Lignocellulosic biomass is a renewable resource of interest for biorefinery. However, current poplar varieties have not been selected for this specific purpose. The factors affecting biomass yield and chemical properties need thus to be studied. With this objective, we have initiated a systems biology approach, integrating genomic, transcriptomic and phenotypic data in natural populations of black poplar (Populus nigra). Up to now, we have focused on a subset of 12 genotypes from 6 populations and trialled in a randomized complete block design located at INRA Orléans, France. The transcriptome of 2 biological replicates of each genotype has been explored through RNA sequencing (RNAseq) of pools of young differentiating xylem and cambium. Additionally, biomass yield was evaluated through measurements of height and diameter on 6 replicates of each genotype across several years and rotations, while biomass propertieswere assessed through chemical analyses of lignin, cellulose and hemicellulose concentrations as well as saccharification potential on 3 replicates of each genotype. The resulting data were used to build a weighted gene co-expression network and identify gene modules whose expression was correlated with biomass yield and/or quality at the genotypic level. Remarkably, the largest module (1,460 transcripts) was significantly associated with klason lignin content and displayed an enrichment in genes involved in secondary cell wall formation. Four candidate genes from this module were further selected to validate the detected quantitative trait transcripts (QTTs) on 2 new replicates of the 12 genotypes using RT-qPCR. The resulting expression levels were significantly correlated to those previously quantified by RNAseq and to the klason lignin content in the wood samples. These results demonstrate the interest of our approach, and thus open some prospects towards the identification of new candidate genes whose functions remain to be elucidated.