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PubMed2004

An efficient Monte Carlo approach to assessing statistical significance in genomic studies.

MOTIVATION: Multiple hypothesis testing is a common problem in genome research, particularly in microarray experiments and genomewide association studies. Failure to account for the effects of multiple comparisons would result in an abundance of false positive results. The Bonferroni correction and Holm's step-down procedure are overly conservative, whereas the permutation test is time-consuming and is restricted to simple problems. RESULTS: We developed an efficient Monte Carlo approach to approximating the joint distribution of the test statistics along the genome. We then used the Monte Carlo distribution to evaluate the commonly used criteria for error control, such as familywise error rates and positive false discovery rates. This approach is applicable to any data structures and test statistics. Applications to simulated and real data demonstrate that the proposed approach provides accurate error control, and can be substantially more powerful than the Bonferroni and Holm methods, especially when the test statistics are highly correlated.

Algorithms↗
PubMed2005

The role of monovalent cation transporters in plant responses to salinity.

Exposure to high ambient levels of NaCl affects plant water relations and creates ionic stress in the form of the cellular accumulation of Cl- and, in particular, Na+ ions. However, salt stress also impacts heavily on the homeostasis of other ions such as Ca2+, K+, and NO(3)(-) and therefore requires insights into how transport and compartmentation of these nutrients is altered during salinity stress. A genomics approach can greatly help with the identification of genes, and therefore potentially gene products, that are involved in plant salinity. Both the literature and public databases contain the results of many genomics studies and, in this report, those data are collated in the context of cation membrane transport and salinity. The efficacy of genomics approaches in isolation is low due to large inherent variability and the exclusion of gene products that are predominantly regulated post-transcriptionally. In conjunction with complementary approaches, however, transcriptomics can help identify important transcripts and relevant associations between physiological processes. This analysis identified (i) vascular K+ circulation, (ii) root shoot translocation of Ca2+, and (iii) transition metal homeostasis as potentially important aspects of the plant response to salt stress.

Arabidopsis↗
PubMed2005

Genomic responses in rat cerebral cortex after traumatic brain injury.

BACKGROUND: Traumatic brain injury (TBI) initiates a complex sequence of destructive and neuroprotective cellular responses. The initial mechanical injury is followed by an extended time period of secondary brain damage. Due to the complicated pathological picture a better understanding of the molecular events occurring during this secondary phase of injury is needed. This study was aimed at analysing gene expression patterns following cerebral cortical contusion in rat using high throughput microarray technology with the goal of identifying genes involved in an early and in a more delayed phase of trauma, as genomic responses behind secondary mechanisms likely are time-dependent. RESULTS: Among the upregulated genes 1 day post injury, were transcription factors and genes involved in metabolism, e.g. STAT-3, C/EBP-delta and cytochrome p450. At 4 days post injury we observed increased gene expression of inflammatory factors, proteases and their inhibitors, like cathepsins, alpha-2-macroglobulin and C1q. Notably, genes with biological function clustered to immune response were significantly upregulated 4 days after injury, which was not found following 1 day. Osteopontin and one of its receptors, CD-44, were both upregulated showing a local mRNA- and immunoreactivity pattern in and around the injury site. Fewer genes had decreased expression both 1 and 4 days post injury and included genes implicated in transport, metabolism, signalling, and extra cellular matrix formation, e.g. vitronectin, neuroserpin and angiotensinogen. CONCLUSION: The different patterns of gene expression, with little overlap in genes, 1 and 4 days post injury showed time dependence in genomic responses to trauma. An early induction of factors involved in transcription could lead to the later inflammatory response with strongly upregulated CD-44 and osteopontin expression. An increased knowledge of genes regulating the pathological mechanisms in trauma will help to find future treatment targets. Since trauma is a risk factor for development of neurodegenerative disease, this knowledge may also reduce late negative effects.

Animals↗
PubMed2004

The use of differential display to isolate viral genomic sequence for rapid development of PCR-based detection methods. A test case using Taura syndrome virus.

The purpose of this study was to explore the efficacy of using differential display (DD) to isolate viral genomic sequence using tissues from infected organisms so that a PCR procedure to detect the pathogen may be developed rapidly. The model virus used was the Taura syndrome virus (TSV), a ssRNA virus that cause high rates of mortality at shrimp farms. Two random primers in combination with four anchored primers were used to isolate five cDNAs, ranging in size from 241 to 822 bp, that were differentially expressed in TSV-infected shrimp (Litopenaeus vannamei). PCR experiments revealed that four of the five encoded shrimp genes while the fifth was likely to be a TSV gene. Evidence that the putative TSV sequence is part of the TSV genome was obtained by the 97% sequence identity it shared with the published TSV genome. PCR primers were designed successfully using the differential display sequence to develop a RT-PCR-based method to detect TSV. Because differential display does not require physical isolation of the virus and only a small amount of infected sample is needed, the technique may be useful as a method to isolate nucleic acid sequences from emerging pathogens so that PCR primers for their detection may be developed rapidly.

Animals↗
PubMed2006

HURP controls spindle dynamics to promote proper interkinetochore tension and efficient kinetochore capture.

Through a functional genomic screen for mitotic regulators, we identified hepatoma up-regulated protein (HURP) as a protein that is required for chromosome congression and alignment. In HURP-depleted cells, the persistence of unaligned chromosomes and the reduction of tension across sister kinetochores on aligned chromosomes resulted in the activation of the spindle checkpoint. Although these defects transiently delayed mitotic progression, HeLa cells initiated anaphase without resolution of these deficiencies. This bypass of the checkpoint arrest provides a tumor-specific mechanism for chromosome missegregation and genomic instability. Mechanistically, HURP colocalized with the mitotic spindle in a concentration gradient increasing toward the chromosomes. HURP binds directly to microtubules in vitro and enhances their polymerization. In vivo, HURP stabilizes mitotic microtubules, promotes microtubule polymerization and bipolar spindle formation, and decreases the turnover rate of the mitotic spindle. Thus, HURP controls spindle stability and dynamics to achieve efficient kinetochore capture at prometaphase, timely chromosome congression to the metaphase plate, and proper interkinetochore tension for anaphase initiation.

Cell Nucleus Division↗
PubMed2003

Resource and hardware options for microarray-based experimentation.

DNA microarray technology permits the study of biological systems and processes on a genome-wide scale. Arrays based on cDNA clones, oligonucleotides and genomic clones have been developed for investigations of gene expression, genetic analysis and genomic changes associated with disease. Over the past 3-4 years, microarrays have become more widely available to the research community. This has occurred through increased commercial availability of custom and generic arrays and the development of robotic equipment that has enabled array printing and analysis facilities to be established in academic research institutions. This brief review examines the public and commercial resources, the microarray fabrication and data capture and analysis equipment currently available to the user.

Computational Biology↗
PubMed2003

SOURCE: a unified genomic resource of functional annotations, ontologies, and gene expression data.

The explosion in the number of functional genomic datasets generated with tools such as DNA microarrays has created a critical need for resources that facilitate the interpretation of large-scale biological data. SOURCE is a web-based database that brings together information from a broad range of resources, and provides it in manner particularly useful for genome-scale analyses. SOURCE's GeneReports include aliases, chromosomal location, functional descriptions, GeneOntology annotations, gene expression data, and links to external databases. We curate published microarray gene expression datasets and allow users to rapidly identify sets of co-regulated genes across a variety of tissues and a large number of conditions using a simple and intuitive interface. SOURCE provides content both in gene and cDNA clone-centric pages, and thus simplifies analysis of datasets generated using cDNA microarrays. SOURCE is continuously updated and contains the most recent and accurate information available for human, mouse, and rat genes. By allowing dynamic linking to individual gene or clone reports, SOURCE facilitates browsing of large genomic datasets. Finally, SOURCEs batch interface allows rapid extraction of data for thousands of genes or clones at once and thus facilitates statistical analyses such as assessing the enrichment of functional attributes within clusters of genes. SOURCE is available at http://source.stanford.edu.

Animals↗
PubMed2005

Genome-wide requirements for resistance to functionally distinct DNA-damaging agents.

