Advertisement
Browse Subject Areas
?

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here.

  • Loading metrics

Identification of Restricted Subsets of Mature microRNA Abnormally Expressed in Inactive Colonic Mucosa of Patients with Inflammatory Bowel Disease

  • Magali Fasseu ,

    Contributed equally to this work with: Magali Fasseu, Xavier Tréton

    Affiliations INSERM U773, Centre de Recherche Biomédicale Bichat Beaujon, Paris, France, Université Paris 7 Denis Diderot, Paris, France

  • Xavier Tréton ,

    Contributed equally to this work with: Magali Fasseu, Xavier Tréton

    Affiliations INSERM U773, Centre de Recherche Biomédicale Bichat Beaujon, Paris, France, Université Paris 7 Denis Diderot, Paris, France, Service de Gastroentérologie et d'Assistance Nutritive, Hôpital Beaujon, Clichy, France

  • Cécile Guichard,

    Affiliations INSERM U773, Centre de Recherche Biomédicale Bichat Beaujon, Paris, France, Université Paris 7 Denis Diderot, Paris, France

  • Eric Pedruzzi,

    Affiliations INSERM U773, Centre de Recherche Biomédicale Bichat Beaujon, Paris, France, Université Paris 7 Denis Diderot, Paris, France

  • Dominique Cazals-Hatem,

    Affiliations INSERM U773, Centre de Recherche Biomédicale Bichat Beaujon, Paris, France, Université Paris 7 Denis Diderot, Paris, France, Service d'Anatomo-Pathologie, Hôpital Beaujon, Clichy, France

  • Christophe Richard,

    Affiliations INSERM U773, Centre de Recherche Biomédicale Bichat Beaujon, Paris, France, Université Paris 7 Denis Diderot, Paris, France

  • Thomas Aparicio,

    Affiliations INSERM U773, Centre de Recherche Biomédicale Bichat Beaujon, Paris, France, Université Paris 7 Denis Diderot, Paris, France, Service de Gastroentérologie, Hôpital Xavier Bichat, Paris, France

  • Fanny Daniel,

    Affiliations INSERM U773, Centre de Recherche Biomédicale Bichat Beaujon, Paris, France, Université Paris 7 Denis Diderot, Paris, France

  • Jean-Claude Soulé,

    Affiliations INSERM U773, Centre de Recherche Biomédicale Bichat Beaujon, Paris, France, Université Paris 7 Denis Diderot, Paris, France, Service de Gastroentérologie, Hôpital Xavier Bichat, Paris, France

  • Richard Moreau,

    Affiliations INSERM U773, Centre de Recherche Biomédicale Bichat Beaujon, Paris, France, Université Paris 7 Denis Diderot, Paris, France

  • Yoram Bouhnik,

    Affiliations INSERM U773, Centre de Recherche Biomédicale Bichat Beaujon, Paris, France, Université Paris 7 Denis Diderot, Paris, France, Service de Gastroentérologie et d'Assistance Nutritive, Hôpital Beaujon, Clichy, France

  • Marc Laburthe,

    Affiliations INSERM U773, Centre de Recherche Biomédicale Bichat Beaujon, Paris, France, Université Paris 7 Denis Diderot, Paris, France

  • André Groyer ,

    andre.groyer@inserm.fr

    These authors also contributed equally to this work.

    Affiliations INSERM U773, Centre de Recherche Biomédicale Bichat Beaujon, Paris, France, Université Paris 7 Denis Diderot, Paris, France

  • Eric Ogier-Denis

    These authors also contributed equally to this work.

    Affiliations INSERM U773, Centre de Recherche Biomédicale Bichat Beaujon, Paris, France, Université Paris 7 Denis Diderot, Paris, France

Identification of Restricted Subsets of Mature microRNA Abnormally Expressed in Inactive Colonic Mucosa of Patients with Inflammatory Bowel Disease

  • Magali Fasseu, 
  • Xavier Tréton, 
  • Cécile Guichard, 
  • Eric Pedruzzi, 
  • Dominique Cazals-Hatem, 
  • Christophe Richard, 
  • Thomas Aparicio, 
  • Fanny Daniel, 
  • Jean-Claude Soulé, 
  • Richard Moreau
PLOS
x

Abstract

Background

Ulcerative Colitis (UC) and Crohn's Disease (CD) are two chronic Inflammatory Bowel Diseases (IBD) affecting the intestinal mucosa. Current understanding of IBD pathogenesis points out the interplay of genetic events and environmental cues in the dysregulated immune response. We hypothesized that dysregulated microRNA (miRNA) expression may contribute to IBD pathogenesis. miRNAs are small, non-coding RNAs which prevent protein synthesis through translational suppression or mRNAs degradation, and regulate several physiological processes.

Methodology/Findings

Expression of mature miRNAs was studied by Q-PCR in inactive colonic mucosa of patients with UC (8), CD (8) and expressed relative to that observed in healthy controls (10). Only miRNAs with highly altered expression (>5 or <0.2 -fold relative to control) were considered when Q-PCR data were analyzed. Two subsets of 14 (UC) and 23 (CD) miRNAs with highly altered expression (5.2->100 -fold and 0.05–0.19 -fold for over- and under- expression, respectively; 0.001<p≤0.05) were identified in quiescent colonic mucosa, 8 being commonly dysregulated in non-inflamed UC and CD (mir-26a,-29a,-29b,-30c,-126*,-127-3p,-196a,-324-3p). Several miRNA genes with dysregulated expression co-localize with acknowledged IBD-susceptibility loci while others, (eg. clustered on 14q32.31), map on chromosomal regions not previously recognized as IBD-susceptibility loci. In addition, in silico clustering analysis identified 5 miRNAs (mir-26a,-29b,-126*,-127-3p,-324-3p) that share coordinated dysregulation of expression both in quiescent and in inflamed colonic mucosa of IBD patients. Six miRNAs displayed significantly distinct alteration of expression in non-inflamed colonic biopsies of UC and CD patients (mir-196b,-199a-3p,-199b-5p,-320a,-150,-223).

Conclusions/Significance

Our study supports miRNAs as crucial players in the onset and/or relapse of inflammation from quiescent mucosal tissues in IBD patients. It allows speculating a role for miRNAs as contributors to IBD susceptibility and suggests that some of the miRNA with altered expression in the quiescent mucosa of IBD patients may define miRNA signatures for UC and CD and help develop new diagnostic biomarkers.

Introduction

Ulcerative Colitis (UC) and Crohn's Disease (CD) are two subphenotypes of inflammatory bowel disease (IBD) affecting the intestinal mucosa. UC and CD share similarities such as a chronic relapsing-remitting course and common extra-intestinal manifestations. However, several differences in localization (any part of the gastrointestinal tract -CD- or restricted to the colon -UC), endoscopic appearance and histology support differences in underlying physiopathology.

The current understanding of IBD pathogenesis points out the interplay of genetic, epigenetic and environmental factors in the dysregulated immune response of the intestinal mucosa [1][3] where inappropriate control of innate and acquired immunity plays a major role [4].

Long term follow-up stressed that basal colonic lesions extend progressively in more than 50% of UC patients [5]. In CD patients, ileal recurrence involving microscopically quiescent tissues at the time of ileo-colonic resection was reported to reach 73% at one year [6]. These observations suggest that quiescent mucosa of IBD patients display increased susceptibility to inflammation. In this connection, animals models (mice carrying intestinal epithelial cell-specific invalidation of genes involved in the unfolded protein response -XBP1, X-box Protein 1- or essential for embryonic development of the colon -HNF4, Hepatic Nuclear Factor 4) support the notion that epithelial cell dysfunction in the quiescent mucosa can trigger intestinal inflammation [7][8]. However the early epithelial disorders that, in pre-inflammatory states, confer susceptibility to uncontrolled mucosal inflammation remain poorly understood.

Strong evidence supports UC and CD as complex genetic disorders with significant overlap and mandates systematic approaches to identify causal molecular events. First, Genome Wide Association Scans (GWAS) [9][19] and candidate gene approach [20][25] led to the identification of more than 30 susceptibility loci for CD and UC and identified “IBD-specific” gene variants within these loci (eg. CARD15, TNFSF15, IL23R, ATG16L1, IRGM, PTPN2). Otherwise, genome-wide arrays and subtractive hybridization studies identified hundreds of mRNAs with altered expression in non-inflamed [26], [27] and in inflamed [28][32] colonic biopsies obtained from UC and CD patients. This provided valuable insights into dysregulated gene expression associated with IBD. In this connection, we hypothesized that dysregulated microRNA (miRNA) gene expression and/or pri-/pre- miRNA maturation may contribute to IBD pathogenesis.

miRNAs are small (∼18–24 nt), non-coding RNAs which, by base-pairing to complementary sequences in the 3′-UTR of selected mRNA targets, prevent protein synthesis either by translational suppression [33], [34] or by degradation of their target mRNAs [35], [36]. miRNAs are regulators of early development, cell fate determination, differentiation, proliferation, apoptosis [37][39] and dysregulation of their expression has been involved in various human diseases such as cancer [40][44], developmental abnormalities [45], muscular disorders [46] and inflammatory diseases [47][51].

In the present paper, our first objective was to pinpoint alterations in the pattern of miRNA expression in the non-inflamed colonic mucosa of UC and CD patients relative to that of healthy subjects. Indeed, such altered miRNA expression in the quiescent colonic mucosa of IBD patients may account for epithelial dysfunction in the absence of epithelial damage (eg. ulcerations) and sensitize the mucosa to severe inflammation and infiltration of immune cells. Our second objective was to search whether dysregulated expression of several miRNAs may be coordinated and thus contribute to IBD susceptibility.

