Mapping and characterization of structural variation in 17,795 human genomes

Discovery of a polymorphic gene fusion via bottom-up chimeric RNA prediction

Gene fusions and their chimeric products are commonly linked with cancer. However, recent studies have found chimeric transcripts in non-cancer tissues and cell lines. Large-scale efforts to annotate structural variations have identified gene fusions capable of generating chimeric transcripts even in normal tissues. In this study, we present a bottom-up approach targeting population-specific chimeric RNAs, identifying 58 such instances in the GTEx cohort, including notable cases such as SUZ12P1-CRLF3, TFG-ADGRG7 and TRPM4-PPFIA3, which possess distinct patterns across different ancestry groups. We provide direct evidence for an additional 29 polymorphic chimeric RNAs with associated structural variants, revealing 13 novel rare structural variants. Additionally, we utilize the All of Us dataset and a large cohort of clinical samples to characterize the association of the SUZ12P1-CRLF3-causing variant with patient phenotypes. Our study showcases SUZ12P1-CRLF3 as a representative example, illustrating the identification of elusive structural variants by focusing on those producing population-specific fusion transcripts.

Mapping and functional characterization of structural variation in 1060 pig genomes

BACKGROUND

Structural variations (SVs) have significant impacts on complex phenotypes by rearranging large amounts of DNA sequence.

RESULTS

We present a comprehensive SV catalog based on the whole-genome sequence of 1060 pigs (Sus scrofa) representing 101 breeds, covering 9.6% of the pig genome. This catalog includes 42,487 deletions, 37,913 mobile element insertions, 3308 duplications, 1664 inversions, and 45,184 break ends. Estimates of breed ancestry and hybridization using genotyped SVs align well with those from single nucleotide polymorphisms. Geographically stratified deletions are observed, along with known duplications of the KIT gene, responsible for white coat color in European pigs. Additionally, we identify a recent SINE element insertion in MYO5A transcripts of European pigs, potentially influencing alternative splicing patterns and coat color alterations. Furthermore, a Yorkshire-specific copy number gain within ABCG2 is found, impacting chromatin interactions and gene expression across multiple tissues over a stretch of genomic region of ~200 kb. Preliminary investigations into SV's impact on gene expression and traits using the Pig Genotype-Tissue Expression (PigGTEx) data reveal SV associations with regulatory variants and gene-trait pairs. For instance, a 51-bp deletion is linked to the lead eQTL of the lipid metabolism regulating gene FADS3, whose expression in embryo may affect loin muscle area, as revealed by our transcriptome-wide association studies.

CONCLUSIONS

This SV catalog serves as a valuable resource for studying diversity, evolutionary history, and functional shaping of the pig genome by processes like domestication, trait-based breeding, and adaptive evolution.

A comparative study of structural variant calling in WGS from Alzheimer's disease families

Detecting structural variants (SVs) in whole-genome sequencing poses significant challenges. We present a protocol for variant calling, merging, genotyping, sensitivity analysis, and laboratory validation for generating a high-quality SV call set in whole-genome sequencing from the Alzheimer's Disease Sequencing Project comprising 578 individuals from 111 families. Employing two complementary pipelines, Scalpel and Parliament, for SV/indel calling, we assessed sensitivity through sample replicates (N = 9) with in silico variant spike-ins. We developed a novel metric, D-score, to evaluate caller specificity for deletions. The accuracy of deletions was evaluated by Sanger sequencing. We generated a high-quality call set of 152,301 deletions of diverse sizes. Sanger sequencing validated 114 of 146 detected deletions (78.1%). Scalpel excelled in accuracy for deletions ≤100 bp, whereas Parliament was optimal for deletions >900 bp. Overall, 83.0% and 72.5% of calls by Scalpel and Parliament were validated, respectively, including all 11 deletions called by both Parliament and Scalpel between 101 and 900 bp. Our flexible protocol successfully generated a high-quality deletion call set and a truth set of Sanger sequencing-validated deletions with precise breakpoints spanning 1-17,000 bp.

CNVoyant: A Highly Performant and Explainable Multi-Classifier Machine Learning Approach for Determining the Clinical Significance of Copy Number Variants

The precise classification of copy number variants ( CNVs ) presents a significant challenge in genomic medicine, primarily due to the complex nature of CNVs and their diverse impact on genetic disorders. This complexity is compounded by the limitations of existing methods in accurately distinguishing between benign, uncertain, and pathogenic CNVs. Addressing this gap, we introduce CNVoyant, a machine learning-based multi-class framework designed to enhance the clinical significance classification of CNVs. Trained on a comprehensive dataset of 52,176 ClinVar entries across pathogenic, uncertain, and benign classifications, CNVoyant incorporates a broad spectrum of genomic features, including genome position, disease-gene annotations, dosage sensitivity, and conservation scores. Models to predict the clinical significance of copy number gains and losses were trained independently. Final models were selected after testing 29 machine learning architectures and 10,000 hyperparameter combinations each for deletions and duplications via 5-fold cross-validation. We validate the performance of the CNVoyant by leveraging a comprehensive set of 21,574 CNVs from the DECIPHER database, a highly regarded resource known for its extensive catalog of chromosomal imbalances linked to clinical outcomes. Compared to alternative approaches, CNVoyant shows marked improvements in precision-recall and ROC AUC metrics for binary pathogenic classifications while going one step further, offering multi-classification of clinical significance and corresponding SHAP explainability plots. This large-scale validation demonstrates CNVoyant's superior accuracy and underscores its potential to aid genomic researchers and clinical geneticists in interpreting the clinical implications of real CNVs.

Long-read sequencing and structural variant characterization in 1,019 samples from the 1000 Genomes Project

Structural variants (SVs) contribute significantly to human genetic diversity and disease 1-4 . Previously, SVs have remained incompletely resolved by population genomics, with short-read sequencing facing limitations in capturing the whole spectrum of SVs at nucleotide resolution 5-7 . Here we leveraged nanopore sequencing 8 to construct an intermediate coverage resource of 1,019 long-read genomes sampled within 26 human populations from the 1000 Genomes Project. By integrating linear and graph-based approaches for SV analysis via pangenome graph-augmentation, we uncover 167,291 sequence-resolved SVs in these samples, considerably advancing SV characterization compared to population-wide short-read sequencing studies 3,4 . Our analysis details diverse SV classes-deletions, duplications, insertions, and inversions-at population-scale. LINE-1 and SVA retrotransposition activities frequently mediate transductions 9,10 of unique sequences, with both mobile element classes transducing sequences at either the 3'- or 5'-end, depending on the source element locus. Furthermore, analyses of SV breakpoint junctions suggest a continuum of homology-mediated rearrangement processes are integral to SV formation, and highlight evidence for SV recurrence involving repeat sequences. Our open-access dataset underscores the transformative impact of long-read sequencing in advancing the characterisation of polymorphic genomic architectures, and provides a resource for guiding variant prioritisation in future long-read sequencing-based disease studies.

