A Point Mutation in IKAROS ZF1 Causes a B Cell Deficiency in Mice.

IKZF1 (IKAROS) is essential for normal lymphopoiesis in both humans and mice. Previous Ikzf1 mouse models have demonstrated the dual role for IKZF1 in both B and T cell development and have indicated differential requirements of each zinc finger. Furthermore, mutations in IKZF1 are known to cause common variable immunodeficiency in patients characterized by a loss of B cells and reduced Ab production. Through N-ethyl-N-nitrosourea mutagenesis, we have discovered a novel Ikzf1 mutant mouse with a missense mutation (L132P) in zinc finger 1 (ZF1) located in the DNA binding domain. Unlike other previously reported murine Ikzf1 mutations, this L132P point mutation (Ikzf1L132P ) conserves overall protein expression and has a B cell-specific phenotype with no effect on T cell development, indicating that ZF1 is not required for T cells. Mice have reduced Ab responses to immunization and show a progressive loss of serum Igs compared with wild-type littermates. IKZF1L132P overexpressed in NIH3T3 or HEK293T cells failed to localize to pericentromeric heterochromatin and bind target DNA sequences. Coexpression of wild-type and mutant IKZF1, however, allows for localization to pericentromeric heterochromatin and binding to DNA indicating a haploinsufficient mechanism of action for IKZF1L132P Furthermore, Ikzf1+/L132P mice have late onset defective Ig production, similar to what is observed in common variable immunodeficiency patients. RNA sequencing revealed a total loss of Hsf1 expression in follicular B cells, suggesting a possible functional link for the humoral immune response defects observed in Ikzf1L132P/L132P mice.

NINJ1 mediates plasma membrane rupture during lytic cell death.

Plasma membrane rupture (PMR) is the final cataclysmic event in lytic cell death. PMR releases intracellular molecules known as damage-associated molecular patterns (DAMPs) that propagate the inflammatory response1-3. The underlying mechanism of PMR, however, is unknown. Here we show that the cell-surface NINJ1 protein4-8, which contains two transmembrane regions, has an essential role in the induction of PMR. A forward-genetic screen of randomly mutagenized mice linked NINJ1 to PMR. Ninj1-/- macrophages exhibited impaired PMR in response to diverse inducers of pyroptotic, necrotic and apoptotic cell death, and were unable to release numerous intracellular proteins including HMGB1 (a known DAMP) and LDH (a standard measure of PMR). Ninj1-/- macrophages died, but with a distinctive and persistent ballooned morphology, attributable to defective disintegration of bubble-like herniations. Ninj1-/- mice were more susceptible than wild-type mice to infection with Citrobacter rodentium, which suggests a role for PMR in anti-bacterial host defence. Mechanistically, NINJ1 used an evolutionarily conserved extracellular domain for oligomerization and subsequent PMR. The discovery of NINJ1 as a mediator of PMR overturns the long-held idea that cell death-related PMR is a passive event.

IRF2 transcriptionally induces GSDMD expression for pyroptosis.

Gasdermin-D (GSDMD) is cleaved by caspase-1, caspase-4, and caspase-11 in response to canonical and noncanonical inflammasome activation. Upon cleavage, GSDMD oligomerizes and forms plasma membrane pores, resulting in interleukin-1ß (IL-1ß) secretion, pyroptotic cell death, and inflammatory pathologies, including periodic fever syndromes and septic shock-a plague on modern medicine. Here, we showed that IRF2, a member of the interferon regulatory factor (IRF) family of transcription factors, was essential for the transcriptional activation of GSDMD. A forward genetic screen with N-ethyl-N-nitrosourea (ENU)-mutagenized mice linked IRF2 to inflammasome signaling. GSDMD expression was substantially attenuated in IRF2-deficient macrophages, endothelial cells, and multiple tissues, which corresponded with reduced IL-1ß secretion and inhibited pyroptosis. Mechanistically, IRF2 bound to a previously uncharacterized but unique site within the GSDMD promoter to directly drive GSDMD transcription for the execution of pyroptosis. Disruption of this single IRF2-binding site abolished signaling by both the canonical and noncanonical inflammasomes. Together, our data illuminate a key transcriptional mechanism for expression of the gene encoding GSDMD, a critical mediator of inflammatory pathologies.

