Seeking a new biology through text mining.

Tens of thousands of biomedical journals exist, and the deluge of new articles in the biomedical sciences is leading to information overload. Hence, there is much interest in text mining, the use of computational tools to enhance the human ability to parse and understand complex text.

Mismatch oligonucleotides in human and yeast: guidelines for probe design on tiling microarrays.

BACKGROUND: Mismatched oligonucleotides are widely used on microarrays to differentiate specific from nonspecific hybridization. While many experiments rely on such oligos, the hybridization behavior of various degrees of mismatch (MM) structure has not been extensively studied. Here, we present the results of two large-scale microarray experiments on S. cerevisiae and H. sapiens genomic DNA, to explore MM oligonucleotide behavior with real sample mixtures under tiling-array conditions. RESULTS: We examined all possible nucleotide substitutions at the central position of 36-nucleotide probes, and found that nonspecific binding by MM oligos depends upon the individual nucleotide substitutions they incorporate: C-->A, C-->G and T-->A (yielding purine-purine mispairs) are most disruptive, whereas A-->X were least disruptive. We also quantify a marked GC skew effect: substitutions raising probe GC content exhibit higher intensity (and vice versa). This skew is small in highly-expressed regions (+/- 0.5% of total intensity range) and large (+/- 2% or more) elsewhere. Multiple mismatches per oligo are largely additive in effect: each MM added in a distributed fashion causes an additional 21% intensity drop relative to PM, three-fold more disruptive than adding adjacent mispairs (7% drop per MM). CONCLUSION: We investigate several parameters for oligonucleotide design, including the effects of each central nucleotide substitution on array signal intensity and of multiple MM per oligo. To avoid GC skew, individual substitutions should not alter probe GC content. RNA sample mixture complexity may increase the amount of nonspecific hybridization, magnify GC skew and boost the intensity of MM oligos at all levels.

Genomic analysis of insertion behavior and target specificity of mini-Tn7 and Tn3 transposons in Saccharomyces cerevisiae.

Transposons are widely employed as tools for gene disruption. Ideally, they should display unbiased insertion behavior, and incorporate readily into any genomic DNA to which they are exposed. However, many transposons preferentially insert at specific nucleotide sequences. It is unclear to what extent such bias affects their usefulness as mutagenesis tools. Here, we examine insertion site specificity and global insertion behavior of two mini-transposons previously used for large-scale gene disruption in Saccharomyces cerevisiae: Tn3 and Tn7. Using an expanded set of insertion data, we confirm that Tn3 displays marked preference for the AT-rich 5 bp consensus site TA[A/T]TA, whereas Tn7 displays negligible target site preference. On a genome level, both transposons display marked non-uniform insertion behavior: certain sites are targeted far more often than expected, and both distributions depart drastically from Poisson. Thus, to compare their insertion behavior on a genome level, we developed a windowed Kolmogorov-Smirnov (K-S) test to analyze transposon insertion distributions in sequence windows of various sizes. We find that when scored in large windows (>300 bp), both Tn3 and Tn7 distributions appear uniform, whereas in smaller windows, Tn7 appears uniform while Tn3 does not. Thus, both transposons are effective tools for gene disruption, but Tn7 does so with less duplication and a more uniform distribution, better approximating the behavior of the ideal transposon.

Publishing perishing? Towards tomorrow's information architecture.

Scientific articles are tailored to present information in human-readable aliquots. Although the Internet has revolutionized the way our society thinks about information, the traditional text-based framework of the scientific article remains largely unchanged. This format imposes sharp constraints upon the type and quantity of biological information published today. Academic journals alone cannot capture the findings of modern genome-scale inquiry. Like many other disciplines, molecular biology is a science of facts: information inherently suited to database storage. In the past decade, a proliferation of public and private databases has emerged to house genome sequence, protein structure information, functional genomics data and more; these digital repositories are now a vital component of scientific communication. The next challenge is to integrate this vast and ever-growing body of information with academic journals and other media. To truly integrate scientific information we must modernize academic publishing to exploit the power of the Internet. This means more than online access to articles, hyperlinked references and web-based supplemental data; it means making articles fully computer-readable with intelligent markup and Structured Digital Abstracts.Here, we examine the changing roles of scholarly journals and databases. We present our vision of the optimal information architecture for the biosciences, and close with tangible steps to improve our handling of scientific information today while paving the way for an expansive central index in the future.

