Pathway-based, reaction-specific annotation of disease variants for elucidation of molecular phenotypes

Germline and somatic mutations can give rise to proteins with altered activity, including both gain and loss-of-function. The effects of these variants can be captured in disease-specific reactions and pathways that highlight the resulting changes to normal biology. A disease reaction is defined as an aberrant reaction in which a variant protein participates. A disease pathway is defined as a pathway that contains a disease reaction. Annotation of disease variants as participants of disease reactions and disease pathways can provide a standardized overview of molecular phenotypes of pathogenic variants that is amenable to computational mining and mathematical modeling. Reactome (https://reactome.org/), an open source, manually curated, peer-reviewed database of human biological pathways, in addition to providing annotations for >11 000 unique human proteins in the context of ∼15 000 wild-type reactions within more than 2000 wild-type pathways, also provides annotations for >4000 disease variants of close to 400 genes as participants of ∼800 disease reactions in the context of ∼400 disease pathways. Functional annotation of disease variants proceeds from normal gene functions, described in wild-type reactions and pathways, through disease variants whose divergence from normal molecular behaviors has been experimentally verified, to extrapolation from molecular phenotypes of characterized variants to variants of unknown significance using criteria of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Reactome's data model enables mapping of disease variant datasets to specific disease reactions within disease pathways, providing a platform to infer pathway output impacts of numerous human disease variants and model organism orthologs, complementing computational predictions of variant pathogenicity. Database URL: https://reactome.org/.

Oncogenic ETS fusions promote DNA damage and proinflammatory responses via pericentromeric RNAs in extracellular vesicles

Aberrant expression of the E26 transformation-specific (ETS) transcription factors characterizes numerous human malignancies. Many of these proteins, including EWS:FLI1 and EWS:ERG fusions in Ewing sarcoma (EwS) and TMPRSS2:ERG in prostate cancer (PCa), drive oncogenic programs via binding to GGAA repeats. We report here that both EWS:FLI1 and ERG bind and transcriptionally activate GGAA-rich pericentromeric heterochromatin. The respective pathogen-like HSAT2 and HSAT3 RNAs, together with LINE, SINE, ERV, and other repeat transcripts, are expressed in EwS and PCa tumors, secreted in extracellular vesicles (EVs), and are highly elevated in plasma of patients with EwS with metastatic disease. High human satellite 2 and 3 (HSAT2,3) levels in EWS:FLI1- or ERG-expressing cells and tumors were associated with induction of G2/M checkpoint, mitotic spindle, and DNA damage programs. These programs were also activated in EwS EV-treated fibroblasts, coincident with accumulation of HSAT2,3 RNAs, proinflammatory responses, mitotic defects, and senescence. Mechanistically, HSAT2,3-enriched cancer EVs induced cGAS-TBK1 innate immune signaling and formation of cytosolic granules positive for double-strand RNAs, RNA-DNA, and cGAS. Hence, aberrantly expressed ETS proteins derepress pericentromeric heterochromatin, yielding pathogenic RNAs that transmit genotoxic stress and inflammation to local and distant sites. Monitoring HSAT2,3 plasma levels and preventing their dissemination may thus improve therapeutic strategies and blood-based diagnostics.

Drug-target identification in COVID-19 disease mechanisms using computational systems biology approaches

Introduction

The COVID-19 Disease Map project is a large-scale community effort uniting 277 scientists from 130 Institutions around the globe. We use high-quality, mechanistic content describing SARS-CoV-2-host interactions and develop interoperable bioinformatic pipelines for novel target identification and drug repurposing.

Methods

Extensive community work allowed an impressive step forward in building interfaces between Systems Biology tools and platforms. Our framework can link biomolecules from omics data analysis and computational modelling to dysregulated pathways in a cell-, tissue- or patient-specific manner. Drug repurposing using text mining and AI-assisted analysis identified potential drugs, chemicals and microRNAs that could target the identified key factors.

Results

Results revealed drugs already tested for anti-COVID-19 efficacy, providing a mechanistic context for their mode of action, and drugs already in clinical trials for treating other diseases, never tested against COVID-19.

Discussion

The key advance is that the proposed framework is versatile and expandable, offering a significant upgrade in the arsenal for virus-host interactions and other complex pathologies.

ChatGPT usage in the Reactome curation process

Appreciating the rapid advancement and ubiquity of generative AI, particularly ChatGPT, a chatbot using large language models like GPT, we endeavour to explore the potential application of ChatGPT in the data collection and annotation stages within the Reactome curation process. This exploration aimed to create an automated or semi-automated framework to mitigate the extensive manual effort traditionally required for gathering and annotating information pertaining to biological pathways, adopting a Reactome "reaction-centric" approach. In this pilot study, we used ChatGPT/GPT4 to address gaps in the pathway annotation and enrichment in parallel with the conventional manual curation process. This approach facilitated a comparative analysis, where we assessed the outputs generated by ChatGPT against manually extracted information. The primary objective of this comparison was to ascertain the efficiency of integrating ChatGPT or other large language models into the Reactome curation workflow and helping plan our annotation pipeline, ultimately improving our protein-to-pathway association in a reliable and automated or semi-automated way. In the process, we identified some promising capabilities and inherent challenges associated with the utilisation of ChatGPT/GPT4 in general and also specifically in the context of Reactome curation processes. We describe approaches and tools for refining the output given by ChatGPT/GPT4 that aid in generating more accurate and detailed output.

Pathway-based, reaction-specific annotation of disease variants for elucidation of molecular phenotypes

Disease variant annotation in the context of biological reactions and pathways can provide a standardized overview of molecular phenotypes of pathogenic mutations that is amenable to computational mining and mathematical modeling. Reactome, an open source, manually curated, peer-reviewed database of human biological pathways, provides annotations for over 4000 disease variants of close to 400 genes in the context of ∼800 disease reactions constituting ∼400 disease pathways. Functional annotation of disease variants proceeds from normal gene functions, through disease variants whose divergence from normal molecular behaviors has been experimentally verified, to extrapolation from molecular phenotypes of characterized variants to variants of unknown significance using criteria of the American College of Medical Genetics and Genomics (ACMG). Reactome's pathway-based, reaction-specific disease variant dataset and data model provide a platform to infer pathway output impacts of numerous human disease variants and model organism orthologs, complementing computational predictions of variant pathogenicity.

Evaluating the predictive accuracy of curated biological pathways in a public knowledgebase

Abstract

Reactome is a database of human biological pathways manually curated from the primary literature and peer-reviewed by experts. To evaluate the utility of Reactome pathways for predicting functional consequences of genetic perturbations, we compared predictions of perturbation effects based on Reactome pathways against published empirical observations. Ten cancer-relevant Reactome pathways, representing diverse biological processes such as signal transduction, cell division, DNA repair and transcriptional regulation, were selected for testing. For each pathway, root input nodes and key pathway outputs were defined. We then used pathway-diagram-derived logic graphs to predict, either by inspection by biocurators or using a novel algorithm MP-BioPath, the effects of bidirectional perturbations (upregulation/activation or downregulation/inhibition) of single root inputs on the status of key outputs. These predictions were then compared to published empirical tests. In total, 4968 test cases were analyzed across 10 pathways, of which 847 were supported by published empirical findings. Out of the 847 test cases, curators’ predictions agreed with the experimental evidence in 670 and disagreed in 177 cases, resulting in ∼81% overall accuracy. MP-BioPath predictions agreed with experimental evidence for 625 and disagreed for 222 test cases, resulting in ∼75% overall accuracy. The expected accuracy of random guessing was 33%. Per-pathway accuracy did not correlate with the number of pathway edges nor the number of pathway nodes but varied across pathways, ranging from 56% (curator)/44% (MP-BioPath) for ‘Mitotic G1 phase and G1/S transition’ to 100% (curator)/94% (MP-BioPath) for ‘RAF/MAP kinase cascade’. This study highlights the potential of pathway databases such as Reactome in modeling genetic perturbations, promoting standardization of experimental pathway activity readout and supporting hypothesis-driven research by revealing relationships between pathway inputs and outputs that have not yet been directly experimentally tested.

Database URL

www.reactome.org

Reactome enhanced pathway visualization

Motivation

Reactome is a free, open-source, open-data, curated and peer-reviewed knowledge base of biomolecular pathways. Pathways are arranged in a hierarchical structure that largely corresponds to the GO biological process hierarchy, allowing the user to navigate from high level concepts like immune system to detailed pathway diagrams showing biomolecular events like membrane transport or phosphorylation. Here, we present new developments in the Reactome visualization system that facilitate navigation through the pathway hierarchy and enable efficient reuse of Reactome visualizations for users’ own research presentations and publications.

Results

For the higher levels of the hierarchy, Reactome now provides scalable, interactive textbook-style diagrams in SVG format, which are also freely downloadable and editable. Repeated diagram elements like ‘mitochondrion’ or ‘receptor’ are available as a library of graphic elements. Detailed lower-level diagrams are now downloadable in editable PPTX format as sets of interconnected objects.

