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At least 685 records · Page 38Linked to original sources
PubMed2026

Balancing growth and immunity of potato by humidity-dependent expression of a late blight resistance gene.

Inducible expression of resistance genes is an effective approach to balance plant growth and immunity, thus facilitating the development of disease-resistant crop cultivars. While pathogen-responsive and immunity-related promoters have been adopted for this purpose, alternative design strategies remain to be explored. High relative humidity (RH) has been recognized as a crucial permissive environmental condition for the occurrence of devastating plant diseases including tomato and potato late blight. Here, we identified humidity-activated cis-regulatory elements (HAEs) in Solanum lycopersicum through an integrative analysis of transcriptomics and chromatin accessibility data. Sequence homology-inferred HAEs in S. tuberosum can predict humidity-elicited changes in downstream gene expression. Transgenic S. tuberosum lines expressing a late blight resistance gene driven by an artificial humidity-inducible promoter containing a natural S. tuberosum HAE were generated. These transgenic lines exhibited comparable late blight resistance levels to the lines overexpressing the same resistance gene in controlled zoospore inoculation bioassays, while avoiding growth suppression and tuber yield penalties in common garden experiments. Our findings highlight the importance of plant cis-regulatory elements in the transcriptional responses to high RH and provide a proof-of-concept for a humidity-inducible environment-responsive resistance gene deployment strategy to engineer disease-resistant crop cultivars without compromising growth and yield.

Phytophthora infestans↗
PubMed2026

Multi-omics evidence reveals robust airborne-human resistome connectivity driven by high-risk ARGs and mediated by Staphylococcus.

Airborne microbiomes are considered an important source of human antimicrobial resistance (AMR) exposure, yet multi-omics evidence linking airborne and human nasal resistomes remains limited. Here, we integrated metagenomic sequencing and whole-genome sequencing of antibiotic-resistant Staphylococcus isolates to investigate the connectivity between air and human nasal resistomes in dairy farm environments. Metagenomic taxonomic profiling showed that Staphylococcus was prominent in total suspended particles (TSP) and consistently detected across all samples. Among environmental reservoirs, TSP resistomes exhibited the strongest similarity to human nasal resistomes. This connectivity was supported by multiple lines of evidence, including highly similar resistome profiles, extensive homologous antibiotic resistance gene (ARG) pairs, strain-level similarity of resistant Staphylococcus isolates, and conserved mobile ARG genetic contexts. Notably, this connectivity was primarily driven by high-risk ARGs, while Staphylococcus was frequently associated with mobile ARGs and represented the only shared pathogenic genomes carrying both ARGs and virulence factor genes between airborne and nasal samples. Although lower ARG diversity, nasal resistomes exhibited higher ARG burden, risk scores, antibiotic-resistant bacterial genome abundance, and prevalence of resistant Staphylococcus. Occupational exposure further increased total and high-risk ARG burdens among farm workers. Together, these findings indicate that TSP can serve as an important route of occupational AMR exposure, with high-risk ARGs and Staphylococcus contributing to connectivity between airborne and nasal resistomes. Incorporating the host microbiome may therefore provide a more complete assessment of human-associated AMR exposure within a One Health framework.

Airborneresistome↗
PubMed2026

Outcomes of elacestrant in patients with ER-positive, HER2-negative, ESR1-mutated metastatic breast cancer who received prior endocrine therapy and cyclin-dependent kinase inhibitor in a real-world setting.

BACKGROUND: Real-world data analyses show durable benefits with elacestrant, with or without prior treatment with cyclin-dependent kinase 4/6 inhibitor (CDK4/6i). This cohort focused on patients with ER-positive/HER2-negative estrogen receptor 1 (ESR1)-mutated metastatic breast cancer (mBC) treated with elacestrant after at least one line of endocrine therapy (ET) combined with CDK4/6i (N = 281). PATIENTS AND METHODS: Claims data from the Komodo Research Dataset linked with Foundation Medicine clinical-genomics data were used. Primary outcome was median time-to-next-treatment (mTTNT). RESULTS: In patients with ER-positive/HER2-negative ESR1-mutated mBC who received one to two prior lines of ET + CDK4/6i (n = 108), mTTNT with elacestrant was 8.2 months [95% confidence interval (CI) 6.0-12.2]. In patients who received one to two prior lines of ET + CDK4/6i for ≥12 months (n = 85), mTTNT was 9.0 months (95% CI 7.7-13.7), including an mTTNT of 12.2 months (95% CI 9.0-not reached) in those who received one prior line of ET (n = 31). In patients with liver and/or lung metastasis (n = 169), mTTNT was 6.9 months (95% CI 5.8-8.3), whereas it was 7.4 months (95% CI 5.6-12.9) in patients with brain metastasis (n = 68). In patients with coexisting ESR1- and phosphoinositide 3-kinase-pathway-mutated tumors (n = 115), mTTNT was 6.1 months (95% CI 5.0-8.1). CONCLUSIONS: Elacestrant showed durable benefits in patients with ER-positive/HER2-negative ESR1-mutated mBC previously exposed to at least one line of ET + CDK4/6i, reinforcing the role of elacestrant as a potential first-choice option for patients with endocrine-sensitive tumors.

