Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Canary genome

ABSTRACT: Genome sequence of the canary (Serinus canaria)

PROVIDER: PRJEB1766 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	CAVT01.dat.gz	Other
	CAVT01.fasta.gz	Fasta.gz
	CAVT01.master.dat	Other
	CAVT01.dat.gz	Other

Items per page:

1 - 4 of 4

Similar Datasets

Serinus canaria

Project description:Serinus canaria

| PRJNA852807 | ENA

Serinus canaria strain:SECAWH01

Project description:Serinus canaria genome sequencing

| PRJNA38215 | ENA

Serinus canaria isolate:sc_yellow_7_cibi

Project description:Serinus canaria isolate:sc_yellow_7_cibi Genome sequencing and assembly

| PRJNA548289 | ENA

From silence to song: Testosterone triggers extensive transcriptional changes in the female canary HVC

Project description:In this data set, we compared the expression data of song nuclei HVC dissected from adult female canaries (S. canaria) implanted with 7-mm SilasticTM tubes filled with testosterone for 6 periods (1h, 3h, 8h, 3d, 7d, and 14d) with control birds (implanted with empty tube) to identify testosterone effects on gene expression.

2019-12-31 | GSE118522 | GEO

Canary Oyk

Project description:Taxonomic status of the extinct Canary Islands Oystercatcher Haematopus meadewaldoi

| PRJEB32908 | ENA

Expression data from Serinus canaria HVC, RA and Entopallium

Project description:Expression data from Serinus canaria HVC, RA and Entopallium

| PRJNA215935 | ENA

Transcriptome sequencing of Serinus Canaria and Taeniopygia guttata barin tissues

Project description:Transcriptome sequencing of Serinus Canaria and Taeniopygia guttata barin tissues

| PRJEB4463 | ENA

Genomic Resources for Birdsong Research

Project description:Vocal learning and neuronal replacement have been studied extensively in the songbird brain, but until recently, few molecular and genomic tools have been available for this work. Here we describe new molecular/genomic resources for songbird research. We made cDNA libraries from zebra finch (Taeniopygia guttata) brains at different developmental stages. A total of 11000 clones were sequenced from these libraries, representing 5870 unique gene transcripts. A web-based database has been established for sequence analysis and functional annotations. The cDNA libraries were not normalized. Sequence analysis revealed that a cDNA library made from brains at post-hatching day 30-50, when the song system goes through rapid development and birds learn to sing, shows the highest gene discovery rate. We grouped genes into functional categories according to the Gene Ontology classification and found that expression of the functional categories changed as the brain developed. We also identified five microRNAs whose sequences are highly conserved between zebra finch and other species. We printed cDNA microarrays and profiled gene expression in the HVC of both adult male zebra finches and canaries (Serinus canaria). Statistical Analysis of Microarrays (SAM) was used for data analysis. A subset of the differentially regulated genes was validated by in situ hybridization. The bioinformatic tools EASE and Ingenuity Pathway Analysis were used to identify over-represented functional groups and gene networks among the regulated genes. These resources provide songbird biologists with tools for genome annotation, comparative genomics, and microarray gene expression analysis. Keywords: HVC, songbird, cDNA microarray, gene expression

2006-12-06 | GSE6412 | GEO

Genome-scale DNA methylation profiling of lung adenocarcinoma: validation using Ontario Tumor Bank samples

Project description:The independent population of lung adenocarcinoma and adjacent non-tumor lung used for verification of the EDRN/Canary Foundation study

2012-03-21 | GSE32866 | GEO

Trachea Epithelium as a “ Canary” for Cigarette Smoking-induced Biologic Phenotype of Small Airway Epithelium

Project description:The initial site of smoking-induced lung disease is the small airway epithelium, which is difficult and time consuming to sample by fiberoptic bronchoscopy. We developed a rapid, office-based procedure to obtain trachea epithelium without conscious sedation from healthy nonsmokers (n=26) and healthy smokers (n=19, 27 ± 15 pack-yr). Gene expression differences [fold-change >1.5, p< 0.01, Benjamini-Hochberg correction] were assessed with Affymetrix microarrays. 1,057 probe sets were differentially expressed in healthy smokers vs nonsmokers, representing >500 genes. Trachea gene expression was compared to an independent group of small airway epithelial samples (n=23 healthy nonsmokers, n=19 healthy smokers, 25 ± 12 pack-yr). The trachea epithelium is more sensitive to smoking, responding with 3-fold more differentially-expressed genes than small airway epithelium. The trachea transcriptome paralleled the small airway epithelium, with 156 of 167 (93%) genes that are significantly up- and down-regulated by smoking in the small airway epithelium showing similar direction and magnitude of response to smoking in the trachea. Trachea epithelium can be obtained without conscious sedation, representing a less invasive surrogate “canary” for smoking-induced changes in the small airway epithelium. This should prove useful in epidemiologic studies correlating gene expression with clinical outcome in assessing smoking-induced lung disease.

2009-08-27 | GSE13933 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data