An integrated map of structural variation in 2,504 human genomes

Identification of novel compound heterozygous variants of the ALMS1 gene in a child with Alström syndrome by whole genome sequencing

BACKGROUND

Alström syndrome (ALMS), a rare recessively inherited ciliopathy caused by mutations in ALMS1, is characterized by retinal dystrophy, childhood obesity, sensorineural hearing loss, and type 2 diabetes mellitus. The majority of pathogenic variants in ALMS1 are nonsense and frameshift mutations, which would lead to premature protein truncation, whereas copy number variants are seldom reported.

METHODS

Herein, we present a 10-year-old Chinese girl with ALMS. The potential causative genetic variant was confirmed through whole genome sequencing, quantitative real-time PCR analysis, and Sanger sequencing. Additionally, breakpoint analysis was performed to determine the exact breakpoint site of the large deletion and elucidate its probable formation mechanism.

RESULTS

The patient had a cor triatriatum sinister (CTS) structure. Genetic analysis identified novel compound heterozygous variants in the patient, consisting of a frameshift variant c.4414_4415delGT (p.V1472Nfs*26) in ALMS1 and a novel large deletion at chr2:73,612,355-73,626,339, which encompasses exon 1 of the ALMS1 gene. Moreover, breakpoint analysis revealed that the large deletion probably formed through the microhomology-mediated end joining (MMEJ) mechanism due to the 6-bp microhomologies (TCCTTC) observed at both ends of the breakpoints.

CONCLUSIONS

In this study, novel compound heterozygous variants in the ALMS1 gene were identified in an ALMS patient with a CTS structure. The molecular confirmation of these variants expands the mutational spectrum of ALMS1, while the manifestation of ALMS in the patient provides additional clinical insights into this syndrome.

Identification and functional characterisation of DNA methylation differences between East- and West-originating Finns

Eastern and Western Finns show a striking difference in coronary heart disease-related mortality; genetics is a known contributor for this discrepancy. Here, we discuss the potential role of DNA methylation in mediating the discrepancy in cardiometabolic disease-risk phenotypes between the sub-populations. We used data from the Young Finns Study (n = 969) to compare the genome-wide DNA methylation levels of East- and West-originating Finns. We identified 21 differentially methylated loci (FDR < 0.05; Δβ >2.5%) and 7 regions (smoothed FDR < 0.05; CpGs ≥ 5). Methylation at all loci and regions associates with genetic variants (p < 5 × 10-8). Independently of genetics, methylation at 11 loci and 4 regions associates with transcript expression, including genes encoding zinc finger proteins. Similarly, methylation at 5 loci and 4 regions associates with cardiometabolic disease-risk phenotypes including triglycerides, glucose, cholesterol, as well as insulin treatment. This analysis was also performed in LURIC (n = 2371), a German cardiovascular patient cohort, and results replicated for the association of methylation at cg26740318 and DMR_11p15 with diabetes-related phenotypes and methylation at DMR_22q13 with triglyceride levels. Our results indicate that DNA methylation differences between East and West Finns may have a functional role in mediating the cardiometabolic disease discrepancy between the sub-populations.

Comprehensive genetic analysis uncovers the mutational spectrum of MFRP and its genotype-phenotype correlation in a large cohort of Chinese microphthalmia patients

PURPOSE

Microphthalmia is a severe congenital ocular disease featured by abnormal ocular development. The aim of this study was to detail the genetic and clinical characteristics of a large cohort of Chinese patients with microphthalmia related to MFRP variants, focusing on uncovering genotype-phenotype correlations.

METHODS

Fifty microphthalmia patients from 44 unrelated Chinese families were recruited. Whole-exome sequencing (WES) was conducted to analyze the coding regions and adjacent intronic regions of MFRP. Axial lengths (AL) were measured for all probands and available family members. Protein structures of mutations with high frequency in our cohort were predicted. The genotype-phenotype correlations were explored by statistical analysis.

RESULTS

Sixteen MFRP variants were detected in 17 families, accounting for 38.64 % of all microphthalmia families. There were 9 novel mutations (c.427+1G>C, c.428-2A>C, c.561_575del:p.A188_E192del, c.836G>A:p.C279Y, c.1010_1021del:p.H337_E340del:p.Y479*, c.1516_1517del:p.S506Pfs*66, c.1561T>G:p.C521G, c.1616G>A:p.R539H, and c.1735C>T:p.P579S) and six previously reported variants in MFRP, with p.E496K and p.H337_E340del being highly frequent, found in eight (47.06 %) and two families (11.76 %), respectively. Seven variants (43.75 %) were located in the C-terminal cysteine-rich frizzled-related domain (CRD) (7/16, 43.75 %). Protein prediction implicated p.E496K and p.H337_E340del mutations might lead to a destabilization of the MFRP protein. The average AL of all 42 eyes was 16.02 ± 1.05 mm, and 78.36 % of eyes with AL < 16 mm harbored p.E496K variant. Twenty-six eyes with variant variant had shorter AL than that of the other 16 eyes without this variant (p = 0.006), highlighting a novel genotype-phenotype correlation.

CONCLUSIONS

In this largest cohort of Chinese patients with microphthalmia, the 9 novel variants, high frequency of p.E496W, and mutation hotspots in CRD reveals unique insights into the MFRP mutation spectrum among Chinese patients, indicating ethnic variability. A new genotype-phenotype correlation that p.E496K variant associated with a shorter AL is unveiled. Our findings enhance the current knowledge of MFRP-associated microphthalmia and provide valuable information for prenatal diagnosis as well as future therapy.

Genome-Wide and Transcriptome-Wide Association Studies on Northern New England and Ohio Amyotrophic Lateral Sclerosis Cohorts

Background and Objectives

Amyotrophic lateral sclerosis (ALS) is an age-associated, fatal neurodegenerative disorder causing progressive paralysis and respiratory failure. The genetic architecture of ALS is still largely unknown.

Methods

We performed a genome-wide association study (GWAS) and transcriptome-wide association study (TWAS) to understand genetic risk factors for ALS using a population-based case-control study of 435 ALS cases and 279 controls from Northern New England and Ohio. Single nucleotide polymorphism (SNP) genotyping was conducted using the Illumina NeuroChip array. Odds ratios were estimated using covariate-adjusted logistic regression. We also performed a genome-wide SNP-smoking interaction screening. TWAS analyses used PrediXcan to estimate associations between predicted gene expression levels across 15 tissues (13 brain tissues, skeletal muscle, and whole blood) and ALS risk.

Results

GWAS analyses identified the p.A382T missense variant (rs367543041, p = 3.95E-6) in the TARDBP gene, which has previously been reported in association with increased ALS risk and was found to share a close affinity with the Sardinian haplotype. Both GWAS and TWAS analyses suggested that ZNF235 is associated with decreased ALS risk.

Discussion

Our results support the need for future evaluation to clarify the role of these potential genetic risk factors for ALS and to understand genetic susceptibility to environmental risk factors.

Retrotransposon-driven environmental regulation of FLC leads to adaptive response to herbicide

The mobilization of transposable elements is a potent source of mutations. In plants, several stransposable elements respond to external cues, fuelling the hypothesis that natural transposition can create environmentally sensitive alleles for adaptation. Here we report on the detailed characterization of a retrotransposon insertion within the first intron of the Arabidopsis floral-repressor gene FLOWERING LOCUS C (FLC) and the discovery of its role for adaptation. The insertion mutation augments the environmental sensitivity of FLC by affecting the balance between coding and non-coding transcripts in response to stress, thus expediting flowering. This balance is modulated by DNA methylation and orchestrated by IBM2, a factor involved in the processing of intronic heterochromatic sequences. The stress-sensitive allele of FLC has spread across populations subjected to recurrent chemical weeding, and we show that retrotransposon-driven acceleration of the life cycle represents a rapid response to herbicide application. Our work provides a compelling example of a transposable element-driven environmentally sensitive allele that confers an adaptive response in nature.

