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Comparative transcriptome analysis reveals key genes associated with meiotic stability and high seed setting rate in tetraploid rice

BMC Plant Biology volume 25, Article number: 645 (2025) Cite this article

Abstract

Background

Polyploid rice has a high yield potential and excellent nutritional quality. The development of polyploid rice remained critically limited for several decades due to low seed setting rate until the successful breeding of polyploid meiosis stability (PMeS) lines. To determine the mechanism responsible for meiotic stability and high seed setting rate of PMeS line, agronomic traits, pollen fertility and viability, and meiotic behaviors of PMeS and non-PMeS lines were investigated. Further, comparative transcriptome analysis was performed to identify genes associated with meiotic stability and high seed setting rate in PMeS line.

Results

The seed setting rate, fertile and viable pollen ratios of PMeS line were significantly higher than those of non-PMeS line. The PMeS line exhibited stable meiosis, and chromosomes mainly paired as bivalents, rarely as univalents and multivalents in prophase I. Few lagging chromosomes were observed in anaphase I. By contrast, the homologous chromosomes pairing was disorganized in the non-PMeS line, with low frequencies of bivalents and high frequencies of univalents and multivalents in prophase I, while more cells with increased lagging chromosomes were detected in anaphase I. Many differentially expressed genes (DEGs) between PMeS and non-PMeS lines were identified through comparative transcriptome analysis. Some meiosis-related genes were specifically investigated from all DEGs. Further, several meiotic genes were identified as candidate genes.

Conclusions

The study not only demonstrates the morphological, cytological, and molecular differences between the PMeS and non-PMeS lines, but also provides several key genes associated with meiotic stability and high seed setting rate in tetraploid rice.

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Background

Polyploidization (whole-genome duplication) is a predominant driver of plant evolution and speciation that enhance plant fitness through increased genetic diversity and adaptation to diverse environments [1,2,3,4]. Naturally occurring polyploids have been identified in a wide range of taxa and recent estimates suggest that almost all extant angiosperm species have experienced one or more polyploidization events in their evolutionary history [5,6,7,8,9]. Many crops, such as wheat (Triticum aestivum L.), cotton (Gossypium hirsutum L.), and rape (Brassica napus L.), are great examples of polyploid evolution in plants. After undergoing the evolution from diploid to polyploids, they have not only generated rich genetic diversity but their yields have also increased [10]. Artificially induced polyploidy is a valuable tool for facilitating plant breeding and development of new crops [11]. Polyploid rice (Oryza sativa L.) is characterized by thick stems, large grains, increased nutritive value, strong stress resistance, and high yield potential [12,13,14]. Following the discovery of autotetraploid rice [15], intense polyploid rice breeding programs were conducted before 1960s. But nearly all research ceased because of the low seed setting rate of polyploid rice [16]. The low seed setting rate was the bottleneck problem that seriously limited the development of polyploid rice breeding [12, 17]. According to the fact that natural allopolyploid plants often exhibit diploid-like meiotic behavior and normal sexual reproduction, Cai et al. proposed that the origin of the low seed setting rate in autotetraploid rice was the formation of unstable pairing forms, such as univalent and multivalent during meiosis [18]. Expanding the genetic distance between chromosomes and reducing the formation of unstable pairing forms is a key strategy to overcoming the low seed setting rate in polyploid rice [18]. After years of work, two polyploid meiosis stability (PMeS) lines, HN2026-4x and Sg99012-4x with stable meiosis and high seed setting rates (> 80%) were bred through extensive inter-subspecies and composite crosses between indica and japonica [19]. Moreover, hybrids between PMeS lines and common autotetraploid rice lines with low seed setting rates showed over 80% high seed setting rates [19, 20]. This indicated that the breeding of PMeS lines solved the bottleneck of low seed setting rate in polyploid rice [19, 21]. Based on the PMeS lines, over 5,000 polyploid rice lines have been developed and cultured, with numerous lines nearing production and application phases [22, 23]. Therefore, the determination of meiotic stability and high seed setting rate mechanism in PMeS line has important theoretical and practical significance for polyploid rice breeding. In the present study, the agronomic traits, pollen fertility and viability, and meiotic behaviors of PMeS line HN2026-4x and non-PMeS line 9311-4x were investigated. Moreover, deep illumina RNA sequencing was used to analyze their genetic differences at the transcriptome level. Some meiosis related genes were specifically investigated from all differentially expressed genes (DEGs). This study reveals key morphological, cytological and molecular diversity between PMeS and non-PMeS lines and provides candidate meiotic genes associated with stable meiosis and high seed setting rate in tetraploid rice.

