Perry L. Miller

Large-scale analysis of the yeast genome by transposon tagging and gene disruption

Economical methods by which gene function may be analysed on a genomic scale are relatively scarce. To fill this need, we have developed a transposon-tagging strategy for the genome-wide analysis of disruption phenotypes, gene expression and protein localization, and have applied this method to the large-scale analysis of gene function in the budding yeast Saccharomyces cerevisiae. Here we present the largest collection of defined yeast mutants ever generated within a single genetic background—a collection of over 11,000 strains, each carrying a transposon inserted within a region of the genome expressed during vegetative growth and/or sporulation. These insertions affect nearly 2,000 annotated genes, representing about one-third of the 6,200 predicted genes in the yeast genome. We have used this collection to determine disruption phenotypes for nearly 8,000 strains using 20 different growth conditions; the resulting data sets were clustered to identify groups of functionally related genes. We have also identified over 300 previously non-annotated open reading frames and analysed by indirect immunofluorescence over 1,300 transposon-tagged proteins. In total, our study encompasses over 260,000 data points, constituting the largest functional analysis of the yeast genome ever undertaken.

Distribution of NF-B-binding sites across human chromosome 22

We have mapped the chromosomal binding site distribution of a transcription factor in human cells. The NF-κB family of transcription factors plays an essential role in regulating the induction of genes involved in several physiological processes, including apoptosis, immunity, and inflammation. The binding sites of the NF-κB family member p65 were determined by using chromatin immunoprecipitation and a genomic microarray of human chromosome 22 DNA. Sites of binding were observed along the entire chromosome in both coding and noncoding regions, with an enrichment at the 5′ end of genes. Strikingly, a significant proportion of binding was seen in intronic regions, demonstrating that transcription factor binding is not restricted to promoter regions. NF-κB binding was also found at genes whose expression was regulated by tumor necrosis factor α, a known inducer of NF-κB-dependent gene expression, as well as adjacent to genes whose expression is not affected by tumor necrosis factor α. Many of these latter genes are either known to be activated by NF-κB under other conditions or are consistent with NF-κBs role in the immune and apoptotic responses. Our results suggest that binding is not restricted to promoter regions and that NF-κB binding occurs at a significant number of genes whose expression is not altered, thereby suggesting that binding alone is not sufficient for gene activation.

CREB binds to multiple loci on human chromosome 22.

ABSTRACT The cyclic AMP-responsive element-binding protein (CREB) is an important transcription factor that can be activated by hormonal stimulation and regulates neuronal function and development. An unbiased, global analysis of where CREB binds has not been performed. We have mapped for the first time the binding distribution of CREB along an entire human chromosome. Chromatin immunoprecipitation of CREB-associated DNA and subsequent hybridization of the associated DNA to a genomic DNA microarray containing all of the nonrepetitive DNA of human chromosome 22 revealed 215 binding sites corresponding to 192 different loci and 100 annotated potential gene targets. We found binding near or within many genes involved in signal transduction and neuronal function. We also found that only a small fraction of CREB binding sites lay near well-defined 5′ ends of genes; the majority of sites were found elsewhere, including introns and unannotated regions. Several of the latter lay near novel unannotated transcriptionally active regions. Few CREB targets were found near full-length cyclic AMP response element sites; the majority contained shorter versions or close matches to this sequence. Several of the CREB targets were altered in their expression by treatment with forskolin; interestingly, both induced and repressed genes were found. Our results provide novel molecular insights into how CREB mediates its functions in humans.

Organization of Heterogeneous Scientific Data Using the EAV/CR Representation

Entity-attribute-value (EAV) representation is a means of organizing highly heterogeneous data using a relatively simple physical database schema. EAV representation is widely used in the medical domain, most notably in the storage of data related to clinical patient records. Its potential strengths suggest its use in other biomedical areas, in particular research databases whose schemas are complex as well as constantly changing to reflect evolving knowledge in rapidly advancing scientific domains. When deployed for such purposes, the basic EAV representation needs to be augmented significantly to handle the modeling of complex objects (classes) as well as to manage interobject relationships. The authors refer to their modification of the basic EAV paradigm as EAV/CR (EAV with classes and relationships). They describe EAV/CR representation with examples from two biomedical databases that use it.

