The Ohio State University
Cancer Biology and Genetics
RNA editing is a dynamic mechanism for gene regulation attained through the alteration of the sequence of primary RNA transcripts. A-to-I (adenosine-to-inosine) RNA editing, which is catalyzed by members of the adenosine deaminase acting... more
RNA editing is a dynamic mechanism for gene regulation attained through the alteration of the sequence of primary RNA transcripts. A-to-I (adenosine-to-inosine) RNA editing, which is catalyzed by members of the adenosine deaminase acting on RNA (ADAR) family of enzymes, is the most common post-transcriptional modification in humans. The ADARs bind double-stranded regions and deaminate adenosine (A) into inosine (I), which in turn is interpreted by the translation and splicing machineries as guanosine (G). In recent years, this modification has been discovered to occur not only in coding RNAs but also in non-coding RNAs (ncRNA), such as microRNAs, small interfering RNAs, transfer RNAs, and long non-coding RNAs. This may have several consequences, such as the creation or disruption of microRNA/mRNA binding sites, and thus affect the biogenesis, stability, and target recognition properties of ncRNAs. The malfunction of the editing machinery is not surprisingly associated with various human diseases, such as neurodegenerative, cardiovascular, and carcinogenic diseases. Despite the enormous efforts made so far, the real biological function of this phenomenon, as well as the features of the ADAR substrate, in particular in non-coding RNAs, has still not been fully understood. In this work, we focus on the current knowledge of RNA editing on ncRNA molecules and provide a few examples of computational approaches to elucidate its biological function.
- by Giovanni Nigita and +1
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- RNA Editing, ncRNAs, miRNAs
The majority of the human transcriptome is defined as non-coding RNA (ncRNA), since only a small fraction of human DNA encodes for proteins, as reported by the ENCODE project. Several distinct classes of ncRNAs, such as transfer RNA,... more
The majority of the human transcriptome is defined as non-coding RNA (ncRNA), since
only a small fraction of human DNA encodes for proteins, as reported by the ENCODE
project. Several distinct classes of ncRNAs, such as transfer RNA, microRNA, and long
non-coding RNA, have been classified, each with its own three-dimensional folding and
specific function. As ncRNAs are highly abundant in living organisms and have been
discovered to play important roles in many biological processes, there has been an ever
increasing need to investigate the entire ncRNAome in further unbiased detail. Recently,
the advent of next-generation sequencing (NGS) technologies has substantially increased
the throughput of transcriptome studies, allowing an unprecedented investigation of
ncRNAs, as regulatory pathways and novel functions involving ncRNAs are now also
emerging. The huge amount of transcript data produced by NGS has progressively
required the development and implementation of suitable bioinformatics workflows,
complemented by knowledge-based approaches, to identify, classify, and evaluate the
expression of hundreds of ncRNAs in normal and pathological conditions, such as
cancer. In this mini-review, we present and discuss current bioinformatics advances in
the development of such computational approaches to analyze and classify the ncRNA
component of human transcriptome sequence data obtained from NGS technologies.
only a small fraction of human DNA encodes for proteins, as reported by the ENCODE
project. Several distinct classes of ncRNAs, such as transfer RNA, microRNA, and long
non-coding RNA, have been classified, each with its own three-dimensional folding and
specific function. As ncRNAs are highly abundant in living organisms and have been
discovered to play important roles in many biological processes, there has been an ever
increasing need to investigate the entire ncRNAome in further unbiased detail. Recently,
the advent of next-generation sequencing (NGS) technologies has substantially increased
the throughput of transcriptome studies, allowing an unprecedented investigation of
ncRNAs, as regulatory pathways and novel functions involving ncRNAs are now also
emerging. The huge amount of transcript data produced by NGS has progressively
required the development and implementation of suitable bioinformatics workflows,
complemented by knowledge-based approaches, to identify, classify, and evaluate the
expression of hundreds of ncRNAs in normal and pathological conditions, such as
cancer. In this mini-review, we present and discuss current bioinformatics advances in
the development of such computational approaches to analyze and classify the ncRNA
component of human transcriptome sequence data obtained from NGS technologies.
