Adipocyte long noncoding RNA transcriptome …...2018/03/08 · Adipocyte long noncoding RNA...

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Adipocyte long noncoding RNA transcriptome analysis of obese mice identified Lnc-leptin which

regulates Leptin

Kinyui Alice Lo1,2

, Shiqi Huang3, Arcinas Camille Esther Walet

2, Zhi-chun Zhang

2, Melvin Khee-Shing

Leow2,4,5,6

, Meihui Liu3, Lei Sun

1,2*

1Institute of Molecular and Cell Biology, 61 Biopolis Drive, Proteos, Singapore 138673

2Cardiovascular & Metabolic Disorders, Duke-NUS, 8 College Road, Singapore 169857

3Food Science and Technology Program c/o Department of Chemistry, National University of Singapore,

Singapore, 117543 4Clinical Nutrition Research Centre (CNRC), Singapore Institute for Clinical Sciences (SICS), Agency for

Science, Technology and Research (A*STAR) and National University Health System (NUHS), 117599, Singapore 5National University Health System (NUHS), 119074, Singapore

6Department of Endocrinology, Tan Tock Seng Hospital, 308433, Singapore

*Corresponding: Lei Sun Cardiovascular & Metabolic Disorders, Duke-NUS, 8 College Road, Singapore 169857 Phone: 65-66013021 [email protected]

CONFLICT OF INTEREST STATEMENT

The authors have declared that no conflict of interest exists.

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Abstract

Obesity induces profound transcriptome changes in adipocytes; recent evidence suggests that lncRNAs

play key roles in this process. Here, we performed a comprehensive transcriptome study by RNA-Seq in

adipocytes isolated from interscapular brown, inguinal and epididymal white adipose tissues in diet-

induced obese mice. Our analysis reveals a set of obesity-dysregulated lncRNAs, many of which exhibit

dynamic changes in fed vs. fasted state, potentially serving as novel molecular markers reflecting adipose

energy status. Among the most prominent ones is Lnc-leptin, an lncRNA transcribed from an enhancer

region upstream of Leptin. Expression of Lnc-leptin is sensitive to insulin and closely correlates to Leptin

expression across diverse pathophysiological conditions. Functionally, induction of Lnc-leptin is essential

for adipogenesis, and its presence is required for the maintenance of Leptin expression in vitro and in

vivo. Direct interaction was detected between DNA loci of Lnc-leptin and Leptin in mature adipocytes,

which diminished upon Lnc-leptin knockdown. Our study establishes Lnc-leptin as a new regulator of

Leptin.

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Introduction

Obesity has reached an epidemic level worldwide (1). Central to the obesity problem is adipocytes, which

play a dual role of storing excess energy as triglycerides and secreting adipokines that exert systemic

effects on metabolic homeostasis (2). Governing adipose tissue function is a set of expressed transcripts

and proteins, many of which are dysregulated upon obesity. In order to discover novel obesity genes,

transcriptome analysis has been extensively carried out in both mouse and human adipose tissues (3–7),

but most studies have primarily focused on protein-coding genes. Long non-coding RNAs (lncRNAs) are

relatively new players in the field of gene regulation (8, 9). We and others have shown that lncRNAs are

essential regulators of adipogenesis, insulin sensitivity and thermogenesis (10–12). Using RNA-

Sequencing on three types of mouse adipose tissues, namely inguinal white adipose tissue (iWAT),

epididymal white adipose tissue (eWAT) and interscapular brown adipose tissue (BAT), and followed by

de novo transcriptome assembly, we have built a catalogue of over 1500 mouse adipose lncRNAs (13).

Recently, another catalogue of lncRNAs regulating energy metabolism in liver, adipose tissue and muscle

has been built based on microarray data (14).

Mutation in Lep, a circulating adipokine released from adipocytes, leads to an extreme form of

obesity, exemplified by the ob/ob mice (15). A few cases of obese human patients harboring Lep mutation

have been reported, and such patients are responsive to recombinant LEP treatment (16)(17). There is a

great interest in understanding the regulation of the leptin gene. Using leptin-BAC EGFP transgenic mice,

a region 4.5kb upstream of Lep has been found to act as an adipocyte-specific enhancer, and this region

was bound by the transcription factor FOSL2 (18). A similar strategy reveals a totally different element

required for Lep expression in vivo: it is a nuclear-factor Y-bound element -16.5kb upstream of the Lep

transcription start site (19).

To systemically evaluate the changes of lncRNA transcriptome upon obesity, we performed RNA-

Seq on adipocytes isolated BAT, iWAT and eWAT from control and diet-induced obese mice. We

identified 68 lncRNAs that are differentially expressed upon obesity, termed as lnc-ORIAs (obesity-

regulated lncRNAs in adipocytes). Specifically, we focused on one particular lnc-ORIA, Lnc-leptin, which

is located in an enhancer region upstream of Lep and highly correlates to the expression of Lep. Using

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multiple independent loss-of-function approaches, we show that Lnc-leptin regulates the expression of

Lep in vitro and in vivo.

Research Design and Methods

Diet-induced obesity models

Male mice on the C57BL/6 background were kept at the Duke-NUS animal facilities. Mice were fed

regular chow diet or high fat diet (Research Diets, #D12492) for 16 weeks commenced upon weaning at 3

weeks of age.

Primary adipocyte culture and differentiation

Inguinal fat pads from 3-week-old C57BL/6 pups were excised, minced and digested in collagenase

solution at 37ºC for 20min. The suspension was filtered through 100µm strainers and spun at 2000rpm for

5min. The pelleted stromal vascular fraction was resuspended in 10ml of Dulbecco’s modified Eagle’s

medium (DMEM) supplemented with 10% new calf bovine serum (Invitrogen), 100 units/ml penicillin,

100µg/ml streptomycin and 10 µg/ml of gentamicin (Invitrogen). Cells were grown to confluence, and

differentiation was initiated at Day0 with DMEM containing 10% fetal bovine serum (FBS), 0.5µM

dexamethasone, 850nM insulin, 0.25mM 3-isobutyl-1-methyxanthine and 1µM rosiglitazone for 2 days.

Cells were then incubated in DMEM containing 10% FBS and 170 nM insulin for 2 more days. After Day 4,

cells were maintained for two more days in DMEM containing 10% FBS. Experiments were performed on

mature adipocytes at Day 6.

Adipocytes and stromal vascular fraction (SVF) isolation from adipose tissue

Adipose tissues were excised from mice and immediately minced in a collagenase solution comprising

0.2% collagenase (C6885, Sigma) and 2% BSA dissolved in Hanks’ balanced salt solution (HBSS, Gibco).

Minced tissues were transferred to a 50ml tube and incubated at 37ºC for 20min (for EPI and ING) or

40min (for BAT) at 500rpm. 10ml complete DMEM was subsequently added. Cell resuspensions were

filtered through 100µm strainers, spun at 2000rpm for 5min, and washed once with PBS. The floating

adipocyte layer and the pelleted SVF fraction were collected separately. The SVF fraction was treated

with ammonium chloride solution (STEMCELL, # 07800) to lyse red blood cells.

Lnc-leptin knockdown using shRNAs

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Sequences targets Lnc-leptin were cloned into a retroviral vector pSUPER (oligoengine). shRNA

sequences are listed in Supplemental Table 4. Retroviral vectors were transfected into packaging cell line

293T cells using XtremeGENE 9 (Roche). Viruses-containing media were harvested 48h later post-

transfection and were used to infect primary preadipocytes at ~60% confluence supplemented with

8µg/ml polybrene. Media were changed the next day and cells were induced to differentiate 48h post

infection.

Lnc-leptin knockdown using DisRNAs or antisense oligos (ASOs) in vitro

For knocking down Lnc-leptin in preadipocytes to assess its role in adipogenesis, DsiRNA or ASO and

their respective controls were transfected into Day -2 preadipocytes (> 90% confluence) using

lipofectamine (6ul/ml, Life Technology). Media were changed the next day and cells were induced to

differentiate 48h post transfection. For knocking down Lnc-leptin in primary mature adipocytes, a reverse

transfection protocol was used (35). 200nM of DsiRNA (IDT) or 150nM of antisense oligos (Gapmers,

Exiqon) mixed with lipofectamine in Opti-MEM medium (6ul/ml) were added to each well of a 24-well plate

pre-coated with 0.1% gelatin. Mature primary adipocytes at Day6 were trypsinsed and reseeded onto the

oligo-lipofectamine mix. Medium was changed the next day and knockdown efficiency was measured 48h

post-transfection. Sequences of DsiRNAs and antisense oligos used in this study are listed in

Supplemental Tables 5 and 6 respectively.

