EVLncRNAs 3.0: an updated comprehensive database for manually curated functional long non-coding RNAs validated by low-throughput experiments.

Long noncoding RNAs (lncRNAs) have emerged as crucial regulators across diverse biological processes and diseases. While high-throughput sequencing has enabled lncRNA discovery, functional characterization remains limited. The EVLncRNAs database is the first and exclusive repository for all experimentally validated functional lncRNAs from various species. After previous releases in 2018 and 2021, this update marks a major expansion through exhaustive manual curation of nearly 25 000 publications from 15 May 2020, to 15 May 2023. It incorporates substantial growth across all categories: a 154% increase in functional lncRNAs, 160% in associated diseases, 186% in lncRNA-disease associations, 235% in interactions, 138% in structures, 234% in circular RNAs, 235% in resistant lncRNAs and 4724% in exosomal lncRNAs. More importantly, it incorporated additional information include functional classifications, detailed interaction pathways, homologous lncRNAs, lncRNA locations, COVID-19, phase-separation and organoid-related lncRNAs. The web interface was substantially improved for browsing, visualization, and searching. ChatGPT was tested for information extraction and functional overview with its limitation noted. EVLncRNAs 3.0 represents the most extensive curated resource of experimentally validated functional lncRNAs and will serve as an indispensable platform for unravelling emerging lncRNA functions. The updated database is freely available at https://www.sdklab-biophysics-dzu.net/EVLncRNAs3/.

EVlncRNA-Dpred: improved prediction of experimentally validated lncRNAs by deep learning.

Long non-coding RNAs (lncRNAs) played essential roles in nearly every biological process and disease. Many algorithms were developed to distinguish lncRNAs from mRNAs in transcriptomic data and facilitated discoveries of more than 600 000 of lncRNAs. However, only a tiny fraction (<1%) of lncRNA transcripts (~4000) were further validated by low-throughput experiments (EVlncRNAs). Given the cost and labor-intensive nature of experimental validations, it is necessary to develop computational tools to prioritize those potentially functional lncRNAs because many lncRNAs from high-throughput sequencing (HTlncRNAs) could be resulted from transcriptional noises. Here, we employed deep learning algorithms to separate EVlncRNAs from HTlncRNAs and mRNAs. For overcoming the challenge of small datasets, we employed a three-layer deep-learning neural network (DNN) with a K-mer feature as the input and a small convolutional neural network (CNN) with one-hot encoding as the input. Three separate models were trained for human (h), mouse (m) and plant (p), respectively. The final concatenated models (EVlncRNA-Dpred (h), EVlncRNA-Dpred (m) and EVlncRNA-Dpred (p)) provided substantial improvement over a previous model based on support-vector-machines (EVlncRNA-pred). For example, EVlncRNA-Dpred (h) achieved 0.896 for the area under receiver-operating characteristic curve, compared with 0.582 given by sequence-based EVlncRNA-pred model. The models developed here should be useful for screening lncRNA transcripts for experimental validations. EVlncRNA-Dpred is available as a web server at https://www.sdklab-biophysics-dzu.net/EVlncRNA-Dpred/index.html, and the data and source code can be freely available along with the web server.

EVLncRNAs 2.0: an updated database of manually curated functional long non-coding RNAs validated by low-throughput experiments.

Long non-coding RNAs (lncRNAs) play important functional roles in many diverse biological processes. However, not all expressed lncRNAs are functional. Thus, it is necessary to manually collect all experimentally validated functional lncRNAs (EVlncRNA) with their sequences, structures, and functions annotated in a central database. The first release of such a database (EVLncRNAs) was made using the literature prior to 1 May 2016. Since then (till 15 May 2020), 19 245 articles related to lncRNAs have been published. In EVLncRNAs 2.0, these articles were manually examined for a major expansion of the data collected. Specifically, the number of annotated EVlncRNAs, associated diseases, lncRNA-disease associations, and interaction records were increased by 260%, 320%, 484% and 537%, respectively. Moreover, the database has added several new categories: 8 lncRNA structures, 33 exosomal lncRNAs, 188 circular RNAs, and 1079 drug-resistant, chemoresistant, and stress-resistant lncRNAs. All records have checked against known retraction and fake articles. This release also comes with a highly interactive visual interaction network that facilitates users to track the underlying relations among lncRNAs, miRNAs, proteins, genes and other functional elements. Furthermore, it provides links to four new bioinformatics tools with improved data browsing and searching functionality. EVLncRNAs 2.0 is freely available at https://www.sdklab-biophysics-dzu.net/EVLncRNAs2/.

