The expression pattern of EVA1C, a novel Slit receptor, is consistent with an axon guidance role in the mouse nervous system

Downregulating EVA1C exerts the potential to promote neuron growth after neonatal hypoxic-ischemic encephalopathy injury associated with alternative splicing

Neonatal hypoxic-ischemic encephalopathy (NHIE) is one of the major diseases in newborns during the perinatal stage, which globally is the main reason for children's morbidity and mortality. However, the mechanism of NHIE still remains poorly clear. In this study, the 7-day-old rats were subjected to hypoxic-ischemia (HI), then brain damage was detected. Afterward, the expression of eva-1 homolog C (EVA1C) was measured in vitro by establishing the oxygen-glucose deprivation (OGD) model in SHSY5Y cells and human fetal neurons. Subsequently, the potential function and mechanism of EVA1C were explored by silencing EVA1C and alternative splicing prediction. As a result, obvious neurobehavioral impairment and brain infarction were detected through Zea-Longa score and TTC staining; meanwhile, neuron injury was tested by HE and Nissl staining post HI. Moreover, it was found that the expression of EVA1C was notably upregulated in SHSY5Y cells and human fetal neurons after OGD. In addition, cell survival and growth were increased after silencing EVA1C, which might be associated with alternative splicing. In conclusion, EVA1C interference exhibited potential in promoting neuron survival and growth, associated with exon skipping with the alternative splicing site in 34613318:34687258, which may provide the basis for the therapeutic target and mechanism research of NHIE.

Multiple genome viewer (MGV): a new tool for visualization and comparison of multiple annotated genomes

The assembled and annotated genomes for 16 inbred mouse strains (Lilue et al., Nat Genet 50:1574–1583, 2018) and two wild-derived strains (CAROLI/EiJ and PAHARI/EiJ) (Thybert et al., Genome Res 28:448–459, 2018) are valuable resources for mouse genetics and comparative genomics. We developed the multiple genome viewer (MGV; http://www.informatics.jax.org/mgv) to support visualization, exploration, and comparison of genome annotations within and across these genomes. MGV displays chromosomal regions of user-selected genomes as horizontal tracks. Equivalent features across the genome tracks are highlighted using vertical ‘swim lane’ connectors. Navigation across the genomes is synchronized as a researcher uses the scroll and zoom functions. Researchers can generate custom sets of genes and other genome features to be displayed in MGV by entering genome coordinates, function, phenotype, disease, and/or pathway terms. MGV was developed to be genome agnostic and can be used to display homologous features across genomes of different organisms.

EVA1C Is a Potential Prognostic Biomarker and Correlated With Immune Infiltration Levels in WHO Grade II/III Glioma

Background

Immunotherapy is an effective therapeutic approach for multiple human cancer types. However, the correlations between EVA1C and patients’ prognosis as well as immune infiltration remain obscure. Herein, we employed transcriptomic and clinical data extracted from two independent databases to systematically investigate the role of EVA1C in the oncological context.

Methods

The differential expression of EVA1C was analyzed via TCGA and Oncomine databases. We evaluated the influence of EVA1C on clinical prognosis using Kaplan-Meier plotter. We then used the expression profiler to calculate stromal score, immune score, and ESTIMATE score based on the ESTIMATE algorithm. The abundance of infiltrating immune cells was calculated via TIMER. The correlations between EVA1C expression and immune infiltration levels were analyzed in two independent cohorts.

Results

In patients with World Health Organization (WHO) grade II/III glioma, high EVA1C expression was associated with malignant clinicopathological features and poor overall survival in both cohorts. EVA1C expression was positively associated with immune infiltration levels of B cell, CD4+ T cell, neutrophil, macrophage, and dendritic cells (DCs). Besides, EVA1C expression strongly correlated with diverse immune marker sets. And the predictive power of EVA1C was better than that of other indicators in predicting high immune infiltration levels in glioma.

Conclusions

For the first time, we identified the overexpression of EVA1C in glioma, which was tightly correlated with the high infiltration levels of multiple immune cells as well as poor prognosis. Meanwhile, EVA1C might be a potential biomarker for predicting high immune infiltration in WHO grade II/III gliomas.

