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PubMed2003

Genomic dissection for characterization of cancerous oral epithelium tissues using transcription profiling.

Genome-wide and high-throughput functional genomic tools offer the potential of identifying disease-associated genes and dissecting disease regulatory patterns. There is a need for a set of systematic bioinformatic tools that handles efficiently a large number of variables for extracting biological meaning from experimental outputs. We present well-characterized statistical tools to discover genes that are differentially expressed between malignant oral epithelial and normal tissues in microarray experiments and to construct a robust classifier using the identified discriminatory genes. Those tools include Wilks' lambda score, error rate estimated from leave-one out cross-validation (LOOCV) and Fisher Discriminant Analysis (FDA). High Density DNA microarrays and Real Time Quantitative PCR were employed for the generation and validation of the transcription profile of the oral cancer and normal samples. We identified 45 genes that are strongly correlated with malignancy. Of the 45 genes identified, six have been previously implicated in the disease, and two are uncharacterized clones.

Gene Expression Profiling↗

PubMed2026

In vivo CRISPR screening identifies metastasis suppressors in triple-negative breast cancer.

Metastatic cancer remains the leading cause of cancer-related mortality, yet tumor cell-intrinsic mechanisms restraining metastatic dissemination remain incompletely defined. Here, we perform an unbiased in vivo genome-wide CRISPR/Cas9 loss-of-function screen in a breast cancer xenograft model to identify regulators of metastatic progression. This approach uncovers clinically relevant metastasis suppressor genes (MSGs), including VPS45, CMTR2, RBSN, and NF2, whose loss enhances lung colonization. Functional validation demonstrates that depletion of these genes promotes epithelial-to-mesenchymal transition, migration, invasion, intravasation, and angiogenesis, whereas CRISPR-mediated activation suppresses metastatic spread. Integration with patient datasets reveals reduced expression in tumors and associations with advanced disease, with higher expression trending toward improved outcomes. Notably, CMTR2 loss induces vascular remodeling and intratumoral heterogeneity, supporting a role in tumor-vascular interactions. Collectively, this study identifies a network of MSGs that constrain tumor dissemination and highlights the power of in vivo CRISPR functional genomics to uncover regulators of metastatic disease.

Humans↗

PubMed2001

Region-specific transcriptional activity in the genome of Streptomyces coelicolor A3(2).

Transcriptional analysis of microbial genomes is an important component of functional genomics. Strategies such as hybridization of labeled total RNA against ordered clone libraries or differential-display approaches have already been carried out to identify expressed genes. We describe here an additional method which applies subtractive hybridization between genome-specific DNA and total RNA followed by a PCR approach to identify expressed microbial genes. With the new strategy, the expression of genes in the terminal regions of the linear Streptomyces coelicolor A3(2) chromosome and the accessory linear plasmid SCP1 was analyzed. The results indicate that the method is useful for the identification of expressed genes in actinomycetes and other microbial systems. We demonstrate for the first time that at least 24 genes in the chromosome end regions (silent regions) of S. coelicolor are actively expressed. In addition, several expressed SCP1 genes were identified, including a gene which shows high similarity to microbial dnaN genes and which seems to play a role in SCP1 maintenance.

Bacterial Proteins↗

PubMed2005

FrankSum: new feature selection method for protein function prediction.

In the study of in silico functional genomics, improving the performance of protein function prediction is the ultimate goal for identifying proteins associated with defined cellular functions. The classical prediction approach is to employ pairwise sequence alignments. However this method often faces difficulties when no statistically significant homologous sequences are identified. An alternative way is to predict protein function from sequence-derived features using machine learning. In this case the choice of possible features which can be derived from the sequence is of vital importance to ensure adequate discrimination to predict function. In this paper we have successfully selected biologically significant features for protein function prediction. This was performed using a new feature selection method (FrankSum) that avoids data distribution assumptions, uses a data independent measurement (p-value) within the feature, identifies redundancy between features and uses an appropriate ranking criterion for feature selection. We have shown that classifiers generated from features selected by FrankSum outperforms classifiers generated from full feature sets, randomly selected features and features selected from the Wrapper method. We have also shown the features are concordant across all species and top ranking features are biologically informative. We conclude that feature selection is vital for successful protein function prediction and FrankSum is one of the feature selection methods that can be applied successfully to such a domain.

