Construction of a High-Density Genetic Map and Identification of Leaf Trait-Related QTLs in Chinese Bayberry ( Myrica rubra )

• Published in: Frontiers in plant science Vol. 12; p. 675855
• Main Authors: Zhang, Shuwen, Yu, Zheping, Qi, Xingjiang, Wang, Zhao, Zheng, Yuanyuan, Ren, Haiying, Liang, Senmiao, Zheng, Xiliang
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers Media S.A 14-06-2021
• Subjects: genetic map; leaf traits; Myrica rubra; Plant Science; quantitative trait loci mapping; re-sequencing; Myrica rubra; genetic map; re-sequencing; quantitative trait loci mapping; leaf traits
• ISSN: 1664-462X; 1664-462X
• DOI: 10.3389/fpls.2021.675855

Chinese bayberry (
) is an economically important fruit tree that is grown in southern China. Owing to its over 10-year seedling period, the crossbreeding of bayberry is challenging. The characteristics of plant leaves are among the primary factors that control plant architecture and potential yields, making the analysis of leaf trait-related genetic factors crucial to the hybrid breeding of any plant. In the present study, molecular markers associated with leaf traits were identified
a whole-genome re-sequencing approach, and a genetic map was thereby constructed. In total, this effort yielded 902.11 Gb of raw data that led to the identification of 2,242,353 single nucleotide polymorphisms (SNPs) in 140 F
individuals and parents (
cv. Biqizhong ×
cv. 2012LXRM). The final genetic map ultimately incorporated 31,431 SNPs in eight linkage groups, spanning 1,351.85 cM. This map was then used to assemble and update previous scaffold genomic data at the chromosomal level. The genome size of
was thereby established to be 275.37 Mb, with 94.98% of sequences being assembled into eight pseudo-chromosomes. Additionally, 18 quantitative trait loci (QTLs) associated with nine leaf and growth-related traits were identified. Two QTL clusters were detected (the LG3 and LG5 clusters). Functional annotations further suggested two chlorophyll content-related candidate genes being identified in the LG5 cluster. Overall, this is the first study on the QTL mapping and identification of loci responsible for the regulation of leaf traits in
, offering an invaluable scientific for future marker-assisted selection breeding and candidate gene analyses.