Global diversity, population stratification, and selection of human copy-number variation

Diversity of U1 Small Nuclear RNAs and Diagnostic Methods for Their Mutations

U1 small nuclear RNA (snRNA) mutations are recurrent non-coding alterations found in various malignancies, yet their identification has proven challenging due to their repetitive nature. We characterized the complex interindividual diversity and genomic architecture of U1 snRNA loci using sequencing data and a pangenome reference. Our analysis uncovered copy number variations and the diversity of single-nucleotide variants in regions not predicted to have significant functional impact. Compared to traditional linear reference-based analyses for mutations, the pangenome graph demonstrated the best accuracy, successfully identifying previously undetectable mutations. This underscores the utility of pangenome graph references for cancer genome research, particularly in repetitive and highly diverse genomic regions. Additionally, we developed mutation detection methods employing targeted capture sequencing, rapid quantitative polymerase chain reaction, and a machine learning approach based on splicing patterns, all exhibiting high precision in identifying U1 snRNA mutations. Our findings elucidate the structural complexity of U1 snRNA loci and establish robust methodologies for precise mutation detection in these regions.

A Systematic Review of the Advances and New Insights into Copy Number Variations in Plant Genomes

Copy number variations (CNVs), as an important structural variant in genomes, are widely present in plants, affecting their phenotype and adaptability. In recent years, CNV research has not only focused on changes in gene copy numbers but has also been linked to complex mechanisms such as genome rearrangements, transposon activity, and environmental adaptation. The advancement in sequencing technologies has made the detection and analysis of CNVs more efficient, not only revealing their crucial roles in plant disease resistance, adaptability, and growth development, but also demonstrating broad application potential in crop improvement, particularly in selective breeding and genomic selection. By studying CNV changes during the domestication process, researchers have gradually recognized the important role of CNVs in plant domestication and evolution. This article reviews the formation mechanisms of CNVs in plants, methods for their detection, their relationship with plant traits, and their applications in crop improvement. It emphasizes future research directions involving the integration of multi-omics to provide new perspectives on the structure and function of plant genomes.

The additional diagnostic yield of long-read sequencing in undiagnosed rare diseases

Long-read sequencing (LRS) is a promising technology positioned to study the significant proportion of rare diseases (RDs) that remain undiagnosed as it addresses many of the limitations of short-read sequencing, detecting and clarifying additional disease-associated variants that may be missed by the current standard diagnostic workflow for RDs. Some key areas where additional diagnostic yields may be realized include: (1) detection and resolution of structural variants (SVs); (2) detection and characterization of tandem repeat expansions; (3) coverage of regions of high sequence similarity; (4) variant phasing; (5) the use of de novo genome assemblies for reference-based or graph genome variant detection; and (6) epigenetic and transcriptomic evaluations. Examples from over 50 studies support that the main areas of added diagnostic yield currently lie in SV detection and characterization, repeat expansion assessment, and phasing (with or without DNA methylation information). Several emerging studies applying LRS in cohorts of undiagnosed RDs also demonstrate that LRS can boost diagnostic yields following negative standard-of-care clinical testing and provide an added yield of 7%-17% following negative short-read genome sequencing. With this evidence of improved diagnostic yield, we discuss the incorporation of LRS into the diagnostic care pathway for undiagnosed RDs, including current challenges and considerations, with the ultimate goal of ending the diagnostic odyssey for countless individuals with RDs.

The impact of the COVID-19 pandemic on alcohol use disorder symptoms: Testing interactions with polygenic risk

Objective: The purpose of this study was to test whether COVID impact interacts with genetic risk (polygenic risk score/PRS) to predict alcohol use disorder (AUD) symptoms. Method: Participants were n = 455 college students (79.6% female, 51% European Ancestry/EA, 24% African Ancestry/AFR, 25% Americas Ancestry/AMER) from a longitudinal study during the initial stage (March-May 2020) of the pandemic. Path models allowed for the examination of PRS and previously identified COVID-19 impact constructs. Results: There was a main effect of the AUD PRS on AUD symptoms within the EA group (β: .165, p < .01). Additionally, food/housing insecurity was predictive in the AMER group (β.295, p < .05), and greater increases in substance use were associated with AUD symptoms for EA (β:.459, p < .001) and AMER groups (β:.468, p < .001). Conclusions: Greater food/housing instability and increases in substance use, as well higher scores on PRS are associated with more AUD symptoms for some ancestral groups within this college sample.

Performance evaluation of structural variation detection using DNBSEQ whole-genome sequencing

BACKGROUND

DNBSEQ platforms have been widely used for variation detection, including single-nucleotide variants (SNVs) and short insertions and deletions (INDELs), which is comparable to Illumina. However, the performance and even characteristics of structural variations (SVs) detection using DNBSEQ platforms are still unclear.

RESULTS

In this study, we assessed the detection of SVs using 40 tools on eight DNBSEQ whole-genome sequencing (WGS) datasets and two Illumina WGS datasets of NA12878. Our findings confirmed that the performance of SVs detection using the same tool on DNBSEQ and Illumina datasets was highly consistent, with correlations greater than 0.80 on metrics of number, size, precision and sensitivity, respectively. Furthermore, we constructed a "DNBSEQ" SV set (4,785 SVs) from the DNBSEQ datasets and an "Illumina" SV set (6,797 SVs) from the Illumina datasets. We found that these two SV sets were highly consistent of SV sites and genomic characteristics, including repetitive regions, GC distribution, difficult-to-sequence regions, and gene features, indicating the robustness of our comparative analysis and highlights the value of both platforms in understanding the genomic context of SVs.

CONCLUSIONS

Our study systematically analyzed and characterized germline SVs detected on WGS datasets sequenced from DNBSEQ platforms, providing a benchmark resource for further studies of SVs using DNBSEQ platforms.

