Long-read sequencing and optical mapping generates near T2T assemblies that resolves a centromeric translocation.

Long-read genome sequencing (lrGS) is a promising method in genetic diagnostics. Here we investigate the potential of lrGS to detect a disease-associated chromosomal translocation between 17p13 and the 19 centromere. We constructed two sets of phased and non-phased de novo assemblies; (i) based on lrGS only and (ii) hybrid assemblies combining lrGS with optical mapping using lrGS reads with a median coverage of 34X. Variant calling detected both structural variants (SVs) and small variants and the accuracy of the small variant calling was compared with those called with short-read genome sequencing (srGS). The de novo and hybrid assemblies had high quality and contiguity with N50 of 62.85 Mb, enabling a near telomere to telomere assembly with less than a 100 contigs per haplotype. Notably, we successfully identified the centromeric breakpoint of the translocation. A concordance of 92% was observed when comparing small variant calling between srGS and lrGS. In summary, our findings underscore the remarkable potential of lrGS as a comprehensive and accurate solution for the analysis of SVs and small variants. Thus, lrGS could replace a large battery of genetic tests that were used for the diagnosis of a single symptomatic translocation carrier, highlighting the potential of lrGS in the realm of digital karyotyping.

Genomic, transcriptomic and epigenomic sequencing data of the B-cell leukemia cell line REH.

OBJECTIVES: The aim of this data paper is to describe a collection of 33 genomic, transcriptomic and epigenomic sequencing datasets of the B-cell acute lymphoblastic leukemia (ALL) cell line REH. REH is one of the most frequently used cell lines for functional studies of pediatric ALL, and these data provide a multi-faceted characterization of its molecular features. The datasets described herein, generated with short- and long-read sequencing technologies, can both provide insights into the complex aberrant karyotype of REH, and be used as reference datasets for sequencing data quality assessment or for methods development. DATA DESCRIPTION: This paper describes 33 datasets corresponding to 867 gigabases of raw sequencing data generated from the REH cell line. These datasets include five different approaches for whole genome sequencing (WGS) on four sequencing platforms, two RNA sequencing (RNA-seq) techniques on two different sequencing platforms, DNA methylation sequencing, and single-cell ATAC-sequencing.

Long-read whole-genome analysis of human single cells.

Long-read sequencing has dramatically increased our understanding of human genome variation. Here, we demonstrate that long-read technology can give new insights into the genomic architecture of individual cells. Clonally expanded CD8+ T-cells from a human donor were subjected to droplet-based multiple displacement amplification (dMDA) to generate long molecules with reduced bias. PacBio sequencing generated up to 40% genome coverage per single-cell, enabling detection of single nucleotide variants (SNVs), structural variants (SVs), and tandem repeats, also in regions inaccessible by short reads. 28 somatic SNVs were detected, including one case of mitochondrial heteroplasmy. 5473 high-confidence SVs/cell were discovered, a sixteen-fold increase compared to Illumina-based results from clonally related cells. Single-cell de novo assembly generated a genome size of up to 598 Mb and 1762 (12.8%) complete gene models. In summary, our work shows the promise of long-read sequencing toward characterization of the full spectrum of genetic variation in single cells.

Correction: Copy number of pancreatic polypeptide receptor gene NPY4R correlates with body mass index and waist circumference.

[This corrects the article DOI: 10.1371/journal.pone.0194668.].

Multi-Omic Investigations of a 17-19 Translocation Links MINK1 Disruption to Autism, Epilepsy and Osteoporosis.

Balanced structural variants, such as reciprocal translocations, are sometimes hard to detect with sequencing, especially when the breakpoints are located in repetitive or insufficiently mapped regions of the genome. In such cases, long-range information is required to resolve the rearrangement, identify disrupted genes and, in symptomatic carriers, pinpoint the disease-causing mechanisms. Here, we report an individual with autism, epilepsy and osteoporosis and a de novo balanced reciprocal translocation: t(17;19) (p13;p11). The genomic DNA was analyzed by short-, linked- and long-read genome sequencing, as well as optical mapping. Transcriptional consequences were assessed by transcriptome sequencing of patient-specific neuroepithelial stem cells derived from induced pluripotent stem cells (iPSC). The translocation breakpoints were only detected by long-read sequencing, the first on 17p13, located between exon 1 and exon 2 of MINK1 (Misshapen-like kinase 1), and the second in the chromosome 19 centromere. Functional validation in induced neural cells showed that MINK1 expression was reduced by >50% in the patient's cells compared to healthy control cells. Furthermore, pathway analysis revealed an enrichment of changed neural pathways in the patient's cells. Altogether, our multi-omics experiments highlight MINK1 as a candidate monogenic disease gene and show the advantages of long-read genome sequencing in capturing centromeric translocations.

