{"id":9109,"date":"2025-04-10T21:58:22","date_gmt":"2025-04-10T21:58:22","guid":{"rendered":"https:\/\/www.europesays.com\/uk\/9109\/"},"modified":"2025-04-10T21:58:22","modified_gmt":"2025-04-10T21:58:22","slug":"integrating-qtl-mapping-and-gwas-to-decipher-the-genetic-mechanisms-behind-the-calcium-contents-of-brassica-napus-shoots","status":"publish","type":"post","link":"https:\/\/www.europesays.com\/uk\/9109\/","title":{"rendered":"Integrating QTL mapping and GWAS to decipher the genetic mechanisms behind the calcium contents of Brassica napus shoots"},"content":{"rendered":"

Introduction<\/p>\n

Rapeseed (Brassica napus, AACC, 2n = 38) is the third-largest oil crop in the world (Hu et\u00a0al., 2021<\/a>). In recent years, to increase its economic value rapeseed cultivars have been developed as sources of flowers, feed, and vegetables (Shi et\u00a0al., 2023<\/a>). The production of oilseed-vegetable-dual-purpose (OVDP) varieties can meet the double demand of the market for edible oil and vegetables (Wu et\u00a0al., 2021<\/a>). Picking B. napus shoots can promote secondary branching and increase the total silique number (Huang et\u00a0al., 2014<\/a>). This does not result in a significant decrease in seed yield, thereby increasing the economic value (Zhu et\u00a0al., 2020<\/a>). B. napus shoots have a high edible value and are rich in nutrients such as vitamin C, calcium (Ca), selenium (Se), and zinc (Zn) (Fu et\u00a0al., 2022<\/a>). Brassica vegetables, such as kale and broccoli, contain high levels of vitamins, minerals, and other bioactive substances that have antibacterial, anti-inflammatory, and anti-cancer effects (Pods\u0119dek, 2007<\/a>; Mandrich and Caputo, 2020<\/a>; Cicio et\u00a0al., 2023<\/a>; Garcia-Iba\u00f1ez et\u00a0al., 2024<\/a>). B. napus belongs to the Brassicaceae family, consequently, its shoots have the potential to develop into functional vegetables. The yields and income changes resulting from growing OVDP varieties have been studied, but less attention has been paid to their nutritional qualities. At present, Se-rich B. napus varieties have been cultivated to enhance immunity (Huang et\u00a0al., 2022<\/a>), but no high-Ca B. napus OVDP varieties have been cultivated.<\/p>\n

As the most abundant mineral element in the human body, Ca participates in various metabolic activities and is essential for maintaining health (Enders et\u00a0al., 2020<\/a>). Deficiencies in Ca can cause disease, and humans mainly supplement daily Ca intake by consuming plant-based foods, which may not meet nutritional requirements. The development of high-Ca vegetables will help meet consumer\u2019s daily Ca needs, resulting in a population with a more balanced nutrition (Ma et\u00a0al., 2023<\/a>). Additionally, Ca is an essential plant nutrient element that plays a central role in growth, development, and responses to environmental stress. It is a structural component of cell walls and membranes, and a second messenger in cells (Thor, 2019<\/a>). Calcium in the soil is passively and actively absorbed by plant roots in the form of ions, which are transported upward to stems and leaves under the action of transpiration or Ca-ATPases, and the intracellular redistribution is completed by channel and transporter proteins (White et\u00a0al., 2002<\/a>; DalCorso et\u00a0al., 2014<\/a>; Torres et\u00a0al., 2024<\/a>). Thus, there are many factors affecting the accumulation of Ca in B. napus during its sprout stage, and studies have mainly focused on increasing Ca concentration through different external conditions. However, a single external factor has limited influence on Ca concentration (CaC) (Yuan et\u00a0al., 2018<\/a>).<\/p>\n

