Long-read mapping to repetitive reference sequences using Winnowmap2

ESKEMAP: exact sketch-based read mapping

BACKGROUND

Given a sequencing read, the broad goal of read mapping is to find the location(s) in the reference genome that have a "similar sequence". Traditionally, "similar sequence" was defined as having a high alignment score and read mappers were viewed as heuristic solutions to this well-defined problem. For sketch-based mappers, however, there has not been a problem formulation to capture what problem an exact sketch-based mapping algorithm should solve. Moreover, there is no sketch-based method that can find all possible mapping positions for a read above a certain score threshold.

RESULTS

In this paper, we formulate the problem of read mapping at the level of sequence sketches. We give an exact dynamic programming algorithm that finds all hits above a given similarity threshold. It runs in O ( | t | + | p | + ℓ 2 ) time and O ( ℓ log ℓ ) space, where |t| is the number of k -mers inside the sketch of the reference, |p| is the number of k -mers inside the read's sketch and ℓ is the number of times that k -mers from the pattern sketch occur in the sketch of the text. We evaluate our algorithm's performance in mapping long reads to the T2T assembly of human chromosome Y, where ampliconic regions make it desirable to find all good mapping positions. For an equivalent level of precision as minimap2, the recall of our algorithm is 0.88, compared to only 0.76 of minimap2.

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.

Dynamic co-evolution of transposable elements and the piRNA pathway in African cichlid fishes

East African cichlid fishes have diversified in an explosive fashion, but the (epi)genetic basis of the phenotypic diversity of these fishes remains largely unknown. Although transposable elements (TEs) have been associated with phenotypic variation in cichlids, little is known about their transcriptional activity and epigenetic silencing. Here, we describe dynamic patterns of TE expression in African cichlid gonads and during early development. Orthology inference revealed an expansion of piwil1 genes in Lake Malawi cichlids, likely driven by PiggyBac TEs. The expanded piwil1 copies have signatures of positive selection and retain amino acid residues essential for catalytic activity. Furthermore, the gonads of African cichlids express a Piwi-interacting RNA (piRNA) pathway that target TEs. We define the genomic sites of piRNA production in African cichlids and find divergence in closely related species, in line with fast evolution of piRNA-producing loci. Our findings suggest dynamic co-evolution of TEs and host silencing pathways in the African cichlid radiations. We propose that this co-evolution has contributed to cichlid genomic diversity.

Comparison of structural variant callers for massive whole-genome sequence data

BACKGROUND

Detecting structural variations (SVs) at the population level using next-generation sequencing (NGS) requires substantial computational resources and processing time. Here, we compared the performances of 11 SV callers: Delly, Manta, GridSS, Wham, Sniffles, Lumpy, SvABA, Canvas, CNVnator, MELT, and INSurVeyor. These SV callers have been recently published and have been widely employed for processing massive whole-genome sequencing datasets. We evaluated the accuracy, sequence depth, running time, and memory usage of the SV callers.

RESULTS

Notably, several callers exhibited better calling performance for deletions than for duplications, inversions, and insertions. Among the SV callers, Manta identified deletion SVs with better performance and efficient computing resources, and both Manta and MELT demonstrated relatively good precision regarding calling insertions. We confirmed that the copy number variation callers, Canvas and CNVnator, exhibited better performance in identifying long duplications as they employ the read-depth approach. Finally, we also verified the genotypes inferred from each SV caller using a phased long-read assembly dataset, and Manta showed the highest concordance in terms of the deletions and insertions.

CONCLUSIONS

Our findings provide a comprehensive understanding of the accuracy and computational efficiency of SV callers, thereby facilitating integrative analysis of SV profiles in diverse large-scale genomic datasets.

The Application of Long-Read Sequencing to Cancer

Cancer is a multifaceted disease arising from numerous genomic aberrations that have been identified as a result of advancements in sequencing technologies. While next-generation sequencing (NGS), which uses short reads, has transformed cancer research and diagnostics, it is limited by read length. Third-generation sequencing (TGS), led by the Pacific Biosciences and Oxford Nanopore Technologies platforms, employs long-read sequences, which have marked a paradigm shift in cancer research. Cancer genomes often harbour complex events, and TGS, with its ability to span large genomic regions, has facilitated their characterisation, providing a better understanding of how complex rearrangements affect cancer initiation and progression. TGS has also characterised the entire transcriptome of various cancers, revealing cancer-associated isoforms that could serve as biomarkers or therapeutic targets. Furthermore, TGS has advanced cancer research by improving genome assemblies, detecting complex variants, and providing a more complete picture of transcriptomes and epigenomes. This review focuses on TGS and its growing role in cancer research. We investigate its advantages and limitations, providing a rigorous scientific analysis of its use in detecting previously hidden aberrations missed by NGS. This promising technology holds immense potential for both research and clinical applications, with far-reaching implications for cancer diagnosis and treatment.

Complete genome assembly provides a high-quality skeleton for pan-NLRome construction in melon

Melon (Cucumis melo L.), being under intensive domestication and selective breeding, displays an abundant phenotypic diversity. Wild germplasm with tolerance to stress represents an untapped genetic resource for discovery of disease-resistance genes. To comprehensively characterize resistance genes in melon, we generate a telomere-to-telomere (T2T) and gap-free genome of wild melon accession PI511890 (C. melo var. chito) with a total length of 375.0 Mb and a contig N50 of 31.24 Mb. The complete genome allows us to dissect genome architecture and identify resistance gene analogs. We construct a pan-NLRome using seven melon genomes, which include 208 variable and 18 core nucleotide-binding leucine-rich repeat receptors (NLRs). Multiple disease-related transcriptome analyses indicate that most up-regulated NLRs induced by pathogens are shell or cloud NLRs. The T2T gap-free assembly and the pan-NLRome not only serve as essential resources for genomic studies and molecular breeding of melon but also provide insights into the genome architecture and NLR diversity.

Co-linear chaining on pangenome graphs

Pangenome reference graphs are useful in genomics because they compactly represent the genetic diversity within a species, a capability that linear references lack. However, efficiently aligning sequences to these graphs with complex topology and cycles can be challenging. The seed-chain-extend based alignment algorithms use co-linear chaining as a standard technique to identify a good cluster of exact seed matches that can be combined to form an alignment. Recent works show how the co-linear chaining problem can be efficiently solved for acyclic pangenome graphs by exploiting their small width and how incorporating gap cost in the scoring function improves alignment accuracy. However, it remains open on how to effectively generalize these techniques for general pangenome graphs which contain cycles. Here we present the first practical formulation and an exact algorithm for co-linear chaining on cyclic pangenome graphs. We rigorously prove the correctness and computational complexity of the proposed algorithm. We evaluate the empirical performance of our algorithm by aligning simulated long reads from the human genome to a cyclic pangenome graph constructed from 95 publicly available haplotype-resolved human genome assemblies. While the existing heuristic-based algorithms are faster, the proposed algorithm provides a significant advantage in terms of accuracy. Implementation ( https://github.com/at-cg/PanAligner ).

pathMap: a path-based mapping tool for long noisy reads with high sensitivity

With the rapid development of single-molecule sequencing (SMS) technologies, the output read length is continuously increasing. Mapping such reads onto a reference genome is one of the most fundamental tasks in sequence analysis. Mapping sensitivity is becoming a major concern since high sensitivity can detect more aligned regions on the reference and obtain more aligned bases, which are useful for downstream analysis. In this study, we present pathMap, a novel k-mer graph-based mapper that is specifically designed for mapping SMS reads with high sensitivity. By viewing the alignment chain as a path containing as many anchors as possible in the matched k-mer graph, pathMap treats chaining as a path selection problem in the directed graph. pathMap iteratively searches the longest path in the remaining nodes; more candidate chains with high quality can be effectively detected and aligned. Compared to other state-of-the-art mapping methods such as minimap2 and Winnowmap2, experiment results on simulated and real-life datasets demonstrate that pathMap obtains the number of mapped chains at least 11.50% more than its closest competitor and increases the mapping sensitivity by 17.28% and 13.84% of bases over the next-best mapper for Pacific Biosciences and Oxford Nanopore sequencing data, respectively. In addition, pathMap is more robust to sequence errors and more sensitive to species- and strain-specific identification of pathogens using MinION reads.

