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Article

Dissection and Fine-Mapping of Two QTL Controlling Grain Size Linked in a 515.6-kb Region on Chromosome 10 of Rice

1
Jiangxi Early-Season Rice Research Centre, China National Rice Research Institute, Hangzhou 310006, China
2
College of Life and Environmental Sciences, Hangzhou Normal University, Hangzhou 310012, China
3
State Key Laboratory of Rice Biology and Breeding, China National Rice Research Institute, Hangzhou 310006, China
*
Authors to whom correspondence should be addressed.
These authors contributed equally to this work.
Plants 2024, 13(15), 2054; https://doi.org/10.3390/plants13152054
Submission received: 19 June 2024 / Revised: 13 July 2024 / Accepted: 24 July 2024 / Published: 25 July 2024
(This article belongs to the Special Issue Rice Genetics and Molecular Design Breeding)

Abstract

:
Grain size is a primary determinant of grain weight, which is one of the three essential components of rice grain yield. Mining the genes that control grain size plays an important role in analyzing the regulation mechanism of grain size and improving grain appearance quality. In this study, two closely linked quantitative trait loci (QTL) controlling grain size, were dissected and fine-mapped in a 515.6-kb region on the long arm of chromosome 10 by using six near isogenic line populations. One of them, qGS10.2, which controlled 1000 grain weight (TGW) and grain width (GW), was delimited into a 68.1-kb region containing 14 annotated genes. The Teqing allele increased TGW and GW by 0.17 g and 0.011 mm with the R2 of 12.7% and 11.8%, respectively. The other one, qGL10.2, which controlled grain length (GL), was delimited into a 137.3-kb region containing 22 annotated genes. The IRBB52 allele increased GL by 0.018 mm with the R2 of 6.8%. Identification of these two QTL provides candidate regions for cloning of grain size genes.

1. Introduction

Grain size is a primary determinant of grain weight, which is one of the three essential components of rice grain yield. Additionally, grain size is also a trait for grain appearance quality that rice breeders pay attention to, because the rice consumers in many countries prefer slender rice. Mining the genes that control grain size plays an important role in analyzing the regulation mechanism of grain size and improving grain appearance quality.
To date, causal genes for 28 QTL controlling grain size have been cloned [1,2,3,4], including genes for 1000-grain weight (TGW) such as qTGW1.2b [4], TGW2 [5], qTGW3/GL3.3 [6,7] and TGW6 [8]; genes for grain length (GL) such as GS3 [9], GSA1 [10], GL3.1/qGL3 [11,12], qGL5 [13] and GL6 [14]; and genes for grain width (GW) such as GW2 [15], GW5/GSE5 [16,17], GW6 [18] and GW8 [19]. These cloned QTL have been found to be involved in several signal pathways regulating cell elongation and proliferation, such as plant hormone signaling, G-protein signaling, ubiquitin-proteasome pathway, and a range of transcriptional regulators. Eleven of them, GS2/GL2 [20,21], GL3.1/qGL3 [11,12], GS3.1 [22], GSW3 [3], qTGW3/GL3.3 [6,7], GS5 [23], GW5/GSE5 [16,17], qGL5 [13], GW6 [18], TGW6 [8] and GW10 [24], encoded components of Brassinosteroid, Gibberellin and Auxin signaling pathways. Ten of them, OsLG3 [25], SG3 [26], OsLG3b/qLGY3 [27,28], GW6a [29], GL6 [14], GL7/GW7 [30,31], GLW7 [32], GW8 [19], GS9/GL9 [33,34] and qTGW10-20.8/qGL10/GL10 [35,36,37], encoded transcriptional regulatory factors. Two of them, GW2 [15] and GS3 [9], were involved in the ubiquitin-proteasome and G-protein signaling pathways, respectively. One of them, GSA1 [10], regulating grain size and abiotic stress tolerance, was involved in metabolic flux redirection. The remaining four, qTGW1.2b [4], OsPUB3 [38,39], TGW2 [5] and GSE9 [3], were not clear about the regulatory pathways involved at present. These studies have gradually elucidated the regulatory pathways of rice grain size, providing valuable references for mining new genes and unraveling regulatory mechanisms.
Although there were many QTL cloned for grain size, their proportion was still very low compared to the number of QTL that have been primary mapped. According to statistics, a total of 568 QTL for grain size were collected in Gramene database (https://archive.gramene.org/qtl/, accessed on 15 April 2024), and only 4.9% of them were cloned. The reason was that most of these cloned QTL show major effects and were easy to be isolated and cloned. However, the genetic effects of most QTL for grain size were small, and the phenotype was easily disturbed by environment and background genes, which made it difficult for fine-mapping and gene functional complementation verification. Nonetheless, based on quantitative genetics theory and modern molecular mapping results, minor-effect QTL also played important roles in regulating important agronomic traits in rice, whether in mechanism analysis or breeding applications [40], these QTL cannot be ignored.
In our previous study, a minor-effect QTL for controlling TGW and GW, qGS10.2, was located in the region RM3123–RM6673 on the long arm of chromosome 10 by using five near isogenic line (NIL) populations derived from the cross between indica rice varieties Teqing (TQ) and IRBB52 [41]. In this study, the genetic effect of qGS10.2 on grain size was further validated by using six NIL populations. Finally, two closely linked QTL controlling grain size, were dissected and fine-mapped in a 515.6-kb region. qGS10.2, which controlled TGW and GW, was delimited into a 68.1-kb region. qGL10.2, which controlled GL, was delimited into a 137.3-kb region.

