Large multiallelic copy number variations in humans

VolcanoSV enables accurate and robust structural variant calling in diploid genomes from single-molecule long read sequencing

Structural variants (SVs) significantly contribute to human genome diversity and play a crucial role in precision medicine. Although advancements in single-molecule long-read sequencing offer a groundbreaking resource for SV detection, identifying SV breakpoints and sequences accurately and robustly remains challenging. We introduce VolcanoSV, an innovative hybrid SV detection pipeline that utilizes both a reference genome and local de novo assembly to generate a phased diploid assembly. VolcanoSV uses phased SNPs and unique k-mer similarity analysis, enabling precise haplotype-resolved SV discovery. VolcanoSV is adept at constructing comprehensive genetic maps encompassing SNPs, small indels, and all types of SVs, making it well-suited for human genomics studies. Our extensive experiments demonstrate that VolcanoSV surpasses state-of-the-art assembly-based tools in the detection of insertion and deletion SVs, exhibiting superior recall, precision, F1 scores, and genotype accuracy across a diverse range of datasets, including low-coverage (10x) datasets. VolcanoSV outperforms assembly-based tools in the identification of complex SVs, including translocations, duplications, and inversions, in both simulated and real cancer data. Moreover, VolcanoSV is robust to various evaluation parameters and accurately identifies breakpoints and SV sequences.

Differentiation in detoxification gene complements, including neofunctionalization of duplicated cytochrome P450 genes, between lineages of cotton bollworm, Helicoverpa armigera

Here we investigate the evolutionary dynamics of five enzyme superfamilies (CYPs, GSTs, UGTs, CCEs and ABCs) involved in detoxification in Helicoverpa armigera. The reference assembly for an African isolate of the major lineages, H. a. armigera, has 373 genes in the five superfamilies. Most of its CYPs, GSTs, UGTs and CCEs and a few of its ABCs occur in blocks and most of the clustered genes are in subfamilies specifically implicated in detoxification. Most of the genes have orthologues in the reference genome for the Oceania lineage, H. a. conferta. However, clustered orthologues and subfamilies specifically implicated in detoxification show greater sequence divergence and less constraint on non-synonymous differences between the two assemblies than do other members of the five superfamilies. Two duplicated CYPs, which were found in the H. a. armigera but not H. a. conferta reference genome, were also missing in 16 Chinese populations spanning two different lineages of H. a. armigera. The enzyme produced by one of these duplicates has higher activity against esfenvalerate than a previously described chimeric CYP mutant conferring pyrethroid resistance. Various transposable elements were found in the introns of most detoxification genes, generating diverse gene structures. Extensive resequencing data for the Chinese H. a. armigera and H. a. conferta lineages also revealed complex copy number polymorphisms in 17 CCE001s in a cluster also implicated in pyrethroid metabolism, with substantial haplotype differences between all three lineages. Our results suggest that cotton bollworm has a versatile complement of detoxification genes which are evolving in diverse ways across its range.

Exploring gene content with pangene graphs

MOTIVATION

The gene content regulates the biology of an organism. It varies between species and between individuals of the same species. Although tools have been developed to identify gene content changes in bacterial genomes, none is applicable to collections of large eukaryotic genomes such as the human pangenome.

RESULTS

We developed pangene, a computational tool to identify gene orientation, gene order and gene copy-number changes in a collection of genomes. Pangene aligns a set of input protein sequences to the genomes, resolves redundancies between protein sequences and constructs a gene graph with each genome represented as a walk in the graph. It additionally finds subgraphs, which we call bibubbles, that capture gene content changes. Applied to the human pangenome, pangene identifies known gene-level variations and reveals complex haplotypes that are not well studied before. Pangene also works with high-quality bacterial pangenome and reports similar numbers of core and accessory genes in comparison to existing tools.

AVAILABILITY AND IMPLEMENTATION

Source code at https://github.com/lh3/pangene; pre-built pangene graphs can be downloaded from https://zenodo.org/records/8118576 and visualized at https://pangene.bioinweb.org.

Global diversity, recurrent evolution, and recent selection on amylase structural haplotypes in humans

The adoption of agriculture, first documented ~12,000 years ago in the Fertile Crescent, triggered a rapid shift toward starch-rich diets in human populations. Amylase genes facilitate starch digestion and increased salivary amylase copy number has been observed in some modern human populations with high starch intake, though evidence of recent selection is lacking. Here, using 52 long-read diploid assemblies and short read data from ~5,600 contemporary and ancient humans, we resolve the diversity, evolutionary history, and selective impact of structural variation at the amylase locus. We find that amylase genes have higher copy numbers in populations with agricultural subsistence compared to fishing, hunting, and pastoral groups. We identify 28 distinct amylase structural architectures and demonstrate that nearly identical structures have arisen recurrently on different haplotype backgrounds throughout recent human history. AMY1 and AMY2A genes each exhibit multiple duplications/deletions with mutation rates >10,000-fold the SNP mutation rate, whereas AMY2B gene duplications share a single origin. Using a pangenome graph-based approach to infer structural haplotypes across thousands of humans, we identify extensively duplicated haplotypes present at higher frequencies in modern day populations with traditionally agricultural diets. Leveraging 533 ancient human genomes we find that duplication-containing haplotypes (i.e. haplotypes with more amylase gene copies than the ancestral haplotype) have increased in frequency more than seven-fold over the last 12,000 years providing evidence for recent selection in West Eurasians. Together, our study highlights the potential impacts of the agricultural revolution on human genomes and the importance of long-read sequencing in identifying signatures of selection at structurally complex loci.

DEFA1A3 DNA gene-dosage regulates the kidney innate immune response during upper urinary tract infection

Antimicrobial peptides (AMPs) are host defense effectors with potent neutralizing and immunomodulatory functions against invasive pathogens. The AMPs α-Defensin 1-3/DEFA1A3 participate in innate immune responses and influence patient outcomes in various diseases. DNA copy-number variations in DEFA1A3 have been associated with severity and outcomes in infectious diseases including urinary tract infections (UTIs). Specifically, children with lower DNA copy numbers were more susceptible to UTIs. The mechanism of action by which α-Defensin 1-3/DEFA1A3 copy-number variations lead to UTI susceptibility remains to be explored. In this study, we use a previously characterized transgenic knock-in of the human DEFA1A3 gene mouse to dissect α-Defensin 1-3 gene dose-dependent antimicrobial and immunomodulatory roles during uropathogenic Escherichia coli (UPEC) UTI. We elucidate the relationship between kidney neutrophil- and collecting duct intercalated cell-derived α-Defensin 1-3/DEFA1A3 expression and UTI. We further describe cooperative effects between α-Defensin 1-3 and other AMPs that potentiate the neutralizing activity against UPEC. Cumulatively, we demonstrate that DEFA1A3 directly protects against UPEC meanwhile impacting pro-inflammatory innate immune responses in a gene dosage-dependent manner.

