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Identification of smRNA-based cell-type markers for the stem cell manufacture system with a statistical scoring function

ABSTRACT: Identification of smRNA-based cell-type markers for the stem cell manufacture system with a statistical scoring function

PROVIDER: PRJNA852701 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR19850390.fastq.gz	Fastqsanger.gz
	SRR19850391.fastq.gz	Fastqsanger.gz
	SRR19850392.fastq.gz	Fastqsanger.gz
	SRR19850393.fastq.gz	Fastqsanger.gz
	SRR19850394.fastq.gz	Fastqsanger.gz

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Identification of smRNA-based cell-type markers for the stem cell manufacture system with a statistical scoring function

Project description:Cell-type biomarkers are useful in stem cell manufacture to monitor cell purification, cell quantity, and quality. However, the study on cell-type marker, specifically for stem cell manufacture, is limited. The emerging questions are which RNA transcripts can serve as biomarkers during stem cell culture, and what method can efficiently and accurately discover these biomarkers. We developed a scoring function system to identify small RNA (smRNA) biomarkers with RNA-seq data. We applied the method to two data sets, one for extracellular smRNAs and the other for intracellular smRNAs. To get the RNA-seq data from intracellular smRNAs, we cultured four types of cells: human embryo stem cells (H9), neural stem cells (NSC), hESC-derived endothelial cells (EC) and conducted small RNA-seq to their intracellular smRNAs. Using these data, we identified a set of smRNAs as candidates of biomarkers for different types of cells.

2022-08-01 | GSE206925 | GEO

Identification of RNA-based cell-type markers for stem-cell manufacturing systems with a statistical scoring function.

Project description:Cell-type biomarkers are useful in stem-cell manufacturing to monitor cell purity, quantity, and quality. However, the study on cell-type markers, specifically for stem cell manufacture, is limited. Emerging questions include which RNA transcripts can serve as biomarkers during stem cell culture and how to discover these biomarkers efficiently and precisely. We developed a scoring function system to identify RNA biomarkers with RNA-seq data for systems that have a limited number of cell types. We applied the method to two data sets, one for extracellular RNAs (ex-RNAs) and the other for intracellular microRNAs (miRNAs). The first data set has RNA-seq data of ex-RNAs from cell culture media for six different types of cells, including human embryonic stem cells. To get the RNA-seq data from intracellular miRNAs, we cultured three types of cells: human embryonic stem cells (H9), neural stem cells (NSC), hESC-derived endothelial cells (EC) and conducted small RNA-seq to their intracellular miRNAs. Using these data, we identified a set of ex-RNAs/smRNAs as candidates of biomarkers for different types of cells for cell manufacture. The validity of these findings was confirmed by the utilization of additional data sets and experimental procedures. We also used deep-learning-based prediction methods and simulated data to validate these discovered biomarkers.

| S-EPMC10861185 | biostudies-literature

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Project description:The Immunoscore is a method to quantify the immune cell infiltration within cancers to predict the disease prognosis. Previous immune profiling approaches relied on limited immune markers to establish patients’ tumor immunity. However, immune cells exhibit a higher-level complexity that is typically not obtained by the conventional immunohistochemistry methods. Herein, we present a spatially variant immune infiltration score, termed as SpatialVizScore, to quantify immune cells infiltration within lung tumor samples using multiplex protein imaging data. Imaging mass cytometry (IMC) was used to target 26 markers in tumors to identify stromal, immune, and cancer cell states within 26 human tissues from lung cancer patients. Unsupervised clustering methods dissected the spatial infiltration of cells in tissue using the high-dimensional analysis of 16 immune markers and other cancer and stroma enriched labels to profile alterations in the tumors’ immune infiltration patterns. Spatially resolved maps of distinct tumors determined the spatial proximity and neighborhoods of immune-cancer cell pairs. These SpatialVizScore maps provided a ranking of patients’ tumors consisting of immune inflamed, immune suppressed, and immune cold states, demonstrating the tumor’s immune continuum assigned to three distinct infiltration score ranges. Several inflammatory and suppressive immune markers were used to establish the cell-based scoring schemes at the single-cell and pixel-level, depicting the cellular spectra in diverse lung tissues. Thus, SpatialVizScore is an emerging quantitative method to deeply study tumor immunology in cancer tissues.

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Project description:Animal and plant genomes produce numerous small RNAs (smRNAs) regulating gene expression affecting metabolism, development, and epigenetic inheritance. In order to characterize the repertoire of endogenous microRNAs and potential gene targets, we conducted smRNA and mRNA expression profiling over nine experimental treatments of cultures from the dinoflagellate Symbiodinium sp. A1, a photosynthetic symbiont of scleractinian corals. We identified a total of 75 novel smRNAs in Symbiodinum sp. A1 that share stringent key features with functional microRNAs from other model organisms. A subset of 38 smRNAs was predicted independently over all nine treatments and their putative gene targets were identified. We found 3,187 animal-like target sites in the 3'UTRs of 12,858 mRNAs and 53 plant-like target sites in 51,917 genes. We assembled a transcriptome of 58,649 genes and determined differentially expressed genes (DEGs) between treatments. Heat stress was found to produce a much larger number of DEGs than other treatments. Analysis of DEGs also revealed that minicircle-encoded photosynthesis proteins seem to be common targets of transcriptional regulation. Furthermore, we identified the core RNAi protein machinery in Symbiodinium. Integration of smRNA and mRNA expression profiling identified a variety of processes that could be under microRNA control, e.g. regulation of translation, DNA modification, and chromatin silencing. Given that Symbiodinium seems to have a paucity of transcription factors and differentially expressed genes, identification and characterization of its smRNA repertoire establishes the possibility of a range of gene regulatory mechanisms in dinoflagellates acting post-transcriptionally.

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YM500: An integrative small RNA sequencing (smRNA-seq) database for microRNA research

Project description:MicroRNAs (miRNAs) are small RNAs of ~22 nucleotides in length that are involved in the regulation of a variety of physiological and pathological processes. Advances in high-throughput small RNA sequencing (smRNA-seq), one of the next generation sequencing applications, have reshaped the miRNA research landscape. In this study, we established an integrative database containing analysis pipelines and analysis results of 609 human and mice smRNA-seq results, including public data from GEO and private ones. YM500 collects analysis results for miRNA quantification, for isomiR identification (incl. RNA editing), for arm switching discovery, and, more importantly, for novel miRNA predictions. Wetlab validation on >100 miRNAs confirmed high correlation between miRNA profiling and RT-qPCR results (R=0.84). This database allows researchers to search these 4 different types of analysis results via our interactive web interface. YM500 allows researchers to define the criteria of isomiRs, as well as integrates the information of dbSNP to help researchers to distinguish isomiRs from SNPs. A user-friendly interface is provided to integrate miRNA-related information and existing evidences from hundreds of sequencing datasets. The identified novel miRNAs and isomiRs hold the potentials for both basic research and biotech applications. YM500 is now available on http://ngs.ym.edu.tw/ym500/.

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