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Biomedical subjects

John Quackenbush

Publications and source records attributed to John Quackenbush.

At least 19 recordsLinked to original sources

Marked genomic differences characterize primary and secondary glioblastoma subtypes and identify two distinct molecular and clinical secondary glioblastoma entities.

Glioblastoma is classified into two subtypes on the basis of clinical history: "primary glioblastoma" arising de novo without detectable antecedent disease and "secondary glioblastoma" evolving from a low-grade astrocytoma. Despite their distinctive clinical courses, they arrive at an indistinguishable clinical and pathologic end point highlighted by widespread invasion and resistance to therapy and, as such, are managed clinically as if they are one disease entity. Because the life history of a cancer cell is often reflected in the pattern of genomic alterations, we sought to determine whether primary and secondary glioblastomas evolve through similar or different molecular pathogenetic routes. Clinically annotated primary and secondary glioblastoma samples were subjected to high-resolution copy number analysis using oligonucleotide-based array comparative genomic hybridization. Unsupervised classification using genomic nonnegative matrix factorization methods identified three distinct genomic subclasses. Whereas one corresponded to clinically defined primary glioblastomas, the remaining two stratified secondary glioblastoma into two genetically distinct cohorts. Thus, this global genomic analysis showed wide-scale differences between primary and secondary glioblastomas that were previously unappreciated, and has shown for the first time that secondary glioblastoma is heterogeneous in its molecular pathogenesis. Consistent with these findings, analysis of regional recurrent copy number alterations revealed many more events unique to these subclasses than shared. The pathobiological significance of these shared and subtype-specific copy number alterations is reinforced by their frequent occurrence, resident genes with clear links to cancer, recurrence in diverse cancer types, and apparent association with clinical outcome. We conclude that glioblastoma is composed of at least three distinct molecular subtypes, including novel subgroups of secondary glioblastoma, which may benefit from different therapeutic strategies.

Astrocytoma↗

A simple spreadsheet-based, MIAME-supportive format for microarray data: MAGE-TAB.

BACKGROUND: Sharing of microarray data within the research community has been greatly facilitated by the development of the disclosure and communication standards MIAME and MAGE-ML by the MGED Society. However, the complexity of the MAGE-ML format has made its use impractical for laboratories lacking dedicated bioinformatics support. RESULTS: We propose a simple tab-delimited, spreadsheet-based format, MAGE-TAB, which will become a part of the MAGE microarray data standard and can be used for annotating and communicating microarray data in a MIAME compliant fashion. CONCLUSION: MAGE-TAB will enable laboratories without bioinformatics experience or support to manage, exchange and submit well-annotated microarray data in a standard format using a spreadsheet. The MAGE-TAB format is self-contained, and does not require an understanding of MAGE-ML or XML.

Computational Biology↗

Sonic hedgehog promotes CD4+ T lymphocyte proliferation and modulates the expression of a subset of CD28-targeted genes.

Sonic hedgehog (Shh) is a crucial morphogen in the development of numerous tissues and organs, including the nervous system, gastrointestinal tract and lung. Recent findings suggest that Shh plays an important role in thymocyte development and peripheral T cell function. Here we report that the Shh receptors, patched and smoothened, are expressed in resting and activated T cells and their expression is regulated upon T cell activation. Shh protein is also detected on the surface of freshly isolated T cells. Although exogenous Shh alone does not activate resting T cells, it exhibits co-stimulatory activity which is reflected in its ability to potentiate CD3-mediated proliferation and cytokine production by CD4(+) T cells. The co-stimulatory effect is most prominent at sub-optimal TCR stimulation level. Gene expression analysis reveals that Shh signaling in CD4(+) T cells modulates a different set of transcriptional targets from that in neuronal cells. Furthermore, Shh co-stimulation modulates the expression of a subset of CD28-responsive genes, including cyclin A and B cell translocation gene 2.

Animals↗

Uneven chromosome contraction and expansion in the maize genome.

