KSNP: a fast de Bruijn graph-based haplotyping tool approaching data-in time cost.

Long reads that cover more variants per read raise opportunities for accurate haplotype construction, whereas the genotype errors of single nucleotide polymorphisms pose great computational challenges for haplotyping tools. Here we introduce KSNP, an efficient haplotype construction tool based on the de Bruijn graph (DBG). KSNP leverages the ability of DBG in handling high-throughput erroneous reads to tackle the challenges. Compared to other notable tools in this field, KSNP achieves at least 5-fold speedup while producing comparable haplotype results. The time required for assembling human haplotypes is reduced to nearly the data-in time.

A genetic atlas for the butterflies of continental Canada and United States.

Multi-locus genetic data for phylogeographic studies is generally limited in geographic and taxonomic scope as most studies only examine a few related species. The strong adoption of DNA barcoding has generated large datasets of mtDNA COI sequences. This work examines the butterfly fauna of Canada and United States based on 13,236 COI barcode records derived from 619 species. It compiles i) geographic maps depicting the spatial distribution of haplotypes, ii) haplotype networks (minimum spanning trees), and iii) standard indices of genetic diversity such as nucleotide diversity (π), haplotype richness (H), and a measure of spatial genetic structure (GST). High intraspecific genetic diversity and marked spatial structure were observed in the northwestern and southern North America, as well as in proximity to mountain chains. While species generally displayed concordance between genetic diversity and spatial structure, some revealed incongruence between these two metrics. Interestingly, most species falling in this category shared their barcode sequences with one at least other species. Aside from revealing large-scale phylogeographic patterns and shedding light on the processes underlying these patterns, this work also exposed cases of potential synonymy and hybridization.

Improving HLA typing imputation accuracy and eplet identification with local next-generation sequencing training data.

Assessing donor/recipient HLA compatibility at the eplet level requires second field DNA typings but these are not always available. These can be estimated from lower-resolution data either manually or with computational tools currently relying, at best, on data containing typing ambiguities. We gathered NGS typing data from 61,393 individuals in 17 French laboratories, for loci A, B, and C (100% of typings), DRB1 and DQB1 (95.5%), DQA1 (39.6%), DRB3/4/5, DPB1, and DPA1 (10.5%). We developed HaploSFHI, a modified iterative maximum likelihood algorithm, to impute second field HLA typings from low- or intermediate-resolution ones. Compared with the reference tools HaploStats, HLA-EMMA, and HLA-Upgrade, HaploSFHI provided more accurate predictions across all loci on two French test sets and four European-independent test sets. Only HaploSFHI could impute DQA1, and solely HaploSFHI and HaploStats provided DRB3/4/5 imputations. The improved performance of HaploSFHI was due to our local and nonambiguous data. We provided explanations for the most common imputation errors and pinpointed the variability of a low number of low-resolution haplotypes. We thus provided guidance to select individuals for whom sequencing would optimize incompatibility assessment and cost-effectiveness of HLA typing, considering not only well-imputed second field typing(s) but also well-imputed eplets.

A chromosomal-scale genome assembly of modern cultivated hybrid sugarcane provides insights into origination and evolution.

Sugarcane is a vital crop with significant economic and industrial value. However, the cultivated sugarcane's ultra-complex genome still needs to be resolved due to its high ploidy and extensive recombination between the two subgenomes. Here, we generate a chromosomal-scale, haplotype-resolved genome assembly for a hybrid sugarcane cultivar ZZ1. This assembly contains 10.4 Gb genomic sequences and 68,509 annotated genes with defined alleles in two sub-genomes distributed in 99 original and 15 recombined chromosomes. RNA-seq data analysis shows that sugar accumulation-associated gene families have been primarily expanded from the ZZSO subgenome. However, genes responding to pokkah boeng disease susceptibility have been derived dominantly from the ZZSS subgenome. The region harboring the possible smut resistance genes has expanded significantly. Among them, the expansion of WAK and FLS2 families is proposed to have occurred during the breeding of ZZ1. Our findings provide insights into the complex genome of hybrid sugarcane cultivars and pave the way for future genomics and molecular breeding studies in sugarcane.