Adaptive functions of structural variants in human brain development

Quantifying the structural variants (SVs) in nonhuman primates could provide a niche to clarify the genetic backgrounds underlying human-specific traits, but such resource is largely lacking. Here, we report an accurate SV map in a population of 562 rhesus macaques, verified by in-house benchmarks of eight macaque genomes with long-read sequencing and another one with genome assembly. This map indicates stronger selective constrains on inversions at regulatory regions, suggesting a strategy for prioritizing them with the most important functions. Accordingly, we identified 75 human-specific inversions and prioritized them. The top-ranked inversions have substantially shaped the human transcriptome, through their dual effects of reconfiguring the ancestral genomic architecture and introducing regional mutation hotspots at the inverted regions. As a proof of concept, we linked APCDD1, located on one of these inversions and down-regulated specifically in humans, to neuronal maturation and cognitive ability. We thus highlight inversions in shaping the human uniqueness in brain development.

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.

Protein-altering variants at copy number-variable regions influence diverse human phenotypes

Copy number variants (CNVs) are among the largest genetic variants, yet CNVs have not been effectively ascertained in most genetic association studies. Here we ascertained protein-altering CNVs from UK Biobank whole-exome sequencing data (n = 468,570) using haplotype-informed methods capable of detecting subexonic CNVs and variation within segmental duplications. Incorporating CNVs into analyses of rare variants predicted to cause gene loss of function (LOF) identified 100 associations of predicted LOF variants with 41 quantitative traits. A low-frequency partial deletion of RGL3 exon 6 conferred one of the strongest protective effects of gene LOF on hypertension risk (odds ratio = 0.86 (0.82-0.90)). Protein-coding variation in rapidly evolving gene families within segmental duplications-previously invisible to most analysis methods-generated some of the human genome's largest contributions to variation in type 2 diabetes risk, chronotype and blood cell traits. These results illustrate the potential for new genetic insights from genomic variation that has escaped large-scale analysis to date.

Integration of transcriptomics and long-read genomics prioritizes structural variants in rare disease

Rare structural variants (SVs) - insertions, deletions, and complex rearrangements - can cause Mendelian disease, yet they remain difficult to accurately detect and interpret. We sequenced and analyzed Oxford Nanopore long-read genomes of 68 individuals from the Undiagnosed Disease Network (UDN) with no previously identified diagnostic mutations from short-read sequencing. Using our optimized SV detection pipelines and 571 control long-read genomes, we detected 716 long-read rare (MAF < 0.01) SV alleles per genome on average, achieving a 2.4x increase from short-reads. To characterize the functional effects of rare SVs, we assessed their relationship with gene expression from blood or fibroblasts from the same individuals, and found that rare SVs overlapping enhancers were enriched (LOR = 0.46) near expression outliers. We also evaluated tandem repeat expansions (TREs) and found 14 rare TREs per genome; notably these TREs were also enriched near overexpression outliers. To prioritize candidate functional SVs, we developed Watershed-SV, a probabilistic model that integrates expression data with SV-specific genomic annotations, which significantly outperforms baseline models that don't incorporate expression data. Watershed-SV identified a median of eight high-confidence functional SVs per UDN genome. Notably, this included compound heterozygous deletions in FAM177A1 shared by two siblings, which were likely causal for a rare neurodevelopmental disorder. Our observations demonstrate the promise of integrating long-read sequencing with gene expression towards improving the prioritization of functional SVs and TREs in rare disease patients.

Landscape of genomic structural variations in Indian population-based cohorts: Deeper insights into their prevalence and clinical relevance

Structural variations (SV) are large (>50 base pairs) genomic rearrangements comprising deletions, duplications, insertions, inversions, and translocations. Studying SVs is important because they play active and critical roles in regulating gene expression, determining disease predispositions, and identifying population-specific differences among individuals of diverse ancestries. However, SV discoveries in the Indian population using whole-genome sequencing (WGS) have been limited. In this study, using short-read WGS having an average 42X depth of coverage, we identify and characterize 36,210 SVs from 529 individuals enrolled in population-based cohorts in India. These SVs include 24,574 deletions, 2,913 duplications, 8,710 insertions, and 13 inversions; 1.26% (456 out of 36,210) of the identified SVs can potentially impact the coding regions of genes. Furthermore, 56 of these SVs are highly intolerant to loss-of-function changes to the mapped genes, and five SVs impacting ADAMTS17, CCDC40, and RHCE are common in our study individuals. Seven rare SVs significantly impact dosage sensitivity of genes known to be associated with various clinical phenotypes. Most of the SVs in our study are rare and heterozygous. This fine-scale SV discovery in the underrepresented Indian population provides valuable insights that extend beyond Eurocentric human genetic studies.

Integrating Optical Genome Mapping and Whole Genome Sequencing in Somatic Structural Variant Detection

Structural variants drive tumorigenesis by disrupting normal gene function through insertions, inversions, translocations, and copy number changes, including deletions and duplications. Detecting structural variants is crucial for revealing their roles in tumor development, clinical outcomes, and personalized therapy. Presently, most studies rely on short-read data from next-generation sequencing that aligns back to a reference genome to determine if and, if so, where a structural variant occurs. However, structural variant discovery by short-read sequencing is challenging, primarily because of the difficulty in mapping regions of repetitive sequences. Optical genome mapping (OGM) is a recent technology used for imaging and assembling long DNA strands to detect structural variations. To capture the structural variant landscape more thoroughly in the human genome, we developed an integrated pipeline that combines Bionano OGM and Illumina whole-genome sequencing and applied it to samples from 29 pediatric B-ALL patients. The addition of OGM allowed us to identify 511 deletions, 506 insertions, 93 duplications/gains, and 145 translocations that were otherwise missed in the short-read data. Moreover, we identified several novel gene fusions, the expression of which was confirmed by RNA sequencing. Our results highlight the benefit of integrating OGM and short-read detection methods to obtain a comprehensive analysis of genetic variation that can aid in clinical diagnosis, provide new therapeutic targets, and improve personalized medicine in cancers driven by structural variation.

Structural Variants and Speciation: Multiple Processes at Play

Research on the genomic architecture of speciation has increasingly revealed the importance of structural variants (SVs) that affect the presence, abundance, position, and/or direction of a nucleotide sequence. SVs include large chromosomal rearrangements such as fusion/fissions and inversions and translocations, as well as smaller variants such as duplications, insertions, and deletions (CNVs). Although we have ample evidence that SVs play a key role in speciation, the underlying mechanisms differ depending on the type and length of the SV, as well as the ecological, demographic, and historical context. We review predictions and empirical evidence for classic processes such as underdominance due to meiotic aberrations and the coupling effect of recombination suppression before exploring how recent sequencing methodologies illuminate the prevalence and diversity of SVs. We discuss specific properties of SVs and their impact throughout the genome, highlighting that multiple processes are at play, and possibly interacting, in the relationship between SVs and speciation.

