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author:("flame, Daisy")
1.  Molecular diagnostics for congenital hearing loss including 15 deafness genes using a next generation sequencing platform 
BMC Medical Genomics  2012;5:17.
Background
Hereditary hearing loss (HL) can originate from mutations in one of many genes involved in the complex process of hearing. Identification of the genetic defects in patients is currently labor intensive and expensive. While screening with Sanger sequencing for GJB2 mutations is common, this is not the case for the other known deafness genes (> 60). Next generation sequencing technology (NGS) has the potential to be much more cost efficient. Published methods mainly use hybridization based target enrichment procedures that are time saving and efficient, but lead to loss in sensitivity. In this study we used a semi-automated PCR amplification and NGS in order to combine high sensitivity, speed and cost efficiency.
Results
In this proof of concept study, we screened 15 autosomal recessive deafness genes in 5 patients with congenital genetic deafness. 646 specific primer pairs for all exons and most of the UTR of the 15 selected genes were designed using primerXL. Using patient specific identifiers, all amplicons were pooled and analyzed using the Roche 454 NGS technology. Three of these patients are members of families in which a region of interest has previously been characterized by linkage studies. In these, we were able to identify two new mutations in CDH23 and OTOF. For another patient, the etiology of deafness was unclear, and no causal mutation was found. In a fifth patient, included as a positive control, we could confirm a known mutation in TMC1.
Conclusions
We have developed an assay that holds great promise as a tool for screening patients with familial autosomal recessive nonsyndromal hearing loss (ARNSHL). For the first time, an efficient, reliable and cost effective genetic test, based on PCR enrichment, for newborns with undiagnosed deafness is available.
doi:10.1186/1755-8794-5-17
PMCID: PMC3443074  PMID: 22607986
Deafness; Next generation sequencing; PCR based enrichment; Genetic diagnostics
2.  Cytokines Interleukin-1β and Tumor Necrosis Factor-α Regulate Different Transcriptional and Alternative Splicing Networks in Primary β-Cells 
Diabetes  2009;59(2):358-374.
OBJECTIVE
Cytokines contribute to pancreatic β-cell death in type 1 diabetes. This effect is mediated by complex gene networks that remain to be characterized. We presently utilized array analysis to define the global expression pattern of genes, including spliced variants, modified by the cytokines interleukin (IL)-1β + interferon (IFN)-γ and tumor necrosis factor (TNF)-α + IFN-γ in primary rat β-cells.
RESEARCH DESIGN AND METHODS
Fluorescence-activated cell sorter–purified rat β-cells were exposed to IL-1β + IFN-γ or TNF-α + IFN-γ for 6 or 24 h, and global gene expression was analyzed by microarray. Key results were confirmed by RT-PCR, and small-interfering RNAs were used to investigate the mechanistic role of novel and relevant transcription factors identified by pathway analysis.
RESULTS
Nearly 16,000 transcripts were detected as present in β-cells, with temporal differences in the number of genes modulated by IL-1β + IFNγ or TNF-α + IFN-γ. These cytokine combinations induced differential expression of inflammatory response genes, which is related to differential induction of IFN regulatory factor-7. Both treatments decreased the expression of genes involved in the maintenance of β-cell phenotype and growth/regeneration. Cytokines induced hypoxia-inducible factor-α, which in this context has a proapoptotic role. Cytokines also modified the expression of >20 genes involved in RNA splicing, and exon array analysis showed cytokine-induced changes in alternative splicing of >50% of the cytokine-modified genes.
CONCLUSIONS
The present study doubles the number of known genes expressed in primary β-cells, modified or not by cytokines, and indicates the biological role for several novel cytokine-modified pathways in β-cells. It also shows that cytokines modify alternative splicing in β-cells, opening a new avenue of research for the field.
doi:10.2337/db09-1159
PMCID: PMC2809955  PMID: 19934004
3.  Detailed transcriptome atlas of the pancreatic beta cell 
Background
Gene expression patterns provide a detailed view of cellular functions. Comparison of profiles in disease vs normal conditions provides insights into the processes underlying disease progression. However, availability and integration of public gene expression datasets remains a major challenge. The aim of the present study was to explore the transcriptome of pancreatic islets and, based on this information, to prepare a comprehensive and open access inventory of insulin-producing beta cell gene expression, the Beta Cell Gene Atlas (BCGA).
