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Supplementary Material
Materials and Methods
Agilent cDNA Microarray Annotation
The custom Agilent cDNA Microarray chip is made up of clones from four libraries: RIKEN, NIA, Research Genetics, and Genome systems, with
the large majority of clones being RIKEN. The chip was designed to encompass a wide part of the mouse genome, and to target many of the
proteins on the AfCS Protein List (about 50%). The cDNA clones used in the array come from a wide range of tissues. The tissues that have at least
100 cDNA clones include: whole body, testis, tongue, head, pancreas, small intestine, hippocampus, stomach, liver, cerebellum, kidney, mixed,
placenta, thymus, skin, lung, brain, retina, cecum, urinary bladder, ovary, and uterus. In addition, there are 818 cDNA clones that have unknown or
unspecified tissue sources.
AfCS Agilent cDNA chip clone distribution
Clone Set
Unique Clones
RIKEN
14828
NIA
447
Research Genetics
155
Genome Systems
64
Total
15494
Array Positions
14890
723
155
64
15832
No resequencing was performed on the clones on the chip, therefore the only starting point for annotation was the clone ID – which was used as a
link to public databases via UniGene or Genbank ID. Because most of the RIKEN clones were annotated in the Fantom database [PMID:
12466851, PMID: 11752270, PMID: 11217851] and many of the NIA clones had additional annotation [PMID: 12466305, PMID: 11326268], this
gave us a source for full-length cDNA sequences and some additional functional annotation. Of the 15494 clones, 14856 (close to 96%) have
known cDNA sequences, with the rest having only EST sequences available for analysis.
We chose to give each clone a representative gene, which is tantamount to a unique mouse LocusLink ID [PMID: 12519942, PMID: 12519942] or
Mouse Genome Informatics (MGI) ID [PMID: 12519980, PMID: 11752269] if no analogous LocusLink ID was available. The selection process
involves a comparison of the cDNA sequence, or all EST sequences if no cDNA sequence is available, to the LocusLink and MGI databases. If the
cDNA sequence belongs to a database record (most of the cDNA sequences have Genbank accessions, in the HTC division), then that is used to
assign the gene. Otherwise, BlastN is used to find the highest scoring gene, which is then verified by Unigene references for the cDNA and the
ESTs for a particular clone. For clones without a cDNA sequence and thus no clear representative sequence, the highest-scoring EST match to the
representative gene is chosen as the representative sequence.
Close to 1,000 of the clones find multiple potential genes with our method. This often is a result of ESTs for the same clone belonging to different
Unigene clusters, and can also be the result of closely related genes being found with the Blast method. In some cases, this automated method may
not choose the best gene, but the annotation process records all potential genes, so that further mining of the data can be performed if necessary.
The representative sequences are also compared the Ensembl genome database [PMID: 12519944, PMID: 12519943], with the same Blast
procedure as described above. In addition, all LocusLink references in Ensembl are used to build the Ensembl annotation for the clones. All
database references in LocusLink, Unigene, and MGI are used to build a list of all potential gene identities for a particular clone. Once this list of
gene links is built, we find references to all potential protein database records (e.g. SwissProt, Refseq), chromosome information, Gene Ontology
annotation, InterPro references, and some of the additional annotation associated with the RIKEN and NIA clones. References to the AfCS
Molecule Pages are found by merging the LocusLink references in the two sets of data.
Data preparation for SAM
The input for the SAM analysis was Cy5 fluorescence intensity that has been background-subtracted and normalized for dye bias and inter-array
variance. The dye-normalization was performed by the Agilent G2566AA Extraction Software Version A.6.1.1 using the Rank consistent filter and
the LOWESS algorithm. The inter-array normalization was done by multiplying the dye-normalized Cy5 intensity ("gProcessedSig") with the ratio
of Cy3 intensity ("rProcessedSig") relative to the median of Cy3 intensity measurements of all the arrays. Features that did not have at least two
replicate measurements were excluded from further analysis.
