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

The impact of long-read sequencing on human population-scale genomics

Long-read sequencing technologies, particularly those from Pacific Biosciences and Oxford Nanopore Technologies, are revolutionizing genome research by providing high-resolution insights into complex and repetitive regions of the human genome that were previously inaccessible. These advances have been particularly enabling for the comprehensive detection of genomic structural variants (SVs), which is critical for linking genotype to phenotype in population-scale and rare disease studies, as well as in cancer. Recent developments in sequencing throughput and computational methods, such as pangenome graphs and haplotype-resolved assemblies, are paving the way for the future inclusion of long-read sequencing in clinical cohort studies and disease diagnostics. DNA methylation signals directly obtained from long reads enhance the utility of single-molecule long-read sequencing technologies by enabling molecular phenotypes to be interpreted, and by allowing the identification of the parent of origin of de novo mutations. Despite this recent progress, challenges remain in scaling long-read technologies to large populations due to cost, computational complexity, and the lack of tools to facilitate the efficient interpretation of SVs in graphs. This perspective provides a succinct review on the current state of long-read sequencing in genomics by highlighting its transformative potential and key hurdles, and emphasizing future opportunities for advancing the understanding of human genetic diversity and diseases through population-scale long-read analysis.

Deciphering new insights into copy number variations as drivers of genomic diversity and adaptation in farm animal species

The basis of all improvement in (re)production performance of animals and plants lies in the genetic variation. The underlying genetic variation can be further explored through investigations using molecular markers including single nucleotide polymorphism (SNP) and microsatellite, and more recently structural variants like copy number variations (CNVs). Unlike SNPs, CNVs affect a larger proportion of the genome, making them more impactful vis-à-vis variation at the phenotype level. They significantly contribute to genetic variation and provide raw material for natural and artificial selection for improved performance. CNVs are characterized as unbalanced structural variations that arise from four major mechanisms viz., non-homologous end joining (NHEJ), non-allelic homologous recombination (NAHR), fork stalling and template switching (FoSTeS), and retrotransposition. Various detection methods have been developed to identify CNVs, including molecular techniques and massively parallel sequencing. Next-generation sequencing (NGS)/high-throughput sequencing offers higher resolution and sensitivity, but challenges remain in delineating CNVs in regions with repetitive sequences or high GC content. High-throughput sequencing technologies utilize different methods based on read-pair, split-read, read depth, and assembly approaches (or their combination) to detect CNVs. Read-pair based methods work by mapping discordant reads, while the read-depth approach works on detecting the correlation between read depth and copy number of genetic segments or a gene. Split-read methods involve mapping segments of reads to different locations on the genome, while assembly methods involve comparing contigs to a reference or de novo sequencing. Similar to other marker-trait association studies, CNV-association studies are not uncommon in humans and farm animals. Soon, extensive studies will be needed to deduce the unique evolutionary trajectories and underlying molecular mechanisms for targeted genetic improvements in different farm animal species. The present review delineates the importance of CNVs in genetic studies, their generation along with programs and principles to efficiently identify them, and finally throw light on the existing literature on studies in farm animal species vis-à-vis CNVs.

Diagnostic utility of single-locus DNA methylation mark in Sotos syndrome developed by nanopore sequencing-based episignature

BACKGROUND

In various neurodevelopmental disorders (NDDs), sets of differential methylation marks (referred to as DNA methylation signatures or episignatures) are syndrome-specific and useful in evaluating the pathogenicity of detected genetic variants. These signatures have generally been tested using methylation arrays, requiring additional experimental and evaluation costs. As an alternative, long-read sequencing can simultaneously and accurately evaluate genetic and epigenetic changes. In addition, genome-wide DNA methylation profiling with more complete sets of CpG using long-read sequencing (than methylation arrays) may provide alternative but more comprehensive DNA methylation signatures, which have yet to be adequately investigated.

