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Mutations in X-linked methyl-CpG-binding protein 2 ( MECP2) cause Rett syndrome (RTT). To identify functional pathways that could inform therapeutic entry points, we carried out a genetic screen for secondary mutations that improved phenotypes in Mecp2 /Y mice after mutagenesis with N -ethyl- N -nitrosourea (ENU). Here, we report the isolation of 106 founder animals that show suppression of Mecp2 -null traits from screening 3177 Mecp2 /Y genomes. Whole-exome sequencing, genetic crosses, and association analysis identified 22 candidate genes. Additional lesions in these candidate genes or pathway components associate variant alleles with phenotypic improvement in 30 lines. A network analysis shows that 63% of the genes cluster into the functional categories of transcriptional repression, chromatin modification, or DNA repair, delineating a pathway relationship with MECP2. Many mutations lie in genes that modulate synaptic signaling or lipid homeostasis. Mutations in genes that function in the DNA damage response (DDR) also improve phenotypes in Mecp2/Y mice. Association analysis was successful in resolving combinatorial effects of multiple loci. One line, which carries a suppressor mutation in a gene required for cholesterol synthesis, Sqle , carries a second mutation in retinoblastoma binding protein 8, endonuclease ( Rbbp8 , also known as CtIP ), which regulates a DDR choice in double-stranded break (DSB) repair. Cells from Mecp2 /Y mice have increased DSBs, so this finding suggests that the balance between homology-directed repair and nonhomologous end joining is important for neuronal cells. In this and other lines, two suppressor mutations confer greater improvement than one alone, suggesting that combination therapies could be effective in RTT., (© 2020 Enikanolaiye et al.; Published by Cold Spring Harbor Laboratory Press.)

Variants of uncertain significance fundamentally limit the clinical utility of genetic information. The challenge they pose is epitomized by BRCA1, a tumour suppressor gene in which germline loss-of-function variants predispose women to breast and ovarian cancer. Although BRCA1 has been sequenced in millions of women, the risk associated with most newly observed variants cannot be definitively assigned. Here we use saturation genome editing to assay 96.5% of all possible single-nucleotide variants (SNVs) in 13 exons that encode functionally critical domains of BRCA1. Functional effects for nearly 4,000 SNVs are bimodally distributed and almost perfectly concordant with established assessments of pathogenicity. Over 400 non-functional missense SNVs are identified, as well as around 300 SNVs that disrupt expression. We predict that these results will be immediately useful for the clinical interpretation of BRCA1 variants, and that this approach can be extended to overcome the challenge of variants of uncertain significance in additional clinically actionable genes.

Marfan syndrome (MFS) due to mutations in FBN1 is a known cause of thoracic aortic aneurysms and acute aortic dissections (TAAD) associated with pleiotropic manifestations. Genetic predisposition to TAAD can also be inherited in families in the absence of syndromic features, termed familial TAAD (FTAAD), and several causative genes have been identified to date. FBN1 mutations can also be identified in FTAAD families, but the frequency of these mutations has not been established. We performed exome sequencing of 183 FTAAD families and identified pathogenic FBN1 variants in five (2.7%) of these families. We also identified eight additional FBN1 rare variants that could not be unequivocally classified as disease-causing in six families. FBN1 sequencing should be considered in individuals with FTAAD even without significant systemic features of MFS., (© 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Next-generation sequencing (NGS) of exomes and genomes has accelerated the identification of genes involved in Mendelian phenotypes. However, many NGS studies fall short of identifying causal variants, with estimates for success rates as low as 25% for uncovering the pathological variant underlying disease etiology. An important reason for such failures is familial locus heterogeneity, where within a single pedigree causal variants in two or more genes underlie Mendelian trait etiology. As examples of intra- and inter-sibship familial locus heterogeneity, we present 10 consanguineous Pakistani families segregating hearing impairment due to homozygous variants in two different hearing impairment genes and a European-American pedigree in which hearing impairment is caused by four variants in three different genes. We have identified 41 additional pedigrees with syndromic and nonsyndromic hearing impairment for which a single previously reported hearing impairment gene has been identified but only segregates with the phenotype in a subset of affected pedigree members. We estimate that locus heterogeneity occurs in 15.3% (95% confidence interval: 11.9%, 19.9%) of the families in our collection. We demonstrate novel approaches to apply linkage analysis and homozygosity mapping (for autosomal recessive consanguineous pedigrees), which can be used to detect locus heterogeneity using either NGS or SNP array data. Results from linkage analysis and homozygosity mapping can also be used to group sibships or individuals most likely to be segregating the same causal variants and thereby increase the success rate of gene identification.

