Single-cell paired-end genome sequencing reveals structural variation per cell cycle

Copy number variation analysis identifies MIR9-3 and MIR1299 as novel miRNA candidate genes for CAKUT

BACKGROUND

Congenital anomalies of the kidney and urinary tract (CAKUT) represent a frequent cause of pediatric kidney failure. CNVs, as a major class of genomic variations, can also affect miRNA regions. Common CNV corresponding miRNAs (cCNV-miRNAs) are functional variants regulating crucial processes which could affect urinary system development. Thus, we hypothesize that cCNV-miRNAs are associated with CAKUT occurrence and its expressivity.

METHODS

The extraction and filtering of common CNVs, identified in control samples deposited in publicly available databases gnomAD v2.1 and dbVar, were coupled with mapping of miRNA sequences using UCSC Genome Browser. After verification of the mapped miRNAs using referent miRBase V22.1, prioritization of cCNV-miRNA candidates has been performed using bioinformatic annotation and literature research. Genotyping of miRNA gene copy numbers for MIR9-3, MIR511, and MIR1299, was conducted on 221 CAKUT patients and 192 controls using TaqMan™ technology.

RESULTS

We observed significantly different MIR9-3 and MIR1299 gene copy number distribution between CAKUT patients and controls (Chi-square, P = 0.006 and P = 0.0002, respectively), while difference of MIR511 copy number distribution showed nominal significance (Chi-square, P = 0.027). The counts of less and more than two of MIR1299 copy numbers were more frequent within CAKUT patients compared to controls (P = 0.01 and P = 0.008, respectively) and also in cohort of patients with anomalies of the urinary tract compared to controls (P = 0.016 and P = 0.003, respectively).

CONCLUSIONS

Copy number variations of miRNA genes represent a novel avenue in clarification of the inheritance complexity in CAKUT and provide potential evidence about the association of common genetic variation with CAKUT phenotypes.

Single-cell somatic copy number variants in brain using different amplification methods and reference genomes

The presence of somatic mutations, including copy number variants (CNVs), in the brain is well recognized. Comprehensive study requires single-cell whole genome amplification, with several methods available, prior to sequencing. We compared PicoPLEX with two recent adaptations of multiple displacement amplification (MDA): primary template-directed amplification (PTA) and droplet MDA, across 93 human brain cortical nuclei. We demonstrated different properties for each, with PTA providing the broadest amplification, PicoPLEX the most even, and distinct chimeric profiles. Furthermore, we performed CNV calling on two brains with multiple system atrophy and one control brain using different reference genomes. We found that 38% of brain cells have at least one Mb-scale CNV, with some supported by bulk sequencing or single-cells from other brain regions. Our study highlights the importance of selecting whole genome amplification method and reference genome for CNV calling, while supporting the existence of somatic CNVs in healthy and diseased human brain.

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.

Advances in novel strategies for isolation, characterization, and analysis of CTCs and ctDNA

Over the past decade, the detection and analysis of liquid biopsy biomarkers such as circulating tumor cells (CTCs) and circulating tumor DNA (ctDNA) have advanced significantly. They have received recognition for their clinical usefulness in detecting cancer at an early stage, monitoring disease, and evaluating treatment response. The emergence of liquid biopsy has been a helpful development, as it offers a minimally invasive, rapid, real-time monitoring, and possible alternative to traditional tissue biopsies. In resource-limited settings, the ideal platform for liquid biopsy should not only extract more CTCs or ctDNA from a minimal sample volume but also accurately represent the molecular heterogeneity of the patient's disease. This review covers novel strategies and advancements in CTC and ctDNA-based liquid biopsy platforms, including microfluidic applications and comprehensive analysis of molecular complexity. We discuss these systems' operational principles and performance efficiencies, as well as future opportunities and challenges for their implementation in clinical settings. In addition, we emphasize the importance of integrated platforms that incorporate machine learning and artificial intelligence in accurate liquid biopsy detection systems, which can greatly improve cancer management and enable precision diagnostics.

Somatic CNV Detection by Single-Cell Whole-Genome Sequencing in Postmortem Human Brain

The evidence for a role of somatic mutations, including copy-number variants (CNVs), in neurodegeneration has increased in the last decade. However, the understanding of the types and origins of these mutations, and their exact contributions to disease onset and progression, is still in its infancy. The use of single-cell (or nuclear) whole-genome sequencing (scWGS) has emerged as a powerful tool to answer these questions. In the present chapter, we provide laboratory and bioinformatic protocols used successfully in our lab to detect megabase-scale CNVs in single cells from multiple system atrophy (MSA) human postmortem brains, using immunolabeling prior to selection of nuclei for whole-genome amplification (WGA). We also present an unpublished comparison of scWGS generated from the same control substantia nigra (SN) sample, using the latest versions of popular WGA chemistries, MDA and PicoPLEX. We have used this protocol to focus on brain cell types most relevant to synucleinopathies (dopaminergic [DA] neurons in Parkinson's disease [PD] and oligodendrocytes in MSA), but it can be applied to any tissue and/or cell type with appropriate markers.

Chimera: The spoiler in multiple displacement amplification

Multiple displacement amplification (MDA) based on isothermal random priming and high fidelity phi29 DNA polymerase-mediated processive extension has revolutionized the field of whole genome amplification by enabling the amplification of minute amounts of DNA, such as from a single cell, generating vast amounts of DNA with high genome coverage. Despite its advantages, MDA has its own challenges, one of the grandest being the formation of chimeric sequences (chimeras), which presents in all MDA products and seriously disturbs the downstream analysis. In this review, we provide a comprehensive overview of current research on MDA chimeras. We first reviewed the mechanisms of chimera formation and chimera detection methods. We then systematically summarized the characteristics of chimeras, including overlap, chimeric distance, chimeric density, and chimeric rate, as found in independently published sequencing data. Finally, we reviewed the methods used to process chimeric sequences and their impacts on the improvement of data utilization efficiency. The information presented in this review will be useful for those interested in understanding the challenges with MDA and in improving its performance.

Leveraging single cell sequencing to unravel intra-tumour heterogeneity and tumour evolution in human cancers

Intra-tumour heterogeneity and tumour evolution are well-documented phenomena in human cancers. While the advent of next-generation sequencing technologies has facilitated the large-scale capture of genomic data, the field of single cell genomics is nascent but rapidly advancing and generating many new insights into the complex molecular mechanisms of tumour biology. In this review, we provide an overview of current single cell DNA sequencing technologies, exploring how recent methodological advancements have enumerated new insights into intra-tumour heterogeneity and tumour evolution. Areas highlighted include the potential power of single cell genome sequencing studies to explore evolutionary dynamics contributing to tumourigenesis through to progression, metastasis and therapy resistance. We also explore the use of in-situ sequencing technologies to study intra-tumour heterogeneity in a spatial context, as well as examining the use of single cell genomics to perform lineage tracing in both normal and malignant tissues. Finally, we consider the use of multi-modal single cell sequencing technologies. Taken together, it is hoped that these many facets of single cell genome sequencing will improve our understanding of tumourigenesis, progression and lethality in cancer leading to the development of novel therapies. This article is protected by copyright. All rights reserved.

