Imputation accuracy of wheat genotyping-by-sequencing (GBS) data using barley and wheat genome references

Alipour, Hadi; Bai, Guihua; Zhang, Guorong; Bihamta, Mohammad Reza; Mohammadi, Valiollah; Peyghambari, S A

doi:10.1371/journal.pone.0208614

Cited by 51 publications

(44 citation statements)

References 68 publications

(76 reference statements)

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“…Dubcovsky and Dvorak (2007) reported the hexaploid wheat was found to have a larger portion of the natural gene diversity from its tetraploid ancestor (AABB) than the diversity found in the Aegilops tauschii (DD). Similarly, the identification of a relatively higher frequency of SNPs showing transition substitutions (62.3%) than transversions is consistent with previous genome-wide SNP discovery studies in crop plants, including wheat (Parida et al, 2012;Lai et al, 2015;Rimbert et al, 2018;Alipour et al, 2019). The present study showed that the GBS-derived SNPs hold potential variation among genomes, which has to be explored further by analyzing the genomic variation of Triticum genotypes.…”

Section: Genotyping Assaysupporting

confidence: 91%

“…(Wong et al, 2015;Edet et al, 2018). Various studies reported the impact of missing datasets on phylogenetic analyses (Philippe et al, 2004;Xi et al, 2015) and concluded that the missing data can be addressed with a statistical method (Alipour et al, 2019;Schurz et al, 2019). Therefore, to explore further the utility of missing SNP datasets on phylogenetic analysis, we employed missing rates of 20, 50, and 80%, which revealed that decreasing the missing rates leads to reduction of SNPs.…”

Section: Genotyping Assaymentioning

confidence: 99%

“…Though the T. timopheevii and T. zhukovskyi accessions formed an individual (cluster 5) cluster representing their genomic differences from other species, the present study has some limitation owing to lack of complete genomic information of the G genome. As sequence read alignment to the reference genome is a fundamental step in genomic studies (Alipour et al, 2019), unavailability of the reference genome may hinder the accuracy of biological data. Hence, further studies need to be conducted on these species once the reference genome is made available for the G genome.…”

Section: Population Genomic Differentiationmentioning

confidence: 99%

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Genotyping-by-Sequencing Derived Single Nucleotide Polymorphisms Provide the First Well-Resolved Phylogeny for the Genus Triticum (Poaceae)

et al. 2020

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Wheat (Triticum spp.) has been an important staple food crop for mankind since the beginning of agriculture. The genus Triticum L. is composed of diploid, tetraploid, and hexaploid species, majority of which have not yet been discriminated clearly, and hence their phylogeny and classification remain unresolved. Genotyping-by-sequencing (GBS) is an easy and affordable method that allows us to generate genome-wide single nucleotide polymorphism (SNP) markers. In this study, we used GBS to obtain SNPs covering all seven chromosomes from 283 accessions of Triticum-related genera. After filtering low-quality and redundant SNPs based on haplotype information, the GBS assay provided 14,188 high-quality SNPs that were distributed across the A (71%), B (26%), and D (2.4%) genomes. Cluster analysis and discriminant analysis of principal components (DAPC) allowed us to distinguish six distinct groups that matched well with Triticum species complexity. We constructed a Bayesian phylogenetic tree using 14,188 SNPs, in which 17 Triticum species and subspecies were discriminated. Dendrogram analysis revealed that the polyploid wheat species could be divided into groups according to the presence of A, B, D, and G genomes with strong nodal support and provided new insight into the evolution of spelt wheat. A total of 2,692 speciesspecific SNPs were identified to discriminate the common (T. aestivum) and durum (T. turgidum) wheat cultivar and landraces. In principal component analysis grouping, the two wheat species formed individual clusters and the SNPs were able to distinguish up to nine groups of 10 subspecies. This study demonstrated that GBS-derived SNPs could be used efficiently in genebank management to classify Triticum species and subspecies that are very difficult to distinguish by their morphological characters.

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Section: Genotyping Assaysupporting

confidence: 91%

Section: Genotyping Assaymentioning

confidence: 99%

Section: Population Genomic Differentiationmentioning

confidence: 99%

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Genotyping-by-Sequencing Derived Single Nucleotide Polymorphisms Provide the First Well-Resolved Phylogeny for the Genus Triticum (Poaceae)

et al. 2020

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“…We used the genotyping-by-sequencing (GBS) [ 32 ] method for genetic fingerprinting and Poland et al [ 33 ] method for library construction. The genotyping method has been described for the association panel, previously [ 34 , 35 ]. Briefly, DNA was extracted by a modified cetyltrimethylammonium bromide (CTAB) method [ 36 ] and double-digested with PstI and MspI restriction enzymes, barcoded adapters were ligated to each DNA sample using T4 ligase, polymerase chain reactions (PCRs) were done using primers complementary to both adaptors, size-selection for 250–300 bp fragments was conducted using an E-gel system (Life Technologies, Inc.), and the size-selected library was sequenced on an Ion Proton sequencer (Life Technologies, Inc.).…”

