Genetic variation and molecular profiling of congenital malformations of the female genital tract based on whole-genome sequencing.

BACKGROUND: Congenital malformations of the female genital tract (CM-FGT) are characterized by abnormal development of the fallopian tubes, uterus, and vagina, often accompanied by malformations in the urinary system, bones and hearing. However, no definitive pathogenic genes and molecular genetic causes have been identified. METHODS: We present the largest whole-genome sequencing study of CM-FGT to date, analyzing 590 individuals in China: 95 patients, 442 case-controls, and 53 familial controls. RESULTS: Among the patients, 5.3% carried known CM-FGT-related variants. Pedigree and case-control analyses in two dimensions of coding and non-coding regulatory regions revealed seven novel de novo copy number variations, 12 rare single-nucleotide variations, and 10 rare 3' untranslated region (UTR) mutations in genes related to CM-FGT, particularly highlighting ASH1L as a pathogenic gene. Single-cell sequencing data showed that the majority of CM-FGT-related risk genes are spatiotemporally specifically expressed early in uterus development. CONCLUSIONS: In conclusion, this study identified novel variants related to CM-FGT, particularly highlighting ASH1L as a pathogenic gene. The findings provide insights into the genetic variants underlying CM-FGT, with single-cell sequencing data revealing spatiotemporal specific expression patterns of key risk genes early in uterine development. This study significantly advances the understanding of CM-FGT etiology and genetic landscape, offering new opportunities for prenatal screening.

High frequency of GATA2 variants in patients with pulmonary fungal disease without immunocompromised risk factors: a retrospective study.

Background: The global incidence of pulmonary fungal diseases is on the rise. Individuals harboring underlying immunocompromised conditions such as human immunodeficiency virus (HIV)/acquired immune deficiency syndrome (AIDS), malignant tumors, or those who have undergone organ transplantation, among others, are particularly susceptible to fungal infections. However, in clinical practice, certain patients diagnosed with pulmonary fungal infections exhibit no discernible risk factors for immunosuppression. GATA2, a pivotal transcription factor governing hematopoiesis, is implicated in GATA2 deficiency, predisposing individuals to fungal infections. This study aims to scrutinize GATA2 variants in adult patients afflicted with pulmonary fungal infections devoid of recognized risk factors for immunosuppression. Methods: A cohort of adult patients (aged 18-65 years old, n=22) diagnosed with pulmonary fungal diseases lacking underlying immunosuppression risk factors, treated at Sun Yat-sen Memorial Hospital from January 2016 to December 2021, underwent Sanger sequencing of the GATA2 gene. Results: Among the 22 patients devoid of immunocompromised risk factors and diagnosed with pulmonary fungal diseases, 17 patients (77.3%) exhibited single nucleotide variants (SNVs) within the exons of the GATA2 gene. Notably, exon 3 variants were present in 7 cases (41.2%), exon 4 variants in 10 cases (58.8%), and exon 5 variants in 11 cases (64.7%), emerging as the most prevalent exonic variants within GATA2. Among the 17 patients harboring GATA2 SNVs, a total of 28 SNVs were identified. Of these, eight variants (NM_001145661.2:c.33G>A, NM_001145661.2:c.523C>T, NM_001145661.2:c.77A>G, NM_001145661.2:c.545C>T, NM_001145661.2:c.7G>A, NM_001145661.2:c.1406A>G, NM_001145661.2:c.977A>G, NM_001145661.2:c.742A>C) were identified as missense mutations with the potential to alter the structure and function of the GATA2 protein on the basis of multiple in silico predictive programs interpretation. One nonsense mutation (NM_001145661.2:c.664A>T) was classified as "likely pathogenic" according to 2015 American College of Medical Genetics and Genomics (ACMG) guidelines. Conclusions: GATA2 variants are prevalent among patients afflicted with pulmonary fungal infections in the absence of traditional immunosuppressive risk factors. Further investigations are warranted to elucidate the impact of GATA2 variants on the expression and functionality of the GATA2 protein.

Genetic interactions and pleiotropy in metabolic diseases: Insights from a comprehensive GWAS analysis.