Pangenome databases improve host removal and mycobacteria classification from clinical metagenomic data

BACKGROUND

Culture-free real-time sequencing of clinical metagenomic samples promises both rapid pathogen detection and antimicrobial resistance profiling. However, this approach introduces the risk of patient DNA leakage. To mitigate this risk, we need near-comprehensive removal of human DNA sequences at the point of sequencing, typically involving the use of resource-constrained devices. Existing benchmarks have largely focused on the use of standardized databases and largely ignored the computational requirements of depletion pipelines as well as the impact of human genome diversity.

RESULTS

We benchmarked host removal pipelines on simulated and artificial real Illumina and Nanopore metagenomic samples. We found that construction of a custom kraken database containing diverse human genomes results in the best balance of accuracy and computational resource usage. In addition, we benchmarked pipelines using kraken and minimap2 for taxonomic classification of Mycobacterium reads using standard and custom databases. With a database representative of the Mycobacterium genus, both tools obtained improved specificity and sensitivity, compared to the standard databases for classification of Mycobacterium tuberculosis. Computational efficiency of these custom databases was superior to most standard approaches, allowing them to be executed on a laptop device.

CONCLUSIONS

Customized pangenome databases provide the best balance of accuracy and computational efficiency when compared to standard databases for the task of human read removal and M. tuberculosis read classification from metagenomic samples. Such databases allow for execution on a laptop, without sacrificing accuracy, an especially important consideration in low-resource settings. We make all customized databases and pipelines freely available.

Screening Host Genomic Data for Wolbachia Infections

Less than a decade ago, the production of Wolbachia genomic assemblies was tedious, time-consuming, and expensive. The production of Wolbachia genomic DNA free of contamination from host DNA, as required for Wolbachia-targeted sequencing, was then only possible after the amplification and extraction of a large amount of clonal Wolbachia DNA. However, as an endosymbiotic bacterium, Wolbachia does not grow outside the host cell environment, and large-scale recovery of the bacteria required mass rearing of their host, preferably clones of a single individual to avoid strain genetic diversity, or amplification of cell cultures infected with a single Wolbachia strain. Bacterial DNA could be separated from host DNA based on genomic size. Nowadays, the production of full Wolbachia genomes does not require the physical isolation of the bacterial strains from their respective hosts, and the bacterium is often sequenced as a by-catch of host genomic projects. Here, we provide a step-by-step protocol to (1) identify whether host genome projects contain reads from associated Wolbachia and (2) isolate/retrieve the Wolbachia reads from the rest of the sequenced material. We hope this simple protocol will support many projects aiming at studying diverse Wolbachia genome assemblies.

Improved sequence mapping using a complete reference genome and lift-over

Complete, telomere-to-telomere (T2T) genome assemblies promise improved analyses and the discovery of new variants, but many essential genomic resources remain associated with older reference genomes. Thus, there is a need to translate genomic features and read alignments between references. Here we describe a method called levioSAM2 that performs fast and accurate lift-over between assemblies using a whole-genome map. In addition to enabling the use of several references, we demonstrate that aligning reads to a high-quality reference (for example, T2T-CHM13) and lifting to an older reference (for example, Genome reference Consortium (GRC)h38) improves the accuracy of the resulting variant calls on the old reference. By leveraging the quality improvements of T2T-CHM13, levioSAM2 reduces small and structural variant calling errors compared with GRC-based mapping using real short- and long-read datasets. Performance is especially improved for a set of complex medically relevant genes, where the GRC references are lower quality.

Density and Conservation Optimization of the Generalized Masked-Minimizer Sketching Scheme

Minimizers and syncmers are sketching methods that sample representative k-mer seeds from a long string. The minimizer scheme guarantees a well-spread k-mer sketch (high coverage) while seeking to minimize the sketch size (low density). The syncmer scheme yields sketches that are more robust to base substitutions (high conservation) on random sequences, but do not have the coverage guarantee of minimizers. These sketching metrics are generally adversarial to one another, especially in the context of sketch optimization for a specific sequence, and thus are difficult to be simultaneously achieved. The parameterized syncmer scheme was recently introduced as a generalization of syncmers with more flexible sampling rules and empirically better coverage than the original syncmer variants. However, no approach exists to optimize parameterized syncmers. To address this shortcoming, we introduce a new scheme called masked minimizers that generalizes minimizers in manner analogous to how parameterized syncmers generalize syncmers and allows us to extend existing optimization techniques developed for minimizers. This results in a practical algorithm to optimize the masked minimizer scheme with respect to both density and conservation. We evaluate the optimization algorithm on various benchmark genomes and show that our algorithm finds sketches that are overall more compact, well-spread, and robust to substitutions than those found by previous methods. Our implementation is released at https://github.com/Kingsford-Group/maskedminimizer. This new technique will enable more efficient and robust genomic analyses in the many settings where minimizers and syncmers are used.

Benchmarking long-read genome sequence alignment tools for human genomics applications

Background

The utility of long-read genome sequencing platforms has been shown in many fields including whole genome assembly, metagenomics, and amplicon sequencing. Less clear is the applicability of long reads to reference-guided human genomics, which is the foundation of genomic medicine. Here, we benchmark available platform-agnostic alignment tools on datasets from nanopore and single-molecule real-time platforms to understand their suitability in producing a genome representation.

Results

For this study, we leveraged publicly-available data from sample NA12878 generated on Oxford Nanopore and sample NA24385 on Pacific Biosciences platforms. We employed state of the art sequence alignment tools including GraphMap2, long-read aligner (LRA), Minimap2, CoNvex Gap-cost alignMents for Long Reads (NGMLR), and Winnowmap2. Minimap2 and Winnowmap2 were computationally lightweight enough for use at scale, while GraphMap2 was not. NGMLR took a long time and required many resources, but produced alignments each time. LRA was fast, but only worked on Pacific Biosciences data. Each tool widely disagreed on which reads to leave unaligned, affecting the end genome coverage and the number of discoverable breakpoints. No alignment tool independently resolved all large structural variants (1,001-100,000 base pairs) present in the Database of Genome Variants (DGV) for sample NA12878 or the truthset for NA24385.

Conclusions

These results suggest a combined approach is needed for LRS alignments for human genomics. Specifically, leveraging alignments from three tools will be more effective in generating a complete picture of genomic variability. It should be best practice to use an analysis pipeline that generates alignments with both Minimap2 and Winnowmap2 as they are lightweight and yield different views of the genome. Depending on the question at hand, the data available, and the time constraints, NGMLR and LRA are good options for a third tool. If computational resources and time are not a factor for a given case or experiment, NGMLR will provide another view, and another chance to resolve a case. LRA, while fast, did not work on the nanopore data for our cluster, but PacBio results were promising in that those computations completed faster than Minimap2. Due to its significant burden on computational resources and slow run time, Graphmap2 is not an ideal tool for exploration of a whole human genome generated on a long-read sequencing platform.

