Supporting Information Figs S1–S5, Table S1 and Methods S1
Table S1 List of the primers for RT-PCR analysis of the genes
Unigene
gnl|UG|Les#S50865824
gnl|UG|Les#S5295427
gnl|UG|Les#S50870002
PLA08N18C
TVR05N17C
gnl|UG|Les#S50875591
PLA07L14C
gnl|UG|Les#S50868330
YFR02I11A
MLF03E07A
X67238
TVR18P14C
Unigene
gnl|UG|Les#S50865824
gnl|UG|Les#S5295427
gnl|UG|Les#S50870002
PLA08N18C
TVR05N17C
gnl|UG|Les#S50875591
PLA07L14C
gnl|UG|Les#S50868330
X67238
609267
X55749
Semi-quantitative RT-PCR primers
CGCCTGCTCCCTCCAAAACCAG
CCTCACCCACCCCTGGTGTCA
ATCAGTAGTAGAAGATTGTGGA
TGATGATGGGAATGAACATG
TGAAGAACAAGAAGCTTT
TCTCCCCATGCATTCTTCAT
ACAATGGACGCTAACAAGCTTG
CTTCTCCTCCTCCTCCTTCTCC
GTATGGAATCTCTTCTCAGGAT
GCAACAACTCCAAGAAAATCA
GTTTTGGGCGTGGGGCAGGG
TTTCCAGCGCCACCAGCACC
AGGGTCTCGCAAAAATGCGGT
TGCAGCGGCAATGATGCACT
TGGTGCTGATCAAGAAATGGGTGC
CCTGGAGAATGCAACCACCAAGTCCC
TCAAGTGTCCCATATCAT
GATGCTTGGAGAGCTCT
TGATGCACATGACCTTYT
ATCAAGCACAGGCACAWG
TTCTGTCGGCGATGCGCTCC
GCCTCAAACTTCCGCGGCCT
TCCTCCGTCTCCGTGGTGGT
AGGGTGCGGCCATCCTCAAG
RT-qPCR primers
CGCCTGCTCCCTCCAAAACCA
CGAAGGCCTTGGCCACGCT
TGGCTATTGACTCTATAGCTACTAG
TGATGATGGGAATGAACATG
CAAAATCCTAAGCTCAAG
TATTGTCTCCAACAAGGCATA
ACAATGGACGCTAACAAGCTTG
CTTCTCCTCCTCCTCCTTCTCC
TATGGTGGAGATGGTACTACTG
GCAACAACTCCAAGAAAATCA
GCCGCTCTTGACTGCTGTGCT
CCAGCGCCACCAGCACCAAT
AGGGTCTCGCAAAAATGCGGT
TGCAGCGGCAATGATGCACT
TGGTGCTGATCAAGAAATGGGTGC
CCTGGAGAATGCAACCACCAAGTCCC
CCTAGGTGTGCACCGGTCGTCTT
CCGATCCCGAAGGCCAACGTA
CAGATCTTCCGTCCTGATAACTT
TTACGAACAACATCGAGAAC
GGTGATGGTGTCAGCCACAC
GU594243
DQ228344
X64562
TVR18P14C
ATCAGTGAGGTCACGACCTG
GGTAAGCAGCTCGAGGATGGTCG
CGGCAGTTGACAGCACGAGG
TCCCACCGTCGGAGGCAGAG
TTCTCAAGAACAATCCCCTTGGC
GGTCATGCCAGTACAGTCCGTCG
GTCAGCCTTGGCTGCAGTAGCA
TCCTCCGTCTCCGTGGTGGT
CCAGGGTGCGGCCATCCTC
Table S2 List of differentially expressed genes.
Please see the EXCEL file ‘Table S2’.
Sequencing Quality Evaluation
Distribution of Clean Tag Copy Number
Fig. S1 Sequencing quality evaluation and the distribution of tag expression.
"Only adaptors" indicates that the reads contained only the adaptor sequence; "Copy Number < 2" indicates the tags that had a copy number of
less than 2; "Clean tags" indicates the tags that were used for the analysis after filtering the dirty tags. AckR, control for S. nigrum roots; BckR,
control for S. torvum roots; AtrR, Cd-treated S. nigrum roots; BtrR, Cd-treated S. torvum roots.
Fig. S2 Gene expression stability and pairwise variation of the candidate reference
genes.
Fig. S3 Summary of the experimental process of DGE analysis.
Fig. S4 Procedure for tag preparation.
Oligo (dT) beads were used to enrich the mRNA from the total RNA, and the mRNA was
reverse transcribed into double-stranded cDNA. The four-base recognition enzyme NlaIII
was used to digest the cDNA, and the Illumina adaptor 1 was ligated. MmeI was used to
digest the DNA 17 bp downstream of the CATG site, and the Illumina adaptor 2 was ligated
at the 3' end. The primers GX1 and GX2 were used for PCR. The 95 bp fragments were
recovered through 6% TBE PAGE. The DNA was purified prior to Illumina sequencing.
Fig. S5 Bioinformatics analysis procedure for DGE profiling data.
