Linkage Disequilibrium Research Articles

Genetic association and causal effects between inflammatory bowel disease and conjunctivitis.

Inflammatory bowel disease (IBD) is often clinically associated with conjunctivitis, which may result from genetic associations and causal effects. Genetic correlations were investigated through the genome-wide association study (GWAS) data on IBD and conjunctivitis using the linkage disequilibrium score regression (LDSC) and heritability estimated in summary statistics (HESS). The causal effect analysis was performed using four methods of Mendelian randomization (MR) and the genetic risk loci common to both diseases were identified by the statistical method of conditional/conjoint false discovery rate (cond/conjFDR), followed by genetic overlap analysis. Finally, a multi-trait GWAS analysis (MTAG) was performed to validate the identified shared loci. IBD (including CD and UC) and conjunctivitis showed a significant overall correlation at the genomic level; however, the local correlation of IBD and CD with conjunctivitis was significant and limited to chromosome 11. MR analysis suggested a significant positive and non-significant negative correlation between IBD (including CD and UC) and conjunctivitis. The conjFDR analysis confirmed the genetic overlap between the two diseases. Additionally, MTAG was employed to identify and validate multiple genetic risk loci. The present study provides evidence of genetic structure and causal effects for the co-morbidity between IBD (both CD and UC) and conjunctivitis, expanding the epidemiologic understanding of the two diseases.

Hypothyroidism and dermato/polymyositis: a two-sample Mendelian randomization study.

Observational studies have revealed a higher probability of hypothyroidism in patients with dermatomyositis (DM) or polymyositis (PM), but there is no consensus on whether hypothyroidism causally influences DM or PM. In the present study, we assessed the causal association between hypothyroidism and the risk of dermatomyositis or polymyositis using two-sample Mendelian randomization (TSMR). The genome-wide association data of hypothyroidism and dermatomyositis/polymyositis were obtained from the IEU Open GWAS project. Then, TSMR was used to determine whether hypothyroidism is causally associated with DM or PM. Single-nucleotide polymorphisms (SNPs) significantly associated with hypothyroidism were identified and used as instrumental variables (IVs), and the causal relationship between hypothyroidism and DM/PM was examined using TSMR. MR pleiotropy and Cochran's Q test were used to confirm the heterogeneity and pleiotropy of identified IVs, then four different models, including the inverse variance weighted model (IVW), MR-Egger, weighted median and weighted model were applied in this MR analysis. Sixty-eight SNPs for DM and 68 SNPs for PM were selected as the IVs (P<5×10-8; linkage disequilibrium R2 <0.001) to assess the causal association between hypothyroidism and DM/PM selected from GWASs on hypothyroidism. The results revealed a positive causal effect of hypothyroidism on both DM and PM (DM: OR 2.563, 95% CI [1.348, 4.874], P = 0.00156; PM: OR1.709, 95% CI [1.157, 2.525], P =0.007). Moreover, there was no heterogeneity or pleiotropy in the results. In conclusion, the MR analysis results provided strong evidence to indicate that hypothyroidism might be causally associated with DM and PM. These findings may have important implications for the pathogenesis and possible future therapies of DM/PM.

Effect of Chromosomal Localization of NGS-Based Markers on Their Applicability for Analyzing Genetic Variation and Population Structure of Hexaploid Triticale.

This study aimed to determine whether using DNA-based markers assigned to individual chromosomes would detect the genetic structures of 446 winter triticale forms originating from two breeding companies more effectively than using the entire pool of markers. After filtering for quality control parameters, 6380 codominant single nucleotide polymorphisms (SNPs) markers and 17,490 dominant diversity array technology (silicoDArT) markers were considered for analysis. The mean polymorphic information content (PIC) values varied depending on the chromosomes and ranged from 0.30 (2R) to 0.43 (7A) for the SNPs and from 0.28 (2A) to 0.35 (6R) for the silicoDArTs. The highest correlation of genetic distance (GD) matrices based on SNP markers was observed among the 5B-5R (0.642), 5B-7B (0.626), and 5A-5R (0.605) chromosomes. When silicoDArTs were used for the analysis, the strongest correlations were found between 5B-5R (0.732) and 2B-5B (0.718). A Bayesian analysis showed that SNPs (total marker pool) allowed for the identification of a more complex structure (K = 4, ΔK = 2460.2) than the analysis based on silicoDArTs (K = 2, ΔK = 128). Triticale lines formed into groups, ranging from two (most of the chromosomes) to four (7A) groups depending on the analyzed chromosome when SNP markers were used for analysis. Linkage disequilibrium (LD) varied among individual chromosomes, ranging from 0.031 for 1A to 0.228 for 7R.

