Sus scrofa
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA295107 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:To identify biological processes as well as molecular markers for drip loss, the transcriptomes of logissimus dorsi from 6 sib pair of F2 animals Experiment Overall Design: 12 F2 animals of a resource population based on the breeds Duroc and Pietrain known to differ in meat quality and quantity traits were hybridized to Affymetrix Porcine Genome Arrays
2009-01-14 | E-GEOD-11193 | biostudies-arrayexpress
Project description:A CNV map in pigs could facilitate the identification of chromosomal regions that segregate for important economic and disease phenotypes. The goal of this study was to identify CNV regions (CNVRs) in pigs based on a custom array comparative genome hybridization (aCGH). We carried out a custom-made array comparative genome hybridization (aCGH) experiment in order to identify copy number variations (CNVs) in the pig genome analysing animals of diverse pig breeds (White Duroc, Yangxin, Erhualian, Tongcheng, Large White, Pietrain, Landrace and Chinese new pig line DIV ) using a tiling oligonucleotide array with ~720,000 probes designed on the pig genome (Sus scrofa genome version 9.0). In this study, a custom-made tiling oligo-nucleotide 720k array was used with a median probe spacing of 2506 bp for screening 12 pigs with a female Duroc as the reference. WD: White Duroc (♀); YX: Yangxin (♂); EH: Erhualian (♀); TC: Tongcheng (♀); LW: Large White (♀); PT: Pietrain (♂); LD1: Landrace × DIV pig 1 (♂); LD2: Landrace × DIV pig 2 (♀); DIV1: Chinese new pig line DIV 1 (♀); DIV2: Chinese new pig line DIV 2 (♀); L1: Landrace 1 (♂); L2: Landrace 2 (♂).
2013-08-09 | E-GEOD-41488 | biostudies-arrayexpress
Project description:In this study, we used correlation analysis of the expression profiles and drip loss to produce a list of functional candidate genes under the assumption that genes with strong correlation between their expression values and drip belong to pathways or networks relevant for the control of the trait. Expression QTL analyses for transcripts showing trait dependent expression were done in order to identify genes which show trait associated expression, map to pQTL regions, and exhibit cis regulation. Experiment Overall Design: 74 F2 animals of a resource population based on the breeds Duroc and Pietrain known to differ in meat quality and quantity traits were hybridized to Affymetrix Porcine Genome Arrays.
2009-01-14 | E-GEOD-10204 | biostudies-arrayexpress
Project description:RNA-Seq analysis carried out in three different backcrosses based on Iberian breed with Landrace, Pietrain and Duroc breeds
2017-10-31 | PRJEB23068 | EVA
Project description:Gene expression data of micro RNA from skeletal muscle sample of pig breed Duroc and Pietrain with malignant hyperthermia syndrome homozygous negative
| PRJNA318262 | ENA
Project description:Transcriptional profiling during fetal skeletal muscle development of Piau and Yorkshire-Landrace crossbred pigs
| PRJNA126353 | ENA
Project description:We firstly compared the expression file of circRNAs in longissimus muscle (LM) between the Chinese indigenous Huainan (HN, the fat type line ) and the Western commercial Duroc×(Landrace×Yorkshire) (DLY, the thin type line) to identify the key circRNAs involved in the genetic basis of pork quality traits.
2019-03-27 | GSE86919 | GEO
Project description:Gene expression profiling in a Duroc/Landrace pig population differing in intramuscular fat content
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Project description:Sus scrofa strain:Duroc, Landrace, Yorkshire Metagenome
| PRJNA263439 | ENA
Project description:Peripheral blood transcriptome is an important intermediate data source for investigation of the mechanism of Salmonella invasion, proliferation, and transmission but its development in pig is quite limited. We challenged four-week-old piglets (Duroc × Landrace × Yorkshire crossbred) with Salmonella enterica serovar Typhimurium LT2 and investigated the peripheral blood miRNA expression profile before treatment (d0) and at 2 days post inoculation (dpi) using deep sequencing technology.
2018-09-21 | GSE120266 | GEO