Imputed Single Nucleotide Polymorphisms Research Articles

Genome-Wide Association Study with Three Control Cohorts of Japanese Patients with Esotropia and Exotropia of Comitant Strabismus and Idiopathic Superior Oblique Muscle Palsy.

Esotropia and exotropia in the entity of comitant strabismus are multifactorial diseases with both genetic and environmental backgrounds. Idiopathic superior oblique muscle palsy, as the predominant entity of non-comitant (paralytic) strabismus, also has a genetic background, as evidenced by varying degrees of muscle hypoplasia. A genome-wide association study (GWAS) was conducted of 711 Japanese patients with esotropia (n= 253), exotropia (n = 356), and idiopathic superior oblique muscle palsy (n = 102). The genotypes of single nucleotide polymorphisms (SNPs) were determined by Infinium Asian Screening Array. Three control cohorts from the Japanese population were used: two cohorts from BioBank Japan (BBJ) and the Nagahama Cohort. BBJ (180K) was genotyped by a different array, Illumina Infinium OmniExpressExome or HumanOmniExpress, while BBJ (ASA) and the Nagahama Cohort were genotyped by the same Asian array. After quality control of SNPs and individuals, common SNPs between the case cohort and the control cohort were chosen in the condition of genotyping by different arrays, while all SNPs genotyped by the same array were used for SNP imputation. The SNPs imputed with R-square values ≥ 0.3 were used to compare the case cohort of each entity or the combined entity with the control cohort. In comparison with BBJ (180K), the esotropia group and the exotropia group showed CDCA7 and HLA-F, respectively, as candidate genes at a significant level of p < 5 × 10-8, while the idiopathic superior oblique muscle palsy group showed DAB1 as a candidate gene which is involved in neuronal migration. DAB1 was also detected as a candidate in comparison with BBJ (ASA) and the Nagahama Cohort at a weak level of significance of p < 1 × 10-6. In comparison with BBJ (180K), RARB (retinoic acid receptor-β) was detected as a candidate at a significant level of p < 5 × 10-8 in the combined group of esotropia, exotropia, and idiopathic superior oblique muscle palsy. In conclusion, a series of GWASs with three different control cohorts would be an effective method with which to search for candidate genes for multifactorial diseases such as strabismus.

Assessing and mitigating privacy risks of sparse, noisy genotypes by local alignment to haplotype databases.

Single nucleotide polymorphisms (SNPs) from omics data create a reidentification risk for individuals and their relatives. Although the ability of thousands of SNPs (especially rare ones) to identify individuals has been repeatedly shown, the availability of small sets of noisy genotypes, from environmental DNA samples or functional genomics data, motivated us to quantify their informativeness. We present a computational tool suite, termed Privacy Leakage by Inference across Genotypic HMM Trajectories (PLIGHT), using population-genetics-based hidden Markov models (HMMs) of recombination and mutation to find piecewise alignment of small, noisy SNP sets to reference haplotype databases. We explore cases in which query individuals are either known to be in the database, or not, and consider several genotype queries, including those from environmental sample swabs from known individuals and from simulated "mosaics" (two-individual composites). Using PLIGHT on a database with ∼5000 haplotypes, we find for common, noise-free SNPs that only ten are sufficient to identify individuals, ∼20 can identify both components in two-individual mosaics, and 20-30 can identify first-order relatives. Using noisy environmental-sample-derived SNPs, PLIGHT identifies individuals in a database using ∼30 SNPs. Even when the individuals are not in the database, local genotype matches allow for some phenotypic information leakage based on coarse-grained SNP imputation. Finally, by quantifying privacy leakage from sparse SNP sets, PLIGHT helps determine the value of selectively sanitizing released SNPs without explicit assumptions about population membership or allele frequency. To make this practical, we provide a sanitization tool to remove the most identifying SNPs from genomic data.

Genomic prediction and genome-wide association studies for additive and dominance effects for body composition traits using 50 K and imputed high-density SNP genotypes in Yunong-black pigs.

Body composition traits are complex traits controlled by minor genes and, in hybrid populations, are impacted by additive and nonadditive effects. We aimed to identify candidate genes and increase the accuracy of genomic prediction of body composition traits in crossbred pigs by including dominance genetic effects. Genomic selection (GS) and genome-wide association studies were performed on seven body composition traits in 807 Yunong-black pigs using additive genomic models (AM) and additive-dominance genomic models (ADM) with an imputed high-density single nucleotide polymorphism (SNP) array and the Illumina Porcine SNP50 BeadChip. The results revealed that the additive heritabilities estimated for AM and ADM using the 50 K SNP data ranged from 0.20 to 0.34 and 0.11 to 0.30, respectively. However, the ranges of additive heritability for AM and ADM in the imputed data ranged from 0.20 to 0.36 and 0.12 to 0.30, respectively. The dominance variance accounted for 23% and 27% of the total variance for the 50 K and imputed data, respectively. The accuracy of genomic prediction improved by 5% on average for 50 K and imputed data when dominance effect were considered. Without the dominance effect, the accuracies for 50 K and imputed data were 0.35 and 0.38, respectively, and 0.41 and 0.43, respectively, upon considering it. A total of 12 significant SNP and 16 genomic regions were identified in the AM, and 14 significant SNP and 21 genomic regions were identified in the ADM for both the 50 K and imputed data. There were five overlapping SNP in the 50 K and imputed data. In the AM, a significant SNP (CNC10041568) was found in both body length and backfat thickness traits, which was in the PLAG1 gene strongly and significantly associated with body length and backfat thickness in pigs. Moreover, a significant SNP (CNC10031356) with a heterozygous dominant genotype was present in the ADM. Furthermore, several functionally related genes were associated with body composition traits, including MOS, RPS20, LYN, TGS1, TMEM68, XKR4, SEMA4D and ARNT2. These findings provide insights into molecular markers and GS breeding for the Yunong-black pigs.

Association of PDGFRA polymorphisms with the risk of corneal astigmatism in a Japanese population

Corneal astigmatism is reportedly associated with polymorphisms of the platelet-derived growth factor receptor alpha (PDGFRA) gene region in Asian populations of Chinese, Malay, and Indian ancestry and populations of European ancestry. In this study, we investigated whether these PDGFRA polymorphisms are associated with corneal astigmatism in a Japanese population. We recruited 1,535 cases with corneal astigmatism (mean corneal cylinder power across both eyes: ≤ − 0.75 diopters [D]) and 842 controls (> − 0.75 D) to genotype 13 single-nucleotide polymorphisms (SNPs) in the PDGFRA gene region. We also performed imputation analysis in the region, with 179 imputed SNPs included in the statistical analyses. The PDGFRA SNPs were not significantly associated with the cases with corneal astigmatism ≤ − 0.75 D. However, the odds ratios (ORs) of the minor alleles of SNPs in the upstream region of PDGFRA, including rs7673984, rs4864857, and rs11133315, tended to increase according to the degree of corneal astigmatism, and these SNPs were significantly associated with the cases with corneal astigmatism ≤ − 1.25 D or ≤ − 1.50 D (Pc < 0.05, OR = 1.34–1.39). These results suggest that PDGFRA SNPs play a potential role in the development of greater corneal astigmatism.

Genetic variants associated with spontaneous preterm birth in women from India: a prospective cohort study.

Despite having the highest number of preterm births globally, no genomic study on preterm birth was previously published from India or other South-Asian countries. We conducted a genome-wide association (GWA) study of spontaneous preterm birth (sPTB) on 6211 women from India. We used a novel resampling procedure to identify the associated single nucleotide polymorphisms (SNPs) followed by haplotype association analysis and imputation. We found that 512 maternal SNPs were associated with sPTB (p<2.51e-3), of which minor allele at 19 SNPs (after Bonferroni correction) had increased genotype relative risk. Haplotypes containing six of the 19 SNPs (rs13011430, rs8179838, rs2327290, rs4798499, rs7629800, and rs13180906) were associated with sPTB (p<9.9e-4; Bonferroni adjusted p-value <0.05). After imputation in regions around the 19 SNPs, 15 imputed SNPs were found to be associated with sPTB (Bonferroni adjusted p-value <0.05). One of these imputed SNPs, rs35760881, and three other SNPs (rs17307697, rs4308815, and rs10983507) were also reported to be associated with sPTB in women belonging to European ancestry. Moreover, we found that GG genotype at rs1152954, one of the associated SNPs, enhanced risk of sPTB and reduced telomere length. This is the first study from South Asia on the genome-wide identification of maternal SNPs associated with sPTB. These SNPs are known to alter the expression of genes associated with major pathways in sPTB viz. inflammation, apoptosis, cervical ripening, telomere maintenance, selenocysteine biosynthesis, myometrial contraction, and innate immunity. From a public health perspective, the trans-ethnic association of four SNPs identified in our study may help to stratify women with risk of sPTB in most populations. Department of Biotechnology (India), Grand Challenges India - All Children Thriving Program and Biotechnology Industry Research Assistance Council (BIRAC).

