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Showing papers by "Alistair R. R. Forrest published in 2018"


Journal ArticleDOI
TL;DR: A comprehensive in depth gene expression/regulation profile in Mtb-infected macrophages is provided, an important step forward for a better understanding of host-pathogen interaction dynamics in Mt b infection.
Abstract: Mycobacterium tuberculosis (Mtb) infection reveals complex and dynamic host-pathogen interactions, leading to host protection or pathogenesis. Using a unique transcriptome technology (CAGE), we investigated the promoter-based transcriptional landscape of IFNγ (M1) or IL-4/IL-13 (M2) stimulated macrophages during Mtb infection in a time-kinetic manner. Mtb infection widely and drastically altered macrophage-specific gene expression, which is far larger than that of M1 or M2 activations. Gene Ontology enrichment analysis for Mtb-induced differentially expressed genes revealed various terms, related to host-protection and inflammation, enriched in up-regulated genes. On the other hand, terms related to dis-regulation of cellular functions were enriched in down-regulated genes. Differential expression analysis revealed known as well as novel transcription factor genes in Mtb infection, many of them significantly down-regulated. IFNγ or IL-4/IL-13 pre-stimulation induce additional differentially expressed genes in Mtb-infected macrophages. Cluster analysis uncovered significant numbers, prolonging their expressional changes. Furthermore, Mtb infection augmented cytokine-mediated M1 and M2 pre-activations. In addition, we identified unique transcriptional features of Mtb-mediated differentially expressed lncRNAs. In summary we provide a comprehensive in depth gene expression/regulation profile in Mtb-infected macrophages, an important step forward for a better understanding of host-pathogen interaction dynamics in Mtb infection.

71 citations


Journal ArticleDOI
TL;DR: This work expands a previous method to quantitatively evaluate enrichment of genome-wide association study (GWAS) signals on miRNA–target gene networks (MIGWAS) to further estimate tissue-specific enrichment, and highlighted that miRNA-target gene network contributes to human disease genetics in a cell type-specific manner.
Abstract: MicroRNAs (miRNAs) modulate the post-transcriptional regulation of target genes and are related to biology of complex human traits, but genetic landscape of miRNAs remains largely unknown. Given the strikingly tissue-specific miRNA expression profiles, we here expand a previous method to quantitatively evaluate enrichment of genome-wide association study (GWAS) signals on miRNA-target gene networks (MIGWAS) to further estimate tissue-specific enrichment. Our approach integrates tissue-specific expression profiles of miRNAs (∼1800 miRNAs in 179 cells) with GWAS to test whether polygenic signals enrich in miRNA-target gene networks and whether they fall within specific tissues. We applied MIGWAS to 49 GWASs (nTotal = 3 520 246), and successfully identified biologically relevant tissues. Further, MIGWAS could point miRNAs as candidate biomarkers of the trait. As an illustrative example, we performed differentially expressed miRNA analysis between rheumatoid arthritis (RA) patients and healthy controls (n = 63). We identified novel biomarker miRNAs (e.g. hsa-miR-762) by integrating differentially expressed miRNAs with MIGWAS results for RA, as well as novel associated loci with significant genetic risk (rs56656810 at MIR762 at 16q11; n = 91 482, P = 3.6 × 10-8). Our result highlighted that miRNA-target gene network contributes to human disease genetics in a cell type-specific manner, which could yield an efficient screening of miRNAs as promising biomarkers.

35 citations


Journal ArticleDOI
TL;DR: Exome sequencing on two consanguineous probands diagnosed with a congenital myopathy and muscle biopsy showing selective atrophy/hypotrophy or absence of type II myofibres implicate MyL1 as a crucial protein for adequate skeletal muscle function and that MYL1 deficiency is associated with severe congenitalMyopathy.
Abstract: OBJECTIVE: Congenital myopathies are typically characterised by early onset hypotonia, weakness and hallmark features on biopsy. Despite the rapid pace of gene discovery, approximately 50% of patients with a congenital myopathy remain without a genetic diagnosis following screening of known disease genes. METHODS: We performed exome sequencing on two consanguineous probands diagnosed with a congenital myopathy and muscle biopsy showing selective atrophy/hypotrophy or absence of type II myofibres. RESULTS: We identified variants in the gene (MYL1) encoding the skeletal muscle fast-twitch specific myosin essential light chain in both probands. A homozygous essential splice acceptor variant (c.479-2A>G, predicted to result in skipping of exon 5 was identified in Proband 1, and a homozygous missense substitution (c.488T>G, p.(Met163Arg)) was identified in Proband 2. Protein modeling of the p.(Met163Arg) substitution predicted it might impede intermolecular interactions that facilitate binding to the IQ domain of myosin heavy chain, thus likely impacting on the structure and functioning of the myosin motor. MYL1 was markedly reduced in skeletal muscle from both probands, suggesting that the missense substitution likely results in an unstable protein. Knock down of myl1 in zebrafish resulted in abnormal morphology, disrupted muscle structure and impaired touch-evoked escape responses, thus confirming that skeletal muscle fast-twitch specific myosin essential light chain is critical for myofibre development and function. INTERPRETATION: Our data implicate MYL1 as a crucial protein for adequate skeletal muscle function and that MYL1 deficiency is associated with a severe congenital myopathy.

