Genome Association Research Articles

Advancing Genetic Engineering through AI: Sequencing and Editing Innovations

As an important part of modern biotechnology, genetic engineering is widely used in fields such as disease treatment, agricultural improvement, and environmental protection. Gene sequencing technology, especially next-generation sequencing technology, provides a powerful tool for studying biological genetic information. However, with the rapid growth of genomic data, how to efficiently and accurately analyze and apply this huge data has become a major challenge facing genetic engineering. In recent years, artificial intelligence (AI) technology, especially deep learning, has been widely used in the automated processing of large-scale data and has shown great potential in genetic engineering. AI technology not only shows advantages in gene editing optimization, genetic variation detection and genome association analysis, but also significantly improves the efficiency and accuracy of genetic data analysis. Although AI has brought many conveniences in genetic engineering, challenges such as technology transparency, data quality issues, and ethics and privacy protection still need to be solved. This article explores the application of artificial intelligence in genetic engineering sequencing and data analysis, analyzes how AI can improve the efficiency and accuracy of genetic data analysis, and discusses the potential contribution of AI in gene editing and precision medicine. As AI continues to develop, it is expected to play an increasingly important role in fields such as genomics, gene editing, and precision medicine, and provide more effective strategies for future disease treatment

Genetic analysis of psychosis Biotypes: shared Ancestry-adjusted polygenic risk and unique genomic associations.

The Bipolar-Schizophrenia Network for Intermediate Phenotypes (B-SNIP) created psychosis Biotypes based on neurobiological measurements in a multi-ancestry sample. These Biotypes cut across DSM diagnoses of schizophrenia, schizoaffective disorder, and bipolar disorder with psychosis. Two recently developed post hoc ancestry adjustment methods of Polygenic Risk Scores (PRSs) generate Ancestry-Adjusted PRSs (AAPRSs), which allow for PRS analysis of multi-ancestry samples. Applied to schizophrenia PRS, we found the Khera AAPRS method to show superior portability and comparable prediction accuracy as compared with the Ge method. The three Biotypes of psychosis disorders had similar AAPRSs across ancestries. In genomic analysis of Biotypes, 12 genes, and isoforms showed significant genomic associations with specific Biotypes in a Transcriptome-Wide Association Study (TWAS) of genetically regulated expression (GReX) in the adult brain and fetal brain. TWAS inflation was addressed by the inclusion of genotype principal components in the association analyses. Seven of these 12 genes/isoforms satisfied Mendelian Randomization (MR) criteria for putative causality, including four genes TMEM140, ARTN, C1orf115, CYREN, and three transcripts ENSG00000272941, ENSG00000257176, ENSG00000287733. These genes are enriched in the biological pathways of Rearranged during Transfection (RET) signaling, Neural Cell Adhesion Molecule 1 (NCAM1) interactions, and NCAM signaling for neurite out-growth. The specific associations with Biotypes suggest that pharmacological clinical trials and biological investigations might benefit from analyzing Biotypes separately.

Heritability and Genome-Wide Association Study of Dog Behavioral Phenotypes in a Commercial Breeding Cohort.

Background: Canine behavior plays an important role in the success of the human-dog relationship and the dog's overall welfare, making selection for behavior a vital part of any breeding program. While behaviors are complex traits determined by gene × environment interactions, genetic selection for desirable behavioral phenotypes remains possible. Methods: No genomic association studies of dog behavior to date have been reported on a commercial breeding (CB) cohort; therefore, we utilized dogs from these facilities (n = 615 dogs). Behavioral testing followed previously validated protocols, resulting in three phenotypes/variables [social fear (SF), non-social fear (NSF), and startle response (SR)]. Dogs were genotyped on the 710 K Affymetrix Axiom CanineHD SNP array. Results: Inbreeding coefficients indicated that dogs from CB facilities are statistically less inbred than dogs originating from other breeding sources. Heritability estimates for behavioral phenotypes ranged from 0.042 ± 0.045 to 0.354 ± 0.111. A genome-wide association analysis identified genetic loci associated with SF, NSF, and SR; genes near many of these loci have been previously associated with behavioral phenotypes in other populations of dogs. Finally, genetic risk scores demonstrated differences between dogs that were more or less fearful in response to test stimuli, suggesting that these behaviors could be subjected to genetic improvement. Conclusions: This study confirms several canine genetic behavioral loci identified in previous studies. It also demonstrates that inbreeding coefficients of dogs in CB facilities are typically lower than those in dogs originating from other breeding sources. SF and NSF were more heritable than SR. Risk allele and weighted risk scores suggest that fearful behaviors could be subjected to genetic improvement.