Unveiling the population genetic structure of Iranian horses breeds by whole-genome resequencing analysis

Preserving genetic diversity is pivotal for enhancing genetic improvement and facilitating adaptive responses to selection. This study focuses on identifying key genetic variants, including single nucleotide polymorphisms (SNPs), insertion/deletion polymorphisms (INDELs), and copy number variants (CNVs), while exploring the genomic evolutionary connectedness among seven Iranian horses representing five indigenous breeds: Caspian, Turkemen, DareShuri, Kurdish, and Asil. Using whole-genome resequencing, we generated 2.7 Gb of sequence data, with raw reads ranging from 1.2 Gb for Caspian horses to 0.38 Gb for Turkoman horses. Post-filtering, approximately 1.9 Gb of reads remained, with ~ 1.5 Gb successfully mapped to the horse reference genome (EquCab3.0), achieving mapping rates between 76.4% (Caspian) and 98.35% (Turkoman). We identified 2,909,816 SNPs in Caspian horses, constituting around 0.1% of the genome. Notably, 71% of these SNPs were situated in intergenic regions, while 8.5 and 6.8% were located upstream and downstream, respectively. A comparative analysis of SNPs between Iranian and non-Iranian horse breeds showed that Caspian horses had the lowest number of shared SNPs with Turkoman horses. Instead, they showed a closer genetic relationship with DareShuri, Quarter, Arabian, Standardbred, and Asil breeds. Hierarchical clustering highlighted Caspian horses as a distinct cluster, underscoring their distinctive genomic signature. Caspian horses exhibit a unique genetic profile marked by an enrichment of private mutations in neurological genes, influencing sensory perception and awareness. This distinct genetic makeup shapes mating preferences and signifies a separate evolutionary trajectory. Additionally, significant non-synonymous single nucleotide polymorphisms (nsSNPs) in reproductive genes offer intervention opportunities for managing Caspian horses. These findings reveal the population genetic structure of Iranian horse breeds, contributing to the advancement of knowledge in areas such as conservation, performance traits, climate adaptation, reproduction, and resistance to diseases in equine science.

Exploring gene content with pangene graphs

Motivation

The gene content regulates the biology of an organism. It varies between species and between individuals of the same species. Although tools have been developed to identify gene content changes in bacterial genomes, none is applicable to collections of large eukaryotic genomes such as the human pangenome.

Results

We developed pangene, a computational tool to identify gene orientation, gene order and gene copy-number changes in a collection of genomes. Pangene aligns a set of input protein sequences to the genomes, resolves redundancies between protein sequences and constructs a gene graph with each genome represented as a walk in the graph. It additionally finds subgraphs, which we call bibubbles, that capture gene content changes. Applied to the human pangenome, pangene identifies known gene-level variations and reveals complex haplotypes that are not well studied before. Pangene also works with high-quality bacterial pangenome and reports similar numbers of core and accessory genes in comparison to existing tools.

Availability and implementation

Source code at https://github.com/lh3/pangene; pre-built pangene graphs can be downloaded from https://zenodo.org/records/8118576 and visualized at https://pangene.bioinweb.org.

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.

The prevalence of copy number increase at multiallelic copy number variants associated with cave colonization

Copy number variation is a common contributor to phenotypic diversity, yet its involvement in ecological adaptation is not easily discerned. Instances of parallelly evolving populations of the same species in a similar environment marked by strong selective pressures present opportunities to study the role of copy number variants (CNVs) in adaptation. By identifying CNVs that repeatedly occur in multiple populations of the derived ecotype and are not (or are rarely) present in the populations of the ancestral ecotype, the association of such CNVs with adaptation to the novel environment can be inferred. We used this paradigm to identify CNVs associated with recurrent adaptation of the Mexican tetra (Astyanax mexicanus) to cave environment. Using a read-depth approach, we detected CNVs from previously re-sequenced genomes of 44 individuals belonging to two ancestral surfaces and three derived cave populations. We identified 102 genes and 292 genomic regions that repeatedly diverge in copy number between the two ecotypes and occupy 0.8% of the reference genome. Functional analysis revealed their association with processes previously recognized to be relevant for adaptation, such as vision, immunity, oxygen consumption, metabolism, and neural function and we propose that these variants have been selected for in the cave or surface waters. The majority of the ecotype-divergent CNVs are multiallelic and display copy number increases in cavefish compared to surface fish. Our findings suggest that multiallelic CNVs - including gene duplications - and divergence in copy number provide a fast route to produce novel phenotypes associated with adaptation to subterranean life.

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.

Artificial Intelligence and Computational Biology in Gene Therapy: A Review

One of the trending fields in almost all areas of science and technology is artificial intelligence. Computational biology and artificial intelligence can help gene therapy in many steps including: gene identification, gene editing, vector design, development of new macromolecules and modeling of gene delivery. There are various tools used by computational biology and artificial intelligence in this field, such as genomics, transcriptomic and proteomics data analysis, machine learning algorithms and molecular interaction studies. These tools can introduce new gene targets, novel vectors, optimized experiment conditions, predict the outcomes and suggest the best solutions to avoid undesired immune responses following gene therapy treatment.

Population Neuroscience: Principles and Advances

In population neuroscience, three disciplines come together to advance our knowledge of factors that shape the human brain: neuroscience, genetics, and epidemiology (Paus, Human Brain Mapping 31:891-903, 2010). Here, I will come back to some of the background material reviewed in more detail in our previous book (Paus, Population Neuroscience, 2013), followed by a brief overview of current advances and challenges faced by this integrative approach.

Genetic determinants of plasma protein levels in the Estonian population

The proteome holds great potential as an intermediate layer between the genome and phenome. Previous protein quantitative trait locus studies have focused mainly on describing the effects of common genetic variations on the proteome. Here, we assessed the impact of the common and rare genetic variations as well as the copy number variants (CNVs) on 326 plasma proteins measured in up to 500 individuals. We identified 184 cis and 94 trans signals for 157 protein traits, which were further fine-mapped to credible sets for 101 cis and 87 trans signals for 151 proteins. Rare genetic variation contributed to the levels of 7 proteins, with 5 cis and 14 trans associations. CNVs were associated with the levels of 11 proteins (7 cis and 5 trans), examples including a 3q12.1 deletion acting as a hub for multiple trans associations; and a CNV overlapping NAIP, a sensor component of the NAIP-NLRC4 inflammasome which is affecting pro-inflammatory cytokine interleukin 18 levels. In summary, this work presents a comprehensive resource of genetic variation affecting the plasma protein levels and provides the interpretation of identified effects.

