http://orcid.org/0000-0002-2768-3572
Figures
Abstract
As a major component of ideal plant architecture, leaf angle especially flag leaf angle (FLA) makes a large contribution to grain yield in rice. We utilized a worldwide germplasm collection to elucidate the genetic basis of FLA that would be helpful for molecular design breeding in rice. Genome-wide association studies (GWAS) identified a total of 40 and 32 QTLs for FLA in Wuhan and Hainan, respectively. Eight QTLs were commonly detected in both conditions. Of these, 2 and 3 QTLs were identified in the indica and japonica subpopulations, respectively. In addition, the candidates of 5 FLA QTLs were verified by haplotype-level association analysis. These results indicate diverse genetic bases for FLA between the indica and japonica subpopulations. Three candidates, OsbHLH153, OsbHLH173 and OsbHLH174, quickly responded to BR and IAA involved in plant architecture except for OsbHLH173, whose expression level was too low to be detected; their overexpression in plants increased rice leaf angle. Together with previous studies, it was concluded that all 6 members in bHLH subfamily 16 had the conserved function in regulating FLA in rice. A comparison with our previous GWAS for tiller angle (TA) showed only one QTL had pleiotropic effects on FLA and TA, which explained low similarity of the genetic basis between FLA and TA. An ideal plant architecture is expected to be efficiently developed by combining favorable alleles for FLA from indica with favorable alleles for TA from japonica by inter-subspecies hybridization.
Author summary
Rice leaf angle is a major component of ideal plant architecture that determines plant density. Many leaf angle-related genes have been characterized based on mutants, but natural variations of these genes and potential values in genetic improvement have not been evaluated. Here we explore the genetic basis of rice FLA in rice by GWAS. Dozens of quantitative trait loci (QTLs) have been identified, but few FLA QTLs have been commonly detected between indica and japonica subpopulations. Alleles for small leaf angle mostly come from indica rice. Three novel OsbHLH genes have been confirmed to regulate leaf angle by overexpression. Together with previous studies, all 6 members of bHLH subfamily 16 have a conserved function in regulating leaf angle. Only one QTL has been identified with pleiotropic effects on FLA and TA in the same collection, indicated the diverse genetic basis between FLA and TA. Alleles for small TA mostly come from japonica rice. We suggest to breed compact plant type cultivars by simultaneously utilizing favorable alleles for FLA and TA via inter-subspecies hybridization.
Citation: Dong H, Zhao H, Li S, Han Z, Hu G, Liu C, et al. (2018) Genome-wide association studies reveal that members of bHLH subfamily 16 share a conserved function in regulating flag leaf angle in rice (Oryza sativa). PLoS Genet 14(4): e1007323. https://doi.org/10.1371/journal.pgen.1007323
Editor: Kenneth M. Olsen, Washington University, UNITED STATES
Received: January 12, 2018; Accepted: March 20, 2018; Published: April 4, 2018
Copyright: © 2018 Dong et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data are within the paper and its Supporting Information files.
Funding: This project was partly supported by the national key research and development program of China (2016YFD0100403) (http://www.most.gov.cn/), National Special Program for Research of Transgenic Plant of China (2011ZX08009-001-002) (http://www.moa.gov.cn/), and the natural science foundation of Hubei province, China (2015CFA006) (http://www.hbstd.gov.cn/). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Introduction
Leaf angle is the inclination between leaf and stem, which is an important agronomic trait that attracts attention. Erect leaves maximize carbon gain by optimizing the interception of photosynthetically active radiation for canopy photosynthesis and by mitigating heat stress induced by excess infrared radiation [1–3]. Crops with erect leaves can be grown in an increasing plant density without compensation by the photosynthesis rate, which consequently increases grain yield. Therefore, leaf erectness as one of the components of ideal plant architecture has been a breeding target for several decades [4–7]. In addition, the more upright leaves also improve the accumulation of leaf nitrogen for grain filling in rice [8].
In addition to breeders, scientists in plant developmental biology have paid much attention to the mechanism of leaf angle formation. The molecular mechanisms in leaf angle have differed among various reports, but there is a common opinion that phytohormone synergism is the key regulator of leaf angle. Endogenous hormones, especially brassinosteroids (BRs), play important roles in controlling rice leaf angle by promoting the growth of cells on the adaxial side of the lamina joint [9, 10]. Most of the rice leaf angle-related genes with regard to BR biosynthesis and BR signaling or that are otherwise BR related have been identified, such as OsDWARF4, D2/CYP90D2, OsBRI1 and OsBZR1 [11–14]. OsIAA1 and OsARF19 control the leaf angle by responding to auxin and BR hormones [15, 16]. OsSPY and D1/RGA1 are two genes in the GA signaling pathway that regulate leaf angle in a BR-GA crosstalk manner in rice [17, 18]. Increased Leaf Angle 1 (ILA1), different from the abovementioned leaf angle-related genes, regulates mechanical tissue formation in the rice leaf lamina joint [19]. CYCU4;1 promotes the proliferation of sclerenchyma cells on the abaxial side of the lamina joints to affect rice leaf erectness through the BR signaling pathway [20]. oslg1 is the T-DNA insertion mutant of OsLIGULELESS1 (OsLG1), with erect leaves from the loss of the lamina joint structure [21]. Therefore, there are many findings on the development of leaf angle of rice that are helpful for understanding its molecular mechanism.
However, many of these studies are based on the reverse genetic approach. While understanding the natural variation in rice leaf angle is still limited, which is more important for breeding rice varieties with ideal plant architecture. Since the 1990s, researchers have explored several leaf angle-related quantitative trait loci (QTLs) with bi-parental mapping populations [22–24]. Recently, genome-wide association study (GWAS) has become a popular approach for QTL mapping in crops due to its strong power and high-resolution mapping [25, 26]. In maize, GWAS demonstrated that the genetic architecture of the leaf traits, including leaf angle, is dominated by multiple minor QTLs, with little epitasis or environmental interaction [27]. GWAS focused on plant architecture traits, including FLA, were conducted in two separate indica rice collections [28, 29]. Although several novel FLA-related loci have been detected, this alone is not comprehensive for understanding the natural variation in leaf angle in cultivated rice.
The upper canopy of the rice plant, especially the flag leaf, the top leaf after heading, intercepts most of the solar radiation at stages of heading and grain filling. FLA is closely associated with the efficiency of solar utilization by the flag leaf. It is of significance to further dissect the genetic basis of FLA for improvement of plant architecture. In this study, we performed GWAS for FLA with 529 Oryza sativa accessions at the heading stage using a linear mixed model (LMM). Several genome regions were associated with FLA, and 3 previously uncharacterized genes of basic helix-loop-helix (bHLH) transcriptional factor subfamily 16 were in or around the associated regions. Overexpression transgenic plant analysis confirmed that members of bHLH subfamily 16 have a conserved function in controlling rice leaf angle. Although both TA and FLA are the major components of plant architecture, a low correlation between TA and FLA and only one QTL with pleiotropic effects on both traits indicated their different genetic bases.
