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PubMed2025

Harnessing Landscape Genomics to Evaluate Genomic Vulnerability and Future Climate Resilience in an East Asia Perennial.

In this era of rapid climate change, understanding the adaptive potential of organisms is imperative for buffering biodiversity loss. Genomic forecasting provides invaluable insights into population vulnerability and adaptive potential under diverse climatic conditions, thereby facilitating management interventions and bolstering shaping species-specific germplasm conservation strategies. We primarily employed landscape genomics approaches, leveraging single-nucleotide polymorphisms obtained through whole-genome resequencing of 201 individuals across 43 Rheum palmatum complex populations, to pinpoint adaptive variation and its significance in the context of future climates, delineate seed zones, and establish guidelines for ex situ germplasm conservation. The species complex exhibited strong signatures of local adaptation and differential genomic vulnerabilities across its distribution range, with eastern lineage populations facing significant maladaptation risks under future climate scenarios. Using diverse datasets of putatively adaptive loci and climate change scenarios, we delineated three distinct seed zones within the species' range, estimated varying sample sizes per zone to capture most adaptive diversity, and predicted shifts in seed zone centroids ranging from 48.3 to 359.3 km from historical distributions to mitigate climate change impacts. Collectively, our findings underscore the importance of integrating genomic and environmental data to forecast the adaptive trajectory of an East Asian perennial under anticipated climate changes, guide seed zone delineation for germplasm conservation and enhance population resilience. These results provide a blueprint for designing targeted conservation strategies and restoration plans in other imperilled species.

Climate Change↗

PubMed2026

Dissecting genetic variance structure and evaluating genomic prediction models for single-cross hybrids derived from Stiff Stalk and Non-Stiff Stalk maize heterotic groups.

The early 20th-century discovery of heterosis and the establishment of heterotic groups transformed maize (Zea mays L.) into a keystone of global agriculture. However, maize breeding faces two significant challenges: the gradual decline of general combining ability (GCA) variance within heterotic groups and the impracticality of testing all possible single crosses in the early stages of a breeding program. Here, we developed genomic best linear unbiased prediction (GBLUP)-based multikernel models, using additive and two alternative nonadditive genomic relationship matrices, to estimate the variance components associated with the general combining ability of Stiff Stalk (SS) and Non-Stiff Stalk (NSS) heterotic groups and the specific combining ability arising from their crosses. We further applied these models to predict the performance of untested single-cross combinations under varying levels of parental information. We showed that the SS and NSS groups retained significant GCA variance across traits in both early- and late-maturity groups. The SS group, in contrast, exhibited no detectable GCA variance in grain yield for the intermediate-flowering subset of hybrids, highlighting a limitation for future genetic improvement. Furthermore, our results showed that GBLUP-based multikernel models effectively identified superior hybrids when parental information was available. In the absence of this information, however, these models underperformed compared to covariance-based approaches. Both nonadditive matrices yielded similar results, indicating that they capture comparable genetic relationship patterns despite their distinct formulations. Overall, this study sheds light on the future use of US maize commercial germplasm and demonstrates how GBLUP-based multikernel models can improve the efficiency of hybrid breeding programs.

Zea mays↗

PubMed2026

Validation of a national genetic evaluation for methane emission in Holstein cattle.

