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| Status |
Public on Dec 31, 2020 |
| Title |
Alternative transcription start sites contribute to acute-stress–induced transcriptome response in human skeletal muscle |
| Organism |
Homo sapiens |
| Experiment type |
Expression profiling by high throughput sequencing
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| Summary |
More than half of human protein-coding genes have an alternative transcription start site (TSS). We aimed to investigate the contribution of alternative TSSs to the acute-stress–induced transcriptome response in human tissue (skeletal muscle) using the cap analysis of gene expression approach. TSSs were examined at baseline and during recovery after acute stress (a cycling exercise).
We identified 44,680 CAGE TSS clusters (including 3,764 first defined) belonging to 12,268 genes and annotated for the first time 290 TSSs belonging to 163 genes. The transcriptome dynamically changes during the first hours after acute stress; the change in the expression of 10% of genes was associated with the activation of alternative TSSs, indicating differential TSSs usage. The majority of the alternative TSSs do not increase proteome complexity suggesting that the function of thousands of alternative TSSs is associated with the fine regulation of mRNA isoform expression from a gene due to the transcription factor-specific activation of various alternative TSSs. We identified individual muscle promoter regions for each TSS using muscle open chromatin data (ATAC-seq and DNase-seq). Then, using the positional weight matrix approach we predicted time course activation of “classic” transcription factors involved in response of skeletal muscle to contractile activity, as well as diversity of less/un-investigated factors.
Transcriptome response induced by acute stress related to activation of the alternative TSSs indicates that differential TSSs usage is an essential mechanism of fine regulation of gene response to stress stimulus. A comprehensive resource of accurate TSSs and individual promoter regions for each TSS in muscle was created. This resource together with the positional weight matrix approach can be used to accurate prediction of TFs in any gene(s) of interest involved in the response to various stimuli, interventions or pathological conditions in human skeletal muscle.
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| Overall design |
Ten amateur endurance-trained athletes (long distance runners, cyclists and cross country skiers, median age 32 years [interquartile range, 30–36 years]; weight 75 kg [71–78 kg]; V’O2max/kg [maximal pulmonary O2 consumption rate] 58 ml/min/kg [54–60 ml/min/kg of body mass]) were involved in our study. Each subject carried out an intermittent exercise (60 min, [3 min at intensity 50% of lactate threshold [LT4 , power at blood lactate 4 mmol/l] + 2 min, 100% LT4] x 12) on a cycle ergometer 2 h after a standardized breakfast (3582 kJ; 22 g protein, 154 g carbohydrates and 16 g fat). Subjects ate a standardized lunch (3714 kJ; 45 g protein, 183 g carbohydrates and 27 g fat) 1 h 15 min after an intermittent exercise. Biopsy samples were taken under local anesthesia (2 mL 2% lidocaine) using a Bergstrome needle with aspiration from the m. vastus lateralis prior to, 2 min, 1 h, 3 h, and 6 h after an intermittent exercise (1st, 2d, and 3d from the one leg, 4st and 5st from another leg).
For each subject samples from time points: prior to, 1 h, 3 h, and 6 h after an exercise were analyzed in one run. Additionally, we analyzed all samples from time point 2 min after an exercise in a separate run. To improve the quality of identification of CAGE TSSs, all data were used for calculation. However, differential expressions of CAGE TSSs and genes as well as differential TSSs usage were evaluated for time points: prior to, 1 h, 3 h, and 6 h after an exercise only.
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| Contributor(s) |
Popov DV, Makhnovskii PA |
| Citation(s) |
35869513 |
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| Submission date |
Dec 30, 2020 |
| Last update date |
Aug 05, 2022 |
| Contact name |
Pavel Makhnovsky |
| E-mail(s) |
maxpauel@gmail.com
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| Organization name |
Institute of Biomedical Problems of the Russian Academy of Sciences
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| Lab |
Laboratory of muscle physiology
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| Street address |
76A Khoroshevskoye shosse
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| City |
Moscow |
| ZIP/Postal code |
123007 |
| Country |
Russia |
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| Platforms (3) |
| GPL11154 |
Illumina HiSeq 2000 (Homo sapiens) |
| GPL16791 |
Illumina HiSeq 2500 (Homo sapiens) |
| GPL18573 |
Illumina NextSeq 500 (Homo sapiens) |
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| Samples (50)
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| Relations |
| BioProject |
PRJNA688748 |
| SRA |
SRP299847 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSE164081_DPI_robust_TSS_tag_clusters.bed.gz |
1.5 Mb |
(ftp)(http) |
BED |
| GSE164081_TSS_tag_cluster_annotation.txt.gz |
3.4 Mb |
(ftp)(http) |
TXT |
SRA Run Selector |
| Raw data are available in SRA |
| Processed data are available on Series record |
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