Hi-C-Based Structural Variant Detection Market Outlook

According to our latest research, the global Hi-C-based structural variant detection market size reached USD 340 million in 2024, reflecting the growing adoption of advanced genomic technologies across healthcare and life sciences. The market is expected to expand at a robust CAGR of 14.2% from 2025 to 2033, reaching a forecasted value of USD 1.03 billion by 2033. This remarkable growth is primarily driven by the increasing demand for high-resolution genomic mapping in cancer research, genetic disease studies, and drug discovery, as well as the continuous evolution of next-generation sequencing (NGS) technologies. As per our latest research, the integration of Hi-C-based methods into mainstream genomic workflows is reshaping the landscape of structural variant detection, offering unparalleled accuracy and efficiency.

One of the principal growth factors propelling the Hi-C-based structural variant detection market is the escalating focus on personalized medicine and precision oncology. Hi-C technology enables researchers to map chromatin interactions and detect structural variants such as translocations, inversions, and copy number changes with unprecedented clarity. This capability is crucial for understanding the genetic basis of complex diseases, particularly cancer, where structural rearrangements play a pivotal role in disease progression and therapeutic resistance. Pharmaceutical and biotechnology companies are increasingly leveraging Hi-C-based approaches to identify novel drug targets and develop tailored therapies, thereby fueling market expansion. Furthermore, as the cost of sequencing continues to decline, the barrier to entry for adopting Hi-C-based techniques is also lowering, making these methods accessible to a broader range of end-users.

Another significant driver is the surge in government and private funding for genomics research worldwide. Countries in North America, Europe, and Asia Pacific are investing heavily in genomics infrastructure, recognizing the transformative potential of structural variant detection in healthcare and biomedical research. Large-scale initiatives such as the Human Genome Project and the Cancer Genome Atlas have paved the way for advanced structural variant analysis, with Hi-C-based methodologies now at the forefront of these efforts. This influx of funding has led to the proliferation of academic and research institutes equipped with state-of-the-art sequencing platforms, further accelerating the adoption of Hi-C-based technologies. Simultaneously, collaborations between academia, industry, and healthcare providers are fostering innovation and driving the development of novel applications for structural variant detection in both clinical and translational settings.

Technological advancements in software and analytical tools have also played a critical role in the market’s growth. The complexity of Hi-C data requires sophisticated algorithms and bioinformatics platforms capable of efficiently processing and interpreting large datasets. Recent innovations in machine learning and artificial intelligence have enhanced the accuracy and speed of structural variant detection, enabling real-time analysis and integration with other omics data. This has broadened the utility of Hi-C-based methods beyond basic research, extending their application to clinical diagnostics and therapeutic monitoring. The ongoing convergence of Hi-C technology with cloud computing and big data analytics is expected to further streamline workflows, reduce turnaround times, and support the scalability of these solutions across diverse end-user segments.

Regionally, North America currently dominates the Hi-C-based structural variant detection market, accounting for the largest share due to its advanced healthcare infrastructure, high research and development spending, and the presence of leading genomic technology providers. However, Asia Pacific is poised to exhibit the fastest growth over the forecast period, with a projected CAGR exceeding 16.5%, driven by expanding genomics research capacity, rising healthcare investments, and increasing awareness of precision medicine. Europe also remains a significant contributor, supported by robust academic research networks and favorable regulatory frameworks. Meanwhile, Latin America and the Middle East & Africa are gradually emerging as promising markets, bolstered by ongoing healthcare modernization efforts and growing participation in global genomics ini

AbstractRapid adaptation during invasion has historically been considered limited and unpredictable. We leverage whole-genome sequencing of >2600 plants across six continents to investigate the relative roles of colonization history and adaptation during the worldwide invasion of Trifolium repens. Introduced populations contain high levels of genetic variation with independent colonization histories evident on different continents. Five large structural variants on three chromosomes exist as standing genetic variation within the native range, and exhibit strong signatures of parallel climate-associated adaptation across continents. Common gardens in the native and introduced ranges demonstrate that three structural variants exhibit patterns of selection consistent with local adaptation across each range. Our results provide strong evidence that rapid and parallel adaptation during invasion is caused by large-effect structural variants introduced throughout the world. MethodsThis dataset contains fitness data for 472 indviduals from four field common gardens located in the native and introduced ranges of Trifolium repens (white clover), as described in the main text and methods of Battlay et al.. Briefly, seeds from 46 populations were collected along a latitudinal transect in North American by Lucas Albano and 47 populations were collected along a latitudinal transect in Western Europe by Simon Innes. Seeds from each of these populations were grown in a greenhouse refresher generation and crossed to other plants from the same population. The resulting lines were grown in four common gardens (Uppsula, Sweden; Montpellier, France; Mississauga, Canada; Lafayette, USA). The methods of Battlay et al. describes the fitness metrics measured for each individual. Tissue was taken for DNA extractions for each individual. Methods describing DNA extractions, library construction, and sequencing are described in the methods of Battlay et al..

The detection of founder pathogenic variants, those observed in high frequency only in a group of individuals with increased inter-relatedness, can help improve delivery of health care for that community. We identified 16 groups with shared ancestry, based on genomic segments that are shared through identity by descent (IBD), in New York City using the genomic data of 25,366 residents from the All Of Us Research Program and the Mount Sinai BioMe biobank. From these groups we defined 7 as founder populations, mostly communities currently under-represented in medical genomics research, such as Puerto Rican and Garifuna. The enrichment analysis of ClinVar pathogenic or likely pathogenic (P/LP) variants in each group identified 201 of these damaging variants across the seven founder populations. We confirmed disease-causing variants previously reported to occur at increased frequencies in Ashkenazi Jewish and Puerto Rican genetic ancestry groups, but most of the damaging variants identified have not been previously associated with any such founder populations, and most of these founder populations have not been described to have increased prevalence of the associated rare disease. Twenty-two of 47 variants meeting Tier 2 prenatal screening criteria (1/100 carrier frequency within these founder groups) have never previously been reported. We show how population structure studies can provide insights into rare diseases disproportionately affecting under-represented founder populations, delivering a health care benefit but also a potential source of stigmatization of these communities, who should be part of the decision-making about implementation into health care delivery.

