Wham: Identifying Structural Variants of Biological Consequence

Genomic Analysis of Indel and SV Reveals Functional and Adaptive Signatures in Hubei Indigenous Cattle Breeds

The genetic diversity of cattle plays a crucial role in adapting to environmental challenges and enhancing production traits. While research has predominantly focused on single nucleotide polymorphisms (SNPs), small indel and structural variants (SVs) also significantly contribute to genetic variation. This study investigates the distribution and functional impact of insertions and deletions in five Hubei indigenous cattle breeds. A total of 3,208,816 deletions and 2,082,604 insertions were identified, with the majority found in intergenic and intronic regions. Hotspot regions enriched in immune-related genes were identified, underscoring the role of these variants in disease resistance and environmental adaptation. Our analysis revealed a strong influence of transposable elements (TEs), particularly LINEs and SINEs, on genomic rearrangements. The variants were also found to overlap with economically important traits, such as meat quality, reproduction, and immune response. Population structure analysis revealed genetic differentiation among the breeds, with Wuling cattle showing the highest differentiation. Notably, the NOTCH2 gene was identified as a candidate for regional adaptation due to its significant differentiation across populations. These findings provide valuable genomic resources for enhancing breeding programs, aiming at improving the productivity and resilience of indigenous cattle breeds in China.

Modeling the long-range effect of an inversion downstream of EFNB1 concludes a 43-year molecular diagnostic odyssey for craniofrontonasal syndrome

Craniofrontonasal syndrome (CFNS; MIM #304110) is a rare craniofacial disorder characterized by hypertelorism, a broad nasal root with a bifid nasal tip, orofacial clefting, and genital malformations caused by pathogenic variants in the X-linked gene EFNB1 (MIM *300035). CFNS exhibits sex-specific heterogeneity, with increased severity in females likely secondary to cellular interference related to random X-inactivation, resulting in mosaic EFNB1 expression. Previous studies have identified over 140 variants in EFNB1, but approximately 20% of CFNS have negative molecular testing, either due to a yet undiscovered causal gene or causal variants in regulatory regions not covered by traditional genetic testing methodologies. Here, we report a two-generation family with a clinical diagnosis of CFNS and negative clinical molecular testing. Research short-read genome testing identified a 2-Mb inversion together with two smaller deletions (13- and 7-bp), about 106-Kb downstream of EFNB1, which cosegregated with CFNS. Patient-derived fibroblasts reprogrammed into induced pluripotent stem cells (iPSCs) demonstrated two distinct iPSC populations in affected females, where one or other of the two X chromosomes was inactivated. In vitro assays further demonstrated that iPSCs with the active X chromosome bearing the inversion, exhibited a significant increase in EFNB1 expression, suggesting allelic imbalance contributes to mosaic EFNB1 expression. These findings nominate a novel causal variant type of CFNS, conclude a 43-year diagnostic odyssey for an affected family, and offer new hope for family planning for affected individuals.

A population-based analysis of the molecular landscape of glioma in adolescents and young adults reveals insights into gliomagenesis

Gliomas are a major cause of cancer-related deaths in adolescents and young adults (AYAs; ages 15-39 years). Different molecular alterations drive gliomas in children and adults, leading to distinct biology and clinical consequences, but the implications of pediatric- versus adult-type alterations in AYAs are unknown. Our population-based analysis of 1,456 clinically and molecularly characterized gliomas in patients aged 0-39 years addresses this gap. Pediatric-type alterations were found in 31% of AYA gliomas and conferred superior outcomes compared to adult-type alterations. AYA low-grade gliomas with specific RAS-MAPK alterations exhibited senescence, tended to arise in different locations and were associated with superior outcomes compared to gliomas in children, suggesting different cellular origins. Hemispheric IDH-mutant, BRAF p.V600E and FGFR-altered gliomas were associated with the risk of malignant transformation, having worse outcomes with increased age. These insights into gliomagenesis may provide a rationale for earlier intervention for certain tumors to disrupt the typical behavior, leading to improved outcomes.

Understanding the epidemiology and pathogenesis of Mycobacterium tuberculosis with non-redundant pangenome of epidemic strains in China

Tuberculosis is a major public health threat resulting in more than one million lives lost every year. Many challenges exist to defeat this deadly infectious disease which address the importance of a thorough understanding of the biology of the causative agent Mycobacterium tuberculosis (MTB). We generated a non-redundant pangenome of 420 epidemic MTB strains from China including 344 Lineage 2 strains, 69 Lineage 4 strains, six Lineage 3 strains, and one Lineage 1 strain. We estimate that MTB strains have a pangenome of 4,278 genes encoding 4,183 proteins, of which 3,438 are core genes. However, due to 99,694 interruptions in 2,447 coding genes, we can only confidently confirm 1,651 of these genes are translated in all samples. Of these interruptions, 67,315 (67.52%) could be classified by various genetic variations detected by currently available tools, and more than half of them are due to structural variations, mostly small indels. Assuming a proportion of these interruptions are artifacts, the number of active core genes would still be much lower than 3,438. We further described differential evolutionary patterns of genes under the influences of selective pressure, population structure and purifying selection. While selective pressure is ubiquitous among these coding genes, evolutionary adaptations are concentrated in 1,310 genes. Genes involved in cell wall biogenesis are under the strongest selective pressure, while the biological process of disruption of host organelles indicates the direction of the most intensive positive selection. This study provides a comprehensive view on the genetic diversity and evolutionary patterns of coding genes in MTB which may deepen our understanding of its epidemiology and pathogenicity.

A sequence context-based approach for classifying tumor structural variants without paired normal samples

Although several recent studies have characterized structural variants (SVs) in germline and cancer genomes independently, the genomic contexts of these SVs have not been comprehensively compared. We examined similarities and differences between 2 million germline and 115 thousand tumor SVs from a cohort of 963 patients from The Cancer Genome Atlas. We found significant differences in features related to their genomic sequences and localization that suggest differences between SV-generating processes and selective pressures. For example, our results show that features linked to transposon-mediated processes are associated with germline SVs, while somatic SVs more frequently show features characteristic of chromoanagenesis. These genomic differences enabled us to develop a classifier-the Germline and Tumor Structural Variant or "the great GaTSV" -that accurately distinguishes between germline and cancer SVs in tumor samples that lack a matched normal sample.

