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Matthew Hurles and colleagues sequence the genomes of three multi-sibling families and investigate the rates and spectra of germline mutation. Their analyses suggest that the mutation rate per cell division is higher during early embryogenesis than in post-pubertal spermatogenesis. Germline mutations are a driving force behind genome evolution and genetic disease. We investigated genome-wide mutation rates and spectra in multi-sibling families. The mutation rate increased with paternal age in all families, but the number of additional mutations per year differed by more than twofold between families. Meta-analysis of 6,570 mutations showed that germline methylation influences mutation rates. In contrast to somatic mutations, we found remarkable consistency in germline mutation spectra between the sexes and at different paternal ages. In parental germ line, 3.8% of mutations were mosaic, resulting in 1.3% of mutations being shared by siblings. The number of these shared mutations varied significantly between families. Our data suggest that the mutation rate per cell division is higher during both early embryogenesis and differentiation of primordial germ cells but is reduced substantially during post-pubertal spermatogenesis. These findings have important consequences for the recurrence risks of disorders caused by de novo mutations.

Whole genome sequencing (WGS) studies have estimated the human germline mutation rate per basepair per generation (~1.2 × 10 −8 ) to be higher than in mice (3.5–5.4 × 10 −9 ). In humans, most germline mutations are paternal in origin and numbers of mutations per offspring increase with paternal and maternal age. Here we estimate germline mutation rates and spectra in six multi-sibling mouse pedigrees and compare to three multi-sibling human pedigrees. In both species we observe a paternal mutation bias, a parental age effect, and a highly mutagenic first cell division contributing to the embryo. We also observe differences between species in mutation spectra, in mutation rates per cell division, and in the parental bias of mutations in early embryogenesis. These differences between species likely result from both species-specific differences in cellular genealogies of the germline, as well as biological differences within the same stage of embryogenesis or gametogenesis. Estimates of mutation rates differ between species. Here, Lindsay et al. perform side-by-side analyses of germline mutation rates using multi-sibling mouse and human pedigrees and find different mutation rates between species, also stratified by sex and temporal stage of mutation acquisition.

Haploinsufficiency, wherein a single functional copy of a gene is insufficient to maintain normal function, is a major cause of dominant disease. Human disease studies have identified several hundred haploinsufficient (HI) genes. We have compiled a map of 1,079 haplosufficient (HS) genes by systematic identification of genes unambiguously and repeatedly compromised by copy number variation among 8,458 apparently healthy individuals and contrasted the genomic, evolutionary, functional, and network properties between these HS genes and known HI genes. We found that HI genes are typically longer and have more conserved coding sequences and promoters than HS genes. HI genes exhibit higher levels of expression during early development and greater tissue specificity. Moreover, within a probabilistic human functional interaction network HI genes have more interaction partners and greater network proximity to other known HI genes. We built a predictive model on the basis of these differences and annotated 12,443 genes with their predicted probability of being haploinsufficient. We validated these predictions of haploinsufficiency by demonstrating that genes with a high predicted probability of exhibiting haploinsufficiency are enriched among genes implicated in human dominant diseases and among genes causing abnormal phenotypes in heterozygous knockout mice. We have transformed these gene-based haploinsufficiency predictions into haploinsufficiency scores for genic deletions, which we demonstrate to better discriminate between pathogenic and benign deletions than consideration of the deletion size or numbers of genes deleted. These robust predictions of haploinsufficiency support clinical interpretation of novel loss-of-function variants and prioritization of variants and genes for follow-up studies.

There are thousands of rare human disorders that are caused by single deleterious, protein-coding genetic variants 1 . However, patients with the same genetic defect can have different clinical presentations 2 – 4 , and some individuals who carry known disease-causing variants can appear unaffected 5 . Here, to understand what explains these differences, we study a cohort of 6,987 children assessed by clinical geneticists to have severe neurodevelopmental disorders such as global developmental delay and autism, often in combination with abnormalities of other organ systems. Although the genetic causes of these neurodevelopmental disorders are expected to be almost entirely monogenic, we show that 7.7% of variance in risk is attributable to inherited common genetic variation. We replicated this genome-wide common variant burden by showing, in an independent sample of 728 trios (comprising a child plus both parents) from the same cohort, that this burden is over-transmitted from parents to children with neurodevelopmental disorders. Our common-variant signal is significantly positively correlated with genetic predisposition to lower educational attainment, decreased intelligence and risk of schizophrenia. We found that common-variant risk was not significantly different between individuals with and without a known protein-coding diagnostic variant, which suggests that common-variant risk affects patients both with and without a monogenic diagnosis. In addition, previously published common-variant scores for autism, height, birth weight and intracranial volume were all correlated with these traits within our cohort, which suggests that phenotypic expression in individuals with monogenic disorders is affected by the same variants as in the general population. Our results demonstrate that common genetic variation affects both overall risk and clinical presentation in neurodevelopmental disorders that are typically considered to be monogenic. A genome-wide association study of approximately 7,000 patients with neurodevelopmental disorders demonstrates that overall risk and clinical presentation in putative monogenic disorders is also influenced by common genetic variants present in the general population.

We previously estimated that 42% of patients with severe developmental disorders carry pathogenic de novo mutations in coding sequences. The role of de novo mutations in regulatory elements affecting genes associated with developmental disorders, or other genes, has been essentially unexplored. We identified de novo mutations in three classes of putative regulatory elements in almost 8,000 patients with developmental disorders. Here we show that de novo mutations in highly evolutionarily conserved fetal brain-active elements are significantly and specifically enriched in neurodevelopmental disorders. We identified a significant twofold enrichment of recurrently mutated elements. We estimate that, genome-wide, 1–3% of patients without a diagnostic coding variant carry pathogenic de novo mutations in fetal brain-active regulatory elements and that only 0.15% of all possible mutations within highly conserved fetal brain-active elements cause neurodevelopmental disorders with a dominant mechanism. Our findings represent a robust estimate of the contribution of de novo mutations in regulatory elements to this genetically heterogeneous set of disorders, and emphasize the importance of combining functional and evolutionary evidence to identify regulatory causes of genetic disorders. Analysis of rare de novo mutations in gene regulatory elements suggests that 1–3% of patients with neurodevelopmental disorders carry such mutations in elements that are active in the fetal brain. Regulatory mutations in developmental disorders Matthew Hurles and colleagues, as part of the Deciphering Developmental Disorders (DDD) project, examine the contribution of rare de novo mutations (DNMs) in regulatory elements—sections of DNA that regulate the expression of genes—to developmental disorders. The authors analysed targeted sequencing data for three classes of potential regulatory elements in 7,930 individuals with a severe, undiagnosed developmental disorder. They find an enrichment of DNMs in highly evolutionarily conserved elements that are active in the fetal brain. The authors previously estimated that 42% of patients with severe developmental disorders carry pathogenic DNMs in coding sequences. They now estimate that 1%–3% of the remaining patients carry pathogenic DNMs in fetal brain-active regulatory elements.

Human genome sequencing has transformed our understanding of genomic variation and its relevance to health and disease, and is now starting to enter clinical practice for the diagnosis of rare diseases. The question of whether and how some categories of genomic findings should be shared with individual research participants is currently a topic of international debate, and development of robust analytical workflows to identify and communicate clinically relevant variants is paramount. The Deciphering Developmental Disorders (DDD) study has developed a UK-wide patient recruitment network involving over 180 clinicians across all 24 regional genetics services, and has performed genome-wide microarray and whole exome sequencing on children with undiagnosed developmental disorders and their parents. After data analysis, pertinent genomic variants were returned to individual research participants via their local clinical genetics team. Around 80 000 genomic variants were identified from exome sequencing and microarray analysis in each individual, of which on average 400 were rare and predicted to be protein altering. By focusing only on de novo and segregating variants in known developmental disorder genes, we achieved a diagnostic yield of 27% among 1133 previously investigated yet undiagnosed children with developmental disorders, whilst minimising incidental findings. In families with developmentally normal parents, whole exome sequencing of the child and both parents resulted in a 10-fold reduction in the number of potential causal variants that needed clinical evaluation compared to sequencing only the child. Most diagnostic variants identified in known genes were novel and not present in current databases of known disease variation. Implementation of a robust translational genomics workflow is achievable within a large-scale rare disease research study to allow feedback of potentially diagnostic findings to clinicians and research participants. Systematic recording of relevant clinical data, curation of a gene–phenotype knowledge base, and development of clinical decision support software are needed in addition to automated exclusion of almost all variants, which is crucial for scalable prioritisation and review of possible diagnostic variants. However, the resource requirements of development and maintenance of a clinical reporting system within a research setting are substantial. Health Innovation Challenge Fund, a parallel funding partnership between the Wellcome Trust and the UK Department of Health.

