September 22, 2019  |  

Draft genome of Glyptosternon maculatum, an endemic fish from Tibet Plateau.

Authors: Liu, Haiping and Liu, Qiyong and Chen, Zhiqiang and Liu, Yanchao and Zhou, Chaowei and Liang, Qiqi and Ma, Caixia and Zhou, Jianshe and Pan, Yingzi and Chen, Meiqun and Wangjiu and Jiang, Wenkai and Xiao, Shijun and Mou, Zhenbo

Mechanisms for high-altitude adaption have attracted widespread interest among evolutionary biologists. Several genome-wide studies have been carried out for endemic vertebrates in Tibet, including mammals, birds, and amphibians. However, little information is available about the adaptive evolution of highland fishes. Glyptosternon maculatum (Regan 1905), also known as Regan or barkley and endemic to the Tibetan Plateau, belongs to the Sisoridae family, order Siluriformes (catfishes). This species lives at an elevation ranging from roughly 2,800 m to 4,200 m. Hence, a high-quality reference genome of G. maculatum provides an opportunity to investigate high-altitude adaption mechanisms of fishes.To obtain a high-quality reference genome sequence of G. maculatum, we combined Pacific Bioscience single-molecule real-time sequencing, Illumina paired-end sequencing, 10X Genomics linked-reads, and BioNano optical map techniques. In total, 603.99 Gb sequencing data were generated. The assembled genome was about 662.34 Mb with scaffold and contig N50 sizes of 20.90 Mb and 993.67 kb, respectively, which captured 83% complete and 3.9% partial vertebrate Benchmarking Universal Single-Copy Orthologs. Repetitive elements account for 35.88% of the genome, and ?22,066 protein-coding genes were predicted from the genome, of which 91.7% have been functionally annotated.We present the first comprehensive de novo genome of G. maculatum. This genetic resource is fundamental for investigating the origin of G. maculatum and will improve our understanding of high-altitude adaption of fishes. The assembled genome can also be used as reference for future population genetic studies of G. maculatum.

Journal: GigaScience
DOI: 10.1093/gigascience/giy104
Year: 2018

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