Thousands of novel translated open reading frames in humans inferred by ribosome footprint profiling

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Abstract

Accurate annotation of protein coding regions is essential for understanding how genetic information is translated into function. We describe riboHMM, a new method that uses ribosome footprint data to accurately infer translated sequences. Applying riboHMM to human lymphoblastoid cell lines, we identified 7,273 novel coding sequences, including 2,442 translated upstream open reading frames. We observed an enrichment of footprints at inferred initiation sites after drug-induced arrest of translation initiation, validating many of the novel coding sequences. The novel proteins exhibit significant selective constraint in the inferred reading frames, suggesting that many are functional. Moreover, ~40% of bicistronic transcripts showed negative correlation in the translation levels of their two coding sequences, suggesting a potential regulatory role for these novel regions. Despite known limitations of mass spectrometry to detect protein expressed at low level, we estimated a 14% validation rate. Our work significantly expands the set of known coding regions in humans.

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Anil Raj

Department of Genetics, Stanford University, Stanford, United States

For correspondence
rajanil@stanford.edu

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The authors declare that no competing interests exist.
Sidney H Wang

Department of Human Genetics, University of Chicago, Chicago, United States

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The authors declare that no competing interests exist.
Heejung Shim

Department of Statistics, Purdue University, West Lafayette, United States

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The authors declare that no competing interests exist.
Arbel Harpak

Department of Biology, Stanford University, Stanford, United States

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The authors declare that no competing interests exist.
Yang I Li

Department of Genetics, Stanford University, Stanford, United States

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The authors declare that no competing interests exist.
Brett Engelmann

Department of Human Genetics, University of Chicago, Chicago, United States

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The authors declare that no competing interests exist.
Matthew Stephens

Department of Human Genetics, University of Chicago, Chicago, United States

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The authors declare that no competing interests exist.
Yoav Gilad

Department of Human Genetics, University of Chicago, Chicago, United States

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The authors declare that no competing interests exist.
Jonathan K Pritchard

Department of Genetics, Stanford University, Stanford, United States

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The authors declare that no competing interests exist.

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