2. Results

2.1. Validation of qGS10.2

One F12:13 NIL population carrying the heterozygous region Te21873–Te22365, W1, was firstly used to validate the genetic effect of qGS10.2. As illustrated in Figure 1, it consisted of 28 NIL-TQ homozygous lines and 28 NIL-IRBB52 homozygous lines in the segregating region, derived from an F11 plant of the rice cross TQ/IRBB52. At maturity, three traits, TGW, GL and GW, were measured.
Two genotypic groups were used as two series to plot the frequency distributions of the three traits. For TGW and GW, the NIL-TQ lines concentrated in the high-value area, and the NIL-IRBB52 lines concentrated in the low-value area (Figure 2A,C). These results suggested that QTL for TGW and GW was segregated in W1 with the enhancing allele derived from TQ.
Two-way analysis of variance (ANOVA) was performed to test the phenotypic differences in W1 population. The analysis was performed using the statistical analysis software SAS [42]. A mixed model GENOTYPE + LINE (GENOTYPE) + REP + GENOTYPE*REP was applied, in which LINE (GENOTYPE) was defined as a random effect and used as the error term to test GENOTYPE differences. When significant differences were detected (p < 0.05), the additive effect was estimated by (IRBB52–TQ)/2. Positive values indicate that the increasing allele from IRBB52, and negative values indicate that the increasing allele from TQ. As shown in Table 1, highly significant effects were detected for TGW and GW. The TQ allele increased TGW and GW by 0.14 g and 0.011 mm with the R2 of 6.6% and 8.1%, respectively. The results indicated that qGS10.2 was segregated in the region flanked by markers Te21852 and Te22367 (Figure 3A), corresponding to a 531.6-kb region in the Nipponbare genome.

2.2. Dissection and Fine-Mapping of qGS10.2

Five F15:16 NIL populations, heterozygous in Te21873–Te21927, Te21873–Te21986, Te21945–Te22077, Te21995–Te22077, and Te22215–Te22365, respectively, were used to fine-mapped qGS10.2 (Figure 3B). They were derived from five F14 plants with sequential heterozygous segments covering the region Te21873–Te22365 (Figure 1). Each of the NIL population consisted of 28 NIL-TQ homozygous lines and 28 NIL-IRBB52 homozygous lines in the segregating regions.
Frequency distributions of the three traits in each population were exhibited in Figure 2D–R. In K2 and K3, the NIL-TQ and NIL-IRBB52 lines concentrated in the high- and low-value areas of TGW and GW, respectively (Figure 2G–L). In K4 and K5, the NIL-IRBB52 and NIL-TQ lines concentrated in the high- and low-value areas of GL, respectively (Figure 2M–R). These results suggested that there may be two QTL segregating in the region of qGS10.2, one controlled TGW and GW, and the other controlled GL.
Results of the two-way ANOVA on the three traits in these five NIL populations were shown in Table 1. No significant effect was detected in K1. Highly significant effects were detected for TGW and GW in K2 and K3. Additive effects estimated in these two NIL populations were similar. The TQ allele increased TGW and GW by 0.17 and 0.13 g, and 0.011 and 0.007 mm with the R2 of 12.7% and 10.0%, 11.8% and 10.7%, respectively. In addition, highly significant effects were also detected for GL in K4 and K5. The additive effects estimated in these two populations were also similar. The IRBB52 allele increased GL by 0.018 and 0.017 mm with the R2 of 6.8% and 6.7%, respectively.
As shown in Figure 3B, since the segregating regions of K2 and K5 were totally separated from each other, this suggested that each of these two segregating regions contained one QTL. The additive effects of TGW and GW detected in K2 and K3 were similar to those of qGS10.2, indicating that qGS10.2 was located in the common segregating region of K2 and K3. This region was flanked by markers Te21927 and Te21995, corresponding to a 68.1-kb region in the Nipponbare genome. In addition, the other QTL detected in K4 and K5, suggesting that this QTL was located in the common segregating regions of K4 and K5. This region was flanked by markers Te22077 and Te22215, corresponding to 137.7-kb region in the Nipponbare genome. Since this QTL only controlled GL, it is named qGL10.2.
In summary, two QTL closely linked in a 515.6-kb region were separated. The qGS10.2 controlling TGW and GW was delimited into a 68.1-kb region. The other QTL, qGL10.2 controlling GL, was located within a 137.3-kb region.

2.3. Candidate Genes for qGS10.2 and qGL10.2

According to the Rice Genome Annotation Project (http://rice.uga.edu/, accessed on 30 April 2024), there are fourteen annotated genes in the 68.1-kb region of qGS10.2. As shown in Table 2, three annotated genes encode retrotransposon protein, two encode expressed protein, one encodes a hypothetical protein, and the remaining eight encode protein with known functional domains. Three of the eight, Os10g40880, Os10g40900 and Os10g40934, all encode flavonol synthases. The other five, Os10g40810, Os10g40830, Os10g40859, Os10g40920 and Os10g40950, encode GATA zinc finger domain containing protein, metalloendoproteinase 1 precursor, matrixin family protein, pentatricopeptide and polyol transporter 5, respectively.
For the qGL10.2, there are 22 annotated genes in the 137.3-kb region (Table 2). One of them encodes a hypothetical protein, six of them encode expressed protein, and the remaining 15 encode protein with known functional domains. Four of the fifteen, Os10g41130, Os10g41200, Os10g41260 and Os10g41330, encode AP2 domain containing protein and MYB family transcription factor, which are similar to the proteins encoded by the cloned grain size genes OsLG3 [25] and SG3 [26]. In addition, the coding products of the other 11 annotation genes are different from those of the cloned grain size genes. More studies will continue for map-based cloning of qGS10.2 and qGL10.2.