Genetic Analysis of Psychosis Biotypes: Shared Ancestry-Adjusted Polygenic Risk and Unique Genomic Associations.

The Bipolar-Schizophrenia Network for Intermediate Phenotypes (B-SNIP) created psychosis Biotypes based on neurobiological measurements in a multi-ancestry sample. These Biotypes cut across DSM diagnoses of schizophrenia, schizoaffective disorder and bipolar disorder with psychosis. Two recently developed post hoc ancestry adjustment methods of Polygenic Risk Scores (PRSs) generate Ancestry-Adjusted PRSs (AAPRSs), which allow for PRS analysis of multi-ancestry samples. Applied to schizophrenia PRS, we found the Khera AAPRS method to show superior portability and comparable prediction accuracy as compared with the Ge method. The three Biotypes of psychosis disorders had similar AAPRSs across ancestries. In genomic analysis of Biotypes, 12 genes and isoforms showed significant genomic associations with specific Biotypes in Transcriptome-Wide Association Study (TWAS) of genetically regulated expression (GReX) in adult brain and fetal brain. TWAS inflation was addressed by inclusion of genotype principal components in the association analyses. Seven of these 12 genes/isoforms satisfied Mendelian Randomization (MR) criteria for putative causality, including four genes TMEM140, ARTN, C1orf115, CYREN, and three transcripts ENSG00000272941, ENSG00000257176, ENSG00000287733. These genes are enriched in the biological pathways of Rearranged during Transfection (RET) signaling, Neural Cell Adhesion Molecule 1 (NCAM1) interactions, and NCAM signaling for neurite out-growth. The specific associations with Biotypes suggest that pharmacological clinical trials and biological investigations might benefit from analyzing Biotypes separately.

Association of IL10 gene polymorphism with the susceptibility to dengue and disease severity in a population with asymptomatic and symptomatic dengue.

Infections caused by Orthoflavivirus denguei can either manifest asymptomatically or present a wide spectrum of clinical manifestations. This variety of symptoms results from its complex pathogenesis, which is influenced by viral factors, in addition to host genetics and immunological factors. It is known that anti-inflammatory cytokines can play an immunomodulatory role throughout the course of dengue. Therefore, we investigated the single nucleotide polymorphisms (SNPs) -1082 A/G (rs1800896) and -819 C/T (rs1800871) in the interleukin-10 (IL10) gene and their possible relationship with the development of symptomatic dengue in a Brazilian population. This study, carried out in northeastern Brazil, involved 333 volunteers, including 74 patients with dengue without warning signs (DWWS), 45 patients with dengue with warning signs (DWAS), 85 patients with asymptomatic dengue infection (ASY) and 129 health controls. The genomic DNA was extracted and the SNPs were genotyped using quantitative real-time polymerase chain reaction (qPCR). The data obtained were used to conduct statistical analyses of the genotype and allele frequencies. We observed an association of A/G and G/G genotypes of the -1082 A/G SNP of the IL10 gene with susceptibility to symptomatic dengue and DWAS regarding the asymptomatic dengue. The G allele of this SNP has also been identified as a risk factor for symptomatic dengue, DWWS and DWAS. Regarding the analyses between the SNPs -1082 A/G and -819 C/T of the IL10 gene, there was an association of the G-C haplotype with symptomatic dengue, DWWS and DWAS, as well as a correlation of the A-C haplotype with asymptomatic dengue. Moreover, the data indicate an association between the presence of the G allele and the development of symptoms, compared to those without the G allele. Our results indicate the presence of the G allele of SNP -1082 A/G of the IL10 gene as a risk factor for the clinical development of symptomatic dengue in the studied population and show the importance of genomics association studies involving asymptomatic individuals.