Comparisons of performances of structural variants detection algorithms in solitary or combination strategy

Structural variants (SVs) have been associated with changes in gene expression, which may contribute to alterations in phenotypes and disease development. However, the precise identification and characterization of SVs remain challenging. While long-read sequencing offers superior accuracy for SV detection, short-read sequencing remains essential due to practical and cost considerations, as well as the need to analyze existing short-read datasets. Numerous algorithms for short-read SV detection exist, but none are universally optimal, each having limitations for specific SV sizes and types. In this study, we evaluated the efficacy of six advanced SV detection algorithms, including the commercial software DRAGEN, using the GIAB v0.6 Tier 1 benchmark and HGSVC2 cell lines. We employed both individual and combination strategies, with systematic assessments of recall, precision, and F1 scores. Our results demonstrate that the union combination approach enhanced detection capabilities, surpassing single algorithms in identifying deletions and insertions, and delivered comparable recall and F1 scores to the commercial software DRAGEN. Interestingly, expanding the number of algorithms from three to five in the combination did not enhance performance, highlighting the efficiency of a well-chosen ensemble over a larger algorithmic pool.

Genomic insights into demographic history, structural variation landscape, and complex traits from 514 Hu sheep genomes

Hu sheep is an indigenous breed from the Taihu Lake Plain in China, known for its high fertility. Although Hu sheep belong to the Mongolian group, their demographic history and genetic architecture remain inconclusive. Here, we analyze 697 sheep genomes from representatives of Mongolian sheep breeds. Our study suggests that the ancestral Hu sheep first separated from the Mongolian group approximately 3000 years ago. As Hu sheep migrated from the north and flourished in the Taihu Lake Plain around 1000 years ago, they developed a unique genetic foundation and phenotypic characteristics, which are evident in the genomic footprints of selective sweeps and structural variation landscape. Genes associated with reproductive traits (BMPR1B and TDRD10) and horn phenotype (RXFP2) exhibit notable selective sweeps in the genome of Hu sheep. A genome-wide association analysis reveals that structural variations at LOC101110773, MAST2, and ZNF385B may significantly impact polledness, teat number, and early growth in Hu sheep, respectively. Our study offers insights into the evolutionary history of Hu sheep and may serve as a valuable genetic resource to enhance the understanding of complex traits in Hu sheep.

Computational Tools for Studying Genome Structural Variation

Structural variation (SV) typically refers to alterations in DNA fragments at least 50 base pairs long in the human genome. It can alter thousands of DNA nucleotides and thus significantly influence human health, disease, and clinical phenotypes. There is a shared and growing recognition that the emergence of effective computational tools and high-throughput technologies such as short-read sequencing and long-read sequencing offers novel insight into SV and, by extension, diseases affecting planetary health. However, numerous available SV tools exist with varying strengths and weaknesses. This is currently hampering the abilities of scholars to select the optimal tools to study SVs. Here, we reviewed 175 tools developed in the past two decades for SV detection, annotation, visualization, and downstream analysis of human genomics. In this expert review, we provide a comprehensive catalog of SV-related tools across different technology platforms and summarize their features, strengths, and limitations with an eye to accelerate systems science and planetary health innovations.

Rare germline structural variants increase risk for pediatric solid tumors

Pediatric solid tumors are a leading cause of childhood disease mortality. In this work, we examined germline structural variants (SVs) as risk factors for pediatric extracranial solid tumors using germline genome sequencing of 1765 affected children, their 943 unaffected parents, and 6665 adult controls. We discovered a sex-biased association between very large (>1 megabase) germline chromosomal abnormalities and increased risk of solid tumors in male children. The overall impact of germline SVs was greatest in neuroblastoma, where we uncovered burdens of ultrarare SVs that cause loss of function of highly expressed, mutationally constrained genes, as well as noncoding SVs predicted to disrupt chromatin domain boundaries. Collectively, we estimate that rare germline SVs explain 1.1 to 5.6% of pediatric cancer liability, establishing them as an important component of disease predisposition.

Integrating genetic subtypes with PET scan monitoring to predict outcome in diffuse large B-cell lymphoma

Next Generation Sequencing-based subtyping and interim- and end of treatment positron emission tomography (i/eot-PET) monitoring have high potential for upfront and on-treatment risk assessment of diffuse large B-cell lymphoma patients. We performed Dana Farber Cancer Institute (DFCI) and LymphGen genetic subtyping for the HOVON84 (n = 208, EudraCT-2006-005174-42) and PETAL (n = 204, EudraCT-2006-001641-33) trials retrospectively combined with DFCI genetic data (n = 304). For all R-CHOP treated patients (n = 592), C5/MCD- and C2/A53-subtypes show significantly worse outcome independent of the international prognostic index. For all subtypes, adverse prognostic value of i/eot-PET-positive status is confirmed. Consistent with frequent primary refractory disease, only 67% C2 patients become eot-PET-negative versus 81-88% for other subtypes. Indicative of high relapse rates, outcome of C5 i/eot-PET-negative patients remains significantly worse in HOVON-84, which trend validates in the PETAL and SAKK38-07 trials (NCT00544219). These results show the added value of integrated genetic subtyping and PET monitoring for prognostic stratification and subtype-specific trial design.

Fusion Transcript Detection from Short-Read RNA-Seq

Fusion proteins have been shown to play an important role in many different cancers and other diseases. While the causal mutation can often be found in the genome as a structural variant (SV), differentiating between normal variation within individuals and somatic variants with functional consequences can be time-consuming as well as expensive since it requires a whole-genome sequencing (WGS) method. RNA Sequencing (RNA-Seq) provides a much cheaper and more straightforward approach to the detection of functional somatic events such as overexpression of proto-oncogenes as well as gene fusion. This chapter aims to discuss the utility of RNA-Seq for fusion detection as well as provide a detailed analysis pipeline for the detection of fusion transcripts.

Recurrent small variants in NESP55/NESPAS associated with broad GNAS methylation defects and pseudohypoparathyroidism type 1B

Pseudohypoparathyroidism type 1B (PHP1B) is associated with epigenetic changes in the maternal allele of the imprinted GNAS gene that inhibit expression of the α subunit of Gs (Gsα), thereby leading to parathyroid hormone resistance in renal proximal tubule cells where expression of Gsα from the paternal GNAS allele is normally silent. Although all patients with PHP1B show loss of methylation for the exon A/B differentially methylated region (DMR), some patients with autosomal dominant PHP1B (AD-PHP1B) and most patients with sporadic PHP1B have additional methylation defects that affect the DMRs corresponding to exons XL, AS1, and NESP. Because the genetic defect is unknown in most of these patients, we sought to identify the underlying genetic basis for AD-PHP1B in 2 multigenerational families with broad GNAS methylation defects and negative clinical exomes. Genome sequencing identified small GNAS variants in each family that were also present in unrelated individuals with PHP1B in a replication cohort. Maternal transmission of one GNAS microdeletion showed reduced penetrance in some unaffected patients. Expression of AS transcripts was increased, and NESP was decreased, in cells from affected patients. These results suggest that the small deletion activated AS transcription, leading to methylation of the NESP DMR with consequent inhibition of NESP transcription, and thereby provide a potential mechanism for PHP1B.