Small polymorphisms are a source of ancestral bias in structural variant breakpoint placement

High-quality genome assemblies and sophisticated algorithms have increased sensitivity for a wide range of variant types, and breakpoint accuracy for structural variants (SVs, ≥50 bp) has improved to near base pair precision. Despite these advances, many SV breakpoint locations are subject to systematic bias affecting variant representation. To understand why SV breakpoints are inconsistent across samples, we reanalyzed 64 phased haplotypes constructed from long-read assemblies released by the Human Genome Structural Variation Consortium (HGSVC). We identify 882 SV insertions and 180 SV deletions with variable breakpoints not anchored in tandem repeats (TRs) or segmental duplications (SDs). SVs called from aligned sequencing reads increase breakpoint disagreements by 2×-16×. Sequence accuracy had a minimal impact on breakpoints, but we observe a strong effect of ancestry. We confirm that SNP and indel polymorphisms are enriched at shifted breakpoints and are also absent from variant callsets. Breakpoint homology increases the likelihood of imprecise SV calls and the distance they are shifted, and tandem duplications are the most heavily affected SVs. Because graph genome methods normalize SV calls across samples, we investigated graphs generated by two different methods and find the resulting breakpoints are subject to other technical biases affecting breakpoint accuracy. The breakpoint inconsistencies we characterize affect ∼5% of the SVs called in a human genome and can impact variant interpretation and annotation. These limitations underscore a need for algorithm development to improve SV databases, mitigate the impact of ancestry on breakpoints, and increase the value of callsets for investigating breakpoint features.

Whole genome sequencing enables new genetic diagnosis for inherited retinal diseases by identifying pathogenic variants

Inherited retinal diseases (IRDs) are a group of common primary retinal degenerative disorders. Conventional genetic testing strategies, such as panel-based sequencing and whole exome sequencing (WES), can only elucidate the genetic etiology in approximately 60% of IRD patients. Studies have suggested that unsolved IRD cases could be attributed to previously undetected structural variants (SVs) and intronic variants in IRD-related genes. The aim of our study was to obtain a definitive genetic diagnosis by employing whole genome sequencing (WGS) in IRD cases where the causative genes were inconclusive following an initial screening by panel sequencing. A total of 271 unresolved IRD patients and their available family members (n = 646) were screened using WGS to identify pathogenic SVs and intronic variants in 792 known ocular disease genes. Overall, 13% (34/271) of IRD patients received a confirmed genetic diagnosis, among which 7% were exclusively attributed to SVs, 4% to a combination of single nucleotide variants (SNVs) and SVs while another 2% were linked to intronic variants. 22 SVs, 3 deep-intronic variants, and 2 non-canonical splice-site variants across 14 IRD genes were identified in the entire cohort. Notably, all of these detected SVs and intronic variants were novel pathogenic variants. Among those, 74% (20/27) of variants were found in genes causally linked to Retinitis Pigmentosa (RP), with the gene EYS being the most frequently affected by SVs. The identification of SVs and intronic variants through WGS enhances the genetic diagnostic yield of IRDs and broadens the mutational spectrum of known IRD-associated genes.

Monitoring Genomic Structural Rearrangements Resulting from Gene Editing

The cytogenomics-based methodology of directional genomic hybridization (dGH) enables the detection and quantification of a more comprehensive spectrum of genomic structural variants than any other approach currently available, and importantly, does so on a single-cell basis. Thus, dGH is well-suited for testing and/or validating new advancements in CRISPR-Cas9 gene editing systems. In addition to aberrations detected by traditional cytogenetic approaches, the strand specificity of dGH facilitates detection of otherwise cryptic intra-chromosomal rearrangements, specifically small inversions. As such, dGH represents a powerful, high-resolution approach for the quantitative monitoring of potentially detrimental genomic structural rearrangements resulting from exposure to agents that induce DNA double-strand breaks (DSBs), including restriction endonucleases and ionizing radiations. For intentional genome editing strategies, it is critical that any undesired effects of DSBs induced either by the editing system itself or by mis-repair with other endogenous DSBs are recognized and minimized. In this paper, we discuss the application of dGH for assessing gene editing-associated structural variants and the potential heterogeneity of such rearrangements among cells within an edited population, highlighting its relevance to personalized medicine strategies.

Genome-wide association study between copy number variation and feeding behavior, feed efficiency, and growth traits in Nellore cattle

BACKGROUND

Feeding costs represent the largest expenditures in beef production. Therefore, the animal efficiency in converting feed in high-quality protein for human consumption plays a major role in the environmental impact of the beef industry and in the beef producers' profitability. In this context, breeding animals for improved feed efficiency through genomic selection has been considered as a strategic practice in modern breeding programs around the world. Copy number variation (CNV) is a less-studied source of genetic variation that can contribute to phenotypic variability in complex traits. In this context, this study aimed to: (1) identify CNV and CNV regions (CNVRs) in the genome of Nellore cattle (Bos taurus indicus); (2) assess potential associations between the identified CNVR and weaning weight (W210), body weight measured at the time of selection (WSel), average daily gain (ADG), dry matter intake (DMI), residual feed intake (RFI), time spent at the feed bunk (TF), and frequency of visits to the feed bunk (FF); and, (3) perform functional enrichment analyses of the significant CNVR identified for each of the traits evaluated.

RESULTS

A total of 3,161 CNVs and 561 CNVRs ranging from 4,973 bp to 3,215,394 bp were identified. The CNVRs covered up to 99,221,894 bp (3.99%) of the Nellore autosomal genome. Seventeen CNVR were significantly associated with dry matter intake and feeding frequency (number of daily visits to the feed bunk). The functional annotation of the associated CNVRs revealed important candidate genes related to metabolism that may be associated with the phenotypic expression of the evaluated traits. Furthermore, Gene Ontology (GO) analyses revealed 19 enrichment processes associated with FF.

CONCLUSIONS

A total of 3,161 CNVs and 561 CNVRs were identified and characterized in a Nellore cattle population. Various CNVRs were significantly associated with DMI and FF, indicating that CNVs play an important role in key biological pathways and in the phenotypic expression of feeding behavior and growth traits in Nellore cattle.

Rare copy-number variants as modulators of common disease susceptibility

BACKGROUND

Copy-number variations (CNVs) have been associated with rare and debilitating genomic disorders (GDs) but their impact on health later in life in the general population remains poorly described.

METHODS

Assessing four modes of CNV action, we performed genome-wide association scans (GWASs) between the copy-number of CNV-proxy probes and 60 curated ICD-10 based clinical diagnoses in 331,522 unrelated white British UK Biobank (UKBB) participants with replication in the Estonian Biobank.

RESULTS

We identified 73 signals involving 40 diseases, all of which indicating that CNVs increased disease risk and caused earlier onset. We estimated that 16% of these associations are indirect, acting by increasing body mass index (BMI). Signals mapped to 45 unique, non-overlapping regions, nine of which being linked to known GDs. Number and identity of genes affected by CNVs modulated their pathogenicity, with many associations being supported by colocalization with both common and rare single-nucleotide variant association signals. Dissection of association signals provided insights into the epidemiology of known gene-disease pairs (e.g., deletions in BRCA1 and LDLR increased risk for ovarian cancer and ischemic heart disease, respectively), clarified dosage mechanisms of action (e.g., both increased and decreased dosage of 17q12 impacted renal health), and identified putative causal genes (e.g., ABCC6 for kidney stones). Characterization of the pleiotropic pathological consequences of recurrent CNVs at 15q13, 16p13.11, 16p12.2, and 22q11.2 in adulthood indicated variable expressivity of these regions and the involvement of multiple genes. Finally, we show that while the total burden of rare CNVs-and especially deletions-strongly associated with disease risk, it only accounted for ~ 0.02% of the UKBB disease burden. These associations are mainly driven by CNVs at known GD CNV regions, whose pleiotropic effect on common diseases was broader than anticipated by our CNV-GWAS.

