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April 21, 2020  |  

Pseudomolecule-level assembly of the Chinese oil tree yellowhorn (Xanthoceras sorbifolium) genome.

Authors: Bi, Quanxin and Zhao, Yang and Du, Wei and Lu, Ying and Gui, Lang and Zheng, Zhimin and Yu, Haiyan and Cui, Yifan and Liu, Zhi and Cui, Tianpeng and Cui, Deshi and Liu, Xiaojuan and Li, Yingchao and Fan, Siqi and Hu, Xiaoyu and Fu, Guanghui and Ding, Jian and Ruan, Chengjiang and Wang, Libing

Yellowhorn (Xanthoceras sorbifolium) is a species of the Sapindaceae family native to China and is an oil tree that can withstand cold and drought conditions. A pseudomolecule-level genome assembly for this species will not only contribute to understanding the evolution of its genes and chromosomes but also bring yellowhorn breeding into the genomic era.Here, we generated 15 pseudomolecules of yellowhorn chromosomes, on which 97.04% of scaffolds were anchored, using the combined Illumina HiSeq, Pacific Biosciences Sequel, and Hi-C technologies. The length of the final yellowhorn genome assembly was 504.2 Mb with a contig N50 size of 1.04 Mb and a scaffold N50 size of 32.17 Mb. Genome annotation revealed that 68.67% of the yellowhorn genome was composed of repetitive elements. Gene modelling predicted 24,672 protein-coding genes. By comparing orthologous genes, the divergence time of yellowhorn and its close sister species longan (Dimocarpus longan) was estimated at ~33.07 million years ago. Gene cluster and chromosome synteny analysis demonstrated that the yellowhorn genome shared a conserved genome structure with its ancestor in some chromosomes.This genome assembly represents a high-quality reference genome for yellowhorn. Integrated genome annotations provide a valuable dataset for genetic and molecular research in this species. We did not detect whole-genome duplication in the genome. The yellowhorn genome carries syntenic blocks from ancient chromosomes. These data sources will enable this genome to serve as an initial platform for breeding better yellowhorn cultivars. © The Author(s) 2019. Published by Oxford University Press.

Journal: GigaScience
DOI: 10.1093/gigascience/giz070
Year: 2019

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