METHODS

Nine and seven cases of molecularly diagnosed Sotos syndrome and ATR-X syndrome, respectively, were sequenced using nanopore long-read sequencing, together with 22 controls. Genome-wide differential DNA methylation analysis was performed. Among these differential DNA methylation sites, a single-locus DNA methylation mark at part of the NSD1 CpG island (CpGi) was subsequently studied in an additional 22 cases with a NSD1 point mutation or a 5q35 submicroscopic deletion involving NSD1. To investigate the potential utility of a single-locus DNA methylation test at NSD1 CpGi for differential diagnosis, nine cases with NSD1-negative clinically overlapping overgrowth intellectual disability syndromes (OGIDs) were also tested.

RESULTS

Long-read sequencing enabled the successful extraction of two sets of differential methylation marks unique to each of Sotos syndrome and ATR-X syndrome, referred to as long-read-based DNA methylation signatures (LR-DNAm signatures), as alternatives to reported DNA methylation signatures (obtained by methylation array). Additionally, we found that a part, but not all, of the NSD1 CpGi were hypomethylated compared with the level in controls in both cases harboring NSD1 point mutations and those with a 5q35 submicroscopic deletion. This difference in methylation is specific to Sotos syndrome and lacking in other OGIDs.

CONCLUSIONS

Simultaneous evaluation of genetic and epigenetic alterations using long-read sequencing may improve the discovery of DNA methylation signatures, which may in turn increase the diagnostic yields. As an example of the outcomes of these analyses, we propose that a single-locus DNA methylation test at NSD1 CpGi may streamline the molecular diagnosis of Sotos syndrome, regardless of the type of NSD1 aberration.

Uncovering the complexity of structural variants in four individuals with autism spectrum disorder

Autism spectrum disorder (ASD) is an increasingly recognized childhood developmental disorder. Despite extensive study, causal variants and molecular diagnosis remain elusive. There is both heterogeneity of the phenotype, as well as the genetic landscape associated with phenotype, which includes both inherited and de novo mutations. Currently, diagnosis is complex and behaviourally based, oftentimes occurring years after the ideal 1-2 years of age. Structural variants (SVs) are large and sometimes complex genomic variants that are likely underrepresented contributors to ASD due to the limitations of short-read DNA sequencing, such as alignment in repetitive regions and regions with GC bias. Here, we performed long-read sequencing (LRS) on four individuals with autism spectrum disorder to delineate SV complexity and determine precise breakpoints for SVs, which was not possible with short-read whole-genome sequencing (SRS). We use LRS to interrogate the methylation pattern associated with the SVs and phase the SV haplotypes to further clarify their contribution to disorder. LRS allows insight into the genome and methylome that allow us to uncover variant complexity and contribution that was previously unseen with SRS. Ultimately, this furthers precision diagnosis and contributes to individualized treatment for affected individuals and their families within the clinic.

Long-read sequencing for detection and subtyping of Prader-Willi and Angelman syndromes

Prader-Willi syndrome (PWS) and Angelman syndrome (AS) are imprinting disorders caused by genetic or epigenetic aberrations of 15q11.2-q13. Their clinical testing is often multitiered; diagnostic testing begins with methylation-specific multiplex ligation-dependent probe amplification or methylation-sensitive PCR and then proceeds to molecular subtyping to determine the mechanism and recurrence risk. Currently, correct classification of a proband's PWS/AS subtype often requires parental samples, a costly process for families and health systems. The use of nanopore sequencing for molecular diagnosis of PWS and AS has been explored by Yamada et al; however, to confirm heterodisomy parental data were still required. Here, we investigate genome-wide nanopore sequencing in a larger cohort of PWS (18) and AS (6) as a singular test to detect the molecular subtype, without parental data. We accurately subtyped these cases including uniparental heterodisomy, mixed iso-/heterodisomy, type 1 and 2 deletions, microdeletion and UBE3A indels. One PWS case with a previously unresolved diagnosis subtyped as maternal isodisomy. This work highlights the application of long-read sequencing and other imprinted regions outside of the PWS/AS critical region to resolve the molecular diagnosis and subtyping of PWS and AS without parental data. The work also outlines an approach to generically detect heterodisomy through the interrogation of distant imprinted regions.

