High-throughput novel microsatellite marker of faba bean via next generation sequencing
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Author(s)
Yang, Tao
Bao, Shi-Ying
Ford, Rebecca
Jia, Teng-Jiao
Guan, Jian-Ping
He, Yu-Hua
Sun, Xue-Lian
Jiang, Jun-Ye
Hao, Jun-Jie
Zhang, Xiao-Yan
Zong, Xu-Xiao
Griffith University Author(s)
Year published
2012
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Background: Faba bean (Vicia faba L.) is an important food legume crop, grown for human consumption globally
including in China, Turkey, Egypt and Ethiopia. Although genetic gain has been made through conventional
selection and breeding efforts, this could be substantially improved through the application of molecular methods.
For this, a set of reliable molecular markers representative of the entire genome is required.
Results: A library with 125,559 putative SSR sequences was constructed and characterized for repeat type and
length from a mixed genome of 247 spring and winter sown faba bean genotypes using 454 sequencing. ...
View more >Background: Faba bean (Vicia faba L.) is an important food legume crop, grown for human consumption globally including in China, Turkey, Egypt and Ethiopia. Although genetic gain has been made through conventional selection and breeding efforts, this could be substantially improved through the application of molecular methods. For this, a set of reliable molecular markers representative of the entire genome is required. Results: A library with 125,559 putative SSR sequences was constructed and characterized for repeat type and length from a mixed genome of 247 spring and winter sown faba bean genotypes using 454 sequencing. A suit of 28,503 primer pair sequences were designed and 150 were randomly selected for validation. Of these, 94 produced reproducible amplicons that were polymorphic among 32 faba bean genotypes selected from diverse geographical locations. The number of alleles per locus ranged from 2 to 8, the expected heterozygocities ranged from 0.0000 to 1.0000, and the observed heterozygosities ranged from 0.0908 to 0.8410. The validation by UPGMA cluster analysis of 32 genotypes based on Nei's genetic distance, showed high quality and effectiveness of those novel SSR markers developed via next generation sequencing technology. Conclusions: Large scale SSR marker development was successfully achieved using next generation sequencing of the V. faba genome. These novel markers are valuable for constructing genetic linkage maps, future QTL mapping, and marker-assisted trait selection in faba bean breeding efforts.
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View more >Background: Faba bean (Vicia faba L.) is an important food legume crop, grown for human consumption globally including in China, Turkey, Egypt and Ethiopia. Although genetic gain has been made through conventional selection and breeding efforts, this could be substantially improved through the application of molecular methods. For this, a set of reliable molecular markers representative of the entire genome is required. Results: A library with 125,559 putative SSR sequences was constructed and characterized for repeat type and length from a mixed genome of 247 spring and winter sown faba bean genotypes using 454 sequencing. A suit of 28,503 primer pair sequences were designed and 150 were randomly selected for validation. Of these, 94 produced reproducible amplicons that were polymorphic among 32 faba bean genotypes selected from diverse geographical locations. The number of alleles per locus ranged from 2 to 8, the expected heterozygocities ranged from 0.0000 to 1.0000, and the observed heterozygosities ranged from 0.0908 to 0.8410. The validation by UPGMA cluster analysis of 32 genotypes based on Nei's genetic distance, showed high quality and effectiveness of those novel SSR markers developed via next generation sequencing technology. Conclusions: Large scale SSR marker development was successfully achieved using next generation sequencing of the V. faba genome. These novel markers are valuable for constructing genetic linkage maps, future QTL mapping, and marker-assisted trait selection in faba bean breeding efforts.
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Journal Title
BMC Genomics
Volume
13
Issue
1
Copyright Statement
© 2012 Yang et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative
Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and
reproduction in any medium, provided the original work is properly cited.
Subject
Biological sciences
Genomics
Information and computing sciences
Biomedical and clinical sciences