Whole genome amplification using a degenerate oligonucleotide primer allows hundreds of genotypes to be performed on less than one nanogram of genomic DNA

Advances in single-cell omics and multiomics for high-resolution molecular profiling

Single-cell omics technologies have revolutionized molecular profiling by providing high-resolution insights into cellular heterogeneity and complexity. Traditional bulk omics approaches average signals from heterogeneous cell populations, thereby obscuring important cellular nuances. Single-cell omics studies enable the analysis of individual cells and reveal diverse cell types, dynamic cellular states, and rare cell populations. These techniques offer unprecedented resolution and sensitivity, enabling researchers to unravel the molecular landscape of individual cells. Furthermore, the integration of multimodal omics data within a single cell provides a comprehensive and holistic view of cellular processes. By combining multiple omics dimensions, multimodal omics approaches can facilitate the elucidation of complex cellular interactions, regulatory networks, and molecular mechanisms. This integrative approach enhances our understanding of cellular systems, from development to disease. This review provides an overview of the recent advances in single-cell and multimodal omics for high-resolution molecular profiling. We discuss the principles and methodologies for representatives of each omics method, highlighting the strengths and limitations of the different techniques. In addition, we present case studies demonstrating the applications of single-cell and multimodal omics in various fields, including developmental biology, neurobiology, cancer research, immunology, and precision medicine.

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.

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.

Advances in Single-Cell Sequencing Technology and Its Application in Poultry Science

Single-cell sequencing (SCS) uses a single cell as the research material and involves three dimensions: genes, phenotypes and cell biological mechanisms. This type of research can locate target cells, analyze the dynamic changes in the target cells and the relationships between the cells, and pinpoint the molecular mechanism of cell formation. Currently, a common problem faced by animal husbandry scientists is how to apply existing science and technology to promote the production of high-quality livestock and poultry products and to breed livestock for disease resistance; this is also a bottleneck for the sustainable development of animal husbandry. In recent years, although SCS technology has been successfully applied in the fields of medicine and bioscience, its application in poultry science has been rarely reported. With the sustainable development of science and technology and the poultry industry, SCS technology has great potential in the application of poultry science (or animal husbandry). Therefore, it is necessary to review the innovation of SCS technology and its application in poultry science. This article summarizes the current main technical methods of SCS and its application in poultry, which can provide potential references for its future applications in precision breeding, disease prevention and control, immunity, and cell identification.

New Perspectives for Whole Genome Amplification in Forensic STR Analysis

Modern PCR-based analytical techniques have reached sensitivity levels that allow for obtaining complete forensic DNA profiles from even tiny traces containing genomic DNA amounts as small as 125 pg. Yet these techniques have reached their limits when it comes to the analysis of traces such as fingerprints or single cells. One suggestion to overcome these limits has been the usage of whole genome amplification (WGA) methods. These methods aim at increasing the copy number of genomic DNA and by this means generate more template DNA for subsequent analyses. Their application in forensic contexts has so far remained mostly an academic exercise, and results have not shown significant improvements and even have raised additional analytical problems. Until very recently, based on these disappointments, the forensic application of WGA seems to have largely been abandoned. In the meantime, however, novel improved methods are pointing towards a perspective for WGA in specific forensic applications. This review article tries to summarize current knowledge about WGA in forensics and suggests the forensic analysis of single-donor bioparticles and of single cells as promising applications.

Whole Genome Amplification in Preimplantation Genetic Testing in the Era of Massively Parallel Sequencing

Successful whole genome amplification (WGA) is a cornerstone of contemporary preimplantation genetic testing (PGT). Choosing the most suitable WGA technique for PGT can be particularly challenging because each WGA technique performs differently in combination with different downstream processing and detection methods. The aim of this review is to provide insight into the performance and drawbacks of DOP-PCR, MDA and MALBAC, as well as the hybrid WGA techniques most widely used in PGT. As the field of PGT is moving towards a wide adaptation of comprehensive massively parallel sequencing (MPS)-based approaches, we especially focus our review on MPS parameters and detection opportunities of WGA-amplified material, i.e., mappability of reads, uniformity of coverage and its influence on copy number variation analysis, and genomic coverage and its influence on single nucleotide variation calling. The ability of MDA-based WGA solutions to better cover the targeted genome and the ability of PCR-based solutions to provide better uniformity of coverage are highlighted. While numerous comprehensive PGT solutions exploiting different WGA types and adjusted bioinformatic pipelines to detect copy number and single nucleotide changes are available, the ones exploiting MDA appear more advantageous. The opportunity to fully analyse the targeted genome is influenced by the MPS parameters themselves rather than the solely chosen WGA.

Assessment of Multiple Annealing and Looping-Based Amplification Cycle-Based Whole-Genome Amplification for Short Tandem Repeat Genotyping of Low Copy Number-DNA

Aim: A common problem in forensic practice is the lack of sufficient amounts of good quality genomic DNA. A possible solution is the amplification of the available genomic DNA before locus-specific polymerase chain reaction (PCR) analysis. The aim of this study was to evaluate multiple annealing and looping-based amplification cycle (MALBAC)-based whole-genome amplification (WGA) for short tandem repeat (STR) genotyping of low copy number DNA (LCN-DNA). Materials and Methods: DNA isolated from five blood samples was quantified and diluted to 250, 150, 100, 50, 25, and 5 pg/μL. After preamplification with MALBAC, WGA products were quantified. PCR-STR genotyping was performed in triplicate using dilution or purification-treated WGA products for each level of DNA. STR profiles were analyzed and compared with that from non-WGA DNA. Results: The purification treatment performed better than dilution of the MALBAC-based WGA products. Compared with the non-WGA DNA, both the average number and peak heights of correct alleles were significantly improved after preamplification with the MALBAC-based WGA at DNA inputs of ≤50 pg. Like other WGA methods, allele dropout and allele drop-in were observed in the profiling results for many samples. Conclusions: MALBAC shows great potential in LCN-DNA analysis and could find broader application in the fields of forensics and genetics.