A chromosome-level genome assembly for the Silkie chicken resolves complete sequences for key chicken metabolic, reproductive, and immunity genes

A set of high-quality pan-genomes would help identify important genes that are still hidden/incomplete in bird reference genomes. In an attempt to address these issues, we have assembled a de novo chromosome-level reference genome of the Silkie (Gallus gallus domesticus), which is an important avian model for unique traits, like fibromelanosis, with unclear genetic foundation. This Silkie genome includes the complete genomic sequences of well-known, but unresolved, evolutionarily, endocrinologically, and immunologically important genes, including leptin, ovocleidin-17, and tumor-necrosis factor-α. The gap-less and manually annotated MHC (major histocompatibility complex) region possesses 38 recently identified genes, with differentially regulated genes recovered in response to pathogen challenges. We also provide whole-genome methylation and genetic variation maps, and resolve a complex genetic region that may contribute to fibromelanosis in these animals. Finally, we experimentally show leptin binding to the identified leptin receptor in chicken, confirming an active leptin ligand-receptor system. The Silkie genome assembly not only provides a rich data resource for avian genome studies, but also lays a foundation for further functional validation of resolved genes.

Haplotype-resolved assemblies and variant benchmark of a Chinese Quartet

BACKGROUND

Recent state-of-the-art sequencing technologies enable the investigation of challenging regions in the human genome and expand the scope of variant benchmarking datasets. Herein, we sequence a Chinese Quartet, comprising two monozygotic twin daughters and their biological parents, using four short and long sequencing platforms (Illumina, BGI, PacBio, and Oxford Nanopore Technology).

RESULTS

The long reads from the monozygotic twin daughters are phased into paternal and maternal haplotypes using the parent-child genetic map and for each haplotype. We also use long reads to generate haplotype-resolved whole-genome assemblies with completeness and continuity exceeding that of GRCh38. Using this Quartet, we comprehensively catalogue the human variant landscape, generating a dataset of 3,962,453 SNVs, 886,648 indels (< 50 bp), 9726 large deletions (≥ 50 bp), 15,600 large insertions (≥ 50 bp), 40 inversions, 31 complex structural variants, and 68 de novo mutations which are shared between the monozygotic twin daughters. Variants underrepresented in previous benchmarks owing to their complexity-including those located at long repeat regions, complex structural variants, and de novo mutations-are systematically examined in this study.

CONCLUSIONS

In summary, this study provides high-quality haplotype-resolved assemblies and a comprehensive set of benchmarking resources for two Chinese monozygotic twin samples which, relative to existing benchmarks, offers expanded genomic coverage and insight into complex variant categories.

The Complete Sequence and Comparative Analysis of Ape Sex Chromosomes

Apes possess two sex chromosomes-the male-specific Y and the X shared by males and females. The Y chromosome is crucial for male reproduction, with deletions linked to infertility. The X chromosome carries genes vital for reproduction and cognition. Variation in mating patterns and brain function among great apes suggests corresponding differences in their sex chromosome structure and evolution. However, due to their highly repetitive nature and incomplete reference assemblies, ape sex chromosomes have been challenging to study. Here, using the state-of-the-art experimental and computational methods developed for the telomere-to-telomere (T2T) human genome, we produced gapless, complete assemblies of the X and Y chromosomes for five great apes (chimpanzee, bonobo, gorilla, Bornean and Sumatran orangutans) and a lesser ape, the siamang gibbon. These assemblies completely resolved ampliconic, palindromic, and satellite sequences, including the entire centromeres, allowing us to untangle the intricacies of ape sex chromosome evolution. We found that, compared to the X, ape Y chromosomes vary greatly in size and have low alignability and high levels of structural rearrangements. This divergence on the Y arises from the accumulation of lineage-specific ampliconic regions and palindromes (which are shared more broadly among species on the X) and from the abundance of transposable elements and satellites (which have a lower representation on the X). Our analysis of Y chromosome genes revealed lineage-specific expansions of multi-copy gene families and signatures of purifying selection. In summary, the Y exhibits dynamic evolution, while the X is more stable. Finally, mapping short-read sequencing data from >100 great ape individuals revealed the patterns of diversity and selection on their sex chromosomes, demonstrating the utility of these reference assemblies for studies of great ape evolution. These complete sex chromosome assemblies are expected to further inform conservation genetics of nonhuman apes, all of which are endangered species.

Creating and Using Minimizer Sketches in Computational Genomics

Processing large data sets has become an essential part of computational genomics. Greatly increased availability of sequence data from multiple sources has fueled breakthroughs in genomics and related fields but has led to computational challenges processing large sequencing experiments. The minimizer sketch is a popular method for sequence sketching that underlies core steps in computational genomics such as read mapping, sequence assembling, k-mer counting, and more. In most applications, minimizer sketches are constructed using one of few classical approaches. More recently, efforts have been put into building minimizer sketches with desirable properties compared with the classical constructions. In this survey, we review the history of the minimizer sketch, the theories developed around the concept, and the plethora of applications taking advantage of such sketches. We aim to provide the readers a comprehensive picture of the research landscape involving minimizer sketches, in anticipation of better fusion of theory and application in the future.

Long-Read Sequencing Resolves a Complex Structural Variant in PRKN Parkinson's Disease

BACKGROUND

Parkin RBR E3 ubiquitin-protein ligase (PRKN) mutations are the most common cause of young onset and autosomal recessive Parkinson's disease (PD). PRKN is located in FRA6E, which is one of the common fragile sites in the human genome, making this region prone to structural variants. However, complex structural variants such as inversions of PRKN are seldom reported, suggesting that there are potentially unrevealed complex pathogenic PRKN structural variants.

OBJECTIVES

To identify complex structural variants in PRKN using long-read sequencing.

METHODS

We investigated the genetic cause of monozygotic twins presenting with a young onset dystonia-parkinsonism using targeted sequencing, whole exome sequencing, multiple ligation probe amplification, and long-read sequencing. We assessed the presence and frequency of complex inversions overlapping PRKN using whole-genome sequencing data of Accelerating Medicines Partnership Parkinson's disease (AMP-PD) and United Kingdom (UK)-Biobank datasets.

RESULTS

Multiple ligation probe amplification identified a heterozygous exon three deletion in PRKN and long-read sequencing identified a large novel inversion spanning over 7 Mb, including a large part of the coding DNA sequence of PRKN. We could diagnose the affected subjects as compound heterozygous carriers of PRKN. We analyzed whole genome sequencing data of 43,538 participants of the UK-Biobank and 4941 participants of the AMP-PD datasets. Nine inversions in the UK-Biobank and two in AMP PD were identified and were considered potentially damaging and likely to affect PRKN expression.

CONCLUSIONS

This is the first report describing a large 7 Mb inversion involving breakpoints outside of PRKN. This study highlights the importance of using long-read sequencing for structural variant analysis in unresolved young-onset PD cases. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

T2T-YAO: A Telomere-to-telomere Assembled Diploid Reference Genome for Han Chinese

Since its initial release in 2001, the human reference genome has undergone continuous improvement in quality, and the recently released telomere-to-telomere (T2T) version - T2T-CHM13 - reaches its highest level of continuity and accuracy after 20 years of effort by working on a simplified, nearly homozygous genome of a hydatidiform mole cell line. Here, to provide an authentic complete diploid human genome reference for the Han Chinese, the largest population in the world, we assembled the genome of a male Han Chinese individual, T2T-YAO, which includes T2T assemblies of all the 22 + X + M and 22 + Y chromosomes in both haploids. The quality of T2T-YAO is much better than those of all currently available diploid assemblies, and its haploid version, T2T-YAO-hp, generated by selecting the better assembly for each autosome, reaches the top quality of fewer than one error per 29.5 Mb, even higher than that of T2T-CHM13. Derived from an individual living in the aboriginal region of the Han population, T2T-YAO shows clear ancestry and potential genetic continuity from the ancient ancestors. Each haplotype of T2T-YAO possesses ∼ 330-Mb exclusive sequences, ∼ 3100 unique genes, and tens of thousands of nucleotide and structural variations as compared with CHM13, highlighting the necessity of a population-stratified reference genome. The construction of T2T-YAO, an accurate and authentic representative of the Chinese population, would enable precise delineation of genomic variations and advance our understandings in the hereditability of diseases and phenotypes, especially within the context of the unique variations of the Chinese population.

