Genome-wide association study of fiber quality traits in US upland cotton (Gossypium hirsutum L.).

KEY MESSAGE: A GWAS in an elite diversity panel, evaluated across 10 environments, identified genomic regions regulating six fiber quality traits, facilitating genomics-assisted breeding and gene discovery in upland cotton. In this study, an elite diversity panel of 348 upland cotton accessions was evaluated in 10 environments across the US Cotton Belt and genotyped with the cottonSNP63K array, for a genome-wide association study of six fiber quality traits. All fiber quality traits, upper half mean length (UHML: mm), fiber strength (FS: g tex-1), fiber uniformity (FU: %), fiber elongation (FE: %), micronaire (MIC) and short fiber content (SFC: %), showed high broad-sense heritability (> 60%). All traits except FE showed high genomic heritability. UHML, FS and FU were all positively correlated with each other and negatively correlated with FE, MIC and SFC. GWAS of these six traits identified 380 significant marker-trait associations (MTAs) including 143 MTAs on 30 genomic regions. These 30 genomic regions included MTAs identified in at least three environments, and 23 of them were novel associations. Phenotypic variation explained for the MTAs in these 30 genomic regions ranged from 6.68 to 11.42%. Most of the fiber quality-associated genomic regions were mapped in the D-subgenome. Further, this study confirmed the pleiotropic region on chromosome D11 (UHML, FS and FU) and identified novel co-localized regions on D04 (FU, SFC), D05 (UHML, FU, and D06 UHML, FU). Marker haplotype analysis identified superior combinations of fiber quality-associated genomic regions with high trait values (UHML = 32.34 mm; FS = 32.73 g tex-1; FE = 6.75%). Genomic analyses of traits, haplotype combinations and candidate gene information described in the current study could help leverage genetic diversity for targeted genetic improvement and gene discovery for fiber quality traits in cotton.

Shared genetic architecture between gastro-esophageal reflux disease, asthma, and allergic diseases.

The aim is to investigate the evidence for shared genetic architecture between each of asthma, allergic rhinitis and eczema with gastro-esophageal reflux disease (GERD). Structural equation models (SEM) and polygenic risk score (PRS) analyses are applied to three Swedish twin cohorts (n = 46,582) and reveal a modest genetic correlation between GERD and asthma of 0.18 and bidirectional PRS and phenotypic associations ranging between OR 1.09-1.14 and no correlations for eczema and allergic rhinitis. Linkage disequilibrium score regression is applied to summary statistics of recently published GERD and asthma/allergic disease genome wide association studies and reveals a genetic correlation of 0.48 for asthma and GERD, and Genomic SEM supports a single latent factor. A gene-/gene-set analysis using MAGMA reveals six pleiotropic genes (two at 12q13.2) associated with asthma and GERD. This study provides evidence that there is a common genetic architecture unique to asthma and GERD that may explain comorbidity and requires further investigation.

Genetic interactions and pleiotropy in metabolic diseases: Insights from a comprehensive GWAS analysis.

This study offers insights into the genetic and biological connections between nine common metabolic diseases using data from genome-wide association studies. Our goal is to unravel the genetic interactions and biological pathways of these complex diseases, enhancing our understanding of their genetic architecture. We employed a range of advanced analytical techniques to explore the genetic correlations and shared genetic variants of these diseases. These methods include Linked Disequilibrium Score Regression, High-Definition Likelihood (HDL), genetic analysis combining multiplicity and annotation (GPA), two-sample Mendelian randomization analyses, analysis under the multiplicity-complex null hypothesis (PLACO), and Functional mapping and annotation of genetic associations (FUMA). Additionally, Bayesian co-localization analyses were used to examine associations of specific loci across traits. Our study discovered significant genomic correlations and shared loci, indicating complex genetic interactions among these metabolic diseases. We found several shared single nucleotide variants and risk loci, notably highlighting the role of the immune system and endocrine pathways in these diseases. Particularly, rs2476601 and its associated gene PTPN22 appear to play a crucial role in the connection between type 2 diabetes mellitus, hypothyroidism/mucous oedema and hypoglycaemia. These findings enhance our understanding of the genetic underpinnings of these diseases and open new potential avenues for targeted therapeutic and preventive strategies. The results underscore the importance of considering pleiotropic effects in deciphering the genetic architecture of complex diseases, especially metabolic ones.

