The impact of using related individuals for haplotype reconstruction in population studies

Recent studies have highlighted the dangers of using haplotypes reconstructed directly from population data for a fine-scale mapping analysis. Family data may help resolve ambiguity, yet can be costly to obtain. This study is concerned with the following question: How much family data (if any) should be used to facilitate haplotype reconstruction in a population study? We conduct a simulation study to evaluate how changes in family information can affect the accuracy of haplotype frequency estimates and phase reconstruction. To reconstruct haplotypes, we introduce an EM-based algorithm that can efficiently accommodate unrelated individuals, parent-child trios, and arbitrarily large half-sib pedigrees. Simulations are conducted for a diverse set of haplotype frequency distributions, all of which have been previously published in empirical studies. A wide variety of important results regarding the effectiveness of using pedigree data in a population study are presented in a coherent, unified framework. Insight into the different properties of the haplotype frequency distribution that can influence experimental design is provided. We show that a preliminary estimate of the haplotype frequency distribution can be valuable in large population studies with fixed resources.     

Inference of Chromosome-Length Haplotypes Using Genomic Data of Three or a Few More Single Gametes

Compared with genomic data of individual markers, haplotype data provide higher resolution for DNA variants, advancing our knowledge in genetics and evolution. Although many computational and experimental phasing methods have been developed for analyzing diploid genomes, it remains challenging to reconstruct chromosome-scale haplotypes at low cost, which constrains the utility of this valuable genetic resource. Gamete cells, the natural packaging of haploid complements, are ideal materials for phasing entire chromosomes because the majority of the haplotypic allele combinations has been preserved. Therefore, compared with the current diploid-based phasing methods, using haploid genomic data of single gametes may substantially reduce the complexity in inferring the donor’s chromosomal haplotypes. In this study, we developed the first easy-to-use R package, Hapi, for inferring chromosome-length haplotypes of individual diploid genomes with only a few gametes. Hapi outperformed other phasing methods when analyzing both simulated and real single gamete cell sequencing data sets. The results also suggested that chromosome-scale haplotypes may be inferred by using as few as three gametes, which has pushed the boundary to its possible limit. The single gamete cell sequencing technology allied with the cost-effective Hapi method will make large-scale haplotype-based genetic studies feasible and affordable, promoting the use of haplotype data in a wide range of research.     

HapTree: A Novel Bayesian Framework for Single Individual Polyplotyping Using NGS Data

As the more recent next-generation sequencing (NGS) technologies provide longer read sequences, the use of sequencing datasets for complete haplotype phasing is fast becoming a reality, allowing haplotype reconstruction of a single sequenced genome. Nearly all previous haplotype reconstruction studies have focused on diploid genomes and are rarely scalable to genomes with higher ploidy. Yet computational investigations into polyploid genomes carry great importance, impacting plant, yeast and fish genomics, as well as the studies of the evolution of modern-day eukaryotes and (epi)genetic interactions between copies of genes. In this paper, we describe a novel maximum-likelihood estimation framework, HapTree, for polyploid haplotype assembly of an individual genome using NGS read datasets. We evaluate the performance of HapTree on simulated polyploid sequencing read data modeled after Illumina sequencing technologies. For triploid and higher ploidy genomes, we demonstrate that HapTree substantially improves haplotype assembly accuracy and efficiency over the state-of-the-art; moreover, HapTree is the first scalable polyplotyping method for higher ploidy. As a proof of concept, we also test our method on real sequencing data from NA12878 (1000 Genomes Project) and evaluate the quality of assembled haplotypes with respect to trio-based diplotype annotation as the ground truth. The results indicate that HapTree significantly improves the switch accuracy within phased haplotype blocks as compared to existing haplotype assembly methods, while producing comparable minimum error correction (MEC) values. A summary of this paper appears in the proceedings of the RECOMB 2014 conference, April 2–5.     

Efficient algorithms for polyploid haplotype phasing

Background

Inference of haplotypes, or the sequence of alleles along the same chromosomes, is a fundamental problem in genetics and is a key component for many analyses including admixture mapping, identifying regions of identity by descent and imputation. Haplotype phasing based on sequencing reads has attracted lots of attentions. Diploid haplotype phasing where the two haplotypes are complimentary have been studied extensively. In this work, we focused on Polyploid haplotype phasing where we aim to phase more than two haplotypes at the same time from sequencing data. The problem is much more complicated as the search space becomes much larger and the haplotypes do not need to be complimentary any more.