Lnc-leptin knockdown using antisense oligos (ASOs) in vivo

8-12 week-old C57BL/6 male mice were anesthetized. Hair located at the inguinal area was removed with

a trimmer, the underlying skin was incised, and the inguinal adipose tissue exposed. Control ASO or ASO

Lnc-leptin (20mg/kg) were injected into the left and right inguinal adipose tissue (~50ul/injection),

respectively. The surgical wounds were closed with sutures and disinfected with 70% ethanol. Adipose

tissues from both sides of the inguinal depot were excised 48h post-injection and RNA was extracted and

subjected to reverse transcription qPCR.

Chromatin Immunoprecipitation (ChIP)

Preadipocytes or mature adipocytes were trypsinized and resuspended in PBS. A two-step crosslinking

protocol was used (44): Cells were incubated with 1.5mM of ethylene glycol-bis (EGS, Sigma) at room

temp for 30min, it was followed by 1% formaldehyde for 10min. Crosslinking was stopped by quenching

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with 0.125M of glycine. ChIP experiment was performed as described (45). 5ug of Med1 antibody (Bethyl

Laboratories, A300-793A) was used for immunoprecipitation, normal rabbit IgG (Santa Cruz

Biotechnology, sc-2027) was used as control. ChIP primers used in this study are listed in Supplemental

Table 7.

Chromatin conformation capture (3C)

3C was performed as described previously (46) with modifications. Briefly, mouse adipose cells and

tissues were cross-linked with 1% formaldehyde for 10 mins and the reaction was quenched by 125mM

glycine for 5mins. Lysed nuclei were resuspended in 500 µl of 1.2 x restriction enzyme buffer before

incubation at 65°C for 20 min with 22.5 µl of 20% SDS, followed by additional 1 hr incubation at 37°C.

Then, 150 µl of 20% Triton X-100 was added and samples were incubated at 37°C for other 1 hr.

Samples were then digested with 800 units of XbaI (NEB) by incubating at 37°C overnight. After

restriction enzyme digestion, 40 µl of 20% SDS was added to the digested nuclei and incubated at 65°C

for 15 min. 6.125 ml of 1.15x ligation buffer and 375 µl 20% Triton X-100 was added to dilute the total

DNA to favour intramolecular ligation. The diluted sample was incubated at 37°C for 1 hr before the

addition of 100 units of T4 DNA ligase (NEB) at 16°C for 4 hr followed by 30min at room temperature.

Samples were finally de-crosslinked at 65°C overnight with addition of 300 µg of proteinase K (Thermo

Scientifics) before phenol-chloroform extraction and ethanol precipitation. Samples were further purified

by QIAquick spin columns (Qiagen) and total DNA concentration quantified using Nanodrop. BAC that

spans the whole locus of interest is: RP24-369M21. All primers were designed to be within a region of

25-150 bp from the restriction enzyme digestion site and are unidirectional from the 5’ side of the

restriction fragment. Primers were designed using Primer3 software listed in Supplemental Table 8.

Quantitative real time PCR was carried out with SYBR green master mix on the ABI Vii7. Semi-

quantitative PCR of these primers pairs using the control template re-confirmed that there was only a

single PCR product of the correct size when visualized on a 2% agarose gel. The identities of the PCR

products were also confirmed through direct sequencing. To obtain data points for “normalized relative

interaction” in the final results, Ct values of 3C template were first normalized with values from an

internal primer of “control interaction frequencies”, which was commonly used Ercc3 locus in mouse (46,

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47). Each qPCR was carried out in duplicates and 3C validations were repeated between four to six

times independently for each condition.

Hierarchical clustering

Clustering was done in Cluster and visualized in Treeview. For each model and for each gene, the gene

expression value in fpkm was log transformed and mean-centered before clustering.

Western Blot and Realtime PCR

Antibodies used for Western: Leptin (Abcam: Ab16227), Pparg (Santa Cruz, sc-7273) and β-actin

antibody (Sigma A1978, 43kD) as loading control. Total RNA was extracted using Qiagen kit. Sequences

of qPCR primers are listed on Supplemental Table 3.

RNA-Seq library preparation, sequencing, and analysis

1ug of total RNA was used for each RNA-Seq library preparation according to the manufacturer's

instructions (New England Biolab), and sequencing was done on HiSeq 2000 (Illumina). Pair-end reads

from each sample were aligned to the mouse genome (mm10 build) using TopHat (version 2.0.9).

Differential expression between high-fat diet and normal chow samples was quantified using Cuffdiff

(version 2.1.1). Differentially expressed genes are those that have a log2 fold change of > 1 or < -1 and a

q-value < 0.05 when compared to the control condition. We also required that the differentially expressed

genes used for downstream analysis have a FPKM greater than 1 in any of the condition.

Gene Ontologies and pathway analysis

For obesity-induced protein-coding genes, gene ontology and network analysis was performed using

GeneGo (Thomson Reuters). For obesity-induced lncRNAs, gene ontology and motif analysis was done

using GREAT (Genomic Regions Enrichment of Annotations Tools) (25).

Study Approval

All studies involving animals have been approved by the institutional review board in Duke-NUS.

Results

Transcriptome analysis of adipocytes from three different adipose depots identified a set of

obesity-regulated lncRNAs (lnc-ORIAs)

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To systemically evaluate the changes of adipocyte lncRNA transcriptome during obesity, we isolated

adipocytes from BAT, inguinal WAT and epididymal WAT of mice on a high-fat diet (HFD) or a normal

chow diet (ND) using a collagenous digestion and fractionation method (Figure 1A). As adipose tissue is

infiltrated with macrophages and other immune cells upon obesity (20), this step enriches for adipocytes

and minimizes the contribution from the other cell types. Leptin (Lep), an adipocyte-specific gene, was

enriched over hundred folds in the floating adipocyte layer compared to the pelleted stromal vascular

fraction (SVF) (Figure 1B). In contrast, expression of the macrophage marker F4/80 (Emr1) was highly

enriched in SVF compared to adipocytes (Figure 1B). Lineage marker expression such as Hoxc9, Hoxc10

and Ucp1 both before and after collagenous digestion indicated that our brown adipose tissue and

isolated adipocytes were not contaminated by each other (Figure 1S).

We performed RNA-Seq on adipocytes isolated from three different adipose depots (BAT, ING

and EPI) under two different diets (HFD vs ND). Over 200 million paired-end reads in total were aligned

(Supplemental Table 1) to Ensembl protein-coding genes (mm10) and a published adipose lncRNA

catalogue (13). To assess if obesity affects global mRNA and lncRNA transcriptomes in a similar manner,

we performed unsupervised hierarchical clustering on the sets of expressed mRNAs and lncRNAs

(FPKM > 1), respectively. The main branch of the dendrogram, with the exception of BAT that only has

one data set per condition, primarily separates all samples based on diet rather than sites of origin in both

mRNA and lncRNA clustering (Figure 1C). There are 353 protein-coding genes differentially expressed in

adipocytes from the three different depots upon obesity (Figure 1D). They include Lep (15), Sfrp5 (21)

and Egr1 (22); many of which have previously been identified and studied in the context of obesity.

Network analysis of the obesity-upregulated genes using GeneGo which incorporates curated data from

published literature identified the NF-κB subunit RelA, Esr1 and Creb1 to be the top three transcription

factor hubs (Figure S2A) mediating the expression changes. Gene ontology (GO) analysis identified

developmental processes (p<1E-17), response to stress (p<9E-14) and cell differentiation (p<3E-11) as

the top categories associated with the obesity-upregulated protein-coding genes (Figure S2B). These

processes, together with the transcription factors NF-κB, Esr1 and Creb1, have been implicated in

previous studies (23, 24), indicating that our data do reflect biological changes of adipocytes during

obesity.

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Compared to protein-coding genes, less is known about adipocyte lncRNA changes upon obesity.

