Regulation of anti-sense transcription by Mot1p and NC2 via removal of TATA-binding protein (TBP) from the 3′-end of genes
Open accessAbstract
The activity and dynamic nature of TATA-binding protein (TBP) crucial to RNA polymerase II-mediated transcription is under control of the Mot1p and NC2 complexes. Here we show that both TBP regulatory factors play 'hidden' roles in ensuring transcription fidelity by restricting anti-sense non-coding RNA (ncRNA) synthesis. Production of anti-sense ncRNA transcripts is suppressed by Mot1p- and NC2-mediated release of TBP from binding sites at the 3'-end of genes. In this, Mot1p and NC2 collaborate with the Nrd1p-Nab3p-Sen1p (NNS) complex that terminates the synthesis of anti-sense ncRNAs. In several cases anti-sense ncRNA expression interferes with expression of the cognate sense transcript. Our data reveal a novel regulatory mechanism to suppress anti-sense ncRNA expression and pre-initiation complex (PIC) formation at spurious sites.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
PCR is an exponential process, so small random variations early on in amplification can have a large impact on distribution.
“PCR is an exponential process, so small random variations early on in amplification can have a large impact on distribution18–24.”
From Quantifying Molecular Bias in DNA Data Storage (2019) · cites this paper as [24]
The Materials and Methods sections on plasmids and chromatin immunoprecipitation describe using PCR to generate fragments and analyze samples. Neither those passages nor searches for exponential amplification and early-cycle stochastic variation address whether small random variations can substantially change the resulting distribution. Page numbers are unavailable in our copy. (LLM, conf=0.76)
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Bidirectional promoters generate pervasive transcription in yeast
Xu, Z., Wei, W., Gagneur, J., Perocchi, F., Clauder‐Münster, S., Camblong, J., Guffanti, E., Stutz, F., Huber, W. K., & Steinmetz, L. M. (2009) · Nature · doi:10.1038/nature07728 · Cited by 926 · see citing works
Wyers, F., Rougemaille, M., Badis, G., Rousselle, J.-C., Dufour, M., Boulay, J., Regnault, B., Devaux, F., Namane, A., Séraphin, B., et al. (2005) · Cell · doi:10.1016/j.cell.2005.04.030 · Cited by 843 · see citing works
Nascent transcript sequencing visualizes transcription at nucleotide resolution
Churchman, L. S., & Weissman, J. S. (2011) · Nature · doi:10.1038/nature09652 · Cited by 823 · see citing works
A high-resolution map of transcription in the yeast genome
David, L., Huber, W. K., Granovskaia, M. V., Toedling, J., Palm, C. J., Bofkin, L., Jones, T., Davis, R. W., & Steinmetz, L. M. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0601091103 · Cited by 697 · see citing works
A barrier nucleosome model for statistical positioning of nucleosomes throughout the yeast genomePreprint
Mavrich, T. N., Ioshikhes, I. P., Venters, B. J., Jiang, C., Tomsho, L. P., Qi, J., Schuster, S. C., Albert, I. U., & Pugh, B. F. (2008) · Genome Research · doi:10.1101/gr.078261.108 · Cited by 673 · see citing works
Gene regulation by antisense transcription
Pelechano, V., & Steinmetz, L. M. (2013) · Nature Reviews Genetics · doi:10.1038/nrg3594 · Cited by 628 · see citing works
Widespread bidirectional promoters are the major source of cryptic transcripts in yeast
Neil, H., Malabat, C., D'Aubenton-Carafa, Y., Xu, Z.-Y., Steinmetz, L., & Jacquier, A. (2009) · Nature · doi:10.1038/nature07747 · Cited by 626 · see citing works
