Run Browser : Browse : Sequence Read Archive : NCBI/NLM/NIH

Run	Spots	Bases	Size	GC content	Published	Access Type
SRR2539795	5.9M	604.4Mbp	299.1M	47%	2016-03-22	public

Quality graph (bigger)(smaller)

240

Phred quality score

This run has 2 reads per spot:

L=51, 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
SRX1296328		Illumina	RNA-Seq	TRANSCRIPTOMIC	RT-PCR	PAIRED

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Prior to library preparation the RNA quality and integrity was assessed according to Illumina guidelines. Library preparation was done using the TruSeq® Stranded mRNA sample preparation 96 rxn kit (Illumina™) following the low sample protocol according to manufacturer’s recommendations. Briefly, approximately 2.5 µg of total RNA was diluted and purified using RNA purification beads targeting the poly-A tail of the mRNA and subsequently was fragmented by means of the enzymes provided in the kit. After the cDNA synthesis adenylation of 3’ ends and ligation of the adaptors were employed. Adaptors were ligated in 12-plex formations, allowing the pooling of 12 samples after the PCR enrichment of the library. Subsequently, the library was quantified using PicoGreen® dye (Life Technologies™) as described in the manufacturer’s protocol. Thereafter 12 samples were pooled at equal concentrations to create the eight pools. In order to accurately quantify the concentration in nM of our pools, the Kapa SYBR® FAST universal qPCR kit (Kapa Biosystems™) for Illunima™ sequencing was used to quantify the number of the amplifiable molecules in the pools and the Bioanalyzer® (Agilent Technologies™) to determine the average fragment size of the pools. These measurements allowed optimizing the flow cell clustering and proceed with the Run. The samples were sequenced in five lanes of an Illumina HiSeq2000 sequencer, for 50 bp pair-end read.

Biosample	Sample Description	Organism	Links
SAMN04123238 (SRS1095022)	Embryos were obtained from Public Center "Fur-bearing and farm animals" of Federal State Budget Scientific Institution "The Federal Research Center Institute of Cytology and Genetics of Siberian Branch of the Russian Academy of Sciences" (ICG SB RAS), Novosibirsk, Russia.	Neovison vison	PRJNA297393

Bioproject	SRA Study	Title
PRJNA297393	SRP064337	Neovison vison Genome sequencing and assembly

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Background: Recently fibroblasts of many mammalian species were reprogrammed to pluripotent state using overexpression of several transcription factors. This technology allows production of induced pluripotent stem (iPS) cells with properties similar to embryonic stem (ES) cells. The completeness of reprogramming process is well studied in such species as mouse and human but there is not enough data on other species. We decided to produce American mink (Neovison vison) ES and iPS cells and to compare these cells using transcriptome analysis.Results: We report the generation of 10 mink ES and 22 iPS cell lines. The majority of analyzed cell lines had normal diploid chromosome number. We produced teratomas with cell types representing all three germ layers. The only ES cell line with XX chromosome set had both X chromosomes in active state that is characteristic of pluripotent cells. Transcriptome analysis of mink embryonic fibroblasts (EF), two ES and two iPS cell lines allowed us to identify 6891 genes. 3201 of them were differentially expressed between mink EF and ES cells. We analysed expression levels of these genes in iPS cell lines. It allowed us to show that 80% of genes were correctly reprogrammed in iPS cells, about 6% had intermediate, about 7% – not reprogrammed and about 5% – “novel” expression pattern. We observed expression of pluripotency marker genes such as Oct4, Sox2 and Rex1 with notable exception of Nanog.Conclusions: We had produced and characterized American mink ES and iPS cells. These cells were pluripotent by a number of criteria and iPS cells exhibited effective reprogramming. Interestingly, we had showed lack of Nanog expression, we consider it as species-specific feature.

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	292,103 Kb	AWS	https://sra-pub-run-odp.s3.amazonaws.com/sra/SRR2539795/SRR2539795	worldwide	anonymous
SRA Lite	161,461 Kb	NCBI	https://sra-downloadb.be-md.ncbi.nlm.nih.gov/sos5/sra-pub-zq-11/SRR002/539/SRR2539795/SRR2539795.sralite.1	worldwide	anonymous
		AWS	s3://sra-pub-zq-8/SRR2539795/SRR2539795.sralite.1	s3.us-east-1	aws identity
		GCP	gs://sra-pub-zq-104/SRR2539795/SRR2539795.zq.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	1,003,843 Kb	AWS	s3://sra-pub-src-7/SRR2539795/MES12b_TCCGGAGA-TATAGCCT_L001_R2_001.fastq	-	Use Cloud Data Delivery
fastq	1,003,843 Kb	AWS	s3://sra-pub-src-8/SRR2539795/MES12b_TCCGGAGA-TATAGCCT_L001_R1_001.fastq	-	Use Cloud Data Delivery

Egress and Access: what does it mean?

Egressterm used by cloud providers to describe cost (charged to the user) of moving data outside of the storage region

Free Egress column 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: 51.59%
Identified reads: 48.41%

View in Krona

Strong signals

SuperKingdom	Organism	Rank	%%	Kbp
Eukaryota	Mustela putorius furo	subspecies	30.0	181,490
Eukaryota	Neovison vison	species	10.9	65,703
Eukaryota	Ursidae	family	0.5	3,141
Eukaryota	Odobenidae	family	0.4	2,229

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

How taxonomy analysis is done?: A fast, scalable, MinHash-based k-mer tool to assess Sequence Read Archive next generation sequence submissions

mink ESC MES12 transcriptome(SRR2539795)

SRA archive data

Original format

Taxonomy Analysis

Strong signals

Intensity graph

	View: biological readstechnical readsquality scoresadvanced options Hide Reads base space color space show separated reads quality score with bases show clipped show 4 channel quality scorewith bases Intensity graph Signals table
	Intensity graph