Biology subjects

Paterson, A.

Publications and source records attributed to Paterson, A..

6 recordsLinked to original sources

bioRxiv2025

Confidence: A Web App for Cross-Platform Differential Gene Expression Analysis, Gene Scoring, and Enrichment Analysis

RNA sequencing (RNA-seq) is used to quantify transcript levels through measurement of nucleotide sequences. To evaluate statistically significant changes in gene expression, transcript counts between samples are compared using differential expression analysis methods. However, three of the most pressing challenges in transcriptomics analyses are: 1) analytical packages produce a distinct number of differentially expressed genes with varied P-value and fold-change values; 2) the effective use of these analytical packages requires substantial knowledge of programming and bioinformatics; and 3) there are a lack of intuitive methods to select target genes for further investigation in an unbiased manner. To address these challenges, we developed Confidence, a web-based application to perform simultaneous statistical analysis of RNA-seq count data. Confidence incorporates the Confidence Score (CS), ranging from 1 to 4 to aid in gene prioritization, where 1 represents low confidence and 4 represents high confidence. The Confidence web-based application was designed for rapid and intuitive analysis of standard experimental metadata and gene count inputs. Confidence provided a web-based, wide-net approach to differential gene expression analysis. Gene scoring allows for unbiased gene selection and identification of novel genes strongly associated with disease and treatment models across multiple species. Additionally, pathway analysis tools have been integrated so that highly confident genes can be placed into biological context in terms of functions and pathways. Confidence provides a new strategy for target prioritization in RNA-seq analysis and the generation of publication-quality figures.

bioinformatics↗

bioRxiv2025

The impact of testosterone on paraventricular nucleus gene expression in male and female spontaneously hypertensive rats

BackgroundHypertension is a polygenic, complex disease that impacts men and women differently; whilst the incidence of high blood pressure (BP) is roughly equal over a lifetime, men typically are at higher risk of developing the disease earlier in life, before 50 years of age. There is adequate evidence that the brain is critical for the BP setpoint. The paraventricular nucleus (PVN) of the hypothalamus is an integrative structure that can influence not only neurohumoral responses to blood pressure changes, but also sympathetic drive. Here we manipulate the androgenic status of both male and female spontaneously hypertensive rats (SHRs) to determine how this changes gene expression within the PVN of these animals. MethodsSHR (8-weeks old) were either sham-operated or orchiectomized, whereas all females were oophorectomized, half of which received 10mg testosterone propionate subcutaneously. Mean arterial pressure (MAP) and testosterone (T) were measured by carotid cannulation and ELISA respectively. Sequencing was performed on hand-punched PVN sections and subjected to robust bioinformatic analysis. ResultsIn total, 6,571 differentially regulated genes (DRGs) are regulated in the PVN of male and female rats. High T (endogenous or replaced) correlates with higher MAP in both sexes. Orchidectomy-induced T depletion resulted in the significant regulation of 5,104 genes, involved in thousands of biological roles, including ones related to hormone and sex-hormone signalling. In the female SHR, testosterone replacement in oophorectomized animals induced the regulation of 1,727 genes, sharing many biological functions with those in the high T males. We validated key genes by qPCR to determine false discovery rate. ConclusionsT status in hypertensive rats correlates with MAP, and consistent changes in PVN transcriptome

neuroscience↗

bioRxiv2024

Mining the CRBN Target Space Redefines Rules for Molecular Glue-induced Neosubstrate Recognition

The CRL4CRBN ubiquitin ligase is leveraged by molecular glue degraders, small molecules that reprogram ligase specificity to induce degradation of clinically relevant neosubstrate proteins. Known CRBN neosubstrates share a generalizable {beta}-hairpin G-loop recognition motif, yet systematic exploration of the CRBN target landscape is still pending. Through computational mining of the human proteome using structure-based approaches, we predict over 1,400 CRBN-compatible {beta}-hairpin G-loop proteins across diverse target classes, identify novel mechanisms of neosubstrate recognition through structurally differentiated helical motifs and molecular surface mimicry, and validate 22 representative neosubstrates with clinical implications. This work broadens the CRBN target space, redefines rules for neosubstrate recognition and establishes a platform for the elimination of challenging drug targets by repurposing CRL4CRBN through next-generation molecular glue degraders.

biochemistry↗

bioRxiv2024

PRMT5 inhibition preferentially targets MYCN-amplified neuroblastoma via altered transcriptional and splicing programmes regulating key cancer cell fitness pathways.

