Sources of resistance in bread wheat to Russian wheat aphid (<i>Diuraphis noxia</i>) in Syria identified using the Focused Identification of Germplasm Strategy (FIGS)

Bouhssini, Mustapha El; Street, Kenneth; Amri, Ahmed; Mackay, Michael; Ogbonnaya, Francis C.; Omran, A. F.; Abdalla, O.; Baum, Michaël; Dabbous, A.; Rihawi, F.

doi:10.1111/j.1439-0523.2010.01814.x

Cited by 92 publications

(43 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Wheat germplasm collected from regions where RWA is endemic provides fundamental materials for genetic improvement of RWA resistance to help ensure food security for the world's rapidly growing population (El Bouhssini et al, 2011). Advances in translational genomics have highlighted the need of homogeneous resistance sources for gene mapping, gene cloning, and molecular breeding.…”

Section: Resultsmentioning

confidence: 99%

Evaluation and Reselection of Wheat Resistance to Russian Wheat Aphid Biotype 2

Xu¹,

Bai

Carver

et al. 2015

Crop Science

View full text Add to dashboard Cite

Russian wheat aphid (RWA, Diuraphis noxia, Mordvilko) biotype 2 (RWA2) is virulent to most known RWA resistance genes and severely threatens wheat (Triticum aestivum L.) production in the hard winter wheat area of the U.S. western Great Plains. We determined RWA2 reactions of 386 cultivars from China, 227 advanced breeding lines and recently released cultivars from the United States, 505 landraces from countries where RWA is endemic, and 31 genetic stocks developed in the United States, Australia, Canada, and Russia. The majority of wheat accessions from China and the United States were highly susceptible to RWA2. Only nine landrace accessions produced a homogeneous resistant reaction. In addition, highly resistant plants were identified in 28 heterogeneous landraces. Thus, reselection was conducted to purify some potential resistance sources, and the single‐plant progenies of 220 selected plants were evaluated. Homogeneous resistant or highly resistant lines were identified from seven previously heterogeneous landraces. Reselection line PI 626759‐20‐32 offered a high level of resistance similar to lines carrying Dn7, the rye (Secale cereale L.)‐derived resistance gene associated with undesirable bread‐making quality. PI 626759‐20‐32 has the potential to supplement or replace Dn7 as a new RWA2 resistance source in wheat breeding.

show abstract

Section: Resultsmentioning

confidence: 99%

Evaluation and Reselection of Wheat Resistance to Russian Wheat Aphid Biotype 2

Xu¹,

Bai

Carver

et al. 2015

Crop Science

View full text Add to dashboard Cite

show abstract

“…[38], Russian wheat aphid ( Diuraphis noxia Kurdj.) [39] and stem rust ( Puccinia graminis Pers.) [34], [35] as well as net blotch ( Pyrenophora teres Drechs.)…”

Section: Introductionmentioning

confidence: 99%

The FIGS (Focused Identification of Germplasm Strategy) Approach Identifies Traits Related to Drought Adaptation in Vicia faba Genetic Resources

et al. 2013

View full text Add to dashboard Cite

Efficient methods to explore plant agro-biodiversity for climate change adaptive traits are urgently required. The focused identification of germplasm strategy (FIGS) is one such approach. FIGS works on the premise that germplasm is likely to reflect the selection pressures of the environment in which it developed. Environmental parameters describing plant germplasm collection sites are used as selection criteria to improve the probability of uncovering useful variation. This study was designed to test the effectiveness of FIGS to search a large faba bean (Vicia faba L.) collection for traits related to drought adaptation. Two sets of faba bean accessions were created, one from moisture-limited environments, and the other from wetter sites. The two sets were grown under well watered conditions and leaf morpho-physiological traits related to plant water use were measured. Machine-learning algorithms split the accessions into two groups based on the evaluation data and the groups created by this process were compared to the original climate-based FIGS sets. The sets defined by trait data were in almost perfect agreement to the FIGS sets, demonstrating that ecotypic differentiation driven by moisture availability has occurred within the faba bean genepool. Leaflet and canopy temperature as well as relative water content contributed more than other traits to the discrimination between sets, indicating that their utility as drought-tolerance selection criteria for faba bean germplasm. This study supports the assertion that FIGS could be an effective tool to enhance the discovery of new genes for abiotic stress adaptation.

