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Development of InDel markers for Oryza sativa ssp. javanica based on whole-genome resequencing

  • Weixiong Long ,

    Contributed equally to this work with: Weixiong Long, Yonghui Li, Zhengqing Yuan

    Roles Data curation, Funding acquisition, Methodology, Project administration, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing

    Affiliation Jiangxi Super-rice Research and Development Center, Jiangxi Academy of Agricultural Sciences, National Engineering Laboratory for Rice, Nanchang, China

  • Yonghui Li ,

    Contributed equally to this work with: Weixiong Long, Yonghui Li, Zhengqing Yuan

    Roles Formal analysis, Investigation, Software

    Affiliation Jiangxi Super-rice Research and Development Center, Jiangxi Academy of Agricultural Sciences, National Engineering Laboratory for Rice, Nanchang, China

  • Zhengqing Yuan ,

    Contributed equally to this work with: Weixiong Long, Yonghui Li, Zhengqing Yuan

    Roles Conceptualization, Methodology, Software, Writing – review & editing

    Affiliation State key Laboratory of Hybrid Rice, Wuhan University, Wuhan, China

  • Lihua Luo,

    Roles Investigation

    Affiliation Jiangxi Super-rice Research and Development Center, Jiangxi Academy of Agricultural Sciences, National Engineering Laboratory for Rice, Nanchang, China

  • Laiyang Luo,

    Roles Investigation

    Affiliation Jiangxi Super-rice Research and Development Center, Jiangxi Academy of Agricultural Sciences, National Engineering Laboratory for Rice, Nanchang, China

  • Weibiao Xu,

    Roles Investigation

    Affiliation Jiangxi Super-rice Research and Development Center, Jiangxi Academy of Agricultural Sciences, National Engineering Laboratory for Rice, Nanchang, China

  • Yaohui Cai,

    Roles Resources

    Affiliation Jiangxi Super-rice Research and Development Center, Jiangxi Academy of Agricultural Sciences, National Engineering Laboratory for Rice, Nanchang, China

  • Hongwei Xie

    Roles Conceptualization, Funding acquisition, Project administration, Resources, Validation

    xhw206@163.com

    Affiliation Jiangxi Super-rice Research and Development Center, Jiangxi Academy of Agricultural Sciences, National Engineering Laboratory for Rice, Nanchang, China

Abstract

Oryza sativa ssp. javanica rice varieties exhibit a wide variation in the phenotypes of several important agronomic traits, including grain quality, grain shape, plant architecture, disease resistance, and high adaption to an unfavorable environment, indicating a great potential for rice improvement. DNA molecular markers are basic and critical tools in genetic analysis and gene mining. However, only a few whole-genome variation analyses have been performed in Oryza sativa ssp. Javanica (tropical japonica rice), and this has hampered the utilization of such an important resource. In this study, the length of insertions/deletions variation greater larger than 10 bp from 10 Oryza sativa ssp. indica rice and 10 Oryza sativa ssp. tropical japonica rice were extracted by using the Nipponbare genome as a reference. A total of 118 primer pairs which were almost evenly distributed on each chromosome corresponding to the loci of InDels were designed by the Primer 5 program. We confirmed 85 InDel markers from 60 rice varieties, including indica and tropical japonica, by running polyacrylamide gels. The InDel markers function like SSRs in identifying hybrids, calculating genetic distance, constructing the genetic linkage map, and gene mining. The InDel markers developed in this study might help in genetic studies and to investigate the tropical japonica rice varieties.

Backgrounds

Oryza sativa spp. javanica, also known as tropical japonica rice, is famous for its late-maturation, tall stalk, long spikelet, large grains, wide and light green leaves, weak tillering ability, light photosensitivity, and poor shattering. It is widely distributed in Malaysia, Indonesia, the Philippines, and some other regions [1]. Compared to the traits of the indica and temperate japonica varieties, the javanica rice variety exhibits a wide variation in several important agronomic traits, such as high-temperature tolerance, lodging resistance, larger panicles and grains, well-developed root system, and resistance to rice blast. Hence, it might be regarded as a genetic resource for future rice improvement [24]. Furthermore, javanica rice might be utilized for heterosis and can be a resource for developing highly adaptable hybrid rice.

