Unbiased pangenome graphs

AlfaPang: alignment free algorithm for pangenome graph construction

The success of pangenome-based approaches to genomics analysis depends largely on the existence of efficient methods for constructing pangenome graphs that are applicable to large genome collections. In the current paper we present AlfaPang, a new pangenome graph building algorithm. AlfaPang is based on a novel alignment-free approach that allows to construct pangenome graphs using significantly less computational resources than state-of-the-art tools. The code of AlfaPang is freely available at https://github.com/AdamCicherski/AlfaPang .

What Are We Learning from Plant Pangenomes?

A single reference genome does not fully capture species diversity. By contrast, a pangenome incorporates multiple genomes to capture the entire set of nonredundant genes in a given species, along with its genome diversity. New sequencing technologies enable researchers to produce multiple high-quality genome sequences and catalog diverse genetic variations with better precision. Pangenomic studies have detected structural variants in plant genomes, dissected the genetic architecture of agronomic traits, and helped unravel molecular underpinnings and evolutionary origins of plant phenotypes. The pangenome concept has further evolved into a so-called super-pangenome that includes wild relatives within a genus or clade and shifted to graph-based reference systems. Nevertheless, building pangenomes and representing complex structural variants remain challenging in many crops. Standardized computing pipelines and common data structures are needed to compare and interpret pangenomes. The growing body of plant pangenomics data requires new algorithms, huge data storage capacity, and training to help researchers and breeders take advantage of newly discovered genes and genetic variants.

Taurine pangenome uncovers a segmental duplication upstream of KIT associated with depigmentation in white-headed cattle

Cattle have been selectively bred for coat color, spotting, and depigmentation patterns. The assumed autosomal dominant inherited genetic variants underlying the characteristic white head of Fleckvieh, Simmental, and Hereford cattle have not been identified yet, although the contribution of structural variation upstream of the KIT gene has been proposed. Here, we construct a graph pangenome from 24 haplotype assemblies representing seven taurine cattle breeds to identify and characterize the white-head-associated locus for the first time based on long-read sequencing data and pangenome analyses. We introduce a pangenome-wide association mapping approach that examines assembly path similarities within the graph to reveal an association between two most likely serial alleles of a complex structural variant (SV) 66 kb upstream of KIT and facial depigmentation. The complex SV contains a variable number of tandemly duplicated 14.3 kb repeats, consisting of LTRs, LINEs, and other repetitive elements, leading to misleading alignments of short and long reads when using a linear reference. We align 250 short-read sequencing samples spanning 15 cattle breeds to the pangenome graph, further validating that the alleles of the SV segregate with head depigmentation. We estimate an increased count of repeats in Hereford relative to Simmental and other white-headed cattle breeds from the graph alignment coverage, suggesting a large under-assembly in the current Hereford-based cattle reference genome, which had fewer copies. Our work shows that exploiting assembly path similarities within graph pangenomes can reveal trait-associated complex SVs.

Mars: simplifying bioinformatics workflows through a containerized approach to tool integration and management

Summary

Bioinformatics is a rapidly evolving field with numerous specialized tools developed for essential genomic analysis tasks, such as read simulation, mapping, and variant calling. However, managing these tools presents significant challenges due to varied dependencies, execution steps, and output formats, complicating the installation and configuration processes. To address these issues, we introduce "Mars" a bioinformatics solution encapsulated within a singularity container that preloads a comprehensive suite of widely used genomic tools. Mars not only simplifies the installation of these tools but also automates critical workflow functions, including sequence sample preparation, read simulation, read mapping, variant calling, and result comparison. By streamlining the execution of these workflows, Mars enables users to easily manage input-output formats and compare results across different tools, thereby enhancing reproducibility and efficiency. Furthermore, by providing a cohesive environment that integrates tool management with a flexible workflow interface, Mars empowers researchers to focus on their analyses rather than the complexities of tool configuration. This integrated solution facilitates the testing of various combinations of tools and algorithms, enabling users to evaluate performance based on different metrics and identify the optimal tools for their specific genomic analysis needs. Through Mars, we aim to enhance the accessibility and usability of bioinformatics tools, ultimately advancing research in genomic analysis.

