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Article

The Relationship between Cadmium-Related Gene Sequence Variations in Rice and Cadmium Accumulation

by
Weixing Li
1,
Feng Xu
2,
Tingting Cai
1,
Wanling Zhao
1,
Jianting Lin
1,
Jiayu Huang
1,
Liguo Wang
1,
Jianmin Bian
1,
Junru Fu
1,
Linjuan Ouyang
1,
Yicong Cai
1,
Haohua He
1,*,
Xiaotang Sun
1,* and
Changlan Zhu
1,*
1
Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Ministry of Education, Jiangxi Agricultural University, Nanchang 330045, China
2
National Maize Improvement Center, China Agricultural University, Beijing 100193, China
*
Authors to whom correspondence should be addressed.
Agronomy 2023, 13(3), 800; https://doi.org/10.3390/agronomy13030800
Submission received: 10 February 2023 / Revised: 4 March 2023 / Accepted: 8 March 2023 / Published: 9 March 2023
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Abstract

:
Cadmium (Cd) pollution and uptake into the grains of developing rice plants represent a major threat to human health. Studies of specific genes can offer new insights into the functional roles of particular genes, highlighting candidate alleles that can be leveraged as DNA markers. Accordingly, the identification of novel Cd-related traits and sequence variants can provide new molecular markers for Cd resistance in rice. In the present study, a genetic diversity analysis was carried out on 85 rice varieties exhibiting varied Cd accumulation, and 436 single polymorphic sites (SNP) corresponding to 43 haplotypes were detected across 12 Cd-associated genes (CAL1, OsCADT1, Oscd1, OsHMA4, OsHMA9, OsNRAMP1, OsNRAMP2, OsNRAMP5, OsHMA2, OsHSMA3, OsPCR1, and OsABCG43). By utilizing the information of the SNPs, 85 rice varieties was classified the into 2 clusters with different source categories and Cd contents. Among the variants, 45 sites in 5 genes were significantly associated with the Cd content in rice grains, of which 8 alleles in OsPCR1, CAL1, and Oscd1 were negatively correlated with Cd accumulation. The results of haplotype aggregation analysis for OsPCR1, Oscd1, and CAL1 showed that 85 rice varieties were divided into 5 clusters. Interestingly, most of the varieties in Cluster A belonged to tropical type, which contained the aggregation of three favorable alleles, whereas the temperate varieties constituted the majority of Cluster B lacking favorable alleles. This observation suggests that the allelic combination found in tropical rice varieties may hold promise for reducing Cd accumulation levels in rice grains. The Cd-associated alleles identified in the present study can not only be used to check the Cd tolerance of rice varieties, but also serve as functional molecular markers to differentiate the source of the rice varieties, which provides a better understanding of the relationship between the sequence variation in Cd-related genes and Cd accumulation in rice.

1. Introduction

Rice (Oryza sativa L.) is a staple food crop cultivated worldwide, and ensuring the safety and integrity of the rice supply is, thus, essential. Recently, the increases in the production of solid and gaseous waste, industrial wastewater discharge, acid rate, sewage irrigation, and soil acidification have all contributed to the contamination of agricultural land by toxic metals, with the concentration of cadmium (Cd) far exceeding the established safety threshold [1]. The subsequent Cd stress will adversely impact rice plant growth and development, causing plants to become shorter, exhibit leaf yellowing, and produce smaller yields [2]. Even more seriously, Cd pollution of soil tends to result in the bioaccumulation of Cd within rice grains, thus posing a major food safety risk for human health [3]. As early as 1968, the issue was reported in Japan, where an outbreak of painful disease was linked to the consumption of Cd-contaminated rice [4]. In recent years, this issue has grown even more pressing owing to inadequate quality control measures for cultivated land and a lack of safety awareness among farmers, resulting in Cd levels exceeding the established standards in agricultural settings [5]. The growing attention to Cd uptake in rice grains has led to increased research interest on the genes involved in the Cd accumulation process [6,7,8,9,10]. Several genes have been reported to be associated with this activity, including members of the natural resistance-associated macrophage protein (NRAMP) family, heavy metal ATPase (HMA) genes, and other transporters [7,8,10].
NRAMP proteins function as bivalent metal ion transporters capable of influencing the trafficking of Mn2+, Zn2+, Cu2+, Fe2+, Cd2+, Ni2+, Co2+, and Al3+ ions. Research indicates that the rice genome encodes seven OsNRAMP genes, of which OsNRAMP5 [10], OsNRAMP1 [11], and OsNRAMP2 [12] are documented to be associated with Cd accumulation. OsNRAMP1 not only transports various metal ions such as Mn2+, Ni2+, Cd2+, and Pb2+, but also participates in the uptake of Cd to cells. Therefore, the knockout of this gene reduces the levels of these ions, and the overexpression of OsNRAMP1 enhances Cd accumulation in leaf tissue [7,11,13]. Compared to OsNRAMP1, OsNRAMP5 has a more pronounced impact on rice yield and quality because OsNRAMP5 not only affects the absorption of heavy metal ions, but also affects their distribution in roots and leaves as well as their transport from roots to stems. Given that OsNRAMP5 is highly expressed in rice root and panicle tissues [6,10], osnramp5 mutants were found to show markedly reduced Cd2+ absorption in roots, thereby mitigating the accumulation of these Cd2+ ions in rice stems and grains [10,14,15].
Generally speaking, heavy metal ATPases (HMAs) are the most important proteins involved in the heavy metal accumulation process in plants [16]. In rice, HMA family proteins, including OsHMA2, OsHMA3, and OsHMA9, are transmembrane transporter proteins located on the vacuole membrane of roots that can facilitate Cd transport [6,17,18]. OsHMA2, in particular, serves as a key Cd and Zn transporter protein in the roots and shoots of rice plants, regulating xylem loading. When OsHMA2 is overexpressed, it can substantially decrease the transport and accumulation of Cd in rice grains [8,19]. The Cd transporter OsHMA3 is found on rice root vacuole membranes that transport Cd2+ into the vacuoles, thereby sequestering it and preventing its transport to the plant canopy, thus protecting against Cd toxicity [7,20]. Overexpressing OsHMA3 in Zhongjiazao 17, the most cultivated rice variety in Southern China, led to a 94 to 98% drop in Cd content in rice grains to such a degree that these levels were well below the established safety standards in China, without any significant impact of the essential trace element content on the plant agronomic traits [6]. OsHMA9 is a Cu/Ag subgroup HMA protein primarily expressed in mesophyll cells and anthers. OsHMA9 has long been thought to mainly facilitate the transport of Cu, Zn, and Pb from the cells outwards, but actually, it can also regulate Cd transport in the xylem, so OsHMA9-deficient mutant plants exhibit increased Cd accumulation [8,21].
Other relevant transporter genes in rice include LCD [22], OsLCT1 [23,24], OsABCG43 [25], OsPCR1 [9], OsCd1 [26], CAL1 [27], and OsCADT1 [6]. Among these genes, LCD has been linked to the ability of rice plants to tolerate Cd stress as well as Cd2+ transport and bioaccumulation, with its expression largely restricted to root vascular bundles and phloem-associated cells in the leaves [22]. OsLCT1 encodes a low-affinity cation transport protein that plays a critical role in regulating Cd transport through the phloem to rice grains [24]. The coexpression of OsLCT1, OsHMA2, and OsZIP can substantially reduce Cd transport and accumulation in the grains of developing rice plants [23]. The Cd-induced transporter gene OsABCG43 is highly expressed in root tissue exposed to Cd pollution with little expression changes in the aboveground tissues, which can augment plant Cd tolerance [25]. The Cd resistance gene OsPCR1 is mainly expressed in the roots of rice seedlings and the first and second internodes in the reproductive stage, with lower expression during the heading stage. Although Song et al. found that the Cd accumulation in ospcr1 mutants was significantly reduced, the length and weight of grains also decreased with different proportions, which is noteworthy in breeding applications [9]. OsCd1 belongs to the MFS superfamily of transporters, which can transport cadmium ions and participate in the uptake of Cd in roots. According to research results of Yan et al. [26], a missense mutation Val449Asp of OsCd1 is the main reason for the difference in cadmium (Cd) in the grains of indica and japonica rice, and indica rice varieties carrying the japonica allele OsCd1V449 could reduce Cd accumulation in grains. These genes play crucial roles in Cd uptake and transport in rice, providing insights into molecular mechanisms underlying Cd accumulation in rice and the development of low-Cd rice varieties.
While the specific genes associated with Cd accumulation have been linked to the levels of Cd in rice, few studies have applied these Cd-accumulation-related genes in the context of breeding. Therefore, it is urgent to fully clarify the role that these genes play and to explore allelic variations associated with Cd accumulation in rice grains, which will enable the more reliable use of appropriate molecular markers to accelerate the breeding of rice varieties with low Cd accumulation levels.
Linkage analysis techniques can be utilized to explore genome locations that most strongly influence target traits, but they cannot be leveraged to evaluate low-frequency phenotypes within natural populations. In contrast, linkage disequilibrium (LD)-based association analyses can clarify the association between groups of target traits and genetic markers [28,29]. These analyses include both studies focused on specific candidate gene sequences and genome-wide association studies (GWAS) [30], enabling the efficient screening of variant loci related to particular traits [18]. Natural populations can, thus, be used for research exploring the relationship between polymorphisms in candidate genes and target traits, thereby elucidating the links between specific functional loci and phenotypic outcomes. Thornsberry et al. [31], for example, performed an early association study in plants using a candidate gene approach wherein they focused on the relationship between polymorphic loci in the Dwarf8 gene and Zea mays flowering time phenotypes. Andersen et al. [32] subsequently carried out an association analysis using inbred lines to confirm the relationship between maize Dwarf8 polymorphisms and plant height as well as flowering time under four tested environmental conditions. Such association analyses can serve as an effective approach for gene mining and functional verification, providing novel opportunities for quantitative trait research.
In the present study, 85 natural rice varieties from different ecological settings exhibiting high levels of genetic diversity were utilized as experimental materials. Associations between single-nucleotide polymorphisms (SNPs) in 12 Cd-related candidate genes (CAL1, OsCADT1, Oscd1, OsHMA4, OsHMA9, OsNRAMP1, OsNRAMP2, OsNRAMP5, OsHMA2, OsHSMA3, OsPCR1, and OsABCG43) and the accumulation of Cd in rice grains were analyzed with a general linear model. The results of this study will provide new insight into the relationship between Cd-related gene variants and Cd bioaccumulation in rice.