CONCLUSIONS

Our results shed light on the prominent role of rare CNVs in determining common disease susceptibility within the general population and provide actionable insights for anticipating later-onset comorbidities in carriers of recurrent CNVs.

Comprehensive and accurate genome analysis at scale using DRAGEN accelerated algorithms

Research and medical genomics require comprehensive and scalable solutions to drive the discovery of novel disease targets, evolutionary drivers, and genetic markers with clinical significance. This necessitates a framework to identify all types of variants independent of their size (e.g., SNV/SV) or location (e.g., repeats). Here we present DRAGEN that utilizes novel methods based on multigenomes, hardware acceleration, and machine learning based variant detection to provide novel insights into individual genomes with ~30min computation time (from raw reads to variant detection). DRAGEN outperforms all other state-of-the-art methods in speed and accuracy across all variant types (SNV, indel, STR, SV, CNV) and further incorporates specialized methods to obtain key insights in medically relevant genes (e.g., HLA, SMN, GBA). We showcase DRAGEN across 3,202 genomes and demonstrate its scalability, accuracy, and innovations to further advance the integration of comprehensive genomics for research and medical applications.

Mapping cis- and trans-regulatory target genes of human-specific deletions

Deletion of functional sequence is predicted to represent a fundamental mechanism of molecular evolution1,2. Comparative genetic studies of primates2,3 have identified thousands of human-specific deletions (hDels), and the cis-regulatory potential of short (≤31 base pairs) hDels has been assessed using reporter assays4. However, how structural variant-sized (≥50 base pairs) hDels influence molecular and cellular processes in their native genomic contexts remains unexplored. Here, we design genome-scale libraries of single-guide RNAs targeting 7.2 megabases of sequence in 6,358 hDels and present a systematic CRISPR interference (CRISPRi) screening approach to identify hDels that modify cellular proliferation in chimpanzee pluripotent stem cells. By intersecting hDels with chromatin state features and performing single-cell CRISPRi (Perturb-seq) to identify their cis- and trans-regulatory target genes, we discovered 19 hDels controlling gene expression. We highlight two hDels, hDel_2247 and hDel_585, with tissue-specific activity in the liver and brain, respectively. Our findings reveal a molecular and cellular role for sequences lost in the human lineage and establish a framework for functionally interrogating human-specific genetic variants.

Copy number variations and their effect on the plasma proteome

Structural variations, including copy number variations (CNVs), affect around 20 million bases in the human genome and are common causes of rare conditions. CNVs are rarely investigated in complex disease research because most CNVs are not targeted on the genotyping arrays or the reference panels for genetic imputation. In this study, we characterize CNVs in a Swedish cohort (N = 1,021) using short-read whole-genome sequencing (WGS) and use long-read WGS for validation in a subcohort (N = 15), and explore their effect on 438 plasma proteins. We detected 184,182 polymorphic CNVs and identified 15 CNVs to be associated with 16 proteins (P < 8.22×10-10). Of these, 5 CNVs could be perfectly validated using long-read sequencing, including a CNV which was associated with measurements of the osteoclast-associated immunoglobulin-like receptor (OSCAR) and located upstream of OSCAR, a gene important for bone health. Two other CNVs were identified to be clusters of many short repetitive elements and another represented a complex rearrangement including an inversion. Our findings provide insights into the structure of common CNVs and their effects on the plasma proteome, and highlights the importance of investigating common CNVs, also in relation to complex diseases.

Protein-coding potential of non-canonical open reading frames in human transcriptome

In recent years, proteogenomics and ribosome profiling studies have identified a large number of proteins encoded by noncoding regions in the human genome. They are encoded by small open reading frames (sORFs) in the untranslated regions (UTRs) of mRNAs and long non-coding RNAs (lncRNAs). These sORF encoded proteins (SEPs) are often <150AA and show poor evolutionary conservation. A subset of them have been functionally characterized and shown to play an important role in fundamental biological processes including cardiac and muscle function, DNA repair, embryonic development and various human diseases. How many novel protein-coding regions exist in the human genome and what fraction of them are functionally important remains a mystery. In this review, we discuss current progress in unraveling SEPs, approaches used for their identification, their limitations and reliability of these identifications. We also discuss functionally characterized SEPs and their involvement in various biological processes and diseases. Lastly, we provide insights into their distinctive features compared to canonical proteins and challenges associated with annotating these in protein reference databases.

Using Computational Simulations to Model Deleterious Variation and Genetic Load in Natural Populations

AbstractDeleterious genetic variation is abundant in wild populations, and understanding the ecological and conservation implications of such variation is an area of active research. Genomic methods are increasingly used to quantify the impacts of deleterious variation in natural populations; however, these approaches remain limited by an inability to accurately predict the selective and dominance effects of mutations. Computational simulations of deleterious variation offer a complementary tool that can help overcome these limitations, although such approaches have yet to be widely employed. In this perspective article, we aim to encourage ecological and conservation genomics researchers to adopt greater use of computational simulations to aid in deepening our understanding of deleterious variation in natural populations. We first provide an overview of the components of a simulation of deleterious variation, describing the key parameters involved in such models. Next, we discuss several approaches for validating simulation models. Finally, we compare and validate several recently proposed deleterious mutation models, demonstrating that models based on estimates of selection parameters from experimental systems are biased toward highly deleterious mutations. We describe a new model that is supported by multiple orthogonal lines of evidence and provide example scripts for implementing this model (https://github.com/ckyriazis/simulations_review).

Multiomics tools for improved atherosclerotic cardiovascular disease management

Multiomics studies offer accurate preventive and therapeutic strategies for atherosclerotic cardiovascular disease (ASCVD) beyond traditional risk factors. By using artificial intelligence (AI) and machine learning (ML) approaches, it is possible to integrate multiple 'omics and clinical data sets into tools that can be utilized for the development of personalized diagnostic and therapeutic approaches. However, currently multiple challenges in data quality, integration, and privacy still need to be addressed. In this opinion, we emphasize that joined efforts, exemplified by the AtheroNET COST Action, have a pivotal role in overcoming the challenges to advance multiomics approaches in ASCVD research, with the aim to foster more precise and effective patient care.

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.

Structural variants and short tandem repeats impact gene expression and splicing in bovine testis tissue

Structural variants (SVs) and short tandem repeats (STRs) are significant sources of genetic variation. However, the impacts of these variants on gene regulation have not been investigated in cattle. Here, we genotyped and characterized 19,408 SVs and 374,821 STRs in 183 bovine genomes and investigated their impact on molecular phenotypes derived from testis transcriptomes. We found that 71% STRs were multiallelic. The vast majority (95%) of STRs and SVs were in intergenic and intronic regions. Only 37% SVs and 40% STRs were in high linkage disequilibrium (LD) (R2 > 0.8) with surrounding SNPs/insertions and deletions (Indels), indicating that SNP-based association testing and genomic prediction are blind to a nonnegligible portion of genetic variation. We showed that both SVs and STRs were more than 2-fold enriched among expression and splicing QTL (e/sQTL) relative to SNPs/Indels and were often associated with differential expression and splicing of multiple genes. Deletions and duplications had larger impacts on splicing and expression than any other type of SV. Exonic duplications predominantly increased gene expression either through alternative splicing or other mechanisms, whereas expression- and splicing-associated STRs primarily resided in intronic regions and exhibited bimodal effects on the molecular phenotypes investigated. Most e/sQTL resided within 100 kb of the affected genes or splicing junctions. We pinpoint candidate causal STRs and SVs associated with the expression of SLC13A4 and TTC7B and alternative splicing of a lncRNA and CAPP1. We provide a catalog of STRs and SVs for taurine cattle and show that these variants contribute substantially to gene expression and splicing variation.