Results

Agronomic traits

The main morphology and agronomic traits of HN2026-4x (PMeS line) and 9311-4x (non-PMeS line) are shown in Table 1; Fig. 1. The plant height, effective panicle number per plant, total grain number per panicle, and filled grain number per panicle of HN2026-4x were significantly higher than those of 9311-4x. However, the grain length and 1000-grain weight of HN2026-4x were significantly lower than those of 9311-4x. Especially, the seed setting rate of HN2026-4x was 83.73%, which was significantly higher than that of 9311-4x (32.15%). This is the most typical difference between PMeS and non-PMeS lines in polyploid rice.

Table 1 Main agronomic traits of HN2026-4x and 9311-4x
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Fig. 1
figure 1

Morphological characteristics of HN2026-4x and 9311-4x. A Plants; B Panicles; C Grains. Left: HN2026-4x; Right: 9311-4x; Bars: A = 20 cm; B = 5 cm; C = 1 cm

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Meiotic behavior of chromosomes in pollen mother cells

There were significant differences in meiotic behavior of pollen mother cells (PMCs) between HN2026-4x and 9311-4x (Fig. 2). Chromosomes mainly paired as bivalents (16.42/cell) in HN2026-4x, with some quadrivalents (3.62/cell), while only a few univalents (0.06/cell), trivalents (0.04/cell) and multivalents (0.08/cell) were detected in prophase I. Only 1.4 lagging chromosomes were detected in anaphase I and the percentage of cells with lagging chromosomes was only 10.71% (Tables 2 and 3). By contrast, irregular chromosome pairing was detected in 9311-4x, with low frequency of bivalents and high frequencies of univalents, trivalents, quadrivalents, and multivalents in prophase I. In addition, the number of lagging chromosomes and the percentage of cells with lagging chromosomes in anaphase I were significantly greater than those of HN2026-4x (Tables 2 and 3).

Fig. 2
figure 2

The meiosis behavior of pollen mother cells in HN2026-4x and 9311-4x. A, B, C, D HN2026-4x; E, F, G, H 9311-4x. A, E Prophase I (Diakinesis); B, F Metaphase I; C, G Anaphase I; D, H Telophase I. The lagging chromosomes are indicated by arrows. Bar = 10 μm

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Table 2 Chromosome configurations in PMCs meiosis of HN2026-4x and 9311-4x
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Table 3 Lagging chromosomes in PMCs meiosis of HN2026-4x and 9311-4x
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Pollen fertility and viability

The results of pollen fertility and vitality analyses were shown in Fig. 3. The ratios of fertile pollen and viable pollen of HN2026-4x were 82.93% and 80.63%, respectively, while those of 9311-4x were 75.07% and 58.69%, respectively. The pollen fertility and viability of HN2026-4x were both significantly higher than those of 9311-4x.

Fig. 3
figure 3

Analysis of pollen fertility and viability of HN2026-4x and 9311-4x. A Pollens of HN2026-4x stained by I2-KI; B Pollens of 9311-4x stained by I2-KI; C Pollens of HN2026-4x stained by FDA; D Pollens of 9311-4x stained by FDA; E Comparison of pollen fertility and viability; H: HN2026-4x; Y: 9311-4x; Significant differences were determined using independent samples t-test; *** and **** indicate significant differences at 0.001 and 0.0001 probability levels, respectively. Bar = 200 μm

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Transcriptome sequencing and reads mapping

Comparative transcriptome analysis of HN2026-4x and 9311-4x was performed to identify the gene expression differences at meiosis stage. A total of 151,152,958 and 158,155,192 clean reads, with Q30 of 85.10% and 85.13%, and GC content of 57.83% and 57.35% were identified from HN2026-4x and 9311-4x transcriptome, respectively. The reads were successfully mapped to Nipponbare genome (IRGSP-1.0 pseudomolecule/MSU7) with 81.98–83.45% coverage, of which 80.28–81.80% were uniquely mapped (Table 4; Fig. S1).