Investigation of HLA susceptibility alleles and genotypes with hematological disease among Chinese Han population.

Several genes involved in the pathogenesis have been identified, with the human leukocyte antigen (HLA) system playing an essential role. However, the relationship between HLA and a cluster of hematological diseases has received little attention in China. Blood samples (n = 123913) from 43568 patients and 80345 individuals without known pathology were genotyped for HLA class I and II using sequencing-based typing. We discovered that HLA-A*11:01, B*40:01, C*01:02, DQB1*03:01, and DRB1*09:01 were prevalent in China. Furthermore, three high-frequency alleles (DQB1*03:01, DQB1*06:02, and DRB1*15:01) were found to be hazardous in malignant hematologic diseases when compared to controls. In addition, for benign hematologic disorders, 7 high-frequency risk alleles (A*01:01, B*46:01, C*01:02, DQB1*03:03, DQB1*05:02, DRB1*09:01, and DRB1*14:54) and 8 high-frequency susceptible genotypes (A*11:01-A*11:01, B*46:01-B*58:01, B*46:01-B*46:01, C*01:02-C*03:04, DQB1*03:01-DQB1*05:02, DQB1*03:03-DQB1*06:01, DRB1*09:01-DRB1*15:01, and DRB1*14:54-DRB1*15:01) were observed. To summarize, our findings indicate the association between HLA alleles/genotypes and a variety of hematological disorders, which is critical for disease surveillance.

Identifying Causal Genes for Thermo-Responsive Rosette Growth in Arabidopsis by Genome-Wide Association Study.

Temperature responsive plant growth, such as thermo-morphogenesis, varied greatly among Arabidopsis natural accessions. Here we describe a procedure to identify causal genes for thermo-morphogenesis variation by a genome-wide association study (GWAS). It includes methods of measuring thermo-responsive rosette growth architecture, using GWA-Portal webtool for GWAS, analyzing haplotypes, and validating functional natural variations. In addition, we discuss key factors that affect the success of identifying causal genes from GWAS.

Genetic introgression from commercial European pigs to the indigenous Chinese Lijiang breed and associated changes in phenotypes.

BACKGROUND: Gene flow is crucial for enhancing economic traits of livestock. In China, breeders have used hybridization strategies for decades to improve livestock performance. Here, we performed whole-genome sequencing of a native Chinese Lijiang pig (LJP) breed. By integrating previously published data, we explored the genetic structure and introgression of genetic components from commercial European pigs (EP) into the LJP, and examined the impact of this introgression on phenotypic traits. RESULTS: Our analysis revealed significant introgression of EP breeds into the LJP and other domestic pig breeds in China. Using a haplotype-based approach, we quantified introgression levels and compared EP to LJP and other Chinese domestic pigs. The results show that EP introgression is widely prevalent in Chinese domestic pigs, although there are significant differences between breeds. We propose that LJP could potentially act as a mediator for the transmission of EP haplotypes. We also examined the correlation between EP introgression and the number of thoracic vertebrae in LJP and identified VRTN and STUM as candidate genes for this trait. CONCLUSIONS: Our study provides evidence of introgressed European haplotypes in the LJP breed and describes the potential role of EP introgression on phenotypic changes of this indigenous breed.

Haplotype diversity of 17 Y-STR in the Iranian population.

The current study aimed to evaluate Y chromosome haplotypes obtained from 1353 unrelated Iranian males using the AmpFlSTRTM YfilerTM kit; 1353 out of the 1353 identified haplotypes were unique. The haplotype diversity (HD) and discriminating capacity (DC) values were 1.00000 and 0.997, respectively. Analysis of genetic distance was performed using molecular variance (AMOVA) and multidimensional scaling plots (MDS), revealing a statistically significant difference between the study population and previous data reported for other Iranian populations and other neighboring countries. The present findings are likely to be useful for forensic casework analyses and kinship investigations.

Haplotype-resolved genome of Mimosa bimucronata revealed insights into leaf movement and nitrogen fixation.