Results

We proposed two algorithms, (1) Poly-Harsh, a Gibbs Sampling based algorithm which alternatively samples haplotypes and the read assignments to minimize the mismatches between the reads and the phased haplotypes, (2) An efficient algorithm to concatenate haplotype blocks into contiguous haplotypes.

Conclusions

Our experiments showed that our method is able to improve the quality of the phased haplotypes over the state-of-the-art methods. To our knowledge, our algorithm for haplotype blocks concatenation is the first algorithm that leverages the shared information across multiple individuals to construct contiguous haplotypes. Our experiments showed that it is both efficient and effective.

     

HaploRec: efficient and accurate large-scale reconstruction of haplotypes

Background  

Haplotypes extracted from human DNA can be used for gene mapping and other analysis of genetic patterns within and across populations. A fundamental problem is, however, that current practical laboratory methods do not give haplotype information. Estimation of phased haplotypes of unrelated individuals given their unphased genotypes is known as the haplotype reconstruction or phasing problem.     

Linkage disequilibrium between mutation and RFLP haplotype at the phenylalanine hydroxylase locus in the German population

Summary Restriction fragment length polymorphism (RFLP) haplotypes at the phenylalanine hydroxylase (PAH) locus have been determined in 60 German families with PAH deficiency. Similar to the Danish population, about 90% of the mutant alleles are confined to four distinct haplotypes. There are however, differences in the frequency distributiion of these haplotypes among the mutant alleles between the two populations. Using an oligonucleotide probe for the splicing mutation associated with mutant haplotype 3 in the Danish population, a tight association between the mutation and the RFLP haplotype has also been observed in Germany. The results provide strong evidence that the splicing mutation occurred on a haplotype 3 chromosome and that the mutant allele has spread into different populations smong Caucasians.     

Linked‐read sequencing enables haplotype‐resolved resequencing at population scale

The feasibility to sequence entire genomes of virtually any organism provides unprecedented insights into the evolutionary history of populations and species. Nevertheless, many population genomic inferences – including the quantification and dating of admixture, introgression and demographic events, and inference of selective sweeps – are still limited by the lack of high‐quality haplotype information. The newest generation of sequencing technology now promises significant progress. To establish the feasibility of haplotype‐resolved genome resequencing at population scale, we investigated properties of linked‐read sequencing data of songbirds of the genus Oenanthe across a range of sequencing depths. Our results based on the comparison of downsampled (25×, 20×, 15×, 10×, 7×, and 5×) with high‐coverage data (46–68×) of seven bird genomes mapped to a reference suggest that phasing contiguities and accuracies adequate for most population genomic analyses can be reached already with moderate sequencing effort. At 15× coverage, phased haplotypes span about 90% of the genome assembly, with 50% and 90% of phased sequences located in phase blocks longer than 1.25–4.6 Mb (N50) and 0.27–0.72 Mb (N90). Phasing accuracy reaches beyond 99% starting from 15× coverage. Higher coverages yielded higher contiguities (up to about 7 Mb/1 Mb [N50/N90] at 25× coverage), but only marginally improved phasing accuracy. Phase block contiguity improved with input DNA molecule length; thus, higher‐quality DNA may help keeping sequencing costs at bay. In conclusion, even for organisms with gigabase‐sized genomes like birds, linked‐read sequencing at moderate depth opens an affordable avenue towards haplotype‐resolved genome resequencing at population scale.     

Towards accurate,contiguous and complete alignment-based polyploid phasing algorithms

Phasing, and in particular polyploid phasing, have been challenging problems held back by the limited read length of high-throughput short read sequencing methods which can't overcome the distance between heterozygous sites and labor high cost of alternative methods such as the physical separation of chromosomes for example. Recently developed single molecule long-read sequencing methods provide much longer reads which overcome this previous limitation. Here we review the alignment-based methods of polyploid phasing that rely on four main strategies: population inference methods, which leverage the genetic information of several individuals to phase a sample; objective function minimization methods, which minimize a function such as the Minimum Error Correction (MEC); graph partitioning methods, which represent the read data as a graph and split it into k haplotype subgraphs; cluster building methods, which iteratively grow clusters of similar reads into a final set of clusters that represent the haplotypes. We discuss the advantages and limitations of these methods and the metrics used to assess their performance, proposing that accuracy and contiguity are the most meaningful metrics. Finally, we propose the field of alignment-based polyploid phasing would greatly benefit from the use of a well-designed benchmarking dataset with appropriate evaluation metrics. We consider that there are still significant improvements which can be achieved to obtain more accurate and contiguous polyploid phasing results which reflect the complexity of polyploid genome architectures.     

