Toshiaki Baba

Screening the single nucleotide polymorphisms in patients with internal carotid artery stenosis by oligonucleotide-based custom DNA array.

In this article we try to discuss nonparametric linkage (NPL) score functions within a broad and quite general framework. The main focus of the paper is the structure, derivation principles and interpretations of the score function entity itself. We define and discuss several families of one-locus score function definitions, i.e. the implicit, explicit and optimal ones. Some generalizations and comments to the two-locus, unconditional and conditional, cases are included as well. Although this article mainly aims at serving as an overview, where the concept of score functions are put into a covering context, we generalize the noncentrality parameter (NCP) optimal score functions in Ängquist et al. (2007) to facilitate—through weighting—for incorporation of several plausible distinct genetic models. Since the genetic model itself most oftenly is to some extent unknown this facilitates weaker prior assumptions with respect to plausible true disease models without loosing the property of NCP-optimality. Moreover, we discuss general assumptions and properties of score functions in the above sense. For instance, the concept of identical by descent (IBD) sharing structures and score function equivalence are discussed in some detail.Background: Microarray technology has become highly valuable for identifying complex global changes in gene expression patterns. The assignment of functional information to these complex patterns remains a challenging task in effectively interpreting data and correlating results from across experiments, projects and laboratories. Methods which allow the rapid and robust evaluation of multiple functional hypotheses increase the power of individual researchers to data mine gene expression data more efficiently. Results: We have developed (gene set matrix analysis) GSMA as a useful method for the rapid testing of group-wise up- or down-regulation of gene expression simultaneously for multiple lists of genes (gene sets) against entire distributions of gene expression changes (datasets) for single or multiple experiments. The utility of GSMA lies in its flexibility to rapidly poll gene sets related by known biological function or as designated solely by the end-user against large numbers of datasets simultaneously. Conclusions: GSMA provides a simple and straightforward method for hypothesis testing in which genes are tested by groups across multiple datasets for patterns of expression enrichment.Loops represent an important part of protein structures. The study of loop is critical for two main reasons: First, loops are often involved in protein function, stability and folding. Second, despite improvements in experimental and computational structure prediction methods, modeling the conformation of loops remains problematic. Here, we present a structural classification of loops, ArchDB, a mine of information with application in both mentioned fields: loop structure prediction and function prediction. ArchDB (http://sbi.imim.es/archdb) is a database of classified protein loop motifs. The current database provides four different classification sets tailored for different purposes. ArchDB-40, a loop classification derived from SCOP40, well suited for modeling common loop motifs. Since features relevant to loop structure or function can be more easily determined on well-populated clusters, we have developed ArchDB-95, a loop classification derived from SCOP95. This new classification set shows a ~40% increase in the number of subclasses, and a large 7-fold increase in the number of putative structure/function-related subclasses. We also present ArchDB-EC, a classification of loop motifs from enzymes, and ArchDB-KI, a manually annotated classification of loop motifs from kinases. Information about ligand contacts and PDB sites has been included in all classification sets. Improvements in our classification scheme are described, as well as several new database features, such as the ability to query by conserved annotations, sequence similarity, or uploading 3D coordinates of a protein. The lengths of classified loops range between 0 and 36 residues long. ArchDB offers an exhaustive sampling of loop structures. Functional information about loops and links with related biological databases are also provided. All this information and the possibility to browse/query the database through a web-server outline an useful tool with application in the comparative study of loops, the analysis of loops involved in protein function and to obtain templates for loop modeling.Background Bioassays are routinely used to evaluate the toxicity of test agents. Experimental designs for bioassays are largely encompassed by fixed effects linear models. In toxicogenomics studies where DNA arrays measure mRNA levels, the tissue samples are typically generated in a bioassay. These measurements introduce additional sources of variation, which must be properly managed to obtain valid tests of treatment