Ancestry background of AoU IBD clusters. (A) PCA plot for all AoU NYC participants and reference panels. (B) PCA plots highlighting individuals belonging to the 14 IBD clusters detected in AoU NYC participants. (C) SCOPE analysis for AoU NYC participants labelled with the 14 IBD clusters. Each color represents global ancestry proportion of the five superpopulations (African, European, American, East Asian and South Asian) inferred using supervised mode in SCOPE.

All candidate founder P/LP variants in the seven founder populations in NYC.

Copy number variants (CNVs) are a major component of genotypic and phenotypic variation in genomes. To date, our knowledge of genotypic variation and evolution has largely been acquired by means of single nucleotide polymorphism (SNPs) analyses. Until recently, the adaptive role of structural variants (SVs) and particularly that of CNVs has been overlooked in wild populations, partly due to their challenging identification. Here, we document the usefulness of Rapture, a derived reduced‐representation shotgun sequencing approach, to detect and investigate copy number variants (CNVs) alongside SNPs in American lobster (Homarus americanus) populations. We conducted a comparative study to examine the potential role of SNPs and CNVs in local adaptation by sequencing 1,141 lobsters from 21 sampling sites within the southern Gulf of St. Lawrence, which experiences the highest yearly thermal variance of the Canadian marine coastal waters. Our results demonstrated that CNVs account for higher genetic differentiation than SNP markers. Contrary to SNPs, for which no significant genetic–environment association was found, 48 CNV candidates were significantly associated with the annual variance of sea surface temperature, leading to the genetic clustering of sampling locations despite their geographic separation. Altogether, we provide a strong empirical case that CNVs putatively contribute to local adaptation in marine species and unveil stronger spatial signal of population structure than SNPs. Our study provides the means to study CNVs in nonmodel species and highlights the importance of considering structural variants alongside SNPs to enhance our understanding of ecological and evolutionary processes shaping adaptive population structure.

Methods A total of 1,141 lobster samples were collected from 21 sites between May and July in 2016 in the southern area of the Gulf of St-Lawrence. DNA was extracted from half of the walking leg of each lobster using salt extraction (Aljanabi & Martinez, 1997) with an additional RNAse treatment following the manufacturer’s instructions. DNA quality was assessed using 1% agarose gel electrophoresis. Genomic DNA concentrations were normalized to 20ng/µl based on a fluorescence quantification method (AccuClear™ Ultra High Sensitivity dsDNA Quantitation Solution). Individual reduced-representation shotgun sequencing (i.e. RRS) libraries were prepared following the Rapture approach (Ali et al., 2016). Briefly, the Rapture approach is a form of RRS sequencing which combines double-digested libraries (i.e. GBS, ddRADseq) with a sequence capture step using DNA probes designed from known genomic sequences. Here, we used the same 9,818 targeted loci previously used for the American lobster and all the details about the wet protocol are described in Dorant et al. (2019). All Rapture libraries were sequenced on the Ion Torrent p1v3 chip at the Plateforme d’analyses génomiques of the Institute of Integrative and Systems Biology (IBIS, Université Laval, Québec, Canada http://www.ibis.ulaval.ca/en/home/). Two rounds of sequencing (i.e. two separated chips) were conducted for all Rapture libraries.

Ticks and tick-borne pathogens represent the greatest vector-borne disease threat in the US. Blacklegged ticks are responsible for most human cases, yet the disease burden is unevenly distributed across the northern and southern US. Understanding the genetic characteristics influencing phenotypic differences in tick vectors is critical to elucidating disparities in tick-borne pathogen transmission dynamics. Applying evolutionary analyses to molecular variation in natural tick populations across ecological gradients will help identify signatures of local adaptation, which will improve control and mitigation strategies. In this study, we performed whole genome nanopore sequencing of individual (n=1) blacklegged ticks across their geographical range (Minnesota, Pennsylvania, and Texas) to evaluate genetic divergence among populations. Our integrated analyses identified genetic variants associated with numerous biological processes and molecular functions that segregated across populations. Notably, northern populations displayed genetic variants in genes linked to xenobiotic detoxification, transmembrane transport, and sulfation that may underpin key phenotypes influencing tick dispersal, host associations, and vectorial capacity. Nanopore sequencing further allowed the recovery of complete mitochondrial and commensal endosymbiont genomes. Our study provides further evidence of genetic divergence in epidemiologically relevant gene families among blacklegged tick clades. This report emphasizes the need to elucidate the genetic basis driving divergence among conspecific blacklegged tick clades in the US. Methods Sample Collection Questing ticks were collected by dragging a 1-m2 cloth along natural vegetation, stopping every ~10 m to collect attached ticks, from four locations throughout the United States: Minnesota (Anoka County, MN, USA), Pennsylvania (Allegheny County, PA, USA), Texas (Polk County, TX, USA), and California (Riverside County, CA, USA). Collected ticks were preserved in 70% EtOH or RNAlater and sent to the University of Minnesota for processing. Ticks were morphologically identified using keys from Keirans and Clifford (1978), and Cooley and Kohls (1945). Ticks were rinsed with molecular grade water and transferred to Zymo DNA/RNA shield until DNA extraction. DNA Extraction and Sequencing DNA was extracted using a Qiagen MagAttract kit (Cat. 67563; Aarhus, Denmark) according to the manufacturer's instructions, with a final elution step extended to 1 h at 37°C. DNA was sheared by 20 passes through a standard 30-gauge insulin syringe. Library prep was performed with an SQK-LSK-114 native ligation sequencing kit (ONT, Oxford, UK). Sequencing was performed on a P2 Solo instrument and basecalled using Nvidia 4090 GPUs. Sequencing was performed over 3 days with nuclease flush and library reload every 24 h. Individual adult females were used for sequencing of I. scapularis and I. pacificus (n = 1) from each location. Raw data from all runs were basecalled together using Dorado v0.8.1 with the “super accuracy” model dna_r10.4.1_e8.2_400bps_supv4.2.0. Read quality was assessed using Nanoq v0.10.0 (Steinig and Coin 2022). Variant Analysis

