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PubMed2004

Comparative genomics: digging for data.

Comparative genomics is a science in its infancy. It has been driven by a huge increase in freely available genome-sequence data, and the development of computer techniques to allow whole-genome sequence analyses. Other approaches, which use hybridization as a method for comparing the gene content of related organisms, are rising alongside these more bioinformatic methods. All these approaches have been pioneered using bacterial genomes because of their simplicity and the large number of complete genome sequences available. The aim of bacterial comparative genomics is to determine what genotypic differences are important for the expression of particular traits. The benefits of such studies will be a deeper understanding of these phenomena; the possibility of exposing novel drug targets, including those for antivirulence drugs; and the development of molecular techniques that reveal patients who are infected with virulent organisms so that health care resources can be allocated appropriately. With more and more genome sequences becoming available, the rise of comparative genomics continues apace.

Bacteria↗

PubMed2025

Beacon Reconstruction Attack: Reconstruction of genomes in genomic data-sharing beacons using summary statistics.

MOTIVATION: Genomic data-sharing beacon protocol, developed by the Global Alliance for Genomics and Health, offers a privacy-preserving mechanism for querying genomic datasets while restricting direct data access. Despite their design, beacons remain vulnerable to privacy attacks. This study introduces a novel privacy vulnerability of the protocol: one can reconstruct large portions of the genomes of all beacon participants by only using the summary statistics reported by the protocol. RESULTS: We introduce a novel optimization-based algorithm that leverages beacon responses and SNP correlations for reconstruction. By optimizing for the SNP correlations and allele frequencies, the proposed approach achieves genome reconstruction with a substantially higher F1-score (70%) compared to baseline methods (45%) on beacons generated using individuals from the HapMap and OpenSNP datasets. We show that reconstructed genomes can be used by downstream applications such as in membership inference attacks against other beacons. Our findings reveal that beacons releasing allele frequencies substantially increase the reconstruction risk, underscoring the need for enhanced privacy-preserving mechanisms to protect genomic data. AVAILABILITY AND IMPLEMENTATION: Our implementation is available at https://github.com/ASAP-Bilkent/Beacon-Reconstruction-Attack.

Genomics↗

PubMed2005

Estimating gene regulatory networks and protein-protein interactions of Saccharomyces cerevisiae from multiple genome-wide data.

MOTIVATION: Biological processes in cells are properly performed by gene regulations, signal transductions and interactions between proteins. To understand such molecular networks, we propose a statistical method to estimate gene regulatory networks and protein-protein interaction networks simultaneously from DNA microarray data, protein-protein interaction data and other genome-wide data. RESULTS: We unify Bayesian networks and Markov networks for estimating gene regulatory networks and protein-protein interaction networks according to the reliability of each biological information source. Through the simultaneous construction of gene regulatory networks and protein-protein interaction networks of Saccharomyces cerevisiae cell cycle, we predict the role of several genes whose functions are currently unknown. By using our probabilistic model, we can detect false positives of high-throughput data, such as yeast two-hybrid data. In a genome-wide experiment, we find possible gene regulatory relationships and protein-protein interactions between large protein complexes that underlie complex regulatory mechanisms of biological processes.

Algorithms↗

PubMed2006

From information to understanding: the role of model organism databases in comparative and functional genomics.

Data integration is key to functional and comparative genomics because integration allows diverse data types to be evaluated in new contexts. To achieve data integration in a scalable and sensible way, semantic standards are needed, both for naming things (standardized nomenclatures, use of key words) and also for knowledge representation. The Mouse Genome Informatics database and other model organism databases help to close the gap between information and understanding of biological processes because these resources enforce well-defined nomenclature and knowledge representation standards. Model organism databases have a critical role to play in ensuring that diverse kinds of data, especially genome-scale data sets and information, remain useful to the biological community in the long-term. The efforts of model organism database groups ensure not only that organism-specific data are integrated, curated and accessible but also that the information is structured in such a way that comparison of biological knowledge across model organisms is facilitated.

Animals↗

PubMed2003

GeneMerge--post-genomic analysis, data mining, and hypothesis testing.

SUMMARY: GeneMerge is a web-based and standalone program written in PERL that returns a range of functional and genomic data for a given set of study genes and provides statistical rank scores for over-representation of particular functions or categories in the data set. Functional or categorical data of all kinds can be analyzed with GeneMerge, facilitating regulatory and metabolic pathway analysis, tests of population genetic hypotheses, cross-experiment comparisons, and tests of chromosomal clustering, among others. GeneMerge can perform analyses on a wide variety of genomic data quickly and easily and facilitates both data mining and hypothesis testing. AVAILABILITY: GeneMerge is available free of charge for academic use over the web and for download from: http://www.oeb.harvard.edu/hartl/lab/publications/GeneMerge.html.