2. Materials and Methods

2.1. Plant Materials and Growth Conditions

Natural populations corresponding to 85 different rice varieties (Table S1) were selected from the International Rice Research Institute based on plant height and growth period (1 October 2022, https://snpseek.irri.org/). The levels of Cd in rice grains from these different varieties were then analyzed. These 85 rice varieties were selected from across 23 countries and regions, covering a broad geographical range spanning from 53° N latitude to 35° S latitude, which included temperate, tropical, subtropical, and subfrigid regions. All rice materials were collected in compliance with local laws and there were no conflicts of interest. The collected rice seeds were soaked in warm water for 2 days and germinated for 2 days in a 30 °C incubator. Subsequently, 15-day-old seedlings were transplanted into paddy soil containing 5 mg/kg Cd at the end of June 2021. Three seedlings were added to each bucket (30 cm × 30 cm) filled with paddy soil, and three replicates were analyzed for each rice variety.

2.2. Measurement of Cd Concentrations in Rice Grains

Samples of brown rice were heated at 105 °C in an oven for 12 h and then heated at 70 °C until fully dehydrated. The samples were then weighed and digested in 10 mL of HNO3–HClO4 (4:1 v/v) at 160–180 °C, and levels of Cd therein were assessed with atomic absorption spectrophotometry (AAS, GBC3000).

2.3. Sequence Data Analysis

Nucleotide polymorphisms across the selected genes for all rice varieties were analyzed through a sliding window analysis using DnaSP (v5.10) [33]. The selection pressure at particular loci was assessed through statistical tests of neutrality, including levels of nucleotide diversity per site (Pi), Tajima’s D [34], Fu and Li’s D* and F*. Haplotype diversity was analyzed with Arlequin (v3.5) [35], and haplotype relationships were examined by constructing TCS haplotype network maps using PopART (v1.7) [36]. The 12 Cd-associated genes were subjected to phylogenetics analyses, and favorable haplotypes were determined through an aggregation analysis. SNPs with a minor allele frequency (MAF) ≥ 0.05 were extracted using plink (v1.90b4.4) [37], and a FASTA file was concatenated using SeqKit (v0.11.0) [38] before being employed for neighbor-joining (NJ) phylogenetic tree construction using FastTree (v2.1.0) [39] with default parameters. The resulting trees and associated heatmaps for all analyzed rice varieties were then visualized using ggtree (v2.0.4) [40] in R (v3.6.4).

2.4. Association Analysis

The relationships between Cd-associated candidate genes and Cd accumulation were analyzed using TASSEL (v5.0) [41]. To ensure the accuracy of the collected data, the phenotypic data were normalized, and the SNP data were filtered prior to association mapping. First, genotypic data were subjected to numerical transformation, and the SNPs exhibiting a minor allele frequency (MAF) less than 0.05 were excluded. LD structures were analyzed by assessing the D’ (standardized disequilibrium coefficient) and the R2 (squared allele–frequency correlation) was assessed, with 1000 permutations being applied [42]. Relationships between phenotypic values and SNPs with a MAF > 0.05 were assessed in TASSEL with GLMs.

2.5. Analysis of Allele Phenotypic Effects

The null allele method proposed by Breseghello and Sorrells was used to gauge the phenotypic effects of individual alleles based on the sites identified in the association analysis [43]. The phenotypic effects of allele variants were computed as follows:
ai = Σ Xij/ni − Σ Nk/nk
where ai denotes the phenotypic effect of allele variation I, Xij corresponds to the phenotype value of material j carrying allele variation I, Ni indicates the number of materials harboring allelic variation I, Nk is the phenotypic value of material k with invalid alleles, and nk denotes the number of materials exhibiting invalid alleles. A positive ai value suggests a synergistic effect between the variants, while a negative ai value indicates an antagonistic effect.

3. Results

3.1. Phenotypic Variations in Cd Levels in Rice Grains from Natural Population Variants

Plants with a seed-setting rate higher than 70% were retained for assessing Cd content, and the frequency distribution of Cd content in 85 varieties is presented in Figure 1. The Cd content of grains was found to be continuously distributed with the content ranging from a minimum of 0.2 mg/kg to a maximum of 11.95 mg/kg, including 17 varieties which showed extremely low (<0.5 mg/kg) and 9 which showed extremely high cd content (>4.0 mg/kg) (Table S2). It is worth noting that when the Cd content in grains exceeds 0.8 mg/kg, it will cause Cd poisoning to human beings which is extremely harmful [44]. In present study, 31 (36.4%) out of 85 varieties exhibited Cd levels below 0.8 mg/kg, indicating that they may be more harmlessly planted in naturally Cd-polluted environments (Figure 1). In addition, interestingly, when the 85 varieties were divided by their source in each Cd level bin, the result showed that a large number of tropical varieties showed lower Cd accumulations (<2.0 mg/kg), while those with a higher Cd level (>3.5 mg/kg) were usually temperate varieties (Figure 1). The finding suggests that the tropical varieties used in the present study may possess some favorable alleles that make them more Cd-tolerant, paving the way for the following analyses.

