Large Structural Variants Research Articles

Quantitative haplotype-resolved analysis of mitochondrial DNA heteroplasmy in Human single oocytes, blastoids, and pluripotent stem cells.

Maternal mitochondria are the sole source of mtDNA for every cell of the offspring. Heteroplasmic mtDNA mutations inherited from the oocyte are a common cause of metabolic diseases and associated with late-onset diseases. However, the origin and dynamics of mtDNA heteroplasmy remain unclear. We used our individual Mitochondrial Genome sequencing (iMiGseq) technology to study mtDNA heterogeneity, quantitate single nucleotide variants (SNVs) and large structural variants (SVs), track heteroplasmy dynamics, and analyze genetic linkage between variants at the individual mtDNA molecule level in single oocytes and human blastoids. Our study presented the first single-mtDNA analysis of the comprehensive heteroplasmy landscape in single human oocytes. Unappreciated levels of rare heteroplasmic variants well below the detection limit of conventional methods were identified in healthy human oocytes, of which many are reported to be deleterious and associated with mitochondrial disease and cancer. Quantitative genetic linkage analysis revealed dramatic shifts of variant frequency and clonal expansions of large SVs during oogenesis in single-donor oocytes. iMiGseq of a single human blastoid suggested stable heteroplasmy levels during early lineage differentiation of naïve pluripotent stem cells. Therefore, our data provided new insights of mtDNA genetics and laid a foundation for understanding mtDNA heteroplasmy at early stages of life.

Abstract 6539: Application of optical genome mapping to identify samples with homologous recombination deficiency

Abstract Certain cancer treatments, such as the poly (ADP-ribos) polymerase (PARP) inhibitors, have been shown to be effective in killing cancer cells exhibiting genome instability signatures indicative of homologous recombination deficiency (HRD). Hence, these signatures are used as biomarkers to inform treatment decisions and prognosis. There are three measurements of HRD signatures commonly employed: loss of heterozygosity (HRD-LOH), telomeric allelic imbalance (TAI) and large-scale state transition (LST). It has been shown that combining all three scores can better determine the HRD phenotype, leading to a higher clinical impact. Yet current HRD signature tests, used to estimate HRD, have low negative predictive value, and one possible reason is that current genomic technologies lack sensitivity to capture the full extent of somatic genomic rearrangements. Here, optical genome mapping (OGM) was used to detect large structural variants (SVs) and calculate a HRD score. OGM captures high molecular weight DNA to call SVs by aligning these molecules to the public reference genome. OGM can comprehensively detect insertions and deletions >5kbp, inversions, interchromosomal translocations, plus large interstitial copy number variation (CNV) and aneusomies. Subsequently, an automated script was developed to compute the HRD score, which is the summation of the three HRD signatures: HRD-LOH, the number of regions with a loss >15 Mbp but shorter than the whole chromosome; TAI, the number of regions of gain and loss >10Mbp that extend to a subtelomere but do not cross the centromere; and LST, the number of chromosomal breakpoints whose SV size >10Mb but not the whole chromosome. We applied this script on 20 samples of solid tumors and myeloid neoplasms, and the automated scores are concordant with expertly curated scores, confirming the validity of the calculation. We believe that OGM data combined with this automated analysis of HRD signatures is much more sensitive and accurate for detection of HRD signatures and that this will enable more precise prediction of drug response for multiple tumor types. Citation Format: Andy Wing Chun Pang, Kelsea Chang, Nikhil Sahajpal, Daniel Saul, Ravindra Kolhe, Alka Chaubey, Alex Hastie. Application of optical genome mapping to identify samples with homologous recombination deficiency [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6539.

Three-dimensional and single-cell sequencing of liver cancer reveals comprehensive host-virus interactions in HBV infection.

