Genome Association Analysis Research Articles

PLIN2 IS AN ARYL HYDROCARBON RECEPTOR TRANSCRIPTIONAL TARGET AND MAY CONTRIBUTE TO MUCOSAL RESTITUTION

Abstract INTRODUCTION Dysregulated barrier function contributes to the pathogenesis in inflammatory bowel diseases (Crohn’s (CD) and ulcerative colitis (UC)). The cytosolic transcription factor aryl hydrocarbon receptor (AHR) is activated by both endogenous and exogenous ligands, and functionally contributes to maintaining mucosal homeostasis. Recently, we demonstrated that AHR activity promotes a pro-restitutive program in small intestine, but this pathway is disrupted in Crohn’s disease. In this study, we sought to identify genetic loci associated with AHR pathway dysfunction and to identify candidate downstream effectors linking AHR activity to mucosal healing. METHODS Organoid lines were established with biopsies from healthy patients (N=4) and patients with IBD (CD=4, UC=5) and from mice with intact Ahr (WT) or Ahr null (KO). Genomic DNA was isolated and genotyped with a custom GSA SNP chip. Organoids were differentiated and treated with AHR agonist 6-Formylindolo[3,2-b]carbazole (FICZ) or vehicle. Expression of AHR transcriptional target cytochrome P450 1A1 (CYP1A1) was determined by quantitative realtime (qRT) PCR and was used to measure AHR activity. Genomic association analysis was performed using PLINK with cell lines with high (>3 fold) CYP1A1 expression as controls and cells with low CYP1A1 expression as cases. RESULTS Using human organoids, nine genetic variants were associated with low AHR activity (p<5x10-8). One variant, rs12338361, has been identified as an expression quantitative trait locus (eQTL) for Perilipin 2 (PLIN2) in other tissues. PLIN2 is involved in lipid droplet formation and trafficking in the liver, but has also been shown to be a PPARγ effector and reduce inflammation by lowering the release of TNFa in the intestine. In WT mouse organoids, expression of Plin2 was increased in response to FICZ treatment (∼50% increase). This upregulation was dependent on Ahr, as Plin2 expression did not increase in KO mouse organoids (∼7% increase). Expression of PLIN2 was assessed in human organoids treated with FICZ and was found to correlate with AHR activity (r=0.953, p=4.896 x 10-7). CONCLUSIONS PLIN2 is a transcriptional target of AHR and may contribute to AHR-mediated epithelial restitution through activation of the PPARγ pathway. This may represent a novel method of controlling inflammation in the intestinal epithelium.

The theory on and software simulating large-scale genomic data for genotype-by-environment interactions

BackgroundWith the emphasis on analysing genotype-by-environment interactions within the framework of genomic selection and genome-wide association analysis, there is an increasing demand for reliable tools that can be used to simulate large-scale genomic data in order to assess related approaches.ResultsWe proposed a theory to simulate large-scale genomic data on genotype-by-environment interactions and added this new function to our developed tool GPOPSIM. Additionally, a simulated threshold trait with large-scale genomic data was also added. The validation of the simulated data indicated that GPOSPIM2.0 is an efficient tool for mimicking the phenotypic data of quantitative traits, threshold traits, and genetically correlated traits with large-scale genomic data while taking genotype-by-environment interactions into account.ConclusionsThis tool is useful for assessing genotype-by-environment interactions and threshold traits methods.

An L0 Regularization Method for Imaging Genetics and Whole Genome Association Analysis on Alzheimer's Disease.

Although the neuroimaging measures build a bridge between genetic variants and disease phenotypes, an assessment of single nucleotide variants changes in brain structure and their clinically influence on the progression of Alzheimer's disease remain largely preliminary. Note that each variant has very weak correlation signal to neuroimaging measures or Alzheimer's disease phenotypes. Therefore, traditional sparse regression-based image genetics approaches confront with unresolvable features, relative high regression error or inapplicability of high-dimensional data. Adopting an [Formula: see text] regularization method, we significantly elevate the regression accuracy of imaging genetics compared with group-sparse multitask regression method. With further analysis on the simulation results, we conclude that multiple regression tasks model may be unsuitable for image genetics. In addition, we carried out a whole genome association analysis between genetic variants (about 388 million loci) and phenotypes (cognition normal, mild cognitive impairment and Alzheimer's disease) with using the [Formula: see text] regularization method. After annotating the effect of all variants by Ensembl Variant Effect Predictor (VEP), our method locates 33 missense variants which can explain 40% phenotype variance. Then, we mapped each missense variant to the nearest gene and carried out pathway enrichment analysis. The Notch signaling pathway and Apoptosis pathway have been reported to be related to the formation of Alzheimer's disease.

