Systematic evaluation of genome sequencing for the diagnostic assessment of autism spectrum disorder and fetal structural anomalies.

Short-read genome sequencing (GS) holds the promise of becoming the primary diagnostic approach for the assessment of autism spectrum disorder (ASD) and fetal structural anomalies (FSAs). However, few studies have comprehensively evaluated its performance against current standard-of-care diagnostic tests: karyotype, chromosomal microarray (CMA), and exome sequencing (ES). To assess the clinical utility of GS, we compared its diagnostic yield against these three tests in 1,612 quartet families including an individual with ASD and in 295 prenatal families. Our GS analytic framework identified a diagnostic variant in 7.8% of ASD probands, almost 2-fold more than CMA (4.3%) and 3-fold more than ES (2.7%). However, when we systematically captured copy-number variants (CNVs) from the exome data, the diagnostic yield of ES (7.4%) was brought much closer to, but did not surpass, GS. Similarly, we estimated that GS could achieve an overall diagnostic yield of 46.1% in unselected FSAs, representing a 17.2% increased yield over karyotype, 14.1% over CMA, and 4.1% over ES with CNV calling or 36.1% increase without CNV discovery. Overall, GS provided an added diagnostic yield of 0.4% and 0.8% beyond the combination of all three standard-of-care tests in ASD and FSAs, respectively. This corresponded to nine GS unique diagnostic variants, including sequence variants in exons not captured by ES, structural variants (SVs) inaccessible to existing standard-of-care tests, and SVs where the resolution of GS changed variant classification. Overall, this large-scale evaluation demonstrated that GS significantly outperforms each individual standard-of-care test while also outperforming the combination of all three tests, thus warranting consideration as the first-tier diagnostic approach for the assessment of ASD and FSAs.

Expectations and blind spots for structural variation detection from long-read assemblies and short-read genome sequencing technologies.

Virtually all genome sequencing efforts in national biobanks, complex and Mendelian disease programs, and medical genetic initiatives are reliant upon short-read whole-genome sequencing (srWGS), which presents challenges for the detection of structural variants (SVs) relative to emerging long-read WGS (lrWGS) technologies. Given this ubiquity of srWGS in large-scale genomics initiatives, we sought to establish expectations for routine SV detection from this data type by comparison with lrWGS assembly, as well as to quantify the genomic properties and added value of SVs uniquely accessible to each technology. Analyses from the Human Genome Structural Variation Consortium (HGSVC) of three families captured ~11,000 SVs per genome from srWGS and ~25,000 SVs per genome from lrWGS assembly. Detection power and precision for SV discovery varied dramatically by genomic context and variant class: 9.7% of the current GRCh38 reference is defined by segmental duplication (SD) and simple repeat (SR), yet 91.4% of deletions that were specifically discovered by lrWGS localized to these regions. Across the remaining 90.3% of reference sequence, we observed extremely high (93.8%) concordance between technologies for deletions in these datasets. In contrast, lrWGS was superior for detection of insertions across all genomic contexts. Given that non-SD/SR sequences encompass 95.9% of currently annotated disease-associated exons, improved sensitivity from lrWGS to discover novel pathogenic deletions in these currently interpretable genomic regions is likely to be incremental. However, these analyses highlight the considerable added value of assembly-based lrWGS to create new catalogs of insertions and transposable elements, as well as disease-associated repeat expansions in genomic sequences that were previously recalcitrant to routine assessment.

De novo structural mutation rates and gamete-of-origin biases revealed through genome sequencing of 2,396 families.

Each human genome includes de novo mutations that arose during gametogenesis. While these germline mutations represent a fundamental source of new genetic diversity, they can also create deleterious alleles that impact fitness. Whereas the rate and patterns of point mutations in the human germline are now well understood, far less is known about the frequency and features that impact de novo structural variants (dnSVs). We report a family-based study of germline mutations among 9,599 human genomes from 33 multigenerational CEPH-Utah families and 2,384 families from the Simons Foundation Autism Research Initiative. We find that de novo structural mutations detected by alignment-based, short-read WGS occur at an overall rate of at least 0.160 events per genome in unaffected individuals, and we observe a significantly higher rate (0.206 per genome) in ASD-affected individuals. In both probands and unaffected samples, nearly 73% of de novo structural mutations arose in paternal gametes, and we predict most de novo structural mutations to be caused by mutational mechanisms that do not require sequence homology. After multiple testing correction, we did not observe a statistically significant correlation between parental age and the rate of de novo structural variation in offspring. These results highlight that a spectrum of mutational mechanisms contribute to germline structural mutations and that these mechanisms most likely have markedly different rates and selective pressures than those leading to point mutations.

Functional annotation of rare structural variation in the human brain.

Structural variants (SVs) contribute to many disorders, yet, functionally annotating them remains a major challenge. Here, we integrate SVs with RNA-sequencing from human post-mortem brains to quantify their dosage and regulatory effects. We show that genic and regulatory SVs exist at significantly lower frequencies than intergenic SVs. Functional impact of copy number variants (CNVs) stems from both the proportion of genic and regulatory content altered and loss-of-function intolerance of the gene. We train a linear model to predict expression effects of rare CNVs and use it to annotate regulatory disruption of CNVs from 14,891 independent genome-sequenced individuals. Pathogenic deletions implicated in neurodevelopmental disorders show significantly more extreme regulatory disruption scores and if rank ordered would be prioritized higher than using frequency or length alone. This work shows the deleteriousness of regulatory SVs, particularly those altering CTCF sites and provides a simple approach for functionally annotating the regulatory consequences of CNVs.

A structural variation reference for medical and population genetics.

Structural variants (SVs) rearrange large segments of DNA1 and can have profound consequences in evolution and human disease2,3. As national biobanks, disease-association studies, and clinical genetic testing have grown increasingly reliant on genome sequencing, population references such as the Genome Aggregation Database (gnomAD)4 have become integral in the interpretation of single-nucleotide variants (SNVs)5. However, there are no reference maps of SVs from high-coverage genome sequencing comparable to those for SNVs. Here we present a reference of sequence-resolved SVs constructed from 14,891 genomes across diverse global populations (54% non-European) in gnomAD. We discovered a rich and complex landscape of 433,371 SVs, from which we estimate that SVs are responsible for 25-29% of all rare protein-truncating events per genome. We found strong correlations between natural selection against damaging SNVs and rare SVs that disrupt or duplicate protein-coding sequence, which suggests that genes that are highly intolerant to loss-of-function are also sensitive to increased dosage6. We also uncovered modest selection against noncoding SVs in cis-regulatory elements, although selection against protein-truncating SVs was stronger than all noncoding effects. Finally, we identified very large (over one megabase), rare SVs in 3.9% of samples, and estimate that 0.13% of individuals may carry an SV that meets the existing criteria for clinically important incidental findings7. This SV resource is freely distributed via the gnomAD browser8 and will have broad utility in population genetics, disease-association studies, and diagnostic screening.

A Balanced Translocation in Kallmann Syndrome Implicates a Long Noncoding RNA, RMST, as a GnRH Neuronal Regulator.

CONTEXT: Kallmann syndrome (KS) is a rare, genetically heterogeneous Mendelian disorder. Structural defects in KS patients have helped define the genetic architecture of gonadotropin-releasing hormone (GnRH) neuronal development in this condition. OBJECTIVE: Examine the functional role a novel structural defect affecting a long noncoding RNA (lncRNA), RMST, found in a KS patient. DESIGN: Whole genome sequencing, induced pluripotent stem cells and derived neural crest cells (NCC) from the KS patient were contrasted with controls. SETTING: The Harvard Reproductive Sciences Center, Massachusetts General Hospital Center for Genomic Medicine, and Singapore Genome Institute. PATIENT: A KS patient with a unique translocation, t(7;12)(q22;q24). INTERVENTIONS/MAIN OUTCOME MEASURE/RESULTS: A novel translocation was detected affecting the lncRNA, RMST, on chromosome 12 in the absence of any other KS mutations. Compared with controls, the patient's induced pluripotent stem cells and NCC provided functional information regarding RMST. Whereas RMST expression increased during NCC differentiation in controls, it was substantially reduced in the KS patient's NCC coincident with abrogated NCC morphological development and abnormal expression of several "downstream" genes essential for GnRH ontogeny (SOX2, PAX3, CHD7, TUBB3, and MKRN3). Additionally, an intronic single nucleotide polymorphism in RMST was significantly implicated in a genome-wide association study associated with age of menarche. CONCLUSIONS: A novel deletion in RMST implicates the loss of function of a lncRNA as a unique cause of KS and suggests it plays a critical role in the ontogeny of GnRH neurons and puberty.

Genome-wide de novo risk score implicates promoter variation in autism spectrum disorder.

Whole-genome sequencing (WGS) has facilitated the first genome-wide evaluations of the contribution of de novo noncoding mutations to complex disorders. Using WGS, we identified 255,106 de novo mutations among sample genomes from members of 1902 quartet families in which one child, but not a sibling or their parents, was affected by autism spectrum disorder (ASD). In contrast to coding mutations, no noncoding functional annotation category, analyzed in isolation, was significantly associated with ASD. Casting noncoding variation in the context of a de novo risk score across multiple annotation categories, however, did demonstrate association with mutations localized to promoter regions. We found that the strongest driver of this promoter signal emanates from evolutionarily conserved transcription factor binding sites distal to the transcription start site. These data suggest that de novo mutations in promoter regions, characterized by evolutionary and functional signatures, contribute to ASD.

Environmental governance in China: Interactions between the state and "nonstate actors".

