Gene essentiality in cancer cell lines is modified by the sex chromosomes.

Human sex differences arise from gonadal hormones and sex chromosomes. Studying the direct effects of sex chromosomes in humans is still challenging. Here we studied how the sex chromosomes can modulate gene expression and the outcome of mutations across the genome by exploiting the tendency of cancer cell lines to lose or gain sex chromosomes. We inferred the dosage of the sex chromosomes in 355 female and 408 male cancer cell lines and used it to dissect the contributions of the Y and X Chromosomes to sex-biased gene expression. Furthermore, based on genome-wide CRISPR screens, we identified genes whose essentiality is different between male and female cells depending on the sex chromosomes. The most significant genes were X-linked genes compensated by Y-linked paralogs. Our sex-based analysis identifies genes that, when mutated, can affect male and female cells differently and reinforces the roles of the X and Y Chromosomes in sex-specific cell function.

The chromatin factor ROW cooperates with BEAF-32 in regulating long-range inducible genes.

Insulator proteins located at the boundaries of topological associated domains (TAD) are involved in higher-order chromatin organization and transcription regulation. However, it is still not clear how long-range contacts contribute to transcriptional regulation. Here, we show that relative-of-WOC (ROW) is essential for the long-range transcription regulation mediated by the boundary element-associated factor of 32kD (BEAF-32). We find that ROW physically interacts with heterochromatin proteins (HP1b and HP1c) and the insulator protein (BEAF-32). These proteins interact at TAD boundaries where ROW, through its AT-hook motifs, binds AT-rich sequences flanked by BEAF-32-binding sites and motifs. Knockdown of row downregulates genes that are long-range targets of BEAF-32 and bound indirectly by ROW (without binding motif). Analyses of high-throughput chromosome conformation capture (Hi-C) data reveal long-range interactions between promoters of housekeeping genes bound directly by ROW and promoters of developmental genes bound indirectly by ROW. Thus, our results show cooperation between BEAF-32 and the ROW complex, including HP1 proteins, to regulate the transcription of developmental and inducible genes through long-range interactions.

Transfer RNA fragments replace microRNA regulators of the cholinergic poststroke immune blockade.

Stroke is a leading cause of death and disability. Recovery depends on a delicate balance between inflammatory responses and immune suppression, tipping the scale between brain protection and susceptibility to infection. Peripheral cholinergic blockade of immune reactions fine-tunes this immune response, but its molecular regulators are unknown. Here, we report a regulatory shift in small RNA types in patient blood sequenced 2 d after ischemic stroke, comprising massive decreases of microRNA levels and concomitant increases of transfer RNA fragments (tRFs) targeting cholinergic transcripts. Electrophoresis-based size-selection followed by qRT-PCR validated the top six up-regulated tRFs in a separate cohort of stroke patients, and independent datasets of small and long RNA sequencing pinpointed immune cell subsets pivotal to these responses, implicating CD14+ monocytes in the cholinergic inflammatory reflex. In-depth small RNA targeting analyses revealed the most-perturbed pathways following stroke and implied a structural dichotomy between microRNA and tRF target sets. Furthermore, lipopolysaccharide stimulation of murine RAW 264.7 cells and human CD14+ monocytes up-regulated the top six stroke-perturbed tRFs, and overexpression of stroke-inducible tRF-22-WE8SPOX52 using a single-stranded RNA mimic induced down-regulation of immune regulator Z-DNA binding protein 1. In summary, we identified a "changing of the guards" between small RNA types that may systemically affect homeostasis in poststroke immune responses, and pinpointed multiple affected pathways, which opens new venues for establishing therapeutics and biomarkers at the protein and RNA level.

Genes essential for embryonic stem cells are associated with neurodevelopmental disorders.

Mouse embryonic stem cells (mESCs) are key components in generating mouse models for human diseases and performing basic research on pluripotency, yet the number of genes essential for mESCs is still unknown. We performed a genome-wide screen for essential genes in mESCs and compared it to screens in human cells. We found that essential genes are enriched for basic cellular functions, are highly expressed in mESCs, and tend to lack paralog genes. We discovered that genes that are essential specifically in mESCs play a role in pathways associated with their pluripotent state. We show that 29.5% of human genes intolerant to loss-of-function mutations are essential in mouse or human ESCs, and that the human phenotypes most significantly associated with genes essential for ESCs are neurodevelopmental. Our results provide insights into essential genes in the mouse, the pathways which govern pluripotency, and suggest that many genes associated with neurodevelopmental disorders are essential at very early embryonic stages.

