Next Generation Deep Sequencing Facilitates Quantitative Analysis of microRNA affected by thapsigargin treatment
ABSTRACT: Purpose: microRNA profiles were generated from NIH-3T3 cells control and thapsigargin treated, in duplicate. The goal of this study was to compare microRNA profiles of untreated and thapsigargin treated NIH-3T3 fibroblast cells. Methods: NIH-3T3 cells were grown to confluency and either untreated or treated with 500 nM thapsigargin in media for 24 hours. Cells were harvested with TriZol and RNA isolated according to manufacturers protocol Analysis Outline: Short reads in fastq format were assembled using BclToFastq.pl script from Illumina CASAVA 1.8.1 software pipeline.Read quality was examined using FastQC program (http://www.bioinformatics.bbsrc.ac.uk/projects/fastqc). Adapters were trimmed at the 3'end using Btrim prgram (PMID:21651976), only sequences equal to and longer than 18nt were retained, leading N base was trimmed at the 5' end. Unique reads were collapsed using Raw_data_parse program from miRExpress suite (PMID:19821977) (the result of this process is a file that contains unique sequences in one column and number of times this sequence was found in the library in another). They can be found in *.merge files in trimmed_reads directory. Collapsed reads were reformatted and uploaded into miRanalyzer web-based pipeline (http://bioinfo2.ugr.es/miRanalyzer/miRanalyzer.php; PMID:21515631) and matched to known mature miRNA (miRBase vesion 16), RFAM database (version 15) of known non-coding RNAs and known gene transcripts. The purpose of miRAnalyzer analysis was to only detect known miRNAs, prediction of novel miRNAs was not performed; search parameters were kept at default. MiRanalyzer output is saved in miRanalyzer folder with detailed information about mapping to known miRNA. Known miRNAs were divided into mature, maturestar (star sequences), maturestarunobs (star sequences not in miRBase) and hairpin. For each of the libraries there are files with unique and ambiguous mappings. Differentional expression analysis was based on unique alignments to known miRNAs (mature_unique.txt file in miRanalyzer folder). Mature_unique.txt has following columns: name: mature miRNA ID from miRBase; #unique reads: number of unique reads mapped; readCount: number of reads mapped; norm_expressed_all: normalized to all reads; norm_expressed_mapped: normalized to mapped reads. miRNA expression profiling was performed using edgeR bioconductor package (PMID:20478825). For differential expression analysis, used TMM normalization and analysis using common disperion (using tagwise dispersion yielded the same results). FDR was calculated according to Hochberg-Benjamini procedure (PMID:2218183). Results of differential expression analysis were saved in diff_exp folder as diff_exp.txt. diff_exp.txt contains miRNA concentrations in log scale, log2 ratio of WT to KO; p-values and FDR corrected p-values. miRNAs were sorted by p-value. NIH-3T3 cells grown to confluency and treated with 500 nM thapsigargin in media for 24 hours
Project description:MicroRNAs are 18-23 nucleotide non-coding RNAs that regulate gene expression in a sequence specific manner. Little is known about the repertoire and function of miRNAs in melanoma or the melanocytic lineage. We therefore undertook a comprehensive analysis of the miRNAome in a diverse range of pigment cells including: melanoblasts, melanocytes, congenital nevocytes, acral, mucosal, cutaneous and uveal melanoma cells. We sequenced 12 small RNA libraries using Illumina's GAII platform. This massively parallel sequencing approach revealed a total of 539 known mature and mature-star sequences, along with the prediction of 389 novel miRNA candidates. Using the relative proportion of the total unique read counts against total number of reads, hierarchal clustering of all novel candidates plus known miRNAs gave good separation of the different histological subtypes. Some of the novel miRNAs may be specific to the melanocytic lineage and as such could be used as biomarkers to assist in the early detection of distant metastasises by measuring the circulating levels in blood. Follow up studies of the functional roles of these pigment cell miRNAs and the identification of their targets should shed further light on their role in the development and progression of melanoma. Illumina GAII deep sequencing of 12 melanoma and pigment cell lines
Project description:MicroRNAs (miRNA) have alternative forms known as isomiRs, which differ from each other by a few nucleotides. Next generation sequencing platforms facilitate identification of these isomiRs and recent discoveries regarding their functional importance have increased our understandings of the regulatory complexities of the microRNAome. Observed changes in the miRNA profiles in mosquitoes infected with flaviviruses have implicated small RNAs in the interactions between viruses and their vectors. Here we analysed the isomiR profiles of both uninfected and infected blood fed Aedes aegypti mosquitoes with a major human pathogen, Dengue virus at two time points post-infection. We found noticeable changes to the isomiR expression profile in response to infection and aging. Data analysis revealed a distinct bias towards isomiR production in the mature miRNA as opposed to the star strand. Furthermore, we noticed that only in 40% of Ae. aegypti miRNAs, the most abundant reads for each particular miRNA match the exact sequence reported in the miRbase. The isomiR expression variations between an Ae. aegypti embryonic cell line (Aag2) and whole mosquitoes demonstrated a tissue-specific pattern of isomiR production. Our results illustrated a bias for certain types of isomiRs for each miRNA. The findings presented in this study also provide evidence that isomiR production is not a random phenomenon and may be important in DENV colonisation of its vector. Examination of isomiR production rate in DENV infected and non infected mosquitoes
Project description:Vesper bats (family Vespertilionidae) experienced a rapid adaptive radiation beginning around 36 mya that resulted in the second most species rich mammalian family. Coincident with that radiation was an initial burst of DNA transposon activity that has continued into the present. Deep sequencing of small RNAs from the vespertilionid, Eptesicus fuscus, as well as dog and horse revealed that substantial numbers of novel bat miRNAs are derived from DNA transposons unique to vespertilionids. In fact, 35.9% of Eptesicus-specific miRNAs derive from DNA transposons compared to 2.2 and 5.9% of dog- and horse-specific miRNAs, respectively and targets of several miRNAs are identifiable. Timing of the DNA transposon expansion and the introduction of novel miRNAs coincides remarkably well with the rapid diversification of the family Vespertilionidae. We suggest that the rapid and repeated perturbation of regulatory networks by the introduction of many novel miRNA loci was a factor in the rapid radiation. A testicular tissue sample from dog, horse, and two different Eptesicus fuscus individuals. Four samples total.