[...]while selective interactions and functional overlap between duplicates declines relatively slowly over evolutionary time, the potential for recombinatorial interactions between paralogues is relatively short-lived. Extensive functional studies targeted at duplicated genes are required if we are to more fully understand the range of evolutionary outcomes. [...]collaborations between the proteomics and evolutionary genetics communities would facilitate investigation of the potential role of gene duplication during the evolution of the protein-protein and cell-cell interactions that are fundamental to the biology of multicellular organisms.

Matthew Hurles and colleagues report exome sequencing of 1,891 individuals with syndromic or nonsyndromic congenital heart defects (CHD). They found that nonsyndromic CHD patients were enriched for protein-truncating variants in CHD-associated genes inherited from unaffected parents and identified three new syndromic CHD disorders caused by de novo mutations. Congenital heart defects (CHDs) have a neonatal incidence of 0.8–1% (refs. 1 , 2 ). Despite abundant examples of monogenic CHD in humans and mice, CHD has a low absolute sibling recurrence risk (∼2.7%) 3 , suggesting a considerable role for de novo mutations (DNMs) and/or incomplete penetrance 4 , 5 . De novo protein-truncating variants (PTVs) have been shown to be enriched among the 10% of 'syndromic' patients with extra-cardiac manifestations 6 , 7 . We exome sequenced 1,891 probands, including both syndromic CHD (S-CHD, n = 610) and nonsyndromic CHD (NS-CHD, n = 1,281). In S-CHD, we confirmed a significant enrichment of de novo PTVs but not inherited PTVs in known CHD-associated genes, consistent with recent findings 8 . Conversely, in NS-CHD we observed significant enrichment of PTVs inherited from unaffected parents in CHD-associated genes. We identified three genome-wide significant S-CHD disorders caused by DNMs in CHD4 , CDK13 and PRKD1 . Our study finds evidence for distinct genetic architectures underlying the low sibling recurrence risk in S-CHD and NS-CHD.

The complexity of the human brain has made it difficult to study many brain disorders in model organisms, highlighting the need for an in vitro model of human brain development. Here we have developed a human pluripotent stem cell-derived three-dimensional organoid culture system, termed cerebral organoids, that develop various discrete, although interdependent, brain regions. These include a cerebral cortex containing progenitor populations that organize and produce mature cortical neuron subtypes. Furthermore, cerebral organoids are shown to recapitulate features of human cortical development, namely characteristic progenitor zone organization with abundant outer radial glial stem cells. Finally, we use RNA interference and patient-specific induced pluripotent stem cells to model microcephaly, a disorder that has been difficult to recapitulate in mice. We demonstrate premature neuronal differentiation in patient organoids, a defect that could help to explain the disease phenotype. Together, these data show that three-dimensional organoids can recapitulate development and disease even in this most complex human tissue. Here the authors present a human pluripotent stem cell-derived three-dimensional organoid culture system that is able to recapitulate several aspects of human brain development in addition to modelling the brain disorder microcephaly, which has been difficult to achieve using mouse models. A model for the human brain Genetically altered mice are used widely to model human diseases, but as the organization of the human brain is so much more complicated than that of a rodent, brain development diseases have not been tackled. Juergen Knoblich and colleagues have developed an alternative model, a three-dimensional organoid culture system, using human pluripotent stem cells, that recapitulates several aspects of human brain development. The system mimics the temporal development of neuronal subtypes and the organization of the tissue into layers. In proof-of-principle experiments the authors produce a microcephaly model using patient-derived induced pluripotent stem cells and describe defects in neuronal differentiation not previously observed in rodent models.

A primary goal of human genetics is to identify DNA sequence variants that influence biomedical traits, particularly those related to the onset and progression of human disease. Over the past 25 years, progress in realizing this objective has been transformed by advances in technology, foundational genomic resources and analytical tools, and by access to vast amounts of genotype and phenotype data. Genetic discoveries have substantially improved our understanding of the mechanisms responsible for many rare and common diseases and driven development of novel preventative and therapeutic strategies. Medical innovation will increasingly focus on delivering care tailored to individual patterns of genetic predisposition. This Review describes progress in the study of human genetics, in which rapid advances in technology, foundational genomic resources and analytical tools have contributed to the understanding of the mechanisms responsible for many rare and common diseases and to preventative and therapeutic strategies for many of these conditions.