Fig. 1 K-mer volume histograms of illumina sequencing data from several plant genomes a:The first peak,at the depth at 1-2,is derived from sequencing error. b:The second peak,is the main peak in haploid genome or homozygous diploid genome. c-d:The peak c,is composed of the repetitive k-mers with relative low copy number while the right-most peak d,is composed of the highly repetitive k-mers. In heterozygous diploid genome,the peak b1 contains k-mers derived from heterozygous regions and the peak b2 contains k-mers derived from homozygous regions. The depth of peak b1 is only half of the average sequencing depth. In heterozygous autotetraploid genome,both of the peak b1 and b2 present heterozygous k-mers and the peak b3 presents homozygous k-mers. This figure is modified based on the references[4,5,6,7,8,9]

Fig. 2 Three assembly and genotyping strategies of genome in plants a:The trio-sequencing based genotyping strategy Triobin[41]. The sequencing reads of F1 hybrid was firstly partitioned into paternal and maternal sets using the parental unique K-mers,then assembled separately into two haplotypes. b:Genotyping based on haploid population[44]. To phase the pre-assembled BAC clones,12 pollen cells were sequenced individually and the alignment results between each BAC and each pollen cell were encoded into a 12-bit binary barcode. In this approach,the BAC clones could be replaced with the high-accuracy and long segment such as HiFi reads or assembled contigs,etc. c:Genotyping based on selfing segregation population[7]. Firstly,the diploid contigs were de novo assembled,and a segregation population was sequenced to identify the genotypes of contigs. Then,the genetic map was constructed to identify different chromosomes. Lastly,the contigs belonging to same chromosome were partitioned into different haplotypes based on their genotypes’ similarity

Fig. 3 Three approaches of assembling pan-genome a: Iterative assembly pan-genome. Construction of pan-genome by mapping reads to a reference genome,the unaligned reads were then assembled into novel contigs and they were iteratively added to the reference genome. b: De novo assembly pan-genome. Multiple genomes were assembled and annotated,and pan-gene clusters were predicted using clustering algorithm. Gene-clusters were further cataloged to core- and dispensable-sets according to the cluster frequency among all samples. The pan- and core-genome curves were fitted using nonlinear models. c: Graph-based genome. A pan-genome graph can be constructed by integrating variations to a reference genome. Grey box indicated the alternative path differing from reference genome. Right side showed the actual structure of 2 regions in graph-based genome