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Biomedical subjects

Paul Bertone

Publications and source records attributed to Paul Bertone.

At least 19 recordsLinked to original sources
PubMed2006

Transcriptional regulatory networks in bacteria: from input signals to output responses.

Transcriptional regulatory systems play a central role in coordinating bacterial responses to diverse stimuli. These systems can be studied in progressive stages: from input signals to the final output. At the input stage, transcription factors (TFs) can be classified by their activation from endogenous or exogenous stimuli; in Escherichia coli, up to three-quarters of regulators are estimated to respond directly to extracellular signals through phosphorylation and small-molecule binding. At the processing stage, the signals feed into a densely connected network. The endogenous regulators form most of the connections between TFs and, by dynamically rewiring interactions, they coordinate and distribute the appropriate responses for distinct cellular conditions. At the output stage, network motifs (which are specific patterns of interconnections within a small group of TFs and target genes) determine the precise temporal programme of gene expression changes. Eventually, these components of the regulatory system could be assembled to describe complex bacterial behaviour at the level of whole organisms.

Bacteria↗
PubMed2006

Target hub proteins serve as master regulators of development in yeast.

To understand the organization of the transcriptional networks that govern cell differentiation, we have investigated the transcriptional circuitry controlling pseudohyphal development in Saccharomyces cerevisiae. The binding targets of Ste12, Tec1, Sok2, Phd1, Mga1, and Flo8 were globally mapped across the yeast genome. The factors and their targets form a complex binding network, containing patterns characteristic of autoregulation, feedback and feed-forward loops, and cross-talk. Combinatorial binding to intergenic regions was commonly observed, which allowed for the identification of a novel binding association between Mga1 and Flo8, in which Mga1 requires Flo8 for binding to promoter regions. Further analysis of the network showed that the promoters of MGA1 and PHD1 were bound by all of the factors used in this study, identifying them as key target hubs. Overexpression of either of these two proteins specifically induced pseudohyphal growth under noninducing conditions, highlighting them as master regulators of the system. Our results indicate that target hubs can serve as master regulators whose activity is sufficient for the induction of complex developmental responses and therefore represent important regulatory nodes in biological networks.

Blotting, Western↗
PubMed2005

Design optimization methods for genomic DNA tiling arrays.

A recent development in microarray research entails the unbiased coverage, or tiling, of genomic DNA for the large-scale identification of transcribed sequences and regulatory elements. A central issue in designing tiling arrays is that of arriving at a single-copy tile path, as significant sequence cross-hybridization can result from the presence of non-unique probes on the array. Due to the fragmentation of genomic DNA caused by the widespread distribution of repetitive elements, the problem of obtaining adequate sequence coverage increases with the sizes of subsequence tiles that are to be included in the design. This becomes increasingly problematic when considering complex eukaryotic genomes that contain many thousands of interspersed repeats. The general problem of sequence tiling can be framed as finding an optimal partitioning of non-repetitive subsequences over a prescribed range of tile sizes, on a DNA sequence comprising repetitive and non-repetitive regions. Exact solutions to the tiling problem become computationally infeasible when applied to large genomes, but successive optimizations are developed that allow their practical implementation. These include an efficient method for determining the degree of similarity of many oligonucleotide sequences over large genomes, and two algorithms for finding an optimal tile path composed of longer sequence tiles. The first algorithm, a dynamic programming approach, finds an optimal tiling in linear time and space; the second applies a heuristic search to reduce the space complexity to a constant requirement. A Web resource has also been developed, accessible at http://tiling.gersteinlab.org, to generate optimal tile paths from user-provided DNA sequences.

Algorithms↗
PubMed2005

Global changes in STAT target selection and transcription regulation upon interferon treatments.

The STAT (signal transducer and activator of transcription) proteins play a crucial role in the regulation of gene expression, but their targets and the manner in which they select them remain largely unknown. Using chromatin immunoprecipitation and DNA microarray analysis (ChIP-chip), we have identified the regions of human chromosome 22 bound by STAT1 and STAT2 in interferon-treated cells. Analysis of the genomic loci proximal to these binding sites introduced new candidate STAT1 and STAT2 target genes, several of which are affiliated with proliferation and apoptosis. The genes on chromosome 22 that exhibited interferon-induced up- or down-regulated expression were determined and correlated with the STAT-binding site information, revealing the potential regulatory effects of STAT1 and STAT2 on their target genes. Importantly, the comparison of STAT1-binding sites upon interferon (IFN)-gamma and IFN-alpha treatments revealed dramatic changes in binding locations between the two treatments. The IFN-alpha induction revealed nonconserved STAT1 occupancy at IFN-gamma-induced sites, as well as novel sites of STAT1 binding not evident in IFN-gamma-treated cells. Many of these correlated with binding by STAT2, but others were STAT2 independent, suggesting that multiple mechanisms direct STAT1 binding to its targets under different activation conditions. Overall, our results reveal a wealth of new information regarding IFN/STAT-binding targets and also fundamental insights into mechanisms of regulation of gene expression in different cell states.

