Marcinkowska et al. BMC Genomics 2011, 12:183 http://www.biomedcentral.com/1471-2164/12/183 have identified 38 loci of miRNAs located in chromoso- mal regions implicated in microdeletion/microduplica- tion syndromes (DECYPHER v5.0 [50]) (Additional file 5). For example, six miRNA loci (hsa-mir-185, hsa-mir- 1306, hsa-mir-1286, hsa-mir-649, hsa-mir-301b and hsa- mir-130b) are located within genomic region implicated in DiGeorge syndrome. The role of somatic copy num- ber variation of miRNA genes in cancer is extensively investigated in multiple studies (e.g. [27-31]) and was recently summarized in several review articles [51-53]. Conclusions Although ‘polymorphic’ CNVs showed some purifying effects at miRNA loci, there were still many miRNA loci that overlapped with known CNV regions (Additional file 2 and Table 2), including those that are highly vali- dated and confirmed by high-quality genotyping (Table 1). Taking into account the CNV genome coverage (1.2% ‘polymorphic-SMC’ and 2.3% ‘polymorphic-DC’) and the relatively small overlapping fractions (0.39 and 0.20, respectively) between the two sets of ‘polymorphic’ CNVs analyzed in this study, we estimated that up to 10% of the human genome is covered by highly poly- morphic CNVs. This fraction corresponds to approxi- mately 30 highly polymorphic CNV-miRNAs in the human genome (extrapolation of the fraction of miRNA loci covered by highly polymorphic CNVs analyzed in this study). It is likely that at least some of these loci are among the CNV-miRNAs identified from the top- validated ‘DGV-deposited’ CNVs (Table 2 and Addi- tional file 2). CNV-miRNAs are potential functional variants and should be considered high priority candidate variants in genotype-phenotype association studies, especially when they are located in regions implicated by linkage or association studies. As indicated in Table 1, only a small fraction of CNV-miRNAs were genotyped in three Hap- Map populations, which provides precise information about their polymorphisms. This is mostly due to the lack of appropriate methods for precise characterization of CNV polymorphisms. Although several genome-wide approaches that substantially fulfill the above require- ment were proposed recently, a simple and inexpensive method that enables accurate characterization of several CNVs of interest in a large number of samples is still needed. The lack of such a method significantly ham- pers the analyses of CNVs and their correlation with the phenotype. To verify and characterize the polymorph- isms of all CNV-miRNAs, we are developing several medium-throughput assays suited for large scale popula- tion studies that are focused on selected CNVs of poten- tial functional effect. These assays will take advantage of the MLPA-based strategy proposed previously [54-56]. Page 7 of 9 Methods Genomic coordinates (hg18) of 718 human miRNA loci, 13 600 093 SNPs (only annotated as ‘single’), 29 133 CNVs (only annotated as ‘Copy Number’) and 58 loci implicated in microdeletion syndromes were down- loaded from miRBase v13.0 http://www.mirbase.org, dbSNP build 130; Apr 30, 2009, Database of Genomic Variants update Aug 05, 2009 http://projects.tcag.ca/var- iation and DECIPHER database v5.0 [50]http://decipher. sanger.ac.uk, respectively. The coordinates of 1319 CNVs described as ‘polymorphic-SMC’ and 5037 CNVs described as ‘polymorphic-DC’ were extracted from sup- plementary materials of references [32] and [22], respec- tively. The number of miRNA loci and fraction of genome covered by CNV regions were calculated using ‘feature coverage’ and ‘base coverage’ tools available on the Galaxy, web portal for large-scale interactive data analyses [57]. The expression profiles of CNV-miRNAs were gener- ated with the use of mimiRNA database [36] that sum- marizes expression data from miRNA Atlas [58], quantitative real-time PCR [59,60] as well as microarray and deep sequencing data from GEO (Gene Expression Omnibus) [61]. The assessment of evolutionary conser- vation of microRNAs was done based on the data avail- able at the miRBase and blast searches of the vertebrate genomic sequences with human pre-microRNAs. All statistical analyses were performed using Statistica (StatSoft, Tulsa, OK). The Fisher’s exact test for com- parison of SNPs frequency in the annotated miRNA sequences and in the total genome sequence was calcu- lated as described in [62], with the use of the online tool available on webpage http://www.langsrud.com/ fisher.htm. Additional material Additional file 1: SNPs identified in pre-miRNA sequences. Excel table containing list of SNPs identified in annotated pre-miRNA sequences. Additional file 2: miRNA identified in CNV regions. Excel table containing list of pre-miRNA annotated sequences identified in ‘DGV- deposited’ CNVs. Additional file 3: Expression profiles of selected CNV-miRNAs. Expression profiles of selected CNV-miRNAs generated with the use of mimiRNA database [36]. The expression of all miRNAs was normalized in each tissue to a standard score spanning 1-1,000 (1,000 represents highest expression observed in tissue). The bars represent mean expression measured in multiple experiments and the error bars represent standard error of the mean. The variability of the expression level is indicated by colors (red - lowest variability; yellow - highest variability). Details can be found on mimiRNA webpage http://mimirna. centenary.org.au and in [36]. Additional file 4: miRNAs located in CNVs with well defined breakpoints. Excel table showing characteristics of miRNAs located in CNVs with well defined breakpoints.