Dense and accurate whole-chromosome haplotyping of individual genomes

Phased nanopore assembly with Shasta and modular graph phasing with GFAse

Reference-free genome phasing is vital for understanding allele inheritance and the impact of single-molecule DNA variation on phenotypes. To achieve thorough phasing across homozygous or repetitive regions of the genome, long-read sequencing technologies are often used to perform phased de novo assembly. As a step toward reducing the cost and complexity of this type of analysis, we describe new methods for accurately phasing Oxford Nanopore Technologies (ONT) sequence data with the Shasta genome assembler and a modular tool for extending phasing to the chromosome scale called GFAse. We test using new variants of ONT PromethION sequencing, including those using proximity ligation, and show that newer, higher accuracy ONT reads substantially improve assembly quality.

Phasing Diploid Genome Assembly Graphs with Single-Cell Strand Sequencing

Haplotype information is crucial for biomedical and population genetics research. However, current strategies to produce de-novo haplotype-resolved assemblies often require either difficult-to-acquire parental data or an intermediate haplotype-collapsed assembly. Here, we present Graphasing, a workflow which synthesizes the global phase signal of Strand-seq with assembly graph topology to produce chromosome-scale de-novo haplotypes for diploid genomes. Graphasing readily integrates with any assembly workflow that both outputs an assembly graph and has a haplotype assembly mode. Graphasing performs comparably to trio-phasing in contiguity, phasing accuracy, and assembly quality, outperforms Hi-C in phasing accuracy, and generates human assemblies with over 18 chromosome-spanning haplotypes.

BLR: a flexible pipeline for haplotype analysis of multiple linked-read technologies

Linked-read sequencing promises a one-method approach for genome-wide insights including single nucleotide variants (SNVs), structural variants, and haplotyping. We introduce Barcode Linked Reads (BLR), an open-source haplotyping pipeline capable of handling millions of barcodes and data from multiple linked-read technologies including DBS, 10× Genomics, TELL-seq and stLFR. Running BLR on DBS linked-reads yielded megabase-scale phasing with low (<0.2%) switch error rates. Of 13616 protein-coding genes phased in the GIAB benchmark set (v4.2.1), 98.6% matched the BLR phasing. In addition, large structural variants showed concordance with HPRC-HG002 reference assembly calls. Compared to diploid assembly with PacBio HiFi reads, BLR phasing was more continuous when considering switch errors. We further show that integrating long reads at low coverage (∼10×) can improve phasing contiguity and reduce switch errors in tandem repeats. When compared to Long Ranger on 10× Genomics data, BLR showed an increase in phase block N50 with low switch-error rates. For TELL-Seq and stLFR linked reads, BLR generated longer or similar phase block lengths and low switch error rates compared to results presented in the original publications. In conclusion, BLR provides a flexible workflow for comprehensive haplotype analysis of linked reads from multiple platforms.

Allele detection using k-mer-based sequencing error profiles

Motivation

For genotype and haplotype inference, typically, sequencing reads aligned to a reference genome are used. The alignments identify the genomic origin of the reads and help to infer the absence or presence of sequence variants in the genome. Since long sequencing reads often come with high rates of systematic sequencing errors, single nucleotides in the reads are not always correctly aligned to the reference genome, which can thus lead to wrong conclusions about the allele carried by a sequencing read at the variant site. Thus, allele detection is not a trivial task, especially for single-nucleotide polymorphisms and indels.

Results

To learn the characteristics of sequencing errors, we introduce a method to create an error model in non-variant regions of the genome. This information is later used to distinguish sequencing errors from alternative alleles in variant regions. We show that our method, k-merald, improves allele detection accuracy leading to better genotyping performance as compared to the existing WhatsHap implementation using edit-distance-based allele detection, with a decrease of 18% and 24% in error rate for high-coverage Oxford Nanopore and PacBio CLR sequencing reads for sample HG002, respectively. We additionally observed a prominent improvement in genotyping performance for sequencing data with low coverage. For 3× coverage Oxford Nanopore sequencing data, the genotyping error rate reduced from 34% to 31%, corresponding to a 9% decrease.

Availability and implementation

https://github.com/whatshap/whatshap.

Toward the functional interpretation of somatic structural variations: bulk- and single-cell approaches

Structural variants (SVs) are genomic rearrangements that can take many different forms such as copy number alterations, inversions and translocations. During cell development and aging, somatic SVs accumulate in the genome with potentially neutral, deleterious or pathological effects. Generation of somatic SVs is a key mutational process in cancer development and progression. Despite their importance, the detection of somatic SVs is challenging, making them less studied than somatic single-nucleotide variants. In this review, we summarize recent advances in whole-genome sequencing (WGS)-based approaches for detecting somatic SVs at the tissue and single-cell levels and discuss their advantages and limitations. First, we describe the state-of-the-art computational algorithms for somatic SV calling using bulk WGS data and compare the performance of somatic SV detectors in the presence or absence of a matched-normal control. We then discuss the unique features of cutting-edge single-cell-based techniques for analyzing somatic SVs. The advantages and disadvantages of bulk and single-cell approaches are highlighted, along with a discussion of their sensitivity to copy-neutral SVs, usefulness for functional inferences and experimental and computational costs. Finally, computational approaches for linking somatic SVs to their functional readouts, such as those obtained from single-cell transcriptome and epigenome analyses, are illustrated, with a discussion of the promise of these approaches in health and diseases.

Dominance vs epistasis: the biophysical origins and plasticity of genetic interactions within and between alleles

An important challenge in genetics, evolution and biotechnology is to understand and predict how mutations combine to alter phenotypes, including molecular activities, fitness and disease. In diploids, mutations in a gene can combine on the same chromosome or on different chromosomes as a "heteroallelic combination". However, a direct comparison of the extent, sign, and stability of the genetic interactions between variants within and between alleles is lacking. Here we use thermodynamic models of protein folding and ligand-binding to show that interactions between mutations within and between alleles are expected in even very simple biophysical systems. Protein folding alone generates within-allele interactions and a single molecular interaction is sufficient to cause between-allele interactions and dominance. These interactions change differently, quantitatively and qualitatively as a system becomes more complex. Altering the concentration of a ligand can, for example, switch alleles from dominant to recessive. Our results show that intra-molecular epistasis and dominance should be widely expected in even the simplest biological systems but also reinforce the view that they are plastic system properties and so a formidable challenge to predict. Accurate prediction of both intra-molecular epistasis and dominance will require either detailed mechanistic understanding and experimental parameterization or brute-force measurement and learning.