Results

In a first series of experiments, miRNA expression was quantified in right and left colon from healthy control subjects. Measuring the abundance of 321 mature human miRNA transcripts by real-time Q-PCR, preliminary analysis (2−ΔCT) showed that right and left colon displayed similar patterns of miRNA expression, as exemplified for a subset of miRNAs in Table S1.

In a second series of experiments, miRNA expression was measured by real-time Q-PCR in biopsies from UC and CD patients (Table 1; quiescent and inflamed mucosal tissues, Figure S1). Overall, miRNA expression varied continuously from −11.06 to +20.31 -fold (quiescent and inflamed CD biopsies) and from −7.50 to +18.34 -fold (quiescent and inflamed UC biopsies) when compared to healthy control subjects. However, a careful inspection of the data showed that even under our strictly controlled (i) biopsy selection (Figure S2), (ii) RT and (iii) Q-PCR conditions, miRNA expression levels were variable among patients (Figure S3). Thus, in order to avoid false/erroneous classification of miRNAs as up- and down- regulated in mucosal biopsies of IBD patients, only miRNAs with alterations of expression that fitted stringent thresholds (2−ΔΔCT>5-fold and 2−ΔΔCT<0.2-fold, respectively) were considered.

miRNA expression is altered in both UC and CD

In order to check for specific modifications that may account for epithelial cell dysfunction in the quiescent colonic mucosa of IBD patients, we focused on biopsies scored grades 0 and 1 (both grades were observed in healthy controls and in quiescent UC and CD mucosa; Table S2). However, grades 2–4 (inflamed mucosa; see Figure S1) were also studied for comparison of both stages of the diseases.

According to our stringent criteria for the selection of miRNAs with altered expression, up- and down- regulations were balanced in UC (45.47% and 54.5%, respectively), whereas up-regulation was predominant (88.2%) in CD.

UC. 173 miRNAs were expressed above the level of detection (CT<35). Of the 22 miRNAs that fit our stringent criteria, only 14 (7 up- and 7 down- regulated) exhibited significant differential expression when non-inflamed UC and healthy control tissues were compared (0.001<p<0.05; non parametric Mann-Whitney test), (Table S3, Figure 1A). With respect to cut-off values and statistical significance the expression of 9 miRNAs was dysregulated in both quiescent and inflamed UC mucosa and that of 1 miRNAs was specifically dysregulated in quiescent UC mucosa (mir-196a).

thumbnail
Figure 1. Disease- and stage- specific alterations of miRNA expression.

miRNA expression was measured in non-inflamed and inflamed UC and CD tissues and computed vs. that measured in healthy controls. The total numbers of miRNAs that were underexpressed and overexpressed in non-inflamed (dark-colored ovals) or inflamed (light-colored ovals) IBD tissues, as well as those that were commonly altered in both states of the disease (intersect between light and dark-colored ovals) were determined. UC (A) or CD (B) tissues were considered independently. (C) miRNAs that were underexpressed and overexpressed in non-inflamed UC (dark-blue) or non-inflamed CD (dark-red), as well as those that were commonly altered in both diseases (intersect between ovals) were determined. Underexpressed miRNAs are underlined. Bolded characters, miRNA with statistically significant dysregulation of expression relative to healthy controls (p≤0.05).

https://doi.org/10.1371/journal.pone.0013160.g001

CD. 204 miRNAs were expressed above the level of detection. Of the 33 miRNAs that fit our stringent criteria, only 23 (all up-regulated) exhibited significant differential expression when non-inflamed CD and healthy control tissues were compared (0.002<p<0.05; non parametric Mann-Whitney test), (Table S4, Figure 1B). With respect to cut-off values and statistical significance the expression of 18 miRNAs were dysregulated in both quiescent and inflamed CD mucosa and that of 4 miRNAs were specifically dysregulated in quiescent CD mucosa (mir-9*, mir-30a*, mir-30c, mir-223).

Finally, taking into account cut-off values and statistical significance, we also noticed alterations in miRNA expression specific to inflamed UC or CD tissues (4 and 5 miRNAs, respectively) (Figure 1A, B).

Common and specific alterations in miRNA expression in UC and CD

With respect to cut-off values and statistical significance 8 miRNAs shared common altered expression in non-inflamed CD and in non-inflamed UC (Figure 1C, Table S5), of which 6 (all but mir-30c, and mir-196a) were also overexpressed both in inflamed UC and in inflamed CD biopsies.

On the other hand, the expression of 6 miRNAs was statistically different in non-inflamed colonic biopsies of UC and CD patients (mir-150, p = 0.0273; mir-196b, p = 0.0472; mir-199a-3p, p = 0.0472; mir-199b-5p, p = 0.0283; mir-223, p = 0.0357 and mir-320a, p = 0.0163; non-parametric Mann-Whitney test) (Figure 2). These miRNAs, and an additional selection of 9 miRNAs (selected in an unsupervised manner using the GenePattern “ComparativeMarkerSelection” module) (Owing to patent pending the identity of these miRNA is not disclosed in the manuscript) were tested for their ability to discriminate between UC and CD. Classification was performed with a supervised algorithm (GenePattern “KNNXValidation” module). Based on the clinical classification of our panel of patients as UC or CD, the selection of 15 miRNAs was able to predict 15/16 patients in their true class (Table 2).

thumbnail
Figure 2. miRNAs with differentially altered expression in non-inflamed UC and CD tissues : Box-whisker plot analysis.

miRNA expression was measured in non-inflamed colonic mucosa obtained from UC and CD patients (8 patients/IBD) and computed vs. that measured in healthy controls. Data corresponding to 6 miRNAs (mir-150, mir-196b, mir-199a-3p, mir-199b-5p, mir-223 and mir-320a) with statistically different alteration of expression in UC and CD mucosal tissues are presented as box-whisker plots [78] (box, 25–75%; whisker, 10–90%; line, median); p<0.05.

https://doi.org/10.1371/journal.pone.0013160.g002

thumbnail
Table 2. Achievement of patient's class (UC or CD) prediction using the selection of 15 miRNAs.

https://doi.org/10.1371/journal.pone.0013160.t002

Altogether, these data unambiguously show that altered miRNA expression pre-exists in non-inflamed UC and CD mucosa.

Concerted regulation of miRNA expression in UC and CD

We then sought whether the altered levels of miRNA noticed in both quiescent UC and CD colonic mucosa could be accounted for by coordinated regulation(s) of miRNA expression. In silico clustering was achieved in an unsupervised manner using a K-Means algorithm, the expression data being partitioned into 20 distinct computational clusters. Interestingly, 7/8 miRNAs overexpressed both in non-inflamed UC and CD tissues (mir-26a, mir-29a, mir-29b, mir-30c, mir-126*, mir-127-3p, mir-324-3p), localized on different chromosomes, were assigned to a single computational cluster (cluster #7) when examining UC data, and to two such clusters (cluster #7: mir-26a, mir-30c, mir-127-3p, mir-324-3p and cluster #13: mir-29a, mir-29b, mir-126*) when CD data were inspected (Table 3). Moreover, five of these miRNAs (mir-26a, mir-29b, mir-126*, mir-127-3p, mir-324-3p) were also assigned to a single computational cluster when inflamed UC (cluster #7) and CD (cluster #13) data were classified. This suggested common regulation of expression for mir-26a, mir-29b, mir-126*, mir-127-3p and mir-324-3p.

thumbnail
Table 3. Concerted regulation of expression of miRNAs in non-inflamed and inflamed CD and UC tissues.

https://doi.org/10.1371/journal.pone.0013160.t003

Chromosomal localization of miRNA genes with altered expression

The chromosomal distribution of miRNA genes with altered expression in UC and CD mucosa was not even. Indeed, 9 chromosomes (1, 5, 9, 11, 14, 15, 17, 19 and X) housed ≥4 and up to 12 miRNA genes with dysregulated expression (overall: ∼70% of such miRNAs genes) (Table S6, Figure S4). The chromosomal loci where miRNA genes with dysregulated expression are localized encompass either one, two (miRNA duplexes) or more (miRNA clusters) distinct miRNA genes.

Interestingly, it could be observed that several miRNAs mapped within acknowledged IBD susceptibility loci (IBD-2, 3, 5 and 6), or colocalized with genetic variations identified in several GWAS studies that (i) account for part of the overall genetic susceptibility to CD and (ii) contribute to UC pathogenesis (Figure S5, Table S7). None mapped with IBD susceptibility loci 1, 4, 7, 8 and 9.

Otherwise, one chromosomal miRNA cluster (on chromosome 14q32.31) and several miRNA duplexes (6q13, 7q32.3, 9q34.11–q34.3, 15q26.1; 17p13.1–p13.3, 22q11.21, Xq26.2) were identified that map on chromosomal regions that have not been previously reported as IBD-susceptibility loci (Figure S5, Table 4). Interestingly, in the majority of loci, alterations of miRNA expression were observed in quiescent UC and CD tissues.

thumbnail
Table 4. Compilation of the sub-chromosomal regions where two or more miRNA genes with altered expression colocalize.

https://doi.org/10.1371/journal.pone.0013160.t004

Alteration of miRNA expression: in silico characterization of target transcripts

Identification of a subset of 8 miRNAs that share common regulated overexpression in both UC and CD (see Table S5) could represent the first step towards the identification of regulatory networks, the dysregulation of which could be involved in the pathophysiology of IBD. In silico, 4094 genes (372 strictly down-regulated genes) stand as putative targets for these miRNAs.