- by Dario Veneziano and +1
- •
- Bioinformatics
Chronic lymphocytic leukemia (CLL) is the most common human leukemia, and transgenic mouse studies indicate that activation of the T-cell leukemia/lymphoma 1 (TCL1) oncogene is a contributing event in the pathogenesis of the aggressive... more
Chronic lymphocytic leukemia (CLL) is the most common human leukemia, and transgenic mouse studies indicate that activation of the T-cell leukemia/lymphoma 1 (TCL1) oncogene is a contributing event in the pathogenesis of the aggressive form of this disease. While studying the regulation of TCL1 expression, we identified the microRNA cluster miR-4521/3676 and discovered that these two microRNAs are associated with tRNA sequences and that this region can produce two small RNAs, members of a recently identified class of small noncoding RNAs, tRNA-derived small RNAs (tsRNAs). We further proved that miR-3676 and miR-4521 are tsRNAs using Northern blot analysis. We found that, like ts-3676, ts-4521 is down-regulated and mutated in CLL. Analysis of lung cancer samples revealed that both ts-3676 and ts-4521 are down-regulated and mutated in patient tumor samples. Because tsRNAs are similar in nature to piRNAs [P-element–induced wimpy testis (Piwi)-interacting small RNAs], we investigated whether ts-3676 and ts-4521 can interact with Piwi proteins and found these two tsRNAs in complexes containing Piwi-like protein 2 (PIWIL2). To determine whether other tsRNAs are involved in cancer, we generated a custom microarray chip containing 120 tsRNAs 16 bp or more in size. Microarray hybridization experiments revealed tsRNA signatures in CLL and lung cancer, indicating that, like microRNAs, tsRNAs may have an oncogenic and/or tumor-suppressor function in he-matopoietic malignancies and solid tumors. Thus, our results show that tsRNAs are dysregulated in human cancer.
- by Giovanni Nigita and +1
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RNA editing is a finely tuned, dynamic mechanism for post-transcriptional gene regulation that has been thoroughly investigated in the last decade. Nevertheless , RNA editing in non-coding RNA, such as microRNA (miRNA), have caused great... more
RNA editing is a finely tuned, dynamic mechanism for post-transcriptional gene regulation that has been thoroughly investigated in the last decade. Nevertheless , RNA editing in non-coding RNA, such as microRNA (miRNA), have caused great debate and have called for deeper investigation. Until recently, in fact, inadequate methodologies and experimental contexts have been unable to provide detailed insights for further elucidation of RNA editing affecting miRNAs, especially in cancer. In this work, we leverage on recent innovative bioinformatics approaches applied to a more informative experimental context in order to analyze the variations in miRNA seed region editing activity during a time course of a hypoxia-exposed breast cancer cell line. By investigating its behavior in a dynamic context, we found that miRNA editing events in the seed region are not depended on miRNA expression, unprecedentedly providing insights on the targetome shifts derived from these modifications. This reveals that miRNA editing acts under the influence of environmentally induced stimuli. Our results show a miRNA editing activity trend aligning with cellular pathways closely associated to hypoxia, such as the VEGF and PI3K/Akt pathways, providing important novel insights on this poorly elucidated phenomenon.
- by Giovanni Nigita and +2
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- RNA Editing
Juvenile myelomonocytic leukemia (JMML) is an aggressive leukemia of early childhood characterized by aberrant proliferation of myelomonocytic cells and hypersensitivity to GM-CSF stimulation. Mutually exclusive mutations in the RAS/ ERK... more
Juvenile myelomonocytic leukemia (JMML) is an aggressive leukemia of early childhood characterized by aberrant proliferation of myelomonocytic cells and hypersensitivity to GM-CSF stimulation. Mutually exclusive mutations in the RAS/ ERK pathway genes such as PTPN11, NRAS, KRAS, CBL, or NF1 are found in ~90% of the cases. These mutations give rise to disease at least in part by activating STAT5 through phosphorylation and by promoting cell growth. MicroRNAs (miRs) are small non-coding RNAs that regulate gene expression, which are often deregulated in leukemia. However, little is known about their role in JMML. Here, we report distinctive miR expression signatures associated with the molecular subgroups of JMML. Among the downregulated miRs in JMML, miR-150-5p was found to target STAT5b, a gene which is often over-activated in JMML, and contributes to the characteristic aberrant signaling of this disorder. Moreover, loss of miR-150-5p and upregulation of STAT5b expression were also identified in a murine model of JMML. Ectopic overexpression of miR-150-5p in mononuclear cells from three JMML patients significantly decreased cell proliferation. Altogether, our data indicate that miR expression is deregulated in JMML and may play a role in the pathogenesis of this disorder by modulating key effectors of cytokine receptor pathways.
