Illumina HiSeq 2500 paired end sequencing; Root transcriptome profiling in chilling-sensitive tomato (S. lycopersicum cv. Moneymaker) and the more cold-tolerant wild tomato S. habrochaites LA1777 compared at optimal and suboptimal temperature.(ERR1533153)
| Run | Spots | Bases | Size | GC content | Published | Access Type |
|---|---|---|---|---|---|---|
ERR1533153 |
18.6M | 4.7Gbp | 2.2G | 44.2% | 2016-07-25 | public |
This run has 2 reads per spot:
| L=126, 100% | L=126, 100% |
- Legend
Technical read Application Read L=4, 100% Length is 4, 100% spots contain this read ̅L=165, σ=92.8, 66% Average length is 165, standard deviation is 92.8, 66% spots contain this read
| Name | Value |
|---|---|
| ENA-FIRST-PUBLIC | 2016-07-24 |
| ENA-LAST-UPDATE | 2018-11-16 |
| Experiment | Library Name | Platform | Strategy | Source | Selection | Layout | Action |
|---|---|---|---|---|---|---|---|
| ERX1604045 | Sample 12_p | Illumina | RNA-Seq | TRANSCRIPTOMIC | cDNA | PAIRED |
| Biosample | Sample Description | Organism |
|---|---|---|
| SAMEA4079221 (ERS1250331) | Protocols: Seeds of S. lycopersicum cv. Moneymaker and S. habrochaites LA1777 were germinated in a climate-controlled room at 23°C as described above. Five-day-old germinated seedlings were separated into two groups: half of them were transferred to an identical climate room at 15°C (suboptimal-temperature treatment), whereas the other half remained in the room at 23°C (near-optimal temperature treatment). After 3 days, three replicates of whole roots were collected from both genotypes at the two temperature treatments and immediately frozen in liquid nitrogen. The samples were stored at −80°C until RNA extraction. Seeds of S. lycopersicum cv. Moneymaker and S. habrochaites LA1777 were germinated in a climate-controlled room at 23°C as described above. Five-day-old germinated seedlings were separated into two groups: half of them were transferred to an identical climate room at 15°C (suboptimal-temperature treatment), whereas the other half remained in the room at 23°C (near-optimal temperature treatment). After 3 days, three replicates of whole roots were collected from both genotypes at the two temperature treatments and immediately frozen in liquid nitrogen. The samples were stored at −80°C until RNA extraction. Total RNA from whole roots was extracted by TRIzol reagent according to the manufacturer's instructions (Sigma-Aldrich). The quantity and quality of total RNA treated with RNase-free DNase I (Thermo Scientific) were determined by an Agilent Technologies 2100 Bioanalyzer and RNA samples with RNA integrity number (RIN) > 8 were used for the RNA sequencing and quantitative RT-PCR analysis. Illumina HiSeq2500 (with v4 kit) and Nextera XT sample preparation kits were used for RNA sequencing and all raw reads were paired-end sequenced. Reads for each of the 12 samples were processed by CLC genomics workbench and were aligned to ITAG-cDNA 2.1 (with S. lycopersicum as reference genome). Read counts of each sample were used to quantify the gene expression. Differential expression analysis was carried out with the negative binomial test of DESeq R package v1.20.0 (Anders and Huber, 2010). The False Discovery Rate (FDR) threshold according the multiple testing correction of Benjamini-Hochberg FDR method (Benjamini and Hochberg, 1995) was applied and genes with an adjusted P-value (Padj ≤ 0.05) and log2-fold change in the ratio between 15 and 23°C of more than 1 and less than -1 defined the significantly differentially expressed genes (DEGs). The Plant MetGenMAP system was used to identify significantly altered pathways and for gene ontology (GO) term enrichment analysis (Joung et al, 2009). Functional annotation was retrieved from Panther (http://pantherdb.org) and SGN tomato (http://solgenomics.net). | Solanum lycopersicum |
| Bioproject | SRA Study | Title |
|---|---|---|
| PRJEB14805 | ERP016476 | Root transcriptome profiling in chilling-sensitive tomato (S. lycopersicum cv. Moneymaker) and the more cold-tolerant wild tomato S. habrochaites LA1777 compared at optimal and suboptimal temperature. |
In this study the root transcriptome profiles of young seedlings (5 days after germination at 23°C) of two tomato species differing in cold tolerance were analysed and compared after a subsequent treatment for 3 days at 23 or 15°C by RNAseq. Aim was to elucidate molecular mechanisms underlying root development associated with suboptimal-temperature tolerance during early seedling establishment.
SRA archive data
SRA archive data is normalized by the SRA load process and used by the SRA Toolkit to read and produce formats like FASTQ, SAM, etc. The default toolkit configuration enables it to find and retrieve SRA runs by accession.
