Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 1,540

The DOI matches its Crossref record.

Optimizing parental selection for genetic linkage maps

Anderson, J. A., Churchill, G. A., Autrique, J. E., Tanksley, S. D., Sorrells, M. E.·1993·Genome

Abstract

Genetic linkage maps based on restriction fragment length polymorphisms are useful for many purposes; however, different populations are required to fulfill different objectives. Clones from the linkage map(s) are subsequently probed onto populations developed for special purposes such as gene tagging. Therefore, clones contained on the initial map(s) must be polymorphic on a wide range of genotypes to have maximum utility. The objectives of this research were to (i) calculate polymorphism information content values of 51 low-copy DNA clones and (ii) use the resulting values to choose potential mapping parents. Polymorphism information content was calculated using gene diversity by classifying restriction fragment patterns on a diverse set of 18 wheat genotypes. Combinations of potential parents were then compared by examining both the proportion of polymorphic clones and the likelihood that those mapped clones would give a polymorphism when used on other populations. Genotype pairs were identified that would map more highly informative DNA clones compared with a population derived from the most polymorphic potential parents. The methodologies used to characterize clones and rank potential parents should be applicable to other species and types of markers as well.Key words: restriction fragment length polymorphism, mapping, Triticum aestivum.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1139/g93-024

Cites

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cited by

See all 1,540

Metadata

Authors
Anderson, J. A., Churchill, G. A., Autrique, J. E., Tanksley, S. D., & Sorrells, M. E.
Venue
Genome
Published
1993-02-01
Volume
36
Issue
1
Pages
181-186
ISSN
  • 0831-2796 (ISSN-L)
  • 1480-3321
OpenAlex
W2104043339
Cited by
1,540
References
0
FWCI
3.87
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Optimizing parental selection for genetic linkage maps. https://app.cochat.ai/papers/10.1139/g93-024
The paper
Anderson, J. A., Churchill, G. A., Autrique, J. E., Tanksley, S. D., & Sorrells, M. E. (1993). Optimizing parental selection for genetic linkage maps. Genome. https://doi.org/10.1139/g93-024

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.