Availability and implementation

Mars is freely available at https://github.com/GenomicAI/mars. It is implemented within a Singularity container environment and supports modular extension for additional genomic tools and custom workflows.

Leveraging a phased pangenome for haplotype design of hybrid potato

The tetraploid genome and clonal propagation of the cultivated potato (Solanum tuberosum L.)1,2 dictate a slow, non-accumulative breeding mode of the most important tuber crop. Transitioning potato breeding to a seed-propagated hybrid system based on diploid inbred lines has the potential to greatly accelerate its improvement3. Crucially, the development of inbred lines is impeded by manifold deleterious variants; explaining their nature and finding ways to eliminate them is the current focus of hybrid potato research4-10. However, most published diploid potato genomes are unphased, concealing crucial information on haplotype diversity and heterozygosity11-13. Here we develop a phased potato pangenome graph of 60 haplotypes from cultivated diploids and the ancestral wild species, and find evidence for the prevalence of transposable elements in generating structural variants. Compared with the linear reference, the graph pangenome represents a broader diversity (3,076 Mb versus 742 Mb). Notably, we observe enhanced heterozygosity in cultivated diploids compared with wild ones (14.0% versus 9.5%), indicating extensive hybridization during potato domestication. Using conservative criteria, we identify 19,625 putatively deleterious structural variants (dSVs) and reveal a biased accumulation of deleterious single nucleotide polymorphisms (dSNPs) around dSVs in coupling phase. Based on the graph pangenome, we computationally design ideal potato haplotypes with minimal dSNPs and dSVs. These advances provide critical insights into the genomic basis of clonal propagation and will guide breeders to develop a suite of promising inbred lines.

Genetic modulation of protein expression in rat brain

Genetic variations in protein expression are implicated in a broad spectrum of common diseases and complex traits but remain less explored compared to mRNA and classical phenotypes. This study systematically analyzed brain proteomes in a rat family using tandem mass tag (TMT)-based quantitative mass spectrometry. We quantified 8,119 proteins across two parental strains (SHR/Olalpcv and BN-Lx/Cub) and 29 HXB/BXH recombinant inbred (RI) strains, identifying 597 proteins with differential expression and 464 proteins linked to cis-acting quantitative trait loci (pQTLs). Proteogenomics identified 95 variant peptides, and sex-specific analyses revealed both shared and distinct cis-pQTLs. We improved the ability to pinpoint candidate genes underlying pQTLs by utilizing the rat pangenome and explored the connections between pQTLs in rats and human disorders. Collectively, this study highlights the value of large proteo-genetic datasets in elucidating protein modulation in the brain and its links to complex central nervous system (CNS) traits.

Interactive visualization and interpretation of pangenome graphs by linear reference-based coordinate projection and annotation integration

With the increasing availability of high-quality genome assemblies, pangenome graphs emerged as a new paradigm in the genomic field for identifying, encoding, and presenting genomic variation at both the population and species level. However, it remains challenging to truly dissect and interpret pangenome graphs via biologically informative visualization. To facilitate better exploration and understanding of pangenome graphs toward novel biological insights, here we present a web-based interactive visualization and interpretation framework for linear reference-projected pangenome graphs (VRPG). VRPG provides efficient and intuitive support for exploring and annotating pangenome graphs along a linear-genome-based coordinate system (e.g., that of a primary linear reference genome). Moreover, VRPG offers many unique features such as in-graph path highlighting for graph-constituent input assemblies, copy number characterization for graph-embedding nodes, and graph-based mapping for query sequences, all of which are highly valuable for researchers working with pangenome graphs. Additionally, VRPG enables side-by-side visualization between the graph-based pangenome representation and the conventional primary linear reference genome-based feature annotations, therefore seamlessly bridging the graph and linear genomic contexts. To further demonstrate its functionality and scalability, we applied VRPG to the cutting-edge yeast and human reference pangenome graphs derived from hundreds of high-quality genome assemblies via a dedicated web portal and examined their local genome diversity in the graph contexts.

