Ismail Moghul

Sequenceserver: a modern graphical user interface for custom BLAST databases

The dramatic drop in DNA sequencing costs has created many opportunities for novel biological research. These opportunities largely rest upon the ability to effectively compare newly obtained and previously known sequences. This is commonly done with BLAST, yet using BLAST directly on new datasets requires substantial technical skills or helpful colleagues. Furthermore, graphical interfaces for BLAST are challenging to install and largely mimic underlying computational processes rather than work patterns of researchers. We combined a user-centric design philosophy with sustainable software development approaches to create Sequenceserver (http://sequenceserver.com), a modern graphical user interface for BLAST. Sequenceserver substantially increases the efficiency of researchers working with sequence data. This is due to innovations at three levels. First, our software can be installed and used on custom datasets extremely rapidly for personal and shared applications. Second, based on analysis of user input and simple algorithms, Sequenceserver reduces the amount of decisions the user must make, provides interactive visual feedback, and prevents common potential errors that would otherwise cause erroneous results. Finally, Sequenceserver provides multiple highly visual and text-based output options that mirror the requirements and work patterns of researchers. Together, these features greatly facilitate BLAST analysis and interpretation and thus substantially enhance researcher productivity.

Discovery of novel representatives of bilaterian neuropeptide families and reconstruction of neuropeptide precursor evolution in ophiuroid echinoderms

Neuropeptides are a diverse class of intercellular signalling molecules that mediate neuronal regulation of many physiological and behavioural processes. Recent advances in genome/transcriptome sequencing are enabling identification of neuropeptide precursor proteins in species from a growing variety of animal taxa, providing new insights into the evolution of neuropeptide signalling. Here, detailed analysis of transcriptome sequence data from three brittle star species, Ophionotus victoriae, Amphiura filiformis and Ophiopsila aranea, has enabled the first comprehensive identification of neuropeptide precursors in the class Ophiuroidea of the phylum Echinodermata. Representatives of over 30 bilaterian neuropeptide precursor families were identified, some of which occur as paralogues. Furthermore, homologues of endothelin/CCHamide, eclosion hormone, neuropeptide-F/Y and nucleobinin/nesfatin were discovered here in a deuterostome/echinoderm for the first time. The majority of ophiuroid neuropeptide precursors contain a single copy of a neuropeptide, but several precursors comprise multiple copies of identical or non-identical, but structurally related, neuropeptides. Here, we performed an unprecedented investigation of the evolution of neuropeptide copy number over a period of approximately 270 Myr by analysing sequence data from over 50 ophiuroid species, with reference to a robust phylogeny. Our analysis indicates that the composition of neuropeptide ‘cocktails’ is functionally important, but with plasticity over long evolutionary time scales.

Phenopolis: an open platform for harmonization and analysis of genetic and phenotypic data.

Summary Phenopolis is an open-source web server providing an intuitive interface to genetic and phenotypic databases. It integrates analysis tools such as variant filtering and gene prioritization based on phenotype. The Phenopolis platform will accelerate clinical diagnosis, gene discovery and encourage wider adoption of the Human Phenotype Ontology in the study of rare genetic diseases. Availability and Implementation A demo of the website is available at https://phenopolis.github.io . If you wish to install a local copy, source code and installation instruction are available at https://github.com/phenopolis . The software is implemented using Python, MongoDB, HTML/Javascript and various bash shell scripts. Contact n.pontikos@ucl.ac.uk. Supplementary information Supplementary data are available at Bioinformatics online.

GeneValidator: identify problems with protein-coding gene predictions

Summary: Genomes of emerging model organisms are now being sequenced at very low cost. However, obtaining accurate gene predictions remains challenging: even the best gene prediction algorithms make substantial errors and can jeopardize subsequent analyses. Therefore, many predicted genes must be time-consumingly visually inspected and manually curated. We developed GeneValidator (GV) to automatically identify problematic gene predictions and to aid manual curation. For each gene, GV performs multiple analyses based on comparisons to gene sequences from large databases. The resulting report identifies problematic gene predictions and includes extensive statistics and graphs for each prediction to guide manual curation efforts. GV thus accelerates and enhances the work of biocurators and researchers who need accurate gene predictions from newly sequenced genomes. Availability and implementation: GV can be used through a web interface or in the command-line. GV is open-source (AGPL), available at https://wurmlab.github.io/tools/genevalidator. Contact: y.wurm@qmul.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online.

