One Hundred Years of Linkage Disequilibrium

The wildcat (Felis s. silvestris) in the Mediterranean forest: sighting through photo-trapping and non-invasive hair collection for genetic purposes

The European wildcat (Felis silvestris silvestris) is a mesocarnivore species widely distributed in Europe, from Eastern Europe to Portugal and from Scotland to Italy. Recent biogeographical studies of wildcat populations have endeavoured to assess in detail the various issues that pose a threat to this species, including hybridization with domestic cats. The use of non-invasive sampling methods supported by photo-trapping and some attractants has made it possible to gather genetic material for the detection of native wildcats in locally threatened populations, some of which live in the Iberian Peninsula. Testimonies of naturalists, hunters and farm workers led our team to choose specific areas in two large territories of Mediterranean forests where the presence of wildcats has been historically attested: the Almonte River basin and the Sierra de San Pedro Mountains. Between 2014 and 2018, non-invasive hair sampling was performed using valerian (Valeriana officinalis) as an attractant and supported by photo-trapping to guarantee the collection of genuine biological material (hair samples). The hair samples were genetically assessed by sequencing the nuclear gene IRBP (interphotoreceptor retinoid-binding protein) and the mtDNA gene ND4 (NADH dehydrogenase subunit 4). Despite the low density of wildcats, this combined protocol proved to be an applicable tool for detecting the presence of elusive wildcats and other mesocarnivore species in this remote region of southern Europe. In addition, non-invasive hair trapping contributes to the collection of genetic material from current wildcat populations. This procedure could enhance future management actions focused on collecting quality individualized biological material.

Effective population size in field pea

BACKGROUND

Effective population size (Ne) is a pivotal parameter in population genetics as it can provide information on the rate of inbreeding and the contemporary status of genetic diversity in breeding populations. The population with smaller Ne can lead to faster inbreeding, with little potential for genetic gain making selections ineffective. The importance of Ne has become increasingly recognized in plant breeding, which can help breeders monitor and enhance the genetic variability or redesign their selection protocols. Here, we present the first Ne estimates based on linkage disequilibrium (LD) in the pea genome.

RESULTS

We calculated and compared Ne using SNP markers from North Dakota State University (NDSU) modern breeding lines and United States Department of Agriculture (USDA) diversity panel. The extent of LD was highly variable not only between populations but also among different regions and chromosomes of the genome. Overall, NDSU had a higher and longer-range LD than the USDA that could extend up to 500 Kb, with a genome-wide average r2 of 0.57 (vs 0.34), likely due to its lower recombination rates and the selection background. The estimated Ne for the USDA was nearly three-fold higher (Ne = 174) than NDSU (Ne = 64), which can be confounded by a high degree of population structure due to the selfing nature of pea.

CONCLUSIONS

Our results provided insights into the genetic diversity of the germplasm studied, which can guide plant breeders to actively monitor Ne in successive cycles of breeding to sustain viability of the breeding efforts in the long term.

Plasma metabolites as mediators in immune cell-pancreatic cancer risk: insights from Mendelian randomization

Background

Immune cells play a crucial role in the development and progression of pancreatic cancer, yet the causal relationship remains uncertain due to complex immune microenvironments and conflicting research findings. Mendelian randomization (MR), this study aims to delineate the causal relationships between immune cells and pancreatic cancer while identifying intermediary factors.

Methods

The genome-wide association study (GWAS) data on immune cells, pancreatic cancer, and plasma metabolites are derived from public databases. In this investigation, inverse variance weighting (IVW) as the primary analytical approach to investigate the causal relationship between exposure and outcome. Furthermore, this study incorporates MR-Egger, simple mode, weighted median, and weighted mode as supplementary analytical approaches. To ensure the reliability of our findings, we further assessed horizontal pleiotropy and heterogeneity and evaluated the stability of MR results using the Leave-one-out method. In conclusion, this study employed mediation analysis to elucidate the potential mediating effects of plasma metabolites.