Antineoplastic Agents↗
PubMed2005

Applications of DNA tiling arrays to experimental genome annotation and regulatory pathway discovery.

Microarrays have become a popular and important technology for surveying global patterns in gene expression and regulation. A number of innovative experiments have extended microarray applications beyond the measurement of mRNA expression levels, in order to uncover aspects of large-scale chromosome function and dynamics. This has been made possible due to the recent development of tiling arrays, where all non-repetitive DNA comprising a chromosome or locus is represented at various sequence resolutions. Since tiling arrays are designed to contain the entire DNA sequence without prior consultation of existing gene annotation, they enable the discovery of novel transcribed sequences and regulatory elements through the unbiased interrogation of genomic loci. The implementation of such methods for the global analysis of large eukaryotic genomes presents significant technical challenges. Nonetheless, tiling arrays are expected to become instrumental for the genome-wide identification and characterization of functional elements. Combined with computational methods to relate these data and map the complex interactions of transcriptional regulators, tiling array experiments can provide insight toward a more comprehensive understanding of fundamental molecular and cellular processes.

Gene Expression Profiling↗
PubMed2005

Issues in the analysis of oligonucleotide tiling microarrays for transcript mapping.

Traditional microarrays use probes complementary to known genes to quantitate the differential gene expression between two or more conditions. Genomic tiling microarray experiments differ in that probes that span a genomic region at regular intervals are used to detect the presence or absence of transcription. This difference means the same sets of biases and the methods for addressing them are unlikely to be relevant to both types of experiment. We introduce the informatics challenges arising in the analysis of tiling microarray experiments as open problems to the scientific community and present initial approaches for the analysis of this nascent technology.

Algorithms↗
PubMed2005

Multi-species microarrays reveal the effect of sequence divergence on gene expression profiles.

Interspecies comparisons of gene expression levels will increase our understanding of the evolution of transcriptional mechanisms and help to identify targets of natural selection. This approach holds particular promise for apes, as many human-specific adaptations are thought to result from differences in gene expression rather than in coding sequence. To date, however, all studies directly comparing interspecies gene expression have been performed on single-species arrays, so that it has been impossible to distinguish differential hybridization due to sequence mismatches from underlying expression differences. To evaluate the severity of this potential problem, we constructed a new multiprimate cDNA array using probes from human, chimpanzee, orangutan, and rhesus. We find a large effect of sequence divergence on hybridization signal, even in the closest pair of species, human and chimpanzee. By comparing single-species array analyses with results from multispecies arrays, we examine how estimates of differential gene expression are affected by sequence divergence. Our results indicate that naive use of single-species arrays in direct interspecies comparisons can yield spurious results.

Animals↗
PubMed2005

Advances in functional protein microarray technology.

Numerous innovations in high-throughput protein production and microarray surface technologies have enabled the development of addressable formats for proteins ordered at high spatial density. Protein array implementations have largely focused on antibody arrays for high-throughput protein profiling. However, it is also possible to construct arrays of full-length, functional proteins from a library of expression clones. The advent of protein-based microarrays allows the global observation of biochemical activities on an unprecedented scale, where hundreds or thousands of proteins can be simultaneously screened for protein-protein, protein-nucleic acid, and small molecule interactions. This technology holds great potential for basic molecular biology research, disease marker identification, toxicological response profiling and pharmaceutical target screening.

Animals↗
PubMed2004

Global identification of human transcribed sequences with genome tiling arrays.

Elucidating the transcribed regions of the genome constitutes a fundamental aspect of human biology, yet this remains an outstanding problem. To comprehensively identify coding sequences, we constructed a series of high-density oligonucleotide tiling arrays representing sense and antisense strands of the entire nonrepetitive sequence of the human genome. Transcribed sequences were located across the genome via hybridization to complementary DNA samples, reverse-transcribed from polyadenylated RNA obtained from human liver tissue. In addition to identifying many known and predicted genes, we found 10,595 transcribed sequences not detected by other methods. A large fraction of these are located in intergenic regions distal from previously annotated genes and exhibit significant homology to other mammalian proteins.

