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.
Project description:We constructed two independent small RNA libraries from leaves of mock and Cucumber mosaic virus (CMV) infected tomatoes, respectively, and sequenced with a high-throughput Illumina Solexa system. Based on sequence analysis and hairpin structure prediction, a total of 50 known miRNAs (32 families) and 568 potentially candidate miRNAs (PC-miRNAs) were firstly identified in tomato, with 12 known miRNAs and 154 PC-miRNAs supported by both the 3p and 5p strands. Comparative analysis revealed 79 miRNAs (including 15 novel tomato miRNAs) and 40 PC-miRNAs were differentially expressed between the two libraries. Among these virus responsive miRNAs, expression patters of some novel tomato miRNAs and PC-miRNAs in mock and in CMV-Fny infected tomatoes were further validated by qRT-PCR. Moreover, we revealed 563 potential targets for 66 tomato miRNAs by the recently developed degradome sequencing approach, including 124 targets for 7 new tomato miRNAs and 97 targets for 24 PC-miRNAs. Target annotation for the newly identified miRNA and PC-miRNAs indicated that they were involved in multiple biological processes, including transcriptional regulation and virus resistance. Gene ontology analysis of these target transcripts demonstrated that stress response- and photosynthesis-related genes were most affected in CMV-Fny infected tomatoes. Examination of small RNAs and their targets in mock and CMV-Fny infected tomatoes.
Project description:High-throughput small RNA sequencing were performed to identify a large number of miRNAs and their targets in mature G. biloba ovules. Our study is the first to provide useful information for uncovering the regulatory networks of miRNAs in basal gymnosperm G. biloba ovules. small RNA sequencing in ovules of G. biloba
Project description:High-throughput small RNA sequencing were performed to identify a large number of miRNAs and their targets in mature female and male G. biloba leaves for the first time. We ascertained that the regulatory networks of the miRNAs are involved in many different primary biological processes based on potential target designations. Our study is the first to provide useful information for uncovering the regulatory networks of miRNAs in basal gymnosperm G. biloba leaves. small RNA sequencing in female and male leaves of G. biloba
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
Project description:Phytochrome B (phyB), one member of phytochrome family in rice, plays important roles in regulating a range of developmental processes, and stress responses. However, little information about the mechanism involved in phyB-mediated light signaling pathway has been reported in rice. Another, it has been well-known that microRNAs (miRNAs) perform important roles in plant development and stress responses. Thus it is intriguing to explore the role of miRNAs in phyB-mediated light signaling pathway in rice. In this study, comparative high-throughput sequencing and degradome analysis were adopted to identify candidate miRNAs and their targets that participate in phyB-mediated light signaling pathway. A total of 838 known miRNAs, 663 novel miRNAs and 1,957 target genes were identified from wild-type (WT) and phyB mutant. Among them, 135 miRNAs showed differential expression, suggesting that the expressions of these miRNAs are under the control of phyB. In addition, 32 out of the 135 differentially expressed miRNAs were detected to slice 70 genes in rice genome. Analysis of these target genes showed that members of various transcription factor families constitute the largest proportion, indicating miRNAs are probably involved in phyB-mediated light signaling pathway mainly via regulating the expression of transcription factors. This study presented a comprehensive expression analysis of miRNAs and their targets that might be involved in phyB-mediated light signaling pathway for the first time. The results provide new clues for functional characterization of miRNAs in phyB-mediated light signaling pathway, which would be helpful in comprehensively uncovering molecular mechanism of phytochrome-mediated photomorphogenesis and stress responses in plant. Examination of miRNA profiles in wild type (WT) and phyB mutant at four-leaf stage by deep sequencing using Illumina Hiseq2500.
