Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Complexity of Murine Cardiomyocyte miRNA Biogenesis, Sequence Variant Expression and Function

ABSTRACT: microRNAs (miRNAs) are critical to heart development and disease. Emerging research indicates that regulated precursor processing can give rise to an unexpected diversity of miRNA variants. We subjected small RNA from murine HL-1 cardiomyocyte cells to next generation sequencing to investigate the relevance of such diversity to cardiac biology. ~40 million tags were mapped to known miRNA hairpin sequences as deposited in miRBase version 16, calling 403 generic miRNAs as appreciably expressed. Hairpin arm bias broadly agreed with miRBase annotation, although 44 miR* were unexpectedly abundant (>20% of tags); conversely, 33 -5p/-3p annotated hairpins were asymmetrically expressed. Overall, variability was infrequent at the 5M-bM-^@M-2 start but common at the 3M-bM-^@M-2 end of miRNAs (5.2% and 52.3% of tags, respectively). Nevertheless, 105 miRNAs showed marked 5M-bM-^@M-2 isomiR expression (>20% of tags). Among these was miR-133a, a miRNA with important cardiac functions, and we demonstrated differential mRNA targeting by two of its prevalent 5M-bM-^@M-2 isomiRs. Analyses of miRNA termini and base-pairing patterns around Drosha and Dicer cleavage regions confirmed the known bias towards uridine at the 5M-bM-^@M-2 most position of miRNAs, as well as supporting the thermodynamic asymmetry rule for miRNA strand selection and a role for local structural distortions in fine tuning miRNA processing. We further recorded appreciable expression of 5 novel miR*, 38 extreme variants and 8 antisense miRNAs. Analysis of genome-mapped tags revealed 147 novel candidate miRNAs. In summary, we revealed pronounced sequence diversity among cardiomyocyte miRNAs, knowledge of which will underpin future research into the mechanisms involved in miRNA biogenesis and, importantly, cardiac function, disease and therapy. We examined miRNA profiles of mouse HL1 cells in culture at 4 time points (3 in biological duplicate)

ORGANISM(S): Mus musculus

SUBMITTER: Hardip Patel

PROVIDER: E-GEOD-39531 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Publications

Complexity of murine cardiomyocyte miRNA biogenesis, sequence variant expression and function.

Humphreys David T DT Hynes Carly J CJ Patel Hardip R HR Wei Grace H GH Cannon Leah L Fatkin Diane D Suter Catherine M CM Clancy Jennifer L JL Preiss Thomas T

PloS one 20120203 2

microRNAs (miRNAs) are critical to heart development and disease. Emerging research indicates that regulated precursor processing can give rise to an unexpected diversity of miRNA variants. We subjected small RNA from murine HL-1 cardiomyocyte cells to next generation sequencing to investigate the relevance of such diversity to cardiac biology. ∼40 million tags were mapped to known miRNA hairpin sequences as deposited in miRBase version 16, calling 403 generic miRNAs as appreciably expressed. Ha ...[more]

PMID: 22319597

Similar Datasets

Project description:While the importance of random sequencing errors decreases at higher DNA or RNA sequencing depths, systematic sequencing errors (SSEs) dominate at high sequencing depths and can be difficult to distinguish from biological variants. These SSEs can cause base quality scores to underestimate the probability of error at certain genomic positions, resulting in false positive variant calls, particularly in mixtures such as samples with RNA editing, tumors, circulating tumor cells, bacteria, mitochondrial heteroplasmy, or pooled DNA. Most algorithms proposed for correction of SSEs require a training data set, which is typically either from a part of the data set being M-bM-^@M-^\recalibratedM-bM-^@M-^] (Genome Analysis ToolKit, or GATK) or from a separate data set with special characteristics (SysCall). Here, we combine the advantages of these approaches by adding synthetic RNA spike-in standards to human RNA, and use GATK to recalibrate base quality scores with reads mapped to the spike-in standards. Compared to conventional GATK recalibration that uses reads mapped to the genome, spike-ins improve the accuracy of Illumina base quality scores by a mean of 5 units, and by as much as 13 units M-BM- at CpG sites. In addition, since reads mapping to the genome are not used for recalibration, our method allows run-specific recalibration even for the many species without a comprehensive and accurate SNP database. We also use GATK with the spike-in standards to demonstrate that the Illumina RNA sequencing runs overestimate quality scores for AC, CC, GC, GG, and TC dinucleotides, while SOLiD has less dinucleotide SSEs but more SSEs for certain cycles. We conclude that using these DNA and RNA spike-in standards with GATK improves base quality score recalibration. Four human RNA samples with equimolar ERCC spike-in standards were sequenced on Illumina. Two human brain/liver/muscle RNA mixtures with dynamic range of ERCC spike-in standards were sequenced on SOLiD.

