Genome-Scale Profiling and High-Throughput Analyses Unravel the Genetic Basis of Arsenic Content Variation in Rice

Sang-Beom Lee; Gyeong-Jin Kim; Jung-Du Shin; Woojin Chung; Soo-Kwon Park; Geun-Hyoung Choi; Sang-Won Park; Yong-Jin Park

doi:10.3389/fpls.2022.905842

Genome-Scale Profiling and High-Throughput Analyses Unravel the Genetic Basis of Arsenic Content Variation in Rice

Front Plant Sci. 2022 Jul 18:13:905842. doi: 10.3389/fpls.2022.905842. eCollection 2022.

Authors

Sang-Beom Lee¹, Gyeong-Jin Kim², Jung-Du Shin³, Woojin Chung⁴, Soo-Kwon Park¹, Geun-Hyoung Choi², Sang-Won Park⁵, Yong-Jin Park⁶

Affiliations

¹ Crop Foundation Research Division, National Institute of Crop Science, Wanju, South Korea.
² Residual Agrochemical Assessment Division, National Institute of Agriculture Science, Wanju, South Korea.
³ Bio-Technology of Multidisciplinary Sciences Co., Wanju, South Korea.
⁴ Department of Environmental Energy Engineering, Kyonggi University, Suwon, South Korea.
⁵ Reserch Policy Bureau, Rural Development Administration, Wanju, South Korea.
⁶ Department of Plant Resources, College of Industrial Sciences, Kongju National University, Yesan, South Korea.

Abstract

Ionomics, the study of the composition of mineral nutrients and trace elements in organisms that represent the inorganic component of cells and tissues, has been widely studied to explore to unravel the molecular mechanism regulating the elemental composition of plants. However, the genetic factors of rice subspecies in the interaction between arsenic and functional ions have not yet been explained. Here, the correlation between As and eight essential ions in a rice core collection was analyzed, taking into account growing condition and genetic factors. The results demonstrated that the correlation between As and essential ions was affected by genetic factors and growing condition, but it was confirmed that the genetic factor was slightly larger with the heritability for arsenic content at 53%. In particular, the cluster coefficient of japonica (0.428) was larger than that of indica (0.414) in the co-expression network analysis for 23 arsenic genes, and it was confirmed that the distance between genes involved in As induction and detoxification of japonica was far than that of indica. These findings provide evidence that japonica populations could accumulate more As than indica populations. In addition, the cis-eQTLs of AIR2 (arsenic-induced RING finger protein) were isolated through transcriptome-wide association studies, and it was confirmed that AIR2 expression levels of indica were lower than those of japonica. This was consistent with the functional haplotype results for the genome sequence of AIR2, and finally, eight rice varieties with low AIR2 expression and arsenic content were selected. In addition, As-related QTLs were identified on chromosomes 5 and 6 under flooded and intermittently flooded conditions through genome-scale profiling. Taken together, these results might assist in developing markers and breeding plans to reduce toxic element content and breeding high-quality rice varieties in future.

Keywords: arsenic; co-expression network; eQTLs; ionomics; transcriptome-wide association studies.