Combined Genome-wide Association Study Research Articles

Genome-Wide and Exome-Wide Association Study Identifies Genetic Underpinning of Comorbidity between Myocardial Infarction and Severe Mental Disorders.

Myocardial Infarction (MI) and severe mental disorders (SMDs) are two types of highly prevalent and complex disorders and seem to have a relatively high possibility of mortality. However, the contributions of common and rare genetic variants to their comorbidity arestill unclear. We conducted a combined genome-wide association study (GWAS) and exome-wide association study (EWAS) approach. Using gene-based and gene-set association analyses based on the results of GWAS, we found the common genetic underpinnings of nine genes (GIGYF2, KCNJ13, PCCB, STAG1, HLA-C, HLA-B, FURIN, FES, and SMG6) and nine pathways significantly shared between MI and SMDs. Through Mendelian randomization analysis, we found that twenty-seven genes were potential causal genes for SMDs and MI. Based on the exome sequencing data of MI and SMDs patients from the UK Biobank, we found that MUC2 was exome-wide significant in the two diseases. The gene-set analyses of the exome-wide association study indicated that pathways related to insulin processing androgen catabolic process and angiotensin receptor binding may be involved in the comorbidity between SMDs and MI. We also found that six candidate genes were reported to interact with known therapeutic drugs based on the drug-gene interaction information in DGIdb. Altogether, this study revealed the overlap of common and rare genetic underpinning between SMDs and MI and may provide useful insights for their mechanism study and therapeutic investigations.

Knockdown of β-conglycinin α' and α subunits alters seed protein composition and improves salt tolerance in soybean.

Soybean is an important plant source of protein worldwide. Increasing demands for soybean can be met by improving the quality of its seed protein. In this study, GmCG-1, which encodes the β-conglycinin α' subunit, was identified via combined genome-wide association study and transcriptome analysis. We subsequently knocked down GmCG-1 and its paralogues GmCG-2 and GmCG-3 with CRISPR-Cas9 technology and generated two stable multigene knockdown mutants. As a result, the β-conglycinin content decreased, whereas the 11S/7S ratio, total protein content and sulfur-containing amino acid content significantly increased. Surprisingly, the globulin mutant exhibited salt tolerance in both the germination and seedling stages. Little is known about the relationship between seed protein composition and the salt stress response in soybean. Metabonomics and RNA-seq analysis indicated that compared with the WT, the mutant was formed through a pathway that was more similar to that of active salicylic acid biosynthesis; however, the synthesis of cytokinin exhibited greater defects, which could lead to increased expression of plant dehydrin-related salt tolerance proteins and cell membrane ion transporters. Population evolution analysis suggested that GmCG-1, GmCG-2, and GmCG-3 were selected during soybean domestication. The soybean accessions harboring GmCG-1Hap1 presented relatively high 11S/7S ratios and relatively high salt tolerance. In conclusion, knockdown of the β-conglycinin α and α' subunits can improve the nutritional quality of soybean seeds and increase the salt tolerance of soybean plants, providing a strategy for designing soybean varieties with high nutritional value and high salt tolerance.

Decoding the genetic basis of ear‐related traits in maize (Zea mays L.) using linkage mapping, association mapping and genomic prediction

AbstractAs important yield components, the genetic analysis of ear‐related traits could provide a theoretical basis for maize breeding. Here, we reported the comprehensive genetic architecture of five ear‐related traits using 150 recombinant inbred lines (RIL) populations derived from the cross between Xu178 and K12. Besides, two sets of association populations were used to dissect genetic loci of five traits by genome‐wide association study (GWAS). A total of 32 QTLs of ear‐related traits were detected in the linkage mapping. Based on the mixed linear model (MLM), a total of 117 significant SNP markers of ear‐related traits were detected. Furthermore, a combined GWAS and linkage mapping analysis revealed 51 significant SNP markers fell within the confidence interval of QTLs. A total of seven co‐located significant SNP markers among different traits were found. Finally, six important candidate genes related to grain development were screened out. In addition, through haplotype analysis, two favourable haplotypes were found on chromosome 4, which could increase row number per ear (RNE), kernel number per row (KNR) and grain yield per plant (GYP) to a certain extent. Compared with the random model, the prediction accuracy of genomic prediction (GP) was improved in different degrees by considering the significant SNP markers as fixed effects. The stable genetic QTLs, candidate genes and favourable haplotypes found in this study are valuable resources, which will provide theoretical reference for high‐yield breeding of maize. Taken together, the research results also highlight the benefits of integrating GWAS with GP to further improve the accuracy of GP.

