Transcript profiling of Populus tomentosa genes in normal, tension, and opposite wood by RNA-seq

Wood formation affects the chemical and physical properties of wood, and thus affects its utility as a building material or a feedstock for biofuels, pulp and paper. To obtain genome-wide insights on the transcriptome changes and regulatory networks in wood formation, we used high-throughput RNA sequencing to characterize cDNA libraries of mature xylem from tension wood (TW), opposite wood (OW), and normal wood (NW), in the industrial tree species Populus tomentosa.

Here, we identified the global patterns and differences in gene expression among TW, OW, and NW, and constructed two transcriptomic regulatory networks involved in TW formation in P. tomentosa. We also identified candidate genes for molecular breeding of wood quality, and provided a starting point to decipher the molecular mechanisms of wood formation in Populus.

Our sequencing generated 140,978,316 (TW), 128,972,228 (OW), and 117,672,362 (NW) reads, corresponding to 10,127 (TW), 10,129 (OW), and 10,129 (NW) unique genes. Of these, 361 genes were differentially transcribed between TW and OW (log2FC ≥ 1 or ≤ -1, FDR < 0.05), 2,658 differed between OW and NW, and 2,417 differed between TW and NW. This indicates that NW differs significantly from the wood in branches; GO term analysis also indicated that OW experienced more transcriptome remodeling. The differentially expressed genes included 97 encoding transcription factors (TFs), 40 involved in hormone signal transduction, 33 in lignin biosynthesis, 21 in flavonoid biosynthesis, and 43 in cell wall metabolism, including cellulose synthase, sucrose synthase, and COBRA. More than half of the differentially expressed TF showed more than 4-fold lower transcript levels in NW compared with TW or OW, indicating that TF abundances differed dramatically in different wood types and may have important roles in the formation of reaction wood. In addition, transcripts of most of the genes involved in lignin biosynthesis were more abundant in OW compared with TW, consistent with the higher lignin content of OW. We constructed two transcriptomic networks for the regulation of lignin and cellulose biosynthesis, including TFs, based on the co-expression patterns of different genes. Lastly, we used reverse transcription quantitative PCR to validate the differentially expressed genes identified. Conclusions: Here, we identified the global patterns and differences in gene expression among TW, OW, and NW, and constructed two transcriptomic regulatory networks involved in TW formation in P. tomentosa. We also identified candidate genes for molecular breeding of wood quality, and provided a starting point to decipher the molecular mechanisms of wood formation in Populus.