@article{fdi:010097897,
  title = {{A}dopting graph-based pangenomics for agronomy and biodiversity studies : current resources and challenges},
  author = {{B}ocs, {S}. and {C}arrette, {C}. and {C}onfais, {J}. and {D}ubois, {S}. and {D}uvaux, {L}. and {K}lopp, {C}. and {L}apalu, {N}. and {L}asserre-{Z}uber, {P}. and {L}egeai, {F}. and {L}emaitre, {C}. and {L}inard, {B}. and {M}arthe, {N}. and {P}ierre, {B}. and {S}arah, {G}. and {S}abot, {F}ran{\c{c}}ois and {D}ubreuil {T}ranchant, {C}hristine and {Z}ytnicki, {M}.},
  editor = {},
  language = {{ENG}},
  abstract = {{P}angenomics is transforming the way genomics is done. {B}y using assemblies of multiple complete genomes for the same species, it is possible to depart from a biased, reference-centric, point of view. {R}epresented as graphs, these pangenomes open new paths for genome understanding and improvement of species of agricultural interest. {T}hey have, for instance, been used to discover new structural variants linked with traits of interest, and increased the heritability prediction. {H}owever, transitioning to a graph-based approach is not straightforward, and many tools are still needed for this shift. {W}hile numerous papers present both methodological and applied approaches on pangenomics, and many reviews present advantages of these methods, very few resources outline what remains to be done. {I}n this paper, we would like to list methods that are still required to fully exploit pangenomes, and favor the widespread adoption of this approach.},
  keywords = {},
  booktitle = {},
  journal = {{P}eer {C}ommunity {J}ournal},
  volume = {6},
  numero = {},
  pages = {e86 [33 ]},
  ISSN = {2804-3871},
  year = {2026},
  DOI = {10.24072/pcjournal.781},
  URL = {https://www.documentation.ird.fr/hor/fdi:010097897},
}