Single-Cell Whole-Genome Amplification and Sequencing: Methodology and Applications

Recent Innovations and Technical Advances in High-Throughput Parallel Single-Cell Whole-Genome Sequencing Methods

Single-cell whole-genome sequencing (scWGS) detects cell heterogeneity at the aspect of genomic variations, which are inheritable and play an important role in life processes such as aging and cancer progression. The recent explosive development of high-throughput single-cell sequencing methods has enabled high-performance heterogeneity detection through a vast number of novel strategies. Despite the limitation on total cost, technical advances in high-throughput single-cell whole-genome sequencing methods are made for higher genome coverage, parallel throughput, and level of integration. This review highlights the technical advancements in high-throughput scWGS in the aspects of strategies design, data efficiency, parallel handling platforms, and their applications on human genome. The experimental innovations, remaining challenges, and perspectives are summarized and discussed.

Applications of single-cell multi-omics in liver cancer

Primary liver cancer, more specifically hepatocellular carcinoma (HCC), remains a significant global health problem associated with increasing incidence and mortality. Clinical, biological, and molecular heterogeneity are well-known hallmarks of cancer and HCC is considered one of the most heterogeneous tumour types, displaying substantial inter-patient, intertumoural and intratumoural variability. This heterogeneity plays a pivotal role in hepatocarcinogenesis, metastasis, relapse and drug response or resistance. Unimodal single-cell sequencing techniques have already revolutionised our understanding of the different layers of molecular hierarchy in the tumour microenvironment of HCC. By highlighting the cellular heterogeneity and the intricate interactions among cancer, immune and stromal cells before and during treatment, these techniques have contributed to a deeper comprehension of tumour clonality, hematogenous spreading and the mechanisms of action of immune checkpoint inhibitors. However, major questions remain to be elucidated, with the identification of biomarkers predicting response or resistance to immunotherapy-based regimens representing an important unmet clinical need. Although the application of single-cell multi-omics in liver cancer research has been limited thus far, a revolution of individualised care for patients with HCC will only be possible by integrating various unimodal methods into multi-omics methodologies at the single-cell resolution. In this review, we will highlight the different established single-cell sequencing techniques and explore their biological and clinical impact on liver cancer research, while casting a glance at the future role of multi-omics in this dynamic and rapidly evolving field.

Single-Cell RNA Sequencing: Technological Progress and Biomedical Application in Cancer Research

Single-cell RNA-seq (scRNA-seq) is a revolutionary technology that allows for the genomic investigation of individual cells in a population, allowing for the discovery of unusual cells associated with cancer and metastasis. ScRNA-seq has been used to discover different types of cancers with poor prognosis and medication resistance such as lung cancer, breast cancer, ovarian cancer, and gastric cancer. Besides, scRNA-seq is a promising method that helps us comprehend the biological features and dynamics of cell development, as well as other disorders. This review gives a concise summary of current scRNA-seq technology. We also explain the main technological steps involved in implementing the technology. We highlight the present applications of scRNA-seq in cancer research, including tumor heterogeneity analysis in lung cancer, breast cancer, and ovarian cancer. In addition, this review elucidates potential applications of scRNA-seq in lineage tracing, personalized medicine, illness prediction, and disease diagnosis, which reveals that scRNA-seq facilitates these events by producing genetic variations on the single-cell level.

Deciphering brain cellular and behavioral mechanisms: Insights from single-cell and spatial RNA sequencing

The brain is a complex computing system composed of a multitude of interacting neurons. The computational outputs of this system determine the behavior and perception of every individual. Each brain cell expresses thousands of genes that dictate the cell's function and physiological properties. Therefore, deciphering the molecular expression of each cell is of great significance for understanding its characteristics and role in brain function. Additionally, the positional information of each cell can provide crucial insights into their involvement in local brain circuits. In this review, we briefly overview the principles of single-cell RNA sequencing and spatial transcriptomics, the potential issues and challenges in their data processing, and their applications in brain research. We further outline several promising directions in neuroscience that could be integrated with single-cell RNA sequencing, including neurodevelopment, the identification of novel brain microstructures, cognition and behavior, neuronal cell positioning, molecules and cells related to advanced brain functions, sleep-wake cycles/circadian rhythms, and computational modeling of brain function. We believe that the deep integration of these directions with single-cell and spatial RNA sequencing can contribute significantly to understanding the roles of individual cells or cell types in these specific functions, thereby making important contributions to addressing critical questions in those fields. This article is categorized under: RNA Evolution and Genomics > Computational Analyses of RNA RNA in Disease and Development > RNA in Development RNA in Disease and Development > RNA in Disease.

Advances in single-cell long-read sequencing technologies

With an increase in accuracy and throughput of long-read sequencing technologies, they are rapidly being assimilated into the single-cell sequencing pipelines. For transcriptome sequencing, these techniques provide RNA isoform-level information in addition to the gene expression profiles. Long-read sequencing technologies not only help in uncovering complex patterns of cell-type specific splicing, but also offer unprecedented insights into the origin of cellular complexity and thus potentially new avenues for drug development. Additionally, single-cell long-read DNA sequencing enables high-quality assemblies, structural variant detection, haplotype phasing, resolving high-complexity regions, and characterization of epigenetic modifications. Given that significant progress has primarily occurred in single-cell RNA isoform sequencing (scRiso-seq), this review will delve into these advancements in depth and highlight the practical considerations and operational challenges, particularly pertaining to downstream analysis. We also aim to offer a concise introduction to complementary technologies for single-cell sequencing of the genome, epigenome and epitranscriptome. We conclude by identifying certain key areas of innovation that may drive these technologies further and foster more widespread application in biomedical science.

Spatiotemporal multi-omics: exploring molecular landscapes in aging and regenerative medicine

Aging and regeneration represent complex biological phenomena that have long captivated the scientific community. To fully comprehend these processes, it is essential to investigate molecular dynamics through a lens that encompasses both spatial and temporal dimensions. Conventional omics methodologies, such as genomics and transcriptomics, have been instrumental in identifying critical molecular facets of aging and regeneration. However, these methods are somewhat limited, constrained by their spatial resolution and their lack of capacity to dynamically represent tissue alterations. The advent of emerging spatiotemporal multi-omics approaches, encompassing transcriptomics, proteomics, metabolomics, and epigenomics, furnishes comprehensive insights into these intricate molecular dynamics. These sophisticated techniques facilitate accurate delineation of molecular patterns across an array of cells, tissues, and organs, thereby offering an in-depth understanding of the fundamental mechanisms at play. This review meticulously examines the significance of spatiotemporal multi-omics in the realms of aging and regeneration research. It underscores how these methodologies augment our comprehension of molecular dynamics, cellular interactions, and signaling pathways. Initially, the review delineates the foundational principles underpinning these methods, followed by an evaluation of their recent applications within the field. The review ultimately concludes by addressing the prevailing challenges and projecting future advancements in the field. Indubitably, spatiotemporal multi-omics are instrumental in deciphering the complexities inherent in aging and regeneration, thus charting a course toward potential therapeutic innovations.

Comprehensive profiling of L1 retrotransposons in mouse

L1 elements are retrotransposons currently active in mammals. Although L1s are typically silenced in most normal tissues, elevated L1 expression is associated with a variety of conditions, including cancer, aging, infertility and neurological disease. These associations have raised interest in the mapping of human endogenous de novo L1 insertions, and a variety of methods have been developed for this purpose. Adapting these methods to mouse genomes would allow us to monitor endogenous in vivo L1 activity in controlled, experimental conditions using mouse disease models. Here, we use a modified version of transposon insertion profiling, called nanoTIPseq, to selectively enrich young mouse L1s. By linking this amplification step with nanopore sequencing, we identified >95% annotated L1s from C57BL/6 genomic DNA using only 200 000 sequencing reads. In the process, we discovered 82 unannotated L1 insertions from a single C57BL/6 genome. Most of these unannotated L1s were near repetitive sequence and were not found with short-read TIPseq. We used nanoTIPseq on individual mouse breast cancer cells and were able to identify the annotated and unannotated L1s, as well as new insertions specific to individual cells, providing proof of principle for using nanoTIPseq to interrogate retrotransposition activity at the single-cell level in vivo.

