STRIDE-DB: a comprehensive database for exploration of instability and phenotypic relevance of short tandem repeats in the human genome

Short Tandem Repeats (STRs) are genetic markers made up of repeating DNA sequences. The variations of the STRs are widely studied in forensic analysis, population studies and genetic testing for a variety of neuromuscular disorders. Understanding polymorphic STR variation and its cause is crucial for deciphering genetic information and finding links to various disorders. In this paper, we present STRIDE-DB, a novel and unique platform to explore STR Instability and its Phenotypic Relevance, and a comprehensive database of STRs in the human genome. We utilized RepeatMasker to identify all the STRs in the human genome (hg19) and combined it with frequency data from the 1000 Genomes Project. STRIDE-DB, a user-friendly resource, plays a pivotal role in investigating the relationship between STR variation, instability and phenotype. By harnessing data from genome-wide association studies (GWAS), ClinVar database, Alu loci, Haploblocks in genome and Conservation of the STRs, it serves as an important tool for researchers exploring the variability of STRs in the human genome and its direct impact on phenotypes. STRIDE-DB has its broad applicability and significance in various research domains like forensic sciences and other repeat expansion disorders. Database URL: https://stridedb.igib.res.in.

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.

Characterizing identity by descent segments in Chinese interpopulation unrelated individual pairs

Identity by descent (IBD) segments, uninterrupted DNA segments derived from the same ancestral chromosomes, are widely used as indicators of relationships in genetics. A great deal of research focuses on IBD segments between related pairs, while the statistical analyses of segments in irrelevant individuals are rare. In this study, we investigated the basic informative features of IBD segments in unrelated pairs in Chinese populations from the 1000 Genome Project. A total of 5922 IBD segments in Chinese interpopulation unrelated individual pairs were detected via IBIS and the average length of IBD was 3.71 Mb in length. It was found that 17.86% of unrelated pairs shared at least one IBD segment in the Chinese cohort. Furthermore, a total of 49 chromosomal regions where IBD segments clustered in high abundance were identified, which might be sharing hotspots in the human genome. Such regions could also be observed in other ancestry populations, which implies that similar IBD backgrounds also exist. Altogether, these results demonstrated the distribution of common background IBD segments, which helps improve the accuracy in pedigree studies based on IBD analysis.

Deep whole-genome analysis of 494 hepatocellular carcinomas

Over half of hepatocellular carcinoma (HCC) cases diagnosed worldwide are in China1-3. However, whole-genome analysis of hepatitis B virus (HBV)-associated HCC in Chinese individuals is limited4-8, with current analyses of HCC mainly from non-HBV-enriched populations9,10. Here we initiated the Chinese Liver Cancer Atlas (CLCA) project and performed deep whole-genome sequencing (average depth, 120×) of 494 HCC tumours. We identified 6 coding and 28 non-coding previously undescribed driver candidates. Five previously undescribed mutational signatures were found, including aristolochic-acid-associated indel and doublet base signatures, and a single-base-substitution signature that we termed SBS_H8. Pentanucleotide context analysis and experimental validation confirmed that SBS_H8 was distinct to the aristolochic-acid-associated SBS22. Notably, HBV integrations could take the form of extrachromosomal circular DNA, resulting in elevated copy numbers and gene expression. Our high-depth data also enabled us to characterize subclonal clustered alterations, including chromothripsis, chromoplexy and kataegis, suggesting that these catastrophic events could also occur in late stages of hepatocarcinogenesis. Pathway analysis of all classes of alterations further linked non-coding mutations to dysregulation of liver metabolism. Finally, we performed in vitro and in vivo assays to show that fibrinogen alpha chain (FGA), determined as both a candidate coding and non-coding driver, regulates HCC progression and metastasis. Our CLCA study depicts a detailed genomic landscape and evolutionary history of HCC in Chinese individuals, providing important clinical implications.

Gene architecture is a determinant of the transcriptional response to bulky DNA damages

Bulky DNA damages block transcription and compromise genome integrity and function. The cellular response to these damages includes global transcription shutdown. Still, active transcription is necessary for transcription-coupled repair and for induction of damage-response genes. To uncover common features of a general bulky DNA damage response, and to identify response-related transcripts that are expressed despite damage, we performed a systematic RNA-seq study comparing the transcriptional response to three independent damage-inducing agents: UV, the chemotherapy cisplatin, and benzo[a]pyrene, a component of cigarette smoke. Reduction in gene expression after damage was associated with higher damage rates, longer gene length, and low GC content. We identified genes with relatively higher expression after all three damage treatments, including NR4A2, a potential novel damage-response transcription factor. Up-regulated genes exhibit higher exon content that is associated with preferential repair, which could enable rapid damage removal and transcription restoration. The attenuated response to BPDE highlights that not all bulky damages elicit the same response. These findings frame gene architecture as a major determinant of the transcriptional response that is hardwired into the human genome.

Genomic data in the All of Us Research Program

Comprehensively mapping the genetic basis of human disease across diverse individuals is a long-standing goal for the field of human genetics1-4. The All of Us Research Program is a longitudinal cohort study aiming to enrol a diverse group of at least one million individuals across the USA to accelerate biomedical research and improve human health5,6. Here we describe the programme's genomics data release of 245,388 clinical-grade genome sequences. This resource is unique in its diversity as 77% of participants are from communities that are historically under-represented in biomedical research and 46% are individuals from under-represented racial and ethnic minorities. All of Us identified more than 1 billion genetic variants, including more than 275 million previously unreported genetic variants, more than 3.9 million of which had coding consequences. Leveraging linkage between genomic data and the longitudinal electronic health record, we evaluated 3,724 genetic variants associated with 117 diseases and found high replication rates across both participants of European ancestry and participants of African ancestry. Summary-level data are publicly available, and individual-level data can be accessed by researchers through the All of Us Researcher Workbench using a unique data passport model with a median time from initial researcher registration to data access of 29 hours. We anticipate that this diverse dataset will advance the promise of genomic medicine for all.