Breeding varieties with high-yield, high quality and high-combining abilities by hybridizing indica and japonica has become an important technical approach for utilizing the heterosis of the subspecies [57]. However, there are several problems in utilizing heterosis between the two subspecies, which include low seed setting rate, high plant height, low grain fullness, long heading date, and low ecological adaptability [8, 9]. Hybridization between indica-javanica and javanica-japonica can overcome the limitations of the indica-japonica hybrid [1012]. Previous studies have shown that the degree of heterosis in rice follows the order: indica-japonica > indica-javanica > japonica-javanica > indica-indica > japonica-japonica hybrid. Hence, it is important to understand the genetic variation in Oryza sativa ssp. javanica for further utilizing the heterosis of the subspecies.

DNA markers play an important role in genetic analysis and breeding programs, including estimating genetic diversity, construction of the evolutionary tree, population structure analysis, construction of genetic linkage maps, identification of QTLs, gene mining, molecular assisted breeding, and characterization of alien introgression of cultivar rice. To effectively utilize the DNA variation, three generations of DNA markers have been developed, which include restriction fragment length polymorphism (RFLP) by restriction enzyme digestion and hybridization with isotope-labeling [13], rapid amplified polymorphic DNA (RAPD) [14], cleaved amplified polymorphic sequence (CAPS) [15], simple sequence repeats [16], single nucleotide polymorphism (SNP), and insertion/deletion (InDel) markers [1720]. The first-generation DNA markers (RFLP) have rarely been used in plant genetics in recent years as it is time-consuming and pollutes the environment. The development of second-generation DNA markers such as SSRs are based on a variable number of short tandem repeats and the separation is based on polymerase chain reaction (PCR), followed by agarose or polyacrylamide gel electrophoresis. The characteristics such as codominance, easy readability, and the random and wide distribution of SSR markers have significantly contributed to genetic analysis, gene mapping, and marker assisted selection (MAS) in crops [21]. Owing to the development of re-sequencing technology, the third-generation DNA markers, including SNP and InDel, are applied based on single nucleotide polymorphism (SNP) and insertion/deletion variation in the whole genome [22]. These two kinds of markers are quite popular in plant genetic studies because they exhibit codominance, high density, and easy accessibility. However, genotyping with SNP markers is based on resequencing or SNP arrays, which is rarely conducted in most breeding institutions. Moreover, the validation of such SNP markers relies on restriction enzyme digestion and PCR-based gel electrophoretic separation [23]. Hence, SNP genotyping is widely used commercially since it takes a long time to obtain the data sets. The InDel markers are designed to amplify 150–350 bp DNA sequences and contain insertion/deletion sequences with variations greater than 10 bp that can be easily separated by agarose or polyacrylamide gel electrophoresis due to the presence of a large polymorphic region. A few genome-wide InDel markers have been developed to distinguish the two subspecies in O. sativa [20, 2426], but there are no reports on the development of InDel markers for discriminating the Oryza sativa ssp. javanica and Oryza sativa ssp. indica alleles. Therefore, it is important and urgent to develop a genome-wide InDel marker of Oryza sativa ssp. javanica rice.

In this study, we developed polyacrylamide-resolvable InDel markers by re-sequencing the whole genome of 10 indica rice varieties and 10 javanica rice varieties and identifying DNA sequence variations (insertion and deletion) in the two subspecies by comparing them with the reference genome sequence of the japonica rice variety Nipponbare. The development and characterization of these InDel markers depend greatly on the separation of their PCR products through polyacrylamide gel electrophoresis, determination of their polymorphism and genetic distance, and relationship of the javanica varieties. A total of 60 rice varieties, including 30 indica and 30 javanica varieties, were used to verify the accuracy and applicability of the InDel markers that were developed based on the variation. This study might provide polymorphic markers for indica and javanica and lay the foundation for research on heterosis between rice subspecies indica and javanica.

Materials and methods

Plant meterials

A total of 80 rice accessions, including 40 indica varieties and 40 javanica rice varieties, were analyzed. The indica rice varieties were collected from China and the javanica rice varieties were obtained from the International Rice Research Institute (IRRI). All the germplasms were planted in the Jiangxi Academy of Agricultural Sciences, Nanchang, China for the investigation of agronomic characters. We selected 10 representative accessions of indica and 10 japonica varieties for resequencing (S1 Table). The remaining 60 rice varieties were used to test the accuracy of the InDel primer pairs that we developed in this study (S2 Table). The 20 varieties resequencing data generated in this study were submitted to the National Genomic Data Center with the BioProject number PRJNA763248.

