A graph-based approach to diploid genome assembly

Developing pangenomes for large and complex plant genomes and their representation formats

BACKGROUND

The development of pangenomes has revolutionized genomic studies by capturing the complete genetic diversity within a species. Pangenome assembly integrates data from multiple individuals to construct a comprehensive genomic landscape, revealing both core and accessory genomic elements. This approach enables the identification of novel genes, structural variations, and gene presence-absence variations, providing insights into species evolution, adaptation, and trait variation. Representing pangenomes requires innovative visualization formats that effectively convey the complex genomic structures and variations.

AIM

This review delves into contemporary methodologies and recent advancements in constructing pangenomes, particularly in plant genomes. It examines the structure of pangenome representation, including format comparison, conversion, visualization techniques, and their implications for enhancing crop improvement strategies.

KEY SCIENTIFIC CONCEPTS OF REVIEW

Earlier comparative studies have illuminated novel gene sequences, copy number variations, and presence-absence variations across diverse crop species. The concept of a pan-genome, which captures multiple genetic variations from a broad spectrum of genotypes, offers a holistic perspective of a species' genetic makeup. However, constructing a pan-genome for plants with larger genomes poses challenges, including managing vast genome sequence data and comprehending the genetic variations within the germplasm. To address these challenges, researchers have explored cost-effective alternatives to encapsulate species diversity in a single assembly known as a pangenome. This involves reducing the volume of genome sequences while focusing on genetic variations. With the growing prominence of the pan-genome concept in plant genomics, several software tools have emerged to facilitate pangenome construction. This review sheds light on developing and utilizing software tools tailored for constructing pan-genomes in plants. It also discusses representation formats suitable for downstream analyses, offering valuable insights into the genetic landscape and evolutionary dynamics of plant species. In summary, this review underscores the significance of pan-genome construction and representation formats in resolving the genetic architecture of plants, particularly those with complex genomes. It provides a comprehensive overview of recent advancements, aiding in exploring and understanding plant genetic diversity.

Graphasing: phasing diploid genome assembly graphs with single-cell strand sequencing

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

Phasing Diploid Genome Assembly Graphs with Single-Cell Strand Sequencing

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

STAR+WASP reduces reference bias in the allele-specific mapping of RNA-seq reads

Allele-specific expression (ASE) is an important genetic phenomenon that impacts an individual's phenotype and is relevant in various biological and medical contexts. Next-generation RNA sequencing technologies provide an unprecedented opportunity to measure ASE genome-wide across all heterozygous alleles expressed in a given sample. One of the major obstacles to the accurate calculation of ASE from RNA-seq data is the reference mapping bias, i.e., the preferential misalignment of the reads to the reference allele. Here, we present STAR+WASP, our re-implementation of WASP, a highly accurate algorithm for reducing the reference bias (Van De Geijn et al. 2015). We show that STAR+WASP is an order of magnitude faster than WASP while significantly reducing reference bias and providing ASE estimations similar to the original WASP algorithm.

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 ).

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.

From contigs towards chromosomes: automatic improvement of long read assemblies (ILRA)

Recent advances in long read technologies not only enable large consortia to aim to sequence all eukaryotes on Earth, but they also allow individual laboratories to sequence their species of interest with relatively low investment. Long read technologies embody the promise of overcoming scaffolding problems associated with repeats and low complexity sequences, but the number of contigs often far exceeds the number of chromosomes and they may contain many insertion and deletion errors around homopolymer tracts. To overcome these issues, we have implemented the ILRA pipeline to correct long read-based assemblies. Contigs are first reordered, renamed, merged, circularized, or filtered if erroneous or contaminated. Illumina short reads are used subsequently to correct homopolymer errors. We successfully tested our approach by improving the genome sequences of Homo sapiens, Trypanosoma brucei, and Leptosphaeria spp., and by generating four novel Plasmodium falciparum assemblies from field samples. We found that correcting homopolymer tracts reduced the number of genes incorrectly annotated as pseudogenes, but an iterative approach seems to be required to correct more sequencing errors. In summary, we describe and benchmark the performance of our new tool, which improved the quality of novel long read assemblies up to 1 Gbp. The pipeline is available at GitHub: https://github.com/ThomasDOtto/ILRA.

