Haplotype Phasing Research Articles

Haplotype phasing of CYP2D6: an allelic ratio method using Agena MassARRAY data

Pharmacogenomics aims to use the genetic information of an individual to personalize drug prescribing. There is evidence that pharmacogenomic testing before prescription may prevent adverse drug reactions, increase efficacy, and reduce cost of treatment. CYP2D6 is a key pharmacogene of relevance to multiple therapeutic areas. Indeed, there are prescribing guidelines available for medications based on CYP2D6 enzyme activity as deduced from CYP2D6 genetic data. The Agena MassARRAY system is a cost-effective method of detecting genetic variation that has been clinically applied to other genes. However, its clinical application to CYP2D6 has to date been limited by weaknesses such as the inability to determine which haplotype was present in more than one copy for individuals with more than two copies of the CYP2D6 gene. We report application of a new protocol for CYP2D6 haplotype phasing of data generated from the Agena MassARRAY system. For samples with more than two copies of the CYP2D6 gene for which the prior consensus data specified which one was present in more than one copy, our protocol was able to conduct CYP2D6 haplotype phasing resulting in 100% concordance with the prior data. In addition, for three reference samples known to have more than two copies of CYP2D6 but for which the exact number of CYP2D6 genes was unknown, our protocol was able to resolve the number for two out of the three of these, and estimate the likely number for the third. Finally, we demonstrate that our method is applicable to CYP2D6 hybrid tandem configurations.

A Novel Targeted Hi-C Assay for Comprehensive Typing and Haplotype Phasing of the HLA Region Using Short-Read Sequencing

A Novel Targeted Hi-C Assay for Comprehensive Typing and Haplotype Phasing of the HLA Region Using Short-Read Sequencing

Haplotype-resolved assembly of a tetraploid potato genome using long reads and low-depth offspring data

Potato is one of the world’s major staple crops, and like many important crop plants, it has a polyploid genome. Polyploid haplotype assembly poses a major computational challenge. We introduce a novel strategy for the assembly of polyploid genomes and present an assembly of the autotetraploid potato cultivar Altus. Our method uses low-depth sequencing data from an offspring population to achieve chromosomal clustering and haplotype phasing on the assembly graph. Our approach generates high-quality assemblies of individual chromosomes with haplotype-specific sequence resolution of whole chromosome arms and can be applied in common breeding scenarios where collections of offspring are available.

Detection of hidden intronic DDC variant in aromatic L-amino acid decarboxylase deficiency by adaptive sampling.

Aromatic l-amino acid decarboxylase (AADC) deficiency is an autosomal recessive neurotransmitter disorder caused by pathogenic DOPA decarboxylase (DDC) variants. We previously reported Japanese siblings with AADC deficiency, which was confirmed by the lack of enzyme activity; however, only a heterozygous missense variant was detected. We therefore performed targeted long-read sequencing by adaptive sampling to identify any missing variants. Haplotype phasing and variant calling identified a novel deep intronic variant (c.714+255 C > A), which was predicted to potentially activate the noncanonical splicing acceptor site. Minigene assay revealed that wild-type and c.714+255 C > A alleles had different impacts on splicing. Three transcripts, including the canonical transcript, were detected from the wild-type allele, but only the noncanonical cryptic exon was produced from the variant allele, indicating that c.714+255 C > A was pathogenic. Target long-read sequencing may be used to detect hidden pathogenic variants in unresolved autosomal recessive cases with only one disclosed hit variant.

Hapsolutely: a user-friendly tool integrating haplotype phasing, network construction, and haploweb calculation.

Haplotype networks are a routine approach to visualize relationships among alleles. Such visual analysis of single-locus data is still of importance, especially in species diagnosis and delimitation, where a limited amount of sequence data usually are available and sufficient, along with other datasets in the framework of integrative taxonomy. In diploid organisms, this often requires separating (phasing) sequences with heterozygotic positions, and typically separate programs are required for phasing, reformatting of input files, and haplotype network construction. We therefore developed Hapsolutely, a user-friendly program with an ergonomic graphical user interface that integrates haplotype phasing from single-locus sequences with five approaches for network/genealogy reconstruction. Among the novel options implemented, Hapsolutely integrates phasing and graphical reconstruction steps of haplotype networks, supports input of species partition data in the common SPART and SPART-XML formats, and calculates and visualizes haplowebs and fields for recombination, thus allowing graphical comparison of allele distribution and allele sharing among subsets for the purpose of species delimitation. The new tool has been specifically developed with a focus on the workflow in alpha-taxonomy, where exploring fields for recombination across alternative species partitions may help species delimitation. Hapsolutely is written in Python, and integrates code from Phase, SeqPHASE, and PopART in C++ and Haxe. Compiled stand-alone executables for MS Windows and Mac OS along with a detailed manual can be downloaded from https://www.itaxotools.org; the source code is openly available on GitHub (https://github.com/iTaxoTools/Hapsolutely).

