4.7 Article

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

期刊

PLANT BIOTECHNOLOGY JOURNAL
卷 19, 期 12, 页码 2488-2500

出版社

WILEY
DOI: 10.1111/pbi.13674

关键词

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

资金

  1. Australia Research Council [DP1601004497, LP140100537, LP130100925]
  2. Australian Government
  3. Government of Western Australia
  4. Forrest Research Foundation
  5. Korea Institute of Planning and Evaluation for Technology in Food, Agriculture, and Forestry (IPET) through Golden Seed Project - Ministry of Agriculture, Food and Rural Affairs (MAFRA), South Korea [213006-05-4-SB110]
  6. Ministry of Oceans and Fisheries (MOF), South Korea
  7. Rural Development Administration (RDA), South Korea
  8. Korea Forest Services (KFS), South Korea
  9. UK Biotechnology and Biological Sciences Research Council [BB/L002124/1, BB/R019819/1]

向作者/读者索取更多资源

Plant genomes show significant presence/absence variation (PAV) within a species, with different causes of gene loss between diploids and polyploids. In diploids, gene loss propensity is primarily associated with transposable elements, while in polyploids like B. napus, gene loss propensity is linked to homoeologous recombination. These findings provide insights into the underlying biological and physical factors of gene presence/absence, paving the way for the application of machine learning methods in the field.
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.

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