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.

NPSV-deep: a deep learning method for genotyping structural variants in short read genome sequencing data

MOTIVATION

Structural variants (SVs) play a causal role in numerous diseases but can be difficult to detect and accurately genotype (determine zygosity) with short-read genome sequencing data (SRS). Improving SV genotyping accuracy in SRS data, particularly for the many SVs first detected with long-read sequencing, will improve our understanding of genetic variation.

RESULTS

NPSV-deep is a deep learning-based approach for genotyping previously reported insertion and deletion SVs that recasts this task as an image similarity problem. NPSV-deep predicts the SV genotype based on the similarity between pileup images generated from the actual SRS data and matching SRS simulations. We show that NPSV-deep consistently matches or improves upon the state-of-the-art for SV genotyping accuracy across different SV call sets, samples and variant types, including a 25% reduction in genotyping errors for the Genome-in-a-Bottle (GIAB) high-confidence SVs. NPSV-deep is not limited to the SVs as described; it improves deletion genotyping concordance a further 1.5 percentage points for GIAB SVs (92%) by automatically correcting imprecise/incorrectly described SVs.

AVAILABILITY AND IMPLEMENTATION

Python/C++ source code and pre-trained models freely available at https://github.com/mlinderm/npsv2.

A concerted neuron-astrocyte program declines in ageing and schizophrenia

Human brains vary across people and over time; such variation is not yet understood in cellular terms. Here we describe a relationship between people's cortical neurons and cortical astrocytes. We used single-nucleus RNA sequencing to analyse the prefrontal cortex of 191 human donors aged 22-97 years, including healthy individuals and people with schizophrenia. Latent-factor analysis of these data revealed that, in people whose cortical neurons more strongly expressed genes encoding synaptic components, cortical astrocytes more strongly expressed distinct genes with synaptic functions and genes for synthesizing cholesterol, an astrocyte-supplied component of synaptic membranes. We call this relationship the synaptic neuron and astrocyte program (SNAP). In schizophrenia and ageing-two conditions that involve declines in cognitive flexibility and plasticity1,2-cells divested from SNAP: astrocytes, glutamatergic (excitatory) neurons and GABAergic (inhibitory) neurons all showed reduced SNAP expression to corresponding degrees. The distinct astrocytic and neuronal components of SNAP both involved genes in which genetic risk factors for schizophrenia were strongly concentrated. SNAP, which varies quantitatively even among healthy people of similar age, may underlie many aspects of normal human interindividual differences and may be an important point of convergence for multiple kinds of pathophysiology.

The T2T-CHM13 reference assembly uncovers essential WASH1 and GPRIN2 paralogues

Summary

The recently published T2T-CHM13 reference assembly completed the annotation of the final 8% of the human genome. It introduced 1956 genes, close to 100 of which are predicted to be coding because they have a protein coding parent gene. Here, we confirm the coding status and functional relevance of two of these genes, paralogues of WASHC1 and GPRIN2. We find that LOC124908094, one of four novel subtelomeric WASH1 genes uncovered in the new assembly, produces the WASH1 protein that forms part of the vital actin-regulatory WASH complex. Its coding status is supported by abundant proteomics, conservation, and cDNA evidence. It was previously assumed that gene WASHC1 produced the functional WASH1 protein, but new evidence shows that WASHC1 is a human-derived duplication and likely to be one of 12 WASH1 pseudogenes in the human gene set. We also find that the T2T-CHM13 assembly has added a functionally important copy of GPRIN2 to the human gene set. We demonstrate that uniquely mapping peptides from proteomics databases support the novel LOC124900631 rather than the GRCh38 assembly GPRIN2 gene. These new additions to the set of human coding genes underlines the importance of the new T2T-CHM13 assembly.

Availability and implementation

None.

Association of Structural Forms of 17q21.31 with the Risk of Progressive Supranuclear Palsy and MAPT Sub-haplotypes

Importance

The chromosome 17q21.31 region, containing a 900 Kb inversion that defines H1 and H2 haplotypes, represents the strongest genetic risk locus in progressive supranuclear palsy (PSP). In addition to H1 and H2, various structural forms of 17q21.31, characterized by the copy number of α, β, and γ duplications, have been identified. However, the specific effect of each structural form on the risk of PSP has never been evaluated in a large cohort study.

Objective

To assess the association of different structural forms of 17q.21.31, defined by the copy numbers of α, β, and γ duplications, with the risk of PSP and MAPT sub-haplotypes.

Design setting and participants

Utilizing whole genome sequencing data of 1,684 (1,386 autopsy confirmed) individuals with PSP and 2,392 control subjects, a case-control study was conducted to investigate the association of copy numbers of α, β, and γ duplications and structural forms of 17q21.31 with the risk of PSP. All study subjects were selected from the Alzheimer's Disease Sequencing Project (ADSP) Umbrella NG00067.v7. Data were analyzed between March 2022 and November 2023.

Main outcomes and measures

The main outcomes were the risk (odds ratios [ORs]) for PSP with 95% CIs. Risks for PSP were evaluated by logistic regression models.

Results

The copy numbers of α and β were associated with the risk of PSP only due to their correlation with H1 and H2, while the copy number of γ was independently associated with the increased risk of PSP. Each additional duplication of γ was associated with 1.10 (95% CI, 1.04-1.17; P = 0.0018) fold of increased risk of PSP when conditioning H1 and H2. For the H1 haplotype, addition γ duplications displayed a higher odds ratio for PSP: the odds ratio increases from 1.21 (95%CI 1.10-1.33, P = 5.47 × 10-5) for H1β1γ1 to 1.29 (95%CI 1.16-1.43, P = 1.35 × 10-6) for H1β1γ2, 1.45 (95%CI 1.27-1.65, P = 3.94 × 10-8) for H1β1γ3, and 1.57 (95%CI 1.10-2.26, P = 1.35 × 10-2) for H1β1γ4. Moreover, H1β1γ3 is in linkage disequilibrium with H1c (R2 = 0.31), a widely recognized MAPT sub-haplotype associated with increased risk of PSP. The proportion of MAPT sub-haplotypes associated with increased risk of PSP (i.e., H1c, H1d, H1g, H1o, and H1h) increased from 34% in H1β1γ1 to 77% in H1β1γ4.

