Genome-wide profiling of novel and conserved <Emphasis Type="Italic">Populus</Emphasis> microRNAs involved in pathogen stress response by deep sequencing

MicroRNAs (miRNAs) are small RNAs, generally of 20–23 nt, that down-regulate target gene expression during development, differentiation, growth, and metabolism. In Populus, extensive studies of miRNAs involved in cold, heat, dehydration, salinity, and mechanical stresses have been performed; however, there are few reports profiling the miRNA expression patterns during pathogen stress. We obtained almost 38 million raw reads through Solexa sequencing of two libraries from Populus inoculated and uninoculated with canker disease pathogen. Sequence analyses identified 74 conserved miRNA sequences belonging to 37 miRNA families from 154 loci in the Populus genome and 27 novel miRNA sequences from 35 loci, including their complementary miRNA* strands. Intriguingly, the miRNA* of three conserved miRNAs were more abundant than their corresponding miRNAs. The overall expression levels of conserved miRNAs increased when subjected to pathogen stress, and expression levels of 33 miRNA sequences markedly changed. The expression trends determined by sequencing and by qRT-PCR were similar. Finally, nine target genes for three conserved miRNAs and 63 target genes for novel miRNAs were predicted using computational analysis, and their functions were annotated. Deep sequencing provides an opportunity to identify pathogen-regulated miRNAs in trees, which will help in understanding the regulatory mechanisms of plant defense responses during pathogen infection.     

Repertoire of Bovine miRNA and miRNA-Like Small Regulatory RNAs Expressed upon Viral Infection

MicroRNA (miRNA) and other types of small regulatory RNAs play a crucial role in the regulation of gene expression in eukaryotes. Several distinct classes of small regulatory RNAs have been discovered in recent years. To extend the repertoire of small RNAs characterized in mammals and to examine relationship between host miRNA expression and viral infection we used Illumina''s ultrahigh throughput sequencing approach. We sequenced three small RNA libraries prepared from cell line derived from the adult bovine kidney under normal conditions and upon infection of the cell line with Bovine herpesvirus 1. We used a bioinformatics approach to distinguish authentic mature miRNA sequences from other classes of small RNAs and short RNA fragments represented in the sequencing data. Using this approach we detected 219 out of 356 known bovine miRNAs and 115 respective miRNA* sequences. In addition we identified five new bovine orthologs of known mammalian miRNAs and discovered 268 new cow miRNAs many of which are not identifiable in other mammalian genomes and thus might be specific to the ruminant lineage. In addition we found seven new bovine mirtron candidates. We also discovered 10 small nucleolar RNA (snoRNA) loci that give rise to small RNA with possible miRNA-like function. Results presented in this study extend our knowledge of the biology and evolution of small regulatory RNAs in mammals and illuminate mechanisms of small RNA biogenesis and function. New miRNA sequences and the original sequencing data have been submitted to miRNA repository (miRBase) and NCBI GEO archive respectively. We envisage that these resources will facilitate functional annotation of the bovine genome and promote further functional and comparative genomics studies of small regulatory RNA in mammals.     

miR-29b,miR-205 and miR-221 Enhance Chemosensitivity to Gemcitabine in HuH28 Human Cholangiocarcinoma Cells

Background and Aims

Cholangiocarcinoma (CCA) is highly resistant to chemotherapy, including gemcitabine (Gem) treatment. MicroRNAs (miRNAs) are endogenous, non-coding, short RNAs that can regulate multiple genes expression. Some miRNAs play important roles in the chemosensitivity of tumors. Here, we examined the relationship between miRNA expression and the sensitivity of CCA cells to Gem.

Methods

Microarray analysis was used to determine the miRNA expression profiles of two CCA cell lines, HuH28 and HuCCT1. To determine the effect of candidate miRNAs on Gem sensitivity, expression of each candidate miRNA was modified via either transfection of a miRNA mimic or transfection of an anti-oligonucleotide. Ontology-based programs were used to identify potential target genes of candidate miRNAs that were confirmed to affect the Gem sensitivity of CCA cells.

Results

HuCCT1 cells were more sensitive to Gem than were HuH28 cells, and 18 miRNAs were differentially expressed whose ratios over ± 2log2 between HuH28 and HuCCT1. Among these 18 miRNAs, ectopic overexpression of each of three downregulated miRNAs in HuH28 (miR-29b, miR-205, miR-221) restored Gem sensitivity to HuH28. Suppression of one upregulated miRNA in HuH28, miR-125a-5p, inhibited HuH28 cell proliferation independently to Gem treatment. Selective siRNA-mediated downregulation of either of two software-predicted targets, PIK3R1 (target of miR-29b and miR-221) or MMP-2 (target of miR-29b), also conferred Gem sensitivity to HuH28.

