Fertilization controls tiller numbers via transcriptional regulation of a MAX1-like gene in rice cultivation

Cui, Jinying; Nishide, Noriko; Mashiguchi, Kiyoshi; Kuroha, Kana; Miya, Masayuki; Sugimoto, Kazuhiko; Itoh, Jun-Ichi; Yamaguchi, Shinjiro; Izawa, Takeshi

doi:10.1038/s41467-023-38670-8

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Published: 08 June 2023

Fertilization controls tiller numbers via transcriptional regulation of a MAX1-like gene in rice cultivation

Nature Communications volume 14, Article number: 3191 (2023) Cite this article

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Abstract

Fertilization controls various aspects of cereal growth such as tiller number, leaf size, and panicle size. However, despite such benefits, global chemical fertilizer use must be reduced to achieve sustainable agriculture. Here, based on field transcriptome data from leaf samples collected during rice cultivation, we identify fertilizer responsive genes and focus on Os1900, a gene orthologous to Arabidopsis thaliana MAX1, which is involved in strigolactone biosynthesis. Elaborate genetic and biochemical analyses using CRISPR/Cas9 mutants reveal that Os1900 together with another MAX1-like gene, Os5100, play a critical role in controlling the conversion of carlactone into carlactonoic acid during strigolactone biosynthesis and tillering in rice. Detailed analyses of a series of Os1900 promoter deletion mutations suggest that fertilization controls tiller number in rice through transcriptional regulation of Os1900, and that a few promoter mutations alone can increase tiller numbers and grain yields even under minor-fertilizer conditions, whereas a single defective os1900 mutation does not increase tillers under normal fertilizer condition. Such Os1900 promoter mutations have potential uses in breeding programs for sustainable rice production.

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Introduction

Plant growth requires nutrition in the form of nitrogen (N), phosphorous (P), potassium (K), and minerals incorporated mainly from the soil, as well as carbohydrates obtained through photosynthetic activity¹. Although the development of chemical fertilizers has led to increased crop yield, that of major cereal crops is limited by lodging caused by overgrowth. In breeding programs of the Green Revolution (1940–1960s), genetic improvement through the use of semi-dwarf traits successfully boosted lodging resistance in wheat and rice, achieving historic yield increases that saving many lives^2,3,4,5. These semi-dwarf traits were obtained through a few genetic changes in the biosynthesis or signaling pathways of gibberellin (GA) phytohormones. However, the overuse of chemical fertilizers has led to aquatic and terrestrial pollution, including water eutrophication and soil consolidation⁵. The application of chemical fertilizer in agriculture also requires advance investment prior to income realization. Thus, chemical fertilizer-based agriculture is unsustainable, and more sustainable agricultural methods to reduce the demand of chemical fertilizer are sought globally⁶.

Fertilization results in biological changes in many plant growth parameters, particularly increases in tiller (i.e., cereal branch) number. This is closely related to panicle number, leaf size, and panicle size, all of which help improve cereal yield⁶. Fertilizer regulates branching via mediating the phytohormone balance¹. The phytohormone of strigolactone (SL), which can be induced in poor soil⁷, is also involved in branching regulation¹. Moreover, SL biosynthesis- and signaling-deficient mutants e.g., d17, d27, d3 in rice displayed insensitivity to nutrient depletion⁸, while mutants for either the SL—biosynthesis or SL—signaling pathway contributed significantly to the increase in branching or tiller numbers^9,10,11.

Inorganic P is often presented as an insoluble complex in soil, which greatly hinders the accessibility of P to plants^12,13. Therefore, apart from the direct uptake of soluble P by roots¹⁴, plants such as rice and soybean have developed an indirect absorption method, i.e., P transfers from mycorrhizal hyphae into root cortical cells to ensure sufficient supply^15,16. For such an indirect nutrient uptake, SLs act as signaling molecules to establish necessary symbiosis between the host plant and arbuscular mycorrhizal (AM) fungi¹⁷. As reported, many genes synergistically promote SL biosynthesis in rice via a multi-step biochemical reactions including the formation of carlactone (CL) from all-trans-β-carotene and its further transformations to carlactonoic acid (CLA), 4-deoxyorobanchol (4DO), and orobanchol (ORO, a hydroxylated 4DO)^18,19.

A rice genomic region, which contains deletions of both Os900 (Os01g0700900) and Os1400 (Os01g0701400) genes that are homologous to MORE AXILLARY GROWTH1 (MAX1) gene in A. thaliana, was identified as a major quantitative trait locus (QTL) influencing tiller number and SL-derivative biosynthesis²⁰. MAX1 gene encodes a cytochrome P450 enzyme for SL biosynthesis to regulate branching in A.thaliana⁹. It has been known that MAX1 gene and its orthologs play essential roles in the transformation of CL in many plants²¹. Unlike dicotyledons, however, such as A. thaliana and tomato possessing only one MAX1 gene for the conversion of CL into CLA in their genomes^9,22,23, multiple MAX1 genes exist in monocotyledons like rice and maize¹⁸. The rice genome consists of five MAX1-like genes, Os900, Os1400, Os1500 (Os01g0701500), Os1900 (Os02g0221900), and Os5100 (Os06g0565100), while Os1500 among them is considered as a loss-of-function allele according to the DNA sequence data^18,19. Until very recently, no study besides the above QTL analysis has been carried out to analyze mutations of these MAX1-like genes in rice. Based on an extensive analysis of os900 mutants, Ito et al. (2022) strongly suggest that canonical SLs such as 4DO are important rhizospheric signals but not the major determinant of tillering²⁴. Thus, how rice each MAX1-like gene is involved in rice tillering remains an open question in this field. It is also reported that the P starvation can induce the expression of Os900 and Os1900 (but not for Os1400 and Os5100)²⁵, which Os900 and Os1400, as the QTL genes, facilitate the biochemical CL-to-CLA conversion and the further biosynthesis from CLA to 4DO (by Os900) and from 4DO to ORO (by Os1400) in vitro^18,19. By contrast, Os1900 and Os5100 transfer only small amount of CL into 4DO in vitro¹⁹. Apparently, Os900 and Os1400 rather than Os1900 or Os5100 are considered as major genetic contributors so far in the biosynthesis of 4DO and ORO in rice.

