Genome-wide single-cell analysis of recombination activity and de novo mutation rates in human sperm

Single-cell multi-omics in the study of digestive system cancers

Digestive system cancers are prevalent diseases with a high mortality rate, posing a significant threat to public health and economic burden. The diagnosis and treatment of digestive system cancer confront conventional cancer problems, such as tumor heterogeneity and drug resistance. Single-cell sequencing (SCS) emerged at times required and has developed from single-cell RNA-seq (scRNA-seq) to the single-cell multi-omics era represented by single-cell spatial transcriptomics (ST). This article comprehensively reviews the advances of single-cell omics technology in the study of digestive system tumors. While analyzing and summarizing the research cases, vital details on the sequencing platform, sample information, sampling method, and key findings are provided. Meanwhile, we summarize the commonly used SCS platforms and their features, as well as the advantages of multi-omics technologies in combination. Finally, the development trends and prospects of the application of single-cell multi-omics technology in digestive system cancer research are prospected.

Single-cell omics: experimental workflow, data analyses and applications

Cells are the fundamental units of biological systems and exhibit unique development trajectories and molecular features. Our exploration of how the genomes orchestrate the formation and maintenance of each cell, and control the cellular phenotypes of various organismsis, is both captivating and intricate. Since the inception of the first single-cell RNA technology, technologies related to single-cell sequencing have experienced rapid advancements in recent years. These technologies have expanded horizontally to include single-cell genome, epigenome, proteome, and metabolome, while vertically, they have progressed to integrate multiple omics data and incorporate additional information such as spatial scRNA-seq and CRISPR screening. Single-cell omics represent a groundbreaking advancement in the biomedical field, offering profound insights into the understanding of complex diseases, including cancers. Here, we comprehensively summarize recent advances in single-cell omics technologies, with a specific focus on the methodology section. This overview aims to guide researchers in selecting appropriate methods for single-cell sequencing and related data analysis.

Opportunities and Challenges in Advancing Plant Research with Single-cell Omics

Plants possess diverse cell types and intricate regulatory mechanisms to adapt to the ever-changing environment of nature. Various strategies have been employed to study cell types and their developmental progressions, including single-cell sequencing methods which provide high-dimensional catalogs to address biological concerns. In recent years, single-cell sequencing technologies in transcriptomics, epigenomics, proteomics, metabolomics, and spatial transcriptomics have been increasingly used in plant science to reveal intricate biological relationships at the single-cell level. However, the application of single-cell technologies to plants is more limited due to the challenges posed by cell structure. This review outlines the advancements in single-cell omics technologies, their implications in plant systems, future research applications, and the challenges of single-cell omics in plant systems.

Revalidation of DNA Fragmentation Analyses for Human Sperm-Measurement Principles, Comparative Standards, Calibration Curve, Required Sensitivity, and Eligibility Criteria for Test Sperm

(1) Background: Double-strand breaks (DSBs) in a single nucleus are usually measured using the sperm chromatin structure assay (SCSA), sperm chromatin dispersion (SCD) test, and comet assay (CA). Mono-dimensional single-cell pulsed-field gel electrophoresis (1D-SCPFGE) and angle-modulated two- dimensional single-cell pulsed-field gel electrophoresis (2D-SCPFGE) were developed to observe DNA fragmentation in separated motile sperm. (2) Methods: Comparative standards, calibration curves, required sensitivity levels, and eligibility criteria for test sperm were set up to validate the measurement principles of these tests. (3) Results: The conventional methods overlooked the interference of nucleoproteins in their measurements. In-gel proteolysis improves the measurement accuracies of 1D- and 2D-SCPFGE. Naked DNA is suitable for comparative standards and test specimens. Moreover, several dysfunctions that might induce DNA damage are observed in the separated motile sperm. Overall, the discussion highlights the need to revisit the conventional univariable analyses based on the SCSA, SCD test, and CA. (4) Conclusions: Human infertility is a complex syndrome, and the aim of quality control in intracytoplasmic sperm injection is to identify the underlying dysfunctions remaining in the separated motile sperm that render them ineligible for injection. Multivariable analyses with special consideration to confounding factors are necessary in future cohort studies.

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.

Radiation and male reproductive system: Damage and protection

Male fertility has been declining in recent decades, and a growing body of research points to environmental and lifestyle factors as the cause. The widespread use of radiation technology may result in more people affected by male infertility, as it is well established that radiation can cause reproductive impairment in men. This article provides a review of radiation-induced damage to male reproduction, and the effects of damage mechanisms and pharmacotherapy. It is hoped that this review will contribute to the understanding of the effects of radiation on male reproduction, and provide information for research into drugs that can protect the reproductive health of males.

Scalable integration of multiomic single-cell data using generative adversarial networks

MOTIVATION

Single-cell profiling has become a common practice to investigate the complexity of tissues, organs, and organisms. Recent technological advances are expanding our capabilities to profile various molecular layers beyond the transcriptome such as, but not limited to, the genome, the epigenome, and the proteome. Depending on the experimental procedure, these data can be obtained from separate assays or the very same cells. Yet, integration of more than two assays is currently not supported by the majority of the computational frameworks avaiable.

RESULTS

We here propose a Multi-Omic data integration framework based on Wasserstein Generative Adversarial Networks suitable for the analysis of paired or unpaired data with a high number of modalities (>2). At the core of our strategy is a single network trained on all modalities together, limiting the computational burden when many molecular layers are evaluated.

AVAILABILITY AND IMPLEMENTATION

Source code of our framework is available at https://github.com/vgiansanti/MOWGAN.

Single-cell sequencing: A promising approach for uncovering the characteristic of pancreatic islet cells in type 2 diabetes

Single-cell sequencing is a novel and rapidly advancing high-throughput technique that can be used to investigating genomics, transcriptomics, and epigenetics at a single-cell level. Currently, single-cell sequencing can not only be used to draw the pancreatic islet cells map and uncover the characteristics of cellular heterogeneity in type 2 diabetes, but can also be used to label and purify functional beta cells in pancreatic stem cells, improving stem cells and islet organoids therapies. In addition, this technology helps to analyze islet cell dedifferentiation and can be applied to the treatment of type 2 diabetes. In this review, we summarize the development and process of single-cell sequencing, describe the potential applications of single-cell sequencing in the field of type 2 diabetes, and discuss the prospects and limitations of single-cell sequencing to provide a new direction for exploring the pathogenesis of type 2 diabetes and finding therapeutic targets.

