Comparing methods for constructing and representing human pangenome graphs

Reference-free identification and pangenome analysis of accessory chromosomes in a major fungal plant pathogen

Accessory chromosomes, found in some but not all individuals of a species, play an important role in pathogenicity and host specificity in fungal plant pathogens. However, their variability complicates reference-based analysis, especially when these chromosomes are missing in the reference genome. Pangenome variation graphs offer a reference-free alternative for studying these chromosomes. Here, we constructed a pangenome variation graph for 73 diverse Fusarium oxysporum genomes, a major fungal plant pathogen with a compartmentalized genome that includes conserved core as well as variable accessory chromosomes. To obtain insights into accessory chromosome dynamics, we first constructed a chromosome similarity network using all-vs-all similarity mapping. We identified eleven core chromosomes conserved across all strains and a substantial number of highly variable accessory chromosomes. Some of these accessory chromosomes are host-specific and likely play a role in determining host range. Using a k-mer based approach, we further identified the presence of these accessory chromosomes in all available (581) F. oxysporum assemblies and corroborated the occurrence of host-specific accessory chromosomes. To further analyze the evolution of chromosomes in F. oxysporum, we constructed a pangenome variation graph per group of homologous chromosomes. This reveals that accessory chromosomes are composed of different stretches of accessory regions, and possibly rearrangements between accessory regions gave rise to these mosaic accessory chromosomes. Furthermore, we show that accessory chromosomes are likely horizontally transferred in natural populations. Our findings demonstrate that a pangenome variation graph is a powerful approach to elucidate the evolutionary dynamics of accessory chromosomes in F. oxysporum, which is not only a useful resource for Fusarium but also provides a framework for similar analyses in other species containing accessory chromosomes.

Long read and preliminary pangenome analyses reveal breed-specific structural variations and novel sequences in Holstein and Jersey cattle

INTRODUCTION

Most SV studies in livestock rely on short-read sequencing, posing challenges in accurately characterizing large genomic variants due to their limited read length.

OBJECTIVES

Our goal is to reveal structural variation and novel sequences specific to Holstein and Jersey cattle breeds using long-read and pan-genome analyses.

METHODS

We sequenced 20 Holsteins and 8 Jersey cattle using PacBio HiFi to 20×, and integrated five read-based and one assembly-based SV caller to determine SVs.

RESULTS

We assembled the 28 genomes averaging 3.25 Gb with a contig N50 of 69.36 Mb and using the ARS-UCD1.2 reference, we acquired Holstein/Jersey SV catalogs with 74,068/54,689 events spanning 202/135 Mb (7.43 %/4.97 % of the genome). SVs were enriched in less conserved, non-coding, and non-regulatory regions. Comparing Holsteins with differing feed efficiency (FE), SVs unique to high FE were linked to energy metabolism and olfactory receptors, while those specific to low FE were associated with material transport. We constructed Holstein/Jersey pangenome graphs with 148,598/105,875 nodes and 208,891/147,990 edges, representing 47,028/37,137 biallelic and multi-allelic events, and 63.75/42.34 Mb of novel sequence. We observed SV count saturation with 20 Holsteins, while adding Jerseys significantly increased the SV count, highlighting breed-specific SV events.

CONCLUSION

Our long-read data and SV catalogs are valuable resources, revealing that the cattle genome is more complex than previously thought.

MUSET: set of utilities for constructing abundance unitig matrices from sequencing data

SUMMARY

MUSET is a novel set of utilities designed to efficiently construct abundance unitig matrices from sequencing data. Unitig matrices extend the concept of k-mer matrices by merging overlapping k-mers that unambiguously belong to the same sequence. MUSET addresses the limitations of current software by integrating k-mer counting and unitig extraction to generate unitig matrices containing abundance values, as opposed to only presence-absence in previous tools. These matrices preserve variations between samples while reducing disk space and the number of rows compared to k-mer matrices. We evaluated MUSET's performance using datasets derived from a 618-GB collection of ancient oral sequencing samples, producing a filtered unitig matrix that records abundances in <10 h and 20 GB memory.

