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

View Article: PubMed Central - PubMed

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 7273 novel coding sequences, including 2442 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.

Doi:: http://dx.doi.org/10.7554/eLife.13328.001

No MeSH data available.


Robustness of parameters for start codon usage to choice of learning set.The estimated values of the parameter  when using the 5000 most expressed genes (blue) and random sets of 5000 genes (gray) show that start codon usage is robust to the choice of the learning set.DOI:http://dx.doi.org/10.7554/eLife.13328.009
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fig1s7: Robustness of parameters for start codon usage to choice of learning set.The estimated values of the parameter when using the 5000 most expressed genes (blue) and random sets of 5000 genes (gray) show that start codon usage is robust to the choice of the learning set.DOI:http://dx.doi.org/10.7554/eLife.13328.009

Mentions: In addition to identifying individual novel coding sequences, our method enables us to observe general properties shared across these coding regions. Interestingly, we found novel coding sequences to have a higher usage of non-AUG start codons than would be expected by considering current translation initiation site annotation (Figure 3B). We emphasize that although our model assumes shared properties between novel CDS and annotated CDS, we did not use any information about annotated translation initiation and termination sites when learning the model parameters. We used well-expressed genes as our learning set to ensure that when the footprint data do not provide very strong evidence regarding the initiation site, novel coding sequences identified by our method are as similar as possible to annotated coding sequences in the sequence composition of their initiation sites. While this allows us to be conservative and identify novel CDS that are similar to annotated CDS in their ribosome footprint patterns, our approach will not be able to identify translation events that differ in their footprint patterns from the majority of translation events. In other words, our choice of learning set could potentially bias the inference. Nevertheless, similar start codon usage frequencies were observed when random sets of 5000 genes were used as learning set (Figure 1—figure supplement 7) further confirming the robustness of our method.


Thousands of novel translated open reading frames in humans inferred by ribosome footprint profiling
Robustness of parameters for start codon usage to choice of learning set.The estimated values of the parameter  when using the 5000 most expressed genes (blue) and random sets of 5000 genes (gray) show that start codon usage is robust to the choice of the learning set.DOI:http://dx.doi.org/10.7554/eLife.13328.009
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Related In: Results  -  Collection

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fig1s7: Robustness of parameters for start codon usage to choice of learning set.The estimated values of the parameter when using the 5000 most expressed genes (blue) and random sets of 5000 genes (gray) show that start codon usage is robust to the choice of the learning set.DOI:http://dx.doi.org/10.7554/eLife.13328.009
Mentions: In addition to identifying individual novel coding sequences, our method enables us to observe general properties shared across these coding regions. Interestingly, we found novel coding sequences to have a higher usage of non-AUG start codons than would be expected by considering current translation initiation site annotation (Figure 3B). We emphasize that although our model assumes shared properties between novel CDS and annotated CDS, we did not use any information about annotated translation initiation and termination sites when learning the model parameters. We used well-expressed genes as our learning set to ensure that when the footprint data do not provide very strong evidence regarding the initiation site, novel coding sequences identified by our method are as similar as possible to annotated coding sequences in the sequence composition of their initiation sites. While this allows us to be conservative and identify novel CDS that are similar to annotated CDS in their ribosome footprint patterns, our approach will not be able to identify translation events that differ in their footprint patterns from the majority of translation events. In other words, our choice of learning set could potentially bias the inference. Nevertheless, similar start codon usage frequencies were observed when random sets of 5000 genes were used as learning set (Figure 1—figure supplement 7) further confirming the robustness of our method.

View Article: PubMed Central - PubMed

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 7273 novel coding sequences, including 2442 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.

Doi:: http://dx.doi.org/10.7554/eLife.13328.001

No MeSH data available.