Hepatitis B virus (HBV) infection is a major risk factor for chronic liver diseases and liver cancer (mainly hepatocellular carcinoma, HCC), while the underlying mechanisms and host-virus interactions are still largely elusive. We applied HiC sequencing to HepG2 (HBV-) and HepG2-2.2.15 (HBV+) cell lines and combined them with public HCC single-cell RNA-seq data, HCC bulk RNA-seq data, and both genomic and epigenomic ChIP-seq data to reveal potential disease mechanisms of HBV infection and host-virus interactions reflected by 3D genome organization. We found that HBV enhanced overall proximal chromatin interactions (CIs) of liver cells and primarily affected regional CIs on chromosomes 13, 14, 17, and 22. Interestingly, HBV altered the boundaries of many topologically associating domains (TADs), and genes nearby these boundaries showed functional enrichment in cell adhesion which may promote cancer metastasis. Moreover, A/B compartment analysis revealed dramatic changes on chromosomes 9, 13 and 21, with more B compartments (inactive or closed) shifting to A compartments (active or open). The A-to-B regions (closing) harbored enhancers enriched in the regulation of inflammatory responses, whereas B-to-A regions (opening) were enriched for transposable elements (TE). Furthermore, we identified large HBV-induced structural variations (SVs) that disrupted tumor suppressors, NLGN4Y and PROS1. Finally, we examined differentially expressed genes and TEs in single hepatocytes with or without HBV infection, by using single-cell RNA-seq data. Consistent with our HiC sequencing findings, two upregulated genes that promote HBV replication, HNF4A and NR5A2, were located in regions with HBV-enhanced CIs, and five TEs were located in HBV-activated regions. Therefore, HBV may promote liver diseases by affecting the human 3D genome structure. Our work promotes mechanistic understanding of HBV infection and host-virus interactions related to liver diseases that affect billions of people worldwide. Our findings may also have implications for novel immunotherapeutic strategies targeting HBV infection.

In Silico Identification and Functional Characterization of Genetic Variations across DLBCL Cell Lines.

Diffuse large B-cell lymphoma (DLBCL) is the most common form of non-Hodgkin lymphoma and frequently develops through the accumulation of several genetic variations. With the advancement in high-throughput techniques, in addition to mutations and copy number variations, structural variations have gained importance for their role in genome instability leading to tumorigenesis. In this study, in order to understand the genetics of DLBCL pathogenesis, we carried out a whole-genome mutation profile analysis of eleven human cell lines from germinal-center B-cell-like (GCB-7) and activated B-cell-like (ABC-4) subtypes of DLBCL. Analysis of genetic variations including small sequence variants and large structural variations across the cell lines revealed distinct variation profiles indicating the heterogeneous nature of DLBCL and the need for novel patient stratification methods to design potential intervention strategies. Validation and prognostic significance of the variants was assessed using annotations provided for DLBCL samples in cBioPortal for Cancer Genomics. Combining genetic variations revealed new subgroups between the subtypes and associated enriched pathways, viz., PI3K-AKT signaling, cell cycle, TGF-beta signaling, and WNT signaling. Mutation landscape analysis also revealed drug-variant associations and possible effectiveness of known and novel DLBCL treatments. From the whole-genome-based mutation analysis, our findings suggest putative molecular genetics of DLBCL lymphomagenesis and potential genomics-driven precision treatments.

Fine mapping of meiotic crossovers in Brassica oleracea reveals patterns and variations depending on direction and combination of crosses.

Meiotic recombination is crucial for assuring proper segregation of parental chromosomes and generation of novel allelic combinations. As this process is tightly regulated, identifying factors influencing rate, and distribution of meiotic crossovers (COs) is of major importance, notably for plant breeding programs. However, high-resolution recombination maps are sparse in most crops including the Brassica genus and knowledge about intraspecific variation and sex differences is lacking. Here, we report fine-scale resolution recombination landscapes for 10 female and 10 male crosses in Brassica oleracea, by analyzing progenies of five large four-way-cross populations from two reciprocally crossed F1s per population. Parents are highly diverse inbred lines representing major crops, including broccoli, cauliflower, cabbage, kohlrabi, and kale. We produced approximately 4.56T Illumina data from 1248 progenies and identified 15 353 CO across the 10 reciprocal crosses, 51.13% of which being mapped to <10kb. We revealed fairly similar Mb-scale recombination landscapes among all cross combinations and between the sexes, and provided evidence that these landscapes are largely independent of sequence divergence. We evidenced strong influence of gene density and large structural variations on CO formation in B. oleracea. Moreover, we found extensive variations in CO number depending on the direction and combination of the initial parents crossed with, for the first time, a striking interdependency between these factors. These data improve our current knowledge on meiotic recombination and are important for Brassica breeders.

