School of Mathematics and Statistics - Research Publications
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ItemNo Preview AvailableToblerone: detecting exon deletion events in cancer using RNA-seq.(F1000 Research Ltd, 2023)Cancer is driven by mutations of the genome that can result in the activation of oncogenes or repression of tumour suppressor genes. In acute lymphoblastic leukemia (ALL) focal deletions in IKAROS family zinc finger 1 (IKZF1) result in the loss of zinc-finger DNA-binding domains and a dominant negative isoform that is associated with higher rates of relapse and poorer patient outcomes. Clinically, the presence of IKZF1 deletions informs prognosis and treatment options. In this work we developed a method for detecting exon deletions in genes using RNA-seq with application to IKZF1. We developed a pipeline that first uses a custom transcriptome reference consisting of transcripts with exon deletions. Next, RNA-seq reads are mapped using a pseudoalignment algorithm to identify reads that uniquely support deletions. These are then evaluated for evidence of the deletion with respect to gene expression and other samples. We applied the algorithm, named Toblerone, to a cohort of 99 B-ALL paediatric samples including validated IKZF1 deletions. Furthermore, we developed a graphical desktop app for non-bioinformatics users that can quickly and easily identify and report deletions in IKZF1 from RNA-seq data with informative graphical outputs.
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ItemNo Preview AvailableBenchmarking single-cell hashtag oligo demultiplexing methods(OXFORD UNIV PRESS, 2023-10-11)Sample multiplexing is often used to reduce cost and limit batch effects in single-cell RNA sequencing (scRNA-seq) experiments. A commonly used multiplexing technique involves tagging cells prior to pooling with a hashtag oligo (HTO) that can be sequenced along with the cells' RNA to determine their sample of origin. Several tools have been developed to demultiplex HTO sequencing data and assign cells to samples. In this study, we critically assess the performance of seven HTO demultiplexing tools: hashedDrops, HTODemux, GMM-Demux, demuxmix, deMULTIplex, BFF (bimodal flexible fitting) and HashSolo. The comparison uses data sets where each sample has also been demultiplexed using genetic variants from the RNA, enabling comparison of HTO demultiplexing techniques against complementary data from the genetic 'ground truth'. We find that all methods perform similarly where HTO labelling is of high quality, but methods that assume a bimodal count distribution perform poorly on lower quality data. We also suggest heuristic approaches for assessing the quality of HTO counts in an scRNA-seq experiment.
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ItemNo Preview AvailableEnhancer retargeting of CDX2 and UBTF::ATXN7L3 define a subtype of high-risk B-progenitor acute lymphoblastic leukemia(AMER SOC HEMATOLOGY, 2022-06-16)Transcriptome sequencing has identified multiple subtypes of B-progenitor acute lymphoblastic leukemia (B-ALL) of prognostic significance, but a minority of cases lack a known genetic driver. Here, we used integrated whole-genome (WGS) and -transcriptome sequencing (RNA-seq), enhancer mapping, and chromatin topology analysis to identify previously unrecognized genomic drivers in B-ALL. Newly diagnosed (n = 3221) and relapsed (n = 177) B-ALL cases with tumor RNA-seq were studied. WGS was performed to detect mutations, structural variants, and copy number alterations. Integrated analysis of histone 3 lysine 27 acetylation and chromatin looping was performed using HiChIP. We identified a subset of 17 newly diagnosed and 5 relapsed B-ALL cases with a distinct gene expression profile and 2 universal and unique genomic alterations resulting from aberrant recombination-activating gene activation: a focal deletion downstream of PAN3 at 13q12.2 resulting in CDX2 deregulation by the PAN3 enhancer and a focal deletion of exons 18-21 of UBTF at 17q21.31 resulting in a chimeric fusion, UBTF::ATXN7L3. A subset of cases also had rearrangement and increased expression of the PAX5 gene, which is otherwise uncommon in B-ALL. Patients were more commonly female and young adult with median age 35 (range,12-70 years). The immunophenotype was characterized by CD10 negativity and immunoglobulin M positivity. Among 16 patients with known clinical response, 9 (56.3%) had high-risk features including relapse (n = 4) or minimal residual disease >1% at the end of remission induction (n = 5). CDX2-deregulated, UBTF::ATXN7L3 rearranged (CDX2/UBTF) B-ALL is a high-risk subtype of leukemia in young adults for which novel therapeutic approaches are required.