Table 4 Summary of transcriptome data by the illumina platform
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Identification and functional annotation of DEGs

Using FPKM method, a total of 36,029 genes (including 1,742 new genes) were detected for expression (Table S1). Among them, a total of 1,441 genes were identified as DEGs between HN2026-4x and 9311-4x with a screening criteria of fold Change ≥ 2 (|log2FC| ≥ 1) and FDR < 0.01, with 864 and 577 up- and down-regulated genes, respectively in HN2026-4x (Fig. 4). A total of 1,153 unigenes were annotated, with 1,152, 801, 329, 905, and 96 unigenes being annotated in Nr, Swiss-Prot, COG, GO, and KEGG databases, respectively (Table S2).

Fig. 4
figure 4

Volcano map of differentially expressed genes between HN2026-4x and 9311-4x. Each dot represents a gene, with turquoise dots representing differentially expressed genes and red dots representing non differentially expressed genes

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GO annotation classified DEGs into three functional categories, including cellular component (CC), molecular function (MF), and biological process (BP), which could further be divided into 16, 16, and 24 subcategories, respectively (Fig. 5). Cell, cell part, and organelle were the most annotated unigenes in CC category, while binding, catalytic activity, and transporter activity were the most annotated in MF category. In addition, cellular process, metabolic process, and response to stimulus were the most annotated unigenes in BP category. Significantly, high number of unigenes were annotated in the reproduction and reproductive process subcategory, which was consistent with the significant differences in reproductive characteristics between HN2026-4x and 9311-4x.

Fig. 5
figure 5

Gene ontology (GO) analysis of differentially expressed genes between HN2026-4x and 9311-4x. The percentage and number of genes in each subcategory are shown on the left and right y-axes, respectively. The GO subcategories are shown on the x-axis

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The DEGs in COG annotation were classified into 22 COG categories, with ‘General function prediction only’(R) as the largest group, followed by ‘Replication, recombination and repair’ (L), and ‘Function unknown’ (S) (Fig. 6). The result indicated the differences in replication, recombination, and repair between HN2026-4x and 9311-4x.

Fig. 6
figure 6

Clusters of orthologous groups (COG) classification of differentially expressed genes between HN2026-4x and 9311-4x. A total of 329 unigenes are classified into 22 COG categories

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KEGG analysis showed that 96 DEGs were assigned to 67 pathways (Table S3). The most enriched category was metabolism with 48 unigenes, which included carbohydrate metabolism, amino acid metabolism, lipid metabolism, metabolism of other amino acids, nucleotide metabolism, energy metabolism, and other subcategories. The genetic information processing was the second most enriched category with 20 unigenes, which included translation, folding, sorting and degradation, replication and repair, and transcription. The result suggested significant differences in genetic processes between HN2026-4x and 9311-4x.

Screening of key genes associated with tetraploid rice meiosis

Since the seed setting rate is directly affected by meiosis, DEGs screening was performed to identify specific functional genes related to meiotic stage. Based on GO annotation, a total of 19 DEGs related to meiosis were screened, which involved in 20 GO terms in CC, MF, and BP categories (Table 5). Of these, Os07g0486000 and Os11g0615800 belonged to several terms, and their expression levels significantly differed between HN2026-4x and 9311-4x. Annotation of Os07g0486000 and Os11g0615800 in the RAP database (http://rapdb.dna.affrc.go.jp/) revealed that the two genes were OsMSH4 and OsRAD51A1, respectively, which are key meiotic genes in rice. COG annotation revealed 39 unigenes were annotated in ‘Replication, recombination and repair’ category, including Os07g0486000 and Os11g0615800, with the latter also being annotated in ‘homologous recombination’ (ko03440) pathway based on KEGG analysis (Fig. S2). Based on the comprehensive analysis of gene function and differential expression levels, three meiotic genes Os07g0486000, Os11g0615800, and Os09g0506800 (PAIR2) were identified as candidates responsible for meiotic stability and high seed setting rate in tetraploid rice.