Microfluidic chip as a promising evaluation method in assisted reproduction: A systematic review

The aim of assisted reproductive technology (ART) is to select the high-quality sperm, oocytes, and embryos, and finally achieve a successful pregnancy. However, functional evaluation is hindered by intra- and inter-operator variability. Microfluidic chips emerge as the one of the most powerful tools to analyze biological samples for reduced size, precise control, and flexible extension. Herein, a systematic search was conducted in PubMed, Scopus, Web of Science, ScienceDirect, and IEEE Xplore databases until March 2023. We displayed and prospected all detection strategies based on microfluidics in the ART field. After full-text screening, 71 studies were identified as eligible for inclusion. The percentages of human and mouse studies equaled with 31.5%. The prominent country in terms of publication number was the USA (n = 13). Polydimethylsiloxane (n = 49) and soft lithography (n = 28) were the most commonly used material and fabrication method, respectively. All articles were classified into three types: sperm (n = 38), oocytes (n = 20), and embryos (n = 13). The assessment contents included motility, counting, mechanics, permeability, impedance, secretion, oxygen consumption, and metabolism. Collectively, the microfluidic chip technology facilitates more efficient, accurate, and objective evaluation in ART. It can even be combined with artificial intelligence to assist the daily activities of embryologists. More well-designed clinical studies and affordable integrated microfluidic chips are needed to validate the safety, efficacy, and reproducibility. Trial registration: The protocol was registered in the Open Science Frame REGISTRIES (identification: osf.io/6rv4a).

A cohort study of neurodevelopmental disorders and/or congenital anomalies using high resolution chromosomal microarrays in southern Brazil highlighting the significance of ASD

Chromosomal microarray (CMA) is the reference in evaluation of copy number variations (CNVs) in individuals with neurodevelopmental disorders (NDDs), such as intellectual disability (ID) and/or autism spectrum disorder (ASD), which affect around 3-4% of the world's population. Modern platforms for CMA, also include probes for single nucleotide polymorphisms (SNPs) that detect homozygous regions in the genome, such as long contiguous stretches of homozygosity (LCSH). These regions result from complete or segmental chromosomal homozygosis and may be indicative of uniparental disomy (UPD), inbreeding, population characteristics, as well as replicative DNA repair events. In this retrospective study, we analyzed CMA reading files requested by geneticists and neurologists for diagnostic purposes along with available clinical data. Our objectives were interpreting CNVs and assess the frequencies and implications of LCSH detected by Affymetrix CytoScan HD (41%) or 750K (59%) platforms in 1012 patients from the south of Brazil. The patients were mainly children with NDDs and/or congenital anomalies (CAs). A total of 206 CNVs, comprising 132 deletions and 74 duplications, interpreted as pathogenic, were found in 17% of the patients in the cohort and across all chromosomes. Additionally, 12% presented rare variants of uncertain clinical significance, including LPCNVs, as the only clinically relevant CNV. Within the realm of NDDs, ASD carries a particular importance, owing to its escalating prevalence and its growing repercussions for individuals, families, and communities. ASD was one clinical phenotype, if not the main reason for referral to testing, for about one-third of the cohort, and these patients were further analyzed as a sub-cohort. Considering only the patients with ASD, the diagnostic rate was 10%, within the range reported in the literature (8-21%). It was higher (16%) when associated with dysmorphic features and lower (7%) for "isolated" ASD (without ID and without dysmorphic features). In 953 CMAs of the whole cohort, LCSH (≥ 3 Mbp) were analyzed not only for their potential pathogenic significance but were also explored to identify common LCSH in the South Brazilians population. CMA revealed at least one LCSH in 91% of the patients. For about 11.5% of patients, the LCSH suggested consanguinity from the first to the fifth degree, with a greater probability of clinical impact, and in 2.8%, they revealed a putative UPD. LCSH found at a frequency of 5% or more were considered common LCSH in the general population, allowing us to delineate 10 regions as potentially representing ancestral haplotypes of neglectable clinical significance. The main referrals for CMA were developmental delay (56%), ID (33%), ASD (33%) and syndromic features (56%). Some phenotypes in this population may be predictive of a higher probability of indicating a carrier of a pathogenic CNV. Here, we present the largest report of CMA data in a cohort with NDDs and/or CAs from the South of Brazil. We characterize the rare CNVs found along with the main phenotypes presented by each patient and show the importance and usefulness of LCSH interpretation in CMA results that incorporate SNPs, as well as we illustrate the value of CMA to investigate CNV in ASD.

Single-cell lineage tracing with endogenous markers

Resolving lineage relationships between cells in an organism provides key insights into the fate of individual cells and drives a fundamental understanding of the process of development and disease. A recent rapid increase in experimental and computational advances for detecting naturally occurring somatic nuclear and mitochondrial mutation at single-cell resolution has expanded lineage tracing from model organisms to humans. This review discusses the advantages and challenges of experimental and computational techniques for cell lineage tracing using somatic mutation as endogenous DNA barcodes to decipher the relationships between cells during development and tumour evolution. We outlook the advantages of spatial clonal evolution analysis and single-cell lineage tracing using endogenous genetic markers.

Epigenetic aging of mammalian gametes

The process of aging refers to physiological changes that occur to an organism as time progresses and involves changes to DNA, proteins, metabolism, cells, and organs. Like the rest of the cells in the body, gametes age, and it is well established that there is a decline in reproductive capabilities in females and males with aging. One of the major pathways known to be involved in aging is epigenetic changes. The epigenome is the multitude of chemical modifications performed on DNA and chromatin that affect the ability of chromatin to be transcribed. In this review, we explore the effects of aging on female and male gametes with a focus on the epigenetic changes that occur in gametes throughout aging. Quality decline in oocytes occurs at a relatively early age. Epigenetic changes constitute an important part of oocyte aging. DNA methylation is reduced with age, along with reduced expression of DNA methyltransferases (DNMTs). Histone deacetylases (HDAC) expression is also reduced, and a loss of heterochromatin marks occurs with age. As a consequence of heterochromatin loss, retrotransposon expression is elevated, and aged oocytes suffer from DNA damage. In sperm, aging affects sperm number, motility and fecundity, and epigenetic changes may constitute a part of this process. 5 methyl-cytosine (5mC) methylation is elevated in sperm from aged men, but methylation on Long interspersed nuclear elements (LINE) elements is reduced. Di and trimethylation of histone 3 lysine 9 (H3K9me2/3) is reduced in sperm from aged men and trimethylation of histone 3 lysine 27 (H3K27me3) is elevated. The protamine makeup of sperm from aged men is also changed, with reduced protamine expression and a misbalanced ratio between protamine proteins protamine P1 and protamine P2. The study of epigenetic reproductive aging is recently gaining interest. The current status of the field suggests that many aspects of gamete epigenetic aging are still open for investigation. The clinical applications of these investigations have far-reaching consequences for fertility and sociological human behavior.

Identifying crossovers and shared genetic material in whole genome sequencing data from families

Large, whole-genome sequencing (WGS) data sets containing families provide an important opportunity to identify crossovers and shared genetic material in siblings. However, the high variant calling error rates of WGS in some areas of the genome can result in spurious crossover calls, and the special inheritance status of the X Chromosome presents challenges. We have developed a hidden Markov model that addresses these issues by modeling the inheritance of variants in families in the presence of error-prone regions and inherited deletions. We call our method PhasingFamilies. We validate PhasingFamilies using the platinum genome family NA1281 (precision: 0.81; recall: 0.97), as well as simulated genomes with known crossover positions (precision: 0.93; recall: 0.92). Using 1925 quads from the Simons Simplex Collection, we found that PhasingFamilies resolves crossovers to a median resolution of 3527.5 bp. These crossovers recapitulate existing recombination rate maps, including for the X Chromosome; produce sibling pair IBD that matches expected distributions; and are validated by the haplotype estimation tool SHAPEIT. We provide an efficient, open-source implementation of PhasingFamilies that can be used to identify crossovers from family sequencing data.