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ItemNo Preview AvailableRNA-Seq of amniotic fluid cell-free RNA: a discovery phase study of the pathophysiology of congenital cytomegalovirus infection(MOSBY-ELSEVIER, 2022-10)BACKGROUND: Congenital cytomegalovirus infection is the most common perinatal infection and a significant cause of sensorineural hearing loss, cerebral palsy, and neurodevelopmental disability. There is a paucity of human gene expression studies examining the pathophysiology of cytomegalovirus infection. OBJECTIVE: This study aimed to perform a whole transcriptomic assessment of amniotic fluid from pregnancies with live fetuses to identify differentially expressed genes and enriched Gene Ontology categories associated with congenital cytomegalovirus infection. STUDY DESIGN: Amniotic fluid supernatant was prospectively collected from pregnant women undergoing amniocentesis for suspected congenital cytomegalovirus infection because of first-trimester maternal primary infection or ultrasound features suggestive of fetal infection. Women who had received therapy to prevent fetal infection were excluded. Congenital cytomegalovirus infection was diagnosed via viral polymerase chain reaction of amniotic fluid; cytomegalovirus-infected fetuses were paired with noninfected controls, matched for gestational age and fetal sex. Paired-end RNA sequencing was performed on amniotic fluid cell-free RNA with the Novaseq 6000 at a depth of 30 million reads per sample. Following quality control and filtering, reads were mapped to the human genome and counts summarized across genes. Differentially expressed genes were identified using 2 approaches: voomWithQualityWeights in conjunction with limma and RUVSeq with edgeR. Genes with a false discovery rate <0.05 were considered statistically significant. Differential exon use was analyzed using DEXSeq. Functional analysis was performed using gene set enrichment analysis and Ingenuity Pathway Analysis. Manual curation of differentially regulated genes was also performed. RESULTS: Amniotic fluid samples were collected from 50 women; 16 (32%) had congenital cytomegalovirus infection confirmed by polymerase chain reaction. After excluding 3 samples without matched controls, 13 cytomegalovirus-infected samples collected at 18 to 23 weeks and 13 cytomegalovirus-negative gestation-matched controls were submitted for RNA sequencing and analysis (N=26). Ten of the 13 pregnancies with cytomegalovirus-infected fetuses had amniocentesis because of serologic evidence of maternal primary infection with normal fetal ultrasound, and 3 had amniocentesis because of ultrasound abnormality suggestive of cytomegalovirus infection. Four cytomegalovirus-infected pregnancies ended in termination (n=3) or fetal death (n=1), and 9 resulted in live births. Pregnancy outcomes were available for 11 of the 13 cytomegalovirus-negative controls; all resulted in live births of clinically-well infants. Differential gene expression analysis revealed 309 up-regulated and 32 down-regulated genes in the cytomegalovirus-infected group compared with the cytomegalovirus-negative group. Gene set enrichment analysis showed significant enrichment of multiple Gene Ontology categories involving the innate immune response to viral infection and interferon signaling. Of the 32 significantly down-regulated genes, 8 were known to be involved in neurodevelopment and preferentially expressed by the brain. Six specific cellular restriction factors involved in host defense to cytomegalovirus infection were up-regulated in the cytomegalovirus-infected group. Ingenuity Pathway Analysis predicted the activation of pathways involved in progressive neurologic disease and inflammatory neurologic disease. CONCLUSION: In this next-generation sequencing study, we revealed new insights into the pathophysiology of congenital cytomegalovirus infection. These data on the up-regulation of the intraamniotic innate immune response to cytomegalovirus infection and the dysregulation of neurodevelopmental genes may inform future approaches to developing prognostic markers and assessing fetal responses to in utero therapy.
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ItemNo Preview AvailableUnusual PDGFRB fusion reveals novel mechanism of kinase activation in Ph-like B-ALL(SPRINGERNATURE, 2023-04)
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Itempropeller: testing for differences in cell type proportions in single cell data(OXFORD UNIV PRESS, 2022-10-15)Single cell RNA-Sequencing (scRNA-seq) has rapidly gained popularity over the last few years for profiling the transcriptomes of thousands to millions of single cells. This technology is now being used to analyse experiments with complex designs including biological replication. One question that can be asked from single cell experiments, which has been difficult to directly address with bulk RNA-seq data, is whether the cell type proportions are different between two or more experimental conditions. As well as gene expression changes, the relative depletion or enrichment of a particular cell type can be the functional consequence of disease or treatment. However, cell type proportion estimates from scRNA-seq data are variable and statistical methods that can correctly account for different sources of variability are needed to confidently identify statistically significant shifts in cell type composition between experimental conditions.
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ItemDefining the Fetal Gene Program at Single-Cell Resolution in Pediatric Dilated Cardiomyopathy(LIPPINCOTT WILLIAMS & WILKINS, 2022-10-04)
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ItemLarge-scale manipulation of promoter DNA methylation reveals context-specific transcriptional responses and stability(BMC, 2022-07-26)BACKGROUND: Cytosine DNA methylation is widely described as a transcriptional repressive mark with the capacity to silence promoters. Epigenome engineering techniques enable direct testing of the effect of induced DNA methylation on endogenous promoters; however, the downstream effects have not yet been comprehensively assessed. RESULTS: Here, we simultaneously induce methylation at thousands of promoters in human cells using an engineered zinc finger-DNMT3A fusion protein, enabling us to test the effect of forced DNA methylation upon transcription, chromatin accessibility, histone modifications, and DNA methylation persistence after the removal of the fusion protein. We find that transcriptional responses to DNA methylation are highly context-specific, including lack of repression, as well as cases of increased gene expression, which appears to be driven by the eviction of methyl-sensitive transcriptional repressors. Furthermore, we find that some regulatory networks can override DNA methylation and that promoter methylation can cause alternative promoter usage. DNA methylation deposited at promoter and distal regulatory regions is rapidly erased after removal of the zinc finger-DNMT3A fusion protein, in a process combining passive and TET-mediated demethylation. Finally, we demonstrate that induced DNA methylation can exist simultaneously on promoter nucleosomes that possess the active histone modification H3K4me3, or DNA bound by the initiated form of RNA polymerase II. CONCLUSIONS: These findings have important implications for epigenome engineering and demonstrate that the response of promoters to DNA methylation is more complex than previously appreciated.
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ItemsplatPop: simulating population scale single-cell RNA sequencing data(BMC, 2021-12-15)Population-scale single-cell RNA sequencing (scRNA-seq) is now viable, enabling finer resolution functional genomics studies and leading to a rush to adapt bulk methods and develop new single-cell-specific methods to perform these studies. Simulations are useful for developing, testing, and benchmarking methods but current scRNA-seq simulation frameworks do not simulate population-scale data with genetic effects. Here, we present splatPop, a model for flexible, reproducible, and well-documented simulation of population-scale scRNA-seq data with known expression quantitative trait loci. splatPop can also simulate complex batch, cell group, and conditional effects between individuals from different cohorts as well as genetically-driven co-expression.