Results
Phenotypic variation of FLA at heading stage
The FLA of 529 O. sativa accessions shared a similar distribution in Hainan and Wuhan, China (Fig 1). There was a large variation in FLA in the whole population: from 3.5° to 152.5° in Hainan and from 6° to 163° in Wuhan. However, the FLA of one half of the accessions in the middle ranged from 15° to 30°, and the median value of the FLA was approximately 20°. FLA showed a high heritability of 0.79. FLA in the indica accessions had smaller variations with smaller mean values than those in japonica in both environments (Fig 1). The correlation coefficients of FLA between Hainan and Wuhan were 0.40 and 0.60 within the indica and japonica subpopulations that both reached a significant level (P<0.05), respectively. Two-way ANOVA revealed that FLA was dominantly controlled by genetic factors but also influenced by genotype-by-environment interactions (Table 1). In the indica subpopulation, the interaction between genotype and environment accounted for 28.4% of the variation (Table 1). We also measured TA at the heading stage for the collection grown in the two environments [30]. A significant positive correlation was observed between FLA and TA only in the indica subpopulation, but the correlation coefficients were small in both environments (Hainan, 0.20; Wuhan, 0.34).
The boxplot shows the differences in FLA among the whole population and indica and japonica subpopulations. The box edges represent the upper and lower quantile, with the median value shown by the bold line in the middle of the box. Whiskers represent the data from the lowest quantile to the top quantile. Individuals falling outside the range of the whiskers are shown as open dots. All, Ind and Jap represent the whole population and indica and japonica subpopulations, respectively; HN and WH represent the Hainan and Wuhan environments, respectively.
QTLs for FLA identified by GWAS
GWAS for FLA were performed using LMM approach in the whole population and in the indica and japonica subpopulations, respectively (S1 Fig). We detected a total of 62 QTLs in Hainan and Wuhan (Table 2; S1 and S2 Tables). They were unevenly distributed on 12 chromosomes. Chromosome 8 harbored the highest number, with 10 QTLs. Eight QTLs were commonly detected in both environments (Table 2). Of these, 3 QTLs (qFLA1e, qFLA8f and qFLA12a) were identified in the full population, 2 QTLs (qFLA3a and qFLA11a) were found in the indica subpopulations, and 3 QTLs (qFLA3e, qFLA6b and qFLA7e) were detected in the japonica populations. Additionally, qFLA6b and qFLA7e were also detected in the full population separately in Hainan and Wuhan (S1 and S2 Tables). qFLA1g was identified in the full population in Hainan, as well as in the indica subpopulation in Wuhan, while qFLA5b was detected both in the indica subpopulation in Hainan and in the full population in Wuhan (S1 and S2 Tables). We detected 22 QTLs that were unique in Hainan (S1 Table): 16, 3 and 2 QTLs were only detected in the full population, indica and japonica subpopulations, respectively, and one QTL, qFLA1c, was identified both in the full population and the japonica population. Thirty QTLs were only detected in Wuhan (S2 Table): 18, 10 and 1 QTLs were found in the full population, indica and japonica subpopulations, respectively, and one QTL, qFLA8e, was detected both in the full population and the japonica population.
Co-localization of associated sites with previously reported QTLs/genes for FLA
We compared the genomic positions of known leaf angle genes with the associated sites detected in this study. Four genes were co-localized with our associated sites (S1 and S2 Tables): OsBRI1, an orthologue of Arabidopsis BRI1, which plays an important role in BR signaling [14], was located in the linkage disequilibrium (LD) region where qFLA1d was detected in Wuhan. PGL1 and PGL2/OsBUL1, the homologs of OsILI1 and BU1 in rice [31–33], were located in the LD regions of qFLA3b detected in Hainan and qFLA2f detected in Wuhan, respectively. OsSPY, encoding an O-linked N-acetylglucosamine transferase [17], was located in the region of qFLA8j detected in Wuhan.
In addition, we compared the localization of the associated sites detected in this study with previously detected leaf angle QTLs with bi-parental mapping populations from the gramene website (http://www.gramene.org) and with the significant FLA loci detected via GWAS in previous studies [28, 29]. A total of 11 associated sites were co-localized with 8 previously reported QTLs (Table 2; S1 and S2 Tables): both qFLA1e and qFLA6b, commonly identified in both environments, were located in the regions of QLa1 and QFla6, respectively; qFLA6c and qFLA6d, detected only in Wuhan, were located in the region of QFla6; qFLA9c and qFLA9d, only identified in Hainan, were co-localized with fla9; qFLA5b was located in the QFla5 region; and qFLA1f, qFLA2f, qFLA3d and qFLA7d, only detected in Wuhan, were also located in the previous QTL regions. These results indicated the reliability of FLA-related associations in our study.
Haplotype-level association analysis of genes of bHLH subfamily 16
Three bHLH genes, such as OsILI1 (OsbHLH154), BU1 (OsbHLH172) and PGL2/OsBUL1 (OsbHLH170), control leaf angle and belong to bHLH subfamily 16 [32–37]. Interestingly, OsbHLH173 and OsbHLH174, two members of subfamily 16, are in the local LD regions where the lead SNP of qFLA10c was located (S1 Table). In addition, OsbHLH153 was located close to the QTL qFLA3b (S1 Table). They are likely the genes underlying these QTLs. Haplotype level association analysis frequently improves the power of QTL mapping [26, 38, 39]. To provide more evidence for their identities, we constructed the haplotypes of all 6 members of bHLH subfamily 16 and tested the difference in FLA between all possible haplotype pairs. All these genes except BU1 were highly significantly associated with FLA in the whole population in both environments (S3 Table). OsbHLH153, OsbHLH174 and ILI1 were significantly associated in the japonica subpopulation in Hainan, but none of the 6 genes were associated in the indica subpopulation (S3 Table).
