Deep sequencing analysis of human red blood cells
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE27250 | GEO | 2012/07/01
SECONDARY ACCESSION(S): PRJNA137201
REPOSITORIES: GEO
Similar Datasets
Project description:Small RNAs isolated from RBCs were size fractionated by gel electrophoresis and used for the creation of 6 libraries. For the library from healthy children (library 1), RNA from 4 individuals was pooled. Libraries were multiplexed and analyzed on a 454 sequencing platform 26 yielding 569,621 sequence reads after demultiplexing into the 6 libraries Analysis of 6 small RNA libraries from human red blood cells
2012-06-30 | E-GEOD-27250 | biostudies-arrayexpress
Project description:Data dependent acquisition (DDA) is the method of choice for mass spectrometry based proteomics discovery experiments, data-independent acquisition (DIA) is steadily becoming more important. One of the most important requirement to perform a DIA analysis is the availability of spectral libraries for the peptide identification and quantification. Several researches were already conducted regarding the creation of spectral libraries from DDA analyses and obtaining identifications with these in DIA measurements. But so far only few experiments were conducted, to estimate the effect of these libraries on the quantitative level. In this work we created a spike-in gold standard dataset with known contents and ratios of proteins in a complex sample matrix. With this dataset, we first created spectral libraries using different sample preparation approaches with and without sample prefractionation on peptide and protein level. Two different search engines were used for protein identification. In total, five different spike-in states were compared with DIA analyses, comparing eight different spectral libraries generated by varying approaches and one library free method, as well as one default DDA analysis. Not only the number of identifications on peptide and protein level in the spectral libraries and the corresponding analyses was inspected, but also the number of expected and identified significant quantifications and their ratios were thoroughly examined. We found, that while libraries of prefractionationed samples are generally larger, the actually yielded identifications are not increased compared to repetitive non-fractionated measurements. Furthermore, we show that the accuracy of the quantifications is also highly dependent on the applied spectra library and also whether the peptide or protein level is analysed. Overall, the reproducibility and accuracy of DIA is superior to DDA in all analysed approaches.
2019-11-08 | PXD014956 | Pride
Project description:Data dependent acquisition (DDA) is the method of choice for mass spectrometry based proteomics discovery experiments, data-independent acquisition (DIA) is steadily becoming more important. One of the most important requirement to perform a DIA analysis is the availability of spectral libraries for the peptide identification and quantification. Several researches were already conducted regarding the creation of spectral libraries from DDA analyses and obtaining identifications with these in DIA measurements. But so far only few experiments were conducted, to estimate the effect of these libraries on the quantitative level. In this work we created a spike-in gold standard dataset with known contents and ratios of proteins in a complex sample matrix. With this dataset, we first created spectral libraries using different sample preparation approaches with and without sample prefractionation on peptide and protein level. Two different search engines were used for protein identification. In total, five different spike-in states were compared with DIA analyses, comparing eight different spectral libraries generated by varying approaches and one library free method, as well as one default DDA analysis. Not only the number of identifications on peptide and protein level in the spectral libraries and the corresponding analyses was inspected, but also the number of expected and identified significant quantifications and their ratios were thoroughly examined. We found, that while libraries of prefractionationed samples are generally larger, the actually yielded identifications are not increased compared to repetitive non-fractionated measurements. Furthermore, we show that the accuracy of the quantifications is also highly dependent on the applied spectra library and also whether the peptide or protein level is analysed. Overall, the reproducibility and accuracy of DIA is superior to DDA in all analysed approaches.
2019-11-08 | PXD012986 | Pride
Project description:Despite evolving stem cell and organoid application of next-generation sequencing (NGS) at single cell level, current techniques in NGS library preparation are restrictive as individual samples within a single library are indistinguishable, necessitating the laborious and costly preparation of distinct libraries for each sample. To combat this challenge, we report the development of a novel poly(ß-amino) ester labeling system synthesized with inexpensive, common reagents, termed POLYseq, capable of efficiently delivering fluorescent molecules or sample-distinguishing DNA barcodes through non-covalent binding enabling rapid creation of custom libraries.