Applications of advanced technologies for detecting genomic structural variation

Chromosomal structural variation (SV) encompasses a heterogenous class of genetic variants that exerts strong influences on human health and disease. Despite their importance, many structural variants (SVs) have remained poorly characterized at even a basic level, a discrepancy predicated upon the technical limitations of prior genomic assays. However, recent advances in genomic technology can identify and localize SVs accurately, opening new questions regarding SV risk factors and their impacts in humans. Here, we first define and classify human SVs and their generative mechanisms, highlighting characteristics leveraged by various SV assays. We next examine the first-ever gapless assembly of the human genome and the technical process of assembling it, which required third-generation sequencing technologies to resolve structurally complex loci. The new portions of that "telomere-to-telomere" and subsequent pangenome assemblies highlight aspects of SV biology likely to develop in the near-term. We consider the strengths and limitations of the most promising new SV technologies and when they or longstanding approaches are best suited to meeting salient goals in the study of human SV in population-scale genomics research, clinical, and public health contexts. It is a watershed time in our understanding of human SV when new approaches are expected to fundamentally change genomic applications.

Phylogenetic Analysis of Allotetraploid Species Using Polarized Genomic Sequences

Phylogenetic analysis of polyploid hybrid species has long posed a formidable challenge as it requires the ability to distinguish between alleles of different ancestral origins in order to disentangle their individual evolutionary history. This problem has been previously addressed by conceiving phylogenies as reticulate networks, using a two-step phasing strategy that first identifies and segregates homoeologous loci and then, during a second phasing step, assigns each gene copy to one of the subgenomes of an allopolyploid species. Here, we propose an alternative approach, one that preserves the core idea behind phasing-to produce separate nucleotide sequences that capture the reticulate evolutionary history of a polyploid-while vastly simplifying its implementation by reducing a complex multistage procedure to a single phasing step. While most current methods used for phylogenetic reconstruction of polyploid species require sequencing reads to be pre-phased using experimental or computational methods-usually an expensive, complex, and/or time-consuming endeavor-phasing executed using our algorithm is performed directly on the multiple-sequence alignment (MSA), a key change that allows for the simultaneous segregation and sorting of gene copies. We introduce the concept of genomic polarization that, when applied to an allopolyploid species, produces nucleotide sequences that capture the fraction of a polyploid genome that deviates from that of a reference sequence, usually one of the other species present in the MSA. We show that if the reference sequence is one of the parental species, the polarized polyploid sequence has a close resemblance (high pairwise sequence identity) to the second parental species. This knowledge is harnessed to build a new heuristic algorithm where, by replacing the allopolyploid genomic sequence in the MSA by its polarized version, it is possible to identify the phylogenetic position of the polyploid's ancestral parents in an iterative process. The proposed methodology can be used with long-read and short-read high-throughput sequencing data and requires only one representative individual for each species to be included in the phylogenetic analysis. In its current form, it can be used in the analysis of phylogenies containing tetraploid and diploid species. We test the newly developed method extensively using simulated data in order to evaluate its accuracy. We show empirically that the use of polarized genomic sequences allows for the correct identification of both parental species of an allotetraploid with up to 97% certainty in phylogenies with moderate levels of incomplete lineage sorting (ILS) and 87% in phylogenies containing high levels of ILS. We then apply the polarization protocol to reconstruct the reticulate histories of Arabidopsis kamchatica and Arabidopsis suecica, two allopolyploids whose ancestry has been well documented. [Allopolyploidy; Arabidopsis; genomic polarization; homoeologs; incomplete lineage sorting; phasing; polyploid phylogenetics; reticulate evolution.].

Phased nanopore assembly with Shasta and modular graph phasing with GFAse

As a step towards simplifying and reducing the cost of haplotype resolved de novo assembly, we describe new methods for accurately phasing nanopore data with the Shasta genome assembler and a modular tool for extending phasing to the chromosome scale called GFAse. We test using new variants of Oxford Nanopore Technologies' (ONT) PromethION sequencing, including those using proximity ligation and show that newer, higher accuracy ONT reads substantially improve assembly quality.

Interrogating the Human Diplome: Computational Methods, Emerging Applications, and Challenges

Human DNA sequencing protocols have revolutionized human biology, biomedical science, and clinical practice, but still have very important limitations. One limitation is that most protocols do not separate or assemble (i.e., "phase") the nucleotide content of each of the maternally and paternally derived chromosomal homologs making up the 22 autosomal pairs and the chromosomal pair making up the pseudo-autosomal region of the sex chromosomes. This has led to a dearth of studies and a consequent underappreciation of many phenomena of fundamental importance to basic and clinical genomic science. We discuss a few protocols for obtaining phase information as well as their limitations, including those that could be used in tumor phasing settings. We then describe a number of biological and clinical phenomena that require phase information. These include phenomena that require precise knowledge of the nucleotide sequence in a chromosomal segment from germline or somatic cells, such as DNA binding events, and insight into unique cis vs. trans-acting functionally impactful variant combinations-for example, variants implicated in a phenotype governed by compound heterozygosity. In addition, we also comment on the need for reliable and consensus-based diploid-context computational workflows for variant identification as well as the need for laboratory-based functional verification strategies for validating cis vs. trans effects of variant combinations. We also briefly describe available resources, example studies, as well as areas of further research, and ultimately argue that the science behind the study of human diploidy, referred to as "diplomics," which will be enabled by nucleotide-level resolution of phased genomes, is a logical next step in the analysis of human genome biology.

Chromosome-Length Haplotypes with StrandPhaseR and Strand-seq

Dense local haplotypes can now readily be extracted from long-read or droplet-based sequence data. However, these methods struggle to combine subchromosomal haplotype blocks into global chromosome-length haplotypes. Strand-seq is a single cell sequencing technique that uses read orientation to capture sparse global phase information by sequencing only one of two DNA strands for each parental homolog. In combination with dense local haplotypes from other technologies, Strand-seq data can be used to obtain complete chromosome-length phase information. In this chapter, we run the R package StrandPhaseR to phase SNVs using publicly available sequence data for sample HG005 of the Genome in a Bottle project.

Phased Genome Assemblies

The ultimate goal of de novo assembly of reads sequenced from a diploid individual is the separate reconstruction of the sequences corresponding to the two copies of each chromosome. Unfortunately, the allele linkage information needed to perform phased genome assemblies has been difficult to generate. Hence, most current genome assemblies are a haploid mixture of the two underlying chromosome copies present in the sequenced individual. Sequencing technologies providing long (20 kb) and accurate reads are the basis to generate phased genome assemblies. This chapter provides a brief overview of the main milestones in traditional genome assembly, focusing on the bioinformatic techniques developed to generate haplotype information from different specialized protocols. Using these techniques as a knowledge background, the chapter reviews the current algorithms to generate phased assemblies from long reads with low error rates. Current techniques perform haplotype-aware error correction steps to increase the quality of the raw reads. In addition, variations on the traditional overlap-layout-consensus (OLC) graph have been developed in an effort to eliminate edges between reads sequenced from different chromosome copies. This allows for large presence-absence variants between the chromosome copies to be taken into account. The development of these algorithms, along with the improved sequencing technologies has been crucial to finish chromosome-level assemblies of complex genomes.