Perspectives and opportunities in forensic human, animal, and plant integrative genomics in the Pangenome era

The Human Pangenome Reference Consortium, the Chinese Pangenome Consortium, and other plant and animal pangenome projects have announced the completion of pilot work aimed at constructing high-quality, haplotype-resolved reference graph genomes representative of global ethno-linguistically different populations or different plant and animal species. These graph-based, gapless pangenome references, which are enriched in terms of genomic diversity, completeness, and contiguity, have the potential for enhancing long-read sequencing (LRS)-based genomic research, as well as improving mappability and variant genotyping on traditional short-read sequencing platforms. We comprehensively discuss the advancements in pangenome-based genomic integrative genomic discoveries across forensic-related species (humans, animals, and plants) and summarize their applications in variant identification and forensic genomics, epigenetics, transcriptomics, and microbiome research. Recent developments in multiplexed array sequencing have introduced a highly efficient and programmable technique to overcome the limitations of short forensic marker lengths in LRS platforms. This technique enables the concatenation of short RNA transcripts and DNA fragments into LRS-optimal molecules for sequencing, assembly, and genotyping. The integration of new pangenome reference coordinates and corresponding computational algorithms will benefit forensic integrative genomics by facilitating new marker identification, accurate genotyping, high-resolution panel development, and the updating of statistical algorithms. This review highlights the necessity of integrating LRS-based platforms, pangenome-based study designs, and graph-based pangenome references in short-read mapping and LRS-based innovations to achieve precision forensic science.

Diversity and consequences of structural variation in the human genome

The biomedical community is increasingly invested in capturing all genetic variants across human genomes, interpreting their functional consequences and translating these findings to the clinic. A crucial component of this endeavour is the discovery and characterization of structural variants (SVs), which are ubiquitous in the human population, heterogeneous in their mutational processes, key substrates for evolution and adaptation, and profound drivers of human disease. The recent emergence of new technologies and the remarkable scale of sequence-based population studies have begun to crystalize our understanding of SVs as a mutational class and their widespread influence across phenotypes. In this Review, we summarize recent discoveries and new insights into SVs in the human genome in terms of their mutational patterns, population genetics, functional consequences, and impact on human traits and disease. We conclude by outlining three frontiers to be explored by the field over the next decade.

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.

PangeBlocks: customized construction of pangenome graphs via maximal blocks

BACKGROUND

The construction of a pangenome graph is a fundamental task in pangenomics. A natural theoretical question is how to formalize the computational problem of building an optimal pangenome graph, making explicit the underlying optimization criterion and the set of feasible solutions. Current approaches build a pangenome graph with some heuristics, without assuming some explicit optimization criteria. Thus it is unclear how a specific optimization criterion affects the graph topology and downstream analysis, like read mapping and variant calling.

RESULTS

In this paper, by leveraging the notion of maximal block in a Multiple Sequence Alignment (MSA), we reframe the pangenome graph construction problem as an exact cover problem on blocks called Minimum Weighted Block Cover (MWBC). Then we propose an Integer Linear Programming (ILP) formulation for the MWBC problem that allows us to study the most natural objective functions for building a graph. We provide an implementation of the ILP approach for solving the MWBC and we evaluate it on SARS-CoV-2 complete genomes, showing how different objective functions lead to pangenome graphs that have different properties, hinting that the specific downstream task can drive the graph construction phase.

CONCLUSION

We show that a customized construction of a pangenome graph based on selecting objective functions has a direct impact on the resulting graphs. In particular, our formalization of the MWBC problem, based on finding an optimal subset of blocks covering an MSA, paves the way to novel practical approaches to graph representations of an MSA where the user can guide the construction.

Building pangenome graphs

Pangenome graphs can represent all variation between multiple reference genomes, but current approaches to build them exclude complex sequences or are based upon a single reference. In response, we developed the PanGenome Graph Builder, a pipeline for constructing pangenome graphs without bias or exclusion. The PanGenome Graph Builder uses all-to-all alignments to build a variation graph in which we can identify variation, measure conservation, detect recombination events and infer phylogenetic relationships.

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.

Building pangenome graphs

Pangenome graphs can represent all variation between multiple reference genomes, but current approaches to build them exclude complex sequences or are based upon a single reference. In response, we developed the PanGenome Graph Builder (PGGB), a pipeline for constructing pangenome graphs without bias or exclusion. PGGB uses all-to-all alignments to build a variation graph in which we can identify variation, measure conservation, detect recombination events, and infer phylogenetic relationships.

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.