23 citations


Journal ArticleDOI
TL;DR: In chronic inflammation or autoimmunity, altered Treg/Tconv function may be influenced by changes in enhancer–promoter interactions, which are highly cell type‐specific and may go some way to explaining T‐cell plasticity.
Abstract: Regulatory T cells (Treg) are critical for preventing autoimmunity and curtailing responses of conventional effector T cells (Tconv). The reprogramming of T-cell fate and function to generate Treg requires switching on and off of key gene regulatory networks, which may be initiated by a subtle shift in expression levels of specific genes. This can be achieved by intermediary regulatory processes that include microRNA and long noncoding RNA-based regulation of gene expression. There are well-documented microRNA profiles in Treg and Tconv, and these can operate to either reinforce or reduce expression of a specific set of target genes, including FOXP3 itself. This type of feedforward/feedback regulatory loop is normally stable in the steady state, but can alter in response to local cues or genetic risk. This may go some way to explaining T-cell plasticity. In addition, in chronic inflammation or autoimmunity, altered Treg/Tconv function may be influenced by changes in enhancer-promoter interactions, which are highly cell type-specific. These interactions are impacted by genetic risk based on genome-wide association studies and may cause subtle alterations to the gene regulatory networks controlled by or controlling FOXP3 and its target genes. Recent insights into the 3D organisation of chromatin and the mapping of noncoding regulatory regions to the genes they control are shedding new light on the direct impact of genetic risk on T-cell function and susceptibility to inflammatory and autoimmune conditions.

21 citations


Journal ArticleDOI
TL;DR: The NDA coexpression approach identifies new genetic variants associated with specific traits, including an association between the regulation of the OCT1 cation transporter and genetic variants underlying circulating cholesterol levels, and enables a deeper biological understanding of the causal basis of complex traits.
Abstract: Genetic variants underlying complex traits, including disease susceptibility, are enriched within the transcriptional regulatory elements, promoters and enhancers. There is emerging evidence that regulatory elements associated with particular traits or diseases share similar patterns of transcriptional activity. Accordingly, shared transcriptional activity (coexpression) may help prioritise loci associated with a given trait, and help to identify underlying biological processes. Using cap analysis of gene expression (CAGE) profiles of promoter- and enhancer-derived RNAs across 1824 human samples, we have analysed coexpression of RNAs originating from trait-associated regulatory regions using a novel quantitative method (network density analysis; NDA). For most traits studied, phenotype-associated variants in regulatory regions were linked to tightly-coexpressed networks that are likely to share important functional characteristics. Coexpression provides a new signal, independent of phenotype association, to enable fine mapping of causative variants. The NDA coexpression approach identifies new genetic variants associated with specific traits, including an association between the regulation of the OCT1 cation transporter and genetic variants underlying circulating cholesterol levels. NDA strongly implicates particular cell types and tissues in disease pathogenesis. For example, distinct groupings of disease-associated regulatory regions implicate two distinct biological processes in the pathogenesis of ulcerative colitis; a further two separate processes are implicated in Crohn's disease. Thus, our functional analysis of genetic predisposition to disease defines new distinct disease endotypes. We predict that patients with a preponderance of susceptibility variants in each group are likely to respond differently to pharmacological therapy. Together, these findings enable a deeper biological understanding of the causal basis of complex traits.