[Causal association between immune cells and sepsis: a based on Mendelian randomization method study].

OBJECTIVE: To investigate the causal association between immune cell and different types of sepsis by using Mendelian randomization (MR) method, and to find the immune cell phenotypes causally associated with sepsis. METHODS: Summary data for various circulating immune cell phenotypes were obtained from the GWAS catalog (GCST90001391-GCST90002121). Sepsis data were sourced from the UK Biobank database. Single nucleotide polymorphisms (SNP) were used as instrumental variables. The correlation threshold of P < 5×10-6 was used to identify the strongly correlated instrumental variables, and the code was used to remove the linkage disequilibrium and the instrumental variables with F-value < 10. Inverse variance weighting (IVW) was used as the main research method to evaluate the stability and reliability of the results, including Cochran's Q test, MR-Egger regression and Leave one out. Reverse MR analysis was performed based on the immunophenotypic results of the removal of horizontal pleiotropy, and the immune cell phenotype with one-way causal association was obtained. Odds ratio (OR) and 95% confidence interval (95%CI) were used to represent the effect value of the results. RESULTS: CD16 on CD14-CD16+; monocyte had horizontal pleiotropy in sepsis (OR = 0.965 4, 95%CI was 0.933 5-0.998 3, P = 0.039 6). There were five immunophenotypes that had reverse causal associations with the types associated with sepsis. After excluding immune cell phenotypes with horizontal pleiotropy and reverse causation, a total of 42 immune cell phenotypes with sepsis, 36 immune cell phenotypes with sepsis (28-day death in critical care), 32 immune cell phenotypes with sepsis (critical care), 44 immune cell phenotypes with sepsis (28-day death), and 30 immune cell phenotypes had potential causal associations with sepsis (under 75 years old). After false discovery rate (FDR) correction, the correlations between BAFF-R on IgD- CD38br and sepsis (28-day death) were negative and strong (OR = 0.737 8, 95%CI was 0.635 9-0.856 0, P = 6.05×10-5, PFDR = 0.044 2). CONCLUSIONS: A variety of immune cell phenotypes may have a protective effect on sepsis, especially BAFF-R on IgD- CD38br expression is negatively correlated with sepsis (28-day death), which provides a new idea for immune modulation therapy in sepsis.

GA-GBLUP: leveraging the genetic algorithm to improve the predictability of genomic selection.

Genomic selection (GS) has emerged as an effective technology to accelerate crop hybrid breeding by enabling early selection prior to phenotype collection. Genomic best linear unbiased prediction (GBLUP) is a robust method that has been routinely used in GS breeding programs. However, GBLUP assumes that markers contribute equally to the total genetic variance, which may not be the case. In this study, we developed a novel GS method called GA-GBLUP that leverages the genetic algorithm (GA) to select markers related to the target trait. We defined four fitness functions for optimization, including AIC, BIC, R2, and HAT, to improve the predictability and bin adjacent markers based on the principle of linkage disequilibrium to reduce model dimension. The results demonstrate that the GA-GBLUP model, equipped with R2 and HAT fitness function, produces much higher predictability than GBLUP for most traits in rice and maize datasets, particularly for traits with low heritability. Moreover, we have developed a user-friendly R package, GAGBLUP, for GS, and the package is freely available on CRAN (https://CRAN.R-project.org/package=GAGBLUP).

FLT4 gene polymorphisms influence isolated ventricular septal defect predisposition in a Southwest China population.