Archival single-cell genomics reveals persistent subclones during DCIS progression

Ductal carcinoma in situ (DCIS) is a common precursor of invasive breast cancer. Our understanding of its genomic progression to recurrent disease remains poor, partly due to challenges associated with the genomic profiling of formalin-fixed paraffin-embedded (FFPE) materials. Here, we developed Arc-well, a high-throughput single-cell DNA-sequencing method that is compatible with FFPE materials. We validated our method by profiling 40,330 single cells from cell lines, a frozen tissue, and 27 FFPE samples from breast, lung, and prostate tumors stored for 3-31 years. Analysis of 10 patients with matched DCIS and cancers that recurred 2-16 years later show that many primary DCIS had already undergone whole-genome doubling and clonal diversification and that they shared genomic lineages with persistent subclones in the recurrences. Evolutionary analysis suggests that most DCIS cases in our cohort underwent an evolutionary bottleneck, and further identified chromosome aberrations in the persistent subclones that were associated with recurrence.

Barcoded multiple displacement amplification for high coverage sequencing in spatial genomics

Determining mutational landscapes in a spatial context is essential for understanding genetically heterogeneous cell microniches. Current approaches, such as Multiple Displacement Amplification (MDA), offer high genome coverage but limited multiplexing, which hinders large-scale spatial genomic studies. Here, we introduce barcoded MDA (bMDA), a technique that achieves high-coverage genomic analysis of low-input DNA while enhancing the multiplexing capabilities. By incorporating cell barcodes during MDA, bMDA streamlines library preparation in one pot, thereby overcoming a key bottleneck in spatial genomics. We apply bMDA to the integrative spatial analysis of triple-negative breast cancer tissues by examining copy number alterations, single nucleotide variations, structural variations, and kataegis signatures for each spatial microniche. This enables the assessment of subclonal evolutionary relationships within a spatial context. Therefore, bMDA has emerged as a scalable technology with the potential to advance the field of spatial genomics significantly.

Long-read-based single sperm genome sequencing for chromosome-wide haplotype phasing of both SNPs and SVs

Although localized haploid phasing can be achieved using long read genome sequencing without parental data, reliable chromosome-scale phasing remains a great challenge. Given that sperm is a natural haploid cell, single-sperm genome sequencing can provide a chromosome-wide phase signal. Due to the limitation of read length, current short-read-based single-sperm genome sequencing methods can only achieve SNP haplotyping and come with difficulties in detecting and haplotyping structural variations (SVs) in complex genomic regions. To overcome these limitations, we developed a long-read-based single-sperm genome sequencing method and a corresponding data analysis pipeline that can accurately identify crossover events and chromosomal level aneuploidies in single sperm and efficiently detect SVs within individual sperm cells. Importantly, without parental genome information, our method can accurately conduct de novo phasing of heterozygous SVs as well as SNPs from male individuals at the whole chromosome scale. The accuracy for phasing of SVs was as high as 98.59% using 100 single sperm cells, and the accuracy for phasing of SNPs was as high as 99.95%. Additionally, our method reliably enabled deduction of the repeat expansions of haplotype-resolved STRs/VNTRs in single sperm cells. Our method provides a new opportunity for studying haplotype-related genetics in mammals.

Long-read whole-genome analysis of human single cells

Long-read sequencing has dramatically increased our understanding of human genome variation. Here, we demonstrate that long-read technology can give new insights into the genomic architecture of individual cells. Clonally expanded CD8+ T-cells from a human donor were subjected to droplet-based multiple displacement amplification (dMDA) to generate long molecules with reduced bias. PacBio sequencing generated up to 40% genome coverage per single-cell, enabling detection of single nucleotide variants (SNVs), structural variants (SVs), and tandem repeats, also in regions inaccessible by short reads. 28 somatic SNVs were detected, including one case of mitochondrial heteroplasmy. 5473 high-confidence SVs/cell were discovered, a sixteen-fold increase compared to Illumina-based results from clonally related cells. Single-cell de novo assembly generated a genome size of up to 598 Mb and 1762 (12.8%) complete gene models. In summary, our work shows the promise of long-read sequencing toward characterization of the full spectrum of genetic variation in single cells.

In vivo and in vitro matured bovine oocytes present a distinct pattern of single-cell gene expression

Oocyte gene expression is a well controlled event that promotes gamete competence to undergo maturation, fertilization, and to support early embryo development, directly affecting reproductive outcomes. Considering that in vivo controlled ovarian stimulation or in vitro maturation (IVM) for the acquisition of mature oocytes has distinct implications for gene expression, we sought to evaluate the effects of these procedures on the expression of competence-related genes in single-cell oocytes. Healthy Nelore cows of reproductive age were synchronized to harvest in vivo matured oocytes; ovaries from slaughtered animals were used to obtain cumulus-oocyte complexes that were in vitro matured. Single-cell gene expression was performed using TaqMan Low-Density Arrays and 42 genes were evaluated. In silico analysis of protein interactions and Gene Ontology (GO) analysis was performed. Reduced gene expression was observed for 24 targets in IVM oocytes when compared with those of in vivo matured oocytes (P < 0.05). Differences ranged from 1.5-fold to 4.8-fold higher in in vivo oocytes and the BMP15 (5.28), GDF9 (6.23), NOBOX (7.25), HSPA8 (7.85) and MSX1 (11.00) showed the greatest fold increases. The strongest score of functional interactions was observed between the CDC20 and CKS2, with the differentially expressed gene CDC20 being the main marker behind GO enrichment. IVM negatively affected the expression of important genes related to oocyte competency, and showed higher expression levels in in vivo matured oocytes. In vivo controlled ovarian stimulation may be a better strategy to achieve proper oocyte competence and increase the success of assisted reproductive technologies.

Application of single-cell transcriptome sequencing in gastric cancer

Gastric cancer (GC) is the fifth most common cancer worldwide and the third leading cause of cancer death. With the development of single-cell RNA-sequencing (scRNA-seq) technology, the research on GC has gradually developed from the histopathological level to the transcriptional level. In this paper, we discuss the principle of scRNA-seq technology and its application in GC research, including the transcriptional characteristics and origin of GC precancerous lesions, intratumor heterogeneity of primary tumors, tumor microenvironment, and metastatic dissemination.