In this study, we show that the fertilizer-responsive MAX1-like gene, Os1900, cooperating with Os5100, contribute to the CL-to-CLA conversion to regulate tillering in rice. Furthermore, the study on a series of cis-regulatory variations in Os1900 reveals that fertilizer mediates tillering through the transcriptional regulation of Os1900 and such artificial promoter variations have great potential for the agricultural applications, which will lay the foundation for breeding novel rice varieties with low fertilizer demand and high production yield.

Results and discussion

To elucidate the molecular mechanisms of fertilizer response in rice in real paddy field cultivation, we first performed field transcriptome analysis of leaf samples from rice plants that were grown under three fertilization treatments (None, Once, Twice, as shown in Fig. 1a) in adjacent paddy fields, and analyzed the frequency distribution of panicle and seed numbers of tested plants. Rice panicle numbers and grain yields increased clearly in association with additional fertilization treatment (Fig. 1b and Supplementary Fig. 1a, b). To confirm the effects of fertilization on gene expression in response to environmental factors in rice cultivation, we collected leaf samples on eight different dates after transplanting for transcriptome analysis (at 10:00 and 16:00 randomly during the sampling terms, see details in Fig. 1a, Supplementary Data 1, 2). Accordingly, these transcriptome data showed broad variations due to fluctuating environmental factors such as ambient temperature and solar radiation, as well as endogenous factors e.g., growth stage and circadian clock phase. A principal component analysis (PCA), which was conducted using these transcriptome data, indicated that the factors including sampling time and transplantation time besides fertilization had the greatest influence on the transcriptome (Supplementary Fig. 1c). Thus, these data encompass the effects of all environmental factors as well as fertilization. Accordingly, in this transcriptome data the effects of fertilizers were relatively low against the fluctuations of gene expression due to various environmental stimuli in nature, which can be represented by the standard deviations of those data. Then, in order to only highlight effects of fertilizer using such data from the real rice cultivations, we plotted the expression fold changes against fertilization (FCs) versus their ratios (FC/SDs) to the standard deviation (SD) of gene expression among all tested samples for each gene (Fig. 1c). Genes with high FCs and high FC/SD ratios can be further identified as candidate genes related to fertilizer effects (Fig. 1c). With these fluctuating data, we repeated simple paired t-test using only different fertilization conditions for many sample combinations (Supplementary Data 1, 3). These paired t-tests suggest that 107 genes are stable fertilizer-responsive genes in rice leaves under natural paddy field conditions (Fig. 1d, Supplementary Data 3).

**Fig. 1: Rice gene expression in response to fertilization under natural paddy field conditions.**

Considering the annotation information for the identified 107 genes and the FC/SD ratio, we focused on Os1900, a rice MAX1-like gene involved in SL biosynthesis (Fig. 1c, d) since we came up with an idea in which fertilizer-controlled transcript of Os1900 can be a key to explain the relationship between fertilizer and tillering in rice. It is known that some of SL-related genes, e.g., D10, D17, D27, Os900 and Os1900⁷, respond to changes in the concentration of the major plant nutrient of P²⁵. However, only Os1900 expression is repressed by fertilization in the leaf samples under paddy field cultivation conditions, where their tissue specific expression might be involved. A question then arises: does fertilization control tiller numbers via Os1900 in rice? In addition to Os1900, other MAX1-like genes such as Os900, Os1400, and Os5100 were reported to restore max1 mutant in A. thaliana to the wild type phenotypes when artificially expressed^20,26. Since Os5100 is more closely homologous to Os1900 than the other MAX1-like genes¹⁸, CRISPR-Cas9 mutants of Os1900 and Os5100 including os1900 single, os5100 single and os1900&os5100 double mutant (Fig. 2a; Supplementary Fig. 2a–c) were generated. Unexpectedly, we only observed significant increase of tillers in os1900&os5100 double mutant plants under normal fertilization conditions, rather than in the os1900 or os5100 single mutant plants (Fig. 2c, d). Notably, several independent T₀ mutants having os1900&os5100 double mutations exhibited similar phenotypes (Supplementary Fig. 2d). To exclude any unexpected mutations through off-target CRISPR/Cas9 action, we examined k-mer coverages using rice genome DNA sequences (IRGSP1.0) as references for all MAX1-like gene regions of the os1900&os5100 double mutations. The k-mer gaps indicated that mutations occurred only in Os1900 and Os5100 instead of in Os900, Os1400, or Os1500 (Fig. 2b).

**Fig. 2: Phenotypic analysis and genotype identification results for the *os1900*&*os5100* mutant.**

Given that environmental factors such as ambient temperature and radiation often influence axillary bud dormancy (or elongation), branching, or tiller (branch) numbers under natural cultivation conditions²⁷, we cultivated the wild-type (WT, cv. Koshihikari) and os1900&os5100 double mutant plants under four different photoperiod and ambient temperature conditions, which showed consistent phenotypes for each condition (Fig. 2e) in spite of differences in tiller numbers among treatments. Thus, these tiller number phenotypes were very stable in the os1900&os5100 double mutants. In addition, the double mutants produced more secondary and tertiary tillers instead of primary tillers than WT plants. After one month of sowing without fertilization, however, even the os1900&os5100 double mutants exhibited no increase in tiller numbers (Supplementary Fig. 3a, b). Since it is known that the lack of nitrate reduces shoot branching in A. thaliana²⁸, in the absence of nutrient uptake, the rice plants could not execute axial bud elongation anymore.

As described above, Os900 and Os1400 were previously identified as major QTLs using Azucena and Bala as parent cultivars²⁰, which strongly implies that they are the major genetic contributors to tillering in rice. To solve this controversy, we further generated the os900&os1400 double mutants and compared its phenotypes with os1900&os5100 double mutants (Supplementary Fig. 4a) under normal fertilizer conditions. We found a considerably sharper increase of tiller numbers in os1900&os5100 double mutants than that in os900&os1400 mutants (Supplementary Fig. 4b, c). Even under minor and trace fertilization conditions, os900&os1400 displayed almost same tiller number with wild type (Supplementary Fig. 4d). This indicates that tiller number was mainly regulated by Os1900 & Os5100, although Os900 and Os1400 together contributed to the control of maintained natural variations in tiller number among the rice cultivars.

