Towards high-throughput parallel imaging and single-cell transcriptomics of microbial eukaryotic plankton.

Single-cell transcriptomics has the potential to provide novel insights into poorly studied microbial eukaryotes. Although several such technologies are available and benchmarked on mammalian cells, few have been tested on protists. Here, we applied a microarray single-cell sequencing (MASC-seq) technology, that generates microscope images of cells in parallel with capturing their transcriptomes, on three species representing important plankton groups with different cell structures; the ciliate Tetrahymena thermophila, the diatom Phaeodactylum tricornutum, and the dinoflagellate Heterocapsa sp. Both the cell fixation and permeabilization steps were adjusted. For the ciliate and dinoflagellate, the number of transcripts of microarray spots with single cells were significantly higher than for background spots, and the overall expression patterns were correlated with that of bulk RNA, while for the much smaller diatom cells, it was not possible to separate single-cell transcripts from background. The MASC-seq method holds promise for investigating "microbial dark matter", although further optimizations are necessary to increase the signal-to-noise ratio.

Stratified genetic analysis reveals sex differences in MPO-ANCA-associated vasculitis.

OBJECTIVE: To identify and genetically characterize subgroups of patients with ANCA-associated vasculitides (AAV) based on sex and ANCA subtype. METHODS: A previously established SNP dataset derived from DNA sequencing of 1853 genes and genotyping of 1088 Scandinavian cases with AAV and 1589 controls was stratified for sex and ANCA subtype and analysed for association with five top AAV SNPs. rs9274619, a lead variant at the HLA-DQB1/HLA-DQA2 locus previously associated with AAV positive for myeloperoxidase (MPO)-ANCA, was analysed for association with the cumulative disease involvement of ten different organ systems. RESULTS: rs9274619 showed a significantly stronger association to MPO-ANCA-positive females than males [P = 2.0 × 10-4, OR = 2.3 (95% CI 1.5, 3.5)], whereas proteinase 3 (PR3)-ANCA-associated variants rs1042335, rs9277341 (HLA-DPB1/A1) and rs28929474 (SERPINA1) were equally associated with females and males with PR3-ANCA. In MPO-ANCA-positive cases, carriers of the rs9274619 risk allele were more prone to disease engagement of eyes [P = 0.021, OR = 11 (95% CI 2.2, 205)] but less prone to pulmonary involvement [P = 0.026, OR = 0.52 (95% CI 0.30, 0.92)]. Moreover, AAV with both MPO-ANCA and PR3-ANCA was associated with the PR3-ANCA lead SNP rs1042335 [P = 0.0015, OR = 0.091 (95% CI 0.0022, 0.55)] but not with rs9274619. CONCLUSIONS: Females and males with MPO-ANCA-positive AAV differ in genetic predisposition to disease, suggesting at least partially distinct disease mechanisms between the sexes. Double ANCA-positive AAV cases are genetically similar to PR3-ANCA-positive cases, providing clues to the clinical follow-up and treatment of these patients.

Identification and functional characterization of a novel susceptibility locus for small vessel vasculitis with MPO-ANCA.

OBJECTIVE: To identify and characterize genetic loci associated with the risk of developing ANCA-associated vasculitides (AAV). METHODS: Genetic association analyses were performed after Illumina sequencing of 1853 genes and subsequent replication with genotyping of selected single nucleotide polymorphisms in a total cohort of 1110 Scandinavian cases with granulomatosis with polyangiitis or microscopic polyangiitis, and 1589 controls. A novel AAV-associated single nucleotide polymorphism was analysed for allele-specific effects on gene expression using luciferase reporter assay. RESULTS: PR3-ANCA+ AAV was significantly associated with two independent loci in the HLA-DPB1/HLA-DPA1 region [rs1042335, P = 6.3 × 10-61, odds ratio (OR) 0.10; rs9277341, P = 1.5 × 10-44, OR 0.22] and with rs28929474 in the SERPINA1 gene (P = 2.7 × 10-10, OR 2.9). MPO-ANCA+ AAV was significantly associated with the HLA-DQB1/HLA-DQA2 locus (rs9274619, P = 5.4 × 10-25, OR 3.7) and with a rare variant in the BACH2 gene (rs78275221, P = 7.9 × 10-7, OR 3.0), the latter a novel susceptibility locus for MPO-ANCA+ granulomatosis with polyangiitis/microscopic polyangiitis. The rs78275221-A risk allele reduced luciferase gene expression in endothelial cells, specifically, as compared with the non-risk allele. CONCLUSION: We identified a novel susceptibility locus for MPO-ANCA+ AAV and propose that the associated variant is of mechanistic importance, exerting a regulatory function on gene expression in specific cell types.

