Ubiquitin-induced RNF168 condensation promotes DNA double-strand break repair.

Rapid accumulation of repair factors at DNA double-strand breaks (DSBs) is essential for DSB repair. Several factors involved in DSB repair have been found undergoing liquid-liquid phase separation (LLPS) at DSB sites to facilitate DNA repair. RNF168, a RING-type E3 ubiquitin ligase, catalyzes H2A.X ubiquitination for recruiting DNA repair factors. Yet, whether RNF168 undergoes LLPS at DSB sites remains unclear. Here, we identified K63-linked polyubiquitin-triggered RNF168 condensation which further promoted RNF168-mediated DSB repair. RNF168 formed liquid-like condensates upon irradiation in the nucleus while purified RNF168 protein also condensed in vitro. An intrinsically disordered region containing amino acids 460-550 was identified as the essential domain for RNF168 condensation. Interestingly, LLPS of RNF168 was significantly enhanced by K63-linked polyubiquitin chains, and LLPS largely enhanced the RNF168-mediated H2A.X ubiquitination, suggesting a positive feedback loop to facilitate RNF168 rapid accumulation and its catalytic activity. Functionally, LLPS deficiency of RNF168 resulted in delayed recruitment of 53BP1 and BRCA1 and subsequent impairment in DSB repair. Taken together, our finding demonstrates the pivotal effect of LLPS in RNF168-mediated DSB repair.

Assessing computational predictions of antimicrobial resistance phenotypes from microbial genomes.

The advent of rapid whole-genome sequencing has created new opportunities for computational prediction of antimicrobial resistance (AMR) phenotypes from genomic data. Both rule-based and machine learning (ML) approaches have been explored for this task, but systematic benchmarking is still needed. Here, we evaluated four state-of-the-art ML methods (Kover, PhenotypeSeeker, Seq2Geno2Pheno and Aytan-Aktug), an ML baseline and the rule-based ResFinder by training and testing each of them across 78 species-antibiotic datasets, using a rigorous benchmarking workflow that integrates three evaluation approaches, each paired with three distinct sample splitting methods. Our analysis revealed considerable variation in the performance across techniques and datasets. Whereas ML methods generally excelled for closely related strains, ResFinder excelled for handling divergent genomes. Overall, Kover most frequently ranked top among the ML approaches, followed by PhenotypeSeeker and Seq2Geno2Pheno. AMR phenotypes for antibiotic classes such as macrolides and sulfonamides were predicted with the highest accuracies. The quality of predictions varied substantially across species-antibiotic combinations, particularly for beta-lactams; across species, resistance phenotyping of the beta-lactams compound, aztreonam, amoxicillin/clavulanic acid, cefoxitin, ceftazidime and piperacillin/tazobactam, alongside tetracyclines demonstrated more variable performance than the other benchmarked antibiotics. By organism, Campylobacter jejuni and Enterococcus faecium phenotypes were more robustly predicted than those of Escherichia coli, Staphylococcus aureus, Salmonella enterica, Neisseria gonorrhoeae, Klebsiella pneumoniae, Pseudomonas aeruginosa, Acinetobacter baumannii, Streptococcus pneumoniae and Mycobacterium tuberculosis. In addition, our study provides software recommendations for each species-antibiotic combination. It furthermore highlights the need for optimization for robust clinical applications, particularly for strains that diverge substantially from those used for training.

Alpha oscillatory activity is causally linked to working memory retention.