CRISPR-Cas9 induces large structural variants at on-target and off-target sites in vivo that segregate across generations.

CRISPR-Cas9 genome editing has potential to cure diseases without current treatments, but therapies must be safe. Here we show that CRISPR-Cas9 editing can introduce unintended mutations in vivo, which are passed on to the next generation. By editing fertilized zebrafish eggs using four guide RNAs selected for off-target activity in vitro, followed by long-read sequencing of DNA from >1100 larvae, juvenile and adult fish across two generations, we find that structural variants (SVs), i.e., insertions and deletions ≥50 bp, represent 6% of editing outcomes in founder larvae. These SVs occur both at on-target and off-target sites. Our results also illustrate that adult founder zebrafish are mosaic in their germ cells, and that 26% of their offspring carries an off-target mutation and 9% an SV. Hence, pre-testing for off-target activity and SVs using patient material is advisable in clinical applications, to reduce the risk of unanticipated effects with potentially large implications.

Transcriptome Analysis of Post-Mortem Brain Tissue Reveals Up-Regulation of the Complement Cascade in a Subgroup of Schizophrenia Patients.

Schizophrenia is a genetically complex neuropsychiatric disorder with largely unresolved mechanisms of pathology. Identification of genes and pathways associated with schizophrenia is important for understanding the development, progression and treatment of schizophrenia. In this study, pathways associated with schizophrenia were explored at the level of gene expression. The study included post-mortem brain tissue samples from 68 schizophrenia patients and 44 age and sex-matched control subjects. Whole transcriptome poly-A selected paired-end RNA sequencing was performed on tissue from the prefrontal cortex and orbitofrontal cortex. RNA expression differences were detected between case and control individuals, focusing both on single genes and pathways. The results were validated with RT-qPCR. Significant differential expression between patient and controls groups was found for 71 genes. Gene ontology analysis of differentially expressed genes revealed an up-regulation of multiple genes in immune response among the patients (corrected p-value = 0.004). Several genes in the category belong to the complement system, including C1R, C1S, C7, FCN3, SERPING1, C4A and CFI. The increased complement expression is primarily driven by a subgroup of patients with increased expression of immune/inflammatory response genes, pointing to important differences in disease etiology within the patient group. Weighted gene co-expression network analysis highlighted networks associated with both synaptic transmission and activation of the immune response. Our results demonstrate the importance of immune-related pathways in schizophrenia and provide evidence for elevated expression of the complement cascade as an important pathway in schizophrenia pathology.

Interpretable Machine Learning Reveals Dissimilarities Between Subtypes of Autism Spectrum Disorder.

Autism spectrum disorder (ASD) is a heterogeneous neuropsychiatric disorder with a complex genetic background. Analysis of altered molecular processes in ASD patients requires linear and nonlinear methods that provide interpretable solutions. Interpretable machine learning provides legible models that allow explaining biological mechanisms and support analysis of clinical subgroups. In this work, we investigated several case-control studies of gene expression measurements of ASD individuals. We constructed a rule-based learning model from three independent datasets that we further visualized as a nonlinear gene-gene co-predictive network. To find dissimilarities between ASD subtypes, we scrutinized a topological structure of the network and estimated a centrality distance. Our analysis revealed that autism is the most severe subtype of ASD, while pervasive developmental disorder-not otherwise specified and Asperger syndrome are closely related and milder ASD subtypes. Furthermore, we analyzed the most important ASD-related features that were described in terms of gene co-predictors. Among others, we found a strong co-predictive mechanism between EMC4 and TMEM30A, which may suggest a co-regulation between these genes. The present study demonstrates the potential of applying interpretable machine learning in bioinformatics analyses. Although the proposed methodology was designed for transcriptomics data, it can be applied to other omics disciplines.

