Potential of Association Mapping and Genomic Selection to Explore PI 88788 Derived Soybean Cyst Nematode Resistance

Bao, Yong; Vuong, Tri D.; Meinhardt, Clinton G.; Tiffin, Peter; Denny, Roxanne; Chen, Senyu; Nguyen, Henry T.; Orf, J. H.; Young, Nevin D.

doi:10.3835/plantgenome2013.11.0039

Cited by 74 publications

(96 citation statements)

References 67 publications

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“…Locus no. 7 (Gm18-5112839) was not only within the previously reported interval (Winter et al 2007) but also 4 Mb away form an SNP marker (BARC-019001-03050) tagging a previously described locus associated with resistance to SCN HG type 0 (Bao et al 2014). Apart from these overlaps, our GWAS identified 3 novel QTL, including QTL on Chr.…”

Section: Analysis Of Phenotypic Variationmentioning

confidence: 58%

“…Recent genomewide association study (GWAS) on 282 accessions of soybean breeding lines have detected significant signals at two loci corresponding to rhg1 and FGAM1, plus a third locus located at the end (55.9 Mb) of Chr. 18 underlying resistance to SCN HG type 0 (Bao et al 2014). By using a data set of 55,159 SNPs across 440 diverse soybean landraces and elite cultivars, Han et al (2015) also identified 19 association loci significantly related to the resistance for two SCN HG types.…”

Section: Introductionmentioning

confidence: 97%

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Genome-wide association study for soybean cyst nematode resistance in Chinese elite soybean cultivars

Zhang

et al. 2017

Mol Breeding

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Soybean cyst nematode (SCN) (Heterodera glycines Ichinohe) is a highly recalcitrant endoparasite of soybean roots, causing more yield loss than any other pest. To identify quantitative trait loci (QTL) controlling resistance to SCN (HG type 2.5.7, race 1), a genomewide association study (GWAS) was performed. The association panel, consisting of 120 Chinese soybean cultivars, was genotyped with 7189 single nucleotide polymorphism (SNPs). A total of 6204 SNPs with minor allele frequency >0.05 were used to estimate linkage disequilibrium (LD) and population structure. The mean level of LD measured by r 2 declined very rapidly to half its maximum value (0.51) at 220 kb. The overall population structure was approximately coincident with geographic origin. The GWAS results identified 13 SNPs in 7 different genomic regions significantly associated with SCN resistance. Of these, three SNPs were localized in previously mapped QTL intervals, including rhg1 and Rhg4. The GWAS results also detected 10 SNPs in 5 different genomic regions associated with SCN resistance. The identified loci explained an average of 95.5% of the phenotypic variance. The proportion of phenotypic variance was due to additive genetic variance of the validated SNPs. The present study identified multiple new loci and refined chromosomal regions of known loci associated with SCN resistance. The loci and trait-associated SNPs identified in this study can be used for developing soybean cultivars with durable resistance against SCN.

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Section: Analysis Of Phenotypic Variationmentioning

confidence: 58%

Section: Introductionmentioning

confidence: 97%

Genome-wide association study for soybean cyst nematode resistance in Chinese elite soybean cultivars

Zhang

et al. 2017

Mol Breeding

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“…The potential and limits of genome-wide predictions have been examined for several major crops, such as barley [33], wheat [15, 34–36], maize [37–42], rice [43], sunflower [44], forage plants [45], sugar beet [46, 47], and soybean [48, 49]. The results underlined the potential of genome-wide prediction as a powerful tool to accelerate selection gain in plant breeding.…”

Section: Introductionmentioning

confidence: 99%

Seed Quality Traits Can Be Predicted with High Accuracy in Brassica napus Using Genomic Data

et al. 2016

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Improving seed oil yield and quality are central targets in rapeseed (Brassica napus) breeding. The primary goal of our study was to examine and compare the potential and the limits of marker-assisted selection and genome-wide prediction of six important seed quality traits of B. napus. Our study is based on a bi-parental population comprising 202 doubled haploid lines and a diverse validation set including 117 B. napus inbred lines derived from interspecific crosses between B. rapa and B. carinata. We used phenotypic data for seed oil, protein, erucic acid, linolenic acid, stearic acid, and glucosinolate content. All lines were genotyped with a 60k SNP array. We performed five-fold cross-validations in combination with linkage mapping and four genome-wide prediction approaches in the bi-parental population. Quantitative trait loci (QTL) with large effects were detected for erucic acid, stearic acid, and glucosinolate content, blazing the trail for marker-assisted selection. Despite substantial differences in the complexity of the genetic architecture of the six traits, genome-wide prediction models had only minor impacts on the prediction accuracies. We evaluated the effects of training population size, marker density and phenotyping intensity on the prediction accuracy. The prediction accuracy in the independent and genetically very distinct validation set still amounted to 0.14 for protein content and 0.17 for oil content reflecting the utility of the developed calibration models even in very diverse backgrounds.

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“…The combination of predictive modeling with SNP data could also reduce the time needed to stack multiple resistance QTLs into elite cultivars and to select for these QTLs in breeding programs (Bao et al, 2014;Shi et al, 2015). High-throughput genotyping platforms could identify new alleles and genes that can be stacked using MAS to create cultivars with broad-based resistance to SCN.…”

Section: Discussionmentioning

confidence: 99%

Pyramiding of Alleles from Multiple Sources Increases the Resistance of Soybean to Highly Virulent Soybean Cyst Nematode Isolates

Brzostowski

Diers

2017

Crop Science

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Soybean cyst nematode (SCN) (Heterodera glycines Ichinohe) is estimated to be the pathogen that causes the greatest economic loss to soybean [Glycine max (L.) Merr.] in the United States. Genetic resistance is an effective way to manage SCN. Resistance sources have been identified, and quantitative trait loci (QTLs) conferring resistance from these sources have been mapped. However, there is a need to diversify SCN resistance genes in cultivars, as most grown in the northern United States have resistance tracing only to the source PI 88788. The objective of this study was to determine the effectiveness of combinations of SCN resistance alleles from different sources in two populations formed via backcrossing. Population 1 segregates for a resistance QTL from both PI 567516C and PI 88788, whereas Population 2 segregates for the same QTL as Population 1 and two QTLs from PI 468916. Lines from both populations were evaluated with two virulent nematode isolates. Furthermore, a subset of lines from Population 2 (Population 2 Subset) was evaluated with two additional nematode isolates. The SCN resistance alleles from each source significantly increased SCN resistance compared with the alternative alleles. The effect of resistance alleles varied depending on SCN isolate and population, and there was generally an increase in resistance as more resistance alleles were stacked together. These results indicate that stacking multiple sources of resistance can be an effective means to increase broad‐spectrum SCN resistance.

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Potential of Association Mapping and Genomic Selection to Explore PI 88788 Derived Soybean Cyst Nematode Resistance

Cited by 74 publications

References 67 publications

Genome-wide association study for soybean cyst nematode resistance in Chinese elite soybean cultivars

Genome-wide association study for soybean cyst nematode resistance in Chinese elite soybean cultivars

Seed Quality Traits Can Be Predicted with High Accuracy in Brassica napus Using Genomic Data

Pyramiding of Alleles from Multiple Sources Increases the Resistance of Soybean to Highly Virulent Soybean Cyst Nematode Isolates

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