Our data indicates that 68 lncRNAs are significantly differentially expressed between normal chow and

high-fat diet in at least two of the three types of adipocytes that we profiled (Figure 1D). We termed them

obesity-regulated lncRNAs in adipocytes (lnc-ORIAs, Supplemental Table 2). Many of them display

adipocyte-specific expression (Figure 1E & Figure S3). Using the software GREAT (Genomic Regions

Enrichment of Annotations Tool) that infers function of genomic regions based on the ontology

annotations of their neighboring protein-coding genes (25), we found that activation of JNK kinase activity

is the only significant (pval < 1E-6) GO category associated with the obesity-induced lncRNAs (Figure 1F).

Furthermore, the C/EBPβ motif was found to be enriched from this group of induced lncRNA genes

(Figure S1C). JNK has been shown to have a central role in obesity (26), while C/EBPβ has recently been

implicated in adipose insulin resistance (27). Together, our data suggests that meaningful biological

insight could be gleaned from transcriptome analysis of lncRNAs, and lncRNAs could be important

regulators of obesity.

Many lnc-ORIAs are regulated in various metabolic conditions and bound by PPARG

To confirm the expression changes of the lnc-ORIAs that we identified from our high-throughput RNA-Seq,

we isolated RNA from independent cohorts of control and high fat diet-fed mice, and we confirmed the

expression changes of 10 selected lnc-ORIAs based on their expression values, fold changes and gene

structures (Figure 2A). Out of the 10 lnc-ORIAs chosen based on their higher expression level and

unambiguous gene structure, 9 were induced upon obesity and 1 was repressed (Lnc-ORIA1). The

expression changes generally occurred in all the three tissues profiled, though tissue-specific differences

exist (e.g.Lnc-ORIA6). To test whether the changes of these lncRNAs are a general feature in other

obesity models, we examined their expression in adipose tissue from ob/ob and control mice and found

that the expression of all 10 lnc-ORIAs change in the same direction as that in diet-induced obesity, with

8 reach significant level (Figure S4).

To investigate if these selected lnc-ORIAs are responsive to alteration of nutritional status, we

measured their expression in adipose tissue of ad libitum mice (fed) and mice underwent an overnight

fast (fasted). 9 of 10 of these targets (except Lnc-ORIA7) have significant decreased expression in the

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different adipose tissues upon fasting (Figure 2B). Fasting and diet-induced obesity represents two

extremes of nutritional spectrum, one being an acute nutrient-deprived state and the other a chronic

nutrient-excess state. The majority of the lncRNAs examined display an inverse correlation pattern of

expression in these two conditions (Figure 2C), suggesting that these lnc-ORIAs could be molecular

sensors reflecting the energy status in adipose tissue.

Previous studies have shown that tissue- or condition-specific lncRNAs, similar to protein-coding

genes, are often bound and regulated by key transcription factors. Using published PPARG ChIP-Seq

data from mouse white and brown adipose tissue (28), we found that half of the 10 lnc-ORIAs that we

studied are bound by PPARG at their promoters (3 are shown in Figure 2D), suggesting that many of

these lnc-ORIAs are transcriptionally regulated by PPARG in vivo.

Lnc-leptin is an enhancer lncRNA

We are particularly intrigued by Lnc-ORIA9, hereafter we named Lnc-leptin, which lies 28kb upstream of

Lep, a satiety hormone secreted by adipocytes that acts centrally to regulate systemic metabolism and

immunity (17). Lnc-leptin has 2 exons, and it overlaps largely with an uncharacterized known transcript

Gm30838, which shares the same splice sites as Lnc-leptin (Figure 3A). The promoter of Lnc-leptin has

an open chromatin conformation as shown by published DNase-Seq data. There is positive H3K4

trimethylation (H3K4Me3) signal and RNA Polymerase II binding at the transcription start site of Lnc-leptin

as shown by published ChIP-Seq data (Figure 3B and Figure S5A), indicating that this gene is actively

transcribed in adipose tissue. Lnc-leptin also harbors positive H3K4 methylation 1 (H3K4Me1) and H3K27

acetylation (H3K27Ac) marks in white adipose tissue (Figure 3B); these histone modifications typically

associate with enhancers (H3K4Me1) and active enhancers (H3K27Ac) (29). Similar histone modification

architecture in this region was also observed in BAT (Figure S5B). Furthermore, to test whether the Lnc-

leptin region is associated with MED1, a component of the Mediator complex known to bridge enhancer

regions with the general transcription machinery and RNA Pol II at gene promoters (30), we performed

chromatin immunoprecipitation (ChIP) experiment in differentiated white primary adipocyte culture (Figure

3C). Because Lnc-leptin is undetectable in brown adipocytes culture, the ChIP experiment was only

performed in differentiated white primary adipocytes. Our ChIP result indicates that MED1 is recruited to

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the promoter regions of Lnc-leptin and Lep (Figure 3C). Taken together, Lnc-leptin is transcribed from an

enhancer near Lep and is an enhancer lncRNA.

Expression of Lnc-leptin is highly correlated to that of Lep

Next, we investigated the spatial and temporal expression of Lnc-leptin. Using mouse SVF-derived

primary adipocyte culture, we found that expression of Lnc-leptin increases gradually as differentiation

progresses, in a similar manner as Lep and Pparg (Figure 4A). To assess if the expression of Lnc-leptin is

specific to adipose tissue, we measured its expression in 20 different mouse tissues, and we found that it

is highest in epididymal white fat, followed by inguinal white fat and interscapular brown fat. It is also

expressed, albeit at a much lower level, in testicle and eye (Figure 4B). Interestingly, the tissue specific

expression of Lnc-leptin highly mirrors that of Lep (Figure 4B). To examine if the expression of these two

genes are correlated, we plotted the expression of Lnc-leptin and Lep across a variety of conditions

including HFD vs ND (n=45), ob/ob vs wildtype (n=9), fasted vs fed (n=42) in mouse adipose tissues. A

very tight correlation (r>0.76) was found between the expression of Lnc-leptin and Lep in all examined

conditions (Figure 4C). To further assess whether Lnc-leptin and Lep respond to hormonal signaling in a

similar manner, we treated differentiated primary adipocytes with different agents that are known to alter

the expression of Lep. Acute insulin stimulation induced Lep expression (31, 32); we found that such

increase was accompanied by an induction of Lnc-leptin (Figure 4D). Conversely, upon TNFα and

norepinephrine treatment where Lep was repressed (33, 34), Lnc-leptin expression was concomitantly

reduced (Figures 4E and 4F). Taken together, we have demonstrated a close correlation between the

expression of Lnc-leptin and Lep, pointing to a potential causative relationship between them.

Lnc-leptin is required for adipogenesis

To investigate the role of Lnc-leptin during adipogenesis, we employed two independent strategies to

knock it down in primary adipocyte cultures: short hairpin RNAs (shRNA) and Dicer-substrate short

interfering RNA (DsiRNA). First, we infected primary white preadipocytes with retrovirus harboring control

shRNA or shRNA constructs targeting Lnc-leptin. Cells were then differentiated as per normal, and RNA

was harvested at Day6 post differentiation. Lnc-leptin knockdown using 2 different shRNA constructs led

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to more than 80% reduction of the gene (Figure 5A). Furthermore, it almost completely blocked adipocyte

differentiation: oil red O staining shows there was very little lipid accumulation in the knockdown cells

compared to the control (Figure 5B). This defect was accompanied by a reduction in Lep and the

adipocyte-markers Pparg and Adipoq (Figure 5C). Similar results were obtained when Lnc-leptin was

knocked down in preadipocytes by DsiRNA (Figure 5D). These results suggest that Lnc-leptin is required

for adipogenesis.

Lnc-leptin regulates the expression of Lep in mature adipocytes

Depletion of Lnc-leptin during adipogenesis results in severe inhibition of cell differentiation that can

indirectly block Lep expression, so it is unclear whether Lnc-leptin can directly affect Lep expression. To

test this, we knocked down Lnc-leptin in mature adipocytes. Primary white preadipocytes were

differentiated into mature adipocytes and DsiRNAs or Antisense oligos (ASOs) were transfected into the

cells using a reverse transfection protocol (35). Both methods resulted in more than 80% reduction in

Lnc-leptin expression (Figures 5E and 5F), and both were accompanied by a concomitant reduction of

Lep expression. Interestingly, the expression of two mature adipocyte markers, Pparg and Adipoq were

also significantly reduced upon Lnc-leptin knockdown, but the extent of reduction is less. To test if

knocking down Lnc-leptin would affect Lep expression in vivo, we injected ASO against Lnc-leptin directly

into one side of mouse inguinal tissue, with the contralateral side injected with a scrambled control.

