Design and Characterization of a 52K SNP Chip for Goats

The success of Genome Wide Association Studies in the discovery of sequence variation linked to complex traits in humans has increased interest in high throughput SNP genotyping assays in livestock species. Primary goals are QTL detection and genomic selection. The purpose here was design of a 50–60,000 SNP chip for goats. The success of a moderate density SNP assay depends on reliable bioinformatic SNP detection procedures, the technological success rate of the SNP design, even spacing of SNPs on the genome and selection of Minor Allele Frequencies (MAF) suitable to use in diverse breeds. Through the federation of three SNP discovery projects consolidated as the International Goat Genome Consortium, we have identified approximately twelve million high quality SNP variants in the goat genome stored in a database together with their biological and technical characteristics. These SNPs were identified within and between six breeds (meat, milk and mixed): Alpine, Boer, Creole, Katjang, Saanen and Savanna, comprising a total of 97 animals. Whole genome and Reduced Representation Library sequences were aligned on >10 kb scaffolds of the de novo goat genome assembly. The 60,000 selected SNPs, evenly spaced on the goat genome, were submitted for oligo manufacturing (Illumina, Inc) and published in dbSNP along with flanking sequences and map position on goat assemblies (i.e. scaffolds and pseudo-chromosomes), sheep genome V2 and cattle UMD3.1 assembly. Ten breeds were then used to validate the SNP content and 52,295 loci could be successfully genotyped and used to generate a final cluster file. The combined strategy of using mainly whole genome Next Generation Sequencing and mapping on a contig genome assembly, complemented with Illumina design tools proved to be efficient in producing this GoatSNP50 chip. Advances in use of molecular markers are expected to accelerate goat genomic studies in coming years.     

Selection Signatures in Worldwide Sheep Populations

The diversity of populations in domestic species offers great opportunities to study genome response to selection. The recently published Sheep HapMap dataset is a great example of characterization of the world wide genetic diversity in sheep. In this study, we re-analyzed the Sheep HapMap dataset to identify selection signatures in worldwide sheep populations. Compared to previous analyses, we made use of statistical methods that (i) take account of the hierarchical structure of sheep populations, (ii) make use of linkage disequilibrium information and (iii) focus specifically on either recent or older selection signatures. We show that this allows pinpointing several new selection signatures in the sheep genome and distinguishing those related to modern breeding objectives and to earlier post-domestication constraints. The newly identified regions, together with the ones previously identified, reveal the extensive genome response to selection on morphology, color and adaptation to new environments.     

Genetic diversity and subdivision of 57 European and Middle-Eastern sheep breeds

The population structure and genetic diversity of 57 European and Middle Eastern marginal and cosmopolitan sheep breeds from 15 countries were analysed by typing 31 microsatellite markers. Mean unbiased expected heterozygosities ranged from 0.63 in British Exmoor Horn to 0.77 in Albanian Ruda. South-eastern European and Middle-Eastern sheep breeds were significantly more variable than northwestern and western European breeds. An overall heterozygote deficiency (f) across all loci was observed (P < 0.001), while genetic differentiation (theta) was 5.7%. Principal component analysis and Bayesian model-based clustering indicate a south-east to north-west cline, but also revealed distinct groups of Middle-Eastern fat-tailed sheep, south-eastern European sheep and north-western/western European sheep. Within the last group, two less-distinct clusters comprised the Merino-type and Alpine breeds respectively. The incomplete demarcations of most clusters probably reflects cross-breeding and/or upgrading.     

Serum Iron Levels and the Risk of Parkinson Disease: A Mendelian Randomization Study

Background

Although levels of iron are known to be increased in the brains of patients with Parkinson disease (PD), epidemiological evidence on a possible effect of iron blood levels on PD risk is inconclusive, with effects reported in opposite directions. Epidemiological studies suffer from problems of confounding and reverse causation, and mendelian randomization (MR) represents an alternative approach to provide unconfounded estimates of the effects of biomarkers on disease. We performed a MR study where genes known to modify iron levels were used as instruments to estimate the effect of iron on PD risk, based on estimates of the genetic effects on both iron and PD obtained from the largest sample meta-analyzed to date.

Methods and Findings

We used as instrumental variables three genetic variants influencing iron levels, HFE rs1800562, HFE rs1799945, and TMPRSS6 rs855791. Estimates of their effect on serum iron were based on a recent genome-wide meta-analysis of 21,567 individuals, while estimates of their effect on PD risk were obtained through meta-analysis of genome-wide and candidate gene studies with 20,809 PD cases and 88,892 controls. Separate MR estimates of the effect of iron on PD were obtained for each variant and pooled by meta-analysis. We investigated heterogeneity across the three estimates as an indication of possible pleiotropy and found no evidence of it. The combined MR estimate showed a statistically significant protective effect of iron, with a relative risk reduction for PD of 3% (95% CI 1%–6%; p = 0.001) per 10 µg/dl increase in serum iron.

