Construction and validation of somatic mutation-derived long noncoding RNAs signatures of genomic instability to predict prognosis of hepatocellular carcinoma

BACKGROUND Long non-coding RNAs(LncRNAs)have been found to be a potential prognostic factor for cancers,including hepatocellular carcinoma(HCC).Some LncRNAs have been confirmed as potential indicators to quantify genomic instability(GI).Nevertheless,GI-LncRNAs remain largely unexplored.This study established a GI-derived LncRNA signature(GILncSig)that can predict the prognosis of HCC patients.AIM To establish a GILncSig that can predict the prognosis of HCC patients.METHODS Identification of GI-LncRNAs was conducted by combining LncRNA expression and somatic mutation profiles.The GI-LncRNAs were then analyzed for functional enrichment.The GILncSig was established in the training set by Cox regression analysis,and its predictive ability was verified in the testing set and TCGA set.In addition,we explored the effects of the GILncSig and TP53 on prognosis.RESULTS A total of 88 GI-LncRNAs were found,and functional enrichment analysis showed that their functions were mainly involved in small molecule metabolism and GI.The GILncSig was constructed by 5 LncRNAs(miR210HG,AC016735.1,AC116351.1,AC010643.1,LUCAT1).In the training set,the prognosis of high-risk patients was significantly worse than that of low-risk patients,and similar results were verified in the testing set and TCGA set.Multivariate Cox regression analysis and stratified analysis confirmed that the GILncSig could be used as an independent prognostic factor.Receiver operating characteristic curve analysis of the GILncSig showed that the area under the curve(0.773)was higher than the two LncRNA signatures published recently.Furthermore,the GILncSig may have a better predictive performance than TP53 mutation status alone.CONCLUSION We established a GILncSig that can predict the prognosis of HCC patients,which will help to guide prognostic evaluation and treatment decisions.

Advancing prognostic understanding in hepatocellular carcinoma through the integration of genomic instability and lncRNA signatures: GILncSig model

The recently published study by Duan et al introduces a promising method that combines genomic instability and long non-coding RNAs to improve the prognostic evaluation of hepatocellular carcinoma(HCC),a deadly cancer associated with considerable morbidity and mortality.This editorial aims to analyze the methodology,key findings,and broader implications of the study within the fields of gastroenterology and oncological surgery,highlighting the shift towards precision medicine in the management of HCC.

Clinical application value of long non-coding RNAs signatures of genomic instability in predicting prognosis of hepatocellular carcinoma

Hepatocellular carcinoma(HCC)presents challenges due to its high recurrence and metastasis rates and poor prognosis.While current clinical diagnostic and prognostic indicators exist,their accuracy remains imperfect due to their biol-ogical complexity.Therefore,there is a quest to identify improved biomarkers for HCC diagnosis and prognosis.By combining long non-coding RNA(lncRNA)expression and somatic mutations,Duan et al identified five representative lncRNAs from 88 lncRNAs related to genomic instability(GI),forming a GI-derived lncRNA signature(LncSig).This signature outperforms previously re-ported LncSig and TP53 mutations in predicting HCC prognosis.In this editorial,we comprehensively evaluate the clinical application value of such prognostic evaluation model based on sequencing technology in terms of cost,time,and practicability.Additionally,we provide an overview of various prognostic models for HCC,aiding in a comprehensive understanding of research progress in pro-gnostic evaluation methods.

Urgent need for prognostic markers for hepatocellular carcinoma in the light of genomic instability and non-coding RNA signatures

In this editorial,we comment on an original article by Duan et al.Despite ad-vancements in the diagnosis and treatment of hepatocellular carcinoma(HCC),the identification of suitable prognostic factors remains challenging.In their paper,Duan et al identified long non-coding RNAs(LncRNAs)to quantify ge-nomic instability(GI)by combining LncRNA expression and somatic mutation profiles.They confirmed that the GI-derived LncRNA signature(GI-LncSig)could be an independent prognostic factor with the area under the curve of 0.773.Fur-thermore,the authors stated that GI-LncSig may have a better predictive perfor-mance than TP53 mutation status alone.However,studies exploring genetic markers for predicting the prognosis of HCC are crucial for identifying thera-peutic targets and enhancing diagnostic and treatment strategies to mitigate the global burden of liver cancer.