Aneuploidy in mammalian oocytes and the impact of maternal ageing

During fertilization, the egg and the sperm are supposed to contribute precisely one copy of each chromosome to the embryo. However, human eggs frequently contain an incorrect number of chromosomes - a condition termed aneuploidy, which is much more prevalent in eggs than in either sperm or in most somatic cells. In turn, aneuploidy in eggs is a leading cause of infertility, miscarriage and congenital syndromes. Aneuploidy arises as a consequence of aberrant meiosis during egg development from its progenitor cell, the oocyte. In human oocytes, chromosomes often segregate incorrectly. Chromosome segregation errors increase in women from their mid-thirties, leading to even higher levels of aneuploidy in eggs from women of advanced maternal age, ultimately causing age-related infertility. Here, we cover the two main areas that contribute to aneuploidy: (1) factors that influence the fidelity of chromosome segregation in eggs of women from all ages and (2) factors that change in response to reproductive ageing. Recent discoveries reveal new error-causing pathways and present a framework for therapeutic strategies to extend the span of female fertility.

Chromosome-level genome and recombination map of the male buffalo

BACKGROUND

The swamp buffalo (Bubalus bubalis carabanesis) is an economically important livestock supplying milk, meat, leather, and draft power. Several female buffalo genomes have been available, but the lack of high-quality male genomes hinders studies on chromosome evolution, especially Y, as well as meiotic recombination.

RESULTS

Here, a chromosome-level genome with a contig N50 of 72.2 Mb and a fine-scale recombination map of male buffalo were reported. We found that transposable elements (TEs) and structural variants (SVs) may contribute to buffalo evolution by influencing adjacent gene expression. We further found that the pseudoautosomal region (PAR) of the Y chromosome is subject to stronger purification selection. The meiotic recombination map showed that there were 2 obvious recombination hotspots on chromosome 8, and the genes around them were mainly related to tooth development, which may have helped to enhance the adaption of buffalo to inferior feed. Among several genomic features, TE density has the strongest correlation with recombination rates. Moreover, the TE subfamily, SINE/tRNA, is likely to play a role in driving recombination into SVs.

CONCLUSIONS

The male genome and sperm sequencing will facilitate the understanding of the buffalo genomic evolution and functional research.

Versatile, facile and low-cost single-cell isolation, culture and sequencing by optical tweezer-assisted pool-screening

Real-time image-based sorting of target cells in a precisely indexed manner is desirable for sequencing or cultivating individual human or microbial cells directly from clinical or environmental samples; however, the versatility of existing methods is limited as they are usually not broadly applicable to all cell sizes. Here, an optical tweezer-assisted pool-screening and single-cell isolation (OPSI) system is established for precise, indexed isolation of individual bacterial, yeast or human-cancer cells. A controllable static flow field that acts as a cell pool is achieved in a microfluidics chip, to enable precise and ready screening of cells of 1 to 40 μm in size by bright-field, fluorescence, or Raman imaging. The target cell is then captured by a 1064 nm optical tweezer and deposited as one-cell-harboring nanoliter microdroplets in a one-cell-one-tube manner. For bacterial, yeast and human cells, OPSI achieves a >99.7% target-cell sorting purity and a 10-fold elevated speed of 10-20 cells per min. Moreover, OPSI-based one-cell RNA-seq of human cancer cells yields high quality and reproducible single-cell transcriptome profiles. The versatility, facileness, flexibility, modularized design, and low cost of OPSI suggest its broad applications for image-based sorting of target cells.

Rapid Evolution of the Fine-scale Recombination Landscape in Wild House Mouse (Mus musculus) Populations

Meiotic recombination is an important evolutionary force and an essential meiotic process. In many species, recombination events concentrate into hotspots defined by the site-specific binding of PRMD9. Rapid evolution of Prdm9's zinc finger DNA-binding array leads to remarkably abrupt shifts in the genomic distribution of hotspots between species, but the question of how Prdm9 allelic variation shapes the landscape of recombination between populations remains less well understood. Wild house mice (Mus musculus) harbor exceptional Prdm9 diversity, with >150 alleles identified to date, and pose a particularly powerful system for addressing this open question. We employed a coalescent-based approach to construct broad- and fine-scale sex-averaged recombination maps from contemporary patterns of linkage disequilibrium in nine geographically isolated wild house mouse populations, including multiple populations from each of three subspecies. Comparing maps between wild mouse populations and subspecies reveals several themes. First, we report weak fine- and broad-scale recombination map conservation across subspecies and populations, with genetic divergence offering no clear prediction for recombination map divergence. Second, most hotspots are unique to one population, an outcome consistent with minimal sharing of Prdm9 alleles between surveyed populations. Finally, by contrasting aggregate hotspot activity on the X versus autosomes, we uncover evidence for population-specific differences in the degree and direction of sex dimorphism for recombination. Overall, our findings illuminate the variability of both the broad- and fine-scale recombination landscape in M. musculus and underscore the functional impact of Prdm9 allelic variation in wild mouse populations.

Incorporating cell hierarchy to decipher the functional diversity of single cells

Cells possess functional diversity hierarchically. However, most single-cell analyses neglect the nested structures while detecting and visualizing the functional diversity. Here, we incorporate cell hierarchy to study functional diversity at subpopulation, club (i.e., sub-subpopulation), and cell layers. Accordingly, we implement a package, SEAT, to construct cell hierarchies utilizing structure entropy by minimizing the global uncertainty in cell-cell graphs. With cell hierarchies, SEAT deciphers functional diversity in 36 datasets covering scRNA, scDNA, scATAC, and scRNA-scATAC multiome. First, SEAT finds optimal cell subpopulations with high clustering accuracy. It identifies cell types or fates from omics profiles and boosts accuracy from 0.34 to 1. Second, SEAT detects insightful functional diversity among cell clubs. The hierarchy of breast cancer cells reveals that the specific tumor cell club drives AREG-EGFT signaling. We identify a dense co-accessibility network of cis-regulatory elements specified by one cell club in GM12878. Third, the cell order from the hierarchy infers periodic pseudo-time of cells, improving accuracy from 0.79 to 0.89. Moreover, we incorporate cell hierarchy layers as prior knowledge to refine nonlinear dimension reduction, enabling us to visualize hierarchical cell layouts in low-dimensional space.

Superhydrophilic–superhydrophobic patterned surfaces: From simplified fabrication to emerging applications

Superhydrophilic–superhydrophobic patterned surfaces constitute a branch of surface chemistry involving the two extreme states of superhydrophilicity and superhydrophobicity combined on the same surface in precise patterns. Such surfaces have many advantages, including controllable wettability, enrichment ability, accessibility, and the ability to manipulate and pattern water droplets, and they offer new functionalities and possibilities for a wide variety of emerging applications, such as microarrays, biomedical assays, microfluidics, and environmental protection. This review presents the basic theory, simplified fabrication, and emerging applications of superhydrophilic–superhydrophobic patterned surfaces. First, the fundamental theories of wettability that explain the spreading of a droplet on a solid surface are described. Then, the fabrication methods for preparing superhydrophilic–superhydrophobic patterned surfaces are introduced, and the emerging applications of such surfaces that are currently being explored are highlighted. Finally, the remaining challenges of constructing such surfaces and future applications that would benefit from their use are discussed.

