High-throughput small RNA sequencing
Total RNA (10 µg) from mouse liver was isolated by tissue homogenization in Qiazol
followed by total RNA isolation using miRNeasy Mini kits (Qiagen, Valencia, CA). Total
RNA, miSPIKE 21 nt control RNA (Integrated DNA Technologies, Coralville, IA) and RNA
ladder (Invitrogen, Carlsbad, CA), were run on 15% TBE-Urea gels. RNA 20-30 nts in
length was gel-extracted with 0.3M NaAc and 0.1% SDS, isolated from gel elute by
phenol/chloroform extraction (2x), and precipitated by 100% ethanol and
centrifugation. Washed pellets (75% ethanol) were air dried and re-suspended in RNasefree water. Small RNA was ligated (3’) to a 3’ adapter (10 µM, Supporting Table S4) using
T4 RNA ligase (Promega, Madison, WI) for 6 h at 20oC. The ligation reaction was stopped
using 2X RNA loading buffer at 65oC. After cooling, the ligated product was run on 15%
TBA-Urea gels along with RNA ladder and ligated miSPIKE 21 nt RNA control marker.
Bands at 40-60 nt in length were gel-excised and RNA was eluted and purified as
described above. Purified 3’-ligated small RNA was 5’ ligated to a 5’ adapter (10 µM)
using T4 RNA ligase for 6 h at 20oC and the reaction was stopped as described above.
Ligated product was run on 10% TBE-Urea gels. Bands at 60-80 nt in length were gelexcised, and the RNA was eluted and purified as described above. Reverse transcription
was performed, using 100 µM small RNA RT primer (Supporting Table S4), 12.5 mM
dNTPs, 5X first-strand buffer, 100 mM DTT, and SuperScript III (Invitrogen).
Amplification (18 cycles) was performed with 5X Phusion HF buffer, small RNA PCR
primers (25 µM each) (Supporting Table S4), 12.5 dNTPs, and Phusion DNA polymerase.
Reaction was stopped with 6X DNA loading buffer, and the cDNA product was size
selected at 110-120 nt, gel-eluted, and purified, using phenol/chloroform followed by
clean up with Zymo DNA Clean and Concentrator-5 kit (Zymo, Orange, CA), as per
instructions.
Illumina small RNA sequencing was performed on the amplified cDNA product,
using an Illumina Genome Analyzer IIx (Illumina, San Diego, CA), as per the Illumina
small RNA sequencing kit 1.5v protocol with custom sequencing primer, 5’CTCTTGGAATTCTCGGGCACCAAGGT-3’, for 35 sequencing cycles. Raw sequencing reads
were clustered by sequence identity, and 3’ and 5’ adapter sequences were trimmed.
Trimmed reads were mapped to the mouse genome using MEGABLAST
(blast.ncbi.nlm.nih.gov), and high-confidence miRNA reads were identified based on
perfect match with miRBase annotations (miRBase v17.0, microrna.sanger.ac.uk). Read
counts were normalized to total read count and expressed as percent total reads. The
ratio between high-fat mouse liver miRNAs and normal chow liver miRNAs was
calculated only for annotated miRNAs with ≥ 2 reads in each condition. An absolute foldchange ≥ 2 was considered to be differentially abundant.
Prediction of miR-27b target sites
For seed-based target prediction in 3’ UTRs, the TargetScanS 4.1 algorithm was used
(Perl script and relevant data files downloaded from http://targetscan.org). For
centered target prediction in 3’ UTRs, an in-house strategy was implemented to search
for complementary matches to at least 9 nucleotides of a miRNA starting from position
4 from its 5’-end.
For target prediction in open reading frames (ORFs), the dataset of human ORFs
was downloaded from the UCSC Genome Browser (http://genome.ucsc.edu). Only those
that were unique and exactly translatable to the corresponding annotated amino acid
sequence were retained. Seed sites were predicted in these ORFs, using the TargetScan
4.1 algorithm, and those that were preceded by a region with a “low codon-usage
score” (i.e. a stretch of infrequently used or rare codons) were identified as candidate
coding-region target sites. The codon-usage score was calculated as follows: first,
ORFeome-wide raw codon frequencies were counted. Next, the 10-codon region
immediately preceding each predicted seed site was assigned a weighted score using
the formula

freq(c)
where d(c) is the codon-distance of codon c to the seed site and
d(c)
freq(c) is the ORFeome wide codon count. Seed sites that were preceded by a 10-codon

region with a codon-usage score in the bottom 5th percentile were identified as “low”,
and thus, candidate coding-region target sites.