Shedding light on DNA methylation and its clinical implications: the impact of long-read-based nanopore technology

DNA methylation is an essential epigenetic mechanism for regulation of gene expression, through which many physiological (X-chromosome inactivation, genetic imprinting, chromatin structure and miRNA regulation, genome defense, silencing of transposable elements) and pathological processes (cancer and repetitive sequences-associated diseases) are regulated. Nanopore sequencing has emerged as a novel technique that can analyze long strands of DNA (long-read sequencing) without chemically treating the DNA. Interestingly, nanopore sequencing can also extract epigenetic status of the nucleotides (including both 5-Methylcytosine and 5-hydroxyMethylcytosine), and a large variety of bioinformatic tools have been developed for improving its detection properties. Out of all genomic regions, long read sequencing provides advantages in studying repetitive elements, which are difficult to characterize through other sequencing methods. Transposable elements are repetitive regions of the genome that are silenced and usually display high levels of DNA methylation. Their demethylation and activation have been observed in many cancers. Due to their repetitive nature, it is challenging to accurately estimate DNA methylation levels within transposable elements using short sequencing technologies. The advantage to sequence native DNA (without PCR amplification biases or harsh bisulfite treatment) and long and ultra long reads coupled with epigenetic states of the DNA allows to accurately estimate DNA methylation levels in transposable elements. This is a big step forward for epigenomic studies, and unsolved questions regarding gene expression and transposable elements silencing through DNA methylation can now be answered.

Expanding Upon Genomics in Rare Diseases: Epigenomic Insights

DNA methylation is an essential epigenetic modification that plays a crucial role in regulating gene expression and maintaining genomic stability. With the advancement in sequencing technology, methylation studies have provided valuable insights into the diagnosis of rare diseases through the various identification of episignatures, epivariation, epioutliers, and allele-specific methylation. However, current methylation studies are not without limitations. This mini-review explores the current understanding of DNA methylation in rare diseases, highlighting the key mechanisms and diagnostic potential, and emphasizing the need for advanced methodologies and integrative approaches to enhance the understanding of disease progression and design more personable treatment for patients, given the nature of rare diseases.

Prognostic importance of direct assignment of parent of origin via long-read genome and epigenome sequencing in retinoblastoma

BACKGROUNDCurrent clinical sequencing methods cannot effectively detect DNA methylation and allele-specific variation to provide parent-of-origin information from the proband alone. Parent-of-origin effects can lead to differential disease, and the inability to assign parent of origin in de novo cases limits prognostication in the majority of affected individuals with retinoblastoma, a hereditary cancer with suspected parent-of-origin effects.METHODSTo directly assign parent of origin in patients with retinoblastoma, we extracted genomic DNA from blood samples for sequencing using a programmable, targeted, single-molecule, long-read DNA genomic and epigenomic approach. This allowed germline variant calling and simultaneous haplotype-resolved CpG methylation in participants with familial (n = 7) and de novo (n = 9) retinoblastoma.RESULTSTargeted long-read sequencing allowed phasing genomic variation with a differentially methylated region in intron 2 of the retinoblastoma gene to confirm parent of origin in known familial samples. This approach allowed us to directly assign parent of origin in simple and complex de novo cases from the proband alone. The ability to assign parent of origin in all retinoblastoma cases showed that harboring disease-causing variants on the paternally inherited allele, whether arising familially or de novo, was associated with more advanced cancer staging at presentation and significantly greater risk of chemotherapy failure (P = 0.002).CONCLUSIONThis study demonstrates the diagnostic potential of multiomic long-read profiling to unveil the parent-of-origin effect in hereditary cancer. The approach in this work will be instrumental in assigning parent of origin to other genetic diseases using local and distant imprinting signals in the genome.FUNDINGNational Eye Institute, NIH; Gerber Foundation; Research to Prevent Blindness; Angie Karalis Johnson Fund; Dawn's Light Foundation; and Mark J. Daily, MD Research Fund.

