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Identification of Rice Mutants with Altered Grain Alkali Digestion Trait
Plant Breed. Biotech. 2020;8:19-27
Published online March 1, 2020
© 2020 Korean Society of Breeding Science.

HyunJung Kim1†, Ralph Vin B. Imatong1, Thomas H. Tai1,2*

1Department of Plant Sciences, University of California, Davis, CA 95616, USA
2USDA-ARS Crops Pathology and Genetics Research Unit, Davis, CA 95616, USA
Corresponding author: *Thomas H. Tai,, Tel: +1-530-752-4342, Fax: +1-530-754-7195
Present Address: LG Chem, Ltd. E6 Block LG Science Park, 30 Magokjungang 10-ro, Gangseo-gu, Seoul, 07796, Korea
Received September 26, 2019; Revised November 13, 2019; Accepted January 10, 2020.
This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Gelatinization temperature (GT) is an important component of eating and cooking quality (ECQ) of rice. While direct measurement of GT is cumbersome, the alkali spreading value (ASV) test is a robust method commonly used to rapidly identify different GT types. In this study, we employed a modified ASV assay to screen a population of chemically-induced rice (cv. Kitaake) mutants (n = 405). Two mutant families, KDS-1623B and KDS-1824B, with significantly lower ASV (higher GT type) than wild type Kitaake (low GT type) were isolated. A nonsynonymous homozygous mutation in the isoamylase-type starch debranching enzyme gene ISA1 was identified in KDS-1623B. The mutation (G2709T) is predicted to change a valine at position 354 to a leucine in the α-amylase catalytic domain of ISA1. This result is consistent with the shrunken endosperm exhibited by KDS-1623B grains and the replacement of starch with phytoglycogen in isa1 (sugary-1) mutants. The altered ASV trait in KDS-1824B appears to be controlled by a single recessive mutation; however, the causal genetic lesion remains to be determined. These mutants will be useful resources for elucidating the complex nature of starch metabolism and its influence on ECQ of rice.
Keywords : Induced mutation, Alkali spreading value, Eating and cooking quality, Targeted exon capture, Next-generation sequencing, Rice (Oryza sativa L.)

Rice (Oryza sativa L.) is unique among the major cereals as almost the entire crop is used directly for human consumption in the form of whole milled kernels. As such, the eating and cooking qualities (ECQs) of rice grains, which consist mainly of starch (∼90%), are critical to consumers. Rice starch is comprised of amylopectin and amylose, extensively branched and long unbranched polysaccharides, whose chemical and physical properties are the major determinants of ECQs (Umemoto et al. 2008; Tian et al. 2009). While apparent amylose content (AAC) is the most important factor affecting ECQ of rice grains (Umemoto et al. 2008; Tian et al. 2009), differences in ECQ observed among varieties with similar AAC point towards the role of other starch properties (Pang et al. 2016).

Pasting viscosity, gel consistency (GC), and gelatinization temperature (GT) are examples of other significant factors affecting ECQ of milled rice grains (Pang et al. 2016; Wang et al. 2019). GT is the critical temperature at which about 90% of rice starch gelatinizes or transforms from a semicrystalline structure to a gel-like, edible form (Waters et al. 2006; Gao et al. 2011). GT influences cooking time and the texture of cooked and cool cooked rice, making it an important ECQ factor (Waters et al. 2006). While GT can be determined directly using differential scanning calorimetry (Umemoto et al. 2008), it is typically estimated using the alkali spreading or digestion value (ASV, ADV) which is determined by the degree of dispersal or disintegration of whole milled rice grains incubated in a dilute alkali solution (Little et al. 1958). Rice grains that have low, intermediate, and high GT exhibit complete disintegration, partial dispersal, and very little or no change in morphology. The ASV test has been widely used in rice breeding programs due to the ease and simplicity of the assay compared to direct determination of GT (Tian et al. 2005).

Using the ASV assay, the involvement of the rice starch biosynthesis genes in controlling GT was established with the genetic mapping of a major gene, ALK, to the same locus on chromosome 6 as the starch synthase IIa (SSIIa, also known as SSII-3) gene, which affects amylopection structure (Umemoto et al. 2002) followed by the confirmation of this as the ALK gene by map-based cloning (Gao et al. 2003). Further characterization of the ALK gene alleles from rice varieties of various GT types revealed a number of functional single nucleotide polymorphisms, which could be used to classify varieties (Umemoto et al. 2004; Nakamura et al. 2005; Umemoto and Aoki 2005; Bao et al. 2006; Waters et al. 2006; Yu et al. 2010). In addition to the SSIIa/ALK gene, about twenty QTLs affecting GT, have been mapped onto chromosomes of 1, 2, 5, 6, 7, 8, 10, 11 and 12 (Wang et al. 2019).

