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Abstract

There is little evidence for the involvement of microRNAs (miRs) in the regulation of circadian rhythms, despite the potential relevance of these elements in the posttranscriptional regulation of the clock machinery. The present work aimed to identify miRs targeting circadian genes through a predictive analysis of conserved miRs in mammals. Besides 23 miRs previously associated with circadian rhythms, we found a number of interesting candidate genes, equally predicted by the 3 software programs used, including miR-9, miR-24, miR25, miR-26, miR-27, miR-29, miR-93, miR-211, miR-302, and miR-346. Moreover, several miRs are predicted to be regulated by circadian transcription factors, such as CLOCK/BMAL, DEC2, and REV-ERBalpha. Using real-time PCR we demonstrated that the selected candidate miR-27b showed a daily variation in human leukocytes. This study presents predicted feedback loops for mammalian molecular clock and the first description of an miR with in vivo daily variation in humans.

Keywords

posttranscriptional regulation miR bioinformatics mammals clock genes

Approximately 5% to 10% of transcripts present a circadian oscillation (Pegoraro and Tauber, 2008). However, proteome analysis in mammals reveals that around 20% of proteins present cyclic expression, some of them with the corresponding mRNAs being constitutively expressed (Reddy et al., 2006). Moreover, cycling mature mRNAs are more abundant than cycling precursor RNAs, as recently reported in a genome scale analysis (Koike et al., 2012). These differences emphasize the importance of posttranscriptional and posttranslational mechanisms in the regulation of biological rhythms.

Recently, the participation of microRNAs (miRs) in the posttranscriptional control of circadian rhythms has been demonstrated (Alvarez-Saavedra et al., 2011; Balakrishnan et al., 2010; Cheng et al., 2007; Kojima et al., 2010; Luo and Sehgal, 2012; Tan et al., 2012; Yamakuchi, 2012). miRs are small noncoding transcripts responsible for the regulation of various genes (Filipowicz et al., 2008). It is estimated that in mammals, approximately 50% of coding genes are regulated by these elements (Krol et al., 2010). However, few miRs and target clock genes have been reported in the circadian literature.

The aim of this work was to perform an in silico analysis to identify candidate miRs potentially involved in mammalian circadian control. Based on the prediction of target genes and promoter analysis for clock transcription factors, we propose a series of posttranscriptional feedback loops that can be explored in subsequent studies. We also investigated the diurnal expression of miR-27b in human leukocytes.

Materials and Methods

Analysis of 3′UTR Region of Clock Genes

The bioinformatics tools Pictar (http://pictar.bio.nyu.edu), microrna.org (http://www.microrna.org), and TargetScan (http://www.targetscan.org) were used in this study. These programs use conserved elements for the prediction of targets (Lewis et al., 2003; Xia et al., 2009; Yoon and De Micheli, 2006).

We used the target mRNA search in microrna.org, with target sites of conserved miRs with good mirSVR scores. All miRs showed in the results were selected for our analysis. In TargetScanHuman and TargetScanMouse, we used the entrez gene symbol option. In the 3′UTRs of target genes, we selected those with conserved sites for miR families broadly conserved among vertebrates and conserved only among mammals. We chose the target predictions in PicTar for all human miRs based on conservation in mammals (human, chimp, mouse, rat, and dog). The gene ID was included in the search for all miRs predicted to the target gene.

The circadian genes and their isoforms Clock, Bma1l (Arntl), Per1-3, Cry1-2, Rerv-erbalpha (Nr1d1), Rerv-erbbeta (Nr1d2), Timeless, Dec1 (Bhlhe40), Dec2 (Bhlhe41), Rora (Ror-alpha), Rorb (Ror-beta), Rorc (Ror-gamma), Csnk1e (casein kinase 1, epsilon), Csnk1d (casein kinase 1, delta), and Nocturnin (Ccrn4L) were selected for analysis.

We also included Ccne1 (Cyclin e1), Ccnd1 (Cyclin d1), Scp2, Rgn, Khk, Hspd1, Hao1, Grp58 (Pdia3), Gnpat, Eno1, Cat, Calr, Atp5b, Atp5a1, Apoa4, Aldo2 (AldoB), Aldh1a1, and Acaa2, which present a circadian pattern of protein expression with mRNAs expressed constitutively (Balakrishnan et al., 2010; Reddy et al., 2006), and Adcy6 (adenylyl cyclase VI), targeted by the circadian miR-96/miR-182 in mice retina (Xu et al., 2007). Only miRs conserved in mammals and targeting the mentioned genes in humans and mice were selected.

Identification of Putative Target Sites for Circadian Transcription Factors in the Promoter of Candidate miRs

The candidate miRs that presented targets equally predicted in 3 bioinformatics software programs were selected for promoter analysis. The promoter sequences of miRs were obtained in Eukaryotic Promoter Database (EPD). The predictive analyses of putative target sites for circadian transcription factors were performed with the MatInspector program (Cartharius et al., 2005), using an interval of −499 to 100 bp relative to the transcription starting site. ENSEMBL coordinates for promoter sequences and sequence motifs used are available in Supplementary Tables S1 and S2, respectively.