Benchmarking of structural variant detection in the tetraploid potato genome using linked-read sequencing

It has recently been shown that structural variants (SV) can have a higher impact on gene expression variation compared to single nucleotide variants (SNV) in different plant species. Additionally, SV were associated with phenotypic variation in several crops. However, compared to the established SV detection based on short-read sequencing, less approaches were described for linked-read based SV calling. We therefore evaluated the performance of six linked-read SV callers compared to an established short-read SV caller based on simulated linked-reads in tetraploid potato. The objectives of our study were to i) compare the performance of SV callers based on linked-read sequencing to short-read sequencing, ii) examine the influence of SV type, SV length, haplotype incidence (HI), as well as sequencing coverage on the SV calling performance in the tetraploid potato genome, and iii) evaluate the accuracy of detecting insertions by linked-read compared to short-read sequencing. We observed high break point resolutions (BPR) detecting short SV and slightly lower BPR for large SV. Our observations highlighted the importance of short-read signals provided by Manta and LinkedSV to detect short SV. Manta and NAIBR performed well for detecting larger deletions, inversions, and duplications. Detected large SV were weakly influenced by the HI. Furthermore, we illustrated that large insertions can be assembled by Novel-X. Our results suggest the usage of the short-read and linked-read SV callers Manta, NAIBR, LinkedSV, and Novel-X based on at least 90x linked-read sequencing coverage to ensure the detection of a broad range of SV in the tetraploid potato genome.

Ten new high-quality genome assemblies for diverse bioenergy sorghum genotypes.

Sorghum (Sorghum bicolor (L.) Moench) is an agriculturally and economically important staple crop that has immense potential as a bioenergy feedstock due to its relatively high productivity on marginal lands. To capitalize on and further improve sorghum as a potential source of sustainable biofuel, it is essential to understand the genomic mechanisms underlying complex traits related to yield, composition, and environmental adaptations. Expanding on a recently developed mapping population, we generated de novo genome assemblies for 10 parental genotypes from this population and identified a comprehensive set of over 24 thousand large structural variants (SVs) and over 10.5 million single nucleotide polymorphisms (SNPs). We show that SVs and nonsynonymous SNPs are enriched in different gene categories, emphasizing the need for long read sequencing in crop species to identify novel variation. Furthermore, we highlight SVs and SNPs occurring in genes and pathways with known associations to critical bioenergy-related phenotypes and characterize the landscape of genetic differences between sweet and cellulosic genotypes. These resources can be integrated into both ongoing and future mapping and trait discovery for sorghum and its myriad uses including food, feed, bioenergy, and increasingly as a carbon dioxide removal mechanism.