The overlap of genetic susceptibility to schizophrenia and cardiometabolic disease can be used to identify metabolically different groups of individuals.

Understanding why individuals with severe mental illness (Schizophrenia, Bipolar Disorder and Major Depressive Disorder) have increased risk of cardiometabolic disease (including obesity, type 2 diabetes and cardiovascular disease), and identifying those at highest risk of cardiometabolic disease are important priority areas for researchers. For individuals with European ancestry we explored whether genetic variation could identify sub-groups with different metabolic profiles. Loci associated with schizophrenia, bipolar disorder and major depressive disorder from previous genome-wide association studies and loci that were also implicated in cardiometabolic processes and diseases were selected. In the IMPROVE study (a high cardiovascular risk sample) and UK Biobank (general population sample) multidimensional scaling was applied to genetic variants implicated in both psychiatric and cardiometabolic disorders. Visual inspection of the resulting plots used to identify distinct clusters. Differences between these clusters were assessed using chi-squared and Kruskall-Wallis tests. In IMPROVE, genetic loci associated with both schizophrenia and cardiometabolic disease (but not bipolar disorder or major depressive disorder) identified three groups of individuals with distinct metabolic profiles. This grouping was replicated within UK Biobank, with somewhat less distinction between metabolic profiles. This work focused on individuals of European ancestry and is unlikely to apply to more genetically diverse populations. Overall, this study provides proof of concept that common biology underlying mental and physical illness may help to stratify subsets of individuals with different cardiometabolic profiles.

Analysis of the genetic variants associated with circulating levels of sgp130. Results from the IMPROVE study.

The genes regulating circulating levels of soluble gp130 (sgp130), the antagonist of the inflammatory response in atherosclerosis driven by interleukin 6, are largely unknown. Aims of the present study were to identify genetic loci associated with circulating sgp130 and to explore the potential association between variants associated with sgp130 and markers of subclinical atherosclerosis. The study is based on IMPROVE (n = 3703), a cardiovascular multicentre study designed to investigate the determinants of carotid intima media thickness, a measure of subclinical atherosclerosis. Genomic DNA was genotyped by the CardioMetaboChip and ImmunoChip. About 360,842 SNPs were tested for association with log-transformed sgp130, using linear regression adjusted for age, gender, and population stratification using PLINK v1.07. A p value of 1 × 10-5 was chosen as threshold for significance value. In an exploratory analysis, SNPs associated with sgp130 were tested for association with c-IMT measures. We identified two SNPs significantly associated with sgp130 levels and 24 showing suggestive association with sgp130 levels. One SNP (rs17688225) on chromosome 14 was positively associated with sgp130 serum levels (ß = 0.03 SE = 0.007, p = 4.77 × 10-5) and inversely associated with c-IMT (c-IMTmean-max ß = -0.001 SE = 0.005, p = 0.0342). Our data indicate that multiple loci regulate sgp130 levels and suggest a possible common pathway between sgp130 and c-IMT measures.

Genetic variation in CADM2 as a link between psychological traits and obesity.

CADM2 has been associated with a range of behavioural and metabolic traits, including physical activity, risk-taking, educational attainment, alcohol and cannabis use and obesity. Here, we set out to determine whether CADM2 contributes to mechanisms shared between mental and physical health disorders. We assessed genetic variants in the CADM2 locus for association with phenotypes in the UK Biobank, IMPROVE, PROCARDIS and SCARFSHEEP studies, before performing meta-analyses. A wide range of metabolic phenotypes were meta-analysed. Psychological phenotypes analysed in UK Biobank only were major depressive disorder, generalised anxiety disorder, bipolar disorder, neuroticism, mood instability and risk-taking behaviour. In UK Biobank, four, 88 and 172 genetic variants were significantly (p < 1 × 10-5) associated with neuroticism, mood instability and risk-taking respectively. In meta-analyses of 4 cohorts, we identified 362, 63 and 11 genetic variants significantly (p < 1 × 10-5) associated with BMI, SBP and CRP respectively. Genetic effects on BMI, CRP and risk-taking were all positively correlated, and were consistently inversely correlated with genetic effects on SBP, mood instability and neuroticism. Conditional analyses suggested an overlap in the signals for physical and psychological traits. Many significant variants had genotype-specific effects on CADM2 expression levels in adult brain and adipose tissues. CADM2 variants influence a wide range of both psychological and metabolic traits, suggesting common biological mechanisms across phenotypes via regulation of CADM2 expression levels in adipose tissue. Functional studies of CADM2 are required to fully understand mechanisms connecting mental and physical health conditions.

