Development of a Proteome-Wide Data Mining Pipeline to Discover Novel Soybean Genes Associated with Soybean Cyst Nematode (SCN) Resistance

Citation

Bahram Samanfar, Nour Nissan, Benjamin Mimee, Elroy Cober, Ashkan Golshani: Development of a Proteome-Wide Data Mining Pipeline to Discover Novel Soybean Genes Associated with Soybean Cyst Nematode (SCN) Resistance. Plant and Animal Genome (PAG-31), 2024, Sandiego, USA [Oral].

Abstract

The soybean (Glycine max (L.) Merr.) holds significant economic importance due to its role in sustainable agriculture, as well as its vital contributions to food, feed, and fuel production. However, soybean cultivation faces a formidable threat from the soybean cyst nematode, scientifically known as Heterodera glycines (SCN), resulting in yield losses of up to 80%. Once established in the soil, eradicating this pest becomes nearly impossible. Currently, only two resistant genes, rhg1 and Rhg4, are extensively utilized in SCN-infested fields. Consequently, SCN populations have started to adapt and overcome this resistance mechanism. Therefore, the identification of novel resistance genes in soybean is imperative to safeguard this crucial crop. A cutting-edge pipeline has been developed employing functional genomics and systems biology methodologies. This process involved the exploration of various computational databases, such as those housing single nucleotide polymorphisms, loss of function data, TAIR10, and BLASTP. Additionally, two prominent sequence-based protein-protein interaction prediction tools, namely the Protein-protein Interaction Prediction Engine (PIPE4) and Scoring PRotein INTeractions (SPRINT), were employed. These computational engines were utilized to search the entire proteomes of both soybean and SCN for proteins interacting with the already identified resistance proteins, rhg1 and Rhg4. By applying this pipeline to the entire soybean genome, a curated list of 91 potential candidate genes was generated. Among these candidates, nine have been recently published, with six conferring SCN resistance and five demonstrating resistance to other pathogens. Furthermore, 16 out of the 91 genes possess annotations related to plant pathogen resistance. Ongoing research involves a detailed examination of these promising candidate genes through RNA-seq experiments, aiming to develop allele-specific markers. These markers will play a crucial role in assisting breeding programs focused on creating new soybean cultivars with enhanced resistance to SCN.