All target predictions of each type were assessed for exact sequence
conservation by comparing with the genome sequences of three other mammalian
species (rat, mouse, and dog).
Identification of candidate miRNA regulatory hubs
Monte-Carlo simulations were performed to identify miRNAs that are predicted to
target 151 known lipid-metabolism genes significantly more than expected by chance.
First, 151 genes were randomly selected from the human genome under the condition
that each has at least one predicted miRNA target site. Then, the number of genes from
this randomly selected set that each known human miRNA is predicted to target was
calculated. By repeating this simulation 10,000 times, a background distribution of the
number of predicted target genes for each miRNA was generated, which was then used
to calculate an empirical p-value for the number of predicted lipid-metabolism target
genes. To account for differences in the average 3’ UTR length between the lipidmetabolism genes and the randomly selected genes in each simulation, the number of
predicted target genes was normalized to the average 3’ UTR length.
Gene expression studies
Microarray- Total RNA was isolated from Huh7 cells using the miRNeasy Mini kit
(Qiagen, Valencia, CA). RNA quality control was assessed with an Agilent 2100
Bioanalyzer (Agilent, Palo Alto, CA). Affymetrix GeneChip Human Genome U133A 2.0
microarrays were hybridized, stained, and washed according to Affymetrix protocols
(Affymetrix, Santa Clara, CA). The chips were scanned (Affymetrix scanner 3000) and the
images were analyzed with the Affymetrix GCOS program (GeneChip Operating System)
to generate the .cel files. Low and high-level post-analyses of the gene expression
(mRNA) data were carried out using GeneSpring GX11.5 software (Agilent). Briefly, raw
data (human Affymetrix GeneChip HG_U133A_2 .cel files) were uploaded and
summarized using the LiWong algorithm(23). Summarized data were quantile
normalized with no baseline transformation. Entities were filtered by expression (20100th percentile raw data) and by error (coefficient of variation ≤ 50%), and statistical
analyses were conducted using unpaired t-tests with Benjamini-Hochberg false
discovery rate for multiple-testing correction. A significant differential gene expression
change was considered as corrected P-value ≤ 0.05 and absolute fold change ≥ 1.5.
Real-time PCR- For miRNA analysis, total RNA was reverse transcribed using the
MicroRNA RT kit (Applied Biosystems, Foster City, CA) with individual miRNA RT primers
(stem-loop). Individual TaqMan miRNA probes (Applied Biosystems) were used to
perform real-time PCR (ABI 7900HT real-time PCR System), and relative quantitative
values (RQV) were determined by the delta Ct method (RQV = 2-dCt). miRNA Ct values
were normalized to U6 snoRNA Ct levels. For mRNA analysis, total RNA was reverse
transcribed, using TaqMan RT kit (Applied Biosystems) with random hexamers, as per
instructions. Individual transcript levels were quantified with real-time PCR TaqMan
probes and relative quantitation (RQV), as described above. Ct values for genes of
interest were normalized to the Ct of the housekeeping gene, peptidylprolyl isomerase
A (PPIA).
ELISA - Total protein was isolated from culture wells using RIPA buffer (0.05M Hepes, pH
7.6, 1mM EDTA, 0.7% Na-Deoxycholate, 1% NP-40, 0.5M LiCl) with 1X Complete (EDTAfree) protease inhibitor cocktail. Cell lysates were sheared using 27-gauge needles and
centrifuged for 10 min (10,000 x g), and cleared lysate supernatants were collected.
Total protein concentration was determined by BCA protein assays (Thermo Scientific).
GPAM protein levels (ng/mL) were quantified in cell lysates (100 µL) using enzymelinked immunosorbent assays (ELISA) (human GPAM ELISA Kit, USCN Life Science, Inc.),
as per instructions. ANGPTL3 (secreted) protein levels (ng/mL) were quantified in the
media of cultured cells by ELISA (AdipoGen), as per instructions. Both cellular GPAM and
secreted ANGPTL3 levels (ng/mL) were normalized to total cellular protein (mg/mL).
PPARG Transcription Factor Activity Assays
Nuclear extracts were prepared from transfected (miR-27b, HI-27b, or mock control)
Huh7 cells using a nuclear extraction kit (CaymanChem), as per instructions. PPARG
transcriptional activity was quantified in nuclear extracts (~4-7 µg) using a PPARG
transcription factor assay kit (CaymanChem), as per instructions. Transcriptional
activities were normalized to total protein of nuclear extracts.
Reporter Gene (Luciferase) Assays
A truncated 3’ UTR (bases 1-806) of human GPAM (NM_020918.3) was cloned
downstream of firefly luciferase in a pEZX-MT01 vector (GeneCopoeia). Site-directed
mutagenesis (QuickChange II XL, Stratagene), using custom primers (Supporting Table
S4), was performed to alter the predicted miR-27b target site at base 329 (G>A). XL10Gold ultracompetent cells were used for transformation and LB-Kanamycin (30-50
µg/mL) agar plates were used for colony growth and selection. Plasmid DNA was
extracted from expanded bacterial growth (LB-Kanamycin 50 µg/mL) by HiSpeed
Plasmid Midi Kits (Qiagen), as per instructions. HEK293 cells were plated at 1 x 105
cells/mL for 24 h prior to dual transfection. HEK293 cells were transiently transfected
with 500 ng of reporter plasmid per cell with 10 nM miR-27b miRIDIAN mimic or 10/100
nM HI-27b miRIDIAN hairpin inhibitor for 48 h, as described above. HEK293 cells were
washed (1X PBS) and lysed in-well using 1X Passive Lysis Buffer (Promega). Luciferase
activity was determined by Luc-Pair miR Luciferase Assay reagents (GeneCopoeia), as
per instructions. Firefly luciferase activity (reporter) was normalized to Renilla luciferase
(transfection control). Site-directed mutagenesis was confirmed by DNA sequencing
(ACGT, Inc., Wheeler, Illinois).
Plasma lipid analysis
Blood was collected in tubes, containing EDTA (4 mM), from retro-orbital plexus of
fasting (4 h) C57BL/6J mice after ~3 weeks (19-21 days) on chow or high-fat Western
diet, or weekly for 4 weeks (28 days) for Apoe-/- C57BL/6J mice on chow or Cocoa butter
diet. Plasma was separated by centrifugation (3000 x RPM, 20 min, 40C) and triglyceride
(mg/dL, Roche Diagnostics, Indianapolis, IN) and cholesterol (mg/dL, Wako Diagnostics,
Richmond, VA) were quantified enzymatically.
Hepatic lipid analysis
Briefly, mouse liver tissue (100 mg) was placed in 1 mL chloroform (methanol (2:1) +
0.05% Triton-X-100) and chilled on ice (4oC) 10 min prior to homogenization using a
Precellys bead-based (CK14) system. Lipids were extracted from liver homogenates
through room temperature orbital shaking (2 h) followed by centrifugation (5,000 rpm,
5 min). Supernatants were collected, washed with 0.4 mL chloroform: methanol (2:1)
(20 min, room temperature), and centrifuged (5,000 rpm, 5 min). New supernatants
were washed with 0.2 volume 0.9% NaCl and centrifuged (5,000 rpm, 5 min).
Supernatants were removed (discarded) and lower-phase was evaporated (dried) with
nitrogen flux at 42oC. Dried lipids were re-suspended in 0.4 mL 100% ethanol and
vortexed, and 0.4 mL saline was added to mixture. After vigorous vortexing, ethanol was
removed from mixture by evaporation (speed vac) and volume was re-suspended to 0.8
mL with fresh saline. Triglycerides (mg/dL) were quantified, as described above.
Selection of lipid metabolism genes for real time PCR validation
(1) PPARG is a master regulator of adipogenesis, and has been previously identified as a
miR-27 target in adipocytes(38, 39) and macrophages(40); (2) ANGPTL3 is expressed
specifically in the liver(41), regulates plasma lipid levels in mice(42), and harbors
mutations that cause human lipid disorders(43); (3) NDST1 is required for hepatic
heparan sulfate-mediated triglyceride-rich lipoprotein catabolism(44); (4) HMGCR is the
rate-limiting enzyme for cholesterol biosynthesis(45), and is the molecular target of
statins(46), a class of drugs used to control plasma cholesterol levels; (5) GPAM is
essential for triglyceride synthesis and metabolism(47), has been implicated in
regulating total cholesterol levels(34), and is a potential therapeutic target for obesity
and related disorders(48); and, finally, (6) SREBF1 is the master transcriptional regulator
of fatty acid homeostasis(5).