Correction: Development and extensive sequencing of a broadly-consented Genome in a Bottle matched tumor-normal pair.
Explore the source record for details and available documents.
Published Erratum↗
Biomedical subjects
Shawn Levy
Publications and source records attributed to Shawn Levy.
Development and extensive sequencing of a broadly-consented Genome in a Bottle matched tumor-normal pair.
The Genome in a Bottle Consortium (GIAB), hosted by the National Institute of Standards and Technology (NIST), is developing new matched tumor-normal samples, the first explicitly consented for public dissemination of genomic data and cell lines. Here, we describe a comprehensive genomic dataset from the first individual, HG008, including DNA from an adherent, epithelial-like pancreatic ductal adenocarcinoma (PDAC) tumor cell line and matched normal cells from duodenal and pancreatic tissues. Data for the tumor-normal matched samples comes from seventeen distinct state-of-the-art whole genome measurement technologies, including high depth short and long-read bulk whole genome sequencing (WGS), single cell WGS, Hi-C, and karyotyping. These data will be used by the GIAB Consortium to develop matched tumor-normal benchmarks for somatic variant detection. We expect these data to facilitate innovation for whole genome measurement technologies, de novo assembly of tumor and normal genomes, and bioinformatic tools to identify small and structural somatic variants. This first-of-its-kind broadly consented open-access resource will facilitate further understanding of sequencing methods used for cancer biology.
Humans↗
Development and extensive sequencing of a broadly-consented Genome in a Bottle matched tumor-normal pair.
The Genome in a Bottle Consortium (GIAB), hosted by the National Institute of Standards and Technology (NIST), is developing new matched tumor-normal samples, the first to be explicitly consented for public dissemination of genomic data and cell lines. Here, we describe a comprehensive genomic dataset from the first individual, HG008, including DNA from an adherent, epithelial-like pancreatic ductal adenocarcinoma (PDAC) tumor cell line and matched normal cells from duodenal and pancreatic tissues. Data for the tumor-normal matched samples comes from seventeen distinct state-of-the-art whole genome measurement technologies, including high depth short and long-read bulk whole genome sequencing (WGS), single cell WGS, and Hi-C, and karyotyping. In future publications, these data will be used by the GIAB Consortium to develop matched tumor-normal benchmarks for somatic variant detection. We expect these data to facilitate innovation for whole genome measurement technologies, de novo assembly of tumor and normal genomes, and bioinformatic tools to identify small and structural somatic mutations. This first-of-its-kind broadly consented open-access resource will facilitate further understanding of sequencing methods used for cancer biology.
Journal Article↗
A comprehensive evaluation of multicategory classification methods for microarray gene expression cancer diagnosis.
MOTIVATION: Cancer diagnosis is one of the most important emerging clinical applications of gene expression microarray technology. We are seeking to develop a computer system for powerful and reliable cancer diagnostic model creation based on microarray data. To keep a realistic perspective on clinical applications we focus on multicategory diagnosis. To equip the system with the optimum combination of classifier, gene selection and cross-validation methods, we performed a systematic and comprehensive evaluation of several major algorithms for multicategory classification, several gene selection methods, multiple ensemble classifier methods and two cross-validation designs using 11 datasets spanning 74 diagnostic categories and 41 cancer types and 12 normal tissue types. RESULTS: Multicategory support vector machines (MC-SVMs) are the most effective classifiers in performing accurate cancer diagnosis from gene expression data. The MC-SVM techniques by Crammer and Singer, Weston and Watkins and one-versus-rest were found to be the best methods in this domain. MC-SVMs outperform other popular machine learning algorithms, such as k-nearest neighbors, backpropagation and probabilistic neural networks, often to a remarkable degree. Gene selection techniques can significantly improve the classification performance of both MC-SVMs and other non-SVM learning algorithms. Ensemble classifiers do not generally improve performance of the best non-ensemble models. These results guided the construction of a software system GEMS (Gene Expression Model Selector) that automates high-quality model construction and enforces sound optimization and performance estimation procedures. This is the first such system to be informed by a rigorous comparative analysis of the available algorithms and datasets. AVAILABILITY: The software system GEMS is available for download from http://www.gems-system.org for non-commercial use. CONTACT: alexander.statnikov@vanderbilt.edu.
Algorithms↗
Chaotic mixer improves microarray hybridization.