A duplication variant within the middle ear-specific gene A2ML1 cosegregates with otitis media in an indigenous Filipino pedigree (LOD score = 7.5 at reduced penetrance) and lies within a founder haplotype that is also shared by 3 otitis-prone European-American and Hispanic-American children but is absent in non-otitis-prone children and >62,000 next-generation sequences. We identified seven additional A2ML1 variants in six otitis-prone children. Collectively, our studies support a role for A2ML1 in the pathophysiology of otitis media.

A major challenge in human genetics is pinpointing which non-coding genetic variants affect gene expression and disease risk. A new study in this issue describes a broadly applicable approach for this task that explicitly models cell type-specific regulatory motifs and generates variant effect predictions that are more accurate and interpretable than those of alternative tools.

Autism spectrum disorder (ASD) has a strong but complex genetic component. Here we report on the resequencing of 64 candidate neurodevelopmental disorder risk genes in 5,979 individuals: 3,486 probands and 2,493 unaffected siblings. We find a strong burden of de novo point mutations for these genes and specifically implicate nine genes. These include CHD2 and SYNGAP1, genes previously reported in related disorders, and novel genes TRIP12 and PAX5. We also show that mutation carriers generally have lower IQs and enrichment for seizures. These data begin to distinguish genetically distinct subtypes of autism important for aetiological classification and future therapeutics.

Whole exome sequencing has proven to be a powerful tool for understanding the genetic architecture of human disease. Here we apply it to more than 2,500 simplex families, each having a child with an autistic spectrum disorder. By comparing affected to unaffected siblings, we show that 13% of de novo missense mutations and 43% of de novo likely gene-disrupting (LGD) mutations contribute to 12% and 9% of diagnoses, respectively. Including copy number variants, coding de novo mutations contribute to about 30% of all simplex and 45% of female diagnoses. Almost all LGD mutations occur opposite wild-type alleles. LGD targets in affected females significantly overlap the targets in males of lower intelligence quotient (IQ), but neither overlaps significantly with targets in males of higher IQ. We estimate that LGD mutation in about 400 genes can contribute to the joint class of affected females and males of lower IQ, with an overlapping and similar number of genes vulnerable to contributory missense mutation. LGD targets in the joint class overlap with published targets for intellectual disability and schizophrenia, and are enriched for chromatin modifiers, FMRP-associated genes and embryonically expressed genes. Most of the significance for the latter comes from affected females.

Copy number variants (CNVs) are associated with many neurocognitive disorders; however, these events are typically large, and the underlying causative genes are unclear. We created an expanded CNV morbidity map from 29,085 children with developmental delay in comparison to 19,584 healthy controls, identifying 70 significant CNVs. We resequenced 26 candidate genes in 4,716 additional cases with developmental delay or autism and 2,193 controls. An integrated analysis of CNV and single-nucleotide variant (SNV) data pinpointed 10 genes enriched for putative loss of function. Follow-up of a subset of affected individuals identified new clinical subtypes of pediatric disease and the genes responsible for disease-associated CNVs. These genetic changes include haploinsufficiency of SETBP1 associated with intellectual disability and loss of expressive language and truncations of ZMYND11 in individuals with autism, aggression and complex neuropsychiatric features. This combined CNV and SNV approach facilitates the rapid discovery of new syndromes and genes involved in neuropsychiatric disease despite extensive genetic heterogeneity.