Results

Our investigation revealed a causal relationship between immune cells and pancreatic cancer, highlighting the pivotal roles of CD11c+ monocytes (odds ratio, ORIVW=1.105; 95% confidence interval, 95%CI: 1.002-1.218; P=0.045), HLA DR+ CD4+ antigen-presenting cells (ORIVW=0.920; 95%CI: 0.873-0.968; P=0.001), and HLA DR+ CD8br T cells (ORIVW=1.058; 95%CI: 1.002-1.117; P=0.041) in pancreatic cancer progression. Further mediation analysis indicated that oxalate (proportion of mediation effect in total effect: -11.6%, 95% CI: -89.7%, 66.6%) and the mannose to trans-4-hydroxyproline ratio (-19.4, 95% CI: -136%, 96.8%) partially mediate the relationship between HLA DR+ CD8br T cells and pancreatic cancer in nature. In addition, our analysis indicates that adrenate (-8.39%, 95% CI: -18.3%, 1.54%) plays a partial mediating role in the association between CD11c+ monocyte and pancreatic cancer, while cortisone (-26.6%, 95% CI: 138%, -84.8%) acts as a partial mediator between HLA DR+ CD4+ AC and pancreatic cancer.

Conclusion

This MR investigation provides evidence supporting the causal relationship between immune cell and pancreatic cancer, with plasma metabolites serving as mediators. Identifying immune cell phenotypes with potential causal effects on pancreatic cancer sheds light on its underlying mechanisms and suggests novel therapeutic targets.

Causal association of sarcopenia with hepatocellular carcinoma risk in European population: a Mendelian randomization study

Background

The causal association of sarcopenia with the incidence risk of hepatocellular carcinoma (HCC) in the European population, and the potential mediating role of C-reactive protein (CRP), remains unclear. This study employed a bidirectional two-sample, two-step Mendelian randomization (MR) analysis to investigate the causality and identify the mediator.

Methods

Summary statistics for HCC, CRP, and sarcopenia-related traits, including appendicular lean mass (ALM), hand grip strength (HGS), and walking pace (WP), were acquired from publicly available databases. We conducted bidirectional MR and Steiger tests of directionality to check the presence of reverse causality. Additionally, a two-step MR analysis was used to assess the mediating effect of CRP in the causality between sarcopenia and HCC. Tests for heterogeneity and horizontal pleiotropy were performed.

Results

As ALM increases, the risk of HCC occurrence decreases [odds ratio (OR), 95% confidence interval (CI): 0.703, 0.524-0.943; P = 0.019]. And, genetically predicted low-HGS (OR, 95%CI: 2.287, 1.013-5.164; P = 0.047) was associated with an increased incidence risk of HCC, with no reverse causality. However, we found no evidence supporting a causality between WP and HCC. CRP was identified as the mediator of the causal effect of ALM and low-HGS on HCC, with corresponding mediating effects of 9.1% and 7.4%.

Conclusions

This MR study effectively demonstrates that lower ALM and low-HGS are linked to an elevated risk of HCC within the European population, and the causality was not bidirectional. Furthermore, CRP serves as a mediator in the associations. These findings may help mitigate HCC risk among individuals with sarcopenia.

Mediating effect of metabolic syndrome in the association of educational attainment with intervertebral disc degeneration and low back pain