Quantitative Real-Time PCR

For the analysis of daily variation of miR-27b in human leukocytes, we selected 5 young men (mean age 22.8 ± 3.42 years), named herein as S1-S5, of the same ethnicity and intermediate chronotype according to the Horne-Ostberg Morningness-Eveningness Questionnaire (Horne and Ostberg, 1976). These individuals did not experience shift-work or jet lag, were not smokers, and did not regularly use medications. They also presented normal hematological findings. The subjects were told that during the week that preceded the study they should perform their daily activities under a regular routine of sleeping and eating, should avoid excessive light at night, should not ingest foods with caffeine or energetics, and should not perform extensive physical activities.

On the day of blood sampling, food was available from 0700 to 0800 h (breakfast), 0930 to 1030 h (snack), 1200 to 1300 h (lunch), 1530 to 1630 h (snack), and 1900 to 2030 h (dinner), with water available ad libitum. Blood was collected in EDTA tubes every 4 h along a circadian cycle. The study was approved by the Committee on Ethics of the Federal University of Alagoas (#007138/2011-41).

Red blood cells were lysed with Buffer EL (Qiagen, Hilden, Germany), and RNA purification of the remaining cells was performed with miRNeasy Mini Kit (Qiagen). The samples were then stored at −80 °C for further analysis.

The cDNA was synthesized from 1 µg of total RNA using the miScript Reverse Transcription Kit (Qiagen) according to the manufacturer’s protocol. As suggested, we added 4 µL of miScript RT Buffer (includes Mg²⁺, dNTPs, and primers) and 1 µL of miScript Reverse Transcriptase. The reactions were adjusted to a final volume of 20 µL with RNase-free water. All cDNA samples were diluted (1:10) in RNase-free water for analysis.

The qRT-PCR reactions were performed using StepOne Plus (Applied Biosystems, Foster City, CA, USA) with 2 µL of miScript Primer Assays (Qiagen) for miR-27b and 10 µL of 2x QuantiTect SYBR Green PCR Master Mix, 2 µL of 10x miScript Universal primer, and 4 µL of RNase-free water, which compose the miScript SYBR Green PCR Kit (Qiagen). The cycling conditions were 15 min/95 °C for initial activation of HotStarTaq DNA Polymerase, 15 sec/94 °C for denaturation, 30 sec/55 °C for annealing, and 30 sec/70 °C for extension in a total of 40 cycles. All reactions were performed in duplicates with negative controls, and efficiency tests with melting curve analysis were performed for each primer.

For normalization of miR-27b expression data, we selected SCARNA-17 (Small Cajal body-specific RNA 17) and SNORA-73A (small nucleolar RNA, C/D box 73A) (miScript PCR Controls, Qiagen) as reference genes. The stability analysis of SCARNA-17 and SNORA-73 in the geNorm program (Vandesompele et al., 2002) showed that both genes are stable across our samples (subjects and time points). However, SNORA-73 had a better stability score (0.582) than SCARNA-17 (0.613). Given these results, we decided to use SNORA-73 to normalize the expression data.

The expression of the clock gene Per3 was used as a positive control for diurnal variation. The reactions were also performed with miScript SYBR Green PCR Kit reagents (Qiagen) using the specific forward primer (5′-GCAGAGGAAATTGGCGGACA-3′) and reverse primer (5′-AGAGTGTTGGCTTATTGCGTC-3′). The primer sequences of the noncoding RNAs used were not supplied by the company (Qiagen). Data are presented as relative expression (2^–ΔΔCt), and the nadir (time point with the lowest expression level) was used as the calibrator sample.

Statistical Analysis

The grouped time-series data were analyzed by repeated-measures ANOVA and Bonferroni multiple comparison posttest. Considering interindividual differences, we grouped subjects with the same phase according to their peak of expression (based on fold change). The values for each time point are presented as means and SEM. In addition, we analyzed the expression individually with the cosinor test with periods adjusted to 24 h. We also calculated the mean, amplitude, acrophase, and fitted cosine wave from relative expression data. In all analyses, p < 0.05 was considered significant.

The calculations were performed using GraphPad Prism (GraphPad Software, San Diego, CA) for ANOVA and Acro software (http://www.circadian.org/softwar.html) for calculation of the mean, amplitude,acrophase, and fitted cosine wave.

Results

We found 237 predicted miRs in humans and 227 in mice using microrna.org, 202 in humans and 159 in mice using TargetScan, and 114 miRs in both species using PicTar for analysis (data not shown). Sixty-nine miRs were equally predicted using the 3 programs in humans and/or mice (Suppl. Table S3). In Table 1 we present a selected list of these candidate miRs based on literature search for validated targets previously associated with circadian rhythms.

Table 1.

Selected candidate miRs for circadian regulation based on bioinformatic screening and literature search for validated targets or pathway genes.

