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Article ; Online: nf-core/circrna: a portable workflow for the quantification, miRNA target prediction and differential expression analysis of circular RNAs.

Digby, Barry / Finn, Stephen P / Ó Broin, Pilib

2023 Volume 24, Issue 1, Page(s) 27

Abstract: Background: Circular RNAs (circRNAs) are a class of covalenty closed non-coding RNAs that have garnered increased attention from the research community due to their stability, tissue-specific expression and role as transcriptional modulators via ... ...

Abstract	Background: Circular RNAs (circRNAs) are a class of covalenty closed non-coding RNAs that have garnered increased attention from the research community due to their stability, tissue-specific expression and role as transcriptional modulators via sequestration of miRNAs. Currently, multiple quantification tools capable of detecting circRNAs exist, yet none delineate circRNA-miRNA interactions, and only one employs differential expression analysis. Efforts have been made to bridge this gap by way of circRNA workflows, however these workflows are limited by both the types of analyses available and computational skills required to run them. Results: We present nf-core/circrna, a multi-functional, automated high-throughput pipeline implemented in nextflow that allows users to characterise the role of circRNAs in RNA Sequencing datasets via three analysis modules: (1) circRNA quantification, robust filtering and annotation (2) miRNA target prediction of the mature spliced sequence and (3) differential expression analysis. nf-core/circrna has been developed within the nf-core framework, ensuring robust portability across computing environments via containerisation, parallel deployment on cluster/cloud-based infrastructures, comprehensive documentation and maintenance support. Conclusion: nf-core/circrna reduces the barrier to entry for researchers by providing an easy-to-use, platform-independent and scalable workflow for circRNA analyses. Source code, documentation and installation instructions are freely available at https://nf-co.re/circrna and https://github.com/nf-core/circrna .
MeSH term(s)	MicroRNAs/genetics ; MicroRNAs/metabolism ; RNA, Circular ; Workflow ; Software ; Sequence Analysis, RNA
Chemical Substances	MicroRNAs ; RNA, Circular
Language	English
Publishing date	2023-01-24
Publishing country	England
Document type	Journal Article
ZDB-ID	2041484-5
ISSN	1471-2105 ; 1471-2105
ISSN (online)	1471-2105
ISSN	1471-2105
DOI	10.1186/s12859-022-05125-8
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: CCPlotR: an R package for the visualization of cell-cell interactions.

Ennis, Sarah / Ó Broin, Pilib / Szegezdi, Eva

Bioinformatics advances

2023 Volume 3, Issue 1, Page(s) vbad130

Abstract: Summary: We present CCPlotR-an R package that generates visualizations of cell-cell interactions. CCPlotR is designed to work with the output of tools that predict cell-cell interactions from single-cell gene expression data and requires only a table of ...

Abstract	Summary: We present CCPlotR-an R package that generates visualizations of cell-cell interactions. CCPlotR is designed to work with the output of tools that predict cell-cell interactions from single-cell gene expression data and requires only a table of predicted interactions as input. The package can generate a comprehensive set of publication-ready figures such as heatmaps, dotplots, circos plots and network diagrams, providing a useful resource for researchers working on cell-cell interactions. Availability and implementation: CCPlotR is available to download and install from GitHub (https://github.com/Sarah145/CCPlotR) and comes with a toy dataset to demonstrate the different functions. Support for users will be provided via the GitHub issues tracker (https://github.com/Sarah145/CCPlotR/issues).
Language	English
Publishing date	2023-09-20
Publishing country	England
Document type	Journal Article
ISSN	2635-0041
ISSN (online)	2635-0041
DOI	10.1093/bioadv/vbad130
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Article: Surrogate Biomarker Prediction from Whole-Slide Images for Evaluating Overall Survival in Lung Adenocarcinoma.

Murchan, Pierre / Baird, Anne-Marie / Ó Broin, Pilib / Sheils, Orla / Finn, Stephen P

Diagnostics (Basel, Switzerland)

2024 Volume 14, Issue 5

Abstract: Background: Recent advances in computational pathology have shown potential in predicting biomarkers from haematoxylin and eosin (H&E) whole-slide images (WSI). However, predicting the outcome directly from WSIs remains a substantial challenge. In this ... ...