Sustained and targeted delivery of siRNA/DP7-C nanoparticles from injectable thermosensitive hydrogel for hepatocellular carcinoma therapy.

Hepatocellular carcinoma (HCC) is one of the most lethal cancers in humans. The inhibition of peptidyl-prolyl cis/trans isomerase (Pin1) gene expression may have great potential in the treatment of HCC. N-Acetylgalactosamine (GalNAc) was used to target the liver. Cholesterol-modified antimicrobial peptide DP7 (DP7-C) acts as a carrier, the GalNAc-siRNA/DP7-C complex increases the uptake of GalNAc-siRNA and the escape of endosomes in hepatocytes. In addition, DP7-C nanoparticles and hydrogel-assisted GalNAc-Pin1 siRNA delivery can effectively enhance the stability and prolong the silencing effects of Pin1 siRNA. In an orthotopic liver cancer model, the GalNAc-Pin1 siRNA/DP7-C/hydrogel complex can potentially regulate Pin1 expression in hepatocellular carcinoma cells and effectively inhibit tumor progression. Our study proves that Pin1 siRNA is an efficient method for the treatment of HCC and provides a sustainable and effective drug delivery system for the suppression of liver cancer.

A Peptide-Based Small RNA Delivery System to Suppress Tumor Growth by Remodeling the Tumor Microenvironment.

MicroRNAs can regulate a variety of physiological and pathological processes and are increasingly recognized as being involved in regulating the malignant progression of cancer, which is an important direction for the study and treatment of cancer. In addition, the tumor microenvironment has gradually become an important direction of study for combating cancer. Researchers can inhibit tumor growth by remodeling and suppressing an immunosuppressive phenotype in the tumor microenvironment. Therefore, the combination of microRNA delivery and tumor microenvironment remodeling may be a potential research direction. In a previous study, we developed a novel cationic and hydrophilic antimicrobial peptide, DP7, by computer simulation. It was found that cholesterol-modified DP7 (DP7-C) has dual functions as a carrier and an immune adjuvant. In this experiment, we used DP7-C to deliver microRNAs or inhibitors intratumorally, where it played a dual role as a carrier and an immune adjuvant. As a delivery vector, DP7-C has more advantages in terms of transfection efficiency and cytotoxicity than Lipo2000 and PEI25K. Components of the DP7-C/RNA complex can effectively escape endosomes after uptake via caveolin- and clathrin-dependent pathways. As an immune adjuvant, DP7-C can activate dendritic cells and promote macrophage polarization. Moreover, it can transform the immunosuppressive tumor microenvironment into an immune-activated tumor microenvironment, indicating its potential as an anticancer therapy. In conclusion, this study identifies a novel microRNA and inhibitor delivery system that can remodel the tumor microenvironment and introduces an alternative scheme for antitumor treatment.

(EX-4)2-Fc, an effective long-acting GLP-1 receptor agonist, reduces obesity-related inflammation by inhibiting leptin expression.

Obesity has been recognized as a low-grade, chronic inflammatory disease that leads to an increase in obesity-associated disorders, including type 2 diabetes (T2D), fatty liver diseases and cancer. Glucagon-like peptide-1 (GLP-1) is an effective drug for T2D, and it not only has glucose-regulating effects but also has anti-inflammatory effects in obesity. In our previous study, we designed a novel GLP-1 analogue, (EX-4)2-Fc, which has been shown to reduce body weight and improve glucose tolerance in vivo. In this study, we observed that (EX-4)2-Fc also has anti-inflammatory functions in adipose tissue. After the treatment of diet-induced obesity (DIO) mice with (EX-4)2-Fc, we found that the inflammatory response in adipose tissue was significantly attenuated. (Ex-4)2-Fc can reduce obesity-associated proinflammatory cytokine levels and macrophage numbers in DIO mice. In addition, (EX-4)2-Fc treatment resulted in proinflammatory M1-type macrophages beginning to transform into anti-inflammatory M2-type macrophages. The inflammatory mitogen-activated protein kinase (MAPK) signalling pathway and nuclear factor kappa B (NF-κB) were altered in adipose tissue after (EX-4)2-Fc treatment. Leptin has been proven to be closely related to immunity, and we demonstrated that the effect of (EX-4)2-Fc on adipocyte inflammation was related to leptin. The data suggested that (EX-4)2-Fc could modulate the inflammatory response by inhibiting the expression of leptin in adipose tissue.