Genomic Instability Is a Mechanism for Diminished Male Fertility Following Chronic Dichlorvos Exposure

Background and Objectives: Chronic low-dose exposure to dichlorvos occurs in communities in Africa where the substance is used indiscriminately for a variety of purposes. This experiment used an animal model to evaluate genomic instability induced by this pattern of chronic exposure and its relationship with some measures of fertility in males. Methods: Seventy-five male Rattus norvegicus rats obtained for this experiment, were randomly allotted into five groups. Dichlorvos was given by oral gavage at doses of 0.28 mg/kg, 0.56 mg/kg and, 1.68 mg/kg, respectively, to three of the groups, on alternate days for 50 weeks. The remaining two groups received plain drinking water and cyclophosphamide as negative and positive controls, respectively. Samples were collected at 17, 34, and 50 weeks. Sperm count, sperm morphology and serum levels of follicle-stimulating hormone, luteinizing hormone, dihydrotestosterone, oestrogen and progesterone were determined. Furthermore, the frequency of micronucleated polychromatic erythrocytes was determined in bone marrow cells obtained from the femur. Results: The mean ranks of micronuclei frequency had an increasing trend. The frequency of micronucleated polychromatic erythrocytes (MnPCE) had a significant negative correlation with oestrogen (rs = -0.47, p = 0.00, n = 50), follicle-stimulating hormone (rs = -0.41, p = 0.00, n = 50) and progesterone (rs = -0.37, p = 0.01, n = 50) serum levels. A positive monotonic relationship also existed between micronuclei frequency and those of tubular necrosis, tubular vacuolation, and residual bodies. A positive significant moderate correlation was found between MnPCE and the proportion of immotile sperms (rs = 0.41, p = 0.00, n = 50). Conclusion: The nature of the correlations between micronuclei frequency and the proportion of immotile sperms, adverse histological changes and serum hormone levels found in this study suggest genomic instability as the possible mechanism for diminished fertility in males chronically exposed to dichlorvos.

The evolution of cancer genomic medicine in Japan and the role of the National Cancer Center Japan

The journey to implement cancer genomic medicine(CGM)in oncology practice began in the 1980s,which is considered the dawn of genetic and genomic cancer research.At the time,a variety of activating oncogenic alterations and their functional significance were unveiled in cancer cells,which led to the development of molecular targeted therapies in the 2000s and beyond.Although CGM is still a relatively new discipline and it is difficult to predict to what extent CGM will benefit the diverse pool of cancer patients,the National Cancer Center(NCC)of Japan has already contributed considerably to CGM advancement for the conquest of cancer.Looking back at these past achievements of the NCC,we predict that the future of CGM will involve the following:1)A biobank of paired cancerous and non-cancerous tissues and cells from various cancer types and stages will be developed.The quantity and quality of these samples will be compatible with omics analyses.All biobank samples will be linked to longitudinal clinical information.2)New technologies,such as whole-genome sequencing and artificial intelligence,will be introduced and new bioresources for functional and pharmacologic analyses(e.g.,a patient-derived xenograft library)will be systematically deployed.3)Fast and bidirectional translational research(bench-to-bedside and bedside-to-bench)performed by basic researchers and clinical investigators,preferably working alongside each other at the same institution,will be implemented;4)Close collaborations between academia,industry,regulatory bodies,and funding agencies will be established.5)There will be an investment in the other branch of CGM,personalized preventive medicine,based on the individual's genetic predisposition to cancer.

Conservation genomic investigation of an endangered conifer,Thuja sutchuenensis,reveals low genetic diversity but also low genetic load

Endangered species generally have small populations with low genetic diversity and a high genetic load.Thuja sutchuenensis is an endangered conifer endemic to southwestern China.It was once considered extinct in the wild,but in 1999 was rediscovered.However,little is known about its genetic load.We collected 67 individuals from five wild,isolated T.sutchuenensis populations,and used 636,151 SNPs to analyze the level of genetic diversity and genetic load in T.sutchuenensis to delineate the conservation units of T.sutchuenensis,based on whole transcriptome sequencing data,as well as target capture sequencing data.We found that populations of T.sutchuenensis could be divided into three groups.These groups had low levels genetic diversity and were moderately genetically differentiated.Our findings also indicate that T.sutchuenensis suffered two severe bottlenecks around the Last Glaciation Period and Last Glacial Maximum.Among Thuja species,T.sutchuenensis presented the lowest genetic load and hence might have purged deleterious mutations efficiently through purifying selection.However,distribution of fitness effects analysis indicated a high extinction risk for T.sutchuenensis.Multiple lines of evidence identified three management units for T.sutchuenensis.Although T.sutchuenensis possesses a low genetic load,low genetic diversity,suboptimal fitness,and anthropogenic pressures all present an extinction risk for this rare conifer.This might also hold true for many endangered plant species in the mountains all over the world.

