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Article

Cytological Observation and RNA-Seq Analyses Reveal miR9564 and Its Target Associated with Pollen Sterility in Autotetraploid Rice

by
Zijun Lu
1,2,3,4,
Weicong Huang
1,3,4,
Lianjun Zhu
1,3,4,
Guobin Liang
1,3,4,
Yu Huang
1,3,4,
Jinwen Wu
1,3,4,
Rou Chen
1,3,4,
Xiang Li
2,* and
Xiangdong Liu
1,3,4,*
1
State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangdong Laboratory for Lingnan Modern Agriculture, South China Agricultural University, Guangzhou 510642, China
2
Guangdong Provincial Key Laboratory of Utilization and Conservation of Food and Medicinal Resources in Northern Region, Shaoguan University, Shaoguan 512005, China
3
Guangdong Provincial Key Laboratory of Plant Molecular Breeding, South China Agricultural University, Guangzhou 510642, China
4
Guangdong Base Bank for Lingnan Rice Germplasm Resources, College of Agriculture, South China Agricultural University, Guangzhou 510642, China
*
Authors to whom correspondence should be addressed.
Plants 2024, 13(11), 1461; https://doi.org/10.3390/plants13111461
Submission received: 8 April 2024 / Revised: 18 May 2024 / Accepted: 22 May 2024 / Published: 24 May 2024
(This article belongs to the Section Plant Genetics, Genomics and Biotechnology)
Browse Figures
Versions Notes

Abstract

:
Understanding the regulation of autotetraploid sterility is essential for harnessing the strong advantages in genomic buffer capacity, biodiversity, and heterosis of autotetraploid rice. miRNAs play crucial roles in fertility regulation, yet information about their reproductive roles and target genes in tetraploid rice remains limited. Here, we used three tetraploid lines, H1 (fertile), HF (fertile), and LF (sterile), to investigate cytological features and identify factors associated with autotetraploid sterility. LF showed abnormal meiosis, resulting in low pollen fertility and viability, ultimately leading to scarce fertilization and a low-seed setting compared to H1 and HF. RNA-seq revealed 30 miRNA-candidate target pairs related to autotetraploid pollen sterility. These pairs showed opposite expression patterns, with differential expression between fertile lines (H1 and HF) and the sterile line (LF). qRT-PCR confirmed that miR9564, miR528, and miR27874 were highly expressed in the anthers of H1 and HF but not in LF, while opposite results were obtained in their targets (ARPS, M2T, and OsRPC53). Haplotype and expression pattern analyses revealed that ARPS was specifically expressed in lines with the same haplotype of MIR9564 (the precursor of miR9564) as LF. Furthermore, the Dual-GFP assay verified that miR9564 inhibited the fluorescence signal of ARPS-GFP. The over-expression of ARPS significantly decreased the seed setting rate (59.10%) and pollen fertility (50.44%) of neo-tetraploid rice, suggesting that ARPS plays important roles in autotetraploid pollen sterility. This study provides insights into the cytological characteristic and miRNA expression profiles of tetraploid lines with different fertility, shedding light on the role of miRNAs in polyploid rice.

1. Introduction

Regardless of autopolyploidy and allopolyploidy, polyploid individuals have substantial advantages in stress resistance, biosynthesis, genomic buffering capacity, biodiversity, and heterosis [1,2,3]. However, the widespread complex reproductive defects in autotetraploid plants limit their application [4,5,6,7]. Autotetraploid rice, resulting from doubling its diploid counterpart, represents a promising breeding germplasm, which displays high salt and heavy metal ion resistance [8,9,10,11]. Partial pollen sterility stands out as a major factor contributing to a low-seed set of autotetraploid rice. Within this context of pollen sterility, abundant abnormalities had been observed in the meiotic anthers of autotetraploid rice, including abnormal chromosome behavior and tapetum development [12,13,14]. Chinese scientists dedicated at least 20 years in repeated selfing and selection to overcome polyploid infertility, resulting in the successful breeding of fertile tetraploid rice, such as PMeS polyploid rice and neo-tetraploid rice (NTR, with 80% seed setting) [15,16,17,18]. Notably, NTR lines have shown the ability to overcome polyploidization sterility when crossed with typical autotetraploid rice exhibiting low fertility [16]. These fertile tetraploid rice germplasms have produced a valuable opportunity to identify genes associated with autotetraploid infertility. Our previous studies had reported 15 NTR lines to assess their yield traits, reproduction, and gene expression [16,17,18]. Relative to diploid counterparts and NTR lines, great changes have been detected in expression levels of genes, microRNAs (miRNAs), and long non-coding RNAs during embryo sac development in autotetraploid rice, such as meiotic genes [12,13,14,19].
miRNA is a special non-coding RNA that targets specific areas of mRNA to suppress gene expression by a direct cleaving of mRNAs by miRNAs or inhibiting the translation of the target mRNA to participate in numerous crucial processes [20]. For instance, miR528 regulates pollen intine formation by targeting the uclacyanin gene OsUCL23 to impact flavonoid metabolism [21], modulates flowering time by targeting OsRFI2 [22], and regulates OsSPL9 to affect the antiviral response [23]. miR2118 regulates reproductive tissue development in rice [24]. Additionally, miR167d, miR398b, miR7695, and miR1873 are associated with blast resistance [25,26,27,28]. miR156 defines ideal plant architecture by targeting OsSPL14 and regulates seed dormancy through the gibberellin pathway [29,30]. Recently, the regulatory network of OsPIL15-miR530-OsPL3 and miR1432-OsACOT was found to be related to rice grain yield [31,32].
From diploidy to autotetraploidy, the expression patterns of miRNA dynamically changed in the anther and ovary, indicating the important roles of miRNAs in autotetraploid reproduction [12,13,16]. There were 172 miRNAs differentially expressed in the meiosis anther of autotetraploid rice, including 57 miRNAs specifically expressed in autotetraploid rice [12]. Furthermore, 321 and 368 miRNAs showed differential expression during anther and embryo sac development in autotetraploid rice, respectively [13]. In addition, 122 miRNAs were differentially expressed in the meiotic anther of the neo-tetraploid line H3 compared to autotetraploidy T452 [16]. However, the functional verification about miRNAs and their negative targets in the reproductive regulation of tetraploid rice is still limited.
In this study, two neo-tetraploid lines (H1 and HF) and one low-fertility tetraploid line (LF) were utilized for cytological observation, miRNA-seq, and RNA-seq to identify common differentially expressed miRNAs and their negative targets relative to tetraploid reproduction. One key candidate target was further over-expressed in neo-tetraploid rice. As expected, the transgenic materials exhibited a low-seed set and low pollen fertility. These findings contributed to enrich our understanding of pollen development in autotetraploid rice.