The causal association of educational attainment (EA) with intervertebral disc degeneration (IVDD) or low back pain (LBP), and the mediating effect of metabolic syndrome (MetS) in this association, is not studied to date. In this study, using summary statistics of genome-wide association studies primarily conducted in the individuals of European ancestry, Mendelian randomization (MR) analyses were performed to investigate: (1) the total and direct effects of EA on IVDD and LBP, (2) bidirectional associations of EA with MetS or the components of MetS, (3) causal effects of MetS or its components on IVDD and LBP, and (4) mediating effects of MetS or its components on the causal associations of EA with IVDD and LBP. Univariable MR analysis demonstrated that genetically proxied EA was inversely associated with IVDD (ORIVW: 0.90; 95 % CI: 0.87-0.92) and LBP (ORIVW: 0.86; 95 % CI: 0.84-0.89). Consistent results were obtained after adjusting for potential confounders (cognition, economic level, smoking traits, and metabolic factors). Mediation analysis proved that the effect of EA on IVDD mediated by MetS, waist circumference, and high-density lipoprotein cholesterol was 11.38 %, 9.22 %, and 2.17 %, respectively. Besides, MetS mediated 8.42 % and waist circumference mediated 5.81 % of the EA effects on LBP, respectively. Our findings provided support for MetS mediating the causal protective effects of EA on IVDD and LBP, which provided causal evidence to the etiology and intervention targets of IVDD and LBP.

Population diversity, admixture, and demographic trend of the Sumba Ongole cattle based on genomic data

OBJECTIVE

Sumba Ongole (SO) cattle are valuable breed due to their important role in the development of Indonesian cattle. Despite rapid advances in molecular technology, no genomic studies on SO cattle have been conducted to date. The aim of this study is to provide genomic profile related to the population diversity, admixture, and demographic trends of SO cattle.

METHODS

Genomic information was gathered from 79 SO cattle using the Illumina Bovine SNP50 v3 Beadchip, and for comparative purposes, additional genotypes from 209 cattle populations worldwide were included. The expected and observed heterozygosity, inbreeding coefficient, pairwise fixation indices between-population, and Nei's genetic distance were examined. Multidimensional scaling, admixture, and treemix analyses were used to investigate the population structure. Based on linkage disequilibrium and effective population size calculations, the demographic trend was observed.

RESULTS

The findings indicated that the genetic diversity of SO cattle was similar to that of other indicine breeds. SO cattle were genetically related to indicines but not to taurines or Bali cattle. The study further confirmed the close relationship between SO, Ongole, and Nellore cattle. Additionally, a small portion of the Ongole mixture were identified dominant in the SO population at the moment. The study also discovered that SO and Bali cattle (Bos javanicus) could have been ancestors in the development of Ongole Grade cattle, which corresponds to the documented history of Ongolization. Our finding indicate that SO cattle have maintained stability and possess unique traits separate from their ancestors.

CONCLUSION

In conclusion, the genetic diversity of the SO cattle has been conserved as a result of the growing significance of the present demographic trend. Consistent endeavors are necessary to uphold the fitness of the breed.

GWLD: an R package for genome-wide linkage disequilibrium analysis

Linkage disequilibrium (LD) analysis is fundamental to the investigation of the genetic architecture of complex traits (e.g. human disease, animal and plant breeding) and population structure and evolution dynamics. However, until now, studies primarily focus on LD status between genetic variants located on the same chromosome. Moreover, genome (re)sequencing produces unprecedented numbers of genetic variants, and fast LD computation becomes a challenge. Here, we have developed GWLD, a parallelized and generalized tool designed for the rapid genome-wide calculation of LD values, including conventional D/D', r2, and (reduced) mutual information (MI and RMI) measures. LD between genetic variants within and across chromosomes can be rapidly computed and visualized in either an R package or a standalone C++ software package. To evaluate the accuracy and speed of LD calculation, we conducted comparisons using 4 real datasets. Interchromosomal LD patterns observed potentially reflect levels of selection intensity across different species. Both versions of GWLD, the R package (https://github.com/Rong-Zh/GWLD/GWLD-R) and the standalone C++ software (https://github.com/Rong-Zh/GWLD/GWLD-C++), are freely available on GitHub.

Low-density lipoprotein cholesterol and risk of hepatocellular carcinoma: a Mendelian randomization and mediation analysis

BACKGROUND

A previous study demonstrated that low-density lipoprotein cholesterol (LDL-C) is associated with hepatocellular carcinoma (HCC); however, the causality between them has not been proven due to conflicting research results and the interference of confounders. This study utilized Mendelian randomization (MR) to investigate the causal relationship between LDL-C and HCC and identify the mediating factors.