This study offers insights into the genetic and biological connections between nine common metabolic diseases using data from genome-wide association studies. Our goal is to unravel the genetic interactions and biological pathways of these complex diseases, enhancing our understanding of their genetic architecture. We employed a range of advanced analytical techniques to explore the genetic correlations and shared genetic variants of these diseases. These methods include Linked Disequilibrium Score Regression, High-Definition Likelihood (HDL), genetic analysis combining multiplicity and annotation (GPA), two-sample Mendelian randomization analyses, analysis under the multiplicity-complex null hypothesis (PLACO), and Functional mapping and annotation of genetic associations (FUMA). Additionally, Bayesian co-localization analyses were used to examine associations of specific loci across traits. Our study discovered significant genomic correlations and shared loci, indicating complex genetic interactions among these metabolic diseases. We found several shared single nucleotide variants and risk loci, notably highlighting the role of the immune system and endocrine pathways in these diseases. Particularly, rs2476601 and its associated gene PTPN22 appear to play a crucial role in the connection between type 2 diabetes mellitus, hypothyroidism/mucous oedema and hypoglycaemia. These findings enhance our understanding of the genetic underpinnings of these diseases and open new potential avenues for targeted therapeutic and preventive strategies. The results underscore the importance of considering pleiotropic effects in deciphering the genetic architecture of complex diseases, especially metabolic ones.

AI-derived comparative assessment of the performance of pathogenicity prediction tools on missense variants of breast cancer genes.

Single nucleotide variants (SNVs) can exert substantial and extremely variable impacts on various cellular functions, making accurate predictions of their consequences challenging, albeit crucial especially in clinical settings such as in oncology. Laboratory-based experimental methods for assessing these effects are time-consuming and often impractical, highlighting the importance of in-silico tools for variant impact prediction. However, the performance metrics of currently available tools on breast cancer missense variants from benchmarking databases have not been thoroughly investigated, creating a knowledge gap in the accurate prediction of pathogenicity. In this study, the benchmarking datasets ClinVar and HGMD were used to evaluate 21 Artificial Intelligence (AI)-derived in-silico tools. Missense variants in breast cancer genes were extracted from ClinVar and HGMD professional v2023.1. The HGMD dataset focused on pathogenic variants only, to ensure balance, benign variants for the same genes were included from the ClinVar database. Interestingly, our analysis of both datasets revealed variants across genes with varying penetrance levels like low and moderate in addition to high, reinforcing the value of disease-specific tools. The top-performing tools on ClinVar dataset identified were MutPred (Accuracy = 0.73), Meta-RNN (Accuracy = 0.72), ClinPred (Accuracy = 0.71), Meta-SVM, REVEL, and Fathmm-XF (Accuracy = 0.70). While on HGMD dataset they were ClinPred (Accuracy = 0.72), MetaRNN (Accuracy = 0.71), CADD (Accuracy = 0.69), Fathmm-MKL (Accuracy = 0.68), and Fathmm-XF (Accuracy = 0.67). These findings offer clinicians and researchers valuable insights for selecting, improving, and developing effective in-silico tools for breast cancer pathogenicity prediction. Bridging this knowledge gap contributes to advancing precision medicine and enhancing diagnostic and therapeutic approaches for breast cancer patients with potential implications for other conditions.

Exploring the Role of the TAS2R16 Protein and Its Single Nucleotide Variants in Pituitary Adenoma Development.