3.2. Sequence Polymorphism Analyses

In order to better explore the sequence pattern of tropical and temperate rice exhibiting different Cd accumulation, 12 Cd-associated genes were collected based on the literature data, i.e., CAL1, OsCADT1, Oscd1, OsHMA4, OsHMA9, OsNRAMP1, OsNRAMP2, OsNRAMP5, OsHMA2, OsHSMA3, OsPCR1, and OsABCG43. Full sequence information for the genes was downloaded from the International Rice Research Institute (1 October 2022, https://snpseek.irri.org/) and then employed for sequence polymorphism analyses using the methods described in Section 2.3. The result showed that 436 variant sites were identified, with the majority being found in noncoding regions (Table 1). Among the genes, OsHMA9 had the highest number of polymorphic sites with an average of 1 SNP per 60 bp, while CAL1 exhibited the lowest sequence polymorphism with an average of 1 SNP per 120 bp. In total, 103 polymorphic sites were detected in the coding regions of the genes, with the highest number of polymorphic sites (n = 25) in OsHMA9 and only one in Oscd1. As indicated in the result, many SNPs were also located on untranslated regions (UTR), including 34 in 5′-UTR and 62 in 3′-UTR. Given that some studies found that mutations in UTR were also important for the normal function of rice genes, these seemingly useless sites also deserve attention.

3.3. Cd-Associated Gene Sequence Diversity

To better understand the selection pressures that Cd-associated genes are undergoing, sequence and haplotype diversity analyses were carried out for the selected genes. As shown in Table 2, CAL1, OsHMA9, OsNRAMP1, and OsNRAMP5 were associated with a single segregation site, with OsHMA9 exhibiting the lowest nucleotide diversity (0.00002). OsHMA2 contains 51 segregation sites with a nucleotide diversity of 0.00448, which is the highest among all other genes (Table 2). The polymorphic sites analyzed in Cd-associated genes were used to construct 43 haplotypes (Figure 2), and the number of haplotypes in each gene ranged from 2 to 7, with the haplotype diversity values in gene sequence region ranging from 0.052 to 0.699 (Table 2). CAL1, OsHMA9, OsNRAMP1, OsNRAMP2, and OsNRAMP5 were associated with just two haplotypes, while OsHMA2 was associated with seven haplotypes. The maximum haplotype diversity value of 0.699 was observed for the OsABCG43 gene, while the lowest haplotype diversity value of 0.052 was observed for the OsNRAMP2 gene (Table 2).

3.4. Identification of Cd Accumulation Groups of Genotypes Based on 12 Candidate Genes

459 SNPs within the UTR, coding, and noncoding regions of the 12 target Cd-associated genes were utilized to construct an NJ phylogenetic tree (Figure 3a). This tree classified the 85 rice varieties into two groups designated cluster I and cluster II. These two clusters exhibited distinct regional associations, with the majority of the varieties in cluster I being tropical and those in cluster II being of temperate varieties. Notably, although 12 tropical varieties were categorized in cluster II, 7 were placed at one end of the cluster, suggesting a unique evolutionary pattern between the tropical and temperate varieties in cluster II. Moreover, the Cd content level of each revealed a different pattern: that cluster I showed a lower level than cluster II (Figure 3b), suggesting that the certain allelic combinations of these candidate genes or SNPs are linked to Cd accumulation. Interestingly, the finding is largely consistent with the results revealed in Figure 1, indicating that these 12 Cd-associated gene can also serve as molecular markers differentiating rice varieties that thrive in tropical and temperate environments.

3.5. Association Analysis of SNPs Related to Cd Accumulation in Rice Grains

Generally speaking, a small point mutation will also cause a great phenotypic change in crops. To determine the key SNPs related to Cd accumulation, a general linear model (GLM) in TASSEL 5.0 was used to conduct an association analysis concerning the causal correlation between the polymorphisms in 12 Cd-related genes and Cd accumulation in rice [41]. The results showed that 45 variant sites in 5 of these genes were either significantly or extremely significantly associated with the accumulation of Cd (Table 3). Although 14 SNPs were located in the coding regions, only 3 SNPs (at positions 824990, 825477, and 826066 in the OsPCR1 exon) led to nonsynonymous amino acid substitutions. Specifically, the SNPs were located on the first, third, and fourth exons of OsPRC1, respectively.
As for the contribution of SNPs located in the UTRs or noncoding regions related to Cd accumulation, one SNP at position 25190520 (C→G) in 5′-UTR of CAL1 was found to be significantly associated with Cd accumulation (p < 0.01), explaining 16.794% of the observed phenotypic variation. Similarly, two polymorphic sites in the OsCADT1 gene were significantly linked to the accumulation of Cd in rice grains, with SNPs located at 37964661 and 37965214 explaining 20.677% and 18.538% of the observed phenotypic variation, respectively. In Oscd1, 10 SNPs were identified to be significantly associated with Cd accumulation, explaining 7.601% to 10.277% of the observed phenotypic variation. Moreover, five SNPs in OsHMA2 were observed to significantly correlated with Cd accumulation, with individual SNPs explaining 8.9% to 14.561% of the phenotypic variation. An additional set of 27 moderate SNPs were identified in OsPCR1, which were estimated to account for a significant proportion (from 6.533% to 10.132%) of the Cd accumulation variation observed in rice grains.