The mechanistic and therapeutic differences in the cellular response to DNA-damaging compounds are not completely understood, despite intense study. To expand our knowledge of DNA damage, we assayed the effects of 12 closely related DNA-damaging agents on the complete pool of approximately 4,700 barcoded homozygous deletion strains of Saccharomyces cerevisiae. In our protocol, deletion strains are pooled together and grown competitively in the presence of compound. Relative strain sensitivity is determined by hybridization of PCR-amplified barcodes to an oligonucleotide array carrying the barcode complements. These screens identified genes in well-characterized DNA-damage-response pathways as well as genes whose role in the DNA-damage response had not been previously established. High-throughput individual growth analysis was used to independently confirm microarray results. Each compound produced a unique genome-wide profile. Analysis of these data allowed us to determine the relative importance of DNA-repair modules for resistance to each of the 12 profiled compounds. Clustering the data for 12 distinct compounds uncovered both known and novel functional interactions that comprise the DNA-damage response and allowed us to define the genetic determinants required for repair of interstrand cross-links. Further genetic analysis allowed determination of epistasis for one of these functional groups.

Antifungal Agents↗
PubMed2002

GeneCards 2002: towards a complete, object-oriented, human gene compendium.

MOTIVATION: In the post-genomic era, functional analysis of genes requires a sophisticated interdisciplinary arsenal. Comprehensive resources are challenged to provide consistently improving, state-of-the-art tools. RESULTS: GeneCards (Rebhan et al., 1998) has made innovative strides: (a). regular updates and enhancements incorporating new genes enriched with sequences, genomic locations, cDNA assemblies, orthologies, medical information, 3D protein structures, gene expression, and focused SNP summaries; (b). restructured software using object-oriented Perl, migration to schema-driven XML, and (c). pilot studies, introducing methods to produce cards for novel and predicted genes.

Algorithms↗
PubMed2002

Analysis of mRNA expression and protein abundance data: an approach for the comparison of the enrichment of features in the cellular population of proteins and transcripts.

MOTIVATION: Protein abundance is related to mRNA expression through many different cellular processes. Up to now, there have been conflicting results on how correlated the levels of these two quantities are. Given that expression and abundance data are significantly more complex and noisy than the underlying genomic sequence information, it is reasonable to simplify and average them in terms of broad proteomic categories and features (e.g. functions or secondary structures), for understanding their relationship. Furthermore, it will be essential to integrate, within a common framework, the results of many varied experiments by different investigators. This will allow one to survey the characteristics of highly expressed genes and proteins. RESULTS: To this end, we outline a formalism for merging and scaling many different gene expression and protein abundance data sets into a comprehensive reference set, and we develop an approach for analyzing this in terms of broad categories, such as composition, function, structure and localization. As the various experiments are not always done using the same set of genes, sampling bias becomes a central issue, and our formalism is designed to explicitly show this and correct for it. We apply our formalism to the currently available gene expression and protein abundance data for yeast. Overall, we found substantial agreement between gene expression and protein abundance, in terms of the enrichment of structural and functional categories. This agreement, which was considerably greater than the simple correlation between these quantities for individual genes, reflects the way broad categories collect many individual measurements into simple, robust averages. In particular, we found that in comparison to the population of genes in the yeast genome, the cellular populations of transcripts and proteins (weighted by their respective abundances, the transcriptome and what we dub the translatome) were both enriched in: (i) the small amino acids Val, Gly, and Ala; (ii) low molecular weight proteins; (iii) helices and sheets relative to coils; (iv) cytoplasmic proteins relative to nuclear ones; and (v) proteins involved in 'protein synthesis,' 'cell structure,' and 'energy production.' SUPPLEMENTARY INFORMATION: http://genecensus.org/expression/translatome

Algorithms↗
PubMed2004

Discovering modes of action for therapeutic compounds using a genome-wide screen of yeast heterozygotes.

Modern medicine faces the challenge of developing safer and more effective therapies to treat human diseases. Many drugs currently in use were discovered without knowledge of their underlying molecular mechanisms. Understanding their biological targets and modes of action will be essential to design improved second-generation compounds. Here, we describe the use of a genome-wide pool of tagged heterozygotes to assess the cellular effects of 78 compounds in Saccharomyces cerevisiae. Specifically, lanosterol synthase in the sterol biosynthetic pathway was identified as a target of the antianginal drug molsidomine, which may explain its cholesterol-lowering effects. Further, the rRNA processing exosome was identified as a potential target of the cell growth inhibitor 5-fluorouracil. This genome-wide screen validated previously characterized targets or helped identify potentially new modes of action for over half of the compounds tested, providing proof of this principle for analyzing the modes of action of clinically relevant compounds.

Drug Evaluation, Preclinical↗
PubMed2025

Mapping early PRC2 nucleation sites upon Suz12 reintroduction reveals features of de novo Polycomb recruitment.

Polycomb domains safeguard cell identity by maintaining lineage-specific chromatin states enriched in repressive histone modifications, preserving the epigenetic memory of cell lineages. While Polycomb Repressive Complex 2 (PRC2) can re-establish its occupancy after perturbation, the mechanisms that guide de novo Polycomb recruitment remain unclear. To address this, we engineered an auxin-inducible degradation system to reversibly deplete and reintroduce the endogenous PRC2 core subunit Suz12 in mouse embryonic stem cells (mESCs). Genome-wide profiling at an early recovery time point revealed ~1,100 PRC2 nucleation sites, characterized by rapid Suz12 and histone H3K27me3 re-accumulation with strong signal, with minimal impact on gene expression. These sites were significantly enriched at bivalent promoters, coinciding with unmethylated CpG islands and chromatin states associated with developmental regulation, and were largely conserved in differentiated cells. Motif analysis identified G/C-rich DNA sequences associated with E2F and zinc-finger proteins, alongside strong co-occupancy with MTF2 and JARID2, two PRC2 cofactors previously implicated in Polycomb targeting. Notably, a subset of nucleation sites overlapped with long-range chromatin interaction anchors in histone H3K27me3 HiChIP datasets. These findings reveal that PRC2 de novo nucleation sites are associated with a combination of chromatin states, DNA sequence features, cofactor co-occupancy and spatial genome organization, suggesting that epigenetic memory can be re-established through defined genomic and chromatin features.

Epigenetic memory↗
PubMed2006

Towards high-throughput characterization of small molecule mechanisms of action.

Drug discovery is hampered by the lack of general strategies to characterize the mechanisms of action and intracellular targets of bioactive small molecules. Genomics and proteomics promise to aid in this process. Genome-wide approaches in yeast have proven useful to infer the targets and target pathways of small molecules. These approaches are being systematically transferred into mammalian cell culture systems in order to interrogate more complex pathways in a more relevant setting. Advances in proteomics and in vivo genetic screening in multicellular model organism systems are also becoming increasingly powerful and amenable to high-throughput. Current methodologies and technologies are discussed, including how these global approaches complement affinity-based target identification strategies.

Animals↗
PubMed2002

Gene Expression Omnibus: NCBI gene expression and hybridization array data repository.

The Gene Expression Omnibus (GEO) project was initiated in response to the growing demand for a public repository for high-throughput gene expression data. GEO provides a flexible and open design that facilitates submission, storage and retrieval of heterogeneous data sets from high-throughput gene expression and genomic hybridization experiments. GEO is not intended to replace in house gene expression databases that benefit from coherent data sets, and which are constructed to facilitate a particular analytic method, but rather complement these by acting as a tertiary, central data distribution hub. The three central data entities of GEO are platforms, samples and series, and were designed with gene expression and genomic hybridization experiments in mind. A platform is, essentially, a list of probes that define what set of molecules may be detected. A sample describes the set of molecules that are being probed and references a single platform used to generate its molecular abundance data. A series organizes samples into the meaningful data sets which make up an experiment. The GEO repository is publicly accessible through the World Wide Web at http://www.ncbi.nlm.nih.gov/geo.

Animals↗
PubMed2005

A class of models for analyzing GeneChip gene expression analysis array data.