BACKGROUND: Pituitary adenoma (PA) is a common benign tumor that develops in the pituitary gland, causing hormonal imbalances and potential health issues. The TAS2R16 gene codes for a taste receptor and is involved in bitter taste perception, but there is currently no known direct link between this gene and pituitary adenoma. METHODS: This study included 221 healthy controls and 131 patients with pituitary adenoma (PA) from the Lithuanian population. DNA was isolated from peripheral venous blood using the salt precipitation method. Genotyping was performed via RT-PCR. Statistical analysis was conducted with IBM SPSS Statistics 29.0 software, incorporating the Bonferroni correction for multiple comparisons. RESULTS: This study found that the TAS2R16 rs978739 C allele is less common in the non-invasive PA group compared to the control group (p = 0.045). The TAS2R16 rs860170 CT genotype reduces the likelihood of developing non-invasive PA by 1.9-fold under the codominant (p = 0.024) and overdominant (p = 0.030) models. The odds of developing non-invasive PA are reduced by 2-fold under the dominant (p = 0.021) model for TAS2R16 rs860170 CT + CC genotypes and by 2-fold under the additive (p = 0.018) model for each TAS2R16 rs860170 C allele. The PA group had higher serum levels of TAS2R16 than the control group (p < 0.001). The present study found that patients with the TAS2R16 rs978739 TT or CT genotype had higher serum TAS2R16 levels and protein concentrations than healthy individuals (p = 0.025 and p = 0.019, respectively), and those with the AA or AG genotype of TAS2R16 rs1357949 had higher protein concentrations (p = 0.005 and p = 0.007, respectively). CONCLUSIONS: The TAS2R16 rs978739 C allele was less common in the non-invasive PA group compared to the control group, while the TAS2R16 rs860170 CT genotype was linked to a reduced likelihood of developing non-invasive PA. Additionally, the PA group showed higher serum levels of TAS2R16, and increased serum protein concentrations were observed in PA patients with specific TAS2R16 variants.

Association of SCN1A Polymorphisms rs3812718 and rs2298771 with Epilepsy.

Background/Objectives: Epilepsy is a brain disease with both environmental and genetic inputs. Ion channel dysfunction seems to be of great significance for abnormal neuronal behavior during epileptic seizures. Within neurons, the voltage-gated sodium channels are crucial proteins contributing to the initiation and propagation of action potentials. The voltage-gated sodium channel α subunit 1 (SCN1A) gene encodes for the α subunit of a voltage-gated ion channel. The aim of the study was to investigate the relation of two common SCN1A variants, i.e., rs3812718 and rs2298771, with distinct epileptic phenotypes in a South-Eastern European population. Methods: DNA was extracted from 214 unrelated participants with focal onset, focal to bilateral tonic-clonic, or generalized onset epileptic seizures and genotyped using real-time PCR (LightSNiP assays) followed by melting curve analysis. Statistical analysis of the results was performed using IBM SPSS Statistics software (version 29.0 for Windows). Results: Genotype frequency distribution analysis indicated an association for the A-allele-containing genotypes of both rs3812718 and rs2298771 polymorphisms of SCN1A with generalized onset seizures and focal to bilateral tonic-clonic seizures versus focal onset seizures. Conclusions: Consequently, the study provides evidence that supports a potential association of the investigated SCN1A polymorphisms with distinct seizure subtype susceptibility in South-Eastern Europeans.

Investigating the Link between STAT4 Genetic Variants, STAT4 Protein Concentrations, and Laryngeal Squamous Cell Carcinoma: A Comprehensive Analysis of Clinical Manifestations.

According to recent research, inflammatory STAT4 and its protein impact may be important factors in developing cancerous diseases. Still unanalyzed is this effect in patients with laryngeal squamous cell carcinoma (LSCC). In the present study, we evaluated four single nucleotide variants (SNVs) of STAT4 (rs10181656, rs7574865, rs7601754, and rs10168266) and STAT4 serum levels to determine their link between LSCC development and its clinical manifestations. A total of 632 men (324 LSCC patients and 338 healthy individuals) were involved in this study. The genotyping was carried out using real-time PCR. Additionally, we measured 80 study subjects' (40 LSCC patients and 40 control subjects) STAT4 protein concentrations using an enzyme-linked immunosorbent assay (ELISA). In our study, the T allele of STAT4 rs7574865 significantly increases the likelihood of LSCC occurrence by 1.4-fold. Additionally, this SNV is associated with higher odds of early-stage disease, T1 size LSCC development, absence of metastasis to neck lymph nodes, and well-differentiated carcinoma. The G allele of rs10181656 is significantly associated with various clinical characteristics of LSCC, increasing the odds of early- and advanced-stage disease by 2.8-fold and 1.9-fold, respectively. Additionally, this allele is linked to an increased likelihood of developing tumors of different sizes and non-metastasized LSCC, as well as poorly differentiated carcinoma, highlighting its potential impact on the development and features of LSCC. Conclusion: The analysis of the STAT4 rs7574865 SNV revealed that the G allele is linked to a more favorable prognosis in LSCC. Additionally, it is hypothesized that the G allele of rs10181656 may be associated with the occurrence of LSCC but may not serve as a sensitive prognostic biomarker for distinguishing between disease stages, cell differentiation, or tumor size.