1. Variant Calling Super-high accuracy basecalled reads from the three female adult I. scapularis (MN, PA, TX) specimens were individually mapped to the I. scapularis reference genome, PalLabHiFi (GCF_016920785.2) (De et al. 2023), using Minimap2 v2.28 (Li 2018). The resulting mapped bam file was sorted and indexed using Samtools v1.20 (Li et al. 2009) and served as input to call variants with Clair3 v1.0.10 (Zheng et al. 2022). Variants with quality scores of < 10 and allele frequencies of < 20% were masked using BCFtools v1.20 (Danecek et al. 2021). Filtering variants with a minor allele frequency of 20% and a quality score of 10 reflects a balance between excluding likely sequence errors and retaining biologically meaningful variation. Filtered variant call files generated alternative whole genome assemblies for each tick by replacing variant sites in the reference assembly using BCFtools. Variants were not called for the I. pacificus individual, as the reference assembly was scaffolded using the I. scapularis reference genome, limiting our confidence in the variants called for this sister species.

2. Variant Statistics Summary statistics were generated for each variant call file using VariantQC v1.05 (Yan et al. 2019) and Nanoq (Steinig and Coin 2022). Genome-wide heterozygosity and SNP density were calculated in 100 kb windows as a proxy for genome-wide diversity using VCFtools v0.1.16 (Danecek et al. 2011). Runs of homozygosity (ROH) were analyzed with Plink v1.90 (Purcell et al. 2007) specifying a sliding window of 100 kb, a threshold of 0.05 for overlapping homozygous windows, a minimum of 100 homozygous SNPs per window, a minimum SNP density of 50 kb per SNP, a minimum of 25 homozygous SNPs per ROH, a maximum of one heterozygous position per window, a maximum of 1000 kb gap between SNPs, and a maximum of 100 heterozygous sites in each final ROH (Dehasque et al. 2024). Genome-wide heterozygosity, SNP density, and runs of homozygosity were visualized using circlize v0.4.15 (Gu et al. 2014) in R v4.2 (R Core Team 2022) (Figure 1).

3. Variant Annotation Filtered variant files were annotated using snpEff v5.2 (Cingolani, Platts, et al. 2012). SnpEff requires an annotation database to perform variant effect prediction. We built a custom database by specifying the reference genome (GCF_016920785.2), including the FASTA and GTF annotation file from NCBI. SnpEff annotates variants and predicts the coding effects of genetic variants by creating a data structure that algorithmically identifies intersecting genomic regions to calculate variant effects (Cingolani, Platts, et al. 2012). Annotated variant call files were sifted using snpSift (Cingolani, Patel, et al. 2012) to partition variant annotations, including the impact and effect of each variant, by the 14 longest scaffolds in the PalLabHiFi assembly. Annotation summary statistics for the whole genome and scaffolds were generated by snpSift.

4. Gene Ontology Gene ontology (GO) analysis was performed using the Database for Annotation, Visualization, and Integrated Discovery v2023q4 (DAVID) (Sherman et al. 2022; Huang et al. 2009). GO discovery was performed on two curated datasets. The first dataset was established to identify regions putatively identical by descent among the three female adult I. scapularis individuals (MN, PA, TX). To do so, runs of homozygosity shared across all three individuals were identified using dplyr v1.1.4 (Wickham et al. 2023) in R. Genes falling within these shared runs of homozygosity were intersected with gene annotation files using BedTools v2.31.1 (Quinlan and Hall 2010) to produce a dataset that contained locations of genes, with their respective gene IDs, shared across the individuals. The second dataset included all genes annotated as having a high impact through snpEff. The gene IDs from the two datasets were then independently used as input into DAVID and extracted as tables. GO terms shared among all individuals, some individuals, or unique to an individual were investigated. GO terms were visualized using ggVennDiagram v1.5.2 (Gao et al. 2021) and ggplot2 v3.5.1 (Wickham 2016). Mitogenome Assembly, Annotation, and Phylogenetics The mitogenomes of the three I. scapularis (MN, PA, TX) and I. pacificus (CA) individuals were extracted from their respective assemblies and characterized with MitoHiFi v3.2.2 (Uliano-Silva et al. 2023). MitoHiFi identifies mitochondrial contigs from whole genome sequencing datasets, assembles the genome, and annotates it for protein and RNA genes through external tools (e.g., minimap2, Hifiasm, MitoFinder, etc.) (Uliano-Silva et al. 2023). MitoHiFi was explicitly designed to handle long-read sequencing data. To ensure proper assembly and annotation, the consensus FASTA generated from MitoHiFi was polished using Medaka v2.0.1 (https://github.com/nanoporetech/medaka) and annotated using Mitos2 v2.1.9 (Bernt et al. 2013) with specifications for metazoan RefSeq and invertebrate genetic code. Manual annotation correction was performed to correct frameshift mutations resulting in premature stop codons within highly conserved protein-coding genes to ensure consistency with conserved mitochondrial gene structures. All frameshift mutations were found in homopolymer regions (i.e., stretches of consecutive adenine and thymine), a known limitation of nanopore sequencing. Manual correction was also performed to confirm tRNA annotations or added if any annotations were absent. Any tRNA annotation additions were performed using Geneious Prime software v2024.0.7 (https://www.geneious.com) by aligning the gene in question from reference mitogenomes with our polished mitogenome assembly using minimap2. Polished and assembled mitogenomes were visualized using OGDRAW v1.3.1 (Greiner et al. 2019). After the mitogenomes were annotated, each mitogenome, cytochrome c oxidase subunit I (COI), and 16S gene sequences were used in phylogenetic analyses to determine their relatedness to congeneric Ixodes spp. To build the phylogenies, COI, 16S, and mitogenome sequences were downloaded from GenBank for each available North American Ixodes spp. The genus Ixodes (Acari: Ixodidae) is monophyletic and shares a most recent common ancestor with Metastriata, which resides within the same family, Ixodidae. As such, the metastriate species Amblyomma americanum was chosen as the outgroup and included in each analysis to root the phylogeny. Sequences were aligned using CLUSTALO v.1.2.3 (Thompson et al. 1994), and alignments were used in maximum likelihood analyses in RAxML v8.0.0 (Stamatakis 2014) with the GTRGAMMAI model of evolution and 1000 bootstrap replicates. The final tree was visualized in FigTree v1.4.4

