An efficient method for constructing a random insertional mutant library for forward genetics in Nannochloropsis oceanica

Insertional mutation,phenotypic evaluation,and mutated gene cloning are widely used to clone genes from scratch.Exogenous genes can be integrated into the genome during non-homologous end joining(NHEJ)of the double-strand breaks of DNA,causing insertional mutation.The random insertional mutant library constructed using this method has become a method of forward genetics for gene cloning.However,the establishment of a random insertional mutant library requires a high transformation efficiency of exogenous genes.Many microalgal species show a low transformation efficiency,making constructing random insertional mutant libraries difficult.In this study,we established a highly efficient transformation method for constructing a random insertional mutant library of Nannochloropsis oceanica,and tentatively tried to isolate its genes to prove the feasibility of the method.A gene that may control the growth rate and cell size was identified.This method will facilitate the genetic studies of N.oceanica,which should also be a reference for other microalgal species.

Population genomic data reveal low genetic diversity,divergence and local adaptation among threatened Reeves's Pheasant(Syrmaticus reevesii)

Population genomic data could provide valuable information for conservation efforts;however,limited studies have been conducted to investigate the genetic status of threatened pheasants.Reeves’s Pheasant(Syrmaticus reevesii)is facing population decline,attributed to increases in habitat loss.There is a knowledge gap in understanding the genomic status and genetic basis underlying the local adaptation of this threatened bird.Here,we used population genomic data to assess population structure,genetic diversity,inbreeding patterns,and genetic divergence.Furthermore,we identified candidate genes linked with adaptation across the current distribution of Reeves’s Pheasant.The present study assembled the first de novo genome sequence of Reeves’s Pheasant and annotated 19,458 genes.We also sequenced 30 individuals from three populations(Dabie Mountain,Shennongjia,Qinling Mountain)and found that there was clear population structure among those populations.By comparing with other threatened species,we found that Reeves’s Pheasants have low genetic diversity.Runs of homozygosity suggest that the Shennongjia population has experienced serious inbreeding.The demographic history results indicated that three populations experienced several declines during the glacial period.Local adaptative analysis among the populations identified 241 candidate genes under directional selection.They are involved in a large variety of processes,including the immune response and pigmentation.Our results suggest that the three populations should be considered as three different conservation units.The current study provides genetic evidence for conserving the threatened Reeves’s Pheasant and provides genomic resources for global biodiversity management.

Mobile genetic elements facilitate the transmission of antibiotic resistance genes in multidrug-resistant Enterobacteriaceae from duck farms

Multidrug-resistant(MDR)Enterobacteriaceae critically threaten duck farming and public health.The phenotypes,genotypes,and associated mobile genetic elements(MGEs)of MDR Enterobacteriaceae isolated from 6 duck farms in Zhejiang Province,China,were investigated.A total of 215 isolates were identified as Escherichia coli(64.65%),Klebsiella pneumoniae(12.09%),Proteus mirabilis(10.23%),Salmonella(8.84%),and Enterobacter cloacae(4.19%).Meanwhile,all isolates were resistant to at least two antibiotics.Most isolates carried tet(A)(85.12%),blaTEM(78.60%)and sul1(67.44%)resistance genes.Gene co-occurrence analysis showed that the resistance genes were associated with IS26 and integrons.A conjugative IncFII plasmid pSDM004 containing all the above MGEs was detected in Proteus mirabilis isolate SDM004.This isolate was resistant to 18 antibiotics and carried the blaNDM-5 gene.MGEs,especially plasmids,are the primary antibiotic resistance gene transmission route in duck farms.These findings provide a theoretical basis for the rational use of antibiotics in farms which are substantial for evaluating public health and food safety.

A Theory of Bio-Quantum Genetics

The physical mechanism of heredity or inheritance of genes is a quantum mechanical and/or quantum computational process. A theory of bio-quantum genetics is established in this paper. Principle of Bio-quantum Genetics is suggested. I propose and define the soft-genes of genetics controlling the processes of heredity or inheritance of genes. This research deals with the quantum mechanisms of Mendel plant heredity and family inheritance as examples of bio-quantum genetics, deepening our understanding of heredity or inheritance. I believe that more contributions will be made to promote researches of bio-quantum genetics or quantum biology at large.