Two novel Bartonella (sub)species isolated from edible dormice (Glis glis): hints of cultivation stress-induced genomic changes

Bartonelloses are neglected emerging infectious diseases caused by facultatively intracellular bacteria transmitted between vertebrate hosts by various arthropod vectors. The highest diversity of Bartonella species has been identified in rodents. Within this study we focused on the edible dormouse (Glis glis), a rodent with unique life-history traits that often enters households and whose possible role in the epidemiology of Bartonella infections had been previously unknown. We identified and cultivated two distinct Bartonella sub(species) significantly diverging from previously described species, which were characterized using growth characteristics, biochemical tests, and various molecular techniques including also proteomics. Two novel (sub)species were described: Bartonella grahamii subsp. shimonis subsp. nov. and Bartonella gliris sp. nov. We sequenced two individual strains per each described (sub)species. During exploratory genomic analyses comparing two genotypes ultimately belonging to the same species, both factually and most importantly even spatiotemporally, we noticed unexpectedly significant structural variation between them. We found that most of the detected structural variants could be explained either by prophage excision or integration. Based on a detailed study of one such event, we argue that prophage deletion represents the most probable explanation of the observed phenomena. Moreover, in one strain of Bartonella grahamii subsp. shimonis subsp. nov. we identified a deletion related to Bartonella Adhesin A, a major pathogenicity factor that modulates bacteria-host interactions. Altogether, our results suggest that even a limited number of passages induced sufficient selective pressure to promote significant changes at the level of the genome.

Gap-Sensitive Colinear Chaining Algorithms for Acyclic Pangenome Graphs

A pangenome graph can serve as a better reference for genomic studies because it allows a compact representation of multiple genomes within a species. Aligning sequences to a graph is critical for pangenome-based resequencing. The seed-chain-extend heuristic works by finding short exact matches between a sequence and a graph. In this heuristic, colinear chaining helps identify a good cluster of exact matches that can be combined to form an alignment. Colinear chaining algorithms have been extensively studied for aligning two sequences with various gap costs, including linear, concave, and convex cost functions. However, extending these algorithms for sequence-to-graph alignment presents significant challenges. Recently, Makinen et al. introduced a sparse dynamic programming framework that exploits the small path cover property of acyclic pangenome graphs, enabling efficient chaining. However, this framework does not consider gap costs, limiting its practical effectiveness. We address this limitation by developing novel problem formulations and provably good chaining algorithms that support a variety of gap cost functions. These functions are carefully designed to enable fast chaining algorithms whose time requirements are parameterized in terms of the size of the minimum path cover. Through an empirical evaluation, we demonstrate the superior performance of our algorithm compared with existing aligners. When mapping simulated long reads to a pangenome graph comprising 95 human haplotypes, we achieved 98.7% precision while leaving <2% of reads unmapped.

The telomere-to-telomere gap-free reference genome of wild blueberry (Vaccinium duclouxii) provides its high soluble sugar and anthocyanin accumulation

Vaccinium duclouxii, endemic to southwestern China, is a berry-producing shrub or small tree belonging to the Ericaceae family, with high nutritive, medicinal, and ornamental value, abundant germplasm resources, and good edible properties. In addition, V. duclouxii exhibits strong tolerance to adverse environmental conditions, making it a promising candidate for research and offering wide-ranging possibilities for utilization. However, the lack of V. duclouxii genome sequence has hampered its development and utilization. Here, a high-quality telomere-to-telomere genome sequence of V. duclouxii was de novo assembled and annotated. All of 12 chromosomes were assembled into gap-free single contigs, providing the highest integrity and quality assembly reported so far for blueberry. The V. duclouxii genome is 573.67 Mb, which encodes 41 953 protein-coding genes. Combining transcriptomics and metabolomics analyses, we have uncovered the molecular mechanisms involved in sugar and acid accumulation and anthocyanin biosynthesis in V. duclouxii. This provides essential molecular information for further research on the quality of V. duclouxii. Moreover, the high-quality telomere-to-telomere assembly of the V. duclouxii genome will provide insights into the genomic evolution of Vaccinium and support advancements in blueberry genetics and molecular breeding.

Genomic variant benchmark: if you cannot measure it, you cannot improve it

Genomic benchmark datasets are essential to driving the field of genomics and bioinformatics. They provide a snapshot of the performances of sequencing technologies and analytical methods and highlight future challenges. However, they depend on sequencing technology, reference genome, and available benchmarking methods. Thus, creating a genomic benchmark dataset is laborious and highly challenging, often involving multiple sequencing technologies, different variant calling tools, and laborious manual curation. In this review, we discuss the available benchmark datasets and their utility. Additionally, we focus on the most recent benchmark of genes with medical relevance and challenging genomic complexity.

The complete and fully-phased diploid genome of a male Han Chinese

Since the release of the complete human genome, the priority of human genomic study has now been shifting towards closing gaps in ethnic diversity. Here, we present a fully phased and well-annotated diploid human genome from a Han Chinese male individual (CN1), in which the assemblies of both haploids achieve the telomere-to-telomere (T2T) level. Comparison of this diploid genome with the CHM13 haploid T2T genome revealed significant variations in the centromere. Outside the centromere, we discovered 11,413 structural variations, including numerous novel ones. We also detected thousands of CN1 alleles that have accumulated high substitution rates and a few that have been under positive selection in the East Asian population. Further, we found that CN1 outperforms CHM13 as a reference genome in mapping and variant calling for the East Asian population owing to the distinct structural variants of the two references. Comparison of SNP calling for a large cohort of 8869 Chinese genomes using CN1 and CHM13 as reference respectively showed that the reference bias profoundly impacts rare SNP calling, with nearly 2 million rare SNPs miss-called with different reference genomes. Finally, applying the CN1 as a reference, we discovered 5.80 Mb and 4.21 Mb putative introgression sequences from Neanderthal and Denisovan, respectively, including many East Asian specific ones undetected using CHM13 as the reference. Our analyses reveal the advances of using CN1 as a reference for population genomic studies and paleo-genomic studies. This complete genome will serve as an alternative reference for future genomic studies on the East Asian population.

Sequence Alignment/Map format: a comprehensive review of approaches and applications

The Sequence Alignment/Map (SAM) format file is the text file used to record alignment information. Alignment is the core of sequencing analysis, and downstream tasks accept mapping results for further processing. Given the rapid development of the sequencing industry today, a comprehensive understanding of the SAM format and related tools is necessary to meet the challenges of data processing and analysis. This paper is devoted to retrieving knowledge in the broad field of SAM. First, the format of SAM is introduced to understand the overall process of the sequencing analysis. Then, existing work is systematically classified in accordance with generation, compression and application, and the involved SAM tools are specifically mined. Lastly, a summary and some thoughts on future directions are provided.

Repetitive DNA sequence detection and its role in the human genome

Repetitive DNA sequences playing critical roles in driving evolution, inducing variation, and regulating gene expression. In this review, we summarized the definition, arrangement, and structural characteristics of repeats. Besides, we introduced diverse biological functions of repeats and reviewed existing methods for automatic repeat detection, classification, and masking. Finally, we analyzed the type, structure, and regulation of repeats in the human genome and their role in the induction of complex diseases. We believe that this review will facilitate a comprehensive understanding of repeats and provide guidance for repeat annotation and in-depth exploration of its association with human diseases.

