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Open AccessArticle

RECTA: Regulon Identification Based on Comparative Genomics and Transcriptomics Analysis

by Xin Chen 1,†, Anjun Ma 2,3,†, Adam McDermaid 2,3, Hanyuan Zhang 4, Chao Liu 5, Huansheng Cao 6 and Qin Ma 2,3,*
1
Center for Applied Mathematics, Tianjin University, Tianjin 300072, China
2
Bioinformatics and Mathematical Biosciences Lab, Department of Agronomy, Horticulture and Plant Science, South Dakota State University, Brookings, SD 57006, USA
3
Department of Mathematics and Statistics, South Dakota State University, Brookings, SD 57006, USA
4
College of Computer Science and Engineering, University of Nebraska Lincoln, Lincoln, NE 68588, USA
5
Shandong Provincial Hospital affiliated to Shandong University, Jinan 250021, China
6
Center for Fundamental and Applied Microbiomics, Biodesign Institute, Arizona State University, Tempe, AZ 85287, USA
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Genes 2018, 9(6), 278; https://doi.org/10.3390/genes9060278
Received: 30 March 2018 / Revised: 19 May 2018 / Accepted: 25 May 2018 / Published: 30 May 2018
Regulons, which serve as co-regulated gene groups contributing to the transcriptional regulation of microbial genomes, have the potential to aid in understanding of underlying regulatory mechanisms. In this study, we designed a novel computational pipeline, regulon identification based on comparative genomics and transcriptomics analysis (RECTA), for regulon prediction related to the gene regulatory network under certain conditions. To demonstrate the effectiveness of this tool, we implemented RECTA on Lactococcus lactis MG1363 data to elucidate acid-response regulons. A total of 51 regulons were identified, 14 of which have computational-verified significance. Among these 14 regulons, five of them were computationally predicted to be connected with acid stress response. Validated by literature, 33 genes in Lactococcus lactis MG1363 were found to have orthologous genes which were associated with six regulons. An acid response related regulatory network was constructed, involving two trans-membrane proteins, eight regulons (llrA, llrC, hllA, ccpA, NHP6A, rcfB, regulons #8 and #39), nine functional modules, and 33 genes with orthologous genes known to be associated with acid stress. The predicted response pathways could serve as promising candidates for better acid tolerance engineering in Lactococcus lactis. Our RECTA pipeline provides an effective way to construct a reliable gene regulatory network through regulon elucidation, and has strong application power and can be effectively applied to other bacterial genomes where the elucidation of the transcriptional regulation network is needed. View Full-Text
Keywords: RECTA; Lactococcus lactis MG1363; acid stress response; differentially expressed gene; gene co-expression; cis-regulatory motif finding; regulon; gene regulatory network RECTA; Lactococcus lactis MG1363; acid stress response; differentially expressed gene; gene co-expression; cis-regulatory motif finding; regulon; gene regulatory network
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Chen, X.; Ma, A.; McDermaid, A.; Zhang, H.; Liu, C.; Cao, H.; Ma, Q. RECTA: Regulon Identification Based on Comparative Genomics and Transcriptomics Analysis. Genes 2018, 9, 278.

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