Modelling of gene loss propensity in the pangenomes of three Brassica species suggests different mechanisms between polyploids and diploids

Philipp E. Bayer, Armin Scheben, Agnieszka A. Golicz, Yuxuan Yuan, Sebastien Faure, Huey Tyng Lee, Harmeet Singh Chawla, Robyn Anderson, Ian Bancroft, Harsh Raman, Yong Pyo Lim, Steven Robbens, Lixi Jiang, Shengyi Liu, Michael S. Barker, M. Eric Schranz, Xiaowu Wang, Graham J. King, J. Chris Pires, Boulos ChalhoubRod J. Snowdon, Jacqueline Batley, David Edwards

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

Abstract

Plant genomes demonstrate significant presence/absence variation (PAV) within a species; however, the factors that lead to this variation have not been studied systematically in Brassica across diploids and polyploids. Here, we developed pangenomes of polyploid Brassica napus and its two diploid progenitor genomes B. rapa and B. oleracea to infer how PAV may differ between diploids and polyploids. Modelling of gene loss suggests that loss propensity is primarily associated with transposable elements in the diploids while in B. napus, gene loss propensity is associated with homoeologous recombination. We use these results to gain insights into the different causes of gene loss, both in diploids and following polyploidization, and pave the way for the application of machine learning methods to understanding the underlying biological and physical causes of gene presence/absence.

Original languageEnglish (US)
Pages (from-to)2488-2500
Number of pages13
JournalPlant Biotechnology Journal
Volume19
Issue number12
DOIs
StatePublished - Dec 2021

Keywords

  • Brassica
  • XGBoost
  • gene loss propensity
  • machine learning
  • pangenome
  • transposable elements

ASJC Scopus subject areas

  • Biotechnology
  • Agronomy and Crop Science
  • Plant Science

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