Evidence map›Paper›PMID 24555023›Full record

ArticleF1000Research2013

De novo genetic variation revealed in somatic sectors of single Arabidopsis plants.

Marianne T Hopkins, Aaron M Khalid, Pei-Chun Chang, Karen C Vanderhoek, Dulcie Lai, Meghan D Doerr, Susan J Lolle

Abstract read
In one paragraph

Article in F1000Research, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

7 authors.

Marianne T HopkinsDepartment of Biology, University of Waterloo, Waterloo, N2L 3G1, Canada.
Aaron M KhalidDepartment of Biology, University of Waterloo, Waterloo, N2L 3G1, Canada.
Pei-Chun ChangDepartment of Biology, University of Waterloo, Waterloo, N2L 3G1, Canada.
Karen C VanderhoekDepartment of Biology, University of Waterloo, Waterloo, N2L 3G1, Canada.
Dulcie LaiDepartment of Pathology and Molecular Medicine, Queen's University, Kingston, K7L 3N6, Canada.
Meghan D DoerrDepartment of Biology, University of Waterloo, Waterloo, N2L 3G1, Canada.
Susan J LolleDepartment of Biology, University of Waterloo, Waterloo, N2L 3G1, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Concern over the tremendous loss of genetic diversity among many of our most important crops has prompted major efforts to preserve seed stocks derived from cultivated species and their wild relatives.  Arabidopsis thaliana propagates mainly by self-fertilizing, and therefore, like many crop plants, theoretically has a limited potential for producing genetically diverse offspring. Despite this, inbreeding has persisted in Arabidopsis for over a million years suggesting that some underlying adaptive mechanism buffers the deleterious consequences of this reproductive strategy. Using presence-absence molecular markers we demonstrate that single Arabidopsis plants can have multiple genotypes. Sequence analyses reveal single nucleotide changes, loss of sequences and, surprisingly, acquisition of unique genomic insertions. Estimates based on quantitative analyses suggest that these genetically discordant sectors are very small but can have a complex genetic makeup. In ruling out more trivial explanations for these data, our findings raise the possibility that intrinsic drivers of genetic variation are responsible for the targeted sequence changes we detect. Given the evolutionary advantage afforded to populations with greater genetic diversity, we hypothesize that organisms that primarily self-fertilize or propagate clonally counteract the genetic cost of such reproductive strategies by leveraging a cryptic reserve of extra-genomic information.

Identifiers

PMID24555023
PMCPMC3894806

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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.