Long-Read Sequencing in Blood Group Genetics

Background: The key advantages of latest third-generation long-read sequencing (TGS) technologies include the ability to resolve long haplotypes and to characterize genomic regions that are challenging to analyze with short-read sequencing. Recent advancements in TGS technologies have significantly improved accuracy, a crucial requirement for the transition from research to diagnostic applications. Summary: In the field of immunohematology, the adoption of TGS is still in its early stages and published applications are scarce. An undeniable utility of TGS in blood group genomics is the ability to resolve ambiguous genotype-phenotype blood group results. In particular, hybrid genes and other large structural variants, as commonly found in the RHD/CE and MNS blood group systems, cause such discrepant results that can hardly be resolved by conventional methods. Long-read sequencing also greatly aids to generate high-standard reference alleles, establish haplotype sequence databases, or could even serve for high-resolution genotyping of all blood groups in parallel. Additionally, TGS holds the potential to close important knowledge gaps in blood group transcriptomics and epigenetics. Key Messages: The aims of this review were to examine the prospects of TGS technologies within the field of immunohematology and to highlight practical applications. Furthermore, we present a comprehensive overview of the existing and emerging wet-laboratory strategies for data generation, as well as a summary on bioinformatic data analysis methods. Finally, we provide an outlook on anticipated advancements in the near future.

Long-read sequencing improves diagnostic rate in neuromuscular disorders.

Massive parallel sequencing methods, such as exome, genome, and targeted DNA sequencing, have aided molecular diagnosis of genetic diseases in the last 20 years. However, short-read sequencing methods still have several limitations, such inaccurate genome assembly, the inability to detect large structural variants, and variants located in hard-to-sequence regions like highly repetitive areas. The recently emerged PacBio single-molecule real-time (SMRT) and Oxford nanopore technology (ONT) long-read sequencing (LRS) methods have been shown to overcome most of these technical issues, leading to an increase in diagnostic rate. LRS methods are contributing to the detection of repeat expansions in novel disease-causing genes (e.g., ABCD3, NOTCH2NLC and RILPL1 causing an Oculopharyngodistal myopathy or PLIN4 causing a Myopathy with rimmed ubiquitin-positive autophagic vacuolation), of structural variants (e.g., in DMD), and of single nucleotide variants in repetitive regions (TTN and NEB). Moreover, these methods have simplified the characterization of the D4Z4 repeats in DUX4, facilitating the diagnosis of Facioscapulohumeral muscular dystrophy (FSHD). We review recent studies that have used either ONT or PacBio SMRT sequencing methods and discuss different types of variants that have been detected using these approaches in individuals with neuromuscular disorders.

Ultra-broadband and highly efficient silicon nitride bi-layer grating couplers

The silicon nitride (Si3N4) waveguide platform becomes prominent in silicon photonics due to its ultralow propagation loss, negligible two-photon absorption, tolerance to phase error, and so on. Particularly, Si3N4 photonic circuits provide nonlinear opportunities as thick waveguides enable dispersion engineering, which is fundamental for frequency comb and supercontinuum generation. However, grating couplers based on thick Si3N4 waveguides, as the building block for any device, are prone to higher-order Bloch mode excitation, restricting the coupling efficiency dramatically, thus precluding practical applications that large bandwidth and are power restricted. We propose and demonstrate an 800 nm-thick Si3N4bi-layer fully etched grating coupler which is ultra-broadband and highly efficient. By applying the apodization technique, the bi-layer grating shows a conversion efficiency of −1.44 dB and a 1 dB bandwidth of 135 nm. Further integrated with a bottom reflector, a conversion efficiency of −1.01 dB with a 1-dB bandwidth of 117 nm is achieved. The proposed structures are highly fabrication tolerant and remain great performance regardless large structural parameter variations. It paves the way for a large-volume high-yield production towards fully-integrated frequency comb chip, optical beam forming network, Lidar, etc.

Using coding and non-coding rare variants to target candidate genes in patients with severe tinnitus