Discovery of genomic and transcriptomic pleiotropy between kidney function and soluble receptor for advanced glycation end products using correlated meta-analyses: The Long Life Family Study.

Patients with chronic kidney disease (CKD) have increased oxidative stress and chronic inflammation, which may escalate the production of advanced glycation end-products (AGEs). High soluble receptor for AGE (sRAGE) and low estimated glomerular filtration rate (eGFR) levels are associated with CKD and aging. We evaluated whether eGFR calculated from creatinine and cystatin C share pleiotropic genetic factors with sRAGE. We employed whole-genome sequencing and correlated meta-analyses on combined genome-wide association study (GWAS) p-values in 4182 individuals (age range: 24-110) from the Long Life Family Study (LLFS). We also conducted transcriptome-wide association studies (TWAS) on whole blood in a subset of 1209 individuals. We identified 59 pleiotropic GWAS loci (p < 5 × 10-8) and 17 TWAS genes (Bonferroni-p < 2.73 × 10-6) for eGFR traits and sRAGE. TWAS genes, LSP1 and MIR23AHG, were associated with eGFR and sRAGE located within GWAS loci, lncRNA-KCNQ1OT1 and CACNA1A/CCDC130, respectively. GWAS variants were eQTLs in the kidney glomeruli and tubules, and GWAS genes predicted kidney carcinoma. TWAS genes harbored eQTLs in the kidney, predicted kidney carcinoma, and connected enhancer-promoter variants with kidney function-related phenotypes at p < 5 × 10-8. Additionally, higher allele frequencies of protective variants for eGFR traits were detected in LLFS than in ALFA-Europeans and TOPMed, suggesting better kidney function in healthy-aging LLFS than in general populations. Integrating genomic annotation and transcriptional gene activity revealed the enrichment of genetic elements in kidney function and aging-related processes. The identified pleiotropic loci and gene expressions for eGFR and sRAGE suggest their underlying shared genetic effects and highlight their roles in kidney- and aging-related signaling pathways.

Identification of potential candidate genes associated with milk protein differences in Holstein cows: a meta-analysis integrating GWAS and RNA-Seq transcriptome

Despite the identification of candidate genes influencing milk protein, the connections between genes and regulatory pathways remains elusive. This study aimed integrate findings from genome-wide association studies (GWAS) and RNA sequencing (RNA-Seq) through meta-analysis to pinpoint single nucleotide polymorphisms (SNPs) and genes responsible for high and low protein yield in cows. Previous GWAS and RNA-Seq analyses had identified 663 SNPs and 1106 genes ( P &lt; 0.05). Twenty SNPs from GWAS, 10 genes from RNA-Seq, and 49 SNP/gene associations from both datasets, were identified using meta-analysis. Meta-analysis validated several SNPs previously identified through GWAS, such as rs135549651 ( P = 2.6 × 10−256), rs109146371 ( P = 3.1 × 10−208), rs109350371 ( P = 4.0 × 10−207), and rs109774038 ( P = 8.6 × 10−587). Genes identified in RNA-Seq experiments, including NR4A1 ( P = 3.2 × 10−7), ATF3 ( P = 9.6 × 10−7), CDH16 ( P = 9.9 × 10−7), VEGFA ( P = 1.0 × 10−6), and SAA3 ( P = 7.3 × 10−11), were confirmed. The combined GWAS and RNA-Seq datasets highlighted CCND2 ( P = 8.9 × 10−111), MAPK15 ( P = 1.3 × 10−151), and CPSF1 ( P = 1.2 × 10−306) as the most significant genes. Additionally, significant gene ontology (GO) terms, including ionizing radiation ( P = 1.5 × 10−4), nuclear pore cytoplasmic filaments ( P = 9.4 × 10−5), and phenylalanine 4-monooxygenase activity ( P = 1.4 × 10−5), were identified. In conclusion, the integration of GWAS and RNA-Seq, coupled with GO enrichment, allowed identification of candidate SNPs and genes with higher accuracy. These findings improve our knowledge about genomic architecture of milk protein and enhance evaluation of Holstein cows.