Public SRA files are now available from GCP and AWS cloud platforms as well as from NCBI. Access to most data in the cloud requires a user account with the cloud service provider. The user’s account will incur costs for cloud compute or to copy data outside of the specified cloud service region.
| Type | Size | Location | Name | Free Egress | Access Type |
|---|---|---|---|---|---|
| SRA Normalized | 2,112,237 Kb | AWS | https://sra-pub-run-odp.s3.amazonaws.com/sra/ERR1533153/ERR1533153 | worldwide | anonymous |
| SRA Lite | 1,153,153 Kb | NCBI | https://sra-downloadb.be-md.ncbi.nlm.nih.gov/sos2/sra-pub-zq-18/ERR001/1533/ERR1533153/ERR1533153.lite.2 | worldwide | anonymous |
| AWS | s3://sra-pub-zq-6/ERR1533153/ERR1533153.lite.2 | s3.us-east-1 | aws identity | ||
| GCP | gs://sra-pub-zq-106/ERR1533153/ERR1533153.lite.2 | gs.us-east1 | gcp identity |
Original format
The original files submitted to SRA. These files may require specific software to open, read and interpret data.
| Type | Size | Location | Name | Free Egress | Access Type |
|---|---|---|---|---|---|
| fastq | 5,779,929 Kb | AWS | s3://sra-pub-src-14/ERR1533153/C40J5ANXX_102450-12_GTAGAGGA-ACTGCA_L007_R1.fastq.1 | - | Use Cloud Data Delivery |
| fastq | 5,779,929 Kb | AWS | s3://sra-pub-src-14/ERR1533153/C40J5ANXX_102450-12_GTAGAGGA-ACTGCA_L007_R2.fastq.1 | - | Use Cloud Data Delivery |
- Egress and Access: what does it mean?
-
Egress
term used by cloud providers to describe cost (charged to the user) of moving data outside of the storage region Free Egresscolumn indicates where the data can be accessed without an egress charge: - worldwide can be downloaded from anywhere for free
- s3.us-east-1 is free to access from machines running in Amazon's us-east-1 region, access from other regions or transport outside of AWS will require paying egress charges
- gs.US is free to access from machines running in Google’s gs.US region, access from other regions or transport outside of GCP will require paying egress charges
Access Typedescribes whether a cloud service user account is necessary for data access. "anonymous" access means general public access Namecolumn provides either a link to free download location at NCBI or a URL for the cloud provider storage location. Either s3:// for Amazon or gs:// for Google storage
- Why is SRA data in the cloud?
-
In order to support large scale (hyper parallel) data analyses SRA data is now available at GCP and AWS with few caveats:
- SRA data is copied to the cloud from NCBI. There may be a lag between availability from NCBI and from CSP (cloud service providers)
- To access public data user account with the cloud service provider is required. Your account will incur costs for cloud compute and/or to copy data (either archival or results of your comute) outside of the specified cloud service region
- Distribution of protected data is signed by NIH account and requires user to operate in the same region as the data
SRA has also begun to provide access to originally submitted source files:
- not all files have been validated by SRA
- not all files have been copied to cloud locations (recovering it from NCBI tape system takes time ).
- the volume of this type of data a much larger and it is not used as often so we will keep most of it on tape or "cold" storage in cloud. As a result the data may not be available instantly and restore requests will be served on first-come first-served basis and cost of resore may be charged to your user account.
- What is "Cloud Data Delivery"?
-
Please visit SRA Data Delivery service to request Sequence Read Archive (SRA) data to be delivered to an Amazon Web Services (AWS) or Google Cloud Platform (GCP) bucket of your choice.
Taxonomy Analysis
- Unidentified reads: 2.97%
- Identified reads: 97.03%
Strong signals
| SuperKingdom | Organism | Rank | %% | Kbp | Coverage |
|---|---|---|---|---|---|
| Eukaryota | Solanum lycopersicum | species | 76.6 | 3,596,274 | |
| Bacteria | Bacteria | superkingdom | 19.6 | 921,733 | |
| Eukaryota | Solanum pennellii | species | 0.7 | 31,651 | |
| Bacteria | Escherichia coli | species | 0.5 | 21,557 | 4.2 |
| Bacteria | Acinetobacter baumannii | species | 0.2 | 11,335 | 2.8 |
| Bacteria | Klebsiella aerogenes | species | 0.2 | 10,247 | 2.0 |
| Eukaryota | Solanum tuberosum | species | 0.1 | 5,895 | |
| Bacteria | Staphylococcus aureus | species | 0.1 | 4,426 | 1.6 |
| Bacteria | Klebsiella pneumoniae | species | 0.1 | 2,614 | 0.5 |
- How to read results?
Results show distribution of reads mapping to specific taxonomy nodes as a percentage of total reads within the analyzed run. In cases where a read maps to more than one related taxonomy node, the read is reported as originating from the lowest shared taxonomic node. So when a read maps to two species belonging to the same genus, it is assigned at the genus level. Sequence reads from a single organism will map to several taxonomy nodes spanning the organism’s lineage. The number of reads mapping to higher level nodes will typically be greater than those that map to terminal nodes.
STAT results are proportional to the size of sequenced genomes. Given a mixed sample containing several organisms at equal copy number, proportionally more reads originate from the larger genomes. This means that the percentages reported by STAT will reflect genome size and must be considered against the genomic complexity of the sequenced sample.
- How can I query this analysis data?
Please take a look at NCBI SRA Cloud-based Taxonomy Analysis Table