Gene-based association analysis of a large patient cohort provides insights into genetics of atypical femur fractures.

Several small genetic association studies have been conducted for atypical femur fracture (AFF) without replication of results. We assessed previously implicated and novel genes associated with AFFs in a larger set of unrelated AFF cases using whole exome sequencing (WES). We performed gene-based association analysis on 139 European AFF cases and 196 controls matched for bisphosphonate use. We tested all rare, protein-altering variants using both candidate gene and hypothesis-free approaches. In the latter, genes suggestively associated with AFFs (uncorrected p-values <.01) were investigated in a Swedish whole-genome sequencing replication study and assessed in 46 non-European cases. In the candidate gene analysis, PLOD2 showed a suggestive signal. The hypothesis-free approach revealed 10 tentative associations, with XRN2, SORD, and PLOD2 being the most likely candidates for AFF. XRN2 and PLOD2 showed consistent direction of effect estimates in the replication analysis, albeit not statistically significant. Three SNPs associated with SORD expression according to the GTEx portal were in linkage disequilibrium (R2 ≥ 0.2) with an SNP previously reported in a genome-wide association study of AFF. The prevalence of carriers of variants for both PLOD2 and SORD was higher in Asian versus European cases. While we did not identify genes enriched for damaging variants, we found suggestive evidence of a role for XRN2, PLOD2, and SORD, which requires further investigation. Our findings indicate that genetic factors responsible for AFFs are not widely shared among AFF cases. The study provides a stepping-stone for future larger genetic studies of AFF.

Linkage equilibrium between rare mutations.

Recombination breaks down genetic linkage by reshuffling existing variants onto new genetic backgrounds. These dynamics are traditionally quantified by examining the correlations between alleles, and how they decay as a function of the recombination rate. However, the magnitudes of these correlations are strongly influenced by other evolutionary forces like natural selection and genetic drift, making it difficult to tease out the effects of recombination. Here we introduce a theoretical framework for analyzing an alternative family of statistics that measure the homoplasy produced by recombination. We derive analytical expressions that predict how these statistics depend on the rates of recombination and recurrent mutation, the strength of negative selection and genetic drift, and the present-day frequencies of the mutant alleles. We find that the degree of homoplasy can strongly depend on this frequency scale, which reflects the underlying timescales over which these mutations occurred. We show how these scaling properties can be used to isolate the effects of recombination, and discuss their implications for the rates of horizontal gene transfer in bacteria.

Whole-genome re-sequencing reveals genetic structure and selection signals of different populations in Megalobrama amblycephala

Characterization of genetic variants is crucial for understanding the molecular mechanisms behind selected traits and enhancing the rate of genetic gain through artificial selection. This study explored the genetic diversity and population structure of blunt snout bream Megalobrama amblycephala, a key freshwater fish in Chinese aquaculture. We conducted whole-genome re-sequencing of individuals from six populations, comprising three natural and three genetically improved strains, to assess genetic diversity, population structure and the impacts of selective breeding. We identified 17,009,590 high-quality biallelic single nucleotide polymorphism (SNP) loci. Genetic diversity assessments revealed low levels of polymorphism across populations, with genetically improved strains showing moderate to high genetic differentiation from their source populations. The study also highlighted runs of homozygosity (ROH) and analyzed linkage disequilibrium (LD) decay, indicating minimal recent inbreeding and diverse recombination events among populations. Selective sweep analyses uncovered significant selection loci associated with growth and hypoxia tolerance traits. Enrichment analyses identified genes involved in olfactory signal transduction, immune response, and metabolism pathways, which are closely related to these selective traits. These findings offer insights into the genetic basis of critical traits in M. amblycephala, contributing to the conservation of germplasm resources and supporting ongoing selective breeding efforts.