Although previous studies have reported correlations between alpha oscillations and the "retention" subprocess of working memory (WM), causal evidence has been limited in human neuroscience due to the lack of delicate modulation of human brain oscillations. Conventional transcranial alternating current stimulation (tACS) is not suitable for demonstrating the causal evidence for parietal alpha oscillations in WM retention because of its inability to modulate brain oscillations within a short period (i.e., the retention subprocess). Here, we developed an online phase-corrected tACS system capable of precisely correcting for the phase differences between tACS and concurrent endogenous oscillations. This system permits the modulation of brain oscillations at the target stimulation frequency within a short stimulation period and is here applied to empirically demonstrate that parietal alpha oscillations causally relate to WM retention. Our experimental design included both in-phase and anti-phase alpha-tACS applied to participants during the retention subprocess of a modified Sternberg paradigm. Compared to in-phase alpha-tACS, anti-phase alpha-tACS decreased both WM performance and alpha activity. These findings strongly support a causal link between alpha oscillations and WM retention and illustrate the broad application prospects of phase-corrected tACS.

Critical Assessment of Metagenome Interpretation: the second round of challenges.

Evaluating metagenomic software is key for optimizing metagenome interpretation and focus of the Initiative for the Critical Assessment of Metagenome Interpretation (CAMI). The CAMI II challenge engaged the community to assess methods on realistic and complex datasets with long- and short-read sequences, created computationally from around 1,700 new and known genomes, as well as 600 new plasmids and viruses. Here we analyze 5,002 results by 76 program versions. Substantial improvements were seen in assembly, some due to long-read data. Related strains still were challenging for assembly and genome recovery through binning, as was assembly quality for the latter. Profilers markedly matured, with taxon profilers and binners excelling at higher bacterial ranks, but underperforming for viruses and Archaea. Clinical pathogen detection results revealed a need to improve reproducibility. Runtime and memory usage analyses identified efficient programs, including top performers with other metrics. The results identify challenges and guide researchers in selecting methods for analyses.

Metal bond strength regulation enables large-scale synthesis of intermetallic nanocrystals for practical fuel cells.

Structurally ordered L10-PtM (M = Fe, Co, Ni and so on) intermetallic nanocrystals, benefiting from the chemically ordered structure and higher stability, are one of the best electrocatalysts used for fuel cells. However, their practical development is greatly plagued by the challenge that the high-temperature (>600 °C) annealing treatment necessary for realizing the ordered structure usually leads to severe particle sintering, morphology change and low ordering degree, which makes it very difficult for the gram-scale preparation of desirable PtM intermetallic nanocrystals with high Pt content for practical fuel cell applications. Here we report a new concept involving the low-melting-point-metal (M' = Sn, Ga, In)-induced bond strength weakening strategy to reduce Ea and promote the ordering process of PtM (M = Ni, Co, Fe, Cu and Zn) alloy catalysts for a higher ordering degree. We demonstrate that the introduction of M' can reduce the ordering temperature to extremely low temperatures (≤450 °C) and thus enable the preparation of high-Pt-content (≥40 wt%) L10-Pt-M-M' intermetallic nanocrystals as well as ten-gram-scale production. X-ray spectroscopy studies, in situ electron microscopy and theoretical calculations reveal the fundamental mechanism of the Sn-facilitated ordering process at low temperatures, which involves weakened bond strength and consequently reduced Ea via Sn doping, the formation and fast diffusion of low-coordinated surface free atoms, and subsequent L10 nucleation. The developed L10-Ga-PtNi/C catalysts display outstanding performance in H2-air fuel cells under both light- and heavy-duty vehicle conditions. Under the latter condition, the 40% L10-Pt50Ni35Ga15/C catalyst delivers a high current density of 1.67 A cm-2 at 0.7 V and retains 80% of the current density after extended 90,000 cycles, which exceeds the United States Department of Energy performance metrics and represents among the best cathodic electrocatalysts for practical proton-exchange membrane fuel cells.

Dual-Region Computed Tomography Radiomics-Based Machine Learning Predicts Subcarinal Lymph Node Metastasis in Patients with Non-small Cell Lung Cancer.