Amino Acid Sequence↗

PubMed2026

Unveiling the Molecular Secrets of Seaweeds: A Comprehensive Review of Bioinformatics Applications in Algal Research.

Recent advances in high-throughput sequencing, bioinformatics, and multi-omics technologies have transformed seaweed research by overcoming long-standing challenges associated with complex genomes, diverse life cycles, and limited genomic resources. This review provides a comprehensive overview of bioinformatics approaches used to investigate seaweed genomics, transcriptomics, proteomics, metabolomics, microbiomes, and functional genomics, with emphasis on the computational tools and databases that support these analyses. Applications of bioinformatics in phylogenetics, drug discovery, microbiome characterization, and the development of biofuels, nutraceuticals, pharmaceuticals, and sustainable agriculture are also discussed. Particular attention is given to emerging strategies involving multi-omics integration, genome editing, artificial intelligence, machine learning, and synthetic biology that are reshaping seaweed research. The review further examines current challenges, including incomplete genomic resources, data standardization, and the need for experimental validation of computational predictions. Collectively, these advances highlight the growing role of bioinformatics in enabling systems-level understanding of seaweed biology and accelerating their translation into sustainable biotechnological and marine bioeconomy applications.

macroalgal genomics↗

PubMed2003

An automated method for high-throughput protein purification applied to a comparison of His-tag and GST-tag affinity chromatography.

BACKGROUND: Functional Genomics, the systematic characterisation of the functions of an organism's genes, includes the study of the gene products, the proteins. Such studies require methods to express and purify these proteins in a parallel, time and cost effective manner. RESULTS: We developed a method for parallel expression and purification of recombinant proteins with a hexahistidine tag (His-tag) or glutathione S-transferase (GST)-tag from bacterial expression systems. Proteins are expressed in 96-well microplates and are purified by a fully automated procedure on a pipetting robot. Up to 90 microgram purified protein can be obtained from 1 ml microplate cultures. The procedure is readily reproducible and 96 proteins can be purified in approximately three hours. It avoids clearing of crude cellular lysates and the use of magnetic affinity beads and is therefore less expensive than comparable commercial systems. We have used this method to compare purification of a set of human proteins via His-tag or GST-tag. Proteins were expressed as fusions to an N-terminal tandem His- and GST-tag and were purified by metal chelating or glutathione affinity chromatography. The purity of the obtained protein samples was similar, yet His-tag purification resulted in higher yields for some proteins. CONCLUSION: A fully automated, robust and cost effective method was developed for the purification of proteins that can be used to quickly characterise expression clones in high throughput and to produce large numbers of proteins for functional studies.His-tag affinity purification was found to be more efficient than purification via GST-tag for some proteins.

Chromatography, Affinity↗

PubMed1998

Production of therapeutic proteins in the milk of transgenic livestock.

With the advent of the Human Genome Project and associated developments in 'functional genomics', there are going to be increasing numbers of proteins identified and developed for clinical use. There are a number of production methods available, although only three, bacterial, yeast and mammalian cell culture, have produced recombinant proteins that have been approved for clinical use. Nevertheless other production systems are under development, and one, the production of human proteins in the milk of transgenic livestock, is showing great promise, with two proteins now in clinical trials. This chapter will compare and contrast the various competing technologies and will then concentrate on factors influencing the choice and use of the transgenic system.

Animals↗

PubMed2002

[Transcriptomes for serial analysis of gene expression].