Hybridization is an important aspect of microarray experimental design which influences array signal levels and the repeatability of data within an array and across different arrays. Current methods typically require 24h and use target inefficiently. In these studies, we compare hybridization signals obtained in conventional static hybridization, which depends on diffusional target delivery, with signals obtained in a dynamic hybridization chamber, which employs a fluid mixer based on chaotic advection theory to deliver targets across a conventional glass slide array. Microarrays were printed with a pattern of 102 identical probe spots containing a 65-mer oligonucleotide capture probe. Hybridization of a 725-bp fluorescently labeled target was used to measure average target hybridization levels, local signal-to-noise ratios, and array hybridization uniformity. Dynamic hybridization for 1h with 1 or 10ng of target DNA increased hybridization signal intensities approximately threefold over a 24-h static hybridization. Similarly, a 10- or 60-min dynamic hybridization of 10ng of target DNA increased hybridization signal intensities fourfold over a 24h static hybridization. In time course studies, static hybridization reached a maximum within 8 to 12h using either 1 or 10ng of target. In time course studies using the dynamic hybridization chamber, hybridization using 1ng of target increased to a maximum at 4h and that using 10ng of target did not vary over the time points tested. In comparison to static hybridization, dynamic hybridization reduced the signal-to-noise ratios threefold and reduced spot-to-spot variation twofold. Therefore, we conclude that dynamic hybridization based on a chaotic mixer design improves both the speed of hybridization and the maximum level of hybridization while increasing signal-to-noise ratios and reducing spot-to-spot variation.
DNA↗
TGF-beta1 induction of the adenine nucleotide translocator 1 in astrocytes occurs through Smads and Sp1 transcription factors.
BACKGROUND: The adenine nucleotide translocator 1 (Ant1) is an inner mitochondrial membrane protein involved with energy mobilization during oxidative phosphorylation. We recently showed that rodent Ant1 is upregulated by transforming growth factor-beta (TGF-beta) in reactive astrocytes following CNS injury. In the present study, we describe the molecular mechanisms by which TGF-beta1 regulates Ant1 gene expression in cultured primary rodent astrocytes. RESULTS: Transcription reporter analysis verified that TGF-beta1 regulates transcription of the mouse Ant1 gene, but not the gene encoding the closely related Ant2 isoform. A 69 basepair TGF-beta1 responsive element of the Ant1 promoter was also identified. Electrophoretic mobility shift assays demonstrated that astrocyte nuclear proteins bind to this response element and TGF-beta1 treatment recruits additional nuclear protein binding to this element. Antibody supershift and promoter deletion analyses demonstrated that Sp1 consensus binding sites in the RE are important for TGF-beta1 regulation of Ant1 in astrocytes. Additionally, we demonstrate that Smad 2, 3 and 4 transcription factors are expressed in injured cerebral cortex and in primary astrocyte cultures. TGF-beta1 activated Smad transcription factors also contribute to Ant1 regulation since transcription reporter assays in the presence of dominant negative (DN)-Smads 3 and 4 significantly reduced induction of Ant1 by TGF-beta1. CONCLUSION: The specific regulation of Ant1 by TGF-beta1 in astrocytes involves a cooperative interaction of both Smad and Sp1 binding elements located immediately upstream of the transcriptional start site. The first report of expression of Smads 2, 3 and 4 in astrocytes provided here is consistent with a regulation of Ant1 gene expression by these transcription factors in reactive astrocytes. Given the similarity in TGF-beta1 regulation of Ant1 with other genes that are thought to promote neuronal survival, this interaction may represent a general mechanism that underlies the neuroprotective effects of TGF-beta1.
Adenine Nucleotide Translocator 1↗
Anatomical methods for voxelation of the mammalian brain.
Voxelation allows high-throughput acquisition of three-dimensional gene expression patterns in the brain through analysis of spatially registered voxels (cubes). The method results in multiple volumetric maps of gene expression analogous to the images reconstructed in biomedical imaging techniques. An important issue for voxelation is the development of approaches to anchor correctly harvested voxels to the underlying anatomy. Here, we describe experiments to identify fixation and cryopreservation protocols for improved registration of harvested voxels with neuroanatomical structures. Paraformaldehyde fixation greatly reduced RNA recovery as judged by ribosomal RNA abundance. However, gene expression signals from paraformaldehyde-fixed samples were not appreciably diminished as judged by average signal-noise ratios from microarrays, highlighting the difficulties of accurate quantitation of cross-linked RNA. Additional use of cryoprotection helped to improve further RNA recovery and signal from fixed tissue. It appears that the best protocol to provide the necessary resolution of neuroanatomical information in voxelation entails a controlled dose of fixation and thorough cryoprotection, complemented by histological staining.