Personalized neoantigen-pulsed dendritic cell vaccines show superior immunogenicity to neoantigen-adjuvant vaccines in mouse tumor models.

Development of personalized cancer vaccines based on neoantigens has become a new direction in cancer immunotherapy. Two forms of cancer vaccines have been widely studied: tumor-associated antigen (including proteins, peptides, or tumor lysates)-pulsed dendritic cell (DC) vaccines and protein- or peptide-adjuvant vaccines. However, different immune modalities may produce different therapeutic effects and immune responses when the same antigen is used. Therefore, it is necessary to choose a more effective neoantigen vaccination method. In this study, we compared the differences in immune and anti-tumor effects between neoantigen-pulsed DC vaccines and neoantigen-adjuvant vaccines using murine lung carcinoma (LL2) candidate neoantigens. The enzyme-linked immunospot (ELISPOT) assay showed that 4/6 of the neoantigen-adjuvant vaccines and 6/6 of the neoantigen-pulsed DC vaccines induced strong T-cell immune responses. Also, 2/6 of the neoantigen-adjuvant vaccines and 5/6 of the neoantigen-pulsed DC vaccines exhibited potent anti-tumor effects. The results indicated that the neoantigen-pulsed DC vaccines were superior to the neoantigen-adjuvant vaccines in both activating immune responses and inhibiting tumor growth. Our fundings provide an experimental basis for the selection of immune modalities for the use of neoantigens in individualized tumor immunotherapies.

A novel in silico antimicrobial peptide DP7 combats MDR Pseudomonas aeruginosa and related biofilm infections.

BACKGROUND: Antimicrobial peptides are promising alternative antimicrobial agents to combat MDR. DP7, an antimicrobial peptide designed in silico, possesses broad-spectrum antimicrobial activities and immunomodulatory effects. However, the effects of DP7 against Pseudomonas aeruginosa and biofilm infection remain largely unexplored. OBJECTIVES: To assess (i) the antimicrobial activity of DP7 against MDR P. aeruginosa; and (ii) the antibiofilm activity against biofilm infection. Also, to preliminarily investigate the possible antimicrobial mode of action. METHODS: The MICs of DP7 for 104 clinical P. aeruginosa strains (including 57 MDR strains) and the antibiofilm activity were determined. RNA-Seq, genome sequencing and cell morphology were conducted. Both acute and chronic biofilm infection mouse models were established. Two mutants, resulting from point mutations associated with LPS and biofilms, were constructed to investigate the potential mode of action. RESULTS: DP7, at 8-32 mg/L, inhibited the growth of clinical P. aeruginosa strains and, at 64 mg/L, reduced biofilm formation by 43% to 68% in vitro. In acute lung infection, 0.5 mg/kg DP7 exhibited a 70% protection rate and reduced bacterial colonization by 50% in chronic infection. DP7 mainly suppressed gene expression involving LPS and outer membrane proteins and disrupted cell wall structure. Genome sequencing of the DP7-resistant strain DP7R revealed four SNPs controlling LPS and biofilm production. gshA44 and wbpJ139 mutants displayed LPS reduction and motility deficiency, conferring the reduction of LPS and biofilm biomass of strain DP7R and indicating that LPS was a potential target of DP7. CONCLUSIONS: These results demonstrate that DP7 may hold potential as an effective antimicrobial agent against MDR P. aeruginosa and related infections.

EVLncRNAs: a manually curated database for long non-coding RNAs validated by low-throughput experiments.

Long non-coding RNAs (lncRNAs) play important functional roles in various biological processes. Early databases were utilized to deposit all lncRNA candidates produced by high-throughput experimental and/or computational techniques to facilitate classification, assessment and validation. As more lncRNAs are validated by low-throughput experiments, several databases were established for experimentally validated lncRNAs. However, these databases are small in scale (with a few hundreds of lncRNAs only) and specific in their focuses (plants, diseases or interactions). Thus, it is highly desirable to have a comprehensive dataset for experimentally validated lncRNAs as a central repository for all of their structures, functions and phenotypes. Here, we established EVLncRNAs by curating lncRNAs validated by low-throughput experiments (up to 1 May 2016) and integrating specific databases (lncRNAdb, LncRANDisease, Lnc2Cancer and PLNIncRBase) with additional functional and disease-specific information not covered previously. The current version of EVLncRNAs contains 1543 lncRNAs from 77 species that is 2.9 times larger than the current largest database for experimentally validated lncRNAs. Seventy-four percent lncRNA entries are partially or completely new, comparing to all existing experimentally validated databases. The established database allows users to browse, search and download as well as to submit experimentally validated lncRNAs. The database is available at http://biophy.dzu.edu.cn/EVLncRNAs.