NIPT-PG: empowering non-invasive prenatal testing to learn from population genomics through an incremental pan-genomic approach

Non-invasive prenatal testing (NIPT) is a quite popular approach for detecting fetal genomic aneuploidies. However, due to the limitations on sequencing read length and coverage, NIPT suffers a bottleneck on further improving performance and conducting earlier detection. The errors mainly come from reference biases and population polymorphism. To break this bottleneck, we proposed NIPT-PG, which enables the NIPT algorithm to learn from population data. A pan-genome model is introduced to incorporate variant and polymorphic loci information from tested population. Subsequently, we proposed a sequence-to-graph alignment method, which considers the read mis-match rates during the mapping process, and an indexing method using hash indexing and adjacency lists to accelerate the read alignment process. Finally, by integrating multi-source aligned read and polymorphic sites across the pan-genome, NIPT-PG obtains a more accurate z-score, thereby improving the accuracy of chromosomal aneuploidy detection. We tested NIPT-PG on two simulated datasets and 745 real-world cell-free DNA sequencing data sets from pregnant women. Results demonstrate that NIPT-PG outperforms the standard z-score test. Furthermore, combining experimental and theoretical analyses, we demonstrate the probably approximately correct learnability of NIPT-PG. In summary, NIPT-PG provides a new perspective for fetal chromosomal aneuploidies detection. NIPT-PG may have broad applications in clinical testing, and its detection results can serve as a reference for false positive samples approaching the critical threshold.

A hepatitis B virus (HBV) sequence variation graph improves alignment and sample-specific consensus sequence construction

Nearly 300 million individuals live with chronic hepatitis B virus (HBV) infection (CHB), for which no curative therapy is available. As viral diversity is associated with pathogenesis and immunological control of infection, improved methods to characterize this diversity could aid drug development efforts. Conventionally, viral sequencing data are mapped/aligned to a reference genome, and only the aligned sequences are retained for analysis. Thus, reference selection is critical, yet selecting the most representative reference a priori remains difficult. We investigate an alternative pangenome approach which can combine multiple reference sequences into a graph which can be used during alignment. Using simulated short-read sequencing data generated from publicly available HBV genomes and real sequencing data from an individual living with CHB, we demonstrate alignment to a phylogenetically representative 'genome graph' can improve alignment, avoid issues of reference ambiguity, and facilitate the construction of sample-specific consensus sequences more genetically similar to the individual's infection. Graph-based methods can, therefore, improve efforts to characterize the genetics of viral pathogens, including HBV, and have broader implications in host-pathogen research.

Measuring, visualizing, and diagnosing reference bias with biastools

Many bioinformatics methods seek to reduce reference bias, but no methods exist to comprehensively measure it. Biastools analyzes and categorizes instances of reference bias. It works in various scenarios: when the donor's variants are known and reads are simulated; when donor variants are known and reads are real; and when variants are unknown and reads are real. Using biastools, we observe that more inclusive graph genomes result in fewer biased sites. We find that end-to-end alignment reduces bias at indels relative to local aligners. Finally, we use biastools to characterize how T2T references improve large-scale bias.

Pangenome graph construction from genome alignments with Minigraph-Cactus

Pangenome references address biases of reference genomes by storing a representative set of diverse haplotypes and their alignment, usually as a graph. Alternate alleles determined by variant callers can be used to construct pangenome graphs, but advances in long-read sequencing are leading to widely available, high-quality phased assemblies. Constructing a pangenome graph directly from assemblies, as opposed to variant calls, leverages the graph's ability to represent variation at different scales. Here we present the Minigraph-Cactus pangenome pipeline, which creates pangenomes directly from whole-genome alignments, and demonstrate its ability to scale to 90 human haplotypes from the Human Pangenome Reference Consortium. The method builds graphs containing all forms of genetic variation while allowing use of current mapping and genotyping tools. We measure the effect of the quality and completeness of reference genomes used for analysis within the pangenomes and show that using the CHM13 reference from the Telomere-to-Telomere Consortium improves the accuracy of our methods. We also demonstrate construction of a Drosophila melanogaster pangenome.

Ribotin: automated assembly and phasing of rDNA morphs

MOTIVATION

The ribosomal DNA (rDNA) arrays are highly repetitive and homogenous regions which exist in all life. Due to their repetitiveness, current assembly methods do not fully assemble the rDNA arrays in humans and many other eukaryotes, and so variation within the rDNA arrays cannot be effectively studied.