Gouge stability controlled by temperature elevation and obsidian addition in basaltic faults and implications for moonquakes

Basalt is a major component of the earth and moon crust.Mineral composition and temperature influence frictional instability and thus the potential for seismicity on basaltic faults.We performed velocitystepping shear experiments on basalt gouges at a confining pressure of 100 MPa,temperatures in the range of 100-400℃ and with varied obsidian mass fractions of 0-100%under wet/dry conditions to investigate the frictional strength and stability of basaltic faults.We observe a transition from velocity-neutral to velocity-weakening behaviors with increasing obsidian content.The frictional stability response of the mixed obsidian/basalt gouges is characterized by a transition from velocitystrengthening to velocity-weakening at 200℃ and another transition to velocity-strengthening at temperatures>300℃.Conversely,frictional strengths of the obsidian-bearing gouges are insensitive to temperature and wet/dry conditions.These results suggest that obsidian content dominates the potential seismic response of basaltic faults with the effect of temperature controlling the range of seismogenic depths.Thus,shallow moonquakes tend to occur in the lower lunar crust due to the corresponding anticipated higher glass content and a projected temperature range conducive to velocity-weakening behavior.These observations contribute to a better understanding of the nucleation mechanism of shallow seismicity in basaltic faults.

Mechanical Modeling and Analysis of Stability Deterioration of Production Well During Marine Hydrate Depressurization Production

Different from oil and gas production,hydrate reservoirs are shallow and unconsolidated,whose mechanical properties deteriorate with hydrate decomposition.Therefore,the formations will undergo significant subsidence during depressurization,which will destroy the original force state of the production well.However,existing research on the stability of oil and gas production wells assumes the formation to be stable,and lacks consideration of the force exerted on the hydrate production well by formation subsidence caused by hydrate decomposition during production.To fill this gap,this paper proposes an analytical method for the dynamic evolution of the stability of hydrate production well considering the effects of hydrate decomposition.Based on the mechanical model of the production well,the basis for stability analysis has been proposed.A multi-field coupling model of the force state of the production well considering the effect of hydrate decomposition and formation subsidence is established,and a solver is developed.The analytical approach is verified by its good agreement with the results from the numerical method.A case study found that the decomposition of hydrate will increase the pulling-down force and reduce the supporting force,which is the main reason for the stability deterioration.The higher the initial hydrate saturation,the larger the reservoir thickness,and the lower the production pressure,the worse the stability or even instability.This work can provide a theoretical reference for the stability maintaining of the production well.

Influence of variable viscosity and double diffusion on the convective stability of a nanofluid flow in an inclined porous channel

The influence of variable viscosity and double diffusion on the convective stability of a nanofluid flow in an inclined porous channel is investigated.The DarcyBrinkman model is used to characterize the fluid flow dynamics in porous materials.The analytical solutions are obtained for the unidirectional and completely developed flow.Based on a normal mode analysis,the generalized eigenvalue problem under a perturbed state is solved.The eigenvalue problem is then solved by the spectral method.Finally,the critical Rayleigh number with the corresponding wavenumber is evaluated at the assigned values of the other flow-governing parameters.The results show that increasing the Darcy number,the Lewis number,the Dufour parameter,or the Soret parameter increases the stability of the system,whereas increasing the inclination angle of the channel destabilizes the flow.Besides,the flow is the most unstable when the channel is vertically oriented.

Probabilistic analysis of tunnel face seismic stability in layered rock masses using Polynomial Chaos Kriging metamodel

Face stability is an essential issue in tunnel design and construction.Layered rock masses are typical and ubiquitous;uncertainties in rock properties always exist.In view of this,a comprehensive method,which combines the Upper bound Limit analysis of Tunnel face stability,the Polynomial Chaos Kriging,the Monte-Carlo Simulation and Analysis of Covariance method(ULT-PCK-MA),is proposed to investigate the seismic stability of tunnel faces.A two-dimensional analytical model of ULT is developed to evaluate the virtual support force based on the upper bound limit analysis.An efficient probabilistic analysis method PCK-MA based on the adaptive Polynomial Chaos Kriging metamodel is then implemented to investigate the parameter uncertainty effects.Ten input parameters,including geological strength indices,uniaxial compressive strengths and constants for three rock formations,and the horizontal seismic coefficients,are treated as random variables.The effects of these parameter uncertainties on the failure probability and sensitivity indices are discussed.In addition,the effects of weak layer position,the middle layer thickness and quality,the tunnel diameter,the parameters correlation,and the seismic loadings are investigated,respectively.The results show that the layer distributions significantly influence the tunnel face probabilistic stability,particularly when the weak rock is present in the bottom layer.The efficiency of the proposed ULT-PCK-MA is validated,which is expected to facilitate the engineering design and construction.