The CaC of a plant is a complex quantitative trait controlled by multiple genes and easily affected by environmental conditions (Jaiswal et\u00a0al., 2019<\/a>). Quantitative trait locus (QTL) mapping has been widely applied to dissect the genetic bases of mineral elements in crops (Ma et\u00a0al., 2017<\/a>; Wang et\u00a0al., 2017<\/a>). Genome-wide association studies (GWASs) are another useful method to study complex quantitative traits, and have the advantage of detecting the genetic structure of traits without the need for population construction (Saini et\u00a0al., 2021<\/a>). These studies have been widely used to identify candidate genes for quantitative vegetable traits, such as in soybean and pepper (Haile et\u00a0al., 2023<\/a>; Jo et\u00a0al., 2023<\/a>). In B. napus, GWASs have been used to investigate seed yield (Liu et\u00a0al., 2022<\/a>), seed oil content (Zhao et\u00a0al., 2022<\/a>), silique length (Wang et\u00a0al., 2021<\/a>), and seed fatty acids (Gazave et\u00a0al., 2020<\/a>). Additionally, GWAS have been used to dissect the accumulation of minerals in other crops, such as pearl millet (Singh et\u00a0al., 2024<\/a>). Integrating GWASs and QTL mapping provides an effective method to understand the genetic structures of quantitative traits. The combination has been widely applied to genetic analyses of maize yield (Wang et\u00a0al., 2023<\/a>), soluble solid content in melon (Yan et\u00a0al., 2023<\/a>), and cadmium accumulation in maize leaves (Zhao et\u00a0al., 2018<\/a>). In B. napus, two traits, soluble solid content (Wu et\u00a0al., 2021<\/a>) and crude fiber, have been studied using QTL mapping and GWAS combined (Shi et\u00a0al., 2023<\/a>, Shi et\u00a0al., 2024<\/a>).<\/p>\n

In this study, QTL mapping and GWAS were performed to obtain loci controlling CaC in B. napus shoots using phenotypic data in multiple environments. This study aimed to increase the understanding of genetic mechanisms related to CaC in B. napus shoots at the stem elongation stage and to provide excellent germplasm resources for breeding high-Ca OVDP varieties.<\/p>\n

Materials and methodsExperimental materials<\/p>\n

In the present study, a recombinant inbred line (RIL) population, containing 189 lines and named the AH population (Wang et\u00a0al., 2015<\/a>), and an association panel consisted of 202 diverse accessions, named the CF population (Shi et\u00a0al., 2024<\/a>), were used for QTL mapping and GWAS of the loci associated with CaC. All the materials were planted in Nanjing City, Jiangsu Province, and Guiyang City, Guizhou Province, China. The AH population was planted in Guiyang for two consecutive years (2020\u20132021) and Nanjing for three straight years (2020\u20132022), and the CF population was planted in Nanjing and Guiyang for three straight years (2020\u20132022). The two populations were planted in October, and the shoots were harvested in the following March. According to planting location and harvesting time, experimental materials are denoted as 21NJ, 22NJ, 23NJ, 21GY, 22GY, and 23GY. All of the experimental materials were used in a completely randomized block design. The single experimental plot consisted of two rows, with 20 plants per row and 40 cm between the rows. Field management practices adhered to local agricultural production standards (Sun et\u00a0al., 2018<\/a>). According to the national agricultural industry standard \u2018Grades and specification of flowering Chinese cabbage\u2019, three plants of nonflowering and uniform growth from B. napus shoots were harvested at the stem elongation stage. They were approximately 20 cm in length and of uniform thickness (Shi et\u00a0al., 2024<\/a>).<\/p>\n

Calcium element detection<\/p>\n

The B. napus shoots were treated in an electric thermostatic air-drying oven (DGG-9240A, Senxin, Shanghai, China), dried at 105\u00b0C for 15 min, followed by drying at 80\u00b0C to constant weights. The dried samples were crushed in a grinder, passed through a 60-mesh screen, and maintained at low temperatures (Nerdy, 2018<\/a>).<\/p>\n

In accordance with the method of Saleem et\u00a0al (Saleem et\u00a0al., 2021<\/a>), the determination of mineral elements were as follows: 0.25 g of sample was accurately weighed and placed into a digestion tube. Then, 8 mL of concentrated nitric acid and 2 mL perchloric acid were added, the tubes were sealed, and the samples were mixed. They were left standing for 24 h. A variable temperature digestion process of 100 \u00b0C for 1 h, 130 \u00b0C for 3 h, and finally 180 \u00b0C for 2.5 h was carried out, and samples were then allowed to naturally cool to room temperature. Each reaction sample solution was poured into a 25 mL test tube, washed with a small constant volume of nitric acid solution (1%) four times, then constant volume to 25ml. Finally, the solution to be tested was obtained by filtration.<\/p>\n