In this study, we screened a temperate japonica (cv. Kitaake) M2 mutant population (n = 405) derived from chemical seed mutagenesis using an ASV assay to identify lines exhibiting altered alkali spreading/digestion trait in milled rice grains. Four M2 mutant families derived from three independently mutagenized M1 plants (KDS-1623B, 1824B, 1835B and 1835C) were identified which showed significantly lower ASV than wild type Kitaake. Two of the mutant lines (KDS-1623B and 1824B) appeared to be homozygous (fixed) for the mutant phenotype in the M3 generation and were subjected to further characterization. While both mutations were determined to be recessive, the brown rice grains of the KDS-1623B mutant were significantly smaller and thinner than wild type and appeared similar to the previously described sugary-1 phenotype (Nakamura et al. 1997; Kubo et al. 1999; Kawagoe et al. 2005; Kubo et al. 2005). Using an in-solution target enrichment approach in conjunction with next-generation sequencing, a single nonsynonymous mutation, a G→T transversion at nucleotide 2709, was found in ISA1, an isoamylase-type starch debranching enzyme involved in biosynthesis of amylopectin, which was consistent with the sugary-1 appearance of the KDS-1623B grains and their resistance to alkali digestion (Kubo et al. 1999, 2005; Chao et al. 2019).


Plant materials, alkali digestion assay, and grain phenotyping

Screening for rice mutants with altered alkali spreading value (ASV) or alkali digestion trait was performed using a population derived from sodium azide seed mutagenesis of the temperate japonica variety Kitaake (Monson-Miller et al. 2012). A total of 405 M2 families, representing 235 independently mutagenized M1 plants, were screened using a modified alkali digestion assay. In brief, ten M3 seeds from each family were manually husked and milled for 15 seconds in a laboratory grain polisher (Pearlest, Kett US, Villa Park, CA, USA). For initial screening, three milled grains from each line were placed in a 5 mL (35 mm × 10 mm) plastic petri dish with 4 mL of freshly prepared 1.7% potassium hydroxide [KOH]. Grains were incubated at 20°C for 23 hours before visual evaluation as described by Little et al. (1958). The California long grain rice variety A-202, intermediate gelatinization temperature (GT) type, and wild type Kitaake, low GT type, were included as controls. Lines exhibiting possible altered ASV in the initial screen were re-tested in the same manner to confirm phenotypes. Representative samples of brown rice grains (n = 20) from two Kitaake, KDS-1623B, and KDS-1824B plants grown under standard greenhouse conditions (Orchard Park greenhouse complex, Department of Plant Sciences, University of California, Davis) were prepared by manual husking and the grain length, width, and weight were measured. Length and width were determined using a VIBE QM3 Rice Analyzer (Burlingame, CA, USA). Individual grains were weighed, and the means and standard deviations were calculated, and one-way analysis of variance (ANOVA) and Bonferroni-corrected posthoc t-tests were performed using MS Excel 2016.

Exon capture, sequencing, and data analysis

Exon capture was performed using the MYbaits® platform (MYcroarray, Ann Arbor, MI, USA). A capture reagent consisting of 19,748 custom biotinylated RNA probes (i.e. baits) with about 2.85X tiling density was designed and generated by MYcroarray (now Arbor Biosciences) from a set of 321 rice genes that were selected to cover various biosynthetic pathways and gene families of interest to our research program (Kim and Tai 2019). The gene set included starch biosynthesis genes (Kharabian-Masouleh et al. 2011), glutathione transferases (Jain et al. 2010), phytic acid biosynthesis genes (Kim and Tai 2014), microtubule cytoskeleton genes (Guo et al. 2009), ATP-binding cassette (ABC) transporter genes (Nguyen et al. 2014), and Glossy1-like (GL1-like) genes (Islam et al. 2009). Exon capture and sequencing was performed on three wild type controls (Nipponbare, Kitaake, and Sabine) and nine mutants (Kim and Tai 2019). Of the mutants, four were wet leaf/glossy (i.e., wax crystal-sparseless leaf, wsl) mutants (Tai 2015; Kim and Tai 2019) and five grain quality mutants in the Kitaake (four including KDS-1623B) and Nipponbare (one) backgrounds. As described previously, DNA samples were extracted from one month-old seedlings of M4 generation mutants and wild-type lines, quantified, and one mg of genomic DNA from each sample was sheared by sonication to an average fragment size of 300 bp. Genomic libraries were constructed using a KAPA HyperPlus Kit (KAPA Biosystems, Wilmington, MA, USA) and equal amounts of the 12 libraries were pooled and subjected to in-solution target enrichment using the MYbaits® kit.