BACKGROUND: Ventricular septal defect (VSD) is the most common congenital heart disease. Although a small number of genes associated with VSD have been found, the genetic factors of VSD remain unclear. In this study, we evaluated the association of 10 candidate single nucleotide polymorphisms (SNPs) with isolated VSD in a population from Southwest China. METHODS: Based on the results of 34 congenital heart disease whole-exome sequencing and 1000 Genomes databases, 10 candidate SNPs were selected. A total of 618 samples were collected from the population of Southwest China, including 285 VSD samples and 333 normal samples. Ten SNPs in the case group and the control group were identified by SNaPshot genotyping. The chi-square (χ2) test was used to evaluate the relationship between VSD and each candidate SNP. The SNPs that had significant P value in the initial stage were further analysed using linkage disequilibrium, and haplotypes were assessed in 34 congenital heart disease whole-exome sequencing samples using Haploview software. The bins of SNPs that were in very strong linkage disequilibrium were further used to predict haplotypes by Arlequin software. ViennaRNA v2.5.1 predicted the haplotype mRNA secondary structure. We evaluated the correlation between mRNA secondary structure changes and ventricular septal defects. RESULTS: The χ2 results showed that the allele frequency of FLT4 rs383985 (P = 0.040) was different between the control group and the case group (P < 0.05). FLT4 rs3736061 (r2 = 1), rs3736062 (r2 = 0.84), rs3736063 (r2 = 0.84) and FLT4 rs383985 were in high linkage disequilibrium (r2 > 0.8). Among them, rs3736061 and rs3736062 SNPs in the FLT4 gene led to synonymous variations of amino acids, but predicting the secondary structure of mRNA might change the secondary structure of mRNA and reduce the free energy. CONCLUSIONS: These findings suggest a possible molecular pathogenesis associated with isolated VSD, which warrants investigation in future studies.

Genetic diversity and genome-wide association study of partial resistance to Sclerotinia stem rot in a Canadian soybean germplasm panel.

KEY MESSAGE: Developing genetically resistant soybean cultivars is key in controlling the destructive Sclerotinia Stem Rot (SSR) disease. Here, a GWAS study in Canadian soybeans identified potential marker-trait associations and candidate genes, paving the way for more efficient breeding methods for SSR. Sclerotinia stem rot (SSR), caused by the fungal pathogen Sclerotinia sclerotiorum, is one of the most important diseases leading to significant soybean yield losses in Canada and worldwide. Developing soybean cultivars that are genetically resistant to the disease is the most inexpensive and reliable method to control the disease. However, breeding for resistance is hampered by the highly complex nature of genetic resistance to SSR in soybean. This study sought to understand the genetic basis underlying SSR resistance particularly in soybean grown in Canada. Consequently, a panel of 193 genotypes was assembled based on maturity group and genetic diversity as representative of Canadian soybean cultivars. Plants were inoculated and screened for SSR resistance in controlled environments, where variation for SSR phenotypic response was observed. The panel was also genotyped via genotyping-by-sequencing and the resulting genotypic data were imputed using BEAGLE v5 leading to a catalogue of 417 K SNPs. Through genome-wide association analyses (GWAS) using FarmCPU method with threshold of FDR-adjusted p-values < 0.1, we identified significant SNPs on chromosomes 2 and 9 with allele effects of 16.1 and 14.3, respectively. Further analysis identified three potential candidate genes linked to SSR disease resistance within a 100 Kb window surrounding each of the peak SNPs. Our results will be important in developing molecular markers that can speed up the breeding for SSR resistance in Canadian grown soybean.

Integrating RTM-GWAS and meta­QTL data revealed genomic regions and candidate genes associated with the first fruit branch node and its height in upland cotton.