Combined ATAC-seq, RNA-seq, and GWAS analysis reveals glycogen metabolism regulatory network in Jinjiang oyster ( Crassostrea ariakensis).

Glycogen serves as the principal energy reserve for metabolic processes in aquatic shellfish and substantially contributes to the flavor and quality of oysters. The Jinjiang oyster ( Crassostrea ariakensis) is an economically and ecologically important species in China. In the present study, RNA sequencing (RNA-seq) and assay for transposase-accessible chromatin using sequencing (ATAC-seq) were performed to investigate gene expression and chromatin accessibility variations in oysters with different glycogen contents. Analysis identified 9 483 differentially expressed genes (DEGs) and 7 215 genes with significantly differential chromatin accessibility (DCAGs) were obtained, with an overlap of 2 600 genes between them. Notably, a significant proportion of these genes were enriched in pathways related to glycogen metabolism, including "Glycogen metabolic process" and "Starch and sucrose metabolism". In addition, genome-wide association study (GWAS) identified 526 single nucleotide polymorphism (SNP) loci associated with glycogen content. These loci corresponded to 241 genes, 63 of which were categorized as both DEGs and DCAGs. This study enriches basic research data and provides insights into the molecular mechanisms underlying the regulation of glycogen metabolism in C. ariakensis.

Identification of an Aux/IAA regulator for flesh firmness using combined GWAS and bulked segregant RNA-Seq analysis in watermelon

Watermelon is a highly cultivated fruit crop renowned for its quality properties of fruit flesh. Among various quality factors, fruit flesh firmness is a crucial quality parameter influencing the fruit texture, shelf life and its commercial value. The auxin/indole-3-acetic acid (Aux/IAA) plays a significant role in fruit development and ripening of non-climacteric fruits. However, the regulatory mechanism of Aux/IAA in controlling fruit flesh firmness and ripening in watermelon remains unknown. In this study, we employed an integrative approach combining genome-wide association study (GWAS) and bulked segregant RNA-Seq analysis (BSR-Seq) to identify an overlapping candidate region between 12 776 310 and 12 968 331 bp on chromosome 6, underlying an auxin-responsive gene (Aux/IAA) associated with flesh firmness in watermelon. Transcriptome analysis, followed by real-time quantitative reverse transcription PCR (qRT-PCR), confirmed that the expression of Aux/IAA was consistently higher in fruits with high flesh firmness. The sequence alignment revealed a single base mutation in the coding region of Aux/IAA. Furthermore, the concomitant Kompetitive/Competitive allele-specific PCR (KASP) genotyping data sets for F2 population and germplasm accessions identified Aux/IAA as a strong candidate gene associated with flesh firmness. Aux/IAA was enriched in the plant hormone signal transduction pathway, involving cell enlargement and leading to low flesh firmness. We determined the higher accumulation of abscisic acid (ABA) in fruits with low flesh firmness than hard flesh. Moreover, overexpression of Aux/IAA induced higher flesh firmness with an increased number of fruit flesh cells while reducing ABA content and flesh cell sizes. Additionally, the allelic variation in Aux/IAA for soft flesh firmness was found to exist in Citrullus mucosospermus and gradually fixed into Citrullus lanatus during domestication, indicating that soft flesh firmness was a domesticated trait. These findings significantly enhanced our understanding of watermelon fruit flesh firmness and consequently the watermelon fruit quality.

