Gene co-expression network analysis for identifying modules and functionally enriched pathways in SCA2

Spinocerebellar ataxia type 2 (SCA2) is an autosomal dominant neurodegenerative disease caused by CAG repeat expansion in the ATXN2 gene. The repeat resides in an encoded region of the gene resulting in polyglutamine (polyQ) expansion which has been assumed to result in gain of function, predominantly, for the ATXN2 protein. We evaluated temporal cerebellar expression profiles by RNA sequencing of ATXN2Q127 mice versus wild-type (WT) littermates. ATXN2Q127 mice are characterized by a progressive motor phenotype onset, and have progressive cerebellar molecular and neurophysiological (Purkinje cell firing frequency) phenotypes. Our analysis revealed previously uncharacterized early and progressive abnormal patterning of cerebellar gene expression. Weighted Gene Coexpression Network Analysis revealed four gene modules that were significantly correlated with disease status, composed primarily of genes associated with GTPase signaling, calcium signaling and cell death. Of these genes, few overlapped with differentially expressed cerebellar genes that we identified in Atxn2−/− knockout mice versus WT littermates, suggesting that loss-of-function is not a significant component of disease pathology. We conclude that SCA2 is a disease characterized by gain of function for ATXN2

Neurodegeneration in SCA14 is associated with increased PKCγ kinase activity, mislocalization and aggregation

Abstract Spinocerebellar ataxia type 14 (SCA14) is a subtype of the autosomal dominant cerebellar ataxias that is characterized by slowly progressive cerebellar dysfunction and neurodegeneration. SCA14 is caused by mutations in the PRKCG gene, encoding protein kinase C gamma (PKCγ). Despite the identification of 40 distinct disease-causing mutations in PRKCG, the pathological mechanisms underlying SCA14 remain poorly understood. Here we report the molecular neuropathology of SCA14 in post-mortem cerebellum and in human patient-derived induced pluripotent stem cells (iPSCs) carrying two distinct SCA14 mutations in the C1 domain of PKCγ, H36R and H101Q. We show that endogenous expression of these mutations results in the cytoplasmic mislocalization and aggregation of PKCγ in both patient iPSCs and cerebellum. PKCγ aggregates were not efficiently targeted for degradation. Moreover, mutant PKCγ was found to be hyper-activated, resulting in increased substrate phosphorylation. Together, our findings demonstrate that a combination of both, loss-of-function and gain-of-function mechanisms are likely to underlie the pathogenesis of SCA14, caused by mutations in the C1 domain of PKCγ. Importantly, SCA14 patient iPSCs were found to accurately recapitulate pathological features observed in post-mortem SCA14 cerebellum, underscoring their potential as relevant disease models and their promise as future drug discovery tools

Landscape Genomics: Understanding Relationships Between Environmental Heterogeneity and Genomic Characteristics of Populations

Landscape genomics is a rapidly advancing research field that combines population genomics, landscape ecology, and spatial analytical techniques to explicitly quantify the effects of environmental heterogeneity on neutral and adaptive genetic variation and underlying processes. Landscape genomics has tremendous potential for addressing fundamental and applied research questions in various research fields, including ecology, evolution, and conservation biology. However, the unique combination of different scientific disciplines and analytical approaches also constitute a challenge to most researchers wishing to apply landscape genomics. Here, we present an introductory overview of important concepts and methods used in current landscape genomics. For this, we first define the field and explain basic concepts and methods to capture different hypotheses of landscape influences on neutral genetic variation. Next, we highlight established and emerging genomic tools for quantifying adaptive genetic variation in landscape genomic studies. To illustrate the covered topics and to demonstrate the potential of landscape genomics, we provide empirical examples addressing a variety of research question, i.e., the investigation of evolutionary processes driving population differentiation, the landscape genomics of range expanding species, and landscape genomic patterns in organisms of special interest, including species inhabiting aquatic and terrestrial environments. We conclude by outlining remaining challenges and future research avenues in landscape genomics