Whole-genome sequencing identifies novel genes for autism in Chinese trios.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder with high genetic heritability but heterogeneity. Fully understanding its genetics requires whole-genome sequencing (WGS), but the ASD studies utilizing WGS data in Chinese population are limited. In this study, we present a WGS study for 334 individuals, including 112 ASD patients and their non-ASD parents. We identified 146 de novo variants in coding regions in 85 cases and 60 inherited variants in coding regions. By integrating these variants with an association model, we identified 33 potential risk genes (P<0.001) enriched in neuron and regulation related biological process. Besides the well-known ASD genes (SCN2A, NF1, SHANK3, CHD8 etc.), several high confidence genes were highlighted by a series of functional analyses, including CTNND1, DGKZ, LRP1, DDN, ZNF483, NR4A2, SMAD6, INTS1, and MRPL12, with more supported evidence from GO enrichment, expression and network analysis. We also integrated RNA-seq data to analyze the effect of the variants on the gene expression and found 12 genes in the individuals with the related variants had relatively biased expression. We further presented the clinical phenotypes of the proband carrying the risk genes in both our samples and Caucasian samples to show the effect of the risk genes on phenotype. Regarding variants in non-coding regions, a total of 74 de novo variants and 30 inherited variants were predicted as pathogenic with high confidence, which were mapped to specific genes or regulatory features. The number of de novo variants found in patient was significantly associated with the parents' ages at the birth of the child, and gender with trend. We also identified small de novo structural variants in ASD trios. The results in this study provided important evidence for understanding the genetic mechanism of ASD.

Variant Impact Predictor database (VIPdb), version 2: Trends from 25 years of genetic variant impact predictors.

Background: Variant interpretation is essential for identifying patients' disease-causing genetic variants amongst the millions detected in their genomes. Hundreds of Variant Impact Predictors (VIPs), also known as Variant Effect Predictors (VEPs), have been developed for this purpose, with a variety of methodologies and goals. To facilitate the exploration of available VIP options, we have created the Variant Impact Predictor database (VIPdb). Results: The Variant Impact Predictor database (VIPdb) version 2 presents a collection of VIPs developed over the past 25 years, summarizing their characteristics, ClinGen calibrated scores, CAGI assessment results, publication details, access information, and citation patterns. We previously summarized 217 VIPs and their features in VIPdb in 2019. Building upon this foundation, we identified and categorized an additional 186 VIPs, resulting in a total of 403 VIPs in VIPdb version 2. The majority of the VIPs have the capacity to predict the impacts of single nucleotide variants and nonsynonymous variants. More VIPs tailored to predict the impacts of insertions and deletions have been developed since the 2010s. In contrast, relatively few VIPs are dedicated to the prediction of splicing, structural, synonymous, and regulatory variants. The increasing rate of citations to VIPs reflects the ongoing growth in their use, and the evolving trends in citations reveal development in the field and individual methods. Conclusions: VIPdb version 2 summarizes 403 VIPs and their features, potentially facilitating VIP exploration for various variant interpretation applications. Availability: VIPdb version 2 is available at https://genomeinterpretation.org/vipdb.

Post-implantation analysis of genomic variations in the progeny from developing fetus to birth.

