Genome-wide gene expression profiles of the developing mouse hippocampus

We have analyzed the developmental molecular programs of the mouse hippocampus, a cortical structure critical for learning and memory, by means of large-scale DNA microarray techniques. Of 11,000 genes and expressed sequence tags examined, 1,926 showed dynamic changes during hippocampal development from embryonic day 16 to postnatal day 30. Gene-cluster analysis was used to group these genes into 16 distinct clusters with striking patterns that appear to correlate with major developmental hallmarks and cellular events. These include genes involved in neuronal proliferation, differentiation, and synapse formation. A complete list of the transcriptional changes has been compiled into a comprehensive gene profile database (http://BrainGenomics.Princeton.edu), which should prove valuable in advancing our understanding of the molecular and genetic programs underlying both the development and the functions of the mammalian brain.

Ancient single origin for Malagasy primates.

We report new evidence that bears decisively on a long-standing controversy in primate systematics. DNA sequence data for the complete cytochrome b gene, combined with an expanded morphological data set, confirm the results of a previous study and again indicate that all extant Malagasy lemurs originated from a single common ancestor. These results, as well as those from other genetic studies, call for a revision of primate classifications in which the dwarf and mouse lemurs are placed within the Afro-Asian lorisiforms. The phylogenetic results, in agreement with paleocontinental data, indicate an African origin for the common ancestor of lemurs and lorises (the Strepsirrhini). The molecular data further suggest the surprising conclusion that lemurs began evolving independently by the early Eocene at the latest. This indicates that the Malagasy primate lineage is more ancient than generally thought and places the split between the two strepsirrhine lineages well before the appearance of known Eocene fossil primates. We conclude that primate origins were marked by rapid speciation and diversification sometime before the late Paleocene.

Gene conversions and unequal crossovers between CYP21 (steroid 21-hydroxylase gene) and CYP21P involve different mechanisms.

Most cases of congenital adrenal hyperplasia, the inherited inability to synthesize cortisol, are caused by mutations in the steroid 21-hydroxylase gene (CYP21). Steroid 21-hydroxylase deficiency is unusual among genetic diseases in that approximately 95% of the mutant alleles have apparently been generated by recombination between a normally active gene (CYP21) and a linked pseudogene (CYP21P). Approximately 20% of mutant alleles carry DNA deletions of 30 kb that have presumably been generated by unequal meiotic crossing-over, whereas 75% carry one or more mutations in CYP21 that are normally found in the CYP21P pseudogene. These latter mutations are termed "gene conversions," although the mechanism by which they are generated is not well understood. To assess the frequency at which these different recombination events occur, we have used PCR to detect de novo deletions and gene conversions in matched sperm and peripheral blood leukocyte DNA samples from normal individuals. Deletions with breakpoints in a 100-bp region in intron 2 and exon 3 were detected in sperm DNA samples with frequencies of approximately 1 in 10(5)-10(6) genomes but were never detected in the matching leukocyte DNA. Gene conversions in the same region occur in approximately 1 in 10(3)-10(5) genomes in both sperm and leukocyte DNA. These data suggest that whereas deletions occur exclusively in meiosis, gene conversions occur during both meiosis and mitosis, or perhaps only during mitosis. Thus, gene conversions must occur by a mechanism distinct from unequal crossing-over.

A novel information theory method for filter feature selection

In this paper, we propose a novel filter for feature selection. Such filter relies on the estimation of the mutual information between features and classes. We bypass the estimation of the probability density function with the aid of the entropic-graphs approximation of Rényi entropy, and the subsequent approximation of the Shannon one. The complexity of such bypassing process does not depend on the number of dimensions but on the number of patterns/samples, and thus the curse of dimensionality is circumvented. We show that it is then possible to outperform a greedy algorithm based on the maximal relevance and minimal redundancy criterion. We successfully test our method both in the contexts of image classification and microarray data classification.

Searching oligo sets of human chromosome 12 using evolutionary strategies

DNA Microarray is a powerful tool to measure the level of a mixed population of nucleic acids at one time, which has great impact in many aspects of life sciences research. In order to distinguish nucleic acids with very similar composition by hybridization, it is necessary to design microarray probes with high specificities and sensitivities. Highly specific probes correspond to probes having unique DNA sequences; whereas highly sensitive probes correspond to those with melting temperature within a desired range and having no secondary structure. The selection of these probes from a set of functional DNA sequences (exons) constitutes a computationally expensive discrete non-linear search problem. We delegate the search task to a simple yet effective Evolution Strategy algorithm. The computational efficiency is also greatly improved by making use of an available bioinformatics tool.

Identifying the molecular phenotype of renal progenitor cells

Although many of the molecular interactions in kidney development are now well understood, the molecules involved in the specification of the metanephric mesenchyme from surrounding intermediate mesoderm and, hence, the formation of the renal progenitor population are poorly characterized. In this study, cDNA microarrays were used to identify genes enriched in the murine embryonic day 10.5 (E10.5) uninduced metanephric mesenchyme, the renal progenitor population, in comparison with more rostral derivatives of the intermediate mesoderm. Microarray data were analyzed using R statistical software to determine accurately genes differentially expressed between these populations. Microarray outliers were biologically verified, and the spatial expression pattern of these genes at E10.5 and subsequent stages of early kidney development was determined by RNA in situ hybridization. This approach identified 21 genes preferentially expressed by the E10.5 metanephric mesenchyme, including Ewing sarcoma homolog, 14-3-3 theta, retinoic acid receptor-alpha, stearoyl-CoA desaturase 2, CD24, and cadherin-11, that may be important in formation of renal progenitor cells. Cell surface proteins such as CD24 and cadherin-11 that were strongly and specifically expressed in the uninduced metanephric mesenchyme and mark the renal progenitor population may prove useful in the purification of renal progenitor cells by FACS. These findings may assist in the isolation and characterization of potential renal stem cells for use in cellular therapies for kidney disease.

Cell cycle alterations in biopsied olfactory neuroepithelium in schizophrenia and bipolar I disorder using cell culture and gene expression analyses

We previously demonstrated that olfactory cultures front individuals with schizophrenia had increased cell proliferation compared to Cultures from healthy controls. The aims of this study were to (a) replicate this observation in a new group Of individuals with schizophrenia, (b) examine the specificity of these findings by including individuals with bipolar I disorder and (c) explore gene expression differences that may underlie cell cycle differences in these diseases. Compared to controls (n = 10), there was significantly more mitosis in schizophrenia patient cultures (it = 8) and significantly more cell death in the bipolar I disorder patient cultures (n=8). Microarray data showed alterations to the cell cycle and phosphatidylinositol signalling pathways in schizophrenia and bipolar I disorder, respectively. Whilst caution is required in the interpretation of the array results, the study provides evidence indicating that cell proliferation and cell death in olfactory neuroepithelial cultures is differentially altered in schizophrenia and bipolar disorder. (c) 2005 Elsevier B.V. All rights reserved.

Development of the Minimum Information Specification for in situ Hybridization and Immunohistochemistry Experiments (MISFISHIE)

We describe the creation process of the Minimum Information Specification for In Situ Hybridization and Immunohistochemistry Experiments (MISFISHIE). Modeled after the existing minimum information specification for microarray data, we created a new specification for gene expression localization experiments, initially to facilitate data sharing within a consortium. After successful use within the consortium, the specification was circulated to members of the wider biomedical research community for comment and refinement. After a period of acquiring many new suggested requirements, it was necessary to enter a final phase of excluding those requirements that were deemed inappropriate as a minimum requirement for all experiments. The full specification will soon be published as a version 1.0 proposal to the community, upon which a more full discussion must take place so that the final specification may be achieved with the involvement of the whole community. This paper is part of the special issue of OMICS on data standards.

The human genome and gene expression profiling

The mapping and sequencing of the human genome has generated a large resource for answering questions about human disease. This achievement is akin in scientific importance to developing the periodic table of elements. Plastic surgery has always been at the frontier medical research. This resource will help us to improve our understanding on the many unknown physiological and pathogical conditions we deal with daily, such as wound heating keloid scar formation, Dupuytren's disease, rheumatoid arthritis, vascular malformation and carcinogenesis. We are primed in obtaining both disease and normal tissues to use this resource and applying it to clinical use. This review is about the human genome, the basis of gene expression profiling and how it will affect our clinical and research practices in the future and for those embarking on the use of this new technology as a research tool, we provide a brief insight on its limitations and pitfalls. (C) 2006 The British Association of Plastic Surgeons. Published by Elsevier Ltd. All rights reserved.

Isolates of 'Candidatus Nostocoida limicola' Blackall et al. 2000 should be described as three novel species of the genus Tetrasphaera, as Tetrasphaera jenkinsii sp nov., Tetrasphaera vanveenii sp nov and Tetrasphaera veronensis sp nov.

Despite differences in their morphologies, comparative analyses of 16S rRNA gene sequences revealed high levels of similarity (> 94 %) between strains of the filamentous bacterium 'Candidatus Nostocoida limicola' and the cocci Tetrasphaera australiensis and Tetrasphaera japonica and the rod Tetrasphaera elongata, all isolated from activated sludge. These sequence data and their chemotaxonomic characters, including cell wall, menaquinone and lipid compositions and fingerprints of their 16S-23S rRNA intergenic regions, support the proposition that these isolates should be combined into a single genus containing six species, in the family Intrasporangiaceae in the Actinobacteria. This suggestion receives additional support from DNA-DNA hybridization data and when partial sequences of the rpoC1 gene are compared between these strains. Even though few phenotypic characterization data were obtained for these slowly growing isolates, it is proposed, on the basis of the extensive chemotaxonomic and molecular evidence presented here, that 'Candidatus N. limicola' strains Ben 17, Ben 18, Ben 67, Ben 68 and Ben 74 all be placed into the species Tetrasphaera jenkinsii sp. nov. (type strain Ben 74(T) = DSM 17519(T) = NCIMB 14128(T)), 'Candidatus N. limicola' strain Ben 70 into Tetrasphaera vanveenii sp. nov. (type strain Ben 70(T) = DSM 17518(T) = NCIMB 14127(T)) and 'Candidatus N. limicola' strains Ver 1 and Ver 2 into Tetrasphaera veronensis sp. nov. (type strain Ver 1(T) = DSM 17520(T) = NCIMB 14129(T)).

Rationalization of taro germplam collections in the Pacific Island region using simple sequence repeat (SSR) markers

A regional (Oceania) core collection for taro germplasm has been developed based on phenotypic and molecular characterization. In total, 2199 accessions of taro germplasm have been collected by TaroGen (Taro Genetic Resources: Conservation and Utilisation) from 10 countries in Oceania: Papua New Guinea, Solomon Islands, Vanuatu, New Caledonia, Fiji, Palau, Niue, Tonga, Cook Islands and Samoa. Our objective was to select 10% from each country to contribute to a regional core. The larger collections from Papua New Guinea, Vanuatu and New Caledonia were analysed based on phenotypic characters, and a diverse subset representing 20% of these collections was fingerprinted. A diverse 20% subsample was also taken from the Solomon Islands. All accessions from the other six countries were fingerprinted. In total, 515 accessions were genotyped (23.4% overall) using taro specific simple sequence repeat (SSR) markers. DNA fingerprint data showed that great allelic diversity existed in Papua New Guinea and the Solomon Islands. Interestingly, rare alleles were identified in taros from the Solomon Islands province of Choiseul which were not observed in any of the other collections. Overall, 211 accessions were recommended for inclusion in the final regional core collection based on the phenotypic and molecular characterization.

Real-Time Gene-Expression Extraction with Fast Classification (FC) Networks

Fast Classification (FC) networks were inspired by a biologically plausible mechanism for short term memory where learning occurs instantaneously. Both weights and the topology for an FC network are mapped directly from the training samples by using a prescriptive training scheme. Only two presentations of the training data are required to train an FC network. Compared with iterative learning algorithms such as Back-propagation (which may require many hundreds of presentations of the training data), the training of FC networks is extremely fast and learning convergence is always guaranteed. Thus FC networks may be suitable for applications where real-time classification is needed. In this paper, the FC networks are applied for the real-time extraction of gene expressions for Chlamydia microarray data. Both the classification performance and learning time of the FC networks are compared with the Multi-Layer Proceptron (MLP) networks and support-vector-machines (SVM) in the same classification task. The FC networks are shown to have extremely fast learning time and comparable classification accuracy.

Searching oligo sets of human chromosome 12 using evolutionary strategies

DNA microarray is a powerful tool to measure the level of a mixed population of nucleic acids at one time, which has great impact in many aspects of life sciences research. In order to distinguish nucleic acids with very similar composition by hybridization, it is necessary to design probes with high specificities, i.e. uniqueness, and also sensitivities, i.e., suitable melting temperature and no secondary structure. We make use of available biology tools to gain necessary sequence information of human chromosome 12, and combined with evolutionary strategy (ES) to find unique subsequences representing all predicted exons. The results are presented and discussed.

Predictive gene lists for breast cancer prognosis: a topographic visualisation study

Background: The controversy surrounding the non-uniqueness of predictive gene lists (PGL) of small selected subsets of genes from very large potential candidates as available in DNA microarray experiments is now widely acknowledged 1. Many of these studies have focused on constructing discriminative semi-parametric models and as such are also subject to the issue of random correlations of sparse model selection in high dimensional spaces. In this work we outline a different approach based around an unsupervised patient-specific nonlinear topographic projection in predictive gene lists. Methods: We construct nonlinear topographic projection maps based on inter-patient gene-list relative dissimilarities. The Neuroscale, the Stochastic Neighbor Embedding(SNE) and the Locally Linear Embedding(LLE) techniques have been used to construct two-dimensional projective visualisation plots of 70 dimensional PGLs per patient, classifiers are also constructed to identify the prognosis indicator of each patient using the resulting projections from those visualisation techniques and investigate whether a-posteriori two prognosis groups are separable on the evidence of the gene lists. A literature-proposed predictive gene list for breast cancer is benchmarked against a separate gene list using the above methods. Generalisation ability is investigated by using the mapping capability of Neuroscale to visualise the follow-up study, but based on the projections derived from the original dataset. Results: The results indicate that small subsets of patient-specific PGLs have insufficient prognostic dissimilarity to permit a distinction between two prognosis patients. Uncertainty and diversity across multiple gene expressions prevents unambiguous or even confident patient grouping. Comparative projections across different PGLs provide similar results. Conclusion: The random correlation effect to an arbitrary outcome induced by small subset selection from very high dimensional interrelated gene expression profiles leads to an outcome with associated uncertainty. This continuum and uncertainty precludes any attempts at constructing discriminative classifiers. However a patient's gene expression profile could possibly be used in treatment planning, based on knowledge of other patients' responses. We conclude that many of the patients involved in such medical studies are intrinsically unclassifiable on the basis of provided PGL evidence. This additional category of 'unclassifiable' should be accommodated within medical decision support systems if serious errors and unnecessary adjuvant therapy are to be avoided.

Knowledge integration for analyzing ChIP-seq

To capture the genomic profiles for histone modification, chromatin immunoprecipitation (ChIP) is combined with next generation sequencing, which is called ChIP-seq. However, enriched regions generated from the ChIP-seq data are only evaluated on the limited knowledge acquired from manually examining the relevant biological literature. This paper proposes a novel framework, which integrates multiple knowledge sources such as biological literature, Gene Ontology, and microarray data. In order to precisely analyze ChIP-seq data for histone modification, knowledge integration is based on a unified probabilistic model. The model is employed to re-rank the enriched regions generated from peak finding algorithms. Through filtering the reranked enriched regions using some predefined threshold, more reliable and precise results could be generated. The combination of the multiple knowledge sources with the peaking finding algorithm produces a new paradigm for ChIP-seq data analysis. © (2012) Trans Tech Publications, Switzerland.