MicroRNA	Predicted Targets for Mouse	Predicted Targets for Human	Validated Targets or Pathway Genes Associated with Circadian Rhythms	References
Let-7a	mCry2; mRorc	hCry2	Fxyd5, Brca1, Ccnd2, Ezh2, Myc, p53, Nf-kb	Balakrishnan et al., 2010; Bjarnason et al., 1999; Cai et al., 2012; Cecon et al., 2010; Colamaio et al., 2012; Etchegaray et al., 2006; He et al., 2010; Kawai and Amano, 2012; Okazaki et al., 2010; Saleh et al., 2011; Stow et al., 2012; Wang et al., 2012; Wang et al., 2011; Winter et al., 2007
Let-7b	mCry2; mRorc	hCry2	p53	Bjarnason et al., 1999; Saleh et al., 2011
Let-7c	mCry2; mRorc	hCry2	Myc, Interleukin-10, Bcl-xl	Bertani et al., 2010; Jiang et al., 2012; Nadiminty et al., 2012; Okazaki et al., 2010; Qin et al., 2012; Zhao et al., 2011
Let-7d	mCry2	hCry2	Myc	Okazaki et al., 2010; Wang et al., 2011
Let-7f^a	mCry2; mRorc	hCry2	Myc	Okazaki et al., 2010; Wang et al., 2011
Let-7g	mCry2; mRorc	hCry2	Myc, p16	Griniatsos et al., 2006; Lan et al., 2011; Okazaki et al., 2010
miR-9	mClock	hClock	Myc, Sirt1	Asher et al., 2008; Belden and Dunlap, 2008; Bellet et al., 2011; Khew-Goodall and Goodall, 2010; Nakahata et al., 2008; Okazaki et al., 2010; Repouskou et al., 2010; Saunders et al., 2010; Yamakuchi, 2012
miR-16^a	mCcne1	hClock	Ccnd1, Ccnd2, Ccnd3, Ccne1, Cdk6	Balakrishnan et al., 2010
miR-24	mPer2	hPer1; hPer2	Myc	Kutty et al., 2010; Lal et al., 2009; Okazaki et al., 2010
miR-25	mPer2	hPer2	Pten, p53, Ezh2	Bjarnason et al., 1999; Etchegaray et al., 2006; Kumar et al., 2011; Mullenders et al., 2009; Ogawa et al., 2007; Poliseno et al., 2010
miR-26a^a	mHao1	hHao1	Myc, Ezh2, Interleukin-2, Ccne2	Alajez et al., 2010; Etchegaray et al., 2006; Lissoni et al., 1998; Okazaki et al., 2010; Salvatori et al., 2011; Sander et al., 2008; Shi et al., 2009; Xu et al., 2010
miR-27a	mAdcy6	hAdcy6	Rxr-alpha, Ppar-gamma	Cho et al., 2009; Grimaldi et al., 2010; Ji et al., 2009; Kawai and Rosen, 2010; Kim et al., 2010; McNamara et al., 2001; Nakamura et al., 2008; Oishi et al., 2005; Yang et al., 2010
miR-27b	mAdcy6	hAdcy6	Rxr-alpha. Nf-kb, Ppar-alpha, Ppar-gamma	Cecon et al., 2010; Cho et al., 2009; Grimaldi et al., 2010; Jennewein et al., 2010; Ji et al., 2009; Kawai and Rosen, 2010; Kida et al., 2011; McGregor and Choi, 2011; Nakamura et al., 2008; Oishi et al., 2005; Thulasingam et al., 2011; Yang et al., 2010
miR-29a	mPer3	hPer3	Mct1	Pullen et al., 2011; Stearns et al., 2008
miR-29b	mPer3	hPer3	Mct1	Pullen et al., 2011; Stearns et al., 2008
miR-29c	mPer3	hPer3	Ccne1	Balakrishnan et al., 2010; Ding et al., 2011
miR-30c	mPer2	hPer2	Pai1	Karbiener et al., 2011; Masuda et al., 2009; Oishi et al., 2009; Oishi et al., 2007; Wang et al., 2006
miR-30d	mClock; mPer2	hClock; hPer2	p53, Ezh2	Bjarnason et al., 1999; Esposito et al., 2012; Etchegaray et al., 2006; Kumar et al., 2011; Mullenders et al., 2009
miR-93^a	mClock; mCry2; mCcnd1	hClock; hCry2; hCcnd1	Pten, Vegf, Sp1, Sirt1	Asher et al., 2008; Belden and Dunlap, 2008; Bellet et al., 2011; Bozek et al., 2009; Bozek et al., 2010; Fu et al., 2012; Koyanagi et al., 2003; Li et al., 2011; Long et al., 2010; Nakahata et al., 2008; Ogawa et al., 2007; Sato et al., 2008; Yamakuchi, 2012
miR-96^a	mAdcy6	hClock; hAdcy6	Clock, Adcy6	Xu et al., 2007
miR-98	mCry2; Rorc	hCry2	Ezh2	Alajez et al., 2010; Etchegaray et al., 2006; Liu et al., 2011
miR-101	—	hAdcy6	Ezh2	Alajez et al., 2010; Etchegaray et al., 2006
miR-106a	mClock; mCry2; mCcnd1	hCry2	p21, Tnf-alpha, Fas, App, Interleukin-10	Bedrosian et al., 2011; Griniatsos et al., 2006; Jiang and Li, 2011; Liu et al., 2010; Patel et al., 2008; Perez-Aso et al., 2012; Sharma et al., 2009; Wang et al., 2010, 2012b
miR-132^a	mHao1	hHao1	Per1, Per2	Alvarez-Saavedra et al., 2011; Cheng et al., 2007
miR-142-3p^a	mBmal1	hBmal1	Bmal1	Shende et al., 2011; Tan et al., 2012
miR-152^a	mClock; mGrp58	hClock; hGrp58	Bmal1	Shende et al., 2011
miR-182^a	mClock; mAcdy6	hClock; hAdcy6	Clock, Adcy6	Xu et al., 2007
miR-190	mClock	hClock,	Phlpp1, NeuroD1, mu-opioid receptor	Beezhold et al., 2011; Dupre et al., 2008; Masubuchi et al., 2010; Mitchell et al., 1998; Zheng et al., 2010
miR-195	mCcne1	hClock; hCcnd1;hCcne1	Ccne1, Bdnf, Sirt1	Asher et al., 2008; Balakrishnan et al., 2010; Begliuomini et al., 2008; Belden and Dunlap, 2008; Bellet et al., 2011; Choi et al., 2011; Liang et al., 2000; Liang et al., 1998; Mellios et al., 2008; Nakahata et al., 2008; Sekiya et al., 2010; Yamakuchi, 2012; Zhu et al., 2011
miR-203	mBmal1	hBmal1	Scr, Akt, Socs-3	Moffatt and Lamont, 2011; Saini et al., 2011
miR-204	mAcdy6	hAdcy6	Runx2, Interleukin-10, Sirt1	Asher et al., 2008; Athanassiou-Papaefthymiou et al., 2011; Belden and Dunlap, 2008; Bellet et al., 2011; Chien et al., 2006; Huang et al., 2010; Nakahata et al., 2008; Pollari et al., 2012; Saunders et al., 2010; Yamakuchi, 2012
miR-211^a	mAcdy6	hAdcy6	Angiopoietin-1	Chen et al., 2010a; Kitazawa et al., 2011; Krol et al., 2010a; Na et al., 2009
miR-212^a	mHao1	hHao1	Creb	Cermakian et al., 2011; Cermakian and Sassone-Corsi, 2002; Na et al., 2009; Remenyi et al., 2010; Tognini et al., 2011
miR-219^a	mRor-beta	—	Clock/Bmal1	Cheng et al., 2007
miR-302a^a	mRor-beta; mCcnd1	hRor-beta; hCcnd1	Oct4, Sox2, Ccnd1	Balakrishnan et al., 2010; Card et al., 2008; Na et al., 2009; Yagita et al., 2010
miR-302b^a	mRor-beta; mCcnd1	hRor-beta; hCcnd1	Fmr1	Gatto and Broadie, 2009; Na et al., 2009; Yi et al., 2010
miR-346	mCsnk1D	hCsnk1D	Rip-140	Poliandri et al., 2011; Tsai et al., 2009
miR-367	mPer2	hPer2	Ryr3	Ding et al., 1998; Gamble and Ciarleglio, 2009; Zhang et al., 2011