Algorithms↗

PubMed1999

bioWidgets: data interaction components for genomics.

MOTIVATION: The presentation of genomics data in a perspicuous visual format is critical for its rapid interpretation and validation. Relatively few public database developers have the resources to implement sophisticated front-end user interfaces themselves. Accordingly, these developers would benefit from a reusable toolkit of user interface and data visualization components. RESULTS: We have designed the bioWidget toolkit as a set of JavaBean components. It includes a wide array of user interface components and defines an architecture for assembling applications. The toolkit is founded on established software engineering design patterns and principles, including componentry, Model-View-Controller, factored models and schema neutrality. As a proof of concept, we have used the bioWidget toolkit to create three extendible applications: AnnotView, BlastView and AlignView.

Amino Acid Sequence↗

PubMed2004

i-Genome: a database to summarize oligonucleotide data in genomes.

BACKGROUND: Information on the occurrence of sequence features in genomes is crucial to comparative genomics, evolutionary analysis, the analyses of regulatory sequences and the quantitative evaluation of sequences. Computing the frequencies and the occurrences of a pattern in complete genomes is time-consuming. RESULTS: The proposed database provides information about sequence features generated by exhaustively computing the sequences of the complete genome. The repetitive elements in the eukaryotic genomes, such as LINEs, SINEs, Alu and LTR, are obtained from Repbase. The database supports various complete genomes including human, yeast, worm, and 128 microbial genomes. CONCLUSIONS: This investigation presents and implements an efficiently computational approach to accumulate the occurrences of the oligonucleotides or patterns in complete genomes. A database is established to maintain the information of the sequence features, including the distributions of oligonucleotide, the gene distribution, the distribution of repetitive elements in genomes and the occurrences of the oligonucleotides. The database can provide more effective and efficient way to access the repetitive features in genomes.

Alu Elements↗

PubMed2026

Whole genome sequence data on Ethiopian key sorghum landraces and founder lines.

Sorghum (Sorghum bicolor (L.) Moench) is the fifth most important cereal globally. Its genetic diversity is key to improving yield stability, stress tolerance, and adaptation to different environments. Ethiopia is one of the centers for the crop's origin, diversity, and use in both human food and livestock feed. However, genomic data on Ethiopian sorghum remain limited, especially for landraces preferred by local farmers. This dataset consists of whole-genome sequencing data for 188 Ethiopian sorghum accessions, including founder lines and important landraces from major agroecological zones. Sequencing was performed using the Complete Genomics DNBSEQ-T7 platform, generating high-coverage whole-genome data (20 × coverage). On average, each accession produced 64.7 million reads. Reads were aligned to the Sorghum bicolor NCBIv3 reference genome and variants called using GATK HaplotypeCaller with joint genotyping (GATK v4.6.1.0). Hard-filtering followed GATK best-practice thresholds (QD <2.0, FS> 60.0, MQ <40.0, MQRankSum <-12.5, ReadPosRankSum <-8.0), retaining biallelic SNPs with mean depth 10-50×, missingness ≤20%, and MAF ≥0.05, yielding 6095,752 high-confidence SNPs across 185 accessions. Both the raw FASTQ files and processed VCF files are publicly available to support studies of sorghum genetic diversity, population structure, selection, and the genetic basis of important traits.

Adaptation↗

PubMed2006

GENOMIZER: an integrated analysis system for genome-wide association data.

Genome-wide association analysis appears to be a promising way to identify heritable susceptibility factors for complex human disorders. However, the feasibility of large-scale genotyping experiments is currently limited by an incomplete marker coverage of the genome, a restricted understanding of the functional role of given genomic regions, and the small sample sizes used. Thus, genome-wide association analysis will be a screening tool to facilitate subsequent gene discovery rather than a means to completely resolve individual genetic risk profiles. The validation of association findings will continue to rely upon the replication of "leads" in independent samples from either the same or different populations. Even under such pragmatic conditions, the timely analysis of the large data sets in question poses serious technical challenges. We have therefore developed public-domain software, GENOMIZER, that implements the workflow of an association experiment, including data management, single-point and haplotype analysis, "lead" definition, and data visualization. GENOMIZER (www.ikmb.uni-kiel.de/genomizer) comes with a complete user manual, and is open-source software licensed under the GNU Lesser General Public License. We suggest that the use of this software will facilitate the handling and interpretation of the currently emerging genome-wide association data.