About 50% of poor prognosis neuroblastoma arises due to MYCN over-expression. We previously demonstrated that MYCN and PRMT5 proteins interact and PRMT5 knockdown led to apoptosis of MYCN amplified (MNA) neuroblastoma. Here we evaluate PRMT5 inhibitors GSK3203591/GSK3326593 as targeted therapeutics for MNA neuroblastoma and show MYCN-dependent growth inhibition and apoptosis. RNAseq revealed dysregulated MYCN transcriptional programmes and altered mRNA splicing, converging on key regulatory pathways such as DNA damage response, epitranscriptomics and cellular metabolism. Metabolic tracing showed glutamine metabolism was impeded following GSK3203591 treatment, which disrupted the MLX/Mondo nutrient sensors via intron retention of MLX mRNA. Glutaminase (GLS) protein was decreased by GSK3203591 despite unchanged transcript levels, suggesting post-transcriptional regulation. We demonstrate the RNA methyltransferase METTL3 and cognate reader YTHDF3 proteins are lowered following splicing alterations; accordingly, we observed hypomethylation of GLS mRNA and decreased GLS following YTHDF3 knockdown. In vivo efficacy of GSK3326593 was confirmed by increased survival of Th-MYCN mice together with splicing events and protein decreases consistent with in vitro data. Our study supports the spliceosome as a key vulnerability of MNA neuroblastoma and rationalises PRMT5 inhibition as a targeted therapy. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=133 SRC="FIGDIR/small/582087v2_ufig1.gif" ALT="Figure 1"> View larger version (54K): org.highwire.dtl.DTLVardef@1ac6b5org.highwire.dtl.DTLVardef@1eb9520org.highwire.dtl.DTLVardef@18b980corg.highwire.dtl.DTLVardef@1ab46e0_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2022

Deciphering TP53 mutant Cancer Evolution with Single-Cell Multi-Omics

TP53 is the most commonly mutated gene in human cancer, typically occurring in association with complex cytogenetics and dismal outcomes. Understanding the genetic and non-genetic determinants of TP53-mutation driven clonal evolution and subsequent transformation is a crucial step towards the design of rational therapeutic strategies. Here, we carry out allelic resolution single-cell multi-omic analysis of haematopoietic stem/progenitor cells (HSPC) from patients with a myeloproliferative neoplasm who transform to TP53-mutant secondary acute myeloid leukaemia (AML), a tractable model of TP53-mutant cancer evolution. All patients showed dominant TP53 multi-hit HSPC clones at transformation, with a leukaemia stem cell transcriptional signature strongly predictive of adverse outcome in independent cohorts, across both TP53-mutant and wild-type AML. Through analysis of serial samples and antecedent TP53-heterozygous clones, we demonstrate a hitherto unrecognised effect of chronic inflammation, which supressed TP53 wild-type HSPC whilst enhancing the fitness advantage of TP53 mutant cells. Our findings will facilitate the development of risk-stratification, early detection and treatment strategies for TP53-mutant leukaemia, and are of broader relevance to other cancer types.

cancer biology↗

bioRxiv2018

Fast and accurate shared segment detection and relatedness estimation in un-phased genetic data using TRUFFLE

Relationship estimation and segment detection between individuals is an important aspect of disease gene mapping. Existing methods are either tailored for computational efficiency, or require phasing to improve accuracy. We developed TRUFFLE, a method that integrates computational techniques and statistical principles for the identification and visualization of identity-by-descent (IBD) segments using un-phased data. By skipping the haplotype phasing step and, instead, relying on a simpler region-based approach, our method is computationally efficient while maintaining inferential accuracy. In addition, an error model corrects for segment break-ups that occur as a consequence of genotyping errors. TRUFFLE can estimate relatedness for 3.1 million pairs from the 1000 Genomes Project data in a few minutes on a typical laptop computer. Consistent with expectation, we identified only three second cousin or closer pairs across different populations, while commonly used methods identified a large number of such pairs. Similarly, within populations, we identified much fewer related pairs. Compared to methods relying on phased data, TRUFFLE has comparable accuracy but is drastically faster and has fewer broken segments. We also identified specific local genomic regions that are commonly shared within populations, suggesting selection. When applied to pedigree data, we observed 99.6% accuracy in detecting 1st to 5th degree relationships. As genomic datasets become much larger, TRUFFLE can enable disease gene mapping through implicit shared haplotypes by accurate IBD segment detection.

genomics↗