Parent-of-origin detection and chromosome-scale haplotyping using long-read DNA methylation sequencing and Strand-seq

Hundreds of loci in human genomes have alleles that are methylated differentially according to their parent of origin. These imprinted loci generally show little variation across tissues, individuals, and populations. We show that such loci can be used to distinguish the maternal and paternal homologs for all human autosomes without the need for the parental DNA. We integrate methylation-detecting nanopore sequencing with the long-range phase information in Strand-seq data to determine the parent of origin of chromosome-length haplotypes for both DNA sequence and DNA methylation in five trios with diverse genetic backgrounds. The parent of origin was correctly inferred for all autosomes with an average mismatch error rate of 0.31% for SNVs and 1.89% for insertions or deletions (indels). Because our method can determine whether an inherited disease allele originated from the mother or the father, we predict that it will improve the diagnosis and management of many genetic diseases.

Novel Virus Identification through Metagenomics: A Systematic Review

Metagenomic Next Generation Sequencing (mNGS) allows the evaluation of complex microbial communities, avoiding isolation and cultivation of each microbial species, and does not require prior knowledge of the microbial sequences present in the sample. Applications of mNGS include virome characterization, new virus discovery and full-length viral genome reconstruction, either from virus preparations enriched in culture or directly from clinical and environmental specimens. Here, we systematically reviewed studies that describe novel virus identification through mNGS from samples of different origin (plant, animal and environment). Without imposing time limits to the search, 379 publications were identified that met the search parameters. Sample types, geographical origin, enrichment and nucleic acid extraction methods, sequencing platforms, bioinformatic analytical steps and identified viral families were described. The review highlights mNGS as a feasible method for novel virus discovery from samples of different origins, describes which kind of heterogeneous experimental and analytical protocols are currently used and provides useful information such as the different commercial kits used for the purification of nucleic acids and bioinformatics analytical pipelines.

Semi-automated assembly of high-quality diploid human reference genomes

The current human reference genome, GRCh38, represents over 20 years of effort to generate a high-quality assembly, which has benefitted society1,2. However, it still has many gaps and errors, and does not represent a biological genome as it is a blend of multiple individuals3,4. Recently, a high-quality telomere-to-telomere reference, CHM13, was generated with the latest long-read technologies, but it was derived from a hydatidiform mole cell line with a nearly homozygous genome5. To address these limitations, the Human Pangenome Reference Consortium formed with the goal of creating high-quality, cost-effective, diploid genome assemblies for a pangenome reference that represents human genetic diversity6. Here, in our first scientific report, we determined which combination of current genome sequencing and assembly approaches yield the most complete and accurate diploid genome assembly with minimal manual curation. Approaches that used highly accurate long reads and parent-child data with graph-based haplotype phasing during assembly outperformed those that did not. Developing a combination of the top-performing methods, we generated our first high-quality diploid reference assembly, containing only approximately four gaps per chromosome on average, with most chromosomes within ±1% of the length of CHM13. Nearly 48% of protein-coding genes have non-synonymous amino acid changes between haplotypes, and centromeric regions showed the highest diversity. Our findings serve as a foundation for assembling near-complete diploid human genomes at scale for a pangenome reference to capture global genetic variation from single nucleotides to structural rearrangements.

Benchmarking challenging small variants with linked and long reads

Genome in a Bottle benchmarks are widely used to help validate clinical sequencing pipelines and develop variant calling and sequencing methods. Here we use accurate linked and long reads to expand benchmarks in 7 samples to include difficult-to-map regions and segmental duplications that are challenging for short reads. These benchmarks add more than 300,000 SNVs and 50,000 insertions or deletions (indels) and include 16% more exonic variants, many in challenging, clinically relevant genes not covered previously, such as PMS2. For HG002, we include 92% of the autosomal GRCh38 assembly while excluding regions problematic for benchmarking small variants, such as copy number variants, that should not have been in the previous version, which included 85% of GRCh38. It identifies eight times more false negatives in a short read variant call set relative to our previous benchmark. We demonstrate that this benchmark reliably identifies false positives and false negatives across technologies, enabling ongoing methods development.

Recurrent inversion polymorphisms in humans associate with genetic instability and genomic disorders

Unlike copy number variants (CNVs), inversions remain an underexplored genetic variation class. By integrating multiple genomic technologies, we discover 729 inversions in 41 human genomes. Approximately 85% of inversions <2 kbp form by twin-priming during L1 retrotransposition; 80% of the larger inversions are balanced and affect twice as many nucleotides as CNVs. Balanced inversions show an excess of common variants, and 72% are flanked by segmental duplications (SDs) or retrotransposons. Since flanking repeats promote non-allelic homologous recombination, we developed complementary approaches to identify recurrent inversion formation. We describe 40 recurrent inversions encompassing 0.6% of the genome, showing inversion rates up to 2.7 × 10^-4 per locus per generation. Recurrent inversions exhibit a sex-chromosomal bias and co-localize with genomic disorder critical regions. We propose that inversion recurrence results in an elevated number of heterozygous carriers and structural SD diversity, which increases mutability in the population and predisposes specific haplotypes to disease-causing CNVs.

Familial long-read sequencing increases yield of de novo mutations

Studies of de novo mutation (DNM) have typically excluded some of the most repetitive and complex regions of the genome because these regions cannot be unambiguously mapped with short-read sequencing data. To better understand the genome-wide pattern of DNM, we generated long-read sequence data from an autism parent-child quad with an affected female where no pathogenic variant had been discovered in short-read Illumina sequence data. We deeply sequenced all four individuals by using three sequencing platforms (Illumina, Oxford Nanopore, and Pacific Biosciences) and three complementary technologies (Strand-seq, optical mapping, and 10X Genomics). Using long-read sequencing, we initially discovered and validated 171 DNMs across two children-a 20% increase in the number of de novo single-nucleotide variants (SNVs) and indels when compared to short-read callsets. The number of DNMs further increased by 5% when considering a more complete human reference (T2T-CHM13) because of the recovery of events in regions absent from GRCh38 (e.g., three DNMs in heterochromatic satellites). In total, we validated 195 de novo germline mutations and 23 potential post-zygotic mosaic mutations across both children; the overall true substitution rate based on this integrated callset is at least 1.41 × 10^-8 substitutions per nucleotide per generation. We also identified six de novo insertions and deletions in tandem repeats, two of which represent structural variants. We demonstrate that long-read sequencing and assembly, especially when combined with a more complete reference genome, increases the number of DNMs by >25% compared to previous studies, providing a more complete catalog of DNM compared to short-read data alone.