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

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

Dealing With Assumptions and Sampling Bias in the Estimation of Effective Population Size: A Case Study in an Amphibian Population.

Accurately estimating effective population size (N e) is essential for understanding evolutionary processes and guiding conservation efforts. This study investigates N e estimation methods in spatially structured populations using a population of moor frog (Rana arvalis) as a case study. We assessed the behaviour of N e estimates derived from the linkage disequilibrium (LD) method as we changed the spatial configuration of samples. Moor frog eggs were sampled from 25 breeding patches (i.e., separate vernal ponds, ditches or parts of larger fens) within a single population, revealing an isolation-by-distance pattern and a local spatial genetic structure. Varying buffer sizes around each patch were used to examine the impact of sampling window size on the estimation of effective number of breeders (N b). Our results indicate a downward bias in LD N b estimates with increasing buffer size, suggesting an underestimation of N b. The observed bias is attributed to LD resulting from including genetically divergent individuals (mixture-LD) confounding LD due to drift. This emphasises the significance of considering even subtle spatial genetic patterns. The implications of these findings are discussed, emphasising the need to account for spatial genetic structure to accurately assess population viability and inform conservation efforts. This study contributes to our understanding of the challenges associated with N e estimation in spatially structured populations and underscores the importance of refining methodologies to address population-specific spatial dynamics for effective conservation planning and management.

Causal relationship between Brugada syndrome and electrocardiogram traits: A bidirectional Mendelian randomization study

IntroductionObservational studies have suggested associations between Brugada syndrome (BrS) and electrocardiograms traits. Nonetheless, the causal relationships remains uncertain in observational studies. This study aims to investigate the causal relationships between BrS phenotypic risk and electrocardiogram traits using Mendelian randomization (MR) analysis and colocalization analysis. MethodsMR analysis was performed to investigate the causal relationships between BrS phenotype risk and electrocardiogram traits (P wave duration, PR interval, QRS wave duration, ST segment duration, T wave duration, QT interval, heart rate (HR) and heart rate variability). The genetic instruments for BrS (number of cases = 12,821) were obtained from the latest GWAS. GWAS summary data of electrocardiogram traits were obtained from the MRC-IEU and GWAS catalog databases. The causal relationships were obtained through MR methods, and sensitivity analyses (e.g. Cochran's Q test, MR-PRESSO). Furthermore, the causal relationships were evaluated whether they were driven by one linkage disequilibrium using colocalization analysis. ResultsWe found that there are positive causal relationships between BrS phenotypic risk and P wave duration, PR interval, QRS wave duration and QT interval, respectively (IVWP: β = 1.238, 95 % CI = 0.857–1.619, P<0.001; IVWPR: β = 2.199, 95 % CI = 1.358–3.039, P<0.001; IVWQRS: β = 0.157, 95 % CI = 0.115–0.198, P<0.001; IVWQT: β = 0.593, 95 % CI = 0.391–0.796, P<0.001), and there is a negative causal relationship between BrS phenotypic risk and heart rate (IVWHR: β = −0.023, 95 % CI = −0.03 ~ −0.015, P<0.001). Additionally, there are bidirectional causal relationships between BrS phenotypic risk and P wave duration and PR interval, respectively (IVWP: OR = 1.217, 95 % CI = 1.118–1.325, P<0.001; IVWPR: OR = 1.02, 95 % CI = 1.008–1.032, P = 0.001). Furthermore, colocalization analysis identified that the causal relationships between BrS phenotype risk and P wave duration, PR interval and QRS wave duration were driven by rs6790396, rs6801957 and rs6801957, respectively. ConclusionsBidirectional causal relationships were identified between BrS phenotypic risk and P wave duration and PR interval, respectively. There were positive causal relationships between BrS phenotypic risk and QRS wave duration and QT interval, respectively, and there is a negative causal relationship between BrS phenotypic risk and heart rate.