R.ROSETTA: an interpretable machine learning framework.

BACKGROUND: Machine learning involves strategies and algorithms that may assist bioinformatics analyses in terms of data mining and knowledge discovery. In several applications, viz. in Life Sciences, it is often more important to understand how a prediction was obtained rather than knowing what prediction was made. To this end so-called interpretable machine learning has been recently advocated. In this study, we implemented an interpretable machine learning package based on the rough set theory. An important aim of our work was provision of statistical properties of the models and their components. RESULTS: We present the R.ROSETTA package, which is an R wrapper of ROSETTA framework. The original ROSETTA functions have been improved and adapted to the R programming environment. The package allows for building and analyzing non-linear interpretable machine learning models. R.ROSETTA gathers combinatorial statistics via rule-based modelling for accessible and transparent results, well-suited for adoption within the greater scientific community. The package also provides statistics and visualization tools that facilitate minimization of analysis bias and noise. The R.ROSETTA package is freely available at https://github.com/komorowskilab/R.ROSETTA . To illustrate the usage of the package, we applied it to a transcriptome dataset from an autism case-control study. Our tool provided hypotheses for potential co-predictive mechanisms among features that discerned phenotype classes. These co-predictors represented neurodevelopmental and autism-related genes. CONCLUSIONS: R.ROSETTA provides new insights for interpretable machine learning analyses and knowledge-based systems. We demonstrated that our package facilitated detection of dependencies for autism-related genes. Although the sample application of R.ROSETTA illustrates transcriptome data analysis, the package can be used to analyze any data organized in decision tables.

DLG4-related synaptopathy: a new rare brain disorder.

PURPOSE: Postsynaptic density protein-95 (PSD-95), encoded by DLG4, regulates excitatory synaptic function in the brain. Here we present the clinical and genetic features of 53 patients (42 previously unpublished) with DLG4 variants. METHODS: The clinical and genetic information were collected through GeneMatcher collaboration. All the individuals were investigated by local clinicians and the gene variants were identified by clinical exome/genome sequencing. RESULTS: The clinical picture was predominated by early onset global developmental delay, intellectual disability, autism spectrum disorder, and attention deficit-hyperactivity disorder, all of which point to a brain disorder. Marfanoid habitus, which was previously suggested to be a characteristic feature of DLG4-related phenotypes, was found in only nine individuals and despite some overlapping features, a distinct facial dysmorphism could not be established. Of the 45 different DLG4 variants, 39 were predicted to lead to loss of protein function and the majority occurred de novo (four with unknown origin). The six missense variants identified were suggested to lead to structural or functional changes by protein modeling studies. CONCLUSION: The present study shows that clinical manifestations associated with DLG4 overlap with those found in other neurodevelopmental disorders of synaptic dysfunction; thus, we designate this group of disorders as DLG4-related synaptopathy.

Characterization of the nuclear and cytosolic transcriptomes in human brain tissue reveals new insights into the subcellular distribution of RNA transcripts.

Transcriptome analysis has mainly relied on analyzing RNA sequencing data from whole cells, overlooking the impact of subcellular RNA localization and its influence on our understanding of gene function, and interpretation of gene expression signatures in cells. Here, we separated cytosolic and nuclear RNA from human fetal and adult brain samples and performed a comprehensive analysis of cytosolic and nuclear transcriptomes. There are significant differences in RNA expression for protein-coding and lncRNA genes between cytosol and nucleus. We show that transcripts encoding the nuclear-encoded mitochondrial proteins are significantly enriched in the cytosol compared to the rest of protein-coding genes. Differential expression analysis between fetal and adult frontal cortex show that results obtained from the cytosolic RNA differ from results using nuclear RNA both at the level of transcript types and the number of differentially expressed genes. Our data provide a resource for the subcellular localization of thousands of RNA transcripts in the human brain and highlight differences in using the cytosolic or the nuclear transcriptomes for expression analysis.

Hybrid sequencing resolves two germline ultra-complex chromosomal rearrangements consisting of 137 breakpoint junctions in a single carrier.

