Linkage Disequilibrium Research Articles

Meta-analysis of Epstein-Barr virus genomes in Southern Chinese identifies genetic variants and high risk viral lineage associated with nasopharyngeal carcinoma.

Genetic variants in Epstein-Barr virus (EBV) have been strongly associated with nasopharyngeal carcinoma (NPC) in South China. However, different results regarding the most significant viral variants, with polymorphisms in EBER2 and BALF2 loci, have been reported in separate studies. In this study, we newly sequenced 100 EBV genomes derived from 61 NPC cases and 39 population controls. Comprehensive genomic analyses of EBV sequences from both NPC patients and healthy carriers in South China were conducted, totaling 279 cases and 227 controls. Meta-analysis of genome-wide association study revealed a 4-bp deletion downstream of EBER2 (coordinates, 7188-7191; EBER-del) as the most significant variant associated with NPC. Furthermore, multiple viral variants were found to be genetically linked to EBER-del forming a risk haplotype, suggesting that multiple viral variants might be associated with NPC pathogenesis. Population structure and phylogenetic analyses further characterized a high risk EBV lineage for NPC revealing a panel of 38 single nucleotide polymorphisms (SNPs), including those in the EBER2 and BALF2 loci. With linkage disequilibrium clumping and feature selection algorithm, the 38 SNPs could be narrowed down to 9 SNPs which can be used to accurately detect the high risk EBV lineage. In summary, our study provides novel insight into the role of EBV genetic variation in NPC pathogenesis by defining a risk haplotype of EBV for downstream functional studies and identifying a single high risk EBV lineage characterized by 9 SNPs for potential application in population screening of NPC.

Whole-genome resequencing reveals diversity and selective signals in the Wuxue goat.

Animal genetic resources are crucial for ensuring global food security. However, in recent years, a noticeable decline in the genetic diversity of livestock has occurred worldwide. This decline is pronounced in developing countries, where the management of these resources is insufficient. In the current study, we performed whole genome sequencing for 20 Wuxue (WX) and five Guizhou White (GW) goats. Additionally, we utilized the published genomes of 131 samples representing five different goat breeds from various regions in China. We investigated and compared the genetic diversity and selection signatures of WX goats. Whole genome sequencing analysis of the WX and GW populations yielded 120 425 063 SNPs, which resided primarily in intergenic and intron regions. Population genetic structure revealed that WX exhibited genetic resemblance to GW, Chengdu Brown, and Jintang Black and significant differentiation from the other goat breeds. In addition, three methods (nucleotide diversity, linkage disequilibrium decay, and runs of homozygosity) showed moderate genetic diversity in WX goats. We used nucleotide diversity and composite likelihood ratio methods to identify within-breed signatures of positive selection in WX goats. A total of 369 genes were identified using both detection methods, including genes related to reproduction (GRID2, ZNF276, TCF25, and SPIRE2), growth (HMGA2 and GJA3), and immunity (IRF3 and SRSF3). Overall, this study explored the adaptability of WX goats, shedding light on their genetic richness and potential to thrive in challenges posed by climatic changes and diseases. Further investigations are warranted to harness these insights to enhance more efficient and sustainable goat breeding initiatives.

Falls, fracture and frailty risk in multiple sclerosis: a Mendelian Randomization study to identify shared genetics.

Patients with multiple sclerosis (MS) commonly present musculoskeletal disorders characterized by lower bone mineral density (BMD) and muscle weakness. However, the underlying etiology remains unclear. Our objective is to identify shared pleiotropic genetic effects and estimate the causal relationship between MS and musculoskeletal disorders. We conducted linkage disequilibrium score regression (LDSR), colocalization, and Mendelian randomization (MR) analyses using summary statistics from recent large-scale genome-wide association studies (GWAS), encompassing MS, falls, fractures, and frailty. Additional MR analyses explored the causal relationship with musculoskeletal risk factors, such as BMD, lean mass, grip strength, and vitamin D. We observed a moderate genetic correlation between MS and falls (RG = 0.10, P-value = 0.01) but not between MS with fracture or frailty in the LDSR analyses. MR revealed MS had no causal association with fracture and frailty but a moderate association with falls (OR: 1.004, FDR q-value = 0.018). We further performed colocalization analyses using nine SNPs that exhibited significant associations with both MS and falls in MR. Two SNPs (rs7731626 on ANKRD55 and rs701006 on OS9 gene) showed higher posterior probability of colocalization (PP.H4 = 0.927), suggesting potential pleiotropic effects between MS and falls. The nine genes are associated with central nervous system development and inflammation signaling pathways. We found potential pleiotropic genetic effects between MS and falls. However, our analysis did not reveal a causal relationship between MS and increased risks of falls, fractures, or frailty. This suggests that the musculoskeletal disorders frequently reported in MS patients in clinical studies are more likely attributed to secondary factors associated with disease progression and treatment, rather than being directly caused by MS itself.