2. Results

2.1. The Low-Fertility Tetraploid Line (LF) Exhibited Defects in Pollen Development and Fertilization

An F2 population (1409 individuals) was constructed from the combination of fertile Huaduo1 (H1, neo-tetraploid rice) and sterile Linglun-4x (autotetraploid rice) in 2012. Two groups of plants were selected: group 1 (113 individuals, seed setting ≥ 88%) and group 2 (75 individuals, seed setting ≤ 40%). From F3 to F11, group 1 maintained fertile selfing progenies (seed setting rate ≥ 70%), while group 2 maintained sterile progenies (seed setting rate ≤ 20%). From 2017 (F11), a fertile line designated as High-Fertility Tetraploidy (HF) was selected from group 1, while another sterile line designated as Low-Fertility Tetraploidy (LF) was selected from group 2 (Figure S1A,B and Figure 1A). The plant height (16.48–18.19% reduction), panicle length (15.16–17.76% reduction), and grain number per panicle (17.02–28.60% reduction) of LF were significantly lower than that of HF (Figure S1C–E). The successive generations of HF and LF displayed stable fertility and sterility, respectively. The seed setting of LF (5.17%) was significantly lower than that of HF (71.39%) and H1 (74.38%) (Table 1, Figure 1A,B). A high-seed setting was observed in hybrids of T428 × H1 (86.72%), LF × HF (75.30%), and LF × H1 (79.43%) (Figure S2), suggesting the presence of dominance gene action for high fertility. The pollen grains developed normally in HF (90.31%) and H1 (97.10%), whereas a large number of aborted pollen grains were found in LF (only 26.02% normal pollen grains) (Table 1, Figure 1C). The 2,3,5-Triphenyl-2H-tetrazolium chloride (TTC) solution was applied to detect pollen viability, and the results showed that the pollen viability of H1, HF, and LF was 46.93%, 65.75%, and 17.95%, respectively (Table 1, Figure 1D). Additionally, whole-mount eosin B-staining confocal laser scanning microscopy (WE-CLSM) observations of mature embryo sacs revealed that HF and LF had a polygonum-type embryo sac (Figure 2A,B), with embryo sac fertility of 87.65% for HF and 80.00% for LF, respectively (Figure 2C).
Moreover, the embryogenesis and endosperm development of HF and LF were also observed using WE-CLSM at 1 h after flowering, 1 day after flowering (DAF), 3 DAF, and 5 DAF. In HF, 91.67%, 77.62%, 77.35%, and 77.01% samples were able to be fertilized at 1 h, 1 DAF, 3 DAF, and 5 DAF, respectively, while only 19.05%, 15.67%, 37.32%, and 6.18% of observed samples were fertilized in LF (Figure 2C–G). Most of the samples in LF were still unfertilized and retained the mature embryo-sac-like morphology (Figure 2H–K) or exhibited other abnormalities (Figure S3). These results indicate that LF displayed defects during pollen development, double fertilization, and embryogenesis.

2.2. LF Showed Severe Abnormal Male Meiotic Process

Similar to diploid rice, HF underwent meiosis with fewer abnormalities. However, more abnormal chromosome behaviors were observed in meiotic pollen mother cells (PMCs) of LF, including chromosome dragging at metaphase I and metaphase II, chromosome lagging at anaphase I and anaphase II, chromosome behavior disorder, micronuclei at telophase I and telophase II, abnormal cell shape and asynchrony of the chromosome during meiosis II, and an abnormal tetrad (Figure 3). High frequencies of chromosome behavior abnormalities were observed since the early stage of meiosis in LF, which were significantly higher than HF at all observed stages (Figure 4A). Abnormal chromosome configurations were found in both LF and HF, such as univalents, trivalents, and particularly quadrivalents. The number of quadrivalents per cell was lower in LF (6.86) compared to HF at diakinesis (7.97, Figure 4B). A ring shape was the most frequent configuration of quadrivalents in both HF and LF. HF had a higher frequency of ring-shape (64.28%) and X-shape (16.91%) quadrivalents than LF (57.93%, 11.76%, respectively), while LF had a higher frequency of chain-shaped quadrivalents (21.10%) than HF (12.54%, Figure 4C). A similar result was observed during metaphase I (Figure 4B,C).

2.3. Comparative miRNA Expression Profiles in Meiotic Anthers of H1, HF, and LF

To investigate the differences in miRNA expression during anther development among tetraploid lines with opposite fertility, three small RNA libraries from meiotic anthers of H1, HF, and LF were sequenced by using Illumina Solexa high-throughput sequencing technology. A total of 38,569,001, 39,942,383, and 45,913,426 raw reads were generated, yielding 28,129,531 (72.93%), 27,818,269 (69.65%), and 27,648,526 (60.22%) valid reads from H1, HF, and LF, respectively (Table S1). A significant correlation was observed among three biological replicates of each library with a correlation coefficient exceeding 0.95 (Figure S4).
A total of 929 miRNAs were detected across the three libraries (Table S2). A total of 692 miRNAs were detected in H1, comprising 268 known and 424 novel miRNAs. Among these 268 known miRNAs, 146 miRNAs showed an identical sequence compared to miRBase (labeled as “Yes”) and others had a different sequence (labeled as “Diff”). In HF, 761 miRNAs were detected, consisting of 277 known (150 Yes and 127 Diff) and 484 novel miRNAs. Similarly, 722 miRNAs were detected in LF with 277 known (154 Yes and 123 Diff) and 445 novel miRNAs (Figure 5A). A total of 521 miRNAs were shared in all three libraries, while 36, 63, and 105 miRNAs were specifically detected in H1, HF, and LF, respectively (Figure 5B). The length distribution of mature miRNAs was primarily enriched in 21 nt and 24 nt (Figure 5C). Among these miRNAs, 128 showed high expression levels (FPKM > 260.81), 422 displayed low expression levels (FPKM < 10.00), and the remaining 378 were considered as moderately expressed. The 422 low-expressed miRNAs were subsequently excluded from the further analysis (Figure 5D).
In comparison to LF, 179 differentially expressed miRNAs (DEMs) were identified in H1, including 64 up-regulated (up) and 115 down-regulated (down) DEMs (Table S3). Among them, 24 up- and 33 down-DEMs displayed high expression levels. HF showed 227 DEMs, with 104 up- and 123 down-DEMs (Figure 5E, Table S4). The Venn diagram analysis revealed that 18 DEMs (5.80%) were co-up-regulated (cuDEM), while 44 DEMs (14.10%) were co-down-regulated (cdDEM) in HF and H1 (Figure 5F, Table S5). These 62 coDEMs were considered as candidate miRNAs related to autotetraploid pollen fertility (Figure 5G).
To gain further insight into the functions of coDEMs, we conducted an analysis of their potential targets. In total, 5944 mRNAs transcribed by 4866 genes were annotated as potential targets of 60 coDEMs. Gene Ontology (GO) analyses of 3476 predicted target genes of 44 cdDEMs revealed significant enrichment in various processes including the protein modification process (GO: 0006464), regulation of gene expression and epigenetics (GO: 0040029), signal transduction (GO: 0007165), pollen–pistil interaction (GO: 0009875), cell differentiation (GO: 0030154), post-embryonic development (GO: 0009791), anatomical structure morphogenesis (GO: 0009653), plasma membrane (GO: 0005886), kinase activity (GO: 0016301), and nucleotide binding (GO: 0000166) (Figure S5). Most of the enriched GO items were associated with reproductive development, suggesting that these coDEMs might play important roles during reproductive development in tetraploid rice.

2.4. Identification of Negative Regulative miRNA-Target Pairs during Meiosis in Neo-Tetraploid Rice

Previously, the same RNA samples were used for RNA-seq analyses, which identified 668 common differentially expressed genes (coDEGs) in meiotic anthers of HF and H1 relative to LF, comprising 232 up- (cuDEGs) and 436 down-regulated coDEGs (cdDEGs) (Table S6) [33]. The Venn diagram analysis of coDEGs and coDEMs–targets identified 30 miRNA-target pairs demonstrating negative regulatory relationships between miRNAs and their targets (Figure 5H, Table S7). Among them, four cuDEGs, LOC_Os11g17290 (named as ARPS here, predicted target of miR9564), LOC_Os02g06760 (named as M2T here, predicted target of miR528), LOC_Os04g32350 (OsRPC53, predicted target of miR27874), and LOC_Os06g38210 (named as M4T here, predicted target of miR818d), showed high expression levels (FPKM > 10) in meiotic anthers and significant differences in the expression level between HF/H1 and LF (Figure 6A).
qRT-PCR was performed to verify the expression levels of the four aforementioned coDEM–DEG pairs during anther development of H1, HF, and LF. miR9564 showed up-regulated expression in developmental stage 7 to 10 (S7–S10) anthers of HF and H1 compared to LF, while its target ARPS showed down-regulated expression during the same stage. Similarly, miR528 and miR27874 displayed up-regulated expression in S7–S10 anthers of HF and H1, while their targets M2T and M3T showed down-regulated expression during the same stage. Another cuDEM, miR818d, was confirmed with up-regulated expression in S8a–S8b anthers of HF and H1, but its potential target M4T was also up-regulated in S8a anthers. M4T1 encoded an expressed protein without known function and was mainly highly expressed in vegetative organs. Opposite expression patterns were found in miR9564-ARPS, miR528-M2T, and miR27874-M3T, but not in miR818d-M4T (Figure 6B). Because of its most substantial expression differences, the miR9564-ARPS couple was selected as autotetraploid rice pollen sterility candidates for further verification.

