Cutaneous mechanosensory neurons are activated by mechanical loads applied to the skin, and these stimuli are proposed to generate mechanical strain within sensory neurons. Using a microfluidic device to deliver controlled stimuli to intact animals and large, immobile, and fluorescent protein-tagged mitochondria as fiducial markers in the touch receptor neurons (TRNs), we visualized and measured touch-induced mechanical strain in Caenorhabditis elegans worms. At steady state, touch stimuli sufficient to activate TRNs induce an average strain of 3.1% at the center of the actuator and this strain decays to near zero at the edges of the actuator. We also measured strain in animals carrying mutations affecting links between the extracellular matrix (ECM) and the TRNs but could not detect any differences in touch-induced mechanical strain between wild-type and mutant animals. Collectively, these results demonstrate that touching the skin induces local mechanical strain in intact animals and suggest that a fully intact ECM is not essential for transmitting mechanical strain from the skin to cutaneous mechanosensory neurons.
Pubmed ID: 32579427
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A software package to analyze next-generation resequencing data. The toolkit offers a wide variety of tools, with a primary focus on variant discovery and genotyping as well as strong emphasis on data quality assurance. Its robust architecture, powerful processing engine and high-performance computing features make it capable of taking on projects of any size. This software library makes writing efficient analysis tools using next-generation sequencing data very easy, and second it's a suite of tools for working with human medical resequencing projects such as 1000 Genomes and The Cancer Genome Atlas. These tools include things like a depth of coverage analyzers, a quality score recalibrator, a SNP/indel caller and a local realigner. (entry from Genetic Analysis Software)
View all literature mentionsGenetic variant annotation and effect prediction software toolbox that annotates and predicts effects of variants on genes (such as amino acid changes). By using standards, such as VCF, SnpEff makes it easy to integrate with other programs.
View all literature mentionsJava toolset for working with next generation sequencing data in the BAM format.
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