Recent next-generation sequencing analysis of various rice genomes has revealed that the region carrying Os900 and Os1400 represent more likely an insertion in an ancient Oryza sativa subsp. japonica accession, rather than a deletion in another ancient Oryza sativa subsp. indica accession²⁹. Because the induced expression of Os900 by P starvation in roots resembles that of Os1900 in shoots²⁵, this insertion could be an adaptation for enhanced P acquisition^29,30 by inducing hyphal branching of arbuscular mycorrhizal fungi¹⁷. Taking these into consideration, Os1900 and Os5100 may have been originally involved in the regulation of tiller dormancy and subsequent elongation with response to fertilization.

The previous transient expression assay using Nicotiana benthamiana revealed more enzymatic activity of Os900 and Os1400 proteins than those of Os1900 and Os5100 proteins in the biosynthesis of 4DO and ORO (Fig. 3a)¹⁹. Os1900 and Os5100 proteins could convert only a small amount of CL into 4DO¹⁹. In addition, the CL feeding assay using recombinant proteins in yeast suggested that Os1900 and Os5100 can catalyze the conversion of CL to CLA¹⁸. However, the genetic roles of Os1900 and Os5100 in SL biosynthesis remain elusive in rice.

**Fig. 3: Analyses of strigolactone (SL) biosynthesis in WT and *os1900*&*os5100* mutant plants.**

In this context, we performed liquid chromatography–tandem mass spectrometry (LC–MS/MS) to measure the SLs content in the extracts from shoots and roots of WT (a cultivar termed Koshihikari) and os1900&os5100 double mutant from young rice seedlings (Fig. 3b, c and Supplementary Fig. 5a, b).

Tremendous CL accumulation was observed in both shoots and roots in os1900&os5100 double mutants (Fig. 3b, c). The accumulation in shoots was up to approximately 92,000 pg/g fresh weight, which was significantly superior to that in WT (Fig. 3b), while only tiny amount of CLA was detected in os1900&os5100 double mutants. Notably, the detected amount of CL in shoots (Fig. 3b) exceeds that in roots (Fig. 3c) in the os1900&os5100 double mutants with almost triple digit difference. MAX1 gene is a crucial gene to convert CL into CLA in A.thaliana, the same as the reported activity of Os900 and Os1400 in rice^18,19,22. When MAX1-like transcripts were examined, Os900 and Os1400 genes exhibited the same transcriptional levels in os1900&os5100 mutants as those in WT in both shoots and roots (Fig. 3d, e), while Os1900 and Os5100 genes exhibited significantly lesser transcriptional levels in os1900&os5100, may be due to the incomplete nonsense-mediated mRNA decay (Fig. 3d, e). Thus, different accumulation of CLs between shoots and roots can be ascribed to the higher expression of Os900 and Os1400 in the roots, thus resulting in higher consumption of CL in roots²⁵ (Fig. 3d, e). Accordingly, the loss of function mutations of Os1900 and Os5100 directly causes the accumulation of CL in shoots and roots of os1900&os5100 mutants.

Small amount of 4DO was detected in shoots of the os1900&os5100 double mutants while no 4DO was detected in WT shoots (Supplementary Fig. 5a). Although there is no difference of Os900 (which converts CL to 4DO¹⁸) expression at shoot samples (Fig. 3d), it was induced at stem base and tiller base in os1900&os5100 mutants (Supplementary Fig. 5c, d). This might result in the small amounts of 4DO in shoots of the double mutants. Furthermore, larger amounts of 4DO were detected in the roots of the os1900&os5100 double mutants than that of WT (Supplementary Fig. 5b), despite no induced expression of Os900 (Fig. 3e). This agrees with the phenomenon that Os900 protein facilitates CLA carboxylation into 4DO via intramolecular cyclization in vitro^18,19, as Os900 expression was detected predominantly in roots²⁵. It is possible that Os900 can immediately produce 4DO from accumulated CL, and the intermediate, CLA, is not sufficiently released during this conversion. Taken together, the higher level of 4DO in the roots of os1900&os5100 double mutants may be due to the conversion of the excessively accumulated CL to 4DO by Os900 in the roots. No ORO, which is a hydroxylated 4DO catalyzed by Os1400 as the final product of proposed SL biosynthetic pathway^18,19 (Fig. 3a), was detected in the WT or os1900&os5100 double mutants in this study. Pairwise sequence alignment in Os1400 between Azucena, an ORO-producing cultivar²⁰ and Koshihikari showed a single-nucleotide polymorphism (SNP), G-to-A in the exon 5, that results in the R-to-Q substitution of the corresponding amino acid (Supplementary Fig. 6a). This R in this corresponding amino acid site is highly conserved in MAX1 homologous genes among the plant kingdom (Supplementary Fig. 6b, c); and we only found the SNP change from R to Q among Oryza sativa subsp. japonica cultivars including Koshihikari (Supplementary Fig. 6d), suggesting that the R-to-Q amino acid substitution may result in a weak enzymatic activity of the Koshihikari-type of Os1400 protein.

Methyl carlactonoate (MeCLA) that is produced through CLA methylation in A. thaliana²², was under the detection limit in the shoots and the roots of os1900 & os5100 (Supplementary Fig. 5a, b), which may be because of the absence of its precursor, CLA.

As reported in other known SL biosynthesis mutants³¹, axillary bud elongation in os1900&os5100 was inhibited by the application of the synthetic SL analog (+)-GR24, and the inhibitory effect was weak under low concentration (Fig. 3f–h), which reminds that although small amounts of 4DO were detected in shoots of the os1900&os5100 double mutants (Supplementary Fig. 5a), the os1900&os5100 double mutants produced more tillers than WT, indicating that those small amounts of 4DO could not rescue the higher tiller number phenotype in the os1900&os5100 double mutants compared to WT.