Conclusions and relevance

This study revealed that the copy number of γ was associated with the risk of PSP independently from H1 and H2. The H1 haplotype with more γ duplications showed a higher odds ratio for PSP and were associated with MAPT sub-haplotypes with increased risk of PSP. These findings expand our understanding of how the complex structure at 17q21.31 affect the risk of PSP.

Incomplete reprogramming of DNA replication timing in induced pluripotent stem cells

Induced pluripotent stem cells (iPSCs) are the foundation of cell therapy. Differences in gene expression, DNA methylation, and chromatin conformation, which could affect differentiation capacity, have been identified between iPSCs and embryonic stem cells (ESCs). Less is known about whether DNA replication timing, a process linked to both genome regulation and genome stability, is efficiently reprogrammed to the embryonic state. To answer this, we compare genome-wide replication timing between ESCs, iPSCs, and cells reprogrammed by somatic cell nuclear transfer (NT-ESCs). While NT-ESCs replicate their DNA in a manner indistinguishable from ESCs, a subset of iPSCs exhibits delayed replication at heterochromatic regions containing genes downregulated in iPSCs with incompletely reprogrammed DNA methylation. DNA replication delays are not the result of gene expression or DNA methylation aberrations and persist after cells differentiate to neuronal precursors. Thus, DNA replication timing can be resistant to reprogramming and influence the quality of iPSCs.

Concerted neuron-astrocyte gene expression declines in aging and schizophrenia

Human brains vary across people and over time; such variation is not yet understood in cellular terms. Here we describe a striking relationship between people's cortical neurons and cortical astrocytes. We used single-nucleus RNA-seq to analyze the prefrontal cortex of 191 human donors ages 22-97 years, including healthy individuals and persons with schizophrenia. Latent-factor analysis of these data revealed that in persons whose cortical neurons more strongly expressed genes for synaptic components, cortical astrocytes more strongly expressed distinct genes with synaptic functions and genes for synthesizing cholesterol, an astrocyte-supplied component of synaptic membranes. We call this relationship the Synaptic Neuron-and-Astrocyte Program (SNAP). In schizophrenia and aging - two conditions that involve declines in cognitive flexibility and plasticity 1,2 - cells had divested from SNAP: astrocytes, glutamatergic (excitatory) neurons, and GABAergic (inhibitory) neurons all reduced SNAP expression to corresponding degrees. The distinct astrocytic and neuronal components of SNAP both involved genes in which genetic risk factors for schizophrenia were strongly concentrated. SNAP, which varies quantitatively even among healthy persons of similar age, may underlie many aspects of normal human interindividual differences and be an important point of convergence for multiple kinds of pathophysiology.

High-throughput complement component 4 genomic sequence analysis with C4Investigator

The complement component 4 gene loci, composed of the C4A and C4B genes and located on chromosome 6, encodes for complement component 4 (C4) proteins, a key intermediate in the classical and lectin pathways of the complement system. The complement system is an important modulator of immune system activity and is also involved in the clearance of immune complexes and cellular debris. C4A and C4B gene loci exhibit copy number variation, with each composite gene varying between 0 and 5 copies per haplotype. C4A and C4B genes also vary in size depending on the presence of the human endogenous retrovirus (HERV) in intron 9, denoted by C4(L) for long-form and C4(S) for short-form, which affects expression and is found in both C4A and C4B. Additionally, human blood group antigens Rodgers and Chido are located on the C4 protein, with the Rodger epitope generally found on C4A protein, and the Chido epitope generally found on C4B protein. C4A and C4B copy number variation has been implicated in numerous autoimmune and pathogenic diseases. Despite the central role of C4 in immune function and regulation, high-throughput genomic sequence analysis of C4A and C4B variants has been impeded by the high degree of sequence similarity and complex genetic variation exhibited by these genes. To investigate C4 variation using genomic sequencing data, we have developed a novel bioinformatic pipeline for comprehensive, high-throughput characterization of human C4A and C4B sequences from short-read sequencing data, named C4Investigator. Using paired-end targeted or whole genome sequence data as input, C4Investigator determines the overall gene copy numbers, as well as C4A, C4B, C4(Rodger), C4(Ch), C4(L), and C4(S). Additionally, C4Ivestigator reports the full overall C4A and C4B aligned sequence, enabling nucleotide level analysis. To demonstrate the utility of this workflow we have analyzed C4A and C4B variation in the 1000 Genomes Project Data set, showing that these genes are highly poly-allelic with many variants that have the potential to impact C4 protein function.

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.

Comparative analysis of genome-wide copy number variations between Tibetan sheep and White Suffolk sheep

The DNA copy number variations (CNVs) are widely involved in affecting various kinds of biological functions, such as environmental adaptation. Tibetan sheep and White Suffolk sheep are two representative indigenous and exotic breeds raised in Sichuan, China, and both of them have many contrasting biological characteristics. In this study, we employed high-throughput sequencing approach to investigate genome-wide CNVs between the two sheep breeds. A total of 11,135 CNV regions (CNVRs) consisting of 6,488 deletions and 4,647 duplications were detected, whose length ranged from 1,599 bp to 0.56 Mb with the mean of 4,658 bp. There were 281 CNVRs segregated between Tibetan sheep and White Suffolk sheep, and 18 of them have been fixed within both breeds. Functional analyses of candidate genes within the segregating CNVRs revealed the thyroid hormone signaling pathway and CTNNB1 gene that would be responsible for differential biological characteristics of breeds, such as energy metabolism, seasonal reproduction, and litter size. Furthermore, the segregating CNVRs identified in this study were overlapped with many known quantitative trait loci that are associated with growth, testis weight, and reproductive seasonality. In conclusion, these results help us better understanding differential biological characteristics between Tibetan sheep and White Suffolk sheep.

Systematic analysis of paralogous regions in 41,755 exomes uncovers clinically relevant variation

The short lengths of short-read sequencing reads challenge the analysis of paralogous genomic regions in exome and genome sequencing data. Most genetic variants within these homologous regions therefore remain unidentified in standard analyses. Here, we present a method (Chameleolyser) that accurately identifies single nucleotide variants and small insertions/deletions (SNVs/Indels), copy number variants and ectopic gene conversion events in duplicated genomic regions using whole-exome sequencing data. Application to a cohort of 41,755 exome samples yields 20,432 rare homozygous deletions and 2,529,791 rare SNVs/Indels, of which we show that 338,084 are due to gene conversion events. None of the SNVs/Indels are detectable using regular analysis techniques. Validation by high-fidelity long-read sequencing in 20 samples confirms >88% of called variants. Focusing on variation in known disease genes leads to a direct molecular diagnosis in 25 previously undiagnosed patients. Our method can readily be applied to existing exome data.