Intergenic transcription is required to repress the Saccharomyces cerevisiae SER3 gene
Martens, J. A., Laprade, L., & Winston, F. (2004) · Nature · doi:10.1038/nature02538 · Cited by 594 · see citing works
The Anchor-Away Technique: Rapid, Conditional Establishment of Yeast Mutant Phenotypes
Haruki, H., Nishikawa, J., & Laemmli, U. K. (2008) · Molecular Cell · doi:10.1016/j.molcel.2008.07.020 · Cited by 547 · see citing works
Genome-wide structure and organization of eukaryotic pre-initiation complexes
Rhee, H. S., & Pugh, B. F. (2012) · Nature · doi:10.1038/nature10799 · Cited by 496 · see citing works
Chromatin remodelling at promoters suppresses antisense transcription
Whitehouse, I., Rando, O. J., Delrow, J., & Tsukiyama, T. (2007) · Nature · doi:10.1038/nature06391 · Cited by 456 · see citing works
Extensive transcriptional heterogeneity revealed by isoform profiling
Pelechano, V., Wu, W., & Steinmetz, L. M. (2013) · Nature · doi:10.1038/nature12121 · Cited by 450 · see citing works
XUTs are a class of Xrn1-sensitive antisense regulatory non-coding RNA in yeast
van Dijk, E., Chen, C.-L., d’Aubenton-Carafa, Y., Gourvennec, S., Kwapisz, M., Roche, V., Bertrand, C., Silvain, M., Legoix-Né, P., Loeillet, S., et al. (2011) · Nature · doi:10.1038/nature10118 · Cited by 367 · see citing works
Camblong, J., Iglesias, N., Fickentscher, C., Dieppois, G., & Stutz, F. (2007) · Cell · doi:10.1016/j.cell.2007.09.014 · Cited by 354 · see citing works
Smolle, M., Venkatesh, S., Gogol, M., Li, H., Zhang, Y., Florens, L. A., Washburn, M. P., & Workman, J. L. (2012) · Nature Structural & Molecular Biology · doi:10.1038/nsmb.2312 · Cited by 305 · see citing works
Auble, D., Hansen, K. E., Mueller, C. G., Lane, W. S., Thorner, J. W., & Hahn, S. (1994) · Genes & Development · doi:10.1101/gad.8.16.1920 · Cited by 295 · see citing works
Vasiljeva, L., Kim, M., Mutschler, H., Buratowski, S., & Meinhart, A. (2008) · Nature Structural & Molecular Biology · doi:10.1038/nsmb.1468 · Cited by 290 · see citing works
A Role for Snf2-Related Nucleosome-Spacing Enzymes in Genome-Wide Nucleosome Organization
Gkikopoulos, T., Schofield, P., Singh, V., Pinskaya, M., Mellor, J., Smolle, M. M., Workman, J. L., Barton, G. J., & Owen‐Hughes, T. (2011) · Science · doi:10.1126/science.1206097 · Cited by 288 · see citing works
Termination of Cryptic Unstable Transcripts Is Directed by Yeast RNA-Binding Proteins Nrd1 and Nab3
Arigo, J. T., Eyler, D. E., Carroll, K. L., & Corden, J. L. (2006) · Molecular Cell · doi:10.1016/j.molcel.2006.07.024 · Cited by 257 · see citing works
van Werven, F. J., Neuert, G., Hendrick, N., Lardenois, A., Buratowski, S., van Oudenaarden, A., Primig, M., & Amon, A. (2012) · Cell · doi:10.1016/j.cell.2012.06.049 · Cited by 257 · see citing works
Martens, J. A., Wu, P.-Y. J., & Winston, F. (2005) · Genes & Development · doi:10.1101/gad.1367605 · Cited by 240 · see citing works
A Transcriptome-wide Atlas of RNP Composition Reveals Diverse Classes of mRNAs and lncRNAs
Tuck, A., & Tollervey, D. W. (2013) · Cell · doi:10.1016/j.cell.2013.07.047 · Cited by 231 · see citing works
Transcriptome Surveillance by Selective Termination of Noncoding RNA Synthesis
Schulz, D., Schwalb, B., Kiesel, A., Baejen, C., Torkler, P., Gagneur, J., Söding, J., & Cramer, P. (2013) · Cell · doi:10.1016/j.cell.2013.10.024 · Cited by 219 · see citing works