To reveal the genome-wide effects of the key MAX1-like genes to establish the tillering phenotypes in this study, i.e., genetic roles of Os1900 and Os5100 in transcriptome and their potential physiological roles, RNA-seq analysis was performed on leaves and tiller bases of WT and os1900&os5100 (Supplementary Fig. 7-9). Plenty of differentially expressed genes (DEGs) in both tiller bases and leaves were identified by QLF test in edge R with FDR < 0.01 (Supplementary Fig. 7b and Supplementary Data5). The mean of log2FC values between WT and the os1900&os5100 double mutants were used in graphs (Supplementary Fig. 7-9). Some key genes expression was confirmed with real-time qPCR using same samples (Supplementary Fig. 7, 10). With os1900 & os5100 double mutations, which have blocked conversion from CL to CLA, inhibiting the production of active SLs, we first revealed that the genetic loss in Os1900 & Os5100 decreased the expression of D53, a key repressor gene of SLs signaling, in both tiller bases and leaves (Supplementary Fig. 7c). However, the expression of D14, a SL receptor that 4DO can bind to, displayed slightly higher level in os1900&os5100 double mutants (Supplementary Fig. 7d), which can be assigned to a feedback enhancement of SL sensitivity (Supplementary Fig. 7c) and Os900-induced production of more 4DO (consistently with data in Supplementary Fig. 5). Besides, the rice Teosinte Branched 1 (OsTB1), a negative regulator of branching, was down-regulated with only half fold difference in os1900&os5100 double mutants (Supplementary Fig. 7d), which is consistent with the insensitivity of tb1 mutants to GR24³². In this context, the drastic CL accumulation accompanied with the production of trace SLs in os1900&os5100, have associations (or influences) on the expression of genes related to SL biosynthesis and signal transduction.

Unexpectedly, we further found transcriptional regulations related to biosynthesis and signaling of other phytohormones by Os1900 &Os5100 based on the RNA-seq data. Both cytokinins (CKs) and SLs are second messengers of auxin that can regulate plant architectures. SLs interfere with the formation of auxin-conducting channels by inhibiting the intracellular accumulation of PINs in A.thaliana³³. In our data, the expression of these auxin transporter genes, i.e., PIN FORMED5a (PIN5a), PIN9, and AUXIN4 (AUX4) were down-regulated in the tiller bases of os1900&os5100 (Supplementary Fig. 8a). We found induced expression of CKs-biosynthesis related genes (i.e., LONELY GUY 1(LOG) and LOG-Like genes) and a CKs-signaling related gene (i.e., A-TYPE RESPONSE REGULATOR 2 (RR2)) in tiller bases or leaves in os1900 & os5100 double mutant, while the expression of CKs-inactivation- related genes (i.e., cytokinin oxidases (CKXs)) was repressed (Supplementary Fig. 8b), which was consistent with that CKs is the hormone for promoting tiller elongation³⁴.

The key genes related to ABA and JA signal transduction (i.e., Serine/threonine protein kinases (SAPKs), a type 2 C protein phosphatase (PP2C), and JASMONATE-ZIM-domain (JAZ) proteins) were up-regulated in os1900&os5100 (Supplementary Fig. 8c,d), indicative of controlled axillary bud dormancy by SLs via mediating the ABA and JA signaling pathways in rice³⁵. Furthermore, the expression of genes related to biosynthesis and signaling of salicylic acids (SAs) was induced thus promoting the CO₂ fixation³⁶ (Supplementary Figs. 8g and 9a). Taken together, differentially expressed genes related to CKs, auxins biosynthesis and signaling pathways; ABA signal pathway; JA biosynthesis pathway behaved in the same manner in tiller bases as that in leaves (Supplementary Fig. 7, 8). These results clearly revealed the central role of Os1900 & Os5100 in controlling most of phytohormone signaling networks to control tiller dormancy and elongation in rice.

In the previous studies, it has been shown that SLs are synthesized in roots and transported upward to the stem bases to inhibit branching (or tillering)^9,37. In this study, Os1900 and Os5100 clearly are expressed in shoot, e.g., stem base and tiller base (Fig. 3d, Supplementary Fig. 5c, d). The in situ expression analysis of Os1900 and Os5100 reveals their transcripts around axial bud apex regions and a slightly distinct expression pattern of Os5100 from those of Os1900 near vascular tissues around apex regions (Fig. 3i). Together, these findings imply that the expression pattern of in vivo Os1900 and Os5100 proteins at tiller bases, corresponding to the distribution of genuine MAX1 enzymatic activity and the spatial transformation of CL to CLA including possible transportation of SL derivatives from shoots needs to be further revealed to understand detailed regulation of tillers in rice^22,23,38.

FT-like genes i.e., Hd3a in rice³⁹ and PtFT1 in Populus tomentosa^40,41 could break axillary bud dormancy and promote the lateral branching. In our data, a FT-like gene of FTL6 had a higher expression level in leaves in os1900&os5100 than that in WT (Supplementary Fig. 9b). Thus, there was a possibility that FTL6 was also involved in breaking axillary bud dormancy in rice. In addition, since OsMFT1 and OsMFT2, could break seed dormancy⁴², it is also possible that the increased expression of OsMFT1 in both leaves and tiller bases in os1900&os5100 are involved in the tiller number phenotypes (Supplementary Fig. 9b).