Haplotype-Aware Detection of SERPINA1 Variants by Nanopore Sequencing

Alpha-1 antitrypsin (AAT) is an acute-phase reactant with immunomodulatory properties that mainly inhibits neutrophil elastase. Low serum levels cause AAT deficiency (AATD), an underdiagnosed condition that predisposes to pulmonary and hepatic diseases. The SERPINA1 gene, which encodes AAT, contains more than 500 variants. PI*Z and PI*S alleles are the most diagnosed causes of AATD, but the role of the SERPINA1 haplotypes in AAT function remains unknown. SERPINA1 gene was PCR amplified from 94 asthma patients, using primers with tails for indexing. Sequencing libraries were loaded into a MinION-Mk1C, and MinKNOW was used for basecalling and demultiplexing. Nanofilt and Minimap2 were used for filtering and mapping/alignment. Variant calling/phasing were performed with PEPPER-Margin-DeepVariant. SERPINA1 gene was 100% covered for all samples, with a minimum sequencing depth of 500X. 75 single nucleotide variants and 4 indels were detected, with 45 and 2 of them highly polymorphic (MAF>0.1), respectively. Nine of the SNVs showed differences in allele frequencies when compared with the overall Spanish population. More than 90% of heterozygous SNVs were phased, yielding 91 and 58 different haplotypes for each SERPINA1 amplified region. Haplotype-based Linkage Disequilibrium (LD) analysis suggests that a recombination hotspot could generate variation in the SERPINA1 gene. The proposed workflow enables haplotype-aware genotyping of the SERPINA1 gene by nanopore sequencing, which will allow the development of novel AATD diagnostic strategies.

Causality of Genetically Determined Metabolites on Chronic Kidney Disease: A Two-Sample Mendelian Randomization Study In Silico.

Introduction: Chronic kidney disease (CKD) is associated with metabolic disorders. However, the evidence for the causality of circulating metabolites to promote or prevent CKD is still lacking. Methods: The two-sample Mendelian randomization (MR) analysis was conducted to evaluate the latent causal relationship between the genetically proxied 486 blood metabolites and CKD. Genome-wide association study (GWAS) data for exposures were derived from 7824 European GWAS on metabolite levels, which have been extensively utilized in the medical field to elucidate the mechanisms underlying disease onset and progression. The random inverse variance weighted (IVW) is the primary analysis for causality analysis while MR-Egger and weighted median as complementary analyses. For the further identification of metabolites, reverse MR and linkage disequilibrium score regression were performed for further evaluation. The drug target for N-acetylornithine was subsequently supplemented into the analysis, with MR and colocalization analysis being utilized. Key metabolic pathways were identified via MetaboAnalyst 4.0 (https://www.metaboanalyst.ca/) online website. Results: N-acetylornithine was identified as a reliable metabolite that increases the susceptibility to estimated glomerular filtration rate (eGFR) decrease (β = 0.047; 95% confidence interval: -0.068 to -0.026; PIVW = 1.5E-5). The "glyoxylate and dicarboxylate metabolism" pathway showed significant relevance to CKD development (P = 6E-4), whereas the "glycine, serine, and threonine metabolism" pathway was also recognized as associated with CKD by general practitioners (P = 7E-4). Colocalization analysis revealed a robust genetic link between N-acetylornithine and both CKD and eGFR, with 85.1% and 99.4% colocalization rates, respectively. IVW-MR analysis substantiated these findings with a significant positive association for CKD (odds ratio = 1.43, P = 4.7E-5) and a negative correlation with eGFR (b = -0.04, P = 1.13E-31). Conclusions: MR was utilized to explore the potential causal links between 61 genetic serum metabolites and CKD. N-acetylornithine and NAT8 were further explored as a potential therapeutic target for CKD treatment.