Breast cancer quantitative proteome and proteogenomic landscape.

In the preceding decades, molecular characterization has revolutionized breast cancer (BC) research and therapeutic approaches. Presented herein, an unbiased analysis of breast tumor proteomes, inclusive of 9995 proteins quantified across all tumors, for the first time recapitulates BC subtypes. Additionally, poor-prognosis basal-like and luminal B tumors are further subdivided by immune component infiltration, suggesting the current classification is incomplete. Proteome-based networks distinguish functional protein modules for breast tumor groups, with co-expression of EGFR and MET marking ductal carcinoma in situ regions of normal-like tumors and lending to a more accurate classification of this poorly defined subtype. Genes included within prognostic mRNA panels have significantly higher than average mRNA-protein correlations, and gene copy number alterations are dampened at the protein-level; underscoring the value of proteome quantification for prognostication and phenotypic classification. Furthermore, protein products mapping to non-coding genomic regions are identified; highlighting a potential new class of tumor-specific immunotherapeutic targets.

Conbase: a software for unsupervised discovery of clonal somatic mutations in single cells through read phasing.

Accurate variant calling and genotyping represent major limiting factors for downstream applications of single-cell genomics. Here, we report Conbase for the identification of somatic mutations in single-cell DNA sequencing data. Conbase leverages phased read data from multiple samples in a dataset to achieve increased confidence in somatic variant calls and genotype predictions. Comparing the performance of Conbase to three other methods, we find that Conbase performs best in terms of false discovery rate and specificity and provides superior robustness on simulated data, in vitro expanded fibroblasts and clonal lymphocyte populations isolated directly from a healthy human donor.

GWAS and colocalization analyses implicate carotid intima-media thickness and carotid plaque loci in cardiovascular outcomes.

Carotid artery intima media thickness (cIMT) and carotid plaque are measures of subclinical atherosclerosis associated with ischemic stroke and coronary heart disease (CHD). Here, we undertake meta-analyses of genome-wide association studies (GWAS) in 71,128 individuals for cIMT, and 48,434 individuals for carotid plaque traits. We identify eight novel susceptibility loci for cIMT, one independent association at the previously-identified PINX1 locus, and one novel locus for carotid plaque. Colocalization analysis with nearby vascular expression quantitative loci (cis-eQTLs) derived from arterial wall and metabolic tissues obtained from patients with CHD identifies candidate genes at two potentially additional loci, ADAMTS9 and LOXL4. LD score regression reveals significant genetic correlations between cIMT and plaque traits, and both cIMT and plaque with CHD, any stroke subtype and ischemic stroke. Our study provides insights into genes and tissue-specific regulatory mechanisms linking atherosclerosis both to its functional genomic origins and its clinical consequences in humans.

Author Correction: Discovery and refinement of genetic loci associated with cardiometabolic risk using dense imputation maps.

In the version of the article published, the surname of author Aaron Isaacs is misspelled as Issacs.

H19 Induces Abdominal Aortic Aneurysm Development and Progression.

BACKGROUND: Long noncoding RNAs have emerged as critical molecular regulators in various biological processes and diseases. Here we sought to identify and functionally characterize long noncoding RNAs as potential mediators in abdominal aortic aneurysm development. METHODS: We profiled RNA transcript expression in 2 murine abdominal aortic aneurysm models, Angiotensin II (ANGII) infusion in apolipoprotein E-deficient ( ApoE-/-) mice (n=8) and porcine pancreatic elastase instillation in C57BL/6 wild-type mice (n=12). The long noncoding RNA H19 was identified as 1 of the most highly upregulated transcripts in both mouse aneurysm models compared with sham-operated controls. This was confirmed by quantitative reverse transcription-polymerase chain reaction and in situ hybridization. RESULTS: Experimental knock-down of H19, utilizing site-specific antisense oligonucleotides (LNA-GapmeRs) in vivo, significantly limited aneurysm growth in both models. Upregulated H19 correlated with smooth muscle cell (SMC) content and SMC apoptosis in progressing aneurysms. Importantly, a similar pattern could be observed in human abdominal aortic aneurysm tissue samples, and in a novel preclinical LDLR-/- (low-density lipoprotein receptor) Yucatan mini-pig aneurysm model. In vitro knock-down of H19 markedly decreased apoptotic rates of cultured human aortic SMCs, whereas overexpression of H19 had the opposite effect. Notably, H19-dependent apoptosis mechanisms in SMCs appeared to be independent of miR-675, which is embedded in the first exon of the H19 gene. A customized transcription factor array identified hypoxia-inducible factor 1α as the main downstream effector. Increased SMC apoptosis was associated with cytoplasmic interaction between H19 and hypoxia-inducible factor 1α and sequential p53 stabilization. Additionally, H19 induced transcription of hypoxia-inducible factor 1α via recruiting the transcription factor specificity protein 1 to the promoter region. CONCLUSIONS: The long noncoding RNA H19 is a novel regulator of SMC survival in abdominal aortic aneurysm development and progression. Inhibition of H19 expression might serve as a novel molecular therapeutic target for aortic aneurysm disease.