The analysis of genomic variations in offspring after implantation has been infrequently studied. In this study, we aim to investigate the extent of de novo mutations in humans from developing fetus to birth. Using high-depth whole-genome sequencing, 443 parent-offspring trios were studied to compare the results of de novo mutations (DNMs) between different groups. The focus was on fetuses and newborns, with DNA samples obtained from the families' blood and the aspirated embryonic tissues subjected to deep sequencing. It was observed that the average number of total DNMs in the newborns group was 56.26 (54.17-58.35), which appeared to be lower than that the multifetal reduction group, which was 76.05 (69.70-82.40) (F = 2.42, P = 0.12). However, after adjusting for parental age and maternal pre-pregnancy body mass index (BMI), significant differences were found between the two groups. The analysis was further divided into single nucleotide variants (SNVs) and insertion/deletion of a small number of bases (indels), and it was discovered that the average number of de novo SNVs associated with the multifetal reduction group and the newborn group was 49.89 (45.59-54.20) and 51.09 (49.22-52.96), respectively. No significant differences were noted between the groups (F = 1.01, P = 0.32). However, a significant difference was observed for de novo indels, with a higher average number found in the multifetal reduction group compared to the newborn group (F = 194.17, P < 0.001). The average number of de novo indels among the multifetal reduction group and the newborn group was 26.26 (23.27-29.05) and 5.17 (4.82-5.52), respectively. To conclude, it has been observed that the quantity of de novo indels in the newborns experiences a significant decrease when compared to that in the aspirated embryonic tissues (7-9 weeks). This phenomenon is evident across all genomic regions, highlighting the adverse effects of de novo indels on the fetus and emphasizing the significance of embryonic implantation and intrauterine growth in human genetic selection mechanisms.

Intramolecular Nucleophilic Vinylic Substitution (SNV) by Carbon Nucleophiles: Conformationally Directed Formation of Dienes from N,N'-Diallyl Ureas.

Nucleophilic vinylic substitution (SNV) by carbon nucleophiles allows the formation of vinylic C-C bonds without transition metal catalysts. In this paper, we show that tethering two alkenes together through a urea linkage can lead to the formation of a diene by an intramolecular SNV reaction. The starting materials are fully substituted N,N'-diallyl ureas; the reaction proceeds in the presence of base, and entails a cascade of deprotonations, reprotonations, and an SNV reaction of an allylic carbanion on a rare electrophile: a vinylic urea. As a result, two allylic substituents couple to form a diene, despite the fact that neither is activated towards electrophilic attack. The reaction is tolerant of significant steric bulk, and exhibits regioselectivity with unsymmetrical diallyl ureas: ß-substituted allyl groups invariably behave as nucleophiles, while electrophilic behavior may be enforced by the use of an E-vinylic urea substituent that cannot be deprotonated under the reaction conditions.

Association between PD-1 single nucleotide gene variants and the risk of metastatic melanoma.

Previous studies showed an association between single nucleotide gene variants (SNVs) of PD-1 and cancer susceptibility. We analyzed PD1.5 C > T and PD1.7 T > C SNVs to investigate their association with the risk of developing metastatic melanoma (MM). Utilizing a cohort of 125 MM patients treated with anti-PD-1 agents and 84 healthy controls, we examined genotype/allele frequencies through a modified Poisson regression model, adjusted for age and sex. Our findings indicate that the PD1.5 T allele is associated with a reduced risk of MM, showing a significantly lower risk in both codominant (RR = 0.56, 95%CL: 0.37-0.87) and dominant (RR = 0.73 95%CL: 0.59-0.90) models. Conversely, the PD1.7 C allele is linked to an increased risk of MM, with the C/C genotype exhibiting a higher risk in the codominant (RR = 1.65, 95%CL: 1.32-2.05) and allelic (RR = 1.23, 95%CL: 1.06-1.43) models. These results are consistent with previous meta-analyses on other cancer types, mainly highlighting the PD1.5 SNV's potential role in promoting anti-tumor immunity through increased PD1-positive circulating effector T cell activity.

Single nucleotide variation catalog from clinical isolates mapped on tertiary and quaternary structures of ESX-1-related proteins reveals critical regions as putative Mtb therapeutic targets.