GeneToCN: an alignment-free method for gene copy number estimation directly from next-generation sequencing reads

Genomes exhibit large regions with segmental copy number variation, many of which include entire genes and are multiallelic. We have developed a computational method GeneToCN that counts the frequencies of gene-specific k-mers in FASTQ files and uses this information to infer copy number of the gene. We validated the copy number predictions for amylase genes (AMY1, AMY2A, AMY2B) using experimental data from digital droplet PCR (ddPCR) on 39 individuals and observed a strong correlation (R = 0.99) between GeneToCN predictions and experimentally determined copy numbers. An additional validation on FCGR3 genes showed a higher concordance for FCGR3A compared to two other methods, but reduced accuracy for FCGR3B. We further tested the method on three different genomic regions (SMN, NPY4R, and LPA Kringle IV-2 domain). Predicted copy number distributions of these genes in a set of 500 individuals from the Estonian Biobank were in good agreement with the previously published studies. In addition, we investigated the possibility to use GeneToCN on sequencing data generated by different technologies by comparing copy number predictions from Illumina, PacBio, and Oxford Nanopore data of the same sample. Despite the differences in variability of k-mer frequencies, all three sequencing technologies give similar predictions with GeneToCN.

Sibling chimerism among microglia in marmosets

Chimerism happens rarely among most mammals but is common in marmosets and tamarins, a result of fraternal twin or triplet birth patterns in which in utero connected circulatory systems (through which stem cells transit) lead to persistent blood chimerism (12-80%) throughout life. The presence of Y-chromosome DNA sequences in other organs of female marmosets has long suggested that chimerism might also affect these organs. However, a longstanding question is whether this chimerism is driven by blood-derived cells or involves contributions from other cell types. To address this question, we analyzed single-cell RNA-seq data from blood, liver, kidney and multiple brain regions across a number of marmosets, using transcribed single nucleotide polymorphisms (SNPs) to identify cells with the sibling's genome in various cell types within these tissues. Sibling-derived chimerism in all tissues arose entirely from cells of hematopoietic origin (i.e., myeloid and lymphoid lineages). In brain tissue this was reflected as sibling-derived chimerism among microglia (20-52%) and macrophages (18-64%) but not among other resident cell types (i.e., neurons, glia or ependymal cells). The percentage of microglia that were sibling-derived showed significant variation across brain regions, even within individual animals, likely reflecting distinct responses by siblings' microglia to local recruitment or proliferation cues or, potentially, distinct clonal expansion histories in different brain areas. In the animals and tissues we analyzed, microglial gene expression profiles bore a much stronger relationship to local/host context than to sibling genetic differences. Naturally occurring marmoset chimerism will provide new ways to understand the effects of genes, mutations and brain contexts on microglial biology and to distinguish between effects of microglia and other cell types on brain phenotypes.

Detection of copy number variations based on a local distance using next-generation sequencing data

As one of the main types of structural variation in the human genome, copy number variation (CNV) plays an important role in the occurrence and development of human cancers. Next-generation sequencing (NGS) technology can provide base-level resolution, which provides favorable conditions for the accurate detection of CNVs. However, it is still a very challenging task to accurately detect CNVs from cancer samples with different purity and low sequencing coverage. Local distance-based CNV detection (LDCNV), an innovative computational approach to predict CNVs using NGS data, is proposed in this work. LDCNV calculates the average distance between each read depth (RD) and its k nearest neighbors (KNNs) to define the distance of KNNs of each RD, and the average distance between the KNNs for each RD to define their internal distance. Based on the above definitions, a local distance score is constructed using the ratio between the distance of KNNs and the internal distance of KNNs for each RD. The local distance scores are used to fit a normal distribution to evaluate the significance level of each RDS, and then use the hypothesis test method to predict the CNVs. The performance of the proposed method is verified with simulated and real data and compared with several popular methods. The experimental results show that the proposed method is superior to various other techniques. Therefore, the proposed method can be helpful for cancer diagnosis and targeted drug development.

Genotypic diversity and unrecognized antifungal resistance among populations of Candida glabrata from positive blood cultures

The longstanding model is that most bloodstream infections (BSIs) are caused by a single organism. We perform whole genome sequencing of five-to-ten strains from blood culture (BC) bottles in each of ten patients with Candida glabrata BSI. We demonstrate that BCs contain mixed populations of clonal but genetically diverse strains. Genetically distinct strains from two patients exhibit phenotypes that are potentially important during BSIs, including differences in susceptibility to antifungal agents and phagocytosis. In both patients, the clinical microbiology lab recovered a fluconazole-susceptible index strain, but we identify mixed fluconazole-susceptible and -resistant populations. Diversity in drug susceptibility is likely clinically relevant, as fluconazole-resistant strains were subsequently recovered by the clinical laboratory during persistent or relapsing infections. In one patient, unrecognized respiration-deficient small colony variants are fluconazole-resistant and significantly attenuated for virulence during murine candidiasis. Our data suggest a population-based model of C. glabrata genotypic and phenotypic diversity during BSIs.

Population history modulates the fitness effects of Copy Number Variation in the Roma

We provide the first whole genome Copy Number Variant (CNV) study addressing Roma, along with reference populations from South Asia, the Middle East and Europe. Using CNV calling software for short-read sequence data, we identified 3171 deletions and 489 duplications. Taking into account the known population history of the Roma, as inferred from whole genome nucleotide variation, we could discern how this history has shaped CNV variation. As expected, patterns of deletion variation, but not duplication, in the Roma followed those obtained from single nucleotide polymorphisms (SNPs). Reduced effective population size resulting in slightly relaxed natural selection may explain our observation of an increase in intronic (but not exonic) deletions within Loss of Function (LoF)-intolerant genes. Over-representation analysis for LoF-intolerant gene sets hosting intronic deletions highlights a substantial accumulation of shared biological processes in Roma, intriguingly related to signaling, nervous system and development features, which may be related to the known profile of private disease in the population. Finally, we show the link between deletions and known trait-related SNPs reported in the genome-wide association study (GWAS) catalog, which exhibited even frequency distributions among the studied populations. This suggests that, in general human populations, the strong association between deletions and SNPs associated to biomedical conditions and traits could be widespread across continental populations, reflecting a common background of potentially disease/trait-related CNVs.