P109 Heterogeneity of 68Ga-PSMA PET/CT in metastatic castration-resistant prostate cancer: Genomic characteristics and association with new hormonal agent response, an international multi-center cohort study

P109 Heterogeneity of 68Ga-PSMA PET/CT in metastatic castration-resistant prostate cancer: Genomic characteristics and association with new hormonal agent response, an international multi-center cohort study

Genome-wide association study for milking speed in Fleckvieh cattle

Milking speed is an important trait influencing udder health of dairy cows as well as labor efficiency. Yet, it has received little attention in genomic association studies. The main objective of this study was to determine regions and genes on the genome with a potential effect on milking speed in Fleckvieh (dual purpose Simmental) cattle. Genome-wide association studies were conducted using de-regressed breeding values of bulls as phenotypes. Six SNP on 4 autosomes were significantly associated with milking speed for additive effects. Significant regions on BTA4 and BTA19 correspond with findings for other dairy cattle breeds. Based on the observation of Fleckvieh breed managers, variation of milking speed in batches of daughters of some bulls is much higher than in daughter groups of other bulls. This difference in within family variation may be caused by transmission of alternative alleles of bulls being heterozygous for a gene affecting milking speed. To check on this, we considered standard deviation of yield deviations in milking speed of half-sib daughters as a new trait and performed GWAS for dominance effects. One signal on BTA5 passed the genome wide Bonferroni threshold that corresponded to the significant signal from standard GWAS on de-regressed breeding values. The key conclusion of this study is that several strong genomic signals were found for milking speed in Fleckvieh cattle and that the strongest of them are supported by similar findings in Brown Swiss and Holstein Friesian cattle. Milking speed is a complex trait whose sub-processes have not yet been elucidated in detail. Hence, it remains a challenge to link the associated regions on the genome with causal genes and their functions.

NF1 expression profiling in IDH-wildtype glioblastoma: genomic associations and survival outcomes

BackgroundNF1 inactivation is associated with sensitivity to MEK inhibitor targeted therapy in low-grade and some high-grade gliomas. NF1 loss may also be a harbinger of exploitable vulnerabilities in IDH-wildtype glioblastoma (GBM). Accurate and consistent detection of NF1 loss, however, is fraught given the large gene size, challenges with complete coverage and variant calling upon sequencing, and mechanisms of mRNA and protein regulation that result in early degradation in the absence of genomic alterations. Here, we seek to perform a composite analysis for NF1 loss accounting for genomic alterations and protein expression via immunohistochemistry. We also characterize the landscape of NF1 alterations in GBM.MethodsWe assembled a single-institution, retrospective cohort of 542 IDH-wildtype GBM with somatic next generation sequencing to investigate the frequency and nature of detected NF1 alterations. We selected 69 GBMs from which to build a tissue microarray (TMA) of 44 NF1-wildtype and 25 NF1-mutant cases. We performed NF1 immunohistochemistry using two different NF1 antibodies (NFC, Sigma-Aldrich; and iNF-07E, iNFixion Bioscience) and correlated results with clinical, genomic, and other immunohistochemical features.ResultsIn our retrospective cohort, we identified 88 IDH-wildtype GBM with NF1 alterations (16%). NF1 alterations were mutually exclusive with EGFR and MDM2 alterations (p-adj < 0.001, 0.05, respectively), but co-occurred with PIK3R1 alterations (Log2(OR) = − 1.6, p-adj = 0.03). Of the 63 scorable sporadic GBMs in the TMA, 14 harbored NF1 inactivating alterations and of those, 12 (86%) demonstrated minimal NF1 immunoreactivity by NFC antibody, compared to 8 (57%) by iNF-07E antibody. Among the 42 scorable NF1-wildtype GBM in the TMA, NF1 immunostaining was minimal in 18 (43%) by NFC antibody compared to 4 (10%) by iNF-07E antibody, potentially reflecting false positives or differential protein regulation. Minimal immunoreactivity by NFC antibody was associated with decreased median overall survival (8.5 vs. 16.4 months, p = 0.011). Cox proportional hazards model correcting for prognostic variables in this subset revealed HR 3.23 (95% CI 1.29–8.06, p = 0.01) associated with decreased NF1 expression by IHC.ConclusionNF1 immunostaining may serve as a sensitive surrogate marker of NF1 genomic inactivation and a valuable extension to next-generation sequencing for defining NF1 status. Minimal NF1 immunoreactivity is a poor prognostic marker, even in IDH-wildtype glioblastoma without apparent NF1 genomic alterations, but the underlying molecular mechanism requires further investigation.