Decoding the fibromelanosis locus complex chromosomal rearrangement of black-bone chicken: genetic differentiation, selective sweeps and protein-coding changes in Kadaknath chicken

Black-bone chicken (BBC) meat is popular for its distinctive taste and texture. A complex chromosomal rearrangement at the fibromelanosis (Fm) locus on the 20th chromosome results in increased endothelin-3 (EDN3) gene expression and is responsible for melanin hyperpigmentation in BBC. We use public long-read sequencing data of the Silkie breed to resolve high-confidence haplotypes at the Fm locus spanning both Dup1 and Dup2 regions and establish that the Fm_2 scenario is correct of the three possible scenarios of the complex chromosomal rearrangement. The relationship between Chinese and Korean BBC breeds with Kadaknath native to India is underexplored. Our data from whole-genome re-sequencing establish that all BBC breeds, including Kadaknath, share the complex chromosomal rearrangement junctions at the fibromelanosis (Fm) locus. We also identify two Fm locus proximal regions (∼70 Kb and ∼300 Kb) with signatures of selection unique to Kadaknath. These regions harbor several genes with protein-coding changes, with the bactericidal/permeability-increasing-protein-like gene having two Kadaknath-specific changes within protein domains. Our results indicate that protein-coding changes in the bactericidal/permeability-increasing-protein-like gene hitchhiked with the Fm locus in Kadaknath due to close physical linkage. Identifying this Fm locus proximal selective sweep sheds light on the genetic distinctiveness of Kadaknath compared to other BBC.

De novo genome assembly of the partial homozygous dihaploid potato identified PVY resistance gene (Rychc) derived from Solanum chacoense

The isolation of disease resistance genes introduced from wild or related cultivated species is essential for understanding their mechanisms, spectrum and risk of breakdown. To identify target genes not included in reference genomes, genomic sequences with the target locus must be reconstructed. However, de novo assembly approaches of the entire genome, such as those used for constructing reference genomes, are complicated in higher plants. Moreover, in the autotetraploid potato, the heterozygous regions and repetitive structures located around disease resistance gene clusters fragment the genomes into short contigs, making it challenging to identify resistance genes. In this study, we report that a de novo assembly approach of a target gene-specific homozygous dihaploid developed through haploid induction was suitable for gene isolation in potatoes using the potato virus Y resistance gene Ry_chc as a model. The assembled contig containing Ry_chc-linked markers was 3.3 Mb in length and could be joined with gene location information from the fine mapping analysis. Ry_chc was successfully identified in a repeated island located on the distal end of the long arm of chromosome 9 as a Toll/interleukin-1 receptor-nucleotide-binding site-leucine rich repeat (TIR-NBS-LRR) type resistance gene. This approach will be practical for other gene isolation projects in potatoes.

Using average nucleotide identity (ANI) to evaluate microsporidia species boundaries based on their genetic relatedness

Microsporidia are obligatory intracellular parasites related to fungi and since their discovery their classification and origin has been controversial due to their unique morphology. Early taxonomic studies of microsporidia were based on ultrastructural spore features, characteristics of their life cycle and transmission modes. However, taxonomy and phylogeny based solely on these characteristics can be misleading. SSU rRNA is a traditional marker used in taxonomical classifications, but the power of SSU rRNA to resolve phylogenetic relationships between microsporidia is considered weak at the species level, as it may not show enough variation to distinguish closely related species. Overall genome relatedness indices (OGRI), such as average nucleotide identity (ANI), allows fast and easy-to-implement comparative measurements between genomes to assess species boundaries in prokaryotes, with a 95% cutoff value for grouping genomes of the same species. Due to the increasing availability of complete genomes, metrics of genome relatedness have been applied for eukaryotic microbes taxonomy such as microsporidia. However, the distribution of ANI values and cutoff values for species delimitation have not yet been fully tested in microsporidia. In this study we examined the distribution of ANI values for 65 publicly available microsporidian genomes and tested whether the 95% cutoff value is a good estimation for circumscribing species based on their genetic relatedness.

VPrimer: A Method of Designing and Updating Primer and Probe With High Variant Coverage for RNA Virus Detection

Fatal infectious diseases caused by RNA viruses, such as COVID-19, have emerged around the world. RT-PCR is widely employed for virus detection, and its accuracy depends on the primers and probes since RT-PCR can detect a virus only when the primers and probes bind to the target gene of the virus. Most of primer design methods are for a single host and so require a great deal of effort to design for RNA virus detection, including homology tests among the host and all the viruses for the host using BLAST-like tools. Furthermore, they do not consider variant sequences, which are very common in viruses. In this study, we describe VPrimer, a method of designing high-quality primer-probe sets for RNA viruses. VPrimer can find primer-probe sets that cover more than 95% of the variants of a target virus but do not cover any sequences of other viruses or the host. With VPrimer, we found 381,698,582 primer-probe sets for 3,104 RNA viruses. Multiplex PCR assays using the top 2 primer-probe sets suggested by VPrimer usually cover 100% of variants. To address the rapid changes in viral genomes, VPrimer finds the best and up-to-date primer-probe sets incrementally against the most recently reported variants.