KEY MESSAGE: Two genomic regions associated with FFBN and HFFBN and a potential regulatory gene (GhE6) of HFFBN were identified through the integration of RTM-GWAS and meta­QTL analyses. Abstract The first fruit branch node (FFBN) and the height of the first fruit branch node (HFFBN) are two important traits that are related to plant architecture and early maturation in upland cotton. Several studies have been conducted to elucidate the genetic basis of these traits in cotton using biparental and natural populations. In this study, by using 9,244 SNP linkage disequilibrium block (SNPLDB) loci from 315 upland cotton accessions, we carried out restricted two-stage multilocus and multiallele genome-wide association studies (RTM-GWASs) and identified promising haplotypes/alleles of the four stable and true major SNPLDB loci that were significantly associated with FFBN and HFFBN. Additionally, a meta-quantitative trait locus (MQTL) analysis was conducted on 274 original QTLs that were reported in 27 studies, and 40 MQTLs associated with FFBN and HFFBN were identified. Through the integration of the RTM-GWAS and meta­QTL analyses, two stable and true major SNPLDBs (LDB_5_15144433 and LDB_16_37952328) that were distributed in the two MQTLs were identified. Ultimately, 142 genes in the two genomic regions were annotated, and three candidate genes associated with FFBN and HFFBN were identified in the genomic region (A05:14.64-15.64 Mb) via RNA-Seq and qRT‒PCR. The results of virus-induced gene silencing (VIGS) experiments indicated that GhE6 was a key gene related to HFFBN and that GhDRM1 and GhGES were important genes associated with early flowering in upland cotton. These findings will aid in the future identification of molecular markers and genetic resources for developing elite early-maturing cultivars with ideal plant characteristics.

Genetic associations between gut microbiota and type 2 diabetes mediated by plasma metabolites: a Mendelian randomization study.

Background: Numerous research studies have indicated a possible association between type 2 diabetes (T2DM) and gut microbiota. To explore specific metabolic pathways connecting gut microbiota and T2DM, we employed Mendelian randomization (MR) and linkage disequilibrium score regression (LDSC) techniques. Methods: This research utilized data from genome-wide association studies (GWAS) that are publicly accessible. We evaluated the genetic correlation between gut microbiota and T2DM using LDSC. Causality was primarily determined through the inverse variance weighted (IVW) method. To verify the robustness of our results, we conducted sensitivity analyses using several approaches, including the weighted median, MR-Egger, and MR-PRESSO. We integrated summary effect estimates from LDSC, along with forward and reverse MR, into a meta-analysis for T2DM using various data sources. Additionally, mediation analysis was performed to explore the impact of plasma metabolites on the relationship between gut microbiota and T2DM. Results: Our study indicated a significant genetic correlation between genus RuminococcaceaeUCG005 (Rg = -0.26, Rg_P = 2.07×10-4) and T2DM. Moreover, the forward MR analysis identified genus RuminococcaceaeUCG010 (OR = 0.857, 95% CI 0.795, 0.924; P = 6.33×10-5) and order Clostridiales (OR = 0.936, 95% CI 0.878, 0.997; P = 0.039) as being significantly associated with a decreased risk of T2DM. The analysis also highlighted several plasma metabolites as significant mediators in these relationships, with metabolites like octadecadienedioate (C18:2-DC) and branched chain 14:0 dicarboxylic acid being notably involved. Conclusion: The findings demonstrate a significant impact of gut microbiota on T2DM via plasma metabolites, suggesting potential metabolic pathways for therapeutic targeting. This study enhances our understanding of the microbiota's role in T2DM pathogenesis and supports the development of microbiota-based interventions.

Association between endometriosis and arthritis: results from NHANES 1999-2006, genetic correlation analysis, and Mendelian randomization study.

Background: Previous studies reported that endometriosis may have a higher risk of arthritis. However, it remains unclear whether the association between endometriosis and arthritis has genetic correlations, or the relationship is causal. Linkage Disequilibrium Score (LDSC) and Mendelian Randomization (MR) analyses use genetic variation as a natural experiment to explore genetic correlations and causal inferences from observational data, reducing unmeasured confounding factors. Method: Participants (aged 20-54 years, n = 2,915) for the cross-sectional study were obtained from the National Health and Nutrition Examination Survey (NHANES). Endometriosis and arthritis were diagnosed based on self-reported by reproductive health and medical condition questionnaire. Weighted multivariable logistic regression was used to explore the relationship between endometriosis and arthritis. LDSC and MR analysis were performed using the genome-wide association study (GWAS) summary statistics to identify the causal association. Result: A significant positive association between endometriosis and arthritis was found after multivariable adjustment (OR = 1.89; 95% CI: 1.33, 2.67). When exploring different types of arthritis, a positive association was revealed with rheumatoid arthritis (RA), other types of arthritis, and cases that the arthritis type were unknown, with an OR of 2.07 (95% CI: 1.03, 4.17), 2.78 (95% CI: 1.30, 5.95), and 2.06 (95% CI: 1.36, 3.11), respectively. However, genetic correlation analysis between endometriosis and RA did not reveal any significant findings (all P values > 0.05). Moreover, MR analysis also failed to identify a causal relationship between endometriosis and RA (all P values > 0.05). Conclusion: Cross-sectional study identified a significant positive association between endometriosis and arthritis among US women, especially among RA, while findings based on LDSC and MR analysis did not support a genetic correlation or causal role. These findings suggest that clinicians should pay more attention to the coexistence of RA in endometriosis patients and explore the shared pathophysiological mechanisms of these two disorders, with a particular focus on extrinsic factors rather than intrinsic genetic inheritance.

