bioRxivPlant Biology
Pangenome of white lupin provides insights into the diversity of the species
B. Hufnagel, A. Soriano, J. Taylor, F. Divol, M. Kroc, H. Sanders, L. Yeheyis, M. Nelson, B. Peret
Abstract
BackgroundWhite lupin is an old crop with renewed interest due to its seed high protein content and high nutritional value. Despite a long domestication history in the Mediterranean basin, modern breeding efforts have been fairly scarce. Recent sequencing of its genome has provided tools for further description of genetic resources but detailed characterization is still missing. ResultsHere, we report the genome sequencing of several accessions that were used to establish a white lupin pangenome. We defined core genes that are present in all individuals and variable genes that are absent in some and may represent a gene pool for stress adaptation. We believe that the identification of novel genes, together with a more comprehensive reference sequence, represents a significant improvement of the white lupin genetic resources. As an example, we used this pangenome to identify selection footprints and to provide a candidate gene for one of the main QTLs associated with late flowering in Ethiopian lupin types. A 686 nucleotide deletion was identified in exon 3 of the LaFTa1 (Lupinus albus Flowering Time a1) gene that suggests a molecular origin for this trait of importance, defining the need for vernalization in some lupins. ConclusionsThe white lupin pangenome provides a novel genetic resource to better understand how domestication has shaped the genomic variability amongst this crop. It will be of major importance for breeders to select new breeding traits and incorporate them into new, more efficient and robust cultivars in order to face a growing demand for plant protein sources, notably in Europe.
- organism: plant (other)
- assay: whole-genome sequencing
- research focus: genome assembly
- research focus: gene regulatory network inference
- research focus: variant calling
- approach: experimental assay
- approach: statistical model
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