Next-Generation Sequencing and Emerging Technologies

Genetic sequencing technologies are evolving at a rapid pace with major implications for research and clinical practice. In this review, the authors provide an updated overview of next-generation sequencing (NGS) and emerging methodologies. NGS has tremendously improved sequencing output while being more time and cost-efficient in comparison to Sanger sequencing. The authors describe short-read sequencing approaches, such as sequencing by synthesis, ion semiconductor sequencing, and nanoball sequencing. Third-generation long-read sequencing now promises to overcome many of the limitations of short-read sequencing, such as the ability to reliably resolve repeat sequences and large genomic rearrangements. By combining complementary methods with massively parallel DNA sequencing, a greater insight into the biological context of disease mechanisms is now possible. Emerging methodologies, such as advances in nanopore technology, in situ nucleic acid sequencing, and microscopy-based sequencing, will continue the rapid evolution of this area. These new technologies hold many potential applications for hematological disorders, with the promise of precision and personalized medical care in the future.

Beyond single cells: microfluidics empowering multiomics analysis

Single-cell multiomics technologies empower simultaneous measurement of multiple types of molecules within individual cells, providing a more profound comprehension compared with the analysis of discrete molecular layers from different cells. Microfluidic technology, on the other hand, has emerged as a pivotal facilitator for high-throughput single-cell analysis, offering precise control and manipulation of individual cells. The primary focus of this review encompasses an appraisal of cutting-edge microfluidic platforms employed in the realm of single-cell multiomics analysis. Furthermore, it discusses technological advancements in various single-cell omics such as genomics, transcriptomics, epigenomics, and proteomics, with their perspective applications. Finally, it provides future prospects of these integrated single-cell multiomics methodologies, shedding light on the possibilities for future biological research.

Mapping crossover events of mouse meiotic recombination by restriction fragment ligation-based Refresh-seq

Single-cell whole-genome sequencing methods have undergone great improvements over the past decade. However, allele dropout, which means the inability to detect both alleles simultaneously in an individual diploid cell, largely restricts the application of these methods particularly for medical applications. Here, we develop a new single-cell whole-genome sequencing method based on third-generation sequencing (TGS) platform named Refresh-seq (restriction fragment ligation-based genome amplification and TGS). It is based on restriction endonuclease cutting and ligation strategy in which two alleles in an individual cell can be cut into equal fragments and tend to be amplified simultaneously. As a new single-cell long-read genome sequencing method, Refresh-seq features much lower allele dropout rate compared with SMOOTH-seq. Furthermore, we apply Refresh-seq to 688 sperm cells and 272 female haploid cells (secondary polar bodies and parthenogenetic oocytes) from F1 hybrid mice. We acquire high-resolution genetic map of mouse meiosis recombination at low sequencing depth and reveal the sexual dimorphism in meiotic crossovers. We also phase the structure variations (deletions and insertions) in sperm cells and female haploid cells with high precision. Refresh-seq shows great performance in screening aneuploid sperm cells and oocytes due to the low allele dropout rate and has great potential for medical applications such as preimplantation genetic diagnosis.

Extended application of PGT-M strategies for small pathogenic CNVs

PURPOSE

The preimplantation genetic testing for aneuploidy (PGT-A) platform is not currently available for small copy-number variants (CNVs), especially those < 1 Mb. Through strategies used in PGT for monogenic disease (PGT-M), this study intended to perform PGT for families with small pathogenic CNVs.

METHODS

Couples who carried small pathogenic CNVs and underwent PGT at the Reproductive and Genetic Hospital of CITIC-Xiangya (Hunan, China) between November 2019 and April 2023 were included in this study. Haplotype analysis was performed through two platforms (targeted sequencing and whole-genome arrays) to identify the unaffected embryos, which were subjected to transplantation. Prenatal diagnosis using amniotic fluid was performed during 18-20 weeks of pregnancy.

RESULTS

PGT was successfully performed for 20 small CNVs (15 microdeletions and 5 microduplications) in 20 families. These CNVs distributed on chromosomes 1, 2, 6, 7, 13, 15, 16, and X with sizes ranging from 57 to 2120 kb. Three haplotyping-based PGT-M strategies were applied. A total of 89 embryos were identified in 25 PGT cycles for the 20 families. The diagnostic yield was 98.9% (88/89). Nineteen transfers were performed for 17 women, resulting in a 78.9% (15/19) clinical pregnancy rate after each transplantation. Of the nine women who had healthy babies, eight accepted prenatal diagnosis and the results showed no related pathogenic CNVs.

CONCLUSION

Our results show that the extended haplotyping-based PGT-M strategy application for small pathogenic CNVs compensated for the insufficient resolution of PGT-A. These three PGT-M strategies could be applied to couples with small pathogenic CNVs.

The first clinical validation of whole-genome screening on standard trophectoderm biopsies of preimplantation embryos

Objective

To validate the performance of our laboratory-developed whole-genome screening assay within clinical preimplantation genetic testing environments.

Design

Perform a laboratory-developed whole-genome assay on both cell lines and trophectoderm biopsies, subsequently employing the next-generation sequencing procedure to reach a sequencing depth of 30X. Adhere to the Genome Analysis Toolkit best practices for accuracy, sensitivity, specificity, and precision calculations by comparing samples with references. Our assay was then applied to cell lines and biopsies harboring known pathogenic variants, aiming to ascertain these changes solely from the next-generation sequencing data, independent of parental genome information.

Settings

Clinical laboratory.

Patients

Coriell cell lines and research embryos with known chromosomal or genetic variants. Research trophectoderm biopsies from a couple that are heterozygous carriers for distinct variants in the same autosomal recessive gene (HOGA1).

Intervention

Not applicable.

Main Outcome Measures

Accuracy, sensitivity, specificity, and precision were assessed by comparing the samples to their references. For samples with known variants, we calculated our sensitivity to detecting established variants. For the research embryos, noncarrier, carrier, and compound heterozygous states of inherited HOGA1 variants were distinguished independently of parental samples.

Results

Amplification of DNA from cell lines and embryos yielded success rates exceeding 99.9% and 98.2%, respectively, although maintaining an accuracy of >99.9% for aneuploidy assessment. The accuracy (99.99%), specificity (99.99%), sensitivity (98.0%), and precision (98.1%) of amplified genome in the bottle (reference NA12878) and embryo biopsies were comparable to results on genomic DNA, including mitochondrial heteroplasmy. Using our assay, we achieved >99.99% sensitivity when examining samples with known chromosomal and genetic variants. This encompassed pathogenic CFTR, BRCA1, and other variants, along with uniparental isodisomies and microdeletions such as DiGeorge syndrome. Our research study identified noncarrier, carrier, and compound heterozygous states within trophectoderm biopsies while simultaneously screening for 1,300 other severe monogenic diseases.

Conclusion

To our knowledge, this is the first clinical validation of whole-genome embryo screening. In this study, we demonstrated high accuracy for aneuploidy calls (>99.9%) and genetic variants (99.99%), even in the absence of parental genomes. This assay demonstrates advancements in genomic screening and an extended scope for testing capabilities in the realm of preimplantation genetic testing.

