Whole-genome DNA Sequencing Research Articles

It Takes Two to Make a Thing Go Right: Epistasis, Two-Component Response Systems, and Bacterial Adaptation

Understanding the interplay between genotype and fitness is a core question in evolutionary biology. Here, we address this challenge in the context of microbial adaptation to environmental stressors. This study explores the role of epistasis in bacterial adaptation by examining genetic and phenotypic changes in silver-adapted Escherichia coli populations, focusing on the role of beneficial mutations in two-component response systems (TCRS). To do this, we measured 24-hour growth assays and conducted whole-genome DNA and RNA sequencing on E. coli mutants that confer resistance to ionic silver. We showed recently that the R15L cusS mutation is central to silver resistance, primarily through upregulation of the cus efflux system. However, here we show that this mutation’s effectiveness is significantly enhanced by epistatic interactions with additional mutations in regulatory genes such as ompR, rho, and fur. These interactions reconfigure global stress response networks, resulting in robust and varied resistance strategies across different populations. This study underscores the critical role of epistasis in bacterial adaptation, illustrating how interactions between multiple mutations and how genetic backgrounds shape the resistance phenotypes of E. coli populations. This work also allowed for refinement of our model describing the role TCRS genes play in bacterial adaptation by now emphasizing that adaptation to environmental stressors is a complex, context-dependent process, driven by the dynamic interplay between genetic and environmental factors. These findings have broader implications for understanding microbial evolution and developing strategies to combat antimicrobial resistance.

Improved allele-specific single-cell copy number estimation in low-coverage DNA-sequencing.

Advances in whole-genome single-cell DNA sequencing (scDNA-seq) have led to the development of numerous methods for detecting copy number aberrations (CNAs), a key driver of genetic heterogeneity in cancer. While most of these methods are limited to the inference of total copy number, some recent approaches now infer allele-specific CNAs using innovative techniques for estimating allele-frequencies in low coverage scDNA-seq data. However, these existing allele-specific methods are limited in their segmentation strategies, a crucial step in the CNA detection pipeline. We present SEACON (Single-cell Estimation of Allele-specific COpy Numbers), an allele-specific copy number profiler for scDNA-seq data. SEACON uses a Gaussian Mixture Model to identify latent copy number states and breakpoints between contiguous segments across cells, filters the segments for high-quality breakpoints using an ensemble technique, and adopts several strategies for tolerating noisy read-depth and allele frequency measurements. Using a wide array of both real and simulated datasets, we show that SEACON derives accurate copy numbers and surpasses existing approaches under numerous experimental conditions, and identify its strengths and weaknesses. SEACON is implemented in Python and is freely available open-source from https://github.com/NabaviLab/SEACON and https://doi.org/10.5281/zenodo.12727008.

Next-Generation Sequencing for Characterizing Respiratory Tract Virome and Improving Detection of Viral Pathogens in Children With Pneumonia.

Pneumonia is typically caused by a variety of pathogenic microorganisms. Traditional research often focuses on the infection of a few microorganisms, whereas metagenomic studies focus on the impact of the bacteriome and mycobiome on respiratory diseases. Reports on the virome characteristics of pediatric pneumonia remain relatively scarce. We employed de novo assembly and combined homology- and feature-based methods to characterize the respiratory virome in whole-genome DNA sequencing samples from oropharynx (OP) swabs, nasopharynx (NP) swabs, and bronchoalveolar lavage fluids (BALF) of children with pneumonia. Significant differences were observed in the alpha and beta diversity indexes, as well as in the composition of the oropharyngeal virome, between pneumonia cases and controls. We identified 1137 viral operational taxonomic units (vOTUs) with significant differences, indicating a preference of pneumonia-reduced vOTUs for infecting Prevotella, Neisseria, and Veillonella, whereas pneumonia-enriched vOTUs included polyomavirus, human adenovirus, and phages targeting Staphylococcus, Streptococcus, Granulicatella, and Actinomyces. Comparative analysis revealed higher relative abundances and prevalence rates of pneumonia-enriched OP vOTUs in NP and BALF samples compared to pneumonia-reduced vOTUs. Additionally, virome analysis identified six pediatric patients with severe human adenovirus or polyomavirus infections, five of whom might have been undetected by targeted polymerase chain reaction (PCR)-based testing. This study offers insights into pediatric pneumonia respiratory viromes, highlighting frequent transmission of potentially pathogenic viruses and demonstrating virome analysis as a valuable adjunct for pathogen detection.