Proteins encoded by the ESX-1 genes of interest are essential for full virulence in all Mycobacterium tuberculosis complex (Mtbc) lineages, the pathogens causing the highest mortality worldwide. Identifying critical regions in these ESX-1-related proteins could provide preventive or therapeutic targets for Mtb infection, the game changer needed for tuberculosis control. We analyzed a compendium of whole genome sequences of clinical Mtb isolates from all lineages from >32,000 patients and identified single nucleotide polymorphisms. When mutations corresponding to all non-synonymous single nucleotide polymorphisms were mapped on structural models of the ESX-1 proteins, fully conserved regions emerged. Some could be assigned to known quaternary structures, whereas others could be predicted to be involved in yet-to-be-discovered interactions. Some mutants had clonally expanded (found in >1% of the isolates); these mutants were mostly located at the surface of globular domains, remote from known intra- and inter-molecular protein-protein interactions. Fully conserved intrinsically disordered regions of proteins were found, suggesting that these regions are crucial for the pathogenicity of the Mtbc. Altogether, our findings highlight fully conserved regions of proteins as attractive vaccine antigens and drug targets to control Mtb virulence. Extending this approach to the whole Mtb genome as well as other microorganisms will enhance vaccine development for various pathogens. IMPORTANCE: We mapped all non-synonymous single nucleotide polymorphisms onto each of the experimental and predicted ESX-1 proteins' structural models and inspected their placement. Varying sizes of conserved regions were found. Next, we analyzed predicted intrinsically disordered regions within our set of proteins, finding two putative long stretches that are fully conserved, and discussed their potential essential role in immunological recognition. Combined, our findings highlight new targets for interfering with Mycobacterium tuberculosis complex virulence.

HiFi long-read amplicon sequencing for full-spectrum variants of human mtDNA.

BACKGROUND: Mitochondrial diseases (MDs) can be caused by single nucleotide variants (SNVs) and structural variants (SVs) in the mitochondrial genome (mtDNA). Presently, identifying deletions in small to medium-sized fragments and accurately detecting low-percentage variants remains challenging due to the limitations of next-generation sequencing (NGS). METHODS: In this study, we integrated targeted long-range polymerase chain reaction (LR-PCR) and PacBio HiFi sequencing to analyze 34 participants, including 28 patients and 6 controls. Of these, 17 samples were subjected to both targeted LR-PCR and to compare the mtDNA variant detection efficacy. RESULTS: Among the 28 patients tested by long-read sequencing (LRS), 2 patients were found positive for the m.3243 A > G hotspot variant, and 20 patients exhibited single or multiple deletion variants with a proportion exceeding 4%. Comparison between the results of LRS and NGS revealed that both methods exhibited similar efficacy in detecting SNVs exceeding 5%. However, LRS outperformed NGS in detecting SNVs with a ratio below 5%. As for SVs, LRS identified single or multiple deletions in 13 out of 17 cases, whereas NGS only detected single deletions in 8 cases. Furthermore, deletions identified by LRS were validated by Sanger sequencing and quantified in single muscle fibers using real-time PCR. Notably, LRS also effectively and accurately identified secondary mtDNA deletions in idiopathic inflammatory myopathies (IIMs). CONCLUSIONS: LRS outperforms NGS in detecting various types of SNVs and SVs in mtDNA, including those with low frequencies. Our research is a significant advancement in medical comprehension and will provide profound insights into genetics.

Unraveling the complex role of MAPT-containing H1 and H2 haplotypes in neurodegenerative diseases.

A ~ 1 Mb inversion polymorphism exists within the 17q21.31 locus of the human genome as direct (H1) and inverted (H2) haplotype clades. This inversion region demonstrates high linkage disequilibrium, but the frequency of each haplotype differs across ancestries. While the H1 haplotype exists in all populations and shows a normal pattern of genetic variability and recombination, the H2 haplotype is enriched in European ancestry populations, is less frequent in African ancestry populations, and nearly absent in East Asian ancestry populations. H1 is a known risk factor for several neurodegenerative diseases, and has been associated with many other traits, suggesting its importance in cellular phenotypes of the brain and entire body. Conversely, H2 is protective for these diseases, but is associated with predisposition to recurrent microdeletion syndromes and neurodevelopmental disorders such as autism. Many single nucleotide variants and copy number variants define H1/H2 haplotypes and sub-haplotypes, but identifying the causal variant(s) for specific diseases and phenotypes is complex due to the extended linkage equilibrium. In this review, we assess the current knowledge of this inversion region regarding genomic structure, gene expression, cellular phenotypes, and disease association. We discuss recent discoveries and challenges, evaluate gaps in knowledge, and highlight the importance of understanding the effect of the 17q21.31 haplotypes to promote advances in precision medicine and drug discovery for several diseases.