RESULTS

Here, we present the tool ribotin to assemble full length rDNA copies, or morphs. Ribotin uses a combination of highly accurate long reads and extremely long nanopore reads to resolve the variation between rDNA morphs. We show that ribotin successfully recovers the most abundant morphs in human and nonhuman genomes. We also find that genome wide consensus sequences of the rDNA arrays frequently produce a mosaic sequence that does not exist in the genome.

AVAILABILITY AND IMPLEMENTATION

Ribotin is available on https://github.com/maickrau/ribotin and as a package on bioconda.

Comparative Pangenomic Insights into the Distinct Evolution of Virulence Factors Among Grapevine Trunk Pathogens

The permanent organs of grapevines (Vitis vinifera L.), like those of other woody perennials, are colonized by various unrelated pathogenic ascomycete fungi secreting cell wall-degrading enzymes and phytotoxic secondary metabolites that contribute to host damage and disease symptoms. Trunk pathogens differ in the symptoms they induce and the extent and speed of damage. Isolates of the same species often display a wide virulence range, even within the same vineyard. This study focuses on Eutypa lata, Neofusicoccum parvum, and Phaeoacremonium minimum, causal agents of Eutypa dieback, Botryosphaeria dieback, and Esca, respectively. We sequenced 50 isolates from viticulture regions worldwide and built nucleotide-level, reference-free pangenomes for each species. Through examination of genomic diversity and pangenome structure, we analyzed intraspecific conservation and variability of putative virulence factors, focusing on functions under positive selection and recent gene family dynamics of contraction and expansion. Our findings reveal contrasting distributions of putative virulence factors in the core, dispensable, and private genomes of each pangenome. For example, carbohydrate active enzymes (CAZymes) were prevalent in the core genomes of each pangenome, whereas biosynthetic gene clusters were prevalent in the dispensable genomes of E. lata and P. minimum. The dispensable fractions were also enriched in Gypsy transposable elements and virulence factors under positive selection (polyketide synthase genes in E. lata and P. minimum, glycosyltransferases in N. parvum). Our findings underscore the complexity of the genomic architecture in each species and provide insights into their adaptive strategies, enhancing our understanding of the underlying mechanisms of virulence. [Formula: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

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.

A super-pangenome of the North American wild grape species

BACKGROUND

Capturing the genetic diversity of wild relatives is crucial for improving crops because wild species are valuable sources of agronomic traits that are essential to enhance the sustainability and adaptability of domesticated cultivars. Genetic diversity across a genus can be captured in super-pangenomes, which provide a framework for interpreting genomic variations.

RESULTS

Here we report the sequencing, assembly, and annotation of nine wild North American grape genomes, which are phased and scaffolded at chromosome scale. We generate a reference-unbiased super-pangenome using pairwise whole-genome alignment methods, revealing the extent of the genomic diversity among wild grape species from sequence to gene level. The pangenome graph captures genomic variation between haplotypes within a species and across the different species, and it accurately assesses the similarity of hybrids to their parents. The species selected to build the pangenome are a great representation of the genus, as illustrated by capturing known allelic variants in the sex-determining region and for Pierce's disease resistance loci. Using pangenome-wide association analysis, we demonstrate the utility of the super-pangenome by effectively mapping short reads from genus-wide samples and identifying loci associated with salt tolerance in natural populations of grapes.

CONCLUSIONS

This study highlights how a reference-unbiased super-pangenome can reveal the genetic basis of adaptive traits from wild relatives and accelerate crop breeding research.

Comparing methods for constructing and representing human pangenome graphs

BACKGROUND

As a single reference genome cannot possibly represent all the variation present across human individuals, pangenome graphs have been introduced to incorporate population diversity within a wide range of genomic analyses. Several data structures have been proposed for representing collections of genomes as pangenomes, in particular graphs.

RESULTS

In this work, we collect all publicly available high-quality human haplotypes and construct the largest human pangenome graphs to date, incorporating 52 individuals in addition to two synthetic references (CHM13 and GRCh38). We build variation graphs and de Bruijn graphs of this collection using five of the state-of-the-art tools: Bifrost, mdbg, Minigraph, Minigraph-Cactus and pggb. We examine differences in the way each of these tools represents variations between input sequences, both in terms of overall graph structure and representation of specific genetic loci.

