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Genes, Volume 6, Issue 1 (March 2015) – 7 articles , Pages 1-149

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Review
RNA Export through the NPC in Eukaryotes
Genes 2015, 6(1), 124-149; https://0-doi-org.brum.beds.ac.uk/10.3390/genes6010124 - 20 Mar 2015
Cited by 59 | Viewed by 6854
Abstract
In eukaryotic cells, RNAs are transcribed in the nucleus and exported to the cytoplasm through the nuclear pore complex. The RNA molecules that are exported from the nucleus into the cytoplasm include messenger RNAs (mRNAs), ribosomal RNAs (rRNAs), transfer RNAs (tRNAs), small nuclear [...] Read more.
In eukaryotic cells, RNAs are transcribed in the nucleus and exported to the cytoplasm through the nuclear pore complex. The RNA molecules that are exported from the nucleus into the cytoplasm include messenger RNAs (mRNAs), ribosomal RNAs (rRNAs), transfer RNAs (tRNAs), small nuclear RNAs (snRNAs), micro RNAs (miRNAs), and viral mRNAs. Each RNA is transported by a specific nuclear export receptor. It is believed that most of the mRNAs are exported by Nxf1 (Mex67 in yeast), whereas rRNAs, snRNAs, and a certain subset of mRNAs are exported in a Crm1/Xpo1-dependent manner. tRNAs and miRNAs are exported by Xpot and Xpo5. However, multiple export receptors are involved in the export of some RNAs, such as 60S ribosomal subunit. In addition to these export receptors, some adapter proteins are required to export RNAs. The RNA export system of eukaryotic cells is also used by several types of RNA virus that depend on the machineries of the host cell in the nucleus for replication of their genome, therefore this review describes the RNA export system of two representative viruses. We also discuss the NPC anchoring-dependent mRNA export factors that directly recruit specific genes to the NPC. Full article
(This article belongs to the Special Issue Mechanisms of mRNA Nuclear Export)
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Review
Genetics of Type 2 Diabetes—Pitfalls and Possibilities
Genes 2015, 6(1), 87-123; https://0-doi-org.brum.beds.ac.uk/10.3390/genes6010087 - 12 Mar 2015
Cited by 216 | Viewed by 14622
Abstract
Type 2 diabetes (T2D) is a complex disease that is caused by a complex interplay between genetic, epigenetic and environmental factors. While the major environmental factors, diet and activity level, are well known, identification of the genetic factors has been a challenge. However, [...] Read more.
Type 2 diabetes (T2D) is a complex disease that is caused by a complex interplay between genetic, epigenetic and environmental factors. While the major environmental factors, diet and activity level, are well known, identification of the genetic factors has been a challenge. However, recent years have seen an explosion of genetic variants in risk and protection of T2D due to the technical development that has allowed genome-wide association studies and next-generation sequencing. Today, more than 120 variants have been convincingly replicated for association with T2D and many more with diabetes-related traits. Still, these variants only explain a small proportion of the total heritability of T2D. In this review, we address the possibilities to elucidate the genetic landscape of T2D as well as discuss pitfalls with current strategies to identify the elusive unknown heritability including the possibility that our definition of diabetes and its subgroups is imprecise and thereby makes the identification of genetic causes difficult. Full article
(This article belongs to the Special Issue Genetics of Diabetes)
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Review
Role of Mecp2 in Experience-Dependent Epigenetic Programming
Genes 2015, 6(1), 60-86; https://0-doi-org.brum.beds.ac.uk/10.3390/genes6010060 - 06 Mar 2015
Cited by 27 | Viewed by 4819
Abstract
Mutations in the X-linked gene MECP2, the founding member of a family of proteins recognizing and binding to methylated DNA, are the genetic cause of a devastating neurodevelopmental disorder in humans, called Rett syndrome. Available evidence suggests that MECP2 protein has a [...] Read more.
Mutations in the X-linked gene MECP2, the founding member of a family of proteins recognizing and binding to methylated DNA, are the genetic cause of a devastating neurodevelopmental disorder in humans, called Rett syndrome. Available evidence suggests that MECP2 protein has a critical role in activity-dependent neuronal plasticity and transcription during brain development. Moreover, recent studies in mice show that various posttranslational modifications, notably phosphorylation, regulate Mecp2’s functions in learning and memory, drug addiction, depression-like behavior, and the response to antidepressant treatment. The hypothalamic-pituitary-adrenal (HPA) axis drives the stress response and its deregulation increases the risk for a variety of mental disorders. Early-life stress (ELS) typically results in sustained HPA-axis deregulation and is a major risk factor for stress related diseases, in particular major depression. Interestingly, Mecp2 protein has been shown to contribute to ELS-dependent epigenetic programming of Crh, Avp, and Pomc, all of these genes enhance HPA-axis activity. Hereby ELS regulates Mecp2 phosphorylation, DNA binding, and transcriptional activities in a tissue-specific and temporospatial manner. Overall, these findings suggest MECP2 proteins are so far underestimated and have a more dynamic role in the mediation of the gene-environment dialog and epigenetic programming of the neuroendocrine stress system in health and disease. Full article
(This article belongs to the Section Molecular Genetics and Genomics)
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Article
Applicability of Next Generation Sequencing Technology in Microsatellite Instability Testing
Genes 2015, 6(1), 46-59; https://0-doi-org.brum.beds.ac.uk/10.3390/genes6010046 - 12 Feb 2015
Cited by 31 | Viewed by 4551
Abstract
Microsatellite instability (MSI) is a useful marker for risk assessment, prediction of chemotherapy responsiveness and prognosis in patients with colorectal cancer. Here, we describe a next generation sequencing approach for MSI testing using the MiSeq platform. Different from other MSI capturing strategies that [...] Read more.