Methods S1 Supplemental Materials and Methods
Digital Transcriptomics
Four-week-old S. nigrum and S. torvum plants were treated with 50 µM CdCl2 for 24 h. The
RNA was extracted from the roots of the control and the two treated Solanum species using
TRIzol (Gibco/BRL, Life Technologies). The RNA quality and integrity were checked
before the cDNA was synthesized using the Bio-Rad Experion RNA StdSens analysis kit
(Bio-Rad, Hercules, CA, USA). Six micrograms of total RNA were extracted (eight
biological replicates for each treatment), Oligo (dT) magnetic bead adsorption was used to
purify the mRNA, and Oligo (dT) was used as a primer to synthesize the first and second
strand cDNA. The 5' ends of tags can be generated using two types of endonucleases, NlaIII
or DpnII. The bead-bound cDNA is subsequently digested with the restriction enzyme NlaIII,
which recognizes and removes the CATG sites. The fragments that are separated from the 3'
cDNA fragments that are connected to Oligo (dT) beads were washed away, and the
Illumina adaptor 1 was ligated to the sticky 5' end of the digested bead-bound cDNA
fragments. The junction of the Illumina adaptor 1 and the CATG site is the recognition site
of MmeI, which is a type of endonuclease that contains separated recognition sites and
digestion sites. It cuts DNA 17 bp downstream of the CATG site and produces tags that
contain adaptor 1. After the 3' fragments were removed with magnetic bead precipitation, the
Illumina adaptor 2 was ligated to the 3' ends of the tags; as a result, tags that contained
different adaptors at both ends were acquired to form a tag library. After 15 cycles of linear
PCR amplification, the 105 bp fragments were purified by 6% TBE PAGE gel
electrophoresis. After denaturation, the single-chain molecules were fixed onto the Illumina
Sequencing Chip (flowcell). Each molecule was amplified in situ until single-molecule
cluster sequencing templates were formed. Next, four types of nucleotides labeled by four
colors were added, and sequencing was performed using the sequencing by synthesis (SBS)
method. Each tunnel generated millions of raw reads, which have a sequencing length of 49
bp (see Fig. S3 and S4 for details of the experimental process). The procedure that was used
for bioinformatic analysis for DGE profiling is shown in Fig. S5. The raw sequences were
transformed into clean tags after certain steps of data processing were performed, including
the removal of the 3' adaptor sequence, empty reads, low quality tags, tags that were too long
or too short (leaving tags of 21nt long), and tags with a copy number of 1 (which were likely
related to sequencing errors); finally, clean tags were generated. Sequences from tomato
(http://www.ncbi.nlm.nih.gov/gquery/?term=tomato),
eggplant
and
(http://vegmarks.nivot.affrc.go.jp/VegMarks/jsp/page.do?transition=link)
S.
were
torvum
used
to
obtain the reference gene sequence. All of the clean tags were mapped to the reference
sequences, and only a 1 bp mismatch was tolerated. The clean tags that mapped to reference
sequences of multiple genes were filtered. The remaining clean tags were designated as
unambiguous clean tags. The number of unambiguous clean tags for each gene was
calculated and then normalized to the TPM (number of transcripts per million clean tags).
Screening of differentially expressed genes
A rigorous algorithm to identify the differentially expressed genes between the two samples
has been developed by BGI (formerly known as Beijing Genomics Institute). Here, x denotes
the number of unambiguous clean tags from gene A because its expression occupies only a
small part of the library, and p(x) is in the Poisson distribution.
(λ is the real transcripts of the gene)
The total number of clean tags for Sample 1 is N1, and the total number of clean tags for
Sample 2 is N2; gene A returns x tags in Sample 1 and y tags in Sample 2. The probability
that gene A is expressed equally in both Samples can be calculated with the following:
The P value corresponds to the differential gene expression test. The FDR (False
Discovery Rate) is a method to determine the threshold of the P value in multiple tests and
analyses by manipulating the FDR value. We used the FDR ≤ 0.001 and the absolute value
of log2Ratio ≥ 1.5 as the threshold to judge the significance of the constitutive and induced
gene expression differences.
RT-qPCR analysis
For the RT-qPCR, we first accurately quantified the RNA concentration using
spectrophotometry. The cDNA was synthesized from the DNase-treated total RNA (1 µg)
using the Reverse Transcription System Kit (Promega) and oligo (dT) primers. The cDNA
produced was diluted 1:15, and 3 μl was used in RT-qPCR in a 7500 Real Time System
(Applied Biosystems, USA) using Platinum® SYBR® Green qPCR SuperMix-UDG
(Invitrogen). Based on our transcriptome expression data, semiquantitative RT-PCR analysis,
and the Genevestigators’ RefGenes tool V3 (Hruz et al., 2008), we selected UBQ14
(TVR18P14C), 18S RNA (X67238), ACT (X55749), TUBST1 (609267), S23 (DQ228344),
RPL8 (X64562), and UBI2 (GU594243) as the candidate reference genes for RT-qPCR
normalization. Data acquisition and determination of quantification cycle (Cq) were
performed using the 7500 System SDS Software Version 1.2 (Applied Biosystems). Zero
template controls were included for each primer pair. Specific primers for each gene are
listed in Table S1. All primer pairs produced only one peak in DNA melting curves
indicating high specificity of the primers. The Cq values were converted into relative
quantities via the delta-Cq method using the sample with the lowest Cq as calibrator and
incorporating the calculated amplification efficiencies for each primer pair. The qRT-PCR for
each gene was done on three biological replicates with duplicates for each biological
replicate. The relative transcript level was determined for each sample and averaged over the
six replicates. The geNorm software (Vandesompele et al., 2002) was used to choose the
most suitable reference genes and estimate the number of genes required to calculate a robust
normalization factor. The pairwise variation (Vn/Vn+1) was analyzed between the
normalization factors NFn and NFn+1 by geNorm program to determine the optimal number
of reference genes required for RT-qPCR normalization. The gene expression levels were
normalized using the geometric mean of selected reference gene quantities as described in
the geNorm manual (http://medgen.ugent.be/~jvdesomp/genorm/geNorm_manual.pdf) and
the 95% confidence interval was calculated. Differential gene expression was considered
significant when the 95% confidence interval of the mean normalized expression levels did
not overlap (equivalent to P < 0.05).