Asthma is a complex genetic disease caused by a combination of genetic and environmental risk factors. We sought to test classes of genetic variants largely missed by genome-wide association studies (GWAS), including copy number variants (CNVs) and low-frequency variants, by performing whole-genome sequencing (WGS) on 16 individuals from asthma-enriched and asthma-depleted families. The samples were obtained from an extended 13-generation Hutterite pedigree with reduced genetic heterogeneity due to a small founding gene pool and reduced environmental heterogeneity as a result of a communal lifestyle. We sequenced each individual to an average depth of 13-fold, generated a comprehensive catalog of genetic variants, and tested the most severe mutations for association with asthma. We identified and validated 1960 CNVs, 19 nonsense or splice-site single nucleotide variants (SNVs), and 18 insertions or deletions that were out of frame. As follow-up, we performed targeted sequencing of 16 genes in 837 cases and 540 controls of Puerto Rican ancestry and found that controls carry a significantly higher burden of mutations in IL27RA (2.0% of controls; 0.23% of cases; nominal p = 0.004; Bonferroni p = 0.21). We also genotyped 593 CNVs in 1199 Hutterite individuals. We identified a nominally significant association (p = 0.03; Odds ratio (OR) = 3.13) between a 6 kbp deletion in an intron of NEDD4L and increased risk of asthma. We genotyped this deletion in an additional 4787 non-Hutterite individuals (nominal p = 0.056; OR = 1.69). NEDD4L is expressed in bronchial epithelial cells, and conditional knockout of this gene in the lung in mice leads to severe inflammation and mucus accumulation. Our study represents one of the early instances of applying WGS to complex disease with a large environmental component and demonstrates how WGS can identify risk variants, including CNVs and low-frequency variants, largely untested in GWAS.

The discovery of rare genetic variants is accelerating, and clear guidelines for distinguishing disease-causing sequence variants from the many potentially functional variants present in any human genome are urgently needed. Without rigorous standards we risk an acceleration of false-positive reports of causality, which would impede the translation of genomic research findings into the clinical diagnostic setting and hinder biological understanding of disease. Here we discuss the key challenges of assessing sequence variants in human disease, integrating both gene-level and variant-level support for causality. We propose guidelines for summarizing confidence in variant pathogenicity and highlight several areas that require further resource development.

Objective: To determine the genes underlying Dravet syndrome in patients who do not have an SCN1A mutation on routine testing., Methods: We performed whole-exome sequencing in 13 SCN1A-negative patients with Dravet syndrome and targeted resequencing in 67 additional patients to identify new genes for this disorder., Results: We detected disease-causing mutations in 2 novel genes for Dravet syndrome, with mutations in GABRA1 in 4 cases and STXBP1 in 3. Furthermore, we identified 3 patients with previously undetected SCN1A mutations, suggesting that SCN1A mutations occur in even more than the currently accepted ∼ 75% of cases., Conclusions: We show that GABRA1 and STXBP1 make a significant contribution to Dravet syndrome after SCN1A abnormalities have been excluded. Our results have important implications for diagnostic testing, clinical management, and genetic counseling of patients with this devastating disorder and their families.

Autism spectrum disorder (ASD) and intellectual disability (ID) are neurodevelopmental disorders with large genetic components, but identification of pathogenic genes has proceeded slowly because hundreds of loci are involved. New exome sequencing technology has identified novel rare variants and has found that sporadic cases of ASD/ID are enriched for disruptive de novo mutations. Targeted large-scale resequencing studies have confirmed the significance of specific loci, including chromodomain helicase DNA binding protein 8 (CHD8), sodium channel, voltage-gated, type II, alpha subunit (SCN2A), dual specificity tyrosine-phosphorylation-regulated kinase 1A (DYRK1A), and catenin (cadherin-associated protein), beta 1, 88 kDa (CTNNB1, beta-catenin). We review recent studies and suggest that they have led to a convergence on three functional pathways: (i) chromatin remodeling; (ii) wnt signaling during development; and (iii) synaptic function. These pathways and genes significantly expand the neurobiological targets for study, and suggest a path for future genetic and functional studies., (Copyright © 2013 Elsevier Ltd. All rights reserved.)