Single-cell low-pass whole genome sequencing accurately detects circulating tumor cells for liquid biopsy-based multi-cancer diagnosis

Accurate detection of circulating tumor cells (CTCs) in blood and non-blood body fluids enables generation of deterministic cancer diagnosis and represent a less invasive and safer liquid biopsy approach. Although genomic alternations have been widely used in circulating tumor DNA (ctDNA) analysis, studies on cell-based genomic alternations profiling for CTC detection are rare due to major technical limitations in single-cell whole genome sequencing (WGS) including low throughput, low accuracy and high cost. We report a single-cell low-pass WGS-based protocol (scMet-Seq) for sensitive and accurate CTC detection by combining a metabolic function-associated marker Hexokinase 2 (HK2) and a Tn5 transposome-based WGS method with improved cell fixation strategy. To explore the clinical use, scMet-Seq has been investigated with blood and non-blood body fluids in diagnosing metastatic diseases, including ascites-based diagnosis of malignant ascites (MA) and blood-based diagnosis of metastatic small-cell lung cancer (SCLC). ScMet-Seq shows high diagnostic sensitivity (MA: 79% in >10 cancer types; metastatic SCLC: 90%) and ~100% of diagnostic specificity and positive predictive value, superior to clinical cytology that exhibits diagnostic sensitivity of 52% in MA diagnosis and could not generate blood-based diagnosis. ScMet-Seq represents a liquid biopsy approach for deterministic cancer diagnosis in different types of cancers and body fluids.

Nanopore-based DNA long-read sequencing analysis of the aged human brain

Aging disrupts cellular processes such as DNA repair and epigenetic control, leading to a gradual buildup of genomic alterations that can have detrimental effects in post-mitotic cells. Genomic alterations in regions of the genome that are rich in repetitive sequences, often termed "dark loci," are difficult to resolve using traditional sequencing approaches. New long-read technologies offer promising avenues for exploration of previously inaccessible regions of the genome. Using nanopore-based long-read whole-genome sequencing of DNA extracted from aged 18 human brains, we identify previously unreported structural variants and methylation patterns within repetitive DNA, focusing on transposable elements ("jumping genes") as crucial sources of variation, particularly in dark loci. Our analyses reveal potential somatic insertion variants and provides DNA methylation frequencies for many retrotransposon families. We further demonstrate the utility of this technology for the study of these challenging genomic regions in brains affected by Alzheimer's disease and identify significant differences in DNA methylation in pathologically normal brains versus those affected by Alzheimer's disease. Highlighting the power of this approach, we discover specific polymorphic retrotransposons with altered DNA methylation patterns. These retrotransposon loci have the potential to contribute to pathology, warranting further investigation in Alzheimer's disease research. Taken together, our study provides the first long-read DNA sequencing-based analysis of retrotransposon sequences, structural variants, and DNA methylation in the aging brain affected with Alzheimer's disease neuropathology.

Analyzing somatic mutations by single-cell whole-genome sequencing

Somatic mutations are the cause of cancer and have been implicated in other, noncancerous diseases and aging. While clonally expanded mutations can be studied by deep sequencing of bulk DNA, very few somatic mutations expand clonally, and most are unique to each cell. We describe a detailed protocol for single-cell whole-genome sequencing to discover and analyze somatic mutations in tissues and organs. The protocol comprises single-cell multiple displacement amplification (SCMDA), which ensures efficiency and high fidelity in amplification, and the SCcaller software tool to call single-nucleotide variations and small insertions and deletions from the sequencing data by filtering out amplification artifacts. With SCMDA and SCcaller at its core, this protocol describes a complete procedure for the comprehensive analysis of somatic mutations in a single cell, covering (1) single-cell or nucleus isolation, (2) single-cell or nucleus whole-genome amplification, (3) library preparation and sequencing, and (4) computational analyses, including alignment, variant calling, and mutation burden estimation. Methods are also provided for mutation annotation, hotspot discovery and signature analysis. The protocol takes 12-15 h from single-cell isolation to library preparation and 3-7 d of data processing. Compared with other single-cell amplification methods or single-molecular sequencing, it provides high genomic coverage, high accuracy in single-nucleotide variation and small insertions and deletion calling from the same single-cell genome, and fewer processing steps. SCMDA and SCcaller require basic experience in molecular biology and bioinformatics. The protocol can be utilized for studying mutagenesis and genome mosaicism in normal and diseased human and animal tissues under various conditions.

Preimplantation genetic testing in couples with balanced chromosome rearrangement: a four-year period real world retrospective cohort study

BACKGROUND

Couples with balanced chromosome rearrangement (BCR) are at high risk of recurrent miscarriages or birth defects due to chromosomally abnormal embryos. This study aimed to provide real-world evidence of the euploidy rate of blastocysts from couples with BCR using preimplantation genetic testing (PGT) and to guide pretesting genetic counselling.

METHODS

A continuous four-year PGT data from couples with BCR were retrospectively analyzed. Biopsied trophectoderm cells were amplified using whole genome amplification, and next-generation sequencing was performed to detect the chromosomal numerical and segmental aberrations. Clinical data and molecular genetic testing results were analyzed and compared among the subgroups.

RESULTS

A total of 1571 PGT cycles with 5942 blastocysts were performed chromosomal numerical and segmental aberrations detection during the four years. Of them, 1034 PGT cycles with 4129 blastocysts for BCR couples were included; 68.96% (713/1034) PGT cycles had transferable euploid embryos. The total euploidy rate of blastocysts in couples carrying the BCR was 35.29% (1457/4129). Couples with complex BCR had euploid blastocyst rates similar to those of couples with non-complex BCR (46.15% vs. 35.18%, P > 0.05). Chromosome inversion had the highest chance of obtaining a euploid blastocyst (57.27%), followed by Robertsonian translocation (RobT) (46.06%), and the lowest in reciprocal translocation (RecT) (30.11%) (P < 0.05). Couples with males carrying RobT had higher rates of euploid embryo both in each PGT cycles and total blastocysts than female RobT carriers did, despite the female age in male RobT is significant older than those with female RobT (P < 0.05). The proportions of non-carrier embryos were 52.78% (95/180) and 47.06% (40/85) in euploid blastocysts from couples with RecT and RobT, respectively (P > 0.05). RecT had the highest proportion of blastocysts with translocated chromosome-associated abnormalities (74.23%, 1527/2057), followed by RobT (54.60%, 273/500) and inversion (30.85%, 29/94) (P < 0.05).

CONCLUSIONS

In couples carrying BCR, the total euploidy rate of blastocysts was 35.29%, with the highest in inversion, followed by RobT and RecT. Even in couples carrying complex BCR, the probability of having a transferable blastocyst was 46.15%. Among the euploid blastocysts, the non-carrier ratios in RecT and RobT were 52.78% and 47.06%, respectively. RecT had the highest proportion of blastocysts with translocated chromosome-associated abnormalities.

Novel Insights into the Initiation, Evolution, and Progression of Multiple Myeloma by Multi-Omics Investigation

The evolutionary history of multiple myeloma (MM) includes malignant transformation, followed by progression to pre-malignant stages and overt malignancy, ultimately leading to more aggressive and resistant forms. Over the past decade, large effort has been made to identify the potential therapeutic targets in MM. However, MM remains largely incurable. Most patients experience multiple relapses and inevitably become refractory to treatment. Tumor-initiating cell populations are the postulated population, leading to the recurrent relapses in many hematological malignancies. Clonal evolution of tumor cells in MM has been identified along with the disease progression. As a consequence of different responses to the treatment of heterogeneous MM cell clones, the more aggressive populations survive and evolve. In addition, the tumor microenvironment is a complex ecosystem which plays multifaceted roles in supporting tumor cell evolution. Emerging multi-omics research at single-cell resolution permits an integrative and comprehensive profiling of the tumor cells and microenvironment, deepening the understanding of biological features of MM. In this review, we intend to discuss the novel insights into tumor cell initiation, clonal evolution, drug resistance, and tumor microenvironment in MM, as revealed by emerging multi-omics investigations. These data suggest a promising strategy to unravel the pivotal mechanisms of MM progression and enable the improvement in treatment, both holistically and precisely.