19 citations


Journal ArticleDOI
TL;DR: A rigorous meta-analysis of eight genome-wide FANTOM5 CAGE (cap analysis of gene expression) time course datasets reveals successive waves of promoter activation in IEGs, and finds strong conservation of the ordering of activation for these genes, such that 77 pairwise promoter activation orderings are conserved.
Abstract: The promoters of immediate early genes (IEGs) are rapidly activated in response to an external stimulus. These genes, also known as primary response genes, have been identified in a range of cell types, under diverse extracellular signals and using varying experimental protocols. Whereas genomic dissection on a case-by-case basis has not resulted in a comprehensive catalogue of IEGs, a rigorous meta-analysis of eight genome-wide FANTOM5 CAGE (cap analysis of gene expression) time course datasets reveals successive waves of promoter activation in IEGs, recapitulating known relationships between cell types and stimuli: we obtain a set of 57 (42 protein-coding) candidate IEGs possessing promoters that consistently drive a rapid but transient increase in expression over time. These genes show significant enrichment for known IEGs reported previously, pathways associated with the immediate early response, and include a number of non-coding RNAs with roles in proliferation and differentiation. Surprisingly, we also find strong conservation of the ordering of activation for these genes, such that 77 pairwise promoter activation orderings are conserved. Using the leverage of comprehensive CAGE time series data across cell types, we also document the extensive alternative promoter usage by such genes, which is likely to have been a barrier to their discovery until now. The common activation ordering of the core set of early-responding genes we identify may indicate conserved underlying regulatory mechanisms. By contrast, the considerably larger number of transiently activated genes that are specific to each cell type and stimulus illustrates the breadth of the primary response.

9 citations


Journal ArticleDOI
TL;DR: This study provides an initial insight into the TFs of cerebellar granule cells that might be important for development and provide valuable information for further functional studies on these transcriptional regulators.
Abstract: Laser-capture microdissection was used to isolate external germinal layer tissue from three developmental periods of mouse cerebellar development: embryonic days 13, 15, and 18. The cerebellar granule cell-enriched mRNA library was generated with next-generation sequencing using the Helicos technology. Our objective was to discover transcriptional regulators that could be important for the development of cerebellar granule cells-the most numerous neuron in the central nervous system. Through differential expression analysis, we have identified 82 differentially expressed transcription factors (TFs) from a total of 1311 differentially expressed genes. In addition, with TF-binding sequence analysis, we have identified 46 TF candidates that could be key regulators responsible for the variation in the granule cell transcriptome between developmental stages. Altogether, we identified 125 potential TFs (82 from differential expression analysis, 46 from motif analysis with 3 overlaps in the two sets). From this gene set, 37 TFs are considered novel due to the lack of previous knowledge about their roles in cerebellar development. The results from transcriptome-wide analyses were validated with existing online databases, qRT-PCR, and in situ hybridization. This study provides an initial insight into the TFs of cerebellar granule cells that might be important for development and provide valuable information for further functional studies on these transcriptional regulators.

6 citations



Posted ContentDOI
29 Sep 2018-bioRxiv
TL;DR: This manuscript introduces CANCERSIGN as an open access bioinformatics tool that uses raw mutation data (BED files) as input, and generates 3-mer and 5-mer mutational signatures, and enables users to perform clustering on tumor samples based on the raw mutation counts as well as using the proportion ofmutational signatures in each sample.
Abstract: Analyses of large somatic mutation datasets, using advanced computational algorithms, have revealed at least 30 independent mutational signatures in tumor samples. These studies have been instrumental in identification and quantification of responsible endogenous and exogenous molecular processes in cancer. The quantitative approach used to deconvolute mutational signatures is becoming an integral part of cancer research. Therefore, development of a stand-alone tool with a user-friendly graphical interface for analysis of cancer mutational signatures is necessary. In this manuscript, we introduce CANCERSIGN as an open access bioinformatics tool that uses raw mutation data (BED files) as input, and identifies 3-mer and 5-mer mutational signatures. CANCERSIGN enables users to identify signatures within whole genome, whole exome or pooled samples. It can also identify signatures in specific regions of the genome (defined by user). Additionally, this tool enables users to perform clustering on tumor samples based on the raw mutation counts as well as using the proportion of mutational signatures in each sample. Using this tool, we analysed all the whole genome somatic mutation datasets profiled by the International Cancer Genome Consortium (ICGC) and identified a number of novel signatures. By examining signatures found in exonic and non-exonic regions of the genome using WGS and comparing this to signatures found in WES data we observe that WGS can identify additional non-exonic signatures that are enriched in the non-coding regions of the genome while the deeper sequencing of WES may help identify weak signatures that are otherwise missed in shallower WGS data.

1 citations


Journal ArticleDOI
TL;DR: The authors of the original article would like to recognize the critical contribution of core members of the FANTOM5 Consortium, who played the critical role of HeliScopeCAGE sequencing experiments, quality control of tag reads and processing of the raw sequencing data.
Abstract: The authors of the original article [1] would like to recognize the critical contribution of core members of the FANTOM5 Consortium, who played the critical role of HeliScopeCAGE sequencing experiments, quality control of tag reads and processing of the raw sequencing data.