Single nucleotide variants in the CCL2, OAS1 and DPP9 genes and their association with the severity of COVID-19 in an Ecuadorian population.

COVID-19 has a broad clinical spectrum, ranging from asymptomatic-mild form to severe phenotype. The severity of COVID-19 is a complex trait influenced by various genetic and environmental factors. Ethnic differences have been observed in relation to COVID-19 severity during the pandemic. It is currently unknown whether genetic variations may contribute to the increased risk of severity observed in Latin-American individuals The aim of this study is to investigate the potential correlation between gene variants at CCL2, OAS1, and DPP9 genes and the severity of COVID-19 in a population from Quito, Ecuador. This observational case-control study was conducted at the Carrera de Biologia from the Universidad Central del Ecuador and the Hospital Quito Sur of the Instituto Ecuatoriano de Seguridad Social (Quito-SUR-IESS), Quito, Ecuador. Genotyping for gene variants at rs1024611 (A>G), rs10774671 (A>G), and rs10406145 (G>C) of CCL2, OAS1, and DPP9 genes was performed on 100 COVID-19 patients (43 with severe form and 57 asymptomatic-mild) using RFLP-PCR. The genotype distribution of all SNVs throughout the entire sample of 100 individuals showed Hardy Weinberg equilibrium (P=0.53, 0.35, and 0.4 for CCL2, OAS1, and DPP9, respectively). The HWE test did not find any statistically significant difference in genotype distribution between the study and control groups for any of the three SNVs. The multivariable logistic regression analysis showed that individuals with the GG of the CCL2 rs1024611 gene variant had an increased association with the severe COVID-19 phenotype in a recessive model (P = 0.0003, OR = 6.43, 95% CI 2.19-18.89) and for the OAS1 rs10774671 gene variant, the log-additive model showed a significant association with the severe phenotype of COVID-19 (P=0.0084, OR=3.85, 95% CI 1.33-11.12). Analysis of haplotype frequencies revealed that the coexistence of GAG at CCL2, OAS1, and DPP9 variants, respectively, in the same individual increased the presence of the severe COVID-19 phenotype (OR=2.273, 95% CI: 1.271-4.068, P=0.005305). The findings of the current study suggests that the ethnic background affects the allele and genotype frequencies of genes associated with the severity of COVID-19. The experience with COVID-19 has provided an opportunity to identify an ethnicity-based approach to recognize genetically high-risk individuals in different populations for emerging diseases.

Characterization of the Common Genetic Variation in the Spanish Population of Navarre.

Large-scale genomic studies have significantly increased our knowledge of genetic variability across populations. Regional genetic profiling is essential for distinguishing common benign variants from disease-causing ones. To this end, we conducted a comprehensive characterization of exonic variants in the population of Navarre (Spain), utilizing whole genome sequencing data from 358 unrelated individuals of Spanish origin. Our analysis revealed 61,410 biallelic single nucleotide variants (SNV) within the Navarrese cohort, with 35% classified as common (MAF > 1%). By comparing allele frequency data from 1000 Genome Project (excluding the Iberian cohort of Spain, IBS), Genome Aggregation Database, and a Spanish cohort (including IBS individuals and data from Medical Genome Project), we identified 1069 SNVs common in Navarre but rare (MAF ≤ 1%) in all other populations. We further corroborated this observation with a second regional cohort of 239 unrelated exomes, which confirmed 676 of the 1069 SNVs as common in Navarre. In conclusion, this study highlights the importance of population-specific characterization of genetic variation to improve allele frequency filtering in sequencing data analysis to identify disease-causing variants.

Changes in intrahost genetic diversity according to lesion severity in longitudinal HPV16 samples.

