4.8 Article

Analysis of 427 genomes reveals moso bamboo population structure and genetic basis of property traits

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NATURE COMMUNICATIONS
卷 12, 期 1, 页码 -

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NATURE PORTFOLIO
DOI: 10.1038/s41467-021-25795-x

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  1. Special Fund for Forest Scientific Research in the Public Welfare from the State Forestry Administration of China [201504106]
  2. Fundamental Research Funds for the International Center for Bamboo and Rattan [1632020004]
  3. National Natural Science Foundation of China [31971733]

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The study analyzed 427 genomes of moso bamboo from 15 representative geographic areas, identifying genes related to population adaptation, historic demography patterns, and candidate genes for important traits.
Moso bamboo (Phyllostachys edulis) is an economically and ecologically important nontimber forestry species. Further development of this species as a sustainable bamboo resource has been hindered by a lack of population genome information. Here, we report a moso bamboo genomic variation atlas of 5.45 million single-nucleotide polymorphisms (SNPs) from whole-genome resequencing of 427 individuals covering 15 representative geographic areas. We uncover low genetic diversity, high genotype heterozygosity, and genes under balancing selection underlying moso bamboo population adaptation. We infer its demographic history with one bottleneck and its recently small population without a rebound. We define five phylogenetic groups and infer that one group probably originated by a single-origin event from East China. Finally, we conduct genome-wide association analysis of nine important property-related traits to identify candidate genes, many of which are involved in cell wall, carbohydrate metabolism, and environmental adaptation. These results provide a foundation and resources for understanding moso bamboo evolution and the genetic mechanisms of agriculturally important traits. Moso bamboo is an economically and ecologically important nontimber forestry species. Here, the authors analyze 427 genomes collected from 15 representative geographic areas, and identify genes under balancing selection, putative patterns of historic demography, and candidate genes associated with important traits.

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