THE ASSOCIATION BETWEEN BLOOD PRESSURE VARIABILITY AND DEMENTIA: A TWO-SAMPLE MENDELIAN RANDOMIZATION STUDY

Objective: This study aims to investigate the causal inference by applying a mendelian randomization (MR) study using single-nucleotide polymorphisms (SNPs) from the genome-wide association study (GWAS) based on the UK biobank. Design and method: The genetic instruments were chosen from BPV GWAS based on UK Biobank data. Four GWA studies were used for the genetic evaluation of dementia, including (1) The International Genomic of Alzheimer's Project (IGAP) GWAS for dementia; (2) and (3) UK Biobank GWAS for proxy phenotypes of Alzheimer's dementia: the maternal and paternal family history (MFH and PFH-UKBB); (4) A combined GWAS meta-analysis from the abovementioned three GWAS results. The following exclusion criteria were applied for SNPs: (1) confounding SNPs by searching hypertension and artery stiffness GWAS; (2) significant SNPs that are associated with dementia in the datasets; (3) palindromic SNPs with an effect allele frequency between 0.4 and 0.7. Proxy SNPs were manually selected for some SNPs. (4) only SNPs with linkage disequilibrium r2 &lt; 0.01 were selected as genetic instruments, also known as independent SNPs. The effect/reference alleles were checked to ensure the consistency of the base pair between BPV and dementia GWAS, which is also known as data harmonization. After data harmonization, four MR methods were employed to measure the causal effect: IVW-MR with random effect, IVW-MR with fixed effect, MR-Egger, and weighted median MR. Results: Finally, six independent SNPs were chosen as instrument variants for SBPV, and five for DBPV. Significant causal effects of SBPV on dementia were found in the PFH-UKBB dataset, and the odds ratio of dementia per 10-unit increase in SBPV was 1.028, 1.015, and 1.015 for MR-Egger, weighted median, and IVW-MR, respectively (Table 1). In contrast, only one significant result was found for DBPV in MFH-UKBB. No significant results were found on other datasets. Conclusions: Along with the evidence from different observational studies, this GWAS study demonstrates that systolic blood pressure variability is a potential causal risk factor for Alzheimer's dementia, while the evidence from diastolic blood pressure variability is still uncertain.

Identification of candidate genes associated with carcass component weights in commercial crossbred pigs through a combined GWAS approach.

In the pork industry chain, carcass cutting is crucial for enhancing the commercial value of pork carcasses. However, the genetic mechanisms underlying carcass component weights remain poorly understood. Here, we used a combined genome-wide association study (GWAS) approach that integrated single- and multi-locus models to map genetic markers and genes associated with the weights of seven carcass components in Duroc × Landrace × Yorkshire (DLY) pigs. As multi-locus GWAS captures more single nucleotide polymorphisms (SNPs) with large effects than single-locus GWAS, the combined GWAS approach detected more SNPs than using the single-locus model alone. We identified 177 nonredundant SNPs associated with these traits in 526 DLY pigs, including boneless butt shoulder (BBS), boneless picnic shoulder (BPS), boneless leg (BL), belly (BELLY), front fat (FF), rear fat (RF), and skin-on whole loin (SLOIN). Using single-locus GWAS, we identified a quantitative trait locus (QTL) for SLOIN on Sus scrofa chromosome 15 (SSC15). Notably, a single SNP (ASGA0069883) in the proximity of this QTL was consistently detected by all GWAS models (one single-locus and four multi-locus models) and explained more than 4% of the phenotypic variance. Our findings suggest that the involved gene, MYO3B, is proposed to be a strong candidate for SLOIN. Further analysis also identified several candidate genes related to BBS (PPP3CA and CPEB4), BPS (ECH1), FF (CACNB2 and ZNF217), BELLY (FGFRL1), BL (CHST11), and RF (LRRK2). The identified SNPs can be used as molecular markers for the genetic improvement of pork carcasses in the molecular-guided breeding of modern commercial pigs.

Enhanced genome-wide association reveals the role of YABBY11-NGATHA-LIKE1 in leaf serration development of Populus.

Leaf margins are complex plant morphological features that contribute to leaf shape diversity, which affects plant structure, yield, and adaptation. Although several leaf margin regulators have been identified to date, the genetic basis of their natural variation has not been fully elucidated. In this study, we profiled two distinct leaf morphology types (serrated and smooth) using the persistent homology mathematical framework (PHMF) in two poplar species (Populus tomentosa and Populus simonii, respectively). A combined genome-wide association study (GWAS) and expression quantitative trait nucleotide (eQTN) mapping were applied to create a leaf morphology control module using data from P. tomentosa and P. simonii populations. Natural variation in leaf margins was associated with YABBY11 (YAB11) transcript abundance in poplar. In P. tomentosa, PtoYAB11 carries a premature stop codon (PtoYAB11PSC), resulting in the loss of its positive regulation of NGATHA-LIKE1 (PtoNGAL-1) and RIBULOSE BISPHOSPHATE CARBOXYLASE LARGE SUBUNIT (PtoRBCL). Overexpression of PtoYAB11PSC promoted serrated leaf margins, enlarged leaves, enhanced photosynthesis, and increased biomass. Overexpression of PsiYAB11 in P. tomentosa promoted smooth leaf margins, higher stomatal density, and greater light damage repair ability. In poplar, YAB11-NGAL1 is sensitive to environmental conditions, acts as a positive regulator of leaf margin serration, and may also link environmental signaling to leaf morphological plasticity.