Single-cell genome-wide concurrent haplotyping and copy-number profiling through genotyping-by-sequencing

Single-cell whole-genome haplotyping allows simultaneous detection of haplotypes associated with monogenic diseases, chromosome copy-numbering and subsequently, has revealed mosaicism in embryos and embryonic stem cells. Methods, such as karyomapping and haplarithmisis, were deployed as a generic and genome-wide approach for preimplantation genetic testing (PGT) and are replacing traditional PGT methods. While current methods primarily rely on single-nucleotide polymorphism (SNP) array, we envision sequencing-based methods to become more accessible and cost-efficient. Here, we developed a novel sequencing-based methodology to haplotype and copy-number profile single cells. Following DNA amplification, genomic size and complexity is reduced through restriction enzyme digestion and DNA is genotyped through sequencing. This single-cell genotyping-by-sequencing (scGBS) is the input for haplarithmisis, an algorithm we previously developed for SNP array-based single-cell haplotyping. We established technical parameters and developed an analysis pipeline enabling accurate concurrent haplotyping and copy-number profiling of single cells. We demonstrate its value in human blastomere and trophectoderm samples as application for PGT for monogenic disorders. Furthermore, we demonstrate the method to work in other species through analyzing blastomeres of bovine embryos. Our scGBS method opens up the path for single-cell haplotyping of any species with diploid genomes and could make its way into the clinic as a PGT application.

SCSit: A high-efficiency preprocessing tool for single-cell sequencing data from SPLiT-seq

SPLiT-seq provides a low-cost platform to generate single-cell data by labeling the cellular origin of RNA through four rounds of combinatorial barcoding. However, an automatic and rapid method for preprocessing and classifying single-cell sequencing (SCS) data from SPLiT-seq, which directly identified and labeled combinatorial barcoding reads and distinguished special cell sequencing data, is currently lacking. Here, we develop a high-efficiency preprocessing tool for single-cell sequencing data from SPLiT-seq (SCSit), which can directly identify combinatorial barcodes and UMI of cell types and obtain more labeled reads, and remarkably enhance the retained data from SCS due to the exact alignment of insertion and deletion. Compared with the original method used in SPLiT-seq, the consistency of identified reads from SCSit increases to 97%, and mapped reads are twice than the original. Furthermore, the runtime of SCSit is less than 10% of the original. It can accurately and rapidly analyze SPLiT-seq raw data and obtain labeled reads, as well as effectively improve the single-cell data from SPLiT-seq platform. The data and source of SCSit are available on the GitHub website https://github.com/shang-qian/SCSit.

Prognostic Value of Germline Copy Number Variants and Environmental Exposures in Non-small Cell Lung Cancer

Germline copy number variant (gCNV) has been studied as a genetic determinant for prognosis of several types of cancer, but little is known about how it affects non-small cell lung cancer (NSCLC) prognosis. We aimed to develop a prognostic nomogram for NSCLC based on gCNVs. Promising gCNVs that are associated with overall survival (OS) of NSCLC were sorted by analyzing the TCGA data and were validated in a small Chinese population. Then the successfully verified gCNVs were determined in a training cohort (n = 570) to develop a prognostic nomogram, and in a validation cohort (n = 465) to validate the nomogram. Thirty-five OS-related gCNVs were sorted and were reduced to 15 predictors by the Lasso regression analysis. Of them, only CNVR395.1 and CNVR2239.1 were confirmed to be associated with OS of NSCLC in the Chinese population. High polygenic risk score (PRS), which was calculated by the hazard effects of CNVR395.1 and CNVR2239.1, exerted a significantly higher death rate in the training cohort (HR = 1.41, 95%CI: 1.16–1.74) and validation cohort (HR = 1.42, 95%CI: 1.13–1.77) than low PRS. The nomogram incorporating PRS and surrounding factors, achieved admissible concordance indexes of 0.678 (95%CI: 0.664–0.693) and 0.686 (95%CI: 0.670–0.702) in predicting OS in the training and validation cohorts, respectively, and had well-fitted calibration curves. Moreover, an interaction between PRS and asbestos exposure was observed on affecting OS (P_interaction = 0.042). Our analysis developed a nomogram that achieved an admissible prediction of NSCLC survival, which would be beneficial to the personalized intervention of NSCLC.

CellCoal: Coalescent Simulation of Single-Cell Sequencing Samples

Our capacity to study individual cells has enabled a new level of resolution for understanding complex biological systems such as multicellular organisms or microbial communities. Not surprisingly, several methods have been developed in recent years with a formidable potential to investigate the somatic evolution of single cells in both healthy and pathological tissues. However, single-cell sequencing data can be quite noisy due to different technical biases, so inferences resulting from these new methods need to be carefully contrasted. Here, I introduce CellCoal, a software tool for the coalescent simulation of single-cell sequencing genotypes. CellCoal simulates the history of single-cell samples obtained from somatic cell populations with different demographic histories and produces single-nucleotide variants under a variety of mutation models, sequencing read counts, and genotype likelihoods, considering allelic imbalance, allelic dropout, amplification, and sequencing errors, typical of this type of data. CellCoal is a flexible tool that can be used to understand the implications of different somatic evolutionary processes at the single-cell level, and to benchmark dedicated bioinformatic tools for the analysis of single-cell sequencing data. CellCoal is available at https://github.com/dapogon/cellcoal.

Methodological Advancements for Investigating Intra-tumoral Heterogeneity in Breast Cancer at the Bench and Bedside

There is a major need to overcome therapeutic resistance and metastasis that eventually arises in many breast cancer patients. Therapy resistant and metastatic tumors are increasingly recognized to possess intra-tumoral heterogeneity (ITH), a diversity of cells within an individual tumor. First hypothesized in the 1970s, the possibility that this complex ITH may endow tumors with adaptability and evolvability to metastasize and evade therapies is now supported by multiple lines of evidence. Our understanding of ITH has been driven by recent methodological advances including next-generation sequencing, computational modeling, lineage tracing, single-cell technologies, and multiplexed in situ approaches. These have been applied across a range of specimens, including patient tumor biopsies, liquid biopsies, cultured cell lines, and mouse models. In this review, we discuss these approaches and how they have deepened our understanding of the mechanistic origins of ITH amongst tumor cells, including stem cell-like differentiation hierarchies and Darwinian evolution, and the functional role for ITH in breast cancer progression. While ITH presents a challenge for combating tumor evolution, in-depth analyses of ITH in clinical biopsies and laboratory models hold promise to elucidate therapeutic strategies that should ultimately improve outcomes for breast cancer patients.