Methods
We performed Massively Parallel Signature Sequencing (MPSS) analysis of human pancreatic islet samples and microarray analyses of purified rat beta cells, alpha cells and INS-1 cells, and compared the information with available array data in the literature.
Results
MPSS analysis detected around 7600 mRNA transcripts, of which around a third were of low abundance. We identified 2000 and 1400 transcripts that are enriched/depleted in beta cells compared to alpha cells and INS-1 cells, respectively. Microarray analysis identified around 200 transcription factors that are differentially expressed in either beta or alpha cells. We reanalyzed publicly available gene expression data and integrated these results with the new data from this study to build the BCGA. The BCGA contains basal (untreated conditions) gene expression level estimates in beta cells as well as in different cell types in human, rat and mouse pancreas. Hierarchical clustering of expression profile estimates classify cell types based on species while beta cells were clustered together.
Conclusion
Our gene atlas is a valuable source for detailed information on the gene expression distribution in beta cells and pancreatic islets along with insulin producing cell lines. The BCGA tool, as well as the data and code used to generate the Atlas are available at the T1Dbase website (T1DBase.org).
doi:10.1186/1755-8794-2-3
PMCID: PMC2635377  PMID: 19146692
4.  T1DBase: integration and presentation of complex data for type 1 diabetes research 
Nucleic Acids Research  2006;35(Database issue):D742-D746.
T1DBase () [Smink et al. (2005) Nucleic Acids Res., 33, D544–D549; Burren et al. (2004) Hum. Genomics, 1, 98–109] is a public website and database that supports the type 1 diabetes (T1D) research community. T1DBase provides a consolidated T1D-oriented view of the complex data world that now confronts medical researchers and enables scientists to navigate from information they know to information that is new to them. Overview pages for genes and markers summarize information for these elements. The Gene Dossier summarizes information for a list of genes. GBrowse [Stein et al. (2002) Genome Res., 10, 1599–1610] displays genes and other features in their genomic context, and Cytoscape [Shannon et al. (2003) Genome Res., 13, 2498–2504] shows genes in the context of interacting proteins and genes. The Beta Cell Gene Atlas shows gene expression in β cells, islets, and related cell types and lines, and the Tissue Expression Viewer shows expression across other tissues. The Microarray Viewer shows expression from more than 20 array experiments. The Beta Cell Gene Expression Bank contains manually curated gene and pathway annotations for genes expressed in β cells. T1DMart is a query tool for markers and genotypes. PosterPages are ‘home pages’ about specific topics or datasets. The key challenge, now and in the future, is to provide powerful informatics capabilities to T1D scientists in a form they can use to enhance their research.
doi:10.1093/nar/gkl933
PMCID: PMC1781218  PMID: 17169983
5.  The AMP-activated protein kinase α2 catalytic subunit controls whole-body insulin sensitivity 
AMP-activated protein kinase (AMPK) is viewed as a fuel sensor for glucose and lipid metabolism. To better understand the physiological role of AMPK, we generated a knockout mouse model in which the AMPKα2 catalytic subunit gene was inactivated. AMPKα2–/– mice presented high glucose levels in the fed period and during an oral glucose challenge associated with low insulin plasma levels. However, in isolated AMPKα2–/– pancreatic islets, glucose- and L-arginine–stimulated insulin secretion were not affected. AMPKα2–/– mice have reduced insulin-stimulated whole-body glucose utilization and muscle glycogen synthesis rates assessed in vivo by the hyperinsulinemic euglycemic clamp technique. Surprisingly, both parameters were not altered in mice expressing a dominant-negative mutant of AMPK in skeletal muscle. Furthermore, glucose transport was normal in incubated isolated AMPKα2–/– muscles. These data indicate that AMPKα2 in tissues other than skeletal muscles regulates insulin action. Concordantly, we found an increased daily urinary catecholamine excretion in AMPKα2–/– mice, suggesting altered function of the autonomic nervous system that could explain both the impaired insulin secretion and insulin sensitivity observed in vivo. Therefore, extramuscular AMPKα2 catalytic subunit is important for whole-body insulin action in vivo, probably through modulation of sympathetic nervous activity.
doi:10.1172/JCI200316567
PMCID: PMC151837  PMID: 12511592

Results 1-5 (5)