Supplementary Materials and methods

Download 22.18 Kb.
NameSupplementary Materials and methods
A typeDocumentation > manual > Documentation

Supplementary Materials and methods

Cell culture and RNA extraction

Human monoblast leukemia THP-1 cells were maintained in RPMI1640 medium (Invitrogen, Carlsbad, CA, USA), 1mM sodium pyruvate, 10 mM HEPES supplemented with 0.001 % (v/v) 2-mercaptoethanol, 10 g/ml Penicillin/ Streptomycin (Invitrogen) and 10% fetal bovine serum at 37°C in a 5% CO2 and 95% O2 atmosphere. RNA was purified for expression analysis by Qiagen RNeasy columns, Takara FastPure RNA Kit or TRIzol. RNA quality was checked by Nanodrop and Bioanalyser. For the pre-microRNA over-expression experiments Total RNA was extracted 48h after transfection, using the FastPure RNA kit (TAKARA BIO, Ohtsu, Shiga, Japan) in accordance with the manufacturer’s instructions.

pre-miRNA overexpression experiments

THP-1 cells were seeded in 6 cm dishes at a density of 1 × 106 cells/dish for transfection. Transfection was performed with 1.6 g/ml (final concentration) of Lipofectamine 2000 (Invitrogen) and 20 M (final concentration) of pre-miRNA (Ambion or Nihon-shinyaku) by reverse transfection protocol in accordance with the manufacturer’s instructions. For the co-over-expression experiment 5uM for mir-155, mir-222, mir-424 and mir-503 was used.

Agilent miRNA microarrays

RNA purification, sample preparation and hybridization to Agilent Human miRNA Microarrays (Agilent) was performed essentially as described in the Agilent Technical Manual using 100 ng total RNA. Microarrays were scanned with Agilent’s DNA Microarray Scanner and expressed numerically with Agilent Feature Extraction Software. The biological triplicate data was ‘per chip’ normalized in GeneSpring GX (Agilent). Each measurement was divided by the 90th percentile of all measurements in that sample. Note: due to the small number of probes on the arrays (534), per chip normalization is generally not recommended however an alternative such as spike in controls was not available, therefore, we trialed normalization to the median and other deciles. The 90th percentile gave us the most consistent profiles between the biological replicate time-courses.

Deep Sequencing data analysis

Library generation and sequence mapping is described previously (1). All sequences shorter than 18 nucleotides were discarded. The remaining sequences were aligned against all mature and star sequences in mirbase (release 12) using nexalign (T.Lassman manuscript in preparation). The raw expression for each miRNA sequence was determined by counting the number of sequences mapping to genome loci overlapping the genomic location of the mature miRNA. Normalized expression values were derived by dividing each raw expression with the total expression of miRNAs at each time-point and multiplying by one million.

Illumina microarray analysis

Sample amplification and hybridisation

RNA (500 ng) was amplified using the Illumina TotalPrep RNA Amplification Kit, according to manufacturer’s instructions. cRNA was hybridized to Illumina Human Sentrix-6 bead chips Ver.2, according to standard Illumina protocols (

Raw data curation and normalization of Illumina microarray

Chips scans were processed using Illumina BeadScan and BeadStudio software packages and summarized data was generated in BeadStudio (version 3.1). The summarized data from BeadStudio was imported into R/BioConductor using the readBead function from the BeadExplorer package ( Background adjustment and quantile normalization (2) was performed using algorithms within the affymetrix package (3) (function: bg.adjust and normalize.quantiles). The normalized data was exported out off R/BioConductor with write.beadData function.

Normalisation and statistical analysis of Illumina microarray data

All microarray experiments were conducted in biological triplicate. A gene was considered detected if the average detection score (p-value) of the three replicates was less than 0.01. Quantile normalization and B-statistic calculations were carried out using the lumi and limma packages of Bioconductor in the R statistical language (4-6). For differential gene expression during the timecourse and between siRNAs, pre-miRNAs and negative control transfections we required a B-statistic ≥ 2.5, fold change ≥ 2 and the gene had to be detected in one of the conditions (average detection score ≤ 0.01).

RT-PCR confirmation of the hsa-mir-424, hsa-mir-503 precursor

Primers were designed overlapping the mature hsa-mir-424 and hsa-mir-503 sequences and internal to the transcription start sites described in (7). The primers for amplicons 1 to 5 are the following. amplicon 1 (chrX:133508023-133508403) used primer1: GGG ATA CAG CAG CAA TTC ATG T, and primer4: TTA CCC TGG CAG CGG AAA CAA TAC, amplicon 2 (chrX:133508023-133508586) used primer2: CAC CTG CAG CTC CTG GAA ATC AAA and primer4, amplicon 3 (chrX:133508023-133508641) used primer4 and primer3: CGT TGT TCC AAG ATT CAT CCT CAG GG, amplicon 4 (chrX:133508337-133508586) used primer2 and primer5: GGT ATA GCA GCG CCT CAC GTT T and amplicon 5 (chrX:133508336-133508641) used primer3 and primer5.

cDNA was made from a pool of THP-1 RNAs across the PMA time-course (0~96hr 10point Mix). Templates tested by PCR were 1) positive control Genomic DNA 100ng/100ul, 2) negative control RT(-) total RNA 12.5ng/25ul, and 3) test RT(+) total RNA 12.5ng/25ul RNA).