SSA Multi-ancestry Structural Variation Catalog (Germline, Synthetic)

  Dataset summary

This dataset provides a germline structural variation (SV) catalog for a multi-ancestry cohort of 20,000 synthetic individuals with a strong focus on sub-Saharan African (SSA) ancestry. It complements the genome-wide SNP array synthetic dataset by adding copy number variants (CNVs) and small indels with explicit population-specific structural variants. The cohort includes:

Four SSA… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/ssa-structural-variation-catalog.

This collection contains supplementary data for the manuscript "Genotypic characterization of the U.S. Peanut Core Collection", which describes genotyping results for the USDA peanut core collection. Each accession was genotyped with the Arachis_Axiom2 SNP array, yielding 14,430 high-quality, informative SNPs across the collection. Additionally, a subset of the core collection was replicated genotyped in replicate, using between two and five seeds per accession to assess heterogeneity within an accession. Supplementary files include: descriptive information about the genotyped accessions, SNP genotype calls in several formats, a phylogenetic tree calculated from the genotype data, Structure analysis, PCA analysis, and comparisons with the diploid progenitors. This research was co-funded by the National Institute of Food and Agriculture and the National Peanut Board. Resources in this dataset:Resource Title: Structure membership breakdown. File Name: SF10_K5_membership.pdfResource Description: The proportion of accessions assigned to clusters 1-5 in a Structure analysis (manuscript Figure 3), for K=5 clusters. Resource Title: Structure membership assignments for accessions. File Name: SF11_K5_cluster_assignment.xlsxResource Description: The proportional assignments of each cluster to all accessions (relative to the Structure diagram shown in manuscript Figure 3). Resource Title: Principal components analysis. File Name: SF12_pca_34.pdfResource Description: Principal Component Analysis of 1120 samples based on 2063 unlinked SNP markers. The X-axis represents PC 3 and the Y-axis represents PC 4. Samples are colored and grouped according to: A. clade membership as defined in the phylogenetic and network analyses, B. botanical varieties, C. market type, D. growth Habit, E. pod shape, and F. collection type Resource Title: Pod images for PI 497426. File Name: SF14_PI497426_pods.jpgResource Description: Pods from accession PI 497426 (clade 4), illustrating the distinctive reticulation pattern seen in some accessions in this clade. Resource Title: Data dictionary. File Name: data_dictionary_KNWV.txtResource Description: Description of all files in this Dataset. Changes were made to this file on 4/15/202, to update some file names to indicate new versions.Resource Title: Main descriptive information about genotyped accessions. File Name: SF01_peanut_core_v14.xlsxResource Description: The main descriptive information about the genotyped accessions, including: information about replicate similarity; phylogenetic clades, geographic origin, and phenotype; and summaries of phenotypic and country information relative to clade assignments. Changes were made to this file on 4/15/2020: Added INDEX worksheet and corrected three peanut variety identifiers: ROL11 --> TamrunOL-11; NCL06 --> TamnutOL-06; NM309N2 --> NM309-2Resource Title: SNPs as called by the Axiom suite . File Name: SF02_SNPs_whole_Axiom_Arachis2_txt.gzResource Description: The original genotype calls for the Axiom array (for poly-high resolution SNPs). Changes were made to this file on 4/15/2020: Corrected three peanut variety identifiers: ROL11 --> TamrunOL-11; NCL06 --> TamnutOL-06; NM309N2 --> NM309-2Resource Title: Genotyping calls in VCF format. File Name: SF03_SNPs_whole_Axiom_Arachis2_vcf.gzResource Description: The Axiom array genotype calls, in VCF format. Changes were made to this file on 4/15/2020: Corrected three peanut variety identifiers: ROL11 --> TamrunOL-11; NCL06 --> TamnutOL-06; NM309N2 --> NM309-2Resource Title: DNA variants for all accessions, including from genome assemblies, in TSV format. File Name: SF04_SNPs_w_4_genomes_tsv.gzResource Description: The predominant DNA variants at each SNP location, for all accessions, including variants inferred from four available genome assemblies: A. duranensis and A. ipaensis together, and A. hypogaea accessions Tifrunner, Shitouqi, and Fuhuasheng. The format is in a simple tab-separated table, with 14431 columns (SNP positions). Changes were made to this file on 4/15/2020: Corrected three peanut variety identifiers: ROL11 --> TamrunOL-11; NCL06 --> TamnutOL-06; NM309N2 --> NM309-2Resource Title: DNA variants for all accessions, including from genome assemblies, in fasta format. File Name: SF05_SNPs_w_4_gnm_mrgd_fas.gzResource Description: The predominant DNA variants at each SNP location, for all accessions, including variants inferred from four available genome assemblies: A. duranensis and A. ipaensis together, and A. hypogaea accessions Tifrunner, Shitouqi, and Fuhuasheng. In fasta format. Changes were made to this file on 4/15/2020: Corrected three peanut variety identifiers: ROL11 --> TamrunOL-11; NCL06 --> TamnutOL-06; NM309N2 --> NM309-2Resource Title: Base-calls for selected accessions, relative to A- and B-genome progenitors. File Name: SF06_chip_and_genome_samples_v05.xlsxResource Description: DNA base-calls for 16 selected, diverse accessions, with comparisons to the variants observed in the A. duranensis and A. ipaensis genomes, and inferences regarding the likely progenitor for the DNA, i.e. A-genome (A. duranensis) or B-genome (A. ipaensis). Changes were made to this file on 4/15/2020: Added INDEX worksheet and corrected three peanut variety identifiers: ROL11 --> TamrunOL-11; NCL06 --> TamnutOL-06; NM309N2 --> NM309-2Resource Title: Reduced fasta alignments, at 98% identity. File Name: SF07_SNPs_w_4_gnm_mrgd_cen98_fas.gzResource Description: Reduced fasta alignments (relative to the complete alignment file, S5). File S7 has the centroid representatives at 98% identity. This files has 518 sequences. Changes were made to this file on 4/15/2020: Corrected three peanut variety identifiers: ROL11 --> TamrunOL-11; NCL06 --> TamnutOL-06; NM309N2 --> NM309-2Resource Title: Reduced fasta alignments, at 99% identity. File Name: SF08_SNPs_w_4_gnm_mrgd_cen99_fas.gzResource Description: Reduced fasta alignments (relative to the complete alignment file, S5). File S8 has the centroid representatives at 99% identity. This file has 680 sequences. Changes were made to this file on 4/15/2020: Corrected three peanut variety identifiers: ROL11 --> TamrunOL-11; NCL06 --> TamnutOL-06; NM309N2 --> NM309-2Resource Title: Phylogenetic tree of genotype data. File Name: SF09_SNPs_w_4_gnm_mrgd_rt3_nh_txt.gzResource Description: Phylogenetic tree (Newick format) calculated from the alignent in S5, and corresponding with the phylogenetic tree shown in manuscript Figure 1. Changes were made to this file on 4/15/2020: Corrected three peanut variety identifiers: ROL11 --> TamrunOL-11; NCL06 --> TamnutOL-06; NM309N2 --> NM309-2Resource Title: Subgenome origins of SNPs relative to the A-genome and B-genome progenitors. File Name: SF13_chip_and_genome_GFFs.xlsxResource Description: Inferred subgenome origins of SNPs relative to the A-genome and B-genome progenitors (A. duranensis and A. ipaensis). This data is in GFF format, derived from S6, and used as the basis for the plots in Figure 7 (showing regions of possible subgenome invasions). Changes were made to this file on 4/15/2020: Added INDEX worksheet and corrected three peanut variety identifiers: ROL11 --> TamrunOL-11; NCL06 --> TamnutOL-06; NM309N2 --> NM309-2Resource Title: Peruvian Moche-era peanut necklace. File Name: SF15_Sipan_neclkace_Donnan_Einstein.jpgResource Description: Picture of necklace of peanuts, sculpted in gold and silver, from the Moche-era tomb at Sipán (c.AD 250) in coastal Peru. Photograph by Susan Einstein, courtesy of Christopher Donnan. Changes were made to this file on 4/15/2020: Replaced black-and-white derived image with original color image

