Biology subjects

Breen, J.

Publications and source records attributed to Breen, J..

13 recordsLinked to original sources

bioRxiv2022

Human Liver Organoids as a Patient-derived Model for HBV Infection and Cellular Response

Background & AimsCurrent HBV in vitro model systems suffer from many physiological limitations that restrict understanding of complex viral-host interactions and thus prohibit prediction of disease in vivo. We developed and assessed adult stem cell (AdSC) derived liver organoids as a novel model system for characterisation of the HBV lifecycle, the cellular response to infection and demonstrate their utility in assessing antiviral and immunomodulator response. This model system has the potential to be used in predicting individual HBV responses to antivirals and viral reactivation in the setting of immunosuppressive agents. MethodsDuctal stem cells were isolated from healthy tissue acquired from liver resections or biopsy (n=12). Wnt3a & RSPO-1 containing medium was used to stimulate ductal stem cell expansion into organoids which were subsequently differentiated into hepatocyte-like cells. Mature hepatocyte metabolic markers (albumin, CYP3A4) and HBV entry receptor (Na-taurocholate co-transporting polypeptide, NTCP) expression were evaluated throughout differentiation using qRT-PCR and confocal microscopy. We assessed the organoids culture conditions required for HBV infection and HBV life cycle using HepAD38 (genotype D) and plasma derived HBV (genotype B & C). HBV infection was confirmed using immunofluorescence staining (HBcAg), qRT-PCR (RNA, cccDNA, extracellular DNA) and ELISA (HBsAg and HBeAg). We also assessed drug responsiveness using antivirals and an immunosuppressive agent, and cellular responses (interferon-stimulated genes) using interferon- and viral mimic (PolyI:C). ResultsFollowing differentiation, organoids underwent structural remodelling and changes in cellular polarity, accompanied with an increase in albumin, CYP3A4 and NTCP mRNA expression. Optimal HBV infection was achieved in well-differentiated organoids using spinoculation of at least 200 copies/cell of AD38 derived HBV. Infected organoids demonstrate time and donor dependent increase in HBV RNA, cccDNA, extracellular DNA, HBe and HBsAg consistent with viral replication and antigen secretion. Using these markers we assessed drug-responsiveness to the HBV entry inhibitor, Myrcludex B and the JAK inhibitor, Baricitinib. Despite having a very robust interferon stimulated gene response to interferon- and PolyI:C stimulation, HBV infection in liver organoids did not reveal innate immune activation. ConclusionsAdSC derived liver organoids support the full life cycle of HBV with significant donor dependent variation in viral replication and cellular responses. These features can be utilised for development of personalised drug testing platform for antivirals. Lay SummaryHuman liver organoid culture provides a personalised assessment of HBV infection, replication and responsiveness to antiviral therapy. This model system has a robust innate immune response and could be used to assess novel immune-modulating curative therapy.

microbiology↗

bioRxiv2022

Core and Flanking bHLH-PAS:DNA interactions mediate specificity and drive obesity

The basic-Helix-Loop-Helix Per-Arnt-Sim (PAS) homology domain (bHLH-PAS) transcription factor (TF) family comprises critical biological sensors of physiological (hypoxia, tryptophan metabolites, neuronal activity, and appetite) and environmental (diet derived metabolites and environmental pollutants) stimuli to regulate genes involved in signal adaptation and homeostasis1. bHLH TFs bind DNA as homo or heterodimers via E-box (CANNTG) response elements, however the DNA binding specificity of the PAS domain-containing bHLH subfamily remains unresolved1. We systematically analysed cognate DNA binding hierarchies of prototypical bHLH-PAS family members (ARNT, ARNT2, HIF1, HIF2, AhR, NPAS4, SIM1) and demonstrate distinct core (NNCGTG) specificities for different heterodimer classes. The results also show that bHLH-PAS TFs bind over a large footprint 12-15bp and recognise preferential DNA sequences flanking the core. For example, specificity beyond otherwise identical core binding by SIM1 and the HIFs is mediated through N-terminal HIF-DNA interactions. We also reveal an intimate relationship between DNA shape and both core and flanking TF binding allowing motif sequence flexibility and underpinning TF binding specificity. Furthermore, DNA-shape affinity relationships revealed that novel downstream PAS-A-loop DNA interactions are associated with AT-rich sequences that lead to high-affinity binding, and that loss of this function underpins a monogenic cause of human hyperphagic obesity in a recapitulated SIM1.R171H knock-in mouse model. Importantly, models of protein-DNA binding accurately predict in vivo occupancy, while response element methylation blocks DNA binding and predicts cell type specific chromatin occupancy. These data provide a definitive and accurate map of bHLH-PAS TF specificity and target selectivity through novel flanking protein-DNA interactions that are crucial for in vivo biological function.