Tinnitus is the phantom percept of an internal non-verbal set of noises and tones. It is reported by 15% of the population and it is usually associated with hearing and/or brain disorders. The role of structural variants (SVs) in coding and non-coding regions has not been investigated in patients with severe tinnitus. In this study, we performed whole-genome sequencing in 97 unrelated Swedish individuals with chronic tinnitus (TIGER cohort). Rare single nucleotide variants (SNV), large structural variants (LSV), and copy number variations (CNV) were retrieved to perform a gene enrichment analysis in TIGER and in a subgroup of patients with severe tinnitus (SEVTIN, n = 34), according to the tinnitus handicap inventory (THI) scores. An independent exome sequencing dataset of 147 Swedish tinnitus patients was used as a replication cohort (JAGUAR cohort) and population-specific datasets from Sweden (SweGen) and Non-Finish Europeans (NFE) from gnomAD were used as control groups. SEVTIN patients showed a higher prevalence of hyperacusis, hearing loss, and anxiety when they were compared to individuals in the TIGER cohort. We found an enrichment of rare missense variants in 6 and 8 high-constraint genes in SEVTIN and TIGER cohorts, respectively. Of note, an enrichment of missense variants was found in the CACNA1E gene in both SEVTIN and TIGER. We replicated the burden of missense variants in 9 high-constrained genes in the JAGUAR cohort, including the gene NAV2, when data were compared with NFE. Moreover, LSVs in constrained regions overlapping CACNA1E, NAV2, and TMEM132D genes were observed in TIGER and SEVTIN.

ONT-Based Alternative Assemblies Impact on the Annotations of Unique versus Repetitive Features in the Genome of a Romanian Strain of Drosophila melanogaster

To date, different strategies of whole-genome sequencing (WGS) have been developed in order to understand the genome structure and functions. However, the analysis of genomic sequences obtained from natural populations is challenging and the biological interpretation of sequencing data remains the main issue. The MinION device developed by Oxford Nanopore Technologies (ONT) is able to generate long reads with minimal costs and time requirements. These valuable assets qualify it as a suitable method for performing WGS, especially in small laboratories. The long reads resulted using this sequencing approach can cover large structural variants and repetitive sequences commonly present in the genomes of eukaryotes. Using MinION, we performed two WGS assessments of a Romanian local strain of Drosophila melanogaster, referred to as Horezu_LaPeri (Horezu). In total, 1,317,857 reads with a size of 8.9 gigabytes (Gb) were generated. Canu and Flye de novo assembly tools were employed to obtain four distinct assemblies with both unfiltered and filtered reads, achieving maximum reference genome coverages of 94.8% (Canu) and 91.4% (Flye). In order to test the quality of these assemblies, we performed a two-step evaluation. Firstly, we considered the BUSCO scores and inquired for a supplemental set of genes using BLAST. Subsequently, we appraised the total content of natural transposons (NTs) relative to the reference genome (ISO1 strain) and mapped the mdg1 retroelement as a resolution assayer. Our results reveal that filtered data provide only slightly enhanced results when considering genes identification, but the use of unfiltered data had a consistent positive impact on the global evaluation of the NTs content. Our comparative studies also revealed differences between Flye and Canu assemblies regarding the annotation of unique versus repetitive genomic features. In our hands, Flye proved to be moderately better for gene identification, while Canu clearly outperformed Flye for NTs analysis. Data concerning the NTs content were compared to those obtained with ONT for the D. melanogaster ISO1 strain, revealing that our strategy conducted to better results. Additionally, the parameters of our ONT reads and assemblies are similar to those reported for ONT experiments performed on various model organisms, revealing that our assembly data are appropriate for a proficient annotation of the Horezu genome.

Quantifying aboveground biomass dynamics from charcoal degradation in Mozambique using GEDI Lidar and Landsat

