SNP genotyping: technologies and biomedical applications

Allele-specific detection of isoniazid metabolism modulating variants of N-acetyltransferase 2 enzyme and their frequencies in the Bangladeshi population

Tuberculosis is one of the oldest diseases that still affects millions of people worldwide and remains a significant public health challenge. The N-acetyltransferase 2 (NAT2) enzyme metabolizes isoniazid (INH), a primary antibiotic in tuberculosis treatment. The single nucleotide polymorphisms (SNPs) of NAT2 affect the metabolism and function of isoniazid. The rs1801280 (T341C) and rs1208 (G803A) variants of NAT2 are associated with INH drug responses. Individuals with the slow-metabolizing rs1801280 variant of the NAT2 enzyme are at a higher risk of INH-induced liver damage and require lower doses or longer treatment regimens. At the same time, individuals with the fast-metabolizing rs1208 variant are at risk of treatment failure due to rapid drug metabolism. Genotyping of the NAT2 variants can help clinicians personalize tuberculosis treatment, optimize drug doses, and thus minimize adverse effects. Under this study, an allele-specific PCR (ASPCR) method was developed for genotyping the NAT2 variants, and the results were validated through targeted sequencing. The allele frequencies at the rs1801280 locus were 0.60 for the T allele and 0.40 for the C. For rs1208, the participants' allele frequencies were 0.27 for the G allele and 0.73 for the A allele. This ASPCR method is quick, affordable, and could be used in routine genotyping to personalize the treatment for tuberculosis patients, leading to more effective and safer treatments. We also used molecular docking to study how the rs1801280 and rs1208 variants affect the interaction between the NAT2 enzyme and drugs. A slight change was visible in the flexibility of the amino acid residues. However, those amino acids were not involved in the ligand binding mechanism.

A quantitative polymerase chain reaction approach for distinguishing the geographical origin of Pagrus major from Korea and Japan

Illegal distribution and mislabeling of imported fishery products pose challenges to country-of-origin labeling regulations in Korea. To address this issue, a quantitative PCR (qPCR)-based method was developed to distinguish Pagrus major from Korea and Japan. Using genotyping-by-sequencing (GBS), two single nucleotide polymorphism (SNP) markers were identified, and allele-specific primers were designed. Gaussian mixture modeling established Ct thresholds, achieving accuracy of 81.67% and 77.78% for SNP001 and SNP008, respectively. The amplification efficiency and limit of detection (LOD) were assessed using tenfold serial dilutions (10-0.001 ng/μL). Standard curves for AA and TT homotypes showed high linearity (R2 > 0.994) with amplification efficiencies of 103.65% and 97.63%, respectively. This qPCR-based method provides a reliable approach for origin verification of P. major, aiding regulatory enforcement and ensuring seafood authenticity.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10068-025-01877-0.

Biosensing of single-nucleotide polymorphism: Technological advances and their transformative applications on health

Single nucleotide polymorphisms (SNPs) are important genetic changes related to many diseases such as breast cancer, Alzheimer's disease, and β-thalassemia. Because of the increased interest in biosensor technologies, there has been a notable surge in the creation of new techniques to identify these changes in recent years. These new methods are highly accurate and sensitive, cost-effective and fast, making them ideal for use in clinical analysis. The non-invasive nature of biosensing techniques further enhances their integration into clinical protocols and point-of-care diagnostics. Several electrochemical, optical, and mass-based biosensors are carefully examined in this extensive review; each is distinguished by unique sensing platforms and techniques. This review presents in-depth discussions of linear dynamic ranges, detection limits, and real-world applications of contemporary research in the diagnosis of biological substrate disorders.

Explainable AI Model Reveals Informative Mutational Signatures for Cancer-Type Classification

Background/Objectives: The prediction of cancer types is primarily reliant on driver genes and their specific mutations. The advancement in novel omics technologies has led to the acquisition of additional genetic data. When integrated with artificial intelligence models, there is considerable potential for this to enhance the accuracy of cancer diagnosis. As mutational signatures can provide insights into repair mechanism malfunctions, they also have the potential for more accurate cancer diagnosis. Methods: First, we compared unsupervised and supervised machine learning approaches to predict cancer types. We employed deep and artificial neural network architectures with an explainable component like layerwise relevance propagation to extract the most relevant features for the cancer-type prediction. Ten-fold cross-validation and an extensive grid search were used to optimize the neural network architecture using driver gene mutations, mutational signatures and topological mutation information as input. The PCAWG dataset was used as input to discriminate between 17 primary sites and 24 cancer types. Results: Overall, our approach showed that the most relevant mutation information to discriminate between cancer types is increased by >10% using the whole genome or intergenic and intronic genome regions instead of exome information. Furthermore, the most relevant features for most cancer types, except for two, are in the mutational signatures and not the topological mutation information. Conclusions: Informative mutational signatures outperformed the prediction of cancer types in comparison to driver gene mutations and added a new layer of diagnostic information. As the degree of information within the mutational signatures is not solely based on the frequency of occurrence, it is even possible to separate cancer types from the same primary site by the different relevant mutations. Furthermore, the comparison of informative mutational signatures allowed the cancer-type assignment of specific impaired repair mechanisms.

Research trends and hotspots of single nucleotide polymorphisms in endometrial cancer: a bibliometric analysis

BACKGROUND

Endometrial cancer (EC) is a common gynecological malignancy with increasing incidence, especially in developed nations. Understanding genetic variations, particularly single nucleotide polymorphisms (SNPs), is crucial for uncovering the disease's pathogenesis, progression, and treatment responses. This study explores the global research landscape of SNPs in EC, focusing on field evolution, key contributors, and emerging trends.

METHODS

A systematic search of the Web of Science Core Collection (WoSCC) retrieved 838 publications on SNPs in EC from 1991 to 2024. Bibliometric indicators, including publication volume, citation counts, and keyword occurrences, were analyzed using VOSviewer, CiteSpace, and the R package "bibliometrix" for visual mapping and trend analysis.

RESULTS

The United States (230 publications) and China (182 publications) were leaders in research output. Harvard University and the National Cancer Institute were prominent contributors. Key themes included "microsatellite instability" (a hallmark of DNA mismatch repair deficiency) and "genome-wide association studies" (GWAS), identifying susceptibility loci like HNF1B and CYP19A1. Recent trends, such as "Mendelian randomization," have enhanced causal inference in risk factor studies. SNP research has advanced risk prediction models and personalized therapeutic strategies, such as hormone therapy tailored to genetic profiles.

CONCLUSION

SNP research has deepened our understanding of EC's genetic basis, with a growing emphasis on Mendelian randomization and GWAS. These advancements have refined risk prediction and opened new avenues for personalized medicine. Integrating SNP data with environmental and hormonal factors remains crucial for advancing prevention, diagnosis, and treatment strategies in EC.

SVHunter: long-read-based structural variation detection through the transformer model

Structural variations (SVs) are genomic rearrangements larger than 50 bp, that are widely present in the human genome and are associated with various complex diseases. Existing long-read-based SV detection tools often rely on fixed rules or heuristic algorithms, which can oversimplify the complexity of SV signatures. Therefore, these methods usually lack flexibility and cannot fully capture SV signals, leading to reduced accuracy and robustness. To address these issues, we propose SVHunter, a transformer-based method for long-read SV detection. SVHunter combines convolutional neural networks and transformers to capture both local and global SV signatures, enabling accurate identification of SVs. Additionally, SVHunter employs the mean shift clustering algorithm, which dynamically adjusts bandwidth parameters to accommodate different types of SVs without requiring a preset number of clusters, thus allowing precise breakpoint clustering. Validation across multiple sequencing platforms and datasets demonstrates that SVHunter excels at detecting various types of SVs, with a notable reduction in the false discovery rate. This highlights considerable strong potential for both research and clinical applications.

Screening Biomarkers and Risk Factors for COVID-19 Progression in a Border Population Between Brazil-Bolivia

Background

The performance and genetic role in host response delineate investigative points of polymorphisms as potential biomarkers in viral infections.

Methods

Thus, this research aimed to map biomarkers and risk factors in the severity of COVID-19 in individuals in Western Amazon (n = 243).

Results

Patients aged 40 to 59 years showed an association with clinical progression (P = .003), also evidencing the relationship for individuals >60 years (P < .001), besides the non-vaccination influenced the pathology (P = .023). qPCR for human genotyping of the targets rs2070788, rs4702, rs76635825, rs540856718, rs35803318, rs12979860, and rs16899066, as well as for gene expression of ACE2, HLA-A, HLA-B, IFNL-3/2, IL-6, and TMPRSS2 was used. The rs12979860 (C > T) and rs2070788 (A > G) showed association among the analyzed groups (P < .05) with the allelic and genotypic frequency of rs12979860 (x 2 < 3.84) and evolutionary pointing of rs2070788G allele among infected people, including deaths.

Conclusion

Gene expression showed high levels between the moderate and severe groups, with emphasis on TMPRSS2 and IL-6 genes that performed better. Thus, there is possibly an association regarding the role of the TMPRSS2 gene and rs2070788G, as well as age and IL-6 levels for COVID-19, pointing in parallel to the considerable influence of the vaccine on the SARS-CoV-2 pathway.

Identification of single nucleotide polymorphisms (SNPs) potentially associated with residual feed intake in Qinchuan beef cattle by hypothalamus and duodenum RNA-Seq data

The regulation of residual feed intake (RFI) in beef cattle involves brain-gut mechanisms due to the interaction between neural signals in the brain and hunger or satiety in the gut. RNA-Seq data contain an extensive resource of untapped SNPs. Therefore, hypothalamic and duodenal tissues from ten extreme RFI individuals were collected, and transcriptome sequenced in this study. All the alignment data were combined according to RFI, and the SNPs in the same group were identified. A total of 270,410 SNPs were found in the high RFI group, and 255,120 SNPs were found in the low RFI group. Most SNPs were detected in the intronic region, followed by the intergenic region, and the exon region accounts for 1.11% and 1.38% in the high and low RFI groups, respectively. Prediction of high-impact SNPs and annotation of the genes in which they are located yielded 83 and 97 genes in the high-RFI and low-RFI groups, respectively. GO enrichment analysis of these genes revealed multiple NADH/NADPH-related pathways, with ND4, ND5, and ND6 significantly enriched as core subunits of NADH dehydrogenase (complex I), and is closely related to mitochondrial function. KEGG enrichment analysis of ND4, ND5, and ND6 genes was enriched in the thermogenic pathway. Multiple genes, such as ATP1A2, SLC9A4, and PLA2G5, were reported to be associated with RFI energy metabolism in the concurrent enrichment analysis. Protein-protein interaction analysis identified multiple potential candidate genes related to energy metabolism that were hypothesized to be potentially associated with the RFI phenotype. The results of this study will help to increase our understanding of identifying SNPs with significant genetic effects and their potential biological functions.

Nonequilibrium hybridization-driven CRISPR/Cas adapter with extended energetic penalty for discrimination of single-nucleotide variants

Accurate identification of single-nucleotide variants (SNVs) is critical in clinical diagnostics but remains challenging due to subtle free energy variations, particularly for hard-to-detect SNVs such as wobble base pairs and those in high guanine-cytosine (GC) regions. Here we report a high-energetic-penalty SNV detection (HEPSD) platform that redesigns the hybridization regions of CRISPR RNA (crRNA) in the CRISPR/Cas12a system. This system employs a binary crRNA architecture design that enables the activation of the cleavage activity of Cas12a while amplifying the energetic penalty for single-nucleotide mismatches through nonequilibrium hybridization-driven regulation. Consequently, the entire targeting region of CRISPR/Cas exhibits a marked preference for mutations in genomic DNA, while preventing false activation induced by sequences containing a single mismatched nucleotide. Moreover, HEPSD exhibits exceptional differentiation performance for hard-to-detect SNVs including wobble mutations at extreme GC contents. As proof of principle, profiling of BRAF V600E and EGFR L858R tumor mutations down to a 0.01% variant allele frequency was achieved, enabling accurate discrimination of 132 clinical sample pairs, which showed high consistency with quantitative polymerase chain reaction-based techniques and next-generation sequencing. The proven effectiveness of this platform showcases its potential for clinical molecular diagnostics and expands the fundamental scope of hybridization-based protocols.

Exploring the Frontiers of Nanopore Sequencing in Food Safety and Food Microbiology

Foodborne illnesses are a significant global public health challenge, with an estimated 600 million cases annually. Conventional food microbiology methods tend to be laborious and time consuming, pose difficulties in real-time utilization, and can display subpar accuracy or typing capabilities. With the recent advancements in third-generation sequencing and microbial omics, nanopore sequencing technology and its long-read sequencing capabilities have emerged as a promising platform. In recent years, nanopore sequencing technology has been benchmarked for its amplicon sequencing, whole-genome and transcriptome analysis, meta-analysis, and other advanced omics approaches. This review comprehensively covers nanopore sequencing technology's current advances in food safety applications, including outbreak investigation, pathogen surveillance, and antimicrobial resistance profiling. Despite significant progress, ongoing research and development are crucial to overcoming challenges in sequencing chemistry, accuracy, bioinformatics, and real-time adaptive sampling to fully realize nanopore sequencing technology's potential in food safety and food microbiology.

Identification and validation of lncRNA mutation hotspot SNPs associated with myasthenia gravis susceptibility

Background

Myasthenia gravis (MG) is an autoimmune disorder caused by antibodies that target the postsynaptic muscle membrane. Recent evidence suggests that genetic variants and long noncoding RNAs (lncRNAs) play crucial roles in the pathogenesis of MG. The purpose of this study was to investigate the associations between lncRNA-related single-nucleotide polymorphisms (SNPs) and MG susceptibility in Chinese populations.

Methods

First, we identified lncRNA mutation hotspot regions based on the improved Kolmogorov‒Smirnov test and the cumulative hypergeometric distribution principle. Next, we further identified lncRNA mutation hotspot SNPs by calculating conservative scores. Finally, experiments were conducted to verify the associations between lncRNA mutation hotspot SNPs and MG susceptibility. A total of 82 patients with MG and 82 healthy controls were recruited for genotyping of lncRNA mutation hotspot SNPs using the SNaPshot technique. Quantitative real-time PCR was used to investigate lncRNA expression in 34 patients with MG and 37 healthy controls.

Results

In the multistep calculation, 14 candidate SNPs of 3 lncRNAs (AL031686.1, NONHSAT028539.2 and AC245014.3) in MG were identified as mutation hotspot SNPs. The genotyping results of the 14 SNPs in our study revealed no statistically significant differences in the frequencies of genotypes and alleles between patients with MG and controls. However, in the lncRNA AL031686.1, rs1000383 and rs6094353 were in perfect linkage disequilibrium (LD) and were associated with an increased risk of ocular MG. Additionally, rs6094347 was associated with an increased risk of ocular MG. Nevertheless, no SNP was found to be associated with factors such as sex, age, the presence or absence of thymoma, or the genetic model of MG. Further experiments revealed that NONHSAT028539.2 expression was upregulated in peripheral blood mononuclear cells (PBMCs) from patients with MG compared with those from healthy controls.

Conclusion

In our study, we did not find an association between the 14 mutation hotspot SNPs of lncRNAs and susceptibility to MG. However, we observed that the rs6094347 and rs1000383/rs6094353 polymorphisms in the lncRNA AL031686.1 were associated with the risk of ocular MG.

Genetic Evidence of Obesity-Induced Chronic Wounds Mediated by Inflammatory Biomarkers

Background: Obese patients are increasingly recognized as being at higher risk for skin diseases, particularly chronic wounds. While the exact mechanisms remain unclear, obesity is suspected to influence the development of chronic injuries via inflammatory biomarkers. Single nucleotide polymorphisms (SNPs) may further influence gene expression, protein function, and levels of inflammatory biomarkers through various mechanisms, thereby modulating inflammatory responses that contribute to wound pathogenesis. Methods: A two-sample two-step Mendelian Randomization (MR) was employed to explore the causal relationship between obesity and chronic wounds, focusing on the mediating role of inflammatory biomarkers. SNPs were used as instrumental variables (IVs) to infer causality. Obesity-related genetic data were sourced from the UK Biobank and GIANT consortium. Genome-wide association studies provided data on 92 inflammatory biomarkers, involving 14,824 and 575,531 individuals. Pressure injuries, lower limb venous ulcers, and diabetic foot ulcer data were obtained from FinnGen R10 and the Pan-UK Biobank. Results: Obesity significantly increased the risk of pressure injuries, lower limb venous ulcers, and diabetic foot ulcers. CCL19, hGDNF, IL-12B, and TNFRSF9 were identified as mediators in obesity-induced lower limb venous ulcers. Conclusion: This study provides genetic evidence that obesity leads to lower limb venous ulcers via inflammatory biomarkers, suggesting potential therapeutic targets for intervention.

Single nucleotide polymorphisms: Implications in the early diagnosis and targeted intervention of coronary microvascular dysfunction

Coronary microvascular dysfunction (CMD) is a clinical syndrome of myocardial ischemia caused by structural and/or functional abnormalities of pre-coronary arterioles and arterioles. While genetics and other factors play a role in CMD etiology, the key pathogenic mechanism remains unclear. Currently, the diagnostic procedure for CMD is still cumbersome, and there is a lack of effective targeted interventions. Single nucleotide polymorphisms (SNPs) offer promise in addressing these issues. SNPs, reflecting common genetic variations, have garnered extensive investigation across multiple diseases. Several SNPs associated with CMD have been discovered, and some have the potential to be therapeutic targets. Nevertheless, studies on CMD-related SNPs are relatively nascent and limited in number. In this review, we summarize the previously reported CMD-associated SNPs, delineate their pathophysiological mechanisms, and predict potentially important CMD sites by analyzing the SNPs linked to diseases sharing similar pathogenetic mechanisms and risk factors, such as coronary artery disease. We aim to explore reliable genetic markers implicated in CMD risk and prognosis, thereby providing a novel approach for early diagnosis and gene-targeted interventions of CMD in subsequent studies.

Accurate assembly of full-length consensus for viral quasispecies

BACKGROUND

Viruses can inhabit their hosts in the form of an ensemble of various mutant strains. Reconstructing a robust consensus representation for these diverse mutant strains is essential for recognizing the genetic variations among strains and delving into aspects like virulence, pathogenesis, and selecting therapies. Virus genomes are typically small, often composed of only a few thousand to several hundred thousand nucleotides. While constructing a high-quality consensus of virus strains might seem feasible, most current assemblers only generated fragmented contigs. It's important to emphasize the significance of assembling a single full-length consensus contig, as it's vital for identifying genetic diversity and estimating strain abundance accurately.