Construction of Strand-seq libraries in open nanoliter arrays

Single-cell Strand-seq generates directional genomic information to study DNA repair, assemble genomes, and map structural variation onto chromosome-length haplotypes. We report a nanoliter-volume, one-pot (OP) Strand-seq library preparation protocol in which reagents are added cumulatively, DNA purification steps are avoided, and enzymes are inactivated with a thermolabile protease. OP-Strand-seq libraries capture 10%-25% of the genome from a single-cell with reduced costs and increased throughput.

A method for low-coverage single-gamete sequence analysis demonstrates adherence to Mendel's first law across a large sample of human sperm

Recently published single-cell sequencing data from individual human sperm (n=41,189; 969-3377 cells from each of 25 donors) offer an opportunity to investigate questions of inheritance with improved statistical power, but require new methods tailored to these extremely low-coverage data (∼0.01× per cell). To this end, we developed a method, named rhapsodi, that leverages sparse gamete genotype data to phase the diploid genomes of the donor individuals, impute missing gamete genotypes, and discover meiotic recombination breakpoints, benchmarking its performance across a wide range of study designs. We then applied rhapsodi to the sperm sequencing data to investigate adherence to Mendel's Law of Segregation, which states that the offspring of a diploid, heterozygous parent will inherit either allele with equal probability. While the vast majority of loci adhere to this rule, research in model and non-model organisms has uncovered numerous exceptions whereby 'selfish' alleles are disproportionately transmitted to the next generation. Evidence of such 'transmission distortion' (TD) in humans remains equivocal in part because scans of human pedigrees have been under-powered to detect small effects. After applying rhapsodi to the sperm data and scanning for evidence of TD, our results exhibited close concordance with binomial expectations under balanced transmission. Together, our work demonstrates that rhapsodi can facilitate novel uses of inferred genotype data and meiotic recombination events, while offering a powerful quantitative framework for testing for TD in other cohorts and study systems.

Variant calling: Considerations, practices, and developments

The success of many clinical, association, or population genetics studies critically relies on properly performed variant calling step. The variety of modern genomics protocols, techniques, and platforms makes our choices of methods and algorithms difficult and there is no "one size fits all" solution for study design and data analysis. In this review, we discuss considerations that need to be taken into account while designing the study and preparing for the experiments. We outline the variety of variant types that can be detected using sequencing approaches and highlight some specific requirements and basic principles of their detection. Finally, we cover interesting developments that enable variant calling for a broad range of applications in the genomics field. We conclude by discussing technological and algorithmic advances that have the potential to change the ways of calling DNA variants in the nearest future.

Long-read technologies identify a hidden inverted duplication in a family with choroideremia

The lack of molecular diagnoses in rare genetic diseases can be explained by limitations of current standard genomic technologies. Upcoming long-read techniques have complementary strengths to overcome these limitations, with a particular strength in identifying structural variants. By using optical genome mapping and long-read sequencing, we aimed to identify the pathogenic variant in a large family with X-linked choroideremia. In this family, aberrant splicing of exon 12 of the choroideremia gene CHM was detected in 2003, but the underlying genomic defect remained elusive. Optical genome mapping and long-read sequencing approaches now revealed an intragenic 1,752 bp inverted duplication including exon 12 and surrounding regions, located downstream of the wild-type copy of exon 12. Both breakpoint junctions were confirmed with Sanger sequencing and segregate with the X-linked inheritance in the family. The breakpoint junctions displayed sequence microhomology suggestive for an erroneous replication mechanism as the origin of the structural variant. The inverted duplication is predicted to result in a hairpin formation of the pre-mRNA with the wild-type exon 12, leading to exon skipping in the mature mRNA. The identified inverted duplication is deemed the hidden pathogenic cause of disease in this family. Our study shows that optical genome mapping and long-read sequencing have significant potential for the identification of (hidden) structural variants in rare genetic diseases.

Using de novo assembly to identify structural variation of eight complex immune system gene regions

Driven by the necessity to survive environmental pathogens, the human immune system has evolved exceptional diversity and plasticity, to which several factors contribute including inheritable structural polymorphism of the underlying genes. Characterizing this variation is challenging due to the complexity of these loci, which contain extensive regions of paralogy, segmental duplication and high copy-number repeats, but recent progress in long-read sequencing and optical mapping techniques suggests this problem may now be tractable. Here we assess this by using long-read sequencing platforms from PacBio and Oxford Nanopore, supplemented with short-read sequencing and Bionano optical mapping, to sequence DNA extracted from CD14⁺ monocytes and peripheral blood mononuclear cells from a single European individual identified as HV31. We use this data to build a de novo assembly of eight genomic regions encoding four key components of the immune system, namely the human leukocyte antigen, immunoglobulins, T cell receptors, and killer-cell immunoglobulin-like receptors. Validation of our assembly using k-mer based and alignment approaches suggests that it has high accuracy, with estimated base-level error rates below 1 in 10 kb, although we identify a small number of remaining structural errors. We use the assembly to identify heterozygous and homozygous structural variation in comparison to GRCh38. Despite analyzing only a single individual, we find multiple large structural variants affecting core genes at all three immunoglobulin regions and at two of the three T cell receptor regions. Several of these variants are not accurately callable using current algorithms, implying that further methodological improvements are needed. Our results demonstrate that assessing haplotype variation in these regions is possible given sufficiently accurate long-read and associated data. Continued reductions in the cost of these technologies will enable application of these methods to larger samples and provide a broader catalogue of germline structural variation at these loci, an important step toward making these regions accessible to large-scale genetic association studies.

The human immune system is incredibly versatile underlying its capacity to defend the body against thousands of pathogens. At a molecular level, it recognizes pathogens using large libraries of antibodies and related protein receptors. These molecules are encoded by gene families that are particularly difficult to analyze due to their unusually complex patterns of similarities and differences between genes and individuals. To overcome this, we applied several sequencing methods to DNA from a single individual and developed methods to reconstruct the underlying sequence at eight of the immune-associated regions. Importantly, we used DNA extracted from monocytes to avoid capturing the further rearrangements that occur in active immune cells. We generated accurate assemblies by integrating multiple complementary data types, although we noted a small subset of locations that remain challenging. Moreover, we found that this individual contains multiple structural differences between the two inherited chromosomes and compared to previously analyzed genomes, affecting the copy number of immune system genes. Application of these methods in larger numbers of individuals will clearly uncover much more variation than is currently known, and might lead to new understanding of the effect of genetic variation on the broad range of human diseases determined by the immune response.

InvertypeR: Bayesian inversion genotyping with Strand-seq data

Background

Single cell Strand-seq is a unique tool for the discovery and phasing of genomic inversions. Conventional methods to discover inversions with Strand-seq data are blind to known inversion locations, limiting their statistical power for the detection of inversions smaller than 10 Kb. Moreover, the methods rely on manual inspection to separate false and true positives.