ESR1 mutation↗
PubMed2026

Tumor genomic landscape of older patients with metastatic breast cancer☆.

BACKGROUND: Metastatic breast cancer (MBC) in older patients has distinct clinical and histologic characteristics. Elucidating the genomic basis of MBC helps identify potential therapeutic targets to improve outcomes for older patients with MBC. PATIENTS AND METHODS: Using a prospective database and targeted DNA sequencing (OncoPanel), we examined MBC's genomic landscape in older patients (age &#x2265;70 years at MBC diagnosis) and compared findings with those in younger (aged <50 years) and middle-aged (aged 50-69 years) patients. After classifying single nucleotide variants (SNVs) and copy number variations (CNVs) as oncogenic (via OncoKB), the frequencies of SNVs and CNVs, tumor mutational burden (TMB), and oncogenic signaling pathways were compared by age group using Fisher's exact tests. We estimated the association between continuous age at MBC diagnosis and mutations via multivariate logistic regression analysis, adjusting for race, stage at initial diagnosis, subtype, histology, and sample tested (primary versus metastatic). RESULTS: Our study included 2379 patients [853 (35%) younger, 1311 (55%) middle-aged, and 215 (9%) older] who underwent OncoPanel testing between 2013 and 2020. The most frequent tumor alterations in older patients were SNVs in PIK3CA (44%), TP53 (33%), CDH1 (22%) and amplifications in CCND1 (18%). After adjustment, older age was associated with higher frequency of SNVs in CDH1 [odds ratio (OR) = 1.43, 95% confidence interval (CI) 1.21-1.68, q < 0.001], MAP3K1 [OR = 1.30, 95% CI 1.10-1.54, q = 0.008], and PIK3CA [OR = 1.21, 95% CI 1.11-1.31, q < 0.001] and fewer SNVs in TP53 [OR = 0.84, 95% CI 0.77-0.91, q < 0.001]. Patients in the older group were more likely to have tumors with &#x2265;10 mutations/megabase than the youngest patients (26% versus 17%, P = 0.003). CONCLUSIONS: In this large cohort of patients with MBC, the tumor genomic landscape differed between older and younger patients even after accounting for tumor subtype. Older patients were more likely to have high-TMB and PIK3CA-mutated tumors, highlighting the importance of genomic testing for treatment applications in this population.

NGS↗
PubMed2026

Impact of Diabetes on Outcomes of Contemporary PCI Guided by OCT vs Angiography: The ILUMIEN IV Trial.

BACKGROUND: Patients with diabetes are at higher risk for adverse events after percutaneous coronary intervention (PCI) compared with patients without diabetes. OBJECTIVES: This study sought to assess the influence of diabetes and complex lesions on the outcomes of patients undergoing PCI with and without optical coherence tomography (OCT) guidance during a follow-up period of 2 years. METHODS: Patients in ILUMIEN IV randomized to OCT-guided vs angiography-guided PCI were grouped into those with (n = 1,044) and without diabetes (n = 1,443). Study endpoints were target vessel failure (TVF) and serious major adverse cardiovascular events (MACE). RESULTS: After adjustment for differences in clinical and angiographic characteristics, the 2-year rates of both TVF (9.9% vs 6.3%; adjusted HR: 1.48; 95% CI: 1.09-2.02; P = 0.01) and serious MACE (5.3% vs 2.7%; adjusted HR: 1.77; 95% CI: 1.14-2.76; P = 0.01) were increased in diabetic compared with nondiabetic patients, consistently in patients with and without complex lesions (Pinteraction = 0.22 and 0.14, respectively), although the highest 2-year rates were in patients with diabetes and complex lesions. In all randomized patients, OCT guidance compared with angiography guidance did not reduce TVF or serious MACE. These effects were consistent in patients with and without diabetes (Pinteraction = 0.41 and 0.20, respectively), and were not modified by treatment of complex lesions. CONCLUSIONS: In the large-scale ILUMIEN IV trial, patients with diabetes remained at increased risk for adverse events after PCI compared with nondiabetic patients despite the use of OCT procedural guidance. Patients with diabetes and complex lesions were at particularly high risk for adverse outcomes after PCI.

