%0 Generic
%A van Workum, Dirk-Jan M.
%A Mehrem, Sarah L.
%A Snoek, Basten L.
%A Alderkamp, Marrit C.
%A Lapin, Dmitry
%A Mulder, Flip F. M.
%A van den Ackerveken, Guido
%A de Ridder, D. (Dick)
%A Eric Schranz, M.
%A Smit, Sandra
%D 2024
%T Data underlying the publication: Lactuca super-pangenome reduces bias towards reference genes in lettuce research
%U 
%R 10.4121/c7935d6a-d6ae-42e7-af7e-0ae8cddf70d7.v1
%K lettuce
%K Lactuca sativa
%K pangenomics
%K super-pangenome
%K PAV-GWAS
%X <p>Supplementary data belonging to "<em>Lactuca</em> super-pangenome reduces bias towards reference genes in lettuce research". In order to get an overview of the gene content of the genus <em>Lactuca</em>, we used WGS data of 474 accessions beloning to <em>L. sativa</em>, <em>L. serriola</em>, <em>L. saligna</em> and <em>L. virosa</em> for the construction of a linear pangenome per species. This linear pangenome was built using the assemble-and-iteratively-add approach. Once constructed, presence-absence variation (PAV) and copy-number variation (CNV) were calculated from the WGS data on the linear pangenomes. The PAV data was integrated across species into a <em>Lactuca</em> wide table that contains the variation for each of the 474 accessions for all genes in the super-pangenome. This super-pangenome resource was then used for functional characterisation of the core and variable genes, and a phylogeny of all accessions. Finally, we used the <em>L. sativa</em> PAV data to show its complementary and benefits in GWAS over SNPs. All data underlying these analyses is bundled together in one tarball including README.</p>
%I 4TU.ResearchData