Functional & Integrative Genomics最新文献

{"title":"Comparative genomic analysis of hypervirulent and classical Klebsiella pneumoniae isolates from respiratory samples: A computational assessment of virulence genes","authors":"Manoj Kumar Thirugnanasambantham,&nbsp;Srimathy Ramachandran,&nbsp;Suma Mohan S.,&nbsp;Diraviyam Thirumalai","doi":"10.1007/s10142-026-01869-1","DOIUrl":"10.1007/s10142-026-01869-1","url":null,"abstract":"<div>\u0000 \u0000 <p>Hypervirulent <i>Klebsiella pneumoniae</i> (hvKp) has emerged as a major cause of severe respiratory infections worldwide; however, its genomic distinction from classical <i>K. pneumoniae</i> (cKp), particularly within respiratory isolates, remains incompletely understood. In this study, we conducted a large-scale comparative genomic analysis of 1,293 respiratory Kp genomes retrieved from the BV-BRC database, of which 538 were classified as hvKp and 755 as cKp based on established marker genes. Comprehensive profiling of 127 virulence-associated genes revealed distinct virulence architectures between the two groups. HvKp isolates exhibited significantly higher prevalence of key virulence determinants, particularly iron acquisition systems (aerobactin and yersiniabactin) and capsule-associated loci (<i>p</i> &lt; 0.001), reflecting a specialized and optimized virulence strategy. In contrast, cKp isolates showed greater overall virulence gene diversity, as indicated by higher Shannon diversity indices despite lower marker prevalence. Notably, dominant lineages such as ST11-K64 displayed hybrid virulence profiles, suggesting ongoing genomic convergence. Phylogenetic and PCoA analyses demonstrated clustering driven by functional gene repertoires rather than strict lineage relationships, highlighting functional convergence. To improve predictive resolution, a weighted virulence scoring framework was developed, integrating key determinants such as siderophores, capsule regulators, and hypervirulence-associated genes. This model enabled stratification of isolates into low-, intermediate-, and high-risk categories, with high-risk clusters strongly associated with hvKp signatures. The scoring system demonstrated excellent discriminatory performance (AUC = 0.987) and improved classification accuracy compared to single-marker approaches. Overall, this study provides a robust framework for genomic risk stratification and enhances surveillance of emerging hvKp lineages.</p>\u0000 </div>","PeriodicalId":574,"journal":{"name":"Functional & Integrative Genomics","volume":"26 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147759219","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Whole-transcriptome insights into light-responsive non-coding RNA networks regulating circadian clock and DNA repair in zebrafish","authors":"Shuang Wang,&nbsp;Zhirui Zhu,&nbsp;Minjian Zou,&nbsp;Alessandra Boiti,&nbsp;Xianyong Lan,&nbsp;Daniela Vallone,&nbsp;Shengxiang Zhang,&nbsp;Nicholas S. Foulkes,&nbsp;Haiyu Zhao","doi":"10.1007/s10142-026-01854-8","DOIUrl":"10.1007/s10142-026-01854-8","url":null,"abstract":"<div>\u0000 \u0000 <p>Light is a fundamental environmental cue that orchestrates a wide range of biological processes, from behavioral rhythms to molecular signaling pathways. Although the effects of light on entraining circadian clock and DNA repair have been well established, the post-transcriptional mechanisms involved in these responses are still not fully understood. In particular, the role of non-coding RNAs (ncRNAs), including microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs), in light-regulated gene expression remains unclear. Using light-responsive whole-transcriptome RNA sequencing of zebrafish larvae, we identified 1,365 differentially expressed (DE) mRNAs, 66 DE miRNAs, 330 DE lncRNAs, and 71 DE circRNAs. RT-qPCR analyses validated the expression changes of representative transcripts. Subsequently, by integrating mRNA and ncRNA datasets, we constructed a light-responsive competing endogenous RNA (ceRNA) network, which suggested extensive miRNA-mediated interactions among coding and non-coding RNA. Additional cis- and trans-regulatory network analyses uncovered potential regulatory relationships between ncRNAs and light-responsive genes. Functional enrichment analyses of target genes highlighted key pathways, including circadian rhythm, steroid biosynthesis, phototransduction, and oxidative stress response. Subnetwork analyses further identified ncRNA-mediated regulatory networks converging on circadian clock and DNA repair. Overall, our results suggest that light exposure induces a complex post-transcriptional regulatory network in zebrafish larvae. These findings contribute to our understanding of how ncRNAs function within the circadian clock and DNA repair systems, and advance the molecular basis of light-dependent gene regulation in vertebrates.