Mapping and characterization of InDel variation

The clean data of 20 rice varieties were generated from the raw data after a strict filtering process (Table 1). Then, the clean data of the 20 rice accessions were mapped on the Nipponbare reference genome using the BWA version and a BAM file was produced [27]. The Samtools software was used to sort the BAM file and the Picard software was used to remove the PCR duplicates [28]. The GATK pipeline was performed to detect the InDels for each sample and a vcf file was exported with InDel calls and quality [29]. To understand the function of the InDel variation, the vcf file was annotated using the snpEff software [30].

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Table 1. The re-sequencing information of 20 rice varieties.

https://doi.org/10.1371/journal.pone.0274418.t001

Extraction of InDel-flanking sequences and primer designing

To develop the InDel markers, a flanking sequence of 200 nucleotides on both sides of the InDel was extracted as the target sequence based on the Nipponbare reference by using Samtools. The design of the InDel primers was based on the following criteria: i) The primers for the InDel markers must be highly specific and should not match with other loci in the genome. ii) The PCR products of the InDel should be 150–300 bp long so that the polymorphism among the genotypes can be easily identified on a polyacrylamide gel or a 4% agarose gel. Next, the Primer 5 software was used to design the InDel primers [31]. The InDel primers had the following characteristics: the primers were 18–25 bp long, with an optimum length of 21 bp; the melting temperature, optimum temperature, GC content, and the optimum annealing temperature of the primers were 55 to 63°C, 58°C, 40% to 60%, and 48%, respectively. The designed InDel markers that were uniquely aligned to the reference genome were selected as the primers for further analysis.

PCR amplification

A total of 118 InDel markers, with almost 10 markers evenly distributed on each chromosome, were selected from the primers pairs designed with the custom scripts. A total of 60 rice varieties were used to examine the accuracy of these designed InDel markers. A total volume of 20 μL PCR reaction mix were used, which included approximately 10–100 ng of DNA template, 10 μL of 2 x PCR mix buffer, 1 μL of each primer (10 nM), and 13 μL of ddH2O. The PCR reaction was performed as follows: denaturation at 95°C for 5 min, 38 cycles of denaturation at 95°C for 20 s, annealing at 58°C for 20 s, extension at 72°C for 20 s, and a final extension at 25°C for 5 min. PCR amplification was conducted using a Thermal Cycler (Bio-rad).

Graphical mapping and validation of InDel markers

The chromosomal location of the InDel markers was obtained based on the genome annotation GFF3 files (accessed on 26 August 2021). The PCR products (1–3 μL) were used for electrophoresis on a 6% polyacrylamide gel, visualized, and recorded as a binary code (0/1) by silver staining using a gel imaging system (Yuejin Machinery Co. Ltd.). Only the InDel markers can easily distinguish the indica and javanica varieties were selected for further analysis.

Results

Identification and distribution of genome-wide InDels

High-quality clean reads of 368,645,134 and 423,297,832 were generated for the subspecies varieties of indica and tropical japonica, respectively (Table 1). A total of 372,946,555 reads for the indica group and 393,523,062 reads for the tropical japonica group were mapped at an average depth of 10 to the japonica Nipponbare reference genome. A total of 115,576 InDels and 33,456 InDels shared by the selected indica varieties and tropical japonica accessions, respectively, were identified (Fig 1). The number of InDels in tropical japonica on each chromosome ranged from 1,830 (Chr10) to 34,821 (Chr12), with the density ranging from 68.78 InDels/Mb (Chr11) to 104.93 InDels/Mb (Chr12) (Fig 2, S3 Table).

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Fig 1. Distribution of InDels in Oryza sativa ssp. indica and Oryza sativa spp. javanica on each chromosome with a window size of 100 kb.

The outermost circle represents 12 rice chromosomes; the middle circle represents the distribution of common InDels in the 10 indica rice varieties with Nipponbare as a reference; the innermost circle indicates the distribution of 10 javanica common InDels on each chromosome with a window size of 100 kb, orange line indicates the indica common InDel number per 100kb, cyan-blue line suggests the javanica common InDel number per 100kb.

https://doi.org/10.1371/journal.pone.0274418.g001

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Fig 2. The number and density of InDels in javanica rice varieties.

