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Biomedical subjects

Ewan Birney

Publications and source records attributed to Ewan Birney.

16 recordsLinked to original sources
PubMed2025

Ophthalmic imaging as a measure of cardiovascular and neurological health: a multi-omic analysis of deep-learning derived phenotypes.

The eye is a recognised source of biomarkers for cardiovascular and neurodegenerative disease risk. Here, we characterise the breadth of these associations and identify biological axes that may mediate them. Using UK Biobank data, we developed a multi-omic analysis pipeline integrating physiological, radiomic, metabolomic, and genomic information. We trained adversarial autoencoders (Ret-AAE) to represent optical coherence tomography (OCT) images and colour fundus photographs as 256-dimensional embeddings. Ret-AAE derived embeddings were associated with a range of cardiovascular and neurodegenerative diseases, including ischaemic heart disease, cerebrovascular disease, Parkinson's disease, and dementia. Examining associations across diverse omics datasets, we provide evidence linking ophthalmic imaging features to neurological and cardiovascular anatomy and function, lipid metabolism, and gene sets associated with neurodegenerative pathology. Collectively, our findings demonstrate that ophthalmic features reflect complex, multisystem biological processes, and reinforce the role of the eye as a composite indicator of systemic health.

Journal Article↗
PubMed2025

Measurement and classification of bold-shy behaviours in medaka fish.

MOTIVATION: Boldness-shyness is considered a fundamental axis of behavioural variation in humans and other species, with obvious adaptive causes and evolutionary implications. Besides an individual's own genetics, this phenotype is also affected by the genetic make-up of peers in the individual's social environment. To identify genetic determinants of variation along the bold-shy behavioural axis, a reliable experimental and analytical set-up able to highlight direct and indirect genetic effects is needed. RESULTS: We describe a custom assay designed to detect bold-shy behaviours in medaka fish, combining an open-field and novel-object component. We use this assay to explore direct and social genetic effects on the behaviours of 307 pairs of fish from five inbred medaka strains. Applying a hidden Markov model (HMM) to classify behavioural modes, we find that direct genetic effects influence the proportions of time the five strains spent in slow-moving states, explaining up to 29.7% of the variance in time spent in those states. We also found that an individual's behaviour is influenced by the genetics of its tank partner, explaining up to 8.64% of the variance in the time spent in slow-moving states. Our behavioural assay in combination with the HMM analysis is applicable to follow-up genetic linkage studies of genetic variants involved in direct behavioural effects and indirect social genetic effects. A suitable genetic resource for such studies, the Medaka Inbred Kiyosu-Karlsruhe (MIKK) panel has recently been established. AVAILABILITY AND IMPLEMENTATION: The code associated with this work is available on GitHub (https://github.com/birneylab/medaka_behaviour_pilot) and Software Heritage (swh: 1: dir: c9abec1c5d62d22e43c9e97d995c56261784d9ab). Experimental data have been uploaded to the EBI Bioimage Archive (https://doi.org/10.6019/S-BIAD1421).

Animals↗
PubMed2005

Gene finding in the chicken genome.

BACKGROUND: Despite the continuous production of genome sequence for a number of organisms, reliable, comprehensive, and cost effective gene prediction remains problematic. This is particularly true for genomes for which there is not a large collection of known gene sequences, such as the recently published chicken genome. We used the chicken sequence to test comparative and homology-based gene-finding methods followed by experimental validation as an effective genome annotation method. RESULTS: We performed experimental evaluation by RT-PCR of three different computational gene finders, Ensembl, SGP2 and TWINSCAN, applied to the chicken genome. A Venn diagram was computed and each component of it was evaluated. The results showed that de novo comparative methods can identify up to about 700 chicken genes with no previous evidence of expression, and can correctly extend about 40% of homology-based predictions at the 5' end. CONCLUSIONS: De novo comparative gene prediction followed by experimental verification is effective at enhancing the annotation of the newly sequenced genomes provided by standard homology-based methods.

Animals↗
PubMed2004

EnsMart: a generic system for fast and flexible access to biological data.

The EnsMart system (www.ensembl.org/EnsMart) provides a generic data warehousing solution for fast and flexible querying of large biological data sets and integration with third-party data and tools. The system consists of a query-optimized database and interactive, user-friendly interfaces. EnsMart has been applied to Ensembl, where it extends its genomic browser capabilities, facilitating rapid retrieval of customized data sets. A wide variety of complex queries, on various types of annotations, for numerous species are supported. These can be applied to many research problems, ranging from SNP selection for candidate gene screening, through cross-species evolutionary comparisons, to microarray annotation. Users can group and refine biological data according to many criteria, including cross-species analyses, disease links, sequence variations, and expression patterns. Both tabulated list data and biological sequence output can be generated dynamically, in HTML, text, Microsoft Excel, and compressed formats. A wide range of sequence types, such as cDNA, peptides, coding regions, UTRs, and exons, with additional upstream and downstream regions, can be retrieved. The EnsMart database can be accessed via a public Web site, or through a Java application suite. Both implementations and the database are freely available for local installation, and can be extended or adapted to 'non-Ensembl' data sets.

