Analysis of lncRNAs in macrophages
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA533296 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR11483070.fastq.gz | Fastqsanger.gz | |||
| SRR11483071.fastq.gz | Fastqsanger.gz | |||
| SRR11483072.fastq.gz | Fastqsanger.gz | |||
| SRR11483073.fastq.gz | Fastqsanger.gz | |||
| SRR11483074.fastq.gz | Fastqsanger.gz |
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Project description:A vast portion of the mammalian genome is transcribed as long non-coding RNAs (lncRNAs) acting in the cytoplasm with largely unknown functions. Surprisingly, lncRNAs have been shown to interact with ribosomes, encode uncharacterized proteins, or act as ribosome sponges. These functions still remain mostly undetected and understudied owing to the lack of efficient tools for genome-wide simultaneous identification of ribosome-associated lncRNAs and peptide-producing lncRNAs. Here we present AHARIBO, a method for the detection of lncRNAs either untranslated, but associated with ribosomes, or encoding small peptides. Using AHARIBO in mouse embryonic stem cells during neuronal differentiation, we isolated ribosome-protected RNA fragments, translated RNAs and corresponding de novo synthesized polypeptides. Besides identifying mRNAs under active translation and associated ribosomes, we found and distinguished lncRNAs acting as ribosome sponges or encoding micropeptides, laying the ground for a better functional understanding of hundreds lncRNAs.
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Project description:RNA-Seq analysis identifies pancreatic lncRNAs
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Project description:BLaER1 cells are human leukemia pre-B cells able to transdifferentiate into functional and non-tumorigenic macrophages. With the goal of uncovering the genes involved in the transdifferentiation process, we have designed a DECKO (Double Excision CRISPR Knockout) library to knockout lncRNAs and protein coding genes (pc-genes) overexpressed along the seven days the process lasts. We have seen that targeting pc-genes with two gRNAs synergistically enhances the efficiency of knock out, by inducing deletions and/or frameshifts that promote the expression of non-functional proteins. Thus, using the CRISPETa tool, we designed paired guide RNAs targeting either the region surrounding the Transcription Start Site of the 166 lncRNAs or the coding exons of the 874 pc candidate genes. Cas9-expressing BLaER1 cells were infected at low-multiplicity of infection with the combined library and induced transdifferentiation. Delayed and differentiated subpopulations of cells were isolated by Fluorescence-Activated Cell Sorting at 3 days and 6 days after induction, and pgRNAs were sequenced in an Illumina HiSeq2500 instrument. The sequencing reads were mapped and quantified to uncover the enriched pgRNAs found in each subpopulation. Among all genes targeted in the library, we identified twenty pc-genes and six lncRNAs as strong candidates to be involved in the process, as the pgRNAs targeting their loci were enriched in the delayed population compared to the differentiated one, either at 3 days or at 6 days after transdifferentiation induction. From these, we selected two pc-genes and two lncRNAs for deeper characterization.
2022-04-25 | E-MTAB-10445 | biostudies-arrayexpress
Project description:Recent studies have uncovered thousands of long non-coding RNAs (lncRNAs) in human pancreatic β cells. β cell lncRNAs are often cell type specific and exhibit dynamic regulation during differentiation or upon changing glucose concentrations. Although these features hint at a role of lncRNAs in β cell gene regulation and diabetes, the function of β cell lncRNAs remains largely unknown. In this study, we investigated the function of β cell-specific lncRNAs and transcription factors using transcript knockdowns and co-expression network analysis. This revealed lncRNAs that function in concert with transcription factors to regulate β cell-specific transcriptional networks. We further demonstrate that the lncRNA PLUTO affects local 3D chromatin structure and transcription of PDX1, encoding a key β cell transcription factor, and that both PLUTO and PDX1 are downregulated in islets from donors with type 2 diabetes or impaired glucose tolerance. These results implicate lncRNAs in the regulation of β cell-specific transcription factor networks.
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Project description:Small, compact genomes confer a selective advantage to viruses, yet human cytomegalovirus (HCMV) expresses the long non-coding RNAs (lncRNAs) RNA1.2, RNA2.7, RNA4.9, and RNA5.0. These lncRNAs account for majority of the viral transcriptome, but their functions remain largely unknown. Here, we showed that HCMV lncRNAs, except for RNA5.0, are required throughout the entire viral life cycle. Deletion of each lncRNA resulted in a decrease in viral progeny during lytic replication and failing to efficiently establish latent reservoirs and reactivate. Nanopore direct RNA sequencing of native lncRNA molecules revealed that each lncRNA exhibited a dynamic modification landscape, depending on the state of infection. Global analysis of the lncRNA interactome identified 32, 11, and 89 host factors that specifically bind to RNA1.2, RNA2.7, and RNA4.9, respectively. Moreover, 52 proteins commonly bound to the three lncRNAs were identified, including 11 antiviral immunity-related proteins. Our molecular analyses found that three lncRNAs are modified with N⁶-methyladenosine (m6A) and interact with m6A readers in all infection states. In-depth functional analysis revealed that m6A–mediated lncRNA stabilization as the key mechanism by which lncRNAs are maintained at high levels. Our study lays the groundwork for understanding viral lncRNA–mediated regulation of host-virus interaction throughout the HCMV life cycle.
2022-11-14 | PXD034587 | Pride
Project description:Uncovering functional lncRNAs by unconventional scRNA-seq analysis
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Project description:Background: Long non-coding RNAs (lncRNAs) are an important class of pervasive genes involved in a variety of biological functions. They are aberrantly expressed in many types of diseases. We want to study the lncRNAs profiles in preeclampsia. Preeclampsia has been observed in patients with molar pregnancy where a fetus is absent demonstrating that the placenta is sufficient to cause the condition. So we analyze the lncRNAs profiles in preeclampsia placentas. In this study, we described the lncRNAs profiles in 6 preeclampsia placentas (T) and 5 matched normal pregnancy placentas (N) tissues by microarray. Methodology/Principal Findings: With abundant and varied probes accounting 33,045 LncRNAs in our microarray, the number of lncRNAs that expressed at a certain level could be detected is 28,443. From the data we found there were 738 lncRNAs that differentially expressed (M-bM-^IM-%1.5 fold-change) among preeclampsia placentas compared with matched controls. Up to 18,063 coding transcripts could be detected in placenta samples through 30,215 coding transcripts probes. Coding-non-coding gene co-expression networks (CNC network) were constructed based on the correlation analysis between the differential expressed lncRNAs and mRNAs. According to the GO-Pathway analysis of differential expressed lncRNAs/mRNAs, we choose three lncRNAs to analyze the relationship between lncRNAs and preeclampsia. LOC391533, LOC284100, CEACAMP8 were evaluated by qPCR in 40 of preeclampsia placentas and 40 of controls. The results showed three lncRNAs were aberrantly expressed in preeclampsia placentas compared with controls. Conclusions/Significance: Our study is the first one to determine genome-wide lncRNAs expression patterns in preeclampsia placenta by microarray. The results displayed that clusters of lncRNAs were aberrantly expressed in preeclampsia placenta compared with controls, which revealed that lncRNAs differentially expressed in preeclampsia placenta may exert a partial or key role in preeclampsia development. Misregulation of LOC391533, LOC284100, CEACAMP8 might be associated with preeclampsia. Taken together, this study may provide potential targets for future treatment of preeclampsia and novel insights into preeclampsia biology. LncRNAs/mRNAs profiles in 6 preeclampsia placentas and 5 matched normal pregnancy placentas tissues by microarray using Arraystar v2.0.
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