Eleanor G. Seaby

Recent progress in human disease genetics is leading to rapid advances in understanding pathobiological mechanisms. However, the sheer number of risk-conveying genetic variants being identified demands in vivo model systems that are amenable to functional analyses at scale. Here we provide a practical guide for using the diploid frog species Xenopus tropicalis to study many genes and variants to uncover conserved mechanisms of pathobiology relevant to human disease. We discuss key considerations in modelling human genetic disorders: genetic architecture, conservation, phenotyping strategy and rigour, as well as more complex topics, such as penetrance, expressivity, sex differences and current challenges in the field. As the patient-driven gene discovery field expands significantly, the cost-effective, rapid and higher throughput nature of Xenopus make it an essential member of the model organism armamentarium for understanding gene function in development and in relation to disease.

Genome sequencing is available as a clinical test in the UK through the Genomic Medicine Service (GMS). The GMS analytical strategy predominantly filters genome data on preselected gene panels. Whilst this reduces variants requiring assessment by reporting laboratories, pathogenic variants outside applied panels may be missed, and variants in genes without established disease–gene relationships are largely ignored. This study compares the analysis of a research exome to a GMS clinical genome for the same patients. For the research exome, we applied a panel-agnostic approach filtering for variants with High Pathogenic Potential (HiPPo) using ClinVar, allele frequency, and in silico prediction tools. We then restricted HiPPo variants to Gene Curation Coalition (GenCC) disease genes. These results were compared with the GMS genome panel-based approach. Twenty-four participants from eight families underwent parallel research exome and GMS genome sequencing. Exome HiPPo analysis identified a similar number of variants as the GMS panel-based approach. GMS genome analysis returned two pathogenic variants and one de novo variant. Exome HiPPo analysis returned the same variants plus an additional pathogenic variant and three further de novo variants in novel genes, where case series are underway. When HiPPo was restricted to GenCC disease genes, statistically fewer variants required assessment to identify more pathogenic variants than reported by the GMS, giving a diagnostic rate per variant assessed of 20% for HiPPo versus 3% for the GMS. With UK plans to sequence 5 million genomes, strategies are needed to optimise genome analysis beyond gene panels whilst minimising the burden of variants requiring clinical assessment.

Introduction: DDX17 is an RNA helicase shown to be involved in critical processes during the early phases of neuronal differentiation. Globally, we identified 11 patients with neurodevelopmental phenotypes with de novo monoallelic variants in DDX17 . All 11 patients had a neurodevelopmental phenotype, whereby intellectual disability, delayed speech and language, and motor delay predominated. Materials and methods: We performed in utero cortical electroporation in the brain of developing mice, assessing axon complexity and outgrowth of electroporated neurons, comparing wild-type and Ddx17 knockdown. We then undertook ex vivo cortical electroporation on neuronal progenitors to quantitively assess axonal development at a single cell resolution. Homozygous and heterozygous ddx17 crispant knockouts in Xenopus tropicalis were generated for assessment of morphology, performed behavioural assays, and neuronal outgrowth measurements. We further undertook transcriptomic analysis of neuroblastoma SH-SY5Y cells, to identify differentially expressed genes in DDX17-KD cells compared to controls. Results: Knockdown of Ddx17 in electroporated mouse neurons in vivo showed delayed neuronal migration as well as decreased cortical axon complexity. Mouse primary cortical neurons revealed reduced axon outgrowth upon knockdown of Ddx17 in vitro . The axon outgrowth phenotype was replicated in crispant ddx17 tadpoles, including in a heterozygous model. Crispant tadpoles had clear functional neural defects and showed an impaired neurobehavioral phenotype. Transcriptomic analysis identified a statistically significant number of differentially expressed genes involved in neurodevelopmental processes in DDX17-KD cells compared to control cells. Discussion: We have identified a new gene, DDX17 , representing a rare cause of neurodevelopmental delay. We provide evidence for the role of the gene and mechanistic basis of dysfunctional neurodevelopment in both mammalian and non-mammalian species.

With the increased availability of genomic sequencing technologies, the molecular bases for kidney diseases such as nephronophthisis and mitochondrially inherited and autosomal-dominant tubulointerstitial kidney diseases (ADTKD) has become increasingly apparent. These tubulointerstitial kidney diseases (TKD) are monogenic diseases of the tubulointerstitium and result in interstitial fibrosis and tubular atrophy (IF/TA). However, monogenic inheritance alone does not adequately explain the highly variable onset of kidney failure and extra-renal manifestations. Phenotypes vary considerably between individuals harbouring the same pathogenic variant in the same putative monogenic gene, even within families sharing common environmental factors. While the extreme end of the disease spectrum may have dramatic syndromic manifestations typically diagnosed in childhood, many patients present a more subtle phenotype with little to differentiate them from many other common forms of non-proteinuric chronic kidney disease (CKD). This review summarises the expanding repertoire of genes underpinning TKD and their known phenotypic manifestations. Furthermore, we collate the growing evidence for a role of modifier genes and discuss the extent to which these data bridge the historical gap between apparently rare monogenic TKD and polygenic non-proteinuric CKD (excluding polycystic kidney disease).

SRRM2 encodes a splicing factor recently implicated in developmental disorders due to a statistical enrichment of de novo mutations. Using data from the 100,000 Genomes Project, four unrelated individuals with intellectual disability (ID) were identified, each harbouring de novo whole gene deletions of SRRM2. Deletions ranged between 248 and 482 kb in size and all distal breakpoints clustered within a complex 144 kb palindrome situated 75 kb upstream of SRRM2. Strikingly, three of the deletions were complex, with inverted internal segments of 45-94 kb. In one proband-mother duo, de novo status was inferred by haplotype analysis. Together with two additional patients who harboured smaller predicted protein-truncating variants (p.Arg632 and p.Ala2223Leufs13), we estimate the prevalence of this condition in cohorts of patients with unexplained ID to be ~1/1300. Phenotypic blending, present for two cases with additional pathogenic variants in CASR/PKD1 and SLC17A5, hampered the phenotypic delineation of this recently described condition. Our data highlights the benefits of genome sequencing for resolving structural complexity and inferring de novo status. The genomic architecture of 16p13.3 may give rise to relatively high rates of complex rearrangements, adding to the list of loci associated with recurrent genomic disorders.

The 100,000 Genomes Project (100KGP) diagnosed a quarter of recruited affected participants, but 26% of diagnoses were in genes not on the chosen gene panel(s); with many being de novo variants of high impact. However, assessing biallelic variants without a gene panel is challenging, due to the number of variants requiring scrutiny. We sought to identify potential missed biallelic diagnoses independent of the gene panel applied using GenePy - a whole gene pathogenicity metric. GenePy scores all variants called in a given individual, incorporating allele frequency, zygosity, and a user-defined deleterious metric (CADD v1.6 applied herein). GenePy then combines all variant scores for individual genes, generating an aggregate score per gene, per participant. We calculated GenePy scores for 2862 recessive disease genes in 78,216 individuals in 100KGP. For each gene, we ranked participant GenePy scores for that gene, and scrutinised affected individuals without a diagnosis whose scores ranked amongst the top-5 for each gene. We assessed these participants’ phenotypes for overlap with the disease gene associated phenotype for which they were highly ranked. Where phenotypes overlapped, we extracted rare variants in the gene of interest and applied phase, ClinVar and ACMG classification looking for putative causal biallelic variants. 3184 affected individuals without a molecular diagnosis had a top-5 ranked GenePy gene score and 682/3184 (21%) had phenotypes overlapping with one of the top-ranking genes. After removing 13 withdrawn participants, in 122/669 (18%) of the phenotype-matched cases, we identified a putative missed diagnosis in a top-ranked gene supported by phasing, ClinVar and ACMG classification. A further 334/669 (50%) of cases have a possible missed diagnosis but require functional validation. Applying GenePy at scale has identified potential diagnoses for 456/3183 (14%) of undiagnosed participants who had a top-5 ranked GenePy score in a recessive disease gene, whilst adding only 1.2 additional variants (per individual) for assessment.

Genome sequencing is now available as a clinical test on the National Health Service (NHS) through the Genome Medicine Service (GMS). The GMS have set out an analytical strategy that predominantly filters genome data on a pre-selected gene panel(s). Whilst this approach reduces the number of variants requiring assessment by reporting laboratories, pathogenic variants outside of the gene panel applied may be missed, and candidate variants in novel genes are largely ignored. This study sought to compare a research exome analysis to an independent clinical genome analysis performed through the NHS for the same group of patients. When analysing the exome data, we applied a panel agnostic approach filtering for variants with Hi gh P athogenic Po tential (HiPPo) using ClinVar, allele frequency, and in silico prediction tools. We then compared this gene agnostic analysis to the panel-based approach as applied by the GMS to genome data. Later we restricted HiPPo variants to a panel of the Gene Curation Coalition (GenCC) morbid genes and compared the diagnostic yield with the variants filtered using the GMS strategy. 24 patients from 8 families underwent parallel research exome sequencing and GMS genome sequencing. HiPPo analysis applied to research exome data identified a similar number of variants as the gene panel-based approach applied by the GMS. GMS clinical genome analysis identified and returned 2 pathogenic variants and 3 variants of uncertain significance. HiPPo research exome analysis identified the same variants plus an additional pathogenic variant and a further 3 de novo variants of uncertain significance in novel genes, where case series and functional studies are underway. When HiPPo was restricted to GenCC disease genes (strong or definitive), the same pathogenic variants were identified yet statistically fewer variants required assessment to identify more diagnostic variants than reported by the GMS genome strategy. This gave a diagnostic rate per variant assessed of 20% for HiPPo restricted to GenCC versus 3% for the GMS panel-based approach. With plans to sequence 5 million more NHS patients, strategies are needed to optimise the full potential of genome data beyond gene panels whilst minimising the burden of variants that require clinical assessment.

Background: Genome sequencing was first offered clinically in the UK through the 100,000 Genomes Project (100KGP). Analysis was restricted to predefined gene panels associated with the patient’s phenotype. However, panels rely on clearly characterised phenotypes and risk missing diagnoses outside of the panel(s) applied. We propose a complementary method to rapidly identify pathogenic variants, including those missed by 100KGP methods. Methods: The Loss-of-function Observed/Expected Upper-bound Fraction (LOEUF) score quantifies gene constraint, with low scores correlated with haploinsufficiency. We applied DeNovoLOEUF, a filtering strategy to sequencing data from 13,949 rare disease trios in the 100KGP, by filtering for rare, de novo, loss-of-function variants in disease genes with a LOEUF score < 0.2. We compared our findings with the corresponding patient’s diagnostic reports. Results: 324/332 (98%) of the variants identified using DeNovoLOEUF were diagnostic or partially diagnostic (whereby the variant was responsible for some of the phenotype). We identified 39 diagnoses that were “missed” by 100KGP standard analyses, which are now being returned to patients. Conclusion: We have demonstrated a highly specific and rapid method with a 98% positive predictive value that has good concordance with standard analysis, low false-positive rate, and can identify additional diagnoses. Globally, as more patients are being offered genome sequencing, we anticipate that DeNovoLOEUF will rapidly identify new diagnoses and facilitate iterative analyses when new disease genes are discovered.

Renal Fanconi syndrome (RFS) is a generalised disorder of the proximal convoluted tubule. Many genes have been associated with RFS including those that cause systemic disorders such as cystinosis, as well as isolated RFS. We discuss the case of a 10‐year‐old female who presented with leg pain and raised creatinine on a screening blood test. Her mother has RFS and required a kidney transplant in her thirties. Further investigations confirmed RFS in the daughter. Exome sequencing was performed on the affected mother, child, and unaffected father. We identified a novel variant in GATM; c.965G>C p.(Arg322Pro) segregating dominantly in the mother and daughter. We validated our finding with molecular dynamics simulations and demonstrated a dynamic signature that differentiates our variant and two previously identified pathogenic variants in GATM from wildtype. Genetic testing has uncovered a novel pathogenic variant that predicts progression to end stage kidney failure and has important implications for family planning and cascade testing. We recommend that GATM is screened for in children presenting with RFS, in addition to adults, particularly with kidney failure, who may have had previous negative gene testing.