Results

Here we describe “InvertypeR”, a method based on a Bayesian binomial model that genotypes inversions using fixed genomic coordinates. We validated InvertypeR by re-genotyping inversions reported for three trios by the Human Genome Structural Variation Consortium. Although 6.3% of the family inversion genotypes in the original study showed Mendelian discordance, this was reduced to 0.5% using InvertypeR. By applying InvertypeR to published inversion coordinates and predicted inversion hotspots (n = 3701), as well as coordinates from conventional inversion discovery, we furthermore genotyped 66 inversions not previously reported for the three trios.

Conclusions

InvertypeR discovers, genotypes, and phases inversions without relying on manual inspection. For greater accessibility, results are presented as phased chromosome ideograms with inversions linked to Strand-seq data in the genome browser. InvertypeR increases the power of Strand-seq for studies on the role of inversions in phenotypic variation, genome instability, and human disease.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07892-9.

Profiling variable-number tandem repeat variation across populations using repeat-pangenome graphs

Variable number tandem repeats (VNTRs) are composed of consecutive repetitive DNA with hypervariable repeat count and composition. They include protein coding sequences and associations with clinical disorders. It has been difficult to incorporate VNTR analysis in disease studies that use short-read sequencing because the traditional approach of mapping to the human reference is less effective for repetitive and divergent sequences. In this work, we solve VNTR mapping for short reads with a repeat-pangenome graph (RPGG), a data structure that encodes both the population diversity and repeat structure of VNTR loci from multiple haplotype-resolved assemblies. We develop software to build a RPGG, and use the RPGG to estimate VNTR composition with short reads. We use this to discover VNTRs with length stratified by continental population, and expression quantitative trait loci, indicating that RPGG analysis of VNTRs will be critical for future studies of diversity and disease.

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.

Determination of complete chromosomal haplotypes by bulk DNA sequencing

Haplotype phase represents the collective genetic variation between homologous chromosomes and is an essential feature of non-haploid genomes. Here we describe a computational strategy to reliably determine complete whole-chromosome haplotypes using a combination of bulk long-range sequencing and Hi-C sequencing. We demonstrate that this strategy can resolve the haplotypes of parental chromosomes in diploid human genomes with high precision (>99%) and completeness (>98%) and assemble the syntenic structure of rearranged chromosomes in aneuploid cancer genomes at base pair level resolution. Our work enables direct interrogation of chromosome-specific alterations and chromatin reorganization using bulk DNA sequencing.

Extended haplotype-phasing of long-read de novo genome assemblies using Hi-C

Haplotype-resolved genome assemblies are important for understanding how combinations of variants impact phenotypes. To date, these assemblies have been best created with complex protocols, such as cultured cells that contain a single-haplotype (haploid) genome, single cells where haplotypes are separated, or co-sequencing of parental genomes in a trio-based approach. These approaches are impractical in most situations. To address this issue, we present FALCON-Phase, a phasing tool that uses ultra-long-range Hi-C chromatin interaction data to extend phase blocks of partially-phased diploid assembles to chromosome or scaffold scale. FALCON-Phase uses the inherent phasing information in Hi-C reads, skipping variant calling, and reduces the computational complexity of phasing. Our method is validated on three benchmark datasets generated as part of the Vertebrate Genomes Project (VGP), including human, cow, and zebra finch, for which high-quality, fully haplotype-resolved assemblies are available using the trio-based approach. FALCON-Phase is accurate without having parental data and performance is better in samples with higher heterozygosity. For cow and zebra finch the accuracy is 97% compared to 80-91% for human. FALCON-Phase is applicable to any draft assembly that contains long primary contigs and phased associate contigs.

Computational methods for chromosome-scale haplotype reconstruction

High-quality chromosome-scale haplotype sequences of diploid genomes, polyploid genomes, and metagenomes provide important insights into genetic variation associated with disease and biodiversity. However, whole-genome short read sequencing does not yield haplotype information spanning whole chromosomes directly. Computational assembly of shorter haplotype fragments is required for haplotype reconstruction, which can be challenging owing to limited fragment lengths and high haplotype and repeat variability across genomes. Recent advancements in long-read and chromosome-scale sequencing technologies, alongside computational innovations, are improving the reconstruction of haplotypes at the level of whole chromosomes. Here, we review recent and discuss methodological progress and perspectives in these areas.

Haplotype-resolved diverse human genomes and integrated analysis of structural variation

Long-read and strand-specific sequencing technologies together facilitate the de novo assembly of high-quality haplotype-resolved human genomes without parent-child trio data. We present 64 assembled haplotypes from 32 diverse human genomes. These highly contiguous haplotype assemblies (average minimum contig length needed to cover 50% of the genome: 26 million base pairs) integrate all forms of genetic variation, even across complex loci. We identified 107,590 structural variants (SVs), of which 68% were not discovered with short-read sequencing, and 278 SV hotspots (spanning megabases of gene-rich sequence). We characterized 130 of the most active mobile element source elements and found that 63% of all SVs arise through homology-mediated mechanisms. This resource enables reliable graph-based genotyping from short reads of up to 50,340 SVs, resulting in the identification of 1526 expression quantitative trait loci as well as SV candidates for adaptive selection within the human population.

ASHLEYS: automated quality control for single-cell Strand-seq data

Summary

Single-cell DNA template strand sequencing (Strand-seq) enables chromosome length haplotype phasing, construction of phased assemblies, mapping sister-chromatid exchange events and structural variant discovery. The initial quality control of potentially thousands of single-cell libraries is still done manually by domain experts. ASHLEYS automates this tedious task, delivers near-expert performance and labels even large datasets in seconds.

Availability and implementation

github.com/friendsofstrandseq/ashleys-qc, MIT license.

Supplementary information

Supplementary data are available at Bioinformatics online.

Construction of Whole Genomes from Scaffolds Using Single Cell Strand-Seq Data

Accurate reference genome sequences provide the foundation for modern molecular biology and genomics as the interpretation of sequence data to study evolution, gene expression, and epigenetics depends heavily on the quality of the genome assembly used for its alignment. Correctly organising sequenced fragments such as contigs and scaffolds in relation to each other is a critical and often challenging step in the construction of robust genome references. We previously identified misoriented regions in the mouse and human reference assemblies using Strand-seq, a single cell sequencing technique that preserves DNA directionality Here we demonstrate the ability of Strand-seq to build and correct full-length chromosomes by identifying which scaffolds belong to the same chromosome and determining their correct order and orientation, without the need for overlapping sequences. We demonstrate that Strand-seq exquisitely maps assembly fragments into large related groups and chromosome-sized clusters without using new assembly data. Using template strand inheritance as a bi-allelic marker, we employ genetic mapping principles to cluster scaffolds that are derived from the same chromosome and order them within the chromosome based solely on directionality of DNA strand inheritance. We prove the utility of our approach by generating improved genome assemblies for several model organisms including the ferret, pig, Xenopus, zebrafish, Tasmanian devil and the Guinea pig.