Snapshot img { margin: 10px !important; } Whole Exome Sequencing Market Size 2025-2029

The whole exome sequencing market size is forecast to increase by USD 3.7 billion, at a CAGR of 21.1% between 2024 and 2029.

The global whole exome sequencing market is expanding, driven by technological advancements and a steep decline in sequencing costs. This has transitioned WES from a niche research application to a routine tool in clinical diagnostics and genomics. The integration of artificial intelligence and machine learning is a key trend, accelerating variant interpretation and addressing the data bottleneck. This synergy enhances the dna sequencing market by shifting value from sequencing speed to the accuracy of interpretive reports. Such developments in bioinformatics are crucial for managing the large datasets generated and improving the diagnostic yield from genomic tests. The focus on genome engineering is also contributing to the evolution of sequencing applications in clinical practice.Despite these advancements, the market's growth is constrained by the bioinformatics bottleneck and the complexity of data interpretation. The process of identifying clinically significant variants from tens of thousands of possibilities requires specialized expertise and sophisticated computational tools. This analytical hurdle limits the scalability of WES services and impacts their cost-effectiveness. A significant portion of variants identified through WES are of uncertain significance, creating diagnostic ambiguity. The next generation sequencing market is therefore heavily invested in developing advanced analytical tools and promoting carrier screening to overcome these challenges and unlock the full potential of whole exome sequencing in routine healthcare.

What will be the Size of the Whole Exome Sequencing Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019 - 2023 and forecasts 2025-2029 - in the full report.
Request Free SampleThe technical foundation of the global whole exome sequencing market continues to advance, with developments in sequencing by synthesis and ion semiconductor sequencing improving throughput and accuracy. Innovations in exome enrichment kits and library preparation kits are crucial for enhancing diagnostic yield. The emergence of long-read sequencing technologies is particularly significant, offering new capabilities to resolve structural variants and copy number variations that are challenging for short-read methods. These advancements in the next generation sequencing market are expanding the scope of both research and clinical applications in genomics.In clinical practice, the application of whole exome sequencing is broadening beyond its initial focus on rare genetic diseases. It is now integral to targeted therapy selection in oncology, where the identification of somatic mutations and germline sequencing informs personalized treatment plans. The field of pharmacogenomics also increasingly relies on WES to predict patient responses to drugs. This expansion into mainstream clinical diagnostic workflows is supported by a growing body of evidence demonstrating its utility. The development of comprehensive sample-to-report solutions is making this technology more accessible to a wider range of healthcare providers undertaking carrier screening.The primary operational challenge remains the complexity of clinical variant interpretation and the associated bioinformatics bottleneck. The use of sophisticated bioinformatics pipelines and machine learning algorithms is essential for managing the large datasets and addressing the issue of variants of uncertain significance. The focus on next generation sequencing data analysis market is therefore critical. Establishing large-scale clinico-genomic databases and federated data networks is a key priority to improve the accuracy of variant classification and support the continued growth of precision medicine initiatives globally.

How is this Whole Exome Sequencing Industry segmented?

