Supplement S1: Material and methods 1. Subjects The BD patient group consisted of 41 % males and 59 % females. The SZ patient group consisted of 64.9 % males and 35.1 % females and a control group of 51.4 % female and 48.6% male participants. Clinical characterization of the patients included the MiniInternational Neuropsychiatric Interview (MINI1), the Diagnostic Interview for Genetic Studies (DIGS2), the Family Interview for Genetic Studies (FIGS3) and the Schedules for Clinical Assessment in Neuropsychiatry (SCAN4), a highly reliable and valid method for DSM-IV diagnoses5. The final diagnoses were made according to the DSMIV-TR criteria6 and determined by consensus of 2 research psychiatrists. Only the patients where consensus was reached were included in the study. The unrelated Swedish control individuals, consisting of a large population-based sample representative of the general population of the region, were randomly selected from the ‘Betula study’7, 8. The population stratification of the association sample was analyzed with free software package STRUCTURE (http://pritch.bsd.uchicago.edu/structure.html) using 37 short tandem repeat markers. No population substructure was observed. 2. Gene selection References for the ‘in silico’ miRNA selection: Linkage/association evidence: 9, 10, 11, 12, 13, 14 Expression in mammalian brain evidence: 15, 16, 17, 18,19, 20, 21, 22, 23, 24 3. Sanger sequencing based variant discovery 10 ng of DNA, 1.5 µl 10X PCR buffer (Titatinum taq buffer, Clonetech, California, USA), 0.15 µl of 25 mM dNTPs (Invitrogen, Life Technology, NY, USA), 0.075 µl of 100µM forward and reverse primer (IDT, Integrated DNA Technologies Inc, CA, USA) and 0.075 µl of Titanium Taq (Clonetech, CA, USA) were used in each 15 µl PCR amplification. For some of the reactions 1 M betaine (Thermo Scientific, DE, USA) was used (when used, it is listed next to the melting temperature Tm of the amplicons). The PCR conditions were as follows: initial denaturation step for 3 min at 95 °C, followed by 35 cycles of [30sec at 95 °C, 30 sec at Tm and 45 sec at 72 °C] and the final elongation step for 5 min at 72 °C on Veriti thermal cycles (Applied Biosystems, Life technologies, CA, USA). Primers for sequencing miRNA (in brackets are melting temperatures Tm for each primer pair and if used, concentration of betaine): MIR34A-F: CAAACTTCTCCCAGCCAAAA MIR34A-R: CTTTCCTCCCCACATTTCCT (Tm-63 °C, 1 M betaine) MIR99B-F: TTCTATCAGGCCATGCCTTC MIR99B-R: TGATCTCCTTGGGTGTCCTC (Tm-62 °C, 1 M betaine) MIR103A1 and MIR103B1-F: AAAGCGTACTTCCCAATCCA MIR103A1 and MIR103B1-R: CACAACCTAAATCCCTTGAGGA (Tm-58 °C) MIR128-1-F: ATACTGTGAAGTACACTGCATATAAGG MIR128-1-R: GCCAAAGATGTCACTTAAATTCT (Tm- 58 °C) MIR132-F: CACGTGGGATCTTGACTCG MIR132-R: GGCACCTTGGCTCTAGACTG (Tm-62 °C, 1 M betaine) MIR135B-F: CCGATCCCAGGTTACCAGAT MIR135B -R: CAAGAACTGGAAACTCATTACTGG (Tm-63 °C, 1 M betaine) MIR137-F: CTTTCCGGTGGAACCAGTG MIR137-R: GCACAGCTTTGGATCCTTCT (Tm-63 °C) MIR301A-F: TCCAGACGTGTTTCATAATGC MIR301A -R: TCATCAATAAGCAACATCACTTTG (Tm-63 °C, 1 M betaine) MIR448-F: AGGCCAGAAGAGGCTTTCAT MIR448-R: CAGATCTACTGGCCCTGAGC (Tm-62 °C) MIR764-F: GGAGGAACTTGGTTTTTAAAGGA MIR764-R: CAGTCCCTTTACCGCTGTTT (Tm-62 °C) MIRLET7A2-F: AACCCGAGGAAACAGAATATGA MIRLET7A2-R: TTGCTCCCTTCATGTTTTCA (Tm-58 °C) MIRLET7E-F: ACCCGTAGAACCGACCTTG MIRLET7E-R: GGAAAACAGATTTCAGGGGAAG (Tm-63 °C, 1M betaine) PCR products were treated with ExoSAP-IT (GE Healthcare, Chalfont St. Giles, UK) and sequenced using the BigDye Terminator v3.1 Cycle Sequencing Kit, according to the instructions of the manufacturers (Applied Biosystems, Life technologies, CA, USA). Sequencing ran for 25 cycles: 10 sec at 96°C, 5 sec at 50°C and 4 min at 60°C on Veriti thermal cyclers (Applied Biosystems, Life technologies, CA, USA). Sequencing reactions were run on an ABI 3730XL automated sequencer (Applied Biosystems, Life Technologies, CA, USA), and the resulting trace files were analyzed for variants using NovoSNP25. 4. Fragment analysis Fragment analysis was carried out on the 3730XL DNA Analyzer (Applied Biosystems Inc, Life Technologies, CA, USA) with a G5 filter. 2 µl of the PCR product was mixed with 10 µl of Hi-Di formamide, and 0.3 µl Liz-500 GeneScanTM sizing standard (Applied Biosystems, Life Technologies, CA, USA) in an optical 96-well plate. The mixture was denatured at 95 °C for 5 minutes, immediately placed on ice for 15 minutes and subjected to the analysis. Products were sized using an ABI 3730XL sequencer and the sizes 399, 414, 430, 445, 460, 475 and 489 corresponded to PCR products with 3, 4, 5, 6, 7, 8 and 9 (15 bp) VNTRs. The genotypes were assigned and scored using GeneScan® Analysis, v3.5.2 (Applied Biosystems, Life Technologies, CA, USA). Primers used for fragment analysis: FAM labeled forward primer: 5’-CTTTCCGGTGGAACCAGTG-3’-FAM reverse primer: 5’-GCACAGCTTTGGATCCTTCT-3’ 5. Generation of SH-SY5Y stable cell lines expressing mature miR-137 SH-SY5Y cells were cultivated in a minimum essential medium (MEM) that included 10% (vol/vol) fetal calf serum, 1X non-essential amino acids, 2mM L-glutamine and penicillin (100U/ml) /streptomycin (100µg/ml). The HEK293T cell line was purchased from Invitrogen (Life Technologies, CA, USA) and cultivated in DMEM with 10 % fetal calf serum, 2mM L-glutamine, and penicillin (100 U/ml), streptomycin (100 µg/ml), 1X non-essential amino acids. Both cell lines were cultivated at 37 °C with 5 % CO2. Gateway attB1 and attB2 sequences were added by PCR to the 5’ and 3’ of a miRNA gene sequence in order to amplify specific constructs: MIR137 wt (3 VNTRs), MIR137 -4C>T, MIR137 4 VNTR and MIR137 8 VNTR. Constructs with or without specific variants were ordered from IDT (Integrated DNA Technologies Inc, CA, USA) and confirmed by sequencing. Gateway primers: mir137-F: GGGGACAAGTTTGTACAAAAAAGCAGGCTGGCGGGCTCAGCGAGCAGCA attB1 mir137-R: GGGGACCACTTTGTACAAGAAAGCTGGGTAAACACCCGAGGAAATGAAAAGAAC attB2 DNA constructs (Integrated DNA Technologies Inc, CA, USA) MIR137 (wild type, 3 VNTR) TCGAGGATCCAAACACCCGAGGAAATGAAAAGAACAAGAAAGTGCTACCTT GGCAACCACGGGCGTTTAGTGGCCAGCTGGTGGGCTGGGGAGGGCGGCCGCT GCCCCCCTGCCGCTGGTACTCTCCTCGACTACGCGTATTCTTAAGCAATAACA ACGTAATCCGTATTATCCACCCAAGAATACCCGTCACCGAAGAGAGTCAGAG GACCAAGCTGCCGCTGCCGCTGCTACCGCTGCCGCTGCTACCGCTGCCGCTGC TACTGCCGCCGCCGCCGCCACCAGAACTCTTGCTGCTCGCTGAGCCCGCCCGC TAGCTCGA MIR137 (variant -4 T, 3 VNTR) TCGAGGATCCAAACACCCGAGGAAATGAAAAGAACAAGAAAGTGCTACCTT GGCAACCACGGGCGTTTAGTGGCCAGCTGGTGGGCTGGGGAGGGCGGCCGCT GCCCCCCTGCCGCTGGTACTCTCCTCGACTACGCGTATTCTTAAGCAATAACA