Sequencing of the captured libraries was performed using the Illumina HiSeq2500 (3% of a lane; SR50 run) and HiSeq4000 (5% of a lane; PE150 run) platforms. Candidate mutations were detected using the Mutation and Polymorphism Survey tool with parameter 10 threads, minimum of 6 libraries, minimum coverage of 20, maximum coverage of 2000 (Henry et al. 2014). Protein effect was determined based on the Oryza sativa ssp. japonica cv. Nipponbare pseudomolecules (MSU version 7.0) using Geneious v9.1.5 (; Kearse et al. 2012). Novelty of the mutations was based on a search of a 32 Mb single nucleotide polymorphism (SNP) dataset from the IRRI 3,000 Rice Genomes Project sequence information without any threshold (Alexandrov et al. 2014; Mansueto et al. 2017). Information on protein families and transmembrane regions was predicted using Pfam 31.0 ( and TMHMM (Krogh et al. 2001), respectively, and implemented by the Rice Genome Annotation Project server (

Validation of KDS-1623B mutation and segregation analysis

The putative candidate mutation identified by exon capture and next-generation sequencing were validated by Sanger sequencing of PCR products spanning those mutations. Sanger sequencing was also used to confirm the F1 of crosses made between mutants (M4 generation) and with wild type Kitaake. Given the relationship of the sugary-1 grain type and the altered ASV, the KDS-1623B/Kitaake F2 population was scored by visual evaluation of the brown rice morphology. For genotyping of the mapping population, genomic DNA samples were extracted from the F2 seedlings using a DNeasy®96 Plant Kit. The DNAs were subjected to PCR with primers (5ʹ-AGTTGATGCCCTG CCATGAA-3ʹ and 5ʹ-TCCCTGTAGGCACAAACACC-3ʹ) which amplified a 1,085 bp containing the ISA1 SNP generated in the KDS-1623B mutant. PCR reactions and conditions used for amplifying DNA fragments for sequencing were as previously described (Kim and Tai 2014). PCR products were purified using the Agencourt Ampure® XP magnetic beads (Beckman Coulter Genomics, Danvers, MA, USA) and Sanger sequencing was performed by the College of Biological Sciences UCDNA Sequencing Facility at UC Davis. Sequence data alignment and analysis were performed using Geneious v9.1.5. Segregation ratios were subjected to Pearson’s c2 test for goodness-of-fit.

Preliminary genetic analysis of KDS-1824B mutant

Reciprocal crosses between the KDS-1824B mutant and the wild type progenitor variety Kitaake were performed to examine the mode of inheritance of its altered alkali digestion trait. Approximately 100 F2 seeds from a single F1 plant of each cross were husked using a laboratory rice sheller (TR200; Kett US, Villa Park, CA, USA) and then milled using a Pearlest grain polisher for 1 minute. Single milled F2 grains (n = 48) for each F1 were placed in individual wells of a 24 well culture plate (MP Biomedicals LLC, Solon, OH, USA) and each well was filled with 1 mL of freshly prepared 1.7% KOH solution. Plates were incubated at 30°C for 23 hours before visual evaluation (Supplementary Fig. S1). The segregation ratio of wild type to mutant ASV was subjected to Pearson’s c2 test for goodness-of-fit to the single recessive gene mode of inheritance.


Identification mutants with altered alkali digestion

In order to identify rice mutants with altered grain quality phenotypes, a modified alkali digestion assay (i.e. alkali spreading value [ASV] test) was employed to screen a population of Kitaake rice mutants derived from sodium azide mutagenesis. Initial screening was performed by evaluating the digestion of three milled M3 grains from each of 405 M2 families, representing 235 independently mutagenized M1 plants. Preliminary evaluation of Kitaake, the progenitor wild type variety of the mutant population, revealed similar ASV (low gelatinization temperature [GT] type) at both 20°C and 30°C and the initial screening was performed at the lower temperature for convenience. Grain appearance and digestion was visually rated as described by Little et al. (1958). Under the conditions of the modified alkali digestion test, Kitaake was typically rated as low GT type (ASV score between 6 and 7) and the intermediate GT type California long grain variety A-202 was rated as high/high-intermediate (ASV score of 2 and above but below 3), likely due to the lower temperature at which the screen was conducted.