2021-06-22 | GSE163971 | GEO
Project description:This article describes a mass spectrometry data set generated from human substantia nigra tissue that was spiked with iRT peptides. The data set can be used as a spectral library for analysis of the human brain, especially human substantia nigra, for example, in the context of Parkinson’s disease. Obtaining a sufficient amount of high-quality substantia nigra tissue is the key limiting factor for establishing a brain region-specific spectral library. Hence, combining existing spectral libraries for data-independent acquisition analysis (DIA) can overcome this major limitation. Moreover, these data can be used to map brain region-specific proteins and to model brain region-specific pathways. Both can improve our understanding of the functioning of the brain in greater depth. In addition, these data can also be used to determine the optimal settings for measuring proteins and peptides of interest. To create the substantia nigra-specific spectral library, the tissue was first homogenized and then fractionated via different types of SDS gel electrophoresis, resulting in 18 fractions. These fractions were analysed in triplicate by nanoHPLC-ESI-MS/MS, resulting in 54 data files.
2019-08-15 | PXD011076 | Pride
Project description:Circulating human red blood cells (RBCs) consist of mature erythrocytes, and immature reticulocytes. As being anucleated cells, RBCs lack typical, abundant transcriptomes but are known to contain low amounts of diverse long transcripts and microRNAs. The exact role and importance of these RNAs is, however, lacking. To study this further, we have explored the RNA content of RBCs as well as extracellular vesicles of RBCs using next-generation sequencing (NGS). Furthermore, to understand the dynamics of the RBC transcriptome, we performed single cell RNA sequencing on RBCs both from fresh blood and blood unit. Analysis of the single cell transcriptomes revealed that while the majority of the cells don’t have detectable RNA, the remaining, approximately 10% of the cells fall into three sub-populations based on their RNA content. Overall decrease in the RNA quantity over the populations is observed. Qualitative changes include the differences in the hemoglobin (Hb) content of the cells, and the changes in the expression of ribosomal and mitochondrial genes. A previously unknown transcript of a long non-coding RNA, MALAT1 (Metastasis Associated Lung Adenocarcinoma Transcript 1) is the most enriched marker gene for one subpopulation of RBCs, suggesting a role for MALAT1 in reticulocyte maturation. Enriched pathways in RBC transcriptome, such as autophagy, reflect the processes required for reticulocyte maturation to erythrocytes. RBC transcriptome is transferred to extracellular vesicles (EVs), suggesting the vesiculation as the mechanism to remove the cellular contents at the final stages of erythrocyte maturation.
2019-12-20 | GSE108378 | GEO
Project description:Circulating human red blood cells (RBCs) consist of mature erythrocytes, and immature reticulocytes. As being anucleated cells, RBCs lack typical, abundant transcriptomes but are known to contain low amounts of diverse long transcripts and microRNAs. The exact role and importance of these RNAs is, however, lacking. To study this further, we have explored the RNA content of RBCs as well as extracellular vesicles of RBCs using next generation sequencing (NGS). Furthermore, to understand the dynamics of the RBC transcriptome we performed single cell RNA sequencing on RBCs both from fresh blood and blood unit. Analysis of the single cell transcriptomes revealed that while the majority of the cells don’t have detectable RNA the remaining, approximately 10% of the cells fall into three sub-populations based on their RNA content. Overall decrease in the RNA quantity over the populations is observed. Qualitative changes include the differences in the hemoglobin (Hb) content of the cells, and the changes in the expression of ribosomal and mitochondrial genes. A previously unknown transcript of a long non-coding RNA, MALAT1 (Metastasis Associated Lung Adenocarcinoma Transcript 1) is the most enriched marker gene for one subpopulation of RBCs suggesting a role for MALAT1 in reticulocyte maturation. Enriched pathways in RBC transcriptome, such as autophagy, reflect the processes required for reticulocyte maturation to erythrocytes. RBC transcriptome is transferred to extracellular vesicles (EVs) suggesting the vesiculation as the mechanism to remove the cellular contents at the final stages of erythrocyte maturation.
