Biology subjects

Genomics England Research Consortium,

Publications and source records attributed to Genomics England Research Consortium,.

9 recordsLinked to original sources

bioRxiv2022

Heritability of de novo germline mutation reveals a contribution from paternal but not maternal genetic factors

De novo mutations (DNMs) in the germline have long been identified as a key element in the causes of developmental and other genetic disorders. Previous attempts to investigate genetic factors affecting DNMs have suffered from a lack of statistical power, due to the difficulty of obtaining a sufficient number of parent-offspring trios. Thus, the rare disease cohort of the UKs 100k Genomes Project (100kGP), comprising more than 10,000 trios, represents an unprecedented opportunity to investigate the genetics of germline mutation. Here we estimate SNP heritability of DNM count in offspring, as a measure of the relative contribution of genetic factors to the variance of the trait, in a PCA-selected subset of the 100kGP cohort. We estimate separate SNP heritabilities for paternally and maternally transmitted mutations (based on parentally phased DNMs in offspring), computed using parental genetic variants at a range of minimum frequencies and a variety of methodologies. We estimate a heritability of 10-20% for paternal DNMs; by contrast, for maternal DNMs we find no significant evidence for non-zero heritability. We investigated the partitioning of heritability among genes with different expression profiles in different tissue or cell states, and found a relative heritability enrichment for genes expressed in gonadal tissues, particularly testis. Among germ cells in adult testes we observed relative enrichment of heritability in genes associated with the (undifferentiated) spermatogonial stem cell state.

genetics↗

bioRxiv2022

Zfp503/Nlz2 is Required for RPE Differentiation and Optic Fissure Closure

PurposeUveal coloboma is a congenital eye malformation caused by failure of the optic fissure to close in early human development. Despite significant progress in identifying genes whose regulation is important for executing this closure, mutations are detected in a minority of cases using known gene panels, implying additional genetic complexity. We have previously shown knock down of znf503 (the ortholog of mouse Zfp503) in zebrafish causes coloboma. Here we characterize Zfp503 knock out (KO) mice and evaluate transcriptomic profiling of mutant vs. wild-type (WT) retinal pigment epithelium (RPE)/Choroid. MethodsZfp503 KO mice were generated by gene targeting using homologous recombination. Embryos were characterized grossly and histologically. Patterns and level of developmentally relevant proteins/genes were examined with immunostaining/in situ hybridization. The transcriptomic profile of E11.5 KO RPE/choroid was compared to that of WT. ResultsZfp503 is dynamically expressed in developing mouse eyes and that loss of its expression results in uveal coloboma. KO embryos exhibit altered mRNA levels and expression patterns of several key transcription factors involved in eye development, including Otx2, Mitf, Pax6, Pax2, Vax1 and Vax2, resulting in reduced melanin pigmentation in the presumptive RPE and its differentiation into neural-retina-like lineages. Comparison of RNA-Seq data from wild type and KO E11.5 embryos demonstrated reduced expression of melanin-related genes and significant overlap with genes known to be dynamically regulated at the optic fissure. ConclusionsThese results demonstrate a critical role of Zfp503 in RPE differentiation and in optic fissure closure.

developmental biology↗

bioRxiv2022

Clinical application of tumour in normal contamination assessment from whole genome sequencing

The unexpected contamination of normal samples with tumour cells reduces variant detection sensitivity, compromising downstream analyses in canonical tumour-normal analyses. Leveraging whole-genome sequencing data available at Genomics England, we develop a tool for normal sample contamination assessment, which we validate in silico and against minimal residual disease testing. From a systematic review of 771 patients with haematological malignancies and sarcomas, we find contamination across a range of cancer clinical indications and DNA sources, with highest prevalence in saliva samples from acute myeloid leukaemia patients, and sorted CD3+ T-cells from myeloproliferative neoplasms. Further exploration reveals 108 hotspot mutations in genes associated with haematological cancers at risk of being subtracted by standard variant calling pipelines. Our work highlights the importance of contamination assessment for accurate somatic variants detection in research and clinical settings, especially with large-scale sequencing projects being utilised to deliver accurate data from which to make clinical decisions for patient care.

bioinformatics↗

bioRxiv2022

Mutation Rate Evolution Drives Immune Escape In Mismatch Repair-Deficient Cancer

Mutation rate optimisation drives evolution and immune evasion of bacteria and lentiviral strains, including HIV. Whether evolving cancer lineages similarly adapt mutation rates to increase tumour cell fitness is unknown. Here, by mapping the clonal topography of mismatch repair-deficient (MMRd) colorectal cancer, we show that genomic MMRd mutability co-evolves with neoantigen selection to drive intratumour diversification and immune escape. Mechanistically, we find that microsatellite instability modulates subclonal DNA repair by toggling two hypermutable mononucleotide homopolymer runs in the mismatch repair genes MSH6 and MSH3 (C8 and A8, respectively) through stochastic frameshift switching. Spontaneous mutation and reversion at these evolvability switches modulates subclonal mutation rate, mutation bias, and clonal HLA diversity during MMRd cancer evolution. Combined experimental and simulation studies demonstrate that subclonal immune selection favours incremental MMR mutations. MMRd cancers thus fuel intratumour heterogeneity by adapting subclonal mutation rate and mutation bias to immune selection, revealing a conserved co-evolutionary arms race between neoantigen selection and adaptive genomic mutability. Our work reveals layers of mutational complexity and microsatellite biology in MMRd cancer evolution previously hidden in bulk analyses.

cancer biology↗

bioRxiv2021

A basement membrane discovery pipeline uncovers network complexity, new regulators, and human disease associations

Basement membranes (BMs) are ubiquitous extracellular matrices whose composition remains elusive, limiting our understanding of BM regulation and function. By developing a bioinformatic and in vivo discovery pipeline, we define a network of 222 human proteins localized to BMs. Network analysis and screening in C. elegans and zebrafish identified new BM regulators, including ADAMTS, ROBO, and TGF{beta}. More than 100 BM-network genes associate with human phenotypes and by screening 63,039 genomes from families with rare disorders, we discovered loss-of-function variants in LAMA5, MPZL2, and MATN2, and show they regulate BM composition and function. This cross-disciplinary study establishes the immense complexity and role of BMs in human health.

cell biology↗

bioRxiv2021

REViewer: Haplotype-resolved visualization of read alignments in and around tandem repeats

BackgroundExpansions of short tandem repeats are the cause of many neurogenetic disorders including familial amyotrophic lateral sclerosis, Huntington disease, and many others. Multiple methods have been recently developed that can identify repeat expansions in whole genome or exome sequencing data. Despite the widely-recognized need for visual assessment of variant calls in clinical settings, current computational tools lack the ability to produce such visualizations for repeat expansions. Expanded repeats are difficult to visualize because they correspond to large insertions relative to the reference genome and involve many misaligning and ambiguously aligning reads. ResultsWe implemented REViewer, a computational method for visualization of sequencing data in genomic regions containing long repeat expansions. To generate a read pileup, REViewer reconstructs local haplotype sequences and distributes reads to these haplotypes in a way that is most consistent with the fragment lengths and evenness of read coverage. To create appropriate training materials for onboarding new users, we performed a concordance study involving 12 scientists involved in STR research. We used the results of this study to create a user guide that describes the basic principles of using REViewer as well as a guide to the typical features of read pileups that correspond to low confidence repeat genotype calls. Additionally, we demonstrated that REViewer can be used to annotate clinically-relevant repeat interruptions by comparing visual assessment results of 44 FMR1 repeat alleles with the results of triplet repeat primed PCR. For 38 of these alleles, the results of visual assessment were consistent with triplet repeat primed PCR. ConclusionsRead pileup plots generated by REViewer offer an intuitive way to visualize sequencing data in regions containing long repeat expansions. Laboratories can use REViewer to assess the quality of repeat genotype calls as well as to visually detect interruptions or other imperfections in the repeat sequence and the surrounding flanking regions.

bioinformatics↗

bioRxiv2021

Genetic and pharmacological causes of germline hypermutation

Mutation in the germline is the source of all evolutionary genetic variation and a cause of genetic disease. Previous studies have shown parental age to be the primary determinant of the number of new germline mutations seen in an individuals genome. Here we analysed the genome-wide sequences of 21,879 families with rare genetic diseases and identified 12 hypermutated individuals with between two and seven times more de novo single nucleotide variants (dnSNVs) than expected. In most of these families (8/12) the excess mutations could be attributed to the father. We determined that two of these families had genetic drivers of germline hypermutation, with the fathers carrying damaging genetic variation in known DNA repair genes, causing distinctive mutational signatures. For five families, by analysing clinical records and mutational signatures, we determined that paternal exposure to chemotherapeutic agents prior to conception was a key driver of hypermutation. Our results suggest that the germline is well protected from mutagenic effects, hypermutation is rare and relatively modest in degree and that most hypermutated individuals will not have a genetic disease.

genomics↗

bioRxiv2020

New pathogenic variants and insights into pathogenic mechanisms in GRK1-related Oguchi disease.

PurposeBiallelic mutations in G-Protein coupled receptor kinase 1 (GRK1) cause Oguchi disease, a rare subtype of congenital stationary night blindness (CSNB). The purpose of this study was to identify pathogenic GRK1 variants and use in-depth bioinformatic analyses to evaluate how their impact on protein structure could lead to pathogenicity. MethodsPatients genomic DNA was sequenced by whole genome, whole exome or focused exome sequencing. Pathogenic variants, published and novel, were compared to nondisease associated missense variants. The impact of GRK1 missense variants at the protein level were then predicted using a series of computational tools. ResultsWe identified eleven previously unpublished cases with biallelic pathogenic GRK1 variants, including seven novel variants, and reviewed all GRK1 pathogenic variants. Further structure-based scoring revealed a hotspot for missense variants in the kinase domain. Additionally, to aid future clinical interpretation, we identified the bioinformatics tools best able to differentiate pathogenic from non-pathogenic variants. ConclusionWe identified new GRK1 pathogenic variants in Oguchi disease patients and investigated how disease-causing variants may impede protein function, giving new insights into the mechanisms of pathogenicity. All pathogenic GRK1 variants described to date have been collated into a Leiden Open Variation Database (http://dna2.leeds.ac.uk/GRK1_LOVD/genes/GRK1).

genetics↗

bioRxiv2019

Functional and in-silico interrogation of rare genomic variants impacting RNA splicing for the diagnosis of genomic disorders

PurposeTo develop a comprehensive analysis framework to identify pre-messenger RNA splicing mutations in the context of rare disease.\n\nMethodsWe assessed variants of uncertain significance through six in-silico prioritization strategies. Firstly, through comparison to functional analyses, we determined the precise effect on splicing of variants identified through clinical multi-disciplinary meetings. Next, we calculated the sensitivity of in-silico prioritization strategies to distinguish known splicing mutations from common variation (>2% in allele frequency in gnomAD) within relevant disease genes. These approaches defined an accurate in-silico strategy for variant prioritization, which we retrospectively applied to a large cohort of 2783 individuals who had previously received genomic testing for rare genomic disorders. We assessed the clinical impact of such prioritization strategies alongside routine diagnostic testing strategies.\n\nResultsWe identified 21 variants that potentially impacted splicing, and used cell based splicing assays to identify those variants which disrupted normal splicing. These findings underpinned new molecular diagnoses for 14 individuals. This process established that the use of pre-defined thresholds from a machine learning splice prediction algorithm, SpliceAI, was the most efficient method for variant prioritization, with a positive predictive value of 86%. We analysed 1,346,744 variants identified through diagnostic testing for 2783 individuals and observed that splicing variant prioritization strategies would improve clarity in clinical analysis for 15% of the individuals surveyed. Prioritized variants could provide new molecular diagnoses or provide additional support for molecular diagnosis for up to 81 individuals within our cohort.\n\nConclusionWe present an in-silico and functional analysis framework for the assessment of variants impacting pre-messenger RNA splicing which is applicable across monogenic disorders. Incorporation of these strategies improves clarity in diagnostic reporting, increases diagnostic yield and, with the advent of targeted treatment strategies, can directly alter patient clinical management.\n\nKey HighlightsO_LIWe establish an in-silico and functional analysis framework for the incorporation of splice variant assessment into diagnostic testing that is applicable across monogenic disorders.\nC_LIO_LIAfter assessment of six distinct variant prioritization strategies, we concluded that SpliceAI was the best method to accurately identify genomic variation disrupting normal pre-mRNA splicing. We determined this through (i) functional assessment of novel variants of uncertain significance described in this study, and (ii) calculation of sensitivity and specificity for prioritization strategies to distinguish known splicing mutations from common variants in the general population.\nC_LIO_LIWe describe novel disease-causing variants with support from cell based functional assays which underpin autosomal recessive, autosomal dominant and X-linked Mendelian disorders. This includes variants which are deeply intronic, within the nearby splice region of canonical splice sites and variants which activate cryptic splice sites within the protein-coding regions of genes.\nC_LIO_LIWe integrated the best performing variant prioritization strategy alongside clinical diagnostic testing for 2783 individuals referred to a well-established targeted gene panel test available through the UK National Health Service. We show that integration of such strategies will increase accuracy and clarity of diagnostic reporting, including the identification of variants which could provide new diagnoses and new carrier findings for referred individuals.\nC_LIO_LIFunctional assessment is essential for accurate clinical assessment of variants disrupting pre-mRNA splicing. We show through cell based functional assessments that variants impacting splicing may have complex impacts on pre-mRNA splicing, which may cause multiple interpretable consequences according to ACMG guidelines.\nC_LI

genomics↗