Evidence map›Paper›PMID 24634730›Full record

ArticleEcology and evolution2014

The effects of locus number, genetic divergence, and genotyping error on the utility of dominant markers for hybrid identification.

Michael G Sovic, Laura S Kubatko, Paul A Fuerst

Abstract read
In one paragraph

Article in Ecology and evolution, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Constructing a linkage-linkage disequilibrium map using dominant-segregating markers.DNA research : an international journal for rapid publication of reports on genes and genomes · 2016
    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

3 authors.

Michael G SovicDepartment of Evolution, Ecology, and Organismal Biology, 314 Aronoff Laboratory, The Ohio State University 318 W. 12th Ave, Columbus, Ohio, 43210.
Laura S KubatkoDepartments of Statistics and Evolution, Ecology, and Organismal Biology, The Ohio State University 404 Cockins Hall, 1958 Neil Ave., Columbus, Ohio, 43210.
Paul A FuerstDepartment of Evolution, Ecology, and Organismal Biology, 386 Aronoff Laboratory, The Ohio State University 318 W. 12th Ave, Columbus, Ohio, 43210.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In surveys of hybrid zones, dominant genetic markers are often used to identify individuals of hybrid origin and assign these individuals to one of several potential hybrid classes. Quantitative analyses that address the statistical power of dominant markers in such inference are scarce. In this study, dominant genotype data were simulated to evaluate the effects of, first, the number of loci analyzed, second, the magnitude of differentiation between the markers scored in the groups that are hybridizing, and third, the level of genotyping error associated with the data when assigning individuals to various parental and hybrid categories. The overall performance of the assignment methods was relatively modest at the lowest level of divergence examined (F st ˜ 0.4), but improved substantially at higher levels of differentiation (F st ˜ 0.67 or 0.8). The effect of genotyping error was dependent on the level of divergence between parental taxa, with larger divergences tempering the effects of genotyping error. These results highlight the importance of considering the effects of each of the variables when assigning individuals to various parental and hybrid categories, and can help guide decisions regarding the number of loci employed in future hybridization studies to achieve the power and level of resolution desired.

Indexed as

AFLPDominant MarkersGenotyping ErrorHybridizationRAPDSimulation

Identifiers

PMID24634730
PMCPMC3936392

What OpenQuestion holds

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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.