Haplotype Estimation Using Sequencing Reads

High-throughput sequencing technologies produce short sequence reads that can contain phase information if they span two or more heterozygote genotypes. This information is not routinely used by current methods that infer haplotypes from genotype data. We have extended the SHAPEIT2 method to use phase-informative sequencing reads to improve phasing accuracy. Our model incorporates the read information in a probabilistic model through base quality scores within each read. The method is primarily designed for high-coverage sequence data or data sets that already have genotypes called. One important application is phasing of single samples sequenced at high coverage for use in medical sequencing and studies of rare diseases. Our method can also use existing panels of reference haplotypes. We tested the method by using a mother-father-child trio sequenced at high-coverage by Illumina together with the low-coverage sequence data from the 1000 Genomes Project (1000GP). We found that use of phase-informative reads increases the mean distance between switch errors by 22% from 274.4 kb to 328.6 kb. We also used male chromosome X haplotypes from the 1000GP samples to simulate sequencing reads with varying insert size, read length, and base error rate. When using short 100 bp paired-end reads, we found that using mixtures of insert sizes produced the best results. When using longer reads with high error rates (5–20 kb read with 4%–15% error per base), phasing performance was substantially improved.     

Identity by descent mapping of founder mutations in cancer using high-resolution tumor SNP data

Dense genotype data can be used to detect chromosome fragments inherited from a common ancestor in apparently unrelated individuals. A disease-causing mutation inherited from a common founder may thus be detected by searching for a common haplotype signature in a sample population of patients. We present here FounderTracker, a computational method for the genome-wide detection of founder mutations in cancer using dense tumor SNP profiles. Our method is based on two assumptions. First, the wild-type allele frequently undergoes loss of heterozygosity (LOH) in the tumors of germline mutation carriers. Second, the overlap between the ancestral chromosome fragments inherited from a common founder will define a minimal haplotype conserved in each patient carrying the founder mutation. Our approach thus relies on the detection of haplotypes with significant identity by descent (IBD) sharing within recurrent regions of LOH to highlight genomic loci likely to harbor a founder mutation. We validated this approach by analyzing two real cancer data sets in which we successfully identified founder mutations of well-characterized tumor suppressor genes. We then used simulated data to evaluate the ability of our method to detect IBD tracts as a function of their size and frequency. We show that FounderTracker can detect haplotypes of low prevalence with high power and specificity, significantly outperforming existing methods. FounderTracker is thus a powerful tool for discovering unknown founder mutations that may explain part of the "missing" heritability in cancer. This method is freely available and can be used online at the FounderTracker website.     

Footprints of adaptive evolution revealed by whole Z chromosomes haplotypes in flycatchers

Detecting positive selection using genomic data is critical to understanding the role of adaptive evolution. Of particular interest in this context is sex chromosomes since they are thought to play a special role in local adaptation and speciation. We sought to circumvent the challenges associated with statistical phasing when using haplotype‐based statistics in sweep scans by benefitting from that whole chromosome haplotypes of the sex chromosomes can be obtained by resequencing of individuals of the hemizygous sex. We analyzed whole Z chromosome haplotypes from 100 females from several populations of four black and white flycatcher species (in birds, females are ZW and males ZZ). Based on integrated haplotype score (iHS) and number of segregating sites by length (nSL) statistics, we found strong and frequent haplotype structure in several regions of the Z chromosome in each species. Most of these sweep signals were population‐specific, with essentially no evidence for regions under selection shared among species. Some completed sweeps were revealed by the cross‐population extended haplotype homozygosity (XP‐EHH) statistic. Importantly, by using statistically phased Z chromosome data from resequencing of males, we failed to recover the signals of selection detected in analyses based on whole chromosome haplotypes from females; instead, what likely represent false signals of selection were frequently seen. This highlights the power issues in statistical phasing and cautions against conclusions from selection scans using such data. The detection of frequent selective sweeps on the avian Z chromosome supports a large role of sex chromosomes in adaptive evolution.     