METHODS

LDL-C, HCC, and coronary artery disease (CAD) genome-wide association study (GWAS) data were obtained from a public database. To investigate causality, inverse variance weighting (IVW) was the main analysis approach. MR‒Egger, simple mode, weighted median (WM), and weighted mode were employed as supplementary analytic methods. In addition, horizontal pleiotropy and heterogeneity were tested. To evaluate the stability of the MR results, a "leave-one-out" approach was used. Multivariate MR (MVMR) was utilized to correct the confounders that might affect causality, and mediation analysis was used to investigate the potential mediating effects. Finally, we used HCC risk to infer the reverse causality with LDL-C level.

RESULTS

Random effects IVW results were (LDL-C-HCC: odds ratio (OR) = 0.703, 95% confidence interval (CI) = [0.508, 0.973], P = 0.034; CAD-HCC: OR = 0.722, 95% CI = [0.645, 0.808], P = 1.50 × 10^-8; LDL-C-CAD: OR = 2.103, 95% CI = [1.862, 2.376], P = 5.65 × 10^-33), demonstrating a causal link between LDL-C levels and a lower risk of HCC. Through MVMR, after mutual correction, the causal effect of LDL-C and CAD on HCC remained significant (P < 0.05). Through mediation analysis, it was proven that CAD mediated the causative connection between LDL-C and HCC, and the proportion of mediating effect on HCC was 58.52%. Reverse MR showed that HCC could affect LDL-C levels with a negative correlation (OR_IVW = 0.979, 95% CI = [0.961, 0.997], P = 0.025).

CONCLUSION

This MR study confirmed the causal effect between LDL-C levels and HCC risk, with CAD playing a mediating role. It may provide a new view on HCC occurrence and development mechanisms, as well as new metabolic intervention targets for treatment.

Association of the gut microbiota with coronary artery disease and myocardial infarction: A Mendelian randomization study

Background: Previous studies have indicated that the gut microbiota (GM) is associated with coronary artery disease (CAD), but the causality of these associations remains unestablished due to confounding factors and reverse causality. We conducted Mendelian randomization study (MR) to determine the causal effect of the specific bacterial taxa on CAD/myocardial infarction (MI) and identify the mediating factors involved. Methods: Two-sample MR, multivariable MR (MVMR) and mediation analysis were performed. Inverse-variance weighting (IVW) was the main method used to analyze causality, and sensitivity analysis was used to verify the reliability of the study. Causal estimates from CARDIoGRAMplusC4D and FinnGen databases were combined using the meta-analysis method, and repeated validation was conducted based on the UK Biobank (UKB) database. Confounders that may affect the causal estimates were corrected by MVMP and the potential mediation effects were investigated by using mediation analysis. Results: The study suggested that increased abundance of the RuminococcusUCG010 genus leads to a lower risk of CAD (OR, 0.88; 95% CI, 0.78, 1.00; p = 2.88 × 10^-2) and MI (OR, 0.88; 95% CI, 0.79, 0.97; p = 1.08 × 10^-2), with consistent results in both meta-analysis (CAD: OR, 0.86; 95% CI, 0.78, 0.96; p = 4.71 × 10^-3; MI: OR, 0.82; 95% CI, 0.73, 0.92; p = 8.25 × 10^-4) and repeated analysis of the UKB dataset (CAD: OR, 0.99; 95% CI, 0.99, 1.00, p = 2.53 × 10^-4; MI: OR, 0.99; 95% CI, 0.99, 1.00, p = 1.85 × 10-11). Based on multiple databases, T2DM was proved as a mediating factor in the causal effect of RuminococcusUCG010 and CAD/MI, with an average mediation effect proportion of 20% on CAD and 17% on MI, respectively. Conclusion: This MR study provided suggestive genetic evidence that the higher the RuminococcusUCG010 abundance is, the lower the risk of CAD and MI, with T2DM playing a mediating effect. This genus may become a novel target in strategies for treating and preventing CAD and MI.