</p>\u0000 </div>","PeriodicalId":574,"journal":{"name":"Functional & Integrative Genomics","volume":"26 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10142-026-01854-8.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147738923","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Metabolism-related genes CYP4F2, CYP8B1, and SP1 link type 2 diabetes mellitus and non-alcoholic fatty liver disease: A multi-omics and clinical validation study","authors":"Li Ling,&nbsp;Tahir Ali,&nbsp;Mingyue Lv,&nbsp;Xiaoying Zeng,&nbsp;Caixue Duan,&nbsp;Shuayan Gui,&nbsp;Haiyan Zhao","doi":"10.1007/s10142-026-01864-6","DOIUrl":"10.1007/s10142-026-01864-6","url":null,"abstract":"<div><p>Mitochondrial dysfunction is a central pathological feature in the comorbidity of Type 2 Diabetes Mellitus (T2DM) and Non-Alcoholic Fatty Liver Disease (NAFLD). This study employed an integrative genomics approach to identify key mitochondrial metabolism-related genes (MMRGs), including genes annotated in mitochondrial pathways) serving as shared diagnostic and therapeutic targets. By integrating transcriptomic data from human NAFLD and T2DM datasets and applying machine learning algorithms with cross-dataset validation, we identified three pivotal biomarkers: <i>CYP4F2</i>,<i> CYP8B1</i>, and <i>SP1</i>. Nomogram models incorporating these genes demonstrated high predictive accuracy for both conditions. Functional enrichment analyses linked these genomic markers to critical pathways, including actin cytoskeleton regulation in NAFLD and phagosome signaling in T2DM. Immune profiling further revealed significant associations, including CYP8B1 correlating with monocytes in NAFLD and neutrophils in T2DM. Computational drug prediction identified potential therapeutic candidates targeting each biomarker. Crucially, the diagnostic utility of these markers was translated from transcript to protein via ELISA validation, which confirmed significant dysregulation in serum levels that correlated with NAFLD severity in diabetic patients. In conclusion, this study establishes CYP4F2, CYP8B1, and SP1 as pivotal genomic bridges in metabolism-related pathways linking T2DM and NAFLD, providing a foundation for novel diagnostic strategies and targeted precision therapies.</p><h3>Graphical Abstract</h3><div><figure><div><div><picture><source><img></source></picture><span>The alternative text for this image may have been generated using AI.</span></div></div></figure></div></div>","PeriodicalId":574,"journal":{"name":"Functional & Integrative Genomics","volume":"26 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147728018","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Transcription factor LchiTCP1 modulates abiotic stress response in arabidopsis","authors":"Hwarari Delight,&nbsp;Yinyue Zuo,&nbsp;Yao Zhang,&nbsp;Xinyi Cao,&nbsp;Tian Min,&nbsp;Jinhui Chen,&nbsp;Liming Yang","doi":"10.1007/s10142-026-01819-x","DOIUrl":"10.1007/s10142-026-01819-x","url":null,"abstract":"<div>\u0000 \u0000 <p>Plant transcription factors are essential for stress adaptation, regulating responses to both abiotic and biotic stimuli. Among these factors, Teosinte Branched 1, Cycloidea, and PCF (TCP) play key roles in modulating plant responses to abiotic stress. In this study, the specific roles of TCP1 from <i>Liriodendron chinense</i> were examined through gene expression analysis. LchiTCP1 was isolated and transformed into Arabidopsis; its expression under drought, cold, and salt stress conditions was monitored. Transgenic Arabidopsis plants carrying the LchiTCP1 gene showed enhanced growth and root development with distinctive features. Biochemical analyses indicated that LchiTCP1 confers abiotic stress tolerance. Notably, plants overexpressing LchiTCP1 exhibited higher chlorophyll levels after exposure to various stress conditions than wild-type (WT) plants. Histochemical staining of leaves from transgenic plants with DAB and NBT showed reduced staining relative to WT, suggesting lower reactive oxygen species (ROS) activity in TCP1-overexpressing plants. To confirm these findings, the levels of SOD, POD, and CAT enzymes were significantly lower in OE-LchiTCP1 stressed plants than in WT plants. Conversely, OE-LchiTCP1 plants showed at least a twofold increase in MDA content relative to WT plants. qPCR analysis across different stresses revealed increased expression of stress-responsive genes in LchiTCP1-overexpressing plants compared to WT. Therefore, we conclude that the TCP1 gene in <i>L. chinense</i> regulates responses to cold, drought, and salt stress through interactions with downstream stress-responsive genes. This study enhances our understanding of how plants respond to abiotic stresses.