Targeted Double-Stranded cDNA Sequencing-Based Phase Analysis to Identify Compound Heterozygous Mutations and Differential Allelic Expression

Simple Summary

Phase analysis to distinguish between in cis and in trans heterozygous mutations is important for clinical diagnosis because in trans compound heterozygous mutations cause autosomal recessive diseases. However, conventional phase analysis is limited because of the large target size of genomic DNA. Here, we performed a targeted double-stranded cDNA sequencing-based phase analysis to resolve the limitation of distance using direct adapter ligation library preparation and paired-end sequencing; we elucidated that two heterozygous mutations on a patient with Wilson disease are in trans compound heterozygous mutations. Furthermore, we detected the differential allelic expression. Our results indicate that a targeted double-stranded cDNA sequencing-based phase analysis is useful for determining compound heterozygous mutations and confers information on allelic expression.

Abstract

There are two combinations of heterozygous mutation, i.e., in trans, which carries mutations on different alleles, and in cis, which carries mutations on the same allele. Because only in trans compound heterozygous mutations have been implicated in autosomal recessive diseases, it is important to distinguish them for clinical diagnosis. However, conventional phase analysis is limited because of the large target size of genomic DNA. Here, we performed a genetic analysis on a patient with Wilson disease, and we detected two heterozygous mutations chr13:51958362;G>GG (NM_000053.4:c.2304dup r.2304dup p.Met769HisfsTer26) and chr13:51964900;C>T (NM_000053.4:c.1841G>A r.1841g>a p.Gly614Asp) in the causative gene ATP7B. The distance between the two mutations was 6.5 kb in genomic DNA but 464 bp in mRNA. Targeted double-stranded cDNA sequencing-based phase analysis was performed using direct adapter ligation library preparation and paired-end sequencing, and we elucidated they are in trans compound heterozygous mutations. Trio analysis showed that the mutation (chr13:51964900;C>T) derived from the father and the other mutation from the mother, validating that the mutations are in trans composition. Furthermore, targeted double-stranded cDNA sequencing-based phase analysis detected the differential allelic expression, suggesting that the mutation (chr13:51958362;G>GG) caused downregulation of expression by nonsense-mediated mRNA decay. Our results indicate that targeted double-stranded cDNA sequencing-based phase analysis is useful for determining compound heterozygous mutations and confers information on allelic expression.

Fully phased human genome assembly without parental data using single-cell strand sequencing and long reads

Human genomes are typically assembled as consensus sequences that lack information on parental haplotypes. Here we describe a reference-free workflow for diploid de novo genome assembly that combines the chromosome-wide phasing and scaffolding capabilities of single-cell strand sequencing1,2 with continuous long-read or high-fidelity3 sequencing data. Employing this strategy, we produced a completely phased de novo genome assembly for each haplotype of an individual of Puerto Rican descent (HG00733) in the absence of parental data. The assemblies are accurate (quality value > 40) and highly contiguous (contig N50 > 23 Mbp) with low switch error rates (0.17%), providing fully phased single-nucleotide variants, indels and structural variants. A comparison of Oxford Nanopore Technologies and Pacific Biosciences phased assemblies identified 154 regions that are preferential sites of contig breaks, irrespective of sequencing technology or phasing algorithms.

A Long-Read Sequencing Approach for Direct Haplotype Phasing in Clinical Settings

The reconstruction of individual haplotypes can facilitate the interpretation of disease risks; however, high costs and technical challenges still hinder their assessment in clinical settings. Second-generation sequencing is the gold standard for variant discovery but, due to the production of short reads covering small genomic regions, allows only indirect haplotyping based on statistical methods. In contrast, third-generation methods such as the nanopore sequencing platform developed by Oxford Nanopore Technologies (ONT) generate long reads that can be used for direct haplotyping, with fewer drawbacks. However, robust standards for variant phasing in ONT-based target resequencing efforts are not yet available. In this study, we presented a streamlined proof-of-concept workflow for variant calling and phasing based on ONT data in a clinically relevant 12-kb region of the APOE locus, a hotspot for variants and haplotypes associated with aging-related diseases and longevity. Starting with sequencing data from simple amplicons of the target locus, we demonstrated that ONT data allow for reliable single-nucleotide variant (SNV) calling and phasing from as little as 60 reads, although the recognition of indels is less efficient. Even so, we identified the best combination of ONT read sets (600) and software (BWA/Minimap2 and HapCUT2) that enables full haplotype reconstruction when both SNVs and indels have been identified previously using a highly-accurate sequencing platform. In conclusion, we established a rapid and inexpensive workflow for variant phasing based on ONT long reads. This allowed for the analysis of multiple samples in parallel and can easily be implemented in routine clinical practice, including diagnostic testing.

Long-read human genome sequencing and its applications

Over the past decade, long-read, single-molecule DNA sequencing technologies have emerged as powerful players in genomics. With the ability to generate reads tens to thousands of kilobases in length with an accuracy approaching that of short-read sequencing technologies, these platforms have proven their ability to resolve some of the most challenging regions of the human genome, detect previously inaccessible structural variants and generate some of the first telomere-to-telomere assemblies of whole chromosomes. Long-read sequencing technologies will soon permit the routine assembly of diploid genomes, which will revolutionize genomics by revealing the full spectrum of human genetic variation, resolving some of the missing heritability and leading to the discovery of novel mechanisms of disease.

Detecting chromatin interactions between and along sister chromatids with SisterC

Chromosome segregation requires both compaction and disentanglement of sister chromatids. We describe SisterC, a chromosome conformation capture assay that distinguishes interactions between and along identical sister chromatids. SisterC employs BrdU incorporation during S-phase to label newly replicated strands, followed by Hi-C and then the destruction of BrdU-containing strands by UV/Hoechst treatment. After sequencing of the remaining intact strands, this allows for assignment of Hi-C products as inter- and intra-sister interactions based on the strands that reads are mapped to. We performed SisterC on mitotic S. cerevisiae cells. We find precise alignment of sister chromatids at centromeres. Along arms, sister chromatids are less precisely aligned with inter-sister connections every ~35kb. Inter-sister interactions occur between cohesin binding sites that often are offset by 5 to 25kb. Along sister chromatids, cohesin forms loops of up to 50kb. SisterC allows study of the complex interplay between sister chromatid compaction and their segregation during mitosis.

