Development and application of the Faba_bean_130K targeted next-generation sequencing SNP genotyping platform based on transcriptome sequencing
- PMID: 34117907
- DOI: 10.1007/s00122-021-03885-0
Development and application of the Faba_bean_130K targeted next-generation sequencing SNP genotyping platform based on transcriptome sequencing
Abstract
Large-scale faba bean transcriptome data are available, and the first genotyping platform based on liquid-phase probe targeted capture technology was developed for genetic and molecular breeding studies. Faba bean (Vicia faba L., 2n = 12) is an important food legume crop that is widely grown for multiple uses worldwide. However, no reference genome is currently available due to its very large genome size (approximately 13 Gb) and limited single nucleotide polymorphism (SNP) markers as well as highly efficient genotyping tools have been reported for faba bean. In this study, 16.7 billion clean reads were obtained from transcriptome libraries of flowers and leaves of 102 global faba bean accessions. A total of 243,120 unigenes were de novo assembled and functionally annotated. Moreover, a total of 1,579,411 SNPs were identified and further filtered according to a selection pipeline to develop a high-throughput, flexible, low-cost Faba_bean_130K targeted next-generation sequencing (TNGS) genotyping platform. A set of 69 Chinese faba bean accessions were genotyped with the TNGS genotyping platform, and the average mapping rate of captured reads to reference transcripts was 93.14%, of which 53.23% were located in the targeted regions. The TNGS genotyping results were validated by Sanger sequencing and the average consistency rate reached 93.6%. Comprehensive population genetic analysis was performed on the 69 Chinese faba bean accessions and identified four genetic subgroups correlated with the geographic distribution. This study provides valuable genomic resources and a reliable genotyping tool that could be implemented in genetic and molecular breeding studies to accelerate new cultivar development and improvement in faba bean.
© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.
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References
-
- Alexander DH, Novembre J, Lange K (2009) Fast model-based estimation of ancestry in unrelated individuals. Genome Res 19:1655–1664. https://doi.org/10.1101/gr.094052.109 - DOI - PubMed - PMC
-
- Baird NA, Etter PD, Atwood TS, Currey MC, Shiver AL, Lewis ZA, Selker EU, Cresko WA, Johnson EA (2008) Rapid SNP discovery and genetic mapping using sequenced RAD markers. PLoS ONE 3:e3376. https://doi.org/10.1371/journal.pone.0003376 - DOI - PubMed - PMC
-
- Barbazuk WB, Emrich SJ, Chen HD, Li L, Schnable PS (2007) SNP discovery via 454 transcriptome sequencing. Plant J 51:910–918. https://doi.org/10.1111/j.1365-313x.2007.03193.x - DOI - PubMed - PMC
-
- Brown AF, Yousef GG, Chebrolu KK, Byrd RW, Everhart KW, Thomas A, Reid RW, Parkin IA, Sharpe AG, Oliver R, Guzman I, Jackson EW (2014) High-density single nucleotide polymorphism (SNP) array mapping in Brassica oleracea: identification of QTL associated with carotenoid variation in broccoli florets. Theor Appl Genet 127:2051–2064. https://doi.org/10.1007/s00122-014-2360-5 - DOI - PubMed
-
- Buchfink B, Xie C, Huson DH (2015) Fast and sensitive protein alignment using DIAMOND. Nat Methods 12:59–60. https://doi.org/10.1038/nmeth.3176 - DOI - PubMed
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- 2019YFD1001300/National Key R&D Program of China
- CX(18)2019/Agricultural Science and Technology Independent Innovation Fund of Jiangsu Province
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