Detecting serologically difficult ABO blood groups using single-molecule real-time sequencing technology.

BACKGROUND AND OBJECTIVES: Recently, third-generation long-read sequencing technology has been increasingly applied to the detection of various blood group systems. Because of its long read length and use of single-molecule sequencing, it is capable of obtaining the sequences of blood group genes in their entirety as well as of distinguishing haplotypes. Therefore, here, we collected ABO blood group samples that were difficult to classify serologically and analysed the sequences of the coding regions of the ABO genes as well as the sequences upstream and downstream of the coding regions. MATERIALS AND METHODS: Samples with ABO antigen typing and reverse serum typing discrepancies were screened in a total of 21 patients. All samples were subjected to serological testing and preliminary ABO genotyping (polymerase chain reaction with sequence-specific primers [PCR-SSP]), followed by single-molecule real-time (SMRT) sequencing to obtain complete ABO gene sequences. PCR sequence-based typing (PCR-SBT) was performed to validate the results. RESULTS: Of the 21 samples, 15 had common ABO types, and 6 had rare ABO subtypes. One new allele, ABO*B.NEW (c.861C>T), and one allelic base recombination event was identified. Forty-two haplotype sequences were obtained via SMRT sequencing with intronic single-nucleotide variants (SNVs) specific to the ABO allele, and all of the exon region sequences were consistent with the PCR-SBT results. CONCLUSION: SMRT sequencing is capable of accurately obtaining complete ABO gene sequences, distinguishing haplotypes and identifying allelic recombination.

DNA-binding factor footprints and enhancer RNAs identify functional non-coding genetic variants.

BACKGROUND: Genome-wide association studies (GWAS) have revealed a multitude of candidate genetic variants affecting the risk of developing complex traits and diseases. However, the highlighted regions are typically in the non-coding genome, and uncovering the functional causative single nucleotide variants (SNVs) is challenging. Prioritization of variants is commonly based on genomic annotation with markers of active regulatory elements, but current approaches still poorly predict functional variants. To address this, we systematically analyze six markers of active regulatory elements for their ability to identify functional variants. RESULTS: We benchmark against molecular quantitative trait loci (molQTL) from assays of regulatory element activity that identify allelic effects on DNA-binding factor occupancy, reporter assay expression, and chromatin accessibility. We identify the combination of DNase footprints and divergent enhancer RNA (eRNA) as markers for functional variants. This signature provides high precision, but with a trade-off of low recall, thus substantially reducing candidate variant sets to prioritize variants for functional validation. We present this as a framework called FINDER-Functional SNV IdeNtification using DNase footprints and eRNA. CONCLUSIONS: We demonstrate the utility to prioritize variants using leukocyte count trait and analyze variants in linkage disequilibrium with a lead variant to predict a functional variant in asthma. Our findings have implications for prioritizing variants from GWAS, in development of predictive scoring algorithms, and for functionally informed fine mapping approaches.

Single nucleotide variants in lung cancer.

Germline genetic variants, including single-nucleotide variants (SNVs) and copy number variants (CNVs), account for interpatient heterogeneity. In the past several decades, genome-wide association studies (GWAS) have identified multiple lung cancer-associated SNVs in Caucasian and Chinese populations. These variants either reside within coding regions and change the structure and function of cancer-related proteins or reside within non-coding regions and alter the expression level of cancer-related proteins. The variants can be used not only for cancer risk assessment and prevention but also for the development of new therapies. In this review, we discuss the lung cancer-associated SNVs identified to date, their contributions to lung tumorigenesis and prognosis, and their potential use in predicting prognosis and implementing therapeutic strategies.

De Novo Cancer Mutations Frequently Associate with Recurrent Chromosomal Abnormalities during Long-Term Human Pluripotent Stem Cell Culture.

