The Human Pangenome Project: a global resource to map genomic diversity

Structurally divergent and recurrently mutated regions of primate genomes

To better understand the pattern of primate genome structural variation, we sequenced and assembled using multiple long-read sequencing technologies the genomes of eight nonhuman primate species, including New World monkeys (owl monkey and marmoset), Old World monkey (macaque), Asian apes (orangutan and gibbon), and African ape lineages (gorilla, bonobo, and chimpanzee). Compared to the human genome, we identified 1,338,997 lineage-specific fixed structural variants (SVs) disrupting 1,561 protein-coding genes and 136,932 regulatory elements, including the most complete set of human-specific fixed differences. Across 50 million years of primate evolution, we estimate that 819.47 Mbp or ~27% of the genome has been affected by SVs based on analysis of these primate lineages. We identify 1,607 structurally divergent regions (SDRs) wherein recurrent structural variation contributes to creating SV hotspots where genes are recurrently lost (CARDs, ABCD7, OLAH) and new lineage-specific genes are generated (e.g., CKAP2, NEK5) and have become targets of rapid chromosomal diversification and positive selection (e.g., RGPDs). High-fidelity long-read sequencing has made these dynamic regions of the genome accessible for sequence-level analyses within and between primate species for the first time.

Targeted Phasing of 2-200 Kilobase DNA Fragments with a Short-Read Sequencer and a Single-Tube Linked-Read Library Method

In the human genome, heterozygous sites are genomic positions with different alleles inherited from each parent. On average, there is a heterozygous site every 1-2 kilobases (kb). Resolving whether two alleles in neighboring heterozygous positions are physically linked-that is, phased-is possible with a short-read sequencer if the sequencing library captures long-range information. TELL-Seq is a library preparation method based on millions of barcoded micro-sized beads that enables instrument-free phasing of a whole human genome in a single PCR tube. TELL-Seq incorporates a unique molecular identifier (barcode) to the short reads generated from the same high-molecular-weight (HMW) DNA fragment (known as 'linked-reads'). However, genome-scale TELL-Seq is not cost-effective for applications focusing on a single locus or a few loci. Here, we present an optimized TELL-Seq protocol that enables the cost-effective phasing of enriched loci (targets) of varying sizes, purity levels, and heterozygosity. Targeted TELL-Seq maximizes linked-read efficiency and library yield while minimizing input requirements, fragment collisions on microbeads, and sequencing burden. To validate the targeted protocol, we phased seven 180-200 kb loci enriched by CRISPR/Cas9-mediated excision coupled with pulse-field electrophoresis, four 20 kb loci enriched by CRISPR/Cas9-mediated protection from exonuclease digestion, and six 2-13 kb loci amplified by PCR. The selected targets have clinical and research relevance (BRCA1, BRCA2, MLH1, MSH2, MSH6, APC, PMS2, SCN5A-SCN10A, and PKI3CA). These analyses reveal that targeted TELL-Seq provides a reliable way of phasing allelic variants within targets (2-200 kb in length) with the low cost and high accuracy of short-read sequencing.

A sheep pangenome reveals the spectrum of structural variations and their effects on tail phenotypes

Structural variations (SVs) are a major contributor to genetic diversity and phenotypic variations, but their prevalence and functions in domestic animals are largely unexplored. Here we generated high-quality genome assemblies for 15 individuals from genetically diverse sheep breeds using Pacific Biosciences (PacBio) high-fidelity sequencing, discovering 130.3 Mb nonreference sequences, from which 588 genes were annotated. A total of 149,158 biallelic insertions/deletions, 6531 divergent alleles, and 14,707 multiallelic variations with precise breakpoints were discovered. The SV spectrum is characterized by an excess of derived insertions compared to deletions (94,422 vs. 33,571), suggesting recent active LINE expansions in sheep. Nearly half of the SVs display low to moderate linkage disequilibrium with surrounding single-nucleotide polymorphisms (SNPs) and most SVs cannot be tagged by SNP probes from the widely used ovine 50K SNP chip. We identified 865 population-stratified SVs including 122 SVs possibly derived in the domestication process among 690 individuals from sheep breeds worldwide. A novel 168-bp insertion in the 5' untranslated region (5' UTR) of HOXB13 is found at high frequency in long-tailed sheep. Further genome-wide association study and gene expression analyses suggest that this mutation is causative for the long-tail trait. In summary, we have developed a panel of high-quality de novo assemblies and present a catalog of structural variations in sheep. Our data capture abundant candidate functional variations that were previously unexplored and provide a fundamental resource for understanding trait biology in sheep.

