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High-quality assembly and methylome of a Tibetan wild tree peony genome ( Paeonia ludlowii) reveal the evolution of giant genome architecture.

Pei-Xuan XiaoYuanrong LiJin LuHao ZuoGesang PingcuoHong YingFan ZhaoQiang XuXiuli ZengWen-Biao Jiao
Published in: Horticulture research (2023)
Tree peony belongs to one of the Saxifragales families, Paeoniaceae. It is one of the most famous ornamental plants, and is also a promising woody oil plant. Although two Paeoniaceae genomes have been released, their assembly qualities are still to be improved. Additionally, more genomes from wild peonies are needed to accelerate genomic-assisted breeding. Here we assemble a high-quality and chromosome-scale 10.3-Gb genome of a wild Tibetan tree peony, Paeonia ludlowii , which features substantial sequence divergence, including around 75% specific sequences and gene-level differentials compared with other peony genomes. Our phylogenetic analyses suggest that Saxifragales and Vitales are sister taxa and, together with rosids, they are the sister taxon to asterids. The P. ludlowii genome is characterized by frequent chromosome reductions, centromere rearrangements, broadly distributed heterochromatin, and recent continuous bursts of transposable element (TE) movement in peony, although it lacks recent whole-genome duplication. These recent TE bursts appeared during the uplift and glacial period of the Qinghai-Tibet Plateau, perhaps contributing to adaptation to rapid climate changes. Further integrated analyses with methylome data revealed that genome expansion in peony might be dynamically affected by complex interactions among TE proliferation, TE removal, and DNA methylation silencing. Such interactions also impact numerous recently duplicated genes, particularly those related to oil biosynthesis and flower traits. This genome resource will not only provide the genomic basis for tree peony breeding but also shed light on the study of the evolution of huge genome structures as well as their protein-coding genes.
Keyphrases
  • genome wide
  • dna methylation
  • copy number
  • gene expression
  • climate change
  • machine learning
  • transcription factor
  • fatty acid
  • amino acid
  • deep learning
  • big data
  • protein protein