Evidence map›Paper›PMID 18510771›Full record

ArticlePlant methods2008

Development and evaluation of a high-throughput, low-cost genotyping platform based on oligonucleotide microarrays in rice.

Jeremy D Edwards, Jaroslav Janda, Megan T Sweeney, Ambika B Gaikwad, Bin Liu, Hei Leung, David W Galbraith

Open access · goldAbstract read
In one paragraph

Article in Plant methods, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
2.5field-weighted citation impact, top 11% of its field
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

10 citing papers in PubMed, 40 citations in OpenAlex.

  1. Article
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  5. Dissecting quantitative resistance against blast disease using heterogeneous inbred family lines in rice.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2011
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors at 5 institutions in 4 countries.

Jeremy D EdwardsUniversity of Florida, Gulf Coast Research & Education Center, Wimauma FL, 33598, USA. edwardsjd@ufl.edu.
Jaroslav Janda
Megan T Sweeney
Ambika B Gaikwad
Bin Liu
Hei Leung
David W Galbraith
University of Arizona · USGuangdong Academy of Agricultural Sciences · CNInternational Rice Research Institute · PHNational Bureau of Plant Genetic Resources · INUniversity of Florida · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWe report the development of a microarray platform for rapid and cost-effective genetic mapping, and its evaluation using rice as a model. In contrast to methods employing whole-genome tiling microarrays for genotyping, our method is based on low-cost spotted microarray production, focusing only on known polymorphic features.

resultsWe have produced a genotyping microarray for rice, comprising 880 single feature polymorphism (SFP) elements derived from insertions/deletions identified by aligning genomic sequences of the japonica cultivar Nipponbare and the indica cultivar 93-11. The SFPs were experimentally verified by hybridization with labeled genomic DNA prepared from the two cultivars. Using the genotyping microarrays, we found high levels of polymorphism across diverse rice accessions, and were able to classify all five subpopulations of rice with high bootstrap support. The microarrays were used for mapping of a gene conferring resistance to Magnaporthe grisea, the causative organism of rice blast disease, by quantitative genotyping of samples from a recombinant inbred line population pooled by phenotype.

conclusionWe anticipate this microarray-based genotyping platform, based on its low cost-per-sample, to be particularly useful in applications requiring whole-genome molecular marker coverage across large numbers of individuals.

Identifiers

PMID18510771
PMCPMC2435114
OpenAlexW2086105398

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LicenceCC BY
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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.