2023-04-01 | GSE108241 | GEO
Project description:Background: Plasmodium falciparum causes the majority of malaria mortality worldwide, and the disease occurs during the asexual red blood cell (RBC) stage of infection. In the absence of an effective and available vaccine, and with increasing drug resistance, asexual RBC stage parasites are an important research focus. In recent years, mass spectrometry-based proteomics using Data Dependent Acquisition (DDA) has been extensively used to understand the biochemical processes within the parasite. However, DDA is problematic for the detection of low abundance proteins, protein coverage, and has poor run-to-run reproducibility. Results: Here, we present a comprehensive P. falciparum-infected RBC (iRBC) spectral library to measure the abundance of 44,449 peptides from 3,113 P. falciparum and 1,617 RBC proteins using a Data Independent Acquisition (DIA) approach. The spectral library includes proteins expressed in the three morphologically distinct RBC stages (ring, trophozoite, schizont), the RBC compartment of trophozoite-iRBCs, and the cytosolic fractions from uninfected RBCs (uRBC). This spectral library contains 87% of P. falciparum proteins with previously blood-stage protein-level evidence as well as 692 previously unidentified proteins. The P. falciparum spectral library was successfully applied to generate semi-quantitative proteomics datasets that characterise the three distinct asexual parasite stages in RBCs, and compare artemisinin resistant (Cam3.IIR539T) and sensitive (Cam3.IIrev) parasites. Conclusion: A reproducible, high-coverage proteomics spectral library and analysis method has been generated for investigating sets of proteins expressed in the iRBC stage of P. falciparum malaria. This will provide a foundation for an improved understanding of parasite biology, pathogenesis, drug mechanisms and vaccine candidate discovery for malaria.
2021-08-06 | PXD027241 | Pride
Project description:Background: Plasmodium falciparum causes the majority of malaria mortality worldwide, and the disease occurs during the asexual red blood cell (RBC) stage of infection. In the absence of an effective and available vaccine, and with increasing drug resistance, asexual RBC stage parasites are an important research focus. In recent years, mass spectrometry-based proteomics using Data Dependent Acquisition (DDA) has been extensively used to understand the biochemical processes within the parasite. However, DDA is problematic for the detection of low abundance proteins, protein coverage, and has poor run-to-run reproducibility. Results: Here, we present a comprehensive P. falciparum-infected RBC (iRBC) spectral library to measure the abundance of 44,449 peptides from 3,113 P. falciparum and 1,617 RBC proteins using a Data Independent Acquisition (DIA) approach. The spectral library includes proteins expressed in the three morphologically distinct RBC stages (ring, trophozoite, schizont), the RBC compartment of trophozoite-iRBCs, and the cytosolic fractions from uninfected RBCs (uRBC). This spectral library contains 87% of P. falciparum proteins with previously blood-stage protein-level evidence as well as 692 previously unidentified proteins. The P. falciparum spectral library was successfully applied to generate semi-quantitative proteomics datasets that characterise the three distinct asexual parasite stages in RBCs, and compare artemisinin resistant (Cam3.IIR539T) and sensitive (Cam3.IIrev) parasites. Conclusion: A reproducible, high-coverage proteomics spectral library and analysis method has been generated for investigating sets of proteins expressed in the iRBC stage of P. falciparum malaria. This will provide a foundation for an improved understanding of parasite biology, pathogenesis, drug mechanisms and vaccine candidate discovery for malaria.
2021-11-15 | PXD027301 | Pride
Project description:Comparison of the endogenous small RNA content of Arabidopsis flower bud tissue: wild type vs. mutants in polIV pathways Keywords: High throughput 454 small RNA sequencing. Size fractionated small RNA from total RNA extracts was ligated to adapters, purified again and reverse transcribed. After PCR amplification the sample was subjected to 454 high throughput pyrosequencing. Please see www.454.com for details of the sequencing technology.
2008-02-25 | E-GEOD-10180 | biostudies-arrayexpress