2.5. miR9564 Could Negatively Regulate the Expression Level of ARPS

miR9564 was 24 nt long and its precursor MIR9564 was 92 nt long on chromosome 11. A re-sequencing analysis revealed different haplotypes of MIR9564 between HF-H1 and LF. The haplotype in HF and H1 (labeled as Ha1) contained two SNPs, including the 10th G:C and the 27th C:T, while the haplotype in LF (labeled as Ha2) was the same as the reference genome (Figure 7A,B). The mRNAs of Ha2-MIR9564 were predicted to form three RNA secondary structures different from that of Ha1-MIR9564 (Figure 7C). Interestingly, previously finished RNA-seq and re-sequencing datasets revealed that 33 samples with Ha2-MIR9564 and 22 samples with heterozygous MIR9564 displayed a high expression level of ARPS, but not in 29 samples with Ha1-MIR9564 (Figure 7D).
To verify if the expression level of ARPS is repressed by miR9564, a Dual-GFP assay was further performed, which used a nuclear-localized GFP signal as the internal control (Figure S6). In the control, strong ARPS-GFP fluorescence was distributed in both the nucleus and cytoplasm of protoplasts. While co-expressing the Ubi::MIR9564 effecter (pOX9564) and APRS-DGFP reporter, APRS-GFP signals were repressed in the cytoplasm, and only nuclear GFP signals were observed. Once ARPS was mutated in the target site, the pOX9564 effecter lost its ability to repress the fluorescence signal of ARPSm-GFP (Figure 8). Taken together, these results suggested that miR9564 might negatively affect the expression level of ARPS.

2.6. Over-Expression of ARPS Reduced Pollen Fertility and Seed Set in Neo-Tetraploid Rice

To further understand the reproductive roles of ARPS, three over-expression lines of ARPS driven by the Ubique promoter (ARPS-OE1, ARPS-OE2, and ARPS-OE3) were constructed in the H1 background (Figure 9A). ARPS showed 6856.03~37238.58-fold up-regulation in obtained ARPS-OE lines (Figure 9B). The plant height (14.05–22.85% reduction), panicle length (2.47–11.95% reduction), and grain number per panicle (0.00–39.56% reduction) slightly reduced relative to WT plants (Figure 9C–E), which is consistent with the difference between HF and LF (Figure S1C–E). As expected, the seed setting rates of ARPS-OE1 (45.68%) and ARPS-OE3 (64.12%) were significantly lower than that of WT plants (77.27%) (Figure 9F,G). Moreover, abundant abortive pollen grains were found in ARPS-OE plants. The pollen fertility of ARPS-OE lines ranged from 48.00% to 53.03%, which was significantly lower than that of WT plants (97.10%) (Figure 9H,I). These results indicate that the up-regulation of ARPS expression in anthers would be detrimental to normal pollen development.

3. Discussion

In recent years, various factors affecting autotetraploidization sterility have been identified, including meiotic genes, miRNAs, long non-coding RNA, and DNA methylation sites [6,10,11,12,13,14,19,33,34]. Among these regulators, miRNAs with variable expression patterns have been proposed as an important factor for low fertility of autotetraploid rice. In comparison to Taichung65, 172 differentially expressed miRNAs were identified from anthers of autotetraploid rice Taichung65-4x [12]. Relative to 02428-2x, 321 and 368 miRNAs were differentially expressed in anthers and ovaries of autotetraploid rice 02428-4x, respectively [13]. Additionally, some differentially expressed miRNAs in the meiotic anther relative to the fertile neo-tetraploid lines were identified, such as osa-miR408-3p and osa-miR528-5p [16,34].
In this study, 62 coDEMs were identified from meiotic anthers of two neo-tetraploid lines to further enrich the understanding about miRNAs related to autotetraploid rice pollen sterility. Moreover, 30 miRNA-target pairs were highlighted because of their opposite expression patterns in both H1/LF and HF/LF comparative RNA-seq analyses. One of these coDEMs, miR528, has been previously reported to regulate pollen intine formation by targeting OsUCL23 to influence flavonoid metabolism [21]. The STTM (Short Tandem Target Mimic) lines of miR528 in neo-tetraploid rice exhibited a significant reduction in seed setting and pollen fertility [34]. Here, we identified the OsINH2 gene as a novel candidate target of miR528, which functions in regulating pollen viability and grain numbers [35]. In both H1/LF and HF/LF, miR528 was up-regulated during pollen development, while OsINH2 showed down-regulation. The altered expression pattern of miR528-OsINH2 from sterile autotetraploid rice to fertile neo-tetraploid rice suggests its potential importance in enhancing pollen fertility.
OsRPC53 encodes a subunit of RNA polymerase C (III), which is required for the hybrid pollen sterility, grain length, and grain number in rice [36,37]. The mutation of OsRPC53 caused pollen sterility in interspecific hybrid progeny of cultivated rice and Asian annual wild rice (Oryza nivara) [36]. In this study, a negative relationship in expression between miR27874 and OsRPC53 was identified and verified by qRT-PCR. miR27874 showed high-level expression in developing anthers of H1 and HF, but not in LF, while its target, OsRPC53, maintained a high expression level in LF anthers. These results suggest that miR27874-OsRPC53 might play important roles in regulating pollen fertility of neo-tetraploid rice.
In rice, STS1 encodes an endoplasmic reticulum-localized protein with lipase activity, essential for tapetal degeneration and pollen wall formation [38]. In this study, the expression of STS1 was up-regulated in both H1 and HF compared to LF, while its regulator miRNA, osa-MIR5522-p3, was down-regulated. These results suggested that the expression level of STS1 may be insufficient for post-remodeled reproduction in autotetraploid rice, leading to partial pollen sterility. However, the down-regulated expression of osa-MIR5522-p3 might facilitate the rescue of a higher expression level of STS1 during pollen development in neo-tetraploid rice, contributing to its high pollen fertility.
miR9564 was initially identified in the flowers of Brassica rapa, but its function remained unknown [39]. Here, we identified the homologous miR9564 from the meiosis anther of H1 and HF, which displayed a high expression level in developing anthers of H1 and HF, but not in LF. Conversely, its predicted target (ARPS) maintained a high expression level only in LF anthers. Moreover, the Dual-GFP assay revealed that the expression of MIR9564 could inhibit the fluorescence signals of ARPS-GFP, but not in mutant ARPS-GFP. These results indicate that ARPS is a target of miR9564. ARPS is a homologous gene of AtULP1a from Arabidopsis, which encodes an ESD4-like SUMO (small ubiquitin-related modifier) protein kinase 1 [40]. SUMO is a micromolecule with a similar structure to ubiquitin molecules and participates in protein modification after translation. It has been found that the SUMO genes regulate the nitrogen homeostasis, grain size, anther dehiscence, pollen fertility, and seed set in rice [41,42]. In this study, two haplotypes of MIR9564 were identified, in which one haplotype related to H1 and HF exhibited a low expression level of ARPS. Furthermore, the over-expression of ARPS was detrimental to pollen fertility and seed setting in neo-tetraploid rice. These results suggested that the high expression of miR9564 may suppress ARPS expression, preventing the partial autotetraploid pollen sterility caused by polyploidization in neo-tetraploid rice.
Taken together, our results unveil the regulatory roles of miR528-OsINH2, miR27874-OsPRC53, miR5522-p3-STS1, and miR9564-ARPS in autotetraploid pollen sterility, providing a unique perspective on the mechanisms underlying sterility in autotetraploid rice.

