Identification of microRNA-Like RNAs in the filamentous fungus Trichoderma reesei by solexa sequencing

Abstract

microRNAs (miRNAs) are non-coding small RNAs (sRNAs) capable of negatively regulating gene expression. Recently, microRNA-like small RNAs (milRNAs) were discovered in several filamentous fungi but not yet in Trichoderma reesei, an industrial filamentous fungus that can secrete abundant hydrolases. To explore the presence of milRNA in T. reesei and evaluate their expression under induction of cellulose, two T. reesei sRNA libraries of cellulose induction (IN) and non-induction (CON) were generated and sequenced using Solexa sequencing technology. A total of 726 and 631 sRNAs were obtained from the IN and CON samples, respectively. Global expression analysis showed an extensively differential expression of sRNAs in T. reesei under the two conditions. Thirteen predicted milRNAs were identified in T. reesei based on the short hairpin structure analysis. The milRNA profiles obtained in deep sequencing were further validated by RT-qPCR assay. Computational analysis predicted a number of potential targets relating to many processes including regulation of enzyme expression. The presence and differential expression of T. reesei milRNAs imply that milRNA might play a role in T. reesei growth and cellulase induction. This work lays foundation for further functional study of fungal milRNAs and their industrial application.

Figure 1. Common and specific sequences between T. reesei IN and CON samples.

Venn charts show the summary of unique (A) and total (B) sRNAs sequence between T. reesei IN and CON samples. The number in brackets indicates the reads of the sequences.

Figure 2. Global expression analysis of T. reesei sRNAs.

A volcano plot shows the magnitude (fold change; x-axis) and significance (P-value; y-axis) of the unique sRNAs between IN and CON samples. The horizontal dashed line indicates the threshold of statistical significance (P-value= 0.01). The vertical dashed line shows the fold changes of 2.0 (log₂ = ±1.0). sRNAs were divided into three groups based on the fold changes (IN/CON) : (1) up-expressed sRNAs: log₂ fold change≥1.0; (2) equally expressed sRNAs: -1.0<log₂ fold change<1.0; (3) down-expressed sRNAs: log₂ fold change ≤ -1.0.

Figure 3. Prediction of T. reesei pre-milRNAs hairpin structures.

The secondary structures were analyzed with the Mfold software. The mature milRNA sequences were highlighted in blue.

Figure 4. Validation of differentially expressed milRNAs obtained in high-throughput sequencing with S-Poly(T) RT-qPCR method.

The expression levels of the selected milRNAs were assayed in both IN and CON. The 18S rRNA was used as a normalization control and the CON was served as the reference sample. All analyses were performed in biological triplicate. Statistical analysis was performed using a two-tailed Student’s t-test. Each bar represents mean ± SD. *P<0.05.