Novel variants and genotype-phenotype correlation in a multicentre cohort of GNE myopathy in China

BACKGROUND

GlcNAc2-epimerase (GNE) myopathy is a rare autosomal recessive disorder caused by pathogenic variants in the GNE gene, which is essential for the sialic acid biosynthesis pathway.

OBJECTIVE

This multi-centre study aimed to delineate the clinical phenotype and GNE variant spectrum in Chinese patients, enhancing our understanding of the genetic diversity and clinical manifestation across different populations.

METHODS

We retrospectively analysed GNE variants from 113 patients, integrating these data with external GNE variants from online databases for a global perspective, examining their consequences, distribution, ethnicity and severity.

RESULTS

This study revealed 97 distinct GNE variants, including 35 (36.08%) novel variants. Two more patients with deep intronic variant c.862+870C>T were identified, while whole genome sequencing (WGS) uncovered another two novel intronic variants: c.52-8924G>T and c.1505-12G>A. Nanopore long reads sequencing (LRS) and further PCR analysis verified a 639 bp insertion at chr9:36249241. Missense variants predominantly located in the epimerase/kinase domain coding region, indicating the impairment of catalytic function as a key pathogenic consequence. Comparative studies with Japanese, Korean and Jewish, our cohorts showed later onset ages by 2 years. The high allele frequency of the non-catalytic GNE variant, c.620A>T, might underlie the milder phenotype of Chinese patients.

CONCLUSIONS

Comprehensive techniques such as WGS and Nanopore LRS warrants the identifying of GNE variants. Patients with the non-catalytic GNE variant, c.620A>T, had a milder disease progression and later wheelchair use.

Graphasing: 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.

Genome assembly in the telomere-to-telomere era

Genome sequences largely determine the biology and encode the history of an organism, and de novo assembly - the process of reconstructing the genome sequence of an organism from sequencing reads - has been a central problem in bioinformatics for four decades. Until recently, genomes were typically assembled into fragments of a few megabases at best, but now technological advances in long-read sequencing enable the near-complete assembly of each chromosome - also known as telomere-to-telomere assembly - for many organisms. Here, we review recent progress on assembly algorithms and protocols, with a focus on how to derive near-telomere-to-telomere assemblies. We also discuss the additional developments that will be required to resolve remaining assembly gaps and to assemble non-diploid genomes.

MethPhaser: methylation-based long-read haplotype phasing of human genomes

The assignment of variants across haplotypes, phasing, is crucial for predicting the consequences, interaction, and inheritance of mutations and is a key step in improving our understanding of phenotype and disease. However, phasing is limited by read length and stretches of homozygosity along the genome. To overcome this limitation, we designed MethPhaser, a method that utilizes methylation signals from Oxford Nanopore Technologies to extend Single Nucleotide Variation (SNV)-based phasing. We demonstrate that haplotype-specific methylations extensively exist in Human genomes and the advent of long-read technologies enabled direct report of methylation signals. For ONT R9 and R10 cell line data, we increase the phase length N50 by 78%-151% at a phasing accuracy of 83.4-98.7% To assess the impact of tissue purity and random methylation signals due to inactivation, we also applied MethPhaser on blood samples from 4 patients, still showing improvements over SNV-only phasing. MethPhaser further improves phasing across HLA and multiple other medically relevant genes, improving our understanding of how mutations interact across multiple phenotypes. The concept of MethPhaser can also be extended to non-human diploid genomes. MethPhaser is available at https://github.com/treangenlab/methphaser .

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.

Pseudoexon activation by deep intronic variation in GNE myopathy with thrombocytopenia

INTRODUCTION/AIMS

GNE myopathy is a rare autosomal recessive disorder caused by pathogenic variants in the GNE gene, which is essential for the sialic acid biosynthesis pathway. Although over 300 GNE variants have been reported, some patients remain undiagnosed with monoallelic pathogenic variants. This study aims to analyze the entire GNE genomic region to identify novel pathogenic variants.

