Functional Genomics Experiments Research Articles

Genome-wide BAC-end sequencing of Musa acuminata DH Pahang reveals further insights into the genome organization of banana

Banana and plantain (Musa spp.) are grown in more than 120 countries in tropical and subtropical regions and constitute an important staple food for millions of people. A Musa acuminata ssp. malaccencis DH Pahang bacterial artificial chromosome (BAC) library (MAMB) was submitted for BAC-end sequencing. MAMB consists of 23,040 clones, with a 140-kbp average insert size, accounting for a five times coverage of the banana genome. A total of 46,080 reads were generated, and 42,750 (92.8%) high-quality sequences were obtained after trimming for vector and quality. Analysis of these data shows a GC content of 41.39%, whereas interspersed repeats comprise 32.3%. The most common repeated sequences found show homology to ribosomal RNA genes, particularly 18S rRNA, while the Ty3/gypsy type monkey retrotransposon is the most common retro element. The sequence data were used to generate a banana-specific repeat library containing 54 new repetitive elements which accounted for 11.86% of the total nucleotides. Simple sequence repeats represent 0.7% of the sequence data and allowed the identification of 2,455 potentially useful marker sites. Functional annotation identified 2,705 sequences that could code for proteins of known function. Microsynteny analysis shows a higher number of co-linear matches to Oryza sativa, in contrast to Arabidopsis thaliana. This database of BAC-end sequences is useful for the assembly of the complete banana genome sequence and is important for identification in functional genomics experiments.

Extending pathways and processes using molecular interaction networks to analyse cancer genome data

BackgroundCellular processes and pathways, whose deregulation may contribute to the development of cancers, are often represented as cascades of proteins transmitting a signal from the cell surface to the nucleus. However, recent functional genomic experiments have identified thousands of interactions for the signalling canonical proteins, challenging the traditional view of pathways as independent functional entities. Combining information from pathway databases and interaction networks obtained from functional genomic experiments is therefore a promising strategy to obtain more robust pathway and process representations, facilitating the study of cancer-related pathways.ResultsWe present a methodology for extending pre-defined protein sets representing cellular pathways and processes by mapping them onto a protein-protein interaction network, and extending them to include densely interconnected interaction partners. The added proteins display distinctive network topological features and molecular function annotations, and can be proposed as putative new components, and/or as regulators of the communication between the different cellular processes. Finally, these extended pathways and processes are used to analyse their enrichment in pancreatic mutated genes. Significant associations between mutated genes and certain processes are identified, enabling an analysis of the influence of previously non-annotated cancer mutated genes.ConclusionsThe proposed method for extending cellular pathways helps to explain the functions of cancer mutated genes by exploiting the synergies of canonical knowledge and large-scale interaction data.

ArrayExpress update--an archive of microarray and high-throughput sequencing-based functional genomics experiments

The ArrayExpress Archive (http://www.ebi.ac.uk/arrayexpress) is one of the three international public repositories of functional genomics data supporting publications. It includes data generated by sequencing or array-based technologies. Data are submitted by users and imported directly from the NCBI Gene Expression Omnibus. The ArrayExpress Archive is closely integrated with the Gene Expression Atlas and the sequence databases at the European Bioinformatics Institute. Advanced queries provided via ontology enabled interfaces include queries based on technology and sample attributes such as disease, cell types and anatomy.

Annotating non-coding regions of the genome

Most of the human genome consists of non-protein-coding DNA. Recently, progress has been made in annotating these non-coding regions through the interpretation of functional genomics experiments and comparative sequence analysis. One can conceptualize functional genomics analysis as involving a sequence of steps: turning the output of an experiment into a 'signal' at each base pair of the genome; smoothing this signal and segmenting it into small blocks of initial annotation; and then clustering these small blocks into larger derived annotations and networks. Finally, one can relate functional genomics annotations to conserved units and measures of conservation derived from comparative sequence analysis.