A novel locus in CSMD1 gene is associated with increased susceptibility to severe malaria in Malian children

BackgroundPlasmodium falciparum malaria is still a leading cause of child mortality in sub-Saharan Africa. The clinical manifestations of malaria range from asymptomatic infection to severe disease. The variation in clinical presentation is partly attributed to host genetic factors with estimated narrow-sense heritability of 23%. Here, we investigate the associations between candidate gene polymorphisms and the likelihood of severe malaria (SM) in a cohort of Malian children.MethodsBased on our previous genome-wide association studies (GWAS) analysis, candidate genes were selected for in-depth analysis using several criteria including gene-level GWAS scores, functional overlap with malaria pathogenesis, and evidence of association with protection or susceptibility to other infectious or inflammatory diseases. Single Nucleotide Polymorphisms (SNPs) residing within these genes were selected mainly based on p-values from previous severe malaria susceptibility GWAS studies and minor allele frequency (MAF) in West African populations.ResultsOf 182 candidate genes reported in our previous study, 11 genes and 22 SNPs residing in these genes were selected. The selected SNPs were genotyped using KASP technology in 477 DNA samples (87 SM and 390 controls). Logistic regression analysis revealed that a common intron variant, rs13340578 in CUB and Sushi Multi Domain (CSMD1) gene, is associated with increased odds of SM in recessive mode of inheritance (MAF = 0.42, OR = 1.8, 95% CI = [1.78, 1.84], p = 0.029). The SNP is in linkage disequilibrium (LD) with multiple variants with regulatory features.ConclusionTaken together, the current study showed that an intron variant rs13340578, residing in CSMD1 gene, is associated with increased susceptibility to malaria. This finding suggests that modified regulation of complement may contribute to malaria disease severity. Further studies are needed to identify the causal variants and the underlying molecular mechanisms.

Genetic associations between gut microbiota and allergic rhinitis: an LDSC and MR analysis

BackgroundSeveral studies have suggested a potential link between allergic rhinitis (AR) and gut microbiota. In response, we conducted a meta-analysis of Linkage Disequilibrium Score Regression (LDSC) and Mendelian randomization (MR) to detect their genetic associations.MethodsSummary statistics for 211 gut microbiota taxa were gathered from the MiBioGen study, while data for AR were sourced from the Pan-UKB, the FinnGen, and the Genetic Epidemiology Research on Aging (GERA). The genetic correlation between gut microbiota and AR was assessed using LDSC. The principal estimate of causality was determined using the Inverse-Variance Weighted (IVW) method. To assess the robustness of these findings, sensitivity analyses were conducted employing methods such as the weighted median, MR-Egger, and MR-PRESSO. The summary effect estimates of LDSC, forward MR and reverse MR were combined using meta-analysis for AR from different data resources.ResultsOur study indicated a significant genetic correlation between genus Sellimonas (Rg = −0.64, p = 3.64 × 10−5, Adjust_P = 3.64 × 10−5) and AR, and a suggestive genetic correlation between seven bacterial taxa and AR. Moreover, the forward MR analysis identified genus Gordonibacter, genus Coprococcus2, genus LachnospiraceaeUCG010, genus Methanobrevibacter, and family Victivallaceae as being suggestively associated with an increased risk of AR. The reverse MR analysis indicated that AR was suggestively linked to an increased risk for genus Coprococcus2 and genus RuminococcaceaeUCG011.ConclusionOur findings indicate a causal relationship between specific gut microbiomes and AR. This enhances our understanding of the gut microbiota’s contribution to the pathophysiology of AR and lays the groundwork for innovative approaches and theoretical models for future prevention and treatment strategies in this patient population.