molecular biology↗

bioRxiv2021

Somatic point mutations are enriched in long non-coding RNAs with possible regulatory function in breast cancer

De novo somatic point mutations identified in breast cancer are predominantly non-coding and typically attributed to altered regulatory elements such as enhancers and promoters. However, while the non-coding RNAs (ncRNAs) form a large portion of the mammalian genome, their biological functions are mostly poorly characterized in cancers. In this study, using a newly developed tool, SomaGene, we reanalyze de novo somatic point mutations from the International Cancer Genome Consortium (ICGC) whole-genome sequencing data of 1,855 breast cancers. We identify 929 candidates of ncRNAs that are significantly and explicitly mutated in breast cancer samples. By integrating data from the ENCODE regulatory features and FANTOM5 expression atlas, we show that the candidate ncRNAs in breast cancer samples significantly enrich for active chromatin histone marks (1.9 times), CTCF binding sites (2.45 times), DNase accessibility (1.76 times), HMM predicted enhancers (2.26 times) and eQTL polymorphisms (1.77 times). Importantly, we show that the 929 ncRNAs contain a much higher level (3.64 times) of breast cancer-associated genome-wide association (GWAS) single nucleotide polymorphisms (SNPs) than genome-wide expectation. Such enrichment has not been seen with GWAS SNPs from other diseases. Using breast tissue related Hi-C data we then show that 82% of our candidate ncRNAs (1.9 times) significantly interact with the promoter of protein-coding genes, including previously known cancer-associated genes, suggesting the critical role for candidate ncRNA genes in activation of essential regulators of development and differentiation in breast cancer. We provide an extensive web-based resource (http://ncrna.ictic.sharif.edu), to communicate our results with the research community. Our list of breast cancer-specific ncRNA genes has the potential to provide a better understanding of the underlying genetic causes of breast cancer. Lastly, the tool developed in this study can be used in the analysis of somatic mutations in all cancers.

cancer biology↗

bioRxiv2021

Progesterone receptor-A isoform interaction with RUNX transcription factors controls chromatin remodelling at promoters during ovulation

Progesterone receptor (PGR) plays diverse roles in reproductive tissues and thus coordinates mammalian fertility. In the ovary, acutely induced PGR is the key determinant of ovulation through transcriptional control of a unique set of genes that culminates in follicle rupture. However, the molecular mechanisms for PGRs specialised function in ovulation is poorly understood. To address this, we assembled a detailed genomic profile of PGR action through combined ATAC-seq, RNA-seq and ChIP-seq analysis in wildtype and isoform-specific PGR null mice. We demonstrated the unique action of PGR-A isoform in the ovary through a transcriptional complex involving physical interaction with RUNX and JUN/FOS transcription factors. The assembly of this unique complex directs targeting of PGR binding to proximal promoter regions and enables chromatin accessibility, leading to ovulatory gene induction. This PGR signalling mechanism is specific to ovulation and provides potential targets for infertility treatments as well as new contraceptives that block ovulation.

molecular biology↗

bioRxiv2020

Seeing the forest through the trees: Identifying functional interactions from Hi-C

Eukaryotic genomes are highly organised within the nucleus of a cell, allowing widely dispersed regulatory elements such as enhancers to interact with gene promoters through physical contacts in three-dimensional space. Recent chromosome conformation capture methodologies such as Hi-C have enabled the analysis of interacting regions of the genome providing a valuable insight into the three-dimensional organisation of the chromatin in the nucleus, including chromosome compartmentalisation and gene expression. Complicating the analysis of Hi-C data however is the massive amount of identified interactions, many of which do not directly drive gene function, thus hindering the identification of potentially biologically functional 3D interactions. In this review, we collate and examine the downstream analysis of Hi-C data with particular focus on methods that identify significant functional interactions. We classify three groups of approaches; structurally-associated domain discovery methods e.g. topologically-associated domains and compartments, detection of statistically significant interactions via background models, and the use of epigenomic data integration to identify functional interactions. Careful use of these three approaches is crucial to successfully identifying functional interactions within the genome.

bioinformatics↗

bioRxiv2020

3DFAACTS-SNP: Using regulatory T cell-specific epigenomics data to uncover candidate mechanisms of Type-1 Diabetes (T1D) risk

BackgroundGenome-wide association and fine-mapping studies have enabled the discovery of single nucleotide polymorphisms (SNPs) and other variants that are significantly associated with many autoimmune diseases including type 1 diabetes (T1D). However, many of the SNPs lie in non-coding regions, limiting the identification of mechanisms that contribute to autoimmune disease progression. MethodsAutoimmunity results from a failure of immune tolerance, suggesting that regulatory T cells (Treg) are likely a significant point of impact for this genetic risk, as Treg are critical for immune tolerance. Focusing on T1D as a model of defective function of Treg in autoimmunity, we designed a SNPs filtering workflow called 3 Dimensional Functional Annotation of Accessible Cell Type Specific SNPs (3DFAACTS-SNP) that utilises overlapping profiles of Treg-specific epigenomic data (ATAC-seq, Hi-C and FOXP3-ChIP) to identify regulatory elements potentially driving the effect of variants associated with T1D, and the gene(s) that they control. ResultsUsing 3DFAACTS-SNP we identified 36 SNPs with plausible Treg-specific mechanisms of action contributing to T1D from 1,228 T1D fine-mapped variants, identifying 119 novel interacting regions resulting in the identification of 51 candidate target genes. We further demonstrated the utility of the workflow by applying it to three other fine-mapped/meta-analysed SNP autoimmune datasets, identifying 17 Treg-centric candidate variants and 35 interacting genes. Finally, we demonstrate the broad utility of 3DFAACTS-SNP for functional annotation of any genetic variation using all common (>10% allele frequency) variants from the Genome Aggregation Database (gnomAD). We identified 7,900 candidate variants and 3,245 candidate target genes, generating a list of potential sites for future T1D or autoimmune research. ConclusionsWe demonstrate that it is possible to further prioritise variants that contribute to T1D based on regulatory function and illustrate the power of using cell type specific multi-omics datasets to determine disease mechanisms. The 3DFAACTS-SNP workflow can be customised to any cell type for which the individual datasets for functional annotation have been generated, giving broad applicability and utility.

bioinformatics↗

bioRxiv2020

Wine terroir and the soil microbiome: an amplicon sequencing-based assessment of the Barossa Valley and its sub-regions

Soil is an important factor that contributes to the uniqueness of a wine produced by vines grown in specific conditions. Recent data shows that the composition, diversity and function of soil microbial communities may play important roles in determining wine quality and indirectly affect its economic value. Here, we evaluated the impact of environmental variables on the soil microbiomes of 22 Barossa Valley vineyard sites based on the 16S rRNA gene hypervariable region 4. In this study, we report that environmental heterogeneity (soil plant-available P content, elevation, rainfall, temperature, spacing between row and spacing between vine) caused more microbial dissimilarity than geographic distance. Vineyards located in cooler and wetter regions showed lower beta diversity and a higher ratio of dominant taxa. Differences in microbial community composition were significantly associated with differences in fruit traits and in wine chemical and metabolomic profiles, highlighting the potential influence of microbial communities on the phenotype of grapevines. Our results suggest that environmental factors affect wine terroir, and this may be mediated by changes in microbial structure, thus providing a basic understanding of how growing conditions affect interactions between plants and their soil microbiomes.

microbiology↗

bioRxiv2020

Genomic evolutionary analysis in R with geaR.

The analysis and interpretation of datasets generated through sequencing large numbers of individual genomes is becoming commonplace in population and evolutionary genetic studies. Here we introduce geaR, a modular R package for evolutionary analysis of genome-wide genotype data. The package leverages the Genomic Data Structure (GDS) format, which enables memory and time efficient querying of genotype datasets compared to standard VCF genotype files. geaR utilizes GRange object classes to partition an analysis based on features from GFF annotation files, select codons based on position or degeneracy, and construct both positional and coordinate genomic windows. Tests of genetic diversity (eg. dXY,{pi} , FST) and admixture [Formula] along with tree building and sequence output, can be carried out on partitions using a single function regardless of sample ploidy or number of observed alleles. The package and associated documentation are available on GitHub at https://github.com/CMWbio/geaR.

genomics↗

bioRxiv2020

Integrative analysis of mutated genes and mutational processes reveals seven colorectal cancer subtypes

Colorectal cancer (CRC) is one of the leading causes of cancer-related deaths in the world. It has been reported that [~]10%-15% of individuals with colorectal cancer experience a causative mutation in the known susceptibility genes, highlighting the importance of identifying mutations for early detection in high risk individuals. Through extensive sequencing projects such as the International Cancer Genome Consortium (ICGC), a large number of somatic point mutations have been identified that can be used to identify cancer-associated genes, as well as the signature of mutational processes defined by the tri-nucleotide sequence context (motif) of mutated sites. Mutation is the hallmark of cancer genome, and many studies have reported cancer subtyping based on the type of frequently mutated genes, or the proportion of mutational processes, however, none of these cancer subtyping methods consider these features simultaneously. This highlights the need for a better and more inclusive subtype classification approach to enable biomarker discovery and thus inform drug development for CRC. In this study, we developed a statistical pipeline based on a novel concept gene-motif, which merges mutated gene information with tri-nucleotide motif of mutated sites, to identify cancer subtypes, in this case CRCs. Our analysis identified for the first time, 3,131 gene-motif combinations that were significantly mutated in 536 ICGC colorectal cancer samples compared to other cancer types, identifying seven CRC subtypes with distinguishable phenotypes and biomarkers. Interestingly, we identified several genes that were mutated in multiple subtypes but with unique sequence contexts. Taken together, our results highlight the importance of considering both the mutation type and mutated genes in identification of cancer subtypes and cancer biomarkers.

cancer biology↗

bioRxiv2020

Dicistronic tRNA-mRNA transcripts in grapevine (Vitis vinifera) display distinct, regional expression patterns that correlate with tRNA expression

Transfer RNAs (tRNA) are crucial adaptor molecules between messenger RNA (mRNA) and amino acids. Recent evidence in plants suggests that dicistronic tRNA-like structures also act as mobile signals for mRNA transcripts to move between distant tissues. Co-transcription is not a common feature in the plant nuclear genome and, in the few cases where polycistronic transcripts have been found, they include non-coding RNA species such as small nucleolar RNAs and microRNAs. It is not known, however, the extent to which dicistronic transcripts of tRNA and mRNAs are expressed in field-grown plants, or the factors contributing to their expression. We analysed tRNA-mRNA dicistronic transcripts in the major horticultural crop grapevine (Vitis vinifera) using a novel pipeline developed to identify dicistronic transcripts from high-throughput RNA sequencing data. We identified dicistronic tRNA-mRNA in leaf and berry samples from 22 commercial vineyards. Of the 124 tRNA genes that were expressed in both tissues, 18 tRNA were expressed forming part of 19 dicistronic tRNA-mRNAs. The presence and abundance of dicistronic molecules was tissue and geographic sub-region specific. In leaves, the expression patterns of dicistronic tRNA-mRNAs significantly correlated with tRNA expression, suggesting that their transcriptional regulation might be linked. We also found evidence of syntenic genomic arrangements of tRNAs and protein coding genes between grapevine and Arabidopsis thaliana, and widespread prevalence of dicistronic tRNA-mRNA transcripts among vascular land plants but no evidence of these transcripts in nonvascular lineages. This suggests that the appearance of plant vasculature and tRNA-mRNA occurred concurrently during the evolution of land plants.

plant biology↗

bioRxiv2018

Extensive field-sampling reveals the uniqueness of a trophy mountain goat population

Collaborations between academic researchers and agencies is crucial for genetic data to have a tangible impact on conservation and wildlife management. Such partnerships are particularly important elusive species where the difficult terrain requires that a significant amount of resources and a combination of methods be used to estimate population parameters needed for conservation. We report and multi-year academic-agency collaboration on the North American mountain goat that used an extensive field sampling of genetic and phenotypic data to determine whether, and to what degree, genetic and phenotypic differences separate an isolated population of mountain goats on the Cleveland Peninsula form those in southeast Alaska. We observed significantly larger horns on the peninsula and the population appears demographically isolated. Isolation-by-distance accompanied by limited migration and low effective population size on the Cleveland Peninsula suggest this population will continue to lose genetic diversity. While the large horns of mountain goats have generated interest in re-opening mountain goat harvest on Cleveland Peninsula, our genetic data suggest this population is vulnerable to demographic and environmental perturbations and is unlikely to support a sustained harvest.

genetics↗

bioRxiv2018

Laboratory contamination over time during low-biomass sample analysis

Bacteria are not only ubiquitous on earth but can also be incredibly diverse within clean laboratories and reagents. The presence of both living and dead bacteria in laboratory environments and reagents is especially problematic when examining samples with low endogenous content (e.g. skin swabs, tissue biopsies, ice, water, degraded forensic samples, or ancient material), where contaminants can outnumber endogenous microorganisms within samples. The contribution of contaminants within high-throughput studies remains poorly understood because of the relatively low number of contaminant surveys. Here, we examined 144 negative control samples (extraction blank and no-template amplification controls) collected in both typical molecular laboratories and an ultraclean ancient DNA laboratory over five years to characterize long-term contaminant diversity. We additionally compared the contaminant content within a homemade silica-based extraction method, commonly used to analyse low-endogenous samples, with a widely used commercial DNA extraction kit. The contaminant taxonomic profile of the ultraclean ancient DNA laboratory was unique compared to the modern molecular biology laboratories, and changed over time according to researchers, month, and season. The commercial kit contained higher microbial diversity and several human-associated taxa in comparison to the homemade silica extraction protocol. We recommend a minimum of two strategies to reduce the impacts of laboratory contaminants within low-biomass metagenomic studies: 1) extraction blank controls should be included and sequenced with every batch of extractions and 2) the contributions of laboratory contamination should be assessed and reported in each high-throughput metagenomic study.

microbiology↗

bioRxiv2017

Environmental Conditions And Agronomic Practices Induce Consistent Global Changes In DNA Methylation Patterns In Grapevine (Vitis vinifera cv Shiraz)

Fruit attributes that affect wine quality are thought to be largely driven by the interaction of grapevines genetic characteristics with environmental factors (i.e. climate, soil and topography) and vineyard management. All these variables, in conjunction with the wine making process, give a wine its distinctive character. Understanding how grapevines perceive and adapt to a changing environment will provide us with an insight into how to better manage crop quality. Mounting evidence suggests that epigenetic mechanisms are a key interface between the environment and the genotype that ultimately affect the plants phenotype. Moreover, it is now widely accepted that epigenetic mechanisms are a source of useful variability during crop varietal selection that could affect crop performance. While the contribution of DNA methylation to plant performance has been extensively studied in other major crops, very little work has been done in grapevine. Here we used Methylation Sensitive Amplified Polymorphisms to obtain global patterns of DNA methylation, and to identify the main drivers of epigenetic diversity across 22 vineyards planted with the cultivar Shiraz in six distinctive wine areas of a major wine zone, The Barossa, South Australia. The observed epigenetic profiles showed a high level of differentiation that grouped vineyards by their area of provenance despite the low genetic differentiation between vineyards and sub-regions. Furthermore, pairwise epigenetic distances between vineyards with similar management systems showed a significant correlation with geographic distance. Finally, methylation sensitive Genotyping By Sequencing identified 3,598 differentially methylated genes that were assigned to 1,144 unique GO terms of which 8.6% were associated with response to environmental stimulus. Taken together, our results indicate that the intensity and directionality of DNA methylation differentiation between vineyards and wine sub-regions within The Barossa are driven by management and local growing conditions. Finally, we discuss how epigenetic variability can be used as a tool to understand and potentially modulate terroir in grapevine.

plant biology↗