Transcriptome variations in hybrids of wild emmer wheat (Triticum turgidum ssp. dicoccoides)

BackgroundWild emmer wheat is a great candidate to revitalize domesticated wheat genetic diversity. Recent years have seen intensive investigation into the evolution and domestication of wild emmer wheat, including whole-genome DNA and transcriptome sequencing. However, the impact of intraspecific hybridization on the transcriptome of wild emmer wheat has been poorly studied. In this study, we assessed changes in methylation patterns and transcriptomic variations in two accessions of wild emmer wheat collected from two marginal populations, Mt. Hermon and Mt. Amasa, and in their stable F4 hybrid.ResultsMethylation-Sensitive Amplified Polymorphism (MSAP) detected significant cytosine demethylation in F4 hybrids vs. parental lines, suggesting potential transcriptome variation. After a detailed analysis, we examined nine RNA-Seq samples, which included three biological replicates from the F4 hybrid and its parental lines. RNA-Seq databases contained approximately 200 million reads, with each library consisting of 15 to 25 million reads. There are a total of 62,490 well-annotated genes in these databases, with 6,602 genes showing differential expression between F4 hybrid and parental lines Mt. Hermon and Mt. Amasa. The differentially expressed genes were classified into four main categories based on their expression patterns. Gene ontology (GO) analysis revealed that differentially expressed genes are associated with DNA/RNA metabolism, photosynthesis, stress response, phosphorylation and developmental processes.ConclusionThis study highlights the significant transcriptomic changes resulting from intraspecific hybridization within natural plant populations, which might aid the nascent hybrid in adapting to various environmental conditions.

Diagnosis and genetic characterization of CNS metastases in lung cancer via shallow whole-genome sequencing of CSF cell-free DNA.

e14013 Background: The genetic characterization of CNS metastases in lung cancer is hindered by the limited sampling opportunities and genetic heterogeneity between intracranial and extracranial lesions. To address these challenges, this study uses cerebrospinal fluid (CSF) and blood samples, to detect and characterize CNS metastasis variants through shallow whole-genome sequencing (sWGS). Methods: From Dec. 2021 to Aug. 2023, 57 lung cancer patients were recruited, comprising 29 with leptomeningeal metastases (LMs) and 28 with only parenchymal brain metastases (PMs). A total of 66 blood and 112 CSF samples were collected for cfDNA sWGS to analyze chromosomal arm CNVs, focal amplifications (CN > 5) and SNV/InDels. Cytology was also conducted on 95 of these CSF samples. Variant differences between PMs and extracranial metastases (EMs) were analyzed using the MSK-MET database. Results: CSF cfDNA concentration was significantly lower than that in plasma (p < 0.0001), with 41.7% of samples unquantifiable, yet all samples successfully completed sWGS. The cfDNA tumor fraction in CSF was significantly higher than in paired plasma (p < 0.0001), and most arm CNVs and gene amplifications exclusively detected in CSF. Cytology, as the gold standard for LM diagnosis, had a sensitivity of 0.76. The sensitivity for LM diagnosis based on aneuploidy and genomic amplification fraction (GAF) were 0.51 and 0.80, respectively, without compromising specificity. Gains in 1p, 7p, 11q, 16p, and 17q, as well as losses in 9p and 9q, were significantly more frequent in PMs compared to EMs and further increased in the LMs (p < 0.05). Notably, losses in 1p, 4p, 5q, and 11p, significantly more frequent in PMs than in extracranial metastases, but showed a significant increase in gain frequency in LMs (p < 0.05). In the LM group, the frequency of EGFR L858R and amplification of nearly the entire 7p where the EGFR located, were significantly increased, whereas KRAS G12D frequency significantly decreased (p < 0.05). Conclusions: The characteristics of extremely low concentration but high tumor fraction of CSF cfDNA make it suitable for sWGS, enhancing LM diagnostic sensitivity without compromising specificity, and identifying molecular characteristics of CNS metastasis. These molecular features require further validation in larger prospective clinical cohorts, offering potential for personalized diagnosis and treatment of CNS metastases.

