WE-E-17A-10: Singular Value Decomposition Identifies Transcript Length Distribution Functions from DNA Microarray Data and Reveals Evolutionary Forces Globally Affecting Glioblastoma Multiforme Metabolism

Authors


Abstract

Purpose:

To search for evolutionary forces that might act upon eukaryotic mRNA transcript length, e.g., as a normal cell is transformed to a tumor cell.

Methods:

We use the singular value decomposition (SVD) to identify the length distribution functions of sets and subsets of human and yeast transcripts from profiles of mRNA abundance levels across gel electrophoresis migration distances that were previously measured by DNA microarrays. We show that the SVD identifies the transcript length distribution functions as “asymmetric generalized coherent states” from the DNA microarray data and with no a-priori assumptions [Alter and Golub, Proc. Natl. Acad. Sci. USA 103 (32), pp. 11828-11833 (2006); doi: 10.1073/pnas.0604756103].

Results:

Comparing subsets of human and yeast transcripts of the same gene ontology annotations, we find that in both disparate eukaryotes, transcripts involved in protein synthesis or mitochondrial metabolism are significantly shorter than typical, and in particular, significantly shorter than those involved in glucose metabolism. Comparing the subsets of human transcripts that are overexpressed in glioblastoma multiforme (GBM) or normal brain tissue samples from The Cancer Genome Atlas, we find that GBM maintains normal brain overexpression of significantly short transcripts, enriched in transcripts that are involved in protein synthesis or mitochondrial metabolism, but suppresses normal overexpression of significantly longer transcripts, enriched in transcripts that are involved in glucose metabolism and brain activity [Bertagnolli, Drake, Tennessen and Alter, PLoS One 8 (11), article e78913 (2013); doi: 10.1371/journal.pone.0078913].

Conclusion:

These global relations among transcript length, cellular metabolism and tumor development suggest a previously unrecognized physical mode for tumor and normal cells to differentially regulate metabolism in a transcript length-dependent manner. The identified distribution functions support a previous hypothesis from mathematical modeling of evolutionary forces that act upon transcript length in the manner of the restoring force of the harmonic oscillator.

This research was supported by the Utah Science, Technology and Research (USTAR) Initiative, National Human Genome Research Institute (NHGRI) R01 Grant HG-004302 and National Science Foundation (NSF) CAREER Award DMS-0847173

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