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Supplementary Material For:

Method for improved Illumina sequencing library preparation using NuGEN Ovation RNA-Seq System Steven R. Head1, H. Kiyomi Komori2, G. Traver Hart2, John Shimashita1, Lana Schaffer1, Daniel R. Salomon2, Phillip T. Ordoukhanian1 1 Next Generation Sequencing Core, The Scripps Research Institute, La Jolla, CA, USA and 2Department of Molecular & Experimental Medicine, The Scripps Research Institute, La Jolla, CA, USA BioTechniques 50:177-181 (March 2011) doi 10.2144/000113613 Keywords: RNA-seq; Next-generation sequencing; deep sequencing; gene expression; cDNA library

Ethics statement All the studies in this manuscript were covered by Human Subjects Research Protocols approved by the Center’s Institutional Review Board and by the IRB of The Scripps Research Institute. Informed written consent was obtained from all study subjects in the study. Isolation of CD4 T cells Peripheral blood was collected from healthy donors and peripheral blood mononuclear cells (PBMC) were collected by centrifugation through a histopaque gradient. For total CD4 T cell purification, T cells from six donors were positively selected from PBMCs on anti-CD2 beads (Miltenyi Biotec, Auburn, CA, USA) followed by positive selection on anti-CD4 beads (Invitrogen, Carlsbad, CA, USA). Total CD4+ T cells were cultured in RPMI (Mediatech, Manassas, VA, USA) supplemented with 10% FBS, 100 U/mL penicillin (Gibco, Invitrogen), and 100μg/mL Streptomycin (Gibco, Invitrogen) for 48 h with and

rank correlations between gene expression levels observed in S1-treated and untreated naive CD4+ T cells were calculated for 12,956 genes observed in all four data sets; the same gene set was used to compare gene expression levels in S1-treated and untreated memory T cells. To measure differential expression between naive and memory cells for a given prep, we took the log10 ratio of respective RPKM values. To minimize the effect of measurement noise on estimates of differential expression, we only considered genes with mean RPKM > 1 (n = 9,076 genes) in all four samples. The Pearson correlation was calculated for these genes’ differential expression observed in the S1-treated samples versus the untreated samples.

without stimulation with anti-CD3/CD28 beads (Invitrogen). Cells were harvested and resuspended in TRIzol (Invitrogen). RNA was isolated following a standard TRIzol extraction protocol. Naive and memory CD4 T cells from a single donor were negatively selected from PBMCs using the naive CD4 T cell isolation kit II (Miltenyi Biotec) or the Memory CD4 T cell isolation kit (Miltenyi Biotec) following the manufacturer’s directions. RNA was isolated from purified naive and memory CD4 T cells using an All Prep kit (Qiagen, Valencia, CA, USA) following manufacturer’s directions. A summary of TRIzol and AllPrep methods for RNA extraction can be found at www.genetics.ucla.edu/transplantgenomics/files/AllprepPBL.pdf Methods for analysis of memory and naive CD4+ cells Reads per kilobase per million reads (RPKM) values for each gene were calculated by the Illumina pipeline. Spearman

Supplementary Table S1. Alignment statistics for CD4+ memory and naive T cell RNA-seq. Sample

Description

RNA extraction method

Total number of reads

mRNA

Mitochondrial

rRNA

1

Memory (S1 treated)

AllPrep (Qiagen)

46417954

25.6%

10.8%

4.5%

2

Memory (Untreated)

AllPrep (Qiagen)

46472604

27.6%

12.5%

2.8%

3

Naïve (S1 Treated)

AllPrep (Qiagen)

43687177

21.8%

10.4%

6.8%

4

Naïve (S1 Untreated)

AllPrep (Qiagen)

36224797

19.8%

9.4%

4.4%

We determined the total reads and percent alignments to mRNA (including splice junctions), mitochondrial and rRNA sequences using CASAVA software version 1.7 (Illumina) for all four samples. All 40 base single reads were aligned with a filter set to 1 across the four samples (memory and naive, S1-treated and untreated), differential expression for each gene was calculated for S1-treated and untreated samples by taking the log(RPKM-memory/RPKM-naive). Differential expression of the S1-treated sample (x axis) was plotted against differential expression measured in the untreated sample (y axis). The high correlation (Pearson r = 0.82) indicates that genes differentially expressed in one prep are also observed to be differentially expressed in the other.

Supplemental Figure S6. Gel analysis of libraries prepared using 1 µg cDNA with and without S1 treatment and PCR cycled 6 or 8 times. S1-treated and untreated sequencing libraries were prepared from 1 µg cDNA and size-selected at ~350 and 800 bp. Libraries were then amplified either 6 or 8 cycles. Lane 1, 100-bp ladder with size markers indicated at 100, 200, 300 and 600 bp; Lane 2, S1-treated, 6 cycles of PCR, ~350 bp; Lane 3, S1treated, 6 cycles of PCR, ~800 bp; Lane 4, untreated, 6 cycles of PCR, ~350 bp; Lane 5, untreated, 6 cycles of PCR, ~800 bp; Lane 6, S1-treated, 8 cycles of PCR, ~350 bp; Lane 7, S1-treated, 8 cycles of PCR, ~800 bp; Lane 8, untreated, 8 cycles of PCR, ~350 bp; Lane 9, untreated, 8 cycles of PCR, ~800 bp; Lane 10, 100-bp ladder.

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Supplemental Figure S7. Traces and quantitation from Agilent Bioanalyzer of each PCR product excised from the gel shown in Figure 5. Agilent size markers are seen at 35 bp and 10,380 bp.

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