North American pitseed goosefoot (Chenopodium berlandieri) is a genetic resource to improve Andean quinoa (C. quinoa)

Pitseed goosefoot (Chenopodium berlandieri) is a free-living North American member of an allotetraploid complex that includes the Andean pseudocereal quinoa (C. quinoa). Like quinoa, pitseed goosefoot was domesticated, possibly independently, in eastern North America (subsp. jonesianum) and Mesoamerica (subsp. nuttaliae). To test the utility of C. berlandieri as a resource for quinoa breeding, we produced the whole-genome DNA sequence of PI 433,231, a huauzontle from Puebla, México. The 1.295 Gb genome was assembled into 18 pseudomolecules and annotated using RNAseq data from multiple tissues. Alignment with the v.2.0 genome of Chilean-origin C. quinoa cv. ‘QQ74’ revealed several inversions and a 4A-6B reciprocal translocation. Despite these rearrangements, some quinoa x pitseed goosefoot crosses produce highly fertile hybrids with faithful recombination, as evidenced by a high-density SNP linkage map constructed from a Bolivian quinoa ‘Real-1’ × BYU 937 (Texas coastal pitseed goosefoot) F2 population. Recombination in that cross was comparable to a ‘Real-1’ × BYU 1101 (Argentine C. hircinum) F2 population. Furthermore, SNP-based phylogenetic and population structure analyses of 90 accessions supported the hypothesis of multiple independent domestications and descent from a common 4 × ancestor, with a likely North American Center of Origin.

P07 Mutagenicity of narrowband ultraviolet B

Abstract Introduction and aims Exposure to ultraviolet (UV) radiation causes DNA mutations in skin and development of skin cancer. Despite this, UV radiation in the form of narrowband UVB is commonly used by dermatologists to treat skin diseases such as psoriasis. However, the mutagenicity of narrowband UVB in human skin is unknown. In this study, we investigated the mutation burden resulting from a course of narrowband UVB in patients with psoriasis. Methods Skin biopsies were taken from uninvolved skin of sixteen patients with psoriasis before and after a treatment course of narrowband UVB. Following microdissection, DNA was extracted from the epidermis and sequenced using nanorate sequencing (NanoSeq), which detects mutations in single molecules of DNA with an error rate of fewer than five errors per billion base pairs. Whole-genome sequencing of blood DNA was employed as germline control. Comparison of mutations in prenarrowband UVB and postnarrowband UVB skin samples allowed quantification of mutation burden and mutational signatures owing to narrowband UVB. Results There was a significant increase in the mutation burden in skin following the narrowband UVB treatment course, with UV radiation signatures SBS7a, SBS7b and DBS1 documented in both nonsun-exposed skin and frequently sun-exposed skin samples. Comparison of the magnitude of the mutation burden resulting from narrowband UVB to that in keratinocyte cancers provided insight into the mutagenicity of narrowband UVB in relation to the potential numbers of narrowband UVB courses over a lifetime that might lead to skin cancer development. Conclusions Narrowband UVB treatment for psoriasis Results in significant numbers of UV-radiation-induced mutations in human skin.

Abstract PL-01: Breast Cancer Evolution, Immune Evasion and Metastasis Driven by Chromosomal Instability

Abstract Chromosomal instability (CIN) is a poor prognostic feature with high prevalence in breast cancer and is responsible for driving Somatic Copy Number Aberrations and Intratumour Heterogeneity (ITH) within subclones during breast cancer evolution. We have observed that SCNAs are enriched in metastatic samples, including gains in chromosome 11q13.3 (encompassing CCND1) in HER2+ breast cancer. However, there have thus far been no prospective, comprehensive studies of intratumor heterogeneity in breast cancer. We will present data from TRACERx Breast/SCANDARE a prospective, multicentre study of triple-negative breast cancer (TNBC) in which multi-region biopsies have been collected from primary TNBC prior to neoadjuvant treatment, and at longitudinal time points including surgery and relapse. We find prevalent intratumor heterogeneity in somatic mutations and SCNAs in the primary tumor prior to treatment. We have leveraged the rich clinical annotation in this cohort to correlate intratumor heterogeneity scores with key clinical outcomes, including treatment response (pathological complete response to neoadjuvant chemotherapy) and survival. We find that CIN manifests as oncogenic amplification on extrachromosomal DNA (ecDNA), which plays a pivotal role in driving drug resistance and tumor evolution. Through analysis of Whole Genome Sequencing data from 2936 breast tumors from the Genomics England breast cancer cohort, we have identified focal amplifications driven by ecDNA in 46.4% of HER2+ breast cancers. EcDNA were enriched in metastatic tumors and was associated with poor clinical outcomes. In addition to oncogenic amplifications such as HER2 derived from ecDNA during cancer evolution, ecDNAs contained immunomodulatory genes associated with reduced T cell infiltration. Further Immune-modulation by CIN results from loss of heterozygosity of the HLA locus (HLA LOH) and is a prevalent subclonal event in breast cancer. CIN is further drives haploid LOH, resulting in the high prevalence of whole genome doubling and further CIN in TNBC. Tumors are heterogeneous compositions of distinct clones with different compliments of SCNAs and varying levels of fitness, hence measuring the proliferation of individual clones to predict future evolutionary outcomes is likely to be critical. We have developed SPRINTER (Single-cell Proliferation Rate Inference in Non-homogeneous Tumours through Evolutionary Routes), a novel computational method to measure proliferation rates in individual tumour clones using single-cell whole-genome DNA sequencing data. We applied SPRINTER to 42,009 triple negative breast cancer cells, demonstrating significant proliferative heterogeneity between distinct tumor clones. Importantly, we show a correlation between higher proliferation rates and increased rates of somatic variants, suggesting proliferation links to clone evolvability. Taken together, these complimentary analyses provide evidence for the importance of CIN in driving ITH, selection, metastasis and immune evasion and provide a framework to determine recurrent evolutionary patterns in breast cancer evolution. Citation Format: C. Swanton. Breast Cancer Evolution, Immune Evasion and Metastasis Driven by Chromosomal Instability [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PL-01.

