Plant culture and treatment
Seeds of indica rice (cv. Yangdao 6, namely 9311), provided by the Jiangsu Lixiahe Agricultural Research Institute, were subjected to ethyl methanesulfonate (EMS) mutagenesis. Approximately 450 g seeds were immersed in distilled water for 12 h, and then incubated in 1% EMS for 12 h. After the EMS treatment, the seeds were washed in distilled water. The low Cd accumulation mutant (namely lcd1) in rice grains was identified according to the grain Cd concentration of 35,689 M2 plants determined by inductively coupled plasma-mass spectrometry (ICP-MS; X Series 2, Thermo Fisher Corp., Waltham, MA, USA), and was further self-pollinated to obtain M5 generation of lcd1. The mapping population was generated from the cross between the M5 generation of lcd1 and WT and was grown in Yoshida’s nutrient solution containing 0.1 μM Cd . The F2 individuals with extremely high and low Cd accumulation in rice leaves were isolated at seedling stage and used as the mapping population for the MutMap method.
Field experiments were conducted during rice growing season from 2016 to 2017. Seeds of lcd1 and WT were sterilized in 10% NaClO for 20 min and washed with deionized water. Then seeds were germinated on moist filter paper at 37 °C and sown in sterilized moist quartz sand. Uniform 25-day-old seedlings were subsequently respectively transplanted into the Cd-contaminated experimental paddy field in Hangzhou (Field A, 1.5 mg kg− 1 of total Cd, pH 5.4), Quzhou (Field B, 2.6 mg kg− 1 of total Cd, pH 5.8), Yiyang (Field C, 4.5 mg kg− 1 of total Cd, pH 4.8) and Xiangtan (Field D, 0.35 mg kg− 1 of total Cd, pH 5.2). Rice plants grown in different experimental paddy fields were uniformly managed and harvested at tillering, heading, filling and maturity stages, respectively. All samples were oven dried to constant weight at 70 °C for mineral element concentration analysis.
Hydroponics experiments were also conducted to investigate the effects of Cd stress on growth and Cd accumulation of lcd1 and WT rice seedlings. Sterilized rice seeds were germinated on moist filter paper at 37 °C and grown on a plastic mesh floating on half-strength Yoshida’s nutrient solution. Uniform 15-day-old seedlings were transferred into fresh nutrient solutions for different Cd concentration treatments (0 and 5 μM). Each treatment was conducted in five replicated runs. After different times (0, 3, 6, 12 h and 14 days) of Cd treatment, rice plants were carefully washed with deionized water and separated into roots and shoots, immediately frozen in liquid nitrogen and then stored at − 80 °C until use.
Kinetic analyses of cd uptake in roots
The Cd uptake in roots was determined according to Uraguchi et al.  with some modifications. Uniform 15-day-old seedlings of lcd1 and WT were transferred to the uptake solution containing 0.5 mM CaCl2 and 2 mM MES (pH 5.6) for 24 h, and then carried out at room temperature for the uptake experiments.
For the dose-dependent Cd uptake experiment, rice seedlings were transferred to 1-L plastic container with the uptake solution containing different concentrations of CdCl2 (0, 0.1, 0.25, 0.5, 1, 5, 10, 15, 30 and 50 μM). Each treatment was replicated three times. After 1 h of uptake, plants were carefully washed with deionized water and separated into roots and shoots, oven dried and digested with HNO3 for Cd concentration analysis. Values of Km and Vmax for each genotype were calculated using software (GraphPadPRISM4; GraphPad Software Inc., CA, USA).
For the time-course Cd uptake experiment, rice seedlings were transferred to 1-L plastic container with the uptake solution containing 5 μM CdCl2 for different time treatments (0, 5, 10, 30, 60, 90, 120 and 180 min). Each treatment was replicated three times. The concentration of Cd in roots was determined as described below.
Determination of metal elements concentrations
The metal elements (Cd, Fe, Mn, Zn and Cu) concentrations were determined by ICP-MS according to Cao et al. . Briefly, dried rice root, shoot and grain samples (0.25 g) were digested in concentrated HNO3, and diluted to 50 mL by deionized water for metal elements determination.
DNAs for MutMap analysis were extracted from rice leaves with DNeasy Plant Mini Kit (Qiagen, Hilden, Germany). Two parents and two bulked DNA pools were used for MutMap analysis. The bulked DNA were prepared by mixing DNA equally from 31 F2 individuals with extremely high and low Cd accumulation in rice leaves respectively. DNA quality and concentration were checked using the NanoPhotometer® spectrophotometer (IMPLEN, CA, USA) and Qubit® DNA Assay Kit in Qubit® 2.0 Flurometer (Life Technologies, CA, USA). Sequencing libraries were generated using Truseq Nano DNA HT Sample preparation Kit (Illumina, USA) and were sequenced by Illumina HiSeq4000 platform (Illumina, CA, USA).