References presented in this table are available in the supplementary material.

miRs previously described with circadian expression, daily variations or that present clock genes as validated targets.

We used MatInspector to investigate whether the 69 miRs have themselves conserved sites for circadian transcription factors in their promoters. Table 2 shows the 33 miRs that meet this criterion. Several hypothetical feedback loops potentially mediated by some of these miRs can be predicted from these data and are represented in Supplementary Figure S1.

Table 2.

Candidate miRs presenting putative sites for circadian transcription factors in their promoters.

Predicted Targets (TargetScan, microRNA.org, and PicTar)			Predicted Transcription Factors (MatInspector)
MicroRNA	Mouse	Human	Mouse	Human
let-7a	mCry2; mRor-gamma	hCry2	—	CREB; DEC1; ROR-alpha
let-7b	mCry2; mRor-gamma	hCry2	—	DEC1; ROR-alpha
let-7c	mCry2; mRor-gamma	hCry2	—	CREB; ROR-alpha
let-7d	mCry2	hCry2	—	CREB; REV-ERBalpha; ROR-alpha
let-7f^a	mCry2; mRor-gamma	hCry2	—	DEC1; REV-ERBalpha; ROR-alpha
let-7g	mCry2; mRor-gamma	hCry2	—	DEC2; ROR-gamma
miR-106a	mClock; mCry2; mCcnd1	hCry2	CREB	—
miR-106b^a	mClock; mCry2; mCcnd1	hCry2	CREB, DEC2; REV-ERBalpha	—
miR-142-3p^a	mBmal1	hBmal1	REV-ERBalpha	—
miR-152^a	mClock; mGrp58	hClock; hGrp58	CREB; REV-ERBalpha	CREB
miR-182^a	mClock; mAcdy6	hClock; hAdcy6	ROR-alpha; CREB	CREB
miR-190	mClock	hClock	CLOCK/BMAL1; DEC2	CREB; DEC2
miR-203	mBmal1	hBmal1	REV-ERBalpha	—
miR-204	mAcdy6	hAdcy6	DEC2; REV-ERBalpha	—
miR-211^a	mAcdy6	hAdcy6	DEC2; REV-ERBalpha	CREB
miR-24	mPer2	hPer1; hPer2	—	CLOCK/BMAL1; REV-ERBalpha; CREB
miR-25	mPer2	hPer2	REV-ERBalpha; DEC2; ROR-alpha	ROR-alpha
miR-27b	mAdcy6	hAdcy6	DEC2; ROR-alpha	DEC2; ROR-alpha; CREB
miR-29b	mPer3	hPer3	ROR-gamma; ROR-alpha; REV-ERBalpha	ROR-alpha; CREB
miR-29c	mPer3	hPer3	REV-ERBalpha; CREB	DEC2; REV-ERBalpha
miR-302a^a	mRor-beta; mCcnd1	hRor-beta; hCcnd1	REV-ERBalpha	ROR-alpha
miR-302b^a	mRor-beta; mCcnd1	hRor-beta; hCcnd1	REV-ERBalpha; ROR-alpha	ROR-alpha
miR-302d	mRor-beta; mCcnd1	hRor-beta; hCcnd1	REV-ERBalpha	—
miR-30b^a	mPer2	hPer2	CREB; ROR-alpha	CREB
miR-30c	mPer2	hPer2	DEC2; REV-ERBalpha; CREB	REV-ERBalpha
miR-30d	mClock; mPer2	hClock; hPer2	REV-ERBalpha; ROR-alpha	CREB
miR-30e	mClock;mPer2	hClock; hPer2	DEC2; ROR-alpha	—
miR-346	mCsnk1D	hCsnk1D	CREB; ROR-alpha	—
miR-367	mPer2	hPer2	—	REV-ERBalpha
miR-9	mClock	hClock	ROR-alpha	DEC2; REV-ERBalpha; ROR-alpha; CREB
miR-93^a	mClock; mCry2; mCcnd1	hClock; hCry2; hCcnd1	DEC2; REV-ERBalpha; ROR-alpha; CREB	ROR-alpha
miR-96^a	mAdcy6	hClock; hAdcy6	—	ROR-alpha
miR-98	mCry2; Ror-gamma	hCry2	—	DEC2