Abstract	Background: Recent advances in computational pathology have shown potential in predicting biomarkers from haematoxylin and eosin (H&E) whole-slide images (WSI). However, predicting the outcome directly from WSIs remains a substantial challenge. In this study, we aimed to investigate how gene expression, predicted from WSIs, could be used to evaluate overall survival (OS) in patients with lung adenocarcinoma (LUAD). Methods: Differentially expressed genes (DEGs) were identified from The Cancer Genome Atlas (TCGA)-LUAD cohort. Cox regression analysis was performed on DEGs to identify the gene prognostics of OS. Attention-based multiple instance learning (AMIL) models were trained to predict the expression of identified prognostic genes from WSIs using the TCGA-LUAD dataset. Models were externally validated in the Clinical Proteomic Tumour Analysis Consortium (CPTAC)-LUAD dataset. The prognostic value of predicted gene expression values was then compared to the true gene expression measurements. Results: The expression of 239 prognostic genes could be predicted in TCGA-LUAD with cross-validated Pearson's R > 0.4. Predicted gene expression demonstrated prognostic performance, attaining a cross-validated concordance index of up to 0.615 in TCGA-LUAD through Cox regression. In total, 36 genes had predicted expression in the external validation cohort that was prognostic of OS. Conclusions: Gene expression predicted from WSIs is an effective method of evaluating OS in patients with LUAD. These results may open up new avenues of cost- and time-efficient prognosis assessment in LUAD treatment.
Language	English
Publishing date	2024-02-20
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2662336-5
ISSN	2075-4418
ISSN	2075-4418
DOI	10.3390/diagnostics14050462
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Article ; Online: Genes positively regulated by Mef2c in cortical neurons are enriched for common genetic variation associated with IQ and educational attainment.

Fahey, Laura / Ali, Deema / Donohoe, Gary / Ó Broin, Pilib / Morris, Derek W

Human molecular genetics

2023 Volume 32, Issue 22, Page(s) 3194–3203

Abstract: The myocyte enhancer factor 2 C (MEF2C) gene encodes a transcription factor important for neurogenesis and synapse development and contains common variants associated with intelligence (IQ) and educational attainment (EA). Here, we took gene expression ... ...

Abstract	The myocyte enhancer factor 2 C (MEF2C) gene encodes a transcription factor important for neurogenesis and synapse development and contains common variants associated with intelligence (IQ) and educational attainment (EA). Here, we took gene expression data from the mouse cortex of a Mef2c mouse model with a heterozygous DNA binding-deficient mutation of Mef2c (Mef2c-het) and combined these data with MEF2C ChIP-seq data from cortical neurons and single-cell data from the mouse brain. This enabled us to create a set of genes that were differentially regulated in Mef2c-het mice, represented direct target genes of MEF2C and had elevated in expression in cortical neurons. We found this gene-set to be enriched for genes containing common genetic variation associated with IQ and EA. Genes within this gene-set that were down-regulated, i.e. have reduced expression in Mef2c-het mice versus controls, were specifically significantly enriched for both EA and IQ associated genes. These down-regulated genes were enriched for functionality in the adenylyl cyclase signalling system, which is known to positively regulate synaptic transmission and has been linked to learning and memory. Within the adenylyl cyclase signalling system, three genes regulated by MEF2C, CRHR1, RGS6, and GABRG3, are associated at genome-wide significant levels with IQ and/or EA. Our results indicate that genetic variation in MEF2C and its direct target genes within cortical neurons contribute to variance in cognition within the general population, and the molecular mechanisms involved include the adenylyl cyclase signalling system's role in synaptic function.
MeSH term(s)	Humans ; Mice ; Animals ; Adenylyl Cyclases/genetics ; Neurons/metabolism ; MEF2 Transcription Factors/genetics ; Educational Status ; Genetic Variation
Chemical Substances	Adenylyl Cyclases (EC 4.6.1.1) ; MEF2 Transcription Factors ; Mef2c protein, mouse
Language	English
Publishing date	2023-10-26
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	1108742-0
ISSN	1460-2083 ; 0964-6906
ISSN (online)	1460-2083
ISSN	0964-6906
DOI	10.1093/hmg/ddad142
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Article: Thirteen Independent Genetic Loci Associated with Preserved Processing Speed in a Study of Cognitive Resilience in 330,097 Individuals in the UK Biobank

Fitzgerald, Joan / Fahey, Laura / Holleran, Laurena / Ó Broin, Pilib / Donohoe, Gary / Morris, Derek W.

Genes. 2022 Jan. 10, v. 13, no. 1

2022

Abstract: Cognitive resilience is the ability to withstand the negative effects of stress on cognitive functioning and is important for maintaining quality of life while aging. The UK Biobank does not have measurements of the same cognitive phenotype at distal ... ...