A quantitative genetic model of background selection in humans

Across the human genome, there are large-scale fluctuations in genetic diversity caused by the indirect effects of selection. This "linked selection signal" reflects the impact of selection according to the physical placement of functional regions and recombination rates along chromosomes. Previous work has shown that purifying selection acting against the steady influx of new deleterious mutations at functional portions of the genome shapes patterns of genomic variation. To date, statistical efforts to estimate purifying selection parameters from linked selection models have relied on classic Background Selection theory, which is only applicable when new mutations are so deleterious that they cannot fix in the population. Here, we develop a statistical method based on a quantitative genetics view of linked selection, that models how polygenic additive fitness variance distributed along the genome increases the rate of stochastic allele frequency change. By jointly predicting the equilibrium fitness variance and substitution rate due to both strong and weakly deleterious mutations, we estimate the distribution of fitness effects (DFE) and mutation rate across three geographically distinct human samples. While our model can accommodate weaker selection, we find evidence of strong selection operating similarly across all human samples. Although our quantitative genetic model of linked selection fits better than previous models, substitution rates of the most constrained sites disagree with observed divergence levels. We find that a model incorporating selective interference better predicts observed divergence in conserved regions, but overall our results suggest uncertainty remains about the processes generating fitness variation in humans.

Precise genome-editing in human diseases: mechanisms, strategies and applications

Precise genome-editing platforms are versatile tools for generating specific, site-directed DNA insertions, deletions, and substitutions. The continuous enhancement of these tools has led to a revolution in the life sciences, which promises to deliver novel therapies for genetic disease. Precise genome-editing can be traced back to the 1950s with the discovery of DNA's double-helix and, after 70 years of development, has evolved from crude in vitro applications to a wide range of sophisticated capabilities, including in vivo applications. Nonetheless, precise genome-editing faces constraints such as modest efficiency, delivery challenges, and off-target effects. In this review, we explore precise genome-editing, with a focus on introduction of the landmark events in its history, various platforms, delivery systems, and applications. First, we discuss the landmark events in the history of precise genome-editing. Second, we describe the current state of precise genome-editing strategies and explain how these techniques offer unprecedented precision and versatility for modifying the human genome. Third, we introduce the current delivery systems used to deploy precise genome-editing components through DNA, RNA, and RNPs. Finally, we summarize the current applications of precise genome-editing in labeling endogenous genes, screening genetic variants, molecular recording, generating disease models, and gene therapy, including ex vivo therapy and in vivo therapy, and discuss potential future advances.

Ancestral genome reconstruction enhances transposable element annotation by identifying degenerate integrants

Growing evidence indicates that transposable elements (TEs) play important roles in evolution by providing genomes with coding and non-coding sequences. Identification of TE-derived functional elements, however, has relied on TE annotations in individual species, which limits its scope to relatively intact TE sequences. Here, we report a novel approach to uncover previously unannotated degenerate TEs (degTEs) by probing multiple ancestral genomes reconstructed from hundreds of species. We applied this method to the human genome and achieved a 10.8% increase in coverage over the most recent annotation. Further, we discovered that degTEs contribute to various cis-regulatory elements and transcription factor binding sites, including those of a known TE-controlling family, the KRAB zinc-finger proteins. We also report unannotated chimeric transcripts between degTEs and human genes expressed in embryos. This study provides a novel methodology and a freely available resource that will facilitate the investigation of TE co-option events on a full scale.

Expanding the DNA editing toolbox: Novel lambda integrase variants targeting microalgal and human genome sequences

Recombinase enzymes are extremely efficient at integrating very large DNA fragments into target genomes. However, intrinsic sequence specificities curtail their use to DNA sequences with sufficient homology to endogenous target motifs. Extensive engineering is therefore required to broaden applicability and robustness. Here, we describe the directed evolution of novel lambda integrase variants capable of editing exogenous target sequences identified in the diatom Phaeodactylum tricornutum and the algae Nannochloropsis oceanica. These microorganisms hold great promise as conduits for green biomanufacturing and carbon sequestration. The evolved enzyme variants show >1000-fold switch in specificity towards the non-natural target sites when assayed in vitro. A single-copy target motif in the human genome with homology to the Nannochloropsis oceanica site can also be efficiently targeted using an engineered integrase, both in vitro and in human cells. The developed integrase variants represent useful additions to the DNA editing toolbox, with particular application for targeted genomic insertion of large DNA cargos.

The Born in Guangzhou Cohort Study enables generational genetic discoveries

Genomic research that targets large-scale, prospective birth cohorts constitutes an essential strategy for understanding the influence of genetics and environment on human health1. Nonetheless, such studies remain scarce, particularly in Asia. Here we present the phase I genome study of the Born in Guangzhou Cohort Study2 (BIGCS), which encompasses the sequencing and analysis of 4,053 Chinese individuals, primarily composed of trios or mother-infant duos residing in South China. Our analysis reveals novel genetic variants, a high-quality reference panel, and fine-scale local genetic structure within BIGCS. Notably, we identify previously unreported East Asian-specific genetic associations with maternal total bile acid, gestational weight gain and infant cord blood traits. Additionally, we observe prevalent age-specific genetic effects on lipid levels in mothers and infants. In an exploratory intergenerational Mendelian randomization analysis, we estimate the maternal putatively causal and fetal genetic effects of seven adult phenotypes on seven fetal growth-related measurements. These findings illuminate the genetic links between maternal and early-life traits in an East Asian population and lay the groundwork for future research into the intricate interplay of genetics, intrauterine exposures and early-life experiences in shaping long-term health.

A general approach for inferring the ancestry of recent ancestors of an admixed individual

The genome of an individual from an admixed population consists of segments originated from different ancestral populations. Most existing ancestry inference approaches focus on calling these segments for the extant individual. In this paper, we present a general ancestry inference approach for inferring recent ancestors from an extant genome. Given the genome of an individual from a recently admixed population, our method can estimate the proportions of the genomes of the recent ancestors of this individual that originated from some ancestral populations. The key step of our method is the inference of ancestors (called founders) right after the formation of an admixed population. The inferred founders can then be used to infer the ancestry of recent ancestors of an extant individual. Our method is implemented in a computer program called PedMix2. To the best of our knowledge, there is no existing method that can practically infer ancestors beyond grandparents from an extant individual's genome. Results on both simulated and real data show that PedMix2 performs well in ancestry inference.