The 1000 Chinese Indigenous Pig Genomes Project provides insights into the genomic architecture of pigs

Pigs play a central role in human livelihoods in China, but a lack of systematic large-scale whole-genome sequencing of Chinese domestic pigs has hindered genetic studies. Here, we present the 1000 Chinese Indigenous Pig Genomes Project sequencing dataset, comprising 1011 indigenous individuals from 50 pig populations covering approximately two-thirds of China's administrative divisions. Based on the deep sequencing (~25.95×) of these pigs, we identify 63.62 million genomic variants, and provide a population-specific reference panel to improve the imputation performance of Chinese domestic pig populations. Using a combination of methods, we detect an ancient admixture event related to a human immigration climax in the 13th century, which may have contributed to the formation of southeast-central Chinese pig populations. Analyzing the haplotypes of the Y chromosome shows that the indigenous populations residing around the Taihu Lake Basin exhibit a unique haplotype. Furthermore, we find a 13 kb region in the THSD7A gene that may relate to high-altitude adaptation, and a 0.47 Mb region on chromosome 7 that is significantly associated with body size traits. These results highlight the value of our genomic resource in facilitating genomic architecture and complex traits studies in pigs.

Comprehensive analysis of Mycobacterium tuberculosis genomes reveals genetic variations in bacterial virulence

Tuberculosis, a disease caused by Mycobacterium tuberculosis (Mtb), is a significant health problem worldwide. Here, we developed a method to detect large insertions and deletions (indels), which have been generally understudied. Leveraging this framework, we performed a comprehensive analysis of single nucleotide variants and small and large indels across 1,960 Mtb clinical isolates. Comparing the distribution of variants demonstrated that gene disruptive variants are underrepresented in genes essential for bacterial survival. An evolutionary analysis revealed that Mtb genomes are enriched in partially deleterious mutations. Genome-wide association studies identified small and large deletions in eccB2 significantly associated with patient prognosis. Additionally, we unveil significant associations with antibiotic resistance in 23 non-canonical genes. Among these, large indels are primarily found in genetic regions of Rv1216c, Rv1217c, fadD11, and ctpD. This study provides a comprehensive catalog of genetic variations and highlights their potential impact for the future treatment and risk prediction of tuberculosis.

Whole-genome sequencing identifies novel genes for autism in Chinese trios

Autism spectrum disorder (ASD) is a neurodevelopmental disorder with high genetic heritability but heterogeneity. Fully understanding its genetics requires whole-genome sequencing (WGS), but the ASD studies utilizing WGS data in Chinese population are limited. In this study, we present a WGS study for 334 individuals, including 112 ASD patients and their non-ASD parents. We identified 146 de novo variants in coding regions in 85 cases and 60 inherited variants in coding regions. By integrating these variants with an association model, we identified 33 potential risk genes (P<0.001) enriched in neuron and regulation related biological process. Besides the well-known ASD genes (SCN2A, NF1, SHANK3, CHD8 etc.), several high confidence genes were highlighted by a series of functional analyses, including CTNND1, DGKZ, LRP1, DDN, ZNF483, NR4A2, SMAD6, INTS1, and MRPL12, with more supported evidence from GO enrichment, expression and network analysis. We also integrated RNA-seq data to analyze the effect of the variants on the gene expression and found 12 genes in the individuals with the related variants had relatively biased expression. We further presented the clinical phenotypes of the proband carrying the risk genes in both our samples and Caucasian samples to show the effect of the risk genes on phenotype. Regarding variants in non-coding regions, a total of 74 de novo variants and 30 inherited variants were predicted as pathogenic with high confidence, which were mapped to specific genes or regulatory features. The number of de novo variants found in patient was significantly associated with the parents' ages at the birth of the child, and gender with trend. We also identified small de novo structural variants in ASD trios. The results in this study provided important evidence for understanding the genetic mechanism of ASD.

Genomic evidence of Escherichia coli gut population diversity translocation in leukemia patients

Escherichia coli, a commensal species of the human gut, is an opportunistic pathogen that can reach extra-intestinal compartments, including the bloodstream and the bladder, among others. In non-immunosuppressed patients, purifying or neutral evolution of E. coli populations has been reported in the gut. Conversely, it has been suggested that when migrating to extra-intestinal compartments, E. coli genomes undergo diversifying selection as supported by strong evidence for adaptation. The level of genomic polymorphism and the size of the populations translocating from gut to extra-intestinal compartments is largely unknown. To gain insights into the pathophysiology of these translocations, we investigated the level of polymorphism and the evolutionary forces acting on the genomes of 77 E. coli isolated from various compartments in three immunosuppressed patients. Each patient had a unique strain, which was a mutator in one case. In all instances, we observed that translocation encompasses much of the genomic diversity present in the gut. The same signature of selection, whether purifying or diversifying, and as anticipated, neutral for mutator isolates, was observed in both the gut and bloodstream. Additionally, we found a limited number of non-specific mutations among compartments for non-mutator isolates. In all cases, urine isolates were dominated by neutral selection. These findings indicate that substantial proportions of populations are undergoing translocation and that they present a complex compartment-specific pattern of selection at the patient level.IMPORTANCEIt has been suggested that intra and extra-intestinal compartments differentially constrain the evolution of E. coli strains. Whether host particular conditions, such as immunosuppression, could affect the strain evolutionary trajectories remains understudied. We found that, in immunosuppressed patients, large fractions of E. coli gut populations are translocating with variable modifications of the signature of selection for commensal and pathogenic isolates according to the compartment and/or the patient. Such multiple site sampling should be performed in large cohorts of patients to gain a better understanding of E. coli extra-intestinal diseases.

Comprehensive evaluation and guidance of structural variation detection tools in chicken whole genome sequence data

BACKGROUND

Structural variations (SVs) are widespread across genome and have a great impact on evolution, disease, and phenotypic diversity. Despite the development of numerous bioinformatic tools, commonly referred to as SV callers, tailored for detecting SVs using whole genome sequence (WGS) data and employing diverse algorithms, their performance necessitates rigorous evaluation with real data and validated SVs. Moreover, a considerable proportion of these tools have been primarily designed and optimized using human genome data. Consequently, their applicability and performance in Avian species, characterized by smaller genomes and distinct genomic architectures, remain inadequately assessed.

RESULTS

We performed a comprehensive assessment of the performance of ten widely used SV callers using population-level real genomic data with the validated five common types of SVs. The performance of SV callers varies with the types and sizes of SVs. As compared with other tools, GRIDSS, Lumpy, Wham, and Manta present better detection accuracy. Pindel can detect more small SVs than others. CNVnator and CNVkit can detect more medium and large copy number variations. Given the poor consistency among different SV callers, the combination calling strategy is not recommended. All tools show poor ability in the detection of insertions (especially with size > 150 bp). At least 50× read depth is required to detect more than 80% of the SVs for most tools.

CONCLUSIONS

This study highlights the importance and necessity of using real sequencing data, rather than simulated data only, with validated SVs for SV caller evaluation. Some practical guidance and suggestions are provided for SV detection in future researches.