The Practice and Exploration of Applying EBM to Bilingual Teaching of Medical Genetics at OSBCM

In the process of teaching medical genetics of undergraduate clinical medicine, the practice and exploration of applying EBM to the bilingual teaching of OSBCM medical genetics are carried out. Using CBL and PBL as the carrier can make up for the shortcomings of a single teaching mode, synthesize the advantages of multiple teaching modes. It starts from integrating the basic theoretical knowledge of medicine and clinical practice knowledge, improving students’ bilingual level of medical genetics, cultivating students’ literature retrieval ability, and promoting early clinical, multi-clinical and repeated clinical consciousness for medical students. Therefore, it is more conducive to cultivate students’ ability to learn independently, accurately analyze and solve problems, improve medical students’ clinical thinking ability and scientific research awareness, improve medical students’ ability of international communication, and lay a solid foundation for improving medical students’ future post competence, innovative spirit and lifelong learning ability.

Winter wheat yield improvement by genetic gain across different provinces in China

The replacement of winter wheat varieties has contributed significantly to yield improvement worldwide,with remarkable progress in China.Drawing on two sets of data,production yield from the National Bureau of Statistics of China and experimental yield from literature,this study aims to(1)illustrate the increasing patterns of production yield among different provinces from 1978 to 2018 in China,(2)explore the genetic gain in yield and yield relevant traits through the variety replacement based on experimental yield from 1937 to 2016 in China,and(3)compare the yield gap between experimental yield and production yield.The results show that both the production and experimental yields significantly increased along with the variety replacement.The national annual yield increase ratio for the production yield was 1.67%from 1978 to 2018,varying from 0.96%in Sichuan Province to 2.78%in Hebei Province;such ratio for the experimental yield was 1.13%from 1937 to 2016.The yield gap between experimental and production yields decreased from the 1970s to the 2010s.This study reveals significant increases in some yield components consequent to variety replacement,including thousand-grain weight,kernel number per spike,and grain number per square meter;however,no change is shown in spike number per square meter.The biomass and harvest index consistently and significantly increased,whereas the plant height decreased significantly.

A dual-RPA based lateral flow strip for sensitive,on-site detection of CP4-EPSPS and Cry1Ab/Ac genes in genetically modified crops

Traditional transgenic detection methods require high test conditions and struggle to be both sensitive and efficient.In this study,a one-tube dual recombinase polymerase amplification(RPA)reaction system for CP4-EPSPS and Cry1Ab/Ac was proposed and combined with a lateral flow immunochromatographic assay,named“Dual-RPA-LFD”,to visualize the dual detection of genetically modified(GM)crops.In which,the herbicide tolerance gene CP4-EPSPS and the insect resistance gene Cry1Ab/Ac were selected as targets taking into account the current status of the most widespread application of insect resistance and herbicide tolerance traits and their stacked traits.Gradient diluted plasmids,transgenic standards,and actual samples were used as templates to conduct sensitivity,specificity,and practicality assays,respectively.The constructed method achieved the visual detection of plasmid at levels as low as 100 copies,demonstrating its high sensitivity.In addition,good applicability to transgenic samples was observed,with no cross-interference between two test lines and no influence from other genes.In conclusion,this strategy achieved the expected purpose of simultaneous detection of the two popular targets in GM crops within 20 min at 37°C in a rapid,equipmentfree field manner,providing a new alternative for rapid screening for transgenic assays in the field.

LociScan,a tool for screening genetic marker combinations for plant variety discrimination

To reduce the cost and increase the efficiency of plant genetic marker fingerprinting for variety discrimination,it is desirable to identify the optimal marker combinations.We describe a marker combination screening model based on the genetic algorithm(GA)and implemented in a software tool,Loci Scan.Ratio-based variety discrimination power provided the largest optimization space among multiple fitness functions.Among GA parameters,an increase in population size and generation number enlarged optimization depth but also calculation workload.Exhaustive algorithm afforded the same optimization depth as GA but vastly increased calculation time.In comparison with two other software tools,Loci Scan accommodated missing data,reduced calculation time,and offered more fitness functions.In large datasets,the sample size of training data exerted the strongest influence on calculation time,whereas the marker size of training data showed no effect,and target marker number had limited effect on analysis speed.

