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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.


Related in: MedlinePlus

Translation of uaCDS regulates translation of mCDS.(A) Spearman correlation, across LCLs, between mCDS translation and uaCDS translation (red histogram). Using random (mCDS, uaCDS) pairs, matched for length and pairwise distance, we computed an empirical  distribution of Spearman correlations (gray histogram). At 10% FDR, 917 inferred (uaCDS, mCDS) pairs have significant negative correlation (shaded red region). (B) 365 orfQTLs (genetic variants associated with ORF usage; i.e., whether the mCDS or uaCDS of a transcript is translated) were identified at 10% FDR (41 pairs of mCDS/uaCDS). (C) Illustrating an example of an orfQTL in the histocompatibility minor serpin domain-containing (HMSD) gene (introns removed for better visualization). The most significant variant (marked x) lies within an intron between the mCDS and uaCDS of the transcript.DOI:http://dx.doi.org/10.7554/eLife.13328.023
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fig7: Translation of uaCDS regulates translation of mCDS.(A) Spearman correlation, across LCLs, between mCDS translation and uaCDS translation (red histogram). Using random (mCDS, uaCDS) pairs, matched for length and pairwise distance, we computed an empirical distribution of Spearman correlations (gray histogram). At 10% FDR, 917 inferred (uaCDS, mCDS) pairs have significant negative correlation (shaded red region). (B) 365 orfQTLs (genetic variants associated with ORF usage; i.e., whether the mCDS or uaCDS of a transcript is translated) were identified at 10% FDR (41 pairs of mCDS/uaCDS). (C) Illustrating an example of an orfQTL in the histocompatibility minor serpin domain-containing (HMSD) gene (introns removed for better visualization). The most significant variant (marked x) lies within an intron between the mCDS and uaCDS of the transcript.DOI:http://dx.doi.org/10.7554/eLife.13328.023

Mentions: With 2442 uaCDS identified as translated in LCLs, we next tested the hypothesis that uaCDS expression negatively correlates with mCDS for each pair. We observed that, at 10% FDR, 917 pairs of uaCDS and mCDS had significant negative correlations across individuals between the proportion of footprints assigned to them (Figure 7A). Our observation that nearly 40% of pairs of uaCDS and mCDS are significantly anti-correlated, despite incomplete power due to low sample size, suggests that a potential role of alternate CDSs in a transcript is to regulate the translation of the main CDS.10.7554/eLife.13328.023Figure 7.Translation of uaCDS regulates translation of mCDS.


Thousands of novel translated open reading frames in humans inferred by ribosome footprint profiling
Translation of uaCDS regulates translation of mCDS.(A) Spearman correlation, across LCLs, between mCDS translation and uaCDS translation (red histogram). Using random (mCDS, uaCDS) pairs, matched for length and pairwise distance, we computed an empirical  distribution of Spearman correlations (gray histogram). At 10% FDR, 917 inferred (uaCDS, mCDS) pairs have significant negative correlation (shaded red region). (B) 365 orfQTLs (genetic variants associated with ORF usage; i.e., whether the mCDS or uaCDS of a transcript is translated) were identified at 10% FDR (41 pairs of mCDS/uaCDS). (C) Illustrating an example of an orfQTL in the histocompatibility minor serpin domain-containing (HMSD) gene (introns removed for better visualization). The most significant variant (marked x) lies within an intron between the mCDS and uaCDS of the transcript.DOI:http://dx.doi.org/10.7554/eLife.13328.023
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fig7: Translation of uaCDS regulates translation of mCDS.(A) Spearman correlation, across LCLs, between mCDS translation and uaCDS translation (red histogram). Using random (mCDS, uaCDS) pairs, matched for length and pairwise distance, we computed an empirical distribution of Spearman correlations (gray histogram). At 10% FDR, 917 inferred (uaCDS, mCDS) pairs have significant negative correlation (shaded red region). (B) 365 orfQTLs (genetic variants associated with ORF usage; i.e., whether the mCDS or uaCDS of a transcript is translated) were identified at 10% FDR (41 pairs of mCDS/uaCDS). (C) Illustrating an example of an orfQTL in the histocompatibility minor serpin domain-containing (HMSD) gene (introns removed for better visualization). The most significant variant (marked x) lies within an intron between the mCDS and uaCDS of the transcript.DOI:http://dx.doi.org/10.7554/eLife.13328.023
Mentions: With 2442 uaCDS identified as translated in LCLs, we next tested the hypothesis that uaCDS expression negatively correlates with mCDS for each pair. We observed that, at 10% FDR, 917 pairs of uaCDS and mCDS had significant negative correlations across individuals between the proportion of footprints assigned to them (Figure 7A). Our observation that nearly 40% of pairs of uaCDS and mCDS are significantly anti-correlated, despite incomplete power due to low sample size, suggests that a potential role of alternate CDSs in a transcript is to regulate the translation of the main CDS.10.7554/eLife.13328.023Figure 7.Translation of uaCDS regulates translation of mCDS.

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.


Related in: MedlinePlus