Impacts of ribosomal RNA sequence variation on gene expression and phenotype

Since the framing of the Central Dogma, it has been speculated that physically distinct ribosomes within cells may influence gene expression and cellular physiology. While heterogeneity in ribosome composition has been reported in bacteria, protozoans, fungi, zebrafish, mice and humans, its functional implications remain actively debated. Here, we review recent evidence demonstrating that expression of conserved variant ribosomal DNA (rDNA) alleles in bacteria, mice and humans renders their actively translating ribosome pool intrinsically heterogeneous at the level of ribosomal RNA (rRNA). In this context, we discuss reports that nutrient limitation-induced stress in Escherichia coli leads to changes in variant rRNA allele expression, programmatically altering transcription and cellular phenotype. We highlight that cells expressing ribosomes from distinct operons exhibit distinct drug sensitivities, which can be recapitulated in vitro and potentially rationalized by subtle perturbations in ribosome structure or in their dynamic properties. Finally, we discuss evidence that differential expression of variant rDNA alleles results in different populations of ribosome subtypes within mammalian tissues. These findings motivate further research into the impacts of rRNA heterogeneities on ribosomal function and predict that strategies targeting distinct ribosome subtypes may hold therapeutic potential.This article is part of the discussion meeting issue 'Ribosome diversity and its impact on protein synthesis, development and disease'.

Structural polymorphism and diversity of human segmental duplications

Segmental duplications (SDs) contribute significantly to human disease, evolution and diversity but have been difficult to resolve at the sequence level. We present a population genetics survey of SDs by analyzing 170 human genome assemblies (from 85 samples representing 38 Africans and 47 non-Africans) in which the majority of autosomal SDs are fully resolved using long-read sequence assembly. Excluding the acrocentric short arms and sex chromosomes, we identify 173.2 Mb of duplicated sequence (47.4 Mb not present in the telomere-to-telomere reference) distinguishing fixed from structurally polymorphic events. We find that intrachromosomal SDs are among the most variable, with rare events mapping near their progenitor sequences. African genomes harbor significantly more intrachromosomal SDs and are more likely to have recently duplicated gene families with higher copy numbers than non-African samples. Comparison to a resource of 563 million full-length isoform sequencing reads identifies 201 novel, potentially protein-coding genes corresponding to these copy number polymorphic SDs.

Diversity and consequences of structural variation in the human genome

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

The landscape of structural variation in aye-ayes (Daubentonia madagascariensis)

Aye-ayes (Daubentonia madagascariensis) are one of the 25 most critically endangered primate species in the world. Endemic to Madagascar, their small and highly fragmented populations make them particularly vulnerable to both genetic disease and anthropogenic environmental changes. Over the past decade, conservation genomic efforts have largely focused on inferring and monitoring population structure based on single nucleotide variants to identify and protect critical areas of genetic diversity. However, the recent release of a highly contiguous genome assembly allows, for the first time, for the study of structural genomic variation (deletions, duplications, insertions, and inversions) which are likely to impact a substantial proportion of the species' genome. Based on whole-genome, short-read sequencing data from 14 individuals, >1,000 high-confidence autosomal structural variants were detected, affecting ~240 kb of the aye-aye genome. The majority of these variants (>85%) were deletions shorter than 200 bp, consistent with the notion that longer structural mutations are often associated with strongly deleterious fitness effects. For example, two deletions longer than 850 bp located within disease-linked genes were predicted to impose substantial fitness deficits owing to a resulting frameshift and gene fusion, respectively; whereas several other major effect variants outside of coding regions are likely to impact gene regulatory landscapes. Taken together, this first glimpse into the landscape of structural variation in aye-ayes will enable future opportunities to advance our understanding of the traits impacting the fitness of this endangered species, as well as allow for enhanced evolutionary comparisons across the full primate clade.

Low-pass whole genome sequencing as a cost-effective alternative to chromosomal microarray analysis for low- and middle-income countries

Low-pass whole genome sequencing (LP-WGS) has been applied as alternative method to detect copy number variants (CNVs) in the clinical setting. Compared with chromosomal microarray analysis (CMA), the sequencing-based approach provides a similar resolution of CNV detection at a lower cost. In this study, we assessed the efficiency and reliability of LP-WGS as a more affordable alternative to CMA. A total of 1363 patients with unexplained neurodevelopmental delay/intellectual disability, autism spectrum disorders, and/or multiple congenital anomalies were enrolled. Those patients were referred from 15 nonprofit organizations and university centers located in different states in Brazil. The analysis of LP-WGS at 1x coverage (>50kb) revealed a positive testing result in 22% of the cases (304/1363), in which 219 and 85 correspond to pathogenic/likely pathogenic (P/LP) CNVs and variants of uncertain significance (VUS), respectively. The 16% (219/1363) diagnostic yield observed in our cohort is comparable to the 15%-20% reported for CMA in the literature. The use of commercial software, as demonstrated in this study, simplifies the implementation of the test in clinical settings. Particularly for countries like Brazil, where the cost of CMA presents a substantial barrier to most of the population, LP-WGS emerges as a cost-effective alternative for investigating copy number changes in cytogenetics.

Copy-number variants differ in frequency across genetic ancestry groups

Copy-number variants (CNVs) have been implicated in a variety of neuropsychiatric and cognitive phenotypes. We found that deleterious CNVs are less prevalent in non-European ancestry groups than they are in European ancestry groups of both the UK Biobank (UKBB) and a US replication cohort (SPARK). We also identified specific recurrent CNVs that consistently differ in frequency across ancestry groups in both the UKBB and SPARK. These ancestry-related differences in CNV prevalence present in both an unselected community population and a family cohort enriched with individuals diagnosed with autism spectrum disorder (ASD) strongly suggest that genetic ancestry should be considered when probing associations between CNVs and health outcomes.

The goat pan-genome reveals patterns of gene loss during domestication

BACKGROUND

Unveiling genetic diversity features and understanding the genetic mechanisms of diverse goat phenotypes are pivotal in facilitating the preservation and utilization of these genetic resources. However, the total genetic diversity within a species can't be captured by the reference genome of a single individual. The pan-genome is a collection of all the DNA sequences that occur in a species, and it is expected to capture the total genomic diversity of the specific species.

RESULTS

We constructed a goat pan-genome using map-to-pan assemble based on 813 individuals, including 723 domestic goats and 90 samples from their wild relatives, which presented a broad regional and global representation. In total, 146 Mb sequences and 974 genes were identified as absent from the reference genome (ARS1.2; GCF_001704415.2). We identified 3,190 novel single nucleotide polymorphisms (SNPs) using the pan-genome analysis. These novel SNPs could properly reveal the population structure of domestic goats and their wild relatives. Presence/absence variation (PAV) analysis revealed gene loss and intense negative selection during domestication and improvement.

CONCLUSIONS

Our research highlights the importance of the goat pan-genome in capturing the missing genetic variations. It reveals the changes in genomic architecture during goat domestication and improvement, such as gene loss. This improves our understanding of the evolutionary and breeding history of goats.

Gelada genomes highlight events of gene flow, hybridisation and local adaptation that track past climatic changes

Theropithecus gelada, the last surviving species of this genus, occupy a unique and highly specialised ecological niche in the Ethiopian highlands. A subdivision into three geographically defined populations (Northern, Central and Southern) has been tentatively proposed for this species on the basis of genetic analyses, but genomic data have been investigated only for two of these groups (Northern and Central). Here we combined newly generated whole genome sequences of individuals sampled from the population living south of the East Africa Great Rift Valley with available data from the other two gelada populations to reconstruct the evolutionary history of the species. Integrating genomic and paleoclimatic data we found that gene-flow across populations and with Papio species tracked past climate changes. The isolation and climatic conditions experienced by Southern geladas during the Holocene shaped local diversity and generated diet-related genomic signatures.

Recurrent evolution and selection shape structural diversity at the amylase locus

The adoption of agriculture triggered a rapid shift towards starch-rich diets in human populations1. Amylase genes facilitate starch digestion, and increased amylase copy number has been observed in some modern human populations with high-starch intake2, although evidence of recent selection is lacking3,4. Here, using 94 long-read haplotype-resolved assemblies and short-read data from approximately 5,600 contemporary and ancient humans, we resolve the diversity and evolutionary history of structural variation at the amylase locus. We find that amylase genes have higher copy numbers in agricultural populations than in fishing, hunting and pastoral populations. 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 underwent multiple duplication/deletion events with mutation rates up to more than 10,000-fold the single-nucleotide polymorphism mutation rate, whereas AMY2B gene duplications share a single origin. Using a pangenome-based approach, we infer structural haplotypes across thousands of humans identifying extensively duplicated haplotypes at higher frequency in modern agricultural populations. Leveraging 533 ancient human genomes, we find that duplication-containing haplotypes (with more gene copies than the ancestral haplotype) have rapidly increased in frequency over the past 12,000 years in West Eurasians, suggestive of positive selection. Together, our study highlights the potential effects of the agricultural revolution on human genomes and the importance of structural variation in human adaptation.

Selective Effect of DNA N6-Methyladenosine Modification on Transcriptional Genetic Variations in East Asian Samples

Genetic variations and DNA modification are two common dominant factors ubiquitous across the entire human genome and induce human disease, especially through static genetic variations in DNA or RNA that cause human genetic diseases. DNA N6-methyladenosine (6mA) methylation, as a new epigenetic modification mark, has been widely studied for regulatory biological processes in humans. However, the effect of DNA modification on dynamic transcriptional genetic variations from DNA to RNA has rarely been reported. Here, we identified DNA, RNA and transcriptional genetic variations from Illumina short-read sequencing data in East Asian samples (HX1 and AK1) and detected global DNA 6mA modification using single-molecule, real-time sequencing (SMRT) data. We decoded the effects of DNA 6mA modification on transcriptional genetic variations in East Asian samples and the results were extensively verified in the HeLa cell line. DNA 6mA modification had a stabilized distribution in the East Asian samples and the methylated genes were less likely to mutate than the non-methylated genes. For methylated genes, the 6mA density was positively correlated with the number of variations. DNA 6mA modification had a selective effect on transcriptional genetic variations from DNA to RNA, in which the dynamic transcriptional variations of heterozygous (0/1 to 0/1) and homozygous (1/1 to 1/1) were significantly affected by 6mA modification. The effect of DNA methylation on transcriptional genetic variations provides new insights into the influencing factors of DNA to RNA transcriptional regulation in the central doctrine of molecular biology.

Complex genetic variation in nearly complete human genomes

Diverse sets of complete human genomes are required to construct a pangenome reference and to understand the extent of complex structural variation. Here, we sequence 65 diverse human genomes and build 130 haplotype-resolved assemblies (130 Mbp median continuity), closing 92% of all previous assembly gaps1,2 and reaching telomere-to-telomere (T2T) status for 39% of the chromosomes. We highlight complete sequence continuity of complex loci, including the major histocompatibility complex (MHC), SMN1/SMN2, NBPF8, and AMY1/AMY2, and fully resolve 1,852 complex structural variants (SVs). In addition, we completely assemble and validate 1,246 human centromeres. We find up to 30-fold variation in α-satellite high-order repeat (HOR) array length and characterize the pattern of mobile element insertions into α-satellite HOR arrays. While most centromeres predict a single site of kinetochore attachment, epigenetic analysis suggests the presence of two hypomethylated regions for 7% of centromeres. Combining our data with the draft pangenome reference1 significantly enhances genotyping accuracy from short-read data, enabling whole-genome inference3 to a median quality value (QV) of 45. Using this approach, 26,115 SVs per sample are detected, substantially increasing the number of SVs now amenable to downstream disease association studies.

Diversity in Recombination Hotspot Characteristics and Gene Structure Shape Fine-Scale Recombination Patterns in Plant Genomes

During the meiosis of many eukaryote species, crossovers tend to occur within narrow regions called recombination hotspots. In plants, it is generally thought that gene regulatory sequences, especially promoters and 5' to 3' untranslated regions, are enriched in hotspots, but this has been characterized in a handful of species only. We also lack a clear description of fine-scale variation in recombination rates within genic regions and little is known about hotspot position and intensity in plants. To address this question, we constructed fine-scale recombination maps from genetic polymorphism data and inferred recombination hotspots in 11 plant species. We detected gradients of recombination in genic regions in most species, yet gradients varied in intensity and shape depending on specific hotspot locations and gene structure. To further characterize recombination gradients, we decomposed them according to gene structure by rank and number of exons. We generalized the previously observed pattern that recombination hotspots are organized around the boundaries of coding sequences, especially 5' promoters. However, our results also provided new insight into the relative importance of the 3' end of genes in some species and the possible location of hotspots away from genic regions in some species. Variation among species seemed driven more by hotspot location among and within genes than by differences in size or intensity among species. Our results shed light on the variation in recombination rates at a very fine scale, revealing the diversity and complexity of genic recombination gradients emerging from the interaction between hotspot location and gene structure.