Isolation and sequencing of a single copy of an introgressed chromosome from a complex genome for gene and SNP identification

This manuscript describes the identification, isolation and sequencing of a single chromosome containing high value resistance genes from a complex polyploid where sequencing the whole genome is too costly. The large complex genomes of many crops constrain the use of new technologies for genome-assisted selection and genetic improvement. One method to simplify a genome is to break it into individual chromosomes by flow cytometry; however, in many crop species most chromosomes cannot be isolated individually. Flow sorting of a single copy of a chromosome has been developed in wheat, and here we demonstrate its use to identify markers of interest in an Erianthus/Sacchurum hybrid. Erianthus/Saccharum hybrids are of interest because Erianthus is known to be highly resistant to soil borne diseases which cause extensive sugarcane yield losses in Australia. Sugarcane (Saccharum) cultivars are autopolyploids with a highly complex genome and over 100 chromosomes. Flow cytometry for sugarcane, as in most crops, does not resolve individual chromosomes to a karyotype peak for sorting. To isolate a single chromosome, we used genomic in situ hybridization (GISH) to identify the flow karyotype region containing the Erianthus chromosomes, flow sorted single chromosomes from this region, PCR screened for the Erianthus chromosomes and sequenced them. One Erianthus chromosome amplified and sequenced well, and from this data we could identify 57 resistant type genes and SNPs in nearly half of these genes. We developed KASP SNP assays and demonstrated that the identified SNP markers segregated as expected in a small introgression population. The pipeline we developed here to flow sort and sequence single chromosomes could be used in any crop with a large complex genome to rapidly discover and develop markers to important loci.

Recent advances and application of whole genome amplification in molecular diagnosis and medicine

Whole genome amplification (WGA) is a technology for non-selective amplification of the whole genome sequence, first appearing in 1992. Its primary purpose is to amplify and reflect the whole genome of trace tissues and single cells without sequence bias and to provide sufficient DNA template for subsequent multigene and multilocus analysis, along with comprehensive genome research. WGA provides a method to obtain a large amount of genetic information from a small amount of DNA and provides a valuable tool for preserving limited samples in molecular biology. WGA technology is especially suitable for forensic identification and genetic disease research, along with new technologies such as next-generation sequencing (NGS). In addition, WGA is also widely used in single-cell sequencing. Due to the small amount of DNA in a single cell, it is often unable to meet the amount of samples needed for sequencing, so WGA is generally used to achieve the amplification of trace samples. This paper reviews WGA methods based on different principles, summarizes both amplification principle and amplification quality, and discusses the application prospects and challenges of WGA technology in molecular diagnosis and medicine.

Multiplexed detection of bacterial nucleic acids using Cas13 in droplet microarrays

Rapid and accurate diagnosis of infections is fundamental to individual patient care and public health management. Nucleic acid detection methods are critical to this effort, but are limited either in the breadth of pathogens targeted or by the expertise and infrastructure required. We present here a high-throughput system that enables rapid identification of bacterial pathogens, bCARMEN, which utilizes: (1) modular CRISPR-Cas13-based nucleic acid detection with enhanced sensitivity and specificity; and (2) a droplet microfluidic system that enables thousands of simultaneous, spatially multiplexed detection reactions at nanoliter volumes; and (3) a novel preamplification strategy that further enhances sensitivity and specificity. We demonstrate bCARMEN is capable of detecting and discriminating 52 clinically relevant bacterial species and several key antibiotic resistance genes. We further develop a simple proof of principle workflow using stabilized reagents and cell phone camera optical readout, opening up the possibility of a rapid point-of-care multiplexed bacterial pathogen identification and antibiotic susceptibility testing.

Refining the evolutionary time machine: An assessment of whole genome amplification using single historical Daphnia eggs

Whole genome sequencing is instrumental for the study of genome variation in natural populations, delivering important knowledge on genomic modifications and potential targets of natural selection at the population level. Large dormant eggbanks of aquatic invertebrates such as the keystone herbivore Daphnia, a microcrustacean widespread in freshwater ecosystems, provide detailed sedimentary archives to study genomic processes over centuries. To overcome the problem of limited DNA amounts in single Daphnia dormant eggs, we developed an optimized workflow for whole genome amplification (WGA), yielding sufficient amounts of DNA for downstream whole genome sequencing of individual historical eggs, including polyploid lineages. We compare two WGA kits, applied to recently produced Daphnia magna dormant eggs from laboratory cultures, and to historical dormant eggs of Daphnia pulicaria collected from Arctic lake sediment between 10 and 300 years old. Resulting genome coverage breadth in most samples was ~70%, including those from >100-year-old isolates. Sequence read distribution was highly correlated among samples amplified with the same kit, but less correlated between kits. Despite this, a high percentage of genomic positions with single nucleotide polymorphisms in one or more samples (maximum of 74% between kits, and 97% within kits) were recovered at a depth required for genotyping. As a by-product of sequencing we obtained 100% coverage of the mitochondrial genomes even from the oldest isolates (~300 years). The mitochondrial DNA provides an additional source for evolutionary studies of these populations. We provide an optimized workflow for WGA followed by whole genome sequencing including steps to minimize exogenous DNA.

Successful Pregnancy Following Preimplantation Genetic Diagnosis of Adrenoleukodystrophy by Detection of Mutation on the ABCD1 Gene

Background

Adrenoleukodystrophy (ALD) is a rare sex-linked recessive disorder that disrupts adrenal gland function and the white matter of the nervous system. According to recent epidemiological statistics, up to this moment, the disease is the most recorded peroxisomal disorder. ABCD1 is a gene related to ALD, with more than 850 unique mutations have been reported. Early diagnosis of the disease would help to consult families with ALD to plan for interventions to prevent passing along the pathogenic mutations to their children.

Material and Methods

A heterozygous ABCD1 gene mutation related to ALD found in a Vietnamese woman was used to design primers for the polymerase chain reaction (PCR) to amplify the segment spanning the mutation. Then, combining sequencing methods for the PCR products, especially Sanger sequencing and next-generation sequencing (NGS), a protocol was developed to detect mutations on the ABCD1 gene to apply for the DNA samples of in-vitro fertilization (IVF) embryos biopsied at the blastocyst stage to screen for pathogenic alleles.

Results

The established protocol for PGD of ALD detected mutant alleles in 5/8 embryos (62.5%), while the remaining 3 embryos (37.5%) did not carry any mutation. One of the 3 embryos was transferred, and a healthy female baby was born after a full-term pregnancy.

Conclusion

The developed protocol was helpful for the preimplantation genetic diagnosis process to help families with the monogenic disease of ALD but wish to have healthy children.

ChromInst: A single cell sequencing technique to accomplish pre-implantation comprehensive chromosomal screening overnight

Next Generation Sequencing (NGS) is a powerful tool getting into the field of clinical examination. Its preliminary application in pre-implantation comprehensive chromosomal screening (PCCS) of assisted reproduction (test-tube baby) has shown encouraging outcomes that improves the success rate of in vitro fertilization. However, the conventional NGS library construction is time consuming. In addition with the whole genome amplification (WGA) procedure in prior, makes the single cell NGS assay hardly be accomplished within an adequately short turnover time in supporting fresh embryo implantation. In this work, we established a concise single cell sequencing protocol, ChromInst, in which the single cell WGA and NGS library construction were integrated into a two-step PCR procedure of ~ 2.5hours reaction time. We then validated the feasibility of ChromInst for overnight PCCS assay by examining 14 voluntary donated embryo biopsy samples in a single sequencing run of Miseq with merely 13M reads production. The good compatibility of ChromInst with the restriction of Illumina sequencing technique along with the good library yield uniformity resulted superior data usage efficiency and reads distribution evenness that ensures precisely distinguish of 6 normal embryos from 8 abnormal one with variable chromosomal aneuploidy. The superior succinctness and effectiveness of this protocol permits its utilization in other time limited single cell NGS applications.

Multiple Displacement Amplification as a Solution for Low Copy Number Plasmid Sequencing

Plasmids play a major role in bacterial adaptation to environmental stress and often contribute to antibiotic resistance and disease virulence. Although the complete sequence of each plasmid is essential for studying plasmid biology, most antibiotic resistance and virulence plasmids in Salmonella are present only in a low copy number, making extraction and sequencing difficult. Long read sequencing technologies require higher concentrations of DNA to provide optimal results. To resolve this problem, we assessed the sufficiency of multiple displacement amplification (MDA) for replicating Salmonella plasmid DNA to a satisfactory concentration for accurate sequencing and multiplexing. Nine Salmonella enterica isolates, representing nine different serovars carrying plasmids for which sequence data are already available at NCBI, were cultured and their plasmids isolated using an alkaline lysis extraction protocol. We then used the Phi29 polymerase to perform MDA, thereby obtaining enough plasmid DNA for long read sequencing. These amplified plasmids were multiplexed and sequenced on one single molecule, real-time (SMRT) cell with the Pacific Biosciences (Pacbio) Sequel sequencer. We were able to close all Salmonella plasmids (sizes ranged from 38 to 166 Kb) with sequencing coverage from 24 to 2,582X. This protocol, consisting of plasmid isolation, MDA, and multiplex sequencing, is an effective and fast method for closing high-molecular weight and low-copy-number plasmids. This high throughput protocol reduces the time and cost of plasmid closure.

Methods and platforms for analysis of nucleic acids from single-cell based on microfluidics

Single-cell nucleic acid analysis aims at discovering the genetic differences between individual cells which is well known as the cellular heterogeneity. This technology facilitates cancer diagnosis, stem cell research, immune system analysis, and other life science applications. The conventional platforms for single-cell nucleic acid analysis more rely on manual operation or bulky devices. Recently, the emerging microfluidic technology has provided a perfect platform for single-cell nucleic acid analysis with the characteristic of accurate and automatic single-cell manipulation. In this review, we briefly summarized the procedure of single-cell nucleic acid analysis including single-cell isolation, single-cell lysis, nucleic acid amplification, and genetic analysis. And then, three representative microfluidic platforms for single-cell nucleic acid analysis are concluded as valve-, microwell-, and droplet-based platforms. Furthermore, we described the state-of-the-art integrated single-cell nucleic acid analysis systems based on the three platforms. Finally, the future development and challenges of microfluidics-based single-cell nucleic acid analysis are discussed as well.

Disjunction between canola distribution and the genetic structure of its recently described pest, the canola flower midge (Contarinia brassicola)

Population genomics is a useful tool to support integrated pest management as it can elucidate population dynamics, demography, and histories of invasion. Here, we use a restriction site-associated DNA sequencing approach combined with whole-genome amplification (WGA) to assess genomic population structure of a newly described pest of canola, the diminutive canola flower midge, Contarinia brassicola. Clustering analyses recovered little geographic structure across the main canola production region but differentiated several geographically disparate populations at edges of the agricultural zone. Given a lack of alternative hypotheses for this pattern, we suggest these data support alternative hosts for this species and thus our canola-centric view of this midge as a pest has limited our understanding of its biology. These results speak to the need for increased surveying efforts across multiple habitats and other potential hosts within Brassicaceae to improve both our ecological and evolutionary knowledge of this species and contribute to effective management strategies. We additionally found that use of WGA prior to library preparation was an effective method for increasing DNA quantity of these small insects prior to restriction site-associated DNA sequencing and had no discernible impact on genotyping consistency for population genetic analysis; WGA is therefore likely to be tractable for other similar studies that seek to randomly sample markers across the genome in small organisms.

SCELLECTOR: ranking amplification bias in single cells using shallow sequencing

Background

The study of mosaic mutation is important since it has been linked to cancer and various disorders. Single cell sequencing has become a powerful tool to study the genome of individual cells for the detection of mosaic mutations. The amount of DNA in a single cell needs to be amplified before sequencing and multiple displacement amplification (MDA) is widely used owing to its low error rate and long fragment length of amplified DNA. However, the phi29 polymerase used in MDA is sensitive to template fragmentation and presence of sites with DNA damage that can lead to biases such as allelic imbalance, uneven coverage and over representation of C to T mutations. It is therefore important to select cells with uniform amplification to decrease false positives and increase sensitivity for mosaic mutation detection.