The availability of the sequences for whole genomes is changing our understanding of cell biology. Functional genomics refers to the comprehensive analysis, at the protein level (proteome) and at the mRNA level (transcriptome) of all events associated with the expression of whole sets of genes. New methods have been developed for transcriptome analysis. Serial Analysis of Gene Expression (SAGE) is based on the massive sequential analysis of short cDNA sequence tags. Each tag is derived from a defined position within a transcript. Its size (14 bp) is sufficient to identify the corresponding gene and the number of times each tag is observed provides an accurate measurement of its expression level. Since tag populations can be widely amplified without altering their relative proportions, SAGE may be performed with minute amounts of biological extract. Dealing with the mass of data generated by SAGE necessitates computer analysis. A software is required to automatically detect and count tags from sequence files. Criterias allowing to assess the quality of experimental data can be included at this stage. To identify the corresponding genes, a database is created registering all virtual tags susceptible to be observed, based on the present status of the genome knowledge. By using currently available database functions, it is easy to match experimental and virtual tags, thus generating a new database registering identified tags, together with their expression levels. As an open system, SAGE is able to reveal new, yet unknown, transcripts. Their identification will become increasingly easier with the progress of genome annotation. However, their direct characterization can be attempted, since tag information may be sufficient to design primers allowing to extend unknown sequences. A major advantage of SAGE is that, by measuring expression levels without reference to an arbitrary standard, data are definitively acquired and cumulative. All publicly available data can thus be stored in a unique database, facilitating whole-genome analysis of differential expression between cell types, normal and diseased samples, or samples with and without drug treatment. SAGE data are readily amenable to statistical comparisons, allowing to determine the level of confidence of the observed variations. A major limitation of SAGE is that, because each analysis is obligatory performed on the whole set of expressed genes, it can hardly be performed on multiple samples, for example in kinetics studies or to compare the effects of large numbers of drugs. To overcome this limitation, high-throughput detection of a subset of mRNAs is more rapidly performed by parallel hybridization of mRNAs on arrays of nucleic acids immobilized on solid supports. From this point of view, a SAGE platform is a powerful instrument for selecting the most informative subset of genes, assembling them to design microarrays dedicated to a specific problem and calibrating measurement by comparison with a standard cell model for which SAGE data are available. This approach is an attractive alternative to strategies based exclusively on pangenomic arrays. A very large amount of SAGE data are already available and the problem is now to extract their biological meaning. Knowledge on metabolic pathways is already organized so that its successful integration in a SAGE platform can be undertaken. For other cell components and pathways, the problem lies on the lack of controlled vocabulary to describe gene activities, starting form a clear definition of the concept of biological function itself. Progress in gene and cell ontology is expected to facilitate computer-based extraction of biological knowledge from existing and forthcoming SAGE data.

Animals↗

PubMed1999

An automated comparative analysis of 17 complete microbial genomes.

MOTIVATION: As sequenced genomes become larger and sequencing becomes faster, there is a need to develop accurate automated genome comparison techniques and databases to facilitate derivation of genome functionality; identification of enzymes, putative operons and metabolic pathways; and to derive phylogenetic classification of microbes. RESULTS: This paper extends an automated pair-wise genome comparison technique (Bansal et al., Math. Model. Sci. Comput., 9, 1-23, 1998, Bansal and Bork, in First International Workshop of Declarative Languages, Springer, pp. 275-289, 1999) used to identify orthologs and gene groups to derive orthologous genes in a group of genomes and to identify genes with conserved functionality. Seventeen microbial genomes archived at ftp://ncbi.nlm.nih.gov/genbank/genomes have been compared using the automated technique. Data related to orthologs, gene groups, gene duplication, gene fusion, orthologs with conserved functionality, and genes specifically orthologous to Escherichia coli and pathogens has been presented and analyzed. AVAILABILITY: A prototype database is available at ftp://www.mcs.kent.edu/arvind/intellibio / orthos.html. The software is free for academic research under an academic license. The detailed database for every microbial genome in NCBI is commercially available through intellibio software and consultancy corporation (Web site: http://www.mcs.kent.edu/årvind/intellibio . html). CONTACT: arvind@mcs.kent.edu.

Algorithms↗

PubMed2002

Metabolomics and microarrays for improved understanding of phenotypic characteristics controlled by both genomics and environmental constraints.