Phased genome assemblies reveal haplotype-specific genetic load in the critically endangered Chinese Bahaba (Teleostei, Sciaenidae).

While haplotype-specific genetic load shapes the evolutionary trajectory of natural and captive populations, mixed-haplotype assembly and genotyping hindered its characterization in diploids. Herein, we produced two phased genome assemblies of the critically endangered fish Chinese Bahaba (Bahaba taipingensis, Sciaenidae, Teleostei) and resequenced 20 whole genomes to quantify population genetic load at a haplotype level. We identified frame-shifting variants as the most deleterious type, followed by mutations in the 5'-UTR, 3'-UTR and missense mutations at conserved amino acids. Phased haplotypes revealed gene deletions and high-impact deleterious variants. We estimated ~1.12% of genes missing or interrupted per haplotype, with a significant overlap of disrupted genes (30.35%) between haplotype sets. Relative proportions of deleterious variant categories differed significantly between haplotypes. Simulations suggested that purifying selection struggled to purge slightly deleterious genetic load in captive breeding compared to genotyping interventions, and that higher inter-haplotypic variance of genetic load predicted more efficient purging by artificial selection. Combining the knowledge of haplotype-resolved genetic load with predictive modelling will be immensely useful for understanding the evolution of deleterious variants and guiding conservation planning.

Association between suicidal ideation and tandem repeats in contactins.

Death by suicide is one of the leading causes of death among adolescents. Genome-wide association studies (GWAS) have identified loci that associate with suicidal ideation and related behaviours. One such group of loci are the six contactin genes (CNTN1-6) that are critical to neurodevelopment through regulating neurite structure. Because single nucleotide polymorphisms (SNPs) detected by GWAS often map to non-coding intergenic regions, we investigated whether repetitive variants in CNTNs associated with suicidality in a young cohort aged 8 to 21. Understanding the genetic liability of suicidal thought and behavior in this age group will promote early intervention and treatment. Genotypic and phenotypic data were obtained from the Philadelphia Neurodevelopment Cohort (PNC). Across six CNTNs, 232 short tandem repeats (STRs) were analyzed in up to 4,595 individuals of European ancestry who expressed current, previous, or no suicidal ideation. STRs were imputed into SNP arrays using a phased SNP-STR haplotype reference panel from the 1000 Genomes Project. We tested several additive and interactive models of locus-level burden (i.e., sum of STR alleles) with respect to suicidal ideation. Additive models included sex, birth year, developmental stage ("DevStage"), and the first 10 principal components of ancestry as covariates; interactive models assessed the effect of STR-by-DevStage considering all other covariates. CNTN1-[T]N interacted with DevStage to increase risk for current suicidal ideation (CNTN1-[T]N-by-DevStage; p = 0.00035). Compared to the youngest age group, the middle (OR = 1.80, p = 0.0514) and oldest (OR = 3.82, p = 0.0002) participant groups had significantly higher odds of suicidal ideation as their STR length expanded; this result was independent of polygenic scores for suicidal ideation. These findings highlight diversity in the genetic effects (i.e., SNP and STR) acting on suicidal thoughts and behavior and advance our understanding of suicidal ideation across childhood and adolescence.