Robust Performance of Potentially Functional SNPs in Machine Learning Models for the Prediction of Atorvastatin-Induced Myalgia

Background:Statins can cause muscle symptoms resulting in poor adherence to therapy and increased cardiovascular risk. We hypothesize that combinations of potentially functional SNPs (pfSNPs), rather than individual SNPs, better predict myalgia in patients on atorvastatin. This study assesses the value of potentially functional single nucleotide polymorphisms (pfSNPs) and employs six machine learning algorithms to identify the combination of SNPs that best predict myalgia. Methods: Whole genome sequencing of 183 Chinese, Malay and Indian patients from Singapore was conducted to identify genetic variants associated with atorvastatin induced myalgia. To adjust for confounding factors, demographic and clinical characteristics were also examined for their association with myalgia. The top factor, sex, was then used as a covariate in the whole genome association analyses. Variants that were highly associated with myalgia from this and previous studies were extracted, assessed for potential functionality (pfSNPs) and incorporated into six machine learning models. Predictive performance of a combination of different models and inputs were compared using the average cross validation area under ROC curve (AUC). The minimum combination of SNPs to achieve maximum sensitivity and specificity as determined by AUC, that predict atorvastatin-induced myalgia in most, if not all the six machine learning models was determined. Results: Through whole genome association analyses using sex as a covariate, a larger proportion of pfSNPs compared to non-pf SNPs were found to be highly associated with myalgia. Although none of the individual SNPs achieved genome wide significance in univariate analyses, machine learning models identified a combination of 15 SNPs that predict myalgia with good predictive performance (AUC >0.9). SNPs within genes identified in this study significantly outperformed SNPs within genes previously reported to be associated with myalgia. pfSNPs were found to be more robust in predicting myalgia, outperforming non-pf SNPs in the majority of machine learning models tested. Conclusion: Combinations of pfSNPs that were consistently identified by different machine learning models to have high predictive performance have good potential to be clinically useful for predicting atorvastatin-induced myalgia once validated against an independent cohort of patients.

Genomic signatures of drift and selection driven by predation and human pressure in an insular lizard

Genomic divergence was studied in 10 small insular populations of the endangered Balearic Islands lizard (Podarcis lilfordi) using double digest restriction-site associated DNA sequencing. The objectives were to establish levels of divergence among populations, investigate the impact of population size on genetic variability and to evaluate the role of different environmental factors on local adaptation. Analyses of 72,846 SNPs supported a highly differentiated genetic structure, being the populations with the lowest population size (Porros, Foradada and Esclatasang islets) the most divergent, indicative of greater genetic drift. Outlier tests identified ~ 2% of loci as candidates for selection. Genomic divergence-Enviroment Association analyses were performed using redundancy analyses based on SNPs putatively under selection, detecting predation and human pressure as the environmental variables with the greatest explanatory power. Geographical distributions of populations and environmental factors appear to be fundamental drivers of divergence. These results support the combined role of genetic drift and divergent selection in shaping the genetic structure of these endemic island lizard populations.

Identification and Verification of Molecular Subtypes with Enhanced Immune Infiltration Based on m6A Regulators in Cutaneous Melanoma.