SAM analysis
The SAM procedure computes a modified two-sample t-statistic for each feature and uses it to rank all features. Experimental condition labels are
then randomly permutated for multiple runs and features are ranked according to their t-statistic in each permutation. Significantly expressed
features were those whose t-statistic in the original data set is greater, by a user-defined threshold, than the median of the t-statistic at the same rank
of the permutated data. A false discovery rate (FDR) was computed as the percentage of the number of significant features identified in randomly
permutated data relative to that in the original data set at a given threshold of t-statistic difference. FDR usually monotonically decreases as the
threshold of t-statistic difference increases until it reaches a local minimum. The threshold t-statistic difference at which FDR reaches its local
minimum was used in our current analysis.
Quantitative real-time PCR (Q_RT_PCR)
1 g total RNA from pooled duplicate or triplicate RNA samples used for microarray experiments was treated with DNase I (Invitrogen) to remove
contaminating genomic DNA. First-strand cDNA was synthesized with SuperScript II (Invitorgen) and random hexamer priming (Invitrogen).
Quantitative real-time PCR was performed by using i-Cycler (Biorad) and SYBR green detection. Reactions were performed in 25 l in triplicate
wells in 96-well plates with the following ingredients: 5’ and 3’ primers (200 nM each), iQTM SYBR Green Supermix (Bio-Rad), and cDNA
corresponding to 40 ng of total RNA. Mouse -actin was amplified in separate reactions in the same plate to be used as an internal control for
variances in the amount of cDNA in PCR reactions. See supplementary table VIII for primer sequences and amplicon lengths. PCR cycle setup was
as the following: 95 Cº for 1 min, 95 Cº for 3 min, 40x (95 Cº for 30 sec, 60 Cº for 10 sec, 72 Cº for 10 sec). The Pfaffl’s equation (1) was used to
calculate the expression ratio (R) of ligand-treated versus control B cells. Briefly,
(Etarget)ΔCPtarget (control-treated)
R=
(E-actin)ΔCP-actin (control-treated)
Where E = 10(-1/slope), with the slope being the slope of the standard curve of the target genes or -actin; ΔCPtarget (control-treated) is the average
cross point cycle number of the control minus that of the treated sample for the target gene; ΔCP-actin (control-treated) is the average cross point
cycle number of control minus the treated sample for -actin.
Q_RT_PCR primers and the amplicon length of selected genes
Symbol
Gene Name
Syk
Mus musculus spleen tyrosine kinase
Mus musculus protein phosphatase 3,
catalytic subunit, gamma isoform
Mus musculus X-box binding protein 1
Mus musculus nuclear factor of
activated T-cells, cytoplasmic,
calcineurin-dependent 1
Mus musculus ATPase, H+
transporting, lysosomal accessory
protein 2
Mus musculus lymphotoxin B
Ppp3cc
Xbp-1
Nfatc1
Atp6ap2
Ltb
Accession
Number
NM_011518
Amplicon
Size (bp)
135
NM_008915
NM_013842
141
133
CGGGTCTTTACGGTTCTTC
NM_198429
NM_027439
NM_008518
Sense Primer
AGACAGACAAGCAGCAAGAC
Length
(bp)
20
Anti-sense Primer
CCCAGAGGAACGGAATGATG
Length
(bp)
20
CTCCTCTGCGGCTTCTTG
GAGTGGAGTAAGGCTGGTG
19
19
AAGAGGCAACAGTGTCAGAG
18
20
112
GAAGAGCCTCCTGCGTATC
19
TGACTATGAGAGAGCCAAGAAG
22
100
108
CGCAGTGGTAGAGTTAGTGAC
21
19
AGGACTTTGGGTGTTCTCTTG
21
18
CCGACATGGTGGACTACAG
ACACATTCGCACCGTCAG
Nfkb2
-actin
Mus musculus nuclear factor of kappa
light polypeptide gene enhancer in Bcells 2, p49/p100
Mus musculus actin, beta, cytoplasmic
NM_019408
NM_007393
134
117
GATGGCACAGGACGAGAAC
TGTGGCTGAGGACTTTGTAC
19
20
GGTGGTTGGTGAGGTTGATG
GGGAGGGTGAGGGACTTC
20
18
Table I. The abbreviation, full name, manufacturer, source, catalog number, dosage, and the stock solution protocol of single ligands used
in B cell single ligand screen.
