Helper-embedded satellites from an integrase clade that repeatedly targets prophage late genes.

Satellites such as phage-induced chromosomal islands (PICIs) are mobile genetic elements relying on helper phages for their mobilization, through trans-regulatory interactions. We discovered a PICI with a more intimate cis-regulatory configuration, integrated within a late gene of its helper prophage. This helper-embedded PICI (HE-PICI) configuration delays expression of the interrupted helper late gene until the satellite excises and provides passive helper-driven components to both HE-PICI replication and late transcription. Upon induction of a helper-satellite composite, precise excision of the entire composite was observed, followed by composite replication, then satellite excision. We mapped 491 additional HE-PICIs to one of 14 sites in cognates of phage lambda late genes. Associated integrases form a single phylogenetic clade with subclades respecting the 14 site groups, exhibiting repeated tropism for prophage late genes as new integration sites evolve. Four ordered zones in a general gram-negative PICI genome organization are: an integration zone encoding integrase and AlpA, a dynamic zone encoding members of the Bro-N network of domain-swapping DNA-interactive proteins and immunity repressor RNAs, a replication zone, and a dynamic late zone in which clusters as large as 17 consecutive helper prophage late genes have been captured. Helper-embedded satellites present new dimensions in satellite/helper relationships.

Alterations in oligodendrocyte transcriptional networks reveal region-specific vulnerabilities to neurological disease.

Neurological disease is characterized the by dysfunction of specific neuroanatomical regions. To determine whether region-specific vulnerabilities have a transcriptional basis at cell-type-specific resolution, we analyzed gene expression in mouse oligodendrocytes across various brain regions. Oligodendrocyte transcriptomes cluster in an anatomical arrangement along the rostrocaudal axis. Moreover, regional oligodendrocyte populations preferentially regulate genes implicated in diseases that target their region of origin. Systems-level analyses identify five region-specific co-expression networks representing distinct molecular pathways in oligodendrocytes. The cortical network exhibits alterations in mouse models of intellectual disability and epilepsy, the cerebellar network in ataxia, and the spinal network in multiple sclerosis. Bioinformatic analyses reveal potential molecular regulators of these networks, which were confirmed to modulate network expression in vitro in human oligodendroglioma cells, including reversal of the disease-associated transcriptional effects of a pathogenic Spinocerebellar ataxia type 1 allele. These findings identify targetable region-specific vulnerabilities to neurological disease mediated by oligodendrocytes.

multiWGCNA: an R package for deep mining gene co-expression networks in multi-trait expression data.

BACKGROUND: Gene co-expression networks represent modules of genes with shared biological function, and have been widely used to model biological pathways in gene expression data. Co-expression networks associated with a specific trait can be constructed and identified using weighted gene co-expression network analysis (WGCNA), which is especially useful for the study of transcriptional signatures in disease. WGCNA networks are typically constructed using both disease and wildtype samples, so molecular pathways associated with disease are identified. However, it would be advantageous to study such co-expression networks in their disease context across spatiotemporal conditions, but currently there is no comprehensive software implementation for this type of analysis. RESULTS: Here, we introduce a WGCNA-based procedure, multiWGCNA, that is tailored to datasets with variable spatial or temporal traits. As well as constructing the combined network, multiWGCNA also generates a network for each condition separately, and subsequently maps these modules between and across designs, and performs relevant downstream analyses, including module-trait correlation and module preservation. When applied to astrocyte-specific RNA-sequencing (RNA-seq) data from various brain regions of mice with experimental autoimmune encephalitis, multiWGCNA resolved the de novo formation of the neurotoxic astrocyte transcriptional program exclusively in the disease setting. Using time-course RNA-seq from mice with tau pathology (rTg4510), we demonstrate how multiWGCNA can also be used to study the temporal evolution of pathological modules over the course of disease progression. CONCLUSION: The multiWGCNA R package can be applied to expression data with two dimensions, which is especially useful for the study of disease-associated modules across time or space. The source code and functions are freely available at: https://github.com/fogellab/multiWGCNA .