100 ancient genomes show repeated population turnovers in Neolithic Denmark

Major migration events in Holocene Eurasia have been characterized genetically at broad regional scales1-4. However, insights into the population dynamics in the contact zones are hampered by a lack of ancient genomic data sampled at high spatiotemporal resolution5-7. Here, to address this, we analysed shotgun-sequenced genomes from 100 skeletons spanning 7,300 years of the Mesolithic period, Neolithic period and Early Bronze Age in Denmark and integrated these with proxies for diet (13C and 15N content), mobility (87Sr/86Sr ratio) and vegetation cover (pollen). We observe that Danish Mesolithic individuals of the Maglemose, Kongemose and Ertebølle cultures form a distinct genetic cluster related to other Western European hunter-gatherers. Despite shifts in material culture they displayed genetic homogeneity from around 10,500 to 5,900 calibrated years before present, when Neolithic farmers with Anatolian-derived ancestry arrived. Although the Neolithic transition was delayed by more than a millennium relative to Central Europe, it was very abrupt and resulted in a population turnover with limited genetic contribution from local hunter-gatherers. The succeeding Neolithic population, associated with the Funnel Beaker culture, persisted for only about 1,000 years before immigrants with eastern Steppe-derived ancestry arrived. This second and equally rapid population replacement gave rise to the Single Grave culture with an ancestry profile more similar to present-day Danes. In our multiproxy dataset, these major demographic events are manifested as parallel shifts in genotype, phenotype, diet and land use.

Distinct Hodgkin lymphoma subtypes defined by noninvasive genomic profiling

The scarcity of malignant Hodgkin and Reed-Sternberg cells hampers tissue-based comprehensive genomic profiling of classic Hodgkin lymphoma (cHL). By contrast, liquid biopsies show promise for molecular profiling of cHL due to relatively high circulating tumour DNA (ctDNA) levels1-4. Here we show that the plasma representation of mutations exceeds the bulk tumour representation in most cases, making cHL particularly amenable to noninvasive profiling. Leveraging single-cell transcriptional profiles of cHL tumours, we demonstrate Hodgkin and Reed-Sternberg ctDNA shedding to be shaped by DNASE1L3, whose increased tumour microenvironment-derived expression drives high ctDNA concentrations. Using this insight, we comprehensively profile 366 patients, revealing two distinct cHL genomic subtypes with characteristic clinical and prognostic correlates, as well as distinct transcriptional and immunological profiles. Furthermore, we identify a novel class of truncating IL4R mutations that are dependent on IL-13 signalling and therapeutically targetable with IL-4Rα-blocking antibodies. Finally, using PhasED-seq5, we demonstrate the clinical value of pretreatment and on-treatment ctDNA levels for longitudinally refining cHL risk prediction and for detection of radiographically occult minimal residual disease. Collectively, these results support the utility of noninvasive strategies for genotyping and dynamic monitoring of cHL, as well as capturing molecularly distinct subtypes with diagnostic, prognostic and therapeutic potential.

Accurate detection of identity-by-descent segments in human ancient DNA

Long DNA segments shared between two individuals, known as identity-by-descent (IBD), reveal recent genealogical connections. Here we introduce ancIBD, a method for identifying IBD segments in ancient human DNA (aDNA) using a hidden Markov model and imputed genotype probabilities. We demonstrate that ancIBD accurately identifies IBD segments >8 cM for aDNA data with an average depth of >0.25× for whole-genome sequencing or >1× for 1240k single nucleotide polymorphism capture data. Applying ancIBD to 4,248 ancient Eurasian individuals, we identify relatives up to the sixth degree and genealogical connections between archaeological groups. Notably, we reveal long IBD sharing between Corded Ware and Yamnaya groups, indicating that the Yamnaya herders of the Pontic-Caspian Steppe and the Steppe-related ancestry in various European Corded Ware groups share substantial co-ancestry within only a few hundred years. These results show that detecting IBD segments can generate powerful insights into the growing aDNA record, both on a small scale relevant to life stories and on a large scale relevant to major cultural-historical events.

The selection landscape and genetic legacy of ancient Eurasians

The Holocene (beginning around 12,000 years ago) encompassed some of the most significant changes in human evolution, with far-reaching consequences for the dietary, physical and mental health of present-day populations. Using a dataset of more than 1,600 imputed ancient genomes1, we modelled the selection landscape during the transition from hunting and gathering, to farming and pastoralism across West Eurasia. We identify key selection signals related to metabolism, including that selection at the FADS cluster began earlier than previously reported and that selection near the LCT locus predates the emergence of the lactase persistence allele by thousands of years. We also find strong selection in the HLA region, possibly due to increased exposure to pathogens during the Bronze Age. Using ancient individuals to infer local ancestry tracts in over 400,000 samples from the UK Biobank, we identify widespread differences in the distribution of Mesolithic, Neolithic and Bronze Age ancestries across Eurasia. By calculating ancestry-specific polygenic risk scores, we show that height differences between Northern and Southern Europe are associated with differential Steppe ancestry, rather than selection, and that risk alleles for mood-related phenotypes are enriched for Neolithic farmer ancestry, whereas risk alleles for diabetes and Alzheimer's disease are enriched for Western hunter-gatherer ancestry. Our results indicate that ancient selection and migration were large contributors to the distribution of phenotypic diversity in present-day Europeans.

A genomic mutational constraint map using variation in 76,156 human genomes

The depletion of disruptive variation caused by purifying natural selection (constraint) has been widely used to investigate protein-coding genes underlying human disorders1-4, but attempts to assess constraint for non-protein-coding regions have proved more difficult. Here we aggregate, process and release a dataset of 76,156 human genomes from the Genome Aggregation Database (gnomAD)-the largest public open-access human genome allele frequency reference dataset-and use it to build a genomic constraint map for the whole genome (genomic non-coding constraint of haploinsufficient variation (Gnocchi)). We present a refined mutational model that incorporates local sequence context and regional genomic features to detect depletions of variation. As expected, the average constraint for protein-coding sequences is stronger than that for non-coding regions. Within the non-coding genome, constrained regions are enriched for known regulatory elements and variants that are implicated in complex human diseases and traits, facilitating the triangulation of biological annotation, disease association and natural selection to non-coding DNA analysis. More constrained regulatory elements tend to regulate more constrained protein-coding genes, which in turn suggests that non-coding constraint can aid the identification of constrained genes that are as yet unrecognized by current gene constraint metrics. We demonstrate that this genome-wide constraint map improves the identification and interpretation of functional human genetic variation.