Minmers are a generalization of minimizers that enable unbiased local Jaccard estimation

MOTIVATION

The Jaccard similarity on k-mer sets has shown to be a convenient proxy for sequence identity. By avoiding expensive base-level alignments and comparing reduced sequence representations, tools such as MashMap can scale to massive numbers of pairwise comparisons while still providing useful similarity estimates. However, due to their reliance on minimizer winnowing, previous versions of MashMap were shown to be biased and inconsistent estimators of Jaccard similarity. This directly impacts downstream tools that rely on the accuracy of these estimates.

RESULTS

To address this, we propose the minmer winnowing scheme, which generalizes the minimizer scheme by use of a rolling minhash with multiple sampled k-mers per window. We show both theoretically and empirically that minmers yield an unbiased estimator of local Jaccard similarity, and we implement this scheme in an updated version of MashMap. The minmer-based implementation is over 10 times faster than the minimizer-based version under the default ANI threshold, making it well-suited for large-scale comparative genomics applications.

AVAILABILITY AND IMPLEMENTATION

MashMap3 is available at https://github.com/marbl/MashMap.

The complete sequence of a human Y chromosome

The human Y chromosome has been notoriously difficult to sequence and assemble because of its complex repeat structure that includes long palindromes, tandem repeats and segmental duplications1-3. As a result, more than half of the Y chromosome is missing from the GRCh38 reference sequence and it remains the last human chromosome to be finished4,5. Here, the Telomere-to-Telomere (T2T) consortium presents the complete 62,460,029-base-pair sequence of a human Y chromosome from the HG002 genome (T2T-Y) that corrects multiple errors in GRCh38-Y and adds over 30 million base pairs of sequence to the reference, showing the complete ampliconic structures of gene families TSPY, DAZ and RBMY; 41 additional protein-coding genes, mostly from the TSPY family; and an alternating pattern of human satellite 1 and 3 blocks in the heterochromatic Yq12 region. We have combined T2T-Y with a previous assembly of the CHM13 genome4 and mapped available population variation, clinical variants and functional genomics data to produce a complete and comprehensive reference sequence for all 24 human chromosomes.

Long-read sequencing resolves a complex structural variant in PRKN Parkinson's disease

Background

PRKN mutations are the most common cause of young onset and autosomal recessive Parkinson's disease (PD). PRKN is located in FRA6E which is one of the common fragile sites in the human genome, making this region prone to structural variants. However, complex structural variants such as inversions of PRKN are seldom reported, suggesting that there are potentially unrevealed complex pathogenic PRKN structural variants.

Objectives

To identify complex structural variants in PRKN using long-read sequencing.

Methods

We investigated the genetic cause of monozygotic twins presenting with a young onset dystonia-parkinsonism using targeted sequencing, whole exome sequencing, multiple ligation probe amplification, and long-read. We assessed the presence and frequency of complex inversions overlapping PRKN using whole-genome sequencing data of AMP-PD and UK-Biobank datasets.

Results

Multiple ligation probe amplification identified a heterozygous exon 3 deletion in PRKN and long-read sequencing identified a large novel inversion spanning over 7Mb, including a large part of the coding DNA sequence of PRKN. We could diagnose the affected subjects as compound heterozygous carriers of PRKN. We analyzed whole genome sequencing data of 43,538 participants of the UK-Biobank and 4,941 participants of the AMP-PD datasets. Nine inversions in the UK-Biobank and two in AMP PD were identified and were considered potentially damaging and likely to affect PRKN isoforms.

Conclusions

This is the first report describing a large 7Mb inversion involving breakpoints outside of PRKN. This study highlights the importance of using long-read whole genome sequencing for structural variant analysis in unresolved young-onset PD cases.

Seedability: optimizing alignment parameters for sensitive sequence comparison

Motivation

Most sequence alignment techniques make use of exact k-mer hits, called seeds, as anchors to optimize alignment speed. A large number of bioinformatics tools employing seed-based alignment techniques, such as Minimap2 , use a single value of k per sequencing technology, without a strong guarantee that this is the best possible value. Given the ubiquity of sequence alignment, identifying values of k that lead to more sensitive alignments is thus an important task. To aid this, we present Seedability , a seed-based alignment framework designed for estimating an optimal seed k-mer length (as well as a minimal number of shared seeds) based on a given alignment identity threshold. In particular, we were motivated to make Minimap2 more sensitive in the pairwise alignment of short sequences.

Results

The experimental results herein show improved alignments of short and divergent sequences when using the parameter values determined by Seedability in comparison to the default values of Minimap2 . We also show several cases of pairs of real divergent sequences, where the default parameter values of Minimap2 yield no output alignments, but the values output by Seedability produce plausible alignments.

Availability and implementation

https://github.com/lorrainea/Seedability (distributed under GPL v3.0).

Coordinated inheritance of extrachromosomal DNA species in human cancer cells

The chromosomal theory of inheritance has dominated human genetics, including cancer genetics. Genes on the same chromosome segregate together while genes on different chromosomes assort independently, providing a fundamental tenet of Mendelian inheritance. Extrachromosomal DNA (ecDNA) is a frequent event in cancer that drives oncogene amplification, dysregulated gene expression and intratumoral heterogeneity, including through random segregation during cell division. Distinct ecDNA sequences, herein termed ecDNA species, can co-exist to facilitate intermolecular cooperation in cancer cells. However, how multiple ecDNA species within a tumor cell are assorted and maintained across somatic cell generations to drive cancer cell evolution is not known. Here we show that cooperative ecDNA species can be coordinately inherited through mitotic co-segregation. Imaging and single-cell analyses show that multiple ecDNAs encoding distinct oncogenes co-occur and are correlated in copy number in human cancer cells. EcDNA species are coordinately segregated asymmetrically during mitosis, resulting in daughter cells with simultaneous copy number gains in multiple ecDNA species prior to any selection. Computational modeling reveals the quantitative principles of ecDNA co-segregation and co-selection, predicting their observed distributions in cancer cells. Finally, we show that coordinated inheritance of ecDNAs enables co-amplification of specialized ecDNAs containing only enhancer elements and guides therapeutic strategies to jointly deplete cooperating ecDNA oncogenes. Coordinated inheritance of ecDNAs confers stability to oncogene cooperation and novel gene regulatory circuits, allowing winning combinations of epigenetic states to be transmitted across cell generations.

Efficient mapping of accurate long reads in minimizer space with mapquik

DNA sequencing data continue to progress toward longer reads with increasingly lower sequencing error rates. We focus on the critical problem of mapping, or aligning, low-divergence sequences from long reads (e.g., Pacific Biosciences [PacBio] HiFi) to a reference genome, which poses challenges in terms of accuracy and computational resources when using cutting-edge read mapping approaches that are designed for all types of alignments. A natural idea would be to optimize efficiency with longer seeds to reduce the probability of extraneous matches; however, contiguous exact seeds quickly reach a sensitivity limit. We introduce mapquik, a novel strategy that creates accurate longer seeds by anchoring alignments through matches of k consecutively sampled minimizers (k-min-mers) and only indexing k-min-mers that occur once in the reference genome, thereby unlocking ultrafast mapping while retaining high sensitivity. We show that mapquik significantly accelerates the seeding and chaining steps-fundamental bottlenecks to read mapping-for both the human and maize genomes with [Formula: see text] sensitivity and near-perfect specificity. On the human genome, for both real and simulated reads, mapquik achieves a [Formula: see text] speedup over the state-of-the-art tool minimap2, and on the maize genome, mapquik achieves a [Formula: see text] speedup over minimap2, making mapquik the fastest mapper to date. These accelerations are enabled from not only minimizer-space seeding but also a novel heuristic [Formula: see text] pseudochaining algorithm, which improves upon the long-standing [Formula: see text] bound. Minimizer-space computation builds the foundation for achieving real-time analysis of long-read sequencing data.