Preliminary evaluation resulted in the identification of 42 M2 families with putative altered alkali digestion compared to Kitaake based on the ASV score and differences in grain appearance. Of these 42 families, the milled grains of 32 families exhibited heterogeneous digestion phenotypes while those of 10 families were uniform in their appearance after the digestion with 1.7% KOH. Among the 10 families, two were rated as exhibiting a higher ASV than Kitaake (ASV = 7) and were derived from the same M1 individual (KDS-1578A and KDS-1578C). The remaining eight lines appeared to have lower ASV ratings and less disintegration than Kitaake. Of these lines, two were most clearly distinct from Kitaake. KDS-1623B milled grains exhibiting no apparent change in shape (ASV = 2) and KDS-1824B milled grains exhibiting a high-intermediate/intermediate GT type (ASV = 3.7) (1). A phenotype similar to KDS-1824B was observed among two lines exhibiting heterogeneous digestion, KDS-1835B and KDS-1835C, which are derived from the same M1 individual (Supplementary Fig. S2). These results were consistent with homozygous mutations in KDS-1623B and KDS-1824B and heterozygous mutations in the sibling M2 lines KDS-1835B and KDS-1835C underlying the altered alkali digestion trait observed in these lines. Following confirmation of the initial observed phenotypes for these mutant lines by testing additional M3 milled grains, KDS-1623B and KDS-1824B were selected for further genetic analysis due to the likelihood that the underlying mutations in these lines were homozygous.

Seed morphology and grain weight of low ASV mutants

Visual evaluation of representative brown rice grains from Kitaake and the KDS-1623B and KDS-1824B mutants indicated that the grains from the two mutants are smaller than the wild type (Fig. 2). For each genotype, twenty randomly selected seeds from two representative plants (n = 40) were dehulled and grain widths, lengths, and weights were measured and the means and standard deviations (SD) determined (Table 1). Statistically significant differences were detected among the group means for each of the traits using one-way ANOVA (P <0.01). Posthoc t-tests (Bonferroni-corrected P<0.003) indicated that Kitaake and KDS-1824B grain widths were significantly different from KDS-1623B but not from each other. With regard to grain length and weight, all three genotypes were significantly different from each other. The KDS-1623B mutant grain weighed less than half that of Kitaake and had the same shrunken appearance as the sugary-1 mutant (Kubo et al. 1999, 2005). In these mutants, the endosperm starch is completely replaced by phytoglycogen resulting in a characteristic lack of iodine staining of sugary-1 grains (Kubo et al. 1999; Kawagoe et al. 2005; Kubo et al. 2005). This effect was confirmed in the KDS-1623B grain whereas iodine staining of the KDS-1824B grain was comparable to Kitaake (T. Tai, data not shown).

Exon capture and sequencing

As we reported previously, an in-solution target enrichment and next generation sequencing approach was employed using the MYbaits® platform in order to examine the utility of targeted exon capture and sequencing for identifying candidate mutations (Kim and Tai 2019). Custom biotinylated RNA probes were designed from 321 genes of interest including sixteen involved in starch biosynthesis (Kharabian-Masouleh et al. 2011). Based on the appearance of the seed and the altered alkali digestion trait, the KDS-1623B was among five grain quality mutants that were subjected to this approach (Kim and Tai 2019). Results of the targeted sequencing strategy for the KDS-1623B mutant and the wild-type progenitor cultivar Kitaake are shown in Table 2. Approximately 103 million sequencing reads were “on target” (i.e., covering the baits used for enrichment) for both KDS-1623B and Kitaake, representing about 65X coverage of the coding regions (i.e. exons) of the genes from which the baits were designed.

Single nonsynonymous homozygous point mutations were detected in three genes in the KDS-1623B mutant (Table 2). One of these genes is ISA1 (LOC _Os08g40930), which encodes an isoamylase-type starch debranching enzyme (Kubo et al. 1999; Kawagoe et al. 2005; Kubo et al. 2005; Chao et al. 2019). This mutation was validated by Sanger sequencing of the original DNA (M4 generation) used for exon capture and DNA from a M5 generation mutant. The ISA1 mutation detected in KDS-1623B, a transversion from G to T at position 2709 in the gene, is predicted to result in the substitution of a valine at position 354 with a leucine in the α-amylase catalytic domain of the protein (Fig. 3). The mutation was not found in any of the naturally-occurring alleles of ISA1 in the 3,000 Rice Genomes Project database (Alexandrov et al. 2014).

Genetic analysis of low ASV rice mutants

The inheritance of the low ASV mutant phenotypes was examined by performing crosses between the mutants and the wild-type progenitor Kitaake. In the case of crosses with KDS-1623B, M3 generation mutants were used as the female parents only because of their poor fertility. F1 seeds were obtained from crosses in which the KDS-1623B parent was sterile or low fertility. True F1 hybrids were confirmed by sequencing of the KDS-1623B mutant SNP. An F2 population (n = 122) from one F1, which was derived from a cross involving a sterile KDS-1623B maternal parent, was grown for genotyping by Sanger sequencing and to produce F3 sseeds for phenotypic evaluation. Of the 122 F2 plants, 85 produced seeds and 37 were sterile. These observed segregation ratios did not significantly deviate from those expected for a single gene recessive mutation conferring sterility (c2 = 1.847, df = 1, P = 0.174, not significant at P ≤ 0.01). Visual evaluation of brown rice grains (n ≈ 20) of those plants for which F3 seeds were available resulted in the identification of 35 lines with all normal (wild type ASV) grains, 44 lines segregating for the sugary-1 (low ASV) grains, and 6 lines with all sugary-1 (low ASV) grains. Sanger sequencing was performed to genotype the ISA1 mutant SNP in all 122 of the F2. Among the fertile plants, the SNP alleles segregated completely in agreement with the brown rice phenotypes (i.e. all 6 sugary-1 mutants had homozygous mutant T alleles for the SNP in ISA1, all 35 normal lines had homozygous wild-type G alleles, and all 44 lines with segregating grain phenotypes were heterozygous for the SNP). Of the 37 sterile F2 plants, 19 were homozygous for the wild-type G allele, 17 were heterozygous, and one was homozygous for the mutant T allele. The segregation ratios of the ISA1 SNP marker were significantly distorted (c2 = 36.21, df = 2, P < 0.00001, significant at P ≤ 0.01).

To further genetically characterize the KDS-1824B mutant, reciprocal crosses were made to Kitaake. F2 seeds (n = 48) were randomly selected from a representative F1 plant from each cross and the dehulled grains were phenotyped using the ASV assay resulting in the identification of 35 wild type (high ASV) and 13 mutant (low ASV) grains from the Kitaake/KDS-1824B F1 (segregation ratio of 2.7:1) and 36 wild type and 12 mutant from the KDS-1824B/Kitaake F1 (segregation ratio of 3:1). The segregation ratios observed from both populations were consistent with a single gene recessive mutation conferring the altered alkali digestion trait observed in KDS-1824B (c2 = 0.111, df = 1, P = 0.739, not significant at P ≤ 0.01; c2 = 0, df = 1, P = 1, not significant at P ≤ 0.01).


ECQ of rice is governed primarily by AAC and other physico-chemical properties of starch such as GC and GT (Pang et al. 2016; Wang et al. 2019). GT directly reflects the energy and time needed for cooking rice grains (Tian et al. 2005) and is related to the digestibility and taste of cooked rice (Kim and Kim 2016). Since the direct measurement of GT is not trivial, the alkali spreading value (ASV) as determined by the dispersal or disintegration and spread of milled rice grains in dilute alkali solution is commonly used instead as it is a much simpler and rapid way to evaluate rice GT type (Little et al. 1958; Tian et al. 2005). The ASV assay was employed to identify the first major gene (ALK) controlling GT in rice (He et al. 1999; Umemoto et al. 2002; Gao et al. 2003) as well as numerous GT QTLs (Wang et al. 2019). Most japonica varieties like Kitaake have lower GT due to three SNPs in the SSIIa (ALK) gene that significantly reduce SSIIa activity, leading to more amylopectin short chains with degree of polymerization (DP) ≤ 12 which are only able to form short double helical structures that do not require as much energy to transform (Miura et al. 2018).

