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

Approach for Phased Sequence-Based Genotyping of the Critical Pharmacogene Dihydropyrimidine Dehydrogenase (DPYD)

Pre-treatment genotyping of four well-characterized toxicity risk-variants in the dihydropyrimidine dehydrogenase gene (DPYD) has been widely implemented in Europe to prevent serious adverse effects in cancer patients treated with fluoropyrimidines. Current genotyping practices are largely limited to selected commonly studied variants and are unable to determine phasing when more than one variant allele is detected. Recent evidence indicates that common DPYD variants modulate the functional impact of deleterious variants in a phase-dependent manner, where a cis- or a trans-configuration translates into different toxicity risks and dosing recommendations. DPYD is a large gene with 23 exons spanning nearly a mega-base of DNA, making it a challenging candidate for full-gene sequencing in the diagnostic setting. Herein, we present a time- and cost-efficient long-read sequencing approach for capturing the complete coding region of DPYD. We demonstrate that this method can reliably produce phased genotypes, overcoming a major limitation with current methods. This method was validated using 21 subjects, including two cancer patients, each of whom carried multiple DPYD variants. Genotype assignments showed complete concordance with conventional approaches. Furthermore, we demonstrate that the method is robust to technical challenges inherent in long-range sequencing of PCR products, including reference alignment bias and PCR chimerism.

Exome-wide evidence of compound heterozygous effects across common phenotypes in the UK Biobank

The phenotypic impact of compound heterozygous (CH) variation has not been investigated at the population scale. We phased rare variants (MAF ∼0.001%) in the UK Biobank (UKBB) exome-sequencing data to characterize recessive effects in 175,587 individuals across 311 common diseases. A total of 6.5% of individuals carry putatively damaging CH variants, 90% of which are only identifiable upon phasing rare variants (MAF < 0.38%). We identify six recessive gene-trait associations (p < 1.68 × 10-7) after accounting for relatedness, polygenicity, nearby common variants, and rare variant burden. Of these, just one is discovered when considering homozygosity alone. Using longitudinal health records, we additionally identify and replicate a novel association between bi-allelic variation in ATP2C2 and an earlier age at onset of chronic obstructive pulmonary disease (COPD) (p < 3.58 × 10-8). Genetic phase contributes to disease risk for gene-trait pairs: ATP2C2-COPD (p = 0.000238), FLG-asthma (p = 0.00205), and USH2A-visual impairment (p = 0.0084). We demonstrate the power of phasing large-scale genetic cohorts to discover phenome-wide consequences of compound heterozygosity.

Assessing the merits: an opinion on the effectiveness of simulation techniques in tumor subclonal reconstruction

Summary

Neoplastic tumors originate from a single cell, and their evolution can be traced through lineages characterized by mutations, copy number alterations, and structural variants. These lineages are reconstructed and mapped onto evolutionary trees with algorithmic approaches. However, without ground truth benchmark sets, the validity of an algorithm remains uncertain, limiting potential clinical applicability. With a growing number of algorithms available, there is urgent need for standardized benchmark sets to evaluate their merits. Benchmark sets rely on in silico simulations of tumor sequence, but there are no accepted standards for simulation tools, presenting a major obstacle to progress in this field.

Availability and implementation

All analysis done in the paper was based on publicly available data from the publication of each accessed tool.

Haplotype Inference Using Long-Read Nanopore Sequencing: Application to GSTA1 Promoter

Recovering true haplotypes can have important clinical consequences. The laboratory process is difficult and is, therefore, most often done through inference. In this paper, we show that when using the Oxford nanopore sequencing technology, we could recover the true haplotypes of the GSTA1 promoter region. Eight LCL cell lines with potentially ambiguous haplotypes were used to characterize the efficacy of Oxford nanopore sequencing to phase the correct GSTA1 promoter haplotypes. The results were compared to Sanger sequencing and inferred haplotypes in the 1000 genomes project. The average read length was 813 bp out of a total PCR length of 1336 bp. The best coverage of sequencing was in the middle of the PCR product and decreased to 50% at the PCR ends. SNPs separated by less than 200 bp showed > 90% of correct haplotypes, while at the distance of 1089 bp, this proportion still exceeded 58%. The number of cycles influences the generation of hybrid haplotypes but not extension or annealing time. The results demonstrate that this long sequencing reads methodology, can accurately determine the haplotypes without the need for inference. The technology proved to be robust but the success of phasing nonetheless depends on the distances and frequencies of SNPs.