MOALG: A Metaheuristic Hybrid of Multi-Objective Ant Lion Optimizer and Genetic Algorithm for Solving Design Problems

This study proposes a hybridization of two efficient algorithm’s Multi-objective Ant Lion Optimizer Algorithm(MOALO)which is a multi-objective enhanced version of the Ant Lion Optimizer Algorithm(ALO)and the Genetic Algorithm(GA).MOALO version has been employed to address those problems containing many objectives and an archive has been employed for retaining the non-dominated solutions.The uniqueness of the hybrid is that the operators like mutation and crossover of GA are employed in the archive to update the solutions and later those solutions go through the process of MOALO.A first-time hybrid of these algorithms is employed to solve multi-objective problems.The hybrid algorithm overcomes the limitation of ALO of getting caught in the local optimum and the requirement of more computational effort to converge GA.To evaluate the hybridized algorithm’s performance,a set of constrained,unconstrained test problems and engineering design problems were employed and compared with five well-known computational algorithms-MOALO,Multi-objective Crystal Structure Algorithm(MOCryStAl),Multi-objective Particle Swarm Optimization(MOPSO),Multi-objective Multiverse Optimization Algorithm(MOMVO),Multi-objective Salp Swarm Algorithm(MSSA).The outcomes of five performance metrics are statistically analyzed and the most efficient Pareto fronts comparison has been obtained.The proposed hybrid surpasses MOALO based on the results of hypervolume(HV),Spread,and Spacing.So primary objective of developing this hybrid approach has been achieved successfully.The proposed approach demonstrates superior performance on the test functions,showcasing robust convergence and comprehensive coverage that surpasses other existing algorithms.

Intelligent Design of High Strength and High Conductivity Copper Alloys Using Machine Learning Assisted by Genetic Algor

Metallic alloys for a given application are usually designed to achieve the desired properties by devising experimentsbased on experience, thermodynamic and kinetic principles, and various modeling and simulation exercises.However, the influence of process parameters and material properties is often non-linear and non-colligative. Inrecent years, machine learning (ML) has emerged as a promising tool to dealwith the complex interrelation betweencomposition, properties, and process parameters to facilitate accelerated discovery and development of new alloysand functionalities. In this study, we adopt an ML-based approach, coupled with genetic algorithm (GA) principles,to design novel copper alloys for achieving seemingly contradictory targets of high strength and high electricalconductivity. Initially, we establish a correlation between the alloy composition (binary to multi-component) andthe target properties, namely, electrical conductivity and mechanical strength. Catboost, an ML model coupledwith GA, was used for this task. The accuracy of the model was above 93.5%. Next, for obtaining the optimizedcompositions the outputs fromthe initial model were refined by combining the concepts of data augmentation andPareto front. Finally, the ultimate objective of predicting the target composition that would deliver the desired rangeof properties was achieved by developing an advancedMLmodel through data segregation and data augmentation.To examine the reliability of this model, results were rigorously compared and verified using several independentdata reported in the literature. This comparison substantiates that the results predicted by our model regarding thevariation of conductivity and evolution ofmicrostructure and mechanical properties with composition are in goodagreement with the reports published in the literature.

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.

Analysis on Genetic Diversity of 40 Flowering Cherry Cultivars and Construction of Molecular ID Based on SSR Markers

Studying on the genetic diversity and genetic relationship of flowering cherry cultivars is extremely important for germplasm conservation, cultivar identification and breeding. Flowering cherry is widely cultivated as an important woody ornamental plant in worldwide, especially Japan, China. However, owning to the morphological similarity, many cultivars are distinguished hardly in non-flowering season. Here, we evaluated the genetic diversity and genetic relationship of 40 flowering cherry cultivars, which are mainly cultivated in China. We selected 13 polymorphicprimers to amplify to allele fragments with fluorescent-labeled capillary electrophoresis technology. The population structure analysis results show that these cultivars could be divided into 4 subpopulations. At the population level, Na and Ne were 6.062, 4.326, respectively. Ho and He were 0.458 and 0.670, respectively. The Shannon’s information index (I) was 1.417. The Pop3, which originated from P. serrulata, had the highest Ho, He, and I among the 4 subpopulations. AMOVA showed that only 4% of genetic variation came from populations, the 39% variation came from individuals and 57% (p < 0.05) came from intra-individuals. 5 polymorphic SSR primers were selected to construct molecular ID code system of these cultivars. This analysis on the genetic diversity and relationship of the 40 flowering cherry cultivars will help to insight into the genetic background, relationship of these flowering cherry cultivars and promote to identify similar cultivars.