Whole‐genome sequencing identifies interferon-induced protein IFI6/IFI27-like as a strong candidate gene for VNN resistance in European sea bass

BackgroundViral nervous necrosis (VNN) is a major disease that affects European sea bass, and understanding the biological mechanisms that underlie VNN resistance is important for the welfare of farmed fish and sustainability of production systems. The aim of this study was to identify genomic regions and genes that are associated with VNN resistance in sea bass.ResultsWe generated a dataset of 838,451 single nucleotide polymorphisms (SNPs) identified from whole-genome sequencing (WGS) in the parental generation of two commercial populations (A: 2371 individuals and B: 3428 individuals) of European sea bass with phenotypic records for binary survival in a VNN challenge. For each population, three cohorts were submitted to a red-spotted grouper nervous necrosis virus (RGNNV) challenge by immersion and genotyped on a 57K SNP chip. After imputation of WGS SNPs from their parents, quantitative trait loci (QTL) were mapped using a Bayesian sparse linear mixed model (BSLMM). We found several QTL regions that were specific to one of the populations on different linkage groups (LG), and one 127-kb QTL region on LG12 that was shared by both populations and included the genes ZDHHC14, which encodes a palmitoyltransferase, and IFI6/IFI27-like, which encodes an interferon-alpha induced protein. The most significant SNP in this QTL region was only 1.9 kb downstream of the coding sequence of the IFI6/IFI27-like gene. An unrelated population of four large families was used to validate the effect of the QTL. Survival rates of susceptible genotypes were 40.6% and 45.4% in populations A and B, respectively, while that of the resistant genotype was 66.2% in population B and 78% in population A.ConclusionsWe have identified a genomic region that carries a major QTL for resistance to VNN and includes the ZDHHC14 and IFI6/IFI27-like genes. The potential involvement of the interferon pathway, a well-known anti-viral defense mechanism in several organisms (chicken, human, or fish), in survival to VNN infection is of particular interest. Our results can lead to major improvements for sea bass breeding programs through marker-assisted genomic selection to obtain more resistant fish.

Genomic inbreeding coefficients using imputed genotypes: assessing differences among SNP panels in Holstein-Friesian dairy cows.

The objective of this study was to evaluate the effect of imputation of single nucleotide polymorphisms (SNP) on the estimation of genomic inbreeding coefficients. Imputed genotypes of 68,127 Italian Holstein dairy cows were analyzed. Cows were initially genotyped with two high density (HD) SNP panels, namely the Illumina Infinium BovineHD BeadChip (678 cows; 777,962 SNP) and the Genomic Profiler HD-150K (641 cows; 139,914 SNP), and four medium density (MD): GeneSeek Genomic Profiler 3 (10,679 cows; 26,151 SNP), GeneSeek Genomic Profiler 4 (33,394 cows; 30,113 SNP), GeneSeek MD (12,030 cows; 47,850 SNP) and the Labogena MD (10,705 cows; 41,911 SNP). After imputation, all cows had genomic information on 84,445 SNP. Seven genomic inbreeding estimators were tested: (i) four PLINK v1.9 estimators (F, Fhat1,2,3), (ii) two genomic relationship matrix (grm) estimators [VanRaden's 1st method, but with observed allele frequencies (Fgrm) and VanRaden's 3rd method that is allelic free and pedigree dependent (Fgrm2)], and (iii) a runs of homozygosity (roh) - based estimator (Froh). Genomic inbreeding coefficients of each SNP panel were compared with genomic inbreeding coefficients derived from the 84,445 imputation SNP. Coefficients of the HD SNP panels were consistent between genotyped-imputed SNP (Pearson correlations ~99%), while variability across SNP panels and estimators was observed in the MD SNP panels, with Labogena MD providing, on average, more consistent estimates. The robustness of Labogena MD, can be partly explained by the fact that 97.85% of the SNP of this panel is included in the 84,445 SNP selected by ANAFIBJ for routine genomic imputations, while this percentage for the other MD SNP panels varied between 55 and 60%. Runs of homozygosity was the most robust estimator. Genomic inbreeding estimates using imputation SNP are influenced by the SNP number of the SNP panel that are included in the imputed SNP, and performance of genomic inbreeding estimators depends on the imputation.