The whole exome sequencing industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in "USD million" for the period 2025-2029, as well as historical data from 2019 - 2023 for the following segments. ProductConsumablesServicesInstrumentsTechnologySequencing by synthesisION semiconductor sequencingOthersApplicationDrug discovery and developmentDiagnosticsPersonalized medicinePrenatal and neonatal screeningOthersGeographyNorth AmericaUSCanadaMexicoEuropeGermanyUKFranceItalyThe NetherlandsSpainRussiaAsiaRest of World (ROW)

By Product Insights

The consumables segment is estimated to witness significant growth during the forecast period.The consumables segment represents the financial engine of the whole exome sequencing market, encompassing all recurring materials required for the WES workflow. Th

Genome sequence and annotation of Fragaria vesca cv. Reine des Vallées In order to generate a reference genome for Fragaria vesca cv. Reine des Vallées, we used MinIon long-read sequencing data to substitute the F. vesca genome v.4.0.a2 genome. The detailed method used to obtain these results were the following: Genome sequencing and assembly NIL Fb2 Genomic DNA from strawberry plants was extracted by a Hexadecyltrimethylammonium bromide (Cetrimonium bromide, CTAB) modified protocol (Healey, Furtado, Cooper, & Henry, 2014) and purified with Agencourt AMPure XP beads (cat# A63880). Long-read sequencing was performed for the genome assembly; Genomic DNA by Ligation (Oxford Nanopore, cat# SQK-LSK109) library was prepared as described by the manufacturer and sequenced on a MinION for 72 h (Oxford Nanopore). Reference genome polishing Reads obtained from nanopore were filtered with Filtlong v0.2.1 (https://github.com/rrwick/Filtlong) using --min_mean_q 80 and --min_length 200. Cleaned reads were then aligned to the most recent version of the F. vesca genome v4.0.a2, downloaded from the Genome Database for Rosaceae (GDR) (https://www.rosaceae.org/species/fragaria_vesca/genome_v4.0.a2), using minimap2 v2.21 (H. Li, 2018) with parameters -aLx map-ont --MD -Y. The generated BAM file was then sorted and indexed with samtools v1.11 (H. Li et al., 2009). We used mosdepth v0.3.1 (Pedersen & Quinlan, 2018) to verify that coverage on chromosomic scaffolds was over 50 X. Sniffles v1.0.12a (Sedlazeck et al., 2018) with parameters -s 10 -r 1000 -q 20 --genotype -l 30 -d 1000 was used to detect structural variations larger than 30 bp. The VCF files obtained from Sniffles was sorted and filtered with BCFtools v1.14 (Danecek et al., 2021) to keep only structural variants (SV) with smaller than 200,00 bp (we observed that larger SV were most of the time false positive caused by misalignments in regions with gaps or Ns), supported by 10 or more reads and with allelic frequencies above 0.8 (we were interested in homozygous changes). The complete filtering command used is “bcftools view -q 0.8 -Oz -i '(SVTYPE = "DUP" || SVTYPE = "INS" || SVTYPE = "DEL" || SVTYPE = "TRA" || SVTYPE = "INV" || SVTYPE = "INVDUP") && %FILTER = "PASS" && FMT/DV>9 && SVLEN>29 && SVLEN<200000' “ From the VCF listing all the structural variants that we detected in our F. vesca accession, we generated a substituted genome version based on the reference F. vesca genome v.4.0.a2. The reference genome was first indexed with samtools faidx v1.11(Danecek et al., 2021) and a sequence dictionary was generated with Picard CreateSequenceDictionary v2.25.6 (https://broadinstitute.github.io/picard). The VCF containing the SV produced from our Nanopore sequencing was also indexed with gatk (Van der Auwera GA & O'Connor BD, 2020) IndexFeatureFile v4.2.0.0 (https://gatk.broadinstitute.org/hc/en-us/articles/360037262651-IndexFeatureFile). FastaAlternateReferenceMaker v4.2.0.0 (https://gatk.broadinstitute.org/hc/en-us/articles/360037594571-FastaAlternateReferenceMaker) was then run with the reference genome and the VCF file to generate a substituted genome representative of our Fragaria accession. As substituting our genome with the detected structural variants changes genomic coordinates, we also corrected the public GFF genome annotation of F. vesca (Y, Pi, Gao, Liu, & Kang, 2019) using liftoff v1.6.1 (Shumate & Salzberg, 2021). Liftoff also detects and annotates duplications within the substituted genome. Transposable elements annotation was carried out using the EDTA transposable element annotation pipeline v. 1.9.6 (S. Ou et al., 2019) on the substituted genome using default parameters. Differentially methylated regions The file Stress_vs_control_DMRs.zip file contains the DMRs that were called using the reads submitted to ENA (ERP135585) and obtained as follows: First, bedGraph files from wgbs pipeline were pre-filtered for a minimum coverage of 5 reads using awk command. These output files were then used as input for the EpiDiverse/dmr bioinformatics analysis pipeline for non-model plant species to define DMRs (Nunn et al., 2021) with default parameters (minimum coverage threshold 5; maximum q-value 0.05; minimum differential methylation level 10%; 10 as minimum number of Cs; Minimum distance (bp) between Cs that are not to be considered as part of the same DMR is 146 bp). The pipeline uses metilene v.0.2.6.1 (https://www.bioinf.uni-leipzig.de/Software/metilene/) for pairwise comparison between groups and R-packages ggplot2 v.3.3.5 and gplots v.3.1.1, for visualization results (Fig. S1). Based on our F. vesca genome transcript annotation and methylation data (overlapped regions with DNA methylation cytosines and DMRs), we detected the methylated genes, promoters, 3’ UTRs, 5’UTR and transposable elements in strawberry. Global DNA methylation and DMR plots were performed with R-package ggplot2. Gene analyses by methylation patterns and analysis of per-family TE DNA m

The CYP2D6 gene encodes an enzyme important in the metabolism of many commonly used medications. Variation in CYP2D6 is associated with inter-individual differences in medication response, and genetic testing is used to optimize medication therapy. This report describes a retrospective study of CYP2D6 allele frequencies in a large population of 104,509 de-identified patient samples across all regions of the United States (US). Thirty-seven unique CYP2D6 alleles including structural variants were identified. A majority of these alleles had frequencies which matched published frequency data from smaller studies, while eight had no previously published frequencies. Importantly, CYP2D6 structural variants were observed in 13.1% of individuals and accounted for 7% of the total variants observed. The majority of structural variants detected (73%) were decreased-function or no-function alleles. As such, structural variants were found in approximately one-third (30%) of CYP2D6 poor metabolizers in this study. This is the first CYP2D6 study to evaluate, with a consistent methodology, both structural variants and single copy alleles in a large US population, and the results suggest that structural variants have a substantial impact on CYP2D6 function.