3. Discussion

In this study, we identified two closely linked QTL controlling grain size from a 515.6-kb region on the long arm of chromosome 10. One QTL controlling TGW and GW, qGS10.2, was delimited into a 68.1-kb region, which contained 14 annotated genes. One of them, Os10g40810 encoding a GATA zinc finger domain containing protein, functions in controlling rice plant architecture and panicle/grain development. The knock-down lines in a japonica variety Wuyunjing 7 background have ideal architecture, better grain shape, and enhanced grain yield [43]. These results implied that Os10g40810 was the most likely candidate gene for qGS10.2. The other one controlling GL, qGL10.2, was delimited into a 137.3-kb region, which contained 22 annotated genes. In addition, we also noticed that the GL of NIL-TQ lines was longer than that of NIL-IRBB52 lines in K2 and K3 populations separated by qGS10.2 (Table 1). This result showed that TQ allele may have an effect of increasing GL in qGS10.2 segregation region, but it was not statistically significant. This may be the reason why the genetic effect of qGL10.2 was not detected in W1 population, that is, TQ allele increased the GL in qGS10.2 region, but decreased the GL in qGL10.2 region. In the meantime, it was found that K1 and K3 differed from the remaining three populations in terms of the GL and GW (Table 1), which was not unexpected since K2, K4 and K5 were derived from the same F12 recombinant plant, whereas K1 and K3 were derived from another F12 recombinant plant. This phenomenon also happened in our previous study [44]. Identification of these two QTL provides candidate regions for cloning of grain size genes.
In our previous study, three QTL controlling grain size, qGL10, qGS10.1 and qGS10.2, were identified in a 4.2-Mb region on the long arm of chromosome 10 [41]. Up to now, GW10 controlling grain size and number [24] and qTGW10-20.8/qGL10/GL10 [35,36,37] controlling TGW and GL have been cloned in the region of qGL10 and qGS10.1, respectively. In this study, we not only fine-mapped qGS10.2, but also identified a new QTL, qGL10.2, controlling grain length. For the region of qGS10.2, one annotated gene, Os10g40810, was determined to be related to rice grain development by reverse genetics [43]. It suggested that there were at least three genes controlling grain size in the 4.2-Mb region. Similarly, the phenomenon of tightly linked genes simultaneously controlling grain size also occurs on the other chromosomes. OsLG3 and OsLG3b for grain length were cloned in a 1.7-Mb region on chromosome 3 [25,27,28], GS5 and GSE5 for grain width in a 1.9-Mb region on chromosome 5 [16,17,23], and TGW6 and GW6a for grain weight in a 0.6-Mb region on chromosome 6 [8,29]. These results implied that the genes controlling quantitative traits are often distributed in clusters.
In recent years, our group has cloned several minor-effect QTL controlling grain size, such as qTGW1.2b, qGS1-35.5 and qTGW10-20.8 [4,35,38]. In the process of map-based cloning of these QTL, a genetic resource, residual heterozygote (RH), was used for the construction of NIL populations. RH means that a single plant was heterozygous in the region covering the target QTL, while in other regions, it was homozygous for the parental alleles. The advantage was that the NIL populations derived from a RH can effectively eliminate the interference of background genes. Therefore, although the genetic effects of the target QTL were small, the effects remain stable in different NIL populations. For example, the additive effects of qGS10.2 and qGL10.2 here were similar in K2 and K3, K4 and K5 populations respectively (Table 1). Based on this advantage, more and more studies began to apply RH to map-based cloning of QTL for yield-related traits in rice [45,46].
Generally, the QTL genetic effects are determined by the phenotypic differences between different alleles in a genetical population. For example, if the two parents carry functional and non-functional alleles respectively at the target gene locus in a bi-parental mapping population, the genetic effect is generally large. Conversely, if the two parents both carry functional alleles, the effect may be small. qTGW10-20.8/OsMADS56 is a minor-effect QTL for controlling grain weight and grain length, which was previously cloned from the cross between indica rice varieties TQ and IRBB52 by our group [35]. Since both TQ and IRBB52 carrying functional alleles, genetic effect analysis reveals qTGW10-20.8 as a minor effect QTL, with TQ allele increasing TGW and GL by only 0.22 g and 0.026 mm, respectively. In addition, this gene was also isolated from two other indica/japonica crosses, Huajingxian 74 (HJX74) / Lemont and Zhai-Ye-Xi (ZYX) / 02428 [36,37]. Compared with the genome sequence of HJX74, Lemont has a 1019-bp deletion in the 5′UTR and exon 1 region, resulting in the loss of transcriptional activity of OsMADS56 [36]. In another cross, five haplotypes were detected from 15 SNPs in the OsMADS56 promoter region. The Hap3 was associated with higher values of TGW and GL and was distributed mainly in the japonica varieties [37]. Due to the genetic effects of OsMADS56 representing the difference between the indica- and the japonica-allele in these two mapping populations, it is manifested as a major effect gene. These results suggested that strong functional allele can be discovered from germplasm resources through minor-effect gene cloning and haplotype analysis.

4. Materials and Methods

4.1. Rice Materials

Six NIL populations segregating in an isogenic background were used in this study. As shown in Figure 1, one F11 plant of TQ/IRBB52, heterozygous in the region RM3123–RM6673, was firstly selected. Then, 11 new polymorphic markers were developed in this region and used to test genotypes of the F11 plant. The heterozygous region was updated to Te21873–Te22365. In the resultant F12 population consisting of 192 plants, homozygous non-recombinants were identified and selfed to develop homozygous lines. One NIL population in F12:13 named W1 was constructed and was used for validation of qGS10.2.
In addition, five F14 plants, heterozygous in Te21873–Te21927, Te21873–Te21986, Te21945–Te22077, Te21995–Te22077, and Te22215–Te22365, respectively, were identified and selfed to produce five F15 populations. In each population, homozygous non-recombinants were identified and selfed to develop homozygous lines. Five F15:16 NIL populations named K1, K2, K3, K4 and K5 were constructed and were used for fine-mapping of qGS10.2.