Although Os1900 was responsive to fertilization, the tiller numbers did not increase for os1900 single mutant under normal experimental conditions (Fig. 2c, d). Thus, we conducted a detailed gene expression analysis of Os1900 expression under laboratory conditions (Fig. 4a). More specifically, fertilizer was applied once on the 7^th day after sowing. Os1900 expression remained at the baseline level until the 13^th day after sowing, when fertilizer concentration (in terms of total dissolved solids, TDS) gradually decreased down to ~60 ppm (Fig. 4b-i). From the 14^th day, Os1900 was gradually expressed as TDS concentration decreased (Fig. 4b-i). Thus, Os1900 expression was strongly repressed under moderate fertilization conditions in young seedlings, which gradually expressed in response to a decrease in soluble fertilizer concentration. When TDS concentration was reduced to 30 ppm, Os1900 expression raised significantly compared to that at higher TDS concentration (Fig. 4b-i). For the individuals with high expression of Os1900, fertilizer treatment resulted in rapid decrease in Os1900 expression to basal levels within 1 h (Fig. 4b-ii, -iii, -iv). The expression dynamics of Os1900 under the laboratory conditions implied that its biological role could be clarified at lower-than-normal fertilization conditions. Therefore, we examined the tiller number phenotypes of os1900 single, os5100 single, and os1900&os5100 double mutants by using minor- and trace-fertilization conditions. We only found a mild increase in tiller numbers for the single os1900 mutation upon fertilization in trace level (Fig. 4c, d), indicating that though os1900 mutation resulted in no changes in the gene expression of Os5100 (Supplementary Fig. 3c). Fertilizer responses of Os1900 transcripts and the tillering phenotype in related mutants implies the importance of transcriptional regulation of Os1900 to control tiller number in rice. Thus, the identification of key cis-regulatory sites in the Os1900 promoter related to complex fertilization responses would help to elucidate the molecular mechanisms of transcriptional regulation in fertilization responses and tiller number control in rice. Although CRISPR/Cas9 mutants generated by targeting protein coding regions often result in clear loss-of-function alleles and extreme biological phenotypes, promoter region mutations can confer a variety of related phenotypes⁴³. In the cis-regulatory editing system, alleles with overlapped deletions show similar phenotypic effects⁴³ and hidden pleiotropic roles⁴⁴ in genes. Therefore, we next generated a string of deletion alleles covering the entire Os1900 promoter region to identify the regulatory regions, which are responsible for tiller number control by fertilization. We designed 19 guide RNAs (gRNAs) to create this set of mutants; every three adjacent gRNA expression units were cloned into one vector construct, for a total of nine vectors (Fig. 5a, b), as each deletion mutant had a deletion of a few hundred bps in the promoter region (till 5,000 bp upstream regions from the translation start site) of the Os1900 gene. In the first generation (T₀) of regenerated plants, plants with large deletions (> ~100 bp) were selected by polymerase chain reaction (PCR). DNA sequence analysis of plants of the T₁ generation identified nine alleles with distinct deletions, covering most of the entire target promoter region (Fig. 5c). Using these deletion mutants, we examined the fertilizer response of Os1900 expression under four sampling conditions (i.e., 50 ppm 0 h and 1 h: TDS is 50ppm and 245ppm, respectively; 30 ppm 0 h and 1 h: TDS is 30ppm and 245ppm, respectively).

**Fig. 4: Detailed gene expression of *Os1900* to fertilization and regulation of tiller number under minor- and trace- fertilization conditions.**

**Fig. 5: Engineering of the *Os1900* promoter provided a continuum of alleles with different fertilization responses.**

To predict the evolutionarily conversed cis-regulatory elements (CREs), possible CREs related to N, P fertilizer (Fig. 5d, Supplementary Data. 6) and the conserved motifs in promoter regions of other MAX1-like genes including Os900, Os1400 and Os5100 (Fig. 5e, Supplementary Data. 7) were surveyed. We found dozen of CRE candidate sites as evolutionarily conserved ones (Fig. 5d), meanwhile, CRE filtering was done in comparison with other MAX1-like genes (Fig. 5e). The major CREs for transcription factors (TFs) included members of the WRKY and MYB families, which include the main TFs of the AM symbiosis network¹⁶. Os900 and Os1900 were induced by manure starvation, while the Os1400 and Os5100 were insensitive to it. Accordingly, it might be reasonable that there are no fertilizer-related CREs predicted in promoter regions of Os1400 and Os5100.

Then, Os1900 expression levels for the four fertilizer conditions ((1) 50 ppm,0 h: TDS is ~50 ppm; (2) 50ppm,1 h: TDS is ~245ppm; (3) 30 ppm,0 h: TDS is ~30 ppm; (4) 30 ppm,1 h: TDS is ~245 ppm) are compared to those of WT in Fig. 5f. Os1900 expression was unchanged by fertilization in WT (50 ppm, 0 h vs. 50 ppm, 1 h), even when the fertilizer concentration changed rapidly (Figs. 4b and 5f and Supplementary Data. 4). The intercept values (which indicate Os1900 expression at 0 h) of all tested mutants were significantly lower than that of WT at 50 ppm, except M2 and M6 (Fig. 5f; Supplementary Fig. 11 and Supplementary Data 4 and 8). All mutants exhibited at most a very weak fertilizer response at 50 ppm; however, positive trends were observed in M2 and M3 (Supplementary Fig. 11; Supplementary Data 8). By contrast, at 30 ppm, Os1900 expression clearly decreased after fertilization in WT and all tested mutant lines, while the rates of decrease were low in M3, M6, and M9 (Supplementary Fig.11). At 30ppm, M2 showed the same transcript level as WT (Fig. 5f, Supplementary Fig. 11). In addition, the expression of M1, M4, M7 and M8 have clear differences from those in WT under four fertilization conditions (Fig. 5f), suggesting that deletions with M1, M4, M7 and M8 contain critical cis-regulatory elements to determine the basic levels of Os1900 gene expression. In contrast, M3, M6, and M9 mutants with more gentle slopes than WT, exhibited less responsive to fertilizer at 30 ppm (Supplementary Fig.11; Supplementary Data 8), suggesting that these deleted regions contained regulatory elements needed for Os1900 induction in response to nutrient deficiency. These results demonstrate that several novel deletion alleles of Os1900 promoter regions exhibited various fertilizer responses, which were different from those in WT.

Phosphate starvation responses (PHRs), which are required for mycorrhizal symbiosis, regulate symbiosis related genes via PHR1-binding sequences (P1BS) motif¹⁶. Thus, P1BS is a motif existing in promoter region of Pi starvation-responsive genes and distributed in both the Os900 and Os1900 promoter (Fig. 5d, e), which are covered in the deleted areas of M2, M4, M7 and M9 mutants (Fig. 5d). As shown in Fig. 5f, the transcript level of both M4 and M7 decreased under four fertilization conditions. However, M2 was the only one line showing no different expression under all the tested conditions compared with WT (Fig. 5f). Besides, even one P1BS was found in M9 deletion region, the expression of Os1900 only showed difference at 50 ppm (Fig. 5f). These results suggest that not only the presence of the known key cis-regulatory elements, but also the positions of the deletions against the start sites of Os1900 transcription could be critical for changing the distance between RNA polymerase complexes and the binding sites for the responsible TFs. Otherwise, some combinations of other cis-regulatory motif(s) with these P1BS would be involved. It is of note that there must be other critical cis-regulatory elements for nutrient deficiency since there are no P1BS in the M3 and M6 deleted regions. In addition, the one P1BS deletion in M4 region caused the increase of tiller numbers due to low expression of Os1900, but was still able to respond to the nutrient deficiency. Thus, the role of P1BS sites in response to nutrient deficiency was not clear in Os1900.