show abstract

“…The FIGS approach assumes a predictive link between some eco‐geographic parameters of the original collecting site of germplasm (with focus on landraces and crop wild relatives) and a target adaptive trait, such as disease resistance. Recent studies have proposed the algorithms and methods for implementation of trait mining using FIGS (El Bouhssini et al, 2009, 2011; Endresen, 2010; Endresen et al, 2011; Bari et al, 2011). Zeven (1998) presented a review of definitions and classifications for landraces and suggested the definition provided by Mansholt (1909), which reads, “an autochthonous landrace is a variety with a high capacity to tolerate biotic and abiotic stress, resulting in a high yield stability and an intermediate yield level under a low input agricultural system” (Zeven 1998, 137).…”

mentioning

confidence: 99%

“…The rationale or fundamental theory for trait mining using FIGS is that crop traits are linked to the eco‐climatic environment associated with the collecting site of accessions and that this link can be exploited to build predictive models to identify a subset of accessions with a higher likelihood of holding a target trait property (Mackay and Street, 2004). The first studies to validate the FIGS approach were conducted using a heuristic approach in which expert knowledge from the scientific literature was used to identify the boundaries for each of the eco‐climatic variables (Street et al, 2008; Bhullar et al, 2009; El Bouhssini et al, 2009, 2011). Other studies were designed to calibrate a predictive computer model to validate the FIGS approach (Endresen, 2010; Endresen et al, 2011).…”

mentioning

confidence: 99%

Sources of Resistance to Stem Rust (Ug99) in Bread Wheat and Durum Wheat Identified Using Focused Identification of Germplasm Strategy

et al. 2012

View full text Add to dashboard Cite

The focused identification of germplasm strategy (FIGS) has been validated using predictive computer models in simulation studies to predict a priori known trait soores. This study was designed as a "blind" study where the person calculating the computer model did not know the actual trait scores. This study design provides a more realistic test of the predictive capacity of the FIGS approach compared to previous studies. Furthermore this study also explored the suitability of FIGS for the identification of resistance in bread wheat {Triticum aestivum L. subsp. aestivum) and durum wheat [Triticum turgidum L. subsp. durum (Desf.) Husn.] to Ug99-a strain of stem rust {Puccinia graminis Pers. f. sp. tritici Eriks. & Henn.) and typified to race TTKSK. The predictions were validated against a dataset with the screening of wheat accessions conducted in Yemen in 2008. Only a small training set representing 20% of the trait soreening results was disclosed to the person conducting the data analysis for the calibration of the prediction model. The hit rate for identification of Ug99-resistant accessions was more than two times higher when using the FIGS approach compared to a random selection of accessions. These results suggested that FIGS was well suited for the identification of samples with resistance to fungal pathogens. It is therefore recommended that FIGS approach be used as a complement to expert knowledge and experience when selecting accessions for plant breeding and crop research activities.

show abstract

Sources of resistance in bread wheat to Russian wheat aphid (Diuraphis noxia) in Syria identified using the Focused Identification of Germplasm Strategy (FIGS)

Cited by 92 publications

References 9 publications

Evaluation and Reselection of Wheat Resistance to Russian Wheat Aphid Biotype 2

Evaluation and Reselection of Wheat Resistance to Russian Wheat Aphid Biotype 2

The FIGS (Focused Identification of Germplasm Strategy) Approach Identifies Traits Related to Drought Adaptation in Vicia faba Genetic Resources

Sources of Resistance to Stem Rust (Ug99) in Bread Wheat and Durum Wheat Identified Using Focused Identification of Germplasm Strategy

Contact Info

Product

Resources

About