ACGTAATCCGTATTATCCACCCAAGAATACCCGTCACCGAAGAGAGTCAGAG GACCAAGTTGCCGCTGCCGCTGCTACCGCTGCCGCTGCTACCGCTGCCGCTGC TACTGCCGCCGCCGCCGCCACCAGAACTCTTGCTGCTCGCTGAGCCCGCCCGC TAGCTCGA MIR137 (4 VNTR) TCGAGGATCCAAACACCCGAGGAAATGAAAAGAACAAGAAAGTGCTACCTT GGCAACCACGGGCGTTTAGTGGCCAGCTGGTGGGCTGGGGAGGGCGGCCGCT GCCCCCCTGCCGCTGGTACTCTCCTCGACTACGCGTATTCTTAAGCAATAACA ACGTAATCCGTATTATCCACCCAAGAATACCCGTCACCGAAGAGAGTCAGAG GACCAAGCTGCCGCTGCCGCTGCTACCGCTGCCGCTGCTACCGCTGCCGCTGC TACCGCTGCCGCTGCTACTGCCGCCGCCGCCGCCACCAGAACTCTTGCTGCTC GCTGAGCCCGCCCGCTAGCTCGA MIR137 (8 VNTR) TCGAGGATCCAAACACCCGAGGAAATGAAAAGAACAAGAAAGTGCTACCTT GGCAACCACGGGCGTTTAGTGGCCAGCTGGTGGGCTGGGGAGGGCGGCCGCT GCCCCCCTGCCGCTGGTACTCTCCTCGACTACGCGTATTCTTAAGCAATAACA ACGTAATCCGTATTATCCACCCAAGAATACCCGTCACCGAAGAGAGTCAGAG GACCAAGCTGCCGCTGCCGCTGCTACCGCTGCCGCTGCTACCGCTGCCGCTGC TACCGCTGCCGCTGCTACCGCTGCCGCTGCTACCGCTGCCGCTGCTACCGCTG CCGCTGCTACCGCTGCCGCTGCTACTGCCGCCGCCGCCGCCACCAGAACTCTT GCTGCTCGCTGAGCCCGCCCGCTAGCTCGA Lentiviruses encoding MIR137-EGFP wild type and variant fusion constructs, where the EGFP is fused at the 3’-terminal of the MIR137 sequence, were produced in HEK293T cells by calcium phosphate co-transfection of 10 µg of pLenti-MIR137 expression constructs and 3 µg of pMD2-VSV and 6.5 µg of pCMV-R8.91 viral packaging vectors. The calcium transfection medium was removed 8 hours after transfection. Cells were washed with PBS and replaced with medium containing 10 mM sodium butyrate to enhance promoter activity. The following day the medium was replaced with complete NB medium and incubated for 24 h. Lentiviruses were harvested by filtering the supernatant of the HEK293T cells. SHY-SY5Y cells, seeded in the culture dishes were transduced with lentiviral particles. After the infection, the cells were selected in MEM media supplemented with 10% fetal calf serum, 1% non-essential amino acids, 2mM Lglutamine and 100 U/ml penicillin, 100 µg/ml streptomycin and 3 µg/ml blasticidin for 3–4 weeks. Transduced SH-SY5Y cell lines were named as follows: a) MIR137 wt: clones c1 (S51.2), c2(S52), c3(S53), c4, c5 and c6 were transduced with MIR137 vector with 3 VNTRs and Chr1:98511731, -4 C (wt) in pri-miR137. b) MIR137 4C>T: clones c1(S41), c2(S42), c3(S43.2), c4, c5, c6 were transduced with MIR137 vector with 3 VNTRs and Chr1:98511731, -4 T. c) MIR137 4VNTRs: clones c1(S61), c2(S62), c3(S63), c4, c5 and c6 were transduced with MIR137 vector with 4 VNTRs and Chr1:98511731, -4 C. d) MIR137 8VNTRs: clones c1(S71), c2(S72), c3(S73), c4, c5 and c6 were transduced with MIR137 vector with 8 VNTRs and Chr1:98511731, -4 C. For all transductions (a-d): clones c4, c5 and c6 were used for independent transduction followed by replication of the RT-qPCR analysis. 6. RNA isolation Triplicates of approximately 1 x 106 cells originating from clone SH-SY5Y population with the vector of interest were used for each extraction. The concentration and quality of RNA was assessed by spectrophotometry on Nanodrop (Thermo Scientific, DE, USA) and Agilent 2100 Bioanalyzer with Agilent Small RNA kit and Agilent RNA 6000 Pico kit (all Agilent Technologies, CA, USA). Total RNA was treated with TURBO DNA-free kit according to manufacturer’s protocol (Ambion, Life Technologies, CA, USA) prior to RT-qPCR and microarray experiments. 