4.2. Field Experiments and Phenotyping

All the NIL populations were planted in the paddy field of the China National Rice Research Institute in Hangzhou, Zhejiang province, China. For all trails, a randomized complete block design with two replications was performed. In each replication, each line was planted in a single row of 10 plants, with 26.7 cm between rows and 16.7 cm between plants. Field management followed local agricultural practice.
At maturity, four of the middle 8 plants in each row were harvested. Fully filled grains were selected and measured for TGW, GW and GL following the method reported by Zhang et al. [47].

4.3. DNA Marker Analysis

A total of 15 markers were used in this study, including 11 InDel and 4 simple sequence repeat (SSR) markers (Table S1). The InDels were developed based on the variance between TQ and IRBB52 as defined by whole-genome resequencing, while the SSRs were chosen from the Gramene database. DNA extraction and PCR amplification were followed Zheng et al. [48] and Chen et al. [49], respectively. The PCR products were visualized on 6.0% non-denaturing polyacrylamide gels using silver staining.

4.4. Data Analysis

For the six NIL populations, two-way ANOVA was used to analyze phenotypic differences between the two homozygous genotypic groups in each population. The analysis was performed using SAS procedure GLM (general linear model). When significant differences were detected (p < 0.05), the genetic effects of the QTL, including additive effect (A) and the proportions of phenotypic variance explained (R2) were estimated using the same model.

5. Conclusions

In this study, two closely linked QTL controlling grain size, were dissected and fine-mapped in a 515.6-kb region on the long arm of chromosome 10. One of them, qGS10.2, which controlled TGW and GW, was delimited into a 68.1-kb region. The other was qGL10.2, which controlled GL. It was delimited into a 137.3-kb region. Identification of these two QTL provides candidate regions for cloning of grain size genes.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/plants13152054/s1, Table S1: Polymorphic markers developed and used in this study.

Author Contributions

Conceptualization, J.Z., B.S. and Z.S.; methodology, Z.Z. and Y.F.; investigation, Y.S. and D.H.; data curation, Y.S. and D.H.; writing—original draft preparation, Y.S., D.H. and Y.Z.; writing—review and editing, B.S. and Y.Z. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Key R&D Program of Jiangxi Province (20232BBF60001); the Agricultural Science and Technology Innovation Program (ASTIP), the Central Public-interest Scientific Institution Basal Research Fund (CPSIBRF-CNRRI-202112).

Data Availability Statement

The original contributions presented in the study are included in the article/Supplementary Materials, further inquiries can be directed to the corresponding author/s.