Human papillomavirus type 16 (HPV16) is the most common cause of cervical cancer, but most infections are transient with lesions not progressing to cancer. There is a lack of specific biomarkers for early cancer risk stratification. This study aimed to explore the intrahost HPV16 genomic variation in longitudinal samples from HPV16-infected women with different cervical lesion severity (normal, low-grade, and high-grade). The TaME-seq deep sequencing protocol was used to generate whole genome HPV16 sequences of 102 samples collected over time from 40 individuals. Single nucleotide variants (SNVs) and intrahost SNVs (iSNVs) were identified in the viral genomes. A majority of individuals had a unique set of SNVs and these SNVs were stable over time. Overall, the number of iSNVs and APOBEC3-induced iSNVs were significantly lower in high-grade relative to normal and low-grade samples. A significant increase in the number of APOBEC3-induced iSNVs over time was observed for normal samples when compared to high-grade. Our results indicates that the lower incidence of iSNVs and APOBEC3-induced iSNVs in high-grade lesions may have implications for novel biomarkers discoveries, potentially aiding early stratification of HPV-induced cervical precancerous lesions.

Exploring Viral Genome Profile in Mpox Patients during the 2022 Outbreak, in a North-Eastern Centre of Italy.

In 2022, an unprecedented outbreak of mpox raged in several nations. Sequences from the 2022 outbreak reveal a higher nucleotide substitution if compared with the estimated rate for orthopoxviruses. Recently, intra-lesion SNVs (single nucleotide variants) have been described, and these have been suggested as possible sources of genetic variation. Until now, it has not been clear if the presence of several SNVs could represents the result of local mutagenesis or a possible co-infection. We investigated the significance of SNVs through whole-genome sequencing analysis of four unrelated mpox cases. In addition to the known mutations harboured by the circulating strains of virus (MPXV), 7 novel mutations were identified, including SNVs located in genes that are involved in immune evasion mechanisms and/or viral fitness, six of these appeared to be APOBEC3-driven. Interestingly, three patients exhibited the coexistence of mutated and wild-type alleles for five non-synonymous variants. In addition, two patients, apparently unrelated, showed an analogous pattern for two novel mutations, albeit with divergent frequencies. The coexistence of mixed viral populations, harbouring non-synonymous mutations in patients, supports the hypothesis of possible co-infection. Additional investigations of larger clinical cohorts are essential to validating intra-patient viral genome heterogeneity and determining the possibility of co-presence events of slightly divergent MPXV strains.

Validation of Single-Nucleotide Mosaic Variants Through Droplet Digital PCR.

The detection, validation, and subsequent interpretation of potentially mosaic single-nucleotide variants (SNV) within next-generation sequencing data remains a challenge in both research and clinical laboratory settings. The ability to identify mosaic variants in high genome coverage sequencing data at levels of ≤1% underscores the necessity for developing guidelines and best practices to verify these variants orthogonally. Droplet digital PCR (ddPCR) has proven to be a powerful and precise method that allows for the determination of low-level variant fractions within a given sample. Herein we describe two precise ddPCR methods using either a fluorescent TaqMan hydrolysis probe approach or an EvaGreen fluorescent dye protocol. The TaqMan approach relies on two different fluorescent probes (FAM and HEX/VIC), each designed to amplify selectively only in the presence of a single nucleotide change denoting the variant or reference position. The fractional abundance is then calculated to determine the relative quantities of both alleles in the final sample. The EvaGreen protocol relies on two independent reactions with oligonucleotide primers designed with the single nucleotide change denoting the variant at the penultimate position of the primer. The relative amplification efficiency of both primer sets (reference and variant) can be compared to determine the mosaic level of a given variant. As the cost of high-coverage sequencing continues to decrease, the identification of potentially mosaic variants will also increase. The approaches outlined will allow clinicians and researchers a more precise determination of the true mosaic level of a given variant allowing them to better assess not only its potential pathogenicity but also its possible recurrence risk when offering genetic counseling to families. © 2024 Wiley Periodicals LLC. Basic Protocol: Droplet digital PCR (ddPCR) with TaqMan hydrolysis probes Alternate Protocol: EvaGreen oligonucleotide-specific ddPCR.