AUTS2 isoforms control neuronal differentiation.

Mutations in AUTS2 are associated with autism, intellectual disability, and microcephaly. AUTS2 is expressed in the brain and interacts with polycomb proteins, yet it is still unclear how mutations in AUTS2 lead to neurodevelopmental phenotypes. Here we report that when neuronal differentiation is initiated, there is a shift in expression from a long isoform to a short AUTS2 isoform. Yeast two-hybrid screen identified the splicing factor SF3B1 as an interactor of both isoforms, whereas the polycomb group proteins, PCGF3 and PCGF5, were found to interact exclusively with the long AUTS2 isoform. Reporter assays showed that the first exons of the long AUTS2 isoform function as a transcription repressor, but the part that consist of the short isoform acts as a transcriptional activator, both influenced by the cellular context. The expression levels of PCGF3 influenced the ability of the long AUTS2 isoform to activate or repress transcription. Mouse embryonic stem cells (mESCs) with heterozygote mutations in Auts2 had an increase in cell death during in vitro corticogenesis, which was significantly rescued by overexpressing the human AUTS2 transcripts. mESCs with a truncated AUTS2 protein (missing exons 12-20) showed premature neuronal differentiation, whereas cells overexpressing AUTS2, especially the long transcript, showed increase in expression of pluripotency markers and delayed differentiation. Taken together, our data suggest that the precise expression of AUTS2 isoforms is essential for regulating transcription and the timing of neuronal differentiation.

Expansion of the GRIA2 phenotypic representation: a novel de novo loss of function mutation in a case with childhood onset schizophrenia.

Childhood-onset schizophrenia (COS) is a rare form of schizophrenia with an onset before 13 years of age. There is rising evidence that genetic factors play a major role in COS etiology, yet, only a few single gene mutations have been discovered. Here we present a diagnostic whole-exome sequencing (WES) in an Israeli Jewish female with COS and additional neuropsychiatric conditions such as obsessive-compulsive disorder (OCD), anxiety, and aggressive behavior. Variant analysis revealed a de novo novel stop gained variant in GRIA2 gene (NM_000826.4: c.1522 G > T (p.Glu508Ter)). GRIA2 encodes for a subunit of the AMPA sensitive glutamate receptor (GluA2) that functions as ligand-gated ion channel in the central nervous system and plays an important role in excitatory synaptic transmission. GluA2 subunit mutations are known to cause variable neurodevelopmental phenotypes including intellectual disability, autism spectrum disorder, epilepsy, and OCD. Our findings support the potential diagnostic role of WES in COS, identify GRIA2 as possible cause to a broad psychiatric phenotype that includes COS as a major manifestation and expand the previously reported GRIA2 loss of function phenotypes.

Value-complexity tradeoff explains mouse navigational learning.

We introduce a novel methodology for describing animal behavior as a tradeoff between value and complexity, using the Morris Water Maze navigation task as a concrete example. We develop a dynamical system model of the Water Maze navigation task, solve its optimal control under varying complexity constraints, and analyze the learning process in terms of the value and complexity of swimming trajectories. The value of a trajectory is related to its energetic cost and is correlated with swimming time. Complexity is a novel learning metric which measures how unlikely is a trajectory to be generated by a naive animal. Our model is analytically tractable, provides good fit to observed behavior and reveals that the learning process is characterized by early value optimization followed by complexity reduction. Furthermore, complexity sensitively characterizes behavioral differences between mouse strains.

Widespread Allelic Heterogeneity in Complex Traits.

Recent successes in genome-wide association studies (GWASs) make it possible to address important questions about the genetic architecture of complex traits, such as allele frequency and effect size. One lesser-known aspect of complex traits is the extent of allelic heterogeneity (AH) arising from multiple causal variants at a locus. We developed a computational method to infer the probability of AH and applied it to three GWASs and four expression quantitative trait loci (eQTL) datasets. We identified a total of 4,152 loci with strong evidence of AH. The proportion of all loci with identified AH is 4%-23% in eQTLs, 35% in GWASs of high-density lipoprotein (HDL), and 23% in GWASs of schizophrenia. For eQTLs, we observed a strong correlation between sample size and the proportion of loci with AH (R2 = 0.85, p = 2.2 × 10-16), indicating that statistical power prevents identification of AH in other loci. Understanding the extent of AH may guide the development of new methods for fine mapping and association mapping of complex traits.

