Perspectives on Codebook: sequence specificity of uncharacterized human transcription factors

Jolma, Arttu; Laverty, Kaitlin U.; Fathi, Ali; Yang, Ally W.H.; Yellan, Isaac; Vorontsov, Ilya E.; Inukai, Sachi; Kribelbauer-Swietek, Judith F.; Gralak, Antoni J.; Razavi, Rozita; Albu, Mihai; Brechalov, Alexander; Patel, Zain M.; Nozdrin, Vladimir; Meshcheryakov, Georgy; Kozin, Ivan; Abramov, Sergey; Boytsov, Alexandr; ,; Fornes, Oriol; Makeev, Vsevolod J.; Grau, Jan; Grosse, Ivo; Bucher, Philipp; Deplancke, Bart; Kulakovskiy, Ivan V.; Hughes, Timothy R.

doi:10.1101/2024.11.11.622097

2024

DOI: 10.1101/2024.11.11.622097

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Perspectives on Codebook: sequence specificity of uncharacterized human transcription factors

Arttu Jolma,

Kaitlin U. Laverty,

Ali Fathi

et al.

Abstract: We describe an effort ("Codebook") to determine the sequence specificity of 332 putative and largely uncharacterized human transcription factors (TFs), as well as 61 control TFs. Nearly 5,000 independent experiments across multiplein vitroandin vivoassays produced motifs for just over half of the putative TFs analyzed (177, or 53%), of which most are unique to a single TF. The data highlight the extensive contribution of transposable elements to TF evolution, both in cis and trans, and identify tens of thousan… Show more

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Cited by 4 publications

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GHT-SELEX demonstrates unexpectedly high intrinsic sequence specificity and complex DNA binding of many human transcription factors

Jolma,

Hernandez-Corchado,

Yang

et al. 2024

Preprint

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A long-standing challenge in human regulatory genomics is that transcription factor (TF) DNA-binding motifs are short and degenerate, while the genome is large. Motif scans therefore produce many false-positive binding site predictions. By surveying 179 TFs across 25 families using >1,500 cyclicin vitroselection experiments with fragmented, naked, and unmodified genomic DNA – a method we term GHT-SELEX (Genomic HT-SELEX) – we find that many human TFs possess much higher sequence specificity than anticipated. Moreover, genomic binding regions from GHT-SELEX are often surprisingly similar to those obtained in vivo (i.e. ChIP-seq peaks). We find that comparable specificity can also be obtained from motif scans, but performance is highly dependent on derivation and use of the motifs, including accounting for multiple local matches in the scans. We also observe alternative engagement of multiple DNA-binding domains within the same protein: long C2H2 zinc finger proteins often utilize modular DNA recognition, engaging different subsets of their DNA binding domain (DBD) arrays to recognize multiple types of distinct target sites, frequently evolving via internal duplication and divergence of one or more DBDs. Thus, contrary to conventional wisdom, it is common for TFs to possess sufficient intrinsic specificity to independently delineate cellular targets.

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GHT-SELEX demonstrates unexpectedly high intrinsic sequence specificity and complex DNA binding of many human transcription factors

Jolma,

Hernandez-Corchado,

Yang

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

Cross-platform DNA motif discovery and benchmarking to explore binding specificities of poorly studied human transcription factors

Vorontsov,

Kozin,

Abramov

et al. 2024

Preprint

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A DNA sequence pattern, or "motif", is an essential representation of DNA-binding specificity of a transcription factor (TF). Any particular motif model has potential flaws due to shortcomings of the underlying experimental data and computational motif discovery algorithm. As a part of the Codebook/GRECO-BIT initiative, here we evaluated at large scale the cross-platform recognition performance of positional weight matrices (PWMs), which remain popular motif models in many practical applications. We applied ten different DNA motif discovery tools to generate PWMs from the "Codebook" data comprised of 4,237 experiments from five different platforms profiling the DNA-binding specificity of 394 human proteins, focusing on understudied transcription factors of different structural families. For many of the proteins, there was no prior knowledge of a genuine motif. By benchmarking-supported human curation, we constructed an approved subset of experiments comprising about 30% of all experiments and 50% of tested TFs which displayed consistent motifs across platforms and replicates. We present the Codebook Motif Explorer (https://mex.autosome.org), a detailed online catalog of DNA motifs, including the top-ranked PWMs, and the underlying source and benchmarking data. We demonstrate that in the case of high-quality experimental data, most of the popular motif discovery tools detect valid motifs and generate PWMs, which perform well both on genomic and synthetic data. Yet, for each of the algorithms, there were problematic combinations of proteins and platforms, and the basic motif properties such as nucleotide composition and information content offered little help in detecting such pitfalls. By combining multiple PMWs in decision trees, we demonstrate how our setup can be readily adapted to train and test binding specificity models more complex than PWMs. Overall, our study provides a rich motif catalog as a solid baseline for advanced models and highlights the power of the multi-platform multi-tool approach for reliable mapping of DNA binding specificities.

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Identification of methylation-sensitive human transcription factors using meSMiLE-seq

Gralak,

Faltejskova,

Yang

et al. 2024

Preprint

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Transcription factors (TFs) are key players in eukaryotic gene regulation, but the DNA binding specificity of many TFs remains unknown. Here, we assayed 284 mostly poorly characterized, putative human TFs using selective microfluidics-based ligand enrichment followed by sequencing (SMiLE-seq), revealing 72 new DNA binding motifs. To investigate whether some of the 158 TFs for which we did not find motifs preferably bind epigenetically modified DNA (i.e. methylated CG dinucleotides), we developed methylation-sensitive SMiLE-seq (meSMiLE-seq). This microfluidic assay simultaneously probes the affinity of a protein to methylated and unmethylated DNA, augmenting the capabilities of the original method to infer methylation-aware binding sites. We assayed 114 TFs with meSMiLE-seq and identified DNA-binding models for 48 proteins, including the known methylation-sensitive binding modes for POU5F1 and RFX5. For 11 TFs, binding to methylated DNA was preferred or resulted in the discovery of alternative, methylation-dependent motifs (e.g. PRDM13), while aversion towards methylated sequences was found for 13 TFs (e.g. USF3). Finally, we uncovered a potential role for ZHX2 as a putative binder of Z-DNA, a left-handed helical DNA structure which is adopted more frequently upon CpG methylation. Altogether, our study significantly expands the human TF codebook by identifying DNA binding motifs for 98 TFs, while providing a versatile platform to quantitatively assay the impact of DNA modifications on TF binding.

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Perspectives on Codebook: sequence specificity of uncharacterized human transcription factors

Cited by 4 publications

References 95 publications

GHT-SELEX demonstrates unexpectedly high intrinsic sequence specificity and complex DNA binding of many human transcription factors

GHT-SELEX demonstrates unexpectedly high intrinsic sequence specificity and complex DNA binding of many human transcription factors

Cross-platform DNA motif discovery and benchmarking to explore binding specificities of poorly studied human transcription factors

Identification of methylation-sensitive human transcription factors using meSMiLE-seq

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