Here we presented the results of OsbHLH174 and OsbHLH173 as the candidate genes of qFLA10c and OsbHLH153 as the candidate gene of qFLA3b. Only one SNP (sf1013651480) causing amino acid change (S8G) was detected in OsbHLH174 coding region (Fig 2A). Most aus accessions belong to Hap1 containing Ser8, while most indica and japonica accessions were divided into Hap2-Hap10 shared Gly8 (Fig 2A). The effects of two major haplotypes in the indica subpopulation were similar, while the effects were significantly different among major haplotypes in the japonica accessions, especially between Hap6 and Hap7 (Fig 2B). Ser and Gly are both uncharged hydrophilic amino acids, and both have similar biochemical characters. Therefore, sf1013651480 was not a functional nucleotide polymorphism site (FNP), and the nucleotide change in promoter may lead to the significant difference for FLA. Accordingly, only a SNP (sf1013702588) causing a non-synonymous mutation (S3G) was detected in OsbHLH173, and most aus and indica accessions carried Ser at this site (S2A Fig). Although significant differences in FLA were detected among haplotypes in japonica (S2B Fig), sf1013702588 was not associated with leaf angle. This result suggested the genetic variation of promoter controlling FLA. For OsbHLH153, one SNP (sf0303844743) caused a non-synonymous mutation (G12V) (S3A Fig). Most aus, indica and japonica accessions carried Gly at site 12 (Haplotypes 1–5 and 7). A small proportion of japonica accessions carried Val at site 12 (haplotypes 6 and 8). Unlike Gly, Val is an uncharged hydrophobic amino acid. Within japonica rice, FLA of Hap5 with G12 was significantly smaller than that of Hap6 with V12 in Hainan (S3B Fig). In addition, some SNPs in the promoter region were also associated with FLA such as sf0303844574, sf0303844528, sf0303844032, sf0303843859 and sf0303843700 (S3A Fig). Therefore, both polymorphisms in coding and promotor regions of OsbHLH153 caused the variation of leaf angle. To verify the contribution of promotor variation, we firstly examined the expression pattern of these bHLH genes with the rice chip DB “CREP” (http://crep.ncpgr.cn/crep-cgi/home.pl), and found they preferably expressed in young and growing tissues but not in mature tissues (S4B Fig). Then we sampled the flag leaf from 296 accessions for RNA sequencing. Accordingly, it was hard to detect the expressions of all the six members of bHLH subfamily 16 (S6 Table). Therefore, it was failed to perform the associations between expression amounts of these three bHLH genes and FLA.
(A) Major haplotypes (haplotypes each carried by more than 5 accessions) of OsbHLH174 in the whole population according to SNPs data from RiceVarMap version 1. The region contains 2 kb upstream and coding region. The SNP in red and bold is a non-Synonymous SNP. (B) Comparison of FLA between Hap2 and Hap3 in indica rice and FLA among Hap4-Hap8 in japonica rice using an independent t-test and a Duncan’s test (P< 0.01), respectively.
Overexpression of OsbHLH153, OsbHLH173 and OsbHLH174 increased rice leaf angle
To test whether the expression level of these genes affects leaf angle, then we generated overexpression plants for these 3 bHLH genes. Many OsbHLH174 overexpression plants (T0) showed a significantly increased leaf angle (Fig 3A). We measured FLA and the top second leaf angle (TSLA) in two T1 overexpressing lines. All the overexpression plants showed significantly increased lamina joint bending (Fig 3B and 3C). T0 overexpression plants of OsbHLH153 and OsbHLH173 showed an increased leaf angle, and some of these exhibited defective phenotypic variations, including leaf and stem twisting (S5 Fig). A mutation in the promoter of Style2.1, a homolog of these rice bHLHs genes, resulted its decreased expression and differentiated its function in cultivated tomatoes [40]. We overexpressed Style2.1 from tomato Solanum pennellii in japonica rice variety Zhonghua 11. The overexpression plants showed an increased lamina joint (S6 Fig).
(A) The morphology of wild type (WT) and OsbHLH174: OX plants, at the seedling, tillering and heading stages. (B) quantitative real-time reverse transcription-polymerase chain reaction (qRT-PCR) analysis of OsbHLH174 transcripts in WT and OsbHLH174: OX at the seedling stage. (C) FLA and TSLA of the wild type and OsbHLH174:OX-1 and -2 at the heading stage (P< 0.001, n≥ 5).
Responses of OsbHLH genes to exogenous phytohormones
As many leaf angle-related genes are regulated by plant hormones, especially BRs, we treated the three-leaf seedlings with 4 kinds of hormones and checked the expression change of these 3 bHLH genes, OsbHLH153, OsbHLH173 and OsbHLH174, by quantitative real-time reverse transcription-polymerase chain reaction (qRT-PCR). OsbHLH153 and OsbHLH174 were up-regulated immediately and reached a maximum level of over 27× compared with the control group at 4 h after treatment with 100 μM indole-3-acetic acid (IAA), whereas they gradually decreased expression after treatment with 100 μM abscisic acid (ABA) (Fig 4). The expression of OsbHLH153 was up-regulated to a maximum level (3.7×) at 8 h after treatment with 10 μM epibrassinolide (eBL) and increased 3.0× at 1 h after treatment with 100 μM GA4/7 compared with the control group (Fig 4). The expression of OsbHLH174 reached 3.1× and 2.2× at 4 h when treated with 10 μM eBL or 100 μM GA4/7, respectively, compared with the control group (Fig 4). However, the expression of OsbHLH173 was too low to be detected in seedling and other tissues (S4A Fig). These results suggested that these bHLH genes were regulated by plant hormones and might regulate leaf angle by these hormone pathways.
qRT-PCR analysis of the transcripts of OsbHLH153 and OsbHLH174 in Zhonghua 11 wild type treated with 100 μM IAA, 10 μM eBL, 100 μM ABA and 100 μM GA as the experimental groups and with water as the control group for different times. Data are the means ± SD (n = 3).
Haplotype effects of OsBRI1 on FLA
qFLA1d/OsBRI1 made a large contribution to FLA variation in the full population in Wuhan (S2 Table). Haplotype-level association analysis showed that OsBRI1 was strongly associated not only in the whole population in two environments but also in the indica and japonica subpopulations in Hainan (S3 Table). A total of 6 major haplotypes were constructed based on all SNPs in OsBRI1. Most indica accessions belong to Hap2 or Hap3, and most japonica rice carried Hap4-Hap6 (Fig 5A). Within indica subpopulation, the flag leaf of accessions carried Hap2 (D212; Asp, an amino acid with a negative charge of polarity) was more erect than those carried Hap3 (G212; Gly) (Fig 5A and 5B). Within japonica, FLA of the accessions carried OsBRI1-Hap6 (L623; Leu, a nonpolar amino acid) was larger than those carried OsBRI1-Hap4 (S623; Ser, an uncharged hydrophilic amino acid) and OsBRI1-Hap5 (S623) (Fig 5A and 5C). SNPs sf0129929653 and sf0129928420 might be FNPs separately controlling leaf angle in the indica and japonica subpopulations.
(A) Major haplotypes (haplotypes each carried by more than 5accessions) of OsBRI1 in the full population according to SNPs data from RiceVarMap version 1. The SNPs in red and bold are non-Synonymous SNPs. (B) Comparison of FLA between Hap2 and Hap3 in indica rice by an independent t-test. (C) Comparison of FLA among Hap4-Hap6 in japonica rice by a Duncan’s test (P< 0.01), respectively.