A cell type-aware framework for nominating non-coding variants in Mendelian regulatory disorders

Unsolved Mendelian cases often lack obvious pathogenic coding variants, suggesting potential non-coding etiologies. Here, we present a single cell multi-omic framework integrating embryonic mouse chromatin accessibility, histone modification, and gene expression assays to discover cranial motor neuron (cMN) cis-regulatory elements and subsequently nominate candidate non-coding variants in the congenital cranial dysinnervation disorders (CCDDs), a set of Mendelian disorders altering cMN development. We generate single cell epigenomic profiles for ~86,000 cMNs and related cell types, identifying ~250,000 accessible regulatory elements with cognate gene predictions for ~145,000 putative enhancers. We evaluate enhancer activity for 59 elements using an in vivo transgenic assay and validate 44 (75%), demonstrating that single cell accessibility can be a strong predictor of enhancer activity. Applying our cMN atlas to 899 whole genome sequences from 270 genetically unsolved CCDD pedigrees, we achieve significant reduction in our variant search space and nominate candidate variants predicted to regulate known CCDD disease genes MAFB, PHOX2A, CHN1, and EBF3 - as well as candidates in recurrently mutated enhancers through peak- and gene-centric allelic aggregation. This work delivers non-coding variant discoveries of relevance to CCDDs and a generalizable framework for nominating non-coding variants of potentially high functional impact in other Mendelian disorders.

Structural genomic variation and behavioral interactions underpin a balanced sexual mimicry polymorphism

How phenotypic diversity originates and persists within populations are classic puzzles in evolutionary biology. While balanced polymorphisms segregate within many species, it remains rare for both the genetic basis and the selective forces to be known, leading to an incomplete understanding of many classes of traits under balancing selection. Here, we uncover the genetic architecture of a balanced sexual mimicry polymorphism and identify behavioral mechanisms that may be involved in its maintenance in the swordtail fish Xiphophorus birchmanni. We find that ∼40% of X. birchmanni males develop a "false gravid spot," a melanic pigmentation pattern that mimics the "pregnancy spot" associated with sexual maturity in female live-bearing fish. Using genome-wide association mapping, we detect a single intergenic region associated with variation in the false gravid spot phenotype, which is upstream of kitlga, a melanophore patterning gene. By performing long-read sequencing within and across populations, we identify complex structural rearrangements between alternate alleles at this locus. The false gravid spot haplotype drives increased allele-specific expression of kitlga, which provides a mechanistic explanation for the increased melanophore abundance that causes the spot. By studying social interactions in the laboratory and in nature, we find that males with the false gravid spot experience less aggression; however, they also receive increased attention from other males and are disdained by females. These behavioral interactions may contribute to the maintenance of this phenotypic polymorphism in natural populations. We speculate that structural variants affecting gene regulation may be an underappreciated driver of balanced polymorphisms across diverse species.

9,000 years of genetic continuity in southernmost Africa demonstrated at Oakhurst rockshelter

Southern Africa has one of the longest records of fossil hominins and harbours the largest human genetic diversity in the world. Yet, despite its relevance for human origins and spread around the globe, the formation and processes of its gene pool in the past are still largely unknown. Here, we present a time transect of genome-wide sequences from nine individuals recovered from a single site in South Africa, Oakhurst Rockshelter. Spanning the whole Holocene, the ancient DNA of these individuals allows us to reconstruct the demographic trajectories of the indigenous San population and their ancestors during the last 10,000 years. We show that, in contrast to most regions around the world, the population history of southernmost Africa was not characterized by several waves of migration, replacement and admixture but by long-lasting genetic continuity from the early Holocene to the end of the Later Stone Age. Although the advent of pastoralism and farming substantially transformed the gene pool in most parts of southern Africa after 1,300 BP, we demonstrate using allele-frequency and identity-by-descent segment-based methods that the ‡Khomani San and Karretjiemense from South Africa still show direct signs of relatedness to the Oakhurst hunter-gatherers, a pattern obscured by recent, extensive non-Southern African admixture. Yet, some southern San in South Africa still preserve this ancient, Pleistocene-derived genetic signature, extending the period of genetic continuity until today.

Multi-ancestry GWAS reveals loci linked to human variation in LINE-1- and Alu-copy numbers

Long INterspersed Element-1 (LINE-1; L1) and Alu are two families of transposable elements (TEs) occupying ~17% and ~11% of the human genome, respectively. Though only a small fraction of L1 copies is able to produce the machinery to mobilize autonomously, Alu elements and degenerate L1 copies can hijack their functional machinery and mobilize in trans. The expression and subsequent copy number expansion of L1 and Alu can exert pathological effects on their hosts, promoting genome instability, inflammation, and cell cycle alterations. These features have made L1 and Alu promising focus subjects in studies of aging and aging diseases where they can become active. However, the mechanisms regulating variation in their expression and copy number remain incompletely characterized. Moreover, the relevance of known mechanisms to diverse human populations remains unclear, as mechanisms are often characterized in isogenic cell culture models. To address these gaps, we leveraged genomic data from the 1000 Genomes Project to carry out a trans-ethnic GWAS of L1 and Alu insertion global singletons. These singletons are rare insertions observed only once in a population, potentially reflecting recently acquired L1 and Alu integrants or structural variants, and which we used as proxies for L1/Alu-associated copy number variation. Our computational approach identified single nucleotide variants in genomic regions containing genes with potential and known TE regulatory properties, and it enriched for single nucleotide variants in regions containing known regulators of L1 expression. Moreover, we identified many reference TE copies and polymorphic structural variants that were associated with L1/Alu singletons, suggesting their potential contribution to TE copy number variation through transposition-dependent or transposition-independent mechanisms. Finally, a transcriptional analysis of lymphoblastoid cells highlighted potential cell cycle alterations in a subset of samples harboring L1/Alu singletons. Collectively, our results (i) suggest that known TE regulatory mechanisms may also play regulatory roles in diverse human populations, (ii) expand the list of genic and repetitive genomic loci implicated in TE copy number variation, and (iii) reinforce the links between TEs and disease.

Inference of Host-Pathogen Interaction Matrices from Genome-Wide Polymorphism Data

Host-pathogen coevolution is defined as the reciprocal evolutionary changes in both species due to genotype × genotype (G×G) interactions at the genetic level determining the outcome and severity of infection. While co-analyses of hosts and pathogen genomes (co-genome-wide association studies) allow us to pinpoint the interacting genes, these do not reveal which host genotype(s) is/are resistant to which pathogen genotype(s). The knowledge of this so-called infection matrix is important for agriculture and medicine. Building on established theories of host-pathogen interactions, we here derive four novel indices capturing the characteristics of the infection matrix. These indices can be computed from full genome polymorphism data of randomly sampled uninfected hosts, as well as infected hosts and their pathogen strains. We use these indices in an approximate Bayesian computation method to pinpoint loci with relevant G×G interactions and to infer their underlying interaction matrix. In a combined single nucleotide polymorphism dataset of 451 European humans and their infecting hepatitis C virus (HCV) strains and 503 uninfected individuals, we reveal a new human candidate gene for resistance to HCV and new virus mutations matching human genes. For two groups of significant human-HCV (G×G) associations, we infer a gene-for-gene infection matrix, which is commonly assumed to be typical of plant-pathogen interactions. Our model-based inference framework bridges theoretical models of G×G interactions with host and pathogen genomic data. It, therefore, paves the way for understanding the evolution of key G×G interactions underpinning HCV adaptation to the European human population after a recent expansion.

GGTyper: genotyping complex structural variants using short-read sequencing data

MOTIVATION

Complex structural variants (SVs) are genomic rearrangements that involve multiple segments of DNA. They contribute to human diversity and have been shown to cause Mendelian disease. Nevertheless, our abilities to analyse complex SVs are very limited. As opposed to deletions and other canonical types of SVs, there are no established tools that have explicitly been designed for analysing complex SVs.