3.6. Combination of Favorable Alleles

Based on the effects of particular alleles on the accumulation of Cd in the analyzed brown rice grains, variants with a high contribution to phenotypic variation were further classified as favorable or unfavorable. The phenotypic allele effects, usually used to assess the contribution of an allele to the phenotype, were estimated by comparing the average Cd accumulation for accessions harboring that allele to that in accessions harboring a “null allele”.
An aggregation analysis of haplotypes across the 5 Cd accumulation-related genes showed that only OsPCR1, Oscd1, and CAL1 harbored major and minor haplotypes, with over 10 haplotypes being identified. A haplotype cluster analysis of these 3 genes further stratified the 85 rice varieties into 5 distinct clusters (Figure 4). The varieties in cluster A carried the major haplotype for OsPCR1, Oscd1, and CAL1, while cluster B contained varieties harboring the minor haplotype. Notably, the lowest and highest levels of Cd accumulation were observed for varieties in cluster A and cluster B, respectively, suggesting that the major haplotype of OsPCR1, Oscd1, and CAL1 is desirable for the study trait (Figure 4). It is worth noting that cluster C, cluster D, and cluster E also showed reduced Cd accumulation compared to cluster B, indicating that a single beneficial haplotype can mitigate the impacts of Cd to some extent, although the effect is limited.
Meanwhile, as shown in Table 3, 38 SNPs in OsPCR1, Oscd1, and CAL1 were significantly related to Cd accumulation, in which eight favorable alleles (five for OsPCR1, two for CAL1, and one for Oscd1) were negatively correlated with Cd accumulation (Table 4). It can be inferred that low-Cd phenotypes were, thus, closely related to the favorable alleles, and the simultaneous aggregation of multiple favorable alleles can result in superior phenotypic outcomes for a certain trait of interest. Moreover, the result is consistent with the findings presented in Figure 2 and Figure 3 that cluster A and B predominantly consisted of tropical and temperate rice varieties, respectively, emphasizing the potential utility of these three genes as effective markers for the molecular breeding of rice varieties that accumulate low levels of Cd.