Table 5 List of DEGs participated in tetraploid rice meiosis annotated by GO database
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Validation of candidate genes with quantitative real-time PCR

Six genes with obvious expression differences between HN2026-4x and 9311-4x, including Os07g0486000, Os11g0615800, Os09g0506800, Os01g0917500, Os06g0553200, and Os04g0543700 were validated by quantitative real-time PCR (qRT-PCR). The result showed that the gene expression levels in qRT-PCR were highly consistent with those in RNA-Seq (Table 6; Fig. 7), suggesting reliability and accuracy of the RNA-Seq data in this study.

Table 6 The expression levels of DEGs in RNA-Seq and qRT-PCR
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Fig. 7
figure 7

Validation of six differentially expressed genes by qRT-PCR. H: HN2026-4x; Y: 9311-4x. Significant differences were determined using independent samples t-test; *, ***, and **** indicate significant differences at 0.05, 0.001, and 0.0001 probability levels, respectively

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Discussion

Stable meiosis is crucial for high seed setting rate in tetraploid rice

Rice is one of the three major food crops globally and consumed by over half of the world’s population [24]. The increasing human population is projected to be 9 billion by 2050, which puts pressure on the need to increase rice yield by at least 60% to guarantee future food security [25, 26]. However, limited research breakthroughs have been witnessed since the introduction of the dwarf breeding and rice hybridization technology. Thus, new technological approaches are warranted to ensure significant increase in rice yield. Given their high yield and nutritional potential, polyploid rice breeding is considered as one of the new breeding strategies in the 21st century [12,13,14, 18, 27, 28]. However, the low seed setting rate seriously prevented the development of polyploid rice breeding for a long time [12, 17, 18]. Therefore, to achieve the application of polyploid rice, it is necessary to solve the bottleneck problem of low seed setting rate.

The low seed setting rate in polyploid rice has been associated various factors, such gamete and zygote abortion, environmental effects, and abnormal cell separations in the meiotic anaphase I [16]. Moreover, autotetraploid rice exhibited more aborted pollen as well as more degenerated and aberrant embryo sacs, which suggested that the low seed setting rate resulted from reduced sexual reproduction ability due to abnormal development of male and female gametophytes [29, 30]. Numerous abnormalities that potentially influence seed setting rate have also been observed in the autotetraploid rice during embryo sac, fertilization, embryogenesis, and endosperm formation [31,32,33,34,35,36,37]. Recent molecular studies detected abnormal expression profiles of fertility related genes, altered methylation levels, and differentially expressed non-coding RNAs during pollen and embryo sac development in autotetraploid rice [38,39,40,41,42], which provide crucial basis for uncovering the molecular mechanisms of low seed setting rate.

After analyzing the evolution of allopolyploids in plants, Cai et al. proposed that the low seed setting rate of autotetraploid rice was ultimately caused by its chromosome composition [18]. Unlike allopolyploid, the chromosome set of autopolyploid is derived from the same plant species. In the first meiotic division (MI), a pair of homologous chromosomes forms a bivalent in diploid or allopolyploid that regularly segregate away from one another. However, in autopolyploid, typical formation of bivalents is often inhibited due to homology of three or more chromosomes, which prevent intrinsic cues necessary for normal, diploid-like segregation [43]. The formation of univalent and multivalent at prophase I as well as unequal separation of chromosomes at anaphase I results in the formation of unbalanced gametes, gamete sterility, and low seed setting rate in autotetraploid plants [44,45,46]. Consequently, a novel pathway for “breeding super rice using double advantages of wide cross and polyploidization” has been proposed [18], to overcome low seed setting rate in tetraploid rice by expanding the genetic distance between chromosomes to enhance bivalent formations and reduce unstable pairing forms, leading to improved chromosome segregation. Under the guidance of this strategy, two PMeS lines were bred through extensive inter-subspecies and composite crosses of indica and japonica [19]. The PMeS lines have stable meiosis and high seed setting rates. Crucially, this trait exhibits stable dominant inheritance [19, 20].