miRs previously described with circadian expression, daily variations or that present clock genes as validated targets.

As an initial approach for experimental evaluation of the potential contribution of the identified miRs to circadian process, we collected blood samples from healthy donors over a period of 24 h and evaluated the expression of miR-27b by qRT-PCR. miR-27b was selected for expression analysis in human leukocytes based on its potential involvement in hematopoiesis and immune response.

The individual analysis showed that miR-27b expression data from S3 and S4 present a significant difference in cosinor test. In the analysis of Per3 expression, only S4 presents p < 0.05 (Fig. 1). ANOVA showed a significant temporal variation in miR-27b when S1 and S5, with peak expression at 00 h, were combined (p = 0.041), and when S3, S4, and S5, with peak expression at 12 h (S3) and 8 h (S4 and S5), were combined for Per3 analysis (p = 0.040) (Fig. 1). Table 3 shows the descriptive analysis of miR-27b and Per3 expression. The average fold change in relative expression between nadir and acrophase (sampled time point with the highest expression level) was 2.01 (±0.11 SEM) for miR-27b and 2.31 (±0.10 SEM) for Per3.

Figure 1.

Daily variation of miR-27b and Per3 expression in human leukocytes measured by qRT-PCR. (A) Cosinor analysis of each subject. The lines show the fitted cosine wave and the dots correspond to the relative expression data (fold change). (B) Analysis by repeated-measures ANOVA of different groups. Above are clustered subjects with peak of expression in dark phase and below in light phase. The data are presented as mean and SEM. Shaded area marks the dark phase of the day. Nadir (time point with the lowest expression level) was used as calibrator sample in fold change equation (2^−ΔΔCT) and SNORA-73A as endogenous reference gene. p < 0.05 was considered significant for both statistical tests.

Table 3.

Descriptive analysis of miR-27b and Per3 expression in leukocytes of 5 subjects.

Subject	Genes	Mean	Amplitude	Acrophase/Hours	Fold Change^a
S1	Per3	2.0	2.3	14.8	5.7
	miR-27b	1.0	0.4	3.2	1.8
S2	Per3	2.5	2.3	0.0	5.7
	miR-27b	0.7	0.6	10.8	1.9
S3	Per3	1.0	0.3	8.8	1.6
	miR-27b*	1.7	1.0	15.2	3.1
S4	Per3*	1.5	0.9	8.0	2.9
	miR-27b*	1.2	0.8	7.2	2.6
S5	Per3	1.5	0.8	6.4	2.6
	miR-27b	1.2	0.6	0.0	2.3

Relative difference between the time point with the highest expression and nadir (calibrator sample) in qRT-PCR experiments.

p < 0.05 in Cosinor.

Discussion

Despite the pivotal role of posttranscriptional mechanisms in the regulation of circadian rhythms and the involvement of miRs in this process, there are few examples in the literature linking these genetic elements to the control of circadian clock. Using an in silico approach for identifying miR target sites in clock genes or genes with circadian expression at a protein level only, coupled with the investigation of putative sites for clock transcription factors in the promoter of these miRs, we present a list of candidate genes that might be important for the circadian molecular machinery. Since this strategy is independent of the biological sample examined, it has the potential to reveal miRs that show circadian expression in any particular tissue.

The bioinformatics tools TargetScan, PicTar, and microrna.org have been successfully used to identify candidate genes further validated experimentally, including miRs previously mentioned in circadian studies, such as miR-182, miR-132, miR-219, miR-142-3p, and miR-16 (Alvarez-Saavedra et al., 2011; Balakrishnan et al., 2010; Cheng et al., 2007; Saus et al., 2010; Tan et al., 2012). The intersection of the results using different prediction algorithms increases the confidence of the findings. In fact, one-third of the 69 miRs were previously described with circadian expression or daily variation in different tissues (Alvarez-Saavedra et al., 2011; Balakrishnan et al., 2010; Cheng et al., 2007; Na et al., 2009; Nagel et al., 2009; Saus et al., 2010; Shende et al., 2011; Tan et al., 2012; Xu et al., 2007). Some of them modulate circadian rhythms targeting clock genes (Alvarez-Saavedra et al., 2011; Cheng et al., 2007; Nagel et al., 2009; Shende et al., 2011; Tan et al., 2012).