Entropy predicts sensitivity of pseudorandom seeds

Seed design is important for sequence similarity search applications such as read mapping and average nucleotide identity (ANI) estimation. Although k-mers and spaced k-mers are likely the most well-known and used seeds, sensitivity suffers at high error rates, particularly when indels are present. Recently, we developed a pseudorandom seeding construct, strobemers, which was empirically shown to have high sensitivity also at high indel rates. However, the study lacked a deeper understanding of why. In this study, we propose a model to estimate the entropy of a seed and find that seeds with high entropy, according to our model, in most cases have high match sensitivity. Our discovered seed randomness-sensitivity relationship explains why some seeds perform better than others, and the relationship provides a framework for designing even more sensitive seeds. We also present three new strobemer seed constructs: mixedstrobes, altstrobes, and multistrobes. We use both simulated and biological data to show that our new seed constructs improve sequence-matching sensitivity to other strobemers. We show that the three new seed constructs are useful for read mapping and ANI estimation. For read mapping, we implement strobemers into minimap2 and observe 30% faster alignment time and 0.2% higher accuracy than using k-mers when mapping reads at high error rates. As for ANI estimation, we find that higher entropy seeds have a higher rank correlation between estimated and true ANI.

The gap-free genome of mulberry elucidates the architecture and evolution of polycentric chromosomes

Mulberry is a fundamental component of the global sericulture industry, and its positive impact on our health and the environment cannot be overstated. However, the mulberry reference genomes reported previously remained unassembled or unplaced sequences. Here, we report the assembly and analysis of the telomere-to-telomere gap-free reference genome of the mulberry species, Morus notabilis, which has emerged as an important reference in mulberry gene function research and genetic improvement. The mulberry gap-free reference genome produced here provides an unprecedented opportunity for us to study the structure and function of centromeres. Our results revealed that all mulberry centromeric regions share conserved centromeric satellite repeats with different copies. Strikingly, we found that M. notabilis is a species with polycentric chromosomes and the only reported polycentric chromosome species up to now. We propose a compelling model that explains the formation mechanism of new centromeres and addresses the unsolved scientific question of the chromosome fusion-fission cycle in mulberry species. Our study sheds light on the functional genomics, chromosome evolution, and genetic improvement of mulberry species.

Chromosomal conservatism vs chromosomal megaevolution: enigma of karyotypic evolution in Lepidoptera

In the evolution of many organisms, periods of slow genome reorganization (= chromosomal conservatism) are interrupted by bursts of numerous chromosomal changes (= chromosomal megaevolution). Using comparative analysis of chromosome-level genome assemblies, we investigated these processes in blue butterflies (Lycaenidae). We demonstrate that the phase of chromosome number conservatism is characterized by the stability of most autosomes and dynamic evolution of the sex chromosome Z, resulting in multiple variants of NeoZ chromosomes due to autosome-sex chromosome fusions. In contrast during the phase of rapid chromosomal evolution, the explosive increase in chromosome number occurs mainly through simple chromosomal fissions. We show that chromosomal megaevolution is a highly non-random canalized process, and in two phylogenetically independent Lysandra lineages, the drastic parallel increase in number of fragmented chromosomes was achieved, at least partially, through reuse of the same ancestral chromosomal breakpoints. In species showing chromosome number doubling, we found no blocks of duplicated sequences or duplicated chromosomes, thus refuting the hypothesis of polyploidy. In the studied taxa, long blocks of interstitial telomere sequences (ITSs) consist of (TTAGG)_n arrays interspersed with telomere-specific retrotransposons. ITSs are sporadically present in rapidly evolving Lysandra karyotypes, but not in the species with ancestral chromosome number. Therefore, we hypothesize that the transposition of telomeric sequences may be triggers of the rapid chromosome number increase. Finally, we discuss the hypothetical genomic and population mechanisms of chromosomal megaevolution and argue that the disproportionally high evolutionary role of the Z sex chromosome can be additionally reinforced by sex chromosome-autosome fusions and Z-chromosome inversions.

A survey of mapping algorithms in the long-reads era

It has been over a decade since the first publication of a method dedicated entirely to mapping long-reads. The distinctive characteristics of long reads resulted in methods moving from the seed-and-extend framework used for short reads to a seed-and-chain framework due to the seed abundance in each read. The main novelties are based on alternative seed constructs or chaining formulations. Dozens of tools now exist, whose heuristics have evolved considerably. We provide an overview of the methods used in long-read mappers. Since they are driven by implementation-specific parameters, we develop an original visualization tool to understand the parameter settings ( http://bcazaux.polytech-lille.net/Minimap2/ ).

Genome-wide Association Identifies Novel Etiological Insights Associated with Parkinson's Disease in African and African Admixed Populations

Background

Understanding the genetic mechanisms underlying diseases in ancestrally diverse populations is a critical step towards the realization of the global application of precision medicine. The African and African admixed populations enable mapping of complex traits given their greater levels of genetic diversity, extensive population substructure, and distinct linkage disequilibrium patterns.

Methods

Here we perform a comprehensive genome-wide assessment of Parkinson's disease (PD) in 197,918 individuals (1,488 cases; 196,430 controls) of African and African admixed ancestry, characterizing population-specific risk, differential haplotype structure and admixture, coding and structural genetic variation and polygenic risk profiling.

Findings

We identified a novel common risk factor for PD and age at onset at the GBA1 locus (risk, rs3115534-G; OR=1.58, 95% CI = 1.37 - 1.80, P=2.397E-14; age at onset, BETA =-2.004, SE =0.57, P = 0.0005), that was found to be rare in non-African/African admixed populations. Downstream short- and long-read whole genome sequencing analyses did not reveal any coding or structural variant underlying the GWAS signal. However, we identified that this signal mediates PD risk via expression quantitative trait locus (eQTL) mechanisms. While previously identified GBA1 associated disease risk variants are coding mutations, here we suggest a novel functional mechanism consistent with a trend in decreasing glucocerebrosidase activity levels. Given the high population frequency of the underlying signal and the phenotypic characteristics of the homozygous carriers, we hypothesize that this variant may not cause Gaucher disease. Additionally, the prevalence of Gaucher's disease in Africa is low.

Interpretation

The present study identifies a novel African-ancestry genetic risk factor in GBA1 as a major mechanistic basis of PD in the African and African admixed populations. This striking result contrasts to previous work in Northern European populations, both in terms of mechanism and attributable risk. This finding highlights the importance of understanding population-specific genetic risk in complex diseases, a particularly crucial point as the field moves toward precision medicine in PD clinical trials and while recognizing the need for equitable inclusion of ancestrally diverse groups in such trials. Given the distinctive genetics of these underrepresented populations, their inclusion represents a valuable step towards insights into novel genetic determinants underlying PD etiology. This opens new avenues towards RNA-based and other therapeutic strategies aimed at reducing lifetime risk.

Research in Context

Evidence Before this Study

Our current understanding of Parkinson's disease (PD) is disproportionately based on studying populations of European ancestry, leading to a significant gap in our knowledge about the genetics, clinical characteristics, and pathophysiology in underrepresented populations. This is particularly notable in individuals of African and African admixed ancestries. Over the last two decades, we have witnessed a revolution in the research area of complex genetic diseases. In the PD field, large-scale genome-wide association studies in the European, Asian, and Latin American populations have identified multiple risk loci associated with disease. These include 78 loci and 90 independent signals associated with PD risk in the European population, nine replicated loci and two novel population-specific signals in the Asian population, and a total of 11 novel loci recently nominated through multi-ancestry GWAS efforts.Nevertheless, the African and African admixed populations remain completely unexplored in the context of PD genetics.