Abstract	Cognitive resilience is the ability to withstand the negative effects of stress on cognitive functioning and is important for maintaining quality of life while aging. The UK Biobank does not have measurements of the same cognitive phenotype at distal time points. Therefore, we used education years (EY) as a proxy phenotype for past cognitive performance and current cognitive performance was based on processing speed. This represented an average time span of 40 years between past and current cognitive performance in 330,097 individuals. A confounding factor was that EY is highly polygenic and masked the genetics of resilience. To overcome this, we employed Genomics Structural Equation Modelling (GenomicSEM) to perform a genome-wide association study (GWAS)-by-subtraction using two GWAS, one GWAS of EY and resilience and a second GWAS of EY but not resilience, to generate a GWAS of Resilience. Using independent discovery and replication samples, we found 13 independent genetic loci for Resilience. Functional analyses showed enrichment in several brain regions and specific cell types. Gene-set analyses implicated the biological process “neuron differentiation”, the cellular component “synaptic part” and the “WNT signalosome”. Mendelian randomisation analysis showed a causative effect of white matter volume on cognitive resilience. These results may contribute to the neurobiological understanding of resilience.
Keywords	brain ; cognition ; education ; equations ; genome-wide association study ; genomics ; phenotype ; quality of life
Language	English
Dates of publication	2022-0110
Publishing place	Multidisciplinary Digital Publishing Institute
Document type	Article
ZDB-ID	2527218-4
ISSN	2073-4425
ISSN	2073-4425
DOI	10.3390/genes13010122
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: Thirteen Independent Genetic Loci Associated with Preserved Processing Speed in a Study of Cognitive Resilience in 330,097 Individuals in the UK Biobank.

Fitzgerald, Joan / Fahey, Laura / Holleran, Laurena / Ó Broin, Pilib / Donohoe, Gary / Morris, Derek W

Genes

2022 Volume 13, Issue 1

Abstract	Cognitive resilience is the ability to withstand the negative effects of stress on cognitive functioning and is important for maintaining quality of life while aging. The UK Biobank does not have measurements of the same cognitive phenotype at distal time points. Therefore, we used education years (EY) as a proxy phenotype for past cognitive performance and current cognitive performance was based on processing speed. This represented an average time span of 40 years between past and current cognitive performance in 330,097 individuals. A confounding factor was that EY is highly polygenic and masked the genetics of resilience. To overcome this, we employed Genomics Structural Equation Modelling (GenomicSEM) to perform a genome-wide association study (GWAS)-by-subtraction using two GWAS, one GWAS of EY and resilience and a second GWAS of EY but not resilience, to generate a GWAS of
MeSH term(s)	Adaptation, Psychological ; Biological Specimen Banks ; Cognition/physiology ; Genetic Loci ; Genetic Predisposition to Disease ; Humans ; Memory/physiology ; Middle Aged ; Multifactorial Inheritance ; Polymorphism, Single Nucleotide ; Psychomotor Performance ; Resilience, Psychological ; United Kingdom
Language	English
Publishing date	2022-01-10
Publishing country	Switzerland
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2527218-4
ISSN	2073-4425 ; 2073-4425
ISSN (online)	2073-4425
ISSN	2073-4425
DOI	10.3390/genes13010122
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Article ; Online: Cell-cell interactome of the hematopoietic niche and its changes in acute myeloid leukemia.

Ennis, Sarah / Conforte, Alessandra / O'Reilly, Eimear / Takanlu, Javid Sabour / Cichocka, Tatiana / Dhami, Sukhraj Pal / Nicholson, Pamela / Krebs, Philippe / Ó Broin, Pilib / Szegezdi, Eva

iScience

2023 Volume 26, Issue 6, Page(s) 106943

Abstract: The bone marrow (BM) is a complex microenvironment, coordinating the production of billions of blood cells every day. Despite its essential role and its relevance to hematopoietic diseases, this environment remains poorly characterized. Here we present a ...

Abstract	The bone marrow (BM) is a complex microenvironment, coordinating the production of billions of blood cells every day. Despite its essential role and its relevance to hematopoietic diseases, this environment remains poorly characterized. Here we present a high-resolution characterization of the niche in health and acute myeloid leukemia (AML) by establishing a single-cell gene expression database of 339,381 BM cells. We found significant changes in cell type proportions and gene expression in AML, indicating that the entire niche is disrupted. We then predicted interactions between hematopoietic stem and progenitor cells (HSPCs) and other BM cell types, revealing a remarkable expansion of predicted interactions in AML that promote HSPC-cell adhesion, immunosuppression, and cytokine signaling. In particular, predicted interactions involving transforming growth factor β1 (TGFB1) become widespread, and we show that this can drive AML cell quiescence
Language	English
Publishing date	2023-05-23
Publishing country	United States
Document type	Journal Article
ISSN	2589-0042
ISSN (online)	2589-0042
DOI	10.1016/j.isci.2023.106943
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Article ; Online: Genes influenced by MEF2C contribute to neurodevelopmental disease via gene expression changes that affect multiple types of cortical excitatory neurons.