Chromosome Mapping↗

PubMed1995

Computer survey for likely genes in the one megabase contiguous genomic sequence data of Synechocystis sp. strain PCC6803.

Using the computer program GeneMark, the open reading frames (ORFs) previously assigned within the one megabase sequence data of the genome of the cyanobacterium, Synechocystis sp. strain PCC6803 (Kaneko et al., DNA Res. 2: 153-166, 1995), were re-examined. Matrices required by GeneMark for its statistical calculation were generated and modified by running a script termed GeneMark-Genesis that performed recursive application of GeneMark against the Synechocystis data and evaluated the probability scores for optimization. Based on the matrices thus generated, 752 of the 818 previously assigned ORFs (92%) were supported by GeneMark as likely coding sequences, of which 26 were predicted to start at more internal positions than previously assigned. In addition, 50 ORFs were newly identified as likely coding sequences, most of them being shorter than 300 bp. Thus, the procedure was proven to be very powerful to locate likely coding regions within the genomic sequence data of Synechocystis without having prior information concerning their similarity to the genes of other organisms. However, GeneMark did not predict 66 previously assigned ORFs as likely genes: 14 of them showed significant degrees of similarity to known genes and 10 others were found within IS-like elements. It seems that these genes, many of which appear to be exogenous origin, escaped detection by GeneMark as in the case of "class 3 (horizontally transferred) genes" of E. coli, which in turn suggests that genes of different phylogenetic origins might also be detected as such by modifying the matrices.

Base Sequence↗

PubMed2002

Assessing the impact of comparative genomic sequence data on the functional annotation of the Drosophila genome.

BACKGROUND: It is widely accepted that comparative sequence data can aid the functional annotation of genome sequences; however, the most informative species and features of genome evolution for comparison remain to be determined. RESULTS: We analyzed conservation in eight genomic regions (apterous, even-skipped, fushi tarazu, twist, and Rhodopsins 1, 2, 3 and 4) from four Drosophila species (D. erecta, D. pseudoobscura, D. willistoni, and D. littoralis) covering more than 500 kb of the D. melanogaster genome. All D. melanogaster genes (and 78-82% of coding exons) identified in divergent species such as D. pseudoobscura show evidence of functional constraint. Addition of a third species can reveal functional constraint in otherwise non-significant pairwise exon comparisons. Microsynteny is largely conserved, with rearrangement breakpoints, novel transposable element insertions, and gene transpositions occurring in similar numbers. Rates of amino-acid substitution are higher in uncharacterized genes relative to genes that have previously been studied. Conserved non-coding sequences (CNCSs) tend to be spatially clustered with conserved spacing between CNCSs, and clusters of CNCSs can be used to predict enhancer sequences. CONCLUSIONS: Our results provide the basis for choosing species whose genome sequences would be most useful in aiding the functional annotation of coding and cis-regulatory sequences in Drosophila. Furthermore, this work shows how decoding the spatial organization of conserved sequences, such as the clustering of CNCSs, can complement efforts to annotate eukaryotic genomes on the basis of sequence conservation alone.

Animals↗

PubMed1998

Comparison of genomic methods for differentiating strains of Enterococcus faecium: assessment using clinical epidemiologic data.

Genomic DNA extracted from 45 vancomycin-resistant Enterococcus faecium (VRE) isolates was cleaved with HindIII and HaeIII and subjected to agarose gel electrophoresis. The ability of this method (restriction endonuclease analysis [REA]) to distinguish strains at the subspecies level was compared with results previously determined by pulsed-field gel electrophoresis (PFGE). Chart reviews were performed to provide a clinical correlation of possible epidemiologic relatedness. A likely clinical association was found for 29 patients as part of two outbreaks. REA found 21 of 21 isolates were the same type in the first outbreak, with PFGE calling 19 strains the same type. In the second outbreak with eight patient isolates, HindIII found six were the same type and two were unique types. HaeIII found three strains were the same type, two strains were a separate type, and three more strains were unique types, while PFGE found three were the same type and five were unique types. No single "ideal" method can be used without clinical epidemiologic investigation, but any of these techniques is helpful in providing focus to infection control practitioners assessing possible outbreaks of nosocomial infection.

