Identification of miRNAs and Their Target Genes in Peach (Prunus persica L.) Using High-Throughput Sequencing and Degradome Analysis
ABSTRACT: MicroRNAs play critical roles in various biological and metabolic processes. The function of miRNAs has been widely studied in model plants such as Arabidopsis and rice. However, the number of identified miRNAs and related miRNA targets in peach (Prunus persica) is limited. To understand further the relationship between miRNAs and their target genes during tissue development in peach, a small RNA library and three degradome libraries were constructed from three tissues for deep sequencing. We identified 117 conserved miRNAs and 186 novel miRNA candidates in peach by deep sequencing and 19 conserved miRNAs and 13 novel miRNAs were further evaluated for their expression by RT-qPCR. The number of gene targets that were identified for 26 conserved miRNA families and 38 novel miRNA candidates, were 172 and 87, respectively. Some of the identified miRNA targets were abundantly represented as conserved miRNA targets in plant. However, some of them were first identified and showed important roles in peach development. Our study provides information concerning the regulatory network of miRNAs in peach and advances our understanding of miRNA functions during tissue development. To identify more conserved and peach-speciﬁc miRNAs and their target genes and to understand further the mechanism of miRNA-regulated target genes during tissue development in peach, a small RNA library and three degradome libraries were constructed from three different tissues for deep sequencing.
Project description:microRNAs (miRNAs) are a class of small non-coding RNAs involved in the coordination and/or fine-tuning of gene expression. As such, miRNAs are thought to be critical cis-acting regulatory factors that control a wide range of physiological processes in the brain. The datasets presented here represent the miRNA transcriptome of the adult and larval Drosophila melanogaster CNS as determined by small RNA deep sequencing (RNA-Seq). They were derived from adult and larval samples explanted from the animal that contain minimal extraneous (non-neuronal) tissues. Here we present a concise summary of our profiling results as well as the original sequencing data. We identify many miRNAs that are expressed at equal levels in both tissues and several that are significantly enriched in the larval and adult brain. Some of these belong to miRNA families with conserved members in mammals. These datasets should provide a good starting point for others interested in characterizing miRNAs with putative functions in Drosophila neurons. The datasets presented here represent the miRNA transcriptome of the adult and larval Drosophila melanogaster CNS as determined by small RNA deep sequencing (RNA-Seq).
Project description:The degradation and 3′ end modification of plant microRNAs (miRNAs) play crucial roles in regulating miRNA function and stability. However, the process and mechanism of miRNA degradation and 3′ end modification has, to date, been poorly characterized. Here, we report that analysis of the two small RNA libraries constructed from two hickory floral differentiation stages by deep sequencing obtained a large number of truncated miRNAs and miRNAs with 3′ end modifications. The presence of so many truncated miRNAs suggests that plant miRNAs may be degraded through the 5′ to 3′ and 3′ to 5′ ends simultaneously, but the probability of miRNAs being truncated from the 3′ end was higher than from the 5′ end. Single- or double-nucleotide 3′ additions to miRNAs has been observed in many families. In this study, the 3′ addition of adenine to miRNA was the most common, accounting for more than 50% of all miRNA 3′ end modification in both small RNA libraries, followed by uridine addition. This suggests that the 3′ end modification of miRNAs shows a bias towards adenine and uridine in plants. Furthermore, we observed that both truncated miRNA and isomiR expressions associated with mature miRNAs. Our study provides more information regarding the degradation and 3′ end modification of miRNAs in plants. Examination of 2 different female flower buds