Identification and genomic characterization of major effect bacterial blight resistance locus (BB-13) in Upland cotton (Gossypium hirsutum L.).

Identification and genomic characterization of major resistance locus against cotton bacterial blight (CBB) using GWAS and linkage mapping to enable genomics-based development of durable CBB resistance and gene discovery in cotton. Cotton bacterial leaf blight (CBB), caused by Xanthomonas citri subsp. malvacearum (Xcm), has periodically been a damaging disease in the USA. Identification and deployment of genetic resistance in cotton cultivars is the most economical and efficient means of reducing crop losses due to CBB. In the current study, genome-wide association study (GWAS) of CBB resistance using an elite diversity panel of 380 accessions, genotyped with the cotton single nucleotide polymorphism (SNP) 63K array, and phenotyped with race-18 of CBB, localized the CBB resistance to a 2.01-Mb region in the long arm of chromosome D02. Molecular genetic mapping using an F6 recombinant inbred line (RIL) population showed the CBB resistance in cultivar Arkot 8102 was controlled by a single locus (BB-13). The BB-13 locus was mapped within the 0.95-cM interval near the telomeric region in the long arm of chromosome D02. Flanking SNP markers, i04890Gh and i04907Gh of the BB-13 locus, identified from the combined linkage analysis and GWAS, targeted it to a 371-Kb genomic region. Candidate gene analysis identified thirty putative gene sequences in the targeted genomic region. Nine of these putative genes and two NBS-LRR genes adjacent to the targeted region were putatively involved in plant disease resistance and are possible candidate genes for BB-13 locus. Genetic mapping and genomic targeting of the BB13 locus in the current study will help in cloning the CBB-resistant gene and establishing the molecular genetic architecture of the BB-13 locus towards developing durable resistance to CBB in cotton.

Linkage mapping combined with GWAS revealed the genetic structural relationship and candidate genes of maize flowering time-related traits

BackgroundFlowering time is an important agronomic trait of crops and significantly affects plant adaptation and seed production. Flowering time varies greatly among maize (Zea mays) inbred lines, but the genetic basis of this variation is not well understood. Here, we report the comprehensive genetic architecture of six flowering time-related traits using a recombinant inbred line (RIL) population obtained from a cross between two maize genotypes, B73 and Abe2, and combined with genome-wide association studies to identify candidate genes that affect flowering time.ResultsOur results indicate that these six traits showed extensive phenotypic variation and high heritability in the RIL population. The flowering time of this RIL population showed little correlation with the leaf number under different environmental conditions. A genetic linkage map was constructed by 10,114 polymorphic markers covering the whole maize genome, which was applied to QTL mapping for these traits, and identified a total of 82 QTLs that contain 13 flowering genes. Furthermore, a combined genome-wide association study and linkage mapping analysis revealed 17 new candidate genes associated with flowering time.ConclusionsIn the present study, by using genetic mapping and GWAS approaches with the RIL population, we revealed a list of genomic regions and candidate genes that were significantly associated with flowering time. This work provides an important resource for the breeding of flowering time traits in maize.

Variant to function mapping at single-cell resolution through network propagation

Genome-wide association studies in combination with single-cell genomic atlases can provide insights into the mechanisms of disease-causal genetic variation. However, identification of disease-relevant or trait-relevant cell types, states and trajectories is often hampered by sparsity and noise, particularly in the analysis of single-cell epigenomic data. To overcome these challenges, we present SCAVENGE, a computational algorithm that uses network propagation to map causal variants to their relevant cellular context at single-cell resolution. We demonstrate how SCAVENGE can help identify key biological mechanisms underlying human genetic variation, applying the method to blood traits at distinct stages of human hematopoiesis, to monocyte subsets that increase the risk for severe Coronavirus Disease 2019 (COVID-19) and to intermediate lymphocyte developmental states that predispose to acute leukemia. Our approach not only provides a framework for enabling variant-to-function insights at single-cell resolution but also suggests a more general strategy for maximizing the inferences that can be made using single-cell genomic data.