Identification of a novel proinsulin-associated SNP and demonstration that proinsulin is unlikely to be a causal factor in subclinical vascular remodelling using Mendelian randomisation.

BACKGROUND AND AIMS: Increased proinsulin relative to insulin levels have been associated with subclinical atherosclerosis (measured by carotid intima-media thickness (cIMT)) and are predictive of future cardiovascular disease (CVD), independently of established risk factors. The mechanisms linking proinsulin to atherosclerosis and CVD are unclear. A genome-wide meta-analysis has identified nine loci associated with circulating proinsulin levels. Using proinsulin-associated SNPs, we set out to use a Mendelian randomisation approach to test the hypothesis that proinsulin plays a causal role in subclinical vascular remodelling. METHODS: We studied the high CVD-risk IMPROVE cohort (n = 3345), which has detailed biochemical phenotyping and repeated, state-of-the-art, high-resolution carotid ultrasound examinations. Genotyping was performed using Illumina Cardio-Metabo and Immuno arrays, which include reported proinsulin-associated loci. Participants with type 2 diabetes (n = 904) were omitted from the analysis. Linear regression was used to identify proinsulin-associated genetic variants. RESULTS: We identified a proinsulin locus on chromosome 15 (rs8029765) and replicated it in data from 20,003 additional individuals. An 11-SNP score, including the previously identified and the chromosome 15 proinsulin-associated loci, was significantly and negatively associated with baseline IMTmean and IMTmax (the primary cIMT phenotypes) but not with progression measures. However, MR-Eggers refuted any significant effect of the proinsulin-associated 11-SNP score, and a non-pleiotropic SNP score of three variants (including rs8029765) demonstrated no effect on baseline or progression cIMT measures. CONCLUSIONS: We identified a novel proinsulin-associated locus and demonstrated that whilst proinsulin levels are associated with cIMT measures, proinsulin per se is unlikely to have a causative effect on cIMT.

Fast and general tests of genetic interaction for genome-wide association studies.

A complex disease has, by definition, multiple genetic causes. In theory, these causes could be identified individually, but their identification will likely benefit from informed use of anticipated interactions between causes. In addition, characterizing and understanding interactions must be considered key to revealing the etiology of any complex disease. Large-scale collaborative efforts are now paving the way for comprehensive studies of interaction. As a consequence, there is a need for methods with a computational efficiency sufficient for modern data sets as well as for improvements of statistical accuracy and power. Another issue is that, currently, the relation between different methods for interaction inference is in many cases not transparent, complicating the comparison and interpretation of results between different interaction studies. In this paper we present computationally efficient tests of interaction for the complete family of generalized linear models (GLMs). The tests can be applied for inference of single or multiple interaction parameters, but we show, by simulation, that jointly testing the full set of interaction parameters yields superior power and control of false positive rate. Based on these tests we also describe how to combine results from multiple independent studies of interaction in a meta-analysis. We investigate the impact of several assumptions commonly made when modeling interactions. We also show that, across the important class of models with a full set of interaction parameters, jointly testing the interaction parameters yields identical results. Further, we apply our method to genetic data for cardiovascular disease. This allowed us to identify a putative interaction involved in Lp(a) plasma levels between two 'tag' variants in the LPA locus (p = 2.42 ⋅ 10-09) as well as replicate the interaction (p = 6.97 ⋅ 10-07). Finally, our meta-analysis method is used in a small (N = 16,181) study of interactions in myocardial infarction.

Mapping of 79 loci for 83 plasma protein biomarkers in cardiovascular disease.

