Comparative Analysis of Coding and Non-Coding Features within Insect Tolerance Loci in Wheat with Their Homologs in Cereal Genomes

Food insecurity and malnutrition have reached critical levels with increased human population, climate fluctuations, water shortage; therefore, higher-yielding crops are in the spotlight of numerous studies. Abiotic factors affect the yield of staple food crops; among all, wheat stem sawfly (Cephus cinctus Norton) and orange wheat blossom midge (Sitodiplosis mosellana) are two of the most economically and agronomically harmful insect pests which cause yield loss in cereals, especially in wheat in North America. There is no effective strategy for suppressing this pest damage yet, and only the plants with intrinsic tolerance mechanisms such as solid stem phenotypes for WSS and antixenosis and/or antibiosis mechanisms for OWBM can limit damage. A major QTL and a causal gene for WSS resistance were previously identified in wheat, and 3 major QTLs and a causal gene for OWBM resistance. Here, we present a comparative analysis of coding and non-coding features of these loci of wheat across important cereal crops, barley, rye, oat, and rice. This research paves the way for our cloning and editing of additional WSS and OWBM tolerance gene(s), proteins, and metabolites.

Pan-Genome miRNomics in Brachypodium

Pan-genomes are efficient tools for the identification of conserved and varying genomic sequences within lineages of a species. Investigating genetic variations might lead to the discovery of genes present in a subset of lineages, which might contribute into beneficial agronomic traits such as stress resistance or yield. The content of varying genomic regions in the pan-genome could include protein-coding genes as well as microRNA(miRNAs), small non-coding RNAs playing key roles in the regulation of gene expression. In this study, we performed in silico miRNA identification from the genomic sequences of 54 lineages of Brachypodium distachyon, aiming to explore varying miRNA contents and their functional interactions. A total of 115 miRNA families were identified in 54 lineages, 56 of which were found to be present in all lineages. The miRNA families were classified based on their conservation among lineages and potential mRNA targets were identified. Obtaining information about regulatory mechanisms stemming from these miRNAs offers strong potential to provide a better insight into the complex traits that were potentially present in some lineages. Future work could lead us to introduce these traits to different lineages or other economically important plant species in order to promote their survival in different environmental conditions.