RESULTS

In this paper, we developed FC-Virus, a de novo genome assembly strategy specifically targeting highly diverse viral populations. FC-Virus first identifies the k-mers that are common across most viral strains, and then uses these k-mers as a backbone to build a full-length consensus sequence covering the entire genome. We benchmark FC-Virus against state-of-the-art genome assemblers.

CONCLUSION

Experimental results confirm that FC-Virus can construct a single, accurate full-length consensus, whereas other assemblers only manage to produce fragmented contigs. FC-Virus is freely available at https://github.com/qdu-bioinfo/FC-Virus.git .

A MALDI-TOF MS-based multiple detection panel of drug resistance-associated multiple single-nucleotide polymorphisms in Candida tropicalis

Candida tropicalis is one of the main causes of invasive candidiasis. Rapid identification of antifungal resistance is crucial for selection of an appropriate antifungal to improve patient outcomes. Mutations at specific loci are strongly correlated with resistance to antifungal agents. In this study, we developed a multi-single-nucleotide polymorphism (SNP) panel to accurately identify 36 mutation sites across seven genes of C. tropicalis that are associated with resistance to azoles and/or echinocandins. Ten isolates were selected to test repeatability, and another 20 isolates of C. tropicalis were selected to validate consistency. Intra-assay and inter-assay repeatability of the panel was 100%, with the loci accuracy being 99.44% (716 of 720). Furthermore, 109 isolates were examined for clinical research, and the most commonly detected mutations were G751A and A866T of UPC2, A491T of TAC1, and A395T and C461T of ERG11. The G751A and A866T mutations of UPC2 as well as the A395T and C461T mutations of ERG11 co-existed. The SNP panel enables identification of specific mutations at critical sites of drug-resistant strains to facilitate the rapid selection of appropriate antifungal agents and efficient monitoring of the regional epidemiological trends of resistance of C. tropicalis.IMPORTANCEC. tropicalis infections pose a growing global public health challenge, with mortality rates approaching 40%. C. tropicalis is one of the top four Candida spp. responsible for candidiasis, particularly in the Asia-Pacific region and Latin America, notably affecting patients with neutropenia and malignancies. The azole resistance rate of C. tropicalis ranges from 0% to 30%. Between 2009 and 2018, the China Hospital Invasive Fungal Surveillance Network reported an increase in fluconazole and voriconazole resistance from 5.7% to ~30%. Although resistance to echinocandins and amphotericin B remains low, multi-resistance to echinocandins and azoles has been observed. Current methods for detecting drug resistance are limited by the long turnaround time of antifungal susceptibility testing, low throughput of Sanger sequence to target resistance mutations, complex data analysis, and high costs of second-generation sequencing. We developed and validated a rapid, high-throughput, and cost-effective panel to detect and monitor drug-resistance mutations of C. tropicalis.

Multiplex Detection of SNPs for Genetic Monitoring in Laboratory Mice by Luminex xTAG Assay

Background: The genetic quality of laboratory mice may have a direct impact on the results of research. Therefore, it is essential to improve genetic monitoring methods to guarantee research quality. However, few current methods boast high efficiency, high throughput, low cost, and general applicability at the same time. Methods: First, we got 34 SNP loci from previous studies for inbred strains and screened out 15 loci with good polymorphism for outbred groups from these 34 loci. Then, by using the Luminex xTAG assay, we tested inbred strains and outbred groups. Results: We tested commonly used inbred strains and five DNA samples from the International Council for Laboratory Animal Science, obtaining correct genotyping results. Additionally, some loci were potentially confirmed to be useful for distinguishing C57BL/6 and BALB/c mouse substrains. Furthermore, we tested three outbred groups and analyzed the genetic structure, and we compared the results of the SNP markers by xTAG assay to the STR markers by PCR, the trends of the three groups are the same. Conclusions: In our studies, the panels could meet the requirements for method promotion and provide a good choice for the genetic monitoring of inbred and outbred mice.

Molecular quantification of fritillariae cirrhosae bulbus and its adulterants

BACKGROUND

Fritillariae Cirrhosae Bulbus (FCB) is frequently adulterated with its closely related species due to personal or non-man made factors, leading to alterations in the composition of its constituents and compromising the efficacy of its products.

METHODS

The specific single nucleotide polymorphisms (SNPs) were screened by comparing candidate barcodes of Fritillaria and verified by amplification and sequencing. Herb molecular quantification (Herb-Q) was established by detecting specific SNPs, and the methodological validation was performed. Quantitative standard curves were established for FCB mixed with each adulterated species, and the quantitative validity of this method was verified based on external standard substance. In addition, eight commercial Shedan Chuanbei capsules (SDCBs) randomly selected were detected.

RESULTS

FCB and its five adulterants can be distinguished based on the ITS 341 site. The methodological investigation of Herb-Q shows optimal accuracy, and repeatability, which exhibited good linearity with an R2 of 0.9997 (> 0.99). An average bias in quantitative validity was 5.973% between the measured and actual values. Four of eight commercial SDCBs were adulterated with F. ussuriensis or F. thunbergia with adulteration levels ranging from 9 to 15% of the total weight.

CONCLUSION

This study confirmed that Herb-Q can quantitatively detect both the mixed herbs and Chinese patent medicines (CPMs) containing FCB with high reproducibility and accuracy. This method provides technical support for market regulation and helps safeguard patient rights.

Integrating targeted genetic markers to genotyping-by-sequencing for an ultimate genotyping tool

New selection methods, using trait-specific markers (marker-assisted selection (MAS)) and/or genome-wide markers (genomic selection (GS)), are becoming increasingly widespread in breeding programs. This new era requires innovative and cost-efficient solutions for genotyping. Reduction in sequencing cost has enhanced the use of high-throughput low-cost genotyping methods such as genotyping-by-sequencing (GBS) for genome-wide single-nucleotide polymorphism (SNP) profiling in large breeding populations. However, the major weakness of GBS methodologies is their inability to genotype targeted markers. Conversely, targeted methods, such as amplicon sequencing (AmpSeq), often face cost constraints, hindering genome-wide genotyping across a large cohort. Although GBS and AmpSeq data can be generated from the same sample, an efficient method to achieve this is lacking. In this study, we present the Genome-wide & Targeted Amplicon (GTA) genotyping platform, an innovative way to integrate multiplex targeted amplicons into the GBS library preparation to provide an all-in-one cost-effective genotyping solution to breeders and research communities. Custom primers were designed to target 23 and 36 high-value markers associated with key agronomical traits in soybean and barley, respectively. The resulting multiplex amplicons were compatible with the GBS library preparation enabling both GBS and targeted genotyping data to be produced efficiently and cost-effectively. To facilitate data analysis, we have introduced Fast-GBS.v3, a user-friendly bioinformatic pipeline that generates comprehensive outputs from data obtained following sequencing of GTA libraries. This high-throughput low-cost approach will greatly facilitate the application of DNA markers as it provides required markers for both MAS and GS in a single assay.

Vitamin D receptor gene polymorphisms, bioavailable 25-hydroxyvitamin D, and hepatocellular carcinoma survival

BACKGROUND

Little is known about the role of vitamin D receptor polymorphisms and their interaction with vitamin D status in hepatocellular carcinoma (HCC) prognosis.

METHODS

We evaluated the association of TaqI, BsmI, Cdx-2, and ApaI polymorphisms, individually and in combination, with liver cancer-specific (LCSS) and overall survival (OS) among 967 patients with newly diagnosed HCC. Subsequently, we examined whether these polymorphisms modified the association between serum bioavailable 25-hydroxyvitamin D (25OHD) concentrations and survival. Cox proportional hazard models were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs).

RESULTS

During a median follow-up of 1017 days, 393 deaths occurred, with 360 attributed to HCC. Having TaqI G allele (HRper allele = 1.30, 95% CI = 1.08 to 1.57) or BsmI T allele (HRper allele = 1.41, 95% CI = 1.01 to 1.99) was associated with worse LCSS. Carrying increasing numbers of protective alleles was associated with superior LCSS (HR6-8 vs 0-3 = 0.52, 95% CI = 0.34 to 0.80). The inverse association of bioavailable 25OHD with LCSS was statistically significant only in patients with TaqI AA (HRQuartile 4 vs Quartile 1 = 0.63, 95% CI = 0.44 to 0.92), BsmI CC (HRQuartile 4 vs Quartile 1 = 0.62, 95% CI = 0.44 to 0.88), and 6 to 8 protective alleles (HRQuartile 4 vs Quartile 1 = 0.45, 95% CI = 0.23 to 0.87). Similar associations were observed for OS.

CONCLUSIONS

Patients carrying wild-type TaqI, BsmI, or more protective alleles had improved survival and might benefit from optimizing bioavailable 25OHD status.