BACKGROUND: Various analytical methods exist that first quantify gene expression and then analyze differentially expressed genes from Affymetrix GeneChip gene expression analysis array data. These methods differ in the choice of probe measure (quantification of probe hybridization), summarizing multiple probe intensities into a gene expression value, and analysis of differential gene expression. Research papers that describe these methods focus on performance, and how their approaches differ from others. To better understand the common features and differences between various methods, and to evaluate their impact on the results of gene expression analysis, we describe a class of models, referred to as generalized probe models (GPMs), which encompass various currently available methods. RESULTS: Using an empirical dataset, we compared different formulations of GPMs, and GPMs with three other commonly used methods, i.e. MAS 5.0, dChip, and RMA. The comparison shows that, on a genome-wide scale , different methods yield similar results if the same probe measures are chosen. CONCLUSION: In this paper we present a general framework, i.e. GPMs, which encompasses various methods. GPMs permit the use of a wide range of probe measures and facilitate appropriate comparison between commonly used methods. We demonstrate that the dissimilar results stem primarily from different choice of probe measures, rather than other factors.

Algorithms↗
PubMed2003

[Novel approaches; improved diagnostics and therapeutics with DNA microarrays. II. Applications].

The most important (future) applications of DNA microarrays in medicine are based on three different molecular analyses: gene expression analysis, genotyping with a specific type of microarray (single nucleotide polymorphism chip (SNP chip)), and DNA sequencing to search for a well-known mutation in a certain gene. With gene expression analysis one can obtain a 'molecular signature' of a tissue by allowing tissue RNA to react with a DNA microarray. This information may help to refine disease classifications, to guide the choice of therapy and to find new therapeutic targets. Genotyping utilizes genomic DNA that, after digestion, reacts with a SNP chip to obtain an individual SNP pattern. An SNP is a change of a single base pair within a gene sequence that can sometimes influence the function of the gene product. SNPs are considered to be variations in the genome and should be distinguished from mutations. These variations can for instance provide information about the probability of a certain disease, or the effectiveness or side effect of a certain drug. Sequencing well characterized genes to search for mutations is used to screen for genetic abnormalities. This process can be accelerated with the aid of oligonucleotide arrays. With this tool an individual's risk of developing certain forms of cancer or monogenetic diseases can be estimated.

Diagnostic Techniques and Procedures↗
PubMed2001

Back to the future: the human protein index (HPI) and the agenda for post-proteomic biology.

The effort to produce an index of all human proteins (the human protein index, or HPI) began twenty years ago, before the initiation of the human genome program. Because DNA sequencing technology is inherently simpler and more scalable than protein analytical technology, and because the finiteness of genomes invited a spirit of rapid conquest, the notion of genome sequencing has displaced that of protein databases in the minds of most molecular biologists for the last decade. However, now that the human genome sequence is nearing completion, a major realignment is under way that brings proteins back to the center of biological thinking. Using an influx of new and improved protein technologies--from mass spectrometry to re-engineered two-dimensional (2-D) gel systems, the original objectives of the HPI have been expanded and the time frame for its execution radically shortened. Several additional large scale technology efforts flowing from the HPI are also described.

Biotechnology↗
PubMed2006

Genomic screening of head and neck cancer and its implications for therapy planning.

Despite great technical improvements in radiotherapy and surgery, survival for patients with squamous cell carcinoma of the head and neck (SCCHN) has still not improved significantly over the last decades. Management of SCCHN has mainly been based on the TNM staging and site over this time period, even though we know that there are individual differences independent of the TNM status. Individual patients with small tumors might have a poor outcome, and patients with large tumors may end up with a favorable prognosis, despite their respective TNM classification. Recent molecular studies indicate that underlying genetic abnormalities may reflect such individual differences independently of TNM status. Individualization of treatment based on such biological properties of the tumors might result in less over as well as under treatment. However, the optimal panel of biomarkers to be used for the individualization of treatment is yet to be defined. A variety of laboratory techniques have been used in studies that investigate the individual biological features, spanning from methods that screen the genome for chromosomal and genetic abnormalities, e.g., cytogenetics, CGH, SKY and cDNA micro array, to detailed studies of specific aberrations. The purpose of this review of the literature is to summarize what has been studied so far by methods for genetic screening and to relate these results to the prediction of the clinical outcome. We conclude that it is time to focus future prospective studies on how treatment can be individualized based on biomarkers in combination with the macroscopic features of SCCHN.

Biomarkers, Tumor↗