Introduction
Soil salinity, ranking as one of the foremost abiotic stressors, exerts a profound impact on rice (Oryza sativa L.), leading to significant yield losses (Jiménez-Mejía et al., Reference Jiménez-Mejía, Medina-Estrada, Carballar-Hernández, Orozco-Mosqueda, Santoyo and Loeza-Lara2022). Addressing this challenge, breeding salt-tolerant rice varieties is the most direct and efficient strategy (Qin et al., Reference Qin, Li and Huang2020). Dongxiang wild rice (DXWR, Oryza rufipogon Griff.), renowned for its strong salt tolerance, holds immense potential as a valuable genetic resource for enhancing the salt tolerance of rice varieties, thereby mitigating the negative effects of soil salinity (Chen et al., Reference Chen, Yang, Gao, Chen, Zhou, Xie and Zhang2023).
Numerous studies have unequivocally demonstrated that microRNAs (miRNAs) play crucial roles in salt tolerance (Islam et al., Reference Islam, Waheed, Naveed and Zeng2022). In the previous study, our team discovered significant alterations in the expression profiles of 164 miRNAs in DXWR under salt-stress conditions, indicating that these differentially expressed miRNAs play crucial roles in the salt tolerance (Chen et al., Reference Chen, Yang, Gao, Chen, Zhou, Xie and Zhang2023). Simple sequence repeats (SSRs) stand out as elite molecular markers due to their remarkable polymorphism, reproducibility and co-dominant inheritance (Alekseeva et al., Reference Alekseeva, Rusanova, Rusanov and Atanassov2023). Due to recent advancements in high-throughput sequencing, the detection of SSRs within miRNAs and their flanking sequences has become feasible (Sharma et al., Reference Sharma, Mehta, Shefali, Muthusamy, Singh and Singh2021; Sihag et al., Reference Sihag, Sagwal, Kumar, Balyan, Mir, Dhankher and Kumar2021; Sabana et al., Reference Sabana, Antony, Rajesh, Gangaraj, Niral, Sudha and Jerard2022). Notably, the occurrence of SSRs in the miRNAs regions exhibits no preferential location, indicating their ubiquitous nature and significance as a crucial component of miRNAs and their flanking sequences (Patil et al., Reference Patil, Singh, Parashuram, Bohra, Mundewadikar, Sangnure, Babu and Sharma2020). Based on previous research, it is hypothesized that salt-tolerant rice varieties may exhibit distinct expression patterns of miRNAs, distinguishing them from non-tolerant varieties (Szymonik et al., Reference Szymonik, Klimek-Chodacka, Lukasiewicz, Macko-Podgórni, Grzebelus and Baranski2023). Consequently, the primary aim of this study is to develop a specific set of SSR markers derived from the salt-responsive miRNAs identified in DXWR, and to use these markers to confirm this hypothesis.
Experimental
A total of 38 accessions of rice germplasm, collected from 26 countries and areas, were utilized in this study (online Supplementary Table S1). The rice materials were collected in our laboratory. Salt treatment was performed using a published method (Chen et al., Reference Chen, Yang, Gao, Chen, Zhou, Xie and Zhang2023). SSR mining and primer design were performed according to the method described by Chen et al. (Reference Chen, Fan, Yang, Ding, Xie and Zhang2022). SSR Hunter software v.1.3 was used to identify SSR loci with a maximum motif length of 6 bp and a minimum of three repeats. The following parameters were set: (1) optimum primer length 18–25 bp; (2) GC content of 40–60%; (3) annealing temperature of 50–60°C (55°C optimum) and (4) expected amplicon size of 100–400 bp. Polymerase chain reaction (PCR) amplification was performed using a 2× Fast Taq Premix kit (Tolo Biotech Co., Ltd., China). PCR products were separated using a vertical 9% non-denaturing polyacrylamide gel electrophoresis system. The separated PCR fragments were visualized through silver staining, following the methodology outlined by Sanguinetti and Simpson (Reference Sanguinetti and Simpson1994). The genetic diversity parameters were analysed using Power Marker v.3.25.
Discussion
In the previous study, we observed significant changes in the expression patterns of 164 miRNAs in DXWR when exposed to salt-stress conditions (Chen et al., Reference Chen, Yang, Gao, Chen, Zhou, Xie and Zhang2023). Meanwhile, 144 corresponding pre-miRNA sequences were obtained for the 164 miRNAs, as some miRNAs shared the identical pre-miRNA sequences (Chen et al., Reference Chen, Yang, Gao, Chen, Zhou, Xie and Zhang2023). In this study, the 144 pre-miRNA sequences were aligned against the Nipponbare reference genome (http://rice.uga.edu/) to obtain flanking sequences. Then, the 144 sequences harbouring pre-miRNA sequences and the corresponding flanking sequences were used to identify SSR loci and develop SSR markers. SSR analysis revealed that dinucleotide (61.31%) and trinucleotide (30.66%) repeats were predominant (Table 1). TA (27.38%) and AT (23.81%) were the most frequent dinucleotide repeats (online Supplementary Table S2).