Personalized genomic medicine with a patchwork, partially owned genome.

"His book was known as the Book of Sand, because neither the book nor the sand have any beginning or end." - Jorge Luis BorgesThe human genome is a three billion-letter recipe for the genesis of a human being, directing development from a single-celled embryo to the trillions of adult cells. Since the sequencing of the human genome was announced in 2001, researchers have an increased ability to discern the genetic basis for diseases. This reference genome has opened the door to genomic medicine, aimed at detecting and understanding all genetic variations of the human genome that contribute to the manifestation and progression of disease. The overarching vision of genomic (or "personalized") medicine is to custom-tailor each treatment for maximum effectiveness in an individual patient. Detecting the variation in a patient's deoxyribonucleic acid (DNA), ribonucleic acid (RNA), and protein structures is no longer an insurmountable hurdle. Today, the challenge for genomic medicine lies in contextualizing those myriad genetic variations in terms of their functional consequences for a person's health and development throughout life and in terms of that patient's susceptibility to disease and differential clinical responses to medication. Additionally, several recent developments have complicated our understanding of the nominal human genome and, thereby, altered the progression of genomic medicine. In this brief review, we shall focus on these developments and examine how they are changing our understanding of our genome.

Uncovering trends in gene naming.

We take stock of current genetic nomenclature and attempt to organize strange and notable gene names. We categorize, for instance, those that involve a naming system transferred from another context (for example, Pavlov's dogs). We hope this analysis provides clues to better steer gene naming in the future.

Transcription factor binding site identification in yeast: a comparison of high-density oligonucleotide and PCR-based microarray platforms.

In recent years, techniques have been developed to map transcription factor binding sites using chromatin immunoprecipitation combined with DNA microarrays (chIP chip). Initially, polymerase chain reaction (PCR)-based DNA arrays were used for the chIP chip procedure, however, high-density oligonucleotide (HDO) arrays, which allow for the production of thousands more features per array, have emerged as a competing array platform. To compare the two platforms, data from chIP chip analysis performed for three factors (Tec1, Ste12, and Sok2) using both HDO and PCR arrays under identical experimental conditions were compared. HDO arrays provided increased reproducibility and sensitivity, detecting approximately three times more binding events than the PCR arrays while also showing increased accuracy. The increased resolution provided by the HDO arrays also allowed for the identification of multiple binding peaks in close proximity and of novel binding events such as binding within ORFs. The HDO array platform provides a far more robust array system by all measures than PCR-based arrays, all of which is directly attributable to the large number of probes available.

Divergence of transcription factor binding sites across related yeast species.

Characterization of interspecies differences in gene regulation is crucial for understanding the molecular basis of both phenotypic diversity and evolution. By means of chromatin immunoprecipitation and DNA microarray analysis, the divergence in the binding sites of the pseudohyphal regulators Ste12 and Tec1 was determined in the yeasts Saccharomyces cerevisiae, S. mikatae, and S. bayanus under pseudohyphal conditions. We have shown that most of these sites have diverged across these species, far exceeding the interspecies variation in orthologous genes. A group of Ste12 targets was shown to be bound only in S. mikatae and S. bayanus under pseudohyphal conditions. Many of these genes are targets of Ste12 during mating in S. cerevisiae, indicating that specialization between the two pathways has occurred in this species. Transcription factor binding sites have therefore diverged substantially faster than ortholog content. Thus, gene regulation resulting from transcription factor binding is likely to be a major cause of divergence between related species.

Predicting essential genes in fungal genomes.

