AUTHOR=Zhang Shuwen , Yu Zheping , Qi Xingjiang , Wang Zhao , Zheng Yuanyuan , Ren Haiying , Liang Senmiao , Zheng Xiliang 

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

JOURNAL=Frontiers in Plant Science

VOLUME=Volume 12 - 2021

YEAR=2021

URL=https://www.frontiersin.org/journals/plant-science/articles/10.3389/fpls.2021.675855

DOI=10.3389/fpls.2021.675855

ISSN=1664-462X

ABSTRACT=Chinese bayberry (Myrica rubra) is an economically important fruit tree that is grown in southern China. Owing to its over 10-year seedling period, the cross-breeding 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 plants. In the present study, molecular markers associated with leaf traits were identified via 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 F1 individuals and parents (Myrica rubra cv. Biqizhong × Myrica rubra cv. 2012LXRM). The final genetic map ultimately incorporated 31,431 SNP in 8 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 M. rubra was thereby established to be 275.37 Mb, with 94.98% of sequences being assembled into 8 pseudo-chromosomes. Additionally, 18 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 study is the first to report the QTL mapping and identification of loci responsible for the regulation of leaf traits in Myrica rubra, offering an invaluable scientific for future marker-assisted selection breeding and candidate gene analyses.