Turning coldspots into hotspots: targeted recruitment of axis protein Hop1 stimulates meiotic recombination in Saccharomyces cerevisiae

The DNA double-strand breaks that initiate meiotic recombination are formed in the context of the meiotic chromosome axis, which in Saccharomyces cerevisiae contains a meiosis-specific cohesin isoform and the meiosis-specific proteins Hop1 and Red1. Hop1 and Red1 are important for double-strand break formation; double-strand break levels are reduced in their absence and their levels, which vary along the lengths of chromosomes, are positively correlated with double-strand break levels. How axis protein levels influence double-strand break formation and recombination remains unclear. To address this question, we developed a novel approach that uses a bacterial ParB-parS partition system to recruit axis proteins at high levels to inserts at recombination coldspots where Hop1 and Red1 levels are normally low. Recruiting Hop1 markedly increased double-strand breaks and homologous recombination at target loci, to levels equivalent to those observed at endogenous recombination hotspots. This local increase in double-strand breaks did not require Red1 or the meiosis-specific cohesin component Rec8, indicating that, of the axis proteins, Hop1 is sufficient to promote double-strand break formation. However, while most crossovers at endogenous recombination hotspots are formed by the meiosis-specific MutLγ resolvase, crossovers that formed at an insert locus were only modestly reduced in the absence of MutLγ, regardless of whether or not Hop1 was recruited to that locus. Thus, while local Hop1 levels determine local double-strand break levels, the recombination pathways that repair these breaks can be determined by other factors, raising the intriguing possibility that different recombination pathways operate in different parts of the genome.

Testis-Specific Isoform of Na+-K+ ATPase and Regulation of Bull Fertility

An advanced understanding of sperm function is relevant for evidence-based male fertility prediction and addressing male infertility. A standard breeding soundness evaluation (BSE) merely identifies gross abnormalities in bulls, whereas selection based on single nucleotide polymorphisms and genomic estimated breeding values overlooks sub-microscopic differences in sperm. Molecular tools are important for validating genomic selection and advancing knowledge on the regulation of male fertility at an interdisciplinary level. Therefore, research in this field is now focused on developing a combination of in vitro sperm function tests and identifying biomarkers such as sperm proteins with critical roles in fertility. The Na+-K+ ATPase is a ubiquitous transmembrane protein and its α4 isoform (ATP1A4) is exclusively expressed in germ cells and sperm. Furthermore, ATP1A4 is essential for male fertility, as it interacts with signaling molecules in both raft and non-raft fractions of the sperm plasma membrane to regulate capacitation-associated signaling, hyperactivation, sperm-oocyte interactions, and activation. Interestingly, ATP1A4 activity and expression increase during capacitation, challenging the widely accepted dogma of sperm translational quiescence. This review discusses the literature on the role of ATP1A4 during capacitation and fertilization events and its prospective use in improving male fertility prediction.

Frontiers in single cell analysis: multimodal technologies and their clinical perspectives

Single cell multimodal analysis is at the frontier of single cell research: it defines the roles and functions of distinct cell types through simultaneous analysis to provide unprecedented insight into cellular processes. Current single cell approaches are rapidly moving toward multimodal characterizations. It replaces one-dimensional single cell analysis, for example by allowing for simultaneous measurement of transcription and post-transcriptional regulation, epigenetic modifications and/or surface protein expression. By providing deeper insights into single cell processes, multimodal single cell analyses paves the way to new understandings in various cellular processes such as cell fate decisions, physiological heterogeneity or genotype-phenotype linkages. At the forefront of this, microfluidics is key for high-throughput single cell analysis. Here, we present an overview of the recent multimodal microfluidic platforms having a potential in biomedical research, with a specific focus on their potential clinical applications.

Karyotype of the Blastocoel Fluid Derived by Laser-Assisted Hatching Demonstrates a Low Agreement With the Trophectoderm

Objective

The aim of this study is to compare the amplification efficiency and the genomic profiles of blastocoel fluid (BF) derived by laser-assisted hatching and trophectoderm (TE) cells derived from the same blastocyst.

Methods

Fifty-four fresh blastocysts underwent shrinkage by laser-assisted hatching, and each BF sample was collected individually. BF and TE cells were retrieved from each blastocyst for chromosome analysis through multiple annealing and looping-based amplification cycles (MALBAC) and next-generation sequencing (NGS).

Results

Fifty-four BF samples and 32 TE samples were retrieved for this study. Out of the 54 BF samples, only 35 provided reliable NGS data for comprehensive chromosome analysis (64.8%), while all 32 TE samples did (100%). Finally, there were 23 pairs of BF and TE samples from the same blastocyst. Only 17.4% of the BF-DNA karyotypes were completely agreeable with the TE samples (4/23).

Conclusion

Blastocoel fluid derived by laser-assisted hatching is easy to operate, and BF-DNA can be successfully amplified and subjected to NGS. Due to the low amplification efficiency and increased discordance with TE, BF does not adequately represent the status of the rest of the blastocyst. The use of BF as a single source of DNA for preimplantation genetic screening (PGS) is not yet advised.

Single-cell sequencing: expansion, integration and translation

With the rapid advancement in sequencing technologies, the concept of omics has revolutionized our understanding of cellular behaviors. Conventional omics investigation approaches measure the averaged behaviors of multiple cells, which may easily hide signals represented by a small-cell cohort, urging for the development of techniques with enhanced resolution. Single-cell RNA sequencing, investigating cell transcriptomics at the resolution of a single cell, has been rapidly expanded to investigate other omics such as genomics, proteomics and metabolomics since its invention. The requirement for comprehensive understanding of complex cellular behavior has led to the integration of multi-omics and single-cell sequencing data with other layers of information such as spatial data and the CRISPR screening technique towards gained knowledge or innovative functionalities. The development of single-cell sequencing in both dimensions has rendered it a unique field that offers us a versatile toolbox to delineate complex diseases, including cancers.

HBV genome-enriched single cell sequencing revealed heterogeneity in HBV-driven hepatocellular carcinoma (HCC)

BACKGROUND

Hepatitis B virus (HBV) related hepatocellular carcinoma (HCC) is heterogeneous and frequently contains multifocal tumors, but how the multifocal tumors relate to each other in terms of HBV integration and other genomic patterns is not clear.

METHODS

To interrogate heterogeneity of HBV-HCC, we developed a HBV genome enriched single cell sequencing (HGE-scSeq) procedure and a computational method to identify HBV integration sites and infer DNA copy number variations (CNVs).