4. Materials and Methods

4.1. Plant Material

Anthers during meiosis of two fertile neo-tetraploid lines, Huaduo1 (H1) and High-Fertility Tetraploidy (HF), and one low-fertility tetraploid line (LF), were used for miRNAs’ analysis. HF and LF were sister lines derived from the progenies of Linglun-4x (infertile) × H1. H1 was the receptor for over-expression lines of ARPS.

4.2. Cytological Observation

Three florets from each of the three plants for each line were collected for evaluation on pollen fertility or viability. Pollen grains fixed in a Carnoy solution (ethanol/acetic acid = 3:1 v/v) for a minimum of 24 h were stained by a 1% iodine–potassium iodide solution (w/v) to evaluate pollen fertility. Pollen viability was evaluated with live pollen grains subjected to a 1% 2,3,5-Triphenyl-2H-tetrazolium chloride (TTC, w/v) solution at 31 °C. Subsequently, viable pollen grains turned red, while devitalized pollen grains retained their original color (Figure S7). Each sample was then photographed, obtaining five pictures from different perspectives under a Motic BA200 microscope, to count the pollen grains.
Florets were collected and fixed in the Carnoy solution for at least 24 h. Pollen mother cells were isolated and placed into a 1% acetocarmine solution for 3–5 min. Slides were briefly exposed to a flame for 5–7 s to induce thermal expansion and squashed to obtain separated meiotic chromosomes. Meiotic chromosomes were observed and photographed under a Motic BA200 microscope. The quantification of chromosome behaviors and chromosome configurations was performed as described in our previous study [18].
Whole-mount eosin B-staining confocal laser scanning microscopy (WE-CLSM) observations were performed to characterize embryo sac fertility, endosperm development, and embryogenesis in ovaries or developing seeds, as described in our previous study [33]. Those collected samples were fixed in an FAA solution (70% ethanol/acetic acid/methanal = 89:5:5, v/v), went through gradient rehydration (50%, 30%, 10%, and 0% ethanol, v/v), were stained by a 4% eosin B solution (w/v), were dehydrated by gradient ethanol (10%, 30%, 50%, 70%, 90%, 100% × 3, v/v), and were hyalinized via 50% (ethanol/methyl salicylate = 1:1, v/v) and pure methyl salicylate before observation under WE-CLSM. WE-CLSM was performed on Leica TCS SP2 under a 532 nm laser with an emission range from 545 to 638 nm.

4.3. miRNA Analysis

RNA samples were extended from anthers during meiosis, which were used for RNA-seq [33]. Small RNA libraries were constructed by Illumina’s TruSeq small RNA sample preparation Kits (San Diego, CA, USA). The miRNA sequencing was performed by LC-BIO (Hangzhou, China). The ACGT101-miR program was used to eliminate junk, adapter dimers, common RNA families (snoRNA, snRNA, tRNA, rRNA), low complexity, and repeats from raw reads. Subsequently, unique sequences (18–25 nt in length) were aligned against in miRBase 21.0 (ftp://mirbase.org/pub/mirbase/ (accessed on 21 November 2018)) to identify known or derived miRNAs. Unmapped sequences were used to predict novel miRNAs using BLAST tools and RNAfold software (http://rna.tbi.univie.ac.at/cgi-bin/RNAWebSuite/RNAfold.cgi (accessed on 9 November 2018)). Normalized deep-sequencing counts represented the expression level of miRNA. MiRNAs with log2(fold change ratio) > 1 and p-value < 0.05 were considered as differentially expressed miRNAs (DEMs). miRNAs with a maximum expression level among all samples less than 10.00 were categorized as low-expression miRNAs, those with a maximum expression level higher than the average expression level of all miRNAs were considered as high-expression miRNAs, and the remaining miRNAs were categorized as middle-expression miRNAs.

4.4. Bioinformatics Analysis Tools

The RNA structure of the precursor of miRNA was predicted by Mfold [43]. psRNATarget was employed to identify targeted mRNA of DEMs [44]. The targeted genes were annotated on the National Rice Data Center website (http://www.ricedata.cn/gene (accessed on 8 April 2019)). Gene expression levels of ARPS were analyzed using our 84 RNA-seq datasets, as described in our previous study [33]. The Gene Ontology (GO) enriched terms of miRNA targets were analyzed by using AgriGO (https://systemsbiology.cau.edu.cn/agriGOv2/ (accessed on 14 October 2018)). Venn diagram analyses and a heatmap diagram were created by TBtools [45,46].

4.5. Quantitative Real-Time Polymerase Chain Reaction (qRT-PCR) Analysis

The total RNA samples were extracted as templates. The Transcroptor First Strand cDNA Synthesis Kit (Roche, Mannheim, Germany) was used for reverse transcription. The cDNA of targeted genes was typically reverse-transcribed following the manufacturer’s instructions of the kit. Ubiquitin was used as the internal control gene for qRT-PCR of candidate genes. For the reverse transcription of DEMs, miRNA-specific stem-loop RT primers replaced the OligodT20 primer in Transcroptor First Strand cDNA Synthesis Kit. The reaction was incubated at 16 °C for 30 min; then, pulsed RT of 60 cycles occurred at 30 °C for 30 s, 42 °C for 30 s, 50 °C for 1 s; 85 °C for 5 min to stop the reaction. U6 snRNA was used as the internal control gene for qRT-PCR of DEMs. The qRT-PCRs were performed as described by Lu et al. [33]. Relative expression levels were calculated using the 2−ΔΔCT method [47]. All primers were designed by using Primer Premier 5.0 software and the Primer-BLAST website (https://www.ncbi.nlm.nih.gov/tools/primer-blast/ (accessed on 12 December 2018)) (Table S8).

4.6. Dual-GFP Assay

A combined sequence, consisting of one eGFP, one CaMV poly A terminative sequence, one 35S promoter, one nuclear localization peptide, and another eGFP, was combined in HindIII and KpnI cloning sites of a pGreenII 62SK vector to construct a Dual-GFP vector. The 35S::NLS-eGFP in the Dual-GFP vector served as the internal reference signal. A fragment (946 to 1470 bp, Figure S8) from the ARPS coding sequence (LOC_Os11g17290.3) was PCR-amplified from H1 cDNA, and was combined into the Dual-GFP vector to construct the ARPS-DGFP vector. Subsequently, the mutant ARPS coding sequence (Figure S8) was obtained by overlapping PCR, and combined into the Dual-GFP vector to construct the ARPSm-DGFP vector. In addition, the sequence of Ha1-MIR9564 (92 bp, Figure 7B) was combined with the Ubiquitin promoter to construct the Ubi::MIR9564 vector. The Ubi control and Ubi::MIR9564 were used as effecters, while ARPS-DGFP and ARPSm-DGFP were used as reporters. One effecter and one reporter were co-transformed into protoplasts extracted from a Taichung65 sheath, which were observed under a CLSM system. The related primers are listed in Table S8.