Abstract 5224: Genome-wide interaction study of smoking and bladder cancer risk: results from the COBLAnCE cohort

Abstract Introduction: Bladder Cancer (BC) is the 6th most common cancer and the 9th leading cause of cancer death among men worldwide. Tobacco smoking is the main risk factor for BC. Accumulating evidence has found that genetic variants are also associated with the risk of BC. More insights into the biological mechanism of the disease have been gained through candidate gene-environment interaction studies, with the most known examples of the interactions between cigarette smoking and NAT2 and GSTM1 gene variants. Our objective was to perform a genome-wide association case-only study using the French national prospective COBLAnCE cohort (COhort to study BLAdder CancEr), while focusing on three important smoking behavior characteristics. Materials and Methods: The COBLAnCE cohort comprises 1,800 BC patients included within 14 centers in France between 2012 and 2018. Peripheral blood samples and complete history of tobacco smoking were collected at enrollment and genotyping was performed using the Illumina Global Screening Array with a Multi-Disease drop-in panel. After the quality control and imputation, 9,719,614 Single Nucleotide Polymorphisms (SNPs) were investigated. Genotyping data of 1,674, 1,283 and 1,342 patients were analyzed for smoking status, average tobacco consumption and age at smoking initiation, respectively. Genome-wide association study (GWAS) was conducted using logistic (for smoking status) and linear (for age at smoking initiation and average tobacco consumption, both log-transformed) regression models with each of the imputed SNPs as the independent variable adjusting for gender, age and first ten genetic principal components. Results: For smoking status, none of the SNPs reached the GWAS significant threshold of 5e-08, but results are suggesting tentative loci at 1p31.3 (rs114073636: OR [95%CI] = 0.31 [0.20-0.47], p = 8.68e-08; rs116571608: OR = 0.31 [0.20-0.47], p = 8.87e-08) and 4q22.1 (rs542541627: OR = 1.69 [1.39-2.06], p = 1.81e-07; rs1533294: OR = 1.63 [1.34-1.98], p = 1.01e-06). Analyses of age at smoking initiation revealed three significant SNPs: rs531756449, rs77186197 and rs78947799 with positive interaction associations (β (SE) = 0.3 (0.05), p = 8.26e-09; β = 0.29 (0.05), p = 3.74e-09; β = 0.31 (0.06), p = 3.97e-08, respectively). Only one SNP at 11q24.1, reached the significant threshold for the average tobacco consumption analyses: rs2714069 (β = 0.63 (0.11), p = 1.35e-08). The locus 16p13.3 seems to have protective variants for the interaction with average tobacco consumption: rs113683380 (β = -0.66 (0.12), p = 6.44e-08) and rs113590624 (β = -0.64 (0.12), p = 2.74e-07). Conclusion: Our study suggests new candidate loci interacting with smoking behavior for the risk of BC. Based on a case-only approach, our results need to be validated in a case-control or cohort study. A large-scale meta-analysis GWAS would be needed to identify SNPs with small Minor Allele Frequencies. Citation Format: Maryam Karimi, Sebastian Mendez-Pineda, Hélène Blanché, Anne Boland, Jean-François Deleuze, Xiang-Yu Meng, Karine Groussard, Thierry Lebret, Julia Bonastre, Yves Allory, François Radvanyi, Simone Benhamou, Stefan Michiels. Genome-wide interaction study of smoking and bladder cancer risk: results from the COBLAnCE cohort. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5224.

Estimating inbreeding rate and effective population size in the Finnish Ayrshire population in the era of genomic selection.

Genomic selection has been applied in dairy cattle breeding over the last decade. Using genomic information may speed up genetic gain as breeding values can be predicted reasonably accurately directly after birth. However, genetic diversity may decrease if the inbreeding rate per generation increases and the effective population size decreases. Despite many positive qualities of the Finnish Ayrshire, for example, high average protein yield and fertility, over time the breed has lost its place as the most common dairy breed in Finland. Thus, maintaining the genetic variability of the breed is becoming more important. The aim of our research was to estimate the impact of genomic selection on inbreeding rate and effective population size using both pedigree and genomic data. The genomic data included 46,914 imputed single nucleotide polymorphism (SNP) variants from 75,038 individuals, and the pedigree data included 2,770,025 individuals. All animals in the data were born between 2000 and 2020. Genomic inbreeding coefficients were estimated as the proportion of SNPs in runs of homozygosity (ROH) out of the total number of SNPs. The inbreeding rate was estimated by regressing the mean genomic inbreeding coefficients on birth years. Effective population size was then estimated based on the inbreeding rate. Additionally, effective population size was estimated from the mean increase in individual inbreeding using pedigree data. Introduction of genomic selection was assumed to have taken place gradually; years 2012-2014 were treated as a transition period from the traditional phenotype-based breeding value estimation to genomic-based estimation. The median length of the identified homozygous segments was 5.5Mbp, and a slight increase in the proportion of segments over 10Mbp was observed after 2010. The inbreeding rate decreased from 2000 to 2011 and subsequently increased slightly. The pedigree- and genomic-based estimates of inbreeding rate were similar to each other. The estimates of effective population size based on the regression method were very sensitive to the number of years considered; thus, the estimates were not very reliable. The effective population size estimated from the mean increase in individual inbreeding reached its highest value of 160 in 2011 and decreased to 150 after that. In addition, the generation interval in the sire path has decreased from 5.5 years to 3.5 years after genomic selection was implemented. Based on our results, after the implementation of genomic selection, the proportion of long ROH stretches has increased, the generation interval in the sire path has decreased, the inbreeding rate has increased and the effective population size has decreased. However, the effective population size is still at a good level, allowing for an efficient selection scheme in the Finnish Ayrshire breed.

