De novo sequencing and comparative transcriptome analysis of adventitious root development induced by exogenous indole-3-butyric acid in cuttings of tetraploid black locust

Abstract

Background: Indole-3-butyric acid (IBA) is applied to the cuttings of various plant species to induce formation of adventitious roots (ARs) in commercial settings. Tetraploid black locust is an attractive ornamental tree that is drought resistant, sand tolerant, can prevent sand erosion and has various commercial uses. To further elucidate the mechanisms of AR formation, we used Illumina sequencing to analyze transcriptome dynamics and differential gene expression at four developmental stages in control (CK) and IBA-treated groups.

Results: The short reads were assembled into 127,038 unitranscripts and 101,209 unigenes, with average lengths of 986 and 852 bp. In total, 10,181 and 14,924 differentially expressed genes (DEGs) were detected in the CK and IBA-treated groups, respectively. Comparison of the four consecutive developmental stages showed that 282 and 260 DEGs were shared between IBA-treated and CK, suggesting that IBA treatment increased the number of DEGs. We observed 1,721 up-regulated and 849 down-regulated genes in CI vs. II, 849 up-regulated and 836 down-regulated genes in CC vs. IC, 881 up-regulated and 631 down-regulated genes in CRP vs. IRP, and 5,626 up-regulated and 4,932 down-regulated genes in CAR vs. IAR, of which 25 up-regulated DEGs were common to four pairs, and these DEGs were significantly up-regulated at AR. These results suggest that substantial changes in gene expression are associated with adventitious rooting. GO functional category analysis indicated that IBA significantly up- or down-regulated processes associated with regulation of transcription, transcription of DNA dependent, integral to membrane and ATP binding during the development process. KEGG pathway enrichment indicated that glycolysis/gluconeogenesis, cysteine and methionine metabolism, photosynthesis, nucleotide sugar metabolism, and lysosome were the pathways most highly regulated by IBA. We identified a number of differentially regulated unigenes, including 12 methionine-related genes and 12 ethylene-related genes, associated with the KEGG pathway cysteine and methionine metabolism. The GO enrichment, pathway mapping, and gene expression profile analyses revealed molecular traits for root induction and initiation.

Conclusion: Our study presents a global view of the transcriptomic profiles of tetraploid black locust cuttings in response to IBA treatment and provides new insights into the fundamental mechanisms associated with auxin-induced adventitious rooting.

Keywords: Adventitious root development; IBA; Tetraploid black locust; Transcriptome; de novo.

Fig. 1

Morphological changes in tetraploid black locust cuttings undergoing adventitious root development in a sand bed. a Softwood cuttings before cutting. b White callus appeared 10 days after cutting. c-d Yellow callus appeared and tiny adventitious roots emerged (root primordium) at 15 days after cutting. e Adventitious root formation and elongation at 20 days after cutting. As biological replicates, 10 samples were randomly selected from the groups treated with IBA

Fig. 2

The species distribution of unigene blastx results against the NCBI-Nr protein database

Fig. 3

RNA-seq-based transcriptome dynamics of IBA-treated cuttings during adventitious root development. The fold-change >2.0 for each gene was used for the hierarchical clustering analysis at each of the four selected developmental stages (II, IC, IRP and IAR). The 14,924 genes were classified into 40 regulation patterns (groups 1–10, 14–18, and 20–24)

Fig. 4

Differentially expressed genes among stages in IBA treatment and between IBA-treated and CK for each developmental stage

Fig. 5

The distribution of GO terms enriched in the sample pairs

Fig. 6

q-PCR validation of differential expression. Transcript levels of 21 genes in CK (black column) and IBA (gray column). The y-axis shows the relative gene expression levels as analyzed by q-PCR. Bars represent the standard error (n = 3). A Comparison of the gene expression ratios obtained from RNA-seq data and q-PCR