We selected miR-27b to investigate its expression in human leukocytes collected over a period of 24 h as an experimental model of biological rhythmicity. Studies have demonstrated that clock genes oscillate in human leukocytes and that changes in their expression are associated with different pathologies (Ando et al., 2009; Boivin et al., 2003; Cai et al., 2010; Gouin et al., 2010; Haimovich et al., 2010; Kusanagi et al., 2004; Taniguchi et al., 2009; Watanabe et al., 2012; Yang et al., 2011).

We selected miR-27b for this experimental study based on its potentially relevant functional participation in leukocyte biology. miR-27b expression is altered in T-lymphocytes from patients with multiple sclerosis (Guerau-de-Arellano et al., 2011). Moreover, there is evidence for the possible involvement of this miR in hematopoiesis and immune response through the modulation of retinoid X receptor α (RXR-alpha), peroxisome proliferator–activated receptors (PPARs), and nuclear factor-κB (NF-κB), which were previously associated with circadian rhythms (Cecon et al., 2010; Cho et al., 2009; Gerondakis et al., 2012; Grimaldi et al., 2010; Jennewein et al., 2010; Ji et al., 2009; Karbiener et al., 2011; Kawai and Rosen, 2010; Kida et al., 2011; Kim et al., 2010; McGregor and Choi, 2011; McNamara et al., 2001; Oishi et al., 2005; Rasooly et al., 2005; Stephensen et al., 2007; Thulasingam et al., 2011; Yang et al., 2010). Thus, the study of miR-27b may add to our understanding of its contribution to the normal and altered physiology of leukocytes.

Herein, miR-27b is consistently predicted to target Adcy6, which presents circadian expression in the pineal gland (Han et al., 2005) and daily variation in the retina (Xu et al., 2007). ROR-alpha and DEC2 are predicted to be potential regulators of miR-27b in human and mouse and CREB only in human (Table 2).

We showed that miR-27b presented daily variation in some subjects when they were studied individually with cosinor analysis or when they were grouped in ANOVA according to peak phase of expression (Fig. 1). The divergences in the acrophase observed between individuals may result from differences in behavior, environmental conditions, or genetic background and may have contributed to the lack of statistical significance found in some grouped data. In fact, interindividual variations have been reported in diurnal expression of clock genes in leukocytes (Balmforth et al., 2007; Teboul et al., 2005) and may be an interfering factor for ANOVA, since grouping subjects with different phases could mask temporal variation.

The amount of data across time series (interval of sampling) might not have been ideal for cosinor testing in our samples, which may have resulted in nonsignificant values, even for Per3 expression in some individuals. These, together with the total number of subjects evaluated, are limitations of our study. However, we believe that the statistical significance found in the analysis of miR-27b in different individuals, using cosinor or ANOVA, reinforces the hypothesis of a circadian variation of this miR in human leukocytes and its possible contribution to the circadian control of RXR-alpha, PPAR-gamma, NF-κB, and ACDY6 activity.

To our knowledge, this is the first study that demonstrates an in vivo diurnal variation of an miR in human tissue. Although the gene list corresponds to predicted candidates based on bioinformatic strategies, which is the main limitation of our study, the data presented in the literature and herein suggest the potential involvement of the identified miRs with the posttranscriptional regulation of biological rhythms and highlight them as potential candidates for circadian genes. Further validation studies could confirm these hypotheses.

Footnotes

Acknowledgements

This research was supported by CAPES and CNPq. The authors thank Bruna P. dos Santos for collecting blood samples.

Conflict of Interest Statement

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Note

Supplementary online material is available on the journal’s website at .

References

Alvarez-Saavedra

Antoun

Yanagiya

Oliva-Hernandez

Cornejo-Palma

Perez-Iratxeta

Sonenberg

Cheng

(2011) miRNA-132 orchestrates chromatin remodeling and translational control of the circadian clock. Hum Mol Genet 20:731-751.

Ando

Takamura

Matsuzawa-Nagata

Shima

Eto

Misu

Shiramoto

Tsuru

Irie

Fujimura

. (2009) Clock gene expression in peripheral leucocytes of patients with type 2 diabetes. Diabetologia 52:329-335.

Balakrishnan

Stearns

Park

Dreyfuss

Ashley

Rhoads

Tavakkolizadeh

(2010) MicroRNA mir-16 is anti-proliferative in enterocytes and exhibits diurnal rhythmicity in intestinal crypts. Exp Cell Res 316:3512-3521.

Balmforth

Grant

Scott

Wheatcroft

Kearney

Staels

Marx

(2007) Inter-subject differences in constitutive expression levels of the clock gene in man. Diab Vasc Dis Res 4:39-43.

Boivin

James

Cho-Park

Xiong

Sun

(2003) Circadian clock genes oscillate in human peripheral blood mononuclear cells. Blood 102:4143-4145.

Cai

Liu

Sothern

Chan

(2010) Expression of clock genes Per1 and Bmal1 in total leukocytes in health and Parkinson’s disease. Eur J Neurol 17:550-554.