OneGene PGT: comprehensive preimplantation genetic testing method utilizing next-generation sequencing

PURPOSE

Preimplantation genetic testing for monogenic disorders (PGT-M) allows early diagnosis in embryos conceived in vitro. PGT-M helps to prevent known genetic disorders in affected families and ensures that pathogenic variants in the male or female partner are not passed on to offspring. The trend in genetic testing of embryos is to provide a comprehensive platform that enables robust and reliable testing for the causal pathogenic variant(s), as well as chromosomal abnormalities that commonly occur in embryos. In this study, we describe PGT protocol that allows direct mutation testing, haplotyping, and aneuploidy screening.

METHODS

Described PGT protocol called OneGene PGT allows direct mutation testing, haplotyping, and aneuploidy screening using next-generation sequencing (NGS). Whole genome amplification product is combined with multiplex PCR used for SNP enrichment. Dedicated bioinformatic tool enables mapping, genotype calling, and haplotyping of informative SNP markers. A commercial software was used for aneuploidy calling.

RESULTS

OneGenePGT has been implemented for seven of the most common monogenic disorders, representing approximately 30% of all PGT-M indications at our IVF centre. The technique has been thoroughly validated, focusing on direct pathogenic variant testing, haplotype identification, and chromosome abnormality detection. Validation results show full concordance with Sanger sequencing and karyomapping, which were used as reference methods.

CONCLUSION

OneGene PGT is a comprehensive, robust, and cost-effective method that can be established for any gene of interest. The technique is particularly suitable for common monogenic diseases, which can be performed based on a universal laboratory protocol without the need for set-up or pre-testing.

Single-Cell Sequencing Technology and Its Application in the Study of Central Nervous System Diseases

The mammalian central nervous system consists of a large number of cells, which contain not only different types of neurons, but also a large number of glial cells, such as astrocytes, oligodendrocytes, and microglia. These cells are capable of performing highly refined electrophysiological activities and providing the brain with functions such as nutritional support, information transmission and pathogen defense. The diversity of cell types and individual differences between cells have brought inspiration to the study of the mechanism of central nervous system diseases. In order to explore the role of different cells, a new technology, single-cell sequencing technology has emerged to perform specific analysis of high-throughput cell populations, and has been continuously developed. Single-cell sequencing technology can accurately analyze single-cell expression in mixed-cell populations and collect cells from different spatial locations, time stages and types. By using single-cell sequencing technology to compare gene expression profiles of normal and diseased cells, it is possible to discover cell subsets associated with specific diseases and their associated genes. Therefore, scientists can understand the development process, related functions and disease state of the nervous system from an unprecedented depth. In conclusion, single-cell sequencing technology provides a powerful technology for the discovery of novel therapeutic targets for central nervous system diseases.

Exploration of a Novel Noninvasive Prenatal Testing Approach for Monogenic Disorders Based on Fetal Nucleated Red Blood Cells

BACKGROUND

Due to technical issues related to cell-specific capture methods, amplification, and sequencing, noninvasive prenatal testing (NIPT) based on fetal nucleated red blood cells (fNRBCs) has rarely been used for the detection of monogenic disorders.

METHODS

Maternal peripheral blood was collected from 11 families with hereditary hearing loss. After density gradient centrifugation and cellular immunostaining for multiple biomarkers, candidate individual fetal cells were harvested by micromanipulation and amplified by whole-genome amplification (WGA). Whole-exome sequencing/whole-genome sequencing (WGS) and Sanger sequencing were performed on the identified fNRBCs to determine the fetal genotype. The impact of single-cell and pooled WGA products on the sequencing quality and results was compared. A combined analysis strategy, encompassing whole-exome sequencing/WGS, haplotype analysis, and Sanger sequencing, was used to enhance the NIPT results.

RESULTS

fNRBCs were harvested and identified in 81.8% (9/11) of families. The results of cell-based-NIPT (cb-NIPT) were consistent with those of invasive prenatal diagnosis in 8 families; the coincidence rate was 88.9% (8/9). The combined analysis strategy improved the success of cb-NIPT. The overall performance of pooled WGA products was better than that of individual cells. Due to a lack of alternative fetal cells or sufficient sequencing data, cb-NIPT failed in 3 families.

CONCLUSIONS

We developed a novel fNRBC-based NIPT method for monogenic disorders. By combining multiple analysis strategies and multiple fetal cell WGA products, the problem of insufficient genome information in a single cell was remedied. Our method has promising prospects in the field of NIPT for the detection of monogenic disorders.

Application of the PGT-M strategy using single sperm and/or affected embryos as probands for linkage analysis in males with hereditary tumor syndromes without family history

Hereditary tumor syndromes have garnered substantial attention due to their adverse effects on both the physical and psychological health of patients, as well as the elevated risk of transmission to subsequent generations. This has prompted a growing interest in exploring preimplantation genetic testing (PGT) as a treatment option to mitigate and eliminate these impacts. Several studies have demonstrated that de novo variants have become a great cause of many hereditary tumor syndromes, which introduce certain difficulties to PGT. In the absence of adequate genetic linkage information (parents and offspring), haplotype construction seems unrealizable. In the study, researchers used single sperm or affected embryos as proband to perform single-nucleotide polymorphism linkage analysis for cases with de novo variants. For complicated variants, the strategy that sperm combined with embryo detection will increase accuracy while avoiding the limitations and potential failures of using a single detection material. The study recruited 11 couples with male de novo carriers, including 3 tumor types and 4 genes. To date, 4 couples have been clinically confirmed as pregnant and three healthy babies have been born. The results of amniocentesis or umbilical cord blood verification were consistent with the results of PGT-M. The study aims to introduce the application of the PGT-M strategy in hereditary tumor syndromes.

Chinese experts' consensus guideline on preimplantation genetic testing of monogenic disorders

Recent developments in molecular biological technologies and genetic diagnostic methods, accompanying with updates of relevant terminologies, have enabled the improvements of new strategies of preimplantation genetic testing for monogenic (single gene) disorders (PGT-M) to prevent the transmission of inherited diseases. However, there has been much in the way of published consensus on PGT-M. To properly regulate the application of PGT-M, Chinese experts in reproductive medicine and genetics have jointly developed this consensus statement. The consensus includes indications for patient selection, genetic and reproductive counseling, informed consent, diagnostic strategies, report generation, interpretation of results and patient follow-ups. This consensus statement serves to assist in establishment of evidence-based clinical and laboratory practices for PGT-M.

Preimplantation Genetic Testing for Genetic Diseases: Limits and Review of Current Literature

Preimplantation genetic testing (PGT) has emerged as a revolutionary technique in the field of reproductive medicine, allowing for the selection and transfer of healthy embryos, thus reducing the risk of transmitting genetic diseases. However, despite remarkable advancements, the implementation of PGT faces a series of limitations and challenges that require careful consideration. This review aims to foster a comprehensive reflection on the constraints of preimplantation genetic diagnosis, encouraging a broader discussion about its utility and implications. The objective is to inform and guide medical professionals, patients, and society overall in the conscious and responsible adoption of this innovative technology, taking into account its potential benefits and the ethical and practical challenges that it presents.