Genome Wide Association Studies for milk production traits in two autochthonous Aosta cattle breeds

Genome wide association studies (GWAS) are used to identify quantitative trait loci for phenotypic traits of interest. The use of multi-locus mixed models allows to correct for population stratification and account for long-range linkage disequilibrium. In this study, GWAS were conducted to identify the genetic bases of milk production (milk yield, protein and fat composition, and yield) in two autochthonous dual-purpose cattle breeds from the Aosta Valley. Using either the breeding values or the deregressed proofs, common significative Single Nucleotide Polymorphisms (SNPs) have been identified for milk yield, protein percentage, and fat percentage. Two major quantitative trait loci (QTL) regions have been identified on the chromosome 5 and 14 for the fat percentage, harbouring the MGST1, CYHR1, VPS28, and CPSF1 genes. For the protein percentage, a candidate region has been identified on BTA 6; in this region the CSN1S1, CSN2, HSTN, CSN3, and RUFY3 genes are annotated. Most of the identified genes have already been associated with milk composition in other studies on cosmopolitan and local cattle. These results show that the genes involved in milk composition quantitative traits in the Aosta cattle are common also in other cattle breeds and they can be further investigated with the use of whole genome sequencing data.

Causal relationship between genetically determined plasma metabolites and stroke: A two sample Mendelian randomization study

IntroductionThis study investigates the causal relationship between plasma metabolites and stroke. MethodThe primary analytical approach employed was the inverse variance weighted (IVW) method, complemented by the weighted median (WM) and MR Egger methods for Additionally, validation of the identified plasma metabolites was performed using the Steiger test and LD linkage disequilibrium score. Furthermore, the main results were confirmed through data from the UK Biobank. ResultThe IVW analysis revealed the most notable negative association found in X-17335 levels (OR [95 % CI]: 0.82 [0.72, 0.94]). On the other hand, the strongest positive effect was seen in the 5′-homophase (AMP) to phase ratio (OR [95 % CI]: 1.17 [1.03, 1.32]). Moving on to the validation dataset, the most significant positive effect was observed in the 13 HODE+9-HODE levels (OR [95 % CI]: 0.996 [0.993, 0.999]), whereas the most significant negative effect was seen in the Dihydroxide levels (OR [95 % CI]: 1.004 [1.00, 1.007]). Notably, Alpha ketoglutarate levels exhibited strong causal effects in both datasets (OR 0.908 [0.841, 0.981], p = 0.0144). Enrichment analysis highlighted the association of Alpha ketoglutarate levels with five plasma metabolites in metabolic pathways relevant to stroke, specifically Arginine biosynthesis, Butanoate metabolism, Citrate cycle (TCA cycle), Alanine, aspartate, and glutamate metabolism, and Lipid acid metabolism, all linked to oxoglutaric acid. ConclusionThe discovery dataset showed the most significant positive effect of the 5′-homophase (AMP) to phase ratio, while the validation dataset revealed the most significant positive effect of the 13 HODE+9-HODE levels. Additionally, alpha ketoglutarate may offer a potential protective effect on stroke by influencing five metabolic pathways that intersect with Oxoglutaric acid during the progression of the condition.

Causal association between epilepsy and its DNA methylation profile and atrial fibrillation

BackgroundThe "epileptic heart" concept is emerging, but the causal relationship between epilepsy and atrial fibrillation (AF) remains unclarified. ObjectiveThis study explores the genetic correlations and bidirectional causality between various epilepsy phenotypes and AF. MethodsGenome-wide association study (GWAS) statistics for 10 epilepsy subtypes (29,944 cases, 52,538 controls) and AF (60,620 cases, 970,216 controls) were sourced from the International League Against Epilepsy (ILAE) and HGRI-EBI Catalog-GWAS, respectively. Linkage disequilibrium score regression (LDSC) and genome-wide Mendelian Randomization (MR) evaluated genetic correlations and bidirectional causal relationships. Epilepsy-related DNA methylation data (N= ∼800) from EWAS catalog were analyzed to identify causal CpG sites influencing AF risk through epigenetic MR. ResultsLDSC revealed significant genetic correlations between four epilepsy subtypes and AF (rg from 0.116 to 0.241). Forward MR suggested a significant causal effect of focal epilepsy with hippocampal sclerosis (FE with HS) on AF risk (IVW and MR-PRESSO: OR = 1.046, P ≤ 0.004), with results robust against heterogeneity, horizontal pleiotropy, and outliers. Epigenetic MR indicated that lower methylation at cg06222062 (OR = 0.994, P = 3.16E-04) mapped to PLA2G5 and cg08461451 mapped to SPPL2B gene (OR = 0.954, P = 1.19E-03), and higher cg10541930 in the C10orf143 promoter (OR = 1.043, P = 4.18E-22) increases AF risk. Sensitivity analyses affirmed no pleiotropic bias. ConclusionFE with HS significantly increases AF risk, highlighting the natural neural-cardiac connection and the need for cardiac monitoring in epilepsy patients. Specific methylated CpG sites may serve as biomarkers and preventive targets for AF susceptibility.