GATK-gCNV enables the discovery of rare copy number variants from exome sequencing data

Copy number variants (CNVs) are major contributors to genetic diversity and disease. While standardized methods, such as the genome analysis toolkit (GATK), exist for detecting short variants, technical challenges have confounded uniform large-scale CNV analyses from whole-exome sequencing (WES) data. Given the profound impact of rare and de novo coding CNVs on genome organization and human disease, we developed GATK-gCNV, a flexible algorithm to discover rare CNVs from sequencing read-depth information, complete with open-source distribution via GATK. We benchmarked GATK-gCNV in 7,962 exomes from individuals in quartet families with matched genome sequencing and microarray data, finding up to 95% recall of rare coding CNVs at a resolution of more than two exons. We used GATK-gCNV to generate a reference catalog of rare coding CNVs in WES data from 197,306 individuals in the UK Biobank, and observed strong correlations between per-gene CNV rates and measures of mutational constraint, as well as rare CNV associations with multiple traits. In summary, GATK-gCNV is a tunable approach for sensitive and specific CNV discovery in WES data, with broad applications.

Repeat polymorphisms underlie top genetic risk loci for glaucoma and colorectal cancer

Many regions in the human genome vary in length among individuals due to variable numbers of tandem repeats (VNTRs). To assess the phenotypic impact of VNTRs genome-wide, we applied a statistical imputation approach to estimate the lengths of 9,561 autosomal VNTR loci in 418,136 unrelated UK Biobank participants and 838 GTEx participants. Association and statistical fine-mapping analyses identified 58 VNTRs that appeared to influence a complex trait in UK Biobank, 18 of which also appeared to modulate expression or splicing of a nearby gene. Non-coding VNTRs at TMCO1 and EIF3H appeared to generate the largest known contributions of common human genetic variation to risk of glaucoma and colorectal cancer, respectively. Each of these two VNTRs associated with a >2-fold range of risk across individuals. These results reveal a substantial and previously unappreciated role of non-coding VNTRs in human health and gene regulation.

Relation between HLA and copy number variation of steroid 21-hydroxylase in a Swedish cohort of patients with autoimmune Addison's disease

OBJECTIVE

Autoantibodies against the adrenal enzyme 21-hydroxylase is a hallmark manifestation in autoimmune Addison's disease (AAD). Steroid 21-hydroxylase is encoded by CYP21A2, which is located in the human leucocyte antigen (HLA) region together with the highly similar pseudogene CYP21A1P. A high level of copy number variation is seen for the 2 genes, and therefore, we asked whether genetic variation of the CYP21 genes is associated with AAD.

DESIGN

Case-control study on patients with AAD and healthy controls.

METHODS

Using next-generation DNA sequencing, we estimated the copy number of CYP21A2 and CYP21A1P, together with HLA alleles, in 479 Swedish patients with AAD and autoantibodies against 21-hydroxylase and in 1393 healthy controls.

RESULTS

With 95% of individuals carrying 2 functional 21-hydroxylase genes, no difference in CYP21A2 copy number was found when comparing patients and controls. In contrast, we discovered a lower copy number of the pseudogene CYP21A1P among AAD patients (P = 5 × 10-44), together with associations of additional nucleotide variants, in the CYP21 region. However, the strongest association was found for HLA-DQB1*02:01 (P = 9 × 10-63), which, in combination with the DRB1*04:04-DQB1*03:02 haplotype, imposed the greatest risk of AAD.

CONCLUSIONS

We identified strong associations between copy number variants in the CYP21 region and risk of AAD, although these associations most likely are due to linkage disequilibrium with disease-associated HLA class II alleles.

Genomic structural variation: A complex but important driver of human evolution

Structural variants (SVs)-including duplications, deletions, and inversions of DNA-can have significant genomic and functional impacts but are technically difficult to identify and assay compared with single-nucleotide variants. With the aid of new genomic technologies, it has become clear that SVs account for significant differences across and within species. This phenomenon is particularly well-documented for humans and other primates due to the wealth of sequence data available. In great apes, SVs affect a larger number of nucleotides than single-nucleotide variants, with many identified SVs exhibiting population and species specificity. In this review, we highlight the importance of SVs in human evolution by (1) how they have shaped great ape genomes resulting in sensitized regions associated with traits and diseases, (2) their impact on gene functions and regulation, which subsequently has played a role in natural selection, and (3) the role of gene duplications in human brain evolution. We further discuss how to incorporate SVs in research, including the strengths and limitations of various genomic approaches. Finally, we propose future considerations in integrating existing data and biospecimens with the ever-expanding SV compendium propelled by biotechnology advancements.

High-throughput complement component 4 genomic sequence analysis with C4Investigator

The complement component 4 gene locus, composed of the C4A and C4B genes and located on chromosome 6, encodes for C4 protein, a key intermediate in the classical and lectin pathways of the complement system. The complement system is an important modulator of immune system activity and is also involved in the clearance of immune complexes and cellular debris. The C4 gene locus exhibits copy number variation, with each composite gene varying between 0-5 copies per haplotype, C4 genes also vary in size depending on the presence of the HERV retrovirus in intron 9, denoted by C4(L) for long-form and C4(S) for short-form, which modulates expression and is found in both C4A and C4B. Additionally, human blood group antigens Rodgers and Chido are located on the C4 protein, with the Rodger epitope generally found on C4A protein, and the Chido epitope generally found on C4B protein. C4 copy number variation has been implicated in numerous autoimmune and pathogenic diseases. Despite the central role of C4 in immune function and regulation, high-throughput genomic sequence analysis of C4 variants has been impeded by the high degree of sequence similarity and complex genetic variation exhibited by these genes. To investigate C4 variation using genomic sequencing data, we have developed a novel bioinformatic pipeline for comprehensive, high-throughput characterization of human C4 sequence from short-read sequencing data, named C4Investigator. Using paired-end targeted or whole genome sequence data as input, C4Investigator determines gene copy number for overall C4, C4A, C4B, C4(Rodger), C4(Ch), C4(L), and C4(S), additionally, C4Ivestigator reports the full overall C4 aligned sequence, enabling nucleotide level analysis of C4. To demonstrate the utility of this workflow we have analyzed C4 variation in the 1000 Genomes Project Dataset, showing that the C4 genes are highly poly-allelic with many variants that have the potential to impact C4 protein function.

