al. 2015b
2017	Seedling establishment	qSES11	Iwata et al. 2010
2017	Low-temperature germinability	qLTG3-1	Fujino et al. 2008
2017	Root characteristicc	Dro1	Uga et al. 2013
2017	Yield	Gn1	Ashikari et al. 2005
2017	Amylopectin property	sbe1	Okamoto et al. 2013

Because genes for amylose content and disease (blast fungus) resistance have large effects on these traits, improvements in these traits are useful for MAS using DNA markers targeted to the desired alleles. Control of amylose content is a major strategy for rice breeding programs for the improvement of eating quality. Wx1-1 for low amylose content was identified on the short arm of chromosome 6 (Ando et al. 2010), and rice variety Yumepirika harboring Wx1-1 exhibited sticky eating quality. This eating quality has been evaluated as a premium characteristic in the Japanese market.

Previously, we identified the blast resistant gene Pi-cd on chromosome 11 as a major genetic factor in the local rice population in Hokkaido (Fig. 3F), although it may be derived from a rice variety Cody from USA (Shinada et al. 2015b). The Pi-cd locus is distributed specifically in tropical japonica (upland) rice varieties over the world and might be introgressed from wild relative O. meridionalis (Fujino et al. 2019c). Pi-cd is only one blast resistance gene, which has been used in rice breeding programs in Hokkaido. The rice variety Kitakurin was registered in 2014 and exhibits good eating quality and vigorous resistance to rice blast (http://www.pref.hokkaido.lg.jp/ns/nsk/kome/index3.htm). Pi-cd plays a major role in blast resistance in Kitakurin (Fujino et al. 2019c, Shinada et al. 2015b).

Rapid changes in the virulence characteristics of populations raises a continuous threat to the effectiveness of existing blast-resistant varieties, because breakdown of resistance in newly developed resistant varieties is often observed due to evolution of new virulent pathogen strains. However, MAS for the utilization of the known resistance genes/QTLs could be reliable in achieving disease resistance in a variety. This approach accelerated the monogenic nature of blast resistance in a local gene pool. Accurate understanding of the genetic structure and genes controlling virulence is required in management strategies for the durability of blast resistance in rice.

We are able to select plants homozygous for the gene/QTL targeted in a single generation using MAS. This is the main advantage of MAS compared with conventional strategies. When selection is carried out based on phenotypic values, it is difficult to distinguish plants that are homozygous or heterozygous for the target gene/QTL. To determine the genotype of traits, progeny testing needs to be carried, which is laborious, expensive, and time-consuming. Conversely, with MAS we can select the desired genotype directly, facilitating rice breeding programs.

This efficiency of MAS is dependent on the heritability of the traits targeted. In the next section, we will focus on the efficiency of selection not on the selection process itself for plants with desirable genotypes but also in the improvement of traits. We have to manage genetic diversity to meet human demands. Therefore, it is necessary to clarify which genes in any germplasm exhibit a novel phenotype in agronomic traits of interest. Consequently, MAS should focus on agronomic traits to meet human demands in the future.

Genes/QTLs for the desirable traits

At least 98 genomic studies on various agronomic traits have been carried out using rice varieties in Hokkaido during the past 10 years (Supplemental Table 3). Among these, desirable genes/QTLs for trait improvement have been identified (Table 4). These DNA markers have already been utilized for MAS and facilitated improvements in the traits.

Table 4 Genes/QTLs found in rice varieties from Hokkaido

Gene/QTL	Locus		Desirable allele			Reference
	Name	Function	Name	Effect	Variety
Gene	Wx	Amylose content in rice grain	Wx1-1	Decrease	Hokkai No. 287	Ando et al. 2010
QTL	qAC2	Amylose content in rice grain	qAC2	Decrease	Kuiku No. 162	Takemoto-Kuno et al. 2015
QTL	qAC9.3	Amylose content in rice grain	qAC9.3	Decrease	Hokkai PL-9	Ando et al. 2010
QTL	Pi-cd	Blast resistance	Pi-cd	Resistance	Kitaake	Shinada et al. 2015b
Gene	Hd5	Heading date	hd5	Promote	Bozu No. 6	Wei et al. 2010, Fujino et al. 2013
Gene	Ghd7	Heading date	ghd7	Promote	na	Xue et al. 2008, Fujino et al. 2013
Gene	OsPRR37	Heading date	osprr37	Promote	na	Koo et al. 2013, Fujino et al. 2019b
Gene	Hd1	Heading date	Hd1	Promote	na	Yano et al. 2000, Fujino et al. 2019b
Gene	qLTG3-1	Cold tolerance at the seed germination	qLTG3-1	Promote	na	Fujino et al. 2008, Fujino and Iwata 2011
QTL	qCTF7	Cold tolerance at the fertilization stage	qCTF7	Tolerance	Eikei 88223	Shinada et al. 2013
QTL	qWCR	Grain quality (Whiteness of cooked rice)	qWCR	Whiteness	na	Shinada et al. 2015a

na; not avaibable.