CONCLUSION

This work sheds light on key differences between pangenome graph representations, informing end-users on how to select the most appropriate graph type for their application.

A pangenome graph reference of 30 chicken genomes allows genotyping of large and complex structural variants

BACKGROUND

The red junglefowl, the wild outgroup of domestic chickens, has historically served as a reference for genomic studies of domestic chickens. These studies have provided insight into the etiology of traits of commercial importance. However, the use of a single reference genome does not capture diversity present among modern breeds, many of which have accumulated molecular changes due to drift and selection. While reference-based resequencing is well-suited to cataloging simple variants such as single-nucleotide changes and short insertions and deletions, it is mostly inadequate to discover more complex structural variation in the genome.

METHODS

We present a pangenome for the domestic chicken consisting of thirty assemblies of chickens from different breeds and research lines.

RESULTS

We demonstrate how this pangenome can be used to catalog structural variants present in modern breeds and untangle complex nested variation. We show that alignment of short reads from 100 diverse wild and domestic chickens to this pangenome reduces reference bias by 38%, which affects downstream genotyping results. This approach also allows for the accurate genotyping of a large and complex pair of structural variants at the K feathering locus using short reads, which would not be possible using a linear reference.

CONCLUSIONS

We expect that this new paradigm of genomic reference will allow better pinpointing of exact mutations responsible for specific phenotypes, which will in turn be necessary for breeding chickens that meet new sustainability criteria and are resilient to quickly evolving pathogen threats.

Mesomycoplasma ovipneumoniae from goats with respiratory infection: pathogenic characteristics, population structure, and genomic features

BACKGROUND

Mycoplasma ovipneumoniae is a critical pathogen that causes respiratory diseases that threaten Caprini health and cause economic damage. A genome-wide study of M. ovipneumoniae will help understand the pathogenic characteristics of this microorganism.

RESULTS

Toxicological pathology and whole-genome sequencing of nine M. ovipneumoniae strains isolated from goats were performed using an epidemiological survey. These strains exhibited anterior ventral lung consolidation, typical of bronchopneumonia in goats. Average nucleotide identity and phylogenetic analysis based on whole-genome sequences showed that all M. ovipneumoniae strains clustered into two clades, largely in accordance with their geographical origins. The pan-genome of the 23 M. ovipneumoniae strains contained 5,596 genes, including 385 core, 210 soft core, and 5,001 accessory genes. Among these genes, two protein-coding genes were annotated as cilium adhesion and eight as paralog surface adhesins when annotated to VFDB, and no antibiotic resistance-related genes were predicted. Additionally, 23 strains carried glucosidase-related genes (ycjT and group_1595) and glucosidase-related genes (atpD_2), indicating that M. ovipneumoniae possesses a wide range of glycoside hydrolase activities.

CONCLUSIONS

The population structure and genomic features identified in this study will facilitate further investigations into the pathogenesis of M. ovipneumoniae and lay the foundation for the development of preventive and therapeutic methods.

Multiscale analysis of pangenomes enables improved representation of genomic diversity for repetitive and clinically relevant genes

Advancements in sequencing technologies and assembly methods enable the regular production of high-quality genome assemblies characterizing complex regions. However, challenges remain in efficiently interpreting variation at various scales, from smaller tandem repeats to megabase rearrangements, across many human genomes. We present a PanGenome Research Tool Kit (PGR-TK) enabling analyses of complex pangenome structural and haplotype variation at multiple scales. We apply the graph decomposition methods in PGR-TK to the class II major histocompatibility complex demonstrating the importance of the human pangenome for analyzing complicated regions. Moreover, we investigate the Y-chromosome genes, DAZ1/DAZ2/DAZ3/DAZ4, of which structural variants have been linked to male infertility, and X-chromosome genes OPN1LW and OPN1MW linked to eye disorders. We further showcase PGR-TK across 395 complex repetitive medically important genes. This highlights the power of PGR-TK to resolve complex variation in regions of the genome that were previously too complex to analyze.