Incomplete Reprogramming of DNA Replication Timing in Induced Pluripotent Stem Cells

Induced pluripotent stem cells (iPSC) are a widely used cell system and a foundation for cell therapy. Differences in gene expression, DNA methylation, and chromatin conformation, which have the potential to affect differentiation capacity, have been identified between iPSCs and embryonic stem cells (ESCs). Less is known about whether DNA replication timing - a process linked to both genome regulation and genome stability - is efficiently reprogrammed to the embryonic state. To answer this, we profiled and compared genome-wide replication timing between ESCs, iPSCs, and cells reprogrammed by somatic cell nuclear transfer (NT-ESCs). While NT-ESCs replicated their DNA in a manner indistinguishable from ESCs, a subset of iPSCs exhibit delayed replication at heterochromatic regions containing genes downregulated in iPSC with incompletely reprogrammed DNA methylation. DNA replication delays were not the result of gene expression and DNA methylation aberrations and persisted after differentiating cells to neuronal precursors. Thus, DNA replication timing can be resistant to reprogramming and lead to undesirable phenotypes in iPSCs, establishing it as an important genomic feature to consider when evaluating iPSC lines.

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.

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.

Differences in the intraspecies copy number variation of Arabidopsis thaliana conserved and nonconserved miRNA genes

MicroRNAs (miRNAs) regulate gene expression by RNA interference mechanism. In plants, miRNA genes (MIRs) which are grouped into conserved families, i.e. they are present among the different plant taxa, are involved in the regulation of many developmental and physiological processes. The roles of the nonconserved MIRs-which are MIRs restricted to one plant family, genus, or even species-are less recognized; however, many of them participate in the responses to biotic and abiotic stresses. Both over- and underproduction of miRNAs may influence various biological processes. Consequently, maintaining intracellular miRNA homeostasis seems to be crucial for the organism. Deletions and duplications in the genomic sequence may alter gene dosage and/or activity. We evaluated the extent of copy number variations (CNVs) among Arabidopsis thaliana (Arabidopsis) MIRs in over 1000 natural accessions, using population-based analysis of the short-read sequencing data. We showed that the conserved MIRs were unlikely to display CNVs and their deletions were extremely rare, whereas nonconserved MIRs presented moderate variation. Transposon-derived MIRs displayed exceptionally high diversity. Conversely, MIRs involved in the epigenetic control of transposons reactivated during development were mostly invariable. MIR overlap with the protein-coding genes also limited their variability. At the expression level, a higher rate of nonvariable, nonconserved miRNAs was detectable in Col-0 leaves, inflorescence, and siliques compared to nonconserved variable miRNAs, although the expression of both groups was much lower than that of the conserved MIRs. Our data indicate that CNV rate of Arabidopsis MIRs is related with their age, function, and genomic localization.

Genotypic diversity and unrecognized antifungal resistance among populations of Candida glabrata from positive blood cultures

The longstanding paradigm is that most bloodstream infections (BSIs) are caused by a single organism. We performed whole genome sequencing of five-to-ten strains from blood culture (BC) bottles in each of ten patients with Candida glabrata BSI. We demonstrated that BCs contained mixed populations of clonal but genetically diverse strains. Genetically distinct strains from two patients exhibited phenotypes that were potentially important during BSIs, including differences in susceptibility to antifungal agents and phagocytosis. In both patients, the clinical microbiology lab recovered a fluconazole-susceptible index strain, but we identified mixed fluconazole-susceptible and â€"resistant populations. Diversity in drug susceptibility was likely clinically relevant, as fluconazole-resistant strains were subsequently recovered by the clinical laboratory during persistent or relapsing infections. In one patient, unrecognized respiration-deficient small colony variants were fluconazole-resistant and significantly attenuated for virulence during murine candidiasis. Our data suggest a new population-based paradigm of C. glabrata genotypic and phenotypic diversity during BSIs.

Multiallelic Copy Number Variation in ORM1 is Associated with Plasma Cell-Free DNA Levels as an Intermediate Phenotype for Venous Thromboembolism

Venous thromboembolism (VTE) is a common disease with high heritability. However, only a small portion of the genetic variance of VTE can be explained by known genetic risk factors. Neutrophil extracellular traps (NETs) have been associated with prothrombotic activity. Therefore, the genetic basis of NETs could reveal novel risk factors for VTE. A recent genome-wide association study of plasma cell-free DNA (cfDNA) levels in the Genetic Analysis of Idiopathic Thrombophilia 2 (GAIT-2) Project showed a significant associated locus near ORM1. We aimed to further explore this candidate region by next-generation sequencing, copy number variation (CNV) quantification, and expression analysis using an extreme phenotype sampling design involving 80 individuals from the GAIT-2 Project. The RETROVE study with 400 VTE cases and 400 controls was used to replicate the results. A total of 105 genetic variants and a multiallelic CNV (mCNV) spanning ORM1 were identified in GAIT-2. Of these, 17 independent common variants, a region of 22 rare variants, and the mCNV were significantly associated with cfDNA levels. In addition, eight of these common variants and the mCNV influenced ORM1 expression. The association of the mCNV and cfDNA levels was replicated in RETROVE (p-value = 1.19 × 10-6). Additional associations between the mCNV and thrombin generation parameters were identified. Our results reveal that increased mCNV dosages in ORM1 decreased gene expression and upregulated cfDNA levels. Therefore, the mCNV in ORM1 appears to be a novel marker for cfDNA levels, which could contribute to VTE risk.

Allele-dependent interaction of LRRK2 and NOD2 in leprosy

Leprosy, caused by Mycobacterium leprae, rarely affects children younger than 5 years. Here, we studied a multiplex leprosy family that included monozygotic twins aged 22 months suffering from paucibacillary leprosy. Whole genome sequencing identified three amino acid mutations previously associated with Crohn’s disease and Parkinson’s disease as candidate variants for early onset leprosy: LRRK2 N551K, R1398H and NOD2 R702W. In genome-edited macrophages, we demonstrated that cells expressing the LRRK2 mutations displayed reduced apoptosis activity following mycobacterial challenge independently of NOD2. However, employing co-immunoprecipitation and confocal microscopy we showed that LRRK2 and NOD2 proteins interacted in RAW cells and monocyte-derived macrophages, and that this interaction was substantially reduced for the NOD2 R702W mutation. Moreover, we observed a joint effect of LRRK2 and NOD2 variants on Bacillus Calmette-Guérin (BCG)-induced respiratory burst, NF-κB activation and cytokine/chemokine secretion with a strong impact for the genotypes found in the twins consistent with a role of the identified mutations in the development of early onset leprosy.