Our results showed obvious differences between the meiotic behaviors of PMeS line, HN2026-4x and non-PMeS line, 9311-4x. For example, chromosome pairings mostly formed bivalents in HN2026-4x, but with rare univalents and multivalents in prophase I, as well as few lagging chromosomes in anaphase I. By contrast, the homologous chromosome pairing in 9311-4x was disorganized and formed more univalents and multivalents in prophase I, as well as more cells with more lagging chromosomes in anaphase I. This suggested that the PMeS line rather than the non-PMeS line had more regular and stable meiosis process. Further, the pollen fertility and viability of PMeS line were significantly higher than those of non-PMeS line, which is likely due to the stable meiosis in PMeS line. Therefore, it can be inferred that unstable meiosis is the origin of low seed setting rate in autotetraploid rice. The occurrence of univalents, multivalents, and lagging chromosomes caused unbalanced distribution of chromosomes to daughter cells, which further decreased gamete fertility, inevitably affecting fertilization and embryonic development, leading to low seed setting rate. These results suggest that stable meiosis is crucial for high seed setting rate in the tetraploid rice.

Stable meiosis is controlled by key meiotic genes

Meiosis is a key biological process in sexual reproduction and is important for genetic diversity of populations. During meiosis, a single round of DNA replication is followed by two successive rounds of nuclear division to generate haploid gametes. The first division (meiosis I) has been recognized as the crucial stage of meiosis, in which prophase I is particularly important [47,48,49,50]. In prophase I, homologous chromosomes recognition, pairing, synapsis, and recombination are delicately linked to ensure formation of stable bivalents and precise separation of homologous chromosomes. Any errors in these processes will lead to irregular segregation of homologous chromosomes and affect fertility [49,50,51,52,53]. To date, numerous genes involved in the regulation of meiosis have been characterized in diploid species, including rice [54, 55], while only limited studies on meiosis mechanism are available in polyploids. Due to the presence of more than two homologous chromosomes (homologs) in autopolyploids, or homoeologous chromosomes (homoeologs) in allopolyploids, faithful chromosome segregation in meiosis is especially demanding to ensure genome stability and fertility in polyploid species [56, 57]. Chromosomes need to be sorted out during meiosis to produce balanced gametes, otherwise multiple or illegitimate chiasmatic associations would result in homologous chromosome missegregation, which further leads to aneuploidy and partial fertility [58, 59]. Crossovers (COs) play a key role in faithful segregation of homologous chromosomes at the first meiotic division. In autopolyploids, homologous chromosome segregation can be improved by reducing CO frequency to inhibit multivalent and thereby enhance bivalent formation [59]. The tetraploid Arabidopsis arenosa is a natural autotetraploid with fewer chiasmata per bivalent than those observed in diploids, and exhibits stable meiosis and fully fertile. Eight meiotic genes which sharply differentiated between diploid and tetraploid A. arenosa were identified through genome scan. They encoded proteins that are critical to CO formation, including meiotic chromosome axis components (ASY1, ASY3, SMC3, and SYN1) and the synaptonemal complex (ZYP1a and ZYP1b) [60, 61]. They may play a critical role in meiotic stability by reducing CO frequencies in autotetraploid A. arenosa.

In allopolyploids, stable meiosis requires both inter-homoeologue CO inhibition and homologous CO activation [59, 62]. A typical example is the Pairing homoeologous 1 (Ph1) locus in allohexaploid wheat (T. aestivum), which can promote CO formation between homologous chromosomes and prevent maturation of CO between homoeologous chromosomes leading to faithful segregation [63, 64]. The Pairing Regulator in B. napus (PrBn) locus was identified as a controlling factor of homoeologous chromosome pairing in allohaploids B. napus [65, 66]. Meiotic stability in polyploid plants is also regulated by MSH4 and MSH5 genes. For example, MSH4 in allotetraploid B. napus could prevent homoeologous CO by promoting homologous CO formation [62]. In allotetraploid wheat (Triticum turgidum L.) and allohexaploid wheat (T. aestivum), both MSH4 and MSH5 genes are required for the obligate CO between homologous chromosomes [67]. Most eukaryotes contain two kinds of CO, class I and II Cos [68]. The majority (85–90%) COs belong to class I, exhibit CO interference, and their formation is dependent on ZMM proteins (ZIP1, ZIP2, ZIP3, ZIP4, MSH4, MSH5, and MER3) [55, 69]. MSH4 and MSH5 are meiosis-specific MutS homologues of bacterial mismatch repair proteins that form heterodimers (MutSγ) to promote class I COs formation. Data from Arabidopsis, rice, tomato (Solanum lycopersicum L.), T. turgidum, and B. napus show that MutSγ is required for 85% of COs and the obligate chiasma, indicating that it is mostly likely the major meiotic recombination pathway in plants [67]. Moreover, MSH4 and MSH5 act upstream of other ZMMs, and the loss of MSH4 function resulted in a more severe diminution in CO formation than other zmm mutants [50, 68]. Overall, these observations demonstrated the key roles of MSH4 and MSH5 in CO formation in both diploid and polyploid plants.