Single-cell analysis of structural variations and complex rearrangements with tri-channel processing

Structural variation (SV), involving deletions, duplications, inversions and translocations of DNA segments, is a major source of genetic variability in somatic cells and can dysregulate cancer-related pathways. However, discovering somatic SVs in single cells has been challenging, with copy-number-neutral and complex variants typically escaping detection. Here we describe single-cell tri-channel processing (scTRIP), a computational framework that integrates read depth, template strand and haplotype phase to comprehensively discover SVs in individual cells. We surveyed SV landscapes of 565 single cells, including transformed epithelial cells and patient-derived leukemic samples, to discover abundant SV classes, including inversions, translocations and complex DNA rearrangements. Analysis of the leukemic samples revealed four times more somatic SVs than cytogenetic karyotyping, submicroscopic copy-number alterations, oncogenic copy-neutral rearrangements and a subclonal chromothripsis event. Advancing current methods, single-cell tri-channel processing can directly measure SV mutational processes in individual cells, such as breakage-fusion-bridge cycles, facilitating studies of clonal evolution, genetic mosaicism and SV formation mechanisms, which could improve disease classification for precision medicine.

Characterization and expression profiling of the ICE-CBF-COR genes in wheat

Cold stress is one of the major abiotic stresses that limit crop production. The ICE-CBF-COR pathway is associated with cold stress response in a wide variety of crop species. However, the ICE-CBF-COR genes has not been well characterized in wheat (Triticum aestivum). This study identified, characterized and examined the expression profiles of the ICE, CBF and COR genes for cold defense in wheat. Five ICE (inducer of CBF expression) genes, 37 CBF (C-repeat binding factor) genes and 11 COR (cold-responsive or cold-regulated) genes were discovered in the wheat genome database. Phylogenetic trees based on all 53 genes revealed that CBF genes were more diverse than ICE and COR genes. Twenty-two of the 53 genes appeared to include 11 duplicated pairs. Twenty rice (Oryza sativa) genes and 21 sorghum (Sorghum bicolor) and maize (Zea mays) genes showed collinearity with the wheat ICE, CBF and COR genes. Transcriptome data and qRT-PCR analyses revealed tissue-specific expression patterns of the ICE, CBF and COR genes, and identified similarities in the expression pattern of genes from the same family when subjected to drought, heat, drought plus heat, and cold stress. These results provide information for better understanding the biological roles of ICE, CBF, COR genes in wheat.

In vitro fertilization does not increase the incidence of de novo copy number alterations in fetal and placental lineages

Although chromosomal instability (CIN) is a common phenomenon in cleavage-stage embryogenesis following in vitro fertilization (IVF)^1-3, its rate in naturally conceived human embryos is unknown. CIN leads to mosaic embryos that contain a combination of genetically normal and abnormal cells, and is significantly higher in in vitro-produced preimplantation embryos as compared to in vivo-conceived preimplantation embryos⁴. Even though embryos with CIN-derived complex aneuploidies may arrest between the cleavage and blastocyst stages of embryogenesis^5,6, a high number of embryos containing abnormal cells can pass this strong selection barrier^7,8. However, neither the prevalence nor extent of CIN during prenatal development and at birth, following IVF treatment, is well understood. Here we profiled the genomic landscape of fetal and placental tissues postpartum from both IVF and naturally conceived children, to investigate the prevalence and persistence of large genetic aberrations that probably arose from IVF-related CIN. We demonstrate that CIN is not preserved at later stages of prenatal development, and that de novo numerical aberrations or large structural DNA imbalances occur at similar rates in IVF and naturally conceived live-born neonates. Our findings affirm that human IVF treatment has no detrimental effect on the chromosomal constitution of fetal and placental lineages.

Advanced liquid biopsy technologies for circulating biomarker detection

Liquid biopsy is a new diagnostic concept that provides important information for monitoring and identifying tumor genomes in body fluid samples. Detection of tumor origin biomolecules like circulating tumor cells (CTCs), circulating tumor specific nucleic acids (circulating tumor DNA (ctDNA), circulating tumor RNA (ctRNA), microRNAs (miRNAs), long non-coding RNAs (lnRNAs)), exosomes, autoantibodies in blood, saliva, stool, urine, etc. enables cancer screening, early stage diagnosis and evaluation of therapy response through minimally invasive means. From reliance on painful and hazardous tissue biopsies or imaging depending on sophisticated equipment, cancer management schemes are witnessing a rapid evolution towards minimally invasive yet highly sensitive liquid biopsy-based tools. Clinical application of liquid biopsy is already paving the way for precision theranostics and personalized medicine. This is achieved especially by enabling repeated sampling, which in turn provides a more comprehensive molecular profile of tumors. On the other hand, integration with novel miniaturized platforms, engineered nanomaterials, as well as electrochemical detection has led to the development of low-cost and simple platforms suited for point-of-care applications. Herein, we provide a comprehensive overview of the biogenesis, significance and potential role of four widely known biomarkers (CTCs, ctDNA, miRNA and exosomes) in cancer diagnostics and therapeutics. Furthermore, we provide a detailed discussion of the inherent biological and technical challenges associated with currently available methods and the possible pathways to overcome these challenges. The recent advances in the application of a wide range of nanomaterials in detecting these biomarkers are also highlighted.

Uncovering low-level mosaicism in human embryonic stem cells using high throughput single cell shallow sequencing

Human pluripotent stem cells (hPSCs) have significant levels of low-grade genetic mosaicism, which commonly used techniques fail to detect in bulk DNA. These copy number variations remain a hurdle for the clinical translation of hPSC, as their effect in vivo ranges from unknown to dangerous, and the ability to detect them will be necessary as the field advances. As such there is need for techniques which can efficiently analyse genetic content in single cells with higher throughput and lower costs. We report here on the use of the Fluidigm C1 single cell WGA platform in combination with shallow whole genome sequencing to analyse the genetic content of single hPSCs. From a hPSC line carrying an isochromosome 20, 56 single cells were analysed and found to carry a total of 50 aberrations, across 23% of cells, which could not be detected by bulk analysis. Aberrations were predominantly segmental gains, with a fewer number of segmental losses and aneuploidies. Interestingly, 40% of the breakpoints seen here correspond to known DNA fragile sites. Our results therefore demonstrate the feasibility of single cell shallow sequencing of hPSC and further expand upon the biological importance and frequency of single cell mosaicism in hPSC.