Lactanet Canada launched a genomic evaluation for methane efficiency for Holsteins in April 2023, utilizing milk mid-infrared-predicted methane (CH4) emissions (CH4MIR) as a proxy. This study validated the methane efficiency genomic evaluation using genotyped cows with CH4MIR and CH4 records from GreenFeed systems (CH4GF), along with relative breeding values (RBV) for methane production and methane efficiency from the April 2023 evaluation. In Lactanet's methane efficiency evaluation, a higher RBV indicates more desirable, lower-emitting animals. For the validation, RBV were categorized into quintiles for the CH4MIR dataset and tertiles for the CH4GF dataset to evaluate trends across the RBV distribution. Mean CH4MIR decreased progressively across RBV quintiles for both traits, with all pairwise comparisons among quintiles significantly different. Similarly, CH4GF emissions declined across RBV tertiles, with significant differences observed between the lowest and highest tertiles. Additional analyses using RBV threshold categories confirmed that cows with the highest RBV consistently exhibited lower methane emissions. Linear regression analyses further demonstrated a negative relationship between RBV and methane emissions, supporting the predictive ability of the genomic evaluation. These findings confirm that Canada's genomic evaluation for methane efficiency effectively differentiates cows by methane emission potential, reinforcing its potential as a tool for genetic selection to reduce methane emissions in dairy cattle.

Journal Article↗

PubMed2026

Enhancing CRISPR-Cas12a base editing in plants with LbCas12a variants and introns.

Cytosine base editors (CBEs) and adenine base editors (ABEs) are powerful tools for precise genome editing in plants. Conventionally, such base editors are built upon the CRISPR-Cas9 systems where Cas9 nickases are used. To expand the base editing scope and minimize off-target effects, base editors derived from the CRISPR-Cas12a systems are desired. However, the use of deactivated Cas12a (dCas12a) in such base editors constrains the editing activity, preventing the wide use of Cas12a base editors for plant research and trait development. In this study, we demonstrate the use of an ABE based on the efficient LbCas12a-RRV variant to introduce herbicide-resistant mutations in OsACCase in rice. To improve Cas12a CBEs and ABEs, we inserted introns into the coding sequence of dLbCas12a-RRV. This intron-containing Cas12a-CBE shows substantial improvement in editing efficiency in rice, compared to the intron-less counterparts. By contrast, the improvement of ABE with the intron-containing dLbCas12a-RRV is very limited, partly due to the already high baseline editing efficiency of the intron-less dLbCas12a-RRV ABE. Testing of these base editors in poplar shows elevated C-to-T base editing by dLbCas12a-RRV-intron-CBE. For A-to-G editing, ABEs built upon dLbCas12a-RV and dLbCas12a-RRV variants showed significant improvement over ABEs derived from wild-type LbCas12a and the ttLbCas12a variant. The addition of introns to dLbCas12a-RRV does not further improve the base editing efficiency. With whole genome sequencing in rice, we evaluated genome editing specificities with these improved Cas12a base editors. Our analyses show that both intron-containing Cas12a CBE and ABE barely introduce guide RNA-dependent off-target mutations. However, they can generate guide RNA-independent off-target mutations, which are likely attributed to the high enzymatic activities of the deaminases. Collectively, our study demonstrates the successful use of a Cas12a base editor for trait development and reports improved Cas12a CBEs and ABEs for precise base editing in plants.

Oryza↗

PubMed2023

Utilizing evolutionary conservation to detect deleterious mutations and improve genomic prediction in cassava.

INTRODUCTION: Cassava (Manihot esculenta) is an annual root crop which provides the major source of calories for over half a billion people around the world. Since its domestication ~10,000 years ago, cassava has been largely clonally propagated through stem cuttings. Minimal sexual recombination has led to an accumulation of deleterious mutations made evident by heavy inbreeding depression. METHODS: To locate and characterize these deleterious mutations, and to measure selection pressure across the cassava genome, we aligned 52 related Euphorbiaceae and other related species representing millions of years of evolution. With single base-pair resolution of genetic conservation, we used protein structure models, amino acid impact, and evolutionary conservation across the Euphorbiaceae to estimate evolutionary constraint. With known deleterious mutations, we aimed to improve genomic evaluations of plant performance through genomic prediction. We first tested this hypothesis through simulation utilizing multi-kernel GBLUP to predict simulated phenotypes across separate populations of cassava. RESULTS: Simulations showed a sizable increase of prediction accuracy when incorporating functional variants in the model when the trait was determined by<100 quantitative trait loci (QTL). Utilizing deleterious mutations and functional weights informed through evolutionary conservation, we saw improvements in genomic prediction accuracy that were dependent on trait and prediction. CONCLUSION: We showed the potential for using evolutionary information to track functional variation across the genome, in order to improve whole genome trait prediction. We anticipate that continued work to improve genotype accuracy and deleterious mutation assessment will lead to improved genomic assessments of cassava clones.

cassava (Manihot esculenta)↗

PubMed2026

Sparse phenotyping for wheat grain yield enabled by multiomics prediction.

