Dataset Information

Exome of Holstein Friesian Cows

ABSTRACT: Despite the large amounts of transcriptome data generated for many non-model organisms, there has been a much lesser uptake of individual genomic sequencing for detecting SNPs and determining haplotypes in these species. Transcriptome data represents a source of variant information, specifically for coding DNA, however there is little information on the accuracy, coverage and limitations of using transcriptomic data for the identification of single nucleotide polymorphisms (SNPs) in non-model organisms. To investigate this, we generated the first whole exome design for bovine using the Roche Nimblegen Developer system (Roche, USA) and used it to sequence and call SNPs from a lactating dairy cow model with genetically divergent fertility phenotypes (Fert+, n=8; Fert-, n=8). We compared these results to SNPs called from liver and muscle transcriptomes from the same animals. Our exome demonstrated 99.1% coverage of the target design of 56.7MB, whereas the transcriptomes only covered 60 and 54.5% of 44.2 and 42.8MB in liver and muscle respectively. We found that specificity of SNP detection in the transcriptome data is ~75% following basic hard-filtering, but could be increased marginally to ~80% by increasing the minimum threshold of reads covering a SNP, and number of samples in which it was found. Functional annotation of non-synonymous SNPs specific to both the high and low fertility phenotype identified immune response-related genes, supporting previous work that identified this process as key to the phenotype.

ORGANISM(S): Bos taurus

PROVIDER: GSE62160 | GEO | 2015/10/08

SECONDARY ACCESSION(S): PRJNA263328

REPOSITORIES: GEO

ACCESS DATA

Similar Datasets

Project description:The Systemic Capillary Leak Syndrome (SCLS) is an extremely rare, orphan disease that resembles systemic anaphylaxis. The disorder is characterized by repeated, transient, and seemingly unprovoked episodes of hypotensive shock and peripheral edema due to transient endothelial hyperpermeability. SCLS is often accompanied by a monoclonal gammopathy of unknown significance (MGUS). Using Affymetrix Single Nucleotide Polymorphism (SNP) microarrays, we performed the first genome-wide SNP analysis of SCLS in a cohort of 12 disease subjects and 18 controls. Exome capture sequencing was performed on genomic DNA from nine of these patients as validation for the SNP-chip discoveries and de novo data generation. We identified candidate susceptibility loci for SCLS, which included a region flanking CAV3 (3p25.3) as well as SNP clusters in PON1 (7q21.3), PSORS1C1 (6p21.3), and CHCHD3 (7q33). Among the most highly ranked discoveries were gene-associated SNPs in the uncharacterized LOC100130480 gene (rs6417039, rs2004296). Top case-associated SNPs were observed in BTRC (rs1235580, 3rs4436485), ARHGEF18 (rs11668246), CDH13 (rs4782779), and EDG2 (rs12552348), which encode proteins with known or suspected roles in B cell function and/or vascular integrity. SNPs that were significantly associated with SCLS by microarray analysis were also detected and validated by exome deep sequencing. Functional annotation of highly ranked SNPs revealed enrichment of cell projections, cell junctions and adhesion, and molecules containing pleckstrin homology, Ras/Rho regulatory, and immunoglobulin Ig-like C2/fibronectin type III domains, all of which involve mechanistic functions that correlate with the SCLS phenotype. These results highlight SNPs with potential relevance to SCLS. Our study cohort included 12 patients with SCLS. The control group included 17 age, sex and ethnicity-matched healthy donors (including two relatives of SCLS patients), and a reference sample supplied by the SNP-chip manufacturer (Affymetrix), for which age information was not available. Affymetrix SNP arrays were performed according to the manufacturer's directions on DNA extracted from purified B lymphocytes.

Project description:This dataset results from the discovery, characterization and validation of 74 genetically variant peptides from fingermark protein. These peptides contain single amino acid polymorphisms, the result of non-synonymous SNPs. Detection of these peptide markers in fingermark proteomic datasets allows inferences to be made about the genotype status of corresponding SNP alleles. These inferences provide an individual genetic profile that may be used to calculate random match probabilities and provide information about potential genetic background. Epidermal corneocytes from five European and four South Asian subjects were isolated, processed, proteolytically digested with trypsin and 0.75 µg applied to a Q ExactiveTM hybrid quadrupole-Orbitrap mass spectrometer. The resulting datasets were used for discovery of genetically variant peptides by a “bottom-up” analysis of potential variants identified in X!Tandem datasets (thegpm.org) or by a “top-down” proteomic confirmation of non-synonymous SNP variants shown to be present in corresponding subject exome datasets. The later method resulted in discovery of a rare allele that was not observed in the 1000 Genome Project. The cumulative profiles of detected genetically variant peptides were obtained for each subject. Candidate genetically variant peptides were then validated by comparing proteomically inferred SNP alleles with matching genotypes in exome datasets. An average of 28.8 ± 4.4 genetically variant peptides were detected from each subject. Across the 9 subjects a total of 264 SNP allele inferences were made resulting in 260 true positives and 4 false positives, a false positive rate of 1.5%. Random match probabilities were calculated using the genotype frequencies of common genetically variant peptides from the matching major populations in the 1000 genome project. Estimates ranged up to a value of 1 in 1.7 x 108, with a median probability of 1 in 2.4 x 106. When probabilities were recalculated using values from other major genetic population groups African values were considerably less conservative, with resulting likelihood ratios (AFR/other populations) ranging up to 6 orders of magnitude. Conversely there was no resolution among estimates obtained from all non-African population groups, where resulting random match probabilities were within an order of magnitude. These genetically variant peptides are a starting point for the development of targeted mass spectrometry-based proteomic analyses that will increase the sensitivity of peptide detection. This project represents a novel mode of genetic information that can be obtained from fingermarks and has the potential to complement or confirm other methods of human identification including analysis of ridge patterns or touch DNA.

Dataset Information

Exome of Holstein Friesian Cows

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure