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20 pages, 3352 KiB

Open AccessArticle

Murine Long Noncoding RNA Morrbid Contributes in the Regulation of NRAS Splicing in Hepatocytes In Vitro

by Anna Fefilova, Pavel Melnikov, Tatiana Prikazchikova, Tatiana Abakumova, Ilya Kurochkin, Pavel V. Mazin, Rustam Ziganshin, Olga Sergeeva and Timofei S. Zatsepin

Int. J. Mol. Sci. 2020, 21(16), 5605; https://doi.org/10.3390/ijms21165605 - 5 Aug 2020

Cited by 7 | Viewed by 3399

Abstract

The coupling of alternative splicing with the nonsense-mediated decay (NMD) pathway maintains quality control of the transcriptome in eukaryotes by eliminating transcripts with premature termination codons (PTC) and fine-tunes gene expression. Long noncoding RNA (lncRNA) can regulate multiple cellular processes, including alternative splicing. [...] Read more.

The coupling of alternative splicing with the nonsense-mediated decay (NMD) pathway maintains quality control of the transcriptome in eukaryotes by eliminating transcripts with premature termination codons (PTC) and fine-tunes gene expression. Long noncoding RNA (lncRNA) can regulate multiple cellular processes, including alternative splicing. Previously, murine Morrbid (myeloid RNA repressor of Bcl2l11 induced death) lncRNA was described as a locus-specific controller of the lifespan of short-living myeloid cells via transcription regulation of the apoptosis-related Bcl2l11 protein. Here, we report that murine Morrbid lncRNA in hepatocytes participates in the regulation of proto-oncogene NRAS (neuroblastoma RAS viral oncogene homolog) splicing, including the formation of the isoform with PTC. We observed a significant increase of the NRAS isoform with PTC in hepatocytes with depleted Morrbid lncRNA. We demonstrated that the NRAS isoform with PTC is degraded via the NMD pathway. This transcript is presented almost only in the nucleus and has a half-life ~four times lower than other NRAS transcripts. Additionally, in UPF1 knockdown hepatocytes (the key NMD factor), we observed a significant increase of the NRAS isoform with PTC. By a modified capture hybridization (CHART) analysis of the protein targets, we uncovered interactions of Morrbid lncRNA with the SFPQ (splicing factor proline and glutamine rich)-NONO (non-POU domain-containing octamer-binding protein) splicing complex. Finally, we propose the regulation mechanism of NRAS splicing in murine hepatocytes by alternative splicing coupled with the NMD pathway with the input of Morrbid lncRNA. Full article

(This article belongs to the Special Issue RNA Regulatory Networks)

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Figure 1

Figure 1
Characterization of Morrbid long noncoding RNA (lncRNA) expression, cellular localization and knockdown phenotype. (A) Comparison of Morrbid expression levels in AML12 normal murine hepatocytes and the Hepa1-6 hepatoma cell line with RT-qPCR. (B) Fluorescence in situ hybridization analysis (FISH) of Morrbid localization in AML12 cells (DNA was stained with Dapi and Morrbid was stained with a Cy5-labeled probe). (C) RT-qPCR analysis of Morrbid expression in the nuclear and cytoplasmic fractions extracted from AML12 cells. (D) Viability assay of Hepa1-6 and AML12 cells depleted in Morrbid, on the 1, 1.5, 2, 3 and 4 days of knockdown, normalized to control the luciferase antisense oligonucleotides (LUC ASO) treatment and viability at day 1 after the initial transfection. (E) Wound-healing assay of Morrbid knockdown (KD) and LUC control KD in AML12 and Hepa1-6 cells. The wound was introduced just after the initial transfection, and data were normalized to the wound area at the first timepoint. Results show mean ± SD. n.s.—not significant. * p < 0.05, ** p < 0.01 and *** p < 0.001. Full article ">Figure 2
Morrbid lncRNA depletion leads to the enhanced incorporation of the NRAS premature termination codons (PTC) exon in murine hepatocytes. (A) RNA coverage of the zoomed region of the NRAS transcript in Morrbid and LUC control knockdowns. The solid and dashed arced lines represent the RNA coverage of the splice junctions. (B) RT-qPCR analysis of the NRAS isoform expression after Morrbid KD and control LUC KD using primers laying on the junction between the PTC exon and neighboring exons (PTC junction) and spanning across the junction to the downstream neighboring exon (PTC down). (C) Image of amplicon separation by agarose gel electrophoresis. Amplicons were obtained with primers spanning across the alternative NRAS exon to amplify the PTC and no PTC NRAS transcripts. (D) RT-qPCR analysis of the NRAS pre-mRNA level in the control LUC and Morrbid KD cells using primers that amplify the fragment with exon1 and intron. NMD: nonsense-mediated decay. Results show mean ± SD. n.s.—not significant. * p < 0.05, ** p < 0.01 and *** p < 0.001. Full article ">Figure 3
The SFPQ-NONO heterodimer interacts with Morrbid and influences NRAS PTC exon splicing. (A) Summary table of the Capture Hybridization Analysis of RNA Targets (CHART) and RNA pulldown assay results. (B) Fold enrichment of Morrbid lncRNA in the RNA immunoprecipitation assay (RIP) performed with SFPQ and NONO antibodies, as well as DDX3 and IgG antibodies as controls, quantified with RT-qPCR. (C) Relative expression of NRAS isoforms after 6 days of inhibition of the SFPQ protein (RT-qPCR analysis). siRNA: small interfering RNA. Results show mean ± SD. n.s.—not significant. * p < 0.05, ** p < 0.01. Full article ">Figure 4
NRAS PTC transcript is degraded in the cytosol via the NMD pathway. (A) RT-qPCR analysis of NRAS PTC, no PTC transcripts and NRAS total in the nuclear and cytoplasmic fractions extracted from AML12 cells. (B) Estimation of the NRAS transcripts degradation rate by an actinomycin D assay. (C) RT-qPCR analysis of gene expressions after 6 days of knockdown of the UPF1 protein. Results show mean ± SD. n.s.—not significant. ** p < 0.01 and *** p < 0.001. mRNA: messenger RNA. Full article ">Figure 5
Proposed mechanism of the Morrbid lncRNA contribution in the regulation of NRAS mRNA alternative splicing. Full article ">

20 pages, 3863 KiB

Open AccessArticle

mRNA with Mammalian Codon Bias Accumulates in Yeast Mutants with Constitutive Stress Granules

by Natalia V. Kozlova, Chantal Pichon and A. Rachid Rahmouni

Int. J. Mol. Sci. 2020, 21(4), 1234; https://doi.org/10.3390/ijms21041234 - 12 Feb 2020

Cited by 3 | Viewed by 3510

Abstract

Stress granules and P bodies are cytoplasmic structures assembled in response to various stress factors and represent sites of temporary storage or decay of mRNAs. Depending on the source of stress, the formation of these structures may be driven by distinct mechanisms, but [...] Read more.

Stress granules and P bodies are cytoplasmic structures assembled in response to various stress factors and represent sites of temporary storage or decay of mRNAs. Depending on the source of stress, the formation of these structures may be driven by distinct mechanisms, but several stresses have been shown to stabilize mRNAs via inhibition of deadenylation. A recent study identified yeast gene deletion mutants with constitutive stress granules and elevated P bodies; however, the mechanisms which trigger its formation remain poorly understood. Here, we investigate the possibility of accumulating mRNA with mammalian codon bias, which we termed the model RNA, in these mutants. We found that the model RNA accumulates in dcp2 and xrn1 mutants and in four mutants with constitutive stress granules overlapping with P bodies. However, in eight other mutants with constitutive stress granules, the model RNA is downregulated, or its steady state levels vary. We further suggest that the accumulation of the model RNA is linked to its protection from the main mRNA surveillance path. However, there is no obvious targeting of the model RNA to stress granules or P bodies. Thus, accumulation of the model RNA and formation of constitutive stress granules occur independently and only some paths inducing formation of constitutive stress granules will stabilize mRNA as well. Full article

(This article belongs to the Special Issue RNA Regulatory Networks)

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Figure 1

Figure 1
The steady-state level of the model RNA is unaffected by its suboptimal codon bias. (A): comparison of codon optimality for expression in yeast between EGFP and yEGFP. Codon stabilization coefficient (CSC) was attributed to each amino acid codon according to [<a href="#B25-ijms-21-01234" class="html-bibr">25</a>], and color-coding was added, as indicated in the lower panel. For image convenience, the open reading frame (ORF) of EGFP and yEGFP was divided into four regions depicted from left to right and separated by vertical white line. (B): EGFP fluorescence (EGFP) was detected by live-cell imaging in strains expressing the model RNA (mKozak EGFP), the EGFP RNA flanked with yeast optimized Kozak sequence (yKozak EGFP), and the yEGFP RNA flanked with yeast optimized Kozak sequence (yKozak yEGFP). All the constructs above were integrated into GPD locus and expressed under control of GPD promoter. NTF indicates non-transformed cells (negative control for unspecific signal). Scale bar is 20 µm. (C): Northern blot analysis on total RNA isolated from the strains used for live-cell imaging in (B). The probe for Northern detection was located downstream of EGFP/yEGFP ORF in the region identical for all three RNAs. SCR1, 25S and 18S RNAs were used as endogenous controls. SCR1 was detected by Northern blot, and ribosomal RNA was detected by ethidium bromide staining. Full article ">Figure 2
The model RNA accumulates in mutants with constitutive stress granules. Northern blot analysis was performed on total RNA from wild-type strain (W.T., BY4741) and mutants (indicated above each line) transformed with episomal plasmid expressing the model RNA in Tet-Off system. The model RNA was detected with the probe to EGFP. Ribosomal RNA (25S and 18S) was visualized by ethidium bromide staining and served as endogenous control. RNA from uninduced cells (dox) served as control for unspecific hybridization. The wide white vertical line indicates that the samples were run on two different gels. The narrow white vertical line indicates that the samples were run on the same gel, but some lines between left and right part were removed. Full-length gel and blot for the cropped images are shown in <a href="#app1-ijms-21-01234" class="html-app">Supplementary File 1</a>: <a href="#app1-ijms-21-01234" class="html-app">Figure S3A</a>. Full article ">Figure 3
Accumulation of the model RNA in rtc2Δ and cho2Δ mutants is linked to compromised 5′ to 3′ degradation path. (A): The model RNA was expressed in wild-type (BY4741) and mutant strains (indicated on the left), as in <a href="#ijms-21-01234-f002" class="html-fig">Figure 2</a>. Expression of the model RNA and Pab1 was then simultaneously detected by fluorescent in situ hybridization (FISH) and immunofluorescence, respectively (FISH-IF). Cells were examined by epifluorescence microscopy and manually counted. Scale bar is 5 µm. (B) and (C): Combining of dcp2-7, rtc2Δ, and cho2Δ mutations in one strain does not lead to further accumulation of the model RNA. The model RNA was expressed as above in single, double, and triple mutants (indicated above each line) and its steady-state levels were detected by Northern blot (B), quantified using phosphoimager and expressed as fold increase relative to the levels in dcp2-7 mutant (C). Ribosomal RNA (25S and 18S) was visualized by ethidium bromide staining and served as endogenous control. Quantitation in (C) represents data from three experiments. Full article ">Figure 4
The model RNA is located to cytoplasmic granules distinct from stress granules. (A) and (B): Expression of the model RNA was visualized by FISH in wild-type (BY4741) (A) and in PAB1-GFP (B) strains and showed a similar pattern of cytoplasmic granules formed in approximately 50% of cells. (C): Live-cell imaging of PAB1-GFP strain expressing the model RNA did not detect formation of stress granules. In all panels, the model RNA was expressed as in <a href="#ijms-21-01234-f002" class="html-fig">Figure 2</a>, and uninduced cells were used to control for unspecific FISH signal (A) and (B) and for appearance of stress granules unrelated to the expression of the model RNA (C). Scale bar is 5 µm. Full article ">Figure 5
Expression of the model RNA does not induce formation of P bodies. (A): Live-cell imaging of nontransformed EDC3-GFP strain. Generally, under normal conditions, between one and three small P bodies per cell were detected. (B) and (C): The model RNA was expressed in EDC3-GFP strain as in <a href="#ijms-21-01234-f002" class="html-fig">Figure 2</a>. Uninduced cells were used to control for P bodies unrelated to the expression of the model RNA and for unspecific FISH signal. (B): Live-cell imaging of EDC3-GFP strain. Expression of the model RNA leads to the increase in neither the size nor the number of P bodies per cell. (C): FISH-IF of the model RNA and Edc3-GFP showed that the granules of the model RNA are distinct from P bodies, although some of them may be located in the vicinity of each other. In (A) and (B), overlay of Edc3-GFP signal and bright field is shown. In (C), “FISH” corresponds to FISH detection of the model RNA, “Edc3-GFP/BF” corresponds to overlay of bright field and Edc3-GFP signal, and “merge” corresponds to overlay of bright field, FISH, and Edc3-GFP labeling. Scale bar is 5 µm. Full article ">Figure 6
Accumulation of the model RNA in the mutants is not linked to its targeting to stress granules. FISH-IF of the model RNA (expressed as in <a href="#ijms-21-01234-f002" class="html-fig">Figure 2</a>) and stress granule markers Pab1 (left panel) and Pub1 (right panel) in wild-type (BY4741, W.T.) and mutant strains as indicated on the left. Scale bar is 5 µm. Full article ">Figure 7
Endoplasmic reticulum of the mutants accumulating the model RNA shows deviations from the wild type. Live-cell imaging of wild-type (BY4741, W.T.) and mutant strains (indicated on the left) transformed with the plasmid expressing RFP-ER. Scale bar is 5 µm. Full article ">

18 pages, 4215 KiB

Open AccessArticle

Characterization of a G-Quadruplex Structure in Pre-miRNA-1229 and in Its Alzheimer’s Disease-Associated Variant rs2291418: Implications for miRNA-1229 Maturation

by Joshua A. Imperatore, McKenna L. Then, Keefe B. McDougal and Mihaela Rita Mihailescu

Int. J. Mol. Sci. 2020, 21(3), 767; https://doi.org/10.3390/ijms21030767 - 24 Jan 2020

Cited by 31 | Viewed by 4965

Abstract

Alzheimer’s disease (AD), the most common age-related neurodegenerative disease, is associated with various forms of cognitive and functional impairment that worsen with disease progression. AD is typically characterized as a protein misfolding disease, in which abnormal plaques form due to accumulation of tau [...] Read more.

Alzheimer’s disease (AD), the most common age-related neurodegenerative disease, is associated with various forms of cognitive and functional impairment that worsen with disease progression. AD is typically characterized as a protein misfolding disease, in which abnormal plaques form due to accumulation of tau and β-amyloid (Aβ) proteins. An assortment of proteins is responsible for the processing and trafficking of Aβ, including sortilin-related receptor 1 (SORL1). Recently, a genome-wide association study of microRNA-related variants found that a single nucleotide polymorphism (SNP) rs2291418 within premature microRNA-1229 (pre-miRNA-1229) is significantly associated with AD. Moreover, the levels of the mature miRNA-1229-3p, which has been shown to regulate the SORL1 translation, are increased in the rs2291418 pre-miRNA-1229 variant. In this study we used various biophysical techniques to show that pre-miRNA-1229 forms a G-quadruplex secondary structure that coexists in equilibrium with the canonical hairpin structure, potentially controlling the production of the mature miR-1229-3p, and furthermore, that the AD-associated SNP rs2291418 pre-miR-1229 changes the equilibrium between these structures. Thus, the G-quadruplex structure we identified within pre-miRNA-1229 could potentially act as a novel therapeutic target in AD. Full article

(This article belongs to the Special Issue RNA Regulatory Networks)

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Graphical abstract

Graphical abstract
Full article ">Figure 1
Predicted secondary structures of pre-miRNA-1229 sequences. RNA Structure prediction software (<a href="https://rna.urmc.rochester.edu/RNAstructureWeb/" target="_blank">https://rna.urmc.rochester.edu/RNAstructureWeb/</a>) was used to determine the most likely hairpin structures for full-length pre-miRNA-1229_WT (A) and pre-miRNA-1229_SNP (B). G-tracts are numbered and highlighted by red boxes. The location of the SNP is indicated with an arrow in both structures. The predicted GQ structure of full-length pre-miRNA-1229 was determined using the online QGRS Mapper software (C). Nucleotides involved in GQ formation are colored according to the legend below and the location of SNP is indicated with an arrow. Full article ">Figure 2
Biophysical characterization of the truncated pre-miRNA-1229_WT GQ sequence. 1H NMR spectra (A) and CD spectra (B) at various KCl concentrations in 10 mM cacodylic acid, pH 6.5, demonstrating the formation of a GQ structure. The UV thermal denaturation hypochromic transition (C) at 10 µM RNA in 150 mM KCl was fit using Equation (1) (Materials and Methods), to determine a Tm of ~80 °C. The Tm values plotted as a function of the RNA concentration (D) revealed that an intramolecular GQ structure is formed. Nondenaturing gel electrophoresis (E) visualized by UV shadow (left panel) and stained with the GQ-specific N-methyl mesoporphyrin IX (NMM) dye (right panel), revealing the formation of a GQ structure at all KCl concentrations. Full article ">Figure 3
Biophysical characterization of the full-length pre-miRNA-1229_WT FL sequence. 1H NMR spectra (A) and CD spectra (B) at various KCl concentrations in 10 mM cacodylic acid, pH 6.5, reveal an equilibrium between hairpin and GQ structures after annealing the RNA in 150 mM KCl. The UV thermal denaturation hypochromic transition (C) at 10 µM RNA in 100 mM KCl was fit using Equation (1) (Materials and Methods), to determine a Tm of ~85 °C. Nondenaturing gel electrophoresis (D) visualized by UV shadow (left panel) and stained with the GQ-specific NMM dye, revealing the formation of multiple GQ structures. Full article ">Figure 4
Time-dependent 1H NMR spectra of full-length pre-miR-1229_WT FL in the presence of 150 mM KCl and 1 mM MgCl2 (A). After approximately 140 h, the GQ structure is the preferred structure, as indicated by the increased intensity of the imino proton resonances corresponding to Hoogsteen base pairs in the GQ structure compared to those assigned to Watson–Crick imino proton resonances. An overlay of the spectra is shown in (B). Full article ">Figure 5
Biophysical characterization of the truncated pre-miR-1229_SNP GQ sequence. 1H NMR spectra (A) and CD spectra (B) at various KCl concentrations in 10 mM cacodylic acid, pH 6.5, demonstrating the formation of a GQ structure. The UV thermal denaturation hypochromic transition (C) at 10 µM RNA in 150 mM KCl was fit using Equation (1) (Materials and Methods), to determine a Tm of ~78 °C. The Tm values plotted as a function of the RNA concentration (D) revealed that an intramolecular GQ structure is formed. Nondenaturing gel electrophoresis (E) visualized by UV shadow (left panel) and stained with the GQ-specific NMM dye (right panel), revealing the formation of a GQ structure at all KCl concentrations. Full article ">Figure 6
Biophysical characterization of the full-length pre-miR-1229_SNP FL sequence. 1H NMR spectra (A) and CD spectra (B) at various KCl concentrations in 10 mM cacodylic acid, pH 6.5 reveal an equilibrium between hairpin and GQ structures after annealing the RNA in 150 mM KCl. UV thermal denaturation hypochromic transition (C) at 10 µM RNA in 100 mM KCl was fit using Equation (1) (Materials and Methods), to determine a Tm of ~86 °C. Nondenaturing gel electrophoresis (D) visualized by UV shadow (left panel) and stained with the GQ-specific NMM dye (right panel), revealing the formation of multiple GQ structures as well as a hairpin structure. Full article ">Figure 7
Time-dependent NMR spectra of full-length pre-miR-1229_SNP FL in the presence of 150 mM KCl and 1 mM MgCl2 (A). After 138 h, the hairpin structure is the preferred structure, as noted by the increased intensity of the Watson–Crick imino proton resonances compared to the decreased intensity of the imino proton resonances assigned to Hoogsteen base pairs in the GQ structure. An overlay of the spectra is shown in (B). Full article ">

15 pages, 22343 KiB

Open AccessArticle

Integrative Analyses of mRNA Expression Profile Reveal the Involvement of IGF2BP1 in Chicken Adipogenesis

by Jiahui Chen, Xueyi Ren, Limin Li, Shiyi Lu, Tian Chen, Liangtian Tan, Manqing Liu, Qingbin Luo, Shaodong Liang, Qinghua Nie, Xiquan Zhang and Wen Luo

Int. J. Mol. Sci. 2019, 20(12), 2923; https://doi.org/10.3390/ijms20122923 - 14 Jun 2019

Cited by 36 | Viewed by 4011

Abstract

Excessive abdominal fat deposition is an issue with general concern in broiler production, especially for Chinese native chicken breeds. A high-fat diet (HFD) can induce body weight gained and excessive fat deposition, and genes and pathways participate in fat metabolism and adipogenesis would [...] Read more.

Excessive abdominal fat deposition is an issue with general concern in broiler production, especially for Chinese native chicken breeds. A high-fat diet (HFD) can induce body weight gained and excessive fat deposition, and genes and pathways participate in fat metabolism and adipogenesis would be influenced by HFD. In order to reveal the main genes and pathways involved in chicken abdominal fat deposition, we used HFD and normal diet (ND) to feed a Chinese native chicken breed, respectively. Results showed that HFD can increase abdominal fat deposition and induce adipocyte hypertrophy. Additionally, we used RNA-sequencing to identify the differentially expressed genes (DEGs) between HFD and ND chickens in liver and abdominal fat. By analyzed these DEGs, we found that the many DEGs were enriched in fat metabolism related pathways, such as peroxisome proliferator-activated receptor (PPAR) signaling, fat digestion and absorption, extracellular matrix (ECM)-receptor interaction, and steroid hormone biosynthesis. Notably, the expression of insulin-like growth factor II mRNA binding protein 1 (IGF2BP1), which is a binding protein of IGF2 mRNA, was found to be induced in liver and abdominal fat by HFD. Ectopic expression of IGF2BP1 in chicken liver-related cell line Leghorn strain M chicken hepatoma (LMH) cell revealed that IGF2BP1 can regulate the expression of genes associated with fatty acid metabolism. In chicken preadipocytes (ICP cell line), we found that IGF2BP1 can promote adipocyte proliferation and differentiation, and the lipid droplet content would be increased by overexpression of IGF2BP1. Taken together, this study provides new insights into understanding the genes and pathways involved in abdominal fat deposition of Chinese native broiler, and IGF2BP1 is an important candidate gene for the study of fat metabolism and adipogenesis in chicken. Full article

(This article belongs to the Special Issue RNA Regulatory Networks)

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Figure 1

Figure 1
High-fat diet promotes chicken abdominal fat deposition and induces adipocyte hypertrophy. (a) Body weight of the broilers fed with high-fat diet (HFD) and normal diet (ND). (b) Abdominal fat weight of the broilers fed with HFD and ND. (c) Abdominal fat rate of the broilers fed with HFD and ND. (d) Micrograph of abdominal fat cross-section from HFD (left) and ND (right) chickens. Bar, 200 µm. (e) Area (left) and diameter (right) of the adipocyte from HFD and ND chicken abdominal fat. * p < 0.05; ** p < 0.01. Full article ">Figure 2
Differentially expressed genes between HFD and ND chickens. (a) Scatter plot of differentially expressed genes (DEGs) between HFD and ND chickens in abdominal fat. (b) Scatter plot of DEGs between HFD and ND chickens in liver. (c) Enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway of DEGs between HFD and ND chickens in abdominal fat. (d) Enriched KEGG pathway of DEGs between HFD and ND chickens in liver. (e) Gene Ontology (GO) enrichment of DEGs between HFD and ND chickens in abdominal fat. (f) GO enrichment of DEGs between HFD and ND chickens in liver. Full article ">Figure 3
The expression of IGF2BP1 can be significantly induced in a high-fat condition. (a) Specific and common DEGs in liver and abdominal fat. The three groups of the Venn diagram represent the liver specific DEGs between HFD and ND chicken (blue), common DEGs between HFD and ND chicken in liver and abdominal fat (deep red), and abdominal fat specific DEGs between HFD and ND chicken (light red), respectively. (b) RNA-sequencing revealed that HFD can significantly induce IGF2BP1 expression in liver and abdominal fat of chicken. (c) qPCR validation of six DEGs obtained from RNA-seq in liver. (d) qPCR validation of 6 DEGs obtained from RNA-seq in abdominal fat. (e). High-fat medium can significantly promote IGF2BP1 expression in chicken LMH cell. (f) High-fat medium can significantly promote IGF2BP1 expression in chicken ICP cell. The data are mean ± S.E.M. with four samples (<a href="#ijms-20-02923-f003" class="html-fig">Figure 3</a>b has three samples). Independent sample t-test was used to analyze the statistical differences between groups. * p < 0.05; ** p < 0.01. Full article ">Figure 4
IGF2BP1 promotes the expression of genes involved in fatty acid metabolism in LMH cell. (a) The mRNA expression of IGF2BP1 after 48 h transfection of si-IGF2BP1 in LMH cell. (b) The protein expression of IGF2BP1 after 48 h transfection of si-IGF2BP1 in LMH cell. (c) The mRNA expression of IGF2BP1 after 48 h transfection of IGF2BP1 overexpression vector in LMH cell. (d) The protein expression of IGF2BP1 after 48 h transfection of IGF2BP1 overexpression vector in LMH cell. (e) The expression of genes related to fatter acid metabolism after transfection of si-IGF2BP1 in LMH cell. (f) The expression of genes related to fatter acid metabolism after transfection of pcDNA3.1-IGF2BP1 in LMH cell. The data are mean ± S.E.M. with four samples (n = 4/treatment group). Independent sample t test was used to analyze the statistical differences between groups. * p < 0.05; ** p < 0.01. Full article ">Figure 5
IGF2BP1 promotes chicken adipocyte proliferation. (a) The mRNA and protein expression of IGF2BP1 after 48 h transfection of si-IGF2BP1 in an ICP cell. (b) The mRNA and protein expression of IGF2BP1 after 48 h transfection of IGF2BP1 overexpression vector in an ICP cell. (c). The expression of cell cycle related genes after transfection of si-IGF2BP1 in an ICP cell. (d) The expression of cell cycle related genes after overexpression of IGF2BP1 in an ICP cell. (e) IGF2BP1 inhibition induced cell cycle arrest in an ICP cell. (f) IGF2BP1 overexpression promote cell cycle progress in an ICP cell. (g) IGF2BP1 inhibition repressed cell proliferation in an ICP cell. (h) IGF2BP1 overexpression promote cell proliferation in an ICP cell. The data are mean ± S.E.M. with at least 3 samples (n ≥ 3/treatment group). Independent sample t test was used to analyze the statistical differences between groups. * p < 0.05; ** p < 0.01. Full article ">Figure 6
IGF2BP1 promotes chicken adipocyte differentiation and increases lipid droplet accumulation. (a) The expression of IGF2BP1 during ICP cell differentiation. (b) The expression of genes related to adipocyte differentiation and fatty acid metabolism after IGF2BP1 overexpression in an ICP cell. (c). The expression of genes related to adipocyte differentiation and fatty acid metabolism after inhibition of IGF2BP1 expression in an ICP cell. (d). Representative images of oil red O staining (red) after overexpression of IGF2BP1 in an ICP cell; scale bar: 100 μm. (e). Lipid droplet content by oil red O staining and extraction method of cells transfected with IGF2BP1 overexpression vector. (f). Representative images of oil red O staining (red) after inhibition of IGF2BP1 in an ICP cell; scale bar: 100 μm. (g). Lipid droplet content by oil red O staining and extraction method of cells transfected with si-IGF2BP1 and si-NC. The data are mean ± S.E.M. with four samples (n = 4/treatment group). Independent sample t test was used to analyze the statistical differences between groups. * p < 0.05; ** p < 0.01. Full article ">

12 pages, 3577 KiB

Open AccessArticle

The Possible Role of Complete Loss of Myostatin in Limiting Excessive Proliferation of Muscle Cells (C2C12) via Activation of MicroRNAs

by Peixuan Huang, Daxin Pang, Kankan Wang, Aishi Xu, Chaogang Yao, Mengjing Li, Wenni You, Qiushuang Wang and Hao Yu

Int. J. Mol. Sci. 2019, 20(3), 643; https://doi.org/10.3390/ijms20030643 - 2 Feb 2019

Cited by 9 | Viewed by 4141

Abstract

Myostatin (MSTN) is a member of the TGF-β superfamily that negatively regulates skeletal muscle growth and differentiation. However, the mechanism by which complete MSTN deletion limits excessive proliferation of muscle cells remains unclear. In this study, we knocked out MSTN in mouse myoblast [...] Read more.

Myostatin (MSTN) is a member of the TGF-β superfamily that negatively regulates skeletal muscle growth and differentiation. However, the mechanism by which complete MSTN deletion limits excessive proliferation of muscle cells remains unclear. In this study, we knocked out MSTN in mouse myoblast lines using a Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR/Cas9) system and sequenced the mRNA and miRNA transcriptomes. The results show that complete loss of MSTN upregulates seven miRNAs targeting an interaction network composed of 28 downregulated genes, including TGFB1, FOS and RB1. These genes are closely associated with tumorigenesis and cell proliferation. Our study suggests that complete loss of MSTN may limit excessive cell proliferation via activation of miRNAs. These data will contribute to the treatment of rhabdomyosarcoma (RMS). Full article

(This article belongs to the Special Issue RNA Regulatory Networks)

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Figure 1

Figure 1
Preparation and validation of knockout (KO) cells. (A) Schematic of the recombinant plasmid. The plasmid was designed with the enzyme restriction sites after the U6 promoter. (B) Fluorescence microscopy images of cells. From left to right: mock group, scramble group and myostatin (MSTN) sgRNA group (scale bar = 1000 μm). (C) Electrophoretogram of the results of cell validation by PCR. (D) Wild-type (WT) and C11 sequences. C11 cells have a deleted section due to the sgRNA. (E) Identification of MSTN protein levels in WT and C11 cells by Western blot analysis. There was no MSTN protein expression in C11 cells. Full article ">Figure 2
Differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs) in KO cell lines. (A) Heatmap hierarchical clustering revealed the presence of DEGs and DEMs in the MSTN-KO groups compared with the control groups. (B) Expression of DEGs displayed by heatmap hierarchical clustering and the expression levels of MSTN in the control groups and the rhabdo groups. *** p < 0.001. Full article ">Figure 3
Identification of miRNAs involved in mRNA regulation. (A) Thirty-five upregulated miRNAs were identified, 11 of which led to the downregulation of target DEGs. (B) Fourteen downregulated miRNAs were identified, only one of which led to the upregulation of target DEGs. Full article ">Figure 4
Functional enrichment analysis of DEGs and DEMs. (A) Significantly enriched pathways for the upregulated DEGs were ranked by p-values. (B) Pathways in which the downregulated DEGs were significantly involved. (C,D) Pathways in which the upregulated or downregulated DEMs were significantly enriched. Full article ">Figure 5
Expression analysis of DEGs between the MSTN-KO and rhabdo groups. (A) Overlapping DEGs between the MSTN-KO and rhabdo groups. (B) Apoptosis-related gene expression differences between the KO and rhabdo groups. All data are shown as the mean ± SEM. Two-tailed Mann–Whitney U tests were used for pairwise comparisons between groups. ** p < 0.01, *** p < 0.001. Full article ">Figure 6
miRNA–mRNA network in the MSTN-KO group. (A) Interactive network of upregulated miRNAs and downregulated mRNAs in the MSTN-KO group. (B) KEGG pathway enrichment of DEGs in the miRNA–mRNA network. Full article ">Figure 7
Expression of selected genes and miRNAs in the WT and MSTN-KO groups. (A,B) Expression levels of four DEGs and five DEMs in the WT and MSTN-KO groups measured by qRT-PCR and normalized to GAPDH and U6 snRNA expression levels, respectively. (C) Expression levels of TGFB1 and FOS in WT, miR-130b-3p mimics and miR-335-5p groups. The experiments were performed in triplicate with three biological replicates for each gene or miRNA. All data are shown as the mean ± SEM. Two-tailed Mann–Whitney U tests were used for pairwise comparisons between groups. ** p < 0.01, *** p < 0.001. Full article ">

Review

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31 pages, 8825 KiB

Open AccessReview

A Census and Categorization Method of Epitranscriptomic Marks

by Julia Mathlin, Loredana Le Pera and Teresa Colombo

Int. J. Mol. Sci. 2020, 21(13), 4684; https://doi.org/10.3390/ijms21134684 - 30 Jun 2020

Cited by 27 | Viewed by 4823

Abstract

In the past few years, thorough investigation of chemical modifications operated in the cells on ribonucleic acid (RNA) molecules is gaining momentum. This new field of research has been dubbed “epitranscriptomics”, in analogy to best-known epigenomics, to stress the potential of ensembles of [...] Read more.