How local reference panels improve imputation in French populations

Imputation servers offer the exclusive possibility to harness the largest public reference panels which have been shown to deliver very high precision in the imputation of European genomes. Many studies have nonetheless stressed the importance of ‘study specific panels’ (SSPs) as an alternative and have shown the benefits of combining public reference panels with SSPs. But such combined approaches are not attainable when using external imputation servers. To investigate how to confront this challenge, we imputed 550 French individuals using either the University of Michigan imputation server with the Haplotype Reference Consortium (HRC) panel or an in-house SSP of 850 whole-genome sequenced French individuals. With approximate geo-localization of both our target and SSP individuals we are able to pinpoint different scenarios where SSP-based imputation would be preferred over server-based imputation or vice-versa. This is achieved by showing to a high degree of resolution the importance of the proximity of the reference panel to target individuals; with a focus on the clear added value of SSPs for estimating haplotype phase and for the imputation of rare variants (minor allele-frequency below 0.01). Such benefits were most evident for individuals from the same geographical regions in France as the SSP individuals. Overall, only 42.3% of all 125,442 variants evaluated were better imputed with an SSP from France compared to an external reference panel, however this rises to 58.1% for individuals from geographic regions well covered by the SSP. By investigating haplotype sharing and population fine-structure in France, we show the importance of including SSP haplotypes for imputation but also that they should ideally be combined with large public panels. In the absence of the unattainable results from a combined panel of the HRC and our French SSP, we put forward a pragmatic solution where server-based and SSP-based imputation outcomes can be combined based on comparing posterior genotype probabilities. We show that such an approach can give a level of imputation accuracy in excess of what could be achieved with either strategy alone. The results presented provide detailed insights into the accuracy of imputation that should be expected from different strategies for European populations.

Selscan 2.0: scanning for sweeps in unphased data.

Several popular haplotype-based statistics for identifying recent or ongoing positive selection in genomes require knowledge of haplotype phase. Here, we provide an update to selscan which implements a re-definition of these statistics for use in unphased data. Source code and binaries are freely available at https://github.com/szpiech/selscan, implemented in C/C++, and supported on Linux, Windows, and MacOS.

Small polymorphisms are a source of ancestral bias in structural variant breakpoint placement.

High-quality genome assemblies and sophisticated algorithms have increased sensitivity for a wide range of variant types, and breakpoint accuracy for structural variants (SVs, ≥50 bp) has improved to near base pair precision. Despite these advances, many SV breakpoint locations are subject to systematic bias affecting variant representation. To understand why SV breakpoints are inconsistent across samples, we reanalyzed 64 phased haplotypes constructed from long-read assemblies released by the Human Genome Structural Variation Consortium (HGSVC). We identify 882 SV insertions and 180 SV deletions with variable breakpoints not anchored in tandem repeats (TRs) or segmental duplications (SDs). SVs called from aligned sequencing reads increase breakpoint disagreements by 2×-16×. Sequence accuracy had a minimal impact on breakpoints, but we observe a strong effect of ancestry. We confirm that SNP and indel polymorphisms are enriched at shifted breakpoints and are also absent from variant callsets. Breakpoint homology increases the likelihood of imprecise SV calls and the distance they are shifted, and tandem duplications are the most heavily affected SVs. Because graph genome methods normalize SV calls across samples, we investigated graphs generated by two different methods and find the resulting breakpoints are subject to other technical biases affecting breakpoint accuracy. The breakpoint inconsistencies we characterize affect ∼5% of the SVs called in a human genome and can impact variant interpretation and annotation. These limitations underscore a need for algorithm development to improve SV databases, mitigate the impact of ancestry on breakpoints, and increase the value of callsets for investigating breakpoint features.

Non-invasive real-time genomic monitoring of the critically endangered kākāpō.

We used non-invasive real-time genomic approaches to monitor one of the last surviving populations of the critically endangered kākāpō (Strigops habroptilus). We first established an environmental DNA metabarcoding protocol to identify the distribution of kākāpō and other vertebrate species in a highly localized manner using soil samples. Harnessing real-time nanopore sequencing and the high-quality kākāpō reference genome, we then extracted species-specific DNA from soil. We combined long read-based haplotype phasing with known individual genomic variation in the kākāpō population to identify the presence of individuals, and confirmed these genomically informed predictions through detailed metadata on kākāpō distributions. This study shows that individual identification is feasible through nanopore sequencing of environmental DNA, with important implications for future efforts in the application of genomics to the conservation of rare species, potentially expanding the application of real-time environmental DNA research from monitoring species distribution to inferring fitness parameters such as genomic diversity and inbreeding.