Section: Methodsmentioning

confidence: 99%

A simple, cost-effective high-throughput image analysis pipeline improves genomic prediction accuracy for days to maturity in wheat

et al. 2020

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Background High-throughput phenotyping and genomic selection accelerate genetic gain in breeding programs by advances in phenotyping and genotyping methods. This study developed a simple, cost-effective high-throughput image analysis pipeline to quantify digital images taken in a panel of 286 Iran bread wheat accessions under terminal drought stress and well-watered conditions. The color proportion of green to yellow (tolerance ratio) and the color proportion of yellow to green (stress ratio) was assessed for each canopy using the pipeline. The estimated tolerance and stress ratios were used as covariates in the genomic prediction models to evaluate the effect of change in canopy color on the improvement of the genomic prediction accuracy of different agronomic traits in wheat. Results The reliability of the high-throughput image analysis pipeline was proved by three to four times of improvement in the accuracy of genomic predictions for days to maturity with the use of tolerance and stress ratios as covariates in the univariate genomic selection models. The higher prediction accuracies were attained for days to maturity when both tolerance and stress ratios were used as fixed effects in the univariate models. The results of this study indicated that the Bayesian ridge regression and ridge regression-best linear unbiased prediction methods were superior to other genomic prediction methods which were used in this study under terminal drought stress and well-watered conditions, respectively. Conclusions This study provided a robust, quick, and cost-effective machine learning-enabled image-phenotyping pipeline to improve the genomic prediction accuracy for days to maturity in wheat. The results encouraged the integration of phenomics and genomics in breeding programs.

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“…After specifying the haplotype phase for all individuals, the data was subjected to imputation using BEAGLE v3.3.2 [71] based on available allele frequencies obtained. During imputation, four different reference genomes were assessed that among them W7984 reference genome was shown to have the greatest imputation accuracy [72]. The different chromosomes LD decay was obtained using the ggplot2 package in RStudio [73] based on LOESS regression.…”

Section: Genotyping By Sequencing and Imputation Methodsmentioning

confidence: 99%

Association mapping of Iranian wheat genotypes to detect QTLs conferring resistance to stem rust at seedling stage

Saremirad¹,

Bihamta²,

Malihipour³

et al. 2020

Preprint

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Background Stem rust caused by Puccinia graminis f. sp. tritici (Pgt) is an important disease of wheat in the world. Pgt pathogen is constantly evolving and creating more virulent races that break down stem rust (Sr) resistance genes. As a result, many of Sr genes have become ineffective against new Pgt races. Exploring new sources of resistance to detect new Sr genes/QTLs is very important in order to introducing them into wheat breeding programs and developing resistant wheat cultivars. The objective of the present study was to evaluate 297 Iranian wheat genotypes for resistance to stem rust at seedling stage and to detect Sr resistance genes/QTLs through association mapping (AM). Results A set of 297 Iran bread wheat cultivars and landraces were evaluated for infection type and latent period in four race of Pgt. Genotypic data of 282 genotypes were available, so AM was performed based on 282 genotypes. The results of population structure analysis showed that 277 genotypes clearly were distinguished in the three subpopulations and the other five genotypes were classified in the mixed group. The mean linkage disequilibrium decreased with increasing genetic distance. The markers did not have a uniform distribution on the genomes, so the share of each of the A, B and D genomes in commercial cultivars and landraces was approximately 37, 46 and 17%, respectively. Collectively, 69 QTLs for infection type and 62 QTLs for latent period of studied Pgt races were identified in the original dataset (P ≤ 0.001). In the imputed SNPs dataset, the number of QTLs for infection type increased to 504 QTL and for latent period increased to 454 QTLs (P ≤ 0.001). Conclusion Based on the results of this study, it can be concluded that the Iranian wheat genotypes are valuable source resistance to stem rust. By incorporating these genotypes into wheat breeding programs and optimizing effective resistance genes, an important step can be taken to prevent the threat of and the disease to ensure food security. This study provides additional useful information for selection of resistant genotypes against the disease by improving marker-assisted selection efficiency.

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Imputation accuracy of wheat genotyping-by-sequencing (GBS) data using barley and wheat genome references

Cited by 51 publications

References 68 publications

Genotyping-by-Sequencing Derived Single Nucleotide Polymorphisms Provide the First Well-Resolved Phylogeny for the Genus Triticum (Poaceae)

Genotyping-by-Sequencing Derived Single Nucleotide Polymorphisms Provide the First Well-Resolved Phylogeny for the Genus Triticum (Poaceae)

A simple, cost-effective high-throughput image analysis pipeline improves genomic prediction accuracy for days to maturity in wheat

Association mapping of Iranian wheat genotypes to detect QTLs conferring resistance to stem rust at seedling stage

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