Humans↗
PubMed2026

Ultrashort vs Standard-Duration Dual Antiplatelet Therapy in Acute Coronary Syndrome Patients Undergoing PCI: A Meta-Analysis.

BACKGROUND: The efficacy and safety of ultrashort (&#x2264;1-month) dual antiplatelet therapy (DAPT) followed by antiplatelet monotherapy remain uncertain in acute coronary syndrome (ACS) patients. OBJECTIVES: This study sought to compare ultrashort vs standard-duration DAPT in patients with ACS undergoing percutaneous coronary intervention (PCI). METHODS: We conducted a systematic review and meta-analysis of randomized controlled trials until February 15, 2026. Primary outcomes were major adverse cardiac and cerebrovascular events (MACCE), major bleeding, and net adverse clinical event (NACE). Prespecified subgroup analyses examined by ethnicity (East Asian vs non-East Asian) and abbreviation strategy (intensive: &#x2264;1-week DAPT or clopidogrel/aspirin monotherapy vs moderate: &#x2265;2-week DAPT, followed by ticagrelor/prasugrel monotherapy). RESULTS: Across 10 trials (n = 29,232), ultrashort DAPT did not increase MACCE risk (HR: 1.06; 95% CI: 0.93-1.20; P = 0.38; I2 = 24%), with higher MACCE risk observed in ST-segment elevation myocardial infarction (STEMI) but not non-ST-segment elevation ACS (NSTE-ACS), and significantly reduced major bleeding (HR: 0.47; 95% CI: 0.35-0.64; P < 0.00001; I2 = 44%), resulting in a net clinical benefit (HR: 0.83; 95% CI: 0.72-0.97; P = 0.02; I2 = 61%). Bleeding reduction was more pronounced in East Asians (HR: 0.35; 95% CI: 0.25-0.49; P < 0.00001; I2 = 0%) than non-East Asians (HR: 0.63; 95% CI: 0.43-0.93; P = 0.02; I2 = 44%), with a significant interaction (P = 0.02). The abbreviation strategy significantly modified outcomes (P for interaction = 0.003): intensive abbreviation raised MACCE risk (HR: 1.37; 95% CI: 1.11-1.69; P = 0.003; I2 = 0%), while moderate abbreviation had no statistically significant difference (HR: 0.96; 95% CI: 0.85-1.08; P = 0.47; I2 = 0%). CONCLUSIONS: In patients with ACS undergoing PCI, ultrashort DAPT reduced bleeding without increasing ischemic events overall, although a signal of increased MACCE was observed in STEMI but not in NSTE-ACS. Bleeding reduction was greater in East Asians, while &#x2264;1-week DAPT or clopidogrel/aspirin monotherapy may increase ischemic risk.

Humans↗
PubMed2026

Nanopore-based, long-range Parvovirus B19 amplicon sequencing for near-whole genome characterization.

BACKGROUND: Whole-Genome Sequencing (WGS) enables monitoring of genomic variation and evaluation of diagnostic PCR assays. However, WGS data for Parvovirus B19 (B19V) remains limited despite its relevance for clinical care and transfusion safety. To increase the availability of high-quality B19V genomic data, a near-WGS protocol was developed and validated. METHOD: The protocol combines long-range PCR to generate a 4.6-kb amplicon, covering &#x223c;82% of the B19V genome, with Oxford Nanopore sequencing. Validation was performed using six reference samples and nineteen B19V-positive donor plasma samples. RESULTS: After quality control, samples achieved a median sequencing depth of 152x. Sequences generated from the six reference samples showed 100% concordance with previously published data. Genomic analysis of donor samples explained atypical amplification profiles observed during routine PCR screening. CONCLUSION: The newly developed protocol provides a scalable method for B19V genome characterization, enabling assessment of oligonucleotide-binding regions for PCR assay monitoring and facilitating the generation of genomic data for future epidemiological investigations.

PCR assay monitoring↗
PubMed2026

Long-term saline-alkaline selection rewires the growth-survival trade-off in Priestia megaterium.