Atomic absorption spectroscopy (AA-7000, Shimadzu Corporation, Kyoto, Japan) was used to measure the total CaC in samples. A standard curve was constructed using a mixed standard product. After diluting the solution to be measured by 20 times, the calcium concentration in the sample solution was detected. The calculation formula was as follows:<\/p>\n

CaC\u00a0(mg\/g)=[(C\u00d720\u00d7V)\/m]\u00d710\u22126<\/p>\n

where m represents the weighed sample, V represents the constant volume, and C represents the Ca concentration of the sample.<\/p>\n

QTL mapping<\/p>\n

A high-density linkage map was constructed for the AH population, and it contained 11,458 single nucleotide polymorphisms (SNPs) and 57 simple sequence repeat markers, covering a genome length of 2,027.53 cM, with an average distance of 0.72 cM between markers (Wang et\u00a0al., 2015<\/a>). The QTL analysis of CaC in B. napus shoots was performed using the composite interval mapping method of Windows QTL Cartographer 2.5 software (Wang et\u00a0al., 2015<\/a>). The LOD threshold was determined by 1,000 permutation tests (P \u2264 0.05) for each trait, and QTLs with LOD values greater than the threshold were considered as putative QTLs. The QTLs were named following the description of Wang et\u00a0al. (Wang et\u00a0al., 2015<\/a>). The name begins with the letter \u2018q\u2019, followed by the character, environment, and chromosomal number. Serial numbers were added to distinguish whether multiple significant QTLs were detected on the same chromosome in the same environment, such as qCaC.21NJ.A1-1.<\/p>\n

GWAS analysis<\/p>\n

A DNA library of the CF population was constructed and sequenced, with a sequencing depth of ~20\u00d7. A total of 6,093,649 SNPs and 996,252 InDels were detected in the whole genome of the GWAS population, with 2,719,348 and 3,352,074 SNPs in the A and C subgenomes, respectively (Shi et\u00a0al., 2024<\/a>). The mixed linear model in the TASSEL5.1 software (trait analysis by association, evolution and linkage) was used for the GWAS analysis (Bradbury et\u00a0al., 2007<\/a>), and two correction modes, kinship and population stratification, were added. The significance threshold was determined using the Genetic Type I error calculator, and 1,454,769 highly-effective sites were obtained (Yang et\u00a0al., 2011<\/a>; Li et\u00a0al., 2012<\/a>; Zhou and Stephens, 2012<\/a>). The average linkage disequilibrium decay distance for the whole genome was 90.3 kb when r2 = 0.2; when r2 was decreased to half of the maximum value (r2 = 0.345), the decay distance was 4 kb (Shi et\u00a0al., 2024<\/a>). The Manhattan and QQ plots were constructed using the qqman package in R software (Turner, 2018<\/a>; Wu et\u00a0al., 2021<\/a>).<\/p>\n

Candidate gene prediction<\/p>\n

In AH population, based on the resequencing results, all the variation sites between parents were identified (Yu et\u00a0al., 2021<\/a>). Then, using the SNP probe sequence on the genetic map, the markers on both sides of the QTL interval were mapped to the \u2018Darmor-bzh\u2019 reference genome using Blast (E-value \u2264 1e-10) software (Chalhoub et\u00a0al., 2014<\/a>). Then, SNPs and InDels within the QTL interval, and SNPs causing non-synonymous mutations and InDels causing frameshift mutations, were identified. Finally, for SNPs with non-synonymous mutations and InDels with frameshift mutations, candidate genes related to the accumulation of calcium were screened based on Arabidopsis gene function annotations.<\/p>\n

In addition, in CF population, by analyzing the gene and protein sequences of the \u2018ZS11\u2019 reference genome within the linkage disequilibrium (90.3 kb) range, the gene coding sequences of significant sites were extracted. Blast2GO (v3.3) was used for the enrichment analysis of all the genes, and the whole genome sequence was used as a reference. Then, functional annotation information on candidate genes was obtained, and candidate genes related to CaC were screened based on the functional gene annotations (Yang et\u00a0al., 2024<\/a>).<\/p>\n

