Analysis of temporal transcription expression profiles reveal links between protein function and developmental stages of Drosophila melanogaster

Cen Wan, Jonathan G Lees, Federico Minneci, Christine A Orengo and David T Jones

PLOS Computational Biology, 2017, vol. 13, issue 10, 1-22

Abstract: Accurate gene or protein function prediction is a key challenge in the post-genome era. Most current methods perform well on molecular function prediction, but struggle to provide useful annotations relating to biological process functions due to the limited power of sequence-based features in that functional domain. In this work, we systematically evaluate the predictive power of temporal transcription expression profiles for protein function prediction in Drosophila melanogaster. Our results show significantly better performance on predicting protein function when transcription expression profile-based features are integrated with sequence-derived features, compared with the sequence-derived features alone. We also observe that the combination of expression-based and sequence-based features leads to further improvement of accuracy on predicting all three domains of gene function. Based on the optimal feature combinations, we then propose a novel multi-classifier-based function prediction method for Drosophila melanogaster proteins, FFPred-fly+. Interpreting our machine learning models also allows us to identify some of the underlying links between biological processes and developmental stages of Drosophila melanogaster.Author summary: Despite painstaking experimental efforts and the extensive sequence similarity based annotation transfers, less than a half of the fruit fly protein sequences in UniProtKB have some functional annotation. To help fill in this gap, we test the usefulness of publicly available temporal gene expression profiles and their combination with many biophysical attributes that can be effectively derived from the corresponding protein sequence. We find that such an integrative function prediction method provides more accurate predictions than using sequence data alone and we expect these predictions to help narrow down the number of experimental assays required to characterise fly protein function. We demonstrate by highlighting correlations between predicted biological process functions and known facts about fly developmental stages.

Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pcbi00:1005791

DOI: 10.1371/journal.pcbi.1005791

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