Conclusions

miRNA expression profiling was used to identify key miRNAs that regulate Gem sensitivity in CCA cells, and software that predicts miRNA targets was used to identify promising target genes for anti-tumor therapies.     

Genome-wide microRNA expression analysis of clear cell renal cell carcinoma by next generation deep sequencing

MicroRNAs (miRNAs), non-coding RNAs regulating gene expression, are frequently aberrantly expressed in human cancers. Next-generation deep sequencing technology enables genome-wide expression profiling of known miRNAs and discovery of novel miRNAs at unprecedented quantitative and qualitative accuracy. Deep sequencing was performed on 11 fresh frozen clear cell renal cell carcinoma (ccRCC) and adjacent non-tumoral renal cortex (NRC) pairs, 11 additional frozen ccRCC tissues, and 2 ccRCC cell lines (n?=?35). The 22 ccRCCs patients belonged to 3 prognostic sub-groups, i.e. those without disease recurrence, with recurrence and with metastatic disease at diagnosis. Thirty-two consecutive samples (16 ccRCC/NRC pairs) were used for stem-loop PCR validation. Novel miRNAs were predicted using 2 distinct bioinformatic pipelines. In total, 463 known miRNAs (expression frequency 1-150,000/million) were identified. We found that 100 miRNA were significantly differentially expressed between ccRCC and NRC. Differential expression of 5 miRNAs was confirmed by stem-loop PCR in the 32 ccRCC/NRC samples. With respect to RCC subgroups, 5 miRNAs discriminated between non-recurrent versus recurrent and metastatic disease, whereas 12 uniquely distinguished non-recurrent versus metastatic disease. Blocking overexpressed miR-210 or miR-27a in cell line SKCR-7 by transfecting specific antagomirs did not result in significant changes in proliferation or apoptosis. Twenty-three previously unknown miRNAs were predicted in silico. Quantitative genome-wide miRNA profiling accurately separated ccRCC from (benign) NRC. Individual differentially expressed miRNAs may potentially serve as diagnostic or prognostic markers or future therapeutic targets in ccRCC. The biological relevance of candidate novel miRNAs is unknown at present.     

Deep sequencing of small RNAs identifies canonical and non-canonical miRNA and endogenous siRNAs in mammalian somatic tissues

MicroRNAs (miRNAs) are small RNA molecules that regulate gene expression. They are characterized by specific maturation processes defined by canonical and non-canonical biogenic pathways. Analysis of ∼0.5 billion sequences from mouse data sets derived from different tissues, developmental stages and cell types, partly characterized by either ablation or mutation of the main proteins belonging to miRNA processor complexes, reveals 66 high-confidence new genomic loci coding for miRNAs that could be processed in a canonical or non-canonical manner. A proportion of the newly discovered miRNAs comprises mirtrons, for which we define a new sub-class. Notably, some of these newly discovered miRNAs are generated from untranslated and open reading frames of coding genes, and we experimentally validate these. We also show that many annotated miRNAs do not present miRNA-like features, as they are neither processed by known processing complexes nor loaded on AGO2; this indicates that the current miRNA miRBase database list should be refined and re-defined. Accordingly, a group of them map on ribosomal RNA molecules, whereas others cannot undergo genuine miRNA biogenesis. Notably, a group of annotated miRNAs are Dgcr8 independent and DICER dependent endogenous small interfering RNAs that derive from a unique hairpin formed from a short interspersed nuclear element.     

Characterization of the mammalian miRNA turnover landscape

Steady state cellular microRNA (miRNA) levels represent the balance between miRNA biogenesis and turnover. The kinetics and sequence determinants of mammalian miRNA turnover during and after miRNA maturation are not fully understood. Through a large-scale study on mammalian miRNA turnover, we report the co-existence of multiple cellular miRNA pools with distinct turnover kinetics and biogenesis properties and reveal previously unrecognized sequence features for fast turnover miRNAs. We measured miRNA turnover rates in eight mammalian cell types with a combination of expression profiling and deep sequencing. While most miRNAs are stable, a subset of miRNAs, mostly miRNA*s, turnovers quickly, many of which display a two-step turnover kinetics. Moreover, different sequence isoforms of the same miRNA can possess vastly different turnover rates. Fast turnover miRNA isoforms are enriched for 5′ nucleotide bias against Argonaute-(AGO)-loading, but also additional 3′ and central sequence features. Modeling based on two fast turnover miRNA*s miR-222-5p and miR-125b-1-3p, we unexpectedly found that while both miRNA*s are associated with AGO, they strongly differ in HSP90 association and sensitivity to HSP90 inhibition. Our data characterize the landscape of genome-wide miRNA turnover in cultured mammalian cells and reveal differential HSP90 requirements for different miRNA*s. Our findings also implicate rules for designing stable small RNAs, such as siRNAs.