scholarly journals A Genome-Wide Library of MADM Mice for Single-Cell Genetic Mosaic Analysis

2020 ◽  
Author(s):  
Ximena Contreras ◽  
Amarbayasgalan Davaatseren ◽  
Nicole Amberg ◽  
Andi H. Hansen ◽  
Johanna Sonntag ◽  
...  
Cell Reports ◽  
2021 ◽  
Vol 35 (12) ◽  
pp. 109274
Author(s):  
Ximena Contreras ◽  
Nicole Amberg ◽  
Amarbayasgalan Davaatseren ◽  
Andi H. Hansen ◽  
Johanna Sonntag ◽  
...  

Author(s):  
Ximena Contreras ◽  
Amarbayasgalan Davaatseren ◽  
Nicole Amberg ◽  
Andi H. Hansen ◽  
Johanna Sonntag ◽  
...  

SUMMARYMosaic Analysis with Double Markers (MADM) offers a unique approach to visualize and concomitantly manipulate genetically-defined cells in mice with single-cell resolution. MADM applications include the analysis of lineage; single-cell morphology and physiology; genomic imprinting phenotypes; and dissection of cell-autonomous gene functions in vivo in health and disease. Yet, MADM could only be applied to <25% of all mouse genes on select chromosomes thus far. To overcome this limitation, we generated transgenic mice with knocked-in MADM cassettes near the centromeres of all 19 autosomes and validated their use across organs. With this resource, >96% of the entire mouse genome can now be subjected to single-cell genetic mosaic analysis. Beyond proof-of-principle, we applied our MADM library to systematically trace sister chromatid segregation in distinct mitotic cell lineages. We found striking chromosome-specific biases in segregation patterns, reflecting a putative mechanism for the asymmetric segregation of genetic determinants in somatic stem cell division.


2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Akdes Serin Harmanci ◽  
Arif O. Harmanci ◽  
Xiaobo Zhou

AbstractRNA sequencing experiments generate large amounts of information about expression levels of genes. Although they are mainly used for quantifying expression levels, they contain much more biologically important information such as copy number variants (CNVs). Here, we present CaSpER, a signal processing approach for identification, visualization, and integrative analysis of focal and large-scale CNV events in multiscale resolution using either bulk or single-cell RNA sequencing data. CaSpER integrates the multiscale smoothing of expression signal and allelic shift signals for CNV calling. The allelic shift signal measures the loss-of-heterozygosity (LOH) which is valuable for CNV identification. CaSpER employs an efficient methodology for the generation of a genome-wide B-allele frequency (BAF) signal profile from the reads and utilizes it for correction of CNVs calls. CaSpER increases the utility of RNA-sequencing datasets and complements other tools for complete characterization and visualization of the genomic and transcriptomic landscape of single cell and bulk RNA sequencing data.


2021 ◽  
Author(s):  
Yanling Peng ◽  
Qitong Huang ◽  
Rui Kamada ◽  
Keiko Ozato ◽  
Yubo Zhang ◽  
...  

Alternative transcription start sites (TSSs) usage plays a critical role in gene transcription regulation in mammals. However, precisely identifying alternative TSSs remains challenging at the genome-wide level. Here, we report a single-cell genomic technology for alternative TSSs annotation and cell heterogeneity detection. In the method, we utilize Fluidigm C1 system to capture individual cells of interest, SMARTer cDNA synthesis kit to recover full-length cDNAs, then dual priming oligonucleotide system to specifically enrich TSSs for genomic analysis. We apply this method to a genome-wide study of alternative TSSs identification in two different IFN-β stimulated mouse embryonic fibroblasts (MEFs). We quantify the performance of our method and find it as accurate as other single cell methods for the detection of TSSs. Our data are also clearly discriminate two IFN-β stimulated MEFs. Moreover, our results indicate 82% expressed genes in these two cell types containing multiple TSSs, which is much higher than previous predictions based on CAGE (58%) or empirical determination (54%) in various cell types. This indicates that alternative TSSs are more pervasive than expected and implies our strategy could position them at an unprecedented sensitivity. It would be helpful for elucidating their biological insights in future.


2020 ◽  
Author(s):  
Mary V. Arrastia ◽  
Joanna W. Jachowicz ◽  
Noah Ollikainen ◽  
Matthew S. Curtis ◽  
Charlotte Lai ◽  
...  