ResultsStatistical analysis of phenotypic data<\/p>\n

In this study, the CaC of the parents and the AH population lines in five environments (Table\u00a01<\/a>; Figure\u00a01<\/a>), and the CF population lines in six environments (Table\u00a02<\/a>; Figure\u00a02<\/a>), were analyzed. The CaC in the AH and CF population lines were normally distributed, indicating that CaC was a quantitative trait controlled by multiple genes.<\/p>\n

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Table\u00a01<\/b>. Analysis of Ca concentration in the AH population.<\/p>\n

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Figure\u00a01<\/b>. Frequency distributions of five environmental phenotypes in the AH recombinant inbred lines (RIL) population. Blue dots represent the calcium concentration of the male parent \u2018Holly\u2019 in five environments; Yellow dots represent the calcium concentration of the female parent \u2018APL01\u2019 in five environments.<\/p>\n

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Table\u00a02<\/b>. Analysis of Ca concentration in the CF population.<\/p>\n

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Figure\u00a02<\/b>. Frequency distributions of six environmental phenotypes in the CF population.<\/p>\n

In the AH population, CaC values of the male parent \u2018Holly\u2019 and female parent \u2018APL01\u2019 exhibited significant differences across individual environments, indicating that synergistic alleles were distributed in both parents (Table\u00a01<\/a>). There were significant differences in CaC among different lines. In the 21NJ environment, the minimum CaC value in the AH population was 7.52 mg\/g, and the maximum CaC value was 37.31 mg\/g (Table\u00a01<\/a>). In the 23NJ environment, the CaC in CF population ranged from 0.67 to 18.15 mg\/g (Table\u00a02<\/a>).<\/p>\n

The coefficients of variation among AH lines ranged from 14.5% to 46.5%, with an average of 26.16%, whereas the coefficients of variation among CF population lines ranged from 15.93% to 57%, with an average of 33.89%. This suggested that the phenotypic traits of the two populations changed significantly in different years and areas.<\/p>\n

QTL mapping of the AH population<\/p>\n

The QTL mapping of CaC in the AH population was performed using the phenotypic data from five different environments. A total of 12 QTLs were detected, which were located on A1, A3, A5, A7, A9, and C7 (Table\u00a03<\/a>). Among the 12 QTLs, the phenotypic variance (PV) values explained by a single QTL ranged from 1.67% to 10.10%, and the additive effect ranged from \u22121.12 to 0.80. Four QTLs related to CaC were identified in the 21GY environment, of which three QTLs were located on chromosome A1 and the other QTL on chromosome C7. In the 22NJ environment, only one QTL was identified on chromosome A9. QTL qCaC\/22GY-A5-1 located on chromosome A5, with a PV value of 10.10%, was considered the major QTL conducive to improving CaC traits of B. napus shoots. However, no QTL was repeatedly detected in multiple environments, indicating that the environment significantly affected the CaC.<\/p>\n

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Table\u00a03<\/b>. The single QTL of Ca concentration in the AH population was detected in five environments.<\/p>\n

GWAS of the CF population<\/p>\n

A GWAS of CF the population in six environments identified SNPs having -log10 (P) \u2265 5.16 as significant sites. A total of 282 significant SNPs were detected, and they were distributed on all of the chromosomes except A10 (Supplementary Figure S1<\/a>). A total of 112 candidate association intervals were obtained by integrating these SNPs (Supplementary Table S1<\/a>). Among them, 46 and 56 SNPs were distributed on A5 and C5 chromosomes, respectively, accounting for 16.3% and 19.9% of the total SNPs, respectively, but only two SNP sites were detected on both chromosomes A4 and A6. In addition, the number of SNPs significantly related to CaC in the six environments was quite different. There were only 13 SNPs detected in 22NJ, whereas 136 SNPs were identified in 21NJ.<\/p>\n

