Rice Genomics and Genetics 2024, Vol.15, No.4, 153-163 http://cropscipublisher.com/index.php/rgg 157 OsDREB1C, which enhances photosynthetic capacity, nitrogen utilization, and flowering time, leading to significant yield increases. Similarly, the expression profiling of yield-related genes under various developmental stages and abiotic stress conditions has provided insights into the genetic reprogramming involved in yield traits (Tripathi et al., 2012). These studies highlight the importance of RNA-Seq in understanding the molecular mechanisms underlying yield improvement. Quantitative real-time PCR (qRT-PCR) is often used to validate the expression levels of key yield-related genes identified through RNA-Seq. For example, the expression of selected yield-related genes was analyzed by qRT-PCR under abiotic stress conditions, revealing tight transcriptional regulation and stress-responsive expression patterns (Tripathi et al., 2012). This method has also been employed to confirm the overexpression of specific genes, such as OsmiR397, which increases grain size and promotes panicle branching, thereby enhancing overall grain yield (Wang and Ortigosa, 2013). 3.2 Functional genomics approaches Mutant analysis has been instrumental in elucidating the functions of yield-related genes. Various mutants have been studied to characterize genes involved in yield traits, such as tiller number, grain number, grain size, and plant height (Sakamoto and Matsuoka, 2008). The identification and functional characterization of these mutants have provided valuable insights into the genetic basis of yield traits and have facilitated the compilation of a list of genes available for breeding high-yielding rice varieties (Ikeda et al., 2013). Overexpression and knockdown studies are powerful tools for functional genomics. Overexpression of specific genes, such as OsDREB1C, has been shown to significantly increase grain yield (Figure 2) and improve nitrogen use efficiency (Wei et al., 2022). Similarly, the overexpression of microRNA OsmiR397 has been reported to enhance grain size and panicle branching, leading to a 25% increase in grain yield (Wang and Ortigosa, 2013). Knockdown studies, on the other hand, help in understanding the loss-of-function effects of yield-related genes, providing a comprehensive view of their roles in yield enhancement. Wei et al. (2022) found that overexpression of the OsDREB1Cgene significantly increased yield in transgenic rice. Key genes upregulated under nitrogen deprivation conditions were identified through RNA seq and qRT PCR analysis. The field experiment results showed that compared with the wild type, transgenic plants increased in yield, number of grains per spike, straw weight, and harvest index (Figure 2). These findings provide new strategies for improving crop yields through genetic engineering, which can help address the challenges of global food security. The functional characterization of yield-related genes through gene expression studies and functional genomics approaches has significantly advanced our understanding of the molecular mechanisms underlying yield traits in rice. These insights are crucial for developing molecular breeding strategies aimed at enhancing rice yield. 4 Integrating Yield-Related Genes into Breeding Programs 4.1 Pyramiding multiple yield genes Pyramiding multiple yield-related genes involves combining several beneficial alleles into a single genotype to enhance rice yield. This strategy leverages the cumulative effects of multiple quantitative trait loci (QTLs) to achieve superior performance. Marker-assisted selection (MAS) is a common approach used to facilitate the pyramiding process by identifying and selecting desirable alleles at each generation (Guo and Ye, 2014). However, challenges include the complexity of interactions between different QTLs, the need for precise phenotyping, and the potential for negative epistasis where the combined effect of multiple genes is less than their individual effects (Zong et al., 2012; Huang et al., 2016). Several successful examples of gene pyramiding in rice breeding have been documented. For instance, the pyramiding of eight grain yield-related QTLs resulted in new rice lines with increased panicle and spikelet size, demonstrating the effectiveness of this approach (Zong et al., 2012). Another study highlighted the pyramiding of high-yielding npt1 and dep1-1 alleles, which significantly increased rice yield potential (Wang et al., 2017).
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