BACKGROUND: Noninvasively and accurately predicting subcarinal lymph node metastasis (SLNM) for patients with non-small cell lung cancer (NSCLC) remains challenging. This study was designed to develop and validate a tumor and subcarinal lymph nodes (tumor-SLNs) dual-region computed tomography (CT) radiomics model for predicting SLNM in NSCLC. METHODS: This retrospective study included NSCLC patients who underwent lung resection and SLNs dissection between January 2017 and December 2020. The radiomic features of the tumor and SLNs were extracted from preoperative CT, respectively. Ninety machine learning (ML) models were developed based on tumor region, SLNs region, and tumor-SLNs dual-region. The model performance was assessed by the area under the curve (AUC) and validated internally by fivefold cross-validation. RESULTS: In total, 202 patients were included in this study. ML models based on dual-region radiomics showed good performance for SLNM prediction, with a median AUC of 0.794 (range, 0.686-0.880), which was superior to those of models based on tumor region (median AUC, 0.746; range, 0.630-0.811) and SLNs region (median AUC, 0.700; range, 0.610-0.842). The ML model, which is developed by using the naive Bayes algorithm and dual-region features, had the highest AUC of 0.880 (range of cross-validation, 0.825-0.937) among all ML models. The optimal logistic regression model was inferior to the optimal ML model for predicting SLNM, with an AUC of 0.727. CONCLUSIONS: The CT radiomics showed the potential for accurately predicting SLNM in NSCLC patients. The ML model with dual-region radiomic features has better performance than the logistic regression or single-region models.

Entanglement signatures for quantum synchronization with single-ion phonon laser.

The entanglement properties of quantum synchronization, based on a single-ion phonon laser subjected to an external drive, have been studied. It is found that the maximum value of steady-state entanglement between the ion's internal and external states occurs near the noiseless boundary from synchronization to unsynchronization, accompanied by noticeable oscillatory behaviors during the corresponding time evolution of entanglement. In addition, the later time dynamics of entanglement also indicates the occurrence of frequency entrainment, as evidenced by the strong consistency between the bending of the observed frequency and the emergence of Liouvillian exceptional points (LEPs) in the first two eigenvalues of the Liouvillian eigenspectrum. Moreover, the emergence of LEPs, which is intimately associated with frequency entrainment, should be widely observed in quantum synchronization and can be explored in LEPs-based applications.

Electroconvulsive therapy-induced volumetric brain changes converge on a common causal circuit in depression.

Neurostimulation is a mainstream treatment option for major depression. Neuromodulation techniques apply repetitive magnetic or electrical stimulation to some neural target but significantly differ in their invasiveness, spatial selectivity, mechanism of action, and efficacy. Despite these differences, recent analyses of transcranial magnetic stimulation (TMS) and deep brain stimulation (DBS)-treated individuals converged on a common neural network that might have a causal role in treatment response. We set out to investigate if the neuronal underpinnings of electroconvulsive therapy (ECT) are similarly associated with this causal depression network (CDN). Our aim here is to provide a comprehensive analysis in three cohorts of patients segregated by electrode placement (N = 246 with right unilateral, 79 with bitemporal, and 61 with mixed) who underwent ECT. We conducted a data-driven, unsupervised multivariate neuroimaging analysis Principal Component Analysis (PCA) of the cortical and subcortical volume changes and electric field (EF) distribution to explore changes within the CDN associated with antidepressant outcomes. Despite the different treatment modalities (ECT vs TMS and DBS) and methodological approaches (structural vs functional networks), we found a highly similar pattern of change within the CDN in the three cohorts of patients (spatial similarity across 85 regions: r = 0.65, 0.58, 0.40, df = 83). Most importantly, the expression of this pattern correlated with clinical outcomes (t = -2.35, p = 0.019). This evidence further supports that treatment interventions converge on a CDN in depression. Optimizing modulation of this network could serve to improve the outcome of neurostimulation in depression.

The impact of body mass index on the clinical features of bipolar disorder: A STEP-BD study.