Understanding changes to aboveground biomass (AGB) in forests undergoing degradation is crucial for accurately and completely quantifying carbon emissions from forest loss and for environmental monitoring in the context of climate change. Monitoring forest degradation as compared to deforestation presents technical challenges because degradation involves widespread, low-intensity AGB removal under varying temporal dynamics. Charcoal production is a key driver for forest degradation in Africa and is projected to increase in the future years. In Sub-Saharan Africa (SSA), where charcoal production drives widespread ABG removal, the utility of optical remote sensing for degradation quantification is challenged by the large inter-seasonal variation and high complexities in ecosystem structure. Limited field measurements on tree structure and aboveground biomass density (AGBD) in many parts of the SSA also impose constraints. In this study, we present a novel data fusion approach combining 3D forest structure from NASA's GEDI Lidar with optical time-series data from Landsat to quantify biomass losses associated with charcoal-related forest degradation over a 10-year time period. We used machine learning models with Landsat spectral indices from the time period of limited hydric stress (LHS) as predictor variables. By applying the best performing Random Forest (RF) model to LandTrendr-stabilized annual LHS Landsat composites, we produced annual forest AGBD maps from 2007 to 2019 over the Mabalane district in southern Mozambique where the dry forest ecosystem was under active charcoal-related degradation since 2008. The RF model achieved an RMSE value of 7.05 Mg/ha (RMSE% = 42%) and R2 value of 0.64 using a 10-fold cross-validation dataset. We quantified a total AGB loss of 2.12 ± 0.06 Megatons (Mt) over the 10-year period, which is only 6.35 ± 2.56% less than the total loss estimated using field-based data as previously published for the same area and time. In addition to quantifying biomass loss, we constructed annual AGBD maps that enabled the characterization of disturbance and recovery. Our framework demonstrates that fusing GEDI and Landsat data through predictive modeling can be used to quantify past forest AGBD dynamics in low biomass forests. This approach provides a satellite-based method to support REDD+ monitoring and evaluation activities in areas where field data is limited and has the potential to be extended to investigate a variety of different disturbance events.

F8 variants in Women and Girls Evaluated for Hemophilia a

Background: A paradigm shift in our understanding of women and girls with hemophilia A is evolving. van Galen et al published an ISTH SSC-recommended nomenclature based on bleeding phenotype and baseline FVIII activity levels to reflect current clinical wisdom- women/girls with mild, moderate, or severe hemophilia (FVIII activity >0.05 and <0.40 IU/ml, 0.01-0.05 IU/ml, and <0.01 IU/ml, respectively) and symptomatic and asymptomatic carriers (FVIII activity ≥0.40 IU/ml with and without a bleeding phenotype, respectively). Therefore, it is imperative to identify the F8 variants these women and girls harbor. Methods: Genetic testing for F8 variants was obtained as a component of clinical practice. Each patient or legal guardian provided written permission for genetic testing. Genomic DNA was isolated via standard technique. Inverse-shifting polymerase chain reaction was used to screen for intron 1 and 22 inversions if there was a history of severe hemophilia A or no family history. If negative, Sanger sequencing of the coding region, intron/exon boundaries, and areas 5' upstream and downstream of the coding region was performed. If Sanger sequencing was negative, multiplex ligation-dependent probe amplification assay was performed to detect large structural variants. If a candidate causative variant was found confirmation on a second aliquot of genomic DNA was performed. Results: 235 females underwent F8 variant testing. All but 17 provided a family history of hemophilia A. For 168 individuals a familial variant and for 65 baseline FVIII activity (3-180%) was provided. A candidate causative variant (CCV) was detected in 146 individuals. 89 females without a CCV detected had a median FVIII activity of 60% (30-180%; n=16) or were normal (familial variant was not found) with a median baseline FVIII activity of 94% (20-159%; n=6), 76 had predicted non-null variants with a median baseline FVIII activity of 35% (5.3- 171%; n=20) and 69 had predicted null variants with a median baseline FVIII activity of 38.4% (15-157%; n=19). One woman harboring a splice variant that could not be classified as non-null or null had a FVIII activity of 3%. In the individuals with FVIII < 40% and no family history of hemophilia A, a CCV was found in 3 of 8, suggesting an alternative diagnosis for the low FVIII in most. One individual was identified with a deletion only after it was subsequently identified in her son, and she was retested with variant-specific primers. Of the 76 females with predicted non-null variants 63 harbored missense variants, 10 synonymous variants, 2 large duplications, and 1 a variant in the 5' untranslated region of F8. Of the 69 females with predicted null variants 35 harbored intron 22 inversions, 16 frameshift deletions or insertions, 13 nonsense variants, and 5 large deletions (Table 1). Conclusion: As our clinical knowledge of women and girls affected by hemophilia expands so must our knowledge of the genetic variants that they harbor. Baseline FVIII activity levels are not predictive of variant type. Knowledge of the F8 variant in the patient and her family is important in reproductive decision making and obstetrical management to reduce the risk of consequential delivery methods, as well as understanding bleeding symptoms, inhibitor risks, and potentially treatment choices for her and her family. Knowledge of the variant in affected males improves variant detection or exclusion in females. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

A Simple Cost-Effective Method for Whole-Genome Sequencing, Haplotyping, and Assembly.

