Mucaki, E.J., Shirley, B.C. and Rogan, P.K., 2020. Expression changes confirm genomic variants predicted to result in allele-specific, alternative mRNA splicing. Frontiers in Genetics, 11: 109 (https://www.frontiersin.org/articles/10.3389/fgene.2020.00109/full).
(preprint in bioRxiv, 549089 [doi: https://doi.org/10.1101/549089])
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The following paper has been accepted for presentation:
“Pan-Cancer Repository of Validated Natural and Cryptic mRNA Splicing Mutations”,
Category: “Laboratory genetics and genomics”, Abstract Poster Number: 754 (link to Abstract)
Where: Exhibit hall, Washington Convention Center, ACMG Clinical Genetics Meeting in Seattle, Washington
When: April 2 – 6, 2019; Poster presentation time: Friday, 4/5 from 10:30am-12:00pm
This work will be available as an ePoster AS WELL AS being presented in printed format on a poster board during the Annual Meeting. Details to access the ePoster will be available soon.
Peter Rogan, President of Cytognomix has been invited by Oxford Global to present at the 6th Annual Next Generation Sequencing Congress at the Queen Elizabeth II Conference Center in London, UK on Nov. 21, 2014. The oral presentation is titled: “Impact Of Non-coding Mutation Analysis In Hereditary and Somatic Breast Cancer.” In the talk, Dr. Rogan will showcase results of the use of Cytognomix’s software and genomic reagents to obtain new insights into the genomic abnormalities present in breast cancer.
MutationForecaster® (mutationforecaster.com) is Cytognomix’s patented web-portal for analysis of all types of mutations (coding and non-coding), including interpretation, comparison and management of genetic variant data. It’s a fully automated genome interpretation solution for research, translational and clinical labs.
MutationForecaster® combines our world-leading genome interpretation software on your exome, gene panel, or complete genome (Shannon transcription factor and splicing pipelines, ASSEDA, Veridical) with the Cytognomix User Variation Database and Variant Effect Predictor. With our integrated suite of software products, analyze coding, non-coding, and copy number variants, and compare new results with existing or your own database. Select predicted mutations by phenotype using articles with Cyto Visualization Analytics. With Workflows, automatically perform end-to-end analysis with all of our software products.
Download an 1 page overview of MutationForecaster®: link .
You can now experience our integrated suite of genome interpretation products through a free trial of MutationForecaster®. Once you register, analyze datasets that we have analyzed in our peer-reviewed publications with any of our software tools.
To obtain a subscription (2 months or 1 year [pricing]) to MutationForecaster®, please contact us.
Don’t want to run your own analyses? Let us do it for you with our Bespoke Analysis Service.
mutationforecaster.com
Volume 34, Issue 4
“Prediction of mutant mRNA splice isoforms by information theory-based exon definition,” by Eliseos Mucaki, Ben Shirley and Peter Rogan has been accepted for publication by the journal Human Mutation.
Abstract. Mutations that affect mRNA splicing often produce multiple mRNA isoforms, resulting in complex molecular phenotypes. Definition of an exon and its inclusion in mature mRNA relies on joint recognition of both acceptor and donor splice sites. This study predicts cryptic and exon skipping isoforms in mRNA produced by splicing mutations from the combined information contents (Ri, which measures binding site affinity) and distribution of the splice sites defining these exons. The total information content of an exon (Ri,total) is the sum of the Ri values of its acceptor and donor splice sites, adjusted for the distance separating these sites, ie. the gap surprisal. Differences between total exon information contents (ΔRi,total) are predictive of the relative abundance of these exons in distinct processed mRNAs. Constraints on splice site and exon selection are used to eliminate non-conforming and poorly expressed isoforms. Molecular phenotypes are computed by the Automated Splice Site and Exon Definition Analysis server (ASSEDA; http://splice.uwo.ca). Predictions of splicing mutations were highly concordant (85.2%; n=61) with published expression data. In silico exon definition analysis will contribute to streamlining assessment of abnormal and normal splice isoforms resulting from mutations.
Update: The paper is now available online from the Journal website: DOI: 10.1002/humu.22277 and is cited on PubMed.
Update 2: John Mucaki has produced a Video Tutorial on using the ASSEDA server on YouTube.
Update 3: The accepted paper has now been copyedited, typeset and published online: http://onlinelibrary.wiley.com/doi/10.1002/humu.22277/abstract. Supplementary data are available as well. (2-21-2013)
Update 4: Annual subscriptions to the Automated Splice Site and Exon Definition server are available through Cytognomix (2-22-2013).
Update 5: The paper has been highlighted in the April 2013 issue of the Journal, where it appeared. Bing Yu, University of Sydney, authored the commentary (Vol 34[4], page v).
Update 6: Mucaki EJ., Shirley BC, and Rogan PK. Prediction of Mutant mRNA Splice Isoforms by Information Theory-Based Exon Definition has been published in print. Human Mutation, April 2013, Volume 34 (4), pages 557–565. The journal has made the paper FREE for anyone to download.
Monitoring and discriminating infectious disease hotspots from high disease burden regions, eg. for COVID-19:
Zenodo repository: Geostatistical Analysis of SARS-CoV-2 Positive Cases in the United States
Defence Canada IDEaS project: Locating emerging COVID19 hotspots in Ontario after community transmission by time-correlated, geospatial analysis
Addressing large scale radiation incidents and accidents:
Article in PLOS One: Meeting radiation dosimetry capacity requirements of population-scale exposures …. (Funded by High performance computing consortium: SOSCIP and CytoGnomix)
How to: Protocol for Geostatistical Determination of Radiation Dosimetry Maps of Population-Scale Exposures
Capacity of supercomputer version of Automated Dicentric Chromosome Identifier and Dose Estimator (ADCI) software: Automated Cytogenetic Biodosimetry at Population-Scale and Radiation, Radiation, 2021 (link to published article).