Exploring the molecular functions associated to these gene products using The Gene Ontology, GeneCards and GeneNote data bases, we found associations to several biological processes (Figure 3). These include (i) cell proliferation (Cyclins D1, D2 and E1, PCNA, CDKs 6 and 8, GADD45A, RB1), (ii) apoptosis (BCL2, Caspase 2, C/EBP β,γ, DAPK, FOXO3, PTEN), (iii) autophagy (ATG 4a, 5 and 9a, Beclin-1, CDKN1B, IFNγ), (iv) extracellular matrix organization, cell adhesion and cell surface marker gene expression (COL(1,11,12,15,16)A1, Integrin-α1,2,3,5, β1,3, Laminin γ1, MMPs 13 and 16, Keratin 5, NCAM1), (v) oxidative stress (GPX4, OXR1, OSXR1), (vi) the unfolded protein response (HSPA5, HSPA2, SERP1, XBP-1, EIF2AK3, ETF1) (vii) innate and adaptive immunity (IL1A, IL10, IL1R1, IL6R, IRAK2, p40phox, TLR10, CXCL2, 12 and 14, CXCR4, NFATC3 and C4, PREX1). In addition, several of these genes are acknowledged IBD-susceptibility genes or are localized at replicated risk loci identified by GWAS (eg. ATG16L1, IL10, IL12B, JAK2, ARPC2, PTGER4, ZNF365, NKX2-3, PTPN2, PTPN22, C11orf30, ORMDL3, STAT3 (Table S8).

thumbnail
Figure 3. Alteration of miRNA expression in the colonic mucosa of UC and CD patients: in silico characterization of target transcripts.

The exhaustive list of genes which are putatively targeted by the subset of 8 miRNAs that share common dysregulated expression both in quiescent UC and in quiescent CD was downloaded from the PITA catalog of predicted human microRNA targets (http://genie.weizmann.ac.il/pubs/mir07/mir07_data.html). The algorithm makes use of the parameter-free model for miRNA-target interaction described by Kertesz et al. [75]. The total number of genes involved in each single biological process is computed. Strict down regulation (light purple) stands for genes, the 3′-UTR of which interacts only with up-regulated miRNA(s).

https://doi.org/10.1371/journal.pone.0013160.g003

Discussion

In the present study, we have addressed the question of whether altered miRNA expression in quiescent UC and CD mucosa may be relevant to IBD pathogenesis. Our data allowed two major conclusions.

First. Alteration of miRNA expression was not confined to inflamed (grades 2–4), but preexisted in non-inflamed (grades 0 and 1) mucosa. Applying strictly controlled RT and real-time Q-PCR protocols and stringent cut-off values (>5-fold or <0.2-fold vs. healthy individuals), we identified 14 and 23 miRNAs with dysregulated expression in non-inflamed UC and CD biopsies, respectively, of which 8 were similarly dysregulated both in non-inflamed UC and CD biopsies. Our observation that mir-26a and 29a are up-regulated in quiescent UC mucosa has also been reported by Wu et al. [51]. In contrast, the other miRNAs (9/10, mir-629 was not tested in our screen) which were found to be up- (eg. mir-21, mir-126 and Let-7f) or down- (eg. mir-19b) regulated in [51] displayed only slight alterations in relative expression that did not match the stringent selection criteria we applied in our study. This suggests (i) that the discrepancies between both studies may be explained either by the differential sensitivity of the methods used for initial screening (microarray vs. real-time Q-PCR) and/or rather by the drastic cut-off value (>5-fold or <0.2-fold) we used to state altered miRNA expression in the present study and (ii) that the overlap in the alteration of miRNA expression observed in our study and in that reported by Wu et al. [51] may not have occurred only by chance. As far as we are aware, alteration of miRNA expression in non-inflamed CD colonic biopsies has not yet been reported.

Importantly, despite (i) the choice of a drastic cut-off that takes into account the variability in miRNA expression between IBD patients and (ii) the limited number of subjects kept for analysis in the present study, we could select miRNAs highly and significantly dysregulated in IBD relative to healthy controls. Interestingly, comparison of non-inflamed to inflamed tissues showed significant overlap in the alteration pattern of miRNA expression both in CD patients (this study) and UC (this study, [51]).

Altogether, these results support the notion that dysregulation of miRNA expression pre-exists in the quiescent colonic mucosa of UC and CD patients and may play a key role in the sensitization of the quiescent mucosa to environmental factors and/or to IBD inducers (ie. commensal flora), and in fine the onset and/or relapse of inflammation. Furthermore, they suggest that quiescent UC and CD mucosa already has distinct miRNA signatures which are not associated with significant variations in cellular contexts. Indeed, the quiescent colonic mucosa of IBD patients and that of healthy subjects were almost similar (grades 0 or 1 in both cases).

Since significant overlap was observed in the alteration of miRNA expression in quiescent UC and CD mucosa, our results also imply that several common molecular mechanisms may underlie the UC and CD pathogenic processes. Furthermore, alteration of miRNA expression in quiescent IBD tissues is consistent with the notion that genetic variants that result in differential gene expression (eg. that of regulatory molecules such as miRNAs) as well as mutations in the open reading frame are expected to contribute to multifaceted diseases.

In this connection, one major drawback in investigating the dysregulation of miRNAs and of protein-coding genes expression in IBD tissues is related to cell type variations between samples (eg. inflamed vs. quiescent mucosa and normal healthy tissue). Indeed, inflamed mucosal tissue is characterized by a decreased number of epithelial cells, concomitant with an increased infiltration of inflammatory cells. This bias was taken into account in some genome wide cDNA microarray studies [26] but not in others [31]. For instance, decreased MICA (a gene expressed in intestinal epithelial cells) transcript expression was reported in inflamed CD [31] whereas flow cytometry and immuno-histochemistry identified strong MICA overexpression in intestinal epithelial cells of macroscopically involved areas of CD patients [52]. Similarly, it could be anticipated that the decreased level of mir-192 expression in inflamed mucosa of UC patients [51] may depend on cell-type heterogeneity between non-inflamed and inflamed mucosal tissues rather than on decreased gene expression (of note, in our study the slight decrease in mir-192 expression did not match our selection criteria in inflamed UC mucosa). Thus, the increase in MIP2α expression observed in [51] could be miRNA-independent and accounted for by increased TNFα secretion by immune infiltrating cells.

Finally, starting with a wide screen of 321 miRNAs, we could define (i) a selection of 8 miRNAs relevant in defining quiescent IBD vs. healthy mucosa and (ii) a distinct subset of 15 miRNAs (Patent pending) that allows discriminating between non-inflamed UC and CD colonic mucosa and may define specific biomarkers relevant for UC and CD. Indeed on the basis of our panel of 16 patients, this selection of 15 miRNAs was able to predict 15/16 patients (94%) as UC or CD correctly. Such biomarkers may prove helpful as diagnostic tools of minimal invasivity (eg. for pediatric patients, incomplete colonoscopy) and as guidelines for surgical decisions. It can also be anticipated that miRNA signatures could be associated with different IBD profiles as prognostic biomarkers. This is out of the scope of the present study and deserves further studies on a larger cohort of patients.

Second. miRNAs play a major role in regulating coding-gene expression at the transcript and/or translational levels [34], [36]. In this connection, we would like to emphasize that our study is the first one that reports the mapping of several miRNA genes with altered expression in quiescent UC and CD mucosa (i) at acknowledged IBD loci [53][55] or (ii) at loci conclusively associated with CD [11], [16] } or UC [12], [13], [19] by GWAS studies. In this connection, we should like to emphasize that the co-localization of miRNA genes with dyregulated expression at chromosomal loci associated with IBD susceptibility does not occur only by chance. Indeed, our computations show that 1 miRNA gene (out of 321 tested) would be expected to be localized by chance in the vicinity of the 50 loci reported in [11], [12], [16][19] where 14 miRNA genes (14-fold more) with altered expression in quiescent UC and CD tissues map. In addition, even if 8 miRNA genes could map by chance within IBD susceptibility loci 1, 4, 7, 8 and 9, no miRNA genes with altered expression in quiescent UC and CD tissues were localized in these chromosomal regions (although they encompass a total of 18 miRNA genes, the expression of which is not altered in IBD).

On this basis, we speculate that in addition to mutational events, IBD susceptibility might result from dysregulated miRNA expression in intestinal mucosa and to subsequent alteration of miRNA-dependent regulation of gene expression; consistent with the notion that not only allele variation, but also the alteration of regulatory processes that result in differential gene expression may contribute to multifaceted diseases.

Furthermore, our study characterizes band 14q32.31 as a cluster of 3 miRNA genes with altered expression in IBD. With the exception of mir-382, these miRNAs display altered expression in quiescent UC (mir-127-3p, mir-370) or in quiescent CD (mir-127-3p) mucosa. These miRNA genes are intergenic and constitute at least two distinct transcription units (mir-127 and mir-370). Alteration of miRNA expression within this sub-chromosomal region does not result from the overall chromosomal environment since (i) only the expression of 3 (UC) and 1 (CD) miRNAs was altered out of 38 localized within a DNA stretch of 44.74 kbp at 14q32.31, (ii) expression was either increased (mir-127-3p, CD/UC; mir-382, UC) or decreased (mir-370, UC) and (iii) expression was altered either in non-inflamed or in inflamed or in both states of the diseases. We speculate band 14q32.31 may represent a new, yet undefined IBD-susceptibility locus; this remains to be established and will be the subject of future studies.