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

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

Deciphering the exact breakpoints of structural variations using long sequencing reads with DeBreak

Long-read sequencing has demonstrated great potential for characterizing all types of structural variations (SVs). However, existing algorithms have insufficient sensitivity and precision. To address these limitations, we present DeBreak, a computational method for comprehensive and accurate SV discovery. Based on alignment results, DeBreak employs a density-based approach for clustering SV candidates together with a local de novo assembly approach for reconstructing long insertions. A partial order alignment algorithm ensures precise SV breakpoints with single base-pair resolution, and a k-means clustering method can report multi-allele SV events. DeBreak outperforms existing tools on both simulated and real long-read sequencing data from both PacBio and Nanopore platforms. An important application of DeBreak is analyzing cancer genomes for potentially tumor-driving SVs. DeBreak can also be used for supplementing whole-genome assembly-based SV discovery.

CONGA: Copy number variation genotyping in ancient genomes and low-coverage sequencing data

To date, ancient genome analyses have been largely confined to the study of single nucleotide polymorphisms (SNPs). Copy number variants (CNVs) are a major contributor of disease and of evolutionary adaptation, but identifying CNVs in ancient shotgun-sequenced genomes is hampered by typical low genome coverage (<1×) and short fragments (<80 bps), precluding standard CNV detection software to be effectively applied to ancient genomes. Here we present CONGA, tailored for genotyping CNVs at low coverage. Simulations and down-sampling experiments suggest that CONGA can genotype deletions >1 kbps with F-scores >0.75 at ≥1×, and distinguish between heterozygous and homozygous states. We used CONGA to genotype 10,002 outgroup-ascertained deletions across a heterogenous set of 71 ancient human genomes spanning the last 50,000 years, produced using variable experimental protocols. A fraction of these (21/71) display divergent deletion profiles unrelated to their population origin, but attributable to technical factors such as coverage and read length. The majority of the sample (50/71), despite originating from nine different laboratories and having coverages ranging from 0.44×-26× (median 4×) and average read lengths 52-121 bps (median 69), exhibit coherent deletion frequencies. Across these 50 genomes, inter-individual genetic diversity measured using SNPs and CONGA-genotyped deletions are highly correlated. CONGA-genotyped deletions also display purifying selection signatures, as expected. CONGA thus paves the way for systematic CNV analyses in ancient genomes, despite the technical challenges posed by low and variable genome coverage.

Quantitative PCR from human genomic DNA: The determination of gene copy numbers for congenital adrenal hyperplasia and RCCX copy number variation

Quantitative PCR (qPCR) is used for the determination of gene copy number (GCN). GCNs contribute to human disorders, and characterize copy number variation (CNV). The single laboratory method validations of duplex qPCR assays with hydrolysis probes on CYP21A1P and CYP21A2 genes, residing a CNV (RCCX CNV) and related to congenital adrenal hyperplasia, were performed using 46 human genomic DNA samples. We also performed the verifications on 5 qPCR assays for the genetic elements of RCCX CNV; C4A, C4B, CNV breakpoint, HERV-K(C4) CNV deletion and insertion alleles. Precision of each qPCR assay was under 1.01 CV%. Accuracy (relative error) ranged from 4.96±4.08% to 9.91±8.93%. Accuracy was not tightly linked to precision, but was significantly correlated with the efficiency of normalization using the RPPH1 internal reference gene (Spearman's ρ: 0.793-0.940, p>0.0001), ambiguity (ρ = 0.671, p = 0.029) and misclassification (ρ = 0.769, p = 0.009). A strong genomic matrix effect was observed, and target-singleplex (one target gene in one assay) qPCR was able to appropriately differentiate 2 GCN from 3 GCN at best. The analysis of all GCNs from the 7 qPCR assays using a multiplex approach increased the resolution of differentiation, and produced 98% of GCNs unambiguously, and all of which were in 100% concordance with GCNs measured by Southern blot, MLPA and aCGH. We conclude that the use of an internal (in one assay with the target gene) reference gene, the use of allele-specific primers or probes, and the multiplex approach (in one assay or different assays) are crucial for GCN determination using qPCR or other methods.

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

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

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

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

Influences of rare copy-number variation on human complex traits

The human genome contains hundreds of thousands of regions harboring copy-number variants (CNV). However, the phenotypic effects of most such polymorphisms are unknown because only larger CNVs have been ascertainable from SNP-array data generated by large biobanks. We developed a computational approach leveraging haplotype sharing in biobank cohorts to more sensitively detect CNVs. Applied to UK Biobank, this approach accounted for approximately half of all rare gene inactivation events produced by genomic structural variation. This CNV call set enabled a detailed analysis of associations between CNVs and 56 quantitative traits, identifying 269 independent associations (p < 5 × 10-8) likely to be causally driven by CNVs. Putative target genes were identifiable for nearly half of the loci, enabling insights into dosage sensitivity of these genes and uncovering several gene-trait relationships. These results demonstrate the ability of haplotype-informed analysis to provide insights into the genetic basis of human complex traits.

Omics-informed CNV calls reduce false-positive rates and improve power for CNV-trait associations

Copy-number variations (CNV) are believed to play an important role in a wide range of complex traits, but discovering such associations remains challenging. While whole-genome sequencing (WGS) is the gold-standard approach for CNV detection, there are several orders of magnitude more samples with available genotyping microarray data. Such array data can be exploited for CNV detection using dedicated software (e.g., PennCNV); however, these calls suffer from elevated false-positive and -negative rates. In this study, we developed a CNV quality score that weights PennCNV calls (pCNVs) based on their likelihood of being true positive. First, we established a measure of pCNV reliability by leveraging evidence from multiple omics data (WGS, transcriptomics, and methylomics) obtained from the same samples. Next, we built a predictor of omics-confirmed pCNVs, termed omics-informed quality score (OQS), using only PennCNV software output parameters. Promisingly, OQS assigned to pCNVs detected in close family members was up to 35% higher than the OQS of pCNVs not carried by other relatives (p < 3.0 × 10⁻⁹⁰), outperforming other scores. Finally, in an association study of four anthropometric traits in 89,516 Estonian Biobank samples, the use of OQS led to a relative increase in the trait variance explained by CNVs of up to 56% compared with published quality filtering methods or scores. Overall, we put forward a flexible framework to improve any CNV detection method leveraging multi-omics evidence, applied it to improve PennCNV calls, and demonstrated its utility by improving the statistical power for downstream association analyses.