Parva K. Sharma

Abstract Provided here is a study of large language models (LLMs) and retrieval augmented generation (RAG) frameworks in air-gapped environments for genome research on small grain crops. We developed two main applications: (1) a RAG-based system for contextual analysis of scientific literature, collecting over 5,000 PDFs on wheat pathogens, and (2) a GFF3 file analysis tool called Genoma that enables exploration of genome annotation through an interactive interface.

Abstract Bread wheat (Triticum aestivum) is a globally dominant crop and major source of calories and proteins for the human diet. Compared with its wild ancestors, modern bread wheat shows lower genetic diversity, caused by polyploidisation, domestication and breeding bottlenecks1,2. Wild wheat relatives represent genetic reservoirs, and harbour diversity and beneficial alleles that have not been incorporated into bread wheat.

Abstract Einkorn (Triticum monococcum) was the first domesticated wheat species, and was central to the birth of agriculture and the Neolithic Revolution in the Fertile Crescent around 10,000 years ago1,2. Here we generate and analyse 5.2-Gb genome assemblies for wild and domesticated einkorn, including completely assembled centromeres. Einkorn centromeres are highly dynamic, showing evidence of ancient and recent centromere shifts caused by structural rearrangements.