EST derived SSR markers for comparative mapping in wheat and rice

Yu, Jiangyan; Rota, Mauricio La; Kantety, Ramesh V.; Sorrells, Mark E.

doi:10.1007/s00438-004-1027-3

Cited by 163 publications

(108 citation statements)

References 59 publications

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“…The rate of polymorphic sites was about the same as reported by Torada et al (2006). The same EST-SSR sites frequently exist among closely related plant species and have been used as a tool for comparative genomics (Rudd et al 2003, Gao et al 2004, Yu et al 2004. However, our results show that functional wheat-specific markers can be developed from EST information.…”

Section: Wheat Cultivar Identification In Four Processed Foodssupporting

confidence: 81%

Identification of wheat cultivars using EST-SSR markers

Fujita

Fukuoka²,

Yano

2009

Breed. Sci.

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The recent amendment of the Plant Variety Protection Law in Japan has extended plant breeders' rights to cover the harvested materials and manufactured products from a cultivar. The Government Quality Labeling Standards require proper food labeling, which includes cultivar names if they appear on the product label. To protect the breeder's right and ensure the proper labeling of wheat products, we have developed simple sequence repeat (SSR) markers from wheat expressed sequence tags (ESTs) to identify the wheat cultivars used in wheat products. From a total of 3,759 SSR sites found in the EST data base, PCR amplification was tested at 186 sites in 14 wheat cultivars. We also confirmed that the markers did not occur in other crops, and so can accurately identify wheat cultivars used in products blended with these crops. A total of 10 SSR sites were finally selected and their capacity to identify 41 Japanese cultivars and 17 USA, Australian, or Canadian cultivars was examined. These SSR markers are sufficient to distinguish the Japanese cultivars from foreign cultivars and to individually identify the major Japanese cultivars, such as Hokushin and Norin 61. The SSR markers can also determine the wheat cultivars used in processed foods.

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Section: Wheat Cultivar Identification In Four Processed Foodssupporting

confidence: 81%

Identification of wheat cultivars using EST-SSR markers

Fujita

Fukuoka²,

Yano

2009

Breed. Sci.

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“…A total of 93 SSR loci were detected by 88 markers, including 31 BARC (Song et al 2005), 30 WMS (Rö der et al 1998), 18 WMC (Gupta et al 2002), 8 CFA/CFD markers (Guyomarc'h et al 2002, and the EST-SSR KSUM244 (Yu et al 2004). Alleles were identified as A#, where # indicates the approximate fragment size.…”

Section: Methodsmentioning

confidence: 99%

Association Mapping of Kernel Size and Milling Quality in Wheat (Triticum aestivum L.) Cultivars

2006

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Association mapping is a method for detection of gene effects based on linkage disequilibrium (LD) that complements QTL analysis in the development of tools for molecular plant breeding. In this study, association mapping was performed on a selected sample of 95 cultivars of soft winter wheat. Population structure was estimated on the basis of 36 unlinked simple-sequence repeat (SSR) markers. The extent of LD was estimated on chromosomes 2D and part of 5A, relative to the LD observed among unlinked markers. Consistent LD on chromosome 2D was ,1 cM, whereas in the centromeric region of 5A, LD extended for 5 cM. Association of 62 SSR loci on chromosomes 2D, 5A, and 5B with kernel morphology and milling quality was analyzed through a mixed-effects model, where subpopulation was considered as a random factor and the marker tested was considered as a fixed factor. Permutations were used to adjust the threshold of significance for multiple testing within chromosomes. In agreement with previous QTL analysis, significant markers for kernel size were detected on the three chromosomes tested, and alleles potentially useful for selection were identified. Our results demonstrated that association mapping could complement and enhance previous QTL information for marker-assisted selection. T HE basic objective of association mapping (AM)studies is to detect correlations between genotypes and phenotypes in a sample of individuals on the basis of linkage disequilibrium (LD) (Zondervan and Cardon 2004). In the study of genetics of complex diseases in humans, AM offers the important advantage of sampling unrelated individuals in the population, as compared to other experimental designs that require sampling within families (Risch 2000). In contrast to humans, plants can be manipulated to develop large experimental populations with desirable characteristics for genetic mapping, so in principle use of the association approach might not seem as appealing as it is in humans.However, sampling unrelated genotypes presents a number of advantages for the development of tools for marker-assisted selection in plant breeding ( Jannink et al. 2001). First, the experimental population can be a representative sample of the population to which inference is desired. Examples are a core collection from a gene bank, varieties representing the elite germplasm of a breeding program or inbred lines representing a synthetic outcrossing population. In this way, information derived from the experiments should be readily applicable to crop improvement. Second, AM can be more efficient in the use of resources. A group of unrelated individuals normally presents variation for many phenotypic aspects; thus several traits can be studied in the same population using the same genotypic data. A higher proportion of molecular markers are likely to be polymorphic, providing better genome coverage than any biparental map. Furthermore, if elite lines are used for study, multi-year and multi-location phenotypic data may be available at no additional cost (Ra...