In the present study, cytological observation revealed obvious different meiotic behaviors between PMeS line HN2026-4x and non-PMeS line 9311-4x. Through further transcriptome analysis, some meiosis-related genes were screened from DEGs between HN2026-4x and 9311-4x. Based on the comprehensive analysis of gene function and differential expression level, three meiotic genes Os07g0486000 (OsMSH4), Os11g0615800 (OsRAD51A1), and Os09g0506800 (PAIR2) were identified as candidate genes for meiotic stability and high seed setting rate in tetraploid rice. Notably, MSH4 gene exhibited most significant expression differences between PMeS and non-PMeS lines. Due to the pivotal role of MSH4 in CO formation, it is reasonable to speculate that MSH4 gene is a key gene for regulating meiotic stability in PMeS lines. For RAD51, it is a eukaryotic homolog of bacterial RecA recombinase and functions as an essential protein in homologous recombination and recombinational repair of DNA double-stranded breaks (DSBs) [70,71,72]. In rice, OsRAD51 gene includes OsRAD51A1 and OsRAD51A2 two copies. Both single mutants Osrad51a1 and Osrad51a2 exhibited normal vegetative growth and fertility, while double mutants Osrad51 (Osrad51a1 Osrad51a2) showed normal vegetative growth but with complete sterility, indicating functional redundancy of OsRAD51A1 and OsRAD51A2 in rice fertility [73]. While in vitro experiment have shown that homologous-pairing activity of RAD51A2 is about 10-fold higher than that of RAD51A1 [72]. Compared to the wild type, Osrad51 chromosomes showed imperfect pairing at the pachytene and deficient synaptonemal complex formation. Univalents and multivalents were observed at metaphase I, chromosome fragments and unbalanced chromosome segregation were detected at anaphase I, and CO formation was suppressed in Osrad51 PMCs [73]. Moreover, OsRAD51 paralogues, especially OsRAD51D, have also been shown to inhibit nonhomologous connections, thus ensuring faithful pairing and recombination during meiosis [74]. Although the activity of OsRAD51A1 is much lower than OsRAD51A2 in diploid rice, has its activity and function altered in tetraploid rice to adapt to the evolution of polyploids? PAIR2 is the orthologue of Arabidopsis ASY1. PAIR2 protein associates with axial elements at leptotene and zygotene and is required for the formation of synaptonemal complex. The pair2 mutant in diploid rice exhibited 24 completely unpaired univalents at pachytene and diakinesis [75, 76]. Given the adaptive evolution of meiosis in autotetraploid A. arenosa, it remains unclear whether the PAIR2 also play similar roles in reducing CO frequencies in the tetraploid rice. Next, functional analysis of candidate genes will be performed to uncover the molecular mechanism of meiotic stability and high seed setting rate in PMeS lines, which can provide theoretical and practical basis for promoting polyploid rice breeding.

Conclusion

The seed setting rate, fertile and viable pollen ratios of PMeS line were significantly higher than those of non-PMeS line. PMeS line exhibited stable meiosis, with chromosomes mainly pairing as bivalents, but with rare univalents and multivalents in prophase I. In addition, few lagging chromosomes were detected in anaphase I. DEGs between PMeS and non-PMeS lines were identified, and some meiosis-related genes were specifically investigated. Three meiotic genes Os07g0486000, Os11g0615800, and Os09g0506800 were identified as candidate genes. The study reveals the differences between PMeS and non-PMeS lines from morphology, cytology and molecular biology, and also provides several key genes essential for meiotic stability and high seed setting rate in tetraploid rice.