In this study, we used a modified ASV assay to evaluate milled grains from M2 mutants derived from the low GT type rice variety Kitaake. Three M2 families exhibiting low ASV scores (i.e. higher GT type) compared to wild type Kitaake were identified, two of which appeared to be fixed (i.e. homozygous) for the mutant phenotype based on the uniform appearance and response of the milled grains to the dilute alkali solution (KDS-1623B and KDS-1824B). Exposure to the 1.7% KOH had almost no effect on the KDS-1623B grains which exhibited shrunken endosperms characteristic of the sugary-1 mutant (Kubo et al. 1999). In sugary-1 mutants the endosperm starch is replaced by phytoglycogen due to reduced activity of the isoamylase-type starch debranching enzyme encoded by ISA1 (Kubo et al. 1999; Kawagoe et al. 2005). This lack of starch is consistent with the low ASV phenotype of KDS-1623B. Identification of a missense mutation in the catalytic domain of ISA1 by targeted exon capture and sequencing and the complete association of this mutation with the shrunken endosperm/low ASV phenotype in and F2 mapping population (KDS-1623B/Kitaake) strongly supports the causal relationship of this mutation and the altered alkali digestion trait. Interestingly, a severe segregation distortion was observed in the F2 population, which was derived from a cross in which the maternal KDS-1623B parent was found to be sterile. The segregation distortion suggests that a closely linked mutation affects viability.

Milled grains of the KDS-1824B mutant exhibited ASV ratings corresponding to high intermediate/intermediate GT type. While the same average width as Kitaake, KDS-1824B brown rice grains were shorter and weighed about 13% less. Initial genetic analysis indicates that a single recessive gene mutation underlies the altered alkali digestion trait observed in this mutant and F2 populations are being grown for genotyping and phenotyping of F3 seeds. While the targeted exon capture and sequencing approach was successful in identifying the likely causal mutation in KDS-1623B, the KDS-1824B mutant was not included in this pilot experiment due to sample limitations (Kim and Tai 2019). Given the limited number of starch-related target genes included in the capture reagent, a mutation mapping approach (Abe et al. 2012) may be a more robust strategy considering the large number of QTLs identified for GT (Kim and Kim 2016; Wang et al. 2019).

Supplemental Materials

This work was supported by funds from USDA-ARS Agricultural Research Project 21000-2032-023-00D to T.H.T. We thank Sarah C. Magee for technical assistance and the Rice Experiment Station (Biggs, CA) for the use of their VIBE QM3 Rice Analyzer.

Mention of trade names or commercial products in this publication is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the U.S. Department of Agriculture. USDA is an equal opportunity provider and employer.


Dehulled grain width, length, and weight of wild type and low ASV mutantsz)

Accession Width (mm) Length (mm) Weight (mg)
Kitaake 3.13 ± 0.12a 5.08 ± 0.19a 22.58 ± 1.57a
KDS-1623B 2.75 ± 0.16b 4.74 ± 0.20b 9.58 ± 0.66b
KDS-1824B 3.15 ± 0.19a 4.47 ± 0.19c 19.02 ± 1.50c

z)Values shown are means ± SD of 40 seeds. Significant differences between mean values for each trait are indicated by different letters (Bonferroni-corrected posthoc t-test, P<0.003).

Homozygous nonsynonymous mutation detected in KDS-1623B by target enrichment and next generation sequencing.

Accession Readsz) (106) Coveragey) Gene Locus IDx) Mutationw) Effectv)
Kitaake 102.84 65.11 - - - -
KDS-1623B 103.47 65.51 ISA1 LOC_Os08g40930 G2709T V354L
OsABCB22 LOC_Os08g45030 C1213T A321V
OsGSTU50 LOC_Os10g38740 G1103A E149K

z)Total number of aligned reads on target.

y)Coverage on target (i.e., number of times target region covered by sequencing).

x)Locus identification from Oryza sativa ssp. japonica cv. Nipponbare pseudomolecules MSU version 7.0 (

w)Nucleotide base change and position in the genomic DNA from the start codon.

v)Predicted amino acid change and position in the protein.