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:Background: The identification of new high sensitivity and specificity markers for HCC are essential. We aimed to identify serum microRNAs for diagnosing hepatitis B virus (HBV) –related HCC. Methods: Serum microRNA expression was investigated with four cohorts including 667 participants (261 HCC patients ,233 cirrhosi patients and 173 healthy controls), recruited between August 2010 and June 2013. First, An initial screening of miRNA expression by Illumina sequencing was performed using serum samples pooled from HCC patients and controls,respectively. Quantitative reverse-transcriptase polymerase chain reaction assay was then applied to evaluate the expression of selected microRNAs. A logistic regression model was constructed using a training cohort (n=357) and then validated using a cohort(n=241). The area under the receiver operating characteristic curve (AUC) was used to evaluate diagnostic accuracy. Results: , We identified 8 miRNAs(hsa-miR-206, hsa-miR-141-3p, hsa-miR-433-3p, hsa-miR-1228-5p, hsa-miR-199a-5p, hsa-miR-122-5p, hsa-miR-192-5p and hsa-miR-26a-5p.) formed a miRNA panel that provided a high diagnostic accuracy of HCC (AUC=0.887 and 0.879 for training and validation data set, respectively). The microRNA panel can also differentiate HCC from healthy (AUC =0.894) and cirrhosis (AUC = 0.892), respectively. Conclusions:We found a serum microRNAs panel that has considerable clinical value in diagnosing HCC. 9 serum samples pooled from 3 healthy control donors and 3 HCC patients, 3 cirrhosi patients treated at The First Affiliated Hospital of Soochow University were subjected to Illumina HiSeq 2000 deep sequencing to identify the miRNAs that were significantly differentially expressed.
Project description:In our study, small RNA library and degradome library were constructed from developing soybean seeds for deep sequencing. We identified 26 new miRNAs in soybean by bioinformatic analysis, and further confirmed their expression by stem-loop RT-PCR. The miRNA star sequences of 38 known miRNAs and 8 new miRNAs were also discovered, providing additional evidence for the existence of miRNAs. Through degradome sequencing, 145 and 25 genes were identified as targets of annotated miRNAs and new miRNAs, respectively. Many identified miRNA targets may perform functions in soybean seed development by GO analysis. Additionally, soybean homolog of Arabidopsis SUPPRESSOR OF GENE SLIENCING 3(AtSGS3) was detected as target of the new identified miRNA Soy_25, suggesting presence of feedback control of miRNA biogenesis sample 1: Examination of small RNA in soybean seed sample 2: identification of miRNA targets in soybean seed
Project description:To identify miRNAs involved in senescence of strawberry fruit, two independent small RNA libraries and one degradome library from strawberry fruits stored at 20 °C for 0 and 24 h were constructed. A total of 18,759,735 and 20,293,492 mappable small RNA sequences were generated in the two small RNA libraries, respectively, and 88 known and 1224 new candidate miRNAs were obtained. Among them, 94 miRNAs were up-regulated and 64 were down-regulated in the senescence of strawberry fruit. Through degradome sequencing, 103 targets cleaved by 19 known miRNAs families and 55 new candidate miRNAs were identified. 14 targets, including NAC transcription factor, Auxin response factors (ARF) and Myb transcription factors, cleaved by 6 known miRNA families and 6 predicted candidates, were found to be involved in regulating fruit senescence. sample 1: Examination of small RNA in strawberry fruits stored at 20 °C for 0; sample 2: Examination of small RNA in strawberry fruits stored at 20 °C for 24 h
Project description:Purpose: To identify Fusarium wilt and salt-responsive miRNAs at genome wide level in Chickpea. Results: A total of 12,135,571 unique reads were obtained. In addition to 122 conserved miRNAs belonging to 25 different families, 59 novel miRNAs along with their star sequences were identified. Four legume specific miRNAs, miR5213, miR5232, miR2111 and miR2118 were found in all the libraries. The Poly (A) tailing assay based qRT-PCR was used to validate eleven conserved and five novel miRNAs. miR530 was highly up regulated in response to fungal infection and targets zinc knuckle and microtubule-associated proteins. Many miRNAs responded in a similar fashion under both biotic and abiotic stresses indicating a cross talk between the pathways involved in regulating these stresses. The potential target genes for the conserved and novel miRNAs were predicted based on sequence homology. miR166 targets a HD-ZIPIII transcription factor and was validated by 5’ RLM-RACE. Conclusions: The present study has led to identification of several conserved and novel miRNAs in chickpea associated with gene regulation in reference to wilt and salt stress conditions. This study will help in better understanding of how chickpea functions in response to stresses. Total three small RNA libraries from chickpea were prepared and sequenced independently [Control (C), Wilt stress (WS), Salt stress (SS)] on Illumina GAIIx.