Conflicts of Interest

The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

References

  1. Ren, D.; Ding, C.; Qian, Q. Molecular bases of rice grain size and quality for optimized productivity. Sci. Bull. 2023, 68, 314–350. [Google Scholar] [CrossRef] [PubMed]
  2. Bai, F.; Ma, H.; Cai, Y.; Shahid, M.Q.; Zheng, Y.; Lang, C.; Chen, Z.; Wu, J.; Liu, X.; Wang, L. Natural allelic variation in GRAIN SIZE AND WEIGHT 3 of wild rice regulates the grain size and weight. Plant Physiol. 2023, 193, 502–518. [Google Scholar] [CrossRef]
  3. Chen, R.; Xiao, N.; Lu, Y.; Tao, T.; Huang, Q.; Wang, S.; Wang, Z.; Chuan, M.; Bu, Q.; Lu, Z.; et al. A de novo evolved gene contributes to rice grain shape difference between indica and japonica. Nat. Commun. 2023, 14, 5906. [Google Scholar] [CrossRef] [PubMed]
  4. Chan, A.N.; Wang, L.L.; Zhu, Y.J.; Fan, Y.Y.; Zhuang, J.Y.; Zhang, Z.H. Identification through fine mapping and verification using CRISRP/Cas9-targeted mutagenesis for a minor QTL controlling grain weight in rice. Theor. Appl. Genet. 2021, 134, 327–337. [Google Scholar] [CrossRef] [PubMed]
  5. Ruan, B.; Shang, L.; Zhang, B.; Hu, J.; Wang, Y.; Lin, H.; Zhang, A.; Liu, C.; Peng, Y.; Zhu, L.; et al. Natural variation in the promoter of TGW2 determines grain width and weight in rice. New Phytol. 2020, 227, 629–640. [Google Scholar] [CrossRef]
  6. Hu, Z.; Lu, S.J.; Wang, M.J.; He, H.; Sun, L.; Wang, H.; Liu, X.H.; Jiang, L.; Sun, J.L.; Xin, X.; et al. A novel QTL qTGW3 encodes the GSK3/SHAGGY-Like kinase OsGSK5/OsSK41 that interacts with OsARF4 to negatively regulate grain size and weight in rice. Mol. Plant 2018, 11, 736–749. [Google Scholar] [CrossRef] [PubMed]
  7. Xia, D.; Zhou, H.; Liu, R.; Dan, W.; Li, P.; Wu, B.; Chen, J.; Wang, L.; Gao, G.; Zhang, Q.; et al. GL3.3, a Novel QTL encoding a GSK3/SHAGGY-like kinase, epistatically interacts with GS3 to produce extra-long grains in rice. Mol. Plant 2018, 11, 754–756. [Google Scholar] [CrossRef] [PubMed]
  8. Ishimaru, K.; Hirotsu, N.; Madoka, Y.; Murakami, N.; Hara, N.; Onodera, H.; Kashiwagi, T.; Ujiie, K.; Shimizu, B.; Onishi, A.; et al. Loss of function of the IAA-glucose hydrolase gene TGW6 enhances rice grain weight and increases yield. Nat. Genet. 2013, 45, 707–711. [Google Scholar] [CrossRef]
  9. Fan, C.; Xing, Y.; Mao, H.; Lu, T.; Han, B.; Xu, C.; Li, X.; Zhang, Q. GS3, a major QTL for grain length and weight and minor QTL for grain width and thickness in rice, encodes a putative transmembrane protein. Theor. Appl. Genet. 2006, 112, 1164–1171. [Google Scholar] [CrossRef]
  10. Dong, N.Q.; Sun, Y.; Guo, T.; Shi, C.L.; Zhang, Y.M.; Kan, Y.; Xiang, Y.H.; Zhang, H.; Yang, Y.B.; Li, Y.C.; et al. UDP-glucosyltransferase regulates grain size and abiotic stress tolerance associated with metabolic flux redirection in rice. Nat. Commun. 2020, 11, 2629. [Google Scholar] [CrossRef]
  11. Zhang, X.; Wang, J.; Huang, J.; Lan, H.; Wang, C.; Yin, C.; Wu, Y.; Tang, H.; Qian, Q.; Li, J.; et al. Rare allele of OsPPKL1 associated with grain length causes extra-large grain and a significant yield increase in rice. Proc. Natl. Acad. Sci. USA 2012, 109, 21534–21539. [Google Scholar] [CrossRef] [PubMed]
  12. Hu, Z.; He, H.; Zhang, S.; Sun, F.; Xin, X.; Wang, W.; Qian, X.; Yang, J.; Luo, X. A Kelch motif-containing serine/threonine protein phosphatase determines the large grain QTL trait in rice. J. Integr. Plant Biol. 2012, 54, 979–990. [Google Scholar] [CrossRef] [PubMed]
  13. Qiao, J.; Jiang, H.; Lin, Y.; Shang, L.; Wang, M.; Li, D.; Fu, X.; Geisler, M.; Qi, Y.; Gao, Z.; et al. A novel miR167a-OsARF6-OsAUX3 module regulates grain length and weight in rice. Mol. Plant 2021, 14, 1683–1698. [Google Scholar] [CrossRef]
  14. Wang, A.; Hou, Q.; Si, L.; Huang, X.; Luo, J.; Lu, D.; Zhu, J.; Shangguan, Y.; Miao, J.; Xie, Y.; et al. The PLATZ transcription factor GL6 affects grain length and number in rice. Plant Physiol. 2019, 180, 2077–2090. [Google Scholar] [CrossRef] [PubMed]
  15. Song, X.J.; Huang, W.; Shi, M.; Zhu, M.Z.; Lin, H.X. A QTL for rice grain width and weight encodes a previously unknown RING-type E3 ubiquitin ligase. Nat. Genet. 2007, 39, 623–630. [Google Scholar] [CrossRef]
  16. Duan, P.; Xu, J.; Zeng, D.; Zhang, B.; Geng, M.; Zhang, G.; Huang, K.; Huang, L.; Xu, R.; Ge, S.; et al. Natural variation in the promoter of GSE5 contributes to grain size diversity in rice. Mol. Plant 2017, 10, 685–694. [Google Scholar] [CrossRef]
  17. Tian, P.; Liu, J.; Mou, C.; Shi, C.; Zhang, H.; Zhao, Z.; Lin, Q.; Wang, J.; Wang, J.; Zhang, J.; et al. GW5-Like, a homolog of GW5, negatively regulates grain width, weight and salt resistance in rice. J. Integr. Plant Biol. 2019, 11, 1171–1185. [Google Scholar] [CrossRef]