Recent advances in highly multiplexed immunoassays have allowed systematic large-scale measurement of hundreds of plasma proteins in large cohort studies. In combination with genotyping, such studies offer the prospect to 1) identify mechanisms involved with regulation of protein expression in plasma, and 2) determine whether the plasma proteins are likely to be causally implicated in disease. We report here the results of genome-wide association (GWA) studies of 83 proteins considered relevant to cardiovascular disease (CVD), measured in 3,394 individuals with multiple CVD risk factors. We identified 79 genome-wide significant (p<5e-8) association signals, 55 of which replicated at P<0.0007 in separate validation studies (n = 2,639 individuals). Using automated text mining, manual curation, and network-based methods incorporating information on expression quantitative trait loci (eQTL), we propose plausible causal mechanisms for 25 trans-acting loci, including a potential post-translational regulation of stem cell factor by matrix metalloproteinase 9 and receptor-ligand pairs such as RANK-RANK ligand. Using public GWA study data, we further evaluate all 79 loci for their causal effect on coronary artery disease, and highlight several potentially causal associations. Overall, a majority of the plasma proteins studied showed evidence of regulation at the genetic level. Our results enable future studies of the causal architecture of human disease, which in turn should aid discovery of new drug targets.

Genome-wide association study with additional genetic and post-transcriptional analyses reveals novel regulators of plasma factor XI levels.

Coagulation factor XI (FXI) has become increasingly interesting for its role in pathogenesis of thrombosis. While elevated plasma levels of FXI have been associated with venous thromboembolism and ischemic stroke, its deficiency is associated with mild bleeding. We aimed to determine novel genetic and post-transcriptional plasma FXI regulators.We performed a genome-wide association study (GWAS) for plasma FXI levels, using novel data imputed to the 1000 Genomes reference panel. Individual GWAS analyses, including a total of 16,169 European individuals from the ARIC, GHS, MARTHA and PROCARDIS studies, were meta-analysed and further replicated in 2,045 individuals from the F5L family, GAIT2 and MEGA studies. Additional association with activated partial thromboplastin time (aPTT) was tested for the top SNPs. In addition, a study on the effect of miRNA on FXI regulation was performed using in silico prediction tools and in vitro luciferase assays.Three loci showed robust, replicating association with circulating FXI levels: KNG1 (rs710446, P-value = 2.07 × 10-302), F11 (rs4253417, P-value = 2.86 × 10-193), and a novel association in GCKR (rs780094, P-value = 3.56 ×10-09), here for the first time implicated in FXI regulation. The two first SNPs (rs710446 and rs4253417) also associated with aPTT. Conditional and haplotype analyses demonstrated a complex association signal, with additional novel SNPs modulating plasma FXI levels in both the F11 and KNG1 loci. Finally, eight miRNAs were predicted to bind F11 mRNA. Over-expression of either miR-145 or miR-181 significantly reduced the luciferase activity in cells transfected with a plasmid containing FXI-3'UTR.These results should open the door to new therapeutic targets for thrombosis prevention.

Soluble CD93 Is Involved in Metabolic Dysregulation but Does Not Influence Carotid Intima-Media Thickness.

Type 2 diabetes and cardiovascular disease are complex disorders involving metabolic and inflammatory mechanisms. Here we investigated whether sCD93, a group XIV c-type lectin of the endosialin family, plays a role in metabolic dysregulation or carotid intima-media thickness (IMT). Although no association was observed between sCD93 and IMT, sCD93 levels were significantly lower in subjects with type 2 diabetes (n = 901, mean ± SD 156.6 ± 40.0 ng/mL) compared with subjects without diabetes (n = 2,470, 164.1 ± 44.8 ng/mL, P < 0.0001). Genetic variants associated with diabetes risk (DIAGRAM Consortium) did not influence sCD93 levels (individually or combined in a single nucleotide polymorphism score). In a prospective cohort, lower sCD93 levels preceded the development of diabetes. Consistent with this, a cd93-deficient mouse model (in addition to apoe deficiency) demonstrated no difference in atherosclerotic lesion development compared with apoe(-/-) cd93-sufficient littermates. However, cd93-deficient mice showed impaired glucose clearance and insulin sensitivity (compared with littermate controls) after eating a high-fat diet. The expression of cd93 was observed in pancreatic islets, and leaky vessels were apparent in cd93-deficient pancreases. We further demonstrated that stress-induced release of sCD93 is impaired by hyperglycemia. Therefore, we propose CD93 as an important component in glucometabolic regulation.

Discovery and refinement of genetic loci associated with cardiometabolic risk using dense imputation maps.

