QTL Mapping for Leaf Area of Tea Plants (Camellia sinensis) Based on a High-Quality Genetic Map Constructed by Whole Genome Resequencing

Abstract

High-quality genetic maps play important roles in QTL mapping and molecular marker-assisted breeding. Tea leaves are not only important vegetative organs but are also the organ for harvest with important economic value. However, the key genes and genetic mechanism of regulating leaf area have not been clarified. In this study, we performed whole-genome resequencing on “Jinxuan,” “Yuncha 1” and their 96 F1 hybrid offspring. From the 1.84 Tb of original sequencing data, abundant genetic variation loci were identified, including 28,144,625 SNPs and 2,780,380 indels. By integrating the markers of a previously reported genetic map, a high-density genetic map consisting of 15 linkage groups including 8,956 high-quality SNPs was constructed. The total length of the genetic map is 1,490.81 cM, which shows good collinearity with the genome. A total of 25 representative markers (potential QTLs) related to leaf area were identified, and there were genes differentially expressed in large and small leaf samples near these markers. GWAS analysis further verified the reliability of QTL mapping. Thirty-one pairs of newly developed indel markers located near these potential QTLs showed high polymorphism and had good discrimination between large and small leaf tea plant samples. Our research will provide necessary support and new insights for tea plant genetic breeding, quantitative trait mapping and yield improvement.

Identification of gene family members and a key structural variation reveal important roles of OVATE genes in regulating tea (Camellia sinensis) leaf development

“…In addition to a large number of light-responsive elements identified in the promoter sequence, many cis-acting elements related to hormone response, stress response and growth and development were also found. This result further proves that OVATE gene family may play an important role in regulating the growth and development of tea plants (Hackbusch et al, 2005;Chen et al, 2021;Yu et al, 2021).…”

TeaPVs: a comprehensive genomic variation database for tea plant (Camellia sinensis)

“…In order to construct a relatively complete database, we collected the genome assembly and Pacbio data of 6 tea plant varieties, including “Shuchazao” [ 14 ], “Longjing43” [ 14 ], “Tieguanyin” [ 16 ], “Biyun” [ 15 ], “Huangdan” [ 17 ], “DASZ” [ 18 ] and “Yunkang 10” [ 1 ]; 238 whole-genome resequencing datasets (Additional file 1: Table S 1 ) [ 4 , 13 , 16 ]; a F1 hybrid population with 96 offspring [ 2 ]; 213 transcriptome sequencing data (Additional file 2: Table S 2 ) [ 18 ]. The above data were used for the identification of SNPs, Indels, SSRs and SVs; an additional 66 transcriptomes were collected from NCBI ( https://www.ncbi.nlm.nih.gov/ ) for expression abundance calculations (Additional file 3: Table S 3 ) [ 22 ].…”

“…Tea plant [ Camellia sinensis (L.) O. Kuntze] is a perennial evergreen woody plant with important economic value originating in southwest China [ 1 ]. Tea beverages have become the most popular non-alcoholic beverages in the world due to their rich content of amino acids, catechins and caffeine and other active substances that are beneficial to the human body [ 2 ]. According to reports, more than 300 tea varieties have been bred in China, and more than 3000 tea germplasm have been collected and preserved in China National Germplasm Tea Repository.…”

Construction of ultra-high-density genetic linkage map of a sorghum-sudangrass hybrid using whole genome resequencing

“…Compared with the previously reported maps, the map density here was shortened. However, despite low experimental cost and simple operation of the simplified genome sequencing, some deficiencies still exist, including insufficient sequencing depth, low marker coverage, and the inability to find certain key SNPs loci closely related to the main traits [ 30 , 31 ].…”

“…With the development of NGS and the reduction of sequencing cost, whole genome resequencing (WGRS) technology has become one of the most effective research strategies in breeding and genomics, which has been applied to construct maps of important crops, such as rice [ 32 ], tea [ 31 ], and potato [ 33 ]. However, an ultra-high-density map of sorghum-sudangrass hybrid based on WGRS technology has not been reported.…”