Anti-Bacterial Agents↗

PubMed1996

A graph conceptual model for developing Human Genome Center databases.

We have developed a representation of genome data which has proven itself useful for describing data at a Human Genome Center. Genomic data have a graph-like structure and representing the concepts and relationships of genetics as a graph simplifies the development of databases for genome laboratories. Graphs are a comfortable communication medium for biologists and computer scientists and graph diagrams assist in the development of databases by facilitating the exchange of expertise. We have tailored a graph language for modeling genomic data and describe our process of using graphs to develop genome databases.

Computer Graphics↗

PubMed2005

Non-linear mapping for exploratory data analysis in functional genomics.

BACKGROUND: Several supervised and unsupervised learning tools are available to classify functional genomics data. However, relatively less attention has been given to exploratory, visualisation-driven approaches. Such approaches should satisfy the following factors: Support for intuitive cluster visualisation, user-friendly and robust application, computational efficiency and generation of biologically meaningful outcomes. This research assesses a relaxation method for non-linear mapping that addresses these concerns. Its applications to gene expression and protein-protein interaction data analyses are investigated. RESULTS: Publicly available expression data originating from leukaemia, round blue-cell tumours and Parkinson disease studies were analysed. The method distinguished relevant clusters and critical analysis areas. The system does not require assumptions about the inherent class structure of the data, its mapping process is controlled by only one parameter and the resulting transformations offer intuitive, meaningful visual displays. Comparisons with traditional mapping models are presented. As a way of promoting potential, alternative applications of the methodology presented, an example of exploratory data analysis of interactome networks is illustrated. Data from the C. elegans interactome were analysed. Results suggest that this method might represent an effective solution for detecting key network hubs and for clustering biologically meaningful groups of proteins. CONCLUSION: A relaxation method for non-linear mapping provided the basis for visualisation-driven analyses using different types of data. This study indicates that such a system may represent a user-friendly and robust approach to exploratory data analysis. It may allow users to gain better insights into the underlying data structure, detect potential outliers and assess assumptions about the cluster composition of the data.

Algorithms↗

PubMed2001

Analysis and comparison of metabolic pathway databases.

Enormous amounts of data result from genome sequencing projects and new experimental methods. Within this tremendous amount of genomic data 30-40 per cent of the genes being identified in an organism remain unknown in terms of their biological function. As a consequence of this lack of information the overall schema of all the biological functions occurring in a specific organism cannot be properly represented. To understand the functional properties of the genomic data more experimental data must be collected. A pathway database is an effort to handle the current knowledge of biochemical pathways and in addition can be used for interpretation of sequence data. Some of the existing pathway databases can be interpreted as detailed functional annotations of genomes because they are tightly integrated with genomic information. However, experimental data are often lacking in these databases. This paper summarises a list of pathway databases and some of their corresponding biological databases, and also focuses on information about the content and the structure of these databases, the organisation of the data and the reliability of stored information from a biological point of view. Moreover, information about the representation of the pathway data and tools to work with the data are given. Advantages and disadvantages of the analysed databases are pointed out, and an overview to biological scientists on how to use these pathway databases is given.

Animals↗

PubMed2006

BBP: Brucella genome annotation with literature mining and curation.

BACKGROUND: Brucella species are Gram-negative, facultative intracellular bacteria that cause brucellosis in humans and animals. Sequences of four Brucella genomes have been published, and various Brucella gene and genome data and analysis resources exist. A web gateway to integrate these resources will greatly facilitate Brucella research. Brucella genome data in current databases is largely derived from computational analysis without experimental validation typically found in peer-reviewed publications. It is partially due to the lack of a literature mining and curation system able to efficiently incorporate the large amount of literature data into genome annotation. It is further hypothesized that literature-based Brucella gene annotation would increase understanding of complicated Brucella pathogenesis mechanisms. RESULTS: The Brucella Bioinformatics Portal (BBP) is developed to integrate existing Brucella genome data and analysis tools with literature mining and curation. The BBP InterBru database and Brucella Genome Browser allow users to search and analyze genes of 4 currently available Brucella genomes and link to more than 20 existing databases and analysis programs. Brucella literature publications in PubMed are extracted and can be searched by a TextPresso-powered natural language processing method, a MeSH browser, a keywords search, and an automatic literature update service. To efficiently annotate Brucella genes using the large amount of literature publications, a literature mining and curation system coined Limix is developed to integrate computational literature mining methods with a PubSearch-powered manual curation and management system. The Limix system is used to quickly find and confirm 107 Brucella gene mutations including 75 genes shown to be essential for Brucella virulence. The 75 genes are further clustered using COG. In addition, 62 Brucella genetic interactions are extracted from literature publications. These results make possible more comprehensive investigation of Brucella pathogenesis. Other BBP features include publication email alert service, Brucella researchers' contact database, and discussion forum. CONCLUSION: BBP is a gateway for Brucella researchers to search, analyze, and curate Brucella genome data originated from public databases and literature. Brucella gene mutations and genetic interactions are annotated using Limix leading to better understanding of Brucella pathogenesis.