Understanding of the origins of desirable alleles can facilitate rice breeding programs. We have divided these origins into three categories (Table 4). The first is de novo mutations under intensive human demand during rice cultivation in Japan. Second is natural variation, which occurred before rice came to Japan and involves genetically diverse germplasm from all over the world. The third is induced mutations generated by chemical mutagens and ionizing radiation. Taken together, all kinds of genetic variations are significant for improvements in traits for human demands.

In addition, desirable alleles for important traits frequently existed in the local germplasm. Desired alleles at qLTG3-1 locus for low temperature germinability has been selected along with the cultivation system (Fujino et al. 2004, 2008, Fujino and Iwata 2011). There were three alleles at the qLTG3-1 locus. First, a functional allele, is found in Italica Livorno, the IL allele. Second, the NP allele is found in Nipponbare, where a single amino acid substitution was present in a conserved domain of qLTG3-1, which led to a reduction in function. Third, a loss-of-function allele caused by a 71 bp deletion is found in rice variety Hayamasari, the HY allele. In landraces and varieties from the initial phase of rice breeding programs in Hokkaido, most varieties carried the IL allele, then the predominant allele shifted to the NP allele, and finally it shifted to the HY allele (Fujino and Iwata 2011). The rapid shifts in alleles for qLTG3-1 indicated that there were strong selection pressures toward weaker germinability at low temperature during rice breeding programs in Hokkaido (Fujino and Iwata 2011). The mutant alleles might become adaptable to the cultivation system in Hokkaido.

Prospects

Shaping the cultivation systems and phenotypes in a variety by intensive artificial selections has decreased the genetic diversity in plant breeding programs (Fu 2015, Louwaars 2018). For human demands in the future, the control of genetic diversity may be significant for how to establish desirable genotypes using diverse exotic germplasm over cultivated species and their wild relatives, which is clearly and genetically distinguishable from local elite varieties. Depending on the status of plant breeding programs, the control of genetic diversity in an elite variety may be critical for the activity of plant breeding programs.

Cross (hybridization) breeding strategies are a major driver for the control and increase of genetic diversity in local gene pools, especially for those with an inbreeding habit such as rice. The utilization of exotic germplasm as a parental variety can be used to explore the genetic diversity of local gene pools and may break the balance of elite phenotypes from the combination of desirable traits/genes. The modernization of rice breeding programs with molecular technology may dramatically and immediately reduce genetic diversity, forming a bottleneck.

Novel phenotypes are generated from novel genes themselves and genetic interactions (Fujino et al. 2019a, 2019b). For example, extremely earlier heading date is expressed in EARLY DUO, ghd7osprr37, in natural variation but also in EARLY TRYO, Hd1ghd7osprr37, derived from rice breeding programs (Fig. 4) (Fujino et al. 2019a). Plant breeding programs can construct novel combinations of genes that never occur in natural variations, exhibiting novel phenotypes. However, we could not fully elucidate which combinations of genes generate novel phenotypes. This is a limitation of plant breeding programs rather than MAS.

Fig. 4

A working model of the distribution of Hd1 in Japan. Open and closed arrows indicate the drivers of Hd1 alleles from natural variation and rice breeding programs, respectively.

Conclusion

Molecular techniques for MAS are enough for practical application in rice breeding programs. As well as the methodological advantages and significance of MAS, we should also further examine the consequences of MAS in the improvement of traits. Conventional strategies in rice breeding programs can involve several genetic steps. Firstly, we collect genetically and phenotypically diverse germplasm from all over the world. Second, we evaluate the trait values in these germplasms. Then, we identified genes/QTLs, and introduced them into elite local varieties. Conversely, MAS facilitates not only the selection of rice plants but also all the processes in rice breeding programs. We can design new varieties using available DNA markers only. The resultant new varieties may exhibit a phenotype within an expected range. To break through the limitations of MAS, we should develop new strategies with genomic inputs.

The current rice breeding programs enhanced by MAS looked to combine desirable traits/genes among the local gene pool into a single variety. Although rice breeding programs have had various achievements in meeting current human demands, there still remains an unmet need to control genetic diversity in rice breeding programs for human demands in the future. Now, we are in the genomic-era. Novel genes/QTLs for desirable traits found in local rice breeding programs, such as semi-dwarf sd1 (Asano et al. 2007), could be shared all over the world using molecular techniques with several kinds of resolution: phenotype, Mb level at the chromosomal region, kb level for physical distance, and bp level in the responsible gene itself.

Germplasm under diverse environmental conditions and in different culture conditions is valuable for various human demands (Dwivedi et al. 2016, 2017). Various local populations, such as at the country level, have been analyzed for their genetic diversity as genetic population structures (Table 5). We should use it in field evaluation systems depending on the genetic classification, because phenotypic values are expressed from the results of interactions between the genotype and environment.

Table 5 Research on genetical population structure analysis in local rice populations

Area	DNA	marker References
Hokkaido, Japan	SSR	Shinada et al. 2014
	SSR	Fujino et al. 2019a
Japan	SSR	Ebana et al. 2008
	SNP	Yonemaru et al. 2012
Argentina	SSR	Giarrocco et al. 2007
Cambodia	SSR	Orn et al. 2015
Indonesia	SSR	Thomson et al. 2007
Italy	SSR	Cai et al. 2013
Portugal	SSR	Jayamani et al. 2007
Thailand	Indel	Chakhonkaen et al. 2012
USA	SSR	Lu et al. 2005
Vietnam	RFLP	Fukuoka et al. 2003
Europe	SSR	Courtois et al. 2012
Northeast Asia	SSR	Wang et al. 2014
Temperate region	SNP	Reig-Valiente et al. 2016

DNA marker indicates SSR; Simple Sequence Repeat, Indel; Insertion and deletion, SNP; Single Nucleotide Polymorphism, RFLP; Restriction Fragment Length Polymorphism.

The main advantages for genomic research focusing on improved rice varieties from Hokkaido include understanding the tolerance mechanism to abiotic stresses such as low temperature (Guo et al. 2018, Jha et al. 2017, Lv et al. 2016, Xiao et al. 2018, Zhao et al. 2017). Following the optimization of the adaptability to local regions, tolerance to low temperature for stable rice production in Hokkaido can be improved (Fujino et al. 2019a). There still remain questions on intensive artificial selection. Which traits/genes control adaptability? Where were the traits/genes from? Why were adaptive traits/genes selected? These answers may impact global food security in the face of climate changes in the future (Lustenhouwer et al. 2018, Stuecker et al. 2018).

Author Contribution Statement

KF, HY, and RK envisaged the concept. HY and RK collected recent information on rice breeding programs. KF wrote the manuscript. KF, HY, and RK approved the final manuscript.

Acknowledgments

We thank members of rice breeding programs in Kamikawa Agricultural Experiment Station, Local Independent Administrative Agency Hokkaido Research Organization, and Hokkaido Agricultural Research Center, National Agricultural Research Organization.