effects. Results An analysis of covariance model is developed which combines a fixed-effects linear model for the bioassay with important variance components associated with DNA array measurements. These models can accommodate the dominant characteristics of measurements from DNA arrays, and they account for technical variation associated with normalization, spots, dyes, and batches as well as the biological variation associated with the bioassay. An example illustrates how the model is used to identify valid designs and to compare competing designs. Conclusions Many toxicogenomics studies are bioassays which measure gene expression using DNA arrays. These studies can be designed and analyzed using standard methods with a few modifications to account for characteristics of array measurements, such as multiple endpoints and normalization. As much as possible, technical variation associated with probes, dyes, and batches are managed by blocking treatments within these sources of variation. An example shows how some practical constraints can be accommodated by this modelling and how it allows one to objectively compare competing designs.A well-known folk-law in biology is that there is no general law in biology because of exceptions. In her recent elegant essay E.F. Keller gave a particular nice presentation on the exceptions to rules or laws in biology [1]. Her example of scaling laws was especially illuminative. Nevertheless, for this cherished folk-law the present author is wondering about its exceptions, too. Several examples immediately jump into his minds. One, of course, would be the folk-law itself: It had no exception in biology. This would be a bit disappointing because it would only permit us to work as what the cartographers did in J.L. Borges’ fable [2]. Though eventually a map as big and as detail as the empire itself might be obtained, one would then ask where is the understanding within such an immense object? More disappointedly, such folk-law is really not biological. It has been used by some philosophers to argue against the unity of science [3]. Another example is distinctively biological and would be more exciting, and the author believes its existence should be not surprising to biologists: Evolution by Variation and Selection by Darwin and Wallace. To the author’s knowledge this dynamical law has no exception in biology. Nevertheless, under the influence of above folk-law this marvelous dynamics has been named Darwin’s principle, just falling short to regard it as a fundamental law [4]. Any scientists and mathematicians would know better the difference between a principle and an equation or a law. Here the word “principle”, though powerful and insightful, implies imprecision and possible fallacy, such as the Dirichlet’s principle in mathematics [5]. The Darwin’s principle has perhaps been used in this sense in biology [1,4]. It may be the time to change such attitude. Indeed it has been expressed that there may be general laws in biology [6], and fundamental biological laws have been articulated [7]. Based on generalizations of Fisher’s fundamental theorem of natural selection [8] and Wright’s adaptive landscape [9], this dynamical law of Darwin and Wallace had recently been formulated by the author into a concise set of mathematical equations [10]. Within such formulation it had been further shown that the classical Newtonian dynamics in physics, including Newton’s renowned second law, may be regarded as one of its special cases. Thus, by all accepted standards in both physical and biological sciences, the dynamical law of Darwin and Wallace has indeed achieved the status of universal laws. It will certainly play an increasingly important role in our understanding of biology at systems level. The author would like to further speculate that such a universal law may actually be one of what physicists have been searching for during past 150 years. For practicing biologists, the more pressing questions would be: If there are such fundamental laws, what would be their utilities in applications? Are they of any help to us to understand the diverse biological phenomena in some concrete manners? etc. Two immediate applications of the fundamental biological law may be mentioned here, which have already been elaborated from different perspectives. First, there is an issue of robustness vs evolvability [11–13]. It is clear that Wright’s adaptive landscape provides a quantitative measure of robustness in addition to its metaphoric function. The variations encoded in the fundamental theorem of natural selection provide an instant framework to address the evolvability from two angles: the ability of the system to move from one adaptive peak to another and the implied possibility of stochastic change in the dynamical components. Second, there is another issue of cooperation [14–15]. The existence of multiple adaptive peaks common in evolutionary dynamics is a sufficient condition to show the ubiquitous nonlinear interaction, including cooperation. It is now well established that without cooperation it is impossible to maintain the robustness