Non-invasive real-time genomic monitoring of the critically endangered kākāpō

We used non-invasive real-time genomic approaches to monitor one of the last surviving populations of the critically endangered kākāpō (Strigops habroptilus). We first established an environmental DNA metabarcoding protocol to identify the distribution of kākāpō and other vertebrate species in a highly localized manner using soil samples. Harnessing real-time nanopore sequencing and the high-quality kākāpō reference genome, we then extracted species-specific DNA from soil. We combined long read-based haplotype phasing with known individual genomic variation in the kākāpō population to identify the presence of individuals, and confirmed these genomically informed predictions through detailed metadata on kākāpō distributions. This study shows that individual identification is feasible through nanopore sequencing of environmental DNA, with important implications for future efforts in the application of genomics to the conservation of rare species, potentially expanding the application of real-time environmental DNA research from monitoring species distribution to inferring fitness parameters such as genomic diversity and inbreeding.

FiMAP: A fast identity-by-descent mapping test for biobank-scale cohorts.

Although genome-wide association studies (GWAS) have identified tens of thousands of genetic loci, the genetic architecture is still not fully understood for many complex traits. Most GWAS and sequencing association studies have focused on single nucleotide polymorphisms or copy number variations, including common and rare genetic variants. However, phased haplotype information is often ignored in GWAS or variant set tests for rare variants. Here we leverage the identity-by-descent (IBD) segments inferred from a random projection-based IBD detection algorithm in the mapping of genetic associations with complex traits, to develop a computationally efficient statistical test for IBD mapping in biobank-scale cohorts. We used sparse linear algebra and random matrix algorithms to speed up the computation, and a genome-wide IBD mapping scan of more than 400,000 samples finished within a few hours. Simulation studies showed that our new method had well-controlled type I error rates under the null hypothesis of no genetic association in large biobank-scale cohorts, and outperformed traditional GWAS single-variant tests when the causal variants were untyped and rare, or in the presence of haplotype effects. We also applied our method to IBD mapping of six anthropometric traits using the UK Biobank data and identified a total of 3,442 associations, 2,131 (62%) of which remained significant after conditioning on suggestive tag variants in the ± 3 centimorgan flanking regions from GWAS.

Unraveling Diverse Mechanisms of Complex Structural Variant Interactions through Multiomic Data in Multiple Myeloma

Introduction: Structural variants (SVs) play a role in proliferation of plasma cells that characterizes multiple myeloma (MM). Several hallmark SVs have been identified in MM, including translocations involving the immunoglobulin heavy chain locus and several partner genes, as well as deletions and duplications affecting key genes such as TP53, RB1, and MYC. Complex SVs such as templated insertions, chromothripsis, and chromoplexy are associated with disease progression but have not yet systematically been studied. Methods: Paired short-read (Illumina, average depth 75x), long-read HiFi (PacBio, 16x), optical genome mapping (OGM; Bionano Genomics, 341x) and Micro-C (Cantata Bio, 45x) data were sequenced from 8 relapsed MM patient-derived xenograft samples and 2 cell lines, covering t(11;14), t(4;14), and hyperdiploid subgroups. Reads were aligned to the hg38 reference genome while complex SVs (chromothripsis, chromoplexy and templated insertion) were systematically identified and accurately reconstructed by combining short-read (Manta), HiFi (pbsv), OGM, and Micro-C data (EagleC). Chromosome organization including loops, topologically associated domains (TADs) and A/B compartments were called from Micro-C data (Mustache and Juicer). Haplotype phasing was conducted using small variants detected from HiFi data. De novo assembly of the genome was conducted using HiFi and Micro-C data and compared to the reference genome. Reconstructed derivative chromosome interactions due to complex SVs were further identified by aligning Micro-C reads to the newly assembled genomes. Previously identified super-enhancers from H3K27Ac ChIP-seq from MM cell lines were mapped onto these SVs and expression of target genes assessed by RNA-seq. Results: 1,340 SVs were found in 10 samples using OGM of which 828 were identified in short-read WGS data. 16 complex SVs including chromothripsis, chromoplexy and templated insertions were detected in 10 samples, and we describe two (Fig.1) in detail here. A complex templated insertion consisting of a t(2;6;8) was found in a t(11;14) PDX sample with copy number gains at breakpoints which could not be resolved from short-read data alone. OGM data revealed a single contig consisting of DNA from chromosomes 2, 6, and 8. Micro-C data revealed interactions between these chromosomes, specifically the gained regions on chromosomes 2 and 8 showed more interactions with chromosome 6 than with other chromosomes, indicating insertions into chromosome 6. As a result, both MYC at chromosome 8 and GALM at chromosome 2 were inserted into the TXNDC5 locus, containing a known MM super-enhancer, leading to the over-expression of both MYC and GALM (log 2FC=1.7 and 1.0) in this sample. A de novo genome assembly indicated neo-TAD formation encompassing the super-enhancer and both genes. In coMMpass dataset, high expression of GALM and MYC are significantly associated with inferior overall (p=0.002 and 0.05, logrank test) and progression-free survival (p=0.01 and 0.09). Another complex templated insertion consisting of a t(3;4;16) was identified in a hyperdiploid PDX sample, again with copy number gains at breakpoints. Although the short-read data indicated an assembly similar to the previous templated insertion SV, the OGM and Micro-C data indicated a 3-way chromosome swap where the short arm of chromosome 3 was translocated to the short arm of chromosome 4, the short arm of chromosome 4 was translocated to the long arm of chromosome 16, and the long arm of chromosome 16 was translocated to the short arm of chromosome 3. Separate contigs for the t(4;16), t(3;16) and t(3;4) were confirmed by OGM data and only 2-way chromosomal interactions were seen in the Micro-C data. This complex event led to numerous oncogenes juxtaposed to super-enhancers, which caused over-expression of target genes such as ACD and RANBP10 (log 2FC=1.0 and 0.4), both of which were on chromosome 16 and are significantly associated with inferior overall (p=0.02 and p=0.004) and progression-free survival (p=0.003 and p=0.005). Conclusion: By utilizing multiomic techniques we were able to reconstruct complex SV events, showing different mechanisms of generating templated insertion events and identifying their biological consequences. We demonstrated how these complex events could potentially facilitate tumor proliferation via engaging the super-enhancers and regulating the expression of key oncogenes.