Factors Influencing Mortality in Children with Central Nervous System Tumors: A Cohort Study on Clinical Characteristics and Genetic Markers.

Multidrug resistance (MDR) commonly leads to cancer treatment failure because cancer cells often expel chemotherapeutic drugs using ATP-binding cassette (ABC) transporters, which reduce drug levels within the cells. This study investigated the clinical characteristics and single nucleotide variant (SNV) in ABCB1, ABCC1, ABCC2, ABCC4, and ABCG2, and their association with mortality in pediatric patients with central nervous system tumors (CNST). Using TaqMan probes, a real-time polymerase chain reaction genotyped 15 SNPs in 111 samples. Patients were followed up until death or the last follow-up day using the Cox proportional hazards model. An association was found between the rs1045642 (ABCB1) in the recessive model (HR = 2.433, 95% CI 1.098-5.392, p = 0.029), and the ICE scheme in the codominant model (HR = 9.810, 95% CI 2.74-35.06, p ≤ 0.001), dominant model (HR = 6.807, 95% CI 2.87-16.103, p ≤ 0.001), and recessive model (HR = 6.903, 95% CI 2.915-16.544, p = 0.038) significantly increased mortality in this cohort of patients. An association was also observed between the variant rs3114020 (ABCG2) and mortality in the codominant model (HR = 5.35, 95% CI 1.83-15.39, p = 0.002) and the dominant model (HR = 4.421, 95% CI 1.747-11.185, p = 0.002). A significant association between the ICE treatment schedule and increased mortality risk in the codominant model (HR = 6.351, 95% CI 1.831-22.02, p = 0.004, HR = 9.571, 95% CI 2.856-32.07, p ≤ 0.001), dominant model (HR = 6.592, 95% CI 2.669-16.280, p ≤ 0.001), and recessive model (HR = 5.798, 95% CI 2.411-13.940, p ≤ 0.001). The genetic variants rs3114020 in the ABCG2 gene and rs1045642 in the ABCB1 gene and the ICE chemotherapy schedule were associated with an increased mortality risk in this cohort of pediatric patients with CNST.

A Predictive Noninvasive Single-Nucleotide Variation-Based Biomarker Signature for Resectable Pancreatic Cancer: Protocol for a Prospective Validation Study.

BACKGROUND: Single-nucleotide variations (SNVs; formerly SNPs) are inherited genetic variants that can be easily determined in routine clinical practice using a simple blood or saliva test. SNVs have potential to serve as noninvasive biomarkers for predicting cancer-specific patient outcomes after resection of pancreatic ductal adenocarcinoma (PDAC). Two recent analyses led to the identification and validation of three SNVs in the CD44 and CHI3L2 genes (rs187115, rs353630, and rs684559), which can be used as predictive biomarkers to help select patients most likely to benefit from pancreatic resection. These variants were associated with an over 2-fold increased risk for tumor-related death in three independent PDAC study cohorts from Europe and the United States, including The Cancer Genome Atlas cohorts (reaching a P value of 1×10-8). However, these analyses were limited by the inherent biases of a retrospective study design, such as selection and publication biases, thereby limiting the clinical use of these promising biomarkers in guiding PDAC therapy. OBJECTIVE: To overcome the limitations of previous retrospectively designed studies and translate the findings into clinical practice, we aim to validate the association of the identified SNVs with survival in a controlled setting using a prospective cohort of patients with PDAC following pancreatic resection. METHODS: All patients with PDAC who will undergo pancreatic resection at three participating hospitals in Switzerland and fulfill the inclusion criteria will be included in the study consecutively. The SNV genotypes will be determined using standard genotyping techniques from patient blood samples. For each genotyped locus, log-rank and Cox multivariate regression tests will be performed, accounting for the relevant covariates American Joint Committee on Cancer stage and resection status. Clinical follow-up data will be collected for at least 3 years. Sample size calculation resulted in a required sample of 150 patients to sufficiently power the analysis. RESULTS: The follow-up data collection started in August 2019 and the estimated end of data collection will be in May 2027. The study is still recruiting participants and 142 patients have been recruited as of November 2023. The DNA extraction and genotyping of the SNVs will be performed after inclusion of the last patient. Since no SNV genotypes have been determined, no data analysis has been performed to date. The results are expected to be published in 2027. CONCLUSIONS: This is the first prospective study of the CD44 and CHI3L2 SNV-based biomarker signature in PDAC. A prospective validation of this signature would enable its clinical use as a noninvasive predictive biomarker of survival after pancreatic resection that is readily available at the time of diagnosis and can assist in guiding PDAC therapy. The results of this study may help to individualize treatment decisions and potentially improve patient outcomes. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/54042.