AGC: compact representation of assembled genomes with fast queries and updates

MOTIVATION

High-quality sequence assembly is the ultimate representation of complete genetic information of an individual. Several ongoing pangenome projects are producing collections of high-quality assemblies of various species. Each project has already generated assemblies of hundreds of gigabytes on disk, greatly impeding the distribution of and access to such rich datasets.

RESULTS

Here, we show how to reduce the size of the sequenced genomes by 2-3 orders of magnitude. Our tool compresses the genomes significantly better than the existing programs and is much faster. Moreover, its unique feature is the ability to access any contig (or its part) in a fraction of a second and easily append new samples to the compressed collections. Thanks to this, AGC could be useful not only for backup or transfer purposes but also for routine analysis of pangenome sequences in common pipelines. With the rapidly reduced cost and improved accuracy of sequencing technologies, we anticipate more comprehensive pangenome projects with much larger sample sizes. AGC is likely to become a foundation tool to store, distribute and access pangenome data.

AVAILABILITY AND IMPLEMENTATION

The source code of AGC is available at https://github.com/refresh-bio/agc. The package can be installed via Bioconda at https://anaconda.org/bioconda/agc.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Target-allele-specific probe single-base extension (TASP-SBE): a novel MALDI-TOF-MS strategy for multi-variants analysis and its application in simultaneous detection of α-/β-thalassemia mutations

Single-nucleotide variants (SNVs) and copy number variations (CNVs) are the most common genomic variations that cause phenotypic diversity and genetic disorders. MALDI-TOF-MS is a rapid and cost-effective technique for multi-variant genotyping, but it is challenging to efficiently detect CNVs and clustered SNVs, especially to simultaneously detect CNVs and SNVs in one reaction. Herein, a novel strategy termed Target-Allele-Specific Probe Single-Base Extension (TASP-SBE) was devised to efficiently detect CNVs and clustered SNVs with MALDI-TOF-MS. By comprehensive use of traditional SBE and TASP-SBE strategies, a MALDI-TOF-MS assay was also developed to simultaneously detect 28 α-/β-thalassemia mutations in a single reaction system, including 4 α-thalassemia deletions, 3 HBA and 21 HBB SNVs. The results showed that all 28 mutations were sensitively identified, and the CNVs of HBA/HBB genes were also accurately analyzed based on the ratio of peak height (RPH) between the target allele and reference gene. The double-blind evaluation results of 989 thalassemia carrier samples showed a 100% concordance of this assay with other methods. In conclusion, a one-tube MALDI-TOF-MS assay was developed to simultaneously genotype 28 thalassemia mutations. This novel TASP-SBE was also verified a practicable strategy for the detection of CNVs and clustered SNVs, providing a feasible approach for multi-variants analysis with MALDI-TOF-MS technique.

Phased nanopore assembly with Shasta and modular graph phasing with GFAse

As a step towards simplifying and reducing the cost of haplotype resolved de novo assembly, we describe new methods for accurately phasing nanopore data with the Shasta genome assembler and a modular tool for extending phasing to the chromosome scale called GFAse. We test using new variants of Oxford Nanopore Technologies' (ONT) PromethION sequencing, including those using proximity ligation and show that newer, higher accuracy ONT reads substantially improve assembly quality.

Predicting gene mutation status via artificial intelligence technologies based on multimodal integration (MMI) to advance precision oncology

Personalized treatment strategies for cancer frequently rely on the detection of genetic alterations which are determined by molecular biology assays. Historically, these processes typically required single-gene sequencing, next-generation sequencing, or visual inspection of histopathology slides by experienced pathologists in a clinical context. In the past decade, advances in artificial intelligence (AI) technologies have demonstrated remarkable potential in assisting physicians with accurate diagnosis of oncology image-recognition tasks. Meanwhile, AI techniques make it possible to integrate multimodal data such as radiology, histology, and genomics, providing critical guidance for the stratification of patients in the context of precision therapy. Given that the mutation detection is unaffordable and time-consuming for a considerable number of patients, predicting gene mutations based on routine clinical radiological scans or whole-slide images of tissue with AI-based methods has become a hot issue in actual clinical practice. In this review, we synthesized the general framework of multimodal integration (MMI) for molecular intelligent diagnostics beyond standard techniques. Then we summarized the emerging applications of AI in the prediction of mutational and molecular profiles of common cancers (lung, brain, breast, and other tumor types) pertaining to radiology and histology imaging. Furthermore, we concluded that there truly exist multiple challenges of AI techniques in the way of its real-world application in the medical field, including data curation, feature fusion, model interpretability, and practice regulations. Despite these challenges, we still prospect the clinical implementation of AI as a highly potential decision-support tool to aid oncologists in future cancer treatment management.

