Abstract Amongst the sustainable alternatives to increase maize production is the use of plant growth-promoting bacteria (PGPB). Azospirillum brasilense is one of the most well-known PGPB being able to fix nitrogen and produce phytohormones, especially indole-3-acetic acid - IAA. This work investigated if there is any contribution of the bacterium to the plant’s IAA levels, and how it affects the plant. To inhibit plant IAA production, yucasin, an inhibitor of the TAM/YUC pathway, was applied. Plantlets’ IAA concentration was evaluated through HPLC and dual RNA-Seq was used to analyze gene expression. Statistical differences between the group treated with yucasin and the other groups showed that A. brasilense inoculation was able to prevent the phenotype caused by yucasin concerning the number of lateral roots. Genes involved in the auxin and ABA response pathways, auxin efflux transport, and the cell cycle were regulated by the presence of the bacterium, yucasin, or both. Genes involved in the response to biotic/abiotic stress, plant disease resistance, and a D-type cellulose synthase changed their expression pattern among two sets of comparisons in which A. brasilense acted as treatment. The results suggest that A. brasilense interferes with the expression of many maize genes through an IAA-independent pathway. growthpromoting growth promoting PGPB. . (PGPB) wellknown well known phytohormones indole3acetic indoleacetic indole 3 acetic plants s levels TAMYUC TAM YUC pathway applied Plantlets RNASeq RNA Seq A roots pathways transport both bioticabiotic biotic abiotic stress resistance Dtype D type treatment IAAindependent independent (PGPB

Abstract In Dual RNA-Seq experiments the simultaneous extraction of RNA and analysis of gene expression data from both interacting organisms could be a challenge. One alternative is separating the reads during in silico data analysis. There are two main mapping methods used: sequential and combined. Here we present a combined approach in which the libraries were aligned to a concatenated genome to sort the reads before mapping them to the respective annotated genomes. A comparison of this method with the sequential analysis was performed. Two RNA-Seq libraries available in public databases consisting of a eukaryotic (Zea mays) and a prokaryotic (Herbaspirillum seropediceae) organisms were mixed to simulate a Dual RNA-Seq experiment. Libraries from real Dual RNA-Seq experiments were also used. The sequential analysis consistently attributed more reads to the first reference genome used in the analysis (due to cross-mapping) than the combined approach. More importantly, the combined analysis resulted in lower numbers of cross-mapped reads. Our results highlight the necessity of combining the reference genomes to sort reads previously to the counting step to avoid losing information in Dual RNA-Seq experiments. Since most studies first map the RNA-Seq libraries to the eukaryotic genome, much prokaryotic information has probably been lost.