Exploring the potential link between gut microbiota and chronic kidney disease in causality: A 2-sample Mendelian randomization study.

Increasing evidence indicates a significant correlation between gut microbiota (GM) and susceptibility to chronic kidney disease (CKD). However, causal relationship presence remains uncertain. Mendelian randomization (MR) was applied to evaluate potential causal relation from GM to CKD. Genomic association analysis aggregates publicly online databases, utilizing Genome-Wide Association Study (GWAS) database focused on GM and CKD. For examination of potential causal connection from GM to CKD, a 2-way, 2-sample Mendelian randomization (MR) method was applied. Sensitivity analyses were utilized to scrutinize for heterogeneity, horizontal pleiotropy, MR outcomes resilience. Result from inverse variance weighting (IVW) method revealed that 10 microbiotas such as Porphyromonadaceae (OR = 1.351, 95% CI: 1.114-1.638, P = .002), Dorea (OR = 1.236, 95% CI: 1.040-1.468, P = .016), Ruminococcus torques group (OR = 1.290, 95% CI: 1.035-1.608, P = .024) are potential CKD risk factors. Five microbiotas, including the Prevotellaceae (OR = 0.814, 95% CI: 0.719-0.922, P = .001) are potential CKD protective factors. Sensitivity analyses reveal no horizontal pleiotropy or heterogeneity. Additionally, reverse MR results unveiled potential relation between CKD and disorders in 3 microbiotas, including Senegalimassilia. According to the investigation, MR method was employed to delve into reciprocal causal connection from GM to CKD. Our findings identified 15 types of GM causally linked to CKD, as well as CKD demonstrating causal associations with 3 types of GM. Further exploration of these associated GM types is hopeful to raise novel insights, for CKD preventing and early monitoring.

Higher oxygen content and transport characterize high-altitude ethnic Tibetan women with the highest lifetime reproductive success

We chose the "natural laboratory" provided by high-altitude native ethnic Tibetan women who had completed childbearing to examine the hypothesis that multiple oxygen delivery traits were associated with lifetime reproductive success and had genomic associations. Four hundred seventeen (417) women aged 46 to 86 y residing at ≥3,500 m in Upper Mustang, Nepal, provided information on reproductive histories, sociocultural factors, physiological measurements, and DNA samples for this observational cohort study. Simultaneously assessing multiple traits identified combinations associated with lifetime reproductive success measured as the number of livebirths. Women with the most livebirths had distinctive hematological and cardiovascular traits. A hemoglobin concentration near the sample mode and a high percent of oxygen saturation of hemoglobin raised arterial oxygen concentration without risking elevated blood viscosity. We propose ongoing stabilizing selection on hemoglobin concentration because extreme values predicted fewer livebirths and directional selection favoring higher oxygen saturation because higher values had more predicted livebirths. EPAS1, an oxygen homeostasis locus with strong signals of positive natural selection and a high frequency of variants occurring only among populations indigenous to the Tibetan Plateau, associated with hemoglobin concentration. High blood flow into the lungs, wide left ventricles, and low hypoxic heart rate responses aided effective convective oxygen transport to tissues. Women with physiologies closer to unstressed, low altitude values had the highest lifetime reproductive success. This example of ethnic Tibetan women residing at high altitudes in Nepal links reproductive fitness with trait combinations increasing oxygen delivery under severe hypoxic stress and demonstrates ongoing natural selection.

Genomic association of SNPs rs4077582 of CYP11A1 and rs700519 of CYP19A1 genes with polycystic ovarian syndrome.

Polycystic Ovarian Syndrome (PCOS) is a complex endocrine disorder that affects women of reproductive age. Several candidate genes have been shown to be associated with PCOS. Previous studies have shown that variations in CYP11A1 and CYP19A1 genes are associated with hormonal dysregulation associated with PCOS in different ethnic populations. This study aims to investigate the genomic association between SNPs rs4077582 of CYP11A1 and rs700519 of CYP19A1 and the development of PCOS in Pakistani population. A total of 280 subjects were recruited for the study, including 142 PCOS cases diagnosed based on Rotterdam criteria and 138 age-matched controls. The anthropometric, hormonal and biochemical parameters of all subjects were analyzed. Genomic DNA was extracted and genotyping of the selected SNPs was performed using Sanger sequencing. Further, we also examined the genotypic-phenotypic correlation analysis for various clinical and biochemical parameters for SNP rs4077582 of CYP11A1. We found significant differences in allele frequency (OR = 0.42, 95% CI = 0.30-0.60, χ2 = 16.3693, p = 0.000052) and genotypic frequency (χ2 = 26.4376, p = 0.00001) between PCOS women and controls for SNP rs4077582 of CYP11A1. Genotype-phenotype correlation analysis showed a significant difference in FAI (p = 0.005), testosterone (p = 0.001), androstenedione (p = 0.005) and urea (p = 0.049) levels between the three genotypes. No association between SNP rs700519 of CYP19A1 and PCOS was observed. Our results suggest the role of SNP rs4077582 of CYP11A1 gene in the clinical manifestation of PCOS in Pakistani women.