Animals↗
A training-testing approach to the molecular classification of resected non-small cell lung cancer.
PURPOSE: RNA expression patterns associated with non-small cell lung cancer subclassification have been reported, but there are substantial differences in the key genes and clinical features of these subsets casting doubt on their biological significance. EXPERIMENTAL DESIGN: In this study, we used a training-testing approach to test the reliability of cDNA microarray-based classifications of resected human non-small cell lung cancers (NSCLCs) analyzed by cDNA microarray. RESULTS: Groups of genes were identified that were able to differentiate primary tumors from normal lung and lung metastases, as well as identify known histological subgroups of NSCLCs. Groups of genes were identified to discriminate sample clusters. A blinded confirmatory set of tumors was correctly classified by using these patterns. Some histologically diagnosed large cell tumors were clearly classified by expression profile analysis as being either adenocarcinoma or squamous cell carcinoma, indicating that this group of tumors may not be genetically homogeneous. High alpha-actinin-4 expression was identified as highly correlated with poor prognosis. CONCLUSIONS: These results demonstrate that gene expression profiling can identify molecular classes of resected NSCLCs that correctly classifies a blinded test cohort, and correlates with and supplements standard histological evaluation.
Actinin↗
Effects of relative humidity and buffer additives on the contact printing of microarrays by quill pins.
DNA microarrays printed with quill pins exhibit significant variation in probe DNA spots. Interspot variations and nonuniform distribution of probe within spots are major sources of experimental uncertainty in microarray analysis. To gain better insight into the sources of variation, we analyzed 450 consecutive depositions printed at relative humidities between 40 and 80% using three print buffers. Increasing relative humidity improved printing performance by delaying pin failure but did not reduce the variability in spot characteristics. Adding either betaine or dimethyl sulfoxide (DMSO) to the print buffer also improved quill pin performance. Least interspot variation was observed with the DMSO additive printed at 80% relative humidity, but this additive also resulted in the greatest intraspot variation. Least intraspot variation was observed with 1.5M betaine printed at 60% relative humidity, but these conditions produced microarrays with high interspot variability. Evaporation of printing solution from the quill reservoir appeared to be the primary cause of interspot and intraspot variations. Our studies indicate that relative humidity and printing solution additives reduce evaporation. Based on the spot variability requirements for a particular application, humidity and additives may be chosen to optimize either inter- or intraspot variability.
Buffers↗
Profiling genes related to mitochondrial function in mice treated with N-methyl-4-phenyl-1,2,3,6-tetrahydropyridine.
Since mitochondrial dysfunction plays an important role in the pathogenesis of dopaminergic neurodegeneration in Parkinson's disease, we determined the expression of genes related to mitochondrial function in the substantia nigra of mice treated with N-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) using a cDNA array. MPTP treatment significantly depleted striatal dopamine, but did not result in apparent neuronal loss in the substantia nigra at 3 and 18 days post-treatment. We also examined changes in genes in the hypothalamus, a region containing dopaminergic neurons that are relatively resistant to MPTP. Finally, we confirmed those genes identified by microarrays as differentially expressed in the substantia nigra but not in the hypothalamus using in situ hybridization. Our results demonstrated that MPTP significantly changed the expressions of six genes in nigral neurons, four of which were related to the mitochondrial electron transport chain: the NADH-ubiquinone oxidoreductase 13 kDa B subunit, the NADH-ubiquinone oxidoreductase MNLL subunit, cytochrome c, and the cytochrome c oxidase Va subunit. Two other differentially expressed genes were the dihydropyridine-sensitive L-type calcium channel alpha-2 subunit precursor and type III alpha-1 procollagen. None of these six genes are encoded by mitochondrial DNA. The potential significance of these gene alterations in the context of Parkinson's disease is discussed.
1-Methyl-4-phenyl-1,2,3,6-tetrahydropyridine↗