ABSTRACTIn eukaryotes, the nucleus is organized into a three dimensional structure consisting of both local interactions such as those between enhancers and promoters, and long-range higher-order structures such as nuclear bodies. This organization is central to many aspects of nuclear function, including DNA replication, transcription, and cell cycle progression. Nuclear structure intrinsically occurs within single cells; however, measuring such a broad spectrum of 3D DNA interactions on a genome-wide scale and at the single cell level has been a great challenge. To address this, we developed single-cell split-pool recognition of interactions by tag extension (scSPRITE), a new method that enables measurements of genome-wide maps of 3D DNA structure in thousands of individual nuclei. scSPRITE maximizes the number of DNA contacts detected per cell enabling high-resolution genome structure maps within each cells and is easy-to-use and cost-effective. scSPRITE accurately detects chromosome territories, active and inactive compartments, topologically associating domains (TADs), and higher-order structures within single cells. In addition, scSPRITE measures cell-to-cell heterogeneity in genome structure at different levels of resolution and shows that TADs are dynamic units of genome organization that can vary between different cells within a population. scSPRITE will improve our understanding of nuclear architecture and its relationship to nuclear function within an individual nucleus from complex cell types and tissues containing a diverse population of cells.


2021 ◽  
Author(s):  
Shunta Sakaguchi ◽  
Yasushi Okochi ◽  
Chiharu Tanegashima ◽  
Osamu Nishimura ◽  
Tadashi Uemura ◽  
...  

During development, positional information directs cells to specific fates, leading them to differentiate with their own transcriptomes and express specific behaviors and functions. However, the mechanisms underlying these processes in a genome-wide view remain ambiguous, partly because the single-cell transcriptomic data of early developing embryos containing both accurate spatial and lineage information is still lacking. Here, we report a new single-cell transcriptome atlas of Drosophila gastrulae, divided into 65 transcriptomically distinct clusters. We found that the expression profiles of plasma-membrane-related genes, but not those of transcription factor genes, represented each germ layer, supporting the nonequivalent contribution of each transcription factor mRNA level to effector gene expression profiles at the transcriptome level. We also reconstructed the spatial expression patterns of all genes at the single-cell stripe level as the smallest unit. This atlas is an important resource for the genome-wide understanding of the mechanisms by which genes cooperatively orchestrate Drosophila gastrulation.


2017 ◽  
Author(s):  
Hannah A. Pliner ◽  
Jonathan Packer ◽  
José L. McFaline-Figueroa ◽  
Darren A. Cusanovich ◽  
Riza Daza ◽  
...  

AbstractOver a million DNA regulatory elements have been cataloged in the human genome, but linking these elements to the genes that they regulate remains challenging. We introduce Cicero, a statistical method that connects regulatory elements to target genes using single cell chromatin accessibility data. We apply Cicero to investigate how thousands of dynamically accessible elements orchestrate gene regulation in differentiating myoblasts. Groups of co-accessible regulatory elements linked by Cicero meet criteria of “chromatin hubs”, in that they are physically proximal, interact with a common set of transcription factors, and undergo coordinated changes in histone marks that are predictive of gene expression. Pseudotemporal analysis revealed a subset of elements bound by MYOD in myoblasts that exhibit early opening, potentially serving as the initial sites of recruitment of chromatin remodeling and histone-modifying enzymes. The methodological framework described here constitutes a powerful new approach for elucidating the architecture, grammar and mechanisms of cis-regulation on a genome-wide basis.


2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Micha Müller ◽  
Lucas Pelkmans ◽  
Scott Berry

AbstractCoordination of RNA abundance and production rate with cell size has been observed in diverse organisms and cell populations. However, how cells achieve such ‘scaling’ of transcription with size is unknown. Here we describe a genome-wide siRNA screen to identify regulators of global RNA production rates in HeLa cells. We quantify the single-cell RNA production rate using metabolic pulse-labelling of RNA and subsequent high-content imaging. Our quantitative, single-cell measurements of DNA, nascent RNA, proliferating cell nuclear antigen (PCNA), and total protein, as well as cell morphology and population-context, capture a detailed cellular phenotype. This allows us to account for changes in cell size and cell-cycle distribution (G1/S/G2) in perturbation conditions, which indirectly affect global RNA production. We also take advantage of the subcellular information to distinguish between nascent RNA localised in the nucleolus and nucleoplasm, to approximate ribosomal and non-ribosomal RNA contributions to perturbation phenotypes. Perturbations uncovered through this screen provide a resource for exploring the mechanisms of regulation of global RNA metabolism and its coordination with cellular states.


2014 ◽  
Vol 226 (03) ◽  
Author(s):  
F Ponthan ◽  
D Pal ◽  
J Vormoor ◽  
O Heidenreich
Keyword(s):  

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