Learning from Classic: DNA-Based Conditional Equilibrium Constant To Regulate Affinity "On-the-Fly" for Bioassays

Artificial programming of affinity is beneficial to optimize responsiveness in biomolecules for various applications. In one classical theory, one comprehensive parameter, conditional equilibrium constant (K'EDTA), can accurately and quantitatively define the affinity of ethylene diamine tetraacetic acid (EDTA) for metal ions. Learning from the classic, we have proposed a novel DNA-based conditional equilibrium constant (K'DNA) to regulate DNA probes' affinity and response "on-the-fly", long after the probe design and synthesis. Artificial regulation of affinity over several magnitudes has been simply realized via short oligonucleotides with different lengths, concentrations, and combinations. The thermodynamic response can be quantitatively simulated by one DNA-based conditional equilibrium constant (K'DNA), acting as an analogue to the classical EDTA system. The proof of concept of affinity programming also allows improved discrimination of single-nucleotide variants as well as assaying ribonuclease and doxycycline in a homogeneous solution. Therefore, the theory of DNA-based conditional equilibrium constant (K'DNA) will enable to engineer versatile DNA switches with programmable affinity in assays and bionanotechnology.

A multi-AS-PCR-coupled CRISPR/Cas12a assay for the detection of ten single-base mutations

Single-nucleotide polymorphism (SNP) detection is critical for diagnosing diseases, and the development of rapid and accurate diagnostic tools is essential for treatment and prevention. Allele-specific polymerase chain reaction (AS-PCR) is widely used for detecting SNPs with multiplexing capabilities, while CRISPR-based technologies provide high sensitivity and specificity in targeting mutation sites through specific guide RNAs (gRNAs). In this study, we have integrated the high sensitivity and specificity of CRISPR technology with the multiplexing capabilities of AS-PCR, achieving the simultaneous detection of ten single-base mutations. As for Multi-AS-PCR, our research identified that competitive inhibition of primers targeting the same loci, coupled with divergent amplification efficiencies of these primers, could result in diminished amplification efficiency. Consequently, we adjusted and optimized primer combinations and ratios to enhance the amplification efficacy of Multi-AS-PCR. Finally, we successfully developed a novel nested Multi-AS-PCR-Cas12a method for multiplex SNPs detection. To evaluate the clinical utility of this method in a real-world setting, we applied it to diagnose rifampicin-resistant tuberculosis (TB). The limit of detection (LoD) for the nested Multi-AS-PCR-Cas12a was 102 aM, achieving sensitivity, specificity, positive predictive value, and negative predictive value of 100 %, 93.33 %, 90.00 %, and 100 %, respectively, compared to sequencing. In summary, by employing an innovative design that incorporates a universal reverse primer alongside ten distinct forward allele-specific primers, the nested Multi-AS-PCR-Cas12a technique facilitates the parallel detection of ten rpoB gene SNPs. This method also holds broad potential for the detection of drug-resistant gene mutations in infectious diseases and tumors, as well as for the screening of specific genetic disorders.

HapKled: a haplotype-aware structural variant calling approach for Oxford nanopore sequencing data

Introduction: Structural Variants (SVs) are a type of variation that can significantly influence phenotypes and cause diseases. Thus, the accurate detection of SVs is a vital part of modern genetic analysis. The advent of long-read sequencing technology ushers in a new era of more accurate and comprehensive SV calling, and many tools have been developed to call SVs using long-read data. Haplotype-tagging is a procedure that can tag haplotype information on reads and can thus potentially improve the SV detection; nevertheless, few methods make use of this information. In this article, we introduce HapKled, a new SV detection tool that can accurately detect SVs from Oxford Nanopore Technologies (ONT) long-read alignment data. Methods: HapKled utilizes haplotype information underlying alignment data by conducting haplotype-tagging using Whatshap on the reads to improve the detection performance, with three unique calling mechanics including altering clustering conditions according to haplotype information of signatures, determination of similar SVs based on haplotype information, and slack filtering conditions based on haplotype quality. Results: In our evaluations, HapKled outperformed state-of-the-art tools and can deliver better SV detection results on both simulated and real sequencing data. The code and experiments of HapKled can be obtained from https://github.com/CoREse/HapKled. Discussion: With the superb SV detection performance that HapKled can deliver, HapKled could be useful in bioinformatics research, clinical diagnosis, and medical research and development.

Dual toeholds regulated CRISPR-Cas12a sensing platform for ApoE single nucleotide polymorphisms genotyping

Single nucleotide polymorphisms (SNPs) are closely associated with many biological processes, including genetic disease, tumorigenesis, and drug metabolism. Accurate and efficient SNP determination has been proved pivotal in pharmacogenomics and diagnostics. Herein, a universal and high-fidelity genotyping platform is established based on the dual toeholds regulated Cas12a sensing methodology. Different from the conventional single stranded or double stranded activation mode, the dual toeholds regulated mode overcomes protospacer adjacent motif (PAM) limitation via cascade toehold mediated strand displacement reaction, which is highly universal and ultra-specific. To enhance the sensitivity for biological samples analysis, a modified isothermal recombinant polymerase amplification (RPA) strategy is developed via utilizing deoxythymidine substituted primer and uracil-DNA glycosylase (UDG) treatment, designated as RPA-UDG. The dsDNA products containing single stranded toehold domain generated in the RPA-UDG allow further incorporation with dual toeholds regulated Cas12a platform for high-fidelity human sample genotyping. We discriminate all the single-nucleotide polymorphisms of ApoE gene at rs429358 and rs7412 loci with human buccal swab samples with 100% accuracy. Furthermore, we engineer visual readout of genotyping results by exploiting commercial lateral flow strips, which opens new possibilities for field deployable implementation.

Multi-modal deep learning from imaging genomic data for schizophrenia classification

Background

Schizophrenia (SZ) is a psychiatric condition that adversely affects an individual's cognitive, emotional, and behavioral aspects. The etiology of SZ, although extensively studied, remains unclear, as multiple factors come together to contribute toward its development. There is a consistent body of evidence documenting the presence of structural and functional deviations in the brains of individuals with SZ. Moreover, the hereditary aspect of SZ is supported by the significant involvement of genomics markers. Therefore, the need to investigate SZ from a multi-modal perspective and develop approaches for improved detection arises.

Methods

Our proposed method employed a deep learning framework combining features from structural magnetic resonance imaging (sMRI), functional magnetic resonance imaging (fMRI), and genetic markers such as single nucleotide polymorphism (SNP). For sMRI, we used a pre-trained DenseNet to extract the morphological features. To identify the most relevant functional connections in fMRI and SNPs linked to SZ, we applied a 1-dimensional convolutional neural network (CNN) followed by layerwise relevance propagation (LRP). Finally, we concatenated these obtained features across modalities and fed them to the extreme gradient boosting (XGBoost) tree-based classifier to classify SZ from healthy control (HC).

Results

Experimental evaluation on clinical dataset demonstrated that, compared to the outcomes obtained from each modality individually, our proposed multi-modal approach performed classification of SZ individuals from HC with an improved accuracy of 79.01%.

Conclusion

We proposed a deep learning based framework that selects multi-modal (sMRI, fMRI and genetic) features efficiently and fuse them to obtain improved classification scores. Additionally, by using Explainable AI (XAI), we were able to pinpoint and validate significant functional network connections and SNPs that contributed the most toward SZ classification, providing necessary interpretation behind our findings.

CD73 polymorphisms are associated with schizophrenia

Ecto-5'-nucleotidase/CD73 enzyme plays a key role in the regulation of extracellular adenosine levels, thereby exerting influence on adenosine homeostasis. Emerging evidence suggests that perturbations in purines and ecto-5'-nucleotidase activity are associated with an augmented susceptibility to schizophrenia. However, the precise impact of genetic variations in CD73 on individuals with schizophrenia remains poorly understood. Here, our study demonstrated that rs3734442 allele and rs4431401 heterozygote were conferred a significant risk of schizophrenia disease (rs3734442: odds ratio, 0.556; 95% CI, 0.375 to 0.825; p = 0.004; rs4431401: odds ratio, 1.881, 95% CI, 1.117 to 3.166; p = 0.020). Comparing different genders, we observed a significant association between rs3734442 genotypes and male cases (rs3734442: odds ratio, 0.452; 95% CI, 0.257 to 0.796; p = 0.007). Likewise, there was a significant association between rs4431401 genotypes and male patients (rs4431401: odds ratio, 2.570; 95% CI, 1.196 to 5.522; p = 0.015). Based on family history and antipsychotics medication usage, our data reveals that the rs9444348 allele exhibits the most significant association with familial susceptibility to schizophrenia (odds ratio, 1.541; 95% CI, 1.009 to 2.353; p = 0.048 for A vs G). Moreover, individuals carrying variants of rs6922, rs2229523, and rs2065114 while being treated with clozapine demonstrate a higher frequency proportion compared to those receiving risperidone treatment (p = 0.035; p = 0.049; p = 0.027 respectively). Additionally, our results indicate that patients with GG genotype of rs9444348 had significantly higher likelihood of using clozapine instead of sulpiride (p = 0.048). Overall, our data strongly suggest that genetic variations in CD73 are significantly associated with schizophrenia risk and may serve as valuable resources for identifying therapeutic targets.

Polymorphism rs2327430 in TCF21 predicts the risk and prognosis of gastric cancer by affecting the binding between TFAP2A and TCF21

BACKGROUND

Single nuclear polymorphisms (SNPs) have been published to be correlated with multiple diseases. Transcription Factor 21 (TCF21) is a critical transcription factor involved in various types of cancers. However, the association of TCF21 genetic polymorphisms with gastric cancer (GC) susceptibility and prognosis remains unclear.

METHODS

A case-control study comprising 890 patients diagnosed with GC and an equal number of cancer-free controls was conducted. After rigorous statistical analysis, molecular experiments were carried out to elucidate the functional significance of the SNPs in the context of GC.