Non-invasive pre-implantation genetic testing of human embryos: an emerging concept

The accurate genetic screening of pre-implantation embryos currently entails the use of technically challenging and biologically invasive biopsies of the human embryos. Investigating a more conservative sampling approach has emerged as a timely and desired alternative. Circulating cell-free embryonic DNA is present in the blastocoel fluid and spent culture media of blastocysts, and this has lately been sought as an attractive source of genetic information. The genetic analysis of cell-free embryonic DNA has been reported, to be useful in evaluating the genetic constitution of embryos; thus, providing a potential alternative to conventional biopsy-derived pre-implantation genetic testing (PGT). In this review, we have summarized these non-invasive alternative applications of PGT and discussed their current limitations and future clinical implications.

Viral integration drives multifocal HCC during the occult HBV infection

BACKGROUND & AIMS

Although the prognosis of patients with occult hepatitis B virus (HBV) infection (OBI) is usually benign, a small portion may undergo cirrhosis and subsequently hepatocellular carcinoma (HCC). We studied the mechanism of life-long Integration of virus DNA into OBI host's genome, of which may induce hepatocyte transformation.

METHODS

We applied HBV capture sequencing on single cells from an OBI patient who, developed multiple HCC tumors and underwent liver resection in May 2013 at Tongji Hospital in China. Despite with the undetectable virus DNA in serum, we determined the pattern of viral integration in tumor cells and adjacent non-tumor cells and obtained the details of the viral arrangement in host genome, and furthermore the HBV integrated region in cancer genome.

RESULTS

HBV captured sequencing of tissues and individual cells revealed that samples from multiple tumors shared two viral integration sites that could affect three host genes, including CSMD2 on chr1 and MED30/EXT1 on chr8. Whole genome sequencing further indicated one hybrid chromosome formed by HBV integrations between chr1 and chr8 that was shared by multiple tumors. Additional 50 poorly differentiated liver tumors and the paired adjacent non-tumors were evaluated and functional studies suggested up-regulated EXT1 expression promoted HCC growth. We further observed that the most somatic mutations within the tumor cell genome were common among the multiple tumors, suggesting that HBV associated, multifocal HCC is monoclonal in origin.

CONCLUSION

Through analyzing the HBV integration sites in multifocal HCC, our data suggested that the tumor cells were monoclonal in origin and formed in the absence of active viral replication, whereas the affected host genes may subsequently contribute to carcinogenesis.

ChimeraMiner: An Improved Chimeric Read Detection Pipeline and Its Application in Single Cell Sequencing

As the most widely-used single cell whole genome amplification (WGA) approach, multiple displacement amplification (MDA) has a superior performance, due to the high-fidelity and processivity of phi29 DNA polymerase. However, chimeric reads, generated in MDA, cause severe disruption in many single-cell studies. Herein, we constructed ChimeraMiner, an improved chimeric read detection pipeline for analyzing the sequencing data of MDA and classified the chimeric sequences. Two datasets (MDA1 and MDA2) were used for evaluating and comparing the efficiency of ChimeraMiner and previous pipeline. Under the same hardware condition, ChimeraMiner spent only 43.4% (43.8% for MDA1 and 43.0% for MDA2) processing time. Respectively, 24.4 million (6.31%) read pairs out of 773 million reads, and 17.5 million (6.62%) read pairs out of 528 million reads were accurately classified as chimeras by ChimeraMiner. In addition to finding 83.60% (17,639,371) chimeras, which were detected by previous pipelines, ChimeraMiner screened 6,736,168 novel chimeras, most of which were missed by the previous pipeline. Applying in single-cell datasets, all three types of chimera were discovered in each dataset, which introduced plenty of false positives in structural variation (SV) detection. The identification and filtration of chimeras by ChimeraMiner removed most of the false positive SVs (83.8%). ChimeraMiner revealed improved efficiency in discovering chimeric reads, and is promising to be widely used in single-cell sequencing.

Current status of spent embryo media research for preimplantation genetic testing

In recent years, a growing body of literature has emerged investigating the clinical utility of spent embryo media (SEM) for preimplantation genetic testing for aneuploidy (PGT-A) (Hammond et al. in Fertil Steril. 107(1):220-8, 2017; Xu et al. in Proc Natl Acad Sci USA. 113(42):11907-12, 2016; Shamonki et al. in Fertil Steril. 106(6):1312-8, 2016; Feichtinger et al. in Reprod BioMed Online. 34(6):583-9, 2017; Vera-Rodriguez et al. in Hum Reprod. 33(4):745-56, 2018; Kuznyetsov et al. in PLoS One. 13(5):e0197262, 2018; Ho et al. in Fertil Steril. 110(3):467-75, 2018; Capalbo et al. in Fertil Steril. 110(5):870-9, 2018). Most of these studies have reported moderate success rates, suggesting the need for improvements in sensitivity and specificity. The concordance between spent media and embryo biopsy or whole embryo was reported to be between 30.4 and 90%, with 50-70% correlation being the most representative (Xu et al. in Proc Natl Acad Sci USA. 113(42):11907-12, 2016; Shamonki et al. in Fertil Steril. 106(6):1312-8, 2016; Feichtinger et al. in Reprod BioMed Online. 34(6):583-9, 2017; Vera-Rodriguez et al. in Hum Reprod. 33(4):745-56, 2018; Kuznyetsov et al. in PLoS One. 13(5):e0197262, 2018; Ho et al. in Fertil Steril. 110(3):467-75, 2018). Here, we will analyze all spent media testing strategies including SEM collection methods, whole genome amplification (WGA) strategies, chromosome copy number detection, and bioinformatics analysis tools. We will propose improvements to further increase the accuracy and sensitivity of the assay before bringing PGT-A with SEM into the clinical sphere.

Patterns and mechanisms of structural variations in human cancer

Next-generation sequencing technology has enabled the comprehensive detection of genomic alterations in human somatic cells, including point mutations, chromosomal rearrangements, and structural variations (SVs). Using sophisticated bioinformatics algorithms, unbiased catalogs of SVs are emerging from thousands of human cancer genomes for the first time. Via careful examination of SV breakpoints at single-nucleotide resolution as well as local DNA copy number changes, diverse patterns of genomic rearrangements are being revealed. These "SV signatures" provide deep insight into the mutational processes that have shaped genome changes in human somatic cells. This review summarizes the characteristics of recently identified complex SVs, including chromothripsis, chromoplexy, microhomology-mediated breakage-induced replication (MMBIR), and others, to provide a holistic snapshot of the current knowledge on genomic rearrangements in somatic cells.

Detecting Somatic Mutations in Normal Cells

Somatic mutations have been studied extensively in the context of cancer. Recent studies have demonstrated that high-throughput sequencing data can be used to detect somatic mutations in non-tumor cells. Analysis of such mutations allows us to better understand the mutational processes in normal cells, explore cell lineages in development, and examine potential associations with age-related disease. We describe here approaches for characterizing somatic mutations in normal and non-tumor disease tissues. We discuss several experimental designs and common pitfalls in somatic mutation detection, as well as more recent developments such as phasing and linked-read technology. With the dramatically increasing numbers of samples undergoing genome sequencing, bioinformatic analysis will enable the characterization of somatic mutations and their impact on non-cancer tissues.

Circulating tumor cell isolation, culture, and downstream molecular analysis

Circulating tumor cells (CTCs) are a major contributor of cancer metastases and hold a promising prognostic significance in cancer detection. Performing functional and molecular characterization of CTCs provides an in-depth knowledge about this lethal disease. Researchers are making efforts to design devices and develop assays for enumeration of CTCs with a high capture and detection efficiency from whole blood of cancer patients. The existing and on-going research on CTC isolation methods has revealed cell characteristics which are helpful in cancer monitoring and designing of targeted cancer treatments. In this review paper, a brief summary of existing CTC isolation methods is presented. We also discuss methods of detaching CTC from functionalized surfaces (functional assays/devices) and their further use for ex-vivo culturing that aid in studies regarding molecular properties that encourage metastatic seeding. In the clinical applications section, we discuss a number of cases that CTCs can play a key role for monitoring metastases, drug treatment response, and heterogeneity profiling regarding biomarkers and gene expression studies that bring treatment design further towards personalized medicine.

Systematic assessment of the performance of whole-genome amplification for SNP/CNV detection and β-thalassemia genotyping

In this study, we aimed to assess the performance of two whole-genome amplification methods, multiple displacement amplification (MDA), and multiple annealing and looping-based amplification cycle (MALBAC), for β-thalassemia genotyping and single-nucleotide polymorphism (SNP)/copy-number variant (CNV) detection using two DNA sequencing assays. We collected peripheral blood, cell lines, and discarded embryos, and carried out MALBAC and MDA on single-cell and five-cell samples. We detected and statistically analyzed differences in the amplification efficiency, positive predictive value, sensitivity, allele dropout (ADO) rate, SNPs, and CV values between the two methods. Through Sanger sequencing at the single-cell and five-cell levels, we showed that both the amplification rate and ADO rate of MDA were better than those using MALBAC, and the sensitivity and positive predictive value obtained from MDA were higher than those from MALBAC for β-thalassemia genotyping. Using next-generation sequencing (NGS) at the single-cell level, we confirmed that MDA has better properties than MALBAC for SNP detection. However, MALBAC was more stable and homogeneous than MDA using low-depth NGS at the single-cell level for CNV detection. We conclude that MALBAC is the better option for CNV detection, while MDA is better suited for SNV detection.

Evaluation and consequences of heterogeneity in the circulating tumor cell compartment

A growing understanding of the molecular biology of cancer and the identification of specific aberrations driving cancer evolution have led to the development of various targeted agents. Therapeutic decisions concerning these drugs are often guided by single biopsies of the primary tumor. Yet, it is well known that tumors can exhibit significant heterogeneity and change over time as a result of selective pressure. Circulating tumor cells (CTCs) are shed from various tumor sites and are thought to represent the molecular landscape of a patient's overall tumor burden. Moreover, a minimal-invasive liquid biopsy facilitates monitoring of clonal evolution during therapy pressure and disease progression in real-time. While more information becomes available regarding heterogeneity among CTCs, comparison between these studies is needed. In this review, we focus on the genomic and transcriptional heterogeneity found in the CTC compartment, and its significance for clinical decision making.

High Throughput Single Cell RNA Sequencing, Bioinformatics Analysis and Applications

Single cell sequencing (SCS) can be harnessed to acquire the genomes, transcriptomes and epigenomes from individual cells. Next generation sequencing (NGS) technology is the driving force for single cell sequencing. scRNA-seq requires a lengthy pipeline comprising of single cell sorting, RNA extraction, reverse transcription, amplification, library construction, sequencing and subsequent bioinformatic analysis. Computational algorithms are essential to fulfill many tasks of interest using scRNA-seq data. scRNA-seq has already enabled researchers to revisit long-standing questions in cancer biology, including cancer metastasis, heterogeneity and evolution. Circulating Tumor Cells (CTC) are not only an important mechanism for cancer metastasis, but also provide a possibility to diagnose and monitor cancer in a convenient way independent of surgical resection of the cancer.

A short review of variants calling for single-cell-sequencing data with applications

The field of single-cell sequencing is fleetly expanding, and many techniques have been developed in the past decade. With this technology, biologists can study not only the heterogeneity between two adjacent cells in the same tissue or organ, but also the evolutionary relationships and degenerative processes in a single cell. Calling variants is the main purpose in analyzing single cell sequencing (SCS) data. Currently, some popular methods used for bulk-cell-sequencing data analysis are tailored directly to be applied in dealing with SCS data. However, SCS requires an extra step of genome amplification to accumulate enough quantity for satisfying sequencing needs. The amplification yields large biases and thus raises challenge for using the bulk-cell-sequencing methods. In order to provide guidance for the development of specialized analyzed methods as well as using currently developed tools for SNS, this paper aims to bridge the gap. In this paper, we firstly introduced two popular genome amplification methods and compared their capabilities. Then we introduced a few popular models for calling single-nucleotide polymorphisms and copy-number variations. Finally, break-through applications of SNS were summarized to demonstrate its potential in researching cell evolution.

Principles guiding embryo selection following genome-wide haplotyping of preimplantation embryos

STUDY QUESTION

How to select and prioritize embryos during PGD following genome-wide haplotyping?

SUMMARY ANSWER

In addition to genetic disease-specific information, the embryo selected for transfer is based on ranking criteria including the existence of mitotic and/or meiotic aneuploidies, but not carriership of mutations causing recessive disorders.

WHAT IS KNOWN ALREADY

Embryo selection for monogenic diseases has been mainly performed using targeted disease-specific assays. Recently, these targeted approaches are being complemented by generic genome-wide genetic analysis methods such as karyomapping or haplarithmisis, which are based on genomic haplotype reconstruction of cell(s) biopsied from embryos. This provides not only information about the inheritance of Mendelian disease alleles but also about numerical and structural chromosome anomalies and haplotypes genome-wide. Reflections on how to use this information in the diagnostic laboratory are lacking.

STUDY DESIGN, SIZE, DURATION

We present the results of the first 101 PGD cycles (373 embryos) using haplarithmisis, performed in the Centre for Human Genetics, UZ Leuven. The questions raised were addressed by a multidisciplinary team of clinical geneticist, fertility specialists and ethicists.

PARTICIPANTS/MATERIALS, SETTING, METHODS

Sixty-three couples enrolled in the genome-wide haplotyping-based PGD program. Families presented with either inherited genetic variants causing known disorders and/or chromosomal rearrangements that could lead to unbalanced translocations in the offspring.