Scalable, democratized access to ADCI:
Overview of Cloud version- ADCI_Online
Presentation to the International Atomic Energy Agency (CRP E35010)
Mucaki, E.J., Shirley, B.C. and Rogan, P.K., 2021. Improved radiation expression profiling in blood by sequential application of sensitive and specific gene signatures. International Journal of Radiation Biology, doi.org/10.1080/09553002.2021.1998709 Link to pdf: Improved radiation expression profiling…
Zhao, J.Z., Mucaki, E.J. and Rogan, P.K., 2018. Predicting ionizing radiation exposure using biochemically-inspired genomic machine learning. F1000Research, 7(233), p.233. Link to open access article: https://f1000research.com/articles/7-233
Pan-cancer repository of validated natural and cryptic mRNA splicing mutations (a major public resource of mRNA splicing mutations validated according to multiple lines of evidence of abnormal gene expression. )
Article in F1000Research: Pan-Cancer repository of …..
Presentation at the 2019 American College of Medical Genetics Annual Meeting:
Pan-cancer repository of validated natural and cryptic mRNA.ePoster
Caminsky et al. 2014, Videos describing this paper: short and long versions.
Cytognomix has a well-maintained portfolio of multiple issued and pending patents covering its intellectual property which it either owns or licenses:
Complete list of Patents and Patent applications
Information theory based binding site analysis. This invention detects and quantifies the strengths of binding sites in nucleic acids. Binding sites are defined based upon the individual information content of a particular site of interest (US Patent 5,867,402). Substitutions within the binding site sequences can be analyzed to determine whether the substitution will cause a deleterious mutation or a benign polymorphism. In addition, new binding sites can be identified using individual information content. Further a computer system is described for determining and displaying individual information content of a binding site sequence. Several software products have been created and distributed based on this technology, including the ASSA server and the Shannon pipeline. ASSA has be upgraded to the ASSEDA server (Mucaki et al., 2013) which extends this technology to predict mutant mRNA isoforms generated from individual mutations. This works by defining the total individual information of a set of binding sites (including splicing regulatory sites) that recognize a common functional unit, which, in this instance, is an exon (US Pat. App. 14/154,905). We have also implemented our Shannon pipeline software which uses this technology on a genome scale to analyze the molecular phenotypes of splicing-related gene variants discovered in exomes, genomes or targeted sequencing. Results from the Shannon pipeline are validated with Veridical, software which uses matched RNA-Seq data to corroborate predictions (US Pat. App. 14/594,109).
Single copy technology. As important as the protection, is the fact that the SC technology does not infringe on any patents controlled any other organization. US Patent No. 7,734,424 covers the foundational “abinitio”TM technology currently used in probe and microarray designs. US Patents 8,209,129 and 8,407,013 cover single copy DNA probes which include divergent repetitive sequences, thus significantly extending the portions of the genome that can be used for such probes beyond traditional single copy sequences. The technology also increases the density of genomic DNA probes for higher resolution genetic analysis beyond what is used in FISH, genomic microarrays for array comparative genomic hybridization, and solution capture hybridization arrays for sequence enrichment in deep sequencing. It is licensed to Cytognomix.
Cytognomix’s SC FISH probes are one of several products that come from applications of “Ab-initio” design algorithms. The method depends on finished genome sequences as the raw template for a recursive algorithm that results in “single copy” sequence information (which are unique in the genome sequence) and corresponding oligonucleotide or FISH products. The algorithm can easily be applied to any completed genome sequence, limited only by the quality of the input sequences and processing time. The output is in the form of “single copy intervals”, generally varying size from hundreds to thousands of nucleotides. The ab-initio method makes use of parallel computing resources to reduce the time required to identify single copy intervals and distinguish them from repeated sequences.
The Ab-initio process confers advantages over purely repeat-masked probes, which we previously developed (US Pats. 6,828,097, 7,014,997 and others). The design criteria permit inclusion of highly divergent interspersed repeated sequences that don’t cross-hybridize to other genomic locations. This opens up access to regions of the genome that are not covered by our previous inventions. If desired, ab-initio probes can optionally exclude segmental duplications and self-chain blocks of low copy sequences capable of cross-hybridizing to undesirable genomic targets. Aside from FISH, genomic microarrays, and NGS capture reagents, ab-initio single copy sequences have been used to identify stable genes in breast tumour genomes, whose products are often targets of chemotherapy agents (US Pat. App. Ser. No. 13/744,459, US Patent 9,624,549). This technology has led to novel algorithms and copyrighted software that accurately predict cellular and patient responses tailored to individual chemotherapy drugs (chemotherapy.cytognomix.com).
Cytogenetic biodosimetry. Our genome coordinate-based FISH products led us to develop image processing algorithms for automated detection of chromosome abnormalities, which have been published as papers and patent applications. We created new methods for ranking and segmenting chromosome images, which has led to new applications in biological radiation biodosimetry. These technologies are covered by US Patents 8,605,981 and 10,929,641, German Patent 11 2011103687, and other patents pending (PCT/US11/59257, US Pat. App. Ser No. 17/137,317). This technology completely automates the interpretation of dicentric chromosomes for individuals exposed to gamma radiation. The corresponding software, the Automated Dicentric Chromosome Identifier and Dose Estimator (or ADCI), has been implemented for desktop/notebook and high performance computing systems. Data from thousands of patient samples can be analyzed in a few hours. We have recently demonstrated that ADCI can quantify partial body radiation exposures, which are typically used in radiation oncology therapy. We will seek regulatory approval for use of ADCI as a medical device for use in monitoring therapy.