Project description:MicroRNAs (miRNAs) are short noncoding RNA molecules regulating the expression of mRNAs. Target identification of miRNAs is computationally difficult due to the relatively low homology between miRNAs and their targets. We provide data here utilizing an experimental approach to identify targets of mmu-miR-378-3p, where mmu-miR-378-3p was overexpressed and silenced in NIH-3T3 murine fibroblasts and compared to control RNA transfected cells (RISC-free siRNA). Expression of mRNAs was profiled and differentially expressed genes following either treatment as compared to control transfected cells were identified. In this way we identified 491 significantly differentially expressed genes with more than 1.4 fold change in either comparison. One of the putative targets Akt-1 was subsequently confirmed by luciferase reporter assay. All conditions were assayed in triplicates. A commercially available mimic or inhibitor of mmu-miR-378-3p or control RNA (RISC-free siRNA) were transfected into NIH-3T3 fibroblasts using a chemical transfection system (DharmaFECT 1). 48h post transfection total RNA was isolated and mRNA-expression profiled.
Project description:Cultured NIH/3T3 cels were infeced at MOI of 10 with wild type and RDR mutant of SFV virus.. Total RNA was extracted 8 hours post-infection for gene expression analysis. Overall design: NIH/3T3 cells were cultured at 80 confluency prior to infection with SFV wild type or SFV-RDR mutant viruses. Mock infection included NIH/3T3 cells without virus infection. All experiments were carried out in triplicate.
Project description:MicroRNAs (miRNAs) play a important part in post-transcriptional gene regulation and have been shown to control many genes involved in various biological and metabolic processes. There have been extensive studies to discover miRNAs and analyze their functions in model plant species, such as Arabidopsis and rice and other plants. However, the number of miRNAs discovered in grape is relatively low and little is known about miRNAs responded gibberellin during fruit germination. In this study, a small RNA library from gibberellin grape fruits was sequenced by the high throughput sequencing technology. A total of 16,033,273 reads were obtained. 812,099 total reads representing 1726 unique sRNAs matched to known grape miRNAs. Further analysis confirmed a total of 149 conserved grapevine miRNA (Vv-miRNA) belonging to 27 Vv-miRNA families were validated, and 74 novel potential grapevine-specific miRNAs and 23 corresponding novel miRNAs* were discovered. Twenty-seven (36.5%) of the novel miRNAs exhibited differential QRT-PCR expression profiles in different development gibberellin-treated grapevine berries that could further confirm their existence in grapevine. QRT-PCR analysis on transcript abundance of 27 conserved miRNA family and the new candidate miRNAs revealed that most of them were differentially regulated by the gibberellin, with most conserved miRNA family and 26 miRNAs being specifically induced by gibberellin exposure. All novel sequences had not been earlier described in other plant species. In addition, 117 target genes for 29 novel miRNAs were successfully predicted. Our results indicated that miRNA-mediated gene expression regulation is present in gibberellin-treated grape berries. This study led to the confirmation of 101 known miRNAs and the discovery of 74 novel miRNAs in grapevine. Identification of miRNAs resulted in significant enrichment of the gibberellin of grapevine miRNAs and provided insights into miRNA regulation of genes expressed in grape berries. GSM604831 is the control for the gibberellin-treated sample. The mixture samples of young berries (one week after flowering) large berries (five week after flowering after flowering), and old berries (nine week after flowering) treated with gibberellin, respectively, were generated by deep sequencing, in triplicate, using Illumina 1G Genome Analyzer.