Agammaglobulinaemia despite terminal B-cell differentiation in a patient with a novel LRBA mutation.

Mutations in lipopolysaccharide-responsive vesicle trafficking, beach and anchor-containing protein (LRBA) cause immune deficiency and inflammation. Here, we are reporting a novel homozygous mutation in LRBA allele in 7-year-old Omani boy, born to consanguineous parents. He presented with type 1 diabetes, autoimmune haematological cytopenia, recurrent chest infections and lymphocytic interstitial lung disease. The patient was treated with CTLA4-Ig (abatacept) with good outcome every 2 weeks for a period of 3 months. He developed complete IgG deficiency, but remarkably, histological examination revealed germinal centres and plasma cells in lymphoid and inflamed lung tissue. Further charatecterisation showed these cells to express IgM but not IgG. This ex vivo analysis suggests that LRBA mutation confers a defect in class switching despite plasma cell formation.

Heterogeneity of Human Neutrophil CD177 Expression Results from CD177P1 Pseudogene Conversion.

Most humans harbor both CD177neg and CD177pos neutrophils but 1-10% of people are CD177null, placing them at risk for formation of anti-neutrophil antibodies that can cause transfusion-related acute lung injury and neonatal alloimmune neutropenia. By deep sequencing the CD177 locus, we catalogued CD177 single nucleotide variants and identified a novel stop codon in CD177null individuals arising from a single base substitution in exon 7. This is not a mutation in CD177 itself, rather the CD177null phenotype arises when exon 7 of CD177 is supplied entirely by the CD177 pseudogene (CD177P1), which appears to have resulted from allelic gene conversion. In CD177 expressing individuals the CD177 locus contains both CD177P1 and CD177 sequences. The proportion of CD177hi neutrophils in the blood is a heritable trait. Abundance of CD177hi neutrophils correlates with homozygosity for CD177 reference allele, while heterozygosity for ectopic CD177P1 gene conversion correlates with increased CD177neg neutrophils, in which both CD177P1 partially incorporated allele and paired intact CD177 allele are transcribed. Human neutrophil heterogeneity for CD177 expression arises by ectopic allelic conversion. Resolution of the genetic basis of CD177null phenotype identifies a method for screening for individuals at risk of CD177 isoimmunisation.

Reliably Detecting Clinically Important Variants Requires Both Combined Variant Calls and Optimized Filtering Strategies.

A diversity of tools is available for identification of variants from genome sequence data. Given the current complexity of incorporating external software into a genome analysis infrastructure, a tendency exists to rely on the results from a single tool alone. The quality of the output variant calls is highly variable however, depending on factors such as sequence library quality as well as the choice of short-read aligner, variant caller, and variant caller filtering strategy. Here we present a two-part study first using the high quality 'genome in a bottle' reference set to demonstrate the significant impact the choice of aligner, variant caller, and variant caller filtering strategy has on overall variant call quality and further how certain variant callers outperform others with increased sample contamination, an important consideration when analyzing sequenced cancer samples. This analysis confirms previous work showing that combining variant calls of multiple tools results in the best quality resultant variant set, for either specificity or sensitivity, depending on whether the intersection or union, of all variant calls is used respectively. Second, we analyze a melanoma cell line derived from a control lymphocyte sample to determine whether software choices affect the detection of clinically important melanoma risk-factor variants finding that only one of the three such variants is unanimously detected under all conditions. Finally, we describe a cogent strategy for implementing a clinical variant detection pipeline; a strategy that requires careful software selection, variant caller filtering optimizing, and combined variant calls in order to effectively minimize false negative variants. While implementing such features represents an increase in complexity and computation the results offer indisputable improvements in data quality.

Comparison of predicted and actual consequences of missense mutations.