Genome-wide association analyses reveal copy number variant regions associated with reproduction and disease traits in Canadian Holstein cattle

This study aimed to evaluate the impact of copy number variants (CNV) on 13 reproduction and 12 disease traits in Holstein cattle. Intensity signal files containing log R ratio and B allele frequency information from 13,730 Holstein animals genotyped with a 95K SNP panel, and 8,467 Holstein animals genotyped with a 50K SNP panel were used to identify the CNVs. Subsequently, the identified CNVs were validated using whole-genome sequence data from 126 animals, resulting in 870 high-confidence copy number variant regions (CNVR) on 12,131 animals. Out of these, 54 CNVR had frequencies higher than or equal to 1% in the population and were used in the genome-wide association analysis (one CNVR at a time, including the G matrix). Results revealed that 4 CNVR were significantly associated with at least one of the traits analyzed in this study. Specifically, 2 CNVR were associated with 3 reproduction traits (i.e., calf survival, first service to conception, and nonreturn rate), and 2 CNVR were associated with 2 disease traits (i.e., metritis and retained placenta). These CNVR harbored genes implicated in immune response, cellular signaling, and neuronal development, supporting their potential involvement in these traits. Further investigations to unravel the mechanistic and functional implications of these CNVR on the mentioned traits are warranted.

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.

An assessment of the genomic structural variation landscape in Sub-Saharan African populations

Structural variants are responsible for a large part of genomic variation between individuals and play a role in both common and rare diseases. Databases cataloguing structural variants notably do not represent the full spectrum of global diversity, particularly missing information from most African populations. To address this representation gap, we analysed 1,091 high-coverage African genomes, 545 of which are public data sets, and 546 which have been analysed for structural variants for the first time. Variants were called using five different tools and datasets merged and jointly called using SURVIVOR. We identified 67,795 structural variants throughout the genome, with 10,421 genes having at least one variant. Using a conservative overlap in merged data, 6,414 of the structural variants (9.5%) are novel compared to the Database of Genomic Variants. This study contributes to knowledge of the landscape of structural variant diversity in Africa and presents a reliable dataset for potential applications in population genetics and health-related research.

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.

Structural polymorphism and diversity of human segmental duplications

Segmental duplications (SDs) contribute significantly to human disease, evolution, and diversity yet have been difficult to resolve at the sequence level. We present a population genetics survey of SDs by analyzing 170 human genome assemblies where the majority of SDs are fully resolved using long-read sequence assembly. Excluding the acrocentric short arms, we identify 173.2 Mbp of duplicated sequence (47.4 Mbp not present in the telomere-to-telomere reference) distinguishing fixed from structurally polymorphic events. We find that intrachromosomal SDs are among the most variable with rare events mapping near their progenitor sequences. African genomes harbor significantly more intrachromosomal SDs and are more likely to have recently duplicated gene families with higher copy number when compared to non-African samples. A comparison to a resource of 563 million full-length Iso-Seq reads identifies 201 novel, potentially protein-coding genes corresponding to these copy number polymorphic SDs.

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.

Understanding genetic variability: exploring large-scale copy number variants through non-invasive prenatal testing in European populations

Large-scale copy number variants (CNVs) are structural alterations in the genome that involve the duplication or deletion of DNA segments, contributing to genetic diversity and playing a crucial role in the evolution and development of various diseases and disorders, as they can lead to the dosage imbalance of one or more genes. Massively parallel sequencing (MPS) has revolutionized the field of genetic analysis and contributed significantly to routine clinical diagnosis and screening. It offers a precise method for detecting CNVs with exceptional accuracy. In this context, a non-invasive prenatal test (NIPT) based on the sequencing of cell-free DNA (cfDNA) from pregnant women's plasma using a low-coverage whole genome MPS (WGS) approach represents a valuable source for population studies. Here, we analyzed genomic data of 12,732 pregnant women from the Slovak (9,230), Czech (1,583), and Hungarian (1,919) populations. We identified 5,062 CNVs ranging from 200 kbp and described their basic characteristics and differences between the subject populations. Our results suggest that re-analysis of sequencing data from routine WGS assays has the potential to obtain large-scale CNV population frequencies, which are not well known and may provide valuable information to support the classification and interpretation of this type of genetic variation. Furthermore, this could contribute to expanding knowledge about the central European genome without investing in additional laboratory work, as NIPTs are a relatively widely used screening method.

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.

Investigating structural variant, indel and single nucleotide polymorphism differentiation between locally adapted Atlantic salmon populations

Genomic structural variants (SVs) are now recognized as an integral component of intraspecific polymorphism and are known to contribute to evolutionary processes in various organisms. However, they are inherently difficult to detect and genotype from readily available short-read sequencing data, and therefore remain poorly documented in wild populations. Salmonid species displaying strong interpopulation variability in both life history traits and habitat characteristics, such as Atlantic salmon (Salmo salar), offer a prime context for studying adaptive polymorphism, but the contribution of SVs to fine-scale local adaptation has yet to be explored. Here, we performed a comparative analysis of SVs, single nucleotide polymorphisms (SNPs) and small indels (<50 bp) segregating in the Romaine and Puyjalon salmon, two putatively locally adapted populations inhabiting neighboring rivers (Québec, Canada) and showing pronounced variation in life history traits, namely growth, fecundity, and age at maturity and smoltification. We first catalogued polymorphism using a hybrid SV characterization approach pairing both short- (16X) and long-read sequencing (20X) for variant discovery with graph-based genotyping of SVs across 60 salmon genomes, along with characterization of SNPs and small indels from short reads. We thus identified 115,907 SVs, 8,777,832 SNPs and 1,089,321 short indels, with SVs covering 4.8 times more base pairs than SNPs. All three variant types revealed a highly congruent population structure and similar patterns of F ST and density variation along the genome. Finally, we performed outlier detection and redundancy analysis (RDA) to identify variants of interest in the putative local adaptation of Romaine and Puyjalon salmon. Genes located near these variants were enriched for biological processes related to nervous system function, suggesting that observed variation in traits such as age at smoltification could arise from differences in neural development. This study therefore demonstrates the feasibility of large-scale SV characterization and highlights its relevance for salmonid population genomics.