Grain yield is a central target in wheat breeding, yet accurately predicting it remains challenging because it depends on many genes and responds strongly to environmental variation. Genomic selection (GS) has improved breeding efficiency by enabling genome-based prediction of genetic merit, but predictability (PA) for grain yield is often limited under stress environments. At the same time, advances in high-throughput phenotyping (HTP) using unmanned aerial vehicles (UAVs) provide phenomic data that capture environment-responsive plant performance and may complement genomic information. In this study, we evaluated genomic and phenomic models for predicting grain yield in elite bread wheat lines across irrigated, drought, and heat-stress environments. Using a sparse phenotyping framework, we compared parametric and non-parametric models. PA was evaluated within environments and under cross-environment sparse phenotyping scenarios. Genomic models provided a stable baseline and enabled effective information sharing across environments when phenotypic data were incomplete. Phenomics-only models captured environment-specific plant responses but were more sensitive to environmental context. Multiomics models that integrated genomic and phenomic information consistently achieved the highest PA, with the largest gains observed under stress conditions. Overall, our results demonstrate that integrating genomics and UAV-based phenomics within sparse phenotyping designs offers a practical and scalable approach to improve grain yield prediction in wheat.

Triticum↗

PubMed2026

An economic evaluation of functional genomic testing for individuals with undiagnosed rare disorders.

PURPOSE: Functional genomics (FG) approaches, such as RNA-seq and proteomics, offer a complementary diagnostic modality for individuals whose cases remain unsolved after genomic sequencing. This study evaluates the cost-effectiveness and cost-benefit of FG for individuals with suspected monogenic disorders relative to manual reanalysis of genomic data at 18 months. METHODS: A decision tree model compared the costs and outcomes of FG and 18-month reanalysis using data from two Australian Undiagnosed Disease Programs. Deterministic and probability sensitivity analysis were performed. RESULTS: With a diagnostic yield of 13%, FG enabled 4 additional diagnoses per 100 individuals tested at an additional cost of $390 (US $240), resulting in an incremental cost-effectiveness ratio of $8,550 ($5,313) and an 85% probability of being cost-effective. CONCLUSION: Functional genomics enables timely diagnosis for individuals with suspected monogenic disorders by evaluating the functional impact of variants of uncertain significance, offering an advantage over reanalyzing genomic data at 18 months. Integration into the Australian healthcare system, supported by collaborative networks and secure data-sharing infrastructure, coupled with addressing barriers to accessing funded genomic testing, could lead to an annual net benefit of up to $1.1 million ($0.7 M).

Functional genomics↗

PubMed2026

LAMBDA: a prophage detection benchmark for genomic language models.

Transformer-based genomic sequence models represent an emerging frontier in computational biology. Yet, their embeddings have not yet shown the same level of predictive power as natural and protein language models, highlighting a gap between current implementations and theoretical promise. Existing benchmarks for DNA language models primarily focus on classifying regulatory elements in eukaryotic genomes, leaving open the fundamental question of whether these models learn sequence-level features across whole genomes. We introduce LAMBDA, a benchmark designed to rigorously evaluate genome language model embeddings through phage-bacteria sequence discrimination across four categories of increasing complexity: probing tasks, fine-tuning assessments, diagnostic tests, and genome-wide prophage detection. Our comprehensive analysis of current genomic language models provides insight into the importance of training data selection relative to model size, the need for domain-specific training, and the capabilities and limitations of genomic language models for detecting prophage sequences. This benchmark represents a challenging genomic annotation task in the bacterial domain and addresses a key computational problem with direct relevance to microbiology and medicine.

