Understanding plant-pathogen interactions at a molecular level is essential for breeding disease-resistant crops and developing effective disease management strategies. It provides insights into the pathogen infection process and host defence mechanisms, enabling the identification of key genes and pathways involved, which facilitate targeted interventions to enhance plant immunity. Whilst many studies have analysed gene expression in plant-pathogen interactions, relatively few have studied microRNA (miRNA) expression. miRNAs are endogenous, non-coding small RNA (sRNA) molecules, mostly of 18-24 nucleotides in length, that act as key regulators of gene expression in various biological processes like growth and development, reproduction and stress response. They regulate gene expression at the post-transcriptional level by binding target mRNAs and subsequently cleaving the transcript or preventing translation. Recent studies have shown that miRNAs play a key role in the plant immune response by regulating defence genes, hormonal pathways and secondary metabolite pathways. There is also evidence that some plant miRNAs can mediate cross-kingdom communication and manipulate gene expression in pathogens, thereby affecting virulence. Because of their ability to fine-tune the immune response, miRNAs have promising potential as target molecular markers for crop improvement and disease management. To better understand the role of miRNAs in the early stages of plant-fungal interactions, we have studied small RNAs produced in two important pathosystems: canola blackleg (Brassica napus - Leptosphaeria maculans) and tomato early blight (Solanum lycopersicum - Alternaria solani). We extracted sRNAs from infected and mock-inoculated plants prior to the development of visual symptoms and used these to obtain high-depth Illumina sequencing data. The sRNA libraries were aligned to the plant and pathogen genomes using Bowtie, and two different miRNA prediction tools (miRDeep-P2 and miRador) were used to predict miRNAs. Interestingly, an average of 15.4% of sRNA reads from infected tissue aligned to the Alternaria solani genome, compared to 2.30% for mock-inoculated controls. Moreover, miRDeep-P2 predicted 2-11 miRNAs per sample based on sRNA reads aligned to the Alternaria solani genome, suggesting that miRNA-like sequences may exist in this pathogen. Further investigation of these findings may shed light on miRNA sequences that mediate cross-kingdom signalling or pathogen miRNAs involved in the plant infection process.