Monderer-Rothkoff, G. et al. AUTS2 isoforms control neuronal differentiation.
Mol Psychiatry (2019).doi:10.1038/s41380-019-0409-1
AbstractMutations in AUTS2 are associated with autism, intellectual disability, and microcephaly. AUTS2 is expressed in the brain and interacts with polycomb proteins, yet it is still unclear how mutations in AUTS2 lead to neurodevelopmental phenotypes. Here we report that when neuronal differentiation is initiated, there is a shift in expression from a long isoform to a short AUTS2 isoform. Yeast two-hybrid screen identified the splicing factor SF3B1 as an interactor of both isoforms, whereas the polycomb group proteins, PCGF3 and PCGF5, were found to interact exclusively with the long AUTS2 isoform. Reporter assays showed that the first exons of the long AUTS2 isoform function as a transcription repressor, but the part that consist of the short isoform acts as a transcriptional activator, both influenced by the cellular context. The expression levels of PCGF3 influenced the ability of the long AUTS2 isoform to activate or repress transcription. Mouse embryonic stem cells (mESCs) with heterozygote mutations in Auts2 had an increase in cell death during in vitro corticogenesis, which was significantly rescued by overexpressing the human AUTS2 transcripts. mESCs with a truncated AUTS2 protein (missing exons 12-20) showed premature neuronal differentiation, whereas cells overexpressing AUTS2, especially the long transcript, showed increase in expression of pluripotency markers and delayed differentiation. Taken together, our data suggest that the precise expression of AUTS2 isoforms is essential for regulating transcription and the timing of neuronal differentiation.
Filo, S. et al. Disentangling molecular alterations from water-content changes in the aging human brain using quantitative MRI.
Nat Commun 10, 3403 (2019).
AbstractIt is an open question whether aging-related changes throughout the brain are driven by a common factor or result from several distinct molecular mechanisms. Quantitative magnetic resonance imaging (qMRI) provides biophysical parametric measurements allowing for non-invasive mapping of the aging human brain. However, qMRI measurements change in response to both molecular composition and water content. Here, we present a tissue relaxivity approach that disentangles these two tissue components and decodes molecular information from the MRI signal. Our approach enables us to reveal the molecular composition of lipid samples and predict lipidomics measurements of the brain. It produces unique molecular signatures across the brain, which are correlated with specific gene-expression profiles. We uncover region-specific molecular changes associated with brain aging. These changes are independent from other MRI aging markers. Our approach opens the door to a quantitative characterization of the biological sources for aging, that until now was possible only post-mortem.
Chow, J. et al. Dissecting the genetic basis of comorbid epilepsy phenotypes in neurodevelopmental disorders.
Genome Med 11, 65 (2019).
AbstractBACKGROUND: Neurodevelopmental disorders (NDDs) such as autism spectrum disorder, intellectual disability, developmental disability, and epilepsy are characterized by abnormal brain development that may affect cognition, learning, behavior, and motor skills. High co-occurrence (comorbidity) of NDDs indicates a shared, underlying biological mechanism. The genetic heterogeneity and overlap observed in NDDs make it difficult to identify the genetic causes of specific clinical symptoms, such as seizures.
METHODS: We present a computational method, MAGI-S, to discover modules or groups of highly connected genes that together potentially perform a similar biological function. MAGI-S integrates protein-protein interaction and co-expression networks to form modules centered around the selection of a single "seed" gene, yielding modules consisting of genes that are highly co-expressed with the seed gene. We aim to dissect the epilepsy phenotype from a general NDD phenotype by providing MAGI-S with high confidence NDD seed genes with varying degrees of association with epilepsy, and we assess the enrichment of de novo mutation, NDD-associated genes, and relevant biological function of constructed modules.
RESULTS: The newly identified modules account for the increased rate of de novo non-synonymous mutations in autism, intellectual disability, developmental disability, and epilepsy, and enrichment of copy number variations (CNVs) in developmental disability. We also observed that modules seeded with genes strongly associated with epilepsy tend to have a higher association with epilepsy phenotypes than modules seeded at other neurodevelopmental disorder genes. Modules seeded with genes strongly associated with epilepsy (e.g., SCN1A, GABRA1, and KCNB1) are significantly associated with synaptic transmission, long-term potentiation, and calcium signaling pathways. On the other hand, modules found with seed genes that are not associated or weakly associated with epilepsy are mostly involved with RNA regulation and chromatin remodeling.
CONCLUSIONS: In summary, our method identifies modules enriched with de novo non-synonymous mutations and can capture specific networks that underlie the epilepsy phenotype and display distinct enrichment in relevant biological processes. MAGI-S is available at
https://github.com/jchow32/magi-s .