Whole genome re-sequencing reveals high altitude adaptation signatures and admixture in Ladakhi cattle

Ladakhi cattle, native to the high-altitude region of Ladakh in northern India (ranging from 3,000 to 5,000 m above sea level), have evolved unique genetic adaptations to thrive in harsh environmental conditions, such as hypoxia, extreme cold, and low humidity. This study explored the genome of Ladakhi cattle to investigate genetic structure, selection signatures, and adaptive mechanisms. Whole genome sequencing reads, generated on Illumina NovaSeq 6000 platform, were aligned to the Bos taurus reference genome with BWA-MEM. SNPs were identified and filtered using GATK and bcftools, and functionally annotated with SnpEff. For population genomic analysis, PCA and admixture modeling assessed genetic structure, while Neighbor-Joining trees, LD decay, nucleotide diversity (π), and FST evaluated phylogenetic relationships and genetic variation. Selective sweeps were detected using RAiSD, and gene-set enrichment and protein–protein interaction analyses were conducted to explore functional pathways related to adaptation. The study revealed 3,759,279 unique SNPs and demonstrated that Ladakhi cattle form a distinct genetic cluster with an estimated admixture of 68 % Bos indicus and 32 % Bos taurus ancestry. Key findings include rapid linkage disequilibrium decay, low inbreeding level, and the identification of selection signatures and genes associated with hypoxia response, energy metabolism, and cold adaptation. Mean nucleotide diversity (π, 0.0037) and FST values indicated moderate genetic differentiation from other breeds. The analysis highlighted selection signatures for genes like HIF1A, ENO4, ANGPT1, EPO, NOS3, MAPK3, HMOX1, BCL2,CAMK2D, MTOR, AKT2,PIK3CB, and MAP2K1, among others, including various keratin and heat shock proteins. The interaction between genes associated with hypoxia signaling (HIF-1) and other enriched pathways such as PI3K, mTOR, NFκB, ERK, and ER stress, reveals a complex mechanism for managing hypoxic stress in Ladakhi cattle. These findings offer valuable insights for breeding programs aimed at enhancing livestock resilience in extreme environments and enhance understanding of mammalian adaptation to high-altitude conditions.

Association Study of 3-untranslated region Haplotype of Human leukocyte antigen-G Gene with Lupus.

Background: Human leukocyte antigen-G (HLA-G) is a pivotal protein involved in immune regulation and tolerance, while systemic lupus erythematosus (SLE) is a multifaceted autoimmune condition influenced by genetic and environmental factors. Research indicates that variations and mutations in HLA-G may impact SLE development. Objective: This study aimed to explore the relationship between polymorphisms in the 3'-untranslated region (UTR) of the HLA-G gene and SLE. Methods: DNA from 100 SLE patients and 100 controls was analyzed using polymerase chain reaction to amplify the target sequence. Allele and genotype frequencies were determined, and haplotypes were assessed using Haploview v.4.2 software, with linkage disequilibrium calculated. Results: Findings revealed that the +2960 Ins allele was significantly linked to SLE as a risk factor, with the Del allele showing a protective effect. In addition, the +3010C allele and +3187A allele were significantly associated with SLE at both allele and genotype levels. The +3142 GG homozygote was notably linked to SLE at the genotype level. Haplotype analysis identified UTR-2 haplotypes as risk factors for SLE, whereas the UTR-1 haplotype was protective, shedding light on genetic factors influencing SLE risk. Conclusion: This study underscores the importance of HLA-G gene 3'-UTR polymorphisms in SLE susceptibility, suggesting their potential as diagnostic or therapeutic targets.