</p>\u0000 </div>","PeriodicalId":574,"journal":{"name":"Functional & Integrative Genomics","volume":"26 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147715539","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"PSMG3 enhances the proliferation and metastasis of hepatocellular carcinoma via inhibiting HDAC6","authors":"Shuaihui Wu,&nbsp;Caiyan Wu,&nbsp;Huibin Wang,&nbsp;Yang Shi,&nbsp;Ping Jiang,&nbsp;Dilinigeer Tayier,&nbsp;Kunlei Wang,&nbsp;Qian Cheng,&nbsp;Xinyin Li,&nbsp;Qifeng Wei,&nbsp;Zhixiang Cheng,&nbsp;Bo Liao,&nbsp;Zhiyong Yang","doi":"10.1007/s10142-026-01866-4","DOIUrl":"10.1007/s10142-026-01866-4","url":null,"abstract":"<div>\u0000 \u0000 <p>Hepatocellular carcinoma (HCC) is one of the most frequent cancers globally, characterized by significant metastasis and poor prognosis. The proteasome is critical to the pathogenesis of HCC; however, its mechanisms are not fully elucidated. Here, we explored the role of Proteasome Assembly Chaperone 3 (PSMG3) during HCC progression. In this research, both a subcutaneous tumorigenesis model and a lung metastasis model were established in nude mice to investigate the impact of PSMG3 on the proliferation and metastasis of HCC cells. Chromatin immunoprecipitation (ChIP) assays and dual-luciferase reporter assays were performed to determine the regulatory role of the transcription factor CEBPA on PSMG3. Moreover, the RNA sequencing and label-free quantitative proteomics were employed to clarify the mechanisms through which PSMG3 enhances HCC progression. The results indicated that PSMG3 promoted the proliferation and metastasis of HCC. Mechanistically, CEBPA bound to the promoter of PSMG3 and enhanced its transcription. PSMG3 exerted its pro-tumorigenic effects on HCC by modulating the expression of Histone deacetylase 6 (HDAC6). In summary, we show that the CEBPA/PSMG3/HDAC6 axis promotes HCC progression and that PSMG3 might represent a promising therapeutic target in HCC.</p>\u0000 </div>","PeriodicalId":574,"journal":{"name":"Functional & Integrative Genomics","volume":"26 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147715602","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integration of clinical and cellular lipidomics identifies a serum metabolite signature predictive of oxaliplatin resistance in colorectal cancer","authors":"Xue-fei Wu,&nbsp;Li-ye Xie,&nbsp;Fu-wei Lian,&nbsp;Hao-tang Wei,&nbsp;Shu-fang Ning,&nbsp;Bang-li Hu","doi":"10.1007/s10142-026-01868-2","DOIUrl":"10.1007/s10142-026-01868-2","url":null,"abstract":"<div><h3>Background</h3><p>Oxaliplatin resistance remains a major obstacle in colorectal cancer (CRC) treatment. Lipid metabolism reprogramming is increasingly implicated in chemoresistance, but the clinically applicable lipid biomarkers are lacking.</p><h3>Methods</h3><p>We performed untargeted lipidomic profiling using LC–MS/MS on serum from 60 CRC patients (30 chemotherapy-sensitive, 30 -resistant) and an CRC cell (oxaliplatin-sensitive vs. -resistant). Differentially expressed metabolites (DEMs) were screened, and overlapping DEMs were prioritized using Random Forest and LASSO regression. A predictive signature was developed and validated in an independent cohort of 80 patients. Oxaliplatin was used to treat the CRC cells and validate the metabolite levels.</p><h3>Results</h3><p>We identified 238 and 79 DEMs in serum and cells, respectively. Intersection and machine learning selected three metabolites, including: docosapentaenoic acid (DA), 7-(1-imidazolyl) heptanoic acid (IHA), and dihydroxyacetone phosphate (DHAP). The predictive signature achieved AUC of 0.806 (discovery) and 0.838 (validation), with excellent calibration and positive net benefit on decision curve analysis. The signature scores were significantly higher in patients with distant metastasis or advanced tumor stage, suggesting a link between metabolic dysregulation and disease progression. The signature was independent of conventional tumor markers. The experiment of oxaliplatin- resistant cells revealed that these three metabolites exhibited little influence by treatment of oxaliplatin.</p><h3>Conclusion</h3><p>This integrative lipidomics approach yields a robust serum signature for predicting oxaliplatin resistance in CRC, with potential to reflect both therapeutic response and tumor aggressiveness.