7. Expression of miR-137 and EGFP EGFP RT-qPCR primers EGFP-F: GTGGTGCCCATCCTGGTC EGFP-R:CCGTCGTCCTTGAAGAAGAT Endogenous controls: Following the manufacturer’s protocol, 4 µg aliquots of total RNA were transcribed with Superscript III (Invitrogen, Life Technologies, CA, USA) using random hexamers prior to RT-qPCR using SYBR Green I mix. GAPDH-F: TGCACCACCAACTGCTTAGC GAPDH-R: GGCATGGACTGTGGTCATGAG HMBS-F: GAAACTCTGCTTCGCTGCATT HMBS-R: TGCCCATCTTTCATCACTGTATG SDHA-F: TGGGAACAAGAGGGCATCTG SDHA-R: GGCATGGACTGTGGTCATGAG TBP- F: CTACCGTGAATCTTGGCTGTAAA TBP- R: TTCTCATGATGACTGCAGCAAA 8. Microarray analysis (SAM) Statistical analysis of microarrays resulted in the identification of genes with significant changes in expression by assimilating a set of gene specific scores. Each gene was assigned a score based on the expression differences relative to the standard deviation of repeated measurements of that gene. Genes with scores above the threshold are regarded as significant. For statistical analysis of microarrays between miR-137 wild type (class A) and miR-137 -4C>T (class B) datasets, the statistic design using SAM v1.0 was as follows: two class unpaired analysis; delta 1.9660827, upper cutoff 4.572125 lower cutoff –infinity. Data was permuted 500 times. FDR at median and at 90th percentile was 0,00000%. For analysis using SAM on 3 datasets originating from the transcriptome of cells transduced with MIR137 wild type (3VNTR), MIR137 4 VNTRs and 8 VNTRs) we used a multiclass study design (3 classes); delta 1.075725, upper cutoff 2.5578384; lower cutoff – infinity and 500 permutations. FDR at median and at 90th percentile was 0.00000%. 9. GSEA analysis Each probe set in the expression dataset was collapsed into a single vector, identified by the gene symbol and using the maximum probe expression value. Statistical significance of the enrichment score was assessed by 1000 permutations of the gene sets (sets larger than 500 genes and smaller than 15 genes were excluded from the analysis). For the enrichment analysis we compared expression values between cells transduced with wild type and variant MIR137 construct. For analyzing gene expression differences in groups with different number of VNTRs in pri-miR-137 we compared the microarray expression datasets originating from cells transduced with MIR137 wild type (3 VNTRs), 4VNTR MIR137 and 8 VNTR MIR137 constructs. All gene sets with a nominal p-value lower than 0.01 and FDR lower than 5% or lower than 25% (if the 5% threshold was breached) were called as significant or enriched between the analyzed groups. 10. Identification of predicted targets for miR-137 3’UTR sequences were extracted using Ensembl BioMart, v.0.7 from GRCh37.p10. Possible target sites in the 3’UTR sequences were searched using the BLAST algorithm with adjusted settings and with parameters: word size 7, E value of 50000 and number of alignments of 100000. The final input query was mature miR-137 obtained from miRBase version 1826. From the BLAST all possible transcripts of all genes with ‘seedhits’ (complementarity between 3’UTR and bases 2-8 of the mature miR-137) and ‘nonseed hits’ (complementarity of the 3’UTR with mature miR-137 outside the ‘seed’ but not shorter than 7 consecutive