Joint identity among loci under mutation and regular inbreeding

This study describes a compact method for determining joint probabilities of identity-by-state (IBS) within and between loci in populations evolving under genetic drift, crossing-over, mutation, and regular inbreeding (partial self-fertilization). Analogues of classical indices of associations among loci arise as functions of these joint identities. This coalescence-based analysis indicates that multi-locus associations reflect simultaneous coalescence events across loci. Measures of association depend on genetic diversity rather than allelic frequencies, as do linkage disequilibrium and its relatives. Scaled indices designed to show monotonic dependence on rates of crossing-over, inbreeding, and mutation may prove useful for interpreting patterns of genome-scale variation.

Genetic analysis from multiple cohorts implies causality between 2200 druggable genes, telomere length, and leukemia

BackgroundClinical therapeutic targets for leukemia remain to be identified and the causality between leukemia and telomere length is unclear. MethodsThis work employed cis expression quantitative trait locus (eQTL) for 2,200 druggable genes from the eQTLGen Consortium and genome-wide association studies (GWAS) summary data for telomere length in seven blood cell types from the UK Biobank, Netherlands Cohort as exposures. GWAS data for lymphoid leukemia (LL) and myeloid leukemia (ML) from FinnGen and Lee Lab were used as outcomes for discovery and replication cohorts, respectively. Robust Mendelian randomization (MR) findings were generated from seven MR models and a series of sensitivity analyses. Summary-data-based MR (SMR) analysis and transcriptome-wide association studies (TWAS) were further implemented to verify the association between identified druggable genes and leukemia. Single-cell type expression analysis was employed to identify the specific expression of leukemia casual genes on human bone marrow and peripheral blood immune cells. Multivariable MR analysis, linkage disequilibrium score regression (LDSC), and Bayesian colocalization analysis were performed to further validate the relationship between telomere length and leukemia. Mediation analysis was used to assess the effects of identified druggable genes affecting leukemia via telomere length. Phenome-wide MR (Phe-MR) analysis for assessing the effect of leukemia causal genes and telomere length on 1,403 disease phenotypes. ResultsCombining the results of the meta-analysis for MR estimates from two cohorts, SMR and TWAS analysis, we identified five LL causal genes (TYMP, DSTYK, PPIF, GDF15, FAM20A) and three ML causal genes (LY75, ADA, ABCA2) as promising drug targets for leukemia. Univariable MR analysis showed genetically predicted higher leukocyte telomere length increased the risk of LL (odds ratio [OR] = 2.33, 95 % confidence interval [95 % CI] 1.70–3.18; P = 1.33E-07), and there was no heterogeneity and horizontal pleiotropy. Evidence from the meta-analysis of two cohorts strengthened this finding (OR = 1.88, 95 % CI 1.06–3.05; P = 0.01). Multivariable MR analysis showed the causality between leukocyte telomere length and LL without interference from the other six blood cell telomere length (OR = 2.72, 95 % CI 1.88–3.93; P = 1.23E-07). Evidence from LDSC supported the positive genetic correlation between leukocyte telomere length and LL (rg = 0.309, P = 0.0001). Colocalization analysis revealed that the causality from leukocyte telomere length on LL was driven by the genetic variant rs770526 in the TERT region. The mediation analysis via two-step MR showed that the causal effect from TYMP on LL was partly mediated by leukocyte telomere length, with a mediated proportion of 12 %. ConclusionOur study identified several druggable genes associated with leukemia risk and provided new insights into the etiology and drug development of leukemia. We also found that genetically predicted higher leukocyte telomere length increased LL risk and its potential mechanism of action.