DandD: efficient measurement of sequence growth and similarity

Genome assembly databases are growing rapidly. The sequence content in each new assembly can be largely redundant with previous ones, but this is neither conceptually nor algorithmically easy to measure. We propose new methods and a new tool called DandD that addresses the question of how much new sequence is gained when a sequence collection grows. DandD can describe how much human structural variation is being discovered in each new human genome assembly and when discoveries will level off in the future. DandD uses a measure called δ ("delta"), developed initially for data compression. Computing δ directly requires counting k-mers, but DandD can rapidly estimate it using genomic sketches. We also propose δ as an alternative to k-mer-specific cardinalities when computing the Jaccard coefficient, avoiding the pitfalls of a poor choice of k. We demonstrate the utility of DandD's functions for estimating δ, characterizing the rate of pangenome growth, and computing all-pairs similarities using k-independent Jaccard. DandD is open source software available at: https://github.com/jessicabonnie/dandd.

Comprehensive SMN1 and SMN2 profiling for spinal muscular atrophy analysis using long-read PacBio HiFi sequencing

Spinal muscular atrophy, a leading cause of early infant death, is caused by bi-allelic mutations of SMN1. Sequence analysis of SMN1 is challenging due to high sequence similarity with its paralog SMN2. Both genes have variable copy numbers across populations. Furthermore, without pedigree information, it is currently not possible to identify silent carriers (2+0) with two copies of SMN1 on one chromosome and zero copies on the other. We developed Paraphase, an informatics method that identifies full-length SMN1 and SMN2 haplotypes, determines the gene copy numbers, and calls phased variants using long-read PacBio HiFi data. The SMN1 and SMN2 copy-number calls by Paraphase are highly concordant with orthogonal methods (99.2% for SMN1 and 100% for SMN2). We applied Paraphase to 438 samples across 5 ethnic populations to conduct a population-wide haplotype analysis of these highly homologous genes. We identified major SMN1 and SMN2 haplogroups and characterized their co-segregation through pedigree-based analyses. We identified two SMN1 haplotypes that form a common two-copy SMN1 allele in African populations. Testing positive for these two haplotypes in an individual with two copies of SMN1 gives a silent carrier risk of 88.5%, which is significantly higher than the currently used marker (1.7%-3.0%). Extending beyond simple copy-number testing, Paraphase can detect pathogenic variants and enable potential haplotype-based screening of silent carriers through statistical phasing of haplotypes into alleles. Future analysis of larger population data will allow identification of more diverse haplotypes and genetic markers for silent carriers.

In it for the long run: perspectives on exploiting long-read sequencing in livestock for population scale studies of structural variants

Studies have demonstrated that structural variants (SV) play a substantial role in the evolution of species and have an impact on Mendelian traits in the genome. However, unlike small variants (< 50 bp), it has been challenging to accurately identify and genotype SV at the population scale using short-read sequencing. Long-read sequencing technologies are becoming competitively priced and can address several of the disadvantages of short-read sequencing for the discovery and genotyping of SV. In livestock species, analysis of SV at the population scale still faces challenges due to the lack of resources, high costs, technological barriers, and computational limitations. In this review, we summarize recent progress in the characterization of SV in the major livestock species, the obstacles that still need to be overcome, as well as the future directions in this growing field. It seems timely that research communities pool resources to build global population-scale long-read sequencing consortiums for the major livestock species for which the application of genomic tools has become cost-effective.

Anti-cancer effect of afatinib, dual inhibitor of HER2 and EGFR, on novel mutation HER2 E401G in models of patient-derived cancer

BACKGROUND

Precision medicine with gene panel testing based on next-generation sequencing for patients with cancer is being used increasingly in clinical practice. HER2, which encodes the human epidermal growth factor receptor 2 (HER2), is a potentially important driver gene. However, therapeutic strategies aimed at mutations in the HER2 extracellular domain have not been clarified. We therefore investigated the effect of EGFR co-targeted therapy with HER2 on patient-derived cancer models with the HER2 extracellular domain mutation E401G, based on our previous findings that this mutation has an epidermal growth factor receptor (EGFR)-mediated activation mechanism.

METHODS

We generated a xenograft (PDX) and a cancer tissue-originated spheroid (CTOS) from a patient's cancer containing an amplified HER2 E401G mutation. With these platforms, we compared the efficacy of afatinib, a tyrosine kinase inhibitor having anti-HER2 and anti-EGFR activity, with two other therapeutic options: lapatinib, which has similar properties but weaker EGFR inhibition, and trastuzumab plus pertuzumab, for which evidence exists of treatment efficacy against cancers with wild-type HER2 amplification. Similar experiments were also performed with H2170, a cell line with wild-type HER2 amplification, to contrast the characteristics of these drug's efficacies against HER2 E401G.

