Low-coverage Genome Research Articles

Phylogenetic analysis of Syrphidae (Insecta, Diptera) based on low-coverage whole genomes

Abstract The hoverflies are one of the most abundant families in Diptera and an important category of resource insects. They can provide important ecosystem services such as pollination and beneficial biological control agents. In the four-subfamily classification system of the Syrphidae, the monophyly of the Eristalinae within Syrphidae has not been recovered. In this study, we performed new sequencing and analysis of low-coverage whole genomes for 25 species of Syrphidae. Phylogenetic reconstructions were conducted based on different datasets and analytical strategies. Across all our analyses, the monophyly of the Syrphinae is supported but we do not recover the monophyly of the Eristalinae, consistent with previous research findings. Additionally, employing fossil calibrations for divergence time estimation, our results indicate that the origin of the Syrphidae occurred between the Albian and Aptian stages, approximately between 120.5 and 109.3 million years ago, the origin of the subfamily Syrphinae was dated in the Early Eocene, about 50.8–47.8 million years ago, in accordance with the diversification of their prey. This study will help us understand the higher-level phylogenetic and evolutionary relationships within Syrphidae.

A Snakemake Toolkit for the Batch Assembly, Annotationand Phylogenetic Analysis of Mitochondrial Genomes and Ribosomal Genes From Genome Skims of Museum Collections.

Low coverage 'genome-skims' are often used to assemble organelle genomes and ribosomal gene sequences for cost-effective phylogenetic and barcoding studies. Natural history collections hold invaluable biological information, yet poor preservation resulting in degraded DNA often hinders polymerase chain reaction-based analyses. However, it is possible to generate libraries and sequence the short fragments typical of degraded DNA to generate genome-skims from museum collections. Here we introduce a snakemake toolkit comprised of three pipelines skim2mito, skim2rrna and gene2phylo, designed to unlock the genomic potential of historical museum specimens using genome skimming. Specifically, skim2mito and skim2rrna perform the batch assembly, annotation and phylogenetic analysis of mitochondrial genomes and nuclear ribosomal genes, respectively, from low-coverage genome skims. The third pipeline gene2phylo takes a set of gene alignments and performs phylogenetic analysis of individual genes, partitioned analysis of concatenated alignments and a phylogenetic analysis based on gene trees. We benchmark our pipelines with simulated data, followed by testing with a novel genome skimming dataset from both recent and historical solariellid gastropod samples. We show that the toolkit can recover mitochondrial and ribosomal genes from poorly preserved museum specimens of the gastropod family Solariellidae, and the phylogenetic analysis is consistent with our current understanding of taxonomic relationships. The generation of bioinformatic pipelines that facilitate processing large quantities of sequence data from the vast repository of specimens held in natural history museum collections will greatly aid species discovery and exploration of biodiversity over time, ultimately aiding conservation efforts in the face of a changing planet.

Cancer treatment monitoring using cell-free DNA fragmentomes.

Circulating cell-free DNA (cfDNA) assays for monitoring individuals with cancer typically rely on prior identification of tumor-specific mutations. Here, we develop a tumor-independent and mutation-independent approach (DELFI-tumor fraction, DELFI-TF) using low-coverage whole genome sequencing to determine the cfDNA tumor fraction and validate the method in two independent cohorts of patients with colorectal or lung cancer. DELFI-TF scores strongly correlate with circulating tumor DNA levels (ctDNA) (r = 0.90,p < 0.0001, Pearson correlation) even in cases where mutations are undetectable. DELFI-TF scores prior to therapy initiation are associated with clinical response and are independent predictors of overall survival (HR = 9.84, 95% CI = 1.72-56.10,p < 0.0001). Patients with lower DELFI-TF scores during treatment have longer overall survival (62.8 vs 29.1 months, HR = 3.12, 95% CI 1.62-6.00,p < 0.001) and the approach predicts clinical outcomes more accurately than imaging. These results demonstrate the potential of using cfDNA fragmentomes to estimate tumor burden in cfDNA for treatment response monitoring and clinical outcome prediction.

Rapid species-level metagenome profiling and containment estimation with sylph.

