GenomeAsia100K is a human genome project based at Nanyang Technological University in Singapore that aims to sequence one hundred thousand Asian genomes in an effort that addresses an ethnic bias towards Western populations in previous genomic research. GenomeAsia100K consists of a team of bioinformaticians, statisticians and population geneticists, and was initiated by the Nanyang Technological University in collaboration with industrial partners MedGenome (an Indian R&D company specializing in genomic data), the California Biotech company Genentech, and Macrogen, a genome sequencing company from Korea. The GenomeAsia100K project is amongst the most ambitious precision medicine projects to date but it is not clear how the project will challenge or reshape understandings of ethnic and racial differences in Asian populations. Ian McGonigle, a scientist and cultural anthropologist, sat down with geneticist Stephan C. Schuster, the scientific chairman of GenomeAsia100K, to discuss the project and the implications of genomics for social identity in the 21st century.

Beckwith-Wiedemann syndrome (BWS) and Silver-Russell syndrome (SRS) are two imprinting disorders associated with opposite molecular alterations in the 11p15.5 imprinting centres. Their clinical diagnosis is confirmed by molecular testing in 50–70% of patients. The authors from different reference centres for BWS and SRS have identified single patients with unexpected and even contradictory molecular findings in respect to the clinical diagnosis. These patients clinically do not fit the characteristic phenotypes of SRS or BWS, but illustrate their clinical heterogeneity. Thus, comprehensive molecular testing is essential for accurate diagnosis and appropriate management, to avoid premature clinical diagnosis and anxiety for the families.

Noonan syndrome and related disorders are a group of clinically and genetically heterogeneous conditions caused by mutations in genes of the RAS/MAPK pathway. Noonan syndrome causes multiple congenital anomalies, which are frequently accompanied by hypertrophic cardiomyopathy (HCM). We report here a Tunisian patient with a severe phenotype of Noonan syndrome including neonatal HCM, facial dysmorphism, severe failure to thrive, cutaneous abnormalities, pectus excavatum and severe stunted growth, who died in her eighth month of life. Using whole exome sequencing, we identified a de novo mutation in exon 7 of the RAF1 gene: c.776C > A (p.Ser259Tyr). This mutation affects a highly conserved serine residue, a main mediator of Raf-1 inhibition via phosphorylation. To our knowledge the c.776C > A mutation has been previously reported in only one case with prenatally diagnosed Noonan syndrome. Our study further supports the striking correlation of RAF1 mutations with HCM and highlights the clinical severity of Noonan syndrome associated with a RAF1 p.Ser259Tyr mutation.

Compound heterozygotes occur when different variants at the same locus on both maternal and paternal chromosomes produce a recessive trait. Here we present the tool VarCount for the quantification of variants at the individual level. We used VarCount to characterize compound heterozygous coding variants in patients with epileptic encephalopathy and in the 1000 Genomes Project participants. The Epi4k data contains variants identified by whole exome sequencing in patients with either Lennox-Gastaut Syndrome (LGS) or infantile spasms (IS), as well as their parents. We queried the Epi4k dataset (264 trios) and the phased 1000 Genomes Project data (2504 participants) for recessive variants. To assess enrichment, transcript counts were compared between the Epi4k and 1000 Genomes Project participants using minor allele frequency (MAF) cutoffs of 0.5 and 1.0%, and including all ancestries or only probands of European ancestry. In the Epi4k participants, we found enrichment for rare, compound heterozygous variants in six genes, including three involved in neuronal growth and development – PRTG (p = 0.00086, 1% MAF, combined ancestries), TNC (p = 0.022, 1% MAF, combined ancestries) and MACF1 (p = 0.0245, 0.5% MAF, EU ancestry). Due to the total number of transcripts considered in these analyses, the enrichment detected was not significant after correction for multiple testing and higher powered or prospective studies are necessary to validate the candidacy of these genes. However, PRTG, TNC and MACF1 are potential novel recessive epilepsy genes and our results highlight that compound heterozygous variants should be considered in sporadic epilepsy.

Artificial intelligence (AI) is one of the most significant fields of development in the current digital age. Rapid advancements have raised speculation as to its potential benefits in a wide range of fields, with healthcare often at the forefront. However, amidst this optimism, apprehension and opposition continue to strongly persist. Oft-cited concerns include the threat of unemployment, harm to the doctor–patient relationship and questions of safety and accuracy. In this article, we review both the current and future medical applications of AI within the sub-speciality of cancer genomics.

The emerging paradigm in contemporary healthcare, precision medicine, is widely seen as a revolutionary approach to both clinical treatment and overall health promotion. Precision models are making use of the most up-to-date technological advancements – such as genomics and ‘big data’ processing – in an effort to tailor healthcare to each individual. Yet the list of hurdles to successful implementation of precision medicine is no secret. Among the challenges, it was recently suggested in this journal that we must change the ‘mindset’ of patients, practitioners and the wider public (McGonigle, 2016). And while precision medicine indeed demands a significant shift, we must not understate the extent of the overhaul required. In particular, I argue, against McGonigle's suggestion, that the ethical challenges regarding participant contributions cannot be tackled by relying upon existing models of incentivized blood banking or organ donation. Instead, the success of precision medicine requires a wholescale change in mindset.

In response to a recent commentary (Tigard, in press) on my previous article, ‘The Collective Nature of Personalized Medicine’ (McGonigle, 2016), herein I discuss collective responsibilities and rights in relation to the ethics of genomic data and personalized medicine. I respond to and elaborate on some of the issues Tigard raises and I draw on the anthropological concept of ‘dividuality’ to emphasize the precisely shared nature of genomic data in order to illuminate the ethical complexity surrounding their protection. Overall, I argue that genomic data, by virtue of their distributed and shared nature, necessitate novel approaches for bioethical assessment.

In recent years, there has been an increasing interest in detecting disease-related rare variants in sequencing studies. Numerous studies have shown that common variants can only explain a small proportion of the phenotypic variance for complex diseases. More and more evidence suggests that some of this missing heritability can be explained by rare variants. Considering the importance of rare variants, researchers have proposed a considerable number of methods for identifying the rare variants associated with complex diseases. Extensive research has been carried out on testing the association between rare variants and dichotomous, continuous or ordinal traits. So far, however, there has been little discussion about the case in which both genotypes and phenotypes are ordinal variables. This paper introduces a method based on the γ-statistic, called OV-RV, for examining disease-related rare variants when both genotypes and phenotypes are ordinal. At present, little is known about the asymptotic distribution of the γ-statistic when conducting association analyses for rare variants. One advantage of OV-RV is that it provides a robust estimation of the distribution of the γ-statistic by employing the permutation approach proposed by Fisher. We also perform extensive simulations to investigate the numerical performance of OV-RV under various model settings. The simulation results reveal that OV-RV is valid and efficient; namely, it controls the type I error approximately at the pre-specified significance level and achieves greater power at the same significance level. We also apply OV-RV for rare variant association studies of diastolic blood pressure.

Regulated transport through the secretory pathway is essential for embryonic development and homeostasis. Disruptions in this process impact cell fate, differentiation and survival, often resulting in abnormalities in morphogenesis and in disease. Several congenital malformations are caused by mutations in genes coding for proteins that regulate cargo protein transport in the secretory pathway. The severity of mutant phenotypes and the unclear aetiology of transport protein-associated pathologies have motivated research on the regulation and mechanisms through which these proteins contribute to morphogenesis. This review focuses on the role of the p24/transmembrane emp24 domain (TMED) family of cargo receptors in development and disease.