Algorithms↗

PubMed2026

Molecular residual disease assessment in colorectal and bladder cancer by somatic structural variant analysis of cell-free DNA whole-genome sequencing data.

BACKGROUND: Whole-genome sequencing (WGS)-based methods for circulating tumor DNA (ctDNA) detection typically rely on tumor-informed identification of somatic single nucleotide variants (SNVs). Somatic structural variants (SVs) are another type of cancer-specific genomic alteration, which owing to their larger genomic footprint and unique breakpoint junctions, are easier to distinguish from sequencing noise than SNVs. They are, however, rarely used for ctDNA detection because of (1) artifacts from WGS procedures that SV callers may falsely interpret as genuine SVs. This makes it difficult to establish high-confidence SV catalogos from short-read tumor WGS and can cause false-positive ctDNA detections. (2) Lack of robust strategies to quantify SV-supporting reads in plasma WGS. To address these barriers and enable integration of SV biomarkers into WGS-based ctDNA detection, we present a bioinformatic framework for algorithmic curation of somatic SV calls from fresh-frozen and formalin-fixed paraffin-embedded (FFPE) tumors, coupled with a novel approach for sensitive, accurate mapping and quantification of SV breakpoint-supporting reads in plasma WGS. METHODS: Tumor, normal and plasma WGS data from 144 patients with stage III colorectal cancer was used to establish the bioinformatic framework. This included ~30x WGS data from 1564 serially collected plasma samples. The framework was validated using tumor/normal/plasma WGS data from 32 patients with muscle-invasive bladder cancer. SV-based ctDNA detection was benchmarked against previously published SNV-based ctDNA results for the same samples. RESULTS: After curation of SV calls and quantification in plasma WGS, our SV-based approach enabled robust ctDNA detection with overall specificity exceeding 99% in plasma samples. Furthermore, we observed strong concordance (Pearson’s r > 0.93, p < 2.2 × 10− 16) between ctDNA-positive samples identified by our SV-based method and previous SNV-based analyses, validating the reliability of our approach. Finally, we demonstrated application of the method in an independent bladder cancer cohort, highlighting its generalizability and potential clinical use. CONCLUSIONS: We provide a bioinformatic framework that establishes somatic SVs as ultra-specific biomarkers for WGS-based, tumor-informed ctDNA detection. The approach delivers specific detection even when the SV catalogos are established from FFPE samples. The SV framework can stand alone or enhance SNV-based analysis pipelines.

Humans↗

PubMed2000

Integration of cytogenetic data with genome maps and available probes: present status and future promise.

The National Cancer Institute has established an initiative, called the Cancer Chromosome Aberration Project (Ccap), in order to link and integrate the physical and genetic maps of the human genome with cytogenetic data and the location of chromosomal rearrangements in human diseases. This goal will be achieved by high-resolution fluorescence in situ hybridization (FISH) mapping of colony-purified bacterial artificial chromosome (BAC) clones spaced at 1-to 2-Mb intervals across the entire genome. All BAC clones will be anchored on the physical map by the presence of a mapped sequence tagged site (STS). The generation of a publicly accessible clone repository will allow convenient distribution of these BACs. Ccap data can be correlated with other cancer-associated and genomic databases, such as the catalog of chromosomal aberrations in cancer and the emerging full genomic sequence. We anticipate that the use of Ccap clones will expedite and refine the mapping of chromosomal breakpoints. The eventual set of approximately 3,000 Ccap BACs should facilitate the production of BAC-containing DNA chips for assessing copy number of genomic segments by matrix comparative genomic hybridization. In addition, the repository will provide genome-wide tools for defining chromosomal aberrations in cytological specimens by interphase cytogenetics. The Ccap Web site illustrates goals and progress of this initiative (http://www.ncbi.nlm.nih.gov/CCAP/).

Chromosome Mapping↗