Long-read sequencing for brain tumors

Brain tumors and genomics have a long-standing history given that glioblastoma was the first cancer studied by the cancer genome atlas. The numerous and continuous advances through the decades in sequencing technologies have aided in the advanced molecular characterization of brain tumors for diagnosis, prognosis, and treatment. Since the implementation of molecular biomarkers by the WHO CNS in 2016, the genomics of brain tumors has been integrated into diagnostic criteria. Long-read sequencing, also known as third generation sequencing, is an emerging technique that allows for the sequencing of longer DNA segments leading to improved detection of structural variants and epigenetics. These capabilities are opening a way for better characterization of brain tumors. Here, we present a comprehensive summary of the state of the art of third-generation sequencing in the application for brain tumor diagnosis, prognosis, and treatment. We discuss the advantages and potential new implementations of long-read sequencing into clinical paradigms for neuro-oncology patients.

Meat-Borne-Parasite: A Nanopore-Based Meta-Barcoding Work-Flow for Parasitic Microbiodiversity Assessment in the Wild Fauna of French Guiana

French Guiana, located in the Guiana Shield, is a natural reservoir for many zoonotic pathogens that are of considerable medical or veterinary importance. Until now, there has been limited data available on the description of parasites circulating in this area, especially on protozoan belonging to the phylum Apicomplexa; conversely, the neighbouring countries describe a high parasitic prevalence in animals and humans. Epidemiological surveillance is necessary, as new potentially virulent strains may emerge from these forest ecosystems, such as Amazonian toxoplasmosis. However, there is no standard tool for detecting protozoa in wildlife. In this study, we developed Meat-Borne-Parasite, a high-throughput meta-barcoding workflow for detecting Apicomplexa based on the Oxford Nanopore Technologies sequencing platform using the 18S gene of 14 Apicomplexa positive samples collected in French Guiana. Sequencing reads were then analysed with MetONTIIME pipeline. Thanks to a scoring rule, we were able to classify 10 samples out of 14 as Apicomplexa positive and reveal the presence of co-carriages. The same samples were also sequenced with the Illumina platform for validation purposes. For samples identified as Apicomplexa positive by both platforms, a strong positive correlation at up to the genus level was reported. Overall, the presented workflow represents a reliable method for Apicomplexa detection, which may pave the way for more comprehensive biomonitoring of zoonotic pathogens.

A Comprehensive Allele Specific Expression Resource for the Equine Transcriptome

Background

Allele-specific expression (ASE) analysis provides a nuanced view of cis-regulatory mechanisms affecting gene expression.

Results

An equine ASE analysis was performed, using integrated Iso-seq and short-read RNA sequencing data from four healthy Thoroughbreds (2 mares and 2 stallions) across 9 tissues from the Functional Annotation of Animal Genomes (FAANG) project. Allele expression was quantified by haplotypes from long-read data, with 42,900 allele expression events compared. Within these events, 635 (1.48%) demonstrated ASE, with liver tissue containing the highest proportion. Genetic variants within ASE events were in histone modified regions 64.2% of the time. Validation of allele-specific variants, using a set of 66 equine liver samples from multiple breeds, confirmed that 97% of variants demonstrated ASE.

Conclusions

This valuable publicly accessible resource is poised to facilitate investigations into regulatory variation in equine tissues. Our results highlight the tissue-specific nature of allelic imbalance in the equine genome.