Saline-alkaline soils impose persistent osmotic, ionic, pH, and nutrient stress on soil microorganisms, but the evolutionary routes by which beneficial bacteria adapt to such conditions remain poorly resolved. We performed adaptive laboratory evolution to examine the adaption of the plant growth-promoting rhizobacterium Priestia megaterium HA22 to long-term oligotrophic saline-alkaline selection. After 175 serial transfers, the evolved lineage proliferated stably at 40&#x202f;g&#x202f;L-1 Na2SO4 at pH 10.0, whereas the wild-type strain failed to proliferate. Genome resequencing and allelic replacement revealed a 5-bp insertion in spo0A, the master sporulation regulator, as a major adaptive mutation. This mutation abolished sporulation; shortened the lag phase; and enhanced vegetative growth, nutrient uptake, and expression of tricarboxylic acid cycle and nitrogen metabolism gene under saline-alkaline stress. According to untargeted metabolomics, adaptation was accompanied by increased amino acid metabolism and aminoacyl-tRNA biosynthesis, with proline, isoleucine and pantothenic acid functionally promoting growth. A point mutation in ugpB enhanced glycerol-3-phosphate uptake, increased peptidoglycan and wall teichoic acid levels, and partially rescued the survival cost of the spo0A mutation. In greenhouse assays under combined saline-alkaline stress, the evolved strain increased soybean shoot dry weight and root dry weight by 56.08% and 27.02%, respectively. These results indicate that prolonged, predictable saline-alkaline selection can favor active growth rather than dormancy when compensatory cell envelope reinforcement buffers survival costs.

Adaptive laboratory evolution↗
PubMed2026

Data-driven approaches in green microbiology: strategies for plant growth-promoting bacteria.

Plant growth-promoting bacteria (PGPB) are gaining attention as scalable biological solutions to enhance crop productivity and resilience. However, accurately identifying and characterizing PGPB remains challenging, particularly under variable environmental conditions where microbial functions are context-dependent and shaped by complex plant-microbe interactions. Advances in high-throughput sequencing have shifted the field from culture-dependent approaches to genome-informed strategies, enabling large-scale taxonomic and functional profiling. Although trait-based databases support the prediction of plant-beneficial genes, they capture only a fraction of the underlying biological complexity and often require labor-intensive analyses. Machine learning (ML) and deep learning (DL) have emerged as powerful tools to integrate genomic, physiological, and ecological data, enabling the prioritization of candidate strains with plant growth-promoting potential. To evaluate advances in the field, we conducted a systematic review of studies integrating ML and DL with PGPB characterization, assessing algorithm selection, performance, and target plant systems. Across 248 observations, only 6.0% of studies directly addressed PGPB screening, whereas the majority (77.4%) focused on plant disease detection, revealing a substantial gap in the application of AI to beneficial microorganisms for plant growth. Convolutional neural networks (CNNs) were the most frequently applied algorithms, largely driven by image-based phenotyping tasks. Overall, the field is constrained by limited datasets, high computational demands, and challenges in modeling multispecies and host-associated interactions. We highlight the need for integrative and interpretable ML and DL frameworks that bridge genomic data and functional validation. Such approaches represent a promising path toward scalable, data-driven discovery and deployment of bioinoculants in sustainable agriculture.

Agriculture↗
PubMed2026

Sequence optimization targeting mRNA stability enhances monoclonal antibody titers in CHO cells.

This study presents a DNA sequence optimization approach that integrates mRNA stability as a tunable design parameter to enhance monoclonal antibody expression in Chinese hamster ovary (CHO) cells. A comprehensive combinatorial library of synonymous coding-sequence variants of an IgG1 light chain was integrated as single copies at a defined genomic locus in CHO cells with identical regulatory elements. Steady-state mRNA abundance, quantified by deep sequencing of gDNA and mRNA, served as a proxy for mRNA stability. These data were used to train a machine learning model that predicts mRNA abundance from coding sequence using embeddings from a pre-trained nucleotide transformer. This abundance predictor, together with established translational metrics, was incorporated into a genetic algorithm for multi-objective codon optimization. As proof-of-concept, we optimized sequences encoding Trastuzumab to either maximize or minimize the abundance criterion and obtained benchmark sequences from two commercial providers. Using targeted integration, we generated CHO cell lines and measured protein titer and cell-specific productivity. Sequences optimized for high abundance significantly increased intracellular mRNA levels (+41%), protein titer (+59%), and cell-specific productivity (+85%) relative to low-abundance designs, while viable cell densities remained comparable. Compared to commercial benchmarks, high-abundance sequences achieved significantly higher titer (+70%) and cell-specific productivity (+98%). These findings establish mRNA stability as a practical and complementary design parameter for codon optimization in monoclonal antibody production, with potential applicability to other proteins and expression systems.