Cartharius

Frech

Grote

Klocke

Haltmeier

Klingenhoff

Frisch

Bayerlein

Werner

(2005) MatInspector and beyond: promoter analysis based on transcription factor binding sites. Bioinformatics 21:2933-2942.

Cecon

Fernandes

Pinato

Ferreira

Markus

(2010) Daily variation of constitutively activated nuclear factor kappa B (NFKB) in rat pineal gland. Chronobiol Int 27:52-67.

Cheng

Papp

Varlamova

Dziema

Russell

Curfman

Nakazawa

Shimizu

Okamura

Impey

. (2007) microRNA modulation of circadian-clock period and entrainment. Neuron 54:813-829.

10.

Cho

Noshiro

Choi

Morita

Kawamoto

Fujimoto

Kato

Makishima

(2009) The basic helix-loop-helix proteins differentiated embryo chondrocyte (DEC) 1 and DEC2 function as corepressors of retinoid X receptors. Mol Pharmacol 76:1360-1369.

11.

Filipowicz

Bhattacharyya

Sonenberg

(2008) Mechanisms of post-transcriptional regulation by microRNAs: are the answers in sight? Nat Rev Genet 9:102-114.

12.

Gerondakis

Banerjee

Grigoriadis

Vasanthakumar

Gugasyan

Sidwell

Grumont

(2012) NF-kappaB subunit specificity in hemopoiesis. Immunol Rev 246:272-285.

13.

Gouin

Connors

Kiecolt-Glaser

Glaser

Malarkey

Atkinson

Beversdorf

Quan

(2010) Altered expression of circadian rhythm genes among individuals with a history of depression. J Affect Disord 126:161-166.

14.

Grimaldi

Bellet

Katada

Astarita

Hirayama

Amin

Granneman

Piomelli

Leff

Sassone-Corsi

(2010) PER2 controls lipid metabolism by direct regulation of PPARgamma. Cell Metab 12:509-520.

15.

Guerau-de-Arellano

Smith

Godlewski

Liu

Winger

Lawler

Whitacre

Racke

Lovett-Racke

(2011) Micro-RNA dysregulation in multiple sclerosis favours pro-inflammatory T-cell-mediated autoimmunity. Brain 134:3578-3589.

16.

Haimovich

Calvano

Haimovich

Calvano

Coyle

Lowry

(2010) In vivo endotoxin synchronizes and suppresses clock gene expression in human peripheral blood leukocytes. Crit Care Med 38:751-758.

17.

Han

Kim

(2005) Rhythmic expression of adenylyl cyclase VI contributes to the differential regulation of serotonin N-acetyltransferase by bradykinin in rat pineal glands. J Biol Chem 280:38228-38234.

18.

Horne

Ostberg

(1976) A self-assessment questionnaire to determine morningness-eveningness in human circadian rhythms. Int J Chronobiol 4:97-110.

19.

Jennewein

von Knethen

Schmid

Brune

(2010) MicroRNA-27b contributes to lipopolysaccharide-mediated peroxisome proliferator-activated receptor gamma (PPARgamma) mRNA destabilization. J Biol Chem 285:11846-11853.

20.

Zhang

Huang

Qian

Wang

Mei

(2009) Over-expressed microRNA-27a and 27b influence fat accumulation and cell proliferation during rat hepatic stellate cell activation. FEBS Lett 583:759-766.

21.

Karbiener

Neuhold

Opriessnig

Prokesch

Bogner-Strauss

Scheideler

(2011) MicroRNA-30c promotes human adipocyte differentiation and co-represses PAI-1 and ALK2. RNA Biol 8:850-860.

22.

Kawai

Rosen

(2010) PPARgamma: a circadian transcription factor in adipogenesis and osteogenesis. Nat Rev Endocrinol 6:629-636.

23.

Kida

Nakajima

Mohri

Oda

Takagi

Fukami

Yokoi

(2011) PPARalpha is regulated by miR-21 and miR-27b in human liver. Pharm Res 28:2467-2476.

24.

Kim

Lee

Son

Lee

Kim

(2010) miR-27a is a negative regulator of adipocyte differentiation via suppressing PPARgamma expression. Biochem Biophys Res Commun 392:323-328.

25.

Koike

Yoo

Huang

Kumar

Lee

Kim

Takahashi

(2012) Transcriptional architecture and chromatin landscape of the core circadian clock in mammals. Science 338:349-354.

26.

Kojima

Gatfield

Esau

Green

(2010) MicroRNA-122 modulates the rhythmic expression profile of the circadian deadenylase Nocturnin in mouse liver. PLoS One 5:e11264.

27.

Krol

Loedige

Filipowicz

(2010) The widespread regulation of microRNA biogenesis, function and decay. Nat Rev Genet 11:597-610.

28.

Kusanagi

Mishima

Satoh

Echizenya

Katoh

Shimizu

(2004) Similar profiles in human period1 gene expression in peripheral mononuclear and polymorphonuclear cells. Neurosci Lett 365:124-127.

29.

Lewis

Shih

Jones-Rhoades

Bartel

Burge

(2003) Prediction of mammalian microRNA targets. Cell 115:787-798.

30.

Luo

Sehgal

(2012) Regulation of circadian behavioral output via a MicroRNA-JAK/STAT circuit. Cell 148:765-779.

31.