Surface wave inversion with unknown number of soil layers based on a hybrid learning procedure of deep learning and genetic algorithm

Surface wave inversion is a key step in the application of surface waves to soil velocity profiling.Currently,a common practice for the process of inversion is that the number of soil layers is assumed to be known before using heuristic search algorithms to compute the shear wave velocity profile or the number of soil layers is considered as an optimization variable.However,an improper selection of the number of layers may lead to an incorrect shear wave velocity profile.In this study,a deep learning and genetic algorithm hybrid learning procedure is proposed to perform the surface wave inversion without the need to assume the number of soil layers.First,a deep neural network is adapted to learn from a large number of synthetic dispersion curves for inferring the layer number.Then,the shear-wave velocity profile is determined by a genetic algorithm with the known layer number.By applying this procedure to both simulated and real-world cases,the results indicate that the proposed method is reliable and efficient for surface wave inversion.

Conservation genomics provides insights into genetic resilience and adaptation of the endangered Chinese hazelnut, Corylus chinensis

Global climate change has increased concerns regarding biodiversity loss.However,many key conservation issues still required further research,including demographic history,deleterious mutation load,adaptive evolution,and putative introgression.Here we generated the first chromosome-level genome of the endangered Chinese hazelnut,Corylus chinensis,and compared the genomic signatures with its sympatric widespread C.kwechowensis-C yunnanensis complex.We found large genome rearrangements across all Corylus species and identified species-specific expanded gene families that may be involved in adaptation.Population genomics revealed that both C.chinensis and the C.kwechowensis-C.yunnanensis complex had diverged into two genetic lineages,forming a consistent pattern of southwestern-northern differentiation.Population size of the narrow southwestern lineages of both species have decreased continuously since the late Miocene,whereas the widespread northern lineages have remained stable(C.chinensis) or have even recovered from population bottlenecks(C.kwechowensis-C.yunnanensis complex) during the Quaternary.Compared with C.kwechowensis-C. yunnanensis complex,C.chinensis showed significantly lower genomic diversity and higher inbreeding level.However,C.chinensis carried significantly fewer deleterious mutations than C.kwechowensis-C. yunnanensis complex,as more effective purging selection reduced the accumulation of homozygous variants.We also detected signals of positive selection and adaptive introgression in different lineages,which facilitated the accumulation of favorable variants and formation of local adaptation.Hence,both types of selection and exogenous introgression could have mitigated inbreeding and facilitated survival and persistence of C.chinensis.Overall,our study provides critical insights into lineage differentiation,local adaptation,and the potential for future recovery of endangered trees.

Epidemiological Surveillance: Genetic Diversity of Rotavirus Group A in the Pearl River Delta, Guangdong, China in 2019

Objective This study aimed to understand the epidemic status and phylogenetic relationships of rotavirus group A(RVA)in the Pearl River Delta region of Guangdong Province,China.Methods This study included individuals aged 28 days–85 years.A total of 706 stool samples from patients with acute gastroenteritis collected between January 2019 and January 2020 were analyzed for 17 causative pathogens,including RVA,using a Gastrointestinal Pathogen Panel,followed by genotyping,virus isolation,and complete sequencing to assess the genetic diversity of RVA.Results The overall RVA infection rate was 14.59%(103/706),with an irregular epidemiological pattern.The proportion of co-infection with RVA and other pathogens was 39.81%(41/103).Acute gastroenteritis is highly prevalent in young children aged 0–1 year,and RVA is the key pathogen circulating in patients 6–10 months of age with diarrhea.G9P[8](58.25%,60/103)was found to be the predominant genotype in the RVA strains,and the 41 RVA-positive strains that were successfully sequenced belonged to three different RVA genotypes in the phylogenetic analysis.Recombination analysis showed that gene reassortment events,selection pressure,codon usage bias,gene polymorphism,and post-translational modifications(PTMs)occurred in the G9P[8]and G3P[8]strains.Conclusion This study provides molecular evidence of RVA prevalence in the Pearl River Delta region of China,further enriching the existing information on its genetics and evolutionary characteristics and suggesting the emergence of genetic diversity.Strengthening the surveillance of genotypic changes and gene reassortment in RVA strains is essential for further research and a better understanding of strain variations for further vaccine development.