A diploid assembly-based benchmark for variants in the major histocompatibility complex

Most human genomes are characterized by aligning individual reads to the reference genome, but accurate long reads and linked reads now enable us to construct accurate, phased de novo assemblies. We focus on a medically important, highly variable, 5 million base-pair (bp) region where diploid assembly is particularly useful - the Major Histocompatibility Complex (MHC). Here, we develop a human genome benchmark derived from a diploid assembly for the openly-consented Genome in a Bottle sample HG002. We assemble a single contig for each haplotype, align them to the reference, call phased small and structural variants, and define a small variant benchmark for the MHC, covering 94% of the MHC and 22368 variants smaller than 50 bp, 49% more variants than a mapping-based benchmark. This benchmark reliably identifies errors in mapping-based callsets, and enables performance assessment in regions with much denser, complex variation than regions covered by previous benchmarks.

breakpointR: an R/Bioconductor package to localize strand state changes in Strand-seq data

MOTIVATION

Strand-seq is a specialized single-cell DNA sequencing technique centered around the directionality of single-stranded DNA. Computational tools for Strand-seq analyses must capture the strand-specific information embedded in these data.

RESULTS

Here we introduce breakpointR, an R/Bioconductor package specifically tailored to process and interpret single-cell strand-specific sequencing data obtained from Strand-seq. We developed breakpointR to detect local changes in strand directionality of aligned Strand-seq data, to enable fine-mapping of sister chromatid exchanges, germline inversion and to support global haplotype assembly. Given the broad spectrum of Strand-seq applications we expect breakpointR to be an important addition to currently available tools and extend the accessibility of this novel sequencing technique.

AVAILABILITY AND IMPLEMENTATION

R/Bioconductor package https://bioconductor.org/packages/breakpointR.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Fully Phased Sequence of a Diploid Human Genome Determined de Novo from the DNA of a Single Individual

In recent years, improved sequencing technology and computational tools have made de novo genome assembly more accessible. Many approaches, however, generate either an unphased or only partially resolved representation of a diploid genome, in which polymorphisms are detected but not assigned to one or the other of the homologous chromosomes. Yet chromosomal phase information is invaluable for the understanding of phenotypic trait inheritance in the cases of compound heterozygosity, allele-specific expression or cis-acting variants. Here we use a combination of tools and sequencing technologies to generate a de novo diploid assembly of the human primary cell line WI-38. First, data from PacBio single molecule sequencing and Bionano Genomics optical mapping were combined to generate an unphased assembly. Next, 10x Genomics linked reads were combined with the hybrid assembly to generate a partially phased assembly. Lastly, we developed and optimized methods to use short-read (Illumina) sequencing of flow cytometry-sorted metaphase chromosomes to provide phase information. The final genome assembly was almost fully (94%) phased with the addition of approximately 2.5-fold coverage of Illumina data from the sequenced metaphase chromosomes. The diploid nature of the final de novo genome assembly improved the resolution of structural variants between the WI-38 genome and the human reference genome. The phased WI-38 sequence data are available for browsing and download at wi38.research.calicolabs.com. Our work shows that assembling a completely phased diploid genome de novo from the DNA of a single individual is now readily achievable.

MRLR: unraveling high-resolution meiotic recombination by linked reads

MOTIVATION

Meiotic recombination facilitates the transmission of exchanged genetic material between homologous chromosomes and plays a crucial role in increasing the genetic variations in eukaryotic organisms. In humans, thousands of crossover events have been identified by genotyping related family members. However, most of these crossover regions span tens to hundreds of kb, which is not sufficient resolution to accurately identify the crossover breakpoints in a typical trio family.

RESULTS

We have developed MRLR, a software using 10X linked reads to identify crossover events at a high resolution. By reconstructing the gamete genome, MRLR only requires a trio family dataset and can efficiently discover the crossover events. Using MRLR, we revealed a fine-scale pattern of crossover regions in six human families. From the two closest heterozygous alleles around the crossovers, we determined that MRLR achieved a median resolution 4.5 kb. This method can delineate a genome-wide landscape of crossover events at a precise scale, which is important for both functional and genomic features analysis of meiotic recombination.

AVAILABILITY AND IMPLEMENTATION

MRLR is freely available at https://github.com/ChongLab/MRLR, implemented in Perl.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Recurrent inversion toggling and great ape genome evolution

Inversions play an important role in disease and evolution but are difficult to characterize because their breakpoints map to large repeats. We increased by sixfold the number (n = 1,069) of previously reported great ape inversions by using single-cell DNA template strand and long-read sequencing. We find that the X chromosome is most enriched (2.5-fold) for inversions, on the basis of its size and duplication content. There is an excess of differentially expressed primate genes near the breakpoints of large (>100 kilobases (kb)) inversions but not smaller events. We show that when great ape lineage-specific duplications emerge, they preferentially (approximately 75%) occur in an inverted orientation compared to that at their ancestral locus. We construct megabase-pair scale haplotypes for individual chromosomes and identify 23 genomic regions that have recurrently toggled between a direct and an inverted state over 15 million years. The direct orientation is most frequently the derived state for human polymorphisms that predispose to recurrent copy number variants associated with neurodevelopmental disease.

PhaseME: Automatic rapid assessment of phasing quality and phasing improvement

BACKGROUND

The detection of which mutations are occurring on the same DNA molecule is essential to predict their consequences. This can be achieved by phasing the genomic variations. Nevertheless, state-of-the-art haplotype phasing is currently a black box in which the accuracy and quality of the reconstructed haplotypes are hard to assess.

FINDINGS

Here we present PhaseME, a versatile method to provide insights into and improvement of sample phasing results based on linkage data. We showcase the performance and the importance of PhaseME by comparing phasing information obtained from Pacific Biosciences including both continuous long reads and high-quality consensus reads, Oxford Nanopore Technologies, 10x Genomics, and Illumina sequencing technologies. We found that 10x Genomics and Oxford Nanopore phasing can be significantly improved while retaining a high N50 and completeness of phase blocks. PhaseME generates reports and summary plots to provide insights into phasing performance and correctness. We observed unique phasing issues for each of the sequencing technologies, highlighting the necessity of quality assessments. PhaseME is able to decrease the Hamming error rate significantly by 22.4% on average across all 5 technologies. Additionally, a significant improvement is obtained in the reduction of long switch errors. Especially for high-quality consensus reads, the improvement is 54.6% in return for only a 5% decrease in phase block N50 length.

CONCLUSIONS

PhaseME is a universal method to assess the phasing quality and accuracy and improves the quality of phasing using linkage information. The package is freely available at https://github.com/smajidian/phaseme.

Overlap graph-based generation of haplotigs for diploids and polyploids

MOTIVATION

Haplotype-aware genome assembly plays an important role in genetics, medicine and various other disciplines, yet generation of haplotype-resolved de novo assemblies remains a major challenge. Beyond distinguishing between errors and true sequential variants, one needs to assign the true variants to the different genome copies. Recent work has pointed out that the enormous quantities of traditional NGS read data have been greatly underexploited in terms of haplotig computation so far, which reflects that methodology for reference independent haplotig computation has not yet reached maturity.

