基因本体论的蟾蜍bHLH转录因子功能富集分布

基因本体论是国际上标准的基因和蛋白质功能知识词汇.利用基因本体论的功能富集分布比较和分析了两种蟾蜍bHLH基因分子功能分布特点.结果发现,两种蟾蜍的bHLH基因均有显著富集分布的GO注释语句,其中转录调控活性( GO:0030528)、转录调控(GO:0045449)、DNA结合(GO:0003677)、RNA代谢过程调控(G0:0051252)、DNA依赖的转录调控(GO:0006355)、转录(G0:0006350)和转录因子活性(GO:0003700)等频率很高,表明这些GO注释是蟾蜍bHLH基因常见的功能;此外,蟾蜍bHLH基因在肌肉器官发育、神经管和眼发育等一些重要的发育或生理过程的基因表达调控中发挥着重要的作用.     

The Gene Ontology's Reference Genome Project: A Unified Framework for Functional Annotation across Species

The Gene Ontology (GO) is a collaborative effort that provides structured vocabularies for annotating the molecular function, biological role, and cellular location of gene products in a highly systematic way and in a species-neutral manner with the aim of unifying the representation of gene function across different organisms. Each contributing member of the GO Consortium independently associates GO terms to gene products from the organism(s) they are annotating. Here we introduce the Reference Genome project, which brings together those independent efforts into a unified framework based on the evolutionary relationships between genes in these different organisms. The Reference Genome project has two primary goals: to increase the depth and breadth of annotations for genes in each of the organisms in the project, and to create data sets and tools that enable other genome annotation efforts to infer GO annotations for homologous genes in their organisms. In addition, the project has several important incidental benefits, such as increasing annotation consistency across genome databases, and providing important improvements to the GO's logical structure and biological content.     

Immunological function in marine invertebrates: Responses to environmental perturbation

The inception of ecological immunology has led to an increase in the number of studies investigating the impact of environmental stressors on host immune defence mechanisms. This in turn has led to an increased understanding of the importance of invertebrate groups for immunological research. This review discusses the advances made within marine invertebrate ecological immunology over the past decade. By demonstrating the environmental stressors tested, the immune parameters typically investigated, and the species that have received the greatest level of investigation, this review provides a critical assessment of the field of marine invertebrate ecological immunology. In highlighting the methodologies employed within this field, our current inability to understand the true ecological significance of any immune dysfunction caused by environmental stressors is outlined. Additionally, a number of examples are provided in which studies successfully demonstrate a measure of immunocompetence through alterations in disease resistance and organism survival to a realized pathogenic threat. Consequently, this review highlights the potential to advance our current understanding of the ecological and evolutionary significance of environmental stressor related immune dysfunction. Furthermore, the potential for the advancement of our understanding of the immune system of marine invertebrates, through the incorporation of newly emerging and novel molecular techniques, is emphasized.     

Towards an integrated network of coral immune mechanisms

Reef-building corals form bio-diverse marine ecosystems of high societal and economic value, but are in significant decline globally due, in part, to rapid climatic changes. As immunity is a predictor of coral disease and thermal stress susceptibility, a comprehensive understanding of this new field will likely provide a mechanistic explanation for ecological-scale trends in reef declines. Recently, several strides within coral immunology document defence mechanisms that are consistent with those of both invertebrates and vertebrates, and which span the recognition, signalling and effector response phases of innate immunity. However, many of these studies remain discrete and unincorporated into the wider fields of invertebrate immunology or coral biology. To encourage the rapid development of coral immunology, we comprehensively synthesize the current understanding of the field in the context of general invertebrate immunology, and highlight fundamental gaps in our knowledge. We propose a framework for future research that we hope will stimulate directional studies in this emerging field and lead to the elucidation of an integrated network of coral immune mechanisms. Once established, we are optimistic that coral immunology can be effectively applied to pertinent ecological questions, improve current prediction tools and aid conservation efforts.     

Using GOstats to test gene lists for GO term association

MOTIVATION: Functional analyses based on the association of Gene Ontology (GO) terms to genes in a selected gene list are useful bioinformatic tools and the GOstats package has been widely used to perform such computations. In this paper we report significant improvements and extensions such as support for conditional testing. RESULTS: We discuss the capabilities of GOstats, a Bioconductor package written in R, that allows users to test GO terms for over or under-representation using either a classical hypergeometric test or a conditional hypergeometric that uses the relationships among GO terms to decorrelate the results. AVAILABILITY: GOstats is available as an R package from the Bioconductor project: http://bioconductor.org     

Transplantation tolerance from a historical perspective

Although transplantation immunology as a distinctive field began with the development of experimental models that showed the feasibility of bone marrow transplantation, organ engraftment was accomplished first in humans, and was thought for many years to occur by drastically different mechanisms. Here, we present our view of the concepts of allograft acceptance and acquired tolerance from a historical perspective, and attempt to amalgamate them into simple and unifying rules that might guide improvements in clinical therapy.     