Added Value of this Study

To address the lack of diversity in our research field, this study aimed to conduct the first genome-wide assessment of PD genetics in the African and African admixed populations. Here, we identified a genetic risk factor linked to PD etiology, dissected African-specific differences in risk and age at onset, characterized known genetic risk factors, and highlighted the utility of the African and African admixed risk haplotype substructure for future fine-mapping efforts. We identified a novel disease mechanism via expression changes consistent with decreased GBA1 activity levels. Future large scale single cell expression studies should investigate the neuronal populations in which expression differences are most prominent. This novel mechanism may hold promise for future efficient RNA-based therapeutic strategies such as antisense oligonucleotides or short interfering RNAs aimed at preventing and decreasing disease risk. We envisage that these data generated under the umbrella of the Global Parkinson's Genetics Program (GP2) will shed light on the molecular mechanisms involved in the disease process and might pave the way for future clinical trials and therapeutic interventions. This work represents a valuable resource in an underserved population, supporting pioneering research within GP2 and beyond. Deciphering causal and genetic risk factors in all these ancestries will help determine whether interventions, potential targets for disease modifying treatment, and prevention strategies that are being studied in the European populations are relevant to the African and African admixed populations.

Implications of all the Available Evidence

We nominate a novel signal impacting GBA1 as the major genetic risk factor for PD in the African and African admixed populations. The present study could inform future GBA1 clinical trials, improving patient stratification. In this regard, genetic testing can help to design trials likely to provide meaningful and actionable answers. It is our hope that these findings may ultimately have clinical utility for this underrepresented population.

A draft human pangenome reference

Here the Human Pangenome Reference Consortium presents a first draft of the human pangenome reference. The pangenome contains 47 phased, diploid assemblies from a cohort of genetically diverse individuals1. These assemblies cover more than 99% of the expected sequence in each genome and are more than 99% accurate at the structural and base pair levels. Based on alignments of the assemblies, we generate a draft pangenome that captures known variants and haplotypes and reveals new alleles at structurally complex loci. We also add 119 million base pairs of euchromatic polymorphic sequences and 1,115 gene duplications relative to the existing reference GRCh38. Roughly 90 million of the additional base pairs are derived from structural variation. Using our draft pangenome to analyse short-read data reduced small variant discovery errors by 34% and increased the number of structural variants detected per haplotype by 104% compared with GRCh38-based workflows, which enabled the typing of the vast majority of structural variant alleles per sample.

Gapless genome assembly of Fusarium verticillioides, a filamentous fungus threatening plant and human health

Fusarium verticillioides is a filamentous fungus that causes plant diseases and harms human health through cancer-inducing mycotoxin and life-threatening Fusariosis. Given its threat to agriculture and public health, genome assembly of this fungus is critical to our understanding of its pathobiology and developing antifungal drugs. Here, we report a gap-free genome assembly of F. verticillioides using PacBio HiFi data and high-throughput chromosome capture (Hi-C) sequencing data. The assembled 42.0 Mb sequence contains eleven gapless chromosomes capturing all centromeres and 19 of all 22 telomeres. This assembly represents a significant improvement over previous version on contiguity (contig N50: 4.3 Mb), completeness (BUSCO score: 99.0%) and correctness (QV: 88.8). A total of 15,230 protein-coding genes were predicted, 6.2% of which are newly annotated genes. In addition, we identified three-dimension chromatin structures such as TADs-like structures and chromatin loops based on Hi-C data of ultra-high coverage. This gap-free genome of F. verticillioides is an excellent resource for further panoramic understanding mechanisms of fungal genome evolution, mycotoxin production and pathogenesis on plant and human host.

Variant calling and benchmarking in an era of complete human genome sequences

Genetic variant calling from DNA sequencing has enabled understanding of germline variation in hundreds of thousands of humans. Sequencing technologies and variant-calling methods have advanced rapidly, routinely providing reliable variant calls in most of the human genome. We describe how advances in long reads, deep learning, de novo assembly and pangenomes have expanded access to variant calls in increasingly challenging, repetitive genomic regions, including medically relevant regions, and how new benchmark sets and benchmarking methods illuminate their strengths and limitations. Finally, we explore the possible future of more complete characterization of human genome variation in light of the recent completion of a telomere-to-telomere human genome reference assembly and human pangenomes, and we consider the innovations needed to benchmark their newly accessible repetitive regions and complex variants.

Jasmine and Iris: population-scale structural variant comparison and analysis

The availability of long reads is revolutionizing studies of structural variants (SVs). However, because SVs vary across individuals and are discovered through imprecise read technologies and methods, they can be difficult to compare. Addressing this, we present Jasmine and Iris ( https://github.com/mkirsche/Jasmine/ ), for fast and accurate SV refinement, comparison and population analysis. Using an SV proximity graph, Jasmine outperforms six widely used comparison methods, including reducing the rate of Mendelian discordance in trio datasets by more than fivefold, and reveals a set of high-confidence de novo SVs confirmed by multiple technologies. We also present a unified callset of 122,813 SVs and 82,379 indels from 31 samples of diverse ancestry sequenced with long reads. We genotype these variants in 1,317 samples from the 1000 Genomes Project and the Genotype-Tissue Expression project with DNA and RNA-sequencing data and assess their widespread impact on gene expression, including within medically relevant genes.

BLEND: a fast, memory-efficient and accurate mechanism to find fuzzy seed matches in genome analysis

Generating the hash values of short subsequences, called seeds, enables quickly identifying similarities between genomic sequences by matching seeds with a single lookup of their hash values. However, these hash values can be used only for finding exact-matching seeds as the conventional hashing methods assign distinct hash values for different seeds, including highly similar seeds. Finding only exact-matching seeds causes either (i) increasing the use of the costly sequence alignment or (ii) limited sensitivity. We introduce BLEND, the first efficient and accurate mechanism that can identify both exact-matching and highly similar seeds with a single lookup of their hash values, called fuzzy seed matches. BLEND (i) utilizes a technique called SimHash, that can generate the same hash value for similar sets, and (ii) provides the proper mechanisms for using seeds as sets with the SimHash technique to find fuzzy seed matches efficiently. We show the benefits of BLEND when used in read overlapping and read mapping. For read overlapping, BLEND is faster by 2.4×-83.9× (on average 19.3×), has a lower memory footprint by 0.9×-14.1× (on average 3.8×), and finds higher quality overlaps leading to accurate de novo assemblies than the state-of-the-art tool, minimap2. For read mapping, BLEND is faster by 0.8×-4.1× (on average 1.7×) than minimap2. Source code is available at https://github.com/CMU-SAFARI/BLEND.

Automated assembly scaffolding using RagTag elevates a new tomato system for high-throughput genome editing

Advancing crop genomics requires efficient genetic systems enabled by high-quality personalized genome assemblies. Here, we introduce RagTag, a toolset for automating assembly scaffolding and patching, and we establish chromosome-scale reference genomes for the widely used tomato genotype M82 along with Sweet-100, a new rapid-cycling genotype that we developed to accelerate functional genomics and genome editing in tomato. This work outlines strategies to rapidly expand genetic systems and genomic resources in other plant species.

Comparison of structural variants detected by PacBio-CLR and ONT sequencing in pear

BACKGROUND

Structural variations (SVs) have recently become a topic of great interest in the area of genetic diversity and trait regulation. As genomic sequencing technologies have rapidly advanced, longer reads have been used to identify SVs at high resolution and with increased accuracy. It is important to choose a suitable sequencing platform and appropriate sequencing depth for SV detection in the pear genome.