Animals↗
PubMed2004

Fast optimal genome tiling with applications to microarray design and homology search.

In this paper, we consider several variations of the following basic tiling problem: given a sequence of real numbers with two size-bound parameters, we want to find a set of tiles of maximum total weight such that each tiles satisfies the size bounds. A solution to this problem is important to a number of computational biology applications such as selecting genomic DNA fragments for PCR-based amplicon microarrays and performing homology searches with long sequence queries. Our goal is to design efficient algorithms with linear or near-linear time and space in the normal range of parameter values for these problems. For this purpose, we first discuss the solution to a basic online interval maximum problem via a sliding-window approach and show how to use this solution in a nontrivial manner for many of the tiling problems introduced. We also discuss NP-hardness results and approximation algorithms for generalizing our basic tiling problem to higher dimensions. Finally, computational results from applying our tiling algorithms to genomic sequences of five model eukaryotes are reported.

Algorithms↗
PubMed2004

CREB binds to multiple loci on human chromosome 22.

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.

Binding Sites↗
PubMed2003

Distribution of NF-kappaB-binding sites across human chromosome 22.

We have mapped the chromosomal binding site distribution of a transcription factor in human cells. The NF-kappaB 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-kappaB 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-kappaB binding was also found at genes whose expression was regulated by tumor necrosis factor alpha, a known inducer of NF-kappaB-dependent gene expression, as well as adjacent to genes whose expression is not affected by tumor necrosis factor alpha. Many of these latter genes are either known to be activated by NF-kappaB under other conditions or are consistent with NF-kappaB's role in the immune and apoptotic responses. Our results suggest that binding is not restricted to promoter regions and that NF-kappaB binding occurs at a significant number of genes whose expression is not altered, thereby suggesting that binding alone is not sufficient for gene activation.

Binding Sites↗
PubMed2003

ExpressYourself: A modular platform for processing and visualizing microarray data.

DNA microarrays are widely used in biological research; by analyzing differential hybridization on a single microarray slide, one can detect changes in mRNA expression levels, increases in DNA copy numbers and the location of transcription factor binding sites on a genomic scale. Having performed the experiments, the major challenge is to process large, noisy datasets in order to identify the specific array elements that are significantly differentially hybridized. This normally requires aggregating different, often incompatible programs into a multi-step pipeline. Here we present ExpressYourself, a fully integrated platform for processing microarray data. In completely automated fashion, it will correct the background array signal, normalize the Cy5 and Cy3 signals, score levels of differential hybridization, combine the results of replicate experiments, filter problematic regions of the array and assess the quality of individual and replicate experiments. ExpressYourself is designed with a highly modular architecture so various types of microarray analysis algorithms can readily be incorporated as they are developed; for example, the system currently implements several normalization methods, including those that simultaneously consider signal intensity and slide location. The processed data are presented using a web-based graphical interface to facilitate comparison with the original images of the array slides. In particular, Express Yourself is able to regenerate images of the original microarray after applying various steps of processing, which greatly facilities identification of position-specific artifacts. The program is freely available for use at http://bioinfo.mbb.yale.edu/expressyourself.

Algorithms↗
PubMed2003

SPINE 2: a system for collaborative structural proteomics within a federated database framework.

We present version 2 of the SPINE system for structural proteomics. SPINE is available over the web at http://nesg.org. It serves as the central hub for the Northeast Structural Genomics Consortium, allowing collaborative structural proteomics to be carried out in a distributed fashion. The core of SPINE is a laboratory information management system (LIMS) for key bits of information related to the progress of the consortium in cloning, expressing and purifying proteins and then solving their structures by NMR or X-ray crystallography. Originally, SPINE focused on tracking constructs, but, in its current form, it is able to track target sample tubes and store detailed sample histories. The core database comprises a set of standard relational tables and a data dictionary that form an initial ontology for proteomic properties and provide a framework for large-scale data mining. Moreover, SPINE sits at the center of a federation of interoperable information resources. These can be divided into (i) local resources closely coupled with SPINE that enable it to handle less standardized information (e.g. integrated mailing and publication lists), (ii) other information resources in the NESG consortium that are inter-linked with SPINE (e.g. crystallization LIMS local to particular laboratories) and (iii) international archival resources that SPINE links to and passes on information to (e.g. TargetDB at the PDB).