Finally, the tight coordinated regulation of mir-26a, mir-29b, mir-126*, mir-127-3p and mir-324-3p (which genes are widespread on several chromosomes) in non-inflamed UC and CD mucosa also suggests that alteration of miRNA expression do contribute to the physiopathology of IBD. Interestingly, such concerted regulation of expression correlates with related biological functions. For instance, these miRNAs have been demonstrated to play roles either in cell cycle regulation, or in tumorigenesis in a broad spectrum of solid tumors (mir-26a, mir-29b, mir-127-3p and mir-324) [56][61], in the regulation of epithelial-mesenchymal transition and invasiveness (mir-126*) [62], [63] or in the control of apoptosis (mir-29b and mir-126*) [64], [65], in line with the higher than spontaneous occurrence of colorectal cancer (5-10%) in IBD patients. Of note, a recent study has reported that the mir-29 family of miRNAs regulates intestinal membrane permeability [66]. This observation should be connected with the increased gut permeability observed in IBD patients [67].

In silico studies emphasized that the transcripts targeted by the 8 miRNAs which share common overexpression in the quiescent colonic mucosa of both UC and CD patients correspond to genes that are involved/implicated in several cellular processes (eg. proliferation, apoptosis, autophagy, extracellular matrix organization, cell surface marker gene expression, oxidative stress, unfolded protein response, innate and adaptive immunity). Several of these genes stand as acknowledged IBD susceptibility genes or as genes of interest localized at convincingly replicated risk loci identified by GWAS (eg. ATG16L1, IL10, IL12B, JAK2, ARPC2, PTGER4, ZNF365, NKX2-3, PTPN2, PTPN22, C11orf30, ORMDL3, STAT3). However, an exhaustive identification of the genes targeted by UC- and/or CD- associated miRNAs (eg. common to or distinct between UC and CD), the demonstration of their actual regulation by miRNAs and the investigation of their influence on intestinal inflammation in experimental models of colitis is far beyond the scope of this paper and will be the subject of future studies.

Our study supports miRNAs as crucial players in the onset and/or relapse of inflammation from quiescent mucosal tissues in UC and CD patients. It further highlights their putative role as contributors to IBD susceptibility and thus will help unravel the mechanisms (either distinct or shared between UC and CD) involved in relapsing (eg. identification of key targets and of gene networks). Finally, they may help develop new biomarkers to distinguish UC and CD at early stages.

Materials and Methods

IBD patients and controls

Colonic pinch biopsies were obtained in the course of endoscopical examination of patients with mild to severe CD and UC and of healthy control subjects undergoing screening colonoscopies (Table S2 for clinical details). Colonic biopsies were punctured from 24 CD, 18 UC and 19 healthy controls (see Figure S2). However, for the reasons outlined below (see paragraphs “Histopathological analyses” and “RNA isolation”) and in Figure S2, the biopsies collected from some patients were not included in the study. Overall, expression of mature miRNAs was studied in inactive colonic mucosa of 8 patients with UC, 8 patients with CD and in 10 healthy control mucosa.

The diagnosis of UC and CD adhered to the criteria given by Lennard-Jones [68]. Clinical disease activity for CD and UC was assessed according to the Harvey-Bradshaw [69] and to the Colitis Activity (CAI) [70] indexes, respectively. In each IBD patient, endoscopically non-inflamed and inflamed areas of colonic tissue were punctured (5 biopsies/area). Non-inflamed and inflamed areas for biopsy collection were separated by more than 20 cm along the colon. Three biopsies from each area were allocated for immediate RNAlater™ immersion then snap frozen and stored in liquid nitrogen, and two were set apart for histopathological examination. In healthy controls, 5 biopsies were punctured both in right and left colon and processed as above. The protocol was approved by the local Ethic Committee (Comité de Protection des Personnes -CPP- Ile de France IV n°2009/17 and AFFSSAPS D91534-80) and written informed consent was obtained from all patients.

Histopathological analyses

Biopsies were routinely stained with haematoxylin and eosin. Histological assessments of mucosal damage and inflammatory cells infiltration were graded by the same expert gastrointestinal pathologist (DCH) using a score previously validated to characterize the colonic involvement of both UC and CD [71]. Grades were as follows: 0, no evidence of inflammation (normal mucosa); 1, oedema and mild infiltration in the lamina propria; 2, crypt abscess and inflammation in the lamina propria; 3, severe inflammation with destructive crypt abscess and 4, severe inflammation with active ulceration. Grades 0–1 were considered as quiescent (or non-inflamed) mucosa. Grades 2–4 corresponded to various degrees of inflammation of the mucosa and were considered as active disease (Figure S1). Alterations in miRNA expression were studied following this histological dichotomy (0–1 vs. 2–4). IBD patients selected for miRNA analysis had both histologically assessed quiescent and inflammatory samples. 7 CD patients and 3 UC patients were excluded because their endoscopically quiescent colonic mucosa was classified as histologically active. 1 control patient with lymphocytic colitis was excluded (Figure S2).

RNA Isolation

Total RNA was extracted with TRIzol® Reagent (Invitrogen) then quantified using a ND-1000 NanoDrop spectrophotometer (NanoDrop Technologies) and purity/integrity was assessed using disposable RNA chips (Agilent RNA 6000 Nano LabChip kit) and an Agilent 2100 Bioanalyzer (Agilent Technologies, Waldbrunn, Germany). Only RNA preparations with RIN≥7 were further processed for analysis of miRNA expression. Nine CD, 7 UC and 8 controls with RNA preparations of insufficient purity (RIN<7) were excluded. Finally 8 CD, 8 UC and 10 controls with stringent homogeneity in histological assessment and RNA quality were selected for analysis (Figure S2).

Reverse-Transcription and Real-Time Q-PCR

The Human Early Access Release Kit (based on miRBase v 9.2; TaqMan® MicroRNA Assay; Applied Biosystems) designed to quantify 321 mature human miRNAs was used. cDNA was generated from 10 ng of total RNA using miRNA-specific stem-loop RT primers. Real-Time Q-PCR assays were performed according to the manufacturer's instructions using aliquots of cDNA equivalent to ∼1.3 ng of total RNA and were run in a Light Cycler 480 (Roche Diagnostics).

Normalization of Real-Time Q-PCR results. Several RNAs (U6, U24, U48 and S18) were tested as putative standards and U6 (an ubiquitous small nuclear RNA) (Primer for U6 were included in the TaqMan® MicroRNA Assay) was found the most reliable. Expression of miRNAs was computed relative to that of U6 and a comparative threshold cycle method (2−ΔΔCT) [72] was used to compare non-inflamed and inflamed IBD tissues with healthy controls. Since the abundance of mature miRNA transcripts was expressed relative to that of the reference gene U6, we have checked that PCR efficiencies were identical for test (miRNAs) and reference (U6) transcripts, so that the comparison be accurate (see the MIQE guidelines; [73]).

CT, the fractional cycle number at which the amount of amplified target reaches a fixed threshold, was determined (default threshold settings were used in all instances). The cycle number above which the CT was considered as a false positive (cycle cut-off point) was set up at 35, as already argued in the literature dealing with limits of detection in Real-Time Quantitative- RT-PCR [74] ( reviewed in [73]). −ΔΔCT was calculated as follows:whereAnd

Determination of cut-off values for miRNA over- and under- expression. Relative miRNA expressions (2−ΔΔCT) were computed as their log transformed (10×log10) values (after such computation up- and down- regulations were expressed as positive and negative values, respectively), and their means and standard deviations (SDmiRNA) were calculated independently for every miRNA, in each IBD at each stage of the disease. Box-whisker plots analysis of SDmiRNA pointed highly dispersed values among patients (Figure S3). Overall, when the data gathered from the two series of patients were considered (8 UC, 8 CD; non-inflamed and inflamed areas of colonic tissues), a mean value of 6.3±1.4 (meanDisp ± SDDisp) was calculated for the SDmiRNA values. Given such variation in relative miRNA expression, only those with mean 10×log102−ΔΔCT>7 and <−7 (±|meanDisp+0.5 SDDisp|) were considered as up- (2−ΔΔCT>5-fold) and down- (2−ΔΔCT<0.2-fold) regulated relative to healthy.

In silico prediction of miRNA targets

Exhaustive human miRNA targets were predicted using a parameter-free model for miRNA-target interaction. This model computes the difference between the free energy gained from the formation of the miRNA-target duplex (ΔGduplex) and the energetic cost of unpairing the target (and proximal flanking sequences) to make it accessible to the miRNA (ΔGopen) [75].

We made use of the PITA catalog of predicted human microRNA targets (http://genie.weizmann.ac.il/pubs/mir07/mir07_data.html). The seed parameter settings described in Kertesz et al. [75] were followed: seeds of 8 bp in length, beginning at position 2 of the miRNA were chosen, seed conservation being set at 0.9. No mismatches or loops were allowed, but a single G∶U wobble was permitted. In genes missing a 3′ UTR annotation, 800 bp downstream of the annotated end of the coding sequence were used as the predicted 3′ UTR. Flanks of 3 and 15 bp upstream and downstream the miRNA target, respectively, were considered in the computation of ΔGopen.

In some instances (mir-126*) predictions from the miRBase database (miRBase Targets Release Version v5; http://microrna.sanger.ac.uk/cgi-bin/targets/v5/mirna.pl?genome_id=2964) were downloaded. These predictions combine the miRanda algorithm and the conservation of miRNA binding sites in orthologous transcripts from at least two species (http://microrna.sanger.ac.uk/targets/v5/info.html for details) [76].

Biological functions of the in silico predicted miRNA targets

We made use of the Gene Ontology (http://www.geneontology.org), GeneCards (http://www.genecards.org/) and GeneNote (http://bioinfo2.weizmann.ac.il/cgi-bin/genenote/home_page.pl) databases to document the biological functions of the genes that were predicted to be targeted by miRNAs with altered expression in quiescent UC and CD tissues (see Table S8).