METHODS

Patients with clinically compatible GNE myopathy and monoallelic pathogenic variants in the GNE gene were enrolled. The other GNE pathogenic variant was verified using comprehensive methods including exon 2 quantitative polymerase chain reaction and nanopore long-read single-molecule sequencing (LRS).

RESULTS

A deep intronic GNE variant, c.862+870C>T, was identified in nine patients from eight unrelated families. This variant generates a cryptic splice site, resulting in the activation of a novel pseudoexon between exons 5 and 6. It results in the insertion of an extra 146 nucleotides into the messengerRNA (mRNA), which is predicted to result in a truncated humanGNE1(hGNE1) protein. Peanut agglutinin（PNA） lectin staining of muscle tissues showed reduced sialylation of mucin O-glycans on sarcolemmal glycoproteins. Notably, a third of patients with the c.862+870C>T variant exhibited thrombocytopenia. A common core haplotype harboring the deep intronic GNE variant was found in all these patients.

DISCUSSION

The transcript with pseudoexon activation potentially affects sialic acid biosynthesis via nonsense-mediated mRNA decay, or resulting in a truncated hGNE1 protein, which interferes with normal enzyme function. LRS is expected to be more frequently incorporated in genetic analysis given its efficacy in detecting hard-to-find pathogenic variants.

A signal processing and deep learning framework for methylation detection using Oxford Nanopore sequencing

Oxford Nanopore sequencing can detect DNA methylations from ionic current signal of single molecules, offering a unique advantage over conventional methods. Additionally, adaptive sampling, a software-controlled enrichment method for targeted sequencing, allows reduced representation methylation sequencing that can be applied to CpG islands or imprinted regions. Here we present DeepMod2, a comprehensive deep-learning framework for methylation detection using ionic current signal from Nanopore sequencing. DeepMod2 implements both a bidirectional long short-term memory (BiLSTM) model and a Transformer model and can analyze POD5 and FAST5 signal files generated on R9 and R10 flowcells. Additionally, DeepMod2 can run efficiently on central processing unit (CPU) through model pruning and can infer epihaplotypes or haplotype-specific methylation calls from phased reads. We use multiple publicly available and newly generated datasets to evaluate the performance of DeepMod2 under varying scenarios. DeepMod2 has comparable performance to Guppy and Dorado, which are the current state-of-the-art methods from Oxford Nanopore Technologies that remain closed-source. Moreover, we show a high correlation (r = 0.96) between reduced representation and whole-genome Nanopore sequencing. In summary, DeepMod2 is an open-source tool that enables fast and accurate DNA methylation detection from whole-genome or adaptive sequencing data on a diverse range of flowcell types.

Livestock species as emerging models for genomic imprinting

Genomic imprinting is an epigenetically-regulated process of central importance in mammalian development and evolution. It involves multiple levels of regulation, with spatio-temporal heterogeneity, leading to the context-dependent and parent-of-origin specific expression of a small fraction of the genome. Genomic imprinting studies have therefore been essential to increase basic knowledge in functional genomics, evolution biology and developmental biology, as well as with regard to potential clinical and agrigenomic perspectives. Here we offer an overview on the contribution of livestock research, which features attractive resources in several respects, for better understanding genomic imprinting and its functional impacts. Given the related broad implications and complexity, we promote the use of such resources for studying genomic imprinting in a holistic and integrative view. We hope this mini-review will draw attention to the relevance of livestock genomic imprinting studies and stimulate research in this area.

Crosstalk between chromatin, chromosomes, and epigenetics

The International Asilomar Chromatin, Chromosomes, and Epigenetics Conference was held online from 8 to 10 December 2022. Topics of this year's conference included chromosome dysregulation, genome integrity, nuclear organization, regulation of chromatin, epigenetics, transcription, and gene regulation in cell differentiation and disease. The meeting featured four keynote speakers, including Yamini Dalal (National Cancer Institute, USA), Meaghan Jones (University of Manitoba, Canada), Pedro Rocha (National Institute of Child Health and Human Development, USA), and Vincent Pasque (University of Leuven, Belgium). The meeting brought together scientists at all career stages to present and discuss their work in the fields of chromatin and epigenetics.