Genome sequence assembly algorithms and misassembly identification methods

The sequence assembly algorithms have rapidly evolved with the vigorous growth of genome sequencing technology over the past two decades. Assembly mainly uses the iterative expansion of overlap relationships between sequences to construct the target genome. The assembly algorithms can be typically classified into several categories, such as the Greedy strategy, Overlap-Layout-Consensus (OLC) strategy, and de Bruijn graph (DBG) strategy. In particular, due to the rapid development of third-generation sequencing (TGS) technology, some prevalent assembly algorithms have been proposed to generate high-quality chromosome-level assemblies. However, due to the genome complexity, the length of short reads, and the high error rate of long reads, contigs produced by assembly may contain misassemblies adversely affecting downstream data analysis. Therefore, several read-based and reference-based methods for misassembly identification have been developed to improve assembly quality. This work primarily reviewed the development of DNA sequencing technologies and summarized sequencing data simulation methods, sequencing error correction methods, various mainstream sequence assembly algorithms, and misassembly identification methods. A large amount of computation makes the sequence assembly problem more challenging, and therefore, it is necessary to develop more efficient and accurate assembly algorithms and alternative algorithms.

BubbleGun: enumerating bubbles and superbubbles in genome graphs

MOTIVATION

With the fast development of sequencing technology, accurate de novo genome assembly is now possible even for larger genomes. Graph-based representations of genomes arise both as part of the assembly process, but also in the context of pangenomes representing a population. In both cases, polymorphic loci lead to bubble structures in such graphs. Detecting bubbles is hence an important task when working with genomic variants in the context of genome graphs.

RESULTS

Here, we present a fast general-purpose tool, called BubbleGun, for detecting bubbles and superbubbles in genome graphs. Furthermore, BubbleGun detects and outputs runs of linearly connected bubbles and superbubbles, which we call bubble chains. We showcase its utility on de Bruijn graphs and compare our results to vg's snarl detection. We show that BubbleGun is considerably faster than vg especially in bigger graphs, where it reports all bubbles in less than 30 min on a human sample de Bruijn graph of around 2 million nodes.

AVAILABILITY AND IMPLEMENTATION

BubbleGun is available and documented as a Python3 package at https://github.com/fawaz-dabbaghieh/bubble_gun under MIT license.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

De novo sequencing, diploid assembly, and annotation of the black carpenter ant, Camponotus pennsylvanicus, and its symbionts by one person for $1000, using nanopore sequencing

The black carpenter ant (Camponotus pennsylvanicus) is a pest species found widely throughout North America. From a single individual I used long-read nanopore sequencing to assemble a phased diploid genome of 306 Mb and 60X coverage, with quality assessed by a 97.0% BUSCO score, improving upon other ant assemblies. The mitochondrial genome reveals minor rearrangements from other ants. The reads also allowed assembly of parasitic and symbiont genomes. I include a complete Wolbachia bacterial assembly with a size of 1.2 Mb, as well as a commensal symbiont Blochmannia pennsylvanicus, at 791 kb. DNA methylation and hydroxymethylation were measured at base-pair resolution level from the same reads and confirmed extremely low levels seen in the Formicidae family. There was moderate heterozygosity, with 0.16% of bases being biallelic from the parental haplotypes. Protein prediction yielded 14 415 amino acid sequences with 95.8% BUSCO score and 86% matching to previously known proteins. All assemblies were derived from a single MinION flow cell generating 20 Gb of sequence for a cost of $1047 including consumable reagents. Adding fixed costs for equipment brings the total for an ant-sized genome to less than $5000. All analyses were performed in 1 week on a single desktop computer.

