Publications by authors named "Jason Derks"

The Y-linked gene and its X-linked homolog survived the evolution of the human sex chromosomes from ordinary autosomes. encodes a multifunctional RNA helicase, with mutations causing developmental disorders and cancers. We find that, among X-linked genes with surviving Y homologs, is extraordinarily dosage sensitive.

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  • Researchers quantified protein abundance in 5,883 single cells from human testis using advanced mass spectrometry methods to better understand protein regulation beyond just RNA levels.
  • They developed a Bayesian model to distinguish between biological variations and technical factors affecting protein and RNA abundance in a dataset of 29,709 cells, covering 3,861 gene products.
  • The study found that about 28% of the gene products showed significant differences between protein and RNA levels, with specific functions like spermatogenesis regulated post-transcriptionally and associated with unique cell-type specific modifications.
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  • Pre-patterning in embryo development is common in non-mammalian species, but mammals were thought to lack this due to their regulative development, which randomly contributes to the three blastocyst lineages.
  • Recent studies show that early blastomeres in mouse and human embryos actually have distinct developmental fates and differences in protein levels, challenging the previous notion of randomness.
  • Utilizing advanced proteomics, researchers found that 2-cell embryos contain alpha and beta blastomeres with different protein abundances linked to their developmental potential, with beta blastomeres more likely to produce higher amounts of epiblast cells.
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  • The gene discussed has both Y-linked and X-linked versions that evolved from regular autosomes and is important for producing a type of RNA helicase, mutations of which can lead to developmental issues and cancers.
  • Studies show that the levels of these gene transcripts are sensitive to the number of X and Y chromosomes present: more Y decreases the transcript levels, while more X chromosomes do the same.
  • There is a complex regulation in place where these genes regulate each other and maintain balanced protein levels through mechanisms like mRNA destabilization, revealing how their regulation changed as they evolved to their current sex-linked forms.
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The physiological response of a cell to stimulation depends on its proteome configuration. Therefore, the abundance variation of regulatory proteins across unstimulated single cells can be associatively linked with their response to stimulation. Here we developed an approach that leverages this association across individual cells and nuclei to systematically identify potential regulators of biological processes, followed by targeted validation.

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Major aims of single-cell proteomics include increasing the consistency, sensitivity and depth of protein quantification, especially for proteins and modifications of biological interest. Here, to simultaneously advance all these aims, we developed prioritized Single-Cell ProtEomics (pSCoPE). pSCoPE consistently analyzes thousands of prioritized peptides across all single cells (thus increasing data completeness) while maximizing instrument time spent analyzing identifiable peptides, thus increasing proteome depth.

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Analyzing proteins from single cells by tandem mass spectrometry (MS) has recently become technically feasible. While such analysis has the potential to accurately quantify thousands of proteins across thousands of single cells, the accuracy and reproducibility of the results may be undermined by numerous factors affecting experimental design, sample preparation, data acquisition and data analysis. We expect that broadly accepted community guidelines and standardized metrics will enhance rigor, data quality and alignment between laboratories.

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Accurate protein quantification is key to identifying protein markers, regulatory relationships between proteins, and pathophysiological mechanisms. Realizing this potential requires sensitive and deep protein analysis of a large number of samples. Toward this goal, proteomics throughput can be increased by parallelizing the analysis of both precursors and samples using multiplexed data independent acquisition (DIA) implemented by the plexDIA framework: https://plexDIA.

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Current mass spectrometry methods enable high-throughput proteomics of large sample amounts, but proteomics of low sample amounts remains limited in depth and throughput. To increase the throughput of sensitive proteomics, we developed an experimental and computational framework, called plexDIA, for simultaneously multiplexing the analysis of peptides and samples. Multiplexed analysis with plexDIA increases throughput multiplicatively with the number of labels without reducing proteome coverage or quantitative accuracy.

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