RESULTS

TCF21 rs2327430 (OR = 0.78, P = 0.026) provides protection against GC, while rs4896011 (OR = 1.39, P = 0.005) exhibit significant associations with GC risk. Furthermore, patients with the (TC + CC) genotype of rs2327430 demonstrate a relatively favorable prognosis (OR = 0.47, P = 0.012). Mechanistically, chromatin immunoprecipitation assay and luciferase reporter assay revealed that the C allele of rs2327430 disrupts the binding of Transcription Factor AP-2 Alpha (TFAP2A) to the promoter region of TCF21, resulting in increased expression of TCF21 and inhibition of malignant behaviors in GC cells.

CONCLUSION

Our findings highlight the significant role of TCF21 SNPs in both the risk and prognosis of GC and provide valuable insights into the underlying molecular mechanisms. Specifically, the disruptive effect of rs2327430 on TCF21 expression and its ability to modulate malignant cell behaviors suggest that rs2327430 may serve as a potential predictive marker for GC risk and prognosis.

Identifying the association between polymorphisms in the GZMB and IFIH1 genes and psoriasis in Egyptians

OBJECTIVES

This study aims to examine whether the genetic variants in the genes for Granzyme B (GZMB) and Interferon Induced with Helicase C domain 1 (IFIH1) were associated with psoriasis.

BACKGROUND

Psoriasis, a papulosquamous skin disease, was initially thought of as a disorder primarily of epidermal keratinocytes but is now recognized as one of the most common immune-mediated disorders. It is caused by the interplay between multiple genetic and environmental risk factors.

SUBJECTS AND METHODS

This case-control study has 65 participants with psoriasis and 65 healthy controls. Real-time PCR was used to genotype GZMB (rs8192917) and IFIH1 (rs35667974).

RESULTS

Genotype occurrence and allelic spreading for both SNPs are in Hardy - Weinberg equilibrium. The genotype and allele distributions of rs35667974 showed no differences between the studied groups. Regarding rs8192917, compared to Group II, there is a statistically significant rise in the CC genotype and C allele in Group I. Higher PASI scores are detected in the C/C and C/T genotypes more than the T/T genotype. Univariate and multivariate analyses revealed that BMI, catalase, MDA, and rs8192917 (C/C) are associated with psoriasis.

CONCLUSION

GZMB rs8192917 was significantly related to psoriasis risk; its C allele is likewise associated with psoriasis vulnerability. However, our investigation found no link between rs35667974 and psoriasis.

Split G-quadruplex based PfAgo sensing platform for nucleotide mutation discrimination and human genotyping

A PfAgo-G4 sensing platform exploiting G4 as a signal reporter was proposed, validated, and optimized. By introducing two mismatches at the Link strand, a universal nucleotide design rule was established for accurate single nucleotide polymorphism discrimination with PfAgo-G4. The FUT2 gene was then successfully and accurately genotyped using human buccal swab samples.

Kled: an ultra-fast and sensitive structural variant detection tool for long-read sequencing data

Structural Variants (SVs) are a crucial type of genetic variant that can significantly impact phenotypes. Therefore, the identification of SVs is an essential part of modern genomic analysis. In this article, we present kled, an ultra-fast and sensitive SV caller for long-read sequencing data given the specially designed approach with a novel signature-merging algorithm, custom refinement strategies and a high-performance program structure. The evaluation results demonstrate that kled can achieve optimal SV calling compared to several state-of-the-art methods on simulated and real long-read data for different platforms and sequencing depths. Furthermore, kled excels at rapid SV calling and can efficiently utilize multiple Central Processing Unit (CPU) cores while maintaining low memory usage. The source code for kled can be obtained from https://github.com/CoREse/kled.

Molecular epidemiology of SARS-CoV-2 in Northern South Africa: wastewater surveillance from January 2021 to May 2022

Introduction

Wastewater-based genomic surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) provides a comprehensive approach to characterize evolutionary patterns and distribution of viral types in a population. This study documents the molecular epidemiology of SARS-CoV-2, in Northern South Africa, from January 2021 to May 2022.

Methodology

A total of 487 wastewater samples were collected from the influent of eight wastewater treatment facilities and tested for SARS-CoV-2 RNA using quantitative reverse transcriptase polymerase chain reaction (qRT-PCR). SARS-CoV-2 positive samples with genome copies/mL ≥1,500 were subjected to allele-specific genotyping (ASG) targeting the Spike protein; 75 SARS-CoV-2 positive samples were subjected to whole genome sequencing (WGS) on the ATOPlex platform. Variants of concern (VoC) and lineages were assigned using the Nextclade and PangoLIN Software. Concordance for VoC between ASG and WGS analyses was determined. Sequence relationship was determined by phylogenetic analysis.

Results

Seventy-five percent (365/487) of the influent samples were positive for SARS-CoV-2 RNA. Delta and Omicron VoC were more predominant at a prevalence of 45 and 32%, respectively, and they were detected as early as January and February 2021, while Beta VoC was least detected at a prevalence of 5%. A total of 11/60 (18%) sequences were assigned lineages and clades only, but not a specific VoC name. Phylogenetic analysis was used to investigate the relationship of these sequences to other study sequences, and further characterize them. Concordance in variant assignment between ASG and WGS was seen in 51.2% of the study sequences. There was more intra-variant diversity among Beta VoC sequences; mutation E484K was absent. Three previously undescribed mutations (A361S, V327I, D427Y) were seen in Delta VoC.

Discussion and Conclusion

The detection of Delta and Omicron VoCs in study sites earlier in the outbreak than has been reported in other regions of South Africa highlights the importance of population-based approaches over individual sample-based approaches in genomic surveillance. Inclusion of non-Spike protein targets could improve the specificity of ASG, since all VoCs share similar Spike protein mutations. Finally, continuous molecular epidemiology with the application of sensitive technologies such as next generation sequencing (NGS) is necessary for the documentation of mutations whose implications when further investigated could enhance diagnostics, and vaccine development efforts.

Genetic variants of ERBB4 gene and risk of gestational diabetes mellitus: a susceptibility and diagnostic nomogram study

Introduction

Gestational diabetes (GDM) is one of the common complications of female pregnancy, which seriously affects the health of mothers and their offspring. So far, the etiology has not been fully clarified.

Methods

A case-control study was conducted to clarify the relationship between Erb-b2 receptor tyrosine kinase 4 (ERBB4) functional tag genetic variants (rs1595064, rs1595065, rs1595066 and rs6719645) and the risk of GDM. Associations between variants and GDM risk were evaluated with the odds ratios (ORs) and their corresponding 95% confidence intervals (CIs). Subsequently, the false-positive reporting probability (FPRP), multi-factor dimension reduction (MDR) and bioinformatics analysis were adopted to confirm the significant associations. A nomogram model was constructed to predict the risk of GDM.

Results

Association analysis demonstrated that rs1595066 TT genotype performed a protective effect on GDM risk among all subjects (TT vs. CC: adjusted OR = 0.60, 95% CI = 0.38 - 0.94, P = 0.026; TT vs. CC/CT: adjusted OR = 0.61, 95% CI = 0.40 - 0.95, P = 0.027). Meanwhile, stratified analysis showed that rs1595066 TT can also reduce the GDM risk in age > 30.09 years old, pre-pregnancy BMI > 22.23 Kg/m2, SBP ≤ 110.08 mmHg, etc subgroups. Interactions between rs1595066 and DBP (P interaction = 0.01), FPG (P interaction < 0.001) and HbA1c (P interaction < 0.001) were detected. The FPRP analysis confirmed that association between rs1595066 and GDM risk in subjects of FPG < 4.79 mmol/L (P = 0.199) is true. The MDR analysis showed that rs1595066 was the best single locus model while the 4-loci model was the best multiple factors model to predict GDM risk. Functional prediction revealed that rs1595066 may disturb the stability of miRNA-mRNA binding. The predictive nomogram model has a well consistence and acceptable discriminative ability with a diagnosed AUC of 0.813.

Discussion

ERBB4 variants can change an individual's susceptibility to GDM via the interaction of gene-gene, gene-environment and changes in the regulatory effects of miRNAs on ERBB4 expression.

Uncovering genes underlying coat color variation in indigenous cattle breeds through genome-wide positive selection

The identification of candidate genes related to pigmentation and under selective sweep provides insights into the genetic basis of pigmentation and the evolutionary forces that have shaped this variation. The selective sweep events in the genes responsible for normal coat color in Indian cattle groups are still unknown. To find coat color genes displaying signs of selective sweeps in the indigenous cattle, we compiled a list of candidate genes previously investigated for their association with coat color and pigmentation. After that, we performed a genome-wide scan of positive selection signatures using the BovineSNP50K Bead Chip in 187 individuals of seven indigenous breeds. We applied a wide range of methods to find evidence of selection, such as Tajima's D, CLR, iHS, varLD, ROH, and FST. We found a total of sixteen genes under selective sweep, that were involved in coat color and pigmentation physiology. These genes are CRIM1 in Gir, MC1R in Sahiwal, MYO5A, PMEL and POMC in Tharparkar, TYRP1, ERBB2, and ASIP in Red Sindhi, MITF, LOC789175, PAX3 and TYR in Ongole, and IRF2, SDR165 and, KIT in Nelore, ADAMTS19 in Hariana. These genes are related to melanin synthesis, the biology of melanocytes and melanosomes, and the migration and survival of melanocytes during development.