Comprehensive profiling of L1 retrotransposons in mouse

L1 elements are retrotransposons currently active in mammals. Although L1s are typically silenced in most normal tissues, elevated L1 expression is associated with a variety of conditions, including cancer, aging, infertility, and neurological disease. These associations have raised interest in the mapping of human endogenous de novo L1 insertions, and a variety of methods have been developed for this purpose. Adapting these methods to mouse genomes would allow us to monitor endogenous in vivo L1 activity in controlled, experimental conditions using mouse disease models. Here we use a modified version of transposon insertion profiling, called nanoTIPseq, to selectively enrich young mouse L1s. By linking this amplification step with nanopore sequencing, we identified >95% annotated L1s from C57BL/6 genomic DNA using only 200,000 sequencing reads. In the process, we discovered 82 unannotated L1 insertions from a single C57BL/6 genome. Most of these unannotated L1s were near repetitive sequence and were not found with short-read TIPseq. We used nanoTIPseq on individual mouse breast cancer cells and were able to identify the annotated and unannotated L1s, as well as new insertions specific to individual cells, providing proof of principle for using nanoTIPseq to interrogate retrotransposition activity at the single cell level in vivo .

Flow Sorting, Whole Genome Amplification and Next-Generation Sequencing as Combined Tools to Study Heterogeneous Acute Lymphoblastic Leukemia

Next-generation sequencing (NGS) methods have been introduced for immunoglobulin (IG)/T-cell receptor (TR) gene rearrangement analysis in acute lymphoblastic leukemia (ALL) and lymphoma (LBL). These methods likely constitute faster and more sensitive approaches to analyze heterogenous cases of ALL/LBL, yet it is not known whether gene rearrangements constituting low percentages of the total sequence reads represent minor subpopulations of malignant cells or background IG/TR gene rearrangements in normal B-and T-cells. In a comparison of eight cases of B-cell precursor ALL (BCP-ALL) using both the EuroClonality NGS method and the IdentiClone multiplex-PCR/gene-scanning method, the NGS method identified between 29% and 139% more markers than the gene-scanning method, depending on whether the NGS data analysis used a threshold of 5% or 1%, respectively. As an alternative to using low thresholds, we show that IG/TR gene rearrangements in subpopulations of cancer cells can be discriminated from background IG/TR gene rearrangements in normal B-and T-cells through a combination of flow cytometry cell sorting and multiple displacement amplification (MDA)-based whole genome amplification (WGA) prior to the NGS. Using this approach to investigate the clonal evolution in a BCP-ALL patient with double relapse, clonal TR rearrangements were found in sorted leukemic cells at the time of second relapse that could be identified at the time of diagnosis, below 1% of the total sequence reads. These data emphasize that caution should be exerted when interpreting rare sequences in NGS experiments and show the advantage of employing the flow sorting of malignant cell populations in NGS clonality assessments.

Identification of a novel family B DNA polymerase from Enterococcus phage IME199 and its overproduction in Escherichia coli BL21(DE3)

BACKGROUND

Identification and characterization of novel, faithful and processive DNA polymerases is a driving force in the development of DNA amplification methods. Purification of proteins from natural phages is often time-consuming, cumbersome and low yielding. Escherichia coli is a host bacterium widely used for the production of recombinant proteins, is the cell factory of choice for in vitro studies of phage protein function.

RESULTS

We expressed the gene encoding Enterococcus faecium phage IME199 DNA polymerase (IME199 DNAP) in Escherichia coli BL21(DE3), and characterized protein function. IME199 DNAP has 3'-5' exonuclease activity, but does not have 5'-3' exonuclease activity. In addition, IME199 DNAP has dNTP-dependent 5'-3' polymerase activity and can amplify DNA at 15-35 °C and a pH range of 5.5-9.5. The amino acid residues Asp30, Glu32, Asp112 and Asp251 are the 3'-5' exonuclease active sites of IME199 DNAP, while residues Asp596 and Tyr639 are essential for DNA synthesis by IME199 DNAP. More importantly, the IME199 DNAP has strand displacement and processive synthesis capabilities, and can perform rolling circle amplification and multiple displacement amplification with very low error rates (approximately 3.67 × 10-6).

CONCLUSIONS

A novel family B DNA polymerase was successfully overproduced in Escherichia coli BL21(DE3). Based on the characterized properties, IME199 DNAP is expected to be developed as a high-fidelity polymerase for DNA amplification at room temperature.

Single-cell sequencing technology applied to epigenetics for the study of tumor heterogeneity

BACKGROUND

Previous studies have traditionally attributed the initiation of cancer cells to genetic mutations, considering them as the fundamental drivers of carcinogenesis. However, recent research has shed light on the crucial role of epigenomic alterations in various cell types present within the tumor microenvironment, suggesting their potential contribution to tumor formation and progression. Despite these significant findings, the progress in understanding the epigenetic mechanisms regulating tumor heterogeneity has been impeded over the past few years due to the lack of appropriate technical tools and methodologies.

RESULTS

The emergence of single-cell sequencing has enhanced our understanding of the epigenetic mechanisms governing tumor heterogeneity by revealing the distinct epigenetic layers of individual cells (chromatin accessibility, DNA/RNA methylation, histone modifications, nucleosome localization) and the diverse omics (transcriptomics, genomics, multi-omics) at the single-cell level. These technologies provide us with new insights into the molecular basis of intratumoral heterogeneity and help uncover key molecular events and driving mechanisms in tumor development.

CONCLUSION

This paper provides a comprehensive review of the emerging analytical and experimental approaches of single-cell sequencing in various omics, focusing specifically on epigenomics. These approaches have the potential to capture and integrate multiple dimensions of individual cancer cells, thereby revealing tumor heterogeneity and epigenetic features. Additionally, this paper outlines the future trends of these technologies and their current technical limitations.

Exploration of whole genome amplification generated chimeric sequences in long-read sequencing data

MOTIVATION

Multiple displacement amplification (MDA) has become the most commonly used method of whole genome amplification, generating a vast amount of DNA with higher molecular weight and greater genome coverage. Coupling with long-read sequencing, it is possible to sequence the amplicons of over 20 kb in length. However, the formation of chimeric sequences (chimeras, expressed as structural errors in sequencing data) in MDA seriously interferes with the bioinformatics analysis but its influence on long-read sequencing data is unknown.

RESULTS

We sequenced the phi29 DNA polymerase-mediated MDA amplicons on the PacBio platform and analyzed chimeras within the generated data. The 3rd-ChimeraMiner has been constructed as a pipeline for recognizing and restoring chimeras into the original structures in long-read sequencing data, improving the efficiency of using TGS data. Five long-read datasets and one high-fidelity long-read dataset with various amplification folds were analyzed. The result reveals that the mis-priming events in amplification are more frequently occurring than widely perceived, and the propor tion gradually accumulates from 42% to over 78% as the amplification continues. In total, 99.92% of recognized chimeric sequences were demonstrated to be artifacts, whose structures were wrongly formed in MDA instead of existing in original genomes. By restoring chimeras to their original structures, the vast majority of supplementary alignments that introduce false-positive structural variants are recycled, removing 97% of inversions on average and contributing to the analysis of structural variation in MDA-amplified samples. The impact of chimeras in long-read sequencing data analysis should be emphasized, and the 3rd-ChimeraMiner can help to quantify and reduce the influence of chimeras.

AVAILABILITY AND IMPLEMENTATION

The 3rd-ChimeraMiner is available on GitHub, https://github.com/dulunar/3rdChimeraMiner.