Host genetic regulation of human gut microbial structural variation

Although the impact of host genetics on gut microbial diversity and the abundance of specific taxa is well established1-6, little is known about how host genetics regulates the genetic diversity of gut microorganisms. Here we conducted a meta-analysis of associations between human genetic variation and gut microbial structural variation in 9,015 individuals from four Dutch cohorts. Strikingly, the presence rate of a structural variation segment in Faecalibacterium prausnitzii that harbours an N-acetylgalactosamine (GalNAc) utilization gene cluster is higher in individuals who secrete the type A oligosaccharide antigen terminating in GalNAc, a feature that is jointly determined by human ABO and FUT2 genotypes, and we could replicate this association in a Tanzanian cohort. In vitro experiments demonstrated that GalNAc can be used as the sole carbohydrate source for F. prausnitzii strains that carry the GalNAc-metabolizing pathway. Further in silico and in vitro studies demonstrated that other ABO-associated species can also utilize GalNAc, particularly Collinsella aerofaciens. The GalNAc utilization genes are also associated with the host's cardiometabolic health, particularly in individuals with mucosal A-antigen. Together, the findings of our study demonstrate that genetic associations across the human genome and bacterial metagenome can provide functional insights into the reciprocal host-microbiome relationship.

High-throughput PRIME-editing screens identify functional DNA variants in the human genome

Despite tremendous progress in detecting DNA variants associated with human disease, interpreting their functional impact in a high-throughput and single-base resolution manner remains challenging. Here, we develop a pooled prime-editing screen method, PRIME, that can be applied to characterize thousands of coding and non-coding variants in a single experiment with high reproducibility. To showcase its applications, we first identified essential nucleotides for a 716 bp MYC enhancer via PRIME-mediated single-base resolution analysis. Next, we applied PRIME to functionally characterize 1,304 genome-wide association study (GWAS)-identified non-coding variants associated with breast cancer and 3,699 variants from ClinVar. We discovered that 103 non-coding variants and 156 variants of uncertain significance are functional via affecting cell fitness. Collectively, we demonstrate that PRIME is capable of characterizing genetic variants at single-base resolution and scale, advancing accurate genome annotation for disease risk prediction, diagnosis, and therapeutic target identification.

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

Background

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

Results

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

Conclusions

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

The Human Genome Organisation (HUGO) and a vision for Ecogenomics: the Ecological Genome Project

BACKGROUND

The following outlines ethical reasons for widening the Human Genome Organisation's (HUGO) mandate to include ecological genomics. MAIN: The environment influences an organism's genome through ambient factors in the biosphere (e.g. climate and UV radiation), as well as the agents it comes into contact with, i.e. the epigenetic and mutagenic effects of inanimate chemicals and pollution, and pathogenic organisms. Emerging scientific consensus is that social determinants of health, environmental conditions and genetic factors work together to influence the risk of many complex illnesses. That paradigm can also explain the environmental and ecological determinants of health as factors that underlie the (un)healthy ecosystems on which communities rely. We suggest that The Ecological Genome Project is an aspirational opportunity to explore connections between the human genome and nature. We propose consolidating a view of Ecogenomics to provide a blueprint to respond to the environmental challenges that societies face. This can only be achieved by interdisciplinary engagement between genomics and the broad field of ecology and related practice of conservation. In this respect, the One Health approach is a model for environmental orientated work. The idea of Ecogenomics-a term that has been used to relate to a scientific field of ecological genomics-becomes the conceptual study of genomes within the social and natural environment.

CONCLUSION

The HUGO Committee on Ethics, Law and Society (CELS) recommends that an interdisciplinary One Health approach should be adopted in genomic sciences to promote ethical environmentalism. This perspective has been reviewed and endorsed by the HUGO CELS and the HUGO Executive Board.

vcfdist: accurately benchmarking phased small variant calls in human genomes

Accurately benchmarking small variant calling accuracy is critical for the continued improvement of human whole genome sequencing. In this work, we show that current variant calling evaluations are biased towards certain variant representations and may misrepresent the relative performance of different variant calling pipelines. We propose solutions, first exploring the affine gap parameter design space for complex variant representation and suggesting a standard. Next, we present our tool vcfdist and demonstrate the importance of enforcing local phasing for evaluation accuracy. We then introduce the notion of partial credit for mostly-correct calls and present an algorithm for clustering dependent variants. Lastly, we motivate using alignment distance metrics to supplement precision-recall curves for understanding variant calling performance. We evaluate the performance of 64 phased Truth Challenge V2 submissions and show that vcfdist improves measured insertion and deletion performance consistency across variant representations from R2 = 0.97243 for baseline vcfeval to 0.99996 for vcfdist.

The landscape of genomic structural variation in Indigenous Australians

Indigenous Australians harbour rich and unique genomic diversity. However, Aboriginal and Torres Strait Islander ancestries are historically under-represented in genomics research and almost completely missing from reference datasets1-3. Addressing this representation gap is critical, both to advance our understanding of global human genomic diversity and as a prerequisite for ensuring equitable outcomes in genomic medicine. Here we apply population-scale whole-genome long-read sequencing4 to profile genomic structural variation across four remote Indigenous communities. We uncover an abundance of large insertion-deletion variants (20-49 bp; n = 136,797), structural variants (50  b-50 kb; n = 159,912) and regions of variable copy number (>50 kb; n = 156). The majority of variants are composed of tandem repeat or interspersed mobile element sequences (up to 90%) and have not been previously annotated (up to 62%). A large fraction of structural variants appear to be exclusive to Indigenous Australians (12% lower-bound estimate) and most of these are found in only a single community, underscoring the need for broad and deep sampling to achieve a comprehensive catalogue of genomic structural variation across the Australian continent. Finally, we explore short tandem repeats throughout the genome to characterize allelic diversity at 50 known disease loci5, uncover hundreds of novel repeat expansion sites within protein-coding genes, and identify unique patterns of diversity and constraint among short tandem repeat sequences. Our study sheds new light on the dimensions and dynamics of genomic structural variation within and beyond Australia.