Identification of loci associated with schizophrenia by genome-wide association and follow-up.

We carried out a genome-wide association study of schizophrenia (479 cases, 2,937 controls) and tested loci with P < 10(-5) in up to 16,726 additional subjects. Of 12 loci followed up, 3 had strong independent support (P < 5 x 10(-4)), and the overall pattern of replication was unlikely to occur by chance (P = 9 x 10(-8)). Meta-analysis provided strongest evidence for association around ZNF804A (P = 1.61 x 10(-7)) and this strengthened when the affected phenotype included bipolar disorder (P = 9.96 x 10(-9)).

Allelic expression analysis in the brain suggests a role for heterogeneous insults affecting epigenetic processes in autism spectrum disorders.

Monoallelic expression, including genomic imprinting, X-chromosome inactivation and random monoallelic expression of autosomal genes are epigenetic phenomena. Genes that are expressed in a monoallelic way may be more vulnerable to genetic or epigenetic mutations. Thus, comprehensive exploration of monoallelic expression in human brains may shed light on complex brain disorders. Autism-related disorders are known to be associated with imprinted genes on chromosome 15. However, it is not clear whether other imprinted regions or other types of monoallelic expression are associated with autism spectrum disorder (ASD). Here, we performed a genome-wide survey of allele expression imbalance (AEI) in the human brain using single-nucleotide polymorphisms (SNPs), in 18 individuals with ASD and 15 controls. Individuals with ASD had the most extreme number of monoallelic expressed SNPs in both the autosomes and the X chromosome. In two cases that were studied in detail, the monoallelic expression was confined to specific brain region or cell type. Using these data, we were also able to define the allelic expression status of known imprinted genes in the human brain and to identify abnormal imprinting in an individual with ASD. Lastly, we developed an analysis of individual-level expression, focusing on the difference of each individual from the mean. We found that individuals with ASD had more genes that were up- or down-regulated in an individual-specific manner. We also identified pathways perturbed in specific individuals. These results underline the heterogeneity in gene regulation in ASD, at the level of both allelic and total expression.

Competing targets of microRNA-608 affect anxiety and hypertension.

MicroRNAs (miRNAs) can repress multiple targets, but how a single de-balanced interaction affects others remained unclear. We found that changing a single miRNA-target interaction can simultaneously affect multiple other miRNA-target interactions and modify physiological phenotype. We show that miR-608 targets acetylcholinesterase (AChE) and demonstrate weakened miR-608 interaction with the rs17228616 AChE allele having a single-nucleotide polymorphism (SNP) in the 3'-untranslated region (3'UTR). In cultured cells, this weakened interaction potentiated miR-608-mediated suppression of other targets, including CDC42 and interleukin-6 (IL6). Postmortem human cortices homozygote for the minor rs17228616 allele showed AChE elevation and CDC42/IL6 decreases compared with major allele homozygotes. Additionally, minor allele heterozygote and homozygote subjects showed reduced cortisol and elevated blood pressure, predicting risk of anxiety and hypertension. Parallel suppression of the conserved brain CDC42 activity by intracerebroventricular ML141 injection caused acute anxiety in mice. We demonstrate that SNPs in miRNA-binding regions could cause expanded downstream effects changing important biological pathways.

Global coevolution of human microRNAs and their target genes.

MicroRNAs (miRNAs) have presumably contributed to the emergence of the novel expression patterns, higher brain functions, and skills underlying human evolution. However, it is incompletely understood how new miRNAs have evolved in the human lineage because their initial emergence predictably entailed deleterious consequences due to their powerful multitarget effects. Here, we report genetic variation and conservation parameters for miRNAs and their predicted targets in the genomes of 1,092 humans and 58 additional organisms. We show that miRNAs were evolutionarily more conserved than their predicted binding sites, which were inversely subject to the accumulation of single-nucleotide variations over short evolutionary timescales. Moreover, the predictably "younger" human-specific miRNAs presented lower genetic variation than other miRNAs; their targets displayed higher genetic variation compared with other miRNA targets in diverse human populations; and neuronal miRNAs showed yet lower levels of genetic variation and were found to target more protein-coding genes than nonneuronal miRNAs. Furthermore, enrichment analysis indicated that targets of human-specific miRNAs primarily perform neuronal functions. Specifically, the genomic regions harboring the vertebrate-conserved neuronal miRNA-132 presented considerably higher conservation scores than those of its target genes throughout evolution, whereas both the recently evolved human miRNA-941 and its acquired targets showed relatively low conservation. Our findings demonstrate inversely correlated genetic variation around miRNAs and their targets, consistent with theories of coevolution of these elements and the predicted role attributed to miRNAs in recent human evolution.