Tissues were harvested 2 days later for expression analysis. Both Lnc-leptin and Lep expression were

significantly reduced upon ASO injection (Figure 5G), and such decrease was accompanied by a less

significant reduction in Lep and Pparg mRNA (Figure 5G). Importantly, Lnc-leptin knockdown led to a

decrease in LEP but not PPARG protein expression (Figure 5H), arguing that the reduction of LEP protein

is not due to a decreased PPARG protein level. Taken together, we show that knocking down Lnc-leptin

affects Lep expression in mature adipocytes both in vitro and in vivo.

To test whether Lnc-leptin is sufficient to promote Lep expression, we used retroviral vector to

overexpress Lnc-leptin in primary white adipocyte culture. Overexpression of Lnc-leptin did not promote

the expression of Lep or other adipocyte markers (Figure S6). Thus, Lnc-leptin is necessary, but not

sufficient to promote Lep expression or adipogenesis.

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Lnc-leptin mediates a loop formation between genomic loci of Lep and Lnc-leptin

Studies above demonstrate that Lnc-leptin is transcribed from an enhancer region and positively

regulates the expression of Lep. A common mechanism used by many enhancers is to form a long-

distance interaction with the promoter of their target genes to facilitate transcription by recruiting positive

regulators. We hypothesize that Lnc-leptin may be involved in such interaction near the Lep promoter. To

test if there is any long-range chromatin interaction between the genomic loci of Lnc-leptin and Lep,

chromatin conformation capture (3C) experiments were performed to interrogate the chromatin structure

around these two genes (Figure 6A). Using the promoter of Lep as an anchoring point, the genomic locus

encompasses exon2 of Lnc-leptin was found to interact with Lep promoter (Figure 6B). The 3C ligated

fragment was sequenced to confirm that it is indeed a hybrid product ligated from the two separate

genomic regions. This interaction was attenuated upon knocking down of Lnc-leptin (Figure 6C),

indicating that Lnc-leptin is required for the looping event. We propose that Lnc-leptin is a novel enhancer

lncRNA that regulates Lep expression by bringing Lep with its upstream enhancer and the transcriptional

machinery to close proximity (Figure 6D).

Discussion

Whole-genome sequencing efforts in the past two decades have revolutionized our understanding of the

mammalian genome: it is now recognized that the mammalian genome is pervasively transcribed to

generate thousands of non-coding RNA species including lncRNAs (36). Several lncRNAs have been

shown to play key roles in regulating energy metabolism (37). Here, we systemically profiled lncRNAs in

three different types of adipocytes in diet-induced obese mice and identified 68 regulated lncRNAs,

termed as lnc-ORIAs (obesity-regulated lncRNAs in adipocytes). Among the lnc-ORIAs, we focused on

Lnc-leptin because of its proximity to Lep. The local genomic structure and histone modification patterns

of Lnc-leptin are reminiscent of those of a typical enhancer. However, in contrast to the neuronal

enhancer RNAs (eRNAs) which are generally unspliced and lack polyadenylated tails (38), Lnc-leptin was

identified through polyA tail-enriched RNA-Seq and consists of 2 exons. It also differs from the

bidirectional enhancer-derived transcripts (39) as our directional RNA-Seq did not detect any transcript

coming out from the opposite direction (Figure 2D).

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Knockdown experiments using DsiRNA and ASO indicate that knocking down Lnc-leptin leads to a

concomitant reduction in Lep expression both in vitro and in vivo (Figure 5), suggesting that it is the RNA

transcript itself, rather than the act of transcription, which confers the lncRNA’s function. Lnc-Leptin

positively regulates the expression of Lep, similar to those lncRNAs that activate the expression of their

neighboring protein-coding genes (40–42). We showed by 3C experiment that Lnc-leptin is likely to be

required for chromatin interaction between exon2 of Lnc-leptin and the promoter of Lep (Figure 6). This

putative interaction brings the two genes in close proximity in a 3 dimensional space that potentially

enhance the expression of Lep (Figure 6). In our proposed model (Figure 6D), the Lnc-leptin transcript

acts as a bridge to enhance the interaction between the Lep promoter and enhancer: it could directly

interact with Lep promoter or merely serve as a scaffold to bring transcription factors and histone

modifying proteins together. We acknowledge that many details about the mechanism remain

unanswered. For example, we do not know what proteins Lnc-leptin directly interact with, whether Lnc-

leptin forms a RNA-DNA duplex directly with the enhancer or the promoter (or both), whether Lnc-leptin

can interact with other DNA segments. Those questions warrant further investigation in future studies.

It is noteworthy that the regulatory mechanism of Lnc-leptin on Lep may not account for its effects

on adipogenesis. Knockdown of Lnc-leptin during adipogenesis resulted in a severe reduction of lipid

accumulation and expression of mature adipocytes markers (Figure 5A-D). Because the formation of

mature adipocytes in ob/ob mice is not impaired, we believe that Lnc-leptin may employ a LEP-

independent mechanism in regulating adipogenesis, which warrant further investigation. In mature

adipocytes, knocking down Lnc-leptin seem to reduce the expression of adipocyte markers Pparg and

Adipoq, in addition to Lep. How such reduction occurs remains to be answered.

In two previous studies, the genomic region of Lnc-leptin was not identified as a cis-regulatory

element that regulates the adipose-specific expression of Lep. Both studies used BAC transgenic reporter

mice to identify the cis- and trans-regulatory elements of Lep in vivo. Wrann et al. identified a region

containing the three Lep exons, both introns, and 5.2kb of 5’ flanking sequence was sufficient to drive

adipocyte-specific EGFP expression(18), while Lu et al. identified a region -22kb to +8.8kb of Lep as the

region required for adipose-specific Lep expression (19). Both studies excluded the genomic location of

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Lnc-leptin, which lies ~28kb upstream of Lep. It is plausible that Lnc-leptin is not primarily involved in the

basal expression of Lep but instead serves as a metabolic sensor to regulate the expression of Lep upon

different energy statues in adipocytes. For a very dynamically regulated gene such like Lep, its regulation

is likely to be controlled by the coordination of multiple regulatory mechanisms. Our study reveals a new

layer of regulatory complexity, while earlier studies(18)(19) identified several cis and trans regulatory

factors. These layers of regulation are not mutually exclusive but are all orchestrated by the cellular

energy status. They together weave a sophisticated network to rapidly adjust Lep expression to respond

to the nutritional level alternation.

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16

Article information

Funding. This work was supported by Singapore NRF fellowship (NRF-2011NRF-NRFF 001-025) and

Tanoto Initiative in Diabetes Research to L.S. This research was supported by the Singapore National

Research Foundation under its CBRG grant (NMRC/CBRG/0070/2014 and NMRC/CBRG/0101/2016),

Open Fund - Individual Research (OF-IRG) Grant (NMRC/OFIRG/0062/2017) and Ministry of

Education (MOE) Tier2 grant (MOE2017-T2-2-009). This work was supported by the RNA Biology

Center at CSI Singapore, NUS, from funding by the Singapore Ministry of Education’s Tier 3 grants,

grant number MOE2014-T3-1-006. M.H.L and S.H are supported by an NMRC–Cooperative Basic

Research Grant (NMRC-CBRG) New Investigator Grant (NMRC/BNIG/2027/2015).

Duality of interest. No potential conflicts of interest relevant to this article were reported.

Author contributions. K.A.L, S.Q.H, A.C.E.W, M.H.L, Z.Z, M.K.L performed the experiments and

analyzed the data. K.A.L and L.S designed the project, interpreted the data and wrote the manuscript. L.S

is the guarantor of this manuscript.

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References

1. Haslam DW, James WPT. Obesity. [Internet]. Lancet 2005;366(9492):1197–209.

2. Rosen ED, Spiegelman BM. What we talk about when we talk about fat.. Cell 2014;156(1-2):20–44.

3. Morton NM et al. A stratified transcriptomics analysis of polygenic fat and lean mouse adipose tissues identifies novel candidate obesity genes. [Internet]. PLoS One 2011;6(9):e23944.

