Single-Cell RNA Sequencing in Yeast Using the 10× Genomics Chromium Device

Vermeersch, Lieselotte; Jariani, Abbas; Helsen, Jana; Heineike, Benjamin M.; Verstrepen, Kevin J.

doi:10.1007/978-1-0716-2257-5_1

Cited by 6 publications

(4 citation statements)

References 20 publications

(25 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Additionally, they contain only 1-3 pg of total RNA per cell, which is 10 times less than that in mammalian cells, necessitating a specific RNA extraction procedure. Some methods are designed for single-cell sequencing of yeast organisms, such as Smart-seq, which uses zymolyase for efficient lysis of yeast cells within the droplets during single-cell droplet formation in the 10x Genomics Chromium Single Cell 3’ protocol ( 111 ). The authors validated these results using single-cell time-lapse microscopy.…”

Section: Single-cell Transcriptomics: Revolutionizing the Exploration...mentioning

confidence: 99%

Single cell genomics based insights into the impact of cell-type specific microbial internalization on disease severity

Soni,

Pandey

2024

Front. Immunol.

View full text Add to dashboard Cite

Host-microbe interactions are complex and ever-changing, especially during infections, which can significantly impact human physiology in both health and disease by influencing metabolic and immune functions. Infections caused by pathogens such as bacteria, viruses, fungi, and parasites are the leading cause of global mortality. Microbes have evolved various immune evasion strategies to survive within their hosts, which presents a multifaceted challenge for detection. Intracellular microbes, in particular, target specific cell types for survival and replication and are influenced by factors such as functional roles, nutrient availability, immune evasion, and replication opportunities. Identifying intracellular microbes can be difficult because of the limitations of traditional culture-based methods. However, advancements in integrated host microbiome single-cell genomics and transcriptomics provide a promising basis for personalized treatment strategies. Understanding host-microbiota interactions at the cellular level may elucidate disease mechanisms and microbial pathogenesis, leading to targeted therapies. This article focuses on how intracellular microbes reside in specific cell types, modulating functions through persistence strategies to evade host immunity and prolong colonization. An improved understanding of the persistent intracellular microbe-induced differential disease outcomes can enhance diagnostics, therapeutics, and preventive measures.

show abstract

Section: Single-cell Transcriptomics: Revolutionizing the Exploration...mentioning

confidence: 99%

Single cell genomics based insights into the impact of cell-type specific microbial internalization on disease severity

Soni,

Pandey

2024

Front. Immunol.

View full text Add to dashboard Cite

show abstract

“…Prior to loading the Chromium device, frozen cells were fixed in 80% methanol for 10 minutes, washed three times with sorbitol, and diluted to 1000 cells/uL. The 10x reagents were modified by removing 1uL of beads and replacing it with 1uL of zymolyase according to Vermeersch et al 88 . Using these modified reagents, the Chromium device was loaded conventionally and all other aspects of library preparation and loading was done according to 10x and Illumina standard protocols.…”

Section: Single-cell Sequencing Of Gpa1 Allele-replacement Strainsmentioning

confidence: 99%

Single-cell eQTL mapping in yeast reveals a tradeoff between growth and reproduction

Boocock,

Alexander,

Tapia

et al. 2023

Preprint

View full text Add to dashboard Cite

Expression quantitative trait loci (eQTLs) provide a key bridge between noncoding DNA sequence variants and organismal traits. The effects of eQTLs can differ among tissues, cell types, and cellular states, but these differences are obscured by gene expression measurements in bulk populations. We developed a one-pot approach to map eQTLs inSaccharomyces cerevisiaeby single-cell RNA sequencing (scRNA-seq) and applied it to over 100,000 single cells from three crosses. We used scRNA-seq data to genotype each cell, measure gene expression, and classify the cells by cell-cycle stage. We mapped thousands of local and distant eQTLs and identified interactions between eQTL effects and cell-cycle stages. We took advantage of single-cell expression information to identify hundreds of genes with allele-specific effects on expression noise. We used cell-cycle stage classification to map 20 loci that influence cell-cycle progression. One of these loci influenced the expression of genes involved in the mating response. We showed that the effects of this locus arise from a common variant (W82R) in the geneGPA1, which encodes a signaling protein that negatively regulates the mating pathway. The 82R allele increases mating efficiency at the cost of slower cell-cycle progression and is associated with a higher rate of outcrossing in nature. Our results provide a more granular picture of the effects of genetic variants on gene expression and downstream traits.

show abstract

“…ScRNA-seq can annotate unclassified cells according to the mRNA expression pattern of each cell and, thus, is a particularly powerful tool for analyzing cell diversity and heterogeneity, predicting the functions of single-cell populations, and determining functional roadmaps of cell differentiation [18][19][20]. Single-cell molecular profiling is widely expected to make important contributions to our understanding of many fields, such as neurobiology [21], organ growth [22], cancer biology [23], clinical diagnosis [24], immunology [25], microbiology [26] and embryology [27], and is becoming the new focus of life science research. In 2013, scRNA-seq was rated as the annual technology by Nature Methods [28].…”

Section: Introductionmentioning

confidence: 99%

Single-Cell Atlas Reveals the Hemocyte Subpopulations and Stress Responses in Asian Giant Softshell Turtle during Hibernation

Hong

Wang

et al. 2023

Biology

View full text Add to dashboard Cite

Hibernation in turtle species is an adaptive survival strategy to colder winter conditions or food restrictions. However, the mechanisms underlying seasonal adaptions remain unclear. In the present study, we collected hemocytes from Pelochelys cantorii and compared the molecular signature of these cells between the active state and hibernation period based on single-cell RNA sequencing (scRNA-seq) analysis. We found six cell types and identified a list of new marker genes for each cell subpopulation. Moreover, several heat shock genes, including the Hsp40 family chaperone gene (DNAJ) and HSP temperature-responsive genes (HSPs), were upregulated during the hibernation period, which predicted these genes may play crucial roles in the stress response during hibernation. Additionally, compared to hemocytes in the active state, several upregulated differentially expressed immune-related genes, such as stat1, traf3, and socs6, were identified in hemocytes during the hibernation period, thus indicating the important immune function of hemocytes. Therefore, our findings provide a unified classification of P. cantorii hemocytes and identify the genes related to the stress response, thereby providing a better understanding of the adaptive mechanisms of hibernation.

show abstract

Single-Cell RNA Sequencing in Yeast Using the 10× Genomics Chromium Device

Cited by 6 publications

References 20 publications

Single cell genomics based insights into the impact of cell-type specific microbial internalization on disease severity

Single cell genomics based insights into the impact of cell-type specific microbial internalization on disease severity

Single-cell eQTL mapping in yeast reveals a tradeoff between growth and reproduction

Single-Cell Atlas Reveals the Hemocyte Subpopulations and Stress Responses in Asian Giant Softshell Turtle during Hibernation

Contact Info

Product

Resources

About