Set3 HDAC Mediates Effects of Overlapping Noncoding Transcription on Gene Induction Kinetics
Kim, T. S., Xu, Z., Clauder‐Münster, S., Steinmetz, L. M., & Buratowski, S. (2012) · Cell · doi:10.1016/j.cell.2012.08.016 · Cited by 201 · see citing works
Antisense expression increases gene expression variability and locus interdependency
Xu, Z., Wei, W., Gagneur, J., Clauder‐Münster, S., Smolik, M., Huber, W. K., & Steinmetz, L. M. (2011) · Molecular Systems Biology · doi:10.1038/msb.2011.1 · Cited by 176 · see citing works
Goppelt, A., Stelzer, G., Lottspeich, F., & Meisterernst, M. (1996) · The EMBO Journal · doi:10.1002/j.1460-2075.1996.tb00673.x · Cited by 159 · see citing works
An ATP-dependent inhibitor of TBP binding to DNA.Preprint
Auble, D., & Hahn, S. (1993) · Genes & Development · doi:10.1101/gad.7.5.844 · Cited by 159 · see citing works
The mammalian TFIID protein is present in two functionally distinct complexes.Preprint
Timmers, H. T. M., & Sharp, P. A. (1991) · Genes & Development · doi:10.1101/gad.5.11.1946 · Cited by 143 · see citing works
Self-citationYassour, M., Pfiffner, J., Levin, J. Z., Adiconis, X., Gnirke, A., Nusbaum, C., Thompson, D. A., Friedman, N., & Regev, A. (2010) · Genome biology · doi:10.1186/gb-2010-11-8-r87 · Cited by 136 · see citing works
Margaritis, T., Oréal, V., Brabers, N. A. C. H., Maestroni, L., Vitaliano-Prunier, A., Benschop, J. J., van Hooff, S. R., van Leenen, D., Dargemont, C., Géli, V., et al. (2012) · PLoS Genetics · doi:10.1371/journal.pgen.1002952 · Cited by 134 · see citing works
Bimodal expression of PHO84 is modulated by early termination of antisense transcription
Castelnuovo, M., Rahman, S., Guffanti, E., Infantino, V., Stutz, F., & Zenklusen, D. R. (2013) · Nature Structural & Molecular Biology · doi:10.1038/nsmb.2598 · Cited by 131 · see citing works
Molecular Basis for Coordinating Transcription Termination with Noncoding RNA Degradation
Tudek, A., Porrúa, O., Kabzinski, T., Lidschreiber, M., Kubíček, K., Fořtová, A., Lacroute, F., Vaňáčová, Š., Cramer, P., Štefl, R., et al. (2014) · Molecular Cell · doi:10.1016/j.molcel.2014.05.031 · Cited by 126 · see citing works
Molecular Characterization of Saccharomyces cerevisiae TFIID
Sanders, S. L., Garbett, K. A., & Weil, P. A. (2002) · Molecular and Cellular Biology · doi:10.1128/mcb.22.16.6000-6013.2002 · Cited by 107 · see citing works
A Chromatin-Based Mechanism for Limiting Divergent Noncoding Transcription
Marquardt, S., Escalante-Chong, R., Pho, N. H., Wang, J., Churchman, L. S., Springer, M., & Buratowski, S. (2014) · Cell · doi:10.1016/j.cell.2014.04.036 · Cited by 97 · see citing works
Distinct RNA degradation pathways and 3' extensions of yeast non-coding RNA species
Marquardt, S., Hazelbaker, D. Z., & Buratowski, S. (2011) · Transcription · doi:10.4161/trns.2.3.16298 · Cited by 94 · see citing works
ISWI and CHD Chromatin Remodelers Bind Promoters but Act in Gene Bodies
Zentner, G. E., Tsukiyama, T., & Henikoff, S. (2013) · PLoS Genetics · doi:10.1371/journal.pgen.1003317 · Cited by 86 · see citing works
ISWI and CHD chromatin remodelers bind to promoters but act in gene bodies
Zentner, G. E., Tsukiyama, T., & Henikoff, S. (2013) · Epigenetics & Chromatin · doi:10.1186/1756-8935-6-s1-o29 · Cited by 85 · see citing works
Yadon, A., VanDemark, D., Basom, R., Delrow, J., Whitehouse, I., & Tsukiyama, T. (2010) · Molecular and Cellular Biology · doi:10.1128/mcb.00602-10 · Cited by 84 · see citing works
Composition of transcription factor B-TFIID.
