bioRxiv preprint doi: https://doi.org/10.1101/2021.08.16.456528; this version posted August 17, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license. Deciphering Rubber Tree Growth Using Network-Based Multi Omics Approaches Felipe Roberto Francisco1†, Alexandre Hild Aono 1†, Carla Cristina da Silva1, Paulo de Souza Gonçalves2, Erivaldo José Scaloppi Junior2, Vincent Le Guen3, Roberto Fritsche Neto4, Livia Moura Souza1,5, Anete Pereira de Souza1,6* 1Molecular Biology and Genetic Engineering Center (CBMEG), University of Campinas (UNICAMP), Campinas, Brazil 2Center of Rubber Tree and Agroforestry Systems, Agronomic Institute (IAC), Votuporanga, Brazil 3Centre de Coopération Internationale en Recherche Agronomique pour le Développement (CIRAD), UMR AGAP, Montpellier, France 4Department of Genetics, Luiz de Queiroz College of Agriculture (ESALQ), University of São Paulo (USP), Piracicaba, São Paulo, Brazil 5São Francisco University (USF), Itatiba, Brazil 6Department of Plant Biology, Biology Institute, University of Campinas (UNICAMP), Campinas, Brazil †These authors have contributed equally to this work * Correspondence: Anete Pereira de Souza
[email protected] Number of Words: 8909 Number of Figures: 7 Number of Tables: 1 Keywords: GBS, GWAS, Hevea brasiliensis, linkage disequilibrium, metabolic networks, QTL, RNA-Seq, WGCNA Abstract Hevea brasiliensis (rubber tree) is a large tree species of the Euphorbiaceae family with inestimable economic importance. Rubber tree breeding programs currently aim to improve growth and production, and the use of early genotype selection technologies can accelerate such processes, mainly with the incorporation of genomic tools, such as marker-assisted selection (MAS).