Large-scale whole-genome sequence data sets offer novel opportunities to identify genetic variation underlying human traits. Here we apply genotype imputation based on whole-genome sequence data from the UK10K and 1000 Genomes Project into 35,981 study participants of European ancestry, followed by association analysis with 20 quantitative cardiometabolic and hematological traits. We describe 17 new associations, including 6 rare (minor allele frequency (MAF) < 1%) or low-frequency (1% < MAF < 5%) variants with platelet count (PLT), red blood cell indices (MCH and MCV) and HDL cholesterol. Applying fine-mapping analysis to 233 known and new loci associated with the 20 traits, we resolve the associations of 59 loci to credible sets of 20 or fewer variants and describe trait enrichments within regions of predicted regulatory function. These findings improve understanding of the allelic architecture of risk factors for cardiometabolic and hematological diseases and provide additional functional insights with the identification of potentially novel biological targets.

Analysis with the exome array identifies multiple new independent variants in lipid loci.

It has been hypothesized that low frequency (1-5% minor allele frequency (MAF)) and rare (<1% MAF) variants with large effect sizes may contribute to the missing heritability in complex traits. Here, we report an association analysis of lipid traits (total cholesterol, LDL-cholesterol, HDL-cholesterol triglycerides) in up to 27 312 individuals with a comprehensive set of low frequency coding variants (ExomeChip), combined with conditional analysis in the known lipid loci. No new locus reached genome-wide significance. However, we found a new lead variant in 26 known lipid association regions of which 16 were >1000-fold more significant than the previous sentinel variant and not in close LD (six had MAF <5%). Furthermore, conditional analysis revealed multiple independent signals (ranging from 1 to 5) in a third of the 98 lipid loci tested, including rare variants. Addition of our novel associations resulted in between 1.5- and 2.5-fold increase in the proportion of heritability explained for the different lipid traits. Our findings suggest that rare coding variants contribute to the genetic architecture of lipid traits.

Genetic loci on chromosome 5 are associated with circulating levels of interleukin-5 and eosinophil count in a European population with high risk for cardiovascular disease.

IL-5 is a Th2 cytokine which activates eosinophils and is suggested to have an atheroprotective role. Genetic variants in the IL5 locus have been associated with increased risk of CAD and ischemic stroke. In this study we aimed to identify genetic variants associated with IL-5 concentrations and apply a Mendelian randomisation approach to assess IL-5 levels for causal effect on intima-media thickness in a European population at high risk of coronary artery disease. We analysed SNPs within robustly associated candidate loci for immune, inflammatory, metabolic and cardiovascular traits. We identified 2 genetic loci for IL-5 levels (chromosome 5, rs56183820, BETA=0.11, P=6.73E(-5) and chromosome 14, rs4902762, BETA=0.12, P=5.76E(-6)) and one for eosinophil count (rs72797327, BETA=-0.10, P=1.41E(-6)). Both chromosome 5 loci were in the vicinity of the IL5 gene, however the association with IL-5 levels failed to replicate in a meta-analysis of 2 independent cohorts (rs56183820, BETA=0.04, P=0.2763, I(2)=24, I(2)-P=0.2516). No significant associations were observed between SNPs associated with IL-5 levels or eosinophil count and IMT measures. Expression quantitative trait analyses indicate effects of the IL-5 and eosinophil-associated SNPs on RAD50 mRNA expression levels (rs12652920 (r2=0.93 with rs56183820) BETA=-0.10, P=8.64E(-6) and rs11739623 (r2=0.96 with rs72797327) BETA=-0.23, P=1.74E(-29), respectively). Our data do not support a role for IL-5 levels and eosinophil count in intima-media thickness, however SNPs associated with IL-5 and eosinophils might influence stability of the atherosclerotic plaque via modulation of RAD50 levels.

Gene-pseudogene evolution: a probabilistic approach.

Over the last decade, methods have been developed for the reconstruction of gene trees that take into account the species tree. Many of these methods have been based on the probabilistic duplication-loss model, which describes how a gene-tree evolves over a species-tree with respect to duplication and losses, as well as extension of this model, e.g., the DLRS (Duplication, Loss, Rate and Sequence evolution) model that also includes sequence evolution under relaxed molecular clock. A disjoint, almost as recent, and very important line of research has been focused on non protein-coding, but yet, functional DNA. For instance, DNA sequences being pseudogenes in the sense that they are not translated, may still be transcribed and the thereby produced RNA may be functional.