A: the common InDels identified on each chromosome from the 10 Oryza sativa ssp. javanica sequences with Nipponbare as a reference. B: the density of the InDels (n/Mb) of the 10 Oryza sativa ssp. javanica accessions.

https://doi.org/10.1371/journal.pone.0274418.g002

Based on the vcf file, an average of 5,613 InDels on each chromosome were generated by comparing the genotype of the indica group with the tropical japonica group (S4 Table). Additionally, the distribution of the InDel markers in the entire genome of the two groups of subspecies was also analyzed, the results indicated that the length of the identified InDels on each chromosome was approximately consistent with the length of the corresponding chromosome, except for those on Chr5 and Chr9. The highest number of InDels was mapped on chromosome 1 (12,625), while chromosome 10 exhibited the lowest number of InDels at 1,656. The average density of the InDels on the chromosomes of the two subspecies ranged from 79.36 InDels/Mb on chromosome 10 to 292.19 InDels/Mb on chromosome 9, with an average density of 176.37 InDels/Mb (S4 Table).

Development of InDel primers

To establish a high-quality InDel marker resource for discriminating the alleles between the indica and tropical japonica subspecies, certain precautions were taken while designing the InDel primers, which included (i) duplicated/repeat regions in the rice genome were avoided, (ii) InDels that were evenly distributed throughout the genome were selected, and (iii) the alleles could be separated through polyacrylamide gel electrophoresis. To improve the design efficiency of the InDel primers for the tropical japonica varieties, we retained the InDels that were shared by the tropical japonica varieties but absent in the indica group. The location of the InDel polymorphic between one subspecies and the reference genome was established, and the different genotypes of the two subspecies, irrespective of the genotype of the reference genome, were regarded as subspecies-specific InDels. Hence, the 200 tropical japonica-specific InDels distributed across the 12 chromosomes were selected for further development of PCR-based markers. The target sequence length of 400 nucleotides, which contained the corresponding insertion/deletion sites, were extracted as templates for primer designing. Considering the separation ability of electrophoresis, the InDels larger than 10 bp were further selected for primer designing. Then, Primer 5 was used to design PCR primers based on several parameters. A total of 118 InDel primers were successfully designed in this study. The name, location, variation, product length, and annealing temperature of the primers are listed in S5 Table.

Validation of the newly developed specific InDel markers

A set of 118 InDel markers that were almost evenly distributed on the 12 chromosomes were selected, and primers were designed for experimental validation (S5 Table). To determine the accuracy of the designed InDel markers by PCR, we amplified the genomic DNA of 20 samples selected from the two subspecies. Among these primers, 16 pairs were inefficiently amplified or did not include the target sequence from all the resequencing varieties, and hence, were not used for further analysis. Furthermore, 10 of these primers were found to lack polymorphism, with the same production length found in the two subspecies varieties. Seven pairs of primers showed polymorphism, which could not be used to distinguish the indica and tropical japonica rice accessions. The remaining 85 InDel primers can efficiently distinguished the subspecies varieties and served as markers for tropical japonica subspecies in the genetic analysis. To quickly refer to the tropical japonica InDel primers, we renamed them as “IJ” (derived from “Indica” and “Javanica”) and associated it with a number based on the location of the InDel on the chromosome (S6 Table). The InDel primers tightly linked function genes were also listed in S6 Table.

Application of InDel markers

In addition to the resequenced rice varieties, 60 rice accessions, including 30 indica and 30 tropical japonica varieties, were used to investigate polymorphism by using 85 tropical japonica-specific InDel primers. Among them, 13 InDel primers with more than two alleles could distinguish the tropical japonica group from the indica group and a few indica varieties harbored the tropical japonica alleles (Fig 3). Using polyacrylamide gel electrophoresis, 72 InDel primer pairs with two alleles were found to distinguish the two subspecies (Fig 4). The validation results showed that 85 (100%) InDels could distinguish the tropical japonica from the indica subspecies. We found that 84.52% of InDels were subspecies specific and could serve as an important source of marker for identifying the tropical japonica varieties and calculating the genetic map or genetic distance for developing a new population by hybridization between indica and tropical japonica. Additionally, chromosome 12 exhibited the lowest number of tropical japonica-specific InDel markers, while the highest number of tropical japonica-specific InDel markers was located on chromosome 4 (Fig 5).

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Fig 3. Four representative InDel markers show more than two alleles but can distinguish the two subspecies.

The 30 samples on the left and 30 samples on the right show the Oryza sativa ssp. javanica varieties and Oryza sativa ssp. indica accessions, respectively. The detailed information is presented in S2 Table.

https://doi.org/10.1371/journal.pone.0274418.g003

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Fig 4. Application of the newly developed InDel markers in 60 rice varieties, including each 30 indica and javanica accessions.

The 30 samples on the left (javanica) exhibited single bands different from the 30 samples on the right (indica).

https://doi.org/10.1371/journal.pone.0274418.g004

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Fig 5. The physical map of 85 available InDel markers.

The position of each marker is indicated on the reference genome (Nipponbare-IRGSP-1.0) with a horizontal bar.

https://doi.org/10.1371/journal.pone.0274418.g005

Discussion

Rice is a staple food for over 10 billion people, and increases in crop production is crucial to meet the demands of the growing global population. Climate change has threatened food security by reducing crop productivity. Geneticists and breeders are investigating wild rice and landraces for a solution. Tropical japonica preserved by local people has already provided the possibility for rice improvement and is recognized as a “genetic reservoir” for further improvement of elite rice varieties [32]. The rice germplasm of tropical japonica is highly valuable as it harbors superior alleles, rare alleles, and novel genes compared to that of the cultivated varieties [33, 34]. To utilize tropical japonica rice, the genome-wide DNA variation between tropical japonica and indica should be well-understood foremostly. However, previous studies on DNA polymorphism concentrated on the indica, japonica, and wild rice varieties [26, 35]. Based on the published reference sequences of indica (9311) and japonica (Nipponbare), 479,406 InDel regions were identified by comparing the sequences of the two genomes. However, only 108 InDel markers were available for further genetic analysis [20]. By using 1,767 rice resequencing data, 100 high polymorphic InDels were experimentally validated from the 2,329,544 identified regions [24]. A total of 133 polymorphic InDel markers, validated from 506 InDel markers developed based on published sequences of the rice genome, were used to construct the genetic map of indica and japonica [36]. Based on two indica rice genomes and one japonica rice genome, 19,937 large InDel markers (30–55 bp) were extracted and 346 markers exhibited polymorphism from 22 cultivars [25]. Additionally, a few sets of genome-wide markers were developed in wild rice. A total of 94 InDel markers for O. officinalis were developed based on the bacterial artificial chromosome (BAC) end sequences. Twenty-two InDel markers were developed to discriminate all genotypes in the genus Oryza by using 12 Oryza species, which included 102 wild rice accessions [37]. Recently, 541 InDel markers were developed to discriminate the cultivars and AA-genome wild rice by positional multiple sequence alignments among five AA-genome species with four rice varieties [26]. Our study was the first time to provide tropical japonica-specific primers for breeding by investigating genome-wide InDels compared to indica with Nippobare as the reference.

Previously, InDels were developed to discriminate between subspecies or species mainly based on two varieties. To accurately determine the polymorphism between the subspecies of indica and tropical japonica, 20 varieties, including 10 indica with polymorphic phenotypes and 10 javanica with a wide global distribution, were selected for resequencing in this study. To resolve the PCR products on polyacrylamide gels, only those InDel variations that were larger than 10 bp and PCR products that were 100–300 bp were selected, which reduced the number of available InDels. Ten InDel primers from each chromosome were selected to investigate the polymorphism in another 60 varieties, including indica and tropical japonica. Seven of these varieties had more than two alleles but the alleles could not be used to discriminate the two subspecies due to the presence of some repeat sequences in both subspecies. Thirteen of them exhibited more than two alleles that could discriminate the two subspecies and probably resulted in heterozygosity. A few samples of indica showed two alleles in the 85 tropical japonica-specific InDel markers. These results indicated that the indica show more sequence duplication or gene family expansion than the corresponding region to the InDel marker production in javanica group.

In this study, we obtained 92 polymorphic primers for the subspecies of indica and tropical japonica. Using 85 of the 92 markers, we developed markers that could discriminate the indica and tropical japonica varieties. As we can see in the S6 Table, many grain shape related genes was overlapped with our development InDel markers. For example, a QTL for grain length, OsLG3, which encodes MADS-box transcription factor 1 (OsMADS1) were mapped from Oryza javanica [38]. Haplotypes and introgression regions revealed that the long-grain allele of OsLG3b might have arisen after domestication of tropical japonica and spread to subspecies indica or temperate japonica by natural crossing and artificial selection. Grain shape related gene TGW2 was identified through Fst and selective sweep analysis, which suggested the differentiation of TGW2 may contributed to the grain width polymorphism between javanica and indica subspecies [39]. Furthermore, GL7/GW7 encodes a protein homologous to Arabidopsis thaliana LONGIFOLIA proteins, which regulated longitudinal cell elongation was identified from Oryza javanica by using a genome-wide association analysis [40]. Interestingly, a tandem duplication of 17.1-kb segment at the GL7 locus leads to upregulation of GL7 and downregulation of its nearby negative regulator. Different natural and artificial selection during the evolution history resulted in the structural variation, including copy number variation, presence and absence variation, and inversion between javanica and inidca subspecies. These return to give opportunity for us to exploit the huge diversity to improve rice breeding.

To obtain the QTL/gene from Oryza javanica, segregated population from hybrids of javanica subspecies and other cultivar rice subspecies should be constructed. The labor-saving and economic-saving method to construct the population depending on the efficiency of distinguishing the true hybrids. What’s more, these InDel markers can easily be utilized by most of rice breeders with general equipment. The genome-wide InDel markers in both indica and tropical japonica in this study can facilitate marker-assisted breeding and functional gene mining.

Supporting information

S1 Table. The information of the 60 tested varieties which including 30 Oryza sativa ssp. Indica and 30 Oryza sativa ssp. Javanica.

This file is in the tab delimited format and can be open using the software Excel.

https://doi.org/10.1371/journal.pone.0274418.s001

(XLSX)

S2 Table. The information of the 20 sequenced varieties which including 10 Oryza sativa ssp. indica and 10 Oryza sativa ssp. javanica.

This file is in the tab delimited format and can be open using the software Excel.

https://doi.org/10.1371/journal.pone.0274418.s002

(XLSX)

S3 Table. The total InDels number and InDels density (number per Mb) on each chromosome of the two subspecies.

This file is in the tab delimited format and can be open using the software Excel.

https://doi.org/10.1371/journal.pone.0274418.s003

(XLSX)

S4 Table. The group common Indels number and Indels density (number per Mb) on each chromosome within the two subspecies.

This file is in the tab delimited format and can be open using the software Excel.

https://doi.org/10.1371/journal.pone.0274418.s004

(XLSX)

S5 Table. The detailed information of primers used in this study.

This file is in the tab delimited format and can be open using the software Excel.

https://doi.org/10.1371/journal.pone.0274418.s005

(XLSX)

S6 Table. The renames, location, corresponding to designed primers number, and the tightly linked function genes of the 85 available markers.

https://doi.org/10.1371/journal.pone.0274418.s006

(XLSX)

Acknowledgments

We thanks Ms. Sun Tong, and Mr. Liu Yue from State Key Laboratory of Hybrid Rice, college of life science, Wuhan university for assistance with common Indels between Oryza sativa ssp. javanica and Oryza sativa ssp. indica rice analysis.

References

  1. 1. Khush G.S. Origin, dispersal, cultivation and variation of rice. Plant Mol Biol 1997, 35, 25–34. pmid:9291957
  2. 2. Wang G.L.; Mackill D.J.; Bonman J.M.; McCouch S.R.; Champoux M.C.; Nelson R.J. RFLP mapping of genes conferring complete and partial resistance to blast in a durably resistant rice cultivar. Genetics 1994, 136, 1421–1434. pmid:7912216
  3. 3. Fujita D.; Trijatmiko K.R.; Tagle A.G.; Sapasap M.V.; Koide Y.; Sasaki K.; et al. NAL1 allele from a rice landrace greatly increases yield in modern indica cultivars. Proc Natl Acad Sci U S A 2013, 110, 20431–20436, pmid:24297875
  4. 4. Hsieh J.-s. Hsing Y.-i.C.; Hsu T.-f.; Li P.J.-k.; Li K.-t.; Tsang C.-h. Studies on Ancient Rice—Where Botanists, Agronomists, Archeologists, Linguists, and Ethnologists Meet. Rice 2011, 4, 178–183,
  5. 5. Zhang G.-q. Prospects of utilization of inter-subspecific heterosis between indica and japonica rice. Journal of Integrative Agriculture 2020, 19, 1–10,
  6. 6. Shukla S.K.; Pandey M.P. Combining ability and heterosis over environments for yield and yield components in two-line hybrids involving thermosensitive genic male sterile lines in rice (Oryza sativa L.). Plant Breeding 2007, 0, 070915221117002-???,
  7. 7. Zhou H.; Xia D.; Zeng J.; Jiang G.; He Y. Dissecting combining ability effect in a rice NCII-III population provides insights into heterosis in indica-japonica cross. Rice (N Y) 2017, 10, 39, pmid:28853048
  8. 8. Lin S.Y.; Ikehashi H.; Yanagihara S.; Kawashima A. Segregation distortion via male gametes in hybrids between Indica and Japonica or wide-compatibility varieties of rice (Oryza sativa L). Theor Appl Genet 1992, 84, 812–818, pmid:24201479
  9. 9. Zheng W.; Ma Z.; Zhao M.; Xiao M.; Zhao J.; Wang C.; et al. Research and Development Strategies for Hybrid japonica Rice. Rice (N Y) 2020, 13, 36, pmid:32514748
  10. 10. Peng S.; Khush G.S.; Virk P.; Tang Q.; Zou Y. Progress in ideotype breeding to increase rice yield potential. Field Crops Research 2008, 108, 32–38,
  11. 11. Lu Chuangen Z.J. Practice and Thought on Developing Hybrid Rice for Super High Yield by Exploiting Inter-subspecific Heterosis. Rice Science 2005, 1, 1–6.
  12. 12. Peng S., K.G.C S.S. Virmani J. Sheehy G.S. Khush . Yield Potential Trends of Tropical Rice since the Release of IR8 and the Challenge of Increaseing Rice Yield Potential. Crop Science 1999, 1552–1550.
  13. 13. McCouch S.R.; Kochert G.; Yu Z.H.; Wang Z.Y.; Khush G.S.; Coffman W.R.; et al. Molecular mapping of rice chromosomes. Theor Appl Genet 1988, 76, 815–829, pmid:24232389
  14. 14. Reiter R.S.; Williams J.G.; Feldmann K.A.; Rafalski J.A.; Tingey S.V.; Scolnik P.A. Global and local genome mapping in Arabidopsis thaliana by using recombinant inbred lines and random amplified polymorphic DNAs. Proc Natl Acad Sci U S A 1992, 89, 1477–1481, pmid:1346933
  15. 15. Lowe A.J.; Russell J.R.; Powell W.; Dawson I.K. Identification and characterization of nuclear, cleaved amplified polymorphic sequence (CAPS) loci in Irvingia gabonensis and I. wombolu, indigenous fruit trees of west and central Africa. Mol Ecol 1998, 7, 1786–1788, pmid:9859211
  16. 16. Nagaoka T., Y O. Applicability of inter-simple sequence repeat polymorphisms in wheat for use as DNA markers in comparison to RFLP and RAPD markers. Theor Appl Genet 1996, 597–602.
  17. 17. Kim N.S.; Park N.I.; Kim S.H.; Kim S.T.; Han S.S.; Kang K.Y. Isolation of TC/AG repeat microsatellite sequences for fingerprinting rice blast fungus and their possible horizontal transfer to plant species. Mol Cells 2000, 10, 127–134, pmid:10850652
  18. 18. Hayashi K.; Yoshida H.; Ashikawa I. Development of PCR-based allele-specific and InDel marker sets for nine rice blast resistance genes. Theor Appl Genet 2006, 113, 251–260, pmid:16791691
  19. 19. Kenneth L. McNally K.L.C., Regiona Bohnert, Rebecca Davidson M, Keyan Zhao, Victor J. Ulat , et al. Genomewide SNP variation reveals relationships among landraces and modern varieties of rice. Proceeding of the National Academy of Sciences of the United States of America 2009, 30, 12273–12278.
  20. 20. Shen Y.J.; Jiang H.; Jin J.P.; Zhang Z.B.; Xi B.; He Y.Y.; et al. Development of genome-wide DNA polymorphism database for map-based cloning of rice genes. Plant Physiol 2004, 135, 1198–1205, pmid:15266053