The Interleukin-6 gene variants may protect against SARS-CoV-2 infection and the severity of COVID-19: a case-control study in a Moroccan population

The symptoms of SARS-CoV-2 infection vary widely, ranging from asymptomatic cases to severe forms marked by acute respiratory distress syndrome, multi-organ damage, and fatalities. Studies indicate a correlation between specific genes and susceptibility to SARS-CoV-2 infection and disease severity, particularly involving variants in genes linked to inflammation and immune responses. The objective of this study is to investigate the association between rs1800795 (− 174 G > C) and rs1800797 (− 597 A > G) variants in the interleukin-6 (IL-6) promoter region and susceptibility to SARS-CoV-2 infection. Additionally, we aim to explore their correlation with COVID-19 severity in a Moroccan population. In this case-control study, we enrolled 270 unvaccinated COVID-19 patients, consisting of 132 with severe COVID-19 and 138 with asymptomatic-moderate COVID-19. Additionally, we included 339 SARS-CoV-2-negative group. Genotyping of rs1800795 and rs1800797 polymorphisms of the IL-6 gene was performed using predesigned TaqMan SNP genotyping. The median age of SARS-CoV-2-negative controls was 50 years, while severe COVID-19 cases exhibited a median age of 61 years. Additionally, individuals with asymptomatic to moderate COVID-19 had a median age of 36 years. We observed a significant age difference between severe and mild COVID-19 patients (p < 0.0001), and an association was noted between gender and the severity of COVID-19 (p = 0.011). The allele and genotype frequencies of the IL-6 − 597G > A and − 174G > C variants did not show significant associations with susceptibility to SARS-CoV-2 infection (p > 0.05). However, further analysis revealed that the linkage disequilibrium between rs1800797 and rs1800795 indicated that individuals with the GC* haplotype (OR = 0.04, 95% CI 0.01–0.30, p = 0.001) and AG* haplotype (OR = 0.11, 95% CI 0.03–0.46, p = 0.002) were significantly associated with protection against SARS-CoV-2 infection. Moreover, in the overdominant model, the IL-6 − 174 G/C genotype was found to be protective against the development of severe disease compared to those with the G/G-C/C genotypes (p = 0.03; OR = 0.41, 95% CI 0.18–0.96). However, correlations between complete blood count markers, hematological markers, D-dimer, C-reactive protein, and ferritin levels according to − 597 A > G and − 174G > C genotypes showed no significant differences (all p > 0.05). Our findings provide valuable insights into the pathogenesis of COVID-19, suggesting that genetic variations at the IL-6 gene may contribute to the susceptibility to severe SARS-CoV-2 infection within the Moroccan population.

Genetic insights into the gut microbiota, herpes zoster, and postherpetic neuralgia: a bidirectional two-sample Mendelian randomization study

BackgroundAn increasing amount of evidence suggests that gastrointestinal diseases are risk factors for herpes zoster (HZ) and postherpetic neuralgia (PHN). Among them, the gut microbiota may play a crucial role in this process. Therefore, this study aims to explore the potential causal association between the gut microbiota and HZ and PHN.MethodsBidirectional two-sample Mendelian randomization (MR) analysis was used to detect the causal effect between HZ and PHN and the gut microbiota. Gut microbiota data were derived from the MiBioGen consortium, while HZ and PHN data were obtained from the FinnGen database. We selected single-nucleotide polymorphisms (SNPs) as instrumental variables with a threshold of p &amp;lt; 1 × 10⁻⁵ for the association with the gut microbiota in forward MR analysis and p &amp;lt; 5 × 10⁻8 for the association with HZ or PHN in reverse MR analysis and then removed SNPs in linkage disequilibrium (r2 &amp;lt; 0.001) within a distance of 10,000 kb for both the gut microbiota and HZ and PHN. These SNPs were utilized to assess the causal effect between exposures and outcomes using inverse-variance weighting (IVW), MR–Egger, weighted mean, and weighted median tests.ResultsThe class Deltaproteobacteria, order Desulfovibrionales, family Desulfovibrionaceae, and genus Coprococcus 2 were found to reduce the risk of HZ, while the phylum Cyanobacteria, genus Eubacterium rectale group appeared to increase it. The class Coriobacteriia, order Coriobacteriales, family Coriobacteriaceae, genus Lachnospiraceae NK4A136 and genus Ruminococcaceae UCG011 were found to reduce the risk of PHN, while the genus Candidatus Soleaferrea, genus Eubacterium rectale group, and genus Methanobrevibacter appeared to increase it. Moreover, the onset of HZ was found to increase the level of the genus Eubacterium rectale group. These findings remained robust and unaffected by heterogeneity or horizontal pleiotropy among SNPs in both forward and reverse MR analysis.ConclusionThis MR study provided evidence supporting a potential causal relationship between the gut microbiota and HZ and PHN. Moreover, we found that the causal effect between the gut microbiota and HZ is bidirectional. Further studies are required to clarify the biological mechanisms linking the gut microbiota and these conditions.

