MIRNAS ARRAYS: DATABASES AND PLATFORMSUBio Training Courses

Gonzalo Gómez//ggomez@cnio.es

miRNAs

Firstly detected in C. elegans (V. Ambros, 1993)

Mapping to non-coding regions (introns)

Pri-miRNA processed by Drosha

DICER removes the structural loop

mature miRNA: ssRNA, 22 nucleotides

miRNA-RISK complex: mRNAs post-transcriptional inhibition

33% of human genes are supposed to be regulated by miRNAs.

miRNAs

Biological role

• Brain development (miR-430)

• Nervous system development(miR-273)

• Pancreatic Langerhans islands development (miR-375)

• Adipocytes development (miR-143)

• Heart development(miR-1)

• Inmune response (miR-223, cluster miR-17~92, miR-146a,miR-155…)

• Apoptosis (miR-14)

miRNAs and cancerOncomiRs

Esquela-Kerscher & Slack. Nature Reviews Cancer. 2006.

ProliferationInvasionAngiogenesisCell death

Oncogene miRNA

Proliferation Invasion AngiogenesisCell death

Tumor suppressor miRNA

Tumor formation

Upregulation

Downregulation

miRNAs

Target sites

Bartel D. Cell 2009.

miRNAs seed region: 5’, nucleotides 2-7(8)

Most gene targets of a given miRNA have only a single 7 nt matching to that miRNA seed region.

7-8 nt hundreds of target predictions for each miRNA family (~300 conserved targets per miRNA family in vertebrates)

High rate of false positives in predictions.

miRNAs

Target Prediction Algorithms

PREDICTION CRITERIA

• miR seed-target complete base-

pairing

• Interspecies conservation

• Number of binding sites for a given 3’UTR

in a particular gene

• Free energy for the miR-target duplex

• Binding site accessibility

• miRNA- target secondary structure

Other prediction algorithms…Bartel D. Cell 2009.

More target prediction tools: http://en.wikipedia.org/wiki/

List_of_RNA_structure_prediction_software#Inter_molecular_interactions:_MicroRNA:UTR

Version Date miRNAs

1.0 12/02 218 1.1 01/03 262 1.2 04/03 295 1.3 05/03 332 1.4 07/03 345 2.0 07/03 506 2.1 09/03 558 2.2 11/03 593 3.0 01/04 719 3.1 04/04 899 4.0 07/04 1185 5.0 09/04 1345 5.1 12/04 1420 6.0 04/05 1650 7.0 06/05 2909 7.1 10/05 3424 8.0 02/06 3518 8.1 05/06 3963 8.2 07/06 4039 9.0 10/06 4361 9.1 02/07 4449 9.2 05/07 4584 10.0 08/07 5071 10.1 12/07 5395 11.0 04/08 6396 12.0 09/08 8619 13.0 03/09 9539 14.0 09/09 10833

H. Sapiens ~695 miRNAsM. musculus: ~488 miRNAs

miRNAs

Databases

http://www.mirbase.org/

miRBase

miRNAs

a) mir: immature sequence (hairpin). E.g. hsa-mir-203

b) miR: mature miRNA sequence. E.g. hsa-miR-203

- a/b: paralog miRs, difer in 1-2 nucleotides.

E.g. hsa-miR-9a, hsa-miR-9b

- 1-2: Identical miRs, different hairpin.

Ej. hsa-miR-19b-1, hsa-miR-19b-2

- 5p-3p: mature miR generated from precursor 5´ (or 3) sequence.

E.g. hsa-miR-17-5p

- *: Minor transcript complementary to mature miR.

E.g. hsa-miR-33a*

miRNA nomenclature (miRBase)

TarBase http://microrna.gr/tarbase

miRNAs

Databases

The database of experimentally supported targets: a functional update of TarBase. Papadopoulos GL, Reczko M, Simossis VA, Sethupathy P, Hatzigeorgiou AG., Nucleic Acids Res. 2009 Jan;37(Database issue):D155-8.

Contains only those miRNA-target relationships experimentally validated

miRNAs and disease

http://www.mir2disease.org/

Cancer (Calin and Croce 2006; Ura et al 2008; Stamatopoulos et al 2009…)Cardiovascular disease (Latronico et al. 2007; van Rooij and Olson 2007)

Schizophrenia (Hansen, et al. 2007; Perkins et al. 2007)Renal misfunction (Williams 2007)

Tourette syndrome (Esau and Monia 2007)Psoriasis (Sonkoly et al. 2007)

Muscle disorders (Eisenberg et al. 2007),X fragile syndrome (Fiore and Schratt 2007)

Policitemia vera (Bruchova et al. 2007)Diabetes (Williams 2007)

Chronic hepatitis (Murakami et al. 2006)AIDS (Hariharan etal. 2005)

Obesity (Weiler et al. 2006, Lovis et al. 2008, Xie et al. 2009).

http://cmbi.bjmu.edu.cn/hmdd

Databases

miRNAsDetection Methods

miRNA microarrays

Commercial platforms

Human, rat, mouse

Human, rat, mouse, dog, chimpanzee, etc

Human, multispecie

Human, rat, mouse

miRNA microarrays

Commercial platforms

Agilent recommendations.-No normalization-Normalization 75th percentile (75th value = 1)

Additional G-C pair in the probe-target interaction region stabilizes targeted miRNAs relative to homologous RNAs. Additionally, all probes contain a 5' hairpin (blue), abutting the probe-target region, to increase target and size miRNA specificity

miRNA microarrays

Commercial platforms

Background correction = normexpNormalization = quantiles

RG_normexp <- backgroundCorrect(RGfilt_0, method = "normexp", offset=50)MA_norm <- normalizeBetweenArrays(RG_normexp$G, method="quantile")MA_lognorm<-log2(MA_norm)

RG_normexp <- backgroundCorrect(RGfilt_0, method = "normexp", offset=50)MA_norm <- normalizeBetweenArrays(RG_normexp$G, method="quantile")MA_lognorm<-log2(MA_norm)

LNA = Locked Nucleic Acid

LNA is chemical modification.Ribose ring is "locked" with a methylene bridgeconnecting the 2’-O atom and the 4’-C atom.

LNA makes DNA-miR pairs more stable (higher Tm)when perfect match and 1mismatch hybridizations occurs.

Preprocessing scripts provided by Exiqon

Differentially expressed miRNAs between classes

T test, SAM, limma

FWERFDR

METHOD

Pvalueadjustment

FWER: Type I Family Wise Error RateFDR: False Discovery Rate

OK!pvalue

20 normalized arrays600 miRNAs 2 classes (healthy y tumor)

miRNA microarrays

Differential expression analysis

GEPASAsteriasSAM tools…

THANKS!

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