Combined GWAS and Transcriptome Analyses Provide New Insights Into the Response Mechanisms of Sunflower Against Drought Stress.

Sunflower is one of the most important oil crops in the world, and drought stress can severely limit its production and quality. To understand the underlying mechanism of drought tolerance, and identify candidate genes for drought tolerance breeding, we conducted a combined genome-wide association studies (GWAS) and RNA-seq analysis. A total of 226 sunflower inbred lines were collected from different regions of China and other countries. Eight phenotypic traits were evaluated under control and drought stress conditions. Genotyping was performed using a Specific-Locus Amplified Fragment Sequencing (SLAF-seq) approach. A total of 934.08 M paired-end reads were generated, with an average Q30 of 91.97%. Based on the 243,291 polymorphic SLAF tags, a total of 94,162 high-quality SNPs were identified. Subsequent analysis of linkage disequilibrium (LD) and population structure in the 226 accessions was carried out based on the 94,162 high-quality SNPs. The average LD decay across the genome was 20 kb. Admixture analysis indicated that the entire population most likely originated from 11 ancestors. GWAS was performed using three methods (MLM, FarmCPU, and BLINK) simultaneously. A total of 80 SNPs showed significant associations with the 8 traits (p < 1.062 × 10−6). Next, a total of 118 candidate genes were found. To obtain more reliable candidate genes, RNA-seq analysis was subsequently performed. An inbred line with the highest drought tolerance was selected according to phenotypic traits. RNA was extracted from leaves at 0, 7, and 14 days of drought treatment. A total of 18,922 differentially expressed genes were obtained. Gene ontology and Kyoto Encyclopedia of Genes and Genomes analysis showed up-regulated genes were mainly enriched in the branched-chain amino acid catabolic process, while the down-regulated genes were mainly enriched in the photosynthesis-related process. Six DEGs were randomly selected from all DEGs for validation; these genes showed similar patterns in RNA-seq and RT-qPCR analysis, with a correlation coefficient of 0.8167. Through the integration of the genome-wide association study and the RNA-sequencing, 14 candidate genes were identified. Four of them (LOC110885273, LOC110872899, LOC110891369, LOC110920644) were abscisic acid related protein kinases and transcription factors. These genes may play an important role in sunflower drought response and will be used for further study. Our findings provide new insights into the response mechanisms of sunflowers against drought stress and contribute to further genetic breeding.

Pleiotropy method reveals genetic overlap between orofacial clefts at multiple novel loci from GWAS of multi-ethnic trios.

Based on epidemiologic and embryologic patterns, nonsyndromic orofacial clefts– the most common craniofacial birth defects in humans– are commonly categorized into cleft lip with or without cleft palate (CL/P) and cleft palate alone (CP), which are traditionally considered to be etiologically distinct. However, some evidence of shared genetic risk in IRF6, GRHL3 and ARHGAP29 regions exists; only FOXE1 has been recognized as significantly associated with both CL/P and CP in genome-wide association studies (GWAS). We used a new statistical approach, PLACO (pleiotropic analysis under composite null), on a combined multi-ethnic GWAS of 2,771 CL/P and 611 CP case-parent trios. At the genome-wide significance threshold of 5 × 10−8, PLACO identified 1 locus in 1q32.2 (IRF6) that appears to increase risk for one OFC subgroup but decrease risk for the other. At a suggestive significance threshold of 10−6, we found 5 more loci with compelling candidate genes having opposite effects on CL/P and CP: 1p36.13 (PAX7), 3q29 (DLG1), 4p13 (LIMCH1), 4q21.1 (SHROOM3) and 17q22 (NOG). Additionally, we replicated the recognized shared locus 9q22.33 (FOXE1), and identified 2 loci in 19p13.12 (RAB8A) and 20q12 (MAFB) that appear to influence risk of both CL/P and CP in the same direction. We found locus-specific effects may vary by racial/ethnic group at these regions of genetic overlap, and failed to find evidence of sex-specific differences. We confirmed shared etiology of the two OFC subtypes comprising CL/P, and additionally found suggestive evidence of differences in their pathogenesis at 2 loci of genetic overlap. Our novel findings include 6 new loci of genetic overlap between CL/P and CP; 3 new loci between pairwise OFC subtypes; and 4 loci not previously implicated in OFCs. Our in-silico validation showed PLACO is robust to subtype-specific effects, and can achieve massive power gains over existing approaches for identifying genetic overlap between disease subtypes. In summary, we found suggestive evidence for new genetic regions and confirmed some recognized OFC genes either exerting shared risk or with opposite effects on risk to OFC subtypes.

