The Codebook: cracking the puzzle of human transcription factors
A global collaboration spanning eight years has concluded with the creation of the Codebook: an enormous database comprised of over 4,800 experiments that has illuminated how transcription factors influence human gene regulation.
For years, Professor Tim Hughes has been studying transcription, the initial step of gene expression in which a cell duplicates DNA into messenger RNA. An integral part of this process is dependent on transcription factors (TFs), the proteins which bind to DNA sequences to control and regulate the rate of gene transcription. As an extension of the Hughes Lab’s decades-long investigation, the Codebook Project centered around the short DNA sequences known as motifs, which serve as the binding sites of the transcription factors.
“The number one hypothetical function for conserved, non-coding DNA is that it's binding sites for transcription factors,” explains Hughes, professor in the Department of Molecular Genetics and principal investigator at the Donnelly. “We figured we better start identifying where these TFs bind so we can match functional DNA to what it might be recruiting.”
The Codebook Project looked at about a quarter of all human TFs, focusing on ones with little or no known binding information. The team systematically identified distinct and novel motifs for 177 TFs previously lacking them, illuminating the specific binding capabilities of poorly characterized human TFs and revealing tens of thousands of previously unknown binding sites throughout our genome. Taking 4,808 experiments to complete, the work has expanded the scientific community's catalogue of TF motifs by an estimated 15-18%.
“It was a behemoth of a project,” says Arttu Jolma, research associate at the Hughes Lab, and co-first author of the Nature-published paper that describes the entire Codebook effort. “We weren’t just cataloguing the entire system; we were finding conceptual developments as well.”
“Codebook has been a decade in the making,” agrees co-first author and PhD student Ali Fathi. "It fills a major gap for anyone studying genomics and transcription factors and should make large-scale computational modelling much more accessible across the field."
Eight years in the making: How the Codebook was started and finished
It all began in a 2016 workshop that took place in the Donnelly Centre’s Red Room, which brought together a network of global experts and collaborators to discuss transcription factors.
“Following the kickoff meeting, it was clear there were a bunch of different assays that could be run in order to get the sequence specificities of all the human transcription factors,” explains Hughes. “But to run the assays, we needed a list of human TFs—that became a little two-year project all on its own.”
That project resulted in Hughes’ most cited work to date, a 2018 paper which concluded that over one-quarter of the estimated ~1,600 possible human transcription factors lacked established binding motifs. This is the quarter that the Codebook later tackled.
By the late 2010s, Hughes had brought together individuals and labs who showed interest in the Codebook Project. This group included the computational experts who would later become crucial to the analysis of the mountains of unpolished experimental data from the Hughes Lab and the lab of collaborator Bart Deplancke in Switzerland. Together with ten computational labs, including Ivan Kulakovskiy’s group out of Russia and Hamed Najafabadi at McGill, the Codebook Consortium described the network of skilled individuals who brought the Codebook to life.
With all experiments completed by 2022, the group was entirely dedicated to processing the data.
“We needed to make biological stories out of the data,” Hughes says, laughing. “We did much of it during the pandemic, which was the perfect time to stare at spreadsheets and websites for days on end.”
“We organized and analyzed the data to determine which of the 332 putative TFs were sequence specific,” says Kaitlin Laverty, co-first author and former Hughes Lab PhD student and current postdoctoral researcher at the Memorial Sloan Kettering Cancer Center. “It was a highly collaborative effort with a team of incredible scientists across many institutions.”
The Codebook Project coming to an end has left the team with six papers, published across high-impact journals. Among many discoveries, the process of building the computational tool has created a new assay method: co-developed by Jolma, GST-SELEX or Genomic High Throughput SELEX measures how proteins bind the unmodified human genome.
The Hughes Lab will continue to investigate the binding motifs of human TFs until they run out—with Hughes himself saying his own last push to characterize the remaining TFs will likely be done within a year.
Hughes explains, “We have to recount, but my guess is that there's only dozens of transcription factors left to categorize out of about 1,600. So, time to work.”
Read the recently published papers that have resulted from the Hughes Lab’s work with the Codebook below:
"An expanded codebook of human transcription factor DNA-binding specificity" Nature.
"GHT-SELEX demonstrates unexpectedly high intrinsic sequence specificity and complex DNA binding of many human transcription factors" Nature Methods.
"Cross-platform motif discovery and benchmarking to explore binding specificities of poorly studied human transcription factors" Communications Biology.
"Identification of methylation-sensitive human transcription factors using meSMiLE-seq" Nature Communications
"Extensive binding of poorly characterized human transcription factors to genomic dark matter" Nature Communications
"Inferring binding specificities of human transcription factors with the wisdom of crowds" in BioRxiv.
About the Donnelly Centre
The Donnelly Centre for Cellular and Biomolecular Research is a research hub at the University of Toronto’s Temerty Faculty of Medicine, where scientists from diverse fields work together to advance medicine and health. Founded in 2005, the Donnelly Centre is a global leader in research on systems biology, regenerative medicine and disease modelling.
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