Materials and methods

Plant materials

Two tetraploid rice lines HN2026-4x (H) and 9311-4x (Y) were used in this research. HN2026-4x is PMeS line with high seed setting rate and was bred through indica-japonica cross [19]. Autotetraploid rice line 9311-4x (non-PMeS line), which has low seed setting rate, was induced from 9311-2x by chromosome-doubling. All plant materials were provided by the Laboratory of Polyploid Genetics, School of Life Sciences, Hubei University, China. The plant materials were grown in the experimental field of Hubei University, Wuhan, China (30°34′N, 114°20′E). Seedlings were planted with 16.7 cm × 30.0 cm spacing and managed with general field production practices.

Evaluation of agronomic traits

Main agronomic traits of HN2026-4x and 9311-4x were measured according to the methods of He et al. [77], including plant height, number of effective panicles per plant, panicle length, grain length and width, total grains per panicle, filled grains per panicle, seed setting rate, and 1,000-grain weight. Five plants of each line were measured.

Observation of meiotic behaviors in PMCs

Young panicles at meiotic stage were collected and fixed in Carnoy’s fixative (95% ethanol: glacial acetic acid, 3:1 [v/v]) for 24 h, then stored in 70% ethanol at 4 °C. Meiotic chromosome preparations were made according to the protocol of Li and Zhang [78] with modification. The fixed panicles were rinsed in distilled water for 20 min. Then, anthers were picked and digested in an enzyme mixture containing 2% cellulase and 2% pectinase for 3 h at 28 °C, washed three times in distilled water, and incubated in 75 mM KCl for 10 min. The anthers were then placed on precooled slides and squashed in the presence of the fixative. The slides were heated over an alcohol flame to dry the fixative, stained with carbol fuchsin for 20 min, washed under a stream of tap water, and then dried. The meiotic processes were observed under Olympus BX51 light microscope (Olympus Corporation, Tokyo, Japan) to record the chromosome configurations and lagging chromosomes.

Analysis of pollen fertility and viability

Pollen fertility and viability were analyzed by staining mature pollens with 1.0% (w/v) I2-KI and 50 µg mL− 1 fluorescein diacetate (FDA) solutions, respectively followed by observation under microscope. Three slides were made for each observation, and pollens were counted in 10 random micro-optical fields on each slide. Ratios of fertile pollen and viable pollen were calculated using the following formulas: Ratio of fertile pollen (%) = (number of stained pollen grains / number of total pollen grains) × 100; Ratio of viable pollen (%) = (number of pollen grains that emitted bright green fluorescence / number of total pollen grains) × 100.

RNA extraction and library construction

Anthers at the meiotic stage were collected from HN2026-4x and 9311-4x in three biological replicates, frozen in liquid nitrogen, then stored at − 80 °C for RNA extraction. Total RNA from each sample was extracted using TRIzol Reagent (Life technologies, California, USA) according to the manufacturer’s instructions and then treated with RNase-free DNase I (TAKARA, Tokyo, Japan) to remove DNA. RNA integrity and concentration were checked using a Nanodrop 2000 spectrophotometer (Thermo Scientific, Wilmington, DE, USA) and an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). The mRNA was isolated using NEBNext Poly (A) mRNA Magnetic Isolation Module (NEB, E7490). The enriched mRNA was fragmented into approximately 200 nt RNA inserts, which were then reverse transcribed into cDNA. cDNA libraries were constructed with the NEBNext Ultra RNA Library Prep Kit for Illumina (NEB, E7530) and NEBNext Multiplex Oligos for Illumina (NEB, E7500) following the manufacturer’s instructions.

Transcriptome sequencing analysis and DEGs identification

Sequencing was performed on an Illumina HiSeq™ 2500 platform by Biomarker Technologies, Beijing, China. Low quality reads, such as adaptor sequences, unknown nucleotides > 5%, or Q20 < 20%, were removed using perl script. The filtered clean reads were mapped to Nipponbare genome (IRGSP-1.0 pseudomolecule/MSU7) using Tophat2 software [79]. The aligned records from the aligners in BAM/SAM format were further examined to remove potential duplicate molecules, then gene expression levels estimated using FPKM values in Cufflinks software [80]. Differential expression analysis was performed using the DESeq2 [81]. The false discovery rate (FDR) method was used to identify threshold P-value in multiple tests to compute significance differences, and genes with a Fold Change ≥ 2 (|log2FC| ≥ 1) and FDR ≤ 0.01 were selected as significant DEGs.