MicroRNA target predictions

MicroRNA target predictions were downloaded from (version 4.2 April 2008), and (release 2 January 2008).

Luciferase reporter constructs to test sites in the 3’UTR of predicted targets

Luciferase reporter constructs were generated from 3 fragment fusion PCR as described previously (8). The fragments consisted of 1) a CMV promoter driving a destabilised luciferase (the PCR template for this was generated by subcloning the destabilised luciferase from pGL4.12_luc2CP (Promega) into pMIR-REPORT (Ambion)), 2) A fragment containing the predicted miRNA target sites in 3’UTRs of candidate target mRNAs to be tested (PCR primers are given in supplementary table 5) an SV40 late poly-adenylation signal amplified from pG5 vector (Promega).

Samples for the assay were constructed by using PCR. The followings are PCR primers used; target-specific forward primer, 5’-GAA GGA GCC GCC ACC ATG-3’ followed by approximately 20-base 5’-end target sequence; target-specific reverse primer, 5’-CAA TTT CAC ACA GGA AAC TCA-3’ followed by approximately 20-base 3’-end target sequence; PMIR_CMV_F, 5’-GGG TCA TTA GTT CAT AGC CCA-3’; Luc2CP_Luc_R, 5’-CAT GGT GGC GGC TCC TTC TTA GAC GTT GAT CCT GGC GCT-3’; FSV40LPAS02, 5’-GTT TCC TGT GTG AAA TTG TTA TCC GCT GCA GAC ATG ATA AGA TAC ATT G-3’; RSV40LPAS01, 5’-AGC AAG TTC AGC CTG GTT AAG ATC CTT ATC GAT TTT ACC AC-3’; PMIR_CMV_Nested_F, 5’-GGG AGG AGA AGC ATG AAT TCA AGG-3’; LGT10L, 5’-AGC AAG TTC AGC CTG GTT AAG-3’; FPCMV5, 5’-GCC ATG TTG GCA TTG ATT ATT GAC-3’; (The sequences in bold type are complementary to the common tag sequences of the target-specific forward and reverse primers, respectively).

Each target sequence was amplified with the designed target-specific forward and reverse primers. The fragment for the CMV promoter and the Luc2CP gene was PCR-amplified from pMIR_Luc2CP vector using the primer sets PMIR_CMV_F and Luc2CP_Luc_R. The fragment for the SV40 late poly-adenylation signal (SV40LPAS) was PCR-amplified from pG5 vector (Promega) using the primer sets FSV40LPAS02 and RSV40LPAS01. Overlapping PCR was carried out to connect the target fragments with the CMV_Luc2CP-fragment and the SV40LPAS fragment using the primer pair PMIR_CMV_Nested_F and LGT10L. PCR conditions were based on those in our previous reports.

The fragment for the CMV promoter, Renilla luciferase gene and SV40LPAS was also PCR-amplified from pRL-CMV using the primer sets FPCMV5 and RSV40LPAS01. All PCR products were checked by agarose gel electrophoresis after the amplification.

CR Primers were designed flanking miRNA target sites in 3’UTRs of candidate target mRNAs (supplementary table 1). A CMV-luciferase PCR fragment Fusion PCR was used to generate constructs.

MicroRNA target validation by luciferase assay

miRNA target reporter assays were carried out in 96-well assay plates and were repeated three times. Each target construct (0.2 µl), the Renilla luciferase fragment (0.2 µl) and pre-miRNA (2 pmol) were diluted to 95 µl with Opti-MEM (Invitrogen) followed by mixing 50 µl of 2% Lipofectamine2000 (Invitrogen). After 20 min incubation at room temperature, the suspended Hela cells (88,000 cells/55 µl) were mixed for transfection (total 200 µl). After 48h of incubation, fire fly and Renilla luciferase reporters were sequentially measured using the Dual-Glo Luciferase Assay system (Promega) according to the manufacture’s protocol. The reporter activity for fire fly luciferase was normalized by that for Renilla luciferase.

Flow cytometry

48 hours after pre-miRNA transfection, cells were harvested and fixed in 70% ince cold ethanol. Fixed cells were washed in PBS and then DNA stained (2.5 μg/ml propidium iodide, and 0.5 mg/ml RNase A in PBS). Flow cytometry analysis was done using a FACS Calibur (Becton Dickinson, Franklin, NJ, USA) instrument following the manufacturer’s recommended protocol. Data were collected and processed using the FlowJo FACS analysis software (Tree Star, Inc., Ashland, OR, USA).