Identifying the physiological traits associated with DNA marker using genome wide association in wheat under heat stress

Heat stress poses a significant environmental challenge that profoundly impacts wheat productivity. It disrupts vital physiological processes such as photosynthesis, by impeding the functionality of the photosynthetic apparatus and compromising plasma membrane stability, thereby detrimentally affecting grain development in wheat. The scarcity of identified marker trait associations pertinent to thermotolerance presents a formidable obstacle in the development of marker-assisted selection strategies against heat stress. To address this, wheat accessions were systematically exposed to both normal and heat stress conditions and phenotypic data were collected on physiological traits including proline content, canopy temperature depression, cell membrane injury, photosynthetic rate, transpiration rate (at vegetative and reproductive stage and ‘stay-green’. Principal component analysis elucidated the most significant contributors being proline content, transpiration rate, and canopy temperature depression, which exhibited a synergistic relationship with grain yield. Remarkably, cluster analysis delineated the wheat accessions into four discrete groups based on physiological attributes. Moreover, to explore the relationship between physiological traits and DNA markers, 158 wheat accessions were genotyped with 186 SSRs. Allelic frequency and polymorphic information content value were found to be highest on genome A (4.94 and 0.688), chromosome 1A (5.00 and 0.712), and marker Xgwm44 (13.0 and 0.916). Population structure, principal coordinate analysis and cluster analysis also partitioned the wheat accessions into four subpopulations based on genotypic data, highlighting their genetic homogeneity. Population diversity and presence of linkage disequilibrium established the suitability of population for association mapping. Additionally, linkage disequilibrium decay was most pronounced within a 15–20 cM region on chromosome 1A. Association mapping revealed highly significant marker trait associations at Bonferroni correction P < 0.00027. Markers Xwmc418 (located on chromosome 3D) and Xgwm233 (chromosome 7A) demonstrated associations with transpiration rate, while marker Xgwm494 (chromosome 3A) exhibited an association with photosynthetic rates at both vegetative and reproductive stages under heat stress conditions. Additionally, markers Xwmc201 (chromosome 6A) and Xcfa2129 (chromosome 1A) displayed robust associations with canopy temperature depression, while markers Xbarc163 (chromosome 4B) and Xbarc49 (chromosome 5A) were strongly associated with cell membrane injury at both stages. Notably, marker Xbarc49 (chromosome 5A) exhibited a significant association with the 'stay-green' trait under heat stress conditions. These results offers the potential utility in marker-assisted selection, gene pyramiding and genomic selection models to predict performance of wheat accession under heat stress conditions.

Prediction of additive genetic variances of descendants for complex families based on Mendelian sampling variances.

The ability to predict the outcome of selection and mating decisions enables breeders to make strategically better selection decisions. To improve genetic progress, those individuals need to be selected whose offspring can be expected to show high genetic variance next to high breeding values. Previously published approaches enable to predict the variance of descendants of two future generations for up to 4 founding haplotypes, or 2 outbred individuals, based on phased genotypes, allele effects and recombination frequencies. The purpose of this study was to develop a general approach for the analytical calculation of the genetic variance in any future generation. The core development is an equation for the prediction of the variance of double haploid lines, under the assumption of no selection and negligible drift, stemming from an arbitrary number of founder haplotypes. This double haploid variance can be decomposed into gametic Mendelian sampling variances (MSV) of ancestors of the double haploid lines allowing usage for non-double haploid genotypes which enables application in animal breeding programs as well as in plant breeding programs. Together with the breeding values of the founders, the gametic MSV may be used in new selection criteria. We present our idea of such a criterion that describes the genetic level of selected individuals in four generations. Since breeding programs do select, the assumption made for predicting variances is clearly violated which decreases the accuracy of predicted gametic MSV caused by changes in allele frequency and linkage disequilibrium. Despite violating the assumption, we found high predictive correlations of our criterion to the true genetic level which was obtained by means of simulation for the "corn" and "cattle" genome models tested in this study (0.90 and 0.97). In practice, the genotype phases, genetic map and allele effects all need to be estimated meaning inaccuracies in their estimation will lead to inaccurate variance prediction. Investigation of variance prediction accuracy when input parameters are estimated was not part of this study.