Evaluation of slope stability through rock mass classification and kinematic analysis of some major slopes along NH-1A from Ramban to Banihal, North Western Himalayas

The network of Himalayan roadways and highways connects some remote regions of valleys or hill slopes,which is vital for India’s socio-economic growth.Due to natural and artificial factors,frequency of slope instabilities along the networks has been increasing over last few decades.Assessment of stability of natural and artificial slopes due to construction of these connecting road networks is significant in safely executing these roads throughout the year.Several rock mass classification methods are generally used to assess the strength and deformability of rock mass.This study assesses slope stability along the NH-1A of Ramban district of North Western Himalayas.Various structurally and non-structurally controlled rock mass classification systems have been applied to assess the stability conditions of 14 slopes.For evaluating the stability of these slopes,kinematic analysis was performed along with geological strength index(GSI),rock mass rating(RMR),continuous slope mass rating(CoSMR),slope mass rating(SMR),and Q-slope in the present study.The SMR gives three slopes as completely unstable while CoSMR suggests four slopes as completely unstable.The stability of all slopes was also analyzed using a design chart under dynamic and static conditions by slope stability rating(SSR)for the factor of safety(FoS)of 1.2 and 1 respectively.Q-slope with probability of failure(PoF)1%gives two slopes as stable slopes.Stable slope angle has been determined based on the Q-slope safe angle equation and SSR design chart based on the FoS.The value ranges given by different empirical classifications were RMR(37-74),GSI(27.3-58.5),SMR(11-59),and CoSMR(3.39-74.56).Good relationship was found among RMR&SSR and RMR&GSI with correlation coefficient(R 2)value of 0.815 and 0.6866,respectively.Lastly,a comparative stability of all these slopes based on the above classification has been performed to identify the most critical slope along this road.

Insights into ionic association boosting water oxidation activity and dynamic stability

There have been reports about Fe ions boosting oxygen evolution reaction(OER)activity of Ni-based catalysts in alkaline conditions,while the origin and reason for the enhancement remains elusive.Herein,we attempt to identify the activity improvement and discover that Ni sites act as a host to attract Fe(Ⅲ)to form Fe(Ni)(Ⅲ)binary centres,which serve as the dynamic sites to promote OER activity and stability by cyclical formation of intermediates(Fe(Ⅲ)→Fe(Ni)(Ⅲ)→Fe(Ni)-OH→Fe(Ni)-O→Fe(Ni)OOH→Fe(Ⅲ))at the electrode/electrolyte interface to emit O_(2).Additionally,some ions(Co(Ⅱ),Ni(Ⅱ),and Cr(Ⅲ))can also be the active sites to catalyze the OER process on a variety of electrodes.The Fe(Ⅲ)-catalyzed overall water-splitting electrolyzer comprising bare Ni foam as the anode and Pt/Ni-Mo as the cathode demonstrates robust stability for 1600 h at 1000 mA cm^(-2)@~1.75 V.The results provide insights into the ioncatalyzed effects boosting OER performance.

Chromosome-level genome and population genomics of the intermediate horseshoe bat(Rhinolophus affinis)reveal the molecular basis of virus tolerance in Rhinolophus and echolocation call frequency variation