bases) were extracted. We compared the output file with all significantly differentially expressed genes derived from the microarray data by SAM or GSEA. We further used PITA (August 2008 release)27, DIANAmT (v3.0)28, MIRANDA (August 2010 release)29, MIRWALK (March 2011 release)30, PICTAR (5way; March 2007 release)31 and TARGETSCAN (v5.1)32 to detect other potential miR137 targets. The same analysis was done on the set of 21435 genes which were not significantly differentially expressed and the results of the comparison and the statistical evaluation is presented in Supplement S3. References: 1. Lecrubier Y, Sheehan DV, Weiller E, Amorim P, Bonora I, Sheehan KH et al. The Mini International Neuropsychiatric Interview (MINI). A short diagnostic structured interview: Reliability and validity according to the CIDI. Eur Psychiat 1997; 12(5): 224-231. 2. Nurnberger JI, Jr., Blehar MC, Kaufmann CA, York-Cooler C, Simpson SG, Harkavy-Friedman J et al. Diagnostic interview for genetic studies. Rationale, unique features, and training. NIMH Genetics Initiative. Arch Gen Psychiatry 1994; 51(11): 849-859; discussion 863-844. 3. Maxwell M. Family interview for genetic studies. Clinical Neurogenetic Branch, Intramural Research Program, NIMH 1992. 4. Wing JK, Babor T, Brugha T, Burke J, Cooper JE, Giel R et al. SCAN. Schedules for Clinical Assessment in Neuropsychiatry. Arch Gen Psychiatry 1990; 47(6): 589-593. 5. Ekholm B, Ekholm A, Adolfsson R, Vares M, Osby U, Sedvall GC et al. Evaluation of diagnostic procedures in Swedish patients with schizophrenia and related psychoses. Nord J Psychiatry 2005; 59(6): 457-464. 6. American Psychiatric Association., American Psychiatric Association. Task Force on DSM-IV. Diagnostic and statistical manual of mental disorders : DSM-IV-TR. 4th edn. American Psychiatric Association: Washington, DC, 2000, xxxvii, 943 p.pp. 7. Nilsson L-G AR, Bäckman L, de Frias CM, Molander B, et al. The Betula prospective cohort study: memory, health and aging. . Aging Neuropsychol Cognition 1997; (4): 1–32. 8. Nilsson LG, Adolfsson R, Backman L, de Frias CM, Molander B, Nyberg L. Betula: A prospective cohort study on memory, health and aging. Aging Neuropsychol C 2004; 11(2-3): 134-148. 9. Lewis CM, Levinson DF, Wise LH, DeLisi LE, Straub RE, Hovatta I et al. Genome scan meta-analysis of schizophrenia and bipolar disorder, part II: Schizophrenia. Am J Hum Genet 2003; 73(1): 34-48. 10. Segurado R, Detera-Wadleigh SD, Levinson DF, Lewis CM, Gill M, Nurnberger JI, Jr. et al. Genome scan meta-analysis of schizophrenia and bipolar disorder, part III: Bipolar disorder. Am J Hum Genet 2003; 73(1): 49-62. 11. Ng MY, Levinson DF, Faraone SV, Suarez BK, DeLisi LE, Arinami T et al. Meta-analysis of 32 genome-wide linkage studies of schizophrenia. Molecular psychiatry 2009; 14(8): 774-785. 12. Ripke S, Sanders AR, Kendler KS, Levinson DF, Sklar P, Holmans PA et al. Genome-wide association study identifies five new schizophrenia loci. Nat Genet 2011; 43(10): 969-976. 13. Wei J, Hemmings GP. A further study of a possible locus for schizophrenia on the X chromosome. Biochem Biophys Res Commun 2006; 344(4): 1241-1245. 