INTRODUCTION: The effects of body mass index (BMI) on the core symptoms of bipolar disorder (BD) and its implications for disease trajectory are largely unexplored. OBJECTIVE: To examine whether BMI impacted hospitalization rate, medical and psychiatric comorbidities, and core symptom domains such as depression and suicidality in BD. METHODS: Participants (15 years and older) were 2790 BD outpatients enrolled in the longitudinal STEP-BD study; all met DSM-IV criteria for BD-I, BD-II, cyclothymia, BD NOS, or schizoaffective disorder, bipolar subtype. BMI, demographic information, psychiatric and medical comorbidities, and other clinical variables such as bipolarity index, history of electroconvulsive therapy (ECT), and history of suicide attempts were collected at baseline. Longitudinal changes in Montgomery-Åsberg Depression Rating Scale (MADRS) score, Young Mania Rating Scale (YMRS) score, and hospitalizations during the study were also assessed. Depending on the variable of interest, odds-ratios, regression analyses, factor analyses, and graph analyses were applied. RESULTS: A robust increase in psychiatric and medical comorbidities was observed, particularly for baseline BMIs >35. A significant relationship was noted between higher BMI and history of suicide attempts, and individuals with BMIs >40 had the highest prevalence of suicide attempts. Obese and overweight individuals had a higher bipolarity index (a questionnaire measuring disease severity) and were more likely to have received ECT. Higher BMIs correlated with worsening trajectory of core depression symptoms and with worsening lassitude and inability to feel. CONCLUSIONS: In BD participants, elevated BMI was associated with worsening clinical features, including higher rates of suicidality, comorbidities, and core depression symptoms.

Linkages among stem xylem transport, biomechanics, and storage in lianas and trees across three contrasting environments.

PREMISE: Stem xylem transports water and nutrients, mechanically supports aboveground tissues, and stores water and nonstructural carbohydrates. These three functions are associated with three types of cells-vessel, fiber, and parenchyma, respectively. METHODS: We measured stem theoretical hydraulic conductivity (Kt), modulus of elasticity (MOE), tissue water content, starch, soluble sugars, cellulose, and xylem anatomical traits in 15 liana and 16 tree species across three contrasting sites in Southwest China. RESULTS: Lianas had higher hydraulic efficiency and tissue water content, but lower MOE and cellulose than trees. Storage traits (starch and soluble sugars) did not significantly differ between lianas and trees, and trait variation was explained mainly by site, highlighting how environment shapes plant storage strategies. Kt was significantly positively correlated with vessel diameter and vessel area fraction in lianas and all species combined. The MOE was significantly positively correlated with fiber area fraction, wood density, and cellulose in lianas and across all species. The tissue water content was significantly associated with parenchyma area fraction in lianas. Support function was strongly linked with transport and storage functions in lianas. In trees, transport and support functions were not correlated, while storage function was tightly linked with transport and support functions. CONCLUSIONS: These findings enhance our understanding of the relationship between stem xylem structure and function in lianas and trees, providing valuable insights into how plants adapt to environmental changes and the distinct ecological strategies employed by lianas and by trees to balance the demands of hydraulic transport, mechanical support, and storage.

circMTO1/miR-30c-5p/SOCS3 axis alleviates oral submucous fibrosis through inhibiting fibroblast-myofibroblast transition.