Prophages↗

PubMed2026

LAMBDA: A Prophage Detection Benchmark for Genomic Language Models.

Transformer-based genomic sequence models represent an emerging frontier in computational biology. Yet, their embeddings have not yet shown the same level of predictive power as natural and protein language models, indicating a gap between current implementations and theoretical promise. Existing benchmarks for DNA language models primarily focus on classifying regulatory elements in eukaryotic genomes, leaving open the fundamental question of whether these models learn sequence-level features across whole genomes. We introduce LAMBDA, a benchmark designed to rigorously evaluate genome language model embeddings through phage-bacteria sequence discrimination across four categories of increasing complexity: probing tasks, fine-tuning assessments, diagnostic tests, and genome-wide prophage detection. Our comprehensive analysis of current genomic language models provides novel insights into the importance of training data quality relative to model size, the need for domain-specific training, and the application of genomic language models for detecting prophage sequences. This benchmark represents a challenging genomic annotation task in the bacterial domain and addresses a key computational problem with direct relevance to microbiology and medicine.

DNA language model↗

PubMed2026

Whole exome sequencing identifies three novel variants and establishes the molecular diagnosis of ATP6V0A4-related distal renal tubular acidosis in a lebanese infant.

BACKGROUND: Distal renal tubular acidosis (dRTA) is a rare inherited disorder characterized by impaired urinary acidification, leading to metabolic acidosis, hypokalemia, nephrocalcinosis, and growth impairment. Pathogenic variants in ATP6V0A4 are among the most common genetic causes of autosomal recessive dRTA. METHODS AND RESULTS: We report a Lebanese infant presenting with failure to thrive, recurrent vomiting, severe hyperchloremic metabolic acidosis, hypokalemia, and bilateral nephrocalcinosis, in whom whole-exome sequencing (WES) was performed to establish the molecular diagnosis and perform a comprehensive genomic evaluation. WES identified three novel variants, including a novel homozygous likely pathogenic ATP6V0A4 variant, consistent with the patient's phenotype. Two additional novel variants in TTN and CEP290 were also detected. Family segregation analysis confirmed the inheritance pattern of all three variants and refined the interpretation of the additional genomic findings. The patient showed sustained clinical and biochemical improvement to alkali therapy, with normalization of biochemical abnormalities and improvement in growth during follow-up. CONCLUSIONS: This report expands the molecular spectrum of ATP6V0A4-related dRTA and illustrates the clinical utility of comprehensive WES combined with segregation analysis for accurate molecular diagnosis, variant interpretation, genetic counseling, and the evaluation of additional genomic findings in rare inherited disorders.

Humans↗

PubMed2026

Forty years in the field: reproductive biotechnologies shaping genetic progress in cattle in France.

Over the past four decades, reproductive biotechnologies have profoundly transformed cattle breeding by accelerating genetic progress and enabling the dissemination of elite genetics. In this article, I present a perspective based on more than 40 years of practical experience in embryo technologies within Auriva-Elevage, a cooperative organization serving 30,000 farmers in southern France. The development of embryo transfer in France was closely linked to genetic and sanitary challenges, particularly the introduction of North American Holstein genetics and the restrictions on live animal imports due to infectious diseases such as Infectious Bovine Rhinotracheitis. These constraints stimulated the development of national expertise in embryo transfer. Over the years, our team has implemented and adapted a wide range of reproductive technologies including in vivo embryo production and embryo transfer, cryopreservation, embryo sexing, ovum pick-up (OPU), in vitro embryo production (IVP), embryo biopsy, genomic evaluation of embryos, and laser-assisted biopsy techniques. The genomic revolution dramatically increased the strategic value of OPU-IVP for the rapid multiplication of elite donor females. In addition to technological developments, the success of these programs has depended heavily on internal training, collaboration with national organizations such as ELIANCE (previously UNCEIA, ALLICE) and research institutes including INRAE and Toulouse veterinary school, as well as strong international exchanges through scientific networks. Practical examples such as the use of embryo biopsy to prevent genetic diseases demonstrate the applied value of these technologies in breeding programs. This review highlights the technical evolution, organizational structures, and human expertise that have shaped the implementation of reproductive biotechnologies in cattle breeding and discusses the importance of anticipating future needs to ensure continued genetic progress.