RESULTS

Here, we describe a new computational approach that we specifically designed for genotyping complex SVs in short-read sequenced genomes. Given a variant description, our approach computes genotype-specific probability distributions for observing aligned read pairs with a wide range of properties. Subsequently, these distributions can be used to efficiently determine the most likely genotype for any set of aligned read pairs observed in a sequenced genome. In addition, we use these distributions to compute a genotyping difficulty for a given variant, which predicts the amount of data needed to achieve a reliable call. Careful evaluation confirms that our approach outperforms other genotypers by making reliable genotype predictions across both simulated and real data. On up to 7829 human genomes, we achieve high concordance with population-genetic assumptions and expected inheritance patterns. On simulated data, we show that precision correlates well with our prediction of genotyping difficulty. This together with low memory and time requirements makes our approach well-suited for application in biomedical studies involving small to very large numbers of short-read sequenced genomes.

AVAILABILITY AND IMPLEMENTATION

Source code is available at https://github.com/kehrlab/Complex-SV-Genotyping.

Functional Mutations in the microRNA-155 Promoter Modulate its Transcription Efficiency and Expression

Limited research has been conducted on porcine miR-155 promoters, and previous study from our group have identified two haplotypes (TT and CC) in different pig breeds, each associated with five fully linked mutation sites within or near the miR-155 gene (Li et al. Dev Comp Immunol 39(1):110-116, 2013). In this study, the promoter region of porcine miR-155 was screened, and two important transcription factors, Foxp3 and RelA, were identified. The binding ability of Foxp3 protein was found to be affected by the first mutation site (A/C) using EMSA analysis. In vitro experiments revealed that the expression level of miR-155 was significantly higher in the C haplotype compared to the T haplotype. Additionally, northern blotting assays indicated that both the first mutation site (A/C) and the fourth mutation site (G/T) had a significant impact on miR-155 expression levels. These findings provide further insights into the transcriptional regulation of porcine miR-155 and identify crucial mutation sites that influence miR-155 expression. This knowledge can serve as a basis for identifying potential molecular markers associated with disease resistance in swine.

Prioritizing drug targets in systemic lupus erythematosus from a genetic perspective: a druggable genome-wide Mendelian randomization study

OBJECTIVES

Systemic lupus erythematosus (SLE) is a heterogeneous autoimmune disease with an unsatisfactory state of treatment. We aim to explore novel targets for SLE from a genetic standpoint.

METHODS

Cis-expression quantitative trait loci (eQTLs) for whole blood from 31,684 samples provided by the eQTLGen Consortium as well as two large SLE cohorts were utilized for screening and validating genes causally associated with SLE. Colocalization analysis was employed to further investigate whether changes in the expression of risk genes, as indicated by GWAS signals, influence the occurrence and development of SLE. Targets identified for drug development were evaluated for potential side effects using a phenome-wide association study (PheWAS). Based on the multiple databases, we explored the interactions between drugs and genes for drug prediction and the assessment of current medications.

RESULTS

The analysis comprised 5427 druggable genes in total. The two-sample Mendelian randomization (MR) in the discovery phase identified 20 genes causally associated with SLE and validated 8 genes in the replication phase. Colocalization analysis ultimately identified five genes (BLK, HIST1H3H, HSPA1A, IL12A, NEU1) with PPH4 > 0.8. PheWAS further indicated that drugs acting on BLK and IL12A are less likely to have potential side effects, while HSPA1A and NEU1 were associated with other traits. Four genes (BLK, HSPA1A, IL12A, NEU1) have been targeted for drug development in autoimmune diseases and other conditions.

CONCLUSIONS

.This study identified five genes as therapeutic targets for SLE. Repurposing and developing drugs targeting these genes is anticipated to improve the existing treatment state for SLE. Key Points • We identified five gene targets of priority for the treatment of SLE, with BLK and IL12A indicating fewer side effects. • Among the existing drugs that target these candidate genes, Ustekinumab, Ebdarokimab, and Briakinumab (targeting the IL12 gene) and CD24FC (targeting HSPA1A) may potentially be repurposed for the treatment of SLE.

Contribution of copy number variations to education, socioeconomic status and cognition from a genome-wide study of 305,401 subjects

Educational attainment (EA), socioeconomic status (SES) and cognition are phenotypically and genetically linked to health outcomes. However, the role of copy number variations (CNVs) in influencing EA/SES/cognition remains unclear. Using a large-scale (n = 305,401) genome-wide CNV-level association analysis, we discovered 33 CNV loci significantly associated with EA/SES/cognition, 20 of which were novel (deletions at 2p22.2, 2p16.2, 2p12, 3p25.3, 4p15.2, 5p15.33, 5q21.1, 8p21.3, 9p21.1, 11p14.3, 13q12.13, 17q21.31, and 20q13.33, as well as duplications at 3q12.2, 3q23, 7p22.3, 8p23.1, 8p23.2, 17q12 (105 kb), and 19q13.32). The genes identified in gene-level tests were enriched in biological pathways such as neurodegeneration, telomere maintenance and axon guidance. Phenome-wide association studies further identified novel associations of EA/SES/cognition-associated CNVs with mental and physical diseases, such as 6q27 duplication with upper respiratory disease and 17q12 (105 kb) duplication with mood disorders. Our findings provide a genome-wide CNV profile for EA/SES/cognition and bridge their connections to health. The expanded candidate CNVs database and the residing genes would be a valuable resource for future studies aimed at uncovering the biological mechanisms underlying cognitive function and related clinical phenotypes.

Genotyping sequence-resolved copy-number variation using pangenomes reveals paralog-specific global diversity and expression divergence of duplicated genes

Human pangenomes contain assemblies of non-reference copy-number variable (CNV) genes. We developed a new method, ctyper, to identify the copy-number of specific alleles of CNV genes cataloged in pangenomes with NGS datasets. Applying ctyper to the 1000-genomes samples revealed population stratification of paralogs and two classes of CNVs: recent CNVs due to ongoing duplications, and polymorphic CNVs from non-reference ancient paralogs. Expression quantitative trait locus analysis determined allele-specific expression within gene families, revealing that 7.94% of paralogs and 3.28% orthologs had significantly divergent expression. Case studies of individual genes include finding lower expression on SMN-1 copies that arose from conversion from SMN-2, and increased expression on a form of AMY2B that has undergone a translocation. Moreover, 4.7% of paralogs and 1.2% of orthologs had different most-expressed tissues. Furthermore, the genotypes explain more expression variance than known eQTL variants. Overall, ctyper enables biobank-scale genotyping of sequence-resolved CNVs.

Advancing long-read nanopore genome assembly and accurate variant calling for rare disease detection

More than 50% of families with suspected rare monogenic diseases remain unsolved after whole genome analysis by short read sequencing (SRS). Long-read sequencing (LRS) could help bridge this diagnostic gap by capturing variants inaccessible to SRS, facilitating long-range mapping and phasing, and providing haplotype-resolved methylation profiling. To evaluate LRS's additional diagnostic yield, we sequenced a rare disease cohort of 98 samples, including 41 probands and some family members, using nanopore sequencing, achieving per sample ∼36x average coverage and 32 kilobase (kb) read N50 from a single flow cell. Our Napu pipeline generated assemblies, phased variants, and methylation calls. LRS covered, on average, coding exons in ∼280 genes and ∼5 known Mendelian disease genes that were not covered by SRS. In comparison to SRS, LRS detected additional rare, functionally annotated variants, including SVs and tandem repeats, and completely phased 87% of protein-coding genes. LRS detected additional de novo variants, and could be used to distinguish postzygotic mosaic variants from prezygotic de novos . Eleven probands were solved, with diverse underlying genetic causes including de novo and compound heterozygous variants, large-scale SVs, and epigenetic modifications. Our study demonstrates LRS's potential to enhance diagnostic yield for rare monogenic diseases, implying utility in future clinical genomics workflows.

