Honors & Awards


  • Grass Fellow in Neuroscience, Marine Biological Laboratory in Woods Hole (2018)

Professional Education


  • Bachelor of Arts, University of Utah (2011)
  • Doctor of Philosophy, Washington University (2018)

Stanford Advisors


All Publications


  • LONGO: an R package for interactive gene length dependent analysis for neuronal identity McCoy, M. J., Paul, A. J., Victor, M. B., Richner, M., Gabel, H. W., Gong, H., Yoo, A. S., Ahn, T. OXFORD UNIV PRESS. 2018: 422–28

    Abstract

    Reprogramming somatic cells into neurons holds great promise to model neuronal development and disease. The efficiency and success rate of neuronal reprogramming, however, may vary between different conversion platforms and cell types, thereby necessitating an unbiased, systematic approach to estimate neuronal identity of converted cells. Recent studies have demonstrated that long genes (>100 kb from transcription start to end) are highly enriched in neurons, which provides an opportunity to identify neurons based on the expression of these long genes.We have developed a versatile R package, LONGO, to analyze gene expression based on gene length. We propose a systematic analysis of long gene expression (LGE) with a metric termed the long gene quotient (LQ) that quantifies LGE in RNA-seq or microarray data to validate neuronal identity at the single-cell and population levels. This unique feature of neurons provides an opportunity to utilize measurements of LGE in transcriptome data to quickly and easily distinguish neurons from non-neuronal cells. By combining this conceptual advancement and statistical tool in a user-friendly and interactive software package, we intend to encourage and simplify further investigation into LGE, particularly as it applies to validating and improving neuronal differentiation and reprogramming methodologies.LONGO is freely available for download at https://github.com/biohpc/longo.Supplementary data are available at Bioinformatics online.

    View details for DOI 10.1093/bioinformatics/bty243

    View details for Web of Science ID 000438247800048

    View details for PubMedID 29950021

    View details for PubMedCentralID PMC6022641

  • MicroRNAs Induce a Permissive Chromatin Environment that Enables Neuronal Subtype-Specific Reprogramming of Adult Human Fibroblasts CELL STEM CELL Abernathy, D. G., Kim, W., McCoy, M. J., Lake, A. M., Ouwenga, R., Lee, S., Xing, X., Li, D., Lee, H., Heuckeroth, R. O., Dougherty, J. D., Wang, T., Yoo, A. S. 2017; 21 (3): 332-+

    Abstract

    Directed reprogramming of human fibroblasts into fully differentiated neurons requires massive changes in epigenetic and transcriptional states. Induction of a chromatin environment permissive for acquiring neuronal subtype identity is therefore a major barrier to fate conversion. Here we show that the brain-enriched miRNAs miR-9/9∗ and miR-124 (miR-9/9∗-124) trigger reconfiguration of chromatin accessibility, DNA methylation, and mRNA expression to induce a default neuronal state. miR-9/9∗-124-induced neurons (miNs) are functionally excitable and uncommitted toward specific subtypes but possess open chromatin at neuronal subtype-specific loci, suggesting that such identity can be imparted by additional lineage-specific transcription factors. Consistently, we show that ISL1 and LHX3 selectively drive conversion to a highly homogeneous population of human spinal cord motor neurons. This study shows that modular synergism between miRNAs and neuronal subtype-specific transcription factors can drive lineage-specific neuronal reprogramming, providing a general platform for high-efficiency generation of distinct subtypes of human neurons.

    View details for DOI 10.1016/j.stem.2017.08.002

    View details for Web of Science ID 000409527700011

    View details for PubMedID 28886366

    View details for PubMedCentralID PMC5679239