4.7. Over-Expression Line of ARPS in Neo-Tetraploid Rice

The coding sequence of ARPS (2883 bp) was PCR-amplified from H1 cDNA, and combined with the Ubiquitin promoter to construct Ubi::ARPS. The Agrobacterium tumefaciens EHA105 harboring above the constructed vector was transformed into Calli of H1 for transgenic line generation by BioRun (Wuhan, China). Transgenic seedlings and wild-type H1 were collectively assessed under the field condition at the experimental station of South China Agricultural University, Guangzhou, China.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/plants13111461/s1, Figure S1: The breeding procedure of high-fertility (HF) and low-fertility (LF) populations. Figure S2: Plant phenotypes of parents and F1 hybrids of LF × HF and LF × H1. Figure S3: Mature pollen and other abnormalities during double fertilization. Figure S4: Pearson correlation of miRNA-seq among biological replicates of each library. Figure S5: Gene Ontology (GO) enrichment analyses of predicted targets of coDEMs. Figure S6: Subcellular localization of Dual-GFP signal with NLS-mCherry. Figure S7: Pre-experiment of pollen grains stained with 1% TTC solution. Figure S8: Coding sequence fragment of ARPS and ARPSm used for Dual-GFP assay. Table S1: miRNA-seq data quality in H1, HF, and LF. Table S2: Information of miRNA detected from H1, HF, and LF. Table S3: Differentially expressed miRNAs (DEMs) in meiotic anthers between H1 and LF. Table S4: Differentially expressed miRNAs (DEMs) in meiotic anthers between HF and LF. Table S5: Common differentially expressed miRNAs (coDEMs) in meiotic anthers between H1-HF and LF. Table S6: Common differentially expressed genes (coDEGs) in meiotic anthers between H1-HF and LF [33]. Table S7: CoDEMs–coDEGs in meiotic anthers between H1-HF and LF. Table S8: Primers’ information.

Author Contributions

Z.L.: Investigation, Funding acquisition, Writing—original draft. W.H., L.Z., G.L., Y.H., J.W. and R.C.: Investigation, Formal analysis. X.L. (Xiang Li): Funding acquisition, Writing—review and editing. X.L. (Xiangdong Liu): Conceptualization, Resources, Funding acquisition, Supervision, Project administration, Writing—review and editing. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the National Key R&D Program of China (2023YFD1200802), the Base Bank of Lingnan Rice Germplasm Resources Project (2023), a project funded by China Postdoctoral Science Foundation (2022M721212), the Laboratory of Lingnan Modern Agriculture Project (NT2021001), and the Guangdong Natural Science Foundation (2022A1515010270).

Data Availability Statement

Data are contained within the article and Supplementary Materials.

Acknowledgments

The authors thank Shuhong Yu and other lab members for assistance.

Conflicts of Interest

The authors declare that they have no competing interests.