Genome and exome sequencing yield extensive catalogues of human genetic variation. However, pinpointing the few phenotypically causal variants among the many variants present in human genomes remains a major challenge, particularly for rare and complex traits wherein genetic information alone is often insufficient. Here, we review approaches to estimate the deleteriousness of single nucleotide variants (SNVs), which can be used to prioritize disease-causal variants. We describe recent advances in comparative and functional genomics that enable systematic annotation of both coding and non-coding variants. Application and optimization of these methods will be essential to find the genetic answers that sequencing promises to hide in plain sight.

Evidence for the etiology of autism spectrum disorders (ASDs) has consistently pointed to a strong genetic component complicated by substantial locus heterogeneity. We sequenced the exomes of 20 individuals with sporadic ASD (cases) and their parents, reasoning that these families would be enriched for de novo mutations of major effect. We identified 21 de novo mutations, 11 of which were protein altering. Protein-altering mutations were significantly enriched for changes at highly conserved residues. We identified potentially causative de novo events in 4 out of 20 probands, particularly among more severely affected individuals, in FOXP1, GRIN2B, SCN1A and LAMC3. In the FOXP1 mutation carrier, we also observed a rare inherited CNTNAP2 missense variant, and we provide functional support for a multi-hit model for disease risk. Our results show that trio-based exome sequencing is a powerful approach for identifying new candidate genes for ASDs and suggest that de novo mutations may contribute substantially to the genetic etiology of ASDs.

Genome-wide association studies suggest that common genetic variants explain only a modest fraction of heritable risk for common diseases, raising the question of whether rare variants account for a significant fraction of unexplained heritability. Although DNA sequencing costs have fallen markedly, they remain far from what is necessary for rare and novel variants to be routinely identified at a genome-wide scale in large cohorts. We have therefore sought to develop second-generation methods for targeted sequencing of all protein-coding regions ('exomes'), to reduce costs while enriching for discovery of highly penetrant variants. Here we report on the targeted capture and massively parallel sequencing of the exomes of 12 humans. These include eight HapMap individuals representing three populations, and four unrelated individuals with a rare dominantly inherited disorder, Freeman-Sheldon syndrome (FSS). We demonstrate the sensitive and specific identification of rare and common variants in over 300 megabases of coding sequence. Using FSS as a proof-of-concept, we show that candidate genes for Mendelian disorders can be identified by exome sequencing of a small number of unrelated, affected individuals. This strategy may be extendable to diseases with more complex genetics through larger sample sizes and appropriate weighting of non-synonymous variants by predicted functional impact.

We have established strong linkage evidence that supports mapping autosomal-dominant sensory/motor neuropathy with ataxia (SMNA) to chromosome 7q22-q32. SMNA is a rare neurological disorder whose phenotype encompasses both the central and the peripheral nervous system. In order to identify a gene responsible for SMNA, we have undertaken a comprehensive genomic evaluation of the region of linkage, including evaluation for repeat expansion and small deletions or duplications, capillary sequencing of candidate genes, and massively parallel sequencing of all coding exons. We excluded repeat expansion and small deletions or duplications as causative, and through microarray-based hybrid capture and massively parallel short-read sequencing, we identified a nonsynonymous variant in the human interferon-related developmental regulator gene 1 (IFRD1) as a disease-causing candidate. Sequence conservation, animal models, and protein structure evaluation support the involvement of IFRD1 in SMNA. Mutation analysis of IFRD1 in additional patients with similar phenotypes is needed for demonstration of causality and further evaluation of its importance in neurological diseases.