Background As the most aggressive type of skin cancer, cutaneous melanoma (CM) is experiencing a rapidly rising mortality in recent years. Exploring potential prognostic biomarkers or mechanisms of disease progression therefore has a great significance for CM. The purpose of this study was to identify genetic markers and prognostic performance of N6-methyladenosine (m6A) regulators in CM. Method Gene expression profiles, copy number variation (CNV), and single nucleotide polymorphism (SNP) data of patients were obtained from The Cancer Genome Atlas (TCGA) database. Results Genomic variation and association analysis of gene expressions revealed a high degree of genomic variation in the presence of m6A-regulated genes. m6A patients with high-frequency genomic variants in the regulatory gene tended to develop a worse prognosis (p < 0.01). Unsupervised cluster analysis of the expression profiles of m6A-regulated genes identified three clinically distinct molecular subtypes, including degradation-enhanced subgroup and immune-enhanced subgroup, with significant prognostic differences (p = 0.046). A novel prognostic signature, which was established according to m6A-related characteristic genes identified through genome-wide expression spectrum, could effectively identify samples with poor prognosis and enhanced immune infiltration, and the effectiveness was also verified in the dataset of the chip. Conclusion We identified genetic changes in the m6A regulatory gene in CM and related survival outcomes. The findings of this study provide new insights into the epigenetic understanding of m6A in CM.

Whole genome sequence association analyses of brain volumes in the TOPMed program

AbstractBackgroundGenome‐wide association studies (GWAS) of brain volumes have identified common genetic variants with modest effect sizes that lie mainly in non‐coding regions. We sought to identify low frequency and rare variants influencing brain volumes by performing whole genome association analyses using sequence data from the Trans‐Omics for Precision Medicine (TOPMed) Program.MethodsWe analyzed up to 3,975 participants (58% women; 78% Europeans, 22% African‐Americans), mean age of 62.5 (13.9), from four TOPMed population‐ or family‐based studies (FHS, GENESTAR, CHS, and GENOA). We excluded participants with dementia, stroke, presence of large brain infarcts, tumor or any other finding affecting the scan. We tested the association of hippocampal (HV), total brain (TBV), lateral ventricular (LVV) and intracranial (ICV) volumes with individual genetic variants using mixed‐effect linear regression models adjusted for age, age2, sex, study and principal components. Models including HV, TBV and LVV were adjusted for ICV. We accounted for relatedness using a kinship matrix and trait variance variability using a random effects model. We retained variants with a minor allele count greater than 40.ResultsWe detected new genome‐wide significant (P &lt; 5 × 10−8) low frequency or rare variants in five regions associated with HV (5q31, P = 10−9) and TBV (2p22, P = 10−8; 17q25, P = 4 × 10−9; Xp11, P = 2 × 10−10; Xq21, P = 4 × 10−8). We also confirmed previously observed common variants in GWAS loci for HV (12q14 &amp; 12q24), LVV (3q28, 12q23 &amp; 16q24) and ICV (6q21, 6q22 &amp; 17q21). The top 5q31 hit for HV (rs246587) lies at 19kb from the PCDHAC2 gene, encoding neural cadherin‐like cell adhesion proteins that most likely play a critical role in the establishment and maintenance of specific neuronal connections in the brain.ConclusionsOur whole genome analysis revealed intriguing new loci associated with brain volumes. Future work will include ancestry‐specific and conditional analyses, gene‐based and burden tests as well as the inclusion of additional TOPMed cohorts. Supported by: U01s AG058589, AG052409, R01s AG054076, AG033040 AG049607, HL112064, NS062059, FHS contracts HHSN268201500001I and 75N92019D00031, R01HL131136 (Analysis Commons).

Simultaneous Detection of Signal Regions Using Quadratic Scan Statistics With Applications to Whole Genome Association Studies

We consider in this article detection of signal regions associated with disease outcomes in whole genome association studies. Gene- or region-based methods have become increasingly popular in whole genome association analysis as a complementary approach to traditional individual variant analysis. However, these methods test for the association between an outcome and the genetic variants in a prespecified region, for example, a gene. In view of massive intergenic regions in whole genome sequencing (WGS) studies, we propose a computationally efficient quadratic scan (Q-SCAN) statistic based method to detect the existence and the locations of signal regions by scanning the genome continuously. The proposed method accounts for the correlation (linkage disequilibrium) among genetic variants, and allows for signal regions to have both causal and neutral variants, and the effects of signal variants to be in different directions. We study the asymptotic properties of the proposed Q-SCAN statistics. We derive an empirical threshold that controls for the family-wise error rate, and show that under regularity conditions the proposed method consistently selects the true signal regions. We perform simulation studies to evaluate the finite sample performance of the proposed method. Our simulation results show that the proposed procedure outperforms the existing methods, especially when signal regions have causal variants whose effects are in different directions, or are contaminated with neutral variants. We illustrate Q-SCAN by analyzing the WGS data from the Atherosclerosis Risk in Communities study. Supplementary materials for this article are available online.

POPULATION STRUCTURE AND GENOME-WIDE ASSOCIATION ANALYSIS FOR SALINITY TOLERANCE IN BREAD WHEAT USING SNP, SSR AND SCOT MARKER ASSAYS

Wheat is an essential staple food in the developing world, where demand is projected to grow exponentially in the future; simultaneously, climate changes are projected to reduce supply in the near future. One of the main consequences of climate change is salinity, which negatively impacts the world's cultivated area and therefore affects the global wheat production. Our objectives are to study the population structure of several Egyptian and international wheat accessions and to identify the genetic factors controlling the salinity stress response of bread wheat. In addition, we have attempt to identify genes that control some important agronomic parameters of wheat under salinity stress were identified. The wheat germplasm panel consisted of 70 accessions obtained from Egypt, Syria and Iran. The assessment of salinity tolerance was conducted over the years of 2018 and 2019 in the field and in the greenhouse. The genome association analysis (GWAS) and population structure analysis was conducted using six SCoT, five SSR and 93 SNP markers. Analysis of the population structure using allele frequency and phylogenetic analysis indicated that the studied wheat accessions were belong to four population groups. Where, for the most portion, Egyptian, Syrian and Iranian accessions are clustered depending on their country of origin. The GWAS analysis revealed 13 SNP markers that were significantly associated with morpho-agronomic wheat traits during salinity stress. These markers were closely related to genes that are known to have a direct link to wheat response to salinity stress such as CYP709B2, MDIS2, STAYGREEN, PIP5K9, and MSSP2 genes. This study revealed the genetic structure of adapted and imported wheat accessions, which could be used to select potential wheat accessions for local breeding programs. In addition, the SNP genotyping assay is a very potential technology that could be efficiently applied to detect genes that control bread wheat response to salinity stress.

Identification of Disease-Associated Variants by Targeted Gene Panel Resequencing in Parkinson's Disease.

Background: Recent advanced technologies, such as high-throughput sequencing, have enabled the identification of a broad spectrum of variants. Using targeted-gene-panel resequencing for Parkinson's disease (PD)-associated genes, we have occasionally found several single-nucleotide variants (SNVs), which are thought to be disease-associated, in PD patients. To confirm the significance of these potentially disease-associated variants, we performed genome association analyses, using next-generation target resequencing, to evaluate the associations between the identified SNVs and PD.Methods: We obtained genomic DNA from 766 patients, who were clinically diagnosed with PD, and 336 healthy controls, all of Japanese origin. All data were analyzed using Ion AmpliSeq panel sequences, with 29 PD- or dementia-associated genes in a single panel. We excluded any variants that did not comply with the Hardy–Weinberg equilibrium in the control group. Variant frequencies in the PD and control groups were compared using PLINK. The identified variants were confirmed to a frequency difference of P < 0.05, after applying the Benjamini–Hochberg procedure using Fisher's exact test. The pathogenicity and prevalence of each variant were estimated based on a public gene database.Results: We identified three rare variants that were significantly associated with PD: rs201012663/rs150500694 in SYNJ1 and rs372754391 in DJ-1, which are intronic variants, and rs7412 in ApoE, which is an exonic variant. The variants in SYNJ1 and ApoE were frequently identified in the control group, and rs201012663/rs150500694 in SYNJ1 may play a protective role against PD. The DJ-1 variant was frequently identified in the PD group, with a high odds ratio of 2.2.Conclusion: The detected variants may represent genetic modifiers or disease-related variants in PD. Targeted-gene-panel resequencing may represent a useful method for detecting disease-causing variants and genetic association studies in PD.

Population structure and genome-wide association analysis for salinity tolerance in wheat using SNP, SSR and SCoT marker assays.

Wheat is an essential staple food in the developing world, where demand is projected to grow exponentially in the future; simultaneously, climate changes are projected to reduce supply in the near future. One of the main consequences of climate change is salinity, which negatively impacts the world's cultivated area and therefore affects the global wheat production. Our objectives are to study the population structure of several Egyptian and international wheat accessions and to identify the genetic factors controlling the salinity stress response of b wheat. In addition, we have attempt to identify genes that control some important agronomic parameters of wheat under salinity stress were identified. The wheat germplasm panel consisted of 70 accessions obtained from Egypt, Syria and Iran. The assessment of salinity tolerance was conducted over the years of 2018 and 2019 in the field and in the greenhouse. The genome association analysis (GWAS) and population structure analysis was conducted using six SCoT, five SSR and 93 SNP markers. Analysis of the population structure using allele frequency and phylogenetic analysis indicated that the studied wheat accessions were belong to four population groups. Where, for the most portion, Egyptian, Syrian and Iranian accessions are clustered depending on their country of origin. The GWAS analysis revealed 13 SNP markers that were significantly associated with morpho-agronomic wheat traits during salinity stress. These markers were closely related to genes that are known to have a direct link to wheat response to salinity stress such as CYP709B2, MDIS2, STAY-GREEN, PIP5K9, and MSSP2 genes. This study revealed the genetic structure of adapted and imported wheat accessions, which could be used to select potential wheat accessions for local breeding programs. In addition, the SNP genotyping assay is a very potential technology that could be efficiently applied to detect genes that control bread wheat response to salinity stress.

A large-scale genomic association analysis identifies the candidate causal genes conferring stripe rust resistance under multiple field environments.

SummaryThe incorporation of resistance genes into wheat commercial varieties is the ideal strategy to combat stripe or yellow rust (YR). In a search for novel resistance genes, we performed a large‐scale genomic association analysis with high‐density 660K single nucleotide polymorphism (SNP) arrays to determine the genetic components of YR resistance in 411 spring wheat lines. Following quality control, 371 972 SNPs were screened, covering over 50% of the high‐confidence annotated gene space. Nineteen stable genomic regions harbouring 292 significant SNPs were associated with adult‐plant YR resistance across nine environments. Of these, 14 SNPs were localized in the proximity of known loci widely used in breeding. Obvious candidate SNP variants were identified in certain confidence intervals, such as the cloned gene Yr18 and the major locus on chromosome 2BL, despite a large extent of linkage disequilibrium. The number of causal SNP variants was refined using an independent validation panel and consideration of the estimated functional importance of each nucleotide polymorphism. Interestingly, four natural polymorphisms causing amino acid changes in the gene TraesCS2B01G513100 that encodes a serine/threonine protein kinase (STPK) were significantly involved in YR responses. Gene expression and mutation analysis confirmed that STPK played an important role in YR resistance. PCR markers were developed to identify the favourable TraesCS2B01G513100 haplotype for marker‐assisted breeding. These results demonstrate that high‐resolution SNP‐based GWAS enables the rapid identification of putative resistance genes and can be used to improve the efficiency of marker‐assisted selection in wheat disease resistance breeding.

EPAS1 and VEGFA gene variants are related to the symptoms of acute mountain sickness in Chinese Han population: a cross-sectional study

BackgroundMore people ascend to high altitude (HA) for various activities, and some individuals are susceptible to HA illness after rapidly ascending from plains. Acute mountain sickness (AMS) is a general complaint that affects activities of daily living at HA. Although genomic association analyses suggest that single nucleotide polymorphisms (SNPs) are involved in the genesis of AMS, no major gene variants associated with AMS-related symptoms have been identified.MethodsIn this cross-sectional study, 604 young, healthy Chinese Han men were recruited in June and July of 2012 in Chengdu, and rapidly taken to above 3700 m by plane. Basic demographic parameters were collected at sea level, and heart rate, pulse oxygen saturation (SpO2), systolic and diastolic blood pressure and AMS-related symptoms were determined within 18–24 h after arriving in Lhasa. AMS patients were identified according to the latest Lake Louise scoring system (LLSS). Potential associations between variant genotypes and AMS/AMS-related symptoms were identified by logistic regression after adjusting for potential confounders (age, body mass index and smoking status).ResultsIn total, 320 subjects (53.0%) were diagnosed with AMS, with no cases of high-altitude pulmonary edema or high-altitude cerebral edema. SpO2 was significantly lower in the AMS group than that in the non-AMS group (P = 0.003). Four SNPs in hypoxia-inducible factor-related genes were found to be associated with AMS before multiple hypothesis testing correction. The rs6756667 (EPAS1) was associated with mild gastrointestinal symptoms (P = 0.013), while rs3025039 (VEGFA) was related to mild headache (P = 0.0007). The combination of rs6756667 GG and rs3025039 CT/TT further increased the risk of developing AMS (OR = 2.70, P < 0.001).ConclusionsUnder the latest LLSS, we find that EPAS1 and VEGFA gene variants are related to AMS susceptibility through different AMS-related symptoms in the Chinese Han population; this tool might be useful for screening susceptible populations and predicting clinical symptoms leading to AMS before an individual reaches HA.Trial registrationChinese Clinical Trial Registration, ChiCTR-RCS-12002232. Registered 31 May 2012.

Population genomic and genome-wide association analysis of lignin content in a global collection of 206 forage sorghum accessions

Forage sorghum (Sorghum bicolor (L.) Moench) is a wildly cultivated C4 cereal crop in many geographical regions and differs among germplasms in a number of important physiological traits. Lignin is a complex heteropolymer found in plant cell walls that adversely affects economic and environmental benefits of the crop. To understand the genetic basis, we re-sequenced the genomes of 206 sorghum accessions collected around the globe and identified 14,570,430 SNPs and 1,967,033 indels. Based on the SNP markers, we characterized the population structure and identified loci underlying lignin content by genome-wide association studies (GWAS). Analysis of the genetic relationships among the accessions revealed a more diverse spread of sorghum accessions and breeding lines from Asia, America, and their genetically improved variety, but a limited genetic diversity in the European accessions. These findings add new perspectives to the historical processes of crop diffusion within and across agroclimatic zones of America, Asia, and Europe. GWAS revealed 9 quantitative trait loci (QTLs) for lignin content, harboring 184 genes. These genes were significantly enriched into 7 major gene ontology (GO) terms involved in plant-type cell wall organization or bioenergy. The alleles of 9 QTLs in the 206 accessions were geographically distributed. The findings provide us with an understanding of the origin and spread of haplotypes linked to lignin content. The findings will allow improvements to feed quality and adaptation to stresses in sorghum, through the rapid increase of genetic gains for lignin content.

Genome‐wide Quantitative Trait Loci (QTL) Mapping of Metabolites in Human Cerebrospinal Fluid

Genome‐wide association studies (GWAS) are used to identify genetic loci that are associated with a trait of interest in order to decipher underlying biological mechanisms. Metabolite measures in cerebrospinal fluid (CSF), the fluid that surrounds the brain, provides insight into brain function that may be relevant for neurobehavioral traits and neuropsychiatric disorders. We performed a GWAS of 1,000 metabolites in a sample of 600 human subjects, the largest set of CSF data used in a GWAS to date. We applied standard quality control of genetic data including missingness, minor allele frequency cut‐off, and population stratification. Phenotype data were checked for outliers, and non‐normal data were transformed using inverse rank normalization. A linear association, including age and sex as additional covariates, was performed using the PLINK whole genome association analysis toolset. Significant SNP associations were found in 45 metabolites. Analysis via functional mapping and annotation (FUMA) downstream GWAS analysis tool found that many of these SNPs have been associated with other traits by other GWAS. Linked traits include blood metabolite levels and brain related traits such as cognitive performance. Results show that a GWAS can be successfully performed with CSF metabolite data, and indicate a relationship between CSF and blood metabolite levels. Further steps include analysis of other CSF metabolites and the use of dosage genotype data for potentially more detailed results.

Association of α/β-Hydrolase D16B with Bovine Conception Rate and Sperm Plasma Membrane Lipid Composition.

We have identified a Holstein sire named Tarantino who had been approved for artificial insemination that is based on normal semen characteristics (i.e., morphology, thermoresistance, motility, sperm concentration), but had no progeny after 412 first inseminations, resulting in a non-return rate (NRdev) of −29. Using whole genome association analysis and next generation sequencing, an associated nonsense variant in the α/β-hydrolase domain-containing 16B gene (ABHD16B) on bovine chromosome 13 was identified. The frequency of the mutant allele in the German Holstein population was determined to be 0.0018 in 222,645 investigated cattle specimens. The mutant allele was traced back to Whirlhill Kingpin (bornFeb. 13th, 1959) as potential founder. The expression of ABHD16B was detected by Western blotting and immunohistochemistry in testis and epididymis of control bulls. A lipidome comparison of the plasma membrane of fresh semen from carriers and controls showed significant differences in the concentration of phosphatidylcholine (PC), diacylglycerol (DAG), ceramide (Cer), sphingomyelin (SM), and phosphatidylcholine (-ether) (PC O-), indicating that ABHD16B plays a role in lipid biosynthesis. The altered lipid contents may explain the reduced fertilization ability of mutated sperms.

Genomic Prediction and Association Analysis with Models Including Dominance Effects for Important Traits in Chinese Simmental Beef Cattle.

Simple SummaryDominance effects play important roles in determining genetic changes with regard to complex traits. We conducted genomic predictions and genome-wide association studies in order to investigate the effects of dominance on carcass weight, dressing percentage, meat percentage, average daily gain, and chuck roll in 1233 Simmental beef cattle. Using dominance models, we improved the predictive abilities and found several candidate single-nucleotide polymorphisms (SNPs) and genes associated with these traits. Our studies helped us to understand causal mutation mapping and genomic selection models with dominance effects in Chinese Simmental beef cattle.Non-additive effects play important roles in determining genetic changes with regard to complex traits; however, such effects are usually ignored in genetic evaluation and quantitative trait locus (QTL) mapping analysis. In this study, a two-component genome-based restricted maximum likelihood (GREML) was applied to obtain the additive genetic variance and dominance variance for carcass weight (CW), dressing percentage (DP), meat percentage (MP), average daily gain (ADG), and chuck roll (CR) in 1233 Simmental beef cattle. We estimated predictive abilities using additive models (genomic best linear unbiased prediction (GBLUP) and BayesA) and dominance models (GBLUP-D and BayesAD). Moreover, genome-wide association studies (GWAS) considering both additive and dominance effects were performed using a multi-locus mixed-model (MLMM) approach. We found that the estimated dominance variances accounted for 15.8%, 16.1%, 5.1%, 4.2%, and 9.7% of the total phenotypic variance for CW, DP, MP, ADG, and CR, respectively. Compared with BayesA and GBLUP, we observed 0.5–1.1% increases in predictive abilities of BayesAD and 0.5–0.9% increases in predictive abilities of GBLUP-D, respectively. Notably, we identified a dominance association signal for carcass weight within RIMS2, a candidate gene that has been associated with carcass weight in beef cattle. Our results suggest that dominance effects yield variable degrees of contribution to the total genetic variance of the studied traits in Simmental beef cattle. BayesAD and GBLUP-D are convenient models for the improvement of genomic prediction, and the detection of QTLs using a dominance model shows promise for use in GWAS in cattle.

Genomic Analysis of Chilean Strains of Campylobacter jejuni from Human Faeces.

Campylobacter spp., especially C. jejuni, are recognized worldwide as the bacterial species that most commonly cause food-related diarrhea. C. jejuni possesses many different virulence factors, has the ability to survive in different reservoirs, and has shown among isolates the emergence of Antimicrobial Resistance (AMR). Genome association analyses of this bacterial pathogen have contributed to a better understanding of its pathogenic and AMR associated determinants. However, the epidemiological information of these bacteria in Latin American countries is scarce and no genomic information is available in public databases from isolates in these countries. Considering this, the present study is aimed to describe the genomic traits from representative Campylobacter spp. strains recovered from faecal samples of patients with acute diarrhoea from Valparaíso, Chile. Campylobacter spp. was detected from the faeces of 28 (8%) out of 350 patients with acute diarrhoea, mainly from young adults and children, and 26 (93%) of the isolates corresponded to C. jejuni. 63% of the isolates were resistant to ciprofloxacin, 25.9% to tetracycline, and 3.5% to erythromycin. Three isolates were selected for WGS on the basis of their flaA-RFLP genotype. They belonged to the multilocus sequence typing (MLST) clonal clomplex (CC) 21(PUCV-1), CC-48 (PUCV-3), and CC-353 (PUCV-2) and presented several putative virulence genes, including the Type IV and Type VI Secretion Systems, as well as AMR-associated genes in agreement with their susceptibility pattern. On the basis of the wgMLST, they were linked to strains from poultry and ruminants. These are the first genomes of Chilean C. jejuni isolates available in public databases and they provide relevant information about the C. jejuni isolates associated with human infection in this country.

Differential genetic and functional background in inflammatory bowel disease phenotypes of a Greek population: a systems bioinformatics approach

BackgroundCrohn’s disease (CD) and Ulcerative colitis (UC) are the two main entities of inflammatory bowel disease (IBD). Previous works have identified more than 200 risk factors (including loci and signaling pathways) in populations of predominantly European ancestry. Our study was conducted on an extended population-specific cohort of 573 Greek IBD patients (364 CD and 209 UC) and 445 controls.AimsTo highlight the different genetic and functional background of IBD and its phenotypes, utilizing contemporary systems bioinformatics methodologies.MethodsDisease-associated SNPs, obtained via our own 89 loci IBD risk GWAS panel, were detected with the whole genome association analysis toolset PLINK. These SNPs were used as input for 2 novel and different pathway analysis methods to detect functional interactions. Specifically, PathwayConnector was used to create complementary networks of interacting pathways whereas; the online database of protein interactions STRING provided protein–protein association networks and their derived pathways. Network analyses metrics were employed to identify proteins with high significance and subsequently to rank the signaling pathways those participate in.ResultsThe reported complementary pathway and enriched protein–protein association networks reveal several novel and well-known key players, in the functional background of IBD like Toll-like receptor, TNF, Jak-STAT, PI3K-Akt, T cell receptor, Apoptosis, MAPK and B cell receptor signaling pathways. IBD subphenotypes are found to have distinct genetic and functional profiles which can contribute to their accurate identification and classification. As a secondary result we identify an extended network of diseases with common molecular background to IBD.ConclusionsIBD’s burden on the quality of life of patients and intricate functional background presents us constantly with new challenges. Our data and methodology provide researchers with new insights to a specific population, but also, to possible differentiation markers of disease classification and progression. This work, not only provides new insights into the interplay among IBD risk variants and their related signaling pathways, elucidates the mechanisms underlying IBD and its clinical sequelae, but also, introduces a generalized bioinformatics-based methodology which can be applied to studies of different disorders.

Genomic Association Analysis Reveals Variants Associated With Blood Pressure Response to Beta-Blockers in European Americans.

European Americans (EA) have a better antihypertensive response to β‐blockers when compared with African Americans, albeit with some variability. We undertook a genomewide association study to elucidate the underlying genetic determinants in EA contributing to this variability in blood pressure (BP) response. A discovery genomewide association study of change in BP post–metoprolol treatment was performed in EA participants (n = 201) from the Pharmacogenomic Evaluation of Antihypertensive Responses‐2 (PEAR‐2) study and tested for replication in the atenolol‐treated EA from the PEAR study (n = 233). Rs294610 in the FGD5, which encodes for FYVE, RhoGEF and PH Domain Containing 5, (expression quantitative trait loci for FGD5 in the small intestine) was significantly associated with increased diastolic BP response to β‐blockers in the PEAR‐2 study (P = 3.41 × 10−6, β = −2.70) and replicated (P = 0.01, β = −1.17) in the PEAR study. Post–meta‐analysis of these studies, an additional single nucleotide polymorphism rs45545233 in the SLC4A1, encoding for Solute Carrier Family 4 Member 1, (expression quantitative trait loci for dual specificity phosphatase 3 in the artery tibial) was identified that was significantly associated with a poor response to β‐blockers (P = 3.43 × 10−6, β = 4.57) and was replicated in the atenolol add‐on cohort (P = 0.007, β = 4.97). We identified variants in FGD5 and SLC4A1, which have been previously cited as candidate genes for hypertension, to be associated with a β‐blocker BP response in EA. Further elucidation is warranted of the underlying mechanisms of these variants and genes by which they influence the BP response to β‐blockers.