References

  1. Chao, D.; Dilkes, B.; Luo, H.; Douglas, A.; Yakubova, E.; Lahner, B.; Salt, D. Polyploids exhibit higher potassium uptake and salinity tolerance in Arabidopsis. Science 2013, 341, 658–659. [Google Scholar] [CrossRef]
  2. Yu, H.; Lin, T.; Meng, X.; Du, H.; Zhang, J.; Liu, G.; Chen, M.; Jing, Y.; Kou, L.; Li, X.; et al. A route to de novo domestication of wild allotetraploid rice. Cell 2021, 184, 1156–1170. [Google Scholar] [CrossRef] [PubMed]
  3. International Wheat Genome Sequencing Consortium (IWGSC). A chromosome-based draft sequence of the hexaploid bread wheat (Triticum aestivum) genome. Science 2014, 345, 1251788. [Google Scholar] [CrossRef]
  4. Morgan, C.; White, M.A.; Franklin, F.C.H.; Zickler, D.; Kleckner, N.; Bomblies, K. Evolution of crossover interference enables stable autopolyploidy by ensuring pairwise partner connections in Arabidopsis arenosa. Curr. Biol. 2021, 31, 4713–4726. [Google Scholar] [CrossRef] [PubMed]
  5. Morgan, C.; Zhang, H.; Henry, C.E.; Franklin, F.C.H.; Bomblies, K. Derived alleles of two axis proteins affect meiotic traits in autotetraploid Arabidopsis arenosa. Proc. Nat. Acad. Sci. USA 2020, 117, 8980–8988. [Google Scholar] [CrossRef]
  6. Westermann, J.; Srikant, T.; Gonzalo, A.; Tan, H.S.; Bomblies, K. Defective pollen tube tip growth induces neo-polyploid infertility. Science 2024, 383, h755. [Google Scholar] [CrossRef]
  7. Corneillie, S.; De Storme, N.; Van Acker, R.; Fangel, J.U.; De Bruyne, M.; De Rycke, R.; Geelen, D.; Willats, W.; Vanholme, B.; Boerjan, W. Polyploidy affects plant growth and alters cell wall composition. Plant Physiol. 2019, 179, 74–87. [Google Scholar] [CrossRef]
  8. Sun, Y.; Wu, Y.; Wang, Y.; Wang, S.; Wang, X.; Li, G.; Zhang, X.; Liang, Z.; Li, J.; Gong, L.; et al. Homoploid F1 hybrids and segmental allotetraploids of japonica and indica rice subspecies show similar and enhanced tolerance to nitrogen deficiency than parental lines. J. Exp. Bot. 2021, 72, 5612–5624. [Google Scholar] [CrossRef] [PubMed]
  9. Wu, Y.; Lin, F.; Zhou, Y.; Wang, J.; Sun, S.; Wang, B.; Zhang, Z.; Li, G.; Lin, X.; Wang, X.; et al. Genomic mosaicism due to homoeologous exchange generates extensive phenotypic diversity in nascent allopolyploids. Natl. Sci. Rev. 2020, 8, nwaa277. [Google Scholar] [CrossRef]
  10. Wang, L.; Cao, S.; Wang, P.; Lu, K.; Song, Q.; Zhao, F.; Chen, Z. DNA hypomethylation in tetraploid rice potentiates stress-responsive gene expression for salt tolerance. Proc. Natl. Acad. Sci. USA 2021, 118, e2023981118. [Google Scholar] [CrossRef]
  11. Wang, N.; Fan, X.; Lin, Y.; Li, Z.; Wang, Y.; Zhou, Y.; Meng, W.; Peng, Z.; Zhang, C.; Ma, J. Alkaline stress induces different physiological, hormonal and gene expression responses in diploid and autotetraploid rice. Int. J. Mol. Sci. 2022, 23, 5561. [Google Scholar] [CrossRef]
  12. Li, X.; Shahid, M.Q.; Wu, J.; Wang, L.; Liu, X.; Lu, Y. Comparative small RNA analysis of pollen development in autotetraploid and diploid rice. Int. J. Mol. Sci. 2016, 17, 499. [Google Scholar] [CrossRef]
  13. Li, X.; Shahid, M.Q.; Xia, J.; Lu, Z.; Fang, N.; Wang, L.; Wu, J.; Chen, Z.; Liu, X. Analysis of small RNAs revealed differential expressions during pollen and embryo sac development in autotetraploid rice. BMC Genom. 2017, 18, 129. [Google Scholar] [CrossRef] [PubMed]
  14. Ku, T.; Gu, H.; Li, Z.; Tian, B.; Xie, Z.; Shi, G.; Chen, W.; Wei, F.; Cao, G. Developmental differences between anthers of diploid and autotetraploid rice at meiosis. Plants 2022, 11, 1647. [Google Scholar] [CrossRef]
  15. He, Y.; Ge, J.; Jiang, A.; Gan, L.; Song, Z.; Cai, D. Using a polyploid meiosis stability (PMeS) line as a parent improves embryo development and the seed set rate of a tetraploid rice hybrid. Can. J. Plant Sci. 2011, 91, 325–335. [Google Scholar] [CrossRef]
  16. Guo, H.; Mendrikahy, J.N.; Xie, L.; Deng, J.; Lu, Z.; Wu, J.; Li, X.; Shahid, M.Q.; Liu, X. Transcriptome analysis of neo-tetraploid rice reveals specific differential gene expressions associated with fertility and heterosis. Sci. Rep. 2017, 7, 40139. [Google Scholar] [CrossRef]
  17. Koide, Y.; Kuniyoshi, D.; Kishima, Y. Fertile tetraploids: New resources for future rice breeding? Front. Plant Sci. 2020, 11, 1231. [Google Scholar] [CrossRef]
  18. Chen, L.; Yuan, Y.; Wu, J.; Chen, Z.; Wang, L.; Shahid, M.Q.; Liu, X. Carbohydrate metabolism and fertility related genes high expression levels promote heterosis in autotetraploid rice harboring double neutral genes. Rice 2019, 12, 34. [Google Scholar] [CrossRef]
  19. Wang, L.; Yuan, J.; Ma, Y.; Jiao, W.; Ye, W.; Yang, D.; Yi, C.; Chen, Z. Rice interploidy crosses disrupt epigenetic regulation, gene expression, and seed development. Mol. Plant 2018, 11, 300–314. [Google Scholar] [CrossRef]
  20. Iwakawa, H.O.; Tomari, Y. The functions of microRNAs: mRNA decay and translational repression. Trends Cell Biol. 2015, 25, 651–665. [Google Scholar] [CrossRef]
  21. Zhang, Y.; He, R.; Lian, J.; Zhou, Y.; Li, Q.; Yu, Y.; Feng, Y.; Yang, Y.; Lei, M.; He, H.; et al. OsmiR528 regulates rice pollen intine formation by targeting an uclacyanin to influence flavonoid metabolism. Proc. Natl. Acad. Sci. USA 2020, 117, 727–732. [Google Scholar] [CrossRef] [PubMed]
  22. Yang, R.; Li, P.; Mei, H.; Wang, D.; Sun, J.; Yang, C.; Hao, L.; Cao, S.; Chu, C.; Hu, S.; et al. Fine-tuning of miR528 accumulation modulates flowering time in rice. Mol. Plant 2019, 12, 1103–1113. [Google Scholar] [CrossRef]
  23. Yao, S.; Yang, Z.; Yang, R.; Huang, Y.; Guo, G.; Kong, X.; Lan, Y.; Zhou, T.; Wang, H.; Wang, W.; et al. Transcriptional regulation of miR528 by OsSPL9 orchestrates antiviral response in rice. Mol. Plant 2019, 12, 1114–1122. [Google Scholar] [CrossRef]
  24. Araki, S.; Le, N.T.; Koizumi, K.; Villar-Briones, A.; Nonomura, K.; Endo, M.; Inoue, H.; Saze, H.; Komiya, R. miR2118-dependent U-rich phasiRNA production in rice anther wall development. Nat. Commun. 2020, 11, 3115. [Google Scholar] [CrossRef] [PubMed]
  25. Li, Y.; Cao, X.L.; Zhu, Y.; Yang, X.M.; Zhang, K.N.; Xiao, Z.Y.; Wang, H.; Zhao, J.; Zhang, L.; Li, G.; et al. Osa-miR398b boosts H2O2 production and rice blast disease-resistance via multiple superoxide dismutases. New Phytol. 2019, 222, 1507–1522. [Google Scholar] [CrossRef] [PubMed]
  26. Sanchez-Sanuy, F.; Peris-Peris, C.; Tomiyama, S.; Okada, K.; Hsing, Y.I.; San Segundo, B.; Campo, S. Osa-miR7695 enhances transcriptional priming in defense responses against the rice blast fungus. BMC Plant Biol. 2019, 19, 563. [Google Scholar] [CrossRef] [PubMed]
  27. Zhao, Z.; Feng, Q.; Cao, X.; Zhu, Y.; Wang, H.; Chandran, V.; Fan, J.; Zhao, J.; Pu, M.; Li, Y.; et al. Osa-miR167d facilitates infection of Magnaporthe oryzae in rice. J. Integr. Plant Biol. 2020, 62, 702–715. [Google Scholar] [CrossRef] [PubMed]
  28. Zhou, S.; Zhu, Y.; Wang, L.; Zheng, Y.; Chen, J.; Li, T.; Yang, X.; Wang, H.; Li, X.; Ma, X.; et al. Osa-miR1873 fine-tunes rice immunity against Magnaporthe oryzae and yield traits. J. Integr. Plant Biol. 2020, 62, 1213–1226. [Google Scholar] [CrossRef]
  29. Jiao, Y.; Wang, Y.; Xue, D.; Wang, J.; Yan, M.; Liu, G.; Dong, G.; Zeng, D.; Lu, Z.; Zhu, X.; et al. Regulation of OsSPL14 by OsmiR156 defines ideal plant architecture in rice. Nat. Genet. 2010, 42, 541–544. [Google Scholar] [CrossRef]
  30. Miao, C.; Wang, Z.; Zhang, L.; Yao, J.; Hua, K.; Liu, X.; Shi, H.; Zhu, J. The grain yield modulator miR156 regulates seed dormancy through the gibberellin pathway in rice. Nat. Commun. 2019, 10, 3822. [Google Scholar] [CrossRef]
  31. Zhao, Y.; Peng, T.; Sun, H.; Teotia, S.; Wen, H.; Du, Y.; Zhang, J.; Li, J.; Tang, G.; Xue, H.; et al. miR1432-OsACOT (Acyl-CoA thioesterase) module determines grain yield via enhancing grain filling rate in rice. Plant Biotechnol. J. 2019, 17, 712–723. [Google Scholar] [CrossRef] [PubMed]