Animals↗
PubMed2003

The European Bioinformatics Institute's data resources.

As the amount of biological data grows, so does the need for biologists to store and access this information in central repositories in a free and unambiguous manner. The European Bioinformatics Institute (EBI) hosts six core databases, which store information on DNA sequences (EMBL-Bank), protein sequences (SWISS-PROT and TrEMBL), protein structure (MSD), whole genomes (Ensembl) and gene expression (ArrayExpress). But just as a cell would be useless if it couldn't transcribe DNA or translate RNA, our resources would be compromised if each existed in isolation. We have therefore developed a range of tools that not only facilitate the deposition and retrieval of biological information, but also allow users to carry out searches that reflect the interconnectedness of biological information. The EBI's databases and tools are all available on our website at www.ebi.ac.uk.

Animals↗
PubMed2003

Comparative genomics: genome-wide analysis in metazoan eukaryotes.

The increasing number of complete and nearly complete metazoan genome sequences provides a significant amount of material for large-scale comparative genomic analysis. Finding new effective methods to analyse such enormous datasets has been the object of intense research. Three main areas in comparative genomics have recently shown important developments: whole-genome alignment, gene prediction and regulatory-region prediction. Each of these areas improves the methods of deciphering long genomic sequences and uncovering what lies hidden in them.

Animals↗
PubMed2003

Discovering novel cis-regulatory motifs using functional networks.

We combined functional information such as protein-protein interactions or metabolic networks with genome information in Saccharomyces cerevisiae to predict cis-regulatory motifs in the upstream region of genes. We developed a new scoring metric combining these two information sources and used this metric in motif discovery. To estimate the statistical significance of this metric, we used brute-force randomization, which shows a consistent well-behaved trend. In contrast, real data showed complex nonrandom behavior. With conservative parameters we were able to find 42 degenerate motifs (that touch 40% of yeast genes) based on 647 original patterns, five of which are well known. Some of these motifs also show limited spatial position in the promoter, indicative of a true motif. We also tested the metric on other known motifs and show that this metric is a good discriminator of real motifs. As well as a pragmatic motif discovery method, with many applications beyond this work, these results also show that interacting proteins are often coordinated at the level of transcription, even in the absence of obvious coregulation in gene expression data sets.

Amino Acid Motifs↗
PubMed2002

Initial sequencing and comparative analysis of the mouse genome.

The sequence of the mouse genome is a key informational tool for understanding the contents of the human genome and a key experimental tool for biomedical research. Here, we report the results of an international collaboration to produce a high-quality draft sequence of the mouse genome. We also present an initial comparative analysis of the mouse and human genomes, describing some of the insights that can be gleaned from the two sequences. We discuss topics including the analysis of the evolutionary forces shaping the size, structure and sequence of the genomes; the conservation of large-scale synteny across most of the genomes; the much lower extent of sequence orthology covering less than half of the genomes; the proportions of the genomes under selection; the number of protein-coding genes; the expansion of gene families related to reproduction and immunity; the evolution of proteins; and the identification of intraspecies polymorphism.

Animals↗
PubMed2002

Comparative genome and proteome analysis of Anopheles gambiae and Drosophila melanogaster.

Comparison of the genomes and proteomes of the two diptera Anopheles gambiae and Drosophila melanogaster, which diverged about 250 million years ago, reveals considerable similarities. However, numerous differences are also observed; some of these must reflect the selection and subsequent adaptation associated with different ecologies and life strategies. Almost half of the genes in both genomes are interpreted as orthologs and show an average sequence identity of about 56%, which is slightly lower than that observed between the orthologs of the pufferfish and human (diverged about 450 million years ago). This indicates that these two insects diverged considerably faster than vertebrates. Aligned sequences reveal that orthologous genes have retained only half of their intron/exon structure, indicating that intron gains or losses have occurred at a rate of about one per gene per 125 million years. Chromosomal arms exhibit significant remnants of homology between the two species, although only 34% of the genes colocalize in small "microsyntenic" clusters, and major interarm transfers as well as intra-arm shuffling of gene order are detected.

Animals↗
PubMed2002

Immunity-related genes and gene families in Anopheles gambiae.