Horseshoe bats(genus Rhinolophus,family Rhinolophidae)represent an important group within chiropteran phylogeny due to their distinctive traits,including constant high-frequency echolocation,rapid karyotype evolution,and unique immune system.Advances in evolutionary biology,supported by high-quality reference genomes and comprehensive whole-genome data,have significantly enhanced our understanding of species origins,speciation mechanisms,adaptive evolutionary processes,and phenotypic diversity.However,genomic research and understanding of the evolutionary patterns of Rhinolophus are severely constrained by limited data,with only a single published genome of R.ferrumequinum currently available.In this study,we constructed a high-quality chromosome-level reference genome for the intermediate horseshoe bat(R.affinis).Comparative genomic analyses revealed potential genetic characteristics associated with virus tolerance in Rhinolophidae.Notably,we observed expansions in several immune-related gene families and identified various genes functionally associated with the SARS-CoV-2 signaling pathway,DNA repair,and apoptosis,which displayed signs of rapid evolution.In addition,we observed an expansion of the major histocompatibility complex class II(MHC-II)region and a higher copy number of the HLA-DQB2 gene in horseshoe bats compared to other chiropteran species.Based on whole-genome resequencing and population genomic analyses,we identified multiple candidate loci(e.g.,GLI3)associated with variations in echolocation call frequency across R.affinis subspecies.This research not only expands our understanding of the genetic characteristics of the Rhinolophus genus but also establishes a valuable foundation for future research.

Genomic Profile of SARS-COV-2 Associated with COVID-19 Outbreaks in N’Djamena, Chad

Background: SARS-CoV-2 has circulated worldwide with dramatic consequences. In Chad, we have no data reported of variants. The aim of this study was to identify the SARS-CoV-2 variants that circulated during the epidemic from 2020 to 2021. Methods: This is a cross-sectional, descriptive study carried out between 2020 and 2021. Samples from patients with suspected COVID-19 were tested in five laboratories in N’Djamena. One hundred quality samples of the positives were sequenced in Kinshasa using Oxford nanopore technologies minion and the Protocol Midnight SARS-CoV2. Data were processed using Excel version 16 software. Results: Of the 100 samples sequenced, 77 (77%) produced sequences, 23 (23%) did not. The genomic profiles were wild-type Wuhan and minor mutations (19A, 19B (A), 20A (B.1, B.2), 20B (AV.1), 20D (B.1.1.1 /C.36), 20C), variant of concern Alpha (20I), variant of concern Delta (21A/J), variant of interest Eta (21D), variant of concern Omicron (21K) and unclassified variant under surveillance (B.1.640). Of these variants, the maximums were detected in patients aged 26 - 35 with 30.26% and 25.26% in 36 - 45. However, 24.67% were in travelers and 75.32% in residents, 35.06% in those vaccinated against COVID-19 and 62.33% in non-vaccinates. The estimated case-fatality rate was 2.44% (107/4374). Conclusion: This work has provided preliminary data on COVID-19 and SARS-CoV-2 variants circulating during the 2020-2021 epidemics in Chad.

Effect and mechanism of reductive polyaniline on the stability of nitrocellulose

The search for new green and efficient stabilizers is of great importance for the stabilization of nitrocellulose(NC). This is due to the shortcomings of traditional stabilizers, such as high toxicity. In this study, reduced polyaniline(r-PANI), which has a similar functional structure to diphenylamine(DPA) but is non-toxic, was prepared from PANI based on the action with N_(2)H_(4) and NH_(3)-H_(2)O, and used for the first time as a potential stabilizer for NC. XPS, FTIR, Raman, and SEM were used to characterize the reduced chemical structure and surface morphology of r-PANI. In addition, the effect of r-PANI on the stabilization of NC was characterized using DSC, VST, isothermal TG, and MMC. Thermal weight loss was reduced by 83% and 68% and gas pressure release by 75% and 49% compared to pure NC and NC&3%DPA, respectively.FTIR and XPS were used to characterize the structural changes of r-PANI before and after reaction with NO_(2). The 1535 cm^(-1) and 1341 cm^(-1) of the FTIR and the 404.98 eV and 406.05 eV of the XPS showed that the -NO_(2) was generated by the absorption of NO_(2). Furthermore, the quantum chemical calculation showed that NO_(2) was directly immobilized on r-PANI by forming -NO_(2) in the neighboring position of the benzene ring.

Exploring the Unknown: The Application and Prospects of Artificial Intelligence in Genomics and Bioinformatics

This review comprehensively explores the core application of artificial intelligence (AI) in the fields of genomics and bioinformatics, and deeply analyzes how it leads the innovative progress of science. In the cutting-edge fields of genomics and bioinformatics, the application of AI is propelling a deeper understanding of complex genetic mechanisms and the development of innovative therapeutic approaches. The precision of AI in genomic sequence analysis, coupled with breakthroughs in precise gene editing, such as AI-designed gene editors, significantly enhances our comprehension of gene functions and disease associations . Moreover, AI’s capabilities in disease prediction, assessing individual disease risks through genomic data analysis, provide robust support for personalized medicine. AI applications extend beyond gene identification, gene expression pattern prediction, and genomic structural variant analysis, encompassing key areas such as epigenetics, multi-omics data integration, genetic disease diagnosis, evolutionary genomics, and non-coding RNA function prediction. Despite challenges including data privacy, algorithm transparency, and bioethical issues, the future of AI is expected to continue revolutionizing genomics and bioinformatics, ushering in a new era of personalized medicine and precision treatments.