From Mendel to quantitative genetics in the genome era: the scientific legacy of W. G. Hill

The quantitative geneticist W. G. ('Bill') Hill, awardee of the 2018 Darwin Medal of the Royal Society and the 2019 Mendel Medal of the Genetics Society (United Kingdom), died on 17 December 2021 at the age of 81 years. Here, we pay tribute to his multiple key scientific contributions, which span population and evolutionary genetics, animal and plant breeding and human genetics. We discuss his theoretical research on the role of linkage disequilibrium (LD) and mutational variance in the response to selection, the origin of the widely used LD metric r² in genomic association studies, the genetic architecture of complex traits, the quantification of the variation in realized relationships given a pedigree relationship and much more. We demonstrate that basic theoretical research in quantitative and statistical genetics has led to profound insights into the genetics and evolution of complex traits and made predictions that were subsequently empirically validated, often decades later.

Synergistic epistasis of the deleterious effects of transposable elements

The replicative nature and generally deleterious effects of transposable elements (TEs) raise an outstanding question about how TE copy number is stably contained in host populations. Classic theoretical analyses predict that, when the decline in fitness due to each additional TE insertion is greater than linear, or when there is synergistic epistasis, selection against TEs can result in a stable equilibrium of TE copy number. While several mechanisms are predicted to yield synergistic deleterious effects of TEs, we lack empirical investigations of the presence of such epistatic interactions. Purifying selection with synergistic epistasis generates repulsion linkage between deleterious alleles. We investigated this population genetic signal in the likely ancestral Drosophila melanogaster population and found evidence supporting the presence of synergistic epistasis among TE insertions, especially TEs expected to exert large fitness impacts. Even though synergistic epistasis of TEs has been predicted to arise through ectopic recombination and TE-mediated epigenetic silencing mechanisms, we only found mixed support for the associated predictions. We observed signals of synergistic epistasis for a large number of TE families, which is consistent with the expectation that such epistatic interaction mainly happens among copies of the same family. Curiously, significant repulsion linkage was also found among TE insertions from different families, suggesting the possibility that synergism of TEs' deleterious fitness effects could arise above the family level and through mechanisms similar to those of simple mutations. Our findings set the stage for investigating the prevalence and importance of epistatic interactions in the evolutionary dynamics of TEs.

Scalable bias-corrected linkage disequilibrium estimation under genotype uncertainty

Linkage disequilibrium (LD) estimates are often calculated genome-wide for use in many tasks, such as SNP pruning and LD decay estimation. However, in the presence of genotype uncertainty, naive approaches to calculating LD have extreme attenuation biases, incorrectly suggesting that SNPs are less dependent than in reality. These biases are particularly strong in polyploid organisms, which often exhibit greater levels of genotype uncertainty than diploids. A principled approach using maximum likelihood estimation with genotype likelihoods can reduce this bias, but is prohibitively slow for genome-wide applications. Here, we present scalable moment-based adjustments to LD estimates based on the marginal posterior distributions of the genotypes. We demonstrate, on both simulated and real data, that these moment-based estimators are as accurate as maximum likelihood estimators, but are almost as fast as naive approaches based only on posterior mean genotypes. This opens up bias-corrected LD estimation to genome-wide applications. In addition, we provide standard errors for these moment-based estimators. All methods discussed in this manuscript are implemented in the ldsep package, available on the Comprehensive R Archive Network ( https://cran.r-project.org/package=ldsep ).