We have identified 242 Anopheles gambiae genes from 18 gene families implicated in innate immunity and have detected marked diversification relative to Drosophila melanogaster. Immune-related gene families involved in recognition, signal modulation, and effector systems show a marked deficit of orthologs and excessive gene expansions, possibly reflecting selection pressures from different pathogens encountered in these insects' very different life-styles. In contrast, the multifunctional Toll signal transduction pathway is substantially conserved, presumably because of counterselection for developmental stability. Representative expression profiles confirm that sequence diversification is accompanied by specific responses to different immune challenges. Alternative RNA splicing may also contribute to expansion of the immune repertoire.

Alternative Splicing↗
PubMed2002

A physical map of the mouse genome.

A physical map of a genome is an essential guide for navigation, allowing the location of any gene or other landmark in the chromosomal DNA. We have constructed a physical map of the mouse genome that contains 296 contigs of overlapping bacterial clones and 16,992 unique markers. The mouse contigs were aligned to the human genome sequence on the basis of 51,486 homology matches, thus enabling use of the conserved synteny (correspondence between chromosome blocks) of the two genomes to accelerate construction of the mouse map. The map provides a framework for assembly of whole-genome shotgun sequence data, and a tile path of clones for generation of the reference sequence. Definition of the human-mouse alignment at this level of resolution enables identification of a mouse clone that corresponds to almost any position in the human genome. The human sequence may be used to facilitate construction of other mammalian genome maps using the same strategy.

Animals↗
PubMed2002

Genome annotation techniques: new approaches and challenges.

As more of the human genome draft sequence is finished, and genomes from other organisms begin to be sequenced, the demand for accurate and reliable genome annotation will increase significantly. To facilitate this industrial-scale genome annotation, automated bioinformatics solutions are increasingly required. As a result, automatic genome annotation systems have become more important in gene discovery within recent years. The design of such large-scale bioinformatics systems is an evolving and dynamic field, based on central cores of bioinformatics software tools and relational databases. Not only must these systems efficiently manage and integrate large volumes of genomic data, but they must also deliver accurate gene predictions and effectively distribute annotation data to the biosciences community.

Computational Biology↗
PubMed2002

Databases and tools for browsing genomes.

To maximize the value of genome sequences they need to be integrated with other types of biological data and with each other. The entire collection of data then needs to be made available in a way that is easy to view and mine for complex relationships. The recently determined vertebrate genome sequences of human and mouse are so large that building the infrastructure to manage these datasets is a major challenge. This article reviews the database systems and tools for analysis that have so far been developed to address this.

Animals↗
PubMed2002

The Pfam protein families database.

Pfam is a large collection of protein multiple sequence alignments and profile hidden Markov models. Pfam is available on the World Wide Web in the UK at http://www.sanger.ac.uk/Software/Pfam/, in Sweden at http://www.cgb.ki.se/Pfam/, in France at http://pfam.jouy.inra.fr/ and in the US at http://pfam.wustl.edu/. The latest version (6.6) of Pfam contains 3071 families, which match 69% of proteins in SWISS-PROT 39 and TrEMBL 14. Structural data, where available, have been utilised to ensure that Pfam families correspond with structural domains, and to improve domain-based annotation. Predictions of non-domain regions are now also included. In addition to secondary structure, Pfam multiple sequence alignments now contain active site residue mark-up. New search tools, including taxonomy search and domain query, greatly add to the functionality and usability of the Pfam resource.

Animals↗
PubMed2002

The Bioperl toolkit: Perl modules for the life sciences.

The Bioperl project is an international open-source collaboration of biologists, bioinformaticians, and computer scientists that has evolved over the past 7 yr into the most comprehensive library of Perl modules available for managing and manipulating life-science information. Bioperl provides an easy-to-use, stable, and consistent programming interface for bioinformatics application programmers. The Bioperl modules have been successfully and repeatedly used to reduce otherwise complex tasks to only a few lines of code. The Bioperl object model has been proven to be flexible enough to support enterprise-level applications such as EnsEMBL, while maintaining an easy learning curve for novice Perl programmers. Bioperl is capable of executing analyses and processing results from programs such as BLAST, ClustalW, or the EMBOSS suite. Interoperation with modules written in Python and Java is supported through the evolving BioCORBA bridge. Bioperl provides access to data stores such as GenBank and SwissProt via a flexible series of sequence input/output modules, and to the emerging common sequence data storage format of the Open Bioinformatics Database Access project. This study describes the overall architecture of the toolkit, the problem domains that it addresses, and gives specific examples of how the toolkit can be used to solve common life-sciences problems. We conclude with a discussion of how the open-source nature of the project has contributed to the development effort.

Algorithms↗