Evaluation of simulation methods for tumor subclonal reconstruction

Most neoplastic tumors originate from a single cell, and their evolution can be genetically traced through lineages characterized by common alterations such as small somatic mutations (SSMs), copy number alterations (CNAs), structural variants (SVs), and aneuploidies. Due to the complexity of these alterations in most tumors and the errors introduced by sequencing protocols and calling algorithms, tumor subclonal reconstruction algorithms are necessary to recapitulate the DNA sequence composition and tumor evolution in silico. With a growing number of these algorithms available, there is a pressing need for consistent and comprehensive benchmarking, which relies on realistic tumor sequencing generated by simulation tools. Here, we examine the current simulation methods, identifying their strengths and weaknesses, and provide recommendations for their improvement. Our review also explores potential new directions for research in this area. This work aims to serve as a resource for understanding and enhancing tumor genomic simulations, contributing to the advancement of the field.

A Comprehensive Allele Specific Expression Resource for the Equine Transcriptome

Background

Allele-specific expression (ASE) analysis provides a nuanced view of cis-regulatory mechanisms affecting gene expression.

Results

In this work, we introduce and highlight the significance of an equine ASE analysis, containing integrated long- and short-read RNA sequencing data, along with insight from histone modification data, from four healthy Thoroughbreds (2 mares and 2 stallions) across 9 tissues.

Conclusions

This valuable publicly accessible resource is poised to facilitate investigations into regulatory variation in equine tissues and foster a deeper understanding of the impact of allelic imbalance in equine health and disease at the molecular level.

The Oxford Nanopore MinION as a Versatile Technology for the Diagnosis and Characterization of Emerging Plant Viruses

The emergence of novel viral epidemics that could affect major crops represents a serious threat to global food security. The early and accurate identification of the causative viral agent is the most important step for a rapid and effective response to disease outbreaks. Over the last years, the Oxford Nanopore Technologies (ONT) MinION sequencer has been proposed as an effective diagnostic tool for the early detection and identification of emerging viruses in plants, providing many advantages compared with different high-throughput sequencing (HTS) technologies. Here, we provide a step-by-step protocol that we optimized to obtain the virome of "Lamon bean" plants (Phaseolus vulgaris L.), an agricultural product with Protected Geographical Indication (PGI) in North-East of Italy, which is frequently subjected to multiple infections caused by different RNA viruses. The conversion of viral RNA in ds-cDNA enabled the use of Genomic DNA Ligation Sequencing Kit and Native Barcoding DNA Kit, which have been originally developed for DNA sequencing. This allowed the simultaneous diagnosis of both DNA- and RNA-based pathogens, providing a more versatile alternative to the use of direct RNA and/or direct cDNA sequencing kits.

Inferring compound heterozygosity from large-scale exome sequencing data

Recessive diseases arise when both copies of a gene are impacted by a damaging genetic variant. When a patient carries two potentially causal variants in a gene, accurate diagnosis requires determining that these variants occur on different copies of the chromosome (that is, are in trans) rather than on the same copy (that is, in cis). However, current approaches for determining phase, beyond parental testing, are limited in clinical settings. Here we developed a strategy for inferring phase for rare variant pairs within genes, leveraging genotypes observed in the Genome Aggregation Database (v2, n = 125,748 exomes). Our approach estimates phase with 96% accuracy, both in trio data and in patients with Mendelian conditions and presumed causal compound heterozygous variants. We provide a public resource of phasing estimates for coding variants and counts per gene of rare variants in trans that can aid interpretation of rare co-occurring variants in the context of recessive disease.

vcfdist: accurately benchmarking phased small variant calls in human genomes

Accurately benchmarking small variant calling accuracy is critical for the continued improvement of human whole genome sequencing. In this work, we show that current variant calling evaluations are biased towards certain variant representations and may misrepresent the relative performance of different variant calling pipelines. We propose solutions, first exploring the affine gap parameter design space for complex variant representation and suggesting a standard. Next, we present our tool vcfdist and demonstrate the importance of enforcing local phasing for evaluation accuracy. We then introduce the notion of partial credit for mostly-correct calls and present an algorithm for clustering dependent variants. Lastly, we motivate using alignment distance metrics to supplement precision-recall curves for understanding variant calling performance. We evaluate the performance of 64 phased Truth Challenge V2 submissions and show that vcfdist improves measured insertion and deletion performance consistency across variant representations from R2 = 0.97243 for baseline vcfeval to 0.99996 for vcfdist.