Among the 112 candidate association intervals, 11 essential intervals were used for screening candidate genes (Table\u00a04<\/a>). In particular, the 43,898,035\u201344,350,778 (bp) interval on the A5 chromosome containing 38 SNPs and the 56,323,644\u201357,454,448 (bp) interval on C5 chromosome containing 44 SNPs, were used because it was speculated that they contained genes essential for the regulation of CaC. In addition, in the 23NJ and 21NJ environments, overlapping regions were found between 25,973,806 and 26,210,661 (bp) on chromosome A7.<\/p>\n

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Table\u00a04<\/b>. Screening candidate association intervals with a large number of SNPs through integration.<\/p>\n

Co-localization combining the QTL and GWAS<\/p>\n

The combined results of the QTL mapping and GWAS revealed that no duplicate sites were detected by the two methods. Chromosome A5 contained a major QTL, and the GWAS detected more SNP sites than on other chromosomes. Therefore, the A5 chromosome may be closely related to the CaC in B. napus shoots.<\/p>\n

Candidate gene prediction<\/p>\n

Based on the multiple sites involved in the absorption and transport of intracellular Ca detected by the QTL mapping and GWAS, combined with the genome model of B. napus, 10 major candidate genes were functionally annotated (Table\u00a05<\/a>). Based on the functional annotation of Arabidopsis homologs, there were four candidate genes related to CaC in the experimental environment 21NJ, which were mainly screened on chromosomes A5 and C5 (Figure\u00a03<\/a>).<\/p>\n

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Table\u00a05<\/b>. Candidate genes related to Ca concentration in B. napus shoots.<\/p>\n

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Figure\u00a03<\/b>. Genome-wide association study of the Ca concentration in the CF population. Identified candidate genes related to Ca concentration in the experimental environment 21NJ.<\/p>\n

Among these 10 candidate genes, BnaA05G0489600ZS and BnaC05G0546400ZS homologous express the expansionA13 protein, which affects the formation of plant lateral roots (Wang et\u00a0al., 2024<\/a>). The candidate gene BnaA09g18100D uniformly expresses the H+-ATPase 1 protein (Yamauchi et\u00a0al., 2016<\/a>), which can regulate stomatal opening and affect plant transpiration. These proteins indirectly affect the absorption and transport of Ca by regulating other positions. The remaining five genes affected the redistribution of Ca2+ between cells by regulating the expression of vectors and channel proteins. BnaC07g46260D and BnaC07g46310D encode mitochondrial unidirectional cotransporter, a calcium ion transporter located on the mitochondrial membrane (Duan et\u00a0al., 2024<\/a>). BnaC07g46660D is homogeneously expressed with Ca ATPase 2, which is located in the organelle membrane system and is a transporter involved in Ca2+ regulation in plant cells (Rahmati Ishka et\u00a0al., 2021<\/a>). The homologous expression proteins of candidate gene BnaC05G0553600ZS belongs to the Ca lipid-binding family of proteins, which can bind Ca2+ and phospholipids involved in cell-membrane transport (Cui et\u00a0al., 2023<\/a>). BnaC04G0560400ZS encodes a homologous cationic 1 (CAX1) protein, which is highly correlated with Ca2+ ion accumulation. CAX1 shows a higher Ca2+ ion response in rapeseed (Navarro-Le\u00f3n et\u00a0al., 2019<\/a>; Han et\u00a0al., 2022<\/a>). In addition, when the cell is under stress, CaC increases. BnaC03G0237200ZS and BnaA03G0493300ZS express the proteins of calmodulin 5 and calmodulin B-like 3, respectively, which bind to Ca2+ to signal and reduce ion concentrations in the cytoplasm (Ok et\u00a0al., 2015<\/a>).<\/p>\n

Discussion<\/p>\n

The Ca, Se, and zinc contents in B. napus shoots are higher than in traditional vegetables (Fahey et\u00a0al., 2001<\/a>). Single pick-shoots have no significant effect on yield and can increase the grower\u2019s economic benefits. As a green vegetable, the edible parts of B. napus are mainly the young stems and leaves at the stem elongation stage. The soluble solid contents and crude fiber levels of the AH and CF populations have been studied previously (Wu et\u00a0al., 2021<\/a>; Shi et\u00a0al., 2023<\/a>, Shi et\u00a0al., 2024<\/a>). Despite the limited understanding of the genetic mechanisms regulating CaC in B. napus, a combinatorial approach integrating QTL mapping and GWAS analysis has been employed to dissect the molecular basis of CaC at the genetic level.<\/p>\n