Networks of neuronal genes affected by common and rare variants in autism spectrum disorders.

Autism spectrum disorders (ASD) are neurodevelopmental disorders with phenotypic and genetic heterogeneity. Recent studies have reported rare and de novo mutations in ASD, but the allelic architecture of ASD remains unclear. To assess the role of common and rare variations in ASD, we constructed a gene co-expression network based on a widespread survey of gene expression in the human brain. We identified modules associated with specific cell types and processes. By integrating known rare mutations and the results of an ASD genome-wide association study (GWAS), we identified two neuronal modules that are perturbed by both rare and common variations. These modules contain highly connected genes that are involved in synaptic and neuronal plasticity and that are expressed in areas associated with learning and memory and sensory perception. The enrichment of common risk variants was replicated in two additional samples which include both simplex and multiplex families. An analysis of the combined contribution of common variants in the neuronal modules revealed a polygenic component to the risk of ASD. The results of this study point toward contribution of minor and major perturbations in the two sub-networks of neuronal genes to ASD risk.

Analyses of Conditional Knockout Mice for Pogz, a Gene Responsible for Neurodevelopmental Disorders in Excitatory and Inhibitory Neurons in the Brain.

POGZ (Pogo transposable element derived with ZNF domain) is known to function as a regulator of gene expression. While variations in the POGZ gene have been associated with intellectual disabilities and developmental delays in humans, the exact pathophysiological mechanisms remain unclear. To shed light on this, we created two lines of conditional knockout mice for Pogz, one specific to excitatory neurons (Emx1-Pogz mice) and the other to inhibitory neurons (Gad2-Pogz mice) in the brain. Emx1-Pogz mice showed a decrease in body weight, similar to total Pogz knockout mice. Although the two lines did not display significant morphological abnormalities in the telencephalon, impaired POGZ function affected the electrophysiological properties of both excitatory and inhibitory neurons differently. These findings suggest that these mouse lines could be useful tools for clarifying the precise pathophysiological mechanisms of neurodevelopmental disorders associated with POGZ gene abnormalities.

The killifish germline regulates longevity and somatic repair in a sex-specific manner.

Classical evolutionary theories propose tradeoffs between reproduction, damage repair, and lifespan. However, the specific role of the germline in shaping vertebrate aging remains largely unknown. Here, we use the turquoise killifish ( N. furzeri ) to genetically arrest germline development at discrete stages, and examine how different modes of infertility impact life-history. We first construct a comprehensive single-cell gonadal atlas, providing cell-type-specific markers for downstream phenotypic analysis. Next, we show that germline depletion - but not arresting germline differentiation - enhances damage repair in female killifish. Conversely, germline-depleted males instead showed an extension in lifespan and rejuvenated metabolic functions. Through further transcriptomic analysis, we highlight enrichment of pro-longevity pathways and genes in germline-depleted male killifish and demonstrate functional conservation of how these factors may regulate longevity in germline-depleted C. elegans . Our results therefore demonstrate that different germline manipulation paradigms can yield pronounced sexually dimorphic phenotypes, implying alternative responses to classical evolutionary tradeoffs.

The killifish germline regulates longevity and somatic repair in a sex-specific manner.

Classical evolutionary theories propose tradeoffs among reproduction, damage repair and lifespan. However, the specific role of the germline in shaping vertebrate aging remains largely unknown. In this study, we used the turquoise killifish (Nothobranchius furzeri) to genetically arrest germline development at discrete stages and examine how different modes of infertility impact life history. We first constructed a comprehensive single-cell gonadal atlas, providing cell-type-specific markers for downstream phenotypic analysis. We show here that germline depletion-but not arresting germline differentiation-enhances damage repair in female killifish. Conversely, germline-depleted males instead showed an extension in lifespan and rejuvenated metabolic functions. Through further transcriptomic analysis, we highlight enrichment of pro-longevity pathways and genes in germline-depleted male killifish and demonstrate functional conservation of how these factors may regulate longevity in germline-depleted Caenorhabditis elegans. Our results, therefore, demonstrate that different germline manipulation paradigms can yield pronounced sexually dimorphic phenotypes, implying alternative responses to classical evolutionary tradeoffs.

