Analysis of deletion breakpoints from 1,092 humans reveals details of mutation mechanisms

Genome and transcriptomic analysis of the adaptation of Escherichia coli to environmental stresses

In natural niches, bacteria are forced to spend most of their lives under various environmental stresses, such as nutrient limitation, heavy metal pollution, heat and antibiotic stress. To cope with adverse environments, bacterial genome can during the life cycle, produce potential adaptive mutants. The genomic changes, especially mutations, in the genes that encode RNA polymerase and transcription factors, might lead to variations in the transcriptome. These variations enable bacteria to cope with environmental stresses through physiological adaptation in response to stress. This paper reviews the recent contributions of genomic and transcriptomic analyses in understanding the adaption mechanism of Escherichia coli to environmental stresses. Various genomic changes have been observed in E. coli strains in laboratory or under natural stresses, including starvation, heavy metals, acidic conditions, heat shock and antibiotics. The mutations include slight changes (one to several nucleotides), deletions, insertions, chromosomal rearrangements and variations in copy numbers. The transcriptome of E. coli largely changes due to genomic mutations. However, the transcriptional profiles vary due to variations in stress selections. Cellular adaptation to the selections is associated with transcriptional changes resulting from genomic mutations. Changes in genome and transcriptome are cooperative and jointly affect the adaptation of E. coli to different environments. This comprehensive review reveals that coordination of genome mutations and transcriptional variations needs to be explored further to provide a better understanding of the mechanisms of bacterial adaptation to stresses.

Olfactory receptor genes and chromosome 11 structural aberrations: Players or spectators?

The largest multi-gene family in metazoans is the family of olfactory receptor (OR) genes. Human ORs are organized in clusters over most chromosomes and seem to include >0.1% the human genome. Because 369 out of 856 OR genes are mapped on chromosome 11 (HSA11), we sought to determine whether they mediate structural rearrangements involving this chromosome. To this aim, we analyzed 220 specimens collected during diagnostic procedures involving structural rearrangements of chromosome 11. A total of 222 chromosomal abnormalities were included, consisting of inversions, deletions, translocations, duplications, and one insertion, detected by conventional chromosome analysis and/or fluorescence in situ hybridization (FISH) and array comparative genomic hybridization (array-CGH). We verified by bioinformatics and statistical approaches the occurrence of breakpoints in cytobands with or without OR genes. We found that OR genes are not involved in chromosome 11 reciprocal translocations, suggesting that different DNA motifs and mechanisms based on homology or non-homology recombination can cause chromosome 11 structural alterations. We also considered the proximity between the chromosomal territories of chromosome 11 and its partner chromosomes involved in the translocations by using the deposited Hi-C data concerning the possible occurrence of chromosome interactions. Interestingly, most of the breakpoints are located in regions highly involved in chromosome interactions. Further studies should be carried out to confirm the potential role of chromosome territories' proximity in promoting genome structural variation, so fundamental in our understanding of the molecular basis of medical genetics and evolutionary genetics.

The APE2 nuclease is essential for DNA double-strand break repair by microhomology-mediated end joining

Microhomology-mediated end joining (MMEJ) is an intrinsically mutagenic pathway of DNA double-strand break (DSB) repair essential for proliferation of homologous recombination (HR)-deficient tumors. Although targeting MMEJ has emerged as a powerful strategy to eliminate HR-deficient (HRD) cancers, this is limited by an incomplete understanding of the mechanism and factors required for MMEJ repair. Here, we identify the APE2 nuclease as an MMEJ effector. We show that loss of APE2 inhibits MMEJ at deprotected telomeres and at intra-chromosomal DSBs and is epistatic with Pol Theta for MMEJ activity. Mechanistically, we demonstrate that APE2 possesses intrinsic flap-cleaving activity, that its MMEJ function in cells depends on its nuclease activity, and further identify an uncharacterized domain required for its recruitment to DSBs. We conclude that this previously unappreciated role of APE2 in MMEJ contributes to the addiction of HRD cells to APE2, which could be exploited in the treatment of cancer.

PGG.SV: a whole-genome-sequencing-based structural variant resource and data analysis platform

Structural variations (SVs) play important roles in human evolution and diseases, but there is a lack of data resources concerning representative samples, especially for East Asians. Taking advantage of both next-generation sequencing and third-generation sequencing data at the whole-genome level, we developed the database PGG.SV to provide a practical platform for both regionally and globally representative structural variants. In its current version, PGG.SV archives 584 277 SVs obtained from whole-genome sequencing data of 6048 samples, including 1030 long-read sequencing genomes representing 177 global populations. PGG.SV provides (i) high-quality SVs with fine-scale and precise genomic locations in both GRCh37 and GRCh38, covering underrepresented SVs in existing sequencing and microarray data; (ii) hierarchical estimation of SV prevalence in geographical populations; (iii) informative annotations of SV-related genes, potential functions and clinical effects; (iv) an analysis platform to facilitate SV-based case-control association studies and (v) various visualization tools for understanding the SV structures in the human genome. Taken together, PGG.SV provides a user-friendly online interface, easy-to-use analysis tools and a detailed presentation of results. PGG.SV is freely accessible via https://www.biosino.org/pggsv.

Prevalence and mechanisms of somatic deletions in single human neurons during normal aging and in DNA repair disorders

Replication errors and various genotoxins cause DNA double-strand breaks (DSBs) where error-prone repair creates genomic mutations, most frequently focal deletions, and defective repair may lead to neurodegeneration. Despite its pathophysiological importance, the extent to which faulty DSB repair alters the genome, and the mechanisms by which mutations arise, have not been systematically examined reflecting ineffective methods. Here, we develop PhaseDel, a computational method to detect focal deletions and characterize underlying mechanisms in single-cell whole genome sequences (scWGS). We analyzed high-coverage scWGS of 107 single neurons from 18 neurotypical individuals of various ages, and found that somatic deletions increased with age and in highly expressed genes in human brain. Our analysis of 50 single neurons from DNA repair-deficient diseases with progressive neurodegeneration (Cockayne syndrome, Xeroderma pigmentosum, and Ataxia telangiectasia) reveals elevated somatic deletions compared to age-matched controls. Distinctive mechanistic signatures and transcriptional associations suggest roles for somatic deletions in neurodegeneration.

Integrating whole-genome sequencing with multi-omic data reveals the impact of structural variants on gene regulation in the human brain

Structural variants (SVs), genomic rearrangements of >50 bp, are an important source of genetic diversity and have been linked to many diseases. However, it remains unclear how they modulate human brain function and disease risk. Here, we report 170,996 SVs discovered using 1,760 short-read whole genomes from aged adults and Alzheimer’s disease individuals. By applying quantitative trait locus (SV-xQTL) analyses, we quantified the impact of cis-acting SVs on histone modifications, gene expression, splicing, and protein abundance in post-mortem brain tissues. More than 3,200 SVs were associated with at least one molecular phenotype. We found reproducibility of 65–99% SV-eQTLs across cohorts and brain regions. SV associations with mRNA and proteins shared the same direction of effect in more than 87% of SV-gene pairs. Mediation analysis showed ~8% of SV-eQTLs mediated by histone acetylation, and ~11% by splicing. Additionally, associations of SVs with progressive supranuclear palsy identified previously known and novel SVs.