Taking identity-by-descent analysis into the wild: Estimating realized relatedness in free-ranging macaques

Biological relatedness is a key consideration in studies of behavior, population structure, and trait evolution. Except for parent-offspring dyads, pedigrees capture relatedness imperfectly. The number and length of DNA segments that are identical-by-descent (IBD) yield the most precise estimates of relatedness. Here, we leverage novel methods for estimating locus-specific IBD from low coverage whole genome resequencing data to demonstrate the feasibility and value of resolving fine-scaled gradients of relatedness in free-living animals. Using primarily 4-6× coverage data from a rhesus macaque (Macaca mulatta) population with available long-term pedigree data, we show that we can call the number and length of IBD segments across the genome with high accuracy even at 0.5× coverage. The resulting estimates demonstrate substantial variation in genetic relatedness within kin classes, leading to overlapping distributions between kin classes. They identify cryptic genetic relatives that are not represented in the pedigree and reveal elevated recombination rates in females relative to males, which allows us to discriminate maternal and paternal kin using genotype data alone. Our findings represent a breakthrough in the ability to understand the predictors and consequences of genetic relatedness in natural populations, contributing to our understanding of a fundamental component of population structure in the wild.

Genome assembly in the telomere-to-telomere era

De novo assembly is the process of reconstructing the genome sequence of an organism from sequencing reads. Genome sequences are essential to biology, and assembly has been a central problem in bioinformatics for four decades. Until recently, genomes were typically assembled into fragments of a few megabases at best but technological advances in long-read sequencing now enable near complete chromosome-level assembly, also known as telomere-to-telomere assembly, for many organisms. Here we review recent progress on assembly algorithms and protocols. We focus on how to derive near telomere-to-telomere assemblies and discuss potential future developments.

DNA 5-methylcytosine detection and methylation phasing using PacBio circular consensus sequencing

Long single-molecular sequencing technologies, such as PacBio circular consensus sequencing (CCS) and nanopore sequencing, are advantageous in detecting DNA 5-methylcytosine in CpGs (5mCpGs), especially in repetitive genomic regions. However, existing methods for detecting 5mCpGs using PacBio CCS are less accurate and robust. Here, we present ccsmeth, a deep-learning method to detect DNA 5mCpGs using CCS reads. We sequence polymerase-chain-reaction treated and M.SssI-methyltransferase treated DNA of one human sample using PacBio CCS for training ccsmeth. Using long (≥10 Kb) CCS reads, ccsmeth achieves 0.90 accuracy and 0.97 Area Under the Curve on 5mCpG detection at single-molecule resolution. At the genome-wide site level, ccsmeth achieves >0.90 correlations with bisulfite sequencing and nanopore sequencing using only 10× reads. Furthermore, we develop a Nextflow pipeline, ccsmethphase, to detect haplotype-aware methylation using CCS reads, and then sequence a Chinese family trio to validate it. ccsmeth and ccsmethphase can be robust and accurate tools for detecting DNA 5-methylcytosines.

Personalized recurrence risk assessment following the birth of a child with a pathogenic de novo mutation

Following the diagnosis of a paediatric disorder caused by an apparently de novo mutation, a recurrence risk of 1-2% is frequently quoted due to the possibility of parental germline mosaicism; but for any specific couple, this figure is usually incorrect. We present a systematic approach to providing individualized recurrence risk. By combining locus-specific sequencing of multiple tissues to detect occult mosaicism with long-read sequencing to determine the parent-of-origin of the mutation, we show that we can stratify the majority of couples into one of seven discrete categories associated with substantially different risks to future offspring. Among 58 families with a single affected offspring (representing 59 de novo mutations in 49 genes), the recurrence risk for 35 (59%) was decreased below 0.1%, but increased owing to parental mixed mosaicism for 5 (9%)-that could be quantified in semen for paternal cases (recurrence risks of 5.6-12.1%). Implementation of this strategy offers the prospect of driving a major transformation in the practice of genetic counselling.