AVAILABILITY AND IMPLEMENTATION

MUSET is open source and publicly available under the AGPL-3.0 licence in GitHub at https://github.com/CamilaDuitama/muset. Source code is implemented in C++ and provided with kmat_tools, a collection of tools for processing k-mer matrices. Version v0.5.1 is available on Zenodo with DOI 10.5281/zenodo.14164801.

Comparative population pangenomes reveal unexpected complexity and fitness effects of structural variants

Structural variants (SVs) are widespread in vertebrate genomes, yet their evolutionary dynamics remain poorly understood. Using 45 long-read de novo genome assemblies and pangenome tools, we analyze SVs within three closely related species of North American jays (Aphelocoma, scrub-jays) displaying a 60-fold range in effective population size. We find rapid evolution of genome architecture, including ~100 Mb variation in genome size driven by dynamic satellite landscapes with unexpectedly long (> 10 kb) repeat units and widespread variation in gene content, influencing gene expression. SVs exhibit slightly deleterious dynamics modulated by variant length and population size, with strong evidence of adaptive fixation only in large populations. Our results demonstrate how population size shapes the distribution of SVs and the importance of pangenomes to characterizing genomic diversity.

Pangenome graphs and their applications in biodiversity genomics

Complete datasets of genetic variants are key to biodiversity genomic studies. Long-read sequencing technologies allow the routine assembly of highly contiguous, haplotype-resolved reference genomes. However, even when complete, reference genomes from a single individual may bias downstream analyses and fail to adequately represent genetic diversity within a population or species. Pangenome graphs assembled from aligned collections of high-quality genomes can overcome representation bias by integrating sequence information from multiple genomes from the same population, species or genus into a single reference. Here, we review the available tools and data structures to build, visualize and manipulate pangenome graphs while providing practical examples and discussing their applications in biodiversity and conservation genomics across the tree of life.

Visualizing metagenomic and metatranscriptomic data: A comprehensive review

The fields of Metagenomics and Metatranscriptomics involve the examination of complete nucleotide sequences, gene identification, and analysis of potential biological functions within diverse organisms or environmental samples. Despite the vast opportunities for discovery in metagenomics, the sheer volume and complexity of sequence data often present challenges in processing analysis and visualization. This article highlights the critical role of advanced visualization tools in enabling effective exploration, querying, and analysis of these complex datasets. Emphasizing the importance of accessibility, the article categorizes various visualizers based on their intended applications and highlights their utility in empowering bioinformaticians and non-bioinformaticians to interpret and derive insights from meta-omics data effectively.

Structural variation in the pangenome of wild and domesticated barley

Pangenomes are collections of annotated genome sequences of multiple individuals of a species1. The structural variants uncovered by these datasets are a major asset to genetic analysis in crop plants2. Here we report a pangenome of barley comprising long-read sequence assemblies of 76 wild and domesticated genomes and short-read sequence data of 1,315 genotypes. An expanded catalogue of sequence variation in the crop includes structurally complex loci that are rich in gene copy number variation. To demonstrate the utility of the pangenome, we focus on four loci involved in disease resistance, plant architecture, nutrient release and trichome development. Novel allelic variation at a powdery mildew resistance locus and population-specific copy number gains in a regulator of vegetative branching were found. Expansion of a family of starch-cleaving enzymes in elite malting barleys was linked to shifts in enzymatic activity in micro-malting trials. Deletion of an enhancer motif is likely to change the developmental trajectory of the hairy appendages on barley grains. Our findings indicate that allelic diversity at structurally complex loci may have helped crop plants to adapt to new selective regimes in agricultural ecosystems.