CRE mutations likely represent genetic accelerators for many biological and agronomical traits during species diversification, domestication, and breeding processes⁴⁵. As os1900 mutants show increased tiller under some conditions (Fig. 4d), we further investigated tiller number dynamics in these promoter mutants under minor and trace fertilization conditions. Under minor conditions, M3, M4, and M6 mutants produced more tillers than WT (Fig. 6a). It is especially of note that M4 showed decreased Os1900 expression under all the tested fertilization conditions (Fig. 5f). At trace fertilizer concentrations, M1 and M6 mutants exhibited slight decrease in tiller number compared to WT (Fig. 6b). All of them indicated a weak correlation between these tiller numbers and expression phenotypes. Crop yield was affected by other factors in addition to tiller number. Indeed, seed fertility led to the decrease yield of M3 and M6 (Supplementary Fig. 12) although their tiller numbers were increased. Only M4 was identified with significant increase so far in terms of grain yields under the laboratory cultivation conditions (Supplementary Fig. 12a). Although the evaluation of yield needs to be carried out in the paddy field in the future, we can speculate that such increases in mature tiller numbers may result in higher panicle numbers and yields in rice cultivation with a less fertilizer use.

**Fig. 6: Tiller numbers in a series of *Os1900* promoter mutant under minor-(a) and trace-(b) fertilization conditions.**

Besides, any promoter mutational lines of agriculturally important quantitative trait genes can create novel useful alleles⁴³. As an example, here, we demonstrated that M4 mutant, an Os1900 promoter deletion mutant, presented lower gene expression of Os1900, larger tiller numbers, and higher grain yields under minor fertilizer conditions. This may lay a foundation for breeding of rice cultivars adjusted to low fertilizer cultivation conditions in the future.

In this work, the genetic analysis of CRISPR/Cas9 mutants revealed that Os1900&Os5100 are genetically responsible for the conversion of CL to CLA, which regulate tiller numbers. We reliably identified the role of Os1900 as a fertilizer responsive gene under real paddy-field cultivation conditions and demonstrated that Os1900 transcriptional regulation induced by fertilizers was important in controlling the tiller number for rice. Although further detailed CRE identification is still essential, our results clearly indicate that Os1900 is a key gene involved in the regulation of tiller number by fertilization in rice cultivation, and that deletion mutations in the Os1900 promoter region can maintain tiller numbers under minor fertilizer concentrations, which may contribute to the development of novel cultivars for sustainable agriculture.

Methods

Plant materials and growth conditions

Oryza sativa subsp. japonica cultivar Koshihikari plants grown in a paddy field were used for transcriptome analysis. All individuals were divided into two groups: normal transplantation group and delayed transplantation group. Each group was divided into three small groups: fertilization 0 time, 1time, and 2 times. After the first fertilization, we took the samples of rice leaves for 8 times at 10:00 am or 4:00 pm randomly of different dates. Practice amount of a typical commercial fertilizer for rice cultivation (~3 kg N/10a, ~4 kg P/10a, ~5 kg K/10a for both the first and the second fertilization) were used as indicated in instructions for use in this experiment.

The MAX1-like mutants, os1900&os5100, os1900, os5100, and os900&os1400 were generated by CRISPR/Cas9 in the c.v. Koshihikari WT background. The Nipponbare cultivar was used as the background of Os1900 promoter mutants.

Four distinct cultivation conditions of WT and os1900&os5100 mutants, os1900 promoter mutants for tiller number counting are (a) normal fertilization condition: 600 g fertilized soil/per plant; (b) minor fertilization condition: 300 g fertilized soil plus 300 g no-fertilized soil/per plant; (c) trace fertilization condition: 150 g fertilized soil plus 450 g no-fertilized soil/per plant; (d) no fertilization condition: 600 g no fertilized soil/per plant. The fertilized soil for rice seedling was Bonsol (N = 1 g, P = 3 g, and K = 1.7 g per 2.2 kg soil, Sumitomo Chemical CO., LTD.). The no fertilized soil was purchased from TACHIKAWA HEIWA NOUEN CO., LTD.

The four growth conditions for WT and os1900&os5100 mutants were long day (14.5 h light/9.5 h dark) and low temperature (17–21 °C; 12 h light/12 h dark); short day (10 h light/14 h dark) and low temperature; long day and high temperature (26–30 °C; 12 h light/12 h dark); and short day and high temperature.

Kimura’s B⁴⁶ solution was used as liquid fertilization, for Os1900 expression of WT and Os1900 promoter mutants. Liquid fertilizer is composed of N, P, K, and other related salts dissolved in ddH₂O. We used TDS (total dissolved solids) as a fertilizer status to measure the amounts of soluble ions in the aqueous solution. In order to exclude the effect of water absorbed by plants on fertilizer concentration, the solution volume was adjusted the same every time. In all cultivation experiments related to tiller number, “n” represents biological replicates.

Field transcriptome analysis

Samples from three plants were pooled as single samples for transcriptome analysis. RNA was extracted using TRIZOL reagent (Invitrogen, Carlsbad, CA, USA). An Agilent 180k custom arrays were used for hybridization analysis. Gene expression data for each probe were processed using the Agilent protocol and transformed to log₂ scale. Then, q-spline normalization⁴⁷ was applied to the distinct arrays. After normalization, transcriptome data were compared using paired t-tests, and false discovery rates and fold changes were calculated. All expression data and all tested sample combinations and probe sequences are presented in Supplementary Data 2.

Real-time qPCR analysis

Fully emerged leaves or seedling bases (leaves removed) were used for all expression analyses. Leaves and shoots from three plants or seedling bases from five individuals were pooled as a single sample for real-time PCR, with three or four biological replicates. Total RNA was extracted using TRIZOL reagent (Invitrogen, Carlsbad, CA, USA), 2.4 µg of total RNA was used for cDNA synthesis with the ReverTra Ace qPCR RT master mix (Toyobo, Tokyo, Japan).

