Hongbo M. Xie

Rare structural variants found in attention-deficit hyperactivity disorder are preferentially associated with neurodevelopmental genes.

Attention-deficit/hyperactivity disorder (ADHD) is a common and highly heritable disorder, but specific genetic factors underlying risk remain elusive. To assess the role of structural variation in ADHD, we identified 222 inherited copy number variations (CNVs) within 335 ADHD patients and their parents that were not detected in 2026 unrelated healthy individuals. Although no excess CNVs, either deletions or duplications, were found in the ADHD cohort relative to controls, the inherited rare CNV-associated gene set was significantly enriched for genes reported as candidates in studies of autism, schizophrenia and Tourette syndrome, including A2BP1, AUTS2, CNTNAP2 and IMMP2L. The ADHD CNV gene set was also significantly enriched for genes known to be important for psychological and neurological functions, including learning, behavior, synaptic transmission and central nervous system development. Four independent deletions were located within the protein tyrosine phosphatase gene, PTPRD, recently implicated as a candidate gene for restless legs syndrome, which frequently presents with ADHD. A deletion within the glutamate receptor gene, GRM5, was found in an affected parent and all three affected offspring whose ADHD phenotypes closely resembled those of the GRM5 null mouse. Together, these results suggest that rare inherited structural variations play an important role in ADHD development and indicate a set of putative candidate genes for further study in the etiology of ADHD.

High-resolution mapping and analysis of copy number variations in the human genome: A data resource for clinical and research applications

We present a database of copy number variations (CNVs) detected in 2026 disease-free individuals, using high-density, SNP-based oligonucleotide microarrays. This large cohort, comprised mainly of Caucasians (65.2%) and African-Americans (34.2%), was analyzed for CNVs in a single study using a uniform array platform and computational process. We have catalogued and characterized 54,462 individual CNVs, 77.8% of which were identified in multiple unrelated individuals. These nonunique CNVs mapped to 3272 distinct regions of genomic variation spanning 5.9% of the genome; 51.5% of these were previously unreported, and >85% are rare. Our annotation and analysis confirmed and extended previously reported correlations between CNVs and several genomic features such as repetitive DNA elements, segmental duplications, and genes. We demonstrate the utility of this data set in distinguishing CNVs with pathologic significance from normal variants. Together, this analysis and annotation provides a useful resource to assist with the assessment of CNVs in the contexts of human variation, disease susceptibility, and clinical molecular diagnostics.

Rare structural variation of synapse and neurotransmission genes in autism.

Autism spectrum disorders (ASDs) comprise a constellation of highly heritable neuropsychiatric disorders. Genome-wide studies of autistic individuals have implicated numerous minor risk alleles but few common variants, suggesting a complex genetic model with many contributing loci. To assess commonality of biological function among rare risk alleles, we compared functional knowledge of genes overlapping inherited structural variants in idiopathic ASD subjects relative to healthy controls. In this study we show that biological processes associated with synapse function and neurotransmission are significantly enriched, with replication, in ASD subjects versus controls. Analysis of phenotypes observed for mouse models of copy-variant genes established significant and replicated enrichment of observable phenotypes consistent with ASD behaviors. Most functional terms retained significance after excluding previously reported ASD loci. These results implicate several new variants that involve synaptic function and glutamatergic signaling processes as important contributors of ASD pathophysiology and suggest a sizable pool of additional potential ASD risk loci.

Prevalence of rare mitochondrial DNA mutations in mitochondrial disorders

Abstract Background Mitochondrial DNA (mtDNA) diseases are rare disorders whose prevalence is estimated around 1 in 5000. Patients are usually tested only for deletions and for common mutations of mtDNA which account for 5–40% of cases, depending on the study. However, the prevalence of rare mtDNA mutations is not known. Methods We analysed the whole mtDNA in a cohort of 743 patients suspected of manifesting a mitochondrial disease, after excluding deletions and common mutations. Both heteroplasmic and homoplasmic variants were identified using two complementary strategies (Surveyor and MitoChip). Multiple correspondence analyses followed by hierarchical ascendant cluster process were used to explore relationships between clinical spectrum, age at onset and localisation of mutations. Results 7.4% of deleterious mutations and 22.4% of novel putative mutations were identified. Pathogenic heteroplasmic mutations were more frequent than homoplasmic mutations (4.6% vs 2.8%). Patients carrying deleterious mutations showed symptoms before 16 years of age in 67% of cases. Early onset disease (<1 year) was significantly associated with mutations in protein coding genes (mainly in complex I) while late onset disorders (>16 years) were associated with mutations in tRNA genes. MTND5 and MTND6 genes were identified as ‘hotspots’ of mutations, with Leigh syndrome accounting for the large majority of associated phenotypes. Conclusions Rare mitochondrial DNA mutations probably account for more than 7.4% of patients with respiratory chain deficiency. This study shows that a comprehensive analysis of mtDNA is essential, and should include young children, for an accurate diagnosis that is now accessible with the development of next generation sequencing technology.