Large effects of gene combinations between OsbHLHs and OsBRI1
Three members of OsbHLH 16 subfamily genes acted downstream of OsBRI1 in BR signaling pathway [33, 36, 37]. Based on the hypothesis that OsBRI1 combined with its downstream genes controlling leaf angle with varied effects. Then we investigated effects of gene combinations between three OsbHLHs identified in this study and OsBRI1 on FLA in japonica subpopulation (Fig 6). Different combinations showed significant differences in FLA. The combinations constructed by haplotypes with small FLA such as OsBRI1-Hap4/OsbHLH153-Hap5, OsBRI1-Hap5/OsbHLH153-Hap5, OsBRI1-Hap4/OsbHLH173-Hap4, OsBRI1-Hap4/OsbHLH174-Hap6 and OsBRI1-Hap4/OsbHLH174-Hap8 had small FLA; and the combinations constructed by haplotypes with large FLA such as OsBRI1-Hap6/OsbHLH153-Hap6, OsBRI1-Hap6/OsbHLH173-Hap5 and OsBRI1-Hap6/OsbHLH174-Hap7 had large FLA. The other types usually had intermediate FLA such as OsBRI1-Hap5/OsbHLH174-Hap7. These results indicated that selection for the combinations between these three OsbHLHs and OsBRI1 should be more important and efficient than for single gene when improving leaf angle in japonica subpopulation.
Comparison of the FLA among the combinations of haplotypes of OsBRI1 with three OsbHLHs, OsbHLH153 (A), OsbHLH173 (B) and OsbHLH174 (C), using boxplots by a Duncan’s test (P< 0.05) in japonica, respectively.
Discussion
Diverse genetic bases of FLA between indica and japonica subpopulations
In this study, we found that indica rice has a smaller FLA with a narrower distribution than japonica rice in Hainan and Wuhan (Fig 1). A total of 17 and 8 unique associations were detected by GWAS in the indica and japonica subpopulations, respectively. However, only 2 and 3 were commonly detected in both environments in indica and japonica subpopulations, respectively (Table 2; S1 and S2 Tables). Further haplotype-level association analysis of leaf angle-related genes located in or around the regions of associations in the two subpopulations indicated that significant differences in FLA between/among haplotypes were detected for all these genes in the japonica accessions in Hainan, while no significant difference was observed for these genes, except for OsBRI1, in the indica accessions (S3 Table, Figs 2 and 5; S2 and S3 Figs). So, we concluded that FLA has undergone diversifying selection. The indica subpopulation has been fixed with non-functionally differential haplotypes of the leaf angle-related genes, whereas the spread of functionally differentiated haplotypes in japonica has led to a wider variation in FLA. Therefore, there are diverse genetic bases of FLA between the two subpopulations, and some genes regulate FLA, dependent on the environment.
The genes of bHLH subfamily 16 have a conserved function in controlling rice leaf angle
The bHLH family, a large family of transcription factors, is found throughout the eukaryotic kingdoms. The basic region functions as a DNA-binding motif, and the HLH region allows the homodimer or heterodimer formation [34, 35, 41–43]. Many bHLHs have been functionally characterized with multiple functions in regulating many biological developments. bHLH subfamily 16 is composed of several atypical proteins that modulate the expression of downstream genes by forming heterodimers as non-DNA-binding bHLHs. The PREs in Arabidopsis and style2.1 in tomato, which belong to bHLH subfamily 16, have been reported to regulate cell elongation in different tissues [40, 44]. In rice, there are 6 genes in bHLH subfamily 16. Of these, OsILI1 (OsbHLH154), BU1 (OsbHLH172) and PGL2/OsBUL1 (OsbHLH170) were previously confirmed to regulate leaf angle [33, 36, 37]. In this study, the remaining genes of subfamily 16, OsbHLH153, OsbHLH173 and OsbHLH174, were associated with FLA by GWAS (S1 and S2 Tables) and by haplotype analysis (Fig 2, S2 and S3 Figs).
There were few SNPs caused non-synonymous in these three bHLH genes. Meanwhile, the mutations in promoters were associated with the variation of FLA (Fig 2, S2 and S3 Figs). However, we failed to establish the relation between the expression levels of these candidate bHLH genes and FLA because their expressions were too low to be detected in flag leaf (S4 Fig, S6 Table). It is noticed that IBH1 (ILI1 Binding bHLH Protein 1), formed a heterodimer with ILI1 and its homologs, and its activity inhibited by ILI1, could be detected in mature organs [33, 37]. A negative correlation was detected between expression of OsIBH1 and FLA within 64 japonica accessions (-0.255, P = 0.042) that was consistent with its negative regulation to FLA. The accessions carried haplotypes of OsbHLH153 and OsbHLH174 with smaller FLA had higher expression levels of OsIBH1 which indicated the expression of OsbHLH153 and OsbHLH174 might be associated with FLA in japonica (S7 Fig). Moreover, overexpressing these three bHLHs increased the leaf angle, like the phenotypic change of overexpressing OsILI1, BU1 and PGL2/OsBUL1 (Fig 3, S5 Fig). Overexpressed tomato Style2.1 in rice plants also enlarged the FLA (S6 Fig). Although OsILI1 was not associated with FLA at SNP level in this study, haplotype-level association analysis showed that it was associated with FLA in japonica rice (S3 Table). We conclude that the genes in bHLH subfamily 16 had a conserved function in controlling rice leaf angle together with previous studies. In addition, all the members of bHLH subfamily 16 had different expression levels in vivo, but there were similar expression patterns (S4 Fig).
Low similarity in the genetic basis between FLA and TA
Both FLA and TA are important components of plant architecture. The erect growth of cultivated rice showed a smaller TA compared with the prostrate growth of wild rice (O. rufipogon), which was a critical domestication event. A wider phenotypic variation of FLA, from 3.3° to 166.7° (Fig 1), was observed than that of the TA, which ranged from 1.8° to 34.4° [30] in the same collection used in this study. In general, japonica rice has a compact plant architecture, which exhibits a small tiller angle [30]. However, this is completely the opposite for FLA. Specifically, indica rice has a smaller FLA than japonica rice. Therefore, a very low correlation efficient was detected between FLA and TA, indicating distinct genetic bases for FLA and TA. Previous studies also reported a low correlation coefficient [23, 24, 29]. Therefore, the possibility of the co-localization of QTLs for leaf angle and TA or QTLs with pleiotropic effects on both traits is limited.