- by Pierpaolo Leoncini and +4
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Motivation: A-to-I RNA editing is an important mechanism that consists of the conversion of specific adenosines into inosines in RNA molecules. Its dysregulation has been associated to several human diseases including cancer. Recent work... more
Motivation: A-to-I RNA editing is an important mechanism that consists of the conversion of specific adenosines into inosines in RNA molecules. Its dysregulation has been associated to several human diseases including cancer. Recent work has demonstrated a role for A-to-I editing in microRNA (miRNA)-mediated gene expression regulation. In fact, edited forms of mature miRNAs can target sets of genes that differ from the targets of their unedited forms. The specific deamination of mRNAs can generate novel binding sites in addition to potentially altering existing ones. Results: This work presents miR-EdiTar, a database of predicted A-to-I edited miRNA binding sites. The database contains predicted miRNA binding sites that could be affected by A-to-I editing and sites that could become miRNA binding sites as a result of A-to-I editing. Availability: miR-EdiTar is freely available online at http://microrna.
MicroRNAs (miRNAs) are small non-coding RNAs responsible of post-transcriptional regulation of gene expression through interaction with messenger RNAs (mRNAs). They are involved in important biological processes and are often dysregulated... more
MicroRNAs (miRNAs) are small non-coding RNAs responsible of post-transcriptional regulation of gene expression through interaction with messenger RNAs (mRNAs). They are involved in important biological processes and are often dysregulated in a variety of diseases, including cancer and infections. Viruses also encode their own sets of miRNAs, which they use to control the expression of either the host's genes and/or their own. In the past few years evidence of the presence of cellular miRNAs in extracellular human body fluids such as serum, plasma, saliva, and urine has accumulated. They have been found either cofractionate with the Argonaute2 protein or in membrane-bound vesicles such as exosomes. Although little is known about the role of circulating miRNAs, it has been demonstrated that miRNAs secreted by virus-infected cells are transferred to and act in uninfected recipient cells. In this work we summarize the current knowledge on viral circulating miRNAs and provide a few e...
Prioritizing genes is a major concern for all those complex disorders whose genetic causes have not been yet completely understood. Due to its extremely heterogeneous genetics, non-syndromic Hereditary Hearing Loss (HHL) is one of the... more
Prioritizing genes is a major concern for all those complex disorders whose genetic causes have not been yet completely understood. Due to its extremely heterogeneous genetics, non-syndromic Hereditary Hearing Loss (HHL) is one of the best candidates for such an approach: there are indeed 51 genes already known to be responsible, if mutated, of this phenotype, and 111 chromosomal regions linked to this disease over the years where one or more genes causing HHL are located. These regions are often large, containing hundreds of genes, making the systematic screening of all the genes they contain (candidate genes) in search of causative mutations not feasible. In this scenario a computational help to select the candidate genes according to their probability to cause, if mutated, the disease is strongly needed. To address this issue we built a gene scoring system based on Gene Ontology (GO), which scores the candidate genes for HHL by comparing them with the 51 HHL disease genes, relying on the rationale that genes whose dysfunction cause a disease, tend to be functionally related.
- by Dario Veneziano
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Prioritizing genes is a major concern for all those complex disorders whose genetic causes have not been yet completely understood. Due to its extremely heterogeneous genetics, non-syndromic Hereditary Hearing Loss (HHL) is one of the... more
Prioritizing genes is a major concern for all those complex disorders whose genetic causes have not been yet completely understood. Due to its extremely heterogeneous genetics, non-syndromic Hereditary Hearing Loss (HHL) is one of the best candidates for such an approach: there are indeed 51 genes already known to be responsible, if mutated, of this phenotype, and 111 chromosomal regions linked to this disease over the years where one or more genes causing HHL are located. These regions are often large, containing hundreds of genes, making the systematic screening of all the genes they contain (candidate genes) in search of causative mutations not feasible. In this scenario a computational help to select the candidate genes according to their probability to cause, if mutated, the disease is strongly needed. To address this issue we built a gene scoring system based on Gene Ontology (GO), which scores the candidate genes for HHL by comparing them with the 51 HHL disease genes, relying on the rationale that genes whose dysfunction cause a disease, tend to be functionally related.
- by Dario Veneziano
- •