Recombination between heterologous human acrocentric chromosomes

The short arms of the human acrocentric chromosomes 13, 14, 15, 21 and 22 (SAACs) share large homologous regions, including ribosomal DNA repeats and extended segmental duplications1,2. Although the resolution of these regions in the first complete assembly of a human genome-the Telomere-to-Telomere Consortium's CHM13 assembly (T2T-CHM13)-provided a model of their homology3, it remained unclear whether these patterns were ancestral or maintained by ongoing recombination exchange. Here we show that acrocentric chromosomes contain pseudo-homologous regions (PHRs) indicative of recombination between non-homologous sequences. Utilizing an all-to-all comparison of the human pangenome from the Human Pangenome Reference Consortium4 (HPRC), we find that contigs from all of the SAACs form a community. A variation graph5 constructed from centromere-spanning acrocentric contigs indicates the presence of regions in which most contigs appear nearly identical between heterologous acrocentric chromosomes in T2T-CHM13. Except on chromosome 15, we observe faster decay of linkage disequilibrium in the pseudo-homologous regions than in the corresponding short and long arms, indicating higher rates of recombination6,7. The pseudo-homologous regions include sequences that have previously been shown to lie at the breakpoint of Robertsonian translocations8, and their arrangement is compatible with crossover in inverted duplications on chromosomes 13, 14 and 21. The ubiquity of signals of recombination between heterologous acrocentric chromosomes seen in the HPRC draft pangenome suggests that these shared sequences form the basis for recurrent Robertsonian translocations, providing sequence and population-based confirmation of hypotheses first developed from cytogenetic studies 50 years ago9.

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.

Going broad and deep: sequencing-driven insights into plant physiology, evolution, and crop domestication

Deep sequencing is a term that has become embedded in the plant genomic literature in recent years and with good reason. A torrent of (largely) high-quality genomic and transcriptomic data has been collected and most of this has been publicly released. Indeed, almost 1000 plant genomes have been reported (www.plabipd.de) and the 2000 Plant Transcriptomes Project has long been completed. The EarthBioGenome project will dwarf even these milestones. That said, massive progress in understanding plant physiology, evolution, and crop domestication has been made by sequencing broadly (across a species) as well as deeply (within a single individual). We will outline the current state of the art in genome and transcriptome sequencing before we briefly review the most visible of these broad approaches, namely genome-wide association and transcriptome-wide association studies, as well as the compilation of pangenomes. This will include both (i) the most commonly used methods reliant on single nucleotide polymorphisms and short InDels and (ii) more recent examples which consider structural variants. We will subsequently present case studies exemplifying how their application has brought insight into either plant physiology or evolution and crop domestication. Finally, we will provide conclusions and an outlook as to the perspective for the extension of such approaches to different species, tissues, and biological processes.

Genome Evolution and the Future of Phylogenomics of Non-Avian Reptiles

Non-avian reptiles comprise a large proportion of amniote vertebrate diversity, with squamate reptiles-lizards and snakes-recently overtaking birds as the most species-rich tetrapod radiation. Despite displaying an extraordinary diversity of phenotypic and genomic traits, genomic resources in non-avian reptiles have accumulated more slowly than they have in mammals and birds, the remaining amniotes. Here we review the remarkable natural history of non-avian reptiles, with a focus on the physical traits, genomic characteristics, and sequence compositional patterns that comprise key axes of variation across amniotes. We argue that the high evolutionary diversity of non-avian reptiles can fuel a new generation of whole-genome phylogenomic analyses. A survey of phylogenetic investigations in non-avian reptiles shows that sequence capture-based approaches are the most commonly used, with studies of markers known as ultraconserved elements (UCEs) especially well represented. However, many other types of markers exist and are increasingly being mined from genome assemblies in silico, including some with greater information potential than UCEs for certain investigations. We discuss the importance of high-quality genomic resources and methods for bioinformatically extracting a range of marker sets from genome assemblies. Finally, we encourage herpetologists working in genomics, genetics, evolutionary biology, and other fields to work collectively towards building genomic resources for non-avian reptiles, especially squamates, that rival those already in place for mammals and birds. Overall, the development of this cross-amniote phylogenomic tree of life will contribute to illuminate interesting dimensions of biodiversity across non-avian reptiles and broader amniotes.