Nematode chromosomes

The nematode Caenorhabditis elegans has shed light on many aspects of eukaryotic biology, including genetics, development, cell biology, and genomics. A major factor in the success of C. elegans as a model organism has been the availability, since the late 1990s, of an essentially gap-free and well-annotated nuclear genome sequence, divided among 6 chromosomes. In this review, we discuss the structure, function, and biology of C. elegans chromosomes and then provide a general perspective on chromosome biology in other diverse nematode species. We highlight malleable chromosome features including centromeres, telomeres, and repetitive elements, as well as the remarkable process of programmed DNA elimination (historically described as chromatin diminution) that induces loss of portions of the genome in somatic cells of a handful of nematode species. An exciting future prospect is that nematode species may enable experimental approaches to study chromosome features and to test models of chromosome evolution. In the long term, fundamental insights regarding how speciation is integrated with chromosome biology may be revealed.

phasebook: haplotype-aware de novo assembly of diploid genomes from long reads

Haplotype-aware diploid genome assembly is crucial in genomics, precision medicine, and many other disciplines. Long-read sequencing technologies have greatly improved genome assembly. However, current long-read assemblers are either reference based, so introduce biases, or fail to capture the haplotype diversity of diploid genomes. We present phasebook, a de novo approach for reconstructing the haplotypes of diploid genomes from long reads. phasebook outperforms other approaches in terms of haplotype coverage by large margins, in addition to achieving competitive performance in terms of assembly errors and assembly contiguity.

The International Human Genome Project

The human genome project was conceived and executed as an international project, due to both pragmatic and principled reasons. This internationality has served the project well, with the resulting human genome being freely available for all researchers in all countries. Over time the reference human genome will likely have to evolve to a graph genome, and tap into more diverse sequences worldwide. A similar international mindset underpins data analysis for the interpretation of the human genome from basic to clinical research.

Efficient dynamic variation graphs

MOTIVATION

Pangenomics is a growing field within computational genomics. Many pangenomic analyses use bidirected sequence graphs as their core data model. However, implementing and correctly using this data model can be difficult, and the scale of pangenomic datasets can be challenging to work at. These challenges have impeded progress in this field.

RESULTS

Here, we present a stack of two C++ libraries, libbdsg and libhandlegraph, which use a simple, field-proven interface, designed to expose elementary features of these graphs while preventing common graph manipulation mistakes. The libraries also provide a Python binding. Using a diverse collection of pangenome graphs, we demonstrate that these tools allow for efficient construction and manipulation of large genome graphs with dense variation. For instance, the speed and memory usage are up to an order of magnitude better than the prior graph implementation in the VG toolkit, which has now transitioned to using libbdsg's implementations.

AVAILABILITY AND IMPLEMENTATION

libhandlegraph and libbdsg are available under an MIT License from https://github.com/vgteam/libhandlegraph and https://github.com/vgteam/libbdsg.

Diploid genomic architecture of Nitzschia inconspicua, an elite biomass production diatom

A near-complete diploid nuclear genome and accompanying circular mitochondrial and chloroplast genomes have been assembled from the elite commercial diatom species Nitzschia inconspicua. The 50 Mbp haploid size of the nuclear genome is nearly double that of model diatom Phaeodactylum tricornutum, but 30% smaller than closer relative Fragilariopsis cylindrus. Diploid assembly, which was facilitated by low levels of allelic heterozygosity (2.7%), included 14 candidate chromosome pairs composed of long, syntenic contigs, covering 93% of the total assembly. Telomeric ends were capped with an unusual 12-mer, G-rich, degenerate repeat sequence. Predicted proteins were highly enriched in strain-specific marker domains associated with cell-surface adhesion, biofilm formation, and raphe system gliding motility. Expanded species-specific families of carbonic anhydrases suggest potential enhancement of carbon concentration efficiency, and duplicated glycolysis and fatty acid synthesis pathways across cytosolic and organellar compartments may enhance peak metabolic output, contributing to competitive success over other organisms in mixed cultures. The N. inconspicua genome delivers a robust new reference for future functional and transcriptomic studies to illuminate the physiology of benthic pennate diatoms and harness their unique adaptations to support commercial algae biomass and bioproduct production.

Chromosome-scale, haplotype-resolved assembly of human genomes

Haplotype-resolved or phased genome assembly provides a complete picture of genomes and their complex genetic variations. However, current algorithms for phased assembly either do not generate chromosome-scale phasing or require pedigree information, which limits their application. We present a method named diploid assembly (DipAsm) that uses long, accurate reads and long-range conformation data for single individuals to generate a chromosome-scale phased assembly within 1 day. Applied to four public human genomes, PGP1, HG002, NA12878 and HG00733, DipAsm produced haplotype-resolved assemblies with minimum contig length needed to cover 50% of the known genome (NG50) up to 25 Mb and phased ~99.5% of heterozygous sites at 98-99% accuracy, outperforming other approaches in terms of both contiguity and phasing completeness. We demonstrate the importance of chromosome-scale phased assemblies for the discovery of structural variants (SVs), including thousands of new transposon insertions, and of highly polymorphic and medically important regions such as the human leukocyte antigen (HLA) and killer cell immunoglobulin-like receptor (KIR) regions. DipAsm will facilitate high-quality precision medicine and studies of individual haplotype variation and population diversity.