Association between inflammatory bowel disease and osteoporosis in European and East Asian populations: exploring causality, mediation by nutritional status, and shared genetic architecture.

Background: While previous research has established an association between inflammatory bowel disease (IBD) and osteoporosis (OP), the nature of this association in different populations remains unclear. Objective: Our study used linkage disequilibrium scores(LDSC) regression analysis and Mendelian randomization(MR) to assess the genetic correlation and causal relationship between IBD and OP in European and East Asian populations. Methods: We performed separate genetic correlation and causal analyses for IBD and OP in European and East Asian populations, used the product of coefficients method to estimate the mediating effect of nutritional status on the causal relationship, and used multi-trait analysis to explore the biological mechanisms underlying the IBD-nutrition-OP causal pathway. Results: Our analysis revealed a significant genetic correlation and causal relationship between IBD and OP in the European population. Conversely, no such correlation or causal relationship was observed in the East Asian population. Mediation analysis revealed a significant mediating effect of nutritional status on the causal pathway between IBD and OP in the European population. Multi-trait analysis of the IBD-nutrition-OP causal pathway identified MFAP2, ATP13A2, SERPINA1, FTO and VCAN as deleterious variants. Conclusion: Our findings establish a genetic correlation and causal relationship between IBD and OP in the European population, with nutritional status playing a crucial mediating role.

Molecular Mechanisms Linking Genes and Vitamins of the Complex B Related to One-Carbon Metabolism in Breast Cancer: An In Silico Functional Database Study.

Carcinogenesis is closely related to the expression, maintenance, and stability of DNA. These processes are regulated by one-carbon metabolism (1CM), which involves several vitamins of the complex B (folate, B2, B6, and B12), whereas alcohol disrupts the cycle due to the inhibition of folate activity. The relationship between nutrients related to 1CM (all aforementioned vitamins and alcohol) in breast cancer has been reviewed. The interplay of genes related to 1CM was also analyzed. Single nucleotide polymorphisms located in those genes were selected by considering the minor allele frequency in the Caucasian population and the linkage disequilibrium. These genes were used to perform several in silico functional analyses (considering corrected p-values < 0.05 as statistically significant) using various tools (FUMA, ShinyGO, and REVIGO) and databases such as the Kyoto Encyclopedia of Genes and Genomes (KEGG) and GeneOntology (GO). The results of this study showed that intake of 1CM-related B-complex vitamins is key to preventing breast cancer development and survival. Also, the genes involved in 1CM are overexpressed in mammary breast tissue and participate in a wide variety of biological phenomena related to cancer. Moreover, these genes are involved in alterations that give rise to several types of neoplasms, including breast cancer. Thus, this study supports the role of one-carbon metabolism B-complex vitamins and genes in breast cancer; the interaction between both should be addressed in future studies.

Pangenome-spanning epistasis and coselection analysis via de Bruijn graphs.

