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High-resolution silkworm pan-genome provides genetic insights into artificial selection and ecological adaptation

Author

Listed:
  • Xiaoling Tong

    (Southwest University
    Southwest University)

  • Min-Jin Han

    (Southwest University
    Southwest University)

  • Kunpeng Lu

    (Southwest University)

  • Shuaishuai Tai

    (BGI Genomics, BGI-Shenzhen)

  • Shubo Liang

    (Southwest University)

  • Yucheng Liu

    (Chinese Academy of Sciences)

  • Hai Hu

    (Southwest University)

  • Jianghong Shen

    (Southwest University)

  • Anxing Long

    (Southwest University)

  • Chengyu Zhan

    (Southwest University)

  • Xin Ding

    (Southwest University)

  • Shuo Liu

    (Southwest University)

  • Qiang Gao

    (Southwest University)

  • Bili Zhang

    (Southwest University)

  • Linli Zhou

    (Southwest University
    Southwest University)

  • Duan Tan

    (Southwest University
    Southwest University)

  • Yajie Yuan

    (Southwest University)

  • Nangkuo Guo

    (Southwest University)

  • Yan-Hong Li

    (BGI Genomics, BGI-Shenzhen)

  • Zhangyan Wu

    (BGI Genomics, BGI-Shenzhen)

  • Lulu Liu

    (Southwest University)

  • Chunlin Li

    (Southwest University)

  • Yaru Lu

    (Southwest University)

  • Tingting Gai

    (Southwest University)

  • Yahui Zhang

    (Southwest University)

  • Renkui Yang

    (Chongqing Sericulture Science and Technology Research Institute)

  • Heying Qian

    (Jiangsu University of Science and Technology)

  • Yanqun Liu

    (Shenyang Agricultural University)

  • Jiangwen Luo

    (Southwest University)

  • Lu Zheng

    (Southwest University)

  • Jinghou Lou

    (Southwest University)

  • Yunwu Peng

    (Ankang University)

  • Weidong Zuo

    (Southwest University
    Southwest University)

  • Jiangbo Song

    (Southwest University)

  • Songzhen He

    (Southwest University)

  • Songyuan Wu

    (Southwest University
    Southwest University)

  • Yunlong Zou

    (Southwest University
    Southwest University)

  • Lei Zhou

    (Southwest University)

  • Lan Cheng

    (Southwest University
    Southwest University)

  • Yuxia Tang

    (Southwest University)

  • Guotao Cheng

    (Southwest University
    Southwest University)

  • Lianwei Yuan

    (Southwest University)

  • Weiming He

    (BGI Genomics, BGI-Shenzhen)

  • Jiabao Xu

    (BGI Genomics, BGI-Shenzhen)

  • Tao Fu

    (BGI Genomics, BGI-Shenzhen)

  • Yang Xiao

    (Guangdong Academy of Agricultural Sciences)

  • Ting Lei

    (Chongqing Sericulture Science and Technology Research Institute)

  • Anying Xu

    (Jiangsu University of Science and Technology)

  • Ye Yin

    (BGI Genomics, BGI-Shenzhen)

  • Jian Wang

    (BGI-Shenzhen
    James D. Watson Institute of Genome Sciences)

  • Antónia Monteiro

    (National University of Singapore
    Science Division, Yale-NUS College)

  • Eric Westhof

    (Southwest University
    Université de Strasbourg)

  • Cheng Lu

    (Southwest University)

  • Zhixi Tian

    (Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

  • Wen Wang

    (Northwestern Polytechnical University
    Chinese Academy of Sciences)

  • Zhonghuai Xiang

    (Southwest University)

  • Fangyin Dai

    (Southwest University
    Southwest University)

Abstract

The silkworm Bombyx mori is an important economic insect for producing silk, the “queen of fabrics”. The currently available genomes limit the understanding of its genetic diversity and the discovery of valuable alleles for breeding. Here, we deeply re-sequence 1,078 silkworms and assemble long-read genomes for 545 representatives. We construct a high-resolution pan-genome dataset representing almost the entire genomic content in the silkworm. We find that the silkworm population harbors a high density of genomic variants and identify 7308 new genes, 4260 (22%) core genes, and 3,432,266 non-redundant structure variations (SVs). We reveal hundreds of genes and SVs that may contribute to the artificial selection (domestication and breeding) of silkworm. Further, we focus on four genes responsible, respectively, for two economic (silk yield and silk fineness) and two ecologically adaptive traits (egg diapause and aposematic coloration). Taken together, our population-scale genomic resources will promote functional genomics studies and breeding improvement for silkworm.

Suggested Citation

  • Xiaoling Tong & Min-Jin Han & Kunpeng Lu & Shuaishuai Tai & Shubo Liang & Yucheng Liu & Hai Hu & Jianghong Shen & Anxing Long & Chengyu Zhan & Xin Ding & Shuo Liu & Qiang Gao & Bili Zhang & Linli Zhou, 2022. "High-resolution silkworm pan-genome provides genetic insights into artificial selection and ecological adaptation," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
  • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-33366-x
    DOI: 10.1038/s41467-022-33366-x
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