14. Moon HJ, Yim SV, Lee WK, Jeon YW, Kim YH, Ko YJ et al. Identification of DNA copy-number aberrations by array-comparative genomic hybridization in patients with schizophrenia. Biochem Biophys Res Commun 2006; 344(2): 531539. 15. Kim J, Krichevsky A, Grad Y, Hayes GD, Kosik KS, Church GM et al. Identification of many microRNAs that copurify with polyribosomes in mammalian neurons. P Natl Acad Sci USA 2004; 101(1): 360-365. 16. Sempere LF, Freemantle S, Pitha-Rowe I, Moss E, Dmitrovsky E, Ambros V. Expression profiling of mammalian microRNAs uncovers a subset of brainexpressed microRNAs with possible roles in murine and human neuronal differentiation. Genome Biol 2004; 5(3): R13. 17. Barad O, Meiri E, Avniel A, Aharonov R, Barzilai A, Bentwich I et al. MicroRNA expression detected by oligonucleotide microarrays: system establishment and expression profiling in human tissues. Genome Res 2004; 14(12): 2486-2494. 18. Landgraf P, Rusu M, Sheridan R, Sewer A, Iovino N, Aravin A et al. A mammalian microRNA expression atlas based on small RNA library sequencing. Cell 2007; 129(7): 1401-1414. 19. Liang Y, Ridzon D, Wong L, Chen C. Characterization of microRNA expression profiles in normal human tissues. BMC Genomics 2007; 8: 166. 20. Bak M, Silahtaroglu A, Moller M, Christensen M, Rath MF, Skryabin B et al. MicroRNA expression in the adult mouse central nervous system. RNA 2008; 14(3): 432-444. 21. Zhang R, Su B. MicroRNA regulation and the variability of human cortical gene expression. Nucleic Acids Res 2008; 36(14): 4621-4628. 22. Olsen L, Klausen M, Helboe L, Nielsen FC, Werge T. MicroRNAs show mutually exclusive expression patterns in the brain of adult male rats. PLoS One 2009; 4(10): e7225. 23. Tang Y, Liu D, Zhang L, Ingvarsson S, Chen H. Quantitative analysis of miRNA expression in seven human foetal and adult organs. PLoS One 2011; 6(12): e28730. 24. Shinohara Y, Yahagi K, Kawano M, Nishiyori H, Kawazu C, Suzuki N et al. miRNA profiling of bilateral rat hippocampal CA3 by deep sequencing. Biochem Biophys Res Commun 2011; 409(2): 293-298. 25. Weckx S, Del-Favero J, Rademakers R, Claes L, Cruts M, De Jonghe P et al. novoSNP, a novel computational tool for sequence variation discovery. Genome Res 2005; 15(3): 436-442. 26. Kozomara A, Griffiths-Jones S. miRBase: integrating microRNA annotation and deep-sequencing data. Nucleic Acids Res 2011; 39(Database issue): D152-157. 27. Kertesz M, Iovino N, Unnerstall U, Gaul U, Segal E. The role of site accessibility in microRNA target recognition. Nat Genet 2007; 39(10): 1278-1284. 28. Kiriakidou M, Nelson PT, Kouranov A, Fitziev P, Bouyioukos C, Mourelatos Z et al. A combined computational-experimental approach predicts human microRNA targets. Genes Dev 2004; 18(10): 1165-1178. 29. Enright AJ, John B, Gaul U, Tuschl T, Sander C, Marks DS. MicroRNA targets in Drosophila. Genome Biol 2003; 5(1): R1. 30. Dweep H, Sticht C, Pandey P, Gretz N. miRWalk--database: prediction of possible miRNA binding sites by "walking" the genes of three genomes. Journal of biomedical informatics 2011; 44(5): 839-847. 31. Krek A, Grun D, Poy MN, Wolf R, Rosenberg L, Epstein EJ et al. Combinatorial microRNA target predictions. Nat Genet 2005; 37(5): 495-500. 32. Lewis BP, Shih IH, Jones-Rhoades MW, Bartel DP, Burge CB. Prediction of mammalian microRNA targets. Cell 2003; 115(7): 787-798.