Studies of bacterial adaptation and evolution are hampered by the difficulty of measuring traits such as virulence, drug resistance, and transmissibility in large populations. In contrast, it is now feasible to obtain high-quality complete assemblies of many bacterial genomes thanks to scalable high-accuracy long-read sequencing technologies. To exploit this opportunity, we introduce a phenotype- and alignment-free method for discovering coselected and epistatically interacting genomic variation from genome assemblies covering both core and accessory parts of genomes. Our approach uses a compact colored de Bruijn graph to approximate the intragenome distances between pairs of loci for a collection of bacterial genomes to account for the impacts of linkage disequilibrium (LD). We demonstrate the versatility of our approach to efficiently identify associations between loci linked with drug resistance and adaptation to the hospital niche in the major human bacterial pathogens Streptococcus pneumoniae and Enterococcus faecalis.

Exploring the gut microbiota's effect on temporomandibular joint disorder: a two-sample Mendelian randomization analysis.

Background: Temporomandibular joint disorders (TMD) are highly prevalent among people. Numerous investigations have revealed the impact of gut microbiota in many diseases. However, the causal relationship between Temporomandibular joint disorders and gut microbiota remains unclear. Methods: Genome-Wide Association Studies (GWAS) refer to the identification of sequence variations, namely single nucleotide polymorphisms (SNPs), existing across the entire human genome. GWAS data were collected on gut microbiota and TMD. Then, instrumental variables were screened through F-values and removal of linkage disequilibrium. These SNPs underwent mendelian analysis using five mathematical models. Sensitivity analysis was conducted to further verify the stability of the results. Pathogenic factors of TMD mediate the causal relationship between gut microbiota and TMD were explored through a two-step Mendelian randomization analysis. Finally, reverse mendelian analysis was conducted to account for potential reverse effects. Results: The analysis of the data in this article suggests that some gut microbiota, including Coprobacter, Ruminococcus torques group, Catenibacterium, Lachnospiraceae, Turicibacter, Victivallis, MollicutesRF9, Methanobacteriales, Methanobacteriaceae, FamilyXI, Methanobacteria were identified as risk factors, while Peptococcaceae provides protection for TMD. Conclusion: The research reveals the relation of gut microbiota in TMD. These findings provide insights into the underlying mechanisms and suggest potential therapeutic strategy.

Genetic association of antinuclear antibodies with HLA in JIA patients: a Swedish cohort study.

BACKGROUND: Juvenile Idiopathic Arthritis (JIA) is a complex autoimmune disease and the most common chronic rheumatological disease affecting children under the age of 16. The etiology of JIA remains poorly understood, but evidence suggests a significant genetic predisposition. METHODS: We analyzed a Swedish cohort of 329 JIA patients and 728 healthy adult controls using the Illumina OmniExpress array for genotyping. HLA alleles were imputed from GWAS data using the SNP2HLA algorithm. RESULTS: Case-control analysis yielded 12 SNPs with genome-wide significant association to JIA, all located on chromosome 6 within the MHC class II gene region. Notably, the top SNP (rs28421666) was located adjacent to HLA-DQA1 and HLA-DRB1. HLA-DRB1*08:01, HLA-DQA1*04:01, and HLA-DQB1*04:02 were the haplotypes most strongly associated with an increased risk of JIA in the overall cohort. When analyzing disease specific subtypes, these alleles were associated with oligoarthritis and RF-negative polyarthritis. Within the complex linkage disequilibrium of the HLA-DRB1-DQA1-DQB1 haplotype, our analysis suggests that HLA-DRB1*08 might be the primary allele linked to JIA susceptibility. The HLA-DRB1*11 allele group was also independently associated with JIA and specifically enriched in the oligoarthritis patient group. Additionally, our study revealed a significant correlation between antinuclear antibody (ANA) positivity and specific HLA alleles. The ANA-positive JIA group showed stronger associations with the HLA-DRB1-DQA1-DQB1 haplotype, HLA-DRB1*11, and HLA-DPB1*02, suggesting a potential connection between genetic factors and ANA production in JIA. Furthermore, logistic regression analysis reaffirmed the effects of HLA alleles, female sex, and lower age at onset on ANA positivity. CONCLUSIONS: This study identified distinct genetic associations between HLA alleles and JIA subtypes, particularly in ANA-positive patients. These findings contribute to a better understanding of the genetic basis of JIA and provide insights into the genetic control of autoantibody production in ANA-positive JIA patients. This may inform future classification and personalized treatment approaches for JIA, ultimately improving patient outcomes and management of this disease.