The raw data (WT parent: SRR8695240, lcd1 parent: SRR8695241, extremely high Cd accumulation pool: SRR8695238, extremely low Cd accumulation pool: SRR8695239) were filtered by phred quality score to remove adapter sequences and low-quality bases. The clean reads were aligned to the 9311 reference genome (ftp://ftp.ensemblgenomes.org/pub/plants/release-36/fasta/oryza_indica/dna/) using BWA software. Alignment files were converted to BAM files through SAMtools software and applied to GATK to identify reliable SNPs. The SNP-index of two pools were calculated using sliding window methods and the difference between the SNP-index of two pools was calculated as ΔSNP-index.
Total RNAs for RNA-Seq analysis were extracted from rice roots of lcd1 and WT under Cd exposure with RNeasy Plant kit (Qiagen, Hilden, Germany). RNA quality and concentration were determined by NanoPhotometer® spectrophotometer (IMPLEN, CA, USA) and Qubit® RNA Assay Kit in Qubit® 2.0 Flurometer (Life Technologies, CA, USA). Sequencing libraries were generated using NEBNext® Ultra™ RNA Library Prep Kit for Illumina® (NEB, USA) and were sequenced on an Illumina Hiseq platform (Illumina, CA, USA).
The raw sequences for WT (SRR8718745, SRR8718748 and SRR8718749, three biological replicates) and lcd1 (SRR8718744, SRR8718746 and SRR8718747, three biological replicates) libraries were filtered using phred quality score to remove adapter sequences and low-quality bases. In high-quality reads, the sequences were trimmed and mapped to the 9311 reference genome using Hisat2. The best match was used to annotate genes and assign gene ontology information. FPKM values (fragments per kilobase of exon model per million mapped reads) were calculated to estimate gene expression levels. False positive and false negative errors were corrected by calculating the FDR (false discovery rate) adjusted q-values. The DEGs (differentially expressed genes) between lcd1 and WT under Cd exposure were selected based on normalized read count, and fold change (lcd1/WT) ≥ 1.5 and q-value < 0.05 were used as threshold values by using the DESeq R package (1.18.0). Gene ontology (GO) enrichment analysis of DEGs between lcd1 and WT under Cd exposure was performed using the GOseq R-package with q-value < 0.05.
Quantitative real-time RT-PCR
The tissue specificity of the candidate gene and its temporal expression under Cd exposure were examined by quantitative real time RT-PCR (qPCR). The mixture of first-strand cDNA from 1 μg of total RNA served as the templates for qPCR analysis using ReverTra Ace® qPCR RT Master Mix (Toyobo, Japan). The primers used for qPCR were designed by Primer Premier 5.0 (Premier, Palo Alto, California, USA) as listed in Additional file 1: Table S1. The qPCR reactions were run on a QuantStudio® 3 (Applied Biosystems, Thermo Fisher Scientific, Waltham, MA, USA), with a total reaction volume of 25 μL containing 2 μL of diluted cDNA template, 12.5 μL of SYBR Green Realtime PCR Master Mix, 1 μL of 10 μM forward and reverse primer, and 8.5 μL of nuclease-free water. The following reaction conditions were applied: incubation at 95 °C for 60 s, 40 cycles of denaturation at 95 °C for 15 s, annealing at 55 °C for 15 s and extension at 72 °C for 45 s, followed by the dissociation stage for melt curve analysis (from 60 to 94 °C). All of the samples were run with three replicates, and three no-template controls (NTC) were included in every run to monitor possible DNA contamination. ACTIN-1 was used as a control to calculate the relative gene expression levels.
To optimize qPCR conditions for each primer pair, PCR amplification specificity and efficiency were examined according to the MIQE guidelines . The specificity of the PCR amplification was checked with a melt curve analysis. The result showed that the amplified product yielded a single peak at the melting temperature (Tm) for each gene, indicating that primer pairs for qPCR are highly specific. The PCR amplification efficiency was assessed using 5-fold serial dilution calibration-curve. The slopes of calibration curves range from − 3.53 to − 3.48, with corresponding R2 and efficiencies of 0.988–0.997 and 92.1–93.9%, respectively (Additional file 2: Table S2). conforming that the PCR amplification efficiency for each primer pair meets the MIQE recommended range (90.0–105.0%). The samples were normalized using ACTIN-1 expression and the relative gene expression levels were analyzed using the 2(−ΔΔCT) method due to that the amplification efficiencies of the target and reference were similar (Additional file 2: Table S2).
Data were expressed as mean ± standard error of at least three biological replicates for each sample. Statistical analyses were performed using the statistical software graphpad prism (Graphpad Software, San Diego, CA, USA). Statistical significance was assessed using Duncan’s multiple comparison at P < 0.05 level.