We are performing whole genome sequencing (WGS) of families with Autism Spectrum Disorder (ASD) to build a resource, named MSSNG, to enable the sub-categorization of phenotypes and underlying genetic factors involved. Here, we report WGS of 5,205 samples from families with ASD, accompanied by clinical information, creating a database accessible in a cloud platform, and through an internet portal with controlled access. We found an average of 73.8 de novo single nucleotide variants and 12.6 de novo insertion/deletions (indels) or copy number variations (CNVs) per ASD subject. We identified 18 new candidate ASD-risk genes such as MED13 and PHF3, and found that participants bearing mutations in susceptibility genes had significantly lower adaptive ability (p=6×10−4). In 294/2,620 (11.2%) of ASD cases, a molecular basis could be determined and 7.2% of these carried CNV/chromosomal abnormalities, emphasizing the importance of detecting all forms of genetic variation as diagnostic and therapeutic targets in ASD.

The Human Developmental Cell Atlas (HDCA) initiative, which is part of the Human Cell Atlas, aims to create a comprehensive reference map of cells during development. This will be critical to understanding normal organogenesis, the effect of mutations, environmental factors and infectious agents on human development, congenital and childhood disorders, and the cellular basis of ageing, cancer and regenerative medicine. Here we outline the HDCA initiative and the challenges of mapping and modelling human development using state-of-the-art technologies to create a reference atlas across gestation. Similar to the Human Genome Project, the HDCA will integrate the output from a growing community of scientists who are mapping human development into a unified atlas. We describe the early milestones that have been achieved and the use of human stem-cell-derived cultures, organoids and animal models to inform the HDCA, especially for prenatal tissues that are hard to acquire. Finally, we provide a roadmap towards a complete atlas of human development.Most modern developmental biology research has historically focused on model organisms. Owing to practical challenges, human development-from a fertilized ovum to a fully formed fetus at birth-has remained a poorly understood 'black box'. The implications of a human developmental cell atlas for understanding human development are far-reaching, as many congenital disorders and childhood cancers may originate during susceptible windows of development [1][2][3] . The clinical relevance of the atlas extends into adulthood for ageing, cancer and applications in regenerative medicine and stem cell therapies 4-6 . Furthermore, embryonic and fetal stem cells 7,8 and developmental trajectories provide an essential reference and guide for engineering human stem-cell-derived models 9-13 , organoids 14 and cellular therapies.Human development begins with a fertilized oocyte that divides and differentiates through preimplantation, embryonic and fetal stages (Fig. 1). Early studies began with morphometric and qualitative assessments of human embryos, leading to development of the Carnegie staging system 15 (Fig. 1). Advances in imaging, cytometry and genomics technologies have provided further insights into the complex spatiotemporal changes during organogenesis 16 . Recent progress in single-cell profiling technologies has revolutionized our ability to study human development at an unprecedented resolution 17 . Leveraging these advances to build a comprehensive atlas of human development (from the fertilized oocyte to birth) at cellular resolution is an ambitious endeavour that is similar in scale to the Human Genome Project,

There are an increasing number of population studies collecting data and samples to illuminate gene-environment contributions to disease risk and health. The rising affordability of innovative technologies capable of generating large amounts of data helps achieve statistical power and has paved the way for new international research collaborations. Most data and sample collections can be grouped into longitudinal, disease-specific, or residual tissue biobanks, with accompanying ethical, legal, and social issues (ELSI). Issues pertaining to consent, confidentiality, and oversight cannot be examined using a one-size-fits-all approach-the particularities of each biobank must be taken into account. It remains to be seen whether current governance approaches will be adequate to handle the impact of next-generation sequencing technologies on communication with participants in population biobanking studies.

Given the data-rich nature of modern biomedical research, there is a pressing need for a systematic, structured, computer-readable way to capture, communicate, and manage sharing rules that apply to biomedical resources. This is essential for responsible recording, versioning, communication, querying, and actioning of resource sharing plans. However, lack of a common “information model” for rules and conditions that govern the sharing of materials, methods, software, data, and knowledge creates a fundamental barrier. Without this, it can be virtually impossible for Research Ethics Committees (RECs), Institutional Review Boards (IRBs), Data Access Committees (DACs), biobanks, and end users to confidently track, manage, and interpret applicable legal and ethical requirements. This raises costs and burdens of data stewardship and decreases efficient and responsible access to data, biospecimens, and other resources. To address this, the GA4GH and IRDiRC organizations sponsored the creation of the Automatable Discovery and Access Matrix (ADA-M, read simply as “Adam”). ADA-M is a comprehensive information model that provides the basis for producing structured metadata “Profiles” of regulatory conditions, thereby enabling efficient application of those conditions across regulatory spheres. Widespread use of ADA-M will aid researchers in globally searching and prescreening potential data and/or biospecimen resources for compatibility with their research plans in a responsible and efficient manner, increasing likelihood of timely DAC approvals while also significantly reducing time and effort DACs, RECs, and IRBs spend evaluating resource requests and research proposals. Extensive online documentation, software support, video guides, and an Application Programming Interface (API) for ADA-M have been made available.

We propose a standard model for a novel data access tier – registered access – to facilitate access to data that cannot be published in open access archives owing to ethical and legal risk. Based on an analysis of applicable research ethics and other legal and administrative frameworks, we discuss the general characteristics of this Registered Access Model, which would comprise a three-stage approval process: Authentication, Attestation and Authorization. We are piloting registered access with the Demonstration Projects of the Global Alliance for Genomics and Health for which it may provide a suitable mechanism for access to certain data types and to different types of data users.