Functional genomics in Spiralia

Our understanding of the mechanisms that modulate gene expression in animals is strongly biased by studying a handful of model species that mainly belong to three groups: Insecta, Nematoda and Vertebrata. However, over half of the animal phyla belong to Spiralia, a morphologically and ecologically diverse animal clade with many species of economic and biomedical importance. Therefore, investigating genome regulation in this group is central to uncovering ancestral and derived features in genome functioning in animals, which can also be of significant societal impact. Here, we focus on five aspects of gene expression regulation to review our current knowledge of functional genomics in Spiralia. Although some fields, such as single-cell transcriptomics, are becoming more common, the study of chromatin accessibility, DNA methylation, histone post-translational modifications and genome architecture are still in their infancy. Recent efforts to generate chromosome-scale reference genome assemblies for greater species diversity and optimise state-of-the-art approaches for emerging spiralian research systems will address the existing knowledge gaps in functional genomics in this animal group.

oggmap: a Python package to extract gene ages per orthogroup and link them with single-cell RNA data

SUMMARY

For model species, single-cell RNA-based cell atlases are available. A good cell atlas includes all major stages in a species' ontogeny, and soon, they will be standard even for nonmodel species. Here, we propose a Python package called oggmap, which allows for the easy extraction of an orthomap (gene ages per orthogroup) for any given query species from OrthoFinder and other gene family data resources, like homologous groups from eggNOG or PLAZA. oggmap provides extracted gene ages for more than thousand eukaryotic species which can be further used to calculate gene age-weighted expression data from scRNA sequencing objects using the Python Scanpy toolkit. Not limited to one transcriptome evolutionary index, oggmap can visualize the individual gene category (e.g. age class, nucleotide diversity bin) and their corresponding expression profiles to investigate scRNA-based cell type assignments in an evolutionary context.

AVAILABILITY AND IMPLEMENTATION

oggmap source code is available at https://github.com/kullrich/oggmap, documentation is available at https://oggmap.readthedocs.io/en/latest/. oggmap can be installed via PyPi or directly used via a docker container.

Pathogenic SCN2A variants cause early-stage dysfunction in patient-derived neurons

Pathogenic heterozygous variants in SCN2A, which encodes the neuronal sodium channel NaV1.2, cause different types of epilepsy or intellectual disability (ID)/autism without seizures. Previous studies using mouse models or heterologous systems suggest that NaV1.2 channel gain-of-function typically causes epilepsy, whereas loss-of-function leads to ID/autism. How altered channel biophysics translate into patient neurons remains unknown. Here, we investigated iPSC-derived early-stage cortical neurons from ID patients harboring diverse pathogenic SCN2A variants [p.(Leu611Valfs*35); p.(Arg937Cys); p.(Trp1716*)] and compared them with neurons from an epileptic encephalopathy (EE) patient [p.(Glu1803Gly)] and controls. ID neurons consistently expressed lower NaV1.2 protein levels. In neurons with the frameshift variant, NaV1.2 mRNA and protein levels were reduced by ~ 50%, suggesting nonsense-mediated decay and haploinsufficiency. In other ID neurons, only protein levels were reduced implying NaV1.2 instability. Electrophysiological analysis revealed decreased sodium current density and impaired action potential (AP) firing in ID neurons, consistent with reduced NaV1.2 levels. In contrast, epilepsy neurons displayed no change in NaV1.2 levels or sodium current density, but impaired sodium channel inactivation. Single-cell transcriptomics identified dysregulation of distinct molecular pathways including inhibition of oxidative phosphorylation in neurons with SCN2A haploinsufficiency and activation of calcium signaling and neurotransmission in epilepsy neurons. Together, our patient iPSC-derived neurons reveal characteristic sodium channel dysfunction consistent with biophysical changes previously observed in heterologous systems. Additionally, our model links the channel dysfunction in ID to reduced NaV1.2 levels and uncovers impaired AP firing in early-stage neurons. The altered molecular pathways may reflect a homeostatic response to NaV1.2 dysfunction and can guide further investigations.

Midfrontal theta dynamics index the monitoring of postural stability

Stepping is a common strategy to recover postural stability and maintain upright balance. Postural perturbations have been linked to neuroelectrical markers such as the N1 potential and theta frequency dynamics. Here, we investigated the role of cortical midfrontal theta dynamics of balance monitoring, driven by balance perturbations at different initial standing postures. We recorded electroencephalography, electromyography, and motion tracking of human participants while they stood on a platform that delivered a range of forward and backward whole-body balance perturbations. The participants' postural threat was manipulated prior to the balance perturbation by instructing them to lean forward or backward while keeping their feet-in-place in response to the perturbation. We hypothesized that midfrontal theta dynamics index the engagement of a behavioral monitoring system and, therefore, that perturbation-induced theta power would be modulated by the initial leaning posture and perturbation intensity. Targeted spatial filtering in combination with mixed-effects modeling confirmed our hypothesis and revealed distinct modulations of theta power according to postural threat. Our results provide novel evidence that midfrontal theta dynamics subserve action monitoring of human postural balance. Understanding of cortical mechanisms of balance control is crucial for studying balance impairments related to aging and neurological conditions (e.g. stroke).

Examining the Boundary Sharpness Coefficient as an Index of Cortical Microstructure in Autism Spectrum Disorder

Autism spectrum disorder (ASD) is associated with atypical brain development. However, the phenotype of regionally specific increased cortical thickness observed in ASD may be driven by several independent biological processes that influence the gray/white matter boundary, such as synaptic pruning, myelination, or atypical migration. Here, we propose to use the boundary sharpness coefficient (BSC), a proxy for alterations in microstructure at the cortical gray/white matter boundary, to investigate brain differences in individuals with ASD, including factors that may influence ASD-related heterogeneity (age, sex, and intelligence quotient). Using a vertex-based meta-analysis and a large multicenter structural magnetic resonance imaging (MRI) dataset, with a total of 1136 individuals, 415 with ASD (112 female; 303 male), and 721 controls (283 female; 438 male), we observed that individuals with ASD had significantly greater BSC in the bilateral superior temporal gyrus and left inferior frontal gyrus indicating an abrupt transition (high contrast) between white matter and cortical intensities. Individuals with ASD under 18 had significantly greater BSC in the bilateral superior temporal gyrus and right postcentral gyrus; individuals with ASD over 18 had significantly increased BSC in the bilateral precuneus and superior temporal gyrus. Increases were observed in different brain regions in males and females, with larger effect sizes in females. BSC correlated with ADOS-2 Calibrated Severity Score in individuals with ASD in the right medial temporal pole. Importantly, there was a significant spatial overlap between maps of the effect of diagnosis on BSC when compared with cortical thickness. These results invite studies to use BSC as a possible new measure of cortical development in ASD and to further examine the microstructural underpinnings of BSC-related differences and their impact on measures of cortical morphology.