Accurate Haplotype-Resolved Assembly Reveals The Origin Of Structural Variants For Human Trios

MOTIVATION

Achieving a near complete understanding of how the genome of an individual affects the phenotypes of that individual requires deciphering the order of variations along homologous chromosomes in species with diploid genomes. However, true diploid assembly of long-range haplotypes remains challenging.

RESULTS

To address this, we have developed Haplotype-resolved Assembly for Synthetic long reads using a Trio-binning strategy, or HAST, which uses parental information to classify reads into maternal or paternal. Once sorted, these reads are used to independently de novo assemble the parent-specific haplotypes. We applied HAST to co-barcoded second-generation sequencing data from an Asian individual, resulting in a haplotype assembly covering 94.7% of the reference genome with a scaffold N50 longer than 11 Mb. The high haplotyping precision (∼99.7%) and recall (∼95.9%) represents a substantial improvement over the commonly used tool for assembling co-barcoded reads (Supernova), and is comparable to a trio-binning-based third generation long-read based assembly method (TrioCanu) but with a significantly higher single-base accuracy (up to 99.99997% (Q65)). This makes HAST a superior tool for accurate haplotyping and future haplotype-based studies.

AVAILABILITY

The code of the analysis is available at https://github.com/BGI-Qingdao/HAST.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

MBG: Minimizer-based Sparse de Bruijn Graph Construction

Motivation

De Bruijn graphs can be constructed from short reads efficiently and have been used for many purposes. Traditionally, long-read sequencing technologies have had too high error rates for de Bruijn graph-based methods. Recently, HiFi reads have provided a combination of long-read length and low error rate, which enables de Bruijn graphs to be used with HiFi reads.

Results

We have implemented MBG, a tool for building sparse de Bruijn graphs from HiFi reads. MBG outperforms existing tools for building dense de Bruijn graphs and can build a graph of 50× coverage whole human genome HiFi reads in four hours on a single core. MBG also assembles the bacterial E.coli genome into a single contig in 8 s.

Availability and implementation

Package manager: https://anaconda.org/bioconda/mbg and source code: https://github.com/maickrau/MBG.

Supplementary information

Supplementary data are available at Bioinformatics online.

Ratatosk: hybrid error correction of long reads enables accurate variant calling and assembly

A major challenge to long read sequencing data is their high error rate of up to 15%. We present Ratatosk, a method to correct long reads with short read data. We demonstrate on 5 human genome trios that Ratatosk reduces the error rate of long reads 6-fold on average with a median error rate as low as 0.22 %. SNP calls in Ratatosk corrected reads are nearly 99 % accurate and indel calls accuracy is increased by up to 37 %. An assembly of Ratatosk corrected reads from an Ashkenazi individual yields a contig N50 of 45 Mbp and less misassemblies than a PacBio HiFi reads assembly.

Twelve quick steps for genome assembly and annotation in the classroom

Eukaryotic genome sequencing and de novo assembly, once the exclusive domain of well-funded international consortia, have become increasingly affordable, thus fitting the budgets of individual research groups. Third-generation long-read DNA sequencing technologies are increasingly used, providing extensive genomic toolkits that were once reserved for a few select model organisms. Generating high-quality genome assemblies and annotations for many aquatic species still presents significant challenges due to their large genome sizes, complexity, and high chromosome numbers. Indeed, selecting the most appropriate sequencing and software platforms and annotation pipelines for a new genome project can be daunting because tools often only work in limited contexts. In genomics, generating a high-quality genome assembly/annotation has become an indispensable tool for better understanding the biology of any species. Herein, we state 12 steps to help researchers get started in genome projects by presenting guidelines that are broadly applicable (to any species), sustainable over time, and cover all aspects of genome assembly and annotation projects from start to finish. We review some commonly used approaches, including practical methods to extract high-quality DNA and choices for the best sequencing platforms and library preparations. In addition, we discuss the range of potential bioinformatics pipelines, including structural and functional annotations (e.g., transposable elements and repetitive sequences). This paper also includes information on how to build a wide community for a genome project, the importance of data management, and how to make the data and results Findable, Accessible, Interoperable, and Reusable (FAIR) by submitting them to a public repository and sharing them with the research community.