BACKGROUND: Mimosa bimucronata originates from tropical America and exhibits distinctive leaf movement characterized by a relative slow speed. Additionally, this species possesses the ability to fix nitrogen. Despite these intriguing traits, comprehensive studies have been hindered by the lack of genomic resources for M. bimucronata. RESULTS: To unravel the intricacies of leaf movement and nitrogen fixation, we successfully assembled a high-quality, haplotype-resolved, reference genome at the chromosome level, spanning 648 Mb and anchored in 13 pseudochromosomes. A total of 32,146 protein-coding genes were annotated. In particular, haplotype A was annotated with 31,035 protein-coding genes, and haplotype B with 31,440 protein-coding genes. Structural variations (SVs) and allele specific expression (ASE) analyses uncovered the potential role of structural variants in leaf movement and nitrogen fixation in M. bimucronata. Two whole-genome duplication (WGD) events were detected, that occurred ~ 2.9 and ~ 73.5 million years ago. Transcriptome and co-expression network analyses revealed the involvement of aquaporins (AQPs) and Ca2+-related ion channel genes in leaf movement. Moreover, we also identified nodulation-related genes and analyzed the structure and evolution of the key gene NIN in the process of symbiotic nitrogen fixation (SNF). CONCLUSION: The detailed comparative genomic and transcriptomic analyses provided insights into the mechanisms governing leaf movement and nitrogen fixation in M. bimucronata. This research yielded genomic resources and provided an important reference for functional genomic studies of M. bimucronata and other legume species.

Treatment outcome and germline predictive factors of ropeginterferon alpha-2b in myeloproliferative neoplasm patients.

BACKGROUND: Studies have shown that some single nucleotide polymorphisms (SNPs) could serve as excellent markers in foretelling the treatment outcome of interferon (IFN) in myeloproliferative neoplasms (MPN). However, most work originated from western countries, and data from different ethnic populations have been lacking. METHODS: To gain insights, targeted sequencing was performed to detect myeloid-associated mutations and SNPs in eight loci across three genes (IFNL4, IFN-γ, and inosine triphosphate pyrophosphatase [ITPA]) to explore their predictive roles in our cohort of 21 ropeginterferon alpha-2b (ROPEG)-treated MPN patients, among whom real-time quantitative PCR was also performed periodically to monitor the JAK2V617F allele burden in 19 JAK2V617F-mutated cases. RESULTS: ELN response criteria were adopted to designate patients as good responders if they achieved complete hematological responses (CHR) within 1 year (CHR1) or attained major molecular responses (MMR), which occurred in 70% and 45% of the patients, respectively. IFNL4 and IFN-γ gene SNPs were infrequent in our population and were thus excluded from further analysis. Two ITPA SNPs rs6051702 A>C and rs1127354 C>A were associated with an inferior CHR1 rate and MMR rate, respectively. The former seemed to be linked to grade 2 or worse hepatotoxicity as well, although the comparison was of borderline significance only (50%, vs. 6.7% in those with common haplotype, p = 0.053). Twelve patients harbored 19 additional somatic mutations in 12 genes, but the trajectory of these mutations varied considerably and was not predictive of any response. CONCLUSIONS: Overall, this study provided valuable information on the ethnics- and genetics-based algorithm in the treatment of MPN.

Haplotype function score improves biological interpretation and cross-ancestry polygenic prediction of human complex traits.

We propose a new framework for human genetic association studies: at each locus, a deep learning model (in this study, Sei) is used to calculate the functional genomic activity score for two haplotypes per individual. This score, defined as the Haplotype Function Score (HFS), replaces the original genotype in association studies. Applying the HFS framework to 14 complex traits in the UK Biobank, we identified 3619 independent HFS-trait associations with a significance of p < 5 × 10-8. Fine-mapping revealed 2699 causal associations, corresponding to a median increase of 63 causal findings per trait compared with single-nucleotide polymorphism (SNP)-based analysis. HFS-based enrichment analysis uncovered 727 pathway-trait associations and 153 tissue-trait associations with strong biological interpretability, including 'circadian pathway-chronotype' and 'arachidonic acid-intelligence'. Lastly, we applied least absolute shrinkage and selection operator (LASSO) regression to integrate HFS prediction score with SNP-based polygenic risk scores, which showed an improvement of 16.1-39.8% in cross-ancestry polygenic prediction. We concluded that HFS is a promising strategy for understanding the genetic basis of human complex traits.