Cosgrove, Donna / Whitton, Laura / Fahey, Laura / Ó Broin, Pilib / Donohoe, Gary / Morris, Derek W

Human molecular genetics

2020 Volume 30, Issue 11, Page(s) 961–970

Abstract: Myocyte enhancer factor 2 C (MEF2C) is an important transcription factor during neurodevelopment. Mutation or deletion of MEF2C causes intellectual disability (ID), and common variants within MEF2C are associated with cognitive function and schizophrenia ...

Abstract	Myocyte enhancer factor 2 C (MEF2C) is an important transcription factor during neurodevelopment. Mutation or deletion of MEF2C causes intellectual disability (ID), and common variants within MEF2C are associated with cognitive function and schizophrenia risk. We investigated if genes influenced by MEF2C during neurodevelopment are enriched for genes associated with neurodevelopmental phenotypes and if this can be leveraged to identify biological mechanisms and individual brain cell types affected. We used a set of 1055 genes that were differentially expressed in the adult mouse brain following early embryonic deletion of Mef2c in excitatory cortical neurons. Using genome-wide association studies data, we found these differentially expressed genes (DEGs) to be enriched for genes associated with schizophrenia, intelligence and educational attainment but not autism spectrum disorder (ASD). For this gene set, genes that overlap with target genes of the Fragile X mental retardation protein (FMRP) are a major driver of these enrichments. Using trios data, we found these DEGs to be enriched for genes containing de novo mutations reported in ASD and ID, but not schizophrenia. Using single-cell RNA sequencing data, we identified that a number of different excitatory glutamatergic neurons in the cortex were enriched for these DEGs including deep layer pyramidal cells and cells in the retrosplenial cortex, entorhinal cortex and subiculum, and these cell types are also enriched for FMRP target genes. The involvement of MEF2C and FMRP in synapse elimination suggests that disruption of this process in these cell types during neurodevelopment contributes to cognitive function and risk of neurodevelopmental disorders.
MeSH term(s)	Animals ; Autism Spectrum Disorder/genetics ; Autism Spectrum Disorder/pathology ; Brain/metabolism ; Gene Expression Regulation/genetics ; Genome-Wide Association Study ; Humans ; Intellectual Disability/genetics ; Intellectual Disability/physiopathology ; MEF2 Transcription Factors/genetics ; Mice ; Neurodevelopmental Disorders/genetics ; Neurodevelopmental Disorders/pathology ; Neurons/metabolism ; Neurons/pathology ; Schizophrenia/genetics ; Schizophrenia/pathology ; Single-Cell Analysis
Chemical Substances	MEF2 Transcription Factors ; MEF2C protein, human
Language	English
Publishing date	2020-09-25
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	1108742-0
ISSN	1460-2083 ; 0964-6906
ISSN (online)	1460-2083
ISSN	0964-6906
DOI	10.1093/hmg/ddaa213
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Article: Deep Learning of Histopathological Features for the Prediction of Tumour Molecular Genetics.

Murchan, Pierre / Ó'Brien, Cathal / O'Connell, Shane / McNevin, Ciara S / Baird, Anne-Marie / Sheils, Orla / Ó Broin, Pilib / Finn, Stephen P

Diagnostics (Basel, Switzerland)

2021 Volume 11, Issue 8

Abstract: Advanced diagnostics are enabling cancer treatments to become increasingly tailored to the individual through developments in immunotherapies and targeted therapies. However, long turnaround times and high costs of molecular testing hinder the widespread ...

Abstract	Advanced diagnostics are enabling cancer treatments to become increasingly tailored to the individual through developments in immunotherapies and targeted therapies. However, long turnaround times and high costs of molecular testing hinder the widespread implementation of targeted cancer treatments. Meanwhile, gold-standard histopathological assessment carried out by a trained pathologist is widely regarded as routine and mandatory in most cancers. Recently, methods have been developed to mine hidden information from histopathological slides using deep learning applied to scanned and digitized slides; deep learning comprises a collection of computational methods which learn patterns in data in order to make predictions. Such methods have been reported to be successful in a variety of cancers for predicting the presence of biomarkers such as driver mutations, tumour mutational burden, and microsatellite instability. This information could prove valuable to pathologists and oncologists in clinical decision making for cancer treatment and triage for in-depth sequencing. In addition to identifying molecular features, deep learning has been applied to predict prognosis and treatment response in certain cancers. Despite reported successes, many challenges remain before the clinical implementation of such diagnostic strategies in the clinical setting is possible. This review aims to outline recent developments in the field of deep learning for predicting molecular genetics from histopathological slides, as well as to highlight limitations and pitfalls of working with histopathology slides in deep learning.
Language	English
Publishing date	2021-08-03
Publishing country	Switzerland
Document type	Journal Article ; Review
ZDB-ID	2662336-5
ISSN	2075-4418
ISSN	2075-4418
DOI	10.3390/diagnostics11081406
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Article ; Online: Molecular signatures and clinical outcomes of transplant glomerulopathy stratified by microvascular inflammation and donor-specific antibody.

Lubetzky, Michelle / Hayde, Nicole / Ó Broin, Pilib / Ajaimy, Maria / Bao, Yi / Mohammed, Omar / Schwartz, Daniel / Pullman, James / Akalin, Enver

Clinical transplantation

2019 Volume 33, Issue 3, Page(s) e13469

Abstract: Background: We investigated clinical outcomes and molecular signatures of transplant glomerulopathy (TG) stratified by microvascular inflammation (MVI) and donor-specific antibody (DSA) status.: Methods: We performed a retrospective review of 749 ... ...

Abstract	Background: We investigated clinical outcomes and molecular signatures of transplant glomerulopathy (TG) stratified by microvascular inflammation (MVI) and donor-specific antibody (DSA) status. Methods: We performed a retrospective review of 749 kidney transplant patients who received a for-cause kidney biopsy from 2009 to 2014. We classified TG as MVI positive (MVI+) or MVI negative (MVI-), and with or without DSA. We obtained gene expression profiles for 44 biopsies by Affymetrix HuGene 1.0 ST expression arrays. Results: A total of 100 patients had TG; 49 were MVI+, and 51 were MVI-. After a median post-biopsy follow-up of 2.08 years (range 0.43-4.59), Kaplan-Meier survival analysis demonstrated worse allograft survival in MVI+ TG patients compared with MVI- TG patients (P = 0.01), and time to graft failure was significantly shorter in MVI+ patients (1.08 ± 1.01 years vs 2.3 ± 1.8 years; P = 0.002). DSA status did not affect graft survival within MVI+ or MVI- groups. Analysis of pathogenesis-based transcripts (PBT) showed that MVI+ TG biopsies had increased expression of gamma interferon and rejection (GRIT) and DSA-associated transcripts (DSAST), as observed in antibody-mediated rejection. MVI- TG biopsies had increased expression of cytotoxic and regulatory T cell- and B cell-associated transcripts but not GRIT or DSAST. DSA status had no effect on expression of any PBTs studied in MVI- TG biopsies. Conclusions: Graft survival in TG is significantly worse in the presence of MVI. Gene expression profiles of MVI+ TG resemble antibody-mediated rejection while gene expression profiles of MVI- TG resemble cell-mediated rejection regardless of DSA status.
MeSH term(s)	Adult ; Female ; Follow-Up Studies ; Gene Expression Profiling ; Genetic Markers ; Glomerular Filtration Rate ; Glomerulonephritis/etiology ; Glomerulonephritis/genetics ; Glomerulonephritis/pathology ; Graft Rejection/etiology ; Graft Rejection/genetics ; Graft Rejection/pathology ; Graft Survival ; Humans ; Isoantibodies/immunology ; Kidney Function Tests ; Kidney Transplantation/adverse effects ; Male ; Middle Aged ; Postoperative Complications ; Prognosis ; Retrospective Studies ; Risk Factors ; Tissue Donors ; Vasculitis/etiology ; Vasculitis/genetics ; Vasculitis/pathology
Chemical Substances	Genetic Markers ; Isoantibodies
Language	English
Publishing date	2019-01-29
Publishing country	Denmark
Document type	Journal Article
ZDB-ID	639001-8
ISSN	1399-0012 ; 0902-0063
ISSN (online)	1399-0012
ISSN	0902-0063
DOI	10.1111/ctr.13469
Database	MEDical Literature Analysis and Retrieval System OnLINE

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