  1. Abe A, Kosugi S, Yoshida K, Natsume S, Takagi H, Kanzaki H, et al. 2012. Genome sequencing reveals agronomically important loci in rice using MutMap. Nat. Biotechnol. 30: 174-178.
    Pubmed CrossRef
  2. Alexandrov N, Tai S, Wang W, Mansueto L, Palis K, Fuentes RR, et al. 2014. SNP-Seek database of SNPs derived from 3000 rice genomes. Nucleic Acids Res. 43: 1023-1027.
  3. Bao JS, Corke H, Sun M. 2006. Nucleotide diversity in starch synthase IIa and validation of single nucleotide polymorphisms in relation to starch gelatinization temperature and other physicochemical properties in rice (Oryza sativa L.). Theor. Appl. Genet. 113: 1171-1183.
    Pubmed CrossRef
  4. Chao S, Cai Y, Feng B, Jiao G, Sheng Z, Luo J, et al. 2019. Editing of rice isoamylase gene ISA1 provides insights into its function in starch formation. Rice Sci. 26: 77-87.
  5. Gao Z, Zeng D, Cheng F, Tian Z, Guo L, Su Y, et al. 2011. ALK, the key gene for gelatinization temperature is a modifier gene for gel consistency in rice. J. Integr. Plant Biol. 53: 756-765.
    Pubmed CrossRef
  6. Gao ZY, Zheng DL, Cui X, Zhou Y, Yan M, Huang D, et al. 2003. Map-based cloning of the ALK gene, which controls the gelatinization temperature of rice. Sci. China, C, Life Sci. 46: 661-668.
    Pubmed CrossRef
  7. Guo L, Ho CM, Kong Z, Lee YR, Qian Q, Liu B. 2009. Evaluating the microtubule cytoskeleton and its interacting proteins in monocots by mining the rice genome. Ann. Bot. 103: 387-402.
    Pubmed KoreaMed CrossRef
  8. He P, Li SG, Qian Q, Ma YQ, Li JZ, Wang WM, et al. 1999. Genetic analysis of rice grain quality. Theor. Appl. Genet. 98: 502-508.
  9. Henry IM, Nagalakshmi U, Lieberman MC, Ngo KJ, Krasileva KV, Vasquez-Gross H, et al. 2014. Efficient genome-wide detection and cataloging of EMS-induced mutations using exome capture and next-generation sequencing. Plant Cell 26: 1382-1397.
    Pubmed KoreaMed CrossRef
  10. Islam MA, Du H, Ning J, Ye H, Xiong L. 2009. Characterization of Glossy1-homologous genes in rice involved in leaf wax accumulation and drought resistance. Plant Mol. Biol. 70: 443-456.
    Pubmed CrossRef
  11. Jain M, Ghanashyam C, Bhattacharjee A. 2010. Comprehensive expression analysis suggests overlapping and specific roles of rice glutathione S-transferase genes during development and stress responses. BMC Genomics 11: 73.
    Pubmed KoreaMed CrossRef
  12. Kawagoe Y, Kubo A, Satoh H, Takaiwa F, Nakamura Y. 2005. Roles of isoamylase and ADP-glucose pyrophosphorylase in starch granule synthesis in rice endosperm. Plant J. 42: 164-174.
    Pubmed CrossRef
  13. Kearse M, Moir R, Wilson A, Stones-Havas S, Cheung M, Sturrock S, et al. 2012. Geneious Basic: an integrated and extendable desktop software platform for the organization and analysis of sequence data. Bioinformatics 28: 1647-1649.
    Pubmed KoreaMed CrossRef
  14. Kharabian-Masouleh A, Waters DL, Reinke RF, Henry RJ. 2011. Discovery of polymorphisms in starch-related genes in rice germplasm by amplification of pooled DNA and deeply parallel sequencing. Plant Biotechnol. J. 9: 1074-1085.
    Pubmed CrossRef
  15. Kim HY, Kim, K-M. 2016. Mapping of grain alkali digestion trait using a Cheongcheong/Nagdong doubled haploid population in rice. J. Plant Biotechnol. 43: 76-81.
  16. Kim S-I, Tai TH. 2014. Identification of novel rice low phytic acid mutations via TILLING by sequencing. Mol. Breed. 34: 1717-1729.
  17. Kim H, Tai TH. 2019. Identifying a candidate mutation underlying a reduced cuticle wax mutant of rice using targeted exon capture and sequencing. Plant Breed. Biotech. 7: 1-11.
  18. Krogh A, Larsson B, von Heijne, Sonnhammer EL. 2001. Predicting transmembrane protein topology with a hidden markov model: application to complete genomes. J. Mol. Biol. 305: 567-580.
    Pubmed CrossRef
  19. Kubo A, Fujita N, Harada K, Matsuda T, Satoh H, Nakamura Y. 1999. The starch-debranching enzymes isoamylase and pullulanase are both involved in amylopectin biosynthesis in rice endosperm. Plant Physiol. 121: 399-409.
    Pubmed KoreaMed CrossRef
