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Open Access Publications from the University of California

Scholarly Works (2 results)

  • Thesis
  • Peer Reviewed
UC San Diego Electronic Theses and Dissertations (2017)

Our world is becoming quantifiable. The IBM Corporation estimates that our society is collecting data at a rate of 2.5 quintillion bytes per day. To give some perspective, 90% of the data that humans now have access to has been collected in the last two years. Biological science is no exception. This information holds enormous potential but the biggest challenge now lies in data analysis and interpretation.

In biology, this data revolution has been led by sequencing technology. Therefore most data is either genomic or transcriptomic in nature. This dissertation focuses on protein mass spectrometry. We find that by integrating multiple data sets, we achieve the most powerful systems-level descriptions of biological systems. In the following dissertation we show how proteomic data can be integrated with both transcriptomic and epigenomic data sets to provide critical insight into biological systems.

In the first chapter, we show that proteomic and transcriptomic measurements have fundamental differences and lead to different specific results but similar “big-picture” conclusions. We use both to re-construct gene regulatory networks and find that the most accurate network results from integrating both data types.

In the second chapter, we expand on observations made in chapter one and incorporate DNA methylation data. We discover that, using random forest machine learning models and genic DNA methylation data, we are able to classify the subset of expressed mRNAs with high accuracy. Most interestingly, after incorporating proteomic data, we achieve near perfect classification accuracy and go on to discover a surprising association between genic DNA methylation and translations. Such models can be used to annotate the functional subset of maize genes with equal or better accuracy than current manual annotations. These models show excellent accuracy in a diverse set of maize inbreds, leading to speculation that DNA methylation is playing a large role in crop domestication.

In the final chapter we use a novel method to integrates protein and transcript data to discover quantitative trait loci that are specifically controlling protein abundance in a mRNA independent manor in arabidopsis. We then demonstrate how transcript data can be used to prioritize causative genes.

    Cover page: Integrated Omic Networks Reveal Regulatory Elements of Transcription and Translation
    • Article
    • Peer Reviewed
    UC Davis Previously Published Works (2017)
    Plants have evolved tightly regulated signaling networks to respond and adapt to environmental perturbations, but the nature of the signaling hub(s) involved have remained an enigma. We have previously established that methylerythritol cyclodiphosphate (MEcPP), a precursor of plastidial isoprenoids and a stress-specific retrograde signaling metabolite, enables cellular readjustments for high-order adaptive functions. Here, we specifically show that MEcPP promotes two Brassicaceae-specific traits, namely endoplasmic reticulum (ER) body formation and induction of indole glucosinolate (IGs) metabolism selectively, via transcriptional regulation of key regulators NAI1 for ER body formation and MYB51/122 for IGs biosynthesis). The specificity of MEcPP is further confirmed by the lack of induction of wound-inducible ER body genes as well as IGs by other altered methylerythritol phosphate pathway enzymes. Genetic analyses revealed MEcPP-mediated COI1-dependent induction of these traits. Moreover, MEcPP signaling integrates the biosynthesis and hydrolysis of IGs through induction of nitrile-specifier protein1 and reduction of the suppressor, ESM1, and production of simple nitriles as the bioactive end product. The findings position the plastidial metabolite, MEcPP, as the initiation hub, transducing signals to adjust the activity of hard-wired gene circuitry to expand phytochemical diversity and alter the associated subcellular structure required for functionality of the secondary metabolites, thereby tailoring plant stress responses.
      Cover page: Initiation of ER Body Formation and Indole Glucosinolate Metabolism by the Plastidial Retrograde Signaling Metabolite, MEcPP
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