4. Discussion

In recent years, heavy metal pollution in land has brought great challenges to food safety. Among the heavy metal elements, cadmium (Cd) can not only adversely affect the growth and development of rice, but can also cause high blood pressure, liver disease, or brain damage in humans [45]. Thus, characterizing the genetic basis and identifying specific sequence variants involved in Cd accumulation can be leveraged as reliable markers to accelerate the breeding of new superior low-Cd rice varieties [46].
In the present study, nucleotide and haplotype diversity analyses were performed on 12 Cd-related genes among 85 rice varieties exhibiting varied Cd accumulation (Table 1). As expected, the selected genes showed distinct patterns of sequence variations, with a higher level being observed in OsHMA2 and OsPCR1 than CAL1, OsHMA9, OsNRAMP1, and OsNRAMP5 (Table 2), implying that the genes were differently selected in rice breeding. Tajima’s D statistic was then employed to assess the deviation from neutrality for the 12 genes, and the result showed a negative nucleotide diversity for OsCADT1, OsHMA4, OsHMA9, and OsNRAMP2, while other genes exhibited significant deviations from neutrality (Table 2), indicating the absence of population subdivision events or balancing selection during breeding or evolution. These findings were also confirmed by the result of Hao et al. [47].
Association analysis identified 45 alleles in the OsCADT1, CAL1, Oscd1, OsHMA2, and OsPCR1 genes that were strongly related to Cd accumulation (Table 3). Of these SNPs, 13 were in the exon coding regions of OsPCR1, Oscd1, and OsCADT1, whereas the rest were in the 3′-UTR, 5′-UTR, or intronic regions. It is worth noting that only three nonsynonymous mutations were found in OsPCR1 at positions 824990, 825477, and 826066 (Table 4), which resulted in the substitution of Pro, His, and Ala to Arg, Leu, and Ser, respectively. Specifically, the mutation at position 825477 in OsPCR1 entailed the substitution of a nonpolar hydrophobic amino acid (His) by a polar hydrophobic amino acid (Leu), whereas the opposite was observed in two sites. Moreover, Ser residue has been reported to possess a potential target for protein phosphorylation [48]; these nonsynonymous SNPs may, thus, contribute to a conformational change in the OsPCR1 protein and then change the function of the gene. As for other ten exonic SNPs identified in this study, these were synonymous and unrelated to changes in the amino acid sequence.
Of note, several detected SNPs associated with Cd accumulation were located within the 5′-UTR, including one SNP each in CAL1, OsPCR1, and OsHMA2 as well as two in Oscd1. It has been reported that SNPs in untranslated regions can also influence gene expression, such as a single-nucleotide substitution in the 5′-UTR of the bsr-d1 gene leading to a reduced expression of the gene through binding the repressive MYB transcription factor and, consequently, inhibiting the degradation of H2O2 and then enhancing rice broad-spectrum blast resistance [49]. Moreover, the 5′-UTR of OsCAL1 was intensively studied by Luo et al. [27]. In their findings, OsCAL1 was also divided into two genotypes: TN1 (the designed favorable allele in our study) and CJ06. Expression analysis showed that OsCAL1 was expressed in various tissues except leaf blades, and significantly higher expression was observed in node I and the adjoining flag leaf sheath when compared between NIL (TN1) and NIL (CJ06). In addition, compared with NIL (CJ06), higher Cd accumulation was detected in the leaves and xylem sap of NIL (TN1) seedlings. However, a significant difference was not observed for Cd in grains between NIL (TN1) and NIL (CJ06), indicating that the TN1 genotype would not appear to affect Cd accumulation in rice grains while accelerating long-distance Cd transport via the xylem vessels.
In this study, five SNPs associated with Cd accumulation in rice grains were identified in the 3′-UTR regions of OsPCR1, OsHMA2, and OsCADT1. While the cisregulatory elements present within UTR domains are generally conserved across plant families, different lengths of UTR can be of varied functional specificity [50]. Srivastava et al. [50] previously surveyed a diverse array of UTR-dependent regulatory mechanisms, by looking at genes which harboring multiple mRNA variants that differ in UTR length and are associated with nutrient homeostasis, stress responses, flowering regulation, and other key physiological processes. Their analysis ultimately determined that 3′-UTR binding proteins may control protein translation in plants through mechanisms similar to those reported in animals. However, studies focused on this topic are currently lacking, future research may be required to further elucidate the UTR-mediated regulation of gene expression and protein functionality in different plant species.
Several intronic SNPs were also detected to be significantly associated with Cd accumulation, including 28 intronic sites in OsPCR1, Oscd1, OsCADT1, and OsHMA2. While intronic sequences were historically overlooked as “junk” DNA, recent works have shown that these regions play key regulatory roles in plants and other eukaryotic species. For example, introns can provide additional cisacting elements that regulate gene expression and influence the efficiency of transcriptional activity [51,52,53]. In Arabidopsis, intronic sequences in the 5′-UTR regions of two E3 ligase genes have been shown to be essential for the expression of these genes [54]. Developing specific markers for these intronic variants may facilitate the identification of novel rice varieties with reduced Cd accumulation. However, the role of these intronic variable loci in regulating the function of Cd-related genes in rice requires further investigation.
Some studies have shown that the characteristics of the ABC transporter and the HMA gene family may contribute to the functional analysis of Cd-associated genes in crop species [55,56,57]. Guo et al. [58] found that the overexpression of OsNRAMP1 and OsNRAMP5 would facilitate the migration of Cd from root to shoot and increase the content of Cd in grains. Therefore, the identification of favorable alleles in these genes may significantly reduce the Cd content in rice. By analyzing the loci significantly related to Cd accumulation in rice grains, eight loci in OsPCR1, CAL1, and Oscd1 genes were found to be negatively associated with Cd accumulation to such a degree that they may offer value as biomarkers of low Cd levels. Therefore, these markers, together with progeny identification, can be leveraged for the marker-assisted breeding of novel rice varieties which are characterized by low levels of Cd accumulation together with other desirable agronomic traits, even in heavily polluted environments. Moreover, of the 85 rice varieties analyzed in this study, many tropical varieties were found to simultaneously harbor 3 favorable alleles, i.e., OsPCR1, CAL1, and Oscd1, whereas temperate varieties were the opposite (Figure 4). These results suggest that these three alleles may be advantageous for rice to resist Cd stress under high temperature, which may be a consequence of natural or minor artificial selection. Environmental factors such as light exposure and temperature can be big drivers for different rice varieties showing the similar phenotype in the same geographical context [59], while early human activities can conditionally aggregate desirable phenotypes simply by hybridization [60]. Furthermore, the 12 Cd-associated genes used in this study can group the 85 rice varieties into different clusters showing varied Cd content distribution, indicating that the 12 genes can not only be used to check the Cd tolerance of rice varieties, but also the molecular markers to differentiate the source of the rice varieties.
Natural rice is a rich source of genetic variations; however, the variations vary across different gene families. Unravelling the genetic potential residing within individual gene families may indicate their acquired function. The existence of high genetic variations among genes signifies the relationship between adaptive variations and functional significance, which has further been validated by candidate gene-based association analysis. Genetic interaction between genes negatively associated with Cd accumulation may be responsible for Cd tolerance among the studied rice set. The identified haplotypes may play a significant role in analyzing evolutionary studies of crop. Measuring phenotypic variation and exploiting sequence variations in the candidate gene may enhance our understanding towards a low accumulation of Cd and help to develop new rice cultivars with low Cd accumulation.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/agronomy13030800/s1; Table S1: Information of 85 rice germplasm resources, Table S2: Cadmium content in brown rice of 85 rice materials.