Table II. The annotation table of the Agilent cDNA array.
Table III. Log2(Treated/0 h) values for 2937 differentially expressed features identified by SAM. The log2(Treated/0 h) value was calculated
by subtracting log2(0 h/Spleen) from log2(Treated/Spleen), where the log2(Treated/Spleen) is the average of at least two out of three replicate
log2(Cy5/Cy3) measurements of cultured B cells and log2(0 h/Spleen) the average of at least 6 out of the 26 replicate log2(Cy5/Cy3) measurements
of 0h B cells. For features that did not have at least two replicate measurements in cultured B cells or at least 6 replicate measurements in 0 h B
cells, their log2(Treated/0 h) value was set to blank
Table IV. Log2(Treated/0 h) values for all array features. a. The log2(Treated/0 h) values of B cells cultured with media (UNTR), 2MA, Anti-Ig,
BAFF, BLC, BOM, CD27, CD40L. b. The log2(Treated/0 h) values of B cells cultured with CGS, CpG, DIM, ELC, fMLP, IFN, IFN. c. The
log2(Treated/0 h) values of B cells cultured with IGF-1, IL-10, IL-4, LPA, LPS, LTB4, MIP3, NEB. d. The log2(Treated/0h) values of B cells
cultured with NGF, NPY, PAF, PGE, SIP, SDF1, SLC, TER. e. The log2(Treated/0 h) values of B cells cultured with TGF and TNF. The
log2(Treated/0 h) value was calculated by subtracting log2(0 h/Spleen) from log2(Treated/Spleen), where the log2(Treated/Spleen) is the average of
at least two out of three replicate log2(Cy5/Cy3) measurements of cultured B cells and log2(0 h/Spleen) the average of at least 6 out of the 26
replicate log2(Cy5/Cy3) measurements of 0 h B cells. For features that did not have at least two replicate measurements in cultured B cells or at
least 6 replicate measurements in 0 h B cells, their log2(Treated/0 h) value was set to blank
Table V. Expression fold-changes and GO designations of features showing similar temporal patterns of expression changes in response to
Anti-Ig, CD40L, CpG, IL-4 and LPS. Only features changed expression at least 30% to each ligand were included. Features are listed in
ascending order of their featureNumbers. The probe name, gene symbol, LocusLink, expression fold-changes*1 in response to Anti-Ig, CD40L,
CpG, IL-4 and LPS, as well as the Go term designations of the features are included in the excel spreadsheets. Sheet 1 lists the features that
increased expression with time; sheet 2 lists features that decreased expression with time; sheet 3 lists the features whose functions are related to
protein synthesis
Table VI. Expression fold-changes and GO designations of features of known genes showing unique expression patterns in response to IL-4.
Features are listed in ascending order of their featureNumbers. The probe name, gene symbol, LocusLink, expression fold-changes*1 in response to
Anti-Ig, CD40L, CpG, IL-4 and LPS, as well as the Go term designations of the features are included.
Table VII. Expression fold-changes and GO designations of features of known genes showing unique expression patterns in response to
Anti-Ig. Features are listed in ascending order of their featureNumbers. The probe name, gene symbol, LocusLink, expression fold-changes*1 in
response to Anti-Ig, CD40L, CpG, IL-4 and LPS, as well as the Go term designations of the features are included.
Table VIII. Expression fold-changes and GO designations of features of known genes showing unique expression patterns in response to
CD40L. Features are listed in ascending order of their featureNumbers. The probe name, gene symbol, LocusLink, expression fold-changes*1 in
response to Anti-Ig, CD40L, CpG, IL-4 and LPS, as well as the Go term designations of the features are included.
Reference
1.
Pfaffl, M. W. 2001. A new mathematical model for relative quantification in real-time RT-PCR. Nucleic Acids Res 29:e45.