ID
45963
Descripción
Principal Investigator: Graziano Pesole, Prof, IBBE-CNR and University of Bari, Italy MeSH: https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000870 We have deeply sequenced total RNA and whole exome of six different post-mortem human snap-frozen tissues (brain, liver, lung, striated muscle, kidney, heart) from three unrelated healthy Caucasian individuals (males, aged 47-54) with the aim to characterize post-transcriptional events due to alternative splicing and RNA editing. In addition, to facilitate the detection of RNA editing sites we have also resequenced the entire genome of each individual. Data are also used to investigate tissue-specific abundance of mitochondrial DNA from exomes and its correlation with mitochondrial transcription, mass and respiratory activity. Tissues were obtained from Cureline (South San Francisco, CA, USA). DNA and RNA were purified using the DNeasy Blood and Tissue Kit (Qiagen, Hilden, Germany) and the RNeasy Plus Mini Kit (Qiagen, Hilden, Germany), respectively. Exome capture was performed using the TruSeq Exome Enrichment Kit (Illumina, San Diego, CA) and the sequencing was carried out at IGA Technology Services in Udine (Italy) on Illumina HiSeq 2000 (generating for each tissue approximately 40 millions of 100bp paired-end reads). Strand-oriented RNA reads (2x100bp) were generated using the TruSeq Stranded Total RNA Sample Prep Kit (Illumina, San Diego, CA, USA) and sequenced at IGA Technology Services in Udine (Italy) on Illumina HiSeq 2000 platform. Whole genome resequencing was performed at Personal Genomics in Italy on an Illumina HiSeq 2000 platform (2x100bp) with a mean coverage of 30X. MiRNA-Seq was instead performed at IBBE Institute (Italy) using the TruSeq Small RNA Sample Prep Kit on Illumina MiSeq platform. Preliminary bioinformatics analyses have been performed to check quality using FASTQC software and inconsistent read regions have been trimmed using trim_galore. All reads were mapped onto the human reference genome (version hg19) using GSNAP.
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Versiones (1)
- 26/3/24 26/3/24 - Madita Rudolph
Titular de derechos de autor
Graziano Pesole, Prof, IBBE-CNR and University of Bari, Italy
Subido en
26 de marzo de 2024
DOI
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Licencia
Creative Commons BY 4.0
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dbGaP phs000870 Characterization of Human Transcriptome by Computational and HTS Approaches
Eligibility Criteria
- StudyEvent: SEV1
- Eligibility Criteria
- The subject consent data table contains subject IDs, consent information, and affection status for case control status of the subject. All subjects are unrelated healthy individuals.
- The subject sample mapping data table contains mapping of study subject IDs to sample IDs. dbGaP samples are defined as the final preps submitted for genotyping, sequencing, and/or expression data. For example, if one patient (subject ID) gave one sample, and that sample was processed differently to generate 2 sequencing runs, there would be two rows, both using the same subject ID, but having 2 unique sample IDs. The data table also includes sample use.
- This subject phenotype table includes age, gender, race, diagnosis of participant, and post-mortem interval.
- This sample attributes table includes sample IDs, body site where sample was collected, analyte type, tumor status, histological type, sequencing type, and sequencing center.
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Eligibility Criteria
- StudyEvent: SEV1
- Eligibility Criteria
- The subject consent data table contains subject IDs, consent information, and affection status for case control status of the subject. All subjects are unrelated healthy individuals.
- The subject sample mapping data table contains mapping of study subject IDs to sample IDs. dbGaP samples are defined as the final preps submitted for genotyping, sequencing, and/or expression data. For example, if one patient (subject ID) gave one sample, and that sample was processed differently to generate 2 sequencing runs, there would be two rows, both using the same subject ID, but having 2 unique sample IDs. The data table also includes sample use.
- This subject phenotype table includes age, gender, race, diagnosis of participant, and post-mortem interval.
- This sample attributes table includes sample IDs, body site where sample was collected, analyte type, tumor status, histological type, sequencing type, and sequencing center.
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