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bioRxiv · 10.1101/2021.12.20.473422

Identification of upstream transcription factor binding sites in orthologous genes using mixed Student's t-test statistics

Huang, T.·Xiao, H.·Tian, Q.·He, Z.·Yuan, C.·Lin, Z.·Gao, X.·Yao, M.
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Abstract

BackgroundTranscription factor (TF) regulates the transcription of DNA to messenger RNA by binding to upstream sequence motifs. Identifying the locations of known motifs in whole genomes is computationally intensive. Methodology/Principal FindingsThis study presents a computational tool, named "Grit", for screening TF-binding sites (TFBS) by coordinating transcription factors to their promoter sequences in orthologous genes. This tool employs a newly developed mixed Students t-test statistical method that detects high-scoring conserved and non-conserved binding sites among species. The program performs sequence scanning at a rate of 3.2 Mb/s on a quad-core Amazon server and has been benchmarked by the well-established ChIP-Seq datasets, putting Grit amongst the top-ranked TFBS predictors. It marginally outperforms the well-known transcription factor motif scanning tools, Pscan (4.8%) and FIMO (17.8%), in analyzing well-documented ChIP-Atlas human genome Chip-Seq datasets. SignificanceGrit is a good alternative to current available motif scanning tools and is publicly available at http://www.thua45.cn/grit under an academic free license. Author SummaryLocating transcription factor-binding (TF-binding) site in the genome and identification their function is fundamental in understanding various biological processes. Improve the performance of the prediction tools is important because accurate TF-binding site prediction can save cost and time for wet-lab experiments. Also, genome wide TF-binding site prediction can provide new insights for transcriptome regulation in system biology perspective. This study developed a new TF-binding site prediction tool based on mixed Students t-test statistical method. The tool is amongst the top-ranked TF-binding site predictors, as such, it can help the researchers in TF-binding site identification and transcriptional regulation mechanism interpretation of genes.

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Huang, T., Xiao, H., Tian, Q., He, Z., Yuan, C., Lin, Z., Gao, X., Yao, M.. 2021-12-21. Identification of upstream transcription factor binding sites in orthologous genes using mixed Student's t-test statistics. https://doi.org/10.1101/2021.12.20.473422

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