Region-specific expression of Dickkopf-like1 in the adult brain. Abbreviated title: Dkkl1 in the adult brain

Constructing a Multiple Sclerosis Diagnosis Model Based on Microarray

Introduction

Multiple sclerosis is an immune-mediated demyelinating disorder of the central nervous system. Because of the complexity of etiology, pathology, clinical manifestations, and the diversity of classification, the diagnosis of MS is very difficult. We found that McDonald Criteria is very strict and relies heavily on the evidence for DIS and DIT. Therefore, we hope to find a new method to supplement the evidence and improve the accuracy of MS diagnosis.

Results

We finally selected GSE61240, GSE18781, and GSE185047 based on the GPL570 platform to build a diagnosis model. We initially selected 54 MS susceptibility locus genes identified by IMSGC and WTCCC2 as predictors for the model. After Random Forests and other series of screening, the logistic regression model was established with 4 genes as the final predictors. In external validation, the model showed high accuracy with an AUC of 0.96 and an accuracy of 86.30%. Finally, we established a nomogram and an online prediction tool to better display the diagnosis model.

Conclusion

The diagnosis model based on microarray data in this study has a high degree of discrimination and calibration in the validation set, which is helpful for diagnosis in the absence of evidence for DIS and DIT. Only one SLE case was misdiagnosed as MS, indicating that the model has a high specificity (93.93%), which is useful for differential diagnosis. The significance of the study lies in proving that it is feasible to identify MS by peripheral blood RNA, and the further application of the model and be used as a supplement to McDonald Criteria still need to be trained with larger sample size.

Hypothalamic transcriptome of tame and aggressive silver foxes (Vulpes vulpes) identifies gene expression differences shared across brain regions

The underlying neurological events accompanying dog domestication remain elusive. To reconstruct the domestication process in an experimental setting, silver foxes (Vulpes vulpes) have been deliberately bred for tame vs aggressive behaviors for more than 50 generations at the Institute for Cytology and Genetics in Novosibirsk, Russia. The hypothalamus is an essential part of the hypothalamic-pituitary-adrenal axis and regulates the fight-or-flight response, and thus, we hypothesized that selective breeding for tameness/aggressiveness has shaped the hypothalamic transcriptomic profile. RNA-seq analysis identified 70 differentially expressed genes (DEGs). Seven of these genes, DKKL1, FBLN7, NPL, PRIMPOL, PTGRN, SHCBP1L and SKIV2L, showed the same direction expression differences in the hypothalamus, basal forebrain and prefrontal cortex. The genes differentially expressed across the three tissues are involved in cell division, differentiation, adhesion and carbohydrate processing, suggesting an association of these processes with selective breeding. Additionally, 159 transcripts from the hypothalamus demonstrated differences in the abundance of alternative spliced forms between the tame and aggressive foxes. Weighted gene coexpression network analyses also suggested that gene modules in hypothalamus were significantly associated with tame vs aggressive behavior. Pathways associated with these modules include signal transduction, interleukin signaling, cytokine-cytokine receptor interaction and peptide ligand-binding receptors (eg, G-protein coupled receptor [GPCR] ligand binding). Current studies show the selection for tameness vs aggressiveness in foxes is associated with unique hypothalamic gene profiles partly shared with other brain regions and highlight DEGs involved in biological processes such as development, differentiation and immunological responses. The role of these processes in fox and dog domestication remains to be determined.

Genomic responses to selection for tame/aggressive behaviors in the silver fox (Vulpes vulpes)

Animal domestication efforts have led to a shared spectrum of striking behavioral and morphological changes. To recapitulate this process, silver foxes have been selectively bred for tame and aggressive behaviors for more than 50 generations at the Institute for Cytology and Genetics in Novosibirsk, Russia. To understand the genetic basis and molecular mechanisms underlying the phenotypic changes, we profiled gene expression levels and coding SNP allele frequencies in two brain tissue specimens from 12 aggressive foxes and 12 tame foxes. Expression analysis revealed 146 genes in the prefrontal cortex and 33 genes in the basal forebrain that were differentially expressed, with a 5% false discovery rate (FDR). These candidates include genes in key pathways known to be critical to neurologic processing, including the serotonin and glutamate receptor pathways. In addition, 295 of the 31,000 exonic SNPs show significant allele frequency differences between the tame and aggressive populations (1% FDR), including genes with a role in neural crest cell fate determination.

Circuit-wide Transcriptional Profiling Reveals Brain Region-Specific Gene Networks Regulating Depression Susceptibility

Depression is a complex, heterogeneous disorder and a leading contributor to the global burden of disease. Most previous research has focused on individual brain regions and genes contributing to depression. However, emerging evidence in humans and animal models suggests that dysregulated circuit function and gene expression across multiple brain regions drive depressive phenotypes. Here, we performed RNA sequencing on four brain regions from control animals and those susceptible or resilient to chronic social defeat stress at multiple time points. We employed an integrative network biology approach to identify transcriptional networks and key driver genes that regulate susceptibility to depressive-like symptoms. Further, we validated in vivo several key drivers and their associated transcriptional networks that regulate depression susceptibility and confirmed their functional significance at the levels of gene transcription, synaptic regulation, and behavior. Our study reveals novel transcriptional networks that control stress susceptibility and offers fundamentally new leads for antidepressant drug discovery.