RESULTS

We performed HGE-scSeq on 269 cells from four tumor sites and two tumor thrombi of a HBV-HCC patient. HBV integrations were identified in 142 out of 269 (53%) cells sequenced, and were enriched in two HBV integration hotspots chr1:34,397,059 (CSMD2) and chr8:118,557,327 (MED30/EXT1). There were also 162 rare integration sites. HBV integration sites were enriched in DNA fragile sites and sequences around HBV integration sites were enriched for microhomologous sequences between human and HBV genomes. CNVs were inferred for each individual cell and cells were grouped into four clonal groups based on their CNVs. Cells in different clonal groups had different degrees of HBV integration heterogeneity. All of 269 cells carried chromosome 1q amplification, a recurrent feature of HCC tumors, suggesting that 1q amplification occurred before HBV integration events in this case study. Further, we performed simulation studies to demonstrate that the sequential events (HBV infecting transformed cells) could result in the observed phenotype with biologically reasonable parameters.

CONCLUSION

Our HGE-scSeq data reveals high heterogeneity of HCC tumor cells in terms of both HBV integrations and CNVs. There were two HBV integration hotspots across cells, and cells from multiple tumor sites shared some HBV integration and CNV patterns.

inGAP-family: Accurate Detection of Meiotic Recombination Loci and Causal Mutations by Filtering Out Artificial Variants due to Genome Complexities

Accurately identifying DNA polymorphisms can bridge the gap between phenotypes and genotypes and is essential for molecular marker assisted genetic studies. Genome complexities, including large-scale structural variations, bring great challenges to bioinformatic analysis for obtaining high-confidence genomic variants, as sequence differences between non-allelic loci of two or more genomes can be misinterpreted as polymorphisms. It is important to correctly filter out artificial variants to avoid false genotyping or estimation of allele frequencies. Here, we present an efficient and effective framework, inGAP-family, to discover, filter, and visualize DNA polymorphisms and structural variants (SVs) from alignment of short reads. Applying this method to polymorphism detection on real datasets shows that elimination of artificial variants greatly facilitates the precise identification of meiotic recombination points as well as causal mutations in mutant genomes or quantitative trait loci. In addition, inGAP-family provides a user-friendly graphical interface for detecting polymorphisms and SVs, further evaluating predicted variants and identifying mutations related to genotypes. It is accessible at https://sourceforge.net/projects/ingap-family/.

Advances and applications of single-cell omics technologies in plant research

Single-cell sequencing approaches reveal the intracellular dynamics of individual cells and answer biological questions with high-dimensional catalogs of millions of cells, including genomics, transcriptomics, chromatin accessibility, epigenomics, and proteomics data across species. These emerging yet thriving technologies have been fully embraced by the field of plant biology, with a constantly expanding portfolio of applications. Here, we introduce the current technical advances used for single-cell omics, especially single-cell genome and transcriptome sequencing. Firstly, we overview methods for protoplast and nucleus isolation and genome and transcriptome amplification. Subsequently, we use well-executed benchmarking studies to highlight advances made through the application of single-cell omics techniques. Looking forward, we offer a glimpse of additional hurdles and future opportunities that will introduce broad adoption of single-cell sequencing with revolutionary perspectives in plant biology.

RecombineX: A generalized computational framework for automatic high-throughput gamete genotyping and tetrad-based recombination analysis

Meiotic recombination is an essential biological process that ensures faithful chromosome segregation and promotes parental allele shuffling. Tetrad analysis is a powerful approach to quantify the genetic makeups and recombination landscapes of meiotic products. Here we present RecombineX (https://github.com/yjx1217/RecombineX), a generalized computational framework that automates the full workflow of marker identification, gamete genotyping, and tetrad-based recombination profiling based on any organism or genetic background with batch processing capability. Aside from conventional reference-based analysis, RecombineX can also perform analysis based on parental genome assemblies, which facilitates analyzing meiotic recombination landscapes in their native genomic contexts. Additional features such as copy number variation profiling and missing genotype inference further enhance downstream analysis. RecombineX also includes a dedicate module for simulating the genomes and reads of recombinant tetrads, which enables fine-tuned simulation-based hypothesis testing. This simulation module revealed the power and accuracy of RecombineX even when analyzing tetrads with very low sequencing depths (e.g., 1-2X). Tetrad sequencing data from the budding yeast Saccharomyces cerevisiae and green alga Chlamydomonas reinhardtii were further used to demonstrate the accuracy and robustness of RecombineX for organisms with both small and large genomes, manifesting RecombineX as an all-around one stop solution for future tetrad analysis. Interestingly, our re-analysis of the budding yeast tetrad sequencing data with RecombineX and Oxford Nanopore sequencing revealed two unusual structural rearrangement events that were not noticed before, which exemplify the occasional genome instability triggered by meiosis.

Per-nucleus crossover covariation is regulated by chromosome organization

Meiotic crossover (CO) recombination between homologous chromosomes regulates chromosome segregation and promotes genetic diversity. Human females have different CO patterns than males, and some of these features contribute to the high frequency of chromosome segregation errors. In this study, we show that CO covariation is transmitted to progenies without detectable selection in both human males and females. Further investigations show that chromosome pairs with longer axes tend to have stronger axis length covariation and a stronger correlation between axis length and CO number, and the consequence of these two effects would be the stronger CO covariation as observed in females. These findings reveal a previously unsuspected feature for chromosome organization: long chromosome axes are more coordinately regulated than short ones. Additionally, the stronger CO covariation may work with human female-specific CO maturation inefficiency to confer female germlines the ability to adapt to changing environments on evolution.

New insights regarding origin of monosomy occurrence in early developing embryos as demonstrated in preimplantation genetic testing

Introduction

Analyses of miscarriage products indicate that the majority of aneuploidies in early developing embryos derive from errors occurring during maternal meiosis and the paternal contribution is less than 10%. Our aim was to assess the aneuploidy (mainly monosmies) frequencies at the earliest stages of embryo development, 3 days following fertilization during In vitro fertilization (IVF) treatments and to elucidate their parental origin. Later, we compared monosomies rates of day 3 to those of day 5 as demonstrated from Preimplantation Genetic Testing for Structural chromosomal Rearrangement (PGT-SR) results.

Methods

For a retrospective study, we collected data of 210 Preimplantation Genetic Testing for Monogenic Disorder (PGT-M) cycles performed between years 2008 and 2019.This study includes 2083 embryos, of 113 couples. It also included 432 embryos from 90 PGT-SR cycles of other 45 patients, carriers of balanced translocations. Defining the parental origin of aneuploidy in cleavage stage embryos was based on haplotypes analysis of at least six informative markers flanking the analyzed gene. For comprehensive chromosomal screening (CCS), chromosomal microarray (CMA) and next generation sequencing (NGS) was used.

Results

We inspected haplotype data of 40 genomic regions, flanking analyzed genes located on 9 different chromosomes.151 (7.2%) embryos presented numerical alterations in the tested chromosomes. We found similar paternal and maternal contribution to monosomy at cleavage stage. We demonstrated paternal origin in 51.5% of the monosomy, and maternal origin in 48.5% of the monosomies cases.