Data deposition

All expression data has been deposited at the Center for Information Biology gene EXpression database (CIBEX (9)). Accession numbers for the Illumina mRNA measurements are CBX46 (PMA time-course), CBX45 (pre-miRNA over-expression), and CBX47 (52 transcription factor knockdowns). The accession number for the Agilent miRNA array experiment is CBX49. The small RNA sequences of Taft et al. (1) are deposited at DDBJ (Accessions: AIAAF0000001 - AIAAF0055261, AIAAG0000001 - AIAAG0013956, AIAAH0000001 - AIAAH0046376, AIAAI0000001 - AIAAI0087752, AIAAJ0000001 - AIAAJ0100819, AIAAP0000001 - AIAAP0061402, AIAAQ0000001 - AIAAQ0033032, AIAAR0000001 - AIAAR0049623, AIAAS0000001 - AIAAS0055455, AIAAT0000001 - AIAAT0061351).

Authors' contributions statement

MK carried out the Illumina mRNA and Agilent miRNA array experiments. Y. Tomaru performed the pre-miRNA over-expression experiments. NN performed the luciferase reporter experiments and RT-PCR confirmation of the mir-424-mir-503 pri-miRNA. Y. Takahashi performed the FACs experiments. TL conceptualized some of the bioinformatic analysis. MdH provided the normalised miRNA tag counts from the small RNA libraries. AK was involved in experimental testing. MS, JY, were involved in supervision and general discussions. TL, JK, HS, YH and DAH were involved in conceptualization of FANTOM4 and the choice of the THP-1 model. ARRF designed and analysed most of the experiments (including the array profiling, over-expression, reporter assays and FACs experiments), carried out the bioinformatic analysis and wrote the manuscript.

References for supplementary information

1. Taft RJ, Glazov EA, Cloonan N, Simons C, Stephen S, Faulkner GJ, et al. Tiny RNAs associated with transcription start sites in animals. Nat Genet 2009 May; 41(5): 572-578.
2. Bolstad BM, Irizarry RA, Astrand M, Speed TP. A comparison of normalization methods for high density oligonucleotide array data based on variance and bias. Bioinformatics 2003 Jan 22; 19(2): 185-193.
3. Gautier L, Cope L, Bolstad BM, Irizarry RA. affy--analysis of Affymetrix GeneChip data at the probe level. Bioinformatics 2004 Feb 12; 20(3): 307-315.
4. Smyth GK, Yang YH, Speed T. Statistical issues in cDNA microarray data analysis. Methods Mol Biol 2003; 224: 111-136.
5. Smyth GK. Linear models and empirical bayes methods for assessing differential expression in microarray experiments. Stat Appl Genet Mol Biol 2004; 3: Article3.
6. Lin SM, Du P, Huber W, Kibbe WA. Model-based variance-stabilizing transformation for Illumina microarray data. Nucleic Acids Res 2008 Feb; 36(2): e11.
7. Rosa A, Ballarino M, Sorrentino A, Sthandier O, De Angelis FG, Marchioni M, et al. The interplay between the master transcription factor PU.1 and miR-424 regulates human monocyte/macrophage differentiation. Proc Natl Acad Sci U S A 2007 Dec 11; 104(50): 19849-19854.
8. Suzuki H, Fukunishi Y, Kagawa I, Saito R, Oda H, Endo T, et al. Protein-protein interaction panel using mouse full-length cDNAs. Genome Res 2001 Oct; 11(10): 1758-1765.
9. Ikeo K, Ishi-i J, Tamura T, Gojobori T, Tateno Y. CIBEX: center for information biology gene expression database. C R Biol 2003 Oct-Nov; 326(10-11): 1079-1082.

Share in:


Supplementary Materials and methods iconSupplementary Materials and Methods and Supplementary Tables

Supplementary Materials and methods iconSupplementary Materials and Methods

Supplementary Materials and methods iconSupplementary Materials and Methods

Supplementary Materials and methods iconSupplementary Materials and Methods

Supplementary Materials and methods iconSupplementary materials and methods

Supplementary Materials and methods iconSupplementary Materials and Methods

Supplementary Materials and methods iconAdditional File 3 Supplementary Materials and Methods

Supplementary Materials and methods iconSupplementary Materials and Methods, Tables, and Figure Legends

Supplementary Materials and methods iconSupplementary Methods

Supplementary Materials and methods iconSupplementary Methods

Supplementary Materials and methods iconSupplementary Methods

Supplementary Materials and methods iconSupplementary Methods

Supplementary Materials and methods iconSupplementary 1: Material and methods

Supplementary Materials and methods iconSupplementary information – Methods

Supplementary Materials and methods iconRiba, et al. Supplementary Materials

Supplementary Materials and methods iconText S1: Supplementary materials

Supplementary Materials and methods iconDetailed materials and methods

Supplementary Materials and methods iconSupporting Information Materials and methods

Supplementary Materials and methods iconMaterials and methods. Sequence analyses

Supplementary Materials and methods iconBasic concrete materials and methods


When copying material provide a link © 2017