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Aneichyk, T.

Publications and source records attributed to Aneichyk, T..

3 recordsLinked to original sources

Tissue and cell-type specific molecular and functional signatures of 16p11.2 reciprocal genomic disorder across mouse brain and human neuronal models

Recurrent deletion and duplication of [~]743 kilobases of unique genomic sequence and segmental duplications at chromosome 16p11.2 underlie a reciprocal genomic disorder (RGD; OMIM 611913 and 614671) associated with neurodevelopmental and psychiatric phenotypes, including intellectual disability, autism spectrum disorder (ASD), and schizophrenia (SCZ). To define molecular alterations associated with the 16p11.2 RGD, we performed transcriptome analyses of mice with reciprocal copy number variants (CNVs) of the syntenic chromosome 7qF3 region and human neuronal models derived from isogenic human induced pluripotent stem cells (hiPSCs) carrying CRISPR-engineered CNVs at 16p11.2. Analysis of differentially expressed genes (DEGs) in mouse cortex, striatum, cerebellum and three non-brain tissues, as well as in human neural stem cells and induced glutamatergic neurons revealed that the strongest and most consistent effects occurred within the CNV sequence, with notable instances of differential expression of genes in the immediate vicinity that could reflect position effect. While differential expression of genes outside of chromosome 16p11.2 was largely region, tissue, and cell type-specific, a small but significant minority of such DEGs was shared between brain regions or human cell types. Gene Ontology (GO) enrichment analyses to identify cellular processes dysregulated due to these CNVs found support in select circumstances for terms related to energy metabolism, RNA metabolism, and translation but did not reveal a single universally affected process. Weighted gene co-expression network analysis identified modules that showed significant correlation with reciprocal or individual CNV genotype and better captured shared effects, indicating that energy metabolism, RNA metabolism, translation and protein targeting were disrupted across all three brain regions. The first two of these processes also emerged in the human neural stem cell (NSC) data. A subset of co-expression modules that correlated with CNV genotype revealed significant enrichments for known neurodevelopmental disorder genes, loss-of-function constrained genes, FMRP targets, and chromatin modifiers. Intriguingly, neuronal differentiation of the hiPSCs revealed that both the deletion and duplication CNV resulted in similar deficits in neurite extension and branching and alterations in electrical activity. Finally, generation of cerebral organoid derivatives indicated that the CNVs reciprocally altered the ratio of excitatory and inhibitory GABAergic neurons generated during in vitro neurodevelopment, consistent with a major mechanistic hypothesis for ASD. Collectively, our data suggest that the 16p11.2 RGD involves disruption of multiple biological processes, with a relative impact that is context-specific. Perturbation of individual and multiple genes within the CNV region will be required to dissect single-gene effects, uncover regulatory interactions, and define how each contributes to abnormal neurodevelopment.

genomics↗

Comprehensive evaluation of cell-type quantification methods for immuno-oncology

MotivationThe composition and density of immune cells in the tumor microenvironment profoundly influence tumor progression and success of anti-cancer therapies. Flow cytometry, immunohistochemistry staining, or single-cell sequencing is often unavailable such that we rely on computational methods to estimate the immune-cell composition from bulk RNA-sequencing (RNA-seq) data. Various methods have been proposed recently, yet their capabilities and limitations have not been evaluated systematically. A general guideline leading the research community through cell type deconvolution is missing. ResultsWe developed a systematic approach for benchmarking such computational methods and assessed the accuracy of tools at estimating nine different immune- and stromal cells from bulk RNA-seq samples. We used a single-cell RNA-seq dataset of [~]11,000 cells from the tumor microenvironment to simulate bulk samples of known cell type proportions, and validated the results using independent, publicly available gold-standard estimates. This allowed us to analyze and condense the results of more than a hundred thousand predictions to provide an exhaustive evaluation across seven computational methods over nine cell types and [~]1,800 samples from five simulated and real-world datasets. We demonstrate that computational deconvolution performs at high accuracy for well-defined cell-type signatures and propose how fuzzy cell-type signatures can be improved. We suggest that future efforts should be dedicated to refining cell population definitions and finding reliable signatures. AvailabilityA snakemake pipeline to reproduce the benchmark is available at https://github.com/grst/immune_deconvolution_benchmark. An R package allows the community to perform integrated deconvolution using different methods (https://grst.github.io/immunedeconv). Contactg.sturm@tum.de Supplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗

Dissecting the Causal Mechanism of X-Linked Dystonia-Parkinsonism by Integrating Genome and Transcriptome Assembly

X-linked Dystonia-Parkinsonism (XDP) is a Mendelian neurodegenerative disease endemic to the Philippines. We integrated genome and transcriptome assembly with induced pluripotent stem cell-based modeling to identify the XDP causal locus and potential pathogenic mechanism. Genome sequencing identified novel variation that was shared by all probands and three recombination events that narrowed the causal locus to a genomic segment including TAF1. Transcriptome assembly in neural derivative cells discovered novel TAF1 transcripts, including a truncated transcript exclusively observed in probands that involved aberrant splicing and intron retention (IR) associated with a SINE-VNTR-Alu (SVA)-type retrotransposon insertion. This IR correlated with decreased expression of the predominant TAF1 transcript and altered expression of neurodevelopmental genes; both the IR and aberrant TAF1 expression patterns were rescued by CRISPR/Cas9 excision of the SVA. These data suggest a unique genomic cause of XDP and may provide a roadmap for integrative genomic studies in other unsolved Mendelian disorders.\n\nHighlights O_LIGenome assembly narrows the XDP causal locus to a segment including TAF1\nC_LIO_LIXDP-specific SVA insertion induces intron retention and down-regulation of TAF1\nC_LIO_LICRISPR/Cas9 excision of SVA rescues aberrant splicing and cTAF1 expression in XDP\nC_LIO_LIGene networks perturbed in proband cells associate to synapse and neurodevelopment\nC_LI

genomics↗