Predicting functional long non-coding RNAs validated by low throughput experiments.

High-throughput techniques have uncovered hundreds and thousands of long non-coding RNAs (lncRNAs). Among them, only a tiny fraction has experimentally validated functions (EVlncRNAs) by low-throughput methods. What fraction of lncRNAs from high-throughput experiments (HTlncRNAs) is truly functional is an active subject of debate. Here, we developed the first method to distinguish EVlncRNAs from HTlncRNAs and mRNAs by using Support Vector Machines and found that EVlncRNAs can be well separated from HTlncRNAs and mRNAs with 0.6 for Matthews correlation coefficient, 64% for sensitivity, and 81% for precision for the independent human test set. The most useful features for classification are related to sequence conservations at RNA (for separating from HTlncRNAs) and protein (for separating from mRNA) levels. The method is found to be robust as the human-RNA-trained model is applicable to independent mouse RNAs with similar accuracy and to a lesser extent to plant RNAs. The method can recover newly discovered EVlncRNAs with high sensitivity. Its application to randomly selected 2000 human HTlncRNAs indicates that the majority of HTlncRNAs is probably non-functional but a large portion (nearly 30%) are likely functional. In other words, there is an ample number of lncRNAs whose specific biological roles are yet to be discovered. The method developed here is expected to speed up and reduce the cost of the discovery by prioritizing potentially functional lncRNAs prior to experimental validation. EVlncRNA-pred is available as a web server at http://biophy.dzu.edu.cn/lncrnapred/index.html . All datasets used in this study can be obtained from the same website.

Novel Self-Assembled Micelles Based on Cholesterol-Modified Antimicrobial Peptide (DP7) for Safe and Effective Systemic Administration in Animal Models of Bacterial Infection.

Owing to their broad-spectrum antibacterial properties, multitarget effects, and low drug resistance, antimicrobial peptides (AMPs) have played critical roles in the clinical therapy of drug-resistant bacterial infections. However, the potential hazard of hemolysis following systemic administration has greatly limited their application. Here, we developed a novel AMP derivative, DP7-C, by modifying a formerly identified highly active AMP (DP7) with cholesterol to form an amphiphilic conjugate. The prepared DP7-C easily self-assembled into stable nanomicelles in aqueous solution. The DP7-C micelles showed lower hemolytic activity than their unconjugated counterparts toward human red blood cells and a maximum tolerated dose of 80 mg/kg of body weight in mice via intravenous injection, thus demonstrating improved safety. Moreover, by eliciting specific immunomodulatory activities in immune cells, the DP7-C micelles exerted distinct therapeutic effects in zebrafish and mouse models of infection. In conclusion, DP7-C micelles may be an excellent candidate for the treatment of bacterial infections in the clinic.

Effective inhibition of melanoma tumorigenesis and growth via a new complex vaccine based on NY-ESO-1-alum-polysaccharide-HH2.

BACKGROUND: A safe and effective adjuvant plays an important role in the development of a vaccine. However, adjuvants licensed for administration in humans remain limited. Here, for the first time, we developed a novel combination adjuvant alum-polysaccharide-HH2 (APH) with potent immunomodulating activities, consisting of alum, polysaccharide of Escherichia coli and the synthetic cationic innate defense regulator peptide HH2. METHODS: The adjuvant effects of APH were examined using NY-ESO-1 protein-based vaccines in prophylactic and therapeutic models. We further determined the immunogenicity and anti-tumor effect of NY-ESO-1-APH (NAPH) vaccine using adoptive cellular/serum therapy in C57/B6 and nude mice. Cell-mediated and antibody-mediated immune responses were evaluated. RESULTS: The APH complex significantly promoted antigen uptake, maturation and cross-presentation of dendritic cells and enhanced the secretion of TNF-α, MCP-1 and IFN-γ by human peripheral blood mononuclear cells compared with individual components. Vaccination of NAPH resulted in significant tumor regression or delayed tumor progression in prophylactic and therapeutic models. In addition, passive serum/cellular therapy potently inhibited tumor growth of NY-ESO-1-B16. Mice treated with NAPH vaccine produced higher antibody titers and greater antibody-dependent/independent cellular cytotoxicity. Therefore, NAPH vaccination effectively stimulated innate immunity, and boosted both arms of the adaptive humoral and cellular immune responses to suppress tumorigenesis and growth of melanoma. CONCLUSIONS: Our study revealed the potential application of APH complex as a novel immunomodulatory agent for vaccines against tumor refractory and growth.