MAIN RESULTS AND THE ROLE OF CHANCE

Embryos were selected based on the absence or presence of the disease allele, a trisomy or other chromosomal abnormality leading to known developmental disorders. In addition, morphologically normal Day 5 embryos were prioritized for transfer based on the presence of other chromosomal imbalances and/or carrier information.

LIMITATIONS, REASONS FOR CAUTION

Some of the choices made and principles put forward are specific for cleavage-stage-based genetic testing. The proposed guidelines are subject to continuous update based on the accumulating knowledge from the implementation of genome-wide methods for PGD in many different centers world-wide as well as the results of ongoing scientific research.

WIDER IMPLICATIONS OF THE FINDINGS

Our embryo selection principles have a profound impact on the organization of PGD operations and on the information that is transferred among the genetic unit, the fertility clinic and the patients. These principles are also important for the organization of pre- and post-counseling and influence the interpretation and reporting of preimplantation genotyping results. As novel genome-wide approaches for embryo selection are revolutionizing the field of reproductive genetics, national and international discussions to set general guidelines are warranted.

STUDY FUNDING/COMPETING INTEREST(S)

The European Union's Research and Innovation funding programs FP7-PEOPLE-2012-IAPP SARM: 324509 and Horizon 2020 WIDENLIFE: 692065 to J.R.V., T.V., E.D. and M.Z.E. J.R.V., T.V. and M.Z.E. have patents ZL910050-PCT/EP2011/060211-WO/2011/157846 ('Methods for haplotyping single cells') with royalties paid and ZL913096-PCT/EP2014/068315-WO/2015/028576 ('Haplotyping and copy-number typing using polymorphic variant allelic frequencies') with royalties paid, licensed to Cartagenia (Agilent technologies). J.R.V. also has a patent ZL91 2076-PCT/EP20 one 3/070858 ('High throughout genotyping by sequencing') with royalties paid.

TRIAL REGISTRATION NUMBER

N/A.

Principles of Reconstructing the Subclonal Architecture of Cancers

Most cancers evolve from a single founder cell through a series of clonal expansions that are driven by somatic mutations. These clonal expansions can lead to several coexisting subclones sharing subsets of mutations. Analysis of massively parallel sequencing data can infer a tumor's subclonal composition through the identification of populations of cells with shared mutations. We describe the principles that underlie subclonal reconstruction through single nucleotide variants (SNVs) or copy number alterations (CNAs) from bulk or single-cell sequencing. These principles include estimating the fraction of tumor cells for SNVs and CNAs, performing clustering of SNVs from single- and multisample cases, and single-cell sequencing. The application of subclonal reconstruction methods is providing key insights into tumor evolution, identifying subclonal driver mutations, patterns of parallel evolution and differences in mutational signatures between cellular populations, and characterizing the mechanisms of therapy resistance, spread, and metastasis.

The performance of MALBAC and MDA methods in the identification of concurrent mutations and aneuploidy screening to diagnose beta-thalassaemia disorders at the single- and multiple-cell levels

AIM

To select an optimal whole-genome amplification (WGA) method to improve the efficiency of the preimplantation genetic diagnosis and screening (PGD/PGS) of beta-thalassaemia disorders.

METHODS

Fifty-seven fibroblast samples with defined beta-thalassaemia variations and forty-eight single-blastomere samples were amplified from single-, two-, and five-cell samples by multiple annealing and looping-based amplification cycles (MALBAC) and the multiple displacement amplification (MDA) method. Low-depth, high-throughput sequencing was performed to evaluate and compare the coefficiencies of the chromosomal copy number variation (CNV) detection rate and the allele dropout (ADO) rate between these two methods.

RESULTS

At the single-cell level, the success rates of the CNV detection in the fibroblast samples were 100% in the MALBAC group and 91.67% in the MDA group; the coefficient of variation in the CNV detection in the MALBAC group was significantly superior to that in the MDA group (0.15 vs 0.37). The total ADO rate in the HBB allele detection was 4.55% in the MALBAC group, which was significantly lower than the 22.5% rate observed in the MDA group. However, when five or more cells were used as the starting template, the ADO rate significantly decreased, and these two methods did not differ significantly.

CONCLUSIONS

For the genetic diagnosis of HBB gene variation at the single-cell level, MALBAC is a more suitable method due to its higher level of uniformity and specificity. When five or more cells are used as the starting template, both methods exhibit similar efficiency, increased accuracy, and a similar success rate in PGD/PGS.

Prenatal and pre-implantation genetic diagnosis

The past decade has seen the development of technologies that have revolutionized prenatal genetic testing; that is, genetic testing from conception until birth. Genome-wide single-cell arrays and high-throughput sequencing analyses are dramatically increasing our ability to detect embryonic and fetal genetic lesions, and have substantially improved embryo selection for in vitro fertilization (IVF). Moreover, both invasive and non-invasive mutation scanning of the genome are helping to identify the genetic causes of prenatal developmental disorders. These advances are changing clinical practice and pose novel challenges for genetic counselling and prenatal care.

Single-cell template strand sequencing by Strand-seq enables the characterization of individual homologs

The ability to distinguish between genome sequences of homologous chromosomes in single cells is important for studies of copy-neutral genomic rearrangements (such as inversions and translocations), building chromosome-length haplotypes, refining genome assemblies, mapping sister chromatid exchange events and exploring cellular heterogeneity. Strand-seq is a single-cell sequencing technology that resolves the individual homologs within a cell by restricting sequence analysis to the DNA template strands used during DNA replication. This protocol, which takes up to 4 d to complete, relies on the directionality of DNA, in which each single strand of a DNA molecule is distinguished based on its 5'-3' orientation. Culturing cells in a thymidine analog for one round of cell division labels nascent DNA strands, allowing for their selective removal during genomic library construction. To preserve directionality of template strands, genomic preamplification is bypassed and labeled nascent strands are nicked and not amplified during library preparation. Each single-cell library is multiplexed for pooling and sequencing, and the resulting sequence data are aligned, mapping to either the minus or plus strand of the reference genome, to assign template strand states for each chromosome in the cell. The major adaptations to conventional single-cell sequencing protocols include harvesting of daughter cells after a single round of BrdU incorporation, bypassing of whole-genome amplification, and removal of the BrdU⁺ strand during Strand-seq library preparation. By sequencing just template strands, the structure and identity of each homolog are preserved.

New protocol based on massive parallel sequencing for aneuploidy screening of preimplantation human embryos

Novel next-generation sequencing procedures have rapidly emerged into the preimplantation genetic screening framework. This work presents the design and validation of a new low-coverage whole-genome sequencing assay for aneuploidy detection in single blastomeres and trophectodermal samples from preimplantation embryos. The validation ensures analytical sensitivity, specificity, robustness, precision, limit of detection, resolution, and reproducibility. Specific parameters to measure the performance are defined, and the results are compared with a standardized array-based method to stablish the concordance. From the single cell genomics point of view, the main novelties are the length of reads of the libraries (150 nucleotides) together with a paired-end strategy and the design of an original algorithm and copy number viewer. A total of 129 samples were included in six experimental runs using a MiSeq Illumina platform. Samples included: single amniocytes, single blastomeres (cleavage-stage embryos), trophectoderm samples (blastocyst), and diluted DNA. Sensitivity and specificity were calculated per chromosome yielding 96% and 99%, respectively. The percentage of concordant samples was 98.2% and all of the aneuploid samples were confirmed. In conclusion, the validation yields highly reliable and reproducible results, representing an accurate and cost-effective strategy for the routine detection of aneuploidy in human embryos.

Advances in understanding tumour evolution through single-cell sequencing

The mutational heterogeneity observed within tumours poses additional challenges to the development of effective cancer treatments. A thorough understanding of a tumour's subclonal composition and its mutational history is essential to open up the design of treatments tailored to individual patients. Comparative studies on a large number of tumours permit the identification of mutational patterns which may refine forecasts of cancer progression, response to treatment and metastatic potential. The composition of tumours is shaped by evolutionary processes. Recent advances in next-generation sequencing offer the possibility to analyse the evolutionary history and accompanying heterogeneity of tumours at an unprecedented resolution, by sequencing single cells. New computational challenges arise when moving from bulk to single-cell sequencing data, leading to the development of novel modelling frameworks. In this review, we present the state of the art methods for understanding the phylogeny encoded in bulk or single-cell sequencing data, and highlight future directions for developing more comprehensive and informative pictures of tumour evolution. This article is part of a Special Issue entitled: Evolutionary principles - heterogeneity in cancer?, edited by Dr. Robert A. Gatenby.

Small chromosomal regions position themselves autonomously according to their chromatin class

The spatial arrangement of chromatin is linked to the regulation of nuclear processes. One striking aspect of nuclear organization is the spatial segregation of heterochromatic and euchromatic domains. The mechanisms of this chromatin segregation are still poorly understood. In this work, we investigated the link between the primary genomic sequence and chromatin domains. We analyzed the spatial intranuclear arrangement of a human artificial chromosome (HAC) in a xenospecific mouse background in comparison to an orthologous region of native mouse chromosome. The two orthologous regions include segments that can be assigned to three major chromatin classes according to their gene abundance and repeat repertoire: (1) gene-rich and SINE-rich euchromatin; (2) gene-poor and LINE/LTR-rich heterochromatin; and (3) gene-depleted and satellite DNA-containing constitutive heterochromatin. We show, using fluorescence in situ hybridization (FISH) and 4C-seq technologies, that chromatin segments ranging from 0.6 to 3 Mb cluster with segments of the same chromatin class. As a consequence, the chromatin segments acquire corresponding positions in the nucleus irrespective of their chromosomal context, thereby strongly suggesting that this is their autonomous property. Interactions with the nuclear lamina, although largely retained in the HAC, reveal less autonomy. Taken together, our results suggest that building of a functional nucleus is largely a self-organizing process based on mutual recognition of chromosome segments belonging to the major chromatin classes.

Whole-genome single-cell copy number profiling from formalin-fixed paraffin-embedded samples

A substantial proportion of tumors consist of genotypically distinct subpopulations of cancer cells. This intratumor genetic heterogeneity poses a substantial challenge for the implementation of precision medicine. Single-cell genomics constitutes a powerful approach to resolve complex mixtures of cancer cells by tracing cell lineages and discovering cryptic genetic variations that would otherwise be obscured in tumor bulk analyses. Because of the chemical alterations that result from formalin fixation, single-cell genomic approaches have largely remained limited to fresh or rapidly frozen specimens. Here we describe the development and validation of a robust and accurate methodology to perform whole-genome copy-number profiling of single nuclei obtained from formalin-fixed paraffin-embedded clinical tumor samples. We applied the single-cell sequencing approach described here to study the progression from in situ to invasive breast cancer, which revealed that ductal carcinomas in situ show intratumor genetic heterogeneity at diagnosis and that these lesions may progress to invasive breast cancer through a variety of evolutionary processes.

Building a lineage from single cells: genetic techniques for cell lineage tracking

Resolving lineage relationships between cells in an organism is a fundamental interest of developmental biology. Furthermore, investigating lineage can drive understanding of pathological states, including cancer, as well as understanding of developmental pathways that are amenable to manipulation by directed differentiation. Although lineage tracking through the injection of retroviral libraries has long been the state of the art, a recent explosion of methodological advances in exogenous labelling and single-cell sequencing have enabled lineage tracking at larger scales, in more detail, and in a wider range of species than was previously considered possible. In this Review, we discuss these techniques for cell lineage tracking, with attention both to those that trace lineage forwards from experimental labelling, and those that trace backwards across the life history of an organism.

Single-Cell Multiomics: Multiple Measurements from Single Cells

Single-cell sequencing provides information that is not confounded by genotypic or phenotypic heterogeneity of bulk samples. Sequencing of one molecular type (RNA, methylated DNA or open chromatin) in a single cell, furthermore, provides insights into the cell's phenotype and links to its genotype. Nevertheless, only by taking measurements of these phenotypes and genotypes from the same single cells can such inferences be made unambiguously. In this review, we survey the first experimental approaches that assay, in parallel, multiple molecular types from the same single cell, before considering the challenges and opportunities afforded by these and future technologies.

Unambiguous inference that a cellular phenotype is caused by a genotype can only be achieved by their measurement from the same single cell.

Estimating RNA and DNA copy number abundance in single cells is now possible using a variety of experimental approaches.

Parallel measurement of single-cell epigenomes and transcriptomes provides further insight into the regulation of cellular identity and phenotypes.

Parallel measurement of single-cell transcriptomes and protein abundance (by FACS, proximity ligation assays/PEA or mass cytometry) allows insight into expression dynamics.

Our understanding of cancer progression and diversity is likely to be advanced greatly by the multiomics investigation of single cells, as is our understanding of normal developmental and other disease processes.

Ongoing technological advances will see improvements in the coverage, sensitivity of multiomics approaches, as well the number of analytes that can be surveyed in parallel.

Proof of concept: preimplantation genetic screening without embryo biopsy through analysis of cell-free DNA in spent embryo culture media

OBJECTIVE

To assess whether preimplantation genetic screening (PGS) is possible by testing for free embryonic DNA in spent IVF media from embryos undergoing trophectoderm biopsy.

DESIGN

Prospective cohort analysis.

SETTING

Academic fertility center.

PATIENT(S)

Seven patients undergoing IVF and 57 embryos undergoing trophectoderm biopsy for PGS.