Inferring compound heterozygosity from large-scale exome sequencing data

Recessive diseases arise when both the maternal and the paternal copies of a gene are impacted by a damaging genetic variant in the affected individual. When a patient carries two different potentially causal variants in a gene for a given disorder, accurate diagnosis requires determining that these two variants occur on different copies of the chromosome (i.e., are in trans) rather than on the same copy (i.e. in cis). However, current approaches for determining phase, beyond parental testing, are limited in clinical settings. We developed a strategy for inferring phase for rare variant pairs within genes, leveraging genotypes observed in exome sequencing data from the Genome Aggregation Database (gnomAD v2, n=125,748). When applied to trio data where phase can be determined by transmission, our approach estimates phase with 95.7% accuracy and remains accurate even for very rare variants (allele frequency < 1×10-4). We also correctly phase 95.9% of variant pairs in a set of 293 patients with Mendelian conditions carrying presumed causal compound heterozygous variants. We provide a public resource of phasing estimates from gnomAD, including phasing estimates for coding variants across the genome and counts per gene of rare variants in trans, that can aid interpretation of rare co-occurring variants in the context of recessive disease.

Challenges in identifying mRNA transcript starts and ends from long-read sequencing data

Long-read sequencing (LRS) technologies have the potential to revolutionize scientific discoveries in RNA biology, especially by enabling the comprehensive identification and quantification of full length mRNA isoforms. However, inherently high error rates make the analysis of long-read sequencing data challenging. While these error rates have been characterized for sequence and splice site identification, it is still unclear how accurately LRS reads represent transcript start and end sites. Here, we systematically assess the variability and accuracy of mRNA terminal ends identified by LRS reads across multiple sequencing platforms. We find substantial inconsistencies in both the start and end coordinates of LRS reads spanning a gene, such that LRS reads often fail to accurately recapitulate annotated or empirically derived terminal ends of mRNA molecules. To address this challenge, we introduce an approach to condition reads based on empirically derived terminal ends and identified a subset of reads that are more likely to represent full-length transcripts. Our approach can improve transcriptome analyses by enhancing the fidelity of transcript terminal end identification, but may result in lower power to quantify genes or discover novel isoforms. Thus, it is necessary to be cautious when selecting sequencing approaches and/or interpreting data from long-read RNA sequencing.

Exome-wide evidence of compound heterozygous effects across common phenotypes in the UK Biobank

Exome-sequencing association studies have successfully linked rare protein-coding variation to risk of thousands of diseases. However, the relationship between rare deleterious compound heterozygous (CH) variation and their phenotypic impact has not been fully investigated. Here, we leverage advances in statistical phasing to accurately phase rare variants (MAF ~ 0.001%) in exome sequencing data from 175,587 UK Biobank (UKBB) participants, which we then systematically annotate to identify putatively deleterious CH coding variation. We show that 6.5% of individuals carry such damaging variants in the CH state, with 90% of variants occurring at MAF < 0.34%. Using a logistic mixed model framework, systematically accounting for relatedness, polygenic risk, nearby common variants, and rare variant burden, we investigate recessive effects in common complex diseases. We find six exome-wide significant (P < 1.68 × 10 - 7 ) and 17 nominally significant (P < 5.25 × 10 - 5 ) gene-trait associations. Among these, only four would have been identified without accounting for CH variation in the gene. We further incorporate age-at-diagnosis information from primary care electronic health records, to show that genetic phase influences lifetime risk of disease across 20 gene-trait combinations (FDR < 5%). Using a permutation approach, we find evidence for genetic phase contributing to disease susceptibility for a collection of gene-trait pairs, including FLG-asthma (P = 0.00205 ) and USH2A-visual impairment (P = 0.0084 ). Taken together, we demonstrate the utility of phasing large-scale genetic sequencing cohorts for robust identification of the phenome-wide consequences of compound heterozygosity.