Potentially functional variants of INPP5D and EXOSC3 in immunity B cell-related genes are associated with non-small cell lung cancer survival.

B cells are adaptive immune cells in the tumor microenvironment and play an important role in tumor development and metastasis. However, the roles of genetic variants of the immunity B cell-related genes in the survival of patients with non-small cell lung cancer (NSCLC) remain unknown. In the present study, we first evaluated associations between 10,776 single nucleotide polymorphisms (SNPs) in 220 immunity B cell-related genes and survival of NSCLC in a discovery dataset of 1,185 patients from the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial. We found that 369 SNPs were significantly associated with overall survival (OS) of NSCLC in multivariable Cox proportional hazards regression analysis (P ≤ 0.05, Bayesian false discovery probability ≤ 0.80), of which 18 SNPs were validated in another independent genotyping dataset of 984 patients from the Harvard Lung Cancer Susceptibility (HLCS) Study. We then performed linkage disequilibrium (LD) analysis, followed by stepwise analysis with a multivariable Cox regression model. Finally, two independent SNPs, inositol polyphosphate-5-phosphatase D (INPP5D) rs13385922 C>T and exosome component 3 (EXOSC3) rs3208406 A>G, remained significantly associated withNSCLC OS with a combined hazards ratio (HR) of 1.14 (95% confidence interval = 1.06-1.23, P = 2.41×10-4) and 1.20 (95% confidence interval = 1.14-1.28, P = 3.41×10-9), respectively. Furthermore, NSCLC patients with the combination of unfavorable genotypes for these two SNPs were associated with a poor OS (P trend = 0.0002) and disease-specific survival (DSS, P trend < 0.0001) in the PLCO dataset. Expression quantitative trait loci (eQTL) analysis suggested that the INPP5D rs6782875 T allele was significantly correlated with elevated INPP5D mRNA expression levels in normal lung tissues and whole blood samples, while the EXOSC3 rs3208406 G allele was significantly correlated with increased EXOSC3 mRNA expression levels in normal lung tissues. Our data indicated that genetic variants in these immunity B cell-related genes may predict NSCLC survival possibly by influencing the gene expression.

Genome-wide association study for metabolic syndrome reveals APOA5 single nucleotide polymorphisms with multilayered effects in Koreans.

BACKGROUND AND PURPOSE: Genome-wide association studies (GWAS) of metabolic syndrome (MetS) have predominantly focused on non-Asian populations, with limited representation from East Asian cohorts. Moreover, previous GWAS analyses have primarily emphasized the significance of top single nucleotide polymorphisms (SNPs), poorly explaining other SNP signals in linkage disequilibrium. This study aimed to reveal the interaction between rs651821 and rs2266788, the principal variants of apolipoprotein A5 (APOA5), within the most significant loci identified through GWAS on MetS. METHODS: GWAS on MetS and its components was conducted using the data from the Korean Genome and Epidemiology Study (KoGES) city cohort comprising 58,600 individuals with available biochemical, demographic, lifestyle factors, and the most significant APOA5 locus was analyzed further in depth. RESULTS: According to GWAS of MetS and its diagnostic components, a significant association between the APOA5 SNPs rs651821/rs2266788 and MetS/triglycerides/high-density lipoprotein phenotypes was revealed. However, a conditional analysis employing rs651821 unveiled a reversal in the odds ratio for rs2266788. Therefore, rs651821 and rs2266788 emerged as independent and opposing signals in the extended GWAS analysis, i.e., the multilayered effects. Further gene-environment interaction analyses regarding lifestyle factors such as smoking, alcohol consumption, and physical activity underscored these multilayered effects. CONCLUSION: This study unveils the intricate interplay between rs651821 and rs2266788 derived from MetS GWAS. Removing the influence of lead SNP reveals an independent protective signal associated with rs2266788, suggesting a multilayered effect between these SNPs. These findings underline the need for novel perspectives in future MetS GWAS.

Finemap-MiXeR: A variational Bayesian approach for genetic finemapping.

