Evidence map›Paper›PMID 23793550›Full record

ArticleTAG. Theoretical and applied genetics. Theoretische und angewandte Genetik2013

Usefulness of 10 genomic regions in soybean associated with sudden death syndrome resistance.

A S Luckew, L F Leandro, M K Bhattacharyya, D J Nordman, D A Lightfoot, S R Cianzio

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Article in TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

13 citing papers in PubMed.

  1. Article
  2. Breeding for disease resistance in soybean: a global perspective.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2022
    Review
  3. Article
  4. Article
  5. Different loci associated with root and foliar resistance to sudden death syndrome (Fusarium virguliforme) in soybean.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2019
    Article
  6. Article
  7. Field evaluation of three sources of genetic resistance to sudden death syndrome of soybean.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2018
    Article
  8. Integration of sudden death syndrome resistance loci in the soybean genome.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2018
    Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
4 · The record

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5 · Who and what money

Authors and funding

6 authors.

A S LuckewDepartment of Agronomy, Iowa State University, Ames, IA, USA.
L F Leandro
M K Bhattacharyya
D J Nordman
D A Lightfoot
S R Cianzio

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Sudden death syndrome (SDS) is an important soybean [Glycine max (L) Merrill] disease caused by the soilborne fungus Fusarium virguliforme. Currently, 14 quantitative trait loci (QTL) had been confirmed associated with resistance or tolerance to SDS. The objective of the study was to evaluate usefulness of 10 of these QTL in controlling disease expression. Six populations were developed providing a total of 321 F2-derived lines for the study. Recombinant inbred lines (RIL) used as parents were obtained from populations of 'Essex' × 'Forrest' (EF), 'Flyer' × 'Hartwig' (FH), and 'Pyramid' × 'Douglas' (PD). Disease resistance was evaluated in the greenhouse at three different planting times, each with four replications, using sorghum infested with F. virguliforme homogeneously mixed in the soil (Luckew et al., Crop Sci 52:2215-2223, 2012). Four disease assessment criteria-foliar disease incidence (DI), foliar leaf scorch disease severity (DS), area under the disease progress curve (AUDPC), and root rot severity-were used. QTL were identified in more than one of the disease assessment criteria, mainly associated with lines in the most resistant categories. Five QTL (qRfs4, qRfs5, qRfs7, qRfs12, and Rfs16) were associated with at least one of the disease assessments across multiple populations. Of the five, qRfs4 was associated with DI, AUDPC, and root rot severity, and Rfs16 with AUDPC and root rot severity. The findings suggest it may be possible for plant breeders to focus on stacking a subset of the previously identified QTL to improve resistance to SDS in soybean.

Indexed as

Quantitative Trait LociDisease ResistanceDNA, PlantFusariumGenetic LinkageGenetic MarkersGenomicsGlycine maxPlant DiseasesPlant LeavesPlant RootsDNA, PlantGenetic Markers

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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.