CHO↗
PubMed2026

Understanding tumor adaptations and resistance to MET inhibitors in MET-altered non-small cell lung cancer.

AIM: Type Ib MET inhibitors are clinically active in selected MET-altered non-small cell lung cancer, particularly tumors with MET exon 14 skipping or MET amplification, but acquired resistance remains incompletely understood. Here, we investigated resistance across biologically distinct MET-altered contexts, including MET exon 14 skipping, MET amplification, and MET overexpression. METHODS: Paired baseline and progression samples from seven patients treated with tepotinib or capmatinib were analyzed using spatial transcriptomics, whole-exome sequencing, RNA sequencing, CRISPR screening, and drug-combination assays. Patient-derived cultures and resistant cell-line models were used to explore resistance-associated changes. RESULTS: MET inhibitor resistance was heterogeneous, with persistence of the initial MET alteration in most evaluable cases and emergence of patient-specific genomic events. Three main resistance-associated, often overlapping, routes were identified: on-target MET evolution through kinase-domain alterations; extracellular matrix and tumor-microenvironment remodeling, including collagen and fibronectin upregulation, complement-related signaling, and partial EMT-associated programs; and bypass signaling involving EGFR/HER, MAPK, and PI3K/Akt pathways. In vitro models reproduced several tumor-cell-intrinsic features but only partially captured microenvironment-associated changes. CONCLUSIONS: MET inhibitor resistance in this cohort involved overlapping, context-dependent genomic, phenotypic, and signaling adaptations, supporting combination strategies for MET-altered lung cancer.

CRISPR screen↗
PubMed2026

Loss of interruption in the HTT CAG repeat is associated with somatic expansion and loss of medium spiny neurons in Huntington's disease.

Synonymous loss-of-interruption variants in the expanded CAG repeat sequence of Huntingtin (HTT) accelerate the clinical onset and progression of Huntington's disease (HD). Medium spiny neurons (MSNs) are gradually lost in HD and undergo selective somatic CAG expansion, but it is unclear how somatic expansion relates to MSN pathology. Here, we show that MSNs with large (111-150 CAG) and very large (>150 CAG) somatic expansions are rare in early manifest HD but accumulate in proportion with duration of disease. In patients with the deleterious CAG-CCG loss-of-interruption (CAG-CCG LOI) modifier, the proportion of MSNs with large and very large expansions is increased &#x223c;5-fold despite reduced small somatic expansions in blood, and caudate MSN counts are reduced. Our findings suggest that increased somatic CAG expansion contributes to accelerated striatal MSN pathology and onset of HD but that MSNs with very large genomic CAG expansions can persist among surviving neurons of the HD brain.

Huntington&#x2019;s disease↗
PubMed2026

The chemical landscape of plant surface metabolites: Acylsugars as models of ecological function and structural diversity.

Plants produce a multifunctional assortment of specialized metabolites that play important roles in defense, environmental adaptation, and ecological interactions. Among these compounds, acylsugars, nonvolatile metabolites produced primarily in glandular trichomes of Solanaceae species, have emerged as informative model systems for understanding plant surface chemistry. Differences in acyl chain length, branching pattern, saturation, and attachment position generate extensive chemical diversity that influences herbivore deterrence, pathogen resistance, and the physicochemical properties of leaf surfaces. Recent advances in analytical chemistry, particularly liquid chromatography-ion mobility-tandem mass spectrometry (LC-IM-MS/MS), have greatly improved the ability to separate structurally related acylsugar isomers and characterize metabolite complexity at high resolution. When integrated with genomics, transcriptomics, and emerging spatial metabolomics approaches, these analytical tools provide new insights into acylsugar biosynthesis, pathway regulation, evolutionary diversification, and ecological function across plant species. This review positions acylsugars, particularly those of Solanum species, as model systems for understanding how structural diversity, spatial localization, and specialized metabolism shape ecological and physiological function at plant surfaces. We examine acylsugar structural diversity, biosynthetic pathways, ecological and physiological functions, and interactions with environmental and atmospheric processes. Major challenges, including extensive isomeric complexity, incomplete pathway characterization, and difficulties linking chemical structure to biological function, are discussed alongside emerging opportunities in integrative omics, crop improvement, sustainable pest management, and environmental monitoring. Overall, acylsugars provide a powerful model for linking molecular structure, spatial localization, and ecological function, offering broader insight into how specialized metabolism shapes plant adaptation, defense, and environmental interactions.

