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Haplotype-resolved genome assembly plays a crucial role in understanding allele-specific functions. However, obtaining haplotype-resolved assembly for auto-polyploid genomes remains challenging. Existing methods can be classified into reference-based phasing, assembly-based phasing, and gamete binning. Nevertheless, there is a lack of cost-effective and efficient methods for haplotyping auto-polyploid genomes. In this study, we propose a novel phasing algorithm called PolyGH, which combines Hi-C and gametic data. We conducted experiments on tetraploid potato cultivars and divided the method into three steps. Firstly, gametic data was utilized to bin non-collapsed contigs, followed by merging adjacent fragments of the same type within the same contig. Secondly, accurate Hi-C signals related to differential genomic regions were acquired using unique k-mers. Finally, collapsed fragments were assigned to haplotigs based on combined Hi-C and gametic signals. Comparing PolyGH with Hi-C-based and gametic data-based methods, we found that PolyGH exhibited superior performance in haplotyping auto-polyploid genomes when integrating both data types. This approach has the potential to enhance haplotype-resolved assembly for auto-polyploid genomes. [ABSTRACT FROM AUTHOR]

Motivation Constructing a phylogenetic tree requires calculating the evolutionary distance between samples or species via large-scale resequencing data, a process that is both time-consuming and computationally demanding. Striking the right balance between accuracy and efficiency is a significant challenge. Results To address this, we introduce a new algorithm, MIKE (MinHash-based k -mer algorithm). This algorithm is designed for the swift calculation of the Jaccard coefficient directly from raw sequencing reads and enables the construction of phylogenetic trees based on the resultant Jaccard coefficient. Simulation results highlight the superior speed of MIKE compared to existing state-of-the-art methods. We used MIKE to reconstruct a phylogenetic tree, incorporating 238 yeast, 303 Zea , 141 Ficus , 67 Oryza , and 43 Saccharum spontaneum samples. MIKE demonstrated accurate performance across varying evolutionary scales, reproductive modes, and ploidy levels, proving itself as a powerful tool for phylogenetic tree construction. Availability and implementation MIKE is publicly available on Github at https://github.com/Argonum-Clever2/mike.git. [ABSTRACT FROM AUTHOR]