Polymorphism in epigenetic regulating genes in relation to periodontitis, number of teeth, and levels of high-sensitivity C-reactive protein and glycated hemoglobin: The Tromsø Study 2015-2016

BACKGROUND

The aim of this study was to investigate the association between periodontitis and four single nucleotide polymorphisms (SNPs) in genes involved in epigenetic regulation of DNA, and between these same SNPs and tooth loss, high-sensitivity C-reactive protein (hs-CRP), and glycated hemoglobin (HbA1c) levels.

METHODS

We included participants with periodontal examination (n = 3633, aged: 40-93 years) from the Tromsø Study seventh survey (2015-2016), Norway. Periodontitis was defined according to the 2017 AAP/EFP classification system as no periodontitis, grades A, B, or C. Salivary DNA was extracted and genotyping was performed to investigate four SNPs (rs2288349, rs35474715, rs34023346, and rs10010325) in the sequence of the genes DNMT1, IDH2, TET1, and TET2. Association between SNPs and periodontitis was analyzed by logistic regression adjusted for age, sex, and smoking. Subgroup analyses on participants aged 40-49 years were performed.

RESULTS

In participants aged 40-49 years, homozygous carriage of minor A-allele of rs2288349 (DNMT1) was associated with decreased susceptibility to periodontitis (grade A: odds ratio [OR] 0.55; p = 0.014: grade B/C OR 0.48; p = 0.004). The minor A-allele of rs10010325 (TET2) was associated with increased susceptibility to periodontitis (grade A OR 1.69; p = 0.035: grade B/C OR 1.90; p = 0.014). In the entire sample, homozygous carriage of the G-allele of rs35474715 (IDH2) was associated with having ≤24 teeth (OR 1.31; p = 0.018). Homozygous carriage of the A-allele of TET2 was associated with hs-CRP≥3 mg/L (OR 1.37; p = 0.025) and HbA1c≥6.5% (OR 1.62; p = 0.028).

CONCLUSIONS

In this Norwegian population, there were associations between polymorphism in genes related to DNA methylation and periodontitis, tooth loss, low-grade inflammation, and hyperglycemia.

Using Recurrent Neural Networks to Reconstruct Temperatures from Simulated Fluorescent Data for use in Bio-Microfluidics

Many biological systems have a narrow temperature range of operation, meaning high accuracy and spatial distribution level are needed to study these systems. Most temperature sensors cannot meet both the accuracy and spatial distribution required in the microfluidic systems that are often used to study these systems in isolation. This paper introduces a neural network called the Multi-Directional Fluorescent Temperature Long Short-Term Memory Network (MFTLSTM) that can accurately calculate the temperature at every pixel in a fluorescent image to improve upon the standard fitting practice and other machine learning methods use to relate fluorescent data to temperature. This network takes advantage of the nature of heat diffusion in the image to achieve an accuracy of ±0.0199 K RMSE within the temperature range of 298K to 308 K with simulated data. When applied to experimental data from a 3D printed microfluidic device with a temperature range of 290 K to 380 K, it achieved an accuracy of ±0.0684 K RMSE. These results have the potential to allow high temperature resolution in biological systems than is available in many microfluidic devices.

Versatile DNA Balances via Adjacent Base Stacking for Homogeneous Assay of Energy Parameters, Small Molecules, And Ribonuclease

Homogeneous assays often obviate any separation and washing steps, thus minimizing the risks of contamination and false positive. DNA toehold exchange is a homogeneous, reversible process whose thermodynamic properties can be finely tuned for various assay applications. However, the developed probes often rely on direct interactions of analytes with DNA strands involved in toehold exchange, limiting the versatility of probe design. Here, the coaxial adjacent stacking between one auxiliary strand and another invading strand offers a favorable ΔG to shift one DNA balance, while the auxiliary strand is independent of the DNA balance itself. Therefore, such a DNA balance allowed fine tuning of the equilibrium via adjustment of the auxiliary strand alone. The energy contribution of base stacking can be quantified in a homogeneous solution based on the difference in the equilibrium constant. Besides, the proof of concept for DNA balance allows effective assay of a small molecule or ribonuclease in a homogeneous solution. This novel DNA balance via adjacent base stacking provides an interesting alternative to homogeneously assay various analytes.

Semiautomated Electrochemical Melting Curve Analysis Device for the Detection of an Osteoporosis Associated Single Nucleotide Polymorphism in Blood

The detection of single nucleotide polymorphisms (SNPs) is of increasing importance in many areas including clinical diagnostics, patient stratification for pharmacogenomics, and advanced forensic analysis. In the work reported, we apply a semiautomated system for solid-phase electrochemical melting curve analysis (éMCA) for the identification of the allele present at a specific SNP site associated with an increased risk of bone fracture and predisposition to osteoporosis. Asymmetric isothermal recombinase polymerase amplification using ferrocene labeled forward primers was employed to generate single stranded redox labeled amplicons. In a first approach to demonstrate the proof of concept of combining asymmetric RPA with solid-phase éMCA, a simplified system housing a multielectrode array within a polymeric microsystem, sandwiched between two aluminum plates of a heater device, was used. Sample manipulation through the microfluidic channel was controlled by a syringe pump, and an external Ag/AgCl reference electrode was employed. Individual electrodes of the array were functionalized with four different oligonucleotide probes, each probe equivalent in design with the exception of the middle nucleotide. The isothermally generated amplicons were allowed to hybridize to the surface-tethered probes and subsequently subjected to a controlled temperature ramp, and the melting of the duplex was monitored electrochemically. A clear difference between the fully complementary and a single mismatch was observed. Having demonstrated the proof-of-concept, a device for automated éMCA with increased flexibility to house diverse electrode arrays with internal quasi-gold reference electrodes, higher resolution, and broader melting temperature range was developed and exploited for the detection of SNP hetero/homozygosity. Using the optimized conditions, the system was applied to the identification of the allele present at an osteoporosis associated SNP site, rs2741856, in 10 real fingerprick/venous blood samples, with results validated using Sanger sequencing.

A mutation-sensitive, multiplexed and amplification-free detection of nucleic acids by stretching single-molecule tandem hairpin probes

The detection of nucleic acid sequences in parallel with the discrimination of single nucleotide variations (SNVs) is critical for research and clinical applications. A few limitations make the detection technically challenging, such as too small variation in probe-hybridization energy caused by SNVs, the non-specific amplification of false nucleic acid fragments and the few options of dyes limited by spectral overlaps. To circumvent these limitations, we developed a single-molecule nucleic acid detection assay without amplification or fluorescence termed THREF (hybridization-induced tandem DNA hairpin refolding failure) based on multiplexed magnetic tweezers. THREF can detect DNA and RNA sequences at femtomolar concentrations within 30 min, monitor multiple probes in parallel, quantify the expression level of miR-122 in patient tissues, discriminate SNVs including the hard-to-detect G-U or T-G wobble mutations and reuse the probes to save the cost. In our demonstrative detections using mock clinic samples, we profiled the let-7 family microRNAs in serum and genotyped SARS-CoV-2 strains in saliva. Overall, the THREF assay can discriminate SNVs with the advantages of high sensitivity, ultra-specificity, multiplexing, reusability, sample hands-free and robustness.

Defining the single base importance of human mRNAs and lncRNAs

As the fundamental unit of a gene and its transcripts, nucleotides have enormous impacts on the gene function and evolution, and thus on phenotypes and diseases. In order to identify the key nucleotides of one specific gene, it is quite crucial to quantitatively measure the importance of each base on the gene. However, there are still no sequence-based methods of doing that. Here, we proposed Base Importance Calculator (BIC), an algorithm to calculate the importance score of each single base based on sequence information of human mRNAs and long noncoding RNAs (lncRNAs). We then confirmed its power by applying BIC to three different tasks. Firstly, we revealed that BIC can effectively evaluate the pathogenicity of both genes and single bases through single nucleotide variations. Moreover, the BIC score in The Cancer Genome Atlas somatic mutations is able to predict the prognosis of some cancers. Finally, we show that BIC can also precisely predict the transmissibility of SARS-CoV-2. The above results indicate that BIC is a useful tool for evaluating the single base importance of human mRNAs and lncRNAs.