Literature Cited

•  Ando,  I.,  H.  Sato,  N.  Aoki,  Y.  Suzuki,  H.  Hirabayashi,  M.  Kuroki,  H.  Shimizu,  T.  Ando and  Y.  Takeuchi (2010) Genetic analysis of the low-amylose characteristics of rice cultivars Oborozuki and Hokkai-PL9. Breed. Sci. 60: 187–194.
•  Asano,  K.,  T.  Takashi,  K.  Miura,  Q.  Qian,  H.  Kitano,  M.  Matsuoka and  M.  Ashikari (2007) Genetic and molecular analysis of utility of sd1 alleles in rice breeding. Breed. Sci. 57: 53–58.
•  Ashikari,  M.,  H.  Sakakibara,  S.  Lin,  T.  Yamamoto,  T.  Takashi,  A.  Nishimura,  E.R.  Angeles,  Q.  Qian,  H.  Kitano and  M.  Matsuoka (2005) Cytokinin oxidase regulates rice grain production. Science 309: 741–745.
•  Cai,  X.,  J.  Fan,  Z.  Jiang,  B.  Basso,  F.  Sala,  A.  Spada,  F.  Grassi and  B.-R.  Lu (2013) The puzzle of Italian rice origin and evolution: determining genetic divergence and affinity of rice germplasm from Italy and Asia. PLoS ONE 8: e80351.
•  Chakhonkaen,  S.,  K.  Pitnjam,  W.  Saisuk,  K.  Ukoskit and  A.  Muangprom (2012) Genetic structure of Thai rice and rice accessions obtained from the International Rice Research Institute. Rice (N Y) 5: 19.
•  Choi,  J.Y.,  A.E.  Platts,  D.Q.  Fuller,  Y.I.  Hsing,  R.A.  Wing and  M.D.  Purugganan (2017) The rice paradox: multiple origins but single domestication in Asian rice. Mol. Biol. Evol. 34: 969–979.
•  Cobb,  J.N.,  P.S.  Biswas and  J.D.  Platten (2018) Back to the future: revisiting MAS as a tool for modern plant breeding. Theor. Appl. Genet. 132: 647–667.
•  Costanzo,  S. and  Y.  Jia (2010) Sequence variation at the rice blast resistance gene Pi-km locus: Implications for the development of allele specific markers. Plant Sci. 178: 523–530.
•  Courtois,  B.,  J.  Frouin,  R.  Greco,  G.  Bruschi,  G.  Droc,  C.  Hamelin,  M.  Ruiz,  G.  Clément,  J.C.  Evrard,  S.  Van Coppenole et al. (2012) Genetic diversity and population structure in a European collection of rice. Crop Sci. 52: 1663–1675.
•  Das,  G.,  J.K.  Patra and  K.H.  Baek (2017) Insight into MAS: a molecular tool for development of stress resistant and quality of rice through gene stacking. Front. Plant Sci. 8: 985.
•  Dwivedi,  S.L.,  S.  Ceccarelli,  M.W.  Blair,  H.D.  Upadhyaya,  A.K.  Are and  R.  Ortiz (2016) Landrace germplasm for improving yield and abiotic stress adaptation. Trends Plant Sci. 21: 31–42.
•  Dwivedi,  S.L.,  A.  Scheben,  D.  Edwards,  C.  Spillane and  R.  Ortiz (2017) Assessing and exploiting functional diversity in germplasm pools to enhance abiotic stress adaptation and yield in cereals and food legumes. Front. Plant Sci. 8: 1461.
•  Ebana,  K.,  Y.  Kojima,  S.  Fukuoka,  T.  Nagamine and  M.  Kawase (2008) Development of mini core collection of Japanese rice landrace. Breed. Sci. 58: 281–291.
•  Fu,  Y.-B. (2015) Understanding crop genetic diversity under modern plant breeding. Theor. Appl. Genet. 128: 2131–2142.
•  Fujino,  K.,  H.  Sekiguchi,  T.  Sato,  H.  Kiuchi,  Y.  Nonoue,  Y.  Takeuchi,  T.  Ando,  S.Y.  Lin and  M.  Yano (2004) Mapping of quantitative trait loci controlling low-temperature germinability in rice (Oryza sativa L.). Theor. Appl. Genet. 108: 794–799.
•  Fujino,  K.,  H.  Sekiguchi,  Y.  Matsuda,  K.  Sugimoto,  K.  Ono and  M.  Yano (2008) Molecular identification of a major quantitative trait locus, qLTG3-1, controlling low-temperature germinability in rice. Proc. Natl. Acad. Sci. USA 105: 12623–12628.
•  Fujino,  K. and  N.  Iwata (2011) Selection for low-temperature germinability on the short arm of chromosome 3 in rice cultivars adapted to Hokkaido, Japan. Theor. Appl. Genet. 123: 1089–1097.