Interaction between diet and genetics in patients with inflammatory bowel disease

In this editorial,we comment on the article by Marangoni et al,published in the recent issue of the World Journal of Gastroenterology 2023;29:5618-5629,about“Diet as an epigenetic factor in inflammatory bowel disease”.The authors emphasized the role of diet,especially the interaction with genetics,in promoting the inflam-matory process in inflammatory bowel disease(IBD)patients,focusing on DNA methylation,histone modifications,and the influence of microRNAs.In this editorial,we explore the interaction between genetics,gut microbiota,and diet,in an only way.Furthermore,we provided dietary recommendations for patients with IBD.The Western diet,characterized by a low fiber content and deficiency the micronutrients,impacts short-chain fatty acids production and may be related to the pathogenesis of IBD.On the other hand,the consumption of the Mediter-ranean diet and dietary fibers are associated with reduced risk of IBD flares,particularly in Crohn’s disease(CD)patients.According to the dietary guidance from the International Organization for the Study of Inflammatory Bowel Diseases(IOIBD),the regular consumption of fruits and vegetables while reducing the consumption of saturated,trans,dairy fat,additives,processed foods rich in maltodextrins,and artificial sweeteners containing sucralose or saccharine is recommended to CD patients.For patients with ulcerative colitis,the IOIBD recommends the increased intake of natural sources of omega-3 fatty acids and follows the same restrictive recommendations aimed at CD patients,with the possible inclusion of red meats.In conclusion,IBD is a complex and hetero-geneous disease,and future studies are needed to elucidate the influence of epigenetics on diet and microbiota in IBD patients.

Comparative Study of Genetic Structure and Genetic Diversity betweenWild and Cultivated Populations of Taxus cuspidata,Northeast China

Taxus cuspidata is a rare plant with important medicinal and ornamental value.Aiming at the obvious differences between wild and cultivated populations of T.cuspidata from Northeast China,a total of 61 samples,that is,33 wild yews and 28 cultivated yews were used to analyze the differences and correlations of the kinship,genetic diversity,and genetic structure between them by specific length amplified fragment sequencing(SLAF-seq).Finally,470725 polymorphic SLAF tags and 58622 valid SNP markers were obtained.Phylogenetic analysis showed that 61 samples were classified into 2 clusters:wild populations and cultivated populations,and some wild yews were categorized into the cultivated populations;the genetic diversity analysis showed that the Nei diversity index of wild populations(0.4068)was smaller than that of cultivated populations(0.4414),and the polymorphic information content(PIC)of wild populations(0.2861)was smaller than that of cultivated populations(0.3309).The genetic differentiation analysis showed that the total populations of gene diversity(H_(t))of cultivated and wild populations were respectively 0.8159 and 0.5685,the coefficient of gene differentiation(G_(st))of cultivated and wild populations was respectively 0.3021 and 0.1068,and the gene flow(N_(m))(2.4967)of wild populations was larger than cultivated populations(0.8199).The molecular variance(AMOVA)revealed that inter-population variation accounted for 29.57%of the total genetic variation,while intra-population variation accounted for 70.42% of the total genetic variation(p<0.001),this suggested that the genetic variation in the T.cuspidata is mainly attributed to within-population factors.In conclusion,the genetic distance between geographical ecological groups of wild populations was generally smaller than that of cultivated populations,and the degree of genetic diversity and genetic differentiation was smaller than that of cultivated populations.As evident,the utilization of SLAF-seq technology enables efficient and accurate development of SNP markers suitable for genetic analysis of T.cuspidata species.These developed SNP markers can provide a molecular foundation for T.cuspidata breeding,construction of genetic maps,variety identification,and association analysis of agronomic traits.

