Graph-based pan-genome analysis reveals diversity of structural variations in native and commercial chicken

Chickens are one of the most important domesticated animals, serving as an important protein source. Studying genetic variations in chickens to enhance their production performance is of great potential value. The emergence of next-generation sequencing has enabled precise analysis of single nucleotide polymorphisms and insertions/deletions in chicken, while third-generation sequencing achieves the accurate structural variant identification. However, the high cost of third-generation sequencing technology limits its application in population studies. The graph-based pan-genome strategy can overcome this challenge by enabling the detection of structural variations using cost-effective next-generation sequencing data. This study constructed a graph-based pan-genome for chickens using 12 high-quality genomes. This pan-genome used linear genome GRCg6a as the reference genome, containing variant information from two commercial and nine native chicken breeds. Compared to the linear genome, the pan-genome provided significant improvements in the efficiency of structural variation identification. On the basis of the graph-based pan-genome, high-frequency structural variations related to high egg production in Leghorn chicken were predicted. Additionally, it was discovered that potential structural variations was associated with highland adaptation in Tibetan chickens according to next-generation sequencing and transcriptomics data. Using the pan-genome graph, a new strategy to identify structural variations related to traits of interest in chickens is presented.