Genome-wide association studies (GWAS) implicate broad genomic loci containing clusters of highly correlated genetic variants. Finemapping techniques can select and prioritize variants within each GWAS locus which are more likely to have a functional influence on the trait. Here, we present a novel method, Finemap-MiXeR, for finemapping causal variants from GWAS summary statistics, controlling for correlation among variants due to linkage disequilibrium. Our method is based on a variational Bayesian approach and direct optimization of the Evidence Lower Bound (ELBO) of the likelihood function derived from the MiXeR model. After obtaining the analytical expression for ELBO's gradient, we apply Adaptive Moment Estimation (ADAM) algorithm for optimization, allowing us to obtain the posterior causal probability of each variant. Using these posterior causal probabilities, we validated Finemap-MiXeR across a wide range of scenarios using both synthetic data, and real data on height from the UK Biobank. Comparison of Finemap-MiXeR with two existing methods, FINEMAP and SuSiE RSS, demonstrated similar or improved accuracy. Furthermore, our method is computationally efficient in several aspects. For example, unlike many other methods in the literature, its computational complexity does not increase with the number of true causal variants in a locus and it does not require any matrix inversion operation. The mathematical framework of Finemap-MiXeR is flexible and may also be applied to other problems including cross-trait and cross-ancestry finemapping.

Association Analysis of METTL23 Gene Polymorphisms with Reproductive Traits in Kele Pigs.

Methyltransferase-like 23 (METTL23) is a kind of RNA methyltransferase that catalyzes the methylation transfer to the N6-adenosine of RNA, serving as one of the key mediators in this process. However, the METTL23 gene has been poorly researched in pigs. In this study, we investigated the genetic effects of METTL23 single-nucleotide polymorphism(SNPs) on reproductive traits in Kele pigs. The DNA was extracted from 228 healthy multiparous Kele sows, and Sanger sequencing revealed three SNPs, g.4804958 G > T (intron 2), g.4805082 C > T (exon 2), and g.4806821 A > G (exon 3). The polymorphism information content (PIC) for each SNP was 0.264, 0.25, and 0.354, indicating moderate polymorphism (0.25 < PIC < 0.5) and providing genetic information. Linkage disequilibrium analysis showed no strong linkage disequilibrium between the three SNPs. The association analysis revealed that in the SNP g.4804958 G > T individuals with the GG genotype had a significantly higher number of piglets born alive, litter birth weight, number of weaned piglets, and weaning litter weight compared to those with the TT genotype (p < 0.05). Individuals with the GG genotype in the SNP g.4806821 A > G group had significantly higher litter birth weight and average birth weight than those with the AA genotype (p < 0.05). The H4H4 diplotype showed significant effects on the number of piglets born alive, litter birth weight, number of weaned piglets, weaning litter weight, and weaning weight (p < 0.05). Together, the METTL23 gene could be used as a candidate gene for the selection of reproductive traits in Kele pigs.

Discover QTLs for the level of blood components in Shaoxing duck using GWAS and haplotype sharing analysis.

Blood composition is indicative of health-related traits such as immunity and metabolism. The use of molecular genetics to investigate alterations in these attributes in laying ducks is a novel approach. Our objective was to employ genome - wide association studies (GWAS) and haplotype - sharing analysis to identify genomic regions and potential genes associated with 11 blood components in Shaoxing ducks. Our findings revealed 35 SNPs and 1 SNP associated with low-density lipoprotein cholesterol (LDL) and globulin (GLB), respectively. We identified 36 putative candidate genes for the LDL trait in close proximity to major QTLs and key loci. Based on their biochemical and physiological properties, TRA2A, NPY, ARHGEF26, DHX36, and AADAC are the strongest putative candidate genes. Through linkage disequilibrium analysis and haplotype sharing analysis, we identified three haplotypes and one haplotype, respectively, that were significantly linked with LDL and GLB. These haplotypes could be selected as potential candidate haplotypes for molecular breeding of Shaoxing ducks. Additionally, we utilized a bootstrap test to verify the reliability of GWAS with small experimental samples. The test can be accessed at https://github.com/xuwenwu24/Bootstrap-test.