BACKGROUND: circRNAs have been shown to participate in diverse diseases; however, their role in oral submucous fibrosis (OSF), a potentially malignant disorder, remains obscure. Our preliminary experiments detected the expression of circRNA mitochondrial translation optimization 1 homologue (circMTO1) in OSF tissues (n = 20) and normal mucosa tissues (n = 20) collected from Hunan Xiangya Stomatological Hospital, and a significant decrease of circMTO1 expression was showed in OSF tissues. Therefore, we further explored circMTO1 expression in OSF. METHODS: Target molecule expression was detected using RT-qPCR and western blotting. The migration and invasion of buccal mucosal fibroblasts (BMFs) were assessed using wound healing and Transwell assays. The interaction between miR-30c-5p, circMTO1, and SOCS3 was evaluated using dual luciferase, RNA immunoprecipitation (RIP), and RNA pull-down assays. The colocalisation of circMTO1 and miR-30c-5p was observed using fluorescence in situ hybridisation (FISH). RESULTS: circMTO1 and SOCS3 expression decreased, whereas miR-30c-5p expression increased in patients with OSF and arecoline-stimulated BMFs. Overexpression of circMTO1 effectively restrained the fibroblast-myofibroblast transition (FMT), as evidenced by the increase in expression of Coll I, α-SMA, Vimentin, and the weakened migration and invasion functions in BMFs. Mechanistic studies have shown that circMTO1 suppresses FMT by enhancing SOCS3 expression by sponging miR-30c-5p and subsequently inactivating the FAK/PI3K/AKT pathway. FMT induced by SOCS3 silencing was reversed by the FAK inhibitor TAE226 or the PI3K inhibitor LY294002. CONCLUSION: circMTO1/miR-30c-5p/SOCS3 axis regulates FMT in arecoline-treated BMFs via the FAK/PI3K/AKT pathway. Expanding the sample size and in vivo validation could further elucidate their potential as therapeutic targets for OSF.

The Efficacy of Transcranial Magnetic Stimulation in the Treatment of Obsessive-Compulsive Disorder: An Umbrella Review of Meta-Analyses.

BACKGROUND: Repetitive transcranial magnetic stimulation (rTMS) has been increasingly used for treating obsessive-compulsive disorder (OCD). Although several meta-analyses have explored its effectiveness and safety, there is no umbrella review specifically focused on rTMS for OCD. This umbrella review followed Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and analyzed relevant meta-analyses on rTMS for OCD. METHODS: Twenty-three articles were identified from PubMed, and after screening, 12 meta-analyses were included in the review. The studies analyzed in the meta-analyses ranged from 10 to 27, with total participants ranging from 282 to 791. The most commonly studied regions were the dorsolateral prefrontal cortex (DLPFC), supplementary motor area (SMA), and orbito-frontal cortex (OFC). RESULT: The majority of the meta-analyses consistently supported the effectiveness of rTMS in reducing OCD symptoms when applied to the DLPFC and SMA. Encouraging results were also observed when targeting the medial prefrontal cortex (mPFC) and anterior cingulate cortex (ACC) through deep transcranial magnetic stimulation (dTMS). However, there was a high level of heterogeneity in the findings of nine out of 12 meta-analyses. CONCLUSION: In conclusion, existing evidence suggests that rTMS targeting the DLPFC and SMA consistently reduces OCD symptoms, but targeting the mPFC and ACC through dTMS shows variable results. However, the high heterogeneity in the study findings indicates a need for further research and standardization in the field.

Corynoxine promotes TFEB/TFE3-mediated autophagy and alleviates Aß pathology in Alzheimer's disease models.

Autophagy impairment is a key factor in Alzheimer's disease (AD) pathogenesis. TFEB (transcription factor EB) and TFE3 (transcription factor binding to IGHM enhancer 3) are nuclear transcription factors that regulate autophagy and lysosomal biogenesis. We previously showed that corynoxine (Cory), a Chinese medicine compound, protects neurons from Parkinson's disease (PD) by activating autophagy. In this study, we investigated the effect of Cory on AD models in vivo and in vitro. We found that Cory improved learning and memory function, increased neuronal autophagy and lysosomal biogenesis, and reduced pathogenic APP-CTFs levels in 5xFAD mice model. Cory activated TFEB/TFE3 by inhibiting AKT/mTOR signaling and stimulating lysosomal calcium release via transient receptor potential mucolipin 1 (TRPML1). Moreover, we demonstrated that TFEB/TFE3 knockdown abolished Cory-induced APP-CTFs degradation in N2aSwedAPP cells. Our findings suggest that Cory promotes TFEB/TFE3-mediated autophagy and alleviates Aß pathology in AD models.

