The Human tRNA Story: A Complex Epigenomic Landscape Unfolds

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Todd M. Lowe, PhD

Experience: 25+ years creating algorithms and software tools to enable study of genomes and non-coding RNAs. Designed, published (Lowe et al., Nucleic Acids Research, 1990) , and eventually sold software for primer design through Clontech starting freshman year in college. After undergrad, spent a year in the Basic Research Branch at NCBI, where I learned large-scale genomic analysis, implemented EST library annotation (dbEST, Boguski et al., Nature Genetics, 1993) and studied rapid protein annotation methods.

In graduate school at Washington University in St. Louis, acquired a love of RNA biology in Sean Eddy's lab, and created algorithms to identify different classes of non-coding RNA genes (tRNAs, snoRNAs) that are still in regular use today. As a postdoc at Stanford in the Brown/Botstein microarray group, I designed and built DNA microarrays to study gene expression in microbial thermophiles.

I was recruited to UC Santa Cruz in 2001 to co-found a new department integrating molecular and computational biology. Since then, I have been applying comparative genomics to discover novel small RNAs and study RNA-based gene regulation. My academic lab continues to integrate molecular biology and computational approaches for broad-based gene discovery. Graduate students and postdocs in my group often have projects which combine gene modeling with experimental genomics. Our current tools of choice are comparative RNA-seq and ChIP-seq, evolutionary genomics, and probabilistic modeling of RNA genes.


Despite mounting evidence for the importance of tRNA regulation in diverse biological processes, relatively little is known about the regulation of specific tRNA loci in complex multicellular organisms. In humans, as in most eukaryotes, tRNA genes comprise one of the largest single gene families that produce more transcripts than any other type of RNA. However, estimates of transcriptional activity of the 500+ individual human tRNA genes across multiple tissue types are almost entirely absent due to difficulty measuring specific tRNA transcript abundance on a large scale, as well as uncertain assignment of most transcripts among identical loci. I will present our new analyses of human tRNA genes using a combination of (1) specialized tRNA-seq transcriptional analyses (ARM-seq), (2) epigenetic data revealing transcription activation states associated with each gene over a range of cell types, and (3) and novel insights derived from a new version of tRNAscan-SE, which has been the standard for tRNA gene prediction for two decades. Enhancements to tRNAscan-SE include development of over 100 new, specialized tRNA covariance models which enable improved classification of eukaryotic, bacterial, archaeal, and mitochondrial tRNAs. These new computational analyses and experimental data are being integrated into the Genomic tRNA Database to provide the most comprehensive view of tRNA form & function, enabling new insights and suggesting new studies in tRNA and tRNA-derived small RNA research.

Presentation: 1:19:12