In the West, limited government capacity to solve environmental problems has triggered the rise of a variety of "nonstate actors" to supplement government efforts or provide alternative mechanisms for addressing environmental issues. How does this development - along with our efforts to understand it - map onto environmental governance processes in China? China's efforts to address environmental issues reflect institutionalized governance processes that differ from parallel western processes in ways that have major consequences for domestic environmental governance practices and the governance of China "going abroad." China's governance processes blur the distinction between the state and other actors; the "shadow of the state" is a major factor in all efforts to address environmental issues. The space occupied by nonstate actors in western systems is occupied by shiye danwei ("public service units"), she hui tuanti ("social associations") and e-platforms, all of which have close links to the state. Meanwhile, international NGOs and multinational corporations are also significant players in China. As a result, the mechanisms of influence that produce effects in China differ in important ways from mechanisms familiar from the western experience. This conclusion has far-reaching implications for those seeking to address global environmental concerns, given the importance of China's growing economy and burgeoning network of trade relationships.

An analytical framework for whole-genome sequence association studies and its implications for autism spectrum disorder.

Genomic association studies of common or rare protein-coding variation have established robust statistical approaches to account for multiple testing. Here we present a comparable framework to evaluate rare and de novo noncoding single-nucleotide variants, insertion/deletions, and all classes of structural variation from whole-genome sequencing (WGS). Integrating genomic annotations at the level of nucleotides, genes, and regulatory regions, we define 51,801 annotation categories. Analyses of 519 autism spectrum disorder families did not identify association with any categories after correction for 4,123 effective tests. Without appropriate correction, biologically plausible associations are observed in both cases and controls. Despite excluding previously identified gene-disrupting mutations, coding regions still exhibited the strongest associations. Thus, in autism, the contribution of de novo noncoding variation is probably modest in comparison to that of de novo coding variants. Robust results from future WGS studies will require large cohorts and comprehensive analytical strategies that consider the substantial multiple-testing burden.

Potential involvement of the interleukin-18 pathway in schizophrenia.

OBJECTIVE: Accumulating evidence implicates inflammatory cytokines in the development of psychiatric disorders, including schizophrenia (SZ). IL-18 is one of cytokines that plays a crucial role in immune response and neurodevelopment. We aimed to investigate potential genetic alterations of the cytokine system underpinning SZ. METHODS: We tested the association of genetic variants within the cytokine-cytokine receptor interaction (CCRI) pathway with SZ, using GWAS-derived data involving 768 adult SZ patients and 1348 controls, and replicated the association of IL18R1 rs1035130 with SZ in an independent sample of 1957 adult patients and 1509 controls. We compared expression levels of IL18, IL18R1 and IL18RAP in peripheral blood of a cohort of adolescent participants (<18 years), including 14 early-onset SZ patients and 13 healthy controls. Furthermore, we carried out a cis-eQTL (expression Quantitative Trait Loci) and a cis-mQTL (Methylation Quantitative Trait Loci) analysis for IL18R1 rs1035130. RESULTS: In the discovery stage, we detected association signals within two IL18 pathway genes, IL18R1 and IL18RAP, with the most significant marker being IL18R1 rs1035130 (P = 1.84E-7, OR = 0.70). In the validation stage, we found rs1035130 was associated with SZ (P = 0.028, OR = 0.89). Expressions of IL18 and IL18R1 were altered in blood of SZ patients compared with 13 controls. Furthermore, cis-QTL analyses indicated that rs1035130 was associated with an eQTL and 5 mQTLs. CONCLUSION: Our findings suggest the alteration of IL18 pathway may contribute to the psychopathology of SZ.

Family-based tests applied to extended pedigrees identify rare variants related to hypertension.

The application of family-based tests to whole-genome sequenced data provides a new window on the role of rare variant alleles in the etiology of disease. By applying family-based tests to these data, we can now identify rare variants associated with disease. Approaches for common variants, by contrast, require large sample sizes for power, and are powerless when faced with rare variants. When we tested Yip et al's 2011 family-based association tests for rare variants on pedigrees from the Genetic Analysis Workshop 18, we found that weighted collapsing methods generally have more power than unweighted methods, but are more prone to type I errors. We then evaluated a sliding window modification of the weighted family-based association tests for rare variants method. Although this modification inflates the rate of false positives, it significantly increases the power of family-based association tests for rare variants to identify causal rare variants.

New insights into the genetic mechanism of IQ in autism spectrum disorders.

Autism spectrum disorders (ASD) comprise a number of underlying sub-types with various symptoms and presumably different genetic causes. One important difference between these sub-phenotypes is IQ. Some forms of ASD such as Asperger's have relatively intact intelligence while the majority does not. In this study, we explored the role of genetic factors that might account for this difference. Using a case-control study based on IQ status in 1657 ASD probands, we analyzed both common and rare variants provided by the Autism Genome Project (AGP) consortium via dbGaP (database of Genotypes and Phenotypes). We identified a set of genes, among them HLA-DRB1 and KIAA0319L, which are strongly associated with IQ within a population of ASD patients.