Genetic Regulation of SMC Gene Expression and Splicing Predict Causal CAD Genes.

Coronary artery disease (CAD) is the leading cause of death worldwide. Recent meta-analyses of genome-wide association studies have identified over 175 loci associated with CAD. The majority of these loci are in noncoding regions and are predicted to regulate gene expression. Given that vascular smooth muscle cells (SMCs) play critical roles in the development and progression of CAD, we aimed to identify the subset of the CAD loci associated with the regulation of transcription in distinct SMC phenotypes. We measured gene expression in SMCs isolated from the ascending aortas of 151 heart transplant donors of various genetic ancestries in quiescent or proliferative conditions and calculated the association of their expression and splicing with ~6.3 million imputed single-nucleotide polymorphism markers across the genome. We identified 4910 expression and 4412 splicing quantitative trait loci (sQTLs) representing regions of the genome associated with transcript abundance and splicing. A total of 3660 expression quantitative trait loci (eQTLs) had not been observed in the publicly available Genotype-Tissue Expression dataset. Further, 29 and 880 eQTLs were SMC-specific and sex-biased, respectively. We made these results available for public query on a user-friendly website. To identify the effector transcript(s) regulated by CAD loci, we used 4 distinct colocalization approaches. We identified 84 eQTL and 164 sQTL that colocalized with CAD loci, highlighting the importance of genetic regulation of mRNA splicing as a molecular mechanism for CAD genetic risk. Notably, 20% and 35% of the eQTLs were unique to quiescent or proliferative SMCs, respectively. One CAD locus colocalized with a sex-specific eQTL (TERF2IP), and another locus colocalized with SMC-specific eQTL (ALKBH8). The most significantly associated CAD locus, 9p21, was an sQTL for the long noncoding RNA CDKN2B-AS1, also known as ANRIL, in proliferative SMCs. Collectively, our results provide evidence for the molecular mechanisms of genetic susceptibility to CAD in distinct SMC phenotypes.

The effect of high-density genotypic data and different methods on joint genomic prediction: A case study in large white pigs.

Joint genomic prediction (GP) is an attractive method to improve the accuracy of GP by combining information from multiple populations. However, many factors can negatively influence the accuracy of joint GP, such as differences in linkage disequilibrium phasing between single nucleotide polymorphisms (SNPs) and causal variants, minor allele frequencies and causal variants' effect sizes across different populations. The objective of this study was to investigate whether the imputed high-density genotype data can improve the accuracy of joint GP using genomic best linear unbiased prediction (GBLUP), single-step GBLUP (ssGBLUP), multi-trait GBLUP (MT-GBLUP) and GBLUP based on genomic relationship matrix considering heterogenous minor allele frequencies across different populations (wGBLUP). Three traits, including days taken to reach slaughter weight, backfat thickness and loin muscle area, were measured on 67 276 Large White pigs from two different populations, for which 3334 were genotyped by SNP array. The results showed that a combined population could substantially improve the accuracy of GP compared with a single-population GP, especially for the population with a smaller size. The imputed SNP data had no effect for single population GP but helped to yield higher accuracy than the medium-density array data for joint GP. Of the four methods, ssGLBUP performed the best, but the advantage of ssGBLUP decreased as more individuals were genotyped. In some cases, MT-GBLUP and wGBLUP performed better than GBLUP. In conclusion, our results confirmed that joint GP could be beneficial from imputed high-density genotype data, and the wGBLUP and MT-GBLUP methods are promising for joint GP in pig breeding.