Knowledge acquisition,consistency checking and concurrency control for Gene Ontology (GO)

MOTIVATION: A critical element of the computational infrastructure required for functional genomics is a shared language for communicating biological data and knowledge. The Gene Ontology (GO; http://www.geneontology.org) provides a taxonomy of concepts and their attributes for annotating gene products. As GO increases in size, its ongoing construction and maintenance becomes more challenging. In this paper, we assess the applicability of a Knowledge Base Management System (KBMS), Protégé-2000, to the maintenance and development of GO. RESULTS: We transferred GO to Protégé-2000 in order to evaluate its suitability for GO. The graphical user interface supported browsing and editing of GO. Tools for consistency checking identified minor inconsistencies in GO and opportunities to reduce redundancy in its representation. The Protégé Axiom Language proved useful for checking ontological consistency. The PROMPT tool allowed us to track changes to GO. Using Protégé-2000, we tested our ability to make changes and extensions to GO to refine the semantics of attributes and classify more concepts. AVAILABILITY: Gene Ontology in Protégé-2000 and the associated code are located at http://smi.stanford.edu/projects/helix/gokbms/. Protégé-2000 is available from http://protege.stanford.edu.     

A probabilistic generative model for GO enrichment analysis

The Gene Ontology (GO) is extensively used to analyze all types of high-throughput experiments. However, researchers still face several challenges when using GO and other functional annotation databases. One problem is the large number of multiple hypotheses that are being tested for each study. In addition, categories often overlap with both direct parents/descendents and other distant categories in the hierarchical structure. This makes it hard to determine if the identified significant categories represent different functional outcomes or rather a redundant view of the same biological processes. To overcome these problems we developed a generative probabilistic model which identifies a (small) subset of categories that, together, explain the selected gene set. Our model accommodates noise and errors in the selected gene set and GO. Using controlled GO data our method correctly recovered most of the selected categories, leading to dramatic improvements over current methods for GO analysis. When used with microarray expression data and ChIP-chip data from yeast and human our method was able to correctly identify both general and specific enriched categories which were overlooked by other methods.     

What fires prometheus? The link between inflammation and regeneration following chronic liver injury

Liver progenitor cells (LPCs) play a major role in the regeneration process after chronic liver damage, giving rise to hepatocytes and cholangiocytes. Thus, they provide a cell-based therapeutic alternative to organ transplant, the current treatment of choice for end-stage liver disease. In recent years, much attention has focused on unravelling the cytokines and growth factors that underlie this response. Liver regeneration following acute damage is achieved by proliferation of mature hepatocytes; yet similar cytokines, most related to the inflammatory process, are implicated in both acute and chronic liver regeneration. Thus, many recent studies represent attempts to identify LPC-specific factors. This review summarises our current understanding of LPC biology with a particular focus on the liver inflammatory response being associated with the induction of LPCs in the liver. We will describe: (i) the pathways of liver regeneration following acute and chronic damage; (ii) the similarities and differences between the two pathways; (iii) the liver inflammatory environment; (iv) the unique features of liver immunology as well as (v) the interactions between liver immune cells and LPCs. Combining data from studies on the LPC-driven regeneration process with the knowledge in the field of liver immunology will improve our understanding of the LPC response and allow us to regulate these cells in vivo and in vitro for future therapeutic strategies to treat chronic liver disease.     

Bioinformatic strategies for better understanding of immune function

Novartis Foundation sponsored a Symposium which brought together a group of experimental immunologists, theoretical immunologists, and bioinformaticians to discuss the new field of immunoinformatics. The discussion focused on immunological databases, antigen processing and presentation, immunogenomics, host-pathogen interactions, and mathematical modelling of the immune system. A main conclusion of the meeting is the critical role played by immunoinformatics in current immunology research. In particular, immunoinformatics provides a foundation for the emerging fields of systems immunology and immunogenomics.     

Additional gene ontology structure for improved biological reasoning

MOTIVATION: The Gene Ontology (GO) is a widely used terminology for gene product characterization in, for example, interpretation of biology underlying microarray experiments. The current GO defines term relationships within each of the independent subontologies: molecular function, biological process and cellular component. However, it is evident that there also exist biological relationships between terms of different subontologies. Our aim was to connect the three subontologies to enable GO to cover more biological knowledge, enable a more consistent use of GO and provide new opportunities for biological reasoning. RESULTS: We propose a new structure, the Second Gene Ontology Layer, capturing biological relations not directly reflected in the present ontology structure. Given molecular functions, these paths identify biological processes where the molecular functions are involved and cellular components where they are active. The current Second Layer contains 6271 validated paths, covering 54% of the molecular functions of GO and can be used to render existing gene annotation sets more complete and consistent. Applying Second Layer paths to a set of 4223 human genes, increased biological process annotations by 24% compared to publicly available annotations and reproduced 30% of them. AVAILABILITY: The Second GO is publicly available through the GO Annotation Toolbox (GOAT.no): http://www.goat.no.     