Most large structural variants in cancer genomes can be detected without long reads

Short-read sequencing is the workhorse of cancer genomics yet is thought to miss many structural variants (SVs), particularly large chromosomal alterations. To characterize missing SVs in short-read whole genomes, we analyzed 'loose ends'-local violations of mass balance between adjacent DNA segments. In the landscape of loose ends across 1,330 high-purity cancer whole genomes, most large (>10-kb) clonal SVs were fully resolved by short reads in the 87% of the human genome where copy number could be reliably measured. Some loose ends represent neotelomeres, which we propose as a hallmark of the alternative lengthening of telomeres phenotype. These pan-cancer findings were confirmed by long-molecule profiles of 38 breast cancer and melanoma cases. Our results indicate that aberrant homologous recombination is unlikely to drive the majority of large cancer SVs. Furthermore, analysis of mass balance in short-read whole genome data provides a surprisingly complete picture of cancer chromosomal structure.

Indigenous Australian genomes show deep structure and rich novel variation

The Indigenous peoples of Australia have a rich linguistic and cultural history. How this relates to genetic diversity remains largely unknown because of their limited engagement with genomic studies. Here we analyse the genomes of 159 individuals from four remote Indigenous communities, including people who speak a language (Tiwi) not from the most widespread family (Pama-Nyungan). This large collection of Indigenous Australian genomes was made possible by careful community engagement and consultation. We observe exceptionally strong population structure across Australia, driven by divergence times between communities of 26,000-35,000 years ago and long-term low but stable effective population sizes. This demographic history, including early divergence from Papua New Guinean (47,000 years ago) and Eurasian groups1, has generated the highest proportion of previously undescribed genetic variation seen outside Africa and the most extended homozygosity compared with global samples. A substantial proportion of this variation is not observed in global reference panels or clinical datasets, and variation with predicted functional consequence is more likely to be homozygous than in other populations, with consequent implications for medical genomics2. Our results show that Indigenous Australians are not a single homogeneous genetic group and their genetic relationship with the peoples of New Guinea is not uniform. These patterns imply that the full breadth of Indigenous Australian genetic diversity remains uncharacterized, potentially limiting genomic medicine and equitable healthcare for Indigenous Australians.

A complex with poly(A)-binding protein and EWS facilitates the transcriptional function of oncogenic ETS transcription factors in prostate cells

The ETS transcription factor ERG is aberrantly expressed in approximately 50% of prostate tumors due to chromosomal rearrangements such as TMPRSS2/ERG. The ability of ERG to drive oncogenesis in prostate epithelial cells requires interaction with distinct coactivators, such as the RNA-binding protein EWS. Here, we find that ERG has both direct and indirect interactions with EWS, and the indirect interaction is mediated by the poly-A RNA-binding protein PABPC1. PABPC1 directly bound both ERG and EWS. ERG expression in prostate cells promoted PABPC1 localization to the nucleus and recruited PABPC1 to ERG/EWS-binding sites in the genome. Knockdown of PABPC1 in prostate cells abrogated ERG-mediated phenotypes and decreased the ability of ERG to activate transcription. These findings define a complex including ERG and the RNA-binding proteins EWS and PABPC1 that represents a potential therapeutic target for ERG-positive prostate cancer and identify a novel nuclear role for PABPC1.

Genetic continuity and change among the Indigenous peoples of California

Before the colonial period, California harboured more language variation than all of Europe, and linguistic and archaeological analyses have led to many hypotheses to explain this diversity1. We report genome-wide data from 79 ancient individuals from California and 40 ancient individuals from Northern Mexico dating to 7,400-200 years before present (BP). Our analyses document long-term genetic continuity between people living on the Northern Channel Islands of California and the adjacent Santa Barbara mainland coast from 7,400 years BP to modern Chumash groups represented by individuals who lived around 200 years BP. The distinctive genetic lineages that characterize present-day and ancient people from Northwest Mexico increased in frequency in Southern and Central California by 5,200 years BP, providing evidence for northward migrations that are candidates for spreading Uto-Aztecan languages before the dispersal of maize agriculture from Mexico2-4. Individuals from Baja California share more alleles with the earliest individual from Central California in the dataset than with later individuals from Central California, potentially reflecting an earlier linguistic substrate, whose impact on local ancestry was diluted by later migrations from inland regions1,5. After 1,600 years BP, ancient individuals from the Channel Islands lived in communities with effective sizes similar to those in pre-agricultural Caribbean and Patagonia, and smaller than those on the California mainland and in sampled regions of Mexico.

Overlaps Between CDS Regions of Protein-Coding Genes in the Human Genome: A Case Study on the NR1D1-THRA Gene Pair

For several decades, it has been known that a substantial number of genes within human DNA exhibit overlap; however, the biological and evolutionary significance of these overlaps remain poorly understood. This study focused on investigating specific instances of overlap where the overlapping DNA region encompasses the coding DNA sequences (CDSs) of protein-coding genes. The results revealed that proteins encoded by overlapping CDSs exhibit greater disorder than those from nonoverlapping CDSs. Additionally, these DNA regions were identified as GC-rich. This could be partially attributed to the absence of stop codons from two distinct reading frames rather than one. Furthermore, these regions were found to harbour fewer single-nucleotide polymorphism (SNP) sites, possibly due to constraints arising from the overlapping state where mutations could affect two genes simultaneously.While elucidating these properties, the NR1D1-THRA gene pair emerged as an exceptional case with highly structured proteins and a distinctly conserved sequence across eutherian mammals. Both NR1D1 and THRA are nuclear receptors lacking a ligand-binding domain at their C-terminus, which is the region where these gene pairs overlap. The NR1D1 gene is involved in the regulation of circadian rhythm, while the THRA gene encodes a thyroid hormone receptor, and both play crucial roles in various physiological processes. This study suggests that, in addition to their well-established functions, the specifically overlapping CDS regions of these genes may encode protein segments with additional, yet undiscovered, biological roles.