Timmers, H. T. M., Meyers, R. E., & Sharp, P. A. (1992) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.89.17.8140 · Cited by 79 · see citing works
Self-citationRegulation of TATA-binding protein dynamics in living yeast cells
Sprouse, R. O., Karpova, T., Mueller, F., Dasgupta, A., McNally, J. G., & Auble, D. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0801901105 · Cited by 77 · see citing works
Cooperative action of NC2 and Mot1p to regulate TATA-binding protein function across the genomePreprint
van Werven, F. J., van Bakel, H., van Teeffelen, H. A. A. M., Altelaar, M. A. F., Koerkamp, M. J. A. G., Heck, A. J. R., Holstege, F. C. P., & Timmers, H. T. M. (2008) · Genes & Development · doi:10.1101/gad.1682308 · Cited by 73 · see citing works
Self-citationNC2 mobilizes TBP on core promoter TATA boxes
Schluesche, P., Stelzer, G., Piaia, E., Lamb, D. C., & Meisterernst, M. (2007) · Nature Structural & Molecular Biology · doi:10.1038/nsmb1328 · Cited by 72 · see citing works
Structure and mechanism of the Swi2/Snf2 remodeller Mot1 in complex with its substrate TBP
Wollmann, P., Cui, S., Viswanathan, R., Berninghausen, O., Wells, M. N., Moldt, M., Witte, G., Butryn, A., Wendler, P., Beckmann, R., et al. (2011) · Nature · doi:10.1038/nature10215 · Cited by 72 · see citing works
Murray, S. C., Barros, A. S., Brown, D. A., Dudek, P., Ayling, J., & Mellor, J. (2011) · Nucleic Acids Research · doi:10.1093/nar/gkr1121 · Cited by 68 · see citing works
Boa, S., Coert, C., & Patterton, H. (2003) · Yeast · doi:10.1002/yea.995 · Cited by 62 · see citing works
Chromatin interaction of TATA-binding protein is dynamically regulated in human cells
de Graaf, P., Mousson, F., Geverts, B., Scheer, E., Tora, L., Houtsmuller, A. B., & Timmers, H. T. M. (2010) · Journal of Cell Science · doi:10.1242/jcs.064097 · Cited by 58 · see citing works
Self-citationCastelnuovo, M., Zaugg, J. B., Guffanti, E., Maffioletti, A., Camblong, J., Xu, Z., Clauder‐Münster, S., Steinmetz, L. M., Luscombe, N. M., & Stutz, F. (2014) · Nucleic Acids Research · doi:10.1093/nar/gku100 · Cited by 50 · see citing works
Mot1 Redistributes TBP from TATA-Containing to TATA-Less Promoters
Zentner, G. E., & Henikoff, S. (2013) · Molecular and Cellular Biology · doi:10.1128/mcb.01218-13 · Cited by 49 · see citing works
High‐affinity DNA binding by a Mot1p–TBP complex: implications for TAF‐independent transcription
Gumbs, O. H., Campbell, A. M., & Weil, P. A. (2003) · The EMBO Journal · doi:10.1093/emboj/cdg304 · Cited by 43 · see citing works
Suppression of intragenic transcription requires the MOT1 and NC2 regulators of TATA-binding protein
Koster, M. J. E., Yıldırım, A., Weil, P. A., Holstege, F. C. P., & Timmers, H. T. M. (2014) · Nucleic Acids Research · doi:10.1093/nar/gkt1398 · Cited by 18 · see citing works
Self-citationSpedale, G., Meddens, C., Koster, M. J. E., Ko, C. W., van Hooff, S. R., Holstege, F. C. P., Timmers, H. T. M., & Pijnappel, W. W. M. P. (2011) · Nucleic Acids Research · doi:10.1093/nar/gkr784 · Cited by 17 · see citing works
Self-citation
Flagged first, then by citations
Cited by
Sorted by citations
Beng, K. C., & Corlett, R. T. (2020) · Biodiversity and Conservation · doi:10.1007/s10531-020-01980-0 · Cited by 721 · see citing works
Overview of methodologies for T-cell receptor repertoire analysis
Rosati, E., Dowds, C. M., Liaskou, E., Henriksen, E. K. K., Karlsen, T. H., & Franke, A. (2017) · BMC Biotechnology · doi:10.1186/s12896-017-0379-9 · Cited by 322 · see citing works