Results

We propose a method, Scellector (single cell selector), which uses haplotype information to detect amplification quality in shallow coverage sequencing data. We tested Scellector on single human neuronal cells, obtained in vitro and amplified by MDA. Qualities were estimated from shallow sequencing with coverage as low as 0.3× per cell and then confirmed using 30× deep coverage sequencing. The high concordance between shallow and high coverage data validated the method.

Conclusion

Scellector can potentially be used to rank amplifications obtained from single cell platforms relying on a MDA-like amplification step, such as Chromium Single Cell profiling solution.

Application of single-cell sequencing in human cancer

Precision medicine is emerging as a cornerstone of future cancer care with the objective of providing targeted therapies based on the molecular phenotype of each individual patient. Traditional bulk-level molecular phenotyping of tumours leads to significant information loss, as the molecular profile represents an average phenotype over large numbers of cells, while cancer is a disease with inherent intra-tumour heterogeneity at the cellular level caused by several factors, including clonal evolution, tissue hierarchies, rare cells and dynamic cell states. Single-cell sequencing provides means to characterize heterogeneity in a large population of cells and opens up opportunity to determine key molecular properties that influence clinical outcomes, including prognosis and probability of treatment response. Single-cell sequencing methods are now reliable enough to be used in many research laboratories, and we are starting to see applications of these technologies for characterization of human primary cancer cells. In this review, we provide an overview of studies that have applied single-cell sequencing to characterize human cancers at the single-cell level, and we discuss some of the current challenges in the field.

A low cost and input tailing method of quality control on multiple annealing, and looping-based amplification cycles-based whole-genome amplification products

BACKGROUND

Single-cell whole-genome sequencing provides novel insights into the nature of genetic heterogeneity in normal and diseased cells. However, amplification of formalin-fixed tissues with low cell numbers is still problematic and multiple annealing, and looping-based amplification cycles (MALBAC) is a commonly used whole-genome amplification (WGA) method with low cell numbers.

METHODS

We developed a low-input tailing method to evaluate the MALBAC-based WGA from sub-nanogram or less quantities of input DNA. The tailing method uses 2100 BioAnalyzer to evaluate the size distribution of MALBAC products, and comparing the tailing with 10380 bp.

RESULTS

Compared with a 22 loci qPCR panel, the tailing method provided a similar WGA evaluation efficiency in 13 samples on one set of study, with lower input, cheaper cost, shorter manual time, and a clear filtering cut off. Later, we demonstrated a strong correlation between tailing size and coverage breadth in another 29 samples on two sets of assays. As a result, the tailing method showed that it could predict whether a sequence breadth achieved 70% or not with 100% accuracy on these three sets of assays. Although further studies are needed, this tailing method is expected to be used as an excellent tool to select high-quality WGA products before library construction.

CONCLUSIONS

Our tailing method can provide a new WGA quality test to evaluate the WGA efficiency with 100% accuracy (42/42). Compared with qPCR panel, our tailing method needs lower input, cheaper cost, shorter manual time, a clear filtering cut off, and extendable high throughput as well as the same sensitivity.

Current Perspectives on High-Throughput Sequencing (HTS) for Adventitious Virus Detection: Upstream Sample Processing and Library Preparation

A key step for broad viral detection using high-throughput sequencing (HTS) is optimizing the sample preparation strategy for extracting viral-specific nucleic acids since viral genomes are diverse: They can be single-stranded or double-stranded RNA or DNA, and can vary from a few thousand bases to over millions of bases, which might introduce biases during nucleic acid extraction. In addition, viral particles can be enveloped or non-enveloped with variable resistance to pre-treatment, which may influence their susceptibility to extraction procedures. Since the identity of the potential adventitious agents is unknown prior to their detection, efficient sample preparation should be unbiased toward all different viral types in order to maximize the probability of detecting any potential adventitious viruses using HTS. Furthermore, the quality assessment of each step for sample processing is also a critical but challenging aspect. This paper presents our current perspectives for optimizing upstream sample processing and library preparation as part of the discussion in the Advanced Virus Detection Technologies Interest group (AVDTIG) The topics include: use of nuclease treatment to enrich for encapsidated nucleic acids, techniques for amplifying low amounts of virus nucleic acids, selection of different extraction methods, relevant controls, the use of spike recovery experiments, and quality control measures during library preparation.

A streamlined workflow for single-cells genome-wide copy-number profiling by low-pass sequencing of LM-PCR whole-genome amplification products

Chromosomal instability and associated chromosomal aberrations are hallmarks of cancer and play a critical role in disease progression and development of resistance to drugs. Single-cell genome analysis has gained interest in latest years as a source of biomarkers for targeted-therapy selection and drug resistance, and several methods have been developed to amplify the genomic DNA and to produce libraries suitable for Whole Genome Sequencing (WGS). However, most protocols require several enzymatic and cleanup steps, thus increasing the complexity and length of protocols, while robustness and speed are key factors for clinical applications. To tackle this issue, we developed a single-tube, single-step, streamlined protocol, exploiting ligation mediated PCR (LM-PCR) Whole Genome Amplification (WGA) method, for low-pass genome sequencing with the Ion Torrent^™ platform and copy number alterations (CNAs) calling from single cells. The method was evaluated on single cells isolated from 6 aberrant cell lines of the NCI-H series. In addition, to demonstrate the feasibility of the workflow on clinical samples, we analyzed single circulating tumor cells (CTCs) and white blood cells (WBCs) isolated from the blood of patients affected by prostate cancer or lung adenocarcinoma. The results obtained show that the developed workflow generates data accurately representing whole genome absolute copy number profiles of single cell and allows alterations calling at resolutions down to 100 Kbp with as few as 200,000 reads. The presented data demonstrate the feasibility of the Ampli1^™ WGA-based low-pass workflow for detection of CNAs in single tumor cells which would be of particular interest for genome-driven targeted therapy selection and for monitoring of disease progression.

Genetic Fingerprinting Using Microsatellite Markers in a Multiplex PCR Reaction: A Compilation of Methodological Approaches from Primer Design to Detection Systems

Microsatellites are polymorphic DNA loci comprising repeated sequence motifs of two to five base pairs which are dispersed throughout the genome. Genotyping of microsatellites is a widely accepted tool for diagnostic and research purposes such as forensic investigations and parentage testing, but also in clinics (e.g. monitoring of bone marrow transplantation), as well as for the agriculture and food industries. The co-amplification of several short tandem repeat (STR) systems in a multiplex reaction with simultaneous detection helps to obtain more information from a DNA sample where its availability may be limited. Here, we introduce and describe this commonly used genotyping technique, providing an overview on available resources on STRs, multiplex design, and analysis.