Structural Variation Evolution at the 15q11-q13 Disease-Associated Locus

The impact of segmental duplications on human evolution and disease is only just starting to unfold, thanks to advancements in sequencing technologies that allow for their discovery and precise genotyping. The 15q11-q13 locus is a hotspot of recurrent copy number variation associated with Prader-Willi/Angelman syndromes, developmental delay, autism, and epilepsy and is mediated by complex segmental duplications, many of which arose recently during evolution. To gain insight into the instability of this region, we characterized its architecture in human and nonhuman primates, reconstructing the evolutionary history of five different inversions that rearranged the region in different species primarily by accumulation of segmental duplications. Comparative analysis of human and nonhuman primate duplication structures suggests a human-specific gain of directly oriented duplications in the regions flanking the GOLGA cores and HERC segmental duplications, representing potential genomic drivers for the human-specific expansions. The increasing complexity of segmental duplication organization over the course of evolution underlies its association with human susceptibility to recurrent disease-associated rearrangements.

Large-scale causal discovery using interventional data sheds light on the regulatory network architecture of blood traits

Inference of directed biological networks is an important but notoriously challenging problem. We introduce inverse sparse regression (inspre), an approach to learning causal networks that leverages large-scale intervention-response data. Applied to 788 genes from the genome-wide perturb-seq dataset, inspre helps elucidate the network architecture of blood traits.

Genomic architecture of autism spectrum disorder in Qatar: The BARAKA-Qatar Study

BACKGROUND

Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by impaired social and communication skills, restricted interests, and repetitive behaviors. The prevalence of ASD among children in Qatar was recently estimated to be 1.1%, though the genetic architecture underlying ASD both in Qatar and the greater Middle East has been largely unexplored. Here, we describe the first genomic data release from the BARAKA-Qatar Study-a nationwide program building a broadly consented biorepository of individuals with ASD and their families available for sample and data sharing and multi-omics research.

METHODS

In this first release, we present a comprehensive analysis of whole-genome sequencing (WGS) data of the first 100 families (372 individuals), investigating the genetic architecture, including single-nucleotide variants (SNVs), copy number variants (CNVs), tandem repeat expansions (TREs), as well as mitochondrial DNA variants (mtDNA) segregating with ASD in local families.

RESULTS

Overall, we identify potentially pathogenic variants in known genes or regions in 27 out of 100 families (27%), of which 11 variants (40.7%) were classified as pathogenic or likely-pathogenic based on American College of Medical Genetics (ACMG) guidelines. Dominant variants, including de novo and inherited, contributed to 15 (55.6%) of these families, consisting of SNVs/indels (66.7%), CNVs (13.3%), TREs (13.3%), and mtDNA variants (6.7%). Moreover, homozygous variants were found in 7 families (25.9%), with a sixfold increase in homozygous burden in consanguineous versus non-consanguineous families (13.6% and 1.8%, respectively). Furthermore, 28 novel ASD candidate genes were identified in 20 families, 23 of which had recurrent hits in MSSNG and SSC cohorts.

CONCLUSIONS

This study illustrates the value of ASD studies in under-represented populations and the importance of WGS as a comprehensive tool for establishing a molecular diagnosis for families with ASD. Moreover, it uncovers a significant role for recessive variation in ASD architecture in consanguineous settings and provides a unique resource of Middle Eastern genomes for future research to the global ASD community.

The rate of de novo structural variation is increased in in vitro-produced offspring and preferentially affects the paternal genome

Assisted reproductive technologies (ARTs), including in vitro maturation and fertilization (IVF), are increasingly used in human and animal reproduction. Whether these technologies directly affect the rate of de novo mutation (DNM), and to what extent, has been a matter of debate. Here we take advantage of domestic cattle, characterized by complex pedigrees that are ideally suited to detect DNMs and by the systematic use of ART, to study the rate of de novo structural variation (dnSV) in this species and how it is impacted by IVF. By exploiting features of associated de novo point mutations (dnPMs) and dnSVs in clustered DNMs, we provide strong evidence that (1) IVF increases the rate of dnSV approximately fivefold, and (2) the corresponding mutations occur during the very early stages of embryonic development (one- and two-cell stage), yet primarily affect the paternal genome.

Pan-conserved segment tags identify ultra-conserved sequences across assemblies in the human pangenome

The human pangenome, a new reference sequence, addresses many limitations of the current GRCh38 reference. The first release is based on 94 high-quality haploid assemblies from individuals with diverse backgrounds. We employed a k-mer indexing strategy for comparative analysis across multiple assemblies, including the pangenome reference, GRCh38, and CHM13, a telomere-to-telomere reference assembly. Our k-mer indexing approach enabled us to identify a valuable collection of universally conserved sequences across all assemblies, referred to as "pan-conserved segment tags" (PSTs). By examining intervals between these segments, we discerned highly conserved genomic segments and those with structurally related polymorphisms. We found 60,764 polymorphic intervals with unique geo-ethnic features in the pangenome reference. In this study, we utilized ultra-conserved sequences (PSTs) to forge a link between human pangenome assemblies and reference genomes. This methodology enables the examination of any sequence of interest within the pangenome, using the reference genome as a comparative framework.

Structural Variations Contribute to the Genetic Etiology of Autism Spectrum Disorder and Language Impairments

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by restrictive interests and/or repetitive behaviors and deficits in social interaction and communication. ASD is a multifactorial disease with a complex polygenic genetic architecture. Its genetic contributing factors are not yet fully understood, especially large structural variations (SVs). In this study, we aimed to assess the contribution of SVs, including copy number variants (CNVs), insertions, deletions, duplications, and mobile element insertions, to ASD and related language impairments in the New Jersey Language and Autism Genetics Study (NJLAGS) cohort. Within the cohort, ~77% of the families contain SVs that followed expected segregation or de novo patterns and passed our filtering criteria. These SVs affected 344 brain-expressed genes and can potentially contribute to the genetic etiology of the disorders. Gene Ontology and protein-protein interaction network analysis suggested several clusters of genes in different functional categories, such as neuronal development and histone modification machinery. Genes and biological processes identified in this study contribute to the understanding of ASD and related neurodevelopment disorders.

WHOLE GENOME SEQUENCING ANALYSIS OF BODY MASS INDEX IDENTIFIES NOVEL AFRICAN ANCESTRY-SPECIFIC RISK ALLELE

Obesity is a major public health crisis associated with high mortality rates. Previous genome-wide association studies (GWAS) investigating body mass index (BMI) have largely relied on imputed data from European individuals. This study leveraged whole-genome sequencing (WGS) data from 88,873 participants from the Trans-Omics for Precision Medicine (TOPMed) Program, of which 51% were of non-European population groups. We discovered 18 BMI-associated signals (P < 5 × 10-9). Notably, we identified and replicated a novel low frequency single nucleotide polymorphism (SNP) in MTMR3 that was common in individuals of African descent. Using a diverse study population, we further identified two novel secondary signals in known BMI loci and pinpointed two likely causal variants in the POC5 and DMD loci. Our work demonstrates the benefits of combining WGS and diverse cohorts in expanding current catalog of variants and genes confer risk for obesity, bringing us one step closer to personalized medicine.