The landscape of human SVA retrotransposons

SINE-VNTR-Alu (SVA) retrotransposons are evolutionarily young and still-active transposable elements (TEs) in the human genome. Several pathogenic SVA insertions have been identified that directly mutate host genes to cause neurodegenerative and other types of diseases. However, due to their sequence heterogeneity and complex structures as well as limitations in sequencing techniques and analysis, SVA insertions have been less well studied compared to other mobile element insertions. Here, we identified polymorphic SVA insertions from 3646 whole-genome sequencing (WGS) samples of >150 diverse populations and constructed a polymorphic SVA insertion reference catalog. Using 20 long-read samples, we also assembled reference and polymorphic SVA sequences and characterized the internal hexamer/variable-number-tandem-repeat (VNTR) expansions as well as differing SVA activity for SVA subfamilies and human populations. In addition, we developed a module to annotate both reference and polymorphic SVA copies. By characterizing the landscape of both reference and polymorphic SVA retrotransposons, our study enables more accurate genotyping of these elements and facilitate the discovery of pathogenic SVA insertions.

Deep learning of human polyadenylation sites at nucleotide resolution reveals molecular determinants of site usage and relevance in disease

The genomic distribution of cleavage and polyadenylation (polyA) sites should be co-evolutionally optimized with the local gene structure. Otherwise, spurious polyadenylation can cause premature transcription termination and generate aberrant proteins. To obtain mechanistic insights into polyA site optimization across the human genome, we develop deep/machine learning models to identify genome-wide putative polyA sites at unprecedented nucleotide-level resolution and calculate their strength and usage in the genomic context. Our models quantitatively measure position-specific motif importance and their crosstalk in polyA site formation and cleavage heterogeneity. The intronic site expression is governed by the surrounding splicing landscape. The usage of alternative polyA sites in terminal exons is modulated by their relative locations and distance to downstream genes. Finally, we apply our models to reveal thousands of disease- and trait-associated genetic variants altering polyadenylation activity. Altogether, our models represent a valuable resource to dissect molecular mechanisms mediating genome-wide polyA site expression and characterize their functional roles in human diseases.

Envisioning a new era: Complete genetic information from routine, telomere-to-telomere genomes

Advances in long-read sequencing and assembly now mean that individual labs can generate phased genomes that are more accurate and more contiguous than the original human reference genome. With declining costs and increasing democratization of technology, we suggest that complete genome assemblies, where both parental haplotypes are phased telomere to telomere, will become standard in human genetics. Soon, even in clinical settings where rigorous sample-handling standards must be met, affected individuals could have reference-grade genomes fully sequenced and assembled in just a few hours given advances in technology, computational processing, and annotation. Complete genetic variant discovery will transform how we map, catalog, and associate variation with human disease and fundamentally change our understanding of the genetic diversity of all humans.

What's in a name? Justifying terminology for genomic findings beyond the initial test indication: A scoping review

Genome sequencing can generate findings beyond the initial test indication that may be relevant to a patient or research participant's health. In the decade since the American College of Medical Genetics and Genomics published its recommendations for reporting these findings, consensus regarding terminology has remained elusive and a variety of terms are in use globally. We conducted a scoping review to explore terminology choice and the justifications underlying those choices. Documents were included if they contained a justification for their choice of term(s) related to findings beyond the initial genomic test indication. From 3571 unique documents, 52 were included, just over half of which pertained to the clinical context (n = 29, 56%). We identified four inter-related concepts used to defend or oppose terms: expectedness of the finding, effective communication, relatedness to the original test indication, and how genomic information was generated. A variety of justifications were used to oppose the term "incidental," whereas "secondary" had broader support as a term to describe findings deliberately sought. Terminology choice would benefit from further work to include the views of patients. We contend that clear definitions will improve ethical debate and support communication about genomic findings beyond the initial test indication.

Genome-wide analysis of the interplay between chromatin-associated RNA and 3D genome organization in human cells

The interphase genome is dynamically organized in the nucleus and decorated with chromatin-associated RNA (caRNA). It remains unclear whether the genome architecture modulates the spatial distribution of caRNA and vice versa. Here, we generate a resource of genome-wide RNA-DNA and DNA-DNA contact maps in human cells. These maps reveal the chromosomal domains demarcated by locally transcribed RNA, hereafter termed RNA-defined chromosomal domains. Further, the spreading of caRNA is constrained by the boundaries of topologically associating domains (TADs), demonstrating the role of the 3D genome structure in modulating the spatial distribution of RNA. Conversely, stopping transcription or acute depletion of RNA induces thousands of chromatin loops genome-wide. Activation or suppression of the transcription of specific genes suppresses or creates chromatin loops straddling these genes. Deletion of a specific caRNA-producing genomic sequence promotes chromatin loops that straddle the interchromosomal target sequences of this caRNA. These data suggest a feedback loop where the 3D genome modulates the spatial distribution of RNA, which in turn affects the dynamic 3D genome organization.

Demographic modeling of admixed Latin American populations from whole genomes

Demographic models of Latin American populations often fail to fully capture their complex evolutionary history, which has been shaped by both recent admixture and deeper-in-time demographic events. To address this gap, we used high-coverage whole-genome data from Indigenous American ancestries in present-day Mexico and existing genomes from across Latin America to infer multiple demographic models that capture the impact of different timescales on genetic diversity. Our approach, which combines analyses of allele frequencies and ancestry tract length distributions, represents a significant improvement over current models in predicting patterns of genetic variation in admixed Latin American populations. We jointly modeled the contribution of European, African, East Asian, and Indigenous American ancestries into present-day Latin American populations. We infer that the ancestors of Indigenous Americans and East Asians diverged ∼30 thousand years ago, and we characterize genetic contributions of recent migrations from East and Southeast Asia to Peru and Mexico. Our inferred demographic histories are consistent across different genomic regions and annotations, suggesting that our inferences are robust to the potential effects of linked selection. In conjunction with published distributions of fitness effects for new nonsynonymous mutations in humans, we show in large-scale simulations that our models recover important features of both neutral and deleterious variation. By providing a more realistic framework for understanding the evolutionary history of Latin American populations, our models can help address the historical under-representation of admixed groups in genomics research and can be a valuable resource for future studies of populations with complex admixture and demographic histories.