Phenotypic evaluation of group calcium content<\/p>\n

Phenotypic data indicated that the average CaC of AH and CF population in the diverse environments were 7.41 and 6.17 mg\/g, respectively, and ranged from 0.05 to 37.61 mg\/g and 0.67 to 19.71mg\/g, respectively (Table\u00a01<\/a>; Table\u00a02<\/a>). The mean values of CaC in different varieties of cabbage, cauliflower, and Chinese cabbage are 2.38, 1.89, and 3.30 mg\/g, respectively, with ranges from 1.72 to 3.32 mg\/g, 1.56 to 2.57 mg\/g, and 2.83 to 3.89 mg\/g, respectively (Yue et\u00a0al., 2024<\/a>). The dry matter minerals of beans, leafy vegetables, and grains have been determined, and leafy vegetables have the highest CaC. The average value for new cocoyam leaves is 6.5 mg\/g, ranging from 6.05 to 6.82 mg\/g, and the average value of Cassava leaves is 2.64 mg\/g, ranging from 1.78 to 3.91mg\/g (Castro-Alba et\u00a0al., 2019<\/a>). There lines in both the AH and CF populations that had much higher CaC than common vegetables. Therefore, there is an excellent potential to develop high-Ca OVDP varieties. In addition, there are high-quality germplasm resources in the two populations that can be used to cultivate new vegetables with higher CaC.<\/p>\n

Comprehensive analysis of group calcium content<\/p>\n

At present, studies on Ca in vegetables mainly focus on comparing the CaC among different kinds of vegetables (Nerdy, 2018<\/a>), the effect of Ca fertilizer on plant growth (Yuan et\u00a0al., 2018<\/a>), and Ca signaling between plant cells (Li et\u00a0al., 2024<\/a>). Few studies have been conducted to understand the influence of the CaC-related genes in crops by integrating QTL mapping and a GWAS, and only a few crops, such as wheat, pea, and tomato (Capel et\u00a0al., 2017<\/a>; Hussain et\u00a0al., 2017<\/a>; Ma et\u00a0al., 2017<\/a>), have been studied. In the present study, 12 QTLs were detected in the AH population, with PVs ranging from 1.67% to 10.10%, and one QTL located on chromosome A5 explained more than 10% of the total PV (Table\u00a03<\/a>). All of the 12 QTLs were environment-specific QTLs detected in a single environment. In addition, 282 significant SNPs were detected in the CF population, and 112 candidate association regions were obtained by integration (Supplementary Table S1<\/a>). No duplicate sites were found in the two populations in different environments. The calcium content in B. napus is primarily derived from soil uptake, which involves the coordinated activity of multiple transmembrane transporters (e.g., CAX family). Given the substantial effects of environmental variables (e.g., soil pH, temperature, and nutrient availability) on both gene expression and ion bioavailability, the observed phenotypic variation in CaC across experimental environments reflects complex genotype-by-environment interactions (DalCorso et\u00a0al., 2014<\/a>; Wu et\u00a0al., 2021<\/a>). Here, utilizing a combined analysis to investigate the genetic mechanisms of CaC in B. napus shoots led to the identification of superior resources from genomics and also provided a new strategy for improving the quality of other vegetables.<\/p>\n

