Rapid gene identification in sugar beet using deep sequencing of DNA from phenotypic pools selected from breeding panels

Ries D, Holtgräwe D, Viehöver P, Weisshaar B (2016)
BMC Genomics 17: 236.

Zeitschriftenaufsatz | Veröffentlicht | Englisch
 
Download
OA 1.47 MB
Abstract / Bemerkung
Background
The combination of bulk segregant analysis (BSA) and next generation sequencing (NGS), also known as mapping by sequencing (MBS), has been shown to significantly accelerate the identification of causal mutations for species with a reference genome sequence. The usual approach is to cross homozygous parents that differ for the monogenic trait to address, to perform deep sequencing of DNA from F2 plants pooled according to their phenotype, and subsequently to analyze the allele frequency distribution based on a marker table for the parents studied. The method has been successfully applied for EMS induced mutations as well as natural variation. Here, we show that pooling genetically diverse breeding lines according to a contrasting phenotype also allows high resolution mapping of the causal gene in a crop species. The test case was the monogenic locus causing red vs. green hypocotyl color in Beta vulgaris (R locus).
Results
We determined the allele frequencies of polymorphic sequences using sequence data from two diverging phenotypic pools of 180 B. vulgaris accessions each. A single interval of about 31 kbp among the nine chromosomes was identified which indeed contained the causative mutation.
Conclusions
By applying a variation of the mapping by sequencing approach, we demonstrated that phenotype-based pooling of diverse accessions from breeding panels and subsequent direct determination of the allele frequency distribution can be successfully applied for gene identification in a crop species. Our approach made it possible to identify a small interval around the causative gene. Sequencing of parents or individual lines was not necessary. Whenever the appropriate plant material is available, the approach described saves time compared to the generation of an F2 population. In addition, we provide clues for planning similar experiments with regard to pool size and the sequencing depth required.
Stichworte
Allele frequency; Beta vulgaris; Gene identification; Mapping by sequencing; Phenotypic pools; R locus; SNP detection; Sugar beet
Erscheinungsjahr
2016
Zeitschriftentitel
BMC Genomics
Band
17
Art.-Nr.
236
eISSN
1471-2164
Finanzierungs-Informationen
Article Processing Charge funded by the Deutsche Forschungsgemeinschaft and the Open Access Publication Fund of Bielefeld University.
Page URI
https://pub.uni-bielefeld.de/record/2901603

Zitieren

Ries D, Holtgräwe D, Viehöver P, Weisshaar B. Rapid gene identification in sugar beet using deep sequencing of DNA from phenotypic pools selected from breeding panels. BMC Genomics. 2016;17: 236.
Ries, D., Holtgräwe, D., Viehöver, P., & Weisshaar, B. (2016). Rapid gene identification in sugar beet using deep sequencing of DNA from phenotypic pools selected from breeding panels. BMC Genomics, 17, 236. doi:10.1186/s12864-016-2566-9
Ries, D., Holtgräwe, D., Viehöver, P., and Weisshaar, B. (2016). Rapid gene identification in sugar beet using deep sequencing of DNA from phenotypic pools selected from breeding panels. BMC Genomics 17:236.
Ries, D., et al., 2016. Rapid gene identification in sugar beet using deep sequencing of DNA from phenotypic pools selected from breeding panels. BMC Genomics, 17: 236.
D. Ries, et al., “Rapid gene identification in sugar beet using deep sequencing of DNA from phenotypic pools selected from breeding panels”, BMC Genomics, vol. 17, 2016, : 236.
Ries, D., Holtgräwe, D., Viehöver, P., Weisshaar, B.: Rapid gene identification in sugar beet using deep sequencing of DNA from phenotypic pools selected from breeding panels. BMC Genomics. 17, : 236 (2016).
Ries, David, Holtgräwe, Daniela, Viehöver, Prisca, and Weisshaar, Bernd. “Rapid gene identification in sugar beet using deep sequencing of DNA from phenotypic pools selected from breeding panels”. BMC Genomics 17 (2016): 236.
Alle Dateien verfügbar unter der/den folgenden Lizenz(en):
Copyright Statement:
This Item is protected by copyright and/or related rights. [...]
Volltext(e)
Access Level
OA Open Access
Zuletzt Hochgeladen
2019-09-06T09:18:36Z
MD5 Prüfsumme
5d6698c73e1e252f7183f80ee9addb45

Export

Markieren/ Markierung löschen
Markierte Publikationen

Open Data PUB

Web of Science

Dieser Datensatz im Web of Science®

Quellen

PMID: 26980001
PubMed | Europe PMC

Suchen in

Google Scholar