Novel loci and potential mechanisms of major depressive disorder, bipolar disorder, and schizophrenia.

Different psychiatric disorders share genetic relationships and pleiotropic loci to certain extent. We integrated and analyzed datasets related to major depressive disorder (MDD), bipolar disorder (BIP), and schizophrenia (SCZ) from the Psychiatric Genomics Consortium using multitrait analysis of genome-wide association analysis (MTAG). MTAG significantly increased the effective sample size from 99,773 to 119,754 for MDD, from 909,061 to 1,450,972 for BIP, and from 856,677 to 940,613 for SCZ. We discovered 7, 32, and 43 novel lead single nucleotide polymorphisms (SNPs) and 1, 6, and 3 novel causal SNPs for MDD, BIP, and SCZ, respectively, after fine-mapping. We identified rs8039305 in the FURIN gene as a novel pleiotropic locus across the three disorders. We performed marker analysis of genomic annotation (MAGMA) and Hi-C-coupled MAGMA (H-MAGMA) based gene-set analysis and identified 101 genes associated with the three disorders, which were enriched in the regulation of postsynaptic membranes, postsynaptic membrane dopaminergic synapses, and Notch signaling pathway. Next, we performed Mendelian randomization analysis using different tools and detected a causal effect of BIP on SCZ. Overall, we demonstrated the usage of combined genome-wide association studies summary statistics for exploring potential novel mechanisms of the three psychiatric disorders, providing an alternative approach to integrate publicly available summary data.

Are psychiatric disorders risk factors for COVID-19 susceptibility and severity? a two-sample, bidirectional, univariable, and multivariable Mendelian Randomization study

Observational studies have suggested bidirectional associations between psychiatric disorders and COVID-19 phenotypes, but results of such studies are inconsistent. Mendelian Randomization (MR) may overcome the limitations of observational studies, e.g., unmeasured confounding and uncertainties about cause and effect. We aimed to elucidate associations between neuropsychiatric disorders and COVID-19 susceptibility and severity. To that end, we applied a two-sample, bidirectional, univariable, and multivariable MR design to genetic data from genome-wide association studies (GWASs) of neuropsychiatric disorders and COVID-19 phenotypes (released in January 2021). In single-variable Generalized Summary MR analysis, the most significant and only Bonferroni-corrected significant result was found for genetic liability to BIP-SCZ (a combined GWAS of bipolar disorder and schizophrenia as cases vs. controls) increasing risk of COVID-19 (OR = 1.17, 95% CI, 1.06–1.28). However, we found a significant, positive genetic correlation between BIP-SCZ and COVID-19 of 0.295 and could not confirm causal or horizontally pleiotropic effects using another method. No genetic liabilities to COVID-19 phenotypes increased the risk of (neuro)psychiatric disorders. In multivariable MR using both neuropsychiatric and a range of other phenotypes, only genetic instruments of BMI remained causally associated with COVID-19. All sensitivity analyses confirmed the results. In conclusion, while genetic liability to bipolar disorder and schizophrenia combined slightly increased COVID-19 susceptibility in one univariable analysis, other MR and multivariable analyses could only confirm genetic underpinnings of BMI to be causally implicated in COVID-19 susceptibility. Thus, using MR we found no consistent proof of genetic liabilities to (neuro)psychiatric disorders contributing to COVID-19 liability or vice versa, which is in line with at least two observational studies. Previously reported positive associations between psychiatric disorders and COVID-19 by others may have resulted from statistical models incompletely capturing BMI as a continuous covariate.