A haplotype-aware de novo assembly of related individuals using pedigree sequence graph

MOTIVATION

Reconstructing high-quality haplotype-resolved assemblies for related individuals has important applications in Mendelian diseases and population genomics. Through major genomics sequencing efforts such as the Personal Genome Project, the Vertebrate Genome Project (VGP) and the Genome in a Bottle project (GIAB), a variety of sequencing datasets from trios of diploid genomes are becoming available. Current trio assembly approaches are not designed to incorporate long- and short-read data from mother-father-child trios, and therefore require relatively high coverages of costly long-read data to produce high-quality assemblies. Thus, building a trio-aware assembler capable of producing accurate and chromosomal-scale diploid genomes of all individuals in a pedigree, while being cost-effective in terms of sequencing costs, is a pressing need of the genomics community.

RESULTS

We present a novel pedigree sequence graph based approach to diploid assembly using accurate Illumina data and long-read Pacific Biosciences (PacBio) data from all related individuals, thereby generalizing our previous work on single individuals. We demonstrate the effectiveness of our pedigree approach on a simulated trio of pseudo-diploid yeast genomes with different heterozygosity rates, and real data from human chromosome. We show that we require as little as 30× coverage Illumina data and 15× PacBio data from each individual in a trio to generate chromosomal-scale phased assemblies. Additionally, we show that we can detect and phase variants from generated phased assemblies.

AVAILABILITY AND IMPLEMENTATION

https://github.com/shilpagarg/WHdenovo.

GraphAligner: rapid and versatile sequence-to-graph alignment

Genome graphs can represent genetic variation and sequence uncertainty. Aligning sequences to genome graphs is key to many applications, including error correction, genome assembly, and genotyping of variants in a pangenome graph. Yet, so far, this step is often prohibitively slow. We present GraphAligner, a tool for aligning long reads to genome graphs. Compared to the state-of-the-art tools, GraphAligner is 13x faster and uses 3x less memory. When employing GraphAligner for error correction, we find it to be more than twice as accurate and over 12x faster than extant tools.Availability: Package manager: https://anaconda.org/bioconda/graphaligner and source code: https://github.com/maickrau/GraphAligner.

Improved haplotype inference by exploiting long-range linking and allelic imbalance in RNA-seq datasets

Haplotype reconstruction of distant genetic variants remains an unsolved problem due to the short-read length of common sequencing data. Here, we introduce HapTree-X, a probabilistic framework that utilizes latent long-range information to reconstruct unspecified haplotypes in diploid and polyploid organisms. It introduces the observation that differential allele-specific expression can link genetic variants from the same physical chromosome, thus even enabling using reads that cover only individual variants. We demonstrate HapTree-X's feasibility on in-house sequenced Genome in a Bottle RNA-seq and various whole exome, genome, and 10X Genomics datasets. HapTree-X produces more complete phases (up to 25%), even in clinically important genes, and phases more variants than other methods while maintaining similar or higher accuracy and being up to 10×  faster than other tools. The advantage of HapTree-X's ability to use multiple lines of evidence, as well as to phase polyploid genomes in a single integrative framework, substantially grows as the amount of diverse data increases.

Nanopore sequencing and the Shasta toolkit enable efficient de novo assembly of eleven human genomes

De novo assembly of a human genome using nanopore long-read sequences has been reported, but it used more than 150,000 CPU hours and weeks of wall-clock time. To enable rapid human genome assembly, we present Shasta, a de novo long-read assembler, and polishing algorithms named MarginPolish and HELEN. Using a single PromethION nanopore sequencer and our toolkit, we assembled 11 highly contiguous human genomes de novo in 9 d. We achieved roughly 63× coverage, 42-kb read N50 values and 6.5× coverage in reads >100 kb using three flow cells per sample. Shasta produced a complete haploid human genome assembly in under 6 h on a single commercial compute node. MarginPolish and HELEN polished haploid assemblies to more than 99.9% identity (Phred quality score QV = 30) with nanopore reads alone. Addition of proximity-ligation sequencing enabled near chromosome-level scaffolds for all 11 genomes. We compare our assembly performance to existing methods for diploid, haploid and trio-binned human samples and report superior accuracy and speed.

