Sub-cellular level resolution of common genetic variation in the photoreceptor layer identifies continuum between rare disease and common variation.

Photoreceptor cells (PRCs) are the light-detecting cells of the retina. Such cells can be non-invasively imaged using optical coherence tomography (OCT) which is used in clinical settings to diagnose and monitor ocular diseases. Here we present the largest genome-wide association study of PRC morphology to date utilising quantitative phenotypes extracted from OCT images within the UK Biobank. We discovered 111 loci associated with the thickness of one or more of the PRC layers, many of which had prior associations to ocular phenotypes and pathologies, and 27 with no prior associations. We further identified 10 genes associated with PRC thickness through gene burden testing using exome data. In both cases there was a significant enrichment for genes involved in rare eye pathologies, in particular retinitis pigmentosa. There was evidence for an interaction effect between common genetic variants, VSX2 involved in eye development and PRPH2 known to be involved in retinal dystrophies. We further identified a number of genetic variants with a differential effect across the macular spatial field. Our results suggest a continuum between common and rare variation which impacts retinal structure, sometimes leading to disease.

Selective clonal persistence of human retroviruses in vivo: Radial chromatin organization, integration site, and host transcription.

The human retroviruses HTLV-1 (human T cell leukemia virus type 1) and HIV-1 persist in vivo as a reservoir of latently infected T cell clones. It is poorly understood what determines which clones survive in the reservoir. We compared >160,000 HTLV-1 integration sites (>40,000 HIV-1 sites) from T cells isolated ex vivo from naturally infected individuals with >230,000 HTLV-1 integration sites (>65,000 HIV-1 sites) from in vitro infection to identify genomic features that determine selective clonal survival. Three statistically independent factors together explained >40% of the observed variance in HTLV-1 clonal survival in vivo: the radial intranuclear position of the provirus, its genomic distance from the centromere, and the intensity of local host genome transcription. The radial intranuclear position of the provirus and its distance from the centromere also explained ~7% of clonal persistence of HIV-1 in vivo. Selection for the intranuclear and intrachromosomal location of the provirus and host transcription intensity favors clonal persistence of human retroviruses in vivo.

Correction: Genetic variation affects morphological retinal phenotypes extracted from UK Biobank optical coherence tomography images.

[This corrects the article DOI: 10.1371/journal.pgen.1009497.].

Correction: Integrative analysis of genomic variants reveals new associations of candidate haploinsufficient genes with congenital heart disease.

[This corrects the article DOI: 10.1371/journal.pgen.1009679.].

Integrative analysis of genomic variants reveals new associations of candidate haploinsufficient genes with congenital heart disease.

Numerous genetic studies have established a role for rare genomic variants in Congenital Heart Disease (CHD) at the copy number variation (CNV) and de novo variant (DNV) level. To identify novel haploinsufficient CHD disease genes, we performed an integrative analysis of CNVs and DNVs identified in probands with CHD including cases with sporadic thoracic aortic aneurysm. We assembled CNV data from 7,958 cases and 14,082 controls and performed a gene-wise analysis of the burden of rare genomic deletions in cases versus controls. In addition, we performed variation rate testing for DNVs identified in 2,489 parent-offspring trios. Our analysis revealed 21 genes which were significantly affected by rare CNVs and/or DNVs in probands. Fourteen of these genes have previously been associated with CHD while the remaining genes (FEZ1, MYO16, ARID1B, NALCN, WAC, KDM5B and WHSC1) have only been associated in small cases series or show new associations with CHD. In addition, a systems level analysis revealed affected protein-protein interaction networks involved in Notch signaling pathway, heart morphogenesis, DNA repair and cilia/centrosome function. Taken together, this approach highlights the importance of re-analyzing existing datasets to strengthen disease association and identify novel disease genes and pathways.

Genetic variation affects morphological retinal phenotypes extracted from UK Biobank optical coherence tomography images.

Optical Coherence Tomography (OCT) enables non-invasive imaging of the retina and is used to diagnose and manage ophthalmic diseases including glaucoma. We present the first large-scale genome-wide association study of inner retinal morphology using phenotypes derived from OCT images of 31,434 UK Biobank participants. We identify 46 loci associated with thickness of the retinal nerve fibre layer or ganglion cell inner plexiform layer. Only one of these loci has been associated with glaucoma, and despite its clear role as a biomarker for the disease, Mendelian randomisation does not support inner retinal thickness being on the same genetic causal pathway as glaucoma. We extracted overall retinal thickness at the fovea, representative of foveal hypoplasia, with which three of the 46 SNPs were associated. We additionally associate these three loci with visual acuity. In contrast to the Mendelian causes of severe foveal hypoplasia, our results suggest a spectrum of foveal hypoplasia, in part genetically determined, with consequences on visual function.

Comparison of Associations with Different Macular Inner Retinal Thickness Parameters in a Large Cohort: The UK Biobank.

PURPOSE: To describe and compare associations with macular retinal nerve fiber layer (mRNFL), ganglion cell complex (GCC), and ganglion cell-inner plexiform layer (GCIPL) thicknesses in a large cohort. DESIGN: Cross-sectional study. PARTICIPANTS: We included 42 044 participants in the UK Biobank. The mean age was 56 years. METHODS: Spectral-domain OCT macular images were segmented and analyzed. Corneal-compensated intraocular pressure (IOPcc) was measured with the Ocular Response Analyzer (Reichert, Corp., Buffalo, NY). Multivariable linear regression was used to examine associations with mean mRNFL, GCC, and GCIPL thicknesses. Factors examined were age, sex, ethnicity, height, body mass index (BMI), smoking status, alcohol intake, Townsend deprivation index, education level, diabetes status, spherical equivalent, and IOPcc. MAIN OUTCOME MEASURES: Thicknesses of mRNFL, GCC, and GCIPL. RESULTS: We identified several novel independent associations with thinner inner retinal thickness. Thinner inner retina was associated with alcohol intake (most significant for GCIPL: -0.46 µm for daily or almost daily intake compared with special occasion only or never [95% confidence interval (CI), 0.61-0.30]; P = 1.1×10-8), greater social deprivation (most significant for GCIPL: -0.28 µm for most deprived quartile compared with least deprived quartile [95% CI, -0.42 to -0.14]; P = 6.6×10-5), lower educational attainment (most significant for mRNFL: -0.36 µm for less than O level compared with degree level [95% CI, -0.45 to 0.26]; P = 2.3×10-14), and nonwhite ethnicity (most significant for mRNFL comparing blacks with whites: -1.65 µm [95% CI, -1.86 to -1.43]; P = 2.4×10-50). Corneal-compensated intraocular pressure was associated most significantly with GCIPL (-0.04 µm/mmHg [95% CI, -0.05 to -0.03]; P = 4.0×10-10) and was not associated significantly with mRNFL (0.00 µm/mmHg [95% CI, -0.01 to 0.01]; P = 0.77). The variables examined explained a greater proportion of the variance of GCIPL (11%) than GCC (6%) or mRNFL (7%). CONCLUSIONS: The novel associations we identified may be important to consider when using inner retinal parameters as a diagnostic tool. Associations generally were strongest with GCIPL, particularly for IOP. This suggests that GCIPL may be the superior inner retinal biomarker for macular pathophysiologic processes and especially for glaucoma.

The human leukemia virus HTLV-1 alters the structure and transcription of host chromatin in cis.

Chromatin looping controls gene expression by regulating promoter-enhancer contacts, the spread of epigenetic modifications, and the segregation of the genome into transcriptionally active and inactive compartments. We studied the impact on the structure and expression of host chromatin by the human retrovirus HTLV-1. We show that HTLV-1 disrupts host chromatin structure by forming loops between the provirus and the host genome; certain loops depend on the critical chromatin architectural protein CTCF, which we recently discovered binds to the HTLV-1 provirus. We show that the provirus causes two distinct patterns of abnormal transcription of the host genome in cis: bidirectional transcription in the host genome immediately flanking the provirus, and clone-specific transcription in cis at non-contiguous loci up to >300 kb from the integration site. We conclude that HTLV-1 causes insertional mutagenesis up to the megabase range in the host genome in >104 persistently-maintained HTLV-1+ T-cell clones in vivo.

Making new genetic diagnoses with old data: iterative reanalysis and reporting from genome-wide data in 1,133 families with developmental disorders.

PURPOSE: Given the rapid pace of discovery in rare disease genomics, it is likely that improvements in diagnostic yield can be made by systematically reanalyzing previously generated genomic sequence data in light of new knowledge. METHODS: We tested this hypothesis in the United Kingdom-wide Deciphering Developmental Disorders study, where in 2014 we reported a diagnostic yield of 27% through whole-exome sequencing of 1,133 children with severe developmental disorders and their parents. We reanalyzed existing data using improved variant calling methodologies, novel variant detection algorithms, updated variant annotation, evidence-based filtering strategies, and newly discovered disease-associated genes. RESULTS: We are now able to diagnose an additional 182 individuals, taking our overall diagnostic yield to 454/1,133 (40%), and another 43 (4%) have a finding of uncertain clinical significance. The majority of these new diagnoses are due to novel developmental disorder-associated genes discovered since our original publication. CONCLUSION: This study highlights the importance of coupling large-scale research with clinical practice, and of discussing the possibility of iterative reanalysis and recontact with patients and health professionals at an early stage. We estimate that implementing parent-offspring whole-exome sequencing as a first-line diagnostic test for developmental disorders would diagnose >50% of patients.

Detection of structural mosaicism from targeted and whole-genome sequencing data.

Structural mosaic abnormalities are large post-zygotic mutations present in a subset of cells and have been implicated in developmental disorders and cancer. Such mutations have been conventionally assessed in clinical diagnostics using cytogenetic or microarray testing. Modern disease studies rely heavily on exome sequencing, yet an adequate method for the detection of structural mosaicism using targeted sequencing data is lacking. Here, we present a method, called MrMosaic, to detect structural mosaic abnormalities using deviations in allele fraction and read coverage from next-generation sequencing data. Whole-exome sequencing (WES) and whole-genome sequencing (WGS) simulations were used to calculate detection performance across a range of mosaic event sizes, types, clonalities, and sequencing depths. The tool was applied to 4911 patients with undiagnosed developmental disorders, and 11 events among nine patients were detected. For eight of these 11 events, mosaicism was observed in saliva but not blood, suggesting that assaying blood alone would miss a large fraction, possibly >50%, of mosaic diagnostic chromosomal rearrangements.

Distinct genetic architectures for syndromic and nonsyndromic congenital heart defects identified by exome sequencing.

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%), suggesting a considerable role for de novo mutations (DNMs) and/or incomplete penetrance. De novo protein-truncating variants (PTVs) have been shown to be enriched among the 10% of 'syndromic' patients with extra-cardiac manifestations. 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. 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.

Punctuated bursts in human male demography inferred from 1,244 worldwide Y-chromosome sequences.

We report the sequences of 1,244 human Y chromosomes randomly ascertained from 26 worldwide populations by the 1000 Genomes Project. We discovered more than 65,000 variants, including single-nucleotide variants, multiple-nucleotide variants, insertions and deletions, short tandem repeats, and copy number variants. Of these, copy number variants contribute the greatest predicted functional impact. We constructed a calibrated phylogenetic tree on the basis of binary single-nucleotide variants and projected the more complex variants onto it, estimating the number of mutations for each class. Our phylogeny shows bursts of extreme expansion in male numbers that have occurred independently among each of the five continental superpopulations examined, at times of known migrations and technological innovations.

Discovery of four recessive developmental disorders using probabilistic genotype and phenotype matching among 4,125 families.

Discovery of most autosomal recessive disease-associated genes has involved analysis of large, often consanguineous multiplex families or small cohorts of unrelated individuals with a well-defined clinical condition. Discovery of new dominant causes of rare, genetically heterogeneous developmental disorders has been revolutionized by exome analysis of large cohorts of phenotypically diverse parent-offspring trios. Here we analyzed 4,125 families with diverse, rare and genetically heterogeneous developmental disorders and identified four new autosomal recessive disorders. These four disorders were identified by integrating Mendelian filtering (selecting probands with rare, biallelic and putatively damaging variants in the same gene) with statistical assessments of (i) the likelihood of sampling the observed genotypes from the general population and (ii) the phenotypic similarity of patients with recessive variants in the same candidate gene. This new paradigm promises to catalyze the discovery of novel recessive disorders, especially those with less consistent or nonspecific clinical presentations and those caused predominantly by compound heterozygous genotypes.

Copy number variation in the human Y chromosome in the UK population.

We have assessed copy number variation (CNV) in the male-specific part of the human Y chromosome discovered by array comparative genomic hybridization (array-CGH) in 411 apparently healthy UK males, and validated the findings using SNP genotype intensity data available for 149 of them. After manual curation taking account of the complex duplicated structure of Y-chromosomal sequences, we discovered 22 curated CNV events considered validated or likely, mean 0.93 (range 0-4) per individual. 16 of these were novel. Curated CNV events ranged in size from <1 kb to >3 Mb, and in frequency from 1/411 to 107/411. Of the 24 protein-coding genes or gene families tested, nine showed CNV. These included a large duplication encompassing the AMELY and TBL1Y genes that probably has no phenotypic effect, partial deletions of the TSPY cluster and AZFc region that may influence spermatogenesis, and other variants with unknown functional implications, including abundant variation in the number of RBMY genes and/or pseudogenes, and a novel complex duplication of two segments overlapping the AZFa region and including the 3' end of the UTY gene.

Genetic diagnosis of developmental disorders in the DDD study: a scalable analysis of genome-wide research data.

BACKGROUND: 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. METHODS: 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. FINDINGS: 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. INTERPRETATION: 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. FUNDING: Health Innovation Challenge Fund, a parallel funding partnership between the Wellcome Trust and the UK Department of Health.

A novel method for detecting uniparental disomy from trio genotypes identifies a significant excess in children with developmental disorders.

Exome sequencing of parent-offspring trios is a popular strategy for identifying causative genetic variants in children with rare diseases. This method owes its strength to the leveraging of inheritance information, which facilitates de novo variant calling, inference of compound heterozygosity, and the identification of inheritance anomalies. Uniparental disomy describes the inheritance of a homologous chromosome pair from only one parent. This aberration is important to detect in genetic disease studies because it can result in imprinting disorders and recessive diseases. We have developed a software tool to detect uniparental disomy from child-mother-father genotype data that uses a binomial test to identify chromosomes with a significant burden of uniparentally inherited genotypes. This tool is the first to read VCF-formatted genotypes, to perform integrated copy number filtering, and to use a statistical test inherently robust for use in platforms of varying genotyping density and noise characteristics. Simulations demonstrated superior accuracy compared with previously developed approaches. We implemented the method on 1057 trios from the Deciphering Developmental Disorders project, a trio-based rare disease study, and detected six validated events, a significant enrichment compared with the population prevalence of UPD (1 in 3500), suggesting that most of these events are pathogenic. One of these events represents a known imprinting disorder, and exome analyses have identified rare homozygous candidate variants, mainly in the isodisomic regions of UPD chromosomes, which, among other variants, provide targets for further genetic and functional evaluation.

Large scale variation in DNA copy number in chicken breeds.

BACKGROUND: Detecting genetic variation is a critical step in elucidating the molecular mechanisms underlying phenotypic diversity. Until recently, such detection has mostly focused on single nucleotide polymorphisms (SNPs) because of the ease in screening complete genomes. Another type of variant, copy number variation (CNV), is emerging as a significant contributor to phenotypic variation in many species. Here we describe a genome-wide CNV study using array comparative genomic hybridization (aCGH) in a wide variety of chicken breeds. RESULTS: We identified 3,154 CNVs, grouped into 1,556 CNV regions (CNVRs). Thirty percent of the CNVs were detected in at least 2 individuals. The average size of the CNVs detected was 46.3 kb with the largest CNV, located on GGAZ, being 4.3 Mb. Approximately 75% of the CNVs are copy number losses relatively to the Red Jungle Fowl reference genome. The genome coverage of CNVRs in this study is 60 Mb, which represents almost 5.4% of the chicken genome. In particular large gene families such as the keratin gene family and the MHC show extensive CNV. CONCLUSIONS: A relative large group of the CNVs are line-specific, several of which were previously shown to be related to the causative mutation for a number of phenotypic variants. The chance that inter-specific CNVs fall into CNVRs detected in chicken is related to the evolutionary distance between the species. Our results provide a valuable resource for the study of genetic and phenotypic variation in this phenotypically diverse species.

Mobilization of giant piggyBac transposons in the mouse genome.

The development of technologies that allow the stable delivery of large genomic DNA fragments in mammalian systems is important for genetic studies as well as for applications in gene therapy. DNA transposons have emerged as flexible and efficient molecular vehicles to mediate stable cargo transfer. However, the ability to carry DNA fragments >10 kb is limited in most DNA transposons. Here, we show that the DNA transposon piggyBac can mobilize 100-kb DNA fragments in mouse embryonic stem (ES) cells, making it the only known transposon with such a large cargo capacity. The integrity of the cargo is maintained during transposition, the copy number can be controlled and the inserted giant transposons express the genomic cargo. Furthermore, these 100-kb transposons can also be excised from the genome without leaving a footprint. The development of piggyBac as a large cargo vector will facilitate a wider range of genetic and genomic applications.

aCGH.Spline--an R package for aCGH dye bias normalization.

MOTIVATION: The careful normalization of array-based comparative genomic hybridization (aCGH) data is of critical importance for the accurate detection of copy number changes. The difference in labelling affinity between the two fluorophores used in aCGH-usually Cy5 and Cy3-can be observed as a bias within the intensity distributions. If left unchecked, this bias is likely to skew data interpretation during downstream analysis and lead to an increased number of false discoveries. RESULTS: In this study, we have developed aCGH.Spline, a natural cubic spline interpolation method followed by linear interpolation of outlier values, which is able to remove a large portion of the dye bias from large aCGH datasets in a quick and efficient manner. CONCLUSIONS: We have shown that removing this bias and reducing the experimental noise has a strong positive impact on the ability to detect accurately both copy number variation (CNV) and copy number alterations (CNA).