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Purpose: In parent-child trios with genome sequencing data, we investigated inherited biallelic deletions to identify known and novel genetic disorders. Methods: We developed a copy-number variations analysis pipeline based on autosomal genome sequencing read depth of Genomics England 100,000 Genomes Project data from 11,754 parent-child trios and additional 18,875 non-trios. A control cohort of 15,440 cancer patients provided independent deletion frequencies. Results: Autosomal recessive (AR) modeling detected 34 distinct rare deletions that were homozygous in the proband and heterozygous in both parents. These inherited biallelic deletions were only detected in 52 trios. These “knockout” regions included 37 genes, having among them 8 with an Online Mendelian Inheritance in Man AR annotation. Deletions of NPHP1, followed by OTOA, both within segmental duplications, were the only recurrent findings explaining phenotypes in a total of 10 and 3 patients, respectively. Recurrent heterozygous NPHP1 deletions were detected in 0.3%-0.5% of controls. We reviewed “knockout” patients for the remaining 29 genes without disease associations and identified SLC66A1 as a likely novel cause for AR rod-cone dystrophy in 4 families. Conclusion: A tailored copy-number variations analysis of genome sequencing trio data shows that biallelic inherited gene deletions are rare, with NPHP1 biallelic deletions causing nephronophthisis the leading finding. We propose SLC66A1 as a novel cause for AR retinopathy.

Genomic science is increasingly central to the provision of health care. Producing and applying robust genomics knowledge is a complex endeavour in which no single individual, profession, discipline or community holds all the answers. Engagement and involvement of diverse stakeholders can support alignment of societal and scientific interests, understandings and perspectives and promises better science and fairer outcomes. In this context we argue for F.A.I.R.E.R. data and data use that is Findable, Accessible, Interoperable, Reproducible, Equitable and Responsible. Yet there is a paucity of international guidance on how to engage publics, patients and participants in genomics. To support meaningful and effective engagement and involvement we developed an Engagement Framework for involving and engaging participants, patients and publics in genomics research and health implementation. The Engagement Framework is intended to support all those working in genomics research, medicine, and healthcare to deliberatively consider approaches to participant, patient and public engagement and involvement in their work. Through a series of questions, the Engagement Framework prompts new ways of thinking about the aims and purposes of engagement, and support reflection on the strengths, limitations, likely outcomes and impacts of choosing different approaches to engagement. To guide genomics activities, we describe four themes and associated questions for deliberative reflection: (i) fairness; (ii) context; (iii) heterogeneity, and (iv) recognising tensions and conflict. The four key components in the Engagement provide a framework to assist those involved in genomics to reflect on decisions they make for their initiatives, including the strategies selected, the participant, patient and public stakeholders engaged, and the anticipated goals. The Engagement Framework is one step in an actively evolving process of building genomics research and implementation cultures which foster responsible leadership and are attentive to objectives which increase equality, diversity and inclusion in participation and outcomes.

The identification of microbiological infection is usually a diagnostic investigation, a complex process that is firstly initiated by clinical suspicion. With the emergence of high-throughput sequencing (HTS) technologies, metagenomic analysis has unveiled the power to identify microbial DNA/RNA from a diverse range of clinical samples (1). Metagenomic analysis of whole human genomes at the clinical/research interface bypasses the steps of clinical scrutiny and targeted testing and has the potential to generate unexpected findings relating to infectious and sometimes transmissible disease. There is no doubt that microbial findings that may have a significant impact on a patient’s treatment and their close contacts should be reported to those with clinical responsibility for the sample-donating patient. There are no clear recommendations on how such findings that are incidental, or outside the original investigation, should be handled. Here we aim to provide an informed protocol for the management of incidental microbial findings as part of the 100,000 Genomes Project which may have broader application in this emerging field. As with any other clinical information, we aim to prioritise the reporting of data that are most likely to be of benefit to the patient and their close contacts. We also set out to minimize risks, costs and potential anxiety associated with the reporting of results that are unlikely to be of clinical significance. Our recommendations aim to support the practice of microbial metagenomics by providing a simplified pathway that can be applied to reporting the identification of potential pathogens from metagenomic datasets. Given that the ambition for UK sequenced human genomes over the next 5 years has been set to reach 5 million and the field of metagenomics is rapidly evolving, the guidance will be regularly reviewed and will likely adapt over time as experience develops.