Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Imputed whole-genome sequencing data of 669 German Black Pied bulls (DSN)

ABSTRACT: Genotypes from imputed whole-genome sequencing data of 669 German Black Pied bulls (DSN, "Deutsches Schwarzbuntes Niederungsrind")

INSTRUMENT(S): -

ORGANISM(S): Bos Taurus

SUBMITTER: Humboldt Universitat zu Berlin

PROVIDER: PRJEB82246 | EVA | 2024-11-09

REPOSITORIES: EVA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	genotypesWGS.669DSNbulls.ARS_UCD1.2.accessioned.vcf.gz	Vcf
	genotypesWGS.669DSNbulls.ARS_UCD1.2.accessioned.vcf.gz.csi	Vcf
	genotypesWGS.669DSNbulls.ARS_UCD1.2.vcf.csi	Other
	genotypesWGS.669DSNbulls.ARS_UCD1.2.vcf.gz	Vcf

Items per page:

1 - 4 of 4

Similar Datasets

Genotypes of German Black Pied cows (DSN)

Project description:Genotypes of 1490 German Black Pied cows (DSN, "Deutsches Schwarzbuntes Niederungsrind") genotyped using Illumina? Bovine50SNP chip

2021-01-18 | PRJEB42513 | EVA

Whole-Genome Sequencing Data Reveal New Loci Affecting Milk Production in German Black Pied Cattle (DSN).

Project description:German Black Pied (DSN) is considered an ancestral population of the Holstein breed. The goal of the current study was to fine-map genomic loci for milk production traits and to provide sequence variants for selection. We studied genome-wide associations for milk-production traits in 2160 DSN cows. Using 11.7 million variants from whole-genome sequencing of 304 representative DSN cattle, we identified 1980 associated variants (-log10(p) ≥ 7.1) in 13 genomic loci on 9 chromosomes. The highest significance was found for the MGST1 region affecting milk fat content (-log10(p) = 11.93, MAF = 0.23, substitution effect of the minor allele (ßMA) = -0.151%). Different from Holstein, DGAT1 was fixed (0.97) for the alanine protein variant for high milk and protein yield. A key gene affecting protein content was CSN1S1 (-log10(p) = 8.47, MAF = 049, ßMA = -0.055%) and the GNG2 region (-log10(p) = 10.48, MAF = 0.34, ßMA = 0.054%). Additionally, we suggest the importance of FGF12 for protein and fat yield, HTR3C for milk yield, TLE4 for milk and protein yield, and TNKS for milk and fat yield. Selection for favored alleles can improve milk yield and composition. With respect to maintaining the dual-purpose type of DSN, unfavored linkage to genes affecting muscularity has to be investigated carefully, before the milk-associated variants can be applied for selection in the small population.

| S-EPMC10048491 | biostudies-literature

Project description:Genotypes of German Black Pied cows (DSN)

| PRJEB42513 | ENA

DNA methylome of German Shepherd

Project description:Using WGBS we investigated blood DNA methylation profiles of German Shepherd and determined putative regulatory elements (unmethlated regions (UMRs) and lowly methylated regions (LMRs).

2020-02-04 | GSE136348 | GEO

Project description:Imputed whole-genome sequencing data of 669 German Black Pied bulls (DSN)

| PRJEB82246 | ENA

eMERGE Network Imputed GWAS for 41 Phenotypes

Project description:eMERGE Network Imputed GWAS for 41 Phenotypes

| PRJNA278914 | ENA

Improvement of genomic prediction by integrating additional single nucleotide polymorphisms selected from imputed whole genome sequencing data.

Project description:The availability of whole genome sequencing (WGS) data enables the discovery of causative single nucleotide polymorphisms (SNPs) or SNPs in high linkage disequilibrium with causative SNPs. This study investigated effects of integrating SNPs selected from imputed WGS data into the data of 54K chip on genomic prediction in Danish Jersey. The WGS SNPs, mainly including peaks of quantitative trait loci, structure variants, regulatory regions of genes, and SNPs within genes with strong effects predicted with variant effect predictor, were selected in previous analyses for dairy breeds in Denmark-Finland-Sweden (DFS) and France (FRA). Animals genotyped with 54K chip, standard LD chip, and customized LD chip which covered selected WGS SNPs and SNPs in the standard LD chip, were imputed to 54K together with DFS and FRA SNPs. Genomic best linear unbiased prediction (GBLUP) and Bayesian four-distribution mixture models considering 54K and selected WGS SNPs as one (a one-component model) or two separate genetic components (a two-component model) were used to predict breeding values. For milk production traits and mastitis, both DFS (0.025) and FRA (0.029) sets of additional WGS SNPs improved reliabilities, and inclusions of all selected WGS SNPs generally achieved highest improvements of reliabilities (0.034). A Bayesian four-distribution model yielded higher reliabilities than a GBLUP model for milk and protein, but extra gains in reliabilities from using selected WGS SNPs were smaller for a Bayesian four-distribution model than a GBLUP model. Generally, no significant difference was observed between one-component and two-component models, except for using GBLUP models for milk.

| S-EPMC6906477 | biostudies-literature

Unmapped short reads from whole-genome sequencing indicate potential infectious pathogens in german black Pied cattle.

Project description:When resequencing animal genomes, some short reads cannot be mapped to the reference genome and are usually discarded. In this study, unmapped reads from 302 German Black Pied cattle were analyzed to identify potential pathogenic DNA. These unmapped reads were assembled and blasted against NCBI's database to identify bacterial and viral sequences. The results provided evidence for the presence of pathogens. We found sequences of Bovine parvovirus 3 and Mycoplasma species. These findings emphasize the information content of unmapped reads for gaining insight into bacterial and viral infections, which is important for veterinarians and epidemiologists.

| S-EPMC10585868 | biostudies-literature

eMERGE Network Phase III: HRC Imputed Array Data of 85,000+ Participants

Project description:eMERGE Network Phase III: HRC Imputed Array Data of 85,000+ Participants

| PRJNA453658 | ENA

eMERGE Network Phase III: HRC Imputed Array Data of 85,000+ Participants

Project description:eMERGE Network Phase III: HRC Imputed Array Data of 85,000+ Participants

| PRJNA453657 | ENA