OPU-IVP↗

PubMed2026

SpacerScope: binary-vectorized, genome-wide off-target profiling for RNA-guided nucleases without prior candidate-site bias.

The precision of CRISPR/Cas systems is fundamental to their application in plant and animal biotechnology. However, comprehensive sequence-based off-target candidate discovery remains a computational bottleneck, particularly in large and complex genomes. Here we developed SpacerScope, an off-target candidate discovery framework that enables unbiased, genome-wide discovery by leveraging binary vectorization, bitwise filtering, and right-end-anchored alignment. Benchmarking against human CIRCLE-seq data demonstrated that SpacerScope recovered 100% of validated off-target sites (6142/6142), matching the sensitivity of exhaustive algorithms. Crucially, SpacerScope achieved this maximum candidate recovery while substantially reducing computational overhead. In large-genome evaluations, SpacerScope maintained low peak memory usage of 2.20 GiB and achieved substantial runtime improvements over indel-aware comparator tools, including more than 50-fold speedup relative to Cas-OFFinder 3 (544 s versus 29 185 s). Furthermore, comparative analyses in polyploid species, such as the octoploid strawberry, revealed that SpacerScope identified larger sequence-compatible candidate burdens than standard web-based design platforms. Our results establish SpacerScope as a high-speed framework for sequence-based genome-wide off-target candidate discovery across diverse and highly repetitive genomic landscapes. The source code and program was publicly available at https://github.com/charlesqu666/SpacerScope. Short Abstract CRISPR/Cas sequence-based off-target candidate discovery remains computationally challenging in large, repetitive, and polyploid genomes. Existing tools either miss indel-containing candidate sites or incur prohibitive runtime and memory costs. We developed SpacerScope, a binary-vectorized framework that enables unbiased, genome-wide off-target candidate discovery without pre-selected candidate sites. By integrating bitwise filtering with right-end-anchored alignment, SpacerScope recovered 100% of validated off-target sites in human CIRCLE-seq data while using only 2.20 GiB of memory and achieving more than 10-fold speedup over indel-aware alternatives. Evaluation in plant genomes, including rice and octoploid strawberry, further demonstrated SpacerScope's capacity to identify larger sequence-compatible candidate burdens overlooked by standard tools. SpacerScope thus provides a high-speed framework for sequence-based genome-wide off-target candidate discovery across diverse and highly repetitive genomic landscapes, supporting downstream prioritization.

CRISPR-Cas Systems↗

PubMed2026

Assessment of genomic prediction and genetic gain in multi‑population half-sib families in the perennial grass crop intermediate wheatgrass.

The University of Minnesota has been domesticating the perennial forage intermediate wheatgrass (IWG) since 2011 using a combination of conventional methods and modern breeding tools such as genomic selection. Globally, most IWG selection nurseries are spaced-planted individuals of several hundred genotypes whereas commercial fields established for grain production are row-planted panmictic populations. This study evaluated genomic prediction models and estimated genetic gain in yield and agronomic performance of row-planted IWG half-sib families assessed over 3 years and 2 locations, Lamberton and St. Paul, MN, USA. The strongest trait correlation was negative (r = -0.49) between 2023 St. Paul height and 2022 St. Paul seed size. The three St. Paul environments were more similar for plant height and seed size and so were the Lamberton environments yet no specific trend was observed for grain yield. Evaluation of different univariate and multivariate genomic prediction models showed that multivariate models outperformed the best univariate models by 23 percentage points, yet no single multivariate model was the best predictor of all traits. Cross-environment predictions were the best among St. Paul environments and no single environment was the best predictor of the remaining environments. Genetic gain estimates indicated a 20 kg ha-1 increase in grain yield and 3 cm reduction in plant height per breeding cycle. While no single model predicted all traits with high accuracy, results obtained in this study suggest that evaluating IWG sibs in row plots followed by genomic trait predictions could lead to desired breeding progress for desired traits.

Poaceae↗

PubMed2025

Engineered Lactiplantibacillus plantarum and Levilactobacillus brevis utilizing ribonucleoprotein-mediated editing for inactivation of hemolysin gene.

Lactiplantibacillus plantarum and Levilactobacillus brevis are widely used probiotics with significant potential as chassis organisms for probiotic engineering. However, their bioengineering remains underdeveloped compared to that of other probiotic bacteria due to the limited availability of genetic tools. Although CRISPR-Cas systems have shown promise for genome editing in Lactobacillus species, strain- or site-specific targeting challenges must be overcome to enhance their broader applicability. This study aimed to develop a novel editing system with reduced dependency on plasmids and antibiotics in L. plantarum WCFS1, L. plantarum SPC 72 - 1 and L. brevis SPC-SNU 70 - 2 using a Cas9-gRNA ribonucleoprotein (RNP) complex. Although the hlyIII gene has been annotated as a hemolysin-related gene in several Lactobacillus genomes, no functional hemolytic activity has been definitively demonstrated to date. In this study, hlyIII was selected as a target to evaluate genome editing efficiency and to assess its potential relevance to strain safety. To construct ΔhlyIII strains, the RNP complex targeting hlyIII was separately transformed with recombinase RecE/T and double-stranded donor DNA. As a result, ΔhlyIII mutants were obtained under optimized electroporation conditions. Sequencing analysis revealed a 50 bp deletion and the introduction of a stop codon in hlyIII across all mutant strains. The hemolytic activity test showed a reduction in free hemoglobin levels in the ΔhlyIII strains compared to the wild type: 27.0%, 74.3%, and 5.0% in L. plantarum WCFS1, L. plantarum SPC 72 - 1, and L. brevis SPC-SNU 70 - 2, respectively. These results suggest strain-dependent differences in hemolytic activity and indicate that inactivation of hlyIII may contribute to reduced hemolysis, although further validation is needed to clarify its functional role. In conclusion, the hlyIII gene was successfully edited in L. plantarum and L. brevis using Cas9-gRNA ribonucleoprotein-mediated editing, demonstrating the feasibility of this genome editing platform for application in probiotic strains.

Gene Editing↗

PubMed2026

Functional and flavour-enhancing properties of Staphylococcus sp. from Napham.

Napham, traditional fermented food of the Bodo community in Assam, is produced from tender shoots of Colocasia esculenta and dried fish, and was recently granted Geographical Indication (GI) status. Despite its cultural and nutritional significance, its beneficial microbiota remains insufficiently characterized. This study aimed to identify multifunctional bacterial isolates with both functional and flavor-enhancing properties for use as starter cultures. Forty-eight isolates were screened for Gram reaction, enzymatic activities (protease, lipase, carbohydrate fermentation), and biosafety traits. Four isolates (NAP/1, NAP/2, NAP/3, NAP/4) exhibiting a preliminary phenotypic safety profile based on in vitro screening were evaluated for gastrointestinal stress tolerance traits, including tolerance to acid (pH 2.0), phenol (0.4%), salt (8% NaCl), as well as auto-aggregation capacity and adhesion to chicken crop epithelial cells. Among them, isolate NAP/4 exhibited comparatively higher tolerance, strong adhesion, and high auto-aggregation, and demonstrated a favorable in vitro safety profile, including γ-hemolysis and broad antibiotic susceptibility. In curd and rice beverage models, NAP/4 enhanced sensory qualities and produced diverse flavor volatiles, supporting its candidacy as a multifunctional food-fermenting isolate prior to genomic validation. 16S rRNA sequencing revealed NAP/4 as Staphylococcus sp. (GenBank accession: PQ471484.1). Collectively, these findings highlight NAP/4 as a promising candidate for further genomic evaluation toward potential application in controlled fermentation systems and clean-label formulations. However, whole-genome sequencing and in vivo validation remain essential next steps to confirm safety and functional efficacy at the molecular level.

Journal Article↗

PubMed2026

Lineage-specific transmission and spatial clustering of Mycobacterium tuberculosis in Kaohsiung, Taiwan, in 2019-23: a population-based genomic study.

BACKGROUND: The epidemiology of tuberculosis in Taiwan has been influenced by the introduction of multiple Mycobacterium tuberculosis lineages and by the ageing of the population. We conducted a population-based study to investigate M tuberculosis transmission in Kaohsiung, a city in southern Taiwan. METHODS: In this study, we performed whole-genome sequencing (WGS) of M tuberculosis isolates from all culture-positive cases of tuberculosis notified in Kaohsiung between Jan 1, 2019 and Dec 31, 2023. We obtained routine epidemiological data for each case collected through the national tuberculosis control programme. We characterised the lineage composition of the isolate collection and evaluated genomic clustering of isolates, defined as a difference of 12 or fewer single-nucleotide polymorphisms. Univariable and multivariable logistic regression analyses were performed to estimate the odds of a case belonging to a genomic cluster based on host factors (age, sex, sputum smear status, and residential region) and pathogen factors (drug resistance status and strain lineage). Spatial aggregation of large genomic clusters (including greater than or equal to ten isolates) was assessed using a non-parametric statistical clustering method. We used a Bayesian transmission tree inference method to explore the patterns of age-dependent transmission. FINDINGS: During the study period, 5667 tuberculosis cases were notified in Kaohsiung, 4916 (86·7%) of which were culture-positive. Of these 4916 cases, whole-genome sequencing was successfully performed for 4168 (84·8%) isolates. 1219 (29·2%) of 4168 individuals were female and 2947 (70·7%) were male; the median age was 69·7 years (IQR 57·4-80·7). The dominant lineages were lineage 1 (1749 [42·0%] of 4168 isolates), lineage 2 (1510 [36·2%]), and lineage 4 (905 [21·7%]). 1069 (25·6%) of 4168 were genomically linked and formed 287 clusters. Lineage 2 isolates had higher odds (aOR 2·15 [95% CI 1·80-2·52]) than lineage 1 isolates of genomic clustering across all regions, whereas lineage 4 isolates had a significantly higher risk (2·75 [1·16-6·89]) of genomic clustering than lineage 1 only in the rural northeast region, inhabited primarily by indigenous populations. Spatial clustering analysis corroborated these lineage-region interactions. Although younger adults (<35 years) had the highest individual-level odds (5·64 [4·16-7·68]) of clustering in the logistic regression analysis compared with those aged 80 years or older, the transmission inference indicated that individuals aged 55-74 years were responsible for a greater proportion of inferred transmission events, contributing 50·8% of all transmission events. INTERPRETATION: This sequencing study revealed that older adults (aged ≥65 years) might have played a substantial and under-recognised role in the transmission of tuberculosis in Taiwan. The lineage-specific clustering and spatial patterns suggested that both pathogen characteristics and host demographics shaped tuberculosis transmission dynamics. These findings support the use of integrated genomic surveillance to guide precision tuberculosis control and motivate further research on age-specific transmission pathways and targeted interventions to advance tuberculosis elimination efforts. FUNDING: Taiwan National Health Research Institutes and Taiwan National Science and Technology Council.

Mycobacterium tuberculosis↗

PubMed2026

Molecular and Clinical Determinants of Targeted Therapy Treatment in Biliary Tract Cancer.