Scattered throughout the human genome are variations in the genetic code that make individuals more or less likely to develop certain traits. To identify these variants, scientists carry out Genome-wide association studies (GWAS) which compare the DNA variants of large groups of people with and without the trait of interest. This method has been able to find the underlying genes for many human diseases, but it has limitations. For instance, some variations are linked together due to where they are positioned within DNA, which can result in GWAS falsely reporting associations between genetic variants and traits. This phenomenon, known as linkage equilibrium, can be avoided by analyzing functional genomics which looks at the multiple ways a gene's activity can be influenced by a variation. For instance, how the gene is copied and decoded in to proteins and RNA molecules, and the rate at which these products are generated. Researchers can now use an artificial intelligence technique called deep learning to generate functional genomic data from a particular DNA sequence. Here, Song et al. used one of these deep learning models to calculate the functional genomics of haplotypes, groups of genetic variants inherited from one parent. The approach was applied to DNA samples from over 350 thousand individuals included in the UK BioBank. An activity score, defined as the haplotype function score (or HFS for short), was calculated for at least two haplotypes per individual, and then compared to various complex traits like height or bone density. Song et al. found that the HFS framework was better at finding links between genes and specific traits than existing methods. It also provided more information on the biology that may be underpinning these outcomes. Although more work is needed to reduce the computer processing times required to calculate the HFS, Song et al. believe that their new method has the potential to improve the way researchers identify links between genes and human traits.

Genetic Analysis of 27 Y-STR Haplotypes in 11 Iranian Ethnic Groups.

BACKGROUND: The study of Y-chromosomal variations provides valuable insights into male susceptibility in certain diseases like cardiovascular disease (CVD). In this study, we analyzed paternal lineage in different Iranian ethnic groups, not only to identify developing medical etiology, but also to pave the way for gender-specific targeted strategies and personalized medicine in medical genetic research studies. METHODS: The diversity of eleven Iranian ethnic groups was studied using 27 Y-chromosomal short tandem repeat (Y-STR) haplotypes from Y-filer® Plus kit. Analysis of molecular variance (AMOVA) based on pair-wise RST along with multidimensional scaling (MDS) calculation and Network phylogenic analysis was employed to quantify the differences between 503 unrelated individuals from each ethnicity. RESULTS: Results from AMOVA calculation confirmed that Gilaks and Azeris showed the largest genetic distance (RST=0.35434); however, Sistanis and Lurs had the smallest considerable genetic distance (RST=0.00483) compared to other ethnicities. Although Azeris had a considerable distance from other ethnicities, they were still close to Turkmens. MDS analysis of ethnic groups gave the indication of lack of similarity between different ethnicities. Besides, network phylogenic analysis demonstrated insignificant clustering between samples. CONCLUSION: The AMOVA analysis results explain that the close distance of Azeris and Turkmens may be the effect of male-dominant expansions across Central Asia that contributed to historical and demographics of populations in the region. Insignificant differences in network analysis could be the consequence of high mutation events that happened in the Y-STR regions over the years. Considering the ethnic group affiliations in medical research, our results provided an understanding and characterization of Iranian male population for future medical and population genetics studies.

PyPop: a mature open-source software pipeline for population genomics.

Python for Population Genomics (PyPop) is a software package that processes genotype and allele data and performs large-scale population genetic analyses on highly polymorphic multi-locus genotype data. In particular, PyPop tests data conformity to Hardy-Weinberg equilibrium expectations, performs Ewens-Watterson tests for selection, estimates haplotype frequencies, measures linkage disequilibrium, and tests significance. Standardized means of performing these tests is key for contemporary studies of evolutionary biology and population genetics, and these tests are central to genetic studies of disease association as well. Here, we present PyPop 1.0.0, a new major release of the package, which implements new features using the more robust infrastructure of GitHub, and is distributed via the industry-standard Python Package Index. New features include implementation of the asymmetric linkage disequilibrium measures and, of particular interest to the immunogenetics research communities, support for modern nomenclature, including colon-delimited allele names, and improvements to meta-analysis features for aggregating outputs for multiple populations. Code available at: https://zenodo.org/records/10080668 and https://github.com/alexlancaster/pypop.