In this chapter, we describe single-tube long fragment read (stLFR), a simple preparation method for whole-genome sequencing and physical haplotyping based on the DNA co-barcoding strategy. Similar to LFR, stLFR applies the concept of adding the same barcode to subfragments derived from the same long DNA molecule. However, instead of a 384-well plate, stLFR uses the surface of micron-sized magnetic beads to create millions of virtual compartments in a single reaction tube. This is enabled by a split and pool barcoded bead preparation process capable of generating ~500,000 copies of the same unique barcode, from a library of ~3.6 billion unique barcodes, on each bead. The instruments and devices used in the stLFR process are easily accessible in nearly all standard molecular biology laboratories, and the cost of reagents can be as low as 30 dollars per sample. stLFR libraries can be sequenced by standard second-generation sequencing instruments (e.g., MGI or Illumina devices), and the barcode sharing information enables detection and phasing of all variations, including large structural variations. In addition, stLFR data can be used to scaffold contigs and de novo assemble genomes.

23. Paired exome analysis in Mosaic Disease yields expanded Genotype-Phenotype Associations

<h3>Introduction</h3> Somatic mosaicism is increasingly detectable through the use of highly sensitive molecular methodologies. Knowledge of the genetic underpinnings of mosaic disease can aid in diagnosis, inform management and surveillance, and guide therapeutic decision making. Herein, we examine the impact of comprehensive genomic analysis of paired tissue sources in individuals with clinical features of mosaic disease. <h3>Methods</h3> Comprehensive genomic profiling was performed across a cohort of 43 individuals with vascular, lymphatic, or capillary malformations, somatic overgrowth, hamartomatous lesions, or vascular tumors. High-depth paired exome sequencing of a comparator sample and disease-involved tissue was performed, along with whole transcriptome analysis of disease-involved tissue. <h3>Results</h3> The diagnostic yield within this cohort was 67% (29/43). Pathogenic variation included germline findings in 5 individuals, somatic findings in 22 individuals, and both germline and somatic variant contribution in 2 individuals. Variants occurred primarily within the PI3K-AKT and RAS-MAPK pathways. Oncogenic hotspot SNVs comprised 56% (19/34) of detected variants. Small indel events comprised 29% (10/34) of detected variation. Larger structural variation was detected in the form of an internal tandem duplication, as well as chromosome-arm level loss of heterozygosity. Expanded genotype-phenotype associations were gleaned from 5 individuals. Use of paired exome analysis extended the breadth of medically meaningful findings outside of somatic hotspots by 44%. <h3>Conclusion</h3> Paired exome sequencing is a sensitive method to detect germline and somatic variation within known and emerging gene targets enabling expanded genotype-phenotype associations to be learned.