Gene functional annotation

The unigenes were annotated using BLAST program against the NCBI database followed by homology searches in various databases, such as NCBI Non-redundant protein database (Nr), Swiss-Prot database, Kyoto Encyclopedia of Genes and Genomes (KEGG), and Clusters of Orthologous Groups of proteins database (COG) with a BLAST threshold of (E-value < 1E-5), and the best alignment results were selected to annotate the unigenes. Functional annotation by gene ontology terms (GO) was analyzed by Blast2Go software [82].

qRT-PCR validation of DEGs

The profiles of six genes with obvious expression differences between the PMeS and non-PMeS lines were validated using qRT-PCR. Gene-specific primers were designed using Primer3Plus software and the used primer sequences are listed in Table S4. The rice β-actin gene (Os03g0718100) was used as the internal reference gene. The qRT-PCR was performed using SYBR Green (Roche) in ABI 7300 real-time PCR system (Applied Biosystems). The relative gene expression levels were calculated with three technical replicates using the 2−ΔΔCt method [83].

Statistical analysis

Data were analyzed using SPSS Statistics 26.0 (IBM, Armonk, NY, USA) and MS Excel 2019 (Microsoft Corp., Redmond, WA, USA). Significant differences between the means of HN2026-4x and 9311-4x were determined using independent samples t-test.

Data availability

RNA-seq data of this study can be found at the National Center for Biotechnology Information with the BioProject accession No. PRJNA1198123 (https://www.ncbi.nlm.nih.gov/bioproject/PRJNA1198123).

Abbreviations

COG:

Cluster of orthologous groups of proteins

DEGs:

Differentially expressed genes

FC:

Fold change

FDA:

Fluorescein diacetate

FDR:

False discovery rate

FPKM:

Fragments per kilobase of transcript per million fragments mapped

GO:

Gene ontology

KEGG:

Kyoto encyclopedia of genes and genomes

NCBI:

National Center for Biotechnology Information

Nr:

Non-redundant protein sequence database

PMCs:

Pollen mother cells

PMeS:

Polyploid meiosis stability

qRT-PCR:

Quantitative real-time PCR

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Acknowledgements

This work was supported by the Major Science and Technology Project of Wuhan “Development and Application of Polyploid Rice”, and the National Natural Science Foundation of China (31571639, 31271690). We also thank International Science Editing (http://www.internationalscienceediting.com) for editing this manuscript (ISE 104581).

Funding

This work was supported by the Major Science and Technology Project of Wuhan “Development and Application of Polyploid Rice”, and the National Natural Science Foundation of China (31571639, 31271690).

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Authors and Affiliations

  1. State Key Laboratory of Biocatalysis and Enzyme Engineering, School of Life Sciences, Hubei University, Wuhan, 430062, Hubei, China

    Pincang Lv, Man Wang, Rongjie Qiu, Chang Yao, Meng Fang, Yuandong Xing, Xianhua Zhang, Yuchi He, Detian Cai & Zhaojian Song

  2. Wuhan Polyploid Biotechnology Co., Ltd., Hubei, 430345, Wuhan, China

    Detian Cai

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  1. Pincang Lv
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Contributions

Z.S. and D.C. conceived and designed the study. D.C. bred PMeS line HN2026-4x and autotetraploid 9311-4x. P.L., M.W., R.Q., C.Y., M.F., Y.X., X.Z. and Y.H. performed the experiments. P.L. and Z.S. analyzed the data and wrote the manuscript. Z.S. revised the manuscript. All authors read and approved the final manuscript.

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Correspondence to Zhaojian Song.

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Lv, P., Wang, M., Qiu, R. et al. Comparative transcriptome analysis reveals key genes associated with meiotic stability and high seed setting rate in tetraploid rice. BMC Plant Biol 25, 645 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12870-025-06672-x

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BMC Plant Biology

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