Autistic traits predict obsessive-compulsive symptoms: Study in a clinical sample

IntroductionCo-occurrence of obsessive-compulsive disorder (OCD) and autism spectrum disorder (ASD) features is well stablished. Diagnosis of OCD increases the risk of a later diagnosis of ASD, and vice versa. Moreover, a recent combined genome-wide association study identified a shared polygenic risk between the two disorders. Our preliminary results also indicate that OCD patients have higher levels of autistic traits than individuals from the community.ObjectivesTo determine which autistic dimensions (social skill, communication, attention switching, attention to detail imagination) are predictors of OC symptoms.Methods39 OCD patients (52,5% female; 19 to 64 years old) answered the Portuguese versions of the Autism-Spectrum Quotient for Adults and Obsessive Compulsive Inventory – Revised (OCI-R). Spearman correlation and linear multiple regression tests were performed using SPSS.ResultsThe OCI-R global score showed positive correlations with some AQ dimensions (attention switching, attention to detail and communication). The regression model showed that attention to detail (β = .43, p = .01) and attention switching (β = .33, p = .038) explained 36% of obsessive-compulsive symptoms variance.ConclusionsOur results are in line with a dimensional perspective of psychopathological continua and indicate that the overlap between OCD and ASD occurs through shared neurocognitive processes. We suggest that, besides being a predisposing factor for social difficulties (e.g.: facial/emotion recognition) in ASD, attention to detail and deficits in attention switching may also lead to difficulties to dismiss repetitive thoughts or extinguish behaviours in OCD. Future studies should investigate the distinctive features and underlying processes between OCD/ASD.

Genome-wide association coupled gene to gene interaction studies unveil novel epistatic targets among major effect loci impacting rice grain chalkiness.

Rice varieties whose quality is graded as excellent have a lower percent grain chalkiness (PGC) of two per cent and below with higher whole grain yields upon milling, leading to higher economic returns for farmers. We have conducted a genome‐wide association study (GWAS) using a combined population panel of indica and japonica rice varieties, and identified a total of 746 single nucleotide polymorphisms (SNPs) that were strongly associated with the chalk phenotype, covered 78 Quantitative Trait Loci (QTL) regions. Among them, 21 were high‐value QTLs, as they explained at least 10 % of the phenotypic variance for PGC. A combined epistasis and GWAS was applied to dissect the genetics of the complex chalkiness trait, and its regulatory cascades were validated using gene regulatory networks. Promising novel epistatic interactions were found between the loci of chromosomes 6 (PGC6.1) and 7 (PGC7.8) that contributed to lower PGC. Based on haplotype mining only a few modern rice varieties confounded with a lower chalkiness, and they possess several PGC QTLs. The importance of PGC6.1 was validated through multi‐parent advanced generation intercrosses and several low‐chalk lines possessing superior haplotypes were identified. The results of this investigation have deciphered the underlying genetic networks that can reduce PGC to 2%, and will thus support future breeding programs to improve the grain quality of elite genetic material with high‐yielding potentials.

Integrated genetic and epigenetic analyses uncover MSI2 association with allergic inflammation

The relationship between allergic and eosinophilic inflammation, either systemic or local, in allergic diseases remains unclear. We performed combined genome-wide association study (GWAS) and epigenome-wide (EWAS) for atopy and tissue eosinophilia to identify both genetic and epigenetic signatures between systemic and local allergic inflammation, and to capture global patterns of gene regulation. We included 126 subjects for atopy analysis and 147 for tissue eosinophilia analysis, as well as 18 normal nasal tissue samples. We identified differentially methylated positions (DMPs) and genes associated with atopy and tissue eosinophilia. Furthermore, we performed mendelian randomization analysis and penalized regression along with replication in an independent cohort. EWAS identified genes, including Musashi RNA binding protein 2 (MSI2), associated with atopy, which contained enriched DMPs that genetically affect atopy. Adirect association was observed between MSI2 single-nucleotide polymorphisms and atopy, as was a causal effect of changes in MSI2 expression and methylation on atopy, which was replicated in a Costa Rican population. Regarding tissue eosinophilia, EWAS identified genes with enriched DMPs directly contributing to tissue eosinophilia at the gene level, including CAMK1D. The gene ontology terms of the identified genes for both phenotypes encompassed immune-related terms. EWAS combined with GWAS identified novel candidate genes, especially the methylation of MSI2, contributing to systemic allergic inflammation. Certain genes displayed a greater association with either systemic or local allergic inflammation; however, it is expected that a harmonized effect of these genes influences immune responses.