4. Tam CS et al. An early inflammatory gene profile in visceral adipose tissue in children. [Internet]. Int. J. Pediatr. Obes. 2011;6(2-2):e360–3.

5. Rodríguez-Acebes S et al. Gene expression profiling of subcutaneous adipose tissue in morbid obesity using a focused microarray: distinct expression of cell-cycle- and differentiation-related genes. [Internet]. BMC Med. Genomics 2010;3(1):61.

6. Grove KL, Fried SK, Greenberg AS, Xiao XQ, Clegg DJ. A microarray analysis of sexual dimorphism of adipose tissues in high-fat-diet-induced obese mice. [Internet]. Int. J. Obes. (Lond). 2010;34(6):989–1000.

7. Kogelman LJA et al. Identification of co-expression gene networks, regulatory genes and pathways for obesity based on adipose tissue RNA Sequencing in a porcine model. [Internet]. BMC Med. Genomics 2014;7(1):57.

8. Rinn JL, Chang HY. Genome regulation by long noncoding RNAs. [Internet]. Annu. Rev. Biochem. 2012;81:145–66.

9. Fatica A, Bozzoni I. Long non-coding RNAs: new players in cell differentiation and development. [Internet]. Nat. Rev. Genet. 2014;15(1):7–21.

10. Sun L et al. Long noncoding RNAs regulate adipogenesis. [Internet]. Proc. Natl. Acad. Sci. U. S. A. 2013;110(9):3387–92.

11. Zhao X-Y, Li S, Wang G-X, Yu Q, Lin JD. A long noncoding RNA transcriptional regulatory circuit drives thermogenic adipocyte differentiation. [Internet]. Mol. Cell 2014;55(3):372–82.

12. Xu B et al. Multiple roles for the non-coding RNA SRA in regulation of adipogenesis and insulin sensitivity. [Internet]. PLoS One 2010;5(12):e14199.

13. Alvarez-Dominguez J et al. De novo Reconstruction of Adipose Tissue Transcriptomes Reveals Novel Long Non-coding RNAs that Regulate Brown Adipocyte Development. Cell Metab. 2015;Resubmitte.

14. Yang L et al. Integrative Transcriptome Analyses of Metabolic Responses in Mice Define Pivotal LncRNA Metabolic Regulators [Internet]. Cell Metab. 2016;24(4):627–639.

15. Zhang Y et al. Positional cloning of the mouse obese gene and its human homologue.1. Zhang Y, Proenca R, Maffei M, Barone M, Leopold L, Friedman JM. Positional cloning of the mouse obese gene and its human homologue. Nature [Internet] 1994 [cited 2015 Jan 7]; 372:425–32 [Internet]. Nature 1994;372(6505):425–32.

16. Wabitsch M et al. Biologically Inactive Leptin and Early-Onset Extreme Obesity. [Internet]. N. Engl. J. Med. 2015;372(1):48–54.

17. Friedman J. Leptin at 20: An overview. J. Endocrinol. 2014;223(1):T1–T8.

18. Wrann CD et al. FOSL2 promotes leptin gene expression in human and mouse adipocytes. [Internet]. J. Clin. Invest. 2012;122(3):1010–21.

19. Lu YH, Dallner OS, Birsoy K, Fayzikhodjaeva G, Friedman JM. Nuclear Factor-Y is an adipogenic

of 46 Diabetes

18

factor that regulates leptin gene expression [Internet]. Mol. Metab. 2015;4(5):392–405.

20. Weisberg SP et al. Obesity is associated with macrophage accumulation in adipose tissue. J. Clin. Invest. 2003;112(12):1796–1808.

21. Mori H et al. Secreted frizzled-related protein 5 suppresses adipocyte mitochondrial metabolism through WNT inhibition2012;122(7). doi:10.1172/JCI63604DS1

22. Yu X et al. Egr-1 decreases adipocyte insulin sensitivity by tilting PI3K/Akt and MAPK signal balance in mice. [Internet]. EMBO J. 2011;30(18):3754–3765.

23. Manrique C et al. Loss of Estrogen Receptor α Signaling Leads to Insulin Resistance and Obesity in Young and Adult Female Mice. [Internet]. Cardiorenal Med. 2012;2(3):200–210.

24. Qi L et al. Adipocyte CREB Promote insulin resistance in Obesity. Cell Metab. 2010;9(3):277–286.

25. McLean CY et al. GREAT improves functional interpretation of cis-regulatory regions. [Internet]. Nat. Biotechnol. 2010;28(5):495–501.

26. Hirosumi J et al. A central role for JNK in obesity and insulin resistance.. Nature 2002;420(6913):333–336.

27. Lo KA et al. Analysis of in vitro insulin-resistance models and their physiological relevance to in vivo diet-induced adipose insulin resistance. [Internet]. Cell Rep. 2013;5(1):259–70.

28. Rajakumari S et al. EBF2 Determines and Maintains Brown Adipocyte Identity [Internet]. Cell Metab. 2013;17(4):562–574.

29. Creyghton MP et al. Histone H3K27ac separates active from poised enhancers and predicts developmental state. [Internet]. Proc. Natl. Acad. Sci. U. S. A. 2010;107(50):21931–21936.

30. Allen BL, Taatjes DJ. The Mediator complex: a central integrator of transcription. [Internet]. Nat. Rev. Mol. Cell Biol. 2015;16(3):155–166.

31. Buyse M, Viengchareun S, Bado a, Lombès M. Insulin and glucocorticoids differentially regulate leptin transcription and secretion in brown adipocytes.. FASEB J. 2001;15:1357–1366.

32. Lee KN, Jeong IC, Lee SJ, Oh SH, Cho MY. Regulation of leptin gene expression by insulin and growth hormone in mouse adipocytes.. Exp. Mol. Med. 2001;33(4):234–9.

33. Gettys TW, Harkness PJ, Watson PM. The beta 3-adrenergic receptor inhibits insulin-stimulated leptin secretion from isolated rat adipocytes. [Internet]. Endocrinology 1996;137(9):4054–7.

34. Ruan H, Hacohen N, Golub TR, Van Parijs L, Lodish HF. Tumor necrosis factor-alpha suppresses adipocyte-specific genes and activates expression of preadipocyte genes in 3T3-L1 adipocytes: nuclear factor-kappaB activation by TNF-alpha is obligatory. [Internet]. Diabetes 2002;51(5):1319–36.

35. Isidor MS et al. An siRNA-based method for efficient silencing of gene expression in mature brown adipocytes [Internet]. Adipocyte 2015;3945(NOVEMBER):00–00.

36. Birney E et al. Identification and analysis of functional elements in 1% of the human genome by the ENCODE pilot project. [Internet]. Nature 2007;447(7146):799–816.

37. Kornfeld J-W, Brüning JC. Regulation of metabolism by long, non-coding RNAs. [Internet]. Front. Genet. 2014;5(March):57.

38. Kim T-K et al. Widespread transcription at neuronal activity-regulated enhancers [Internet]. Nature 2010;465(7295):182–187.

of 46Diabetes

19

39. Andersson R et al. An atlas of active enhancers across human cell types and tissues [Internet]. Nature 2014;507(7493):455–461.

40. Ørom UA et al. Long noncoding RNAs with enhancer-like function in human cells. [Internet]. Cell 2010;143(1):46–58.

41. Trimarchi T et al. Genome-wide mapping and characterization of notch-regulated long noncoding RNAs in acute leukemia [Internet]. Cell 2014;158(3):593–606.

42. Hsieh C-L et al. Enhancer RNAs participate in androgen receptor-driven looping that selectively enhances gene activation. [Internet]. Proc. Natl. Acad. Sci. U. S. A. 2014;111(20):7319–24.

43. Lo KA, Ng PY, Kabiri Z, Virshup D, Sun L. Wnt inhibition enhances browning of mouse primary white adipocytes2016;3945(May). doi:10.1080/21623945.2016.1148834

44. Zeng PY, Vakoc CR, Chen ZC, Blobel G a., Berger SL. In vivo dual cross-linking for identification of indirect DNA-associated proteins by chromatin immunoprecipitation. Biotechniques 2006;41(6):694–698.

45. Lo KA et al. Genome-Wide Profiling of H3K56 Acetylation and Transcription Factor Binding Sites in Human Adipocytes [Internet]. PLoS One 2011;6(6):12.