Functional prediction of candidate genes<\/p>\n

Candidate genes for controlling mineral elements have been mined in other crops, but limited CaC-regulating genes have been identified in cruciferous vegetables. Based on the Ca transport process Ca in plant cells and the functional annotations of candidate genes, this research explored the candidate genes that control CaC. Finally, 10 CaC-related candidate genes were screened, and the homologous proteins encoded by these genes regulated CaC by affecting the Ca uptake rate, upward transport process, and inter-tissue Ca2+ allocation in rapeseed. The candidate genes BnaA05G0489600ZS and BnaC05G0546400ZS were homologous to expansionA13, which encodes a protein that loosens cell walls. Overexpression of this protein in Arabidopsis increases the number of lateral roots formed (Lee and Kim, 2013<\/a>), a well-developed root structure can improve the Ca absorption rate of rapeseed. According to the functional annotation, BnaA09g18100D encodes the H+-ATPase 1 protein that regulates stomatal opening, which controls the bottom-up transport of Ca in rapeseed by influencing plant transpiration (Yamauchi et\u00a0al., 2016<\/a>). In addition, Ca mainly exists in the form of ions and enters plant cells through carrier and channel proteins. Among the 10 candidate genes, 5 genes were annotated as carrier proteins, which were related to the CAX1, Ca lipid-binding, mitochondrial unidirectional cotransporter, and Ca ATPase 2 proteins. Homologous proteins of two candidate genes are involved in the regulation of Ca2+ concentration in the cytoplasm. In other crops, such as Arabidopsis, cotton, and tomato, these proteins transport Ca2+ into cellular tissues under response conditions, binding with proteins, pectin, phosphate, and other components. BnaC04G0560400ZS is a vital candidate gene, and its encoded protein, CAX1, can transport Ca2+ ions to vacuoles for storage and accumulation (Han et\u00a0al., 2022<\/a>). In carrots, this protein improves Ca bioavailability and promotes growth (Morris et\u00a0al., 2006<\/a>), but there are limited studies in vegetables. Therefore, this protein will provide a basis for research on breeding high-Ca B. napus varieties. The functions of these candidate genes need to be further verified. Still, this research helped increase the understanding of the genetic mechanisms behind the CaC in B. napus and provides a reference for breeding high-quality vegetable rapeseed varieties.<\/p>\n

Data availability statement<\/p>\n

The original contributions presented in the study are included in the article\/Supplementary Material<\/a>. Further inquiries can be directed to the corresponding author\/s.<\/p>\n

Author contributions<\/p>\n

YX: Writing \u2013 original draft, Formal Analysis, Investigation. FC: Writing \u2013 original draft, Formal Analysis, Resources. RS: Conceptualization, Data curation, Resources, Writing \u2013 original draft. TY: Formal Analysis, Software, Writing \u2013 original draft. WZ: Data curation, Formal Analysis, Writing \u2013 original draft. XZ: Data curation, Software, Writing \u2013 original draft. CW: Software, Writing \u2013 original draft. CS: Software, Writing \u2013 original draft. SF: Resources, Visualization, Writing \u2013 original draft. XW: Funding acquisition, Project administration, Writing \u2013 review & editing. JZ: Writing \u2013 review & editing, Project administration, Supervision, Validation. SY: Writing \u2013 review & editing, Project administration, Validation, Supervision.<\/p>\n

Funding<\/p>\n

The author(s) declare that financial support was received for the research and\/or publication of this article. This work was supported by the National Natural Science Foundation of China (32172065), Jiangsu Province Key Research and Development Program (BE2023342) and China Agriculture Research System of MOF and MARA (CARS-12).<\/p>\n

Conflict of interest<\/p>\n

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.<\/p>\n

Generative AI statement<\/p>\n

The author(s) declare that no Generative AI was used in the creation of this manuscript.<\/p>\n

Publisher\u2019s note<\/p>\n

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.<\/p>\n

Supplementary material<\/p>\n

The Supplementary Material for this article can be found online at: https:\/\/www.frontiersin.org\/articles\/10.3389\/fpls.2025.1565329\/full#supplementary-material<\/a><\/p>\n

Supplementary Table\u00a01 |<\/b> Integration of all the relevant SNP\u2019s Ca concentrations from B. napus shoots in six distinct environments.<\/p>\n

Supplementary Figure\u00a01 |<\/b> Genome-wide association study of the Ca concentration of the CF population. (A)<\/b> Manhattan map (left) and QQ map (right) of the CF population planted in the Guiyang area in 2021; (B)<\/b> Manhattan map (left) and QQ map (right) of the CF population planted in the Nanjing area in 2021; (C)<\/b> anhattan map (left) and QQ map (right) of the CF population planted in the Guiyang area in 2022; (D)<\/b> Manhattan map (left) and QQ map (right) of the CF population planted in the Nanjing area in 2022; (E)<\/b> Manhattan map (left) and QQ map (right) of the CF population planted in the Guiyang area in 2023; (F)<\/b> Manhattan map (left) and QQ map (right) of the CF population planted in the Nanjing area in 2023.<\/p>\n

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