26. Identification of novel genomic structural variations in Angiosarcoma by Optical Genome Mapping

Angiosarcomas are malignant vascular tumors with a number of known molecular aberrations identified by standard technologies, such as FISH and next generation sequencing. However, potentially clinically significant large genomic aberrations, such as gene fusion, large amplification and deletions, may not be detectable by these technologies. To gain further insights into the genomic landscape of angiosarcoma, we performed optical genome mapping (OGM) of 3 primary human angiosarcoma cell lines. OGM analysis of these cells revealed multiple unique structural aberrations, including large insertions/deletions, inversions, duplications, inter-chromosomal and intra-chromosomal translocations. Further analysis showed a 354-Kb deletion in Plexin D1 gene locus that regulates the migration of endothelial cells and is required for normal development of the heart and vasculature; reciprocal t(4;9) translocation in UGT8 (UDP Glycosyltransferase 8) gene locus that is involved in biosynthesis of galactocerebrosidase; reciprocal t(6;22) translocation involving HIRA (Histone Cell Cycle Regulator) and EYS (Eyes Shut Homolog) gene loci; and 14 Mb inversion interrupting RYR2 (Ryanodine Receptor 2) and TAF1A (TATA-Box Binding Protein Associated Factor) gene loci. These findings demonstrate the utility of optical genome mapping as a new tool to uncover large genomic structural variations to better understand the molecular pathogenesis of malignant vascular tumors. Future studies are aimed to determine the biological significance of these structural variations in angiosarcoma.

Mutation and selection processes regulating short tandem repeats give rise to genetic and phenotypic diversity across species.

Short tandem repeats (STRs) are units of 1-6 bp that repeat in a tandem fashion in DNA. Along with single nucleotide polymorphisms and large structural variations, they are among the major genomic variants underlying genetic, and likely phenotypic, divergence. STRs experience mutation rates that are orders of magnitude higher than other well-studied genotypic variants. Frequent copy number changes result in a wide range of alleles, and provide unique opportunities for modulating complex phenotypes through variation in repeat length. While classical studies have identified key roles of individual STR loci, the advent of improved sequencing technology, high-quality genome assemblies for diverse species, and bioinformatics methods for genome-wide STR analysis now enable more systematic study of STR variation across wide evolutionary ranges. In this review, we explore mutation and selection processes that affect STR copy number evolution, and how these processes give rise to varying STR patterns both within and across species. Finally, we review recent examples of functional and adaptive changes linked to STRs.

Time-ordering japonica/geng genomes analysis indicates the importance of large structural variants in rice breeding.

Temperate japonica/geng (GJ) rice yield has significantly improved due to intensive breeding efforts, dramatically enhancing global food security. However, little is known about the underlying genomic structural variations (SVs) responsible for this improvement. We compared 58 long-read assemblies comprising cultivated and wild rice species in the present study, revealing 156 319 SVs. The phylogenomic analysis based on the SV dataset detected the putatively selected region of GJ sub-populations. A significant portion of the detected SVs overlapped with genic regions were found to influence the expression of involved genes inside GJ assemblies. Integrating the SVs and causal genetic variants underlying agronomic traits into the analysis enables the precise identification of breeding signatures resulting from complex breeding histories aimed at stress tolerance, yield potential and quality improvement. Further, the results demonstrated genomic and genetic evidence that the SV in the promoter of LTG1 is accounting for chilling sensitivity, and the increased copy numbers of GNP1 were associated with positive effects on grain number. In summary, the current study provides genomic resources for retracing the properties of SVs-shaped agronomic traits during previous breeding procedures, which will assist future genetic, genomic and breeding research on rice.

Graph-based pan-genomes: increased opportunities in plant genomics.

Due to the development of sequencing technology and the great reduction in sequencing costs, an increasing number of plant genomes have been assembled, and numerous genomes have revealed large amounts of variations. However, a single reference genome does not allow the exploration of species diversity, and therefore the concept of pan-genome was developed. A pan-genome is a collection of all sequences available for a species, including a large number of consensus sequences, large structural variations, and small variations including single nucleotide polymorphisms and insertions/deletions. A simple linear pan-genome does not allow these structural variations to be intuitively characterized, so graph-based pan-genomes have been developed. These pan-genomes store sequence and structural variation information in the form of nodes and paths to store and display species variation information in a more intuitive manner. The key role of graph-based pan-genomes is to expand the coordinate system of the linear reference genome to accommodate more regions of genetic diversity. Here, we review the origin and development of graph-based pan-genomes, explore their application in plant research, and further highlight the application of graph-based pan-genomes for future plant breeding.