Genome-wide SNP markers provided insights into the reproductive strategy and genetic diversity of the green tide causative species Ulva prolifera in China

Ulva prolifera is the causative species of the annually occurring large-scale green tides in China since 2007.Its specific biological features on reproductivity strategies,as well as intra-species genetic diversity,are still largely unknown,especially at the genome level,despite their importance in understanding the formation and outbreak of massive green tides.In the present study,the restriction site-associated DNA genotyping approach(2b-RAD)was adopted to identify the genome-wide single-nucleotide polymorphisms(SNPs)of 54 individual thalli including samples collected from Subei Shoal in 2019 and Qingdao coast from 2019 to 2021.SNPs genotype results revealed that most of the thalli in 2019 and 2020 were haploid gametophytes,while only half of the thalli were gametophytes in 2021,indicating flexibility in the reproductive strategies for the formation of the green tides among different years and the dominance of asexual and vegetative reproductive mode for the floating period.Besides,population analysis was conducted,and it revealed a very low genetic diversity among samples from Subei Shoal and the Qingdao coast in the same year and a higher divergence among samples in different years.The results showed the efficiency of 2b-RAD in the exploration of SNPs in U.prolifera and provided the first genome-wide scale evidence for the origin of the large-scale green tides on the Qingdao coast.This study improved our understanding of the reproductive strategy and genetic diversity of the green tide causative species and will help further reveal the biological causes of the green tide in China.

Appropriate Combination of Crossover Operator andMutation Operator in Genetic Algorithms for the Travelling Salesman Problem

Genetic algorithms(GAs)are very good metaheuristic algorithms that are suitable for solving NP-hard combinatorial optimization problems.AsimpleGAbeginswith a set of solutions represented by a population of chromosomes and then uses the idea of survival of the fittest in the selection process to select some fitter chromosomes.It uses a crossover operator to create better offspring chromosomes and thus,converges the population.Also,it uses a mutation operator to explore the unexplored areas by the crossover operator,and thus,diversifies the GA search space.A combination of crossover and mutation operators makes the GA search strong enough to reach the optimal solution.However,appropriate selection and combination of crossover operator and mutation operator can lead to a very good GA for solving an optimization problem.In this present paper,we aim to study the benchmark traveling salesman problem(TSP).We developed several genetic algorithms using seven crossover operators and six mutation operators for the TSP and then compared them to some benchmark TSPLIB instances.The experimental studies show the effectiveness of the combination of a comprehensive sequential constructive crossover operator and insertion mutation operator for the problem.The GA using the comprehensive sequential constructive crossover with insertion mutation could find average solutions whose average percentage of excesses from the best-known solutions are between 0.22 and 14.94 for our experimented problem instances.

Evaluation of genetic response of mesenchymal stem cells to nanosecond pulsed electric fields by whole transcriptome sequencing

BACKGROUND Mesenchymal stem cells(MSCs)modulated by various exogenous signals have been applied extensively in regenerative medicine research.Notably,nanosecond pulsed electric fields(nsPEFs),characterized by short duration and high strength,significantly influence cell phenotypes and regulate MSCs differentiation via multiple pathways.Consequently,we used transcriptomics to study changes in messenger RNA(mRNA),long noncoding RNA(lncRNA),microRNA(miRNA),and circular RNA expression during nsPEFs application.AIM To explore gene expression profiles and potential transcriptional regulatory mechanisms in MSCs pretreated with nsPEFs.METHODS The impact of nsPEFs on the MSCs transcriptome was investigated through whole transcriptome sequencing.MSCs were pretreated with 5-pulse nsPEFs(100 ns at 10 kV/cm,1 Hz),followed by total RNA isolation.Each transcript was normalized by fragments per kilobase per million.Fold change and difference significance were applied to screen the differentially expressed genes(DEGs).Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses were performed to elucidate gene functions,complemented by quantitative polymerase chain reaction verification.RESULTS In total,263 DEGs were discovered,with 92 upregulated and 171 downregulated.DEGs were predominantly enriched in epithelial cell proliferation,osteoblast differentiation,mesenchymal cell differentiation,nuclear division,and wound healing.Regarding cellular components,DEGs are primarily involved in condensed chromosome,chromosomal region,actin cytoskeleton,and kinetochore.From aspect of molecular functions,DEGs are mainly involved in glycosaminoglycan binding,integrin binding,nuclear steroid receptor activity,cytoskeletal motor activity,and steroid binding.Quantitative real-time polymerase chain reaction confirmed targeted transcript regulation.CONCLUSION Our systematic investigation of the wide-ranging transcriptional pattern modulated by nsPEFs revealed the differential expression of 263 mRNAs,2 miRNAs,and 65 lncRNAs.Our study demonstrates that nsPEFs may affect stem cells through several signaling pathways,which are involved in vesicular transport,calcium ion transport,cytoskeleton,and cell differentiation.