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.

Genome Sequencing for Cases Unsolved by Exome Sequencing: Identifying a Single-Exon Deletion in TBCK in a Case from 30 Years Ago

In patients with neurodevelopmental disorders (NDDs), exome sequencing (ES), the diagnostic gold standard, reveals an underlying monogenic condition in only approximately 40% of cases. We report the case of a female patient with profound NDD who died 30 years ago at the age of 3 years and for whom genome sequencing (GS) now identified a single-exon deletion in TBCK previously missed by ExomeDepth, the copy number variation (CNV) detection algorithm in ES.Deoxyribonucleic acid (DNA) was extracted from frozen muscle tissue of the index patient and the parents' blood. Genome data were analyzed for structural variants and single nucleotide variants (SUVs)/indels as part of the Bavarian Genomes consortium project.Biallelic variants in TBCK, which are linked to the autosomal recessive disorder TBCK syndrome, were detected in the affected individual: a novel frameshift variant and a deletion of exon 23, previously established as common but underrecognized pathogenic variant in individuals with TBCK syndrome. While in the foregoing ES analysis, calling algorithms for (SNVs)/indels were able to identify the frameshift variant, ExomeDepth failed to call the intragenic deletion.Our case illustrates the added value of GS for the detection of single-exon deletions for which calling from ES data remains challenging and confirms that the deletion of exon 23 in TBCK may be underdiagnosed in patients with NDDs. Furthermore, it shows the importance of "molecular or genetic autopsy" allowing genetic risk counseling for family members as well as the end of a diagnostic odyssey of 30 years.

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.

Limited Added Diagnostic Value of Whole Genome Sequencing in Genetic Testing of Inherited Retinal Diseases in a Swiss Patient Cohort

The purpose of this study was to assess the added diagnostic value of whole genome sequencing (WGS) for patients with inherited retinal diseases (IRDs) who remained undiagnosed after whole exome sequencing (WES). WGS was performed for index patients in 66 families. The datasets were analyzed according to GATK's guidelines. Additionally, DeepVariant was complemented by GATK's workflow, and a novel structural variant pipeline was developed. Overall, a molecular diagnosis was established in 19/66 (28.8%) index patients. Pathogenic deletions and one deep-intronic variant contributed to the diagnostic yield in 4/19 and 1/19 index patients, respectively. The remaining diagnoses (14/19) were attributed to exonic variants that were missed during WES analysis due to bioinformatic limitations, newly described loci, or unclear pathogenicity. The added diagnostic value of WGS equals 5/66 (9.6%) for our cohort, which is comparable to previous studies. This figure would decrease further to 1/66 (1.5%) with a standardized and reliable copy number variant workflow during WES analysis. Given the higher costs and limited added value, the implementation of WGS as a first-tier assay for inherited eye disorders in a diagnostic laboratory remains untimely. Instead, progress in bioinformatic tools and communication between diagnostic and clinical teams have the potential to ameliorate diagnostic yields.

Long-read genome sequencing reveals a novel intronic retroelement insertion in NR5A1 associated with 46,XY differences of sexual development

Despite significant advancements in rare genetic disease diagnostics, many patients with rare genetic disease remain without a molecular diagnosis. Novel tools and methods are needed to improve the detection of disease-associated variants and understand the genetic basis of many rare diseases. Long-read genome sequencing provides improved sequencing in highly repetitive, homologous, and low-complexity regions, and improved assessment of structural variation and complex genomic rearrangements compared to short-read genome sequencing. As such, it is a promising method to explore overlooked genetic variants in rare diseases with a high suspicion of a genetic basis. We therefore applied PacBio HiFi sequencing in a large multi-generational family presenting with autosomal dominant 46,XY differences of sexual development (DSD), for whom extensive molecular testing over multiple decades had failed to identify a molecular diagnosis. This revealed a rare SINE-VNTR-Alu retroelement insertion in intron 4 of NR5A1, a gene in which loss-of-function variants are an established cause of 46,XY DSD. The insertion segregated among affected family members and was associated with loss-of-expression of alleles in cis, demonstrating a functional impact on NR5A1. This case highlights the power of long-read genome sequencing to detect genomic variants that have previously been intractable to detection by standard short-read genomic testing.

Comparative evaluation of SNVs, indels, and structural variations detected with short- and long-read sequencing data

Short- and long-read sequencing technologies are routinely used to detect DNA variants, including SNVs, indels, and structural variations (SVs). However, the differences in the quality and quantity of variants detected between short- and long-read data are not fully understood. In this study, we comprehensively evaluated the variant calling performance of short- and long-read-based SNV, indel, and SV detection algorithms (6 for SNVs, 12 for indels, and 13 for SVs) using a novel evaluation framework incorporating manual visual inspection. The results showed that indel-insertion calls greater than 10 bp were poorly detected by short-read-based detection algorithms compared to long-read-based algorithms; however, the recall and precision of SNV and indel-deletion detection were similar between short- and long-read data. The recall of SV detection with short-read-based algorithms was significantly lower in repetitive regions, especially for small- to intermediate-sized SVs, than that detected with long-read-based algorithms. In contrast, the recall and precision of SV detection in nonrepetitive regions were similar between short- and long-read data. These findings suggest the need for refined strategies, such as incorporating multiple variant detection algorithms, to generate a more complete set of variants using short-read data.

Distinct genomic contexts predict gene presence-absence variation in different pathotypes of Magnaporthe oryzae

Fungi use the accessory gene content of their pangenomes to adapt to their environments. While gene presence-absence variation contributes to shaping accessory gene reservoirs, the genomic contexts that shape these events remain unclear. Since pangenome studies are typically species-wide and do not analyze different populations separately, it is yet to be uncovered whether presence-absence variation patterns and mechanisms are consistent across populations. Fungal plant pathogens are useful models for studying presence-absence variation because they rely on it to adapt to their hosts, and members of a species often infect distinct hosts. We analyzed gene presence-absence variation in the blast fungus, Magnaporthe oryzae (syn. Pyricularia oryzae), and found that presence-absence variation genes involved in host-pathogen and microbe-microbe interactions may drive the adaptation of the fungus to its environment. We then analyzed genomic and epigenomic features of presence-absence variation and observed that proximity to transposable elements, gene GC content, gene length, expression level in the host, and histone H3K27me3 marks were different between presence-absence variation genes and conserved genes. We used these features to construct a model that was able to predict whether a gene is likely to experience presence-absence variation with high precision (86.06%) and recall (92.88%) in M. oryzae. Finally, we found that presence-absence variation genes in the rice and wheat pathotypes of M. oryzae differed in their number and their genomic context. Our results suggest that genomic and epigenomic features of gene presence-absence variation can be used to better understand and predict fungal pangenome evolution. We also show that substantial intra-species variation can exist in these features.

Comparison of structural variant callers for massive whole-genome sequence data

BACKGROUND

Detecting structural variations (SVs) at the population level using next-generation sequencing (NGS) requires substantial computational resources and processing time. Here, we compared the performances of 11 SV callers: Delly, Manta, GridSS, Wham, Sniffles, Lumpy, SvABA, Canvas, CNVnator, MELT, and INSurVeyor. These SV callers have been recently published and have been widely employed for processing massive whole-genome sequencing datasets. We evaluated the accuracy, sequence depth, running time, and memory usage of the SV callers.

RESULTS

Notably, several callers exhibited better calling performance for deletions than for duplications, inversions, and insertions. Among the SV callers, Manta identified deletion SVs with better performance and efficient computing resources, and both Manta and MELT demonstrated relatively good precision regarding calling insertions. We confirmed that the copy number variation callers, Canvas and CNVnator, exhibited better performance in identifying long duplications as they employ the read-depth approach. Finally, we also verified the genotypes inferred from each SV caller using a phased long-read assembly dataset, and Manta showed the highest concordance in terms of the deletions and insertions.

CONCLUSIONS

Our findings provide a comprehensive understanding of the accuracy and computational efficiency of SV callers, thereby facilitating integrative analysis of SV profiles in diverse large-scale genomic datasets.

A harmonized public resource of deeply sequenced diverse human genomes

Underrepresented populations are often excluded from genomic studies due 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 4,094 whole genomes from 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 demonstrate substantial added value from this dataset compared to 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 to 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.

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 generated 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. Seventy-five percent of elements (44 of 59) validated in an in vivo transgenic reporter assay, demonstrating that single cell accessibility is a strong predictor of enhancer activity. Applying our cMN atlas to 899 whole genome sequences from 270 genetically unsolved CCDD pedigrees, we achieved significant reduction in our variant search space and nominated candidate variants predicted to regulate known CCDD disease genes MAFB, PHOX2A, CHN1, and EBF3 - as well as new candidates in recurrently mutated enhancers through peak- and gene-centric allelic aggregation. This work provides novel 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.

Advances in the discovery and analyses of human tandem repeats

Long-read sequencing platforms provide unparalleled access to the structure and composition of all classes of tandemly repeated DNA from STRs to satellite arrays. This review summarizes our current understanding of their organization within the human genome, their importance with respect to disease, as well as the advances and challenges in understanding their genetic diversity and functional effects. Novel computational methods are being developed to visualize and associate these complex patterns of human variation with disease, expression, and epigenetic differences. We predict accurate characterization of this repeat-rich form of human variation will become increasingly relevant to both basic and clinical human genetics.

Systematic evaluation of multiple NGS platforms for structural variants detection

Structural variations (SV) are critical genome changes affecting human diseases. Although many hybridization-based methods exist, evaluating SVs through next-generation sequencing (NGS) data is still necessary for broader research exploration. Here, we comprehensively compared the performance of 16 SV callers and multiple NGS platforms using NA12878 whole genome sequencing (WGS) datasets. The results indicated that several SV callers performed well relatively, such as Manta, GRIDSS, LUMPY, TARDIS, FermiKit, and Wham. Meanwhile, all NGS platforms have a similar performance using a single software. Additionally, we found that the source of undetected SVs was mostly from long reads datasets, therefore, the more appropriate strategy for accurate SV detection will be an integration of long and shorter reads in the future. At present, in the period of NGS as a mainstream method in bioinformatics, our study would provide helpful and comprehensive guidelines for specific categories of SV research.

Quartet DNA reference materials and datasets for comprehensively evaluating germline variant calling performance

BACKGROUND

Genomic DNA reference materials are widely recognized as essential for ensuring data quality in omics research. However, relying solely on reference datasets to evaluate the accuracy of variant calling results is incomplete, as they are limited to benchmark regions. Therefore, it is important to develop DNA reference materials that enable the assessment of variant detection performance across the entire genome.

RESULTS

We established a DNA reference material suite from four immortalized cell lines derived from a family of parents and monozygotic twins. Comprehensive reference datasets of 4.2 million small variants and 15,000 structural variants were integrated and certified for evaluating the reliability of germline variant calls inside the benchmark regions. Importantly, the genetic built-in-truth of the Quartet family design enables estimation of the precision of variant calls outside the benchmark regions. Using the Quartet reference materials along with study samples, batch effects are objectively monitored and alleviated by training a machine learning model with the Quartet reference datasets to remove potential artifact calls. Moreover, the matched RNA and protein reference materials and datasets from the Quartet project enables cross-omics validation of variant calls from multiomics data.

CONCLUSIONS

The Quartet DNA reference materials and reference datasets provide a unique resource for objectively assessing the quality of germline variant calls throughout the whole-genome regions and improving the reliability of large-scale genomic profiling.

Next-Generation sequencing transforming clinical practice and precision medicine

Next-generation sequencing (NGS) has revolutionized the field of genomics and is rapidly transforming clinical diagnosis and precision medicine. This advanced sequencing technology enables the rapid and cost-effective analysis of large-scale genomic data, allowing comprehensive exploration of the genetic landscape of diseases. In clinical diagnosis, NGS has proven to be a powerful tool for identifying disease-causing variants, enabling accurate and early detection of genetic disorders. Additionally, NGS facilitates the identification of novel disease-associated genes and variants, aiding in the development of targeted therapies and personalized treatment strategies. NGS greatly benefits precision medicine by enhancing our understanding of disease mechanisms and enabling the identification of specific molecular markers for disease subtypes, thus enabling tailored medical interventions based on individual characteristics. Furthermore, NGS contributes to the development of non-invasive diagnostic approaches, such as liquid biopsies, which can monitor disease progression and treatment response. The potential of NGS in clinical diagnosis and precision medicine is vast, yet challenges persist in data analysis, interpretation, and protocol standardization. This review highlights NGS applications in disease diagnosis, prognosis, and personalized treatment strategies, while also addressing challenges and future prospects in fully harnessing genomic potential within clinical practice.

Systematic evaluation of genome sequencing for the diagnostic assessment of autism spectrum disorder and fetal structural anomalies

Short-read genome sequencing (GS) holds the promise of becoming the primary diagnostic approach for the assessment of autism spectrum disorder (ASD) and fetal structural anomalies (FSAs). However, few studies have comprehensively evaluated its performance against current standard-of-care diagnostic tests: karyotype, chromosomal microarray (CMA), and exome sequencing (ES). To assess the clinical utility of GS, we compared its diagnostic yield against these three tests in 1,612 quartet families including an individual with ASD and in 295 prenatal families. Our GS analytic framework identified a diagnostic variant in 7.8% of ASD probands, almost 2-fold more than CMA (4.3%) and 3-fold more than ES (2.7%). However, when we systematically captured copy-number variants (CNVs) from the exome data, the diagnostic yield of ES (7.4%) was brought much closer to, but did not surpass, GS. Similarly, we estimated that GS could achieve an overall diagnostic yield of 46.1% in unselected FSAs, representing a 17.2% increased yield over karyotype, 14.1% over CMA, and 4.1% over ES with CNV calling or 36.1% increase without CNV discovery. Overall, GS provided an added diagnostic yield of 0.4% and 0.8% beyond the combination of all three standard-of-care tests in ASD and FSAs, respectively. This corresponded to nine GS unique diagnostic variants, including sequence variants in exons not captured by ES, structural variants (SVs) inaccessible to existing standard-of-care tests, and SVs where the resolution of GS changed variant classification. Overall, this large-scale evaluation demonstrated that GS significantly outperforms each individual standard-of-care test while also outperforming the combination of all three tests, thus warranting consideration as the first-tier diagnostic approach for the assessment of ASD and FSAs.

Next-Generation Sequencing Technology: Current Trends and Advancements

The advent of next-generation sequencing (NGS) has brought about a paradigm shift in genomics research, offering unparalleled capabilities for analyzing DNA and RNA molecules in a high-throughput and cost-effective manner. This transformative technology has swiftly propelled genomics advancements across diverse domains. NGS allows for the rapid sequencing of millions of DNA fragments simultaneously, providing comprehensive insights into genome structure, genetic variations, gene expression profiles, and epigenetic modifications. The versatility of NGS platforms has expanded the scope of genomics research, facilitating studies on rare genetic diseases, cancer genomics, microbiome analysis, infectious diseases, and population genetics. Moreover, NGS has enabled the development of targeted therapies, precision medicine approaches, and improved diagnostic methods. This review provides an insightful overview of the current trends and recent advancements in NGS technology, highlighting its potential impact on diverse areas of genomic research. Moreover, the review delves into the challenges encountered and future directions of NGS technology, including endeavors to enhance the accuracy and sensitivity of sequencing data, the development of novel algorithms for data analysis, and the pursuit of more efficient, scalable, and cost-effective solutions that lie ahead.

Chronic treatment with ATR and CHK1 inhibitors does not substantially increase the mutational burden of human cells

DNA replication stress (RS) entails the frequent slow down and arrest of replication forks by a variety of conditions that hinder accurate and processive genome duplication. Elevated RS leads to genome instability, replication catastrophe and eventually cell death. RS is particularly prevalent in cancer cells and its exacerbation to unsustainable levels by chemotherapeutic agents remains a cornerstone of cancer treatments. The adverse consequences of RS are normally prevented by the ATR and CHK1 checkpoint kinases that stabilize stressed forks, suppress origin firing and promote cell cycle arrest when replication is perturbed. Specific inhibitors of these kinases have been developed and shown to potentiate RS and cell death in multiple in vitro cancer settings. Ongoing clinical trials are now probing their efficacy against various cancer types, either as single agents or in combination with mainstay chemotherapeutics. Despite their promise as valuable additions to the anti-cancer pharmacopoeia, we still lack a genome-wide view of the potential mutagenicity of these new drugs. To investigate this question, we performed chronic long-term treatments of TP53-depleted human cancer cells with ATR and CHK1 inhibitors (ATRi, AZD6738/ceralasertib and CHK1i, MK8776/SCH-900776). ATR or CHK1 inhibition did not significantly increase the mutational burden of cells, nor generate specific mutational signatures. Indeed, no notable changes in the numbers of base substitutions, short insertions/deletions and larger scale rearrangements were observed despite induction of replication-associated DNA breaks during treatments. Interestingly, ATR inhibition did induce a slight increase in closely-spaced mutations, a feature previously attributed to translesion synthesis DNA polymerases. The results suggest that ATRi and CHK1i do not have substantial mutagenic effects in vitro when used as standalone agents.

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

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

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

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

Whole genome analysis for 163 gRNAs in Cas9-edited mice reveals minimal off-target activity

Genome editing with CRISPR-associated (Cas) proteins holds exceptional promise for "correcting" variants causing genetic disease. To realize this promise, off-target genomic changes cannot occur during the editing process. Here, we use whole genome sequencing to compare the genomes of 50 Cas9-edited founder mice to 28 untreated control mice to assess the occurrence of S. pyogenes Cas9-induced off-target mutagenesis. Computational analysis of whole-genome sequencing data detects 26 unique sequence variants at 23 predicted off-target sites for 18/163 guides used. While computationally detected variants are identified in 30% (15/50) of Cas9 gene-edited founder animals, only 38% (10/26) of the variants in 8/15 founders validate by Sanger sequencing. In vitro assays for Cas9 off-target activity identify only two unpredicted off-target sites present in genome sequencing data. In total, only 4.9% (8/163) of guides tested have detectable off-target activity, a rate of 0.2 Cas9 off-target mutations per founder analyzed. In comparison, we observe ~1,100 unique variants in each mouse regardless of genome exposure to Cas9 indicating off-target variants comprise a small fraction of genetic heterogeneity in Cas9-edited mice. These findings will inform future design and use of Cas9-edited animal models as well as provide context for evaluating off-target potential in genetically diverse patient populations.

Genome-Wide Analysis of Structural Variants in Parkinson Disease

OBJECTIVE

Identification of genetic risk factors for Parkinson disease (PD) has to date been primarily limited to the study of single nucleotide variants, which only represent a small fraction of the genetic variation in the human genome. Consequently, causal variants for most PD risk are not known. Here we focused on structural variants (SVs), which represent a major source of genetic variation in the human genome. We aimed to discover SVs associated with PD risk by performing the first large-scale characterization of SVs in PD.

METHODS

We leveraged a recently developed computational pipeline to detect and genotype SVs from 7,772 Illumina short-read whole genome sequencing samples. Using this set of SV variants, we performed a genome-wide association study using 2,585 cases and 2,779 controls and identified SVs associated with PD risk. Furthermore, to validate the presence of these variants, we generated a subset of matched whole-genome long-read sequencing data.

RESULTS

We genotyped and tested 3,154 common SVs, representing over 412 million nucleotides of previously uncatalogued genetic variation. Using long-read sequencing data, we validated the presence of three novel deletion SVs that are associated with risk of PD from our initial association analysis, including a 2 kb intronic deletion within the gene LRRN4.

INTERPRETATION

We identified three SVs associated with genetic risk of PD. This study represents the most comprehensive assessment of the contribution of SVs to the genetic risk of PD to date. ANN NEUROL 2023;93:1012-1022.

Analysis of genome instability and implications for the consequent phenotype in Plasmodium falciparum containing mutated MSH2-1 (P513T)

Malarial parasites exhibit extensive genomic plasticity, which induces the antigen diversification and the development of antimalarial drug resistance. Only a few studies have examined the genome maintenance mechanisms of parasites. The study aimed at elucidating the impact of a mutation in a DNA mismatch repair gene on genome stability by maintaining the mutant and wild-type parasites through serial in vitro cultures for approximately 400 days and analysing the subsequent spontaneous mutations. A P513T mutant of the DNA mismatch repair protein PfMSH2-1 from Plasmodium falciparum 3D7 was created. The mutation did not influence the base substitution rate but significantly increased the insertion/deletion (indel) mutation rate in short tandem repeats (STRs) and minisatellite loci. STR mutability was affected by allele size, genomic category and certain repeat motifs. In the mutants, significant telomere healing and homologous recombination at chromosomal ends caused extensive gene loss and generation of chimeric genes, resulting in large-scale chromosomal alteration. Additionally, the mutant showed increased tolerance to N-methyl-N'-nitro-N-nitrosoguanidine, suggesting that PfMSH2-1 was involved in recognizing DNA methylation damage. This work provides valuable insights into the role of PfMSH2-1 in genome stability and demonstrates that the genomic destabilization caused by its dysfunction may lead to antigen diversification.

Distinct genomic contexts predict gene presence-absence variation in different pathotypes of a fungal plant pathogen

Background

Fungi use the accessory segments of their pan-genomes to adapt to their environments. While gene presence-absence variation (PAV) contributes to shaping these accessory gene reservoirs, whether these events happen in specific genomic contexts remains unclear. Additionally, since pan-genome studies often group together all members of the same species, it is uncertain whether genomic or epigenomic features shaping pan-genome evolution are consistent across populations within the same species. Fungal plant pathogens are useful models for answering these questions because members of the same species often infect distinct hosts, and they frequently rely on gene PAV to adapt to these hosts.

Results

We analyzed gene PAV in the rice and wheat blast fungus, Magnaporthe oryzae, and found that PAV of disease-causing effectors, antibiotic production, and non-self-recognition genes may drive the adaptation of the fungus to its environment. We then analyzed genomic and epigenomic features and data from available datasets for patterns that might help explain these PAV events. We observed that proximity to transposable elements (TEs), gene GC content, gene length, expression level in the host, and histone H3K27me3 marks were different between PAV genes and conserved genes, among other features. We used these features to construct a random forest classifier that was able to predict whether a gene is likely to experience PAV with high precision (86.06%) and recall (92.88%) in rice-infecting M. oryzae. Finally, we found that PAV in wheat- and rice-infecting pathotypes of M. oryzae differed in their number and their genomic context.

Conclusions

Our results suggest that genomic and epigenomic features of gene PAV can be used to better understand and even predict fungal pan-genome evolution. We also show that substantial intra-species variation can exist in these features.

Genomic architecture of autism from comprehensive whole-genome sequence annotation

Fully understanding autism spectrum disorder (ASD) genetics requires whole-genome sequencing (WGS). We present the latest release of the Autism Speaks MSSNG resource, which includes WGS data from 5,100 individuals with ASD and 6,212 non-ASD parents and siblings (total n = 11,312). Examining a wide variety of genetic variants in MSSNG and the Simons Simplex Collection (SSC; n = 9,205), we identified ASD-associated rare variants in 718/5,100 individuals with ASD from MSSNG (14.1%) and 350/2,419 from SSC (14.5%). Considering genomic architecture, 52% were nuclear sequence-level variants, 46% were nuclear structural variants (including copy-number variants, inversions, large insertions, uniparental isodisomies, and tandem repeat expansions), and 2% were mitochondrial variants. Our study provides a guidebook for exploring genotype-phenotype correlations in families who carry ASD-associated rare variants and serves as an entry point to the expanded studies required to dissect the etiology in the ∼85% of the ASD population that remain idiopathic.

Genomic and microenvironmental landscape of stage I follicular lymphoma, compared with stage III/IV

Although the genomic and immune microenvironmental landscape of follicular lymphoma (FL) has been extensively investigated, little is known about the potential biological differences between stage I and stage III/IV disease. Using next-generation sequencing and immunohistochemistry, 82 FL nodal stage I cases were analyzed and compared with 139 FL stage III/IV nodal cases. Many similarities in mutations, chromosomal copy number aberrations, and microenvironmental cell populations were detected. However, there were also significant differences in microenvironmental and genomic features. CD8+ T cells (P = .02) and STAT6 mutations (false discovery rate [FDR] <0.001) were more frequent in stage I FL. In contrast, programmed cell death protein 1-positive T cells, CD68+/CD163+ macrophages (P < .001), BCL2 translocation (BCL2trl+) (P < .0001), and KMT2D (FDR = 0.003) and CREBBP (FDR = 0.04) mutations were found more frequently in stage III/IV FL. Using clustering, we identified 3 clusters within stage I, and 2 clusters within stage III/IV. The BLC2trl+ stage I cluster was comparable to the BCL2trl+ cluster in stage III/IV. The two BCL2trl- stage I clusters were unique for stage I. One was enriched for CREBBP (95%) and STAT6 (64%) mutations, without BLC6 translocation (BCL6trl), whereas the BCL2trl- stage III/IV cluster contained BCL6trl (64%) with fewer CREBBP (45%) and STAT6 (9%) mutations. The other BCL2trl- stage I cluster was relatively heterogeneous with more copy number aberrations and linker histone mutations. This exploratory study shows that stage I FL is genetically heterogeneous with different underlying oncogenic pathways. Stage I FL BCL2trl- is likely STAT6 driven, whereas BCL2trl- stage III/IV appears to be more BCL6trl driven.

A survey of current methods to detect and genotype inversions

Polymorphic inversions are ubiquitous in humans, and they have been linked to both adaptation and disease. Following their discovery in Drosophila more than a century ago, inversions have proved to be more elusive than other structural variants. A wide variety of methods for the detection and genotyping of inversions have recently been developed: multiple techniques based on selective amplification by PCR, short- and long-read sequencing approaches, principal component analysis of small variant haplotypes, template strand sequencing, optical mapping, and various genome assembly methods. Many methods apply complex wet lab protocols or increasingly refined bioinformatic analyses. This review is an attempt to provide a practical summary and comparison of the methods that are in current use, with a focus on metrics such as the maximum size of segmental duplications at inversion breakpoints that each method can tolerate, the size range of inversions that they recover, their throughput, and whether the locations of putative inversions must be known beforehand. This article is protected by copyright. All rights reserved.

High-coverage whole-genome sequencing of the expanded 1000 Genomes Project cohort including 602 trios

The 1000 Genomes Project (1kGP) is the largest fully open resource of whole-genome sequencing (WGS) data consented for public distribution without access or use restrictions. The final, phase 3 release of the 1kGP included 2,504 unrelated samples from 26 populations and was based primarily on low-coverage WGS. Here, we present a high-coverage 3,202-sample WGS 1kGP resource, which now includes 602 complete trios, sequenced to a depth of 30X using Illumina. We performed single-nucleotide variant (SNV) and short insertion and deletion (INDEL) discovery and generated a comprehensive set of structural variants (SVs) by integrating multiple analytic methods through a machine learning model. We show gains in sensitivity and precision of variant calls compared to phase 3, especially among rare SNVs as well as INDELs and SVs spanning frequency spectrum. We also generated an improved reference imputation panel, making variants discovered here accessible for association studies.

Interstitial deletion 4p15.32p16.1 and complex chromoplexy in a female proband with severe neurodevelopmental delay, growth failure and dysmorphism

Complex chromosomal rearrangements involve the restructuring of genetic material within a single chromosome or across multiple chromosomes. These events can cause serious human disease by disrupting coding DNA and gene regulatory elements via deletions, duplications, and structural rearrangements. Here we describe a 5-year-old female with severe developmental delay, dysmorphic features, multi-suture craniosynostosis, and growth failure found to have a complex series of balanced intra- and inter-chromosomal rearrangements involving chromosomes 4, 11, 13, and X. Initial clinical studies were performed by karyotype, chromosomal microarray, and FISH with research-based short-read genome sequencing coupled with sanger sequencing to precisely map her breakpoints to the base pair resolution to understand the molecular basis of her phenotype. Genome analysis revealed two pathogenic deletions at 4p16.1-p15.32 and 4q31.1, accounting for her developmental delay and dysmorphism. We identified over 60 breakpoints, many with blunt ends and limited homology, supporting a role for non-homologous end joining in restructuring and resolution of the seminal chromoplexy event. We propose that the complexity of our patient’s genomic rearrangements with a high number of breakpoints causes dysregulation of gene expression by three-dimensional chromatin interactions or topologically associating domains leading to growth failure and craniosynostosis. Our work supports an important role for genome sequencing in understanding the molecular basis of complex chromosomal rearrangements in human disease.

Whole-Genome Sequencing Identifies PPARGC1A as a Putative Modifier of Cancer Risk in BRCA1/2 Mutation Carriers

While BRCA1 and BRCA2 mutations are known to confer the largest risk of breast cancer and ovarian cancer, the incomplete penetrance of the mutations and the substantial variability in age at cancer onset among carriers suggest additional factors modifying the risk of cancer in BRCA1/2 mutation carriers. To identify genetic modifiers of BRCA1/2, we carried out a whole-genome sequencing study of 66 ovarian cancer patients that were enriched with BRCA carriers, followed by validation using data from the Pan-Cancer Analysis of Whole Genomes Consortium. We found PPARGC1A, a master regulator of mitochondrial biogenesis and function, to be highly mutated in BRCA carriers, and patients with both PPARGC1A and BRCA1/2 mutations were diagnosed with breast or ovarian cancer at significantly younger ages, while the mutation status of each gene alone did not significantly associate with age of onset. Our study suggests PPARGC1A as a possible BRCA modifier gene. Upon further validation, this finding can help improve cancer risk prediction and provide personalized preventive care for BRCA carriers.

TT-Mars: structural variants assessment based on haplotype-resolved assemblies

Variant benchmarking is often performed by comparing a test callset to a gold standard set of variants. In repetitive regions of the genome, it may be difficult to establish what is the truth for a call, for example, when different alignment scoring metrics provide equally supported but different variant calls on the same data. Here, we provide an alternative approach, TT-Mars, that takes advantage of the recent production of high-quality haplotype-resolved genome assemblies by providing false discovery rates for variant calls based on how well their call reflects the content of the assembly, rather than comparing calls themselves.

Curated variation benchmarks for challenging medically relevant autosomal genes

The repetitive nature and complexity of some medically relevant genes poses a challenge for their accurate analysis in a clinical setting. The Genome in a Bottle Consortium has provided variant benchmark sets, but these exclude nearly 400 medically relevant genes due to their repetitiveness or polymorphic complexity. Here, we characterize 273 of these 395 challenging autosomal genes using a haplotype-resolved whole-genome assembly. This curated benchmark reports over 17,000 single-nucleotide variations, 3,600 insertions and deletions and 200 structural variations each for human genome reference GRCh37 and GRCh38 across HG002. We show that false duplications in either GRCh37 or GRCh38 result in reference-specific, missed variants for short- and long-read technologies in medically relevant genes, including CBS, CRYAA and KCNE1. When masking these false duplications, variant recall can improve from 8% to 100%. Forming benchmarks from a haplotype-resolved whole-genome assembly may become a prototype for future benchmarks covering the whole genome.

Multiple types of genomic variation contribute to adaptive traits in the mustelid subfamily Guloninae

Species of the mustelid subfamily Guloninae inhabit diverse habitats on multiple continents, and occupy a variety of ecological niches. They differ in feeding ecologies, reproductive strategies and morphological adaptations. To identify candidate loci associated with adaptations to their respective environments, we generated a de novo assembly of the tayra (Eira barbara), the earliest diverging species in the subfamily, and compared this with the genomes available for the wolverine (Gulo gulo) and the sable (Martes zibellina). Our comparative genomic analyses included searching for signs of positive selection, examining changes in gene family sizes, as well as searching for species-specific structural variants (SVs). Among candidate loci associated with phenotypic traits, we observed many related to diet, body condition and reproduction. For example, for the tayra, which has an atypical gulonine reproductive strategy of aseasonal breeding, we observe species-specific changes in many pregnancy-related genes. For the wolverine, a circumpolar hypercarnivore that must cope with seasonal food scarcity, we observed many changes in genes associated with diet and body condition. All types of genomic variation examined (single nucleotide polymorphisms, gene family expansions, structural variants) contributed substantially to the identification of candidate loci. This strongly argues for consideration of variation other than single nucleotide polymorphisms in comparative genomics studies aiming to identify loci of adaptive significance.

Similarity-Based Analysis of Allele Frequency Distribution among Multiple Populations Identifies Adaptive Genomic Structural Variants

Structural variants have a considerable impact on human genomic diversity. However, their evolutionary history remains mostly unexplored. Here, we developed a new method to identify potentially adaptive structural variants based on a similarity-based analysis that incorporates genotype frequency data from 26 populations simultaneously. Using this method, we analyzed 57,629 structural variants and identified 576 structural variants that show unusual population differentiation. Of these putatively adaptive structural variants, we further showed that 24 variants are multiallelic and overlap with coding sequences, and 20 variants are significantly associated with GWAS traits. Closer inspection of the haplotypic variation associated with these putatively adaptive and functional structural variants reveals deviations from neutral expectations due to: 1) population differentiation of rapidly evolving multiallelic variants, 2) incomplete sweeps, and 3) recent population-specific negative selection. Overall, our study provides new methodological insights, documents hundreds of putatively adaptive variants, and introduces evolutionary models that may better explain the complex evolution of structural variants.