Maize (Zea mays or corn), both a major food source and an important cytogenetic model, evolved from a tetraploid that arose about 4.8 million years ago (Mya). As a result, maize has extensive duplicated regions within its genome. We have sequenced the two copies of one such region, generating 7.8 Mb of sequence spanning 17.4 cM of the short arm of chromosome 1 and 6.6 Mb (25.6 cM) from the long arm of chromosome 9. Rice, which did not undergo a similar whole genome duplication event, has only one orthologous region (4.9 Mb) on the short arm of chromosome 3, and can be used as reference for the maize homoeologous regions. Alignment of the three regions allowed identification of syntenic blocks, and indicated that the maize regions have undergone differential contraction in genic and intergenic regions and expansion by the insertion of retrotransposable elements. Approximately 9% of the predicted genes in each duplicated region are completely missing in the rice genome, and almost 20% have moved to other genomic locations. Predicted genes within these regions tend to be larger in maize than in rice, primarily because of the presence of predicted genes in maize with larger introns. Interestingly, the general gene methylation patterns in the maize homoeologous regions do not appear to have changed with contraction or expansion of their chromosomes. In addition, no differences in methylation of single genes and tandemly repeated gene copies have been detected. These results, therefore, provide new insights into the diploidization of polyploid species.

Base Sequence↗

Gene expression profiling of lymphoblastoid cell lines from monozygotic twins discordant in severity of autism reveals differential regulation of neurologically relevant genes.

BACKGROUND: The autism spectrum encompasses a set of complex multigenic developmental disorders that severely impact the development of language, non-verbal communication, and social skills, and are associated with odd, stereotyped, repetitive behavior and restricted interests. To date, diagnosis of these neurologically based disorders relies predominantly upon behavioral observations often prompted by delayed speech or aberrant behavior, and there are no known genes that can serve as definitive biomarkers for the disorders. RESULTS: Here we demonstrate, for the first time, that lymphoblastoid cell lines from monozygotic twins discordant with respect to severity of autism and/or language impairment exhibit differential gene expression patterns on DNA microarrays. Furthermore, we show that genes important to the development, structure, and/or function of the nervous system are among the most differentially expressed genes, and that many of these genes map closely in silico to chromosomal regions containing previously reported autism candidate genes or quantitative trait loci. CONCLUSION: Our results provide evidence that novel candidate genes for autism may be differentially expressed in lymphoid cell lines from individuals with autism spectrum disorders. This finding further suggests the possibility of developing a molecular screen for autism based on expressed biomarkers in peripheral blood lymphocytes, an easily accessible tissue. In addition, gene networks are identified that may play a role in the pathophysiology of autism.

Autistic Disorder↗

Discrimination of non-protein-coding transcripts from protein-coding mRNA.

Several recent studies indicate that mammals and other organisms produce large numbers of RNA transcripts that do not correspond to known genes. It has been suggested that these transcripts do not encode proteins, but may instead function as RNAs. However, discrimination of coding and non-coding transcripts is not straightforward, and different laboratories have used different methods, whose ability to perform this discrimination is unclear. In this study, we examine ten bioinformatic methods that assess protein-coding potential and compare their ability and congruency in the discrimination of non-coding from coding sequences, based on four underlying principles: open reading frame size, sequence similarity to known proteins or protein domains, statistical models of protein-coding sequence, and synonymous versus non-synonymous substitution rates. Despite these different approaches, the methods show broad concordance, suggesting that coding and non-coding transcripts can, in general, be reliably discriminated, and that many of the recently discovered extra-genic transcripts are indeed non-coding. Comparison of the methods indicates reasons for unreliable predictions, and approaches to increase confidence further. Conversely and surprisingly, our analyses also provide evidence that as much as approximately 10% of entries in the manually curated protein database Swiss-Prot are erroneous translations of actually non-coding transcripts.

Algorithms↗

Multistrain genetic comparisons reveal CCR5 as a receptor involved in airway hyperresponsiveness.

