Abstract
Absolute or relative transcript amounts measured through high-throughput technologies (e.g., microarrays) are now commonly used in bioinformatics analysis, such as gene clustering and DNA binding motif finding. However, transcription rates that represent mRNA synthesis may be more relevant in these analyses. Because transcription rates are not equivalent to transcript amounts unless the mRNA degradation rates as well as other factors that affect transcript amount are identical across different genes, the use of transcription rates in bioinformatics analysis may lead to a better description of the relationships among genes and better identification of genomic signals. In this article, we propose to use experimentally measured mRNA decay rates and mRNA transcript amounts to jointly infer transcription rates, and then use the inferred transcription rates in downstream analyses. For gene expression similarity analysis, we find that there tends to be higher correlations among co-regulated genes when transcription-rate-based correlations are used compared to those based on transcript amounts. In the context of identifying DNA binding motifs, using inferred transcription rates leads to more significant findings than those based on transcript amounts. These analyses suggest that the incorporation of mRNA decay rates and the use of the inferred transcription rates can facilitate the study of gene regulations and the reconstruction of transcriptional regulatory networks.
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This work was supported by NSF under Grant No. DMS 0241160.
Liang Chen obtained her B.S. degree from Department of Biological Sciences and Biotechnology, Tsinghua University, Beijing, China in 2001. Now she is with the Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, Connecticut.
Hong-Yu Zhao obtained the B.S. degree from Department of Probability and Statistics, Peking University, China in 1990 and the Ph.D. degree from Department of Statistics, University of California at Berkeley, in 1995. From 1995–1996 he was adjunct assistant professor and assistant professor in residence in University of California at Los Angeles. From 1996–present he is assistant professor, associate professor, and Ira V. Hiscock associate professor in Yale University. He is associate editor of Biometrics; Journal of Agricultural, Biological, and Environmental Statistics; Statistical Applications in Genetics and Molecular Biology; Pharmacogenomics.
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Chen, L., Zhao, HY. Integrating mRNA Decay Information into Co-Regulation Study. J Comput Sci Technol 20, 434–438 (2005). https://doi.org/10.1007/s11390-005-0434-1
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DOI: https://doi.org/10.1007/s11390-005-0434-1