MIR152, MIR200B, and MIR338, human positional and functional neuroblastoma candidates, are involved in neuroblast differentiation and apoptosis

MicroRNAs (MIRs) perform critical regulatory functions within cell networks, both in physiology as well as in pathology. Through the positional gene candidate approach, we have identified three MIRs (MIR152, MIR200B, and MIR338) that are located in regions frequently altered in neuroblastoma (NB) and target mRNAs encoding proteins involved in cell proliferation, neuroblast differentiation, neuroblast migration, and apoptosis. Expression analysis in NB biopsies and NB cell lines showed that these MIRs are dysregulated. We have characterized a CpG island, close to the gene encoding MIR200B and hypermethylated in NB samples, that explains its negative regulation. Expression of MIR152, MIR200B, and MIR338 is specifically modulated in NB cell lines during differentiation and apoptosis. Functional genomic experiments through enforced expression of MIR200B and knockdown of MIR152 resulted in a significant decrease of the invasion activity of SH-SY5Y cells. Reconstruction of a NB network comprising MIR152, MIR200B, and MIR338 allowed us to confirm their role in the control of NB cell stemness and apoptosis: This suggests that altered regulation of these MIRs could have a role in NB pathogenesis by interfering with the molecular mechanisms, which physiologically control differentiation and death of neuroblasts. Accordingly, they could be considered as new NB biomarkers and potential targets of antagomirs or epigenetic therapies.

A GMM-IG framework for selecting genes as expression panel biomarkers

The limitation of small sample size of functional genomics experiments has made it necessary to integrate DNA microarray experimental data from different sources. However, experimentation noises and biases of different microarray platforms have made integrated data analysis challenging. In this work, we propose an integrative computational framework to identify candidate biomarker genes from publicly available functional genomics studies. We developed a new framework, Gaussian Mixture Modeling-Coupled Information Gain (GMM-IG). In this framework, we first apply a two-component Gaussian mixture model (GMM) to estimate the conditional probability distributions of gene expression data between two different types of samples, for example, normal versus cancer. An expectation-maximization algorithm is then used to estimate the maximum likelihood parameters of a mixture of two Gaussian models in the feature space and determine the underlying expression levels of genes. Gene expression results from different studies are discretized, based on GMM estimations and then unified. Significantly differentially-expressed genes are filtered and assessed with information gain (IG) measures. DNA microarray experimental data for lung cancers from three different prior studies was processed using the new GMM-IG method. Target gene markers from a gene expression panel were selected and compared with several conventional computational biomarker data analysis methods. GMM-IG showed consistently high accuracy for several classification assessments. A high reproducibility of gene selection results was also determined from statistical validations. Our study shows that the GMM-IG framework can overcome poor reliability issues from single-study DNA microarray experiment while maintaining high accuracies by combining true signals from multiple studies. We present a conceptually simple framework that enables reliable integration of true differential gene expression signals from multiple microarray experiments. This novel computational method has been shown to generate interesting biomarker panels for lung cancer studies. It is promising as a general strategy for future panel biomarker development, especially for applications that requires integrating experimental results generated from different research centers or with different technology platforms.

Information management for high content live cell imaging.

BackgroundHigh content live cell imaging experiments are able to track the cellular localisation of labelled proteins in multiple live cells over a time course. Experiments using high content live cell imaging will generate multiple large datasets that are often stored in an ad-hoc manner. This hinders identification of previously gathered data that may be relevant to current analyses. Whilst solutions exist for managing image data, they are primarily concerned with storage and retrieval of the images themselves and not the data derived from the images. There is therefore a requirement for an information management solution that facilitates the indexing of experimental metadata and results of high content live cell imaging experiments.ResultsWe have designed and implemented a data model and information management solution for the data gathered through high content live cell imaging experiments. Many of the experiments to be stored measure the translocation of fluorescently labelled proteins from cytoplasm to nucleus in individual cells. The functionality of this database has been enhanced by the addition of an algorithm that automatically annotates results of these experiments with the timings of translocations and periods of any oscillatory translocations as they are uploaded to the repository. Testing has shown the algorithm to perform well with a variety of previously unseen data.ConclusionOur repository is a fully functional example of how high throughput imaging data may be effectively indexed and managed to address the requirements of end users. By implementing the automated analysis of experimental results, we have provided a clear impetus for individuals to ensure that their data forms part of that which is stored in the repository. Although focused on imaging, the solution provided is sufficiently generic to be applied to other functional proteomics and genomics experiments. The software is available from:

ArrayExpress update--from an archive of functional genomics experiments to the atlas of gene expression.