Statistical analysis

Unpaired groups of values were compared according to the non-parametric Mann-Whitney test. Statistical significance was set at p≤0.05.

miRNA which shared closely related expression patterns were grouped according to K-means clustering [77] computed on line from the GenePattern Server. The specified number of clusters was set at 20.

When supervised class (UC or CD) prediction of individual patient's data was tested, we used a K Nearest Neighbors Classification algorithm with Leave-One-Out Cross-Validation (GenePattern “KNNXValidation” module). The class predictor was uniquely defined by the initial set of patients and marker miRNAs. The classifications were tested in leave-one-out cross-validation mode by iteratively leaving one sample out, training a classification on the remaining data and testing on the left out sample.

Supporting Information

Figure S1.

Histological grading of disease activity in colonic biopsies. Hematoxylin and eosin staining of biopsies from non-inflamed and inflamed colonic mucosa (see Materials and Methods for details on histological grading). Note the progressive loss of intestinal epithelium with increasing grade of the disease (2–4) and the concomitant increase in the severity of inflammation/infiltration. Magnification, ×100.

https://doi.org/10.1371/journal.pone.0013160.s001

(0.35 MB TIF)

Figure S2.

Flow chart of sample selection. In order to exclude any bias in homogeneity among samples, biopsies of patients with endoscopically quiescent, but histologically active colonic mucosa were excluded. The histological dichotomy (grades 0–1 vs. 2–4) was strictly followed to study the alteration in miRNA gene expression. Similarly, 1 control patient with lymphocytic colitis was excluded. In all cases, RNA preparations of low integrity (RIN<7) were discarded.

https://doi.org/10.1371/journal.pone.0013160.s002

(0.09 MB TIF)

Figure S3.

Alteration of miRNA gene expression in non-inflamed and inflamed UC and CD tissues : Box-whisker plot analysis of standard deviations. miRNA expression was measured in non-inflamed and inflamed colonic mucosa obtained from patients with UC and CD (8 patients/IBD) and computed vs. that measured in healthy controls. The mean and standard deviation (SDmiRNA) of relative miRNA expression were then calculated for every miRNA, independently in each IBD for each state of the disease. SDmiRNA were then plotted as box-whisker plots (box, 25–75%; whisker, 10–90%; line, median) (1). 1 Tukey, J. W. (1977) in Exploratory Data Analysis (Addison-Wesley, Reading, MA), pp. 39–43.

https://doi.org/10.1371/journal.pone.0013160.s003

(0.06 MB TIF)

Figure S4.

Overview of the chromosomal distribution of miRNA genes with altered expression in IBD tissues: The total number of miRNA genes with altered expression was determined by chromosome. Negative and positive ordinates stand of over and under -expression, respectively.

https://doi.org/10.1371/journal.pone.0013160.s004

(0.10 MB TIF)

Figure S5.

Alteration of miRNA gene expression in IBD tissues: sub-chromosomal localization of the affected loci. Chromosomal bands where 2 (arrowheads) or more (squares) miRNA genes with altered expression colocalize are shown. Grey and light-red symbols represent loci where IBD susceptibility has yet been demonstrated by genetic means and previously unidentified loci, respectively.

https://doi.org/10.1371/journal.pone.0013160.s005

(0.12 MB TIF)

Table S1.

miRNA expression in left and right colon of healthy individuals. Relative miRNA expression (10×log102∼ΔCT; see Materials and Methods) was calculated in the right and left colons independently. Note that miRNA expression was similar in both segments of the colon.

https://doi.org/10.1371/journal.pone.0013160.s006

(0.02 MB XLS)

Table S2.

Characteristics of patients with CD or UC and of healthy control individuals. * Sex: F : female/M : male; + disease location: C: colon/IC: ileocolonic/C+AP: colon and anoperineal lesions/R: right colon/S: sigmoid colon/LC: left colon; # Current treatment : CS: steroids/5 ASA: 5 aminosalicylates/AZA: azathioprine/IFX: infliximab/MTX: methotrexate.

https://doi.org/10.1371/journal.pone.0013160.s007

(0.01 MB XLSX)

Table S3.

Alterations of miRNA expression in UC patients. Relative miRNA expression was computed vs. that measured in healthy controls and expressed as 10×log102−ΔΔCT. Are only listed the miRNAs with relative expressions >7 or <−7 in non-inflamed UC tissues. When adequate, alteration of expression in inflamed UC is also mentioned. Access_N°, MIMAT identification number; Mean ± Sem (5–8 patients). Statistical significance (p values) was calculated relative to healthy control tissue using the non-parametric Mann-Whitney test. Bolded, miRNA with statistically significant dysregulation of expression in both quiescent and inflamed UC.

https://doi.org/10.1371/journal.pone.0013160.s008

(0.03 MB XLS)

Table S4.

Alterations of miRNA expression in CD patients. Relative miRNA expression was computed vs. that measured in healthy controls and expressed as 10×log102−ΔΔCT. Are only listed the miRNAs with relative expressions >7 or <−7 in non-inflamed CD tissues. When adequate, alteration of expression in inflamed CD is also mentioned. Access_N°, MIMAT identification number; Mean ± Sem (5–8 patients). Statisticalsignificance (p values) was calculated relative to healthy control tissue using the non-parametric Mann-Whitney test. Bolded, miRNA with statistically significant dysregulation of expression both in quiescent and in inflamed CD.

https://doi.org/10.1371/journal.pone.0013160.s009

(0.04 MB XLS)

Table S5.

Shared alterations of miRNA expression in UC and CD patients. Relative miRNA expression was computed vs. that measured in healthy controls. miRNA with shared and significant overexpression (10×log102−ΔΔCT>7) both in non-inflamed UC and in non-inflamed CD tissues are listed. Access_N°, MIMAT identification number; Mean ± Sem (5–8 patients). Italics (2 lower rows), miRNA that are not overexpressed in inflamed UC (mir-196a) or CD (mir-30c).

https://doi.org/10.1371/journal.pone.0013160.s010

(0.02 MB XLS)

Table S6.

Compilation of the characteristics of the miRNA with significantly altered expression in quiescent UC and CD colonic mucosa. Access_N°, MIMAT identification number; Gene-Id, miRNA gene identification number; Coordinates, coordinate of the miRNA gene on the chromosome [strand] (from http://www.mirbase.org/cgi-bin/mirna_summary.pl?org=hsa); Band, Chromosomal band where the miRNA gene is localized; Gene Context, presence or absence (intergenic) of overlap between the miRNA gene and another gene either on the same or on the opposite strand.

https://doi.org/10.1371/journal.pone.0013160.s011

(0.05 MB XLS)

Table S7.

Compilation of the sub-chromosomal regions where acknowledged IBD-susceptibility loci and miRNA genes with altered expression colocalize. Chromosomal locations where colocalize miRNA genes with altered expression relative to healthy controls in quiescent and/or inflamed UC or CD tissues and (i) acknowledged IBD susceptibility loci or (ii) replicated sub-chromosomal regions identified in GWAS are listed. The location of each IBD susceptibility loci is reminded. Gene_Id, miRNA gene identification number; Locus, chromosomal band where the miRNA gene is localized; Quiescent, non-inflamed; Both, non-inflamed and inflamed; +/−, +: overexpression; −: underexpression.

https://doi.org/10.1371/journal.pone.0013160.s012

(0.01 MB XLSX)

Table S8.

Alteration of miRNA expression in the colonic mucosa of UC and CD patients: in silico characterization of target transcripts. The exhaustive list of genes which are putatively targeted by the subset of 8 miRNAs that share common dysregulated overexpression in both UC and CD was downloaded from the PITA catalog of predicted human microRNA targets (http://genie.weizmann.ac.il/pubs/mir07/mir07_data.html). The algorithm makes use of the parameter-free model for miRNA-target interaction described by Kertesz et al. (2007). Genes involved in a common biological process are listed together. Bold characters: strictly down regulated genes (the 3′-UTR of which interacts only with up-regulated miRNA(s))

https://doi.org/10.1371/journal.pone.0013160.s013

(0.08 MB XLS)

Author Contributions

Conceived and designed the experiments: EOD. Performed the experiments: MF EP DCH FD. Analyzed the data: CR AG. Contributed reagents/materials/analysis tools: XT TA JCS YB. Wrote the paper: AG. Contributed to the experiments: CG. Expert gastrointestinal pathologist who assessed mucosal damage and inflammatory cells infiltration: DCH. Contributed to study design: RM ML.