Progress and challenges of sequencing and analyzing circulating tumor cells

Circulating tumor cells (CTCs) slough off primary tumor tissues and are swept away by the circulatory system. These CTCs can remain in circulation or colonize new sites, forming metastatic clones in distant organs. Recently, CTC analyses have been successfully used as effective clinical tools to monitor tumor progression and prognosis. With advances in next-generation sequencing (NGS) and single-cell sequencing (SCS) technologies, scientists can obtain the complete genome of a CTC and compare it with corresponding primary and metastatic tumors. CTC sequencing has been successfully applied to monitor genomic variations in metastatic and recurrent tumors, infer tumor evolution during treatment, and examine gene expression as well as the mechanism of the epithelial-mesenchymal transition. However, compared with cancer biopsy sequencing and circulating tumor DNA sequencing, the sequencing of CTC genomes and transcriptomes is more complex and technically difficult. Challenges include enriching pure tumor cells from a background of white blood cells, isolating and collecting cells without damaging or losing DNA and RNA, obtaining unbiased and even whole-genome and transcriptome amplification material, and accurately analyzing CTC sequencing data. Here, we review and summarize recent studies using NGS on CTCs. We mainly focus on CTC genome and transcriptome sequencing and the biological and potential clinical applications of these methodologies. Finally, we discuss challenges and future perspectives of CTC sequencing.

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.

Assessment of REPLI-g Multiple Displacement Whole Genome Amplification (WGA) Techniques for Metagenomic Applications

Amplification of minute quantities of DNA is a fundamental challenge in low-biomass metagenomic and microbiome studies because of potential biases in coverage, guanine-cytosine (GC) content, and altered species abundances. Whole genome amplification (WGA), although widely used, is notorious for introducing artifact sequences, either by amplifying laboratory contaminants or by nonrandom amplification of a sample's DNA. In this study, we investigate the effect of REPLI-g multiple displacement amplification (MDA; Qiagen, Valencia, CA, USA) on sequencing data quality and species abundance detection in 8 paired metagenomic samples and 1 titrated, mixed control sample. We extracted and sequenced genomic DNA (gDNA) from 8 environmental samples and compared the quality of the sequencing data for the MDA and their corresponding non-MDA samples. The degree of REPLI-g MDA bias was evaluated by sequence metrics, species composition, and cross-validating observed species abundance and species diversity estimates using the One Codex and MetaPhlAn taxonomic classification tools. Here, we provide evidence of the overall efficacy of REPLI-g MDA on retaining sequencing data quality and species abundance measurements while providing increased yields of high-fidelity DNA. We find that species abundance estimates are largely consistent across samples, even with REPLI-g amplification, as demonstrated by the Spearman's rank order coefficient (R² > 0.8). However, REPLI-g MDA often produced fewer classified reads at the species, genera, and family level, resulting in decreased species diversity. We also observed some areas with the PCR "jackpot effect," with varying input DNA values for the Metagenomics Research Group (MGRG) controls at specific genomic loci. We visualize this effect in whole genome coverage plots and with sequence composition analyses and note these caveats of the MDA method. Despite overall concordance of species abundance between the amplified and unamplified samples, these results demonstrate that amplification of DNA using the REPLI-g method has some limitations. These concerns could be addressed by future improvements in the enzymes or methods for REPLI-g to be considered a >99% robust method for increasing the amount of high-fidelity DNA from low-biomass samples or at the very least, accounted for during computational analysis of MDA samples.

Design and Analysis of Single-Cell Sequencing Experiments

Recent advances in single-cell sequencing hold great potential for exploring biological systems with unprecedented resolution. Sequencing the genome of individual cells can reveal somatic mutations and allows the investigation of clonal dynamics. Single-cell transcriptome sequencing can elucidate the cell type composition of a sample. However, single-cell sequencing comes with major technical challenges and yields complex data output. In this Primer, we provide an overview of available methods and discuss experimental design and single-cell data analysis. We hope that these guidelines will enable a growing number of researchers to leverage the power of single-cell sequencing.

Enhanced sequencing coverage with digital droplet multiple displacement amplification

Sequencing small quantities of DNA is important for applications ranging from the assembly of uncultivable microbial genomes to the identification of cancer-associated mutations. To obtain sufficient quantities of DNA for sequencing, the small amount of starting material must be amplified significantly. However, existing methods often yield errors or non-uniform coverage, reducing sequencing data quality. Here, we describe digital droplet multiple displacement amplification, a method that enables massive amplification of low-input material while maintaining sequence accuracy and uniformity. The low-input material is compartmentalized as single molecules in millions of picoliter droplets. Because the molecules are isolated in compartments, they amplify to saturation without competing for resources; this yields uniform representation of all sequences in the final product and, in turn, enhances the quality of the sequence data. We demonstrate the ability to uniformly amplify the genomes of single Escherichia coli cells, comprising just 4.7 fg of starting DNA, and obtain sequencing coverage distributions that rival that of unamplified material. Digital droplet multiple displacement amplification provides a simple and effective method for amplifying minute amounts of DNA for accurate and uniform sequencing.

Modified DOP-PCR for improved STR typing of degraded DNA from human skeletal remains and bloodstains

Forensic and ancient DNA samples often are damaged and in limited quantity as a result of exposure to harsh environments and the passage of time. Several strategies have been proposed to address the challenges posed by degraded and low copy templates, including a PCR based whole genome amplification method called degenerate oligonucleotide-primed PCR (DOP-PCR). This study assessed the efficacy of four modified versions of the original DOP-PCR primer that retain at least a portion of the 5' defined sequence and alter the number of bases on the 3' end. The use of each of the four modified primers resulted in improved STR profiles from environmentally-damaged bloodstains, contemporary human skeletal remains, American Civil War era bone samples, and skeletal remains of WWII soldiers over those obtained by previously described DOP-PCR methods and routine STR typing. Additionally, the modified DOP-PCR procedure allows for a larger volume of DNA extract to be used, reducing the need to concentrate the sample and thus mitigating the effects of concurrent concentration of inhibitors.