Special feature for the Olympics: effects of exercise on the immune system. Overview: exercise immunology

The review articles in this special feature reflect the current status of knowledge in the field of exercise immunology, with a focus on how exercise affects the human immune system and the health implications for resistance to infections and neoplastic diseases. In an Olympic year, the emphasis of exercise immunology research tends to be on elite athletes and the prevention of infections in the quest for optimum performance. However, research presented in this issue also covers recreational athletes, as well as highlighting the benefits of exercise for our ageing population.     

The gene ontology categorizer

The Gene Ontology Categorizer, developed jointly by the Los Alamos National Laboratory and Procter & Gamble Corp., provides a capability for the categorization task in the Gene Ontology (GO): given a list of genes of interest, what are the best nodes of the GO to summarize or categorize that list? The motivating question is from a drug discovery process, where after some gene expression analysis experiment, we wish to understand the overall effect of some cell treatment or condition by identifying 'where' in the GO the differentially expressed genes fall: 'clustered' together in one place? in two places? uniformly spread throughout the GO? 'high', or 'low'? In order to address this need, we view bio-ontologies more as combinatorially structured databases than facilities for logical inference, and draw on the discrete mathematics of finite partially ordered sets (posets) to develop data representation and algorithms appropriate for the GO. In doing so, we have laid the foundations for a general set of methods to address not just the categorization task, but also other tasks (e.g. distances in ontologies and ontology merger and exchange) in both the GO and other bio-ontologies (such as the Enzyme Commission database or the MEdical Subject Headings) cast as hierarchically structured taxonomic knowledge systems.     

Ontology annotation: mapping genomic regions to biological function

With numerous whole genomes now in hand, and experimental data about genes and biological pathways on the increase, a systems approach to biological research is becoming essential. Ontologies provide a formal representation of knowledge that is amenable to computational as well as human analysis, an obvious underpinning of systems biology. Mapping function to gene products in the genome consists of two, somewhat intertwined enterprises: ontology building and ontology annotation. Ontology building is the formal representation of a domain of knowledge; ontology annotation is association of specific genomic regions (which we refer to simply as 'genes', including genes and their regulatory elements and products such as proteins and functional RNAs) to parts of the ontology. We consider two complementary representations of gene function: the Gene Ontology (GO) and pathway ontologies. GO represents function from the gene's eye view, in relation to a large and growing context of biological knowledge at all levels. Pathway ontologies represent function from the point of view of biochemical reactions and interactions, which are ordered into networks and causal cascades. The more mature GO provides an example of ontology annotation: how conclusions from the scientific literature and from evolutionary relationships are converted into formal statements about gene function. Annotations are made using a variety of different types of evidence, which can be used to estimate the relative reliability of different annotations.     

The representation of heart development in the gene ontology

An understanding of heart development is critical in any systems biology approach to cardiovascular disease. The interpretation of data generated from high-throughput technologies (such as microarray and proteomics) is also essential to this approach. However, characterizing the role of genes in the processes underlying heart development and cardiovascular disease involves the non-trivial task of data analysis and integration of previous knowledge. The Gene Ontology (GO) Consortium provides structured controlled biological vocabularies that are used to summarize previous functional knowledge for gene products across all species. One aspect of GO describes biological processes, such as development and signaling.In order to support high-throughput cardiovascular research, we have initiated an effort to fully describe heart development in GO; expanding the number of GO terms describing heart development from 12 to over 280. This new ontology describes heart morphogenesis, the differentiation of specific cardiac cell types, and the involvement of signaling pathways in heart development. This work also aligns GO with the current views of the heart development research community and its representation in the literature. This extension of GO allows gene product annotators to comprehensively capture the genetic program leading to the developmental progression of the heart. This will enable users to integrate heart development data across species, resulting in the comprehensive retrieval of information about this subject.The revised GO structure, combined with gene product annotations, should improve the interpretation of data from high-throughput methods in a variety of cardiovascular research areas, including heart development, congenital cardiac disease, and cardiac stem cell research. Additionally, we invite the heart development community to contribute to the expansion of this important dataset for the benefit of future research in this area.     