Human pluripotent stem cells (hPSCs) are pivotal in regenerative medicine, yet their in vitro expansion often leads to genetic abnormalities, raising concerns about their safety in clinical applications. This study analyzed ten human embryonic stem cell lines across multiple passages to elucidate the dynamics of chromosomal abnormalities and single-nucleotide variants (SNVs) in 380 cancer-related genes. Prolonged in vitro culture resulted in 80% of the lines acquiring gains of chromosome 20q or 1q, both known for conferring an in vitro growth advantage. 70% of lines also acquired other copy number variants (CNVs) outside the recurrent set. Additionally, we detected 122 SNVs in 88 genes, with all lines acquiring at least one de novo SNV during culture. Our findings showed higher loads of both CNVs and SNVs at later passages, which were due to the cumulative acquisition of mutations over a longer time in culture, and not to an increased rate of mutagenesis over time. Importantly, we observed that SNVs and rare CNVs followed the acquisition of chromosomal gains in 1q and 20q, while most of the low-passage and genetically balanced samples were devoid of cancer-associated mutations. This suggests that recurrent chromosomal abnormalities are potential drivers for the acquisition of other mutations.

Exudative Age-Related Macular Degeneration: Association between Treatment Efficacy and Single-Nucleotide Variants in RAD51B, TRIB1, COL8A1, COL10A1, IL-9, IL-10, and VEGFA Genes.

Age-related macular degeneration (AMD) is a progressive neurodegenerative condition leading to vision loss and eventual blindness, with exudative AMD posing a heightened risk due to choroidal neovascularization and localized edema. Therapies targeting the VEGF pathway aim to address this mechanism for treatment effectiveness. Our study aimed to evaluate associations between specific genetic variants (RAD51B rs8017304, rs2588809; TRIB1 rs6987702, rs4351379; COL8A1 rs13095226; COL10A1 rs1064583; IL-9 rs1859430, rs2069870, rs11741137, rs2069885, rs2069884; IL-10 rs1800871, rs1800872, rs1800896; VEGFA rs1570360, rs699947, rs3025033, rs2146323) and the response to anti-VEGF treatment for exudative AMD. We enrolled 119 patients with exudative AMD categorized as responders or non-responders based on their response to anti-VEGF treatment. Statistical analysis revealed that RAD51B rs8017304 heterozygous and homozygous minor allele carriers had increased CMT before treatment compared to wild-type genotype carriers (p = 0.004). Additionally, TRIB1 rs4351379 heterozygous and homozygous minor allele carriers exhibited a greater decrease in central macular thickness (CMT) after 6 months of treatment than wild-type genotype carriers (p = 0.030). IL-9 rs1859430, rs2069870, and rs2069884 heterozygous and homozygous minor allele carriers had worse BCVA before treatment than wild-type genotype carriers (p = 0.018, p = 0.012, p = 0.041, respectively). Conversely, IL-9 rs2069885 heterozygous and homozygous minor allele carriers showed greater improvement in BCVA after 6 months compared to wild-type genotype carriers (p = 0.032). Furthermore, VEGFA rs699947 heterozygous and homozygous minor allele carriers had better BCVA before treatment and after 3 and 6 months of treatment than wild-type genotype carriers (p = 0.003, p = 0.022, respectively), with these carriers also exhibiting higher CMT after 6 months of anti-VEGF treatment (p = 0.032). Not all results remained statistically significant under this stringent correction for multiple comparisons. The comparisons of the serum concentrations of IL-10, VEGF-A, and VEGF-R2/KDR between non-responders and responders did not yield statistically significant differences. Our study identified significant associations between genetic variants, including RAD51B rs8017304, TRIB1 rs4351379, IL-9 rs1859430, rs2069870, rs2069884, rs2069885, and VEGFA rs699947, and parameters related to the efficacy of exudative AMD treatment, such as BCVA and CMT.

Single-mitochondrion sequencing uncovers distinct mutational patterns and heteroplasmy landscape in mouse astrocytes and neurons.