Rapid IDH1-R132 genotyping panel utilizing locked nucleic acid loop-mediated isothermal amplification.

While the detection of single-nucleotide variants (SNVs) is important for evaluating human health and disease, most genotyping methods require a nucleic acid extraction step and lengthy analytical times. Here, we present a protocol which utilizes the integration of locked nucleic acids (LNAs) into self-annealing loop primers for the allelic discrimination of five isocitrate dehydrogenase 1 R132 (IDH1-R132) variants using loop-mediated isothermal amplification (LAMP). This genotyping panel was initially evaluated using purified synthetic DNA to show proof of specific SNV discrimination. Additional evaluation using glioma tumor lysates with known IDH1-R132 mutational status demonstrated specificity in approximately 35 min without the need for a nucleic acid extraction purification step. This LNA-LAMP-based genotyping assay can detect single base differences in purified nucleic acids or tissue homogenates, including instances where the variant of interest is present in an excess of background wild-type DNA. The pH-based colorimetric indicator of LNA-LAMP facilitates convenient visual interpretation of reactions, and we demonstrate successful translation to an end-point format using absorbance ratio, allowing for an alternative and objective approach for differentiating between positive and negative reactions. Importantly, the LNA-LAMP genotyping panel is highly reproducible, with no false-positive or false-negative results observed.

ISMI-VAE: A deep learning model for classifying disease cells using gene expression and SNV data.

Various studies have linked several diseases, including cancer and COVID-19, to single nucleotide variations (SNV). Although single-cell RNA sequencing (scRNA-seq) technology can provide SNV and gene expression data, few studies have integrated and analyzed these multimodal data. To address this issue, we introduce Interpretable Single-cell Multimodal Data Integration Based on Variational Autoencoder (ISMI-VAE). ISMI-VAE leverages latent variable models that utilize the characteristics of SNV and gene expression data to overcome high noise levels and uses deep learning techniques to integrate multimodal information, map them to a low-dimensional space, and classify disease cells. Moreover, ISMI-VAE introduces an attention mechanism to reflect feature importance and analyze genetic features that could potentially cause disease. Experimental results on three cancer data sets and one COVID-19 data set demonstrate that ISMI-VAE surpasses the baseline method in terms of both effectiveness and interpretability and can effectively identify disease-causing gene features.

ACE Gene Mutations (rs577350502) in Early-Onset and Recurrent Myocardial Infarction: A Case Report and Review.

Background: Acute myocardial infarction (AMI) is a severe acute coronary syndrome, demonstrating a trend toward affecting younger individuals in recent years. The association between early-onset myocardial infarction and single nucleotide polymorphism necessitates further exploration and evaluation. Case description: We present a case of a patient experiencing early-onset and recurrent myocardial infarction. The patient underwent stent implantation for myocardial infarction at the age of 53 and subsequently encountered two more myocardial infarctions within a span of 16 years. Following interventional therapy, genetic testing was conducted to assess the efficacy of subsequent anti-heart failure medications, with the aim to preemptively address heart failure risks. Genetic testing revealed a mutation in the angiotensin-converting enzyme (ACE) gene (rs577350502, g.63488533C>A), characterized by an intron-deletion single nucleotide variant. Conclusion: While this variant has not been previously reported to be associated with any specific disease, we hypothesize that it may contribute to the susceptibility and risk of myocardial infarction and coronary heart disease in the patient under consideration. This observation underscores the significance of investigating the insertion/deletion polymorphisms of the ACE gene in the context of AMI and emphasizes the necessity for further validation of this variant and other genetic markers associated with AMI in related diseases.

