For our next talk, in the BDI/CHG (gen)omics Seminar series, we will be hearing from Yuyang Chen, DPhil, Computational Rare Disease Genomics research group; Dr Ping Zhang, Senior postdoctoral scientist in statistical functional genomics, Centre for Human Genetics and Jennifer Astley, DPhil, Statistical Genomics and Computational Immunology, NDORMS. We’re delighted to host Yuyang, Ping and Jennifer, in what promises to be a great talk!
Date: Tuesday 1 October
Time: 9:30 am – 10:30 am
9:30 – 9:45 : De novo variants in the RNU4-2 snRNA cause a frequent neurodevelopmental syndrome, Yuyang Chen
9:45 – 10:00 : Regulatory variation in MTOR dampens Neutrophil-T cell crosstalk during sepsis, Dr Ping Zhang
10:00 – 10:15 : Single-cell eQTL mapping identifies cell-type and disease-specific genetic control of COVID-19 severity, Jennifer Astley
Followed by Q&A
10:30 – Networking and refreshments in the atrium
Location: Big Data Institute, Seminar Room 1
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Talk 1: De novo variants in the RNU4-2 snRNA cause a frequent neurodevelopmental syndrome
Background: Around 60% of individuals with neurodevelopmental disorders (NDD) remain undiagnosed after comprehensive genetic testing, primarily of protein-coding genes. Increasingly, large genome-sequenced cohorts are improving our ability to discover new diagnoses in the non-coding genome.
Methods/results: Using a cohort of 8,841 probands with genetically undiagnosed NDD in Genomics England (GEL), we identify the non-coding RNA RNU4-2 as a novel syndromic NDD gene. RNU4-2 encodes the U4 small nuclear RNA (snRNA), which is a critical component of the major spliceosome. We identify an 18 bp region of RNU4-2 mapping to two structural elements in the U4/U6 snRNA duplex that is severely depleted of variation in the general population, but in which we identify heterozygous variants in 115 individuals with NDD across cohorts. This region is significantly enriched for variants in GEL NDD probands compared to individuals in the UK Biobank (OR=85.8; 95%CI:56.4-131.6; Fisher’s P=1.84×10-78). The majority of individuals with NDD (77.4%) have the same highly recurrent single base-pair insertion (n.64_65insT). Strikingly, for 54 individuals where we could determine the parent of origin of the identified de novo mutations, all 54 were on the maternal allele, pointing to a novel mutational mechanism. Individuals with RNU4-2 variants have a severe NDD syndrome with global developmental delay, intellectual disability, speech abnormalities, microcephaly, hypotonia, short stature and seizures. Using blood RNA-sequencing data from five individuals, we show a systematic change in 5’ splice site usage in individuals with RNU4-2 variants compared to controls, consistent with the importance of this region of the U4 snRNA in correctly positioning the U6 ACAGAGA sequence to receive the 5’ splice site. We demonstrate that RNU4-2 is highly expressed in the developing human brain, in contrast to other U4 homologs, supporting RNU4-2’s role as the primary U4 transcript in the brain. Finally, we estimate that variants in this 18 bp region of RNU4-2 explain 0.41% of individuals with NDD.
Conclusion: We identify variants in RNU4-2 as one of the most common causes of NDD, underscoring the importance of non-coding genes in rare disorders. This work will provide a diagnosis to thousands of individuals with NDD worldwide and catalyse development of treatments for these individuals.
Bio: Yuyang is a DPhil student from the Computational Rare Disease Genomics research group led by Dr Nicky Whiffin at the Big Data Institute. His research project focuses on identifying variants in the non-coding region that are related to rare diseases.
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Talk 2: Regulatory variation in MTOR dampens Neutrophil-T cell crosstalk during sepsis
Background
Sepsis is a heterogeneous clinical syndrome and personalised stratification strategies are essential to successful targeted therapeutics. A sepsis response signature, SRS1, identifies a subset of severe patients that were associated with immunosuppressive neutrophils, T cell exhaustion and hypoxia networks. We aim to identify and characterise genetic markers that interact with SRS endotypes, and mediators involving key cellular phenotypes that could inform novel therapeutics.