Replacement of microsatellite markers by imputed medium-density SNP arrays for parentage control in German warmblood horses

In horses, parentage control is currently performed based on an internationally standardized panel of 17 microsatellite (MS) markers comprising 12 mandatory and five optional markers. Unlike MS, single nucleotide polymorphism (SNP) profiles support a wider portfolio of genomic applications, including parentage control. A transition to SNP-based parentage control is favorable, but requires additional efforts for ensuring generation-overlapping availability of marker genotypes of the same type. To avoid double genotyping of either parents or offspring for changing to SNP technology and enable efficient transition, we tested whether MS genotypes used for parentage control could be reliably imputed from a medium-density SNP panel in German warmblood horses. Imputation accuracy was tested in a tenfold cross-validation with two approaches: within breed (option A) and across breeds (option B). Average imputation accuracies of 97.98% (A) and 96.17% (B) were achieved, respectively. Due to interbreed differences in genotyping rates, five MS markers of low genotyping rate (GTR; < 90%) could be imputed with higher accuracy within breed (98.18%) than across breeds (90.73%). MS markers with high GTR performed homogeneously well in option B (98.44%) and showed slightly lower accuracy in option A (97.90%). Among these markers, AHT5 proved to be problematic for imputation regardless of the approach, revealing accuracies of 86.40% (A) and 88.70% (B). Better results for MS markers with high GTR and savings in computational processing justified the choice of option B for routine implementation. To date, more than 9500 horses have undergone the new parentage control based on imputed MS genotypes.

Common Variants Near ZIC1 and ZIC4 in Autopsy-Confirmed Multiple System Atrophy.

Multiple System Atrophy is a rare neurodegenerative disease with alpha-synuclein aggregation in glial cytoplasmic inclusions and either predominant olivopontocerebellar atrophy or striatonigral degeneration, leading to dysautonomia, parkinsonism, and cerebellar ataxia. One prior genome-wide association study in mainly clinically diagnosed patients with Multiple System Atrophy failed to identify genetic variants predisposing for the disease. Since the clinical diagnosis of Multiple System Atrophy yields a high rate of misdiagnosis when compared to the neuropathological gold standard, we studied only autopsy-confirmed cases. We studied common genetic variations in Multiple System Atrophy cases (N=731) and controls (N=2898). The most strongly disease-associated markers were rs16859966 on chromosome 3, rs7013955 on chromosome 8, and rs116607983 on chromosome 4 with P-values below 5 × 10-6 , all of which were supported by at least one additional genotyped and several imputed single nucleotide polymorphisms. The genes closest to the chromosome 3 locus are ZIC1 and ZIC4 encoding the zinc finger proteins of cerebellum 1 and 4 (ZIC1 and ZIC4). Since mutations of ZIC1 and ZIC4 and paraneoplastic autoantibodies directed against ZIC4 are associated with severe cerebellar dysfunction, we conducted immunohistochemical analyses in brain tissue of the frontal cortex and the cerebellum from 24 Multiple System Atrophy patients. Strong immunohistochemical expression of ZIC4 was detected in a subset of neurons of the dentate nucleus in all healthy controls and in patients with striatonigral degeneration, whereas ZIC4-immunoreactive neurons were significantly reduced inpatients with olivopontocerebellar atrophy. These findings point to a potential ZIC4-mediated vulnerability of neurons in Multiple System Atrophy. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

The KL genetic polymorphisms Associated with type 2 diabetes Mellitus.

Growing number of research studies have shown that an anti-ageing gene Klotho (KL) is closely associated with Type 2 Diabetes Mellitus (T2DM). In this study, the association is genetically analyzed with single nucleotide polymorphism (SNP) of KL found in T2DM case of an Asian cohort. KL SNP information was obtained from a big database of the Korean Association Resource (KARE) from which 20 KL SNPs were available. Statistical analyses were conducted based on the 3 genetic models, such as additive, dominant, and recessive. Of the 20 KL SNPs, 12 SNPs were found to be significantly associated with T2DM in both of additive and dominant models. Odds ratios of the KL SNPs indicate increased susceptibility to T2DM in additive and dominant models. Significant association of KL with T2DM was further analyzed using imputed KL SNPs from HapMap reference data of the Eastern population. The statistically significant KL SNPs including the imputed SNPs distributed evenly over the KL gene area. The results in this study suggest klotho is a major player in the development of T2DM and the KL SNPs found in the case could be a risk marker of T2DM in the cohort.

Genome-wide association and genotype by environment interactions for growth traits in U.S. Red Angus cattle

BackgroundGenotypic information produced from single nucleotide polymorphism (SNP) arrays has routinely been used to identify genomic regions associated with complex traits in beef and dairy cattle. Herein, we assembled a dataset consisting of 15,815 Red Angus beef cattle distributed across the continental U.S. and a union set of 836,118 imputed SNPs to conduct genome-wide association analyses (GWAA) for growth traits using univariate linear mixed models (LMM); including birth weight, weaning weight, and yearling weight. Genomic relationship matrix heritability estimates were produced for all growth traits, and genotype-by-environment (GxE) interactions were investigated.ResultsModerate to high heritabilities with small standard errors were estimated for birth weight (0.51 ± 0.01), weaning weight (0.25 ± 0.01), and yearling weight (0.42 ± 0.01). GWAA revealed 12 pleiotropic QTL (BTA6, BTA14, BTA20) influencing Red Angus birth weight, weaning weight, and yearling weight which met a nominal significance threshold (P ≤ 1e-05) for polygenic traits using 836K imputed SNPs. Moreover, positional candidate genes associated with Red Angus growth traits in this study (i.e., LCORL, LOC782905, NCAPG, HERC6, FAM184B, SLIT2, MMRN1, KCNIP4, CCSER1, GRID2, ARRDC3, PLAG1, IMPAD1, NSMAF, PENK, LOC112449660, MOS, SH3PXD2B, STC2, CPEB4) were also previously associated with feed efficiency, growth, and carcass traits in beef cattle. Collectively, 14 significant GxE interactions were also detected, but were less consistent among the investigated traits at a nominal significance threshold (P ≤ 1e-05); with one pleiotropic GxE interaction detected on BTA28 (24 Mb) for Red Angus weaning weight and yearling weight.ConclusionsSixteen well-supported QTL regions detected from the GWAA and GxE GWAA for growth traits (birth weight, weaning weight, yearling weight) in U.S. Red Angus cattle were found to be pleiotropic. Twelve of these pleiotropic QTL were also identified in previous studies focusing on feed efficiency and growth traits in multiple beef breeds and/or their composites. In agreement with other beef cattle GxE studies our results implicate the role of vasodilation, metabolism, and the nervous system in the genetic sensitivity to environmental stress.

LmTag: functional-enrichment and imputation-aware tag SNP selection for population-specific genotyping arrays.

Despite the rapid development of sequencing technology, single-nucleotide polymorphism (SNP) arrays are still the most cost-effective genotyping solutions for large-scale genomic research and applications. Recent years have witnessed the rapid development of numerous genotyping platforms of different sizes and designs, but population-specific platforms are still lacking, especially for those in developing countries. SNP arrays designed for these countries should be cost-effective (small size), yet incorporate key information needed to associate genotypes with traits. A key design principle for most current platforms is to improve genome-wide imputation so that more SNPs not included in the array (imputed SNPs) can be predicted. However, current tag SNP selection methods mostly focus on imputation accuracy and coverage, but not the functional content of the array. It is those functional SNPs that are most likely associated with traits. Here, we propose LmTag, a novel method for tag SNP selection that not only improves imputation performance but also prioritizes highly functional SNP markers. We apply LmTag on a wide range of populations using both public and in-house whole-genome sequencing databases. Our results show that LmTag improved both functional marker prioritization and genome-wide imputation accuracy compared to existing methods. This novel approach could contribute to the next generation genotyping arrays that provide excellent imputation capability as well as facilitate array-based functional genetic studies. Such arrays are particularly suitable for under-represented populations in developing countries or non-model species, where little genomics data are available while investment in genome sequencing or high-density SNP arrays is limited. $\textrm{LmTag}$ is available at: https://github.com/datngu/LmTag.

Genetic Architecture of Untargeted Lipidomics in Cardiometabolic-Disease Patients Combines Strong Polygenic Control and Pleiotropy.

Analysis of the genetic control of small metabolites provides powerful information on the regulation of the endpoints of genome expression. We carried out untargeted liquid chromatography–high-resolution mass spectrometry in 273 individuals characterized for pathophysiological elements of the cardiometabolic syndrome. We quantified 3013 serum lipidomic features, which we used in both genome-wide association studies (GWAS), using a panel of over 2.5 M imputed single-nucleotide polymorphisms (SNPs), and metabolome-wide association studies (MWAS) with phenotypes. Genetic analyses showed that 926 SNPs at 551 genetic loci significantly (q-value < 10−8) regulate the abundance of 74 lipidomic features in the group, with evidence of monogenic control for only 22 of these. In addition to this strong polygenic control of serum lipids, our results underscore instances of pleiotropy, when a single genetic locus controls the abundance of several distinct lipid features. Using the LIPID MAPS database, we assigned putative lipids, predominantly fatty acyls and sterol lipids, to 77% of the lipidome signals mapped to the genome. We identified significant correlations between lipids and clinical and biochemical phenotypes. These results demonstrate the power of untargeted lipidomic profiling for high-density quantitative molecular phenotyping in human-genetic studies and illustrate the complex genetic control of lipid metabolism.

Genetic Variants Associated with Neuropeptide Y Autoantibody Levels in Newly Diagnosed Individuals with Type 1 Diabetes.

(1) Autoantibodies to the leucine variant of neuropeptide Y (NPY-LA) have been found in individuals with type 1 diabetes (T1D). We investigated the association between the levels of NPY-LA and single nucleotide polymorphisms (SNP) to better understand the genetic regulatory mechanisms of autoimmunity in T1D and the functional impacts of increased NPY-LA levels. (2) NPY-LA measurements from serum and SNP genotyping were done on 560 newly diagnosed individuals with T1D. SNP imputation with the 1000 Genomes reference panel was followed by an association analysis between the SNPs and measured NPY-LA levels. Additionally, functional enrichment and pathway analyses were done. (3) Three loci (DGKH, DCAF5, and LINC02261) were associated with NPY-LA levels (p-value < 1.5 × 10−6), which indicates an association with neurologic and vascular disorders. SNPs associated with variations in expression levels were found in six genes (including DCAF5). The pathway analysis showed that NPY-LA was associated with changes in gene transcription, protein modification, immunological functions, and the MAPK pathway. (4) Conclusively, we found NPY-LA to be significantly associated with three loci (DGKH, DCAF5, and LINC02261), and based on our findings we hypothesize that the presence of NPY-LA is associated with the regulation of the immune system and possibly neurologic and vascular disorders.

Identification of Candidate Genes Regulating Carcass Depth and Hind Leg Circumference in Simmental Beef Cattle Using Illumina Bovine Beadchip and Next-Generation Sequencing Analyses.

Simple SummaryThe performance of genome-wide association studies with high-density single-nucleotide polymorphism panels and next-generation sequencing is a robust approach to the identification of genetic variants that can elucidate variation in complex diseases and economically important traits in farm animals. We identified many markers associated with crucial traits, such as muscle development in Simmental beef cattle. This information can be used to pinpoint candidate genes affecting traits of interest. Our results contribute to the clarification of molecular mechanisms underlying processes associated with hind-leg meat yield and carcass depth in beef cattle.Genome-wide association studies are a robust means of identifying candidate genes that regulate economically important traits in farm animals. The aim of this study is to identify single-nucleotide polymorphisms (SNPs) and candidate genes potentially related to carcass depth and hind leg circumference in Simmental beef cattle. We performed Illumina Bovine HD Beadchip (~670 k SNPs) and next-generation sequencing (~12 million imputed SNPs) analyses of data from 1252 beef cattle, to which we applied a linear mixed model. Using a statistical threshold (p = 0.05/number of SNPs identified) and adopting a false discovery rate (FDR), we identified many putative SNPs on different bovine chromosomes. We identified 12 candidate genes potentially annotated with the markers identified, including CDKAL1 and E2F3, related to myogenesis and skeletal muscle development. The identification of such genes in Simmental beef cattle will help breeders to understand and improve related traits, such as meat yield.

Genome-Wide Association Study Adjusted for Occupational and Environmental Factors for Bladder Cancer Susceptibility

This study examined the effects of single-nucleotide polymorphisms (SNPs) on the development of bladder cancer, adding longest-held occupational and industrial history as regulators. The genome purified from blood was genotyped, followed by SNP imputation. In the genome-wide association study (GWAS), several patterns of industrial/occupational classifications were added to logistic regression models. The association test between bladder cancer development and the calculated genetic score for each gene region was evaluated (gene-wise analysis). In the GWAS and gene-wise analysis, the gliomedin gene satisfied both suggestive association levels of 10−5 in the GWAS and 10−4 in the gene-wise analysis for male bladder cancer. The expression of the gliomedin protein in the nucleus of bladder cancer cells decreased in cancers with a tendency to infiltrate and those with strong cell atypia. It is hypothesized that gliomedin is involved in the development of bladder cancer.