Effects of demographic history on recombination hotspots in soybean.

Recombination is the primary mechanism underlying genetic improvement in populations and allows plant breeders to create new allelic combinations for agronomic improvement. Soybean [Glycine max (L.) Merr.] has gone through multiple genetic bottlenecks that have significantly affected its genetic diversity, linkage disequilibrium, and altered allele frequencies. To investigate the impact of genetic bottlenecks on recombination hotspots in soybeans, historical recombination was studied in three soybean populations. The populations were wild soybean [Glycine soja (Sieb. and Zucc.)], landraces, and North American elite soybean cultivars that have been genotyped with the SoySNP50K BeadChip. While each population after a genetic bottleneck had an increased average haplotype block size, they did not have a significant difference in the number of hotspots between each population. Instead, the increase in observed haplotype block size is likely due to an elimination of individuals that contained historical recombination at hotspots which decreased the observed rate of recombination for the hotspot after each genetic bottleneck. Conversely, heterochromatic DNA which has an increased haplotype block size compared to euchromatic DNA had a significantly different number of hotspots but not a significant difference in the average hotspot recombination rate. Previously identified genomic motifs associated with hotspots were also associated with hotspots found in the historical populations suggesting a common mechanism. This characterization of historical recombination hotspots in soybeans provides further insights into the effect genetic bottlenecks and selection have on recombination hotspots.

Computing linkage disequilibrium aware genome embeddings using autoencoders.

The completion of the genome has paved the way for genome-wide association studies (GWAS), which explained certain proportions of heritability. GWAS are not optimally suited to detect non-linear effects in disease risk, possibly hidden in non-additive interactions (epistasis). Alternative methods for epistasis detection using e.g. deep neural networks (DNNs) are currently under active development. However, DNNs are constrained by finite computational resources, which can be rapidly depleted due to increasing complexity with the sheer size of the genome. Besides, the curse of dimensionality complicates the task of capturing meaningful genetic patterns for DNNs; therefore necessitates dimensionality reduction. We propose a method to compress single nucleotide polymorphism (SNP) data, while leveraging the linkage disequilibrium (LD) structure and preserving potential epistasis. This method involves clustering correlated SNPs into haplotype blocks and training per-block autoencoders to learn a compressed representation of the block's genetic content. We provide an adjustable autoencoder design to accommodate diverse blocks and bypass extensive hyperparameter tuning. We applied this method to genotyping data from Project MinE, and achieved 99% average test reconstruction accuracy-i.e. minimal information loss-while compressing the input to nearly 10% of the original size. We demonstrate that haplotype-block based autoencoders outperform linear Principal Component Analysis (PCA) by approximately 3% chromosome-wide accuracy of reconstructed variants. To the extent of our knowledge, our approach is the first to simultaneously leverage haplotype structure and DNNs for dimensionality reduction of genetic data. Data are available for academic use through Project MinE at https://www.projectmine.com/research/data-sharing/, contingent upon terms and requirements specified by the source studies. Code is available at https://github.com/gizem-tas/haploblock-autoencoders. Supplementary data are available at Bioinformatics online.

Systems genetics analyses reveals key genes related to behavioral traits in the striatum of CFW mice.