Rapid and accurate identification of ribosomal RNA sequences via deep learning.

Advances in transcriptomic and translatomic techniques enable in-depth studies of RNA activity profiles and RNA-based regulatory mechanisms. Ribosomal RNA (rRNA) sequences are highly abundant among cellular RNA, but if the target sequences do not include polyadenylation, these cannot be easily removed in library preparation, requiring their post-hoc removal with computational techniques to accelerate and improve downstream analyses. Here, we describe RiboDetector, a novel software based on a Bi-directional Long Short-Term Memory (BiLSTM) neural network, which rapidly and accurately identifies rRNA reads from transcriptomic, metagenomic, metatranscriptomic, noncoding RNA, and ribosome profiling sequence data. Compared with state-of-the-art approaches, RiboDetector produced at least six times fewer misclassifications on the benchmark datasets. Importantly, the few false positives of RiboDetector were not enriched in certain Gene Ontology (GO) terms, suggesting a low bias for downstream functional profiling. RiboDetector also demonstrated a remarkable generalizability for detecting novel rRNA sequences that are divergent from the training data with sequence identities of <90%. On a personal computer, RiboDetector processed 40M reads in less than 6 min, which was ∼50 times faster in GPU mode and ∼15 times in CPU mode than other methods. RiboDetector is available under a GPL v3.0 license at https://github.com/hzi-bifo/RiboDetector.

Research progress of microRNA in spinal cord injury.

Spinal cord injury (SCI) is a serious central nervous system disease with high disability and mortality rates and complex pathophysiologic mechanisms. MicroRNA (miRNA), as a kind of non-coding RNA, plays an important role in SCI. miRNA is involved in the regulation of inflammatory response, oxidative stress, axonal regeneration, and apoptosis after SCI, and interacts with long non-coding RNA (lncRNA) and circular RNA (circRNA) to regulate the pathophysiological process of SCI. This paper summarizes the changes in miRNA expression after SCI, and reviews the targeting mechanism of miRNA in SCI and the current research status of miRNA-targeted drugs to provide new targets and new horizons for basic and clinical research on SCI.

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Neonatal necrotizing enterocolitis (NEC) is the most common inflammatory intestinal disease in preterm infants, with a high incidence and mortality rate. The etiology and mechanisms of NEC are not yet fully understood, and multiple factors contribute to its occurrence and development. Recent studies have found that anemia is a risk factor for NEC in neonates, but the specific pathogenic mechanism remains unclear. This article reviews recent research on the relationship between anemia and NEC, providing a reference for further understanding the impact of anemia on intestinal injury and its association with NEC.

Device-Based Modulation of Neurocircuits as a Therapeutic for Psychiatric Disorders.

Device-based neuromodulation of brain circuits is emerging as a promising new approach in the study and treatment of psychiatric disorders. This work presents recent advances in the development of tools for identifying neurocircuits as therapeutic targets and in tools for modulating neurocircuits. We review clinical evidence for the therapeutic efficacy of circuit modulation with a range of brain stimulation approaches, including subthreshold, subconvulsive, convulsive, and neurosurgical techniques. We further discuss strategies for enhancing the precision and efficacy of neuromodulatory techniques. Finally, we survey cutting-edge research in therapeutic circuit modulation using novel paradigms and next-generation devices.

Chromosome-level wild Hevea brasiliensis genome provides new tools for genomic-assisted breeding and valuable loci to elevate rubber yield.