Distinct sequence features underlie microdeletions and gross deletions in the human genome

Microdeletions and gross deletions are important causes (~20%) of human inherited disease and their genomic locations are strongly influenced by the local DNA sequence environment. This notwithstanding, no study has systematically examined their underlying generative mechanisms. Here, we obtained 42,098 pathogenic microdeletions and gross deletions from the Human Gene Mutation Database (HGMD) that together form a continuum of germline deletions ranging in size from 1 to 28,394,429 bp. We analyzed the DNA sequence within 1 kb of the breakpoint junctions and found that the frequencies of non‐B DNA‐forming repeats, GC‐content, and the presence of seven of 78 specific sequence motifs in the vicinity of pathogenic deletions correlated with deletion length for deletions of length ≤30 bp. Further, we found that the presence of DR, GQ, and STR repeats is important for the formation of longer deletions (>30 bp) but not for the formation of shorter deletions (≤30 bp) while significantly (χ², p < 2E−16) more microhomologies were identified flanking short deletions than long deletions (length >30 bp). We provide evidence to support a functional distinction between microdeletions and gross deletions. Finally, we propose that a deletion length cut‐off of 25–30 bp may serve as an objective means to functionally distinguish microdeletions from gross deletions.

Long-read technologies identify a hidden inverted duplication in a family with choroideremia

The lack of molecular diagnoses in rare genetic diseases can be explained by limitations of current standard genomic technologies. Upcoming long-read techniques have complementary strengths to overcome these limitations, with a particular strength in identifying structural variants. By using optical genome mapping and long-read sequencing, we aimed to identify the pathogenic variant in a large family with X-linked choroideremia. In this family, aberrant splicing of exon 12 of the choroideremia gene CHM was detected in 2003, but the underlying genomic defect remained elusive. Optical genome mapping and long-read sequencing approaches now revealed an intragenic 1,752 bp inverted duplication including exon 12 and surrounding regions, located downstream of the wild-type copy of exon 12. Both breakpoint junctions were confirmed with Sanger sequencing and segregate with the X-linked inheritance in the family. The breakpoint junctions displayed sequence microhomology suggestive for an erroneous replication mechanism as the origin of the structural variant. The inverted duplication is predicted to result in a hairpin formation of the pre-mRNA with the wild-type exon 12, leading to exon skipping in the mature mRNA. The identified inverted duplication is deemed the hidden pathogenic cause of disease in this family. Our study shows that optical genome mapping and long-read sequencing have significant potential for the identification of (hidden) structural variants in rare genetic diseases.

Machine-learning predicts genomic determinants of meiosis-driven structural variation in a eukaryotic pathogen

Species harbor extensive structural variation underpinning recent adaptive evolution. However, the causality between genomic features and the induction of new rearrangements is poorly established. Here, we analyze a global set of telomere-to-telomere genome assemblies of a fungal pathogen of wheat to establish a nucleotide-level map of structural variation. We show that the recent emergence of pesticide resistance has been disproportionally driven by rearrangements. We use machine learning to train a model on structural variation events based on 30 chromosomal sequence features. We show that base composition and gene density are the major determinants of structural variation. Retrotransposons explain most inversion, indel and duplication events. We apply our model to Arabidopsis thaliana and show that our approach extends to more complex genomes. Finally, we analyze complete genomes of haploid offspring in a four-generation pedigree. Meiotic crossover locations are enriched for new rearrangements consistent with crossovers being mutational hotspots. The model trained on species-wide structural variation accurately predicts the position of >74% of newly generated variants along the pedigree. The predictive power highlights causality between specific sequence features and the induction of chromosomal rearrangements. Our work demonstrates that training sequence-derived models can accurately identify regions of intrinsic DNA instability in eukaryotic genomes.

LongAGE: defining breakpoints of genomic structural variants through optimal and memory efficient alignments of long reads

Summary

Defining the precise location of structural variations (SVs) at single-nucleotide breakpoint resolution is a challenging problem due to large gaps in alignment. Previously, Alignment with Gap Excision (AGE) enabled us to define breakpoints of SVs at single-nucleotide resolution; however, AGE requires a vast amount of memory when aligning a pair of long sequences. To address this, we developed a memory-efficient implementation—LongAGE—based on the classical Hirschberg algorithm. We demonstrate an application of LongAGE for resolving breakpoints of SVs embedded into segmental duplications on Pacific Biosciences (PacBio) reads that can be longer than 10 kb. Furthermore, we observed different breakpoints for a deletion and a duplication in the same locus, providing direct evidence that such multi-allelic copy number variants (mCNVs) arise from two or more independent ancestral mutations.

Availability and implementation

LongAGE is implemented in C++ and available on Github at https://github.com/Coaxecva/LongAGE.

Supplementary information

Supplementary data are available at Bioinformatics online.

The Cause of Hereditary Hearing Loss in GJB2 Heterozygotes-A Comprehensive Study of the GJB2/DFNB1 Region

Hearing loss is a genetically heterogeneous sensory defect, and the frequent causes are biallelic pathogenic variants in the GJB2 gene. However, patients carrying only one heterozygous pathogenic (monoallelic) GJB2 variant represent a long-lasting diagnostic problem. Interestingly, previous results showed that individuals with a heterozygous pathogenic GJB2 variant are two times more prevalent among those with hearing loss compared to normal-hearing individuals. This excess among patients led us to hypothesize that there could be another pathogenic variant in the GJB2 region/DFNB1 locus. A hitherto undiscovered variant could, in part, explain the cause of hearing loss in patients and would mean reclassifying them as patients with GJB2 biallelic pathogenic variants. In order to detect an unknown causal variant, we examined 28 patients using NGS with probes that continuously cover the 0.4 Mb in the DFNB1 region. An additional 49 patients were examined by WES to uncover only carriers. We did not reveal a second pathogenic variant in the DFNB1 region. However, in 19% of the WES-examined patients, the cause of hearing loss was found to be in genes other than the GJB2. We present evidence to show that a substantial number of patients are carriers of the GJB2 pathogenic variant, albeit only by chance.