ArrayExpress http://www.ebi.ac.uk/arrayexpress consists of three components: the ArrayExpress Repository—a public archive of functional genomics experiments and supporting data, the ArrayExpress Warehouse—a database of gene expression profiles and other bio-measurements and the ArrayExpress Atlas—a new summary database and meta-analytical tool of ranked gene expression across multiple experiments and different biological conditions. The Repository contains data from over 6000 experiments comprising approximately 200 000 assays, and the database doubles in size every 15 months. The majority of the data are array based, but other data types are included, most recently—ultra high-throughput sequencing transcriptomics and epigenetic data. The Warehouse and Atlas allow users to query for differentially expressed genes by gene names and properties, experimental conditions and sample properties, or a combination of both. In this update, we describe the ArrayExpress developments over the last two years.

Yeast Features: Identifying Significant Features Shared Among Yeast Proteins for Functional Genomics

Abstract Background High throughput yeast functional genomics experiments are revealing associations among tens to hundreds of genes using numerous experimental conditions. To fully understand how the identified genes might be involved in the observed system, it is essential to consider the widest range of biological annotation possible. Biologists often start their search by collating the annotation provided for each protein within databases such as the Saccharomyces Genome Database, manually comparing them for similar features, and empirically assessing their significance. Such tasks can be automated, and more precise calculations of the significance can be determined using established probability measures. Results We developed Yeast Features, an intuitive online tool to help establish the significance of finding a diverse set of shared features among a collection of yeast proteins. A total of 18,786 features from the Saccharomyces Genome Database are considered, including annotation based on the Gene Ontology’s molecular function, biological process and cellular compartment, as well as conserved domains, protein-protein and genetic interactions, complexes, metabolic pathways, phenotypes and publications. The significance of shared features is estimated using a hypergeometric probability, but novel options exist to improve the significance by adding background knowledge of the experimental system. For instance, increased statistical significance is achieved in gene deletion experiments because interactions with essential genes will never be observed. We further demonstrate the utility by suggesting the functional roles of the indirect targets of an aminoglycoside with a known mechanism of action, and also the targets of an herbal extract with a previously unknown mode of action. The identification of shared functional features may also be used to propose novel roles for proteins of unknown function, including a role in protein synthesis for YKL075C. Conclusions Yeast Features (YF) is an easy to use web-based application (http://software.dumontierlab.com/yeastfeatures/) which can identify and prioritize features that are shared among a set of yeast proteins. This approach is shown to be valuable in the analysis of complex data sets, in which the extracted associations revealed significant functional relationships among the gene products.

Breast Cancer Risk Reduction and Membrane-Bound Catechol O-Methyltransferase Genetic Polymorphisms

Catechol O-methyltransferase (COMT)-catalyzed methylation of catecholestrogens has been proposed to play a protective role in estrogen-induced genotoxic carcinogenesis. We have taken a comprehensive approach to test the hypothesis that genetic variation in COMT might influence breast cancer risk. Fifteen COMT single nucleotide polymorphisms (SNPs) selected on the basis of in-depth resequencing of the COMT gene were genotyped in 1,482 DNA samples from a Mayo Clinic breast cancer case control study. Two common SNPs in the distal promoter for membrane-bound (MB) COMT, rs2020917 and rs737865, were associated with breast cancer risk reduction in premenopausal women in the Mayo Clinic study, with allele-specific odds ratios (OR) of 0.70 [95% confidence interval (CI), 0.52-0.95] and 0.68 (95% CI, 0.51-0.92), respectively. These two SNPs were then subjected to functional genomic analysis and were genotyped in an additional 3,683 DNA samples from two independent case control studies (GENICA and GESBC). Functional genomic experiments showed that these SNPs could up-regulate transcription and that they altered DNA-protein binding patterns. Furthermore, substrate kinetic and exon array analyses suggested a role for MB-COMT in catecholestrogen inactivation. The GENICA results were similar to the Mayo case control observations, with ORs of 0.85 (95% CI, 0.72-1.00) and 0.85 (95% CI, 0.72-1.01) for the two SNPs. No significant effect was observed in the GESBC study. These studies showed that two SNPs in the COMT distal promoter were associated with breast cancer risk reduction in two of three case control studies, compatible with the results of functional genomic experiments, suggesting a role for MB-COMT in breast cancer risk.