Essential genes are required for an organism's viability, and the ability to identify these genes in pathogens is crucial to directed drug development. Predicting essential genes through computational methods is appealing because it circumvents expensive and difficult experimental screens. Most such prediction is based on homology mapping to experimentally verified essential genes in model organisms. We present here a different approach, one that relies exclusively on sequence features of a gene to estimate essentiality and offers a promising way to identify essential genes in unstudied or uncultured organisms. We identified 14 characteristic sequence features potentially associated with essentiality, such as localization signals, codon adaptation, GC content, and overall hydrophobicity. Using the well-characterized baker's yeast Saccharomyces cerevisiae, we employed a simple Bayesian framework to measure the correlation of each of these features with essentiality. We then employed the 14 features to learn the parameters of a machine learning classifier capable of predicting essential genes. We trained our classifier on known essential genes in S. cerevisiae and applied it to the closely related and relatively unstudied yeast Saccharomyces mikatae. We assessed predictive success in two ways: First, we compared all of our predictions with those generated by homology mapping between these two species. Second, we verified a subset of our predictions with eight in vivo knockouts in S. mikatae, and we present here the first experimentally confirmed essential genes in this species.

TOS9 regulates white-opaque switching in Candida albicans.

In Candida albicans, the a1-alpha2 complex represses white-opaque switching, as well as mating. Based upon the assumption that the a1-alpha2 corepressor complex binds to the gene that regulates white-opaque switching, a chromatinimmunoprecipitation-microarray analysis strategy was used to identify 52 genes that bound to the complex. One of these genes, TOS9, exhibited an expression pattern consistent with a "master switch gene." TOS9 was only expressed in opaque cells, and its gene product, Tos9p, localized to the nucleus. Deletion of the gene blocked cells in the white phase, misexpression in the white phase caused stable mass conversion of cells to the opaque state, and misexpression blocked temperature-induced mass conversion from the opaque state to the white state. A model was developed for the regulation of spontaneous switching between the opaque state and the white state that includes stochastic changes of Tos9p levels above and below a threshold that induce changes in the chromatin state of an as-yet-unidentified switching locus. TOS9 has also been referred to as EAP2 and WOR1.

Analyzing cellular biochemistry in terms of molecular networks.

One way to understand cells and circumscribe the function of proteins is through molecular networks. These networks take a variety of forms including webs of protein-protein interactions, regulatory circuits linking transcription factors and targets, and complex pathways of metabolic reactions. We first survey experimental techniques for mapping networks (e.g., the yeast two-hybrid screens). We then turn our attention to computational approaches for predicting networks from individual protein features, such as correlating gene expression levels or analyzing sequence coevolution. All the experimental techniques and individual predictions suffer from noise and systematic biases. These problems can be overcome to some degree through statistical integration of different experimental datasets and predictive features (e.g., within a Bayesian formalism). Next, we discuss approaches for characterizing the topology of networks, such as finding hubs and analyzing subnetworks in terms of common motifs. Finally, we close with perspectives on how network analysis represents a preliminary step toward a systems approach for modeling cells.

Large-scale mutagenesis of the yeast genome using a Tn7-derived multipurpose transposon.

We present here an unbiased and extremely versatile insertional library of yeast genomic DNA generated by in vitro mutagenesis with a multipurpose element derived from the bacterial transposon Tn7. This mini-Tn7 element has been engineered such that a single insertion can be used to generate a lacZ fusion, gene disruption, and epitope-tagged gene product. Using this transposon, we generated a plasmid-based library of approximately 300,000 mutant alleles; by high-throughput screening in yeast, we identified and sequenced 9032 insertions affecting 2613 genes (45% of the genome). From analysis of 7176 insertions, we found little bias in Tn7 target-site selection in vitro. In contrast, we also sequenced 10,174 Tn3 insertions and found a markedly stronger preference for an AT-rich 5-base pair target sequence. We further screened 1327 insertion alleles in yeast for hypersensitivity to the chemotherapeutic cisplatin. Fifty-one genes were identified, including four functionally uncharacterized genes and 25 genes involved in DNA repair, replication, transcription, and chromatin structure. In total, the collection reported here constitutes the largest plasmid-based set of sequenced yeast mutant alleles to date and, as such, should be singularly useful for gene and genome-wide functional analysis.