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Pedersen, E.

Publications and source records attributed to Pedersen, E..

3 recordsLinked to original sources

DTX4 regulates neural progenitor transitions during cortical development

Neural progenitors drive cellular diversification in the neocortex. Prolongation of their proliferative capacity and increased diversity underpins the evolutionary expansion and morphological complexity of the human neocortex. Here, we investigate the mechanisms that regulate maintenance of the highly proliferative early neural progenitor subtypes and transition to subsequent progenitors of limited proliferative capacity during human and murine neocortical development. We identify DTX4, a Deltex family member, as an evolutionarily conserved molecular determinant of neural progenitor identity in the mammalian neocortex. DTX4 sustains the identity of radial glia, a highly proliferative progenitor subtype. Loss of DTX4, on the other hand, is a prerequisite for the generation of intermediate progenitors which possess low proliferative capacity. Perturbing DTX4 expression in human cerebral organoids and in the murine neocortex, alters progenitor composition, thereby inducing changes in neuronal diversity and cortical morphology. Mechanistically, we reveal that DTX4 controls progenitor identity by regulating the length of the cell cycle. Our findings underscore the critical role of cell cycle dynamics and of DTX4 in determining progenitor identity and thereby defining neuronal outcome during mammalian development. Highlights[bullet] The Deltex family member, DTX4, is expressed in human and murine neuroepithelia and radial glial progenitors but is absent in intermediate progenitor cells. [bullet]DTX4 maintains radial glia identity and prevents generation of intermediate progenitors during murine and human development. [bullet]Disruption of DTX4 expression compromises neuronal composition and neocortical architecture [bullet]DTX4 regulates progenitor identity by regulating cell cycle length

neuroscience↗

Honestly exaggerated: howler monkey roars are reliable signals of body size and behaviourally relevant to listeners

Acoustic signals are key components of animal social behaviour, potentially conveying fitness relevant information about signallers. Howler monkeys produce extremely loud, low frequency roars, which exaggerate the acoustic impression of body size relative to other species. However, it remains unclear whether howler monkey roars contain reliable information about body size within species, and whether conspecific listeners use this information and adjust their responses accordingly. Here, we investigate whether the roars of black and gold howler monkeys (Alouatta caraya) function as an honest signal of body size by examining the relationship between formant spacing and body mass in 11 adult males. We found a strong negative correlation, indicating that larger males produce roars with lower formant spacing. To test the behavioural relevance of variation in formant spacing, we then conducted playback experiments with 23 conspecific listeners, simulating the roars of unknown males of small, average, and large body size. Listeners showed significantly different responses to calls of different body sizes, spending longer orientated towards the playback speaker and being more likely to approach calls simulating larger males. There was no significant impact of simulated body size on the likelihood of listeners vocalising in response, although males spent significantly more time vocalising in response to playbacks than females. Overall, these findings suggest that formant spacing in howler monkey roars serves as an honest indicator of body size and plays a critical role in mediating social interactions. Our study highlights the adaptive significance of acoustic cues to body size, which can provide receivers with accurate information that can be used to assess rivals or choose mates.

animal behavior and cognition↗

Seq-Scope Protocol: Repurposing Illumina Sequencing Flow Cells for High-Resolution Spatial Transcriptomics

Spatial transcriptomics (ST) technologies represent a significant advance in gene expression studies, aiming to profile the entire transcriptome from a single histological slide. These techniques are designed to overcome the constraints faced by traditional methods such as immunostaining and RNA in situ hybridization, which are capable of analyzing only a few target genes simultaneously. However, the application of ST in histopathological analysis is also limited by several factors, including low resolution, a limited range of genes, scalability issues, high cost, and the need for sophisticated equipment and complex methodologies. Seq-Scope--a recently developed novel technology--repurposes the Illumina sequencing platform for high-resolution, high-content spatial transcriptome analysis, thereby overcoming these limitations. Here we provide a detailed step-by-step protocol to implement Seq-Scope with an Illumina NovaSeq 6000 sequencing flow cell that allows for the profiling of multiple tissue sections in an area of 7 mm x 7 mm or larger. In addition to detailing how to prepare a frozen tissue section for both histological imaging and sequencing library preparation, we provide comprehensive instructions and a streamlined computational pipeline to integrate histological and transcriptomic data for high-resolution spatial analysis. This includes the use of conventional software tools for single cell and spatial analysis, as well as our recently developed segmentation-free method for analyzing spatial data at submicrometer resolution. Given its adaptability across various biological tissues, Seq-Scope establishes itself as an invaluable tool for researchers in molecular biology and histology. KEY POINTSO_LIThe protocol outlines a method for repurposing an Illumina NovaSeq 6000 flow cell as a spatial transcriptomics array, enabling the generation of high-resolution spatial datasets. C_LIO_LIThe protocol introduces a streamlined data analysis pipeline that produces a spatial digital gene expression matrix suitable for various single-cell and spatial transcriptome analysis methods. C_LIO_LIThe protocol allows for the capture of histology images from the same tissue section subjected to spatial transcriptomics analysis and allows users to precisely align the transcriptome dataset with the histological image using fiducial marks engraved on the flow cell surface. C_LIO_LILeveraging commonly available Illumina equipment, the protocol offers researchers ultra-high submicrometer resolution in spatial transcriptomics analysis with a comprehensive pipeline, rapid turnaround, cost efficiency, and versatility. C_LI

genomics↗