In the past few years, thorough investigation of chemical modifications operated in the cells on ribonucleic acid (RNA) molecules is gaining momentum. This new field of research has been dubbed “epitranscriptomics”, in analogy to best-known epigenomics, to stress the potential of ensembles of RNA modifications to constitute a post-transcriptional regulatory layer of gene expression orchestrated by writer, reader, and eraser RNA-binding proteins (RBPs). In fact, epitranscriptomics aims at identifying and characterizing all functionally relevant changes involving both non-substitutional chemical modifications and editing events made to the transcriptome. Indeed, several types of RNA modifications that impact gene expression have been reported so far in different species of cellular RNAs, including ribosomal RNAs, transfer RNAs, small nuclear RNAs, messenger RNAs, and long non-coding RNAs. Supporting functional relevance of this largely unknown regulatory mechanism, several human diseases have been associated directly to RNA modifications or to RBPs that may play as effectors of epitranscriptomic marks. However, an exhaustive epitranscriptome’s characterization, aimed to systematically classify all RNA modifications and clarify rules, actors, and outcomes of this promising regulatory code, is currently not available, mainly hampered by lack of suitable detecting technologies. This is an unfortunate limitation that, thanks to an unprecedented pace of technological advancements especially in the sequencing technology field, is likely to be overcome soon. Here, we review the current knowledge on epitranscriptomic marks and propose a categorization method based on the reference ribonucleotide and its rounds of modifications (“stages”) until reaching the given modified form. We believe that this classification scheme can be useful to coherently organize the expanding number of discovered RNA modifications. Full article

(This article belongs to the Special Issue RNA Regulatory Networks)

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24 pages, 1736 KiB

Open AccessReview

The Sophisticated Transcriptional Response Governed by Transposable Elements in Human Health and Disease

by Federica Marasca, Erica Gasparotto, Benedetto Polimeni, Rebecca Vadalà, Valeria Ranzani and Beatrice Bodega

Int. J. Mol. Sci. 2020, 21(9), 3201; https://doi.org/10.3390/ijms21093201 - 30 Apr 2020

Cited by 6 | Viewed by 5471

Abstract

Transposable elements (TEs), which cover ~45% of the human genome, although firstly considered as “selfish” DNA, are nowadays recognized as driving forces in eukaryotic genome evolution. This capability resides in generating a plethora of sophisticated RNA regulatory networks that influence the cell type [...] Read more.

Transposable elements (TEs), which cover ~45% of the human genome, although firstly considered as “selfish” DNA, are nowadays recognized as driving forces in eukaryotic genome evolution. This capability resides in generating a plethora of sophisticated RNA regulatory networks that influence the cell type specific transcriptome in health and disease. Indeed, TEs are transcribed and their RNAs mediate multi-layered transcriptional regulatory functions in cellular identity establishment, but also in the regulation of cellular plasticity and adaptability to environmental cues, as occurs in the immune response. Moreover, TEs transcriptional deregulation also evolved to promote pathogenesis, as in autoimmune and inflammatory diseases and cancers. Importantly, many of these findings have been achieved through the employment of Next Generation Sequencing (NGS) technologies and bioinformatic tools that are in continuous improvement to overcome the limitations of analyzing TEs sequences. However, they are highly homologous, and their annotation is still ambiguous. Here, we will review some of the most recent findings, questions and improvements to study at high resolution this intriguing portion of the human genome in health and diseases, opening the scenario to novel therapeutic opportunities. Full article

(This article belongs to the Special Issue RNA Regulatory Networks)

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Schematic representation of retrotransposons classes organization. Retrotransposons are divided in three major classes: long interspersed elements (LINE), short interspersed elements (SINE) and long terminal repeat (LTR). Left, full length retrotransposons: the regulatory sequences are represented in grey; RNA Pol II and Pol III promoters are indicated with arrows; the protein coding sequences are indicated with colors. Middle, most common transposable elements (TEs) in the human genome. Right, retrotransposon coverage of the human genome (see the main text for details). Full article ">Figure 2
TEs promote innate and adaptive immune response activation in health and disease through RNA and DNA sensing pathways. (A) Nucleic acids of TEs bind and activate the transmembrane Toll-like receptors (TLRs) and cytosolic pattern recognition receptors (PRRs) activating transcription factors that promotes INF gene transcription and IFNs production. (B) TEs in T and B lymphocytes activate adaptive immune response through RNA and DNA sensing pathways, as mentioned in (A). (C) In cancer cells the inhibition of DNA methylation, promotes TEs expression and enhances cytokines production. Full article ">Figure 3
TEs transcriptome contributes to cancer transcriptional fingerprint. A schematic representation of new function mediated by TEs in cancer: (A) TE (in green) can act as promoter sequence or (B) enhancer sequence. Transcription Factor and cofactors (TF) are highlighted in red and violet. (C) TEs can generate new chimeric transcripts, (D) giving origin to new oncogene transcripts and peptides that can be recognized by immune system as not-self, improving cancer immunogenicity. Full article ">Figure 4
Ambiguous reads in transcript quantification. (A) Schematic representation of RNA-seq reads aligned on a gene on the reference genome, the gene is transcribed in two transcript isoforms, A and B. (B) Isoform B is twice more abundant than A; however, if ambiguous reads are discarded from reads count, the difference between A and B will be negligible after normalizing read counts against transcript length. Full article ">

22 pages, 2174 KiB

Open AccessReview

Interspecies Communication in Holobionts by Non-Coding RNA Exchange

by Ana Lúcia Leitão, Marina C. Costa, André F. Gabriel and Francisco J. Enguita

Int. J. Mol. Sci. 2020, 21(7), 2333; https://doi.org/10.3390/ijms21072333 - 27 Mar 2020

Cited by 23 | Viewed by 5043

Abstract

Complex organisms are associations of different cells that coexist and collaborate creating a living consortium, the holobiont. The relationships between the holobiont members are essential for proper homeostasis of the organisms, and they are founded on the establishment of complex inter-connections between all [...] Read more.