Profiling metagenomes against databases allows for the detection and quantification of microorganisms, even at low abundances where assembly is not possible. We introduce sylph, a species-level metagenome profiler that estimates genome-to-metagenome containment average nucleotide identity (ANI) through zero-inflated Poisson k-mer statistics, enabling ANI-based taxa detection. On the Critical Assessment of Metagenome Interpretation II (CAMI2) Marine dataset, sylph was the most accurate profiling method of seven tested. For multisample profiling, sylph took >10-fold less central processing unit time compared to Kraken2 and used 30-fold less memory. Sylph's ANI estimates provided an orthogonal signal to abundance, allowing for an ANI-based metagenome-wide association study for Parkinson disease (PD) against 289,232 genomes while confirming known butyrate-PD associations at the strain level. Sylph took <1 min and 16 GB of random-access memory to profile metagenomes against 85,205 prokaryotic and 2,917,516 viral genomes, detecting 30-fold more viral sequences in the human gut compared to RefSeq. Sylph offers precise, efficient profiling with accurate containment ANI estimation even for low-coverage genomes.

Evaluation of Aedes aegypti control intervention with pyriproxyfen by lcWGS in Manacapuru, Amazonas, Brazil.

Ae. aegypti mosquitoes are considered a global threat to public health due to its ability to transmit arboviruses such as yellow fever, dengue, Zika and Chikungunya to humans. The lack of effective arboviral vaccines and etiological treatments make vector control strategies fundamental in interrupting the transmission cycle of these pathogens. This study evaluated Ae. aegypti mosquito populations pre- and post-intervention period with disseminating stations of the larvicide pyriproxyfen to understand its potential influence on the genetic structure and population diversity of these vectors. This study was conducted in Manacapuru city, Amazonas, Brazil, where 1,000 pyriproxyfen dissemination stations were deployed and monitored from FEB/2014 to FEB/2015 (pre-intervention) and AUG/2015 to JAN/2016 (post-intervention). Low-coverage whole genome sequencing of 36 individuals was performed, revealing significant stratification between pre- and post-intervention groups (pairwise FST estimate of 0.1126; p-value < 0.033). Tajima's D estimates were -3.25 and -3.07 (both p-value < 0.01) for pre- and post-intervention groups, respectively. Molecular diversity estimates (Theta(S) and Theta(Pi)) also showed divergences between pre- and post-intervention groups. PCA and K-means analysis showed clustering for SNP frequency matrix and SNP genotype matrix, respectively, being both mainly represented by the first principal component. PCA and K-means clustering also showed significant results that corroborate the impact of pyriproxyfen intervention on genetic structure populations of Ae. aegypti mosquitoes. The results revealed a bottleneck effect and reduced mosquito populations during intervention, followed by reintroduction from adjacent and unaffected populations by this vector. We highlighted that low-coverage whole genome sequencing can contribute to genetic and structure population data, and also generate important information to aid in genomic and epidemiological surveillance.

Abstract C095: Molecular characterization of gastric adenocarcinoma from Latinos shows homologous recombination deficiency

Abstract Latinos have a higher risk of developing gastric cancer (GC) than non-Latino Whites (NLW). Multiple studies have shown increased treatment resistance in diffuse-type cancers, which are more prevalent in Latino patients and dominated by the genomically stable (GS) genomic subtype. However, there is little genomic data from Latino gastric tumors due to the few studies targeting this minority population. Here, we attempt to rectify the disparity of genomic data by performing whole exome and/or low-coverage whole genome sequencing on tumors from 195 Latino gastric adenocarcinoma patients, from Colombia and Mexico. We also analyze 42 Latino patients from the US from a previous study. In total, we analyze tumors from 237 patients, the largest cohort of Latino gastric cancer tumors comprehensively sequenced thus far. Molecular subtyping of our cohort shows a higher proportion of tumors with a genomically stable (GS) subtype, 59%, and less with chromosomal instability (CIN), 24%, than reported in non-Latino patients from the Cancer Genome Atlas (20% and 50% respectively). Our earlier study of germline variants from Latinos, indicated a potential enrichment of variant related to homologous recombination deficiency (HRD), an important DNA repair mechanism. Focusing on this pathway, we performed HRD scoring and show that CIN tumors had the highest HRD score compared to all other subtypes. An alternative method analyzing somatic mutational patterns identified an indel mutational signature (ID6), also related to HRD, was enriched in GS tumors. Overall, these data provide a broader picture of the genomic landscape of Hispanic tumors, highlighting HRD targeting drugs as a potential treatment for both GS diffuse-types cancers particularly seen in Latinos and CIN tumors found more generally in gastric cancer. Citation Format: Dennis J Montoya, Ana Estrada-Florez, Paul Lott, Katherine Chiu, John Suarez-Olaya, Fabian Castro, Magdalena Echeverry de Polanco, Javier Torres, Mabel Bohorquez, Luis Carvajal-Carmona. Molecular characterization of gastric adenocarcinoma from Latinos shows homologous recombination deficiency [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr C095.