Asthma is a ubiquitous disease with a broad range of clinical phenotypes. To better understand the complex genetic and environmental interactions underlying asthma, we compared the gene-gene interactions of four genetically distinct mouse strains that demonstrate biologically distinct responses to allergen. Using DNA microarrays and knock-out mouse studies, we showed that CCR5 plays a definitive role in the development of ovalbumin-induced allergic airway inflammatory disease. In addition, gene expression profiling data have revealed other potential novel targets for therapeutics-based research and has enhanced the understanding of the molecular mechanisms underlying the etiology of "asthma."

Animals↗

Physiogenomic resources for rat models of heart, lung and blood disorders.

Cardiovascular disorders are influenced by genetic and environmental factors. The TIGR rodent expression web-based resource (TREX) contains over 2,200 microarray hybridizations, involving over 800 animals from 18 different rat strains. These strains comprise genetically diverse parental animals and a panel of chromosomal substitution strains derived by introgressing individual chromosomes from normotensive Brown Norway (BN/NHsdMcwi) rats into the background of Dahl salt sensitive (SS/JrHsdMcwi) rats. The profiles document gene-expression changes in both genders, four tissues (heart, lung, liver, kidney) and two environmental conditions (normoxia, hypoxia). This translates into almost 400 high-quality direct comparisons (not including replicates) and over 100,000 pairwise comparisons. As each individual chromosomal substitution strain represents on average less than a 5% change from the parental genome, consomic strains provide a useful mechanism to dissect complex traits and identify causative genes. We performed a variety of data-mining manipulations on the profiles and used complementary physiological data from the PhysGen resource to demonstrate how TREX can be used by the cardiovascular community for hypothesis generation.

Animals↗

The TIGR Maize Database.

Maize is a staple crop of the grass family and also an excellent model for plant genetics. Owing to the large size and repetitiveness of its genome, we previously investigated two approaches to accelerate gene discovery and genome analysis in maize: methylation filtration and high C(0)t selection. These techniques allow the construction of gene-enriched genomic libraries by minimizing repeat sequences due to either their methylation status or their copy number, yielding a 7-fold enrichment in genic sequences relative to a random genomic library. Approximately 900,000 gene-enriched reads from maize were generated and clustered into Assembled Zea mays (AZM) sequences. Here we report the current AZM release, which consists of approximately 298 Mb representing 243,807 sequence assemblies and singletons. In order to provide a repository of publicly available maize genomic sequences, we have created the TIGR Maize Database (http://maize.tigr.org). In this resource, we have assembled and annotated the AZMs and used available sequenced markers to anchor AZMs to maize chromosomes. We have constructed a maize repeat database and generated draft sequence assemblies of 287 maize bacterial artificial chromosome (BAC) clone sequences, which we annotated along with 172 additional publicly available BAC clones. All sequences, assemblies and annotations are available at the project website via web interfaces and FTP downloads.

Chromosome Mapping↗

TM4 microarray software suite.

Powerful specialized software is essential for managing, quantifying, and ultimately deriving scientific insight from results of a microarray experiment. We have developed a suite of software applications, known as TM4, to support such gene expression studies. The suite consists of open-source tools for data management and reporting, image analysis, normalization and pipeline control, and data mining and visualization. An integrated MIAME-compliant MySQL database is included. This chapter describes each component of the suite and includes a sample analysis walk-through.

Algorithms↗

Development of the Minimum Information Specification for In Situ Hybridization and Immunohistochemistry Experiments (MISFISHIE).

We describe the creation process of the Minimum Information Specification for In Situ Hybridization and Immunohistochemistry Experiments (MISFISHIE). Modeled after the existing minimum information specification for microarray data, we created a new specification for gene expression localization experiments, initially to facilitate data sharing within a consortium. After successful use within the consortium, the specification was circulated to members of the wider biomedical research community for comment and refinement. After a period of acquiring many new suggested requirements, it was necessary to enter a final phase of excluding those requirements that were deemed inappropriate as a minimum requirement for all experiments. The full specification will soon be published as a version 1.0 proposal to the community, upon which a more full discussion must take place so that the final specification may be achieved with the involvement of the whole community.

Computational Biology↗