Conclusions

Our study suggests that increased iron levels are causally associated with a decreased risk of developing PD. Further studies are needed to understand the pathophysiological mechanism of action of serum iron on PD risk before recommendations can be made. Please see later in the article for the Editors'' Summary     

A two-stage meta-analysis identifies several new loci for Parkinson's disease

A previous genome-wide association (GWA) meta-analysis of 12,386 PD cases and 21,026 controls conducted by the International Parkinson''s Disease Genomics Consortium (IPDGC) discovered or confirmed 11 Parkinson''s disease (PD) loci. This first analysis of the two-stage IPDGC study focused on the set of loci that passed genome-wide significance in the first stage GWA scan. However, the second stage genotyping array, the ImmunoChip, included a larger set of 1,920 SNPs selected on the basis of the GWA analysis. Here, we analyzed this set of 1,920 SNPs, and we identified five additional PD risk loci (combined p<5×10⁻¹⁰, PARK16/1q32, STX1B/16p11, FGF20/8p22, STBD1/4q21, and GPNMB/7p15). Two of these five loci have been suggested by previous association studies (PARK16/1q32, FGF20/8p22), and this study provides further support for these findings. Using a dataset of post-mortem brain samples assayed for gene expression (n = 399) and methylation (n = 292), we identified methylation and expression changes associated with PD risk variants in PARK16/1q32, GPNMB/7p15, and STX1B/16p11 loci, hence suggesting potential molecular mechanisms and candidate genes at these risk loci.     

Maximum-likelihood estimation of site-specific mutation rates in human mitochondrial DNA from partial phylogenetic classification

The mitochondrial DNA hypervariable segment I (HVS-I) is widely used in studies of human evolutionary genetics, and therefore accurate estimates of mutation rates among nucleotide sites in this region are essential. We have developed a novel maximum-likelihood methodology for estimating site-specific mutation rates from partial phylogenetic information, such as haplogroup association. The resulting estimation problem is a generalized linear model, with a nonstandard link function. We develop inference and bias correction tools for our estimates and a hypothesis-testing approach for site independence. We demonstrate our methodology using 16,609 HVS-I samples from the Genographic Project. Our results suggest that mutation rates among nucleotide sites in HVS-I are highly variable. The 16,400–16,500 region exhibits significantly lower rates compared to other regions, suggesting potential functional constraints. Several loci identified in the literature as possible termination-associated sequences (TAS) do not yield statistically slower rates than the rest of HVS-I, casting doubt on their functional importance. Our tests do not reject the null hypothesis of independent mutation rates among nucleotide sites, supporting the use of site-independence assumption for analyzing HVS-I. Potential extensions of our methodology include its application to estimation of mutation rates in other genetic regions, like Y chromosome short tandem repeats.     

PECAM-1 expression and activity negatively regulate multiple platelet signaling pathways

Platelet endothelial cell adhesion molecule-1 (PECAM-1) inhibits platelet response to collagen and may also inhibit two other major platelet agonists ADP and thrombin although this has been less well explored. We hypothesized that the combined effect of inhibiting these three platelet activating pathways may act to significantly inhibit thrombus formation. We demonstrate a negative relationship between PECAM-1 surface expression and platelet response to cross-linked collagen related peptide (CRP-XL) and ADP, and an inhibitory effect of PECAM-1 clustering on platelet response to CRP-XL, ADP and thrombin. This combined inhibition of multiple signaling pathways results in a marked reduction in thrombus formation.     

Mutation analysis of the coding sequence of the MECP2 gene in infantile autism

Mutations in the coding region of the methyl-CpG-binding protein 2 ( MECP2) gene cause Rett syndrome and have also been reported in a number of X-linked mental retardation syndromes. Furthermore, such mutations have recently been described in a few autistic patients. In this study, a large sample of individuals with autism was screened in order to elucidate systematically whether specific mutations in MECP2 play a role in autism. The mutation analysis of the coding sequence of the gene was performed by denaturing high-pressure liquid chromatography and direct sequencing. Taken together, 14 sequence variants were identified in 152 autistic patients from 134 German families and 50 unrelated patients from the International Molecular Genetic Study of Autism Consortium affected relative-pair sample. Eleven of these variants were excluded for having an aetiological role as they were either silent mutations, did not cosegregate with autism in the pedigrees of the patients or represented known polymorphisms. The relevance of the three remaining mutations towards the aetiology of autism could not be ruled out, although they were not localised within functional domains of MeCP2 and may be rare polymorphisms. Taking into account the large size of our sample, we conclude that mutations in the coding region of MECP2 do not play a major role in autism susceptibility. Therefore, infantile autism and Rett syndrome probably represent two distinct entities at the molecular genetic level.