  18. Shi, C.L.; Dong, N.Q.; Guo, T.; Ye, W.W.; Shan, J.X.; Lin, H.X. A quantitative trait locus GW6 controls rice grain size and yield through the gibberellin pathway. Plant J. 2020, 103, 1174–1188. [Google Scholar] [CrossRef]
  19. Wang, S.; Wu, K.; Yuan, Q.; Liu, X.; Liu, Z.; Lin, X.; Zeng, R.; Zhu, H.; Dong, G.; Qian, Q.; et al. Control of grain size, shape and quality by OsSPL16 in rice. Nat. Genet. 2012, 44, 950–954. [Google Scholar] [CrossRef]
  20. Hu, J.; Wang, Y.; Fang, Y.; Zeng, L.; Xu, J.; Yu, H.; Shi, Z.; Pan, J.; Zhang, D.; Kang, S.; et al. A rare allele of GS2 enhances grain size and grain yield in rice. Mol. Plant 2015, 8, 1455–1465. [Google Scholar] [CrossRef]
  21. Che, R.; Tong, H.; Shi, B.; Liu, Y.; Fang, S.; Liu, D.; Xiao, Y.; Hu, B.; Liu, L.; Wang, H.; et al. Control of grain size and rice yield by GL2-mediated brassinosteroid responses. Nat. Plants 2016, 2, 15195, Erratum in Nat. Plants 2016, 2, 16002. [Google Scholar] [CrossRef] [PubMed]
  22. Zhang, Y.M.; Yu, H.X.; Ye, W.W.; Shan, J.X.; Dong, N.Q.; Guo, T.; Kan, Y.; Xiang, Y.H.; Zhang, H.; Yang, Y.B.; et al. A rice QTL GS3.1 regulates grain size through metabolic-flux distribution between flavonoid and lignin metabolons without affecting stress tolerance. Commun. Biol. 2021, 4, 1171. [Google Scholar] [CrossRef]
  23. Li, Y.; Fan, C.; Xing, Y.; Jiang, Y.; Luo, L.; Sun, L.; Shao, D.; Xu, C.; Li, X.; Xiao, J.; et al. Natural variation in GS5 plays an important role in regulating grain size and yield in rice. Nat. Genet. 2011, 43, 1266–1269. [Google Scholar] [CrossRef] [PubMed]
  24. Zhan, P.; Wei, X.; Xiao, Z.; Wang, X.; Ma, S.; Lin, S.; Li, F.; Bu, S.; Liu, Z.; Zhu, H.; et al. GW10, a member of P450 subfamily regulates grain size and grain number in rice. Theor. Appl. Genet. 2021, 134, 3941–3950. [Google Scholar] [CrossRef] [PubMed]
  25. Yu, J.; Xiong, H.; Zhu, X.; Zhang, H.; Li, H.; Miao, J.; Wang, W.; Tang, Z.; Zhang, Z.; Yao, G.; et al. OsLG3 contributing to rice grain length and yield was mined by Ho-LAMap. BMC Biol. 2017, 15, 28. [Google Scholar] [CrossRef] [PubMed]
  26. Li, Q.; Lu, L.; Liu, H.; Bai, X.; Zhou, X.; Wu, B.; Yuan, M.; Yang, L.; Xing, Y. A minor QTL, SG3, encoding an R2R3-MYB protein, negatively controls grain length in rice. Theor. Appl. Genet. 2020, 133, 2387–2399. [Google Scholar] [CrossRef]
  27. Yu, J.; Miao, J.; Zhang, Z.; Xiong, H.; Zhu, X.; Sun, X.; Pan, Y.; Liang, Y.; Zhang, Q.; Abdul Rehman, R.M.; et al. Alternative splicing of OsLG3b controls grain length and yield in japonica rice. Plant Biotechnol. J. 2018, 16, 1667–1678. [Google Scholar] [CrossRef]
  28. Liu, Q.; Han, R.; Wu, K.; Zhang, J.; Ye, Y.; Wang, S.; Chen, J.; Pan, Y.; Li, Q.; Xu, X.; et al. G-protein βγ subunits determine grain size through interaction with MADS-domain transcription factors in rice. Nat. Commun. 2018, 9, 852. [Google Scholar] [CrossRef]
  29. Song, X.J.; Kuroha, T.; Ayano, M.; Furuta, T.; Nagai, K.; Komeda, N.; Segami, S.; Miura, K.; Ogawa, D.; Kamura, T.; et al. Rare allele of a previously unidentified histone H4 acetyltransferase enhances grain weight, yield, and plant biomass in rice. Proc. Natl. Acad. Sci. USA 2015, 112, 76–81. [Google Scholar] [CrossRef]
  30. Wang, Y.; Xiong, G.; Hu, J.; Jiang, L.; Yu, H.; Xu, J.; Fang, Y.; Zeng, L.; Xu, E.; Xu, J.; et al. Copy number variation at the GL7 locus contributes to grain size diversity in rice. Nat. Genet. 2015, 47, 944–948. [Google Scholar] [CrossRef]
  31. Wang, S.; Li, S.; Liu, Q.; Wu, K.; Zhang, J.; Wang, S.; Wang, Y.; Chen, X.; Zhang, Y.; Gao, C.; et al. The OsSPL16-GW7 regulatory module determines grain shape and simultaneously improves rice yield and grain quality. Nat. Genet. 2015, 47, 949–954. [Google Scholar] [CrossRef] [PubMed]
  32. Si, L.; Chen, J.; Huang, X.; Gong, H.; Luo, J.; Hou, Q.; Zhou, T.; Lu, T.; Zhu, J.; Shangguan, Y.; et al. OsSPL13 controls grain size in cultivated rice. Nat. Genet. 2016, 48, 447–456. [Google Scholar] [CrossRef] [PubMed]
  33. Zhao, D.S.; Li, Q.F.; Zhang, C.Q.; Zhang, C.; Yang, Q.Q.; Pan, L.X.; Ren, X.Y.; Lu, J.; Gu, M.H.; Liu, Q.Q. GS9 acts as a transcriptional activator to regulate rice grain shape and appearance quality. Nat. Commun. 2018, 9, 1240. [Google Scholar] [CrossRef] [PubMed]
  34. Lin, S.; Liu, Z.; Zhang, K.; Yang, W.; Zhan, P.; Tan, Q.; Gou, Y.; Ma, S.; Luan, X.; Huang, C.; et al. GL9 from Oryza glumaepatula controls grain size and chalkiness in rice. Crop J. 2023, 11, 198–207. [Google Scholar] [CrossRef]