Cooperative Behavior↗
PubMed2003

The transcriptional activity of human Chromosome 22.

A DNA microarray representing nearly all of the unique sequences of human Chromosome 22 was constructed and used to measure global-transcriptional activity in placental poly(A)(+) RNA. We found that many of the known, related and predicted genes are expressed. More importantly, our study reveals twice as many transcribed bases as have been reported previously. Many of the newly discovered expressed fragments were verified by RNA blot analysis and a novel technique called differential hybridization mapping (DHM). Interestingly, a significant fraction of these novel fragments are expressed antisense to previously annotated introns. The coding potential of these novel expressed regions is supported by their sequence conservation in the mouse genome. This study has greatly increased our understanding of the biological information encoded on a human chromosome. To facilitate the dissemination of these results to the scientific community, we have developed a comprehensive Web resource to present the findings of this study and other features of human Chromosome 22 at http://array.mbb.yale.edu/chr22.

Amino Acid Sequence↗
PubMed2003

Identification of pseudogenes in the Drosophila melanogaster genome.

Pseudogenes are copies of genes that cannot produce a protein. They can be detected from disruptions to their apparent coding sequence, caused by frameshifts and premature stop codons. They are classed as either processed pseudogenes (made by reverse transcription from an mRNA) or duplicated pseudogenes, arising from duplication in the genomic DNA and subsequent disablement. Historically, there is anecdotal evidence that the fruit fly (Drosophila melanogaster) has few pseudogenes. Investigators have linked this to a high deletion rate of genomic DNA, for which there is evidence from genetic experiments on genome size. Here, we apply a homology-based pipeline that was developed previously to identify pseudogenes in other eukaryotic genomes, to the fruit fly, so as to derive the first complete survey of its pseudogene population. We find approximately 100 pseudogenes, with at least a sixth of these as candidate processed pseudogenes. This gives a much lower proportion of pseudogenes (compared with the size of the proteome) than in the genomes of other eukaryotes for which data are available (human, nematode and budding yeast). Closest matching proteins to Drosophila pseudogenes are significantly longer than the average protein in its proteome (up to approximately 60% more than the average protein's length), in contrast to the situation in the three other eukaryotic genomes. This may be due to the persistence of fragments of longer genes. In the fly pseudogene population, we found most pseudogenes for serine proteases (which are more abundant in the Drosophila lineage compared with the other eukaryotes), immunoglobulin-motif-containing proteins and cytochromes P450. Data on the sequences and positions of the putative pseudogenes are available at: http://www.pseudogene.org/fly. The detection of a small number of pseudogenes in the Drosophila genome and the higher mean length for the closest matching proteins to pseudogenes (possibly because remnants of genes encoding longer proteins are more likely to persist) are further evidence for a high deletion rate of genomic DNA in the fruit fly. The data are useful for molecular evolution study in Drosophila.

Animals↗
PubMed2002

Complex transcriptional circuitry at the G1/S transition in Saccharomyces cerevisiae.

In the yeast Saccharomyces cerevisiae, SBF (Swi4-Swi6 cell cycle box binding factor) and MBF (MluI binding factor) are the major transcription factors regulating the START of the cell cycle, a time just before DNA replication, bud growth initiation, and spindle pole body (SPB) duplication. These two factors bind to the promoters of 235 genes, but bind less than a quarter of the promoters upstream of genes with peak transcript levels at the G1 phase of the cell cycle. Several functional categories, which are known to be crucial for G1/S events, such as SPB duplication/migration and DNA synthesis, are under-represented in the list of SBF and MBF gene targets. SBF binds the promoters of several other transcription factors, including HCM1, PLM2, POG1, TOS4, TOS8, TYE7, YAP5, YHP1, and YOX1. Here, we demonstrate that these factors are targets of SBF using an independent assay. To further elucidate the transcriptional circuitry that regulates the G1-to-S-phase progression, these factors were epitope-tagged and their binding targets were identified by chIp-chip analysis. These factors bind the promoters of genes with roles in G1/S events including DNA replication, bud growth, and spindle pole complex formation, as well as the general activities of mitochondrial function, transcription, and protein synthesis. Although functional overlap exists between these factors and MBF and SBF, each of these factors has distinct functional roles. Most of these factors bind the promoters of other transcription factors known to be cell cycle regulated or known to be important for cell cycle progression and differentiation processes indicating that a complex network of transcription factors coordinates the diverse activities that initiate a new cell cycle.

Binding Sites↗