How many species are there? Lineage diversification and hidden speciation in Solanaceae from highland grasslands in southern South America.

Species delimitation can be challenging when analysing recently diverged species, especially those taxonomically synonymised due to morphological similarities. We aimed to untangle the relationships between two grassland species, Petunia guarapuavensis and Petunia scheideana, exploring the dynamics of fast divergence and addressing their species delimitation. We used a low-coverage genome sequencing and population genomic approach to distinguish species and populations between P. guarapuavensis and P. scheideana. Our analysis focused on detecting structuration, hybridisation/introgression, and phylogenetic patterns. We employed demographic models to support species delimitation while exploring potential phylogeographic barriers influencing gene flow. Our findings indicated differentiation between the two species and revealed another lineage, which was phylogenetically distinct from the others and had no evidence of gene flow with them. The presence of a river acted as a phylogeographic barrier, limiting gene flow and allowing for structuration between closely related lineages. The optimal species delimitation scenario involved secondary contact between well-established lineages. The rapid divergence observed in these Petunia species explains the lack of significant morphological differences, as floral diagnostic traits in species sharing the pollinators tend to evolve more slowly. This study highlights the complexity of species delimitation in recently diverged groups and emphasises the importance of genomic approaches in understanding evolutionary relationships and speciation dynamics.

Blended Genome Exome (BGE) as a Cost Efficient Alternative to Deep Whole Genomes or Arrays.

Genomic scientists have long been promised cheaper DNA sequencing, but deep whole genomes are still costly, especially when considered for large cohorts in population-level studies. More affordable options include microarrays + imputation, whole exome sequencing (WES), or low-pass whole genome sequencing (WGS) + imputation. WES + array + imputation has recently been shown to yield 99% of association signals detected by WGS. However, a method free from ascertainment biases of arrays or the need for merging different data types that still benefits from deeper exome coverage to enhance novel coding variant detection does not exist. We developed a new, combined, "Blended Genome Exome" (BGE) in which a whole genome library is generated, an aliquot of that genome is amplified by PCR, the exome regions are selected and enriched, and the genome and exome libraries are combined back into a single tube for sequencing (33% exome, 67% genome). This creates a single CRAM with a low-coverage whole genome (2-3x) combined with a higher coverage exome (30-40x). This BGE can be used for imputing common variants throughout the genome as well as for calling rare coding variants. We tested this new method and observed >99% r 2 concordance between imputed BGE data and existing 30x WGS data for exome and genome variants. BGE can serve as a useful and cost-efficient alternative sequencing product for genomic researchers, requiring ten-fold less sequencing compared to 30x WGS without the need for complicated harmonization of array and sequencing data.