RESULTS

We confirmed that PDX and CTOS retained morphological and immunohistochemical characteristics and HER2 gene profiles of the original tumor. In both PDX and CTOS, afatinib reduced tumor size more than lapatinib or trastuzumab plus pertuzumab. In addition, afatinib treatment resulted in a statistically significant reduction in HER2 copy number at the end of treatment. On the other hand, in H2170 xenografts with wild-type HER2 amplification, trastuzumab plus pertuzumab was most effective.

CONCLUSIONS

Afatinib, a dual inhibitor of HER2 and EGFR, showed a promising effect on cancers with amplified HER2 E401G, which have an EGFR-mediated activation mechanism. Analysis of the activation mechanisms of mutations and development of therapeutic strategies based on those mechanisms are critical in precision medicine for cancer patients.

Next-Generation Sequencing (NGS) and Third-Generation Sequencing (TGS) for the Diagnosis of Thalassemia

Thalassemia is one of the most heterogeneous diseases, with more than a thousand mutation types recorded worldwide. Molecular diagnosis of thalassemia by conventional PCR-based DNA analysis is time- and resource-consuming owing to the phenotype variability, disease complexity, and molecular diagnostic test limitations. Moreover, genetic counseling must be backed-up by an extensive diagnosis of the thalassemia-causing phenotype and the possible genetic modifiers. Data coming from advanced molecular techniques such as targeted sequencing by next-generation sequencing (NGS) and third-generation sequencing (TGS) are more appropriate and valuable for DNA analysis of thalassemia. While NGS is superior at variant calling to TGS thanks to its lower error rates, the longer reads nature of the TGS permits haplotype-phasing that is superior for variant discovery on the homologous genes and CNV calling. The emergence of many cutting-edge machine learning-based bioinformatics tools has improved the accuracy of variant and CNV calling. Constant improvement of these sequencing and bioinformatics will enable precise thalassemia detections, especially for the CNV and the homologous HBA and HBG genes. In conclusion, laboratory transiting from conventional DNA analysis to NGS or TGS and following the guidelines towards a single assay will contribute to a better diagnostics approach of thalassemia.

Parent-of-origin detection and chromosome-scale haplotyping using long-read DNA methylation sequencing and Strand-seq

Hundreds of loci in human genomes have alleles that are methylated differentially according to their parent of origin. These imprinted loci generally show little variation across tissues, individuals, and populations. We show that such loci can be used to distinguish the maternal and paternal homologs for all human autosomes without the need for the parental DNA. We integrate methylation-detecting nanopore sequencing with the long-range phase information in Strand-seq data to determine the parent of origin of chromosome-length haplotypes for both DNA sequence and DNA methylation in five trios with diverse genetic backgrounds. The parent of origin was correctly inferred for all autosomes with an average mismatch error rate of 0.31% for SNVs and 1.89% for insertions or deletions (indels). Because our method can determine whether an inherited disease allele originated from the mother or the father, we predict that it will improve the diagnosis and management of many genetic diseases.

Blockchains as a means to promote privacy protecting, access availing, incentive increasing, ELSI lessening DNA databases

Not all blockchains are created equal, and many cannot accommodate all of the primary characteristics of big data: Variety, Velocity, Volume and Veracity. Currently, public blockchains are slow and clunky, it can be expensive to keep up with the velocity of genomic data production. Further, the transparent and universally accessible nature of public blockchain doesn't necessarily accommodate all of the variety of sequence data, including very private information. Bespoke private permissioned blockchains, however, can be created to optimally accommodate all of the big data features of genomic data. Further, private permissioned chains can be implemented to both protect the privacy and security of the genetic information therein, while also providing access to researchers. An NFT marketplace associated with that private chain can provide the discretized sale of anonymous and encrypted data sets while also incentivizing individuals to share their data through payments mediated by smart contracts. Private blockchains can provide a transparent chain of custody for each use of the customers' data, and validation that this data is not corrupted. However, even with all of these benefits there remain some concerns with the implementation of this new technology including the ethical, legal and social implications typically associated with DNA databases.