Modeling the selective advantage of new amino acids on the hemagglutinin of H1N1 influenza viruses using their patient age distributions

In 2009, a new strain of H1N1 influenza A virus caused a pandemic, and its descendant strains are causing seasonal epidemics worldwide. Given the high mutation rate of influenza viruses, variant strains having different amino acids on hemagglutinin (HA) continuously emerge. To prepare vaccine strains for the next influenza seasons, it is an urgent task to predict which variants will be selected in the viral population. An analysis of 24,681 pairs of an amino acid sequence of HA of H1N1pdm2009 viruses and its patient age showed that the empirical fixation probability of new amino acids on HA significantly differed depending on their frequencies in the population, patient age distributions, and epitope flags. The selective advantage of a variant strain having a new amino acid was modeled by linear combinations of patients age distributions and epitope flags, and then the fixation probability of the new amino acid was modeled using Kimura’s formula for advantageous selection. The parameters of models were estimated from the sequence data and models were tested with four-fold cross validations. The frequency of new amino acids alone can achieve high sensitivity, specificity, and precision in predicting the fixation of a new amino acid of which frequency is more than 0.11. The estimated parameter suggested that viruses with a new amino acid having a frequency in the population higher than 0.11 have a significantly higher selective advantage compared to viruses with the old amino acid at the same position. The model considering the Z-value of patient age rank-sums of new amino acids predicted amino acid substitutions on HA with a sensitivity of 0.78, specificity of 0.86, and precision of 0.83, showing significant improvement compared to the constant selective advantage model, which used only the frequency of the amino acid. These results suggested that H1N1 viruses tend to be selected in the adult population, and frequency of viruses having new amino acids and their patient ages are useful to predict amino acid substitutions on HA.

FCGR Genetic Variation in Two Populations From Ecuador Highlands-Extensive Copy-Number Variation, Distinctive Distribution of Functional Polymorphisms, and a Novel, Locally Common, Chimeric FCGR3B/A (CD16B/A) Gene

Fcγ receptors (FcγR), cell-surface glycoproteins that bind antigen-IgG complexes, control both humoral and cellular immune responses. The FCGR locus on chromosome 1q23.3 comprises five homologous genes encoding low-affinity FcγRII and FcγRIII, and displays functionally relevant polymorphism that impacts on human health. Recurrent events of non-allelic homologous recombination across the FCGR locus result in copy-number variation of ~82.5 kbp-long fragments known as copy-number regions (CNR). Here, we characterize a recently described deletion that we name CNR5, which results in loss of FCGR3A, FCGR3B, and FCGR2C, and generation of a recombinant FCGR3B/A gene. We show that the CNR5 recombination spot lies at the beginning of the third FCGR3 intron. Although the FCGR3B/A-encoded hybrid protein CD16B/A reaches the plasma membrane in transfected cells, its possible natural expression, predictably restricted to neutrophils, could not be demonstrated in resting or interferon γ-stimulated cells. As the CNR5-deletion was originally described in an Ecuadorian family from Llano Grande (an indigenous community in North-Eastern Quito), we characterized the FCGR genetic variation in two populations from the highlands of Ecuador. Our results reveal that CNR5-deletion is relatively frequent in Llano Grande (5 carriers out of 36 donors). Furthermore, we found a high frequency of two strong-phagocytosis variants: the FCGR3B-NA1 haplotype and the CNR1 duplication, which translates into an increased FCGR3B and FCGR2C copy-number. CNR1 duplication was particularly increased in Llano Grande, 77.8% of the studied sample carrying at least one such duplication. In contrast, an extended haplotype CD16A-176V – CD32C-ORF+2B.2 – CD32B-2B.4 including strong activating and inhibitory FcγR variants was absent in Llano Grande and found at a low frequency (8.6%) in Ecuador highlands. This particular distribution of FCGR polymorphism, possibly a result of selective pressures, further confirms the importance of a comprehensive, joint analysis of all genetic variations in the locus and warrants additional studies on their putative clinical impact. In conclusion, our study confirms important ethnic variation at the FCGR locus; it shows a distinctive FCGR polymorphism distribution in Ecuador highlands; provides a molecular characterization of a novel CNR5-deletion associated with CD16A and CD16B deficiency; and confirms its presence in that population.