The striatum plays a central role in directing many complex behaviors ranging from motor control to action choice and reward learning. In our study, we used 55 CFW mice with rapid decay linkage disequilibrium to systematically mine the striatum-related behavioral functional genes by analyzing their striatal transcriptomes and 79 measured behavioral phenotypic data. By constructing a gene co-expression network, we clustered the genes into 13 modules, with most of them being positively correlated with motor traits. Based on functional annotations as well as Fisher's exact and hypergeometric distribution tests, brown and magenta modules were identified as core modules. They were significantly enriched for striatal-related functional genes. Subsequent Mendelian randomization analysis verified the causal relationship between the core modules and dyskinesia. Through the intra-modular gene connectivity analysis, Adcy5 and Kcnma1 were identified as brown and magenta module hub genes, respectively. Knockouts of both Adcy5 and Kcnma1 lead to motor dysfunction in mice, and KCNMA1 acts as a risk gene for schizophrenia and smoking addiction in humans. We also evaluated the cellular composition of each module and identified oligodendrocytes in the striatum to have a positive role in motor regulation.Significance Statement The striatum plays a central role in guiding many complex behaviours from motor control to action selection and reward learning. Clinically, striatal dysfunction contributes to a variety of neurodegenerative diseases, including the well-known Alzheimer's disease and Huntington's disease. In our study, we systematically mined striatum-associated behavioural function genes using 55 CFW mice. And we validated our findings in multiple ways. We found that Adcy5 and Kcnma1 knockouts in mice lead to motor dysfunction in mice and that Kcnma1 is associated with schizophrenia, a finding that holds true in humans. Finally, we also assessed the role of different cells in the regulation of striatal behaviour and found that oligodendrocytes in the striatum play an active role in movement regulation.

Copy number and sequence variation in rDNA of Daphnia pulex from natural populations: insights from whole genome sequencing.

Ribosomal DNA (rDNA) has a vital role in ribosome biogenesis as it contains the genes that encode rRNA separated by intergenic spacers. The rRNA genes occur in hundreds to tens of thousands of copies per haploid genome in eukaryotes and are generally highly conserved with low variation within species. Due to the repetitive nature and large size of rDNA arrays, detecting intraindividual variation can be difficult. In this study, we use whole genome sequences of 169 Daphnia pulex individuals from 10 natural populations to measure the copy number and sequence variation in rDNA. This revealed that variation in rDNA copy number between individuals spans an order of magnitude. We further observed a substantial level of sequence variation within individual genomes. As expected, single nucleotide polymorphisms occurred in regions of lower functional constraint such as the intergenic spacer and expansion segments of the rRNA genes. The presence of strong linkage disequilibrium among variants facilitated identification of haplotypes within each population. Although there was evidence of recombination among haplotypes from different populations, it is insufficient to eliminate linkage disequilibrium within populations. Estimating copy number and haplotype diversity within individuals revealed that the level of intraindividual sequence variation is not strongly correlated with copy number. The observed patterns of variation highlight a complex evolutionary history of rDNA in D. pulex. Future research should explore the functional implications of rDNA copy number and sequence variation on organismal phenotypes.

Exploring the causal relationships between rheumatoid arthritis and oral phenotypes: a genetic correlation and Mendelian randomization study

BackgroundRheumatoid arthritis (RA) frequently presents with oral manifestations, including gingival inflammation, loose teeth, and mouth ulcers; however, the causal connections between these conditions remain unclear. This study aims to explore the genetic correlations and causal relationships between RA and prevalent oral phenotypes.MethodsUsing summary data from genome-wide association studies of European populations, a cross-trait linkage disequilibrium score regression was conducted to estimate the genetic correlations between RA and six oral phenotypes. Subsequently, a two-sample Mendelian randomization (MR) approach was employed to assess the causal relationships, corroborated by various sensitivity analyses. Heterogeneity was addressed through the RadialMR method, while potential covariates were corrected using the multivariable MR approach.ResultsA significant negative genetic correlation was detected between RA and denture usage (rg = −0.192, p = 4.88 × 10−8). Meanwhile, a heterogenous causal relationship between RA and mouth ulcers was observed (OR = 1.027 [1.005–1.05], p = 0.016, Pheterogeneity = 4.69 × 10−8), which remained robust across sensitivity analyses. After excluding outlier variants, the results demonstrated robustly consistent (OR = 1.021 [1.008–1.035], p = 1.99 × 10−3, Pheterogeneity = 0.044). However, upon adjusting for covariates such as smoking, alcohol consumption, body mass index, and obesity, the significance diminished, revealing no evidence to support independent genetic associations.ConclusionGenetically predicted RA increases the risk of mouth ulcers, and a negative genetic correlation is identified between RA and denture use. The observed heterogeneity suggests that shared immunological mechanisms and environmental factors may play significant roles. These findings highlight the importance of targeted dental management strategies for RA patients. Further clinical guidelines are required to improve oral health among vulnerable RA patients.