Multimodal deep learning approaches for single-cell multi-omics data integration

Integrating single-cell multi-omics data is a challenging task that has led to new insights into complex cellular systems. Various computational methods have been proposed to effectively integrate these rapidly accumulating datasets, including deep learning. However, despite the proven success of deep learning in integrating multi-omics data and its better performance over classical computational methods, there has been no systematic study of its application to single-cell multi-omics data integration. To fill this gap, we conducted a literature review to explore the use of multimodal deep learning techniques in single-cell multi-omics data integration, taking into account recent studies from multiple perspectives. Specifically, we first summarized different modalities found in single-cell multi-omics data. We then reviewed current deep learning techniques for processing multimodal data and categorized deep learning-based integration methods for single-cell multi-omics data according to data modality, deep learning architecture, fusion strategy, key tasks and downstream analysis. Finally, we provided insights into using these deep learning models to integrate multi-omics data and better understand single-cell biological mechanisms.

Single-cell phylogenies reveal changes in the evolutionary rate within cancer and healthy tissues

Cell lineages accumulate somatic mutations during organismal development, potentially leading to pathological states. The rate of somatic evolution within a cell population can vary due to multiple factors, including selection, a change in the mutation rate, or differences in the microenvironment. Here, we developed a statistical test called the Poisson Tree (PT) test to detect varying evolutionary rates among cell lineages, leveraging the phylogenetic signal of single-cell DNA sequencing (scDNA-seq) data. We applied the PT test to 24 healthy and cancer samples, rejecting a constant evolutionary rate in 11 out of 15 cancer and five out of nine healthy scDNA-seq datasets. In six cancer datasets, we identified subclonal mutations in known driver genes that could explain the rate accelerations of particular cancer lineages. Our findings demonstrate the efficacy of scDNA-seq for studying somatic evolution and suggest that cell lineages often evolve at different rates within cancer and healthy tissues.

A primer-independent DNA polymerase-based method for competent whole-genome amplification of intermediate to high GC sequences

Multiple displacement amplification (MDA) has proven to be a useful technique for obtaining large amounts of DNA from tiny samples in genomics and metagenomics. However, MDA has limitations, such as amplification artifacts and biases that can interfere with subsequent quantitative analysis. To overcome these challenges, alternative methods and engineered DNA polymerase variants have been developed. Here, we present new MDA protocols based on the primer-independent DNA polymerase (piPolB), a replicative-like DNA polymerase endowed with DNA priming and proofreading capacities. These new methods were tested on a genomes mixture containing diverse sequences with high-GC content, followed by deep sequencing. Protocols relying on piPolB as a single enzyme cannot achieve competent amplification due to its limited processivity and the presence of ab initio DNA synthesis. However, an alternative method called piMDA, which combines piPolB with Φ29 DNA polymerase, allows proficient and faithful amplification of the genomes. In addition, the prior denaturation step commonly performed in MDA protocols is dispensable, resulting in a more straightforward protocol. In summary, piMDA outperforms commercial methods in the amplification of genomes and metagenomes containing high GC sequences and exhibits similar profiling, error rate and variant determination as the non-amplified samples.

How single-cell techniques help us look into lung cancer heterogeneity and immunotherapy

Lung cancer patients tend to have strong intratumoral and intertumoral heterogeneity and complex tumor microenvironment, which are major contributors to the efficacy of and drug resistance to immunotherapy. From a new perspective, single-cell techniques offer an innovative way to look at the intricate cellular interactions between tumors and the immune system and help us gain insights into lung cancer and its response to immunotherapy. This article reviews the application of single-cell techniques in lung cancer, with focuses directed on the heterogeneity of lung cancer and the efficacy of immunotherapy. This review provides both theoretical and experimental information for the future development of immunotherapy and personalized treatment for the management of lung cancer.

COMPASS: joint copy number and mutation phylogeny reconstruction from amplicon single-cell sequencing data

Reconstructing the history of somatic DNA alterations can help understand the evolution of a tumor and predict its resistance to treatment. Single-cell DNA sequencing (scDNAseq) can be used to investigate clonal heterogeneity and to inform phylogeny reconstruction. However, most existing phylogenetic methods for scDNAseq data are designed either for single nucleotide variants (SNVs) or for large copy number alterations (CNAs), or are not applicable to targeted sequencing. Here, we develop COMPASS, a computational method for inferring the joint phylogeny of SNVs and CNAs from targeted scDNAseq data. We evaluate COMPASS on simulated data and apply it to several datasets including a cohort of 123 patients with acute myeloid leukemia. COMPASS detected clonal CNAs that could be orthogonally validated with bulk data, in addition to subclonal ones that require single-cell resolution, some of which point toward convergent evolution.

Noninvasive Prenatal Testing Using Circulating DNA and RNA: Advances, Challenges, and Possibilities

Prenatal screening using sequencing of circulating cell-free DNA has transformed obstetric care over the past decade and significantly reduced the number of invasive diagnostic procedures like amniocentesis for genetic disorders. Nonetheless, emergency care remains the only option for complications like preeclampsia and preterm birth, two of the most prevalent obstetrical syndromes. Advances in noninvasive prenatal testing expand the scope of precision medicine in obstetric care. In this review, we discuss advances, challenges, and possibilities toward the goal of providing proactive, personalized prenatal care. The highlighted advances focus mainly on cell-free nucleic acids; however, we also review research that uses signals from metabolomics, proteomics, intact cells, and the microbiome. We discuss ethical challenges in providing care. Finally, we look to future possibilities, including redefining disease taxonomy and moving from biomarker correlation to biological causation.

Single-cell third-generation sequencing-based multi-omics uncovers gene expression changes governed by ecDNA and structural variants in cancer cells

BACKGROUND

Cancer cells often exhibit large-scale genomic variations, such as circular extrachromosomal DNA (ecDNA) and structural variants (SVs), which have been highly correlated with the initiation and progression of cancer. Currently, no adequate method exists to unveil how these variations regulate gene expression in heterogeneous cancer cell populations at a single-cell resolution.

METHODS

Here, we developed a single-cell multi-omics sequencing method, scGTP-seq, to analyse ecDNA and SVs using long-read sequencing technologies.

RESULTS AND CONCLUSIONS

We demonstrated that our method can efficiently detect ecDNA and SVs and illustrated how these variations affect transcriptomic changes in various cell lines. Finally, we applied and validated this method in a clinical sample of hepatocellular carcinoma (HCC), demonstrating a feasible way to monitor the evolution of ecDNA and SVs during cancer progression.

Identification of carrier status of Xp22.31 microdeletions associated with X-linked ichthyosis at the single-cell level using haplotype linkage analysis by karyomapping

PURPOSE

Currently, owing to the limitations of high-throughput sequencing depth and the allele dropout caused by the whole-genome amplification, detection of chromosomal variants in embryos with CNVs <5 Mb is unsatisfactory at the single-cell level using only conventional sequencing methods. Therefore, here we aimed to use a strategy of preimplantation genetic testing for monogenic (PGT-M) to compensate for the shortcomings of conventional sequencing methods. The purpose of this study is to report the effectiveness of haplotype linkage analysis by karyomapping for preimplantation diagnosis microdeletion diseases.

METHODS

Six couples carrying chromosomal microdeletions associated with X-linked ichthyosis were recruited, and all couples entered the PGT process. Multiple displacement amplification (MDA) method was used to amplify the whole-genome DNA of trophectoderm cells. Then karyomapping based on single nucleotide polymorphism (SNP) was used for haplotype linkage analysis to detect alleles carrying microdeletions, and CNVs of embryos were identified to determine euploid identity. Amniotic fluid tests were performed in the second trimester to verify the PGT-M results.