Advances in our understanding of functional genomics are best addressed by integrative studies that include measurements of mRNA, proteins, and low molecular weight metabolites over time and varied conditions. Bioinformatics can then be used to relate this data to the genome. Current technology allows for comprehensive and rapid mRNA expression profiling and mass spectrophotometric measurement of low molecular weight intermediates and metabolic products. In prokaryotic organisms, this combination provides a potentially powerful tool for identifying gene function and regulatory networks even in the absence of a combined proteomic approach.

Carbon Radioisotopes↗

PubMed2005

An in silico mining for simple sequence repeats from expressed sequence tags of zebrafish, medaka, Fundulus, and Xiphophorus.

Teleost fish genome projects involving model species are resulting in a rapid accumulation of genomic and expressed DNA sequences in public databases. The expressed sequence tags (ESTs) collected in the databases can be mined for the analysis of both structural and functional genomics. In this study, we in silico analyzed 49,430 unigenes representing a total of 692,654 ESTs from four model fish for their potential use in developing simple sequence repeats (SSRs), or microsatellites. After bioinformatical mining, a total of 3,018 EST derived SSRs (EST-SSRs) were identified for 2,335 SSR containing ESTs (SSR-ESTs). The frequency of identified SSR-ESTs ranged from 1.5% for Xiphophorus to 7.3% for zebrafish. The dinucleotide repeat motif is the most abundant SSR, accounting for 47%, 52%, 64%, and 78% for medaka, Fundulus, zebrafish, and Xiphophorus, respectively. Simulation analysis suggests that a majority of these EST-SSRs have sufficient flanking sequences for polymerase chain reaction (PCR) primer design. Comparative DNA sequence analyses of SSR-ESTs identified several cross-species SSRs and sequences that may be used as cross-reference genes in comparative studies. For example, the flanking sequences of one SSR (CTG)n within the pituitary tumor-transforming gene (PTTG) 1 interacting protein (PTTGIP), showed conservation spanning the medaka, Fundulus, human, and mouse genomes. This study provides a large body of information on EST-SSRs that can be useful for the development of polymorphic markers, gene mapping, and comparative genome analysis. Functional analysis of these SSR-ESTs may reveal their role in metabolism and gene evolution of these model species.

Amino Acid Sequence↗

PubMed2026

Advances in CRISPR multiplex gene editing to map and modify stress-responsive transcription factor networks for crop improvement.

The development of CRISPR multiplex genome-editing (MGE) tools is rapidly transforming plant functional genomics and accelerating crop improvements. By simultaneously targeting two or more DNA loci, it allows scientists to precisely edit multiple genes at the single-nucleotide level, within the target genome. Simultaneous manipulation of multiple targets has revolutionized the functional elucidation studies, particularly the dissection of complex genetic pathways. Due to its superior precision and feasibility, CRISPR-MGE is widely accepted and has largely replaced alternative editing tools such as TALENs and ZFNs. Several CRISPR-MGE strategies, including the use of individual expression cassettes, tRNA-processing enzymes, Csy4 or ribozymes, have been successfully deployed in plants. Recent advancements, such as Cpf1, transgene-free methods, or ultra-multiplexing approaches, have further refined the technology into a powerful, efficient, and robust toolkit. MGE enables complex genome editing, including multiple-gene knockouts, base alterations, transcriptional regulation, metabolic engineering, or their combinations. Consequently, it is ideal for elucidating the function of transcription factors that are key molecular players in regulating diverse plant responses, especially in stress pathways. Several stress-responsive TFs have been functionally characterized via CRISPR-MGE, and more advanced tools are being employed. This review evaluates multiplexing tools, their diverse applications, and the current progress toward developing advanced MGE tools. Ultimately, we provide evidence to encourage the use of advanced MGE tools for functional characterization studies of stress-responsive TFs, thereby highlighting their potential to accelerate crop improvement.

Gene Editing↗

PubMed2026

Exploring the Effect of Whole-Genome Duplication on Salmonid LincRNA Repertoire.

