| Run | Spots | Bases | Size | GC content | Published | Access Type |
|---|---|---|---|---|---|---|
SRR1758118 |
31.9M | 6.4Gbp | 4.8G | 47.4% | 2015-12-10 | public |
This run has 2 reads per spot:
| L=101, 100% | L=101, 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
| Experiment | Library Name | Platform | Strategy | Source | Selection | Layout | Action |
|---|---|---|---|---|---|---|---|
| SRX842421 | Illumina | RNA-Seq | TRANSCRIPTOMIC | cDNA | PAIRED |
| Biosample | Sample Description | Organism | Links |
|---|---|---|---|
| SAMN03284266 (SRS818597) | Coturnix japonica | PRJNA272589 |
| Bioproject | SRA Study | Title |
|---|---|---|
| PRJNA272589 | SRP052227 | Comprehensive identification of sexual dimorphism-associated differentially expressed genes in two-factorial designed RNA-seq data on Japanese Quail (Coturnix coturnix japonica) |
Japanese quail (Coturnix coturnix japonica) reach sexual maturity early, breed rapidly and successfully, and cost less and require less space than other birds raised for their meat and eggs. Given the value of this species for commercial production and experimental use as well as recent increasing demand, more studies are necessary to determine chromosomal regions and genes associated with gender and breed-differentiation in the species. Identification of sex-related genes can help target chromosomal regions for molecular sexing purposes. This study employed Trinity and edgeR for transcriptome analysis of next-generation RNA-seq data, which included 4 tissues obtained from 3 different breeds of Japanese quail (wild, miniature, and jumbo). The initial goal was to identify genes related to sexual dimorphism, as well as potential novel candidate genes for molecular sexing. Analysis and interpretation of differentially expressed genes shared between female and male tissue contrast groups provided insight into sex-related differences. Several of the genes identified in the present study as significant sex-related genes have been previously found in avian gene expression analyses (e.g. NIPBL, UBAP2), and other genes found differentially expressed in this study and not previously associated with sex-related differences may be considered potential candidates for molecular sexing (e.g. TERA, MYP0, PPR17, CASQ2). Additionally, other genes likely associated with neuronal and brain development (e.g. CHKA, NYAP), as well as body development and size differentiation (e.g. ANKRD26, GRP87) in quail were identified. Expression of homeobox protein regulating genes in the sex-related contrast group revealed two genes (HXC4, ISL1) that may regulate sex-specific anatomical development. Results of these analyses expand the currently limited pool of knowledge on the genetic features of the quail breed and could allow for more effective molecular sexing as well as selective breeding for traits important in commercial production. Overall design: This study employed Trinity and edgeR for transcriptome analysis of next-generation RNA-seq data, which included 4 tissues obtained from 3 different breeds of Japanese quail (wild, miniature, and jumbo).
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 | 4,727,192 Kb | AWS | https://sra-pub-run-odp.s3.amazonaws.com/sra/SRR1758118/SRR1758118 | worldwide | anonymous |
| SRA Lite | 1,645,316 Kb | NCBI | https://sra-downloadb.be-md.ncbi.nlm.nih.gov/sos5/sra-pub-zq-11/SRR001/758/SRR1758118/SRR1758118.sralite.1 | worldwide | anonymous |
| AWS | s3://sra-pub-zq-8/SRR1758118/SRR1758118.sralite.1 | s3.us-east-1 | aws identity | ||
| GCP | gs://sra-pub-zq-103/SRR1758118/SRR1758118.noqual.1 | 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 | 8,204,399 Kb | AWS | s3://sra-pub-src-14/SRR1758118/LQ_O_RNA_ATGTCA_R2.fastq | - | Use Cloud Data Delivery |
| fastq | 8,204,399 Kb | AWS | s3://sra-pub-src-12/SRR1758118/LQ_O_RNA_ATGTCA_R1.fastq | - | 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: 14.87%
- Identified reads: 85.13%
Strong signals
| SuperKingdom | Organism | Rank | %% | Kbp | Coverage |
|---|---|---|---|---|---|
| Eukaryota | Coturnix japonica | species | 83.6 | 5,387,203 | |
| Eukaryota | Gallus gallus | species | 0.6 | 39,468 | |
| Eukaryota | Meleagris gallopavo | species | 0.4 | 27,004 | |
| Eukaryota | Passeriformes | order | 0.1 | 4,599 | |
| Eukaryota | Boreoeutheria | 0.1 | 4,322 | ||
| Eukaryota | Anatidae | family | 0.1 | 3,552 | |
| Bacteria | Bacteria | superkingdom | 0.0 | 1,566 | |
| Viruses | Avian carcinoma virus | species | 0.0 | 55 |
- 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