RESULTS

We present POLYploid genome fitTEr (POLYTE) as a new approach to de novo generation of haplotigs for diploid and polyploid genomes of known ploidy. Our method follows an iterative scheme where in each iteration reads or contigs are joined, based on their interplay in terms of an underlying haplotype-aware overlap graph. Along the iterations, contigs grow while preserving their haplotype identity. Benchmarking experiments on both real and simulated data demonstrate that POLYTE establishes new standards in terms of error-free reconstruction of haplotype-specific sequence. As a consequence, POLYTE outperforms state-of-the-art approaches in various relevant aspects, where advantages become particularly distinct in polyploid settings.

AVAILABILITY AND IMPLEMENTATION

POLYTE is freely available as part of the HaploConduct package at https://github.com/HaploConduct/HaploConduct, implemented in Python and C++.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Hap10: reconstructing accurate and long polyploid haplotypes using linked reads

BACKGROUND

Haplotype information is essential for many genetic and genomic analyses, including genotype-phenotype associations in human, animals and plants. Haplotype assembly is a method for reconstructing haplotypes from DNA sequencing reads. By the advent of new sequencing technologies, new algorithms are needed to ensure long and accurate haplotypes. While a few linked-read haplotype assembly algorithms are available for diploid genomes, to the best of our knowledge, no algorithms have yet been proposed for polyploids specifically exploiting linked reads.

RESULTS

The first haplotyping algorithm designed for linked reads generated from a polyploid genome is presented, built on a typical short-read haplotyping method, SDhaP. Using the input aligned reads and called variants, the haplotype-relevant information is extracted. Next, reads with the same barcodes are combined to produce molecule-specific fragments. Then, these fragments are clustered into strongly connected components which are then used as input of a haplotype assembly core in order to estimate accurate and long haplotypes.

CONCLUSIONS

Hap10 is a novel algorithm for haplotype assembly of polyploid genomes using linked reads. The performance of the algorithms is evaluated in a number of simulation scenarios and its applicability is demonstrated on a real dataset of sweet potato.

Minimum error correction-based haplotype assembly: Considerations for long read data

The single nucleotide polymorphism (SNP) is the most widely studied type of genetic variation. A haplotype is defined as the sequence of alleles at SNP sites on each haploid chromosome. Haplotype information is essential in unravelling the genome-phenotype association. Haplotype assembly is a well-known approach for reconstructing haplotypes, exploiting reads generated by DNA sequencing devices. The Minimum Error Correction (MEC) metric is often used for reconstruction of haplotypes from reads. However, problems with the MEC metric have been reported. Here, we investigate the MEC approach to demonstrate that it may result in incorrectly reconstructed haplotypes for devices that produce error-prone long reads. Specifically, we evaluate this approach for devices developed by Illumina, Pacific BioSciences and Oxford Nanopore Technologies. We show that imprecise haplotypes may be reconstructed with a lower MEC than that of the exact haplotype. The performance of MEC is explored for different coverage levels and error rates of data. Our simulation results reveal that in order to avoid incorrect MEC-based haplotypes, a coverage of 25 is needed for reads generated by Pacific BioSciences RS systems.

Alfred: interactive multi-sample BAM alignment statistics, feature counting and feature annotation for long- and short-read sequencing

Summary

Harmonizing quality control (QC) of large-scale second and third-generation sequencing datasets is key for enabling downstream computational and biological analyses. We present Alfred, an efficient and versatile command-line application that computes multi-sample QC metrics in a read-group aware manner, across a wide variety of sequencing assays and technologies. In addition to standard QC metrics such as GC bias, base composition, insert size and sequencing coverage distributions it supports haplotype-aware and allele-specific feature counting and feature annotation. The versatility of Alfred allows for easy pipeline integration in high-throughput settings, including DNA sequencing facilities and large-scale research initiatives, enabling continuous monitoring of sequence data quality and characteristics across samples. Alfred supports haplo-tagging of BAM/CRAM files to conduct haplotype-resolved analyses in conjunction with a variety of next-generation sequencing based assays. Alfred’s companion web application enables interactive exploration of results and comparison to public datasets.

Availability and implementation

Alfred is open-source and freely available at https://tobiasrausch.com/alfred/.

Supplementary information

Supplementary data are available at Bioinformatics online.

Single-cell analysis of structural variations and complex rearrangements with tri-channel processing

Structural variation (SV), involving deletions, duplications, inversions and translocations of DNA segments, is a major source of genetic variability in somatic cells and can dysregulate cancer-related pathways. However, discovering somatic SVs in single cells has been challenging, with copy-number-neutral and complex variants typically escaping detection. Here we describe single-cell tri-channel processing (scTRIP), a computational framework that integrates read depth, template strand and haplotype phase to comprehensively discover SVs in individual cells. We surveyed SV landscapes of 565 single cells, including transformed epithelial cells and patient-derived leukemic samples, to discover abundant SV classes, including inversions, translocations and complex DNA rearrangements. Analysis of the leukemic samples revealed four times more somatic SVs than cytogenetic karyotyping, submicroscopic copy-number alterations, oncogenic copy-neutral rearrangements and a subclonal chromothripsis event. Advancing current methods, single-cell tri-channel processing can directly measure SV mutational processes in individual cells, such as breakage-fusion-bridge cycles, facilitating studies of clonal evolution, genetic mosaicism and SV formation mechanisms, which could improve disease classification for precision medicine.

Refined detection and phasing of structural aberrations in pediatric acute lymphoblastic leukemia by linked-read whole-genome sequencing

Structural chromosomal rearrangements that can lead to in-frame gene-fusions are a leading source of information for diagnosis, risk stratification, and prognosis in pediatric acute lymphoblastic leukemia (ALL). Traditional methods such as karyotyping and FISH struggle to accurately identify and phase such large-scale chromosomal aberrations in ALL genomes. We therefore evaluated linked-read WGS for detecting chromosomal rearrangements in primary samples of from 12 patients diagnosed with ALL. We assessed the effect of input DNA quality on phased haplotype block size and the detectability of copy number aberrations and structural variants in the ALL genomes. We found that biobanked DNA isolated by standard column-based extraction methods was sufficient to detect chromosomal rearrangements even at low 10x sequencing coverage. Linked-read WGS enabled precise, allele-specific, digital karyotyping at a base-pair resolution for a wide range of structural variants including complex rearrangements and aneuploidy assessment. With use of haplotype information from the linked-reads, we also identified previously unknown structural variants, such as a compound heterozygous deletion of ERG in a patient with the DUX4-IGH fusion gene. We conclude that linked-read WGS allows detection of important pathogenic variants in ALL genomes at a resolution beyond that of traditional karyotyping and FISH.