References

  1. 1. Schreiber S, Rosenstiel P, Albrecht M, Hampe J, Krawczak M (2005) Genetics of Crohn disease, an archetypal inflammatory barrier disease. Nat Rev Genet 6: 376–88.S. SchreiberP. RosenstielM. AlbrechtJ. HampeM. Krawczak2005Genetics of Crohn disease, an archetypal inflammatory barrier disease.Nat Rev Genet637688
  2. 2. Kugathasan S, Amre D (2006) Inflammatory bowel disease–environmental modification and genetic determinants. Pediatr Clin North Am 53: 727–49.S. KugathasanD. Amre2006Inflammatory bowel disease–environmental modification and genetic determinants.Pediatr Clin North Am5372749
  3. 3. Liu L, Li Y, Tollefsbol TO (2008) Gene-environment interactions and epigenetic basis of human diseases. Curr Issues Mol Biol 10: 25–36.L. LiuY. LiTO Tollefsbol2008Gene-environment interactions and epigenetic basis of human diseases.Curr Issues Mol Biol102536
  4. 4. Bouma G, Strober W (2003) The immunological and genetic basis of inflammatory bowel disease. Nat Rev Immunol 3: 521–33.G. BoumaW. Strober2003The immunological and genetic basis of inflammatory bowel disease.Nat Rev Immunol352133
  5. 5. Farmer RG, Easley KA, Rankin GB (1993) Clinical patterns, natural history, and progression of ulcerative colitis. A long-term follow-up of 1116 patients. Dig Dis Sci 38: 1137–46.RG FarmerKA EasleyGB Rankin1993Clinical patterns, natural history, and progression of ulcerative colitis. A long-term follow-up of 1116 patients.Dig Dis Sci38113746
  6. 6. Rutgeerts P, Geboes K, Vantrappen G, Beyls J, Kerremans R, et al. (1990) Predictability of the postoperative course of Crohn's disease. Gastroenterology 99: 956–63.P. RutgeertsK. GeboesG. VantrappenJ. BeylsR. Kerremans1990Predictability of the postoperative course of Crohn's disease.Gastroenterology9995663
  7. 7. Kaser A, Lee AH, Franke A, Glickman JN, Zeissig S, et al. (2008) XBP1 links ER stress to intestinal inflammation and confers genetic risk for human inflammatory bowel disease. Cell 134: 743–56.A. KaserAH LeeA. FrankeJN GlickmanS. Zeissig2008XBP1 links ER stress to intestinal inflammation and confers genetic risk for human inflammatory bowel disease.Cell13474356
  8. 8. Ahn SH, Shah YM, Inoue J, Morimura K, Kim I, et al. (2008) Hepatocyte nuclear factor 4alpha in the intestinal epithelial cells protects against inflammatory bowel disease. Inflamm Bowel Dis 14: 908–20.SH AhnYM ShahJ. InoueK. MorimuraI. Kim2008Hepatocyte nuclear factor 4alpha in the intestinal epithelial cells protects against inflammatory bowel disease.Inflamm Bowel Dis1490820
  9. 9. Paavola-Sakki P, Ollikainen V, Helio T, Halme L, Turunen U, et al. (2003) Genome-wide search in Finnish families with inflammatory bowel disease provides evidence for novel susceptibility loci. Eur J Hum Genet 11: 112–20.P. Paavola-SakkiV. OllikainenT. HelioL. HalmeU. Turunen2003Genome-wide search in Finnish families with inflammatory bowel disease provides evidence for novel susceptibility loci.Eur J Hum Genet1111220
  10. 10. Vermeire S, Rutgeerts P (2005) Current status of genetics research in inflammatory bowel disease. Genes Immun 6: 637–45.S. VermeireP. Rutgeerts2005Current status of genetics research in inflammatory bowel disease.Genes Immun663745
  11. 11. Barrett JC, Hansoul S, Nicolae DL, Cho JH, Duerr RH, et al. (2008) Genome-wide association defines more than 30 distinct susceptibility loci for Crohn's disease. Nat Genet 40: 955–62.JC BarrettS. HansoulDL NicolaeJH ChoRH Duerr2008Genome-wide association defines more than 30 distinct susceptibility loci for Crohn's disease.Nat Genet4095562
  12. 12. Franke A, Balschun T, Karlsen TH, Hedderich J, May S, et al. (2008) Replication of signals from recent studies of Crohn's disease identifies previously unknown disease loci for ulcerative colitis. Nat Genet 40: 713–5.A. FrankeT. BalschunTH KarlsenJ. HedderichS. May2008Replication of signals from recent studies of Crohn's disease identifies previously unknown disease loci for ulcerative colitis.Nat Genet407135
  13. 13. Franke A, Balschun T, Karlsen TH, Sventoraityte J, Nikolaus S, et al. (2008) Sequence variants in IL10, ARPC2 and multiple other loci contribute to ulcerative colitis susceptibility. Nat Genet 40: 1319–23.A. FrankeT. BalschunTH KarlsenJ. SventoraityteS. Nikolaus2008Sequence variants in IL10, ARPC2 and multiple other loci contribute to ulcerative colitis susceptibility.Nat Genet40131923
  14. 14. Kugathasan S, Baldassano RN, Bradfield JP, Sleiman PM, Imielinski M, et al. (2008) Loci on 20q13 and 21q22 are associated with pediatric-onset inflammatory bowel disease. Nat Genet 40: 1211–5.S. KugathasanRN BaldassanoJP BradfieldPM SleimanM. Imielinski2008Loci on 20q13 and 21q22 are associated with pediatric-onset inflammatory bowel disease.Nat Genet4012115
  15. 15. Mathew CG (2008) New links to the pathogenesis of Crohn disease provided by genome-wide association scans. Nat Rev Genet 9: 9–14.CG Mathew2008New links to the pathogenesis of Crohn disease provided by genome-wide association scans.Nat Rev Genet9914
  16. 16. Fisher SA, Tremelling M, Anderson CA, Gwilliam R, Bumpstead S, et al. (2008) Genetic determinants of ulcerative colitis include the ECM1 locus and five loci implicated in Crohn's disease. Nat Genet 40: 710–2.SA FisherM. TremellingCA AndersonR. GwilliamS. Bumpstead2008Genetic determinants of ulcerative colitis include the ECM1 locus and five loci implicated in Crohn's disease.Nat Genet407102
  17. 17. Imielinski M, Baldassano RN, Griffiths A, Russell RK, Annese V, et al. (2009) Common variants at five new loci associated with early-onset inflammatory bowel disease. Nat Genet 41: 1335–40.M. ImielinskiRN BaldassanoA. GriffithsRK RussellV. Annese2009Common variants at five new loci associated with early-onset inflammatory bowel disease.Nat Genet41133540
  18. 18. Asano K, Matsushita T, Umeno J, Hosono N, Takahashi A, et al. (2009) A genome-wide association study identifies three new susceptibility loci for ulcerative colitis in the Japanese population. Nat Genet 41: 1325–9.K. AsanoT. MatsushitaJ. UmenoN. HosonoA. Takahashi2009A genome-wide association study identifies three new susceptibility loci for ulcerative colitis in the Japanese population.Nat Genet4113259
  19. 19. Barrett JC, Lee JC, Lees CW, Prescott NJ, Anderson CA, et al. (2009) Genome-wide association study of ulcerative colitis identifies three new susceptibility loci, including the HNF4A region. Nat Genet 41: 1330–4.JC BarrettJC LeeCW LeesNJ PrescottCA Anderson2009Genome-wide association study of ulcerative colitis identifies three new susceptibility loci, including the HNF4A region.Nat Genet4113304
  20. 20. Hugot JP, Chamaillard M, Zouali H, Lesage S, Cezard JP, et al. (2001) Association of NOD2 leucine-rich repeat variants with susceptibility to Crohn's disease. Nature 411: 599–603.JP HugotM. ChamaillardH. ZoualiS. LesageJP Cezard2001Association of NOD2 leucine-rich repeat variants with susceptibility to Crohn's disease.Nature411599603
  21. 21. Parkes M, Barrett JC, Prescott NJ, Tremelling M, Anderson CA, et al. (2007) Sequence variants in the autophagy gene IRGM and multiple other replicating loci contribute to Crohn's disease susceptibility. Nat Genet 39: 830–2.M. ParkesJC BarrettNJ PrescottM. TremellingCA Anderson2007Sequence variants in the autophagy gene IRGM and multiple other replicating loci contribute to Crohn's disease susceptibility.Nat Genet398302
  22. 22. Hampe J, Franke A, Rosenstiel P, Till A, Teuber M, et al. (2007) A genome-wide association scan of nonsynonymous SNPs identifies a susceptibility variant for Crohn disease in ATG16L1. Nat Genet 39: 207–11.J. HampeA. FrankeP. RosenstielA. TillM. Teuber2007A genome-wide association scan of nonsynonymous SNPs identifies a susceptibility variant for Crohn disease in ATG16L1.Nat Genet3920711
  23. 23. Duerr RH, Taylor KD, Brant SR, Rioux JD, Silverberg MS, et al. (2006) A genome-wide association study identifies IL23R as an inflammatory bowel disease gene. Science 314: 1461–3.RH DuerrKD TaylorSR BrantJD RiouxMS Silverberg2006A genome-wide association study identifies IL23R as an inflammatory bowel disease gene.Science31414613
  24. 24. Ogura Y, Bonen DK, Inohara N, Nicolae DL, Chen FF, et al. (2001) A frameshift mutation in NOD2 associated with susceptibility to Crohn's disease. Nature 411: 603–6.Y. OguraDK BonenN. InoharaDL NicolaeFF Chen2001A frameshift mutation in NOD2 associated with susceptibility to Crohn's disease.Nature4116036
  25. 25. Cho JH, Weaver CT (2007) The genetics of inflammatory bowel disease. Gastroenterology 133: 1327–39.JH ChoCT Weaver2007The genetics of inflammatory bowel disease.Gastroenterology133132739