Olova, N. N., Krueger, F., Andrews, S., Oxley, D., Berrens, R. V., Branco, M. R., & Reik, W. (2018) · Genome biology · doi:10.1186/s13059-018-1408-2 · Cited by 312 · see citing works
A Sequel to Sanger: amplicon sequencing that scales
Hebert, P. D. N., Braukmann, T., Prosser, S. W. J., Ratnasingham, S., deWaard, J. R., Ivanova, N. V., Janzen, D. H., Hallwachs, W., Naik, S., Sones, J. E., et al. (2018) · BMC Genomics · doi:10.1186/s12864-018-4611-3 · Cited by 278 · see citing works
CRISPR-Cas based virus detection: Recent advances and perspectives
Yin, L., Man, S., Ye, S., Liu, G., & Ma, L. (2021) · Biosensors and Bioelectronics · doi:10.1016/j.bios.2021.113541 · Cited by 281 · see citing works
Single-cell sequencing of the small-RNA transcriptome
Faridani, O. R., Abdullayev, I., Hagemann-Jensen, M., Schell, J. P., Lanner, F., & Sandberg, R. (2016) · Nature Biotechnology · doi:10.1038/nbt.3701 · Cited by 219 · see citing works
Cellular barcoding: lineage tracing, screening and beyond
Kebschull, J. M., & Zador, A. M. (2018) · Nature Methods · doi:10.1038/s41592-018-0185-x · Cited by 181 · see citing works
Quantifying Molecular Bias in DNA Data Storage
Chen, Y.-J., Takahashi, C. N., Organick, L., Stewart, K., Ang, S. D., Weiss, P., Peck, B., Seelig, G., Ceze, L., & Strauss, K. (2019) · doi:10.1101/566554 · Cited by 109 · see citing works
Metabarcoding of lake benthic diatoms: from structure assemblages to ecological assessment
Rivera, S. F., Vasselon, V., Jacquet, S., Bouchez, A., Arizteguí, D., & Rimet, F. (2017) · Hydrobiologia · doi:10.1007/s10750-017-3381-2 · Cited by 96 · see citing works
Rimet, F., Vasselon, V., A.-Keszte, B., & Bouchez, A. (2018) · Organisms Diversity & Evolution · doi:10.1007/s13127-018-0359-5 · Cited by 67 · see citing works
Amplifying mutational profiling of extracellular vesicle mRNA with SCOPE
Song, J., Cho, M. H., Cho, H., Song, Y., Lee, S.-W., Nam, H. C., Yoon, T.-H., Shin, J. C., Hong, J., Kim, Y., et al. (2024) · Nature Biotechnology · doi:10.1038/s41587-024-02426-6 · Cited by 57 · see citing works
Genomic signatures of recombination in a natural population of the bdelloid rotifer Adineta vaga
Vakhrusheva, O. A., Mnatsakanova, E. A., Galimov, Y. R., Neretina, T. V., Gerasimov, E. S., Naumenko, S., Ozerova, S. G., Zalevsky, A. O., Yushenova, I. A., Rodríguez, F., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-19614-y · Cited by 54 · see citing works
UMI-linked consensus sequencing enables phylogenetic analysis of directed evolution
Zurek, P. J., Knyphausen, P., Neufeld, K., Pushpanath, A., & Hollfelder, F. (2020) · Nature Communications · doi:10.1038/s41467-020-19687-9 · Cited by 47 · see citing works
Role of the TATA-box binding protein (TBP) and associated family members in transcription regulation
Mishal, R., & Luna‐Arias, J. P. (2022) · Gene · doi:10.1016/j.gene.2022.146581 · Cited by 47 · see citing works
Mellor, J., Woloszczuk, R., & Howe, F. S. (2015) · Trends in Genetics · doi:10.1016/j.tig.2015.10.006 · Cited by 44 · see citing works
A digital twin for DNA data storage based on comprehensive quantification of errors and biases
Gimpel, A. L., Stark, W. J., Heckel, R., & Grass, R. N. (2023) · Nature Communications · doi:10.1038/s41467-023-41729-1 · Cited by 38 · see citing works
A high-throughput assay for quantitative measurement of PCR errors