</p></div>","PeriodicalId":574,"journal":{"name":"Functional & Integrative Genomics","volume":"26 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147669727","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Single-cell and spatial transcriptomics reveal TNF-α promotes glioblastoma proliferation and migration via CP-mediated KLF10 upregulation","authors":"Jiasheng Zhong,&nbsp;Zechuan Peng,&nbsp;Hongyi Cai,&nbsp;Yunhe Zhao,&nbsp;Liya Ma,&nbsp;Yiquan Ke,&nbsp;Xinlin Sun","doi":"10.1007/s10142-026-01859-3","DOIUrl":"10.1007/s10142-026-01859-3","url":null,"abstract":"<div>\u0000 \u0000 <p>Glioblastoma is a highly aggressive brain tumor characterized by substantial intratumoral heterogeneity and poor clinical outcomes. Understanding the transcriptional programs and microenvironmental cues that drive aggressive tumor cell states is essential for developing targeted therapies. We integrated bulk and single-cell RNA-seq data from TCGA, CGGA, and published spatial datasets. Using BayesPrism deconvolution, we identified a glioblastoma subpopulation (G1) whose abundance consistently correlated with poor prognosis. Pseudotime analysis with Monocle2 positioned G1 at the terminal state of malignant differentiation. To uncover regulatory mechanisms, we applied NetAct and SCENIC, which highlighted KLF10 as a key transcription factor. Spatial transcriptomic deconvolution and NicheNet analysis suggest that microenvironment-derived TNF likely drives G1 transition via FAT1/TNFRSF1A and ceruloplasmin (CP) induction. Functional experiments including CCK-8, EdU, Transwell, and wound healing assays validated the TNF/CP/KLF10 axis as a driver of glioblastoma cell proliferation and migration. Among the eight glioma cell subtypes identified, the G1 subtype was consistently associated with poor prognosis and showed higher proliferation and migration scores. G1 cells showed enhanced ER stress signaling. Integrated analysis identified TNF-α as a key ligand secreted by cDCs, macrophages, and microglia within G1-enriched spatial niches. FAT1 and TNFRSF1A were identified as G1-specific TNF receptors. Transcription factor KLF10 was identified as a master regulator of G1 identity. Functional assays demonstrated that TNF-α promotes glioblastoma cell proliferation and migration through a CP/KLF10 axis, wherein TNF-α-induced CP upregulation modulates KLF10 expression, and these biological effects were reversed by CP suppression. Our study defines a malignant glioblastoma cell state (G1) regulated by intrinsic transcriptional programs and extrinsic immune-derived TNF–CP signaling. Targeting the G1 program or interrupting the TNF-α/CP/KLF10 axis may offer new therapeutic strategies for glioblastoma. </p>\u0000 </div>","PeriodicalId":574,"journal":{"name":"Functional & Integrative Genomics","volume":"26 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147642898","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prediction of chemoresistance in ovarian cancer based on deep learning with pathological images","authors":"Leyan Niu,&nbsp;Xiang Li,&nbsp;Zhiquan Mao,&nbsp;Fen Fu,&nbsp;Mingjie Wang,&nbsp;Hengbin Zhang,&nbsp;Le Chen,&nbsp;Qing Zhang,&nbsp;Xiaoli Tang,&nbsp;Weiming Lou","doi":"10.1007/s10142-026-01857-5","DOIUrl":"10.1007/s10142-026-01857-5","url":null,"abstract":"<div>\u0000 \u0000 <p>Background. High‑grade serous ovarian cancer (HGSOC) is a lethal disease marked by frequent platinum‑based chemotherapy resistance, resulting in high recurrence and mortality. Methods. Whole‑slide images (WSIs) and clinical data were retrieved from The Cancer Genome Atlas and our institutional database. After segmenting WSIs and discarding non‑informative tiles, a convolutional neural network (CNN) was trained to classify cancer versus normal tissue and to predict drug response. Clinical variables were integrated and feature selection performed using Lasso, AdaBoost, Naive Bayes, XGBoost and Random Forest, with the best‑performing model identified on validation and test sets. Resistance scores derived from the optimal model were correlated with clinicopathologic factors, and associations between individual features and lymphocyte infiltration were examined; key features were validated pathologically. Results. The CNN achieved an AUC of 0.995 for tumor‑normal discrimination and 0.662 for distinguishing resistant from sensitive tiles. All five machine‑learning models yielded area under the curves (AUCs) ≥ 0.90 for histologic features. Lasso performed best (AUC = 0.993) and selected 85 significant features. Higher resistance scores correlated positively with tumor grade and stage, negatively with silent mutation burden and neoantigen load, and positively with lymphocyte infiltration, especially feature TZ0279. Patients in the resistant group showed significantly poorer overall and disease‑free survival. Conclusion. A deep‑learning pipeline based on pathology images accurately separates tumor from normal tissue in HGSOC, and also has preliminary potential in predicting chemotherapy response. Histopathological features derived from Lasso regression can initially reflect the tumor microenvironment and drug resistance, offering potential biomarkers for prognosis and personalized therapy. This supports the feasibility of applying image-based artificial intelligence technologies to clinical decision-making research.