A pan-cancer landscape of pathogenic somatic copy number variations

OBJECTIVE

Copy number variations (CNVs) play crucial roles in physiological and pathological processes, including cancer. However, the functional implications of somatic CNVs in tumor progression and evolution remain unclear. This study focuses on identifying CNV alterations with high pathogenic potential that drive and sustain tumorigenesis, distinguishing them from passenger alterations that accumulate during tumor growth. Our goal is to explore the variability of CNVs across different tumor types and infer their impact on tumor cell functions.

METHODS

Starting from 7352 copy number profiles across 33 different cancer types, we infer the pathogenicity of each CNV and perform both intra- and inter-tumor analyses to predict the functional impact of different genomic patterns. We evaluate the actionability of genes belonging to altered regions and we correlate the presence of pathogenic regions with genome instability patterns and patients' survival.

RESULTS

Our analysis uncovered large heterogeneity among different tumors suggesting in many cases distinct genetic drivers of tumorigenesis. Recurrent genomic alterations frequently coincide with dysfunctional homologous recombination pathways and negative regulation of the immune system. In certain tumors, the number of pathogenic CNVs emerged as a prognostic biomarker, highlighting their significance in cancer progression.

CONCLUSION

This study contributes to elucidate the functional impact of pathogenic CNVs in tumor progression and sheds light on their potential as prognostic markers in specific cancer types.

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

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

Identification of copy number variation in Tibetan sheep using whole genome resequencing reveals evidence of genomic selection

BACKGROUND

Copy number variation (CNV) is an important source of structural variation in the mammalian genome. CNV assays present a new method to explore the genomic diversity of environmental adaptations in animals and plants and genes associated with complex traits. In this study, the genome-wide CNV distribution characteristics of 20 Tibetan sheep from two breeds (10 Oula sheep and 10 Panou sheep) were analysed using whole-genome resequencing to investigate the variation in the genomic structure of Tibetan sheep during breeding.

RESULTS

CNVs were detected using CNVnator, and the overlapping regions of CNVs between individual sheep were combined. Among them, a total of 60,429 CNV events were detected between the indigenous sheep breed (Oula) and the synthetic sheep breed (Panou). After merging the overlapping CNVs, 4927 CNV regions (CNVRs) were finally obtained. Of these, 4559 CNVRs were shared by two breeds, and there were 368 differential CNVRs. Deletion events have a higher percentage of occurrences than duplication events. Functional enrichment analysis showed that the shared CNVRs were significantly enriched in 163 GO terms and 62 KEGG pathways, which were mainly associated with organ development, neural regulation, immune regulation, digestion and metabolism. In addition, 140 QTLs overlapped with some of the CNVRs at more than 1 kb, such as average daily gain QTL, body weight QTL, and total lambs born QTL. Many of the CNV-overlapping genes such as PPP3CA, SSTR1 and FASN, overlap with the average daily weight gain and carcass weight QTL regions. Moreover, VST analysis showed that XIRP2, ABCB1, CA1, ASPA and EEF2 differed significantly between the synthetic breed and local sheep breed. The duplication of the ABCB1 gene may be closely related to adaptation to the plateau environment in Panou sheep, which deserves further study. Additionally, cluster analysis, based on all individuals, showed that the CNV clustering could be divided into two origins, indicating that some Tibetan sheep CNVs are likely to arise independently in different populations and contribute to population differences.

CONCLUSIONS

Collectively, we demonstrated the genome-wide distribution characteristics of CNVs in Panou sheep by whole genome resequencing. The results provides a valuable genetic variation resource and help to understand the genetic characteristics of Tibetan sheep. This study also provides useful information for the improvement and breeding of Tibetan sheep in the future.

Structural variation of the coding and non-coding human pharmacogenome

Genetic variants in drug targets and genes encoding factors involved in drug absorption, distribution, metabolism and excretion (ADME) can have pronounced impacts on drug pharmacokinetics, response, and toxicity. While the landscape of genetic variability at the level of single nucleotide variants (SNVs) has been extensively studied in these pharmacogenetic loci, their structural variation is only poorly understood. Thus, we systematically analyzed the genetic structural variability across 908 pharmacogenes (344 ADME genes and 564 drug targets) based on publicly available whole genome sequencing data from 10,847 unrelated individuals. Overall, we extracted 14,984 distinct structural variants (SVs) ranging in size from 50 bp to 106 Mb. Each individual harbored on average 10.3 and 1.5 SVs with putative functional effects that affected the coding regions of ADME genes and drug targets, respectively. In addition, by cross-referencing pharmacogenomic SVs with experimentally determined binding data of 224 transcription factors across 130 cell types, we identified 1276 non-coding SVs that overlapped with gene regulatory elements. Based on these data, we estimate that non-coding structural variants account for 22% of the genetically encoded pharmacogenomic variability. Combined, these analyses provide the first comprehensive map of structural variability across pharmacogenes, derive estimates for the functional impact of non-coding SVs and incentivize the incorporation of structural genomic data into personalized drug response predictions.

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.

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.

Intensified glycemic control by HbA1c for patients with coronary heart disease and Type 2 diabetes: a review of findings and conclusions

The occurrence and development of coronary heart disease (CHD) are closely linked to fluctuations in blood glucose levels. While the efficacy of intensified treatment guided by HbA1c levels remains uncertain for individuals with diabetes and CHD, this review summarizes the findings and conclusions regarding HbA1c in the context of CHD. Our review showed a curvilinear correlation between regulated level of HbA1c and therapeutic effectiveness of intensified glycemic control among patients with type 2 diabetes and coronary heart disease. It is necessary to optimize the dynamic monitoring indicators of HbA1c, combine genetic profiles, haptoglobin phenotypes for example and select more suitable hypoglycemic drugs to establish more appropriate glucose-controlling guideline for patients with CHD at different stage of diabetes.