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:MicroRNAs (miRNAs) are involved in nearly every biological process examined to date. Mounting evidence show that some spermatozoa specific miRNAs play important roles in the regulation of spermatogenesis and germ cells development, but little is known of the exact identity and function of miRNA in sperm cells or their potential involvement in spermatogenesis and germ cells development. Here, we investigated the spermatozoa miRNA profiles using illumina deep sequencing combined with bioinformatic analysis using zebrafish as a model system. Deep sequencing of small RNAs yielded 12 million raw reads from zebrafish spermatozoa. Analysis showed that the noncoding RNA of the spermatozoa included tRNA, rRNA, snRNA, snoRNA and miRNA. By mapping to the zebrafish genome, we identified 400 novel and 204 conserved miRNAs which could be grouped into 104 families, including zebrafish specific families, such as mir-731, mir-724, mir-725, mir-729 and mir-2185. We report the first characterization of the miRNAs profiling in zebrafish spermatozoa. The obtained spermatozoa miRNAs profiling will serve as valuable resources to systematically study spermatogenesis in fish and vertebrate. Examination of small RNA populations in zebrafish spermatozoa
Project description:MicroRNA (miRNA) is a class of functional non-coding small RNA with 19-25 nucleotides in length. Amur grape (Vitis amurensis Rupr.) is an important wild fruit crop with the strongest cold resistance in the Vitis genus and is used as an excellent breeding parent for grapevine, and with growing interest in terms of wine production. To date, there is a relatively large number of grapevine miRNAs (vv-miRNAs) from cultivated grapevine varieties such as Vitis vinifera L. and hybrids of V. vinifera and V. labrusca, but there is no report on miRNAs from Vitis amurensis Rupr, a wild grapevine species. In this study, a small RNA library from Amur grapes was constructed and Solexa technology used to perform deep sequencing of the library followed by subsequent bioinformatics analysis to identify new miRNAs. In total, 126 conserved miRNA belonging to 27 miRNA families were identified, and 34 known but non-conserved miRNAs were also found. Significantly, 72 new potential Amur grapevine-specific miRNAs were discovered. The sequences of these new potential va-miRNAs were further validated through miR-RACE, accumulation of 18 new va-miRNAs in seven tissues of grapevines were also confirmed by real time RT-PCR (qRT-PCR) analysis, and expression levels of va-miRNAs in flowers and berries were basically consistent in identity to those from deep sequenced sRNAs libraries of independent corresponding tissues. We also describe the conservation and variation of va-miRNAs using miR-SNPs and miR-LDs during plant evolution based on comparison of orthologous sequences, and revealed the number and sites of miR-SNP of diverse miRNA families exhibited distinct divergence. Finally, 346 target genes for the new miRNAs were predicted and they include a number of Amur grapevine stress tolerance genes and many genes regulating anthocyanin systhesis and sugar metabolism. Deep sequencing of short RNAs from Amur grapes flowers and fruits identified 72 new potential miRNAs and 34 known but non-conserved miRNAs, indicating that specific miRNAs exist in Amur grapes. These results show that a number of regulatory miRNAs exist in Amur grapes and play an important role in Amur grape growth, development, and response to abiotic or biotic stress. High throughput sequencing was employed to identify miRNAs in Amur grapevine and try to describe their functions in Amur grapevine growth and development.
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: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.
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: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:Egg quality is an important aspect in rainbow trout farming. Post-ovulatory aging is one of the most important factors affecting egg quality. MicroRNAs (miRNAs) are the major regulators in various biological processes and their expression profiles could serve as reliable biomarkers for various pathological and physiological conditions. Egg samples from 32 females on day 1, day 7, and day 14 post-ovulation (D1PO, D7PO and D14PO), which had the fertilization rates of 91.8%, 73.4% and less than 50%, respectively, were collected and small RNAs isolated from these samples were subjected to deep sequencing using the Illumina platform. Six miRNAs were found to be differentially expressed between D1PO and D14PO eggs. GO analysis of the target genes of the 6 miRNAs that were down-regulated in D14PO eggs revealed significantly enriched GO terms that are related to stress response, cell death, DNA damage, ATP generation, signal transduction and transcription regulation. Examination of small RNA populations in eggs of different qualities caused by post-ovulatory aging.