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Manley, J.

Publications and source records attributed to Manley, J..

4 recordsLinked to original sources

Splicing dysregulation in glioblastoma alters the function of cell migration-related genes

Glioblastoma (GBM) has a poor prognosis with a high recurrence and low survival rate. Previous RNA-seq analyses have revealed that alternative splicing (AS) plays a role in GBM progression. Here, we present a novel AS analysis method (Semi-Q) and describe its use to identify GBM-specific AS events. We analyzed RNA-seq data from normal brain (NB), normal human astrocytes (NHAs) and GBM samples, and found that comparison between NHA and GBM was especially informative. Importantly, this analysis revealed that genes encoding cell migration-related proteins, including filamins (FLNs) and actinins (ACTNs), were among those most affected by differential AS. Functional assays revealed that dysregulated AS of FLNA, B and C transcripts produced protein isoforms that not only altered transcription of cell proliferation-related genes but also led to enhanced cell migration, resistance to cell death and/or mitochondrial respiratory function, while a dysregulated AS isoform of ACTN4 enhanced cell migration. Together, our results indicate that cell migration and actin cytoskeleton-related genes are differentially regulated by AS in GBM, supporting a role for AS in facilitating tumor growth and invasiveness.

molecular biology↗

Whole-brain neural substrates of behavioral variability in the larval zebrafish

Animals engaged in naturalistic behavior can exhibit a large degree of behavioral variability even under sensory invariant conditions. Such behavioral variability can include not only variations of the same behavior, but also variability across qualitatively different behaviors driven by divergent cognitive states, such as fight-or-flight decisions. However, the neural circuit mechanisms that generate such divergent behaviors across trials are not well understood. To investigate this question, here we studied the visual-evoked responses of larval zebrafish to moving objects of various sizes, which we found exhibited highly variable and divergent responses across repetitions of the same stimulus. Given that the neuronal circuits underlying such behaviors span sensory, motor, and other brain areas, we built a novel Fourier light field microscope which enables high-resolution, whole-brain imaging of larval zebrafish during behavior. This enabled us to screen for neural loci which exhibited activity patterns correlated with behavioral variability. We found that despite the highly variable activity of single neurons, visual stimuli were robustly encoded at the population level, and the visualencoding dimensions of neural activity did not explain behavioral variability. This robustness despite apparent single neuron variability was due to the multi-dimensional geometry of the neuronal population dynamics: almost all neural dimensions that were variable across individual trials, i.e. the "noise" modes, were nearly orthogonal to those encoding for sensory information. Investigating this neuronal variability further, we identified two sparsely-distributed, brain-wide neuronal populations whose pre-motor activity predicted whether the larva would respond to a stimulus and, if so, which direction it would turn on a single-trial level. These populations predicted single-trial behavior seconds before stimulus onset, indicating they encoded time-varying internal modulating behavior, perhaps organizing behavior over longer timescales or enabling flexible behavior routines dependent on the animals internal state. Our results provide the first whole-brain confirmation that sensory, motor, and internal variables are encoded in a highly mixed fashion throughout the brain and demonstrate that de-mixing each of these components at the neuronal population level is critical to understanding the mechanisms underlying the brains remarkable flexibility and robustness.

neuroscience↗

Simultaneous, cortex-wide and cellular-resolution neuronal population dynamics reveal an unbounded scaling of dimensionality with neuron number

The brains remarkable properties arise from collective activity of millions of neurons. Widespread application of dimensionality reduction to multi-neuron recordings implies that neural dynamics can be approximated by low-dimensional "latent" signals reflecting neural computations. However, what would be the biological utility of such a redundant and metabolically costly encoding scheme and what is the appropriate resolution and scale of neural recording to understand brain function? Imaging the activity of one million neurons at cellular resolution and near-simultaneously across mouse cortex, we demonstrate an unbounded scaling of dimensionality with neuron number. While half of the neural variance lies within sixteen behavior-related dimensions, we find this unbounded scaling of dimensionality to correspond to an ever-increasing number of internal variables without immediate behavioral correlates. The activity patterns underlying these higher dimensions are fine-grained and cortex-wide, highlighting that large-scale recording is required to uncover the full neural substrates of internal and potentially cognitive processes.

neuroscience↗

Volumetric Calcium Imaging of 1 Million Neurons Across Cortical Regions at Cellular Resolution Using Light Beads Microscopy

Two-photon microscopy together with genetically encodable calcium indicators has emerged as a standard tool for high-resolution imaging of neuroactivity in scattering brain tissue. However, its various realizations have not overcome the inherent tradeoffs between speed and spatiotemporal sampling in a principled manner which would be necessary to enable, amongst other applications, mesoscale volumetric recording of neuroactivity at cellular resolution and speed compatible with resolving calcium transients. Here, we introduce Light Beads Microscopy (LBM), a scalable and spatiotemporally optimal acquisition approach limited only by fluorescence life-time, where a set of axially-separated and temporally-distinct foci record the entire axial imaging range near-simultaneously, enabling volumetric recording at 1.41 x 108 voxels per second. Using LBM, we demonstrate mesoscopic and volumetric imaging at multiple scales in the mouse cortex, including cellular resolution recordings within ~3x5x0.5 mm3 volumes containing >200,000 neurons at ~5 Hz, recording of populations of ~1 million neurons within ~5.4x6x0.5 mm3 volumes at ~2Hz as well as higher-speed (9.6 Hz) sub-cellular resolution volumetric recordings. LBM provides an unprecedented opportunity for discovering the neurocomputations underlying cortex-wide encoding and processing of information in the mammalian brain.

neuroscience↗