  21. 21. Akagi H.; Yokozeki Y.; Inagaki A.; Fujimura T. Microsatellite DNA markers for rice chromosomes. Theor Appl Genet 1996, 93, 1071–1077, pmid:24162483
  22. 22. Feltus F.A.; Wan J.; Schulze S.R.; Estill J.C.; Jiang N.; Paterson A.H. An SNP resource for rice genetics and breeding based on subspecies indica and japonica genome alignments. Genome Res 2004, 14, 1812–1819, pmid:15342564
  23. 23. Yanagisawa T.; Kiribuchi-Otobe C.; Hirano H.; Suzuki Y.; Fujita M. Detection of single nucleotide polymorphism (SNP) controlling the waxy character in wheat by using a derived cleaved amplified polymorphic sequence (dCAPS) marker. Theor Appl Genet 2003, 107, 84–88, pmid:12669198
  24. 24. Liu J.; Li J.; Qu J.; Yan S. Development of Genome-Wide Insertion and Deletion Polymorphism Markers from Next-Generation Sequencing Data in Rice. Rice (N Y) 2015, 8, 63, pmid:26271787
  25. 25. Hu W.; Zhou T.; Wang P.; Wang B.; Song J.; Han Z.; et al. Development of Whole-Genome Agarose-Resolvable LInDel Markers in Rice. Rice (N Y) 2020, 13, 1, pmid:31907673
  26. 26. Hechanova S.L.; Bhattarai K.; Simon E.V.; Clave G.; Karunarathne P.; Ahn E.K.; et al. Development of a genome-wide InDel marker set for allele discrimination between rice (Oryza sativa) and the other seven AA-genome Oryza species. Sci Rep 2021, 11, 8962, pmid:33903715
  27. 27. Li H.; Durbin R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 2009, 25, 1754–1760, pmid:19451168
  28. 28. Li H.; Handsaker B.; Wysoker A.; Fennell T.; Ruan J.; Homer N.; et al. Genome Project Data Processing, S. The Sequence Alignment/Map format and SAMtools. Bioinformatics 2009, 25, 2078–2079, pmid:19505943
  29. 29. McKenna A.; Hanna M.; Banks E.; Sivachenko A.; Cibulskis K.; Kernytsky A.; et al. The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res 2010, 20, 1297–1303, pmid:20644199
  30. 30. Cingolani P.; Platts A.; Wang le L.; Coon M.; Nguyen T.; Wang L.; et al. A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w1118; iso-2; iso-3. Fly (Austin) 2012, 6, 80–92, pmid:22728672
  31. 31. Singh V.K.; Mangalam A.K.; Dwivedi S.; Naik S. Primer premier: program for design of degenerate primers from a protein sequence. Biotechniques 1998, 24, 318–319, pmid:9494736
  32. 32. Mackill D.J. Classifying Japonica Rice Cultivars with RAPD Markers. Crop Science 1995, 35, 889–894.
  33. 33. Konishi S.; Ebana K.; Izawa T. Inference of the japonica rice domestication process from the distribution of six functional nucleotide polymorphisms of domestication-related genes in various landraces and modern cultivars. Plant Cell Physiol 2008, 49, 1283–1293, pmid:18701522
  34. 34. Oikawa T.; Maeda H.; Oguchi T.; Yamaguchi T.; Tanabe N.; Ebana K.; et al. The Birth of a Black Rice Gene and Its Local Spread by Introgression. Plant Cell 2015, 27, 2401–2414, pmid:26362607
  35. 35. Das S.; Upadhyaya H.D.; Srivastava R.; Bajaj D.; Gowda C.L.; Sharma S.; et al. Genome-wide insertion-deletion (InDel) marker discovery and genotyping for genomics-assisted breeding applications in chickpea. DNA Res 2015, 22, 377–386, pmid:26385353
  36. 36. Wu D.-H.; Wu H.-P.; Wang C.-S.; Tseng H.-Y.; Hwu K.-K. Genome-wide InDel marker system for application in rice breeding and mapping studies. Euphytica 2013, 192, 131–143,
  37. 37. Yamaki S.; Ohyanagi H.; Yamasaki M.; Eiguchi M.; Miyabayashi T.; Kubo T.; et al. Development of INDEL markers to discriminate all genome types rapidly in the genus Oryza. Breed Sci 2013, 63, 246–254, pmid:24273419
  38. 38. Yu J.; Miao J.; Zhang Z.; Xiong H.; Zhu X.; Sun X.; et al. Alternative splicing of OsLG3b controls grain length and yield in japonica rice. Plant Biotechnol J 2018, pmid:29479793
  39. 39. Long W.X.; Luo L.H.; Luo L.Y.; Xu W.B.; Li Y.H.; Cai Y.H.; et al. Whole Genome Resequencing of 20 Accessions of Rice Landraces Reveals Javanica Genomic Structure Variation and Allelic Genotypes of a Grain Weight Gene TGW2. Frontiers in Plant Science 2022, 13, pmid:35548287
  40. 40. Wang Y.X.; Xiong G.S.; Hu J.; Jiang L.; Yu H.; Xu J.; et al. Copy number variation at the GL7 locus contributes to grain size diversity in rice. Nature Genetics 2015, 47, 944, pmid:26147619