Long-read sequencing technologies have considerably improved the Lcu assembly by allowing us to sequence through the many repeat-heavy regions, correcting orientation and scaffold order, and pulling apart collapsed regions. Further exploration of long-read data will greatly facilitate our understanding of the variation outside the genic regions in both cultivated lentil and its wild relatives and enhance our ability to harness adaptive variation lurking in the dark corners of the Lens genepool. It will also help better resolve quantitative trait loci (QTL) and facilitate the design of markers useful for marker-assisted selection. Emerging research suggests that, like SNPs, structural variations are not evenly distributed throughout plant genomes, but instead elevated in regions of high recombination where uneven crossing over is most likely to occur. It has been hypothesized that many structural variants that segregate in wild taxa are fixed during domestication. Understanding lentil phenotypes in the context of these structural variations will help us design better crossing strategies for harnessing existing variation.

In this study we are focusing on generating improved genome assemblies for all Lens species to provide a solid basis for ongoing research. This includes additional data generation using new technologies such as PacBio Hifi, fine-tuning our existing long-read genome assembly workflow and leveraging information from other cool season legumes. Our initial goal was to collect at least 50X whole genome coverage for each genome and to assemble them independently.