High-quality chromosome-level de novo assembly of the Trifolium repens

Abstract

Abstract Background White clover (Trifolium repens L.), an excellent perennial legume forage, is an allotetraploid native to southeastern Europe and southern Asia. It has high nutritional, ecological, genetic breeding, and medicinal values and exhibits excellent resistance to cold, drought, trample, and weed infestation. Thus, white clover is widely planted in Europe, America, and China; however, the lack of reference genome limits its breeding and cultivation. This study generated a white clover de novo genome assembly at the chromosomal level and annotated its components. Results The PacBio third-generation Hi-Fi assembly and sequencing methods generated a 1096 Mb genome size of T. repens, with contigs of N50 = 14 Mb, scaffolds of N50 = 65 Mb, and BUSCO value of 98.5%. The newly assembled genome has better continuity and integrity than the previously reported white clover reference genome; thus provides important resources for the molecular breeding and evolution of white clover and other forage. Additionally, we annotated 90,128 high-confidence gene models from the genome. White clover was closely related to Trifolium pratense and Trifolium medium but distantly related to Glycine max, Vigna radiata, Medicago truncatula, and Cicer arietinum. The expansion, contraction, and GO functional enrichment analysis of the gene families showed that T. repens gene families were associated with biological processes, molecular function, cellular components, and environmental resistance, which explained its excellent agronomic traits. Conclusions This study reports a high-quality de novo assembly of white clover genome obtained at the chromosomal level using PacBio Hi-Fi sequencing, a third-generation sequencing. The generated high-quality genome assembly of white clover provides a key basis for accelerating the research and molecular breeding of this important forage crop. The genome is also valuable for future studies on legume forage biology, evolution, and genome-wide mapping of quantitative trait loci associated with the relevant agronomic traits.