HASLR: Fast Hybrid Assembly of Long Reads

Third-generation sequencing technologies from companies such as Oxford Nanopore and Pacific Biosciences have paved the way for building more contiguous and potentially gap-free assemblies. The larger effective length of their reads has provided a means to overcome the challenges of short to mid-range repeats. Currently, accurate long read assemblers are computationally expensive, whereas faster methods are not as accurate. Moreover, despite recent advances in third-generation sequencing, researchers still tend to generate accurate short reads for many of the analysis tasks. Here, we present HASLR, a hybrid assembler that uses error-prone long reads together with high-quality short reads to efficiently generate accurate genome assemblies. Our experiments show that HASLR is not only the fastest assembler but also the one with the lowest number of misassemblies on most of the samples, while being on par with other assemblers in terms of contiguity and accuracy.

A haplotype-resolved, de novo genome assembly for the wood tiger moth (Arctia plantaginis) through trio binning

BACKGROUND

Diploid genome assembly is typically impeded by heterozygosity because it introduces errors when haplotypes are collapsed into a consensus sequence. Trio binning offers an innovative solution that exploits heterozygosity for assembly. Short, parental reads are used to assign parental origin to long reads from their F1 offspring before assembly, enabling complete haplotype resolution. Trio binning could therefore provide an effective strategy for assembling highly heterozygous genomes, which are traditionally problematic, such as insect genomes. This includes the wood tiger moth (Arctia plantaginis), which is an evolutionary study system for warning colour polymorphism.

FINDINGS

We produced a high-quality, haplotype-resolved assembly for Arctia plantaginis through trio binning. We sequenced a same-species family (F1 heterozygosity ∼1.9%) and used parental Illumina reads to bin 99.98% of offspring Pacific Biosciences reads by parental origin, before assembling each haplotype separately and scaffolding with 10X linked reads. Both assemblies are contiguous (mean scaffold N50: 8.2 Mb) and complete (mean BUSCO completeness: 97.3%), with annotations and 31 chromosomes identified through karyotyping. We used the assembly to analyse genome-wide population structure and relationships between 40 wild resequenced individuals from 5 populations across Europe, revealing the Georgian population as the most genetically differentiated with the lowest genetic diversity.

CONCLUSIONS

We present the first invertebrate genome to be assembled via trio binning. This assembly is one of the highest quality genomes available for Lepidoptera, supporting trio binning as a potent strategy for assembling heterozygous genomes. Using our assembly, we provide genomic insights into the geographic population structure of A. plantaginis.

SPAligner: alignment of long diverged molecular sequences to assembly graphs

BACKGROUND

Graph-based representation of genome assemblies has been recently used in different contexts - from improved reconstruction of plasmid sequences and refined analysis of metagenomic data to read error correction and reference-free haplotype reconstruction. While many of these applications heavily utilize the alignment of long nucleotide sequences to assembly graphs, first general-purpose software tools for finding such alignments have been released only recently and their deficiencies and limitations are yet to be discovered. Moreover, existing tools can not perform alignment of amino acid sequences, which could prove useful in various contexts - in particular the analysis of metagenomic sequencing data.

RESULTS

In this work we present a novel SPAligner (Saint-Petersburg Aligner) tool for aligning long diverged nucleotide and amino acid sequences to assembly graphs. We demonstrate that SPAligner is an efficient solution for mapping third generation sequencing reads onto assembly graphs of various complexity and also show how it can facilitate the identification of known genes in complex metagenomic datasets.

CONCLUSIONS

Our work will facilitate accelerating the development of graph-based approaches in solving sequence to genome assembly alignment problem. SPAligner is implemented as a part of SPAdes tools library and is available on Github.

Pangenome Graphs

Low-cost whole-genome assembly has enabled the collection of haplotype-resolved pangenomes for numerous organisms. In turn, this technological change is encouraging the development of methods that can precisely address the sequence and variation described in large collections of related genomes. These approaches often use graphical models of the pangenome to support algorithms for sequence alignment, visualization, functional genomics, and association studies. The additional information provided to these methods by the pangenome allows them to achieve superior performance on a variety of bioinformatic tasks, including read alignment, variant calling, and genotyping. Pangenome graphs stand to become a ubiquitous tool in genomics. Although it is unclear whether they will replace linearreference genomes, their ability to harmoniously relate multiple sequence and coordinate systems will make them useful irrespective of which pangenomic models become most common in the future.