The effects of different landscape strategies on outdoor thermal comfort in village squares: a case study in Dayuwan village in Wuhan City.

Appropriate landscape configurations significantly mitigate rural thermal degradation. However, limited research exists on seasonal thermal comfort and the interconnections among landscape elements. Using ENVI-met software and field measurements, this study analyzed the microclimate of Dayuwan Village Square in Wuhan City. Fifteen design scenarios, including tree planting, building greening, albedo adjustment, and expanded tree coverage, were quantitatively evaluated to assess their impact on outdoor thermal comfort. Additionally, synergistic interactions between mitigation strategies were explored. The study found that increasing evergreen tree coverage by 50% has minimal impact on comfort during winter and spring. However, it significantly reduces temperatures in summer and autumn, resulting in average predicted mean vote (PMV) decreases of 0.315 and 0.643, respectively. Additionally, this strategy optimizes PMV values at 18:00 on extreme days, with a 0.102 decrease in summer and a 0.002 increase in winter. This research offers practical and sustainable guidance to designers for enhancing mitigation effects through optimal landscape configuration, providing a technical framework for rural environmental improvements.

Acute lymphoblastic leukemia with pseudo-Chediak-Higashi granules in the initial diagnosis and relapse.

Pseudo-Chediak-Higashi granules are large cytoplasmic inclusions commonly encountered in myeloblasts or other myeloid precursors in acute myeloid leukemia and myelodysplastic syndromes. However, pseudo-Chediak-Higashi granules are rarely found in acute lymphoblastic leukemia (ALL). We present the case of an 8-year-old boy who was diagnosed with ALL with pseudo-Chediak-Higashi granules in the initial diagnosis and relapse, acting like a characteristic marker.

Identification of Potent siRNA Delivery Peptides Using Computer Modeling.

Peptides with suitable aggregation behavior and electrical properties are potential siRNA delivery vectors. However, identifying suitable peptides with ideal delivery and safety features is difficult owing to the variations in amino acid sequences. Here, a holistic program based on computer modeling and single-cell RNA sequencing (scRNA-seq) is used to identify ideal siRNA delivery peptides. Stage one of this program consists of a sequential screening process for candidates with ideal assembly and delivery ability; stage two is a cell subtype-level analysis program that screens for high in vivo tissue safety. The leading candidate peptide selected from a library containing 12 amino acids showed strong lung-targeted siRNA delivery capacity after hydrophobic modification. Systemic administration of these compounds caused the least damage to liver and lung tissues and has little impact on macrophage and neutrophil numbers. By loading STAT3 siRNA, strong anticancer effects are achieved in multiple models, including patient-derived xenografts (PDX). This screening procedure may facilitate the development of peptide-based RNA interference (RNAi) therapeutics.

Glucagon-like peptide-1 receptor agonist regulates fat browning by altering the gut microbiota and ceramide metabolism.

Studies have shown that antidiabetic drugs can alter the gut microbiota. The hypoglycemic effects of the drugs can be attributed in part to certain species in the gut microbiome that help the drugs work more effectively. In addition, increasing energy expenditure via the induction of adipose tissue browning has become an appealing strategy to treat obesity and associated metabolic complications. Currently, glucagon-like peptide-1 receptor agonist (GLP-1 RA) treatment for metabolic disorders such as obesity and type 2 diabetes has been widely studied. To determine the mechanism of a long-acting GLP-1 RA affects adipose tissue browning and the gut microbiome, we treated high-fat diet mice with GLP-1 RA and demonstrated that the drug can regulate adipose tissue browning. 16S rRNA and untargeted metabolomics assays suggested that it increased the abundance of bacterium Lactobacillus reuteri and decreased serum ceramide levels in mice. L. reuteri was negatively correlated with ceramide. We found that the mechanism of ceramide decline was alkaline ceramidase 2 (Acer2) overexpression. Moreover, L. reuteri can play a therapeutic synergistic role with GLP-1 RA, suggesting that gut microbiota can be used as a part of the treatment of diabetes.

Transcriptomic insights into the molecular mechanism for response of wild emmer wheat to stripe rust fungus.