Conclusion

In our study, we found equal parental contribution to monosomies in cleavage-stage embryos. Comparison to CCS analyses of PGT-SR patients revealed a lower rate of monosomy per chromosome in embryos at day 5 of development. This is in contrast to the maternal dominancy described in studies of early miscarriage. Mitotic errors and paternal involvement in chemical pregnancies and IVF failure should be re-evaluated. Our results show monosomies are relatively common and may play a role in early development of ART embryos.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13039-022-00582-5.

Towards the detection of copy number variation from single sperm sequencing in cattle

BACKGROUND

Copy number variation (CNV) has been routinely studied using bulk-cell sequencing. However, CNV is not well studied on the single-cell level except for humans and a few model organisms.

RESULTS

We sequenced 143 single sperms of two Holstein bulls, from which we predicted CNV events using 14 single sperms with deep sequencing. We then compared the CNV results derived from single sperms with the bulk-cell sequencing of one bull's family trio of diploid genomes. As a known CNV hotspot, segmental duplications were also predicted using the bovine ARS-UCD1.2 genome. Although the trio CNVs validated only some single sperm CNVs, they still showed a distal chromosomal distribution pattern and significant associations with segmental duplications and satellite repeats.

CONCLUSION

Our preliminary results pointed out future research directions and highlighted the importance of uniform whole genome amplification, deep sequence coverage, and dedicated software pipelines for CNV detection using single cell sequencing data.

Genome-wide recombination map construction from single sperm sequencing in cattle

BACKGROUND

Meiotic recombination is one of the important phenomena contributing to gamete genome diversity. However, except for human and a few model organisms, it is not well studied in livestock, including cattle.

RESULTS

To investigate their distributions in the cattle sperm genome, we sequenced 143 single sperms from two Holstein bulls. We mapped meiotic recombination events at high resolution based on phased heterozygous single nucleotide polymorphism (SNP). In the absence of evolutionary selection pressure in fertilization and survival, recombination events in sperm are enriched near distal chromosomal ends, revealing that such a pattern is intrinsic to the molecular mechanism of meiosis. Furthermore, we further validated these findings in single sperms with results derived from sequencing its family trio of diploid genomes and our previous studies of recombination in cattle.

CONCLUSIONS

To our knowledge, this is the first large-scale single sperm whole-genome sequencing effort in livestock, which provided useful information for future studies of recombination, genome instability, and male infertility.

A Brief Overview of Radiation-Induced Effects on Spermatogenesis and Oncofertility

Simple Summary

Spermatogenesis is one of the most important processes for the propagation of life; however, the testes’ ability to form sperm via this differentiation process is highly radiosensitive and easily impacted by exposure to environmental, occupational, or therapeutic radiation. Furthermore, the possibility that radiation effects on the gonads can be passed on from generation to generation should not be overlooked. This review focuses on the radiation-induced effects on spermatogenesis and the transgenerational effects. We also explore the potential of novel radiobiological approaches to improve male fertility preservation during radiotherapy.

Abstract

The genotoxicity of radiation on germ cells may be passed on to the next generation, thus its elucidation is not only a scientific issue but also an ethical, legal, and social issue in modern society. In this article, we briefly overview the effects of radiation on spermatogenesis and its associated genotoxicity, including the latest findings in the field of radiobiology. The potential role of transgenerational effects is still poorly understood, and further research in this area is desirable. Furthermore, from the perspective of oncofertility, we discuss the historical background and clinical importance of preserving male fertility during radiation treatment and the potential of microbeam radiotherapy. We hope that this review will contribute to stimulating further discussions and investigations for therapies for pediatric and adolescent/young adult patients.

Sensitivity to copy number variation analysis in single cell genomics

While previous studies have given some guidance, the sensitivity of copy number calling in single-cell genomics is still not comprehensive. We studied the impact of sequencing depth and other factors on single-cell copy number analysis. Sequencing Data from 26 datasets were retrieved, and 2946 single cells passed the filter. Thirty-eight single cells were independently downscaled to evaluate copy number variation (CNV) detection sensitivity at different bin sizes. The sensitivity of whole genome amplification (WGA) approaches and cell types to CNV calling were evaluated using downsampling of 101 and 70 cells. Cluster analysis based on t-SNE was executed to evaluate CNV calling performance. Our results suggest 0.75× sequencing depth with moderate resolution (250 kb bin size) may be a practical guideline considering both sequencing cost and performance of copy number calling, which can be appropriately optimized based on amplification approach, cell type, and sample complexity.

Spontaneous mutation rate estimates for the principal malaria vectors Anopheles coluzzii and Anopheles stephensi

Using high-depth whole genome sequencing of F0 mating pairs and multiple individual F1 offspring, we estimated the nuclear mutation rate per generation in the malaria vectors Anopheles coluzzii and Anopheles stephensi by detecting de novo genetic mutations. A purpose-built computer program was employed to filter actual mutations from a deep background of superficially similar artifacts resulting from read misalignment. Performance of filtering parameters was determined using software-simulated mutations, and the resulting estimate of false negative rate was used to correct final mutation rate estimates. Spontaneous mutation rates by base substitution were estimated at 1.00 × 10⁻⁹ (95% confidence interval, 2.06 × 10⁻¹⁰—2.91 × 10⁻⁹) and 1.36 × 10⁻⁹ (95% confidence interval, 4.42 × 10⁻¹⁰—3.18 × 10⁻⁹) per site per generation in A. coluzzii and A. stephensi respectively. Although similar studies have been performed on other insect species including dipterans, this is the first study to empirically measure mutation rates in the important genus Anopheles, and thus provides an estimate of µ that will be of utility for comparative evolutionary genomics, as well as for population genetic analysis of malaria vector mosquito species.

Circular DNA in the human germline and its association with recombination

Extrachromosomal circular DNA (eccDNA) is common in somatic tissue, but its existence and effects in the human germline are unexplored. We used microscopy, long-read DNA sequencing, and new analytic methods to document thousands of eccDNAs from human sperm. EccDNAs derived from all genomic regions and mostly contained a single DNA fragment, although some consisted of multiple fragments. The generation of eccDNA inversely correlates with the meiotic recombination rate, and chromosomes with high coding-gene density and Alu element abundance form the least eccDNA. Analysis of insertions in human genomes further indicates that eccDNA can persist in the human germline when the circular molecules reinsert themselves into the chromosomes. Our results suggest that eccDNA has transient and permanent effects on the germline. They explain how differences in the physical and genetic map might arise and offer an explanation of how Alu elements coevolved with genes to protect genome integrity against deleterious mutations producing eccDNA.