Comparative Genomic Analysis Identifies Great-Ape-Specific Structural Variants and Their Evolutionary Relevance

During the origin of great apes about 14 million years ago, a series of phenotypic innovations emerged, such as the increased body size, the enlarged brain volume, the improved cognitive skill, and the diversified diet. Yet, the genomic basis of these evolutionary changes remains unclear. Utilizing the high-quality genome assemblies of great apes (including human), gibbon, and macaque, we conducted comparative genome analyses and identified 15,885 great ape-specific structural variants (GSSVs), including eight coding GSSVs resulting in the creation of novel proteins (e.g., ACAN and CMYA5). Functional annotations of the GSSV-related genes revealed the enrichment of genes involved in development and morphogenesis, especially neurogenesis and neural network formation, suggesting the potential role of GSSVs in shaping the great ape-shared traits. Further dissection of the brain-related GSSVs shows great ape-specific changes of enhancer activities and gene expression in the brain, involving a group of GSSV-regulated genes (such as NOL3) that potentially contribute to the altered brain development and function in great apes. The presented data highlight the evolutionary role of structural variants in the phenotypic innovations during the origin of the great ape lineage.

Genome-wide identification and phenotypic characterization of seizure-associated copy number variations in 741,075 individuals

Copy number variants (CNV) are established risk factors for neurodevelopmental disorders with seizures or epilepsy. With the hypothesis that seizure disorders share genetic risk factors, we pooled CNV data from 10,590 individuals with seizure disorders, 16,109 individuals with clinically validated epilepsy, and 492,324 population controls and identified 25 genome-wide significant loci, 22 of which are novel for seizure disorders, such as deletions at 1p36.33, 1q44, 2p21-p16.3, 3q29, 8p23.3-p23.2, 9p24.3, 10q26.3, 15q11.2, 15q12-q13.1, 16p12.2, 17q21.31, duplications at 2q13, 9q34.3, 16p13.3, 17q12, 19p13.3, 20q13.33, and reciprocal CNVs at 16p11.2, and 22q11.21. Using genetic data from additional 248,751 individuals with 23 neuropsychiatric phenotypes, we explored the pleiotropy of these 25 loci. Finally, in a subset of individuals with epilepsy and detailed clinical data available, we performed phenome-wide association analyses between individual CNVs and clinical annotations categorized through the Human Phenotype Ontology (HPO). For six CNVs, we identified 19 significant associations with specific HPO terms and generated, for all CNVs, phenotype signatures across 17 clinical categories relevant for epileptologists. This is the most comprehensive investigation of CNVs in epilepsy and related seizure disorders, with potential implications for clinical practice.

Small allelic variants are a source of ancestral bias in structural variant breakpoint placement

High-quality genome assemblies and sophisticated algorithms have increased sensitivity for a wide range of variant types, and breakpoint accuracy for structural variants (SVs, ≥ 50 bp) has improved to near basepair precision. Despite these advances, many SVs in unique regions of the genome are subject to systematic bias that affects breakpoint location. This ambiguity leads to less accurate variant comparisons across samples, and it obscures true breakpoint features needed for mechanistic inferences. To understand why SVs are not consistently placed, we reanalyzed 64 phased haplotypes constructed from long-read assemblies released by the Human Genome Structural Variation Consortium (HGSVC). We identified variable breakpoints for 882 SV insertions and 180 SV deletions not anchored in tandem repeats (TRs) or segmental duplications (SDs). While this is unexpectedly high for genome assemblies in unique loci, we find read-based callsets from the same sequencing data yielded 1,566 insertions and 986 deletions with inconsistent breakpoints also not anchored in TRs or SDs. When we investigated causes for breakpoint inaccuracy, we found sequence and assembly errors had minimal impact, but we observed a strong effect of ancestry. We confirmed that polymorphic mismatches and small indels are enriched at shifted breakpoints and that these polymorphisms are generally lost when breakpoints shift. Long tracts of homology, such as SVs mediated by transposable elements, increase the likelihood of imprecise SV calls and the distance they are shifted. Tandem Duplication (TD) breakpoints are the most heavily affected SV class with 14% of TDs placed at different locations across haplotypes. While graph genome methods normalize SV calls across many samples, the resulting breakpoints are sometimes incorrect, highlighting a need to tune graph methods for breakpoint accuracy. The breakpoint inconsistencies we characterize collectively affect ~5% of the SVs called in a human genome and underscore a need for algorithm development to improve SV databases, mitigate the impact of ancestry on breakpoint placement, and increase the value of callsets for investigating mutational processes.

Detection of trait-associated structural variations using short-read sequencing

Genomic structural variation (SV) affects genetic and phenotypic characteristics in diverse organisms, but the lack of reliable methods to detect SV has hindered genetic analysis. We developed a computational algorithm (MOPline) that includes missing call recovery combined with high-confidence SV call selection and genotyping using short-read whole-genome sequencing (WGS) data. Using 3,672 high-coverage WGS datasets, MOPline stably detected ∼16,000 SVs per individual, which is over ∼1.7-3.3-fold higher than previous large-scale projects while exhibiting a comparable level of statistical quality metrics. We imputed SVs from 181,622 Japanese individuals for 42 diseases and 60 quantitative traits. A genome-wide association study with the imputed SVs revealed 41 top-ranked or nearly top-ranked genome-wide significant SVs, including 8 exonic SVs with 5 novel associations and enriched mobile element insertions. This study demonstrates that short-read WGS data can be used to identify rare and common SVs associated with a variety of traits.

Genome-wide structural variant analysis identifies risk loci for non-Alzheimer's dementias

We characterized the role of structural variants, a largely unexplored type of genetic variation, in two non-Alzheimer's dementias, namely Lewy body dementia (LBD) and frontotemporal dementia (FTD)/amyotrophic lateral sclerosis (ALS). To do this, we applied an advanced structural variant calling pipeline (GATK-SV) to short-read whole-genome sequence data from 5,213 European-ancestry cases and 4,132 controls. We discovered, replicated, and validated a deletion in TPCN1 as a novel risk locus for LBD and detected the known structural variants at the C9orf72 and MAPT loci as associated with FTD/ALS. We also identified rare pathogenic structural variants in both LBD and FTD/ALS. Finally, we assembled a catalog of structural variants that can be mined for new insights into the pathogenesis of these understudied forms of dementia.

Hidden protein-altering variants influence diverse human phenotypes

Structural variants (SVs) comprise the largest genetic variants, altering from 50 base pairs to megabases of DNA. However, SVs have not been effectively ascertained in most genetic association studies, leaving a key gap in our understanding of human complex trait genetics. We ascertained protein-altering SVs from UK Biobank whole-exome sequencing data (n=468,570) using haplotype-informed methods capable of detecting sub-exonic SVs and variation within segmental duplications. Incorporating SVs into analyses of rare variants predicted to cause gene loss-of-function (pLoF) identified 100 associations of pLoF variants with 41 quantitative traits. A low-frequency partial deletion of RGL3 exon 6 appeared to confer one of the strongest protective effects of gene LoF on hypertension risk (OR = 0.86 [0.82-0.90]). Protein-coding variation in rapidly-evolving gene families within segmental duplications-previously invisible to most analysis methods-appeared to generate some of the human genome's largest contributions to variation in type 2 diabetes risk, chronotype, and blood cell traits. These results illustrate the potential for new genetic insights from genomic variation that has escaped large-scale analysis to date.