Circadian genomics of the chick pineal gland in vitro

BackgroundChick pinealocytes exhibit all the characteristics of a complete circadian system, comprising photoreceptive inputs, molecular clockworks and an easily measured rhythmic output, melatonin biosynthesis. These properties make the in vitro pineal a particularly useful model for exploring circadian control of gene transcription in a pacemaker tissue, as well as regulation of the transcriptome by primary inputs to the clock (both photic and noradrenergic).ResultsWe used microarray analysis to investigate the expression of approximately 8000 genes within cultured pinealocytes subjected to both LD and DD. We report that a reduced subset of genes was rhythmically expressed in vitro compared to those previously published in vivo, and that gene expression rhythms were lower in amplitude, although the functional distribution of the rhythmic transcriptome was largely similar. We also investigated the effects of 6-hour pulses of light or of norepinephrine on gene expression in free-running cultures during both subjective day and night. As expected, both light and norepinephrine inhibited melatonin production; however, the two treatments differentially enhanced or suppressed specific sets of genes in a fashion that was dependent upon time of day.ConclusionOur combined approach of utilizing a temporal, photic and pharmacological microarray experiment allowed us to identify novel genes linking clock input to clock function within the pineal. We identified approximately 30 rhythmic, light-responsive, NE-insensitive genes with no previously known clock function, which may play a role in circadian regulation of the pineal. These are candidates for future functional genomics experiments to elucidate their potential role in circadian physiology. Further, we hypothesize that the pineal circadian transcriptome is reduced but functionally conserved in vitro, and supports an endogenous role for the pineal in regulating local rhythms in metabolism, immune function, and other conserved pathways.

Development of new tools for studying gene function in fungi based on the Gateway system

Genomic information of many fungi has been released but large scale functional genomic studies are still limited by a lack of high-throughput methods. The low rates of homologous recombination and low rates of transformation are limiting steps in filamentous fungi, but the molecular tools are also lagging behind. In this paper we describe two new high-throughput functional genomic tools for filamentous fungi that are based on the Gateway technology. One system is the Gateway RNAi vector for fungi that allows gene silencing in a high-throughput manner. The other system is a high-throughput deletion construct system. These systems were tested using the PAC1 gene of Colletotrichum gloeosporioides. Using these types of approaches, large scale functional genomics experiments can be performed in filamentous fungi.

Global Phenotype Screening and Transcript Analysis Outlines the Inhibitory Mode(s) of Action of Two Amphibian-Derived, α-Helical, Cationic Peptides on Saccharomyces cerevisiae

Dermaseptin S3(1-16) [DsS3(1-16)] and magainin 2 (Mag 2) are two unrelated, amphibian-derived cationic peptides that adopt an alpha-helical structure within microbial membranes and have been proposed to kill target organisms via membrane disruption. Using a combination of global deletion mutant library phenotypic screening, expression profiling, and physical techniques, we have carried out a comprehensive in vitro analysis of the inhibitory action of these two peptides on the model fungus Saccharomyces cerevisiae. Gene ontology profiling (of biological processes) was used to identify both common and unique effects of each peptide. Resistance to both peptides was conferred by genes involved in telomere maintenance, chromosome organization, and double-strand break repair, implicating a common inhibitory action of DNA damage. Crucially, each peptide also required unique genes for maintaining resistance; for example, DsS3(1-16) required genes involved in protein targeting to the vacuole, and Mag 2 required genes involved in DNA-dependent DNA replication and DNA repair. Thus, DsS3(1-16) and Mag 2 have both common and unique antifungal actions that are not simply due to membrane disruption. Physical techniques revealed that both peptides interacted with DNA in vitro but in subtly different ways, and this observation was supported by the functional genomics experiments that provided evidence that both peptides also interfered with DNA integrity differently in vivo. This implies that both peptides are able to pass through the cytoplasmic membrane of yeast cells and damage DNA, an inhibitory action that has not been previously attributed to either of these peptides.

