Evidence map›Paper›PMID 20333199›Full record

ArticleGenome biology and evolution2009

High-resolution mapping of evolutionary trajectories in a phage.

Benjamin Dickins, Anton Nekrutenko

Abstract read
In one paragraph

Article in Genome biology and evolution, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Review
  2. Polymorphisms inFrontiers in veterinary science · 2022
    Article
  3. Article
  4. Article
  5. Article
  6. Experimental evolution of viruses: Microviridae as a model system.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2010
    Article
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.

Benjamin DickinsCenter for Comparative Genomics and Bioinformatics, The Pennsylvania State University, USA. ben@bx.psu.edu
Anton Nekrutenko

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Experimental evolution in rapidly reproducing viruses offers a robust means to infer substitution trajectories during evolution. But with conventional approaches, this inference is limited by how many individual genotypes can be sampled from the population at a time. Low-frequency changes are difficult to detect, potentially rendering early stages of adaptation unobservable. Here we circumvent this using short-read sequencing technology in a fine-grained analysis of polymorphism dynamics in the sentinel organism: a single-stranded DNA phage PhiX174. Nucleotide differences were educed from noise with binomial filtering methods that harnessed quality scores and separate data from brief phage amplifications. Remarkably, a significant degree of variation was observed in all samples including those grown in brief 2-h cultures. Sites previously reported as subject to high-frequency polymorphisms over a course of weeks exhibited monotonic increases in polymorphism frequency within hours in this study. Additionally, even with limitations imposed by the short length of sequencing reads, we were able to observe statistically significant linkage among polymorphic sites in evolved lineages. Additional parallels between replicate lineages were apparent in the sharing of polymorphic sites and in correlated polymorphism frequencies. Missense mutations were more likely to occur than silent mutations. This study offers the first glimpse into "real-time" substitution dynamics and offers a robust conceptual framework for future viral resequencing studies.

Indexed as

experimental evolutionnext-generation sequencingsubstitution analysis

Identifiers

PMID20333199
PMCPMC2817424

What OpenQuestion 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 OpenQuestion graph.