PGP-UK: a research and citizen science hybrid project in support of personalized medicine

Molecular analyses such as whole-genome sequencing have become routine and are expected to be transformational for future healthcare and lifestyle decisions. Population-wide implementation of such analyses is, however, not without challenges, and multiple studies are ongoing to identify what these are and explore how they can be addressed. Defined as a research project, the Personal Genome Project UK (PGP-UK) is part of the global PGP network and focuses on open data sharing and citizen science to advance and accelerate personalized genomics and medicine. Here we report our findings on using an open consent recruitment protocol, active participant involvement, open access release of personal genome, methylome and transcriptome data and associated analyses, including 47 new variants predicted to affect gene function and innovative reports based on the analysis of genetic and epigenetic variants. For this pilot study, we recruited ten participants willing to actively engage as citizen scientists with the project. In addition, we introduce Genome Donation as a novel mechanism for openly sharing previously restricted data and discuss the first three donations received. Lastly, we present GenoME, a free, open-source educational app suitable for the lay public to allow exploration of personal genomes. Our findings demonstrate that citizen science-based approaches like PGP-UK have an important role to play in the public awareness, acceptance and implementation of genomics and personalized medicine.

Pheno4J: a gene to phenotype graph database

Summary Efficient storage and querying of large amounts of genetic and phenotypic data is crucial to contemporary clinical genetic research. This introduces computational challenges for classical relational databases, due to the sparsity and sheer volume of the data. Our Java based solution loads annotated genetic variants and well phenotyped patients into a graph database to allow fast efficient storage and querying of large volumes of structured genetic and phenotypic data. This abstracts technical problems away and lets researchers focus on the science rather than the implementation. We have also developed an accompanying webserver with end-points to facilitate querying of the database. Availability and implementation The Java and Python code are available at https://github.com/phenopolis/pheno4j. Contact n.pontikos@ucl.ac.uk. Supplementary information Supplementary data are available at Bioinformatics online.

Phenogenon: Gene to Phenotype Associations for Rare Genetic Diseases

As genome sequencing is increasingly applied to molecular diagnosis of rare Mendelian disorders, large number of patients with diverse phenotypes have their genomic and phenotypic data pooled together to uncover new genotype - phenotype relations. We introduce Phenogenon, a method that combines: the power of Human Phenotype Ontology for describing patient phenotypes, gnomAD for estimating rare variant population frequency, and CADD for variant pathogenicity prediction. By using a divide and conquer approach, we demonstrate here that Phenogenon is able to uncover true gene to phenotype relations, such as “ABCA4 – Macular dystrophy” and “SCN1A – Seizures”. Additionally, it accurately infers mode of inheritance, such as a recessive mode of inheritance in the case of the “ABCA4 – Macular dystrophy” relationship and a dominant mode of inheritance with the “SCN1A – Seizures” relationship. We also found that CADD has more power to detect early-onset rare genetic diseases than late-onset diseases. In this study, we ran Phenogenon against a diverse cohort of 3288 patients. Among the top 13 gene-phenotype relations, seven were previously known. We also highlight four potentially novel gene – phenotype relations such as “SIPA1L3 – Abnormal electroretinogram”.

Whole-genome sequencing reveals a recurrent missense mutation in the Connexin 46 ( GJA3) gene causing autosomal-dominant lamellar cataract

PurposeCongenital cataract, opacification of the ocular lens, is clinically and genetically a heterogeneous childhood disease. In this study we aimed to identify the underlying genetic cause of isolated autosomal-dominant lamellar cataract in a multi-generation English family.MethodsWhole-genome sequencing (WGS) was undertaken in two affected subjects and one unaffected individual. Segregation analysis was performed and a known cataract-causing mutation was identified. Segregation was further validated by sanger sequencing in the entire pedigree.ResultsA heterozygous mutation c.7 G > T; p.D3Y was identified in an NH2-terminal region of the gap junction protein GJA3 and found to co-segregate with disease.ConclusionWe have identified a recurrent mutation in GJA3 in a large British pedigree causing the novel phenotype of autosomal-dominant congenital lamellar cataract. Previously, p.D3Y was found in a Hispanic family causing pulverulent cataract. WGS proved an efficient method to find the underlying molecular cause in this large family, which could not be mapped due to uninformative markers.