The Neuroscience Information Framework: A Data and Knowledge Environment for Neuroscience

With support from the Institutes and Centers forming the NIH Blueprint for Neuroscience Research, we have designed and implemented a new initiative for integrating access to and use of Web-based neuroscience resources: the Neuroscience Information Framework. The Framework arises from the expressed need of the neuroscience community for neuroinformatic tools and resources to aid scientific inquiry, builds upon prior development of neuroinformatics by the Human Brain Project and others, and directly derives from the Society for Neuroscience’s Neuroscience Database Gateway. Partnered with the Society, its Neuroinformatics Committee, and volunteer consultant-collaborators, our multi-site consortium has developed: (1) a comprehensive, dynamic, inventory of Web-accessible neuroscience resources, (2) an extended and integrated terminology describing resources and contents, and (3) a framework accepting and aiding concept-based queries. Evolving instantiations of the Framework may be viewed at http://nif.nih.gov, http://neurogateway.org, and other sites as they come on line.

The Human Brain Project: neuroinformatics tools for integrating, searching and modeling multidisciplinary neuroscience data

What is neuroinformatics? What is the Human Brain Project? Why should you care? Supported by a consortium of US funding agencies, the Human Brain Project aims to bring to the analysis of brain function the same advantages of Internet-accessible databases and database tools that have been crucial to the development of molecular biology and the Human Genome Project. The much greater complexity of neural data, however, makes this a far more challenging task. As a pilot project in this new initiative, we review some of the progress that has been made and indicate some of the problems, challenges and opportunities that lie ahead.

An integrated approach for finding overlooked genes in yeast

We report here the discovery of 137 previously unappreciated genes in yeast through a widely applicable and highly scalable approach integrating methods of gene-trapping, microarray-based expression analysis, and genome-wide homology searching. Our approach is a multistep process in which expressed sequences are first trapped using a modified transposon that produces protein fusions to β-galactosidase (β-gal); non-annotated open reading frames (ORFs) translated as β-gal chimeras are selected as a candidate pool of potential genes. To verify expression of these sequences, labeled RNA is hybridized against a microarray of oligonucleotides designed to detect gene transcripts in a strand-specific manner. In complement to this experimental method, novel genes are also identified in silico by homology to previously annotated proteins. As these methods are capable of identifying both short ORFs and antisense ORFs, our approach provides an effective supplement to current gene-finding schemes. In total, the genes discovered using this approach constitute 2% of the yeast genome and represent a wealth of overlooked biology.

Towards effective and rewarding data sharing.

Recently issued NIH policy statement and implementation guidelines (National Institutes of Health, 2003) promote the sharing of research data. While urging that “all data should be considered for data sharing” and “data should be made as widely and freely available as possible” the current policy requires only high-direct-cost (>US

ALFRED: an allele frequency database for diverse populations and DNA polymorphisms

500,000/yr) grantees to share research data, starting 1 October 2003. Data sharing is central to science, and we agree that data should be made available.

TRIPLES: a database of gene function in Saccharomyces cerevisiae

We have developed a publicly accessible database (ALFRED, the ALlele FREquency Database) that catalogues allele frequency data for a wide range of population samples and DNA polymorphisms. This database is web-accessible through our laboratory (Kidd Lab) Web site: http://info.med.yale.edu/genetics/kkidd. ALFRED currently contains data on 60 populations and 156 genetic systems including single nucleotide polymorphisms (SNPs), short tandem repeat polymorphisms (STRPs), variable number of tandem repeats (VNTRs) and insertion-deletion polymorphisms. While data are not available for all population-DNA polymorphism combinations, over 2000 allele frequency tables have been entered. Our database is designed (i) to address our specific research requirements as well as broader scientific objectives; (ii) to allow researchers and interested educators to easily navigate and retrieve data of interest to them; and (iii) to integrate links to other related public databases such as dbSNP, GenBank and PubMed.