•  Fujino,  K.,  U.  Yamanouchi and  M.  Yano (2013) Roles of the Hd5 gene controlling heading date for adaptation to the northern limits of rice cultivation. Theor. Appl. Genet. 126: 611–618.
•  Fujino,  K.,  M.  Obara,  T.  Ikegaya and  K.  Tamura (2015) Genetic shift in local rice populations during rice breeding programs in the northern limit of rice cultivation in the world. Theor. Appl. Genet. 128: 1739–1746.
•  Fujino,  K.,  T.  Nishimura,  H.  Kiuchi,  Y.  Hirayama and  T.  Sato (2017) Phenotypic changes during 100-year rice breeding programs in Hokkaido. Breed. Sci. 67: 528–534.
•  Fujino,  K.,  M.  Obara and  T.  Ikegaya (2019a) Establishment of adaptability to the northern-limit of rice production. Mol. Genet. Genomics 294: 729–737.
•  Fujino,  K.,  U.  Yamanouchi,  Y.  Nonoue,  M.  Obara and  M.  Yano (2019b) Switching genetic effects of the flowering time gene Hd1 in LD conditions by Ghd7 and OsPRR37 in rice. Breed. Sci. 69: 127–132.
•  Fujino,  K.,  Y.  Hirayama,  M.  Obara and  T.  Ikegaya (2019c) Introgression of the chromosomal region with the Pi-cd locus from Oryza meridionalis into O. sativa L. during rice domestication. Theor. Appl. Genet. 132: 1981–1990.
•  Fukuoka,  S.,  N.V.  Alpatyeva,  K.  Ebana,  N.T.  Luu and  T.  Nagamine (2003) Analysis of Vietnamese rice germplasm provides an insight into Japonica rice differentiation. Plant Breed 122: 497–502.
•  Fukuoka,  S.,  N.  Saka,  H.  Koga,  K.  Ono,  T.  Shimizu,  K.  Ebana,  N.  Hayashi,  A.  Takahashi,  H.  Hirochika,  K.  Okuno et al. (2009) Loss of function of a proline-containing protein confers durable disease resistance in rice. Science 325: 998–1001.
•  Fukuoka,  S.,  S.  Yamamoto,  R.  Mizobuchi,  U.  Yamanouchi,  K.  Ono,  N.  Kitazawa,  N.  Yasuda,  Y.  Fujita,  T.  Thi Thanh Nguyen,  S.  Koizumi et al. (2014) Multiple functional polymorphisms in a single disease resistance gene in rice enhance durable resistance to blast. Sci. Rep. 4: 4550.
•  Fuller,  D.Q. (2011) Pathways to Asian civilizations: tracing the origins and spread of rice and rice cultures. Rice 4: 78–92.
•  Giarrocco,  L.E.,  M.A.  Marassi and  G.L.  Salerno (2007) Assessment, the genetic diversity in Argentina rice cultivars with SSR markers. Crop Sci. 47: 853–858.
•  Guo,  X.,  D.  Liu and  K.  Chong (2018) Cold signaling in plants: Insights into mechanisms and regulation. J. Integr. Plant Biol. 60: 745–756.
•  Hayano-Saito,  Y.,  K.  Saito,  S.  Nakamura,  S.  Kawasaki and  M.  Iwasaki (2000) Fine physical mapping of the rice stripe resistance gene locus, Stv-bi. Theor. Appl. Genet. 101: 59–63.
•  Hayashi,  N.,  H.  Inoue,  T.  Kato,  T.  Funao,  M.  Shirota,  T.  Shimizu,  H.  Kanamori,  H.  Yamane,  Y.  Hayano-Saito,  T.  Matsumoto et al. (2010) Durable panicle blast-resistance gene Pb1 encodes an atypical CC-NBS-LRR protein and was generated by acquiring a promoter through local genome duplication. Plant J. 64: 498–510.
•  Huang,  X.,  N.  Kurata,  X.  Wei,  Z.X.  Wang,  A.  Wang,  Q.  Zhao,  Y.  Zhao,  K.  Liu,  H.  Lu,  W.  Li et al. (2012) A map of rice genome variation reveals the origin of cultivated rice. Nature 490: 497–501.
•  Iwata,  N.,  H.  Shinada,  H.  Kiuchi,  T.  Sato and  K.  Fujino (2010) Mapping of QTLs controlling seedling establishment using a direct seedling method in rice. Breed. Sci. 60: 353–360.
•  Jayamani,  M.P.,  S.  Negrão,  M.  Martins,  B.  Maçãs and  M.M.  Oliveira (2007) Genetic relatedness of Portuguese rice accessions from diverse origins as assessed by microsatellite markers. Crop Sci. 47: 879–884.