Availability and implementation

http://reactome.org

Guidelines for the functional annotation of microRNAs using the Gene Ontology

MicroRNA regulation of developmental and cellular processes is a relatively new field of study, and the available research data have not been organized to enable its inclusion in pathway and network analysis tools. The association of gene products with terms from the Gene Ontology is an effective method to analyze functional data, but until recently there has been no substantial effort dedicated to applying Gene Ontology terms to microRNAs. Consequently, when performing functional analysis of microRNA data sets, researchers have had to rely instead on the functional annotations associated with the genes encoding microRNA targets. In consultation with experts in the field of microRNA research, we have created comprehensive recommendations for the Gene Ontology curation of microRNAs. This curation manual will enable provision of a high-quality, reliable set of functional annotations for the advancement of microRNA research. Here we describe the key aspects of the work, including development of the Gene Ontology to represent this data, standards for describing the data, and guidelines to support curators making these annotations. The full microRNA curation guidelines are available on the GO Consortium wiki (http://wiki.geneontology.org/index.php/MicroRNA_GO_annotation_manual).

Over-expression of either MECP2_e1 or MECP2_e2 in neuronally differentiated cells results in different patterns of gene expression

Mutations in MECP2 are responsible for the majority of Rett syndrome cases. MECP2 is a regulator of transcription, and has two isoforms, MECP2_e1 and MECP2_e2. There is accumulating evidence that MECP2_e1 is the etiologically relevant variant for Rett. In this study we aim to detect genes that are differentially transcribed in neuronal cells over-expressing either of these two MECP2 isoforms. The human neuroblastoma cell line SK-N-SH was stably infected by lentiviral vectors over-expressing MECP2_e1, MECP2_e2, or eGFP, and were then differentiated into neurons. The same lentiviral constructs were also used to infect mouse Mecp2 knockout (Mecp2^tm1.1Bird) fibroblasts. RNA from these cells was used for microarray gene expression analysis. For the human neuronal cells, ∼800 genes showed >three-fold change in expression level with the MECP2_e1 construct, and ∼230 with MECP2_e2 (unpaired t-test, uncorrected p value <0.05). We used quantitative RT-PCR to verify microarray results for 41 of these genes. We found significant up-regulation of several genes resulting from over-expression of MECP2_e1 including SRPX2, NAV3, NPY1R, SYN3, and SEMA3D. DOCK8 was shown via microarray and qRT-PCR to be upregulated in both SK-N-SH cells and mouse fibroblasts. Both isoforms up-regulated GABRA2, KCNA1, FOXG1 and FOXP2. Down-regulation of expression in the presence of MECP2_e1 was seen with UNC5C and RPH3A. Understanding the biology of these differentially transcribed genes and their role in neurodevelopment may help us to understand the relative functions of the two MECP2 isoforms, and ultimately develop a better understanding of RTT etiology and determine the clinical relevance of isoform-specific mutations.

Mutations in MECP2 exon 1 in classical Rett patients disrupt MECP2_e1 transcription, but not transcription of MECP2_e2

The overwhelming majority of Rett syndrome cases are caused by mutations in the gene MECP2. MECP2 has two isoforms, termed MECP2_e1 and MECP2_e2, which differ in their N-terminal amino acid sequences. A growing body of evidence has indicated that MECP2_e1 may be the etiologically relevant isoform in Rett Syndrome based on its expression profile in the brain and because, strikingly, no mutations have been discovered that affect MECP2_e2 exclusively. In this study we sought to characterize four classical Rett patients with mutations that putatively affect only the MECP2_e1 isoform. Our hypothesis was that the classical Rett phenotype seen here is the result of disrupted MECP2_e1 expression, but with MECP2_e2 expression unaltered. We used quantitative reverse transcriptase PCR to assay mRNA expression for each isoform independently, and used cytospinning methods to assay total MECP2 in peripheral blood lymphocytes (PBL). In the two Rett patients with identical 11 bp deletions within the coding portion of exon 1, MECP2_e2 levels were unaffected, whilst a significant reduction of MECP2_e1 levels was detected. In two Rett patients harboring mutations in the exon 1 start codon, MECP2_e1 and MECP2_e2 mRNA amounts were unaffected. In summary, we have shown that patients with exon 1 mutations transcribe normal levels of MECP2_e2 mRNA, and most PBL are positive for MeCP2 protein, despite them theoretically being unable to produce the MECP2_e1 isoform, and yet still exhibit the classical RTT phenotype. Altogether, our work further supports our hypothesis that MECP2_e1 is the predominant isoform involved in the neuropathology of Rett syndrome.