  20. Kubo A, Rahman S, Utsumi Y, Li Z, Mukai Y, Yamamoto M, et al. 2005. Complementation of sugary-1 phenotype in rice endosperm with the wheat isoamylase1 gene supports a direct role for isoamylase1 in amylopectin biosynthesis. Plant Physiol. 137: 43-56.
    Pubmed KoreaMed CrossRef
  21. Little RR, Hilder GB, Dawson EH. 1958. Differential effect of dilute alkali on 25 varieties of milled rice. Cereal Chem. 35: 111-126.
  22. Mansueto L, Fuentes RR, Borja FN, Detras J, Abriol-Santos JM, Chebotarov D, et al. 2017. Rice SNP-seek database update: new SNPs, indels, and queries. Nucleic Acids Res. 45: D1075-D1081.
    Pubmed KoreaMed CrossRef
  23. Miura S, Crofts N, Saito Y, Hosaka Y, Oitome NF, Watanabe T, et al. 2018. Starch synthase IIa-deficient mutant rice line produces endosperm starch with lower gelatinization temperature than Japonica rice cultivars. Front. Plant Sci. 9: 645.
    Pubmed KoreaMed CrossRef
  24. Monson-Miller J, Sanchez-Mendez DC, Fass J, Henry IM, Tai TH, Comai L. 2012. Reference genome-independent assessment of mutation density using restriction enzyme-phased sequencing. BMC Genomics 13: 72.
    Pubmed KoreaMed CrossRef
  25. Nakamura Y, Kubo A, Shimamune T, Matsuda T, Harada K, Satoh H. 1997. Correlation between activities of starch debranching enzyme and α-polyglucan structure in endosperms of sugary-1 mutants of rice. Plant J. 12: 143-153.
  26. Nakamura Y, Francisco PB, Hosaka Y, Sato A, Sawada T, Kubo A, et al. 2005. Essential amino acids of starch synthase IIa differentiate amylopectin structure and starch quality between japonica and indica rice varieties. Plant Mol. Biol. 58: 213-227.
    Pubmed CrossRef
  27. Nguyen VNT, Moon S, Jung K-H. 2014. Genome-wide expression analysis of rice ABC transporter family across spatio-temporal samples and in response to abiotic stresses. J. Plant Physiol. 171: 1276-1288.
    Pubmed CrossRef
  28. Pang Y, Ali J, Wang X, Franje NJ, Revilleza JE, Xu J, et al. 2016. Relationship of rice grain amylose, gelatinization temperature and pasting properties for breeding better eating and cooking quality of rice varieties. PLoS One 11: e0168483.
    Pubmed KoreaMed CrossRef
  29. Tai TH. 2015. Identification and characterization of reduced epicuticular wax mutants in rice. Rice Sci. 22: 171-179.
  30. Tian R, Jiang G-H, Shen L-H, Wang L-Q, He Y-Q. 2005. Mapping quantitative trait loci underlying the cooking and eating quality of rice using a DH population. Mol. Breed. 15: 117-124.
  31. Tian Z, Qian Q, Liu Q, Yan M, Liu X, Yan C, et al. 2009. Allelic diversities in rice starch biosynthesis lead to a diverse array of rice eating and cooking qualities. Proc. Natl. Acad. Sci. U.S.A. 106: 21760-21765.
    Pubmed KoreaMed CrossRef
  32. Umemoto T, Yano M, Satoh H, Shomura A, Nakamura Y. 2002. Mapping of a gene responsible for the difference in amylopectin structure between japonica-type and indica-type rice varieties. Theor. Appl. Genet. 104: 1-8.
    Pubmed CrossRef
  33. Umemoto T, Aoki N, Lin HX, Nakamura Y, Inouchi N, Sato Y, et al. 2004. Natural variation in rice starch synthase IIa affects enzyme and starch properties. Funct. Plant Biol. 31: 671-684.
  34. Umemoto T, Aoki N. 2005. Single-nucleotide polymorphisms in rice starch synthase IIa that alter starch gelatinization and starch association of the enzyme. Funct. Plant Biol. 32: 763-768.
  35. Umemoto T, Horibata T, Aoki N, Hiratsuka M, Yano M, Inouchi N. 2008. Effects of variations in starch synthase on starch properties and eating quality of rice. Plant Prod. Sci. 11: 472-480.
  36. Wang H, Zhu S, Dang X, Liu E, Hu X, Eltahawy MS, et al. 2019. Favorable alleles mining for gelatinization temperature, gel consistency and amylose content in Oryza sativa by association mapping. BMC Genet. 20: 34.
    Pubmed KoreaMed CrossRef
  37. Waters DLE, Henry RJ, Reinke RF, Fitzgerald MA. 2006. Gelatinization temperature of rice explained by polymorphisms in starch synthase. Plant Biotechnol. J. 4: 115-122.
    Pubmed CrossRef
  38. Yu G, Olsen KM, Schaal BA. 2010. Association between nonsynonymous mutations of starch synthase IIa and starch quality in rice (Oryza sativa). New Phytol. 189: 593-601.
    Pubmed CrossRef

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