Bioinformatics approaches to single-cell analysis in developmental biology

Individual cells within the same population show various degrees of heterogeneity, which may be better handled with single-cell analysis to address biological and clinical questions. Single-cell analysis is especially important in developmental biology as subtle spatial and temporal differences in cells have significant associations with cell fate decisions during differentiation and with the description of a particular state of a cell exhibiting an aberrant phenotype. Biotechnological advances, especially in the area of microfluidics, have led to a robust, massively parallel and multi-dimensional capturing, sorting, and lysis of single-cells and amplification of related macromolecules, which have enabled the use of imaging and omics techniques on single cells. There have been improvements in computational single-cell image analysis in developmental biology regarding feature extraction, segmentation, image enhancement and machine learning, handling limitations of optical resolution to gain new perspectives from the raw microscopy images. Omics approaches, such as transcriptomics, genomics and epigenomics, targeting gene and small RNA expression, single nucleotide and structural variations and methylation and histone modifications, rely heavily on high-throughput sequencing technologies. Although there are well-established bioinformatics methods for analysis of sequence data, there are limited bioinformatics approaches which address experimental design, sample size considerations, amplification bias, normalization, differential expression, coverage, clustering and classification issues, specifically applied at the single-cell level. In this review, we summarize biological and technological advancements, discuss challenges faced in the aforementioned data acquisition and analysis issues and present future prospects for application of single-cell analyses to developmental biology.

Comparison of variations detection between whole-genome amplification methods used in single-cell resequencing

BACKGROUND

Single-cell resequencing (SCRS) provides many biomedical advances in variations detection at the single-cell level, but it currently relies on whole genome amplification (WGA). Three methods are commonly used for WGA: multiple displacement amplification (MDA), degenerate-oligonucleotide-primed PCR (DOP-PCR) and multiple annealing and looping-based amplification cycles (MALBAC). However, a comprehensive comparison of variations detection performance between these WGA methods has not yet been performed.

RESULTS

We systematically compared the advantages and disadvantages of different WGA methods, focusing particularly on variations detection. Low-coverage whole-genome sequencing revealed that DOP-PCR had the highest duplication ratio, but an even read distribution and the best reproducibility and accuracy for detection of copy-number variations (CNVs). However, MDA had significantly higher genome recovery sensitivity (~84 %) than DOP-PCR (~6 %) and MALBAC (~52 %) at high sequencing depth. MALBAC and MDA had comparable single-nucleotide variations detection efficiency, false-positive ratio, and allele drop-out ratio. We further demonstrated that SCRS data amplified by either MDA or MALBAC from a gastric cancer cell line could accurately detect gastric cancer CNVs with comparable sensitivity and specificity, including amplifications of 12p11.22 (KRAS) and 9p24.1 (JAK2, CD274, and PDCD1LG2).

CONCLUSIONS

Our findings provide a comprehensive comparison of variations detection performance using SCRS amplified by different WGA methods. It will guide researchers to determine which WGA method is best suited to individual experimental needs at single-cell level.

Comparison of variations detection between whole-genome amplification methods used in single-cell resequencing

BACKGROUND

Single-cell resequencing (SCRS) provides many biomedical advances in variations detection at the single-cell level, but it currently relies on whole genome amplification (WGA). Three methods are commonly used for WGA: multiple displacement amplification (MDA), degenerate-oligonucleotide-primed PCR (DOP-PCR) and multiple annealing and looping-based amplification cycles (MALBAC). However, a comprehensive comparison of variations detection performance between these WGA methods has not yet been performed.

RESULTS

We systematically compared the advantages and disadvantages of different WGA methods, focusing particularly on variations detection. Low-coverage whole-genome sequencing revealed that DOP-PCR had the highest duplication ratio, but an even read distribution and the best reproducibility and accuracy for detection of copy-number variations (CNVs). However, MDA had significantly higher genome recovery sensitivity (~84 %) than DOP-PCR (~6 %) and MALBAC (~52 %) at high sequencing depth. MALBAC and MDA had comparable single-nucleotide variations detection efficiency, false-positive ratio, and allele drop-out ratio. We further demonstrated that SCRS data amplified by either MDA or MALBAC from a gastric cancer cell line could accurately detect gastric cancer CNVs with comparable sensitivity and specificity, including amplifications of 12p11.22 (KRAS) and 9p24.1 (JAK2, CD274, and PDCD1LG2).

CONCLUSIONS

Our findings provide a comprehensive comparison of variations detection performance using SCRS amplified by different WGA methods. It will guide researchers to determine which WGA method is best suited to individual experimental needs at single-cell level.

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

We present a survey of single-cell whole-genome amplification (WGA) methods, including degenerate oligonucleotide-primed polymerase chain reaction (DOP-PCR), multiple displacement amplification (MDA), and multiple annealing and looping-based amplification cycles (MALBAC). The key parameters to characterize the performance of these methods are defined, including genome coverage, uniformity, reproducibility, unmappable rates, chimera rates, allele dropout rates, false positive rates for calling single-nucleotide variations, and ability to call copy-number variations. Using these parameters, we compare five commercial WGA kits by performing deep sequencing of multiple single cells. We also discuss several major applications of single-cell genomics, including studies of whole-genome de novo mutation rates, the early evolution of cancer genomes, circulating tumor cells (CTCs), meiotic recombination of germ cells, preimplantation genetic diagnosis (PGD), and preimplantation genomic screening (PGS) for in vitro-fertilized embryos.