Real-time PCR was conducted using TaqMan Fast Universal PCR Master Mix (Applied Biosystems, Foster City, CA, USA) and the Step-One Real-Time PCR System (Applied Biosystems). The rice ubiquitin gene (Os02g0161900) was used for normalization. Gene-specific primers and TaqMan probe sequences are listed in Supplementary Data 9. To account for expression dynamics and data fluctuations, all gene expression data (or estimated copy numbers of target genes) were logarithmically transformed.

RNA-seq analysis

Rice seedlings of WT and os1900&os5100 mutants were grown under minor fertilization until 8-leaf age. For the first tiller base samples, we removed the outer old leaves and collected 2 cm parts from the base. For leaf samples, we used parts of the mature seventh leaf blade. RNA-seq library were prepared using TruSeq Stranded Total RNA Library Prep Plant Kit (Illumina, San Diego, CA, USA) and the RNA libraries were sequenced using Illumina NovaSeq6000 with paired-end 100-bp at Macrogen Japan. Adaptor sequences were trimmed using Trimmomatic version 0.39⁴⁸. Trimmed reads were mapped to the IRGSP-1.0 genome assembly of rice using the STAR aligner version 2.7.10a⁴⁹. For gene models of GTF file, we combined representative genes and computationally predicted genes in IRGSP-1.0 and removed rRNA and tRNA gene models. For leaf samples, we found that about 60 percent of reads were mapped to multiple loci, and that top over-represented sequences were mapped to plastid genome as well as nuclear genome. We discarded these reads and used remaining about 15 million reads mapped to unique loci for analysis. For first tiller base samples, about 10 to 20 percent of reads were mapped to multiple loci, and about 35 million reads mapped to unique loci were used for analysis. Read counts were quantified using RSEM version 1.3.3⁵⁰ and normalized using edgeR version 3.30.3⁵¹ in R. Lowly expressed genes were filtered out using filterByExpr function and DEGs were extracted using glmQLFTest function in edgeR. Using the list of phytohormone related genes as described in previous reports^{52,53,54,55,56,57,58,59,60,61,62,63,64} (Supplementary Data 10), gene expression was examined. Heatmaps were drawn using ggplot2 package in R⁶⁵. The deposit IDs of our Illumina data for RNA-seq are: PRJNA889215.

Some key genes expression was confirmed with real-time PCR using same samples (Supplementary Fig. 7 and 10).

CRISPR/Cas9 constructions and mutant genotyping

CRISPR/Cas9 (http://crispr.hzau.edu.cn/CRISPR2/) was used to generate MAX1-like mutants and os1900 promoter mutants. gRNAs were ligated using the plasmid pU6gRNA. After PCR amplification, PCR products were assembled into pZH-OsU6gRNA-MMCas9 and transformed into Escherichia coli to obtain the target clone. The final target vector was subjected to Agrobacterium tumefaciens-mediated transformation. T₀ generation plants were hydroponically cultivated for 3 days; after the roots grew out, they were transplanted in soil under standard cultivation conditions in an artificial climate chamber. All gRNA sequences are listed in Supplementary Data 9. The MAX1 mutants were genotyped by sanger sequencing in the T₀ generation. Promoter mutant genotyping was performed via PCR in the T₀ generation to select those with > 100 bp deletions, followed by Sanger sequencing in the T₁ generation.

k-mer analysis

We obtained 12 Gbp Illumina data for the os1900&os5100 mutants and WT. Paired-end fastq raw Illumina next-generation sequencing data were analyzed using k-mer software⁶⁶, and k was 20. Log₁₀ values of (k-mer for the double mutants/k-mer for WT) were plotted. Reference sequence data (Nipponbare) for five MAX1-like genes was obtained using the RAP-database (IRGSP1.0).

In situ hybridization

WT plants were grown in unfertilized soil. At 17 days after germination, one shoot apex from each seedling was sampled before and after fertilization, dissected, fixed in 4% paraformaldehyde in 0.1 M sodium phosphate buffer for 48 h at 4 °C, and then dehydrated in a graded ethanol series. The ethanol was replaced with Histo-Clear (National Diagnostics, Atlanta, GA), and the samples were embedded in Paraplast Plus (Leica, Wetzlar, Germany). Paraffin sections (thickness, 8 μm) were placed on microscope slides coated with 3-aminopropyl triethoxysilane (Matsunami Glass, Osaka, Japan). To generate a probe for Os1900, the full-length cDNA clone AK122077.1 was obtained from the National Institute of Agrobiological Sciences (NIAS) Genebank (http://www.dna.affrc.go.jp/distribution/) and used as a template. For Os5100, a cDNA fragment was amplified by PCR using the primer set 5′-ATCACATACGAGTGATCAAAAGCTC-3′ and 5′-TGAGCACCATCCCGAACTG-3′, and cloned into the pCR Blunt II TOPO vector (Invitrogen). The cDNA of Os1900 and Os5100 was linearized using AvaI (New England Biolabs) and PvuII (Takara, Shiga, Japan), respectively, and then digoxigenin-labeled antisense riboprobes were transcribed using T3 (Roche) or T7 (Takara, Shiga, Japan) RNA polymerase with DIG-RNA labeling mix (Roche). For H4, full length cDNA of H4 was used for transcribing digoxigenin-labeled antisense riboprobe. In situ hybridization and immunological detection of the hybridization signals were performed as previously described⁶⁷.

LC-MS/MS analysis of endogenous 4DO, CL, CLA and MeCLA

Rice plants were grown as previously described⁶⁸, with minor modifications. Eleven-day-old seedlings grown on 0.6% agar media of hydroponic nutrients under a 16 h light/8 h dark photoperiod were transferred to glass vials containing 50 mL hydroponic nutrient solution without inorganic phosphate to activate SL biosynthesis²⁵. The shoot and root of the 32-day-old seedlings were harvested and homogenized in 12.5 mL of acetone containing stable isotope-labeled internal standards [[6’-D₁]−4DO¹¹, [1-¹³CH₃]-(S)-CL⁶⁹, [1-¹³CH₃]-rac-CLA²², [10-D₁]-rac-MeCLA²² using POLYTRON PT3100D (Kinematica).