Abstract 2416: Personalized minimal residual disease detection using tumor-derived structural variants in cell-free DNA

Abstract We demonstrate development and technical validation of a novel approach for analysis of plasma circulating-tumor DNA (ctDNA) for residual disease detection and monitoring that offers improvements over existing technologies. ctDNA in blood can be leveraged to monitor treatment response, detect cancer recurrence, and inform treatment decisions for cancer patients. However, accurate detection and quantification of ctDNA is technically challenging due to low concentration of plasma DNA, especially in the adjuvant setting. Most current assays rely on interrogating multiple patient-specific point mutations to achieve exquisite limits of detection but struggle with polymerase errors, sequencing artifacts and limited conversion of input DNA. To overcome these challenges, we developed an approach called Structural Variant Enrichment and Normalization (SVEN) that targets patient-specific genomic rearrangements to achieve sensitive detection and quantification of plasma ctDNA. This method leverages intrinsic features of tumor-derived structural variants (SVs) to improve enrichment and confidence of detection at low tumor fraction through multiplexed PCR and amplicon-based next generation sequencing. To evaluate the assay, we performed whole genome sequencing of DNA from two breast cancer cell lines, as well as matched FFPE tumor and buffy coat samples from 21 early-stage breast cancer patients. We identified consensus SVs, and designed multiplexed SV-specific primers for each subject. We then conducted PCR amplification of cell-free DNA followed by sequencing, amplicon identification, and quantification. Analytical validation was conducted using 284 replicates of cell line dilutions from 1% to 0.003%, and 5 to 40 ng of input. We developed multiplexed assays targeting 25 and 32 SVs across two cell lines, and 3 - 43 SVs across breast cancer patients (median 23 per patient). 91% and 42% of PCR targets were successfully validated for cell lines and FFPE samples respectively. Cell line dilutions demonstrated a sensitivity of 89% at 0.003% tumor fraction with 10 ng input or more. Tumor fractions measured using SVEN agreed with known values (R2 = 0.989). Application of validated panels to patient plasma samples and tumor/germline dilutions is ongoing. SVEN is a novel approach for tumor-guided ctDNA detection and quantification with potential relevance for residual disease detection. On-going studies are investigating the performance of this approach for ctDNA detection in patients with early and locally advanced breast cancer treated with neoadjuvant therapy. Citation Format: Bradon R. McDonald, Kirsten L. Dennison, Amanda L. Schussman, Stephanie M. McGregor, Barbara A. Pockaj, Muhammed Murtaza. Personalized minimal residual disease detection using tumor-derived structural variants in cell-free DNA [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2416.

An evolutionary view of the Fusarium core genome

Fusarium, a member of the Ascomycota fungi, encompasses several pathogenic species significant to plants and animals. Some phytopathogenic species have received special attention due to their negative economic impact on the agricultural industry around the world. Traditionally, identification and taxonomic analysis of Fusarium have relied on morphological and phenotypic features, including the fungal host, leading to taxonomic conflicts that have been solved using molecular systematic technologies. In this work, we applied a phylogenomic approach that allowed us to resolve the evolutionary history of the species complexes of the genus and present evidence that supports the F. ventricosum species complex as the most basal lineage of the genus. Additionally, we present evidence that proposes modifications to the previous hypothesis of the evolutionary history of the F. staphyleae, F. newnesense, F. nisikadoi, F. oxysporum, and F. fujikuroi species complexes. Evolutionary analysis showed that the genome GC content tends to be lower in more modern lineages, in both, the whole-genome and core-genome coding DNA sequences. In contrast, genome size gain and losses are present during the evolution of the genus. Interestingly, core genome duplication events positively correlate with genome size. Evolutionary and genome conservation analysis supports the F3 hypothesis of Fusarium as a more compact and conserved group in terms of genome conservation. By contrast, outside of the F3 hypothesis, the most basal clades only share 8.8% of its genomic sequences with the F3 clade.

