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Purpose: To investigate the causality between periodontitis and non-alcoholic fatty liver disease (NAFLD) using a two-sample bidirectional Mendelian randomisation (MR) analysis. Materials and Methods: Genetic variations in periodontitis and NAFLD were acquired from genome-wide association studies (GWAS) using the Gene-Lifestyle Interaction in Dental Endpoints, a large-scale meta-analysis, and FinnGen consortia. Data from the first two databases were used to explore the causal relationship between periodontitis and NAFLD (“discovery stage”), and the data from FinnGen was used to validate our results (“validation stage”). We initially performed MR analysis using 5 single nucleotide polymorphisms (SNPs) in the discovery samples and 18 in the replicate samples as genetic instruments for periodontitis to investigate the causative impact of periodontitis on NAFLD. We then conducted a reverse MR analysis using 6 SNPs in the discovery samples and 4 in the replicate samples as genetic instruments for NAFLD to assess the causative impact of NAFLD on periodontitis. We further implemented heterogeneity and sensitivity analyses to assess the reliability of the MR results. Results: Periodontitis was not causally related to NAFLD (odds ratio [OR] = 1.036, 95% CI: 0.914–1.175, p = 0.578 in the discovery stage; OR = 1.070, 95% CI: 0.935–1.224, p = 0.327 in the validation stage), and NAFLD was not causally linked with periodontitis (OR = 1.059, 95% CI: 0.916–1.225, p = 0.439 in the discovery stage; OR = 0.993, 95% CI: 0.896–1.102, p = 0.901 in the validation stage). No heterogeneity was observed among the selected SNPs. Sensitivity analyses demonstrated the absence of pleiotropy and the reliability of our MR results. Conclusion: The present MR analysis showed no genetic evidence for a cause-and-effect relationship between periodontitis and NAFLD. Periodontitis may not directly influence the development of NAFLD and vice versa. [ABSTRACT FROM AUTHOR]

[This corrects the article DOI: 10.3389/fmicb.2023.1154664.].

Atrial fibrillation (AF), the most common arrhythmia, has been associated with different electrophysiological, molecular, and structural alterations in atrial cardiomyocytes. Therefore, more studies are required to elucidate the genetic and molecular basis of AF. Various genome-wide association studies (GWAS) have strongly associated different single nucleotide polymorphisms (SNPs) with AF. One of these GWAS identified the rs13376333 risk SNP as the most significant one from the 1q21 chromosomal region. The rs13376333 risk SNP is intronic to the KCNN3 gene that encodes for small conductance calcium-activated potassium channels type 3 (SK3). However, the functional electrophysiological effects of this variant are not known. SK channels represent a unique family of K+ channels, primarily regulated by cytosolic Ca2+ concentration, and different studies support their critical role in the regulation of atrial excitability and consequently in the development of arrhythmias like AF. Since different studies have shown that both upregulation and downregulation of SK3 channels can lead to arrhythmias by different mechanisms, an important goal is to elucidate whether the rs13376333 risk SNP is a gain-of-function (GoF) or a loss-of-function (LoF) variant. A better understanding of the functional consequences associated with these SNPs could influence clinical practice guidelines by improving genotype-based risk stratification and personalized treatment. Although research using native human atrial cardiomyocytes and animal models has provided useful insights, each model has its limitations. Therefore, there is a critical need to develop a human-derived model that represents human physiology more accurately than existing animal models. In this context, research with human induced pluripotent stem cells (hiPSC) and subsequent generation of cardiomyocytes derived from hiPSC (hiPSC-CMs) has revealed the underlying causes of various cardiovascular diseases and identified treatment opportunities that were not possible using in vitro or in vivo studies with animal models. Thus, the ability to generate atrial cardiomyocytes and atrial tissue derived from hiPSCs from human/patients with specific genetic diseases, incorporating novel genetic editing tools to generate isogenic controls and organelle-specific reporters, and 3D bioprinting of atrial tissue could be essential to study AF pathophysiological mechanisms. In this review, we will first give an overview of SK-channel function, its role in atrial fibrillation and outline pathophysiological mechanisms of KCNN3 risk SNPs. We will then highlight the advantages of using the hiPSC-CM model to investigate SNPs associated with AF, while addressing limitations and best practices for rigorous hiPSC studies.

Accurate and efficient molecular recognition plays a crucial role in the fields of molecular detection and diagnostics. Conventional trial‐and‐error‐based molecular recognition approaches have always been challenged in distinguishing minimal differences between targets and non‐targets, such as single nucleotide polymorphisms (SNPs) of oligonucleotides. To address these challenges, here, a novel concept of dynamic addressing analysis is proposed. In this concept, by dissecting the regions of the target and creating a corresponding recognizer, it is possible to eliminate the inaccuracy and inefficiency of recognition. To achieve this concept, a Dynamic Addressing Molecular Robot (DAMR), a DNA‐based dynamic addressing device is developed which is capable of dynamically locating targets. DAMR is designed to first bind to the conserved region of the target while addressing the specific region dynamically until accurate recognition is achieved. DAMR has provided an approach for analyzing low‐resolution targets and has been used for analyzing SNP of miR‐196a2 in both cell and serum samples, which has opened new avenues for effective and efficient molecular recognition. [ABSTRACT FROM AUTHOR]

Genome‐wide technologies open up new possibilities to clarify questions on genetic structure and phylogeographic history of taxa previously studied with microsatellite loci and mitochondrial sequences. Here, we used 736 individual red deer (Cervus elaphus) samples genotyped at 35,701 single nucleotide polymorphism loci (SNPs) to assess the population structure of the species throughout Europe. The results identified 28 populations, with higher degrees of genetic distinction in peripheral compared to mainland populations. Iberian red deer show high genetic differentiation, with lineages in Western and Central Iberia maintaining their distinctiveness, which supports separate refugial ranges within Iberia along with little recent connection between Iberian and the remaining Western European populations. The Norwegian population exhibited the lowest variability and the largest allele frequency differences from mainland European populations, compatible with a history of bottlenecks and drift during post‐glacial colonization from southern refugia. Scottish populations showed high genetic distance from the mainland but high levels of diversity. Hybrid zones were found between Eastern and Western European lineages in Central Europe as well as in the Pyrenees, where red deer from France are in close contact with Iberian red deer. Anthropogenic restocking has promoted the Pyrenean contact zone, admixture events in populations on the Isle of Rum and in the Netherlands, and at least partly the admixture of the two main lineages in central‐eastern Europe. Our analysis enabled detailed resolution of population structure of a large mammal widely distributed throughout Europe and contributes to resolving the evolutionary history, which can also inform conservation and management policies. [ABSTRACT FROM AUTHOR]

ABSTRACT The woody bamboos (Bambusoideae) exhibit distinctive biological traits within Poaceae, such as highly lignified culms, rapid shoot growth, monocarpic mass flowering and nutlike or fleshy caryopses. Much of the remarkable morphological diversity across the subfamily exists within a single hexaploid clade, the paleotropical woody bamboos (PWB), making it ideal to investigate the factors underlying morphological evolution in woody bamboos. However, the origin and biogeographical history of PWB remain elusive, as does the effect of environmental factors on the evolution of their morphological characters. We generated a robust and time‐calibrated phylogeny of PWB using single nucleotide polymorphisms retrieved from optimized double digest restriction site associated DNA sequencing, and explored the evolutionary trends of habit, inflorescence, and caryopsis type in relation to environmental factors including climate, soil, and topography. We inferred that the PWB started to diversify across the Oligocene–Miocene boundary and formed four major clades, that is, Melocanninae, Racemobambosinae s.l. (comprising Dinochloinae, Greslanlinae, Racemobambosinae s.str. and Temburongiinae), Hickeliinae and Bambusinae s.l. (comprising Bambusinae s.str. plus Holttumochloinae). The ancestor of PWB was reconstructed as having erect habit, indeterminate inflorescence and basic caryopsis. The characters including climbing/scrambling habit, determinate inflorescence, and nucoid/bacoid caryopsis have since undergone multiple changes and reversals during the diversification of PWB. The evolution of all three traits was correlated with, and hence likely influenced by, aspects of climate, topography, and soil, with climate factors most strongly correlated with morphological traits, and soil factors least so. However, topography had more influence than climate or soil on the evolution of erect habit, whereas both factors had greater effect on the evolution of bacoid caryopsis than did soil. Our results provide novel insights into morphological diversity and adaptive evolution in bamboos for future ecological and evolutionary research. [ABSTRACT FROM AUTHOR]

Backgroup: The pathogenesis of shoulder impingement syndrome (SIS) is still unclear, and its questionable causal relationship with rotator cuff (RC) injury has led to confusion in treatment. The purpose of this study was to explore the bidirectional causal relationship between SIS and RC injury. Methods: SIS and RC injury datasets downloaded from the IEU Open GWAS project and GWAS catalog databases. Inverse variance weighted (IVW), MR Egger, Weighted median, and Weighted mode were used in this Mendelian randomization (MR) analysis. Cochran's Q test, leave-one-out, and funnel plot method were used to evaluate heterogeneity between single nucleotide polymorphisms (SNPs). MR-Egger regression was used to test the horizontal pleiotropy of this study. Results: The IVW method (OR = 1.189, P = 0.0059) suggest the putative causal effect of RC injury on SIS. The results of MR Egger method (OR = 1.236, P = 0.2013), weighted median method (OR = 1.097, P = 0.2428) and weighted mode method (OR = 1.013, P = 0.930) showed no statistically significant (OR = 1.069071, P = 0.6173). Heterogeneity test and horizontal pleiotropy analysis suggested that there was no significant heterogeneity and horizontal pleiotropy in the results of this MR analysis. The reverse MR analysis showed heterogeneity, and the conclusion needs to be further explored. Conclusions: The results of MR analysis support that RC injury may be causally associated with SIS. [ABSTRACT FROM AUTHOR]