Shagin, D. A., Shagina, I. A., Zaretsky, A. R., Barsova, E. V., Kelmanson, I. V., Lukyanov, S., Chudakov, D. M., & Shugay, M. (2017) · Scientific Reports · doi:10.1038/s41598-017-02727-8 · Cited by 41 · see citing works
Dynamic epistasis analysis reveals how chromatin remodeling regulates transcriptional bursting
Brouwer, I., Kerklingh, E., van Leeuwen, F., & Lenstra, T. L. (2023) · Nature Structural & Molecular Biology · doi:10.1038/s41594-023-00981-1 · Cited by 38 · see citing works
Spatially resolved and multiplexed MicroRNA quantification from tissue using nanoliter well arrays
Nagarajan, M. B., Tentori, A. M., Zhang, W. C., Slack, F. J., & Doyle, P. S. (2020) · Microsystems & Nanoengineering · doi:10.1038/s41378-020-0169-8 · Cited by 37 · see citing works
SAGA and TFIID: Friends of TBP drifting apart
Timmers, H. T. M. (2020) · Biochimica et Biophysica Acta (BBA) - Gene Regulatory Mechanisms · doi:10.1016/j.bbagrm.2020.194604 · Cited by 36 · see citing works
Self-citationTAC-seq: targeted DNA and RNA sequencing for precise biomarker molecule counting
Teder, H., Koel, M., Paluoja, P., Jatsenko, T., Rekker, K., Laisk, T., Kukuškina, V., Velthut‐Meikas, A., Fjodorova, O., Peters, M., et al. (2018) · npj Genomic Medicine · doi:10.1038/s41525-018-0072-5 · Cited by 35 · see citing works
Expression level is a major modifier of the fitness landscape of a protein coding gene
Wu, Z., Cai, X., Zhang, X., Liu, Y., Tian, G., Yang, J., & Chen, X. (2021) · Nature Ecology & Evolution · doi:10.1038/s41559-021-01578-x · Cited by 32 · see citing works
Busi, S. B., Pramateftaki, P. V., Brandani, J., Fodelianakis, S., Peter, H., Halder, R., Wilmes, P., & Battin, T. J. (2020) · PeerJ · doi:10.7717/peerj.9973 · Cited by 34 · see citing works
Ogawa, T., Kryukov, K. A., Imanishi, T., & Shiroguchi, K. (2017) · Scientific Reports · doi:10.1038/s41598-017-13529-3 · Cited by 31 · see citing works
Using genomics to understand the mechanisms of virulence and drug resistance in fungal pathogens
Schikora-Tamarit, M. À., & Gabaldón, T. (2022) · Biochemical Society Transactions · doi:10.1042/bst20211123 · Cited by 30 · see citing works
Structural basis for recognition and remodeling of the TBP:DNA:NC2 complex by Mot1
Butryn, A., Schuller, J. M., Stoehr, G., Runge-Wollmann, P., Förster, F. G., Auble, D., & Hopfner, K. (2015) · eLife · doi:10.7554/elife.07432 · Cited by 27 · see citing works
A robust targeted sequencing approach for low input and variable quality DNA from clinical samples
So, A. P., Vilborg, A., Bouhlal, Y., Koehler, R. T., Grimes, S. M., Pouliot, Y., Mendoza, D., Ziegle, J. S., Stein, J. B., Goodsaid, F. M., et al. (2018) · npj Genomic Medicine · doi:10.1038/s41525-017-0041-4 · Cited by 26 · see citing works
Nizamuddin, S., Koidl, S., Bhuiyan, T., Werner, T. V., Biniossek, M. L., Bonvin, A. M. J. J., Laßmann, S., & Timmers, H. T. M. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkab038 · Cited by 24 · see citing works
Self-citationThe highly rugged yet navigable regulatory landscape of the bacterial transcription factor TetR
Westmann, C. A., Goldbach, L., & Wagner, A. (2024) · Nature Communications · doi:10.1038/s41467-024-54723-y · Cited by 26 · see citing works
ECOLE: Learning to call copy number variants on whole exome sequencing data
Mandiracioglu, B., Özden, F., Kaynar, G., Yılmaz, M. A., Alkan, C., & Çiçek, A. E. (2024) · Nature Communications · doi:10.1038/s41467-023-44116-y · Cited by 20 · see citing works
Aurora B-dependent Ndc80 degradation regulates kinetochore composition in meiosisPreprint
