Evidence map›Paper›PMID 19654263›Full record

ReviewThe Plant cell2009

Association mapping: critical considerations shift from genotyping to experimental design.

Sean Myles, Jason Peiffer, Patrick J Brown, Elhan S Ersoz, Zhiwu Zhang, Denise E Costich, Edward S Buckler

Abstract readReview
In one paragraph

Review in The Plant cell, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 366 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
366citing papers in PubMed, 1 pooled it
–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

366 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Meta genetic analysis of melon sweetness.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025
    Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Targeted expansion of a barley genebank core collection facilitates the discovery of disease resistance loci.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026
    Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article

306 more citing papers are in PubMed but not listed here.

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.

Sean MylesInstitute for Genomic Diversity, Cornell University, Ithaca, New York 14853-2703, USA. smm367@cornell.edu
Jason Peiffer
Patrick J Brown
Elhan S Ersoz
Zhiwu Zhang
Denise E Costich
Edward S Buckler

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The goal of many plant scientists' research is to explain natural phenotypic variation in terms of simple changes in DNA sequence. Traditionally, linkage mapping has been the most commonly employed method to reach this goal: experimental crosses are made to generate a family with known relatedness, and attempts are made to identify cosegregation of genetic markers and phenotypes within this family. In vertebrate systems, association mapping (also known as linkage disequilibrium mapping) is increasingly being adopted as the mapping method of choice. Association mapping involves searching for genotype-phenotype correlations in unrelated individuals and often is more rapid and cost-effective than traditional linkage mapping. We emphasize here that linkage and association mapping are complementary approaches and are more similar than is often assumed. Unlike in vertebrates, where controlled crosses can be expensive or impossible (e.g., in humans), the plant scientific community can exploit the advantages of both controlled crosses and association mapping to increase statistical power and mapping resolution. While the time and money required for the collection of genotype data were critical considerations in the past, the increasing availability of inexpensive DNA sequencing and genotyping methods should prompt researchers to shift their attention to experimental design. This review provides thoughts on finding the optimal experimental mix of association mapping using unrelated individuals and controlled crosses to identify the genes underlying phenotypic variation.

Indexed as

Research DesignAnimalsChromosome MappingGenotypeHumansPhenotype

Identifiers

PMID19654263
PMCPMC2751942

What OpenQuestion holds

Textmetadata
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.