A method for low-coverage single-gamete sequence analysis demonstrates adherence to Mendel's first law across a large sample of human sperm

Recently published single-cell sequencing data from individual human sperm (n=41,189; 969-3377 cells from each of 25 donors) offer an opportunity to investigate questions of inheritance with improved statistical power, but require new methods tailored to these extremely low-coverage data (∼0.01× per cell). To this end, we developed a method, named rhapsodi, that leverages sparse gamete genotype data to phase the diploid genomes of the donor individuals, impute missing gamete genotypes, and discover meiotic recombination breakpoints, benchmarking its performance across a wide range of study designs. We then applied rhapsodi to the sperm sequencing data to investigate adherence to Mendel's Law of Segregation, which states that the offspring of a diploid, heterozygous parent will inherit either allele with equal probability. While the vast majority of loci adhere to this rule, research in model and non-model organisms has uncovered numerous exceptions whereby 'selfish' alleles are disproportionately transmitted to the next generation. Evidence of such 'transmission distortion' (TD) in humans remains equivocal in part because scans of human pedigrees have been under-powered to detect small effects. After applying rhapsodi to the sperm data and scanning for evidence of TD, our results exhibited close concordance with binomial expectations under balanced transmission. Together, our work demonstrates that rhapsodi can facilitate novel uses of inferred genotype data and meiotic recombination events, while offering a powerful quantitative framework for testing for TD in other cohorts and study systems.

Single-Cell Sequencing to Unveil the Mystery of Embryonic Development

Embryonic development is a fundamental physiological process that can provide tremendous insights into stem cell biology and regenerative medicine. In this process, cell fate decision is highly heterogeneous and dynamic, and investigations at the single-cell level can greatly facilitate the understanding of the molecular roadmap of embryonic development. Rapid advances in the technology of single-cell sequencing offer a perfectly useful tool to fulfill this purpose. Despite its great promise, single-cell sequencing is highly interdisciplinary, and successful applications in specific biological contexts require a general understanding of its diversity as well as the advantage versus limitations for each of its variants. Here, the technological principles of single-cell sequencing are consolidated and its applications in the study of embryonic development are summarized. First, the technology basics are presented and the available tools for each step including cell isolation, library construction, sequencing, and data analysis are discussed. Then, the works that employed single-cell sequencing are reviewed to investigate the specific processes of embryonic development, including preimplantation, peri-implantation, gastrulation, and organogenesis. Further, insights are provided on existing challenges and future research directions.

Accurate and scalable variant calling from single cell DNA sequencing data with ProSolo

Accurate single cell mutational profiles can reveal genomic cell-to-cell heterogeneity. However, sequencing libraries suitable for genotyping require whole genome amplification, which introduces allelic bias and copy errors. The resulting data violates assumptions of variant callers developed for bulk sequencing. Thus, only dedicated models accounting for amplification bias and errors can provide accurate calls. We present ProSolo for calling single nucleotide variants from multiple displacement amplified (MDA) single cell DNA sequencing data. ProSolo probabilistically models a single cell jointly with a bulk sequencing sample and integrates all relevant MDA biases in a site-specific and scalable-because computationally efficient-manner. This achieves a higher accuracy in calling and genotyping single nucleotide variants in single cells in comparison to state-of-the-art tools and supports imputation of insufficiently covered genotypes, when downstream tools cannot handle missing data. Moreover, ProSolo implements the first approach to control the false discovery rate reliably and flexibly. ProSolo is implemented in an extendable framework, with code and usage at: https://github.com/prosolo/prosolo.

Insights from Initial Variant Detection by Sequencing Single Sperm in Cattle

Meiotic de novo mutation (DNM) is one of the important phenomena contributing to gamete genome diversity. However, except for humans and a few model organisms, they are not well studied in livestock, including cattle. Moreover, bulk sperm samples have been routinely utilized in experiments, which include millions of single sperm cells and only report high-frequency variants. In this study, we isolated and sequenced 143 single sperms from two Holstein bulls and identified hundreds of candidate DNM events in ten sperms with deep sequencing coverage. We estimated DNM rates ranging from 1.08 × 10−8 to 3.78 × 10−8 per nucleotide per generation. We further validated 12 out of 14 selected DNM events using Sanger sequencing. To our knowledge, this is the first single sperm whole-genome sequencing effort in livestock, which provided useful information for future studies of point mutations and male fertility. Our preliminary results pointed out future research directions and highlighted the importance of uniform whole genome amplification, deep sequence coverage, and dedicated software pipelines for genetic variant detection using single-cell sequencing data.

Microfluidic single-cell transcriptomics: moving towards multimodal and spatiotemporal omics

Cells are the basic units of life with vast heterogeneity. Single-cell transcriptomics unveils cell-to-cell gene expression variabilities, discovers novel cell types, and uncovers the critical roles of cellular heterogeneity in biological processes. The recent advances in microfluidic technologies have greatly accelerated the development of single-cell transcriptomics with regard to throughput, sensitivity, cost, and automation. In this article, we review state-of-the-art microfluidic single-cell transcriptomics, with a focus on the methodologies. We first summarize six typical microfluidic platforms for isolation and transcriptomic analysis of single cells. Then the on-going trend of microfluidic transcriptomics towards multimodal omics, which integrates transcriptomics with other omics to provide more comprehensive pictures of gene expression networks, is discussed. We also highlight single-cell spatial transcriptomics and single-cell temporal transcriptomics that provide unprecedented spatiotemporal resolution to reveal transcriptomic dynamics in space and time, respectively. The emerging applications of microfluidic single-cell transcriptomics are also discussed. Finally, we discuss the current challenges to be tackled and provide perspectives on the future development of microfluidic single-cell transcriptomics.

Effect of parental origin and predictors for obtaining a euploid embryo in balanced translocation carriers

RESEARCH QUESTION

What is the effect of parental origin of translocation and predictors for obtaining a euploid embryo in preimplantation genetic testing for chromosomal structural rearrangements (PGT-SR) for balanced translocation carriers?

DESIGN

A total of 179 PGT-SR cycles and 614 blastocysts from 123 couples carrying a balanced translocation were retrospectively analysed. Next-generation sequencing (NGS) was performed after trophectoderm biopsy.

RESULTS

There were no differences in ovarian stimulation parameters or PGT-SR outcomes regarding the number of oocytes retrieved (11.95 ± 5.71 versus 11.82 ± 6.26), blastulation rate (0.42 ± 0.27 versus 0.45 ± 0.28), biopsy cancellation rate (11.7% versus 12.9%), the number of blastocysts for biopsy (3.70 ± 2.58 versus 4.04 ± 3.51), or the proportion of euploid embryos (23.80% versus 25.42%), aneuploid embryos (58.10% versus 57.52%) and mosaic embryos (18.10% versus 17.06%) between female carriers and male partner carriers. In a multivariate logistic regression model, the number of blastocysts for biopsy (adjusted odds ratio 1.752; 95% confidence interval 1.359-2.259; P < 0.001) was significantly associated with the chance of obtaining at least one euploid embryo. Receiver operating characteristic analysis with a threshold of 3.5 was conducted to calculate the number of blastocysts required for biopsy to obtain at least one euploid embryo.

CONCLUSIONS

The parental origin of translocation does not significantly affect the PGT-SR outcomes for young balanced translocation carriers. At least 3.5 blastocysts are required to obtain one euploid embryo. Couples should be informed that the probability of obtaining one euploid embryo is low when fewer than 4 blastocysts are obtained in one PGT cycle.