Unexpected mutations occurred in CRISPR/Cas9 edited Drosophila analyzed by deeply whole genomic sequencing.

CRISPR/Cas9 possesses the most promising prospects as a gene-editing tool in post-genomic researches. It becomes an epoch-marking technique for the features of speed and convenience of genomic modification. However, it is still unclear whether CRISPR/Cas9 gene editing can cause irreversible damage to the genome. In this study, we successfully knocked out the WHITE gene in Drosophila, which governs eye color, utilizing CRISPR/Cas9 technology. Subsequently, we conducted high-throughput sequencing to assess the impact of this editing process on the stability of the entire genomic profile. The results revealed the presence of numerous unexpected mutations in the Drosophila genome, including 630 SNVs (Single Nucleotide Variants), 525 Indels (Insertion and Deletion) and 425 MSIs (microsatellite instability). Although the KO (knockout) specifically occurred on chromosome X, the majority of mutations were observed on chromosome 3, indicating that this effect is genome-wide and associated with the spatial structure between chromosomes, rather than being solely limited to the location of the KO gene. It is worth noting that most of the mutations occurred in the intergenic and intron regions, without exerting any significant on the function or healthy of the animal. In addition, the mutations downstream of the knockout gene well beyond the upstream. This study has found that gene editing can lead to unexpected mutations in the genome, but most of these mutations are harmless. This research has deepened our understanding of CRISPR/Cas9 and broadened its application prospects.

Mutation analysis and clinical profile of South African patients with Neurofibromatosis type 1 (NF1) phenotype.

Neurofibromatosis type 1 (NF1) is an autosomal dominant genetic condition with complete age-dependent penetrance, variable expressivity and a global prevalence of ∼1/3,000. It is characteriszed by numerous café-au-lait macules, skin freckling in the inguinal or axillary regions, Lisch nodules of the iris, optic gliomas, neurofibromas, and tumour predisposition. The diagnostic testing strategy for NF1 includes testing for DNA single nucleotide variants (SNVs), copy number variants (CNVs) as well as RNA analysis for deep intronic and splice variants, which can cumulatively identify the causative variant in 95% of patients. In the present study, NF1 patients were screened using a next-generation sequencing (NGS) assay targeting NF1 exons and intron/exon boundaries for SNV and NF1 multiple ligation-dependent probe amplification (MLPA) analysis for CNV detection. Twenty-six unrelated Southern African patients clinically suspected of having NF1, based on the clinical diagnostic criteria developed by the National Institute of Health (NIH), were included in the current study. A detection rate of 58% (15/26) was obtained, with SNVs identified in 80% (12/15) using a targeted gene panel and NF1 gene deletion in 20% (3/15) identified using MLPA. Ten patients (38%) had no variants identified, although they met NF1 diagnostic criteria. One VUS was identified in this study in a patient that met NF1 diagnostic criteria, however there was no sufficient information to classify variant as pathogenic. The clinical features of Southern African patients with NF1 are similar to that of the known NF1 phenotype, with the exception of a lower frequency of plexiform neurofibromas and a higher frequency of developmental/intellectual disability compared to other cohorts. This is the first clinical and molecular characterisation of a Southern African ancestry NF1 cohort using both next-generation sequencing and MLPA analysis. A significant number of patients remained without a diagnosis following DNA-level testing. The current study offers a potential molecular testing strategy for our low resource environment that could benefit a significant proportion of patients who previously only received a clinical diagnosis without molecular confirmation.