Exposure to environmental toxicants is associated with gut microbiome dysbiosis, insulin resistance and obesity

Environmental toxicants (ETs) are associated with adverse health outcomes. Here we hypothesized that exposures to ETs are linked with obesity and insulin resistance partly through a dysbiotic gut microbiota and changes in the serum levels of secondary bile acids (BAs). Serum BAs, per- and polyfluoroalkyl substances (PFAS) and additional twenty-seven ETs were measured by mass spectrometry in 264 Danes (121 men and 143 women, aged 56.6 ± 7.3 years, BMI 29.7 ± 6.0 kg/m2) using a combination of targeted and suspect screening approaches. Bacterial species were identified based on whole-genome shotgun sequencing (WGS) of DNA extracted from stool samples. Personalized genome-scale metabolic models (GEMs) of gut microbial communities were developed to elucidate regulation of BA pathways. Subsequently, we compared findings from the human study with metabolic implications of exposure to perfluorooctanoic acid (PFOA) in PPARα-humanized mice. Serum levels of twelve ETs were associated with obesity and insulin resistance. High chemical exposure was associated with increased abundance of several bacterial species (spp.) of genus (Anaerotruncus, Alistipes, Bacteroides, Bifidobacterium, Clostridium, Dorea, Eubacterium, Escherichia, Prevotella, Ruminococcus, Roseburia, Subdoligranulum, and Veillonella), particularly in men. Conversely, females in the higher exposure group, showed a decrease abundance of Prevotella copri. High concentrations of ETs were correlated with increased levels of secondary BAs including lithocholic acid (LCA), and decreased levels of ursodeoxycholic acid (UDCA). In silico causal inference analyses suggested that microbiome-derived secondary BAs may act as mediators between ETs and obesity or insulin resistance. Furthermore, these findings were substantiated by the outcome of the murine exposure study. Our combined epidemiological and mechanistic studies suggest that multiple ETs may play a role in the etiology of obesity and insulin resistance. These effects may arise from disruptions in the microbial biosynthesis of secondary BAs.

Assay Validation of Cell-Free DNA Shallow Whole-Genome Sequencing to Determine Tumor Fraction in Advanced Cancers

Blood-based liquid biopsy is increasingly used in clinical care of patients with cancer, and fraction of tumor-derived DNA in circulation (tumor fraction; TFx) has demonstrated clinical validity across multiple cancer types. To determine TFx, shallow whole-genome sequencing of cell-free DNA (cfDNA) can be performed from a single blood sample, using an established computational pipeline (ichorCNA), without prior knowledge of tumor mutations, in a highly cost-effective manner. We describe assay validation of this approach to facilitate broad clinical application, including evaluation of assay sensitivity, precision, repeatability, reproducibility, pre-analytic factors, and DNA quality/quantity. Sensitivity to detect TFx of 3% (lower limit of detection) was 97.2% to 100% at 1× and 0.1× mean sequencing depth, respectively. Precision was demonstrated on distinct sequencing instruments (HiSeqX and NovaSeq) with no observable differences. The assay achieved prespecified 95% agreement of TFx across replicates of the same specimen (repeatability) and duplicate samples in different batches (reproducibility). Comparison of samples collected in EDTA and Streck tubes from single venipuncture in 23 patients demonstrated that EDTA or Streck tubes were comparable if processed within 8 hours. On the basis of a range of DNA inputs (1 to 50 ng), 20 ng cfDNA is the preferred input, with 5 ng minimum acceptable. Overall, this shallow whole-genome sequencing of cfDNA and ichorCNA approach offers sensitive, precise, and reproducible quantitation of TFx, facilitating assay application in clinical cancer care.

Understanding gut microbiome-based machine learning platforms: A review on therapeutic approaches using deep learning.

Human beings possess trillions of microbial cells in a symbiotic relationship. This relationship benefits both partners for a long time. The gut microbiota helps in many bodily functions from harvesting energy from digested food to strengthening biochemical barriers of the gut and intestine. But the changes in microbiota composition and bacteria that can enter the gastrointestinal tract can cause infection. Several approaches like culture-independent techniques such as high-throughput and meta-omics projects targeting 16S ribosomal RNA (rRNA) sequencing are popular methods to investigate the composition of the human gastrointestinal tract microbiota and taxonomically characterizing microbial communities. The microbiota conformation and diversity should be provided by whole-genome shotgun metagenomic sequencing of site-specific community DNA associating genome mapping, gene inventory, and metabolic remodelling and reformation, to ease the functional study of human microbiota. Preliminary examination of the therapeutic potency for dysbiosis-associated diseases permits investigation of pharmacokinetic-pharmacodynamic changes in microbial communities for escalation of treatment and dosage plan. Gut microbiome study is an integration of metagenomics which has influenced the field in the last two decades. And the incorporation of artificial intelligence and deep learning through "omics-based" methods and microfluidic evaluation enhanced the capability of identification of thousands of microbes.