SVDSS: structural variation discovery in hard-to-call genomic regions using sample-specific strings from accurate long reads

Structural variants (SVs) account for a large amount of sequence variability across genomes and play an important role in human genomics and precision medicine. Despite intense efforts over the years, the discovery of SVs in individuals remains challenging due to the diploid and highly repetitive structure of the human genome, and by the presence of SVs that vastly exceed sequencing read lengths. However, the recent introduction of low-error long-read sequencing technologies such as PacBio HiFi may finally enable these barriers to be overcome. Here we present SV discovery with sample-specific strings (SVDSS)-a method for discovery of SVs from long-read sequencing technologies (for example, PacBio HiFi) that combines and effectively leverages mapping-free, mapping-based and assembly-based methodologies for overall superior SV discovery performance. Our experiments on several human samples show that SVDSS outperforms state-of-the-art mapping-based methods for discovery of insertion and deletion SVs in PacBio HiFi reads and achieves notable improvements in calling SVs in repetitive regions of the genome.

Genome Analysis Using Whole-Exome Sequencing of Non-Syndromic Cleft Lip and/or Palate from Malagasy Trios Identifies Variants Associated with Cilium-Related Pathways and Asian Genetic Ancestry

Background: Orofacial clefts (OFCs) are common congenital disabilities that can occur as isolated non-syndromic events or as part of Mendelian syndromes. OFC risk factors vary due to differences in regional environmental exposures, genetic variants, and ethnicities. In recent years, significant progress has been made in understanding OFCs, due to advances in sequencing and genotyping technologies. Despite these advances, very little is known about the genetic interplay in the Malagasy population. Methods: Here, we performed high-resolution whole-exome sequencing (WES) on non-syndromic cleft lip with or without palate (nCL/P) trios in the Malagasy population (78 individuals from 26 families (trios)). To integrate the impact of genetic ancestry admixture, we computed both global and local ancestries. Results: Participants demonstrated a high percentage of both African and Asian admixture. We identified damaging variants in primary cilium-mediated pathway genes WNT5B (one family), GPC4 (one family), co-occurrence in MSX1 (five families), WDR11 (one family), and tubulin stabilizer SEPTIN9 (one family). Furthermore, we identified an autosomal homozygous damaging variant in PHGDH (one family) gene that may impact metabiotic activity. Lastly, all variants were predicted to reside on local Asian genetic ancestry admixed alleles. Conclusion: Our results from examining the Malagasy genome provide limited support for the hypothesis that germline variants in primary cilia may be risk factors for nCL/P, and outline the importance of integrating local ancestry components better to understand the multi-ethnic impact on nCL/P.

Multi-Omics Studies in Historically Excluded Populations: The Road to Equity

Over the past few decades, genomewide association studies (GWASs) have identified the specific genetics variants contributing to many complex diseases by testing millions of genetic variations across the human genome against a variety of phenotypes. However, GWASs are limited in their ability to uncover mechanistic insight given that most significant associations are found in non-coding region of the genome. Furthermore, the lack of diversity in studies has stymied the advance of precision medicine for many historically excluded populations. In this review, we summarize most popular multi-omics approaches (genomics, transcriptomics, proteomics, and metabolomics) related to precision medicine and highlight if diverse populations have been included and how their findings have advance biological understanding of disease and drug response. New methods that incorporate local ancestry have been to improve the power of GWASs for admixed populations (such as African Americans and Latinx). Because most signals from GWAS are in the non-coding region, other machine learning and omics approaches have been developed to identify the potential causative single-nucleotide polymorphisms and genes that explain these phenotypes. These include polygenic risk scores, expression quantitative trait locus mapping, and transcriptome-wide association studies. Analogous protein methods, such as proteins quantitative trait locus mapping, proteome-wide association studies, and metabolomic approaches provide insight into the consequences of genetic variation on protein abundance. Whereas, integrated multi-omics studies have improved our understanding of the mechanisms for genetic association, we still lack the datasets and cohorts for historically excluded populations to provide equity in precision medicine and pharmacogenomics.

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.

Accuracy benchmark of the GeneMind GenoLab M sequencing platform for WGS and WES analysis

Background

GenoLab M is a recently developed next-generation sequencing (NGS) platform from GeneMind Biosciences. To establish the performance of GenoLab M, we present the first report to benchmark and compare the WGS and WES sequencing data of the GenoLab M sequencer to NovaSeq 6000 and NextSeq 550 platform in various types of analysis. For WGS, thirty-fold sequencing from Illumina NovaSeq platform and processed by GATK pipeline is currently considered as the golden standard. Thus this dataset is generated as a benchmark reference in this study.

Results

GenoLab M showed an average of 94.62% of Q20 percentage for base quality, while the NovaSeq was slightly higher at 96.97%. However, GenoLab M outperformed NovaSeq or NextSeq at a duplication rate, suggesting more usable data after deduplication. For WGS short variant calling, GenoLab M showed significant accuracy improvement over the same depth dataset from NovaSeq, and reached similar accuracy to NovaSeq 33X dataset with 22x depth. For 100X WES, the F-score and Precision in GenoLab M were higher than NovaSeq or NextSeq, especially for InDel calling.

Conclusions

GenoLab M is a promising NGS platform for high-performance WGS and WES applications. For WGS, 22X depth in the GenoLab M sequencing platform offers a cost-effective alternative to the current mainstream 33X depth on Illumina.

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.

Role of GSTM1 in Hypertension, CKD, and Related Diseases across the Life Span

Over 20 years after the introduction of angiotensin-converting enzyme inhibitors and angiotensin receptor blockers, CKD remains a major public health burden with limited therapeutic options to halt or slow kidney disease progression at all ages. The consensus is that oxidative stress contributes to CKD development and progression. Yet, to date, there is no clear evidence that broad use of antioxidant therapy provides a beneficial effect in CKD. Understanding the specific pathophysiologic mechanisms in those who are genetically most susceptible to oxidative stress is a crucial step to inform therapy in an individualized medicine approach, considering differing exposures and risks across the life span. Glutathione-S-transferase μ 1 (GSTM1) is a phase 2 enzyme involved in inactivation of reactive oxygen species and metabolism of xenobiotics. In particular, those with the highly prevalent GSTM1 null genotype (GSTM1[0/0]) may be more susceptible to kidney disease progression, due to impaired capacity to handle the increased oxidative stress burden in disease states, and might specifically benefit from therapy that targets the redox imbalance mediated by loss of the GSTM1 enzyme. In this review, we will discuss the studies implicating the role of GSTM1 deficiency in kidney and related diseases from experimental rodent models to humans, from the prenatal period through senescence, and the potential underlying mechanism.