RESULTS

In this study, two types of long reads from sequencing platforms, continuous long reads from Pacific Biosciences (PB-CLR) and long reads from Oxford Nanopore Technologies (ONT), were used to comprehensively analyze and compare SVs in the pear genome. The mapping rate of long reads was higher when the program Minimap2 rather than the other three mapping tools (NGMLR, LRA and Winnowmap2) was used. Three SV detection programs (Sniffles_v2, CuteSV, and Nanovar) were compared, and Nanovar had the highest sensitivity in detecting SVs at low sequencing depth (10-15×). A sequencing depth of 15× was suitable for SV detection in the pear genome using Nanovar. SVs detected by Sniffles_v2 and CuteSV with ONT reads had the high overlap with presence/absence variations (PAVs) in the pear cultivars 'Bartlett' and 'Dangshansuli', both of them with 38% of insertions and 55% of deletions overlapping with PAVs at sequencing depth of 30×. For the ONT sequencing data, over 37,526 SVs spanning ~ 28 Mb were identified by all three software packages for the 'Bartlett' and 'Dangshansuli' genomes. Those SVs were annotated and combined with transcriptome profiles derived from 'Bartlett' and 'Dangshansuli' fruit flesh at 60 days after cross-pollination. Several genes related to levels of sugars, acid, stone cells, and aromatic compounds were identified among the SVs. Transcription factors were then predicted among those genes, and results included bHLH, ERF, and MYB genes.

CONCLUSION

SV detection is of great significance in exploring phenotypic differences between pear varieties. Our study provides a framework for assessment of different SV software packages and sequencing platforms that can be applied in other plant genome studies. Based on these analyses, ONT sequencing data was determined to be more suitable than PB-CLR for SV detection in the pear genome. This analysis model will facilitate screening of genes related to agronomic traits in other crops.

Differentiable Learning of Sequence-Specific Minimizer Schemes with DeepMinimizer

Minimizers are widely used to sample representative k-mers from biological sequences in many applications, such as read mapping and taxonomy prediction. In most scenarios, having the minimizer scheme select as few k-mer positions as possible (i.e., having a low density) is desirable to reduce computation and memory cost. Despite the growing interest in minimizers, learning an effective scheme with optimal density is still an open question, as it requires solving an apparently challenging discrete optimization problem on the permutation space of k-mer orderings. Most existing schemes are designed to work well in expectation over random sequences, which have limited applicability to many practical tools. On the other hand, several methods have been proposed to construct minimizer schemes for a specific target sequence. These methods, however, only approximate the original objective with likewise discrete surrogate tasks that are not able to significantly improve the density performance. This article introduces the first continuous relaxation of the density minimizing objective, DeepMinimizer, which employs a novel Deep Learning twin architecture to simultaneously ensure both validity and performance of the minimizer scheme. Our surrogate objective is fully differentiable and, therefore, amenable to efficient gradient-based optimization using GPU computing. Finally, we demonstrate that DeepMinimizer discovers minimizer schemes that significantly outperform state-of-the-art constructions on human genomic sequences.

Algorithms for Colinear Chaining with Overlaps and Gap Costs

Colinear chaining has proven to be a powerful heuristic for finding near-optimal alignments of long DNA sequences (e.g., long reads or a genome assembly) to a reference. It is used as an intermediate step in several alignment tools that employ a seed-chain-extend strategy. Despite this popularity, efficient subquadratic time algorithms for the general case where chains support anchor overlaps and gap costs are not currently known. We present algorithms to solve the colinear chaining problem with anchor overlaps and gap costs in Õ(n) time, where n denotes the count of anchors. The degree of the polylogarithmic factor depends on the type of anchors used (e.g., fixed-length anchors) and the type of precedence an optimal anchor chain is required to satisfy. We also establish the first theoretical connection between colinear chaining cost and edit distance. Specifically, we prove that for a fixed set of anchors under a carefully designed chaining cost function, the optimal "anchored" edit distance equals the optimal colinear chaining cost. The anchored edit distance for two sequences and a set of anchors is only a slight generalization of the standard edit distance. It adds an additional cost of one to an alignment of two matching symbols that are not supported by any anchor. Finally, we demonstrate experimentally that optimal colinear chaining cost under the proposed cost function can be computed orders of magnitude faster than edit distance, and achieves correlation coefficient >0.9 with edit distance for closely as well as distantly related sequences.

Sketching and sampling approaches for fast and accurate long read classification

BACKGROUND

In modern sequencing experiments, quickly and accurately identifying the sources of the reads is a crucial need. In metagenomics, where each read comes from one of potentially many members of a community, it can be important to identify the exact species the read is from. In other settings, it is important to distinguish which reads are from the targeted sample and which are from potential contaminants. In both cases, identification of the correct source of a read enables further investigation of relevant reads, while minimizing wasted work. This task is particularly challenging for long reads, which can have a substantial error rate that obscures the origins of each read.

RESULTS

Existing tools for the read classification problem are often alignment or index-based, but such methods can have large time and/or space overheads. In this work, we investigate the effectiveness of several sampling and sketching-based approaches for read classification. In these approaches, a chosen sampling or sketching algorithm is used to generate a reduced representation (a "screen") of potential source genomes for a query readset before reads are streamed in and compared against this screen. Using a query read's similarity to the elements of the screen, the methods predict the source of the read. Such an approach requires limited pre-processing, stores and works with only a subset of the input data, and is able to perform classification with a high degree of accuracy.

CONCLUSIONS

The sampling and sketching approaches investigated include uniform sampling, methods based on MinHash and its weighted and order variants, a minimizer-based technique, and a novel clustering-based sketching approach. We demonstrate the effectiveness of these techniques both in identifying the source microbial genomes for reads from a metagenomic long read sequencing experiment, and in distinguishing between long reads from organisms of interest and potential contaminant reads. We then compare these approaches to existing alignment, index and sketching-based tools for read classification, and demonstrate how such a method is a viable alternative for determining the source of query reads. Finally, we present a reference implementation of these approaches at https://github.com/arun96/sketching .

Chasing perfection: validation and polishing strategies for telomere-to-telomere genome assemblies

Advances in long-read sequencing technologies and genome assembly methods have enabled the recent completion of the first telomere-to-telomere human genome assembly, which resolves complex segmental duplications and large tandem repeats, including centromeric satellite arrays in a complete hydatidiform mole (CHM13). Although derived from highly accurate sequences, evaluation revealed evidence of small errors and structural misassemblies in the initial draft assembly. To correct these errors, we designed a new repeat-aware polishing strategy that made accurate assembly corrections in large repeats without overcorrection, ultimately fixing 51% of the existing errors and improving the assembly quality value from 70.2 to 73.9 measured from PacBio high-fidelity and Illumina k-mers. By comparing our results to standard automated polishing tools, we outline common polishing errors and offer practical suggestions for genome projects with limited resources. We also show how sequencing biases in both high-fidelity and Oxford Nanopore Technologies reads cause signature assembly errors that can be corrected with a diverse panel of sequencing technologies.

Merfin: improved variant filtering, assembly evaluation and polishing via k-mer validation

Variant calling has been widely used for genotyping and for improving the consensus accuracy of long-read assemblies. Variant calls are commonly hard-filtered with user-defined cutoffs. However, it is impossible to define a single set of optimal cutoffs, as the calls heavily depend on the quality of the reads, the variant caller of choice and the quality of the unpolished assembly. Here, we introduce Merfin, a k-mer based variant-filtering algorithm for improved accuracy in genotyping and genome assembly polishing. Merfin evaluates each variant based on the expected k-mer multiplicity in the reads, independently of the quality of the read alignment and variant caller's internal score. Merfin increased the precision of genotyped calls in several benchmarks, improved consensus accuracy and reduced frameshift errors when applied to human and nonhuman assemblies built from Pacific Biosciences HiFi and continuous long reads or Oxford Nanopore reads, including the first complete human genome. Moreover, we introduce assembly quality and completeness metrics that account for the expected genomic copy numbers.