Genome-wide studies define new genetic mechanisms of IgA vasculitis.

IgA vasculitis (IgAV) is a pediatric disease with skin and systemic manifestations. Here, we conducted genome, transcriptome, and proteome-wide association studies in 2,170 IgAV cases and 5,928 controls, generated IgAV-specific maps of gene expression and splicing from blood of 255 pediatric cases, and reconstructed myeloid-specific regulatory networks to define disease master regulators modulated by the newly identified disease driver genes. We observed significant association at the HLA-DRB1 (OR=1.55, P=1.1×10-25) and fine-mapped specific amino-acid risk substitutions in DRβ1. We discovered two novel non-HLA loci: FCAR (OR=1.51, P=1.0×10-20) encoding a myeloid IgA receptor FcαR, and INPP5D (OR=1.34, P=2.2×10-9) encoding a known inhibitor of FcαR signaling. The FCAR risk locus co-localized with a cis-eQTL increasing FCAR expression; the risk alleles disrupted a PRDM1 binding motif within a myeloid enhancer of FCAR. Another risk locus was associated with a higher genetically predicted levels of plasma IL6R. The IL6R risk haplotype carried a missense variant contributing to accelerated cleavage of IL6R into a soluble form. Using systems biology approaches, we prioritized IgAV master regulators co-modulated by FCAR, INPP5D and IL6R in myeloid cells. We additionally identified 21 shared loci in a cross-phenotype analysis of IgAV with IgA nephropathy, including novel loci PAID4, WLS, and ANKRD55.

Research on the genetic etiology of polycystic ovary syndrome in the post-GWAS era

Great progress has been made in the genetic research of PCOS, thanks to the application of genome association study (GWAS) technology. However, in the post-GWAS era, investigating the pathogenic mechanisms related to numerous genetic loci has become challenging, leading to the current generalized approach to treating PCOS. To address this issue, taking the significantly associated susceptibility gene THADA as an example, we share a series of advancements from the perspectives of genetic evolution, epigenetics, and gene function studies. Our aim is to provide guidance for a better understanding of the essence of PCOS.

Genome-wide association analysis of flowering date in a collection of cultivated olive tree.

Flowering date in perennial fruit trees is an important trait for fruit production. Depending on the winter and spring temperatures, flowering of olive may be advanced, delayed, or even suppressed. Deciphering the genetic control of flowering date is thus key to help selecting cultivars better adapted to the current climate context. Here, we investigated the genetic determinism of full flowering date stage in cultivated olive based on capture sequencing data of 318 genotypes from the worldwide olive germplasm bank of Marrakech, Morocco. The genetic structure of this collection was organized in three clusters that were broadly attributed to eastern, central, and western Mediterranean regions, based on the presumed origin of genotypes. Flowering dates, collected over 7 years, were used to estimate the genotypic best linear unbiased predictors, which were then analyzed in a genome-wide association study. Loci with small effects were significantly associated with the studied trait, by either a single- or a multi-locus approach. The three most robust loci were located on chromosomes 01 and 04, and on a scaffold, and explained 7.1%, 6.2%, and 6.5% of the trait variance, respectively. A significantly higher accuracy in the best linear unbiased predictors of flowering date prediction was reported with Ridge- compared to LASSO-based genomic prediction model. Along with genomic association results, this suggests a complex polygenic determinism of flowering date, as seen in many other fruit perennials. These results and the screening of associated regions for candidate genes open perspectives for further studies and breeding programs targeting flowering date.