Novel liquid biopsy CNV biomarkers in malignant melanoma

Malignant melanoma (MM) is known for its abundance of genetic alterations and a tendency for rapid metastasizing. Identification of novel plasma biomarkers may enhance non-invasive diagnostics and disease monitoring. Initially, we examined copy number variations (CNV) in CDK genes (CDKN2A, CDKN2B, CDK4) using MLPA (gDNA) and ddPCR (ctDNA) analysis. Subsequently, low-coverage whole genome sequencing (lcWGS) was used to identify the most common CNV in plasma samples, followed by ddPCR verification of chosen biomarkers. CNV alterations in CDK genes were identified in 33.3% of FFPE samples (Clark IV, V only). Detection of the same genes in MM plasma showed no significance, neither compared to healthy plasmas nor between pre- versus post-surgery plasma. Sequencing data showed the most common CNV occurring in 6q27, 4p16.1, 10p15.3, 10q22.3, 13q34, 18q23, 20q11.21-q13.12 and 22q13.33. CNV in four chosen genes (KIF25, E2F1, DIP2C and TFG) were verified by ddPCR using 2 models of interpretation. Model 1 was concordant with lcWGS results in 54% of samples, for model 2 it was 46%. Although CDK genes have not been proven to be suitable CNV liquid biopsy biomarkers, lcWGS defined the most frequently affected chromosomal regions by CNV. Among chosen genes, DIP2C demonstrated a potential for further analysis.

Genome resequencing reveals population divergence and local adaptation of blacklegged ticks in the United States.

Tick vectors and tick-borne disease are increasingly impacting human populations globally. An important challenge is to understand tick movement patterns, as this information can be used to improve management and predictive modelling of tick population dynamics. Evolutionary analysis of genetic divergence, gene flow and local adaptation provides insight on movement patterns at large spatiotemporal scales. We develop low coverage, whole genome resequencing data for 92 blacklegged ticks, Ixodes scapularis, representing range-wide variation across the United States. Through analysis of population genomic data, we find that tick populations are structured geographically, with gradual isolation by distance separating three population clusters in the northern United States, southeastern United States and a unique cluster represented by a sample from Tennessee. Populations in the northern United States underwent population contractions during the last glacial period and diverged from southern populations at least 50 thousand years ago. Genome scans of selection provide strong evidence of local adaptation at genes responding to host defences, blood-feeding and environmental variation. In addition, we explore the potential of low coverage genome sequencing of whole-tick samples for documenting the diversity of microbial pathogens and recover important tick-borne pathogens such as Borrelia burgdorferi. The combination of isolation by distance and local adaptation in blacklegged ticks demonstrates that gene flow, including recent expansion, is limited to geographical scales of a few hundred kilometres.

Global and local ancestry estimation in a captive baboon colony.

The last couple of decades have highlighted the importance of studying hybridization, particularly among primate species, as it allows us to better understand our own evolutionary trajectory. Here, we report on genetic ancestry estimates using dense, full genome data from 881 olive (Papio anubus), yellow (Papio cynocephalus), or olive-yellow crossed captive baboons from the Southwest National Primate Research Center. We calculated global and local ancestry information, imputed low coverage genomes (n = 830) to improve marker quality, and updated the genetic resources of baboons available to assist future studies. We found evidence of historical admixture in some putatively purebred animals and identified errors within the Southwest National Primate Research Center pedigree. We also compared the outputs between two different phasing and imputation pipelines along with two different global ancestry estimation software. There was good agreement between the global ancestry estimation software, with R2 > 0.88, while evidence of phase switch errors increased depending on what phasing and imputation pipeline was used. We also generated updated genetic maps and created a concise set of ancestry informative markers (n = 1,747) to accurately obtain global ancestry estimates.

CD147 protein molecule expression and chromosomal instability in the pathogenesis and prognosis of thyroid cancer

Low-coverage whole genome sequencing was performed for tissue samples from thyroid patients who received surgery treatment from 2015 to 2021. The potential biological significance of CD147 protein in thyroid cancer was explored through correlation analysis of CD147 protein expression level and clinical features of thyroid cancer patients. Low coverage whole genome sequencing was performed on the extracted DNA samples. The copy number analysis software was used to analyze the sequencing data, calculate the copy number of CD147 gene, further verify the expression of CD147 gene, and analyze its association with clinical features. The relationship between CIN and high risk was evaluated in the internal cohort. The association of CIN with the disease-free survival was validated in the cohort from The Cancer Genome Atlas Program. Thyroglobulin plays a key role in regulating thyroid function and maintaining normal metabolic rate. By sequencing tissue samples from this study, we can gain a deeper understanding of the association between cin and thyroid disease. The percentage of high risk patients in the multiple CIN group (77.8 %) was significantly higher than that in the 22q negative group (31.3 %), BRAF V600E group (22.2 %) and all negative group (25.0 %; p = 0.043).