In fact, there are very few QTLs with pleiotropic effects on TA and FLA in rice cultivars. It has been reported that only Ta on chromosome 9 and QFla5 had pleiotropic effects on TA and FLA [23]. Here, we compared the genome regions of 62 FLA-related QTLs with 30 QTLs for TA in our previous work [30] and found that only one QTL, qFLA8f, detected in the full population was co-located with TA QTLs qTA8a and qTA8b, likely indicating a new pleiotropic QTL for TA and FLA or two linked genes in this region. More importantly, haplotype analysis showed that the haplotypes of 6 FLA genes were functionally differentiated in japonica accessions, while those in indica accessions were not functionally differentiated, except for OsBRI1 (Figs 2 and 5, S2 and S3 Figs, S3 Table). However, this is almost the opposite for TA-related genes. Specifically, the haplotypes of the TA-related genes are not functionally differentiated in japonica accessions and are fixed with functional alleles, decreasing the TA [30]. These results suggested that these genes have no pleiotropic effects on TA and FLA. Thus, it is promising that cultivars with compact plant status may be developed by combining favorable indica original alleles for leaf angle and japonica original alleles for TA without considering linkage drag.
In summary, FLA is mainly determined by genetic factors in rice, and different genetic factors control the variation of FLA in the indica and japonica subpopulations. The members of bHLH subfamily 16 have the conserved function regulating rice FLA. There is a low correlation coefficient between FLA and TA, and very few QTLs with pleiotropic effects on both traits indicate their diverse genetic bases. The ideal plant architecture in rice may be efficiently developed by combining favorable alleles for both traits by indica-japonica hybridization.
Materials and methods
Plant materials and field experiments
A diverse worldwide collection consisting of 529 O. sativa landraces and elite accessions was sown at the experimental farm of Huazhong Agricultural University in the winter of 2013 in Hainan and in the 2014 rice growing season in Wuhan, China. The 2-year field experiment was designed with 2 replicates per year. The FLA of 5 plants in the middle for each accession 5 days after flowered was used for FLA measurement. The angle between flag leaf and stem was measured by a protractor. The average FLA across 2 replicates within one year was used for GWAS. The basic information of the 529 O. sativa accessions is available in the RiceVarMap (http://ricevarmap.ncpgr.cn/) [45]. The average FLAs used for GWAS are shown in S4 Table.
Two-way analysis of variance and heritability
Two-way analyses of variance were separately used to test significant difference between environments and genotypes for the whole population and two subpopulations. The analysis was run in the program Statistica 7.0 (StatSoft. Tulsa, OK, USA). Broad-sense heritability (H2) of FLA in the whole population was calculated based on the experiments using the formula: , where
,
and
were the estimates of genetic, genotype by environment and error variances derived from the mean square expectations of two-way analysis of variance (ANOVA), respectively; n was the number of environments and r was the number of replicates.
GWAS for FLA
The whole genomic DNA sequences of the 529 cultivar accessions were genotyped with approximately 2.5×coverage genome sequencing using a bar-coded multiplex sequencing approach on an Illumina Genome Analyzer II [46]. The diverse global rice collection was classified into 9 subpopulations: indI, indII, indica intermediate, Tej, Trj, japonica intermediate, Aus, VI and intermediate [46]. Of these 529 varieties, 295 were classified into the indica subpopulation, including indI, indII and indica intermediate, and 156 were classified into the japonica subpopulation, including Tej, Trj and japonica intermediate. To control spurious associations, population structure and kinship were regarded as cofactors when performing GWAS using LMM by the FaST-LMM program [47, 48]. Kinship was calculated as a realized relationship matrix using FaST-LMM program. Population structure was calculated as Q matrix base on the admixture model[47]. A total of 3,916,415, 2,767,159 and 1,857,845 SNPs (minor allele frequency (MAF) ≥0.05; the number of accessions with minor alleles ≥ 6) were employed for GWAS in the full population, indica and japonica subpopulations, respectively. 757,578, 571,843 and 245,348 effective independent SNPs (Me) which were calculated using a method described by Li et al [49] were found in the full population and indica and japonica subpopulations, respectively. The suggestive P values (1/Me, 1.3×10−6 for the full population, 1.8×10−6 for indica and 4.1×10−6 for japonica) were used as the thresholds for associations commonly detected in Hainan and Wuhan or detected only in one environment, but the candidate genes were in their LD regions. Genome-wide significance thresholds (0.05/Me) of 6.6×10−8, 8.7×10−8 and 2.0×10−7 calculated by a modified Bonferroni correction were used for the full population and the indica and japonica subpopulations, respectively, for the associations detected only in Hainan or Wuhan. To obtain independent association signals, multiple SNPs exceeding the threshold in a 5-Mb region were clustered based on an r2 of LD ≥ 0.25; the SNPs showing the minimum P value in a cluster were considered to be the lead SNPs [50].
LD and haplotype analysis
LD was investigated based on standardized disequilibrium coefficients (D’) and squared allele-frequency correlations (r2) for the pairs of SNP loci. The extent of genome-wide LD decay in the different populations was shown in previous studies [50, 51]. The distances in LD decay in the regions surrounding the lead SNPs identified in this study were calculated, and the method was described in our previous study [30].
The SNPs of the targeted genes in the 529 O. sativa accessions were obtained from the RiceVarMap (http://ricevarmap.ncpgr.cn/) using the gene ID, while for OsbHLH153, OsbHLH173 and OsbHLH174, the SNPs in their 2kb promoter regions for the few SNPs in the CDS coordinates were added. The haplotypes of the individual genes carried by at least 10 accessions were used for comparison. An independent t-test and a Duncan’s test were used to compare the differences in the FLA between/among haplotypes using the SSPE program [52]. The method of haplotype-level association analysis of candidate genes was described by our previous studies [38].
Vector construction and rice transformation
Genomic DNA fragments of OsbHLH153, OsbHLH173 and OsbHLH174 were amplified from Nipponbare DNA, and a genomic DNA fragment of Style2.1 was amplified from tomato (Solanum pennellii) DNA with gene-specific primers (S5 Table) using the high-fidelity LA Taq polymerase (Takara). The PCR products without mutations were cloned into PU1301 with a maize (Zea mays) Ubiquitin promoter or into pCAMBIA1301s with the 35S promoter. The constructs were then introduced into Zhonghua 11 (ZH11) by Agrobacterium tumefaciens-mediated transformation using callus induction from mature embryos as subjects [53, 54]. At least two independent overexpression plants for each construct were used for measuring the FLA.
Identification of positive transgenic plants
The total DNA were extracted from fresh leaves using the CTAB method [55]. First, the GUS fragment was amplified from the transgenic plants with the primers GUS-F and GUS-R (S5 Table) to identify the positive transgenic plants. The positive and negative transgenic plants checked by GUS amplification were then selected to compare their expression levels of the target genes by qRT-PCR.