Haplotype reconstruction in connected tetraploid F1 populations

In diploid species, many multiparental populations have been developed to increase genetic diversity and quantitative trait loci (QTL) mapping resolution. In these populations, haplotype reconstruction has been used as a standard practice to increase the power of QTL detection in comparison with the marker-based association analysis. However, such software tools for polyploid species are few and limited to a single biparental F1 population. In this study, a statistical framework for haplotype reconstruction has been developed and implemented in the software PolyOrigin for connected tetraploid F1 populations with shared parents, regardless of the number of parents or mating design. Given a genetic or physical map of markers, PolyOrigin first phases parental genotypes, then refines the input marker map, and finally reconstructs offspring haplotypes. PolyOrigin can utilize single nucleotide polymorphism (SNP) data coming from arrays or from sequence-based genotyping; in the latter case, bi-allelic read counts can be used (and are preferred) as input data to minimize the influence of genotype calling errors at low depth. With extensive simulation we show that PolyOrigin is robust to the errors in the input genotypic data and marker map. It works well for various population designs with ≥30 offspring per parent and for sequences with read depth as low as 10x. PolyOrigin was further evaluated using an autotetraploid potato dataset with a 3 × 3 half-diallel mating design. In conclusion, PolyOrigin opens up exciting new possibilities for haplotype analysis in tetraploid breeding populations.     

Viral Quasispecies Assembly via Maximal Clique Enumeration

Virus populations can display high genetic diversity within individual hosts. The intra-host collection of viral haplotypes, called viral quasispecies, is an important determinant of virulence, pathogenesis, and treatment outcome. We present HaploClique, a computational approach to reconstruct the structure of a viral quasispecies from next-generation sequencing data as obtained from bulk sequencing of mixed virus samples. We develop a statistical model for paired-end reads accounting for mutations, insertions, and deletions. Using an iterative maximal clique enumeration approach, read pairs are assembled into haplotypes of increasing length, eventually enabling global haplotype assembly. The performance of our quasispecies assembly method is assessed on simulated data for varying population characteristics and sequencing technology parameters. Owing to its paired-end handling, HaploClique compares favorably to state-of-the-art haplotype inference methods. It can reconstruct error-free full-length haplotypes from low coverage samples and detect large insertions and deletions at low frequencies. We applied HaploClique to sequencing data derived from a clinical hepatitis C virus population of an infected patient and discovered a novel deletion of length 357±167 bp that was validated by two independent long-read sequencing experiments. HaploClique is available at https://github.com/armintoepfer/haploclique. A summary of this paper appears in the proceedings of the RECOMB 2014 conference, April 2-5.     

High rates of phasing errors in highly polymorphic species with low levels of linkage disequilibrium

Short read sequencing of diploid individuals does not permit the direct inference of the sequence on each of the two homologous chromosomes. Although various phasing software packages exist, they were primarily tailored for and tested on human data, which differ from other species in factors that influence phasing, such as SNP density, amounts of linkage disequilibrium (LD) and sample sizes. Despite becoming increasingly popular for other species, the reliability of phasing in non‐human data has not been evaluated to a sufficient extent. We scrutinized the phasing accuracy for Drosophila melanogaster, a species with high polymorphism levels and reduced LD relative to humans. We phased two D. melanogaster populations and compared the results to the known haplotypes. The performance increased with size of the reference panel and was highest when the reference panel and phased individuals were from the same population. Full genomic SNP data and inclusion of sequence read information also improved phasing. Despite humans and Drosophila having similar switch error rates between polymorphic sites, the distances between switch errors were much shorter in Drosophila with only fragments <300–1500 bp being correctly phased with ≥95% confidence. This suggests that the higher SNP density cannot compensate for the higher recombination rate in D. melanogaster. Furthermore, we show that populations that have gone through demographic events such as bottlenecks can be phased with higher accuracy. Our results highlight that statistically phased data are particularly error prone in species with large population sizes or populations lacking suitable reference panels.     