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“…The number of SSR tandem repeats can vary in a sequence, and many such variants (alleles) can exist in a population (Powell et al, 1996). SSR markers tend to be among the most polymorphic genetic marker types and have been introduced into the process of cultivar and variety identification as well as in pedigree reconstruction and genetic mapping (Holton et al, 2002;Yu et al, 2004a;Celucia et al, 2009), to analyze functional diversity (Senior et al, 1998;Leigh et al, 2003;Dreisigacker et al, 2004), and for comparative mapping (Yu et al, 2004b;Varshney et al, 2005a). Although the identification of SSRs in gene sequences of plants started as early as 1993 (Varshney et al, 2005b), full exploitation of this marker during this period was limited by the amount of sequence data available for SSR analysis, and therefore, only a few genomic SSRs were reported.…”

Section: Introductionmentioning

confidence: 99%

Genetic diversity and relationships among different tomato varieties revealed by EST-SSR markers

Korir¹,

Diao²,

Tao³

et al. 2014

Genet. Mol. Res.

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ABSTRACT. The genetic diversity and relationship of 42 tomato varieties sourced from different geographic regions was examined with EST-SSR markers. The genetic diversity was between 0.18 and 0.77, with a mean of 0.49; the polymorphic information content ranged from 0.17 to 0.74, with a mean of 0.45. This indicates a fairly high degree of diversity among these tomato varieties. Based on the cluster analysis using unweighted pair-group method with arithmetic average (UPGMA), all the tomato varieties fell into 5 groups, with no obvious geographical distribution characteristics despite their diverse sources. The principal component analysis (PCA) supported the clustering result; however, relationships among varieties were more complex in the PCA scatterplot than in the UPGMA dendrogram. This information about the genetic relationships between these tomato lines helps distinguish these 42 varieties and will be useful for tomato variety breeding and selection. We confirm that the EST-SSR marker system is useful for studying genetic diversity among tomato varieties. The high degree of polymorphism and the large number of bands obtained per assay shows that SSR is the most informative marker system for tomato genotyping for purposes of rights/protection and for the tomato industry in general. It is recommended that these varieties be subjected to identification using an SSR-based manual cultivar identification diagram strategy or other easy-to-use and referable methods so as to provide a complete set of information concerning genetic relationships and a readily usable means of identifying these varieties.

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EST derived SSR markers for comparative mapping in wheat and rice

Cited by 163 publications

References 59 publications

Identification of wheat cultivars using EST-SSR markers

Identification of wheat cultivars using EST-SSR markers

Association Mapping of Kernel Size and Milling Quality in Wheat (Triticum aestivum L.) Cultivars

Genetic diversity and relationships among different tomato varieties revealed by EST-SSR markers

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