Targeted haplotyping in pharmacogenomics using Oxford Nanopore Technologies' adaptive sampling.

Pharmacogenomics (PGx) studies the impact of interindividual genomic variation on drug response, allowing the opportunity to tailor the dosing regimen for each patient. Current targeted PGx testing platforms are mainly based on microarray, polymerase chain reaction, or short-read sequencing. Despite demonstrating great value for the identification of single nucleotide variants (SNVs) and insertion/deletions (INDELs), these assays do not permit identification of large structural variants, nor do they allow unambiguous haplotype phasing for star-allele assignment. Here, we used Oxford Nanopore Technologies' adaptive sampling to enrich a panel of 1,036 genes with well-documented PGx relevance extracted from the Pharmacogenomics Knowledge Base (PharmGKB). By evaluating concordance with existing truth sets, we demonstrate accurate variant and star-allele calling for five Genome in a Bottle reference samples. We show that up to three samples can be multiplexed on one PromethION flow cell without a significant drop in variant calling performance, resulting in 99.35% and 99.84% recall and precision for the targeted variants, respectively. This work advances the use of nanopore sequencing in clinical PGx settings.

Haplotype-based noninvasive prenatal diagnosis of methylmalonic acidemia and the discovery of a recurrent pathogenic haplotype associated with c.609G>A.

Early diagnosis and intervention are crucial for the prognosis of methylmalonic acidemia (MMA). However, research focused on early prenatal diagnosis of MMA is limited. A 161.89kb capture panel was designed for selectively enriching highly heterozygous SNPs. Fetal genotypes were inferred using relative haplotype dosage (RHDO) and Bayes factor, followed by invasive prenatal diagnosis (IPD) for validation. A core pathogenic haplotype associated with c.609G>A was identified based on the frequency differences between pathogenic and normal haplotypes. We recruited 41 pregnancies at risk of MMA with a median gestational age of 8+2 weeks. The assay success rate of NIPD-MMA for maternal variants was 92.7% (38/41), and after incorporating the paternal result, the overall assay success rate reached 100% (41/41). All NIPD results were concordant with IPD. Notably, a core haplotype (hap_2), comprising 28 SNPs, demonstrates significant enrichment within pathogenic haplotypes bearing the c.609G>A variation. On average, c.609G>A carriers had 22.38 heterozygous loci within these 28 SNPs. NIPD-MMA presents a viable choice for early, accurate, and safe prenatal diagnosis. Furthermore, the discovery of the recurrent core pathogenic haplotype provides a novel approach for haplotype phasing and has the potential for realizing proband-independent NIPD in the future.

