Evidence map›Paper›PMID 19841254›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2009

Experimental determination of the evolvability of a transcription factor.

Sebastian J Maerkl, Stephen R Quake

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.

0numbers the graph read from it
0cells of the map it votes in
41citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What 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 registry

The 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 literature

Who cites it

41 citing papers in PubMed.

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  8. Cell-free gene-regulatory network engineering with synthetic transcription factors.Proceedings of the National Academy of Sciences of the United States of America · 2019
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Sebastian J MaerklDepartment of Bioengineering, Stanford University and Howard Hughes Medical Institute, Stanford, CA 94305, USA.
Stephen R Quake

Funding

Howard Hughes Medical Institute
6 · The paper itself

Abstract

Sequence-specific binding of a transcription factor to DNA is the central event in any transcriptional regulatory network. However, relatively little is known about the evolutionary plasticity of transcription factors. For example, the exact functional consequence of an amino acid substitution on the DNA-binding specificity of most transcription factors is currently not predictable. Furthermore, although the major structural families of transcription factors have been identified, the detailed DNA-binding repertoires within most families have not been characterized. We studied the sequence recognition code and evolvability of the basic helix-loop-helix transcription factor family by creating all possible 95 single-point mutations of five DNA-contacting residues of Max, a human helix-loop-helix transcription factor and measured the detailed DNA-binding repertoire of each mutant. Our results show that the sequence-specific repertoire of Max accessible through single-point mutations is extremely limited, and we are able to predict 92% of the naturally occurring diversity at these positions. All naturally occurring basic regions were also found to be accessible through functional intermediates. Finally, we observed a set of amino acids that are functional in vitro but are not found to be used naturally, indicating that functionality alone is not sufficient for selection.

Indexed as

Evolution, MolecularGenetic TechniquesBase SequenceBasic Helix-Loop-Helix Leucine Zipper Transcription FactorsGene LibraryGenetic VariationHumansMicrofluidic Analytical TechniquesMutationTranscription FactorsBasic Helix-Loop-Helix Leucine Zipper Transcription FactorsMAX protein, humanTranscription Factors

Identifiers

PMID19841254
PMCPMC2765923

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.