  32. Sun, W.; Xu, X.; Li, Y.; Xie, L.; He, Y.; Li, W.; Lu, X.; Sun, H.; Xie, X. OsmiR530 acts downstream of OsPIL15 to regulate grain yield in rice. New Phytol. 2020, 226, 823–837. [Google Scholar] [CrossRef] [PubMed]
  33. Lu, Z.; Guo, X.; Huang, Z.; Xia, J.; Li, X.; Wu, J.; Yu, H.; Shahid, M.Q.; Liu, X. Transcriptome and gene editing analyses reveal MOF1a defect alters the expression of genes associated with tapetum development and chromosome behavior at meiosis stage resulting in low pollen fertility of tetraploid rice. Int. J. Mol. Sci. 2020, 21, 7489. [Google Scholar] [CrossRef] [PubMed]
  34. Li, X.; Huang, X.; Wen, M.; Yin, W.; Chen, Y.; Liu, Y.; Liu, X. Cytological observation and RNA-seq analysis reveal novel miRNAs high expression associated with the pollen fertility of neo-tetraploid rice. BMC Plant Biol. 2023, 23, 434. [Google Scholar] [CrossRef] [PubMed]
  35. Jadoon, S.; Qin, Q.; Shi, W.; Longfeng, Y.; Hou, S. Rice Protein Phosphatase 1 regulatory subunits OsINH2 and OsINH3 participate actively in growth and adaptive responses under abscisic acid. Front. Plant Sci. 2022, 13, 990575. [Google Scholar] [CrossRef] [PubMed]
  36. Nguyen, G.N.; Yamagata, Y.; Shigematsu, Y.; Watanabe, M.; Miyazaki, Y.; Doi, K.; Tashiro, K.; Kuhara, S.; Kanamori, H.; Wu, J.; et al. Duplication and loss of function of genes encoding RNA Polymerase III Subunit C4 causes hybrid incompatibility in rice. G3 2017, 7, 2565–2575. [Google Scholar] [CrossRef] [PubMed]
  37. Wang, A.; Hou, Q.; Si, L.; Huang, X.; Luo, J.; Lu, D.; Zhu, J.; Shangguan, Y.; Miao, J.; Xie, Y.; et al. The PLATZ transcription factor GL6 affects grain length and number in rice. Plant Physiol. 2019, 180, 2077–2090. [Google Scholar] [CrossRef] [PubMed]
  38. Yuan, G.; Zou, T.; He, Z.; Xiao, Q.; Li, G.; Liu, S.; Xiong, P.; Chen, H.; Peng, K.; Zhang, X.; et al. SWOLLEN TAPETUM AND STERILITY 1 is required for tapetum degeneration and pollen wall formation in rice. Plant Physiol. 2022, 190, 352–370. [Google Scholar] [CrossRef] [PubMed]
  39. Jiang, J.; Lv, M.; Liang, Y.; Ma, Z.; Cao, J. Identification of novel and conserved miRNAs involved in pollen development in Brassica campestris ssp. chinensis by high-throughput sequencing and degradome analysis. BMC Genom. 2014, 15, 146. [Google Scholar] [CrossRef]
  40. Hermkes, R.; Fu, Y.; Nürrenberg, K.; Budhiraja, R.; Schmelzer, E.; Elrouby, N.; Dohmen, R.J.; Bachmair, A.; Coupland, G. Distinct roles for Arabidopsis SUMO protease ESD4 and its closest homolog ELS1. Planta 2011, 233, 63–73. [Google Scholar] [CrossRef]
  41. Pei, W.; Jain, A.; Ai, H.; Liu, X.; Feng, B.; Wang, X.; Sun, Y.; Xu, G.; Sun, S. OsSIZ2 regulates nitrogen homeostasis and some of the reproductive traits in rice. J. Plant Physiol. 2019, 232, 51–60. [Google Scholar] [CrossRef] [PubMed]
  42. Srivastava, A.K.; Zhang, C.; Caine, R.S.; Gray, J.; Sadanandom, A. Rice SUMO protease Overly Tolerant to Salt 1 targets the transcription factor, OsbZIP23 to promote drought tolerance in rice. Plant J. 2017, 92, 1031–1043. [Google Scholar] [CrossRef] [PubMed]
  43. Zuker, M. Mfold web server for nucleic acid folding and hybridization prediction. Nucleic Acids Res. 2003, 31, 3406–3415. [Google Scholar] [CrossRef] [PubMed]
  44. Dai, X.; Zhuang, Z.; Zhao, P. psRNATarget: A plant small RNA target analysis server (2017 release). Nucleic Acids Res. 2018, 46, W49–W54. [Google Scholar] [CrossRef] [PubMed]
  45. Chen, C.; Chen, H.; Zhang, Y.; Thomas, H.R.; Frank, M.H.; He, Y.; Xia, R. TBtools: An integrative toolkit developed for interactive analyses of big biological data. Mol. Plant 2020, 13, 1194–1202. [Google Scholar] [CrossRef] [PubMed]
  46. Chen, C.; Wu, Y.; Li, J.; Wang, X.; Zeng, Z.; Xu, J.; Liu, Y.; Feng, J.; Chen, H.; He, Y.; et al. TBtools-II: A “one for all, all for one” bioinformatics platform for biological big-data mining. Mol. Plant 2023, 16, 1733–1742. [Google Scholar] [CrossRef]
  47. Livak, K.J.; Schmittgen, T.D. Analysis of relative gene expression data using real-time quantitative PCR and the 2−ΔΔCT method. Methods 2001, 25, 402–408. [Google Scholar] [CrossRef]
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Figure 1. Morphological and cytological observations of H1, HF, and LF. (A,B) Plant and panicle types of H1, HF, and LF. (C) Pollen grains stained with 1% I2/KI solution. (D) Pollen grains stained with 1% TTC solution. LF exhibited a high frequency of aborted pollen grains (arrows) and low viability. Bars = 10 cm (A), 1 cm (B), 100 µm (C,D).
Figure 1. Morphological and cytological observations of H1, HF, and LF. (A,B) Plant and panicle types of H1, HF, and LF. (C) Pollen grains stained with 1% I2/KI solution. (D) Pollen grains stained with 1% TTC solution. LF exhibited a high frequency of aborted pollen grains (arrows) and low viability. Bars = 10 cm (A), 1 cm (B), 100 µm (C,D).
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Figure 2. Double fertilization and embryogenesis in LF and HF. (A,B) Mature embryo sac in HF and LF. (C) Frequency distribution of embryo sac development and double fertilization; n, total number of ovules. (D–G) Normal ovaries in HF at 1 h after flowering (1 h), 1 day after flowering (DAF) (1D), 3 DAF (3D), and 5 DAF (5D). (H–K) Infertile ovaries in LF. 1, central cell; 2, antipodal cells; 3, polar nuclei; 4, synergid; 5, egg cell; 6, sperm nucleus approaches polar nuclei at 1 h; 7, sperm nucleus enters egg cell at 1 h; 8, globular embryoid at 1 DAF; 9, free endosperm nucleus at 1 DAF; 10, pear-shaped embryoid at 3 DAF; 11, endosperm at 3 DAF; 12, embryo at 5 DAF. M, mature; h, hour; D, days after flowering. Bars, 100 µm.
Figure 2. Double fertilization and embryogenesis in LF and HF. (A,B) Mature embryo sac in HF and LF. (C) Frequency distribution of embryo sac development and double fertilization; n, total number of ovules. (D–G) Normal ovaries in HF at 1 h after flowering (1 h), 1 day after flowering (DAF) (1D), 3 DAF (3D), and 5 DAF (5D). (H–K) Infertile ovaries in LF. 1, central cell; 2, antipodal cells; 3, polar nuclei; 4, synergid; 5, egg cell; 6, sperm nucleus approaches polar nuclei at 1 h; 7, sperm nucleus enters egg cell at 1 h; 8, globular embryoid at 1 DAF; 9, free endosperm nucleus at 1 DAF; 10, pear-shaped embryoid at 3 DAF; 11, endosperm at 3 DAF; 12, embryo at 5 DAF. M, mature; h, hour; D, days after flowering. Bars, 100 µm.
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Figure 3. Pollen mother cell chromosome behavior during meiosis in LF (low-fertility tetraploid line). (A) Zygotene; (B) Pachytene; (C) Diplotene; (D) Diakinesis; (E) Pre-metaphase I; (F) Metaphase I; (G) Anaphase I; (H) Telophase I; (I) Metaphase II; (J) Anaphase II; (K,L) Chromosome dragging at metaphase I (arrows); (M) Chromosome lagging at anaphase I (arrows); (N) Unordered chromosomes at anaphase I; (O) Micronuclei at telophase I (arrows); (P) Asynchrony of the chromosome during meiosis II. Red number indicates different-type quadrivalents: 1, ring-shaped; 2, chain-shaped; 3, frying pan-shaped; 4, OK-shaped; 5, X-shaped. Bars, 10 μm.
Figure 3. Pollen mother cell chromosome behavior during meiosis in LF (low-fertility tetraploid line). (A) Zygotene; (B) Pachytene; (C) Diplotene; (D) Diakinesis; (E) Pre-metaphase I; (F) Metaphase I; (G) Anaphase I; (H) Telophase I; (I) Metaphase II; (J) Anaphase II; (K,L) Chromosome dragging at metaphase I (arrows); (M) Chromosome lagging at anaphase I (arrows); (N) Unordered chromosomes at anaphase I; (O) Micronuclei at telophase I (arrows); (P) Asynchrony of the chromosome during meiosis II. Red number indicates different-type quadrivalents: 1, ring-shaped; 2, chain-shaped; 3, frying pan-shaped; 4, OK-shaped; 5, X-shaped. Bars, 10 μm.
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Figure 4. Frequency of abnormal chromosome behavior and quadrivalent distribution in meiotic pollen mother cells. (A) Frequency of abnormalities in LF and HF during different stages of meiosis. (B) Average of quadrivalents in LF and HF at diakinesis and metaphase I. (C) Frequency of different types of quadrivalents at diakinesis and metaphase I. “Ring”, “Chain”, “Frying pan”, “OK”, and “X” indicate different-type quadrivalents shown in Figure 3D–F. n, number of pollen mother cells observed.