  26. 26. Noble CL, Abbas AR, Cornelius J, Lees CW, Ho GT, et al. (2008) Regional variation in gene expression in the healthy colon is dysregulated in ulcerative colitis. Gut 57: 1398–405.CL NobleAR AbbasJ. CorneliusCW LeesGT Ho2008Regional variation in gene expression in the healthy colon is dysregulated in ulcerative colitis.Gut571398405
  27. 27. Olsen J, Gerds TA, Seidelin JB, Csillag C, Bjerrum JT, et al. (2009) Diagnosis of ulcerative colitis before onset of inflammation by multivariate modeling of genome-wide gene expression data. Inflamm Bowel Dis 15: 1032–8.J. OlsenTA GerdsJB SeidelinC. CsillagJT Bjerrum2009Diagnosis of ulcerative colitis before onset of inflammation by multivariate modeling of genome-wide gene expression data.Inflamm Bowel Dis1510328
  28. 28. Dooley TP, Curto EV, Reddy SP, Davis RL, Lambert GW, et al. (2004) Regulation of gene expression in inflammatory bowel disease and correlation with IBD drugs: screening by DNA microarrays. Inflamm Bowel Dis 10: 1–14.TP DooleyEV CurtoSP ReddyRL DavisGW Lambert2004Regulation of gene expression in inflammatory bowel disease and correlation with IBD drugs: screening by DNA microarrays.Inflamm Bowel Dis10114
  29. 29. Lawrance IC, Fiocchi C, Chakravarti S (2001) Ulcerative colitis and Crohn's disease: distinctive gene expression profiles and novel susceptibility candidate genes. Hum Mol Genet 10: 445–56.IC LawranceC. FiocchiS. Chakravarti2001Ulcerative colitis and Crohn's disease: distinctive gene expression profiles and novel susceptibility candidate genes.Hum Mol Genet1044556
  30. 30. Dieckgraefe BK, Stenson WF, Korzenik JR, Swanson PE, Harrington CA (2000) Analysis of mucosal gene expression in inflammatory bowel disease by parallel oligonucleotide arrays. Physiol Genomics 4: 1–11.BK DieckgraefeWF StensonJR KorzenikPE SwansonCA Harrington2000Analysis of mucosal gene expression in inflammatory bowel disease by parallel oligonucleotide arrays.Physiol Genomics4111
  31. 31. Costello CM, Mah N, Hasler R, Rosenstiel P, Waetzig GH, et al. (2005) Dissection of the inflammatory bowel disease transcriptome using genome-wide cDNA microarrays. PLoS Med 2: e199.CM CostelloN. MahR. HaslerP. RosenstielGH Waetzig2005Dissection of the inflammatory bowel disease transcriptome using genome-wide cDNA microarrays.PLoS Med2e199
  32. 32. von Stein P, Lofberg R, Kuznetsov NV, Gielen AW, Persson JO, et al. (2008) Multigene analysis can discriminate between ulcerative colitis, Crohn's disease, and irritable bowel syndrome. Gastroenterology 134: 1869–81; quiz 2153–4.P. von SteinR. LofbergNV KuznetsovAW GielenJO Persson2008Multigene analysis can discriminate between ulcerative colitis, Crohn's disease, and irritable bowel syndrome.Gastroenterology134186981; quiz 2153–4
  33. 33. Doench JG, Sharp PA (2004) Specificity of microRNA target selection in translational repression. Genes Dev 18: 504–11.JG DoenchPA Sharp2004Specificity of microRNA target selection in translational repression.Genes Dev1850411
  34. 34. Flynt AS, Lai EC (2008) Biological principles of microRNA-mediated regulation: shared themes amid diversity. Nat Rev Genet 9: 831–42.AS FlyntEC Lai2008Biological principles of microRNA-mediated regulation: shared themes amid diversity.Nat Rev Genet983142
  35. 35. Wu L, Fan J, Belasco JG (2006) MicroRNAs direct rapid deadenylation of mRNA. Proc Natl Acad Sci U S A 103: 4034–9.L. WuJ. FanJG Belasco2006MicroRNAs direct rapid deadenylation of mRNA.Proc Natl Acad Sci U S A10340349
  36. 36. Filipowicz W, Bhattacharyya SN, Sonenberg N (2008) Mechanisms of post-transcriptional regulation by microRNAs: are the answers in sight? Nat Rev Genet 9: 102–14.W. FilipowiczSN BhattacharyyaN. Sonenberg2008Mechanisms of post-transcriptional regulation by microRNAs: are the answers in sight?Nat Rev Genet910214
  37. 37. Reinhart BJ, Slack FJ, Basson M, Pasquinelli AE, Bettinger JC, et al. (2000) The 21-nucleotide let-7 RNA regulates developmental timing in Caenorhabditis elegans. Nature 403: 901–6.BJ ReinhartFJ SlackM. BassonAE PasquinelliJC Bettinger2000The 21-nucleotide let-7 RNA regulates developmental timing in Caenorhabditis elegans.Nature4039016
  38. 38. Miska EA (2005) How microRNAs control cell division, differentiation and death. Curr Opin Genet Dev 15: 563–8.EA Miska2005How microRNAs control cell division, differentiation and death.Curr Opin Genet Dev155638
  39. 39. Kapsimali M, Kloosterman WP, de Bruijn E, Rosa F, Plasterk RH, et al. (2007) MicroRNAs show a wide diversity of expression profiles in the developing and mature central nervous system. Genome Biol 8: R173.M. KapsimaliWP KloostermanE. de BruijnF. RosaRH Plasterk2007MicroRNAs show a wide diversity of expression profiles in the developing and mature central nervous system.Genome Biol8R173
  40. 40. Lu J, Getz G, Miska EA, Alvarez-Saavedra E, Lamb J, et al. (2005) MicroRNA expression profiles classify human cancers. Nature 435: 834–8.J. LuG. GetzEA MiskaE. Alvarez-SaavedraJ. Lamb2005MicroRNA expression profiles classify human cancers.Nature4358348
  41. 41. Calin GA, Croce CM (2006) MicroRNA signatures in human cancers. Nat Rev Cancer 6: 857–66.GA CalinCM Croce2006MicroRNA signatures in human cancers.Nat Rev Cancer685766
  42. 42. Volinia S, Calin GA, Liu CG, Ambs S, Cimmino A, et al. (2006) A microRNA expression signature of human solid tumors defines cancer gene targets. Proc Natl Acad Sci U S A 103: 2257–61.S. VoliniaGA CalinCG LiuS. AmbsA. Cimmino2006A microRNA expression signature of human solid tumors defines cancer gene targets.Proc Natl Acad Sci U S A103225761
  43. 43. Bandres E, Cubedo E, Agirre X, Malumbres R, Zarate R, et al. (2006) Identification by Real-time PCR of 13 mature microRNAs differentially expressed in colorectal cancer and non-tumoral tissues. Mol Cancer 5: 29.E. BandresE. CubedoX. AgirreR. MalumbresR. Zarate2006Identification by Real-time PCR of 13 mature microRNAs differentially expressed in colorectal cancer and non-tumoral tissues.Mol Cancer529
  44. 44. Cummins JM, He Y, Leary RJ, Pagliarini R, Diaz LA Jr, et al. (2006) The colorectal microRNAome. Proc Natl Acad Sci U S A 103: 3687–92.JM CumminsY. HeRJ LearyR. PagliariniLA Diaz Jr2006The colorectal microRNAome.Proc Natl Acad Sci U S A103368792
  45. 45. Kloosterman WP, Lagendijk AK, Ketting RF, Moulton JD, Plasterk RH (2007) Targeted inhibition of miRNA maturation with morpholinos reveals a role for miR-375 in pancreatic islet development. PLoS Biol 5: e203.WP KloostermanAK LagendijkRF KettingJD MoultonRH Plasterk2007Targeted inhibition of miRNA maturation with morpholinos reveals a role for miR-375 in pancreatic islet development.PLoS Biol5e203
  46. 46. Eisenberg I, Eran A, Nishino I, Moggio M, Lamperti C, et al. (2007) Distinctive patterns of microRNA expression in primary muscular disorders. Proc Natl Acad Sci U S A 104: 17016–21.I. EisenbergA. EranI. NishinoM. MoggioC. Lamperti2007Distinctive patterns of microRNA expression in primary muscular disorders.Proc Natl Acad Sci U S A1041701621
  47. 47. O'Connell RM, Taganov KD, Boldin MP, Cheng G, Baltimore D (2007) MicroRNA-155 is induced during the macrophage inflammatory response. Proc Natl Acad Sci U S A 104: 1604–9.RM O'ConnellKD TaganovMP BoldinG. ChengD. Baltimore2007MicroRNA-155 is induced during the macrophage inflammatory response.Proc Natl Acad Sci U S A10416049
  48. 48. Moschos SA, Williams AE, Perry MM, Birrell MA, Belvisi MG, et al. (2007) Expression profiling in vivo demonstrates rapid changes in lung microRNA levels following lipopolysaccharide-induced inflammation but not in the anti-inflammatory action of glucocorticoids. BMC Genomics 8: 240.SA MoschosAE WilliamsMM PerryMA BirrellMG Belvisi2007Expression profiling in vivo demonstrates rapid changes in lung microRNA levels following lipopolysaccharide-induced inflammation but not in the anti-inflammatory action of glucocorticoids.BMC Genomics8240
  49. 49. Sonkoly E, Stahle M, Pivarcsi A (2008) MicroRNAs: novel regulators in skin inflammation. Clin Exp Dermatol 33: 312–5.E. SonkolyM. StahleA. Pivarcsi2008MicroRNAs: novel regulators in skin inflammation.Clin Exp Dermatol333125
  50. 50. Sonkoly E, Pivarcsi A (2009) Advances in microRNAs: implications for immunity and inflammatory diseases. J Cell Mol Med 13: 24–38.E. SonkolyA. Pivarcsi2009Advances in microRNAs: implications for immunity and inflammatory diseases.J Cell Mol Med132438
  51. 51. Wu F, Zikusoka M, Trindade A, Dassopoulos T, Harris ML, et al. (2008) MicroRNAs are differentially expressed in ulcerative colitis and alter expression of macrophage inflammatory peptide-2 alpha. Gastroenterology 135: 1624–35 e24.F. WuM. ZikusokaA. TrindadeT. DassopoulosML Harris2008MicroRNAs are differentially expressed in ulcerative colitis and alter expression of macrophage inflammatory peptide-2 alpha.Gastroenterology135162435 e24