Motivations to learn genomic information are not exceptional: Lessons from behavioral science

Whether to undergo genome sequencing in a clinical or research context is generally a voluntary choice. Individuals are often motivated to learn genomic information even when clinical utility-the possibility that the test could inform medical recommendations or health outcomes-is low or absent. Motivations to seek one's genomic information can be cognitive, affective, social, or mixed (e.g., cognitive and affective) in nature. These motivations are based on the perceived value of the information, specifically, its clinical utility and personal utility. We suggest that motivations to learn genomic information are no different from motivations to learn other types of personal information, including one's health status and disease risk. Here, we review behavioral science relevant to motivations that may drive engagement with genome sequencing, both in the presence of varying degrees of clinical utility and in the absence of clinical utility. Specifically, we elucidate 10 motivations that are expected to underlie decisions to undergo genome sequencing. Recognizing these motivations to learn genomic information will guide future research and ultimately help clinicians to facilitate informed decision making among individuals as genome sequencing becomes increasingly available.

Disruption of regulatory domains and novel transcripts as disease-causing mechanisms

Deletions, duplications, insertions, inversions, and translocations, collectively called structural variations (SVs), affect more base pairs of the genome than any other sequence variant. The recent technological advancements in genome sequencing have enabled the discovery of tens of thousands of SVs per human genome. These SVs primarily affect non-coding DNA sequences, but the difficulties in interpreting their impact limit our understanding of human disease etiology. The functional annotation of non-coding DNA sequences and methodologies to characterize their three-dimensional (3D) organization in the nucleus have greatly expanded our understanding of the basic mechanisms underlying gene regulation, thereby improving the interpretation of SVs for their pathogenic impact. Here, we discuss the various mechanisms by which SVs can result in altered gene regulation and how these mechanisms can result in rare genetic disorders. Beyond changing gene expression, SVs can produce novel gene-intergenic fusion transcripts at the SV breakpoints.

Telomere-to-telomere assembly of diploid chromosomes with Verkko

The Telomere-to-Telomere consortium recently assembled the first truly complete sequence of a human genome. To resolve the most complex repeats, this project relied on manual integration of ultra-long Oxford Nanopore sequencing reads with a high-resolution assembly graph built from long, accurate PacBio high-fidelity reads. We have improved and automated this strategy in Verkko, an iterative, graph-based pipeline for assembling complete, diploid genomes. Verkko begins with a multiplex de Bruijn graph built from long, accurate reads and progressively simplifies this graph by integrating ultra-long reads and haplotype-specific markers. The result is a phased, diploid assembly of both haplotypes, with many chromosomes automatically assembled from telomere to telomere. Running Verkko on the HG002 human genome resulted in 20 of 46 diploid chromosomes assembled without gaps at 99.9997% accuracy. The complete assembly of diploid genomes is a critical step towards the construction of comprehensive pangenome databases and chromosome-scale comparative genomics.

Genotyping, sequencing and analysis of 140,000 adults from Mexico City

The Mexico City Prospective Study is a prospective cohort of more than 150,000 adults recruited two decades ago from the urban districts of Coyoacán and Iztapalapa in Mexico City1. Here we generated genotype and exome-sequencing data for all individuals and whole-genome sequencing data for 9,950 selected individuals. We describe high levels of relatedness and substantial heterogeneity in ancestry composition across individuals. Most sequenced individuals had admixed Indigenous American, European and African ancestry, with extensive admixture from Indigenous populations in central, southern and southeastern Mexico. Indigenous Mexican segments of the genome had lower levels of coding variation but an excess of homozygous loss-of-function variants compared with segments of African and European origin. We estimated ancestry-specific allele frequencies at 142 million genomic variants, with an effective sample size of 91,856 for Indigenous Mexican ancestry at exome variants, all available through a public browser. Using whole-genome sequencing, we developed an imputation reference panel that outperforms existing panels at common variants in individuals with high proportions of central, southern and southeastern Indigenous Mexican ancestry. Our work illustrates the value of genetic studies in diverse populations and provides foundational imputation and allele frequency resources for future genetic studies in Mexico and in the United States, where the Hispanic/Latino population is predominantly of Mexican descent.

Mexican Biobank advances population and medical genomics of diverse ancestries

Latin America continues to be severely underrepresented in genomics research, and fine-scale genetic histories and complex trait architectures remain hidden owing to insufficient data1. To fill this gap, the Mexican Biobank project genotyped 6,057 individuals from 898 rural and urban localities across all 32 states in Mexico at a resolution of 1.8 million genome-wide markers with linked complex trait and disease information creating a valuable nationwide genotype-phenotype database. Here, using ancestry deconvolution and inference of identity-by-descent segments, we inferred ancestral population sizes across Mesoamerican regions over time, unravelling Indigenous, colonial and postcolonial demographic dynamics2-6. We observed variation in runs of homozygosity among genomic regions with different ancestries reflecting distinct demographic histories and, in turn, different distributions of rare deleterious variants. We conducted genome-wide association studies (GWAS) for 22 complex traits and found that several traits are better predicted using the Mexican Biobank GWAS compared to the UK Biobank GWAS7,8. We identified genetic and environmental factors associating with trait variation, such as the length of the genome in runs of homozygosity as a predictor for body mass index, triglycerides, glucose and height. This study provides insights into the genetic histories of individuals in Mexico and dissects their complex trait architectures, both crucial for making precision and preventive medicine initiatives accessible worldwide.