INSurVeyor: improving insertion calling from short read sequencing data

Insertions are one of the major types of structural variations and are defined as the addition of 50 nucleotides or more into a DNA sequence. Several methods exist to detect insertions from next-generation sequencing short read data, but they generally have low sensitivity. Our contribution is two-fold. First, we introduce INSurVeyor, a fast, sensitive and precise method that detects insertions from next-generation sequencing paired-end data. Using publicly available benchmark datasets (both human and non-human), we show that INSurVeyor is not only more sensitive than any individual caller we tested, but also more sensitive than all of them combined. Furthermore, for most types of insertions, INSurVeyor is almost as sensitive as long reads callers. Second, we provide state-of-the-art catalogues of insertions for 1047 Arabidopsis Thaliana genomes from the 1001 Genomes Project and 3202 human genomes from the 1000 Genomes Project, both generated with INSurVeyor. We show that they are more complete and precise than existing resources, and important insertions are missed by existing methods.

Targeted in silico characterization of fusion transcripts in tumor and normal tissues via FusionInspector

Here, we present FusionInspector for in silico characterization and interpretation of candidate fusion transcripts from RNA sequencing (RNA-seq) and exploration of their sequence and expression characteristics. We applied FusionInspector to thousands of tumor and normal transcriptomes and identified statistical and experimental features enriched among biologically impactful fusions. Through clustering and machine learning, we identified large collections of fusions potentially relevant to tumor and normal biological processes. We show that biologically relevant fusions are enriched for relatively high expression of the fusion transcript, imbalanced fusion allelic ratios, and canonical splicing patterns, and are deficient in sequence microhomologies between partner genes. We demonstrate that FusionInspector accurately validates fusion transcripts in silico and helps characterize numerous understudied fusions in tumor and normal tissue samples. FusionInspector is freely available as open source for screening, characterization, and visualization of candidate fusions via RNA-seq, and facilitates transparent explanation and interpretation of machine-learning predictions and their experimental sources.

Mobile element variation contributes to population-specific genome diversification, gene regulation and disease risk

Mobile genetic elements (MEs) are heritable mutagens that recursively generate structural variants (SVs). ME variants (MEVs) are difficult to genotype and integrate in statistical genetics, obscuring their impact on genome diversification and traits. We developed a tool that accurately genotypes MEVs using short-read whole-genome sequencing (WGS) and applied it to global human populations. We find unexpected population-specific MEV differences, including an Alu insertion distribution distinguishing Japanese from other populations. Integrating MEVs with expression quantitative trait loci (eQTL) maps shows that MEV classes regulate tissue-specific gene expression by shared mechanisms, including creating or attenuating enhancers and recruiting post-transcriptional regulators, supporting class-wide interpretability. MEVs more often associate with gene expression changes than SNVs, thus plausibly impacting traits. Performing genome-wide association study (GWAS) with MEVs pinpoints potential causes of disease risk, including a LINE-1 insertion associated with keloid and fasciitis. This work implicates MEVs as drivers of human divergence and disease risk.

A review of the pangenome: how it affects our understanding of genomic variation, selection and breeding in domestic animals?

As large-scale genomic studies have progressed, it has been revealed that a single reference genome pattern cannot represent genetic diversity at the species level. While domestic animals tend to have complex routes of origin and migration, suggesting a possible omission of some population-specific sequences in the current reference genome. Conversely, the pangenome is a collection of all DNA sequences of a species that contains sequences shared by all individuals (core genome) and is also able to display sequence information unique to each individual (variable genome). The progress of pangenome research in humans, plants and domestic animals has proved that the missing genetic components and the identification of large structural variants (SVs) can be explored through pangenomic studies. Many individual specific sequences have been shown to be related to biological adaptability, phenotype and important economic traits. The maturity of technologies and methods such as third-generation sequencing, Telomere-to-telomere genomes, graphic genomes, and reference-free assembly will further promote the development of pangenome. In the future, pangenome combined with long-read data and multi-omics will help to resolve large SVs and their relationship with the main economic traits of interest in domesticated animals, providing better insights into animal domestication, evolution and breeding. In this review, we mainly discuss how pangenome analysis reveals genetic variations in domestic animals (sheep, cattle, pigs, chickens) and their impacts on phenotypes and how this can contribute to the understanding of species diversity. Additionally, we also go through potential issues and the future perspectives of pangenome research in livestock and poultry.

High-resolution structural variants catalogue in a large-scale whole genome sequenced bovine family cohort data

BACKGROUND

Structural variants (SVs) are chromosomal segments that differ between genomes, such as deletions, duplications, insertions, inversions and translocations. The genomics revolution enabled the discovery of sub-microscopic SVs via array and whole-genome sequencing (WGS) data, paving the way to unravel the functional impact of SVs. Recent human expression QTL mapping studies demonstrated that SVs play a disproportionally large role in altering gene expression, underlining the importance of including SVs in genetic analyses. Therefore, this study aimed to generate and explore a high-quality bovine SV catalogue exploiting a unique cattle family cohort data (total 266 samples, forming 127 trios).

RESULTS

We curated 13,731 SVs segregating in the population, consisting of 12,201 deletions, 1,509 duplications, and 21 multi-allelic CNVs (> 50-bp). Of these, we validated a subset of copy number variants (CNVs) utilising a direct genotyping approach in an independent cohort, indicating that at least 62% of the CNVs are true variants, segregating in the population. Among gene-disrupting SVs, we prioritised two likely high impact duplications, encompassing ORM1 and POPDC3 genes, respectively. Liver expression QTL mapping results revealed that these duplications are likely causing altered gene expression, confirming the functional importance of SVs. Although most of the accurately genotyped CNVs are tagged by single nucleotide polymorphisms (SNPs) ascertained in WGS data, most CNVs were not captured by individual SNPs obtained from a 50K genotyping array.

CONCLUSION

We generated a high-quality SV catalogue exploiting unique whole genome sequenced bovine family cohort data. Two high impact duplications upregulating the ORM1 and POPDC3 are putative candidates for postpartum feed intake and hoof health traits, thus warranting further investigation. Generally, CNVs were in low LD with SNPs on the 50K array. Hence, it remains crucial to incorporate CNVs via means other than tagging SNPs, such as investigation of tagging haplotypes, direct imputation of CNVs, or direct genotyping as done in the current study. The SV catalogue and the custom genotyping array generated in the current study will serve as valuable resources accelerating utilisation of full spectrum of genetic variants in bovine genomes.