and efficiency of phage lambda genetic switch, one of most elementary biological models [16]. This genetic switch is also an example of illustrating the robustness and evolvability. Finally, let’s come back to the Borges dilemma. Borges already suggested that the one-to-one map of the imagined cartographers is not useful. The present author wishes to venture further. In his opinion the cartographer’s situation would never happen in biology. We would never be able to exhaust the secrets of Nature. The number of wonders is simply too immense to be recorded down by all silicon available in our universe. Thus, high through and capable tools have been developed, and will continue to be done, such as DNA sequencer [17], protein chips [18], and numerous bioinformatics platforms [19–21], to empower our ability to deeper and broader interrogate Nature and ourselves. Mega endeavors similar to Human Genome Project will be continued to be done [22–27], along with focused and small projects [16,28–30]. Because of the distinct mathematical characteristics in describing biological phenomena comparing to those in physical sciences, such as the explicit stochastics, combinatory, and hierarchy, in addition to the intrinsic nonlinearity, new mathematical structures is expected to be developed for better and more efficient descriptions, in addition to mathematics motivated by biology [31]. Such activities will be carried out together with our effort to understand fundamental laws in biology and with the vision enabled by such laws and by models derived from them [32]. They may be classified as in the domain of systems biology [30,33].This review deals with computer simulation of biological aging, particularly with the Penna model of 1995. They are based on the mutation accumulation theory of half a century ago. The results agree well with demographical reality, and also with the seemingly contradictory influence of predators on the aging of prey.IMAGE is an application tool, based on the vector quantization method, aiding the discovery of nucleotidic sequences corresponding to Transcription Factor binding sites. Starting from the knowledge of regulation regions of a number of co-expressed genes, the software is able to predict the occurrence of specific motifs of different lengths (starting from 6 base pairs) with a defined number of punctual mutations.Early screening of individuals considered to be at risk for severe internal carotid artery (ICA) stenosis is an important strategy for preventing ischemic cerebral stroke. The purpose of this study is to screening candidate single nucleotide polymorphisms (SNPs) associated with severe ICA stenosis using a newly developed oligonucleotide-based custom DNA array. The subjects consisted of 47 controls and 46 patients with severe ICA stenosis (≥70%) who underwent carotid endarterectomy (CEA). Subjects gave informed consent and we obtained samples of blood and genomic DNA. We studied 8 candidate genes: renin-angiotensin system [angiotensinogen (AGT), angiotensin II receptor type 1 (AGTR1), nitric oxide synthase 3 (NOS3)]; growth factor [hepatocyte growth factor (HGF)]; transgelin (SM22); cytokine [chemokine receptor 2 (CCR2)]; coagulation-fibrinolysis system [5,10-methylenetetrahydrofolate reductase (MTHFR)]; and plasminogen activator inhibitor 1 (PAI-1). Genotyping of candidate SNPs was done with a line probe assay (LiPA) based on an oligonucleotide-based DNA array. Results: The allele frequency of PAI-1 –1965 delG (odds ratio (OR), 0.3; 95% confidence interval (CI), 0.2–0.6) and MTHFR (OR 1.3, 95% CI, 1.0–1.5) were significantly different between controls and cases with ICA stenosis by Fisher’s exact test. Multiple logistic analysis revealed that diabetes mellitus (DM), SNPs in PAI-1 –1965 delG and MTHFR were an independent risk for ICA stenosis. In conclusion, genetic factors of coagulation-fibrinolysis as well as diabetes mellitus (DM) were relevant in ICA stenosis.We performed high-throughput cDNA sequencing in colorectal adenocarcinoma and matching normal colorectal epithelium. All six hundred three genes in the UCSC database that were expressed in colon cancers and contained open reading frames of 1000 nucleotides or less were selected for study (total basepairs/bp, 366,686). 304,350 of these 366,686 bp (83.0%) were amplified and sequenced successfully. Seventy-eight sequence variants present in germline (i.e. normal) as well as matching somatic (i.e. tumor) DNA were discovered, yielding a frequency of 1 variant per 3,902 bp. Fifty-one of these sequence variants were homozygous (26 synonymous, 25 non-synonymous), while 27 were heterozygous (11 synonymous, 16 non-synonymous). Cancer tissue contained only one sequence-altered allele of the gene ATP50, which was present heterozygously alongside the wild-type allele in matching normal epithelium. Despite this relatively large number of bp and genes sequenced, no somatic mutations unique to tumor were found. High-throughput cDNA sequencing is a practical approach for detecting novel sequence variations and alterations in human tumors, such as those of the colon.