Evidence map›Paper›PMID 38014077›Full record

ArticlebioRxiv : the preprint server for biology2023

Continuous evolution of user-defined genes at 1-million-times the genomic mutation rate.

Gordon Rix, Rory L Williams, Hansen Spinner, Vincent J Hu, Debora S Marks, Chang C Liu

Open access · greenAbstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2023. 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 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

0 citing papers in PubMed, 9 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors at 3 institutions in 1 country.

University of California, Irvine · USBroad Institute · USHarvard University · US

Funding

Making antibody generation rapid, scalable, and democratic through machine learning and continuous evolutionR01CA260415 · NCI · UNIVERSITY OF CALIFORNIA-IRVINE · PI KRUSE, ANDREW, LIU, CHANG C · 2020 to 2024
$8.4M
Synthetic genetic systems for rapid biomolecular evolution in vivoR35GM136297 · NIGMS · UNIVERSITY OF CALIFORNIA-IRVINE · PI LIU, CHANG C · 2020 to 2024
$2.4M
NCI NIH HHS R01 CA260415NIGMS NIH HHS R35 GM136297
6 · The paper itself

Abstract

When nature maintains or evolves a gene's function over millions of years at scale, it produces a diversity of homologous sequences whose patterns of conservation and change contain rich structural, functional, and historical information about the gene. However, natural gene diversity likely excludes vast regions of functional sequence space and includes phylogenetic and evolutionary eccentricities, limiting what information we can extract. We introduce an accessible experimental approach for compressing long-term gene evolution to laboratory timescales, allowing for the direct observation of extensive adaptation and divergence followed by inference of structural, functional, and environmental constraints for any selectable gene. To enable this approach, we developed a new orthogonal DNA replication (OrthoRep) system that durably hypermutates chosen genes at a rate of >10

Identifiers

PMID38014077
PMCPMC10680746
OpenAlexW4388680622

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.