A non-coding insertional mutation of Grhl2 causes gene over-expression and multiple structural anomalies including cleft palate, spina bifida and encephalocele

Orofacial clefts, including cleft lip and palate (CL/P), and neural tube defects (NTDs) are among the most common congenital anomalies but knowledge of the genetic basis of these conditions remains incomplete. The extent to which genetic risk factors are shared between CL/P, NTDs and related anomalies is also unclear. While identification of causative genes has largely focused on coding and loss of function mutations, it is hypothesised that regulatory mutations account for a portion of the unidentified heritability. We found that excess expression of Grainyhead-like 2 (Grhl2) not only causes spinal NTDs in Axial defects (Axd) mice, but also multiple additional defects affecting the cranial region. These include orofacial clefts comprising midline cleft lip and palate, abnormalities of the craniofacial bones and frontal and/or basal encephalocele, in which brain tissue herniates through the cranium or into the nasal cavity. To investigate the causative mutation in the Grhl2Axd strain, whole genome sequencing identified an approximately 4 kb LTR retrotransposon insertion which disrupts the non-coding regulatory region, lying approximately 300 base pairs upstream of the 5' UTR. This insertion also lies within a predicted long non-coding RNA, oriented on the reverse strand, which like Grhl2 is over-expressed in Axd (Grhl2Axd) homozygous mutant embryos. Initial analysis of the GRHL2 upstream region in individuals with NTDs or cleft palate revealed rare or novel variants in a small number of cases. We hypothesise that mutations affecting the regulation of GRHL2 may contribute to craniofacial anomalies and NTDs in humans

A crowdsourced set of curated structural variants for the human genome.

Funder: U.S. Food and Drug Administration; funder-id: http://dx.doi.org/10.13039/100000038A high quality benchmark for small variants encompassing 88 to 90% of the reference genome has been developed for seven Genome in a Bottle (GIAB) reference samples. However a reliable benchmark for large indels and structural variants (SVs) is more challenging. In this study, we manually curated 1235 SVs, which can ultimately be used to evaluate SV callers or train machine learning models. We developed a crowdsourcing app-SVCurator-to help GIAB curators manually review large indels and SVs within the human genome, and report their genotype and size accuracy. SVCurator displays images from short, long, and linked read sequencing data from the GIAB Ashkenazi Jewish Trio son [NIST RM 8391/HG002]. We asked curators to assign labels describing SV type (deletion or insertion), size accuracy, and genotype for 1235 putative insertions and deletions sampled from different size bins between 20 and 892,149 bp. 'Expert' curators were 93% concordant with each other, and 37 of the 61 curators had at least 78% concordance with a set of 'expert' curators. The curators were least concordant for complex SVs and SVs that had inaccurate breakpoints or size predictions. After filtering events with low concordance among curators, we produced high confidence labels for 935 events. The SVCurator crowdsourced labels were 94.5% concordant with the heuristic-based draft benchmark SV callset from GIAB. We found that curators can successfully evaluate putative SVs when given evidence from multiple sequencing technologies

Astrocyte-produced leukemia inhibitory factor expands the neural stem/progenitor pool following perinatal hypoxia–ischemia

Brain injuries, such as cerebral hypoxia–ischemia (H-I), induce a regenerative response from the neural stem/progenitors (NSPs) of the subventricular zone (SVZ); however, the mechanisms that regulate this expansion have not yet been fully elucidated. The Notch- Delta-Serrate-Lag2 (DSL) signaling pathway is considered essential for the maintenance of neural stem cells, but it is not known if it is necessary for the expansion of the NSPs subsequent to perinatal H-I injury. Therefore, the aim of this study was to investigate whether this pathway contributes to NSP expansion in the SVZ after H-I and, if so, to establish whether this pathway is directly induced by H-I or regulated by paracrine factors. Here we report that Notch1 receptor induction and one of its ligands, Delta-like 1, precedes NSP expansion after perinatal H-I in P6 rat pups and that this increase occurs specifically in the most medial cell layers of the SVZ where the stem cells reside. Pharmacologically inhibiting Notch signaling in vivo diminished NSP expansion. With an in vitro model of H-I, Notch1 was not induced directly by hypoxia, but was stimulated by soluble factors, specifically leukemia inhibitory factor, produced by astrocytes within the SVZ. These data confirm the importance both of the Notch-DSL signaling pathway in the expansion of NSPs after H-I and in the role of the support cells in their niche. They further support the body of evidence that indicates that leukemia inhibitory factor is a key injury-induced cytokine that is stimulating the regenerative response of the NSPs. © 2016 Wiley Periodicals, Inc

Schizophrenia endothelial cells exhibit higher permeability and altered angiogenesis patterns in patient-derived organoids

Abstract Schizophrenia (SCZ) is a complex neurodevelopmental disorder characterized by the manifestation of psychiatric symptoms in early adulthood. While many research avenues into the origins of SCZ during brain development have been explored, the contribution of endothelial/vascular dysfunction to the disease remains largely elusive. To model the neuropathology of SCZ during early critical periods of brain development, we utilized patient-derived induced pluripotent stem cells (iPSCs) to generate 3D cerebral organoids and define cell-specific signatures of disease. Single-cell RNA sequencing revealed that while SCZ organoids were similar in their macromolecular diversity to organoids generated from healthy controls (CTRL), SCZ organoids exhibited a higher percentage of endothelial cells when normalized to total cell numbers. Additionally, when compared to CTRL, differential gene expression analysis revealed a significant enrichment in genes that function in vessel formation, vascular regulation, and inflammatory response in SCZ endothelial cells. In line with these findings, data from 23 donors demonstrated that PECAM1+ microvascular vessel-like structures were increased in length and number in SCZ organoids in comparison to CTRL organoids. Furthermore, we report that patient-derived endothelial cells displayed higher paracellular permeability, implicating elevated vascular activity. Collectively, our data identified altered gene expression patterns, vessel-like structural changes, and enhanced permeability of endothelial cells in patient-derived models of SCZ. Hence, brain microvascular cells could play a role in the etiology of SCZ by modulating the permeability of the developing blood brain barrier (BBB)

Genome-wide investigation identifies a rare copy-number variant burden associated with human spina bifida

Next-generation sequencing has implicated some risk variants for human spina bifida (SB), but the genome-wide contribution of structural variation to this complex genetic disorder remains largely unknown. We examined copy-number variant (CNV) participation in the genetic architecture underlying SB risk. A high-confidence ensemble approach to genome sequences (GS) was benchmarked and employed for systematic detection of common and rare CNVs in two separate ancestry-matched SB case-control cohorts. SB cases were enriched with exon disruptive rare CNVs, 44% of which were under 10 kb, in both ancestral populations (P = 6.75 × 10 ; P = 7.59 × 10 ). Genes containing these disruptive CNVs fall into molecular pathways, supporting a role for these genes in SB. Our results expand the catalog of variants and genes with potential contribution to genetic and gene-environment interactions that interfere with neurulation, useful for further functional characterization. This study underscores the need for genome-wide investigation and extends our previous threshold model of exonic, single-nucleotide variation toward human SB risk to include structural variation. Since GS data afford detection of CNVs with greater resolution than microarray methods, our results have important implications toward a more comprehensive understanding of the genetic risk and mechanisms underlying neural tube defect pathogenesis

Systems biology analysis of human genomes points to key pathways conferring spina bifida risk

Spina bifida (SB) is a debilitating birth defect caused by multiple gene and environment interactions. Though SB shows non-Mendelian inheritance, genetic factors contribute to an estimated 70% of cases. Nevertheless, identifying human mutations conferring SB risk is challenging due to its relative rarity, genetic heterogeneity, incomplete penetrance, and environmental influences that hamper genome-wide association studies approaches to untargeted discovery. Thus, SB genetic studies may suffer from population substructure and/or selection bias introduced by typical candidate gene searches. We report a population based, ancestry-matched whole-genome sequence analysis of SB genetic predisposition using a systems biology strategy to interrogate 298 case-control subject genomes (149 pairs). Genes that were enriched in likely gene disrupting (LGD), rare protein-coding variants were subjected to machine learning analysis to identify genes in which LGD variants occur with a different frequency in cases versus controls and so discriminate between these groups. Those genes with high discriminatory potential for SB significantly enriched pathways pertaining to carbon metabolism, inflammation, innate immunity, cytoskeletal regulation, and essential transcriptional regulation consistent with their having impact on the pathogenesis of human SB. Additionally, an interrogation of conserved noncoding sequences identified robust variant enrichment in regulatory regions of several transcription factors critical to embryonic development. This genome-wide perspective offers an effective approach to the interrogation of coding and noncoding sequence variant contributions to rare complex genetic disorders

Systems biology analysis of human genomes points to key pathways conferring spina bifida risk

Spina bifida (SB) is a debilitating birth defect caused by multiple gene and environment interactions. Though SB shows non-Mendelian inheritance, genetic factors contribute to an estimated 70% of cases. Nevertheless, identifying human mutations conferring SB risk is challenging due to its relative rarity, genetic heterogeneity, incomplete penetrance, and environmental influences that hamper genome-wide association studies approaches to untargeted discovery. Thus, SB genetic studies may suffer from population substructure and/or selection bias introduced by typical candidate gene searches. We report a population based, ancestry-matched whole-genome sequence analysis of SB genetic predisposition using a systems biology strategy to interrogate 298 case-control subject genomes (149 pairs). Genes that were enriched in likely gene disrupting (LGD), rare protein-coding variants were subjected to machine learning analysis to identify genes in which LGD variants occur with a different frequency in cases versus controls and so discriminate between these groups. Those genes with high discriminatory potential for SB significantly enriched pathways pertaining to carbon metabolism, inflammation, innate immunity, cytoskeletal regulation, and essential transcriptional regulation consistent with their having impact on the pathogenesis of human SB. Additionally, an interrogation of conserved noncoding sequences identified robust variant enrichment in regulatory regions of several transcription factors critical to embryonic development. This genome-wide perspective offers an effective approach to the interrogation of coding and noncoding sequence variant contributions to rare complex genetic disorders

SVCurator: A Crowdsourcing app to visualize evidence of structural variants for the human genome

A high quality benchmark for small variants encompassing 88 to 90% of the reference genome has been developed for seven Genome in a Bottle (GIAB) reference samples. However a reliable benchmark for large indels and structural variants (SVs) is yet to be defined. In this study, we manually curated 1235 SVs which can ultimately be used to evaluate SV callers ortrain machine learning models. We developed a crowdsourcing app - SVCurator - to help curators manually review large indels and SVs within the human genome, and report their genotype and size accuracy.SVCurator is a Python Flask-based web platform that displays images from short, long, and linked read sequencing data from the GIAB Ashkenazi Jewish Trio son [NIST RM 8391/HG002]. We asked curators to assign labels describing SV type (deletion or insertion), size accuracy, and genotype for 1235 putative insertions and deletions sampled from different size bins between 20 and 892,149 bp. The crowdsourced results were highly concordant with 37 out ofthe 61 curators having at least 78% concordance with a set of ‘expert’ curators, where there was 93% concordance amongst ‘expert’ curators. This produced high confidence labels for 935 events. When compared to the heuristic-based draft benchmark SV callset from GIAB, the SVCurator crowdsourced labels were 94.5% concordant with the benchmark set. We found that curators can successfully evaluate putative SVs when given evidence from multiple sequencing technologies