PGG.SV: a whole-genome-sequencing-based structural variant resource and data analysis platform

Structural variations (SVs) play important roles in human evolution and diseases, but there is a lack of data resources concerning representative samples, especially for East Asians. Taking advantage of both next-generation sequencing and third-generation sequencing data at the whole-genome level, we developed the database PGG.SV to provide a practical platform for both regionally and globally representative structural variants. In its current version, PGG.SV archives 584 277 SVs obtained from whole-genome sequencing data of 6048 samples, including 1030 long-read sequencing genomes representing 177 global populations. PGG.SV provides (i) high-quality SVs with fine-scale and precise genomic locations in both GRCh37 and GRCh38, covering underrepresented SVs in existing sequencing and microarray data; (ii) hierarchical estimation of SV prevalence in geographical populations; (iii) informative annotations of SV-related genes, potential functions and clinical effects; (iv) an analysis platform to facilitate SV-based case-control association studies and (v) various visualization tools for understanding the SV structures in the human genome. Taken together, PGG.SV provides a user-friendly online interface, easy-to-use analysis tools and a detailed presentation of results. PGG.SV is freely accessible via https://www.biosino.org/pggsv.

Merging morphological and genetic evidence to assess hybridization in Western Eurasian late Pleistocene hominins

Previous scientific consensus saw human evolution as defined by adaptive differences (behavioural and/or biological) and the emergence of Homo sapiens as the ultimate replacement of non-modern groups by a modern, adaptively more competitive group. However, recent research has shown that the process underlying our origins was considerably more complex. While archaeological and fossil evidence suggests that behavioural complexity may not be confined to the modern human lineage, recent palaeogenomic work shows that gene flow between distinct lineages (for example, Neanderthals, Denisovans, early H. sapiens) occurred repeatedly in the late Pleistocene, probably contributing elements to our genetic make-up that might have been crucial to our success as a diverse, adaptable species. Following these advances, the prevailing human origins model has shifted from one of near-complete replacement to a more nuanced view of partial replacement with considerable reticulation. Here we provide a brief introduction to the current genetic evidence for hybridization among hominins, its prevalence in, and effects on, comparative mammal groups, and especially how it manifests in the skull. We then explore the degree to which cranial variation seen in the fossil record of late Pleistocene hominins from Western Eurasia corresponds with our current genetic and comparative data. We are especially interested in understanding the degree to which skeletal data can reflect admixture. Our findings indicate some correspondence between these different lines of evidence, flag individual fossils as possibly admixed, and suggest that different cranial regions may preserve hybridization signals differentially. We urge further studies of the phenotype to expand our ability to detect the ways in which migration, interaction and genetic exchange have shaped the human past, beyond what is currently visible with the lens of ancient DNA.

Genome-wide analysis of CNVs in three populations of Tibetan sheep using whole-genome resequencing

Copy number variation (CNV), an important source of genomic structural variation, can disturb genetic structure, dosage, regulation and expression, and is associated with phenotypic diversity and adaptation to local environments in mammals. In the present study, 24 resequencing datasets were used to characterize CNVs in three ecotypic populations of Tibetan sheep and assess CNVs related to domestication and adaptation in Qinghai-Tibetan Plateau. A total of 87,832 CNV events accounting for 0.3% of the sheep genome were detected. After merging the overlapping CNVs, 2777 CNV regions (CNVRs) were obtained, among which 1098 CNVRs were shared by the three populations. The average length of these CNVRs was more than 3 kb, and duplication events were more frequent than deletions. Functional analysis showed that the shared CNVRs were significantly enriched in 56 GO terms and 18 KEGG pathways that were mainly concerned with ABC transporters, olfactory transduction and oxygen transport. Moreover, 188 CNVRs overlapped with 97 quantitative trait loci (QTLs), such as growth and carcass QTLs, immunoglobulin QTLs, milk yield QTLs and fecal egg counts QTLs. PCDH15, APP and GRID2 overlapped with body weight QTLs. Furthermore, Vst analysis showed that RUNX1, LOC101104348, LOC105604082 and PAG11 were highly divergent between Highland-type Tibetan Sheep (HTS) and Valley-type Tibetan sheep (VTS), and RUNX1 and LOC101111988 were significantly differentiated between VTS and Oura-type Tibetan sheep (OTS). The duplication of RUNX1 may facilitate the hypoxia adaptation of OTS and HTS in Qinghai-Tibetan Plateau, which deserves further research in detail. In conclusion, for the first time, we represented the genome-wide distribution characteristics of CNVs in Tibetan sheep by resequencing, and provided a valuable genetic variation resource, which will facilitate the elucidation of the genetic basis underlying the distinct phenotypic traits and local adaptation of Tibetan sheep.

Copy Number Variants in Two Northernmost Cattle Breeds Are Related to Their Adaptive Phenotypes

Copy number variations (CNVs) are genomic structural variants with potential functional and evolutionary effects on phenotypes. In this study, we report the identification and characterization of CNVs from the whole-genome resequencing data of two northernmost cattle breeds from Russia: the Yakut and Kholmogory cattle and their phylogenetically most related breeds, Hanwoo and Holstein, respectively. Comparisons of the CNV regions (CNVRs) among the breeds led to the identification of breed-specific CNVRs shared by cold-adapted Kholmogory and Yakut cattle. An investigation of their overlap with genes, regulatory domains, conserved non-coding elements (CNEs), enhancers, and quantitative trait loci (QTLs) was performed to further explore breed-specific biology and adaptations. We found CNVRs enriched for gene ontology terms related to adaptation to environments in both the Kholmogory and Yakut breeds and related to thermoregulation specifically in Yakut cattle. Interestingly, the latter has also been supported when exploring the enrichment of breed-specific CNVRs in the regulatory domains and enhancers, CNEs, and QTLs implying the potential contribution of CNVR to the Yakut and Kholmogory cattle breeds’ adaptation to a harsh environment.

