Mutation-specific pathophysiological mechanisms define different neurodevelopmental disorders associated with SATB1 dysfunction.

Whereas large-scale statistical analyses can robustly identify disease-gene relationships, they do not accurately capture genotype-phenotype correlations or disease mechanisms. We use multiple lines of independent evidence to show that different variant types in a single gene, SATB1, cause clinically overlapping but distinct neurodevelopmental disorders. Clinical evaluation of 42 individuals carrying SATB1 variants identified overt genotype-phenotype relationships, associated with different pathophysiological mechanisms, established by functional assays. Missense variants in the CUT1 and CUT2 DNA-binding domains result in stronger chromatin binding, increased transcriptional repression, and a severe phenotype. In contrast, variants predicted to result in haploinsufficiency are associated with a milder clinical presentation. A similarly mild phenotype is observed for individuals with premature protein truncating variants that escape nonsense-mediated decay, which are transcriptionally active but mislocalized in the cell. Our results suggest that in-depth mutation-specific genotype-phenotype studies are essential to capture full disease complexity and to explain phenotypic variability.

Epigenetic regulator genes direct lineage switching in MLL/AF4 leukemia.

The fusion gene MLL/AF4 defines a high-risk subtype of pro-B acute lymphoblastic leukemia. Relapse can be associated with a lineage switch from acute lymphoblastic to acute myeloid leukemia, resulting in poor clinical outcomes caused by resistance to chemotherapies and immunotherapies. In this study, the myeloid relapses shared oncogene fusion breakpoints with their matched lymphoid presentations and originated from various differentiation stages from immature progenitors through to committed B-cell precursors. Lineage switching is linked to substantial changes in chromatin accessibility and rewiring of transcriptional programs, including alternative splicing. These findings indicate that the execution and maintenance of lymphoid lineage differentiation is impaired. The relapsed myeloid phenotype is recurrently associated with the altered expression, splicing, or mutation of chromatin modifiers, including CHD4 coding for the ATPase/helicase of the nucleosome remodelling and deacetylation complex. Perturbation of CHD4 alone or in combination with other mutated epigenetic modifiers induces myeloid gene expression in MLL/AF4+ cell models, indicating that lineage switching in MLL/AF4 leukemia is driven and maintained by disrupted epigenetic regulation.

Opposite Modulation of RAC1 by Mutations in TRIO Is Associated with Distinct, Domain-Specific Neurodevelopmental Disorders.

The Rho-guanine nucleotide exchange factor (RhoGEF) TRIO acts as a key regulator of neuronal migration, axonal outgrowth, axon guidance, and synaptogenesis by activating the GTPase RAC1 and modulating actin cytoskeleton remodeling. Pathogenic variants in TRIO are associated with neurodevelopmental diseases, including intellectual disability (ID) and autism spectrum disorders (ASD). Here, we report the largest international cohort of 24 individuals with confirmed pathogenic missense or nonsense variants in TRIO. The nonsense mutations are spread along the TRIO sequence, and affected individuals show variable neurodevelopmental phenotypes. In contrast, missense variants cluster into two mutational hotspots in the TRIO sequence, one in the seventh spectrin repeat and one in the RAC1-activating GEFD1. Although all individuals in this cohort present with developmental delay and a neuro-behavioral phenotype, individuals with a pathogenic variant in the seventh spectrin repeat have a more severe ID associated with macrocephaly than do most individuals with GEFD1 variants, who display milder ID and microcephaly. Functional studies show that the spectrin and GEFD1 variants cause a TRIO-mediated hyper- or hypo-activation of RAC1, respectively, and we observe a striking correlation between RAC1 activation levels and the head size of the affected individuals. In addition, truncations in TRIO GEFD1 in the vertebrate model X. tropicalis induce defects that are concordant with the human phenotype. This work demonstrates distinct clinical and molecular disorders clustering in the GEFD1 and seventh spectrin repeat domains and highlights the importance of tight control of TRIO-RAC1 signaling in neuronal development.