46. Hagège H et al. Quantitative analysis of chromosome conformation capture assays (3C-qPCR).. Nat. Protoc. 2007;2:1722–1733.

47. Medvedovic J et al. Flexible Long-Range Loops in the VH Gene Region of the Igh Locus Facilitate the Generation of a Diverse Antibody Repertoire. Immunity 2013;39(2):229–244.

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Figure legends

Figure 1. Adipocyte lncRNA transcriptomes reveal meaningful insights of diet-induced obesity

(A) Study schematics: C57BL/6J male mice were put under normal control chow (ND) or high-fat diet

(HFD) for 16 weeks after weaning at 3 weeks. Adipocytes were isolated from interscapular brown adipose

tissue (BAT), inguinal (ING) and epididymal (EPI) adipose tissues by collagenase digestion and

centrifugation. RNA was extracted from the floating adipocyte layer and subjected to high-throughput

RNA-Seq.

(B) qPCR analysis of an adipocyte-specific gene (Lep) and a macrophage marker (Emr1) on isolated

adipocytes and pelleted stromal vascular fraction (SVF). For both genes, the expression in the different

adipose tissues or different fraction was normalized to that in BAT adipocyte, which has a value of 1.

Comparison was made between adipocyte and SVF in the HFD condition (n=4-6). Expression differences

of adipocyte and SVF under ND were also significant but not shown. All data are presented as mean ±

SEM. * p < 0.05, ** p< 0.01 and *** p< 0.001 comparing with the control condition using 2-tailed Student’s

t tests.

(C) Unsupervised hierarchical clustering of fpkm from expressed (fpkm > 1 in all conditions) mRNAs

(n=9640) and lncRNAs (n=355) from adipocytes of mice underwent normal diet (ND) vs high-fat diet

(HFD). Height of each arm of the dendrogram above the heatmaps represents the distance between the

different data sets. Normalized gene expression data (fpkm values after log transformed and mean-

centered) are shown.

(D) Venn diagram showing overlap of obesity-regulated mRNAs (left) and lncRNAs (right) among

adipocytes from BAT, ING and EPI.

(E) Relative abundance of the identified obesity-induced lncRNAs across 30 different mouse tissues

using RNA-Seq data from ENCODE. Adipose tissues (BAT, ING and EPI) were shown in the first three

columns.

(F) Gene Ontology analysis of the obesity-induced lncRNAs using the software GREAT (Genomic

Regions Enrichment of Annotations Tool). The lncRNA-mRNA pairs that are associated with the GO term

“Activation of JNK activities” are shown.

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Figure 2. Selected obesity-regulated lncRNAs in adipocyte (lnc-ORIAs) are dynamically regulated

in diverse pathophysiological conditions

(A) qPCR analysis of selected lnc-ORIAs from BAT, ING and EPI of mice on normal chow (n=8) vs high-

fat diet (n=7).

(B) qPCR analysis of selected lnc-ORIAs from BAT, ING and EPI of mice underwent an overnight fast

(fasted, n=6) vs control (fed, n=7). For A-B, all data are presented as mean ± SEM. * p < 0.05, ** p< 0.01

and *** p< 0.001 comparing with the control condition using 2-tailed Student’s t tests.

(C) Heatmap illustrating the expression fold changes of the 10 selected lnc-ORIAs under high-fat diet vs

normal diet and fasting vs ad libitum. Red represents an increase in expression in HFD (or fasted)

compared to ND (or fed), whereas blue represents a decrease in expression in HFD (or fasted) compared

to ND (or fed).

(D) UCSC genome browser tracks showing promoters of Fabp4 and selected lnc-ORIAs are bound by

PPARG in mouse brown and epididymal adipose tissue. The RNA-Seq tracks were generated in the

current study and corresponds to the expression changes upon HFD in EPI, while the PPARG ChIP-Seq

data were from published data (GSE43763) (28). Red arrows indicate the direction of transcription. Scale

bars indicate a distance of 5kb.

Figure 3. The identification of Lnc-leptin, an enhancer lncRNA upstream of Lep

(A) Genomic location of Lnc-leptin in mm10. Both Lnc-leptin and Lep are on the positive strand and are

28kb apart.

(B) Mouse DNaseI hypersensitivity, histone modification, RNA Polymerase II binding profile and Pparg-

bound sites in a 15kb region around Lnc-leptin. DNaseI hypersensitivity profile of genital fat pad, fat pad

and liver from 8-week old mice (pink) is from ENCODE/University of Washington. Histone modification

data (H3K4Me3, H3K4ME1 and H3K27ac) of pooled white adipose tissue from eWAT and iWAT (green)

is from GSE92590. Epididymal white adipose tissue (WAT) and BAT RNA Polymerase II and histone3

control ChIP-Seq data (blue) is from GSE63964. PPARG ChIP-Seq data from eWAT and BAT (red) is

from GSE43763.

(C) Chromatin immunoprecipitation (ChIP) experiment using Mediator1 (MED1) antibody showing MED1

binding in the promoters of Lnc-leptin and Lep in white mature primary adipocytes differentiated in vitro

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(Day 7) at Lnc-leptin promoter, Lnc-leptin transcription start site (TSS) and Lep promoter. Insulin genomic

region (Ins) is used as negative control. All data (n=3) are presented as mean ± SEM. * p < 0.05, ** p<

0.01 and *** p< 0.001 comparing with the control condition using 2-tailed Student’s t tests.

Figure 4. Expression of Lnc-leptin is highly correlated to that of Lep.

(A) qPCR analysis of expression of Lnc-leptin, Lep and Pparg upon differentiation of primary white

adipocytes (n=4). Gene expression was expressed relative to Day 0.

(B) Lnc-leptin and Lep RNA expression measured by qPCR in 20 different mouse tissues.

(C) Correlation between the expression of Lnc-leptin and Lep under different conditions in mouse adipose

tissue: ND vs HFD (n=45), fasted vs fed (n=38), ob/ob vs control (n=9). δCt of Lnc-leptin (Ct of Lnc-leptin

– Ct of housekeeping gene Rpl23) were plot against δCT of Lep.

(D) Mature primary white adipocytes (Day6) were treated with 100nM of insulin for 3h (n=4). Gene

expression was expressed relative to control treatment.

(E) Mature primary brown and white adipocytes were treated with 2.5nM of TNFα for 24h (n=4). Gene

expression was expressed relative to control treatment.

(F) Mature primary white adipocytes were treated with 1µM of norepinephrine for 24h (n=4). For D-F,

qPCR analysis results were calculated using Rpl23 as housekeeping gene. Data is presented as mean ±

SEM. * p < 0.05, ** p< 0.01 and *** p< 0.001 comparing with the control model using 2-tailed Student’s t

tests.

Figure 5. Knocking down Lnc-leptin represses Lep

(A) Retrovirus-mediated transduction of primary preadipocytes (Day -2) using control and two separate

shRNAs targeting Lnc-leptin. Cells were induced to differentiate and RNA was harvested at Day6.

Expression of Lnc-leptin at Day6 was measured by qPCR (n=4).

(B) Oil red O staining showing adipocyte differentiation defect upon Lnc-leptin knockdown by shRNAs.

Scale bar =100µm.

(C) Expression of three adipocyte maker genes at Day6 upon shRNA transduction as described in A

(n=4).

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(D) Transfection of DsiRNA control or DsiRNAs targeting Lnc-leptin (Dsi1,Dsi2 and Dsi3) was performed

at the preadipocyte stage at Day-2 and RNA was extracted at Day 4. Expression of Lnc-leptin and other

adipocyte marker genes were measured at Day4 using qPCR (n=4).

(E) Expression of Lnc-leptin and other adipocyte markers in mature primary adipocytes reverse-

transfected with DsiRNA control or a specific DsiRNA targeting Lnc-leptin (Dsi2). Transfection was

performed at Day6 and RNA was extracted 48h later (n=4).

(F) Expression of Lnc-leptin and other adipocyte markers in mature primary adipocytes reverse-

transfected with antisense oligo targeting Lnc-leptin (ASO Lnc-leptin) or scrambled control (ASO

scrambled). Transfection was performed at Day6 and RNA was extracted 48h later (n=4).

(G) Lnc-leptin was knock-downed in vivo in mouse inguinal adipose tissue using ASO Lnc-leptin and

compared with control (ASO scrambled) (n=7). For each mouse, ASO Lnc-leptin was injected on one side

and scrambled control was injected on the contralateral side. Tissue was harvested and RNA was

extracted 48h post injection.