HAPLOPOOL: improving haplotype frequency estimation through DNA pools and phylogenetic modeling

MOTIVATION: The search for genetic variants that are linked to complex diseases such as cancer, Parkinson's;, or Alzheimer's; disease, may lead to better treatments. Since haplotypes can serve as proxies for hidden variants, one method of finding the linked variants is to look for case-control associations between the haplotypes and disease. Finding these associations requires a high-quality estimation of the haplotype frequencies in the population. To this end, we present, HaploPool, a method of estimating haplotype frequencies from blocks of consecutive SNPs. RESULTS: HaploPool leverages the efficiency of DNA pools and estimates the population haplotype frequencies from pools of disjoint sets, each containing two or three unrelated individuals. We study the trade-off between pooling efficiency and accuracy of haplotype frequency estimates. For a fixed genotyping budget, HaploPool performs favorably on pools of two individuals as compared with a state-of-the-art non-pooled phasing method, PHASE. Of independent interest, HaploPool can be used to phase non-pooled genotype data with an accuracy approaching that of PHASE. We compared our algorithm to three programs that estimate haplotype frequencies from pooled data. HaploPool is an order of magnitude more efficient (at least six times faster), and considerably more accurate than previous methods. In contrast to previous methods, HaploPool performs well with missing data, genotyping errors and long haplotype blocks (of between 5 and 25 SNPs).     

A global survey of haplotype frequencies and linkage disequilibrium at the DRD2 locus

A four-site haplotype system at the dopamine D2 receptor locus (DRD2) has been studied in a global sample of 28 distinct populations. The haplotype system spans about 25 kb, encompassing the coding region of the gene. The four individual markers include three TaqI restriction site polymorphisms (RSPs) – TaqI “A”, “B”, and “D” sites – and one dinucleotide short tandem repeat polymorphism (STRP). All four of the marker systems are polymorphic in all regions of the world and in most individual populations. The haplotype system shows the highest average heterozygosity in Africa, a slightly lower average heterozygosity in Europe, and the lowest average heterozygosities in East Asia and the Americas. Across all populations, 20 of the 48 possible haplotypes reached a frequency of at least 5% in at least one population sample. However, no single population had more than six haplotypes reaching that frequency. In general, African populations had more haplotypes present in each population and more haplotypes occurring at a frequency of at least 5% in that population. Permutation tests for significance of overall disequilibrium (all sites considered simultaneously) were highly significant (P<0.001) in all 28 populations. Except for three African samples, the pairwise disequilibrium between the outermost RSP markers, TaqI “B” and “A”, was highly significant with D’ values greater than 0.8; in two of those exceptions the RSP marker was not polymorphic. Except for those same two African populations, the 16-repeat allele at the STRP also showed highly significant disequilibrium with the TaqI “B” site in all populations, with D’ values usually greater than 0.7. Only four haplotypes account for more than 70% of all chromosomes in virtually all non-African populations, and two of those haplotypes account for more than 70% of all chromosomes in most East Asian and Amerindian populations. A new measure of the amount of overall disequilibrium shows least disequilibrium in African populations, somewhat more in European populations, and the greatest amount in East Asian and Amerindian populations. This pattern seems best explained by random genetic drift with low levels of recombination, a low mutation rate at the STRP, and essentially no recurrent mutation at the RSP sites, all in conjunction with an “Out of Africa” model for recent human evolution. Received: 14 January 1998 / Accepted 19 March 1998     

Experimental generation of SNP haplotype signatures in patients with sickle cell anaemia

Background

Sickle cell anemia is caused by a single type of mutation, a homozygous A→T substitution in the ß globin gene. Clinical severity is diverse, partially due to additional, disease-modifying genetic factors. We are studying one such modifier locus, HMIP (HBS1L-MYB intergenic polymorphism, chromosome 6q23.3). Working with a genetically admixed patient population, we have encountered the necessity to generate haplotype signatures of genetic markers to label genomic fragments with distinct genealogical origin at this locus. With the goal to generate haplotype signatures from patients experimentally, we have investigated the suitability of an existing nanofluidic assay platform to perform phase alignment with single-nucleotide polymorphism alleles.

Methodology/Principal Findings

Patient DNA samples were loaded onto Fluidigm Digital Arrays and individual DNA molecules were assayed with allele-specific probes for SNP markers. Here we present data showing the utility of the nanofluidic approach, yielding haplotype data identical to those obtained with a family-based method. We then determined haplotype composition in a group of patients with sickle cell disease, including in those where a mathematical inference approach gave ambiguous or misleading results. Experimental phasing of genotypes across 3.8 kb for rs9399137, rs9402685, and rs11759553 created unequivocal haplotype signatures for each of the patients. In 68 patients, we found 8 copies of a haplotype signature (‘C-C-T’), which is known to be prevalent in Europeans but to be absent in West African populations. We have confirmed the identity of our phased allele pairs by single-molecule sequencing and have demonstrated, in principle, that three-allele phasing (using three colors) is a potential extension to this method.