•  Jha,  U.C.,  A.  Bohra and  R.  Jha (2017) Breeding approaches and genomics technologies to increase crop yield under low-temperature stress. Plant Cell Rep. 36: 1–35.
•  Kim,  T.-S.,  Q.  He,  K.-W.  Kim,  M.-Y.  Yoon,  W.-H.  Ra,  F.P.  Li,  W.  Tong,  J.  Yu,  W.H.  Oo,  B.  Choi et al. (2016) Genome-wide resequencing of KRICE_CORE reveals their potential for future breeding, as well as functional and evolutionary studies in the post-genomic era. BMC Genomics 17: 408.
•  Koo,  B.H.,  S.C.  Yoo,  J.W.  Park,  C.T.  Kwon,  B.D.  Lee,  G.  An,  Z.  Zhang,  J.  Li,  Z.  Li and  N.C.  Paek (2013) Natural variation in OsPRR37 regulates heading date and contributes to rice cultivation at a wide range of latitudes. Mol. Plant 6: 1877–1888.
•  Kuroki,  M.,  K.  Saito,  S.  Matsuba,  N.  Yokogami,  H.  Shimizu,  I.  Ando and  Y.  Sato (2007) A quantitative trait locus for cold tolerance at the booting stage on rice chromosome 8. Theor. Appl. Genet. 115: 593–600.
•  Li,  X.,  Q.  Qian,  Z.  Fu,  Y.  Wang,  G.  Xiong,  D.  Zeng,  X.  Wang,  X.  Liu,  S.  Teng,  H.  Fujimoto et al. (2003) Control of tillering in rice. Nature 422: 618–621.
•  Liang,  W.H.,  F.  Shang,  Q.T.  Lin,  C.  Lou and  J.  Zhang (2014) Tillering and panicle branching genes in rice. Gene 537: 1–5.
•  Liu,  X.,  Q.  Yang,  F.  Lin,  L.  Hua,  C.  Wang,  L.  Wang and  Q.  Pan (2007) Identification and fine mapping of Pi39(t), a major gene conferring the broad-spectrum resistance to Magnaporthe oryzae. Mol. Genet. Genomics 278: 403–410.
•  Louwaars,  N.P. (2018) Plant breeding and diversity: A troubled relationship? Euphytica 214: 114.
•  Lu,  H.,  M.A.  Redus,  J.R.  Coburn,  J.N.  Rutger,  S.R.  McCouch and  T.H.  Tai (2005) Population structure and breeding patterns of 145 U.S. rice cultivars based on SSR marker analysis. Crop Sci. 45: 66–76.
•  Lustenhouwer,  N.,  R.A.  Wilschut,  J.L.  Williams,  W.H.  van der Putten and  J.M.  Levine (2018) Rapid evolution of phenology during range expansion with recent climate change. Glob. Chang. Biol. 24: e534–e544.
•  Lv,  Y.,  Z.  Guo,  X.  Li,  H.  Ye,  X.  Li and  L.  Xiong (2016) New insights into the genetic basis of natural chilling and cold shock tolerance in rice by genome-wide association analysis. Plant Cell Environ. 39: 556–570.
•  Nguyen,  T.T.,  S.  Koizumi,  T.N.  La,  K.S.  Zenbayashi,  T.  Ashizawa,  N.  Yasuda,  I.  Imazaki and  A.  Miyasaka (2006) Pi35(t), a new gene conferring partial resistance to leaf blast in the rice cultivar Hokkai 188. Theor. Appl. Genet. 113: 697–704.
•  Okamoto,  K.,  N.  Aoki,  H.  Fujii,  T.  Yanagihara,  A.  Nishi,  H.  Satoh and  T.  Umemoto (2013) Characterization and utilization of spontaneous deficiency in starch branching enzyme I of rice (Oryza sativa L.). J. Appl. Glycosci. 60: 53–60.
•  Orn,  C.,  R.  Shishido,  M.  Akimoto,  R.  Ishikawa,  T.M.  Htun,  K.-I.  Nonomura,  Y.  Koide,  M.  Sarom,  S.  Vang,  S.  Sophany et al. (2015) Evaluation of genetic variation among wild rice populations in Cambodia. Breed. Sci. 65: 430–437.
•  Reig-Valiente,  J.L.,  J.  Viruel,  E.  Sales,  L.  Marqués,  J.  Terol,  M.  Gut,  S.  Derdak,  M.  Talón and  C.  Domingo (2016) Genetic diversity and population structure of rice varieties cultivated in temperate regions. Rice (N Y) 9: 58.
•  Saito,  K.,  K.  Miura,  K.  Nagano,  Y.  Hayano-Saito,  H.  Araki and  A.  Kato (2001) Identification of two closely linked quantitative trait loci for cold tolerance on chromosome 4 of rice and their association with anther length. Theor. Appl. Genet. 103: 862–868.