A draft human pangenome reference

Here the Human Pangenome Reference Consortium presents a first draft of the human pangenome reference. The pangenome contains 47 phased, diploid assemblies from a cohort of genetically diverse individuals1. These assemblies cover more than 99% of the expected sequence in each genome and are more than 99% accurate at the structural and base pair levels. Based on alignments of the assemblies, we generate a draft pangenome that captures known variants and haplotypes and reveals new alleles at structurally complex loci. We also add 119 million base pairs of euchromatic polymorphic sequences and 1,115 gene duplications relative to the existing reference GRCh38. Roughly 90 million of the additional base pairs are derived from structural variation. Using our draft pangenome to analyse short-read data reduced small variant discovery errors by 34% and increased the number of structural variants detected per haplotype by 104% compared with GRCh38-based workflows, which enabled the typing of the vast majority of structural variant alleles per sample.

Chromosomal Instability in Genome Evolution: From Cancer to Macroevolution

The integrity of the genome is crucial for the survival of all living organisms. However, genomes need to adapt to survive certain pressures, and for this purpose use several mechanisms to diversify. Chromosomal instability (CIN) is one of the main mechanisms leading to the creation of genomic heterogeneity by altering the number of chromosomes and changing their structures. In this review, we will discuss the different chromosomal patterns and changes observed in speciation, in evolutional biology as well as during tumor progression. By nature, the human genome shows an induction of diversity during gametogenesis but as well during tumorigenesis that can conclude in drastic changes such as the whole genome doubling to more discrete changes as the complex chromosomal rearrangement chromothripsis. More importantly, changes observed during speciation are strikingly similar to the genomic evolution observed during tumor progression and resistance to therapy. The different origins of CIN will be treated as the importance of double-strand breaks (DSBs) or the consequences of micronuclei. We will also explain the mechanisms behind the controlled DSBs, and recombination of homologous chromosomes observed during meiosis, to explain how errors lead to similar patterns observed during tumorigenesis. Then, we will also list several diseases associated with CIN, resulting in fertility issues, miscarriage, rare genetic diseases, and cancer. Understanding better chromosomal instability as a whole is primordial for the understanding of mechanisms leading to tumor progression.

Identification and characterisation of de novo germline structural variants in two commercial pig lines using trio-based whole genome sequencing

BACKGROUND

De novo mutations arising in the germline are a source of genetic variation and their discovery broadens our understanding of genetic disorders and evolutionary patterns. Although the number of de novo single nucleotide variants (dnSNVs) has been studied in a number of species, relatively little is known about the occurrence of de novo structural variants (dnSVs). In this study, we investigated 37 deeply sequenced pig trios from two commercial lines to identify dnSVs present in the offspring. The identified dnSVs were characterised by identifying their parent of origin, their functional annotations and characterizing sequence homology at the breakpoints.

RESULTS

We identified four swine germline dnSVs, all located in intronic regions of protein-coding genes. Our conservative, first estimate of the swine germline dnSV rate is 0.108 (95% CI 0.038-0.255) per generation (one dnSV per nine offspring), detected using short-read sequencing. Two detected dnSVs are clusters of mutations. Mutation cluster 1 contains a de novo duplication, a dnSNV and a de novo deletion. Mutation cluster 2 contains a de novo deletion and three de novo duplications, of which one is inverted. Mutation cluster 2 is 25 kb in size, whereas mutation cluster 1 (197 bp) and the other two individual dnSVs (64 and 573 bp) are smaller. Only mutation cluster 2 could be phased and is located on the paternal haplotype. Mutation cluster 2 originates from both micro-homology as well as non-homology mutation mechanisms, where mutation cluster 1 and the other two dnSVs are caused by mutation mechanisms lacking sequence homology. The 64 bp deletion and mutation cluster 1 were validated through PCR. Lastly, the 64 bp deletion and the 573 bp duplication were validated in sequenced offspring of probands with three generations of sequence data.

CONCLUSIONS

Our estimate of 0.108 dnSVs per generation in the swine germline is conservative, due to our small sample size and restricted possibilities of dnSV detection from short-read sequencing. The current study highlights the complexity of dnSVs and shows the potential of breeding programs for pigs and livestock species in general, to provide a suitable population structure for identification and characterisation of dnSVs.

Genetic architecture of human brain evolution

Comparative studies of hominids have long sought to identify mutational events that shaped the evolution of the human nervous system. However, functional genetic differences are outnumbered by millions of nearly neutral mutations, and the developmental mechanisms underlying human nervous system specializations are difficult to model and incompletely understood. Candidate-gene studies have attempted to map select human-specific genetic differences to neurodevelopmental functions, but it remains unclear how to contextualize the relative effects of genes that are investigated independently. Considering these limitations, we discuss scalable approaches for probing the functional contributions of human-specific genetic differences. We propose that a systems-level view will enable a more quantitative and integrative understanding of the genetic, molecular and cellular underpinnings of human nervous system evolution.

Analysis of structural variation among inbred mouse strains

BACKGROUND

'Long read' sequencing methods have been used to identify previously uncharacterized structural variants that cause human genetic diseases. Therefore, we investigated whether long read sequencing could facilitate genetic analysis of murine models for human diseases.

RESULTS

The genomes of six inbred strains (BTBR T + Itpr3tf/J, 129Sv1/J, C57BL/6/J, Balb/c/J, A/J, SJL/J) were analyzed using long read sequencing. Our results revealed that (i) Structural variants are very abundant within the genome of inbred strains (4.8 per gene) and (ii) that we cannot accurately infer whether structural variants are present using conventional short read genomic sequence data, even when nearby SNP alleles are known. The advantage of having a more complete map was demonstrated by analyzing the genomic sequence of BTBR mice. Based upon this analysis, knockin mice were generated and used to characterize a BTBR-unique 8-bp deletion within Draxin that contributes to the BTBR neuroanatomic abnormalities, which resemble human autism spectrum disorder.

CONCLUSION

A more complete map of the pattern of genetic variation among inbred strains, which is produced by long read genomic sequencing of the genomes of additional inbred strains, could facilitate genetic discovery when murine models of human diseases are analyzed.

Genome assembly, structural variants, and genetic differentiation between lake whitefish young species pairs (Coregonus sp.) with long and short reads

Nascent pairs of ecologically differentiated species offer an opportunity to get a better glimpse at the genetic architecture of speciation. Of particular interest is our recent ability to consider a wider range of genomic variants, not only single-nucleotide polymorphisms (SNPs), thanks to long-read sequencing technology. We can now identify structural variants (SVs) such as insertions, deletions and other rearrangements, allowing further insights into the genetic architecture of speciation and how different types of variants are involved in species differentiation. Here, we investigated genomic patterns of differentiation between sympatric species pairs (Dwarf and Normal) belonging to the lake whitefish (Coregonus clupeaformis) species complex. We assembled the first reference genomes for both C. clupeaformis sp. Normal and C. clupeaformis sp. Dwarf, annotated the transposable elements and analysed the genomes in the light of related coregonid species. Next, we used a combination of long- and short-read sequencing to characterize SVs and genotype them at the population scale using genome-graph approaches, showing that SVs cover five times more of the genome than SNPs. We then integrated both SNPs and SVs to investigate the genetic architecture of species differentiation in two different lakes and highlighted an excess of shared outliers of differentiation. In particular, a large fraction of SVs differentiating the two species correspond to insertions or deletions of transposable elements (TEs), suggesting that TE accumulation may represent a key component of genetic divergence between the Dwarf and Normal species. Together, our results suggest that SVs may play an important role in speciation and that, by combining second- and third-generation sequencing, we now have the ability to integrate SVs into speciation genomics.