A deep population reference panel of tandem repeat variation

Tandem repeats (TRs) represent one of the largest sources of genetic variation in humans and are implicated in a range of phenotypes. Here we present a deep characterization of TR variation based on high coverage whole genome sequencing from 3550 diverse individuals from the 1000 Genomes Project and H3Africa cohorts. We develop a method, EnsembleTR, to integrate genotypes from four separate methods resulting in high-quality genotypes at more than 1.7 million TR loci. Our catalog reveals novel sequence features influencing TR heterozygosity, identifies population-specific trinucleotide expansions, and finds hundreds of novel eQTL signals. Finally, we generate a phased haplotype panel which can be used to impute most TRs from nearby single nucleotide polymorphisms (SNPs) with high accuracy. Overall, the TR genotypes and reference haplotype panel generated here will serve as valuable resources for future genome-wide and population-wide studies of TRs and their role in human phenotypes.

De novo genome assembly depicts the immune genomic characteristics of cattle

Immunogenomic loci remain poorly understood because of their genetic complexity and size. Here, we report the de novo assembly of a cattle genome and provide a detailed annotation of the immunogenomic loci. The assembled genome contains 143 contigs (N50 ~ 74.0 Mb). In contrast to the current reference genome (ARS-UCD1.2), 156 gaps are closed and 467 scaffolds are located in our assembly. Importantly, the immunogenomic regions, including three immunoglobulin (IG) loci, four T-cell receptor (TR) loci, and the major histocompatibility complex (MHC) locus, are seamlessly assembled and precisely annotated. With the characterization of 258 IG genes and 657 TR genes distributed across seven genomic loci, we present a detailed depiction of immune gene diversity in cattle. Moreover, the MHC gene structures are integrally revealed with properly phased haplotypes. Together, our work describes a more complete cattle genome, and provides a comprehensive view of its complex immune-genome.

MosaiCatcher v2: a single-cell structural variations detection and analysis reference framework based on Strand-seq.

Single-cell DNA template strand sequencing (Strand-seq) allows a range of various genomic analysis including chromosome length haplotype phasing and structural variation (SV) calling in individual cells. Here, we present MosaiCatcher v2, a standardized workflow and reference framework for single-cell SV detection using Strand-seq. This framework introduces a range of functionalities, including: an automated upstream Quality Control (QC) and assembly sub-workflow that relies on multiple genome assemblies and incorporates a multistep normalization module, integration of the single-cell nucleosome occupancy and genetic variation analysis SV functional characterization and of the ArbiGent SV genotyping modules, platform portability, as well as a user-friendly and shareable web report. These new features of MosaiCatcher v2 enable reproducible computational processing of Strand-seq data, which are increasingly used in human genetics and single-cell genomics, toward production environments. MosaiCatcher v2 is compatible with both container and conda environments, ensuring reproducibility and robustness and positioning the framework as a cornerstone in computational processing of Strand-seq data. MosaiCatcher v2 is a standardized workflow, implemented using the Snakemake workflow management system. The pipeline is available on GitHub: https://github.com/friendsofstrandseq/mosaicatcher-pipeline/ and on the snakemake-workflow-catalog: https://snakemake.github.io/snakemake-workflow-catalog/?usage=friendsofstrandseq/mosaicatcher-pipeline. Strand-seq example input data used in the publication can be found in the Data availability statement. Additionally, a lightweight dataset for test purposes can be found on the GitHub repository.

Single-cell allele-specific expression analysis reveals dynamic and cell-type-specific regulatory effects

Differential allele-specific expression (ASE) is a powerful tool to study context-specific cis-regulation of gene expression. Such effects can reflect the interaction between genetic or epigenetic factors and a measured context or condition. Single-cell RNA sequencing (scRNA-seq) allows the measurement of ASE at individual-cell resolution, but there is a lack of statistical methods to analyze such data. We present Differential Allelic Expression using Single-Cell data (DAESC), a powerful method for differential ASE analysis using scRNA-seq from multiple individuals, with statistical behavior confirmed through simulation. DAESC accounts for non-independence between cells from the same individual and incorporates implicit haplotype phasing. Application to data from 105 induced pluripotent stem cell (iPSC) lines identifies 657 genes dynamically regulated during endoderm differentiation, with enrichment for changes in chromatin state. Application to a type-2 diabetes dataset identifies several differentially regulated genes between patients and controls in pancreatic endocrine cells. DAESC is a powerful method for single-cell ASE analysis and can uncover novel insights on gene regulation.