Gene Polymorphisms LEP, LEPR, 5HT2A, GHRL, NPY, and FTO-Obesity Biomarkers in Metabolic Risk Assessment: A Retrospective Pilot Study in Overweight and Obese Population in Romania

Genome-wide association studies (GWAS) have successfully revealed numerous susceptibility loci for obesity. The PREDATORR study (2014) shows that in Romania, 346% of adults aged 20–79 y/o are overweight, and 31.4% are obese with a high risk of cardiometabolic complications, a number that puts almost 67% of Romania’s population in the abnormal weight group. Our study aims to investigate the current status of the genetic foundation in metabolic disease associated with obesity, applied to a pilot group of patients specifically examining the impact of known polymorphisms and their haplotype of six food intake-regulating genes, namely leptin (LEP), leptin receptor (LEP-R), serotonin receptor (5HTR2A), ghrelin (GHRL), neuropeptide Y (NPY), and fat-mass and obesity-associated protein (FTO) with the following polymorphisms: LEP A-2548G, LEPR A-223G, 5HTR2A G-1439A, GHRL G-72T, NPY T-29063C, FTO A-T, and body mass index (BMI). A notable link between the LEP-2548 rs7799039 gene’s AG genotype and the risk of obesity was observed, particularly pronounced in males aged 40–49, with an approximately seven-fold increased likelihood of obesity. The 5HTR2A rs6311 AA genotype was associated with a higher BMI, which was not statistically significant. The FTO rs9939609 gene’s AA genotype emerged as a significant predictor of obesity risk. Besides these significant findings, no substantial associations were observed with the LEPR, 5HTR2A, GHRL, and NPY genes. Haplotype association analysis showed a suggestive indication of GRGMLA (rs7799039, rs1137101, rs6311, rs696217, rs16139, rs9939609 sequence) haplotype with a susceptibility effect towards obesity predisposition. Linkage disequilibrium (LD) analysis showed statistically significant associations between LEP and LEPR gene (p = 0.04), LEP and GHRL gene (p = 0.0047), and GHRL and FTO gene (p = 0.03). Our study, to the best of our knowledge, is one of the very few on the Romanian population, and aims to be a starting point for further research on the targeted interventional strategies to reduce cardiometabolic risks.

Dissecting root system architecture traits in durum wheat–goatgrass (Triticum durum–Aegilops speltoides) backcross introgression lines

AbstractA well‐developed root system is essential for efficient nutrient and water uptake. We phenotyped a set of 172 Triticum durum–Aegilops speltoides backcross introgression lines (BILs) for various root architecture traits during 2019–2020 and 2020–2021 cropping seasons. The roots were sampled at the maximum tillering stage, and data on various root architecture traits were recorded. The quantitative trait loci (QTL) mapping was carried out using 5672 polymorphic SNPs obtained from genotyping‐by‐sequencing. A total of 21 QTLs were detected for various root architecture traits on chromosomes 1A, 2A, 2B, 3B, 5A and 6B. Stable QTLs were detected for total root length, number of root tips and root dry weight over the two seasons. Candidate genes were identified by scanning the physical interval corresponding to the linkage disequilibrium (LD) decay flanking the SNPs linked to the stable QTLs. In silico expression studies of postulated candidate genes revealed root‐specific upregulation of some of the genes. These QTLs can be used in breeding programmes after the development and validation of suitable marker assays.

Genetic control of root architectural traits under drought stress in spring barley (Hordeum vulgare L.).

Root architectural traits play pivotal roles in plant adaptation to drought stress, and hence they are considered promising targets in breeding programs. Here, we phenotyped eight root architecture traits in response to well-watered and drought stress conditions in 200 spring barley (Hordeum vulgare L.) inbred lines over two consecutive field seasons. Root architecture traits were less developed under drought in both seasons when compared with control treatments. Genetic variation in root architectural traits was dissected employing a genome-wide association study (GWAS) coupled with linkage disequilibrium mapping. GWAS uncovered a total of 186 significant single nucleotide polymorphism-trait associations for eight root traits under control, drought, and drought-related indices. Of these, a few loci for root traits were detected on chromosomes 3 and 5, which co-located with QTL identified in previous studies. Interestingly, 13 loci showed simultaneou associations with multiple root traits under drought and drought-related indices. These loci harbored candidate genes, which included a wide range of drought-responsive components such as transcription factors, binding proteins, protein kinases, nutrient and ion transporters, and stress signaling factors. For instance, two candidate genes, HORVU7Hr3G0713160 and HORVU6H r3G0626550, are orthologous to AtACX3 and AtVAMPs, which have reported functions in root length-mediated drought tolerance and as a key protein in abiotic stress tolerance, respectively. Interestingly, one of these loci underlying a high-confidence candidate gene NEW ENHANCER OF ROOT DWARFISM1 (NERD1) showed involvement with root development. An allelic variation of this locus in non-coding region was significantly associated with increased root length under drought. Collectively, these results offer promising multi-trait affecting loci and candidate genes underlying root phenotypic responses to drought stress, which may provide valuable resources for genetic improvement of drought tolerance in barley.

