Biology subjects

Rosain, J.

Publications and source records attributed to Rosain, J..

5 recordsLinked to original sources

bioRxiv2020

Human T-bet governs innate and innate-like adaptive IFN-γ immunity against mycobacteria

Inborn errors of human IFN-{gamma} immunity underlie mycobacterial disease. We report a patient with mycobacterial disease due to an inherited deficiency of the transcription factor T-bet. This deficiency abolishes the expression of T-bet target genes, including IFNG, by altering chromatin accessibility and DNA methylation in CD4+ T cells. The patient has profoundly diminished counts of mycobacterial-reactive circulating NK, invariant NKT (iNKT), mucosal-associated invariant T (MAIT), and V{delta}2+ {gamma}{delta} T lymphocytes, and of non-mycobacterial-reactive classic TH1 lymphocytes, the remainders of which also produce abnormally low amounts of IFN-{gamma}. Other IFN-{gamma}-producing lymphocyte subsets however develop normally, but with low levels of IFN-{gamma} production, with exception of V{delta}2- {gamma}{delta} T lymphocytes, which produce normal amounts of IFN-{gamma} in response to non-mycobacterial stimulation, and non-classic TH1 (TH1*) lymphocytes, which produce IFN-{gamma} normally in response to mycobacterial antigens. Human T-bet deficiency thus underlies mycobacterial disease by preventing the development of, and IFN-{gamma} production by, innate (NK) and innate-like adaptive lymphocytes (iNKT, MAIT, and V{delta}2+ {gamma}{delta} T cells), with mycobacterial-specific, IFN-{gamma}-producing, purely adaptive {beta} TH1* cells unable to compensate for this deficit.

immunology↗

bioRxiv2020

Detection of homozygous and hemizygous partial exon deletions by whole-exome sequencing

The detection of copy number variations (CNVs) in whole-exome sequencing (WES) data is important, as CNVs may underlie a number of human genetic disorders. The recently developed HMZDelFinder algorithm can detect rare homozygous and hemizygous (HMZ) deletions in WES data more effectively than other widely used tools. Here, we present HMZDelFinder_opt, an approach that outperforms HMZDelFinder for the detection of HMZ deletions, including partial exon deletions in particular, in typical laboratory cohorts that are generated over time under different experimental conditions. We show that using an optimized reference control set of WES data, based on a PCA-derived Euclidean distance for coverage, strongly improves the detection of HMZ deletions both in real patients carrying validated disease-causing deletions and in simulated data. Furthermore, we develop a sliding window approach enabling HMZDelFinder-opt to identify HMZ partial deletions of exons that are otherwise undiscovered by HMZDelFinder. HMZDelFinder_opt is a timely and powerful approach for detecting HMZ deletions, particularly partial exon deletions, in laboratory cohorts, which are typically heterogeneous.

bioinformatics↗

bioRxiv2020

Multi-batch cytometry data integration for optimal immunophenotyping

We describe the integration of multi-batch cytometry datasets (iMUBAC), a flexible, robust, and scalable computational framework for unsupervised cell-type identification across multiple batches of high-dimensional cytometry datasets. After overlaying cells from healthy controls across multiple batches, iMUBAC learns batch-specific cell-type classification boundaries and identifies aberrant immunophenotypes in patient samples. We illustrate unbiased and streamlined immunophenotyping, using both in-house and public mass and flow cytometry datasets.

bioinformatics↗

bioRxiv2020

Negative selection on human genes causing severe inborn errors depends on disease outcome and both the mode and mechanism of inheritance

BackgroundGenetic variants underlying severe diseases are less likely to be transmitted to the next generation, and are thus gradually and selectively eliminated from the population through negative selection. Here, we study the determinants of this evolutionary process in genes underlying severe diseases in humans. ResultsWe propose a novel approach, CoNeS, integrating known negative selection scores through principal component projection. We compare evidence for negative selection at 319 genes underlying inborn errors of immunity (IEI), which are life-threatening monogenic disorders. We find that genes underlying autosomal dominant (AD) or X-linked IEI are under stronger negative selection than those underlying autosomal recessive (AR) IEI, which are under no stronger selection than genes not known to be disease-causing. However, we find that genes with mutations causing AR IEI that are lethal before reproductive maturity and that display complete penetrance are under stronger negative selection than other genes underlying AR IEI. We also find that genes underlying AD IEI by haploinsufficiency are under stronger negative selection than other genes underlying AD IEI. Finally, we replicate these results in a study of 1,140 genes causing inborn errors of neurodevelopment. ConclusionsThese findings collectively show that the clinical outcomes of inborn errors, together with the mode and mechanism of inheritance of these errors, determine the strength of negative selection acting on severe disease-causing genes. These findings suggest that estimating the intensity of negative selection with CoNeS may facilitate the selection of candidate genes in patients suspected to carry an inborn error.

genetics↗

bioRxiv2019

Homozygous STAT2 gain-of-function mutation by loss of USP18 activity in a patient with type I interferonopathy

Type I interferonopathies are monogenic disorders characterized by enhanced Type I interferon (IFN-I) activity. Inherited ISG15 and USP18 deficiencies underlie type I interferonopathies by preventing the regulation of late responses to IFN-I. Specifically, ISG15/USP18 are induced by IFN-I and sterically hinder JAK1 from binding to the IFNAR2 subunit of IFN-I receptor. We report an infant who died of autoinflammation due to a homozygous missense mutation (R148Q) in STAT2. The variant is gain-of-function (GOF) for ISGF3-dependent induction of late but not early response to IFN-I. Surprisingly, the mutation does not enhance the intrinsic transcriptional activity of ISGF3. Rather, the STAT2 R148Q variant is GOF because it fails to appropriately interact with and traffic USP18 to IFNAR2, preventing USP18 from negatively regulating responses to IFN-I. Overall, a STAT2 missense mutation that fails to facilitate USP18-mediated signal termination in the homozygous state underlies a novel genetic etiology of type I interferonopathy.

immunology↗