Table 1. Distribution and frequency of different miRNA-SSR motif types and repeat numbers
Totally, 137 miRNA-SSR markers were developed for each of the salt-responsive miRNAs (online Supplementary Table S2), whereas no suitable SSR markers can be designed for seven miRNAs (miR1860-p5, miR3638-p5_2ss17GT18CT, miR3982-3p_L + 1R-1, miR4995-p5_1ss18GC, miR6300_R + 6_2, miR812k-p5, PC-5p-75382_31). These developed miRNA-SSR markers were distributed on all 12 chromosomes. The highest number of markers was on chromosome 3 and the lowest on chromosome 5 (online Supplementary Fig. S1). Furthermore, we analysed the gene distribution in the pre-miRNAs and their flanking sequences, revealing many genes associated with stress tolerance (online Supplementary Table S3). For example, OsMADS57, located on the flanking region of miR444a_L-1R + 1_1ss17GA, is a transcription factor that enables plants to adapt to cold and salt environments (Wu et al., Reference Wu, Yu, Huang and Gan2021). OsTRE1, located on the flanking region of miR162b, affects the rice resistance to salt and drought stresses (Islam et al., Reference Islam, Kato, Shima, Tezuka, Matsui and Imai2019). Hence, these miRNA-SSR markers could play a pivotal role in identifying salt-tolerant genes. Additionally, the miRNAs and functional genes could be precisely targeted for genome editing, thereby enhancing the salt tolerance of rice varieties and enabling promising applications.
To assess the utility of these miRNA-SSR markers, we randomly selected 20 markers and then amplified their corresponding fragments using genomic DNA extracted from three DXWR populations and 35 modern rice varieties. Of these, 13 (65.0%) markers amplified stably with DXWR's genomic DNA, exceeding the success rates reported for coconut (30.0%) (Sabana et al., Reference Sabana, Antony, Rajesh, Gangaraj, Niral, Sudha and Jerard2022) and wheat (53.85%) (Tyagi et al., Reference Tyagi, Kumar, Gautam, Pandey, Rustgi and Mir2021) but falling short of Cleistogenes songorica (77.27%) (Kanzana et al., Reference Kanzana, Zhang, Ma, Liu, Wu, Yan, Min, Yan, Muvunyi, Li, Zhang, Zhao and Zhang2020) and pomegranate (92.15%) (Patil et al., Reference Patil, Singh, Parashuram, Bohra, Mundewadikar, Sangnure, Babu and Sharma2020). The lack of amplification could be attributed to the markers being designed based on the Nipponbare genome sequence. Then, to assess the suitability of miRNA-SSR markers for analysing cultivated rice, we amplified genome DNA fragments from 38 rice accessions using the 13 successfully amplified markers (Fig. 1). As a result, 13 markers exhibited abundant polymorphism, identifying a total of 52 SSR loci, averaging four alleles per locus. The average polymorphism information content value among these markers was 0.49 (online Supplementary Table S4). Notably, the marker miR162a-SSR is a promising diagnostic marker as it exhibits unique alleles and effectively distinguishes salt-tolerant rice varieties (survival rate ⩾ 80%) from susceptible ones (survival rate ⩽ 30%) among the 35 modern rice varieties used in this study (online Supplementary Fig. S2). Therefore, these salt-responsive miRNA-SSR markers can be efficiently employed to distinguish salt-tolerant rice varieties from salt-sensitive ones, thereby enhancing the exploration of salt tolerance genes and genetic improvement of rice cultivars.
Figure 1. Representative electropherograms for the successfully amplified markers: (a) miR167b-p3-SSR and (b) PC-3p-31535_128-SSR. M: DL 2000 marker.
Supplementary material
The supplementary material for this article can be found at https://doi.org/10.1017/S1479262124000297
Acknowledgements
This research was supported by the Major Science and Technology Project of Jiangxi Province, China (20232ACF01001), the National Natural Science Foundation of China (32070374), the Industrial Chain Science and Technology Innovation Consortium Project of Jiangxi Province, China (20224BBF62001) and the ‘Biological Breeding’ project of the State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China (SKL-KF202217).