Identification of a functional rare variant in autism using genome-wide screen for monoallelic expression.

Recent work has led to the identification of several susceptibility genes for autism spectrum disorder (ASD) and an increased appreciation of the importance of rare and de novo mutations. Some of the mutations may be very hard to detect using current strategies, especially if they are located in regulatory regions. We present a new approach to identify functional mutations that exploit the fact that many rare mutations disrupt the expression of genes from a single parental chromosome. The method incorporates measurement of the relative expression of the two copies of a gene across the genome using single nucleotide polymorphism arrays. Allelic expression has been successfully used to study common regulatory polymorphisms; however, it has not been implemented as a screening tool for rare mutation. We tested the potential of this approach by screening for monoallelic expression in lymphoblastoid cell lines derived from a small ASD cohort. After filtering regions shared across multiple samples, we identified genes showing monoallelic expression in specific ASD samples. Validation by quantitative sequencing demonstrated that the genes (or only part of them) are monoallelic expressed. The genes included both previously suspected risk factors for ASD and novel candidates. In one gene, named autism susceptibility candidate 2 (AUTS2), we identified a rare duplication that is likely to be the cause of monoallelic expression. Our results demonstrate the ability to identify rare regulatory mutations using genome-wide allelic expression screens, capabilities that could be expanded to other diseases, especially those with suspected involvement of rare dominantly acting mutations.

Predicting gene knockout effects from expression data.

BACKGROUND: The study of gene essentiality, which measures the importance of a gene for cell division and survival, is used for the identification of cancer drug targets and understanding of tissue-specific manifestation of genetic conditions. In this work, we analyze essentiality and gene expression data from over 900 cancer lines from the DepMap project to create predictive models of gene essentiality. METHODS: We developed machine learning algorithms to identify those genes whose essentiality levels are explained by the expression of a small set of "modifier genes". To identify these gene sets, we developed an ensemble of statistical tests capturing linear and non-linear dependencies. We trained several regression models predicting the essentiality of each target gene, and used an automated model selection procedure to identify the optimal model and hyperparameters. Overall, we examined linear models, gradient boosted trees, Gaussian process regression models, and deep learning networks. RESULTS: We identified nearly 3000 genes for which we accurately predict essentiality using gene expression data of a small set of modifier genes. We show that both in the number of genes we successfully make predictions for, as well as in the prediction accuracy, our model outperforms current state-of-the-art works. CONCLUSIONS: Our modeling framework avoids overfitting by identifying the small set of modifier genes, which are of clinical and genetic importance, and ignores the expression of noisy and irrelevant genes. Doing so improves the accuracy of essentiality prediction in various conditions and provides interpretable models. Overall, we present an accurate computational approach, as well as interpretable modeling of essentiality in a wide range of cellular conditions, thus contributing to a better understanding of the molecular mechanisms that govern tissue-specific effects of genetic disease and cancer.

Genetic insights into childhood-onset schizophrenia: The yield of clinical exome sequencing.

Childhood-onset schizophrenia (COS) is a rare form of schizophrenia with an onset prior to 13 years of age. Although genetic factors play a role in COS etiology, only a few causal variants have been reported to date. This study presents a diagnostic exome sequencing (ES) in 37 Israeli Jewish families with a proband diagnosed with COS. By implementing a trio/duo ES approach and applying a well-established diagnostic pipeline, we detected clinically significant variants in 7 probands (19 %). These single nucleotide variants and indels were mostly inherited. The implicated genes were ANKRD11, GRIA2, CHD2, CLCN3, CLTC, IGF1R and MICU1. In a secondary analysis that compared COS patients to 4721 healthy controls, we observed that patients had a significant enrichment of rare loss of function (LoF) variants in LoF intolerant genes associated with developmental diseases. Taken together, ES could be considered as a valuable tool in the genetic workup for COS patients.