A cross-species approach to identify transcriptional regulators exemplified for Dnajc22 and Hnf4a

• Published in: Scientific reports Vol. 7; no. 1; pp. 4056 - 15
• Main Authors: Aschenbrenner, A. C., Bassler, K., Brondolin, M., Bonaguro, L., Carrera, P., Klee, K., Ulas, T., Schultze, J. L., Hoch, M.
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 22.06.2017; Nature Publishing Group; Nature Portfolio
• Subjects: 13/106; 13/109; 38; 45/15; 631/114; 631/80; 64/116; 64/24; 64/60; Amino Acid Sequence; Animal models; Animals; Binding Sites; Computer applications; Diptera; Gene Expression Regulation; Gene mapping; Gene regulation; Genetic Loci; Heat shock proteins; Hepatocyte nuclear factor 4; Hepatocyte Nuclear Factor 4 - genetics; Hepatocyte Nuclear Factor 4 - metabolism; HSP40 Heat-Shock Proteins - genetics; HSP40 Heat-Shock Proteins - metabolism; Hsp40 protein; Humanities and Social Sciences; Humans; Information processing; Mathematical models; Mice; multidisciplinary; Protein Binding; Science; Science (multidisciplinary); Transcription factors; Transcription Factors - metabolism; Zebrafish
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-017-04370-9

There is an enormous need to make better use of the ever increasing wealth of publicly available genomic information and to utilize the tremendous progress in computational approaches in the life sciences. Transcriptional regulation of protein-coding genes is a major mechanism of controlling cellular functions. However, the myriad of transcription factors potentially controlling transcription of any given gene makes it often difficult to quickly identify the biological relevant transcription factors. Here, we report on the identification of Hnf4a as a major transcription factor of the so far unstudied DnaJ heat shock protein family (Hsp40) member C22 (Dnajc22). We propose an approach utilizing recent advances in computational biology and the wealth of publicly available genomic information guiding the identification of potential transcription factor candidates together with wet-lab experiments validating computational models. More specifically, the combined use of co-expression analyses based on self-organizing maps with sequence-based transcription factor binding prediction led to the identification of Hnf4a as the potential transcriptional regulator for Dnajc22 which was further corroborated using publicly available datasets on Hnf4a. Following this procedure, we determined its functional binding site in the murine Dnajc22 locus using ChIP-qPCR and luciferase assays and verified this regulatory loop in fruitfly, zebrafish, and humans.