Abstract PR010: Linking proliferation rate to the evolution of single-cell primary and metastatic tumor clones

Abstract Proliferation is a key phenotypic feature of cancer, with higher rates associated with poorer clinical outcomes. Thus far, proliferation rates have been measured using pathological or experimental techniques on bulk tumor samples. However, tumors are heterogeneous compositions of distinct clones. Measuring the proliferation of individual clones has been unfeasible to date since proliferation and clonal diversity cannot easily be measured for the same set of cells, but it is potentially important as it may allow the identification of clones that develop more aggressive phenotypes (e.g., metastatic potential or treatment resistance). We have developed SPRINTER, a novel algorithm that uses single-cell whole-genome DNA sequencing (scDNA-seq) data to enable the accurate identification of actively replicating cells in both the S and G2 phases of the cell cycle and their assignment to distinct tumor clones, thus providing a proxy to estimate clone-specific proliferation rates. To evaluate SPRINTER’s accuracy, we generated a ground truth dataset of 8,844 diploid and tetraploid cancer cells by coupling scDNA-seq with 5-Ethynyl-2-deoxyuridine (EdU) labeling, and demonstrated that SPRINTER can accurately distinguish clone proliferation rates in contrast to previous approaches. We further generated a longitudinal, primary-metastasis matched dataset of 23,001 cancer cells obtained from 5 samples from the primary tumor and 5 samples from distinct metastases from a patient with non-small cell lung cancer, allowing us to integrate analyses of proliferation and cancer evolution through the metastatic disease course. We revealed widespread heterogeneity in clone proliferation rates both between and within samples, supported by multiple orthogonal analyses including Ki-67 pathology, nuclei microscopy imaging, and patient clinical imaging, with high proliferation seen in fast-growing metastatic lesions. We demonstrated an association between clones with high proliferation and increased metastatic potential, as well as increased shedding of circulating tumor DNA. We further illustrated SPRINTER’s broad applicability on previous datasets of 42,009 breast cancer cells and 19,905 ovarian cancer cells, revealing an association between high proliferation and increased rates of different genetic variants. In conclusion, SPRINTER infers the proliferation rates of distinct tumor clones from scDNA-seq data, allowing the identification of clones with potentially aggressive phenotypes, such as metastatic potential. Citation Format: Olivia Lucas, Sophia Ward, Rija Zaidi, Abigail Bunkum, Alexander M. Frankell, David A. Moore, Mark S. Hill, Wing Kin Liu, Daniele Marinelli, Emilia L. Lim, Sonya Hessey, Cristina Naceur-Lombardelli, Andrew Rowan, Sukhveer Mann, Haoran Zhai, Michelle Dietzen, Boyue Ding, Gary Royle, Nicholas McGranahan, Mariam Jamal-Hanjani, Nnennaya Kanu, Charles Swanton, Simone Zaccaria. Linking proliferation rate to the evolution of single-cell primary and metastatic tumor clones [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr PR010.

Phylogenetics and Population Genetics of the Asian House Shrew, Suncus murinus-S. montanus Species Complex, Inferred From Whole-Genome and Mitochondrial DNA Sequences, with Special Reference to the Ryukyu Archipelago, Japan.

The house shrew (Suncus murinus-S. montanus species complex) colonized regions across southern Asia and the Indian Ocean following human activity. The house shrew is distributed on islands of the Ryukyu Archipelago, the southernmost part of Japan, but the evolutionary history of the shrew on those islands and possible associations between these populations and humans remain unknown. In this study, we conducted phylogenetic and population genetic analyses based on both nuclear and mitochondrial genome sequences of house shrews. Phylogenetic analyses based on mitochondrial cytochrome b (cytb) sequences revealed that shrews from the Ryukyu Archipelago showed strong genetic affinity to Vietnamese and southern Chinese shrews. Demographic analyses of cytb sequences indicated a rapid population expansion event affecting the haplotype group in Vietnam, southern China, and the Ryukyu Archipelago 3300-7900 years ago. Furthermore, gene flow between Ryukyu (Yonaguni Island) and Taiwan and between Ryukyu and Vietnam inferred from f4 statistics of the nuclear genomes suggested repeated immigration to Ryukyu in recent years. The present study demonstrates that the Nagasaki population has a different origin from the Ryukyu population. These findings elucidate the complex pattern of genetic admixture in house shrews and provide insights into their evolutionary history.