Associations between varicose veins and heart failure: A genetic correlation and mendelian randomization study.

Varicose veins and heart failure (HF) are increasingly prevalent. Although numbers of observational studies have indicated that varicose veins might contribute to the risk of HF, the causal relationship between them remains unclear due to the uncontrolled confounding factors and reverse causation bias. Therefore, this study aimed to explore the potential causal relationship between varicose veins and HF. Based on publicly released genome-wide association studies (GWAS), gene correlation was assessed using linkage disequilibrium score (LDSC) regression, and we conducted a two-sample Mendelian randomization (TSMR) analysis to infer the causal relationship. We performed the Inverse variance weighted (IVW) method as the primary analysis, and used Weighted median, MR-Egger, weighted mode, simple mode, and MR-pleiotropy residual sum and outlier (MR-PRESSO) methods to detect and correct for horizontal pleiotropy. LDSC revealed there was a positive genetic correlation between varicose veins and HF (rg = 0.1726184, Se = 0.04511803, P = .0001). The results of the IVW method indicated that genetically predicted varicose veins were associated with an increased risk of HF (odds ratio (OR) = 1.03; 95% confidence interval (CI): 1.01-1.06; P = .009). Our findings illustrated the significant causal effect of varicose veins on HF, suggesting that people with varicose veins might have a higher risk of HF. The results provided a novel and important perspective into the development mechanism of HF.

Genome-wide association analysis explores the genetic loci of amino acid content in duck’s breast muscle

BackgroundAmino acids are the basic components of protein and an important index to evaluate meat quality. With the rapid development of genomics, candidate regions and genes affecting amino acid content in livestock and poultry have been gradually revealed. Hence, genome-wide association study (GWAS) can be used to screen candidate loci associated with amino acid content in duck meat.ResultIn the current study, the content of 16 amino acids was detected in 358 duck breast muscles. The proportion of Glu to the total amino acid content was relatively high, and the proportion was 0.14. However, the proportion of Met content was relatively low, at just 0.03. By comparative analysis, significant differences were found between males and females in 3 amino acids, including Ser, Met, and Phe. In addition, 12 SNPs were significantly correlated with Pro content by GWAS analysis, and these SNPs were annotated by 7 protein-coding genes; 8 significant SNPs were associated with Tyr content, and these SNPs were annotated by 6 protein-coding genes. At the same time, linkage disequilibrium (LD) analysis was performed on these regions with significant signals. The results showed that three SNPs in the 55–56 Mbp region of chromosome 3 were highly correlated with the leader SNP (chr3:55526954) that affected Pro content (r2 > 0.6). Similarly, LD analysis showed that there were three SNPs in the 21.2–21.6 Mbp region of chromosome 13, which were highly correlated with leader SNP (chr13:21421661) (r2 > 0.6). Moreover, Through functional enrichment analysis of all candidate genes. The results of GO enrichment analysis showed that several significant GO items were associated with amino acid transport function, including amino acid transmembrane transport and glutamine transport. The results further indicate that these candidate genes are closely associated with amino acid transport. Among them, key candidate genes include SLC38A1. For KEGG enrichment analysis, CACNA2D3 and CACNA1D genes were covered by significant pathways.ConclusionIn this study, GWAS analysis found a total of 28 significant SNPs affecting amino acid content. Through gene annotation, a total of 20 candidate genes were screened. In addition, Through LD analysis and enrichment analysis, we considered that SERAC1, CACNA2D3 and SLC38A1 genes are important candidate genes affecting amino acid content in duck breast muscle.

Genetic predisposition to bone mineral density and their health conditions in East Asians.