(H) Western blots showing the reduced protein expression of LEP in mouse inguinal adipose tissue after

knockdown of Lnc-leptin using ASO.

Figure 6. Chromatin looping between Lnc-leptin and Lep is diminished upon Lnc-leptin

knockdown in mature adipocytes

(A) Chromatin Conformation Capture (3C) experiment was performed to explore the 3D chromosome

configuration in the proximity of Lnc-leptin and Lep. Blue lines indicate sites at which restriction enzyme

Xba1 cut in a 47000bp genomic region spanning Lnc-leptin and Lep. Arrows next to the Xba1 cut sites

indicate direction of primers used in the 3C experiment. #15 is the anchor primer that encompasses the

transcription start site of Lep. Black rectangles indicate the exons of Lnc-leptin and Lep genes while

linking lines represent introns.

(B) Interaction frequency between the anchoring point and upstream distal fragments was determined by

qPCR (n=4) and normalized to BAC and control regions in primary adipocytes. Chromatin looping was

detected between fragment 6 (which contains exon2 of Lnc-leptin) and anchoring fragment 15.

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(C) 3C-qPCR result of mouse primary adipocytes with Lnc-leptin knockdown against its scramble control

using ASO. There is a noticeable decrease in interaction frequency between anchoring fragment 15 and

fragment 6 upon Lnc-leptin knockdown (p=0.1).

(D) Model of how Lnc-leptin potentially regulates Lep expression: Lnc-leptin is required for chromatin

interaction between the genomic loci of Lnc-leptin and Lep. Expression of Lnc-leptin enhances the

expression of Lep by bringing together the two genes and their transcription machinery.

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SUPPLEMENTARY FIGURES

Figure S1. Depot-specific markers were examined by real-time PCR (Related to Figure 1)

(A) Adipose tissue from each depot (BAT, EPI and ING) was minced into small pieces. A small fraction of

the minced tissue was kept before collagenase digestion for RNA-exaction and realtime PCR to examine

the expression of WAT markers (HoxC10, HoxC9 and Lep) and BAT marker (Ucp1).

(B) FPKM expression values from the RNA-Seq data of the above WAT and BAT markers in adipocytes

isolated after collagenous digestion.

**

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Figure S2. Biological insights about obesity can be gleaned from both obesity-regulated mRNAs

and lncRNAs (Related to Figure 1)

(A) Network analysis of obesity-induced mRNAs using GeneGo identified RelA as the top-scoring

transcription factor that connects with the most number of induced genes.

(B) Gene ontologies and pathways analysis of obesity-induced mRNAs using GeneGo.

(C) Promoter motif analysis of obesity-induced lncRNAs.

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Figure S3. Expression of lnc-ORIAs in fatty liver (Related to Figure 1)

Real-time PCR was performed to detect the 10 lnc-ORIAs expression in livers from chow and HFD fed

mice. 3 of 10 are detectable. Error bar represent SEM. * P<0.05, Student T test. N=6

lnc-ORIA6

lnc-ORIA3

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Figure S4. Many lnc-ORIAs are regulated in ob/ob mice (Related to Figure 2)

qPCR analysis of selected lncRNAs from inguinal tissue of ob/ob (n=3) vs control mice (n=4)

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Figure S5 Genomic profile around Lnc-leptin (Related to Figure 3)

(A) Mouse DNaseI hypersensitivity, histone modification, RNA Polymerase II binding profile and Pparg-bound sites in a 400kb region around Lnc-leptin. DNaseI hypersensitivity profile of genital fat pad, fat pad and liver from 8-week old mice (pink) is from ENCODE/University of Washington. Histone modification data (H3K4Me3, H3K4ME1 and H3K27ac) of pooled white adipose tissue from eWAT and iWAT (green) is from GSE92590. Epididymal white adipose tissue (WAT) and BAT RNA Polymerase II and histone3 control ChIP-Seq data (blue) is from GSE63964. PPARG ChIP-Seq data from eWAT and BAT (red) is from GSE43763. (B) Mouse DNaseI hypersensitivity profile and histone modification (H3K4Me3, H3K4ME1 and H3K27ac) as measured by ChIP-Seq at the vicinity of Lnc-leptin and Lep. DNaseI hypersensitivity data of mouse fat pad was made available from ENCODE/University of Washington. Brown adipose tissue (BAT) histone modification data was ChIP-Seq datasets made available by ENCODE/LICR. Both sets of data were downloaded via UCSC genome browser.

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Figure S6. Overexpression of lnc-Leptin doesn’t affect Leptin expression (Related to Figure 5)

iWAT preadipocytes were infected by retroviral for Lnc-leptin overexpression, followed by induction of

differentiation for 5 days. Realtime PCR was performed to examine the expression of Lnc-leptin, Lep and

other markers.

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List of Supplemental Tables

Supplemental Table 1: Summary of RNA-Seq data

Supplemental Table 2: The genomic coordinates of the 68 lnc-ORIAs

Supplemental Table 3: Sequences of qPCR primers for lnc-ORIAs and protein-coding genes

Supplemental Table 4: Sequences of shRNAs used to knockdown Lnc-leptin

Supplemental Table 5: Sequences of DisRNAs and antisense oligos used to knockdown Lnc-leptin

Supplemental Table 6: Sequences of anti-sense oligo used to knockdown Lnc-leptin

Supplemental Table 7: Sequences of ChIP primers

Supplemental Table 8: Sequences of 3C primers

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Supplemental Table 1: Summary of RNA-Seq data

Samples input Aliigned pairs Concordant pair alignment rate

Concordant aligned pairs

ND_subq1 11,638,518 11,088,443 93.7% 10,905,291

ND_subq2 14,329,770 13,367,078 89.4% 12,810,814

ND_subq3 9,504,510 8,580,019 84.4% 8,021,806

HFD_subq1 18,924,192 18,087,008 92.2% 17,448,105

HFD_subq2 15,741,275 14,902,029 90.5% 14,245,854

HFD_subq3 22,513,698 21,043,689 88.7% 19,969,650

ND_bat1 13,457,147 12,727,660 88.6% 11,923,032

HFD_bat1 16,712,661 15,963,833 92.3% 15,425,786

ND_epi1 22,372,276 21,195,223 92.1% 20,604,866

ND_epi2 18,467,744 17,537,206 92.7% 17,119,599

ND_epi3 25,495,193 23,839,442 91.6% 23,353,597

HFD_epi1 18,037,866 17,158,404 92.3% 16,648,950

HFD_epi2 16,597,865 15,823,064 93.1% 15,452,612

HFD_epi3 18,099,336 17,211,156 92.8% 16,796,184

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Supplemental Table 2: The genomic coordinates of the 68 lnc-ORIAs in mm10

Name Chromosome Start End

lnc-ORIA1 chr9 85331071 85348086

lnc-ORIA2 chr9 102740573 102741913

lnc-ORIA3 chr9 83117508 83127348

lnc-ORIA4 chr2 61533518 61541880

lnc-ORIA5 chr1 58885697 58890986

lnc-ORIA6 chr1 133977469 133984516

lnc-ORIA7 chr10 114112126 114119642

lnc-ORIA8 chr15 11966755 11971861

lnc-ORIA9 chr6 29032107 29039688

lnc-ORIA10 chr11 83224152 83226572

lnc-ORIA11 chr14 50870363 50880633

lnc-ORIA12 chr14 63652994 63666133

lnc-ORIA13 chr14 103403341 103449863

lnc-ORIA14 chr14 103463810 103512978

lnc-ORIA15 chr15 74930296 74938747

lnc-ORIA16 chr16 42882899 42912104

lnc-ORIA17 chr16 49980486 50049732

lnc-ORIA18 chr16 84713334 84715783

lnc-ORIA19 chr17 36159164 36181074

lnc-ORIA20 chr17 81370555 81377640

lnc-ORIA21 chr18 67321336 67327949

lnc-ORIA22 chr2 11521730 11543659

lnc-ORIA23 chr2 104084898 104120296

lnc-ORIA24 chr2 118553202 118562303

lnc-ORIA25 chr2 131946591 131955930

lnc-ORIA26 chr2 167571295 167580687

lnc-ORIA27 chr2 173110767 173138211

lnc-ORIA28 chr3 59870359 59876968

lnc-ORIA29 chr4 45531357 45533398

lnc-ORIA30 chr4 47198847 47206364

lnc-ORIA31 chr4 60544271 60547243

lnc-ORIA32 chr4 82507878 82547284

lnc-ORIA33 chr4 107433861 107434413

lnc-ORIA34 chr4 125228322 125229981

lnc-ORIA35 chr4 141207569 141211161

lnc-ORIA36 chr4 154637549 154644919

lnc-ORIA37 chr5 123133727 123140725

lnc-ORIA38 chr6 3328537 3346117

lnc-ORIA39 chr6 93193584 93244268

lnc-ORIA40 chr10 25298450 25306389

lnc-ORIA41 chr7 67712915 67716588

lnc-ORIA42 chr7 73544131 73557982

lnc-ORIA43 chr7 92705266 92710324

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lnc-ORIA44 chr8 13210273 13214034