McGregor

Choi

(2011) microRNAs in the regulation of adipogenesis and obesity. Curr Mol Med 11:304-316.

32.

McNamara

Seo

Rudic

Sehgal

Chakravarti

FitzGerald

(2001) Regulation of CLOCK and MOP4 by nuclear hormone receptors in the vasculature: a humoral mechanism to reset a peripheral clock. Cell 105:877-889.

33.

Sung

Lee

Choi

Park

Shin

Kim

(2009) Comprehensive analysis of microRNA-mRNA co-expression in circadian rhythm. Exp Mol Med 41:638-647.

34.

Nagel

Clijsters

Agami

(2009) The miRNA-192/194 cluster regulates the Period gene family and the circadian clock. FEBS J 276:5447-5455.

35.

Oishi

Shirai

Ishida

(2005) CLOCK is involved in the circadian transactivation of peroxisome-proliferator-activated receptor alpha (PPARalpha) in mice. Biochem J 386:575-581.

36.

Pegoraro

Tauber

(2008) The role of microRNAs (miRNA) in circadian rhythmicity. J Genet 87:505-511.

37.

Rasooly

Schuster

Gregg

Xiao

Chandraratna

Stephensen

(2005) Retinoid x receptor agonists increase bcl2a1 expression and decrease apoptosis of naive T lymphocytes. J Immunol 175:7916-7929.

38.

Reddy

Karp

Maywood

Sage

Deery

O’Neill

Wong

Chesham

Odell

Lilley

. (2006) Circadian orchestration of the hepatic proteome. Curr Biol 16:1107-1115.

39.

Saus

Soria

Escaramis

Vivarelli

Crespo

Kagerbauer

Menchon

Urretavizcaya

Gratacos

Estivill

(2010) Genetic variants and abnormal processing of pre-miR-182, a circadian clock modulator, in major depression patients with late insomnia. Hum Mol Genet 19:4017-4025.

40.

Shende

Goldrick

Ramani

Earnest

(2011) Expression and rhythmic modulation of circulating microRNAs targeting the clock gene Bmal1 in mice. PLoS One 6:e22586.

41.

Stephensen

Borowsky

Lloyd

(2007) Disruption of Rxra gene in thymocytes and T lymphocytes modestly alters lymphocyte frequencies, proliferation, survival and T helper type 1/type 2 balance. Immunology 121:484-498.

42.

Tan

Zhang

Zhou

Yin

Pan

Peng

(2012) Clock-controlled mir-142-3p can target its activator, Bmal1. BMC Mol Biol 13:27.

43.

Taniguchi

Fernandez

Setien

Ropero

Ballestar

Villanueva

Yamamoto

Imai

Shinomura

Esteller

(2009) Epigenetic inactivation of the circadian clock gene BMAL1 in hematologic malignancies. Cancer Res 69:8447-8454.

44.

Teboul

Barrat-Petit

Claustrat

Formento

Delaunay

Levi

Milano

(2005) Atypical patterns of circadian clock gene expression in human peripheral blood mononuclear cells. J Mol Med (Berl) 83:693-699.

45.

Thulasingam

Massilamany

Gangaplara

Dai

Yarbaeva

Subramaniam

Riethoven

Eudy

Lou

Reddy

(2011) miR-27b*, an oxidative stress-responsive microRNA modulates nuclear factor-kB pathway in RAW 264.7 cells. Mol Cell Biochem 352:181-188.

46.

Vandesompele

De Preter

Pattyn

Poppe

Van Roy

De Paepe

Speleman

(2002) Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes. Genome Biol 3:RESEARCH0034.

47.

Watanabe

Hida

Kitamura

Enomoto

Ohsawa

Katayose

Nozaki

Moriguchi

Aritake

Higuchi

. (2012) Rhythmic expression of circadian clock genes in human leukocytes and beard hair follicle cells. Biochem Biophys Res Commun 425:902-907.

48.

Xia

Cao

Shao

(2009) Progress in miRNA target prediction and identification. Sci China C Life Sci 52:1123-1130.

49.

Witmer

Lumayag

Kovacs

Valle

(2007) MicroRNA (miRNA) transcriptome of mouse retina and identification of a sensory organ-specific miRNA cluster. J Biol Chem 282:25053-25066.

50.

Yamakuchi

(2012) MicroRNA Regulation of SIRT1. Front Physiol 3:68.

51.

Yang

Lin

Hsu

Hsiao

Liu

Tsai

Chang

Lin

(2011) Altered expression of circadian clock genes in human chronic myeloid leukemia. J Biol Rhythms 26:136-148.

52.

Yang

Guo

Wan

(2010) Deregulation of growth factor, circadian clock, and cell cycle signaling in regenerating hepatocyte RXRalpha-deficient mouse livers. Am J Pathol 176:733-743.

53.

Yoon

De Micheli

(2006) Computational identification of microRNAs and their targets. Birth Defects Res C Embryo Today 78:118-128.

Supplementary Material

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Predicted MicroRNAs for Mammalian Circadian Rhythms

Abstract

Keywords

Materials and Methods

Analysis of 3′UTR Region of Clock Genes

Identification of Putative Target Sites for Circadian Transcription Factors in the Promoter of Candidate miRs

Quantitative Real-Time PCR

Statistical Analysis

Results

Discussion

Footnotes

Acknowledgements

Conflict of Interest Statement

Note

References

Supplementary Material