RESULTS

All couples were tested for chromosomal microdeletions, with deletion fragments ranging in size from 1.60 to 1.73 Mb, and one partner in each couple did not carry the microdeletion. Three couples successfully underwent PGT-M assisted conception and obtained healthy live births.

CONCLUSION

This study shows that haplotype linkage analysis by karyomapping could effectively detect the carrier status of embryos with microdeletions at the single-cell level. This approach may be applied to the preimplantation diagnosis of various chromosomal microvariation diseases.

Single-Cell Analysis in the Omics Era: Technologies and Applications in Cancer

Cancer molecular profiling obtained with conventional bulk sequencing describes average alterations obtained from the entire cellular population analyzed. In the era of precision medicine, this approach is unable to track tumor heterogeneity and cannot be exploited to unravel the biological processes behind clonal evolution. In the last few years, functional single-cell omics has improved our understanding of cancer heterogeneity. This approach requires isolation and identification of single cells starting from an entire population. A cell suspension obtained by tumor tissue dissociation or hematological material can be manipulated using different techniques to separate individual cells, employed for single-cell downstream analysis. Single-cell data can then be used to analyze cell-cell diversity, thus mapping evolving cancer biological processes. Despite its unquestionable advantages, single-cell analysis produces massive amounts of data with several potential biases, stemming from cell manipulation and pre-amplification steps. To overcome these limitations, several bioinformatic approaches have been developed and explored. In this work, we provide an overview of this entire process while discussing the most recent advances in the field of functional omics at single-cell resolution.

Single-cell omics: a new perspective for early detection of pancreatic cancer?

Pancreatic cancer is one of the most lethal cancers, mostly due to late diagnosis and limited treatment options. Early detection of pancreatic cancer in high-risk populations bears the potential to greatly improve outcomes, but current screening approaches remain of limited value despite recent technological advances. This review explores the possible advantages of liquid biopsies for this application, particularly focusing on circulating tumour cells (CTCs) and their subsequent single-cell omics analysis. Originating from both primary and metastatic tumour sites, CTCs provide important information for diagnosis, prognosis and tailoring of treatment strategies. Notably, CTCs have even been detected in the blood of subjects with pancreatic precursor lesions, suggesting their suitability as a non-invasive tool for the early detection of malignant transformation in the pancreas. As intact cells, CTCs offer comprehensive genomic, transcriptomic, epigenetic and proteomic information that can be explored using rapidly developing techniques for analysing individual cells at the molecular level. Studying CTCs during serial sampling and at single-cell resolution will help to dissect tumour heterogeneity for individual patients and among different patients, providing new insights into cancer evolution during disease progression and in response to treatment. Using CTCs for non-invasive tracking of cancer features, including stemness, metastatic potential and expression of immune targets, provides important and readily accessible molecular insights. Finally, the emerging technology of ex vivo culturing of CTCs could create new opportunities to study the functionality of individual cancers at any stage and develop personalised and more effective treatment approaches for this lethal disease.

Clinical application of next generation sequencing-based haplotype linkage analysis in the preimplantation genetic testing for germline mosaicisms

BACKGROUND

Preimplantation genetic testing (PGT) for monogenic disorders (PGT-M) for germline mosaicism was previously highly dependent on polymerase chain reaction (PCR)-based directed mutation detection combined with linkage analysis of short tandem repeats (STRs). However, the number of STRs is usually limited. In addition, designing suitable probes and optimizing the reaction conditions for multiplex PCR are time-consuming and laborious. Here, we evaluated the effectiveness of next generation sequencing (NGS)-based haplotype linkage analysis in PGT of germline mosaicism.

METHODS

PGT-M with NGS-based haplotype linkage analysis was performed for two families with maternal germline mosaicism for an X-linked Duchenne muscular dystrophy (DMD) mutation (del exon 45-50) or an autosomal TSC1 mutation (c.2074C > T). Trophectoderm biopsy and multiple displacement amplification (MDA) were performed for a total of nine blastocysts. NGS and Sanger sequencing were performed in genomic DNA of family members and embryonic MDA products to detect DMD deletion and TSC1 mutation, respectively. Single nucleotide polymorphism (SNP) sites closely linked to pathogenic mutations were detected with NGS and served in haplotype linkage analysis. NGS-based aneuploidy screening was performed for all embryos to reduce the risk of pregnancy loss.

RESULTS

All nine blastocytes showed conclusive PGT results. Each family underwent one or two frozen-thawed embryo transfer cycles to obtain a clinical pregnancy, and the prenatal diagnosis showed that the fetus was genotypically normal and euploid for both families.

CONCLUSIONS

NGS-SNP could effectively realize PGT for germline mosaicism. Compared with PCR-based methods, the NGS-SNP method with increased polymorphic informative markers can achieve a greater diagnostic accuracy. Further studies are warranted to verify the effectiveness of NGS-based PGT of germline mosaicism cases in the absence of surviving offsprings.

DNA Polymerases for Whole Genome Amplification: Considerations and Future Directions

In the same way that specialized DNA polymerases (DNAPs) replicate cellular and viral genomes, only a handful of dedicated proteins from various natural origins as well as engineered versions are appropriate for competent exponential amplification of whole genomes and metagenomes (WGA). Different applications have led to the development of diverse protocols, based on various DNAPs. Isothermal WGA is currently widely used due to the high performance of Φ29 DNA polymerase, but PCR-based methods are also available and can provide competent amplification of certain samples. Replication fidelity and processivity must be considered when selecting a suitable enzyme for WGA. However, other properties, such as thermostability, capacity to couple replication, and double helix unwinding, or the ability to maintain DNA replication opposite to damaged bases, are also very relevant for some applications. In this review, we provide an overview of the different properties of DNAPs widely used in WGA and discuss their limitations and future research directions.

Unraveling the heterogeneity of cholangiocarcinoma and identifying biomarkers and therapeutic strategies with single-cell sequencing technology

Cholangiocarcinoma (CCA) is a common malignant tumor of the biliary tract that carries a high burden of morbidity and a poor prognosis. Due to the lack of precise diagnostic methods, many patients are often diagnosed at advanced stages of the disease. The current treatment options available are of varying efficacy, underscoring the urgency for the discovery of more effective biomarkers for early diagnosis and improved treatment. Recently, single-cell sequencing (SCS) technology has gained popularity in cancer research. This technology has the ability to analyze tumor tissues at the single-cell level, thus providing insights into the genomics and epigenetics of tumor cells. It also serves as a practical approach to study the mechanisms of cancer progression and to explore therapeutic strategies. In this review, we aim to assess the heterogeneity of CCA using single-cell sequencing technology, with the ultimate goal of identifying possible biomarkers and potential treatment targets.

Enhancing clinical potential of liquid biopsy through a multi-omic approach: A systematic review

In the last years, liquid biopsy gained increasing clinical relevance for detecting and monitoring several cancer types, being minimally invasive, highly informative and replicable over time. This revolutionary approach can be complementary and may, in the future, replace tissue biopsy, which is still considered the gold standard for cancer diagnosis. “Classical” tissue biopsy is invasive, often cannot provide sufficient bioptic material for advanced screening, and can provide isolated information about disease evolution and heterogeneity. Recent literature highlighted how liquid biopsy is informative of proteomic, genomic, epigenetic, and metabolic alterations. These biomarkers can be detected and investigated using single-omic and, recently, in combination through multi-omic approaches. This review will provide an overview of the most suitable techniques to thoroughly characterize tumor biomarkers and their potential clinical applications, highlighting the importance of an integrated multi-omic, multi-analyte approach. Personalized medical investigations will soon allow patients to receive predictable prognostic evaluations, early disease diagnosis, and subsequent ad hoc treatments.