The rubber tree (Hevea brasiliensis) is grown in tropical regions and is the major source of natural rubber. Using traditional breeding approaches, the latex yield has increased by sixfold in the last century. However, the underlying genetic basis of rubber yield improvement is largely unknown. Here, we present a high-quality, chromosome-level genome sequence of the wild rubber tree, the first report on selection signatures and a genome-wide association study (GWAS) of its yield traits. Population genomic analysis revealed a moderate population divergence between the Wickham clones and wild accessions. Interestingly, it is suggestive that H. brasiliensis and six relatives of the Hevea genus might belong to the same species. The selective sweep analysis found 361 obvious signatures in the domesticated clones associated with 245 genes. In a 15-year field trial, GWAS identified 155 marker-trait associations with latex yield, in which 326 candidate genes were found. Notably, six genes related to sugar transport and metabolism, and four genes related to ethylene biosynthesis and signalling are associated with latex yield. The homozygote frequencies of the causal nonsynonymous SNPs have been greatly increased under selection, which may have contributed to the fast latex yield improvement during the short domestication history. Our study provides insights into the genetic basis of the latex yield trait and has implications for genomic-assisted breeding by offering valuable resources in this new domesticated crop.

Evaluating assembly and variant calling software for strain-resolved analysis of large DNA viruses.

Infection with human cytomegalovirus (HCMV) can cause severe complications in immunocompromised individuals and congenitally infected children. Characterizing heterogeneous viral populations and their evolution by high-throughput sequencing of clinical specimens requires the accurate assembly of individual strains or sequence variants and suitable variant calling methods. However, the performance of most methods has not been assessed for populations composed of low divergent viral strains with large genomes, such as HCMV. In an extensive benchmarking study, we evaluated 15 assemblers and 6 variant callers on 10 lab-generated benchmark data sets created with two different library preparation protocols, to identify best practices and challenges for analyzing such data. Most assemblers, especially metaSPAdes and IVA, performed well across a range of metrics in recovering abundant strains. However, only one, Savage, recovered low abundant strains and in a highly fragmented manner. Two variant callers, LoFreq and VarScan2, excelled across all strain abundances. Both shared a large fraction of false positive variant calls, which were strongly enriched in T to G changes in a 'G.G' context. The magnitude of this context-dependent systematic error is linked to the experimental protocol. We provide all benchmarking data, results and the entire benchmarking workflow named QuasiModo, Quasispecies Metric determination on omics, under the GNU General Public License v3.0 (https://github.com/hzi-bifo/Quasimodo), to enable full reproducibility and further benchmarking on these and other data.

Co-occurrence of Spondyloepiphyseal Dysplasia and X-Linked Hypophosphatemia in a Three-Generation Chinese Family.

Rare genetic skeletal disorders (GSDs) remain the major problem in orthopedics and result in significant morbidity in patients, but the causes are highly diverse. Precise molecular diagnosis will benefit management and genetic counseling. This study aims to share the diagnostic experience on a three-generation Chinese family with co-occurrence of spondyloepiphyseal dysplasia (SED) and X-linked hypophosphatemia (XLH), and evaluate the therapeutic effects of two third-generation siblings. The proband, his younger brother, and mother presented with short stature, skeletal problems, and hypophosphatemia. His father, paternal grandfather, and aunt also manifested short stature and skeletal deformities. Whole exome sequencing (WES) of proband-brother-parents initially only found the proband and his younger brother had a pathogenic c.2833G > A(p.G945S) variant in the COL2A1 gene inherited from their father. Re-analysis of WES uncovered the proband and his younger brother also harbored a pathogenic ex.12 del variant in the PHEX gene transmitted from their mother. Sanger sequencing, agarose gel electrophoresis, and quantitative polymerase chain reaction proved these results. The proband and his younger brother were confirmed to have a paternally inherited SED and a maternally inherited XLH. During a 2.8-year follow-up, these two siblings remained short stature and hypophosphatemia, but their radiographic signs and serum bone alkaline phosphatase levels were improved with treatment of oral phosphate and calcitriol. Our study presents the first report of co-occurrence of SED and XLH, shows the possibility that two different rare GSDs co-exist in a single patient, and alerts clinicians and geneticists to be cautious about this condition. Our study also suggests that next-generation sequencing has limit in detecting exon-level large deletions.