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Status |
Public on Jun 30, 2023 |
Title |
S94 |
Sample type |
SRA |
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Source name |
plasma
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Organism |
Homo sapiens |
Characteristics |
tissue: plasma age: 57 gender: male disease state: healthy
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Extracted molecule |
total RNA |
Extraction protocol |
Total RNA was extracted from plasma samples using the Qiagen miRNeasy Serum/Plasma Kit. Briefly, frozen plasma samples were thawed, vortexed and centrifuged for 16000 x g in 10 minutes and 50 µl was used for RNA extraction following the manufacturer’s protocol. Purified RNA was eluted in 50µl H2O and saved at -80C. 4 µl of purified RNA was used in a Small-seq protocol to construct the libraries (Hagemann-Jensen et al., 2018). Small RNA libraries were pooled and sequenced using an Illumina HiSeq 3000 platform for 100 bp single read.
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Library strategy |
ncRNA-Seq |
Library source |
transcriptomic |
Library selection |
size fractionation |
Instrument model |
Illumina HiSeq 3000 |
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Description |
94_S66_L001_R1_001
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Data processing |
Reads were mapped to 202,272 Ensembl transcript IDs using the Smallseq data analysis pipeline (Hagemann-Jensen et al., 2018), and to 4,121 transfer RNA fragments (tRF) using the MINTmap pipeline (Loher et al., 2017). Only small RNA with read counts higher than 1 in more than 20% of samples were kept, resulting in a list of 4,767 small RNA. Counts were rounded and data normalization and differential expression analysis was performed with the DESeq2 package (version 1.26.0) (Love et al. 2014). Small RNA levels were used as the dependent variable and chronological age as the explanatory variable. A local fit was used for estimating dispersions. Size factor normalized small RNA counts were obtained using the counts functions with arguments normalized = T. After DESeq2 analysis, small RNA with unclear transcripts biotypes were removed from all analysis since they indicate potential degradation products (i.e. protein coding, lncRNA, processed transcript, retained intron, …). Transcript biotypes were defined using the biomaRt package (version 2.42.0) (Durinck et al. 2005). A total of 587 small RNA were kept after this filtering step, of which 276 were significantly associated with age at an FDR threshold of 0.2. Genome_build: hg38 Supplementary_files_format_and_content: raw_counts_Smallseq_Ensembl.txt (raw counts) Supplementary_files_format_and_content: raw_counts_MINTmap_tRF.txt (raw counts) Supplementary_files_format_and_content: DESeq2_normalized_counts.xlsx (normalized counts) Supplementary_files_format_and_content: DESeq2_small_RNA_association_with_age.xlsx (significance table)
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Submission date |
Aug 23, 2021 |
Last update date |
Jun 30, 2023 |
Contact name |
Christian Günter Riedel |
E-mail(s) |
christian.riedel@ki.se
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Organization name |
Karolinska Institute
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Department |
Biosciences and Nutrition
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Lab |
Riedel
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Street address |
Blickagången 16 (Neo Building, 6th floor)
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City |
Huddinge |
State/province |
Stockholm |
ZIP/Postal code |
SE-141 57 |
Country |
Sweden |
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Platform ID |
GPL21290 |
Series (1) |
GSE182598 |
Age prediction from human blood plasma using proteomic and small RNA data: a comparative analysis |
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Relations |
BioSample |
SAMN20931525 |
SRA |
SRX11865165 |
Supplementary data files not provided |
SRA Run Selector |
Raw data are available in SRA |
Processed data are available on Series record |
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