Rapid Aneuploidy Detection of Chromosomes 13, 18, 21, X and Y Using Quantitative Fluorescent Polymerase Chain Reaction with Few Microdissected Fetal Cells

Objectives: Analysis of DNA from small numbers of cells, such as fetal cells in maternal blood, is a major limiting factor for their use in clinical applications. Traditional methods of single-cells whole genome amplification (SCs-WGA) and accurate analysis have been challenging to date. Our purpose was to assess the feasibility of using a few fetal cells to determine fetal sex and major chromosomal abnormalities by quantitative fluorescent polymerase chain reaction (QF-PCR). Methods: Cultured cells from 26 amniotic fluid samples were used for standard DNA extraction and recovery of 5 fetal cells by laser-capture microdissection. SCs-WGA was performed using the DNA from the microdissected cells. PCR amplification of short tandem repeats specific for chromosomes 13, 18, 21, X and Y was performed on extracted and amplified DNA. Allele dosage and sexing were quantitatively analyzed following separation by capillary electrophoresis. Results: Microsatellite QF-PCR analysis showed high concordance in chromosomal copy number between extracted and amplified DNA when 5 or more cells were used. Results were in concordance with that of conventional cytogenetic analysis. Conclusion: Satisfactory genomic coverage can be obtained from SCs-WGA. Clinically, SCs-WGA coupled with QF-PCR can provide a reliable, accurate, rapid and cost-effective method for detection of major fetal chromosome abnormalities.

Assessing the utility of whole genome amplified DNA for next-generation molecular ecology

DNA quantity can be a hindrance in ecological and evolutionary research programmes due to a range of factors including endangered status of target organisms, available tissue type, and the impact of field conditions on preservation methods. A potential solution to low-quantity DNA lies in whole genome amplification (WGA) techniques that can substantially increase DNA yield. To date, few studies have rigorously examined sequence bias that might result from WGA and next-generation sequencing of nonmodel taxa. To address this knowledge deficit, we use multiple displacement amplification (MDA) and double-digest RAD sequencing on the grey mouse lemur (Microcebus murinus) to quantify bias in genome coverage and SNP calls when compared to raw genomic DNA (gDNA). We focus our efforts in providing baseline estimates of potential bias by following manufacturer's recommendations for starting DNA quantities (>100 ng). Our results are strongly suggestive that MDA enrichment does not introduce systematic bias to genome characterization. SNP calling between samples when genotyping both de-novo and with a reference genome are highly congruent (>98%) when specifying a minimum threshold of 20X stack depth to call genotypes. Relative genome coverage is also similar between MDA and gDNA, and allelic dropout is not observed. SNP concordance varies based on coverage threshold, with 95% concordance reached at ~12X coverage genotyping de-novo and ~7X coverage genotyping with the reference genome. These results suggest that MDA may be a suitable solution for next-generation molecular ecological studies when DNA quantity would otherwise be a limiting factor.

Single-cell sequencing technologies: current and future

Intensively developed in the last few years, single-cell sequencing technologies now present numerous advantages over traditional sequencing methods for solving the problems of biological heterogeneity and low quantities of available biological materials. The application of single-cell sequencing technologies has profoundly changed our understanding of a series of biological phenomena, including gene transcription, embryo development, and carcinogenesis. However, before single-cell sequencing technologies can be used extensively, researchers face the serious challenge of overcoming inherent issues of high amplification bias, low accuracy and reproducibility. Here, we simply summarize the techniques used for single-cell isolation, and review the current technologies used in single-cell genomic, transcriptomic, and epigenomic sequencing. We discuss the merits, defects, and scope of application of single-cell sequencing technologies and then speculate on the direction of future developments.

Microfluidic whole genome amplification device for single cell sequencing

We developed a microfluidic device to perform multiplex single-cell whole-genome amplification (WGA) using multiple annealing and looping-based amplification cycles (MALBAC). This device, made of polydimethylsiloxane (PDMS), allows us to monitor the whole process of cell loading and single-cell WGA for sequencing. We show that the genome coverage of MALBAC amplifications is reproducible between chambers on a single chip and between different chips, which enables data normalization using standard samples to accurately identify copy number variations (CNVs). This device provides an easy-to-operate approach to perform single cell sequencing library preparation with minimum hands-on time. It reduces the requirement of manual expertise as well as the risk of contamination, which is essential in future applications especially the medical diagnosis.

A novel whole genome amplification method using type IIS restriction enzymes to create overhangs with random sequences

Ligation-mediated polymerase chain reaction (LM-PCR) is a whole genome amplification (WGA) method, for which genomic DNA is cleaved into numerous fragments and then all of the fragments are amplified by PCR after attaching a universal end sequence. However, the self-ligation of these fragments could happen and may cause biased amplification and restriction of its application. To decrease the self-ligation probability, here we use type IIS restriction enzymes to digest genomic DNA into fragments with 4-5nt long overhangs with random sequences. After ligation to an adapter with random end sequences to above fragments, PCR is carried out and almost all present DNA sequences are amplified. In this study, whole genome of Vibrio parahaemolyticus was amplified and the amplification efficiency was evaluated by quantitative PCR. The results suggested that our approach could provide sufficient genomic DNA with good quality to meet requirements of various genetic analyses.

Validation of high throughput sequencing and microbial forensics applications

High throughput sequencing (HTS) generates large amounts of high quality sequence data for microbial genomics. The value of HTS for microbial forensics is the speed at which evidence can be collected and the power to characterize microbial-related evidence to solve biocrimes and bioterrorist events. As HTS technologies continue to improve, they provide increasingly powerful sets of tools to support the entire field of microbial forensics. Accurate, credible results allow analysis and interpretation, significantly influencing the course and/or focus of an investigation, and can impact the response of the government to an attack having individual, political, economic or military consequences. Interpretation of the results of microbial forensic analyses relies on understanding the performance and limitations of HTS methods, including analytical processes, assays and data interpretation. The utility of HTS must be defined carefully within established operating conditions and tolerances. Validation is essential in the development and implementation of microbial forensics methods used for formulating investigative leads attribution. HTS strategies vary, requiring guiding principles for HTS system validation. Three initial aspects of HTS, irrespective of chemistry, instrumentation or software are: 1) sample preparation, 2) sequencing, and 3) data analysis. Criteria that should be considered for HTS validation for microbial forensics are presented here. Validation should be defined in terms of specific application and the criteria described here comprise a foundation for investigators to establish, validate and implement HTS as a tool in microbial forensics, enhancing public safety and national security.