The filtrates were evaporated under nitrogen gas until acetone was almost removed. Then, 1 mL of distilled water and 2 mL of saturated NaCl were added, and the concentrated filtrates were extracted with 5 mL of ethyl acetate (EtOAc) three times. The organic phase was then evaporated to dryness under nitrogen gas, dissolved in 1 mL of acetonitrile, and purified using the Bond Elut DEA (100 mg) 1 mL cartridge (Agilent) (SPE method A, see Supplementary Data 11-I). The Fraction A after the SPE method A was further separated into CL-, MeCLA-, and 4DO-containing fractions using the Sep-Pak silica 1 cc vac cartridge (Waters) (SPE method B). The CL- and MeCLA-containing fractions were then purified using the Sep-Pak cyanopropyl 1 cc vac cartridge (SPE methods C and D, respectively). CLA in Fraction B after the SPE method A was purified using the Sep-Pak silica 1 cc vac cartridge (Waters) (SPE method E). The eluates were evaporated to dryness, dissolved with acetonitrile, and subjected to LC-MS/MS. It is noted that the filtrates of the acetone extract were directly used to analyze CL levels in shoots and roots of the os900&os5100 double mutant. LC-MS/MS analysis was carried out by using an X500R QTOF system (AB SCIEX). LC conditions and MS methods are shown in Supplementary Data 11-II, -III, respectively. Data acquisition and quantitative processing were performed by using the SCIEX OS software (version 2.0.1) (AB SCIEX). Calibration curves generated using labeled and non-labeled compounds were used for quantification of SLs.

Bioassay of (+)-GR24 on rice seedlings

The (+)-GR24 treatment was performed as previously described⁶⁸, with minor modifications. One-week-old rice seedlings grown on 0.6% agar media of hydroponic nutrient under a 16 h light/8 h dark photoperiod were transferred to glass vials containing 13 mL hydroponic nutrient solution. All hydroponic nutrient media contained 5 mM MES and were adjusted to pH 5.7. Dimethyl sulfoxide (DMSO) was used to dissolve (+)-GR24, and DMSO (mock) or (+)-GR24 was added to the hydroponic nutrient solution for a final DMSO concentration of 0.1% (v/v). The rice seedlings were incubated under the same conditions for 8 days; the hydroponic nutrient solution was supplemented after 4 days of incubation. The first and second tillers were measured using a digital caliper under a microscope.

Tiller number counts

Tiller numbers of tested rice seedlings were counted every 3 days. Then GLMs or GLMMs (including full model and reduced models) to explain the tiller number increase were made using the presence of Os1900&Os5100 and growth stages as parameters using lme4 in R and then ANOVA analysis of the models were performed to get P values for the effects of Os1900&Os5100 affecting tiller numbers.

Data availability

The data that support the findings of this study are available from the corresponding author (TI) upon request. RNA-seq data associated with this study have been deposited at NCBI under accession code PRJNA889215. Source data are provided with this paper.

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Acknowledgements

We would like to thank Drs. Masaki Endo and Seiichi Toki (National Agriculture and Food Research Organization) for providing CRISPR/Cas9 vectors. We also thank Dr. Kenichiro Hibara (currently, Kibi International University) for teaching some key protocols to J. Cui at the beginning in this study and Dr. Mingchao Wang (Dresden University of Technology) for proofreading some languages. We are grateful to the System for Development and Assessment of Sustainable Humanosphere (RISH, Kyoto University) for providing a greenhouse to KM and SY. This work was supported by JSPS KAKENHI under grant number JP17H06246 (to T.I.), JP22H05180 (to T.I.), JP22H0517222 (to T.I.), JP22H00367 (to T.I.), JP19H02892 (to K.M.), JP17H06474 (to S.Y.), by the Human Frontier Science Program Organization under grant number RGP0011/2019 (to T.I.), and by Cabinet Office, Government of Japan, Cross-ministerial Moonshot Agriculture, Forestry and Fisheries Research and Development Program, “Technologies for Smart Bio-industry and Agriculture”(funding agency: Bio-oriented Technology Research Advancement Institution) (JPJ009237 to T.I.). the Collaborative Research Program of Institute for Chemical Research, Kyoto University (grant # 2020-92) (to T.I., K.M., and S.Y.)

Author information

Kazuhiko Sugimoto
Present address: Division of Crop Design Research, Institute of Crop Science, Tsukuba, Ibaraki, Japan

Authors and Affiliations

Lab. of Plant Breeding & Genetics, Department of Agricultural and Environmental Biology, The University of Tokyo, Tokyo, Japan
Jinying Cui, Noriko Nishide, Masayuki Miya, Jun-Ichi Itoh & Takeshi Izawa
Chemistry of Molecular Biocatalysts Lab, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto, Japan
Kiyoshi Mashiguchi & Shinjiro Yamaguchi
Breeding Material Development Unit, Basic Research Division, National Institute of Crop Science, Tsukuba, Ibaraki, Japan
Kana Kuroha & Kazuhiko Sugimoto

Authors

Jinying Cui
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Noriko Nishide
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Kiyoshi Mashiguchi
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Kana Kuroha
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Masayuki Miya
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Kazuhiko Sugimoto
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Jun-Ichi Itoh
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Shinjiro Yamaguchi
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Takeshi Izawa
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Contributions

T.I. conceived the original idea on this work, organized all the experiments and mainly revised the manuscript. T.I. and N.N. performed the field transcriptome analysis. With substantial support by K.K. and K.S., N.N. made the os1900 & os5100 and os900 & os1400 double mutants and check the tiller number phenotypes firstly. K.M. and S.Y. performed SL analysis and GR24 application assay. M.M. and J.I. performed in situ hybridization analysis and RNA-seq analysis. J.C. performed all of the rest experiments including related to genotyping and phenotyping of all mutants, the entire experiments on the promoter deletion mutant analysis and wrote the original manuscript. All the authors revised the manuscript.

Corresponding author

Correspondence to Takeshi Izawa.

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The authors declare no competing interests.

Peer review

Peer review information

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Cui, J., Nishide, N., Mashiguchi, K. et al. Fertilization controls tiller numbers via transcriptional regulation of a MAX1-like gene in rice cultivation. Nat Commun 14, 3191 (2023). https://doi.org/10.1038/s41467-023-38670-8

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Received: 11 February 2022
Accepted: 05 May 2023
Published: 08 June 2023
DOI: https://doi.org/10.1038/s41467-023-38670-8

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