CNV Workshop: an integrated platform for high-throughput copy number variation discovery and clinical diagnostics

BackgroundRecent studies have shown that copy number variations (CNVs) are frequent in higher eukaryotes and associated with a substantial portion of inherited and acquired risk for various human diseases. The increasing availability of high-resolution genome surveillance platforms provides opportunity for rapidly assessing research and clinical samples for CNV content, as well as for determining the potential pathogenicity of identified variants. However, few informatics tools for accurate and efficient CNV detection and assessment currently exist.ResultsWe developed a suite of software tools and resources (CNV Workshop) for automated, genome-wide CNV detection from a variety of SNP array platforms. CNV Workshop includes three major components: detection, annotation, and presentation of structural variants from genome array data. CNV detection utilizes a robust and genotype-specific extension of the Circular Binary Segmentation algorithm, and the use of additional detection algorithms is supported. Predicted CNVs are captured in a MySQL database that supports cohort-based projects and incorporates a secure user authentication layer and user/admin roles. To assist with determination of pathogenicity, detected CNVs are also annotated automatically for gene content, known disease loci, and gene-based literature references. Results are easily queried, sorted, filtered, and visualized via a web-based presentation layer that includes a GBrowse-based graphical representation of CNV content and relevant public data, integration with the UCSC Genome Browser, and tabular displays of genomic attributes for each CNV.ConclusionsTo our knowledge, CNV Workshop represents the first cohesive and convenient platform for detection, annotation, and assessment of the biological and clinical significance of structural variants. CNV Workshop has been successfully utilized for assessment of genomic variation in healthy individuals and disease cohorts and is an ideal platform for coordinating multiple associated projects.Availability and ImplementationAvailable on the web at: http://sourceforge.net/projects/cnv

Efficient digest of high-throughput sequencing data in a reproducible report

BackgroundHigh-throughput sequencing (HTS) technologies are spearheading the accelerated development of biomedical research. Processing and summarizing the large amount of data generated by HTS presents a non-trivial challenge to bioinformatics. A commonly adopted standard is to store sequencing reads aligned to a reference genome in SAM (Sequence Alignment/Map) or BAM (Binary Alignment/Map) files. Quality control of SAM/BAM files is a critical checkpoint before downstream analysis. The goal of the current project is to facilitate and standardize this process.ResultsWe developed bamchop, a robust program to efficiently summarize key statistical metrics of HTS data stored in BAM files, and to visually present the results in a formatted report. The report documents information about various aspects of HTS data, such as sequencing quality, mapping to a reference genome, sequencing coverage, and base frequency. Bamchop uses the R language and Bioconductor packages to calculate statistical matrices and the Sweave utility and associated LaTeX markup for documentation. Bamchops efficiency and robustness were tested on BAM files generated by local sequencing facilities and the 1000 Genomes Project. Source code, instruction and example reports of bamchop are freely available from https://github.com/CBMi-BiG/bamchop.ConclusionsBamchop enables biomedical researchers to quickly and rigorously evaluate HTS data by providing a convenient synopsis and user-friendly reports.

Copy-number variation is an important contributor to the genetic causality of inherited retinal degenerations.

Purpose:Despite substantial progress in sequencing, current strategies can genetically solve only approximately 55–60% of inherited retinal degeneration (IRD) cases. This can be partially attributed to elusive mutations in the known IRD genes, which are not easily identified by the targeted next-generation sequencing (NGS) or Sanger sequencing approaches. We hypothesized that copy-number variations (CNVs) are a major contributor to the elusive genetic causality of IRDs.Methods:Twenty-eight cases previously unsolved with a targeted NGS were investigated with whole-genome single-nucleotide polymorphism (SNP) and comparative genomic hybridization (CGH) arrays.Results:Deletions in the IRD genes were detected in 5 of 28 families, including a de novo deletion. We suggest that the de novo deletion occurred through nonallelic homologous recombination (NAHR) and we constructed a genomic map of NAHR-prone regions with overlapping IRD genes. In this article, we also report an unusual case of recessive retinitis pigmentosa due to compound heterozygous mutations in SNRNP200, a gene that is typically associated with the dominant form of this disease.Conclusions:CNV mapping substantially increased the genetic diagnostic rate of IRDs, detecting genetic causality in 18% of previously unsolved cases. Extending the search to other structural variations will probably demonstrate an even higher contribution to genetic causality of IRDs.Genet Med advance online publication 13 October 2016

Mitochondrial genome sequence analysis: A custom bioinformatics pipeline substantially improves Affymetrix MitoChip v2.0 call rate and accuracy

BackgroundMitochondrial genome sequence analysis is critical to the diagnostic evaluation of mitochondrial disease. Existing methodologies differ widely in throughput, complexity, cost efficiency, and sensitivity of heteroplasmy detection. Affymetrix MitoChip v2.0, which uses a sequencing-by-genotyping technology, allows potentially accurate and high-throughput sequencing of the entire human mitochondrial genome to be completed in a cost-effective fashion. However, the relatively low call rate achieved using existing software tools has limited the wide adoption of this platform for either clinical or research applications. Here, we report the design and development of a custom bioinformatics software pipeline that achieves a much improved call rate and accuracy for the Affymetrix MitoChip v2.0 platform. We used this custom pipeline to analyze MitoChip v2.0 data from 24 DNA samples representing a broad range of tissue types (18 whole blood, 3 skeletal muscle, 3 cell lines), mutations (a 5.8 kilobase pair deletion and 6 known heteroplasmic mutations), and haplogroup origins. All results were compared to those obtained by at least one other mitochondrial DNA sequence analysis method, including Sanger sequencing, denaturing HPLC-based heteroduplex analysis, and/or the Illumina Genome Analyzer II next generation sequencing platform.ResultsAn average call rate of 99.75% was achieved across all samples with our custom pipeline. Comparison of calls for 15 samples characterized previously by Sanger sequencing revealed a total of 29 discordant calls, which translates to an estimated 0.012% for the base call error rate. We successfully identified 4 known heteroplasmic mutations and 24 other potential heteroplasmic mutations across 20 samples that passed quality control.ConclusionsAffymetrix MitoChip v2.0 analysis using our optimized MitoChip Filtering Protocol (MFP) bioinformatics pipeline now offers the high sensitivity and accuracy needed for reliable, high-throughput and cost-efficient whole mitochondrial genome sequencing. This approach provides a viable alternative of potential utility for both clinical diagnostic and research applications to traditional Sanger and other emerging sequencing technologies for whole mitochondrial genome analysis.

Single nucleotide polymorphism array analysis of bone marrow failure patients reveals characteristic patterns of genetic changes.

The bone marrow failure syndromes (BMFS) are a heterogeneous group of rare blood disorders characterized by inadequate haematopoiesis, clonal evolution, and increased risk of leukaemia. Single nucleotide polymorphism arrays (SNP‐A) have been proposed as a tool for surveillance of clonal evolution in BMFS. To better understand the natural history of BMFS and to assess the clinical utility of SNP‐A in these disorders, we analysed 124 SNP‐A from a comprehensively characterized cohort of 91 patients at our BMFS centre. SNP‐A were correlated with medical histories, haematopathology, cytogenetic and molecular data. To assess clonal evolution, longitudinal analysis of SNP‐A was performed in 25 patients. We found that acquired copy number‐neutral loss of heterozygosity (CN‐LOH) was significantly more frequent in acquired aplastic anaemia (aAA) than in other BMFS (odds ratio 12·2, P < 0·01). Homozygosity by descent was most common in congenital BMFS, frequently unmasking autosomal recessive mutations. Copy number variants (CNVs) were frequently polymorphic, and we identified CNVs enriched in neutropenia and aAA. Our results suggest that acquired CN‐LOH is a general phenomenon in aAA that is probably mechanistically and prognostically distinct from typical CN‐LOH of myeloid malignancies. Our analysis of clinical utility of SNP‐A shows the highest yield of detecting new clonal haematopoiesis at diagnosis and at relapse.

Analysis of chromosomal structural variation in patients with congenital left-sided cardiac lesions.

BACKGROUND We sought to characterize the landscape of structural variation associated with the subset of congenital cardiac defects characterized by left-sided obstruction. METHODS Cases with left-sided cardiac defects (LSCD) and pediatric controls were uniformly genotyped and assessed for copy number variant (CNV) calls. Significance testing was performed to ascertain differences in overall CNV incidence, and for CNV enrichment of specific genes and gene functions in LSCD cases relative to controls. RESULTS A total of 257 cases of European descent and 962 ethnically matched, disease-free pediatric controls were included. Although there was no difference in CNV rate between cases and controls, a significant enrichment in rare LSCD CNVs was detected overall (p=7.30 × 10(-3) , case/control ratio=1.26) and when restricted either to deletions (p=7.58 × 10(-3) , case/control ratio=1.20) or duplications (3.02 × 10(-3) , case/control ratio=1.43). Neither gene-based, functional nor knowledge-based analyses identified genes, loci or pathways that were significantly enriched in cases as compared to controls when appropriate corrections for multiple tests were applied. However, several genes of interest were identified by virtue of their association with cardiac development, known human conditions, or reported disruption by CNVs in other patient cohorts. CONCLUSION This study examines the largest cohort to date with LSCD for structural variation. These data suggest that CNVs play a role in disease risk and identify numerous genes disrupted by CNVs of potential disease relevance. These findings further highlight the genetic heterogeneity and complexity of these disorders.