Exogenous eBL, IAA, GA and ABA treatment
The wild type seeds were sown and germinated on agar medium. After two weeks, the seedlings were transferred to water. On the second day that the plants were grown in water, 4 kinds of hormones were separately added in the water, ensuring the final concentrations of 10 μM eBL, 100 μM IAA, 100 μM GA and 100 μM ABA in the experimental group, with nothing added to the water in the control group. Total RNA was extracted from the whole seedling, except for the root tissue, after treatment for 0.5, 1, 4, 8, 12 and 24 h, respectively. We then analyzed the expression pattern by qRT-PCR.
RNA extraction and expression analysis
Total RNA was extracted using an RNA extraction kit (TRIzol reagent, Invitrogen). RNA sequencing data of OsbHLH genes were listed in S6 Table. The expression patterns of the FLA genes were then analyzed by qRT-PCR. Measurements were obtained using the relative quantification method. Expression levels were normalized against expression of a ubiquitin (UBQ) gene. Error bars indicate standard deviations (n = 3). All primers used for qRT-PCR are listed in S5 Table.
Supporting information
S1 Table. Significant association loci for rice flag leaf angle only detected in Hainan using the LMM.
https://doi.org/10.1371/journal.pgen.1007323.s001
(DOCX)
S2 Table. Significant association loci for rice flag leaf angle only detected in Wuhan using the LMM.
https://doi.org/10.1371/journal.pgen.1007323.s002
(DOCX)
S3 Table. Haplotype-level association analysis of candidate genes using 529 accessions.
https://doi.org/10.1371/journal.pgen.1007323.s003
(DOCX)
S4 Table. The FLA of 529 O. sativa in Hainan and Wuhan.
https://doi.org/10.1371/journal.pgen.1007323.s004
(XLS)
S6 Table. The RNA seq data of OsbHLH genes in the flag leaf of 296 of 529 O.sativa.
https://doi.org/10.1371/journal.pgen.1007323.s006
(XLS)
S1 Fig. Genome-wide association study for FLA in the whole population, the indica and japonica subpopulations by LMM.
Manhattan plots and quantile-quantile plots for flag leaf angle in the full population (A), the indica subpopulation (B) and japonica subpopulation (C). The horizontal dashed lines of the Manhattan plots indicate the significance thresholds that are defined in the section of materials and methods. Lambda of quantile-quantile plots represents the expected null distribution and the observed P value.
https://doi.org/10.1371/journal.pgen.1007323.s007
(TIF)
S2 Fig. The haplotype analysis of qFLA10c/OsbHLH173.
(A) Major haplotyes (haplotypes with more than 5accessions) of OsbHLH173 in the full population according to SNPs data from RiceVarMap version 1. The region contains 2-kb upstream and coding region. The SNP in red and bold is a non-Synonymous SNP. (B) Comparison of the FLA between Hap2 and Hap3 in indica rice and the FLA among Hap4-Hap7 in japonica rice using an independent t-test and a Duncan’s test (P< 0.05), respectively.
https://doi.org/10.1371/journal.pgen.1007323.s008
(TIF)
S3 Fig. The haplotype analysis of QFLA3b/OsbHLH153.
(A) Major haplotyes (haplotypes with more than 5accessions) of OsbHLH153 in the full population according to SNPs data from RiceVarMap version 1. The region contains 2 kb upstream and coding region. The SNP in red and bold is a non-Synonymous SNP. (B) Comparison of the FLA among Hap2-Hap4 in indica rice and the FLA between Hap5 and Hap6 in japonica rice using a Duncan’s test (P< 0.01) and an independent t-test, respectively.
https://doi.org/10.1371/journal.pgen.1007323.s009
(TIF)
S4 Fig. Expression profiles of the subfamily 16 of bHLH.
(A) qRT-PCR expression analysis of OsbHLH153, OsbHLH173 and OsbHLH174 in different tissues of wild type rice. The samples of Root, Stem, Leaf blade, Leaf sheath and Leaf joint were harvested at the transition period of vegetative growth to reproductive growth. (B) The expression profiling of subfamily 16 of bHLH in different tissues, and the expression data was extracted from a database (http://crep.ncpgr.cn/crep-cgi/home.pl). The expression data of BU1 was missing.
https://doi.org/10.1371/journal.pgen.1007323.s010
(TIF)
S5 Fig. The phenotypes of overexpressing OsbHLH153 and OsbHLH173 transgenic plants.
Overexpressing OsbHLH153 (A) and OsbHLH173 (C) transgenic plants increased leaf angle; (B) qRT-PCR analysis of the OsbHLH153 in wild type (WT) and OsbHLH153: OX using leaves at seedling stage; (D) qRT-PCR analysis of the OsbHLH173 in WT and OsbHLH173: OX using leaves at seedling stage.
https://doi.org/10.1371/journal.pgen.1007323.s011
(TIF)
S6 Fig. Overexpressing Style2.1 transgenic plants increased leaf angle.
(A) The plant status of WT and Style2.1: OX at tillering stage; (B) FLA and TSLA of the wild type and Style2.1: OX, n≥ 5; (C) genotyping of transgenic plants Style2.1: OX; (D) reverse transcription PCR (RT-PCR) analysis of the transcripts of Style2.1 in WT and Style2.1: OX at seedling stage.
https://doi.org/10.1371/journal.pgen.1007323.s012
(TIF)
S7 Fig. Comparison of the expression levels of IBH1 among/between haplotypes of OsbHLH174, OsbHLH173 and OsbHLH153 in japonica using RNA-seq data.
Comparison of the expression level of OsIBH1 among/between the haplotypes of OsbHLH174 (A), OsbHLH153 (C) and OsbHLH173 (E) in japonica using RNA-seq data by a Ducan’s test (P< 0.05). Comparison of FLA among/between the haplotypes of OsbHLH174 (B), OsbHLH153 (D) and OsbHLH173 (F) in the corresponding japonica accessions by a Ducan’s test (P< 0.05).
https://doi.org/10.1371/journal.pgen.1007323.s013
(TIF)
Acknowledgments
We thank Mr Jianbo Wang for his excellent work in field management, and Yafen Xing for rice transformation. We appreciate Professor Zhibiao Ye (Huazhong Agricultural University) kindly providing the DNA samples of Solanum pennellii. We thank Xiaokai Li (Huazhong Agricultural University) for the help in the experiment.
References
- 1. Song Q, Zhang G, Zhu XG. Optimal crop canopy architecture to maximise canopy photosynthetic CO2 uptake under elevated CO2 –a theoretical study using a mechanistic model of canopy photosynthesis. Funct Plant Biol. 2013;40(2):108–24.
- 2. Van Zanten M, Pons TL, Janssen JAM, Voesenek LACJ, Peeters AJM. On the Relevance and Control of Leaf Angle. Critical Reviews in Plant Sciences. 2010;29(5):300–16.