Author Contributions

W.L., X.S. and C.Z. designed the experiments; W.L. and F.X. analyzed the data; W.L. wrote the manuscript; W.L., T.C., W.Z., J.L., J.H. and L.W. performed all the phenotypic evaluations; J.B., J.F., L.O. and Y.C. participated in performing the experiments; X.S., H.H. and C.Z. conceived and supervised the experiments. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the Jiangxi Provincial Natural Science Foundation of China (20171ACB20011) and the National Natural Science Foundation of China (32160646).

Data Availability Statement

The SNPs used in this study are openly available in IRRI (https://snpseek.irri.org, accessed on 1 October 2022), and rice varieties are listed in Supplementary Materials.

Acknowledgments

We thank the referees for their critical comments on this manuscript.

Conflicts of Interest

The authors declare that this research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Agronomy 13 00800 g001 550
Figure 1. Frequency distribution of rice varieties binned with the different brown Cd concentrations.
Figure 1. Frequency distribution of rice varieties binned with the different brown Cd concentrations.
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Figure 2. Haplotype networks. (a) CAL1 (b) OsABCG43 (c) OsCADT1 (d) OsHMA9 (e) Oscd1 (f) OsHMA2 (g) OsHMA3 (h) OsNRAMP2 (i) OsNRAMP1 (j) OsNRAMP5 (k) OsHMA4 (l) OsPCR1. Circle sizes are proportional to haplotype frequency across all analyzed cultivars. Five rice types are represented with different colors. The little black circle is an inferred median. Bars or dashes represent mutational steps between haplotypes, including gaps in sequence alignment.
Figure 2. Haplotype networks. (a) CAL1 (b) OsABCG43 (c) OsCADT1 (d) OsHMA9 (e) Oscd1 (f) OsHMA2 (g) OsHMA3 (h) OsNRAMP2 (i) OsNRAMP1 (j) OsNRAMP5 (k) OsHMA4 (l) OsPCR1. Circle sizes are proportional to haplotype frequency across all analyzed cultivars. Five rice types are represented with different colors. The little black circle is an inferred median. Bars or dashes represent mutational steps between haplotypes, including gaps in sequence alignment.
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Figure 3. (a) NJ tree constructed based on 459 SNPs in 12 Cd-related genes. (b) Distribution of Cd content in Cluster I and Cluster II (t-test was used to test the significance p). Genes were concatenated based on their genomic position and aligned, and clustering analyses were performed based on SNPs. The admix, japx, indica, subtropical, and tropical varieties are, respectively, represented by red, mustard, maroon, blue, and purple lines (online color chart).
Figure 3. (a) NJ tree constructed based on 459 SNPs in 12 Cd-related genes. (b) Distribution of Cd content in Cluster I and Cluster II (t-test was used to test the significance p). Genes were concatenated based on their genomic position and aligned, and clustering analyses were performed based on SNPs. The admix, japx, indica, subtropical, and tropical varieties are, respectively, represented by red, mustard, maroon, blue, and purple lines (online color chart).
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Figure 4. Analysis of favorable haplotype combinations. (a) Allele combinations related to Cd accumulation in rice grains were separated into five clusters. Coloring indicates the major (green) and minor (blue) haplotypes for these Cd-accumulation-related genes. (b) Comparison of rice grain Cd accumulation among clusters. Letters A-E in the figure represent different clusters according to the haplotype combination.
Figure 4. Analysis of favorable haplotype combinations. (a) Allele combinations related to Cd accumulation in rice grains were separated into five clusters. Coloring indicates the major (green) and minor (blue) haplotypes for these Cd-accumulation-related genes. (b) Comparison of rice grain Cd accumulation among clusters. Letters A-E in the figure represent different clusters according to the haplotype combination.
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Table
Table 1. Polymorphisms in 12 Cd-related genes.
Table 1. Polymorphisms in 12 Cd-related genes.
GeneFull Length (bp)No. of VariationsNo. of SNP
Coding RegionNoncoding Region3′-UTR Region5′-UTR Region
CAL170262013
OsABCG4313,3913371970
OsCADT142061421020
Oscd138322211425
OsHMA27276606172512
OsHMA338091916300
OsHMA459042211731
OsHMA965051072568140
OsNRAMP148562251421
OsNRAMP24016103502
OsNRAMP572637345847
OsPCR1147548212223
Total 4361032376234
Table
Table 2. Nucleotide and haplotype diversity and neutrality testing for 12 Cd-associated genes from 85 natural rice varieties (with MAF > 0.05).