GENCODE: reference annotation for the human and mouse genomes in 2023

GENCODE produces high quality gene and transcript annotation for the human and mouse genomes. All GENCODE annotation is supported by experimental data and serves as a reference for genome biology and clinical genomics. The GENCODE consortium generates targeted experimental data, develops bioinformatic tools and carries out analyses that, along with externally produced data and methods, support the identification and annotation of transcript structures and the determination of their function. Here, we present an update on the annotation of human and mouse genes, including developments in the tools, data, analyses and major collaborations which underpin this progress. For example, we report the creation of a set of non-canonical ORFs identified in GENCODE transcripts, the LRGASP collaboration to assess the use of long transcriptomic data to build transcript models, the progress in collaborations with RefSeq and UniProt to increase convergence in the annotation of human and mouse protein-coding genes, the propagation of GENCODE across the human pan-genome and the development of new tools to support annotation of regulatory features by GENCODE. Our annotation is accessible via Ensembl, the UCSC Genome Browser and https://www.gencodegenes.org.

Plant pan-genomics and its applications

Plant genomes are so highly diverse that a substantial proportion of genomic sequences are not shared among individuals. The variable DNA sequences, along with the conserved core sequences, compose the more sophisticated pan-genome that represents the collection of all non-redundant DNA in a species. With rapid progress in genome sequencing technologies, pan-genome research in plants is now accelerating. Here we review recent advances in plant pan-genomics, including major driving forces of structural variations that constitute the variable sequences, methodological innovations for representing the pan-genome, and major successes in constructing plant pan-genomes. We also summarize recent efforts toward decoding the remaining dark matter in telomere-to-telomere or gapless plant genomes. These new genome resources, which have remarkable advantages over numerous previously assembled less-than-perfect genomes, are expected to become new references for genetic studies and plant breeding.

Comprehensive variant discovery in the era of complete human reference genomes

Advances in long-read sequencing technologies have broadened our understanding of genetic variation in the human population, uncovered new complex structural variants and offered an opportunity to elucidate new variant associations with disease.

AlcoR: alignment-free simulation, mapping, and visualization of low-complexity regions in biological data

BACKGROUND

Low-complexity data analysis is the area that addresses the search and quantification of regions in sequences of elements that contain low-complexity or repetitive elements. For example, these can be tandem repeats, inverted repeats, homopolymer tails, GC-biased regions, similar genes, and hairpins, among many others. Identifying these regions is crucial because of their association with regulatory and structural characteristics. Moreover, their identification provides positional and quantity information where standard assembly methodologies face significant difficulties because of substantial higher depth coverage (mountains), ambiguous read mapping, or where sequencing or reconstruction defects may occur. However, the capability to distinguish low-complexity regions (LCRs) in genomic and proteomic sequences is a challenge that depends on the model's ability to find them automatically. Low-complexity patterns can be implicit through specific or combined sources, such as algorithmic or probabilistic, and recurring to different spatial distances-namely, local, medium, or distant associations.

FINDINGS

This article addresses the challenge of automatically modeling and distinguishing LCRs, providing a new method and tool (AlcoR) for efficient and accurate segmentation and visualization of these regions in genomic and proteomic sequences. The method enables the use of models with different memories, providing the ability to distinguish local from distant low-complexity patterns. The method is reference and alignment free, providing additional methodologies for testing, including a highly flexible simulation method for generating biological sequences (DNA or protein) with different complexity levels, sequence masking, and a visualization tool for automatic computation of the LCR maps into an ideogram style. We provide illustrative demonstrations using synthetic, nearly synthetic, and natural sequences showing the high efficiency and accuracy of AlcoR. As large-scale results, we use AlcoR to unprecedentedly provide a whole-chromosome low-complexity map of a recent complete human genome and the haplotype-resolved chromosome pairs of a heterozygous diploid African cassava cultivar.

CONCLUSIONS

The AlcoR method provides the ability of fast sequence characterization through data complexity analysis, ideally for scenarios entangling the presence of new or unknown sequences. AlcoR is implemented in C language using multithreading to increase the computational speed, is flexible for multiple applications, and does not contain external dependencies. The tool accepts any sequence in FASTA format. The source code is freely provided at https://github.com/cobilab/alcor.

The Dynamic Structure and Rapid Evolution of Human Centromeric Satellite DNA

The complete sequence of a human genome provided our first comprehensive view of the organization of satellite DNA associated with heterochromatin. We review how our understanding of the genetic architecture and epigenetic properties of human centromeric DNA have advanced as a result. Preliminary studies of human and nonhuman ape centromeres reveal complex, saltatory mutational changes organized around distinct evolutionary layers. Pockets of regional hypomethylation within higher-order α-satellite DNA, termed centromere dip regions, appear to define the site of kinetochore attachment in all human chromosomes, although such epigenetic features can vary even within the same chromosome. Sequence resolution of satellite DNA is providing new insights into centromeric function with potential implications for improving our understanding of human biology and health.

de novo variant calling identifies cancer mutation signatures in the 1000 Genomes Project