•  Sato,  H.,  Y.  Suzuki,  M.  Sakai and  T.  Imbe (2002) Molecular characterization of Wx-mq, a novel mutant gene for low-amylose content in endosperm of rice (Oryza sativa L.). Breed. Sci. 52: 131–135.
•  Shinada,  H.,  N.  Iwata,  T.  Sato and  K.  Fujino (2013) Genetical and morphological characterization of cold tolerance at fertilization stage in rice. Breed. Sci. 63: 197–204.
•  Shinada,  H.,  T.  Yamamoto,  E.  Yamamoto,  K.  Hori,  J.  Yonemaru,  S.  Matsuba and  K.  Fujino (2014) Historical changes in population structure during rice breeding programs in the northern limits of rice cultivation. Theor. Appl. Genet. 127: 995–1004.
•  Shinada,  H.,  T.  Yamamoto,  E.  Yamamoto,  K.  Hori,  Y.  Hirayama,  T.  Maekawa,  H.  Kiuchi,  H.  Sato and  T.  Sato (2015a) Quantitative trait loci for whiteness of cooked rice detected in improved rice cultivars in Hokkaido. Breed. Sci. 65: 201–207.
•  Shinada,  H.,  T.  Yamamoto,  H.  Sato,  E.  Yamamoto,  K.  Hori,  J.  Yonemaru,  T.  Sato and  K.  Fujino (2015b) Quantitative trait loci for rice blast resistance detected in a local rice breeding population by genome-wide association mapping. Breed. Sci. 65: 388–395.
•  Stuecker,  M.F.,  M.  Tigchelaar and  M.B.  Kantar (2018) Climate variability impacts on rice production in the Philippines. PLoS ONE 13: e0201426.
•  Takamiya,  H. (2001) Introductory routes of rice to Japan: an examination of the southern route hypothesis. Asian Perspectives 40: 209–226.
•  Takemoto-Kuno,  Y.,  H.  Mitsueda,  K.  Suzuki,  H.  Hirabayashi,  O.  Ideta,  N.  Aoki,  T.  Umemoto,  T.  Ishii,  I.  Ando,  H.  Kato et al. (2015) qAC2, a novel QTL that interacts with Wx and controls the low amylose content in rice (Oryza sativa L.). Theor. Appl. Genet. 128: 563–573.
•  Terashima,  T.,  S.  Fukuoka,  N.  Saka and  S.  Kudo (2008) Mapping of a blast field resistance gene Pi39(t) of elite rice strain Chubu 111. Plant Breed. 127: 485–489.
•  Thomson,  M.J.,  E.M.  Septiningsih,  F.  Suwardjo,  T.J.  Santoso,  T.S.  Silitonga and  S.R.  McCouch (2007) Genetic diversity analysis of traditional and improved Indonesian rice (Oryza sativa L.) germplasm using microsatellite markers. Theor. Appl. Genet. 114: 559–568.
•  Uga,  Y.,  K.  Sugimoto,  S.  Ogawa,  J.  Rane,  M.  Ishitani,  N.  Hara,  Y.  Kitomi,  Y.  Inukai,  K.  Ono,  N.  Kanno et al. (2013) Control of root system architecture by DEEPER ROOTING 1 increases rice yield under drought conditions. Nat. Genet. 45: 1097–1102.
•  Wang,  J.,  T.  Jiang,  D.  Zou,  H.  Zhao,  Q.  Li,  H.  Liu and  C.  Zhou (2014) Genetic diversity and genetic relationships of japonica rice varieties in Northeast Asia based on SSR markers. Biotechnol. Biotechnol. Equip. 28: 230–237.
•  Wang,  L.,  S.  Sun,  J.  Jin,  D.  Fu,  X.  Yang,  X.  Weng,  C.  Xu,  X.  Li,  J.  Xiao and  Q.  Zhang (2015) Coordinated regulation of vegetative and reproductive branching in rice. Proc. Natl. Acad. Sci. USA 112: 15504–15509.
•  Wang,  W.,  R.  Mauleon,  Z.  Hu,  D.  Chebotarov,  S.  Tai,  Z.  Wu,  M.  Li,  T.  Zheng,  R.R.  Fuentes,  F.  Zhang et al. (2018) Genomic variation in 3,010 diverse accessions of Asian cultivated rice. Nature 557: 43–49.
•  Wang,  Y. and  J.  Li (2008) Molecular basis of plant architecture. Ann. Rev. Plant Biol. 59: 253–279.
•  Wei,  X.,  J.  Xu,  H.  Guo,  L.  Jiang,  S.  Chen,  C.  Yu,  Z.  Zhou,  P.  Hu,  H.  Zhai and  J.  Wan (2010) DTH8 suppresses flowering in rice, influencing plant height and yield potential simultaneously. Plant Physiol. 153: 1747–1758.