Assembly of a pangenome for global cattle reveals missing sequences and novel structural variations, providing new insights into their diversity and evolutionary history

A cattle pangenome representation was created based on the genome sequences of 898 cattle representing 57 breeds. The pangenome identified 83 Mb of sequence not found in the cattle reference genome, representing 3.1% novel sequence compared with the 2.71-Gb reference. A catalog of structural variants developed from this cattle population identified 3.3 million deletions, 0.12 million inversions, and 0.18 million duplications. Estimates of breed ancestry and hybridization between cattle breeds using insertion/deletions as markers were similar to those produced by single nucleotide polymorphism-based analysis. Hundreds of deletions were observed to have stratification based on subspecies and breed. For example, an insertion of a Bov-tA1 repeat element was identified in the first intron of the APPL2 gene and correlated with cattle breed geographic distribution. This insertion falls within a segment overlapping predicted enhancer and promoter regions of the gene, and could affect important traits such as immune response, olfactory functions, cell proliferation, and glucose metabolism in muscle. The results indicate that pangenomes are a valuable resource for studying diversity and evolutionary history, and help to delineate how domestication, trait-based breeding, and adaptive introgression have shaped the cattle genome.

Polishing copy number variant calls on exome sequencing data via deep learning

Accurate and efficient detection of copy number variants (CNVs) is of critical importance owing to their significant association with complex genetic diseases. Although algorithms that use whole-genome sequencing (WGS) data provide stable results with mostly valid statistical assumptions, copy number detection on whole-exome sequencing (WES) data shows comparatively lower accuracy. This is unfortunate as WES data are cost-efficient, compact, and relatively ubiquitous. The bottleneck is primarily due to the noncontiguous nature of the targeted capture: biases in targeted genomic hybridization, GC content, targeting probes, and sample batching during sequencing. Here, we present a novel deep learning model, DECoNT, which uses the matched WES and WGS data, and learns to correct the copy number variations reported by any off-the-shelf WES-based germline CNV caller. We train DECoNT on the 1000 Genomes Project data, and we show that we can efficiently triple the duplication call precision and double the deletion call precision of the state-of-the-art algorithms. We also show that our model consistently improves the performance independent of (1) sequencing technology, (2) exome capture kit, and (3) CNV caller. Using DECoNT as a universal exome CNV call polisher has the potential to improve the reliability of germline CNV detection on WES data sets.

Inferring Signatures of Positive Selection in Whole-Genome Sequencing Data: An Overview of Haplotype-Based Methods

Signatures of positive selection in the genome are a characteristic mark of adaptation that can reveal an ongoing, recent, or ancient response to environmental change throughout the evolution of a population. New sources of food, climate conditions, and exposure to pathogens are only some of the possible sources of selective pressure, and the rise of advantageous genetic variants is a crucial determinant of survival and reproduction. In this context, the ability to detect these signatures of selection may pinpoint genetic variants that are responsible for a significant change in gene regulation, gene expression, or protein synthesis, structure, and function. This review focuses on statistical methods that take advantage of linkage disequilibrium and haplotype determination to reveal signatures of positive selection in whole-genome sequencing data, showing that they emerge from different descriptions of the same underlying event. Moreover, considerations are provided around the application of these statistics to different species, their suitability for ancient DNA, and the usefulness of discovering variants under selection for biomedicine and public health in an evolutionary medicine framework.

Copy Number Analyses Identified a Novel Gene: APOBEC3A Related to Lipid Metabolism in the Pathogenesis of Preeclampsia

Background

Preeclampsia is a heterogeneous and complex disease with its pathogenesis mechanism not fully elucidated. A certain subset of patients with preeclampsia exhibit disturbances in lipid metabolism before clinical symptoms. Moreover, there is a tendency for preeclampsia to run in families. Whether genetic factors play a role in abnormal lipid metabolism during the incidence of preeclampsia has not been well investigated.

Methods

Preeclampsia patients (n = 110) and healthy age- and gravidity-matched pregnant women (n = 110) were enrolled in this study. Peripheral blood specimens were used for genomic analysis (n = 10/group) or laboratory validation (n = 100/group). We retrospectively obtained the baseline clinical characteristics of 68 preeclampsia patients and 107 controls in early pregnancy (12–14 gestational weeks). Correlation analyses between differential genes and baseline lipid profiles were performed to identify candidate genes. In vitro and in vivo gain-of-function models were constructed with lentivirus and adeno-associated virus systems, respectively, to investigate the role of candidate genes in regulating lipid metabolism and the development of preeclampsia.

Results

We observed that preeclampsia patients exhibited significantly elevated plasma TC (P = 0.037) and TG (P < 0.001) levels and increased body mass index (P = 0.006) before the disease onset. Within the region of 27 differential copy number variations, six genes potentially connected with lipid metabolism were identified. The aberrant copies of APOBEC3A, APOBEC3A_B, BTNL3, and LMF1 between preeclampsia patients and controls were verified by quantitative polymerase chain reaction. Especially, APOBEC3A showed a significant positive correlation with TC (P < 0.001) and LDL (P = 0.048) in early pregnancy. Then, our in vitro data revealed that overexpression of APOBEC3A disrupted lipid metabolism in HepG2 cells and affected both cholesterol and fatty acid metabolisms. Finally, in vivo study in a hepatic-specific overexpressed APOBEC3A mouse model revealed abnormal parameters related to lipid metabolism. Pregnant mice of the same model at the end of pregnancy showed changes related to preeclampsia-like symptoms, such as increases in sFlt-1 levels and sFlt-1/PLGF ratios in the placenta and decreases in fetal weight.

Conclusion

Our findings established a new link between genetics and lipid metabolism in the pathogenesis of preeclampsia and could contribute to a better understanding of the molecular mechanisms of preeclampsia.

Molecular Evolutionary Rate Predicts Intraspecific Genetic Polymorphism and Species-Specific Selection

It is unknown what determines genetic diversity and how genetic diversity is associated with various biological traits. In this work, we provide insight into these issues. By comparing genetic variation of 14,671 mammalian gene trees with thousands of individual human, chimpanzee, gorilla, mouse, and dog/wolf genomes, we found that intraspecific genetic diversity can be predicted by long-term molecular evolutionary rates rather than de novo mutation rates. This relationship was established during the early stage of mammalian evolution. Moreover, we developed a method to detect fluctuations of species-specific selection on genes based on the deviations of intraspecific genetic diversity predicted from long-term rates. We showed that the evolution of epithelial cells, rather than connective tissue, mainly contributed to morphological evolution of different species. For humans, evolution of the immune system and selective sweeps caused by infectious diseases are the most representative examples of adaptive evolution.