Chen, J., Liao, A., Powers, E. N., Liao, H., Kohlstaedt, L. A., Evans, R. K., Holly, R. M., Kim, J. K., Jovanović, M., & Ünal, E. (2020) · Genes & Development · doi:10.1101/gad.333997.119 · Cited by 21 · see citing works
Single-Cell Non-coding RNA in Embryonic Development
Fu, Q., Liu, C., Zhai, Z., Zhang, X., Qin, T., & Zhang, H. (2018) · Advances in experimental medicine and biology · doi:10.1007/978-981-13-0502-3_3 · Cited by 18 · see citing works
Topal, S., Van, C., Xue, Y., Carey, M., & Peterson, C. L. (2020) · Cell Reports · doi:10.1016/j.celrep.2020.108106 · Cited by 17 · see citing works
Whole exome sequencing in inborn errors of immunity: use the power but mind the limits
Bucciol, G., Nieuwenhove, E. V., Moens, L., Itan, Y., & Meyts, I. (2017) · Current Opinion in Allergy and Clinical Immunology · doi:10.1097/aci.0000000000000398 · Cited by 17 · see citing works
Xu, Y. F., Lee, J., Li, Z., Wang, L., Ördög, T., & Bailey, R. C. (2018) · Lab on a Chip · doi:10.1039/c8lc00599k · Cited by 14 · see citing works
Kallurkar, P. S., Picardo, M. C. D., Sugimura, Y. K., Saha, M. S., Smith, G. D., & Negro, C. A. D. (2022) · Scientific Reports · doi:10.1038/s41598-022-06834-z · Cited by 15 · see citing works
P-TEFb Regulates Transcriptional Activation in Non-coding RNA Genes
Bunch, H., Choe, H., Kim, J., Jo, D. S., Jeon, S., Lee, S.-H., Cho, D., & Kang, K. (2019) · Frontiers in Genetics · doi:10.3389/fgene.2019.00342 · Cited by 11 · see citing works
Gómez‐Navarro, N., Jordán‐Pla, A., Estruch, F., & Pérez-Ortín, J. E. (2016) · BMC Genomics · doi:10.1186/s12864-016-2536-2 · Cited by 9 · see citing works
Salgado‐Salazar, C., LeBlanc, N., Wallace, E. C., Daughtrey, M., & Crouch, J. A. (2020) · European Journal of Plant Pathology · doi:10.1007/s10658-020-01989-9 · Cited by 9 · see citing works
ACIDES: on-line monitoring of forward genetic screens for protein engineering
Nemoto, T., Ocari, T., Planul, A., Tekinsoy, M., Zin, E. A., Dalkara, D., & Ferrari, U. (2023) · Nature Communications · doi:10.1038/s41467-023-43967-9 · Cited by 8 · see citing works
Krzyczmonik, K., Wroblewska-Swiniarska, A., & Świeżewski, S. (2017) · RNA Biology · doi:10.1080/15476286.2017.1327112 · Cited by 6 · see citing works
Álvarez-Carretero, S., & dos Reis, M. (2020) · Springer eBooks · doi:10.1007/978-3-030-60181-2_13 · Cited by 4 · see citing works
Predicting sequence-specific amplification efficiency in multi-template PCR with deep learning
Gimpel, A. L., Fan, B., Chen, D., Wölfle, L. O. D., Horn, M., Meng-Papaxanthos, L., Antkowiak, P. L., Stark, W. J., Christen, B., Borgwardt, K. M., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-64221-4 · Cited by 3 · see citing works
Bronchain, O. J., Ducos, B., Putzer, H., Delagrange, M., Laalami, S., Philippe-Caraty, L., Saroul, K., & Ciapa, B. (2023) · Journal of Cell Science · doi:10.1242/jcs.261284 · Cited by 2 · see citing works
Essential Elements for Establishing Clinical Next-generation Sequencing Testing
Park, K., Lee, W., Chun, S., & Min, W. (2019) · Laboratory Medicine Online · doi:10.3343/lmo.2019.9.2.37 · Cited by 2 · see citing works
Molecular Pathways and Recent Therapeutic Strategies for Polyglutamine Diseases
Roy, S. K., Barman, A., Richard, S. A., & Lacmane, B. A. (2025) · Current Molecular Medicine · doi:10.2174/0115665240393446250829084646 · Cited by 1 · see citing works