PURPOSE: Actionable genomic alterations occur in all anatomic subsets of biliary tract cancer; however, targeted therapies have not shown a survival advantage over cytotoxics, and resistance mechanisms require further characterization. EXPERIMENTAL DESIGN: We analyzed a prospectively maintained cohort of 1,254 patients with histologically confirmed biliary tract cancer who underwent molecular profiling using an FDA-authorized targeted next-generation sequencing (NGS) assay. We defined actionable alterations across anatomic subsets, compared outcomes with targeted therapy versus cytotoxics, and evaluated genomic correlates of resistance using longitudinal samples. RESULTS: Overall, 59% of patients harbored at least one OncoKB alteration, and 32.2% (intrahepatic 40%, extrahepatic 15%, and gallbladder 22%) had a level 1/2 alteration. Emerging targets included KRAS alterations (17%), MTAP deletions (12.8%), MDM2 amplification (6.5%), and MET amplification (1.5%). Targeted therapy was associated with improved progression-free survival but not overall survival. Co-occurring TP53/RAS pathway and SMAD4 alterations were associated with inferior outcomes in IDH1/FGFR2-and ERBB2-driven tumors, respectively. Longitudinal profiling demonstrated ERBB2 loss in ERBB2-driven tumors, whereas IDH-, FGFR-, BRAF-, and NTRK-driven tumors retained the primary oncogenic driver. Acquired resistance was associated with alterations in RAS, MEK, MET, MYC, and CDKN2A. CONCLUSIONS: This comprehensive molecular profiling study illustrates the real-world utility and limitations of targeted NGS of biliary tract cancer and affirms the use of precision medicine in patients with these diseases. Genomic heterogeneity and therapeutic resistance observed in this study has the potential to inform ongoing drug development efforts for biliary tract cancer.

Humans↗

PubMed2026

Multi-Ancestry Survival GWAS of Substance Use Initiation in the ABCD Study.

BACKGROUND: Substance use initiation in adolescence is influenced by both genetic and environmental factors; however, large-scale genetic studies often treat initiation as a binary outcome and underuse longitudinal timing information. METHODS: We conducted time-to-event (survival) genome-wide association analyses (GWAS) of initiation for four outcomes-alcohol, nicotine, cannabis, and any substance use-using longitudinal follow-up data from the Adolescent Brain Cognitive Development (ABCD) Study. We performed ancestry-stratified GWAS within European (EUR), African (AFR), and Hispanic (HISP) groups, applying consistent quality control and covariate adjustment. Summary statistics were harmonized across ancestries and meta-analyzed using inverse-variance weighted fixed-effects and DerSimonian-Laird random-effects models. We evaluated genomic inflation and heterogeneity (Cochran's Q and I 2), identified independent lead variants at genome-wide and suggestive significance thresholds, and assessed cross-trait overlap of associated loci. RESULTS: In the multi-ancestry meta-analysis, we observed suggestive association signals across traits (minimum p-values: alcohol ~ 1 × 10-7, any ~ 1 × 10-7, cannabis ~ 5 × 10-8, nicotine ~ 1 × 10-8). Nicotine initiation showed one genome-wide significant variant in both fixed- and random-effects meta-analyses (p < 5 × 10-8). Across traits, suggestive loci demonstrated limited overlap, with the strongest concordance between alcohol and any substance use, consistent with shared liability. Heterogeneity statistics indicated that some loci exhibited cross-ancestry variation in effect estimates. CONCLUSIONS: Survival GWAS leveraging initiation timing can identify genetic signals that may be missed by binary designs and enables principled multi-ancestry synthesis. Our results highlight both shared and trait-specific genetic contributions to early substance initiation and provide a foundation for downstream functional annotation and integrative modeling with environmental risk factors. These findings demonstrate the value of incorporating developmental timing into genetic discovery and provide a framework for integrating longitudinal risk modeling with genomic analyses.

ABCD↗