•  Xiao,  N.,  Y.  Gao,  H.  Qian,  Q.  Gao,  Y.  Wu,  D.  Zhang,  X.  Zhang,  L.  Yu,  Y.  Li,  C.  Pan et al. (2018) Identification of genes related to cold tolerance and a functional allele that confers cold tolerance. Plant Physiol. 177: 1108–1123.
•  Xing,  Z.,  F.  Tan,  P.  Hua,  L.  Sun,  G.  Xu and  Q.  Zhang (2002) Characterization of the main effects, epistatic effects and their environmental interactions of QTLs on the genetic basis of yield traits in rice. Theor. Appl. Genet. 105: 248–257.
•  Xue,  W.,  Y.  Xing,  X.  Weng,  Y.  Zhao,  W.  Tang,  L.  Wang,  H.  Zhou,  S.  Yu,  C.  Xu,  X.  Li et al. (2008) Natural variation in Ghd7 is an important regulator of heading date and yield potential in rice. Nat. Genet. 40: 761–767.
•  Yamamoto,  T.,  H.  Nagasaki,  J.  Yonemaru,  K.  Ebana,  M.  Nakajima,  T.  Shibaya and  M.  Yano (2010) Fine definition of the pedigree haplotypes of closely related rice cultivars by means of genome-wide discovery of single-nucleotide polymorphisms. BMC Genomics 11: 267.
•  Yamanaka,  S.,  I.  Nakamura,  K.N.  Watanabe and  Y.  Sato (2004) Identification of SNPs in the waxy gene among glutinous rice cultivars and their evolutionary significance during the domestication process of rice. Theor. Appl. Genet. 108: 1200–1204.
•  Yang,  J.,  X.  Zhao,  K.  Cheng,  H.  Du,  Y.  Ouyang,  J.  Chen,  S.  Qiu,  J.  Huang,  Y.  Jiang,  L.  Jiang et al. (2012) A killer-protector system regulates both hybrid sterility and segregation distortion in rice. Science 337: 1336–1340.
•  Yano,  M.,  Y.  Katayose,  M.  Ashikari,  U.  Yamanouchi,  L.  Monna,  T.  Fuse,  T.  Baba,  K.  Yamamoto,  Y.  Umehara,  Y.  Nagamura 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: 2473–2484.
•  Yokoo,  M. and  F.  Kikuchi (1977) Multiple allelism of the locus controlling heading time of rice, detected using the close linkage with blast-resistance. Japan. J. Breed. 27: 123–130.
•  Yokoo,  M.,  F.  Kikuchi,  A.  Nakane and  H.  Fujimaki (1980) Genetical analysis of heading date by means of close linkage with blast, resistance in rice. Bull. Natl. Inst. Agric. Sci. Ser. D 31: 95–126.
•  Yonemaru,  J.,  T.  Yamamoto,  K.  Ebana,  E.  Yamamoto,  H.  Nagasaki,  T.  Shibaya and  M.  Yano (2012) Genome-wide haplotype changes produced by artificial selection during modern rice breeding in Japan. PLoS ONE 7: e32982.
•  Zhang,  J.,  L.-L.  Chen,  F.  Xing,  D.A.  Kudrna,  W.  Yao,  D.  Copetti,  T.  Mu,  W.  Li,  J.-M.  Song,  W.  Xie et al. (2016) Extensive sequence divergence between the reference genomes of two elite indica rice varieties Zhenshan 97 and Minghui 63. Proc. Natl. Acad. Sci. USA 113: E5163–E5171.
•  Zhao,  J.,  S.  Zhang,  J.  Dong,  T.  Yang,  X.  Mao,  Q.  Liu,  X.  Wang and  B.  Liu (2017) A novel functional gene associated with cold tolerance at the seedling stage in rice. Plant Biotechnol. J. 15: 1141–1148.
•  Zhou,  D.,  W.  Chen,  Z.  Lin,  H.  Chen,  C.  Wang,  H.  Li,  R.  Yu,  F.  Zhang,  G.  Zhen,  J.  Yi et al. (2016) Pedigree-based analysis of derivation of genome segments of an elite rice reveals key regions during its breeding. Plant Biotechnol. J. 14: 638–648.
•  Zhou,  Y.,  Y.  Tao,  Y.  Yuan,  Y.  Zhang,  J.  Miao,  R.  Zhang,  C.  Yi,  Z.  Gong,  Z.  Yang and  G.  Liang (2018) Characterisation of a novel quantitative trait locus, GN4-1, for grain number and yield in rice (Oryza sativa L.). Theor. Appl. Genet. 131: 637–648.