| Autor: |
Lars-Gernot Otto, Prodyut Mondal, Jonathan Brassac, Susanne Preiss, Jörg Degenhardt, Sang He, Jochen Christoph Reif, Timothy Francis Sharbel |
| Jazyk: |
angličtina |
| Rok vydání: |
2017 |
| Předmět: |
|
| Zdroj: |
BMC Genomics, Vol 18, Iss 1, Pp 1-18 (2017) |
| Druh dokumentu: |
article |
| ISSN: |
1471-2164 |
| DOI: |
10.1186/s12864-017-3991-0 |
| Popis: |
Abstract Background Chamomile (Matricaria recutita L.) has a long history of use in herbal medicine with various applications, and the flower heads contain numerous secondary metabolites which are medicinally active. In the major crop plants, next generation sequencing (NGS) approaches are intensely applied to exploit genetic resources, to develop genomic resources and to enhance breeding. Here, genotyping-by-sequencing (GBS) has been used in the non-model medicinal plant chamomile to evaluate the genetic structure of the cultivated varieties/populations, and to perform genome wide association study (GWAS) focusing on genes with large effect on flowering time and the medicinally important alpha-bisabolol content. Results GBS analysis allowed the identification of 6495 high-quality SNP-markers in our panel of 91 M. recutita plants from 33 origins (2–4 genotypes each) and 4 M. discoidea plants as outgroup, grown in the greenhouse in Gatersleben, Germany. M. recutita proved to be clearly distinct from the outgroup, as was demonstrated by different cluster and principal coordinate analyses using the SNP-markers. Chamomile genotypes from the same origin were mostly genetically similar. Model-based cluster analysis revealed one large group of tetraploid genotypes with low genetic differentiation including 39 plants from 14 origins. Tetraploids tended to display lower genetic diversity than diploids, probably reflecting their origin by artificial polyploidisation from only a limited set of genetic backgrounds. Analyses of flowering time demonstrated that diploids generally flowered earlier than tetraploids, and the analysis of alpha-bisabolol identified several tetraploid genotypes with a high content. GWAS identified highly significant (P |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
|
