In one paragraphArticle in bioRxiv : the preprint server for biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from itWhat it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
2 · The registryThe trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
3 · Its place in the literatureWho cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
4 · The recordCorrections and comments
5 · Who and what moneyAuthors and funding
17 authors.
Antoni J GralakLaboratory of Systems Biology and Genetics, Institute of Bioengineering, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.ORCID 0009-0007-1086-6165 Katerina FaltejskovaInstitute of Organic Chemistry and Biochemistry, Czech Academy of Sciences, Prague, Czech Republic.ORCID 0000-0001-7390-8077 Clemence SteinerLaboratory of Systems Biology and Genetics, Institute of Bioengineering, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
Julie RusseilLaboratory of Systems Biology and Genetics, Institute of Bioengineering, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.ORCID 0000-0002-0880-9483 Nadia GrenninglohLaboratory of Systems Biology and Genetics, Institute of Bioengineering, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
Sachi InukaiLaboratory of Systems Biology and Genetics, Institute of Bioengineering, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.ORCID 0000-0002-6404-1384 Mustafa DemirLaboratory of Systems Biology and Genetics, Institute of Bioengineering, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
Riccardo DaineseLaboratory of Systems Biology and Genetics, Institute of Bioengineering, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.ORCID 0000-0003-4894-6586 Cooper OwenLaboratory of Systems Biology and Genetics, Institute of Bioengineering, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
Eugenia PankevichLaboratory of Systems Biology and Genetics, Institute of Bioengineering, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
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Judith F Kribelbauer-SwietekLaboratory of Systems Biology and Genetics, Institute of Bioengineering, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.ORCID 0000-0002-8072-7773 Guido van MierloLaboratory of Systems Biology and Genetics, Institute of Bioengineering, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.ORCID 0000-0001-5883-0339 Bart DeplanckeLaboratory of Systems Biology and Genetics, Institute of Bioengineering, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.ORCID 0000-0001-9935-843X Funding
X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Elisa de Stanchina · 1985 to 2026
$347.4MTissue Repository CoreP30AR070549 · NIAMS · CINCINNATI CHILDRENS HOSP MED CTR · PI Leah Claire Kottyan · 2016 to 2026
$7.7MGene regulatory network modeling of disease-associated DNA methylation perturbationsR01AI173314 · NIAID · CINCINNATI CHILDRENS HOSP MED CTR · PI Minji Byun, Emily Miraldi · 2023 to 2026
$3.1MPost-transcriptional Regulatory NetworksR01HG013328 · NHGRI · SLOAN-KETTERING INST CAN RESEARCH · PI Quaid Morris · 2023 to 2026
$2.6MTranscription Factor Genetics in LupusR01AR073228 · NIAMS · CINCINNATI CHILDRENS HOSP MED CTR · PI KOTTYAN, LEAH CLAIRE, WAGGONER, STEPHEN N. · 2019 to 2023
$2.2MCisBP and CisBP-RNA: web resources for protein-DNA and protein-RNA binding modelsU24HG013078 · NHGRI · CINCINNATI CHILDRENS HOSP MED CTR · PI Matthew Tyson Weirauch · 2024 to 2026
$1.6MMeasuring and describing nucleosome remodeler sequence preferencesR21HG012258 · NHGRI · UNIVERSITY OF TORONTO · PI HUGHES, TIMOTHY · 2022 to 2022
$267kNCI NIH HHS P30 CA008748NHGRI NIH HHS R01 HG013328NHGRI NIH HHS R21 HG012258NHGRI NIH HHS U24 HG013078NIAID NIH HHS R01 AI173314NIAMS NIH HHS P30 AR070549NIAMS NIH HHS R01 AR073228
6 · The paper itselfAbstract
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.
Identifiers
PMID39605503
PMCPMC11601298
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