ENLIGHTENMENT: A Scalable Annotated Database of Genomics and NGS-Based Nucleotide Level Profiles.

The revolution in sequencing technologies has enabled human genomes to be sequenced at a very low cost and time leading to exponential growth in the availability of whole-genome sequences. However, the complete understanding of our genome and its association with cancer is a far way to go. Researchers are striving hard to detect new variants and find their association with diseases, which further gives rise to the need for aggregation of this Big Data into a common standard scalable platform. In this work, a database named Enlightenment has been implemented which makes the availability of genomic data integrated from eight public databases, and DNA sequencing profiles of H. sapiens in a single platform. Annotated results with respect to cancer specific biomarkers, pharmacogenetic biomarkers and its association with variability in drug response, and DNA profiles along with novel copy number variants are computed and stored, which are accessible through a web interface. In order to overcome the challenge of storage and processing of NGS technology-based whole-genome DNA sequences, Enlightenment has been extended and deployed to a flexible and horizontally scalable database HBase, which is distributed over a hadoop cluster, which would enable the integration of other omics data into the database for enlightening the path towards eradication of cancer.

Genomic instability analysis in DNA from Papanicolaou test provides proof-of-principle early diagnosis of high-grade serous ovarian cancer.

Late diagnosis and the lack of screening methods for early detection define high-grade serous ovarian cancer (HGSOC) as the gynecological malignancy with the highest mortality rate. In the work presented here, we investigated a retrospective and multicentric cohort of 250 archival Papanicolaou (Pap) test smears collected during routine gynecological screening. Samples were taken at different time points (from 1 month to 13.5 years before diagnosis) from 113 presymptomatic women who were subsequently diagnosed with HGSOC (pre-HGSOC) and from 77 healthy women. Genome instability was detected through low-pass whole-genome sequencing of DNA derived from Pap test samples in terms of copy number profile abnormality (CPA). CPA values of DNA extracted from Pap test samples from pre-HGSOC women were substantially higher than those in samples from healthy women. Consistently with the longitudinal analysis of clonal pathogenic TP53 mutations, this assay could detect HGSOC presence up to 9 years before diagnosis. This finding confirms the continual shedding of tumor cells from fimbriae toward the endocervical canal, suggesting a new path for the early diagnosis of HGSOC. We integrated the CPA score into the EVA (early ovarian cancer) test, the sensitivity of which was 75% (95% CI, 64.97 to 85.79), the specificity 96% (95% CI, 88.35 to 100.00), and the accuracy 81%. This proof-of-principle study indicates that the early diagnosis of HGSOC is feasible through the analysis of genomic alterations in DNA from endocervical smears.

Single-Cell Whole-Genome Sequencing after Chemotherapeutic Treatment Reveals Cell Type-Specific Mutational Burdens