LDkit: a parallel computing toolkit for linkage disequilibrium analysis

BACKGROUND

Linkage disequilibrium (LD) analysis is broadly utilized in genetics to understand the evolutionary and demographic history and helps geneticists identify genes associated with interested inherited traits, such as diseases. There are some tools for linkage disequilibrium analysis either in a local or online way; however, there has been no such tool supporting both graphical user interface (GUI) and parallel computing.

RESULTS

We developed a GUI software called LDkit for LD analysis, which supports parallel computing. The LDkit supports both variant call format (VCF) and PLINK 'ped + map' format. At the same time, users could also just analyze a subset of individuals from the whole population. The LDkit reads the data by block and then paralleled the computation process by monitoring the usage of processes. Assessment on the Human 1000 genome data showed that when paralleled with 32 threads, the running time was reduced to less than 6 minutes from ~77 minutes using the chromosome 22 dataset with 1,103,547 SNPs and 2504 individuals.

CONCLUSIONS

The software LDkit can be effectively used to calculate and plot LD decay, LD block, and linkage disequilibrium analysis between a site and a given region. Most importantly, both graphical user interface (GUI) and stand-alone packages are available for users' convenience. LDkit was written in JAVA language under cross-platform support.

Estimating linkage disequilibrium from genotypes under Hardy-Weinberg equilibrium

Background

Measures of linkage disequilibrium (LD) play a key role in a wide range of applications from disease association to demographic history estimation. The true population LD cannot be measured directly and instead can only be inferred from genetic samples, which are unavoidably subject to measurement error. Previous studies of r² (a measure of LD), such as the bias due to finite sample size and its variance, were based on the special case that the true population-wise LD is zero. These results generally do not hold for non-zero \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ {r}_{true}^2 $$\end{document}rtrue2 values, which are more common in real genetic data.

Results

This work generalises the estimation of r² to all levels of LD, and for both phased and unphased data. First, we provide new formulae for the effect of finite sample size on the observed r² values. Second, we find a new empirical formula for the variance of the observed r², equals to 2E[r²](1 − E[r²])/n, where n is the diploid sample size. Third, we propose a new routine, Constrained ML, a likelihood-based method to directly estimate haplotype frequencies and r² from diploid genotypes under Hardy-Weinberg Equilibrium. While serving the same purpose as the pre-existing Expectation-Maximisation algorithm, the new routine can have better convergence and is simpler to use. A new likelihood-ratio test is also introduced to test for the absence of a particular haplotype. Extensive simulations are run to support these findings.

Conclusion

Most inferences on LD will benefit from our new findings, from point and interval estimation to hypothesis testing. Genetic analyses utilising r² information will become more accurate as a result.

Evaluation of ADAM33 gene's single nucleotide polymorphism variants against asthma and the unique pattern of inheritance in Northern and Central Punjab, Pakistan

OBJECTIVES

To investigate the relationship of 3 single nucleotide polymorphism (SNP) variants of ADAM33 with asthma susceptibility in patients from Northern and Central Punjab, Punjab, Pakistan. Methods: In this case-control study, healthy and asthmatic participants were recruited between 2015 and 2017. The SNPs of ADAM33 gene, rs2280089, rs2280090, and rs2280091 were analyzed in 296 asthma patients and 343 healthy controls, as well as linkage disequilibrium and haplotype analysis.

RESULTS

The non-significant differences were observed in allele and genotype frequencies of the SNPs in asthmatic and healthy persons even after population stratification based on age, caste, gender, family history, and environment. Although these SNPs were non-significant for disease susceptibility among children and adults, a fixed unique pattern of inheritance was nevertheless observed for the studied SNPs. Linkage disequilibrium analysis presented a very strong linkage between the SNP variants to predict their co-inheritance in study population. However, none of the haplotypes were found to be associated with asthma disease development.

CONCLUSION

The studied SNPs of ADAM33 appeared to be non-significant for asthma susceptibility in  Northern and Central Punjabi population. The fixed allele combination inheritance pattern was a unique observation contrary to findings in other global populations.