An empirical bayesian approach for testing gene expression fold change and its application in detecting global dosage effects

We are motivated by biological studies intended to understand global gene expression fold change. Biologists have generally adopted a fixed cutoff to determine the significance of fold changes in gene expression studies (e.g. by using an observed fold change equal to two as a fixed threshold). Scientists can also use a t-test or a modified differential expression test to assess the significance of fold changes. However, these methods either fail to take advantage of the high dimensionality of gene expression data or fail to test fold change directly. Our research develops a new empirical Bayesian approach to substantially improve the power and accuracy of fold-change detection. Specifically, we more accurately estimate gene-wise error variation in the log of fold change. We then adopt a t-test with adjusted degrees of freedom for significance assessment. We apply our method to a dosage study in Arabidopsis and a Down syndrome study in humans to illustrate the utility of our approach. We also present a simulation study based on real datasets to demonstrate the accuracy of our method relative to error variance estimation and power in fold-change detection. Our developed R package with a detailed user manual is publicly available on GitHub at https://github.com/cuiyingbeicheng/Foldseq.

The Transcriptomic Landscape of Prostate Cancer Development and Progression: An Integrative Analysis

Next-generation sequencing of primary tumors is now standard for transcriptomic studies, but microarray-based data still constitute the majority of available information on other clinically valuable samples, including archive material. Using prostate cancer (PC) as a model, we developed a robust analytical framework to integrate data across different technical platforms and disease subtypes to connect distinct disease stages and reveal potentially relevant genes not identifiable from single studies alone. We reconstructed the molecular profile of PC to yield the first comprehensive insight into its development, by tracking changes in mRNA levels from normal prostate to high-grade prostatic intraepithelial neoplasia, and metastatic disease. A total of nine previously unreported stage-specific candidate genes with prognostic significance were also found. Here, we integrate gene expression data from disparate sample types, disease stages and technical platforms into one coherent whole, to give a global view of the expression changes associated with the development and progression of PC from normal tissue through to metastatic disease. Summary and individual data are available online at the Prostate Integrative Expression Database (PIXdb), a user-friendly interface designed for clinicians and laboratory researchers to facilitate translational research.

Identification of functional mutations associated with environmental variance of litter size in rabbits

Background

Environmental variance (V_E) is partly under genetic control and has recently been proposed as a measure of resilience. Unravelling the genetic background of the V_E of complex traits could help to improve resilience of livestock and stabilize their production across farming systems. The objective of this study was to identify genes and functional mutations associated with variation in V_E of litter size (LS) in rabbits. To achieve this, we combined the results of a genome-wide association study (GWAS) and a whole-genome sequencing (WGS) analysis using data from two divergently selected rabbit lines for high and low V_E of LS. These lines differ in terms of biomarkers of immune response and mortality. Moreover, rabbits with a lower V_E of LS were found to be more resilient to infections than animals with a higher V_E of LS.

Results

By using two GWAS approaches (single-marker regression and Bayesian multiple-marker regression), we identified four genomic regions associated with V_E of LS, on chromosomes 3, 7, 10, and 14. We detected 38 genes in the associated genomic regions and, using WGS, we identified 129 variants in the splicing, UTR, and coding (missense and frameshift effects) regions of 16 of these 38 genes. These genes were related to the immune system, the development of sensory structures, and stress responses. All of these variants (except one) segregated in one of the rabbit lines and were absent (n = 91) or fixed in the other one (n = 37). The fixed variants were in the HDAC9, ITGB8, MIS18A, ENSOCUG00000021276 and URB1 genes. We also identified a 1-bp deletion in the 3′UTR region of the HUNK gene that was fixed in the low V_E line and absent in the high V_E line.

Conclusions

This is the first study that combines GWAS and WGS analyses to study the genetic basis of V_E. The new candidate genes and functional mutations identified in this study suggest that the V_E of LS is under the control of functions related to the immune system, stress response, and the nervous system. These findings could also explain differences in resilience between rabbits with homogeneous and heterogeneous V_E of litter size.

Fibroblast growth factor receptor 1 signaling transcriptionally regulates the axon guidance cue slit1

Axons sense molecular cues in their environment to arrive at their post-synaptic targets. While many of the molecular cues have been identified, the mechanisms that regulate their spatiotemporal expression remain elusive. We examined here the transcriptional regulation of the guidance gene slit1 both in vitro and in vivo by specific fibroblast growth factor receptors (Fgfrs). We identified an Fgf-responsive 2.3 kb slit1 promoter sequence that recapitulates spatiotemporal endogenous expression in the neural tube and eye of Xenopus embryos. We found that signaling through Fgfr1 is the main regulator of slit1 expression both in vitro in A6 kidney epithelial cells, and in the Xenopus forebrain, even when other Fgfr subtypes are present in cells. These data argue that a specific signaling pathway downstream of Fgfr1 controls in a cell-autonomous manner slit1 forebrain expression and are novel in identifying a specific growth factor receptor for in vivo control of the expression of a key embryonic axon guidance cue.