基于COMPASS iStability的浮船坞稳性计算

为比对分段建模与整体建模工作量及稳性计算结果,选取某浮船坞,采用命令流方法,对坞墙无开口,做5分段建模和整体建模稳性计算,对坞墙有开口,做7分段建模和借助体过渡整体建模稳性计算,结果表明,无论坞墙有无开口,整体建模比分段建模节省约一半工作量,两种建模方式稳性计算精度相同,建模过程表明,命令流方法整体建模计算稳性,高效快捷。

Effects of connected automated vehicle on stability and energy consumption of heterogeneous traffic flow system

With the development of intelligent and interconnected traffic system,a convergence of traffic stream is anticipated in the foreseeable future,where both connected automated vehicle(CAV)and human driven vehicle(HDV)will coexist.In order to examine the effect of CAV on the overall stability and energy consumption of such a heterogeneous traffic system,we first take into account the interrelated perception of distance and speed by CAV to establish a macroscopic dynamic model through utilizing the full velocity difference(FVD)model.Subsequently,adopting the linear stability theory,we propose the linear stability condition for the model through using the small perturbation method,and the validity of the heterogeneous model is verified by comparing with the FVD model.Through nonlinear theoretical analysis,we further derive the KdV-Burgers equation,which captures the propagation characteristics of traffic density waves.Finally,by numerical simulation experiments through utilizing a macroscopic model of heterogeneous traffic flow,the effect of CAV permeability on the stability of density wave in heterogeneous traffic flow and the energy consumption of the traffic system is investigated.Subsequent analysis reveals emergent traffic phenomena.The experimental findings demonstrate that as CAV permeability increases,the ability to dampen the propagation of fluctuations in heterogeneous traffic flow gradually intensifies when giving system perturbation,leading to enhanced stability of the traffic system.Furthermore,higher initial traffic density renders the traffic system more susceptible to congestion,resulting in local clustering effect and stop-and-go traffic phenomenon.Remarkably,the total energy consumption of the heterogeneous traffic system exhibits a gradual decline with CAV permeability increasing.Further evidence has demonstrated the positive influence of CAV on heterogeneous traffic flow.This research contributes to providing theoretical guidance for future CAV applications,aiming to enhance urban road traffic efficiency and alleviate congestion.

PCR-HRM for Genomic Surveillance of SARS-CoV-2: A Variant Detection Tool in Côte d’Ivoire, West Africa

The rise of new viruses, like SARS-CoV-2 causing the COVID-19 outbreak, along with the return of antibiotic resistance in harmful bacteria, demands a swift and efficient reaction to safeguard the health and welfare of the global population. It is crucial to have effective measures for prevention, intervention, and monitoring in place to address these evolving and recurring risks, ensuring public health and international security. In countries with limited resources, utilizing recombinant mutation plasmid technology in conjunction with PCR-HRM could help differentiate the existence of novel variants. cDNA synthesis was carried out on 8 nasopharyngeal samples following viral RNA extraction. The P1 segment of the SARS-CoV-2 Spike S protein was amplified via conventional PCR. Subsequently, PCR products were ligated with the pGEM-T Easy vector to generate eight recombinant SARS-CoV-2 plasmids. Clones containing mutations were sequenced using Sanger sequencing and analyzed through PCR-HRM. The P1 segment of the S gene from SARS-CoV-2 was successfully amplified, resulting in 8 recombinant plasmids generated from the 231 bp fragment. PCR-HRM analysis of these recombinant plasmids differentiated three variations within the SARS-CoV-2 plasmid population, each displaying distinct melting temperatures. Sanger sequencing identified mutations A112C, G113T, A114G, G214T, and G216C on the P1 segment, validating the PCR-HRM findings of the variations. These mutations led to the detection of L452R or L452M and F486V protein mutations within the protein sequence of the Omicron variant of SARS-CoV-2. In summary, PCR-HRM is a vital and affordable tool for distinguishing SARS-CoV-2 variants utilizing recombinant plasmids as controls.