PATH-04. OPTIMIZING CELL-FREE DNA ASSAYS FOR LOW INPUT LIQUID BIOPSY SAMPLES FROM PEDIATRIC BRAIN TUMOR PATIENTS

Abstract BACKGROUND Genetic and epigenetic profiling have transformed biological understanding, diagnostics, and therapeutic approaches for pediatric central nervous system (CNS) tumors. Obtaining tumor tissue may be associated with neurosurgical risk, may not be feasible in some cases, and is not routinely performed during follow-up or at relapse. Liquid biopsies (LBs) have emerged as a minimally invasive, serially collectable source of tumor-derived DNA. Here, we collected cerebrospinal fluid (CSF) and serum LBs from a large, unselected, cross-entity pediatric CNS tumor cohort (n=55 patients) for method optimization. METHODS Cell-free DNA (cfDNA) isolated from CSF and serum samples was analyzed 1) by low-coverage whole genome sequencing for copy number variation (CNV)-based tumor detection and 2) by enzymatic conversion (EC)-based DNA methylation profiling using the EPIC DNA methylation array and the Heidelberg Brain Tumor Classifier. All library protocols were optimized for LB samples with low cfDNA amounts in the picogram range. Matched tumor samples were used as reference. RESULTS Our lcWGS-based cfDNA profiling protocol had a high technical success rate across the whole cohort (&amp;gt;95%), despite very low cfDNA amounts for most CSF samples. The majority of CSF LBs captured tumor-derived CNVs and displayed a high fraction of tumor-derived cfDNA (&amp;gt;5%, range 0-78%). For serum LBs, only few samples showed detectable CNVs. Proof-of-concept methylation analyses leveraging a new EC-based workflow allowed molecular classification using CSF, particularly for embryonal brain tumors (11/15 samples). Clinical workup of selected cases illustrates the potential of LBs to aid as diagnostic tool, monitor disease, and characterize tumor evolution. CONCLUSIONS Tackling a major roadblock of clinical translation of LBs, this study delineates new methods tailored to low input cfDNA samples. Results highlight the clinical utility of LBs for the management of brain tumor patients, providing a strong rationale for prospective validation within pediatric neuro-oncology trials.

Whole genome resequencing of sablefish at the northern end of their range reveals genetic panmixia and large putative inversions

Abstract Sablefish (Anoplopoma fimbria) are a highly mobile species that support important commercial fisheries in the North Pacific Ocean. Information on the genetic stock structure of sablefish is vital for constructing management strategies that ensure the long-term viability of the species. Most previous genetic studies on sablefish have found panmixia throughout the majority of their range, but a recent study suggested that a population structure may exist. Here, we use low-coverage whole genome resequencing to investigate genetic structure in the northern end of the species’ range (from Washington State, USA to the Bering Sea and Aleutian Islands, AK, USA). Additionally, we reanalyzed an existing genomic dataset containing 2661 markers to test specific hypotheses about genetic structure by sex. Genome resequencing data from 119 individuals screened at 7 110 228 markers revealed no evidence of population structure, and reanalysis of the existing genomic dataset supported the same conclusion. Differentiation across the genome was largely driven by variation at two putative inversions located ∼1 megabase apart, which did not display any signals of geographic differentiation. Our study further supports the conclusion of genetic panmixia in sablefish throughout its northern range.