Detection of de novo variants (DNVs) is critical for studies of disease-related variation and mutation rates. To accelerate DNV calling, we developed a graphics processing units-based workflow. We applied our workflow to whole-genome sequencing data from three parent-child sequenced cohorts including the Simons Simplex Collection (SSC), Simons Foundation Powering Autism Research (SPARK), and the 1000 Genomes Project (1000G) that were sequenced using DNA from blood, saliva, and lymphoblastoid cell lines (LCLs), respectively. The SSC and SPARK DNV callsets were within expectations for number of DNVs, percent at CpG sites, phasing to the paternal chromosome of origin, and average allele balance. However, the 1000G DNV callset was not within expectations and contained excessive DNVs that are likely cell line artifacts. Mutation signature analysis revealed 30% of 1000G DNV signatures matched B-cell lymphoma. Furthermore, we found variants in DNA repair genes and at Clinvar pathogenic or likely-pathogenic sites and significant excess of protein-coding DNVs in IGLL5; a gene known to be involved in B-cell lymphomas. Our study provides a new rapid DNV caller for the field and elucidates important implications of using sequencing data from LCLs for reference building and disease-related projects.

The consequences of recurrent genetic and epigenetic variants in human pluripotent stem cells

It is well established that human pluripotent stem cells (hPSCs) can acquire genetic and epigenetic changes during culture in vitro. Given the increasing use of hPSCs in research and therapy and the vast expansion in the number of hPSC lines available for researchers, the International Society for Stem Cell Research has recognized the need to reassess quality control standards for ensuring the genetic integrity of hPSCs. Here, we summarize current knowledge of the nature of recurrent genetic and epigenetic variants in hPSC culture, the methods for their detection, and what is known concerning their effects on cell behavior in vitro or in vivo. We argue that the potential consequences of low-level contamination of cell therapy products with cells bearing oncogenic variants are essentially unknown at present. We highlight the key challenges facing the field with particular reference to safety assessment of hPSC-derived cellular therapeutics.

Recent advances and current challenges in population genomics of structural variation in animals and plants

The field of population genomics has seen a surge of studies on genomic structural variation over the past two decades. These studies witnessed that structural variation is taxonomically ubiquitous and represent a dominant form of genetic variation within species. Recent advances in technology, especially the development of long-read sequencing platforms, have enabled the discovery of structural variants (SVs) in previously inaccessible genomic regions which unlocked additional structural variation for population studies and revealed that more SVs contribute to evolution than previously perceived. An increasing number of studies suggest that SVs of all types and sizes may have a large effect on phenotype and consequently major impact on rapid adaptation, population divergence, and speciation. However, the functional effect of the vast majority of SVs is unknown and the field generally lacks evidence on the phenotypic consequences of most SVs that are suggested to have adaptive potential. Non-human genomes are heavily under-represented in population-scale studies of SVs. We argue that more research on other species is needed to objectively estimate the contribution of SVs to evolution. We discuss technical challenges associated with SV detection and outline the most recent advances towards more representative reference genomes, which opens a new era in population-scale studies of structural variation.

Fragile sites, chromosomal lesions, tandem repeats, and disease

Expanded tandem repeat DNAs are associated with various unusual chromosomal lesions, despiralizations, multi-branched inter-chromosomal associations, and fragile sites. Fragile sites cytogenetically manifest as localized gaps or discontinuities in chromosome structure and are an important genetic, biological, and health-related phenomena. Common fragile sites (∼230), present in most individuals, are induced by aphidicolin and can be associated with cancer; of the 27 molecularly-mapped common sites, none are associated with a particular DNA sequence motif. Rare fragile sites ( ≳ 40 known), ≤ 5% of the population (may be as few as a single individual), can be associated with neurodevelopmental disease. All 10 molecularly-mapped folate-sensitive fragile sites, the largest category of rare fragile sites, are caused by gene-specific CGG/CCG tandem repeat expansions that are aberrantly CpG methylated and include FRAXA, FRAXE, FRAXF, FRA2A, FRA7A, FRA10A, FRA11A, FRA11B, FRA12A, and FRA16A. The minisatellite-associated rare fragile sites, FRA10B, FRA16B, can be induced by AT-rich DNA-ligands or nucleotide analogs. Despiralized lesions and multi-branched inter-chromosomal associations at the heterochromatic satellite repeats of chromosomes 1, 9, 16 are inducible by de-methylating agents like 5-azadeoxycytidine and can spontaneously arise in patients with ICF syndrome (Immunodeficiency Centromeric instability and Facial anomalies) with mutations in genes regulating DNA methylation. ICF individuals have hypomethylated satellites I-III, alpha-satellites, and subtelomeric repeats. Ribosomal repeats and subtelomeric D4Z4 megasatellites/macrosatellites, are associated with chromosome location, fragility, and disease. Telomere repeats can also assume fragile sites. Dietary deficiencies of folate or vitamin B12, or drug insults are associated with megaloblastic and/or pernicious anemia, that display chromosomes with fragile sites. The recent discovery of many new tandem repeat expansion loci, with varied repeat motifs, where motif lengths can range from mono-nucleotides to megabase units, could be the molecular cause of new fragile sites, or other chromosomal lesions. This review focuses on repeat-associated fragility, covering their induction, cytogenetics, epigenetics, cell type specificity, genetic instability (repeat instability, micronuclei, deletions/rearrangements, and sister chromatid exchange), unusual heritability, disease association, and penetrance. Understanding tandem repeat-associated chromosomal fragile sites provides insight to chromosome structure, genome packaging, genetic instability, and disease.