Structural variants linked to Alzheimer's Disease and other common age-related clinical and neuropathologic traits

Advances have led to a greater understanding of the genetics of Alzheimer's Disease (AD). However, the gap between the predicted and observed genetic heritability estimates when using single nucleotide polymorphisms (SNPs) and small indel data remains. Large genomic rearrangements, known as structural variants (SVs), have the potential to account for this missing genetic heritability. By leveraging data from two ongoing cohort studies of aging and dementia, the Religious Orders Study and Rush Memory and Aging Project (ROS/MAP), we performed genome-wide association analysis testing around 20,000 common SVs from 1,088 participants with whole genome sequencing (WGS) data. A range of Alzheimer's Disease and Related Disorders (AD/ADRD) clinical and pathologic traits were examined. Given the limited sample size, no genome-wide significant association was found, but we mapped SVs across 81 AD risk loci and discovered 22 SVs in linkage disequilibrium (LD) with GWAS lead variants and directly associated with AD/ADRD phenotypes (nominal P < 0.05). The strongest association was a deletion of an Alu element in the 3'UTR of the TMEM106B gene. This SV was in high LD with the respective AD GWAS locus and was associated with multiple AD/ADRD phenotypes, including tangle density, TDP-43, and cognitive resilience. The deletion of this element was also linked to lower TMEM106B protein abundance. We also found a 22 kb deletion associated with depression in ROSMAP and bearing similar association patterns as AD GWAS SNPs at the IQCK locus. In addition, genome-wide scans allowed the identification of 7 SVs, with no LD with SNPs and nominally associated with AD/ADRD traits. This result suggests potentially new ADRD risk loci not discoverable using SNP data. Among these findings, we highlight a 5.6 kb duplication of coding regions of the gene C1orf186 at chromosome 1 associated with indices of cognitive impairment, decline, and resilience. While further replication in independent datasets is needed to validate these findings, our results support the potential roles of common structural variations in the pathogenesis of AD/ADRD.

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.

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.

Somatic mutation phasing and haplotype extension using linked-reads in multiple myeloma

Somatic mutation phasing informs our understanding of cancer-related events, like driver mutations. We generated linked-read whole genome sequencing data for 23 samples across disease stages from 14 multiple myeloma (MM) patients and systematically assigned somatic mutations to haplotypes using linked-reads. Here, we report the reconstructed cancer haplotypes and phase blocks from several MM samples and show how phase block length can be extended by integrating samples from the same individual. We also uncover phasing information in genes frequently mutated in MM, including DIS3, HIST1H1E, KRAS, NRAS, and TP53, phasing 79.4% of 20,705 high-confidence somatic mutations. In some cases, this enabled us to interpret clonal evolution models at higher resolution using pairs of phased somatic mutations. For example, our analysis of one patient suggested that two NRAS hotspot mutations occurred on the same haplotype but were independent events in different subclones. Given sufficient tumor purity and data quality, our framework illustrates how haplotype-aware analysis of somatic mutations in cancer can be beneficial for some cancer cases.

Evidence for dynastic succession among early Celtic elites in Central Europe

The early Iron Age (800 to 450 BCE) in France, Germany and Switzerland, known as the 'West-Hallstattkreis', stands out as featuring the earliest evidence for supra-regional organization north of the Alps. Often referred to as 'early Celtic', suggesting tentative connections to later cultural phenomena, its societal and population structure remain enigmatic. Here we present genomic and isotope data from 31 individuals from this context in southern Germany, dating between 616 and 200 BCE. We identify multiple biologically related groups spanning three elite burials as far as 100 km apart, supported by trans-regional individual mobility inferred from isotope data. These include a close biological relationship between two of the richest burial mounds of the Hallstatt culture. Bayesian modelling points to an avuncular relationship between the two individuals, which may suggest a practice of matrilineal dynastic succession in early Celtic elites. We show that their ancestry is shared on a broad geographic scale from Iberia throughout Central-Eastern Europe, undergoing a decline after the late Iron Age (450 BCE to ~50 CE).

Structural variation in humans and our primate kin in the era of telomere-to-telomere genomes and pangenomics

Structural variants (SVs) account for the majority of base pair differences both within and between primate species. However, our understanding of inter- and intra-species SV has been historically hampered by the quality of draft primate genomes and the absence of genome resources for key taxa. Recently, advances in long-read sequencing and genome assembly have begun to radically reshape our understanding of SVs. Two landmark achievements include the publication of a human telomere-to-telomere (T2T) genome as well as the development of the first human pangenome reference. In this review, we first look back to the major works laying the foundation for these projects. We then examine the ways in which T2T genome assemblies and pangenomes are transforming our understanding of and approach to primate SV. Finally, we discuss what the future of primate SV research may look like in the era of T2T genomes and pangenomics.

Causes and Consequences of Varying Transposable Element Activity: An Evolutionary Perspective

Transposable elements (TEs) are genomic parasites found in nearly all eukaryotes, including humans. This evolutionary success of TEs is due to their replicative activity, involving insertion into new genomic locations. TE activity varies at multiple levels, from between taxa to within individuals. The rapidly accumulating evidence of the influence of TE activity on human health, as well as the rapid growth of new tools to study it, motivated an evaluation of what we know about TE activity thus far. Here, we discuss why TE activity varies, and the consequences of this variation, from an evolutionary perspective. By studying TE activity in nonhuman organisms in the context of evolutionary theories, we can shed light on the factors that affect TE activity. While the consequences of TE activity are usually deleterious, some have lasting evolutionary impacts by conferring benefits on the host or affecting other evolutionary processes.

The Role of Retrotransposons and Endogenous Retroviruses in Age-Dependent Neurodegenerative Disorders

Over 40% of the human genome is composed of retrotransposons, DNA species that hold the potential to replicate via an RNA intermediate and are evolutionarily related to retroviruses. Retrotransposons are most studied for their ability to jump within a genome, which can cause DNA damage and novel insertional mutations. Retrotransposon-encoded products, including viral-like proteins, double-stranded RNAs, and extrachromosomal circular DNAs, can also be potent activators of the innate immune system. A growing body of evidence suggests that retrotransposons are activated in age-related neurodegenerative disorders and that such activation causally contributes to neurotoxicity. Here we provide an overview of retrotransposon biology and outline evidence of retrotransposon activation in age-related neurodegenerative disorders, with an emphasis on those involving TAR-DNA binding protein-43 (TDP-43) and tau. Studies to date provide the basis for ongoing clinical trials and hold promise for innovative strategies to ameliorate the adverse effects of retrotransposon dysregulation in neurodegenerative disorders.

Single-nucleus multiomics reveals the disrupted regulatory programs in three brain regions of sporadic early-onset Alzheimer's disease

Sporadic early-onset Alzheimer's disease (sEOAD) represents a significant but less-studied subtype of Alzheimer's disease (AD). Here, we generated a single-nucleus multiome atlas derived from the postmortem prefrontal cortex, entorhinal cortex, and hippocampus of nine individuals with or without sEOAD. Comprehensive analyses were conducted to delineate cell type-specific transcriptomic changes and linked candidate cis-regulatory elements (cCREs) across brain regions. We prioritized seven conservative transcription factors in glial cells in multiple brain regions, including RFX4 in astrocytes and IKZF1 in microglia, which are implicated in regulating sEOAD-associated genes. Moreover, we identified the top 25 altered intercellular signaling between glial cells and neurons, highlighting their regulatory potential on gene expression in receiver cells. We reported 38 cCREs linked to sEOAD-associated genes overlapped with late-onset AD risk loci, and sEOAD cCREs enriched in neuropsychiatric disorder risk loci. This atlas helps dissect transcriptional and chromatin dynamics in sEOAD, providing a key resource for AD research.

Polygenic Indices (a.k.a. Polygenic Scores) in Social Science: A Guide for Interpretation and Evaluation

Polygenic indices (PGI)-the new recommended label for polygenic scores (PGS) in social science-are genetic summary scales often used to represent an individual's liability for a disease, trait, or behavior based on the additive effects of measured genetic variants. Enthusiasm for linking genetic data with social outcomes and the inclusion of premade PGIs in social science datasets have facilitated increased uptake of PGIs in social science research-a trend that will likely continue. Yet, most social scientists lack the expertise to interpret and evaluate PGIs in social science research. Here, we provide a primer on PGIs for social scientists focusing on key concepts, unique statistical genetic considerations, and best practices in calculation, estimation, reporting, and interpretation. We summarize our recommended best practices as a checklist to aid social scientists in evaluating and interpreting studies with PGIs. We conclude by discussing the similarities between PGIs and standard social science scales and unique interpretative considerations.