Intronic Breakpoint Signatures Enhance Detection and Characterization of Clinically Relevant Germline Structural Variants

The relevance of large copy number variants (CNVs) to hereditary disorders has been long recognized, and population sequencing efforts have chronicled many common structural variants (SVs). However, limited data are available on the clinical contribution of rare germline SVs. Here, a detailed characterization of SVs identified using targeted next-generation sequencing was performed. Across 50 genes associated with hereditary cancer and cardiovascular disorders, a minimum of 828 unique SVs were reported, including 584 fully characterized SVs. Almost 40% of CNVs were <5 kb, with one in three deletions impacting a single exon. Additionally, 36 mid-range deletions/duplications (50 to 250 bp), 21 mobile element insertions, 6 inversions, and 27 complex rearrangements were detected. This data set was used to model SV detection in a bioinformatics pipeline solely relying on read depth, which revealed that genome sequencing (30×) allows detection of 71%, a 500× panel only targeting coding regions 53%, and exome sequencing (100×) <20% of characterized SVs. SVs accounted for 14.1% of all unique pathogenic variants, supporting the importance of SVs in hereditary disorders. Robust SV detection requires an ensemble of variant-calling algorithms that utilize sequencing of intronic regions. These algorithms should use distinct data features representative of each class of mutational mechanism, including recombination between two sequences sharing high similarity, covariants inserted between CNV breakpoints, and complex rearrangements containing inverted sequences.

Detecting Causal Variants in Mendelian Disorders Using Whole-Genome Sequencing

Increasingly affordable sequencing technologies are revolutionizing the field of genomic medicine. It is now feasible to interrogate all major classes of variation in an individual across the entire genome for less than $1000 USD. While the generation of patient sequence information using these technologies has become routine, the analysis and interpretation of this data remains the greatest obstacle to widespread clinical implementation. This chapter summarizes the steps to identify, annotate, and prioritize variant information required for clinical report generation. We discuss methods to detect each variant class and describe strategies to increase the likelihood of detecting causal variant(s) in Mendelian disease. Lastly, we describe a sample workflow for synthesizing large amount of genetic information into concise clinical reports.

PopDel identifies medium-size deletions simultaneously in tens of thousands of genomes

Thousands of genomic structural variants (SVs) segregate in the human population and can impact phenotypic traits and diseases. Their identification in whole-genome sequence data of large cohorts is a major computational challenge. Most current approaches identify SVs in single genomes and afterwards merge the identified variants into a joint call set across many genomes. We describe the approach PopDel, which directly identifies deletions of about 500 to at least 10,000 bp in length in data of many genomes jointly, eliminating the need for subsequent variant merging. PopDel scales to tens of thousands of genomes as we demonstrate in evaluations on up to 49,962 genomes. We show that PopDel reliably reports common, rare and de novo deletions. On genomes with available high-confidence reference call sets PopDel shows excellent recall and precision. Genotype inheritance patterns in up to 6794 trios indicate that genotypes predicted by PopDel are more reliable than those of previous SV callers. Furthermore, PopDel's running time is competitive with the fastest tested previous tools. The demonstrated scalability and accuracy of PopDel enables routine scans for deletions in large-scale sequencing studies.

Insertion variants missing in the human reference genome are widespread among human populations

Background

Structural variants comprise diverse genomic arrangements including deletions, insertions, inversions, and translocations, which can generally be detected in humans through sequence comparison to the reference genome. Among structural variants, insertions are the least frequently identified variants, mainly due to ascertainment bias in the reference genome, lack of previous sequence knowledge, and low complexity of typical insertion sequences. Though recent developments in long-read sequencing deliver promise in annotating individual non-reference insertions, population-level catalogues on non-reference insertion variants have not been identified and the possible functional roles of these hidden variants remain elusive.

Results

To detect non-reference insertion variants, we developed a pipeline, InserTag, which generates non-reference contigs by local de novo assembly and then infers the full-sequence of insertion variants by tracing contigs from non-human primates and other human genome assemblies. Application of the pipeline to data from 2535 individuals of the 1000 Genomes Project helped identify 1696 non-reference insertion variants and re-classify the variants as retention of ancestral sequences or novel sequence insertions based on the ancestral state. Genotyping of the variants showed that individuals had, on average, 0.92-Mbp sequences missing from the reference genome, 92% of the variants were common (allele frequency > 5%) among human populations, and more than half of the variants were major alleles. Among human populations, African populations were the most divergent and had the most non-reference sequences, which was attributed to the greater prevalence of high-frequency insertion variants. The subsets of insertion variants were in high linkage disequilibrium with phenotype-associated SNPs and showed signals of recent continent-specific selection.

Conclusions

Non-reference insertion variants represent an important type of genetic variation in the human population, and our developed pipeline, InserTag, provides the frameworks for the detection and genotyping of non-reference sequences missing from human populations.

Supplementary information

Supplementary information accompanies this paper at 10.1186/s12915-020-00894-1.

Efficient detection of copy-number variations using exome data: Batch- and sex-based analyses

Many algorithms to detect copy number variations (CNVs) using exome sequencing (ES) data have been reported and evaluated on their sensitivity and specificity, reproducibility, and precision. However, operational optimization of such algorithms for a better performance has not been fully addressed. ES of 1199 samples including 763 patients with different disease profiles was performed. ES data were analyzed to detect CNVs by both the eXome Hidden Markov Model (XHMM) and modified Nord's method. To efficiently detect rare CNVs, we aimed to decrease sequencing biases by analyzing, at the same time, the data of all unrelated samples sequenced in the same flow cell as a batch, and to eliminate sex effects of X-linked CNVs by analyzing female and male sequences separately. We also applied several filtering steps for more efficient CNV selection. The average number of CNVs detected in one sample was <5. This optimization together with targeted CNV analysis by Nord's method identified pathogenic/likely pathogenic CNVs in 34 patients (4.5%, 34/763). In particular, among 142 patients with epilepsy, the current protocol detected clinically relevant CNVs in 19 (13.4%) patients, whereas the previous protocol identified them in only 14 (9.9%) patients. Thus, this batch-based XHMM analysis efficiently selected rare pathogenic CNVs in genetic diseases.

SVFX: a machine learning framework to quantify the pathogenicity of structural variants

There is a lack of approaches for identifying pathogenic genomic structural variants (SVs) although they play a crucial role in many diseases. We present a mechanism-agnostic machine learning-based workflow, called SVFX, to assign pathogenicity scores to somatic and germline SVs. In particular, we generate somatic and germline training models, which include genomic, epigenomic, and conservation-based features, for SV call sets in diseased and healthy individuals. We then apply SVFX to SVs in cancer and other diseases; SVFX achieves high accuracy in identifying pathogenic SVs. Predicted pathogenic SVs in cancer cohorts are enriched among known cancer genes and many cancer-related pathways.

Complex mosaic structural variations in human fetal brains

Somatic mosaicism, manifesting as single nucleotide variants (SNVs), mobile element insertions, and structural changes in the DNA, is a common phenomenon in human brain cells, with potential functional consequences. Using a clonal approach, we previously detected 200-400 mosaic SNVs per cell in three human fetal brains (15-21 wk postconception). However, structural variation in the human fetal brain has not yet been investigated. Here, we discover and validate four mosaic structural variants (SVs) in the same brains and resolve their precise breakpoints. The SVs were of kilobase scale and complex, consisting of deletion(s) and rearranged genomic fragments, which sometimes originated from different chromosomes. Sequences at the breakpoints of these rearrangements had microhomologies, suggesting their origin from replication errors. One SV was found in two clones, and we timed its origin to ∼14 wk postconception. No large scale mosaic copy number variants (CNVs) were detectable in normal fetal human brains, suggesting that previously reported megabase-scale CNVs in neurons arise at later stages of development. By reanalysis of public single nuclei data from adult brain neurons, we detected an extrachromosomal circular DNA event. Our study reveals the existence of mosaic SVs in the developing human brain, likely arising from cell proliferation during mid-neurogenesis. Although relatively rare compared to SNVs and present in ∼10% of neurons, SVs in developing human brain affect a comparable number of bases in the genome (∼6200 vs. ∼4000 bp), implying that they may have similar functional consequences.

Meiotic recombination profiling of interspecific hybrid F1 tomato pollen by linked read sequencing

Genome wide screening of pooled pollen samples from a single interspecific F1 hybrid obtained from a cross between tomato, Solanum lycopersicum and its wild relative, Solanum pimpinellifolium using linked read sequencing of the haploid nuclei, allowed profiling of the crossover (CO) and gene conversion (GC) landscape. We observed a striking overlap between cold regions of CO in the male gametes and our previously established F6 recombinant inbred lines (RILs) population. COs were overrepresented in non-coding regions in the gene promoter and 5'UTR regions of genes. Poly-A/T and AT rich motifs were found enriched in 1 kb promoter regions flanking the CO sites. Non-crossover associated allelic and ectopic GCs were detected in most chromosomes, confirming that besides CO, GC represents also a source for genetic diversity and genome plasticity in tomato. Furthermore, we identified processed break junctions pointing at the involvement of both homology directed and non-homology directed repair pathways, suggesting a recombination machinery in tomato that is more complex than currently anticipated.

Disruption of chromatin folding domains by somatic genomic rearrangements in human cancer

Chromatin is folded into successive layers to organize linear DNA. Genes within the same topologically associating domains (TADs) demonstrate similar expression and histone-modification profiles, and boundaries separating different domains have important roles in reinforcing the stability of these features. Indeed, domain disruptions in human cancers can lead to misregulation of gene expression. However, the frequency of domain disruptions in human cancers remains unclear. Here, as part of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA), which aggregated whole-genome sequencing data from 2,658 cancers across 38 tumor types, we analyzed 288,457 somatic structural variations (SVs) to understand the distributions and effects of SVs across TADs. Notably, SVs can lead to the fusion of discrete TADs, and complex rearrangements markedly change chromatin folding maps in the cancer genomes. Notably, only 14% of the boundary deletions resulted in a change in expression in nearby genes of more than twofold.

Deletion in the Cobalamin Synthetase W Domain-Containing Protein 1 Gene Is associated with Congenital Anomalies of the Kidney and Urinary Tract

BACKGROUND

Researchers have identified about 40 genes with mutations that result in the most common cause of CKD in children, congenital anomalies of the kidney and urinary tract (CAKUT), but approximately 85% of patients with CAKUT lack mutations in these genes. The anomalies that comprise CAKUT are clinically heterogenous, and thought to be caused by disturbances at different points in kidney development. However, identification of novel CAKUT-causing genes remains difficult because of their variable expressivity, incomplete penetrance, and heterogeneity.

METHODS

We investigated two generations of a family that included two siblings with CAKUT. Although the parents and another child were healthy, the two affected siblings presented the same manifestations, unilateral renal agenesis and contralateral renal hypoplasia. To search for a novel causative gene of CAKUT, we performed whole-exome and whole-genome sequencing of DNA from the family members. We also generated two lines of genetically modified mice with a gene deletion present only in the affected siblings, and performed immunohistochemical and phenotypic analyses of these mice.

RESULTS

We found that the affected siblings, but not healthy family members, had a homozygous deletion in the Cobalamin Synthetase W Domain-Containing Protein 1 (CBWD1) gene. Whole-genome sequencing uncovered genomic breakpoints, which involved exon 1 of CBWD1, harboring the initiating codon. Immunohistochemical analysis revealed high expression of Cbwd1 in the nuclei of the ureteric bud cells in the developing kidneys. Cbwd1-deficient mice showed CAKUT phenotypes, including hydronephrosis, hydroureters, and duplicated ureters.

CONCLUSIONS

The identification of a deletion in CBWD1 gene in two siblings with CAKUT implies a role for CBWD1 in the etiology of some cases of CAKUT.

LEMON: a method to construct the local strains at horizontal gene transfer sites in gut metagenomics

BACKGROUND

Horizontal Gene Transfer (HGT) refers to the transfer of genetic materials between organisms through mechanisms other than parent-offspring inheritance. HGTs may affect human health through a large number of microorganisms, especially the gut microbiomes which the human body harbors. The transferred segments may lead to complicated local genome structural variations. Details of the local genome structure can elucidate the effects of the HGTs.

RESULTS

In this work, we propose a graph-based method to reconstruct the local strains from the gut metagenomics data at the HGT sites. The method is implemented in a package named LEMON. The simulated results indicate that the method can identify transferred segments accurately on reference sequences of the microbiome. Simulation results illustrate that LEMON could recover local strains with complicated structure variation. Furthermore, the gene fusion points detected in real data near HGT breakpoints validate the accuracy of LEMON. Some strains reconstructed by LEMON have a replication time profile with lower standard error, which demonstrates HGT events recovered by LEMON is reliable.

CONCLUSIONS

Through LEMON we could reconstruct the sequence structure of bacteria, which harbors HGT events. This helps us to study gene flow among different microbial species.

Chromatin organization modulates the origin of heritable structural variations in human genome

Structural variations (SVs) in the human genome originate from different mechanisms related to DNA repair, replication errors, and retrotransposition. Our analyses of 26 927 SVs from the 1000 Genomes Project revealed differential distributions and consequences of SVs of different origin, e.g. deletions from non-allelic homologous recombination (NAHR) are more prone to disrupt chromatin organization while processed pseudogenes can create accessible chromatin. Spontaneous double stranded breaks (DSBs) are the best predictor of enrichment of NAHR deletions in open chromatin. This evidence, along with strong physical interaction of NAHR breakpoints belonging to the same deletion suggests that majority of NAHR deletions are non-meiotic i.e. originate from errors during homology directed repair (HDR) of spontaneous DSBs. In turn, the origin of the spontaneous DSBs is associated with transcription factor binding in accessible chromatin revealing the vulnerability of functional, open chromatin. The chromatin itself is enriched with repeats, particularly fixed Alu elements that provide the homology required to maintain stability via HDR. Through co-localization of fixed Alus and NAHR deletions in open chromatin we hypothesize that old Alu expansion had a stabilizing role on the human genome.

Templated Insertions: A Smoking Gun for Polymerase Theta-Mediated End Joining

A recognized source of disease-causing genome alterations is erroneous repair of broken chromosomes, which can be executed by two distinct mechanisms: non-homologous end joining (NHEJ) and the recently discovered polymerase theta-mediated end joining (TMEJ) pathway. While TMEJ has previously been considered to act as an alternative mechanism backing up NHEJ, recent work points to a role for TMEJ in the repair of replication-associated DNA breaks that are excluded from repair through homologous recombination. Because of its mode of action, TMEJ is intrinsically mutagenic and sometimes leaves behind a recognizable genomic scar when joining chromosome break ends (i.e., 'templated insertions'). This review article focuses on the intriguing observation that this polymerase theta signature is frequently observed in disease alleles, arguing for a prominent role of this double-strand break repair pathway in genome diversification and disease-causing spontaneous mutagenesis in humans.

Loose ends: almost one in five human genes still have unresolved coding status

Seventeen years after the sequencing of the human genome, the human proteome is still under revision. One in eight of the 22 210 coding genes listed by the Ensembl/GENCODE, RefSeq and UniProtKB reference databases are annotated differently across the three sets. We have carried out an in-depth investigation on the 2764 genes classified as coding by one or more sets of manual curators and not coding by others. Data from large-scale genetic variation analyses suggests that most are not under protein-like purifying selection and so are unlikely to code for functional proteins. A further 1470 genes annotated as coding in all three reference sets have characteristics that are typical of non-coding genes or pseudogenes. These potential non-coding genes also appear to be undergoing neutral evolution and have considerably less supporting transcript and protein evidence than other coding genes. We believe that the three reference databases currently overestimate the number of human coding genes by at least 2000, complicating and adding noise to large-scale biomedical experiments. Determining which potential non-coding genes do not code for proteins is a difficult but vitally important task since the human reference proteome is a fundamental pillar of most basic research and supports almost all large-scale biomedical projects.

Genome sequencing-the dawn of a game-changing era

The development of genome sequencing technologies has revolutionized the biological sciences in ways which could not have been imagined at the time. This article sets out to document the dawning of the age of genomics and to consider the impact of this revolution on biological investigation, our understanding of life, and the relationship between science and society.

Comprehensive evaluation of structural variation detection algorithms for whole genome sequencing

BACKGROUND

Structural variations (SVs) or copy number variations (CNVs) greatly impact the functions of the genes encoded in the genome and are responsible for diverse human diseases. Although a number of existing SV detection algorithms can detect many types of SVs using whole genome sequencing (WGS) data, no single algorithm can call every type of SVs with high precision and high recall.

RESULTS

We comprehensively evaluate the performance of 69 existing SV detection algorithms using multiple simulated and real WGS datasets. The results highlight a subset of algorithms that accurately call SVs depending on specific types and size ranges of the SVs and that accurately determine breakpoints, sizes, and genotypes of the SVs. We enumerate potential good algorithms for each SV category, among which GRIDSS, Lumpy, SVseq2, SoftSV, Manta, and Wham are better algorithms in deletion or duplication categories. To improve the accuracy of SV calling, we systematically evaluate the accuracy of overlapping calls between possible combinations of algorithms for every type and size range of SVs. The results demonstrate that both the precision and recall for overlapping calls vary depending on the combinations of specific algorithms rather than the combinations of methods used in the algorithms.

CONCLUSION

These results suggest that careful selection of the algorithms for each type and size range of SVs is required for accurate calling of SVs. The selection of specific pairs of algorithms for overlapping calls promises to effectively improve the SV detection accuracy.

G-quadruplexes may determine the landscape of recombination in HSV-1

Background

Several lines of evidence suggest that recombination plays a central role in replication and evolution of herpes simplex virus-1 (HSV-1). G-quadruplex (G4)-motifs have been linked to recombination events in human and microbial genomes, but their role in recombination has not been studied in DNA viruses.

Results

The availability of near full-length sequences from 40 HSV-1 recombinant strains with exact position of the recombination breakpoints provided us with a unique opportunity to investigate the role of G4-motifs in recombination among herpes viruses. We mapped the G4-motifs in the parental and all the 40 recombinant strains. Interestingly, the genome-wide distribution of breakpoints closely mirrors the G4 densities in the HSV-1 genome; regions of the genome with higher G4 densities had higher number of recombination breakpoints. Biophysical characterization of oligonucleotides from a subset of predicted G4-motifs confirmed the formation of G-quadruplex structures. Our analysis also reveals that G4-motifs are enriched in regions flanking the recombination breakpoints. Interestingly, about 11% of breakpoints lie within a G4-motif, making these DNA secondary structures hotspots for recombination in the HSV-1 genome. Breakpoints within G4-motifs predominantly lie within G4-clusters rather than individual G4-motifs. Of note, we identified the terminal guanosine of G4-clusters at the boundaries of the U_L (unique long) region on either side of the OriL (origin of replication within U_L) represented the commonest breakpoint among the HSV-1 recombinants.

Conclusion

Our findings suggest a correlation between the HSV-1 recombination landscape and the distribution of G4-motifs and G4-clusters, with possible implications for the evolution of DNA viruses.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-5731-0) contains supplementary material, which is available to authorized users.

Fine-Scale Characterization of Genomic Structural Variation in the Human Genome Reveals Adaptive and Biomedically Relevant Hotspots

Genomic structural variants (SVs) are distributed nonrandomly across the human genome. The "hotspots" of SVs have been implicated in evolutionary innovations, as well as medical conditions. However, the evolutionary and biomedical features of these hotspots remain incompletely understood. Here, we analyzed data from 2,504 genomes to construct a refined map of 1,148 SV hotspots in human genomes. We confirmed that segmental duplication-related nonallelic homologous recombination is an important mechanistic driver of SV hotspot formation. However, to our surprise, we also found that a majority of SVs in hotspots do not form through such recombination-based mechanisms, suggesting diverse mechanistic and selective forces shaping hotspots. Indeed, our evolutionary analyses showed that the majority of SV hotspots are within gene-poor regions and evolve under relaxed negative selection or neutrality. However, we still found a small subset of SV hotspots harboring genes that are enriched for anthropologically crucial functions and evolve under geography-specific and balancing adaptive forces. These include two independent hotspots on different chromosomes affecting alpha and beta hemoglobin gene clusters. Biomedically, we found that the SV hotspots coincide with breakpoints of clinically relevant, large de novo SVs, significantly more often than genome-wide expectations. For example, we showed that the breakpoints of multiple large SVs, which lead to idiopathic short stature, coincide with SV hotspots. Therefore, the mutational instability in SV hotpots likely enables chromosomal breaks that lead to pathogenic structural variation formations. Overall, our study contributes to a better understanding of the mutational and adaptive landscape of the genome.

Megabase Length Hypermutation Accompanies Human Structural Variation at 17p11.2

DNA rearrangements resulting in human genome structural variants (SVs) are caused by diverse mutational mechanisms. We used long- and short-read sequencing technologies to investigate end products of de novo chromosome 17p11.2 rearrangements and query the molecular mechanisms underlying both recurrent and non-recurrent events. Evidence for an increased rate of clustered single-nucleotide variant (SNV) mutation in cis with non-recurrent rearrangements was found. Indel and SNV formation are associated with both copy-number gains and losses of 17p11.2, occur up to ∼1 Mb away from the breakpoint junctions, and favor C > G transversion substitutions; results suggest that single-stranded DNA is formed during the genesis of the SV and provide compelling support for a microhomology-mediated break-induced replication (MMBIR) mechanism for SV formation. Our data show an additional mutational burden of MMBIR consisting of hypermutation confined to the locus and manifesting as SNVs and indels predominantly within genes.

Intronic CNVs and gene expression variation in human populations

Introns can be extraordinarily large and they account for the majority of the DNA sequence in human genes. However, little is known about their population patterns of structural variation and their functional implication. By combining the most extensive maps of CNVs in human populations, we have found that intronic losses are the most frequent copy number variants (CNVs) in protein-coding genes in human, with 12,986 intronic deletions, affecting 4,147 genes (including 1,154 essential genes and 1,638 disease-related genes). This intronic length variation results in dozens of genes showing extreme population variability in size, with 40 genes with 10 or more different sizes and up to 150 allelic sizes. Intronic losses are frequent in evolutionarily ancient genes that are highly conserved at the protein sequence level. This result contrasts with losses overlapping exons, which are observed less often than expected by chance and almost exclusively affect primate-specific genes. An integrated analysis of CNVs and RNA-seq data showed that intronic loss can be associated with significant differences in gene expression levels in the population (CNV-eQTLs). These intronic CNV-eQTLs regions are enriched for intronic enhancers and can be associated with expression differences of other genes showing long distance intron-promoter 3D interactions. Our data suggests that intronic structural variation of protein-coding genes makes an important contribution to the variability of gene expression and splicing in human populations.

Molecular characterization of PRKN structural variations identified through whole-genome sequencing

Background

Early‐onset Parkinson's disease (PD) is the most common inherited form of parkinsonism, with the PRKN gene being the most frequently identified mutated. Exon rearrangements, identified in about 43.2% of the reported PD patients and with higher frequency in specific ethnicities, are the most prevalent PRKN mutations reported to date in PD patients.

Methods

In this study, three consanguineous families with early‐onset PD were subjected to whole‐genome sequencing (WGS) analyses that were followed by Sanger sequencing and droplet digital PCR to validate and confirm the disease segregation of the identified genomic variations and to determine their parental origin.

Results

Five different PRKN structural variations (SVs) were identified. Because the genomic sequences surrounding the break points of the identified SVs might hold important information about their genesis, these were also characterized for the presence of homology and repeated sequences.

Conclusion

We concluded that all identified PRKN SVs might originate through retrotransposition events.

The Genome of the Human Pathogen Candida albicans Is Shaped by Mutation and Cryptic Sexual Recombination

The opportunistic fungal pathogen Candida albicans lacks a conventional sexual program and is thought to evolve, at least primarily, through the clonal acquisition of genetic changes. Here, we performed an analysis of heterozygous diploid genomes from 21 clinical isolates to determine the natural evolutionary processes acting on the C. albicans genome. Mutation and recombination shaped the genomic landscape among the C. albicans isolates. Strain-specific single nucleotide polymorphisms (SNPs) and insertions/deletions (indels) clustered across the genome. Additionally, loss-of-heterozygosity (LOH) events contributed substantially to genotypic variation, with most long-tract LOH events extending to the ends of the chromosomes suggestive of repair via break-induced replication. Consistent with a model of inheritance by descent, most polymorphisms were shared between closely related strains. However, some isolates contained highly mosaic genomes consistent with strains having experienced interclade recombination during their evolutionary history. A detailed examination of mitochondrial genomes also revealed clear examples of interclade recombination among sequenced strains. These analyses therefore establish that both (para)sexual recombination and mitotic mutational processes drive evolution of this important pathogen. To further facilitate the study of C. albicans genomes, we also introduce an online platform, SNPMap, to examine SNP patterns in sequenced isolates.IMPORTANCE Mutations introduce variation into the genome upon which selection can act. Defining the nature of these changes is critical for determining species evolution, as well as for understanding the genetic changes driving important cellular processes. The heterozygous diploid fungus Candida albicans is both a frequent commensal organism and a prevalent opportunistic pathogen. A prevailing theory is that C. albicans evolves primarily through the gradual buildup of mitotic mutations, and a pressing issue is whether sexual or parasexual processes also operate within natural populations. Here, we establish that the C. albicans genome evolves by a combination of localized mutation and both short-tract and long-tract loss-of-heterozygosity (LOH) events within the sequenced isolates. Mutations are more prevalent within noncoding and heterozygous regions and LOH increases towards chromosome ends. Furthermore, we provide evidence for genetic exchange between isolates, establishing that sexual or parasexual processes have contributed to the diversity of both nuclear and mitochondrial genomes.

Co-occurrence of schwannomatosis and rhabdoid tumor predisposition syndrome 1

BACKGROUND

The clinical phenotype associated with germline SMARCB1 mutations has as yet not been fully documented. It is known that germline SMARCB1 mutations may cause rhabdoid tumor predisposition syndrome (RTPS1) or schwannomatosis. However, the co-occurrence of rhabdoid tumor and schwannomas in the same patient has not so far been reported.

METHODS

We investigated a family with members harboring a germline SMARCB1 deletion by means of whole-body MRI as well as high-resolution microstructural magnetic resonance neurography (MRN). Breakpoint-spanning PCRs were performed to characterize the SMARCB1 deletion and its segregation in the family.

RESULTS

The index patient of this family was in complete continuous remission for an atypical teratoid/rhabdoid tumor (AT/RT) treated at the age of 2 years. However, at the age of 21 years, she exhibited paraparesis of her legs and MRI investigations revealed multiple intrathoracic and spinal schwannomas. Breakpoint-spanning PCRs indicated that the germline deletion segregating in the family encompasses 6.4-kb and includes parts of SMARCB1 intron 7, exons 8-9 and 3.3-kb located telomeric to exon 9 including the SMARCB1 3' UTR. The analysis of sequences at the deletion breakpoints showed that the deletion has been caused by replication errors including template-switching. The patient had inherited the deletion from her 56-year-old healthy mother who did not exhibit schwannomas or other tumors as determined by whole-body MRI. However, MRN of the peripheral nerves of the mother's extremities revealed multiple fascicular microlesions which have been previously identified as indicative of schwannomatosis-associated subclinical peripheral nerve pathology.

CONCLUSION

The occurrence of schwannomatosis-associated clinical symptoms independent of the AT/RT as the primary disease should be considered in long-term survivors of AT/RT. Furthermore, our investigations indicate that germline SMARCB1 mutation carriers not presenting RTs or schwannomatosis-associated clinical symptoms may nevertheless exhibit peripheral nerve pathology as revealed by MRN.

Genome-wide analysis of structural variants reveals genetic differences in Chinese pigs

Pigs have experienced long-term selections, resulting in dramatic phenotypic changes. Structural variants (SVs) are reported to exert extensive impacts on phenotypic changes. We built a high resolution and informative SV map based on high-depth sequencing data from 66 Chinese domestic and wild pigs. We inferred the SV formation mechanisms in the pig genome and used SVs as materials to perform a population-level analysis. We detected the selection signals on chromosome X for northern Chinese domestic pigs, as well as the differentiated loci across the whole genome. Analysis showed that these loci differ between southern and northern Chinese domestic pigs. Our results based on SVs provide new insights into genetic differences in Chinese pigs.

An efficient and tunable parameter to improve variant calling for whole genome and exome sequencing data

Next generation sequencing (NGS) has traditionally been performed in various fields including agricultural to clinical and there are so many sequencing platforms available in order to obtain accurate and consistent results. However, these platforms showed amplification bias when facilitating variant calls in personal genomes. Here, we sequenced whole genomes and whole exomes from ten Korean individuals using Illumina and Ion Proton, respectively to find the vulnerability and accuracy of NGS platform in the GC rich/poor area. Overall, a total of 1013 Gb reads from Illumina and ~39.1 Gb reads from Ion Proton were analyzed using BWA-GATK variant calling pipeline. Furthermore, conjunction with the VQSR tool and detailed filtering strategies, we achieved high-quality variants. Finally, each of the ten variants from Illumina only, Ion Proton only, and intersection was selected for Sanger validation. The validation results revealed that Illumina platform showed higher accuracy than Ion Proton. The described filtering methods are advantageous for large population-based whole genome studies designed to identify common and rare variations associated with complex diseases.

Landscape and variation of novel retroduplications in 26 human populations

Retroduplications come from reverse transcription of mRNAs and their insertion back into the genome. Here, we performed comprehensive discovery and analysis of retroduplications in a large cohort of 2,535 individuals from 26 human populations, as part of 1000 Genomes Phase 3. We developed an integrated approach to discover novel retroduplications combining high-coverage exome and low-coverage whole-genome sequencing data, utilizing information from both exon-exon junctions and discordant paired-end reads. We found 503 parent genes having novel retroduplications absent from the reference genome. Based solely on retroduplication variation, we built phylogenetic trees of human populations; these represent superpopulation structure well and indicate that variable retroduplications are effective population markers. We further identified 43 retroduplication parent genes differentiating superpopulations. This group contains several interesting insertion events, including a SLMO2 retroduplication and insertion into CAV3, which has a potential disease association. We also found retroduplications to be associated with a variety of genomic features: (1) Insertion sites were correlated with regular nucleosome positioning. (2) They, predictably, tend to avoid conserved functional regions, such as exons, but, somewhat surprisingly, also avoid introns. (3) Retroduplications tend to be co-inserted with young L1 elements, indicating recent retrotranspositional activity, and (4) they have a weak tendency to originate from highly expressed parent genes. Our investigation provides insight into the functional impact and association with genomic elements of retroduplications. We anticipate our approach and analytical methodology to have application in a more clinical context, where exome sequencing data is abundant and the discovery of retroduplications can potentially improve the accuracy of SNP calling.

Non-homologous DNA end joining and alternative pathways to double-strand break repair

DNA double-strand breaks (DSBs) are the most dangerous type of DNA damage because they can result in the loss of large chromosomal regions. In all mammalian cells, DSBs that occur throughout the cell cycle are repaired predominantly by the non-homologous DNA end joining (NHEJ) pathway. Defects in NHEJ result in sensitivity to ionizing radiation and the ablation of lymphocytes. The NHEJ pathway utilizes proteins that recognize, resect, polymerize and ligate the DNA ends in a flexible manner. This flexibility permits NHEJ to function on a wide range of DNA-end configurations, with the resulting repaired DNA junctions often containing mutations. In this Review, we discuss the most recent findings regarding the relative involvement of the different NHEJ proteins in the repair of various DNA-end configurations. We also discuss the shunting of DNA-end repair to the auxiliary pathways of alternative end joining (a-EJ) or single-strand annealing (SSA) and the relevance of these different pathways to human disease.

Defining the diverse spectrum of inversions, complex structural variation, and chromothripsis in the morbid human genome

Background

Structural variation (SV) influences genome organization and contributes to human disease. However, the complete mutational spectrum of SV has not been routinely captured in disease association studies.

Results

We sequenced 689 participants with autism spectrum disorder (ASD) and other developmental abnormalities to construct a genome-wide map of large SV. Using long-insert jumping libraries at 105X mean physical coverage and linked-read whole-genome sequencing from 10X Genomics, we document seven major SV classes at ~5 kb SV resolution. Our results encompass 11,735 distinct large SV sites, 38.1% of which are novel and 16.8% of which are balanced or complex. We characterize 16 recurrent subclasses of complex SV (cxSV), revealing that: (1) cxSV are larger and rarer than canonical SV; (2) each genome harbors 14 large cxSV on average; (3) 84.4% of large cxSVs involve inversion; and (4) most large cxSV (93.8%) have not been delineated in previous studies. Rare SVs are more likely to disrupt coding and regulatory non-coding loci, particularly when truncating constrained and disease-associated genes. We also identify multiple cases of catastrophic chromosomal rearrangements known as chromoanagenesis, including somatic chromoanasynthesis, and extreme balanced germline chromothripsis events involving up to 65 breakpoints and 60.6 Mb across four chromosomes, further defining rare categories of extreme cxSV.

Conclusions

These data provide a foundational map of large SV in the morbid human genome and demonstrate a previously underappreciated abundance and diversity of cxSV that should be considered in genomic studies of human disease.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-017-1158-6) contains supplementary material, which is available to authorized users.

Diversity in non-repetitive human sequences not found in the reference genome

Genomes usually contain some non-repetitive sequences that are missing from the reference genome and occur only in a population subset. Such non-repetitive, non-reference (NRNR) sequences have remained largely unexplored in terms of their characterization and downstream analyses. Here we describe 3,791 breakpoint-resolved NRNR sequence variants called using PopIns from whole-genome sequence data of 15,219 Icelanders. We found that over 95% of the 244 NRNR sequences that are 200 bp or longer are present in chimpanzees, indicating that they are ancestral. Furthermore, 149 variant loci are in linkage disequilibrium (r² > 0.8) with a genome-wide association study (GWAS) catalog marker, suggesting disease relevance. Additionally, we report an association (P = 3.8 × 10^-8, odds ratio (OR) = 0.92) with myocardial infarction (23,360 cases, 300,771 controls) for a 766-bp NRNR sequence variant. Our results underline the importance of including variation of all complexity levels when searching for variants that associate with disease.

Whole-Genome Sequencing of Cytogenetically Balanced Chromosome Translocations Identifies Potentially Pathological Gene Disruptions and Highlights the Importance of Microhomology in the Mechanism of Formation

Most balanced translocations are thought to result mechanistically from nonhomologous end joining or, in rare cases of recurrent events, by nonallelic homologous recombination. Here, we use low-coverage mate pair whole-genome sequencing to fine map rearrangement breakpoint junctions in both phenotypically normal and affected translocation carriers. In total, 46 junctions from 22 carriers of balanced translocations were characterized. Genes were disrupted in 48% of the breakpoints; recessive genes in four normal carriers and known dominant intellectual disability genes in three affected carriers. Finally, seven candidate disease genes were disrupted in five carriers with neurocognitive disabilities (SVOPL, SUSD1, TOX, NCALD, SLC4A10) and one XX-male carrier with Tourette syndrome (LYPD6, GPC5). Breakpoint junction analyses revealed microhomology and small templated insertions in a substantive fraction of the analyzed translocations (17.4%; n = 4); an observation that was substantiated by reanalysis of 37 previously published translocation junctions. Microhomology associated with templated insertions is a characteristic seen in the breakpoint junctions of rearrangements mediated by error-prone replication-based repair mechanisms. Our data implicate that a mechanism involving template switching might contribute to the formation of at least 15% of the interchromosomal translocation events.

Promises and pitfalls of Illumina sequencing for HIV resistance genotyping

Genetic sequencing ("genotyping") plays a critical role in the modern clinical management of HIV infection. This virus evolves rapidly within patients because of its error-prone reverse transcriptase and short generation time. Consequently, HIV variants with mutations that confer resistance to one or more antiretroviral drugs can emerge during sub-optimal treatment. There are now multiple HIV drug resistance interpretation algorithms that take the region of the HIV genome encoding the major drug targets as inputs; expert use of these algorithms can significantly improve to clinical outcomes in HIV treatment. Next-generation sequencing has the potential to revolutionize HIV resistance genotyping by lowering the threshold that rare but clinically significant HIV variants can be detected reproducibly, and by conferring improved cost-effectiveness in high-throughput scenarios. In this review, we discuss the relative merits and challenges of deploying the Illumina MiSeq instrument for clinical HIV genotyping.

The genomic landscape of balanced cytogenetic abnormalities associated with human congenital anomalies

Despite the clinical significance of balanced chromosomal abnormalities (BCAs), their characterization has largely been restricted to cytogenetic resolution. We explored the landscape of BCAs at nucleotide resolution in 273 subjects with a spectrum of congenital anomalies. Whole-genome sequencing revised 93% of karyotypes and demonstrated complexity that was cryptic to karyotyping in 21% of BCAs, highlighting the limitations of conventional cytogenetic approaches. At least 33.9% of BCAs resulted in gene disruption that likely contributed to the developmental phenotype, 5.2% were associated with pathogenic genomic imbalances, and 7.3% disrupted topologically associated domains (TADs) encompassing known syndromic loci. Remarkably, BCA breakpoints in eight subjects altered a single TAD encompassing MEF2C, a known driver of 5q14.3 microdeletion syndrome, resulting in decreased MEF2C expression. We propose that sequence-level resolution dramatically improves prediction of clinical outcomes for balanced rearrangements and provides insight into new pathogenic mechanisms, such as altered regulation due to changes in chromosome topology.

SRBreak: A Read-Depth and Split-Read Framework to Identify Breakpoints of Different Events Inside Simple Copy-Number Variable Regions

Copy-number variation (CNV) has been associated with increased risk of complex diseases. High-throughput sequencing (HTS) technologies facilitate the detection of copy-number variable regions (CNVRs) and their breakpoints. This helps in understanding genome structure as well as their evolution process. Various approaches have been proposed for detecting CNV breakpoints, but currently it is still challenging for tools based on a single analysis method to identify breakpoints of CNVs. It has been shown, however, that pipelines which integrate multiple approaches are able to report more reliable breakpoints. Here, based on HTS data, we have developed a pipeline to identify approximate breakpoints (±10 bp) relating to different ancestral events within a specific CNVR. The pipeline combines read-depth and split-read information to infer breakpoints, using information from multiple samples to allow an imputation approach to be taken. The main steps involve using a normal mixture model to cluster samples into different groups, followed by simple kernel-based approaches to maximize information obtained from read-depth and split-read approaches, after which common breakpoints of groups are inferred. The pipeline uses split-read information directly from CIGAR strings of BAM files, without using a re-alignment step. On simulated data sets, it was able to report breakpoints for very low-coverage samples including those for which only single-end reads were available. When applied to three loci from existing human resequencing data sets (NEGR1, LCE3, IRGM) the pipeline obtained good concordance with results from the 1000 Genomes Project (92, 100, and 82%, respectively). The package is available at https://github.com/hoangtn/SRBreak, and also as a docker-based application at https://registry.hub.docker.com/u/hoangtn/srbreak/.

arrEYE: a customized platform for high-resolution copy number analysis of coding and noncoding regions of known and candidate retinal dystrophy genes and retinal noncoding RNAs

Purpose:

Our goal was to design a customized microarray, arrEYE, for high-resolution copy number variant (CNV) analysis of known and candidate genes for inherited retinal dystrophy (iRD) and retina-expressed noncoding RNAs (ncRNAs).

Methods:

arrEYE contains probes for the full genomic region of 106 known iRD genes, including those implicated in retinitis pigmentosa (RP) (the most frequent iRD), cone–rod dystrophies, macular dystrophies, and an additional 60 candidate iRD genes and 196 ncRNAs. Eight CNVs in iRD genes identified by other techniques were used as positive controls. The test cohort consisted of 57 patients with autosomal dominant, X-linked, or simplex RP.

Results:

In an RP patient, a novel heterozygous deletion of exons 7 and 8 of the HGSNAT gene was identified: c.634-408_820+338delinsAGAATATG, p.(Glu212Glyfs*2). A known variant was found on the second allele: c.1843G>A, p.(Ala615Thr). Furthermore, we expanded the allelic spectrum of USH2A and RCBTB1 with novel CNVs.

Conclusion:

The arrEYE platform revealed subtle single-exon to larger CNVs in iRD genes that could be characterized at the nucleotide level, facilitated by the high resolution of the platform. We report the first CNV in HGSNAT that, combined with another mutation, leads to RP, further supporting its recently identified role in nonsyndromic iRD.

Genet Med19 4, 457–466.