  52. 52. Allez M, Tieng V, Nakazawa A, Treton X, Pacault V, et al. (2007) CD4+NKG2D+ T cells in Crohn's disease mediate inflammatory and cytotoxic responses through MICA interactions. Gastroenterology 132: 2346–58.M. AllezV. TiengA. NakazawaX. TretonV. Pacault2007CD4+NKG2D+ T cells in Crohn's disease mediate inflammatory and cytotoxic responses through MICA interactions.Gastroenterology132234658
  53. 53. Bonen DK, Cho JH (2003) The genetics of inflammatory bowel disease. Gastroenterology 124: 521–36.DK BonenJH Cho2003The genetics of inflammatory bowel disease.Gastroenterology12452136
  54. 54. Van Limbergen J, Russell RK, Nimmo ER, Satsangi J (2007) The genetics of inflammatory bowel disease. Am J Gastroenterol 102: 2820–31.J. Van LimbergenRK RussellER NimmoJ. Satsangi2007The genetics of inflammatory bowel disease.Am J Gastroenterol102282031
  55. 55. Van Limbergen J, Wilson DC, Satsangi J (2009) The genetics of Crohn's disease. Annu Rev Genomics Hum Genet 10: 89–116.J. Van LimbergenDC WilsonJ. Satsangi2009The genetics of Crohn's disease.Annu Rev Genomics Hum Genet1089116
  56. 56. Xu H, Cheung IY, Guo HF, Cheung NK (2009) MicroRNA miR-29 modulates expression of immunoinhibitory molecule B7-H3: potential implications for immune based therapy of human solid tumors. Cancer Res 69: 6275–81.H. XuIY CheungHF GuoNK Cheung2009MicroRNA miR-29 modulates expression of immunoinhibitory molecule B7-H3: potential implications for immune based therapy of human solid tumors.Cancer Res69627581
  57. 57. Kota J, Chivukula RR, O'Donnell KA, Wentzel EA, Montgomery CL, et al. (2009) Therapeutic microRNA delivery suppresses tumorigenesis in a murine liver cancer model. Cell 137: 1005–17.J. KotaRR ChivukulaKA O'DonnellEA WentzelCL Montgomery2009Therapeutic microRNA delivery suppresses tumorigenesis in a murine liver cancer model.Cell137100517
  58. 58. Flavin R, Smyth P, Barrett C, Russell S, Wen H, et al. (2009) miR-29b expression is associated with disease-free survival in patients with ovarian serous carcinoma. Int J Gynecol Cancer 19: 641–7.R. FlavinP. SmythC. BarrettS. RussellH. Wen2009miR-29b expression is associated with disease-free survival in patients with ovarian serous carcinoma.Int J Gynecol Cancer196417
  59. 59. Sander S, Bullinger L, Wirth T (2009) Repressing the repressor: a new mode of MYC action in lymphomagenesis. Cell Cycle 8: 556–9.S. SanderL. BullingerT. Wirth2009Repressing the repressor: a new mode of MYC action in lymphomagenesis.Cell Cycle85569
  60. 60. Yan LX, Huang XF, Shao Q, Huang MY, Deng L, et al. (2008) MicroRNA miR-21 overexpression in human breast cancer is associated with advanced clinical stage, lymph node metastasis and patient poor prognosis. Rna 14: 2348–60.LX YanXF HuangQ. ShaoMY HuangL. Deng2008MicroRNA miR-21 overexpression in human breast cancer is associated with advanced clinical stage, lymph node metastasis and patient poor prognosis.Rna14234860
  61. 61. Ferretti E, De Smaele E, Miele E, Laneve P, Po A, et al. (2008) Concerted microRNA control of Hedgehog signalling in cerebellar neuronal progenitor and tumour cells. Embo J 27: 2616–27.E. FerrettiE. De SmaeleE. MieleP. LaneveA. Po2008Concerted microRNA control of Hedgehog signalling in cerebellar neuronal progenitor and tumour cells.Embo J27261627
  62. 62. Gebeshuber CA, Zatloukal K, Martinez J (2009) miR-29a suppresses tristetraprolin, which is a regulator of epithelial polarity and metastasis. EMBO Rep 10: 400–5.CA GebeshuberK. ZatloukalJ. Martinez2009miR-29a suppresses tristetraprolin, which is a regulator of epithelial polarity and metastasis.EMBO Rep104005
  63. 63. Musiyenko A, Bitko V, Barik S (2008) Ectopic expression of miR-126*, an intronic product of the vascular endothelial EGF-like 7 gene, regulates prostein translation and invasiveness of prostate cancer LNCaP cells. J Mol Med 86: 313–22.A. MusiyenkoV. BitkoS. Barik2008Ectopic expression of miR-126*, an intronic product of the vascular endothelial EGF-like 7 gene, regulates prostein translation and invasiveness of prostate cancer LNCaP cells.J Mol Med8631322
  64. 64. Park SY, Lee JH, Ha M, Nam JW, Kim VN (2009) miR-29 miRNAs activate p53 by targeting p85 alpha and CDC42. Nat Struct Mol Biol 16: 23–9.SY ParkJH LeeM. HaJW NamVN Kim2009miR-29 miRNAs activate p53 by targeting p85 alpha and CDC42.Nat Struct Mol Biol16239
  65. 65. Li Z, Lu J, Sun M, Mi S, Zhang H, et al. (2008) Distinct microRNA expression profiles in acute myeloid leukemia with common translocations. Proc Natl Acad Sci U S A 105: 15535–40.Z. LiJ. LuM. SunS. MiH. Zhang2008Distinct microRNA expression profiles in acute myeloid leukemia with common translocations.Proc Natl Acad Sci U S A1051553540
  66. 66. Zhou Q, Souba WW, Croce CM, Verne GN (2010) MicroRNA-29a regulates intestinal membrane permeability in patients with irritable bowel syndrome. Gut 59: 775–84.Q. ZhouWW SoubaCM CroceGN Verne2010MicroRNA-29a regulates intestinal membrane permeability in patients with irritable bowel syndrome.Gut5977584
  67. 67. Hollander D (1999) Intestinal permeability, leaky gut, and intestinal disorders. Curr Gastroenterol Rep 1: 410–6.D. Hollander1999Intestinal permeability, leaky gut, and intestinal disorders.Curr Gastroenterol Rep14106
  68. 68. Lennard-Jones JE (1989) Classification of inflammatory bowel disease. Scand J Gastroenterol Suppl 1702–6; discussion 16–9.JE Lennard-Jones1989Classification of inflammatory bowel disease.Scand J GastroenterolSuppl 17026; discussion 16–9
  69. 69. Harvey RF, Bradshaw JM (1980) A simple index of Crohn's-disease activity. Lancet 1: 514.RF HarveyJM Bradshaw1980A simple index of Crohn's-disease activity.Lancet1514
  70. 70. Xiao Li F, Sutherland LR (2002) Assessing disease activity and disease activity indices for inflammatory bowel disease. Curr Gastroenterol Rep 4: 490–6.F. Xiao LiLR Sutherland2002Assessing disease activity and disease activity indices for inflammatory bowel disease.Curr Gastroenterol Rep44906
  71. 71. Gomes P, du Boulay C, Smith CL, Holdstock G (1986) Relationship between disease activity indices and colonoscopic findings in patients with colonic inflammatory bowel disease. Gut 27: 92–5.P. GomesC. du BoulayCL SmithG. Holdstock1986Relationship between disease activity indices and colonoscopic findings in patients with colonic inflammatory bowel disease.Gut27925
  72. 72. Livak KJ, Schmittgen TD (2001) Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method. Methods 25: 402–8.KJ LivakTD Schmittgen2001Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method.Methods254028
  73. 73. Bustin SA, Benes V, Garson JA, Hellemans J, Huggett J, et al. (2009) The MIQE guidelines: minimum information for publication of quantitative real-time PCR experiments. Clin Chem 55: 611–22.SA BustinV. BenesJA GarsonJ. HellemansJ. Huggett2009The MIQE guidelines: minimum information for publication of quantitative real-time PCR experiments.Clin Chem5561122
  74. 74. Burns M, Valdivia H (2008) Modelling the limit of detection in real-time quantitative PCR. Eur Food Res Technol 226: 1513–24.M. BurnsH. Valdivia2008Modelling the limit of detection in real-time quantitative PCR.Eur Food Res Technol226151324
  75. 75. Kertesz M, Iovino N, Unnerstall U, Gaul U, Segal E (2007) The role of site accessibility in microRNA target recognition. Nat Genet 39: 1278–84.M. KerteszN. IovinoU. UnnerstallU. GaulE. Segal2007The role of site accessibility in microRNA target recognition.Nat Genet39127884
  76. 76. Megraw M, Sethupathy P, Corda B, Hatzigeorgiou AG (2007) miRGen: a database for the study of animal microRNA genomic organization and function. Nucleic Acids Res 35: D149–55.M. MegrawP. SethupathyB. CordaAG Hatzigeorgiou2007miRGen: a database for the study of animal microRNA genomic organization and function.Nucleic Acids Res35D14955
  77. 77. MacQueen J Some methods for classification and analysis of multivariate observations. In: Le Cam LMaN J, editor. Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability. Berkeley, Califonia: University of California Press 1967. pp. 281–97.J. MacQueenSome methods for classification and analysis of multivariate observations.J. Le Cam LMaNProceedings of the Fifth Berkeley Symposium on Mathematical Statistics and ProbabilityBerkeley, CalifoniaUniversity of California Press 196728197
  78. 78. Tukey JWBox-and-Whisker Plots. Exploratory Data Analysis. Reading, MA: Addison-Wesley 1977. pp. 39–43.JW TukeyBox-and-Whisker Plots. Exploratory Data AnalysisReading, MAAddison-Wesley 19773943