CRISPR/Cas9-Mediated Enrichment Coupled to Nanopore Sequencing Provides a Valuable Tool for the Precise Reconstruction of Large Genomic Target Regions

Complete and accurate identification of genetic variants associated with specific phenotypes can be challenging when there is a high level of genomic divergence between individuals in a study and the corresponding reference genome. We have applied the Cas9-mediated enrichment coupled to nanopore sequencing to perform a targeted de novo assembly and accurately reconstruct a genomic region of interest. This approach was used to reconstruct a 250-kbp target region on chromosome 5 of the common bean genome (Phaseolus vulgaris) associated with the shattering phenotype. Comparing a non-shattering cultivar (Midas) with the reference genome revealed many single-nucleotide variants and structural variants in this region. We cut five 50-kbp tiled sub-regions of Midas genomic DNA using Cas9, followed by sequencing on a MinION device and de novo assembly, generating a single contig spanning the whole 250-kbp region. This assembly increased the number of Illumina reads mapping to genes in the region, improving their genotypability for downstream analysis. The Cas9 tiling approach for target enrichment and sequencing is a valuable alternative to whole-genome sequencing for the assembly of ultra-long regions of interest, improving the accuracy of downstream genotype-phenotype association analysis.

Long-read sequencing for molecular diagnostics in constitutional genetic disorders

Long-read sequencing (LRS) has been around for more than a decade, but widespread adoption of the technology has been slow due to the perceived high error rates and high sequencing cost. This is changing due to the recent advancements to produce highly accurate sequences and the reducing costs. LRS promises significant improvement over short read sequencing in four major areas: (1) better detection of structural variation (2) better resolution of highly repetitive or nonunique regions (3) accurate long-range haplotype phasing and (4) the detection of base modifications natively from the sequencing data. Several successful applications of LRS have demonstrated its ability to resolve molecular diagnoses where short-read sequencing fails to identify a cause. However, the argument for increased diagnostic yield from LRS remains to be validated. Larger cohort studies may be required to establish the realistic boundaries of LRS's clinical utility and analytical validity, as well as the development of standards for clinical applications. We discuss the limitations of the current standard of care, and contrast with the applications and advantages of two major LRS platforms, PacBio and Oxford Nanopore, for molecular diagnostics of constitutional disorders, and present a critical argument about the potential of LRS in diagnostic settings.

Nanopore Sequencing for De Novo Bacterial Genome Assembly and Search for Single-Nucleotide Polymorphism

Nanopore sequencing (ONT) is a new and rapidly developing method for determining nucleotide sequences in DNA and RNA. It serves the ability to obtain long reads of thousands of nucleotides without assembly and amplification during sequencing compared to next-generation sequencing. Nanopore sequencing can help for determination of genetic changes leading to antibiotics resistance. This study presents the application of ONT technology in the assembly of an E. coli genome characterized by a deletion of the tolC gene and known single-nucleotide variations leading to antibiotic resistance, in the absence of a reference genome. We performed benchmark studies to determine minimum coverage depth to obtain a complete genome, depending on the quality of the ONT data. A comparison of existing programs was carried out. It was shown that the Flye program demonstrates plausible assembly results relative to others (Shasta, Canu, and Necat). The required coverage depth for successful assembly strongly depends on the size of reads. When using high-quality samples with an average read length of 8 Kbp or more, the coverage depth of 30× is sufficient to assemble the complete genome de novo and reliably determine single-nucleotide variations in it. For samples with shorter reads with mean lengths of 2 Kbp, a higher coverage depth of 50× is required. Avoiding of mechanical mixing is obligatory for samples preparation. Nanopore sequencing can be used alone to determine antibiotics-resistant genetic features of bacterial strains.