Yeo, J. H., Lee, S., Kim, S., Min, J.-G., Gopalappa, R., Oh, H.-C., Kim, H. K., Nam, E.-J., & Kim, S. (2025) · Nature Biomedical Engineering · doi:10.1038/s41551-025-01535-0 · Cited by 1 · see citing works
Evolution, structure and assembly of basal Transcription Factor II D
Antonova, S. (2020) · doi:10.33540/207 · Cited by 1 · see citing works
High-resolution binding data of TFIID and cofactors show promoter-specific differences in vivoPreprint
Zeitlinger, J., Alcantara, S. G.-M., Bourdareau, S., & Weilert, M. (2025) · Research Square · doi:10.21203/rs.3.rs-8428476/v1 · Cited by 1 · see citing works
Analytical Challenges of Next-generation Sequencing in Precision Medicine
Liebers, M. R. (2020) · Royal Society of Chemistry eBooks · doi:10.1039/9781788019958-00153
Mapping Brain-Wide Mesoscale Connectome from Single Animals with BRICseq
Huang, L. (2022) · Neuromethods · doi:10.1007/978-1-0716-2321-3_2
An essential gene screening identifies yeast Mot1 as a suppressor of R-loops and genome instability
Soler-Oliva, M. E., Domínguez-Sierra, R. A., Gaillard, H., & Aguilera, A. (2026) · PLoS Genetics · doi:10.1371/journal.pgen.1012040
iMUT-seq mapping of DSB-induced mutations with high sensitivity at single-nucleotide resolution
Bader, A. S., & Bushell, M. (2026) · Nature Protocols · doi:10.1038/s41596-026-01394-2
DNA-encoded libraries through a machine learning lens: challenges and opportunities
Bahia, M. S., Jiang, Y., Gonse, A., Batey, R. A., & Koziarski, M. (2026) · Digital Discovery · doi:10.1039/d6dd00117c
Single‐target contamination modeling in pathogen metagenomic sequencing via simple linear regression
Liu, X., Wang, L., Lou, J., Tan, Z., Shen, S., Wang, Y., Liao, C., & Chen, S. (2026) · Open Research (University of Surrey) · doi:10.1002/viw2.70218
- Authors
- Koster, M. J. E., & Timmers, H. T. M.
- Affiliations
- University Medical Center Utrecht (NL)
- Corresponding author
- Timmers, H.Th. Marc
- ORCID
- Timmers, H.Th. Marc
- Venue
- Nucleic Acids Research
- Publisher
- Oxford University Press (OUP)
- Published
- 2014-11-28
- Volume
- 43
- Issue
- 1
- Pages
- 143-152
- ISSN
- 0305-1048 (ISSN-L)
- 1362-4962
- PMC
- PMC4288163
- OpenAlex
- W2097096882
- Cited by
- 55
- References
- 51
- Citations by year
- 2026: 4 · 2025: 4 · 2024: 3 · 2023: 4 · 2022: 4 · 2021: 3 · 2020: 13 · 2019: 2 · 2018: 8 · 2017: 6 · 2016: 2 · 2015: 2
- FWCI
- 1.37
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Nucleic Acids Research (publishedVersion, cc-by-nc)
- Europe PMC (PubMed Central) (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- Utrecht University Repository (Utrecht University) (submittedVersion, other-oa)
- Funders
- Nederlandse Organisatie voor Wetenschappelijk Onderzoek (820.02.013, 700.57.302)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Research and Splicing
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer-related molecular mechanisms research
- Keywords
- TATA-binding protein, transcription termination, non-coding RNA, RNA polymerase II, preinitiation complex, transcriptional interference, Saccharomyces cerevisiae
- MeSH terms
- Adenosine Triphosphatases, Chromatin, Phosphoproteins, Promoter Regions, Genetic, Saccharomyces cerevisiae, Transcription Factors, Transcription, Genetic, Gene Expression Regulation, Fungal, RNA, Antisense, RNA-Binding Proteins, RNA, Untranslated, 3' Flanking Region, Saccharomyces cerevisiae Proteins, TATA-Box Binding Protein, TATA-Binding Protein Associated Factors
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review