Microsatellite instability (MSI) is a useful marker for risk assessment, prediction of chemotherapy responsiveness and prognosis in patients with colorectal cancer. Here, we describe a next generation sequencing approach for MSI testing using the MiSeq platform. Different from other MSI capturing strategies that are based on targeted gene capture, we utilize “deep resequencing”, where we focus the sequencing on only the microsatellite regions of interest. We sequenced a series of 44 colorectal tumours with normal controls for five MSI loci (BAT25, BAT26, BAT34c4, D18S55, D5S346) and a second series of six colorectal tumours (no control) with two mononucleotide loci (BAT25, BAT26). In the first series, we were able to determine 17 MSI-High, 1 MSI-Low and 26 microsatellite stable (MSS) tumours. In the second series, there were three MSI-High and three MSS tumours. Although there was some variation within individual markers, this NGS method produced the same overall MSI status for each tumour, as obtained with the traditional multiplex PCR-based method. Full article
(This article belongs to the Special Issue Microsatellite Instability)
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Article
Yeast Phenomics: An Experimental Approach for Modeling Gene Interaction Networks that Buffer Disease
Genes 2015, 6(1), 24-45; https://doi.org/10.3390/genes6010024 - 06 Feb 2015
Cited by 8 | Viewed by 4487
Abstract
The genome project increased appreciation of genetic complexity underlying disease phenotypes: many genes contribute each phenotype and each gene contributes multiple phenotypes. The aspiration of predicting common disease in individuals has evolved from seeking primary loci to marginal risk assignments based on many [...] Read more.
The genome project increased appreciation of genetic complexity underlying disease phenotypes: many genes contribute each phenotype and each gene contributes multiple phenotypes. The aspiration of predicting common disease in individuals has evolved from seeking primary loci to marginal risk assignments based on many genes. Genetic interaction, defined as contributions to a phenotype that are dependent upon particular digenic allele combinations, could improve prediction of phenotype from complex genotype, but it is difficult to study in human populations. High throughput, systematic analysis of S. cerevisiae gene knockouts or knockdowns in the context of disease-relevant phenotypic perturbations provides a tractable experimental approach to derive gene interaction networks, in order to deduce by cross-species gene homology how phenotype is buffered against disease-risk genotypes. Yeast gene interaction network analysis to date has revealed biology more complex than previously imagined. This has motivated the development of more powerful yeast cell array phenotyping methods to globally model the role of gene interaction networks in modulating phenotypes (which we call yeast phenomic analysis). The article illustrates yeast phenomic technology, which is applied here to quantify gene X media interaction at higher resolution and supports use of a human-like media for future applications of yeast phenomics for modeling human disease. Full article
(This article belongs to the Special Issue Grand Celebration: 10th Anniversary of the Human Genome Project)
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Editorial
Acknowledgement to Reviewers of Genes in 2014
Genes 2015, 6(1), 22-23; https://0-doi-org.brum.beds.ac.uk/10.3390/genes6010022 - 07 Jan 2015
Viewed by 2091
Abstract
The editors of Genes would like to express their sincere gratitude to the following reviewers for assessing manuscripts in 2014:[...] Full article
Article
Down-Regulation of miR-129-5p and the let-7 Family in Neuroendocrine Tumors and Metastases Leads to Up-Regulation of Their Targets Egr1, G3bp1, Hmga2 and Bach1
Genes 2015, 6(1), 1-21; https://0-doi-org.brum.beds.ac.uk/10.3390/genes6010001 - 24 Dec 2014
Cited by 45 | Viewed by 4726
Abstract
Expression of miRNAs in Neuroendocrine Neoplasms (NEN) is poorly characterized. We therefore wanted to examine the miRNA expression in Neuroendocrine Tumors (NETs), and identify their targets and importance in NET carcinogenesis. miRNA expression in six NEN primary tumors, six NEN metastases and four [...] Read more.
Expression of miRNAs in Neuroendocrine Neoplasms (NEN) is poorly characterized. We therefore wanted to examine the miRNA expression in Neuroendocrine Tumors (NETs), and identify their targets and importance in NET carcinogenesis. miRNA expression in six NEN primary tumors, six NEN metastases and four normal intestinal tissues was characterized using miRNA arrays, and validated by in-situ hybridization and qPCR. Among the down-regulated miRNAs miR-129-5p and the let-7f/let-7 family, were selected for further characterization. Transfection of miR-129-5p inhibited growth of a pulmonary and an intestinal carcinoid cell line. Analysis of mRNA expression changes identified EGR1 and G3BP1 as miR-129-5p targets. They were validated by luciferase assay and western blotting, and found robustly expressed in NETs by immunohistochemistry. Knockdown of EGR1 and G3BP1 mimicked the growth inhibition induced by miR-129-5p. let-7 overexpression inhibited growth of carcinoid cell lines, and let-7 inhibition increased protein content of the transcription factor BACH1 and its targets MMP1 and HMGA2, all known to promote bone metastases. Immunohistochemistry analysis revealed that let-7 targets are highly expressed in NETs and metastases. We found down-regulation of miR-129-5p and the let-7 family, and identified new neuroendocrine specific targets for these miRNAs, which contributes to the growth and metastatic potential of these tumors. Full article
(This article belongs to the Section Human Genomics and Genetic Diseases)
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