Chromoanagenesis is a genomic event responsible for the formation of complex structural chromosomal rearrangements (CCRs). Germline chromoanagenesis is rare and the majority of reported cases are associated with an affected phenotype. Here, we report a healthy female carrying two de novo CCRs involving chromosomes 4, 19, 21 and X and chromosomes 7 and 11, respectively, with a total of 137 breakpoint junctions (BPJs). We characterized the CCRs using a hybrid-sequencing approach, combining short-read sequencing, nanopore sequencing, and optical mapping. The results were validated using multiple cytogenetic methods, including fluorescence in situ hybridization, spectral karyotyping, and Sanger sequencing. We identified 137 BPJs, which to our knowledge is the highest number of reported breakpoint junctions in germline chromoanagenesis. We also performed a statistical assessment of the positioning of the breakpoints, revealing a significant enrichment of BPJ-affecting genes (96 intragenic BPJs, 26 genes, p < 0.0001), indicating that the CCRs formed during active transcription of these genes. In addition, we find that the DNA fragments are unevenly and non-randomly distributed across the derivative chromosomes indicating a multistep process of scattering and re-joining of DNA fragments. In summary, we report a new maximum number of BPJs (137) in germline chromoanagenesis. We also show that a hybrid sequencing approach is necessary for the correct characterization of complex CCRs. Through in-depth statistical assessment, it was found that the CCRs most likely was formed through an event resembling chromoplexy-a catastrophic event caused by erroneous transcription factor binding.

Amplification-free long-read sequencing reveals unforeseen CRISPR-Cas9 off-target activity.

BACKGROUND: One ongoing concern about CRISPR-Cas9 genome editing is that unspecific guide RNA (gRNA) binding may induce off-target mutations. However, accurate prediction of CRISPR-Cas9 off-target activity is challenging. Here, we present SMRT-OTS and Nano-OTS, two novel, amplification-free, long-read sequencing protocols for detection of gRNA-driven digestion of genomic DNA by Cas9 in vitro. RESULTS: The methods are assessed using the human cell line HEK293, re-sequenced at 18x coverage using highly accurate HiFi SMRT reads. SMRT-OTS and Nano-OTS are first applied to three different gRNAs targeting HEK293 genomic DNA, resulting in a set of 55 high-confidence gRNA cleavage sites identified by both methods. Twenty-five of these sites are not reported by off-target prediction software, either because they contain four or more single nucleotide mismatches or insertion/deletion mismatches, as compared with the human reference. Additional experiments reveal that 85% of Cas9 cleavage sites are also found by other in vitro-based methods and that on- and off-target sites are detectable in gene bodies where short-reads fail to uniquely align. Even though SMRT-OTS and Nano-OTS identify several sites with previously validated off-target editing activity in cells, our own CRISPR-Cas9 editing experiments in human fibroblasts do not give rise to detectable off-target mutations at the in vitro-predicted sites. However, indel and structural variation events are enriched at the on-target sites. CONCLUSIONS: Amplification-free long-read sequencing reveals Cas9 cleavage sites in vitro that would have been difficult to predict using computational tools, including in dark genomic regions inaccessible by short-read sequencing.

Evaluation of Single-Molecule Sequencing Technologies for Structural Variant Detection in Two Swedish Human Genomes.

Long-read single molecule sequencing is increasingly used in human genomics research, as it allows to accurately detect large-scale DNA rearrangements such as structural variations (SVs) at high resolution. However, few studies have evaluated the performance of different single molecule sequencing platforms for SV detection in human samples. Here we performed Oxford Nanopore Technologies (ONT) whole-genome sequencing of two Swedish human samples (average 32× coverage) and compared the results to previously generated Pacific Biosciences (PacBio) data for the same individuals (average 66× coverage). Our analysis inferred an average of 17k and 23k SVs from the ONT and PacBio data, respectively, with a majority of them overlapping with an available multi-platform SV dataset. When comparing the SV calls in the two Swedish individuals, we find a higher concordance between ONT and PacBio SVs detected in the same individual as compared to SVs detected by the same technology in different individuals. Downsampling of PacBio reads, performed to obtain similar coverage levels for all datasets, resulted in 17k SVs per individual and improved overlap with the ONT SVs. Our results suggest that ONT and PacBio have a similar performance for SV detection in human whole genome sequencing data, and that both technologies are feasible for population-scale studies.

Exploring autoantibody signatures in brain tissue from patients with severe mental illness.

In recent years, studies have shown higher prevalence of autoantibodies in patients with schizophrenia compared to healthy individuals. This study applies an untargeted and a targeted affinity proteomics approach to explore and characterize the autoantibody repertoire in brain tissues from 73 subjects diagnosed with schizophrenia and 52 control subjects with no psychiatric or neurological disorders. Selected brain tissue lysates were first explored for IgG reactivity on planar microarrays composed of 11,520 protein fragments representing 10,820 unique proteins. Based on these results of ours and other previous studies of autoantibodies related to psychosis, we selected 226 fragments with an average length of 80 amino acids, representing 127 unique proteins. Tissue-based analysis of IgG reactivities using antigen suspension bead arrays was performed in a multiplex and parallel fashion for all 125 subjects. Among the detected autoantigens, higher IgG reactivity in subjects with schizophrenia, as compared to psychiatrically healthy subjects, was found against the glutamate ionotropic receptor NMDA type subunit 2D (anti-GluN2D). In a separate cohort with serum samples from 395 young adults with a wider spectrum of psychiatric disorders, higher levels of serum autoantibodies targeting GluN2D were found when compared to 102 control individuals. By further validating GluN2D and additional potential autoantigens, we will seek insights into how these are associated with severe mental illnesses.

Identification and rescue of a tRNA wobble inosine deficiency causing intellectual disability disorder.

The deamination of adenosine to inosine at the wobble position of tRNA is an essential post-transcriptional RNA modification required for wobble decoding in bacteria and eukaryotes. In humans, the wobble inosine modification is catalyzed by the heterodimeric ADAT2/3 complex. Here, we describe novel pathogenic ADAT3 variants impairing adenosine deaminase activity through a distinct mechanism that can be corrected through expression of the heterodimeric ADAT2 subunit. The variants were identified in a family in which all three siblings exhibit intellectual disability linked to biallelic variants in the ADAT3 locus. The biallelic ADAT3 variants result in a missense variant converting alanine to valine at a conserved residue or the introduction of a premature stop codon in the deaminase domain. Fibroblast cells derived from two ID-affected individuals exhibit a reduction in tRNA wobble inosine levels and severely diminished adenosine tRNA deaminase activity. Notably, the ADAT3 variants exhibit impaired interaction with the ADAT2 subunit and alterations in ADAT2-dependent nuclear localization. Based upon these findings, we find that tRNA adenosine deaminase activity and wobble inosine modification can be rescued in patient cells by overexpression of the ADAT2 catalytic subunit. These results uncover a key role for the inactive ADAT3 deaminase domain in proper assembly with ADAT2 and demonstrate that ADAT2/3 nuclear import is required for maintaining proper levels of the wobble inosine modification in tRNA.

Whole genome sequencing of familial isolated oesophagus atresia uncover shared structural variants.

BACKGROUND: Oesophageal atresia (OA) is a life-threatening developmental defect characterized by a lost continuity between the upper and lower oesophagus. The most common form is a distal connection between the trachea and the oesophagus, i.e. a tracheoesophageal fistula (TEF). The condition may be part of a syndrome or occurs as an isolated feature. The recurrence risk in affected families is increased compared to the population-based incidence suggesting contributing genetic factors. METHODS: To gain insight into gene variants and genes associated with isolated OA we conducted whole genome sequencing on samples from three families with recurrent cases affected by congenital and isolated TEF. RESULTS: We identified a combination of single nucleotide variants (SNVs), splice site variants (SSV) and structural variants (SV) annotated to altogether 100 coding genes in the six affected individuals. CONCLUSION: This study highlights rare SVs among candidate gene variants in our individuals with OA and provides a gene framework for further investigations of genetic factors behind this malformation.

Transcriptome analysis of fibroblasts from schizophrenia patients reveals differential expression of schizophrenia-related genes.

Schizophrenia is a complex neurodevelopmental disorder with high rate of morbidity and mortality. While the heritability rate is high, the precise etiology is still unknown. Although schizophrenia is a central nervous system disorder, studies using peripheral tissues have also been established to search for patient specific biomarkers and to increase understanding of schizophrenia etiology. Among all peripheral tissues, fibroblasts stand out as they are easy to obtain and culture. Furthermore, they keep genetic stability for long period and exhibit molecular similarities to cells from nervous system. Using a unique set of fibroblast samples from a genetically isolated population in northern Sweden, we performed whole transcriptome sequencing to compare differentially expressed genes in seven controls and nine patients. We found differential fibroblast expression between cases and controls for 48 genes, including eight genes previously implicated in schizophrenia or schizophrenia related pathways; HGF, PRRT2, EGR1, EGR3, C11orf87, TLR3, PLEKHH2 and PIK3CD. Weighted gene correlation network analysis identified three differentially co-expressed networks of genes significantly-associated with schizophrenia. All three modules were significantly suppressed in patients compared to control, with one module highly enriched in genes involved in synaptic plasticity, behavior and synaptic transmission. In conclusion, our results support the use of fibroblasts for identification of differentially expressed genes in schizophrenia and highlight dysregulation of synaptic networks as an important mechanism in schizophrenia.

Linkage and exome analysis implicate multiple genes in non-syndromic intellectual disability in a large Swedish family.

BACKGROUND: Non-syndromic intellectual disability is genetically heterogeneous with dominant, recessive and complex forms of inheritance. We have performed detailed genetic studies in a large multi-generational Swedish family, including several members diagnosed with non-syndromic intellectual disability. Linkage analysis was performed on 22 family members, nine affected with mild to moderate intellectual disability and 13 unaffected family members. METHODS: Family members were analyzed with Affymetrix Genome-Wide Human SNP Array 6.0 and the genetic data was used to detect copy number variation and to perform genome wide linkage analysis with the SNP High Throughput Linkage analysis system and the Merlin software. For the exome sequencing, the samples were prepared using the Sure Select Human All Exon Kit (Agilent Technologies, Santa Clara, CA, USA) and sequenced using the Ion Proton™ System. Validation of identified variants was performed with Sanger sequencing. RESULTS: The linkage analysis results indicate that intellectual disability in this family is genetically heterogeneous, with suggestive linkage found on chromosomes 1q31-q41, 4q32-q35, 6p25 and 14q24-q31 (LOD scores of 2.4, simulated p-value of 0.000003 and a simulated genome-wide p-value of 0.06). Exome sequencing was then performed in 14 family members and 7 unrelated individuals from the same region. The analysis of coding variation revealed a pathogenic and candidate variants in different branches of the family. In three patients we find a known homozygous pathogenic mutation in the Homo sapiens solute carrier family 17 member 5 (SLC17A5), causing Salla disease. We also identify a deletion overlapping KDM3B and a duplication overlapping MAP3K4 and AGPAT4, both overlapping variants previously reported in developmental disorders. CONCLUSIONS: DNA samples from the large family analyzed in this study were initially collected based on a hypothesis that affected members shared a major genetic risk factor. Our results show that a complex phenotype such as mild intellectual disability in large families from genetically isolated populations may show considerable genetic heterogeneity.

Novel Y-Chromosome Long Non-Coding RNAs Expressed in Human Male CNS During Early Development.

Global microarray gene expression analyses previously demonstrated differences in female and male embryos during neurodevelopment. In particular, before sexual maturation of the gonads, the differences seem to concentrate on the expression of genes encoded on the X- and Y-chromosomes. To investigate genome-wide differences in expression during this early developmental window, we combined high-resolution RNA sequencing with qPCR to analyze brain samples from human embryos during the first trimester of development. Our analysis was tailored for maximum sensitivity to discover Y-chromosome gene expression, but at the same time, it was underpowered to detect X-inactivation escapees. Using this approach, we found that 5 out of 13 expressed gametolog pairs showed unbalanced gene dosage, and as a consequence, a male-biased expression. In addition, we found six novel non-annotated long non-coding RNAs on the Y-chromosome with conserved expression patterns in newborn chimpanzee. The tissue specific and time-restricted expression of these long non-coding RNAs strongly suggests important functions during central nervous system development in human males.