Introduction: Continuous identification and application of novel resistance genes against stripe rust are of great importance for wheat breeding. Wild emmer wheat, Triticum dicoccoides, has adapted to a broad range of environments and is a valuable genetic resource that harbors important beneficial traits, including resistance to stripe rust caused by Puccinia striiformis f. sp. tritici (Pst). However, there has been a lack of systematic exploration of genes against Pst races in wild emmer wheat. Methods: Genome-wide transcriptome profiles were conducted on two wild emmer wheat genotypes with different levels of resistance to (Pst (DR3 exhibiting moderate (Pst resistance, and D7 displaying high (Pst resistance). qRT-PCR was performed to verify findings by RNA-seq. Results: A higher number of DEGs were identified in the moderately (Pst-resistant genotype, while the highly (Pst-resistant genotype exhibited a greater enrichment of pathways. Nonetheless, there were consistent patterns in the enrichment of pathways between the two genotypes at the same time of inoculation. At 24 hpi, a majority of pathways such as the biosynthesis of secondary metabolites, phenylpropanoid biosynthesis, phenylalanine metabolism, and alpha-Linolenic acid metabolism exhibited significant enrichment in both genotypes. At 72 hpi, the biosynthesis of secondary metabolites and circadian rhythm-plant pathways were notably and consistently enriched in both genotypes. The majority of (WRKY, MADs , and AP2-ERF families were found to be involved in the initial stage of response to Pst invasion (24 hpi), while the MYB, NAC, TCP, and b-ZIP families played a role in defense during the later stage of Pst infection (72 hpi). Discussion: In this present study, we identified numerous crucial genes, transcription factors, and pathways associated with the response and regulation of wild emmer wheat to Pst infection. Our findings offer valuable information for understanding the function of crucial Pst-responsive genes, and will deepen the understanding of the complex resistance mechanisms against Pst in wheat.

Genome-Wide Identification and Functional Characterization of FAR1-RELATED SEQUENCE (FRS) Family Members in Potato (Solanum tuberosum).

FAR1-RELATED SEQUENCE (FRS) transcription factors are generated by transposases and play vital roles in plant growth and development, light signaling transduction, phytohormone response, and stress resistance. FRSs have been described in various plant species. However, FRS family members and their functions remain poorly understood in vegetative crops such as potato (Solanum tuberosum, St). In the present study, 20 putative StFRS proteins were identified in potato via genome-wide analysis. They were non-randomly localized to eight chromosomes and phylogenetic analysis classified them into six subgroups along with FRS proteins from Arabidopsis and tomato. Conserved protein motif, protein domain, and gene structure analyses supported the evolutionary relationships among the FRS proteins. Analysis of the cis-acting elements in the promoters and the expression profiles of StFRSs in various plant tissues and under different stress treatments revealed the spatiotemporal expression patterns and the potential roles of StFRSs in phytohormonal and stress responses. StFRSs were differentially expressed in the cultivar "Xisen 6", which is exposed to a variety of stresses. Hence, these genes may be critical in regulating abiotic stress. Elucidating the StFRS functions will lay theoretical and empirical foundations for the molecular breeding of potato varieties with high light use efficiency and stress resistance.

[Leukemia Genotype Analysis of Children with Acute Lymphoblastic Leukemia in Yunnan Area].

OBJECTIVE: To analyze 43 leukemia genes in children with acute lymphoblastic leukemia (ALL) in Yunnan province, and provide the basis for the diagnosis and treatment of children with ALL in this area. METHODS: The clinical data of 428 children with newly diagnosed ALL in Yunnan area from January 2015 to December 2020 were retrospectively analyzed. Multiple nested PCR technology was used to detect 43 common leukemia genes. RESULTS: Among the 428 children with ALL, 159 were positive for leukemia genes, with a positive rate of 37.15% (159/428), and a total of 15 leukemia genes were detected. Among the 159 leukemia gene-positive children, ETV6-RUNX1+ accounted for 25.79% (41/159), followed by E2A-PBX1+ and BCR-ABL+, accounting for 24.53% (39/159) and 23.27% (37/159) respectively. MLL+ accounted for 6.29% (10/159), WT1+ accounted for 4.40% (7/159), IKZF1 gene deletion and CRLF2+ accounted for 3.77% (6/159) respectively. The positive rate of MLL (46.15%) was the highest in ＜1-year old group, the positive rate of ETV6-RUNX1 (10.56%) was the highest in 1-10-year old group, and BCR-ABL+ rate (23.65%) was the highest in >10-year old group. The distribution of leukemia genes in different age groups was statistically significant (P <0.05). CONCLUSION: The most common fusion gene of children with ALL in Yunnan is ETV6-RUNX1, followed by E2A-PBX1 and BCR-ABL.