Slit-Robo signalling in heart development

The Slit ligands and their Robo receptors are well-known for their roles during axon guidance in the central nervous system but are still relatively unknown in the cardiac field. However, data from different animal models suggest a broad involvement of the pathway in many aspects of heart development, from cardiac cell migration and alignment, lumen formation, chamber formation, to the formation of the ventricular septum, semilunar and atrioventricular valves, caval veins, and pericardium. Absence of one or more of the genes in the pathway results in defects ranging from bicuspid aortic valves to ventricular septal defects and abnormal venous connections to the heart. Congenital heart defects are the most common congenital malformations found in life new-born babies and progress in methods for large scale human genetic testing has significantly enhanced the identification of new causative genes involved in human congenital heart disease. Recently, loss of function variants in ROBO1 have also been linked to ventricular septal defects and tetralogy of Fallot in patients. Here, we will give an overview of the role of the Slit-Robo signalling pathway in Drosophila, zebrafish, and mouse heart development. The extent of these data warrant further attention on the SLIT-ROBO signalling pathway as a candidate for an array of human congenital heart defects.

Slit-Robo signaling

Slits are secreted proteins that bind to Roundabout (Robo) receptors. Slit-Robo signaling is best known for mediating axon repulsion in the developing nervous system. However, in recent years the functional repertoire of Slits and Robo has expanded tremendously and Slit-Robo signaling has been linked to roles in neurogenesis, angiogenesis and cancer progression among other processes. Likewise, our mechanistic understanding of Slit-Robo signaling has progressed enormously. Here, we summarize new insights into Slit-Robo evolutionary and system-dependent diversity, receptor-ligand interactions, signaling crosstalk and receptor activation.

A Syntenic Cross Species Aneuploidy Genetic Screen Links RCAN1 Expression to β-Cell Mitochondrial Dysfunction in Type 2 Diabetes

Type 2 diabetes (T2D) is a complex metabolic disease associated with obesity, insulin resistance and hypoinsulinemia due to pancreatic β-cell dysfunction. Reduced mitochondrial function is thought to be central to β-cell dysfunction. Mitochondrial dysfunction and reduced insulin secretion are also observed in β-cells of humans with the most common human genetic disorder, Down syndrome (DS, Trisomy 21). To identify regions of chromosome 21 that may be associated with perturbed glucose homeostasis we profiled the glycaemic status of different DS mouse models. The Ts65Dn and Dp16 DS mouse lines were hyperglycemic, while Tc1 and Ts1Rhr mice were not, providing us with a region of chromosome 21 containing genes that cause hyperglycemia. We then examined whether any of these genes were upregulated in a set of ~5,000 gene expression changes we had identified in a large gene expression analysis of human T2D β-cells. This approach produced a single gene, RCAN1, as a candidate gene linking hyperglycemia and functional changes in T2D β-cells. Further investigations demonstrated that RCAN1 methylation is reduced in human T2D islets at multiple sites, correlating with increased expression. RCAN1 protein expression was also increased in db/db mouse islets and in human and mouse islets exposed to high glucose. Mice overexpressing RCAN1 had reduced in vivo glucose-stimulated insulin secretion and their β-cells displayed mitochondrial dysfunction including hyperpolarised membrane potential, reduced oxidative phosphorylation and low ATP production. This lack of β-cell ATP had functional consequences by negatively affecting both glucose-stimulated membrane depolarisation and ATP-dependent insulin granule exocytosis. Thus, from amongst the myriad of gene expression changes occurring in T2D β-cells where we had little knowledge of which changes cause β-cell dysfunction, we applied a trisomy 21 screening approach which linked RCAN1 to β-cell mitochondrial dysfunction in T2D.

The multifaceted roles of Slits and Robos in cortical circuits: from proliferation to axon guidance and neurological diseases

Slit repulsion, mediated by Robo receptors, is known to play a major role in axon guidance in the nervous system. However, recent studies have revealed that in the mammalian cortex these molecules are highly versatile and that their function extends far beyond axon guidance. They act at all phases of development to control neurogenesis, neuronal migration, axon patterning, dendritic outgrowth and spinogenesis. The expression of Robo receptors in cortical and thalamocortical axons (TCAs) is tightly regulated by a combination of transcription factors (TFs), proteases and activity. These findings also suggest that Slit and Robos have influenced the evolution of cortical circuits. Last, novel genetic evidence associates various neurological disorders, such as autism, to abnormal Slit/Robo signaling.