- 3. Zhu XG, Long SP, Ort DR. What is the maximum efficiency with which photosynthesis can convert solar energy into biomass? Current Opinion in Biotechnology. 2008;19(2):153–9. pmid:18374559
- 4. Cheng SH, Cao LY, Zhuang JY, Chen SG, Zhan XD, Fan YY, et al. Super Hybrid Rice Breeding in China: Achievements and Prospects. Journal of Integrative Plant Biology. 2007;49(6):805–10.
- 5. Peng S. Evolution of the new plant ideotype for increased yield potential. Breaking the Yield Barrier. 1994:5–20.
- 6. Peng S, Cassman KG, Virmani SS, Sheehy J, Khush GS. Yield Potential Trends of Tropical Rice since the Release of IR8 and the Challenge of Increasing Rice Yield Potential. Crop Science. 1999;39(6):1552–9.
- 7.
Yuan LP, Peng S, Hardy B, editors. Breeding of super hybrid rice. Rice research for food security and poverty alleviation Proceedings of the International Rice Research Conference, Los Baños, Philippines, 31 March-3 April, 2000; 2001.
- 8. Sinclair TR, Sheehy JE. Erect Leaves and Photosynthesis in Rice. Science. 1999;283(5407):1456–7.
- 9. Wada K, Marumo S, Abe H, Morishita T, Nakamura K, Uchiyama M, et al. A Rice Lamina Inclination Test—A Micro-quantitative Bioassay for Brassinosteroids. Agricultural and Biological Chemistry. 1984;48(3):719–26.
- 10. Wada K, Marumo S, Ikekawa N, Morisaki M, Mori K. Brassinolide and Homobrassinolide Promotion of Lamina Inclination of Rice Seedlings. Plant and Cell Physiology. 1981;22(2):323–5.
- 11. Bai MY, Zhang LY, Gampala SS, Zhu S-W, Song WY, Chong K, et al. Functions of OsBZR1 and 14-3-3 proteins in brassinosteroid signaling in rice. Proceedings of the National Academy of Sciences of the United States of America. 2007;104(34):13839–44. pmid:17699623
- 12. Hong Z, Ueguchi-Tanaka M, Umemura K, Uozu S, Fujioka S, Takatsuto S, et al. A Rice Brassinosteroid-Deficient Mutant, ebisu dwarf (d2), Is Caused by a Loss of Function of a New Member of Cytochrome P450. The Plant Cell. 2003;15(12):2900–10. pmid:14615594
- 13. Sakamoto T, Morinaka Y, Ohnishi T, Sunohara H, Fujioka S, Ueguchi-Tanaka M, et al. Erect leaves caused by brassinosteroid deficiency increase biomass production and grain yield in rice. Nat Biotech. 2006;24(1):105–9.
- 14. Yamamuro C, Ihara Y, Wu X, Noguchi T, Fujioka S, Takatsuto S, et al. Loss of Function of a Rice brassinosteroid insensitive1 Homolog Prevents Internode Elongation and Bending of the Lamina Joint. The Plant Cell. 2000;12(9):1591–606. pmid:11006334
- 15. Song Y, You J, Xiong L. Characterization of OsIAA1 gene, a member of rice Aux/IAA family involved in auxin and brassinosteroid hormone responses and plant morphogenesis. Plant Molecular Biology. 2009;70(3):297–309. pmid:19266169
- 16. Zhang S, Wang S, Xu Y, Yu C, Shen C, Qian Q, et al. The auxin response factor, OsARF19, controls rice leaf angles through positively regulating OsGH3-5 and OsBRI1. Plant, Cell & Environment. 2015;38(4):638–54.
- 17. Shimada A, Ueguchi-Tanaka M, Sakamoto T, Fujioka S, Takatsuto S, Yoshida S, et al. The rice SPINDLY gene functions as a negative regulator of gibberellin signaling by controlling the suppressive function of the DELLA protein, SLR1, and modulating brassinosteroid synthesis. The Plant Journal. 2006;48(3):390–402. pmid:17052323
- 18. Ueguchi-Tanaka M, Fujisawa Y, Kobayashi M, Ashikari M, Iwasaki Y, Kitano H, et al. Rice dwarf mutant d1, which is defective in the α subunit of the heterotrimeric G protein, affects gibberellin signal transduction. Proceedings of the National Academy of Sciences of the United States of America. 2000;97(21):11638–43. pmid:11027362
- 19. Ning J, Zhang B, Wang N, Zhou Y, Xiong L. Increased Leaf Angle 1, a Raf-Like MAPKKK That Interacts with a Nuclear Protein Family, Regulates Mechanical Tissue Formation in the Lamina Joint of Rice. The Plant Cell. 2011;23(12):4334–47. pmid:22207574
- 20. Sun S, Chen D, Li X, Qiao S, Shi C, Li C, et al. Brassinosteroid Signaling Regulates Leaf Erectness in Oryza sativa via the Control of a Specific U-Type Cyclin and Cell Proliferation. Developmental Cell. 2015;34(2):220–8. pmid:26190148
- 21. Lee J, Park JJ, Kim SL, Yim J, An G. Mutations in the rice liguleless gene result in a complete loss of the auricle, ligule, and laminar joint. Plant molecular biology. 2007;65(4):487–99. pmid:17594063
- 22. Hu WD, Zhang H, Jiang JH, Wang YY, Sun DY, Wang XS, et al. Genetic Analysis and QTL Mapping of Large Flag Leaf Angle Trait in Japonica Rice. Rice Science. 2012;19(4):277–85.
- 23. Li Z, Paterson AH, Pinson SRM, Stansel JW. RFLP facilitated analysis of tiller and leaf angles in rice (Oryza sativa L.). Euphytica: Netherlands journal of plant breeding. 1999;109(2):79–84.
- 24. Yan J, Zhu J, He C, Benmoussa M, Wu P. Molecular Marker-Assisted Dissection of Genotype × Environment Interaction for Plant Type Traits in Rice (Oryza sativa L.). Crop Science. 1999;39(2):538–44.
- 25. Huang X, Han B. Natural variations and genome-wide association studies in crop plants. Annual Review of Plant Biology. 2013;65(1):531.