</p>\u0000 <p>Clinical trial number. Not applicable.</p>\u0000 </div>","PeriodicalId":574,"journal":{"name":"Functional & Integrative Genomics","volume":"26 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147642925","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Overexpression of NK4 suppresses hepatocellular carcinoma progression by inducing apoptosis and autophagy via MAPK pathway inhibition​","authors":"Shangdi Zhang,&nbsp;Jinming Wang,&nbsp;Shan Gao,&nbsp;Caiyan Gao,&nbsp;Linmei Chen,&nbsp;Ping Qi","doi":"10.1007/s10142-026-01858-4","DOIUrl":"10.1007/s10142-026-01858-4","url":null,"abstract":"<div>\u0000 \u0000 <p>Hepatocellular carcinoma (HCC) remains a therapeutic challenge, necessitating novel treatment strategies. This study explored the antitumor activity and underlying mechanisms of NK4 overexpression in HCC. Utilizing engineered NK4-overexpressing HepG2 cells and a TPA-inducible TP-NK4 system evaluated in both HepG2 and MHCC97-H cells, we demonstrated that NK4 significantly inhibits HCC cell proliferation and migration <i>in vitro</i>. Furthermore, NK4 potently induced apoptotic cell death, as evidenced by the modulation of key regulators Bax and Bcl-2. Crucially, the induction of NK4 expression also promoted autophagy and attenuated tumor growth in a mouse xenograft model. Mechanistic analysis indicated that inhibition of the MAPK pathway is central to these anticancer effects. Our integrated findings establish NK4 as a potent multi-faceted inhibitor of HCC progression and highlight its strong therapeutic potential for precision oncology applications by targeting apoptosis, autophagy, and MAPK signaling.</p>\u0000 </div>","PeriodicalId":574,"journal":{"name":"Functional & Integrative Genomics","volume":"26 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147589241","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fusion protein based strategies for developing insect-resistant crops","authors":"Marri Keerthana,&nbsp;Morthala Shankara Sai Reddy,&nbsp;Yogesh Dashrath Naik,&nbsp;Arindam Pal,&nbsp;Anil Namdev Kale,&nbsp;Satish Kumar Singh,&nbsp;Sudha Nandni,&nbsp;K. Premalatha,&nbsp;Murukarthick Jayakodi,&nbsp;Venugopal Mendu,&nbsp;Manish K. Pandey,&nbsp;Somashekhar Punnuri,&nbsp;Rajeev K. Varshney,&nbsp;Mahendar Thudi","doi":"10.1007/s10142-026-01861-9","DOIUrl":"10.1007/s10142-026-01861-9","url":null,"abstract":"<div><p>Insect pest control in crop production incurs substantial economic costs annually on a global scale. Although broad-spectrum chemical pesticides were once considered the most effective solution, their overreliance has led to adverse effects on beneficial insects, human health, and the environment, as well as the development of pesticide-resistant insect populations. Consequently, there is an urgent need for alternative pest management strategies that minimize pesticide use and reduce unintended impacts on natural enemies, thereby maintaining ecological balance. Host plant resistance plays a pivotal role in integrated pest management (IPM). However, developing pest-resistant varieties through conventional breeding methods can be time-consuming and challenging due to the involvement of multiple quantitative traits controlled by various genetic loci. One promising biotechnological approach is the development of fusion proteins, engineered molecules that combine the functional properties of two or more distinct proteins. These fusion proteins effectively target specific insect pests while minimizing environmental impact. Importantly, they overcome key limitations of single-gene constructs, including narrow target range and rapid resistance development. Numerous fusion proteins have been successfully developed and deployed in various crop plants, demonstrating their versatility and broad-spectrum activity against major insect pests. This review discusses fusion protein technologies and their application in developing transgenic crops with enhanced resistance to insect pests.</p></div>","PeriodicalId":574,"journal":{"name":"Functional & Integrative Genomics","volume":"26 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13035636/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147580143","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}