The Genetic Basis of Brown Rice\'s Total Flavonoid Content is revealed by a Genome-wide Association Study

Hengel Casas^*
*Correspondence: Hengel Casas, Department of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China, Email:

Keywords

Mixed Linear Model (MLM) • Anthocyanins • SNPs

Introduction

Rice (O.sativa L.) is a staple food for over half of the world's population. It is classified into two major subspecies: Oryza sativa japonica and Oryza sativa indica. Brown rice, which is less processed than white rice, retains its bran layer and, consequently, its nutritional components. One of the important nutritional components in brown rice is flavonoids. Flavonoids are a diverse group of phytonutrients (plant chemicals) found in almost all fruits and vegetables, and they have been associated with a variety of health benefits, including anti-inflammatory and antioxidant effects. Understanding the genetic basis of flavonoid content in brown rice can lead to the development of rice varieties with enhanced health benefits. Genome-wide Association Studies (GWAS) have emerged as a powerful tool for uncovering the genetic architecture of complex traits. This study aims to reveal the genetic basis of total flavonoid content in brown rice through a GWAS [1].

Literature Review

Flavonoids are secondary metabolites that contribute to the color, flavor, and nutritional quality of rice. They are divided into several subclasses, including flavonols, flavones, flavanones, isoflavones, anthocyanins and proanthocyanidins. These compounds have been studied extensively for their health benefits, which include, flavonoids can neutralize free radicals, reducing oxidative stress and lowering the risk of chronic diseases such as cancer and cardiovascular disease. Anti-inflammatory effects inhibit enzymes and signaling pathways involved in inflammation. Flavonoids improve endothelial function and reduce the risk of atherosclerosis. Neuroprotective effects may protect against neurodegenerative diseases through their antioxidant and anti-inflammatory properties [2].

Discussion

A diverse panel of brown rice accessions, representing the genetic diversity of both indica and japonica subspecies, was used in this study. The total flavonoid content was measured using spectrophotometric methods. Samples were collected at the same growth stage to ensure uniformity. Genomic DNA was extracted from the leaf tissues of each accession. High-density genotyping was performed using Single Nucleotide Polymorphism (SNP) arrays. This provided a detailed genetic map necessary for GWAS. The GWAS was conducted using a Mixed Linear Model (MLM) to account for population structure and kinship. The SNP data were analyzed to identify loci associated with flavonoid content. Significant SNPs were identified based on a genome-wide significance threshold adjusted for multiple testing [3].

The total flavonoid content varied significantly among the rice accessions, indicating a broad genetic base for this trait. Both indica and japonica accessions exhibited high and low flavonoid content, suggesting the presence of favorable alleles in both subspecies. The GWAS identified several significant SNPs associated with flavonoid content. These SNPs were located on different chromosomes, indicating the polygenic nature of flavonoid biosynthesis in rice. The most significant loci were found on chromosomes 1, 6, and 11. Several candidate genes were located near the significant SNPs. These genes are involved in the flavonoid biosynthetic pathway and regulatory networks, including CHS (Chalcone Synthase) an enzyme that catalyzes the first step in the flavonoid biosynthesis pathway. F3H (Flavanone 3-Hydroxylase) converts flavanones to dihydroflavonols, a critical step in the production of various flavonoids. DFR (Dihydroflavonol 4-Reductase) involved in the synthesis of anthocyanins and proanthocyanidins. MYB transcription factors rregulate the expression of flavonoid biosynthetic genes. The identification of significant SNPs and candidate genes provides insights into the genetic basis of flavonoid content in brown rice. The polygenic nature of the trait suggests that multiple genes and pathways are involved in its regulation. The involvement of known flavonoid biosynthesis genes confirms the validity of the GWAS results [4,5].

The findings from this study can be utilized in rice breeding programs to develop varieties with enhanced flavonoid content. Marker Assisted Selection (MAS) can be employed to introgress favorable alleles into elite cultivars. This can lead to the development of rice varieties with improved nutritional and health benefits. Further research is needed to validate the candidate genes identified in this study. Functional characterization of these genes through gene editing technologies such as CRISPR/Cas9 can provide direct evidence of their roles in flavonoid biosynthesis. Additionally, exploring the interaction between genetic and environmental factors can enhance our understanding of flavonoid accumulation in rice [6].

Conclusion

This study revealed the genetic basis of total flavonoid content in brown rice through a genome-wide association study. Several significant SNPs and candidate genes involved in the flavonoid biosynthesis pathway were identified. These findings provide a foundation for improving the nutritional quality of rice through genetic enhancement. Future research should focus on functional validation of the candidate genes and the development of rice varieties with high flavonoid content to promote better health outcomes.

Acknowledgement

None.

Conflict of Interest

There are no conflicts of interest by author.

References

1. Verma, Vivek, Bhushan Vishal, Ajay Kohli and Prakash P. Kumar. "Systems-based rice improvement approaches for sustainable food and nutritional security." Plant Cell Rep (2021): 1-16.

Google Scholar, Crossref, Indexed at

2. Singh, Sagolshem Priyokumar, S. K. Mehta and Y. Tunginba Singh. "New insight into the pigmented rice of northeast India revealed high antioxidant and mineral compositions for better human health." Heliyon 8 (2022).

Google Scholar, Crossref, Indexed at

3. Akhter, Delara, Ran Qin, Ujjal Kumar Nath and Jamal Eshag, et al. "A rice gene, OsPL, encoding a MYB family transcription factor confers anthocyanin synthesis, heat stress response and hormonal signaling." Gene 699 (2019): 62-72.

Google Scholar, Crossref, Indexed at

4. Yang, Xinghai, Junrui Wang, Xiuzhong Xia and Zongqiong Zhang, et al. "OsTTG1, a WD40 repeat gene, regulates anthocyanin biosynthesis in rice." J Plant 107 (2021): 198-214.

Google Scholar, Crossref, Indexed at

5. Wang, Jing, Qianwen Deng, Yuhua Li and Yang Yu, et al. "Transcription factors Rc and OsVP 1 coordinately regulate preharvest sprouting tolerance in red pericarp rice." J Agric Food Chem 68 (2020): 14748-14757.

Google Scholar, Crossref, Indexed at

6. Tang, You, Xiaolei Liu, Jiabo Wang and Meng Li, et al. "GAPIT version 2: An enhanced integrated tool for genomic association and prediction." Plant Genom 9 (2016): plantgenome2015-11.

Google Scholar, Crossref, Indexed at