Identification of putative miR direct targets

Ovarian Serous Cystadenocarcinoma (Primary solid tumor)

21 April 2013 | analyses__2013_04_21

Maintainer Information

Citation Information

Maintained by Sachet Shukla (Broad Institute)

Cite as Broad Institute TCGA Genome Data Analysis Center (2013): Ovarian Serous Cystadenocarcinoma (Primary solid tumor cohort) - 21 April 2013: Identification of putative miR direct targets. Broad Institute of MIT and Harvard. doi:10.7908/C1R20ZBN

Overview

Introduction

This pipeline infers putative direct gene targets of miRs based on miR and gene expression profiles across multiple samples.

Summary

This pipeline use a relevance network approach to infer putative miR:mRNA regulatory connections. All miR:mRNA pairs that have correlations < -0.3 and have predicted interactions in three sequence prediction databases (Miranda, Pictar, Targetscan) define the final network.

Results

Overlap of miR:gene network with sequence prediction databases

Figure 1. Get High-res Image Distribution of miR:gene pairs by the number of sequence prediction databases that predict an interaction between the two molecules. Miranda, Targetscan and Pictar are the three databases used in the analysis. Only miR:gene pairs that have correlation values less than the threshold are shown.

miR connectivity distribution

Figure 2. Get High-res Image Summary of miR counts by the number of associated genes in the putative direct target network

Gene connectivity distribution

Figure 3. Get High-res Image Summary of gene counts by the number of associated miRs in the putative direct target network

Significant miR:gene edges

Table 1. Get Full Table List of miR:gene pairs with corr < -0.30 and prediction support in Miranda, Targetscan and Pictar

miR	gene	corr	prediction databases	miranda	pictar	targetscan	total
hsa-mir-29b	MLLT11	-0.46	miranda,pictar,targetscan	1	1	1	3
hsa-mir-29b	TDG	-0.43	miranda,pictar,targetscan	1	1	1	3
hsa-mir-29a	TDG	-0.42	miranda,pictar,targetscan	1	1	1	3
hsa-mir-29a	MYBL2	-0.42	miranda,pictar,targetscan	1	1	1	3
hsa-mir-29b	MFAP2	-0.42	miranda,pictar,targetscan	1	1	1	3
hsa-mir-29a	DNMT3B	-0.4	miranda,pictar,targetscan	1	1	1	3
hsa-mir-29b	VASH2	-0.4	miranda,pictar,targetscan	1	1	1	3
hsa-mir-29a	MLLT11	-0.4	miranda,pictar,targetscan	1	1	1	3
hsa-mir-29b	DNMT3A	-0.39	miranda,pictar,targetscan	1	1	1	3
hsa-mir-29b	DNMT3B	-0.38	miranda,pictar,targetscan	1	1	1	3

miR connections

Table 2. Get Full Table All miR hubs with their associated genes in the putative direct target network.

Mir	Number.of.Genes	Genes
hsa-mir-29b	20	BLMH, COL2A1, COL4A2, COL4A5, DNMT3A, DNMT3B, EIF4E2, FAM130A1, GPX7, JARID2, MFAP2, MLLT11, MYBL2, TDG, TRIM37, TUBB, TUBB2A, TUBB2B, VASH2,FSTL1
hsa-mir-29a	13	BLMH, DNMT3A, DNMT3B, GPX7, JARID2, MFAP2, MLLT11, MYBL2, TDG, TRIM37, TUBB, VASH2,EIF4E2
hsa-mir-29c	8	DNMT3A, EIF4E2, GPX7, MFAP2, MLLT11, TUBB2B, VASH2,FSTL1
hsa-mir-9	2	LMNA,KCTD12
hsa-mir-26b	1	TMEM2
hsa-mir-183	1	MEF2C
hsa-mir-142-3p	1	HMGA2
hsa-mir-182	1	MMD
hsa-mir-30b	1	ECOP
hsa-mir-200c	1	ZEB1

Gene connections

Table 3. Get Full Table All gene hubs with their associated miRs in the putative direct target network.

Gene	Number.of.Mirs	Mirs
EIF4E2	3	hsa-mir-29b, hsa-mir-29c,hsa-mir-29a
MFAP2	3	hsa-mir-29b, hsa-mir-29c,hsa-mir-29a
GPX7	3	hsa-mir-29b, hsa-mir-29c,hsa-mir-29a
VASH2	3	hsa-mir-29b, hsa-mir-29c,hsa-mir-29a
MLLT11	3	hsa-mir-29b, hsa-mir-29c,hsa-mir-29a
DNMT3A	3	hsa-mir-29b, hsa-mir-29c,hsa-mir-29a
FSTL1	2	hsa-mir-29c,hsa-mir-29b
MMD	2	hsa-mir-30c,hsa-mir-182
DNMT3B	2	hsa-mir-29b,hsa-mir-29a
JARID2	2	hsa-mir-29b,hsa-mir-29a

Methods & Data

Input

This section should list the files that were used as input.

Level 3 miR expression file = /xchip/cga/gdac-prod/tcga-gdac/jobResults/GDAC_MergeDataFilesPipeline/OV-TP/3024453/2.GDAC_MergeDataFiles.Finished/OV-TP.mirna__h_mirna_8x15kv2__unc_edu__Level_3__unc_DWD_Batch_adjusted__data.data.txt
Level 3 gene expression file = /xchip/cga/gdac-prod/tcga-gdac/jobResults/GDAC_MergeDataFilesPipeline/OV-TP/3024468/2.GDAC_MergeDataFiles.Finished/OV-TP.transcriptome__ht_hg_u133a__broad_mit_edu__Level_3__gene_rma__data.data.txt
miR:gene predicted interactions file = /xchip/cga/reference/miR_predictions/human_interactions.predicted.v2.txt
Miranda = microrna.org Aug 2010 release, Microcosm version 5
Pictar = version 1
Targetscan = release 5.2

Method

Pairwise Pearson correlations coefficients between all miR:gene pairs are first computed. All genes that have correlation values less than the user-defined threshold (-0.3) with a particular miR and have been predicted as targets of that miR in three sequence based prediction databases: Miranda[1][2] Pictar[3][4], TargetScan [5][6][7] are identified as putative direct targets of that miR. We infer a direct target miR:gene network which comprises all such putative direct associations.

threshold = -0.3

Download Results

This is an experimental feature. The full results of the analysis summarized in this report can be downloaded from the TCGA Data Coordination Center.

References

[1] Betel D, Wilson M, Gabow A, Marks DS, Sander C, microRNA target predictions: The microRNA.org resource: targets and expression, Nucleic Acids Res 36:D149-53 (2008)

[2] John B, Enright AJ, Aravin A, Tuschl T, Sander C, Marks DS, miRanda: Human MicroRNA targets., PLoS Biol 3(7):e264 (2005)

[3] Krek A, Grun D, Poy MN, Wolf R, Rosenberg L, Epstein EJ, MacMenamin P, Piedade ID, Gunsalus KC, Stoffel M, Rajewsky N, Combinatorial microRNA target predictions, Nature Genetics 37:495-500 (2005)

[4] Chen K, Rajewsky N, Natural selection on human microRNA binding sites inferred from SNP data., Nat Genet 38:1452-1456 (2006)

[5] Lewis BP, Burge CB, Bartel DP, Conserved Seed Pairing, Often Flanked by Adenosines, Indicates that Thousands of Human Genes are MicroRNA Targets., Cell 120(120):15-20 (2005)

[6] Grimson A, Farh KK, Johnston WK, Garrett-Engele P, Lim LP, Bartel DP, MicroRNA Targeting Specificity in Mammals: Determinants beyond Seed Pairing., Molecular Cell 27:91-105 (2007)

[7] Friedman RC, Farh KK, Burge CB, Bartel DP, Most Mammalian mRNAs Are Conserved Targets of MicroRNAs., Genome Research 19:92-105 (2009)

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