Genome-Wide Association Studies for Key Agronomic and Quality Traits in Potato (Solanum tuberosum L.)

Deciphering the genetic mechanisms underlying key agronomic and quality traits in potato (Solanum tuberosum L.) is essential for advancing varietal improvement. Phenotypic instability in early clonal generations and inbreeding depression, coupled with the complexity of tetrasomic inheritance, pose significant challenges in constructing mapping populations for the genetic dissection of complex traits. Genome-wide association studies (GWASs) offer an efficient method to establish trait–genome associations by analyzing genetic recombination and mutation events in natural populations. This review systematically examines the application of GWASs in identifying agronomic traits in potato, such as plant architecture, yield components, tuber shape, and resistance to early and late blight and nematodes, as well as quality traits including dry matter, starch, and glycoalkaloid content. Some key chromosomal hotspots identified through GWASs include chromosome 5 associated with tuber yield, starch content, and late blight resistance; chromosome 4 and 10 associations with tuber shape and starch content; chromosomes 1, 9, and 11 associated with plant height, tuber number, glycoalkaloid content, and pest resistance. It elucidates the advantages and limitations of GWASs for genetic loci identification in this autotetraploid crop, providing theoretical insights and a reference framework for the precise localization of key genetic loci and the discovery of underlying genes using GWASs.

Bacterial N-Acyl Homoserine Lactone Priming Enhances Leaf-Rust Resistance in Winter Wheat and Some Genomic Regions Are Associated with Priming Efficiency.

Leaf rust (Puccinia triticina) is a common disease that causes significant yield losses in wheat. The most frequently used methods to control leaf rust are the application of fungicides and the cultivation of resistant genotypes. However, high genetic diversity and associated adaptability of pathogen populations hamper achieving durable resistance in wheat. Emerging alternatives, such as microbial priming, may represent an effective measure to stimulate plant defense mechanisms and could serve as a means of controlling a broad range of pathogens. In this study, 175 wheat genotypes were inoculated with two bacterial strains: Ensifer meliloti strain expR+ch (producing N-acyl homoserine lactone (AHL)) or transformed E. meliloti carrying the lactonase gene attM (control). In total, 21 genotypes indicated higher resistance upon bacterial AHL priming. Subsequently, the phenotypic data of 175 genotypes combined with 9917 single-nucleotide polymorphisms (SNPs) in a genome-wide association study to identify quantitative trait loci (QTLs) and associated markers for relative infection under attM and expR+ch conditions and priming efficiency using the Genome Association and Prediction Integrated Tool (GAPIT). In total, 15 QTLs for relative infection under both conditions and priming efficiency were identified on chromosomes 1A, 1B, 2A, 3A, 3B, 3D, 6A, and 6B, which may represent targets for wheat breeding for priming and leaf-rust resistance.

A GWAS of ACE Inhibitor-Induced Angioedema in a South African Population.

Angiotensin-converting enzyme inhibitor-induced angioedema (AE-ACEI) is a life-threatening adverse event and, globally, the commonest cause of emergency presentations with angioedema. Several large genome-wide association studies (GWAS) have found genomic associations with AE-ACEI. However, despite African Americans having a 5-fold increased risk of AE-ACEI, there are no published GWAS from Africa. The aim of this study was to conduct a case-control GWAS of AE-ACEI in a South African population and perform a meta-analysis with an African American and European American population. The GWAS included 202 South African adults with a history of AE-ACEI and 513 controls without angioedema following angiotensin-converting enzyme inhibitor (ACEI) treatment for at least 2 years. A meta-analysis was conducted with GWAS summary statistics from an African American and European American cohort (from Vanderbilt/Marshfield with 174 cases and 489 controls). No SNPs attained genome-wide significance. However, 26 SNPs in the post-imputation standard GWAS of the South African cohort and 37 SNPs in the meta-analysis were associated to AE-ACEI with suggestive threshold(p-value<5.0×10-06). Some of these SNPs were found to be located close to the genes PRKCQ and RIMS1, previously linked with drug-induced angioedema, and also close to the CSMD1 gene linked to ACEI cough, providing replication at the gene level, but with novel lead SNPs. Our results highlight the importance of African populations to detect novel variants in replication studies. Further increased sampling across the continent and matched functional work are needed to confirm the importance of genetic variation in understanding the biology of AE-ACEI.

