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Biology subjects

Firth, H. V.

Publications and source records attributed to Firth, H. V..

9 recordsLinked to original sources

Mapping MAVE data for use in human genomics applications

The large-scale experimental measures of variant functional assays submitted to MaveDB have the potential to provide key information for resolving variants of uncertain significance, but the reporting of results relative to assayed sequence hinders their downstream utility. The Atlas of Variant Effects Alliance mapped multiplexed assays of variant effect data to human reference sequences, creating a robust set of machine-readable homology mappings. This method processed approximately 2.5 million protein and genomic variants in MaveDB, successfully mapping 98.61% of examined variants and disseminating data to resources such as the UCSC Genome Browser and Ensembl Variant Effect Predictor.

bioinformatics↗

Integrating healthcare and research genetic data empowers the discovery of 49 novel developmental disorders

De novo mutations (DNMs) in protein-coding genes are a well-established cause of developmental disorders (DD). However, known DD-associated genes only account for a minority of the observed excess of such DNMs. To identify novel DD-associated genes, we integrated healthcare and research exome sequences on 31,058 DD parent-offspring trios, and developed a simulation-based statistical test to identify gene-specific enrichments of DNMs. We identified 285 significantly DD-associated genes, including 28 not previously robustly associated with DDs. Despite detecting more DD-associated genes than in any previous study, much of the excess of DNMs of protein-coding genes remains unaccounted for. Modelling suggests that over 1,000 novel DD-associated genes await discovery, many of which are likely to be less penetrant than the currently known genes. Research access to clinical diagnostic datasets will be critical for completing the map of dominant DDs.

genomics↗

A cellular census of healthy lung and asthmatic airway wall identifies novel cell states in health and disease

Human lungs enable efficient gas exchange, and form an interface with the environment which depends on mucosal immunity for protection against infectious agents. Tightly controlled interactions between structural and immune cells are required to maintain lung homeostasis. Here, we use single cell transcriptomics to chart the cellular landscape of upper and lower airways and lung parenchyma in health. We report location-dependent airway epithelial cell states, and a novel subset of tissue-resident memory T cells. In lower airways of asthma patients, mucous cell hyperplasia is shown to stem from a novel mucous ciliated cell state, as well as goblet cell hyperplasia. We report presence of pathogenic effector Th2 cells in asthma, and find evidence for type-2 cytokines in maintaining the altered epithelial cell states. Unbiased analysis of cell-cell interactions identify a shift from airway structural cell communication in health to a Th2-dominated interactome in asthma.

immunology↗

Contribution of Retrotransposition to Developmental Disorders

Mobile genetic Elements (MEs) are segments of DNA which, through an RNA intermediate, can generate new copies of themselves and other transcribed sequences through the process of retrotransposition (RT). In humans several disorders have been attributed to RT, but the role of RT in severe developmental disorders (DD) has not yet been explored. As such, we have identified RT-derived events in 9,738 exome sequenced trios with DD-affected probands as part of the Deciphering Developmental Disorders (DDD) study. We have ascertained 9 de novo MEs, 4 of which are likely causative of the patients symptoms (0.04% of probands), as well as 2 de novo gene retroduplications. Beyond identifying likely diagnostic RT events, we have estimated genome-wide germline ME mutagenesis and constraint and demonstrated that coding RT events have signatures of purifying selection equivalent to those of truncating mutations. Overall, our analysis represents a comprehensive interrogation of the impact of retrotransposition on protein coding genes and a framework for future evolutionary and disease studies.

genetics↗

VEP-G2P: A Tool for Efficient, Flexible and Scalable Diagnostic Filtering of Genomic Variants

PurposeWe aimed to develop an efficient, flexible, scalable and evidence-based approach to sequence-based diagnostic analysis/re-analysis of conditions with very large numbers of different causative genes. We then wished to define the expected rate of plausibly causative variants coming through strict filtering in control in comparison to disease populations to quantify background diagnostic \"noise\".\n\nMethodsWe developed G2P (www.ebi.ac.uk/gene2phenotype) as an online system to facilitate the development, validation, curation and distribution of large-scale, evidence-based datasets for use in diagnostic variant filtering. Each locus-genotype-mechanism-disease-evidence thread (LGMDET) associates an allelic requirement and a mutational consequence at a defined locus with a disease entity and a confidence level and evidence links. We then developed an extension to Ensembl Variant Effect Predictor (VEP), VEP-G2P, which can filter based on G2P other widely used gene panel curation systems. We compared the output of disease-associated and control whole exome sequence (WES) using Developmental Disorders G2P (G2PDD; 2044 LGMDETs) and constitutional cancer predisposition G2P (G2PCancer; 128 LGMDETs).\n\nResultsWe have shown a sensitivity/precision of 97.3%/33% and 81.6%/22.7% for causative de novo and inherited variants respectively using VEP-G2PDD in DDD study probands WES. Many of the apparently diagnostic genotypes \"missed\" are likely false-positive reports with lower minor allele frequencies and more severe predicted consequences being diagnostically-discriminative features.\n\nConclusionCase:control comparisons using VEP-G2PDD established an observed:expected ratio of 1:30,000 plausibly causative variants in proband WES to ~1:40,000 reportable but presumed-benign variants in controls. At least half the filtered variants in probands represent background \"noise\". Supporting phenotypic evidence is, therefore, necessary in genetically-heterogeneous disorders. G2P and VEP-G2P provides a practical approach to optimize disease-specific filtering parameters in diagnostic genetic research.

genetics↗

Mutational origins and pathogenic consequences of multinucleotide mutations in 6,688 trios with developmental disorders

De novo mutations (DNMs) in protein-coding genes are a well-established cause of developmental disorders (DD). However, known DD-associated genes only account for a minority of the observed excess of such DNMs. To identify novel DD-associated genes, we integrated healthcare and research exome sequences on 31,058 DD parent-offspring trios, and developed a simulation-based statistical test to identify gene-specific enrichments of DNMs. We identified 299 significantly DD-associated genes, including 49 not previously robustly associated with DDs. Despite detecting more DD-associated genes than in any previous study, much of the excess of DNMs of protein-coding genes remains unaccounted for. Modelling suggests that over 500 novel DD-associated genes await discovery, many of which are likely to be less penetrant than the currently known genes. Research access to clinical diagnostic datasets will be critical for completing the map of dominant DDs.

genomics↗

The contribution of non-canonical splicing mutations to severe dominant developmental disorders

Mutations which perturb normal pre-mRNA splicing are significant contributors to human disease. We used exome sequencing data from 7,833 probands with developmental disorders (DD) and their unaffected parents, as well as >60,000 aggregated exomes from the Exome Aggregation Consortium, to investigate selection around the splice site, and quantify the contribution of splicing mutations to DDs. Patterns of purifying selection, a deficit of variants in highly constrained genes in healthy subjects and excess de novo mutations in patients highlighted particular positions within and around the consensus splice site of greater functional relevance. Using mutational burden analyses in this large cohort of proband-parent trios, we could estimate in an unbiased manner the relative contributions of mutations at canonical dinucleotides (73%) and flanking non-canonical positions (27%), and calculated the positive predictive value of pathogenicity for different classes of mutations. We identified 18 patients with likely diagnostic de novo mutations in dominant DD-associated genes at non-canonical positions in splice sites. We estimate 35-40% of pathogenic variants in non-canonical splice site positions are missing from public databases.

genetics↗

Autosomal recessive coding variants explain only a small proportion of undiagnosed developmental disorders in the British Isles

Large exome-sequencing datasets offer an unprecedented opportunity to understand the genetic architecture of rare diseases, informing clinical genetics counseling and optimal study designs for disease gene identification. We analyzed 7,448 exome-sequenced families from the Deciphering Developmental Disorders study, and, for the first time, estimated the causal contribution of recessive coding variation exome-wide. We found that the proportion of cases attributable to recessive coding variants is surprisingly low in patients of European ancestry, at only 3.6%, versus 50% of cases explained by de novo coding mutations. Surprisingly, we found that, even in European probands with affected siblings, recessive coding variants are only likely to explain ~12% of cases. In contrast, they account for 31% of probands with Pakistani ancestry due to elevated autozygosity. We tested every gene for an excess of damaging homozygous or compound heterozygous genotypes and found three genes that passed stringent Bonferroni correction: EIF3F, KDM5B, and THOC6. EIF3F is a novel disease gene, and KDM5B has previously been reported as a dominant disease gene. KDM5B appears to follow a complex mode of inheritance, in which heterozygous loss-of-function variants (LoFs) show incomplete penetrance and biallelic LoFs are fully penetrant. Our results suggest that a large proportion of undiagnosed developmental disorders remain to be explained by other factors, such as noncoding variants and polygenic risk.

genetics↗

De novo mutations in regulatory elements cause neurodevelopmental disorders

SummaryDe novo mutations in hundreds of different genes collectively cause 25-42% of severe developmental disorders (DD). The cause in the remaining cases is largely unknown. The role of de novo mutations in regulatory elements affecting known DD associated genes or other genes is essentially unexplored. We identified de novo mutations in three classes of putative regulatory elements in almost 8,000 DD patients. Here we show that de novo mutations in highly conserved fetal-brain active elements are significantly and specifically enriched in neurodevelopmental disorders. We identified a significant two-fold enrichment of recurrently mutated elements. We estimate that, genome-wide, de novo mutations in fetaLbrain active elements are likely to be causal for 1-3% of patients without a diagnostic coding variant and that only a small fraction (<2%) of de novo mutations in these elements are pathogenic. Our findings represent a robust estimate of the contribution of de novo mutations in regulatory elements to this genetically heterogeneous set of disorders, and emphasise the importance of combining functional and evolutionary evidence to delineate regulatory causes of genetic disorders.

genetics↗