P0412 Population-Scale Deep Sequencing Reveals Extensive Structural Variation in Medicago species

Peng Zhou , University of Minnesota, St. Paul, MN
Kevin A. T. Silverstein , Masonic Cancer Center, University of Minnesota, Minneapolis, MN
Tim Paape , University of Minnesota, St. Paul, MN
Arvind K. Bharti , National Center for Genome Resources, Santa Fe, NM
Andrew Farmer , National Center for Genome Resources, Santa Fe, NM
Joann Mudge , National Center for Genome Resources, Santa Fe, NM
Gregory D. May , National Center for Genome Resources, Santa Fe, NM
Peter Tiffin , University of Minnesota, St. Paul, MN
Nevin Young , University of Minnesota, St. Paul, MN
Through deep sequencing of 26 Medicago truncatula accessions, we found that in addition to Single Nucleotide Polymorphisms (SNPs) and short insertion/deletions, there are extensive structural variations (large insertions/deletions, translocations, tandem duplications, inversions) among natural populations. Using a pooled-sample analysis, we identified more than 1,400 deletion (>50bp) polymorphisms on Medicago chromosome 5 based on insert size distribution and paired-end mapping signature. Genotypes were then assigned to individual accessions by calculating a genotype probability using evidences from read depth (RD), read pairs (RP) and breakpoint-spanning reads (BR). Not surprisingly, most of the deletion events either occur in intergenic regions or involve transposable elements. However, a considerable number of deletions also involve the coding regions of common genes, probably resulting in large-effect functional changes. In particular, we have observed deletion events involving two interesting classes of plant defense genes: the NBS-LRR gene family and the NCR gene family. These genes have been shown to harbor higher-than-normal substitution rates and characteristics of rapid evolution. However, high sequence similarity among family members also makes it difficult to confidently map reads to the reference, which hinders the detection of structural variation in these gene families. Here, we begin to explore the power of structural variation detection using NGS in different gene families, along with the impact of these structural variations on genome architecture, the functional relevance to known gene families, and their segregating patterns in natural populations.