Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

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Identification and characterization analysis of the Oriental River Prawn (Macrobrachium nipponense) microRNA response to hypoxia using a deep sequencing approach [miRNA-Seq]

ABSTRACT: MicroRNAs (miRNAs) function as regulators in a broad range of phenotypes. The Oriental River Prawn (Macrobrachium nipponense) is an important commercial species that is widely distributed in freshwater and low-salinity estuarine regions of China and other Asian countries. To date, there are no reports describing M. nipponense miRNAs. In this study, Solexa deep sequencing technology was used for high-throughput analysis of miRNAs in a small RNA library isolated from four M. nipponense tissues (gill, hepatopancreas, muscle and hemocytes). In total, 9,227,356 reads were obtained, 4,293,155 of which were related to 267 unique miRNAs, including 203 conserved and 64 prawn-specific miRNAs. Furthermore, miRNA features including length distribution and end variations were characterized. Annotation of targets revealed a broad range of biological processes and signal transduction pathways regulated by M. nipponense miRNAs. In addition, 880 co-expressed and 39 specific (25 normoxia-specific and 14 hypoxia-specific) miRNAs of four combined tissues of prawns that may be involved in the response to hypoxia were confirmed using miRNA microarray analysis. Real-time quantitative PCR (qPCR) analysis of eight miRNAs in the normoxia and hypoxia groups showed good concordance between the sequencing and qPCR data. This study provides the first large-scale identification and characterization of M. nipponense miRNAs and their potential targets, and represents a foundation for further characterization of their roles in the regulation of the diversity of hypoxia processes.

ORGANISM(S): Macrobrachium nipponense

SUBMITTER: sun shengming

PROVIDER: E-GEOD-72417 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Project description: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:Enhancing grain production of rice (Oryza sativa L.) is a top priority in ensuring food security for human being. One approach to increase yield is to delay leaf senescence and to extend the available time for photosynthesis. microRNAs (miRNAs) are key regulators for aging and cellular senescence in eukayotes. However, miRNAs and their roles in rice leaf senescence remain unexplored. Here, we report identification of miRNAs and their putative target genes by deep sequencing of six small RNA libraries, six RNA-seq libraries and two degradome libraries from the leaves of two super hybrid rice, Nei-2-You 6 (N2Y6, age-resistant rice) and Liang-You-Pei 9 (LYP9, age-sensitive rice). Totally 372 known miRNAs and 162 miRNA candidates were identified, and 1145 targets were identified. Compared with the expression of miRNAs in the leaves of LYP9, the numbers of miRNAs up-regulated and down-regulated in the leaves of N2Y6 were 47 and 30 at early stage of grain-filling, 21 and 17 at the middle stage, and 11 and 37 at the late stage, respectively. Six miRNA families, osa-miR159, osa-miR160 osa-miR164, osa-miR167, osa-miR172 and osa-miR1848, targeting the genes encoding APETALA2 (AP2), zinc finger proteins, salicylic acid-induced protein 19 (SIP19), Auxin response factors (ARF) and NAC transcription factors, respectively, were found to be involved in leaf senescence through phytohormone signaling pathways. These results provided valuable information for understanding the miRNA-mediated leaf senescence of rice, and offered an important foundation for rice breeding. [miRNA] sample 1:The flag leaves at early stage of grain-filling of N2Y6 rice; sample 2: The flag leaves at middle stage of grain-filling of N2Y6 rice;sample 3:The flag leaves at late stage of grain-filling of N2Y6 rice; sample 4:The flag leaves at early stage of grain-filling of LYP9 rice; sample 5: The flag leaves at middle stage of grain-filling of LYP9 rice;sample 6:The flag leaves at late stage of grain-filling of LYP9 rice. [DGE]: samples 7-12 [degradome (targets)]: samples 13:The flag leaves at mixed stages of grain-filling of N2Y6 rice; sample 14:The flag leaves at mixed stages of grain-filling of LYP9 rice

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Identification and characterization analysis of the Oriental River Prawn (Macrobrachium nipponense) microRNA response to hypoxia using a deep sequencing approach [miRNA-Seq]

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