Osteoporosis, a condition defined by low bone mineral density (BMD) (typically < -2.5 SD), cause a higher fracture risk and lead to significant economic, social, and clinical impacts. Genome-wide studies mainly in Caucasians have found many genetic links to osteoporosis, fractures, and BMD, with limited research in East Asians. We investigated the genetic aspects of BMD in 86,716 individuals from the Taiwan Biobank and their causal links to health conditions within East Asians. A genome-wide association study (GWAS) was conducted, followed by observational studies, polygenic risk score assessments, and genetic correlation analyses to identify associated health conditions linked to BMD. GWAS and gene-based GWAS studies identified 78 significant SNPs and 75 genes related to BMD, highlighting pathways like Hedgehog, WNT-mediated, and TGF-β. Our cross-trait linkage disequilibrium score regression analyses for BMD and osteoporosis consistently validated their genetic correlations with body mass index (BMI) and type 2 diabetes (T2D) in East Asians. Higher BMD was linked to lower osteoporosis risk but increased BMI and T2D, whereas osteoporosis linked to lower BMI, waist circumference, HbA1c, and reduced T2D risk. Bidirectional Mendelian randomization (MR) analyses revealed that a higher BMI causally increases BMD in East Asians. However, no direct causal relationships were found between BMD and T2D, or between osteoporosis and either BMI or T2D. This study identified key genetic factors for bone health in Taiwan, and revealed significant health conditions in East Asians, particularly highlighting the genetic interplay between bone health and metabolic traits like T2D and BMI.

Accuracy of genomic prediction using multiple Atlantic salmon populations

BackgroundThe accuracy of genomic prediction is partly determined by the size of the reference population. In Atlantic salmon breeding programs, four parallel populations often exist, thus offering the opportunity to increase the size of the reference set by combining these populations. By allowing a reduction in the number of records per population, multi-population prediction can potentially reduce cost and welfare issues related to the recording of traits, particularly for diseases. In this study, we evaluated the accuracy of multi- and across-population prediction of breeding values for resistance to amoebic gill disease (AGD) using all single nucleotide polymorphisms (SNPs) on a 55K chip or a selected subset of SNPs based on the signs of allele substitution effect estimates across populations, using both linear and nonlinear genomic prediction (GP) models in Atlantic salmon populations. In addition, we investigated genetic distance, genetic correlation estimated based on genomic relationships, and persistency of linkage disequilibrium (LD) phase across these populations.ResultsThe genetic distance between populations ranged from 0.03 to 0.07, while the genetic correlation ranged from 0.19 to 0.99. Nonetheless, compared to within-population prediction, there was limited or no impact of combining populations for multi-population prediction across the various models used or when using the selected subset of SNPs. The estimates of across-population prediction accuracy were low and to some extent proportional to the genetic correlation estimates. The persistency of LD phase between adjacent markers across populations using all SNP data ranged from 0.51 to 0.65, indicating that LD is poorly conserved across the studied populations.ConclusionsOur results show that a high genetic correlation and a high genetic relationship between populations do not guarantee a higher prediction accuracy from multi-population genomic prediction in Atlantic salmon.

HiChIP-based Epigenomic Footprinting Identifies a Promoter Variant of UXS1 that Confers Genetic Susceptibility to Gastroesophageal Cancer.

Genome-wide association studies (GWAS) have identified more than a hundred single nucleotide variants (SNVs) associated with the risk of gastroesophageal cancer (GEC). The majority of the identified SNVs map to noncoding regions of the genome. Uncovering the causal SNVs and the genes they modulate could help improve GEC prevention and treatment. Here, we used HiChIP against histone 3 lysine 27 acetylation (H3K27ac) to simultaneously annotate active promoters and enhancers, identify the interactions between them, and detect nucleosome free regions (NFRs) harboring potential causal SNVs in a single assay. Application of H3K27Ac HiChIP in GEC relevant models identified 61 potential functional SNVs that reside in NFRs and interact with 49 genes at 17 loci. The approach led to a 67% reduction in the number of SNVs in linkage disequilibrium at these 17 loci, and at seven loci a single putative causal SNV was identified. One SNV, rs147518036, located within the promoter of the UDP-glucuronate decarboxylase 1 (UXS1) gene appeared to underlie the GEC risk association captured by the rs75460256 index SNV. The rs147518036 SNV creates a GABPA DNA recognition motif, resulting in increased promoter activity, and CRISPR-mediated inhibition of the UXS1 promoter reduced viability of GEC cells. These findings provide a framework that simplifies the identification of potentially functional regulatory SNVs and target genes underlying risk-associated loci. In addition, the study implicates increased expression of the enzyme UXS1 and activation of its metabolic pathway as a predisposition to gastric cancer, which highlights potential therapeutic avenues to treat this disease.