Project description:We investigated the expression profiles of microRNAs (miRNA) in 27 renal cell carcinoma (RCC) FFPE tissues (3 chRCC, 5 papRCC and 18 ccRCC), 4 upper urinary tract-urothelial cell carcinomas of the renal pelvis-ureter (UUT-UCCs) and 20 normal kidneys by using the miRCURY LNAM-bM-^DM-" microRNA Array, 6th gen (Exiqon, Woburn MA), containing capture probes that target all miRNAs for all species registered in the miRBASE version 16.0. Real-time PCR (qRT-PCR) using appropriate endogenous controls was performed in order to validate the microarray results of the 27 most differentially expressed (DE) miRNAs. We identified 434 miRNAs that were significantly deregulated in all kidney tumours compared to the normal tissues. A total of 126 miRNAs (29%) had increased expression while 303 (69.8%) had decreased expression in RCC. Out of the 434 DE miRNAs, we detected 94 co-up-regulated and 218 co-down-regulated microRNAs among chRCC, papRCC and ccRCC. Of these, 89 and 203 were co-up- and co-down-regulated between RCCs and UUT-UCCs, respectively. We detected 11, 44 and 24 up-regulated miRNAs, which were specific for ccRCC, chRCC and papRCC, respectively. Moreover, 19, 18 and 8 miRNAs were uniquelly down-regulated in ccRCC, chRCC and papRCC, respectively. We also detected 89 and 203 co-up- and co-down-regulated miRNAs between kidney cancer and UUT-UCCs. Five miRNAs were up-regulated specifically in renal tumours and 49 in UUT-UCCs, whereas 15 miRNAs were down-regulated specifically in renal tumours and 89 in UUT-UCCs, respectively. Our data validicate that expression of miRNAs tends to be down-regulated renal cell carcinomas compared with normal kidney. We used 18 ccRCC, 3 chRCC, 5 papRCC, 4 UUT-UCC, 1 undifferentiated carcinoma and 19 normal tissue samples for miRNA profiling. Total RNA (0.5 M-BM-5g) from each sample and reference was labeled with Hy3M-bM-^DM-" fluorescent label, using the miRCURY LNAM-bM-^DM-" microRNA Hi-Power Labeling Kit (Exiqon, Woburn MA). The Hy3M-bM-^DM-\"-labeled samples were hybridized to the miRCURY LNAM-bM-^DM-" microRNA Array, 6th gen (Exiqon, Woburn MA), using an Agilent hybridization SureHyb chamber and gasket slide kits. After hybridization, the microarray slides were scanned at 10 M-NM-<m using the High-Resolution Microarray Scanner (Agilent Technologies) and stored in an ozone free environment. The image analysis was carried out using the ImaGene 8.0 software (BioDiscovery, Inc., USA). Raw microarray data were filtered, background corrected and quantile normalizated. Normalized data were further extracted, pre-processed and sorted with Microsoft ExcelM-BM-.. MicroRNAs were considered to be significantly differentially expressed if they obtained a p-value<0.05 and a FDRM-bM-^IM-$0.05.

Dataset Information

Complexity of Murine Cardiomyocyte miRNA Biogenesis, Sequence Variant Expression and Function

Publications

Complexity of murine cardiomyocyte miRNA biogenesis, sequence variant expression and function.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure