Cytosine methylation, an epigenetic modification of DNA, is a target of growing interest for developing high throughput profiling technologies. Here we introduce two new, complementary techniques for cytosine methylation profiling utilizing next generation sequencing technology: bisulfite padlock probes (BSPPs) and methyl sensitive cut counting (MSCC). In the first method, we designed a set of ~10,000 BSPPs distributed over the ENCODE pilot project regions to take advantage of existing expression and chromatin immunoprecipitation data. We observed a pattern of low promoter methylation coupled with high gene body methylation in highly expressed genes. Using the second method, MSCC, we gathered genome-scale data for 1.4 million HpaII sites and confirmed that gene body methylation in highly expressed genes is a consistent phenomenon over the entire genome. Our observations highlight the usefulness of techniques which are not inherently or intentionally biased in favor of only profiling particular subsets like CpG islands or promoter regions.

DNA methylation has been traditionally viewed as a highly stable epigenetic mark in post-mitotic cells, however, postnatal brains appear to exhibit stimulus-induced methylation changes, at least in a few identified CpG dinucleotides. How extensively the neuronal DNA methylome is regulated by neuronal activity is unknown. Using a next-generation sequencing-based method for genome-wide analysis at a single-nucleotide resolution, we quantitatively compared the CpG methylation landscape of adult mouse dentate granule neurons in vivo before and after synchronous neuronal activation. About 1.4% of 219,991 CpGs measured show rapid active demethylation or de novo methylation. Some modifications remain stable for at least 24 hours. These activity-modified CpGs exhibit a broad genomic distribution with significant enrichment in low-CpG density regions, and are associated with brain-specific genes related to neuronal plasticity. Our study implicates modification of the neuronal DNA methylome as a previously under-appreciated mechanism for activity-dependent epigenetic regulation in the adult nervous system.

Recent advances in whole genome sequencing have brought the vision of personal genomics and genomic medicine closer to reality. However, current methods lack clinical accuracy and the ability to describe the context (haplotypes) in which genome variants co-occur in a cost-effective manner. Here we describe a low-cost DNA sequencing and haplotyping process, Long Fragment Read (LFR) technology, similar to sequencing long single DNA molecules without cloning or separation of metaphase chromosomes. In this study, ten LFR libraries were made using only ~100 pg of human DNA per sample. Up to 97% of the heterozygous single nucleotide variants (SNVs) were assembled into long haplotype contigs. Removal of false positive SNVs not phased by multiple LFR haplotypes resulted in a final genome error rate of 1 in 10 Mb. Cost-effective and accurate genome sequencing and haplotyping from 10-20 human cells, as demonstrated here, will enable comprehensive genetic studies and diverse clinical applications.

Rapid advances in DNA sequencing promise to enable new diagnostics and individualized therapies. Achieving personalized medicine, however, will require extensive research on highly reidentifiable, integrated datasets of genomic and health information. To assist with this, participants in the Personal Genome Project choose to forgo privacy via our institutional review board- approved “open consent” process. The contribution of public data and samples facilitates both scientific discovery and standardization of methods. We present our findings after enrollment of more than 1,800 participants, including whole-genome sequencing of 10 pilot participant genomes (the PGP-10). We introduce the Genome-Environment-Trait Evidence (GET-Evidence) system. This tool automatically processes genomes and prioritizes both published and novel variants for interpretation. In the process of reviewing the presumed healthy PGP-10 genomes, we find numerous literature references implying serious disease. Although it is sometimes impossible to rule out a late-onset effect, stringent evidence requirements can address the high rate of incidental findings. To that end we develop a peer production system for recording and organizing variant evaluations according to standard evidence guidelines, creating a public forum for reaching consensus on interpretation of clinically relevant variants. Genome analysis becomes a two-step process: using a prioritized list to record variant evaluations, then automatically sorting reviewed variants using these annotations. Genome data, health and trait information, participant samples, and variant interpretations are all shared in the public domain—we invite others to review our results using our participant samples and contribute to our interpretations. We offer our public resource and methods to further personalized medical research.

Background Increasing numbers of healthy individuals are undergoing predispositional personal genome sequencing. Here we describe the design and early outcomes of the PeopleSeq Consortium, a multi-cohort collaboration of predispositional genome sequencing projects, which is examining the medical, behavioral, and economic outcomes of returning genomic sequencing information to healthy individuals. Methods Apparently healthy adults who participated in four of the sequencing projects in the Consortium were included. Web-based surveys were administered before and after genomic results disclosure, or in some cases only after results disclosure. Surveys inquired about sociodemographic characteristics, motivations and concerns, behavioral and medical responses to sequencing results, and perceived utility. Results Among 1395 eligible individuals, 658 enrolled in the Consortium when contacted and 543 have completed a survey after receiving their genomic results thus far (mean age 53.0 years, 61.4% male, 91.7% white, 95.5% college graduates). Most participants (98.1%) were motivated to undergo sequencing because of curiosity about their genetic make-up. The most commonly reported concerns prior to pursuing sequencing included how well the results would predict future risk (59.2%) and the complexity of genetic variant interpretation (56.8%), while 47.8% of participants were concerned about the privacy of their genetic information. Half of participants reported discussing their genomic results with a healthcare provider during a median of 8.0 months after receiving the results; 13.5% reported making an additional appointment with a healthcare provider specifically because of their results. Few participants (< 10%) reported making changes to their diet, exercise habits, or insurance coverage because of their results. Many participants (39.5%) reported learning something new to improve their health that they did not know before. Reporting regret or harm from the decision to undergo sequencing was rare (< 3.0%). Conclusions Healthy individuals who underwent predispositional sequencing expressed some concern around privacy prior to pursuing sequencing, but were enthusiastic about their experience and not distressed by their results. While reporting value in their health-related results, few participants reported making medical or lifestyle changes. Electronic supplementary material The online version of this article (10.1186/s13073-019-0619-9) contains supplementary material, which is available to authorized users.

BackgroundSince its initiation in 2005, the Harvard Personal Genome Project has enrolled thousands of volunteers interested in publicly sharing their genome, health and trait data. Because these data are highly identifiable, we use an ‘open consent’ framework that purposefully excludes promises about privacy and requires participants to demonstrate comprehension prior to enrollment.DiscussionOur model of non-anonymous, public genomes has led us to a highly participatory model of researcher-participant communication and interaction. The participants, who are highly committed volunteers, self-pursue and donate research-relevant datasets, and are actively engaged in conversations with both our staff and other Personal Genome Project participants. We have quantitatively assessed these communications and donations, and report our experiences with returning research-grade whole genome data to participants. We also observe some of the community growth and discussion that has occurred related to our project.SummaryWe find that public non-anonymous data is valuable and leads to a participatory research model, which we encourage others to consider. The implementation of this model is greatly facilitated by web-based tools and methods and participant education. Project results are long-term proactive participant involvement and the growth of a community that benefits both researchers and participants.

Background Many aspects of our lives are now digitized and connected to the internet. As a result, individuals are now creating and collecting more personal data than ever before. This offers an unprecedented chance for human-participant research ranging from the social sciences to precision medicine. With this potential wealth of data comes practical problems (e.g., how to merge data streams from various sources), as well as ethical problems (e.g., how best to balance risks and benefits when enabling personal data sharing by individuals). Results To begin to address these problems in real time, we present Open Humans, a community-based platform that enables personal data collections across data streams, giving individuals more personal data access and control of sharing authorizations, and enabling academic research as well as patient-led projects. We showcase data streams that Open Humans combines (e.g., personal genetic data, wearable activity monitors, GPS location records, and continuous glucose monitor data), along with use cases of how the data facilitate various projects. Conclusions Open Humans highlights how a community-centric ecosystem can be used to aggregate personal data from various sources, as well as how these data can be used by academic and citizen scientists through practical, iterative approaches to sharing that strive to balance considerations with participant autonomy, inclusion, and privacy.

BackgroundIn recent years, people who sought direct-to-consumer genetic testing services have been increasingly confronted with an unprecedented amount of personal genomic information, which influences their decisions, emotional state, and well-being. However, these users of direct-to-consumer genetic services, who vary in their education and interests, frequently have little relevant experience or tools for understanding, reasoning about, and interacting with their personal genomic data. Online interactive techniques can play a central role in making personal genomic data useful for these users.ObjectiveWe sought to (1) identify the needs of diverse users as they make sense of their personal genomic data, (2) consequently develop effective interactive visualizations of genomic trait data to address these users’ needs, and (3) evaluate the effectiveness of the developed visualizations in facilitating comprehension.MethodsThe first two user studies, conducted with 63 volunteers in the Personal Genome Project and with 36 personal genomic users who participated in a design workshop, respectively, employed surveys and interviews to identify the needs and expectations of diverse users. Building on the two initial studies, the third study was conducted with 730 Amazon Mechanical Turk users and employed a controlled experimental design to examine the effectiveness of different design interventions on user comprehension.ResultsThe first two studies identified searching, comparing, sharing, and organizing data as fundamental to users’ understanding of personal genomic data. The third study demonstrated that interactive and visual design interventions could improve the understandability of personal genomic reports for consumers. In particular, results showed that a new interactive bubble chart visualization designed for the study resulted in the highest comprehension scores, as well as the highest perceived comprehension scores. These scores were significantly higher than scores received using the industry standard tabular reports currently used for communicating personal genomic information.ConclusionsDrawing on multiple research methods and populations, the findings of the studies reported in this paper offer deep understanding of users’ needs and practices, and demonstrate that interactive online design interventions can improve the understandability of personal genomic reports for consumers. We discuss implications for designers and researchers.