Evidence map›Paper›PMID 38617331›Full record

ArticlebioRxiv : the preprint server for biology2024

Linkage equilibrium between rare mutations.

Anastasia S Lyulina, Zhiru Liu, Benjamin H Good

Open access · greenAbstract readPreprint
In one paragraph

Article 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 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, 0 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors at 2 institutions in 1 country.

Anastasia S LyulinaDepartment of Biology, Stanford University, Stanford, CA 94305, USA.ORCID 0000-0002-8450-9618
Zhiru LiuDepartment of Applied Physics, Stanford University, Stanford, CA 94305, USA.ORCID 0000-0002-2604-631X
Benjamin H GoodDepartment of Biology, Stanford University, Stanford, CA 94305, USA.ORCID 0000-0002-7757-3347
Stanford University · USChan Zuckerberg Initiative (United States) · US

Funding

Quantitative approaches for mapping the real-time evolution of the gut microbiotaR35GM146949 · NIGMS · STANFORD UNIVERSITY · PI Benjamin H Good · 2022 to 2026
$2.0M
NIGMS NIH HHS R35 GM146949
6 · The paper itself

Abstract

Recombination breaks down genetic linkage by reshuffling existing variants onto new genetic backgrounds. These dynamics are traditionally quantified by examining the correlations between alleles, and how they decay as a function of the recombination rate. However, the magnitudes of these correlations are strongly influenced by other evolutionary forces like natural selection and genetic drift, making it difficult to tease out the effects of recombination. Here we introduce a theoretical framework for analyzing an alternative family of statistics that measure the homoplasy produced by recombination. We derive analytical expressions that predict how these statistics depend on the rates of recombination and recurrent mutation, the strength of negative selection and genetic drift, and the present-day frequencies of the mutant alleles. We find that the degree of homoplasy can strongly depend on this frequency scale, which reflects the underlying timescales over which these mutations occurred. We show how these scaling properties can be used to isolate the effects of recombination, and discuss their implications for the rates of horizontal gene transfer in bacteria.

Identifiers

PMID38617331
PMCPMC11014483
OpenAlexW4393370943

What Socratic holds

Textmetadata
LicenceCC BY-NC
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 Socratic graph.