Fitness consequences of structural variation inferred from a House Finch pangenome

Genomic structural variants (SVs) play a crucial role in adaptive evolution, yet their average fitness effects and characterization with pangenome tools are understudied in wild animal populations. We constructed a pangenome for House Finches (Haemorhous mexicanus), a model for studies of host-pathogen coevolution, using long-read sequence data on 16 individuals (32 de novo-assembled haplotypes) and one outgroup. We identified 887,118 SVs larger than 50 base pairs, mostly (60%) involving repetitive elements, with reduced SV diversity in the eastern US as a result of its introduction by humans. The distribution of fitness effects of genome-wide SVs was estimated using maximum likelihood approaches and revealed that SVs in both coding and noncoding regions were on average more deleterious than smaller indels or single nucleotide polymorphisms. The reference-free pangenome facilitated identification of a > 10-My-old, 11-megabase-long pericentric inversion on chromosome 1. We found that the genotype frequencies of the inversion, estimated from 135 birds widely sampled temporally and geographically, increased steadily over the 25 y since House Finches were first exposed to the bacterial pathogen Mycoplasma gallisepticum and showed signatures of balancing selection, capturing genes related to immunity and telomerase activity. We also observed shorter telomeres in populations with a greater number of years exposure to Mycoplasma. Our study illustrates the utility of long-read sequencing and pangenome methods for understanding wild animal populations, estimating fitness effects of genome-wide SVs, and advancing our understanding of adaptive evolution through structural variation.

Constructing and personalizing population pangenome graphs

Pangenome graphs signify a new frontier in genome representation. Recent advances in constructing and personalizing them mark progress in this area.

Cluster-efficient pangenome graph construction with nf-core/pangenome

MOTIVATION

Pangenome graphs offer a comprehensive way of capturing genomic variability across multiple genomes. However, current construction methods often introduce biases, excluding complex sequences or relying on references. The PanGenome Graph Builder (PGGB) addresses these issues. To date, though, there is no state-of-the-art pipeline allowing for easy deployment, efficient and dynamic use of available resources, and scalable usage at the same time.

RESULTS

To overcome these limitations, we present nf-core/pangenome, a reference-unbiased approach implemented in Nextflow following nf-core's best practices. Leveraging biocontainers ensures portability and seamless deployment in High-Performance Computing (HPC) environments. Unlike PGGB, nf-core/pangenome distributes alignments across cluster nodes, enabling scalability. Demonstrating its efficiency, we constructed pangenome graphs for 1000 human chromosome 19 haplotypes and 2146 Escherichia coli sequences, achieving a two to threefold speedup compared to PGGB without increasing greenhouse gas emissions.

AVAILABILITY AND IMPLEMENTATION

nf-core/pangenome is released under the MIT open-source license, available on GitHub and Zenodo, with documentation accessible at https://nf-co.re/pangenome/docs/usage.

A stepwise guide for pangenome development in crop plants: an alfalfa (Medicago sativa) case study

BACKGROUND

The concept of pangenomics and the importance of structural variants is gaining recognition within the plant genomics community. Due to advancements in sequencing and computational technology, it has become feasible to sequence the entire genome of numerous individuals of a single species at a reasonable cost. Pangenomes have been constructed for many major diploid crops, including rice, maize, soybean, sorghum, pearl millet, peas, sunflower, grapes, and mustards. However, pangenomes for polyploid species are relatively scarce and are available in only few crops including wheat, cotton, rapeseed, and potatoes.

MAIN BODY

In this review, we explore the various methods used in crop pangenome development, discussing the challenges and implications of these techniques based on insights from published pangenome studies. We offer a systematic guide and discuss the tools available for constructing a pangenome and conducting downstream analyses. Alfalfa, a highly heterozygous, cross pollinated and autotetraploid forage crop species, is used as an example to discuss the concerns and challenges offered by polyploid crop species. We conducted a comparative analysis using linear and graph-based methods by constructing an alfalfa graph pangenome using three publicly available genome assemblies. To illustrate the intricacies captured by pangenome graphs for a complex crop genome, we used five different gene sequences and aligned them against the three graph-based pangenomes. The comparison of the three graph pangenome methods reveals notable variations in the genomic variation captured by each pipeline.