lnc-ORIA45 chr8 34052373 34056819

lnc-ORIA46 chr8 84200888 84209606

lnc-ORIA47 chr1 31045092 31096637

lnc-ORIA48 chr9 35498199 35501504

lnc-ORIA49 chr9 61260956 61268588

lnc-ORIA50 chr9 120351498 120359838

lnc-ORIA51 chrX 8860453 8892939

lnc-ORIA52 chrX 19145397 19146279

lnc-ORIA53 chrX 95960481 95968036

lnc-ORIA54 chr11 59505435 59511216

lnc-ORIA55 chr11 79712040 79732287

lnc-ORIA56 chr11 99168157 99175740

lnc-ORIA57 chr11 113043902 113130598

lnc-ORIA58 chr11 117557675 117560472

lnc-ORIA59 chr12 80120456 80132892

lnc-ORIA60 chr1 70893858 70918402

lnc-ORIA61 chr13 43489823 43494462

lnc-ORIA62 chr13 49260845 49262424

lnc-ORIA63 chr13 52554392 52561721

lnc-ORIA64 chr1 72857935 72862280

lnc-ORIA65 chr13 81754189 81762256

lnc-ORIA66 chr14 28303118 28308783

lnc-ORIA67 chr14 28504614 28506296

lnc-ORIA68 chr14 34661520 34662690

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Supplemental Table 3: Sequences of qPCR primers for lnc-ORIAs and protein-coding genes

lnc-ORIA1_F TAATTGGGCCTGGCTTACAG

lnc-ORIA1_R ACTATGGGTGTGGGCTTCAG

lnc-ORIA2_F ATTCAGAGTCCCTTGTGAGC

lnc-ORIA2_R CTTGTGCAGTGATGTTGACC

lnc-ORIA3_F GAAATTCAGCAAGAGCGTCC

lnc-ORIA3_R TGGCTTAGGCATGTTCCATT

lnc-ORIA4_F ACACAGAGAAATTTTGGTAGTCA

lnc-ORIA4_R GTGTATTTTGAGCTTTGGGGA

lnc-ORIA5_F TTGTTCCTCCGGAATGTCTC

lnc-ORIA5_R AGAGCAGCAAAGCATCTTCT

lnc-ORIA6_F CCAAGTTTGGCAGTAGAGGA

lnc-ORIA6_R CAGCAGGATTGATGGATGGA

lnc-ORIA7_F ACAACTTTAGAGGCTGAAAACTC

lnc-ORIA7_R CTGATGCCGCTTTCTTGATT

lnc-ORIA8_F CGGCTTTCTGTCCATTCCTA

lnc-ORIA8_R GTGAAAATTGTGCCGCTGAT

lnc-ORIA9_F1 GCTCCCTCTGATCCTTGTTG

lnc-ORIA9_R1 CTTGGTGGTCTTGGTCCTGT

lnc-ORIA10_F GGTTCTGGGCAAAATCCTTC

lnc-ORIA10_R TTCTGCCTCTTGATGTGGTT

Lep_F GAGACCCCTGTGTCGGTTC

Lep_R CTGCGTGTGTGAAATGTCATTG

Rpl23_F TGTGAAGGGAATCAAGGGAC

Rpl23_R TGTTTACTATGACCCCTGCG

Ccl9_F CCCTCTCCTTCCTCATTCTTACA

Ccl9_R AGTCTTGAAAGCCCATGTGAAA

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Supplemental Table 4: Sequences of shRNAs used to knockdown Lnc-leptin

sh_anti-lncLeptin1_F

GATCCCCGGGCACCGTGATTCTGAAATACGAATATTTCAGAATCACGGTGCCCTTTTTA

sh_anti-lncLeptin1_R

AGCTTAAAAAGGGCACCGTGATTCTGAAATATTCGTATTTCAGAATCACGGTGCCCGGG

sh_anti-lncLeptin2_F

GATCCCCGGCACCGTGATTCTGAAATAGCGAACTATTTCAGAATCACGGTGCCTTTTTA

sh_anti-lncLeptin2_R

AGCTTAAAAAGGCACCGTGATTCTGAAATAGTTCGCTATTTCAGAATCACGGTGCCGGG

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Supplemental Table 5: Sequences of DisRNAs and antisense oligos used to knockdown Lnc-leptin

Dsi_1_antisense rArGrGrUrArGrArGrUrCrCrArUrCrGrArCrUrCrUrGrArArUrCrUrU

Dsi_1_sense rGrArUrUrCrArGrArGrUrCrGrArUrGrGrArCrUrCrUrArCCT

Dsi2_antisense rGrGrArGrArCrUrUrUrGrCrCrUrUrCrUrUrGrGrUrUrCrUrUrGrGrA

Dsi2_sense rCrArArGrArArCrCrArArGrArArGrGrCrArArArGrUrCrUCC

Dsi3_antisense rUrUrCrArArCrUrUrCrCrUrGrArGrGrUrGrUrGrUrGrUrCrArUrUrU

Dsi3_sense rArUrGrArCrArCrArCrArCrCrUrCrArGrGrArArGrUrUrGAA

Dsi_control_antisense rArUrArCrGrCrGrUrArUrUrArUrArCrGrCrGrArUrUrArArCrGAC

Dsi_control_sense rCrGrUrUrArArUrCrGrCrGrUrArUrArArUrArCrGrCrGrUAT

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Supplemental Table 6: Sequences of anti-sense oligo used to knockdown Lnc-leptin

ASO Lnc-leptin ATGCAGCCGGAGTAT

ASO4 scrambled control TTACAGCCGGAGAGT

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Supplemental Table 7: Sequences of ChIP primers

LncLeptin_ChIP_TSS_F GACTTGGAGGGGGTAGTAAC

LncLeptin_ChIP_TSS_R AGAAAGAGGTCAATGAGGGC

LncLeptin_ChIP_promoter_F CCCGAATAGTCTACACCCTG

LncLeptin_ChIP_promoter_R GTTACTACCCCCTCCAAGTC

Lep_ChIP_promoter_F TTCGGGTACCAAAGGAAGAC

Lep_ChIP_promoter_R CTACTGAGCAGCGGTAGTTT

Ins_ChIP_F GGACCCACAAGTGGAACAAC

Ins_ChIP_R GTGCAGCACTGATCCACAAT

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Supplemental Table 8: Sequences of 3C primers

Name Sequence Note

X-369-15 GCACCCCATACCCTGTATCC Anchor primer, fragment 15 with XbaI

XbaI-369-3 CGCATGGATATCTGTCATCG Lnc-leptin promoter, fragment 3 with XbaI

XbaI-369-4 CGCTCTGACTCTGACTGTGG Lnc-leptin promoter, fragment 4 with XbaI

XbaI-369-5 CAATCACCACACCCACAAAG Lnc-leptin intron, fragment 5 with XbaI

XbaI-369-6 CCAGCTCCTGTTGCCTTGTA Lnc-leptin exon2, fragment 6 with XbaI

XbaI-369-9 GCTAGCTCCTTCATCCTTGCT Negative control, fragment 9 with XbaI

XbaI-369-11 CAGCTCCTTTCTGGGTGACT Negative control, fragment 11 with XbaI

XbaI-369-13 CAAAGTGGCATGGTGTTCAT Negative control, fragment 13 with XbaI

XbaI-369-14 CTCCTTTCCAGTGCCTCAAA Neighbor fragment (14) & positive control with XbaI

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