Each person's genome sequence has thousands of missense variants. Practical interpretation of their functional significance must rely on computational inferences in the absence of exhaustive experimental measurements. Here we analyzed the efficacy of these inferences in 33 de novo missense mutations revealed by sequencing in first-generation progeny of N-ethyl-N-nitrosourea-treated mice, involving 23 essential immune system genes. PolyPhen2, SIFT, MutationAssessor, Panther, CADD, and Condel were used to predict each mutation's functional importance, whereas the actual effect was measured by breeding and testing homozygotes for the expected in vivo loss-of-function phenotype. Only 20% of mutations predicted to be deleterious by PolyPhen2 (and 15% by CADD) showed a discernible phenotype in individual homozygotes. Half of all possible missense mutations in the same 23 immune genes were predicted to be deleterious, and most of these appear to become subject to purifying selection because few persist between separate mouse substrains, rodents, or primates. Because defects in immune genes could be phenotypically masked in vivo by compensation and environment, we compared inferences by the same tools with the in vitro phenotype of all 2,314 possible missense variants in TP53; 42% of mutations predicted by PolyPhen2 to be deleterious (and 45% by CADD) had little measurable consequence for TP53-promoted transcription. We conclude that for de novo or low-frequency missense mutations found by genome sequencing, half those inferred as deleterious correspond to nearly neutral mutations that have little impact on the clinical phenotype of individual cases but will nevertheless become subject to purifying selection.

Reducing the search space for causal genetic variants with VASP.

MOTIVATION: Increasingly, cost-effective high-throughput DNA sequencing technologies are being utilized to sequence human pedigrees to elucidate the genetic cause of a wide variety of human diseases. While numerous tools exist for variant prioritization within a single genome, the ability to concurrently analyze variants within pedigrees remains a challenge, especially should there be no prior indication of the underlying genetic cause of the disease. Here, we present a tool, variant analysis of sequenced pedigrees (VASP), a flexible data integration environment capable of producing a summary of pedigree variation, providing relevant information such as compound heterozygosity, genome phasing and disease inheritance patterns. Designed to aggregate data across a sequenced pedigree, VASP allows both powerful filtering and custom prioritization of both single nucleotide variants (SNVs) and small indels. Hence, clinical and research users with prior knowledge of a disease are able to dramatically reduce the variant search space based on a wide variety of custom prioritization criteria. AVAILABILITY AND IMPLEMENTATION: Source code available for academic non-commercial research purposes at https://github.com/mattmattmattmatt/VASP.

The RNA-binding protein hnRNPLL induces a T cell alternative splicing program delineated by differential intron retention in polyadenylated RNA.

BACKGROUND: Retention of a subset of introns in spliced polyadenylated mRNA is emerging as a frequent, unexplained finding from RNA deep sequencing in mammalian cells. RESULTS: Here we analyze intron retention in T lymphocytes by deep sequencing polyadenylated RNA. We show a developmentally regulated RNA-binding protein, hnRNPLL, induces retention of specific introns by sequencing RNA from T cells with an inactivating Hnrpll mutation and from B lymphocytes that physiologically downregulate Hnrpll during their differentiation. In Ptprc mRNA encoding the tyrosine phosphatase CD45, hnRNPLL induces selective retention of introns flanking exons 4 to 6; these correspond to the cassette exons containing hnRNPLL binding sites that are skipped in cells with normal, but not mutant or low, hnRNPLL. We identify similar patterns of hnRNPLL-induced differential intron retention flanking alternative exons in 14 other genes, representing novel elements of the hnRNPLL-induced splicing program in T cells. Retroviral expression of a normally spliced cDNA for one of these targets, Senp2, partially corrects the survival defect of Hnrpll-mutant T cells. We find that integrating a number of computational methods to detect genes with differentially retained introns provides a strategy to enrich for alternatively spliced exons in mammalian RNA-seq data, when complemented by RNA-seq analysis of purified cells with experimentally perturbed RNA-binding proteins. CONCLUSIONS: Our findings demonstrate that intron retention in mRNA is induced by specific RNA-binding proteins and suggest a biological significance for this process in marking exons that are poised for alternative splicing.

Gene network inference and visualization tools for biologists: application to new human transcriptome datasets.

Gene regulatory networks inferred from RNA abundance data have generated significant interest, but despite this, gene network approaches are used infrequently and often require input from bioinformaticians. We have assembled a suite of tools for analysing regulatory networks, and we illustrate their use with microarray datasets generated in human endothelial cells. We infer a range of regulatory networks, and based on this analysis discuss the strengths and limitations of network inference from RNA abundance data. We welcome contact from researchers interested in using our inference and visualization tools to answer biological questions.