MicroRNAs are endogenous small noncoding RNAs which play critical roles in gene regulation. Few wheat (Triticum aestivumL.) miRNA sequences are available in miRBase repertoire and knowledge of their biological functions related to biotic stress is limited. We identified 52 miRNAs, belonging to 19 families, from next-generation transcriptome sequence data based on homology search. One wheat specific novel miRNA was identified but could not be ascribed or assigned to any known miRNA family. Differentially expressed 22 miRNAs were found between susceptible and resistant wheat near-isogenic lines inoculated with leaf rust pathogenPuccinia triticinaand compared with mock inoculated controls. Most miRNAs were more upregulated in susceptible NIL compared to resistant NIL. We identified 1306 potential target genes for these 52 miRNAs with vital roles in response to stimuli, signaling, and diverse metabolic and cellular processes. Gene ontology analysis showed 66, 20, and 35 target genes to be categorized into biological process, molecular function, and cellular component, respectively. A miRNA-mediated regulatory network revealed relationships among the components of the targetome. The present study provides insight into potential miRNAs with probable roles in leaf rust pathogenesis and their target genes in wheat which establish a foundation for future studies.

Pathogens like Puccinia triticina, the causal organism for leaf rust, extensively damages wheat production. The interaction at molecular level between wheat and the pathogen is complex and less explored. The pathogen induced response was characterized using mock- or pathogen inoculated near-isogenic wheat lines (with or without seedling leaf rust resistance gene Lr28). Four Serial Analysis of Gene Expression libraries were prepared from mock- and pathogen inoculated plants and were subjected to Sequencing by Oligonucleotide Ligation and Detection, which generated a total of 165,767,777 reads, each 35 bases long. The reads were processed and multiple k-mers were attempted for de novo transcript assembly; 22 k-mers showed the best results. Altogether 21,345 contigs were generated and functionally characterized by gene ontology annotation, mining for transcription factors and resistance genes. Expression analysis among the four libraries showed extensive alterations in the transcriptome in response to pathogen infection, reflecting reorganizations in major biological processes and metabolic pathways. Role of auxin in determining pathogenesis in susceptible and resistant lines were imperative. The qPCR expression study of four LRR-RLK (Leucine-rich repeat receptor-like protein kinases) genes showed higher expression at 24 hrs after inoculation with pathogen. In summary, the conceptual model of induced resistance in wheat contributes insights on defense responses and imparts knowledge of Puccinia triticina-induced defense transcripts in wheat plants.