Genes2015, 6(2), 150-162; doi:10.3390/genes6020150 (registering DOI) - published 30 March 2015 Show/Hide Abstract
Abstract: Inherited mutations in the DNA mismatch repair genes (MMR) can cause MMR deficiency and increased susceptibility to colorectal and endometrial cancer. Microsatellite instability (MSI) is the defining molecular signature of MMR deficiency. The clinical classification of identified MMR gene sequence variants has a direct impact on the management of patients and their families. For a significant proportion of cases sequence variants of uncertain clinical significance (also known as unclassified variants) are identified, constituting a challenge for genetic counselling and clinical management of families. The effect on protein function of these variants is difficult to interpret. The presence or absence of MSI in tumours can aid in determining the pathogenicity of associated unclassified MMR gene variants. However, there are some considerations that need to be taken into account when using MSI for variant interpretation. The use of MSI and other tumour characteristics in MMR gene sequence variant classification will be explored in this review.
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 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.
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, 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.
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 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.
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 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.
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 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.