Background: The utilization of long reads for single nucleotide polymorphism (SNP) phasing has become popular, providing substantial support for research on human diseases and genetic studies in animals and plants. However, due to the complexity of the linkage relationships between SNP loci and sequencing errors in the reads, the recent methods still cannot yield satisfactory results. Results: In this study, we present a graph-based algorithm, GCphase, which utilizes the minimum cut algorithm to perform phasing. First, based on alignment between long reads and the reference genome, GCphase filters out ambiguous SNP sites and useless read information. Second, GCphase constructs a graph in which a vertex represents alleles of an SNP locus and each edge represents the presence of read support; moreover, GCphase adopts a graph minimum-cut algorithm to phase the SNPs. Next, GCpahse uses two error correction steps to refine the phasing results obtained from the previous step, effectively reducing the error rate. Finally, GCphase obtains the phase block. GCphase was compared to three other methods, WhatsHap, HapCUT2, and LongPhase, on the Nanopore and PacBio long-read datasets. The code is available from https://github.com/baimawjy/GCphase. Conclusions: Experimental results show that GCphase under different sequencing depths of different data has the least number of switch errors and the highest accuracy compared with other methods. [ABSTRACT FROM AUTHOR]

The SARS-CoV-2 pandemic has brought molecular biology and genomic sequencing into the public consciousness and lexicon. With an emphasis on rapid turnaround, genomic data informed both diagnostic and surveillance decisions for the current pandemic at a previously unheard-of scale. The surge in the submission of genomic data to publicly available databases proved essential as comparing different genome sequences offers a wealth of knowledge, including phylogenetic links, modes of transmission, rates of evolution, and the impact of mutations on infection and disease severity. However, the scale of the pandemic has meant that sequencing runs are rarely repeated due to limited sample material and/or the availability of sequencing resources, resulting in the upload of some imperfect runs to public repositories. As a result, it is crucial to investigate the data obtained from these imperfect runs to determine whether the results are reliable prior to depositing them in a public database. Numerous studies have identified a variety of sources of contamination in public next-generation sequencing (NGS) data as the number of NGS studies increases along with the diversity of sequencing technologies and procedures. For this study, we conducted an in silico experiment with known SARS-CoV-2 sequences produced from Oxford Nanopore Technologies sequencing to investigate the effect of contamination on lineage calls and single nucleotide variants (SNVs). A contamination threshold below which runs are expected to generate accurate lineage calls and maintain genome-relatedness and integrity was identified. Together, these findings provide a benchmark below which imperfect runs may be considered robust for reporting results to both stakeholders and public repositories and reduce the need for repeat or wasted runs. Author summary: Large-scale genomic comparisons provide a wealth of knowledge, including modes of transmission, rates of evolution, and the impact of mutations on infection, disease severity, and treatment effectiveness. As a result, the public release of genomic data has proven crucial to response of the SARS-CoV-2 pandemic. However, studies continue to show that some of the genomic data in public repositories are contaminated from a variety of sources. For instance, the rapid response to the SARS-CoV-2 pandemic prevented many sequencing runs from being repeated, resulting in the occasional upload of imperfect runs to public repositories. It is of note that when genomic data is contaminated, both scientific decisions/studies and public health measures may be compromised. To identify genome contamination threshold(s) for SARS-CoV-2 sequences generated by Nanopore sequencing, computational biology techniques were used to generate artificially subsampled and contaminated libraries. This is the first study of its kind and we hope that the results obtained provide a starting point to investigate and report contamination for groups producing and analyzing NGS data. [ABSTRACT FROM AUTHOR]

Campylobacteriosis outbreaks have previously been linked to dairy foods. While the genetic diversity of Campylobacter is well understood in high-income countries, it is largely unknown in low-income countries, such as Ethiopia. This study therefore aimed to conduct the first genomic characterization of Campylobacter isolates from the Ethiopian dairy supply chain to aid in future epidemiological studies. Fourteen C. jejuni and four C. coli isolates were whole genome sequenced using an Illumina platform. Sequences were analyzed using the bioinformatics tools in the GalaxyTrakr platform to identify MLST types, and single nucleotide polymorphisms, and infer phylogenetic relationships among the studied isolates. Assembled genomes were further screened to detect antimicrobial resistance and virulence gene sequences. Among 14 C. jejuni, ST 2084 and ST 51, which belong to the clonal complexes ST-353 and ST-443, respectively, were identified. Among the 4 sequenced C. coli isolates, two isolates belonged to ST 1628 and two to ST 830 from the clonal complex ST-828. The isolates of C. jejuni ST 2084 and ST 51 carried β-lactam resistance gene blaOXA-605, a fluoroquinolone resistance-associated mutation T86I in the gryA gene, and a macrolide resistance-associated mutation A103V in 50S L22. Only ST 2084 isolates carried the tetracycline resistance gene tetO. Conversely, all four C. coli ST 830 and ST 1628 isolates carried tetO, but only ST 1628 isolates also carried blaOXA-605. Lastly, C. jejuni ST 2084 isolates carried a total of 89 virulence genes, and ST 51 isolates carried up to 88 virulence genes. Among C. coli, ST 830 isolates carried 71 genes involved in virulence, whereas two ST 1628 isolates carried up to 82 genes involved in virulence. Isolates from all identified STs have previously been isolated from human clinical cases, demonstrating a potential food safety concern. This finding warrants further monitoring of Campylobacter in dairy foods in Ethiopia to better understand and manage the risks associated with Campylobacter contamination and transmission. [ABSTRACT FROM AUTHOR]

We consider random sample splitting for estimation and inference in high‐dimensional generalized linear models (GLMs), where we first apply the lasso to select a submodel using one subsample and then apply the debiased lasso to fit the selected model using the remaining subsample. We show that a sample splitting procedure based on the debiased lasso yields asymptotically normal estimates under mild conditions and that multiple splitting can address the loss of efficiency. Our simulation results indicate that using the debiased lasso instead of the standard maximum likelihood method in the estimation stage can vastly reduce the bias and variance of the resulting estimates. Furthermore, our multiple splitting debiased lasso method has better numerical performance than some existing methods for high‐dimensional GLMs proposed in the recent literature. We illustrate the proposed multiple splitting method with an analysis of the smoking data of the Mid‐South Tobacco Case–Control Study. [ABSTRACT FROM AUTHOR]

Background: Adaptation to cold was essential for human migration across Eurasia. Non-shivering thermogenesis through brown adipose tissue (BAT) participates in cold adaptation because some genes involved in the differentiation and function of BAT exhibit signatures of positive natural selection in populations at high latitudes. Whether these genes are associated with the inter-individual variability in BAT thermogenesis remains unclear. In this study, we evaluated the potential associations between BAT activity and single nucleotide polymorphisms (SNPs) in candidate gene regions in East Asian populations. Methods: BAT activity induced by mild cold exposure was measured in 399 healthy Japanese men and women using fluorodeoxyglucose-positron emission tomography and computed tomography (FDG-PET/CT). The capacity for cold-induced thermogenesis and fat oxidation was measured in 56 men. Association analyses with physiological traits were performed for 11 SNPs at six loci (LEPR, ANGPTL8, PLA2G2A, PLIN1, TBX15-WARS2, and FADS1) reported to be under positive natural selection. Associations found in the FDG-PET/CT population were further validated in 84 healthy East Asian men and women, in whom BAT activity was measured using infrared thermography. Associations between the SNP genotypes and BAT activity or other related traits were tested using multiple logistic and linear regression models. Results: Of the 11 putative adaptive alleles of the six genes, two intronic SNPs in LEPR (rs1022981 and rs12405556) tended to be associated with higher BAT activity. However, these did not survive multiple test comparisons. Associations with lower body fat percentage, plasma triglyceride, insulin, and HOMA-IR levels were observed in the FDG-PET/CT population (P < 0.05). Other loci, including TBX15-WARS2, which is speculated to mediate cold adaptation in Greenland Inuits, did not show significant differences in BAT thermogenesis. Conclusions: Our results suggest a marginal but significant association between LEPR SNPs. However, robust supporting evidence was not established for the involvement of other loci under positive natural selection in cold adaptation through BAT thermogenesis in East Asian adults. Given the pleiotropic function of these genes, factors other than cold adaptation through BAT thermogenesis, such as diet adaptation, may contribute to positive natural selection at these loci. [ABSTRACT FROM AUTHOR]

Background: The histopathological classification of T-cell lymphoma (TCL) in humans has distinctive mutational genotyping that suggests different lymphomagenesis. A similar concept is assumed to be observed in dogs with different TCL phenotypes. Objective: This study aimed to identify the previously reported single-nucleotide polymorphisms (SNPs) in both human beings and dogs in canine TCLs and nullcell lymphomas (NCLs) and to design compatible oligonucleotides from each variant based on the multiplex polymerase chain reaction. Methods: Genomic DNA was extracted from 68 tumor specimens (62 TCLs and 6 NCLs) and 5 buffy coat samples from dogs with TCL. Four TCL subtypes and NCL were analyzed in 44 SNPs from 21 genes using the MassARRAY. Results: The greatest incidences of SNPs observed in all TCL subtypes and NCL ware SATB1 c.1259A > C, KIT c.1275A > G, SEL1L c.2040 + 200C > G, and TP53 c.1024C > T, respectively. Some SNP locations were statistically significant associated with NCL, including MYC p.S75F (p = 0.0003), TP53 p.I149N (p = 0.030), PDCD1 p.F37LX (p = 0.012), and POT1 p.R583* (p = 0.012). Conclusion: Each TCL histological subtype and NCL are likely to contain distinctive mutational genetic profiles, which might play a role in lymphoma gene-risk factors and might be useful for selecting therapeutic target drugs for each canine patient. [ABSTRACT FROM AUTHOR]

Genome-wide association studies (GWASs) based on common single nucleotide polymorphisms (SNPs) have identified several loci associated with the risk of monoclonal gammopathy of unknown significance (MGUS), a precursor condition for multiple myeloma (MM). We hypothesized that analyzing haplotypes might be more useful than analyzing individual SNPs, as it could identify functional chromosomal units that collectively contribute to MGUS risk. To test this hypothesis, we used data from our previous GWAS on 992 MGUS cases and 2910 controls from three European populations. We identified 23 haplotypes that were associated with the risk of MGUS at the genome-wide significance level (p < 5 × 10−8) and showed consistent results among all three populations. In 10 genomic regions, strong promoter, enhancer and regulatory element-related histone marks and their connections to target genes as well as genome segmentation data supported the importance of these regions in MGUS susceptibility. Several associated haplotypes affected pathways important for MM cell survival such as ubiquitin-proteasome system (RNF186, OTUD3), PI3K/AKT/mTOR (HINT3), innate immunity (SEC14L1, ZBP1), cell death regulation (BID) and NOTCH signaling (RBPJ). These pathways are important current therapeutic targets for MM, which may highlight the advantage of the haplotype approach homing to functional units. [ABSTRACT FROM AUTHOR]

This study aimed to identify and evaluate the genetic diversity of olive trees in Jordan, a country located in the eastern Mediterranean, where olive domestication originated. For this purpose, a total of 386 olive trees were analyzed, including 338 collected from two surveys (JOCC-1 and JOCC-2) across seven regions, and 48 selected accessions from the Olive Germplasm Bank of Jordan (JGBOC). These trees underwent comprehensive phenotypic and molecular characterization using different tools. Significant differences inmorphological traits were detected among tested regions using the Chi-square test. Principal components analysis revealed that fruit color change and growth habit as the most discriminating traits, segregating the trees into two groups, with the first group including the KANABISI cultivar and the second group including the KFARI BALADI cultivar. Utilizing Kompetitive Allele Specific PCR assay, two sets of informative SNPs were used for the genetic diversity analysis. Cladograms were constructed using the maximum likelihood method, revealing a consistent pattern where two clades containing identical genotypes were observed to cluster with the KFARI BALADI or KANABISI. In addition, the SNP data was used to perform a comparative analysis with the Worldwide Olive Germplasm Bank of Co'rdoba, which revealed 73 unreported olive genotypes from Jordan. Genetic structure analyses using Discriminant Analysis of Principal Components (DAPC) identified four clusters with distinctive patterns of relatedness among 149 unique accessions, including 52 olive accessions from various Mediterranean countries (IOCC-3). ADMIXTURE analysis revealed four genetic clusters, consistentwith the clustering observed inDAPC and cladogram analysis, indicating a high level of genetic admixture among Jordanian olive germplasm. In conclusion, the results show that olive trees in Jordan are highly diverse, providing valuable information for future conservation and management plans. [ABSTRACT FROM AUTHOR]

Introduction: Emerging evidence suggests a connection between vulnerability to infections and Alzheimer's disease (AD). The nectin cell adhesion molecule 2 (NECTIN2) gene coding for a membrane component of adherens junctions is involved in response to infections, and its single nucleotide polymorphism (SNP) rs6859 was significantly associated with AD risk in several human cohorts. It is unclear, however, how exactly rs6859 influences the development of AD pathology. The aggregation of hyperphosphorylated tau protein (pTau) is a key pathological feature of neurodegeneration in AD, which may be induced by infections, among other factors, and potentially influenced by genes involved in both AD and vulnerability to infections, such as NECTIN2. Materials and methods: We conducted a causal mediation analysis (CMA) on a sample of 708 participants in the Alzheimer's disease Neuroimaging Initiative (ADNI). The relationship between rs6859 and Alzheimer's disease (AD), with AD (yes/no) as the outcome and pTau-181 levels in the cerebrospinal fluid (CSF) acting as a mediator in this association, was assessed. Adjusted estimates from the probit and linear regression models were used in the CMA model, where an additive model considered an increase in dosage of the rs6859 A allele (AD risk factor). Results: The increase in dose of allele A of the SNP rs6859 resulted in about 0.144 increase per standard deviation (SD) of pTau-181 (95% CI: 0.041, 0.248, p < 0.01). When included together in the probit model, the change in A allele dose and each standard deviation change in pTau-181 predicted 6.84% and 9.79% higher probabilities for AD, respectively. In the CMA, the proportion of the average mediated effect was 17.05% and was higher for the risk allele homozygotes (AA), at 19.40% (95% CI: 6.20%, 43.00%, p < 0.01). The sensitivity analysis confirmed the evidence of a robust mediation effect. Conclusion: This study reported a new potential causal relationship between pTau-181 and AD. We found that the association between rs6859 in the NECTIN2 gene and AD is partly mediated by pTau-181 levels in CSF. The rest of this association may be mediated by other factors. Our finding sheds light on the complex interplay between genetic susceptibility, protein aggregation, and neurodegeneration in AD. Further research, using other biomarkers, is needed to uncover the remaining mechanisms of the association between the NECTIN2 gene and AD. [ABSTRACT FROM AUTHOR]

Knowledge of past and present genetic diversity within a breed is critical for the design and optimization of breeding programs as well as the development of strategies for the conservation of genetic resources. The Polypay sheep breed was developed at the U.S. Sheep Experiment Station (USSES) in 1968 with the goal of improving productivity in Western U.S. range flocks. It has since flourished in the more intensively managed production systems throughout the U.S. The genetic diversity of the breed has yet to be documented. Therefore, the primary objective of this study was to perform a comprehensive evaluation of the genetic diversity and population structure of U.S. Polypay sheep using both pedigree- and genomic-based methods. Pedigree data from 193 Polypay flocks participating in the National Sheep Improvement Program (NSIP) were combined with pedigree records from USSES (n = 162,997), tracing back to the breed's origin. A subset of these pedigreed sheep from 32 flocks born from 2011 to 2023 were genotyped with the GGP Ovine 50K BeadChip containing 51,867 single nucleotide polymorphisms (SNPs). Four subgroups were used for the pedigree-based analyses: 1) the current generation of animals born in 2020--2022 (n = 20,701), 2) the current generation with a minimum of four generations of known ancestors (n = 12,685), 3) only genotyped animals (n = 1,856), and 4) the sires of the current generation (n = 509). Pedigree-based inbreeding for the full population was 2.2%, with a rate of inbreeding of 0.22% per generation. Pedigree-based inbreeding, Wright's inbreeding, and genomic inbreeding based on runs of homozygosity were 2.9%, 1.3%, and 5.1%, respectively, for the genotyped population. The effective population size ranged from 41 to 249 for the pedigree-based methods and 118 for the genomic-based estimate. Expected and observed heterozygosity levels were 0.409 and 0.403, respectively. Population substructure was evident based on the fixation index (FST), principal component analysis, and model-based population structure. These analyses provided evidence of differentiation from the foundation flock (USSES). Overall, the Polypay breed exhibited substantial genetic diversity and the presence of a population substructure that provides a basis for the implementation of genomic selection in the breed. [ABSTRACT FROM AUTHOR]

AbstractBackgroundMethodsResultsConclusionPrevious observational studies have indicated a potential association between metabolic syndrome (MetS) and asthma, though the causal nature of this connection is still uncertain. Our study used Mendelian randomization (MR) to examine the causal relationship between metabolic syndrome (MetS) and its components with asthma.This study utilized single nucleotide polymorphisms (SNPs) related to MetS and its components, sourced from publicly available genome-wide association studies (GWAS) data, in combination with asthma data from the FinnGen database. Statistical analyses were conducted using the inverse variance weighted method (IVW), MR-Egger, and weighted median method. The robustness of the findings was confirmed through various sensitivity analyses.The IVW analysis indicated that MetS was associated with an increased risk of asthma (OR = 1.0781, 95% CI = 1.0255-1.1333, p = 0.0032). Among the components of MetS, waist circumference (WC) showed a strong association with asthma (OR = 1.4777, 95% CI = 1.3412-1.6281, p = 2.8707 × 10−15). Conversely, high-density lipoprotein cholesterol (HDL-C) was found to be inversely related to the risk of asthma (OR = 0.9186, 95% CI = 0.8669-0.9734, p = 0.0041).The findings of this study support that MetS and its specific components, particularly abdominal obesity, are linked to a higher risk of asthma, while HDL-C might offer protective effects against asthma. These findings provide a foundation both for further research and possible therapeutic interventions. [ABSTRACT FROM AUTHOR]

With the increased next generation sequencing (NGS) based genetic diagnosis due to technological boon, the biomedical world is getting a substantial number of single nucleotide variations (SNVs) every day along with other genetic variations. The detected SNVs may or may not have clinical significance. Based on different levels of study, these SNVs are categorized either as disease associated or not disease associated. However, there exists another category called as "uncertain" where the scientific literature has scanty of data. These "uncertain" or "variants of uncertain significance (VUS)" has become the greatest challenge for the diagnostic fraternity since no specific decision can be taken by them for the persons carrying the VUS. Therefore, there exists a huge knowledge gap that needs to be addressed for better patient care. The present study aims to find out the possible ways of investigation that may help in reducing this knowledge gap so that decisive approaches can be made against VUS for better and accurate patient care. [ABSTRACT FROM AUTHOR]

Background: Progressive supranuclear palsy (PSP) is a rare neurodegenerative disease characterized by the accumulation of aggregated tau proteins in astrocytes, neurons, and oligodendrocytes. Previous genome-wide association studies for PSP were based on genotype array, therefore, were inadequate for the analysis of rare variants as well as larger mutations, such as small insertions/deletions (indels) and structural variants (SVs). Method: In this study, we performed whole genome sequencing (WGS) and conducted association analysis for single nucleotide variants (SNVs), indels, and SVs, in a cohort of 1,718 cases and 2,944 controls of European ancestry. Of the 1,718 PSP individuals, 1,441 were autopsy-confirmed and 277 were clinically diagnosed. Results: Our analysis of common SNVs and indels confirmed known genetic loci at MAPT, MOBP, STX6, SLCO1A2, DUSP10, and SP1, and further uncovered novel signals in APOE, FCHO1/MAP1S, KIF13A, TRIM24, TNXB, and ELOVL1. Notably, in contrast to Alzheimer's disease (AD), we observed the APOE ε2 allele to be the risk allele in PSP. Analysis of rare SNVs and indels identified significant association in ZNF592 and further gene network analysis identified a module of neuronal genes dysregulated in PSP. Moreover, seven common SVs associated with PSP were observed in the H1/H2 haplotype region (17q21.31) and other loci, including IGH, PCMT1, CYP2A13, and SMCP. In the H1/H2 haplotype region, there is a burden of rare deletions and duplications (P = 6.73 × 10–3) in PSP. Conclusions: Through WGS, we significantly enhanced our understanding of the genetic basis of PSP, providing new targets for exploring disease mechanisms and therapeutic interventions. [ABSTRACT FROM AUTHOR]

Background Postinfectious Lyme arthritis (LA) is associated with dysregulated immunity and autoreactive T- and B-cell responses in joints. Here we explored the role of host genetic variation in this outcome. Methods The frequency of 253 702 single-nucleotide polymorphisms (SNPs) was determined in 147 patients with LA (87 with postinfectious LA and 60 with antibiotic-responsive LA), and for comparison in 90 patients with erythema migrans or the general population (n = 2504). Functional outcome of candidate SNPs was assessed by evaluating their impact on clinical outcome and on immune responses in blood and synovial fluid in patients with LA. Results Six SNPs associated with late cornified envelope (LCE3) genes were present at greater frequency in patients with postinfectious LA compared to those with antibiotic-responsive LA (70% vs 30%; odds ratio, 2; P <.01). These SNPs were associated with heightened levels of inflammatory Th17 cytokines in serum but lower levels of interleukin 27, a regulatory cytokine, implying that they may contribute to dysregulated Th17 immunity in blood. Moreover, in patients with postinfectious LA, the levels of these Th17 mediators correlated directly with autoantibody responses in synovial fluid, providing a possible link between LCE3 SNPs, maladaptive systemic Th17 immunity, and autoreactive responses in joints. Conclusions Variation in the LCE3 locus, a known genetic risk factor in psoriasis and psoriatic arthritis, is associated with dysregulated systemic Th17 immunity and heightened autoantibody responses in joints. These findings underscore the importance of host genetic predisposition and systemic Th17 immunity in the pathogenesis of postinfectious (antibiotic-refractory) Lyme arthritis. [ABSTRACT FROM AUTHOR]

A fundamental goal in population genetics is to understand how variation is arrayed over natural landscapes. From first principles we know that common features such as heterogeneous population densities and barriers to dispersal should shape genetic variation over space, however there are few tools currently available that can deal with these ubiquitous complexities. Geographically referenced single nucleotide polymorphism (SNP) data are increasingly accessible, presenting an opportunity to study genetic variation across geographic space in myriad species. We present a new inference method that uses geo‐referenced SNPs and a deep neural network to estimate spatially heterogeneous maps of population density and dispersal rate. Our neural network trains on simulated input and output pairings, where the input consists of genotypes and sampling locations generated from a continuous space population genetic simulator, and the output is a map of the true demographic parameters. We benchmark our tool against existing methods and discuss qualitative differences between the different approaches; in particular, our program is unique because it infers the magnitude of both dispersal and density as well as their variation over the landscape, and it does so using SNP data. Similar methods are constrained to estimating relative migration rates, or require identity‐by‐descent blocks as input. We applied our tool to empirical data from North American grey wolves, for which it estimated mostly reasonable demographic parameters, but was affected by incomplete spatial sampling. Genetic based methods like ours complement other, direct methods for estimating past and present demography, and we believe will serve as valuable tools for applications in conservation, ecology and evolutionary biology. An open source software package implementing our method is available from https://github.com/kr‐colab/mapNN. [ABSTRACT FROM AUTHOR]

The most prevalent hip disease in neonates is developmental dysplasia of the hip (DDH). A timely and accurate diagnosis is required to provide the most effective treatment for pediatric patients with DDH. Heredity and gene variation have been the subject of increased attention and research worldwide as one of the factors contributing to the pathogenesis of DDH. Genome-wide association studies (GWAS), genome-wide linkage analyses (GWLA), and exome sequencing (ES) have identified variants in numerous genes and single-nucleotide polymorphisms (SNPs) as being associated with susceptibility to DDH in sporadic and DDH family patients. Furthermore, the DDH phenotype can be observed in animal models that exhibit susceptibility genes or loci, including variants in CX3CR1, KANSL1, and GDF5. The dentification of noncoding RNAs and de novo gene variants in patients with DDH-related syndrome has enhanced our understanding of the genes implicated in DDH. This article reviews the most recent molecular mechanisms and genetic factors that contribute to DDH. [ABSTRACT FROM AUTHOR]

Glioma represents the most common central nervous system neoplasm in adults. Current classification scheme utilizes molecular alterations, particularly IDH1.R132H, to stratify lesions into distinct prognostic groups. Identification of the single nucleotide variant through traditional tissue biopsy assessment poses procedural risks and does not fully reflect the heterogeneous and evolving tumor landscape. Here, we introduce a liquid biopsy assay, mt-IDH1dx. The blood-based test allows minimally invasive detection of tumor-derived extracellular vesicle RNA using only 2 ml plasma volume. We perform rigorous, blinded validation testing across the study population (n = 133), comprising of IDH1.R132H patients (n = 80), IDH1 wild-type gliomas (n = 44), and age matched healthy controls (n = 9). Results from our plasma testing demonstrate an overall sensitivity of 75.0% (95% CI: 64.1%–84.0%), specificity 88.7% (95% CI: 77.0%–95.7%), positive predictive value 90.9%, and negative predictive value 70.1% compared to the tissue gold standard. In addition to fundamental diagnostic applications, the study also highlights the utility of mt-IDH1dx platform for blood-based monitoring and surveillance, offering valuable prognostic information. Finally, the optimized workflow enables rapid and efficient completion of both tumor tissue and plasma testing in under 4 hours from the time of sampling. Efficient and non-invasive, liquid biopsy methods could greatly improve the molecular classification of gliomas. Here, the authors develop an RNA-based Droplet Digital PCR assay to detect the key IDH1.R132H mutation in plasma-derived extracellular vesicles from glioma patients with high sensitivity, allowing accurate diagnosis, prognostication and longitudinal monitoring. [ABSTRACT FROM AUTHOR]

Background: Gut microbiota (GM) homeostasis in the human body is closely associated with health, which can be used as a regulator for preventing the onset and progression of disease. Diabetic microvascular complications bring about not only a huge economic burden to society, but also miserable mental and physical pain. Thus, alteration of the GM may be a method to delay diabetic microvascular complications. Objective: A two-sample Mendelian randomization (MR) analysis was conducted to reveal the causal inference between GM and three core diabetic microvascular complications, namely, diabetic kidney disease (DKD), diabetic retinopathy (DR), and diabetic neuropathy (DNP). Methods: First, genome-wide association study (GWAS) summary statistics for GM from the MiBioGen consortium and three main diabetic microvascular complications acquired from the FinnGen research project were assessed. Second, a forward MR analysis was conducted to assess the causality of GM on the risk of DKD, DR, and DNP. Third, a series of sensitivity studies, such as heterogeneity tests, pleiotropy evaluations, and leave-one-out analyses, were further conducted to assess the accuracy of MR analysis. Finally, Steiger tests and reverse MR analyses were performed to appraise the possibility of reverse causation. Results: A total of 2,092 single-nucleotide polymorphisms related to 196 bacterial traits were selected as instrumental variables. This two-sample MR analysis provided strongly reasonable evidence that 28 genetically predicted abundance of specific GM that played non-negligible roles in the occurrence of DKD, DR, and DNP complications were causally associated with 23 GM, the odds ratio of which generally ranged from 0.9 to 1.1. Further sensitivity analysis indicated low heterogeneity, low pleiotropy, and high reliability of the causal estimates. Conclusion: The study raised the possibility that GM may be a potential target to prevent and delay the progression of diabetic microvascular complications. Further experiments of GM therapy on diabetic microvascular complications are warranted to clarify their effects and specific mechanisms. [ABSTRACT FROM AUTHOR]

Purpose: Alzheimer's disease (AD) is a common neurodegenerative disease, which can lead to cognitive impairment and dementia. Since AD is tightly associated with aging and cellular senescence, objective of this study was to investigate the association between senescence-related genes and proteins (SRGs and SRPs) and the development of AD. Design: The whole study was based on transcriptomic analysis of control and AD brain tissues and Mendelian randomization (MR) analysis. Methods: For transcriptomic analysis, GSE5281 dataset from GEO database contains the transcriptomic data of human brain tissues (n = 161) from control group and AD patients. The expression of SRGs in control and AD brain tissues were compared by Student's t test. For MR analysis, the instrumental singlenucleotide polymorphisms (SNPs) associated with 110 SRPs were filtered and selected from a large genome-wide association study (GWAS) for plasma proteome. The causality between plasma levels of SRPs and AD was explored using GWAS data of AD from Lambert et al. (17,008 cases and 37,154 controls) and further validated by using data from FinnGen consortium (6,489 patients and 170,489 controls). MR estimate was performed using the inversevariance weighted (IVW) method and the heterogeneity and pleiotropy of results were tested. Results: Transcriptomic analysis identified 36 up-regulated (including PLAUR) and 8 down-regulated SRGs in AD brain tissues. In addition, the MR results at both discovery and validation stages supported the causality between plasma levels of PLAUR (IVW-p = 3.04E-2, odds ratio [OR]= 1.15), CD55 (IVW-p = 1.56E-3, OR= 0.86), and SERPINE2 (IVW-p = 2.74E-2, OR= 0.91) and the risk of AD. Conclusion: Our findings identified that PLAUR, as an SRG, may take part in the development of AD and found that high plasma levels of PLAUR was associated with increased risk of AD, indicating that this gene was a risk factor for this disease and providing the rationale of existing drugs or new preventative and therapeutic strategies. [ABSTRACT FROM AUTHOR]

Background: Regions of genome-wide marker data may have differing influences on the evaluated traits. This can be reflected in the genomic models by assigning different weights to the markers, which can enhance the accuracy of genomic prediction. However, the standard multi-trait single-step genomic evaluation model can be computationally infeasible when the traits are allowed to have different marker weights. Results: In this study, we developed and implemented a multi-trait single-step single nucleotide polymorphism best linear unbiased prediction (SNPBLUP) model for large genomic data evaluations that allows for the use of precomputed trait-specific marker weights. The modifications to the standard single-step SNPBLUP model were minor and did not significantly increase the preprocessing workload. The model was tested using simulated data and marker weights precomputed using BayesA. Based on the results, memory requirements and computing time per iteration slightly increased compared to the standard single-step model without weights. Moreover, convergence of the model was slower when using marker weights, which resulted in longer total computing time. The use of marker weights, however, improved prediction accuracy. Conclusions: We investigated a single-step SNPBLUP model that can be used to accommodate trait-specific marker weights. The marker-weighted single-step model improved prediction accuracy. The approach can be used for large genomic data evaluations using precomputed marker weights. [ABSTRACT FROM AUTHOR]

AbstractObesity is a common public health problem associated with serious, life-threatening complications. MicroRNAs (miRs) have modulating roles in the immune and inflammatory systems. Therefore, this study aimed to analyze the relationship between miR-146a and morbid obesity (MO) in a Turkish population. In this study, a total of 258 subjects (110 patients with MO and 148 controls) were genotyped by the polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method to analyze miR-146a rs2910164. Then, we examined the patients as males and females separately. The results of the analyses were evaluated for statistical significance. There was a significant difference in genotype and allele frequencies of miR-146a rs2910164 between patients with MO and control individuals. miR-146a rs2910164 CC genotype and C allele were shown to increase in the MO patients’ group compared to the control group (p = 0.000, p = 0.000, respectively). Also, the C allele was higher in both female and male patients compared to controls (p = 0.000, p = 0.000, respectively). High differences were also observed when the patients and the controls were compared according to CC versus GG + GC and GG versus GC + CC (p = 0.000, p = 0.000, respectively). A significant difference was found between the female/male patients and the female/male controls in terms of GG + GC versus CC (p = 0.000, p = 0.000, respectively). To the best of our knowledge, this is the first study to investigate the relationship between this variant and MO in Turkey. Our results showed that miR-146a rs2910164 is a valuable biomarker that can be used to distinguish between patients with MO and the healthy population. The findings can be extended by increasing the sample sizes with diverse ethnicities. [ABSTRACT FROM AUTHOR]

Malaria, an ancient mosquito-borne illness caused by Plasmodium parasites, is mostly treated with Artemisinin Combination Therapy (ACT). However, Single Nucleotide Polymorphisms (SNPs) mutations in the P. falciparum Kelch 13 (PfK13) protein have been associated with artemisinin resistance (ART-R). Therefore, this study aims to generate PfK13 recombinant proteins incorporating of two specific SNPs mutations, PfK13-V494I and PfK13-N537I, and subsequently analyze their binding interactions with artemisinin (ART). The recombinant proteins of PfK13 mutations and the Wild Type (WT) variant were expressed utilizing a standard protein expression protocol with modifications and subsequently purified via IMAC and confirmed with SDS-PAGE analysis and Orbitrap tandem mass spectrometry. The binding interactions between PfK13-V494I and PfK13-N537I propeller domain proteins ART were assessed through Isothermal Titration Calorimetry (ITC) and subsequently validated using fluorescence spectrometry. The protein concentrations obtained were 0.3 mg/ml for PfK13-WT, 0.18 mg/ml for PfK13-V494I, and 0.28 mg/ml for PfK13-N537I. Results obtained for binding interaction revealed an increased fluorescence intensity in the mutants PfK13-N537I (83 a.u.) and PfK13-V494I (143 a.u.) compared to PfK13-WT (33 a.u.), indicating increased exposure of surface proteins because of the looser binding between PfK13 protein mutants with ART. This shows that the PfK13 mutations may induce alterations in the binding interaction with ART, potentially leading to reduced effectiveness of ART and ultimately contributing to ART-R. However, this study only elucidated one facet of the contributing factors that could serve as potential indicators for ART-R and further investigation should be pursued in the future to comprehensively explore this complex mechanism of ART-R. [ABSTRACT FROM AUTHOR]

Background: The Alpe-DPD study (NCT02324452) demonstrated that prospective genotyping and dose-individualization using four alleles in DPYD (DPYD*2A/rs3918290, c.1236G > A/rs75017182, c.2846A > T/rs67376798 and c.1679 T > G/rs56038477) can mitigate the risk of severe fluoropyrimidine toxicity. However, this could not prevent all toxicities. The goal of this study was to identify additional genetic variants, both inside and outside DPYD, that may contribute to fluoropyrimidine toxicity. Methods: Biospecimens and data from the Alpe-DPD study were used. Exon sequencing was performed to identify risk variants inside DPYD. In silico and in vitro analyses were used to classify DPYD variants. A genome-wide association study (GWAS) with severe fluoropyrimidine-related toxicity was performed to identify variants outside DPYD. Association with severe toxicity was assessed using matched-pair analyses for the exon sequencing and logistic, Cox, and ordinal regression analyses for GWAS. Results: Twenty-four non-synonymous, frameshift, and splice site DPYD variants were detected in ten of 986 patients. Seven of these variants (c.1670C > T, c.1913 T > C, c.1925 T > C, c.506delC, c.731A > C, c.1740 + 1G > T, c.763 − 2A > G) were predicted to be deleterious. The carriers of either of these variants showed a trend towards a 2.14-fold (95% CI, 0.41–11.3, P = 0.388) increased risk of severe toxicity compared to matched controls (N = 30). After GWAS of 942 patients, no individual single nucleotide polymorphisms achieved genome-wide significance (P ≤ 5 × 10−8), however, five variants were suggestive of association (P < 5 × 10−6) with severe toxicity. Conclusions: Results from DPYD exon sequencing and GWAS analysis did not identify additional genetic variants associated with severe toxicity, which suggests that testing for single markers at a population level currently has limited clinical value. Identifying additional variants on an individual level is still promising to explain fluoropyrimidine-related severe toxicity. In addition, studies with larger samples sizes, in more diverse cohorts are needed to identify potential clinically relevant genetic variants related to severe fluoropyrimidine toxicity. [ABSTRACT FROM AUTHOR]

Background In Santiago, Chile, where typhoid had been hyperendemic (1977–1991), we investigated whether residual chronic carriers could be detected among household contacts of non-travel-related typhoid cases occurring during 2017–2019. Methods Culture-confirmed cases were classified as autochthonous (domestically acquired) versus travel/immigration related. Household contacts of cases had stool cultures and serum Vi antibody measurements to detect chronic Salmonella Typhi carriers. Whole genome sequences of acute cases and their epidemiologically linked chronic carrier isolates were compared. Results Five of 16 autochthonous typhoid cases (31.3%) were linked to 4 chronic carriers in case households; 2 cases (onsets 23 months apart) were linked to the same carrier. Carriers were women aged 69–79 years with gallbladder dysfunction and Typhi fecal excretion; 3 had highly elevated serum anti-Vi titers. Genomic analyses revealed close identity (≤11 core genome single-nucleotide polymorphism [SNP] differences) between case and epidemiologically linked carrier isolates; all were genotypes prevalent in 1980s Santiago. A cluster of 4 additional autochthonous cases unlinked to a carrier was identified based on genomic identity (0-1 SNPs). Travel/immigration isolate genotypes were typical for the countries of travel/immigration. Conclusions Although autochthonous typhoid cases in Santiago are currently rare, 5 of 16 such cases (31.3%) were linked to elderly chronic carriers identified among household contacts of cases. [ABSTRACT FROM AUTHOR]

Background Worldwide, respiratory syncytial virus (RSV) infections are among the most common causes of infant hospitalization. Host genetic factors influencing the risk and severity of RSV infection are not well known. Methods We conducted a genome-wide association study (GWAS) to investigate single-nucleotide polymorphisms (SNPs) associated with severe RSV infections using a nested case-control design based on 2 Danish cohorts. We compared SNPs from 1786 children hospitalized with RSV to 45 060 controls without an RSV-coded hospitalization. We performed gene-based testing, tissue enrichment, gene-set enrichment, and a meta-analysis of the 2 cohorts. Finally, an analysis of potential associations between the severity of RSV infection and genetic markers was performed. Results We did not detect any significant genome-wide associations between SNPs and RSV infection or the severity of RSV. We did find potential loci associated with RSV infections on chromosome 5 in 1 cohort but failed to replicate any signals in both cohorts. Conclusions Despite being the largest GWAS of severe RSV infection, we did not detect any genome-wide significant loci. This may be an indication of a lack of power or an absence of signal. Future studies might include mild illness and need to be larger to detect any significant associations. [ABSTRACT FROM AUTHOR]

Enterovirus 71 (EV-71) has strong neurotropism, and it is the main pathogen causing severe hand, foot, and mouth disease (HFMD). In clinical observations, significant differences were observed in the severity and prognosis of HFMD among children who were also infected with EV-71. Genetic differences among individuals could be one of the important causes of differences in susceptibility to EV-71–induced HFMD. As P-selectin glycoprotein ligand-1 (PSGL-1) is an important receptor of EV-71, the correlation between single-nucleotide polymorphisms (SNPs) in PSGL-1 and the susceptibility to severe HFMD following EV-71 infection is worth studying. Given the role of PSGL-1 in immunity, the correlations between PSGL-1 SNPs and the immune status after EV-71 infection are also worth studying. Meanwhile, PSGL-1 variable number of tandem repeats (VNTR) represents a research hotspot in cardiovascular and cerebrovascular diseases, but PSGL-1 VNTR polymorphism has not been investigated in HFMD caused by EV-71 infection. In this study, specific gene fragments were amplified by polymerase chain reaction, and PSGL-1 VNTR sequences were genotyped using an automatic nucleic acid analyzer. The correlations of PSGL-1 VNTR polymorphism with the susceptibility to EV-71–associated severe HFMD and the post-infection immune status were analyzed. The PSGL-1 VNTR A allele was identified as a susceptible SNP for severe HFMD. The risk of severe HFMD was higher for AA + AB genotype carriers than for BB genotype carriers. The counts of peripheral blood lymphocyte subsets were lower in AA + AB genotype carries than in BB genotype carries. In conclusion, PSGL-1 VNTR polymorphism is associated with the susceptibility to EV-71–induced severe HFMD and the immune status after infection. PSGL-1 VNTR might play a certain role in the pathogenesis of severe cases. [ABSTRACT FROM AUTHOR]

Genetic epilepsy with febrile seizures plus (GEFS+) is a genetic epilepsy syndrome characterized by a marked hereditary tendency inherited as an autosomal dominant trait. Patients with GEFS+ may develop typical febrile seizures (FS), while generalized tonic–clonic seizures (GTCSs) with fever commonly occur between 3 months and 6 years of age, which is generally followed by febrile seizure plus (FS+), with or without absence seizures, focal seizures, or GTCSs. GEFS+ exhibits significant genetic heterogeneity, with polymerase chain reaction, exon sequencing, and single nucleotide polymorphism analyses all showing that the occurrence of GEFS+ is mainly related to mutations in the gamma-aminobutyric acid type A receptor gamma 2 subunit (GABRG2) gene. The most common mutations in GABRG2 are separated in large autosomal dominant families, but their pathogenesis remains unclear. The predominant types of GABRG2 mutations include missense (c.983A → T, c.245G → A, p.Met199Val), nonsense (R136*, Q390*, W429*), frameshift (c.1329delC, p.Val462fs*33, p.Pro59fs*12), point (P83S), and splice site (IVS6+2T → G) mutations. All of these mutations types can reduce the function of ion channels on the cell membrane; however, the degree and mechanism underlying these dysfunctions are different and could be linked to the main mechanism of epilepsy. The γ2 subunit plays a special role in receptor trafficking and is closely related to its structural specificity. This review focused on investigating the relationship between GEFS+ and GABRG2 mutation types in recent years, discussing novel aspects deemed to be great significance for clinically accurate diagnosis, anti-epileptic treatment strategies, and new drug development. [ABSTRACT FROM AUTHOR]

Background/Objectives: This study aims to elucidate the genetic causes of congenital hypogonadotropic hypogonadism (CHH), a rare genetic disorder resulting in GnRH deficiency, in six families from Pakistan. Methods: Eighteen DNA samples from six families underwent genome sequencing followed by standard evaluation for pathogenic single nucleotide variants (SNVs) and small indels. All families were subsequently analyzed for pathogenic copy number variants (CNVs) using CoverageMaster. Results: Novel pathogenic homozygous SNVs in known CHH genes were identified in four families: two families with variants in GNRHR, and two others harboring KISS1R variants. Subsequent investigation of CNVs in the remaining two families identified novel unique large deletions in ANOS1. Conclusion: A combined, systematic analysis of single nucleotide and CNVs helps to improve the diagnostic yield for variants in patients with CHH. [ABSTRACT FROM AUTHOR]

Loss of function mutations in the checkpoint kinase gene CHEK2 are associated with increased risk of breast and other cancers. Most of the 3,188 unique amino acid changes that can result from non-synonymous single nucleotide variants (SNVs) of CHEK2, however, have not been tested for their impact on the function of the CHEK2-enocded protein (CHK2). One successful approach to testing the function of variants has been to test for their ability to complement mutations in the yeast ortholog of CHEK2, RAD53. This approach has been used to provide functional information on over 100 CHEK2 SNVs and the results align with functional assays in human cells and known pathogenicity. Here we tested all but two of the 4,887 possible SNVs in the CHEK2 open reading frame for their ability to complement RAD53 mutants using a high throughput technique of deep mutational scanning (DMS). Among the non-synonymous changes, 770 were damaging to protein function while 2,417 were tolerated. The results correlate well with previous structure and function data and provide a first or additional functional assay for all the variants of uncertain significance identified in clinical databases. Combined, this approach can be used to help predict the pathogenicity of CHEK2 variants of uncertain significance that are found in susceptibility screening and could be applied to other cancer risk genes. Author summary: Variations in gene sequences account for many of the phenotypic differences between individuals, including different susceptibilities to diseases like cancer. Individuals who inherit specific variants in the CHEK2 gene, for example, have increased risk of developing breast cancer and other cancers. These cancer-associated variants all abolish the normal activity of the CHEK2-encoded protein, a protein kinase called Chk2. Most of the CHEK2 variants found in individuals, however, have an unknown effect on the function of the Chk2 protein, and therefore an unknown potential role in cancer. This is because it is cumbersome to individually make and test each newly identified variant to see whether it affects protein function. Here we use an efficient version of a technique called deep mutational scanning to test nearly all possible CHEK2 single nucleotide variants for their impact on Chk2 protein function. Analyses of the resulting data indicate that it will be useful for developing models to predict the cancer risk in individuals who inherit any CHEK2 variants. This study also demonstrates a viable efficient approach to study variants of other genes, including other cancer related genes. [ABSTRACT FROM AUTHOR]

Major depressive disorder (MDD) is considerably heterogeneous in terms of comorbidities, which may hamper the disentanglement of its biological mechanism. In a previous study, we classified the lifetime trajectories of MDD-related multimorbidities into seven distinct clusters, each characterized by unique genetic and environmental risk-factor profiles. The current objective was to investigate genome-wide gene-by-environment (G × E) interactions with childhood trauma burden, within the context of these clusters. We analyzed 77,519 participants and 6,266,189 single-nucleotide polymorphisms (SNPs) of the UK Biobank database. Childhood trauma burden was assessed using the Childhood Trauma Screener (CTS). For each cluster, Plink 2.0 was used to calculate SNP × CTS interaction effects on the participants' cluster membership probabilities. We especially focused on the effects of 31 candidate genes and associated SNPs selected from previous G × E studies for childhood maltreatment's association with depression. At SNP-level, only the high-multimorbidity Cluster 6 revealed a genome-wide significant SNP rs145772219. At gene-level, MPST and PRH2 were genome-wide significant for the low-multimorbidity Clusters 1 and 3, respectively. Regarding candidate SNPs for G × E interactions, individual SNP results could be replicated for specific clusters. The candidate genes CREB1, DBH , and MTHFR (Cluster 5) as well as TPH1 (Cluster 6) survived multiple testing correction. CTS is a short retrospective self-reported measurement. Clusters could be influenced by genetics of individual disorders. The first G × E GWAS for MDD-related multimorbidity trajectories successfully replicated findings from previous G × E studies related to depression, and revealed risk clusters for the contribution of childhood trauma. • First G × E GWAS with childhood trauma for MDD-related multimorbidity trajectories. • Most G × E findings for high MDD-multimorbidity Clusters 5–6. • Significant correlation between cluster probability and CTS (high vs low risk clusters). • stronger genetic findings in the clusters with higher childhood trauma burden. • Differential effects of candidate genes in different comorbidity clusters. [ABSTRACT FROM AUTHOR]

The treponemes infecting lagomorphs include Treponema paraluisleporidarum ecovar Cuniculus (TPeC) and ecovar Lepus (TPeL), infecting rabbits and hares, respectively. In this study, we described the first complete genome sequence of TPeL, isolate V3603-13, from an infected mountain hare (Lepus timidus) in Sweden. In addition, we determined 99.0% of the genome sequence of isolate V246-08 (also from an infected mountain hare, Sweden) and 31.7% of the genome sequence of isolate Z27 A77/78 (from a European hare, Lepus europeaus, The Netherlands). The TPeL V3603-13 genome had considerable gene synteny with the TPeC Cuniculi A genome and with the human pathogen T. pallidum, which causes syphilis (ssp. pallidum, TPA), yaws (ssp. pertenue, TPE) and endemic syphilis (ssp. endemicum, TEN). Compared to the TPeC Cuniculi A genome, TPeL V3603-13 contained four insertions and 11 deletions longer than three nucleotides (ranging between 6 and2,932 nts). In addition, there were 25 additional indels, from one to three nucleotides long, altogether spanning 36 nts. The number of single nucleotide variants (SNVs) between TPeC Cuniculi A and TPeL V3603-13 were represented by 309 nucleotide differences. Major proteome coding differences between TPeL and TPeC were found in the tpr gene family, and (predicted) genes coding for outer membrane proteins, suggesting that these components are essential for host adaptation in lagomorph syphilis. The phylogeny revealed that the TPeL sample from the European brown hare was more distantly related to TPeC Cuniculi A than V3603-13 and V246-08. [ABSTRACT FROM AUTHOR]

The causal relationship between lipid levels and bladder cancer is still inconclusive currently. We aimed to reveal the causal relationship between triglycerides, HDL, and LDL and the risk of bladder cancer by univariable and multivariable Mendelian randomization (MR) analysis. The single nucleotide polymorphisms (SNPs) of exposure (triglycerides: 441,016 samples; HDL: 403,943 samples; LDL: 440,546 samples) were obtained from UK Biobank. The Genetic variation related to bladder cancer included 1554 cases and 359,640 controls. Univariable and multivariable MR methods were conducted with subsequent analysis, and smoking was regarded as a confounder. The inverse-variance weighted (IVW), MR-Egger, weighted-median method, Cochran's Q test, and MR-PRESSO were considered the main MR analysis and sensitivity analysis methods. Univariable MR analysis results suggested the triglycerides level (P = 0.011, OR = 1.001, 95% CI = 1.000–1.002) was causally associated with increased risk of bladder cancer. Multivariable MR results indicated that higher triglyceride levels could still increase the risk of bladder cancer after adjusting the effects of HDL, LDL, and smoking (P = 0.042, OR = 1.001, 95% CI = 1.000–1.002). Our findings supported that triglyceride level is causally associated with an increased risk of bladder cancer independent of LDL and HDL at the genetic level. Timely attention to changes in blood lipid levels might reduce the risk of bladder cancer. [ABSTRACT FROM AUTHOR]

Single nucleotide polymorphism (SNP) interactions are the key to improving polygenic risk scores. Previous studies reported several significant SNP–SNP interaction pairs that shared a common SNP to form a cluster, but some identified pairs might be false positives. This study aims to identify factors associated with the cluster effect of false positivity and develop strategies to enhance the accuracy of SNP–SNP interactions. The results showed the cluster effect is a major cause of false-positive findings of SNP–SNP interactions. This cluster effect is due to high correlations between a causal pair and null pairs in a cluster. The clusters with a hub SNP with a significant main effect and a large minor allele frequency (MAF) tended to have a higher false-positive rate. In addition, peripheral null SNPs in a cluster with a small MAF tended to enhance false positivity. We also demonstrated that using the modified significance criterion based on the 3 p-value rules and the bootstrap approach (3pRule + bootstrap) can reduce false positivity and maintain high true positivity. In addition, our results also showed that a pair without a significant main effect tends to have weak or no interaction. This study identified the cluster effect and suggested using the 3pRule + bootstrap approach to enhance SNP–SNP interaction detection accuracy. [ABSTRACT FROM AUTHOR]

The low heritability of reproduction traits such as total number born (TNB), number born alive (NBA) and adjusted litter weight until 21 days at weaning (ALW) poses a challenge for genetic improvement. In this study, we aimed to identify genetic variants that influence these traits and evaluate the accuracy of genomic selection (GS) using these variants as genomic features. We performed single‐step genome‐wide association studies (ssGWAS) on 17 823 Large White (LW) pigs, of which 2770 were genotyped by 50K single nucleotide polymorphism (SNP) chips. Additionally, we analyzed runs of homozygosity (ROH) in the population and tested their effects on the traits. The genomic feature best linear unbiased prediction (GFBLUP) was then carried out in an independent population of 350 LW pigs using identified trait‐related SNP subsets as genomic features. As a result, our findings identified five, one and four SNP windows that explaining more than 1% of genetic variance for ALW, TNB, and NBA, respectively and discovered 358 hotspots and nine ROH islands. The ROH SSC1:21814570–27186456 and SSC11:7220366–14276394 were found to be significantly associated with ALW and NBA, respectively. We assessed the genomic estimated breeding value accuracy through 20 replicates of five‐fold cross‐validation. Our findings demonstrate that GFBLUP, incorporating SNPs located in effective ROH (p‐value < 0.05) as genomic features, might enhance GS accuracy for ALW compared with GBLUP. Additionally, using SNPs explaining more than 0.1% of the genetic variance in ssGWAS for NBA as genomic features might improve the GS accuracy, too. However, it is important to note that the incorporation of inappropriate genomic features can significantly reduce GS accuracy. In conclusion, our findings provide valuable insights into the genetic mechanisms of reproductive traits in pigs and suggest that the ssGWAS and ROH have the potential to enhance the accuracy of GS for reproductive traits in LW pigs. [ABSTRACT FROM AUTHOR]

The article discusses a study which identified a potential pharmacogenomic interaction between a single-nucleotide polymorphism (SNP) in Toll interactive protein (TOLLIP) and treatment with N-acetylceysteine in patients with idiopathic pulmonary fibrosis (IPF). Topics include TOLLIP SNPs associated with IPF susceptibility, how TOLLIP rs3750920 SNP genotyping was performed, and the need for further mechanistic studies to better understand the interplay between TOLLIP and doxycycline in IPF.

Agarwood is a valuable traditional medicine and fragrance. The production process is a typical injury-induced defense response. Currently, there are approximately 22 known species in the genus Aquilaria Lam., all of which can produce agarwood, whereas there are only two legal species of traditional Chinese medicinal agarwood, Aquilaria sinensis (Lour.) Spreng. and Aquilaria agallocha (Lour.) Roxb. The Taiwan herbal Pharmacopoeia of China stipulates that the medicinal agarwood species are A. sinensis and its relatives in the same genus. Moreover, there are five species of agarwood available for clinical medicinal use in Japan, including A. agallocha and A. sinensis, which are often confused with each other or used in a mixed way in the trade process. Therefore, accurate identification of traditional Chinese medicinal agarwood species is important to ensure the authenticity of traditional medicines and to guide the safety of clinical medication. In this study, 59 specific single-nucleotide polymorphism loci were screened and obtained from the chloroplast genomes of 12 species of the genus Aquilaria Lam. We established an identification method for traditional Chinese medicinal agarwood using mini-barcoding combined with high-resolution melting (HRM) and designed and validated 10 pairs of primers from the psbM-trnD, psbA, rps16, petN, ndhE-psaC, rps4, atpE, ycf1, rps15-trnN, and matK regions. The amplification products were all less than 200 bp, with a high success rate of amplification. The method was applied to successfully identify traditional Chinese medicinal agarwood species from commercial agarwood samples. Overall, the sensitivity of this method was sufficient to detect 1% of adulterants in medicinal agarwood products, proving that mini-barcoding HRM is a powerful and flexible tool. This method can be used as a fast and effective high-throughput method for authenticity testing of traditional Chinese medicinal agarwood and its raw materials containing agarwoodcontaining proprietary Chinese medicines and is recommended for industrial applications. [ABSTRACT FROM AUTHOR]

Background: The toxin-antitoxin (TA) system plays a vital role in the virulence and pathogenicity of Mycobacterium tuberculosis (M. tuberculosis). However, the regulatory mechanisms and the impact of gene mutations on M. tuberculosis transmission remain poorly understood. Objective: To investigate the influence of gene mutations in the toxin-antitoxin system on M. tuberculosis transmission dynamics. Method: We performed whole-genome sequencing on the analyzed strains of M. tuberculosis. The genes associated with the toxin-antitoxin system were obtained from the National Center for Biotechnology Information (NCBI) Gene database. Mutations correlating with enhanced transmission within the genes were identified by using random forest, gradient boosting decision tree, and generalized linear mixed models. Results: A total of 13,518 M. tuberculosis isolates were analyzed, with 42.29% (n = 5,717) found to be part of genomic clusters. Lineage 4 accounted for the majority of isolates (n = 6488, 48%), followed by lineage 2 (n = 5133, 37.97%). 23 single nucleotide polymorphisms (SNPs) showed a positive correlation with clustering, including vapB1 G34A, vapB24 A76C, vapB2 T171C, mazF2 C85T, mazE2 G104A, vapB31 T112C, relB T226A, vapB11 C54T, mazE5 T344C, vapB14 A29G, parE1 (C103T, C88T), and parD1 C134T. Six SNPs, including vapB6 A29C, vapB31 T112C, parD1 C134T, vapB37 G205C, Rv2653c A80C, and vapB22 C167T, were associated with transmission clades across different countries. Notably, our findings highlighted the positive association of vapB6 A29C, vapB31 T112C, parD1 C134T, vapB37 G205C, vapB19 C188T, and Rv2653c A80C with transmission clades across diverse regions. Furthermore, our analysis identified 32 SNPs that exhibited significant associations with clade size. Conclusion: Our study presents potential associations between mutations in genes related to the toxin-antitoxin system and the transmission dynamics of M. tuberculosis. However, it is important to acknowledge the presence of confounding factors and limitations in our study. Further research is required to establish causation and assess the functional significance of these mutations. These findings provide a foundation for future investigations and the formulation of strategies aimed at controlling TB transmission. [ABSTRACT FROM AUTHOR]

Background: Constipation is affected by a number of risk variables, including cardiovascular disease and growth factors. However, the impacts of gut flora on constipation incidence has not been shown. This work, Single-Variable Mendelian Randomization (SVMR) was utilized to estimate the causal relationship between the Eubacterium genus or Rumphococcus, and constipation. Methods: Data for constipation, Eubacterium genus and Rumphococcus were taken from the Integrated Epidemiology Unit (IEU) open GWAS database. Including 218,792 constipation samples, and there were 16,380,466 Single Nucleotide Polymorphisms (SNPs) for constipation. The ids of Eubacterium genus and Rumphococcus were sourced from MiBioGen database. The sample count for the Eubacterium genus was 17,380, with 656 SNPs. In addition, the sample size for Rumphococcus was 15,339, with 545 SNPs. The SVMR was performed to assess the risk of Eubacterium genus and Rumphococcus in constipation using weighted median, MR Egger, simple mode, inverse variance weighted (IVW), and weighted mode. Finally, we did a sensitivity analysis that included a heterogeneity, horizontal pleiotropy, and Leave-One-Out (LOO) test to examine the viability of the MR data. Results: The SVMR revealed that the Eubacterium genus and Rumphococcus were causally connected to constipation, with Rumphococcus (P = 0.042, OR = 1.074) as a hazardous factor and Eubacteriumgenus (P = 0.004, OR = 0.909) as a safety factor. Sensitivity tests then revealed the absence of variability between the constipation and the exposure factors (Eubacteriumgenus and Rumphococcus). Additionally, there were no other confounding factors and the examined SNPs could only influence constipation through the aforementioned exposure factors, respectively. As a result, the MR results were fairly robust. Conclusion: Our investigation verified the causal links between the Eubacterium genus or Rumphococcus, and constipation, with greater Rumphococcus expression increasing the likelihood of constipation and the opposite being true for the Eubacterium genus. [ABSTRACT FROM AUTHOR]

Chimeric RNAs, which can arise from gene recombination at the DNA level or non‐canonical splicing events at the RNA level, have been identified as important roles in human tumors. Dysregulated gene expression caused by somatic mutations and altered splicing patterns of oncogenes or tumor suppressor genes can contribute to the development of tumors. Therefore, investigating the formation mechanism of chimeric RNAs via somatic mutations is critical for understanding tumor pathogenesis. This project is the first to propose studying the association between somatic single nucleotide variants and chimeric RNAs, identifying around 2900 somatic SNVs affecting chimeric RNAs in pan‐cancer level. The somatic SNVs on chimeric RNAs were commonly observed in various types of tumor tissues, providing a valuable resource for future study. Additionally, these SNVs show distinct tumor specificity, and those with high frequency had a significant impact on the survival time of patients with tumors. Further research revealed that somatic SNVs associated with chimeric RNA (chiR‐SNVs) were typically found within 10 nt of the junction site of chimeric RNAs and had a particularly significant effect on chimeric RNAs from different chromosomes. The enrichment analysis revealed that chiR‐SNVs were significantly overrepresented in oncogenes and genes related to RNA binding proteins involved in RNA splicing, which could imply that chiR‐SNVs may disrupt the process of RNA splicing and induce the occurrence of chimeric RNAs. This study sheds light on the potential molecular interaction mechanism between somatic SNVs and chimeric RNAs, which opens up a new avenue for researching disease pathway and tumorigenesis development. [ABSTRACT FROM AUTHOR]

Structural variants (SVs) significantly contribute to human genome diversity and play a crucial role in precision medicine. Although advancements in single-molecule long-read sequencing offer a groundbreaking resource for SV detection, identifying SV breakpoints and sequences accurately and robustly remains challenging. We introduce VolcanoSV, an innovative hybrid SV detection pipeline that utilizes both a reference genome and local de novo assembly to generate a phased diploid assembly. VolcanoSV uses phased SNPs and unique k-mer similarity analysis, enabling precise haplotype-resolved SV discovery. VolcanoSV is adept at constructing comprehensive genetic maps encompassing SNPs, small indels, and all types of SVs, making it well-suited for human genomics studies. Our extensive experiments demonstrate that VolcanoSV surpasses state-of-the-art assembly-based tools in the detection of insertion and deletion SVs, exhibiting superior recall, precision, F1 scores, and genotype accuracy across a diverse range of datasets, including low-coverage (10x) datasets. VolcanoSV outperforms assembly-based tools in the identification of complex SVs, including translocations, duplications, and inversions, in both simulated and real cancer data. Moreover, VolcanoSV is robust to various evaluation parameters and accurately identifies breakpoints and SV sequences. Detecting genomic structural variants (SVs) using long-read sequencing remains challenging. Here the authors introduce a hybrid pipeline for precise haplotype-resolved SV discovery that outperforms current tools across diverse long-read sequencing datasets. [ABSTRACT FROM AUTHOR]

Cultivated potato, Solanum tuberosum L., is considered an autotetraploid with 12 chromosomes with four homologous phases. However, recent evidence found that, due to frequent large phase deletions in the genome, gene ploidy is not constant across the genome. The elite cultivar "Otava" was found to have an average gene copy number of 3.2 across all loci. Breeding programs for elite potato cultivars rely increasingly on genomic prediction tools for selection breeding and elucidation of quantitative trait loci underpinning trait genetic variance. These are typically based on anonymous single nucleotide polymorphism (SNP) markers, which are usually called from, for example, SNP array or sequencing data using a tetraploid model. In this study, we analyzed the impact of using whole genome markers genotyped as either tetraploid or observed allele frequencies from genotype-by-sequencing data on single-trait additive genomic best linear unbiased prediction (GBLUP) genomic prediction (GP) models and single-marker regression genome-wide association studies of potato to evaluate the implications of capturing varying ploidy on the statistical models employed in genomic breeding. A panel of 762 offspring of a diallel cross of 18 parents of elite breeding material was used for modeling. These were genotyped by sequencing and phenotyped for five key performance traits: chipping quality, length/width ratio, senescence, dry matter content, and yield. We also estimated the read coverage required to confidently discriminate between a heterozygous triploid and tetraploid state from simulated data. It was found that using a tetraploid model neither impaired nor improved genomic predictions compared to using the observed allele frequencies that account for true marker ploidy. In genome-wide associations studies (GWAS), very minor variations of both signal amplitude and number of SNPs supporting both minor and major quantitative trait loci (QTLs) were observed between the two data sets. However, all major QTLs were reproducible using both data sets. [ABSTRACT FROM AUTHOR]

Introduction: Chronic obstructive pulmonary disease (COPD) is associated with tobacco smoking and biomass-burning smoke exposure. Toll-like receptor 4 (TLR4) single-nucleotide polymorphisms (SNPs) may contribute to its pathogenesis. The study aimed to assess the association of rs4986790 and rs4986791 in the TLR4 gene in aMexican mestizo populationwith COPD secondary to tobacco smoking (COPDTS) and biomass-burning smoke (COPD-BBS) and to evaluate whether the genotypes of risk affect cytokine serum levels. Materials and methods: We enrolled 2,092 participants and divided them into two comparisons according to their environmental exposure. SNPs were genotyped using TaqMan probes. Serum cytokine levels (IL-4, IL-5, IL-6, IL-10, and INF-γ) were quantified by ELISA. Results: The rs4986790 AA genotype in COPD-TS was associated with a higher COPD risk (OR = 3.53). Haplotype analysis confirmed this association, identifying a block containing the rs4986790 allele (A-C, OR = 3.11). COPD-TS exhibited elevated IL-6, IL-4, and IL-5 levels compared with smokers without COPD (SWOC), whereas COPD-BBS displayed higher IFN-γ, IL-6, and IL-10 levels. The AA carriers in the COPD-TS group had elevated IL-4, IL-5, and IFN-γ compared with carriers of AG or GG. Conclusion: The rs4986790 common allele and the A-C haplotype (rs4986790-rs4986791) were associated with a higher COPD risk in smokers; COPD patients carrying the AA genotype showed increased pro-inflammatory cytokines. [ABSTRACT FROM AUTHOR]

Single-cell RNA sequencing predominantly employs short-read sequencing to characterize cell types, states and dynamics; however, it is inadequate for comprehensive characterization of RNA isoforms. Long-read sequencing technologies enable single-cell RNA isoform detection but are hampered by lower throughput and unintended sequencing of artifacts. Here we develop Single-cell Targeted Isoform Long-Read Sequencing (scTaILoR-seq), a hybridization capture method which targets over a thousand genes of interest, improving the median number of on-target transcripts per cell by 29-fold. We use scTaILoR-seq to identify and quantify RNA isoforms from ovarian cancer cell lines and primary tumors, yielding 10,796 single-cell transcriptomes. Using long-read variant calling we reveal associations of expressed single nucleotide variants (SNVs) with alternative transcript structures. Phasing of SNVs across transcripts enables the measurement of allelic imbalance within distinct cell populations. Overall, scTaILoR-seq is a long-read targeted RNA sequencing method and analytical framework for exploring transcriptional variation at single-cell resolution. Long-read sequencing allows the detection of RNA isoforms, but is hampered by low throughput and potential artefacts. Here, the authors develop the scTaILoR-seq hybridisation capture method for long-read RNA sequencing to improve transcript detection, and use this method to detect isoforms at the single-cell level in ovarian cancer. [ABSTRACT FROM AUTHOR]