Genetic diversity and population structure of Polygonatum cyrtonema Hua in China using SSR markers

Polygonatum cyrtonema Hua is a perennial herbaceous plant of the Polygonatum genus, belonging to the Liliaceae family, with significant medicinal and nutritional value. In China, this species is a traditional medicinal and edible herb with a long history of application and is widely appreciated by the people. However, as the demand for medicinal herbs continues to grow, excessive harvesting has led to the depletion of wild resources and the risk of genetic erosion. In addition, the chaotic cultivation of varieties and the lack of high quality germplasm resources have led to inconsistent quality of medical materials. Therefore, it is urgent to conduct genetic diversity evaluation of this species and establish a sound conservation plan. This study assessed the genetic diversity and population structure of 96 samples collected from seven regions in China using the simple sequence repeat (SSR) molecular marker technology. In this study, a total of 60 alleles (Na) were detected across the 10 polymorphic SSR markers used, with an average of 6.0 alleles generated per locus. The values of polymorphic information content (PIC) values ranged from 0.3396 to 0.8794, with an average value of 0.6430. The average value of the effective number of alleles (Ne) was 2.761, and the average value of the Shannon's information index (I) was 1.196. The population structure analysis indicates that the Polygonatum cyrtonema Hua germplasm can be classified into three subpopulations (JZ, QY, JD) at the molecular level, which corresponds to the previous subgroups identified based on individual plant phenotypic traits. Analysis of Molecular Variance (AMOVA) showed that 74% of the genetic variation was between individuals within populations in different regions. The phylogenetic analysis of the 96 germplasm samples divided them into three main populations. The QY and JD subpopulations are largely clustered together, which could be attributed to their mountainous distribution and the local climate environment. The genetic differentiation coefficient (Fst) value was low at 0.065, indicating relatively low population differentiation. The ratio of the genetic differentiation coefficient (Fst) between the JZ population and the other two populations (QY and JD) is much higher than the ratio between the QY and JD populations. Based on the clustering results and the ratio of the genetic differentiation coefficient (Fst), it can be inferred that the genetic relationship between the QY and JD subpopulations is closer, with a certain degree of genetic differentiation from the JZ subpopulation. This study supports the conservation of germplasm resources of Polygonatum cyrtonema Hua in China and provides new parental material for germplasm genetic improvement and breeding programs.

A Chamber-Based Digital PCR Based on a Microfluidic Chip for the Absolute Quantification and Analysis of KRAS Mutation

The Kirsten rat sarcoma virus gene (KRAS) is the most common tumor in human cancer, and KRAS plays an important role in the growth of tumor cells. Normal KRAS inhibits tumor cell growth. When mutated, it will continuously stimulate cell growth, resulting in tumor development. There are currently few drugs that target the KRAS gene. Here, we developed a microfluidic chip. The chip design uses parallel fluid channels combined with cylindrical chamber arrays to generate 20,000 cylindrical microchambers. The microfluidic chip designed by us can be used for the microsegmentation of KRAS gene samples. The thermal cycling required for the PCR stage is performed on a flat-panel instrument and detected using a four-color fluorescence system. "Glass-PDMS-glass" sandwich structure effectively reduces reagent volatilization; in addition, a valve is installed at the sample inlet and outlet on the upper layer of the chip to facilitate automatic control. The liquid separation performance of the chip was verified by an automated platform. Finally, using the constructed KRAS gene mutation detection system, it is verified that the chip has good application potential for digital polymerase chain reaction (dPCR). The experimental results show that the chip has a stable performance and can achieve a dynamic detection range of four orders of magnitude and a gene mutation detection of 0.2%. In addition, the four-color fluorescence detection system developed based on the chip can distinguish three different KRAS gene mutation types simultaneously on a single chip.

Universal probe-based SNP genotyping with visual readout: a robust and versatile method

Detection of single nucleotide polymorphisms (SNPs) is critical for personalized clinical diagnosis, treatment, and medication. Current clinical detection methods suffer from primer dimerization and require the redesigning of reaction systems for different targets, resulting in a time-consuming and laborious process. Here, we present a robust and versatile method for SNP typing by using tailed primers and universal small molecule probes in combination with a visualized lateral flow assay (LFA). This approach enables not only rapid typing of different targets, but also eliminates the interference of primer dimers and enhances the accuracy and reliability of the results. Our proposed universal assay has been successfully applied to the typing of four SNP loci of clinical samples to verify the accuracy and universality, and the results are consistent with those obtained by Sanger sequencing. Therefore, our study establishes a new universal "typing formula" using nucleic acid tags and small molecule probes that provides a powerful genotyping platform for genetic analysis and molecular diagnostics.

Breed identification using breed-informative SNPs and machine learning based on whole genome sequence data and SNP chip data

BACKGROUND

Breed identification is useful in a variety of biological contexts. Breed identification usually involves two stages, i.e., detection of breed-informative SNPs and breed assignment. For both stages, there are several methods proposed. However, what is the optimal combination of these methods remain unclear. In this study, using the whole genome sequence data available for 13 cattle breeds from Run 8 of the 1,000 Bull Genomes Project, we compared the combinations of three methods (Delta, F_ST, and I_n) for breed-informative SNP detection and five machine learning methods (KNN, SVM, RF, NB, and ANN) for breed assignment with respect to different reference population sizes and difference numbers of most breed-informative SNPs. In addition, we evaluated the accuracy of breed identification using SNP chip data of different densities.

RESULTS

We found that all combinations performed quite well with identification accuracies over 95% in all scenarios. However, there was no combination which performed the best and robust across all scenarios. We proposed to integrate the three breed-informative detection methods, named DFI, and integrate the three machine learning methods, KNN, SVM, and RF, named KSR. We found that the combination of these two integrated methods outperformed the other combinations with accuracies over 99% in most cases and was very robust in all scenarios. The accuracies from using SNP chip data were only slightly lower than that from using sequence data in most cases.

CONCLUSIONS

The current study showed that the combination of DFI and KSR was the optimal strategy. Using sequence data resulted in higher accuracies than using chip data in most cases. However, the differences were generally small. In view of the cost of genotyping, using chip data is also a good option for breed identification.

Machine learning for genetic prediction of chemotherapy toxicity in cervical cancer

BACKGROUND

Locally advanced cervical cancer (LACC) is frequently treated with neoadjuvant chemotherapy (NACT), which includes paclitaxel and platinum. However, the development of severe chemotherapy toxicity is a barrier to successful NACT. Phosphatidylinositol 3-kinase (PI3K)/serine/threonine kinase (AKT) pathway is related to the occurrence of chemotherapeutic toxicity. In this research work, we employ a random forest (RF) machine learning model to forecast NACT toxicity (neurological, gastrointestinal, and hematological reactions).

MATERIALS AND METHODS

Twenty-four single nucleotide polymorphisms (SNPs) in the PI3K/AKT pathway from 259 LACC patients were used to construct a dataset. Following the data preprocessing, the RF model was trained. The Mean Decrease in Impurity approach was adopted to evaluate the relevance of 70 selected genotypes' importance by comparing chemotherapy toxicity grades 1-2 vs. 3.

RESULTS

In the Mean Decrease in Impurity analysis, neurological toxicity was much more likely to occur in LACC patients with homozygous AA in Akt2 rs7259541 than in those with AG or GG genotypes. The CT genotype of PTEN rs532678 and the CT genotype of Akt1 rs2494739 increased the risk of neurological toxicity. The top three loci were rs4558508, rs17431184, and rs1130233, which were attributed to an elevated risk of gastrointestinal toxicity. LACC patients who had heterozygous AG in Akt2 rs7259541 exhibited an obviously greater risk of hematological toxicity than those who had AA or GG genotypes. And the CT genotype for Akt1 rs2494739 and the CC genotype in PTEN rs926091 showed a tendency to increase the risk of suffering from hematological toxicity.

CONCLUSION

Akt2 rs7259541 and rs4558508, Akt1 rs2494739 and rs1130233, PTEN rs532678, rs17431184, and rs926091 polymorphisms are associated with different toxic effects during the chemotherapy treatment of LACC.

Advances in point-of-care genetic testing for personalized medicine applications

Breakthroughs within the fields of genomics and bioinformatics have enabled the identification of numerous genetic biomarkers that reflect an individual's disease susceptibility, disease progression, and therapy responsiveness. The personalized medicine paradigm capitalizes on these breakthroughs by utilizing an individual's genetic profile to guide treatment selection, dosing, and preventative care. However, integration of personalized medicine into routine clinical practice has been limited-in part-by a dearth of widely deployable, timely, and cost-effective genetic analysis tools. Fortunately, the last several decades have been characterized by tremendous progress with respect to the development of molecular point-of-care tests (POCTs). Advances in microfluidic technologies, accompanied by improvements and innovations in amplification methods, have opened new doors to health monitoring at the point-of-care. While many of these technologies were developed with rapid infectious disease diagnostics in mind, they are well-suited for deployment as genetic testing platforms for personalized medicine applications. In the coming years, we expect that these innovations in molecular POCT technology will play a critical role in enabling widespread adoption of personalized medicine methods. In this work, we review the current and emerging generations of point-of-care molecular testing platforms and assess their applicability toward accelerating the personalized medicine paradigm.

Molecular Tools to Infer Resistance-Breaking Abilities of Rice Yellow Mottle Virus Isolates

Rice yellow mottle virus (RYMV) is a major biotic constraint to rice cultivation in Africa. RYMV shows a high genetic diversity. Viral lineages were defined according to the coat protein (CP) phylogeny. Varietal selection is considered as the most efficient way to manage RYMV. Sources of high resistance were identified mostly in accessions of the African rice species, Oryza glaberrima. Emergence of resistance-breaking (RB) genotypes was observed in controlled conditions. The RB ability was highly contrasted, depending on the resistance sources and on the RYMV lineages. A molecular marker linked to the adaptation to susceptible and resistant O. glaberrima was identified in the viral protein genome-linked (VPg). By contrast, as no molecular method was available to identify the hypervirulent lineage able to overcome all known resistance sources, plant inoculation assays were still required. Here, we designed specific RT-PCR primers to infer the RB abilities of RYMV isolates without greenhouse experiments or sequencing steps. These primers were tested and validated on 52 isolates, representative of RYMV genetic diversity. The molecular tools described in this study will contribute to optimizing the deployment strategy of resistant lines, considering the RYMV lineages identified in fields and their potential adaptability.