GeoDiver: Differential Gene Expression Analysis & Gene-Set Analysis For GEO Datasets

Summary GeoDiver is an online web application for performing Differential Gene Expression Analysis (DGEA) and Generally Applicable Gene-set Enrichment Analysis (GAGE) on gene expression datasets. Users can either analyse publically available data from the Gene Expression Omnibus (GEO) or upload their own datasets. The output produced includes numerous high-quality interactive graphics; allowing users to easily explore and examine complex datasets instantly. Furthermore, the results produced can be reviewed at a later date and share with collaborators. Availability GeoDiver is freely available online at http://www.geodiver.co.uk. The source code is available under the GNU AGPL license on Github: https://github.com/GeoDiver/GEODiver.

Ophiuroid Phylotranscriptomics Enables Discovery Of Novel Echinoderm Representatives Of Bilaterian Neuropeptide Families And Reconstruction Of Neuropeptide Precursor Evolution Over ~270 Million Years

Neuropeptides are a diverse class of intercellular signaling molecules that mediate neuronal regulation of many physiological and behavioural processes. Recent advances in genome/transcriptome sequencing are enabling identification of neuropeptide precursor proteins in species from a growing variety of animal taxa, providing new insights into the evolution of neuropeptide signaling. Here detailed analysis of transcriptome sequence data from three brittle star species, Ophionotus victoriae, Amphiura filiformis and Ophiopsila aranea, has enabled the first comprehensive identification of neuropeptide precursors in the class Ophiuroidea of the phylum Echinodermata. Representatives of over thirty bilaterian neuropeptide precursor families were identified, some of which occur as paralogs. Furthermore, homologs of endothelin/CCHamide, eclosion hormone, neuropeptide-F/Y and nucleobinin/nesfatin were discovered here in a deuterostome/echinoderm for the first time. The majority of ophiuroid neuropeptide precursors contain a single copy of a neuropeptide, but several precursors comprise multiple copies of identical or non-identical, but structurally-related, neuropeptides. Here we performed an unprecedented investigation of the evolution of neuropeptide copy-number over a period of ~270 million years by analysing sequence data from over fifty ophiuroid species, with reference to a robust phylogeny. Our analysis indicates that the composition of neuropeptide “cocktails” is functionally important, but with plasticity over long evolutionary time scales.Background: Neuropeptides are a diverse class of intercellular signaling molecules that mediate neuronal regulation of many physiological and behavioural processes, including feeding, reproduction and locomotion. Recent advances in genome/transcriptome sequencing are enabling identification of neuropeptide precursor proteins in species from a growing variety of animal taxa, providing new insights into the evolution of neuropeptide signaling. Here we report a phylo-transcriptomic analysis of neuropeptide precursors in over fifty species of brittle stars (Class Ophiuroidea; Phylum Echinodermata). Results: Detailed analysis of transcriptome sequence data from three brittle star species, Ophionotus victoriae, Amphiura filiformis and Ophiopsila aranea, enabled the first comprehensive identification of neuropeptide precursors in ophiuroids. Representatives of over thirty bilaterian neuropeptide precursor families were identified, some of which occur as paralogs (e.g. thyrotropin-releasing hormone, corticotropin-releasing hormone, cholecystokinin, somatostatin and pedal peptide). Furthermore, homologs of endothelin/CCHamide, eclosion hormone, neuropeptide-F/Y and nucleobinin/nesfatin were discovered here in a deuterostome/echinoderm for the first time. The majority of ophiuroid neuropeptide precursors contain a single copy of a neuropeptide, but several precursors comprise multiple copies of identical or non-identical, but structurally-related, neuropeptides. Here we performed an unprecedented investigation of the evolution of neuropeptide copy-number over a period of ~270 million years by analysing sequence data from over fifty ophiuroid species, with reference to a robust phylogeny. Interestingly, the number of neuropeptide copies in the majority of precursors was constant across all the species examined, but examples of clade-specific losses/gains of neuropeptides were also observed. Conclusions: We report here the most comprehensive analysis to date of neuropeptide precursors in the phylum Echinodermata, with novel representatives of several bilaterian neuropeptide families discovered for the first time in echinoderms. Furthermore, analysis of precursor proteins comprising multiple copies of identical or related neuropeptides across ~270 million years of ophiuroid evolution indicates that the composition of neuropeptide cocktails is functionally important, but with plasticity over long evolutionary time scales.