BACKGROUND: Mitochondrial (mt) heteroplasmy can cause adverse biological consequences when deleterious mtDNA mutations accumulate disrupting "normal" mt-driven processes and cellular functions. To investigate the heteroplasmy of such mtDNA changes, we developed a moderate throughput mt isolation procedure to quantify the mt single-nucleotide variant (SNV) landscape in individual mouse neurons and astrocytes. In this study, we amplified mt-genomes from 1645 single mitochondria isolated from mouse single astrocytes and neurons to (1) determine the distribution and proportion of mt-SNVs as well as mutation pattern in specific target regions across the mt-genome, (2) assess differences in mtDNA SNVs between neurons and astrocytes, and (3) study co-segregation of variants in the mouse mtDNA. RESULTS: (1) The data show that specific sites of the mt-genome are permissive to SNV presentation while others appear to be under stringent purifying selection. Nested hierarchical analysis at the levels of mitochondrion, cell, and mouse reveals distinct patterns of inter- and intra-cellular variation for mt-SNVs at different sites. (2) Further, differences in the SNV incidence were observed between mouse neurons and astrocytes for two mt-SNV 9027:G > A and 9419:C > T showing variation in the mutational propensity between these cell types. Purifying selection was observed in neurons as shown by the Ka/Ks statistic, suggesting that neurons are under stronger evolutionary constraint as compared to astrocytes. (3) Intriguingly, these data show strong linkage between the SNV sites at nucleotide positions 9027 and 9461. CONCLUSIONS: This study suggests that segregation as well as clonal expansion of mt-SNVs is specific to individual genomic loci, which is important foundational data in understanding of heteroplasmy and disease thresholds for mutation of pathogenic variants.

Predictive genetic panel for adult asthma using machine learning methods.

Background: Asthma is a chronic inflammatory disease of the airways that is heterogeneous and multifactorial, making its accurate characterization a complex process. Therefore, identifying the genetic variations associated with asthma and discovering the molecular interactions between the omics that confer risk of developing this disease will help us to unravel the biological pathways involved in its pathogenesis. Objective: We sought to develop a predictive genetic panel for asthma using machine learning methods. Methods: We tested 3 variable selection methods: Boruta's algorithm, the top 200 genome-wide association study markers according to their respective P values, and an elastic net regression. Ten different algorithms were chosen for the classification tests. A predictive panel was built on the basis of joint scores between the classification algorithms. Results: Two variable selection methods, Boruta and genome-wide association studies, were statistically similar in terms of the average accuracies generated, whereas elastic net had the worst overall performance. The predictive genetic panel was completed with 155 single-nucleotide variants, with 91.18% accuracy, 92.75% sensitivity, and 89.55% specificity using the support vector machine algorithm. The markers used range from known single-nucleotide variants to those not previously described in the literature. Our study shows potential in creating genetic prediction panels with tailored penalties per marker, aiding in the identification of optimal machine learning methods for intricate results. Conclusions: This method is able to classify asthma and nonasthma effectively, proving its potential utility in clinical prediction and diagnosis.

Association of polymorphisms within P2RX4 with type 2 diabetes mellitus: a preliminary case-control study.

OBJECTIVE: Type 2 diabetes mellitus (T2DM) is a complex heterogenic metabolic with a wide range of etiology. Purinergic receptors have pivotal roles in different processes and are hypothesized to have roles in the pathogenesis of T2DM. MATERIALS AND METHODS: Three hundred subjects affected by T2DM and 300 healthy subjects were genotyped by amplification refractory mutation system polymerase chain reaction (ARMS-PCR). SPSS V16.0 was recruited for statistical analysis. RESULTS: The findings showed that the G allele of rs25644A > G increases the risk of T2DM in our population statistically (OR = 1.51, 95% CI = 1.14-1.99, p = 0.003). This allele in some genotype models, including the dominant model, caused an increase in the risk of T2DM. The interaction of genotypes between studied variants in the P2XR4 gene increased the risk of T2DM. Haplotype analysis showed that Ars1169727/Grs25644 haplotype caused an increase in the risk of T2DM. CONCLUSIONS: The findings suggest that rs25644A > G plays a role in our population's increased risk of T2DM.

One-base-mismatch CRISPR-based transistors for single nucleotide resolution assay.