Utility of liquid biopsy for predicting cancer type and informing treatment of carcinoma with unknown primary.

e13606 Background: The advent of next-generation sequencing has greatly facilitated physicians in recommending tailored treatments for cancer patients. Despite these advancements, the dependence on the primary tumor site remains crucial for accurate diagnoses, posing a substantial obstacle in cases of carcinomas of unknown primary (CUPs) and hindering optimal patient care. To address this challenge, we propose the implementation of a machine learning model capable of identifying the tissue of origin (TOO) across 16 cancer types. Current standards gravitate to the use of tumor tissue for identifying primary tumor site. Leveraging the advantages of cell-free DNA (cfDNA), our approach provides a non-invasive and highly sensitive alternative to traditional biopsy or radiography methods. Methods: Cell-free DNA was extracted from patients diagnosed with carcinoma of known origin. The model underwent training using a dataset comprising 2,793 cfDNA samples, while the validation set consisted of 1,863 samples. The training and validation cohorts exhibited comparable demographics in terms of sex, age, and cancer types. Employing low-coverage whole genome sequencing (WGS), samples were analyzed to capture cfDNA features, including DNA fragment size distribution, copy number variation, nucleosome coverage pattern, mutational signature, and hotspot regions associated with cancer-related mutations. The final prediction model's accuracy was evaluated based on top 1 and top 2 predictions in accordance with the true tumor site of origin. Results: Overall accuracy of TOO predictions in the training cohort is 80.20% (2240/2793) for top 1 site and 90.26% (2521/2793) for top 2 sites. Overall accuracy of TOO predictions in the validation cohort is 81.80% (1524/1863) for top 1 site and 90.07% (1678/1863) for top 2 sites. Accuracy of tumor site prediction in the validation cohort is highest for lung cancer (Top 1 = 95.9%; Top 2 = 98.0%) tumor sites and lowest for biliary system and kidney tumor types (Top 1 = 54.3% &amp; 57.4%; Top 2 = 71.6% &amp; 63.2%). In the clinical setting, TOO estimation of 12/16 patients with CUP were identified to be in concordance with majority pathological consensus. Of note, two patients with CUP were diagnosed as lung cancer patients through TOO estimation. Molecular biomarkers of lung adenocarcinoma were also identified through targeted sequencing which corroborated the diagnosis, and chemoradiotherapy was recommended to the patient. Conclusions: We developed an accurate predictor of TOO by leveraging machine learning algorithm and incorporating cfDNA mutational, fragmentomic, and epigenetic features. Our results demonstrate high concordance between model-predicted and actual tumor sites across all examined cancer types. This model shows promise in offering valuable insights for the identification of cancers with an unknown primary origin using non-invasive cell free DNA samples.

Identification of the 18 World War II executed citizens of Adele, Rethymnon, Crete using an ancient DNA approach and low coverage genomes

In the Battle of Crete during the World War II occupation of Greece, the German forces faced substantial civilian resistance. To retribute the numerous German losses, a series of mass executions took place in numerous places in Crete; a common practice reported from Greece and elsewhere. In Adele, a village in the regional unit of Rethymnon, 18 male civilians were executed and buried in a burial pit at the Sarakina site. In this study, the first one conducted for a conflict that occurred in Greece, we identified for humanitarian purposes the 18 skulls of the Sarakina victims, following a request from the local community of Adele. The molecular identification of historical human remains via ancient DNA approaches and low coverage whole genome sequencing has only recently been introduced. Here, we performed genome skimming on the living relatives of the victims, as well as high throughput historical DNA analysis on the skulls to infer the kinship degrees among the victims via genetic relatedness analyses. We also conducted targeted anthropological analysis to successfully complete the identification of all Sarakina victims. We demonstrate that our methodological approach constitutes a potentially highly informative forensic tool to identify war victims. It can hence be applied to analogous studies on degraded DNA, thus, paving the path for systematic war victim identification in Greece and beyond.