Complex organisms are associations of different cells that coexist and collaborate creating a living consortium, the holobiont. The relationships between the holobiont members are essential for proper homeostasis of the organisms, and they are founded on the establishment of complex inter-connections between all the cells. Non-coding RNAs are regulatory molecules that can also act as communication signals between cells, being involved in either homeostasis or dysbiosis of the holobionts. Eukaryotic and prokaryotic cells can transmit signals via non-coding RNAs while using specific extracellular conveyors that travel to the target cell and can be translated into a regulatory response by dedicated molecular machinery. Within holobionts, non-coding RNA regulatory signaling is involved in symbiotic and pathogenic relationships among the cells. This review analyzes current knowledge regarding the role of non-coding RNAs in cell-to-cell communication, with a special focus on the signaling between cells in multi-organism consortia. Full article

(This article belongs to the Special Issue RNA Regulatory Networks)

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14 pages, 520 KiB

Open AccessReview

Mutual Regulation of RNA Silencing and the IFN Response as an Antiviral Defense System in Mammalian Cells

by Tomoko Takahashi and Kumiko Ui-Tei

Int. J. Mol. Sci. 2020, 21(4), 1348; https://doi.org/10.3390/ijms21041348 - 17 Feb 2020

Cited by 14 | Viewed by 9458

Abstract

RNA silencing is a posttranscriptional gene silencing mechanism directed by endogenous small non-coding RNAs called microRNAs (miRNAs). By contrast, the type-I interferon (IFN) response is an innate immune response induced by exogenous RNAs, such as viral RNAs. Endogenous and exogenous RNAs have typical [...] Read more.

RNA silencing is a posttranscriptional gene silencing mechanism directed by endogenous small non-coding RNAs called microRNAs (miRNAs). By contrast, the type-I interferon (IFN) response is an innate immune response induced by exogenous RNAs, such as viral RNAs. Endogenous and exogenous RNAs have typical structural features and are recognized accurately by specific RNA-binding proteins in each pathway. In mammalian cells, both RNA silencing and the IFN response are induced by double-stranded RNAs (dsRNAs) in the cytoplasm, but have long been considered two independent pathways. However, recent reports have shed light on crosstalk between the two pathways, which are mutually regulated by protein–protein interactions triggered by viral infection. This review provides brief overviews of RNA silencing and the IFN response and an outline of the molecular mechanism of their crosstalk and its biological implications. Crosstalk between RNA silencing and the IFN response may reveal a novel antiviral defense system that is regulated by miRNAs in mammalian cells. Full article

(This article belongs to the Special Issue RNA Regulatory Networks)

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Graphical abstract
Full article ">Figure 1
RNA silencing directed by endogenous miRNAs. The primary miRNA (pri-miRNA) is transcribed from the genome and processed into precursor miRNA (pre-miRNA) by the endoribonuclease Drosha in the nucleus. After processing, the pre-miRNA is exported to the cytoplasm and processed into miRNA duplexes by the endoribonuclease Dicer. One strand of the miRNA duplex is bound to Argonaute (AGO) and forms RNA-induced silencing complex (RISC) with trinucleotide repeat-containing gene 6 (TNRC6) and decapping or deadenylation enzymes for mRNA degradation or translational repression of mRNAs. Full article ">Figure 2
The interferon (IFN) response directed by exogenous RNAs. Exogenous RNAs such as viral RNAs are detected by toll-like receptor 3 (TLR3) in the endosome or retinoic acid-inducible gene I (RIG-I)-like receptors (RLRs) in the cytoplasm. Activated TLR3 or RLRs transfer signals to downstream molecules, inducing IFN production. Among RLRs, laboratory of genetics and physiology 2 (LGP2) does not contain caspase recruitment domain (CARD), which is necessary for signal transfer. The secreted IFN is recognized by the IFN receptor on the cell surface in a paracrine or autocrine manner, inducing the expression of IFN-stimulated genes (ISGs). An ISG, either 2′-5′-oligoadenylate synthetase (OAS) or protein kinase R (PKR), activates RNase L via 2-5A or phosphorylates eIF2α to carry out RNA degradation or translational repression, respectively. Activation of the IFN response represses viral replication and effectively excludes viruses while limiting damage to the cell. Full article ">Figure 3
Domain structures of Dicer, RLRs, trans-activation response (TAR) RNA-binding protein (TRBP), protein activator of PKR (PACT), adenosine deaminase acting on RNA 1 (ADAR1), and PKR. (A) Domain structures of Dicer and RLRs. E-values were calculated using Protein-BLAST compared to the ATPase/helicase domain of Dicer. (B) The domain structures of TRBP, PACT, ADAR1, and PKR. TRBP, PACT, and ADAR1 are dual-functional modulators of RNA silencing and PKR activation. Full article ">

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