| Run | Spots | Bases | Size | GC content | Published | Access Type |
|---|---|---|---|---|---|---|
ERR3516363 |
5.6M | 1.7Gbp | 746.7M | 49.6% | 2019-11-11 | public |
This run has 2 reads per spot:
| L=151, 100% | L=151, 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 | 2019-11-10 |
| ENA-LAST-UPDATE | 2019-09-26 |
| Experiment | Library Name | Platform | Strategy | Source | Selection | Layout | Action |
|---|---|---|---|---|---|---|---|
| ERX3536079 | unspecified | Illumina | RNA-Seq | TRANSCRIPTOMIC | Oligo-dT | PAIRED |
| Biosample | Sample Description | Organism |
|---|---|---|
| SAMEA5950392 (ERS3738877) | Whole body 28 dpf larve RNA-seq | Mugil cephalus |
| Bioproject | SRA Study | Title |
|---|---|---|
| PRJEB34342 | ERP117232 | Refinement of the sex-determining region in flathead grey mullet (Mugil cephalus) |
Flathead mullet (Mugil cephalus) is a cosmopolitan mugilid species popular in fishery and aquaculture with an economic preference for all-female population. However, it displays neither sexual dimorphisms nor heteromorphic sex chromosomes. In our previous study, we have generated the first draft of linkage map of the flathead mullet locating a single sex determination region (SDR) on its linkage group 9 (LG9) with evidence for XX/XY sex determination (SD) mechanism. In this work, the main objective was to refine the SDR on LG9 and propose positional candidate genes for SD based on expression and function. To elucidate the genetic mechanism of SD, we assembled and compared male and female genomic sequences of 19 syntenic genes within the putative SDR on mullet's LG9, based on orthology to tilapia's LG8 (tLG8) physical map. A total of 25 sequence-based markers in 12 genes were developed. For all markers, we observed association with sex in at least one of the two analyzed M. cephalus full-sib families, but not in the wild-type population. Recombination events were inferred within nuclear families setting the boundaries to an SDR orthologous to ~0.9 Mbp with 27 genes on tLG8. As the realized sex of each larva will not be known until it reaches sexual maturity, larvae were assigned into two sex-groups following segregation of the paternal haplotypes, following a model of XY/XX SD-system. A total of 107 sex-biased differentially expressed genes in larvae were determined, of which 51 had ortholog genes mapped to tLG8 (48% enrichment), as compared to 5% in random control. Of the 27 genes in the SDR, DOCK1, DHX32A and BCCIP were attractive candidates considering theirs potential function previously associated with SD, and were sex-biased differentially expressed in larvae (11% enrichment). Functional and positional enrichment of genes on mullet's LG9 critical region that determines sex suggests the possible role of these three genes in SD, and lends further support for males being heterogametic for this SDR.
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 | 729,224 Kb | AWS | https://sra-pub-run-odp.s3.amazonaws.com/sra/ERR3516363/ERR3516363 | worldwide | anonymous |
| SRA Lite | 426,415 Kb | NCBI | https://sra-downloadb.be-md.ncbi.nlm.nih.gov/sos3/sra-pub-zq-22/ERR003/516/ERR3516363.sralite.1 | worldwide | anonymous |
| AWS | s3://sra-pub-zq-7/ERR3516363/ERR3516363.sralite.1 | s3.us-east-1 | aws identity | ||
| GCP | gs://sra-pub-zq-109/ERR3516363/ERR3516363.zq.1 | gs.us-east1 | gcp identity |
- 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: 49.06%
- Identified reads: 50.94%
Strong signals
| SuperKingdom | Organism | Rank | %% | Kbp | Coverage |
|---|---|---|---|---|---|
| Eukaryota | Percomorphaceae | 41.5 | 704,642 | ||
| Bacteria | Bacteria | superkingdom | 8.0 | 135,878 | |
| Eukaryota | Mugil cephalus | species | 5.8 | 97,966 | |
| Eukaryota | Pomacentridae | family | 1.9 | 32,476 | |
| Eukaryota | Artemia | genus | 1.4 | 23,825 | |
| Eukaryota | Oreochromis niloticus | species | 1.3 | 21,759 | |
| Eukaryota | Cyprinodontiformes | order | 0.8 | 13,332 | |
| Eukaryota | Eupercaria | 0.7 | 11,723 | ||
| Eukaryota | Pleuronectoidei | suborder | 0.6 | 10,378 |
- 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