Database of Genomic Structural Variation (dbVar) is NCBI's database of human genomic Structural Variation — large variants >50 bp including insertions, deletions, duplications, inversions, mobile elements, translocations, and complex variants.

IntroductionAutosomal dominant retinitis pigmentosa type 17 (adRP, type RP17) is caused by complex structural variants (SVs) affecting a locus on chromosome 17 (chr17q22). The SVs disrupt the 3D regulatory landscape by altering the topologically associating domain (TAD) structure of the locus, creating novel TAD structures (neo-TADs) and ectopic enhancer-gene contacts. Currently, screening for RP17-associated SVs is not included in routine diagnostics given the complexity of the variants and a lack of cost-effective detection methods. The aim of this study was to accurately detect novel RP17-SVs by establishing a systematic and efficient workflow.MethodsGenetically unexplained probands diagnosed with adRP (n = 509) from an international cohort were screened using a smMIPs or genomic qPCR-based approach tailored for the RP17 locus. Suspected copy number changes were validated using high-density SNP-array genotyping, and SV breakpoint characterization was performed by mutation-specific breakpoint PCR, genome sequencing and, if required, optical genome mapping. In silico modeling of novel SVs was performed to predict the formation of neo-TADs and whether ectopic contacts between the retinal enhancers and the GDPD1-promoter could be formed.ResultsUsing this workflow, potential RP17-SVs were detected in eight probands of which seven were confirmed. Two novel SVs were identified that are predicted to cause TAD rearrangement and retinal enhancer-GDPD1 contact, one from Germany (DE-SV9) and three with the same SV from the United States (US-SV10). Previously reported RP17-SVs were also identified in three Australian probands, one with UK-SV2 and two with SA-SV3.DiscussionIn summary, we describe a validated multi-step pipeline for reliable and efficient RP17-SV discovery and expand the range of disease-associated SVs. Based on these data, RP17-SVs can be considered a frequent cause of adRP which warrants the inclusion of RP17-screening as a standard diagnostic test for this disease.

Oxford Nanopore Technologies Ltd (Oxford, UK) have recently commercialized MinION, a small single-molecule nanopore sequencer, that offers the possibility of sequencing long DNA fragments from small genomes in a matter of seconds. The Oxford Nanopore technology is truly disruptive, it has the potential to revolutionize genomic applications due to its portability, low-cost, and ease of use compared with existing long reads sequencing technologies. The MinION sequencer enables the rapid sequencing of small eukaryotic genomes, such as the yeast genome. Combined with existing assembler algorithms, near complete genome assemblies can be generated and comprehensive population genomic analyses can be performed.
Here, we resequenced the genome of the Saccharomyces cerevisiae S288C strain to evaluate the performance of nanopore-only assemblers. Then we de novo sequenced and assembled the genomes of 21 isolates representative of the S. cerevisiae genetic diversity using the MinION platform. The contiguity of our assemblies was 14 times higher than the Illumina-only assemblies and we obtained one or two long contigs for 65% of the chromosomes. This high contiguity allowed us to accurately detect large structural variations across the 21 studied genomes.
Because of the high completeness of the nanopore assemblies, we were able to produce a complete cartography of transposable elements insertions and inspect structural variants that are generally missed using a short-read sequencing strategy.

Protein Structure Pathogenicity Dataset

  Dataset Description

This dataset contains protein structures and metadata for benign and pathogenic missense variants, designed for training machine learning models to predict variant pathogenicity using protein structural information.

  Dataset Summary

The dataset includes:

Protein 3D structures predicted via ESMFold Benign and pathogenic variants derived from the ProteinGym benchmark Structural and sequence metadata for… See the full description on the dataset page: https://huggingface.co/datasets/martindanner/protein_structure_pathogenicity_dataset.

ClinVar P/LP variants with allele frequencies exceeding 1/200 within seven founder populations in NYC.

Purpose: Multi-omics offer worthwhile and increasingly accessible technologies to diagnostic laboratories seeking potential second-tier strategies to help patients with unresolved rare diseases, especially patients clinically diagnosed with a rare OMIM (Online Mendelian Inheritance in Man) disease. However, no consensus exists regarding the optimal diagnostic care pathway to adopt after negative results with standard approaches.Methods: In 15 unsolved individuals clinically diagnosed with recognizable OMIM diseases but with negative or inconclusive first-line genetic results, we explored the utility of a multi-step approach using several novel omics technologies to establish a molecular diagnosis. Inclusion criteria included a clinical autosomal recessive disease diagnosis and single heterozygous pathogenic variant in the gene of interest identified by first-line analysis (60%–9/15) or a clinical diagnosis of an X-linked recessive or autosomal dominant disease with no causative variant identified (40%–6/15). We performed a multi-step analysis involving short-read genome sequencing (srGS) and complementary approaches such as mRNA sequencing (mRNA-seq), long-read genome sequencing (lrG), or optical genome mapping (oGM) selected according to the outcome of the GS analysis.Results: SrGS alone or in combination with additional genomic and/or transcriptomic technologies allowed us to resolve 87% of individuals by identifying single nucleotide variants/indels missed by first-line targeted tests, identifying variants affecting transcription, or structural variants sometimes requiring lrGS or oGM for their characterization.Conclusion: Hypothesis-driven implementation of combined omics technologies is particularly effective in identifying molecular etiologies. In this study, we detail our experience of the implementation of genomics and transcriptomics technologies in a pilot cohort of previously investigated patients with a typical clinical diagnosis without molecular etiology.