Discovery and characterization of RecA protein of thermophilic bacterium Thermus thermophilus MAT72 phage Tt72 that increases specificity of a PCR-based DNA amplification

The recA gene of newly discovered Thermus thermophilus MAT72 phage Tt72 (Myoviridae) was cloned and overexpressed in Escherichia coli. The 1020-bp gene codes for a 339-amino-acid polypeptide with an Mr of 38,155 which shows 38.7% positional identity to the E. coli RecA protein. When expressed in E. coli, the Tt72 recA gene did not confer the ability to complement the ultraviolet light (254nm) sensitivity of an E. coli recA mutant. Tt72 RecA protein has been purified with good yield to catalytic and electrophoretic homogeneity using a three-step chromatography procedure. Biochemical characterization indicated that the protein can pair and promote ATP-dependent strand exchange reaction resulting in formation of a heteroduplex DNA at 60°C under conditions otherwise optimal for E. coli RecA. When the Tt72 RecA protein was included in a standard PCR-based DNA amplification reaction, the specificity of the PCR assays was significantly improved by eliminating non-specific products.

Single cell analysis of cancer genomes

Genomic studies have provided key insights into how cancers develop, evolve, metastasize and respond to treatment. Cancers result from an interplay between mutation, selection and clonal expansions. In solid tumours, this Darwinian competition between subclones is also influenced by topological factors. Recent advances have made it possible to study cancers at the single cell level. These methods represent important tools to dissect cancer evolution and provide the potential to considerably change both cancer research and clinical practice. Here we discuss state-of-the-art methods for the isolation of a single cell, whole-genome and whole-transcriptome amplification of the cell's nucleic acids, as well as microarray and massively parallel sequencing analysis of such amplification products. We discuss the strengths and the limitations of the techniques, and explore single-cell methodologies for future cancer research, as well as diagnosis and treatment of the disease.

Single cell genomics: advances and future perspectives

Advances in whole-genome and whole-transcriptome amplification have permitted the sequencing of the minute amounts of DNA and RNA present in a single cell, offering a window into the extent and nature of genomic and transcriptomic heterogeneity which occurs in both normal development and disease. Single-cell approaches stand poised to revolutionise our capacity to understand the scale of genomic, epigenomic, and transcriptomic diversity that occurs during the lifetime of an individual organism. Here, we review the major technological and biological breakthroughs achieved, describe the remaining challenges to overcome, and provide a glimpse into the promise of recent and future developments.

Systematic evaluation of bias in microbial community profiles induced by whole genome amplification

Whole genome amplification methods facilitate the detection and characterization of microbial communities in low biomass environments. We examined the extent to which the actual community structure is reliably revealed and factors contributing to bias. One widely used [multiple displacement amplification (MDA)] and one new primer-free method [primase-based whole genome amplification (pWGA)] were compared using a polymerase chain reaction (PCR)-based method as control. Pyrosequencing of an environmental sample and principal component analysis revealed that MDA impacted community profiles more strongly than pWGA and indicated that this related to species GC content, although an influence of DNA integrity could not be excluded. Subsequently, biases by species GC content, DNA integrity and fragment size were separately analysed using defined mixtures of DNA from various species. We found significantly less amplification of species with the highest GC content for MDA-based templates and, to a lesser extent, for pWGA. DNA fragmentation also interfered severely: species with more fragmented DNA were less amplified with MDA and pWGA. pWGA was unable to amplify low molecular weight DNA (< 1.5 kb), whereas MDA was inefficient. We conclude that pWGA is the most promising method for characterization of microbial communities in low-biomass environments and for currently planned astrobiological missions to Mars.

Deconstructing stem cell population heterogeneity: single-cell analysis and modeling approaches

Isogenic stem cell populations display cell-to-cell variations in a multitude of attributes including gene or protein expression, epigenetic state, morphology, proliferation and proclivity for differentiation. The origins of the observed heterogeneity and its roles in the maintenance of pluripotency and the lineage specification of stem cells remain unclear. Addressing pertinent questions will require the employment of single-cell analysis methods as traditional cell biochemical and biomolecular assays yield mostly population-average data. In addition to time-lapse microscopy and flow cytometry, recent advances in single-cell genomic, transcriptomic and proteomic profiling are reviewed. The application of multiple displacement amplification, next generation sequencing, mass cytometry and spectrometry to stem cell systems is expected to provide a wealth of information affording unprecedented levels of multiparametric characterization of cell ensembles under defined conditions promoting pluripotency or commitment. Establishing connections between single-cell analysis information and the observed phenotypes will also require suitable mathematical models. Stem cell self-renewal and differentiation are orchestrated by the coordinated regulation of subcellular, intercellular and niche-wide processes spanning multiple time scales. Here, we discuss different modeling approaches and challenges arising from their application to stem cell populations. Integrating single-cell analysis with computational methods will fill gaps in our knowledge about the functions of heterogeneity in stem cell physiology. This combination will also aid the rational design of efficient differentiation and reprogramming strategies as well as bioprocesses for the production of clinically valuable stem cell derivatives.

Preimplantation genetic diagnosis guided by single-cell genomics

Preimplantation genetic diagnosis (PGD) aims to help couples with heritable genetic disorders to avoid the birth of diseased offspring or the recurrence of loss of conception. Following in vitro fertilization, one or a few cells are biopsied from each human preimplantation embryo for genetic testing, allowing diagnosis and selection of healthy embryos for uterine transfer. Although classical methods, including single-cell PCR and fluorescent in situ hybridization, enable PGD for many genetic disorders, they have limitations. They often require family-specific designs and can be labor intensive, resulting in long waiting lists. Furthermore, certain types of genetic anomalies are not easy to diagnose using these classical approaches, and healthy offspring carrying the parental mutant allele(s) can result. Recently, state-of-the-art methods for single-cell genomics have flourished, which may overcome the limitations associated with classical PGD, and these underpin the development of generic assays for PGD that enable selection of embryos not only for the familial genetic disorder in question, but also for various other genetic aberrations and traits at once. Here, we discuss the latest single-cell genomics methodologies based on DNA microarrays, single-nucleotide polymorphism arrays or next-generation sequence analysis. We focus on their strengths, their validation status, their weaknesses and the challenges for implementing them in PGD.