Project description:Small RNA high-throughput sequencing technology was used to characterize the miRNAs in F1-zebrafish after 90-day β-diketone antibiotic (DKA) exposure to F0-zebrafish at 6.25 and 12.5 mg/L. The small RNA libraries from 7-dpf F1-zebrafish were constructed. In total, 10,117,347, 9,818,830 and 12,049,949 raw reads were acquired, respectively, under the different DKA-exposure treatments (0, 6.25 mg/L and 12.5mg/L) from the three miRNAs libraries by Illumina sequencing. Low-quality reads were removed, which included 5' contaminants, those missing the 3' primer or insert tag, sequences with a poly A tail, and those shorter than 17 nt and longer than 25 nt. As a result, 8,141,146 (representing 312,735 unique sequences; control), 8,687,210 (representing 251,508 unique sequences; 6.25 mg/L), and 10,569,566 (representing 441,938 unique sequences; 12.5 mg/L) valid reads in the 17 to 25 nt size range were isolated for further analysis. The sRNAs from the three libraries were similar, and the unique sRNA reads were mainly distributed in the 20-24 nt range, among which 22 and 23 nt accounted for 41.8% and 20.0% of total unique sRNA reads, respectively. The 22-nt sRNAs were the most abundant, with the length distribution of counts of sequ-seqs and unique miRNAs displaying a normal distribution. Sample 1: Examination of small RNA in 7-dpf F1-zebrafish after 90-day DKA exposure to F0-zebrafish at 0 mg/L; Sample 2: Examination of small RNA in 7-dpf F1-zebrafish after 90-day DKA exposure to F0-zebrafish at 6.25 mg/L; Sample 3: Examination of small RNA in 7-dpf F1-zebrafish after 90-day DKA exposure to F0-zebrafish at 12.5 mg/L.
Project description:Sus scrofa (pig, or swine) is one of the most important economic animals and a close biological model for complex human diseases such as obesity and diabetes. It is therefore utterly important to decode the porcine microRNAome (miRNAome) as in the literature only a small portion of it is known. In this work, a comprehensive search for porcine microRNAs (miRNAs) by Illumina sequencing was performed in ten small RNA libraries prepared from mixtures of assorted tissues, which included those collected from fetuses to adult pigs. The millions of the sequencing reads were analyzed with reference to 77 known porcine miRNA precursors (pre-miRNAs) and 3,443 distinct pre-miRNAs of other mammals listed in miRBase 13.0, and the most updated porcine genome (Sscrofa9, April 2009) and available EST sequences. Additionally, miRNA candidates specific to pig are predicated by genome & EST match and hairpin folding. Our search found 72 out of 78 (~92%) known porcine miRNAs and miRNA*s, and 36 previously unannotated miRNA*s are also indentified. Furthermore, we discovered 397 novel miRNAs by mapping to the sequencing transcripts to other mammalian pre-miRNAs and 493 candidate miRNAs which do not map to other mammalian miRNAomes and could be pig-specific. We constructed sequence- and genome-position clusters for the total of 998 miRNA candidates originating from 862 pre-miRNAs, which represent 777 unique miRNA sequences. Together with the six known porcine miRNAs that not been observed in our study, we report herein the sequence families of 783 unique miRNAs and genomic distribution patterns of 622 pre-miRNAs. We preformed q-PCR experiments for selected 30 miRNAs in 47 tissue-specific samples and found agreement between the sequencing data and the q-PCR data. We envision that our report will serve as a valuable resource for future studies aimed at understanding miRNAome of pig Ten small RNA libraries from samples of porcine fetuses (30 days after insemination) to mixed tissues (180 days after birth) at ten developmental stages were sequenced.
Project description:To gain insight into the functions of salt-regulated miRNAs, target genes were identified through degradome sequencing approach. Three cotton RNA libraries were constructed and sequenced under normal consideration, osmotic and ionic stress. A total of 73,988,644 reads represented by 3,254,054 unique reads from the 5’ ends of uncapped and poly-adenylated RNAs were obtained. The PairFinder software was used to identify the sliced targets for the known miRNAs and novel miRNAs. These sequences were further compared with transcriptome sequencing data of G. arboretum and G. raimondii. We obtained the data from (Cotton Genome Project, http://cgp.genomics.org.cn/page/species/index.jsp).Based on degradome sequencing, 31 target genes were identified for 20 cotton miRNA families. The abundance of transcripts was plotted for each transcript. Conserved miRNAs target conserved homologous genes in diverse plant species. Three cDNA libraries were constructed using total RNA obtained from control samples (CK), the 4 h and 5 d salt-treated samples. A total of 74,351,180 sequence reads were obtained from three libraries. After removing the 3p and 5p adapter sequences and filtering out low quality ‘‘n’’ sequences, 864,720, 1,217,757 and 1,171,577 clean reads remained in the CK, 4 h and 5 d samples, respectively.
Project description:NIH-3T3 cells transduced with either EBF1-, PPARg2- or empty vector were stimulated with hormones to initiate adipocyte differentiation. RNA extraction was done using TriZol at d0, d2, d4 and d10 after stimulation. Samples were handled according to standard affymetrix protocols. Keywords = Adipogenesis, early B-cell factor 1 (EBF1), commitment, differentiation, NIH-3T3, pparg