Objective: Hmong individuals represent a unique East Asian subpopulation in whom limited information concerning pharmacogenetic variation exists. The objectives of this study were to comprehensively characterize the highly polymorphic CYP2D6 gene in Hmong, estimate allele and phenotype frequencies and to compare results between two testing platforms.Methods: DNA from 48 self-identified Hmong participants were sequenced using a targeted next-generation sequencing (NGS) panel. Star allele calls were made using Astrolabe, manual inspection of NGS variant calls and confirmatory Sanger sequencing. Structural variation was determined by long-range (XL)-PCR and digital droplet PCR (ddPCR). The consensus diplotypes were subsequently translated into phenotype utilizing the activity score system. Clinical grade pharmacogenetic testing was obtained for 12 of the 48 samples enabling an assessment of concordance between the consensus calls and those determined by clinical testing platforms.Results: A total of 13 CYP2D6 alleles were identified. The most common alleles were CYP2D6*10 and its structural arrangements (37.5%, 36/96) and the *5 gene deletion (13.5%, 13/96). Three novel suballeles (*10.007, *36.004, and *75.002) were also identified. Phenotype frequencies were as follows: ultrarapid metabolizers (4.2%, 2/48), normal metabolizers (41.7%, 20/48) and intermediate metabolizers (52.1%, 25/48); none of the 48 participants were predicted to be poor metabolizers. Concordance of diplotype and phenotype calls between the consensus and clinical testing were 66.7 and 50%, respectively.Conclusion: Our study to explore CYP2D6 genotypes in the Hmong population suggests that this subpopulation is unique regarding CYP2D6 allelic variants; also, a higher portion of Hmong participants (50%) are predicted to have an intermediate metabolizer phenotype for CYP2D6 compared to other East Asians which range between 27 and 44%. Results from different testing methods varied considerably. These preliminary findings underscore the importance of thoroughly interrogating unique subpopulations to accurately predict a patient’s CYP2D6 metabolizer status.

As plate tectonics pushed Antarctica into a polar position, by ~34 million years ago, the continent and its surrounding Southern Ocean (SO) became geographically and thermally isolated by the Antarctic Circumpolar Current. Terrestrial and marine glaciation followed, resulting in extinctions as well as the survival and radiation of unique flora and fauna. The notothenioid fish survived and arose from a common ancestral stock into tax with 120 species that dominates today's SO fish fauna. The Notothenioids evolved adaptive traits including novel antifreeze proteins for survival in extreme cold, but also suffered seemingly adverse trait loss including red blood cells in the icefish family, and the ability to mount cellular responses to mitigate heat stress ? otherwise ubiquitous across all life. This project aims to understand how the notothenoid genomes have changed and contributed to their evolution in the cold. The project will sequence, analyze and compare the genomes of two strategic pairs of notothenioid fishes representing both red-blooded and white-blooded species. Each pair will consist of one Antarctic species and one that has readapted to the temperate waters of S. America or New Zealand. The project will also compare the Antarctic species genomes to a genome of the closet non-Antarctic relative representing the temperate notothenioid ancestor. The work aims to uncover the mechanisms that enabled the adaptive evolution of this ecologically vital group of fish in the freezing Southern Ocean, and shed light on their adaptability to a warming world. The finished genomes will be made available to promote and advance Antarctic research and the project will host a symposium of Polar researchers to discuss the cutting edge developments regarding of genomic adaptations in the polar region.

Despite subzero, icy conditions that are perilous to teleost fish, the fish fauna of the isolated Southern Ocean (SO) surrounding Antarctica is remarkably bountiful. A single teleost group - the notothenioid fishes - dominate the fauna, comprising over 120 species that arose from a common ancestor. When Antarctica became isolated and SO temperatures began to plunge in early Oligocene, the prior temperate fishes became extinct. The ancestor of Antarctic notothenioids overcame forbidding polar conditions and, absent niche competition, it diversified and filled the SO. How did notothenioids adapt to freezing environmental selection pressures and achieve such extraordinary success? And having specialized to life in chronic cold for 30 myr, can they evolve in pace with today's warming climate to stay viable? Past studies of Antarctic notothenioid evolutionary adaptation have discovered various remarkable traits including the key, life-saving antifreeze proteins. But life specialized to cold also led to paradoxical trait changes such as the loss of the otherwise universal heat shock response, and of the O2-transporting hemoglobin and red blood cells in the icefish family. A few species interestingly regained abilities to live in temperate waters following the escape of their ancestor out of the freezing SO.

This proposed project is the first major effort to advance the field from single trait studies to understanding the full spectrum of genomic and genetic responses to climatic and environmental change during notothenioid evolution, and to evaluate their adaptability to continuing climate change. To this end, the project will sequence the genomes of four key species that embody genomic responses to different thermal selection regimes during notothenioids' evolutionary history, and by comparative analyses of genomic structure, architecture and content, deduce the responding changes. Specifically, the project will (i) obtain whole genome assemblies of the red-blooded T. borchgrevinki and the S. American icefish C. esox; (ii) using the finished genomes from (i) as template, obtain assemblies of the New Zealand notothenioid N. angustata, and the white-blooded icefish C. gunnari, representing a long (11 myr) and recent (1 myr) secondarily temperate evolutionary history respectively. Genes that are under selection in the temperate environment but not in the Antarctic environment can be inferred to be directly necessary for that environment and the reverse is also true for genes under selection in the Antarctic but not in the temperate environment. Further, genes important for survival in temperate waters will show parallel selection between N. angustata and C. esox despite the fact that the two fish left the Antarctic at far separated time points. Finally, gene families that expanded due to strong selection within the cold Antarctic should show a degradation of duplicates in the temperate environment. The project will test these hypotheses using a number of techniques to compare the content and form of genes, the structure of the chromosomes containing those genes, and through the identification of key characters, such as selfish genetic elements, introns, and structural variants.