Methods
We mapped the genomic and epigenomic determinants of variation for MTOR expression in sepsis and combined with genetic colocalisation and interaction analyses to identify likely causal cell-cell communications. We assayed the genetic and cellular interactions and immune modulators using an ex vivo co-culture model and omics sequencing. We performed association tests for 28 day survival of sepsis patients in the UK Genomic Advances in Sepsis (GAinS) cohort.
Results
We identify genetic variation residing in a context-specific regulatory element of T cells that has an inverted effect on MTOR expression between activated T cells and neutrophils, decreasing and increasing expression respectively. We find significant interaction between the variation and known prognostic markers SRS endotype and neutrophil to lymphocyte ratio. Our co-culture model revealed that activated T cells promote immunosuppressive sepsis neutrophils, which in turn suppress T cell activation. We find the hyper-activation of sepsis neutrophils by T cells is dampened under hypoxia condition and by a specific mTOR inhibitor rapamycin. The minor G allele of the variation associated with reduced mTOR signalling and cytokine release in T cells is protective for patient survival during sepsis.
Significance
This study demonstrates how common genetic variations can interact with disease endotypes to affect immune cell crosstalk, providing a patient stratification strategy for more effective sepsis treatment. Our findings may also contribute to understanding severe infections associated with CAR T-cell therapy.
Bio: Dr Ping Zhang is a senior postdoctoral scientist in statistical functional genomics. He is currently working with Professor Julian Knight’s group at the Centre for Human Genetics, focusing on identifying the genetic factors and underlying mechanisms that contribute to the heterogeneity of infectious diseases.
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Talk 3: Single-cell eQTL mapping identifies cell-type and disease-specific genetic control of COVID-19 severity
Abstract: The impact that genotype has on gene expression can depend on both cellular and organismal context. In this study, we set out to identify expression quantitative trait loci (eQTLs) across multiple blood cell types in individuals suffering from a range of types and severities of infectious disease, including Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) and sepsis, and estimated how the impact of these genetic variants was influenced by disease state. We analysed single-cell transcriptomic and genome-wide genetic data from 76 donors and ~4×105 cells of European ancestry generated as part of the COvid-19 Multi-omics Blood ATlas (COMBAT) Consortium: 8 healthy individuals, 16 diagnosed with sepsis at the time of sample collection, and 52 individuals diagnosed with Coronavirus disease (COVID-19) at WHO-defined stages of severity. In total, we mapped 2,607 independent cis-eQTL signals across 15 cell types. The vast majority of eQTLs showed similar effects across disease conditions, with 3 genes showing significant differences in eQTL effect across disease states. The strongest modified eQTL was found at the RPS26 locus across multiple cell types, which showed a progressively smaller effect in increasingly severe infections. This modified eQTL variant is also associated with Type 1 Diabetes, which may represent a relationship between genotype, infection status and autoimmunity. We performed fine-mapping to identify potential causal variants for modified eQTLs and found potential causal variants that disrupted transcription factor binding motifs. Our results demonstrate that the overriding effect of genetics on gene expression in blood immune cells is independent of infection status or disease severity. However, small numbers of eQTLs are modified by infection, and these differences can illustrate potentially important immune biology.
Bio: I am a third year DPhil student in Molecular and Cellular Medicine at the Kennedy Institute of Rheumatology. I completed my Masters in Mathematics at Durham University before going on to work as a software test engineer at a semi-conductor company for a few years. I then came to Oxford to complete the MSc in Modelling for Global Health where I studied and developed mathematical models for infectious disease transmission with a focus on resource-limited contexts and health policy. In the Kennedy I work in the Luke Jostins and Yang Luo groups where we develop and apply statistical methods to understand the genetic contribution to immune-mediated traits.
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As a reminder, the (gen)omics seminar series runs every other Tuesday morning and is intended to increase interaction between individuals working in genomics across Oxford. We encourage in-person attendance where possible. There is time for discussion over, tea, coffee and pastries after the talks.
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