GBZ file format for pangenome graphs

MOTIVATION

Pangenome graphs representing aligned genome assemblies are being shared in the text-based Graphical Fragment Assembly format. As the number of assemblies grows, there is a need for a file format that can store the highly repetitive data space efficiently.

RESULTS

We propose the GBZ file format based on data structures used in the Giraffe short-read aligner. The format provides good compression, and the files can be efficiently loaded into in-memory data structures. We provide compression and decompression tools and libraries for using GBZ graphs, and we show that they can be efficiently used on a variety of systems.

AVAILABILITY AND IMPLEMENTATION

C++ and Rust implementations are available at https://github.com/jltsiren/gbwtgraph and https://github.com/jltsiren/gbwt-rs, respectively.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

The 22q11.2 Low Copy Repeats

LCR22s are among the most complex loci in the human genome and are susceptible to nonallelic homologous recombination. This can lead to a variety of genomic disorders, including deletions, duplications, and translocations, of which the 22q11.2 deletion syndrome is the most common in humans. Interrogating these phenomena is difficult due to the high complexity of the LCR22s and the inaccurate representation of the LCRs across different reference genomes. Optical mapping techniques, which provide long-range chromosomal maps, could be used to unravel the complex duplicon structure. These techniques have already uncovered the hypervariability of the LCR22-A haplotype in the human population. Although optical LCR22 mapping is a major step forward, long-read sequencing approaches will be essential to reach nucleotide resolution of the LCR22s and map the crossover sites. Accurate maps and sequences are needed to pinpoint potential predisposing alleles and, most importantly, allow for genotype-phenotype studies exploring the role of the LCR22s in health and disease. In addition, this research might provide a paradigm for the study of other rare genomic disorders.

From the reference human genome to human pangenome: Premise, promise and challenge

The Reference Human Genome remains the single most important resource for mapping genetic variations and assessing their impact. However, it is monophasic, incomplete and not representative of the variation that exists in the population. Given the extent of ethno-geographic diversity and the consequent diversity in clinical manifestations of these variations, population specific references were developed overtime. The dramatically plummeting cost of sequencing whole genomes and the advent of third generation long range sequencers allowing accurate, error free, telomere-to-telomere assemblies of human genomes present us with a unique and unprecedented opportunity to develop a more composite standard reference consisting of a collection of multiple genomes that capture the maximal variation existing in the population, with the deepest annotation possible, enabling a realistic, reliable and actionable estimation of clinical significance of specific variations. The Human Pangenome Project thus is a logical next step promising a more accurate and global representation of genomic variations. The pangenome effort must be reciprocally complemented with precise variant discovery tools and exhaustive annotation to ensure unambiguous clinical assessment of the variant in ethno-geographical context. Here we discuss a broad roadmap, the challenges and way forward in developing a universal pangenome reference including data visualization techniques and integration of prior knowledge base in the new graph based architecture and tools to submit, compare, query, annotate and retrieve relevant information from the pangenomes. The biggest challenge, however, will be the ethical, legal and social implications and the training of human resource to the new reference paradigm.

Semi-automated assembly of high-quality diploid human reference genomes

The current human reference genome, GRCh38, represents over 20 years of effort to generate a high-quality assembly, which has benefitted society1,2. However, it still has many gaps and errors, and does not represent a biological genome as it is a blend of multiple individuals3,4. Recently, a high-quality telomere-to-telomere reference, CHM13, was generated with the latest long-read technologies, but it was derived from a hydatidiform mole cell line with a nearly homozygous genome5. To address these limitations, the Human Pangenome Reference Consortium formed with the goal of creating high-quality, cost-effective, diploid genome assemblies for a pangenome reference that represents human genetic diversity6. Here, in our first scientific report, we determined which combination of current genome sequencing and assembly approaches yield the most complete and accurate diploid genome assembly with minimal manual curation. Approaches that used highly accurate long reads and parent-child data with graph-based haplotype phasing during assembly outperformed those that did not. Developing a combination of the top-performing methods, we generated our first high-quality diploid reference assembly, containing only approximately four gaps per chromosome on average, with most chromosomes within ±1% of the length of CHM13. Nearly 48% of protein-coding genes have non-synonymous amino acid changes between haplotypes, and centromeric regions showed the highest diversity. Our findings serve as a foundation for assembling near-complete diploid human genomes at scale for a pangenome reference to capture global genetic variation from single nucleotides to structural rearrangements.