Blocker displacement amplification-based genetic diagnosis for autosomal dominant polycystic kidney disease and the clinical outcomes of preimplantation genetic testing

OBJECTIVE

Given that the molecular diagnosis of autosomal dominant polycystic kidney disease (ADPKD) is complicated, we aim to apply blocker displacement amplification (BDA) on the mutational screening of PKD1 and PKD2.

METHODS

A total of 35 unrelated families with ADPKD were recruited from the Center for Reproductive Medicine, Women and Children's Hospital of Chongqing Medical University (Chongqing, China), from October 2018 to October 2021. Long-range PCR followed by next-generation sequencing were applied for resequencing of PKD1 and PKD2, and the putatively disease-causative variants were verified with BDA. The effects of ADPKD on male and female infertility and the factors influencing the clinical outcomes of preimplantation genetic testing (PGT) for ADPKD were investigated.

RESULTS

A total of 26 PKD1 variants and 5 PKD2 variants were identified, of which 13 were newly discovered. The BDA system worked effectively for eliminating the interference of pseudogenes in genetic testing of PKD1 (1-33 exons) with different concentrations of genome DNA. The females with ADPKD have no specific infertility factors, while 68.2% of the affected men were with abnormal sperm concentration and/or motility with an indefinite genotype-phenotype relationship. As for PGT, the fertilization rate of couples with the male partner having ADPKD was relatively lower compared to those with the female partner being affected. The ADPKD patients receiving PGT usually achieved high rates of live births.

CONCLUSION

These findings expanded the variant spectrum of PKD genes and emphasized the application prospect of blocker displacement amplification on PKD1-related genetic diagnosis.

Spatiotemporal dissection of tumor microenvironment via in situ sensing and monitoring in tumor-on-a-chip

Real-time monitoring in the tumor microenvironment provides critical insights of cancer progression and mechanistic understanding of responses to cancer treatments. However, clinical challenges and significant questions remain regarding assessment of limited clinical tissue samples, establishment of validated, controllable pre-clinical cancer models, monitoring of static versus dynamic markers, and the translation of insights gained from in vitro tumor microenvironments to systematic investigation and understanding in clinical practice. State-of-art tumor-on-a-chip strategies will be reviewed herein, and emerging real-time sensing and monitoring platforms for on-chip analysis of tumor microenvironment will also be examined. The integration of the sensors with tumor-on-a-chip platforms to provide spatiotemporal information of the tumor microenvironment and the associated challenges will be further evaluated. Though optimal integrated systems for in situ monitoring are still in evolution, great promises lie ahead that will open new paradigm for rapid, comprehensive analysis of cancer development and assist clinicians with powerful tools to guide the diagnosis, prognosis and treatment course in cancer.

Benchmarking of Nanopore R10.4 and R9.4.1 flow cells in single-cell whole-genome amplification and whole-genome shotgun sequencing

Third-generation sequencing can be used in human cancer genomics and epigenomic research. Oxford Nanopore Technologies (ONT) recently released R10.4 flow cell, which claimed an improved read accuracy compared to R9.4.1 flow cell. To evaluate the benefits and defects of R10.4 flow cell for cancer cell profiling on MinION devices, we used the human non-small-cell lung-carcinoma cell line HCC78 to construct libraries for both single-cell whole-genome amplification (scWGA) and whole-genome shotgun sequencing. The R10.4 and R9.4.1 reads were benchmarked in terms of read accuracy, variant detection, modification calling, genome recovery rate and compared with the next generation sequencing (NGS) reads. The results highlighted that the R10.4 outperforms R9.4.1 reads, achieving a higher modal read accuracy of over 99.1%, superior variation detection, lower false-discovery rate (FDR) in methylation calling, and comparable genome recovery rate. To achieve high yields scWGA sequencing in the ONT platform as NGS, we recommended multiple displacement amplification with a modified T7 endonuclease Ⅰ cutting procedure as a promising method. In addition, we provided a possible solution to filter the likely false positive sites among the whole genome region with R10.4 by using scWGA sequencing result as a negative control. Our study is the first benchmark of whole genome single-cell sequencing using ONT R10.4 and R9.4.1 MinION flow cells by clarifying the capacity of genomic and epigenomic profiling within a single flow cell. A promising method for scWGA sequencing together with the methylation calling results can benefit researchers who work on cancer cell genomic and epigenomic profiling using third-generation sequencing.

Application of conventional IVF during preimplantation genetic testing for aneuploidies: a feasibility study

RESEARCH QUESTION

Is it feasible to apply conventional IVF to couples undergoing preimplantation genetic testing for aneuploidies (PGT-A) with non-severe male infertility?

DESIGN

The last wash fluid of biopsied trophectoderm (TE) cells was collected for whole genome amplification (WGA). A method was developed to determine parental contamination. Using single-nucleotide polymorphism (SNP) analysis, two standard curves were established; further mixtures were used for verification. Finally, 29 WGA products from couples undergoing conventional IVF were used to evaluate parental contamination.

RESULTS

The WGA results of the last wash fluid of biopsied TE cells revealed almost no free DNA. By adopting two strategies based on maternally and paternally biased SNP in the mixture, data from bioinformatics analysis were analysed to determine the relationship between maternal (Index M) and paternal (Index F) bias statistics. Two standard curves were successfully established based on these indices that allowed the prediction of maternal and parental contamination, which correlated well with actual ratios of known composition mixtures during validation. The average contamination level was 10.6% determined from 10 WGA products that featured maternal contamination, whereas that of the other 19 products that featured paternal contamination was less than 10%.

CONCLUSIONS

This study confirmed the feasibility of applying conventional IVF to couples undergoing PGT-A with non-severe male infertility.

Ultralow-Input Genome Library Preparation for Nanopore Sequencing with Droplet MDA

Genome sequencing of small species, such as those of meinofauna, can be challenging due to the extremely low input of genomic DNA. While nanopore sequencing is a promising technology for genome assembly due to its limitless long reads, recommended input of 1 μg for the Ligation Sequencing Kit often precludes the use of this technology. Here, I detail an unbiased droplet-based multiple displacement amplification of picogram order of DNA to realize nanopore sequencing with ultralow input of genomic DNA. For this purpose, a microfluidic chip of 10X Genomics Chromium Controller is utilized. With this method, over 10 μg of unbiased amplicons around 10 kbp in length can be obtained from as low as 50 μg of input DNA, which is enough for the construction of multiple sequencing libraries, or for the size selection of longer DNA fragments.

Comparative analysis of single-cell genome sequencing techniques toward the characterization of germline and somatic genomes in ciliated protists

Ciliated protists contain both germline micronucleus (MIC) and somatic macronucleus (MAC) in a single cytoplasm. Programmed genome rearrangements occur in ciliates during sexual processes, and the extent of rearrangements varies dramatically among species, which lead to significant differences in genomic architectures. However, genomic sequences remain largely unknown for most ciliates due to the difficulty in culturing and in separating the germline from the somatic genome in a single cell. Single-cell whole genome amplification (WGA) has emerged as a powerful technology to characterize the genomic heterogeneity at the single-cell level. In this study, we compared two single-cell WGA, multiple displacement amplification (MDA) and multiple annealing and looping-based amplification cycles (MALBAC) in characterizing the germline and somatic genomes in ciliates with different genomic architectures. Our results showed that: 1) MALBAC exhibits strong amplification bias towards MAC genome while MDA shows bias towards MIC genome of ciliates with extensively fragmented MAC genome; 2) both MDA and MALBAC could amplify MAC genome more efficiently in ciliates with moderately fragmented MAC genome. Moreover, we found that more sample replicates could help to obtain more genomic data. Our work provides a reference for selecting the appropriate method to characterize germline and somatic genomes of ciliates.