The essential role of GSTP1 I105V polymorphism in the prediction of CDNB metabolism and toxicity: In silico and in vitro insights

Humans are continuously exposed to toxic chemicals such as nitro-chlorobenzene (CDNB) through occupation, water, and even the air we breathe. Due to the severe toxicity caused by the high electrophilicity of CDNB, occupational and environmental exposure to CDNB can produce toxic effects that ultimately lead to cell damage. CDNB can be eliminated from organisms by binding to GSH, the catalytic product of glutathione S-transferase P1 (GSTP1). Therefore, GSTP1 plays an important role in the detoxification of CDNB. However, subtle variations in GSTP1 can result in single nucleotide polymorphisms (SNPs). Indeed, the correlation between the clinical outcome of the disease and certain genotypes of GSTP1 has been extensively studied, however, their impact on the metabolic detoxification of toxicants such as CDNB remains to be elucidated. Among the various SNPs of GSTP1, I105V has a significant effect on the catalytic activity of GSTP1. In this paper, a GSTP1 I105V polymorphism model was successfully established, and its effect on CDNB metabolism and toxicity was studied by computer analysis including molecular docking and molecular dynamics simulation. The result demonstrated that the binding capacity of CDNB decreases with the I105V mutation of GSTP1(p < 0.001), indicating the changes in its detoxification efficacy in CDNB-induced cell damage. Organisms expressing GSTP1 V105 are more susceptible to cell damage caused by CDNB than individuals expressing GSTP1 I105 (p < 0.001). In sum, the data in this study provide prospective insights into the mechanism and capacity of CDNB detoxification in the GSTP1 allele, extending the CDNB-mediated toxicological profile. In addition, the heterogeneity of the GSTP1 allele should be included in toxicological studies of individuals exposed to CDNB.

A duplex tetra-primer ARMS-PCR assay to discriminate three species of the Schistosoma haematobium group: Schistosoma curassoni, S. bovis, S. haematobium and their hybrids

BACKGROUND

The use of applications involving single nucleotide polymorphisms (SNPs) has greatly increased since the beginning of the 2000s, with the number of associated techniques expanding rapidly in the field of molecular research. Tetra-primer amplification refractory mutation system-PCR (T-ARMS-PCR) is one such technique involving SNP genotyping. It has the advantage of amplifying multiple alleles in a single reaction with the inclusion of an internal molecular control. We report here the development of a rapid, reliable and cost-effective duplex T-ARMS-PCR assay to distinguish between three Schistosoma species, namely Schistosoma haematobium (human parasite), Schistosoma bovis and Schistosoma curassoni (animal parasites), and their hybrids. This technique will facilitate studies of population genetics and the evolution of introgression events.

METHODS

During the development of the technique we focused on one of the five inter-species internal transcribed spacer (ITS) SNPs and one of the inter-species 18S SNPs which, when combined, discriminate between all three Schistosoma species and their hybrid forms. We designed T-ARMS-PCR primers to amplify amplicons of specific lengths for each species, which in turn can then be visualized on an electrophoresis gel. This was further tested using laboratory and field-collected adult worms and field-collected larval stages (miracidia) from Spain, Egypt, Mali, Senegal and Ivory Coast. The combined duplex T-ARMS-PCR and ITS + 18S primer set was then used to differentiate the three species in a single reaction.

RESULTS

The T-ARMS-PCR assay was able to detect DNA from both species being analysed at the maximum and minimum levels in the DNA ratios (95/5) tested. The duplex T-ARMS-PCR assay was also able to detect all hybrids tested and was validated by sequencing the ITS and the 18S amplicons of 148 of the field samples included in the study.

CONCLUSIONS

The duplex tetra-primer ARMS-PCR assay described here can be applied to differentiate between Schistosoma species and their hybrid forms that infect humans and animals, thereby providing a method to investigate the epidemiology of these species in endemic areas. The addition of several markers in a single reaction saves considerable time and is of long-standing interest for investigating genetic populations.

Functional exploration of SNP mutations in HIF2αb gene correlated with hypoxia tolerance in blunt snout bream (Megalobrama amblycephala)

Blunt snout bream (Megalobrama amblycephala) is sensitive to hypoxia environment. Hypoxia-inducible factor (HIF) is the most critical factor in the HIF pathway, which strictly regulates the hypoxia stress process of fish. In this study, we found six hifα genes in blunt snout bream that demonstrated different expressions under hypoxia conditions. In HEK293T cells, all six hifαs were detected to activate the HRE region by luciferase reporter assay. More importantly, we identified two linkage-disequilibrium SNP sites at exon 203 and 752 of the hif2αb gene in blunt snout bream. Haplotype II (A²⁰³A⁷⁵²) and its homozygous diplotype II (A²⁰³A²⁰³A⁷⁵²A⁷⁵²) appeared frequently in a selected strain of blunt snout bream with hypoxia tolerance. Diplotype II has a lower oxygen tension threshold for loss of equilibrium (LOE_crit) over a similar range of temperatures. Moreover, its erythrocyte number increased significantly (p < 0.05) than those in diplotype I and diplotype III strains at 48 h of hypoxia. The enzymes related with hypoxia tolerant traits, i.e., reduced glutathione, superoxide dismutase, and catalase, were also significantly (p < 0.05) induced in diplotype II than in diplotype I or III. In addition, the expression of epo in the liver of diplotype II was significantly (p < 0.01) higher than that in the diplotype I or III strains at 48 h of hypoxia. Taken together, our results found that the hypoxia-tolerant-related diplotype II of hif2αb has the potential to be used as a molecular marker in future genetic breeding of hypoxia-tolerant strain.

Association of the ADORA2A receptor and CD73 polymorphisms with epilepsy

Single-nucleotide polymorphisms are connected with the risk of epilepsy on occurrence, progress, and the individual response to drugs. Progress in genomic technology is exposing the complex genetic architecture of epilepsy. Compelling evidence has demonstrated that purines and adenosine are key mediators in the epileptic process. Our previous study found the interconnection of P2Y12 receptor single-nucleotide polymorphisms and epilepsy. However, little is known about the interaction between the purine nucleoside A2A receptor and rate-limiting enzyme ecto-5′-nucleotidase/CD73 and epilepsy from the genetic polymorphism aspect. The aim of the study is to evaluate the impact of A2AR and CD73 polymorphisms on epilepsy cases. The study group encompassed 181 patients with epilepsy and 55 healthy volunteers. A significant correlation was confirmed between CD73 rs4431401 and epilepsy (p &lt; 0.001), with TT genotype frequency being higher and C allele being lower among epilepsy patients in comparison with healthy individuals, indicating that the presence of the TT genotype is related to an increased risk of epilepsy (OR = 2.742, p = 0.006) while carriers of the C allele demonstrated a decreased risk of epilepsy (OR = 0.304, p &lt; 0.001). According to analysis based on gender, the allele and genotype of rs4431401 in CD73 were associated with both male and female cases (p &lt; 0.0001, p = 0.026, respectively). Of note, we found that A2AR genetic variants rs2267076 T&gt;C (p = 0.031), rs2298383 C&gt;T (p = 0.045), rs4822492 T&gt;G (p = 0.034), and rs4822489 T&gt;G (p = 0.029) were only associated with epilepsy in female subjects instead of male. It is evident that the TT genotype and T allele of rs4431401 in CD73 were genetic risk factors for epilepsy, whereas rs2267076, rs2298383, rs4822492, and rs4822489 polymorphisms of the A2AR were mainly associated with female subjects.

Discovery of SNP Molecular Markers and Candidate Genes Associated with Sacbrood Virus Resistance in Apis cerana cerana Larvae by Whole-Genome Resequencing

Sacbrood virus (SBV) is a significant problem that impedes brood development in both eastern and western honeybees. Whole-genome sequencing has become an important tool in researching population genetic variations. Numerous studies have been conducted using multiple techniques to suppress SBV infection in honeybees, but the genetic markers and molecular mechanisms underlying SBV resistance have not been identified. To explore single nucleotide polymorphisms (SNPs), insertions, deletions (Indels), and genes at the DNA level related to SBV resistance, we conducted whole-genome resequencing on 90 Apis cerana cerana larvae raised in vitro and challenged with SBV. After filtering, a total of 337.47 gigabytes of clean data and 31,000,613 high-quality SNP loci were detected in three populations. We used ten databases to annotate 9359 predicted genes. By combining population differentiation index (FST) and nucleotide polymorphisms (π), we examined genome variants between resistant (R) and susceptible (S) larvae, focusing on site integrity (INT < 0.5) and minor allele frequency (MAF < 0.05). A selective sweep analysis with the top 1% and top 5% was used to identify significant regions. Two SNPs on the 15th chromosome with GenBank KZ288474.1_322717 (Guanine > Cytosine) and KZ288479.1_95621 (Cytosine > Thiamine) were found to be significantly associated with SBV resistance based on their associated allele frequencies after SNP validation. Each SNP was authenticated in 926 and 1022 samples, respectively. The enrichment and functional annotation pathways from significantly predicted genes to SBV resistance revealed immune response processes, signal transduction mechanisms, endocytosis, peroxisomes, phagosomes, and regulation of autophagy, which may be significant in SBV resistance. This study presents novel and useful SNP molecular markers that can be utilized as assisted molecular markers to select honeybees resistant to SBV for breeding and that can be used as a biocontrol technique to protect honeybees from SBV.