Towards a consensus on datasets and evaluation metrics for developing B-cell epitope prediction tools

A B-cell epitope is the three-dimensional structure within an antigen that can be bound to the variable region of an antibody. The prediction of B-cell epitopes is highly desirable for various immunological applications, but has presented a set of unique challenges to the bioinformatics and immunology communities. Improving the accuracy of B-cell epitope prediction methods depends on a community consensus on the data and metrics utilized to develop and evaluate such tools. A workshop, sponsored by the National Institute of Allergy and Infectious Disease (NIAID), was recently held in Washington, DC to discuss the current state of the B-cell epitope prediction field. Many of the currently available tools were surveyed and a set of recommendations was devised to facilitate improvements in the currently existing tools and to expedite future tool development. An underlying theme of the recommendations put forth by the panel is increased collaboration among research groups. By developing common datasets, standardized data formats, and the means with which to consolidate information, we hope to greatly enhance the development of B-cell epitope prediction tools.     

A systems‐based approach to investigate dose‐ and time‐dependent methylmercury‐induced gene expression response in C57BL/6 mouse embryos undergoing neurulation

BACKGROUND: Aberrations during neurulation due to genetic and/or environmental factors underlie a variety of adverse developmental outcomes, including neural tube defects (NTDs). Methylmercury (MeHg) is a developmental neurotoxicant and teratogen that perturbs a wide range of biological processes/pathways in animal models, including those involved in early gestation (e.g., cell cycle, cell differentiation). Yet, the relationship between these MeHg‐linked effects and changes in gestational development remains unresolved. Specifically, current information lacks mechanistic comparisons across dose or time for MeHg exposure during neurulation. These detailed investigations are crucial for identifying sensitive indicators of toxicity and for risk assessment applications. METHODS: Using a systems‐based toxicogenomic approach, we examined dose‐ and time‐dependent effects of MeHg on gene expression in C57BL/6 mouse embryos during cranial neural tube closure, assessing for significantly altered genes and associated Gene Ontology (GO) biological processes. Using the GO‐based application GO‐Quant, we quantitatively assessed dose‐ and time‐dependent effects on gene expression within enriched GO biological processes impacted by MeHg. RESULTS: We observed MeHg to significantly alter expression of 883 genes, including several genes (e.g., Vangl2, Celsr1, Ptk7, Twist, Tcf7) previously characterized to be crucial for neural tube development. Significantly altered genes were associated with development cell adhesion, cell cycle, and cell differentiation–related GO biological processes. CONCLUSIONS: Our results suggest that MeHg‐induced impacts within these biological processes during gestational development may underlie MeHg‐induced teratogenic and neurodevelopmental toxicity outcomes. Birth Defects Res (Part B) 89:188–200, 2010. © 2010 Wiley‐Liss, Inc.     

Process attributes in bio-ontologies

ABSTRACT: BACKGROUND: Biomedical processes can provide essential information about the (mal-) functioning of an organism and are thus frequently represented in biomedical terminologies and ontologies, including the GO Biological Process branch. These processes often need to be described and categorised in terms of their attributes, such as rates or regularities. The adequate representation of such process attributes has been a contentious issue in bio-ontologies recently; and domain ontologies have correspondingly developed ad hoc workarounds that compromise interoperability and logical consistency. RESULTS: We present a design pattern for the representation of process attributes that is compatible with upper ontology frameworks such as BFO and BioTop. Our solution rests on two key tenets: firstly, that many of the sorts of process attributes which are biomedically interesting can be characterised by the ways that repeated parts of such processes constitute, in combination, an overall process; secondly, that entities for which a full logical definition can be assigned do not need to be treated as primitive within a formal ontology framework. We apply this approach to the challenge of modelling and automatically classifying examples of normal and abnormal rates and patterns of heart beating processes, and discuss the expressivity required in the underlying ontology representation language. We provide full definitions for process attributes at increasing levels of domain complexity. CONCLUSIONS: We show that a logical definition of process attributes is feasible, though limited by the expressivity of DL languages so that the creation of primitives is still necessary. This finding may endorse current formal upper-ontology frameworks as a way of ensuring consistency, interoperability and clarity.     

Contemplations on the paradigm of self and nonself discrimination and on other concepts ruling contemporary immunology.

The present paper critically deals with the widely accepted but nevertheless in recent years controversely discussed paradigms that the immune system may discriminate between self and nonself and harmless and dangerous, respectively. Concepts like these, and there are some more in actual immunology, -show that contemporary life sciences still are biased towards teleologic and anthropocentric thinking, though the existence of a priori purpose directed causalities has been denied by philosophers from time immemorial. A problem of current immunological language is in this context the usage of numerous metaphors predominantly borrowed from the field of brain functions, a usance that holds the risk of aggravating misinterpretations. In this context some of the paradigms ruling current immunology will be reviewed and discussed in the light of an emergent understanding of the fundamental principles of complex systems being widely spread in our inanimate and animate world.