Estudos de expressão gênica utilizando-se microarrays: delineamento, análise, e aplicações na pesquisa zootécnica

A tecnologia de microarrays, ou microarranjos de DNA, possibilita a avaliação simultânea da expressão de milhares de genes em diferentes tecidos em determinado organismo, em diferentes estágios de desenvolvimento ou condições ambientais. Microarrays são bastante utilizados em experimentos de genômica funcional com diversas espécies animais e vegetais, e têm sido gradativamente incorporados em diferentes áreas da pesquisa zootécnica, como crescimento e metabolismo, resposta imune a doenças, reprodução e resposta a fatores de estresse não-infecciosos (restrição alimentar, exposição a elementos tóxicos e outras condições ambientais desfavoráveis), bem como melhoramento genético animal. Tais experimentos, entretanto, são ainda consideravelmente caros, como consequência, geralmente são conduzidos com tamanhos amostrais relativamente pequenos. Por outro lado, a realização dos experimentos com microarrays, desde a coleta das amostras, até a obtenção das imagens para análise, envolve uma série de procedimentos laboratoriais de alta complexidade, que frequentemente introduzem variações adicionais aos resultados obtidos. Desta maneira, a condução de ensaios com microarrays requer cuidadoso delineamento experimental e análise estatística dos dados. Nesta apresentação são discutidos princípios básicos do planejamento de ensaios com microarrays, bem como as ferramentas estatísticas e computacionais mais comuns para a análise dos mesmos. São também discutidos alguns exemplos de aplicação de experimentos com microarrays em zootecnia e, numa última seção, são traçadas algumas considerações finais envolvendo os tópicos gerais abordados.

Genome-wide analysis of PPARα activation in murine small intestine

The peroxisome proliferator-activated receptor alpha (PPARalpha) is a fatty acid-activated transcription factor that governs a variety of biological processes. Little is known about the role of PPARalpha in the small intestine. Since this organ is frequently exposed to high levels of PPARalpha ligands via the diet, we set out to characterize the function of PPARalpha in small intestine using functional genomics experiments and bioinformatics tools. PPARalpha was expressed at high levels in both human and murine small intestine. Detailed analyses showed that PPARalpha was expressed most highly in villus cells of proximal jejunum. Microarray analyses of total tissue samples revealed, that in addition to genes involved in fatty acid and triacylglycerol metabolism, transcription factors and enzymes connected to sterol and bile acid metabolism, including FXR and SREBP1, were specifically induced. In contrast, genes involved in cell cycle and differentiation, apoptosis, and host defense were repressed by PPARalpha activation. Additional analyses showed that intestinal PPARalpha-dependent gene regulation occurred in villus cells. Functional implications of array results were corroborated by morphometric data. The repression of genes involved in proliferation and apoptosis was accompanied by a 22% increase in villus height and a 34% increase in villus area of wild-type animals treated with WY14643. This is the first report providing a comprehensive overview of processes under control of PPARalpha in the small intestine. We show that PPARalpha is an important transcriptional regulator in small intestine, which may be of importance for the development of novel foods and therapies for obesity and inflammatory bowel diseases.

Representation, Comparison, and Interpretation of Metabolome Fingerprint Data for Total Composition Analysis and Quality Trait Investigation in Potato Cultivars

Understanding attributes of crop varieties and food raw materials underlying desirable characteristics is a significant challenge. Metabolomics technology based on flow infusion electrospray ionization mass spectrometry (FIE-MS) has been used to investigate the chemical composition of potato cultivars associated with quality traits in harvested tubers. Through the combination of metabolite fingerprinting with random forest data modeling, a subset of metabolome signals explanatory of compositional differences between individual genotypes were ranked for importance. Interpretative analysis of highlighted signals based on ranking behavior, intensity correlations, and mathematical relationships of ion masses correctly predicted metabolites associated with flavor and pigmentation traits in potato tubers. GC-MS profiling was used to further validate proposed compositional differences. The potential for the development of a database strategy for large scale, long-term projects requiring comparison of chemical composition in plant breeding, mutant population analysis in functional genomics experiments, or food raw material analysis is described.