- 26. Rafalski JA. Association genetics in crop improvement. Current Opinion in Plant Biology. 2010;13(2):174–80. pmid:20089441
- 27. Tian F, Bradbury PJ, Brown PJ, Hung H, Sun Q, Flint-Garcia S, et al. Genome-wide association study of leaf architecture in the maize nested association mapping population. Nat Genet. 2011;43(2):159–62. pmid:21217756
- 28. Huang X, Wei X, Sang T, Zhao Q, Feng Q, Zhao Y, et al. Genome-wide association studies of 14 agronomic traits in rice landraces. Nat Genet. 2010;42(11):961–7. pmid:20972439
- 29. Lu Q, Zhang M, Niu X, Wang S, Xu Q, Feng Y, et al. Genetic variation and association mapping for 12 agronomic traits in indica rice. BMC Genomics. 2015;16:1067. pmid:26673149
- 30. Dong H, Zhao H, Xie W, Han Z, Li G, Yao W, et al. A Novel Tiller Angle Gene, TAC3, together with TAC1 and D2 Largely Determine the Natural Variation of Tiller Angle in Rice Cultivars. PLOS Genetics. 2016;12(11):e1006412. pmid:27814357
- 31. Heang D, Sassa H. Antagonistic Actions of HLH/bHLH Proteins Are Involved in Grain Length and Weight in Rice. PLoS ONE. 2012;7(2):e31325. pmid:22363621
- 32. Heang D, Sassa H. An atypical bHLH protein encoded by POSITIVE REGULATOR OF GRAIN LENGTH 2 is involved in controlling grain length and weight of rice through interaction with a typical bHLH protein APG. Breeding Science. 2012;62(2):133–41. pmid:23136524
- 33. Jang S, An G, Li HY. Rice Leaf Angle and Grain Size Are Affected by the OsBUL1 Transcriptional Activator Complex. Plant Physiology. 2017;173(1):688–702. pmid:27879391
- 34. Carretero-Paulet L, Galstyan A, Roig-Villanova I, Martínez-García JF, Bilbao-Castro JR, Robertson DL. Genome-Wide Classification and Evolutionary Analysis of the bHLH Family of Transcription Factors in Arabidopsis, Poplar, Rice, Moss, and Algae. Plant Physiology. 2010;153(3):1398–412. pmid:20472752
- 35. Li X, Duan X, Jiang H, Sun Y, Tang Y, Yuan Z, et al. Genome-Wide Analysis of Basic/Helix-Loop-Helix Transcription Factor Family in Rice and Arabidopsis. Plant Physiology. 2006;141(4):1167–84. pmid:16896230
- 36. Tanaka A, Nakagawa H, Tomita C, Shimatani Z, Ohtake M, Nomura T, et al. BRASSINOSTEROID UPREGULATED1, Encoding a Helix-Loop-Helix Protein, Is a Novel Gene Involved in Brassinosteroid Signaling and Controls Bending of the Lamina Joint in Rice. Plant Physiology. 2009;151(2):669–80. pmid:19648232
- 37. Zhang LY, Bai MY, Wu J, Zhu JY, Wang H, Zhang Z, et al. Antagonistic HLH/bHLH Transcription Factors Mediate Brassinosteroid Regulation of Cell Elongation and Plant Development in Rice and Arabidopsis. The Plant Cell. 2009;21(12):3767–80. pmid:20009022
- 38. Han Z, Zhang B, Zhao H, Ayaad M, Xing Y. Genome-Wide Association Studies Reveal that Diverse Heading Date Genes Respond to Short and Long Day Lengths between Indica and Japonica Rice. Frontiers in Plant Science. 2016;7:1270. pmid:27621738
- 39. Zhang L, Li Q, Dong H, He Q, Liang L, Tan C, et al. Three CCT domain-containing genes were identified to regulate heading date by candidate gene-based association mapping and transformation in rice. Scientific reports. 2015;5.
- 40. Chen KY, Cong B, Wing R, Vrebalov J, Tanksley SD. Changes in Regulation of a Transcription Factor Lead to Autogamy in Cultivated Tomatoes. Science. 2007;318(5850):643–5. pmid:17962563
- 41. Atchley WR, Terhalle W, Dress A. Positional Dependence, Cliques, and Predictive Motifs in the bHLH Protein Domain. Journal of Molecular Evolution. 1999;48(5):501–16. pmid:10198117
- 42. Ellenberger T, Fass D, Arnaud M, Harrison SC. Crystal structure of transcription factor E47: E-box recognition by a basic region helix-loop-helix dimer. Genes & Development. 1994;8(8):970–80.
- 43. Massari ME, Murre C. Helix-Loop-Helix Proteins: Regulators of Transcription in Eucaryotic Organisms. Molecular and Cellular Biology. 2000;20(2):429–40. pmid:10611221
- 44. Wang H, Zhu Y, Fujioka S, Asami T, Li J, Li J. Regulation of Arabidopsis Brassinosteroid Signaling by Atypical Basic Helix-Loop-Helix Proteins. The Plant Cell. 2009;21(12):3781–91. pmid:20023194
- 45. Zhao H, Yao W, Ouyang Y, Yang W, Wang G, Lian X, et al. RiceVarMap: a comprehensive database of rice genomic variations. Nucleic Acids Research. 2015;43(D1):D1018–D22.
- 46. Chen W, Gao Y, Xie W, Gong L, Lu K, Wang W, et al. Genome-wide association analyses provide genetic and biochemical insights into natural variation in rice metabolism. Nat Genet. 2014;46(7):714–21. pmid:24908251
- 47. Alexander DH, Lange K. Enhancements to the ADMIXTURE algorithm for individual ancestry estimation. BMC Bioinformatics. 2011;12(1):246.
- 48. Lippert C, Listgarten J, Liu Y, Kadie CM, Davidson RI, Heckerman D. FaST linear mixed models for genome-wide association studies. Nat Meth. 2011;8(10):833–5.
- 49. Li MX, Yeung JMY, Cherny SS, Sham PC. Evaluating the effective numbers of independent tests and significant p-value thresholds in commercial genotyping arrays and public imputation reference datasets. Human Genetics. 2012;131(5):747–56. pmid:22143225
- 50. Wang Q, Xie W, Xing H, Yan J, Meng X, Li X, et al. Genetic Architecture of Natural Variation in Rice Chlorophyll Content Revealed by a Genome-Wide Association Study. Molecular Plant. 2015;8(6):946–57. pmid:25747843
- 51. Xie W, Wang G, Yuan M, Yao W, Lyu K, Zhao H, et al. Breeding signatures of rice improvement revealed by a genomic variation map from a large germplasm collection. Proceedings of the National Academy of Sciences of the United States of America. 2015;112(39):E5411–E9. pmid:26358652
- 52. Lu L, Shao D, Qiu X, Sun L, Yan W, Zhou X, et al. Natural variation and artificial selection in four genes determine grain shape in rice. New Phytologist. 2013;200(4):1269–80. pmid:23952103
- 53. Hiei Y, Ohta S, Komari T, Kumashiro T. Efficient transformation of rice (Oryza sativa L.) mediated by Agrobacterium and sequence analysis of the boundaries of the T-DNA. The Plant Journal. 1994;6(2):271–82. pmid:7920717
- 54. Lin YJ, Zhang Q. Optimising the tissue culture conditions for high efficiency transformation of indica rice. Plant Cell Reports. 2005;23(8):540–7. pmid:15309499
- 55. Murray MG, Thompson WF. Rapid isolation of high molecular weight plant DNA. Nucleic Acids Research. 1980;8(19):4321–5. pmid:7433111