RGG_2025v16n1

Rice Genomics and Genetics 2025, Vol.16, No.1, 1-13 http://cropscipublisher.com/index.php/rgg 6 5.2 Dominant GMS gene Dominant GMS plants are a type of germplasm resource that is extremely rare in nature, with only a few regulatory genes having been cloned. As early as 2001, the Academy of Agricultural Sciences in Sanming City, Fujian Province, discovered a natural mutant plant exhibiting dominant nuclear sterility in rice. This mutant exhibited stable and complete sterility, good exsertion of stigmas, and unaffected female fertility, demonstrating significant application potential. However, the gene regulating Sanming Dominant Genic Male Sterility (SDGMS) had remained uncloned. Recently, Huazhong Agricultural University and Nanjing Agricultural University simultaneously reported on the cloning and functional studies of the same gene locus, designated SDGMS and OsRIP1, respectively. The gene encodes a typical ribosome-inactivating protein (RIP), which inhibits protein synthesis at the translational level. This inhibition results in a defense response in the anthers of the sterile plants during meiosis, triggering intense programmed cell death (PCD) in the tapetum, leading to male sterility (Li et al., 2023; Xu et al., 2023 ). This is the first cloned Dominant Genic Male Sterility (DGMS) gene in rice, providing new insights into the role of transposable elements in genome and phenotypic evolution. It also lays the foundation for further application of SDGMS germplasm resources. The utilization of DGMS genes promises to eliminate the need for emasculation in rice hybrid breeding and genetic research, thus significantly saving labor and resources on a large scale, and potentially giving rise to new breeding models. 5.3 EGMS genes EGMS includes PGMS, TGMS and HGMS. These systems are highly valuable for hybrid rice breeding due to their sensitivity to environmental conditions. The PGMS mutant NK58S, identified in 1973, has been pivotal in the development of two-line hybrids. Key loci such as PMS1 and PMS3 encode long noncoding RNAs (Ding et al., 2012), while the TGMS locus TMS5 encodes an RNase Z (Fan and Zhang, 2017). The mapping of TGMS genes, such as tms3(t) on chromosome 6, further underscores the genetic complexity and potential for marker-assisted selection (MAS) breeding (Song et al., 2020). Furthermore, the identification of miRNAs such as miR156, miR5488, and miR399 in PA64S P/TGMS rice highlights the complex regulatory networks involving GMS genes (Sun et al., 2021). The study previously reveals that tms5 carries a mutation in ribonuclease ZS1, the latest report demonstrate that TMS5 is a tRNA 2′,3′-cyclic phosphatase. The tms5 mutation leads to accumulation of 2’,3’-cyclic phosphate (cP)-ΔCCA-tRNAs (tRNAs without 3’ CCA ended with cP), which is exacerbated by high temperatures, and reduction in the abundance of mature tRNAs, particularly alanine tRNAs (tRNA-Alas) (Figure 3) (Yan et al., 2024). The HGMS lines were discovered more recently, and show fertility under high humidity and sterility under low humidity. Xue et al. (2018) demonstrate that deficiency of a triterpene pathway results in HGMS in rice, OsOSC12/OsPTS1 encodes a triterpene synthase, which affects the biosynthesis of C16 and C18 fatty acids in tryphine and regulates HGMS in rice. Another study reveals the molecular mechanism by which the rice HMS1 and HMS1I genes interact to regulate the synthesis of very-long-chain fatty acids and the formation of the oil layer in the pollen wall, thereby controlling HGMS (Chen et al., 2020). 5.4 Comparative analysis of gene function and regulation Comparing the function and regulation of CMS, GMS, and EGMS genes reveals distinct mechanisms and regulatory pathways. CMS genes often involve mitochondrial-nuclear interactions, with nuclear restorer genes (Rf) playing a crucial role in fertility restoration (Mishra and Bohra, 2018). In contrast, GMS genes are primarily nuclear and can be manipulated through genetic engineering techniques such as CRISPR/Cas9 (Song et al., 2020). EGMS genes, regulated by environmental factors, involve complex epigenetic controls and noncoding RNAs, which add another layer of regulation (Tang et al., 2016). The integration of high-throughput sequencing and molecular mapping techniques has significantly advanced our understanding of these regulatory networks,

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