Table 2. Nucleotide and haplotype diversity and neutrality testing for 12 Cd-associated genes from 85 natural rice varieties (with MAF > 0.05).
GeneRegionNo. of Nucleotide SubstitutionsPiTajima’s DFu and Li’s D* StatisticFu and Li’s F* StatisticHaplotype Diversity
CAL1Coding000000
Noncoding10.000541.317080.502840.810860.41
All10.000541.317080.502840.810860.41
OsABCG43Coding70.000381.816351.205351.508730.683
Noncoding170.000982.639331.472121.918270.696
All240.001352.653361.703922.124960.699
OsCADT1Coding000000
Noncoding30.00009−0.432890.698530.4420.309
All30.00009−0.432890.698530.4420.309
Oscd1Coding10.000071.495540.502840.883970.447
Noncoding100.000663.067361.132981.804490.547
All110.000733.168551.205351.927970.562
OsHMA2Coding50.000471.377460.698530.920650.361
Noncoding460.004011.807951.050551.356280.361
All510.004481.851771.205351.539380.361
OsHMA3Coding70.000561.72270.698531.090120.539
Noncoding10.000080.7739010.504440.621690.315
All80.000631.772650.698531.090120.539
OsHMA4Coding20.00005−0.070850.698530.469490.327
Noncoding000000
All20.00005−0.070850.698530.469490.327
OsHMA9Coding00.000000000
Noncoding10.00002−0.440670.502840.221550.112
All10.00002−0.440670.502840.221550.112
OsNRAMP1Coding000000
Noncoding10.000070.9126550.502840.694550.351
All10.000070.9126550.502840.694550.351
OsNRAMP2Coding10.00001−0.686370.505260.14070.071
Noncoding20.00003−0.83140.704690.20030.074
All30.00004−1.011280.850970.167140.052
OsNRAMP5Coding000000
Noncoding10.000040.6032410.502840.550540.278
All10.000040.6032410.502840.550540.278
OsPCR1Coding130.000954.087690.840891.52730.469
Noncoding210.001444.191660.840891.162360.511
All340.002394.557071.132981.778740.511
Table
Table 3. The relationship between SNPs in selected Cd-associated genes and Cd accumulation in rice (at R2 > 5% and p < 0.05).
Table 3. The relationship between SNPs in selected Cd-associated genes and Cd accumulation in rice (at R2 > 5% and p < 0.05).
GenePosp-Value R2GenePosp-Value R2
OsCADT1379646610.0001340.20677OsPCR18253990.024270.08877
379652140.0002230.185388254770.013210.10132
CAL1251905200.0005330.167948255570.007820.08513
Oscd18426110.026630.084638255960.015270.09926
8427470.010650.076018257720.013650.1006
8434600.010650.076018257730.013950.10011
8441020.010240.078638259100.004890.0926
8441790.027970.084528259260.00920.07894
8442730.011730.102778259380.013490.07391
8442800.009710.078778259800.025280.0868
8443280.013630.099468259810.034450.08076
8443320.010650.076018259890.025280.0868
8455630.023150.087758259940.034450.08076
OsHMA2294779610.021890.0898260420.003750.09796
294787640.015170.099418260660.00920.07894
294787840.002090.144628260910.004530.09524
294806720.0005210.145618261000.007170.0859
294808480.002850.134728261030.007170.0859
OsPCR18249730.037130.08988261180.00920.07894
8249810.009380.08668261210.00920.07894
8249900.009190.081818261720.01530.07218
8249950.009190.081818262620.022120.06533
8251470.00920.07894
Table
Table 4. Estimates of the allelic effects of Cd-related genes on variations in Cd accumulation phenotypes.
Table 4. Estimates of the allelic effects of Cd-related genes on variations in Cd accumulation phenotypes.
GeneRegionPosition (bp)AlleleAllele Effect
OsPCR1Exon1824990G0.00
C−1.07
Exon3825477T0.00
A−1.16
Exon4826066C0.00
A−1.04
3′-UTR824981T0.00
G−0.63
5′-UTR826262A0.00
G−0.38
CAL15′-UTR25190520C0.00
G−1.67
Oscd15′-UTR842611A0.00
G−1.15
842747T0.00
C−0.83
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Li, W.; Xu, F.; Cai, T.; Zhao, W.; Lin, J.; Huang, J.; Wang, L.; Bian, J.; Fu, J.; Ouyang, L.; et al. The Relationship between Cadmium-Related Gene Sequence Variations in Rice and Cadmium Accumulation. Agronomy 2023, 13, 800. https://doi.org/10.3390/agronomy13030800

AMA Style

Li W, Xu F, Cai T, Zhao W, Lin J, Huang J, Wang L, Bian J, Fu J, Ouyang L, et al. The Relationship between Cadmium-Related Gene Sequence Variations in Rice and Cadmium Accumulation. Agronomy. 2023; 13(3):800. https://doi.org/10.3390/agronomy13030800

Chicago/Turabian Style

Li, Weixing, Feng Xu, Tingting Cai, Wanling Zhao, Jianting Lin, Jiayu Huang, Liguo Wang, Jianmin Bian, Junru Fu, Linjuan Ouyang, and et al. 2023. "The Relationship between Cadmium-Related Gene Sequence Variations in Rice and Cadmium Accumulation" Agronomy 13, no. 3: 800. https://doi.org/10.3390/agronomy13030800

APA Style

Li, W., Xu, F., Cai, T., Zhao, W., Lin, J., Huang, J., Wang, L., Bian, J., Fu, J., Ouyang, L., Cai, Y., He, H., Sun, X., & Zhu, C. (2023). The Relationship between Cadmium-Related Gene Sequence Variations in Rice and Cadmium Accumulation. Agronomy, 13(3), 800. https://doi.org/10.3390/agronomy13030800

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