| Title: | Identification of QTL controlling volatile terpene contents in tea plant (Camellia sinensis) using a high-aroma 'Huangdan' x 'Jinxuan' F(1) population |
| Author(s): | Chen S; Li X; Liu Y; Chen J; Ma J; Chen L; |
| Address: | "Key Laboratory of Biology, Genetics and Breeding of Special Economic Animals and Plants, Ministry of Agriculture and Rural Affairs, Tea Research Institute of the Chinese Academy of Agricultural Sciences, Hangzhou, China" |
| DOI: | 10.3389/fpls.2023.1130582 |
| ISSN/ISBN: | 1664-462X (Print) 1664-462X (Electronic) 1664-462X (Linking) |
| Abstract: | "Aroma is an important factor affecting the character and quality of tea. The improvement of aroma trait is a crucial research direction of tea plant breeding. Volatile terpenes, as the major contributors to the floral odors of tea products, also play critical roles in the defense responses of plants to multiple stresses. However, previous studies have largely focused on the aroma formation during the manufacture of tea or the comparison of raw tea samples. The mechanisms causing different aroma profiles between tea cultivars have remained underexplored. In the current study, a high-density genetic linkage map of tea plant was constructed based on an F(1) population of 'Huangdan' x 'Jinxuan' using genotyping by sequencing. This linkage map covered 1754.57 cM and contained 15 linkage groups with a low inter-marker distance of 0.47 cM. A total of 42 QTLs associated with eight monoterpene contents and 12 QTLs associated with four sesquiterpenes contents were identified with the average PVE of 12.6% and 11.7% respectively. Furthermore, six candidate genes related to volatile terpene contents were found in QTL cluster on chromosome 5 by RNA-seq analysis. This work will enrich our understanding of the molecular mechanism of volatile terpene biosynthesis and provide a theoretical basis for tea plant breeding programs for aroma quality improvement" |
| Keywords: | RNA-seq linkage analysis quantitative trait loci tea plant volatile terpene; |
| Notes: | "PubMed-not-MEDLINEChen, Si Li, Xuanye Liu, Yujie Chen, Jiedan Ma, Jianqiang Chen, Liang eng Switzerland 2023/04/18 Front Plant Sci. 2023 Mar 29; 14:1130582. doi: 10.3389/fpls.2023.1130582. eCollection 2023" |