Conclusions/Significance

Phased haplotypes yield more information than the individual marker genotypes. Procedures such as the one described here would therefore benefit genetic mapping and functional studies as well as diagnostic procedures where the identity or parental origin of short genetic fragments is of importance.     

Hap-seqX: Expedite algorithm for haplotype phasing with imputation using sequence data

Haplotype phasing is one of the most important problems in population genetics as haplotypes can be used to estimate the relatedness of individuals and to impute genotype information which is a commonly performed analysis when searching for variants involved in disease. The problem of haplotype phasing has been well studied. Methodologies for haplotype inference from sequencing data either combine a set of reference haplotypes and collected genotypes using a Hidden Markov Model or assemble haplotypes by overlapping sequencing reads. A recent algorithm Hap-seq considers using both sequencing data and reference haplotypes and it is a hybrid of a dynamic programming algorithm and a Hidden Markov Model (HMM), which is shown to be optimal. However, the algorithm requires extremely large amount of memory which is not practical for whole genome datasets. The current algorithm requires saving intermediate results to disk and reads these results back when needed, which significantly affects the practicality of the algorithm. In this work, we proposed the expedited version of the algorithm Hap-seqX, which addressed the memory issue by using a posterior probability to select the records that should be saved in memory. We show that Hap-seqX can save all the intermediate results in memory and improves the execution time of the algorithm dramatically. Utilizing the strategy, Hap-seqX is able to predict haplotypes from whole genome sequencing data.     

Ancestral haplotype reconstruction in endogamous populations using identity-by-descent

In this work we develop a novel algorithm for reconstructing the genomes of ancestral individuals, given genotype or sequence data from contemporary individuals and an extended pedigree of family relationships. A pedigree with complete genomes for every individual enables the study of allele frequency dynamics and haplotype diversity across generations, including deviations from neutrality such as transmission distortion. When studying heritable diseases, ancestral haplotypes can be used to augment genome-wide association studies and track disease inheritance patterns. The building blocks of our reconstruction algorithm are segments of Identity-By-Descent (IBD) shared between two or more genotyped individuals. The method alternates between identifying a source for each IBD segment and assembling IBD segments placed within each ancestral individual. Unlike previous approaches, our method is able to accommodate complex pedigree structures with hundreds of individuals genotyped at millions of SNPs.We apply our method to an Old Order Amish pedigree from Lancaster, Pennsylvania, whose founders came to North America from Europe during the early 18th century. The pedigree includes 1338 individuals from the past 12 generations, 394 with genotype data. The motivation for reconstruction is to understand the genetic basis of diseases segregating in the family through tracking haplotype transmission over time. Using our algorithm thread, we are able to reconstruct an average of 224 ancestral individuals per chromosome. For these ancestral individuals, on average we reconstruct 79% of their haplotypes. We also identify a region on chromosome 16 that is difficult to reconstruct—we find that this region harbors a short Amish-specific copy number variation and the gene HYDIN. thread was developed for endogamous populations, but can be applied to any extensive pedigree with the recent generations genotyped. We anticipate that this type of practical ancestral reconstruction will become more common and necessary to understand rare and complex heritable diseases in extended families.     

Reconstruction of Microbial Haplotypes by Integration of Statistical and Physical Linkage in Scaffolding

DNA sequencing technologies provide unprecedented opportunities to analyze within-host evolution of microorganism populations. Often, within-host populations are analyzed via pooled sequencing of the population, which contains multiple individuals or “haplotypes.” However, current next-generation sequencing instruments, in conjunction with single-molecule barcoded linked-reads, cannot distinguish long haplotypes directly. Computational reconstruction of haplotypes from pooled sequencing has been attempted in virology, bacterial genomics, metagenomics, and human genetics, using algorithms based on either cross-host genetic sharing or within-host genomic reads. Here, we describe PoolHapX, a flexible computational approach that integrates information from both genetic sharing and genomic sequencing. We demonstrated that PoolHapX outperforms state-of-the-art tools tailored to specific organismal systems, and is robust to within-host evolution. Importantly, together with barcoded linked-reads, PoolHapX can infer whole-chromosome-scale haplotypes from 50 pools each containing 12 different haplotypes. By analyzing real data, we uncovered dynamic variations in the evolutionary processes of within-patient HIV populations previously unobserved in single position-based analysis.