An effective strategy for accurately detecting single nucleotide variants (SNVs) is of great significance for genetic research and diagnostics. However, strict amplification conditions, complex experimental instruments, and specialized personnel are required to obtain a satisfactory tradeoff between sensitivity and selectivity for SNV discrimination. In this study, we present a CRISPR-based transistor biosensor for the rapid and highly selective detection of SNVs in viral RNA. By introducing a synthetic mismatch in the crRNA, the CRISPR-Cas13a protein can be engineered to capture the target SNV RNA directly on the surface of the graphene channel. This process induces a fast electrical signal response in the transistor, obviating the need for amplification or reporter molecules. The biosensor exhibits a detection limit for target RNA as low as 5 copies in 100 µL, which is comparable to that of real-time quantitative polymerase chain reaction (PCR). Its operational range spans from 10 to 5 × 105 copy mL-1 in artificial saliva solution. This capability enables the biosensor to discriminate between wild-type and SNV RNA within 15 min. By introducing 10 µL of swab samples during clinical testing, the biosensor provides specific detection of respiratory viruses in 19 oropharyngeal specimens, including influenza A, influenza B, and variants of SARS-CoV-2. This study emphasizes the CRISPR-transistor technique as a highly accurate and sensitive approach for field-deployable nucleic acid screening or diagnostics.

Single-Mitochondrion Sequencing Uncovers Distinct Mutational Patterns and Heteroplasmy Landscape in Mouse Astrocytes and Neurons.

Background: Mitochondrial (mt) heteroplasmy can cause adverse biological consequences when deleterious mtDNA mutations accumulate disrupting 'normal' mt-driven processes and cellular functions. To investigate the heteroplasmy of such mtDNA changes we developed a moderate throughput mt isolation procedure to quantify the mt single-nucleotide variant (SNV) landscape in individual mouse neurons and astrocytes In this study we amplified mt-genomes from 1,645 single mitochondria (mts) isolated from mouse single astrocytes and neurons to 1. determine the distribution and proportion of mt-SNVs as well as mutation pattern in specific target regions across the mt-genome, 2. assess differences in mtDNA SNVs between neurons and astrocytes, and 3. Study cosegregation of variants in the mouse mtDNA. Results: 1. The data show that specific sites of the mt-genome are permissive to SNV presentation while others appear to be under stringent purifying selection. Nested hierarchical analysis at the levels of mitochondrion, cell, and mouse reveals distinct patterns of inter- and intra-cellular variation for mt-SNVs at different sites. 2. Further, differences in the SNV incidence were observed between mouse neurons and astrocytes for two mt-SNV 9027:G>A and 9419:C>T showing variation in the mutational propensity between these cell types. Purifying selection was observed in neurons as shown by the Ka/Ks statistic, suggesting that neurons are under stronger evolutionary constraint as compared to astrocytes. 3. Intriguingly, these data show strong linkage between the SNV sites at nucleotide positions 9027 and 9461. Conclusion: This study suggests that segregation as well as clonal expansion of mt-SNVs is specific to individual genomic loci, which is important foundational data in understanding of heteroplasmy and disease thresholds for mutation of pathogenic variants.

Vibrio cholerae O1 experiences mild bottlenecks through the gastrointestinal tract in some but not all cholera patients.