Influence of novel CYP2C-haplotype on proton pump inhibitor pharmacokinetics in children.

In this brief report, we provide an analysis of the influence of a novel CYP2C haplotype (CYP2C:TG) on proton pump inhibitor (PPI) pharmacokinetics (PK) in children. The CYP2C:TG haplotype has been proposed to be associated with increased CYP2C19 activity. We sought to determine if this CYP2C:TG haplotype resulted in similar alterations in metabolism for proton pump inhibitors, which are primarily metabolized by CYP2C19. In a cohort of 41 children aged 6-21 participating in a PPI pharmacokinetic study, effects of the CYP2C:TG allele were assessed by fitting two linear regression models for each of the six PK outcomes assessed, the second of which accounted for the presence of the CYP2C:TG allele. The difference in R2 values between the two models was computed to quantify the variability in the outcome that could be accounted for by the CYP2C:TG allele after adjustment for the CYP2C19 genotype. We found the CYP2C:TG haplotype to have no measurable additive impact on CYP2C19-mediated metabolism of PPIs in vivo in older children and adolescents. The findings of this study do not support the clinical utility of routine testing for the CYP2C:TG haplotype to guide PPI dose adjustments in children.

MAPT H2 haplotype and risk of Pick's disease in the Pick's disease International Consortium: a genetic association study.

BACKGROUND: Pick's disease is a rare and predominantly sporadic form of frontotemporal dementia that is classified as a primary tauopathy. Pick's disease is pathologically defined by the presence in the frontal and temporal lobes of Pick bodies, composed of hyperphosphorylated, three-repeat tau protein, encoded by the MAPT gene. MAPT has two distinct haplotypes, H1 and H2; the MAPT H1 haplotype is the major genetic risk factor for four-repeat tauopathies (eg, progressive supranuclear palsy and corticobasal degeneration), and the MAPT H2 haplotype is protective for these disorders. The primary aim of this study was to evaluate the association of MAPT H2 with Pick's disease risk, age at onset, and disease duration. METHODS: In this genetic association study, we used data from the Pick's disease International Consortium, which we established to enable collection of data from individuals with pathologically confirmed Pick's disease worldwide. For this analysis, we collected brain samples from individuals with pathologically confirmed Pick's disease from 35 sites (brainbanks and hospitals) in North America, Europe, and Australia between Jan 1, 2020, and Jan 31, 2023. Neurologically healthy controls were recruited from the Mayo Clinic (FL, USA, or MN, USA between March 1, 1998, and Sept 1, 2019). For the primary analysis, individuals were directly genotyped for the MAPT H1-H2 haplotype-defining variant rs8070723. In a secondary analysis, we genotyped and constructed the six-variant-defined (rs1467967-rs242557-rs3785883-rs2471738-rs8070723-rs7521) MAPT H1 subhaplotypes. Associations of MAPT variants and MAPT haplotypes with Pick's disease risk, age at onset, and disease duration were examined using logistic and linear regression models; odds ratios (ORs) and ß coefficients were estimated and correspond to each additional minor allele or each additional copy of the given haplotype. FINDINGS: We obtained brain samples from 338 people with pathologically confirmed Pick's disease (205 [61%] male and 133 [39%] female; 338 [100%] White) and 1312 neurologically healthy controls (611 [47%] male and 701 [53%] female; 1312 [100%] White). The MAPT H2 haplotype was associated with increased risk of Pick's disease compared with the H1 haplotype (OR 1·35 [95% CI 1·12 to 1·64], p=0·0021). MAPT H2 was not associated with age at onset (ß -0·54 [95% CI -1·94 to 0·87], p=0·45) or disease duration (ß 0·05 [-0·06 to 0·16], p=0·35). Although not significant after correcting for multiple testing, associations were observed at p less than 0·05: with risk of Pick's disease for the H1f subhaplotype (OR 0·11 [0·01 to 0·99], p=0·049); with age at onset for H1b (ß 2·66 [0·63 to 4·70], p=0·011), H1i (ß -3·66 [-6·83 to -0·48], p=0·025), and H1u (ß -5·25 [-10·42 to -0·07], p=0·048); and with disease duration for H1x (ß -0·57 [-1·07 to -0·07], p=0·026). INTERPRETATION: The Pick's disease International Consortium provides an opportunity to do large studies to enhance our understanding of the pathobiology of Pick's disease. This study shows that, in contrast to the decreased risk of four-repeat tauopathies, the MAPT H2 haplotype is associated with an increased risk of Pick's disease in people of European ancestry. This finding could inform development of isoform-related therapeutics for tauopathies. FUNDING: Wellcome Trust, Rotha Abraham Trust, Brain Research UK, the Dolby Fund, Dementia Research Institute (Medical Research Council), US National Institutes of Health, and the Mayo Clinic Foundation.