Accurate Tracking of the Mutational Landscape of Diploid Hybrid Genomes

Mutations, recombinations, and genome duplications may promote genetic diversity and trigger evolutionary processes. However, quantifying these events in diploid hybrid genomes is challenging. Here, we present an integrated experimental and computational workflow to accurately track the mutational landscape of yeast diploid hybrids (MuLoYDH) in terms of single-nucleotide variants, small insertions/deletions, copy-number variants, aneuploidies, and loss-of-heterozygosity. Pairs of haploid Saccharomyces parents were combined to generate ancestor hybrids with phased genomes and varying levels of heterozygosity. These diploids were evolved under different laboratory protocols, in particular mutation accumulation experiments. Variant simulations enabled the efficient integration of competitive and standard mapping of short reads, depending on local levels of heterozygosity. Experimental validations proved the high accuracy and resolution of our computational approach. Finally, applying MuLoYDH to four different diploids revealed striking genetic background effects. Homozygous Saccharomyces cerevisiae showed a ∼4-fold higher mutation rate compared with its closely related species S. paradoxus. Intraspecies hybrids unveiled that a substantial fraction of the genome (∼250 bp per generation) was shaped by loss-of-heterozygosity, a process strongly inhibited in interspecies hybrids by high levels of sequence divergence between homologous chromosomes. In contrast, interspecies hybrids exhibited higher single-nucleotide mutation rates compared with intraspecies hybrids. MuLoYDH provided an unprecedented quantitative insight into the evolutionary processes that mold diploid yeast genomes and can be generalized to other genetic systems.

The draft nuclear genome assembly of Eucalyptus pauciflora: a pipeline for comparing de novo assemblies

BACKGROUND

Eucalyptus pauciflora (the snow gum) is a long-lived tree with high economic and ecological importance. Currently, little genomic information for E. pauciflora is available. Here, we sequentially assemble the genome of Eucalyptus pauciflora with different methods, and combine multiple existing and novel approaches to help to select the best genome assembly.

FINDINGS

We generated high coverage of long- (Nanopore, 174×) and short- (Illumina, 228×) read data from a single E. pauciflora individual and compared assemblies from 5 assemblers (Canu, SMARTdenovo, Flye, Marvel, and MaSuRCA) with different read lengths (1 and 35 kb minimum read length). A key component of our approach is to keep a randomly selected collection of ∼10% of both long and short reads separated from the assemblies to use as a validation set for assessing assemblies. Using this validation set along with a range of existing tools, we compared the assemblies in 8 ways: contig N50, BUSCO scores, LAI (long terminal repeat assembly index) scores, assembly ploidy, base-level error rate, CGAL (computing genome assembly likelihoods) scores, structural variation, and genome sequence similarity. Our result showed that MaSuRCA generated the best assembly, which is 594.87 Mb in size, with a contig N50 of 3.23 Mb, and an estimated error rate of ∼0.006 errors per base.

CONCLUSIONS

We report a draft genome of E. pauciflora, which will be a valuable resource for further genomic studies of eucalypts. The approaches for assessing and comparing genomes should help in assessing and choosing among many potential genome assemblies from a single dataset.

Parameterized Algorithms in Bioinformatics: An Overview

Bioinformatics regularly poses new challenges to algorithm engineers and theoretical computer scientists. This work surveys recent developments of parameterized algorithms and complexity for important NP-hard problems in bioinformatics. We cover sequence assembly and analysis, genome comparison and completion, and haplotyping and phylogenetics. Aside from reporting the state of the art, we give challenges and open problems for each topic.

Tools and Strategies for Long-Read Sequencing and De Novo Assembly of Plant Genomes

The commercial release of third-generation sequencing technologies (TGSTs), giving long and ultra-long sequencing reads, has stimulated the development of new tools for assembling highly contiguous genome sequences with unprecedented accuracy across complex repeat regions. We survey here a wide range of emerging sequencing platforms and analytical tools for de novo assembly, provide background information for each of their steps, and discuss the spectrum of available options. Our decision tree recommends workflows for the generation of a high-quality genome assembly when used in combination with the specific needs and resources of a project.

Haplotype-aware diplotyping from noisy long reads

Current genotyping approaches for single-nucleotide variations rely on short, accurate reads from second-generation sequencing devices. Presently, third-generation sequencing platforms are rapidly becoming more widespread, yet approaches for leveraging their long but error-prone reads for genotyping are lacking. Here, we introduce a novel statistical framework for the joint inference of haplotypes and genotypes from noisy long reads, which we term diplotyping. Our technique takes full advantage of linkage information provided by long reads. We validate hundreds of thousands of candidate variants that have not yet been included in the high-confidence reference set of the Genome-in-a-Bottle effort.