Vibrio cholerae O1 causes the diarrheal disease cholera, and the small intestine is the site of active infection. During cholera, cholera toxin is secreted from V. cholerae and induces a massive fluid influx into the small intestine, which causes vomiting and diarrhea. Typically, V. cholerae genomes are sequenced from bacteria passed in stool, but rarely from vomit, a fluid that may more closely represents the site of active infection. We hypothesized that V. cholerae O1 population bottlenecks along the gastrointestinal tract would result in reduced genetic variation in stool compared to vomit. To test this, we sequenced V. cholerae genomes from 10 cholera patients with paired vomit and stool samples. Genetic diversity was low in both vomit and stool, consistent with a single infecting population rather than coinfection with divergent V. cholerae O1 lineages. The amount of single-nucleotide variation decreased from vomit to stool in four patients, increased in two, and remained unchanged in four. The variation in gene presence/absence decreased between vomit and stool in eight patients and increased in two. Pangenome analysis of assembled short-read sequencing demonstrated that the toxin-coregulated pilus operon more frequently contained deletions in genomes from vomit compared to stool. However, these deletions were not detected by PCR or long-read sequencing, indicating that interpreting gene presence or absence patterns from short-read data alone may be incomplete. Overall, we found that V. cholerae O1 isolated from stool is genetically similar to V. cholerae recovered from the upper intestinal tract. IMPORTANCE: Vibrio cholerae O1, the bacterium that causes cholera, is ingested in contaminated food or water and then colonizes the upper small intestine and is excreted in stool. Shed V. cholerae genomes from stool are usually studied, but V. cholerae isolated from vomit may be more representative of where V. cholerae colonizes in the upper intestinal epithelium. V. cholerae may experience bottlenecks, or large reductions in bacterial population sizes and genetic diversity, as it passes through the gut. Passage through the gut may select for distinct V. cholerae mutants that are adapted for survival and gut colonization. We did not find strong evidence for such adaptive mutations, and instead observed that passage through the gut results in modest reductions in V. cholerae genetic diversity, and only in some patients. These results fill a gap in our understanding of the V. cholerae life cycle, transmission, and evolution.

Genetic Findings in Short Turkish Children Born to Consanguineous Parents.

INTRODUCTION: The diagnostic yield of genetic analysis in the evaluation of children with short stature depends on associated clinical characteristics, but the additional effect of parental consanguinity has not been well documented. METHODS: This observational case series of 42 short children from 34 consanguineous families was collected by six referral centres of paediatric endocrinology (inclusion criteria: short stature and parental consanguinity). In 18 patients (12 families, group 1), the clinical features suggested a specific genetic defect in the growth hormone (GH) insulin-like growth factor I (IGF-I) axis, and a candidate gene approach was used. In others (group 2), a hypothesis-free approach was chosen (gene panels, microarray analysis, and whole exome sequencing) and further subdivided into 11 patients with severe short stature (height <-3.5 standard deviation score [SDS]) and microcephaly (head circumference <-3.0 SDS) (group 2a), 10 patients with syndromic short stature (group 2b), and 3 patients with nonspecific isolated GH deficiency (group 2c). RESULTS: In all 12 families from group 1, (likely) pathogenic variants were identified in GHR, IGFALS, GH1, and STAT5B. In 9/12 families from group 2a, variants were detected in PCNT, SMARCAL1, SRCAP, WDR4, and GHSR. In 5/9 families from group 2b, variants were found in TTC37, SCUBE3, NSD2, RABGAP1, and 17p13.3 microdeletions. In group 2c, no genetic cause was found. Homozygous, compound heterozygous, and heterozygous variants were found in 21, 1, and 4 patients, respectively. CONCLUSION: Genetic testing in short children from consanguineous parents has a high diagnostic yield, especially in cases of severe GH deficiency or insensitivity, microcephaly, and syndromic short stature.

Whole-Genome Sequencing and Analysis of Tumour-Forming Radish (Raphanus sativus L.) Line.

Spontaneous tumour formation in higher plants can occur in the absence of pathogen invasion, depending on the plant genotype. Spontaneous tumour formation on the taproots is consistently observed in certain inbred lines of radish (Raphanus sativus var. radicula Pers.). In this paper, using Oxford Nanopore and Illumina technologies, we have sequenced the genomes of two closely related radish inbred lines that differ in their ability to spontaneously form tumours. We identified a large number of single nucleotide variants (amino acid substitutions, insertions or deletions, SNVs) that are likely to be associated with the spontaneous tumour formation. Among the genes involved in the trait, we have identified those that regulate the cell cycle, meristem activity, gene expression, and metabolism and signalling of phytohormones. After identifying the SNVs, we performed Sanger sequencing of amplicons corresponding to SNV-containing regions to validate our results. We then checked for the presence of SNVs in other tumour lines of the radish genetic collection and found the ERF118 gene, which had the SNVs in the majority of tumour lines. Furthermore, we performed the identification of the CLAVATA3/ESR (CLE) and WUSCHEL (WOX) genes and, as a result, identified two unique radish CLE genes which probably encode proteins with multiple CLE domains. The results obtained provide a basis for investigating the mechanisms of plant tumour formation and also for future genetic and genomic studies of radish.