Identification of superior and rare haplotypes to optimize branch number in soybean.

KEY MESSAGE: Using the integrated approach in the present study, we identified eleven significant SNPs, seven stable QTLs and 20 candidate genes associated with branch number in soybean. Branch number is a key yield-related quantitative trait that directly affects the number of pods and seeds per soybean plant. In this study, an integrated approach with a genome-wide association study (GWAS) and haplotype and candidate gene analyses was used to determine the detailed genetic basis of branch number across a diverse set of soybean accessions. The GWAS revealed a total of eleven SNPs significantly associated with branch number across three environments using the five GWAS models. Based on the consistency of the SNP detection in multiple GWAS models and environments, seven genomic regions within the physical distance of ± 202.4 kb were delineated as stable QTLs. Of these QTLs, six QTLs were novel, viz., qBN7, qBN13, qBN16, qBN18, qBN19 and qBN20, whereas the remaining one, viz., qBN12, has been previously reported. Moreover, 11 haplotype blocks, viz., Hap4, Hap7, Hap12, Hap13A, Hap13B, Hap16, Hap17, Hap18, Hap19A, Hap19B and Hap20, were identified on nine different chromosomes. Haplotype allele number across the identified haplotype blocks varies from two to five, and different branch number phenotype is regulated by these alleles ranging from the lowest to highest through intermediate branching. Furthermore, 20 genes were identified underlying the genomic region of ± 202.4 kb of the identified SNPs as putative candidates; and six of them showed significant differential expression patterns among the soybean cultivars possessing contrasting branch number, which might be the potential candidates regulating branch number in soybean. The findings of this study can assist the soybean breeding programs for developing cultivars with desirable branch numbers.

The effects of ANRIL polymorphisms on colorectal cancer, tumor stage, and tumor grade among Iranian population.

BACKGROUND: Colorectal cancer (CRC) is a type of neoplasm, developing in the colon or rectum. The exact etiology of CRC is not well known, but the role of genetic, epigenetic, and environmental factors are established in its pathogenesis. Therefore, the aim of this research was to explore the effects of ANRIL polymorphisms on the CRC and its clinical findings. METHODS AND RESULTS: The peripheral blood specimens were collected from 142 CRC patients and 225 controls referred to Milad Hospital, Tehran, Iran. PCR- RFLP method was used to analyze ANRIL rs1333040, rs10757274 rs4977574, and rs1333048 polymorphisms. The ANRIL rs1333040 polymorphism was related to a higher risk of CRC in the co-dominant, dominant, and log-additive models. ANRIL rs10757274, rs4977574, and rs1333048 polymorphisms showed no effect on CRC susceptibility. The CGAA and TGGA haplotypes of ANRIL rs1333040/ rs10757274/ rs4977574/rs1333048 polymorphisms were associated with the higher and the lower risk of CRC respectively. The rs1333040 polymorphism was associated with higher TNM stages (III and IV). The frequency of ANRIL rs10757274 polymorphism was lower in CRC patients over 50 years of age only in the dominant model. In addition, the rs10757274 was associated with well differentiation in CRC patients. CONCLUSION: The ANRIL rs1333040 polymorphism was associated with a higher risk of CRC and higher TNM stages. ANRIL rs10757274 polymorphism was associated with the well-differentiated tumor in CRC.

Haplotype-resolved assembly of auto-polyploid genomes via combining Hi-C and gametic data.

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.