  35. Zuo, Z.W.; Zhang, Z.H.; Huang, D.R.; Fan, Y.Y.; Yu, S.B.; Zhuang, J.Y.; Zhu, Y.J. Control of thousand-grain weight by OsMADS56 in rice. Int. J. Mol. Sci. 2022, 23, 125. [Google Scholar] [CrossRef] [PubMed]
  36. Zhan, P.; Ma, S.; Xiao, Z.; Li, F.; Wei, X.; Lin, S.; Wang, X.; Ji, Z.; Fu, Y.; Pan, J.; et al. Natural variations in grain length 10 (GL10) regulate rice grain size. J. Genet. Genom. 2022, 49, 405–413. [Google Scholar] [CrossRef] [PubMed]
  37. Chen, T.; Luo, L.; Zhao, Z.; Wang, H.; Chen, C.; Liu, Y.; Li, X.; Guo, T.; Xiao, W. Fine mapping and candidate gene analysis of qGL10 affecting rice grain length. Crop J. 2023, 11, 540–548. [Google Scholar] [CrossRef]
  38. Wang, S.L.; Zhang, Z.H.; Fan, Y.Y.; Huang, D.R.; Yang, Y.L.; Zhuang, J.Y. Control of grain weight and size in rice (Oryza sativa L.) by OsPUB3 encoding a U-Box E3 ubiquitin ligase. Rice 2022, 15, 58. [Google Scholar] [CrossRef]
  39. Li, Z.H.; Wang, S.L.; Zhu, Y.J.; Fan, Y.Y.; Huang, D.R.; Zhu, A.K.; Zhuang, J.Y.; Liang, Y.; Zhang, Z.H. Control of grain shape and size in rice by two functional alleles of OsPUB3 in varied genetic background. Plants 2022, 11, 2530. [Google Scholar] [CrossRef]
  40. Kinoshita, N.; Kato, M.; Koyasaki, K.; Kawashima, T.; Nishimura, T.; Hirayama, Y.; Takamure, I.; Sato, T.; Kato, K. Identification of quantitative trait loci for rice grain quality and yield-related traits in two closely related Oryza sativa L. subsp. japonica cultivars grown near the northernmost limit for rice paddy cultivation. Breed Sci. 2017, 67, 191–206. [Google Scholar]
  41. Zhu, Y.; Sun, Z.; Niu, X.; Ying, J.; Fan, Y.; Mou, T.; Tan, S.; Zhuang, J.Y. Dissection of three quantitative trait loci for grain size on the long arm of chromosome 10 in rice (Oryza sativa L.). PeerJ 2019, 7, e6966. [Google Scholar] [CrossRef]
  42. SAS Institute. SAS/STAT User’s Guide; SAS Institute: Cary, NC, USA, 1999. [Google Scholar]
  43. Zhang, Y.J.; Zhang, Y.; Zhang, L.L.; Huang, H.Y.; Yang, B.J.; Luan, S.; Xue, H.W.; Lin, W.H. OsGATA7 modulates brassinosteroids-mediated growth regulation and influences architecture and grain shape. Plant Biotechnol J. 2018, 16, 1261–1264. [Google Scholar] [CrossRef]
  44. Wang, L.-L.; Chen, Y.-Y.; Guo, L.; Zhang, H.-W.; Fan, Y.-Y.; Zhuang, J.-Y. Dissection of qTGW1.2 to three QTLs for grain weight and grain size in rice (Oryza sativa L.). Euphytica 2015, 202, 119–127. [Google Scholar] [CrossRef]
  45. Xue, P.; Zhang, Y.X.; Lou, X.Y.; Zhu, A.K.; Chen, Y.Y.; Sun, B.; Ping, Y.; Cheng, S.H.; Cao, L.Y.; Zhan, X.D. Mapping and genetic validation of a grain size QTL qGS7.1 in rice (Oryza sativa L.). J. Integr. Agric. 2019, 18, 1838–1850. [Google Scholar] [CrossRef]
  46. Fu, X.; Xu, J.; Zhou, M.; Chen, M.; Shen, L.; Li, T.; Zhu, Y.; Wang, J.; Hu, J.; Zhu, L. Enhanced expression of QTL qLL9/DEP1 facilitates the improvement of leaf morphology and grain yield in rice. Int. J. Mol. Sci. 2019, 20, 866. [Google Scholar] [CrossRef] [PubMed]
  47. Zhang, H.W.; Fan, Y.Y.; Zhu, Y.J.; Chen, J.Y.; Yu, S.B.; Zhuang, J.Y. Dissection of the qTGW1.1 region into two tightly-linked minor QTLs having stable effects for grain weight in rice. BMC Genet. 2016, 17, 98. [Google Scholar] [CrossRef]
  48. Zheng, K.L.; Huang, N.; Bennett, J.; Khush, G.S. PCR-Based Marker-Assisted Selection in Rice Breeding; IRRI Discussion Paper Series No. 12; International Rice Research Institute: Manila, Philippines, 1995. [Google Scholar]
  49. Chen, X.; Temnykh, S.; Xu, Y.; Cho, Y.G.; Mccouch, S.R. Development of a microsatellite framework map providing genome-wide coverage in rice (Oryza sativa L.). Theor. Appl. Genet. 1997, 95, 553–567. [Google Scholar] [CrossRef]
Figure 1. Development of the rice populations used in this study. NIL, near isogenic line.
Figure 1. Development of the rice populations used in this study. NIL, near isogenic line.
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Figure 2. Distributions of 1000 grain weight, grain length and grain width in six near isogenic line populations. (AC): W1, (DF): K1, (GI): K2, (JL): K3, (MO): K4, (PR): K5. TGW, 1000 grain weight; GL, grain length; GW, grain width; NIL-TQ and NIL-IRBB52 are near isogenic lines having Teqing and IRBB52 homozygous genotypes in segregating region, respectively.
Figure 2. Distributions of 1000 grain weight, grain length and grain width in six near isogenic line populations. (AC): W1, (DF): K1, (GI): K2, (JL): K3, (MO): K4, (PR): K5. TGW, 1000 grain weight; GL, grain length; GW, grain width; NIL-TQ and NIL-IRBB52 are near isogenic lines having Teqing and IRBB52 homozygous genotypes in segregating region, respectively.