Chromosome-scale haplotype-resolved pangenomics

Complete pangenomics is crucial for understanding genetic diversity and evolution across the tree of life. Chromosome-scale, haplotype-resolved pangenomics allows complex structural variations, long-range interactions, and associated functions to be discerned in species populations. We explore the need for high-resolution pangenomes, discuss computational strategies for their development, and describe applications in biodiversity and human health.

1000 Genomes Project phase 4: The gift that keeps on giving

In this issue of Cell, Bryska-Bishop et al. report the release of the expanded, high-depth sequencing data that characterize the fourth phase of the 1000 Genomes Project. Using extensive comparisons and benchmarks, they demonstrate how this dataset is positioned to serve as a more comprehensive and accurate resource for global genomics.

Exome/Genome-Wide Testing in Newborn Screening: A Proportionate Path Forward

Population-based newborn screening (NBS) is among the most effective public health programs ever launched, improving health outcomes for newborns who screen positive worldwide through early detection and clinical intervention for genetic disorders discovered in the earliest hours of life. Key to the success of newborn screening programs has been near universal accessibility and participation. Interest has been building to expand newborn screening programs to also include many rare genetic diseases that can now be identified by exome or genome sequencing (ES/GS). Significant declines in sequencing costs as well as improvements to sequencing technologies have enabled researchers to elucidate novel gene-disease associations that motivate possible expansion of newborn screening programs. In this paper we consider recommendations from professional genetic societies in Europe and North America in light of scientific advances in ES/GS and our current understanding of the limitations of ES/GS approaches in the NBS context. We invoke the principle of proportionality-that benefits clearly outweigh associated risks-and the human right to benefit from science to argue that rigorous evidence is still needed for ES/GS that demonstrates clinical utility, accurate genomic variant interpretation, cost effectiveness and universal accessibility of testing and necessary follow-up care and treatment. Confirmatory or second-tier testing using ES/GS may be appropriate as an adjunct to conventional newborn screening in some circumstances. Such cases could serve as important testbeds from which to gather data on relevant programmatic barriers and facilitators to wider ES/GS implementation.

Population-scale genotyping of structural variation in the era of long-read sequencing

Population-scale studies of structural variation (SV) are growing rapidly worldwide with the development of long-read sequencing technology, yielding a considerable number of novel SVs and complete gap-closed genome assemblies. Herein, we highlight recent studies using a hybrid sequencing strategy and present the challenges toward large-scale genotyping for SVs due to the reference bias. Genotyping SVs at a population scale remains challenging, which severely impacts genotype-based population genetic studies or genome-wide association studies of complex diseases. We summarize academic efforts to improve genotype quality through linear or graph representations of reference and alternative alleles. Graph-based genotypers capable of integrating diverse genetic information are effectively applied to large and diverse cohorts, contributing to unbiased downstream analysis. Meanwhile, there is still an urgent need in this field for efficient tools to construct complex graphs and perform sequence-to-graph alignments.

Pangenome-based genome inference allows efficient and accurate genotyping across a wide spectrum of variant classes

Typical genotyping workflows map reads to a reference genome before identifying genetic variants. Generating such alignments introduces reference biases and comes with substantial computational burden. Furthermore, short-read lengths limit the ability to characterize repetitive genomic regions, which are particularly challenging for fast k-mer-based genotypers. In the present study, we propose a new algorithm, PanGenie, that leverages a haplotype-resolved pangenome reference together with k-mer counts from short-read sequencing data to genotype a wide spectrum of genetic variation-a process we refer to as genome inference. Compared with mapping-based approaches, PanGenie is more than 4 times faster at 30-fold coverage and achieves better genotype concordances for almost all variant types and coverages tested. Improvements are especially pronounced for large insertions (≥50 bp) and variants in repetitive regions, enabling the inclusion of these classes of variants in genome-wide association studies. PanGenie efficiently leverages the increasing amount of haplotype-resolved assemblies to unravel the functional impact of previously inaccessible variants while being faster compared with alignment-based workflows.