Long intergenic non-coding RNAs (lincRNAs) are key epigenetic regulators of genome function, yet their evolutionary dynamics following whole-genome duplication (WGD) events remain poorly understood. Salmonids, which underwent a lineage-specific autotetraploidization (salmonid-specific WGD, ~88-100 million years ago), provide an excellent model to investigate the retention, divergence, and functional potential of recently duplicated non-coding elements. LincRNA repertoires were compared across five genome-annotated salmonids (Oncorhynchus tshawytscha, O. kisutch, O. mykiss, Salmo salar, and S. trutta) and their closest non-duplicated relative, northern pike (Esox lucius). LincRNAs represented ~5-7% of annotated genes in all salmonids except S. salar (18%). Sequence conservation was low relative to coding genes, with only 11-68 highly similar (e-value < 1 × 10-30; similarity > 70% and alignments > 100 nucleotides) putative orthologues shared between salmonids and northern pike, and 161-338 among salmonids alone. Synteny conservation was modest in lincRNAs, with lower conservation in putative orthologues (8-16%) compared to putative ohnologues (8-33%). Secondary structure conservation was associated with sequence similarity (ρ = -0.45; p = 2.2 × 10-16), and the association was stronger among WGD ohnologues than orthologues. In S. salar and O. mykiss, lincRNA putative ohnologues showed weaker expression correlations than coding genes, suggesting widespread regulatory divergence, possibly through neo- and subfunctionalisation. Conserved salmonid lincRNAs showed enriched predicted interactions with miRNAs involved in tumour suppression, brain, bone, and muscle development (e.g., miR-455, miR-365, miR124, miR-133a, miR-140, and miR-9), a finding supported by limited transcriptomic data. Although salmonid WGD expanded lincRNA repertoires, lincRNAs have undergone rapid sequence and transcriptional divergence, with limited conservation across species based on sequence similarity, chromosomal position, synteny, and secondary structure. A subset of conserved lincRNAs retains structural features and regulatory signatures consistent with roles as miRNA sponges in brain, skeletal, and muscle development and tumour suppression, potentially acting within conserved regulatory networks. These findings provide new insights into lincRNA evolution following genome duplication and highlight the need for experimental validation of their regulatory functions.

Animals↗

PubMed2003

A new paradigm for drug discovery: integrating clinical, genetic, genomic and molecular phenotype data to identify drug targets.

Application of statistical genetics approaches to variations in mRNA transcript abundances in segregating populations can be used to identify genes and pathways associated with common human diseases. The combination of this genetic information with gene expression and clinical trait data can also be used to identify subtypes of a disease and the genetic loci specific to each subtype. Here we highlight results from some of our recent work in this area and further explore the many possibilities that exist in employing a more comprehensive genetics and functional genomics approach to the functional annotation of genomes, and in applying such methods to the validation of targets for complex traits in the drug discovery process.

Animals↗

PubMed2001

Epigenetic reprogramming in mammalian development.