INTERVENTION(S)

On day 3 of development, each embryo was placed in a separate media droplet. All biopsied embryos received a PGS result by array comparative genomic hybridization. Preimplantation genetic screening was performed on amplified DNA extracted from media and results were compared with PGS results for the corresponding biopsy.

MAIN OUTCOME MEASURE(S)

[1] Presence of DNA in spent IVF culture media. [2] Correlation between genetic screening result from spent media and corresponding biopsy.

RESULT(S)

Fifty-five samples had detectable DNA ranging from 2-642 ng/μL after a 2-hour amplification. Six samples with the highest DNA levels underwent PGS, rendering one result with a derivative log ratio SD (DLRSD) of <0.85 (a quality control metric of oligonucleotide array comparative genomic hybridization). The fluid sample and trophectoderm results were identical demonstrating (45XY, -13). Three samples were reamplified 1 hour later and tested showing improving DLRSD. One of the three samples with a DLRSD of 0.85 demonstrated (46XY), consistent with the biopsy. Overnight DNA amplification showed DNA in all samples.

CONCLUSION(S)

We demonstrate two novel findings: the presence of free embryonic DNA in spent media and a result that is consistent with trophectoderm biopsy. Improvements in DNA collection, amplification, and testing may allow for PGS without biopsy in the future.

Intratumor Heterogeneity in Breast Cancer

Intratumor heterogeneity is the main obstacle to effective cancer treatment and personalized medicine. Both genetic and epigenetic sources of intratumor heterogeneity are well recognized and several technologies have been developed for their characterization. With the technological advances in recent years, investigators are now elucidating intratumor heterogeneity at the single cell level and in situ. However, translating the accumulated knowledge about intratumor heterogeneity to clinical practice has been slow. We are certain that better understanding of the composition and evolution of tumors during disease progression and treatment will improve cancer diagnosis and the design of therapies. Here we review some of the most important considerations related to intratumor heterogeneity. We discuss both genetic and epigenetic sources of intratumor heterogeneity and review experimental approaches that are commonly used to quantify it. We also discuss the impact of intratumor heterogeneity on cancer diagnosis and treatment and share our perspectives on the future of this field.

Comparison of three whole genome amplification methods for detection of genomic aberrations in single cells

OBJECTIVE

Detection of genomic copy number abnormalities in a single cell using array comparative genomic hybridization (CGH) offers a promising non-invasive alternative for prenatal diagnosis. Our objective was to compare three commercially available whole-genome amplification (WGA) kits for their capacity to produce high quality DNA from single cells that is suitable for both molecular genotyping and array CGH.

METHODS

We examined kit performance on unfixed, fixed and fixed/permeabilized lymphoblastoid cells. Molecular genotyping methods were used to evaluate the fidelity of amplified DNA for genomic profiling, while array CGH was used to assess copy number from single cells harboring trisomy 21, a DiGeorge syndrome deletion, a CMT1A duplication or a MECP2 duplication.

RESULTS

Molecular genotyping was achieved from single cells but performance varied between WGA kits. Furthermore, we consistently detected a dosage difference in sex chromosomes for gender mismatched hybridizations and for chromosome 21 in trisomy 21 cells. The 2.5 Mb DiGeorge syndrome deletion was also detected using all three WGA platforms, whereas the 1.3 Mb CMT1A and the 0.6 Mb MECP2 duplications were not consistently detected.

CONCLUSION

These data suggest that single cell molecular genotyping and copy number analysis can be accomplished when WGA conditions are optimized. © 2016 John Wiley & Sons, Ltd.

Comparative study of whole genome amplification and next generation sequencing performance of single cancer cells

BACKGROUND

Whole genome amplification (WGA) is required for single cell genotyping. Effectiveness of currently available WGA technologies in combination with next generation sequencing (NGS) and material preservation is still elusive.

RESULTS

In respect to the accuracy of SNP/mutation, indel, and copy number aberrations (CNA) calling, the HiSeq2000 platform outperformed IonProton in all aspects. Furthermore, more accurate SNP/mutation and indel calling was demonstrated using single tumor cells obtained from EDTA-collected blood in respect to CellSave-preserved blood, whereas CNA analysis in our study was not detectably affected by fixation. Although MDA-based WGA yielded the highest DNA amount, DNA quality was not adequate for downstream analysis. PCR-based WGA demonstrates superiority over MDA-PCR combining technique for SNP and indel analysis in single cells. However, SNP calling performance of MDA-PCR WGA improves with increasing amount of input DNA, whereas CNA analysis does not. The performance of PCR-based WGA did not significantly improve with increase of input material. CNA profiles of single cells, amplified with MDA-PCR technique and sequenced on both HiSeq2000 and IonProton platforms, resembled unamplified DNA the most.

MATERIALS AND METHODS

We analyzed the performance of PCR-based, multiple-displacement amplification (MDA)-based, and MDA-PCR combining WGA techniques (WGA kits Ampli1, REPLI-g, and PicoPlex, respectively) on single and pooled tumor cells obtained from EDTA- and CellSave-preserved blood and archival material. Amplified DNA underwent exome-Seq with the Illumina HiSeq2000 and ThermoFisher IonProton platforms.

CONCLUSION

We demonstrate the feasibility of single cell genotyping of differently preserved material, nevertheless, WGA and NGS approaches have to be chosen carefully depending on the study aims.

Robust high-performance nanoliter-volume single-cell multiple displacement amplification on planar substrates

The genomes of large numbers of single cells must be sequenced to further understanding of the biological significance of genomic heterogeneity in complex systems. Whole genome amplification (WGA) of single cells is generally the first step in such studies, but is prone to nonuniformity that can compromise genomic measurement accuracy. Despite recent advances, robust performance in high-throughput single-cell WGA remains elusive. Here, we introduce droplet multiple displacement amplification (MDA), a method that uses commercially available liquid dispensing to perform high-throughput single-cell MDA in nanoliter volumes. The performance of droplet MDA is characterized using a large dataset of 129 normal diploid cells, and is shown to exceed previously reported single-cell WGA methods in amplification uniformity, genome coverage, and/or robustness. We achieve up to 80% coverage of a single-cell genome at 5× sequencing depth, and demonstrate excellent single-nucleotide variant (SNV) detection using targeted sequencing of droplet MDA product to achieve a median allelic dropout of 15%, and using whole genome sequencing to achieve false and true positive rates of 9.66 × 10(-6) and 68.8%, respectively, in a G1-phase cell. We further show that droplet MDA allows for the detection of copy number variants (CNVs) as small as 30 kb in single cells of an ovarian cancer cell line and as small as 9 Mb in two high-grade serous ovarian cancer samples using only 0.02× depth. Droplet MDA provides an accessible and scalable method for performing robust and accurate CNV and SNV measurements on large numbers of single cells.