Expression profiling of cerebrospinal fluid identifies dysregulated antiviral mechanisms in multiple sclerosis

Despite the overwhelming evidence that multiple sclerosis is an autoimmune disease, relatively little is known about the precise nature of the immune dysregulation underlying the development of the disease. Reasoning that the CSF from patients might be enriched for cells relevant in pathogenesis, we have completed a high-resolution single-cell analysis of 96 732 CSF cells collected from 33 patients with multiple sclerosis (n = 48 675) and 48 patients with other neurological diseases (n = 48 057). Completing comprehensive cell type annotation, we identified a rare population of CD8+ T cells, characterized by the upregulation of inhibitory receptors, increased in patients with multiple sclerosis. Applying a Multi-Omics Factor Analysis to these single-cell data further revealed that activity in pathways responsible for controlling inflammatory and type 1 interferon responses are altered in multiple sclerosis in both T cells and myeloid cells. We also undertook a systematic search for expression quantitative trait loci in the CSF cells. Of particular interest were two expression quantitative trait loci in CD8+ T cells that were fine mapped to multiple sclerosis susceptibility variants in the viral control genes ZC3HAV1 (rs10271373) and IFITM2 (rs1059091). Further analysis suggests that these associations likely reflect genetic effects on RNA splicing and cell-type specific gene expression respectively. Collectively, our study suggests that alterations in viral control mechanisms might be important in the development of multiple sclerosis.

Integration of spatial and single-cell transcriptomic data elucidates mouse organogenesis

Molecular profiling of single cells has advanced our knowledge of the molecular basis of development. However, current approaches mostly rely on dissociating cells from tissues, thereby losing the crucial spatial context of regulatory processes. Here, we apply an image-based single-cell transcriptomics method, sequential fluorescence in situ hybridization (seqFISH), to detect mRNAs for 387 target genes in tissue sections of mouse embryos at the 8-12 somite stage. By integrating spatial context and multiplexed transcriptional measurements with two single-cell transcriptome atlases, we characterize cell types across the embryo and demonstrate that spatially resolved expression of genes not profiled by seqFISH can be imputed. We use this high-resolution spatial map to characterize fundamental steps in the patterning of the midbrain-hindbrain boundary (MHB) and the developing gut tube. We uncover axes of cell differentiation that are not apparent from single-cell RNA-sequencing (scRNA-seq) data, such as early dorsal-ventral separation of esophageal and tracheal progenitor populations in the gut tube. Our method provides an approach for studying cell fate decisions in complex tissues and development.

Mitochondrial heteroplasmy in vertebrates using ChIP-sequencing data

BACKGROUND

Mitochondrial heteroplasmy, the presence of more than one mitochondrial DNA (mtDNA) variant in a cell or individual, is not as uncommon as previously thought. It is mostly due to the high mutation rate of the mtDNA and limited repair mechanisms present in the mitochondrion. Motivated by mitochondrial diseases, much focus has been placed into studying this phenomenon in human samples and in medical contexts. To place these results in an evolutionary context and to explore general principles of heteroplasmy, we describe an integrated cross-species evaluation of heteroplasmy in mammals that exploits previously reported NGS data. Focusing on ChIP-seq experiments, we developed a novel approach to detect heteroplasmy from the concomitant mitochondrial DNA fraction sequenced in these experiments.

RESULTS

We first demonstrate that the sequencing coverage of mtDNA in ChIP-seq experiments is sufficient for heteroplasmy detection. We then describe a novel detection method for accurate detection of heteroplasmies, which also accounts for the error rate of NGS technology. Applying this method to 79 individuals from 16 species resulted in 107 heteroplasmic positions present in a total of 45 individuals. Further analysis revealed that the majority of detected heteroplasmies occur in intergenic regions.

CONCLUSION

In addition to documenting the prevalence of mtDNA in ChIP-seq data, the results of our mitochondrial heteroplasmy detection method suggest that mitochondrial heteroplasmies identified across vertebrates share similar characteristics as found for human heteroplasmies. Although largely consistent with previous studies in individual vertebrates, our integrated cross-species analysis provides valuable insights into the evolutionary dynamics of mitochondrial heteroplasmy.