Genome-wide Genotyping Arrays Research Articles

Association of gut microbiota with critical pneumonia: A two-sample Mendelian randomization study.

This study investigated the causal effect of gut microbiota on critical pneumonia. Data came from a large-scale gut microbiota data set (n = 18,340) and the critical pneumonia genome-wide genotyping array (cases n = 2758 and controls n = 42,8607). Inverse variance weighting was used as the primary Mendelian randomization (MR) analysis method. Weighted median, MR-Egger, simple model, weighted model, and MR-Egger, were used to evaluate robustness. Sensitivity analysis used Cochran Q test, MR-Egger intercept test, and MR-PRESSO. For critical pneumonia, inverse variance weighting estimates suggested that Class Verrucomicrobiae (OR = 0.415; 95% CI: 0.207, 0.833; P = .013), Family Verrucomicrobiaceae (OR = 0.415; 95% CI: 0.207, 0.833; P = .013), Genus Akkermansia (OR = 0.415; 95% CI: 0.207, 0.833; P = .013), Genus LachnospiraceaeFCS020group (OR = 0.449; 95% CI: 0.230, 0.890; P = .021), Genus Parasutterella (OR = 0.466; 95% CI: 0.233, 0.929; P = .030), Genus Prevotella7 (OR = 0.645; 95% CI: 0.432, 0.960; P = .031), Order Verrucomicrobiales (OR = 0.415; 95% CI: 0.207, 0.833; P = .013), and Phylum Cyanobacteria (OR = 0.510; 95% CI: 0.272, 0.956; P = .036) had a reduced risk, while Family Enterobacteriaceae (OR = 2.746; 95% CI: 1.008, 7.474; P = .048), Genus RuminococcaceaeUCG003 (OR = 2.811; 95% CI: 1.349, 5.851; P = .006) and Order Enterobacteriales (OR = 2.746; 95% CI: 1.008, 7.474; P = .048) were associated with an increased risk. Sensitivity analyses confirmed that the aforementioned correlations were robust.

Ancestry-Related Differences in Allele and Genotype Frequencies of EGF A61G Polymorphism in the Cuban Population

Background: The polymorphism rs4444903 of the Epidermal Growth Factor gene (EGF A61G) causes differences in the EGF serum levels. It has become a biomarker for genetic susceptibility to cancer and a pharmacogenomic marker for therapies involving the EGF/EGF-receptor pathway. Objective: The present study aimed to characterize the allele and genotype frequencies of the rs4444903 in a Cuban sample and its relationship to a specific genetic ancestry. Methods: A cross-sectional study was carried out. Genomic data was collected from a dense genome-wide genotyping array analysis of 948 Cubans from all provinces. The allele and genotype frequencies of the rs4444903 were calculated. Analysis of ancestryrelated allelic/genotypic differences was performed. Results: The frequencies for both alleles were found to be very similar (0.52 for G vs. 0.48 for A allele), and genotype frequencies were 24.3%, 47.9%, and 27.8% for AA, AG, and GG, respectively. Greater differences were found between Cuban provinces, with frequencies for the G allele ranging from 0.38 in Artemisa to 0.69 in Guantánamo and for the GG genotype from 14.29% in Mayabeque to 50.88% in Guantánamo. An increased African-ancestry proportion was related to a higher probability of carrying G allele and GG genotype, with a significant (p=0.0038, q=0.024) African-ancestry-enrichment pattern. Conclusion: African ancestry seems to contribute to an increase in the EGF61*G allele in Cubans. Geographic patterns in admixture proportions for African and European ancestry are a determinant factor in the allelic and genotypic frequency differences between Cuban provinces. Such differences should be observed when designing association studies and implementing therapeutic approaches based on the EGF/EGF receptor pathway in Cuba.

NeuroBooster Array: A Genome-Wide Genotyping Platform to Study Neurological Disorders Across Diverse Populations.

Commercial genome-wide genotyping arrays have historically neglected coverage of genetic variation across populations. We aimed to create a multi-ancestry genome-wide array that would include a wide range of neuro-specific genetic content to facilitate genetic research in neurological disorders across multiple ancestral groups, fostering diversity and inclusivity in research studies. We developed the Illumina NeuroBooster Array (NBA), a custom high-throughput and cost-effective platform on a backbone of 1,914,934 variants from the Infinium Global Diversity Array and added custom content comprising 95,273 variants associated with more than 70 neurological conditions or traits, and we further tested its performance on more than 2000 patient samples. This novel platform includes approximately 10,000 tagging variants to facilitate imputation and analyses of neurodegenerative disease-related genome-wide association study loci across diverse populations. In this article, we describe NBA's potential as an efficient means for researchers to assess known and novel disease genetic associations in a multi-ancestry framework. The NBA can identify rare genetic variants and accurately impute more than 15 million common variants across populations. Apart from enabling sample prioritization for further whole-genome sequencing studies, we envisage that NBA will play a pivotal role in recruitment for interventional studies in the precision medicine space. From a broader perspective, the NBA serves as a promising means to foster collaborative research endeavors in the field of neurological disorders worldwide. Ultimately, this carefully designed tool is poised to make a substantial contribution to uncovering the genetic etiology underlying these debilitating conditions. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

Pharmacogenomic allele coverage of genome-wide genotyping arrays: a comparative analysis.

The use of genome-wide genotyping arrays in pharmacogenomics (PGx) research and clinical implementation applications is increasing but it is unclear which arrays are best suited for these applications. Here, we conduct a comparative coverage analysis of PGx alleles included on genome-wide genotyping arrays, with an emphasis on alleles in genes with PGx-based prescribing guidelines. Genomic manifest files for seven arrays including the Axiom Precision Medicine Diversity Array (PMDA), Axiom PMDA Plus, Axiom PangenomiX, Axiom PangenomiX Plus, Infinium Global Screening Array, Infinium Global Diversity Array (GDA) and Infinium GDA with enhanced PGx (GDA-PGx) Array, were evaluated for coverage of 523 star alleles across 19 pharmacogenes included in prescribing guidelines developed by the Clinical Pharmacogenetic Implementation Consortium and Dutch Pharmacogenomics Working Group. Specific attention was given to coverage of the Association of Molecular Pathology's Tier 1 and Tier 2 allele sets for CYP2C9, CYP2C19, CYP2D6, CYP3A4, CYP3A5, NUDT15, TPMT and VKORC1 . Coverage of the examined PGx alleles was highest for the Infinium GDA-PGx (88%), Axiom PangenomiX Plus (77%), Axiom PangenomiX (72%) and Axiom PMDA Plus (70%). Three arrays (Infinium GDA-PGx, Axiom PangenomiX Plus and Axiom PMDA Plus) fully covered the Tier 1 alleles and the Axiom PangenomiX array provided full coverage of Tier 2 alleles. In conclusion, PGx allele coverage varied by gene and array. A superior array for all PGx applications was not identified. Future comparative analyses of genotype data produced by these arrays are needed to determine the robustness of the reported coverage estimates.

Single Nucleotide Polymorphisms of MTHFR (rs1051266) and SLC19A1 (rs1801133) Associated to Genomic Ancestry in Cuban Healthy Population

Background: Several single nucleotide polymorphisms on methotrexate pathway have been implicated with hyperhomocysteinemia, susceptibility to autoimmune diseases and the therapy effectiveness of methotrexate Objective: The present study estimates the ethnogeographic prevalence of rs1801133 (c.665C>T) in methylenetetrahydrofolate reductase and rs1051266 (c.80A>G) in solute carrier family Methods: Genomic data was collected from a dense genome-wide genotyping array analysis of a large sample of individuals from all provinces of Cuba, with a final sample of 946 individuals for rs1801133 and 948 individuals for rs1051266. Results: For rs1801133, T allele and TT genotype were more prevalent in Mayabeque, the province with the highest European (p<0.0001) and the lowest African ancestry proportion (p<0.0001). Whereas, T allele and TT genotype frequency were low in Guantánamo (23.7% and 1.8%), the province with the highest African ancestry proportion (p<0.0001) and the lowest European ancestry proportion (p<0.0001). For rs1051266, the higher frequency of G allele was observed in Villa Clara, Las Tunas, Holguín and Granma and this group was associated with AG and GG genotypes (p=0.0045). This seems to be related to high Native American ancestry proportion in Las Tunas (p<0.0001), Holguín (p<0.0001) and Granma (p<0.0001); with the low African ancestry proportion in Villa Clara (p<0.0001) and with a Native American ancestry-enriched pattern observed for these provinces (p=0.0005). Conclusion: These results provide evidence that ancestry contribution impacts in the ethnogeographic prevalence of rs1801133 (c.665C>T) and rs1051266 (c.80A>G) polymorphisms in healthy Cuban individuals.

Application of a non-invasive tool and identification of genetic markers in swine to enhance ham quality: a preliminary study.

A genome-wide association study (GWAS) was performed as a preliminary step to identify regions potentially related to ham quality traits. In this research, genomic information was obtained from 238 commercial hybrid pigs utilising the GeneSeek® Genomic Profiler genome-wide porcine genotyping array. Carcasses were tested for hot weight, the thickness of backfat and loin, and lean meat percentage. The corresponding fresh hams were assayed for weight and ultimate pH; the activities of Cathepsin B and Ferrochelatase of Semimembranosus muscle were determined through fluorimetric methods. The lean meat percentage of fresh ham (LMPH), salt absorbed after first (SALT1) and overall salting stages (SALT) were estimated online by the Ham Inspector™ apparatus. Hams were processed in compliance with the procedures established for Protected Designation of Origin Parma ham, and ham weight losses were measured at the main processing stages. Hot carcass weights showed a significant negative correlation with their lean meat percentage and LMPH, while LMPH was correlated positively with carcass lean meat, SALT1, SALT, and weight losses. The GWAS detected genome-wide association for 12 single nucleotide polymorphisms with Ferrochelatase activity. The results obtained in this preliminary study were achieved by combining innovative and non-destructive technologies for screening hams under processing, measures of enzymatic muscle properties relevant to dry-cured ham quality, and genomic information obtained through a GWAS. Additional studies carried out in a larger number of pigs have been planned to investigate the effect of gene variants of Ferrochelatase activity in the dry-cured ham's quality with main reference to colour development and to confirm the GWAS results obtained in this study.

CAS Array: design and assessment of a genotyping array for Chinese biobanking.

Chronic diseases are becoming a critical challenge to the aging Chinese population. Biobanks with extensive genomic and environmental data offer opportunities to elucidate the complex gene-environment interactions underlying their aetiology. Genome-wide genotyping array remains an efficient approach for large-scale genomic data collection. However, most commercial arrays have reduced performance for biobanking in the Chinese population. Deep whole-genome sequencing data from 2641 Chinese individuals were used as a reference to develop the CAS array, a custom-designed genotyping array for precision medicine. Evaluation of the array was performed by comparing data from 384 individuals assayed both by the array and whole-genome sequencing. Validation of its mitochondrial copy number estimating capacity was conducted by examining its association with established covariates among 10162 Chinese elderly. The CAS Array adopts the proven Axiom technology and is restricted to 652429 single-nucleotide polymorphism (SNP) markers. Its call rate of 99.79% and concordance rate of 99.89% are both higher than for commercial arrays. Its imputation-based genome coverage reached 98.3% for common SNPs and 63.0% for low-frequency SNPs, both comparable to commercial arrays with larger SNP capacity. After validating its mitochondrial copy number estimates, we developed a publicly available software tool to facilitate the array utility. Based on recent advances in genomic science, we designed and implemented a high-throughput and low-cost genotyping array. It is more cost-effective than commercial arrays for large-scale Chinese biobanking.

Novel Linkage Peaks Discovered for Diabetic Nephropathy in Individuals With Type 1 Diabetes.

Genome-wide association studies (GWAS) and linkage studies have had limited success in identifying genome-wide significantly linked regions or risk loci for diabetic nephropathy (DN) in individuals with type 1 diabetes (T1D). As GWAS cohorts have grown, they have also included more documented and undocumented familial relationships. Here we computationally inferred and manually curated pedigrees in a study cohort of >6,000 individuals with T1D and their relatives without diabetes. We performed a linkage study for 177 pedigrees consisting of 452 individuals with T1D and their relatives using a genome-wide genotyping array with >300,000 single nucleotide polymorphisms and PSEUDOMARKER software. Analysis resulted in genome-wide significant linkage peaks on eight chromosomal regions from five chromosomes (logarithm of odds score >3.3). The highest peak was localized at the HLA region on chromosome 6p, but whether the peak originated from T1D or DN remained ambiguous. Of other significant peaks, the chromosome 4p22 region was localized on top of ARHGAP24, a gene associated with focal segmental glomerulosclerosis, suggesting this gene may play a role in DN as well. Furthermore, rare variants have been associated with DN and chronic kidney disease near the 4q25 peak, localized on top of CCSER1.

Selection signatures in two oldest Russian native cattle breeds revealed using high-density single nucleotide polymorphism analysis.

Native cattle breeds can carry specific signatures of selection reflecting their adaptation to the local environmental conditions and response to the breeding strategy used. In this study, we comprehensively analysed high-density single nucleotide polymorphism (SNP) genotypes to characterise the population structure and detect the selection signatures in Russian native Yaroslavl and Kholmogor dairy cattle breeds, which have been little influenced by introgression with transboundary breeds. Fifty-six samples of pedigree-recorded purebred animals, originating from different breeding farms and representing different sire lines, of the two studied breeds were genotyped using a genome-wide bovine genotyping array (Bovine HD BeadChip). Three statistical analyses-calculation of fixation index (FST) for each SNP for the comparison of the pairs of breeds, hapFLK analysis, and estimation of the runs of homozygosity (ROH) islands shared in more than 50% of animals-were combined for detecting the selection signatures in the genome of the studied cattle breeds. We confirmed nine and six known regions under putative selection in the genomes of Yaroslavl and Kholmogor cattle, respectively; the flanking positions of most of these regions were elucidated. Only two of the selected regions (localised on BTA 14 at 24.4-25.1 Mbp and on BTA 16 at 42.5-43.5 Mb) overlapped in Yaroslavl, Kholmogor and Holstein breeds. In addition, we detected three novel selection sweeps in the genome of Yaroslavl (BTA 4 at 4.74-5.36 Mbp, BTA 15 at 17.80-18.77 Mbp, and BTA 17 at 45.59-45.61 Mbp) and Kholmogor breeds (BTA 12 at 82.40-81.69 Mbp, BTA 15 at 16.04-16.62 Mbp, and BTA 18 at 0.19-1.46 Mbp) by using at least two of the above-mentioned methods. We expanded the list of candidate genes associated with the selected genomic regions and performed their functional annotation. We discussed the possible involvement of the identified candidate genes in artificial selection in connection with the origin and development of the breeds. Our findings on the Yaroslavl and Kholmogor breeds obtained using high-density SNP genotyping and three different statistical methods allowed the detection of novel putative genomic regions and candidate genes that might be under selection. These results might be useful for the sustainable development and conservation of these two oldest Russian native cattle breeds.

Longitudinal Measurements of Glucocerebrosidase activity in Parkinson's patients.

ObjectiveReduction in glucocerebrosidase (GCase; encoded by GBA) enzymatic activity has been linked to Parkinson’s disease (PD). Here, we correlated GCase activity and PD phenotype in the Parkinson’s Progression Markers Initiative (PPMI) cohort.MethodsWe measured GCase activity in dried blood spots from 1559 samples of participants in the inception PPMI cohort, collected in four annual visits (from baseline visit to Year‐3). Participants (PD, n = 392; controls, n = 175) were fully sequenced for GBA variants by means of genome‐wide genotyping arrays, whole‐exome sequencing, whole‐genome sequencing, Sanger sequencing, and RNA‐sequencing.ResultsFifty‐two PD participants (13.4%) and 13 (7.4%) controls carried a GBA variant. GBA status was strongly associated with GCase activity. Among noncarriers, GCase activity was similar between PD and controls. Among GBA p.E326K carriers (PD, n = 20; controls, n = 5), activity was significantly lower in PD carriers than control carriers (9.53 µmol/L/h vs. 11.68 µmol/L/h, P = 0.035). Glucocerebrosidase activity was moderately (r = 0.45) associated with white blood cell (WBC) count. Next, we divided the noncarriers with PD to tertiles based on WBC count‐corrected enzymatic activity. Members of the lower tertile had higher MDS‐Unified Parkinson’s Disease Rating Scale motor score in the “off” medication examination at year‐III exam. Longitudinal analyses demonstrated slight reduction of activity in samples collected earlier on in the study, likely because of longer storage time.InterpretationGCase activity is associated with GBA genotype, WBC count, and among p.E326K variant carriers, with PD status. Reduced activity may also be associated with worse phenotype but longer follow up is required to confirm this observation.

Genetic background of ataxia in children younger than 5 years in Finland.

ObjectiveTo characterize the genetic background of molecularly undefined childhood-onset ataxias in Finland.MethodsThis study examined a cohort of patients from 50 families with onset of an ataxia syndrome before the age of 5 years collected from a single tertiary center, drawing on the advantages offered by next generation sequencing. A genome-wide genotyping array (Illumina Infinium Global Screening Array MD-24 v.2.0) was used to search for copy number variation undetectable by exome sequencing.ResultsExome sequencing led to a molecular diagnosis for 20 probands (40%). In the 23 patients examined with a genome-wide genotyping array, 2 additional diagnoses were made. A considerable proportion of probands with a molecular diagnosis had de novo pathogenic variants (45%). In addition, the study identified a de novo variant in a gene not previously linked to ataxia: MED23. Patients in the cohort had medically actionable findings.ConclusionsThere is a high heterogeneity of causative mutations in this cohort despite the defined age at onset, phenotypical overlap between patients, the founder effect, and genetic isolation in the Finnish population. The findings reflect the heterogeneous genetic background of ataxia seen worldwide and the substantial contribution of de novo variants underlying childhood ataxia.

Use of >100,000 NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium whole genome sequences improves imputation quality and detection of rare variant associations in admixed African and Hispanic/Latino populations.

Most genome-wide association and fine-mapping studies to date have been conducted in individuals of European descent, and genetic studies of populations of Hispanic/Latino and African ancestry are limited. In addition, these populations have more complex linkage disequilibrium structure. In order to better define the genetic architecture of these understudied populations, we leveraged >100,000 phased sequences available from deep-coverage whole genome sequencing through the multi-ethnic NHLBI Trans-Omics for Precision Medicine (TOPMed) program to impute genotypes into admixed African and Hispanic/Latino samples with genome-wide genotyping array data. We demonstrated that using TOPMed sequencing data as the imputation reference panel improves genotype imputation quality in these populations, which subsequently enhanced gene-mapping power for complex traits. For rare variants with minor allele frequency (MAF) < 0.5%, we observed a 2.3- to 6.1-fold increase in the number of well-imputed variants, with 11–34% improvement in average imputation quality, compared to the state-of-the-art 1000 Genomes Project Phase 3 and Haplotype Reference Consortium reference panels. Impressively, even for extremely rare variants with minor allele count <10 (including singletons) in the imputation target samples, average information content rescued was >86%. Subsequent association analyses of TOPMed reference panel-imputed genotype data with hematological traits (hemoglobin (HGB), hematocrit (HCT), and white blood cell count (WBC)) in ~21,600 African-ancestry and ~21,700 Hispanic/Latino individuals identified associations with two rare variants in the HBB gene (rs33930165 with higher WBC [p = 8.8x10-15] in African populations, rs11549407 with lower HGB [p = 1.5x10-12] and HCT [p = 8.8x10-10] in Hispanics/Latinos). By comparison, neither variant would have been genome-wide significant if either 1000 Genomes Project Phase 3 or Haplotype Reference Consortium reference panels had been used for imputation. Our findings highlight the utility of the TOPMed imputation reference panel for identification of novel rare variant associations not previously detected in similarly sized genome-wide studies of under-represented African and Hispanic/Latino populations.

Low coverage whole genome sequencing enables accurate assessment of common variants and calculation of genome-wide polygenic scores

BackgroundInherited susceptibility to common, complex diseases may be caused by rare, pathogenic variants (“monogenic”) or by the cumulative effect of numerous common variants (“polygenic”). Comprehensive genome interpretation should enable assessment for both monogenic and polygenic components of inherited risk. The traditional approach requires two distinct genetic testing technologies—high coverage sequencing of known genes to detect monogenic variants and a genome-wide genotyping array followed by imputation to calculate genome-wide polygenic scores (GPSs). We assessed the feasibility and accuracy of using low coverage whole genome sequencing (lcWGS) as an alternative to genotyping arrays to calculate GPSs.MethodsFirst, we performed downsampling and imputation of WGS data from ten individuals to assess concordance with known genotypes. Second, we assessed the correlation between GPSs for 3 common diseases—coronary artery disease (CAD), breast cancer (BC), and atrial fibrillation (AF)—calculated using lcWGS and genotyping array in 184 samples. Third, we assessed concordance of lcWGS-based genotype calls and GPS calculation in 120 individuals with known genotypes, selected to reflect diverse ancestral backgrounds. Fourth, we assessed the relationship between GPSs calculated using lcWGS and disease phenotypes in a cohort of 11,502 individuals of European ancestry.ResultsWe found imputation accuracy r2 values of greater than 0.90 for all ten samples—including those of African and Ashkenazi Jewish ancestry—with lcWGS data at 0.5×. GPSs calculated using lcWGS and genotyping array followed by imputation in 184 individuals were highly correlated for each of the 3 common diseases (r2 = 0.93–0.97) with similar score distributions. Using lcWGS data from 120 individuals of diverse ancestral backgrounds, we found similar results with respect to imputation accuracy and GPS correlations. Finally, we calculated GPSs for CAD, BC, and AF using lcWGS in 11,502 individuals of European ancestry, confirming odds ratios per standard deviation increment ranging 1.28 to 1.59, consistent with previous studies.ConclusionslcWGS is an alternative technology to genotyping arrays for common genetic variant assessment and GPS calculation. lcWGS provides comparable imputation accuracy while also overcoming the ascertainment bias inherent to variant selection in genotyping array design.

60 Re-ranking of estimated breeding values using different panel densities with ssGBLUP in broiler chickens

Abstract The aim of this study was to compare the rank of estimated breeding values (EBV) for organs (heart, liver, lungs and gizzard) and carcass (breast, thigh and drumstick) traits using pedigree-based BLUP (PBLUP) and single-step genomic BLUP (ssGBLUP) models. A total of 1,453 chickens (703 males and 750 females) from a paternal broiler (TT) reference population belonging to the Poultry Breeding Program from Embrapa Swine and Poultry were genotyped with the Axiom® Genome-Wide Chicken Genotyping Array (Affymetrix) 600K SNP panel. Samples with a call rate lower than 90% were removed. A SNP quality control was applied for removing SNP with call rate lower than 98%, MAF lower than 2% and significant deviations from HWE (p-value &lt; 10–7) leaving 370,608 SNP for further analysis. Estimated breeding values were predicted using the blupf90 family of programs whereby a series of bi-variate animal models that included sex and hatching as fixed effects were fitted. Heritability estimates for carcass and organ traits obtained through PBLUP varied from low (0.16) for lungs to moderate (0.34 to 0.47) for heart, liver, gizzard, breast, thigh and drumstick. The genomic heritability estimates through ssGBLUP varied from low (0.14) for lungs to moderate (0.30 to .041) for all other traits. Five subsets (5, 10, 20, 40 and 80% of SNP) were randomly selected from the full SNP set to determine the impact, in terms of EBV rank, of using reduced subsets of SNP to inform relationships among individuals. Although the 5% subset of SNP consistently had the lowest correlation with the full set of SNP, all correlations were greater than 0.995. Results suggest that a relatively limited proportion of SNP could be used to reliably predict EBV via ssGBLUP in this population.

OPTIMIR, a novel algorithm for integrating available genome-wide genotype data into miRNA sequence alignment analysis.

Next-generation sequencing is an increasingly popular and efficient approach to characterize the full set of microRNAs (miRNAs) present in human biosamples. MiRNAs’ detection and quantification still remain a challenge as they can undergo different posttranscriptional modifications and might harbor genetic variations (polymiRs) that may impact on the alignment step. We present a novel algorithm, OPTIMIR, that incorporates biological knowledge on miRNA editing and genome-wide genotype data available in the processed samples to improve alignment accuracy. OPTIMIR was applied to 391 human plasma samples that had been typed with genome-wide genotyping arrays. OPTIMIR was able to detect genotyping errors, suggested the existence of novel miRNAs and highlighted the allelic imbalance expression of polymiRs in heterozygous carriers. OPTIMIR is written in python, and freely available on the GENMED website (http://www.genmed.fr/index.php/fr/) and on Github (github.com/FlorianThibord/OptimiR).

Genetic diversity and population structure of domestic and wild reindeer (Rangifer tarandus L. 1758): A novel approach using BovineHD BeadChip.

Reindeer (Rangifer tarandus L. 1758) are an essential element of the Russian Far North, providing a significant source of nutrition for the representatives of 18 ethnicities. The species has wild and domestic forms, which are in constant interaction. The aim of our study was to characterize the genetic structure of domestic and wild reindeer populations, using a genome-wide bovine genotyping array (BovineHD BeadChip). The wild reindeer samples were obtained from the western Taymyr Peninsula population and from the taiga and tundra populations in the Sakha Republic (Yakutia). The domestic populations included the Evenk, Even, and Chukotka-Khargin breeds of Yakutia and the Nenets breed from the Nenets Autonomous district and Murmansk region. The level of genetic diversity was higher for the wild population. Analyzing Neighbor-Net tree, multidimensional scaling, and Structure results, we observed strong genetic population structure and clear differentiation between domestic and wild populations. All regional populations of domestic reindeer were clearly separated, while wild reindeer showed similar genetic backgrounds. Nevertheless, we found contrasting patterns in the genetic structure of the tundra and taiga reindeer, in accordance with their morphological and ecological differences. Thus, our study revealed a clear genetic differentiation between domestic and wild reindeer populations. It provides novel insights into the genetic diversity and structure of reindeer populations, to support resource utilization and aid in the development of genetic improvement strategies and conservation programs for this species.

Pharmacogenetic Content of Commercial Genome-Wide Genotyping Arrays

We have evaluated the pharmacogenetic content of commercial human genome-wide genotyping arrays, as it is a critical determinant to enabling pharmacogenomic discoveries. Using bioinformatics approaches, we assessed 27,811 genetic variants in 3146 genes for their presence in 18 Illumina and 15 Affymetrix genome-wide arrays. The pharmacogenetic content of the arrays varied greatly. The combination of the Affymetrix precision medicine array and PharmacoScan arrays (Affymetrix) had the highest coverage for a set of clinically actionable absorption, distribution, metabolism and excretion (ADME) variants, single nucleotide ADME variants and ADME insertions/deletions, with a physical coverage of 125/130 (96.2%), 9924/24,138 (41.1%) and 2252/3994 (56.4%), respectively. The combination of the Affymetrix precision medicine array and PharmacoScan arrays provided both genome-wide and pharmacogene coverage, which is crucial in the discovering of new variants responsible for drug adverse effects. These results will help in the design of pharmacogenomic studies and will enable a critical review of results from past studies.

Variants in immune-related genes and genital HPV 16 persistence in men

ObjectivesWhile most human papillomavirus (HPV) infection clears on its own, persistent HPV infection can cause genital warts and anal, penile and oropharyngeal cancers in men. We conducted genetic analysis in a sub-cohort of the HPV infection in men (HIM) study to test the hypothesis that differences in host genes influence HPV persistence in men. MethodsBaseline and longitudinal genital HPV status at the genitals was measured every 6-months using the Linear Array assay amplified HPV L1 gene fragment using the PGMY09/11 L1 consensus primer system. DNA was extracted from peripheral blood and single nucleotide polymorphisms (SNPs) in the customized genome-wide genotyping array, the “TxArray,” were examined using logistic regression in a case-control study design to assess the association with HPV16 persistence/clearance. ResultsOf the total of 737,742 autosomal SNPs in the array, 605,885 passed basic quality control and were examined between 40 men (cases) with > 18 months persistent genital HPV 16 infection vs. 151 controls who were HPV 16-positive, but whose infections cleared in < 18 months. The logistic regression analysis from this case-control study showed variants in several gene regions associated with genital HPV 16 persistence, with the strongest association detected with SNPs on chromosomes 20 (p < 5.72 × 10−6) and 15 (p < 5.89 × 10−6), after adjusting for age, smoking status, number of sex partners and four principal components (ancestral background). ConclusionsOur results provide a preliminary basis for understanding the biological mechanism of oncogenic HPV 16 pathogenesis at the genitals in men. Some of the genes flanking the top hit SNPs are consistent with previous findings in both HPV related and non-related cancers but further genetic studies in larger cohorts are warranted to confirm these and identify novel major susceptibility genes involved in the pathogenesis of genital HPV persistence in men.

Association analyses of more than 140,000 men identify 63 new prostate cancer susceptibility loci.

Genome-wide association studies (GWAS) and fine-mapping efforts to date have identified more than 100 prostate cancer (PrCa)-susceptibility loci. We meta-analyzed genotype data from a custom high-density array of 46,939 PrCa cases and 27,910 controls of European ancestry with previously genotyped data of 32,255 PrCa cases and 33,202 controls of European ancestry. Our analysis identified 62 novel loci associated (P < 5.0 × 10-8) with PrCa and one locus significantly associated with early-onset PrCa (≤55 years). Our findings include missense variants rs1800057 (odds ratio (OR) = 1.16; P = 8.2 × 10-9; G>C, p.Pro1054Arg) in ATM and rs2066827 (OR = 1.06; P = 2.3 × 10-9; T>G, p.Val109Gly) in CDKN1B. The combination of all loci captured 28.4% of the PrCa familial relative risk, and a polygenic risk score conferred an elevated PrCa risk for men in the ninetieth to ninety-ninth percentiles (relative risk = 2.69; 95% confidence interval (CI): 2.55-2.82) and first percentile (relative risk = 5.71; 95% CI: 5.04-6.48) risk stratum compared with the population average. These findings improve risk prediction, enhance fine-mapping, and provide insight into the underlying biology of PrCa1.

Interdisciplinary Models for Research and Clinical Endeavors in Genomic Medicine: A Scientific Statement From the American Heart Association.

The completion of the Human Genome Project has unleashed a wealth of human genomics information, but it remains unclear how best to implement this information for the benefit of patients. The standard approach of biomedical research, with researchers pursuing advances in knowledge in the laboratory and, separately, clinicians translating research findings into the clinic as much as decades later, will need to give way to new interdisciplinary models for research in genomic medicine. These models should include scientists and clinicians actively working as teams to study patients and populations recruited in clinical settings and communities to make genomics discoveries-through the combined efforts of data scientists, clinical researchers, epidemiologists, and basic scientists-and to rapidly apply these discoveries in the clinic for the prediction, prevention, diagnosis, prognosis, and treatment of cardiovascular diseases and stroke. The highly publicized US Precision Medicine Initiative, also known as All of Us, is a large-scale program funded by the US National Institutes of Health that will energize these efforts, but several ongoing studies such as the UK Biobank Initiative; the Million Veteran Program; the Electronic Medical Records and Genomics Network; the Kaiser Permanente Research Program on Genes, Environment and Health; and the DiscovEHR collaboration are already providing exemplary models of this kind of interdisciplinary work. In this statement, we outline the opportunities and challenges in broadly implementing new interdisciplinary models in academic medical centers and community settings and bringing the promise of genomics to fruition.