Collembase: a repository for springtail genomics and soil quality assessment

BackgroundEnvironmental quality assessment is traditionally based on responses of reproduction and survival of indicator organisms. For soil assessment the springtail Folsomia candida (Collembola) is an accepted standard test organism. We argue that environmental quality assessment using gene expression profiles of indicator organisms exposed to test substrates is more sensitive, more toxicant specific and significantly faster than current risk assessment methods. To apply this species as a genomic model for soil quality testing we conducted an EST sequencing project and developed an online database.DescriptionCollembase is a web-accessible database comprising springtail (F. candida) genomic data. Presently, the database contains information on 8686 ESTs that are assembled into 5952 unique gene objects. Of those gene objects ~40% showed homology to other protein sequences available in GenBank (blastx analysis; non-redundant (nr) database; expect-value < 10-5). Software was applied to infer protein sequences. The putative peptides, which had an average length of 115 amino-acids (ranging between 23 and 440) were annotated with Gene Ontology (GO) terms. In total 1025 peptides (~17% of the gene objects) were assigned at least one GO term (expect-value < 10-25). Within Collembase searches can be conducted based on BLAST and GO annotation, cluster name or using a BLAST server. The system furthermore enables easy sequence retrieval for functional genomic and Quantitative-PCR experiments. Sequences are submitted to GenBank (Accession numbers: EV473060 – EV481745).ConclusionCollembase is a resource of sequence data on the springtail F. candida. The information within the database will be linked to a custom made microarray, based on the Agilent platform, which can be applied for soil quality testing. In addition, Collembase supplies information that is valuable for related scientific disciplines such as molecular ecology, ecogenomics, molecular evolution and phylogenetics.

Transcriptional Profiling and Functional Genomics Reveal a Role for AHR Transcription Factor in Nephrogenesis

Transcriptional profiling and functional genomics experiments using E11.5 metanephros organ cultures from Ahr(-/-) and Ahr(+/+) have shown that aryl hydrocarbon receptor (AHR) transcription factor is involved in the regulation of mesenchymal-to-epithelial transition (MET) during nephrogenesis. This response is mediated by alterations in the post-transcriptional control of Wilms' tumor suppressor (Wt1) gene and Wt1 splicing. In this article, biologically relevant gene predictor sets of the nephrogenic response were calculated for target genes of interest. The predictability of the gene set for each target was quantified by the coefficient of determination which provided a good criterion for identification of predictor sets that define the complex gene-gene interactions co-regulated by Ahr and Wt1. A subset of the signature genes was found to be co-regulated by Ahr and Wt1 and was responsible for shifts in renal cell transdifferentiation.

High-throughput fluorescence microscopy for systems biology

In this post-genomic era, we need to define gene function on a genome-wide scale for model organisms and humans. The fundamental unit of biological processes is the cell. Among the most powerful tools to assay such processes in the physiological context of intact living cells are fluorescence microscopy and related imaging techniques. To enable these techniques to be applied to functional genomics experiments, fluorescence microscopy is making the transition to a quantitative and high-throughput technology.

Microarray image gridding with stochastic search based approaches

The paper reports a novel approach for the problem of automatic gridding in Microarray images. Such problem often requires human intervention; therefore, the development of automated procedures is a fundamental issue for large-scale functional genomic experiments involving many microarray images. Our method uses a two-step process. First a regular rectangular grid is superimposed on the image by interpolating a set of guide spots, this is done by solving a non-linear optimization process with a stochastic search producing the best interpolating grid parameterized by a six values vector. Second, the interpolating grid is adapted, with a Markov Chain Monte Carlo method, to local deformations. This is done by modeling the solution a Markov random field with a Gibbs prior possibly containing first order cliques (1-clique). The algorithm is completely automatic and no human intervention is required, it efficiently accounts arbitrary grid rotations, irregularities and various spot sizes.