The TAg-RB murine retinoblastoma cell of origin has immunohistochemical features of differentiated Muller glia with progenitor properties

PURPOSE

Human retinoblastoma arises from an undefined developing retinal cell after inactivation of RB1. This is emulated in a murine retinoblastoma model by inactivation of pRB by retinal-specific expression of simian virus 40 large T-antigen (TAg-RB). Some mutational events after RB1 loss in humans are recapitulated at the expression level in TAg-RB, supporting preclinical evidence that this model is useful for comparative studies between mouse and human. Here, the characteristics of the TAg-RB cell of origin are defined.

METHODS

TAg-RB mice were killed at ages from embryonic day (E)18 to postnatal day (P)35. Tumors were analyzed by immunostaining, DNA copy number PCR, or real-time quantitative RT-PCR for TAg protein, retinal cell type markers, and retinoblastoma-relevant genes.

RESULTS

TAg expression began at P8 in a row of inner nuclear layer cells that increased in number through P21 to P28, when clusters reminiscent of small tumors emerged from cells that escaped a wave of apoptosis. Early TAg-expressing cells coexpressed the developmental marker Chx10 and glial markers CRALBP, clusterin, and carbonic anhydrase II (Car2), but not TuJ1, an early neuronal marker. Emerging tumors retained expression of only Chx10 and carbonic anhydrase II. As with human retinoblastoma, TAg-RB tumors showed decreased Cdh11 DNA copy number and gain of Kif14 and Mycn. It was confirmed that TAg-RB tumors lose expression of tumor suppressor cadherin-11 and overexpress oncogenes Kif14, Dek, and E2f3.

CONCLUSIONS

TAg-RB tumors displayed molecular similarity to human retinoblastoma and origin in a cell with features of differentiated Müller glia with progenitor properties.

Disruption at the PTCHD1 Locus on Xp22.11 in Autism spectrum disorder and intellectual disability

Autism is a common neurodevelopmental disorder with a complex mode of inheritance. It is one of the most highly heritable of the complex disorders, although the underlying genetic factors remain largely unknown. Here, we report mutations in the X-chromosome PTCHD1 (patched-related) gene in seven families with autism spectrum disorder (ASD) and in three families with intellectual disability. A 167-kilobase microdeletion spanning exon 1 was found in two brothers, one with ASD and the other with a learning disability and ASD features; a 90-kilobase microdeletion spanning the entire gene was found in three males with intellectual disability in a second family. In 900 probands with ASD and 208 male probands with intellectual disability, we identified seven different missense changes (in eight male probands) that were inherited from unaffected mothers and not found in controls. Two of the ASD individuals with missense changes also carried a de novo deletion at another ASD susceptibility locus (DPYD and DPP6), suggesting complex genetic contributions. In additional males with ASD, we identified deletions in the 5' flanking region of PTCHD1 that disrupted a complex noncoding RNA and potential regulatory elements; equivalent changes were not found in male control individuals. Thus, our systematic screen of PTCHD1 and its 5' flanking regions suggests that this locus is involved in ~1% of individuals with ASD and intellectual disability.

Novel 6p rearrangements and recurrent translocation breakpoints in retinoblastoma cell lines identified by spectral karyotyping and mBAND analyses

Gain of the short arm of chromosome 6, usually through isochromosome 6p formation, is present in approximately 50% of retinoblastoma tumors. The minimal region of gain maps to chromosome band 6p22. Two genes, DEK and E2F3, are implicated as candidate oncogenes. However, chromosomal translocations have been overlooked as a potential mechanism of activation of oncogenes at 6p22 in retinoblastoma. Here, we report combined spectral karyotyping), 4',6-diamidino-2-phenylindole banding, mBAND, and locus-specific fluorescence in situ hybridization analyses of four retinoblastoma cell lines, RB1021, RB247c, RB383, and Y79. In RB1021 and RB247c, 6p undergoes structural rearrangements involving a common translocation breakpoint at 6p22. These data imply that 6p translocations may represent another mechanism of activation of 6p oncogene(s) in a subset of retinoblastomas, besides the copy number increase. In addition to 6p22, other recurrent translocation breakpoints identified in this study are 4p16, 11p15, 17q21.3, and 20q13. Common regions of gain map to chromosomal arms 1q, 2p, 6p, 17q, and 21q.