Investigating the association between gut microbiome and aortic aneurysm diseases: a bidirectional two-sample Mendelian randomization analysis

Objective

This study aims to investigate the associations between specific bacterial taxa of the gut microbiome and the development of aortic aneurysm diseases, utilizing Mendelian Randomization (MR) to explore these associations and overcome the confounding factors commonly present in observational studies.

Methods

Employing the largest available gut microbiome and aortic aneurysm Genome-Wide Association Study databases, including MiBioGen, Dutch Microbiome Project, FinnGen, UK Biobank, and Michigan Genomics Initiative, this study performs two-sample bidirectional MR analyses. Instrumental variables, linked to microbiome taxa at significant levels, were selected for identifying relationships with abdominal aortic aneurysms (AAA), thoracic aortic aneurysms (TAA), and aortic dissection (AD). Methods like inverse variance weighted, MR-PRESSO, MR-Egger, weighted median, simple mode, and mode-based estimate were used for MR analysis. Heterogeneity was assessed with the Cochran Q test. MR-Egger regression and MR-PRESSO addressed potential unbalanced horizontal pleiotropy.

Results

The analysis did not find any evidence of statistically significant associations between the gut microbiome and aortic aneurysm diseases after adjusting for the false discovery rate (FDR). Specifically, while initial results suggested correlations between 19 taxa and AAA, 25 taxa and TAA, and 13 taxa with AD, these suggested associations did not hold statistical significance post-FDR correction. Therefore, the role of individual gut microbial taxa as independent factors in the development and progression of aortic aneurysm diseases remains inconclusive. This finding underscores the necessity for larger sample sizes and more comprehensive studies to further investigate these potential links.

Conclusion

The study emphasizes the complex relationship between the gut microbiome and aortic aneurysm diseases. Although no statistically significant associations were found after FDR correction, the findings provide valuable insights and highlight the importance of considering gut microbiota in aortic aneurysm diseases research. Understanding these interactions may eventually contribute to identifying new therapeutic and preventive strategies for aortic aneurysm diseases.

Whole genome sequencing study of identical twins discordant for psychosis

Monozygotic (MZ) twins are often thought to have identical genomes, but recent work has shown that early post-zygotic events can result in a spectrum of DNA variants that are different between MZ twins. Such variants may explain phenotypic discordance and contribute to disease etiology. Here we performed whole genome sequencing in 17 pairs of MZ twins discordant for a psychotic disorder (schizophrenia, schizoaffective disorder or bipolar disorder). We examined various classes of rare variants that are discordant within a twin pair. We identified four genes harboring rare, predicted deleterious missense variants that were private to an affected individual in the cohort. Variants in FOXN1 and FLOT2 would have been categorized as damaging from recent schizophrenia and bipolar exome sequencing studies. Additionally, we identified four rare genic copy number variants (CNVs) private to an affected sample, two of which overlapped genes that have shown evidence for association with schizophrenia or bipolar disorder. One such CNV was a 3q29 duplication previously implicated in autism and developmental delay. We have performed the largest MZ twin study for discordant psychotic phenotypes to date. These findings warrant further investigation using other analytical approaches.

Comprehensive assessment of long-read sequencing platforms and calling algorithms for detection of copy number variation

Copy number variations (CNVs) play pivotal roles in disease susceptibility and have been intensively investigated in human disease studies. Long-read sequencing technologies offer opportunities for comprehensive structural variation (SV) detection, and numerous methodologies have been developed recently. Consequently, there is a pressing need to assess these methods and aid researchers in selecting appropriate techniques for CNV detection using long-read sequencing. Hence, we conducted an evaluation of eight CNV calling methods across 22 datasets from nine publicly available samples and 15 simulated datasets, covering multiple sequencing platforms. The overall performance of CNV callers varied substantially and was influenced by the input dataset type, sequencing depth, and CNV type, among others. Specifically, the PacBio CCS sequencing platform outperformed PacBio CLR and Nanopore platforms regarding CNV detection recall rates. A sequencing depth of 10x demonstrated the capability to identify 85% of the CNVs detected in a 50x dataset. Moreover, deletions were more generally detectable than duplications. Among the eight benchmarked methods, cuteSV, Delly, pbsv, and Sniffles2 demonstrated superior accuracy, while SVIM exhibited high recall rates.

VISTA: an integrated framework for structural variant discovery

Structural variation (SV) refers to insertions, deletions, inversions, and duplications in human genomes. SVs are present in approximately 1.5% of the human genome. Still, this small subset of genetic variation has been implicated in the pathogenesis of psoriasis, Crohn's disease and other autoimmune disorders, autism spectrum and other neurodevelopmental disorders, and schizophrenia. Since identifying structural variants is an important problem in genetics, several specialized computational techniques have been developed to detect structural variants directly from sequencing data. With advances in whole-genome sequencing (WGS) technologies, a plethora of SV detection methods have been developed. However, dissecting SVs from WGS data remains a challenge, with the majority of SV detection methods prone to a high false-positive rate, and no existing method able to precisely detect a full range of SVs present in a sample. Previous studies have shown that none of the existing SV callers can maintain high accuracy across various SV lengths and genomic coverages. Here, we report an integrated structural variant calling framework, Variant Identification and Structural Variant Analysis (VISTA), that leverages the results of individual callers using a novel and robust filtering and merging algorithm. In contrast to existing consensus-based tools which ignore the length and coverage, VISTA overcomes this limitation by executing various combinations of top-performing callers based on variant length and genomic coverage to generate SV events with high accuracy. We evaluated the performance of VISTA on comprehensive gold-standard datasets across varying organisms and coverage. We benchmarked VISTA using the Genome-in-a-Bottle gold standard SV set, haplotype-resolved de novo assemblies from the Human Pangenome Reference Consortium, along with an in-house polymerase chain reaction (PCR)-validated mouse gold standard set. VISTA maintained the highest F1 score among top consensus-based tools measured using a comprehensive gold standard across both mouse and human genomes. VISTA also has an optimized mode, where the calls can be optimized for precision or recall. VISTA-optimized can attain 100% precision and the highest sensitivity among other variant callers. In conclusion, VISTA represents a significant advancement in structural variant calling, offering a robust and accurate framework that outperforms existing consensus-based tools and sets a new standard for SV detection in genomic research.

High-depth whole-genome sequencing identifies structure variants, copy number variants and short tandem repeats associated with Parkinson's disease

While numerous single nucleotide variants and small indels have been identified in Parkinson's disease (PD), the contribution of structural variants (SVs), copy number variants (CNVs), and short tandem repeats (STRs) remains poorly understood. Here we investigated the association using the high-depth whole-genome sequencing data from 466 Chinese PD patients and 513 controls. Totally, we identified 29,561 SVs, 32,153 CNVs, and 174,905 STRs, and found that CNV deletions were significantly enriched in the end-proportion of autosomal chromosomes in PD. After genome-wide association analysis and replication in an external cohort of 352 cases and 547 controls, we validated that the 1.6 kb-deletion neighboring MUC19, 12.4kb-deletion near RXFP1 and GGGAAA repeats in SLC2A13 were significantly associated with PD. Moreover, the MUC19 deletion and the SLC2A13 5-copy repeat reduced the penetrance of the LRRK2 G2385R variant. Moreover, genes with these variants were dosage-sensitive. These data provided novel insights into the genetic architecture of PD.

Developing a Polygenic Risk Score with Age and Sex to Identify High-Risk Myopia in Taiwan

Myopia is the leading cause of impaired vision, and its prevalence is increasing among Asian populations. This study aimed to develop a polygenic risk score (PRS) followed by replication to predict myopia in the Taiwanese population. In total, 23,688 participants with cycloplegic autorefraction-measured mean spherical equivalent (SE), genetic, and demographic data were included. The myopia PRS was generated based on genome-wide association study (GWAS) outcomes in a Taiwanese population and previously published GWAS reports. The results demonstrated that the inclusion of age and sex in the PRS had an area under the curve (AUC) of 0.80, 0.78, and 0.73 (p < 0.001) for participants aged >18 years with high (SE < -6.0 diopters (D); n = 1089), moderate (-6.0 D < SE ≤ -3.0 D; n = 3929), and mild myopia (-3.0 D < SE ≤ -1.0 D; n = 2241), respectively. Participants in the top PRS quartile had a 1.30-fold greater risk of high myopia (95% confidence interval = 1.09-1.55, p = 0.003) compared with that in the remaining participants. Further, a higher PRS significantly increased the risk of high myopia (SE ≤ -2.0 D) in children ≤6 years of age (p = 0.027). In conclusion, including the PRS, age, and sex improved the prediction of high myopia risk in the Taiwanese population.

A comprehensive review of deep learning-based variant calling methods

Genome sequencing data have become increasingly important in the field of personalized medicine and diagnosis. However, accurately detecting genomic variations remains a challenging task. Traditional variation detection methods rely on manual inspection or predefined rules, which can be time-consuming and prone to errors. Consequently, deep learning-based approaches for variation detection have gained attention due to their ability to automatically learn genomic features that distinguish between variants. In our review, we discuss the recent advancements in deep learning-based algorithms for detecting small variations and structural variations in genomic data, as well as their advantages and limitations.

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.

A Comparison of Structural Variant Calling from Short-Read and Nanopore-Based Whole-Genome Sequencing Using Optical Genome Mapping as a Benchmark

The identification of structural variants (SVs) in genomic data represents an ongoing challenge because of difficulties in reliable SV calling leading to reduced sensitivity and specificity. We prepared high-quality DNA from 9 parent-child trios, who had previously undergone short-read whole-genome sequencing (Illumina platform) as part of the Genomics England 100,000 Genomes Project. We reanalysed the genomes using both Bionano optical genome mapping (OGM; 8 probands and one trio) and Nanopore long-read sequencing (Oxford Nanopore Technologies [ONT] platform; all samples). To establish a "truth" dataset, we asked whether rare proband SV calls (n = 234) made by the Bionano Access (version 1.6.1)/Solve software (version 3.6.1_11162020) could be verified by individual visualisation using the Integrative Genomics Viewer with either or both of the Illumina and ONT raw sequence. Of these, 222 calls were verified, indicating that Bionano OGM calls have high precision (positive predictive value 95%). We then asked what proportion of the 222 true Bionano SVs had been identified by SV callers in the other two datasets. In the Illumina dataset, sensitivity varied according to variant type, being high for deletions (115/134; 86%) but poor for insertions (13/58; 22%). In the ONT dataset, sensitivity was generally poor using the original Sniffles variant caller (48% overall) but improved substantially with use of Sniffles2 (36/40; 90% and 17/23; 74% for deletions and insertions, respectively). In summary, we show that the precision of OGM is very high. In addition, when applying the Sniffles2 caller, the sensitivity of SV calling using ONT long-read sequence data outperforms Illumina sequencing for most SV types.

Comprehensive and deep evaluation of structural variation detection pipelines with third-generation sequencing data

BACKGROUND

Structural variation (SV) detection methods using third-generation sequencing data are widely employed, yet accurately detecting SVs remains challenging. Different methods often yield inconsistent results for certain SV types, complicating tool selection and revealing biases in detection.

RESULTS

This study comprehensively evaluates 53 SV detection pipelines using simulated and real data from PacBio (CLR: Continuous Long Read, CCS: Circular Consensus Sequencing) and Nanopore (ONT) platforms. We assess their performance in detecting various sizes and types of SVs, breakpoint biases, and genotyping accuracy with various sequencing depths. Notably, pipelines such as Minimap2-cuteSV2, NGMLR-SVIM, PBMM2-pbsv, Winnowmap-Sniffles2, and Winnowmap-SVision exhibit comparatively higher recall and precision. Our findings also show that combining multiple pipelines with the same aligner, like pbmm2 or winnowmap, can significantly enhance performance. The individual pipelines' detailed ranking and performance metrics can be viewed in a dynamic table: http://pmglab.top/SVPipelinesRanking .

CONCLUSIONS

This study comprehensively characterizes the strengths and weaknesses of numerous pipelines, providing valuable insights that can improve SV detection in third-generation sequencing data and inform SV annotation and function prediction.

Molecular findings in patients for whole exome sequencing and mitochondrial genome assessment

OBJECTIVE

Whole exome sequencing (WES) is becoming more widely used as a diagnostic tool in the field of medicine. In this article, we reported the diagnostic yield of WES and mitochondrial genome assessment in 2226 consecutive cases in a single clinical laboratory.

MATERIALS AND METHODS

We retrospectively analyzed consecutive WES reports from 2226 patients with various genetic disorders. WES-process was focused exclusively on the probands and aimed at a higher diagnostic capacity. We determined the diagnostic rate of WES overall and by phenotypic category, mode of inheritance, mitochondrial genome variant, and copy number variants (CNVs).

RESULTS

Among the 2226 patients who had diagnostic WES proband-only, the overall diagnostic yield of WES was 34.59% (770/2226). The highest diagnostic yield was observed in autosomal dominant disorders, at 45.58% (351/770), followed by autosomal recessive at 31.95%(246/770), X-linked disorder at 9.61%(74/770), and mitochondrial diseases at a notably lower 0.65%(5/770). The 12.21% (94/770) diagnoses were based on a total of 94 copy number variants reported from WES data. CNVs in children accounted for 67.02% of the total CNVs. While majority of the molecular diagnoses were related to nuclear genes, the inclusion of mitochondrial genome sequencing in the WES test contributed to five diagnoses. all mitochondrial diseases were identified in adults.

CONCLUSIONS

The proband-only WES provided a definitive molecular diagnosis for 34.59% of a large cohort of patients while analysis of WES simultaneously analyzed the SNVs, exons, mitochondrial genome, and CNVs, thereby improving the diagnostic yield significantly compared to the single-detection WES method; and facilitating the identification of novel candidate genes.

Genetic Variations in TrkB.T1 Isoform and Their Association With Somatic and Psychological Symptoms in Individuals With IBS

Irritable bowel syndrome (IBS), a disorder of gut-brain interaction, is often comorbid with somatic pain and psychological disorders. Dysregulated signaling of brain-derived neurotrophic factor (BDNF) and its receptor, tropomyosin-related kinase B (TrkB), has been implicated in somatic-psychological symptoms in individuals with IBS. We investigated the association of 10 single-nucleotide polymorphisms (SNPs) in the regulatory 3' untranslated region of neurotrophic receptor tyrosine kinase-2 (NTRK2) kinase domain-deficient truncated isoform (TrkB.T1) and BDNF Val66Met SNP with somatic and psychological symptoms and quality-of-life (QoL) in a cohort from the United States (IBS, n = 464; healthy controls, n = 156). We found that the homozygous recessive genotype (G/G) of rs2013566 in individuals with IBS is associated with worsened somatic symptoms, including headache, back pain, joint pain, muscle pain, and somatization as well as diminished sleep quality, energy level, and overall QoL. Validation using United Kingdom BioBank data confirmed the association of rs2013566 with an increased likelihood of headache. Several SNPs (rs1627784, rs1624327, and rs1147198) showed significant associations with muscle pain in our U.S. cohort. These 4 SNPs are predominantly located in H3K4Me1-enriched regions, suggesting their enhancer and/or transcription regulation potential. Our findings suggest that genetic variation within the 3' untranslated region region of the TrkB.T1 isoform may contribute to comorbid conditions in individuals with IBS, resulting in a spectrum of somatic and psychological symptoms impacting their QoL. These findings advance our understanding of the genetic interaction between BDNF/TrkB pathways and somatic-psychological symptoms in IBS, highlighting the importance of further exploring this interaction for potential clinical applications. PERSPECTIVE: This study aims to understand the genetic effects on IBS-related symptoms across somatic, psychological, and quality-of-life (QoL) domains, validated by United Kingdom BioBank data. The rs2013566 homozygous recessive genotype correlates with worsened somatic symptoms and reduced QoL, emphasizing its clinical significance.

HapKled: a haplotype-aware structural variant calling approach for Oxford nanopore sequencing data

Introduction: Structural Variants (SVs) are a type of variation that can significantly influence phenotypes and cause diseases. Thus, the accurate detection of SVs is a vital part of modern genetic analysis. The advent of long-read sequencing technology ushers in a new era of more accurate and comprehensive SV calling, and many tools have been developed to call SVs using long-read data. Haplotype-tagging is a procedure that can tag haplotype information on reads and can thus potentially improve the SV detection; nevertheless, few methods make use of this information. In this article, we introduce HapKled, a new SV detection tool that can accurately detect SVs from Oxford Nanopore Technologies (ONT) long-read alignment data. Methods: HapKled utilizes haplotype information underlying alignment data by conducting haplotype-tagging using Whatshap on the reads to improve the detection performance, with three unique calling mechanics including altering clustering conditions according to haplotype information of signatures, determination of similar SVs based on haplotype information, and slack filtering conditions based on haplotype quality. Results: In our evaluations, HapKled outperformed state-of-the-art tools and can deliver better SV detection results on both simulated and real sequencing data. The code and experiments of HapKled can be obtained from https://github.com/CoREse/HapKled. Discussion: With the superb SV detection performance that HapKled can deliver, HapKled could be useful in bioinformatics research, clinical diagnosis, and medical research and development.

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.

Exploring the genetic and epigenetic underpinnings of early-onset cancers: Variant prioritization for long read whole genome sequencing from family cancer pedigrees

Despite significant advances in our understanding of genetic cancer susceptibility, known inherited cancer predisposition syndromes explain at most 20% of early-onset cancers. As early-onset cancer prevalence continues to increase, the need to assess previously inaccessible areas of the human genome, harnessing a trio or quad family-based architecture for variant filtration, may reveal further insights into cancer susceptibility. To assess a broader spectrum of variation than can be ascertained by multi-gene panel sequencing, or even whole genome sequencing with short reads, we employed long read whole genome sequencing using an Oxford Nanopore Technology (ONT) PromethION of 3 families containing an early-onset cancer proband using a trio or quad family architecture. Analysis included 2 early-onset colorectal cancer family trios and one quad consisting of two siblings with testicular cancer, all with unaffected parents. Structural variants (SVs), epigenetic profiles and single nucleotide variants (SNVs) were determined for each individual, and a filtering strategy was employed to refine and prioritize candidate variants based on the family architecture. The family architecture enabled us to focus on inapposite variants while filtering variants shared with the unaffected parents, significantly decreasing background variation that can hamper identification of potentially disease causing differences. Candidate d e novo and compound heterozygous variants were identified in this way. Gene expression, in matched neoplastic and pre-neoplastic lesions, was assessed for one trio. Our study demonstrates the feasibility of a streamlined analysis of genomic variants from long read ONT whole genome sequencing and a way to prioritize key variants for further evaluation of pathogenicity, while revealing what may be missing from panel based analyses.

Shared molecular mechanisms and transdiagnostic potential of neurodevelopmental disorders and immune disorders

The co-occurrence and familial clustering of neurodevelopmental disorders and immune disorders suggest shared genetic risk factors. Based on genome-wide association summary statistics from five neurodevelopmental disorders and four immune disorders, we conducted genome-wide, local genetic correlation and polygenic overlap analysis. We further performed a cross-trait GWAS meta-analysis. Pleotropic loci shared between the two categories of diseases were mapped to candidate genes using multiple algorithms and approaches. Significant genetic correlations were observed between neurodevelopmental disorders and immune disorders, including both positive and negative correlations. Neurodevelopmental disorders exhibited higher polygenicity compared to immune disorders. Around 50%-90% of genetic variants of the immune disorders were shared with neurodevelopmental disorders. The cross-trait meta-analysis revealed 154 genome-wide significant loci, including 8 novel pleiotropic loci. Significant associations were observed for 30 loci with both types of diseases. Pathway analysis on the candidate genes at these loci revealed common pathways shared by the two types of diseases, including neural signaling, inflammatory response, and PI3K-Akt signaling pathway. In addition, 26 of the 30 lead SNPs were associated with blood cell traits. Neurodevelopmental disorders exhibit complex polygenic architecture, with a subset of individuals being at a heightened genetic risk for both neurodevelopmental and immune disorders. The identification of pleiotropic loci has important implications for exploring opportunities for drug repurposing, enabling more accurate patient stratification, and advancing genomics-informed precision in the medical field of neurodevelopmental disorders.

Population genomics highlights structural variations in local adaptation to saline coastal environments in woolly grape

Structural variations (SVs) are a feature of plant genomes that has been largely unexplored despite their significant impact on plant phenotypic traits and local adaptation to abiotic and biotic stress. In this study, we employed woolly grape (Vitis retordii), a species native to the tropical and subtropical regions of East Asia with both coastal and inland habitats, as a valuable model for examining the impact of SVs on local adaptation. We assembled a haplotype-resolved chromosomal reference genome for woolly grape, and conducted population genetic analyses based on whole-genome sequencing (WGS) data from coastal and inland populations. The demographic analyses revealed recent bottlenecks in all populations and asymmetric gene flow from the inland to the coastal population. In total, 1,035 genes associated with plant adaptive regulation for salt stress, radiation, and environmental adaptation were detected underlying local selection by SVs and SNPs in the coastal population, of which 37.29% and 65.26% were detected by SVs and SNPs, respectively. Candidate genes such as FSD2, RGA1, and AAP8 associated with salt tolerance were found to be highly differentiated and selected during the process of local adaptation to coastal habitats in SV regions. Our study highlights the importance of SVs in local adaptation; candidate genes related to salt stress and climatic adaptation to tropical and subtropical environments are important genomic resources for future breeding programs of grapevine and its rootstocks.

Analysis of Preimplantation and Clinical Outcomes of Two Cases by Oxford Nanopore Sequencing

It is challenging to distinguish embryos with a balanced translocation karyotype from a normal karyotype by existing conventional genetic testing methods. However, in germ-cell gamete generation, chromosome exchange and separation through cell meiosis form a different proportion of unbalanced gametes. Adverse birth events may occur, such as repeated miscarriages and fetal birth defects. In this study, the exact breakpoints of structural variation (SV) from two balanced translocation carrier families by using Nanopore long reads sequencing technology were obtained, and haplotype analysis and Sanger verified the accuracy of the detection results, confirming the application value of the Nanopore sequencing technology in the detection of balanced translocation before embryo implantation. Nanopore long-read sequencing was performed to find the precise breakpoint of chromosome-balanced translocation carriers. The breakpoints were subsequently verified by designing primers across the breakpoints and Sanger sequencing. Haplotype linkage analysis of SNPs which can be linked by a read block of families around the breakpoint regions was followed. After frozen (-thawed) embryo transfer (FET), prenatal cytogenetic analysis of amniotic fluid cells confirmed the predicted karyotypes from the transferred embryos. The presence of breakpoints was detected in three embryos of patient 1. No breakpoints were detected in either embryo of patient 2. One balanced translocated embryo from patient 1 and one normal euploid embryo from patient 2 were transplanted back into the patients, and amniotic fluid cells were analyzed for the karyotype of fetuses. The results were entirely consistent with the fetal karyotype. And through late follow-up, both patients successfully had a live birth fetus. The breakpoint location of the balanced chromosome translocation can be accurately found by Nanopore sequencing. The haplotype of carriers can be successfully constructed by Nanopore and sanger sequencing confirmed that the results were accurate. This is very advantageous for preimplantation genetic testing for chromosomal structural rearrangements (PGT-SR) detection in the families without proband.

Single-nucleus multiomics reveals the disrupted regulatory programs in three brain regions of sporadic early-onset Alzheimer's disease

Sporadic early-onset Alzheimer's disease (sEOAD) represents a significant but less-studied subtype of Alzheimer's disease (AD). Here, we generated a single-nucleus multiome atlas derived from the postmortem prefrontal cortex, entorhinal cortex, and hippocampus of nine individuals with or without sEOAD. Comprehensive analyses were conducted to delineate cell type-specific transcriptomic changes and linked candidate cis- regulatory elements (cCREs) across brain regions. We prioritized seven conservative transcription factors in glial cells in multiple brain regions, including RFX4 in astrocytes and IKZF1 in microglia, which are implicated in regulating sEOAD-associated genes. Moreover, we identified the top 25 altered intercellular signaling between glial cells and neurons, highlighting their regulatory potential on gene expression in receiver cells. We reported 38 cCREs linked to sEOAD-associated genes overlapped with late-onset AD risk loci, and sEOAD cCREs enriched in neuropsychiatric disorder risk loci. This atlas helps dissect transcriptional and chromatin dynamics in sEOAD, providing a key resource for AD research.

Regulatory Effects of 198-bp Structural Variants in the GSTA2 Promoter Region on Adipogenesis in Chickens

Molecular breeding accelerates animal breeding and improves efficiency by utilizing genetic mutations. Structural variations (SVs), a significant source of genetic mutations, have a greater impact on phenotypic variation than SNPs. Understanding SV functional mechanisms and obtaining precise information are crucial for molecular breeding. In this study, association analysis revealed significant correlations between 198-bp SVs in the GSTA2 promoter region and abdominal fat weight, intramuscular fat content, and subcutaneous fat thickness in chickens. High expression of GSTA2 in adipose tissue was positively correlated with the abdominal fat percentage, and different genotypes of GSTA2 exhibited varied expression patterns in the liver. The 198-bp SVs regulate GSTA2 expression by binding to different transcription factors. Overexpression of GSTA2 promoted preadipocyte proliferation and differentiation, while interference had the opposite effect. Mechanistically, the 198-bp fragment contains binding sites for transcription factors such as C/EBPα that regulate GSTA2 expression and fat synthesis. These SVs are significantly associated with chicken fat traits, positively influencing preadipocyte development by regulating cell proliferation and differentiation. Our work provides compelling evidence for the use of 198-bp SVs in the GSTA2 promoter region as molecular markers for poultry breeding and offers new insights into the pivotal role of the GSTA2 gene in fat generation.

Genome-Wide Association Study with Three Control Cohorts of Japanese Patients with Esotropia and Exotropia of Comitant Strabismus and Idiopathic Superior Oblique Muscle Palsy

Esotropia and exotropia in the entity of comitant strabismus are multifactorial diseases with both genetic and environmental backgrounds. Idiopathic superior oblique muscle palsy, as the predominant entity of non-comitant (paralytic) strabismus, also has a genetic background, as evidenced by varying degrees of muscle hypoplasia. A genome-wide association study (GWAS) was conducted of 711 Japanese patients with esotropia (n= 253), exotropia (n = 356), and idiopathic superior oblique muscle palsy (n = 102). The genotypes of single nucleotide polymorphisms (SNPs) were determined by Infinium Asian Screening Array. Three control cohorts from the Japanese population were used: two cohorts from BioBank Japan (BBJ) and the Nagahama Cohort. BBJ (180K) was genotyped by a different array, Illumina Infinium OmniExpressExome or HumanOmniExpress, while BBJ (ASA) and the Nagahama Cohort were genotyped by the same Asian array. After quality control of SNPs and individuals, common SNPs between the case cohort and the control cohort were chosen in the condition of genotyping by different arrays, while all SNPs genotyped by the same array were used for SNP imputation. The SNPs imputed with R-square values ≥ 0.3 were used to compare the case cohort of each entity or the combined entity with the control cohort. In comparison with BBJ (180K), the esotropia group and the exotropia group showed CDCA7 and HLA-F, respectively, as candidate genes at a significant level of p < 5 × 10-8, while the idiopathic superior oblique muscle palsy group showed DAB1 as a candidate gene which is involved in neuronal migration. DAB1 was also detected as a candidate in comparison with BBJ (ASA) and the Nagahama Cohort at a weak level of significance of p < 1 × 10-6. In comparison with BBJ (180K), RARB (retinoic acid receptor-β) was detected as a candidate at a significant level of p < 5 × 10-8 in the combined group of esotropia, exotropia, and idiopathic superior oblique muscle palsy. In conclusion, a series of GWASs with three different control cohorts would be an effective method with which to search for candidate genes for multifactorial diseases such as strabismus.

A harmonized public resource of deeply sequenced diverse human genomes

Underrepresented populations are often excluded from genomic studies owing in part to a lack of resources supporting their analyses. The 1000 Genomes Project (1kGP) and Human Genome Diversity Project (HGDP), which have recently been sequenced to high coverage, are valuable genomic resources because of the global diversity they capture and their open data sharing policies. Here, we harmonized a high-quality set of 4094 whole genomes from 80 populations in the HGDP and 1kGP with data from the Genome Aggregation Database (gnomAD) and identified over 153 million high-quality SNVs, indels, and SVs. We performed a detailed ancestry analysis of this cohort, characterizing population structure and patterns of admixture across populations, analyzing site frequency spectra, and measuring variant counts at global and subcontinental levels. We also show substantial added value from this data set compared with the prior versions of the component resources, typically combined via liftOver and variant intersection; for example, we catalog millions of new genetic variants, mostly rare, compared with previous releases. In addition to unrestricted individual-level public release, we provide detailed tutorials for conducting many of the most common quality-control steps and analyses with these data in a scalable cloud-computing environment and publicly release this new phased joint callset for use as a haplotype resource in phasing and imputation pipelines. This jointly called reference panel will serve as a key resource to support research of diverse ancestry populations.

Human Y chromosome haplogroup L1-M22 traces Neolithic expansion in West Asia and supports the Elamite and Dravidian connection

West and South Asian populations profoundly influenced Eurasian genetic and cultural diversity. We investigate the genetic history of the Y chromosome haplogroup L1-M22, which, while prevalent in these regions, lacks in-depth study. Robust Bayesian analyses of 165 high-coverage Y chromosomes favor a West Asian origin for L1-M22 ∼20.6 thousand years ago (kya). Moreover, this haplogroup parallels the genome-wide genetic ancestry of hunter-gatherers from the Iranian Plateau and the Caucasus. We characterized two L1-M22 harboring population groups during the Early Holocene. One expanded with the West Asian Neolithic transition. The other moved to South Asia ∼8-6 kya but showed no expansion. This group likely participated in the spread of Dravidian languages. These South Asian L1-M22 lineages expanded ∼4-3 kya, coinciding with the Steppe ancestry introduction. Our findings advance the current understanding of Eurasian historical dynamics, emphasizing L1-M22's West Asian origin, associated population movements, and possible linguistic impacts.

A consensus genome of sika deer (Cervus nippon) and transcriptome analysis provided novel insights on the regulation mechanism of transcript factor in antler development

BACKGROUND

Sika deer (Cervus nippon) holds significance among cervids, with three genomes recently published. However, these genomes still contain hundreds of gaps and display significant discrepancies in continuity and accuracy. This poses challenges to functional genomics research and the selection of an appropriate reference genome. Thus, obtaining a high-quality reference genome is imperative to delve into functional genomics effectively.

FINDINGS

Here we report a high-quality consensus genome of male sika deer. All 34 chromosomes are assembled into single-contig pseudomolecules without any gaps, which is the most complete assembly. The genome size is 2.7G with 23,284 protein-coding genes. Comparative genomics analysis found that the genomes of sika deer and red deer are highly conserved, an approximately 2.4G collinear regions with up to 99% sequence similarity. Meanwhile, we observed the fusion of red deer's Chr23 and Chr4 during evolution, forming sika deer's Chr1. Additionally, we identified 607 transcription factors (TFs) that are involved in the regulation of antler development, including RUNX2, SOX6, SOX8, SOX9, PAX8, SIX2, SIX4, SIX6, SPI1, NFAC1, KLHL8, ZN710, JDP2, and TWST2, based on this consensus reference genome.

CONCLUSIONS

Our results indicated that we acquired a high-quality consensus reference genome. That provided valuable resources for understanding functional genomics. In addition, discovered the genetic basis of sika-red hybrid fertility and identified 607 significant TFs that impact antler development.