Systematic discovery of gene fusions in pediatric cancer by integrating RNA-seq and WGS.

BACKGROUND: Gene fusions are important cancer drivers in pediatric cancer and their accurate detection is essential for diagnosis and treatment. Clinical decision-making requires high confidence and precision of detection. Recent developments show RNA sequencing (RNA-seq) is promising for genome-wide detection of fusion products but hindered by many false positives that require extensive manual curation and impede discovery of pathogenic fusions. METHODS: We developed Fusion-sq to overcome existing disadvantages of detecting gene fusions. Fusion-sq integrates and "fuses" evidence from RNA-seq and whole genome sequencing (WGS) using intron-exon gene structure to identify tumor-specific protein coding gene fusions. Fusion-sq was then applied to the data generated from a pediatric pan-cancer cohort of 128 patients by WGS and RNA sequencing. RESULTS: In a pediatric pan-cancer cohort of 128 patients, we identified 155 high confidence tumor-specific gene fusions and their underlying structural variants (SVs). This includes all clinically relevant fusions known to be present in this cohort (30 patients). Fusion-sq distinguishes healthy-occurring from tumor-specific fusions and resolves fusions in amplified regions and copy number unstable genomes. A high gene fusion burden is associated with copy number instability. We identified 27 potentially pathogenic fusions involving oncogenes or tumor-suppressor genes characterized by underlying SVs, in some cases leading to expression changes indicative of activating or disruptive effects. CONCLUSIONS: Our results indicate how clinically relevant and potentially pathogenic gene fusions can be identified and their functional effects investigated by combining WGS and RNA-seq. Integrating RNA fusion predictions with underlying SVs advances fusion detection beyond extensive manual filtering. Taken together, we developed a method for identifying candidate gene fusions that is suitable for precision oncology applications. Our method provides multi-omics evidence for assessing the pathogenicity of tumor-specific gene fusions for future clinical decision making.

De Novo and Inherited Pathogenic Variants in KDM3B Cause Intellectual Disability, Short Stature, and Facial Dysmorphism.

By using exome sequencing and a gene matching approach, we identified de novo and inherited pathogenic variants in KDM3B in 14 unrelated individuals and three affected parents with varying degrees of intellectual disability (ID) or developmental delay (DD) and short stature. The individuals share additional phenotypic features that include feeding difficulties in infancy, joint hypermobility, and characteristic facial features such as a wide mouth, a pointed chin, long ears, and a low columella. Notably, two individuals developed cancer, acute myeloid leukemia and Hodgkin lymphoma, in childhood. KDM3B encodes for a histone demethylase and is involved in H3K9 demethylation, a crucial part of chromatin modification required for transcriptional regulation. We identified missense and truncating variants, suggesting that KDM3B haploinsufficiency is the underlying mechanism for this syndrome. By using a hybrid facial-recognition model, we show that individuals with a pathogenic variant in KDM3B have a facial gestalt, and that they show significant facial similarity compared to control individuals with ID. In conclusion, pathogenic variants in KDM3B cause a syndrome characterized by ID, short stature, and facial dysmorphism.

Optical genome mapping identifies a germline retrotransposon insertion in SMARCB1 in two siblings with atypical teratoid rhabdoid tumors.

In a subset of pediatric cancers, a germline cancer predisposition is highly suspected based on clinical and pathological findings, but genetic evidence is lacking, which hampers genetic counseling and predictive testing in the families involved. We describe a family with two siblings born from healthy parents who were both neonatally diagnosed with atypical teratoid rhabdoid tumor (ATRT). This rare and aggressive pediatric tumor is associated with biallelic inactivation of SMARCB1, and in 30% of the cases, a predisposing germline mutation is involved. Whereas the tumors of both siblings showed loss of expression of SMARCB1 and acquired homozygosity of the locus, whole exome and whole genome sequencing failed to identify germline or somatic SMARCB1 pathogenic mutations. We therefore hypothesized that the insertion of a pathogenic repeat-rich structure might hamper its detection, and we performed optical genome mapping (OGM) as an alternative strategy to identify structural variation in this locus. Using this approach, an insertion of ~2.8 kb within intron 2 of SMARCB1 was detected. Long-range PCR covering this region remained unsuccessful, but PacBio HiFi genome sequencing identified this insertion to be a SINE-VNTR-Alu, subfamily E (SVA-E) retrotransposon element, which was present in a mosaic state in the mother. This SVA-E insertion disrupts correct splicing of the gene, resulting in loss of a functional allele. This case demonstrates the power of OGM and long-read sequencing to identify genomic variations in high-risk cancer-predisposing genes that are refractory to detection with standard techniques, thereby completing the clinical and molecular diagnosis of such complex cases and greatly improving counseling and surveillance of the families involved. © 2021 The Authors. The Journal of Pathology published by John Wiley & Sons, Ltd. on behalf of The Pathological Society of Great Britain and Ireland.

Genome sequencing identifies major causes of severe intellectual disability.

Severe intellectual disability (ID) occurs in 0.5% of newborns and is thought to be largely genetic in origin. The extensive genetic heterogeneity of this disorder requires a genome-wide detection of all types of genetic variation. Microarray studies and, more recently, exome sequencing have demonstrated the importance of de novo copy number variations (CNVs) and single-nucleotide variations (SNVs) in ID, but the majority of cases remain undiagnosed. Here we applied whole-genome sequencing to 50 patients with severe ID and their unaffected parents. All patients included had not received a molecular diagnosis after extensive genetic prescreening, including microarray-based CNV studies and exome sequencing. Notwithstanding this prescreening, 84 de novo SNVs affecting the coding region were identified, which showed a statistically significant enrichment of loss-of-function mutations as well as an enrichment for genes previously implicated in ID-related disorders. In addition, we identified eight de novo CNVs, including single-exon and intra-exonic deletions, as well as interchromosomal duplications. These CNVs affected known ID genes more frequently than expected. On the basis of diagnostic interpretation of all de novo variants, a conclusive genetic diagnosis was reached in 20 patients. Together with one compound heterozygous CNV causing disease in a recessive mode, this results in a diagnostic yield of 42% in this extensively studied cohort, and 62% as a cumulative estimate in an unselected cohort. These results suggest that de novo SNVs and CNVs affecting the coding region are a major cause of severe ID. Genome sequencing can be applied as a single genetic test to reliably identify and characterize the comprehensive spectrum of genetic variation, providing a genetic diagnosis in the majority of patients with severe ID.

Next-generation phenotyping using computer vision algorithms in rare genomic neurodevelopmental disorders.

PURPOSE: The interpretation of genetic variants after genome-wide analysis is complex in heterogeneous disorders such as intellectual disability (ID). We investigate whether algorithms can be used to detect if a facial gestalt is present for three novel ID syndromes and if these techniques can help interpret variants of uncertain significance. METHODS: Facial features were extracted from photos of ID patients harboring a pathogenic variant in three novel ID genes (PACS1, PPM1D, and PHIP) using algorithms that model human facial dysmorphism, and facial recognition. The resulting features were combined into a hybrid model to compare the three cohorts against a background ID population. RESULTS: We validated our model using images from 71 individuals with Koolen-de Vries syndrome, and then show that facial gestalts are present for individuals with a pathogenic variant in PACS1 (p = 8 × 10-4), PPM1D (p = 4.65 × 10-2), and PHIP (p = 6.3 × 10-3). Moreover, two individuals with a de novo missense variant of uncertain significance in PHIP have significant similarity to the expected facial phenotype of PHIP patients (p < 1.52 × 10-2). CONCLUSION: Our results show that analysis of facial photos can be used to detect previously unknown facial gestalts for novel ID syndromes, which will facilitate both clinical and molecular diagnosis of rare and novel syndromes.

The clustering of functionally related genes contributes to CNV-mediated disease.

Clusters of functionally related genes can be disrupted by a single copy number variant (CNV). We demonstrate that the simultaneous disruption of multiple functionally related genes is a frequent and significant characteristic of de novo CNVs in patients with developmental disorders (P = 1 × 10(-3)). Using three different functional networks, we identified unexpectedly large numbers of functionally related genes within de novo CNVs from two large independent cohorts of individuals with developmental disorders. The presence of multiple functionally related genes was a significant predictor of a CNV's pathogenicity when compared to CNVs from apparently healthy individuals and a better predictor than the presence of known disease or haploinsufficient genes for larger CNVs. The functionally related genes found in the de novo CNVs belonged to 70% of all clusters of functionally related genes found across the genome. De novo CNVs were more likely to affect functional clusters and affect them to a greater extent than benign CNVs (P = 6 × 10(-4)). Furthermore, such clusters of functionally related genes are phenotypically informative: Different patients possessing CNVs that affect the same cluster of functionally related genes exhibit more similar phenotypes than expected (P < 0.05). The spanning of multiple functionally similar genes by single CNVs contributes substantially to how these variants exert their pathogenic effects.

Characteristics of de novo structural changes in the human genome.

Small insertions and deletions (indels) and large structural variations (SVs) are major contributors to human genetic diversity and disease. However, mutation rates and characteristics of de novo indels and SVs in the general population have remained largely unexplored. We report 332 validated de novo structural changes identified in whole genomes of 250 families, including complex indels, retrotransposon insertions, and interchromosomal events. These data indicate a mutation rate of 2.94 indels (1-20 bp) and 0.16 SVs (>20 bp) per generation. De novo structural changes affect on average 4.1 kbp of genomic sequence and 29 coding bases per generation, which is 91 and 52 times more nucleotides than de novo substitutions, respectively. This contrasts with the equal genomic footprint of inherited SVs and substitutions. An excess of structural changes originated on paternal haplotypes. Additionally, we observed a nonuniform distribution of de novo SVs across offspring. These results reveal the importance of different mutational mechanisms to changes in human genome structure across generations.

Gene networks underlying convergent and pleiotropic phenotypes in a large and systematically-phenotyped cohort with heterogeneous developmental disorders.

Readily-accessible and standardised capture of genotypic variation has revolutionised our understanding of the genetic contribution to disease. Unfortunately, the corresponding systematic capture of patient phenotypic variation needed to fully interpret the impact of genetic variation has lagged far behind. Exploiting deep and systematic phenotyping of a cohort of 197 patients presenting with heterogeneous developmental disorders and whose genomes harbour de novo CNVs, we systematically applied a range of commonly-used functional genomics approaches to identify the underlying molecular perturbations and their phenotypic impact. Grouping patients into 408 non-exclusive patient-phenotype groups, we identified a functional association amongst the genes disrupted in 209 (51%) groups. We find evidence for a significant number of molecular interactions amongst the association-contributing genes, including a single highly-interconnected network disrupted in 20% of patients with intellectual disability, and show using microcephaly how these molecular networks can be used as baits to identify additional members whose genes are variant in other patients with the same phenotype. Exploiting the systematic phenotyping of this cohort, we observe phenotypic concordance amongst patients whose variant genes contribute to the same functional association but note that (i) this relationship shows significant variation across the different approaches used to infer a commonly perturbed molecular pathway, and (ii) that the phenotypic similarities detected amongst patients who share the same inferred pathway perturbation result from these patients sharing many distinct phenotypes, rather than sharing a more specific phenotype, inferring that these pathways are best characterized by their pleiotropic effects.

Validation and application of a novel integrated genetic screening method to a cohort of 1,112 men with idiopathic azoospermia or severe oligozoospermia.

Microdeletions of the Y chromosome (YCMs), Klinefelter syndrome (47,XXY), and CFTR mutations are known genetic causes of severe male infertility, but the majority of cases remain idiopathic. Here, we describe a novel method using single molecule Molecular Inversion Probes (smMIPs), to screen infertile men for mutations and copy number variations affecting known disease genes. We designed a set of 4,525 smMIPs targeting the coding regions of causal (n = 6) and candidate (n = 101) male infertility genes. After extensive validation, we screened 1,112 idiopathic infertile men with non-obstructive azoospermia or severe oligozoospermia. In addition to five chromosome YCMs and six other sex chromosomal anomalies, we identified five patients with rare recessive mutations in CFTR as well as a patient with a rare heterozygous frameshift mutation in SYCP3 that may be of clinical relevance. This results in a genetic diagnosis in 11-17 patients (1%-1.5%), a yield that may increase significantly when more genes are confidently linked to male infertility. In conclusion, we developed a flexible and scalable method to reliably detect genetic causes of male infertility. The assay consolidates the detection of different types of genetic variation while increasing the diagnostic yield and detection precision at the same or lower price compared with currently used methods.

Detection of clinically relevant copy-number variants by exome sequencing in a large cohort of genetic disorders.

PURPOSE: Copy-number variation is a common source of genomic variation and an important genetic cause of disease. Microarray-based analysis of copy-number variants (CNVs) has become a first-tier diagnostic test for patients with neurodevelopmental disorders, with a diagnostic yield of 10-20%. However, for most other genetic disorders, the role of CNVs is less clear and most diagnostic genetic studies are generally limited to the study of single-nucleotide variants (SNVs) and other small variants. With the introduction of exome and genome sequencing, it is now possible to detect both SNVs and CNVs using an exome- or genome-wide approach with a single test. METHODS: We performed exome-based read-depth CNV screening on data from 2,603 patients affected by a range of genetic disorders for which exome sequencing was performed in a diagnostic setting. RESULTS: In total, 123 clinically relevant CNVs ranging in size from 727 bp to 15.3 Mb were detected, which resulted in 51 conclusive diagnoses and an overall increase in diagnostic yield of ~2% (ranging from 0 to -5.8% per disorder). CONCLUSIONS: This study shows that CNVs play an important role in a broad range of genetic disorders and that detection via exome-based CNV profiling results in an increase in the diagnostic yield without additional testing, bringing us closer to single-test genomics.Genet Med advance online publication 27 October 2016.

BRCA Testing by Single-Molecule Molecular Inversion Probes.

BACKGROUND: Despite advances in next generation DNA sequencing (NGS), NGS-based single gene tests for diagnostic purposes require improvements in terms of completeness, quality, speed, and cost. Single-molecule molecular inversion probes (smMIPs) are a technology with unrealized potential in the area of clinical genetic testing. In this proof-of-concept study, we selected 2 frequently requested gene tests, those for the breast cancer genes BRCA1 and BRCA2, and developed an automated work flow based on smMIPs. METHODS: The BRCA1 and BRCA2 smMIPs were validated using 166 human genomic DNA samples with known variant status. A generic automated work flow was built to perform smMIP-based enrichment and sequencing for BRCA1, BRCA2, and the checkpoint kinase 2 (CHEK2) c.1100del variant. RESULTS: Pathogenic and benign variants were analyzed in a subset of 152 previously BRCA-genotyped samples, yielding an analytical sensitivity and specificity of 100%. Following automation, blind analysis of 65 in-house samples and 267 Norwegian samples correctly identified all true-positive variants (>3000), with no false positives. Consequent to process optimization, turnaround times were reduced by 60% to currently 10-15 days. Copy number variants were detected with an analytical sensitivity of 100% and an analytical specificity of 88%. CONCLUSIONS: smMIP-based genetic testing enables automated and reliable analysis of the coding sequences of BRCA1 and BRCA2. The use of single-molecule tags, double-tiled targeted enrichment, and capturing and sequencing in duplo, in combination with automated library preparation and data analysis, results in a robust process and reduces routine turnaround times. Furthermore, smMIP-based copy number variation analysis could make independent copy number variation tools like multiplex ligation-dependent probes amplification dispensable.

Mutations in ANTXR1 cause GAPO syndrome.

The genetic cause of GAPO syndrome, a condition characterized by growth retardation, alopecia, pseudoanodontia, and progressive visual impairment, has not previously been identified. We studied four ethnically unrelated affected individuals and identified homozygous nonsense mutations (c.262C>T [p.Arg88*] and c.505C>T [p.Arg169*]) or splicing mutations (c.1435-12A>G [p.Gly479Phefs*119]) in ANTXR1, which encodes anthrax toxin receptor 1. The nonsense mutations predictably trigger nonsense-mediated mRNA decay, resulting in the loss of ANTXR1. The transcript with the splicing mutation theoretically encodes a truncated ANTXR1 containing a neopeptide composed of 118 unique amino acids in its C terminus. GAPO syndrome's major phenotypic features, which include dental abnormalities and the accumulation of extracellular matrix, recapitulate those found in Antxr1-mutant mice and point toward an underlying defect in extracellular-matrix regulation. Thus, we propose that mutations affecting ANTXR1 function are responsible for this disease's characteristic generalized defect in extracellular-matrix homeostasis.

Revertant somatic mosaicism by mitotic recombination in dyskeratosis congenita.

Revertant mosaicism is an infrequently observed phenomenon caused by spontaneous correction of a pathogenic allele. We have observed such reversions caused by mitotic recombination of mutant TERC (telomerase RNA component) alleles in six patients from four families affected by dyskeratosis congenita (DC). DC is a multisystem disorder characterized by mucocutaneous abnormalities, dystrophic nails, bone-marrow failure, lung fibrosis, liver cirrhosis, and cancer. We identified a 4 nt deletion in TERC in a family with an autosomal-dominant form of DC. In two affected brothers without bone-marrow failure, sequence analysis revealed pronounced overrepresentation of the wild-type allele in blood cells, whereas no such skewing was observed in the other tissues tested. These observations suggest that this mosaic pattern might have resulted from somatic reversion of the mutated allele to the normal allele in blood-forming cells. SNP-microarray analysis on blood DNA from the two brothers indeed showed independent events of acquired segmental isodisomy of chromosome 3q, including TERC, indicating that the reversions must have resulted from mitotic recombination events. Subsequently, after developing a highly sensitive method of detecting mosaic homozygosity, we have found four additional cases with a mosaic-reversion pattern in blood cells; these four cases are part of a cohort of 17 individuals with germline TERC mutations. This shows that revertant mosaicism is a recurrent event in DC. This finding has important implications for improving diagnostic testing and understanding the variable phenotype of DC.

Clinical interpretation of CNVs with cross-species phenotype data.

BACKGROUND: Clinical evaluation of CNVs identified via techniques such as array comparative genome hybridisation (aCGH) involves the inspection of lists of known and unknown duplications and deletions with the goal of distinguishing pathogenic from benign CNVs. A key step in this process is the comparison of the individual's phenotypic abnormalities with those associated with Mendelian disorders of the genes affected by the CNV. However, because often there is not much known about these human genes, an additional source of data that could be used is model organism phenotype data. Currently, almost 6000 genes in mouse and zebrafish are, when knocked out, associated with a phenotype in the model organism, but no disease is known to be caused by mutations in the human ortholog. Yet, searching model organism databases and comparing model organism phenotypes with patient phenotypes for identifying novel disease genes and medical evaluation of CNVs is hindered by the difficulty in integrating phenotype information across species and the lack of appropriate software tools. METHODS: Here, we present an integrated ranking scheme based on phenotypic matching, degree of overlap with known benign or pathogenic CNVs and the haploinsufficiency score for the prioritisation of CNVs responsible for a patient's clinical findings. RESULTS: We show that this scheme leads to significant improvements compared with rankings that do not exploit phenotypic information. We provide a software tool called PhenogramViz, which supports phenotype-driven interpretation of aCGH findings based on multiple data sources, including the integrated cross-species phenotype ontology Uberpheno, in order to visualise gene-to-phenotype relations. CONCLUSIONS: Integrating and visualising cross-species phenotype information on the affected genes may help in routine diagnostics of CNVs.

Identification of pathogenic gene variants in small families with intellectually disabled siblings by exome sequencing.

BACKGROUND: Intellectual disability (ID) is a common neurodevelopmental disorder affecting 1-3% of the general population. Mutations in more than 10% of all human genes are considered to be involved in this disorder, although the majority of these genes are still unknown. OBJECTIVES: We investigated 19 small non-consanguineous families with two to five affected siblings in order to identify pathogenic gene variants in known, novel and potential ID candidate genes. Non-consanguineous families have been largely ignored in gene identification studies as small family size precludes prior mapping of the genetic defect. METHODS AND RESULTS: Using exome sequencing, we identified pathogenic mutations in three genes, DDHD2, SLC6A8, and SLC9A6, of which the latter two have previously been implicated in X-linked ID phenotypes. In addition, we identified potentially pathogenic mutations in BCORL1 on the X-chromosome and in MCM3AP, PTPRT, SYNE1, and ZNF528 on autosomes. CONCLUSIONS: We show that potentially pathogenic gene variants can be identified in small, non-consanguineous families with as few as two affected siblings, thus emphasising their value in the identification of syndromic and non-syndromic ID genes.

Beyond the Global Brain Differences: Intraindividual Variability Differences in 1q21.1 Distal and 15q11.2 BP1-BP2 Deletion Carriers.

BACKGROUND: Carriers of the 1q21.1 distal and 15q11.2 BP1-BP2 copy number variants exhibit regional and global brain differences compared with noncarriers. However, interpreting regional differences is challenging if a global difference drives the regional brain differences. Intraindividual variability measures can be used to test for regional differences beyond global differences in brain structure. METHODS: Magnetic resonance imaging data were used to obtain regional brain values for 1q21.1 distal deletion (n = 30) and duplication (n = 27) and 15q11.2 BP1-BP2 deletion (n = 170) and duplication (n = 243) carriers and matched noncarriers (n = 2350). Regional intra-deviation scores, i.e., the standardized difference between an individual's regional difference and global difference, were used to test for regional differences that diverge from the global difference. RESULTS: For the 1q21.1 distal deletion carriers, cortical surface area for regions in the medial visual cortex, posterior cingulate, and temporal pole differed less and regions in the prefrontal and superior temporal cortex differed more than the global difference in cortical surface area. For the 15q11.2 BP1-BP2 deletion carriers, cortical thickness in regions in the medial visual cortex, auditory cortex, and temporal pole differed less and the prefrontal and somatosensory cortex differed more than the global difference in cortical thickness. CONCLUSIONS: We find evidence for regional effects beyond differences in global brain measures in 1q21.1 distal and 15q11.2 BP1-BP2 copy number variants. The results provide new insight into brain profiling of the 1q21.1 distal and 15q11.2 BP1-BP2 copy number variants, with the potential to increase understanding of the mechanisms involved in altered neurodevelopment.

Detection of clinically relevant copy number variants with whole-exome sequencing.

Copy number variation (CNV) is a common source of genetic variation that has been implicated in many genomic disorders. This has resulted in the widespread application of genomic microarrays as a first-tier diagnostic tool for CNV detection. More recently, whole-exome sequencing (WES) has been proven successful for the detection of clinically relevant point mutations and small insertion-deletions exome wide. We evaluate the utility of short-read WES (SOLiD 5500xl) to detect clinically relevant CNVs in DNA from 10 patients with intellectual disability and compare these results to data from two independent high-resolution microarrays. Eleven of the 12 clinically relevant CNVs were detected via read-depth analysis of WES data; a heterozygous single-exon deletion remained undetected by all algorithms evaluated. Although the detection power of WES for small CNVs currently does not match that of high-resolution microarray platforms, we show that the majority (88%) of rare coding CNVs containing three or more exons are successfully identified by WES. These results show that the CNV detection resolution of WES is comparable to that of medium-resolution genomic microarrays commonly used as clinical assays. The combined detection of point mutations, indels, and CNVs makes WES a very attractive first-tier diagnostic test for genetically heterogeneous disorders.