STArS (STrain-Amplicon-Seq), a targeted nanopore sequencing workflow for SARS-CoV-2 diagnostics and genotyping

Diagnostic tests based on reverse transcription–quantitative polymerase chain reaction (RT–qPCR) are the gold standard approach to detect severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection from clinical specimens. However, unless specifically optimized, this method is usually unable to recognize the specific viral strain responsible of coronavirus disease 2019, a crucial information that is proving increasingly important in relation to virus spread and treatment effectiveness. Even if some RT–qPCR commercial assays are currently being developed for the detection of viral strains, they focus only on single/few genetic variants that may not be sufficient to uniquely identify a specific strain. Therefore, genome sequencing approaches remain the most comprehensive solution for virus genotyping and to recognize viral strains, but their application is much less widespread due to higher costs. Starting from the well-established ARTIC protocol coupled to nanopore sequencing, in this work, we developed STArS (STrain-Amplicon-Seq), a cost/time-effective sequencing-based workflow for both SARS-CoV-2 diagnostics and genotyping. A set of 10 amplicons was initially selected from the ARTIC tiling panel, to cover: (i) all the main biologically relevant genetic variants located on the Spike gene; (ii) a minimal set of variants to uniquely identify the currently circulating strains; (iii) genomic sites usually amplified by RT–qPCR method to identify SARS-CoV-2 presence. PCR-amplified clinical samples (both positive and negative for SARS-CoV-2 presence) were pooled together with a serially diluted exogenous amplicon at known concentration and sequenced on a MinION device. Thanks to a scoring rule, STArS had the capability to accurately classify positive samples in agreement with RT–qPCR results, both at the qualitative and quantitative level. Moreover, the method allowed to effectively genotype strain-specific variants and thus also return the phylogenetic classification of SARS-CoV-2-postive samples. Thanks to the reduced turnaround time and costs, the proposed approach represents a step towards simplifying the clinical application of sequencing for viral genotyping, hopefully aiding in combatting the global pandemic.

Features and applications of haplotypes in crop breeding

Climate change with altered pest-disease dynamics and rising abiotic stresses threatens resource-constrained agricultural production systems worldwide. Genomics-assisted breeding (GAB) approaches have greatly contributed to enhancing crop breeding efficiency and delivering better varieties. Fast-growing capacity and affordability of DNA sequencing has motivated large-scale germplasm sequencing projects, thus opening exciting avenues for mining haplotypes for breeding applications. This review article highlights ways to mine haplotypes and apply them for complex trait dissection and in GAB approaches including haplotype-GWAS, haplotype-based breeding, haplotype-assisted genomic selection. Improvement strategies that efficiently deploy superior haplotypes to hasten breeding progress will be key to safeguarding global food security.

Characterization of FMR1 Repeat Expansion and Intragenic Variants by Indirect Sequence Capture

Traditional methods for the analysis of repeat expansions, which underlie genetic disorders, such as fragile X syndrome (FXS), lack single-nucleotide resolution in repeat analysis and the ability to characterize causative variants outside the repeat array. These drawbacks can be overcome by long-read and short-read sequencing, respectively. However, the routine application of next-generation sequencing in the clinic requires target enrichment, and none of the available methods allows parallel analysis of long-DNA fragments using both sequencing technologies. In this study, we investigated the use of indirect sequence capture (Xdrop technology) coupled to Nanopore and Illumina sequencing to characterize FMR1, the gene responsible of FXS. We achieved the efficient enrichment (> 200×) of large target DNA fragments (~60-80 kbp) encompassing the entire FMR1 gene. The analysis of Xdrop-enriched samples by Nanopore long-read sequencing allowed the complete characterization of repeat lengths in samples with normal, pre-mutation, and full mutation status (> 1 kbp), and correctly identified repeat interruptions relevant for disease prognosis and transmission. Single-nucleotide variants (SNVs) and small insertions/deletions (indels) could be detected in the same samples by Illumina short-read sequencing, completing the mutational testing through the identification of pathogenic variants within the FMR1 gene, when no typical CGG repeat expansion is detected. The study successfully demonstrated the parallel analysis of repeat expansions and SNVs/indels in the FMR1 gene at single-nucleotide resolution by combining Xdrop enrichment with two next-generation sequencing approaches. With the appropriate optimization necessary for the clinical settings, the system could facilitate both the study of genotype-phenotype correlation in FXS and enable a more efficient diagnosis and genetic counseling for patients and their relatives.