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Figure 3. Segregating regions of the six near isogenic line populations. (A) W1 was used to validate the genetic effect of qGS10.2. The underlined molecular markers were used in previous study. (B) Five populations were used for fine-mapping of qGS10.2.
Figure 3. Segregating regions of the six near isogenic line populations. (A) W1 was used to validate the genetic effect of qGS10.2. The underlined molecular markers were used in previous study. (B) Five populations were used for fine-mapping of qGS10.2.
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Table 1. Validation and fine-mapping of qGS10.2 using six NIL populations.
Table 1. Validation and fine-mapping of qGS10.2 using six NIL populations.
NameSegregating RegionTrait aPhenotypic MeanpA bR2 (%) c
NIL-TQNIL-IRBB52
W1Te21873-Te22365TGW23.47 ± 0.2923.19 ± 0.19 <0.0001−0.146.6
GL8.839 ± 0.0558.847 ± 0.036 0.5400
GW2.660 ± 0.0202.637 ± 0.015 <0.0001−0.0118.1
K1Te21873-Te21927TGW22.91 ± 0.2522.89 ± 0.190.8001
GL8.481 ± 0.0408.491 ± 0.041 0.3785
GW2.701 ± 0.0132.700 ± 0.0120.6483
K2Te21873-Te21986TGW23.06 ± 0.2522.72 ± 0.31<0.0001−0.1712.7
GL8.832 ± 0.0458.813 ± 0.0420.1160
GW2.673 ± 0.016 2.651 ± 0.017<0.0001−0.01111.8
K3Te21945-Te22077TGW23.47 ± 0.2023.22 ± 0.23<0.0001−0.1310.0
GL8.540 ± 0.0328.524 ± 0.0410.1040
GW2.727 ± 0.0122.714 ± 0.013<0.0001−0.00710.7
K4Te21995-Te22077TGW22.96 ± 0.2123.10 ± 0.160.0533
GL8.879 ± 0.0408.914 ± 0.036 0.0007 0.0186.8
GW2.611 ± 0.0112.614 ± 0.0100.2334
K5Te22215-Te22365TGW22.80 ± 0.2822.85 ± 0.40 0.5900
GL8.806 ± 0.0458.840 ± 0.0520.0130 0.0176.7
GW2.648 ± 0.0272.641 ± 0.0270.3870
a TGW, 1000-grain weight (g); GL, Grain length (mm); GW, Grain width (mm). b A, additive effect of replacing a Teqing allele with a IRBB52 allele. c R2, proportion of the phenotypic variance explained by the QTL.
Table 2. Annotated genes in qGS10.2 and qGL10.2 regions according to Nipponbare genome.
Table 2. Annotated genes in qGS10.2 and qGL10.2 regions according to Nipponbare genome.
QTLLocus NameGene Product Name
qGS10.2LOC_Os10g40804Retrotransposon protein
LOC_Os10g40806Hypothetical protein
LOC_Os10g40810GATA zinc finger domain containing protein
LOC_Os10g40820Expressed protein
LOC_Os10g40824Expressed protein
LOC_Os10g40830Metalloendoproteinase 1 precursor
LOC_Os10g40840Retrotransposon protein
LOC_Os10g40859Matrixin family protein
LOC_Os10g40880Flavonol synthase/flavanone 3-hydroxylase
LOC_Os10g40890Retrotransposon protein
LOC_Os10g40900Flavonol synthase/flavanone 3-hydroxylase
LOC_Os10g40920Pentatricopeptide
LOC_Os10g40934Flavonol synthase/flavanone 3-hydroxylase
LOC_Os10g40950Polyol transporter 5
qGL10.2LOC_Os10g41110Autophagy-related protein 3
LOC_Os10g41120Expressed protein
LOC_Os10g41130AP2 domain containing protein
LOC_Os10g41150Aminotransferase, classes I and II
LOC_Os10g41160Expressed protein
LOC_Os10g41170Dehydrogenase
LOC_Os10g41180Expressed protein
LOC_Os10g41190Transporter family protein
LOC_Os10g41200MYB family transcription factor
LOC_Os10g41220Protein kinase family protein
LOC_Os10g41224Expressed protein
LOC_Os10g41230Homeobox associated leucine zipper
LOC_Os10g41240Dual specificity protein phosphatase
LOC_Os10g41250Glycoprotein
LOC_Os10g41260MYB family transcription factor
LOC_Os10g41270Triacylglycerol lipase like protein
LOC_Os10g41280Expressed protein
LOC_Os10g41290AGC_PVPK_like_kin82y.17—ACG kinases include homologs to PKA, PKG and PKC
LOC_Os10g41300Expressed protein
LOC_Os10g41310DUF630/DUF632 domains containing protein
LOC_Os10g41320Hypothetical protein
LOC_Os10g41330AP2 domain containing protein
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Shen, Y.; Huang, D.; Zhang, Z.; Fan, Y.; Sheng, Z.; Zhuang, J.; Shen, B.; Zhu, Y. Dissection and Fine-Mapping of Two QTL Controlling Grain Size Linked in a 515.6-kb Region on Chromosome 10 of Rice. Plants 2024, 13, 2054. https://doi.org/10.3390/plants13152054

AMA Style

Shen Y, Huang D, Zhang Z, Fan Y, Sheng Z, Zhuang J, Shen B, Zhu Y. Dissection and Fine-Mapping of Two QTL Controlling Grain Size Linked in a 515.6-kb Region on Chromosome 10 of Rice. Plants. 2024; 13(15):2054. https://doi.org/10.3390/plants13152054

Chicago/Turabian Style

Shen, Yi, Derun Huang, Zhenhua Zhang, Yeyang Fan, Zhonghua Sheng, Jieyun Zhuang, Bo Shen, and Yujun Zhu. 2024. "Dissection and Fine-Mapping of Two QTL Controlling Grain Size Linked in a 515.6-kb Region on Chromosome 10 of Rice" Plants 13, no. 15: 2054. https://doi.org/10.3390/plants13152054

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