Acylsugars↗
PubMed2026

Targeting the F17-A Fimbrial gene: An efficient method for the quantitative detection of Escherichia coli F17.

Escherichia coli (E. coli) F17 is one of the leading bacterial causes of diarrhea in farm livestock, which cause huge economic losses and could also pose potential risks to public health. Generally, the monitoring the E. coli F17 is based on the polymerase chain reaction (PCR) and bacteria plate counting method, which were largely limited by the time-consuming nature and susceptibility to detection errors. Hence, there is an urgent need to develop a rapid and quantitative detection method for E. coli F17. In the present study, an E. coli F17 challenge experiment in ovine intestinal epithelial cells (IECs) was employed as an in vitro model. At different post-challenge time points (1&#xa0;h, 2&#xa0;h, and 3&#xa0;h), two conventional methods (bacteria plate counting and microplate method) were conducted as benchmarks to estimate the number of E. coli F17 adhering to the IECs. Additionally, total genomic DNA was extracted and quantitative Real-time PCR (qPCR) was performed to detect the relative abundance of E. coli F17 fimbrial pilin (F17-A) and adhesion (F17-G) genes. Subsequently, statistical analyses, including Pearson's correlation coefficient (PCC) method and linear curve-fitting, were performed to evaluate the correlation between the abundance of F17-A/G genes and the results of the benchmark methods. The results showed that the relative abundances of both genes were highly correlated with the number of E. coli F17 that adhered to the IECs, among them, the F17-A gene showed a stronger correlation with the bacterial counts, exhibiting a correlation coefficient&#xa0;>&#xa0;0.85. Furthermore, standard curves analyses further confirmed the out-performed quantitative performance of F17-A gene and a significantly stronger correlation with bacterial counts which exhibited an outstanding linear correlation (r&#xa0;=&#xa0;-0.9534, R2&#xa0;=&#xa0;0.9252) with amplification efficiency of 101.4%, The results of the present study indicate that targeting fimbrial genetic hallmarks via qPCR is an effective and promising method for E. coli F17 quantification, which could potentially contribute to epidemiological studies and pathogen monitoring in the livestock industry.

Detection↗
PubMed2026

Mitotic chromosomes: from the chromosome scaffold model to condensins and physical forces.

Mitotic chromosome organization and assembly remain fundamental questions in genetics. Since the chromosome scaffold model proposed in 1977 highlighted the role of nonhistone proteins in determining chromosome shape and size, key nonhistone proteins, including condensins and topoisomerase II&#x3b1; (topoII&#x3b1;), have been shown to play critical roles in organizing chromosome axes and chromatin loops. Emerging evidence from biochemistry, imaging, and genomics suggests that mitotic chromosome assembly is a dynamic process driven by the interplay of condensin-mediated looping, topoII&#x3b1;-dependent entanglement/disentanglement, and multiple physical forces, including electrostatic nucleosome interactions, linker histone H1, free Mg2+, and depletion attraction. In this review, we discuss how these mechanisms contribute to chromosome assembly and propose that interphase chromatin domains function as dynamic building blocks of mitotic chromosomes.

chromatin compaction↗
PubMed2026

African genomes are not a subset.

Africa harbors more genetic variation than the rest of the world combined, but approximately 1% of genomes in major databases derive from individuals of African ancestry. This is not an equity problem; it is a scientific error that distorts drug dosing, degrades risk scores, and undermines precision medicine globally.

African pangenome↗
PubMed2026

From feasibility to predictability: prime editing redefines precision breeding in plants.

Originally developed in mammalian systems as a genome editing strategy without double-strand breaks, prime editing (PE) has been adapted for precise genome modifications. However, its deployment revealed key limitations, including reduced efficiency, strong locus dependency, low germline transmission, and somatic chimerism. Consequently, diverse PE variants have emerged, resulting in fragmented landscape of architectures with context-dependent and inconsistent performance. This review consolidates these advances and outlines emerging design principles behind plant PE systems. It evaluates optimization strategies at multiple levels, discusses their applications in monocots and eudicots, and highlights persistent bottlenecks and future directions, including AI-guided protein engineering and improved delivery strategies. These advances position PE as a rapidly evolving platform toward enabling precision breeding in plants.

cis-regulatory engineering↗