CONCLUSION

Pangenome resources are proving invaluable by offering insights into core and dispensable genes, novel gene discovery, and genome-wide patterns of variation. Developing user-friendly online portals for linear pangenome visualization has made these resources accessible to the broader scientific and breeding community. However, challenges remain with graph-based pangenomes including compatibility with other tools, extraction of sequence for regions of interest, and visualization of genetic variation captured in pangenome graphs. These issues necessitate further refinement of tools and pipelines to effectively address the complexities of polyploid, highly heterozygous, and cross-pollinated species.

When less is more: sketching with minimizers in genomics

The exponential increase in sequencing data calls for conceptual and computational advances to extract useful biological insights. One such advance, minimizers, allows for reducing the quantity of data handled while maintaining some of its key properties. We provide a basic introduction to minimizers, cover recent methodological developments, and review the diverse applications of minimizers to analyze genomic data, including de novo genome assembly, metagenomics, read alignment, read correction, and pangenomes. We also touch on alternative data sketching techniques including universal hitting sets, syncmers, or strobemers. Minimizers and their alternatives have rapidly become indispensable tools for handling vast amounts of data.

A gentle introduction to pangenomics

Pangenomes have emerged in response to limitations associated with traditional linear reference genomes. In contrast to a traditional reference that is (usually) assembled from a single individual, pangenomes aim to represent all of the genomic variation found in a group of organisms. The term 'pangenome' is currently used to describe multiple different types of genomic information, and limited language is available to differentiate between them. This is frustrating for researchers working in the field and confusing for researchers new to the field. Here, we provide an introduction to pangenomics relevant to both prokaryotic and eukaryotic organisms and propose a formalization of the language used to describe pangenomes (see the Glossary) to improve the specificity of discussion in the field.

Plant pangenomes for crop improvement, biodiversity and evolution

Plant genome sequences catalogue genes and the genetic elements that regulate their expression. Such inventories further research aims as diverse as mapping the molecular basis of trait diversity in domesticated plants or inquiries into the origin of evolutionary innovations in flowering plants millions of years ago. The transformative technological progress of DNA sequencing in the past two decades has enabled researchers to sequence ever more genomes with greater ease. Pangenomes - complete sequences of multiple individuals of a species or higher taxonomic unit - have now entered the geneticists' toolkit. The genomes of crop plants and their wild relatives are being studied with translational applications in breeding in mind. But pangenomes are applicable also in ecological and evolutionary studies, as they help classify and monitor biodiversity across the tree of life, deepen our understanding of how plant species diverged and show how plants adapt to changing environments or new selection pressures exerted by human beings.

Conway-Bromage-Lyndon (CBL): an exact, dynamic representation of k-mer sets

SUMMARY

In this article, we introduce the Conway-Bromage-Lyndon (CBL) structure, a compressed, dynamic and exact method for representing k-mer sets. Originating from Conway and Bromage's concept, CBL innovatively employs the smallest cyclic rotations of k-mers, akin to Lyndon words, to leverage lexicographic redundancies. In order to support dynamic operations and set operations, we propose a dynamic bit vector structure that draws a parallel with Elias-Fano's scheme. This structure is encapsulated in a Rust library, demonstrating a balanced blend of construction efficiency, cache locality, and compression. Our findings suggest that CBL outperforms existing dynamic k-mer set methods. Unique to this work, CBL stands out as the only known exact k-mer structure offering in-place set operations. Its different combined abilities position it as a flexible Swiss knife structure for k-mer set management.

AVAILABILITY AND IMPLEMENTATION

https://github.com/imartayan/CBL.