Figure 4. Frequency of abnormal chromosome behavior and quadrivalent distribution in meiotic pollen mother cells. (A) Frequency of abnormalities in LF and HF during different stages of meiosis. (B) Average of quadrivalents in LF and HF at diakinesis and metaphase I. (C) Frequency of different types of quadrivalents at diakinesis and metaphase I. “Ring”, “Chain”, “Frying pan”, “OK”, and “X” indicate different-type quadrivalents shown in Figure 3D–F. n, number of pollen mother cells observed.
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Figure 5. Identification of miRNAs from meiotic anthers of H1, HF, and LF. (A) Number of miRNAs detected in H1, HF, and LF. Yes, miRNAs detected in miRBase. Diff, miRNAs detected in miRBase with differing sequence. New, miRNAs not present in miRBase. (B) Venn diagram analysis of miRNAs among H1, HF, and LF. (C) Length distribution of unique miRNAs. (D) Number of miRNAs with different expression levels, categorized as High, Middle, and Low. (E) Number of differentially expressed miRNAs (DEMs) in H1 and HF; (F) identification of coDEMs between H1 and HF; (G) hierarchical cluster analysis among coDEMs; (H) upset plot analysis of coDEM targets and coDEGs to identify negative regulatory groups. DEGs, differentially expressed genes.
Figure 5. Identification of miRNAs from meiotic anthers of H1, HF, and LF. (A) Number of miRNAs detected in H1, HF, and LF. Yes, miRNAs detected in miRBase. Diff, miRNAs detected in miRBase with differing sequence. New, miRNAs not present in miRBase. (B) Venn diagram analysis of miRNAs among H1, HF, and LF. (C) Length distribution of unique miRNAs. (D) Number of miRNAs with different expression levels, categorized as High, Middle, and Low. (E) Number of differentially expressed miRNAs (DEMs) in H1 and HF; (F) identification of coDEMs between H1 and HF; (G) hierarchical cluster analysis among coDEMs; (H) upset plot analysis of coDEM targets and coDEGs to identify negative regulatory groups. DEGs, differentially expressed genes.
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Figure 6. Expression analyses of four key coDEMs and coDEGs in developing anthers. Expression levels of miR9564-ARPS, miR528-M1T, miR27874-OsRPC53, and miR818d-M4T were analyzed using RNA-seq data (A) and qRT-PCR (B) in H1, HF, and LF anthers. Fc, fold change relative to sample with lowest expression. Ubiquitin was used as internal control gene. S7 to S10 represent anther stages. Error bars indicate standard error (SE) with n = 3.
Figure 6. Expression analyses of four key coDEMs and coDEGs in developing anthers. Expression levels of miR9564-ARPS, miR528-M1T, miR27874-OsRPC53, and miR818d-M4T were analyzed using RNA-seq data (A) and qRT-PCR (B) in H1, HF, and LF anthers. Fc, fold change relative to sample with lowest expression. Ubiquitin was used as internal control gene. S7 to S10 represent anther stages. Error bars indicate standard error (SE) with n = 3.
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Figure 7. The relationship between MIR9564 haplotypes and ARPS expression levels. (A,B) Information about the precursor of miR9564 (MIR9564). Ha1 and Ha2 indicate two haplotypes of MIR9564. (C) Predicted RNA secondary structures of Ha1-MIR9564 and Ha2-MIR9564; (D) expression levels of ARPS in plants with different MIR9564 haplotypes. Het indicates the heterozygote of Ha1 and Ha2. N, indicated numbers of RNA-seq samples for expression analyses of ARPS.
Figure 7. The relationship between MIR9564 haplotypes and ARPS expression levels. (A,B) Information about the precursor of miR9564 (MIR9564). Ha1 and Ha2 indicate two haplotypes of MIR9564. (C) Predicted RNA secondary structures of Ha1-MIR9564 and Ha2-MIR9564; (D) expression levels of ARPS in plants with different MIR9564 haplotypes. Het indicates the heterozygote of Ha1 and Ha2. N, indicated numbers of RNA-seq samples for expression analyses of ARPS.
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Figure 8. Dual-GFP assay for negative regulation between MIR9564 and ARPS. (A) Schematic diagrams illustrating information about effectors and reporters. NLS, nuclear localization signal; DG, Dual-GFP. (B) Subcellular localization of Dual-GFP signal for testing MIR9564 regulation on ARPS-GFP activity. (C) Frequency of protoplasts with different types of GFP signals. N, number of observed protoplasts.
Figure 8. Dual-GFP assay for negative regulation between MIR9564 and ARPS. (A) Schematic diagrams illustrating information about effectors and reporters. NLS, nuclear localization signal; DG, Dual-GFP. (B) Subcellular localization of Dual-GFP signal for testing MIR9564 regulation on ARPS-GFP activity. (C) Frequency of protoplasts with different types of GFP signals. N, number of observed protoplasts.
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Figure 9. Morphological identification of ARPS-OE. (A) Plant morphology of WT (H1) and ARPS-OE. (B) Expression level of ARPS in WT and ARPS-OE. (C–I) Plant height (C), grain number per panicle (D), panicle length (E), mature panicles (F), seed setting rate (G), I2/KI-stained pollen fertility (H,I) of WT and ARPS-OE. Aborted pollen grains are marked by arrows. Bars = 20 cm (A), 1 cm (F), and 20 μm (I). Error bars indicate the SE with n ≥ 3. Significant differences are indicated by different lowercase letters (one-way ANOVA, least significant difference (LSD) test, p < 0.05).
Figure 9. Morphological identification of ARPS-OE. (A) Plant morphology of WT (H1) and ARPS-OE. (B) Expression level of ARPS in WT and ARPS-OE. (C–I) Plant height (C), grain number per panicle (D), panicle length (E), mature panicles (F), seed setting rate (G), I2/KI-stained pollen fertility (H,I) of WT and ARPS-OE. Aborted pollen grains are marked by arrows. Bars = 20 cm (A), 1 cm (F), and 20 μm (I). Error bars indicate the SE with n ≥ 3. Significant differences are indicated by different lowercase letters (one-way ANOVA, least significant difference (LSD) test, p < 0.05).
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Table 1. Fertility comparison among H1, HF, and LF.
Table 1. Fertility comparison among H1, HF, and LF.
MaterialsSeed Setting (%)I2/KI-Stained Pollen GrainsTTC-Stained Pollen Grains
Normal (%)NumberViable (%)Number
H174.38 ± 1.90 A97.10 ± 0.26 A277046.93 ± 4.26 A5697
HF71.39 ± 1.91 A90.31 ± 1.58 A374165.75 ± 2.78 A6452
LF5.17 ± 0.80 C26.02 ± 8.06 B356017.95 ± 6.27 B3907
Note: TTC indicates 2,3,5-Triphenyl-2H-tetrazolium chloride solution. Number indicates total number of observed pollen grains. SEs were used here with n ≥ 3. Significant differences are indicated by different uppercase letters (one-way ANOVA, least significant difference (LSD) test, p < 0.01).
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Lu, Z.; Huang, W.; Zhu, L.; Liang, G.; Huang, Y.; Wu, J.; Chen, R.; Li, X.; Liu, X. Cytological Observation and RNA-Seq Analyses Reveal miR9564 and Its Target Associated with Pollen Sterility in Autotetraploid Rice. Plants 2024, 13, 1461. https://doi.org/10.3390/plants13111461

AMA Style

Lu Z, Huang W, Zhu L, Liang G, Huang Y, Wu J, Chen R, Li X, Liu X. Cytological Observation and RNA-Seq Analyses Reveal miR9564 and Its Target Associated with Pollen Sterility in Autotetraploid Rice. Plants. 2024; 13(11):1461. https://doi.org/10.3390/plants13111461

Chicago/Turabian Style

Lu, Zijun, Weicong Huang, Lianjun Zhu, Guobin Liang, Yu Huang, Jinwen Wu, Rou Chen, Xiang Li, and Xiangdong Liu. 2024. "Cytological Observation and RNA-Seq Analyses Reveal miR9564 and Its Target Associated with Pollen Sterility in Autotetraploid Rice" Plants 13, no. 11: 1461. https://doi.org/10.3390/plants13111461

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