High-throughput and cost-effective genotyping by low-coverage whole genome sequencing with genotype imputation in Pacific oyster, Crassostrea gigas

In order to improve the application of genomic resources in genomic selection breeding of aquaculture species, it is imperative to develop high throughput genotyping methods that are suitable for aquatic species with highly heterozygous and complex genomes. This study aimed to address the issue of accurate genotype imputation for lcWGS (low coverage whole genome sequencing) without reference panel in aquatic species. We performed lcWGS with an average depth of 2.8× on 360 individuals of Crassostrea gigas, then performed genotype imputation through reference-free method to achieve genome-wide genotyping. The results demonstrated that STITCH showed outstanding performance in conducting genotype imputation without reference panel, with R2 of 0.860 ± 0.055 and GC of 0.936 ± 0.022. The comparison of accuracy among different populations indicated that the selected breeding population with higher level of linkage disequilibrium within the population showed significant improvement in imputation accuracy compared to the wild population (P < 0.01). The diminishing marginal utility in accuracy beyond 300 samples suggested that hundreds of individuals were adequate for accurate genotyping by lcWGS. The imputed genotypes showed high accuracy in identifying genetic relationships and potential application in selection breeding. This study provides valuable information toward application of high-throughput and cost-effective genotyping in accelerating genetic analysis and genomic selection of economic traits in aquaculture species.

Skimming genomes for systematics and DNA barcodes of corals.

Numerous genomic methods developed over the past two decades have enabled the discovery and extraction of orthologous loci to help resolve phylogenetic relationships across various taxa and scales. Genome skimming (or low-coverage genome sequencing) is a promising method to not only extract high-copy loci but also 100s to 1000s of phylogenetically informative nuclear loci (e.g., ultraconserved elements [UCEs] and exons) from contemporary and museum samples. The subphylum Anthozoa, including important ecosystem engineers (e.g., stony corals, black corals, anemones, and octocorals) in the marine environment, is in critical need of phylogenetic resolution and thus might benefit from a genome-skimming approach. We conducted genome skimming on 242 anthozoan corals collected from 1886 to 2022. Using existing target-capture baitsets, we bioinformatically obtained UCEs and exons from the genome-skimming data and incorporated them with data from previously published target-capture studies. The mean number of UCE and exon loci extracted from the genome skimming data was 1837 ± 662 SD for octocorals and 1379 ± 476 SD loci for hexacorals. Phylogenetic relationships were well resolved within each class. A mean of 1422 ± 720 loci was obtained from the historical specimens, with 1253 loci recovered from the oldest specimen collected in 1886. We also obtained partial to whole mitogenomes and nuclear rRNA genes from >95% of samples. Bioinformatically pulling UCEs, exons, mitochondrial genomes, and nuclear rRNA genes from genome skimming data is a viable and low-cost option for phylogenetic studies. This approach can be used to review and support taxonomic revisions and reconstruct evolutionary histories, including historical museum and type specimens.

A High-Coverage Mesolithic Aurochs Genome and Effective Leveraging of Ancient Cattle Genomes Using Whole Genome Imputation.

Ancient genomic analyses are often restricted to utilizing pseudohaploid data due to low genome coverage. Leveraging low-coverage data by imputation to calculate phased diploid genotypes that enables haplotype-based interrogation and single nucleotide polymorphism (SNP) calling at unsequenced positions is highly desirable. This has not been investigated for ancient cattle genomes despite these being compelling subjects for archeological, evolutionary, and economic reasons. Here, we test this approach by sequencing a Mesolithic European aurochs (18.49×; 9,852 to 9,376 calBCE) and an Early Medieval European cow (18.69×; 427 to 580 calCE) and combine these with published individuals: two ancient and three modern. We downsample these genomes (0.25×, 0.5×, 1.0×, and 2.0×) and impute diploid genotypes, utilizing a reference panel of 171 published modern cattle genomes that we curated for 21.7 million (Mn) phased SNPs. We recover high densities of correct calls with an accuracy of >99.1% at variant sites for the lowest downsample depth of 0.25×, increasing to >99.5% for 2.0× (transversions only, minor allele frequency [MAF] ≥ 2.5%). The recovery of SNPs correlates with coverage; on average, 58% of sites are recovered for 0.25× increasing to 87% for 2.0×, utilizing an average of 3.5 million (Mn) transversions (MAF ≥2.5%), even in the aurochs, despite the highest temporal distance from the modern reference panel. Our imputed genomes behave similarly to directly called data in allele frequency-based analyses, for example consistently identifying runs of homozygosity >2 Mb, including a long homozygous region in the Mesolithic European aurochs.

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

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