Introduction The hematopoietic system is especially vulnerable to chemotherapeutic treatment-related long-term consequences, including clonal and malignant hematopoiesis. These diseases are caused by the acquisition of driver mutations in hematopoietic stem and progenitor cells (HSPCs). An increased rate of mutation accumulation, as identified in HSPCs of patients who receive chemotherapeutic treatment, can therefore result in disrupted blood production. Accordingly, childhood cancer survivors have a five-fold increased risk of secondary cancers, amongst which therapy-related myeloid neoplasms (t-MN) are one of the most prevalent. Here, we aim to increase the understanding of the origin of t-MN through the characterization of the short- and long-term mutational consequences of chemotherapy in different hematopoietic stem and progenitor cell types. Methods We studied the genome-wide mutation burden in the HSPC compartment at the time of an initial cancer diagnosis, following chemotherapeutic treatment, and upon a second cancer diagnosis. We performed whole-genome sequencing (WGS) of single HSPCs, including hematopoietic stem cells (HSCs, CD34+CD38-CD45RA-CD90+), multipotent progenitor cells (MPPs, CD34+CD38-CD45RA-CD90-), common myeloid progenitor cells (CMPs, CD34+CD38+CD45RA-), and granulocyte-monocyte progenitor cells (GMPs, CD34+CD38+CD45RA+). In order to obtain enough DNA for WGS, we performed clonal expansion of single cells or primary template-directed amplification of the DNA of one cell. Next, we normalized the mutation burden in each cell to the expected number of mutations (Osorio et al. Cell Reports 2018). In addition, we performed both whole genome and transcriptome sequencing of individual HSCs/MPPs. Results First, we investigated pediatric ten t-MN patients with a latency between the initial and second cancer diagnosis spanning 1-12 years. We applied WGS to clonally expanded HSPCs (CD34+CD38-CD45RA-) and found that the relative increase in mutation burden in HSPCs is restricted to the first five years after initial treatment. To gain more insight into the heterogeneous HSPC compartment, we subsequently investigated cell-type specific mutational loads based on immunophenotypic markers. So far, we have included three pediatric cancer patients with comparable treatment regimens and diagnoses, namely medium risk acute lymphoblastic leukemia. Here, we found that the mutation burden is lower in HSCs when compared to the progenitor cell types (Figure 1A). When comparing the mutation load in the HSCs to the linear mutation accumulation observed in HSCs and MPPs of healthy donors, we identified a fraction of cells overlapping with the expected mutation load based on the age of the patient (Figure 1B). These data suggest that HSCs are more protected against chemotherapy-induced mutagenesis than progenitor cells, although this protective effect varies between individual cells. Therefore, we also performed both whole genome and transcriptome sequencing from a single cell, to characterize the transcriptional state of HSCs/MPPs showing a relatively high or low mutation load within their respective cell type. Conclusions Our results indicate that primitive hematopoietic stem cells are more protected against chemotherapy-induced mutations than the more proliferative progenitor cells. In addition, we find that in t-MN patients with a long latency (>5 years), the mutation load in HSPCs returns to the expected baseline. Based on our data, we hypothesize that the more damaged progenitor cells may be replaced over time, fueled by the undamaged primitive stem cell pool. Thus, our results may explain why the risk of t-MN drops 5-7 years after treatment end.

Splitting the yeast centromere by recombination.

Although fusions between the centromeres of different human chromosomes have been observed cytologically in cancer cells, since the centromeres are long arrays of satellite sequences, the details of these fusions have been difficult to investigate. We developed methods of detecting recombination within the centromeres of the yeast Saccharomyces cerevisiae (intercentromere recombination). These events occur at similar rates (about 10-8/cell division) between two active or two inactive centromeres. We mapped the breakpoints of most of the recombination events to a region of 43 base pairs of uninterrupted homology between the two centromeres. By whole-genome DNA sequencing, we showed that most (>90%) of the events occur by non-reciprocal recombination (gene conversion/break-induced replication). We also found that intercentromere recombination can involve non-homologous chromosome, generating whole-arm translocations. In addition, intercentromere recombination is associated with very frequent chromosome missegregation. These observations support the conclusion that intercentromere recombination generally has negative genetic consequences.

Clonal Hematopoiesis of Indeterminate Potential (CHIP) and Incident Type 2 Diabetes Risk.

Clonal hematopoiesis of indeterminate potential (CHIP) is an aging-related accumulation of somatic mutations in hematopoietic stem cells, leading to clonal expansion. CHIP presence has been implicated in atherosclerotic coronary heart disease (CHD) and all-cause mortality, but its association with incident type 2 diabetes (T2D) is unknown. We hypothesized that CHIP is associated with elevated risk of T2D. CHIP was derived from whole-genome sequencing of blood DNA in the National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine (TOPMed) prospective cohorts. We performed analysis for 17,637 participants from six cohorts, without prior T2D, cardiovascular disease, or cancer. We evaluated baseline CHIP versus no CHIP prevalence with incident T2D, including associations with DNMT3A, TET2, ASXL1, JAK2, and TP53 variants. We estimated multivariable-adjusted hazard ratios (HRs) and 95% CIs with adjustment for age, sex, BMI, smoking, alcohol, education, self-reported race/ethnicity, and combined cohorts' estimates via fixed-effects meta-analysis. Mean (SD) age was 63.4 (11.5) years, 76% were female, and CHIP prevalence was 6.0% (n = 1,055) at baseline. T2D was diagnosed in n = 2,467 over mean follow-up of 9.8 years. Participants with CHIP had 23% (CI 1.04, 1.45) higher risk of T2D than those with no CHIP. Specifically, higher risk was for TET2 (HR 1.48; CI 1.05, 2.08) and ASXL1 (HR 1.76; CI 1.03, 2.99) mutations; DNMT3A was nonsignificant (HR 1.15; CI 0.93, 1.43). Statistical power was limited for JAK2 and TP53 analyses. CHIP was associated with higher incidence of T2D. CHIP mutations located on genes implicated in CHD and mortality were also related to T2D, suggesting shared aging-related pathology.