Large-scale plasma proteomics comparisons through genetics and disease associations

High-throughput proteomics platforms measuring thousands of proteins in plasma combined with genomic and phenotypic information have the power to bridge the gap between the genome and diseases. Here we performed association studies of Olink Explore 3072 data generated by the UK Biobank Pharma Proteomics Project1 on plasma samples from more than 50,000 UK Biobank participants with phenotypic and genotypic data, stratifying on British or Irish, African and South Asian ancestries. We compared the results with those of a SomaScan v4 study on plasma from 36,000 Icelandic people2, for 1,514 of whom Olink data were also available. We found modest correlation between the two platforms. Although cis protein quantitative trait loci were detected for a similar absolute number of assays on the two platforms (2,101 on Olink versus 2,120 on SomaScan), the proportion of assays with such supporting evidence for assay performance was higher on the Olink platform (72% versus 43%). A considerable number of proteins had genomic associations that differed between the platforms. We provide examples where differences between platforms may influence conclusions drawn from the integration of protein levels with the study of diseases. We demonstrate how leveraging the diverse ancestries of participants in the UK Biobank helps to detect novel associations and refine genomic location. Our results show the value of the information provided by the two most commonly used high-throughput proteomics platforms and demonstrate the differences between them that at times provides useful complementarity.

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

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

The status of the human gene catalogue

Scientists have been trying to identify every gene in the human genome since the initial draft was published in 2001. In the years since, much progress has been made in identifying protein-coding genes, currently estimated to number fewer than 20,000, with an ever-expanding number of distinct protein-coding isoforms. Here we review the status of the human gene catalogue and the efforts to complete it in recent years. Beside the ongoing annotation of protein-coding genes, their isoforms and pseudogenes, the invention of high-throughput RNA sequencing and other technological breakthroughs have led to a rapid growth in the number of reported non-coding RNA genes. For most of these non-coding RNAs, the functional relevance is currently unclear; we look at recent advances that offer paths forward to identifying their functions and towards eventually completing the human gene catalogue. Finally, we examine the need for a universal annotation standard that includes all medically significant genes and maintains their relationships with different reference genomes for the use of the human gene catalogue in clinical settings.

A landscape of complex tandem repeats within individual human genomes

Markedly expanded tandem repeats (TRs) have been correlated with ~60 diseases. TR diversity has been considered a clue toward understanding missing heritability. However, haplotype-resolved long TRs remain mostly hidden or blacked out because their complex structures (TRs composed of various units and minisatellites containing >10-bp units) make them difficult to determine accurately with existing methods. Here, using a high-precision algorithm to determine complex TR structures from long, accurate reads of PacBio HiFi, an investigation of 270 Japanese control samples yields several genome-wide findings. Approximately 322,000 TRs are difficult to impute from the surrounding single-nucleotide variants. Greater genetic divergence of TR loci is significantly correlated with more events of younger replication slippage. Complex TRs are more abundant than single-unit TRs, and a tendency for complex TRs to consist of <10-bp units and single-unit TRs to be minisatellites is statistically significant at loci with ≥500-bp TRs. Of note, 8909 loci with extended TRs (>100b longer than the mode) contain several known disease-associated TRs and are considered candidates for association with disorders. Overall, complex TRs and minisatellites are found to be abundant and diverse, even in genetically small Japanese populations, yielding insights into the landscape of long TRs.

Deciphering complex breakage-fusion-bridge genome rearrangements with Ambigram

Breakage-fusion-bridge (BFB) is a complex rearrangement that leads to tumor malignancy. Existing models for detecting BFBs rely on the ideal BFB hypothesis, ruling out the possibility of BFBs entangled with other structural variations, that is, complex BFBs. We propose an algorithm Ambigram to identify complex BFB and reconstruct the rearranged structure of the local genome during the cancer subclone evolution process. Ambigram handles data from short, linked, long, and single-cell sequences, and optical mapping technologies. Ambigram successfully deciphers the gold- or silver-standard complex BFBs against the state-of-the-art in multiple cancers. Ambigram dissects the intratumor heterogeneity of complex BFB events with single-cell reads from melanoma and gastric cancer. Furthermore, applying Ambigram to liver and cervical cancer data suggests that the BFB mechanism may mediate oncovirus integrations. BFB also exists in noncancer genomics. Investigating the complete human genome reference with Ambigram suggests that the BFB mechanism may be involved in two genome reorganizations of Homo Sapiens during evolution. Moreover, Ambigram discovers the signals of recurrent foldback inversions and complex BFBs in whole genome data from the 1000 genome project, and congenital heart diseases, respectively.

Genome-wide prediction of disease variant effects with a deep protein language model

Predicting the effects of coding variants is a major challenge. While recent deep-learning models have improved variant effect prediction accuracy, they cannot analyze all coding variants due to dependency on close homologs or software limitations. Here we developed a workflow using ESM1b, a 650-million-parameter protein language model, to predict all ~450 million possible missense variant effects in the human genome, and made all predictions available on a web portal. ESM1b outperformed existing methods in classifying ~150,000 ClinVar/HGMD missense variants as pathogenic or benign and predicting measurements across 28 deep mutational scan datasets. We further annotated ~2 million variants as damaging only in specific protein isoforms, demonstrating the importance of considering all isoforms when predicting variant effects. Our approach also generalizes to more complex coding variants such as in-frame indels and stop-gains. Together, these results establish protein language models as an effective, accurate and general approach to predicting variant effects.

Assembly of 43 human Y chromosomes reveals extensive complexity and variation

The prevalence of highly repetitive sequences within the human Y chromosome has prevented its complete assembly to date1 and led to its systematic omission from genomic analyses. Here we present de novo assemblies of 43 Y chromosomes spanning 182,900 years of human evolution and report considerable diversity in size and structure. Half of the male-specific euchromatic region is subject to large inversions with a greater than twofold higher recurrence rate compared with all other chromosomes2. Ampliconic sequences associated with these inversions show differing mutation rates that are sequence context dependent, and some ampliconic genes exhibit evidence for concerted evolution with the acquisition and purging of lineage-specific pseudogenes. The largest heterochromatic region in the human genome, Yq12, is composed of alternating repeat arrays that show extensive variation in the number, size and distribution, but retain a 1:1 copy-number ratio. Finally, our data suggest that the boundary between the recombining pseudoautosomal region 1 and the non-recombining portions of the X and Y chromosomes lies 500 kb away from the currently established1 boundary. The availability of fully sequence-resolved Y chromosomes from multiple individuals provides a unique opportunity for identifying new associations of traits with specific Y-chromosomal variants and garnering insights into the evolution and function of complex regions of the human genome.