DNA methylation is a major epigenetic modification of the genome that regulates crucial aspects of its function. Genomic methylation patterns in somatic differentiated cells are generally stable and heritable. However, in mammals there are at least two developmental periods-in germ cells and in preimplantation embryos-in which methylation patterns are reprogrammed genome wide, generating cells with a broad developmental potential. Epigenetic reprogramming in germ cells is critical for imprinting; reprogramming in early embryos also affects imprinting. Reprogramming is likely to have a crucial role in establishing nuclear totipotency in normal development and in cloned animals, and in the erasure of acquired epigenetic information. A role of reprogramming in stem cell differentiation is also envisaged. DNA methylation is one of the best-studied epigenetic modifications of DNA in all unicellular and multicellular organisms. In mammals and other vertebrates, methylation occurs predominantly at the symmetrical dinucleotide CpG (1-4). Symmetrical methylation and the discovery of a DNA methyltransferase that prefers a hemimethylated substrate, Dnmt1 (4), suggested a mechanism by which specific patterns of methylation in the genome could be maintained. Patterns imposed on the genome at defined developmental time points in precursor cells could be maintained by Dnmt1, and would lead to predetermined programs of gene expression during development in descendants of the precursor cells (5, 6). This provided a means to explain how patterns of differentiation could be maintained by populations of cells. In addition, specific demethylation events in differentiated tissues could then lead to further changes in gene expression as needed. Neat and convincing as this model is, it is still largely unsubstantiated. While effects of methylation on expression of specific genes, particularly imprinted ones (7) and some retrotransposons (8), have been demonstrated in vivo, it is still unclear whether or not methylation is involved in the control of gene expression during normal development (9-13). Although enzymes have been identified that can methylate DNA de novo (Dnmt3a and Dnmt3b) (14), it is unknown how specific patterns of methylation are established in the genome. Mechanisms for active demethylation have been suggested, but no enzymes have been identified that carry out this function in vivo (15-17). Genomewide alterations in methylation-brought about, for example, by knockouts of the methylase genes-result in embryo lethality or developmental defects, but the basis for abnormal development still remains to be discovered (7, 14). What is clear, however, is that in mammals there are developmental periods of genomewide reprogramming of methylation patterns in vivo. Typically, a substantial part of the genome is demethylated, and after some time remethylated, in a cell- or tissue-specific pattern. The developmental dynamics of these reprogramming events, as well as some of the enzymatic mechanisms involved and the biological purposes, are beginning to be understood. Here we look at what is known about reprogramming in mammals and discuss how it might relate to developmental potency and imprinting.

Animals↗

PubMed2004

Finding functional sites in structural genomics proteins.

Assigning function to structures is an important aspect of structural genomics projects, since they frequently provide structures for uncharacterized proteins. Similarities uncovered by structure alignment can suggest a similar function, even in the absence of sequence similarity. For proteins adopting novel folds or those with many functions, this strategy can fail, but functional clues can still come from comparison of local functional sites involving a few key residues. Here we assess the general applicability of functional site comparison through the study of 157 proteins solved by structural genomics initiatives. For 17, the method bolsters confidence in predictions made based on overall fold similarity. For another 12 with new folds, it suggests functions, including a putative phosphotyrosine binding site in the Archaeal protein Mth1187 and an active site for a ribose isomerase. The approach is applied weekly to all new structures, providing a resource for those interested in using structure to infer function.

Algorithms↗

PubMed2002

Numerous potentially functional but non-genic conserved sequences on human chromosome 21.

The use of comparative genomics to infer genome function relies on the understanding of how different components of the genome change over evolutionary time. The aim of such comparative analysis is to identify conserved, functionally transcribed sequences such as protein-coding genes and non-coding RNA genes, and other functional sequences such as regulatory regions, as well as other genomic features. Here, we have compared the entire human chromosome 21 with syntenic regions of the mouse genome, and have identified a large number of conserved blocks of unknown function. Although previous studies have made similar observations, it is unknown whether these conserved sequences are genes or not. Here we present an extensive experimental and computational analysis of human chromosome 21 in an effort to assign function to sequences conserved between human chromosome 21 (ref. 8) and the syntenic mouse regions. Our data support the presence of a large number of potentially functional non-genic sequences, probably regulatory and structural. The integration of the properties of the conserved components of human chromosome 21 to the rapidly accumulating functional data for this chromosome will improve considerably our understanding of the role of sequence conservation in mammalian genomes.

Animals↗

PubMed2005

Trade-offs in detecting evolutionarily constrained sequence by comparative genomics.

As whole-genome sequencing efforts extend beyond more traditional model organisms to include a deep diversity of species, comparative genomic analyses will be further empowered to reveal insights into the human genome and its evolution. The discovery and annotation of functional genomic elements is a necessary step toward a detailed understanding of our biology, and sequence comparisons have proven to be an integral tool for that task. This review is structured to broadly reflect the statistical challenges in discriminating these functional elements from the bulk of the genome that has evolved neutrally. Specifically, we review the comparative genomics literature in terms of specificity, sensitivity, and phylogenetic scope, as well as the trade-offs that relate these factors in standard analyses. We consider the impact of an expanding diversity of orthologous sequences on our ability to resolve functional elements. This impact is assessed through both recent comparative analyses of deep alignments and mathematical modeling.

Animals↗