SARS-CoV-2 Omicron subvariant genomic variation associations with immune evasion in Northern California: A retrospective cohort study.

The possibility of association between SARS-CoV-2 genomic variation and immune evasion is not known among persons with Omicron variant SARS-CoV-2 infection. In a retrospective cohort, using Poisson regression adjusting for sociodemographic variables and month of infection, we examined associations between individual non-lineage defining mutations and SARS-CoV-2 immunity status, defined as a) no prior recorded infection, b) not vaccinated but with at least one prior recorded infection, c) complete primary series vaccination, and/or d) primary series vaccination and ≥ 1 booster. We identified all non-synonymous single nucleotide polymorphisms (SNPs), insertions and deletions in SARS-CoV-2 genomes with ≥5% allelic frequency and population frequency of ≥5% and ≤95%. We also examined correlations between the presence of SNPs with each other, with subvariants, and over time. Seventy-nine mutations met inclusion criteria. Among 15,566 persons infected with Omicron SARS-CoV-2, 1,825 (12%) were unvaccinated with no prior recorded infection, 360 (2%) were unvaccinated with a recorded prior infection, 13,381 (86%) had a complete primary series vaccination, and 9,172 (58%) had at least one booster. After examining correlation between SNPs, 79 individual non-lineage defining mutations were organized into 38 groups. After correction for multiple testing, no individual SNPs or SNP groups were significantly associated with immunity status levels. Genomic variation identified within SARS-CoV-2 Omicron specimens was not significantly associated with immunity status, suggesting that contribution of non-lineage defining SNPs to immune evasion is minimal. Larger-scale surveillance of SARS-CoV-2 genomes linked with clinical data can help provide information to inform future vaccine development.

Genetic mechanisms for impaired synaptic plasticity in schizophrenia revealed by computational modeling

Schizophrenia phenotypes are suggestive of impaired cortical plasticity in the disease, but the mechanisms of these deficits are unknown. Genomic association studies have implicated a large number of genes that regulate neuromodulation and plasticity, indicating that the plasticity deficits have a genetic origin. Here, we used biochemically detailed computational modeling of postsynaptic plasticity to investigate how schizophrenia-associated genes regulate long-term potentiation (LTP) and depression (LTD). We combined our model with data from postmortem RNA expression studies (CommonMind gene-expression datasets) to assess the consequences of altered expression of plasticity-regulating genes for the amplitude of LTP and LTD. Our results show that the expression alterations observed post mortem, especially those in the anterior cingulate cortex, lead to impaired protein kinase A (PKA)-pathway-mediated LTP in synapses containing GluR1 receptors. We validated these findings using a genotyped electroencephalogram (EEG) dataset where polygenic risk scores for synaptic and ion channel-encoding genes as well as modulation of visual evoked potentials were determined for 286 healthy controls. Our results provide a possible genetic mechanism for plasticity impairments in schizophrenia, which can lead to improved understanding and, ultimately, treatment of the disorder.

Unfolding the leaf economics spectrum for wheat: Trait analysis and genomic associations across cultivars

The leaf economics spectrum (LES) is an ecophysiological concept that describes the trade-offs between leaf structural and physiological traits. It has been extensively studied across various scales. However, the coordination hypothesis has rarely been tested at the intraspecific scale, especially in crops, for understanding yield increases or predicting evolutionary trajectories. Here, we first tested the relationships among leaf traits and examined the genetic coordination among 209 wheat genotypes. Compared to non-crop grass species, wheat is a fast-growing species, and tends to have a higher value of photosynthetic rate, leaf nitrogen concentration and leaf respiration rate at a given leaf mass per area, although it does align with the predicted direction of the “fast-slow” spectrum. We conducted a principal component analysis (PCA) to compare different traits within wheat. The first axis from PCA (ranging from slow to fast of plant economic investment) is significantly positively associated with the agronomic traits, especially grain yield (R2=0.11, P<0.001). Partially independent changes in leaf nitrogen content and leaf mass per area may allow crops to maximize photosynthetic rates without sacrificing leaf lifespan. The results reveal that some loci are simultaneously associated with different traits, which may be the genetic basis for the formation of trait-trait relationships. The current study deepens the understanding of LES traits in wheat at the intraspecific and genetic levels, supporting the trait-based adaptation strategies to improve wheat productivity and resource-use efficiency.